Quantifying the relative importance of genetics and environment on the comorbidity between mental and cardiometabolic disorders using 17 million Scandinavians.

Humans Comorbidity Mental Disorders / genetics Male Denmark / epidemiology Sweden / epidemiology Female Cardiovascular Diseases / genetics Autism Spectrum Disorder / genetics Metabolic Diseases / genetics Adult Gene-Environment Interaction Schizophrenia / genetics Middle Aged Attention Deficit Disorder with Hyperactivity / genetics Scandinavians and Nordic People

Journal

Nature communications

ISSN: 2041-1723

Titre abrégé: Nat Commun

Pays: England

ID NLM: 101528555

Informations de publication

Date de publication:
13 Jun 2024

Historique:

received: 05 12 2023

accepted: 07 06 2024

medline: 14 6 2024

pubmed: 14 6 2024

entrez: 13 6 2024

Statut: epublish

Résumé

Mental disorders are leading causes of disability and premature death worldwide, partly due to high comorbidity with cardiometabolic disorders. Reasons for this comorbidity are still poorly understood. We leverage nation-wide health records and near-complete genealogies of Denmark and Sweden (n = 17 million) to reveal the genetic and environmental contributions underlying the observed comorbidity between six mental disorders and 15 cardiometabolic disorders. Genetic factors contributed about 50% to the comorbidity of schizophrenia, affective disorders, and autism spectrum disorder with cardiometabolic disorders, whereas the comorbidity of attention-deficit/hyperactivity disorder and anorexia with cardiometabolic disorders was mainly or fully driven by environmental factors. In this work we provide causal insight to guide clinical and scientific initiatives directed at achieving mechanistic understanding as well as preventing and alleviating the consequences of these disorders.

Identifiants

DOI: 10.1038/s41467-024-49507-3 PMID: 38871766

pubmed: 38871766

doi: 10.1038/s41467-024-49507-3

pii: 10.1038/s41467-024-49507-3

doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

Pagination

5064

Informations de copyright

Références

Momen, N. C. et al. Association between mental disorders and subsequent medical conditions. N. Engl. J. Med. 382, 1721–1731 (2020).

Walker, E. R., McGee, R. E. & Druss, B. G. Mortality in mental disorders and global disease burden implications a systematic review and meta-analysis. JAMA Psychiatry 72, 334–341 (2015).

doi: 10.1001/jamapsychiatry.2014.2502 pubmed: 25671328 pmcid: 4461039

Plana-Ripoll, O. et al. A comprehensive analysis of mortality-related health metrics associated with mental disorders: a nationwide, register-based cohort study. Lancet 394, 1827–1835 (2019).

doi: 10.1016/S0140-6736(19)32316-5 pubmed: 31668728

Nordentoft, M. et al. Excess Mortality, Causes of Death and Life Expectancy in 270,770 Patients with Recent Onset of Mental Disorders in Denmark, Finland and Sweden. PLoS ONE 8, e55176 (2013).

Momen, N. C. et al. Mortality associated with mental disorders and comorbid general medical conditions. JAMA Psychiatry 79, 444–453 (2022).

doi: 10.1001/jamapsychiatry.2022.0347 pubmed: 35353141 pmcid: 8968685

Nicholson, A., Kuper, H. & Hemingway, H. Depression as an aetiologic and prognostic factor in coronary heart disease: A meta-analysis of 6362 events among 146 538 participants in 54 observational studies. Eur. Heart J. 27, 2763–2774 (2006).

Pan, A., Sun, Q., Okereke, O. I., Rexrode, K. M. & Hu, F. B. Depression and risk of stroke morbidity and mortality: A meta-analysis and systematic review. JAMA 306, 1241–1249 (2011).

Ringen, P. A., Engh, J. A., Birkenaes, A. B., Dieset, I. & Andreassen, O. A. Increased mortality in schizophrenia due to cardiovascular disease—a non-systematic review of epidemiology, possible causes and interventions. Front. Psychiatry 5, 137 (2014)

Shen, Q. et al. Cardiovascular disease and subsequent risk of psychiatric disorders: a nationwide sibling-controlled study. Elife 11, e80143 (2022).

doi: 10.7554/eLife.80143 pubmed: 36269046 pmcid: 9718522

Shen, Q. et al. Psychiatric disorders and subsequent risk of cardiovascular disease: a longitudinal matched cohort study across three countries. EClinicalMedicine 61, 102063 (2023).

doi: 10.1016/j.eclinm.2023.102063 pubmed: 37425374 pmcid: 10329128

Penninx, B. W. J. H. Depression and cardiovascular disease: Epidemiological evidence on their linking mechanisms. Neurosci. Biobehav. Rev. 74, 277–286 (2017).

Hagenaars, S. P. et al. Genetic comorbidity between major depression and cardio-metabolic traits, stratified by age at onset of major depression. Am. J. Med. Genet. Part B Neuropsychiatr. Genet. 183, 309–330 (2020).

