Hostname: page-component-cd9895bd7-8ctnn Total loading time: 0 Render date: 2024-12-27T12:29:09.407Z Has data issue: false hasContentIssue false
  • English
  • Français

Gene–environment interplay in depressive symptoms: moderation by age, sex, and physical illness

Published online by Cambridge University Press:  16 February 2017

A. J. Petkus ,
C. R. Beam ,
W. Johnson ,
J. Kaprio ,
T. Korhonen ,
M. McGue ,
J. M. Neiderhiser ,
N. L. Pedersen ,
C. A. Reynolds  and
M. Gatz
...Show all authors
A. J. Petkus
Affiliation:
Department of Neurology, University of Southern California, Los Angeles, CA, USA
C. R. Beam
Affiliation:
Department of Psychology & Davis School of Gerontology, University of Southern California, Los Angeles, CAUSA
W. Johnson
Affiliation:
Department of Psychology, Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
J. Kaprio
Affiliation:
Department of Public Health, University of Helsinki, Helsinki, Finland Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland
T. Korhonen
Affiliation:
Department of Public Health, University of Helsinki, Helsinki, Finland Institute for Molecular Medicine (FIMM), University of Helsinki, Helsinki, Finland Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
M. McGue
Affiliation:
Department of Psychology, University of Minnesota, Minneapolis, MN,USA The Danish Twin Registry, University of Southern Denmark, Institute of Public Health, Epidemiology, Odense C, Denmark
J. M. Neiderhiser
Affiliation:
Department of Psychology, Penn State University, University Park, PA, USA
N. L. Pedersen
Affiliation:
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden Department of Psychology, University of Southern California, Los Angeles, CA, USA
C. A. Reynolds
Affiliation:
Department of Psychology, University of California Riverside, Riverside, CA, USA
M. Gatz*
Affiliation:
Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden Department of Psychology, University of Southern California, Los Angeles, CA, USA
*
*Address for correspondence: M. Gatz, Ph.D., Department of Psychology, University of Southern California, Los Angeles, CA 90089-1061, USA. (Email: [email protected])
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Numerous factors influence late-life depressive symptoms in adults, many not thoroughly characterized. We addressed whether genetic and environmental influences on depressive symptoms differed by age, sex, and physical illness.

Method

The analysis sample included 24 436 twins aged 40–90 years drawn from the Interplay of Genes and Environment across Multiple Studies (IGEMS) Consortium. Biometric analyses tested age, sex, and physical illness moderation of genetic and environmental variance in depressive symptoms.

Results

Women reported greater depressive symptoms than men. After age 60, there was an accelerating increase in depressive symptom scores with age, but this did not appreciably affect genetic and environmental variances. Overlap in genetic influences between physical illness and depressive symptoms was greater in men than in women. Additionally, in men extent of overlap was greater with worse physical illness (the genetic correlation ranged from near 0.00 for the least physical illness to nearly 0.60 with physical illness 2 s.d. above the mean). For men and women, the same environmental factors that influenced depressive symptoms also influenced physical illness.

Conclusions

Findings suggested that genetic factors play a larger part in the association between depressive symptoms and physical illness for men than for women. For both sexes, across all ages, physical illness may similarly trigger social and health limitations that contribute to depressive symptoms.

Keywords

Ageddepressive symptomsheritabilitytwin studies
Type
Original Articles
Information
Psychological Medicine , Volume 47 , Issue 10 , July 2017 , pp. 1836 - 1847
Copyright
Copyright © Cambridge University Press 2017 

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.)

Footnotes

†

Members of the IGEMS Consortium are given in the Appendix.

