Hostname: page-component-586b7cd67f-dsjbd Total loading time: 0 Render date: 2024-11-28T16:06:43.087Z Has data issue: false hasContentIssue false
  • English
  • Français

Associations between depression and cardiometabolic health: A 27-year longitudinal study

Published online by Cambridge University Press:  12 January 2021

Hillary L. Ditmars Open the ORCID record for Hillary L. Ditmars [Opens in a new window] ,
Mark W. Logue ,
Rosemary Toomey ,
Ruth E. McKenzie ,
Carol E. Franz ,
Matthew S. Panizzon ,
Chandra A. Reynolds ,
Kristy N. Cuthbert ,
Richard Vandiver  and
Daniel E. Gustavson
...Show all authors
Hillary L. Ditmars*
Affiliation:
Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
Mark W. Logue
Affiliation:
Research Service, VA Boston Healthcare System, Boston, MA, USA Biomedical Genetics Program, Boston University School of Medicine, Boston, MA, USA Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
Rosemary Toomey
Affiliation:
Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
Ruth E. McKenzie
Affiliation:
Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA School of Education and Social Policy, Merrimack College, North Andover, MA, USA
Carol E. Franz
Affiliation:
Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
Matthew S. Panizzon
Affiliation:
Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
Chandra A. Reynolds
Affiliation:
Department of Psychology, University of California, Riverside, Riverside, CA, USA
Kristy N. Cuthbert
Affiliation:
Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
Richard Vandiver
Affiliation:
Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
Daniel E. Gustavson
Affiliation:
Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
Graham M. L. Eglit
Affiliation:
Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA VA San Diego Healthcare System, San Diego, CA, USA
Jeremy A. Elman
Affiliation:
Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA
Mark Sanderson-Cimino
Affiliation:
Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
McKenna E. Williams
Affiliation:
Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA San Diego State University/UC San Diego Joint Doctoral Program in Clinical Psychology, San Diego, CA, USA
Ole A. Andreassen
Affiliation:
NORMENT, KG Jebsen Centre for Psychosis Research, Institute of Clinical Medicine University of Oslo, Oslo, Norway Division of Mental Health and Addiction, Oslo University Hospital Oslo, Oslo, Norway
Anders M. Dale
Affiliation:
Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA, USA Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
Lisa T. Eyler
Affiliation:
Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
Christine Fennema-Notestine
Affiliation:
Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA Department of Radiology, School of Medicine, University of California, San Diego, La Jolla, CA, USA
Nathan A. Gillespie
Affiliation:
Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
Richard L. Hauger
Affiliation:
Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
Amy J. Jak
Affiliation:
Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
Michael C. Neale
Affiliation:
Department of Psychiatry, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA Department of Human and Molecular Genetics, Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University, Richmond, VA, USA
Xin M. Tu
Affiliation:
Department of Family Medicine and Public Health, VA San Diego Healthcare System, San Diego, CA, USA
Nathan Whitsel
Affiliation:
Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA
Hong Xian
Affiliation:
Department of Epidemiology & Biostatistics, Saint Louis University College for Public Health & Social Justice, Saint Louis, MO, USA
William S. Kremen
Affiliation:
Department of Psychiatry, School of Medicine, University of California, San Diego, La Jolla, CA, USA Center for Behavior Genetics of Aging, University of California, San Diego, La Jolla, CA, USA Center of Excellence for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
Michael J. Lyons
Affiliation:
Department of Psychological and Brain Sciences, Boston University, Boston, MA, USA
*
Author for correspondence: Hillary L. Ditmars, E-mail: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Background

Clarifying the relationship between depression symptoms and cardiometabolic and related health could clarify risk factors and treatment targets. The objective of this study was to assess whether depression symptoms in midlife are associated with the subsequent onset of cardiometabolic health problems.

Methods

The study sample comprised 787 male twin veterans with polygenic risk score data who participated in the Harvard Twin Study of Substance Abuse (‘baseline’) and the longitudinal Vietnam Era Twin Study of Aging (‘follow-up’). Depression symptoms were assessed at baseline [mean age 41.42 years (s.d. = 2.34)] using the Diagnostic Interview Schedule, Version III, Revised. The onset of eight cardiometabolic conditions (atrial fibrillation, diabetes, erectile dysfunction, hypercholesterolemia, hypertension, myocardial infarction, sleep apnea, and stroke) was assessed via self-reported doctor diagnosis at follow-up [mean age 67.59 years (s.d. = 2.41)].

