241-OR: Causal Gene Candidates for Type 2 Diabetes Based on Protein-Coding Variants in 127,676 Individuals

Diabetes ◽  
2020 ◽  
Vol 69 (Supplement 1) ◽  
pp. 241-OR
Author(s):  
PETER DORNBOS ◽  
LAURA RAFFIELD ◽  
XIANYONG YIN ◽  
JASON FLANNICK
Keyword(s):  
Type 2 Diabetes ◽  
Causal Gene ◽  
Protein Coding ◽  
Coding Variants

scholarly journals Protein-Coding Variants Implicate Novel Genes Related to Lipid Homeostasis Contributing to Body Fat Distribution

2018 ◽  
Author(s):  
Anne E Justice ◽  
Tugce Karaderi ◽  
Heather M Highland ◽  
Kristin L Young ◽  
Mariaelisa Graff ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Body Fat ◽  
Low Frequency ◽  
Fat Distribution ◽  
Body Fat Distribution ◽  
European Ancestry ◽  
Novel Genes ◽  
Protein Coding ◽  
Coding Variants

ABSTRACTBody fat distribution is a heritable risk factor for a range of adverse health consequences, including hyperlipidemia and type 2 diabetes. To identify protein-coding variants associated with body fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, we analyzed 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries for discovery and 132,177 independent European-ancestry individuals for validation. We identified 15 common (minor allele frequency, MAF≥5%) and 9 low frequency or rare (MAF<5%) coding variants that have not been reported previously. Pathway/gene set enrichment analyses of all associated variants highlight lipid particle, adiponectin level, abnormal white adipose tissue physiology, and bone development and morphology as processes affecting fat distribution and body shape. Furthermore, the cross-trait associations and the analyses of variant and gene function highlight a strong connection to lipids, cardiovascular traits, and type 2 diabetes. In functional follow-up analyses, specifically in Drosophila RNAi-knockdown crosses, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). By examining variants often poorly tagged or entirely missed by genome-wide association studies, we implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants.

scholarly journals Gain-of-Function Claims for Type-2-Diabetes-Associated Coding Variants in SLC16A11 Are Not Supported by the Experimental Data

Cell Reports ◽  
2019 ◽  
Vol 29 (3) ◽  
pp. 778-780 ◽  
Author(s):  
Eitan Hoch ◽  
Jose C. Florez ◽  
Eric S. Lander ◽  
Suzanne B.R. Jacobs
Keyword(s):  
Experimental Data ◽  
Type 2 Diabetes ◽  
Gain Of Function ◽  
Coding Variants

scholarly journals Analysis of coding variants in the betacellulin gene in type 2 diabetes and insulin secretion in African American subjects

2006 ◽  
Vol 7 (1) ◽  
Author(s):  
Steven C Elbein ◽  
Xiaoqin Wang ◽  
Mohammad A Karim ◽  
Winston S Chu ◽  
Kristi D Silver
Keyword(s):  
Type 2 Diabetes ◽  
African American ◽  
Insulin Secretion ◽  
Coding Variants

scholarly journals Infrequent TRIB3 coding variants and coronary artery disease in type 2 diabetes

2015 ◽  
Vol 242 (1) ◽  
pp. 334-339 ◽  
Author(s):  
Sabrina Prudente ◽  
Diego Bailetti ◽  
Christine Mendonca ◽  
Gaia Chiara Mannino ◽  
Andrea Fontana ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Artery Disease ◽  
Coding Variants

scholarly journals Whole-Exome Sequencing of 2,000 Danish Individuals and the Role of Rare Coding Variants in Type 2 Diabetes

2014 ◽  
Vol 94 (3) ◽  
pp. 479
Author(s):  
Kirk E. Lohmueller ◽  
Thomas Sparsø ◽  
Qibin Li ◽  
Ehm Andersson ◽  
Thorfinn Korneliussen ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Exome Sequencing ◽  
Whole Exome Sequencing ◽  
Whole Exome ◽  
Coding Variants

scholarly journals Genetic discovery and translational decision support from exome sequencing of 20,791 type 2 diabetes cases and 24,440 controls from five ancestries

2018 ◽  
Author(s):  
Jason Flannick ◽  
Josep M Mercader ◽  
Christian Fuchsberger ◽  
Miriam S Udler ◽  
Anubha Mahajan ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Rare Variant ◽  
Drug Targets ◽  
Disease Risk ◽  
Protein Coding ◽  
Gene Sets ◽  
Gene Level ◽  
Variant Gene ◽  
Or Gene

AbstractProtein-coding genetic variants that strongly affect disease risk can provide important clues into disease pathogenesis. Here we report an exome sequence analysis of 20,791 type 2 diabetes (T2D) cases and 24,440 controls from five ancestries. We identify rare (minor allele frequency<0.5%) variant gene-level associations in (a) three genes at exome-wide significance, including a T2D-protective series of >30 SLC30A8 alleles, and (b) within 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 rare variant gene-level signals explain at most 25% of the heritability of the strongest common single-variant signals, and the rare variant gene-level effect sizes we observe in established T2D drug targets will require 110K-180K sequenced cases to exceed exome-wide significance. To help prioritize genes using associations from current smaller sample sizes, we present a Bayesian framework to recalibrate association p-values as posterior probabilities of association, estimating that reaching p<0.05 (p<0.005) in our study increases the odds of causal T2D association for a nonsynonymous variant by a factor of 1.8 (5.3). To help guide target or gene prioritization efforts, our data are freely available for analysis at www.type2diabetesgenetics.org.

scholarly journals Sequence data and association statistics from 12,940 type 2 diabetes cases and controls

2017 ◽  
Vol 4 (1) ◽  
Author(s):  
Jason Flannick ◽  
Christian Fuchsberger ◽  
Anubha Mahajan ◽  
Tanya M. Teslovich ◽  
Vineeta Agarwala ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Sequence Data ◽  
Functional Characterization ◽  
Low Frequency ◽  
Genotype Imputation ◽  
Whole Genome ◽  
Frequency Coding ◽  
Coding Variants ◽  
Or Genes

Abstract To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1–5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

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