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SHR Neuro Krebs Kardio Lipid Stoffw Microb

Hofer, P; Hagmann, M; Brezina, S; Dolejsi, E; Mach, K; Leeb, G; Baierl, A; Buch, S; Sutterlüty-Fall, H; Karner-Hanusch, J; Bergmann, MM; Bachleitner-Hofmann, T; Stift, A; Gerger, A; Rötzer, K; Karner, J; Stättner, S; Waldenberger, M; Meitinger, T; Strauch, K; Linseisen, J; Gieger, C; Frommlet, F; Gsur, A.
Bayesian and frequentist analysis of an Austrian genome-wide association study of colorectal cancer and advanced adenomas.
Oncotarget. 2017; 8(58):98623-98634 Doi: 10.18632/oncotarget.21697 [OPEN ACCESS]
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Co-Autor*innen der Med Uni Graz
Gerger Armin

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Most genome-wide association studies (GWAS) were analyzed using single marker tests in combination with stringent correction procedures for multiple testing. Thus, a substantial proportion of associated single nucleotide polymorphisms (SNPs) remained undetected and may account for missing heritability in complex traits. Model selection procedures present a powerful alternative to identify associated SNPs in high-dimensional settings. In this GWAS including 1060 colorectal cancer cases, 689 cases of advanced colorectal adenomas and 4367 controls we pursued a dual approach to investigate genome-wide associations with disease risk applying both, single marker analysis and model selection based on the modified Bayesian information criterion, mBIC2, implemented in the software package MOSGWA. For different case-control comparisons, we report models including between 1-14 candidate SNPs. A genome-wide significant association of rs17659990 (P=5.43×10-9, DOCK3, chromosome 3p21.2) with colorectal cancer risk was observed. Furthermore, 56 SNPs known to influence susceptibility to colorectal cancer and advanced adenoma were tested in a hypothesis-driven approach and several of them were found to be relevant in our Austrian cohort. After correction for multiple testing (α=8.9×10-4), the most significant associations were observed for SNPs rs10505477 (P=6.08×10-4) and rs6983267 (P=7.35×10-4) of CASC8, rs3802842 (P=8.98×10-5, COLCA1,2), and rs12953717 (P=4.64×10-4, SMAD7). All previously unreported SNPs demand replication in additional samples. Reanalysis of existing GWAS datasets using model selection as tool to detect SNPs associated with a complex trait may present a promising resource to identify further genetic risk variants not only for colorectal cancer.

Find related publications in this database (Keywords)
advanced colorectal adenomas
colorectal cancer
model selection
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