Kelley Faber

The Alzheimer Disease Genetics Consortium (ADGC) performed a genome-wide association study of late-onset Alzheimer disease using a three-stage design consisting of a discovery stage (stage 1) and two replication stages (stages 2 and 3). Both joint analysis and meta-analysis approaches were used. We obtained genome-wide significant results at MS4A4A (rs4938933; stages 1 and 2, meta-analysis P (P(M)) = 1.7 × 10(-9), joint analysis P (P(J)) = 1.7 × 10(-9); stages 1, 2 and 3, P(M) = 8.2 × 10(-12)), CD2AP (rs9349407; stages 1, 2 and 3, P(M) = 8.6 × 10(-9)), EPHA1 (rs11767557; stages 1, 2 and 3, P(M) = 6.0 × 10(-10)) and CD33 (rs3865444; stages 1, 2 and 3, P(M) = 1.6 × 10(-9)). We also replicated previous associations at CR1 (rs6701713; P(M) = 4.6 × 10(-10), P(J) = 5.2 × 10(-11)), CLU (rs1532278; P(M) = 8.3 × 10(-8), P(J) = 1.9 × 10(-8)), BIN1 (rs7561528; P(M) = 4.0 × 10(-14), P(J) = 5.2 × 10(-14)) and PICALM (rs561655; P(M) = 7.0 × 10(-11), P(J) = 1.0 × 10(-10)), but not at EXOC3L2, to late-onset Alzheimer's disease susceptibility.

Pathogenic mutations in APP, PSEN1, PSEN2, MAPT and GRN have previously been linked to familial early onset forms of dementia. Mutation screening in these genes has been performed in either very small series or in single families with late onset AD (LOAD). Similarly, studies in single families have reported mutations in MAPT and GRN associated with clinical AD but no systematic screen of a large dataset has been performed to determine how frequently this occurs. We report sequence data for 439 probands from late-onset AD families with a history of four or more affected individuals. Sixty sequenced individuals (13.7%) carried a novel or pathogenic mutation. Eight pathogenic variants, (one each in APP and MAPT, two in PSEN1 and four in GRN) three of which are novel, were found in 14 samples. Thirteen additional variants, present in 23 families, did not segregate with disease, but the frequency of these variants is higher in AD cases than controls, indicating that these variants may also modify risk for disease. The frequency of rare variants in these genes in this series is significantly higher than in the 1,000 genome project (p = 5.09 × 10⁻⁵; OR = 2.21; 95%CI = 1.49-3.28) or an unselected population of 12,481 samples (p = 6.82 × 10⁻⁵; OR = 2.19; 95%CI = 1.347-3.26). Rare coding variants in APP, PSEN1 and PSEN2, increase risk for or cause late onset AD. The presence of variants in these genes in LOAD and early-onset AD demonstrates that factors other than the mutation can impact the age at onset and penetrance of at least some variants associated with AD. MAPT and GRN mutations can be found in clinical series of AD most likely due to misdiagnosis. This study clearly demonstrates that rare variants in these genes could explain an important proportion of genetic heritability of AD, which is not detected by GWAS.

Genetic data from the Alzheimer's Disease Neuroimaging Initiative (ADNI) have been crucial in advancing the understanding of Alzheimer's disease (AD) pathophysiology. Here, we provide an update on sample collection, scientific progress and opportunities, conceptual issues, and future plans.Lymphoblastoid cell lines and DNA and RNA samples from blood have been collected and banked, and data and biosamples have been widely disseminated. To date, APOE genotyping, genome-wide association study (GWAS), and whole exome and whole genome sequencing data have been obtained and disseminated.ADNI genetic data have been downloaded thousands of times, and >300 publications have resulted, including reports of large-scale GWAS by consortia to which ADNI contributed. Many of the first applications of quantitative endophenotype association studies used ADNI data, including some of the earliest GWAS and pathway-based studies of biospecimen and imaging biomarkers, as well as memory and other clinical/cognitive variables. Other contributions include some of the first whole exome and whole genome sequencing data sets and reports in healthy controls, mild cognitive impairment, and AD.Numerous genetic susceptibility and protective markers for AD and disease biomarkers have been identified and replicated using ADNI data and have heavily implicated immune, mitochondrial, cell cycle/fate, and other biological processes. Early sequencing studies suggest that rare and structural variants are likely to account for significant additional phenotypic variation. Longitudinal analyses of transcriptomic, proteomic, metabolomic, and epigenomic changes will also further elucidate dynamic processes underlying preclinical and prodromal stages of disease. Integration of this unique collection of multiomics data within a systems biology framework will help to separate truly informative markers of early disease mechanisms and potential novel therapeutic targets from the vast background of less relevant biological processes. Fortunately, a broad swath of the scientific community has accepted this grand challenge.

Late-onset Alzheimer's disease (LOAD) is the most common form of dementia in the elderly. The National Institute of Aging-Late Onset Alzheimer's Disease Family Study and the National Cell Repository for Alzheimer's Disease conducted a joint genome-wide association study (GWAS) of multiplex LOAD families (3,839 affected and unaffected individuals from 992 families plus additional unrelated neurologically evaluated normal subjects) using the 610 IlluminaQuad panel. This cohort represents the largest family-based GWAS of LOAD to date, with analyses limited here to the European-American subjects. SNPs near APOE gave highly significant results (e.g., rs2075650, p = 3.2×10−81), but no other genome-wide significant evidence for association was obtained in the full sample. Analyses that stratified on APOE genotypes identified SNPs on chromosome 10p14 in CUGBP2 with genome-wide significant evidence for association within APOE ε4 homozygotes (e.g., rs201119, p = 1.5×10−8). Association in this gene was replicated in an independent sample consisting of three cohorts. There was evidence of association for recently-reported LOAD risk loci, including BIN1 (rs7561528, p = 0.009 with, and p = 0.03 without, APOE adjustment) and CLU (rs11136000, p = 0.023 with, and p = 0.008 without, APOE adjustment), with weaker support for CR1. However, our results provide strong evidence that association with PICALM (rs3851179, p = 0.69 with, and p = 0.039 without, APOE adjustment) and EXOC3L2 is affected by correlation with APOE, and thus may represent spurious association. Our results indicate that genetic structure coupled with ascertainment bias resulting from the strong APOE association affect genome-wide results and interpretation of some recently reported associations. We show that a locus such as APOE, with large effects and strong association with disease, can lead to samples that require appropriate adjustment for this locus to avoid both false positive and false negative evidence of association. We suggest that similar adjustments may also be needed for many other large multi-site studies.

Alzheimer's disease (AD) is a complex genetic disorder with no effective treatments. More than 20 common markers have been identified, which are associated with AD. Recently, several rare variants have been identified in Amyloid Precursor Protein (APP), Triggering Receptor Expressed On Myeloid Cells 2 (TREM2) and Unc-5 Netrin Receptor C (UNC5C) that affect risk for AD. Despite the many successes, the genetic architecture of AD remains unsolved. We used Genome-wide Complex Trait Analysis to (1) estimate phenotypic variance explained by genetics; (2) calculate genetic variance explained by known AD single nucleotide polymorphisms (SNPs); and (3) identify the genomic locations of variation that explain the remaining unexplained genetic variance. In total, 53.24% of phenotypic variance is explained by genetics, but known AD SNPs only explain 30.62% of the genetic variance. Of the unexplained genetic variance, approximately 41% is explained by unknown SNPs in regions adjacent to known AD SNPs, and the remaining unexplained genetic variance outside these regions.

Plasma phosphorylated tau at threonine 181 (p-tau181) has been proposed as an easily accessible biomarker for the detection of Alzheimer disease (AD) pathology, but its ability to monitor disease progression in AD remains unclear.To study the potential of longitudinal plasma p-tau181 measures for assessing neurodegeneration progression and cognitive decline in AD in comparison to plasma neurofilament light chain (NfL), a disease-nonspecific marker of neuronal injury.This longitudinal cohort study included data from the Alzheimer's Disease Neuroimaging Initiative from February 1, 2007, to June 6, 2016. Follow-up blood sampling was performed for up to 8 years. Plasma p-tau181 measurements were performed in 2020. This was a multicentric observational study of 1113 participants, including cognitively unimpaired participants as well as patients with cognitive impairment (mild cognitive impairment and AD dementia). Participants were eligible for inclusion if they had available plasma p-tau181 and NfL measurements and at least 1 fluorine-18-labeled fluorodeoxyglucose (FDG) positron emission tomography (PET) or structural magnetic resonance imaging scan performed at the same study visit. Exclusion criteria included any significant neurologic disorder other than suspected AD; presence of infection, infarction, or multiple lacunes as detected by magnetic resonance imaging; and any significant systemic condition that could lead to difficulty complying with the protocol.Plasma p-tau181 and NfL measured with single-molecule array technology.Longitudinal imaging markers of neurodegeneration (FDG PET and structural magnetic resonance imaging) and cognitive test scores (Preclinical Alzheimer Cognitive Composite and Alzheimer Disease Assessment Scale-Cognitive Subscale with 13 tasks). Data were analyzed from June 20 to August 15, 2020.Of the 1113 participants (mean [SD] age, 74.0 [7.6] years; 600 men [53.9%]; 992 non-Hispanic White participants [89.1%]), a total of 378 individuals (34.0%) were cognitively unimpaired (CU) and 735 participants (66.0%) were cognitively impaired (CImp). Of the CImp group, 537 (73.1%) had mild cognitive impairment, and 198 (26.9%) had AD dementia. Longitudinal changes of plasma p-tau181 were associated with cognitive decline (CU: r = -0.24, P < .001; CImp: r = 0.34, P < .001) and a prospective decrease in glucose metabolism (CU: r = -0.05, P = .48; CImp: r = -0.27, P < .001) and gray matter volume (CU: r = -0.19, P < .001; CImp: r = -0.31, P < .001) in highly AD-characteristic brain regions. These associations were restricted to amyloid-β-positive individuals. Both plasma p-tau181 and NfL were independently associated with cognition and neurodegeneration in brain regions typically affected in AD. However, NfL was also associated with neurodegeneration in brain regions exceeding this AD-typical spatial pattern in amyloid-β-negative participants. Mediation analyses found that approximately 25% to 45% of plasma p-tau181 outcomes on cognition measures were mediated by the neuroimaging-derived markers of neurodegeneration, suggesting links between plasma p-tau181 and cognition independent of these measures.Study findings suggest that plasma p-tau181 was an accessible and scalable marker for predicting and monitoring neurodegeneration and cognitive decline and was, unlike plasma NfL, AD specific. The study findings suggest implications for the use of plasma biomarkers as measures to monitor AD progression in clinical practice and treatment trials.

Because APOE locus variants contribute to risk of late-onset Alzheimer disease (LOAD) and to differences in age at onset (AAO), it is important to know whether other established LOAD risk loci also affect AAO in affected participants.To investigate the effects of known Alzheimer disease risk loci in modifying AAO and to estimate their cumulative effect on AAO variation using data from genome-wide association studies in the Alzheimer Disease Genetics Consortium.The Alzheimer Disease Genetics Consortium comprises 14 case-control, prospective, and family-based data sets with data on 9162 participants of white race/ethnicity with Alzheimer disease occurring after age 60 years who also had complete AAO information, gathered between 1989 and 2011 at multiple sites by participating studies. Data on genotyped or imputed single-nucleotide polymorphisms most significantly associated with risk at 10 confirmed LOAD loci were examined in linear modeling of AAO, and individual data set results were combined using a random-effects, inverse variance-weighted meta-analysis approach to determine whether they contribute to variation in AAO. Aggregate effects of all risk loci on AAO were examined in a burden analysis using genotype scores weighted by risk effect sizes.Age at disease onset abstracted from medical records among participants with LOAD diagnosed per standard criteria.Analysis confirmed the association of APOE with earlier AAO (P = 3.3 × 10(-96)), with associations in CR1 (rs6701713, P = 7.2 × 10(-4)), BIN1 (rs7561528, P = 4.8 × 10(-4)), and PICALM (rs561655, P = 2.2 × 10(-3)) reaching statistical significance (P < .005). Risk alleles individually reduced AAO by 3 to 6 months. Burden analyses demonstrated that APOE contributes to 3.7% of the variation in AAO (R(2) = 0.256) over baseline (R(2) = 0.221), whereas the other 9 loci together contribute to 2.2% of the variation (R(2) = 0.242).We confirmed an association of APOE (OMIM 107741) variants with AAO among affected participants with LOAD and observed novel associations of CR1 (OMIM 120620), BIN1 (OMIM 601248), and PICALM (OMIM 603025) with AAO. In contrast to earlier hypothetical modeling, we show that the combined effects of Alzheimer disease risk variants on AAO are on the scale of, but do not exceed, the APOE effect. While the aggregate effects of risk loci on AAO may be significant, additional genetic contributions to AAO are individually likely to be small.

Genetic loci for Alzheimer's disease (AD) have been identified in whites of European ancestry, but the genetic architecture of AD among other populations is less understood.We conducted a transethnic genome-wide association study (GWAS) for late-onset AD in Stage 1 sample including whites of European Ancestry, African-Americans, Japanese, and Israeli-Arabs assembled by the Alzheimer's Disease Genetics Consortium. Suggestive results from Stage 1 from novel loci were followed up using summarized results in the International Genomics Alzheimer's Project GWAS dataset.Genome-wide significant (GWS) associations in single-nucleotide polymorphism (SNP)-based tests (P < 5 × 10-8) were identified for SNPs in PFDN1/HBEGF, USP6NL/ECHDC3, and BZRAP1-AS1 and for the interaction of the (apolipoprotein E) APOE ε4 allele with NFIC SNP. We also obtained GWS evidence (P < 2.7 × 10-6) for gene-based association in the total sample with a novel locus, TPBG (P = 1.8 × 10-6).Our findings highlight the value of transethnic studies for identifying novel AD susceptibility loci.

Hexanucleotide repeat expansions in the chromosome 9 open reading frame 72 (C9orf72) gene underlie a significant fraction of frontotemporal dementia and amyotrophic lateral sclerosis.To investigate the frequency of C9orf72 repeat expansions in clinically diagnosed late-onset Alzheimer disease (AD).This case-control study genotyped the C9orf72 repeat expansion in 872 unrelated familial AD cases and 888 control subjects recruited as part of the National Institute on Aging Late-Onset Alzheimer Disease Family Study cohort, a multisite collaboration studying 1000 families with 2 or more individuals clinically diagnosed as having late-onset AD.We determined the presence or absence of the C9orf72 repeat expansion by repeat-primed polymerase chain reaction, the length of the longest nonexpanded allele, segregation of the genotype with disease, and clinical features of repeat expansion carriers. RESULTS Three families showed large C9orf72 hexanucleotide repeat expansions. Two additional families carried more than 30 repeats. Segregation with disease could be demonstrated in 3 families. One affected expansion carrier had neuropathology compatible with AD. In the National Institute on Aging Late-Onset Alzheimer Disease Family Study series, the C9orf72 repeat expansions constituted the second most common pathogenic mutation, just behind the PSEN1 A79V mutation, highlighting the heterogeneity of clinical presentations associated with repeat expansions.C9orf72 repeat expansions explain a small proportion of patients with a clinical presentation indistinguishable from AD, and they highlight the necessity of screening frontotemporal dementia genes in clinical AD cases with strong family history.

We created global rating scoring rules for the CDR® plus NACC FTLD to detect and track early frontotemporal lobar degeneration (FTLD) and to conduct clinical trials in FTLD.The CDR plus NACC FTLD rating was applied to 970 sporadic and familial participants from the baseline visit of Advancing Research and Treatment in Frontotemporal Lobar Degeneration (ARTFL)/Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS). Each of the eight domains of the CDR plus NACC FTLD was equally weighed in determining the global score. An interrater reliability study was completed for 40 participants.The CDR plus NACC FTLD showed very good interrater reliability. It was especially useful in detecting clinical features of mild non-fluent/agrammatic variant primary progressive aphasia participants.The global CDR plus NACC FTLD score could be an attractive outcome measure for clinical trials in symptomatic FTLD, and may be useful in natural history studies and clinical trials in FTLD spectrum disorders.

<h3>Objective:</h3> To identify a causative variant(s) that may contribute to Alzheimer disease (AD) in African Americans (AA) in the <i>ATP-binding cassette, subfamily A</i> (<i>ABC1</i>), <i>member 7</i> (<i>ABCA7</i>) gene, a known risk factor for late-onset AD. <h3>Methods:</h3> Custom capture sequencing was performed on ∼150 kb encompassing <i>ABCA7</i> in 40 AA cases and 37 AA controls carrying the AA risk allele (rs115550680). Association testing was performed for an <i>ABCA7</i> deletion identified in large AA data sets (discovery n = 1,068; replication n = 1,749) and whole exome sequencing of Caribbean Hispanic (CH) AD families. <h3>Results:</h3> A 44-base pair deletion (rs142076058) was identified in all 77 risk genotype carriers, which shows that the deletion is in high linkage disequilibrium with the risk allele. The deletion was assessed in a large data set (531 cases and 527 controls) and, after adjustments for age, sex, and <i>APOE</i> status, was significantly associated with disease (<i>p</i> = 0.0002, odds ratio [OR] = 2.13 [95% confidence interval (CI): 1.42–3.20]). An independent data set replicated the association (447 cases and 880 controls, <i>p</i> = 0.0117, OR = 1.65 [95% CI: 1.12–2.44]), and joint analysis increased the significance (<i>p</i> = 1.414 × 10⁻⁵, OR = 1.81 [95% CI: 1.38–2.37]). The deletion is common in AA cases (15.2%) and AA controls (9.74%), but in only 0.12% of our non-Hispanic white cohort. Whole exome sequencing of multiplex, CH families identified the deletion cosegregating with disease in a large sibship. The deleted allele produces a stable, detectable RNA strand and is predicted to result in a frameshift mutation (p.Arg578Alafs) that could interfere with protein function. <h3>Conclusions:</h3> This common <i>ABCA7</i> deletion could represent an ethnic-specific pathogenic alteration in AD.

Alzheimer’s disease (AD) is a leading cause of mortality among the elderly. We performed a whole-genome sequencing study of AD in the Chinese population. In addition to the variants identified in or around the APOE locus (sentinel variant rs73052335, P = 1.44 × 10 −14 ), two common variants, GCH1 (rs72713460, P = 4.36 × 10 −5 ) and KCNJ15 (rs928771, P = 3.60 × 10 −6 ), were identified and further verified for their possible risk effects for AD in three small non-Asian AD cohorts. Genotype–phenotype analysis showed that KCNJ15 variant rs928771 affects the onset age of AD, with earlier disease onset in minor allele carriers. In addition, altered expression level of the KCNJ15 transcript can be observed in the blood of AD subjects. Moreover, the risk variants of GCH1 and KCNJ15 are associated with changes in their transcript levels in specific tissues, as well as changes of plasma biomarkers levels in AD subjects. Importantly, network analysis of hippocampus and blood transcriptome datasets suggests that the risk variants in the APOE , GCH1 , and KCNJ15 loci might exert their functions through their regulatory effects on immune-related pathways. Taking these data together, we identified common variants of GCH1 and KCNJ15 in the Chinese population that contribute to AD risk. These variants may exert their functional effects through the immune system.

Alzheimer's disease (AD) is a chronic progressive neurodegenerative disease impacting an estimated 44 million adults worldwide. The causal pathology of AD (accumulation of amyloid-beta and tau), precedes hallmark symptoms of dementia by more than a decade, necessitating development of early diagnostic markers of disease onset, particularly for new drugs that aim to modify disease processes. To evaluate differentially methylated positions (DMPs) as novel blood-based biomarkers of AD, we used a subset of 653 individuals with peripheral blood (PB) samples in the Alzheimer's disease Neuroimaging Initiative (ADNI) consortium. The selected cohort of AD, mild cognitive impairment (MCI), and age-matched healthy controls (CN) all had imaging, genetics, transcriptomics, cerebrospinal protein markers, and comprehensive clinical records, providing a rich resource of concurrent multi-omics and phenotypic information on a well-phenotyped subset of ADNI participants.In this manuscript, we report cross-diagnosis differential peripheral DNA methylation in a cohort of AD, MCI, and age-matched CN individuals with longitudinal DNA methylation measurements. Epigenome-wide association studies (EWAS) were performed using a mixed model with repeated measures over time with a P value cutoff of 1 × 10-5 to test contrasts of pairwise differential peripheral methylation in AD vs CN, AD vs MCI, and MCI vs CN. The most highly significant differentially methylated loci also tracked with Mini Mental State Examination (MMSE) scores. Differentially methylated loci were enriched near brain and neurodegeneration-related genes (e.g., BDNF, BIN1, APOC1) validated using the genotype tissue expression project portal (GTex).Our work shows that peripheral differential methylation between age-matched subjects with AD relative to healthy controls will provide opportunities to further investigate and validate differential methylation as a surrogate of disease. Given the inaccessibility of brain tissue, the PB-associated methylation marks may help identify the stage of disease and progression phenotype, information that would be central to bringing forward successful drugs for AD.

