Abstract Text |
The majority of genetic variants significantly associated with diabetes-related glycemic traits reside in the noncoding genome, with many causal variants still unknown. Whole genome sequence association (WGSA) analysis allows us to fine-map known and novel loci across the noncoding genome without depending on imputation. Here, we present an initial WGSA of fasting insulin (FI) and fasting glucose (FG) levels in phase 1 (released in the fall of 2016) TOPMed data (N=7,121) with deep (>30x) sequence coverage in five cohorts, three European-ancestry (EA): Framingham Heart Study, N=3,209; Old Order Amish Studies, N=980, Cleveland Family Study, N=197, and two AfricanAmerican (AA): Jackson Heart Study, N=2,487, Cleveland Family Study, N=248. For each cohort, we used linear mixed effects models (as implemented in EMMAX or MMAP software) adjusting for sex, age and BMI, with empirical kinship for relatedness and population structure. We restricted to variants with minor allele count > 5 in more than 1 cohort and meta-analyzed within and across ancestry with METAL. In EA+AA analysis, common (minor allele frequency [MAF]>0.05) variant associations (P<5x108) were identified for FG at known loci: MTNR1B (rs10830963, P=2.5x1016; rs12792753, P=1.4x108), GCK (rs4607517, P=1.16x1010, and 13 additional variants), and G6PC2 (rs560887, P=5.4x1010). At the MTNR1B locus, finemapping across ancestries reduced the significant FG associations from 46 (EA) to 2 (AA+EA). Novel FI associations were seen in rare (MAF<1%) variants: 18q12.1 (rs146884135, P=2.1x109), 4p12 (rs193168677, P=1.2x108), 1q25.3 (rs550837507, P=3.8x108), and DCLK3 (rs573417731, P=4.8x108). These results, which are being extended with phase 2 TOPMed cohorts (expected release is in the summer of 2017; expected total N=27,830), highlight the value of multi-ancestry WGSA to refine known and discover novel associations for complex traits. Future analyses with combined phase 1 and phase 2 data will assess (1) enrichment of subsignificant associations using diabetesspecific functional annotations of the noncoding genome, and (2) the association of rare variants within these diabetesspecific functional annotations with fasting glucose and fasting insulin levels.
|