Larry D. Atwood

Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and ∼ 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 × 10⁻⁸), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.

For nearly 60 years, the Framingham Heart Study has examined the natural history, risk factors, and prognosis of cardiovascular, lung, and other diseases. Recruitment of the Original Cohort began in 1948. Twenty-three years later, 3,548 children of the Original Cohort, along with 1,576 of their spouses, enrolled in the Offspring Cohort. Beginning in 2002, 4,095 adults having at least one parent in the Offspring Cohort enrolled in the Third Generation Cohort, along with 103 parents of Third Generation Cohort participants who were not previously enrolled in the Offspring Cohort. The objective of new recruitment was to complement phenotypic and genotypic information obtained from prior generations, with priority assigned to larger families. From a pool of 6,553 eligible individuals, 1,912 men and 2,183 women consented and attended the first examination (mean age: 40 (standard deviation: 9) years; range: 19-72 years). The examination included clinical and laboratory assessments of vascular risk factors and imaging for subclinical atherosclerosis, as well as assessment of cardiac structure and function. The comparison of Third Generation Cohort data with measures previously collected from the first two generations will facilitate investigations of genetic and environmental risk factors for subclinical and overt diseases, with a focus on cardiovascular and lung disorders.

Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations (P = 10(-8) to P = 10(-190)). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport (ATP8B1 and ABCB11), glucose, carbohydrate and lipid metabolism (FADS1, FADS2, GCKR, JMJD1C, HNF1A, MLXIPL, PNPLA3, PPP1R3B, SLC2A2 and TRIB1), glycoprotein biosynthesis and cell surface glycobiology (ABO, ASGR1, FUT2, GPLD1 and ST3GAL4), inflammation and immunity (CD276, CDH6, GCKR, HNF1A, HPR, ITGA1, RORA and STAT4) and glutathione metabolism (GSTT1, GSTT2 and GGT), as well as several genes of uncertain or unknown function (including ABHD12, EFHD1, EFNA1, EPHA2, MICAL3 and ZNF827). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function.

Central abdominal fat is a strong risk factor for diabetes and cardiovascular disease. To identify common variants influencing central abdominal fat, we conducted a two-stage genome-wide association analysis for waist circumference (WC). In total, three loci reached genome-wide significance. In stage 1, 31,373 individuals of Caucasian descent from eight cohort studies confirmed the role of FTO and MC4R and identified one novel locus associated with WC in the neurexin 3 gene [NRXN3 (rs10146997, p = 6.4x10(-7))]. The association with NRXN3 was confirmed in stage 2 by combining stage 1 results with those from 38,641 participants in the GIANT consortium (p = 0.009 in GIANT only, p = 5.3x10(-8) for combined analysis, n = 70,014). Mean WC increase per copy of the G allele was 0.0498 z-score units (0.65 cm). This SNP was also associated with body mass index (BMI) [p = 7.4x10(-6), 0.024 z-score units (0.10 kg/m(2)) per copy of the G allele] and the risk of obesity (odds ratio 1.13, 95% CI 1.07-1.19; p = 3.2x10(-5) per copy of the G allele). The NRXN3 gene has been previously implicated in addiction and reward behavior, lending further evidence that common forms of obesity may be a central nervous system-mediated disorder. Our findings establish that common variants in NRXN3 are associated with WC, BMI, and obesity.

<h3>Summary</h3> Myopia, or nearsightedness, is the most common human eye disorder. A genomewide screen was conducted to map the gene(s) associated with high, early-onset, autosomal dominant myopia. Eight families that each included two or more individuals with ⩾−6.00 diopters (D) myopia, in two or more successive generations, were identified. Myopic individuals had no clinical evidence of connective-tissue abnormalities, and the average age at diagnosis of myopia was 6.8 years. The average spherical component refractive error for the affected individuals was −9.48 D. The families contained 82 individuals; of these, DNA was available for 71 (37 affected). Markers flanking or intragenic to the genes for Stickler syndrome types 1 and 2 (chromosomes 12q13.1-q13.3 and 6p21.3, respectively), Marfan syndrome (chromosome 15q21.1), and juvenile glaucoma (chromosome 1q21-q31) were also analyzed. No evidence of linkage was found for markers for the Stickler syndrome types 1 and 2, the Marfan syndrome, or the juvenile glaucoma loci. After a genomewide search, evidence of significant linkage was found on chromosome 18p. The maximum LOD score was 9.59, with marker D18S481, at a recombination fraction of .0010. Haplotype analysis further refined this myopia locus to a 7.6-cM interval between markers D18S59 and D18S1138 on 18p11.31.

Myopia, or nearsightedness, is the most common eye disorder worldwide. "Pathologic" high myopia, or myopia of <=-6.00 diopters, predisposes individuals to retinal detachment, macular degeneration, cataract, or glaucoma. A locus for autosomal dominant pathologic high myopia has been mapped to 18p11.31. We now report significant linkage of high myopia to a second locus at the 12q21-23 region in a large German/Italian family. The family had no clinical evidence of connective-tissue abnormalities or glaucoma. The average age at diagnosis of myopia was 5.9 years. The average spherical-component refractive error for the affected individuals was -9.47 diopters. Markers flanking or intragenic to the genes for the 18p locus, Stickler syndromes type I and II (12q13.1-q13.3 and 6p21.3), Marfan syndrome (15q21.1), and juvenile glaucoma (chromosome 1q21-q31) showed no linkage to the myopia in this family. The maximum LOD score with two-point linkage analysis in this pedigree was 3.85 at a recombination fraction of .0010, for markers D12S1706 and D12S327. Recombination events identified markers D12S1684 and D12S1605 as flanking markers that define a 30.1-cM interval on chromosome 12q21-23, for the second myopia gene. These results confirm genetic heterogeneity of myopia. The identification of this gene may provide insight into the pathophysiology of myopia and eye development.

In a previous study of normal elderly male twins, the heritability of quantitative white matter hyperintensity (WMH) volume has been estimated to be high (0.73). We investigated heritability of WMH in a family-based sample of the Framingham Heart Study for sex differences and the impact of age.Brain magnetic resonance scans were performed on 2012 individuals in the cohort and offspring of the Framingham study. This report was limited to 1330 stroke-free and dementia-free members (mean age 61.0 years) of the Framingham offspring. Individuals with a history of multiple sclerosis, stroke, dementia, or other neurological condition including traumatic brain injury were excluded from this analysis. WMH volume and total cranial volume (TCV) were quantified using a previously published algorithm. Because of extreme skewing, measures of WMH were log-transformed before analysis. Variance components methods were used to estimate heritability of WMH after adjusting for sex, age, age2, and TCV.In the full dataset, WMH heritability was 0.55 (P<0.0001). Heritability among women was 0.78 (P<0.0001) whereas heritability among men was 0.52 (P<0.0003). Heritability varied as average age increased, with a peak of 0.68 (P<0.0001) in individuals aged 55 or older.Using a family-based study design comprising generally healthy individuals, this study found high heritability of WMH overall and similar heritability for both men and women. In addition, the heritability of WMH remained high among individuals in whom the prevalence of cerebrovascular brain injury was generally low, suggesting that WMH is also likely to be an excellent genetic marker of brain aging.

White matter hyperintensities (WMHs) detectable by magnetic resonance imaging are part of the spectrum of vascular injury associated with aging of the brain and are thought to reflect ischemic damage to the small deep cerebral vessels. WMHs are associated with an increased risk of cognitive and motor dysfunction, dementia, depression, and stroke. Despite a significant heritability, few genetic loci influencing WMH burden have been identified.We performed a meta-analysis of genome-wide association studies (GWASs) for WMH burden in 9,361 stroke-free individuals of European descent from 7 community-based cohorts. Significant findings were tested for replication in 3,024 individuals from 2 additional cohorts.We identified 6 novel risk-associated single nucleotide polymorphisms (SNPs) in 1 locus on chromosome 17q25 encompassing 6 known genes including WBP2, TRIM65, TRIM47, MRPL38, FBF1, and ACOX1. The most significant association was for rs3744028 (p(discovery) = 4.0 × 10(-9) ; p(replication) = 1.3 × 10(-7) ; p(combined) = 4.0 × 10(-15) ). Other SNPs in this region also reaching genome-wide significance were rs9894383 (p = 5.3 × 10(-9) ), rs11869977 (p = 5.7 × 10(-9) ), rs936393 (p = 6.8 × 10(-9) ), rs3744017 (p = 7.3 × 10(-9) ), and rs1055129 (p = 4.1 × 10(-8) ). Variant alleles at these loci conferred a small increase in WMH burden (4-8% of the overall mean WMH burden in the sample).This large GWAS of WMH burden in community-based cohorts of individuals of European descent identifies a novel locus on chromosome 17. Further characterization of this locus may provide novel insights into the pathogenesis of cerebral WMH.

Brain magnetic resonance imaging (MRI) and cognitive tests can identify heritable endophenotypes associated with an increased risk of developing stroke, dementia and Alzheimer's disease (AD). We conducted a genome-wide association (GWA) and linkage analysis exploring the genetic basis of these endophenotypes in a community-based sample.A total of 705 stroke- and dementia-free Framingham participants (age 62 +9 yrs, 50% male) who underwent volumetric brain MRI and cognitive testing (1999-2002) were genotyped. We used linear models adjusting for first degree relationships via generalized estimating equations (GEE) and family based association tests (FBAT) in additive models to relate qualifying single nucleotide polymorphisms (SNPs, 70,987 autosomal on Affymetrix 100K Human Gene Chip with minor allele frequency > or = 0.10, genotypic call rate > or = 0.80, and Hardy-Weinberg equilibrium p-value > or = 0.001) to multivariable-adjusted residuals of 9 MRI measures including total cerebral brain (TCBV), lobar, ventricular and white matter hyperintensity (WMH) volumes, and 6 cognitive factors/tests assessing verbal and visuospatial memory, visual scanning and motor speed, reading, abstract reasoning and naming. We determined multipoint identity-by-descent utilizing 10,592 informative SNPs and 613 short tandem repeats and used variance component analyses to compute LOD scores.The strongest gene-phenotype association in FBAT analyses was between SORL1 (rs1131497; p = 3.2 x 10(-6)) and abstract reasoning, and in GEE analyses between CDH4 (rs1970546; p = 3.7 x 10(-8)) and TCBV. SORL1 plays a role in amyloid precursor protein processing and has been associated with the risk of AD. Among the 50 strongest associations (25 each by GEE and FBAT) were other biologically interesting genes. Polymorphisms within 28 of 163 candidate genes for stroke, AD and memory impairment were associated with the endophenotypes studied at p < 0.001. We confirmed our previously reported linkage of WMH on chromosome 4 and describe linkage of reading performance to a marker on chromosome 18 (GATA11A06), previously linked to dyslexia (LOD scores = 2.2 and 5.1).Our results suggest that genes associated with clinical neurological disease also have detectable effects on subclinical phenotypes. These hypothesis generating data illustrate the use of an unbiased approach to discover novel pathways that may be involved in brain aging, and could be used to replicate observations made in other studies.

The Framingham Heart Study (FHS), founded in 1948 to examine the epidemiology of cardiovascular disease, is among the most comprehensively characterized multi-generational studies in the world. Many collected phenotypes have substantial genetic contributors; yet most genetic determinants remain to be identified. Using single nucleotide polymorphisms (SNPs) from a 100K genome-wide scan, we examine the associations of common polymorphisms with phenotypic variation in this community-based cohort and provide a full-disclosure, web-based resource of results for future replication studies.Adult participants (n = 1345) of the largest 310 pedigrees in the FHS, many biologically related, were genotyped with the 100K Affymetrix GeneChip. These genotypes were used to assess their contribution to 987 phenotypes collected in FHS over 56 years of follow up, including: cardiovascular risk factors and biomarkers; subclinical and clinical cardiovascular disease; cancer and longevity traits; and traits in pulmonary, sleep, neurology, renal, and bone domains. We conducted genome-wide variance components linkage and population-based and family-based association tests.The participants were white of European descent and from the FHS Original and Offspring Cohorts (examination 1 Offspring mean age 32 +/- 9 years, 54% women). This overview summarizes the methods, selected findings and limitations of the results presented in the accompanying series of 17 manuscripts. The presented association results are based on 70,897 autosomal SNPs meeting the following criteria: minor allele frequency > or + 10%, genotype call rate > or = 80%, Hardy-Weinberg equilibrium p-value > or = 0.001, and satisfying Mendelian consistency. Linkage analyses are based on 11,200 SNPs and short-tandem repeats. Results of phenotype-genotype linkages and associations for all autosomal SNPs are posted on the NCBI dbGaP website at http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 webcite.We have created a full-disclosure resource of results, posted on the dbGaP website, from a genome-wide association study in the FHS. Because we used three analytical approaches to examine the association and linkage of 987 phenotypes with thousands of SNPs, our results must be considered hypothesis-generating and need to be replicated. Results from the FHS 100K project with NCBI web posting provides a resource for investigators to identify high priority findings for replication.

