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The challenges of genome-wide interaction studies: lessons to learn from the analysis of HDL blood levels.
Wednesday,2015-03-04 14:17 America/Los_Angeles — zdrager
| Title | The challenges of genome-wide interaction studies: lessons to learn from the analysis of HDL blood levels. |
| Publication Type | Journal Article |
| Year of Publication | 2014 |
| Authors | van Leeuwen, EM, Smouter, FAS, Kam-Thong, T, Karbalai, N, Smith, AV, Harris, TB, Launer, LJ, Sitlani, CM, Li, G, Brody, JA, Bis, JC, White, CC, Jaiswal, A, Oostra, BA, Hofman, A, Rivadeneira, F, Uitterlinden, AG, Boerwinkle, E, Ballantyne, CM, Gudnason, V, Psaty, BM, Cupples, AL, Jarvelin, M-R, Ripatti, S, Isaacs, A, Müller-Myhsok, B, Karssen, LC, van Duijn, CM |
| Journal | PLoS One |
| Volume | 9 |
| Issue | 10 |
| Pagination | e109290 |
| Date Published | 2014 |
| ISSN | 1932-6203 |
| Keywords | Cholesterol, HDL, Female, Genome-Wide Association Study, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide |
| Abstract | <p>Genome-wide association studies (GWAS) have revealed 74 single nucleotide polymorphisms (SNPs) associated with high-density lipoprotein cholesterol (HDL) blood levels. This study is, to our knowledge, the first genome-wide interaction study (GWIS) to identify SNP×SNP interactions associated with HDL levels. We performed a GWIS in the Rotterdam Study (RS) cohort I (RS-I) using the GLIDE tool which leverages the massively parallel computing power of Graphics Processing Units (GPUs) to perform linear regression on all genome-wide pairs of SNPs. By performing a meta-analysis together with Rotterdam Study cohorts II and III (RS-II and RS-III), we were able to filter 181 interaction terms with a p-value<1 · 10-8 that replicated in the two independent cohorts. We were not able to replicate any of these interaction term in the AGES, ARIC, CHS, ERF, FHS and NFBC-66 cohorts (Ntotal = 30,011) when adjusting for multiple testing. Our GWIS resulted in the consistent finding of a possible interaction between rs774801 in ARMC8 (ENSG00000114098) and rs12442098 in SPATA8 (ENSG00000185594) being associated with HDL levels. However, p-values do not reach the preset Bonferroni correction of the p-values. Our study suggest that even for highly genetically determined traits such as HDL the sample sizes needed to detect SNP×SNP interactions are large and the 2-step filtering approaches do not yield a solution. Here we present our analysis plan and our reservations concerning GWIS.</p> |
| DOI | 10.1371/journal.pone.0109290 |
| Alternate Journal | PLoS ONE |
| PubMed ID | 25329471 |
| PubMed Central ID | PMC4203717 |
| Grant List | AG023629 / AG / NIA NIH HHS / United States DK063491 / DK / NIDDK NIH HHS / United States HHSN268200800007C / / PHS HHS / United States HHSN268201200036C / / PHS HHS / United States HL080295 / HL / NHLBI NIH HHS / United States HL087652 / HL / NHLBI NIH HHS / United States HL105756 / HL / NHLBI NIH HHS / United States N01HC55222 / HC / NHLBI NIH HHS / United States N01HC85079 / HC / NHLBI NIH HHS / United States N01HC85080 / HC / NHLBI NIH HHS / United States N01HC85081 / HC / NHLBI NIH HHS / United States N01HC85082 / HC / NHLBI NIH HHS / United States N01HC85083 / HC / NHLBI NIH HHS / United States N01HC85086 / HC / NHLBI NIH HHS / United States UL1 RR033176 / RR / NCRR NIH HHS / United States UL1RR033176 / RR / NCRR NIH HHS / United States UL1TR000124 / TR / NCATS NIH HHS / United States |