Frontotemporal dementia (FTD) therapy development is hamstrung by a lack of susceptibility, diagnostic, and prognostic biomarkers. Blood neurofilament light (NfL) shows promise as a biomarker, but studies have largely focused only on core FTD syndromes, often grouping patients with different diagnoses. To expedite the clinical translation of NfL, we avail ARTFL LEFFTDS Longitudinal Frontotemporal Lobar Degeneration (ALLFTD) study resources and conduct a comprehensive investigation of plasma NfL across FTD syndromes and in presymptomatic FTD mutation carriers. We find plasma NfL is elevated in all studied syndromes, including mild cases; increases in presymptomatic mutation carriers prior to phenoconversion; and associates with indicators of disease severity. By facilitating the identification of individuals at risk of phenoconversion, and the early diagnosis of FTD, plasma NfL can aid in participant selection for prevention or early treatment trials. Moreover, its prognostic utility would improve patient care, clinical trial efficiency, and treatment outcome estimations.

Abstract Background The polygenic nature of Alzheimer’s disease (AD) suggests that multiple variants jointly contribute to disease susceptibility. As an individual’s genetic variants are constant throughout life, evaluating the combined effects of multiple disease-associated genetic risks enables reliable AD risk prediction. Because of the complexity of genomic data, current statistical analyses cannot comprehensively capture the polygenic risk of AD, resulting in unsatisfactory disease risk prediction. However, deep learning methods, which capture nonlinearity within high-dimensional genomic data, may enable more accurate disease risk prediction and improve our understanding of AD etiology. Accordingly, we developed deep learning neural network models for modeling AD polygenic risk. Methods We constructed neural network models to model AD polygenic risk and compared them with the widely used weighted polygenic risk score and lasso models. We conducted robust linear regression analysis to investigate the relationship between the AD polygenic risk derived from deep learning methods and AD endophenotypes (i.e., plasma biomarkers and individual cognitive performance). We stratified individuals by applying unsupervised clustering to the outputs from the hidden layers of the neural network model. Results The deep learning models outperform other statistical models for modeling AD risk. Moreover, the polygenic risk derived from the deep learning models enables the identification of disease-associated biological pathways and the stratification of individuals according to distinct pathological mechanisms. Conclusion Our results suggest that deep learning methods are effective for modeling the genetic risks of AD and other diseases, classifying disease risks, and uncovering disease mechanisms.

Abstract INTRODUCTION Clinical research in Alzheimer's disease (AD) lacks cohort diversity despite being a global health crisis. The Asian Cohort for Alzheimer's Disease (ACAD) was formed to address underrepresentation of Asians in research, and limited understanding of how genetics and non‐genetic/lifestyle factors impact this multi‐ethnic population. METHODS The ACAD started fully recruiting in October 2021 with one central coordination site, eight recruitment sites, and two analysis sites. We developed a comprehensive study protocol for outreach and recruitment, an extensive data collection packet, and a centralized data management system, in English, Chinese, Korean, and Vietnamese. RESULTS ACAD has recruited 606 participants with an additional 900 expressing interest in enrollment since program inception. DISCUSSION ACAD's traction indicates the feasibility of recruiting Asians for clinical research to enhance understanding of AD risk factors. ACAD will recruit &gt; 5000 participants to identify genetic and non‐genetic/lifestyle AD risk factors, establish blood biomarker levels for AD diagnosis, and facilitate clinical trial readiness. HIGHLIGHTS The Asian Cohort for Alzheimer's Disease (ACAD) promotes awareness of under‐investment in clinical research for Asians. We are recruiting Asian Americans and Canadians for novel insights into Alzheimer's disease. We describe culturally appropriate recruitment strategies and data collection protocol. ACAD addresses challenges of recruitment from heterogeneous Asian subcommunities. We aim to implement a successful recruitment program that enrolls across three Asian subcommunities.

To investigate the association between a genetic risk score (GRS) and familial late-onset Alzheimer disease (LOAD) and its predictive value in families multiply affected by the disease.Using data from the National Institute on Aging Genetics Initiative for Late-Onset Alzheimer Disease (National Institute on Aging-Late-Onset Alzheimer's Disease Family Study), mixed regression models tested the association of familial LOAD with a GRS based on single nucleotide polymorphisms (SNPs) previously associated with LOAD. We modeled associations using unweighted and weighted scores with estimates derived from the literature. In secondary models, we adjusted subsequent models for presence of the APOE ε4 allele and further tested the interaction between APOE ε4 and the GRS. We constructed a similar GRS in a cohort of Caribbean Hispanic families multiply affected by LOAD by selecting the SNP with the strongest p value within the same regions.In the NIA-LOAD families, the GRS was significantly associated with LOAD (odds ratio [OR] 1.29; 95% confidence interval 1.21-1.37). The results did not change after adjusting for APOE ε4. In Caribbean Hispanic families, the GRS also significantly predicted LOAD (OR 1.73; 1.57-1.93). Higher scores were associated with lower age at onset in both cohorts.High GRS increases the risk of familial LOAD and lowers the age at onset, regardless of ethnic group.

Significance Neuroimaging has largely focused on two goals: mapping associations between neuroanatomical features and phenotypes and building individual-level prediction models. This paper presents a complementary analytic strategy called morphometricity that aims to measure the neuroanatomical signatures of different phenotypes. Inspired by prior work on heritability, we define morphometricity as the proportion of phenotypic variation that can be explained by brain morphology (e.g., as captured by structural brain MRI). In the dawning era of large-scale datasets comprising traits across a broad phenotypic spectrum, morphometricity will be critical in prioritizing and characterizing behavioral, cognitive, and clinical phenotypes based on their neuroanatomical signatures. Furthermore, the proposed framework will be significant in dissecting the functional, morphological, and molecular underpinnings of different traits.

The Advancing Research and Treatment for Frontotemporal Lobar Degeneration (ARTFL) and Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS) consortia are two closely connected studies, involving multiple North American centers that evaluate both sporadic and familial frontotemporal dementia (FTD) participants and study longitudinal changes.We screened the major dementia-associated genes in 302 sporadic and 390 familial (symptomatic or at-risk) participants enrolled in these studies.Among the sporadic patients, 16 (5.3%) carried chromosome 9 open reading frame 72 (C9orf72), microtubule-associated protein tau (MAPT), and progranulin (GRN) pathogenic variants, whereas in the familial series we identified 207 carriers from 146 families. Of interest, one patient was found to carry a homozygous C9orf72 expansion, while another carried both a C9orf72 expansion and a GRN pathogenic variant. We also identified likely pathogenic variants in the TAR DNA binding protein (TARDBP), presenilin 1 (PSEN1), and valosin containing protein (VCP) genes, and a subset of variants of unknown significance in other rare FTD genes.Our study reports the genetic characterization of a large FTD series and supports an unbiased sequencing screen, irrespective of clinical presentation or family history.

Longitudinal tau positron emission tomography (PET) is a relevant outcome in clinical trials evaluating disease-modifying therapies in Alzheimer disease (AD). A key unanswered question is whether the use of participant-specific (individualized) regions of interest (ROIs) is superior to conventional approaches where the same ROI (group-level) is used for each participant.To compare group- and participant-level ROIs in participants at different stages of the AD clinical continuum in terms of annual percentage change in tau-PET standardized uptake value ratio (SUVR) and sample size requirements.This was a longitudinal cohort study with consecutive participant enrollment between September 18, 2017, and November 15, 2021. Included in the analysis were participants with mild cognitive impairment and AD dementia from the prospective and longitudinal Swedish Biomarkers For Identifying Neurodegenerative Disorders Early and Reliably 2 (BioFINDER-2) study; in addition, a validation sample (the AVID 05e, Expedition-3, Alzheimer's Disease Neuroimaging Initiative [ADNI], and BioFINDER-1 study cohorts) was also included.Tau PET (BioFINDER-2, [18F]RO948; validation sample, [18F]flortaucipir), 7 group-level (5 data-driven stages, meta-temporal, whole brain), and 5 individualized ROIs.Annual percentage change in tau-PET SUVR across ROIs. Sample size requirements in simulated clinical trials using tau PET as an outcome were also calculated.A total of 215 participants (mean [SD] age, 71.4 (7.5) years; 111 male [51.6%]) from the BioFINDER-2 study were included in this analysis: 97 amyloid-β (Aβ)-positive cognitively unimpaired (CU) individuals, 77 with Aβ-positive mild cognitive impairment (MCI), and 41 with AD dementia. In the validation sample were 137 Aβ-positive CU participants, 144 with Aβ-positive MCI, and 125 with AD dementia. Mean (SD) follow-up time was 1.8 (0.3) years. Using group-level ROIs, the largest annual percentage increase in tau-PET SUVR in Aβ-positive CU individuals was seen in a composite ROI combining the entorhinal cortex, hippocampus, and amygdala (4.29%; 95% CI, 3.42%-5.16%). In individuals with Aβ-positive MCI, the greatest change was seen in the temporal cortical regions (5.82%; 95% CI, 4.67%-6.97%), whereas in those with AD dementia, the greatest change was seen in the parietal regions (5.22%; 95% CI, 3.95%-6.49%). Significantly higher estimates of annual percentage change were found using several of the participant-specific ROIs. Importantly, the simplest participant-specific approach, where change in tau PET was calculated in an ROI that best matched the participant's data-driven disease stage, performed best in all 3 subgroups. For the power analysis, sample size reductions for the participant-specific ROIs ranged from 15.94% (95% CI, 8.14%-23.74%) to 72.10% (95% CI, 67.10%-77.20%) compared with the best-performing group-level ROIs. Findings were replicated using [18F]flortaucipir.Finding suggest that certain individualized ROIs carry an advantage over group-level ROIs for assessing longitudinal tau changes and increase the power to detect treatment effects in AD clinical trials using longitudinal tau PET as an outcome.

Physical activity is associated with cognitive health, even in autosomal dominant forms of dementia. Higher physical activity is associated with slowed cognitive and functional declines over time in adults carrying autosomal dominant variants for frontotemporal lobar degeneration (FTLD), but whether axonal degeneration is a potential neuroprotective target of physical activity in individuals with FTLD is unknown.To examine the association between physical activity and longitudinal neurofilament light chain (NfL) trajectories in individuals with autosomal dominant forms of FTLD.This cohort study included individuals from the ALLFTD Consortium, which recruited patients from sites in the US and Canada. Symptomatic and asymptomatic adults with pathogenic variants in one of 3 common genes associated with FTLD (GRN, C9orf72, or MAPT) who reported baseline physical activity levels and completed annual blood draws were assessed annually for up to 4 years. Genotype, clinical measures, and blood draws were collected between December 2014 and June 2019; data were analyzed from August 2021 to January 2022. Associations between reported baseline physical activity and longitudinal plasma NfL changes were assessed using generalized linear mixed-effects models adjusting for baseline age, sex, education, functional severity, and motor symptoms.Baseline physical activity levels reported via the Physical Activity Scale for the Elderly. To estimate effect sizes, marginal means were calculated at 3 levels of physical activity: 1 SD above the mean represented high physical activity, 0 SD represented average physical activity, and 1 SD below the mean represented low physical activity.Annual plasma NfL concentrations were measured with single-molecule array technology.Of 160 included FTLD variant carriers, 84 (52.5%) were female, and the mean (SD) age was 50.7 (14.7) years. A total of 51 (31.8%) were symptomatic, and 77 carried the C9orf72 variant; 39, GRN variant; and 44, MAPT variant. Higher baseline physical activity was associated with slower NfL trajectories over time. On average, NfL increased 45.8% (95% CI, 22.5 to 73.7) over 4 years in variant carriers. Variant carriers with high physical activity demonstrated 14.0% (95% CI, -22.7 to -4.3) slower NfL increases compared with those with average physical activity and 30% (95% CI, -52.2 to -8.8) slower NfL increases compared with those with low physical activity. Within genotype, C9orf72 and MAPT carriers with high physical activity evidenced 18% to 21% (95% CI, -43.4 to -7.2) attenuation in NfL, while the association between physical activity and NfL trajectory was not statistically significant in GRN carriers. Activities associated with higher cardiorespiratory and cognitive demands (sports, housework, and yardwork) were most strongly correlated with slower NfL trajectories (vs walking and strength training).In this study, higher reported physical activity was associated with slower progression of an axonal degeneration marker in individuals with autosomal dominant FTLD. Physical activity may serve as a primary prevention target in FTLD.

Copy number variants (CNVs) are DNA regions that have gains (duplications) or losses (deletions) of genetic material. CNVs may encompass a single gene or multiple genes and can affect their function. They are hypothesized to play an important role in certain diseases. We previously examined the role of CNVs in late-onset Alzheimer's disease (AD) and mild cognitive impairment (MCI) using participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) study and identified gene regions overlapped by CNVs only in cases (AD and/or MCI) but not in controls. Using a similar approach as ADNI, we investigated the role of CNVs using 794 AD and 196 neurologically evaluated control non-Hispanic Caucasian NIA-LOAD/NCRAD Family Study participants with DNA derived from blood/brain tissue. The controls had no family history of AD and were unrelated to AD participants. CNV calls were generated and analyzed after detailed quality review. 711 AD cases and 171 controls who passed all quality thresholds were included in case/control association analyses, focusing on candidate gene and genome-wide approaches. We identified genes overlapped by CNV calls only in AD cases but not controls. A trend for lower CNV call rate was observed for deletions as well as duplications in cases compared to controls. Gene-based association analyses confirmed previous findings in the ADNI study (ATXN1, HLA-DPB1, RELN, DOPEY2, GSTT1, CHRFAM7A, ERBB4, NRXN1) and identified a new gene (IMMP2L) that may play a role in AD susceptibility. Replication in independent samples as well as further analyses of these gene regions is warranted.

Copy number variations (CNVs) are genomic regions that have added (duplications) or deleted (deletions) genetic material. They may overlap genes affecting their function and have been shown to be associated with disease. We previously investigated the role of CNVs in late-onset Alzheimer's disease (AD) and mild cognitive impairment using Alzheimer's Disease Neuroimaging Initiative (ADNI) and National Institute of Aging-Late Onset AD/National Cell Repository for AD (NIA-LOAD/NCRAD) Family Study participants, and identified a number of genes overlapped by CNV calls. To confirm the findings and identify other potential candidate regions, we analyzed array data from a unique cohort of 1617 Caucasian participants (1022 AD cases and 595 controls) who were clinically characterized and whose diagnosis was neuropathologically verified. All DNA samples were extracted from brain tissue. CNV calls were generated and subjected to quality control (QC). 728 cases and 438 controls who passed all QC measures were included in case/control association analyses including candidate gene and genome-wide approaches. Rates of deletions and duplications did not significantly differ between cases and controls. Case-control association identified a number of previously reported regions (CHRFAM7A, RELN and DOPEY2) as well as a new gene (HLA-DRA). Meta-analysis of CHRFAM7A indicated a significant association of the gene with AD and/or MCI risk (P = 0.006, odds ratio = 3.986 (95% confidence interval 1.490-10.667)). A novel APP gene duplication was observed in one case sample. Further investigation of the identified genes in independent and larger samples is warranted.

<h3>Importance</h3> Late-onset Alzheimer disease (LOAD), defined as onset of symptoms after age 65 years, is the most common form of dementia. Few reports investigate incidence rates in large family-based studies in which the participants were selected for family history of LOAD. <h3>Objective</h3> To determine the incidence rates of dementia and LOAD in unaffected members in the National Institute on Aging Genetics Initiative for Late-Onset Alzheimer Disease/National Cell Repository for Alzheimer Disease (NIA-LOAD/NCRAD) and Estudio Familiar de Influencia Genetica en Alzheimer (EFIGA) family studies. <h3>Design, Setting, and Participants</h3> Families with 2 or more affected siblings who had a clinical or pathological diagnosis of LOAD were recruited as a part of the NIA-LOAD/NCRAD Family Study. A cohort of Caribbean Hispanics with familial LOAD was recruited in a different study at the Taub Institute for Research on Alzheimer’s Disease and the Aging Brain in New York and from clinics in the Dominican Republic as part of the EFIGA study. <h3>Main Outcomes and Measures</h3> Age-specific incidence rates of LOAD were estimated in the unaffected family members in the NIA-LOAD/NCRAD and EFIGA data sets. We restricted analyses to families with follow-up and complete phenotype information, including 396 NIA-LOAD/NCRAD and 242 EFIGA families. Among the 943 at-risk family members in the NIA-LOAD/NCRAD families, 126 (13.4%) developed dementia, of whom 109 (86.5%) met criteria for LOAD. Among 683 at-risk family members in the EFIGA families, 174 (25.5%) developed dementia during the study period, of whom 145 (83.3%) had LOAD. <h3>Results</h3> The annual incidence rates of dementia and LOAD in the NIA-LOAD/NCRAD families per person-year were 0.03 and 0.03, respectively, in participants aged 65 to 74 years; 0.07 and 0.06, respectively, in those aged 75 to 84 years; and 0.08 and 0.07, respectively, in those 85 years or older. Incidence rates in the EFIGA families were slightly higher, at 0.03 and 0.02, 0.06 and 0.05, 0.10 and 0.08, and 0.10 and 0.07, respectively, in the same age groups. Contrasting these results with the population-based estimates, the incidence was increased by 3-fold for NIA-LOAD/NCRAD families (standardized incidence ratio, 3.44) and 2-fold among the EFIGA compared with the NIA-LOAD/NCRAD families (1.71). <h3>Conclusions and Relevance</h3> The incidence rates for familial dementia and LOAD in the NIA-LOAD/NCRAD and EFIGA families are significantly higher than population-based estimates. The incidence rates in all groups increase with age. The higher incidence of LOAD can be explained by segregation of Alzheimer disease–related genes in these families or shared environmental risks.

<h3>Importance</h3> The contribution of cardiovascular disease (CV) and cerebrovascular disease to the risk for late-onset Alzheimer disease (LOAD) has been long debated. Investigations have shown that antecedent CV risk factors increase the risk for LOAD, although other investigations have failed to validate this association. <h3>Objective</h3> To study the contribution of CV risk factors (type 2 diabetes, hypertension, and heart disease) and the history of stroke to LOAD in a data set of large families multiply affected by LOAD. <h3>Design, Setting, and Participants</h3> The National Institute on Aging Late-Onset Alzheimer Disease/National Cell Repository for Alzheimer Disease family study (hereinafter referred to as NIA-LOAD study) is a longitudinal study of families with multiple members affected with LOAD. A multiethnic community-based longitudinal study (Washington Heights–Inwood Columbia Aging Project [WHICAP]) was used to replicate findings. The 6553 participants in the NIA-LOAD study were recruited from 23 US Alzheimer disease centers with ongoing data collection since 2003; the 5972 WHICAP participants were recruited at Columbia University with ongoing data collection since 1992. Data analysis was performed from 2003 to 2015. <h3>Main Outcomes and Measures</h3> Generalized mixed logistic regression models tested the association of CV risk factors (primary association) with LOAD. History of stroke was used for the secondary association. A secondary model adjusted for the presence of an apolipoprotein E (<i>APOE</i>)<i>ε4</i>allele. A genetic risk score, based on common variants associated with LOAD, was used to account for LOAD genetic risk beyond the<i>APOE ε4</i>effect. Mediation analyses evaluated stroke as a mediating factor between the primary association and LOAD. <h3>Results</h3> A total of 6553 NIA-LOAD participants were included in the analyses (4044 women [61.7%]; 2509 men [38.3%]; mean [SD] age, 77.0 [9] years), with 5972 individuals from the WHICAP study included in the replication sample (4072 women [68.2%]; 1900 men [31.8%]; mean [SD] age, 76.5 [7.0] years). Hypertension was associated with decreased LOAD risk (odds ratio [OR], 0.63; 95% CI, 0.55-0.72); type 2 diabetes and heart disease were not. History of stroke conferred greater than 2-fold increased risk for LOAD (OR, 2.23; 95% CI, 1.75-2.83). Adjustment for<i>APOE ε4</i>did not alter results. The genetic risk score was associated with LOAD (OR, 2.85; 95% CI, 2.05-3.97) but did not change the independent association of LOAD with hypertension or stroke. In the WHICAP sample, hypertension was not associated with LOAD (OR, 0.99; 95% CI, 0.88-1.11), whereas history of stroke increased the risk for LOAD (OR, 1.96; 95% CI, 1.56-2.46). The effect of hypertension on LOAD risk was also mediated by stroke in the NIA-LOAD and the WHICAP samples. <h3>Conclusions and Relevance</h3> In familial and sporadic LOAD, a history of stroke was significantly associated with increased disease risk and mediated the association between selected CV risk factors and LOAD, which appears to be independent of the LOAD-related genetic background.

