Kenneth S Kendler1,2, Charles O Gardner1,2, Michael C Neale1,2, Steve Aggen1,2, Andrew Heath3, Lucía Colodro-Conde4, Baptiste Couvyduchesne4,5,6, Enda M Byrne4,6, Nicholas G Martin4,7, Nathan A Gillespie1,2,4. 1. Virginia Institute for Psychiatric and Behavioral Genetics, Richmond, VA, USA. 2. Department of Psychiatry, Virginia Commonwealth University School of Medicine, Richmond, VA, USA. 3. Department of Psychiatry, Washington University in St Louis, St Louis MO, USA. 4. Genetic Epidemiology, QIMR Berghofer Medical Research Institute, Brisbane, Queensland, Australia. 5. Queensland Brain Institute, The University of Queensland, Brisbane, Queensland, Australia. 6. Institute for Molecular Bioscience, The University of Queensland, Brisbane, Queensland, Australia. 7. School of Psychology, University of Queensland, Brisbane, Queensland, Australia.
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.
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.
Entities:
Keywords:
Depressive symptoms; diagnosis; major depression; neuroticism; twin modeling
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