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Shared and specific genetic risk factors for lifetime major depression, depressive symptoms and neuroticism in three population-based twin samples

Published online by Cambridge University Press:  19 December 2018

Kenneth S. Kendler*
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
Charles O. Gardner
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
Michael C. Neale
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
Steve Aggen
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
Andrew Heath
Affiliation:
Department of Psychiatry, Washington University in St Louis, St Louis MO, USA
Lucía Colodro-Conde
Affiliation:
Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
Baptiste Couvyduchesne
Affiliation:
Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
Enda M. Byrne
Affiliation:
Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia
Nicholas G. Martin
Affiliation:
Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia School of Psychology, University of Queensland, Brisbane, Queensland, Australia
Nathan A. Gillespie
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, VA, USA Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia
*
Author for correspondence: Kenneth S. Kendler, E-mail: Kenneth.Kendler@vcuhealth.org

Abstract

Background

Vulnerability to depression can be measured in different ways. We here examine how genetic risk factors are inter-related for lifetime major depression (MD), self-report current depressive symptoms and the personality trait Neuroticism.

Method

We obtained data from three population-based adult twin samples (Virginia n = 4672, Australia #1 n = 3598 and Australia #2 n = 1878) to which we fitted a common factor model where risk for ‘broadly defined depression’ was indexed by (i) lifetime MD assessed at personal interview, (ii) depressive symptoms, and (iii) neuroticism. We examined the proportion of genetic risk for MD deriving from the common factor v. specific to MD in each sample and then analyzed them jointly. Structural equation modeling was conducted in Mx.

Results

The best fit models in all samples included additive genetic and unique environmental effects. The proportion of genetic effects unique to lifetime MD and not shared with the broad depression common factor in the three samples were estimated as 77, 61, and 65%, respectively. A cross-sample mega-analysis model fit well and estimated that 65% of the genetic risk for MD was unique.

Conclusion

A large proportion of genetic risk factors for lifetime MD was not, in the samples studied, captured by a common factor for broadly defined depression utilizing MD and self-report measures of current depressive symptoms and Neuroticism. The genetic substrate for MD may reflect neurobiological processes underlying the episodic nature of its cognitive, motor and neurovegetative manifestations, which are not well indexed by current depressive symptom and neuroticism.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2018 

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