Abstract Introduction It is important to establish the natural history of familial frontotemporal lobar degeneration (f‐FTLD) and provide clinical and biomarker data for planning these studies, particularly in the asymptomatic phase. Methods The Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects protocol was designed to enroll and follow at least 300 subjects for more than at least three annual visits who are members of kindreds with a mutation in one of the three most common f‐FTLD genes—microtubule‐associated protein tau, progranulin, or chromosome 9 open reading frame 72. Results We present the theoretical considerations of f‐FTLD and the aims/objectives of this protocol. We also describe the design and methodology for evaluating and rating subjects, in which detailed clinical and neuropsychological assessments are performed, biofluid samples are collected, and magnetic resonance imaging scans are performed using a standard protocol. Discussion These data and samples, which are available to interested investigators worldwide, will facilitate planning for upcoming disease‐modifying therapeutic trials in f‐FTLD.

Arterial spin labeled (ASL) magnetic resonance imaging (MRI) is the primary method for noninvasively measuring regional brain perfusion in humans. We introduce ASLPrep, a suite of software pipelines that ensure the reproducible and generalizable processing of ASL MRI data. ASLPrep is a software suite for reproducible processing of arterial spin labeled magnetic resonance imaging data.

Recently, a rare variant in the amyloid precursor protein gene (APP) was described in a population from Iceland. This variant, in which alanine is replaced by threonine at position 673 (A673T), appears to protect against late-onset Alzheimer disease (AD). We evaluated the frequency of this variant in AD cases and cognitively normal controls to determine whether this variant will significantly contribute to risk assessment in individuals in the United States.To determine the frequency of the APP A673T variant in a large group of elderly cognitively normal controls and AD cases from the United States and in 2 case-control cohorts from Sweden.Case-control association analysis of variant APP A673T in US and Swedish white individuals comparing AD cases with cognitively intact elderly controls. Participants were ascertained at multiple university-associated medical centers and clinics across the United States and Sweden by study-specific sampling methods. They were from case-control studies, community-based prospective cohort studies, and studies that ascertained multiplex families from multiple sources.Genotypes for the APP A673T variant were determined using the Infinium HumanExome V1 Beadchip (Illumina, Inc) and by TaqMan genotyping (Life Technologies).The A673T variant genotypes were evaluated in 8943 US AD cases, 10 480 US cognitively normal controls, 862 Swedish AD cases, and 707 Swedish cognitively normal controls. We identified 3 US individuals heterozygous for A673T, including 1 AD case (age at onset, 89 years) and 2 controls (age at last examination, 82 and 77 years). The remaining US samples were homozygous for the alanine (A673) allele. In the Swedish samples, 3 controls were heterozygous for A673T and all AD cases were homozygous for the A673 allele. We also genotyped a US family previously reported to harbor the A673T variant and found a mother-daughter pair, both cognitively normal at ages 72 and 84 years, respectively, who were both heterozygous for A673T; however, all individuals with AD in the family were homozygous for A673.The A673T variant is extremely rare in US cohorts and does not play a substantial role in risk for AD in this population. This variant may be primarily restricted to Icelandic and Scandinavian populations.

Previous studies have indicated a heritable component of the etiology of neurodegenerative diseases such as Alzheimer disease (AD), frontotemporal dementia (FTD), and progressive supranuclear palsy (PSP). However, few have examined the contribution of low-frequency coding variants on a genome-wide level.To identify low-frequency coding variants that affect susceptibility to AD, FTD, and PSP.We used the Illumina HumanExome BeadChip array to genotype a large number of variants (most of which are low-frequency coding variants) in a cohort of patients with neurodegenerative disease (224 with AD, 168 with FTD, and 48 with PSP) and in 224 control individuals without dementia enrolled between 2005-2012 from multiple centers participating in the Genetic Investigation in Frontotemporal Dementia and Alzheimer's Disease (GIFT) Study. An additional multiancestral replication cohort of 240 patients with AD and 240 controls without dementia was used to validate suggestive findings. Variant-level association testing and gene-based testing were performed.Statistical association of genetic variants with clinical diagnosis of AD, FTD, and PSP.Genetic variants typed by the exome array explained 44%, 53%, and 57% of the total phenotypic variance of AD, FTD, and PSP, respectively. An association with the known AD gene ABCA7 was replicated in several ancestries (discovery P=.0049, European P=.041, African American P=.043, and Asian P=.027), suggesting that exonic variants within this gene modify AD susceptibility. In addition, 2 suggestive candidate genes, DYSF (P=5.53×10(-5)) and PAXIP1 (P=2.26×10(-4)), were highlighted in patients with AD and differentially expressed in AD brain. Corroborating evidence from other exome array studies and gene expression data points toward potential involvement of these genes in the pathogenesis of AD.Low-frequency coding variants with intermediate effect size may account for a significant fraction of the genetic susceptibility to AD and FTD. Furthermore, we found evidence that coding variants in the known susceptibility gene ABCA7, as well as candidate genes DYSF and PAXIP1, confer risk for AD.

Abstract Introduction Behavioral variant frontotemporal dementia (bvFTD) may present sporadically or due to an autosomal dominant mutation. Characterization of both forms will improve understanding of the generalizability of assessments and treatments. Methods A total of 135 sporadic (s‐bvFTD; mean age 63.3 years; 34% female) and 99 familial (f‐bvFTD; mean age 59.9; 48% female) bvFTD participants were identified. f‐bvFTD cases included 43 with known or presumed chromosome 9 open reading frame 72 ( C9orf72 ) gene expansions, 28 with known or presumed microtubule‐associated protein tau (MAPT) mutations, 14 with known progranulin ( GRN ) mutations, and 14 with a strong family history of FTD but no identified mutation. Results Participants with f‐bvFTD were younger and had earlier age at onset. s‐bvFTD had higher total Neuropsychiatric Inventory Questionnaire (NPI‐Q) scores due to more frequent endorsement of depression and irritability. Discussion f‐bvFTD and s‐bvFTD cases are clinically similar, suggesting the generalizability of novel biomarkers, therapies, and clinical tools developed in either form to the other.

Abnormal gene expression patterns may contribute to the onset and progression of late-onset Alzheimer's disease (LOAD).We performed transcriptome-wide meta-analysis (N = 1440) of blood-based microarray gene expression profiles as well as neuroimaging and cerebrospinal fluid (CSF) endophenotype analysis.We identified and replicated five genes (CREB5, CD46, TMBIM6, IRAK3, and RPAIN) as significantly dysregulated in LOAD. The most significantly altered gene, CREB5, was also associated with brain atrophy and increased amyloid beta (Aβ) accumulation, especially in the entorhinal cortex region. cis-expression quantitative trait loci mapping analysis of CREB5 detected five significant associations (P < 5 × 10-8 ), where rs56388170 (most significant) was also significantly associated with global cortical Aβ deposition measured by [18 F]Florbetapir positron emission tomography and CSF Aβ1-42 .RNA from peripheral blood indicated a differential gene expression pattern in LOAD. Genes identified have been implicated in biological processes relevant to Alzheimer's disease. CREB, in particular, plays a key role in nervous system development, cell survival, plasticity, and learning and memory.

Alzheimer's disease (AD) is a complex and heterogeneous disease that can be affected by various genetic factors. Although the cause of AD is not yet known and there is no treatment to cure this disease, its progression can be delayed. AD has recently been recognized as a brain-specific type of diabetes called type 3 diabetes. Several studies have shown that people with type 2 diabetes (T2D) have a higher risk of developing AD. Therefore, it is important to identify subgroups of patients with AD that may be more likely to be associated with T2D. We here describe a new approach to identify the correlation between AD and T2D at the genetic level. Subgroups of AD and T2D were each generated using a non-negative matrix factorization (NMF) approach, which generated clusters containing subsets of genes and samples. In the gene cluster that was generated by conventional gene clustering method from NMF, we selected genes with significant differences in the corresponding sample cluster by Kruskal-Wallis and Dunn-test. Subsequently, we extracted differentially expressed gene (DEG) subgroups, and candidate genes with the same regulation direction can be extracted at the intersection of two disease DEG subgroups. Finally, we identified 241 candidate genes that represent common features related to both AD and T2D, and based on pathway analysis we propose that these genes play a role in the common pathological features of AD and T2D. Moreover, in the prediction of AD using logistic regression analysis with an independent AD dataset, the candidate genes obtained better prediction performance than DEGs. In conclusion, our study revealed a subgroup of patients with AD that are associated with T2D and candidate genes associated between AD and T2D, which can help in providing personalized and suitable treatments.

Genetics play an important role in late-onset Alzheimer's Disease (AD) etiology and dozens of genetic variants have been implicated in AD risk through large-scale GWAS meta-analyses. However, the precise mechanistic effects of most of these variants have yet to be determined. Deeply phenotyped cohort data can reveal physiological changes associated with genetic risk for AD across an age spectrum that may provide clues to the biology of the disease. We utilized over 2000 high-quality quantitative measurements obtained from blood of 2831 cognitively normal adult clients of a consumer-based scientific wellness company, each with CLIA-certified whole-genome sequencing data. Measurements included: clinical laboratory blood tests, targeted chip-based proteomics, and metabolomics. We performed a phenome-wide association study utilizing this diverse blood marker data and 25 known AD genetic variants and an AD-specific polygenic risk score (PGRS), adjusting for sex, age, vendor (for clinical labs), and the first four genetic principal components; sex-SNP interactions were also assessed. We observed statistically significant SNP-analyte associations for five genetic variants after correction for multiple testing (for SNPs in or near NYAP1, ABCA7, INPP5D, and APOE), with effects detectable from early adulthood. The ABCA7 SNP and the APOE2 and APOE4 encoding alleles were associated with lipid variability, as seen in previous studies; in addition, six novel proteins were associated with the e2 allele. The most statistically significant finding was between the NYAP1 variant and PILRA and PILRB protein levels, supporting previous functional genomic studies in the identification of a putative causal variant within the PILRA gene. We did not observe associations between the PGRS and any analyte. Sex modified the effects of four genetic variants, with multiple interrelated immune-modulating effects associated with the PICALM variant. In post-hoc analysis, sex-stratified GWAS results from an independent AD case-control meta-analysis supported sex-specific disease effects of the PICALM variant, highlighting the importance of sex as a biological variable. Known AD genetic variation influenced lipid metabolism and immune response systems in a population of non-AD individuals, with associations observed from early adulthood onward. Further research is needed to determine whether and how these effects are implicated in early-stage biological pathways to AD. These analyses aim to complement ongoing work on the functional interpretation of AD-associated genetic variants.

Changes in the levels of circulating proteins are associated with Alzheimer's disease (AD), whereas their pathogenic roles in AD are unclear. Here, we identified soluble ST2 (sST2), a decoy receptor of interleukin-33-ST2 signaling, as a new disease-causing factor in AD. Increased circulating sST2 level is associated with more severe pathological changes in female individuals with AD. Genome-wide association analysis and CRISPR-Cas9 genome editing identified rs1921622 , a genetic variant in an enhancer element of IL1RL1, which downregulates gene and protein levels of sST2. Mendelian randomization analysis using genetic variants, including rs1921622 , demonstrated that decreased sST2 levels lower AD risk and related endophenotypes in females carrying the Apolipoprotein E (APOE)-ε4 genotype; the association is stronger in Chinese than in European-descent populations. Human and mouse transcriptome and immunohistochemical studies showed that rs1921622 /sST2 regulates amyloid-beta (Aβ) pathology through the modulation of microglial activation and Aβ clearance. These findings demonstrate how sST2 level is modulated by a genetic variation and plays a disease-causing role in females with AD.

Sex differences are established in associations between apolipoprotein E (APOE) ε4 and cognitive impairment in Alzheimer disease (AD). However, it is unclear whether sex-specific cognitive consequences of APOE are consistent across races and extend to the APOE ε2 allele.To investigate whether sex and race modify APOE ε4 and ε2 associations with cognition.This genetic association study included longitudinal cognitive data from 4 AD and cognitive aging cohorts. Participants were older than 60 years and self-identified as non-Hispanic White or non-Hispanic Black (hereafter, White and Black). Data were previously collected across multiple US locations from 1994 to 2018. Secondary analyses began December 2021 and ended September 2022.Harmonized composite scores for memory, executive function, and language were generated using psychometric approaches. Linear regression assessed interactions between APOE ε4 or APOE ε2 and sex on baseline cognitive scores, while linear mixed-effect models assessed interactions on cognitive trajectories. The intersectional effect of race was modeled using an APOE × sex × race interaction term, assessing whether APOE × sex interactions differed by race. Models were adjusted for age at baseline and corrected for multiple comparisons.Of 32 427 participants who met inclusion criteria, there were 19 007 females (59%), 4453 Black individuals (14%), and 27 974 White individuals (86%); the mean (SD) age at baseline was 74 years (7.9). At baseline, 6048 individuals (19%) had AD, 4398 (14%) were APOE ε2 carriers, and 12 538 (38%) were APOE ε4 carriers. Participants missing APOE status were excluded (n = 9266). For APOE ε4, a robust sex interaction was observed on baseline memory (β = -0.071, SE = 0.014; P = 9.6 × 10-7), whereby the APOE ε4 negative effect was stronger in females compared with males and did not significantly differ among races. Contrastingly, despite the large sample size, no APOE ε2 × sex interactions on cognition were observed among all participants. When testing for intersectional effects of sex, APOE ε2, and race, an interaction was revealed on baseline executive function among individuals who were cognitively unimpaired (β = -0.165, SE = 0.066; P = .01), whereby the APOE ε2 protective effect was female-specific among White individuals but male-specific among Black individuals.In this study, while race did not modify sex differences in APOE ε4, the APOE ε2 protective effect could vary by race and sex. Although female sex enhanced ε4-associated risk, there was no comparable sex difference in ε2, suggesting biological pathways underlying ε4-associated risk are distinct from ε2 and likely intersect with age-related changes in sex biology.

MAPT mutations typically cause behavioral variant frontotemporal dementia with or without parkinsonism. Previous studies have shown that symptomatic MAPT mutation carriers have frontotemporal atrophy, yet studies have shown mixed results as to whether presymptomatic carriers have low gray matter volumes. To elucidate whether presymptomatic carriers have lower structural brain volumes within regions atrophied during the symptomatic phase, we studied a large cohort of MAPT mutation carriers using a voxelwise approach.We studied 22 symptomatic carriers (age 54.7 ± 9.1, 13 female) and 43 presymptomatic carriers (age 39.2 ± 10.4, 21 female). Symptomatic carriers' clinical syndromes included: behavioral variant frontotemporal dementia (18), an amnestic dementia syndrome (2), Parkinson's disease (1), and mild cognitive impairment (1). We performed voxel-based morphometry on T1 images and assessed brain volumetrics by clinical subgroup, age, and mutation subtype.Symptomatic carriers showed gray matter atrophy in bilateral frontotemporal cortex, insula, and striatum, and white matter atrophy in bilateral corpus callosum and uncinate fasciculus. Approximately 20% of presymptomatic carriers had low gray matter volumes in bilateral hippocampus, amygdala, and lateral temporal cortex. Within these regions, low gray matter volumes emerged in a subset of presymptomatic carriers as early as their thirties. Low white matter volumes arose infrequently among presymptomatic carriers.A subset of presymptomatic MAPT mutation carriers showed low volumes in mesial temporal lobe, the region ubiquitously atrophied in all symptomatic carriers. With each decade of age, an increasing percentage of presymptomatic carriers showed low mesial temporal volume, suggestive of early neurodegeneration.

The APOE locus is strongly associated with risk for developing Alzheimer's disease and dementia with Lewy bodies. In particular, the role of the APOE ε4 allele as a putative driver of α-synuclein pathology is a topic of intense debate. Here, we performed a comprehensive evaluation in 2466 dementia with Lewy bodies cases versus 2928 neurologically healthy, aged controls. Using an APOE-stratified genome-wide association study approach, we found that GBA is associated with risk for dementia with Lewy bodies in patients without APOE ε4 (P = 6.58 × 10-9, OR = 3.41, 95% CI = 2.25-5.17), but not with dementia with Lewy bodies with APOE ε4 (P = 0.034, OR = 1.87, 95%, 95% CI = 1.05-3.37). We then divided 495 neuropathologically examined dementia with Lewy bodies cases into three groups based on the extent of concomitant Alzheimer's disease co-pathology: pure dementia with Lewy bodies (n = 88), dementia with Lewy bodies with intermediate Alzheimer's disease co-pathology (n = 66) and dementia with Lewy bodies with high Alzheimer's disease co-pathology (n = 341). In each group, we tested the association of the APOE ε4 against the 2928 neurologically healthy controls. Our examination found that APOE ε4 was associated with dementia with Lewy bodies + Alzheimer's disease (P = 1.29 × 10-32, OR = 4.25, 95% CI = 3.35-5.39) and dementia with Lewy bodies + intermediate Alzheimer's disease (P = 0.0011, OR = 2.31, 95% CI = 1.40-3.83), but not with pure dementia with Lewy bodies (P = 0.31, OR = 0.75, 95% CI = 0.43-1.30). In conclusion, although deep clinical data were not available for these samples, our findings do not support the notion that APOE ε4 is an independent driver of α-synuclein pathology in pure dementia with Lewy bodies, but rather implicate GBA as the main risk gene for the pure dementia with Lewy bodies subgroup.

Pathogenic mutations in APP, PSEN1, PSEN2, MAPT and GRN have previously been linked to familial early onset forms of dementia.Mutation screening in these genes has been performed in either very small series or in single families with late onset AD (LOAD).Similarly, studies in single families have reported mutations in MAPT and GRN associated with clinical AD but no systematic screen of a large dataset has been performed to determine how frequently this occurs.We report sequence data for 439 probands from late-onset AD families with a history of four or more affected individuals.Sixty sequenced individuals (13.7%) carried a novel or pathogenic mutation.Eight pathogenic variants, (one each in APP and MAPT, two in PSEN1 and four in GRN) three of which are novel, were found in 14 samples.Thirteen additional variants, present in 23 families, did not segregate with disease, but the frequency of these variants is higher in AD cases than controls, indicating that these variants may also modify risk for disease.The frequency of rare variants in these genes in this series is significantly higher than in the 1,000 genome project (p = 5.09610 25 ; OR = 2.21; 95%CI = 1.49-3.28)or an unselected population of 12,481 samples (p = 6.82610 25 ; OR = 2.19; 95%CI = 1.347-3.26).Rare coding variants in APP, PSEN1 and PSEN2, increase risk for or cause late onset AD.The presence of variants in these genes in LOAD and early-onset AD demonstrates that factors other than the mutation can impact the age at onset and penetrance of at least some variants associated with AD.MAPT and GRN mutations can be found in clinical series of AD most likely due to misdiagnosis.This study clearly demonstrates that rare variants in these genes could explain an important proportion of genetic heritability of AD, which is not detected by GWAS.

<h3>Objective</h3> To identify genetic variation influencing late-onset Alzheimer disease (LOAD), we used a large data set of non-Hispanic white (NHW) extended families multiply-affected by LOAD by performing whole genome sequencing (WGS). <h3>Methods</h3> As part of the Alzheimer Disease Sequencing Project, WGS data were generated for 197 NHW participants from 42 families (affected individuals and unaffected, elderly relatives). A two-pronged approach was taken. First, variants were prioritized using heterogeneity logarithm of the odds (HLOD) and family-specific LOD scores as well as annotations based on function, frequency, and segregation with disease. Second, known Alzheimer disease (AD) candidate genes were assessed for rare variation using a family-based association test. <h3>Results</h3> We identified 41 rare, predicted-damaging variants that segregated with disease in the families that contributed to the HLOD or family-specific LOD regions. These included a variant in nitric oxide synthase 1 adaptor protein that segregates with disease in a family with 7 individuals with AD, as well as variants in <i>RP11-433J8, ABCA1</i>, and <i>FISP2</i>. Rare-variant association identified 2 LOAD candidate genes associated with disease in these families: <i>FERMT2</i> (<i>p</i>-values = 0.001) and <i>SLC24A4</i> (<i>p</i>-value = 0.009). These genes still showed association while controlling for common index variants, indicating the rare-variant signal is distinct from common variation that initially identified the genes as candidates. <h3>Conclusions</h3> We identified multiple genes with putative damaging rare variants that segregate with disease in multiplex AD families and showed that rare variation may influence AD risk at AD candidate genes. These results identify novel AD candidate genes and show a role for rare variation in LOAD etiology, even at genes previously identified by common variation.