References

Anttila, V et al. (2016). Analysis of shared heritability in common disorders of the brain. bioRxiv. doi:10.1101/048991.Google Scholar
Berkman, LF, Berkman, CS, Kasl, S, Freeman, DH Jr., Leo, L, Ostfeld, AD, Cornoni-Huntley, J, Brody, J (1986). Depressive symptoms in relation to physical health and functioning in the elderly. American Journal of Epidemiology 124, 372–388.CrossRefGoogle ScholarPubMed
Bierut, LJ, Heath, AC, Bucholz, KK, Dinwiddie, SH, Madden, PA, Statham, DJ, Dunne, MP, Martin, NG (1999). Major depressive disorder in a community-based twin sample: are there different genetic and environmental contributions for men and women? Archives of General Psychiatry 56, 557–563.CrossRefGoogle Scholar
Blazer, DG (2003). Depression in late life: review and commentary. Journal of Gerontology Series A: Biological Sciences and Medical Sciences 58A, 249–265.CrossRefGoogle Scholar
Carmelli, D, Swan, GE, Kelly-Hayes, M, Wolf, PA, Reed, T, Miller, B (2000). Longitudinal changes in the contribution of genetic and environmental influences to symptoms of depression in older male twins. Psychology and Aging 15, 505–510.CrossRefGoogle ScholarPubMed
Christensen, K, Holm, NV, McGue, M, Corder, L, Vaupel, JW (1999). A Danish population-based twin study on general health in the elderly. Journal of Aging and Health 11, 49–64.CrossRefGoogle ScholarPubMed
Djernes, JK (2006). Prevalence and predictors of depression in populations of elderly: a review. Acta Psychiatrica Scandinavia 113, 372–387.CrossRefGoogle ScholarPubMed
Ehrlich, BS, Isaacowitz, DM (2002). Does subjective well-being increase with age? Perspectives in Psychology 5, 20–26.Google Scholar
Finkel, D, McGue, M (1993). The origins of individual differences in memory among the elderly: a behavior genetic analysis. Psychology and Aging 8, 527–537.CrossRefGoogle ScholarPubMed
Finkel, D, Pedersen, NL (2004). Processing speed and longitudinal trajectories of change for cognitive abilities: The Swedish Adoption/Twin Study of Aging. Aging, Neuropsychology, and Cognition. Special Issue: Longitudinal Studies of Cognitive Aging 11, 325–345.CrossRefGoogle Scholar
Fiske, A, Wetherell, JL, Gatz, M (2009). Depression in older adults. Annual Review of Clinical Psychology 5, 363–389.CrossRefGoogle ScholarPubMed
Forlani, C, Morri, M, Ferrari, B, Dalmonte, E, Menchetti, M, De Ronchi, D, Atti, AR (2014). Prevalence and gender differences in late-life depression: a population-based study. American Journal of Geriatric Psychiatry 22, 370–380.CrossRefGoogle ScholarPubMed
Franz, CE, Lyons, MJ, O'Brien, R, Panizzon, MS, Kim, K, Bhat, R, Grant, MD, Toomey, R, Eisen, S, Xian, H, Kremen, WS (2011). A 35-year longitudinal assessment of cognition and midlife depression symptoms: the Vietnam Era Twin study of aging. The American Journal of Geriatric Psychiatry 19, 559–570.CrossRefGoogle ScholarPubMed
Gatz, M, Pedersen, NL, Plomin, R, Nesselroade, JR, McClearn, GE (1992). The importance of shared genes and shared environments for symptoms of depression in older adults. Journal of Abnormal Psychology 101, 701–708.CrossRefGoogle ScholarPubMed
Gatz, M, Petkus, A, Reynolds, CA, Franz, C, Kaprio, J, Christensen, K, for the IGEMS Consortium (2015 a). Age moderation of individual differences in chronic medical illness burden [Abstract]. Behavior Genetics 45, 657.Google Scholar
Gatz, M, Reynolds, CR, Finkel, D, Hahn, CJ, Zhou, Y, Zavala, C (2015b). Data harmonization in aging research: not so fast. Journal of Experimental Aging Research 41, 475–495.CrossRefGoogle Scholar
Gillespie, NA, Kirk, KM, Evans, DM, Heath, AC, Hickie, IB, Martin, NG (2004). Do the genetic or environmental determinants of anxiety and depression change with age? A longitudinal study of Australian twins. Twin Research 7, 39–53.CrossRefGoogle ScholarPubMed
Gold, CH, Malmberg, B, McClearn, GE, Pedersen, NL, Berg, S (2002). Gender and health: a study of older unlike-sex twins. Journals of Gerontology: Series B: Psychological Sciences and Social Sciences 57B, S168–S176.CrossRefGoogle Scholar
