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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.

Genome-wide association studies (GWAS) have identified 36 loci associated with body mass index (BMI), predominantly in populations of European ancestry. We conducted a meta-analysis to examine the association of3.2 million SNPs with BMI in 39,144 men and women of African ancestry and followed up the most significant associations in an additional 32,268 individuals of African ancestry. We identified one new locus at 5q33 (GALNT10, rs7708584, P = 3.4 × 10(-11)) and another at 7p15 when we included data from the GIANT consortium (MIR148A-NFE2L3, rs10261878, P = 1.2 × 10(-10)). We also found suggestive evidence of an association at a third locus at 6q16 in the African-ancestry sample (KLHL32, rs974417, P = 6.9 × 10(-8)). Thirty-two of the 36 previously established BMI variants showed directionally consistent effect estimates in our GWAS (binomial P = 9.7 × 10(-7)), five of which reached genome-wide significance. These findings provide strong support for shared BMI loci across populations, as well as for the utility of studying ancestrally diverse populations.

There is evidence across several species for genetic control of phenotypic variation of complex traits, such that the variance among phenotypes is genotype dependent. Understanding genetic control of variability is important in evolutionary biology, agricultural selection programmes and human medicine, yet for complex traits, no individual genetic variants associated with variance, as opposed to the mean, have been identified. Here we perform a meta-analysis of genome-wide association studies of phenotypic variation using ∼170,000 samples on height and body mass index (BMI) in human populations. We report evidence that the single nucleotide polymorphism (SNP) rs7202116 at the FTO gene locus, which is known to be associated with obesity (as measured by mean BMI for each rs7202116 genotype), is also associated with phenotypic variability. We show that the results are not due to scale effects or other artefacts, and find no other experiment-wise significant evidence for effects on variability, either at loci other than FTO for BMI or at any locus for height. The difference in variance for BMI among individuals with opposite homozygous genotypes at the FTO locus is approximately 7%, corresponding to a difference of ∼0.5 kilograms in the standard deviation of weight. Our results indicate that genetic variants can be discovered that are associated with variability, and that between-person variability in obesity can partly be explained by the genotype at the FTO locus. The results are consistent with reported FTO by environment interactions for BMI, possibly mediated by DNA methylation. Our BMI results for other SNPs and our height results for all SNPs suggest that most genetic variants, including those that influence mean height or mean BMI, are not associated with phenotypic variance, or that their effects on variability are too small to detect even with samples sizes greater than 100,000. ispartof: Nature vol:490 issue:7419 pages:267-272 ispartof: location:England status: published

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits1, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait2,3. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways ( P=0.016) and that underlie skeletal growth defects ( P

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.

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 ≤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 ≤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.

Background— 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. Methods and Results— 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. Conclusions— 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.

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.

Weight gain adversely affects blood pressure, lipids, and glycemia. The genetic contribution to weight change is unknown.Variance components linkage analysis using microsatellites was performed on 336 families from the Framingham Heart Study offspring cohort, using a 10-cM genome-wide linkage analysis. We evaluated linkage to two traits: short-term (8-yr) weight change and long-term (up to 24-yr) weight change. Models were adjusted for age, age squared, baseline weight, smoking status, and menopausal status.Mean short-term weight change ranged from 1.4-3.8 kg, and mean long-term weight change was 7.7 kg. The heritability of long-term weight change was 0.24; weight change was minimally heritable among younger individuals and over shorter follow-up intervals. We found significant evidence for linkage for long-term weight change, with a peak LOD score of 3.10 on chromosome 20 at 63.7 cM (nearest marker, D20S481). We also found suggestive evidence for linkage on chromosome 1 at 239.7 cM (LOD score, 2.28; nearest marker, D1S1644).Long-term weight change is heritable, and evidence for linkage exists on chromosomes 1 and 20. Potential candidate genes include MC3R, ASIP, AGT, and HSD11B1. Additional research is necessary to uncover the genetic underpinnings of weight change that might contribute to associated adverse metabolic profiles.