With improved healthcare, the Down syndrome (DS) population is both growing and aging rapidly. However, with longevity comes a very high risk of Alzheimer's disease (AD). The LIFE-DSR study (NCT04149197) is a longitudinal natural history study recruiting 270 adults with DS over the age of 25. The study is designed to characterize trajectories of change in DS-associated AD (DS-AD). The current study reports its cross-sectional analysis of the first 90 subjects enrolled. Plasma biomarkers phosphorylated tau protein (p-tau), neurofilament light chain (NfL), amyloid β peptides (Aβ1-40, Aβ1-42), and glial fibrillary acidic protein (GFAP) were undertaken with previously published methods. The clinical data from the baseline visit include demographics as well as the cognitive measures under the Severe Impairment Battery (SIB) and Down Syndrome Mental Status Examination (DS-MSE). Biomarker distributions are described with strong statistical associations observed with participant age. The biomarker data contributes to understanding DS-AD across the spectrum of disease. Collectively, the biomarker data show evidence of DS-AD progression beginning at approximately 40 years of age. Exploring these data across the full LIFE-DSR longitudinal study population will be an important resource in understanding the onset, progression, and clinical profiles of DS-AD pathophysiology.

The National Institute on Aging Late-Onset Alzheimer's Disease Family Based Study (NIA-LOAD FBS) was established to study the genetic etiology of Alzheimer's disease (AD).Recruitment focused on families with two living affected siblings and a third first-degree relative similar in age with or without dementia. Uniform assessments were completed, DNA was obtained, as was neuropathology, when possible. Apolipoprotein E (APOE) genotypes, genome-wide single nucleotide polymorphism (SNP) arrays, and sequencing was completed in most families.APOE genotype modified the age-at-onset in many large families. Novel variants and known variants associated with early- and late-onset AD and frontotemporal dementia were identified supporting an international effort to solve AD genetics.The NIA-LOAD FBS is the largest collection of familial AD worldwide, and data or samples have been included in 123 publications addressing the genetic etiology of AD. Genetic heterogeneity and variability in the age-at-onset provides opportunities to investigate the complexity of familial AD.

1. Using an isolated turtle brain preparation, we made extracellular spike recordings in the dorsal midbrain during visual stimulation. Single units were isolated by their response to a slow-moving full-field visual pattern imaged on the contralateral retina. This stimulus elicits responses from the basal optic nucleus (BON) and the cerebellar cortex using a similar preparation. Direction and speed tuning were then analyzed, as well as the size and position of the receptive field. 2. In one brain stem region, anterior to the optic tectum and deep to the dorsal surface, all of the visually responsive neurons were direction sensitive (DS) to contralateral retinal stimulation. The location and properties of these cells indicate that they are in the mesencephalic lentiform nucleus (nLM). Anterograde transport of intravitreally injected horseradish peroxidase revealed that this pretectal nucleus receives direct input from the contralateral eye. 3. All but 2 of the 48 cells of the nLM were strongly DS. The most effective stimulus was a slowly moving complex visual pattern that drifted nasally in the contralateral visual field. Brief flashes of spots, patterns, or diffuse light were much less effective. Receptive fields were large and usually (9 of 13 cells) centered in the superior visual field near the horizon and nasal to the blind spot. 4. The visual responses of nLM cells were compared to those of cells in the superficial layers of the optic tectum. In contrast to nLM, the responses of tectal cells were heterogeneous and frequently not DS. Neither tectum or nLM cells had much spontaneous spike activity during darkness or stationary patterns. On the other hand, visual responses of nLM cells were very similar to those of the BON, where neurons also had low spontaneous activity, preferred slow-moving patterns, and were DS. However, nLM and BON exhibit different distributions of preferred directions. Most nLM cells preferred temporal-to-nasal motion, whereas BON cells preferred almost any direction, although few preferred the nasal direction. nLM cell responses were not affected by removal of the ventral brain stem including the BON. 5. The visual properties of nLM cells recorded in vitro were very similar to those that were recorded in intact turtles.(ABSTRACT TRUNCATED AT 400 WORDS)

Abstract Alzheimer’s disease (AD) is a progressive disorder associated with cognitive dysfunction that alters the brain’s functional connectivity. Assessing these alterations has become a topic of increasing interest. However, a few studies have examined different stages of AD from a complex network perspective that cover different topological scales. This study used resting state fMRI data to analyze the trend of functional connectivity alterations from a cognitively normal (CN) state through early and late mild cognitive impairment (EMCI and LMCI) and to Alzheimer’s disease. The analyses had been done at the local (hubs and activated links and areas), meso (clustering, assortativity, and rich-club), and global (small-world, small-worldness, and efficiency) topological scales. The results showed that the trends of changes in the topological architecture of the functional brain network were not entirely proportional to the AD progression. There were network characteristics that have changed non-linearly regarding the disease progression, especially at the earliest stage of the disease, i.e., EMCI. Further, it has been indicated that the diseased groups engaged somatomotor, frontoparietal, and default mode modules compared to the CN group. The diseased groups also shifted the functional network towards more random architecture. In the end, the methods introduced in this paper enable us to gain an extensive understanding of the pathological changes of the AD process.

Determining the genetic architecture of Alzheimer's disease (AD) pathologies can enhance mechanistic understanding and inform precision medicine strategies. Here, we performed a genome-wide association study of cortical tau quantified by positron emission tomography in 3,136 participants from 12 independent studies. The CYP1B1-RMDN2 locus was associated with tau deposition. The most significant signal was at rs2113389, which explained 4.3% of the variation in cortical tau, while APOE4 rs429358 accounted for 3.6%. rs2113389 was associated with higher tau and faster cognitive decline. Additive effects, but no interactions, were observed between rs2113389 and diagnosis, APOE4 , and Aβ positivity. CYP1B1 expression was upregulated in AD. rs2113389 was associated with higher CYP1B1 expression and methylation levels. Mouse model studies provided additional functional evidence for a relationship between CYP1B1 and tau deposition but not Aβ. These results may provide insight into the genetic basis of cerebral tau and novel pathways for therapeutic development in AD.

To compute penetrance and recurrence risk using a genome-wide PRS (including and excluding the APOE region) in families with Alzheimer's disease.Genotypes from the National Institute on Aging Late-Onset Alzheimer's Disease Family-Based Study and a study of familial Alzheimer's disease in Caribbean Hispanics were used to compute PRS with and without variants in the 2 MB region flanking APOE. PRS was calculated in using clumping/thresholding and Bayesian methods and was assessed for association with Alzheimer's disease and age at onset. Penetrance and recurrence risk for carriers in highest and lowest PRS quintiles were compared separately within APOE-ε4 carriers and non-carriers.PRS excluding the APOE region was strongly associated with clinical and neuropathological diagnosis of AD. PRS association with AD was similar in participants who did not carry an APOE-ε4 allele (OR = 1.74 [1.53-1.91]) compared with APOE-ε4 carriers (1.53 [1.4-1.68]). Compared to the lowest quintile, the highest PRS quintile had a 10% higher penetrance at age 70 (p = 0.0006) and a 20% higher penetrance at age 80 (p < 10e-05). Stratifying by APOE-ε4 allele, PRS in the highest quintile was significantly more penetrant than the lowest quintile, both, within APOE-ε4 carriers (14.5% higher at age 80, p = 0.002) and non-carriers (26% higher at 80, p < 10e-05). Recurrence risk for siblings conferred by a co-sibling in the highest PRS quintile increased from 4% between the ages of 65-74 years to 39% at age 85 and older.PRS can be used to estimate penetrance and recurrence risk in familial Alzheimer's disease among carriers and non-carries of APOE-ε4.

Limited ancestral diversity has impaired our ability to detect risk variants more prevalent in non-European ancestry groups in genome-wide association studies (GWAS). We constructed and analyzed a multi-ancestry GWAS dataset in the Alzheimer's Disease (AD) Genetics Consortium (ADGC) to test for novel shared and ancestry-specific AD susceptibility loci and evaluate underlying genetic architecture in 37,382 non-Hispanic White (NHW), 6,728 African American, 8,899 Hispanic (HIS), and 3,232 East Asian individuals, performing within-ancestry fixed-effects meta-analysis followed by a cross-ancestry random-effects meta-analysis. We identified 13 loci with cross-ancestry associations including known loci at/near CR1 , BIN1 , TREM2 , CD2AP , PTK2B , CLU , SHARPIN , MS4A6A , PICALM , ABCA7 , APOE and two novel loci not previously reported at 11p12 ( LRRC4C ) and 12q24.13 ( LHX5-AS1 ). Reflecting the power of diverse ancestry in GWAS, we observed the SHARPIN locus using 7.1% the sample size of the original discovering single-ancestry GWAS (n=788,989). We additionally identified three GWS ancestry-specific loci at/near ( PTPRK ( P =2.4×10 -8 ) and GRB14 ( P =1.7×10 -8 ) in HIS), and KIAA0825 ( P =2.9×10 -8 in NHW). Pathway analysis implicated multiple amyloid regulation pathways (strongest with Padjusted =1.6×10 -4 ) and the classical complement pathway ( Padjusted =1.3×10 -3 ). Genes at/near our novel loci have known roles in neuronal development ( LRRC4C, LHX5-AS1 , and PTPRK ) and insulin receptor activity regulation ( GRB14 ). These findings provide compelling support for using traditionally-underrepresented populations for gene discovery, even with smaller sample sizes.

One goal of the Longitudinal Early Onset Alzheimer's Disease Study (LEADS) is to define the fluid biomarker characteristics of early-onset Alzheimer's disease (EOAD).Cerebrospinal fluid (CSF) concentrations of Aβ1-40, Aβ1-42, total tau (tTau), pTau181, VILIP-1, SNAP-25, neurogranin (Ng), neurofilament light chain (NfL), and YKL-40 were measured by immunoassay in 165 LEADS participants. The associations of biomarker concentrations with diagnostic group and standard cognitive tests were evaluated.Biomarkers were correlated with one another. Levels of CSF Aβ42/40, pTau181, tTau, SNAP-25, and Ng in EOAD differed significantly from cognitively normal and early-onset non-AD dementia; NfL, YKL-40, and VILIP-1 did not. Across groups, all biomarkers except SNAP-25 were correlated with cognition. Within the EOAD group, Aβ42/40, NfL, Ng, and SNAP-25 were correlated with at least one cognitive measure.This study provides a comprehensive analysis of CSF biomarkers in sporadic EOAD that can inform EOAD clinical trial design.

Abstract The heterogeneity of the whole-exome sequencing (WES) data generation methods present a challenge to a joint analysis. Here we present a bioinformatics strategy for joint-calling 20,504 WES samples collected across nine studies and sequenced using ten capture kits in fourteen sequencing centers in the Alzheimer’s Disease Sequencing Project. The joint-genotype called variant-called format (VCF) file contains only positions within the union of capture kits. The VCF was then processed specifically to account for the batch effects arising from the use of different capture kits from different studies. We identified 8.2 million autosomal variants. 96.82% of the variants are high-quality, and are located in 28,579 Ensembl transcripts. 41% of the variants are intronic and 1.8% of the variants are with CADD &gt; 30, indicating they are of high predicted pathogenicity. Here we show our new strategy can generate high-quality data from processing these diversely generated WES samples. The improved ability to combine data sequenced in different batches benefits the whole genomics research community.

The iDA Project (iPSCs to Study Diversity in Alzheimer's and Alzheimer's Disease-related Dementias) is generating 200 induced pluripotent stem cell lines from Alzheimer's Disease Neuroimaging Initiative participants. These lines are sex balanced, include common APOE genotypes, span disease stages, and are ancestrally diverse. Cell lines and characterization data will be shared openly. The iDA Project (iPSCs to Study Diversity in Alzheimer's and Alzheimer's Disease-related Dementias) is generating 200 induced pluripotent stem cell lines from Alzheimer's Disease Neuroimaging Initiative participants. These lines are sex balanced, include common APOE genotypes, span disease stages, and are ancestrally diverse. Cell lines and characterization data will be shared openly.

The pathophysiological mechanisms driving disease progression of frontotemporal lobar degeneration (FTLD) and corresponding biomarkers are not fully understood. We leveraged aptamer-based proteomics (> 4,000 proteins) to identify dysregulated communities of co-expressed cerebrospinal fluid proteins in 116 adults carrying autosomal dominant FTLD mutations (C9orf72, GRN, MAPT) compared to 39 noncarrier controls. Network analysis identified 31 protein co-expression modules. Proteomic signatures of genetic FTLD clinical severity included increased abundance of RNA splicing (particularly in C9orf72 and GRN) and extracellular matrix (particularly in MAPT) modules, as well as decreased abundance of synaptic/neuronal and autophagy modules. The generalizability of genetic FTLD proteomic signatures was tested and confirmed in independent cohorts of 1) sporadic progressive supranuclear palsy-Richardson syndrome and 2) frontotemporal dementia spectrum syndromes. Network-based proteomics hold promise for identifying replicable molecular pathways in adults living with FTLD. 'Hub' proteins driving co-expression of affected modules warrant further attention as candidate biomarkers and therapeutic targets.

Frontotemporal lobar degeneration (FTLD) is relatively rare, behavioral and motor symptoms increase travel burden, and standard neuropsychological tests are not sensitive to early-stage disease. Remote smartphone-based cognitive assessments could mitigate these barriers to trial recruitment and success, but no such tools are validated for FTLD.To evaluate the reliability and validity of smartphone-based cognitive measures for remote FTLD evaluations.In this cohort study conducted from January 10, 2019, to July 31, 2023, controls and participants with FTLD performed smartphone application (app)-based executive functioning tasks and an associative memory task 3 times over 2 weeks. Observational research participants were enrolled through 18 centers of a North American FTLD research consortium (ALLFTD) and were asked to complete the tests remotely using their own smartphones. Of 1163 eligible individuals (enrolled in parent studies), 360 were enrolled in the present study; 364 refused and 439 were excluded. Participants were divided into discovery (n = 258) and validation (n = 102) cohorts. Among 329 participants with data available on disease stage, 195 were asymptomatic or had preclinical FTLD (59.3%), 66 had prodromal FTLD (20.1%), and 68 had symptomatic FTLD (20.7%) with a range of clinical syndromes.Participants completed standard in-clinic measures and remotely administered ALLFTD mobile app (app) smartphone tests.Internal consistency, test-retest reliability, association of smartphone tests with criterion standard clinical measures, and diagnostic accuracy.In the 360 participants (mean [SD] age, 54.0 [15.4] years; 209 [58.1%] women), smartphone tests showed moderate-to-excellent reliability (intraclass correlation coefficients, 0.77-0.95). Validity was supported by association of smartphones tests with disease severity (r range, 0.38-0.59), criterion-standard neuropsychological tests (r range, 0.40-0.66), and brain volume (standardized β range, 0.34-0.50). Smartphone tests accurately differentiated individuals with dementia from controls (area under the curve [AUC], 0.93 [95% CI, 0.90-0.96]) and were more sensitive to early symptoms (AUC, 0.82 [95% CI, 0.76-0.88]) than the Montreal Cognitive Assessment (AUC, 0.68 [95% CI, 0.59-0.78]) (z of comparison, -2.49 [95% CI, -0.19 to -0.02]; P = .01). Reliability and validity findings were highly similar in the discovery and validation cohorts. Preclinical participants who carried pathogenic variants performed significantly worse than noncarrier family controls on 3 app tasks (eg, 2-back β = -0.49 [95% CI, -0.72 to -0.25]; P < .001) but not a composite of traditional neuropsychological measures (β = -0.14 [95% CI, -0.42 to 0.14]; P = .32).The findings of this cohort study suggest that smartphones could offer a feasible, reliable, valid, and scalable solution for remote evaluations of FTLD and may improve early detection. Smartphone assessments should be considered as a complementary approach to traditional in-person trial designs. Future research should validate these results in diverse populations and evaluate the utility of these tests for longitudinal monitoring.

Our aim was to investigate the patterns and trajectories of white matter (WM) diffusion abnormalities in microtubule-associated protein tau (MAPT) mutations carriers. We studied 22 MAPT mutation carriers (12 asymptomatic, 10 symptomatic) and 20 noncarriers from 8 families, who underwent diffusion tensor imaging (DTI) and a subset (10 asymptomatic, 6 symptomatic MAPT mutation carriers, and 10 noncarriers) were followed annually (median = 4 years). Cross-sectional and longitudinal changes in mean diffusivity (MD) and fractional anisotropy were analyzed. Asymptomatic MAPT mutation carriers had higher MD in entorhinal WM, which propagated to the limbic tracts and frontotemporal projections in the symptomatic stage compared with noncarriers. Reduced fractional anisotropy and increased MD in the entorhinal WM were associated with the proximity to estimated and actual age of symptom onset. The annualized change of entorhinal MD on serial DTI was accelerated in MAPT mutation carriers compared with noncarriers. Entorhinal WM diffusion abnormalities precede the symptom onset and track with disease progression in MAPT mutation carriers. Our cross-sectional and longitudinal data showed a potential clinical utility for DTI to track neurodegenerative disease progression for MAPT mutation carriers in clinical trials.

Abstract Introduction Conventional Z‐scores are generated by subtracting the mean and dividing by the standard deviation. More recent methods linearly correct for age, sex, and education, so that these “adjusted” Z‐scores better represent whether an individual's cognitive performance is abnormal. Extreme negative Z‐scores for individuals relative to this normative distribution are considered indicative of cognitive deficiency. Methods In this article, we consider nonlinear shape constrained additive models accounting for age, sex, and education (correcting for nonlinearity). Additional shape constrained additive models account for varying standard deviation of the cognitive scores with age (correcting for heterogeneity of variance). Results Corrected Z‐scores based on nonlinear shape constrained additive models provide improved adjustment for age, sex, and education, as indicated by higher adjusted‐R 2 . Discussion Nonlinearly corrected Z‐scores with respect to age, sex, and education with age‐varying residual standard deviation allow for improved detection of non‐normative extreme cognitive scores.

Psychotic symptoms are frequent in late-onset Alzheimer's disease (LOAD) patients. Although the risk for psychosis in LOAD is genetically mediated, no genes have been identified. To identify loci potentially containing genetic variants associated with risk of psychosis in LOAD, a total of 263 families from the National Institute of Aging-LOAD cohort were classified into psychotic (LOAD+P, n = 215) and nonpsychotic (LOAD-P, n = 48) families based on the presence/absence of psychosis during the course of LOAD. The LOAD+P families yielded strong evidence of linkage on chromosome 19q13 (two-point [2-pt] ​logarithm of odds [LOD] = 3.8, rs2285513 and multipoint LOD = 2.7, rs541169). Joint linkage and association in 19q13 region detected strong association with rs2945988 (p = 8.7 × 10(-7)). Linkage results for the LOAD-P families yielded nonsignificant 19q13 LOD scores. Several 19q13 single-nucleotide polymorphisms generalized the association of LOAD+P in a Caribbean Hispanic (CH) cohort, and the strongest signal was rs10410711 (pmeta = 5.1 × 10(-5)). A variant located 24 kb upstream of rs10410711 and rs10421862 was strongly associated with LOAD+P (pmeta = 1.0 × 10(-5)) in a meta-analysis of the CH cohort and an additional non-Hispanic Caucasian dataset. Identified variants rs2945988 and rs10421862 affect brain gene expression levels. Our results suggest that genetic variants in genes on 19q13, some of which are involved in brain development and neurodegeneration, may influence the susceptibility to psychosis in LOAD patients.

Abstract Objective The Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects evaluates familial frontotemporal lobar degeneration (FTLD) kindreds with MAPT , GRN , or C9orf72 mutations. Objectives were to examine whether health‐related quality of life (HRQoL) correlates with clinical symptoms and caregiver burden, and whether self‐rated and informant‐rated HRQoL would correlate with each other. Methods Individuals were classified using the Clinical Dementia Rating (CDR ® ) Scale plus National Alzheimer's Coordinating Center (NACC) FTLD. HRQoL was measured with DEMQOL and DEMQOL‐proxy; caregiver burden with the Zarit Burden Interview (ZBI). For analysis, Pearson correlations and weighted kappa statistics were calculated. Results The cohort of 312 individuals included symptomatic and asymptomatic individuals. CDR ® plus NACC FTLD was negatively correlated with DEMQOL (r = −0.20, P = .001), as were ZBI and DEMQOL (r = −0.22, P = .0009). There was fair agreement between subject and informant DEMQOL (κ = 0.36, P &lt;.0001). Conclusion Lower HRQoL was associated with higher cognitive/behavior impairment and higher caregiver burden. These findings demonstrate the negative impact of FTLD on individuals and caregivers.

Abstract Genome–wide association studies (GWAS) have revealed a plethora of putative susceptibility genes for Alzheimer’s disease (AD), with the sole exception of APOE gene unequivocally validated in independent study. Considering that the etiology of complex diseases like AD could depend on functional multiple genes interaction network, here we proposed an alternative GWAS analysis strategy based on (i) multivariate methods and on a (ii) telescope approach, in order to guarantee the identification of correlated variables, and reveal their connections at three biological connected levels. Specifically as multivariate methods, we employed two machine learning algorithms and a genetic association test and we considered SNPs, Genes and Pathways features in the analysis of two public GWAS dataset (ADNI-1 and ADNI-2). For each dataset and for each feature we addressed two binary classifications tasks: cases vs. controls and the low vs. high risk of developing AD considering the allelic status of APOEe4. This complex strategy allowed the identification of SNPs, genes and pathways lists statistically robust and meaningful from the biological viewpoint. Among the results, we confirm the involvement of TOMM40 gene in AD and we propose GRM7 as a novel gene significantly associated with AD.

