Distribution and clinical impact of functional variants in 50,726 whole-exome sequences from the DiscovEHR study.

The DiscovEHR collaboration between the Regeneron Genetics Center and Geisinger Health System couples high-throughput sequencing to an integrated health care system using longitudinal electronic health records (EHRs). We sequenced the exomes of 50,726 adult participants in the DiscovEHR study to identify ~4.2 million rare single-nucleotide variants and insertion/deletion events, of which ~176,000 are predicted to result in a loss of gene function. Linking these data to EHR-derived clinical phenotypes, we find clinical associations supporting therapeutic targets, including genes encoding drug targets for lipid lowering, and identify previously unidentified rare alleles associated with lipid levels and other blood level traits. About 3.5% of individuals harbor deleterious variants in 76 clinically actionable genes. The DiscovEHR data set provides a blueprint for large-scale precision medicine initiatives and genomics-guided therapeutic discovery.

Genome-wide interaction of genotype by erythrocyte n-3 fatty acids contributes to phenotypic variance of diabetes-related traits.

BACKGROUND: Little is known about the interplay between n-3 fatty acids and genetic variants for diabetes-related traits at the genome-wide level. The present study aimed to examine variance contributions of genotype by environment (GxE) interactions for different erythrocyte n-3 fatty acids and genetic variants for diabetes-related traits at the genome-wide level in a non-Hispanic white population living in the U.S.A. (n = 820). A tool for Genome-wide Complex Trait Analysis (GCTA) was used to estimate the genome-wide GxE variance contribution of four diabetes-related traits: HOMA-Insulin Resistance (HOMA-IR), fasting plasma insulin, glucose and adiponectin. A GxE genome-wide association study (GWAS) was conducted to further elucidate the GCTA results. Replication was conducted in the participants of the Boston Puerto Rican Health Study (BPRHS) without diabetes (n = 716). RESULTS: In GOLDN, docosapentaenoic acid (DPA) contributed the most significant GxE variance to the total phenotypic variance of both HOMA-IR (26.5%, P-nominal = 0.034) and fasting insulin (24.3%, P-nominal = 0.042). The ratio of arachidonic acid to eicosapentaenoic acid + docosahexaenoic acid contributed the most significant GxE variance to the total variance of fasting glucose (27.0%, P-nominal = 0.023). GxE variance of the arachidonic acid/eicosapentaenoic acid ratio showed a marginally significant contribution to the adiponectin variance (16.0%, P-nominal = 0.058). None of the GCTA results were significant after Bonferroni correction (P < 0.001). For each trait, the GxE GWAS identified a far larger number of significant single-nucleotide polymorphisms (P-interaction ≤ 10E-5) for the significant E factor (significant GxE variance contributor) than a control E factor (non-significant GxE variance contributor). In the BPRHS, DPA contributed a marginally significant GxE variance to the phenotypic variance of HOMA-IR (12.9%, P-nominal = 0.068) and fasting insulin (18.0%, P-nominal = 0.033). CONCLUSION: Erythrocyte n-3 fatty acids contributed a significant GxE variance to diabetes-related traits at the genome-wide level.

Polyunsaturated Fatty Acids Modulate the Association between PIK3CA-KCNMB3 Genetic Variants and Insulin Resistance.

BACKGROUND: Neighboring genes PIK3CA and KCNMB3 are both important for insulin signaling and ß-cell function, but their associations with glucose-related traits are unclear. OBJECTIVE: The objective was to examine associations of PIK3CA-KCNMB3 variants with glucose-related traits and potential interaction with dietary fat. DESIGN: We first investigated genetic associations and their modulation by dietary fat in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study (n = 820). Nine single-nucleotide polymorphisms (SNPs) were selected for analysis, covering more than 80% of the SNPs in the region. We then sought to replicate the findings in the Boston Puerto Rican Health Study (BPRHS) (n = 844). RESULTS: For KCNMB3 missense mutation rs7645550, meta-analysis indicated that homeostasis model assessment of insulin resistance (HOMA-IR) was significantly lower in minor allele T homozygotes compared with major allele C carriers (pooled P-value = 0.004); for another SNP rs1183319, which is in moderate LD with rs7645550, minor allele G carriers had higher HOMA-IR compared with non-carriers in both populations (pooled P-value = 0.028). In GOLDN, rs7645550 T allele homozygotes had lower HOMA-IR only when dietary n-3: n-6 PUFA ratio was low (≤0.11, P = 0.001), but not when it was high (>0.11, P-interaction = 0.033). Similar interaction was observed between rs1183319 and n-3: n-6 PUFA ratio on HOMA-IR (P-interaction = 0.001) in GOLDN. Variance contribution analyses in GOLDN confirmed the genetic association and gene-diet interaction. In BPRHS, dietary n-3: n-6 PUFA ratio significantly modulated the association between rs1183319 and HbA1c (P-interaction = 0.034). CONCLUSION: PIK3CA-KCNMB3 variants are associated with insulin resistance in populations of different ancestries, and are modified by dietary PUFA.

