Lingjun Zuo1, Yunlong Tan2, Xiangyang Zhang3, Xiaoping Wang4, John Krystal1, Boris Tabakoff5, Chunlong Zhong6, Xingguang Luo1,2. 1. Department of Psychiatry, Yale University School of Medicine, New Haven, Connecticut. 2. Biological Psychiatry Research Center , Beijing Huilongguan Hospital, Beijing, China. 3. Menninger Department of Psychiatry and Behavioral Sciences , Baylor College of Medicine, Houston, Texas. 4. Department of Neurology , First People's Hospital, Shanghai Jiaotong University, Shanghai, China. 5. Department of Pharmacology , University of Colorado School of Medicine, Aurora, Colorado. 6. Department of Neurosurgery , Renji Hospital, Shanghai Jiaotong University, Shanghai, China.
Abstract
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.
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.
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