Multi-species data integration and gene ranking enrich significant results in an alcoholism genome-wide association study

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• 作者：Zhongming Zhao (1) (2) (3)
  An-Yuan Guo (1) (4)
  Edwin JCG van den Oord (5)
  Fazil Aliev (6)
  Peilin Jia (1)
  Howard J Edenberg (7)
  Brien P Riley (6) (8)
  Danielle M Dick (6) (8)
  Jill C Bettinger (9)
  Andrew G Davies (9)
  Michael S Grotewiel (8)
  Marc A Schuckit (10)
  Arpana Agrawal (11)
  John Kramer (12)
  John I Nurnberger Jr (13)
  Kenneth S Kendler (6) (8)
  Bradley T Webb (5)
  Michael F Miles (6) (9)
  
• 刊名：BMC Genomics
• 出版年：2012
• 出版时间：December 2012
• 年：2012
• 卷：13
• 期：8-supp
• 全文大小：556KB
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• 作者单位：Zhongming Zhao (1) (2) (3)
  An-Yuan Guo (1) (4)
  Edwin JCG van den Oord (5)
  Fazil Aliev (6)
  Peilin Jia (1)
  Howard J Edenberg (7)
  Brien P Riley (6) (8)
  Danielle M Dick (6) (8)
  Jill C Bettinger (9)
  Andrew G Davies (9)
  Michael S Grotewiel (8)
  Marc A Schuckit (10)
  Arpana Agrawal (11)
  John Kramer (12)
  John I Nurnberger Jr (13)
  Kenneth S Kendler (6) (8)
  Bradley T Webb (5)
  Michael F Miles (6) (9)
  
  1. Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA
  2. Department of Psychiatry, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA
  3. Department of Cancer Biology, Vanderbilt University School of Medicine, Nashville, TN, 37232, USA
  4. Key Laboratory of Molecular Biophysics of the Ministry of Education, College of Life Science and Technology, Huazhong University of Science and Technology, Wuhan, 430074, China
  5. Center for Biomarker Research and Personalized Medicine, School of Pharmacy, Medical College of Virginia, Virginia Commonwealth University, Richmond, VA, 23298, USA
  6. Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, 23298, USA
  7. Department of Biochemistry and Molecular Biology, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
  8. Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, 23298, USA
  9. Department of Pharmacology and Toxicology, Virginia Commonwealth University, Richmond, VA, 23298, USA
  10. Department of Psychiatry, University of California, San Diego, La Jolla, CA, 92093, USA
  11. Department of Psychiatry, Washington University School of Medicine, Saint Louis, MO, 63110, USA
  12. Department of Psychiatry, University of Iowa College of Medicine, Iowa City, IA, 52242, USA
  13. Institute of Psychiatric Research, Department of Psychiatry, Indiana University School of Medicine, Indianapolis, IN, 46202, USA
  

文摘

Background A variety of species and experimental designs have been used to study genetic influences on alcohol dependence, ethanol response, and related traits. Integration of these heterogeneous data can be used to produce a ranked target gene list for additional investigation. Results In this study, we performed a unique multi-species evidence-based data integration using three microarray experiments in mice or humans that generated an initial alcohol dependence (AD) related genes list, human linkage and association results, and gene sets implicated in C. elegans and Drosophila. We then used permutation and false discovery rate (FDR) analyses on the genome-wide association studies (GWAS) dataset from the Collaborative Study on the Genetics of Alcoholism (COGA) to evaluate the ranking results and weighting matrices. We found one weighting score matrix could increase FDR based q-values for a list of 47 genes with a score greater than 2. Our follow up functional enrichment tests revealed these genes were primarily involved in brain responses to ethanol and neural adaptations occurring with alcoholism. Conclusions These results, along with our experimental validation of specific genes in mice, C. elegans and Drosophila, suggest that a cross-species evidence-based approach is useful to identify candidate genes contributing to alcoholism.