Results

Total depression symptoms were longitudinally associated with incident diabetes (OR 1.29, 95% CI 1.07–1.57), erectile dysfunction (OR 1.32, 95% CI 1.10–1.59), hypercholesterolemia (OR 1.26, 95% CI 1.04–1.53), and sleep apnea (OR 1.40, 95% CI 1.13–1.74) over 27 years after controlling for age, alcohol consumption, smoking, body mass index, C-reactive protein, and polygenic risk for specific health conditions. In sensitivity analyses that excluded somatic depression symptoms, only the association with sleep apnea remained significant (OR 1.32, 95% CI 1.09–1.60).

Conclusions

A history of depression symptoms by early midlife is associated with an elevated risk for subsequent development of several self-reported health conditions. When isolated, non-somatic depression symptoms are associated with incident self-reported sleep apnea. Depression symptom history may be a predictor or marker of cardiometabolic risk over decades.

Keywords

DepressionCardiometabolic healthPolygenic risk scores
Type
Original Article
Information
Psychological Medicine , Volume 52 , Issue 14 , October 2022 , pp. 3007 - 3017
Check for updates
Copyright
Copyright © The Author(s), 2021. Published by Cambridge University Press

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

1000 Genomes Project Consortium. (2015). A global reference for human genetic variation. Nature, 526(7571), 68–74. https://doi.org/10.1038/nature15393.CrossRefGoogle Scholar
American Psychiatric Association. (1987). Diagnostic and statistical manual of mental disorders (Revised Th). Washington, DC: American Psychiatric Association. https://doi.org/10.1176/appi.books.9780890425596.Google Scholar
BaHammam, A. S., Kendzerska, T., Gupta, R., Ramasubramanian, C., Neubauer, D. N., Narasimhan, M., … Moscovitch, A. (2016). Comorbid depression in obstructive sleep apnea: An under-recognized association. Sleep and Breathing 20(2), 447–456. https://doi.org/10.1007/s11325-015-1223-x.CrossRefGoogle ScholarPubMed
Bahrami, S., Steen, N. E., Shadrin, A., O'Connell, K., Frei, O., Bettella, F., … Andreassen, O. A. (2020). Shared genetic loci between body mass index and major psychiatric disorders: A genome-wide association study. JAMA Psychiatry, 77(5), 503–512. https://doi.org/10.1001/jamapsychiatry.2019.4188.CrossRefGoogle ScholarPubMed
Benjamini, Y., & Hochberg, Y. (1995). Controlling the false discovery rate: A practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological), 57(1), 289–300.CrossRefGoogle Scholar
Bovijn, J., Jackson, L., Censin, J., Chen, C. Y., Laisk, T., Laber, S., … Holmes, M. V. (2019). GWAS identifies risk locus for erectile dysfunction and implicates hypothalamic neurobiology and diabetes in etiology. American Journal of Human Genetics, 104(1), 157–163. https://doi.org/10.1016/j.ajhg.2018.11.004.CrossRefGoogle ScholarPubMed
Bulik-Sullivan, B., Finucane, H. K., Anttila, V., Gusev, A., Day, F. R., Loh, P. R., … Neale, B. M. (2015). An atlas of genetic correlations across human diseases and traits. Nature Genetics, 47(11), 1236–1241. https://doi.org/10.1038/ng.3406.CrossRefGoogle ScholarPubMed
Capuron, L., Su, S., Miller, A. H., Bremner, J. D., Goldberg, J., Vogt, G. J., … Vaccarino, V. (2008). Depressive symptoms and metabolic syndrome: Is inflammation the underlying link? Biological Psychiatry, 64(10), 896–900. https://doi.org/10.1016/j.biopsych.2008.05.019.CrossRefGoogle ScholarPubMed
