Background: Conventional meta-analysis based on genetic markers may be less powerful for heterogeneous samples. In this study, we introduced a new meta-analysis for 4 genomewide association studies on alcohol dependence that integrated the information of putative causal variants.
Methods: A total of 12,481 subjects in 4 independent cohorts were analyzed, including 1 European American cohort (1,409 cases with alcohol dependence and 1,518 controls), 1 European Australian cohort (a total of 6,438 family subjects with 1,645 probands), 1 African American cohort from SAGE + COGA (681 cases and 508 controls), and 1 African American cohort from Yale (1,429 cases and 498 controls). The genomewide association analysis was conducted for each cohort, and then, a new meta-analysis was performed to derive the combined p-values. cis-Acting expression of quantitative locus (cis-eQTL) analysis of each risk variant in human tissues and RNA expression analysis of each risk gene in rat brain served as functional validation.
Results: In meta-analysis of European American and European Australian cohorts, we found 10 top-ranked single nucleotide polymorphisms (SNPs) (p < 10(-6) ) that were associated with alcohol dependence. They included 6 at SERINC2 (3.1 × 10(-8) ≤ p ≤ 9.6 × 10(-8) ), 1 at STK40 (p = 1.3 × 10(-7) ), 2 at KIAA0040 (3.3 × 10(-7) ≤ p ≤ 5.2 × 10(-7) ), and 1 at IPO11 (p = 6.9 × 10(-7) ). In meta-analysis of 2 African American cohorts, we found 2 top-ranked SNPs including 1 at SLC6A11 (p = 2.7 × 10(-7) ) and 1 at CBLN2 (p = 7.4 × 10(-7) ). In meta-analysis of all 4 cohorts, we found 2 top-ranked SNPs in PTP4A1-PHF3 locus (6.0 × 10(-7) ≤ p ≤ 7.2 × 10(-7) ). In an African American cohort only, we found 1 top-ranked SNP at PLD1 (p = 8.3 × 10(-7) ; OR = 1.56). Many risk SNPs had positive cis-eQTL signals, and all these risk genes except KIAA0040 were found to express in both rat and mouse brains.
Conclusions: We found multiple genes that were significantly or suggestively associated with alcohol dependence. They are among the most appropriate for follow-up as contributors to risk for alcohol dependence.
Keywords: Alcohol Dependence; Genomewide Association; Meta-Analysis.
Copyright © 2015 by the Research Society on Alcoholism.