Laurel Beckett

The pathophysiological process of Alzheimer's disease (AD) is thought to begin many years before the diagnosis of AD dementia. This long "preclinical" phase of AD would provide a critical opportunity for therapeutic intervention; however, we need to further elucidate the link between the pathological cascade of AD and the emergence of clinical symptoms. The National Institute on Aging and the Alzheimer's Association convened an international workgroup to review the biomarker, epidemiological, and neuropsychological evidence, and to develop recommendations to determine the factors which best predict the risk of progression from "normal" cognition to mild cognitive impairment and AD dementia. We propose a conceptual framework and operational research criteria, based on the prevailing scientific evidence to date, to test and refine these models with longitudinal clinical research studies. These recommendations are solely intended for research purposes and do not have any clinical implications at this time. It is hoped that these recommendations will provide a common rubric to advance the study of preclinical AD, and ultimately, aid the field in moving toward earlier intervention at a stage of AD when some disease-modifying therapies may be most efficacious.

Neuroimaging measures and chemical biomarkers may be important indices of clinical progression in normal aging and mild cognitive impairment (MCI) and need to be evaluated longitudinally.To characterize cross-sectionally and longitudinally clinical measures in normal controls, subjects with MCI, and subjects with mild Alzheimer disease (AD) to enable the assessment of the utility of neuroimaging and chemical biomarker measures.A total of 819 subjects (229 cognitively normal, 398 with MCI, and 192 with AD) were enrolled at baseline and followed for 12 months using standard cognitive and functional measures typical of clinical trials.The subjects with MCI were more memory impaired than the cognitively normal subjects but not as impaired as the subjects with AD. Nonmemory cognitive measures were only minimally impaired in the subjects with MCI. The subjects with MCI progressed to dementia in 12 months at a rate of 16.5% per year. Approximately 50% of the subjects with MCI were on antidementia therapies. There was minimal movement on the Alzheimer's Disease Assessment Scale-Cognitive Subscale for the normal control subjects, slight movement for the subjects with MCI of 1.1, and a modest change for the subjects with AD of 4.3. Baseline CSF measures of Abeta-42 separated the 3 groups as expected and successfully predicted the 12-month change in cognitive measures.The Alzheimer's Disease Neuroimaging Initiative has successfully recruited cohorts of cognitively normal subjects, subjects with mild cognitive impairment (MCI), and subjects with Alzheimer disease with anticipated baseline characteristics. The 12-month progression rate of MCI was as predicted, and the CSF measures heralded progression of clinical measures over 12 months.

Abstract With the increasing life expectancy in developed countries, the incidence of Alzheimer's disease (AD) and thus its socioeconomic impact are growing. Increasing knowledge over the last years about the pathomechanisms involved in AD allow for the development of specific treatment strategies aimed at slowing down or even preventing neuronal death in AD. However, this requires also that (1) AD can be diagnosed with high accuracy, because non‐AD dementias would not benefit from an AD‐specific treatment; (2) AD can be diagnosed in very early stages when any intervention would be most effective; and (3) treatment efficacy can be reliably and meaningfully monitored. Although there currently is no ideal biomarker that would fulfill all these requirements, there is increasing evidence that a combination of currently existing neuroimaging and cerebrospinal fluid (CSF) and blood biomarkers can provide important complementary information and thus contribute to a more accurate and earlier diagnosis of AD. The Alzheimer's Disease Neuroimaging Initiative (ADNI) is exploring which combinations of these biomarkers are the most powerful for diagnosis of AD and monitoring of treatment effects.

With increasing life expectancy in developed countries, the incidence of Alzheimer's disease (AD) and its socioeconomic impact are growing. Increasing knowledge of the mechanisms of AD facilitates the development of treatment strategies aimed at slowing down or preventing neuronal death. AD treatment trials using clinical outcome measures require long observation times and large patient samples. There is increasing evidence that neuroimaging and cerebrospinal fluid and blood biomarkers may provide information that may reduce sample sizes and observation periods. The Alzheimer's Disease Neuroimaging Initiative will help identify clinical, neuroimaging, and biomarker outcome measures that provide the highest power for measurement of longitudinal changes and for prediction of transitions.

Cognitive abilities of older persons range from normal, to mild cognitive impairment, to dementia. Few large longitudinal studies have compared the natural history of mild cognitive impairment with similar persons without cognitive impairment.Participants were older Catholic clergy without dementia, 211 with mild cognitive impairment and 587 without cognitive impairment, who underwent annual clinical evaluation for AD and an assessment of different cognitive abilities. Cognitive performance tests were summarized to yield a composite measure of global cognitive function and separate summary measures of episodic memory, semantic memory, working memory, perceptual speed, and visuospatial ability. The authors compared the risk of death, risk of incident AD, and rates of change in global cognition and different cognitive domains among persons with mild cognitive impairment to those without cognitive impairment. All models controlled for age, sex, and education.On average, persons with mild cognitive impairment had significantly lower scores at baseline in all cognitive domains. Over an average of 4.5 years of follow-up, 30% of persons with mild cognitive impairment died, a rate 1.7 times higher than those without cognitive impairment (95% CI, 1.2 to 2.5). In addition, 64 (34%) persons with mild cognitive impairment developed AD, a rate 3.1 times higher than those without cognitive impairment (95% CI, 2.1 to 4.5). Finally, persons with mild cognitive impairment declined significantly faster on measures of episodic memory, semantic memory, and perceptual speed, but not on measures of working memory or visuospatial ability, as compared with persons without cognitive impairment.Mild cognitive impairment is associated with an increased risk of death and incident AD, and a greater rate of decline in selected cognitive abilities.

Abstract Multifactorial mechanisms underlying late-onset Alzheimer’s disease (LOAD) are poorly characterized from an integrative perspective. Here spatiotemporal alterations in brain amyloid-β deposition, metabolism, vascular, functional activity at rest, structural properties, cognitive integrity and peripheral proteins levels are characterized in relation to LOAD progression. We analyse over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Through a multifactorial data-driven analysis, we obtain dynamic LOAD–abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression. Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development. Cognitive decline is noticeable from initial LOAD stages, suggesting early memory deficit associated with the primary disease factors. High abnormality levels are also observed for specific proteins associated with the vascular system’s integrity. Although still subjected to the sensitivity of the algorithms and biomarkers employed, our results might contribute to the development of preventive therapeutic interventions.

Alzheimer's disease (AD) is a slowly progressing disorder in which pathophysiological abnormalities, detectable in vivo by biomarkers, precede overt clinical symptoms by many years to decades. Five AD biomarkers are sufficiently validated to have been incorporated into clinical diagnostic criteria and commonly used in therapeutic trials. Current AD biomarkers fall into two categories: biomarkers of amyloid-β plaques and of tau-related neurodegeneration. Three of the five are imaging measures and two are cerebrospinal fluid analytes. AD biomarkers do not evolve in an identical manner but rather in a sequential but temporally overlapping manner. Models of the temporal evolution of AD biomarkers can take the form of plots of biomarker severity (degree of abnormality) versus time. In this Review, we discuss several time-dependent models of AD that take into consideration varying age of onset (early versus late) and the influence of aging and co-occurring brain pathologies that commonly arise in the elderly.

The authors examined change in cognitive abilities in older Catholic clergy members. For up to 6 years, participants underwent annual clinical evaluations, which included a battery of tests from which summary measures of 7 abilities were derived. On average, decline occurred in each ability and was more rapid in older persons than in younger persons. However, wide individual differences were evident at all ages. Rate of change in a given domain was not strongly related to baseline level of function in that domain but was moderately associated with rates of change in other cognitive domains. The results suggest that change in cognitive function in old age primarily reflects person-specific factors rather than an inevitable developmental process.

In Alzheimer's disease (AD), loss of cortical and hippocampal choline acetyltransferase (ChAT) activity has been correlated with dementia severity and disease duration, and it forms the basis for current therapies. However, the extent to which reductions in ChAT activity are associated with early cognitive decline has not been well established. We quantified ChAT activity in the hippocampus and four cortical regions (superior frontal, inferior parietal, superior temporal, and anterior cingulate) of 58 individuals diagnosed with no cognitive impairment (NCI; n = 26; mean age 81.4 +/- 7.3 years), mild cognitive impairment (MCI; n = 18; mean age 84.5 +/- 5.7), or mild AD (n =14; mean age 86.3 +/- 6.6). Inferior parietal cortex ChAT activity was also assessed in 12 subjects with end-stage AD (mean age 81.4 +/- 4.3 years) and compared to inferior parietal cortex ChAT levels of the other three groups. Only the end-stage AD group had ChAT levels reduced below normal. In individuals with MCI and mild AD, ChAT activity was unchanged in the inferior parietal, superior temporal, and anterior cingulate cortices compared to NCI. In contrast, ChAT activity in the superior frontal cortex was significantly elevated above normal controls in MCI subjects, whereas the mild AD group was not different from NCI or MCI. Hippocampal ChAT activity was significantly higher in MCI subjects than in either NCI or AD. Our results suggest that cognitive deficits in MCI and early AD are not associated with the loss of ChAT and occur despite regionally specific upregulation. Thus, the earliest cognitive deficits in AD involve brain changes other than simply cholinergic system loss. Of importance, the cholinergic system is capable of compensatory responses during the early stage of dementia. The upregulation in frontal cortex and hippocampal ChAT activity could be an important factor in preventing the transition of MCI subjects to AD.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU, CR1, and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI-like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2-year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI-2) in October 2010 through to 2016, with enrollment of an additional 550 participants.

Older people frequently have signs of parkinsonism, but information about the prevalence of parkinsonism and mortality among those with the condition in the community is limited.A stratified random sample of 467 residents of East Boston, Massachusetts, 65 years of age or older, were given structured neurologic examinations. Using uniform, specified combinations of parkinsonian signs, we estimated the prevalence of four categories of signs--bradykinesia, gait disturbance, rigidity, and tremor--and of parkinsonism, defined as the presence of two or more categories. We did not study Parkinson's disease because it could not be distinguished from other conditions that can cause parkinsonism. Proportional-hazards models were used to compare the risk of death among people with and those without parkinsonism.One hundred fifty-nine persons had parkinsonism, 301 did not, and 7 could not be classified. The overall prevalence estimates were 14.9 percent for people 65 to 74 years of age, 29.5 percent for those 75 to 84, and 52.4 percent for those 85 and older. With a mean follow-up period of 9.2 years, 124 persons with parkinsonism (78 percent) and 146 persons without (49 percent) died. Adjusted for age and sex, the overall risk of death among people with parkinsonism was 2.0 (95 percent confidence interval, 1.6 to 2.6) times that among people without. Among people with parkinsonism, the presence of gait disturbance was associated with an increased risk of death.Parkinsonism is very common among people over the age of 65, and its prevalence increases markedly with age. Parkinsonism is associated with a twofold increase in the risk of death, which is strongly related to the presence of a gait disturbance.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) beginning in October 2004, is a 6‐year research project that studies changes of cognition, function, brain structure and function, and biomarkers in elderly controls, subjects with mild cognitive impairment, and subjects with Alzheimer's disease (AD). A major goal is to determine and validate MRI, PET images, and cerebrospinal fluid (CSF)/blood biomarkers as predictors and outcomes for use in clinical trials of AD treatments. Structural MRI, FDG PET, C‐11 Pittsburgh compound B (PIB) PET, CSF measurements of amyloid β (Aβ) and species of tau, with clinical/cognitive measurements were performed on elderly controls, subjects with mild cognitive impairment, and subjects with AD. Structural MRI shows high rates of brain atrophy, and has high statistical power for determining treatment effects. FDG PET, C‐11 Pittsburgh compound B PET, and CSF measurements of Aβ and tau were significant predictors of cognitive decline and brain atrophy. All data are available at UCLA/LONI/ADNI, without embargo. ADNI‐like projects started in Australia, Europe, Japan, and Korea. ADNI provides significant new information concerning the progression of AD.

Cross-sectional and retrospective case-control studies suggest an association of depression symptoms with cognitive impairment and AD, but there have been few prospective studies and their results have been inconsistent.Participants are Catholic clergy members who were aged > or =65 years and who did not have clinical evidence of AD. During a 7-year period, they underwent annual clinical evaluations that included clinical classification of AD and detailed cognitive function testing from which global and specific measures of cognition were derived. Number of depressive symptoms was assessed at baseline with a modified, 10-item Center for Epidemiologic Studies Depression Scale (CES-D). The association of CES-D score with incident AD, using proportional hazards models, and cognitive decline, using random effects models, was examined.At baseline, participants reported an average of about one depressive symptom on the CES-D scale (range, 0 to 8). During the 7 years of follow-up, 108 persons developed AD. In analyses that controlled for selected demographic and clinical variables including baseline level of cognitive function, CES-D score was associated with both risk of AD and rate of cognitive decline. For each depressive symptom, risk of developing AD increased by an average of 19%, and annual decline on a global cognitive measure increased by an average of 24%.The results raise the possibility that depressive symptoms in older persons may be associated with risk of developing AD.

With high resolution, quantitative magnetic resonance imaging (MRI) techniques, it is now possible to examine alterations in brain anatomy in vivo and to identify regions affected in the earliest stages of Alzheimer’s disease (AD). In this study, we compared MRI-derived entorhinal and hippocampal volume in healthy elderly controls, patients who presented at the clinic with cognitive complaints, but did not meet criteria for dementia (non-demented), and patients with very mild AD. The two patient groups differed significantly from controls in entorhinal volume, but not from each other; in contrast, they differed from each other, as well as from controls, in hippocampal volume, with the mild AD cases showing the greatest atrophy. Follow-up clinical evaluations available on 23/28 non-demented patients indicated that 12/23 had converted to AD within 12–77 months from the baseline MRI examination. Converters could be best differentiated from non-converters on the basis of entorhinal, but not hippocampal volume. These data suggest that although both the EC and hippocampal formation degenerate before the onset of overt dementia, EC volume is a better predictor of conversion.

Alzheimer disease will affect increasing numbers of people as baby boomers (persons born between 1946 and 1964) age. This work reports projections of the incidence of Alzheimer disease(AD) that will occur among older Americans in the future. Education adjusted age-specific incidence rates of clinically diagnosed probable AD were obtained from stratified random samples of residents 65 years of age and older in a geographically defined community. These rates were applied to U.S. Census Bureau projections of the total U.S. population by age and sex to estimate the number of people newly affected each year. The annual number of incident cases is expected to more than double by the midpoint of the twenty-first century: from 377,000 (95% confidence interval = 159,000–595,000) in 1995 to 959,000 (95% confidence interval = 140,000–1,778,000) in 2050. The proportion of new onset casess who are age 85 or older will increase from 40% in 1995 to 62% in 2050 when the youngest of the baby boomers will attain that age. Without progress in preventing or delaying onset of Alzheimer disease, both the number of people with Alzheimer disease and the proportion of the total population affected will increase substantially.

