Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10⁻³) and candidate genes from knockout mice (P = 5.2 × 10⁻³). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000–185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.

The estimated prevalence of type 2 diabetes in Mexican adults was 14.4% in 2006,¹ making it one of the leading causes of death in Mexico.² Based on statistics from 1999-2002, the standardized prevalence of diagnosed diabetes was 10% in Mexican Americans and 5.2% in whites.³ Although environmental factors such as lifestyle and diet likely explain the majority of this health disparity, it was recently found that genetic variants in the gene SLC16A11 (NCBI NC_000017.11) were associated with higher rates of type 2 diabetes in Latinos.⁴Latinos, defined as persons who trace their origin to Central and South America, and other Spanish cultures, fall on a continuum of Native American and European genetic ancestry.⁴ Identifying genetic factors associated with type 2 diabetes in Latino populations could increase understanding of its pathophysiology, improve risk prediction, and focus treatment choice based on knowledge of the underlying biology of the disease.

Hundreds of thousands of genetic variants have been reported to cause severe monogenic diseases, but the probability that a variant carrier develops the disease (termed penetrance) is unknown for virtually all of them. Additionally, the clinical utility of common polygenetic variation remains uncertain. Using exome sequencing from 77,184 adult individuals (38,618 multi-ancestral individuals from a type 2 diabetes case-control study and 38,566 participants from the UK Biobank, for whom genotype array data were also available), we apply clinical standard-of-care gene variant curation for eight monogenic metabolic conditions. Rare variants causing monogenic diabetes and dyslipidemias display effect sizes significantly larger than the top 1% of the corresponding polygenic scores. Nevertheless, penetrance estimates for monogenic variant carriers average 60% or lower for most conditions. We assess epidemiologic and genetic factors contributing to risk prediction in monogenic variant carriers, demonstrating that inclusion of polygenic variation significantly improves biomarker estimation for two monogenic dyslipidemias.