Heath, AC, Kessler, RC, Neale, MC, Hewitt, JK, Eaves, LJ, Kendler, KS (1993). Testing hypotheses about direction of causation using cross sectional family data. Behavior Genetics 23, 29–50.CrossRefGoogle ScholarPubMed
Johnson, W (2007). Genetic and environmental influences on behavior: capturing all the interplay. Psychological Review 114, 423–440.CrossRefGoogle ScholarPubMed
Johnson, W, McGue, M, Gaist, D, Vaupel, JW, Christensen, K (2002). Frequency and heritability of depression symptomatology in the second half of life: evidence from Danish twins over 45. Psychological Medicine 32, 1175–1185.CrossRefGoogle ScholarPubMed
Judd, LL, Schettler, PJ, Akiskal, HS (2002). The prevalence, clinical relevance, and public health significance of subthreshold depressions. Psychiatric Clinics of North America 25, 685–698.CrossRefGoogle Scholar
Kaprio, J (2013). The Finnish Twin Cohort Study: an update. Twin Research and Human Genetics 16, 157–162.CrossRefGoogle ScholarPubMed
Kaprio, J, Koskenvuo, M (2002). Genetic and environmental factors in complex diseases: the older Finnish Twin Cohort. Twin Research and Human Genetics 5, 358–365.CrossRefGoogle ScholarPubMed
Kendler, KS, Gardner, CO (2014). Sex differences in the pathways to Major Depression: a study of opposite-sex twin pairs. The American Journal of Psychiatry 171, 426–435.CrossRefGoogle ScholarPubMed
Kendler, KS, Gardner, CO, Neale, MC, Prescott, CA (2001). Genetic risk factors for major depression in men and women: similar or different heritabilities and same or partly distinct genes? Psychological Medicine 4, 605–616.CrossRefGoogle Scholar
Kendler, KS, Gatz, M, Gardner, CO, Pedersen, NL (2006). A Swedish national twin study of lifetime major depression. American Journal of Psychiatry 163, 109–114.CrossRefGoogle ScholarPubMed
Kendler, KS, Thornton, LM, Gilman, SE, Kessler, RC (2000). Sexual orientation in a U.S. national sample of twin and nontwin sibling pairs. American Journal of Psychiatry 157, 1843–1846.CrossRefGoogle Scholar
Kessler, RC, Foster, C, Webster, PS, House, JS (1992). The relationship between age and depressive symptoms in two national surveys. Psychology and Aging 7, 119–126.CrossRefGoogle ScholarPubMed
Korhonen, T, Broms, U, Varjonen, J, Romanov, K, Koskenvuo, M, Kinnunen, T, Kaprio, J (2007). Smoking behaviour as a predictor for depression among Finnish men and women – a prospective study of adult twins. Psychological Medicine 37, 705–715.CrossRefGoogle ScholarPubMed
Kremen, WS, Thompson-Brenner, H, Leung, YJ, Grant, MD, Franz, CE, Eisen, SA, Jacobson, KC, Boake, C, Lyons, MJ (2006). Genes, environment, and time: the Vietnam Era Twin Study of Aging (VETSA). Twin Research and Human Genetics 9, 1009–1022.CrossRefGoogle ScholarPubMed
McArdle, JJ, Hamagami, F (2003). Structural equation models for evaluating dynamic concepts within longitudinal twin analyses. Behavioral Genetics 33, 137–159.CrossRefGoogle ScholarPubMed
McClearn, GE, Johansson, B, Berg, S, Pedersen, NL, Ahern, F, Petrill, SA, Plomin, R (1997). Substantial genetic influence on cognitive abilities in twins 80 or more years old. Science 276, 1560–1563.CrossRefGoogle ScholarPubMed
McGue, M, Christensen, K (1997). Genetic and environmental contributions to depression symptomatology: evidence from Danish twins 75 years of age and older. Journal of Abnormal Psychology 106, 439–448.CrossRefGoogle ScholarPubMed
Meeks, S, Murrell, SA, Mehl, RC (2000). Longitudinal relationships between depressive symptoms and health in normal older and middle-aged adults. Psychology and Aging 15, 100–109.CrossRefGoogle ScholarPubMed
Neale, M, Hunter, M, Pritikin, JN, Zahery, M, Brick, TR, Kickpatrick, RM, Estabrook, R, Bates, TC, Maes, H, Boker, SM (2016). Open Mx 2.0: extended structural equation and statistical modeling. Psychometrika 81, 535–549.CrossRefGoogle Scholar
Neale, M, Roysamb, E, Jacobson, K (2006). Multivariate genetic analysis of sex limitation and GxE interaction. Twin Research and Human Genetics 9, 481–489.CrossRefGoogle Scholar
Neiderhiser, JM, Lichtenstein, P (2008). The Twin and Offspring Study in Sweden: advancing our understanding of genotype-environment interplay by studying twins and their families. Acta Psychologica Sinica 40, 1116–1123.Google Scholar