The Clinical Core of the Alzheimer's Disease Neuroimaging Initiative (ADNI) has provided clinical, operational, and data management support to ADNI since its inception. This article reviews the activities and accomplishments of the core in support of ADNI aims. These include the enrollment and follow-up of more than 800 subjects in the three original cohorts: healthy controls, amnestic mild cognitive impairment (now referred to as late MCI, or LMCI), and mild Alzheimer's disease (AD) in the first phase of ADNI (ADNI 1), with baseline longitudinal, clinical, and cognitive assessments. These data, when combined with genetic, neuroimaging, and cerebrospinal fluid measures, have provided important insights into the neurobiology of the AD spectrum. Furthermore, these data have facilitated the development of novel clinical trial designs. ADNI has recently been extended with funding from an NIH Grand Opportunities (GO) award, and the new ADNI GO phase has been launched; this includes the enrollment of a new cohort, called early MCI, with milder episodic memory impairment than the LMCI group. An application for a further 5 years of ADNI funding (ADNI 2) was recently submitted. This funding would support ongoing follow-up of the original ADNI 1 and ADNI GO cohorts, as well as additional recruitment into all categories. The resulting data would provide valuable data on the earliest stages of AD, and support the development of interventions in these critically important populations.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The study aimed to enroll 400 subjects with early mild cognitive impairment (MCI), 200 subjects with early AD, and 200 normal control subjects; $67 million funding was provided by both the public and private sectors, including the National Institute on Aging, 13 pharmaceutical companies, and 2 foundations that provided support through the Foundation for the National Institutes of Health. This article reviews all papers published since the inception of the initiative and summarizes the results as of February 2011. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are consistent with disease trajectories predicted by β‐amyloid cascade (Hardy, J Alzheimers Dis 2006;9(Suppl 3):151–3) and tau‐mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers combine optimum features from multiple modalities, including MRI, [ 18 F]‐fluorodeoxyglucose‐PET, CSF biomarkers, and clinical tests; (4) the development of methods for the early detection of AD. CSF biomarkers, β‐amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects, and are leading candidates for the detection of AD in its preclinical stages; (5) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Baseline cognitive and/or MRI measures generally predicted future decline better than other modalities, whereas MRI measures of change were shown to be the most efficient outcome measures; (6) the confirmation of the AD risk loci CLU , CR1 , and PICALM and the identification of novel candidate risk loci; (7) worldwide impact through the establishment of ADNI‐like programs in Europe, Asia, and Australia; (8) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker data with clinical data from ADNI to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease‐modifying drugs for AD; and (9) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world. The ADNI study was extended by a 2‐year Grand Opportunities grant in 2009 and a renewal of ADNI (ADNI‐2) in October 2010 through to 2016, with enrollment of an additional 550 participants.

To assess the relations of 3 measures of socioeconomic status (education, occupational prestige, and income) to risk of incident clinically diagnosed Alzheimer disease (AD).Cohort study with an average observation of 4.3 years.East Boston, Mass. a geographically defined community.A stratified random sample of 642 community residents 65 years of age and older who were free of AD at baseline.Clinical diagnosis of probable AD according to standard criteria, using structured uniform evaluation.The relations of the 3 measures of socioeconomic status to risk of disease were assessed using logistic regression analyses. In individual analyses, fewer years of formal schooling, lower income, and lower occupational status each predicted risk of incident AD; risk of disease decreased by approximately 17% for each year of education. In an analysis including all 3 measures, the effect of education on risk for disease remained approximately the same, but the effects of the other 2 measures were somewhat less and did not attain formal statistical significance, compared with separate analysis of each measure.Markers of lower socioeconomic status predict risk of developing incident AD. The mechanism of this relation is uncertain, but the possibility that it reflects unidentified and potentially reversible risk factors for the disease deserves careful investigation.

To determine age-specific incidence rates of clinically diagnosed Alzheimer's disease.Cohort, followed a mean of 4.3 years.East Boston, Mass.Of 2313 persons aged 65 years and older who were initially free of Alzheimer's disease, 1601 participated in the ascertainment of incident disease (80% of survivors), 409 declined participation, and 303 died before the end of the follow-up period. A stratified sample of 642 persons received detailed clinical evaluation.Diagnosis of new probable Alzheimer's disease through structured clinical evaluation including neurologic, neuropsychological, and psychiatric examination. Community incidence rates were computed by 5-year age groups, adjusted for gender, single year of age, length of follow-up interval, and sampling design.The estimated annual incidence of Alzheimer's disease in the population was 0.6% (95% confidence interval [CI], 0.3% to 0.9%) for persons aged 65 to 69 years, 1.0% (95% CI, 0.6% to 1.4%) for persons aged 70 to 74 years, 2.0% (95% CI, 1.3% to 2.7%) for persons aged 75 to 79 years, 3.3% (95% CI, 2.2% to 4.4%) for persons aged 80 to 84 years, and 8.4% (95% CI, 3.7% to 13.1%) for persons aged 85 years and older.The incidence of Alzheimer's disease is substantial and is approximately 14 times higher among persons older than 85 years compared with those between 65 and 69 years of age.

Few studies compare Alzheimer disease (AD) incidence among black and white subjects.To estimate incidence and the effect of the apolipoprotein E (APOE) epsilon4 allele in these races.Population-based study of disease incidence using a random, stratified sample.A geographically defined community of 3 adjacent neighborhoods in Chicago, Ill.A total of 6158 persons (78.7% overall; 80.5% of the black subjects and 74.6% of the white subjects) participated; 4.1 years later, persons initially free of AD were sampled for clinical evaluation for disease incidence (overall 842 persons [74.8%] participated; 67.6% of the black subjects and 81.9% of the white subjects).None.Incident, clinically diagnosed AD.The effect of the APOE epsilon4 allele on the risk of AD differed strongly for black and white subjects. Among white subjects, the presence of the APOE epsilon4 allele was associated with a 2.73-fold (95% confidence interval [CI], 1.40-5.32) increase in risk while among black subjects there was no increase in risk (odds ratio, 1.02; 95% confidence interval, 0.39-2.68). Black race was associated with a nonsignificantly increased risk of AD with an odds ratio of 1.84 (95% CI, 0.73-4.66) if APOE and its interaction with race are considered, and an odds ratio of 1.28 (95% CI, 0.54-2.98) if they are not. The incidence of AD was 1.45% (95% CI, 0.89%-2.01%) per year among persons 65 to 74 years old, 4.73% (95% CI, 3.83%-5.64%) among those 75 to 84 years old, and 9.11% (95% CI, 7.36%-10.9%) among those 85 years and older.Apolipoprotein E epsilon4 led to increased risk of AD among white subjects but not black subjects.

To estimate a regional progression pattern of amyloid deposition from cross-sectional amyloid-sensitive PET data and evaluate its potential for in vivo staging of an individual's amyloid pathology.Multiregional analysis of florbetapir (18F-AV45)-PET data was used to determine individual amyloid distribution profiles in a sample of 667 participants from the Alzheimer's Disease Neuroimaging Initiative cohort, including cognitively normal older individuals (CN) as well as patients with mild cognitive impairment and Alzheimer disease (AD) dementia. The frequency of regional amyloid positivity across CN individuals was used to construct a 4-stage model of progressing amyloid pathology, and individual distribution profiles were used to evaluate the consistency of this hierarchical stage model across the full cohort.According to a 4-stage model, amyloid deposition begins in temporobasal and frontomedial areas, and successively affects the remaining associative neocortex, primary sensory-motor areas and the medial temporal lobe, and finally the striatum. Amyloid deposition in these brain regions showed a highly consistent hierarchical nesting across participants, where only 2% exhibited distribution profiles that deviated from the staging scheme. The earliest in vivo amyloid stages were mostly missed by conventional dichotomous classification approaches based on global florbetapir-PET signal, but were associated with significantly reduced CSF Aβ42 levels. Advanced in vivo amyloid stages were most frequent in patients with AD and correlated with cognitive impairment in individuals without dementia.The highly consistent regional hierarchy of PET-evidenced amyloid deposition across participants resembles neuropathologic observations and suggests a predictable regional sequence that may be used to stage an individual's progress of amyloid pathology in vivo.

Abstract Introduction The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI is a multisite, longitudinal, observational study that has collected many biomarkers since 2004. Recent publications highlight the multifactorial nature of late‐onset AD. We discuss selected topics that provide insights into AD progression and outline how this knowledge may improve clinical trials. Methods We used standard methods to identify nearly 600 publications using ADNI data from 2016 and 2017 (listed in Supplementary Material and searchable at http://adni.loni.usc.edu/news‐publications/publications/ ). Results (1) Data‐driven AD progression models supported multifactorial interactions rather than a linear cascade of events. (2) β‐Amyloid (Aβ) deposition occurred concurrently with functional connectivity changes within the default mode network in preclinical subjects and was followed by specific and progressive disconnection of functional and anatomical networks. (3) Changes in functional connectivity, volumetric measures, regional hypometabolism, and cognition were detectable at subthreshold levels of Aβ deposition. 4. Tau positron emission tomography imaging studies detailed a specific temporal and spatial pattern of tau pathology dependent on prior Aβ deposition, and related to subsequent cognitive decline. 5. Clustering studies using a wide range of modalities consistently identified a “typical AD” subgroup and a second subgroup characterized by executive impairment and widespread cortical atrophy in preclinical and prodromal subjects. 6. Vascular pathology burden may act through both Aβ dependent and independent mechanisms to exacerbate AD progression. 7. The APOE ε4 allele interacted with cerebrovascular disease to impede Aβ clearance mechanisms. 8. Genetic approaches identified novel genetic risk factors involving a wide range of processes, and demonstrated shared genetic risk for AD and vascular disorders, as well as the temporal and regional pathological associations of established AD risk alleles. 9. Knowledge of early pathological changes guided the development of novel prognostic biomarkers for preclinical subjects. 10. Placebo populations of randomized controlled clinical trials had highly variable trajectories of cognitive change, underscoring the importance of subject selection and monitoring. 11. Selection criteria based on Aβ positivity, hippocampal volume, baseline cognitive/functional measures, and APOE ε4 status in combination with improved cognitive outcome measures were projected to decrease clinical trial duration and cost. 12. Multiple concurrent therapies targeting vascular health and other AD pathology in addition to Aβ may be more effective than single therapies. Discussion ADNI publications from 2016 and 2017 supported the idea of AD as a multifactorial disease and provided insights into the complexities of AD disease progression. These findings guided the development of novel biomarkers and suggested that subject selection on the basis of multiple factors may lower AD clinical trial costs and duration. The use of multiple concurrent therapies in these trials may prove more effective in reversing AD disease progression.

Heightened distractibility in participants with ADHD as indexed by increased reaction time (RT) variability has been hypothesized to be due to a failure to sufficiently suppress activation in the default attention network during cognitively demanding situations. The present study utilized fMRI to examine the relationship between intra-individual variability (IIV) in task RT and suppression of BOLD response in regions of the default network, using a working memory paradigm and two levels of control tasks. IIV was calculated separately for thirteen healthy control and twelve children with ADHD, Combined Type. Children with ADHD displayed significantly more RT variability than controls. Neural measures showed that although both groups displayed a pattern of increasing deactivation of the medial prefrontal cortex (PFC) with increasing task difficulty, the ADHD group was significantly less deactive than controls. Correlations between IIV and brain activation suggested that greater variability was associated with a failure to deactivate ventromedial PFC with increasing task difficulty. T-tests on brain activation between participants with ADHD with low versus high IIV implicated a similar region so that high variability was associated with greater activity in this region. These data provide support for the theory that increased distractibility in at least some participants with ADHD may be due to an inability to sufficiently suppress activity in the default attention network in response to increasing task difficulty.

Abstract Introduction The overall goal of the Alzheimer's Disease Neuroimaging Initiative (ADNI) is to validate biomarkers for Alzheimer's disease (AD) clinical trials. ADNI‐3, which began on August 1, 2016, is a 5‐year renewal of the current ADNI‐2 study. Methods ADNI‐3 will follow current and additional subjects with normal cognition, mild cognitive impairment, and AD using innovative technologies such as tau imaging, magnetic resonance imaging sequences for connectivity analyses, and a highly automated immunoassay platform and mass spectroscopy approach for cerebrospinal fluid biomarker analysis. A Systems Biology/pathway approach will be used to identify genetic factors for subject selection/enrichment. Amyloid positron emission tomography scanning will be standardized using the Centiloid method. The Brain Health Registry will help recruit subjects and monitor subject cognition. Results Multimodal analyses will provide insight into AD pathophysiology and disease progression. Discussion ADNI‐3 will aim to inform AD treatment trials and facilitate development of AD disease‐modifying treatments.

Abstract White matter hyperintensities (WMHs) are frequently seen on brain magnetic resonance imaging scans of older people. Usually interpreted clinically as a surrogate for cerebral small vessel disease, WMHs are associated with increased likelihood of cognitive impairment and dementia (including Alzheimer's disease [AD]). WMHs are also seen in cognitively healthy people. In this collaboration of academic, clinical, and pharmaceutical industry perspectives, we identify outstanding questions about WMHs and their relation to cognition, dementia, and AD. What molecular and cellular changes underlie WMHs? What are the neuropathological correlates of WMHs? To what extent are demyelination and inflammation present? Is it helpful to subdivide into periventricular and subcortical WMHs? What do WMHs signify in people diagnosed with AD? What are the risk factors for developing WMHs? What preventive and therapeutic strategies target WMHs? Answering these questions will improve prevention and treatment of WMHs and dementia.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) is an ongoing, longitudinal, multicenter study designed to develop clinical, imaging, genetic, and biochemical biomarkers for the early detection and tracking of Alzheimer's disease (AD). The initial study, ADNI-1, enrolled 400 subjects with early mild cognitive impairment (MCI), 200 with early AD, and 200 cognitively normal elderly controls. ADNI-1 was extended by a 2-year Grand Opportunities grant in 2009 and by a competitive renewal, ADNI-2, which enrolled an additional 550 participants and will run until 2015. This article reviews all papers published since the inception of the initiative and summarizes the results to the end of 2013. The major accomplishments of ADNI have been as follows: (1) the development of standardized methods for clinical tests, magnetic resonance imaging (MRI), positron emission tomography (PET), and cerebrospinal fluid (CSF) biomarkers in a multicenter setting; (2) elucidation of the patterns and rates of change of imaging and CSF biomarker measurements in control subjects, MCI patients, and AD patients. CSF biomarkers are largely consistent with disease trajectories predicted by β-amyloid cascade (Hardy, J Alzheimer's Dis 2006;9(Suppl 3):151-3) and tau-mediated neurodegeneration hypotheses for AD, whereas brain atrophy and hypometabolism levels show predicted patterns but exhibit differing rates of change depending on region and disease severity; (3) the assessment of alternative methods of diagnostic categorization. Currently, the best classifiers select and combine optimum features from multiple modalities, including MRI, [(18)F]-fluorodeoxyglucose-PET, amyloid PET, CSF biomarkers, and clinical tests; (4) the development of blood biomarkers for AD as potentially noninvasive and low-cost alternatives to CSF biomarkers for AD diagnosis and the assessment of α-syn as an additional biomarker; (5) the development of methods for the early detection of AD. CSF biomarkers, β-amyloid 42 and tau, as well as amyloid PET may reflect the earliest steps in AD pathology in mildly symptomatic or even nonsymptomatic subjects and are leading candidates for the detection of AD in its preclinical stages; (6) the improvement of clinical trial efficiency through the identification of subjects most likely to undergo imminent future clinical decline and the use of more sensitive outcome measures to reduce sample sizes. Multimodal methods incorporating APOE status and longitudinal MRI proved most highly predictive of future decline. Refinements of clinical tests used as outcome measures such as clinical dementia rating-sum of boxes further reduced sample sizes; (7) the pioneering of genome-wide association studies that leverage quantitative imaging and biomarker phenotypes, including longitudinal data, to confirm recently identified loci, CR1, CLU, and PICALM and to identify novel AD risk loci; (8) worldwide impact through the establishment of ADNI-like programs in Japan, Australia, Argentina, Taiwan, China, Korea, Europe, and Italy; (9) understanding the biology and pathobiology of normal aging, MCI, and AD through integration of ADNI biomarker and clinical data to stimulate research that will resolve controversies about competing hypotheses on the etiopathogenesis of AD, thereby advancing efforts to find disease-modifying drugs for AD; and (10) the establishment of infrastructure to allow sharing of all raw and processed data without embargo to interested scientific investigators throughout the world.

Brain iron elevation is implicated in Alzheimer's disease (AD) pathogenesis, but the impact of iron on disease outcomes has not been previously explored in a longitudinal study. Ferritin is the major iron storage protein of the body; by using cerebrospinal fluid (CSF) levels of ferritin as an index, we explored whether brain iron status impacts longitudinal outcomes in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. We show that baseline CSF ferritin levels were negatively associated with cognitive performance over 7 years in 91 cognitively normal, 144 mild cognitive impairment (MCI) and 67 AD subjects, and predicted MCI conversion to AD. Ferritin was strongly associated with CSF apolipoprotein E levels and was elevated by the Alzheimer's risk allele, APOE-ɛ4. These findings reveal that elevated brain iron adversely impacts on AD progression, and introduce brain iron elevation as a possible mechanism for APOE-ɛ4 being the major genetic risk factor for AD.