Sullivan, P. F. et al. Psychiatric genomics: An update and an Agenda. Am. J. Psychiatry 175, 15–27 (2018).

doi: 10.1176/appi.ajp.2017.17030283 pubmed: 28969442

Rødevand, L. et al. Extensive bidirectional genetic overlap between bipolar disorder and cardiovascular disease phenotypes. Transl. Psychiatry 11, 1–9 (2021).

doi: 10.1038/s41398-021-01527-z

Strawbridge, R. J. et al. The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals. Sci. Rep. 11, 1–13 (2021).

doi: 10.1038/s41598-020-79964-x

Howe, L. J. et al. Within-sibship genome-wide association analyses decrease bias in estimates of direct genetic effects. Nat. Genet. 54, 581–592 (2022).

doi: 10.1038/s41588-022-01062-7 pubmed: 35534559 pmcid: 9110300

Zhang, Y. et al. Comparison of methods for estimating genetic correlation between complex traits using GWAS summary statistics. Brief. Bioinform. 22, 1–11 (2021).

Athanasiadis, G. et al. A comprehensive map of genetic relationships among diagnostic categories based on 48.6 million relative pairs from the Danish genealogy. Proc. Natl. Acad. Sci. USA 119, e2118688119 (2022).

doi: 10.1073/pnas.2118688119 pubmed: 35131856 pmcid: 8833149

Hansen, S. N., Overgaard, M., Andersen, P. K. & Parner, E. T. Estimating a population cumulative incidence under calendar time trends. BMC Med. Res. Methodol. 17, 1–10 (2017).

doi: 10.1186/s12874-016-0280-6

Baranova, A., Chandhoke, V., Cao, H. & Zhang, F. Shared genetics and bidirectional causal relationships between type 2 diabetes and attention-deficit/hyperactivity disorder. Gen. Psychiatry 36, 100996 (2023).

doi: 10.1136/gpsych-2022-100996

Wray, N. R. & Gottesman, I. I. Using summary data from the Danish National Registers to estimate heritabilities for schizophrenia, bipolar disorder, and major depressive disorder. Front. Genet. 3, 118 (2012).

doi: 10.3389/fgene.2012.00118 pubmed: 22783273 pmcid: 3387670

Lange, K. & Boehnke, M. Extensions to pedigree analysis. IV. Covariance components models for multivariate traits. Am. J. Med. Genet. 14, 513–524 (1983).

doi: 10.1002/ajmg.1320140315 pubmed: 6859102

Almasy, L. & Blangero, J. Variance component methods for analysis of complex phenotypes. Cold Spring Harb. Protoc. 5, pdb.top77 (2010).

doi: 10.1101/pdb.top77

Pedersen, C. B. et al. The iPSYCH2012 case-cohort sample: New directions for unravelling genetic and environmental architectures of severe mental disorders. Mol. Psychiatry 23, 6–14 (2018).

Schork, A. J. et al. A genome-wide association study of shared risk across psychiatric disorders implicates gene regulation during fetal neurodevelopment. Nat. Neurosci. 22, 353–361 (2019).

Lee, S. H., Wray, N. R., Goddard, M. E. & Visscher, P. M. Estimating missing heritability for disease from genome-wide association studies. Am. J. Hum. Genet. 88, 294–305 (2011).

doi: 10.1016/j.ajhg.2011.02.002 pubmed: 21376301 pmcid: 3059431

Zolpidem (Oral Route) Side Effects—Mayo Clinic. https://www.mayoclinic.org/drugs-supplements/clozapine-oral-route/side-effects/drg-20066859?p=1 .

Springall, G. A. C. et al. Long-term cardiovascular consequences of adolescent anorexia nervosa. Pediatr. Res. 94, 1457–1464 (2023).

Micali, N., Simonoff, E. & Treasure, J. Risk of major adverse perinatal outcomes in women with eating disorders. Br. J. Psychiatry 190, 255–259 (2007).

doi: 10.1192/bjp.bp.106.020768 pubmed: 17329747

Pasman, J. A. et al. Epidemiological overview of major depressive disorder in Scandinavia using nationwide registers. Lancet Reg. Heal. Eur. 29, 100621 (2023).

doi: 10.1016/j.lanepe.2023.100621

Pedersen, C. B. The Danish civil registration system. Scand. J. Public Health 39, 22–25 (2011).

Pedersen, C. B., Gøtzsche, H., Møller, J. Ø. & Mortensen, P. B. The danish civil registration system. A cohort of eight million persons. Dan. Med. Bull. 53, 441–449 (2006).

pubmed: 17150149

Schmidt, M. et al. The Danish National patient registry: A review of content, data quality, and research potential. Clin. Epidemiol. 7, 449–490 (2015).

Mors, O., Perto, G. P. & Mortensen, P. B. The Danish psychiatric central research register. Scand. J. Public Health 39, 22–25 (2011).