Background 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. Methods 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, age 2 , 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. Results 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. Conclusions Our findings suggest that genes present on chromosomes 1 and 5 might influence inter-individual variation in aortic root diameter.

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.

Spirometric measures of pulmonary function have been shown to be highly heritable and evidence for major genes influencing forced expiratory volume in 1 s (FEV 1 ) 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 FEV 1 and the FEV 1 /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 FEV 1 at 184.5 cM. LOD scores for FVC and the FEV 1 / FVC ratio were also above 1.0 in this region. Evidence for association with FEV 1 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 FEV 1 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 184cM (D6S503) to 190cM (D6S281).

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 HbA1c, 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∼0.32) containing the minor allele of rs2209772 and the major allele of the rs1887922 SNP (FPG P < 0.001, mFPG P < 0.003, HbA1c P < 0.025). Another haplotype (CC, f∼0.16) was associated with elevated HbA1c (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.

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.

While mechanisms are poorly understood, resting heart rate has been shown to be a strong predictor of the risk of cardiovascular disease, cancer, and all-cause mortality. We performed a genome scan for quantitative trait loci influencing the resting heart rate among 962 Caucasians and 1,124 African-Americans in the Hypertension Genetic Epidemiology Network (HyperGEN), a multi-center study of genetic and environmental factors related to hypertension. The NHLBI Mammalian Genotyping Service typed a total of 391 anonymous microsatellite markers, spaced roughly equally throughout the genome. Within each race and sex, heart rate was adjusted for covariates, including age, age(2), study center, body mass index, beta-blocker use, alcohol consumption, smoking, number of city blocks walked per day, and number of hours watching television. Genome scans were performed using variance component linkage analysis as implemented by GENEHUNTER (version 2) for each race, using race-specific marker allele frequencies derived from random samples. The highest lod score detected in Caucasians was 2.14 on chromosome 4 (at 195.06 cM); a lod score of 1.14 was found at the same locus among the African-Americans, and a lod score of 3.18 resulted when the two racial groups were combined. Evidence was also found on chromosome 10 to support a recent report of an association between heart rate and the beta1 adrenergic receptor. The suggestive evidence for linkage found on chromosome 4 in both Caucasian and African-American hypertensive sib pairs indicates that further investigation on that region may be warranted to locate a gene influencing variability in resting heart rate.

Background 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. Methods 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. Results 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]). Conclusion 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.

Elevated low-density lipoprotein cholesterol (LDL-C) is a treatable, heritable risk factor for cardiovascular disease. Genome-wide association studies (GWASs) have identified 157 variants associated with lipid levels but are not well suited to assess the impact of rare and low-frequency variants. To determine whether rare or low-frequency coding variants are associated with LDL-C, we exome sequenced 2,005 individuals, including 554 individuals selected for extreme LDL-C (>98(th) or

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 1.9, which is the Lander-Kruglyak suggestive linkage standard. D21S1440 had a lod score of 2.78 with a recombination fraction (θ) of 0.02. D7S1799 had a lod score of 2.04 (θ=0.01), D8S1100 had a lod score of 1.98 (θ=0.08), and D18S844 had a lod score of 1.95 (θ=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.

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.

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. Genet. Epidemiol. 20:458–478, 2001. © 2001 Wiley-Liss, Inc.

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 age2) and a fully adjusted model (which included age, age2, 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.

Segregation analysis was performed on the serum uric acid measurements from 523 randomly ascertained Caucasian families from the NHLBI Family Heart Study. Gender-specific standardized residuals were used as the phenotypic variable in both familial correlation and segregation analysis. Uric acid residuals were adjusted for age, age2, age3, body mass index (kg/m2), creatinine level, aspirin use (yes/no), total drinks (per week), HOMA insulin resistance index [(glucose * insulin)/22.5], diuretic use (yes/no), and triglyceride level. Sibling correlations (r=0.193) and parent-offspring correlations (r=0.217) were significantly different from zero, but these two familial correlations were not significantly different from one another. After adjustment for covariates, the heritability estimate for serum uric acid was 0.399. Segregation analysis rejected the "no major gene" model but was unable to discriminate between an "environmental" and a "Mendelian major gene" model. These results support the hypothesis that uric acid is a multifactorial trait possibly influenced by more than one major gene, modifying genes, and environmental factors.