Cardiovascular disease (CVD) and its most common manifestations – including coronary heart disease (CHD), stroke, heart failure (HF), and atrial fibrillation (AF) – are major causes of morbidity and mortality. In many industrialized countries, cardiovascular disease (CVD) claims more lives each year than any other disease. Heart disease and stroke are the first and third leading causes of death in the United States. Prior investigations have reported several single gene variants associated with CHD, stroke, HF, and AF. We report a community-based genome-wide association study of major CVD outcomes. In 1345 Framingham Heart Study participants from the largest 310 pedigrees (54% women, mean age 33 years at entry), we analyzed associations of 70,987 qualifying SNPs (Affymetrix 100K GeneChip) to four major CVD outcomes: major atherosclerotic CVD (n = 142; myocardial infarction, stroke, CHD death), major CHD (n = 118; myocardial infarction, CHD death), AF (n = 151), and HF (n = 73). Participants free of the condition at entry were included in proportional hazards models. We analyzed model-based deviance residuals using generalized estimating equations to test associations between SNP genotypes and traits in additive genetic models restricted to autosomal SNPs with minor allele frequency ≥0.10, genotype call rate ≥0.80, and Hardy-Weinberg equilibrium p-value ≥ 0.001. Six associations yielded p < 10-5. The lowest p-values for each CVD trait were as follows: major CVD, rs499818, p = 6.6 × 10-6; major CHD, rs2549513, p = 9.7 × 10-6; AF, rs958546, p = 4.8 × 10-6; HF: rs740363, p = 8.8 × 10-6. Of note, we found associations of a 13 Kb region on chromosome 9p21 with major CVD (p 1.7 – 1.9 × 10-5) and major CHD (p 2.5 – 3.5 × 10-4) that confirm associations with CHD in two recently reported genome-wide association studies. Also, rs10501920 in CNTN5 was associated with AF (p = 9.4 × 10-6) and HF (p = 1.2 × 10-4). Complete results for these phenotypes can be found at the dbgap website http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 . No association attained genome-wide significance, but several intriguing findings emerged. Notably, we replicated associations of chromosome 9p21 with major CVD. Additional studies are needed to validate these results. Finding genetic variants associated with CVD may point to novel disease pathways and identify potential targeted preventive therapies.

Obesity is related to multiple cardiovascular disease (CVD) risk factors as well as CVD and has a strong familial component. We tested for association between SNPs on the Affymetrix 100K SNP GeneChip and measures of adiposity in the Framingham Heart Study. A total of 1341 Framingham Heart Study participants in 310 families genotyped with the Affymetrix 100K SNP GeneChip had adiposity traits measured over 30 years of follow up. Body mass index (BMI), waist circumference (WC), weight change, height, and radiographic measures of adiposity (subcutaneous adipose tissue, visceral adipose tissue, waist circumference, sagittal height) were measured at multiple examination cycles. Multivariable-adjusted residuals, adjusting for age, age-squared, sex, smoking, and menopausal status, were evaluated in association with the genotype data using additive Generalized Estimating Equations (GEE) and Family Based Association Test (FBAT) models. We prioritized mean BMI over offspring examinations (1–7) and cohort examinations (10, 16, 18, 20, 22, 24, 26) and mean WC over offspring examinations (4–7) for presentation. We evaluated associations with 70,987 SNPs on autosomes with minor allele frequencies of at least 0.10, Hardy-Weinberg equilibrium p ≥ 0.001, and call rates of at least 80%. The top SNPs to be associated with mean BMI and mean WC by GEE were rs110683 (p-value 1.22*10-7) and rs4471028 (p-values 1.96*10-7). Please see http://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?id=phs000007 for the complete set of results. We were able to validate SNPs in known genes that have been related to BMI or other adiposity traits, including the ESR1 Xba1 SNP, PPARG, and ADIPOQ. Adiposity traits are associated with SNPs on the Affymetrix 100K SNP GeneChip. Replication of these initial findings is necessary. These data will serve as a resource for replication as more genes become identified with BMI and WC.

Height is a classic complex trait with common variants in a growing list of genes known to contribute to the phenotype. Using a genecentric genotyping array targeted toward cardiovascular-related loci, comprising 49,320 SNPs across approximately 2000 loci, we evaluated the association of common and uncommon SNPs with adult height in 114,223 individuals from 47 studies and six ethnicities. A total of 64 loci contained a SNP associated with height at array-wide significance (p < 2.4 × 10(-6)), with 42 loci surpassing the conventional genome-wide significance threshold (p < 5 × 10(-8)). Common variants with minor allele frequencies greater than 5% were observed to be associated with height in 37 previously reported loci. In individuals of European ancestry, uncommon SNPs in IL11 and SMAD3, which would not be genotyped with the use of standard genome-wide genotyping arrays, were strongly associated with height (p < 3 × 10(-11)). Conditional analysis within associated regions revealed five additional variants associated with height independent of lead SNPs within the locus, suggesting allelic heterogeneity. Although underpowered to replicate findings from individuals of European ancestry, the direction of effect of associated variants was largely consistent in African American, South Asian, and Hispanic populations. Overall, we show that dense coverage of genes for uncommon SNPs, coupled with large-scale meta-analysis, can successfully identify additional variants associated with a common complex trait.

Genetic loci for body mass index (BMI) in adolescence and young adulthood, a period of high risk for weight gain, are understudied, yet may yield important insight into the etiology of obesity and early intervention. To identify novel genetic loci and examine the influence of known loci on BMI during this critical time period in late adolescence and early adulthood, we performed a two-stage meta-analysis using 14 genome-wide association studies in populations of European ancestry with data on BMI between ages 16 and 25 in up to 29 880 individuals. We identified seven independent loci (P < 5.0 × 10−8) near FTO (P = 3.72 × 10−23), TMEM18 (P = 3.24 × 10−17), MC4R (P = 4.41 × 10−17), TNNI3K (P = 4.32 × 10−11), SEC16B (P = 6.24 × 10−9), GNPDA2 (P = 1.11 × 10−8) and POMC (P = 4.94 × 10−8) as well as a potential secondary signal at the POMC locus (rs2118404, P = 2.4 × 10−5 after conditioning on the established single-nucleotide polymorphism at this locus) in adolescents and young adults. To evaluate the impact of the established genetic loci on BMI at these young ages, we examined differences between the effect sizes of 32 published BMI loci in European adult populations (aged 18–90) and those observed in our adolescent and young adult meta-analysis. Four loci (near PRKD1, TNNI3K, SEC16B and CADM2) had larger effects and one locus (near SH2B1) had a smaller effect on BMI during adolescence and young adulthood compared with older adults (P < 0.05). These results suggest that genetic loci for BMI can vary in their effects across the life course, underlying the importance of evaluating BMI at different ages.

We performed a genomewide linkage analysis of six separate measurements of body mass index (BMI) taken over a span of 28 years, from 1971 to 1998, in the Framingham Heart Study. Variance-components linkage analysis was performed on 330 families, using 401 polymorphic markers. The number of individuals with data at each exam ranged from 1,930, in 1971, to 1,401, in 1998. Sex, age, and age squared were included as covariates in the model. There was substantial evidence for linkage on chromosome 6q23-25, in the area of D6S1009, GATA184A08, D6S2436, and D6S305. The six measurements had maximum LOD scores of 4.64, 2.29, 2.41, 1.40, 0.99, and 3.08, respectively, all in the chromosome 6q23-25 region. There was also evidence for linkage of multiple measures on chromosome 11q14 in the area of D11S1998, D11S4464, and D11S912. The six measurements had maximum LOD scores of 0.61, 3.27, 1.30, 0.68, 1.30, and 2.29, respectively, all in the chromosome 11q14 region. Both of these regions have been reported in previous studies. Evidence in the same regions from multiple measurements does not constitute replication; however, it does indicate that linkage studies of BMI are robust with respect to measurement error. It is unclear whether the variation in LOD scores in these regions is due to age effects, varying sample size, or other confounding factors.

Abstract Insulin resistance is part of a metabolic syndrome that also includes non–insulin-dependent diabetes mellitus, dyslipidemia, obesity, and hypertension. It has been hypothesized that insulin resistance represents the primary physiological defect underlying this syndrome. Since insulin resistance is at least partially genetically determined, we hypothesized that genes influencing insulin resistance would have pleiotropic effects on a number of other traits, including triglyceride (TG) and HDL cholesterol levels, body mass index (BMI) and body fat distribution, and blood pressure levels. To investigate this hypothesis, we analyzed data obtained from individuals in 41 families enrolled in the San Antonio Family Heart Study. Statistical methods that take advantage of the relatedness among individuals were used to differentiate between genetic and nongenetic (ie, environmental) contributions to phenotypic variation between traits. Serum levels of fasting and 2-hour insulin (measured in 767 and 743 nondiabetic family members, respectively) were used as a measure of insulin resistance. The genetic correlations were high between insulin levels (both fasting and 2-hour) and each of the following: BMI, HDL level, waist-to-hip ratio, and subscapular-to-triceps ratio, indicating that the same gene, or set of genes, influences each pair of traits. In contrast, the genetic correlations of insulin levels with systolic and diastolic blood pressures were low. We have previously shown that a single diallelic locus accounts for 31% of the phenotypic variation in 2-hour insulin levels in this population. We conducted a bivariate segregation analysis to see if the common genetic effects on insulin and these other traits could be attributable to this single locus. These results indicated a significant effect of the 2-hour insulin locus on fasting insulin levels ( P =.02) and BMI ( P =.05), with the “high” insulin allele associated with higher levels of fasting insulin but lower levels of BMI. There was no detectable effect of this locus on HDL level, TG level, subscapular-to-triceps ratio, or blood pressure. Overall, these results suggest that a common set of genes influencing insulin levels also influences other insulin resistance syndrome–related traits, although for the most part this pleiotropy is not attributable to the 2-hour insulin level major locus.

Huntington disease (HD) is caused by the expansion of a CAG repeat within the coding region of a novel gene on 4p16.3. Although the variation in age at onset is partly explained by the size of the expanded repeat, the unexplained variation in age at onset is strongly heritable (h2=0.56), which suggests that other genes modify the age at onset of HD. To identify these modifier loci, we performed a 10-cM density genomewide scan in 629 affected sibling pairs (295 pedigrees and 695 individuals), using ages at onset adjusted for the expanded and normal CAG repeat sizes. Because all those studied were HD affected, estimates of allele sharing identical by descent at and around the HD locus were adjusted by a positionally weighted method to correct for the increased allele sharing at 4p. Suggestive evidence for linkage was found at 4p16 (LOD=1.93), 6p21-23 (LOD=2.29), and 6q24-26 (LOD=2.28), which may be useful for investigation of genes that modify age at onset of HD.