Cardiovascular Disease Knowledge Portal. (n.d. https://cvd.hugeamp.org/Google Scholar
Carney, R. M., & Freedland, K. E. (2017). Depression in patients with coronary artery disease: A more significant problem than previously recognized? European Heart Journal – Quality of Care and Clinical Outcomes, 3(4), 262–263. https://doi.org/10.1093/ehjqcco/qcx019.CrossRefGoogle ScholarPubMed
Chaddha, A., Robinson, E. A., Kline-Rogers, E., Alexandris-Souphis, T., & Rubenfire, M. (2016). Mental health and cardiovascular disease. American Journal of Medicine, 129(11), 1145–1148. https://doi.org/10.1016/j.amjmed.2016.05.018.CrossRefGoogle ScholarPubMed
Chang, C. C., Chow, C. C., Tellier, L. C. A. M., Vattikuti, S., Purcell, S. M., & Lee, J. J. (2015). Second-generation PLINK: Rising to the challenge of larger and richer datasets. GigaScience, 4(1), 7. https://doi.org/10.1186/s13742-015-0047-8.CrossRefGoogle Scholar
Chen, C. Y., Pollack, S., Hunter, D. J., Hirschhorn, J. N., Kraft, P., & Price, A. L. (2013). Improved ancestry inference using weights from external reference panels. Bioinformatics, 29(11), 1399–1406. https://doi.org/10.1093/bioinformatics/btt144.CrossRefGoogle ScholarPubMed
Cohen, B. E., Edmondson, D., & Kronish, I. M. (2015). State of the art review: Depression, stress, anxiety, and cardiovascular disease. American Journal of Hypertension, 28(11), 1295–1302. https://doi.org/10.1093/ajh/hpv047.CrossRefGoogle ScholarPubMed
Coleman, J. R. I., Gaspar, H. A., Bryois, J., Byrne, E. M., Forstner, A. J., Holmans, P. A., … Breen, G. (2020). The genetics of the mood disorder spectrum: Genome-wide association analyses of more than 185,000 cases and 439,000 controls. Biological Psychiatry, 88(2), 1–16. https://doi.org/10.1016/j.biopsych.2019.10.015.CrossRefGoogle ScholarPubMed
Colotto, M., Rubini, G., Savoriti, C., D'Adduogo, N., & Mercuri, S. (2010). [Impact of depression syndrome in the management of cardiovascular risk factors in primary prevention: State of the art]. La Clinica Terapeutica, 161(3 PG-e105-10), e105–e110. NS-.Google ScholarPubMed
de Miranda Azevedo, R., Roest, A. M., Hoen, P. W., & De Jonge, P. (2014). Cognitive/affective and somatic/affective symptoms of depression in patients with heart disease and their association with cardiovascular prognosis: A meta-analysis. Psychological Medicine, 44(13), 2689–2703. https://doi.org/10.1017/S0033291714000063.CrossRefGoogle ScholarPubMed
Evangelou, E., Warren, H. R., Mosen-Ansorena, D., Mifsud, B., Pazoki, R., Gao, H., … Caulfield, M. J. (2018). Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits. Nature Genetics, 50(10), 1412–1425. https://doi.org/10.1038/s41588-018-0205-x.CrossRefGoogle ScholarPubMed
Finkel, K. J., Searleman, A. C., Tymkew, H., Tanaka, C. Y., Saager, L., Safer-Zadeh, E., … Avidan, M. S. (2009). Prevalence of undiagnosed obstructive sleep apnea among adult surgical patients in an academic medical center. Sleep Medicine, 10(7), 753–758. https://doi.org/10.1016/j.sleep.2008.08.007.CrossRefGoogle Scholar
Freak-Poli, R., Ikram, M. A., Franco, O. H., Hofman, A., & Tiemeier, H. (2018). Depressive symptoms prior to and after incident cardiovascular disease and long-term survival. A population-based study of older persons. Depression and Anxiety, 35(1), 18–31. https://doi.org/10.1002/da.22689.CrossRefGoogle ScholarPubMed
