期刊
BMC MEDICAL GENETICS
卷 10, 期 -, 页码 -出版社
BMC
DOI: 10.1186/1471-2350-10-86
关键词
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资金
- National Institute of Health (NIH) [R01 GM069940]
- Overseas-Returned Scholars Foundation of Department of Education of Heilongjiang Province [1152HZ01]
- National Institute on Aging [Z01 AG000949-02]
Background: Amyotrophic lateral sclerosis (ALS) is a fatal, degenerative neuromuscular disease characterized by a progressive loss of voluntary motor activity. About 95% of ALS patients are in sporadic form-meaning their disease is not associated with a family history of the disease. To date, the genetic factors of the sporadic form of ALS are poorly understood. Methods: We proposed a two-stage approach based on seventeen biological plausible models to search for two-locus combinations that have significant joint effects to the disease in a genome-wide association study (GWAS). We used a two-stage strategy to reduce the computational burden associated with performing an exhaustive two-locus search across the genome. In the first stage, all SNPs were screened using a single-marker test. In the second stage, all pairs made from the 1000 SNPs with the lowest p-values from the first stage were evaluated under each of the 17 two-locus models. Results: we performed the two-stage approach on a GWAS data set of sporadic ALS from the SNP Database at the NINDS Human Genetics Resource Center DNA and Cell Line Repository http://ccr.coriell.org/ninds/. Our two-locus analysis showed that two two-locus combinations--rs4363506 (SNP1) and rs3733242 (SNP2), and rs4363506 and rs16984239 (SNP3) -- were significantly associated with sporadic ALS. After adjusting for multiple tests and multiple models, the combination of SNP1 and SNP2 had a p-value of 0.032 under the Dom boolean AND Dom epistatic model; SNP1 and SNP3 had a p-value of 0.042 under the Dom x Dom multiplicative model. Conclusion: The proposed two-stage analytical method can be used to search for joint effects of genes in GWAS. The two-stage strategy decreased the computational time and the multiple testing burdens associated with GWAS. We have also observed that the loci identified by our two-stage strategy can not be detected by single-locus tests.
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