期刊
CLINICAL & TRANSLATIONAL IMMUNOLOGY
卷 6, 期 -, 页码 -出版社
WILEY
DOI: 10.1038/cti.2017.54
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资金
- Equity Trustees (Australia) [QPhD2015025]
- Fundacao para a Ciencia e Tecnologia (Portugal) [SFRH/BD/92907/2013]
- National Health and Medical Research Council (Australia) [APP1124501]
- Medical Research Council [MC_qA137853, MC_PC_12028] Funding Source: researchfish
- Fundação para a Ciência e a Tecnologia [SFRH/BD/92907/2013] Funding Source: FCT
- MRC [MC_PC_12028] Funding Source: UKRI
Twenty-five genome-wide association studies (GWAS) of asthma were published between 2007 and 2016, the largest with a sample size of 157242 individuals. Across these studies, 39 genetic variants in low linkage disequilibrium (LD) with each other were reported to associate with disease risk at a significance threshold of P<5x10(-8), including 31 in populations of European ancestry. Results from analyses of the UK Biobank data (n=380 503) indicate that at least 28 of the 31 associations reported in Europeans represent true-positive findings, collectively explaining 2.5% of the variation in disease liability (median of 0.06% per variant). We identified 49 transcripts as likely target genes of the published asthma risk variants, mostly based on LD with expression quantitative trait loci (eQTL). Of these genes, 16 were previously implicated in disease pathophysiology by functional studies, including TSLP, TNFSF4, ADORA1, CHIT1 and USF1. In contrast, at present, there is limited or no functional evidence directly implicating the remaining 33 likely target genes in asthma pathophysiology. Some of these genes have a known function that is relevant to allergic disease, including F11R, CD247, PGAP3, AAGAB, CAMK4 and PEX14, and so could be prioritized for functional follow-up. We conclude by highlighting three areas of research that are essential to help translate GWAS findings into clinical research or practice, namely validation of target gene predictions, understanding target gene function and their role in disease pathophysiology and genomics-guided prioritization of targets for drug development.
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