Synucleinopathies-related disorders such as Lewy body dementia (LBD) and isolated/idiopathic REM sleep behavior disorder (iRBD) have been associated with neuroinflammation. In this study, we examined whether the human leukocyte antigen (HLA) locus plays a role in iRBD and LBD. In iRBD, HLA-DRB1*11:01 was the only allele passing FDR correction (OR = 1.57, 95% CI = 1.27-1.93, p = 2.70e-05). We also discovered associations between iRBD and HLA-DRB1 70D (OR = 1.26, 95%CI = 1.12-1.41, p = 8.76e-05), 70Q (OR = 0.81, 95%CI = 0.72-0.91, p = 3.65e-04) and 71R (OR = 1.21, 95%CI = 1.08-1.35, p = 1.35e-03). Position 71 (pomnibus = 0.00102) and 70 (pomnibus = 0.00125) were associated with iRBD. Our results suggest that the HLA locus may have different roles across synucleinopathies.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Abstract Background Much of the genetic etiology of sporadic early onset Alzheimer’s disease and frontotemporal dementia is largely unknown. Genetic investigation using whole exome sequencing (WES) data in the Longitudinal Early Onset Alzheimer’s Disease Study (LEADS) aims to address this gap, with the hypothesis that some individuals with early onset cognitive impairment may carry pathogenic, potentially causative variants in Parkinson’s disease (PD) genes. Methods Whole exome sequencing data for cognitively impaired LEADS participants (N = 301) was processed using the GATK best practices pipeline with Sentieon software; joint‐called VCFs were annotated with Annovar, and the results were filtered to prioritize amino acid code‐altering variants with minor allele frequencies &lt;1% that have not been reported as benign or likely benign in ClinVar. Variants in the acid beta‐glucocerebrosidase (GBA), leucine‐rich repeat kinase 2 (LRRK2), Parkin RBR E3 ubiquitin protein ligase (PRKN), PTEN‐induced putative kinase 1 (PINK1), protein kinase, interferon‐inducible double‐stranded rna‐dependent activator (PRKRA), and Parkinson disease 7, autosomal recessive early‐onset (PARK7) were reviewed. Heterozygous or homozygous carriers of variants meeting these criteria in GBA and LRRK2, as well as homozygous or potentially compound heterozygous variant carriers in the other genes, were reviewed for the presence of PD‐related symptoms documented with the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS) collected at baseline (N = 283). Results There were no variants meeting inclusion criteria for PINK1, PARK7, PRKN, or PRKRA. However, we observed 21 individuals with predicted or reported functional variant(s) in GBA or LRRK2. The mean screening visit age for these carriers was 59 (range 53‐64), and all but two were amyloid positive. While only one case was documented with motor symptoms, several participants had peripheral nervous symptoms such as neuropathy. 17 carriers had amnestic‐type dementia, with similar frequency to non‐carriers. Conclusions While there are a small subset of individuals carrying functional variants in PD genes, they do not appear to substantially influence the phenotype of most cases at baseline. Future planned research efforts include assessing alpha synuclein pathology via alpha synuclein seeding assays, which will help clarify the potential role of mixed genetic etiology and pathology in risk for non‐familial early onset dementia.

Brain imaging genetics intends to uncover associations between genetic markers and neuroimaging quantitative traits. Sparse canonical correlation analysis (SCCA) can discover bi-multivariate associations and select relevant features, and is becoming popular in imaging genetic studies. The L1-norm function is not only convex, but also singular at the origin, which is a necessary condition for sparsity. Thus most SCCA methods impose [Formula: see text]-norm onto the individual feature or the structure level of features to pursuit corresponding sparsity. However, the [Formula: see text]-norm penalty over-penalizes large coefficients and may incurs estimation bias. A number of non-convex penalties are proposed to reduce the estimation bias in regression tasks. But using them in SCCA remains largely unexplored. In this paper, we design a unified non-convex SCCA model, based on seven non-convex functions, for unbiased estimation and stable feature selection simultaneously. We also propose an efficient optimization algorithm. The proposed method obtains both higher correlation coefficients and better canonical loading patterns. Specifically, these SCCA methods with non-convex penalties discover a strong association between the APOE e4 rs429358 SNP and the hippocampus region of the brain. They both are Alzheimer's disease related biomarkers, indicating the potential and power of the non-convex methods in brain imaging genetics.

Abstract Background The ADSP‐FUS is a National Institute on Aging (NIA) initiative focused on identifying genetic risk and protective variants for late‐onset Alzheimer Disease (LOAD). A major concern in AD genetic studies is a lack of racial‐ethnic diversity. The ADSP‐FUS collects and sequences existing both ethnically diverse and unique cohorts with extensive clinical data to expand the utility of new discoveries for individuals from all populations. Additional multi‐ethnic cohorts are presently being recruited (e.g. Amerindian, Korean and Indian). Method The cohorts consist of participants from studies of AD, dementia, and aging‐related conditions. Clinical classification (i.e., AD, dementia, and non‐affected) is implemented using algorithms based on a minimal set of criteria derived from standard measures (e.g., global cognitive screeners, dementia rating scales, etc.) and pertinent clinical history. Data dictionaries are generated for each cohort by clinical staff at Columbia University and University of Miami (UM). In total, ADSP‐FUS intends to sequence over 40,000 individuals. Existing biospecimens were obtained and processed through the National Centralized Repository for Alzheimer’s (NCRAD), the primary site for preparation and allocation of DNA, which is then delivered to the Uniformed Services University of the Health Sciences (USUHS) for whole genome sequencing (WGS). The resulting raw sequence data is delivered to the Genome Center for Alzheimer’s Disease (GCAD) for processing and harmonization followed by quality control analysis at University of Pennsylvania and University of Miami into analysis‐ready genotype data. The final step is delivery of clinical, genotype and sequence data to the NIA Genetics of Alzheimer Disease Data Storage Site (NIAGADS), which serves as the ASDP‐FUS data storage, management and sharing center. Results Over 30,000 samples have been ascertained and are distributed as follows: 7,896 with African ancestry; 9,475 with Hispanic ancestry; 13,531 with non‐Hispanic white ancestry (1,400 EOAD and 3,745 autopsy) and 89 with Amerindian ancestry. Conclusion The ADSP‐FUS is designed to enhance ongoing efforts for the identification of shared and novel genetic risk factors for LOAD among different populations. This project will expand our current knowledge of potential genetic risk and protective variants for LOAD across all populations with the hope of developing new treatments.

The appearance of clinical symptoms in Alzheimer's disease (AD) trails molecular changes in the brain, hindering effective treatment. Reliable early molecular diagnosis has been a challenge- current methods are invasive, time-consuming, and/or expensive. Several studies have shown that AD etiology and progression may be linked to altered DNA methylation (DNAm) in genes associated with AD pathology (e.g.ABCA7). To identify peripheral blood (PB) biomarkers of prodromal AD, we examined DNAm changes in an Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. DNAm was analyzed on Illumina EPIC chips in 649 individuals categorized as healthy, mild cognitive impairment (MCI), or AD. Longitudinal DNA samples (baseline, +1, +2 years) were obtained from all subjects, with additional samples from subjects converting from healthy to MCI, healthy to AD, or MCI to AD. Samples were randomized using a modified incomplete balanced block design, whereby all samples from a subject were on the same chip, with remaining chip space occupied by age- and sex-matched samples from a subject with a different diagnosis. Unused chip space was leveraged for technical reproducibility assessment via replicated DNA samples. A total of 1920 samples were analyzed, including 1719 unique samples and 201 replicates. One sample failed the run and four additional samples failed quality control since ≥1 % of CpG sites had a detection p-value >0.05. Average CpG call rate was 864,640. In paired replicates, the mean within-subject Pearson correlation was 99.42%(SD=1.2%), 95% confidence interval of 97.99%-99.84%. Replicates on the same plate with the same scan date had a mean correlation of 99.63%(SD=0.32%), whereas replicates that didn't share either of these attributes had a mean correlation of 99.25%(SD=1.8%). All correlations reported are based on raw beta-values, and are not a function of normalization. Analysis is currently underway to identify potential DNAm changes associated with disease state and progression. Our work is the largest study thus far to investigate DNAm dynamics that associate with disease progression, serving as potential biomarkers or mechanistic indicators. The integration of this data with the well-characterized ADNI dataset will leverage the rich phenotypic and genotypic information to examine for epigenetic variants that may alter disease course and/or diagnosis.

One goal of the Longitudinal Early-onset Alzheimer's Disease Study (LEADS) is to investigate the genetic etiology of early onset (40-64 years) cognitive impairment. Toward this goal, LEADS participants are screened for known pathogenic variants.LEADS amyloid-positive early-onset Alzheimer's disease (EOAD) or negative early-onset non-AD (EOnonAD) cases were whole exome sequenced (N = 299). Pathogenic variant frequency in APP, PSEN1, PSEN2, GRN, MAPT, and C9ORF72 was assessed for EOAD and EOnonAD. Gene burden testing was performed in cases compared to similar-age cognitively normal controls in the Parkinson's Progression Markers Initiative (PPMI) study.Previously reported pathogenic variants in the six genes were identified in 1.35% of EOAD (3/223) and 6.58% of EOnonAD (5/76). No genes showed enrichment for carriers of rare functional variants in LEADS cases.Results suggest that LEADS is enriched for novel genetic causative variants, as previously reported variants are not observed in most cases.Sequencing identified eight cognitively impaired pathogenic variant carriers. Pathogenic variants were identified in PSEN1, GRN, MAPT, and C9ORF72. Rare variants were not enriched in APP, PSEN1/2, GRN, and MAPT. The Longitudinal Early-onset Alzheimer's Disease Study (LEADS) is a key resource for early-onset Alzheimer's genetic research.

Abstract PURPOSE Few rare pathogenic variants have been identified in the 70+ genetic loci from genome wide association studies of late-onset Alzheimer’s disease (AD), limiting research on underlying mechanisms, risk assessment, and genetic counseling. METHODS Using genome sequencing data from 197 families in The National Institute on Aging Alzheimer’s Disease Family Based Study (AD-FBS), and 214 families in The Estudio Familiar de la Influencia Genética en Alzheimer (EFIGA), we characterized rare coding variants predicted to highly damaging missense or loss of function variants (LoF) within known GWAS loci. RESULTS Eight coding and one LoF variant segregated in 10 (5.1%) AD-FBS families and 16 coding and two LoF variants segregated in 18 (8.4%) EFIGA families. ABCA7 and AKAP9 contained the most damaging variants. In 51 (25.9%) of the AD-FBS and in 26 (12.1%) of the EFIGA families, APOE-ε4 was the only variant segregating with familial AD (fAD). Neither APOE-ε4 nor missense or LoF variants were found in 44.1% of the AD-FBS and 62.1% of the EFIGA families. CONCLUSIONS Although rare variants were found in both family groups, many families had no gene variant segregating within the family, indicating that the genetic basis for AD has yet to be fully defined.

Abstract Background Only a small percentage of early‐onset Alzheimer’s disease (EOAD) participants are known to carry autosomal dominant pathogenic variants in the amyloid beta precursor protein (APP) gene or in presenilin 1 or 2 (PSEN1/2); more research is needed to identify additional causative genetic variants. This study presents results of the initial genetic analyses in the Longitudinal Early Onset Alzheimer’s Disease Study (LEADS) and planned next steps. Methods Whole exome sequencing (WES) is being performed for all cognitively impaired participants, including individuals with EOAD or frontotemporal dementia. Sequencing data is processed using GATK best practices and all variants for APP , PSEN1/2 , progranulin (GRN), and microtubule associated protein tau (MAPT) are reviewed for previously reported pathogenic variants. C9ORF72 is also assessed for pathogenic repeat expansions. WES was analyzed with CANOES and CoNIFER for copy number variants (CNVs). WES data has been reviewed for reported pathogenic variants in other neurodegenerative disease‐associated genes. Gene burden testing is being done for the LEADS cases and age‐matched controls from the Parkinson’s Progression Markers Initiative for rare variants in these genes. Results To date, WES has been generated for 301 cases, and GWAS for 384 participants (290 cases, 89 controls). Reported pathogenic variants or repeat expansions in C9ORF72 , PSEN1 , GRN , and MAPT were identified in 2% of cases for the six screened genes. No CNVs were detected in APP, PSEN1/2 , GRN , or MAPT . Review also identified individuals with pathogenic variants or CNVs in genes linked with diseases including Parkinson’s disease and Niemann‐Pick disease, including reported or predicted pathogenic variants in GBA , LRRK2 , and SMPD1 . Surprisingly, results do not show enrichment of functional TREM2 variants compared to population frequency. Conclusions Initial results indicate that LEADS is strongly enriched for novel genetic risk and/or causative factors, as only 2% have a reported pathogenic variant or repeat expansion in APP , PSEN1/2 , GRN , MAPT , or C9ORF72 . Review of reported pathogenic variants in other neurodegenerative disease‐associated genes indicates that while a small portion of disease etiology may be explained by these variants, more research is needed to identify additional causative and risk factors contributing to EOAD.

Abstract Background Asian Americans and Canadians (ASACs) are the fastest growing minority group in the U.S. and Canada. However, ASACs are under‐sampled in Alzheimer’s disease (AD) research. To address the need of culturally appropriate clinical protocols and community‐based recruitment approaches for ASACs, the Asian Cohort for Alzheimer’s Disease (ACAD), the first large dementia genetics cohort currently focuses on Chinese, Korean, and Vietnamese, launched in 2021 to examine genetic and non‐genetic risk factors for AD among ASACs. Our clinical and community‐based participatory research (CPBR) scientists have a long collaborative history and diverse cultural and scientific training backgrounds: both are critical in leading AD and CBPR research. Method The ACAD pilot study has 7 recruiting sites (5 US and 2 Canadian), a coordinating site, and an analysis site. ACAD piloted a comprehensive study protocol including community outreach and recruitment strategies, the data collection packet (DCP), pre‐screening and sample collection procedures, and a centralized data management system in English, Chinese (Mandarin and Cantonese), Korean, and Vietnamese. To ensure the protocol consistency, ACAD implemented a training curriculum for the administration of the DCP and for culturally appropriate approaches to recruitment in collaboration with community partners, clinics, and nursing homes that serve Asian communities. Result As of December 2022, ACAD’s pilot study has consented 606 participants, 527 participants have complete DCP data submitted to REDCap (448 Chinese, 54 Korean, and 25 Vietnamese), and more than 1,500 people have expressed interests in ACAD. The majority 66.2%)women. The age range of the sample is 60‐93 years. 47.3% have college or graduate level education. 451 participants provided a saliva (274) or a blood (177) sample. Feedback in pilot indicates a need to adapt the Early Life Enrichment inventory further to apply to wartime deprivation conditions for this population, as well as more cultural tailored neuropsychological tests. Conclusion ACAD has learned valuable experience in interactions with ASACs and shown the feasibility of recruiting ASACs in clinical research. With an expansion plan and in collaboration with other AD research focuses on minority, insights from ACAD may identify potential novel, population‐specific therapeutic pathways for AD.

Abstract Background The National Centralized Repository for Alzheimer’s Disease and Related Dementias (NCRAD) was established in 1990 at Indiana University with the mission to support research focused on the etiology, early detection, and development of therapeutics for ADRD. NCRAD has been funded by the National Institute on Aging (NIA) since 1990 and is an integral international resource for clinical information and biological materials. As ADRD research has advanced, NCRAD and the NIA have worked together to expand the number and type of biological specimens available to the research community. NCRAD currently houses DNA, RNA, CSF, plasma, serum, stool, brain tissue, LCLs, PBMCs, fibroblasts and iPSCs from individuals with ADRD and healthy controls. NCRAD and the NIA have invested in technologies to standardize specimen processing, enhance specimen quality, and increase specimen distribution to researchers. Paired with this, all data generated from NCRAD specimens must be made available to other researchers through approved data warehouses. Method DNA extractions are performed with standardized Chemagen chemistries on the Chemagic360 platform. Genotyping is performed with SNP Type™ assays on Juno™ and Biomark™ platforms. Automated specimen storage is executed by a Hamilton® BiOS M. Biofluid handling and sub‐aliquoting are carried out on Janus®, Biomek, and STARlet liquid‐handling platforms. Result DNA extraction quality, consistency, and throughput increased after adopting the Chemagic360 platform. Custom SNP fingerprint genotyping of DNA specimens upon intake and distribution ensured specimen identity was not lost due to collection site errors or specimen swaps during processing. Additionally, APOE and LRRK2 G2019S genotyping has provided researchers banking specimens with valuable ADRD‐related genetic information. Automated, high‐density storage has permitted the banking of more specimens, allowing for onboarding of additional studies. Storage automation reduced the handling of specimens that could introduce warming events, contributing to confounding preanalytical variables. Conclusion Recent investments in new technologies have allowed NCRAD to accelerate ADRD research by supporting a broader range of biological specimens, increasing the number of specimens banked, limiting the effects of preanalytical variables, and shortening the time to distribute specimens. The broad availability of NCRAD specimens and the data generated from these specimens, has resulted in over 700 peer‐reviewed publications.

Abstract Background The National Centralized Repository for Alzheimer’s Disease and Related Dementias (NCRAD) has established a centralized repository for human induced pluripotent stem cells (iPSCs) and fibroblasts in partnership with the National Institute on Aging (NIA). This is a critical resource for the research community, which can facilitate disease modeling, functional genetic studies, and drug development. However, the utility of this resource is still limited in terms of racial and ethnic diversity, which has the potential to bias neurodegenerative research and drug development unless steps are taken to create and share a more diverse array of cell lines. Method At NCRAD, banked iPSCs are subjected to quality control including short‐read whole genome sequencing (WGS). 78 samples have been submitted for sequencing; of these, data for 51 have been returned and analyzed, including multiple isogenic lines from three donors. WGS data was aligned, and quality control performed using Sentieon software, following GATK best practices. Data was combined with sequencing data from 2,548 1000 Genomes participants and pruned in PLINK. R package SNPRelate was used to generate a kinship matrix and perform principal component analysis (PCA). Clustering analysis was performed utilizing K‐means clustering to group samples into 5 clusters. PCs 1‐3 were graphed, color‐coded by cluster, and final ancestry calls reviewed for clustering with reference groups. Result The NCRAD 51 iPSC lines with analyzed WGS data were sourced from 28 neurodegenerative cases and 12 controls. In this data set, 83% of samples (89% of cases, 67% of controls) have European ancestry. The cohort also includes one case and one control line of East Asian ancestry, as well as 2 cases and 3 controls showing admixture of European/American ancestry. 17 individuals did not have reported race/ethnicity, while 2 controls showed genetic admixture though reported as White non‐Hispanic, and the remaining individuals’ genetic ancestry matched reported race/ethnicity. Conclusion Centralized banking of iPSCs from individuals with neurodegenerative diseases is creating a key resource to advance research; however, to date the diversity of these samples is limited. We urge researchers to develop and share more diverse cell lines, to promote diversity and equity in neurodegenerative research.

Abstract Background The ADSP‐FUS is a National Institute on Aging (NIA) initiative focused on identifying genetic risk and protective variants for Alzheimer Disease (AD) by expanding the ADSP beyond non‐Hispanic Whites of European Ancestry (NHW‐EA) populations. Given the lack of diversity in the ADSP, the ADSP‐FUS was designed to whole genome sequence (WGS) existing ethnically diverse and unique cohorts. The upcoming phase ADSP‐ FUS 2.0: The Diverse Population Initiative, focuses on inclusion of Hispanic/Latino (HL), non‐Hispanic Black with African Ancestry (NHB‐AA), and Asian populations. Methods ADSP‐FUS cohorts consist of studies of AD, dementia, and age‐related conditions. Clinical classifications are assigned based on standard criteria from clinical measures and history, as well as additional neuropathologic data. In addition to production of WGS, genome‐wide array and APOE genotyping is acquired or performed for all ADSP‐FUS samples. Results The ADSP‐FUS currently consists of 38 cohorts comprised of ∼40,000 individuals, with plan to sequence &gt;100,000 individuals from diverse ancestries. Genotyping, sequencing, and clinical adjudication has been performed on 23,428 participants (cases N = 6,961, median age = 73; controls N = 13,007, median age = 72; ADRD N = 3,460, median age = 77. More participants are female (62.3%) than male and are evenly distributed across cases (61.0%), controls (63.1%), and ADRD (61.8%). As expected, the most prevalent APOE genotype is APOE 3/3 (% by cases/controls for 2/2 = 0.2,0.4; 2/3 = 4.3, 8.2; 2/4 = 2.2, 1.8; 3/3 = 43.8, 64.4; 3/4 = 39.5, 23.0; 4/4 = 10.1, 2.2). These proportions vary greatly between ethnicities, with the highest for APOE 4/4 observed in Asian participants (8.8%) and the lowest in Hispanic participants (2.5%), for example. Mean Braak stage for AD cases is higher (5.1+1.2) than controls (2.6+1.3) and ADRD participants (3.5+1.6). Conclusion The results provide an overview of features of ADSP‐FUS cohorts. As the ADSP‐FUS expands in size and diversity, this genomic resource, available via NIAGADS, will be integrated with ADSP programs focused on phenotype harmonization, association analyses, functional genomics, and machine learning. In concert with these programs, the ADSP‐FUS will accelerate the identification and understanding of potential genetic risk and protective variants for AD across all populations with the target of developing new treatments that are globally effective.