Abstract There is considerable debate whether Alzheimer’s disease (AD) originates in basal forebrain or entorhinal cortex. Here we examined whether longitudinal decreases in basal forebrain and entorhinal cortex grey matter volume were interdependent and sequential. In a large cohort of age-matched older adults ranging from cognitively normal to AD, we demonstrate that basal forebrain volume predicts longitudinal entorhinal degeneration. Models of parallel degeneration or entorhinal origin received negligible support. We then integrated volumetric measures with an amyloid biomarker sensitive to pre-symptomatic AD pathology. Comparison between cognitively matched normal adult subgroups, delineated according to the amyloid biomarker, revealed abnormal degeneration in basal forebrain, but not entorhinal cortex. Abnormal degeneration in both basal forebrain and entorhinal cortex was only observed among prodromal (mildly amnestic) individuals. We provide evidence that basal forebrain pathology precedes and predicts both entorhinal pathology and memory impairment, challenging the widely held belief that AD has a cortical origin.

A recently identified variant within the fat mass and obesity-associated (FTO) gene is carried by 46% of Western Europeans and is associated with an approximately 1.2 kg higher weight, on average, in adults and an approximately 1 cm greater waist circumference. With >1 billion overweight and 300 million obese persons worldwide, it is crucial to understand the implications of carrying this very common allele for the health of our aging population. FTO is highly expressed in the brain and elevated body mass index (BMI) is associated with brain atrophy, but it is unknown how the obesity-associated risk allele affects human brain structure. We therefore generated 3D maps of regional brain volume differences in 206 healthy elderly subjects scanned with MRI and genotyped as part of the Alzheimer's Disease Neuroimaging Initiative. We found a pattern of systematic brain volume deficits in carriers of the obesity-associated risk allele versus noncarriers. Relative to structure volumes in the mean template, FTO risk allele carriers versus noncarriers had an average brain volume difference of approximately 8% in the frontal lobes and 12% in the occipital lobes-these regions also showed significant volume deficits in subjects with higher BMI. These brain differences were not attributable to differences in cholesterol levels, hypertension, or the volume of white matter hyperintensities; which were not detectably higher in FTO risk allele carriers versus noncarriers. These brain maps reveal that a commonly carried susceptibility allele for obesity is associated with structural brain atrophy, with implications for the health of the elderly.

Atrophic changes in early Alzheimer's disease (AD) and amnestic mild cognitive impairment (MCI) have been proposed as biomarkers for detection and monitoring. We analyzed magnetic resonance imaging (MRI) atrophy rate from baseline to 1 year in 4 groups of participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI): AD (n = 152), converters from MCI to probable AD (MCI-C, n = 60), stable MCI (MCI-S, n = 261), and healthy controls (HC, n = 200). Scans were analyzed using multiple methods, including voxel-based morphometry (VBM), regions of interest (ROIs), and automated parcellation, permitting comparison of annual percent change (APC) in neurodegeneration markers. Effect sizes and the sample required to detect 25% reduction in atrophy rates were calculated. The influence of APOE genotype on APC was also evaluated. AD patients and converters from MCI to probable AD demonstrated high atrophy APCs across regions compared with minimal change in healthy controls. Stable MCI subjects showed intermediate atrophy rates. APOE genotype was associated with APC in key regions. In sum, APC rates are influenced by APOE genotype, imminent MCI to AD conversion, and AD-related neurodegeneration.

Alzheimer's Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1-3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) has continued development and standardization of methodologies for biomarkers and has provided an increased depth and breadth of data available to qualified researchers. This review summarizes the over 400 publications using ADNI data during 2014 and 2015.We used standard searches to find publications using ADNI data.(1) Structural and functional changes, including subtle changes to hippocampal shape and texture, atrophy in areas outside of hippocampus, and disruption to functional networks, are detectable in presymptomatic subjects before hippocampal atrophy; (2) In subjects with abnormal β-amyloid deposition (Aβ+), biomarkers become abnormal in the order predicted by the amyloid cascade hypothesis; (3) Cognitive decline is more closely linked to tau than Aβ deposition; (4) Cerebrovascular risk factors may interact with Aβ to increase white-matter (WM) abnormalities which may accelerate Alzheimer's disease (AD) progression in conjunction with tau abnormalities; (5) Different patterns of atrophy are associated with impairment of memory and executive function and may underlie psychiatric symptoms; (6) Structural, functional, and metabolic network connectivities are disrupted as AD progresses. Models of prion-like spreading of Aβ pathology along WM tracts predict known patterns of cortical Aβ deposition and declines in glucose metabolism; (7) New AD risk and protective gene loci have been identified using biologically informed approaches; (8) Cognitively normal and mild cognitive impairment (MCI) subjects are heterogeneous and include groups typified not only by "classic" AD pathology but also by normal biomarkers, accelerated decline, and suspected non-Alzheimer's pathology; (9) Selection of subjects at risk of imminent decline on the basis of one or more pathologies improves the power of clinical trials; (10) Sensitivity of cognitive outcome measures to early changes in cognition has been improved and surrogate outcome measures using longitudinal structural magnetic resonance imaging may further reduce clinical trial cost and duration; (11) Advances in machine learning techniques such as neural networks have improved diagnostic and prognostic accuracy especially in challenges involving MCI subjects; and (12) Network connectivity measures and genetic variants show promise in multimodal classification and some classifiers using single modalities are rivaling multimodal classifiers.Taken together, these studies fundamentally deepen our understanding of AD progression and its underlying genetic basis, which in turn informs and improves clinical trial design.

The epsilon4 allele of the apolipoprotein E (APOE) gene is the major genetic risk factor for Alzheimer's disease (AD), but limited work has suggested that APOE genotype may modulate disease phenotype. Carriers of the epsilon4 allele have been reported to have greater medial temporal lobe (MTL) pathology and poorer memory than noncarriers. Less attention has focused on whether there are domains of cognition and neuroanatomical regions more affected in noncarriers. Further, a major potential confound of prior in vivo studies is the possibility of different rates of clinical misdiagnosis for carriers vs. noncarriers. We compared phenotypic differences in cognition and topography of regional cortical atrophy of epsilon4 carriers (n = 67) vs. noncarriers (n = 24) with mild AD from the Alzheimer's Disease Neuroimaging Initiative, restricted to those with a cerebrospinal fluid (CSF) molecular profile consistent with AD. Between-group comparisons were made for psychometric tests and morphometric measures of cortical thickness and hippocampal volume. Carriers displayed significantly greater impairment on measures of memory retention, whereas noncarriers were more impaired on tests of working memory, executive control, and lexical access. Consistent with this cognitive dissociation, carriers exhibited greater MTL atrophy, whereas noncarriers had greater frontoparietal atrophy. Performance deficits in particular cognitive domains were associated with disproportionate regional brain atrophy within nodes of cortical networks thought to subserve these cognitive processes. These convergent cognitive and neuroanatomic findings in individuals with a CSF molecular profile consistent with AD support the hypothesis that APOE genotype modulates the clinical phenotype of AD through influence on specific large-scale brain networks.

Abstract Alzheimer’s disease (AD) is a progressive neurodegenerative condition marked by a decline in cognitive functions with no validated disease modifying treatment. It is critical for timely treatment to detect AD in its earlier stage before clinical manifestation. Mild cognitive impairment (MCI) is an intermediate stage between cognitively normal older adults and AD. To predict conversion from MCI to probable AD, we applied a deep learning approach, multimodal recurrent neural network. We developed an integrative framework that combines not only cross-sectional neuroimaging biomarkers at baseline but also longitudinal cerebrospinal fluid (CSF) and cognitive performance biomarkers obtained from the Alzheimer’s Disease Neuroimaging Initiative cohort (ADNI). The proposed framework integrated longitudinal multi-domain data. Our results showed that 1) our prediction model for MCI conversion to AD yielded up to 75% accuracy (area under the curve (AUC) = 0.83) when using only single modality of data separately; and 2) our prediction model achieved the best performance with 81% accuracy (AUC = 0.86) when incorporating longitudinal multi-domain data. A multi-modal deep learning approach has potential to identify persons at risk of developing AD who might benefit most from a clinical trial or as a stratification approach within clinical trials.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) was established in 2004 to facilitate the development of effective treatments for Alzheimer's disease (AD) by validating biomarkers for AD clinical trials.We searched for ADNI publications using established methods.ADNI has (1) developed standardized biomarkers for use in clinical trial subject selection and as surrogate outcome measures; (2) standardized protocols for use across multiple centers; (3) initiated worldwide ADNI; (4) inspired initiatives investigating traumatic brain injury and post-traumatic stress disorder in military populations, and depression, respectively, as an AD risk factor; (5) acted as a data-sharing model; (6) generated data used in over 600 publications, leading to the identification of novel AD risk alleles, and an understanding of the relationship between biomarkers and AD progression; and (7) inspired other public-private partnerships developing biomarkers for Parkinson's disease and multiple sclerosis.ADNI has made myriad impacts in its first decade. A competitive renewal of the project in 2015 would see the use of newly developed tau imaging ligands, and the continued development of recruitment strategies and outcome measures for clinical trials.

Abstract In Alzheimer’s diseases (AD), tau pathology is strongly associated with cognitive decline. Preclinical evidence suggests that tau spreads across connected neurons in an activity-dependent manner. Supporting this, cross-sectional AD studies show that tau deposition patterns resemble functional brain networks. However, whether higher functional connectivity is associated with higher rates of tau accumulation is unclear. Here, we combine resting-state fMRI with longitudinal tau-PET in two independent samples including 53 (ADNI) and 41 (BioFINDER) amyloid-biomarker defined AD subjects and 28 (ADNI) vs. 16 (BioFINDER) amyloid-negative healthy controls. In both samples, AD subjects show faster tau accumulation than controls. Second, in AD, higher fMRI-assessed connectivity between 400 regions of interest (ROIs) is associated with correlated tau-PET accumulation in corresponding ROIs. Third, we show that a model including baseline connectivity and tau-PET is associated with future tau-PET accumulation. Together, connectivity is associated with tau spread in AD, supporting the view of transneuronal tau propagation.

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.

<h3>Importance</h3> Vitamin D (VitD) deficiency is associated with brain structural abnormalities, cognitive decline, and incident dementia. <h3>Objective</h3> To assess associations between VitD status and trajectories of change in subdomains of cognitive function in a cohort of ethnically diverse older adults. <h3>Design, Setting, and Participants</h3> Longitudinal multiethnic cohort study of 382 participants in an outpatient clinic enrolled between February 2002 and August 2010 with baseline assessment and yearly follow-up visits. Serum 25-hydroxyvitamin D (25-OHD) was measured, with VitD status defined as the following: deficient, less than 12 ng/mL (to convert to nanomoles per liter, multiply by 2.496); insufficient, 12 to less than 20 ng/mL; adequate, 20 to less than 50 ng/mL; or high, 50 ng/mL or higher. Subdomains of cognitive function were assessed using the Spanish and English Neuropsychological Assessment Scales. Associations were evaluated between 25-OHD levels (as continuous and categorical [deficient, insufficient, or adequate]) and trajectories of cognitive decline. <h3>Main Outcomes and Measures</h3> Serum 25-OHD levels, cognitive function, and associations between 25-OHD levels and trajectories of cognitive decline. <h3>Results</h3> Participants (N = 382 at baseline) had a mean (SD) age of 75.5 (7.0) years; 61.8% were women; and 41.4% were white, 29.6% African American, 25.1% Hispanic, and 3.9% other race/ethnicity. Diagnosis at enrollment included 17.5% with dementia, 32.7% with mild cognitive impairment, and 49.5% cognitively normal. The mean (SD) 25-OHD level was 19.2 (11.7) ng/mL, with 26.2% of participants being VitD deficient and 35.1% insufficient. The mean (SD) 25-OHD levels were significantly lower for African American and Hispanic participants compared with white participants (17.9 [15.8] and 17.2 [8.4] vs 21.7 [10.0] ng/mL, respectively;<i>P</i> &lt; .001 for both). The mean (SD) 25-OHD levels were similarly lower in the dementia group compared with the mild cognitive impairment and cognitively normal groups (16.2 [9.4] vs 20.0 [10.3] and 19.7 [13.1] ng/mL, respectively;<i>P</i> = .006). The mean (SD) follow-up was 4.8 (2.5) years. Rates of decline in episodic memory and executive function among VitD-deficient (episodic memory: β = −0.04 [SE = 0.02],<i>P</i> = .049; executive function: β = −0.05 [SE = 0.02],<i>P</i> = .01) and VitD-insufficient (episodic memory: β = −0.06 [SE = 0.02],<i>P</i> &lt; .001; executive function: β = −0.04 [SE = 0.02],<i>P</i> = .008) participants were greater than those with adequate status after controlling for age, sex, education, ethnicity, body mass index, season of blood draw, vascular risk, and apolipoprotein E4 genotype. Vitamin D status was not significantly associated with decline in semantic memory or visuospatial ability. Exclusion of participants with dementia did not substantially affect the associations between VitD status and rates of cognitive decline. <h3>Conclusions and Relevance</h3> Low VitD status was associated with accelerated decline in cognitive function domains in ethnically diverse older adults, including African American and Hispanic individuals who exhibited a high prevalence of VitD insufficiency or deficiency. It remains to be determined whether VitD supplementation slows cognitive decline.

Patients with Alzheimer's disease have reduced cerebral blood flow measured by arterial spin labelling magnetic resonance imaging, but it is unclear how this is related to amyloid-β pathology. Using 182 subjects from the Alzheimer's Disease Neuroimaging Initiative we tested associations of amyloid-β with regional cerebral blood flow in healthy controls (n = 51), early (n = 66) and late (n = 41) mild cognitive impairment, and Alzheimer's disease with dementia (n = 24). Based on the theory that Alzheimer's disease starts with amyloid-β accumulation and progresses with symptoms and secondary pathologies in different trajectories, we tested if cerebral blood flow differed between amyloid-β-negative controls and -positive subjects in different diagnostic groups, and if amyloid-β had different associations with cerebral blood flow and grey matter volume. Global amyloid-β load was measured by florbetapir positron emission tomography, and regional blood flow and volume were measured in eight a priori defined regions of interest. Cerebral blood flow was reduced in patients with dementia in most brain regions. Higher amyloid-β load was related to lower cerebral blood flow in several regions, independent of diagnostic group. When comparing amyloid-β-positive subjects with -negative controls, we found reductions of cerebral blood flow in several diagnostic groups, including in precuneus, entorhinal cortex and hippocampus (dementia), inferior parietal cortex (late mild cognitive impairment and dementia), and inferior temporal cortex (early and late mild cognitive impairment and dementia). The associations of amyloid-β with cerebral blood flow and volume differed across the disease spectrum, with high amyloid-β being associated with greater cerebral blood flow reduction in controls and greater volume reduction in late mild cognitive impairment and dementia. In addition to disease stage, amyloid-β pathology affects cerebral blood flow across the span from controls to dementia patients. Amyloid-β pathology has different associations with cerebral blood flow and volume, and may cause more loss of blood flow in early stages, whereas volume loss dominates in late disease stages.

This study assessed apolipoprotein E (APOE) ε4 carrier status effects on Alzheimer's disease imaging and cerebrospinal fluid (CSF) biomarkers in cognitively normal older adults with significant memory concerns (SMC).Cognitively normal, SMC, and early mild cognitive impairment participants from Alzheimer's Disease Neuroimaging Initiative were divided by APOE ε4 carrier status. Diagnostic and APOE effects were evaluated with emphasis on SMC. Additional analyses in SMC evaluated the effect of the interaction between APOE and [(18)F]Florbetapir amyloid positivity on CSF biomarkers.SMC ε4+ showed greater amyloid deposition than SMC ε4-, but no hypometabolism or medial temporal lobe (MTL) atrophy. SMC ε4+ showed lower amyloid beta 1-42 and higher tau/p-tau than ε4-, which was most abnormal in APOE ε4+ and cerebral amyloid positive SMC.SMC APOE ε4+ show abnormal changes in amyloid and tau biomarkers, but no hypometabolism or MTL neurodegeneration, reflecting the at-risk nature of the SMC group and the importance of APOE in mediating this risk.

