Data for GAW20: Genome-Wide DNA Sequence Variation and Epigenome-Wide DNA Methylation Before and After Fenofibrate Treatment in a Family Study of Metabolic Phenotypes

GAW20 provided participants with an opportunity to comprehensively examine genetic and epigenetic variation among related individuals in the context of drug treatment response. GAW20 used data from 188 families (N = 1105) participating in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study (clinicaltrials.gov identifier NCT00083369), which included CD4+ T-cell DNA methylation at 463,995 cytosine-phosphate-guanine (CpG) sites measured before and after a 3-week treatment with fenofibrate, single-nucleotide variation at 906,600 loci, metabolic syndrome components ascertained before and after the drug intervention, and relevant covariates. All GOLDN participants were of European descent, with an average age of 48 years. In addition, approximately half were women and approximately 40% met the diagnostic criteria for metabolic syndrome. Unique advantages of the GAW20data set included longitudinal (3 weeks apart) measurements of DNA methylation, the opportunity to explore the contributions of both genotype and DNA methylation to the interindividual variability in drug treatment response, and the familial relationships between study participants. The principal disadvantage of GAW20/GOLDN data was the spurious correlation between batch effects and fenofibrate effects on methylation, which arose because the pre- and posttreatment methylation data were generated and normalized separately, and any attempts to remove time-dependent technical artifacts would also remove biologically meaningful changes brought on by fenofibrate. Despite this limitation, the GAW20 data set offered informative, multilayered omics data collected in a large population-based study of common disease traits, which resulted in creative approaches to integration and analysis of inherited human variation

Smoking-by-genotype interaction in type 2 diabetes risk and fasting glucose

Smoking is a potentially causal behavioral risk factor for type 2 diabetes (T2D), but not all smokers develop T2D. It is unknown whether genetic factors partially explain this variation. We performed genome-environment-wide interaction studies to identify loci exhibiting potential interaction with baseline smoking status (ever vs. never) on incident T2D and fasting glucose (FG). Analyses were performed in participants of European (EA) and African ancestry (AA) separately. Discovery analyses were conducted using genotype data from the 50,000-single-nucleotide polymorphism (SNP) ITMAT-Broad-CARe (IBC) array in 5 cohorts from from the Candidate Gene Association Resource Consortium (n = 23,189). Replication was performed in up to 16 studies from the Cohorts for Heart Aging Research in Genomic Epidemiology Consortium (n = 74,584). In meta-analysis of discovery and replication estimates, 5 SNPs met at least one criterion for potential interaction with smoking on incident T2D at p\u3c1x10-7 (adjusted for multiple hypothesis-testing with the IBC array). Two SNPs had significant joint effects in the overall model and significant main effects only in one smoking stratum: rs140637 (FBN1) in AA individuals had a significant main effect only among smokers, and rs1444261 (closest gene C2orf63) in EA individuals had a significant main effect only among nonsmokers. Three additional SNPs were identified as having potential interaction by exhibiting a significant main effects only in smokers: rs1801232 (CUBN) in AA individuals, rs12243326 (TCF7L2) in EA individuals, and rs4132670 (TCF7L2) in EA individuals. No SNP met significance for potential interaction with smoking on baseline FG. The identification of these loci provides evidence for genetic interactions with smoking exposure that may explain some of the heterogeneity in the association between smoking and T2D

Trade-offs in the effects of the apolipoprotein E polymorphism on risks of diseases of the heart, cancer, and neurodegenerative disorders: Insights on mechanisms from the long life family study

The lack of evolutionary established mechanisms linking genes to age-related traits makes the problem of genetic susceptibility to health span inherently complex. One complicating factor is genetic trade-off. Here we focused on long-living participants of the Long Life Family Study (LLFS), their offspring, and spouses to: (1) Elucidate whether trade-offs in the effect of the apolipoprotein E e4 allele documented in the Framingham Heart Study (FHS) are a more general phenomenon, and (2) explore potential mechanisms generating age- and gender-specific trade-offs in the effect of the e4 allele on cancer, diseases of the heart, and neurodegenerative disorders assessed retrospectively in the LLFS populations. The e4 allele can diminish risks of cancer and diseases of the heart and confer risks of diseases of the heart in a sex-, age-, and LLFS-population-specific manner. A protective effect against cancer is seen in older long-living men and, potentially, their sons (>75 years, relative risk [RR](>75)=0.48, p=0.086), which resembles our findings in the FHS. The protective effect against diseases of the heart is limited to long-living older men (RR(>76)=0.50, p=0.016), as well. A detrimental effect against diseases of the heart is characteristic for a normal LLFS population of male spouses and is specific for myocardial infarction (RR=3.07, p=2.1×10(−3)). These trade-offs are likely associated with two inherently different mechanisms, including disease-specific (detrimental; characteristic for a normal male population) and systemic, aging-related (protective; characteristic for older long-living men) mechanisms. The e4 allele confers risks of neurological disorders in men and women (RR=1.98, p=0.046). The results highlight the complex role of the e4 allele in genetic susceptibility to health span