Abstract Brain genetics is an active research area. The degree to which genetic variants impact variations in brain structure and function remains largely unknown. We examined the heritability of regional brain volumes (p ~ 100) captured by single-nucleotide polymorphisms (SNPs) in UK Biobank (n ~ 9000). We found that regional brain volumes are highly heritable in this study population. We observed omni-genic impact across the genome as well as enrichment of SNPs in active chromatin regions. Principal components derived from regional volume data are also highly heritable, but the amount of variance in brain volume explained by the component did not seem to be related to its heritability. Heritability estimates vary substantially across large-scale functional networks and brain regions. The variation in heritability across regions was not related to measurement reliability. Heritability estimates exhibit a symmetric pattern across left and right hemispheres and are consistent in females and males. Our main findings in UK Biobank are consistent with those in Alzheimers Disease Neuroimaging Initiative ( n ~ 1100), Philadelphia Neurodevelopmental Cohort ( n ~ 600), and Pediatric Imaging, Neurocognition, and Genetics ( n ~ 500) datasets, with more stable estimates in UK Biobank.

Abstract Background Asian Americans and Canadians (ASACs) are the fastest growing minority group in the US and Canada. ASACs are under‐sampled in Alzheimer’s disease (AD) research. Culturally appropriate, community‐based approaches to recruit these understudied communities are urgently needed, and in 2021 the Asian Cohort for Alzheimer’s Disease (ACAD) began recruitment to the first large dementia genetics cohort to examine genetic and non‐genetic risk factors for AD among ASACs. Our clinical and community‐based participatory research (CPBR) scientists have a long collaborative history and specific experience in leading AD and CBPR research. Method The ACAD pilot study has 8 recruiting sites (6 US and 2 Canadian), a coordinating site, and an analysis site. ACAD piloted a data collection packet (DCP) and pre‐screening/sample collection procedures. The Outreach workgroup translated the forms and an outreach campaign into Chinese (Mandarin and Cantonese), Vietnamese and Korean. Data Management created a central RedCap database. The Training workgroup developed a curriculum for the administration of the DCP and for culturally appropriate approaches to recruitment. We recruited in collaboration with community partners, clinics, and nursing homes that serve Asian communities. Result ACAD’s pilot study has consented 216 participants (142 Chinese, 20 Vietnamese and 54 Korean), and 126 (58%) have completed the DCP. The majority the consent (64.3%) were given by women. The age range of the sample is 60‐93 years. 60.3% have college or graduate level education. 101 of the 126 participants provided saliva (51) or blood (50) biosamples. Data entry is complete, with Consensus Diagnoses fully reviewed on 18 participants. Among 34 diagnosed participants, there are 19 healthy controls, 11 Subjective Cognitive Complaints, 3 Mild Cognitive Impairments, and 1 Probable or Possible AD case. Conclusion Lessons learned during the pilot phase of ACAD will provide guidance for future studies to explore risk factors for AD and related dementias. In collaboration with ongoing consortium efforts in Alzheimer’s Disease Genetics Consortium (ADGC), insights from ACAD may identify potential novel, population‐specific therapeutic pathways for AD. Our long‐term goal will be to expand ACAD to have a larger sample size and include other Asian American subgroups .

Abstract Background The ADSP‐FUS is a National Institute on Aging (NIA) initiative focused on identifying genetic risk and protective variants for Alzheimer Disease (AD) by expanding the ADSP Discovery and Discovery Extension cohorts beyond non‐Hispanic Whites of European Ancestry (NHW‐EA). Given the lack of diversity in the ADSP, the ADSP‐FUS was designed to sequence existing ethnically diverse and unique cohorts. The upcoming phase for ADSP‐FUS, ADSP‐ FUS 2.0: The Diverse Population Initiative, focuses on Hispanic/Latino (HL), non‐Hispanic Black with African Ancestry (NHB‐AA), and Asian populations (e.g., the Asian cohort for Alzheimer’s disease). The ADSP‐FUS enables the utility of new discoveries for individuals from all populations. Method ADSP‐FUS cohorts consist of studies of AD, dementia, and age‐related conditions. Clinical classifications (AD, dementia, and cognitively intact) are assigned based on standard criteria and derived from clinical measures and history. Data dictionaries are curated for each cohort by the FUS clinical staff. The ADSP‐FUS initiatives intend to sequence over 100,000 individuals from diverse ancestries. Biospecimens are processed and DNA is prepared and allocated for whole genome sequencing (WGS) at designated NIA sequencing centers. All raw sequence data is transferred to the Genome Center for Alzheimer’s Disease (GCAD) for processing and harmonization following QC analysis at the University of Pennsylvania and University of Miami, resulting in analysis‐ready genotype and sequence data. All clinical, genotype and sequence data are housed at the NIA Genetics of Alzheimer Disease Data Storage Site (NIAGADS), which stores, manages, and distributes ASDP‐FUS data to AD researchers. Results Over 50,152 samples have been ascertained with ancestry groupings as follows: 10,166 NHB‐AA; 10,531 HL; 22,002 NHW‐EA (including 1,400 EOAD and 3,745 autopsy); 89 Amerindian; and 7,364 Asian (Korean and Indian) individuals. Currently, we have sequenced up to a total of 31,990 individuals. Conclusion The ADSP‐FUS continues to identify shared and novel genetic risk factors for AD among diverse populations. This genomic resource is crucial to expanding our knowledge of potential genetic risk and protective variants for AD across all populations with the hope of developing new treatments for everyone.

An important step in determining patients with possible dementia based on cognitive scores, is to estimate the distribution of scores in cognitively normal subjects; extreme scores relative to this control distribution may indicate dementia. To date, approaches have focused on determining the distribution of z-scores for a set of normal controls, and then compared the z-scores of new subjects with that distribution. The z-score approach was extended by Shirk et al. [1] to consider linear correction for age, sex, and education. Here this approach is further extended to consider non-linear relationships between predictors and cognitive score, as well as accounting for differing standard deviation of the cognitive scores with age. The same NACC database of normal controls was used as in [1] (data were used from 29 ADCs and considered UDS visits between September 2015 and May 2017). Nonlinear shape-constrained generalized additive models (SCAMs) [2] were fit to the data separately for each cognitive outcome. SCAM fits were generated with nonlinear corrections for age and education (constrained to be monotonic), and an additive term for sex. Another SCAM was then fitted to estimate change in the standard deviation of residuals with respect to age. A lookup table was generated based on these two SCAM fits. For each value of age, education level, and sex, an adjusted z-score (n-score) was generated, using the fitted mean and standard deviation for that age, education level, and sex. The figures display an example SCAM model fit for TRAIL B. There was a clear non-linear relationship between age and TRAIL B (Figure 1). The estimated relationship between education level and TRAIL B was linear (Figure 2). Increasing standard deviation was seen with age (Figure 3). Consistent improvements were seen across different neurocognitive outcomes by allowing for such non-linear adjustment.

May 9, 2019April 9, 2019Free AccessCharacteristics and Progress on 369 Subjects in the Longitudinal Evaluation Familial Frontotemporal Dementia Subjects (LEFFTDS) Protocol (P5.1-009)Leah Forsberg, Danielle Brushaber, Giovanni Coppola, Bradford Dickerson, Jamie Fong, Ralitza Gavrilova, Nupur Ghoshal, … Show All … , Jill Goldman, Neill Graff-Radford, Murray Grossman, Hilary Heuer, Ging-Yuek Hsiung, Edward Huey, David Irwin, Kejal Kantarci, Anna Karydas, David Knopman, John Kornak, Walter Kremers, Walter Kremers, Maria Lapid, Diane Lucente, Ian R.A. Mackenzie, Rosa Rademakers, Eliana Marisa Ramos, Joanne Taylor, Arthur Toga, Zbigniew Wszolek, Bradley Boeve, Adam Boxer, and Howard Rosen Show FewerAuthors Info & AffiliationsApril 9, 2019 issue92 (15_supplement) Letters to the Editor

Parkinsonism, motor neuron disease (MND), apraxia, etc. often occur in frontotemporal lobar degeneration (FTLD) syndromes. Previous instruments developed to capture the key clinical and salient aspects of patients with dementia (standard CDR and FTLD-CDR) did not include these relevant motor features. Additionally these instruments fail to capture sensitive information from a variety of sources like the individual him/herself, the informant and data from neuropsychological testing. The 12-item Multidomain Impairment Rating (MIR) scale was developed to encompass all key manifestations of the FTLD spectrum disorders for use in natural history studies and clinical trials. The MIR encompasses elements of the FTLD-CDR plus a visuospatial domain as well as domains for parkinsonism, MND and other non-cognitive/non-behavioral aspects of FTLD. The ratings of 0, 0.5, 1, 2 or 3 for each domain are based on three data sources – the subject, informant, and neuropsychological testing. Consensus summary ratings include the MIR Neuropsychology score, the global (MIR), and summed score (MIR SS). A reliability exercise was completed using baseline clinical and neuropsychological data in subjects participating in the ARTFL/LEFFTDS Consortium. Twenty subjects each from 2 sites were rated (blinded to the other site's ratings), and the data of the 40 subjects were analyzed. The cases were selected a priori to represent clinically normal (CN), MCI, and more severe degrees of cognitive, behavioral and motor impairment (e.g., bvFTD, PPA, FTD with parkinsonism, and FTD with MND). Weighted kappa statistic measured agreement. The analyses showed very good agreement for the global MIR ratings [κ=0.86 (95% CI 0.74-0.97)], the MIR SS ratings [κ=0.82 (95% CI 0.72-0.92)], and complete concordance on the MIR Neuropsychology ratings [κ=1.0]. These findings suggest good reliability for the global MIR, MIR SS and MIR Neuropsychology ratings. The MIR may provide added utility to the FTLD-CDR, and could be used in natural history studies and clinical trials to more optimally capture the spectrum of features in FTLD.

Brain tissue is an invaluable resource for researchers investigating the pathological etiology and molecular basis of Alzheimer's disease (AD), but this resource is scarce and difficult to obtain compared to other types of biospecimens. The National Centralized Repository for Alzheimer's Disease and Related Dementias (NCRAD) stores and distributes brain tissue to researchers to address this research gap.NCRAD stores fresh frozen, formalin fixed brain tissue collected from participants of the NCRAD Family Study, as well as the NIA Genetics Initiative/NIA-LOAD Family Based Study (FBS). Approved researchers can obtain tissue from NCRAD, and can also obtain access to genetic data for select subjects from the National Institute on Aging Genetics of Alzheimer's Disease Data Storage Site (NIAGADS).The NCRAD Family Study brain tissue collection includes specimens from 249 subjects from 180 families. 65% of participants were female, the average age of death was 81.4 years, with an average age of dementia onset of 70.18 years for those with reported data. 199 subjects had confirmed or probable AD. 14 subjects had known pathogenic AD mutations in PS1, APP, MAPT, or PGRN. Currently, 186 subjects have been sent for RNA-sequencing, 123 have GWAS available through NIAGADS, and 71 have sequencing available through NIAGADS. NCRAD has sent DNA from an additional 125 subjects for GWAS and 170 for whole exome sequencing, which will be made available through NIAGADS. The NIA-LOAD FBS Study includes specimens from 87 subjects from 66 families. 57% of participants were female, the average age of death was 82.9 years, with an average age of dementia onset of 73.5 years. 81 subjects had definite or probable AD. 84 subjects have GWAS data, and 66 subjects have sequencing available through NIAGADS. Subjects from both studies have autopsy data available, including Braak stage, CERAD category, and Reagan category.The brain tissue and clinical information from both these studies are valuable resources for the AD research community, particularly as they are augmented by a growing collection of genetic data. NCRAD strongly encourages researchers to leverage these valuable resources to advance the state of knowledge regarding AD research and therapeutic development.

April 29, 2014April 8, 2014Free AccessAge-Specific Incidence Rate For Dementia And Alzheimer’s Disease In NIA-LOAD/NCRAD and EFIGA Families (P2.148)Badri Vardarajan, Kelley Faber, Thomas Bird, David Bennett, Roger Rosenberg, Bradley Boeve, Neill Graff-Radford, … Show All … , Alison Goate, Martin Farlow, Robert Sweet, Rafeal Lantigua, Martin Medrano, Ruth Ottman, Daniel Schaid, Tatiana Foroud, and Richard Mayeux Show FewerAuthors Info & AffiliationsApril 8, 2014 issue82 (10_supplement)https://doi.org/10.1212/WNL.82.10_supplement.P2.148 Letters to the Editor

The Alzheimer’s Disease Sequencing Project (ADSP) was established in 2012 as a Presidential Initiative to fight Alzheimer’s Disease (AD). Developed jointly by National Institute on Aging (NIA) and the National Human Genome Research Institute (NHGRI), the aims are to: 1) identify protective genomic variants in older adults at risk for AD, 2) identify new risk variants among AD cases, and 3) examine these factors in multi-ethnic populations to identify therapeutic targets for disease prevention. The ADSP Data Flow Work Group (DFWG) and the NIA Genetics of Alzheimer’s Disease Data Storage Site (NIAGADS) supports data production, sharing and management for the ADSP, and facilitates data access to the community. Samples are contributed by the AD Genetics Consortium (ADGC) and Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. Sample plating and shipping is coordinated by the National Cell Repository for AD (NCRAD). Whole-exome (WES) and whole-genome (WGS) sequencing data were generated by three NHGRI funded Sequencing Centers [and were QC’ed by the ADSP]. The DFWG maintains the ADSP web site, providing study design, cohort information, news releases, and application instructions for ADSP access. The ADSP Data Portal is a collaboration with the Database of Genotypes and Phenotypes (dbGaP), Sequence Read Archive, and NIAGADS. The portal allows users to explore the ADSP project data archived at dbGaP with NIH iTrust user authentication. Approved investigators identify data and download files using a customizable filtering system and check-out cart function. The ADSP has completed WES of 10,939 unrelated cases and controls and WGS of 578 members from 111 families. Accompanying each sample are phenotypes that were harmonized according to ADSP protocols. As of February 2016, an additional 427 individuals are being sequenced to extend the WGS study and additional cases and controls are being selected for the next phase of the WES study. The DFWG provides support to all ADSP Work Groups for data related issues, coordinates with dbGaP for data transfers, and reviews, posts, and notifies members of new results generated by other Work Groups. Find additional information at the ADSP website (www.niagads.org/adsp) or at dbGaP (study ID: phs000572).

Gene expression is a fundamental mechanism in susceptibility to and manifestation of complex disease. Prior studies suggest that abnormal gene expression patterns may contribute to the onset and progression of late-onset Alzheimer’s disease (LOAD). We performed genome-wide transcriptome meta-analysis and whole-brain cortical thickness analysis in LOAD using blood-based microarray gene expression profiles. 1,440 non-Hispanic Caucasian participants (661 from the ADNI as a discovery sample and 674 and 105 from the AddNeuroMed and Mayo cohorts as replication samples) were included. Raw microarray expression values from peripheral blood samples (PaxGene RNA tubes) were pre-processed followed by standard quality control (QC) procedures on samples and probe sets. Statistical analysis of microarray data was performed using a linear regression model to evaluate differences in gene expression between LOAD and cognitively normal controls (CN). Meta-analysis was performed using a fixed-effect, inverse-variance-weighted model. Significant associations were determined using FDR adjustment and Bonferroni correction for multiple testing. Of the 21,150 probe sets in ADNI represented on the array after QC, 18 probe sets (16 genes) were significantly up-regulated and 8 probe sets (7 genes) were significantly down-regulated in LOAD after controlling for multiple testing (FDR-corrected p<0.05) (Fig.1). Of the 23 differentially expressed genes, 6 genes were replicated in the meta-analysis (Table 1). The most significantly altered gene was CREB5 (up-regulated). Whole-brain cortical thickness analysis identified and replicated brain regions, especially entorhinal cortex, significantly associated with expression of CREB5 (Fig. 2). Individuals with lower expression showed greater cortical thickness (corrected p<0.05). cis-eQTL mapping analyses of CREB5 detected 5 significant associations with p < 5x10-8 (Fig. 3). cis-eQTL of rs56388170 (most significant) was replicated (Fig. 3) and was significantly associated with global cortical Aβ load (measured by [18F]Florbetapir PET) and CSF Aβ1-42 (Fig. 4). RNA from peripheral blood indicated a differential gene expression pattern between AD patients and controls. Genes identified in this study have been implicated in biological processes that may be relevant to AD. CREB is a key component of nervous system development, cell survival, plasticity and learning and memory (Sakamoto et al. 2011). Volcano plot of transcriptome analysis results in the ADNI cohort (discovery sample). Red circles represent significantly differentially expressed genes in AD compared to CN. Association of CREB5 gene expression levels with brain structure using whole brain surface-based analysis using two independent cohorts: (a) ADNI (discovery sample) and (b) AddNeuroMed (replication sample). Whole-brain cortical thickness analysis demonstrated the identification and replication of brain regions, especially entorhinal cortex, significantly associated with expression of CREB5. Statistical maps computed using SurfStat were thresholded using random field theory (RFT) as a multiple testing correction at p-corrected < 0.05. Results of cis-eQTL mapping analysis of CREB5 using two independent cohorts: (a) ADNI (discovery sample) and (b) AddNeuroMed (replication sample). cis-eQTL mapping analyses of CREB5 detected 5 significant associations with p < 5x10−8 in the ADNI. The most significant cis-eQTL SNP (rs56388170) in the ADNI was replicated in the AddNeroMed. All SNPs are plotted based on their –log10 p-values, NCBI build 37 genomic position, and recombination rates calculated from the 1000 Genomes Project reference data. Association of the most significant cis-eQTL SNP (rs56388170) of CREB5 gene expression levels with (a) log transformed global cortical Aβ levels measured by [18F]Florbetapir PET and (b) CSF Aßi-42 in the ADNI. rs56388170 was significantly associated with global cortical Aβ load and CSF Aβ1-42.

Human brain function depends on the precise regulation of gene expression. Transcriptome profiling has become a major focus of neurodegenerative disease research. Prior studies suggest that abnormal gene expression patterns may contribute to the onset and progression of late-onset Alzheimer’s disease (LOAD). We performed transcriptome meta-analysis and neuroimaging analyses of 22 LOAD susceptibility genes identified from a recent large-scale GWAS (Lambert et al. 2013) using gene expression profiles from three independent cohorts. 1,440 non-Hispanic Caucasian participants (661 from the ADNI as a discovery sample and 674 and 105 from the AddNeuroMed and Mayo cohorts as replication samples) were included. Raw microarray expression values from peripheral blood samples (PaxGene RNA tubes) were pre-processed followed by standard quality control (QC) procedures on samples and probe sets. Statistical analysis of microarray data was performed using a linear regression model to evaluate differences in gene expression between LOAD and cognitively normal controls (CN). Meta-analysis was performed using a fixed-effect, inverse-variance-weighted model. Significant associations were determined using Bonferroni correction for multiple testing. In the ADNI discovery set, of the 19 genes passing QC, 2 genes (ABCA7 and CD33) were significantly up-regulated in LOAD blood samples (p<0.05) and replicated after controlling for multiple testing (Table 1). Whole-brain cortical thickness analysis identified and replicated brain regions, especially entorhinal cortex, as significantly associated with peripheral blood expression of ABCA7 and CD33 (Fig. 1). Individuals with lower expression showed greater cortical thickness (corrected p<0.05). Higher ABCA7 expression was also associated with decreased metabolic activity ([18F] FDG PET) in Hippocampus (p=0.033; Fig. 2). cis-eQTL mapping analyses of ABCA7 detected 63 significant associations with p < 2.5x10-12 (Fig. 3). The most significant cis-eQTL SNP (rs5638817) was replicated (Fig. 2) and was significantly associated with increased metabolic activity ([18F] FDG PET) in Hippocampus (p<0.05) (Fig. 4). Association of ABCA7 and CD33 gene expression levels with brain structure using whole brain surface-based analysis using two independent cohorts: (a) ADNI (discovery sample) and (b) AddNeuroMed (replication sample). Whole-brain cortical thickness analysis demonstrated the identification and replication of brain regions, especially entorhinal cortex, significantly associated with expression of ABCA7 and CD33. Statistical maps computed using SurfStat were thresholded using random field theory (RFT) as a multiple testing correction at p-corrected < 0.05. Association of ABCA7 gene expression levels with [18F] FDG PET SUVR in bilateral hippocampus. ABCA7 expression is significantly associated with decreased metabolic activity in Hippocampus (p=0.033). Results of cis-eQTL mapping analysis of ABCA7 using two independent cohorts: (a) ADNI (discovery sample) and (b) AddNeuroMed (replication sample). cis-eQTL mapping analyses of ABCA7 detected 63 significant associations with p < 2.5×10-12 in the ADNI. The most significant cis-eQTL SNP (rs3087680) in the ADNI was replicated in the AddNeuroMed. All SNPs are plotted based on their − log10 p-values, NCBI build 37 genomic position, and recombination rates calculated from the 1000 Genomes Project reference data. Association of the most significant cis-eQTL SNP (rs3087680) of ABCA7 gene expression levels with [18F] FDG PET SUVR in bilateral hippocampus. rs3087680 (ABCA7) is significantly associated with increased metabolic activity in Hippocampus (p<0.05). This is the first study to show that LOAD susceptibility gene ABCA7 expression in blood is associated with decreased cortical thickness and reduced metabolic activity in AD-related brain regions and CD33 expression is associated with decreased cortical thickness.