To examine associations between aggregate genetic risk and Alzheimer disease (AD) markers in stages preceding the clinical symptoms of dementia using data from 2 large observational cohort studies.We computed polygenic risk scores (PGRS) using summary statistics from the International Genomics of Alzheimer's Project genome-wide association study of AD. Associations between PGRS and AD markers (cognitive decline, clinical progression, hippocampus volume, and β-amyloid) were assessed within older participants with dementia. Associations between PGRS and hippocampus volume were additionally examined within healthy younger participants (age 18-35 years).Within participants without dementia, elevated PGRS was associated with worse memory (p = 0.002) and smaller hippocampus (p = 0.002) at baseline, as well as greater longitudinal cognitive decline (memory: p = 0.0005, executive function: p = 0.01) and clinical progression (p < 0.00001). High PGRS was associated with AD-like levels of β-amyloid burden as measured with florbetapir PET (p = 0.03) but did not reach statistical significance for CSF β-amyloid (p = 0.11). Within the younger group, higher PGRS was associated with smaller hippocampus volume (p = 0.05). This pattern was evident when examining a PGRS that included many loci below the genome-wide association study (GWAS)-level significance threshold (16,123 single nucleotide polymorphisms), but not when PGRS was restricted to GWAS-level significant loci (18 single nucleotide polymorphisms).Effects related to common genetic risk loci distributed throughout the genome are detectable among individuals without dementia. The influence of this genetic risk may begin in early life and make an individual more susceptible to cognitive impairment in late life. Future refinement of polygenic risk scores may help identify individuals at risk for AD dementia.

Significance Alzheimer’s disease (AD) affects 10% of the elderly population. The disease remains poorly understood with no cure. The main symptom is memory loss, but other symptoms might include impaired executive function (ability to plan and accomplish goals; e.g., grocery shopping). The severity of behavioral symptoms and brain atrophy (gray matter loss) can vary widely across patients. This variability complicates diagnosis, treatment, and prevention. A mathematical model reveals distinct brain atrophy patterns, explaining variation in gray matter loss among AD dementia patients. The atrophy patterns can also explain variation in memory and executive function decline among dementia patients and at-risk nondemented participants. This model can potentially be applied to understand brain disorders with varying symptoms, including autism and schizophrenia.

Abstract Neuropathologists assess vast brain areas to identify diverse and subtly-differentiated morphologies. Standard semi-quantitative scoring approaches, however, are coarse-grained and lack precise neuroanatomic localization. We report a proof-of-concept deep learning pipeline that identifies specific neuropathologies—amyloid plaques and cerebral amyloid angiopathy—in immunohistochemically-stained archival slides. Using automated segmentation of stained objects and a cloud-based interface, we annotate &gt; 70,000 plaque candidates from 43 whole slide images (WSIs) to train and evaluate convolutional neural networks. Networks achieve strong plaque classification on a 10-WSI hold-out set (0.993 and 0.743 areas under the receiver operating characteristic and precision recall curve, respectively). Prediction confidence maps visualize morphology distributions at high resolution. Resulting network-derived amyloid beta (Aβ)-burden scores correlate well with established semi-quantitative scores on a 30-WSI blinded hold-out. Finally, saliency mapping demonstrates that networks learn patterns agreeing with accepted pathologic features. This scalable means to augment a neuropathologist’s ability suggests a route to neuropathologic deep phenotyping.

Late-life depression (LLD) is characterized by considerable heterogeneity in clinical manifestation. Unraveling such heterogeneity might aid in elucidating etiological mechanisms and support precision and individualized medicine.To cross-sectionally and longitudinally delineate disease-related heterogeneity in LLD associated with neuroanatomy, cognitive functioning, clinical symptoms, and genetic profiles.The Imaging-Based Coordinate System for Aging and Neurodegenerative Diseases (iSTAGING) study is an international multicenter consortium investigating brain aging in pooled and harmonized data from 13 studies with more than 35 000 participants, including a subset of individuals with major depressive disorder. Multimodal data from a multicenter sample (N = 996), including neuroimaging, neurocognitive assessments, and genetics, were analyzed in this study. A semisupervised clustering method (heterogeneity through discriminative analysis) was applied to regional gray matter (GM) brain volumes to derive dimensional representations. Data were collected from July 2017 to July 2020 and analyzed from July 2020 to December 2021.Two dimensions were identified to delineate LLD-associated heterogeneity in voxelwise GM maps, white matter (WM) fractional anisotropy, neurocognitive functioning, clinical phenotype, and genetics.A total of 501 participants with LLD (mean [SD] age, 67.39 [5.56] years; 332 women) and 495 healthy control individuals (mean [SD] age, 66.53 [5.16] years; 333 women) were included. Patients in dimension 1 demonstrated relatively preserved brain anatomy without WM disruptions relative to healthy control individuals. In contrast, patients in dimension 2 showed widespread brain atrophy and WM integrity disruptions, along with cognitive impairment and higher depression severity. Moreover, 1 de novo independent genetic variant (rs13120336; chromosome: 4, 186387714; minor allele, G) was significantly associated with dimension 1 (odds ratio, 2.35; SE, 0.15; P = 3.14 ×108) but not with dimension 2. The 2 dimensions demonstrated significant single-nucleotide variant-based heritability of 18% to 27% within the general population (N = 12 518 in UK Biobank). In a subset of individuals having longitudinal measurements, those in dimension 2 experienced a more rapid longitudinal change in GM and brain age (Cohen f2 = 0.03; P = .02) and were more likely to progress to Alzheimer disease (Cohen f2 = 0.03; P = .03) compared with those in dimension 1 (N = 1431 participants and 7224 scans from the Alzheimer's Disease Neuroimaging Initiative [ADNI], Baltimore Longitudinal Study of Aging [BLSA], and Biomarkers for Older Controls at Risk for Dementia [BIOCARD] data sets).This study characterized heterogeneity in LLD into 2 dimensions with distinct neuroanatomical, cognitive, clinical, and genetic profiles. This dimensional approach provides a potential mechanism for investigating the heterogeneity of LLD and the relevance of the latent dimensions to possible disease mechanisms, clinical outcomes, and responses to interventions.

For optimal design of anti-amyloid-β (Aβ) and anti-tau clinical trials, we need to better understand the pathophysiological cascade of Aβ- and tau-related processes. Therefore, we set out to investigate how Aβ and soluble phosphorylated tau (p-tau) relate to the accumulation of tau aggregates assessed with PET and subsequent cognitive decline across the Alzheimer's disease (AD) continuum. Using human cross-sectional and longitudinal neuroimaging and cognitive assessment data, we show that in early stages of AD, increased concentration of soluble CSF p-tau is strongly associated with accumulation of insoluble tau aggregates across the brain, and CSF p-tau levels mediate the effect of Aβ on tau aggregation. Further, higher soluble p-tau concentrations are mainly related to faster accumulation of tau aggregates in the regions with strong functional connectivity to individual tau epicenters. In this early stage, higher soluble p-tau concentrations is associated with cognitive decline, which is mediated by faster increase of tau aggregates. In contrast, in AD dementia, when Aβ fibrils and soluble p-tau levels have plateaued, cognitive decline is related to the accumulation rate of insoluble tau aggregates. Our data suggest that therapeutic approaches reducing soluble p-tau levels might be most favorable in early AD, before widespread insoluble tau aggregates.

The gap between chronological age (CA) and biological brain age, as estimated from magnetic resonance images (MRIs), reflects how individual patterns of neuroanatomic aging deviate from their typical trajectories. MRI-derived brain age (BA) estimates are often obtained using deep learning models that may perform relatively poorly on new data or that lack neuroanatomic interpretability. This study introduces a convolutional neural network (CNN) to estimate BA after training on the MRIs of 4,681 cognitively normal (CN) participants and testing on 1,170 CN participants from an independent sample. BA estimation errors are notably lower than those of previous studies. At both individual and cohort levels, the CNN provides detailed anatomic maps of brain aging patterns that reveal sex dimorphisms and neurocognitive trajectories in adults with mild cognitive impairment (MCI, N = 351) and Alzheimer’s disease (AD, N = 359). In individuals with MCI (54% of whom were diagnosed with dementia within 10.9 y from MRI acquisition), BA is significantly better than CA in capturing dementia symptom severity, functional disability, and executive function. Profiles of sex dimorphism and lateralization in brain aging also map onto patterns of neuroanatomic change that reflect cognitive decline. Significant associations between BA and neurocognitive measures suggest that the proposed framework can map, systematically, the relationship between aging-related neuroanatomy changes in CN individuals and in participants with MCI or AD. Early identification of such neuroanatomy changes can help to screen individuals according to their AD risk.

Oxidative stress may play a role in neurologic disease. The present study examined the relation between use of vitamin E and vitamin C and incident Alzheimer disease in a prospective study of 633 persons 65 years and older. A stratified random sample was selected from a disease-free population. At baseline, all vitamin supplements taken in the previous 2 weeks were identified by direct inspection. After an average follow-up period of 4.3 years, 91 of the sample participants with vitamin information met accepted criteria for the clinical diagnosis of Alzheimer disease. None of the 27 vitamin E supplement users had Alzheimer disease compared with 3.9 predicted based on the crude observed incidence among nonusers (p = 0.04) and 2.5 predicted based on age, sex, years of education, and length of follow-up interval (p = 0.23). None of the 23 vitamin C supplement users had Alzheimer disease compared with 3.3 predicted based on the crude observed incidence among nonusers (p = 0.10) and 3.2 predicted adjusted for age, sex, education, and follow-up interval (p = 0.04). There was no relation between Alzheimer disease and use of multivitamins. These data suggest that use of the higher-dose vitamin E and vitamin C supplements may lower the risk of Alzheimer disease.

A standardized antiviral drug susceptibility assay for clinical human immunodeficiency virus type 1 (HIV-1) isolates has been developed for use in clinical trials. The protocol is a two-step procedure that first involves cocultivation of patient infected peripheral blood mononuclear cells (PBMC) with seronegative phytohemagglutinin-stimulated donor PBMC to obtain an HIV-1 stock. The virus stock is titrated for viral infectivity (50% tissue culture infective dose) by use of serial fourfold virus dilutions in donor PBMC. A standardized inoculum of 1,000 50% tissue culture infective doses per 10(6) cells is used in the second step of the procedure to acutely infect seronegative donor PBMC in a 7-day microtiter plate assay with triplicate wells containing zidovudine (ZDV) concentrations ranging from 0 to 5.0 microM. The ZDV 50% inhibitory concentrations (IC50) for reference ZDV-susceptible and ZDV-resistant HIV-1 isolates ranged from 0.002 to 0.113 microM and from 0.15 to &gt; 5.0 microM, respectively. Use of this consensus protocol reduced interlaboratory variability for ZDV IC50 determinations with reference HIV-1 isolates. Among eight laboratories, the coefficient of variation ranged from 0.85 to 1.25 with different PBMC protocols and was reduced to 0.39 to 0.98 with the standardized assay. Among the clinical HIV-1 isolates assayed by the standardized drug susceptibility assay, the median ZDV IC50 increased gradually with more ZDV therapy. This protocol provides an efficient and reproducible means to assess the in vitro susceptibility to antiretroviral agents of virtually all clinical HIV-1 isolates.

In a community population of persons over the age of 65, cognitive function was assessed using brief performance tests on two occasions 3 years apart. Those with fewer years of formal education consistently had greater declines in cognitive function, independently of age, birthplace, language of interview, occupation, and income. These prospective findings suggest that low educational attainment or a correlate predicts cognitive decline. It is not clear, however, whether this relation represents a direct effect of education on future cognition, whether education might be related to occurrence of a disease leading to cognitive decline in older persons, or whether education might be a surrogate for some variable not included in the study.

<b>Objective: </b> To examine how baseline and change of volumetric MRI relate to cognitive decline in older individuals. <b>Background: </b> Memory is associated with hippocampal integrity, whereas executive function has been linked to impaired frontal lobe function. Previous studies have shown that hippocampal and cortical atrophy are more strongly related to cognition than are measures of subcortical cerebrovascular disease (CVD). The authors hypothesized that memory (MEM) decline would be related to change in hippocampal volume (HC), whereas decline in executive function (EXEC) would be related to change of cortical gray matter volume (CGM) and measures of subcortical CVD. <b>Methods: </b> Subjects from a multicenter study (n = 103) included cognitively normal, mildly impaired, and demented cases with and without subcortical lacunes. All had longitudinal cognitive evaluation (mean = 4.8 years) and two or more MRI scans at least one year apart (mean = 3.4 years). MRI measures included HC, CGM, total lacune volume (LAC), and white matter hyperintensity volume (WMH). Random effects modeling of longitudinal data assessed effects of MRI baseline and MRI change on baseline and change of psychometrically matched measures of MEM and EXEC. <b>Results: </b> Change in MEM was related to HC baseline and HC change. Change in EXEC was related to baseline CGM and to change in CGM, HC, and LAC. Results were unchanged when demented cases were excluded. WMH was not associated with change in MEM or EXEC independent of HC, CGM, and LAC. <b>Conclusion: </b> Hippocampal volume was the primary determinant of memory decline, whereas executive function (EXEC) decline was related to multiple brain components. Results support a hypothesis that MEM decline is strongly influenced by Alzheimer disease (AD), whereas EXEC decline may be complexly determined by cerebrovascular disease and AD.

A large proportion of people with Alzheimer's disease (AD) are women; however, it is not clear whether this is due to higher risk of disease or solely to the larger number of women alive at ages when AD is common. Beginning in 1982, two stratified random samples of people aged > or =65 years in East Boston, Massachusetts underwent detailed, structured clinical evaluation for prevalent (467 people) and incident (642 people from a cohort previously ascertained to be disease-free) probable AD. The prevalence sample was followed for mortality for up to 11 years (through December 1992). The age-specific incidence of AD did not differ significantly by sex (for men vs. women, odds ratio = 0.92; 95% confidence interval (CI): 0.51, 1.67). Controlled for age, prevalence also did not differ significantly by sex (for men vs. women, odds ratio = 1.29; 95% CI: 0.67, 2.48). The increase in risk of mortality due to AD did not vary by sex. The odds ratio for women with AD compared with women without AD was 2.07 (95% CI: 1.21, 3.56). For men, the odds ratio was 2.22 (95% CI: 1.02, 4.81). These findings suggest that the excess number of women with AD is due to the longer life expectancy of women rather than sex-specific risk factors for the disease.

Change in self-reported physical function was examined using baseline and 5 years of follow-up data between 1982 and 1991 from the four Established Populations for Epidemiologic Studies of the Elderly studies. In East Boston, Massachusetts (n = 3,809), Iowa and Washington Counties, Iowa (n = 3,673), New Haven, Connecticut (n = 2,812), and North Carolina (n = 4,163), noninstitutionalized persons aged 65 years and older were asked a series of questions to assess their physical function: a modified Katz Activities of Daily Living (ADL) scale, three items from the Rosow-Breslau Functional Health Scale, and questions on physical performance, adapted from Nagi, as well as information on demographic, social, and health characteristics. Longitudinal statistical analyses (random effects and Markov transition models) were used to evaluate improvement, stability, and deterioration in functional ability at both an individual and a population level over multiple years of data. The average decline in physical function associated with age was found to be greater than previous cross-sectional studies have suggested, and the rate of decline increased with increasing age. Considerable individual variation was evident. Although many people experienced declines, a smaller but substantial portion experienced recovery. Women reported a greater rate of decline in physical function and were less likely to recover from disability.

