FUSION exome chip analysis

Dataset

Note that the samples in the GoT2D exome chip analysis and FUSION exome chip analysis datasets are a subset of those included in the ExTexT2D exome chip analysis dataset.

Dataset phenotypes

Phase 1 analysis:

type 2 diabetes
type 2 diabetes adjusted for BMI
fasting glucose
fasting glucose adjusted for BMI
fasting insulin
fasting insulin adjusted for BMI

Phase 2 analysis:

diastolic blood pressure
urinary creatinine
LDL cholesterol
HDL cholesterol
BMI
systolic blood pressure

Dataset subjects

Cases	Controls	Cohort	Ancestry
1,796	1,689	Finland-United States Investigation of NIDDM Genetics Study (FUSION)	European

Project

The FUSION (Finland-United States Investigation of NIDDM Genetics) Study seeks to to map and identify genetic variants that predispose to type 2 diabetes mellitus (T2D) or are responsible for variability in diabetes-related quantitative traits.

Acknowledgments

This study was funded by NIH grants R01-DK062370 and R01-DK072193; intramural project number 1Z01-HG000024; and FNIH grant BOEH15AMP2.

Experiment summary

The FUSION (Finland–United States Investigation of Non–Insulin-Dependent Diabetes Mellitus Genetics) study is a long-term effort to identify genetic variants affecting risk of type 2 diabetes (T2D) or impacting T2D-related quantitative traits. This case-control study initially involved linkage analysis of affected-sibling-pair families based on over 5,000 individuals living in Finland; additional T2D cases and controls were subsequently included.

Individual-level genotype data from 4,233 unique samples, generated on four different arrays, was received by the Analysis Team at the Accelerating Medicines Partnership Data Coordinating Center (AMP-DCC) and subjected to quality control. Since the samples analyzed with the CIDR exome chip consisted of related pairs, they were removed from further analysis. Association analysis was then performed for the three remaining arrays: the Broad exome chip (resulting dataset termed "FUSION exome chip analysis" in the T2DKP); the HumanHap300 chip (resulting dataset termed "FUSION GWAS" in the T2DKP); and the Metabochip (resulting dataset termed "FUSION Metabochip" in the T2DKP).

Data were analyzed by the Analysis Team at the Accelerating Medicines Partnership Data Coordinating Center (AMP-DCC), Broad Institute, using Loamstream software and the AMP-DCC Data Analysis Pipeline. Results are summarized below; see the Quality Control and Analysis Reports (links below) for full details.

Overview of analysis and results

T2D associations were calculated in two models, BMI-unadjusted and BMI-adjusted. In both models, the top association was the variant rs7903146, in the region of the well-known T2D risk gene TCF7L2, with p-values of 2.08 × 10⁻⁸ and 1.48 × 10⁻⁹ in the BMI-unadjusted and BMI-adjusted models, respectively. In both models, this association was one of 2 previously identified associations among the top 20.

No fasting glucose or fasting insulin associations reached genome-wide significance in either the BMI-unadjusted or BMI-adjusted models, and none of the top 20 associations for either phenotype or model had been identified previously.

No associations with diastolic blood pressure, systolic blood pressure, urinary creatinine, or BMI reached genome-wide significance, and none of the top 20 associations had been identified previously.

Two LDL cholesterol associations reached genome-wide significance: rs7412 in the region of the APOE gene and rs11591147 in the region of the PCSK9 gene, with p-values of 1.45 × 10⁻¹⁰ and 6.5 × 10⁻¹⁰, respectively. Both of these associations were previously known, as were an additional 4 associations within the top 20.

Two HDL cholesterol associations reached genome-wide significance: rs247616 in the region of the CETP gene and rs9989419 in the region of the HERPUD1 gene, with p-values of 5.22 × 10⁻²¹ and 1.63 × 10⁻⁹, respectively. Both of these associations were previously known, as were an additional 2 associations within the top 20.