Freitas, C., Deschênes, S., Au, B., Smith, K., & Schmitz, N. (2016). Risk of diabetes in older adults with co-occurring depressive symptoms and cardiometabolic abnormalities: Prospective analysis from the English Longitudinal Study of Ageing. PLoS ONE, 11(5), e0155741. https://doi.org/10.1371/journal.pone.0155741.CrossRefGoogle ScholarPubMed
Fryar, C. D., Kruszon-Moran, D., Gu, Q., & Ogden, C. L. (2018). National Health Statistics Reports: Mean body weight, height, waist circumference, and body mass index among adults: United States, 1999–2000 through 2015–2016.Google Scholar
Fuchsberger, C., Abecasis, G. R., & Hinds, D. A. (2015). Minimac2: Faster genotype imputation. Bioinformatics, 31(5), 782–784. https://doi.org/10.1093/bioinformatics/btu704.CrossRefGoogle ScholarPubMed
Gale, C. R., Hagenaars, S. P., Davies, G., Hill, W. D., Liewald, D. C. M., Cullen, B., … Harris, S. E. (2016). Pleiotropy between neuroticism and physical and mental health: Findings from 108038 men and women in UK biobank. Translational Psychiatry, 6(4), e791. https://doi.org/10.1038/tp.2016.56.CrossRefGoogle Scholar
Harris, M., Glozier, N., Ratnavadivel, R., & Grunstein, R. R. (2009). Obstructive sleep apnea and depression. Sleep Medicine Reviews, 13(6), 437–444. https://doi.org/10.1016/j.smrv.2009.04.001.CrossRefGoogle ScholarPubMed
Ho, C. S., Feng, L., Fam, J., Mahendran, R., Kua, E. H., & Ng, T. P. (2014). Coexisting medical comorbidity and depression: Multiplicative effects on health outcomes in older adults. International Psychogeriatrics, 26(7), 1221–1229. https://doi.org/10.1017/S1041610214000611.CrossRefGoogle ScholarPubMed
Howie, B., Fuchsberger, C., Stephens, M., Marchini, J., & Abecasis, G. R. (2012). Fast and accurate genotype imputation in genome-wide association studies through pre-phasing. Nature Genetics, 44(8), 955–959. https://doi.org/10.1038/ng.2354.CrossRefGoogle ScholarPubMed
Janszky, I., Ahlbom, A., Hallqvist, J., & Ahnve, S. (2007). Hospitalization for depression is associated with an increased risk for myocardial infarction not explained by lifestyle, lipids, coagulation, and inflammation: The SHEEP study. Biological Psychiatry, 62(1), 25–32. https://doi.org/10.1016/j.biopsych.2006.08.039.CrossRefGoogle Scholar
Kan, C., Pedersen, N. L., Christensen, K., Bornstein, S. R., Licinio, J., MacCabe, J. H., … Rijsdijk, F. (2016). Genetic overlap between type 2 diabetes and depression in Swedish and Danish twin registries. Molecular Psychiatry, 21(7), 903–909. https://doi.org/10.1038/mp.2016.28.CrossRefGoogle ScholarPubMed
Kendler, K. S. (2012). The dappled nature of causes of psychiatric illness: Replacing the organic-functional/hardware-software dichotomy with empirically based pluralism. Molecular Psychiatry, 17(4), 377–388. https://doi.org/10.1038/mp.2011.182.CrossRefGoogle ScholarPubMed
Keyes, C. L. M. (2004). The nexus of cardiovascular disease and depression revisited: The complete mental health perspective and the moderating role of age and gender. Aging & Mental Health, 8(3), 266–274. https://doi.org/10.1080/13607860410001669804.CrossRefGoogle ScholarPubMed
Kremen, W. S., Franz, C. E., & Lyons, M. J. (2013). VETSA: The Vietnam Era Twin Study of Aging. Twin Research and Human Genetics, 16(1), 399–402. https://doi.org/10.1017/thg.2012.86.CrossRefGoogle ScholarPubMed