Journal Article Acute Delirium and Functional Decline in the Hospitalized Elderly Patient Get access Anne M. Murray, Anne M. Murray 1North Central Health Care FacilitiesWausau, Wisconsin, and Institute on Aging and Adult Life, University of Wisconsin-Madison Search for other works by this author on: Oxford Academic PubMed Google Scholar Sue E. Levkoff, Sue E. Levkoff 2Division on Aging, Harvard Medical SchoolBoston, Massachusetts Search for other works by this author on: Oxford Academic PubMed Google Scholar Terrie T. Wetle, Terrie T. Wetle 3Braceland Center for Mental Health and Aging, Institute of LivingHartford, Connecticut Search for other works by this author on: Oxford Academic PubMed Google Scholar Laurel Beckett, Laurel Beckett 4Center for Research on Health and Aging, Rush-Presbyterian-St. Luke's Medical CenterChicago Search for other works by this author on: Oxford Academic PubMed Google Scholar Paul D. Cleary, Paul D. Cleary 2Division on Aging, Harvard Medical SchoolBoston, Massachusetts Search for other works by this author on: Oxford Academic PubMed Google Scholar Joshua D. Schor, Joshua D. Schor 5Newark-Beth Israel Medical CenterNewark, New Jersey Search for other works by this author on: Oxford Academic PubMed Google Scholar Lewis A. Lipsitz, Lewis A. Lipsitz 6Hebrew Rehabilitation Center for AgedBoston, Massachusetts Search for other works by this author on: Oxford Academic PubMed Google Scholar John W. Rowe, John W. Rowe 7Mount Sinai Medical CenterNew York Search for other works by this author on: Oxford Academic PubMed Google Scholar Denis A. Evans Denis A. Evans 4Center for Research on Health and Aging, Rush-Presbyterian-St. Luke's Medical CenterChicago Search for other works by this author on: Oxford Academic PubMed Google Scholar Journal of Gerontology, Volume 48, Issue 5, September 1993, Pages M181–M186, https://doi.org/10.1093/geronj/48.5.M181 Published: 01 September 1993 Article history Received: 28 August 1992 Accepted: 15 February 1993 Published: 01 September 1993

When activated, the serine/threonine kinase AKT mediates an antiapoptotic signal implicated in chemoresistance of various cancers. The mechanism(s) of AKT activation are unknown, though overexpression of HER-2/neu has been implicated in breast cancer. Therefore, we determined the incidence of activated AKT in human pancreatic cancer, whether HER-2/neu is involved in AKT activation, and if AKT activation is associated with biologic behaviour. HER-2/neu expression and AKT activation were examined in seven pancreatic cancer cell lines by Western blotting. The in vitro effect of HER-2/neu inhibition on AKT activation was similarly determined. Finally, 78 pancreatic cancer specimens were examined for AKT activation and HER-2/neu overexpression, and correlated with the clinical prognostic variable of histologic grade. HER-2/neu was overexpressed in two of seven cell lines; these two cell lines demonstrated the highest level of AKT activation. Inhibition of HER-2/neu reduced AKT activation in vitro. AKT was activated in 46 out of 78 (59%) of the pancreatic cancers; HER-2/neu overexpression correlated with AKT activation (P=0.015). Furthermore, AKT activation was correlated with higher histologic tumour grade (P=0.047). Thus, it is concluded that AKT is frequently activated in pancreatic cancer; this antiapoptotic signal may be mediated by HER-2/neu overexpression. AKT activation is associated with tumour grade, an important prognostic factor.

The deposition of beta-amyloid within the entorhinal cortex (EC) may play a key role in the development of mild cognitive impairment (MCI) in the elderly. To examine the relationship of beta-amyloid deposition to MCI, EC tissue immunostained for this protein was quantitated from a cohort of aged Catholic religious clergy with a clinical diagnosis of MCI and compared to those with no cognitive impairment (NCI) and Alzheimer's disease (AD). beta-amyloid staining was seen in 12 of the 20 NCI, in 10 of 12 MCI, and in all 12 AD cases within the EC. beta-amyloid immunoreactivity displayed two patterns within the EC: (1) a crescent-shaped band within layers 3-4 or (2) bilaminar staining mainly within layers 2-3 and 5-6. Ten cases failed to display any detectable beta-amyloid imunoreactivity. Despite the heterogeneity of beta-amyloid loads within the clinical groups, decomposing an analysis of variance revealed a significant difference across groups in mean beta-amyloid load within the EC based upon a linear trend analysis. Multiple comparisons testing revealed that NCI individuals had a significantly lower mean beta-amyloid load (1.32) than AD individuals (4.55). The MCI individuals had a mean intermediate (2.60) load between NCI and AD, but not statistically distinguishable from the mean for either NCI or AD. Spearman rank correlation showed a trend for decreasing MMSE with increasing amyloid load that failed to reach statistical significance. Since many NCI cases displayed beta-amyloid loads equal to or greater than that seen in some MCI and some AD cases, it is mostly likely that deposition of this protein is not the sole pathogenic event underlying cognitive impairment in the elderly.

There is considerable evidence that social networks are strongly related to survival and other health outcomes. However, findings regarding the effect of social networks on disability outcomes have been inconsistent. This study examines this relationship with respect to the risk of developing disability and recovering from disability.Data come from a community-based sample of the New Haven population aged 65 years and older, with nine annual interviews conducted between 1982 and 1991. Disability was measured by a 6-item index of activities of daily living (ADL), and a 3-item Rosow-Breslau index, with disability defined as impairment in one or more tasks on each measure. Social network variables were constructed for each of four domains of ties: children, relatives, friends, and a confidant, and a summary measure of total social networks. A Markov model was used to estimate one-year disability transitions averaged across all 8 intervals, after controlling for sociodemographic and health-related variables.Total social networks was associated with a significantly reduced risk of developing ADL disability (beta = -0.009, p < .01), and a significantly increased likelihood of ADL recovery (beta = 0.017, p < .01). Emotional and instrumental support did not affect the protective effect of social networks against disability, but partially accounted for their effect on enhanced recovery. Network variables related to relatives and friends were significantly associated with disability and recovery risks, but those related to children or a confidant were not. The associations with disability transitions as measured by the Rosow-Breslau index were generally smaller and nonsignificant.The findings lend further support for the role of social relationships in important health outcomes in old age. They suggest that being "embedded" in a social network of relatives and friends reduces risk for ADL disability, and enhances recovery from ADL disability.

Pancreatic leak is a major source of morbidity associated with pancreatic surgery. We sought to identify disease and technique-dependent factors associated with morbidity and mortality after distal pancreatectomy.Retrospective review of patients who underwent distal pancreatectomy during a 5-year period. Clinical, technical, and pathologic data were correlated with operative morbidity or mortality.Fifty-one patients underwent distal pancreatectomy for primary pancreatic disease, extrapancreatic malignancy, or trauma. Overall perioperative mortality and morbidity rates were 4% and 47%, respectively. Pancreatic leak was the most common complication, occurring in 26% of patients. Overall complications and pancreatic leaks occurred more often after distal pancreatectomy for trauma and in patients with a sutured pancreatic stump closure.Distal pancreatectomy can be performed with a low rate of mortality, though pancreatic leak is a common cause of morbidity. The urgency of the procedure and the method of pancreatic stump closure may influence postoperative morbidity.

In the study of brain morphometry, it is accepted that a relationship exists between brain structure and function, both normal and abnormal. One descriptor of morphometric structure is volume. Abnormalities in hippocampal morphology, including unilateral or bilateral volume loss, are known to occur in epilepsy, Alzheimer's disease, and in certain amnestic syndromes. Precise quantitation should improve understanding of the role of any biologic system in normal function and in disease. The objectives of magnetic resonance (MR)-based hippocampal volume measurements are precise quantitation, identification of a normal range, and identification of the association between biologic variables and aberrations in this volumetric parameter. Volumetric measures introduce a level of precision in the estimation of hippocampal size that is not available simply by visually inspecting a set of MR images, thus enabling statistically based hypothesis testing. To produce accurate hippocampal volume measurements with magnetic resonance imaging (MRI), attention must be directed to the two major components of the operation as a whole, MR image acquisition and image processing.

In later adulthood brain pathology becomes common and trajectories of cognitive change are heterogeneous. Among the multiple determinants of late-life cognitive course, cognitive reserve has been proposed as an important factor that modifies or buffers the impact of brain pathology on cognitive function. This article presents and investigates a novel method for measuring and investigating such factors. The core concept is that in a population where pathology is common and variably present, 'reserve' may be defined as the difference between the cognitive performance predicted by an individual's level of pathology and that individual's actual performance. By this definition, people whose measured cognitive performance is better than predicted by pathology have high reserve, whereas those who perform worse than predicted have low reserve. To test this hypothesis, we applied a latent variable model to data from a diverse ageing cohort and decomposed the variance in a measure of episodic memory into three components, one predicted by demographics, one predicted by pathology as measured by structural MRI and a 'residual' or 'reserve' term that included all remaining variance. To investigate the plausibility of this approach, we then tested the residual component as an operational measure of reserve. Specific predictions about the effects of this putative reserve measure were generated from a general conceptual model of reserve. Each was borne from the results. The results show that the current level of reserve, as measured by this decomposition approach, modifies rates of conversion from mild cognitive impairment to dementia, modifies rates of longitudinal decline in executive function and, most importantly, attenuates the effect of brain atrophy on cognitive decline such that atrophy is more strongly associated with cognitive decline in subjects with low reserve than in those with high reserve. Decomposing the variance in cognitive function scores offers a promising new approach to the measure and study of cognitive reserve.

The design of the Chicago Health and Aging Project (CHAP) is described. CHAP is a longitudinal population study of common chronic health problems of older persons, especially of risk factors for incident Alzheimer's disease, in a biracial neighborhood of the south side of Chicago. Special attention is given to three unusual design features of the study. One feature is that clinical evaluation for Alzheimer's disease is confined to a stratified random sample of all participants. This feature results in substantial cost savings and substantially less bias than screening approaches but has the disadvantages of adding analytic complexity and requiring the use of indirect means to identify a disease-free cohort for the development of incident Alzheimer's disease. The second unusual feature is efficiently combining in analyses the successive independent multiple samples that are drawn, one from each data collection cycle. The third unusual feature is entering successive age cohorts of community residents into the study as they attain 65 years of age. This has the advantages of enhancing direct investigation of the effect of age on the action of risk factors for Alzheimer's disease and direct examination of cohort effects. The interaction of these features is described, especially as they pertain to a study in which data are collected in successive waves. The results from these waves must be combined for effective analysis of the relation among risk factors and incident disease.

Regions of the temporal and parietal lobes are particularly damaged in Alzheimer's disease (AD), and this leads to a predictable pattern of brain atrophy. In vivo quantification of subregional atrophy, such as changes in cortical thickness or structure volume, could lead to improved diagnosis and better assessment of the neuroprotective effects of a therapy. Toward this end, we have developed a fast and robust method for accurately quantifying cerebral structural changes in several cortical and subcortical regions using serial MRI scans. In 169 healthy controls, 299 subjects with mild cognitive impairment (MCI), and 129 subjects with AD, we measured rates of subregional cerebral volume change for each cohort and performed power calculations to identify regions that would provide the most sensitive outcome measures in clinical trials of disease-modifying agents. Consistent with regional specificity of AD, temporal-lobe cortical regions showed the greatest disease-related changes and significantly outperformed any of the clinical or cognitive measures examined for both AD and MCI. Global measures of change in brain structure, including whole-brain and ventricular volumes, were also elevated in AD and MCI, but were less salient when compared to changes in normal subjects. Therefore, these biomarkers are less powerful for quantifying disease-modifying effects of compounds that target AD pathology. The findings indicate that regional temporal lobe cortical changes would have great utility as outcome measures in clinical trials and may also have utility in clinical practice for aiding early diagnosis of neurodegenerative disease.

The purpose of this study was to validate the results of a meta-analysis showing the efficacy of fish oil in rheumatoid arthritis with the results of a re-analysis of the complete primary data set. A Medline search yielded seven published papers. Three additional trials were found by contacting authorities in the field. Inclusion criteria included (1) a double-blind, placebo-controlled study, (2) use of at least one of seven predetermined outcome measures, (3) results reported for both placebo and treatment groups at baseline and follow-up, (4) randomization, and (5) parallel or cross-over design. Papers were scored for quality. Demographic and outcomes variables were collected. For the re-analysis of the primary data, the same variables were abstracted for the 395 individual patients randomized. The meta-analysis demonstrated that dietary fish oil supplementation for 3 months significantly reduced tender joint count (rate difference [RD][95% CI]= −2.9 [−3.8 to −2.1][p = 0.001]) and morning stiffness (RD [95% CI] = −25.9 [−44.3 to −7.5][p < 0.01]) as compared with heterogeneous dietary control oils. The re-analysis of the primary data confirmed a significant reduction in tender joint count (p = 0.001) and in morning stiffness (p < 0.02) in the parallel analysis that ignored interaction terms. The analyses that included an interaction term between site and treatment again confirmed a significant reduction in tender joint count. The results for morning stiffness were similar to the meta-analysis, but did not quite reach statistical significance (p = 0.052−0.083). The relative improvements in the other outcome variables did not reach statistical significance. Use of fish oil improved the number of tender joints and duration of morning stiffness at 3 months as analyzed by both meta- and mega-analysis. The fuller mega-analysis confirmed the results of the meta-analysis. The advantages of mega-analysis were as follows: (1) the ability to analyze the homogeneity of the patient populations, (2) the ability to make clinically sensible adjustments in the form of the comparison, and (3) the ability to examine subsets of the data.

Impairment of episodic memory is an early and defining feature of Alzheimer disease (AD). The apolipoprotein E (APOE) epsilon 4 allele is known to influence risk of AD but it has been difficult to establish whether it affects episodic memory differently from other cognitive functions.To examine the association of epsilon 4 with decline in different cognitive systems.Longitudinal cohort study.More than 40 groups of Catholic clergy from across the United States.Older Catholic clergy members without clinical evidence of dementia at baseline underwent annual clinical evaluations for up to 6 years. Of 624 persons eligible for follow-up, 611 (98%) participated, of whom 161 (26%) had at least 1 epsilon 4 allele. They completed an average of 5.5 evaluations (range, 2-7).Incident AD and annual rates of change in episodic memory, semantic memory, working memory, perceptual speed, and visuospatial ability.The presence of epsilon 4 was associated with risk of developing AD on follow-up (relative risk, 1.92; 95% confidence interval, 1.27-2.89). In a series of random effects models, epsilon 4 was associated with impaired baseline function in episodic memory and visuospatial ability and with more rapid decline in all domains. The effect of epsilon 4 on annual decline in episodic memory (>3-fold increase) was significantly stronger than its effect on decline in other cognitive systems (P<.01), and at baseline, its effect on episodic memory was marginally stronger than its effect on other cognitive domains (P =.06).The results suggest that the APOE epsilon 4 allele influences risk of AD by a relatively selective effect on episodic memory.

Patterns of cognitive activity, and their relation to cognitive function, were examined in a geographically defined, biracial population of persons aged 65 years and older. Persons (N = 6,162) were given cognitive performance tests and interviewed about their participation in common cognitive activities, like reading a newspaper. Overall, more frequent participation in cognitive activities was associated with younger age, more education, higher family income, female gender, and White race; participation in activities judged to be more cognitively intense was not strongly related to age, but was associated with more education, higher family income, male gender, and White race. Substantial heterogeneity in activity patterns remained after accounting for demographic factors, however. In an analysis controlling for demographic variables, level of cognitive function on performance tests was positively related to composite measures of the frequency and intensity of cognitive activity. Longitudinal studies are needed to assess the relation of cognitive activity patterns to stability and change in cognitive function in older persons.

