👤 James Hixson

Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 × 10 Show less

Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals ( Show less

Factors that contribute to the onset of atherosclerosis may be elucidated by bioinformatic techniques applied to multiple sources of genomic and proteomic data. The results of genome wide association studies, such as the CardioGramPlusC4D study, expression data, such as that available from expression quantitative trait loci (eQTL) databases, along with protein interaction and pathway data available in Ingenuity Pathway Analysis (IPA), constitute a substantial set of data amenable to bioinformatics analysis. This study used bioinformatic analyses of recent genome wide association data to identify a seed set of genes likely associated with atherosclerosis. The set was expanded to include protein interaction candidates to create a network of proteins possibly influencing the onset and progression of atherosclerosis. Local average connectivity (LAC), eigenvector centrality, and betweenness metrics were calculated for the interaction network to identify top gene and protein candidates for a better understanding of the atherosclerotic disease process. The top ranking genes included some known to be involved with cardiovascular disease ( Show less

Genetic variants near and within the fatty acid desaturase (FADS) cluster are associated with polyunsaturated fatty acid (PUFA) biosynthesis, levels of several disease biomarkers and risk of human disease. However, determining the functional mechanisms by which these genetic variants impact PUFA levels remains a challenge. Utilizing an Illumina 450K array, we previously reported strong allele-specific methylation (ASM) associations (p = 2.69×10-29) between a single nucleotide polymorphism (SNP) rs174537 and DNA methylation of CpG sites located in the putative enhancer region between FADS1 and FADS2, in human liver tissue. However, this array only featured 20 CpG sites within this 12kb region. To better understand the methylation landscape within this region, we conducted bisulfite sequencing of the region between FADS1 and FADS2. Liver tissues from 50 male subjects (27 European Americans, 23 African Americans) were obtained from the Pathobiological Determinants of Atherosclerosis in Youth (PDAY) study, and used to ascertain the genotype at rs174537 and methylation status across the region of interest. Associations between rs174537 genotype and methylation status of 136 CpG sites were determined. Age-adjusted linear regressions were used to assess ASM associations with rs174537 genotype. The majority of CpG sites (117 out of 136, 86%) exhibited high levels of methylation with the greatest variability observed at three key regulatory regions-the promoter regions for FADS1 and FADS2 and a putative enhancer site between the two genes. Eight CpG sites within the putative enhancer region displayed significant (FDR p <0.05) ASM associations with rs174537. These data support the concept that both genetic and epigenetic factors regulate PUFA biosynthesis, and raise fundamental questions as to how genetic variants such as rs174537 impact DNA methylation in distant regulatory regions, and ultimately the capacity of tissues to synthesize PUFAs. Show less

Levels of omega-6 (n-6) and omega-3 (n-3), long chain polyunsaturated fatty acids (LcPUFAs) such as arachidonic acid (AA; 20:4, n-6), eicosapentaenoic acid (EPA; 20:5, n-3) and docosahexaenoic acid (DHA; 22:6, n-3) impact a wide range of biological activities, including immune signaling, inflammation, and brain development and function. Two desaturase steps (Δ6, encoded by FADS2 and Δ5, encoded by FADS1) are rate limiting in the conversion of dietary essential 18 carbon PUFAs (18C-PUFAs) such as LA (18:2, n-6) to AA and α-linolenic acid (ALA, 18:3, n-3) to EPA and DHA. GWAS and candidate gene studies have consistently identified genetic variants within FADS1 and FADS2 as determinants of desaturase efficiencies and levels of LcPUFAs in circulating, cellular and breast milk lipids. Importantly, these same variants are documented determinants of important cardiovascular disease risk factors (total, LDL, and HDL cholesterol, triglycerides, CRP and proinflammatory eicosanoids). FADS1 and FADS2 lie head-to-head (5' to 5') in a cluster configuration on chromosome 11 (11q12.2). There is considerable linkage disequilibrium (LD) in this region, where multiple SNPs display association with LcPUFA levels. For instance, rs174537, located ∼ 15 kb downstream of FADS1, is associated with both FADS1 desaturase activity and with circulating AA levels (p-value for AA levels = 5.95 × 10(-46)) in humans. To determine if DNA methylation variation impacts FADS activities, we performed genome-wide allele-specific methylation (ASM) with rs174537 in 144 human liver samples. This approach identified highly significant ASM with CpG sites between FADS1 and FADS2 in a putative enhancer signature region, leading to the hypothesis that the phenotypic associations of rs174537 are likely due to methylation differences. In support of this hypothesis, methylation levels of the most significant probe were strongly associated with FADS1 and, to a lesser degree, FADS2 activities. Show less

