A combined polygenic score of 21,293 rare and 22 common variants improves diabetes diagnosis based on hemoglobin A1C levels.
Dornbos P, et al.
Nat Genet. 2022 Oct 24. doi: 10.1038/s41588-022-01200-1.
Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls.
Flannick J, et al.
Nature. 2019 May 22. doi: 10.1038/s41586-019-1231-2
Sequence data and association statistics from 12,940 type 2 diabetes cases and controls.
Flannick J, Fuchsberger C, Mahajan A, et al.
Sci Data. 2017 Dec 19;4:170179. doi: 10.1038/sdata.2017.179
The genetic architecture of type 2 diabetes.
Fuchsberger C, Flannick J, Teslovich TM, Mahajan A, Agarwala V, Gaulton KJ, et al.
Nature 2016 Aug 4;536(7614):41-7. doi: 10.1038/nature18642
Association of a low-frequency variant in HNF1A with type 2 diabetes in a Latino population.
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Whole-exome sequencing of 2,000 Danish individuals and the role of rare coding variants in type 2 diabetes.
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- Diastolic blood pressure
- Fasting glucose
- Fasting insulin
- HDL cholesterol
- Hip circumference
- LDL cholesterol
- Serum creatinine
- Systolic blood pressure
- Total cholesterol
- Triglyceride-to-HDL ratio
- Waist circumference
- Waist-hip ratio
|Project||Cases||Controls||Cohort (Click to view selection criteria for cases and controls)||Ancestry|
|T2D-GENES||529||537||London Life Sciences Population (LOLIPOP)
|T2D-GENES||854||890||Pakistan Genomic Resource (PGR)
|T2D-GENES||536||576||Singapore Indian Eye Study
Type 2 Diabetes Genetic Exploration by Next-Generation Sequencing in Ethnic Samples (T2D-GENES) Learn more >
T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) is a large collaborative effort to find genetic variants that influence risk of type 2 diabetes. With funding from NIDDK, the group is pursuing three projects: (1) deep whole-exome sequencing in 10,000 people from five ethnicities (African-American, East Asian, South Asian, European, and Hispanic); (2) deep whole-genome sequencing of 600 individuals selected from extended Mexican American pedigrees; and (3) a trans-ethnic fine-mapping "mega-meta-analysis."
Overview of analysis and results
The T2D analysis reported in Flannick et al. 2019 was extended to 24 quantitative traits. Briefly, single-variant association analyses were conducted for each trait (n=24) at the sample sub-group level (n=25). We analyzed samples using the EMMAX test via the EPACTS software package. A genomic relationship matrix (GRM) was included to account for relatedness across samples. In all cases, multiallelic sites were categorized as a single "non-reference" allele.
For each of the 25 sub-studies × 24 traits (n=600) single-variant analyses, quantile-quantile (QQ)-plots of all and common (MAC>20) alleles were used to assess whether the regression models were well-calibrated (i.e., comparison of regression results to expected results under a null-model). Stringencies of the variant filters were increased based on digression from the null model. Variants were filtered based on sequencing quality or excessive heterozygosity. Covariates to adjust for subject ascertainment and/or differing sequencing technologies across sub-studies were added where appropriate. Phenotype-specific outliers were removed where appropriate. Following all sub-study level quality control, a 25-group fixed-effect inverse-variance weighted meta-analysis was then conducted using METAL.