Kremen, W. S., Thompson-Brenner, H., Leung, Y.-M. M. J., Grant, M. D., Franz, C. E., Eisen, S. A., … Lyons, M. J. (2006). Genes, environment, and time: The Vietnam Era Twin Study of Aging (VETSA). Twin Research and Human Genetics, 9(6), 1009–1022. https://doi.org/10.1375/183242706779462750.CrossRefGoogle ScholarPubMed
Lichtman, J. H., Froelicher, E. S., Blumenthal, J. A., Carney, R. M., Doering, L. V, Frasure-Smith, N., … Wulsin, L. (2014). Depression as a risk factor for poor prognosis among patients with acute coronary syndrome: Systematic review and recommendations: A scientific statement from the American Heart Association. Circulation, 129(12), 1350–1369. https://doi.org/10.1161/CIR.0000000000000019.CrossRefGoogle ScholarPubMed
Liu, Q., Zhang, Y., Wang, J., Li, S., Cheng, Y., Guo, J., … Zhu, Z. (2018). Erectile dysfunction and depression: A systematic review and meta-analysis. Journal of Sexual Medicine, 15(8), 1073–1082. https://doi.org/10.1016/j.jsxm.2018.05.016.CrossRefGoogle ScholarPubMed
Locke, A. E., Kahali, B., Berndt, S. I., Justice, A. E., Pers, T. H., Day, F. R., … Econs, M. J. (2015). Genetic studies of body mass index yield new insights for obesity biology. Nature, 518(7538), 197–206. https://doi.org/10.1038/nature14177.CrossRefGoogle ScholarPubMed
Logue, M. W., Panizzon, M. S., Elman, J. A., Gillespie, N. A., Hatton, S. N., Gustavson, D. E., … Kremen, W. S. (2019). Use of an Alzheimer's disease polygenic risk score to identify mild cognitive impairment in adults in their 50s. Molecular Psychiatry, 24(3), 421–430. https://doi.org/10.1038/s41380-018-0030-8.CrossRefGoogle ScholarPubMed
Malik, R., Chauhan, G., Traylor, M., Sargurupremraj, M., Okada, Y., Mishra, A., … Yamaji, T. (2018). Multiancestry genome-wide association study of 520000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nature Genetics, 50(4), 524–537. https://doi.org/10.1038/s41588-018-0058-3.CrossRefGoogle Scholar
Martin, A. R., Kanai, M., Kamatani, Y., Okada, Y., Neale, B. M., & Daly, M. J. (2019). Clinical use of current polygenic risk scores may exacerbate health disparities. Nature Genetics, 51(4), 584–591. https://doi.org/10.1038/s41588-019-0379-x.CrossRefGoogle ScholarPubMed
Meijer, A., Zuidersma, M., & de Jonge, P. (2013). Depression as a non-causal variable risk marker in coronary heart disease. BMC Medicine, 11(1), 130. https://doi.org/10.1186/1741-7015-11-130.CrossRefGoogle ScholarPubMed
Meng, L., Chen, D., Yang, Y., Zheng, Y., & Hui, R. (2012). Depression increases the risk of hypertension incidence: A meta-analysis of prospective cohort studies. Journal of Hypertension, 30(5), 842–851. https://doi.org/10.1097/HJH.0b013e32835080b7.CrossRefGoogle ScholarPubMed
Momen, N. C., Plana-Ripoll, O., Agerbo, E., Benros, M. E., Børglum, A. D., Christensen, M. K., … McGrath, J. J. (2020). Association between mental disorders and subsequent medical conditions. New England Journal of Medicine, 382(18), 1721–1731. https://doi.org/10.1056/NEJMoa1915784.CrossRefGoogle ScholarPubMed
Monami, M., & Marchionni, N. (2007). [Psychological disorders and cardiovascular diseases]. Giornale Italiano Di Cardiologia (2006), 8(6 PG-335–48), 335–348. NS-.Google ScholarPubMed
Montazer, S., & Wheaton, B. (2011). The impact of generation and country of origin on the mental health of children of immigrants. Journal of Health and Social Behavior, 52(1), 23–42. https://doi.org/10.1177/0022146510395027.CrossRefGoogle ScholarPubMed