Adult height is a classic polygenic trait of high heritability (h(2) approximately 0.8). More than 180 single nucleotide polymorphisms (SNPs), identified mostly in populations of European descent, are associated with height. These variants convey modest effects and explain approximately10% of the variance in height. Discovery efforts in other populations, while limited, have revealed loci for height not previously implicated in individuals of European ancestry. Here, we performed a meta-analysis of genome-wide association (GWA) results for adult height in 20,427 individuals of African ancestry with replication in up to 16,436 African Americans. We found two novel height loci (Xp22-rs12393627, P = 3.4×10(-12) and 2p14-rs4315565, P = 1.2×10(-8)). As a group, height associations discovered in European-ancestry samples replicate in individuals of African ancestry (P = 1.7×10(-4) for overall replication). Fine-mapping of the European height loci in African-ancestry individuals showed an enrichment of SNPs that are associated with expression of nearby genes when compared to the index European height SNPs (P<0.01). Our results highlight the utility of genetic studies in non-European populations to understand the etiology of complex human diseases and traits.

Previous studies examining genetic associations with MRI-defined brain infarct have yielded inconsistent findings. We investigated genetic variation underlying covert MRI infarct in persons without histories of transient ischemic attack or stroke. We performed meta-analysis of genome-wide association studies of white participants in 6 studies comprising the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.Using 2.2 million genotyped and imputed single nucleotide polymorphisms, each study performed cross-sectional genome-wide association analysis of MRI infarct using age- and sex-adjusted logistic regression models. Study-specific findings were combined in an inverse-variance-weighted meta-analysis, including 9401 participants with mean age 69.7 (19.4% of whom had >or=1 MRI infarct).The most significant association was found with rs2208454 (minor allele frequency, 20%), located in intron 3 of MACRO domain containing 2 gene and in the downstream region of fibronectin leucine-rich transmembrane protein 3 gene. Each copy of the minor allele was associated with lower risk of MRI infarcts (odds ratio, 0.76; 95% confidence interval, 0.68-0.84; P=4.64x10(-7)). Highly suggestive associations (P<1.0x10(-5)) were also found for 22 other single nucleotide polymorphisms in linkage disequilibrium (r(2)>0.64) with rs2208454. The association with rs2208454 did not replicate in independent samples of 1822 white and 644 black participants, although 4 single nucleotide polymorphisms within 200 kb from rs2208454 were associated with MRI infarcts in the black population sample.This first community-based, genome-wide association study on covert MRI infarcts uncovered novel associations. Although replication of the association with top single nucleotide polymorphisms failed, possibly because of insufficient power, results in the black population sample are encouraging, and further efforts at replication are needed.

This chapter provides an introduction to the Framingham Heart Study and the genetic research related to cardiovascular diseases conducted in this unique population. It briefly describes the origins of the study, the risk factors that contribute to heart disease, and the approaches taken to discover the genetic basis of some of these risk factors. The genetic architecture of several biological risk factors has been explained using family studies, segregation analysis, heritability, and phenotypic and genetic correlations. Many quantitative trait loci underlying cardiovascular diseases have been discovered using different molecular markers. Additionally, initial results from genome-wide association studies using 116,000 markers and the prospects of using 550,000 markers for association studies are presented. Finally, the use of this unique sample to study genotype and environment interactions is described.

Myopia is a complex genetic disorder and a common cause of visual impairment among working age adults. Genome-wide association studies have identified susceptibility loci on chromosomes 15q14 and 15q25 in Caucasian populations of European ancestry. Here, we present a confirmation and meta-analysis study in which we assessed whether these two loci are also associated with myopia in other populations. The study population comprised 31 cohorts from the Consortium of Refractive Error and Myopia (CREAM) representing 4 different continents with 55,177 individuals; 42,845 Caucasians and 12,332 Asians. We performed a meta-analysis of 14 single nucleotide polymorphisms (SNPs) on 15q14 and 5 SNPs on 15q25 using linear regression analysis with spherical equivalent as a quantitative outcome, adjusted for age and sex. We calculated the odds ratio (OR) of myopia versus hyperopia for carriers of the top-SNP alleles using a fixed effects meta-analysis. At locus 15q14, all SNPs were significantly replicated, with the lowest P value 3.87 × 10(-12) for SNP rs634990 in Caucasians, and 9.65 × 10(-4) for rs8032019 in Asians. The overall meta-analysis provided P value 9.20 × 10(-23) for the top SNP rs634990. The risk of myopia versus hyperopia was OR 1.88 (95 % CI 1.64, 2.16, P < 0.001) for homozygous carriers of the risk allele at the top SNP rs634990, and OR 1.33 (95 % CI 1.19, 1.49, P < 0.001) for heterozygous carriers. SNPs at locus 15q25 did not replicate significantly (P value 5.81 × 10(-2) for top SNP rs939661). We conclude that common variants at chromosome 15q14 influence susceptibility for myopia in Caucasian and Asian populations world-wide.

This study presents genome scans for hypertension and blood pressures from 2959 individuals in 500 white families from the National Heart, Lung, and Blood Institute Family Heart Study. Genome scans were performed with different methods of handling the 27% of individuals taking antihypertensive medications. Variance components LOD scores were estimated by assigning medicated hypertensive individuals (1) to have a blood pressure of 140/90; (2) to be missing; and (3) to have a randomly assigned systolic blood pressure between 140 and 160 (N[150,5] distribution) and diastolic blood pressure between 90 and 100 mm Hg (N[95,2.5] distribution). There were 5 regions with heterogeneity LOD scores > or =2.0 for hypertension (unadjusted for multiple models): 2.8 on chromosome 1 (192 cM), 2.6 on chromosome 7 (58 cM), 2.0 on chromosome 7 (127 cM), 2.4 on chromosome 12 (83 cM), and 2.4 on chromosome 15 (103 cM). Diastolic blood pressure had no LOD scores > or =2.0. Only chromosome 6 showed linkage for systolic blood pressure, with a LOD score of 3.3 at 88.7 cM from the initial randomization. Multiple randomizations of medicated subjects' systolic blood pressures yielded a mean LOD score of 2.8+/-0.4, whereas setting medicated systolic blood pressures to 140 mm Hg yielded a LOD score of 3.3. Excluding the medicated individuals or using their treated blood pressures reduced the LOD scores to 0.8 and 1.3, respectively, indicating the importance of including the extremes of quantitative trait distributions in linkage analyses. These results overlap other published scans, particularly regions on chromosomes 1 and 6, which have been implicated in familial combined hyperlipidemia.

Linkage studies have mapped a susceptibility gene for type 2 diabetes to the long arm of chromosome 10, where we have previously identified a quantitative trait locus that affects fasting blood glucose within the Framingham Heart Study cohort. One candidate gene in this region is the insulin-degrading enzyme (IDE), which, in the GK rat model, has been associated with nonobese type 2 diabetes. Single nucleotide polymorphisms (SNPs) were used to map a haplotype block in the 3' end of IDE, which revealed association with HbA(1c), fasting plasma glucose (FPG), and mean fasting plasma glucose (mFPG) measured over 20 years. The strongest associations were found in a sample of unrelated men. The lowest trait values were associated with a haplotype (TT, f approximately 0.32) containing the minor allele of rs2209772 and the major allele of the rs1887922 SNP (FPG P < 0.001, mFPG P < 0.003, HbA(1c) P < 0.025). Another haplotype (CC, f approximately 0.16) was associated with elevated HbA(1c) (P < 0.002) and type 2 diabetes (P < 0.001, odds ratio 1.96, 95% CI 1.28-3.00). The evidence presented supports the possibility that IDE is a susceptibility gene for diabetes in populations of European descent.

The genetic mechanisms that control variation in blood pressure level are largely unknown. One of the first steps in understanding those mechanisms is the localization of the genes that have a significant effect on blood pressure. We performed genome scans of systolic (SBP) and diastolic blood pressure (DBP) on a population-based sample of families in the San Antonio Family Heart Study. A likelihood-based Mendelian model incorporating genotype-specific effects of sex, age, age(2), BMI, and blood pressure (SBP or DBP, as appropriate) as covariates was used to perform two-point lodscore (Z) linkage on 399 polymorphic markers. Results showed that the genotype-specific covariate effects were highly significant for both SBP and DBP. Linkage results showed that a quantitative trait locus (QTL) influencing DBP was significantly linked to D2S1790 (Z = 3.92, theta = 0.00) and showed suggestive linkage to D8S373 (Z = 1.92, theta = 0.00). A QTL influencing SBP showed suggestive linkage to D21S1440 (Z = 2.82, theta = 0.00) and D18S844 (Z = 2.09, theta = 0.11). Without the genotype-specific effects in the model, the linkage to D2S1790 was not even suggestive (Z = 1.33, theta = 0.09); thus genotype-specific modeling was crucial in detecting this linkage. A comparison with linkage studies based in other populations showed that the significant linkage to D2S1790 has been replicated at the same marker in the Quebec Family Study. The replicated significant linkage at D2S1790 may begin to establish the locations of the genes that significantly affect blood pressure across several human ethnic groups.

Decreased renal function is often a complication of hypertension. Although it has been suggested that the response of the kidney to hypertension has an underlying genetic component, there is limited information suggesting that specific genetic regions or candidate genes contribute to the variability in creatinine clearance, a commonly used measure of kidney function. As part of the Hypertension Genetic Epidemiology Network (HyperGEN) study, creatinine clearance measurements were assessed in a large biracial sample of hypertensive siblings (466 African American subjects and 634 white subjects in 215 and 265 sibships, respectively). All participants were hypertensive before the age of 60 years, and the mean age of the siblings was 52 years among the African American subjects and 61 years among the white subjects. Two residual models were created for creatinine clearance: a minimally adjusted model (which included age and age(2)) and a fully adjusted model (which included age, age(2), lean body mass, pulse rate, pulse pressure, hormone-replacement therapy, educational status, and physical activity). Standardized residuals were calculated separately for men and women in both racial groups. The heritability of the residual creatinine clearance was 17% and 18% among the African American and white subjects, respectively. We conducted multipoint variance components linkage analysis using GENEHUNTER2 and 387 anonymous markers (Cooperative Human Linkage Center screening set 8). The best evidence for linkage in African American subjects was found on chromosome 3 (LOD = 3.61 at 214.6 cM, 3q27) with the fully adjusted model, and the best evidence in white subjects was found on chromosome 3 (LOD = 3.36 at 115.1 cM) with the minimally adjusted model. Positional candidate genes that are contained in and around the region on chromosome 3 (214.6 cM) that may contribute to renal function include enoyl-CoA hydratase/3-hydroxyacyl-CoA dehydrogenase (EHHADH) and apolipoprotein D (ApoD). These findings suggest there may be genetic regions related to the variability of creatinine clearance among hypertensive individuals.

Bornholm eye disease (BED) consists of X-linked high myopia, high cylinder, optic nerve hypoplasia, reduced electroretinographic flicker with abnormal photopic responses, and deuteranopia. The disease maps to chromosome Xq28 and is the first designated high-grade myopia locus (MYP1). We studied a second family from Minnesota with a similar X-linked phenotype, also of Danish descent. All affected males had protanopia instead of deuteranopia.X chromosome genotyping, fine-point mapping, and haplotype analysis of the DNA from 22 Minnesota family individuals (8 affected males and 5 carrier females) and 6 members of the original family with BED were performed. Haplotype comparisons and mutation screening of the red-green cone pigment gene array were performed on DNA from both kindreds.Significant maximum logarithm of odds scores of 3.38 and 3.11 at theta = 0.0 were obtained with polymorphic microsatellite markers DXS8106 and DXYS154, respectively, in the Minnesota family. Haplotype analysis defined an interval of 34.4 cM at chromosome Xq27.3-Xq28. Affected males had a red-green pigment hybrid gene consistent with protanopia. We genotyped Xq27-28 polymorphic markers of the family with BED, and narrowed the critical interval to 6.8 cM. The haplotypes of the affected individuals were different from those of the Minnesota pedigree. Bornholm eye disease-affected individuals showed the presence of a green-red hybrid gene consistent with deuteranopia.Because of the close geographic origin of the 2 families, we expected affected individuals to have the same haplotype in the vicinity of the same mutation. Mapping studies, however, suggested independent mutations of the same gene. The red-green and green-red hybrid genes are common X-linked color vision defects, and thus are unrelated to the high myopia and other eye abnormalities in these 2 families.X-linked high myopia with possible cone dysfunction has been mapped to chromosome Xq28 with intervals of 34.4 and 6.8 centimorgan for 2 families of Danish origin.

