SNP by SNP by environment interaction network of alcoholism

Amin Zollanvari, Gil Alterovitz

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Background: Alcoholism has a strong genetic component. Twin studies have demonstrated the heritability of a large proportion of phenotypic variance of alcoholism ranging from 50-80%. The search for genetic variants associated with this complex behavior has epitomized sequence-based studies for nearly a decade. The limited success of genome-wide association studies (GWAS), possibly precipitated by the polygenic nature of complex traits and behaviors, however, has demonstrated the need for novel, multivariate models capable of quantitatively capturing interactions between a host of genetic variants and their association with non-genetic factors. In this regard, capturing the network of SNP by SNP or SNP by environment interactions has recently gained much interest. Results: Here, we assessed 3,776 individuals to construct a network capable of detecting and quantifying the interactions within and between plausible genetic and environmental factors of alcoholism. In this regard, we propose the use of first-order dependence tree of maximum weight as a potential statistical learning technique to delineate the pattern of dependencies underpinning such a complex trait. Using a predictive based analysis, we further rank the genes, demographic factors, biological pathways, and the interactions represented by our SNP×$$ \times $$ SNP ×$$ \times $$ E network. The proposed framework is quite general and can be potentially applied to the study of other complex traits.

Original languageEnglish
Article number19
JournalBMC Systems Biology
Volume11
DOIs
Publication statusPublished - Mar 14 2017

Keywords

  • Alcoholism
  • Environment
  • GWAS
  • Interaction
  • Network
  • SNP

ASJC Scopus subject areas

  • Structural Biology
  • Modelling and Simulation
  • Molecular Biology
  • Computer Science Applications
  • Applied Mathematics

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