To quantify contrast material enhancement of breast lesions scanned with dedicated breast computed tomography (CT) and to compare their conspicuity with that at unenhanced breast CT and mammography.Approval of the institutional review board and the Radiation Use Committee and written informed consent were obtained for this HIPAA-compliant study. Between September 2006 and April 2009, 46 women (mean age, 53.2 years; age range, 35-72 years) with Breast Imaging Reporting and Data System category 4 or 5 lesions underwent unenhanced breast CT and contrast material-enhanced breast CT before biopsy. Two radiologists independently scored lesion conspicuity for contrast-enhanced breast CT versus mammography and for contrast-enhanced breast CT versus unenhanced breast CT. Mean lesion voxel intensity was measured in Hounsfield units and normalized to adipose tissue intensity on manually segmented images obtained before and after administration of contrast material. Regression models focused on conspicuity and quantified enhancement were used to estimate the effect of pathologic diagnosis (benign vs malignant), lesion type (mass vs calcifications), breast density, and interradiologist variability.Fifty-four lesions (25 benign, 29 malignant) in 46 subjects were analyzed. Malignant lesions were seen significantly better at contrast-enhanced breast CT than at unenhanced breast CT (P < .001) or mammography (P < .001). Malignant calcifications (malignant lesions manifested mammographically as microcalcifications only, n = 7) were seen better at contrast-enhanced breast CT than at unenhanced breast CT (P < .001) and were seen similarly at contrast-enhanced breast CT and mammography. Malignant lesions enhanced 55.9 HU +/- 4.0 (standard error), whereas benign lesions enhanced 17.6 HU +/- 6.1 (P < .001). Ductal carcinoma in situ (n = 5) enhanced a mean of 59.6 HU +/- 2.8. Receiver operating characteristic curve analysis of lesion enhancement yielded an area under the receiver operating characteristic curve of 0.876.Conspicuity of malignant breast lesions, including ductal carcinoma in situ, is significantly improved at contrast-enhanced breast CT. Quantifying lesion enhancement may aid in the detection and diagnosis of breast cancer.

Little is known about environmental exposure to low levels of naturally occurring asbestos (NOA) and malignant mesothelioma (MM) risk.To conduct a cancer registry-based case control study of residential proximity to NOA with MM in California.Incident MM cases (n = 2,908) aged 35 yr or more, diagnosed between 1988 and 1997, were selected from the California Cancer Registry and frequency matched to control subjects with pancreatic cancer (n = 2,908) by 5-yr age group and sex. Control subjects were selected by stratified random sampling from 28,123 incident pancreatic cancers in the same time period. We located 93.7% of subjects at the house or street level at initial diagnosis. Individual occupational exposure to asbestos was derived from the longest held occupation, available for 74% of MM cases and 63% of pancreatic cancers. Occupational exposure to asbestos was determined by a priori classification and confirmed by association with mesothelioma.The adjusted odds ratios and 95% confidence interval for low, medium, and high probabilities of occupational exposures to asbestos were 1.71 (1.32-2.21), 2.51 (1.91-3.30), and 14.94 (8.37-26.67), respectively. Logistic regression analysis from a subset of 1,133 mesothelioma cases and 890 control subjects with pancreatic cancer showed that the odds of mesothelioma decreased approximately 6.3% for every 10 km farther from the nearest asbestos source, an odds ratio of 0.937 (95% confidence interval = 0.895-0.982), adjusted for age, sex, and occupational exposure to asbestos.These data support the hypothesis that residential proximity to NOA is significantly associated with increased risk of MM in California.

We report results from the first part of an ongoing longitudinal study aimed at identifying the relative contributions of demographic, seizure, and family variables in the prediction of behavior problems in children with epilepsy. We studied 127 children with epilepsy aged 8-12 years and their mothers. Self-report questionnaires, interviews, and medical records were data sources. Backward and forward stepwise elimination procedures using multiple regression indicated five variables that contributed significantly to prediction of behavior problems: female gender, family stress, family mastery, extended family social support, and seizure frequency. These factors accounted for 29% (p < 0.001) of the variation in behavioral problems. Findings suggest that family variables are important correlates of behavior problems and should be considered in clinical management of children with epilepsy.

Abstract Motivation Diseases that progress slowly are often studied by observing cohorts at different stages of disease for short periods of time. The Alzheimer's Disease Neuroimaging Initiative (ADNI) follows elders with various degrees of cognitive impairment, from normal to impaired. The study includes a rich panel of novel cognitive tests, biomarkers, and brain images collected every 6 months for as long as 6 years. The relative timing of the observations with respect to disease pathology is unknown. We propose a general semiparametric model and iterative estimation procedure to estimate simultaneously the pathological timing and long‐term growth curves. The resulting estimates of long‐term progression are fine‐tuned using cognitive trajectories derived from the long‐term “Personnes Agées Quid” study. Results We demonstrate with simulations that the method can recover long‐term disease trends from short‐term observations. The method also estimates temporal ordering of individuals with respect to disease pathology, providing subject‐specific prognostic estimates of the time until onset of symptoms. When the method is applied to ADNI data, the estimated growth curves are in general agreement with prevailing theories of the Alzheimer's disease cascade. Other data sets with common outcome measures can be combined using the proposed algorithm. Availability Software to fit the model and reproduce results with the statistical software R is available as the grace package. ADNI data can be downloaded from the Laboratory of NeuroImaging.

<h3>Objective:</h3> To investigate the vascular contribution to longitudinal changes in Alzheimer disease (AD) biomarkers. <h3>Methods:</h3> The Alzheimer9s Disease Neuroimaging Initiative is a clinic based, longitudinal study with CSF, PET, and MRI biomarkers repeatedly measured in participants with normal cognition (NC), mild cognitive impairment (MCI), and mild AD. Participants with severe cerebrovascular risks were excluded. Cardiovascular risk scores and MRI white matter hyperintensities (WMHs) were treated as surrogate markers for vascular burden. Generalized estimating equations were applied, and both vascular burden and its interaction with time (vascular burden × time) or time-varying WMHs were entered into regression models to assess whether biomarker rates of change were modified by vascular burden. <h3>Results:</h3> Cardiovascular risk profiles were not predictive of progression in CSF β₄₂-amyloid, [¹⁸F]fluorodeoxyglucose (FDG) PET uptake, and MRI hippocampal atrophy. Greater baseline cardiovascular risks or WMHs were generally associated with cognitive impairment, particularly poor executive function. WMHs increased over time with a faster rate in MCI and AD than in NC. Increased time-varying WMH was associated with faster decline in executive function and lower FDG uptake in NC. Otherwise, WMH was not associated with CSF and MRI biomarkers in the 3 groups. These findings remained unchanged after accounting for <i>APOE</i>4. <h3>Conclusion:</h3> Increased WMHs are associated with aging, decreased glucose metabolism, and decline in executive function but do not affect AD-specific pathologic progression, suggesting that the vascular contribution to dementia is probably additive although not necessarily independent of the amyloid pathway.

This study examined trajectories of cognitive change in psychometrically matched measures of episodic memory, semantic memory, and executive function in an ethnically, demographically, and cognitively diverse sample of older persons. Individual rates of change showed considerable heterogeneity in each domain. Baseline clinical diagnosis predicted differential change in semantic memory and executive function, dementia > mild cognitive impairment (MCI) > normal, but average decline in verbal episodic memory was similar across all 3 diagnostic groups. There was substantial overlap of distributions of cognitive change across baseline diagnostic groups for all 3 measures. Cognitive change was strongly related to change in clinical diagnosis. Rapid and similar change was present for all 3 cognitive measures in patients with dementia and in those with normal cognition and those with MCI who progressed clinically. In cognitively normal patients, verbal episodic memory change was greater than change in the other two domains. Global status, measured by the Clinical Dementia Rating scale (Morris, 1993), predicted change in semantic memory and executive function, whereas APOE genotype predicted change in verbal episodic memory, and age had no effect on rates of change in any domain independent of global status and APOE. Results show important limitations in using cross-sectional diagnosis to predict prognosis and suggest that research to identify robust predictors of cognitive change across the full spectrum from normal to dementia is needed for better early identification of diseases that cause progressive decline.

<h3>Objective:</h3> To examine sex differences in the relationship between clinical symptoms related to Alzheimer disease (AD) (verbal memory deficits) and neurodegeneration (hippocampal volume/intracranial volume ratio [HpVR]) across AD stages. <h3>Methods:</h3> The sample included 379 healthy participants, 694 participants with amnestic mild cognitive impairment (aMCI), and 235 participants with AD and dementia from the Alzheimer9s Disease Neuroimaging Initiative who completed the Rey Auditory Verbal Learning Test (RAVLT). Cross-sectional analyses were conducted using linear regression to examine the interaction between sex and HpVR on RAVLT across and within diagnostic groups adjusting for age, education, and <i>APOE</i> ε4 status. <h3>Results:</h3> Across groups, there were significant sex × HpVR interactions for immediate and delayed recall (<i>p</i> &lt; 0.01). Women outperformed men among individuals with moderate to larger HpVR, but not among individuals with smaller HpVR. In diagnosis-stratified analyses, the HpVR × sex interaction was significant in the aMCI group, but not in the control or AD dementia groups, for immediate and delayed recall (<i>p</i> &lt; 0.01). Among controls, women outperformed men on both outcomes irrespective of HpVR (<i>p</i> &lt; 0.001). In AD dementia, better RAVLT performance was independently associated with female sex (immediate, <i>p</i> = 0.04) and larger HpVR (delayed, <i>p</i> = 0.001). <h3>Conclusion:</h3> Women showed an advantage in verbal memory despite evidence of moderate hippocampal atrophy. This advantage may represent a sex-specific form of cognitive reserve delaying verbal memory decline until more advanced disease stages.

The aim of this study was to investigate predictors of progressive cognitive deterioration in patients with suspected non-Alzheimer disease pathology (SNAP) and mild cognitive impairment (MCI).We measured markers of amyloid pathology (CSF β-amyloid 42) and neurodegeneration (hippocampal volume on MRI and cortical metabolism on [(18)F]-fluorodeoxyglucose-PET) in 201 patients with MCI clinically followed for up to 6 years to detect progressive cognitive deterioration. We categorized patients with MCI as A+/A- and N+/N- based on presence/absence of amyloid pathology and neurodegeneration. SNAPs were A-N+ cases.The proportion of progressors was 11% (8/41), 34% (14/41), 56% (19/34), and 71% (60/85) in A-N-, A+N-, SNAP, and A+N+, respectively; the proportion of APOE ε4 carriers was 29%, 70%, 31%, and 71%, respectively, with the SNAP group featuring a significantly different proportion than both A+N- and A+N+ groups (p ≤ 0.005). Hypometabolism in SNAP patients was comparable to A+N+ patients (p = 0.154), while hippocampal atrophy was more severe in SNAP patients (p = 0.002). Compared with A-N-, SNAP and A+N+ patients had significant risk of progressive cognitive deterioration (hazard ratio = 2.7 and 3.8, p = 0.016 and p < 0.001), while A+N- patients did not (hazard ratio = 1.13, p = 0.771). In A+N- and A+N+ groups, none of the biomarkers predicted time to progression. In the SNAP group, lower time to progression was correlated with greater hypometabolism (r = 0.42, p = 0.073).Our findings support the notion that patients with SNAP MCI feature a specific risk progression profile.

To test the hypothesis that cortical and hippocampal volumes, measured in vivo from volumetric MRI (vMRI) scans, could be used to identify variant subtypes of Alzheimer disease (AD) and to prospectively predict the rate of clinical decline.Amyloid-positive participants with AD from the Alzheimer's Disease Neuroimaging Initiative (ADNI) 1 and ADNI2 with baseline MRI scans (n = 229) and 2-year clinical follow-up (n = 100) were included. AD subtypes (hippocampal sparing [HpSpMRI], limbic predominant [LPMRI], typical AD [tADMRI]) were defined according to an algorithm analogous to one recently proposed for tau neuropathology. Relationships between baseline hippocampal volume to cortical volume ratio (HV:CTV) and clinical variables were examined by both continuous regression and categorical models.When participants were divided categorically, the HpSpMRI group showed significantly more AD-like hypometabolism on 18F-fluorodeoxyglucose-PET (p < 0.05) and poorer baseline executive function (p < 0.001). Other baseline clinical measures did not differ across the 3 groups. Participants with HpSpMRI also showed faster subsequent clinical decline than participants with LPMRI on the Alzheimer's Disease Assessment Scale, 13-Item Subscale (ADAS-Cog13), Mini-Mental State Examination (MMSE), and Functional Assessment Questionnaire (all p < 0.05) and tADMRI on the MMSE and Clinical Dementia Rating Sum of Boxes (CDR-SB) (both p < 0.05). Finally, a larger HV:CTV was associated with poorer baseline executive function and a faster slope of decline in CDR-SB, MMSE, and ADAS-Cog13 score (p < 0.05). These associations were driven mostly by the amount of cortical rather than hippocampal atrophy.AD subtypes with phenotypes consistent with those observed with tau neuropathology can be identified in vivo with vMRI. An increased HV:CTV ratio was predictive of faster clinical decline in participants with AD who were clinically indistinguishable at baseline except for a greater dysexecutive presentation.

The Alzheimer's Disease Neuroimaging Initiative Phase 1 (ADNI-1) is a multisite prospective study designed to examine potential cerebrospinal fluid and imaging markers of Alzheimer's disease (AD) and their relationship to cognitive change. The objective of this study was to provide a global summary of the overall results and patterns of change observed in candidate markers and clinical measures over the first 2 years of follow-up.Change was summarized for 210 normal controls, 357 mild cognitive impairment, and 162 AD subjects, with baseline and at least one cognitive follow-up assessment. Repeated measures and survival models were used to assess baseline biomarker levels as predictors. Potential for improving clinical trials was assessed by comparison of precision of markers for capturing change in hypothetical trial designs.The first 12 months of complete data on ADNI participants demonstrated the potential for substantial advances in characterizing trajectories of change in a range of biomarkers and clinical outcomes, examining their relationship and timing, and assessing the potential for improvements in clinical trial design. Reduced metabolism and greater brain atrophy in the mild cognitive impairment at baseline are associated with more rapid cognitive decline and a higher rate of conversion to AD. Use of biomarkers as study entry criteria or as outcomes could reduce the number of participants required for clinical trials.Analyses and comparisons of ADNI data strongly support the hypothesis that measurable change occurs in cerebrospinal fluid, positron emission tomography, and magnetic resonance imaging well in advance of the actual diagnosis of AD.

<h3>Objective</h3> To study longitudinal relationships between type 2 diabetes mellitus (T2DM), cortical thickness, and cognitive function in older people with normal cognition, mild cognitive impairment, and Alzheimer disease (AD). <h3>Methods</h3> The sample was derived from the Alzheimer9s Disease Neuroimaging Initiative cohort who underwent brain MRI and cognitive tests annually for 5 years. Presence of T2DM was based on fasting blood glucose ≥7.0mml/L or the use of glucose-lowering agents. We used latent growth curve modeling to explore longitudinal relationships between T2DM, cortical thickness, and cognitive function, adjusting for relevant covariates and testing for interactions. <h3>Results</h3> There were 124 people with T2DM (mean age 75.5 years, SD 6.2) and 693 without T2DM (mean age 75.1 years, SD 6.9) with at least 1 MRI available. AD and lower cortical thickness at study entry was associated with a lower chance of having a MRI available at each follow-up phase (all <i>p</i> &lt; 0.001). T2DM was associated with lower baseline cortical thickness (<i>p</i> = 0.01). We found no direct effect of T2DM on decline in cortical thickness or cognitive function, but there was an indirect pathway linking T2DM and cognitive decline via baseline cortical thickness (β = −0.17, <i>p</i> = 0.022). There was an interaction between T2DM and education whereby the negative effect of T2DM on baseline cortical thickness was reduced in those with greater education (β = 0.34, <i>p</i> = 0.037). These associations changed minimally when adjusted for baseline cognitive diagnosis. <h3>Conclusions</h3> In an older cohort with low cerebrovascular disease burden, T2DM contributes to cognitive decline via neurodegeneration. Prior brain and cognitive reserve may protect against this effect.