Polymorphisms in estrogen receptor-alpha (ESR1) may be associated with variation in body mass index and waist circumference. However, most prior studies have been limited by sample size and power.DNA from 1763 unrelated men and women (mean age, 56 yr) from the Framingham Heart Study offspring cohort was genotyped for four ESR1 polymorphisms: T30C (rs2077647) in exon 1, PvuII (rs2234693), and XbaI (rs 9340799) in intron 1, and C1335G (rs 1801132) in exon 4.Men homozygous for the PvuII C allele (frequency, 0.45) had lower waist circumference (99.3 cm), compared with TT homozygous men (99.8 cm) and heterozygotes (100.6 cm) (P < 0.004). Similar results were obtained with XbaI, which lies in the same linkage disequilibrium block. C1335G also demonstrated a gender-specific association: men with CG or GG genotypes had lower mean body mass index, 27.7 and 27.9 kg/m2 respectively, compared with 28.6 kg/m2 among the CC homozygotes (P < 0.01). No significant associations were seen with T30C, nor were associations observed among women.Polymorphisms in ESR1 are associated with measures of adiposity in men. These associations further support the hypothesis that the intron 1 region of ESR1 influences phenotypes important for cardiovascular risk.

Background and Purpose— White matter hyperintensity (WMH) volume is associated with aging and cerebrovascular disease and has been demonstrated to have a high heritability in the Framingham Heart Study as well as in other studies. We performed a genome-wide linkage analysis to identify chromosomal regions that may harbor genes influencing WMH in a family-based sample of the Framingham Heart Study. Methods— Brain magnetic resonance scans were performed, and WMH and total cranial volume (TCV) were quantified as previously described on 2259 cohort and offspring participants. The outcome used for linkage analysis was an age specific (within 10-year age groups) z-score for the natural logarithm of the ratio of WMH to TCV. This z-score was based on 2230 individuals after excluding 26 participants with neurological conditions other than stroke and 3 individuals whose ages were out of range. Variance component linkage analysis included 747 individuals (mean age=62.16±12.43 years) with both magnetic resonance measure and genotype information in 237 families. Mean percent WMH to TCV was 0.098±0.175 with a range of 0.00025% to 1.37% in the linkage analysis subjects. Results— A maximum multipoint logarithm of the odds (LOD) score=3.69, which indicates significant evidence of linkage, was observed at 4 cM on chromosome 4. A suggestive peak with LOD=1.78 was observed at 95 cM on chromosome 17. Conclusion— We have significant evidence that a gene influencing WMH volume is located on chromosome 4 of the human genome.

Genetic Analysis Workshop 16 (GAW16) Problem 2 presented data from the Framingham Heart Study (FHS), an observational, prospective study of risk factors for cardiovascular disease begun in 1948. Data have been collected in three generations of family participants in the study and the data presented for GAW16 included phenotype data from all three generations, with four examinations of data collected repeatedly for the first two generations. The trait data consisted of information on blood pressure, hypertension treatment, lipid levels, diabetes and blood glucose, smoking, alcohol consumed, weight, and coronary heart disease incidence. Additionally, genotype data obtained through a genome-wide scan (FHS SHARe) of 550,000 single-nucleotide polymorphisms from Affymetrix chips were included with the GAW16 data. The genotype data were also used for GAW16 Problem 3, where simulated phenotypes were generated using the actual FHS genotypes. These data served to provide investigators with a rich resource to study the behavior of genome-wide scans with longitudinally collected family data and to develop and apply new procedures.

We conducted a genome-wide scan for quantitative trait loci influencing the systolic blood pressure, diastolic blood pressure, and pulse responses to a postural challenge in 498 white sibling-pairs from the Hypertension Genetic Epidemiology Network, a multicenter study of the genetic susceptibility to hypertension. All participants were hypertensive (systolic blood pressure >/=140 mm Hg, diastolic blood pressure >/=90 mm Hg, or on antihypertensive medications) with diagnosis before age 60. Blood pressure and pulse were measured by an oscillometric method after a 5-minute rest in a supine position and again immediately on standing. The genome scan included a total of 387 autosomal short-tandem-repeat polymorphisms typed by the National Heart, Lung, and Blood Institute Mammalian Genotyping Service at Marshfield. We used multipoint variance-components linkage analysis to identify possible quantitative trait loci influencing postural change phenotypes after adjusting for sex, age, and use of antihypertensive medications. There was suggestive evidence for linkage on chromosome 18q for the postural systolic blood pressure response (maximum logarithm of the odds score=2.6 at 80 centiMorgans). We also observed a maximum logarithm of the odds score of 1.9 for the systolic blood pressure response and 1.7 for the diastolic blood pressure response on chromosome 6p. The marker that demonstrated the strongest evidence for linkage for the systolic blood pressure response (D18S858) lies within 20 centiMorgans of a marker previously linked to rare familial orthostatic hypotensive syndrome. Our findings indicate that there may be 1 or more genes on chromosome 18q that regulate systolic blood pressure during the physiological recovery period after a postural stressor.

We conducted a genome-wide linkage scan for quantitative trait loci influencing total HDL-cholesterol (HDL-C) concentration in a sample of 1027 whites from 101 families participating in the NHLBI Family Heart Study. To maximize the relative contribution of genetic components of variance to the total variance of HDL-C, the HDL-C phenotype was adjusted for age, age(2), body mass index, and Family Heart Study field center, and standardized HDL-C residuals were created separately for men and women. All analyses were completed by the variance components method, as implemented in the program GENEHUNTER using 383 anonymous markers typed at the NHLBI Mammalian Genotyping Service in Marshfield, Wis. Evidence for linkage of residual HDL-C was detected near marker D5S1470 at location 39.9 cM from the p-terminal of chromosome 5 (LOD=3.64). Suggestive linkage was detected near marker D13S1493 at location 27.5 cM on chromosome 13 (LOD=2.36). We conclude that at least 1 genomic region is likely to harbor a gene that influences interindividual variation in HDL cholesterol.

Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.

While several loci for BMI have been identified, it is not known whether genes underlie the process of regional fat deposition. We sought to test whether waist circumference, a measure of central adiposity, contains a genetic component. Variance components linkage analysis was performed on 330 families from the Framingham Heart Study original and offspring cohorts, using a 10-cM genome-wide linkage analysis. Overall, 2,086 subjects (51% women), mean age 48 years, were available for analysis. The overall heritability of waist circumference was 0.41. The maximum logarithm of odds (LOD) score in the full dataset was 3.3 on chromosome 6 at marker D6S1009; when subjects were limited to those aged <60 years, the peak LOD score was 3.7 at the same location. Substantial evidence exists for linkage to waist circumference, a measure of central adiposity. Potential candidate genes include ESR1, OPRM1, and NMBR. Further research is necessary to understand the genes involved in central adiposity.

The authors studied 300 patients with pathologically confirmed cancer of the trachea, bronchus, or lung in a 16-parish (county) area of southern Louisiana. Squamous-cell carcinoma was observed most frequently among these patients (39.3%), with nearly equal numbers of adenocarcinoma (25.0%) and small cell varieties (25.5%). Patients with large cell cancer, the least frequent type (10.3%), were 4.6 years younger on average than those with small cell (P less than 0.05) or squamous cell (P less than 0.05) neoplasias. Squamous cell neoplasia was more frequent among men (45.5%) than women (22.0%) (P less than 0.05). To assess whether family history differed according to the histologic cell type of the index family member, 248 patients were interviewed with regard to a family history of neoplasia. Those with small cell cancer had the highest family-size adjusted mean number of lung cancers per family (0.28). This was 2.2 times greater than the mean number of affected persons among relatives of patients with adenocarcinoma and 1.5 times greater than the mean for the families of patients with large or squamous cell types. However, none of these differences was statistically significant. Similar results were obtained when the total number of cancers at all sites was tabulated. Probands with small cell neoplasia were again most likely to have a positive family history, but the differences between histologic types were small. Although these data suggest an association, a larger study sample is required to determine conclusively whether or not a family history of lung cancer differs according to histologic type.

High myopia (>-6.00 diopters) is a complex common disorder that predisposes individuals to retinal detachment, glaucoma, macular degeneration, and premature cataracts. A recent linkage analysis of seven families with autosomal dominant high myopia has identified one locus (MYP2) for high myopia on chromosome 18p11.31 (Young et al.: Am J Hum Genet 1998;63:109-119). Haplotype analysis revealed an initial interval of 7.6 centimorgans (cM).Transmission disequilibrium tests (TDT) with both the Statistical Analysis for Genetic Epidemiology (SAGE) 3.1 TDTEX and GENEHUNTER 2 (GH2) programs were performed using chromosome 18p marker alleles for this interval.Using SAGE analysis, the following p values were obtained for markers in marker order in this region: D18S1146 (p = 0.227), D18S481 (p = 0.001), D18S63 (p = 0.062), D18S1138 (p = 0.0004), D18S52 (p = 1.79 x 10(-6)), and D18S62 (p = 0.141). GH2 TDT analysis revealed the following p values for the best allele for the markers: D18S1146 (p = 0.083), D18S481 (p = 0.108), D18S63 (p = 0.034), D18S1138 (p = 0.011), D18S52 (p = 0.007), and D18S62 (p = 0.479).These data suggest that the gene for 18p11.31-linked high myopia is most proximal to marker D18S52, with a likely interval of 0.8 cM between markers D18S63 and D18S52. Due to the contraction of the interval size by TDT, these results provide a basis for focused positional cloning and candidate gene analysis at the MYP2 locus.

The blood pressure (BP) and heart rate responses to exercise treadmill testing predict incidence of cardiovascular disease, but the genetic determinants of hemodynamic and chronotropic responses to exercise are largely unknown.We assessed systolic BP, diastolic BP, and heart rate during the second stage of the Bruce protocol and at the third minute of recovery in 2982 Framingham Offspring participants (mean age 43 years; 53% women). With use of residuals from multivariable models adjusted for clinical correlates of exercise treadmill testing responses, we estimated the heritability (variance-components methods), genetic linkage (multipoint quantitative trait analyses), and association with 235 single-nucleotide polymorphisms in 14 candidate genes selected a priori from neurohormonal pathways for their potential role in exercise treadmill testing responses. Heritability estimates for heart rate during exercise and during recovery were 0.32 and 0.34, respectively. Heritability estimates for BP variables during exercise were 0.25 and 0.26 (systolic and diastolic BP) and during recovery, 0.16 and 0.13 (systolic and diastolic BP), respectively. Suggestive linkage was found for systolic BP during recovery from exercise (locus 1q43-44, log-of-the-odds score 2.59) and diastolic BP during recovery from exercise (locus 4p15.3, log-of-the-odds score 2.37). Among 235 single-nucleotide polymorphisms tested for association with exercise treadmill testing responses, the minimum nominal probability value was 0.003, which was nonsignificant after adjustment for multiple testing.Hemodynamic and chronotropic responses to exercise are heritable and demonstrate suggestive linkage to select loci. Genetic mapping with newer approaches such as genome-wide association may yield novel insights into the physiological responses to exercise.

Heritability and genetic and environmental correlations of total and regional brain volumes were estimated from a large, generally healthy, community-based sample, to determine if there are common elements to the genetic influence of brain volumes and white matter hyperintensity (WMH) volume. There were 1538 Framingham Heart Study participants with brain volume measures from quantitative magnetic resonance imaging who were free of stroke and other neurologic disorders that might influence brain volumes and who were members of families with at least 2 Framingham Heart Study participants. Heritability was estimated using variance component methodology and adjusting for the components of the Framingham stroke risk profile. Genetic and environmental correlations between traits were obtained from bivariate analysis. Heritability estimates ranging from 0.46 to 0.60 were observed for total brain, WMH, hippocampal, temporal lobe, and lateral ventricular volumes. Moderate, yet significant, heritability was observed for the other measures. Bivariate analyses demonstrated that relationships between brain volume measures, except for WMH, reflected both moderate to strong shared genetic and shared environmental influences. This study confirms strong genetic effects on brain and WMH volumes. These data extend current knowledge by showing that these 2 different types of magnetic resonance imaging measures do not share underlying genetic or environmental influences.

