Genetics Analysis Workshop 16 Problem 2: tTe Framingham Heart Study Data

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.National Heart, Lung and Blood Institute (2 N01-HC-25195-06); National Institutes of Health (National Institute of General Medical Sciences R01 GM031575

Genome-Wide Association to Body Mass Index and Waist Circumference: The Framingham Heart Study 100K Project

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 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.National Heart, Lung, and Blood Institute's Framingham Heart Study (N01-HC-25195); Atwood (R01 DK066241); National Institutes of Health National Center for Research Resources Shared Instrumentation grant (1S10RR163736-01A1

Consistency of linkage results across exams and methods in the Framingham Heart Study

BACKGROUND: 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. RESULTS: 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. CONCLUSION: The low consistency between exams and between methods may help explain the lack of replication between studies in this field

Sex and age specific effects of chromosomal regions linked to body mass index in the Framingham Study

BACKGROUND: 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: 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. CONCLUSION: 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

Trends in the Association of Parental History of Obesity over 60 Years

Objective: The association of familial as compared to genetic factors in the current obesogenic environment, compared to earlier, leaner time periods, is uncertain. Design and Methods Participants from the Framingham Heart Study were classified according to parental obesity status in the Original, Offspring, and Third Generation cohorts; mean BMI levels were estimated and we compared the association of parental history across generations. Finally, a genetic risk score comprised of 32 well-replicated single nucleotide polymorphisms for BMI was examined in association with BMI levels in 1948, 1971, and 2002. Results: BMI was 1.49 kg/m2 higher per each affected parent among the Offspring, and increased to 2.09 kg/m2 higher among the Third Generation participants (p-value for the cohort comparison=0.007). Parental history of obesity was associated with increased weight gain (p<0.0001) and incident obesity (p=0.009). Despite a stronger association of parental obesity with offspring BMI in more contemporary time periods, we observed no change in the effect size of a BMI genetic risk score from 1948 to 2002 (p=0.11 for test of trend across the time periods). Conclusions: The association of parental obesity has become stronger in more contemporary time period, whereas the association of a BMI genetic risk score has not changed

Genome-Wide Association of Pericardial Fat Identifies a Unique Locus for Ectopic Fat

Pericardial fat is a localized fat depot associated with coronary artery calcium and myocardial infarction. We hypothesized that genetic loci would be associated with pericardial fat independent of other body fat depots. Pericardial fat was quantified in 5,487 individuals of European ancestry from the Framingham Heart Study (FHS) and the Multi-Ethnic Study of Atherosclerosis (MESA). Genotyping was performed using standard arrays and imputed to ∼2.5 million Hapmap SNPs. Each study performed a genome-wide association analysis of pericardial fat adjusted for age, sex, weight, and height. A weighted z-score meta-analysis was conducted, and validation was obtained in an additional 3,602 multi-ethnic individuals from the MESA study. We identified a genome-wide significant signal in our primary meta-analysis at rs10198628 near TRIB2 (MAF 0.49, p = 2.7×10-08). This SNP was not associated with visceral fat (p = 0.17) or body mass index (p = 0.38), although we observed direction-consistent, nominal significance with visceral fat adjusted for BMI (p = 0.01) in the Framingham Heart Study. Our findings were robust among African ancestry (n = 1,442, p = 0.001), Hispanic (n = 1,399, p = 0.004), and Chinese (n = 761, p = 0.007) participants from the MESA study, with a combined p-value of 5.4E-14. We observed TRIB2 gene expression in the pericardial fat of mice. rs10198628 near TRIB2 is associated with pericardial fat but not measures of generalized or visceral adiposity, reinforcing the concept that there are unique genetic underpinnings to ectopic fat distribution

Key Variants via the Alzheimer\u27s Disease Sequencing Project Whole Genome Sequence Data

