Publications
Cohort Profile: The Singapore Multi-Ethnic Cohort (MEC) study.
Tan KHX, et al.
Int J Epidemiol. 2018 Feb 13. doi: 10.1093/ije/dyy014
Patterns of physical activity and sedentary behavior in a representative sample of a multi-ethnic South-East Asian population: a cross-sectional study.
Win AM, et al.
BMC Public Health. 2015 Apr 1;15:318. doi: 10.1186/s12889-015-1668-7
Transferability of type 2 diabetes implicated loci in multi-ethnic cohorts from Southeast Asia.
Sim X, et al.
PLoS Genet. 2011 Apr;7(4):e1001363. doi: 10.1371/journal.pgen.1001363
Dataset phenotypes
Phase 1 analysis:
- fasting glucose
- fasting glucose adjusted for BMI
Dataset subjects
| Subjects | Cohort | Ancestry |
|---|---|---|
| 895 | Singapore Prospective Study Program (SP2), Illumina Human 1M-Duo v3 whole genome SNP genotyping chip | East Asian |
| 976 | Singapore Prospective Study Program (SP2), Illumina Human610-Quad v1.0 DNA Analysis BeadChip | East Asian |
| 697 | Singapore Living Biobank | East Asian (Malay) |
| 947 | Singapore Living Biobank | East Asian (Chinese) |
Project
The Singapore Prospective Study Program (SP2) is a population-based cohort study designed to examine the pathogenesis of cardiovascular and metabolic diseases such as hypertension, dyslipidemia, obesity, and T2D in Singapore. SP2 includes 6,968 participants from one of four previous cross-sectional studies: Thyroid and Heart Study 1982–1984, National Health Survey 1992, National University of Singapore Heart Study 1993–1995 or National Health Survey 1998. Non-diabetic controls were selected from SP2.
Living Biobank is a collection of population-based Chinese and Malay individuals from two multi-ethnic cohorts from Singapore Public Health Studies: Multi Ethnic Cohort (MEC) and the Singapore Health 2012 (SH2012) that aims to investigate the genetic and lifestyle factors that affect the risk of developing chronic diseases such as T2D, cardiovascular outcomes, and cancer in Singapore citizens and permanent residents. The SPHS Living Biobank is a joint collaboration with the pharmaceutical company Merck, which is also one of the industry members of the AMP T2D partnership. The primary aim is to build a catalogue of low frequency and rare coding variants in East Asians, with consent for genotype-phenotype follow-up physiological experiments that would inform and prioritise plausible drug targets. All Living Biobank samples have no prior medical history of diabetes.
Acknowledgments
This study was funded through grants from the Biomedical Research Council of Singapore (BMRC) and the National Medical Research Council of Singapore (NMRC). Genome Institute of Singapore provided services for genotyping.
Experiment summary
Meta-analysis of fasting glucose associations was performed on the cohorts listed above using both BMI-unadjusted and BMI-adjusted models.
Overview of analysis and results
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. After sample quality control (see the Quality Control report, linked below), results from the cohorts listed above were combined in meta-analysis. Results are summarized below; see the Analysis Reports (links below) for full details.
In the BMI-unadjusted model, two associations reached genome-wide significance: rs3732033 in the region of the G6P62 gene with a p-value of 1.47 × 10−10, and rs1522018 in the region of the SPC25 gene with a p-value of 2.37 × 10−9.
In the BMI-adjusted model, two associations reached genome-wide significance: rs12623237 in the region of the G6P62 gene with a p-value of 2.37 × 10−10, and rs1522018 in the region of the SPC25 gene with a p-value of 3.43 × 10−9.
Detailed reports
Genotype Data Quality Control Report (download PDF)
AMP-DCC Phase 1 Data Analysis Report (download PDF)