World Health Organization. The ICD-10 Classification of Mental and Behavioural Disorders. Clin. Descr. Diagnostic Guidel. 1–267 (1992).

Sundhedsdatastyrelsen. Klassifikation af sygdomme. Webpage (2019).

Nørgaard-Pedersen, B. & Hougaard, D. M. Storage policies and use of the Danish Newborn Screening Biobank. J. Inherit. Metab. Dis. 4, 530–536 (2007).

O’Connell, J. et al. Haplotype estimation for biobank-scale data sets. Nat. Genet. 48, 817–820 (2016).

Howie, B. N., Donnelly, P. & Marchini, J. A flexible and accurate genotype imputation method for the next generation of genome-wide association studies. PLoS Genet. 5, 1000529 (2009).

Auton, A. et al. A global reference for human genetic variation. Nature 526, 68–74 (2015).

Ludvigsson, J. F. et al. Registers of the Swedish total population and their use in medical research. Eur. J. Epidemiol. 31, 125–136 (2016).

doi: 10.1007/s10654-016-0117-y pubmed: 26769609

Ekbom, A. The Swedish Multi-generation Register. Methods Mol. Biol. 675, 215–220 (2011).

doi: 10.1007/978-1-59745-423-0_10 pubmed: 20949391

Ludvigsson, J. F. et al. External review and validation of the Swedish national inpatient register. BMC Public Health 11, 450 (2011).

doi: 10.1186/1471-2458-11-450 pubmed: 21658213 pmcid: 3142234

Malik, R. et al. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat. Genet. 50, 524–537 (2018).

Van Der Harst, P. & Verweij, N. Identification of 64 novel genetic loci provides an expanded view on the genetic architecture of coronary artery disease. Circ. Res. 122, 433–443 (2018).

Bakker, M. K. et al. Genome-wide association study of intracranial aneurysms identifies 17 risk loci and genetic overlap with clinical risk factors. Nat. Genet. 52, 1303–1313 (2020).

doi: 10.1038/s41588-020-00725-7 pubmed: 33199917 pmcid: 7116530

Shah, S. et al. Genome-wide association and Mendelian randomisation analysis provide insights into the pathogenesis of heart failure. Nat. Commun. 11, 163 (2020).

Vujkovic, M. et al. Discovery of 318 new risk loci for type 2 diabetes and related vascular outcomes among 1.4 million participants in a multi-ancestry meta-analysis. Nat. Genet. 52, 680–691 (2020).

Klarin, D. et al. Genome-wide association analysis of venous thromboembolism identifies new risk loci and genetic overlap with arterial vascular disease. Nat. Genet. 51, 1574–1579 (2019).

Klarin, D. et al. Genome-wide association study of peripheral artery disease in the Million Veteran Program. Nat. Med. 25, 1274–1279 (2019).

Demontis, D. et al. Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nat. Genet. 51, 63–75 (2019).

Watson, H. J. et al. Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa. Nat. Genet. 51, 1207–1214 (2019).

doi: 10.1038/s41588-019-0439-2 pubmed: 31308545 pmcid: 6779477

Grove, J. et al. Identification of common genetic risk variants for autism spectrum disorder. Nat. Genet. 51, 431–444 (2019).

Mullins, N. et al. Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology. Nat. Genet. 53, 817–829 (2021).

doi: 10.1038/s41588-021-00857-4 pubmed: 34002096 pmcid: 8192451

Howard, D. M. et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat. Neurosci. 22, 343–352 (2019).

Trubetskoy, V. et al. Mapping genomic loci implicates genes and synaptic biology in schizophrenia. Nature 604, 502–508 (2022).

doi: 10.1038/s41586-022-04434-5 pubmed: 35396580 pmcid: 9392466

Gadin, J. R., Zetterberg, R., Meijsen, J. & Schork, A. J. Cleansumstats: Converting GWAS sumstats to a common format to facilitate downstream applications. (2022).

Bulik-Sullivan, B. et al. LD score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat. Genet. 47, 291–295 (2015).

Bulik-Sullivan, B. et al. An atlas of genetic correlations across human diseases and traits. Nat. Genet. 47, 1236–1241 (2015).

Reich, T., James, J. W. & Morris, C. A. The use of multiple thresholds in determining the mode of transmission of semi‐continuous traits. Ann. Hum. Genet. 36, 163–184 (1972).

doi: 10.1111/j.1469-1809.1972.tb00767.x pubmed: 4676360

Falconer, D. S. The inheritance of liability to certain diseases, estimated from the incidence among relatives. Ann. Hum. Genet. 29, 51–76 (1965).

doi: 10.1111/j.1469-1809.1965.tb00500.x

Falconer, D. S. & Mackay, T. F. C. Introduction to quantitative genetics. 4, 463 https://doi.org/10.1002/bimj.19620040211 (1996).

Lynch, M., Walsh, B., 1998. Genetics and analysis of quantitative traits. Sinauer Associates, Sunderland, MA, USA. CEUR Workshop Proc. (2017).