Comparing methods for performing trans-ethnic meta-analysis of genome-wide association studies

被引:52
作者
Wang, Xu [1 ]
Chua, Hui-Xiang [2 ]
Chen, Peng [1 ]
Ong, Rick Twee-Hee [1 ]
Sim, Xueling [6 ]
Zhang, Weihua [7 ]
Takeuchi, Fumihiko [8 ]
Liu, Xuanyao [1 ,3 ]
Khor, Chiea-Chuen [9 ]
Tay, Wan-Ting [10 ]
Cheng, Ching-Yu [1 ,4 ,10 ,11 ]
Suo, Chen [1 ]
Liu, Jianjun [9 ]
Aung, Tin [4 ,10 ]
Chia, Kee-Seng [1 ]
Kooner, Jaspal S. [7 ]
Chambers, John C. [7 ]
Wong, Tien-Yin [4 ,10 ,11 ]
Tai, E-Shyong [1 ]
Kato, Norihiro [8 ]
Teo, Yik-Ying [1 ,2 ,3 ,5 ,9 ]
机构
[1] Natl Univ Singapore, Saw Swee Hock Sch Publ Hlth, Singapore 117546, Singapore
[2] Natl Univ Singapore, Dept Stat & Appl Probabil, Singapore 117546, Singapore
[3] Natl Univ Singapore, NUS Grad Sch Integrat Sci & Engn, Singapore 117546, Singapore
[4] Natl Univ Singapore, Dept Ophthalmol, Singapore 117546, Singapore
[5] Natl Univ Singapore, Inst Life Sci, Singapore 117546, Singapore
[6] Univ Michigan, Dept Biostat, Ann Arbor, MI 48109 USA
[7] Univ London Imperial Coll Sci Technol & Med, Fac Med, London, England
[8] Natl Ctr Global Hlth & Med, Dept Gene Diagnost & Therapeut, Tokyo, Japan
[9] Agcy Sci Technol & Res, Genome Inst Singapore, Singapore, Singapore
[10] Singapore Natl Eye Ctr, Singapore Eye Res Inst, Singapore, Singapore
[11] Duke NUS Grad Med Sch, Singapore, Singapore
基金
新加坡国家研究基金会; 英国医学研究理事会;
关键词
DIABETES SUSCEPTIBILITY LOCI; BLOOD-PRESSURE; VARIANTS; CHALLENGES; GENOTYPES; GLUCOSE; MAP;
D O I
10.1093/hmg/ddt064
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Genome-wide association studies (GWASs) have discovered thousands of variants that are associated with human health and disease. Whilst early GWASs have primarily focused on genetically homogeneous populations of European, East Asian and South Asian ancestries, the next-generation genome-wide surveys are starting to pool studies from ethnically diverse populations within a single meta-analysis. However, classical epidemiological strategies for meta-analyses that assume fixed- or random-effects may not be the most suitable approaches to combine GWAS findings as these either confer low statistical power or identify mostly loci where the variants carry homogeneous effect sizes that are present in most of the studies. In a trans-ethnic meta-analysis, it is likely that some genetic loci will exhibit heterogeneous effect sizes across the populations. This may be due to differences in study designs, differences arising from the interactions with other genetic variants, or genuine biological differences attributed to environmental, dietary or lifestyle factors that modulate the influence of the genes. Here we compare different strategies for meta-analyzing GWAS across genetically diverse populations, where we intentionally vary the effect sizes present across the different populations. We subsequently applied the methods that yielded the highest statistical power to a trans-ethnic meta-analysis of seven GWAS in type 2 diabetes, and showed that these methods identified bona fide associations that would otherwise have been missed by the classical strategies.
引用
收藏
页码:2303 / 2311
页数:9
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