Pulse pressure, a measure of aortic stiffness, is a strong predictor of cardiovascular mortality. To locate genes that affect pulse pressure, we performed genetic analysis on randomly ascertained families in the San Antonio Family Heart Study. Pulse pressure was defined as the difference between systolic and diastolic blood pressures. Likelihood methods were used to construct a model that had both single-locus and polygenic components for 46 families (1308 individuals). The single-locus component included sex-specific and genotype-specific effects of both age and body mass index. Using this model, we then performed 2-point linkage analysis in 10 families (440 individuals) that were among the largest of the 46 families and that had been genotyped for 399 polymorphic markers. The model that contained only the polygenic component and simple effects of the covariates showed pulse pressure heritability of 0.21. When the single-locus component was added, the sex-specific and genotype-specific effects of age and body mass index were highly significant (P<0.002). The full model accounted for 73% of the total variation of pulse pressure. Linkage analysis using this model with each marker revealed 4 markers with lod scores >1.9, which is the Lander-Kruglyak suggestive linkage standard. D21S1440 had a lod score of 2.78 with a recombination fraction (theta) of 0.02. D7S1799 had a lod score of 2.04 (theta=0.01), D8S1100 had a lod score of 1.98 (theta=0.08), and D18S844 had a lod score of 1.95 (theta=0.11). These results are highly correlated with results involving systolic blood pressure, indicating that pulse pressure may not be genetically distinct from systolic blood pressure.

Essential hypertension has been linked to a highly polymorphic marker at the angiotensinogen locus, and association with a polymorphism in this locus has been found in some populations. We tested the hypothesis that these same polymorphic markers are linked to essential hypertension in Mexican Americans. The data comprised all the affected relative pairs in 46 extended families chosen at random from a low-income barrio in San Antonio. Specifically, we searched for linkage by testing for excessive marker alleles shared identical by descent (IBD) among hypertensive relative pairs. When women taking oral contraceptives or hormones were excluded, the affected relative pairs shared a significant excess of alleles IBD for the highly heterozygous GT repeat polymorphism (P=.038) and were marginally significant for the M235T variant (P=.079), which has a much lower heterozygosity (0.43 versus 0.85 for the GT repeat). We also assayed plasma levels of angiotensinogen and, using likelihood methods, found no significant association (P=.43) between plasma levels of angiotensinogen and M235T genotypes. These results support the linkage of essential hypertension to the angiotensinogen locus but do not indicate a specific role for the M235T variant.

Once a significant linkage is found, an important goal is reducing the error in the estimated location of the linked locus. A common approach to reducing location error, called fine-mapping, is the genotyping of additional markers in the linked region to increase the genetic information. The utility of fine-mapping for quantitative trait linkage analysis is largely unknown. To explore this issue, we performed a fine-mapping simulation in which the region containing a significant linkage at a 10-centiMorgan (cM) resolution was fine-mapped at 2, 1, and 0.5 cM. We simulated six quantitative trait models in which the proportion of variation due to the quantitative trait locus (QTL) ranged from 0.20-0.90. We used four sampling designs that were all combinations of 100 and 200 families of sizes 5 and 7. Variance components linkage analysis (Genehunter) was performed until 1,000 replicates were found with a maximum lodscore greater than 3.0. For each of these 1,000 replications, we repeated the linkage analysis three times: once for each of the fine-map resolutions. For the most realistic model, reduction in the average location error ranged from 3-15% for 2-cM fine-mapping and from 3-18% for 1-cM fine-mapping, depending on the number of families and family size. Fine-mapping at 0.5 cM did not differ from the 1-cM results. Thus, if the QTL accounts for a small proportion of the variation, as is the case for realistic traits, fine-mapping has little value.

Spirometric measures of pulmonary function have been shown to be highly heritable and evidence for major genes influencing forced expiratory volume in 1 s (FEV1) and forced vital capacity (FVC) have been reported. A genome scan of pulmonary traits in the Framingham Heart Study identified a region on chromosome 6qter with evidence for linkage to FEV1 and the FEV1/FVC ratio. For this study, additional markers were genotyped in the region to refine the location of linkage and test for association. Variance component linkage analysis was performed using GENEHUNTER, and family-based association tests were performed using FBAT. The chromosome 6 telomeric region provided significant evidence of linkage with the additional markers, resulting in a maximum multipoint LOD score of 5.0 for FEV1 at 184.5 cM. LOD scores for FVC and the FEV1/FVC ratio were also above 1.0 in this region. Evidence for association with FEV1 and FVC was observed with D6S281 at 190 cM. The strongest effect was seen with the 224 allele, which was associated with higher levels of FEV1 and FVC in allele carriers compared with those carrying other alleles. This study supports the presence of a gene influencing pulmonary function on the q-terminus of chromosome 6 in the region of 184 cM (D6S503) to 190 cM (D6S281).

Angiotensin-converting enzyme (ACE) activity is highly heritable and has been associated with cardiovascular disease. We are studying the effects of genes and environmental factors on hypertension and related phenotypes, such as ACE activity, in Mexican-American families. In the current study, we performed multipoint linkage analysis to search for quantitative trait loci (QTLs) that affect ACE activities on data from 793 individuals from 29 pedigrees from the San Antonio Family Heart Study. As expected, we obtained strong evidence (maximum log of the odds [LOD]=4.57, genomic P=0.003) that a QTL for ACE activity is located on chromosome 17 near the ACE structural locus. We subsequently performed linkage analyses conditional on the effect of this QTL and obtained strong evidence (LOD=3.34) for a second QTL on chromosome 4 near D4S1548. We next incorporated the ACEIns/Del genotypes in our analyses and removed the evidence for the chromosome 17 QTL (maximum LOD=0.60); however, we retained our evidence for the QTL on chromosome 4q. We conclude that the QTL on chromosome 17 is tightly linked to ACE and is in strong disequilibrium with the insertion/deletion polymorphism, which is consistent with other reports. We also have evidence that an additional QTL affects ACE activity. Identification of this additional QTL might lead to alternate means of prophylaxis.

Background: Weight gain adversely affects blood pressure, lipids, and glycemia. The genetic contribution to weight change is unknown.

Although previous genome scans have searched for quantitative-trait loci (QTLs) influencing variation in blood pressure (BP), few have investigated the rate of change in BP over time as a phenotype. Here, we compare results from genomewide scans to localize QTLs for systolic, diastolic, and mean arterial BPs (SBP, DBP, and MBP, respectively) and for rates of change in systolic, diastolic, and mean arterial BPs (rSBP, rDBP, and rMBP, respectively), with use of the longitudinal data collected about Mexican Americans of the San Antonio Family Heart Study (SAFHS). Significant evidence of linkage was found for rSBP (LOD 4.15) and for rMBP (LOD 3.94) near marker D11S4464 located on chromosome 11q24.1. This same chromosome 11q region also shows suggestive linkage to SBP (LOD 2.23) and MBP (LOD 2.37) measurements collected during the second clinic visit. Suggestive evidence of linkage to chromosome 5 was also found for rMBP, to chromosome 16 for rSBP, and to chromosomes 1, 5, 6, 7, and 21 for the single-time-point BP traits collected at the first two SAFHS clinic visits. We also present results from fine mapping the chromosome 11 QTL with use of SNP-association analysis within candidate genes identified from a bioinformatic search of the region and from whole-genome transcriptional expression data collected from 1,240 SAFHS participants. Our results show that the use of longitudinal BP data to calculate the rate of change in BP over time provides more information than do the single-time measurements, since they reveal physiological trends in the subjects that a single-time measurement could never capture. Further investigation of this region is necessary for the identification of the genetic variation responsible for QTLs influencing the rate of change in BP.

Abstract Extensive efforts have been aimed at understanding the genetic underpinnings of complex diseases that affect humans. Numerous genome‐wide association studies have assessed the association of genes with human disease, including the Framingham Heart Study (FHS), which genotyped 550,000 SNPs in 9,000 participants. The success of such efforts requires high rates of consent by participants, which is dependent on ethical oversight, communications, and trust between research participants and investigators. To study this we calculated percentages of participants who consented to collection of DNA and to various uses of their genetic information in two FHS cohorts between 2002 and 2009. The data included rates of consent for providing a DNA sample, creating an immortalized cell line, conducting research on various genetic conditions including those that might be considered sensitive, and for notifying participants of clinically significant genetic findings were above 95%. Only with regard to granting permission to share DNA or genetic findings with for‐profit companies was the consent rate below 95%. We concluded that the FHS has maintained high rates of retention and consent for genetic research that has provided the scientific freedom to establish collaborations and address a broad range of research questions. We speculate that our high rates of consent have been achieved by establishing frequent and open communications with participants that highlight extensive oversight procedures. Our approach to maintaining high consent rates via ethical oversight of genetic research and communication with study participants is summarized in this report and should be of help to other studies engaged in similar types of research. Published 2010 Wiley‐Liss, Inc.

Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and approximately 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 x 10(-)(8)), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.

Arterial stiffness is reported in numerous family studies to be heritable. Linkage analysis has identified genomic regions that likely harbor genes contributing to its phenotypic expression. We sought to identify loci contributing to arterial stiffness in a large group of African-American hypertensive families.We performed a genome scan on 1251 African Americans in families participating in the HyperGEN (Hypertension Genetic Epidemiology Network) study. Children of the hypertensive proband generation were also included in the analysis. Arterial stiffness was estimated as pulse pressure (PP; systolic - diastolic blood pressure [BP]) divided by echocardiographically determined stroke volume (SV). The PP/SV ratio was adjusted for several nongenetic sources of variation, including demographic and lifestyle factors. The residual phenotype was analyzed using multipoint variance components linkage implemented in SOLAR 2.0.3.Arterial stiffness was 20% heritable in African Americans. Two regions were highly suggestive of linkage, one between markers D1S1665 and D1S1728 in the 215-cM region of chromosome 1 (LOD = 3.08), and another between D14S588 and D14S606 in the 85-cM region of chromosome 14 (LOD = 2.42). Two candidate genes (GPR-25, SMOC-1) are located in the linked regions. SMOC-1 is of physiological interest because it codes a secreted glycoprotein with five domains, each containing regions homologous to those on other proteins that mediate cell-matrix interactions. GPR-25 is homologous to receptors involved in BP regulation.At least two chromosomal regions in humans are likely to harbor genes contributing to interindividual variation in PP/SV ratio, an index of arterial stiffness, in African Americans.

Previously, we reported significant linkage of body mass index (BMI) to chromosomes 6 and 11 across six examinations, covering 28 years, of the Framingham Heart Study. These results were on all individuals available at each exam, thus the sample size varied from exam to exam. To remove any effect of sample size variation we have now constructed six subsets; for each exam individuals were only included if they were measured at every exam, i.e. for each exam, included individuals comprise the intersection of the original six exams. This strategy preferentially removed older individuals who died before reaching the sixth exam, thus the intersection datasets are smaller (n = 1114) and significantly younger than the full datasets. We performed variance components linkage analysis on these intersection datasets and on their sex-specific subsets.Results from the sex-specific genome scans revealed 11 regions in which a sex-specific maximum lodscore was at least 2.0 for at least one dataset. Randomization tests indicated that all 11 regions had significant (p < 0.05) differences in sex-specific maximum lodscores for at least three datasets. The strongest sex-specific linkage was for men on chromosome 16 with maximum lodscores 2.70, 3.00, 3.42, 3.61, 2.56 and 1.93 for datasets 1-6 respectively. Results from the full genome scans revealed that linked regions on chromosomes 6 and 11 remained significantly and consistently linked in the intersection datasets. Surprisingly, the maximum lodscore on chromosome 10 for dataset 1 increased from 0.97 in the older original dataset to 4.23 in the younger smaller intersection dataset. This difference in maximum lodscores was highly significant (p < 0.0001), implying that the effect of this chromosome may vary with age. Age effects may also exist for the linked regions on chromosomes 6 and 11.Sex specific effects of chromosomal regions on BMI are common in the Framingham study. Some evidence also exists for age-specific effects of chromosomal regions.