Genetics studies have revealed a genetic contribution to susceptibility for common or sporadic forms of neurodegenerative disease such as Alzheimer disease (AD), frontotemporal dementia (FTD), and progressive supra-nuclear palsy (PSP, a syndrome characterized by oculomotor and gait abnormalities). In AD, early genetic mapping approaches have identified rare variants in genes such as APP, PSEN1, and PSEN2that cause familial, early-onset forms.1 APOE was also pinpointed as a late-onset AD susceptibility gene.2 Genome-wide association studies3–5 (GWAS) targeted toward common variants in primarily European populations have identified many variants associated with AD, most clearly near APOE but also consistently near ABCA7, BIN1, CLU, CR1, PICALM, SORL1, and other genes. Next-generation sequencing approaches have also found rare variants with strong effect in the MAPT and TREM2 genes.6,7 In FTD, the most frequently observed mutations in familial cases occur in C9ORF72, GRN, MAPT, TARDBP, and other genes.8 In sporadic cases, a haplotype variant on the long arm of chromosome 17 has been repeatedly associated with PSP.9–11 In addition, GWAS have been performed for sporadic cases of FTD, identifying associated single-nucleotide polymorphisms (SNPs) near TMEM106B12 and BTNL2/HLA-DRA/HLA-DRB5 and RAB38/CTSC,13 as well as for PSP, identifying associated SNPs near MAPT, EIF2AK3, STX6, and MOBP.11 Despite progress in understanding the genetics of neurodegenerative diseases, known genetic risk factors cannot explain a large portion of the heritability of these diseases. For example, in AD, all common variants (including known and unknown risk variants) have been predicted to account for less than 25% of disease variance,14 and known high-penetrance rare variants account for few cases, collectively totaling only a fraction of the estimated 58% to 79% heritability of AD.15 Some of this missing heritability may be due to a blind spot in conventional genetic studies to date. A moderately rare variant with moderate effect size would be too uncommon to be tagged by a standard genotyping array and have too small of an effect to be detected by linkage or genome sequencing in practical sample sizes. The exome array bridges this gap by genotyping at low cost more than 200 000 coding variants identified through sequencing studies (Figure 1). This approach has been applied to phenotypes such as insulin homeostasis,16 bronchopulmonary dysplasia,17 and heart disease.18,19 For AD, Chung et al20 recently reported an exome array study in Korean participants that found an association with APOE, APOC1, and TOMM40 variants (near the APOE locus) but did not identify novel genetic variants. Herein, we report findings from the application of the exome array to the multiancestral Genetic Investigation in Frontotemporal Dementia and Alzheimer’s Disease (GIFT) Study cohort to determine the contribution of low-frequency coding variants to susceptibility to sporadic AD, PSP, and FTD. Figure 1 Comparison of the Exome Array and Related Genotyping and Sequencing Technologies

Human brain function depends on the precise regulation of gene expression. Transcriptome profiling has become a major focus of neurodegenerative disease research. Prior studies suggest that abnormal gene expression patterns may contribute to the onset and progression of late-onset Alzheimer’s disease (LOAD). We performed transcriptome meta-analysis and neuroimaging analyses of 22 LOAD susceptibility genes identified from a recent large-scale GWAS (Lambert et al. 2013) using gene expression profiles from three independent cohorts. 1,440 non-Hispanic Caucasian participants (661 from the ADNI as a discovery sample and 674 and 105 from the AddNeuroMed and Mayo cohorts as replication samples) were included. Raw microarray expression values from peripheral blood samples (PaxGene RNA tubes) were pre-processed followed by standard quality control (QC) procedures on samples and probe sets. Statistical analysis of microarray data was performed using a linear regression model to evaluate differences in gene expression between LOAD and cognitively normal controls (CN). Meta-analysis was performed using a fixed-effect, inverse-variance-weighted model. Significant associations were determined using Bonferroni correction for multiple testing. In the ADNI discovery set, of the 19 genes passing QC, 2 genes (ABCA7 and CD33) were significantly up-regulated in LOAD blood samples (p<0.05) and replicated after controlling for multiple testing (Table 1). Whole-brain cortical thickness analysis identified and replicated brain regions, especially entorhinal cortex, as significantly associated with peripheral blood expression of ABCA7 and CD33 (Fig. 1). Individuals with lower expression showed greater cortical thickness (corrected p<0.05). Higher ABCA7 expression was also associated with decreased metabolic activity ([18F] FDG PET) in Hippocampus (p=0.033; Fig. 2). cis-eQTL mapping analyses of ABCA7 detected 63 significant associations with p < 2.5x10-12 (Fig. 3). The most significant cis-eQTL SNP (rs5638817) was replicated (Fig. 2) and was significantly associated with increased metabolic activity ([18F] FDG PET) in Hippocampus (p<0.05) (Fig. 4). This is the first study to show that LOAD susceptibility gene ABCA7 expression in blood is associated with decreased cortical thickness and reduced metabolic activity in AD-related brain regions and CD33 expression is associated with decreased cortical thickness. Association of ABCA7 and CD33 gene expression levels with brain structure using whole brain surface-based analysis using two independent cohorts: (a) ADNI (discovery sample) and (b) AddNeuroMed (replication sample). Whole-brain cortical thickness analysis demonstrated the identification and replication of brain regions, especially entorhinal cortex, significantly associated with expression of ABCA7 and CD33. Statistical maps computed using SurfStat were thresholded using random field theory (RFT) as a multiple testing correction at p- corrected < 0.05. Association of ABCA7 gene expression levels with [18F] FDG PET SUVR in bilateral hippocampus. ABCA7 expression is significantly associated with decreased metabolic activity in Hippocampus (p=0.033). Results of cis-eQTL mapping analysis of ABCA7 using two independent cohorts: (a) ADNI (discovery sample) and (b) AddNeuroMed (replication sample). cis-eQTL mapping analyses of ABCA7 detected 63 significant associations with p < 2.5x10−12 in the ADNI. The most significant cis-eQTL SNP (rs3087680) in the ADNI was replicated in the AddNeuroMed. All SNPs are plotted based on their -log-m p-values, NCBI build 37 genomic position, and recombination rates calculated from the 1000 Genomes Project reference data. Association of the most significant cis-eQTL SNP (rs3087680) of ABCA7 gene expression levels with [18F] FDG PET SUVR in bilateral hippocampus. rs3087680 (ABCA7) is significantly associated with increased metabolic activity in Hippocampus (p<0.05).

Gene expression is a fundamental mechanism in susceptibility to and manifestation of complex disease. Prior studies suggest that abnormal gene expression patterns may contribute to the onset and progression of late-onset Alzheimer’s disease (LOAD). We performed genome-wide transcriptome meta-analysis and whole-brain cortical thickness analysis in LOAD using blood-based microarray gene expression profiles. 1,440 non-Hispanic Caucasian participants (661 from the ADNI as a discovery sample and 674 and 105 from the AddNeuroMed and Mayo cohorts as replication samples) were included. Raw microarray expression values from peripheral blood samples (PaxGene RNA tubes) were pre-processed followed by standard quality control (QC) procedures on samples and probe sets. Statistical analysis of microarray data was performed using a linear regression model to evaluate differences in gene expression between LOAD and cognitively normal controls (CN). Meta-analysis was performed using a fixed-effect, inverse-variance-weighted model. Significant associations were determined using FDR adjustment and Bonferroni correction for multiple testing. Of the 21,150 probe sets in ADNI represented on the array after QC, 18 probe sets (16 genes) were significantly up-regulated and 8 probe sets (7 genes) were significantly down-regulated in LOAD after controlling for multiple testing (FDR-corrected p<0.05) (Fig. 1). Of the 23 differentially expressed genes, 6 genes were replicated in the meta-analysis (Table 1). The most significantly altered gene was CREB5 (up-regulated). Whole-brain cortical thickness analysis identified and replicated brain regions, especially entorhinal cortex, significantly associated with expression of CREB5 (Fig. 2). Individuals with lower expression showed greater cortical thickness (corrected p<0.05). cis-eQTL mapping analyses of CREB5 detected 5 significant associations with p < 5x10-8 (Fig. 3). cis-eQTL of rs56388170 (most significant) was replicated (Fig. 3) and was significantly associated with global cortical Aβ load (measured by [18F]Florbetapir PET) and CSF Aβ1-42 (Fig. 4). Volcano plot of transcriptome analysis results in the ADNI cohort (discovery sample). Red circles represent significantly differentially expressed genes in AD compared to CN. Association of CREB5 gene expression levels with brain structure using whole brain surface-based analysis using two independent cohorts: (a) ADNI (discovery sample) and (b) AddNeuroMed (replication sample). Whole-brain cortical thickness analysis demonstrated the identification and replication of brain regions, especially entorhinal cortex, significantly associated with expression of CREB5. Statistical maps computed using SurfStat were thresholded using random field theory (RFT) as a multiple testing correction at p-corrected < 0.05. Results of cis-eQTL mapping analysis of CREB5 using two independent cohorts: (a) ADNI (discovery sample) and (b) AddNeuroMed (replication sample). cis-eQTL mapping analyses of CREB5 detected 5 significant associations with p < 5×10-8 in the ADNI. The most significant cis-eQTL SNP (rs56388170) in the ADNI was replicated in the AddNeroMed. All SNPs are plotted based on their -log10 p-values, NCBI build 37 genomic position, and recombination rates calculated from the 1000 Genomes Project reference data. Association of the most significant cis-eQTL SNP (rs56388170) of CREB5 gene expression levels with (a) log transformed global cortical Aβ levels measured by [18F]Florbetapir PET and (b) CSF Aβ1-42 in the ADNI. rs56388170 was significantly associated with global cortical Aβ load and CSF Aβ1-42. RNA from peripheral blood indicated a differential gene expression pattern between AD patients and controls. Genes identified in this study have been implicated in biological processes that may be relevant to AD. CREB is a key component of nervous system development, cell survival, plasticity and learning and memory (Sakamoto et al. 2011).

The National Institute on Aging Genetics Initiative for Late-Onset Alzheimer's Disease (NIA-LOAD) was created to expand the resources for studies to identify additional genes contributing to the risk for LOAD. The study recruited families with two or more affected siblings clinically or pathologically diagnosed with Alzheimer's disease (AD) across 18 AD research centers. The objective of this study was to estimate age-specific incidence rates of AD in the unaffected family members of probands. Most epidemiological studies in AD calculate population specific incidence rates; however such analyses have not been extensively reported in large pedigrees presumed to be enriched for AD risk genes. We analyzed over 300 NIA-LOAD families with multiple affected members with AD. We restricted our analyses to families with complete phenotype information and subjects with a confirmed diagnosis of AD or cognitively normal. We used a 2-year lag period from the date of recruitment of the proband to correctly ascertain the prevalent AD cases. The analysis cohort consisted of 944 at-risk subjects at baseline; 495 subjects developed AD by the end of the 5-year follow-up period. We calculated age-specific incident rates of AD for family members in a five-year follow-up period from the recruitment of the proband The incidence rate for family members in the age-group of 65–74 was 5.9% per person-year, in 75–84 was 13.7% and above the age 85 years was 18.7%. The lag period from the date of ascertainment of the proband, to account correctly for prevalent cases in the family, greatly influenced the rate of incidence calculations. We are conducting sensitivity analyses to find the optimal time period needed to recruit the full pedigree of a proband which would correctly account for the prevalent cases in a family. As hypothesized, the incidence rates for AD in the NIA-LOAD families are higher than those compared to rates in other studies. The incidence rates in all groups increased with age. Effects of sex and education on the incidence rates are being estimated using family-based regression methods. The longitudinally followed subjects of the NIA-LOAD offer a unique opportunity to prospectively investigate the antecedents of AD.

Copy number variations (CNVs) are DNA regions >1 kilobase in size that have added (duplications) or deleted (deletions) genetic material. They may encompass genes affecting their function and resulting in disease. Previously, we investigated the role of CNVs in late-onset AD and MCI using ADNI [1] and NIA-LOAD/NCRAD Family Study [2] participants, and identified a number of genes overlapped by CNV calls. To confirm the findings and identify other possible candidate regions, we analyzed a unique cohort of clinically characterized and neuropathologically defined individuals [3]. CNV calls were generated in PennCNV software for 1617 Caucasian participants (1022 AD and 595 controls) with DNA extracted from brain tissue. After extensive quality control, 1166 samples (728 AD and 438 controls) were analyzed using PLINK software in a case/control association design. Genes overlapped by CNV calls only in cases (AD) were identified. Meta-analysis of the CHRFAM7A gene findings from the three studies was performed using MetaAnalyst and Comprehensive Analysis software. Molecular validation of the APp gene finding was performed using quantitative real-time PCR. AD samples showed a trend toward a higher CNV call rate for deletions and duplications than controls. Case/control association identified previously reported genes including CHRFAM7A, overlapped by CNV calls in 22 AD participants and three controls in this study (Figure 1(a); Table 1). Meta-analysis indicated a significant association of CHRFAM7A with AD and/or MCI risk (Odds Ratio = 3.986; 95% Confidence Interval, 1.490-10.667; p = 0.006). One AD sample (APOE E2/E3 genotype, age at death = 67) had a novel APp gene duplication (Figure 1(b)), validated using quantitative real-time PCR. Representative UCSC Genome Brower (March 2006) (NCBI36/hg 18) assembly) plots of CNV calls overlapping the CHRFAM7A (a) and APP (b) genes. Deletions are represented by red rectangles and duplications are represented by blue rectangles. CNV analyses in the present study identified a number of previously reported genes including CHRFAM7A. One sample with an APp gene duplication was also identified representing a novel finding since APp duplications have been associated with early- but not late-onset AD. Further investigation of the identified genes is warranted in independent and larger samples. References: 1. Swaminathan et al. Int J Alzheimers Dis 2011(2011);729478.2. Swaminathan et al. Curr Alzheimer Res (in press).3. Corneveaux et al. Hum Mol Genet 19(2010):3295-3301.

Copy number variations (CNVs) are DNA regions >1 kilobase in size that have added (duplications) or deleted (deletions) genetic material. They may encompass genes affecting their function and resulting in disease. Previously, we investigated the role of CNVs in late-onset AD and MCI using ADNI [1] and NIA-LOAD/NCRAD Family Study [2] participants, and identified a number of genes overlapped by CNV calls. To confirm the findings and identify other possible candidate regions, we analyzed a unique cohort of clinically characterized and neuropathologically defined individuals [3]. CNV calls were generated in PennCNV software for 1617 Caucasian participants (1022 AD and 595 controls) with DNA extracted from brain tissue. After extensive quality control, 1166 samples (728 AD and 438 controls) were analyzed using PLINK software in a case/control association design. Genes overlapped by CNV calls only in cases (AD) were identified. Meta-analysis of the CHRFAM7A gene findings from the three studies was performed using MetaAnalyst and Comprehensive Analysis software. Molecular validation of the APp gene finding was performed using quantitative real-time PCR. AD samples showed a trend toward a higher CNV call rate for deletions and duplications than controls. Case/control association identified previously reported genes including CHRFAM7A, overlapped by CNV calls in 22 AD participants and three controls in this study (Figure 1(a); Table 1). Meta-analysis indicated a significant association of CHRFAM7A with AD and/or MCI risk (Odds Ratio=3.986; 95% Confidence Interval, 1.490–10.667; P =0.006). One AD sample (APOE E2/E3 genotype, age at death=67) had a novel APp gene duplication (Figure 1(b)), validated using quantitative real-time PCR. CNV analyses in the present study identified a number of previously reported genes including CHRFAM7A. One sample with an APp gene duplication was also identified representing a novel finding since APp duplications have been associated with early- but not late-onset AD. Further investigation of the identified genes is warranted in independent and larger samples. References: 1. Swaminathan et al. Int J Alzheimers Dis 2011(2011);729478. 2. Swaminathan et al. Curr Alzheimer Res (in press). 3. Corneveaux et al. Hum Mol Genet 19(2010);3295–3301. Representative UCSC Genome Browser (March 2006 (NCBI36/hg 18) assembly) plots of CNV calls overlapping the CHRFAM7A (a) and APP (b) genes. Deletions are represented by red rectangles and duplications are represented by blue rectangles.

The Advancing Research and Treatment for Frontotemporal Lobar Degeneration (ARTFL) consortium aims to 1) characterize the North American population of FTLD patients in preparation for clinical trials and 2) characterize longitudinal changes in familial FTLD (fFTLD) over one year to develop new clinical trial outcome measures. Participants are either symptomatic with a sporadic FTLD spectrum disorder, including bvFTD, CBS, FTD-ALS, nfvPPA, PSP, or svPPA (Project 1) or are at risk for or symptomatic with fFTLD with a potentially autosomal dominant syndrome, regardless of whether there is a known underlying mutation (Project 2). ARTFL is closely linked to the LEFFTDS project, sharing a common infrastructure and assessments. Participants receive clinical neurological exams, neuropsychological testing, medical history, and blood draw for biomarker collection as well as surveys on lifestyle factors, autoimmune disease history, and attitudes towards clinical trial participation. Familial participants return for a follow-up visit in one year. Asymptomatic family members also undergo MRI. All ARTFL participants are genotyped for FTLD-associated mutations. We report here the characteristics of 566 (288 female (51%)) participants enrolled over 15 sites through December 2016. 280 individuals with sporadic FTLD have been enrolled in Project 1 (mean age 66 years [range 34–89]) with the most common diagnoses being bvFTD (26.5%), PSP (19.3%), and svPPA±bvFTD (15.1%). CDR-SB scores were higher in bvFTD and PSP than svPPA; MDS-UPDRS was highest in PSP >> bvFTD >> svPPA (normal). Project 2 has enrolled 84 symptomatic (mean age 57.9 years; mean CDR-SB: 5.68) and 201 asymptomatic (mean age 47.7; mean CDR-SB: 0.03) fFTLD. ARTFL is actively enrolling participants across North America to characterize sporadic and familial FTLD and prepare sites and investigators for FTLD clinical trials. Clinical, biomarker, genetic and imaging data from ARTFL and LEFFTDS will soon be available to investigators worldwide.

The Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS) Consortium (U01 AG045390) involves investigators at 8 centers in North America who are evaluating subjects in kindreds with mutations in microtubule associated protein tau (MAPT), progranulin (GRN), or chromosome 9 open reading frame 72 (C9orf72) genes using a standardized battery of measures. We report here the demographic, clinical and genetic characteristics of subjects evaluated through August 2016. There are 209 subjects among 61 kindreds enrolled to date with the following characteristics: 113 (54%) female, 201 (96%) Caucasian (and 5 Asian, 1 African-American, 1 American Indian and 1 Middle-Eastern American), mean age 50 (range 18–80) years, and mean education 15 (range 12–20) years. Using a modified version of the CDR, subjects are classified as symptomatic (CDR>0) or asymptomatic (CDR=0). Characteristics for each genetic group are as follows: MAPT − 17 kindreds with one of the following mutations: IVS9–10, IVS10+16, N279K, P301L, S305I, S305N, V337M, G389R and R406W; 73 subjects (28 CDR>0, 45 CDR=0); GRN − 19 kindreds with one of the following mutations: A9D, C31fs, T52fs, R110*, R198fs, S226fs, A237fs, V279fs, Q300*, W304fs, R418*, I422fs (novel), R493* and P512fs (novel); 66 subjects (25 CDR>0, 41 CDR=0); and C9orf72 − 25 kindreds with the expansion; 69 subjects (23 CDR>0, 46 CDR=0). *2 subjects with double mutation – C9orf72 + GRN. Almost all subjects have had volumetric MRI performed as well as DNA, plasma, RNA and PBMC samples collected. CSF has been collected in 38% of subjects. These clinical, neuropsychological and biomarker data, which will be available to interested investigators worldwide, should facilitate planning for upcoming disease-modifying therapeutic trials in familial frontotemporal lobar degeneration.

