K J Mitchell1, D J Porteous. 1. Smurfit Institute of Genetics, Trinity College Dublin, Ireland. Kevin.Mitchell@tcd.ie
Abstract
BACKGROUND: For many years, the prevailing paradigm has stated that in each individual with schizophrenia (SZ) the genetic risk is due to a combination of many genetic variants, individually of small effect. Recent empirical data are prompting a re-evaluation of this polygenic, common disease-common variant (CDCV) model. Evidence includes a lack of the expected strong positive findings from genome-wide association studies and the concurrent discovery of many different mutations that individually strongly predispose to SZ and other psychiatric disorders. This has led some to adopt a mixed model wherein some cases are caused by polygenic mechanisms and some by single mutations. This model runs counter to a substantial body of theoretical literature that had supposedly conclusively rejected Mendelian inheritance with genetic heterogeneity. Here we ask how this discrepancy between theory and data arose and propose a rationalization of the recent evidence base. METHOD: In light of recent empirical findings, we reconsider the methods and conclusions of early theoretical analyses and the explicit assumptions underlying them. RESULTS: We show that many of these assumptions can now be seen to be false and that the model of genetic heterogeneity is consistent with observed familial recurrence risks, endophenotype studies and other population-wide parameters. CONCLUSIONS: We argue for a more biologically consilient mixed model that involves interactions between disease-causing and disease-modifying variants in each individual. We consider the implications of this model for moving SZ research beyond statistical associations to pathogenic mechanisms.
BACKGROUND: For many years, the prevailing paradigm has stated that in each individual with schizophrenia (SZ) the genetic risk is due to a combination of many genetic variants, individually of small effect. Recent empirical data are prompting a re-evaluation of this polygenic, common disease-common variant (CDCV) model. Evidence includes a lack of the expected strong positive findings from genome-wide association studies and the concurrent discovery of many different mutations that individually strongly predispose to SZ and other psychiatric disorders. This has led some to adopt a mixed model wherein some cases are caused by polygenic mechanisms and some by single mutations. This model runs counter to a substantial body of theoretical literature that had supposedly conclusively rejected Mendelian inheritance with genetic heterogeneity. Here we ask how this discrepancy between theory and data arose and propose a rationalization of the recent evidence base. METHOD: In light of recent empirical findings, we reconsider the methods and conclusions of early theoretical analyses and the explicit assumptions underlying them. RESULTS: We show that many of these assumptions can now be seen to be false and that the model of genetic heterogeneity is consistent with observed familial recurrence risks, endophenotype studies and other population-wide parameters. CONCLUSIONS: We argue for a more biologically consilient mixed model that involves interactions between disease-causing and disease-modifying variants in each individual. We consider the implications of this model for moving SZ research beyond statistical associations to pathogenic mechanisms.
Authors: Gholson J Lyon; Tao Jiang; Richard Van Wijk; Wei Wang; Paul Mark Bodily; Jinchuan Xing; Lifeng Tian; Reid J Robison; Mark Clement; Yang Lin; Peng Zhang; Ying Liu; Barry Moore; Joseph T Glessner; Josephine Elia; Fred Reimherr; Wouter W van Solinge; Mark Yandell; Hakon Hakonarson; Jun Wang; William Evan Johnson; Zhi Wei; Kai Wang Journal: Discov Med Date: 2011-07 Impact factor: 2.970
Authors: Ronald A Yeo; Steven W Gangestad; Jingyu Liu; Stefan Ehrlich; Robert J Thoma; Jessica Pommy; Andrew R Mayer; S Charles Schulz; Thomas H Wassink; Eric M Morrow; Juan R Bustillo; Scott R Sponheim; Beng-Choon Ho; Vince D Calhoun Journal: Biol Psychiatry Date: 2012-12-11 Impact factor: 13.382