Genome scans for identifying susceptibility loci for pulse pressure have produced inconclusive results. A heterogeneity-based genome search meta-analysis was applied to available genome-scan data on pulse pressure. A genome search meta-analysis divides the whole genome into 120 bins and identifies bins that rank high on average in terms of linkage statistics across genome scans unweighted or weighted by study size. The significance of each bin's average rank (right-sided test) and heterogeneity among studies (left-sided test) was calculated using a Monte Carlo test. The meta-analysis involved 7 genome scans, 3 consisting of subjects of European descent. Of the 120 bins, 5 bins had significant average rank (P(rank)<or=0.05) by either unweighted or weighted analyses, 4 of which (bins 21.2: 21q22.11 to 21q22.3, 18.3: 18q12.2 to 18q21.33, 18.4: 18q21.33 to 18q23, and 6.2: 6p22.3 to 6p21.1) were significant by both. In subjects of European descent, 3 bins (22.1: 22q11.1 to 22q12.3, 22.2: 22q12.3 to 22q13.3, 10.4: 10q22.1 to 10q23.32) had P(rank)<or=0.05 with both unweighted and weighted analyses. Bin 10.4 showed low heterogeneity (P(Q)=0.04). None of the bins showed low heterogeneity (P(Q)>0.05), indicating variation in the strength of association. Further investigation of these regions may help to direct the identification of candidate genes for pulse pressure variation.

Interindividual variability in mam-mographic breast density has beenshown to be a major independent riskfactor for breast cancer (1). There is evi-dence for a genetic influence on breastdensity (2,3). In the Journal (4), we re-cently reported a segregation analysisof breast density performed on 1370women from 258 families in the Minne-sota Breast Cancer Family Cohort (5).After adjustment for eight epidemio-logic risk factors, percent breast densitywas consistent with mendelian modelsof inheritance (4). To provide additionalevidence for a major gene influence onbreast density, we report results from apreliminary sibpair linkage analysis on asample of women from the same largebreast cancer family cohort.The sibpairs used in the linkageanalysis were selected from a conve-nience sample of women from the fam-ily study who participated in the veni-puncture, mammogram, and telephoneinterview components of the BreastCancer Family Cohort (5). Women withprior breast cancer were not eligible forthis analysis to reduce potential geneticheterogeneity. Written informed consentwas obtained from the subjects in thisstudy.The fraction of the mammogram oc-cupied by fibroglandular elements wasestimated visually by a radiologist expe-rienced in mammography (C. C. Kuni).Density estimation was made in 5% in-crements from a video display of the leftmediolateral oblique view; the right me-diolateral oblique view was used if theleft was unavailable.Because there are no obvious candi-date genes for breast density, we per-formed a genome screen using a set ofhighly polymorphic short-tandem repeatpolymorphism markers spaced approxi-mately 30 cM apart. Evidence for link-age was determined with both two-point[SIBPAL in SAGE (6)] and multipoint[MAPMAKER/SIBS (7)] linkage analy-ses on both the unadjusted breast densitytrait and the trait adjusted for the in-fluence of nongenetic covariates. TheSIBPAL test for linkage is a test ofnegative slope (i.e., H

Impaired left ventricular (LV) contractility is a major cause of cardiovascular death, especially congestive heart failure. The identification of susceptibility genes that contribute to impaired LV contractility may uncover mechanisms underlying LV contractile impairment and the development of congestive heart failure. The Hypertension Genetic Epidemiology Network (HyperGEN) collected echocardiographic measurements of myocardial contractility in a large biethnic sample of hypertensive siblings (390 blacks and 398 whites in 179 and 165 sibships, respectively). All participants expressed hypertension before age 60 years, and the mean age of siblings was 52 years in blacks and 61 years in whites. We adjusted myocardial contractility for gender, age, and age(2), and we calculated standardized residuals separately for men and women in both ethnic groups. We conducted multipoint variance components linkage analysis using GENEHUNTER2 and 387 anonymous markers (CHCL8 marker set). We found evidence for significant linkage to a microsatellite marker, D11S1993 (lod, 3.93 in blacks), approximately 54 cM from the tip of the short arm of chromosome 11, that accounted for 72% of the phenotypic variation in LV contractility. A chromosome 22 locus showed suggestive evidence for linkage (lod, 2.83 in whites and 1.15 in blacks). The chromosome 11 peak coincides with the region containing myosin-binding protein C. Mutations in this gene are linked to familial hypertrophic cardiomyopathy. Our results show strong evidence for linkage of a region of chromosome 11 with LV contractility in blacks and suggest that an important gene for impaired LV contractility is harbored in this region.

Hyperinsulinemia, which is considered a hallmark of insulin resistance, precedes the development of non-insulin-dependent diabetes mellitus (NIDDM). Results of family and twin studies have shown that heredity influences insulin resistance and insulin levels. In Caucasian families ascertained through two or more NIDDM siblings, it has been reported that single genes with large effects, i.e., major genes, influence both fasting and 1-h postchallenge insulin levels. To determine whether a major gene affects 2-h postchallenge insulin levels in Mexican-Americans, we conducted segregation analyses using data collected on 527 pedigreed individuals from 27 families in San Antonio, TX. Probands for the families were randomly ascertained and all first-, second-, and third-degree relatives aged 16 years and older were invited to participate. Subjects received a 2-h oral glucose tolerance test, and diabetes was diagnosed according to World Health Organization criteria. We found that an autosomal dominant major gene best described the inheritance of 2-h insulin levels (ln-transformed) in these 27 families. Of the individuals in the population, 17% were homozygous for the 2-h low-insulin allele (back-transformed mean = 125 pmol/l) and 83% were heterozygous or homozygous for the 2-h high-insulin allele (back-transformed mean = 406 pmol/l). This major gene accounted for 31% of the variance in ln(2-h insulin levels) in this population. Using quantitative trait linkage analyses, we excluded tight linkage between this gene affecting 2-h insulin levels and three candidate loci for insulin levels: the insulin receptor gene, the low-density lipoprotein receptor gene, and the glucokinase gene. In addition, it is likely that this major gene is not linked to the fatty acid-binding protein gene, a gene that has previously been associated with insulin resistance through sib-pair analysis.

Objective A previous study has shown significant linkage of five markers near the lipoprotein lipase locus to systolic blood pressure, but not to diastolic blood pressure, in nondiabetic members of 48 Taiwanese families selected for noninsulin-dependent diabetes. However, lipoprotein lipase markers did not appear strongly linked to systolic blood pressure in a study of Mexican–Americans using a variety of selection schemes. The objective of the current study was to test whether markers near the lipoprotein lipase gene were linked to hypertension in Caucasians. Design To test for linkage of genetic markers in or near the lipoprotein lipase gene to hypertension in Caucasians, two sets of Caucasian hypertensive sibships were genotyped. The samples included 261 sibships (431 effective sibpairs) from four field centers of the National Heart, Lung and Blood Institute Family Heart Study and 211 sibships (282 effective sibpairs) from the Health Family Tree database in Utah. Results Two highly polymorphic markers in or near the lipoprotein lipase gene showed no evidence of excess allele sharing in either set of hypertensive sibships. Combining the two datasets resulted in 653 and 713 effective sibpairs for the two markers, sharing 0.495 ± 0.30 and 0.486 ± 0.28 alleles identical by descent compared to an expected sharing of 0.50. Multipoint analysis of the two loci also did not show linkage (P = 0.95). Conclusions We conclude that the lipoprotein lipase locus and nearby regions do not appear to be linked to hypertension in Caucasians.

To the Editor: Our recent article (DeWan et al. DeWan et al., 2001DeWan AT Arnett DK Atwood LD Province MA Lewis CE Hunt SC Eckfeldt J A genome scan for renal function among hypertensives: the HyperGEN study.Am J Hum Genet. 2001; 68: 136-144Abstract Full Text Full Text PDF PubMed Scopus (65) Google Scholar) reported suggestive, but not statistically significant, results of a genomewide quantitative-linkage analysis for creatinine clearance (CRCL), a common measure of renal function. The strongest signals were in regions on chromosomes 1, 3, and 6 in whites and in two regions on chromosome 3 in African Americans. The sample that we studied included every genotyped family from the first half of the HyperGEN study sample, a total of 215 African American sibships (n=466) and 265 white sibships (n=634). To confirm these findings, once the remaining sibships were genotyped, we repeated, on the entire HyperGEN study sample, the analysis of linkage to CRCL. All recruiting, phenotyping, genotyping, and linkage-analysis methods were performed as previously reported (DeWan et al. DeWan et al., 2001DeWan AT Arnett DK Atwood LD Province MA Lewis CE Hunt SC Eckfeldt J A genome scan for renal function among hypertensives: the HyperGEN study.Am J Hum Genet. 2001; 68: 136-144Abstract Full Text Full Text PDF PubMed Scopus (65) Google Scholar)—by using adjusted CRCL levels in a multipoint variance-components linkage analysis in GENEHUNTER2 and allowing for dominance at the trait locus—except that 11 new markers were added to the chromosome 3 region near that having the highest LOD score. Table 1 presents the results for linkage on chromosome 3 in African Americans, both for the smaller sample of the previous study and for the complete HyperGEN genotyped sample. In the complete sample, we found significant linkage, in African Americans (n=1,124 in 503 sibships), between chromosome 3p (LOD score 4.66 at 66 cM) and CRCL in our minimally adjusted residual-phenotype model (i.e., CRCL adjusted for age and age2). In the maximally adjusted residual-phenotype model (i.e., CRCL adjusted for age, age2, lean body mass, pulse rate, pulse pressure, hormone-replacement therapy, educational status, and physical activity), the evidence for linkage was slightly weaker (LOD score 3.82 at 65 cM). In our previous report, the LOD scores in this region were 2.50 and 1.78 for the minimally and maximally adjusted phenotypes, respectively.Table 1Peak Multipoint LOD Scores in African AmericansLOD Score (Position [cM]) inaSample 1 was used in the previously published report (DeWan et al. 2001) and consists of one half of the total HyperGEN sample; sample 2 is the complete HyperGEN sample available for the genome scan; "Minimally Adjusted" and "Maximally Adjusted" refer to the type of residual-phenotype model used for the analysis.Sample 1Sample 2ChromosomeMinimally AdjustedMaximally AdjustedMinimally AdjustedMaximally Adjusted3p2.50 (58)1.78 (58)4.66 (66)3.82 (65)3q2.31 (213)3.61 (215)1.35 (191)1.03 (191)a Sample 1 was used in the previously published report (DeWan et al. DeWan et al., 2001DeWan AT Arnett DK Atwood LD Province MA Lewis CE Hunt SC Eckfeldt J A genome scan for renal function among hypertensives: the HyperGEN study.Am J Hum Genet. 2001; 68: 136-144Abstract Full Text Full Text PDF PubMed Scopus (65) Google Scholar) and consists of one half of the total HyperGEN sample; sample 2 is the complete HyperGEN sample available for the genome scan; "Minimally Adjusted" and "Maximally Adjusted" refer to the type of residual-phenotype model used for the analysis. Open table in a new tab To narrow the region, we added 11 new linkage markers between 49 cM and 86 cM and conducted both single-point and multipoint linkage analyses on the combined marker panel. The highest single-point LOD score (3.72) was obtained at 71 cM for the minimally adjusted CRCL, and, with the addition of the 11 markers, the highest multipoint LOD score increased from 4.31 at 67 cM to 4.57 at 66 cM, in the complete African American sample (see fig. 1). In the original genome scan, our best result for linkage was on the q arm of chromosome 3 in African Americans (LOD score 3.61 at 215 cM), for the maximally adjusted residual-phenotype model. In this complete sample, the LOD score was reduced in this region (LOD score 1.03 at 191 cM). There were no other regions, throughout the genome, that exceeded a LOD score of 2.0 (the Lander and Kruglyak [Lander and Kruglyak, 1995Lander E Kruglyak L Genetic dissection of complex traits: guidelines for interpreting and reporting linkage results.Nat Genet. 1995; 11: 241-247Crossref PubMed Scopus (4374) Google Scholar] threshold for suggestive linkage). We were also unable to replicate any of the linkage results on chromosomes 1, 3, or 6 that were observed in the original genome scan in whites. Our LOD score of 4.66 for the confirmation of linkage to chromosome 3p exceeds the statistically significant threshold of 3.7 implied by Morton (Morton, 1998Morton N Significance levels in complex inheritance.Am J Hum Genet. 1998; 62: 690-697Abstract Full Text Full Text PDF PubMed Scopus (141) Google Scholar) for 2-df tests of linkage (ours was a 2-df test, because we estimated both additive and dominance effects at the QTL). In the original, smaller sample, the LOD score of 2.50 was merely suggestive of linkage. As with any complex genetic trait, it is encouraging to observe replication of a linkage finding. Replication by an independent team—with a different population, sampling method, or analysis technique—would further strengthen the evidence that a locus on chromosome 3p contributes to variation in CRCL. The HyperGEN Network is funded by National Heart, Lung, and Blood Institute grant R01 HL55673 and by cooperative agreements (U10) with the National Heart, Lung, and Blood Institute: HL54471 (Utah field center), HL54472 (Minnesota laboratory), HL54473 (data-coordinating center), HL54495 (Alabama field center), HL54496 (Minnesota field center), HL54509 (North Carolina), HL54515 (Utah DNA laboratory).

