Abstract
Background
Major depressive disorder (MDD) is a leading cause of disease-associated disability,
with much of the increased burden due to psychiatric and medical comorbidity. This
comorbidity partly reflects common genetic influences across conditions. Integrating
molecular-genetic tools with health records enables tests of association with the
broad range of physiological and clinical phenotypes. However, standard phenome-wide
association studies analyze associations with individual genetic variants. For polygenic
traits such as MDD, aggregate measures of genetic risk may yield greater insight into
associations across the clinical phenome.
Methods
We tested for associations between a genome-wide polygenic risk score for MDD and
medical and psychiatric traits in a phenome-wide association study of 46,782 unrelated,
European-ancestry participants from the Michigan Genomics Initiative.
Results
The MDD polygenic risk score was associated with 211 traits from 15 medical and psychiatric
disease categories at the phenome-wide significance threshold. After excluding patients
with depression, continued associations were observed with respiratory, digestive,
neurological, and genitourinary conditions; neoplasms; and mental disorders. Associations
with tobacco use disorder, respiratory conditions, and genitourinary conditions persisted
after accounting for genetic overlap between depression and other psychiatric traits.
Temporal analyses of time-at-first-diagnosis indicated that depression disproportionately
preceded chronic pain and substance-related disorders, while asthma disproportionately
preceded depression.
Conclusions
The present results can inform the biological links between depression and both mental
and systemic diseases. Although MDD polygenic risk scores cannot currently forecast
health outcomes with precision at the individual level, as molecular-genetic discoveries
for depression increase, these tools may augment risk prediction for medical and psychiatric
conditions.
Keywords
To read this article in full you will need to make a payment
Purchase one-time access:
Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online accessOne-time access price info
- For academic or personal research use, select 'Academic and Personal'
- For corporate R&D use, select 'Corporate R&D Professionals'
Subscribe:
Subscribe to Biological PsychiatryAlready a print subscriber? Claim online access
Already an online subscriber? Sign in
Register: Create an account
Institutional Access: Sign in to ScienceDirect
References
- Recent trends and increasing differences in life expectancy present opportunities for multidisciplinary research on aging.Nat Aging. 2021; 1: 12-13
- Global, regional, and national incidence, prevalence, and years lived with disability for 354 diseases and injuries for 195 countries and territories, 1990–2017: A systematic analysis for the Global Burden of Disease Study 2017 [published correction appears in Lancet 2019; 393:e44].Lancet. 2018; 392: 1789-1858
- Major depression as a risk factor for chronic disease incidence: Longitudinal analyses in a general population cohort.Gen Hosp Psychiatry. 2008; 30: 407-413
- Depression as a risk factor for diabetes: A meta-analysis of longitudinal studies.J Clin Psychiatry. 2013; 74: 31-37
- Association of mental disorders with subsequent chronic physical conditions: World Mental Health Surveys from 17 countries.JAMA Psychiatry. 2016; 73: 150-158
- Depressive symptoms, health behaviors, and risk of cardiovascular events in patients with coronary heart disease.JAMA. 2008; 300: 2379-2388
- Depression and immune function: Central pathways to morbidity and mortality.J Psychosom Res. 2002; 53: 873-876
- Depression and cardiovascular disease: Epidemiological evidence on their linking mechanisms.Neurosci Biobehav Rev. 2017; 74: 277-286
- Association between lifetime affective symptoms and premature mortality.JAMA Psychiatry. 2020; 77: 806-813
- Chronic medical conditions and metabolic syndrome as risk factors for incidence of major depressive disorder: A longitudinal study based on 4.7 million adults in South Korea.J Affect Disord. 2019; 257: 486-494
- A systematic review and meta-analysis of demoralization and depression in patients with cancer.Psychosomatics. 2015; 56: 634-643
- Genetic epidemiology of major depression: Review and meta-analysis.Am J Psychiatry. 2000; 157: 1552-1562
- The genetic overlap between mood disorders and cardiometabolic diseases: A systematic review of genome wide and candidate gene studies.Transl Psychiatry. 2017; 7e1007
- Major depression and coronary artery disease in the Swedish Twin Registry: Phenotypic, genetic, and environmental sources of comorbidity.Arch Gen Psychiatry. 2009; 66: 857-863
- A twin study of depression symptoms, hypertension, and heart disease in middle-aged men.Psychosom Med. 2003; 65: 548-557
- Chronic pain, depression and cardiovascular disease linked through a shared genetic predisposition: Analysis of a family-based cohort and twin study.PLoS One. 2017; 12e0170653
- Shared mechanisms between coronary heart disease and depression: Findings from a large UK general population-based cohort [published correction appears in Mol Psychiatry 2021; 26:3659–3661].Mol Psychiatry. 2020; 25: 1477-1486