The Alzheimer's Disease Sequencing Project (ADSP) was established in 2012 as a Presidential Initiative to fight Alzheimer's Disease (AD). Developed jointly by National Institute on Aging (NIA) and the National Human Genome Research Institute (NHGRI), the aims are to: 1) identify protective genomic variants in older adults at risk for AD, 2) identify new risk variants among AD cases, and 3) examine these factors in multi-ethnic populations to identify therapeutic targets for disease prevention. The ADSP Data Flow Work Group (DFWG) and the NIA Genetics of Alzheimer's Disease Data Storage Site (NIAGADS) support data production, sharing and management for the ADSP, and facilitation of data access to the community. Samples are contributed by the AD Genetics Consortium and Cohorts for Heart and Aging Research in Genomic Epidemiology consortium. Sample plating and shipping is coordinated by the National Cell Repository for AD. Whole-exome (WES) and whole-genome (WGS) sequencing data were generated by three NHGRI funded Sequencing Centers and QC'ed by the ADSP. The DFWG maintains the ADSP web site, providing study design, cohort information, news releases, and application instructions for ADSP access. The ADSP Data Portal is a collaboration with the Database of Genotypes and Phenotypes (dbGaP), Sequence Read Archive, and NIAGADS. The portal allows users to explore the ADSP project data archived at dbGaP with NIH iTrust user authentication. Approved investigators identify data and download files using a customizable filtering system and check-out cart function. The ADSP has completed WES of 10,939 unrelated cases and controls, WGS of 892 members from 159 families, and WGS of 3,144 unrelated cases and controls. Accompanying each sample are phenotypes that were harmonized according to ADSP protocols. The DFWG provides support to all ADSP Work Groups for data related issues, coordinates with dbGaP for data transfers, and reviews, posts, and notifies members of new results generated by other Work Groups. Find additional information at the ADSP website (www.niagads.org/adsp).

April 24, 2017April 18, 2017Free AccessCharacteristics and Progress on the Initial 209 Subjects in the Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS) Protocol (P2.088)Bradley Boeve, Howard Rosen, Adam Boxer, Giovanni Coppola, Christina Dheel, Bradford Dickerson, Kelley Faber, … Show All … , Julie Fields, Tatiana Foroud, Ralitza Gavrilova, Nupur Ghoshal, Jill Goldman, Neill Graff-Radford, Murray Grossman, Hilary Heuer, John Hsiao, Ging-Yuek Hsiung, Edward Huey, David Irwin, Kejal Kantarci, Anna Karydas, David Knopman, John Kornak, Walter Kukull, Ian R.A. Mackenzie, Bruce Miller, Matt Miller, Creighton Phelps, Rosa Rademakers, Katherine Rankin, Leslie Shaw, Margaret Sutherland, Jeremy Syrjanen, Arthur Toga, John Trojanowski, Ashley Vetor, Sandra Weintraub, and Zbigniew Wszolek Show FewerAuthors Info & AffiliationsApril 18, 2017 issue88 (16_supplement)https://doi.org/10.1212/WNL.88.16_supplement.P2.088 Letters to the Editor

Abstract Background It is not unusual for Alzheimer’s Disease (AD) Research Center (ADRC) participants to enroll in additional studies such as the AD Neuroimaging Initiative (ADNI). In such cases, shared access to neuropathologic biospecimens is important to both studies, but dual‐enrollment status is not always known to acting ADRC personnel, and currently there is no centralized method to track dual enrollment. For this study, we aimed to identify individuals enrolled in ADNI and an ADRC, and identify those with autopsy data available through an ADRC but not ADNI. Method GWAS data were obtained for ADRC participants (N=22,935) through the AD Genetics Consortium (ADGC) and for ADNI participants (N=2,048) through the Laboratory of NeuroImaging (LONI); data were compared in PLINK v1.9 by identity‐by‐descent (IBD). ADRC/ADNI matches were filtered for pi‐hat &gt; 0.8. Genotype data from a custom‐96 SNP microarray for ADRC and ADNI samples banked at the National Centralized Repository for Alzheimer’s Disease and Related Dementias (NCRAD) were also compared to identify additional matches. Year of birth, sex, race, and ethnicity were compared within matches. Participant IDs from matches were reviewed for autopsy data available through the National Alzheimer’s Coordinating Center (NACC) Uniform Data Set (UDS) and from ADNI, to identify participants with autopsy data available through NACC but not ADNI. We generated counts for matches that had year of death, and among those, how many had neuropathology variables. Result We identified 364 pairs with matched genetic (pi‐hat&gt;0.99) and available demographic data from GWAS data, and another 52 from NCRAD genotype data. Of these, 143 matched ADRC participants had a year of death. 98 of the 143 had autopsy variables in the NACC UDS. 44 of these 98 were included in the ADNI autopsy data set (2018 version) or pending integration by the ADNI Neuropathology Core (NPC). Thus, 54 ADRC brain donors could be reported to the ADRCs as dually‐enrolled in ADNI, providing the involved ADRCs the opportunity to share these biospecimens with the ADNI NPC. Conclusion This case study illustrates how identification of dually‐enrolled participants represents a unique opportunity to leverage data collected through multiple studies to enhance AD research.

April 22, 2018April 10, 2018Free AccessThe Advancing Research and Treatment in Frontotemporal Lobar Degeneration (ARTFL) North American Rare Disease Clinical Research Consortium: Progress and Participant Characterization (S2.008)Adam Boxer, Howard Rosen, Bradley Boeve, Hilary W. Heuer, Murray Grossman, Giovanni Coppola, Bradford Dickerson, … Show All … , Brian Appleby, Yvette Bordelon, Danielle Brushaber, Christina Dheel, Kimiko Domoto-Reilly, Kelley Faber, Howard Feldman, Julie Fields, Jamie Fong, Tatiana Foroud, Nupur Ghoshal, Neill Graff-Radford, Ging-Yuek Hsiung, Edward Huey, David Irwin, Kejal Kantarci, Daniel Kaufer, Diana Kerwin, Alex Klein, David Knopman, John Kornak, Irene Litvan, Codrin Lungu, Ian R.A. Mackenzie, Mario Mendez, Bruce Miller, Chiadi Onyike, Alexander Pantelyat, Madeline Potter, Rosa Rademakers, Eliana Marisa Ramos, Katya Rascovsky, Erik Roberson, Margaret Sutherland, Carmela Tartaglia, Nadine Tatton, Arthur Toga, Sandra Weintraub, and Zbigniew Wszolek Show FewerAuthors Info & AffiliationsApril 10, 2018 issue90 (15_supplement)https://doi.org/10.1212/WNL.90.15_supplement.S2.008 Letters to the Editor

Therapies under development for AD employ strategies designed to modify disease processes. Early detection of presymptomatic AD-related changes will be important for effective treatment. Current diagnostic methods rely on the occurrence of late AD symptoms including memory impairment and functional decline, and others are invasive, time-consuming and/or expensive. DNA methylation (DNAm) changes in blood have been shown to associate with AD pathophysiology and progression. Our goal was to identify DNAm changes as associated with disease progression within the Alzheimer's disease Neuroimaging Initiative (ADNI) cohort as peripheral biomarkers of prodromal AD and to facilitate novel drug target discovery. Blood-derived DNA samples from cognitively normal (CN), mild cognitive impairment (MCI), and AD participants in ADNI underwent DNAm analysis using the Illumina EPIC array followed by quality control and normalization. Age, sex, education, and cell composition were used as covariates. Blood RNA expression data on a subset of participants were analyzed. Cross-sectional analyses yielded 483, 139, and 299 differentially methylated positions (DMPs) for the AD-CN, AD-MCI, and MCI-CN comparisons including 433, 135, and 269 genes upon annotation with the nearest transcription start sites (TSS), which enriched for neuronal-associated genes (adj.p<0.01) when analyzing for tissue-specific expression using GTEx data. Gene ontology analysis identified neurodevelopment and neurotransmission as the most highly enriched pathways (adj.p<0.05). We found hypermethylation upstream of the BIN1 (Bridging Integrator 1) TSS in MCI and AD relative to CN subjects. Blood RNA expression analysis indicated downregulation of BIN1 expression in AD relative to CN. We also found DNAm changes in other genes associated with neurodegeneration (e.g. BDNF), and in genes associated with neurotransmission and synaptic function (e.g. KCNN2). In addition to replicating previously characterized DNAm changes in AD subjects, our results show DNAm changes in genes associated with neurodevelopment and synaptic function. This is the largest study on DNAm changes across the AD spectrum thus far. Ongoing analysis of longitudinal DNAm changes and their associations with AD biomarker changes (e.g. amyloid and tau burden, atrophy, cognitive performance) will facilitate the identification of early biomarkers of disease progression, provide insight into the mechanisms of AD pathogenesis, and facilitate novel target discovery.

We aimed to compare the clinical and demographic features of sporadic and genetic forms of behavioral variant frontotemporal dementia (bvFTD) evaluated in the ARTFL/LEFFTDS projects. ARTFL is an 18 center clinical research consortium preparing for FTLD clinical trials that operates in conjunction with the Longitudinal Evaluation of Familial Frontotemporal Dementia Subjects (LEFFTDS) project. Many new FTLD trials will focus on autosomal dominant familial FTLD (fFTLD) because it is possible to definitively determine individuals’ underlying pathology during life and because prevention trials may be possible in asymptomatic gene carriers. A major question is whether findings in fFTLD will translate to the more common sporadic FTLD syndromes, of which bvFTD is the most common syndrome. Clinical and neuropsychological ratings from the National Alzheimer's Coordinating Center Uniform Data Set (UDS) and FTLD modules were evaluated in patients meeting 2011 FTDC criteria for bvFTD evaluated in the ARTFL/LEFFTDS consortium between 2015-2017. Through December, 2017, 213 bvFTD were enrolled in ARTFL, including 136 sporadic cases (36.8% female; mean: 63.6±8.8 years) and 77 familial cases (47.9% female; 58.5±9.7 years). Familial bvFTD included 33 C9orf72, 20 MAPT, 4 GRN mutation carriers (confirmed or presumed) and 20 bvFTD with strong FTLD family history but no identifiable mutation. Sporadic and familial bvFTD did not differ in measures of disease severity such as CDR-FTLD-SB (8-item), MoCA, and CGI-S. Sporadic bvFTD were older (p<0.001) and had higher total NPI-Q scores (11.9±6.0 vs. 10.1±5.9, p =0.05). In patients with worse disease severity (CDR-FTLD-SB ≥ median, which was 8.0), MAPT mutation carriers had worse parkinsonism (UPDRS and PSPRS scores) compared with sporadic and other familial bvFTD patients. No differences in presence of hallucinations or delusions on NPI-Q were noted between C9orf72 bvFTD and other cohorts. Sporadic bvFTD cases are older and tend to have more severe neuropsychiatric symptoms than familial bvFTD, but are otherwise highly similar on the NACC UDS and FTLD module assessments. This supports the hypothesis that a clinically meaningful treatment response in familial bvFTD may be generalizable to sporadic bvFTD.

The IDEAS-Study enrolled over 18,000 individuals from whom amyloid imaging and other clinical data were obtained; however, a DNA sample was not collected. The Amyloid Neuroimaging and Genetics Initiative (ANGI) is an approved IDEAS add-on study that is designed to consent and obtain a saliva sample for DNA, from willing IDEAS participants. All consenting and sample collection is completed either online or by mail as ANGI participants have already completed the IDEAS-Study, and are not seen in person. IDEAS participants interested in the ANGI Study are referred to Indiana University, and contacted by telephone to discuss ANGI. Two consenting processes are offered to participants: a novel online video consent or traditional paper consent via mail. Online participants are emailed a link to view video segments reviewing the consent, and allows participants to submit questions throughout the process. Participants are asked questions after each video segment to evaluate comprehension, before signing the consent online. Traditional paper consents are mailed, signed, and returned to Indiana University. After consenting, participants are sent a saliva kit. The kit includes basic instructions requesting participants provide their saliva sample in a collection tube and return via mail to Indiana University. As of January 15, 2018, 3644 participant referrals have been received from the IDEAS-Study. Of those referred, 3034 (83%) have been contacted, and connections have been made with 2319 (76%) potential participants. Of those contacted, 311 (13%) have declined to participate. Thus far, 2008 participants decided to review either the paper consent (1264, 63%) or the online consent (744, 37%). To date, 937 (47%) have completed the consent process. The majority of participants completed the paper consent process (604, 64%) rather than the online consent process (333, 36%). Over 80% of consented individuals have returned their filled saliva kit.

The National Cell Repository for Alzheimer's Disease (NCRAD) is a cooperative agreement between Indiana University and the National Institutes on Aging (NIA). Founded in 1990, the goal of NCRAD is to obtain and manage high quality biological specimens and clinical data from individuals and families with Alzheimer's disease and related dementias (ADRD) as well as from cognitively normal controls, and to make these resources available to qualified researchers. NCRAD currently serves as a central biorepository, banking a wide range of samples for NIA-supported studies, as well as closed studies. NCRAD employs a high level of data management, data and study coordination, technical resources, and scientific support. In addition to sample storage and distribution, a variety of related services are offered: study design and genetic consultation, procedure manuals, biospecimen collection kits, and study coordinator training. Constantly improving best practices, NCRAD recently implemented in-house DNA fingerprinting, with the goal to assay every stored and distributed sample as well as those newly obtained. NCRAD stores a wide variety of biospecimen types including serum, plasma, DNA, RNA, brain tissue, cerebrospinal fluid and peripheral blood mononuclear cells (PBMCs). NCRAD is developing a pipeline to support maintenance and distribution of induced pluripotent stem cells (iPSCs). NCRAD has developed online catalogs available to approved investigators that can be queried to explore the range of biospecimens available at NCRAD for research use (https://www.ncrad.org/). Key accomplishments of NCRAD include banking samples from 28 different ADRD studies including samples from >63,000 individuals. Over 150 researchers have received samples from NCRAD. These include >230,000 DNA, plasma, serum, RNA, PBMC and cell lines used in >500 publications. NCRAD is a key resource for researchers in neurodegenerative disease, serving as a central biorepository to store and distribute large numbers of a variety of high quality biological specimens. As the scope of research expands from initial genetic discovery to the design of experiments to explore biological mechanisms and potential interventions, the availability of high quality biospecimens from participants with extensive longitudinal phenotyping is critical.

MAPT mutations typically cause behavioral variant frontotemporal dementia (bvFTD) with or without parkinsonism. Previous studies have shown that symptomatic MAPT carriers show atrophy in frontotemporal cortex, with mesial temporal lobes predominantly affected (Rohrer et al., 2010; Whitwell et al., 2009). For presymptomatic MAPT carriers, studies have been mixed, with studies showing either no apparent gray matter deficits, or deficits in region of interest parcellations (Dopper et al., 2014; Rohrer et al., 2015). We studied a large cohort of presymptomatic and symptomatic MAPT carriers using a voxelwise approach to further refine neuroanatomical deficits and to examine relationships between gray matter and age. We studied 16 symptomatic MAPT carriers (age 55.3 ± 9.0, 10 female), 45 presymptomatic MAPT carriers (age 39.7 ± 10.5, 24 female), and 109 healthy controls (age 48.8 ± 13.3, 56 female) who had structural brain MRI scans. Symptomatic MAPT carriers included 15 with behavioral variant frontotemporal dementia (bvFTD), among which two had comorbid progressive supranuclear palsy syndrome, and one had Parkinson's disease. One carrier had an amnestic Alzheimer's-like syndrome. Voxel-based morphometry was performed on T1 images using SPM12. We created smoothed gray matter probability maps to generate voxelwise gray matter w-maps, a method of quantifying the difference between an individual carrier's expected and actual gray matter values, to further examine structural deficits (Ossenkoppele et al., 2015). Symptomatic MAPT carriers had bilateral gray matter atrophy in frontal cortex, insula, striatum with mesial temporal atrophy present in all subjects. Presymptomatic MAPT carriers showed an anatomically similar yet milder pattern of gray matter deficits, focused within bilateral hippocampus, amygdala and lateral temporal cortices. Within these regions, deficits emerged in a subset of presymptomatic MAPT carriers as early as their late thirties, while the remaining presymptomatic carriers showed normal gray matter volumes throughout the entire age span studied. Our findings suggest that early mesial temporal gray matter deficits are detectable in a subset of presymptomatic MAPT carriers, and that these same regions were atrophied in all symptomatic MAPT carriers studied. Longitudinal studies will elucidate whether these gray matter deficits represent early neurodegeneration, neurodevelopmental deficits, or both.

ARTFL is a NIH-sponsored rare disease clinical research consortium involving 18 clinical centers that evaluate participants in order to 1) characterize the North American population of FTLD patients and 2) study longitudinal changes in familial FTLD (fFTLD) over one year. Key goals are to build clinical trial cohorts and to develop new clinical trial outcome measures including fluid biomarkers. Participants with FTLD spectrum disorders (bvFTD, svPPA, nfvPPA, FTD-ALS, CBD or PSP) or with strong family histories of FTLD undergo clinical and neuropsychological evaluations and blood draws for genetic and blood biomarker analyses. ARTFL is closely linked to the LEFFTDS project, sharing a common infrastructure and assessments. Asymptomatic fFTLD and a subset of sporadic cases undergo MRI. All ARTFL participants are genotyped for dementia-associated mutations. 912 (455 female (50%); 95% Caucasian) individuals were evaluated through December, 2017. In the 475 participants with sporadic FTLD, the most common diagnoses were bvFTD (30.5%) and PSP (20.8%), followed by svPPA (13%), nfvPPA (11.8%), CBS (9.8%) and sporadic FTD-ALS (3%). 45 (9.5%) individuals were referred to the project with FTLD diagnoses, but were determined by expert evaluation to have a different diagnosis. Of the 437 fFTLD participants, 35.7% were considered symptomatic (CDR>0) at their initial visit; the most prominent clinical phenotype was bvFTD (48.4%). Other diagnoses included FTD-ALS, MCI, and psychiatric disorders. The most common causative mutations identified in fFTLD were in C9ORF72 (including 3 in cases thought to be sporadic), followed by MAPT and GRN. 95 individuals with a strong FTLD family history, but no identifiable causative mutation in the family, have been enrolled to date. Expected differences in clinical and neuropsychological rating scales from the NACC UDS and FTLD modules were observed between diagnostic groups. ARTFL is building a substantial FTLD cohort at 18 North American research centers to support clinical research studies. Clinical, biomarker, genetic, imaging data and biospecimens from ARTFL and LEFFTDS are available to investigators worldwide via direct request and the NACC, LONI and NCRAD.

Improving clinicians’ ability to predict genetic mutations causing Frontotemporal dementia (FTD) is useful for diagnostic evaluation and potentially referral to appropriate studies including therapeutic trials. Previous studies have shown neuroanatomical differences between the three main genetic mutations in familial FTD, microtubule-associated protein tau (MAPT), chromosome 9 open reading frame 72 (c9orf72) and progranulin (GRN) mutations. MAPT has been associated with atrophy predominantly in the anteromedial temporal lobes; c9orf72 with widespread atrophy in frontoparietal regions; and GRN with asymmetrical atrophy in frontotemporoparietal regions (Whitwell et al., 2012; Rohrer et al., 2010). Using a brain network approach, the main goal of this study was to assess whether different patterns of atrophy in large-scale brain networks identified in prior work (Seeley et al., 2012; Touroutoglou et al., 2012; Vincent et al., 2008) predict genetic mutations in FTD patients spanning different clinical diagnoses. We hypothesized that (1) relatively greater atrophy in the salience and semantic appraisal networks, including frontoinsula and anterior temporal regions would be present in MAPT, (2) relatively greater atrophy in the frontoparietal network would be associated with c9orf72 and (3) relatively greater asymmetrical atrophy in frontoparietal and salience networks would be associated with GRN. The analysis included symptomatic participants recruited from the Longitudinal Evaluation of Familial Frontotemporal Dementia Study (LEFFTDS). To determine network-based patterns of brain atrophy at the individual level, we used single-subject general linear model analysis and compared structural MRI data from healthy controls (N = 166) versus MAPT (N = 18), c9orf72 (N = 27), and GRN (N= 10) mutation patients. Cortical thickness measurements were calculated using FreeSurfer v6.0. An untrained rater predicted gene mutations based on the patterns of brain network atrophy. Prediction accuracy was measured with the percentage of correct predictions. The results showed 74% prediction accuracy for MAPT, 72% prediction accuracy for c9orf72 and 60% prediction accuracy for GRN. Our findings provide preliminary evidence suggesting that a brain network approach can be useful in individual patients to predict the specific genetic mutations in the three major genetic variants of familial FTD.