Total zinc intake may modify the glucose-raising effect of a zinc transporter (SLC30A8) variant: a 14-cohort meta-analysis.

OBJECTIVE: Many genetic variants have been associated with glucose homeostasis and type 2 diabetes in genome-wide association studies. Zinc is an essential micronutrient that is important for ß-cell function and glucose homeostasis. We tested the hypothesis that zinc intake could influence the glucose-raising effect of specific variants. RESEARCH DESIGN AND METHODS: We conducted a 14-cohort meta-analysis to assess the interaction of 20 genetic variants known to be related to glycemic traits and zinc metabolism with dietary zinc intake (food sources) and a 5-cohort meta-analysis to assess the interaction with total zinc intake (food sources and supplements) on fasting glucose levels among individuals of European ancestry without diabetes. RESULTS: We observed a significant association of total zinc intake with lower fasting glucose levels (ß-coefficient ± SE per 1 mg/day of zinc intake: -0.0012 ± 0.0003 mmol/L, summary P value = 0.0003), while the association of dietary zinc intake was not significant. We identified a nominally significant interaction between total zinc intake and the SLC30A8 rs11558471 variant on fasting glucose levels (ß-coefficient ± SE per A allele for 1 mg/day of greater total zinc intake: -0.0017 ± 0.0006 mmol/L, summary interaction P value = 0.005); this result suggests a stronger inverse association between total zinc intake and fasting glucose in individuals carrying the glucose-raising A allele compared with individuals who do not carry it. None of the other interaction tests were statistically significant. CONCLUSIONS: Our results suggest that higher total zinc intake may attenuate the glucose-raising effect of the rs11558471 SLC30A8 (zinc transporter) variant. Our findings also support evidence for the association of higher total zinc intake with lower fasting glucose levels.

ADIPOQ polymorphisms, monounsaturated fatty acids, and obesity risk: the GOLDN study.

Serum adiponectin levels have been positively associated with insulin sensitivity and are decreased in type 2 diabetes (T2D) and obesity. Genetic and environmental factors influence serum adiponectin and may contribute to risk of metabolic syndrome and T2D. Therefore, we investigated the effect of ADIPOQ single-nucleotide polymorphisms (SNPs), -11377C>G and -11391G>A, on metabolic-related traits, and their modulation by dietary fat in white Americans. Data were collected from 1,083 subjects participating in the Genetics of Lipid Lowering Drugs and Diet Network study. Mean serum adiponectin concentration was higher for carriers of the -11391A allele (P = 0.001) but lower for the -11377G allele carriers (P = 0.017). Moreover, we found a significant association with obesity traits for the -11391G>A SNP. Carriers of the -11391A allele had significantly lower weight (P = 0.029), BMI (P = 0.019), waist (P = 0.003), and hip circumferences (P = 0.004) compared to noncarriers. Interestingly, the associations of the -11391G>A with BMI and obesity risk were modified by monounsaturated fatty acids (MUFAs) intake (P-interaction = 0.021 and 0.034 for BMI and obesity risk, respectively). In subjects with MUFA intake above the median (> or =13% of energy intake), -11391A carriers had lower BMI (27.1 kg/m(2) for GA+AA vs. 29.1 kg/m(2) for GG, P = 0.002) and decreased obesity risk (odds ratio for -11391A = 0.52, 95% confidence interval (CI); 0.28-0.96; P = 0.031). However, we did not detect genotype-related differences for BMI or obesity in subjects with MUFA intake <13%. Our findings support a significant association between the -11391G>A SNPs and obesity-related traits and the potential to moderate such effects using dietary modification.