Ryan Koesterer

Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls 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.

IMPORTANCE: Cannabis dependence (CAD) is a serious problem worldwide and is of growing importance in the United States because cannabis is increasingly available legally. Although genetic factors contribute substantially to CAD risk, at present no well-established specific genetic risk factors for CAD have been elucidated. OBJECTIVE: To report findings for DSM-IV CAD criteria from association analyses performed in large cohorts of African American and European American participants from 3 studies of substance use disorder genetics. DESIGN, SETTING, AND PARTICIPANTS: This genome-wide association study for DSM-IV CAD criterion count was performed in 3 independent substance dependence cohorts (the Yale-Penn Study, Study of Addiction: Genetics and Environment [SAGE], and International Consortium on the Genetics of Heroin Dependence [ICGHD]). A referral sample and volunteers recruited in the community and from substance abuse treatment centers included 6000 African American and 8754 European American participants, including some from small families. Participants from the Yale-Penn Study were recruited from 2000 to 2013. Data were collected for the SAGE trial from 1990 to 2007 and for the ICGHD from 2004 to 2009. Data were analyzed from January 2, 2013, to November 9, 2015. MAIN OUTCOMES AND MEASURES: Criterion count for DSM-IV CAD. RESULTS: Among the 14 754 participants, 7879 were male, 6875 were female, and the mean (SD) age was 39.2 (10.2) years. Three independent regions with genome-wide significant single-nucleotide polymorphism associations were identified, considering the largest possible sample. These included rs143244591 (β = 0.54, P = 4.32 × 10-10 for the meta-analysis) in novel antisense transcript RP11-206M11.7;rs146091982 (β = 0.54, P = 1.33 × 10-9 for the meta-analysis) in the solute carrier family 35 member G1 gene (SLC35G1); and rs77378271 (β = 0.29, P = 2.13 × 10-8 for the meta-analysis) in the CUB and Sushi multiple domains 1 gene (CSMD1). Also noted was evidence of genome-level pleiotropy between CAD and major depressive disorder and for an association with single-nucleotide polymorphisms in genes associated with schizophrenia risk. Several of the genes identified have functions related to neuronal calcium homeostasis or central nervous system development. CONCLUSIONS AND RELEVANCE: These results are the first, to our knowledge, to identify specific CAD risk alleles and potential genetic factors contributing to the comorbidity of CAD with major depression and schizophrenia.