Exogenous exposures shape genetic predisposition to lipids, Alzheimer\u27s, and coronary heart disease in the MLXIPL gene locus

Associations of single nucleotide polymorphisms (SNPs) of th

NIA Long Life Family Study: Objectives, design, and heritability of cross-sectional and longitudinal phenotypes

The NIA Long Life Family Study (LLFS) is a longitudinal, multicenter, multinational, population-based multigenerational family study of the genetic and nongenetic determinants of exceptional longevity and healthy aging. The Visit 1 in-person evaluation (2006-2009) recruited 4 953 individuals from 539 two-generation families, selected from the upper 1% tail of the Family Longevity Selection Score (FLoSS, which quantifies the degree of familial clustering of longevity). Demographic, anthropometric, cognitive, activities of daily living, ankle-brachial index, blood pressure, physical performance, and pulmonary function, along with serum, plasma, lymphocytes, red cells, and DNA, were collected. A Genome Wide Association Scan (GWAS) (Ilumina Omni 2.5M chip) followed by imputation was conducted. Visit 2 (2014-2017) repeated all Visit 1 protocols and added carotid ultrasonography of atherosclerotic plaque and wall thickness, additional cognitive testing, and perceived fatigability. On average, LLFS families show healthier aging profiles than reference populations, such as the Framingham Heart Study, at all age/sex groups, for many critical healthy aging phenotypes. However, participants are not uniformly protected. There is considerable heterogeneity among the pedigrees, with some showing exceptional cognition, others showing exceptional grip strength, others exceptional pulmonary function, etc. with little overlap in these families. There is strong heritability for key healthy aging phenotypes, both cross-sectionally and longitudinally, suggesting that at least some of this protection may be genetic. Little of the variance in these heritable phenotypes is explained by the common genome (GWAS + Imputation), which may indicate that rare protective variants for specific phenotypes may be running in selected families

Epigenome-wide association study of triglyceride postprandial responses to a high-fat dietary challenge

Postprandial lipemia (PPL), the increased plasma TG concentration after consuming a high-fat meal, is an independent risk factor for CVD. Individual responses to a meal high in fat vary greatly, depending on genetic and lifestyle factors. However, only a few loci have been associated with TG-PPL response. Heritable epigenomic changes may be significant contributors to the unexplained inter-individual PPL variability. We conducted an epigenome-wide association study on 979 subjects with DNA methylation measured from CD4(+) T cells, who were challenged with a high-fat meal as a part of the Genetics of Lipid Lowering Drugs and Diet Network study. Eight methylation sites encompassing five genes, LPP, CPT1A, APOA5, SREBF1, and ABCG1, were significantly associated with PPL response at an epigenome-wide level (P < 1.1 × 10(−7)), but no methylation site reached epigenome-wide significance after adjusting for baseline TG levels. Higher methylation at LPP, APOA5, SREBF1, and ABCG1, and lower methylation at CPT1A methylation were correlated with an increased TG-PPL response. These PPL-associated methylation sites, also correlated with fasting TG, account for a substantially greater amount of phenotypic variance (14.9%) in PPL and fasting TG (16.3%) when compared with the genetic contribution of loci identified by our previous genome-wide association study (4.5%). In summary, the epigenome is a large contributor to the variation in PPL, and this has the potential to be used to modulate PPL and reduce CVD

Avoiding the high Bonferroni penalty in genome-wide association studies

A major challenge in genome-wide association studies (GWASs) is to derive the multiple testing threshold when hypothesis tests are conducted using a large number of single nucleotide polymorphisms. Permutation tests are considered the gold standard in multiple testing adjustment in genetic association studies. However, it is computationally intensive, especially for GWASs, and can be impractical if a large number of random shuffles are used to ensure accuracy. Many researchers have developed approximation algorithms to relieve the computing burden imposed by permutation. One particularly attractive alternative to permutation is to calculate the effective number of independent tests, Meff, which has been shown to be promising in genetic association studies. In this study, we compare recently developed Meff methods and validate them by the permutation test with 10,000 random shuffles using two real GWAS data sets: an Illumina 1M BeadChip and an Affymetrix GeneChip® Human Mapping 500K Array Set. Our results show that the simpleM method produces the best approximation of the permutation threshold, and it does so in the shortest amount of time. We also show that Meff is indeed valid on a genome-wide scale in these data sets based on statistical theory and significance tests. The significance thresholds derived can provide practical guidelines for other studies using similar population samples and genotyping platforms

Genetic analysis of long-lived families reveals novel variants influencing high density-lipoprotein cholesterol