Morris, A. P., Voight, B. F., Teslovich, T. M., Ferreira, T., Segrè, A. V, Steinthorsdottir, V., … McCarthy, M. I. (2012). Large-scale association analysis provides insights into the genetic architecture and pathophysiology of type 2 diabetes. Nature Genetics, 44(9), 981–990. https://doi.org/10.1038/ng.2383.Google ScholarPubMed
Neale, M. C., & Eaves, L. J. (1993). Estimating and controlling for the effects of volunteer bias with pairs of relatives. Behavior Genetics, 23(3), 271–277. https://doi.org/10.1007/BF01082466.CrossRefGoogle ScholarPubMed
Nelson, C. P., Goel, A., Butterworth, A. S., Kanoni, S., Webb, T. R., Marouli, E., … Deloukas, P. (2017). Association analyses based on false discovery rate implicate new loci for coronary artery disease. Nature Genetics, 49(9), 1385–1391. https://doi.org/10.1038/ng.3913.CrossRefGoogle ScholarPubMed
Norton, J., Pastore, M., Ancelin, M., Hotopf, M., Tylee, A., Mann, A., … Palacios, J. (2020). Time-dependent cognitive and somatic symptoms of depression as predictors of new cardiac-related events in at-risk patients: The UPBEAT-UK cohort. Psychological Medicine, 1–8. https://doi.org/10.1017/S0033291719004082.Google Scholar
Palmer, D. (n.d.). Genetic correlation between traits and disorders in the UK Biobank. https://ukbb-rg.hail.is/.Google Scholar
Pan, A., Sun, Q., Okereke, O. I., Rexrode, K. M., & Hu, F. B. (2011). Depression and risk of stroke morbidity and mortality: A meta-analysis and systematic review. JAMA – Journal of the American Medical Association, 306(11), 1241–1249. https://doi.org/10.1001/jama.2011.1282.CrossRefGoogle ScholarPubMed
Pozuelo, L., Tesar, G., Zhang, J., Penn, M., Franco, K., & Jiang, W. (2009). Depression and heart disease: What do we know, and where are we headed? Cleveland Clinic Journal of Medicine, 76(1), 59–70. https://doi.org/10.3949/ccjm.75a.08011.CrossRefGoogle ScholarPubMed
Radua, J., & Albajes-Eizagirre, A. (n.d.). FDR online calculator.https://www.sdmproject.com/utilities/?show=FDRGoogle Scholar
Rajan, S., McKee, M., Rangarajan, S., Bangdiwala, S., Rosengren, A., Gupta, R., … Yusuf, S. (2020). Association of symptoms of depression with cardiovascular disease and mortality in low-, middle-, and high-income countries. JAMA Psychiatry, 77(10), 1052–1063. https://doi.org/10.1001/jamapsychiatry.2020.1351.CrossRefGoogle ScholarPubMed
Richard, A., Rohrmann, S., Vandeleur, C. L., Schmid, M., Barth, J., & Eichholzer, M. (2017). Loneliness is adversely associated with physical and mental health and lifestyle factors: Results from a Swiss national survey. PLoS ONE, 12(7), e0181442. https://doi.org/10.1371/journal.pone.0181442.CrossRefGoogle ScholarPubMed
Robins, L., Helzer, J., Goldring, E., & Cottler, L. (1989). National Institute of Mental Health (NIHM) Diagnostic Interview Schedule: Version III Revised.Google Scholar
Roselli, C., Chaffin, M. D., Weng, L. C., Aeschbacher, S., Ahlberg, G., Albert, C. M., … Ellinor, P. T. (2018). Multi-ethnic genome-wide association study for atrial fibrillation. Nature Genetics, 50(9), 1225–1233. https://doi.org/10.1038/s41588-018-0133-9.CrossRefGoogle ScholarPubMed
Schoevers, R., Bremmer, M., Beekman, A., Hoogendijk, W., Deeg, D., & van Tilburg, W. (2004). [Explanations for the relation between depression and increased mortality]. Nederlands Tijdschrift Voor Geneeskunde, 148(23 PG-1133–7), 1133–1137. NS -.Google ScholarPubMed
