Hostname: page-component-586b7cd67f-2brh9 Total loading time: 0 Render date: 2024-11-20T17:24:07.476Z Has data issue: false hasContentIssue false

The genetic and environmental relationship between major depression and the five-factor model of personality

Published online by Cambridge University Press:  07 September 2009

K. S. Kendler*
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA Department of Human and Molecular Genetics, Virginia Commonwealth University, Richmond, VA, USA
J. Myers
Affiliation:
Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA Department of Psychiatry, Virginia Commonwealth University, Richmond, VA, USA
*
*Author for correspondence: K. S. Kendler, M.D., Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Box 980126, Richmond, VA 23298-0126, USA. (Email: [email protected])

Abstract

Background

Certain personality traits have long been suspected to reflect an enduring vulnerability to major depression (MD) in part because of shared genetic risk factors. Although many have agreed that normative personality is well captured by the ‘Big-Five’ personality traits of Openness (O), Conscientiousness (C), Extraversion (E), Agreeableness (A) and Neuroticism (N), to date genetically informative studies have only examined the relationship between MD and N and E.

Method

Questionnaires were completed on a website, yielding a sample of 44 112 subjects including both members of 542 same-sex twin pairs. Personality was measured by the Big Five Inventory. Structural modeling was performed by Mx.

Results

Three of the big-five personality traits – O, E and A – had small phenotypic associations with risk for MD and small genetic correlations. Two traits – N and C – had stronger phenotypic associations (positive for N and negative for C) with the following estimates of the genetic correlation with MD: +0.43 for N and −0.36 for C. N and C were moderately negatively correlated. Controlling for N reduced the genetic correlation between C and MD more than controlling for C reduced the genetic correlation between N and MD.

Conclusions

A large proportion of the genetic risk for MD that is expressed via personality is captured by N, with a modest amount due to C, and small amounts from O, E and A.