Although there is evidence that left ventricular (LV) function is genetically controlled, the contribution of familial factors to variation and covariation of LV diastolic filling, contractility, and structure is unknown. Single- and cross-trait sibling correlations were estimated using bivariate familial correlation models in 200 white (400 pairs) and 374 black (539 pairs) hypertensive sibships. LV transmitral early and late peak filling velocities, isovolumic relaxation time, atrial filling fraction, stress-corrected midwall shortening, and LV mass and structure were measured and adjusted for important covariates in race-specific linear regression models. Single-trait sibling correlation was strongest for early peak filling velocity. Significant cross-trait sibling correlation was detected between early and late peak filling velocities. In whites, early peak filling velocity and atrial filling fraction, and isovolumic relaxation time and end-diastolic posterior wall thickness, were also significantly correlated. Familial factors common to early and late peak filling velocities contributed to 64% and 54% of sibling resemblance in early peak filling velocity and to 76% and 77% in late peak filling velocity in blacks and whites, respectively. In whites, 100% of sibling resemblance in isovolumic relaxation time was shared by posterior wall thickness, whereas 75% of sibling influence in posterior wall thickness was common to isovolumic relaxation time. In conclusion, significant cross-trait sibling resemblance was detected between (1) early and late filling parameters and (2) isovolumic relaxation time and posterior wall thickness, suggesting pleiotropy and/or common environment on these traits. These data have potential importance in understanding heritability of LV diastolic function in hypertension.

Altered diastolic filling is an important contributor to several cardiovascular disorders. Multiple lines of evidence suggest a genetic contribution to left ventricular (LV) diastolic filling; however, chromosomal locations harboring genes involved in impaired LV diastolic filling have not been reported. The aim of this study was to identify chromosomal regions contributing to variation of LV transmitral early and late peak filling velocities (E and A velocities), Doppler echocardiographic measures of LV diastolic filling. We adjusted E and A velocities for age, age squared, heart rate, body mass index, systolic blood pressure, field center, and antihypertensive medication in sex- and ethnicity-specific linear regression models. Standardized residuals were calculated and used in multipoint variance components linkage analysis (GENEHUNTER). Anonymous markers (Cooperative Human Linkage Center set 8) were available for 167 white hypertensive sibships (397 subjects, mean age 60 years) and 182 African American (393 subjects, mean age 52 years) hypertensive sibships. For E velocity, linkage was detected on chromosome 5 at 133.6 centimorgan (cM) in African Americans (logarithm of the odds [LOD] = 4.13), and suggestive linkage (LOD >1.9) was observed for regions on chromosome 10 (80.8 cM) and chromosome 20 (1.5 cM). For A velocity, suggestive linkage was found for chromosome 12 (GATA85A04) in whites and for chromosome 8 (122.9 cM) in African Americans. Genes contained in and around the linked region are important candidates for diastolic filling (calcium-modulating cyclophilin ligand [5q23], α-1B adrenergic receptor [5q23-32]). Significant linkage was detected for LV early diastolic peak filling velocity on chromosome 5 in African Americans, indicating that a genomic region may contribute to interindividual variation in LV diastolic filling.

Using random initial parameter estimates, three segregation analysis models of the inheritance of HDL2 in the Berkeley GAW8 data set were maximized 5000 times each. Initial parameter estimates were assumed to be uniformly distributed on intervals formed by parameter boundaries. The three models were unrestricted, environmental, and Mendelian regressive type A models. Likelihood ratio tests of the global maxima rejected the Mendelian model and accepted the environmental model. However, tests using local maxima accepted the Mendelian model and both rejected and accepted the environmental model. Patterns among the initial parameter estimates of convergent runs were examined to develop empirical rules to increase the frequency of convergence. These rules were tested using data on apoAI in the Berkeley GAW8 data set.

We explored the genetic control of cholesterolemic responses to dietary cholesterol and fat in 575 pedigreed baboons. We measured cholesterol in beta-lipoproteins (low density lipoprotein cholesterol [LDLC]) in blood drawn from baboons while they were consuming a baseline (low in cholesterol and fat) diet, a high-saturated fat (lard) diet, and a high-cholesterol, high-saturated fat diet. In addition to baseline levels (LDLC(Base)), we analyzed two variables for diet response: LDLC(RF), which represents the LDLC response to increasing dietary fat (ie, high-fat diet minus baseline), and LDLC(RC), which represents the LDLC response to increasing dietary cholesterol level (ie, high-cholesterol, high-fat diet minus high-fat diet). Heritabilities (h2) of the 3 traits were 0.59 for LDLC(Base), 0.14 for LDLC(RF), and 0.59 for LDLC(RC). In addition, LDLC(Base) and LDLC(RC) had a significant genetic correlation (ie, rhoG=0.54), suggesting that 1 or more genes exert pleiotropic effects on the 2 traits. Segregation analyses detected a single major locus that accounted for nearly all genetic variation in LDLC(RC) and some genetic variation in LDLC(Base) and LDLC(RF) and confirmed the presence of a different major locus that influences LDLC(Base) alone. Preliminary linkage analyses indicated that neither locus was linked to the LDL receptor gene, a likely candidate locus for LDLC. Detection of these major loci with large effects on the LDLC response to dietary cholesterol in a nonhuman primate offers hope of detecting and ultimately identifying similar loci that determine LDLC variation in human populations.

Studies of model-based linkage analysis show that trait or marker model misspecification leads to decreasing power or increasing Type I error rate. An increase in Type I error rate is seen when marker related parameters (e.g., allele frequencies) are misspecified and ascertainment is through the trait, but lod-score methods are expected to be robust when ascertainment is random (as is often the case in linkage studies of quantitative traits). In previous studies, the power of lod-score linkage analysis using the "correct" generating model for the trait was found to increase when the marker allele frequencies were misspecified and parental data were missing. An investigation of Type I error rates, conducted in the absence of parental genotype data and with misspecification of marker allele frequencies, showed that an inflation in Type I error rate was the cause of at least part of this apparent increased power. To investigate whether the observed inflation in Type I error rate in model-based LOD score linkage was due to sampling variation, the trait model was estimated from each sample using REGCHUNT, an automated segregation analysis program used to fit models by maximum likelihood using many different sets of initial parameter estimates.The Type I error rates observed using the trait models generated by REGCHUNT were usually closer to the nominal levels than those obtained when assuming the generating trait model.This suggests that the observed inflation of Type I error upon misspecification of marker allele frequencies is at least partially due to sampling variation. Thus, with missing parental genotype data, lod-score linkage is not as robust to misspecification of marker allele frequencies as has been commonly thought.

This study characterized mast cell- and capsaicin-sensitive sensory nerve vasodilator mechanisms regulating submucosal arterioles in the guinea pig ileum. The outside diameter of arterioles in in vitro submucosal preparations from milk-sensitized guinea pigs was monitored using videomicroscopy. Superfusion of the cow's milk protein, beta-lactoglobulin (beta-Lg; 5 microM), evoked large dilations, which became completely desensitized. beta-Lg-evoked dilations were blocked by pyrilamine or NG-monomethyl-L-arginine plus indomethacin but not by TTX. Electron microscopic studies revealed that mast cells, in preparations receiving beta-Lg, demonstrated significant reductions of the dispersed and intact granule areas compared with preparations not exposed to beta-Lg. Paired experiments were conducted to determine if capsaicin-sensitive, nerve-evoked responses involved mast cell degranulation. One preparation received capsaicin (200 nM) followed by beta-Lg (5 microM); the other preparation received the drugs in reverse order. Prior treatment with capsaicin or beta-Lg had no effect on subsequent dilations evoked by the alternate treatment. Electron microscopy showed that nerve-arteriole associations were 10 times closer than nerve-mast cell associations. Mast cell numbers were not increased by milk sensitization. These findings suggest that mast cell- and capsaicin-sensitive nerve-evoked vasodilator mechanisms act independently in a model in which mast cell numbers are not increased.

Abdominal fat has been shown to be an important risk factor for many chronic conditions, including diabetes, heart disease, and breast cancer. The objective of this study was to provide evidence for a major gene influence on the ratio of waist to hip circumference (WHR), a measurement commonly used in large scale studies to indicate the presence of abdominal fat. Segregation analysis was conducted on three subsets of families from the Minnesota Breast Cancer Family Study. One analysis was conducted among families with WHR measurements on all women. Two additional analyses were conducted on subsets of women stratified on menopausal status. Multiple regression analysis was used to identify factors associated with WHR expressed as a continuous trait. Complex segregation analyses were performed on the continuous trait of WHR and the covariates identified in the regression analysis. In the analysis of all women, all hypotheses were rejected. Among premenopausal women, the environmental hypothesis with no heterogeneity between generations fit the data best (P = 0.85). However, among postmenopausal women, the requirements for conclusion of the presence of a major gene were met. All non-Mendelian hypotheses were rejected (P < 0.0001), but the additive hypothesis was not rejected (P = 0.19) and provided the best fit to the data. The putative major gene identified by this model accounted for 42% of total phenotypic variance in WHR among these postmenopausal women. The allele for high WHR had a frequency of 27%. These findings support the hypothesis that the distribution of abdominal fat in postmenopausal women is under genetic control.

We explored three approaches to heritability and linkage analyses of longitudinal total cholesterol levels (CHOL) in the Genetic Analysis Workshop 13 simulated data without knowing the answers. The first two were univariate approaches and used 1) baseline measure at exam one or 2) summary measures such as mean and slope from multiple exams. The third method was a multivariate approach that directly models multiple measurements on a subject. A variance components model (SOLAR) was employed in the univariate approaches. A mixed regression model with polynomials was employed in the multivariate approach and implemented in SAS/IML.Using the baseline measure at exam 1, we detected all baseline or slope genes contributing a substantial amount (0.08) of variance (LOD > 3). Compared to the baseline measure, the mean measures yielded slightly higher LOD at the slope genes, and a lower LOD at the baseline genes. The slope measure produced a somewhat lower LOD for the slope gene than did the mean measure. Descriptive information on the pattern of changes in gene effects with age was estimated for three linked loci by the third approach.We found simple univariate methods may be effective to detect genes affecting longitudinal phenotypes but may not fully reveal temporal trends in gene effects. The relative efficiency of the univariate methods to detect genes depends heavily on the underlying model. Compared with the univariate approaches, the multivariate approach provided more information on temporal trends in gene effects at the cost of more complicated modelling and more intense computations.