INTRODUCTION: Genome-wide association studies (GWAS) have identified loci associated with Alzheimer\u27s disease (AD) but did not identify specific causal genes or variants within those loci. Analysis of whole genome sequence (WGS) data, which interrogates the entire genome and captures rare variations, may identify causal variants within GWAS loci. METHODS: We performed single common variant association analysis and rare variant aggregate analyses in the pooled population (N cases = 2184, N controls = 2383) and targeted analyses in subpopulations using WGS data from the Alzheimer\u27s Disease Sequencing Project (ADSP). The analyses were restricted to variants within 100 kb of 83 previously identified GWAS lead variants. RESULTS: Seventeen variants were significantly associated with AD within five genomic regions implicating the genes OARD1/NFYA/TREML1, JAZF1, FERMT2, and SLC24A4. KAT8 was implicated by both single variant and rare variant aggregate analyses. DISCUSSION: This study demonstrates the utility of leveraging WGS to gain insights into AD loci identified via GWAS

Multi-Tissue Epigenetic analysis Identifies Distinct associations Underlying insulin Resistance and alzheimer\u27s Disease at Cpt1A Locus

BACKGROUND: Insulin resistance (IR) is a major risk factor for Alzheimer\u27s disease (AD) dementia. The mechanisms by which IR predisposes to AD are not well-understood. Epigenetic studies may help identify molecular signatures of IR associated with AD, thus improving our understanding of the biological and regulatory mechanisms linking IR and AD. METHODS: We conducted an epigenome-wide association study of IR, quantified using the homeostatic model assessment of IR (HOMA-IR) and adjusted for body mass index, in 3,167 participants from the Framingham Heart Study (FHS) without type 2 diabetes at the time of blood draw used for methylation measurement. We identified DNA methylation markers associated with IR at the genome-wide level accounting for multiple testing (P \u3c 1.1 × 10 RESULTS: We confirmed the strong association of blood DNA methylation with IR at three loci (cg17901584-DHCR24, cg17058475-CPT1A, cg00574958-CPT1A, and cg06500161-ABCG1). In FHS, higher levels of blood DNA methylation at cg00574958 and cg17058475 were both associated with lower IR (P = 2.4 × 10 CONCLUSIONS: Our results suggest potentially distinct epigenetic regulatory mechanisms between peripheral blood and dorsolateral prefrontal cortex tissues underlying IR and AD at CPT1A locus

Lack of association between PCK1 polymorphisms and obesity, physical activity, and fitness in European Youth Heart Study (EYHS)

Phosphoenolpyruvate carboxykinase-1 (PCK1) is the rate-limiting enzyme in the hepatic gluconeogenic pathway. Studies have shown that overexpression of Pck1 in mice results in obesity-related traits and higher levels of physical activity (PA). Therefore, our aims were to investigate whether common genetic variation in the PCK1 gene influences obesity-related traits, PA, and fitness, and to examine whether PA and fitness attenuate the influence of the PCK1 polymorphisms on obesity in children. Analyses were undertaken on data from Danish and Estonian children (958 boys and 1,104 girls) from the European Youth Heart Study (EYHS), a school-based, cross-sectional study of children (mean ± s.d. age: 9.6 ± 0.4 years) and adolescents (15.5 ± 0.5 years). We genotyped eight polymorphisms that captured the common genetic variations in the PCK1 gene. The association between the PCK1 polymorphisms and BMI, waist circumference (WC), sum of four skinfolds, PA, and fitness was tested using an additive model adjusted for age, age-group, gender, maturity, and country. Interactions were tested by including interaction terms in the model. None of the polymorphisms were significantly associated with BMI, WC, sum of four skinfolds, PA, and fitness, and also with the risk of being overweight or obese (P > 0.05). The interactions between the polymorphisms and age-group, gender, PA, and fitness were not statistically significant. This is the first study to comprehensively examine the association of PCK1 polymorphisms with obesity, PA, and fitness. Despite strong evidence from animal studies, our study in the EYHS cohort failed to identify an association of PCK1 polymorphisms with obesity, PA, and fitness