SummaryMyopia, 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.

Summary 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.

Abstract 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.

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.

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.

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.

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.

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. © 1995 Wiley-Liss, Inc.

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

International audience; OBJECTIVE: 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.METHODS: 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.RESULTS: 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).INTERPRETATION: 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.

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

Obesity is globaLy prevalent and highly heritable, but its underlying genetic factors remain largely elusive. To identify genetic loci for obesity susceptibility, we examined aSociations betwEn body maS index and ĝ̂1/42.8 miLion SNPs in up to 123,865 individuals with targeted foLow up of 42 SNPs in up to 125,931 aDitional individuals. We confirmed 14 known obesity susceptibility loci and identified 18 new loci aSociated with body maS 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 aSociated loci may provide new insights into human body weight regulation. © 2010 Nature America, Inc. All rights reserved.

Background and Purpose—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.Methods—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 ≥1 MRI infarct).Results—The most significant association was found with rs2208454 (minor allele frequency, 20%), located in intron 3 ofMACRO domain containing 2gene and in the downstream region offibronectin leucine-rich transmembrane protein 3gene. 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=4.64×10−7). Highly suggestive associations (P−5) were also found for 22 other single nucleotide polymorphisms in linkage disequilibrium (r2>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.Conclusions—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.

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.

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.

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

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 = 6.4×10−7)]. 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 = 5.3×10−8 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 = 7.4×10−6, 0.024 z-score units (0.10 kg/m2) per copy of the G allele] and the risk of obesity (odds ratio 1.13, 95% CI 1.07–1.19; p = 3.2×10−5 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., Author Summary Obesity is a major health concern worldwide. In the past two years, genome-wide association studies of DNA markers known as SNPs (single nucleotide polymorphisms) have identified two novel genetic factors that may help scientists better understand why some people may be more susceptible to obesity. Similarly, this paper describes results from a large scale genome-wide association analysis for obesity susceptibility genes that includes 31,373 individuals from 8 separate studies. We uncovered a new gene influencing waist circumference, the neurexin 3 gene (NRXN3), which has been previously implicated in studies of addiction and reward behavior. These findings lend further evidence that our genes may influence our desire and consumption of food and, in turn, our susceptibility to obesity.

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 volume. There were 1538 Framingham Heart Study participants with brain volume measures from quantitative magnetic resonance imaging (MRI) who were free of stroke and other neurological disorders that might influence brain volumes and who were members of families with at least two 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, white matter hyperintensity, 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 white matter hyperintensity, reflected both moderate to strong shared genetic and shared environmental influences. This study confirms strong genetic effects on brain and white matter hyperintensity volumes. These data extend current knowledge by showing that these two different types of MRI measures do not share underlying genetic or environmental influences.

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.

Background 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. Methods 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%. Results 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. Conclusion 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.

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 frequencyor =0.10, genotype call rateor =0.80, and Hardy-Weinberg equilibrium p-valueor = 0.001.Six associations yielded p10(-5). The lowest p-values for each CVD trait were as follows: major CVD, rs499818, p = 6.6 x 10(-6); major CHD, rs2549513, p = 9.7 x 10(-6); AF, rs958546, p = 4.8 x 10(-6); HF: rs740363, p = 8.8 x 10(-6). Of note, we found associations of a 13 Kb region on chromosome 9p21 with major CVD (p 1.7-1.9 x 10(-5)) and major CHD (p 2.5-3.5 x 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 x 10(-6)) and HF (p = 1.2 x 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 webcite.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.

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 frequencyor + 10%, genotype call rateor = 80%, Hardy-Weinberg equilibrium p-valueor = 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.

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.

Background 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. Results 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. Conclusion 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.

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) (P0.004). 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 (P0.01). 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— 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. Methods— 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, age 2 , and TCV. Results— In the full dataset, WMH heritability was 0.55 ( P P P P Conclusion— 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.