Genome-wide association (GWA) studies that use population-based association approaches may identify spurious associations in the presence of population admixture. In this paper, we propose a novel three-stage approach that is computationally efficient and robust to population admixture and more powerful than the family-based association test (FBAT) for GWA studies with family data.We propose a three-stage approach for GWA studies with family data. The first stage is to perform linear regression ignoring phenotypic correlations among family members. SNPs with a first stage p-value below a liberal cut-off (e.g. 0.1) are then analyzed in the second stage that employs a linear mixed effects (LME) model that accounts for within family correlations. Next, SNPs that reach genome-wide significance (e.g. 10-6 for 34,625 genotyped SNPs in this paper) are analyzed in the third stage using FBAT, with correction of multiple testing only for SNPs that enter the third stage. Simulations are performed to evaluate type I error and power of the proposed method compared to LME adjusting for 10 principal components (PC) of the genotype data. We also apply the three-stage approach to the GWA analyses of uric acid in Framingham Heart Study's SNP Health Association Resource (SHARe) project.Our simulations show that whether or not population admixture is present, the three-stage approach has no inflated type I error. In terms of power, using LME adjusting PC is only slightly more powerful than the three-stage approach. When applied to the GWA analyses of uric acid in the SHARe project of FHS, the three-stage approach successfully identified and confirmed three SNPs previously reported as genome-wide significant signals.For GWA analyses of quantitative traits with family data, our three-stage approach provides another appealing solution to population admixture, in addition to LME adjusting for genetic PC.

Aortic root dilation is a prominent feature in several cardiovascular diseases. This study seeks to identify genomic regions linked to variation in the aortic root diameter (ARD) in hypertensive African American and white individuals. We performed a genome scan for ARD in the Hypertension Genetic Epidemiology Network Study, one of four networks in the National Heart, Lung, and Blood Institute Family Blood Pressure Program (FBPP). Data were collected from 1129 African American siblings from 504 hypertensive sibships and 883 white siblings from 374 hypertensive sibships. Standardized residual values of ARD were calculated using linear regression, adjusting for effects of age, age2, and field center (ie, minimally adjusted model), separately in groups composed by sex and ethnicity. The ARD was additionally adjusted for height, weight, diastolic BP, and systolic BP in a fully adjusted model. Multipoint linkage analysis was performed using the GENEHUNTER2 variance components method. Suggestive evidence for linkage was found on chromosome 5 at 85 cM in African Americans, with a maximal log of the odds (LOD) score of 2.07. Suggestive evidence for linkage was found on chromosome 1 at 157 cM in whites, with a maximal LOD score of 2.40. Our findings suggest that genes present on chromosomes 1 and 5 might influence inter-individual variation in aortic root diameter. Am J Hypertens 2005;18:627–632 © 2005 American Journal of Hypertension, Ltd.

This paper examines the consistency of genetic analyses across time, both in the context of replicating results from one data collection point to the next, and from the perspective of modeling longitudinal processes. This summary originates from the examination of findings from nine papers from Genetic Analysis Workshop (GAW) 13 that reported on analyses of longitudinal data of a variety of traits from the Framingham Heart Study. These analyses include both assessments of consistency of aggregate genetic effects, in the form of estimation of heritability and relative risk of disease, as well as localization of quantitative trait loci (QTLs) by genome-wide linkage screens. Consistency varied widely by trait, possibly reflecting differences in measurement error, secular trends, or underlying biological features such as genotype x age interaction. Quantitatively, comparing magnitudes of estimates across age or time, heritability estimates showed greater consistency than LOD scores. However, qualitatively, the same regions of interest were often identified in genome scans from different time points or different ages. Estimates of sibling recurrence risk, on the other hand, showed little consistency. Heritabilities were greater when participants were matched by age than when they were matched by date of examination. Multivariate approaches, either in use of multiple traits or in use of multiple measures of the same trait, appeared to provide stronger genetic signals both for relative risk and for linkage. Finally, modeling of longitudinal processes provided evidence for genotype x age interactions that may partially explain variation in results of genetic analyses across time or age.

Usher Syndrome Type 1 is an autosomal recessive disease characterized by profound congenital hearing impairement and vestibular dysfunction followed by the onset of retinitis pigmentosa in childhood or early adolescence. Members of the Usher Syndrome Consortium, whose objective is to locate and isolate the genes for Usher syndrome, have pooled linkage data from 36 families with 111 affected individuals. We report the analysis of 206 blood group, protein, and DNA marker polymorphisms. No evidence of linkage heterogeneity among families was found for any of the markers studied; the negative lod scores exclude the locus for this disease from about 39% of the genome. Our results indicate the regions of the genome to which our continuing efforts should be directed.

Since the manifestation of a complex disease is likely to be influenced through multiple genetic and/or environmental pathways, it may be advantageous to adjust for these multiple factors in a genetic analysis of a complex quantitative trait. Sib- pair linkage analysis was performed on the simulated complex quantitative trait Q1 after adjustment for age, sex, and the environmental factor (i.e., minimally adjusted) and all combinations of the four intermediate phenotypes Q2, Q3, Q4, and Q5 (n = 15) for all 200 replications of the nuclear families data set. From the minimally adjusted Q1, the power to detect suggestive linkage to any of the three loci affecting Q1 was 0.585 with a false positive rate of 0.0025. Adjusting Q1 for Q3 increased the power to detect suggestive linkage to 0.860 with a similar false positive rate. Additional adjustments for Q2, Q4, and Q5 yielded no substantial improvements in power nor changes in the false positive rate. The power to detect significant linkage was also substantially improved after adjustment of Q1 for Q3 with no change in the false positive rate. The adjustment of a complex trait for other factors in the causal pathway reduces the phenotype variability and enhances the ability to detect linkage. © 1997 Wiley-Liss, Inc.

Complex parametric segregation and linkage analysis was performed on the simulated quantitative trait Q1 for all 200 replicates of the nuclear families data set. The segregation analysis inferred a major gene in 46% of the replicates. Among all replicates, including those that rejected a major gene, the power to detect suggestive linkage to any of three loci affecting Q1 was 0.600 and the false positive rate was 0.002. Among the replicates where a major gene was found, the power to detect suggestive linkage was 0.652 and the false positive rate was also 0.002. Thus, for purposes of linkage to this complex trait, a prior segregation then linkage analysis approach located a gene in 30% of all replicates, whereas a linkage only approach located a gene in 60% of all replicates. © 1997 Wiley-Liss, Inc.

The repeated measures in the Framingham Heart Study in the Genetic Analysis Workshop 13 data set allow us to test for consistency of linkage results within a study across time. We compared regression-based linkage to variance components linkage across time for six quantitative traits in the real data.The variance components approach found 11 significant linkages, the regression-based approach found 4. There was only one region that overlapped. Consistency between exams generally decreased as the time interval between exams increased. The regression-based approach showed higher consistency in linkage results across exams.The low consistency between exams and between methods may help explain the lack of replication between studies in this field.

Segregation and linkage analysis of GAW9 Problem 2 quantitative trait 1 (Q1) was performed. Eight segregation models comprising all possible combinations of the environmental factor (EF), quantitative trait 2 (Q2), and quantitative trait 3 (Q3) as covariates were considered. Seven of the eight segregation models showed strong evidence for a major gene, the other model was marginal. When all genotypes are known, some evidence for linkage (lod > 2) was found to all three of the markers that affect Q1. Furthermore, four of the eight models each showed some linkage (lod > 2) to two of the three markers that affect Q1 with no false positives. Each of these segregation analysis major genes is a hybrid combination of the true multiple loci that affect Q1.

(The American Journal of Human Genetics 88, pages 6–18; December 30, 2010) Maciej Tomaszewski's name was misspelled in the original author list and has been corrected here. The authors regret the error. Meta-analysis of Dense Genecentric Association Studies Reveals Common and Uncommon Variants Associated with HeightLanktree et al.The American Journal of Human GeneticsDecember 30, 2010In BriefHeight is a classic complex trait with common variants in a growing list of genes known to contribute to the phenotype. Using a genecentric genotyping array targeted toward cardiovascular-related loci, comprising 49,320 SNPs across approximately 2000 loci, we evaluated the association of common and uncommon SNPs with adult height in 114,223 individuals from 47 studies and six ethnicities. A total of 64 loci contained a SNP associated with height at array-wide significance (p < 2.4 × 10−6), with 42 loci surpassing the conventional genome-wide significance threshold (p < 5 × 10−8). Full-Text PDF Open Archive

Obesity is globally prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined associations between body mass index and similar to 2.8 million SNPs in up to 123,865 individuals with targeted follow up of 42 SNPs in up to 125,931 additional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci associated with body mass index (P < 5 x 10(-8)), one of which includes a copy number variant near GPRC5B. Some loci (at MC4R, POMC, SH2B1 and BDNF) map near key hypothalamic regulators of energy balance, and one of these loci is near GIPR, an incretin receptor. Furthermore, genes in other newly associated loci may provide new insights into human body weight regulation.

Response bias in epidemiologic studies can occur if affected individuals are more (or less) likely to participate in a survey than their unaffected counterparts. To examine the effect of response bias in the context of a family study, we conducted segregation and linkage analysis in all 1,000 individuals in the Problem 2 data set, and in two different 65% samples: one sample consisting of 648 randomly selected individuals, and the other sample nonrandomly constructed so that individuals with high levels of Q1 were oversampled. In this simulation the ability to detect major genes for Q1-Q4 in segregation analysis and to link these putative major genes to genetic markers in linkage analysis was not markedly different between the 65% random and the 65% enriched samples.

P125 Pulse pressure, a measure of aortic stiffness, has recently been shown to be a strong predictor of cardiovascular mortality in both normotensives and hypertensives. It is also an important predictor of left ventricular hypertrophy. Unfortunately, little is known about the genetic etiology of pulse pressure. To address this problem we performed genetic analysis on 46 randomly ascertained families (1306 individuals) in the San Antonio Family Heart Study. Pulse pressure (PP) was defined as the difference between systolic and diastolic blood pressure. Likelihood methods were used to construct a model that had both single-locus and polygenic components. The single-locus component included sex-specific and genotype-specific effects of both age and body mass index (BMI). Using this model we then performed two-point linkage analysis of 10 large families (440 individuals), which were a randomly chosen subset of the initial 46 families, that have been genotyped for 396 polymorphic markers. Results showed that when the model contained only the polygenic component and simple effects of the covariates then the heritability of PP is .21. Adding the single-locus component was highly significant (p&lt;.0001). In addition, within the single-locus component, the sex-specific and genotype-specific effects of age and BMI were also highly significant (p&lt;.002). This full model accounted for 73% of the total variation of PP. Linkage analysis of this model with each marker showed four markers with lodscores &gt; 1.9, which is the Lander-Kruglyak standard for suggestive linkage. D21S1439 had a lodscore of 2.78 with a recombination fraction (θ) of 0.02. D7S1799 had a lodscore of 2.04 (θ=0.01). D8S1100 had a lodscore of 1.98 (θ=0.08) and D18S844 had a lodscore of 1.95 (θ=0.11). We conjecture that pulse pressure is affected by several major genes and that together these genes account for the highly significant genotype-specific single-locus effect observed here. Supported by HL54707 and HL45522.

Since the manifestation of a complex disease is likely to be influenced through multiple genetic and/or environmental pathways, it may be advantageous to adjust for these multiple factors in a genetic analysis of a complex quantitative trait. Sib- pair linkage analysis was performed on the simulated complex quantitative trait Q1 after adjustment for age, sex, and the environmental factor (i.e., minimally adjusted) and all combinations of the four intermediate phenotypes Q2, Q3, Q4, and Q5 (n = 15) for all 200 replications of the nuclear families data set. From the minimally adjusted Q1, the power to detect suggestive linkage to any of the three loci affecting Q1 was 0.585 with a false positive rate of 0.0025. Adjusting Q1 for Q3 increased the power to detect suggestive linkage to 0.860 with a similar false positive rate. Additional adjustments for Q2, Q4, and Q5 yielded no substantial improvements in power nor changes in the false positive rate. The power to detect significant linkage was also substantially improved after adjustment of Q1 for Q3 with no change in the false positive rate. The adjustment of a complex trait for other factors in the causal pathway reduces the phenotype variability and enhances the ability to detect linkage. © 1997 Wiley-Liss, Inc.