The plasma levels of high-density lipoprotein cholesterol (HDL) have an inverse relationship to the risks of atherosclerosis and cardiovascular disease, and have also been associated with longevity. We sought to identify novel loci for HDL that could potentially provide new insights into biological regulation of HDL metabolism in healthy-longevous subjects. We performed a genome-wide association scan on HDL using a mixed model approach to account for family structure using kinship coefficients. A total of 4,114 subjects of European descent (480 families) were genotyped at ~2.3 million SNPs and ~38 million SNPs were imputed using the 1000 Genome Cosmopolitan reference panel in MACH. We identified novel variants near-NLRP1 (17p13) associated with an increase of HDL levels at genome-wide significant level (p< 5.0E-08). Additionally, several CETP (16q21) and ZNF259-APOA5-A4-C3-A1 (11q23.3) variants associated with HDL were found, replicating those previously reported in the literature. A possible regulatory variant upstream of NLRP1 that is associated with HDL in these elderly LLFS subjects may also contribute to their longevity and health. Our NLRP1 intergenic SNPs show a potential regulatory function in ENCODE; however, it is not clear whether they regulate NLRP1 or other more remote gene. NLRP1 plays an important role in the induction of apoptosis, and its inflammasome is critical for mediating innate immune responses. Nlrp1a (a mouse ortholog of human NLRP1) interacts with SREBP-1a (17p11) which has a fundamental role in lipid concentration and composition, and is involved in innate immune response in macrophages. The NLRP1 region is conserved in mammals, but also has evolved adaptively showing signals of positive selection in European populations that might confer an advantage. NLRP1 intergenic SNPs have also been associated with immunity/inflammasome disorders which highlights the biological importance of this chromosomal region

Leukocyte telomere length is unrelated to cognitive performance among non-demented and demented persons: An examination of long life family study participants

OBJECTIVE: Leukocyte telomere length (LTL) is a widely hypothesized biomarker of biological aging. Persons with shorter LTL may have a greater likelihood of developing dementia. We investigate whether LTL is associated with cognitive function, differently for individuals without cognitive impairment versus individuals with dementia or incipient dementia. METHOD: Enrolled subjects belong to the Long Life Family Study (LLFS), a multi-generational cohort study, where enrollment was predicated upon exceptional family longevity. Included subjects had valid cognitive and telomere data at baseline. Exclusion criteria were age ≤ 60 years, outlying LTL, and missing sociodemographic/clinical information. Analyses were performed using linear regression with generalized estimating equations, adjusting for sex, age, education, country, generation, and lymphocyte percentage. RESULTS: Older age and male gender were associated with shorter LTL, and LTL was significantly longer in family members than spouse controls (p \u3c 0.005). LTL was not associated with working or episodic memory, semantic processing, and information processing speed for 1613 cognitively unimpaired individuals as well as 597 individuals with dementia or incipient dementia (p \u3c 0.005), who scored significantly lower on all cognitive domains (p \u3c 0.005). CONCLUSIONS: Within this unique LLFS cohort, a group of families assembled on the basis of exceptional survival, LTL is unrelated to cognitive ability for individuals with and without cognitive impairment. LTL does not change in the context of degenerative disease for these individuals who are biologically younger than the general population

Genome- and CD4\u3csup\u3e+\u3c/sup\u3e T-Cell Methylome-Wide Association Study of Circulating Trimethylamine-N-Oxide in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN)

Background: Trimethylamine-N-oxide (TMAO), an atherogenic metabolite species, has emerged as a possible new risk factor for cardiovascular disease. Animal studies have shown that circulating TMAO levels are regulated by genetic and environmental factors. However, large-scale human studies have failed to replicate the observed genetic associations, and epigenetic factors such as DNA methylation have never been examined in relation to TMAO levels. Methods and results: We used data from the family-based Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) to investigate the heritable determinants of plasma TMAO in humans. TMAO was not associated with other plasma markers of cardiovascular disease, e.g. lipids or inflammatory cytokines. We first estimated TMAO heritability at 27%, indicating a moderate genetic influence. We used 1000 Genomes imputed data (n = 626) to estimate genome-wide associations with TMAO levels, adjusting for age, sex, family relationships, and study site. The genome-wide study yielded one significant hit at the genome-wide level, located in an intergenic region on chromosome 4. We subsequently quantified epigenome-wide DNA methylation using the Illumina Infinium array on CD4þ Tcells. We tested for association of methylation loci with circulating TMAO (n = 847), adjusting for age, sex, family relationships, and study site as the genome-wide study plus principal components capturing CD4þ T-cell purity. Upon adjusting for multiple testing, none of the epigenetic findings were statistically significant. Conclusions: Our findings contribute to the growing body of evidence suggesting that neither genetic nor epigenetic factors play a critical role in establishing circulating TMAO levels in humans