Type
Original Articles
Copyright
Copyright © Cambridge University Press 2009

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Akaike, H (1987). Factor analysis and AIC. Psychometrika 52, 317332.CrossRefGoogle Scholar
APA (1994). Diagnostic and Statistical Manual of Mental Disorders, 4th edn. American Psychiatric Association: Washington, DC.Google Scholar
Bagby, RM, Joffe, RT, Parker, J, Kalemba, V, Harkness, KL (1995). Major depression and the five-factor model of personality. Journal of Personality Disorders 9, 224234.CrossRefGoogle Scholar
Bouchard, TJ Jr. (1993). Genetic and environmental influences on adult personality: evaluating the evidence. In Foundations of Personality (ed. Hettema, J. and Deary, I. J.), pp. 1544. Kluwer Academic Publishers: Netherlands.Google Scholar
Digman, J (1990). Personality structure: emergence of the five-factor model. Annual Review of Psychology 41, 417440.Google Scholar
Enns, MW, Cox, BJ (1997). Personality dimensions and depression: review and commentary. Canadian Journal of Psychiatry 42, 274284.Google Scholar
Fanous, AH, Neale, MC, Aggen, SH, Kendler, KS (2007). A longitudinal study of personality and major depression in a population-based sample of male twins. Psychological Medicine 37, 11631172.Google Scholar
Fullerton, J, Cubin, M, Tiwari, H, Wang, C, Bomhra, A, Davidson, S, Miller, S, Fairburn, C, Goodwin, G, Neale, MC, Fiddy, S, Mott, R, Allison, DB, Flint, J (2003). Linkage analysis of extremely discordant and concordant sibling pairs identifies quantitative-trait loci that influence variation in the human personality trait neuroticism. American Journal of Human Genetics 72, 879890.Google Scholar
Garb, HN (2007). Computer-administered interviews and rating scales. Psychological Assessment 19, 4–13.CrossRefGoogle ScholarPubMed
Gosling, SD, Vazire, S, Srivastava, S, John, OP (2004). Should we trust web-based studies? A comparative analysis of six preconceptions about Internet questionnaires. American Psychologist 59, 93–104.Google Scholar
John, OP, Srivastava, S (1999). The big-five trait taxonomy: history, measurement, and theoretical perspectives. In Handbook of personality: Theory and Research, 2nd edn (ed. Pervin, L. A. and John, O. P.), pp. 102139. Guilford Press: New York.Google Scholar
Kendler, KS, Gatz, M, Gardner, C, Pedersen, N (2006 a). A Swedish national twin study of lifetime major depression. American Journal of Psychiatry 163, 109114.Google Scholar
Kendler, KS, Gatz, M, Gardner, C, Pedersen, NL (2006 b). Personality and major depression: a Swedish longitudinal, population-based twin study. Archives of General Psychiatry 63, 11131120.CrossRefGoogle ScholarPubMed
Kendler, KS, Myers, JM, Potter, J, Opalesky, J (2009). A web-based study of personality, psychopathology and substance use in twin, other relative and relationship pairs. Twin Research and Human Genetics 12, 137141.Google Scholar
Kendler, KS, Neale, MC, Kessler, RC, Heath, AC, Eaves, LJ (1993 a). A longitudinal twin study of personality and major depression in women. Archives of General Psychiatry 50, 853862.Google Scholar
Kendler, KS, Pedersen, N, Johnson, L, Neale, MC, Mathe, AA (1993 b). A pilot Swedish twin study of affective illness, including hospital- and population-ascertained subsamples. Archives of General Psychiatry 50, 699700.Google Scholar
Kendler, KS, Prescott, CA (2006). Genes, Environment, and Psychopathology: Understanding the Causes of Psychiatric and Substance Use Disorders. Guilford Press: New York.Google Scholar
Kissinger, P, Rice, J, Farley, T, Trim, S, Jewitt, K, Margavio, V, Martin, DH (1999). Application of computer-assisted interviews to sexual behavior research. American Journal of Epidemiology 149, 950954.CrossRefGoogle ScholarPubMed
Klein, MH, Kupfer, DJ, Shea, MT (1993). Personality and Depression: A Current View. Guilford Press: New York.Google Scholar
Kuo, PH, Neale, MC, Riley, BP, Patterson, DG, Walsh, D, Prescott, CA, Kendler, KS (2007). A genome-wide linkage analysis for the personality trait neuroticism in the Irish affected sib-pair study of alcohol dependence. American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics 144, 463468.CrossRefGoogle Scholar
Loehlin, JC (1992). Genes and Environment in Personality Development. Sage Publications: Newbury Park, CA.Google Scholar
Loehlin, JC, McCrae, RR, Costa, PT (1998). Heritabilities of common and measure-specific components of the big five personality factors. Journal of Research in Personality 32, 431453.Google Scholar
McCrae, RR (1989). Why I advocate the five-factor model: joint factor analyses of the NEO-PI with other instruments. In Personality, Psychology: Recent Trends and Emerging Directions (ed. Buss, D. M. and Cantor, N.), pp. 237244. Springer-Verlag: New York.CrossRefGoogle Scholar
Neale, BM, Sullivan, PF, Kendler, KS (2005). A genome scan of neuroticism in nicotine dependent smokers. American Journal of Medical Genetics, Part B: Neuropsychiatric Genetics 132B, 6569.Google Scholar
Neale, MC, Boker, SM, Xie, G, Maes, HH (2003). Mx: Statistical Modeling. Department of Psychiatry, Virginia Commonwealth University Medical School: Box 980126, Richmond VA 23298.Google Scholar
Neale, MC, Eaves, LJ, Kendler, KS (1994). The power of the classical twin study to resolve variation in threshold traits. Behavior Genetics 24, 239258.Google Scholar
Riemann, R, Angleitner, A, Strelau, J (1997). Genetic and environmental influences on personality: a study of twins reared together using the self- and peer report NEO-FFI scales. Journal of Personality 65, 449475.Google Scholar
Shifman, S, Bhomra, A, Smiley, S, Wray, NR, James, MR, Martin, NG, Hettema, JM, An, SS, Neale, MC, van den Oord, EJ, Kendler, KS, Chen, X, Boomsma, DI, Middeldorp, CM, Hottenga, JJ, Slagboom, PE, Flint, J (2008). A whole genome association study of neuroticism using DNA pooling. Molecular Psychiatry 13, 302312.CrossRefGoogle ScholarPubMed
Silventoinen, K, Magnusson, PKE, Tynelius, P, Kaprio, J, Rasmussen, F (2008). Heritability of body size and muscle strength in young adulthood: A study of one million Swedish men. Genetic Epidemiology 32, 341349.CrossRefGoogle ScholarPubMed
Spitzer, RL, Williams, JB, Gibbon, M (1987). Structured Clinical Interview for DSM-III-R. Biometrics Research Department, New York State Psychiatric Institute: New York.Google Scholar
Sullivan, PF, Neale, MC, Kendler, KS (2000). Genetic epidemiology of major depression: review and meta-analysis. American Journal of Psychiatry 157, 15521562.CrossRefGoogle ScholarPubMed
Tellegen, A, Lykken, DT, Bouchard, TJ Jr., Wilcox, KJ, Segal, NL, Rich, S (1988). Personality similarity in twins reared apart and together. Journal of Personality and Social Psychology 54, 10311039.Google Scholar
Wells, JE, Horwood, LJ (2004). How accurate is recall of key symptoms of depression? A comparison of recall and longitudinal reports. Psychological Medicine 34, 10011011.Google Scholar
Williams, L, Holahan, P (1994). Parsimony-based fit indices for multiple-indicator models: do they work? Structural Equation Modeling 1, 161189.Google Scholar