The apolipoproteins (APOA1/C3/A4/A5) are key components in modulating lipoprotein metabolism. It is unknown whether variants at the APOA1/C3/A4/A5 gene cluster are associated with lipid response to pharmacologic intervention. Plasma triglycerides (TGs) and high-density lipoprotein (HDL) levels were measured in 861 Genetics of Lipid-Lowering Drugs and Diet Network study participants who underwent a 3-week fenofibrate trial. We examined 18 common single nucleotide polymorphisms (SNPs) spanning the APOA1/C3/A4/A5 genes to investigate the effects of variants at the gene cluster on lipid response to fenofibrate treatment. We found that the minor alleles of the SNPs rs3135506 (APOA5_S19W), rs5104 (APOA4_N147S), rs4520 (APOC3_G34G), and rs5128 (APOC3₃U386) were associated with enhanced TG response to fenofibrate treatment (P= 0.0004-0.018). The minor allele of SNP rs2854117 (APOC3_M482) was associated with reduced rather than enhanced TG response (P= 0.026). The SNP rs3135506 (APOA5_S19W) was associated with HDL response, with minor allele related to reduced HDL response to fenofibrate (P= 0.002). Association analyses on haplotype provided corroborative evidence to single SNP association analyses. The common haplotypes H2, H3, and H5 were significantly associated with reduced TG response to fenofibrate. The genetic variants at APOA1/C3/A4/A5 gene cluster may be useful markers to predict response of lipid-lowering therapy with fenofibrate. Further studies to replicate/confirm our findings are warranted. Show less

Apolipoprotein A5 (APOA5) is a key determinant of plasma triglyceride (TG) concentrations. Genetic variation at the APOA5 locus could be responsible for some of the observed differences in response to fenofibrate therapy. We examined the association between tag SNPs (-1131T>C and 56C>G) at APOA5 and TG and HDL-C response to fenofibrate and a postprandial lipid challenge in 791 men and women participating in the GOLDN study. After 3-week drug treatment, APOA5 56G carriers displayed significant decrease in TG (P=0.006), and increase in HDL-C (P=0.002) levels relative to their basal values in the fasting state when compared with noncarriers (a TG reduction of -35.8+/-2.8% versus -27.9+/-0.9% and a HDL-C increase of 11.8+/-1.3% versus 6.9+/-0.5%, respectively). In the postprandial lipemia after a fat load, the 56G carriers showed a significant decrease in the area under curve for TG and increase for HDL-C than the noncarriers. These diverse beneficial responses of 56G carriers to fenofibrate were further characterized by a higher increase in large LDL-C concentrations and LDL size. On the other hand, subjects with different APOA5-1131T>C genotypes showed no significant response to fenofibrate intervention. This study suggests that the APOA5 56G carriers benefited more from the fenofibrate treatment than noncarriers in lowering plasma TG and increasing HDL-C levels. Show less

Most tests of association between DNA sequence variation and quantitative phenotypes in samples of randomly chosen individuals rely on specification of genotypic strata followed by comparison of phenotypes across these strata. This strategy often succeeds when phenotypic differences are caused by one or two single nucleotide polymorphisms (SNPs) among the surveyed markers. However, when multiple-SNP haplotypes account for observed phenotypic variation, identification of the best partitioning requires examination of an inordinate number of SNP combinations. An alternative approach is to rank individuals by their phenotypic measures and ask whether attributes of the genotypic variation show a non-random distribution along this phenotypic ranking. One simple version of this strategy selects the top and bottom tails of the distribution, and then tests whether genotypes from these two samples are drawn from a single population. This framework does not require the recovery of phased haplotypes and allows contrasts between large numbers of sites at once. We use a method based on this approach to identify associations between plasma triglyceride level, a risk factor for cardiovascular disease, and multi-site genotypes located in the APOA1/C3/A4/A5 cluster of apolipoprotein genes in unrelated individuals (1,071 African-American females, 780 African-American males, 1,036 European-American females, and 930 European-American males) sampled from four US cities as part of the Coronary Artery Risk Development in Young Adults (CARDIA) study. Method performance is investigated using simulations that model genealogical variation and different genetic architectures. Results indicate that this multi-site test can identify genotype-phenotype associations with reasonable power, including those generated by some simple epistatic models. Show less

Apolipoproteins (apo) A-I and C-III are components of high-density lipoprotein-cholesterol (HDL-C), a quantitative trait negatively correlated with risk of cardiovascular disease (CVD). We analyzed the contribution of individual and pairwise combinations of single nucleotide polymorphisms (SNPs) in the APOA1/APOC3 genes to HDL-C variability to evaluate (1) consistency of published single-SNP studies with our single-SNP analyses; (2) consistency of single-SNP and two-SNP phenotype-genotype relationships across race-, gender-, and geographical location-dependent contexts; and (3) the contribution of single SNPs and pairs of SNPs to variability beyond that explained by plasma apo A-I concentration. We analyzed 45 SNPs in 3,831 young African-American (N=1,858) and European-American (N=1,973) females and males ascertained by the Coronary Artery Risk Development in Young Adults (CARDIA) study. We found three SNPs that significantly impact HDL-C variability in both the literature and the CARDIA sample. Single-SNP analyses identified only one of five significant HDL-C SNP genotype relationships in the CARDIA study that was consistent across all race-, gender-, and geographical location-dependent contexts. The other four were consistent across geographical locations for a particular race-gender context. The portion of total phenotypic variance explained by single-SNP genotypes and genotypes defined by pairs of SNPs was less than 3%, an amount that is miniscule compared to the contribution explained by variability in plasma apo A-I concentration. Our findings illustrate the impact of context-dependence on SNP selection for prediction of CVD risk factor variability. Show less