title: A genetic network model of cellular responses to lithium treatment and cocaine abuse in bipolar disorder.
abstract: BACKGROUND
  Lithium is an effective treatment for Bipolar Disorder (BD) and significantly reduces suicide risk, though the molecular basis of lithium's effectiveness is not well understood. We seek to improve our understanding of this effectiveness by posing hypotheses based on new experimental data as well as published data, testing these hypotheses in silico, and posing new hypotheses for validation in future studies. We initially hypothesized a gene-by-environment interaction where lithium, acting as an environmental influence, impacts signal transduction pathways leading to differential expression of genes important in the etiology of BD mania.
  
  
  RESULTS
  Using microarray and rt-QPCR assays, we identified candidate genes that are differentially expressed with lithium treatment. We used a systems biology approach to identify interactions among these candidate genes and develop a network of genes that interact with the differentially expressed candidates. Notably, we also identified cocaine as having a potential influence on the network, consistent with the observed high rate of comorbidity for BD and cocaine abuse. The resulting network represents a novel hypothesis on how multiple genetic influences on bipolar disorder are impacted by both lithium treatment and cocaine use. Testing this network for association with BD and related phenotypes, we find that it is significantly over-represented for genes that participate in signal transduction, consistent with our hypothesized-gene-by environment interaction. In addition, it models related pharmacogenomic, psychiatric, and chemical dependence phenotypes.
  
  
  CONCLUSIONS
  We offer a network model of gene-by-environment interaction associated with lithium's effectiveness in treating BD mania, as well as the observed high rate of comorbidity of BD and cocaine abuse. We identified drug targets within this network that represent immediate candidates for therapeutic drug testing. Posing novel hypotheses for validation in future work, we prioritized SNPs near genes in the network based on functional annotation. We also developed a "concept signature" for the genes in the network and identified additional candidate genes that may influence the system because they are significantly associated with the signature.
authors.affiliation: Department of Psychiatry, University of Michigan, Ann Arbor, USA. mceachin@umich.edu
authors.forename: Richard C
authors.initials: RC
authors.lastname: McEachin
authors.forename: Haiming
authors.initials: H
authors.lastname: Chen
authors.forename: Maureen A
authors.initials: MA
authors.lastname: Sartor
authors.forename: Scott F
authors.initials: SF
authors.lastname: Saccone
authors.forename: Benjamin J
authors.initials: BJ
authors.lastname: Keller
authors.forename: Alan R
authors.initials: AR
authors.lastname: Prossin
authors.forename: James D
authors.initials: JD
authors.lastname: Cavalcoli
authors.forename: Melvin G
authors.initials: MG
authors.lastname: McInnis
mesh_terms: D000328:Adult; D001714:Bipolar Disorder / Q000150:complications / Q000188:drug therapy* / Q000235:genetics* / Q000473:pathology; D001921:Brain / Q000187:drug effects / Q000378:metabolism; D002460:Cell Line; D019970:Cocaine-Related Disorders / Q000150:complications / Q000235:genetics*; D005260:Female; D020869:Gene Expression Profiling; D053263:Gene Regulatory Networks / Q000187:drug effects*; D006801:Humans; D008094:Lithium / Q000494:pharmacology* / Q000627:therapeutic use; D008297:Male; D008875:Middle Aged; D008957:Models, Genetic; D020411:Oligonucleotide Array Sequence Analysis; D020641:Polymorphism, Single Nucleotide / Q000187:drug effects / Q000235:genetics; D015203:Reproducibility of Results; D020133:Reverse Transcriptase Polymerase Chain Reaction; D015398:Signal Transduction / Q000187:drug effects / Q000235:genetics; D049490:Systems Biology; D016896:Treatment Outcome
chemical_list: D008094:Lithium