Abstract Background Previous work examining normal controls from the Alzheimer's Disease Neuroimaging Initiative (ADNI) identified substantial biological heterogeneity. We hypothesized that ADNI mild cognitive impairment (MCI) subjects would also exhibit heterogeneity with possible clinical implications. Methods ADNI subjects diagnosed with amnestic MCI ( n = 138) were clustered based on baseline magnetic resonance imaging, cerebrospinal fluid, and serum biomarkers. The clusters were compared with respect to longitudinal atrophy, cognitive trajectory, and time to conversion. Results Four clusters emerged with distinct biomarker patterns: The first cluster was biologically similar to normal controls and rarely converted to Alzheimer's disease (AD) during follow‐up. The second cluster had characteristics of early Alzheimer's pathology. The third cluster showed the most severe atrophy but barely abnormal tau levels and a substantial proportion converted to clinical AD. The fourth cluster appeared to be pre‐AD and nearly all converted to AD. Conclusions Subjects with MCI who were clinically similar showed substantial heterogeneity in biomarkers.

Trajectories of cognitive decline among elderly individuals are heterogeneous, and markers that have high reliability for predicting cognitive trajectories across a broad spectrum of the elderly population have yet to be identified. This study examined the utility of a variety of MRI-based brain measures, obtained at baseline, as predictors of subsequent declines in domain-specific measures of cognitive function in a cohort of 307 community-dwelling elderly individuals with varying degrees of cognitive impairment who were diverse across several relevant demographic variables and were evaluated yearly. Psychometrically matched measures of cognition were used to assess episodic memory, semantic memory, and executive function. Relationships between baseline MRI measures, including the volumes of the brain, hippocampus, and white matter hyperintensities (WMH), and cognitive trajectories were assessed in mixed effects regression models that modeled MRI effects on cognitive performance at baseline and rate of change as well as interindividual variability in cognitive baseline and rate of change. Greater baseline brain volume predicted slower subsequent rate of decline in episodic memory and smaller WMH volume predicted slower subsequent rate of decline in executive function and semantic memory. Baseline hippocampal volume, while strongly related to baseline cognitive function, was not predictive of subsequent change in any of the cognitive domains. Baseline measures of brain structure and tissue pathology predicted rate of cognitive decline in a diverse and carefully characterized cohort, suggesting that they may provide summary measures of pre-existing neuropathological damage or the capacity of the brain to compensate for the impact of subsequent neuropathology on cognition. Conventional MRI measures may have use for predicting cognitive outcomes in highly heterogeneous elderly populations.

Examine how longitudinal cognitive trajectories relate to brain baseline measures and change in lobar volumes in a racially/ethnically and cognitively diverse sample of older adults.Participants were 460 older adults enrolled in a longitudinal aging study. Cognitive outcomes were measures of episodic memory, semantic memory, executive function, and spatial ability derived from the Spanish and English Neuropsychological Assessment Scales (SENAS). Latent variable multilevel modeling of the four cognitive outcomes as parallel longitudinal processes identified intercepts for each outcome and a second order global change factor explaining covariance among the highly correlated slopes. We examined how baseline brain volumes (lobar gray matter, hippocampus, and white matter hyperintensity) and change in brain volumes (lobar gray matter) were associated with cognitive intercepts and global cognitive change. Lobar volumes were dissociated into global and specific components using latent variable methods.Cognitive change was most strongly associated with brain gray matter volume change, with strong independent effects of global gray matter change and specific temporal lobe gray matter change. Baseline white matter hyperintensity and hippocampal volumes had significant incremental effects on cognitive decline beyond gray matter change. Baseline lobar gray matter was related to cognitive decline, but did not contribute beyond gray matter change.Cognitive decline was strongly influenced by gray matter volume change and, especially, temporal lobe change. The strong influence of temporal lobe gray matter change on cognitive decline may reflect involvement of temporal lobe structures that are critical for late life cognitive health but also are vulnerable to diseases of aging. (PsycINFO Database Record

Abstract Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer’s disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, ‘shape connections’ between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus.

The purpose of this study was to evaluate how demographic variables relate to cognitive change and address whether cross-sectional demographic effects on cognitive tests are mirrored in differences in longitudinal trajectories of cognitive decline. We hypothesized that race and ethnicity, education, and language of test administration would relate to cross-sectional status and that the rate of cognitive decline would differ among African Americans, Hispanics, and Caucasians, across levels of educational attainment, and according to linguistic background. Participants were 404 educationally, ethnically, and cognitively diverse older adults enrolled in an ongoing longitudinal study of cognition. Mixed-effects regression analysis was used to measure baseline status and longitudinal change in episodic memory, executive functioning, and semantic memory. Results showed that ethnicity and education were strongly associated with baseline scores, but were, at most, weakly associated with change in cognition over time after accounting for confounding variables. There was evidence that the episodic-memory scores of Spanish-speaking Hispanic participants with limited education underestimated their true abilities in the initial evaluation, which may reflect lack of familiarity with the testing environment. These results--consistent with other reports in the literature--suggest that cross-sectional effects of demographic variables on cognitive-test scores result from differences in life experiences that directly influence test performance and do not indicate greater disease effects on cognition in minorities and those with limited education.

We conducted Japanese Alzheimer's Disease Neuroimaging Initiative (J-ADNI) and compared the basic characteristics and progression profiles with those of ADNI in North America.A total of 537 Japanese subjects with normal cognition, late amnestic mild cognitive impairment (LMCI), or mild Alzheimer's disease (AD) were enrolled using the same criteria as ADNI. Rates of changes in representative cognitive or functional measures were compared for amyloid positron emission tomography- or cerebrospinal fluid amyloid β(1-42)-positive LMCI and mild AD between J-ADNI and ADNI.Amyloid positivity rates were significantly higher in normal cognition of ADNI but at similar levels in LMCI and mild AD between J-ADNI and ADNI. Profiles of decline in cognitive or functional measures in amyloid-positive LMCI in J-ADNI (n = 75) and ADNI (n = 269) were remarkably similar, whereas those in mild AD were milder in J-ADNI (n = 73) compared with ADNI (n = 230).These results support the feasibility of bridging of clinical trials in the prodromal stage of AD between Asia and western countries.

Abstract Background Regulatory qualification of a biomarker for a defined context of use provides scientifically robust assurances to sponsors and regulators that accelerate appropriate adoption of biomarkers into drug development. Methods The Coalition Against Major Diseases submitted a dossier to the Scientific Advice Working Party of the European Medicines Agency requesting a qualification opinion on the use of hippocampal volume as a biomarker for enriching clinical trials in subjects with mild cognitive impairment, incorporating a scientific rationale, a literature review and a de novo analysis of Alzheimer's Disease Neuroimaging Initiative data. Results The literature review and de novo analysis were consistent with the proposed context of use, and the Committee for Medicinal Products for Human Use released an opinion in November 2011. Conclusions We summarize the scientific rationale and the data that supported the first qualification of an imaging biomarker by the European Medicines Agency.

<h3>Objective:</h3> To investigate the association between periventricular white mater hyperintensities (PVWMH) and biomarkers of elevated cerebral β-amyloid (Aβ) in the Alzheimer9s Disease Neuroimaging Initiative, a large prospective multicenter observational study. <h3>Methods:</h3> The burden of frontal, parietal, and occipital PVWMH on 3T fluid-attenuated inversion recovery MRI was evaluated in 698 cognitively normal participants and participants with mild cognitive impairment (MCI) using a novel semiquantitative visual rating scale. Results were correlated with CSF-Aβ, florbetapir-PET, and fluorodeoxyglucose (FDG)–PET. <h3>Results:</h3> Increased burden of parietal, occipital, and frontal PVWMH was associated with elevated cerebral amyloid evidenced by high florbetapir-PET signal (<i>p</i> &lt; 0.01) and low CSF-Aβ (<i>p</i> &lt; 0.01). In logistic regression models, including PVWMH, age, sex, <i>APOE</i> status, vascular risk factors, pulse pressure, vascular secondary prevention medications, education, ethnicity, and race, parietal, occipital, and frontal PVWMH burden was independently associated with high florbetapir-PET uptake (<i>p</i> &lt; 0.05). In a similar logistic regression model, parietal and occipital (<i>p</i> &lt; 0.05) but not frontal (<i>p</i> = 0.05) PVWMH were independently associated with CSF-Aβ. Weaker associations were found between parieto-occipital PVWMH and elevated CSF-tau (<i>p</i> &lt; 0.05) and occipital PVWMH and elevated CSF-phospho-tau (<i>p</i> &lt; 0.05). PVWMH were associated with cerebral hypometabolism on FDG-PET independent of CSF-Aβ levels (<i>p</i> &lt; 0.05). Absolute and consistency of agreement intraclass correlation coefficients were, respectively, 0.83 and 0.83 for frontal, 0.78 and 0.8 for parietal, and 0.45 and 0.75 for occipital PVWMH measurements. <h3>Conclusions:</h3> Increased PVWMH were associated with elevated cerebral amyloid independent of potential confounders such as age, <i>APOE</i> genotype, and vascular risk factors. The mechanisms underlying the association between PVWMH and cerebral amyloid remain to be clarified.

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.

Abstract Introduction The Alzheimer's Disease Neuroimaging Initiative (ADNI) has accumulated 15 years of clinical, neuroimaging, cognitive, biofluid biomarker and genetic data, and biofluid samples available to researchers, resulting in more than 3500 publications. This review covers studies from 2018 to 2020. Methods We identified 1442 publications using ADNI data by conventional search methods and selected impactful studies for inclusion. Results Disease progression studies supported pivotal roles for regional amyloid beta (Aβ) and tau deposition, and identified underlying genetic contributions to Alzheimer's disease (AD). Vascular disease, immune response, inflammation, resilience, and sex modulated disease course. Biologically coherent subgroups were identified at all clinical stages. Practical algorithms and methodological changes improved determination of Aβ status. Plasma Aβ, phosphorylated tau181, and neurofilament light were promising noninvasive biomarkers. Prognostic and diagnostic models were externally validated in ADNI but studies are limited by lack of ethnocultural cohort diversity. Discussion ADNI has had a profound impact in improving clinical trials for AD.

Our nation is becoming increasingly diverse; however, few autopsy studies examine multiple ethnoracial groups, especially Hispanics. We examined differences in neuropathological diagnoses of 423 deceased participants with dementia from three ethnoracial groups (35 Black, 28 Hispanic, and 360 non-Hi spanic White) evaluated at the University of California Davis Alzheimer’s Disease Center. We used novel applications of bootstrap resampling and logistic regression standardization to project neuropathological diagnostic rates for non-Hispanic Whites to minority sample characteristics to improve inference of findings. Alzheimer’s disease (AD) without significant cerebrovascular disease (CVD) or other dementia-related pathologies (AD (non-mixed)) was present in 15 Black (43%), 4 Hispanic (14%), and 156 (43%) non-Hispanic Whites. CVD sufficient to contribute to dementia was confirmed in 14 Black (40%), 15 Hispanic (54%), and 101 (28%) non-Hispanic White decedents. The observed CVD prevalence of 40% in Blacks exceeded the predicted 29% [95% CI: 22%-36%]. Despite being outside the 95% confidence interval, the difference between observed and predicted was not statistically significant after bootstrap testing. Conversely, for Hispanics, the observed proportion at 54% exceeded significantly the predicted prevalence of 24% from non-Hispanic Whites [95% CI: 16%-34%], avg. p = 0.008). An identical analysis using AD (non-mixed) as the outcome predicted AD (non-mixed) in Blacks averaging 41% [95% CI: 34%-48%], nearly equal to observed prevalence. For Hispanics, however, the observed proportion at 14%, was well below predictions (mean = 42%, 95% CI: 32%-53%], avg. p = 0.008). We conclude mixed diagnoses and CVD are more common in Hispanic and Black decedents than Non-Hispanic Whites with dementia in our cohort. The increased prevalence of vascular co-morbidity may be a potential opportunity to intervene more effectively in dementia treatment of those individuals.

Abstract Causal Structure Discovery (CSD) is the problem of identifying causal relationships from large quantities of data through computational methods. With the limited ability of traditional association-based computational methods to discover causal relationships, CSD methodologies are gaining popularity. The goal of the study was to systematically examine whether (i) CSD methods can discover the known causal relationships from observational clinical data and (ii) to offer guidance to accurately discover known causal relationships. We used Alzheimer’s disease (AD), a complex progressive disease, as a model because the well-established evidence provides a “gold-standard” causal graph for evaluation. We evaluated two CSD methods, Fast Causal Inference (FCI) and Fast Greedy Equivalence Search (FGES) in their ability to discover this structure from data collected by the Alzheimer’s Disease Neuroimaging Initiative (ADNI). We used structural equation models (which is not designed for CSD) as control. We applied these methods under three scenarios defined by increasing amounts of background knowledge provided to the methods. The methods were evaluated by comparing the resulting causal relationships with the “gold standard” graph that was constructed from literature. Dedicated CSD methods managed to discover graphs that nearly coincided with the gold standard. For best results, CSD algorithms should be used with longitudinal data providing as much prior knowledge as possible.

Abstract Resting state functional connectivity (rs-fMRI) is impaired early in persons who subsequently develop Alzheimer’s disease (AD) dementia. This impairment may be leveraged to aid investigation of the pre-clinical phase of AD. We developed a model that predicts brain age from resting state (rs)-fMRI data, and assessed whether genetic determinants of AD, as well as beta-amyloid (Aβ) pathology, can accelerate brain aging. Using data from 1340 cognitively unimpaired participants between 18–94 years of age from multiple sites, we showed that topological properties of graphs constructed from rs-fMRI can predict chronological age across the lifespan. Application of our predictive model to the context of pre-clinical AD revealed that the pre-symptomatic phase of autosomal dominant AD includes acceleration of functional brain aging. This association was stronger in individuals having significant Aβ pathology.

Heterogeneity of brain diseases is a challenge for precision diagnosis/prognosis. We describe and validate Smile-GAN (SeMI-supervised cLustEring-Generative Adversarial Network), a semi-supervised deep-clustering method, which examines neuroanatomical heterogeneity contrasted against normal brain structure, to identify disease subtypes through neuroimaging signatures. When applied to regional volumes derived from T1-weighted MRI (two studies; 2,832 participants; 8,146 scans) including cognitively normal individuals and those with cognitive impairment and dementia, Smile-GAN identified four patterns or axes of neurodegeneration. Applying this framework to longitudinal data revealed two distinct progression pathways. Measures of expression of these patterns predicted the pathway and rate of future neurodegeneration. Pattern expression offered complementary performance to amyloid/tau in predicting clinical progression. These deep-learning derived biomarkers offer potential for precision diagnostics and targeted clinical trial recruitment.

The Alzheimer's Disease Neuroimaging Initiative (ADNI) aims to validate biomarkers for Alzheimer's disease (AD) clinical trials. To improve generalizability, ADNI4 aims to enroll 50-60% of its new participants from underrepresented populations (URPs) using new biofluid and digital technologies. ADNI4 has received funding from the National Institute on Aging beginning September 2022.ADNI4 will recruit URPs using community-engaged approaches. An online portal will screen 20,000 participants, 4000 of whom (50-60% URPs) will be tested for plasma biomarkers and APOE. From this, 500 new participants will undergo in-clinic assessment joining 500 ADNI3 rollover participants. Remaining participants (∼3500) will undergo longitudinal plasma and digital cognitive testing. ADNI4 will add MRI sequences and new PET tracers. Project 1 will optimize biomarkers in AD clinical trials.ADNI4 will improve generalizability of results, use remote digital and blood screening, and continue providing longitudinal clinical, biomarker, and autopsy data to investigators.