Pedersen, NL, Christensen, K, Dahl, A, Finkel, D, Franz, C, Gatz, M, Horwitz, BN, Johansson, B, Johnson, W, Kremen, WS, Lyons, MJ, Malmberg, B, McGue, M, Neiderhiser, JM, Peterson, I, Reynolds, CA (2013). IGEMS: The Consortium on Interplay of Genes and Environment across Multiple Studies. Twin Research and Human Genetics 16, 481–489.CrossRefGoogle Scholar
Radloff, LS (1977). The CES – D scale: a self – report depressive mood scale for research in the general population. Applied Psychological Measurement 3, 385–401.CrossRefGoogle Scholar
Roth, M, Tym, E, Mountjoy, CQ, Huppert, FA, Hendrie, H, Verma, S, Goodard, R (1986). CAMDEX: a standardised instrument for the diagnosis of mental disorder in the elderly with special reference to the early detection of dementia. British Journal of Psychiatry 149, 698–709.CrossRefGoogle Scholar
Salvi, F, Miller, MD, Grilli, A, Giorgi, R, Towers, AL, Morichi, V, Spazzafumo, L, Mancinelli, L, Espinosa, E, Rappelli, A, Dessì-Fulgheri, P (2008). A manual of guidelines to score the modified cumulative illness rating scale and its validation in acute hospitalized elderly patients. Journal of the American Geriatrics Society 56, 1926–1931.CrossRefGoogle ScholarPubMed
SAS Institute Inc. (2013). SAS 9.4. SAS Institute Inc.: Cary, NC.Google Scholar
Schnittker, J (2014). Natural Symptoms? The Intersection of Social, Biological, and Genetic Determinants of Depression in Later Life. Working paper: University of Pennsylvania Population, Aging Research Center. PARC Working Paper Series, WPS 14–01.Google Scholar
Scott, KM, Lim, C, Al-Hamzawi, A, Alonso, J, Bruffaerts, R, Caldas-de-Almeida, JM, Florescu, S, de Girolamo, G, Hu, C, de Jonge, P, Kawakami, N, Medina-Mora, ME, Moskalewicz, J, Navarro-Mateu, F, O'Neill, S, Piazza, M, Pasada-Villa, J, Torres, Y, Kessler, RC (2016). Association of mental disorders with subsequent chronic physical conditions: world mental health surveys from 17 countries. JAMA Psychiatry 73, 150–158.CrossRefGoogle ScholarPubMed
Skytthe, A, Christiansen, L, Kyvik, KO, Bødker, FL, Hvidberg, L, Petersen, I, Nielsen, MMF, Bingley, P, Hjelmborg, J, Tan, Q, Holm, NV, Vaupel, JW, McGue, M, Christensen, K (2013). The Danish Twin Registry: linking surveys, national registers, and biological information. Twin Research and Human Genetics 16, 104–111.CrossRefGoogle ScholarPubMed
Sonnenberg, CM, Beekman, ATF, Deeg, DJH, van Tilburg, W (2000). Sex differences in late life depression. Acta Psychiatrica Scandinavica 101, 286–292.Google ScholarPubMed
Steptoe, A (2007). Depression and Physical Illness. Cambridge University Press: New York.Google Scholar
Sutin, AR, Terracciano, A, Milaneschi, Y, An, Y, Ferrucci, L, Zonderman, AB (2013). The trajectory of depressive symptoms across the adult lifespan. JAMA Psychiatry 70, 803–811.CrossRefGoogle Scholar
Takkinen, S, Tolvanen, A, Kaprio, J, Berg, S, Koskenvuo, M, Rantanen, T (2004). The genetic and environmental effects on depressive symptoms among older female twins. Twin Research 7, 626–636.CrossRefGoogle ScholarPubMed
Turkheimer, E, Harden, KP (2014). Behavior genetic research methods: testing quasi-causal hypotheses using multivariate twin data. In Handbook of Research Methods in Personality and Social Psychology (ed. Reis, H. T. and Judd, C. M.), pp. 159–187. John Wiley: New York.CrossRefGoogle Scholar
Twenge, JM (2015). Time period and birth cohort differences in depressive symptoms in the U.S., 1982–2013. Social Indicators Research 121, 437–454.CrossRefGoogle Scholar
van der Sluis, S, Posthuma, D, Dolan, CV (2012). A note on false positives and power in GxE modelling of twin data. Behavior Genetics 42, 170–186.CrossRefGoogle Scholar
Van Hulle, C, Lahey, B, Rathouz, P (2013). Operating characteristics of alternative statistical methods for detecting gene-by-measured environment interaction in the presence of gene-environment correlation in twin and sibling studies. Behavior Genetics 43, 71–84.CrossRefGoogle ScholarPubMed
Supplementary material: File

Petkus supplementary material

Petkus supplementary material

Download Petkus supplementary material(File)
File 71.6 KB