Glycemic traits are used to diagnose and monitor type 2 diabetes, and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here, we aggregated genome-wide association studies in up to 281,416 individuals without diabetes (30% non-European ancestry) with fasting glucose, 2h-glucose post-challenge, glycated hemoglobin, and fasting insulin data. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P <5x10 -8 ), 80% with no significant evidence of between-ancestry heterogeneity. Analyses restricted to European ancestry individuals with equivalent sample size would have led to 24 fewer new loci. Compared to single-ancestry, equivalent sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase understanding of diabetes pathophysiology by use of trans-ancestry studies for improved power and resolution.
Performing genetic studies in multiple human populations can identify disease risk alleles that are common in one population but rare in others1, with the potential to illuminate pathophysiology, health disparities, and the population genetic origins of disease alleles. We analyzed 9.2 million single nucleotide polymorphisms (SNPs) in each of 8,214 Mexicans and Latin Americans: 3,848 with type 2 diabetes (T2D) and 4,366 non-diabetic controls. In addition to replicating previous findings2–4, we identified a novel locus associated with T2D at genome-wide significance spanning the solute carriers SLC16A11 and SLC16A13 (P=3.9×10−13; odds ratio (OR)=1.29). The association was stronger in younger, leaner people with T2D, and replicated in independent samples (P=1.1×10−4; OR=1.20). The risk haplotype carries four amino acid substitutions, all in SLC16A11; it is present at ≈50% frequency in Native American samples and ≈10% in East Asian, but rare in European and African samples. Analysis of an archaic genome sequence indicated the risk haplotype introgressed into modern humans via admixture with Neandertals. The SLC16A11 mRNA is expressed in liver, and V5-tagged SLC16A11 protein localizes to the endoplasmic reticulum. Expression of SLC16A11 in heterologous cells alters lipid metabolism, most notably causing an increase in intracellular triacylglycerol levels. Despite T2D having been well studied by genome-wide association studies (GWAS) in other populations, analysis in Mexican and Latin American individuals identified SLC16A11 as a novel candidate gene for T2D with a possible role in triacylglycerol metabolism.
IMPORTANCE Latino populations have one of the highest prevalences of type 2 diabetes worldwide. OBJECTIVES To investigate the association between rare protein-coding genetic variants and prevalence of type 2 diabetes in a large Latino population and to explore potential molecular and physiological mechanisms for the observed relationships. DESIGN, SETTING, AND PARTICIPANTS Whole-exome sequencing was performed on DNA samples from 3756 Mexican and US Latino individuals (1794 with type 2 diabetes and 1962 without diabetes) recruited from 1993 to 2013. One variant was further tested for allele frequency and association with type 2 diabetes in large multiethnic data sets of 14 276 participants and characterized in experimental assays. MAIN OUTCOME AND MEASURES Prevalence of type 2 diabetes. Secondary outcomes included age of onset, body mass index, and effect on protein function. RESULTS A single rare missense variant (c.1522G>A [p.E508K]) was associated with type 2 diabetes prevalence (odds ratio [OR], 5.48; 95% CI, 2.83–10.61; P = 4.4 × 10−7) in hepatocyte nuclear factor 1-α (HNF1A), the gene responsible for maturity onset diabetes of the young type 3 (MODY3). This variant was observed in 0.36% of participants without type 2 diabetes and 2.1% of participants with it. In multiethnic replication data sets, the p.E508K variant was seen only in Latino patients (n = 1443 with type 2 diabetes and 1673 without it) and was associated with type 2 diabetes (OR, 4.16; 95% CI, 1.75–9.92; P = .0013). In experimental assays, HNF-1A protein encoding the p.E508K mutant demonstrated reduced transactivation activity of its target promoter compared with a wild-type protein. In our data, carriers and noncarriers of the p.E508K mutation with type 2 diabetes had no significant differences in compared clinical characteristics, including age at onset. The mean (SD) age for carriers was 45.3 years (11.2) vs 47.5 years (11.5) for noncarriers (P = .49) and the mean (SD) BMI for carriers was 28.2 (5.5) vs 29.3 (5.3) for noncarriers (P = .19). CONCLUSIONS AND RELEVANCE Using whole-exome sequencing, we identified a single low-frequency variant in the MODY3-causing gene HNF1A that is associated with type 2 diabetes in Latino populations and may affect protein function. This finding may have implications for screening and therapeutic modification in this population, but additional studies are required.
Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40–50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10–20% (14–24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.
In many species, the offspring of related parents suffer reduced reproductive success, a phenomenon known as inbreeding depression. In humans, the importance of this effect has remained unclear, partly because reproduction between close relatives is both rare and frequently associated with confounding social factors. Here, using genomic inbreeding coefficients (FROH) for >1.4 million individuals, we show that FROH is significantly associated (p < 0.0005) with apparently deleterious changes in 32 out of 100 traits analysed. These changes are associated with runs of homozygosity (ROH), but not with common variant homozygosity, suggesting that genetic variants associated with inbreeding depression are predominantly rare. The effect on fertility is striking: FROH equivalent to the offspring of first cousins is associated with a 55% decrease [95% CI 44–66%] in the odds of having children. Finally, the effects of FROH are confirmed within full-sibling pairs, where the variation in FROH is independent of all environmental confounding.
Genome-wide association studies (GWAS) have identified more than 80 susceptibility loci for type 2 diabetes (T2D), but most of its heritability still remains to be elucidated. In this study, we conducted a meta-analysis of GWAS for T2D in the Japanese population. Combined data from discovery and subsequent validation analyses (23,399 T2D cases and 31,722 controls) identify 7 new loci with genome-wide significance (P<5 × 10−8), rs1116357 near CCDC85A, rs147538848 in FAM60A, rs1575972 near DMRTA1, rs9309245 near ASB3, rs67156297 near ATP8B2, rs7107784 near MIR4686 and rs67839313 near INAFM2. Of these, the association of 4 loci with T2D is replicated in multi-ethnic populations other than Japanese (up to 65,936 T2Ds and 158,030 controls, P<0.007). These results indicate that expansion of single ethnic GWAS is still useful to identify novel susceptibility loci to complex traits not only for ethnicity-specific loci but also for common loci across different ethnicities.
Several studies have identified nearly 40 different type 2 diabetes susceptibility loci, mainly in European populations, but few of them have been evaluated in the Mexican population. The aim of this study was to examine the extent to which 24 common genetic variants previously associated with type 2 diabetes are associated in Mexican Mestizos. Twenty-four single nucleotide polymorphisms (SNPs) in or near genes (KCNJ11, PPARG, TCF7L2, SLC30A8, HHEX, CDKN2A/2B, CDKAL1, IGF2BP2, ARHGEF11, JAZF1, CDC123/CAMK1D, FTO, TSPAN8/LGR5, KCNQ1, THADA, ADAMTS9, NOTCH2, NXPH1, RORA, UBQLNL, and RALGPS2) were genotyped in Mexican Mestizos. A case-control association study comprising 1,027 type 2 diabetic individuals and 990 control individuals was conducted. To account for population stratification, a panel of 104 ancestry-informative markers was analyzed. Association to type 2 diabetes was found for rs13266634 (SLC30A8), rs7923837 (HHEX), rs10811661 (CDKN2A/2B), rs4402960 (IGF2BP2), rs12779790 (CDC123/CAMK1D), and rs2237892 (KCNQ1). In addition, rs7754840 (CDKAL1) was associated in the nonobese type 2 diabetic subgroup, and for rs7903146 (TCF7L2), association was observed for early-onset type 2 diabetes. Lack of association for the rest of the variants may have resulted from insufficient power to detect smaller allele effects.
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