Using Dimensional Models of Externalizing Psychopathology to Aid in Gene Identification

Abstract

Twin studies provide compelling evidence that alcohol and drug dependence, childhood conduct disorder, adult antisocial behavior, and disinhibitory personality traits share an underlying genetic liability that contributes to a spectrum of externalizing behaviors. However, this information has not been widely used in gene identification efforts, which have focused on specific disorders diagnosed using traditional psychiatric classification systems. To test the utility of using a multivariate externalizing phenotype in (1) linkage analyses and (2) association analyses to identify genes that contribute broadly to a spectrum of externalizing disorders. Data were analyzed from the Collaborative Study on the Genetics of Alcoholism. Linkage analyses were conducted using data from a genome-wide 10-cM microsatellite scan. Association analyses were conducted on 27 single-nucleotide polymorphisms genotyped across a candidate gene, the muscarinic acetylcholine receptor M2 gene (CHRM2). Six centers across the United States. Approximately 2300 individuals from 262 families. Lifetime symptom counts of alcohol dependence, illicit drug dependence, childhood conduct disorder, and adult antisocial personality disorder and novelty seeking, sensation seeking, and general externalizing component scores consisting of a composite of the previous 6 variables. Principal component analyses indicated that the 6 individual variables loaded on a single externalizing factor. Linkage analyses using the resultant component scores identified a region on chromosome 7 consistent with a gene that broadly predisposes individuals to externalizing behavior. Association analyses of a candidate gene, CHRM2, previously of interest in the Collaborative Study on the Genetics of Alcoholism, suggest that it is involved in a general externalizing phenotype. Broader conceptualizations of psychiatric disorders, such as studying a spectrum of externalizing psychopathology, may aid in identifying susceptibility genes and understanding the pathways through which genetic factors affect vulnerability for a variety of poor outcomes.