Semenkovich, K., Brown, M. E., Svrakic, D. M., & Lustman, P. J. (2015). Depression in type 2 diabetes mellitus: Prevalence, impact, and treatment. Drugs, 75(6), 577–587. https://doi.org/10.1007/s40265-015-0347-4.CrossRefGoogle ScholarPubMed
Serrano, C. V., Tiemi Setani, K., Sakamoto, E., Maria Andrei, A., & Fraguas, R. (2011). Association between depression and development of coronary artery disease: Pathophysiologic and diagnostic implications. Vascular Health and Risk Management, 7(1), 159–164. https://doi.org/10.2147/VHRM.S10783.Google ScholarPubMed
SPSS Statistics for Mac (No. 25). (2018). IBM Corp. https://www.ibm.com/products/spss-statistics.Google Scholar
Tarlov, E., Silva, A., Wing, C., Slater, S., Matthews, S. A., Jones, K. K., & Zenk, S. N. (2020). Neighborhood walkability and BMI change: A national study of veterans in large urban areas. Obesity, 28(1), 46–54. https://doi.org/10.1002/oby.22611.CrossRefGoogle Scholar
Tsuang, M. T., Bar, J. L., Harley, R. M., & Lyons, M. J. (2001). The Harvard twin study of substance abuse: What we have learned. Harvard Review of Psychiatry, 9(6), 267–279. http://www.ncbi.nlm.nih.gov/pubmed/11600486.CrossRefGoogle ScholarPubMed
Tsuang, M. T., Lyons, M. J., Eisen, S. A., Goldberg, J., True, W., Lin, N., … Eaves, L. (1996). Genetic influences on DSM-III-R drug abuse and dependence: A study of 3372 twin pairs. American Journal of Medical Genetics – Seminars in Medical Genetics, 67(5), 473–477. https://doi.org/10.1002/(sici)1096-8628(19960920)67:5<473::aid-ajmg6>3.0.co;2-l.3.0.CO;2-L>CrossRefGoogle Scholar
Tyrrell, J., Mulugeta, A., Wood, A. R., Zhou, A., Beaumont, R. N., Tuke, M. A., … Hyppönen, E. (2019). Using genetics to understand the causal influence of higher BMI on depression. International Journal of Epidemiology, 48(3), 834–848. https://doi.org/10.1093/ije/dyy223.CrossRefGoogle ScholarPubMed
UK Biobank – Neale lab. (n.d.). http://www.nealelab.is/uk-biobank/.Google Scholar
Van der Kooy, K., van Hout, H., Marwijk, H., Marten, H., Stehouwer, C., & Beekman, A. (2007). Depression and the risk for cardiovascular diseases: Systematic review and meta analysis. International Journal of Geriatric Psychiatry, 22(7), 613–626. https://doi.org/10.1002/gps.1723.CrossRefGoogle ScholarPubMed
van Marwijk, H. W. J., van der Kooy, K. G., Stehouwer, C. D. A., Beekman, A. T. F., & van Hout, H. P. J. (2015). Depression increases the onset of cardiovascular disease over and above other determinants in older primary care patients, a cohort study. BMC Cardiovascular Disorders, 15, 40. https://doi.org/10.1186/s12872-015-0036-y.CrossRefGoogle ScholarPubMed
Willer, C. J., Schmidt, E. M., Sengupta, S., Peloso, G. M., Gustafsson, S., Kanoni, S., … Abecasis, G. R. (2013). Discovery and refinement of loci associated with lipid levels. Nature Genetics, 45(11), 1274–1285. https://doi.org/10.1038/ng.2797.Google ScholarPubMed
Xian, H., Scherrer, J. F., Franz, C. E., McCaffery, J., Stein, P. K., Lyons, M. J., … Kremen, W. S. (2010). Genetic vulnerability and phenotypic expression of depression and risk for ischemic heart disease in the Vietnam era twin study of aging. Psychosomatic Medicine, 72(4), 370–375. https://doi.org/10.1097/PSY.0b013e3181d28125.CrossRefGoogle ScholarPubMed
Supplementary material: File

Ditmars et al. supplementary material

eTables 1-5

Download Ditmars et al. supplementary material(File)
File 34.1 KB