Characterization of early tau deposition in individuals with preclinical Alzheimer disease (AD) is critical for prevention trials that aim to select individuals at risk for AD and halt the progression of disease.To evaluate the prevalence of cortical tau positron emission tomography (PET) heterogeneity in a large cohort of clinically unimpaired older adults with elevated β-amyloid (A+).This cross-sectional study examined prerandomized tau PET, amyloid PET, structural magnetic resonance imaging, demographic, and cognitive data from the Anti-Amyloid Treatment in Asymptomatic AD (A4) Study from April 2014 to December 2017. Follow-up analyses used observational tau PET data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the Harvard Aging Brain Study (HABS), and the Wisconsin Registry for Alzheimer's Prevention and the Wisconsin Alzheimer's Disease Research Center (together hereinafter referred to as Wisconsin) to evaluate consistency. Participants were clinically unimpaired at the study visit closest to the tau PET scan and had available amyloid and tau PET data (A4 Study, n = 447; ADNI, n = 433; HABS, n = 190; and Wisconsin, n = 328). No participants who met eligibility criteria were excluded. Data were analyzed from May 11, 2021, to January 25, 2022.Individuals with preclinical AD with heterogeneous cortical tau PET patterns (A+T cortical+) were identified by examining asymmetrical cortical tau signal and disproportionate cortical tau signal relative to medial temporal lobe (MTL) tau. Voxelwise tau patterns, amyloid, neurodegeneration, cognition, and demographic characteristics were examined.The 447 A4 participants (A+ group, 392; and normal β-amyloid group, 55), with a mean (SD) age of 71.8 (4.8) years, included 239 women (54%). A total of 36 individuals in the A+ group (9% of the A+ group) exhibited heterogeneous cortical tau patterns and were further categorized into 3 subtypes: asymmetrical left, precuneus dominant, and asymmetrical right. A total of 116 individuals in the A+ group (30% of the A+ group) showed elevated MTL tau (A+T MTL+). Individuals in the A+T cortical+ group were younger than those in the A+T MTL+ group (t61.867 = -2.597; P = .03). Across the A+T cortical+ and A+T MTL+ groups, increased regional tau was associated with reduced hippocampal volume and MTL thickness but not with cortical thickness. Memory scores were comparable between the A+T cortical+ and A+T MTL+ groups, whereas executive functioning scores were lower for the A+T cortical+ group than for the A+T MTL+ group. The prevalence of the A+T cortical+ group and tau patterns within the A+T cortical+ group were consistent in ADNI, HABS, and Wisconsin.This study suggests that early tau deposition may follow multiple trajectories during preclinical AD and may involve several cortical regions. Staging procedures, especially those based on neuropathology, that assume a uniform trajectory across individuals are insufficient for disease monitoring with tau imaging.

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.

Importance Increased white matter hyperintensity (WMH) volume is a common magnetic resonance imaging (MRI) finding in both autosomal dominant Alzheimer disease (ADAD) and late-onset Alzheimer disease (LOAD), but it remains unclear whether increased WMH along the AD continuum is reflective of AD-intrinsic processes or secondary to elevated systemic vascular risk factors. Objective To estimate the associations of neurodegeneration and parenchymal and vessel amyloidosis with WMH accumulation and investigate whether systemic vascular risk is associated with WMH beyond these AD-intrinsic processes. Design, Setting, and Participants This cohort study used data from 3 longitudinal cohort studies conducted in tertiary and community-based medical centers—the Dominantly Inherited Alzheimer Network (DIAN; February 2010 to March 2020), the Alzheimer’s Disease Neuroimaging Initiative (ADNI; July 2007 to September 2021), and the Harvard Aging Brain Study (HABS; September 2010 to December 2019). Main Outcome and Measures The main outcomes were the independent associations of neurodegeneration (decreases in gray matter volume), parenchymal amyloidosis (assessed by amyloid positron emission tomography), and vessel amyloidosis (evidenced by cerebral microbleeds [CMBs]) with cross-sectional and longitudinal WMH. Results Data from 3960 MRI sessions among 1141 participants were included: 252 pathogenic variant carriers from DIAN (mean [SD] age, 38.4 [11.2] years; 137 [54%] female), 571 older adults from ADNI (mean [SD] age, 72.8 [7.3] years; 274 [48%] female), and 318 older adults from HABS (mean [SD] age, 72.4 [7.6] years; 194 [61%] female). Longitudinal increases in WMH volume were greater in individuals with CMBs compared with those without (DIAN: t = 3.2 [ P = .001]; ADNI: t = 2.7 [ P = .008]), associated with longitudinal decreases in gray matter volume (DIAN: t = −3.1 [ P = .002]; ADNI: t = −5.6 [ P &amp;amp;lt; .001]; HABS: t = −2.2 [ P = .03]), greater in older individuals (DIAN: t = 6.8 [ P &amp;amp;lt; .001]; ADNI: t = 9.1 [ P &amp;amp;lt; .001]; HABS: t = 5.4 [ P &amp;amp;lt; .001]), and not associated with systemic vascular risk (DIAN: t = 0.7 [ P = .40]; ADNI: t = 0.6 [ P = .50]; HABS: t = 1.8 [ P = .06]) in individuals with ADAD and LOAD after accounting for age, gray matter volume, CMB presence, and amyloid burden. In older adults without CMBs at baseline, greater WMH volume was associated with CMB development during longitudinal follow-up (Cox proportional hazards regression model hazard ratio, 2.63; 95% CI, 1.72-4.03; P &amp;amp;lt; .001). Conclusions and Relevance The findings suggest that increased WMH volume in AD is associated with neurodegeneration and parenchymal and vessel amyloidosis but not with elevated systemic vascular risk. Additionally, increased WMH volume may represent an early sign of vessel amyloidosis preceding the emergence of CMBs.

Abstract Mechanisms of resilience against tau pathology in individuals across the Alzheimer’s disease spectrum are insufficiently understood. Longitudinal data are necessary to reveal which factors relate to preserved cognition (i.e. cognitive resilience) and brain structure (i.e. brain resilience) despite abundant tau pathology, and to clarify whether these associations are cross-sectional or longitudinal. We used a longitudinal study design to investigate the role of several demographic, biological and brain structural factors in yielding cognitive and brain resilience to tau pathology as measured with PET. In this multicentre study, we included 366 amyloid-β-positive individuals with mild cognitive impairment or Alzheimer’s disease dementia with baseline 18F-flortaucipir-PET and longitudinal cognitive assessments. A subset (n = 200) additionally underwent longitudinal structural MRI. We used linear mixed-effects models with global cognition and cortical thickness as dependent variables to investigate determinants of cognitive resilience and brain resilience, respectively. Models assessed whether age, sex, years of education, APOE-ε4 status, intracranial volume (and cortical thickness for cognitive resilience models) modified the association of tau pathology with cognitive decline or cortical thinning. We found that the association between higher baseline tau-PET levels (quantified in a temporal meta-region of interest) and rate of cognitive decline (measured with repeated Mini-Mental State Examination) was adversely modified by older age (Stβinteraction = −0.062, P = 0.032), higher education level (Stβinteraction = −0.072, P = 0.011) and higher intracranial volume (Stβinteraction = −0.07, P = 0.016). Younger age, higher education and greater cortical thickness were associated with better cognitive performance at baseline. Greater cortical thickness was furthermore associated with slower cognitive decline independent of tau burden. Higher education also modified the negative impact of tau-PET on cortical thinning, while older age was associated with higher baseline cortical thickness and slower rate of cortical thinning independent of tau. Our analyses revealed no (cross-sectional or longitudinal) associations for sex and APOE-ε4 status on cognition and cortical thickness. In this longitudinal study of clinically impaired individuals with underlying Alzheimer’s disease neuropathological changes, we identified education as the most robust determinant of both cognitive and brain resilience against tau pathology. The observed interaction with tau burden on cognitive decline suggests that education may be protective against cognitive decline and brain atrophy at lower levels of tau pathology, with a potential depletion of resilience resources with advancing pathology. Finally, we did not find major contributions of sex to brain nor cognitive resilience, suggesting that previous links between sex and resilience might be mainly driven by cross-sectional differences.

Late-life depression affects physical health and impedes recovery from physical disability. But whether milder symptoms that occur frequently in the general population increase the risk of developing a disability or decrease the likelihood of recovery remains unclear.To examine the effect of mild symptoms of depression, assessed by a reduced version (10 items, ranging from 0-10) of the Center for Epidemiological Studies-Depression Scale, on the course of physical disability, assessed by items from the Katz Activities of Daily Living Scale, the Rosow-Breslau Functional Health Scale, and the Nagi Index.A population-based longitudinal study was conducted, with 6 follow-up interviews of 3434 community-dwelling persons aged 65 years and older in East Boston, Mass.The likelihood of becoming disabled increased with each additional symptom of depression (for the Katz measure: odds ratio, 1.16 per symptom; 95% confidence interval, 1.13-1.19; for the Rosow-Breslau measure: odds ratio, 1.14; 95% confidence interval, 1.11-1.16; and for the Nagi measure: odds ratio, 1.17; 95% confidence interval, 1.14-1.19). As the number of depressive symptoms increased, the likelihood of recovering from a physical disability decreased (for the Katz measure: odds ratio, 0.96; 95% confidence interval, 0.93-0.99; for the Rosow-Breslau measure: odds ratio, 0.86; 95% confidence interval, 0.84-0.89; and for the Nagi measure: odds ratio, 0.89; 95% confidence interval, 0.87-0.91). This effect was not accounted for by age, sex, level of educational attainment, body mass index, or chronic health conditions.Mild depressive symptoms in older persons (those aged > or =65 years) are associated with an increased likelihood of becoming disabled and a decreased chance of recovery, regardless of age, sex, and other factors that contribute to physical disability.

We evaluated the ability of nurse clinicians to assess parkinsonian signs in older persons with a modified version of the motor section of the Unified Parkinson9s Disease Rating Scale (UPDRS). After completing a structured training protocol, three nurse clinicians and a neurologist with expertise in movement disorders administered a modified UPDRS to 75 older persons. The nurses repeated the assessment about 3 weeks later. Inter-rater agreement and short-term temporal stability were estimated for each item, the total modified UPDRS score, and for summary measures of bradykinesia, postural reflex impairment, rigidity, and tremor, and a global parkinsonian sign score. We performed our assessment in Catholic religious communities in the Chicago area, using consecutive subjects at four communities participating in the Religious Orders Study, a longitudinal, clinical-pathologic study of older persons. Our results showed that nurses were not a significant source of variability, with intraclass correlations exceeding 0.97 for all items, and they showed good to excellent agreement with the neurologist for most modified UPDRS items. Correlations between nurses and neurologist exceeded 0.90 for the total modified UPDRS, ranged from 0.76 to 0.95 for the four parkinsonian domain scores, and exceeded 0.90 for the global parkinsonian sign score. Nurses showed fair to good agreement with themselves over the 3-week interval for most modified UPDRS items. Correlations over the 3-week interval exceeded 0.90 for the total modified UPDRS score, ranged from 0.70 to 0.95 for the four domain scores, and exceeded 0.90 for the global parkinsonian sign score. Ratings of parkinsonian signs by nurse clinicians corresponded closely to those of a neurologist with expertise in movement disorders and showed good inter-rater agreement and temporal stability. With appropriate training, nurse clinicians can reliably administer the modified UPDRS.

Impending death is thought to be associated with age-related cognitive decline, but this association has not been well studied.Participants were 763 older Roman Catholic nuns, priests, and brothers without dementia at baseline. They completed an average of 5.6 annual evaluations (range 2 to 9), with >95% follow-up participation in survivors. Each evaluation included administration of 19 cognitive function tests from which previously established measures of global cognition (mean = 0.108, SD = 0.502) and specific cognitive functions were derived. In a series of change point random effects models, the average point before death when rate of cognitive decline changed was identified, and rates of cognitive decline before and after the optimal change point were estimated, controlling for the effects of age, sex, and education.There were 122 deaths during the observation period. Those who died had lower global cognitive function at baseline than survivors (by 0.103 unit; p = 0.03), and beginning about 43 months before death, their annual rate of global cognitive decline sharply accelerated from an annual loss of 0.026 to 0.173 unit, a more than sixfold increase. Results were comparable in analyses that controlled for baseline health and disability. Terminal cognitive decline was evident in nearly all of those who died, but at highly variable rates. Remarkably little cognitive decline was evident in survivors. Decline in episodic memory, semantic memory, working memory, perceptual speed, and visuospatial ability also greatly increased about 3 to 6 years prior to death.On average, cognitive decline sharply accelerates in the last years of life.

Bradykinesia, gait disturbance, rigidity, and tremor are common motor signs in old age. All of these signs are associated with increased morbidity and mortality, but the extent to which they are progressive is unknown.Study participants were 787 older Catholic clergy members without clinically diagnosed PD, related conditions, or dementia at baseline. They were evaluated annually for up to 7 years, with >95% follow-up participation by survivors. Evaluations included administration of a modified version of the motor portion of the Unified PD Rating Scale (UPDRS), from which previously established measures of the global UPDRS and four specific motor signs were derived. Scores represent the percent of the total possible UPDRS score obtained.At baseline, the global UPDRS score ranged from 0 to 36.3 (mean +/- SD, 7.3 +/- 6.4). It increased by an average of 0.69 unit per year during follow-up, with more rapid progression in older persons, but there was wide variability with no progression in 21% of subjects and annual increases of up to 8.23 units in the remaining 79%. Of 129 persons who died, 106 had follow-up UPDRS data. In a proportional hazards model, risk of death was associated with both the level of the global UPDRS score at baseline and the annual rate of progression (both p < 0.001). Overall, risk of death in subjects who had some worsening of the global UPDRS score was 2.93 times the rate among those without progression (95% CI, 1.32-6.50). Gait disorder/postural reflex impairment and rigidity worsened, but bradykinesia and tremor did not. Risk of death was associated with worsening of gait/posture but not with the other signs.Gait disorder and rigidity, as assessed with the modified UPDRS, are usually progressive in old age. Both the severity of the gait disorder and its rate of progression are strongly associated with risk of death.

Muscle-invasive urothelial carcinoma of the bladder is a highly lethal malignancy, particularly in the setting of locally advanced or metastatic disease. Prior reports of HER2/neu (c-erbB-2 or HER2) expression in bladder carcinoma have been mixed; therefore, its value in predicting metastasis or response to therapy has not been established in this tumor type. Thus, the authors evaluated a possible correlation between HER2 expression in patients with high-grade, muscle-invasive urothelial carcinoma of the bladder and outcome in patients who received paclitaxel-based chemotherapy.Archival tumor tissues from patients with advanced urothelial carcinoma who were enrolled on two clinical trials of paclitaxel-based chemotherapy regimens were analyzed for HER2/neu expression by immunohistochemistry (IHC). The authors correlated HER2 expression by IHC with clinical outcomes, such as response rate, progression free survival, and overall survival, using univariate analysis.Thirty-nine tumor specimens were assessed for HER2 expression, most of which (70%) were collected from patients with metastatic disease. All were high-grade urothelial carcinomas (transitional cell carcinomas, Grade 3). Strong HER2 expression (2+/3+) was seen in 28 patients (71%). Patients with responding disease had an HER2 expression rate of 78%, similar to the rate seen in patients with stable disease (75%). In contrast, patients with progressive disease had an HER2 expression rate of 50%, although this difference did not reach statistical significance. However, univariate analysis showed that increased HER2 expression predicted an improvement in progression free and overall survival. When HER2 status was used as a dichotomous variable, tumors with positive HER2 expression did not have any association with response or with progression free survival; however, positive HER2 status was associated significantly with a decreased risk of death (P = 0.03).This study of HER2 expression in bladder carcinoma focused on patients who were treated prospectively in a standardized fashion, unlike prior studies that have evaluated banked, archival specimens. The authors confirmed the findings of others that high-grade, muscle-invasive urothelial carcinoma of the bladder has a significant rate of HER2 expression (71%). However, contrary to other reports, the current study found that HER2 expression in the context of paclitaxel-based chemotherapy decreased the risk of death significantly. Further research is warranted on the possible association of HER2 expression with chemosensitivitiy in urothelial carcinoma as well as the efficacy of HER2-targeted therapies (such as trastuzumab) for patients with high-grade, muscle-invasive urothelial carcinoma of the bladder.