- The familial and genetic contribution to the association between depression and cardiovascular disease: A twin cohort study.Mol Psychiatry. 2020; 26: 4245-4253
- A phenome-wide association and Mendelian randomisation study of polygenic risk for depression in UK Biobank.Nat Commun. 2020; 11: 2301
- Phenome-wide analysis of genome-wide polygenic scores.Mol Psychiatry. 2016; 21: 1188-1193
- Polygenic loading for major depression is associated with specific medical comorbidity.Transl Psychiatry. 2017; 7: e1238
- Association between major depressive disorder and multiple disease outcomes: A phenome-wide Mendelian randomisation study in the UK Biobank.Mol Psychiatry. 2020; 25: 1469-1476
- Polygenic risk of psychiatric disorders exhibits cross-trait associations in electronic health record data from European ancestry individuals.Biol Psychiatry. 2021; 89: 236-245
- Genetic risk for major depressive disorder and loneliness in sex-specific associations with coronary artery disease.Mol Psychiatry. 2021; 26: 4254-4264
- Penetrance and pleiotropy of polygenic risk scores for schizophrenia in 106,160 patients across four health care systems.Am J Psychiatry. 2019; 176: 846-855
- Psychiatry’s opportunity to prevent the rising burden of age-related disease.JAMA Psychiatry. 2019; 76: 461-462
- Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions.Nat Neurosci. 2019; 22: 343-352
- Association of polygenic risk scores for multiple cancers in a phenome-wide study: Results from the Michigan Genomics Initiative.Am J Hum Genet. 2018; 102: 1048-1061
- Genetic architecture of 11 major psychiatric disorders at biobehavioral, functional genomic, and molecular genetic levels of analysis.Nat Genet. 2022; 54: 548-559
- Genomic relationships, novel loci, and pleiotropic mechanisms across eight psychiatric disorders.Cell. 2019; 179: 1469-1482.e11
- MEPE loss-of-function variant associates with decreased bone mineral density and increased fracture risk.Nat Commun. 2020; 11: 4093
- The Michigan Genomics Initiative: A biobank linking genotypes and electronic clinical records in Michigan Medicine patients.medRxiv. 2021; https://doi.org/10.1101/2021.12.15.21267864
- Exploring various polygenic risk scores for skin cancer in the phenomes of the Michigan Genomics Initiative and the UK Biobank with a visual catalog: PRSWeb.PLoS Genet. 2019; 15e1008202
- Ancestry estimation and control of population stratification for sequence-based association studies.Nat Genet. 2014; 46: 409-415
- Worldwide human relationships inferred from genome-wide patterns of variation.Science. 2008; 319: 1100-1104
- Robust relationship inference in genome-wide association studies.Bioinformatics. 2010; 26: 2867-2873
- Identifying large sets of unrelated individuals and unrelated markers.Source Code Biol Med. 2014; 9: 6
- A reference panel of 64,976 haplotypes for genotype imputation.Nat Genet. 2016; 48: 1279-1283
- R PheWAS: Data analysis and plotting tools for phenome-wide association studies in the R environment.Bioinform. 2014; 30: 2375-2376
- Systematic comparison of phenome-wide association study of electronic medical record data and genome-wide association study data.Nat Biotechnol. 2013; 31: 1102-1110
- Phecode Map 1.2 with ICD-9 Codes.(Available at:)https://phewascatalog.org/phecodesDate accessed: March 3, 2022
- Evaluating phecodes, clinical classification software, and ICD-9-CM codes for phenome-wide association studies in the electronic health record.PLoS One. 2017; 12e0175508
- Mapping ICD-10 and ICD-10-CM codes to phecodes: Workflow development and initial evaluation.JMIR Med Inform. 2019; 7e14325
- PheWAS Resources: Phecode Map 1.2 with ICD-10cm Codes (beta).(Available at:)https://phewascatalog.org/phecodes_icd10cmDate accessed: March 3, 2022
- Using phecodes for research with the electronic health record: From PheWAS to PheRS.Annu Rev Biomed Data Sci. 2021; 4: 1-19
- MatchIt: Nonparametric preprocessing for parametric causal inference.J Stat Softw. 2011; 42: 1-28
- Polygenic prediction via Bayesian regression and continuous shrinkage priors.Nat Commun. 2019; 10: 1776
- Genetic prediction of complex traits with polygenic scores: A statistical review.Trends Genet. 2021; 37: 995-1011
- Bidirectional associations between clinically relevant depression or anxiety and COPD: A systematic review and meta-analysis.Chest. 2013; 144: 766-777
- Longitudinal associations of mental disorders with physical diseases and mortality among 2.3 million New Zealand citizens.JAMA Netw Open. 2021; 4e2033448
- The safety, tolerability and risks associated with the use of newer generation antidepressant drugs: A critical review of the literature.Psychother Psychosom. 2016; 85: 270-288
- Urinary side effects of psychotropic drugs: A systematic review and metanalysis.Neurourol Urodyn. 2021; 40: 1333-1348
- The structure of genetic and environmental risk factors for syndromal and subsyndromal common DSM-IV axis I and all axis II disorders.Am J Psychiatry. 2011; 168: 29-39
- Psychiatric genetics and the structure of psychopathology [published correction appears in Mol Psychiatry 2019; 24:471.Mol Psychiatry. 2019; 24: 409-420
- Analysis of shared heritability in common disorders of the brain.Science. 2018; 360 (6395):eaap8757.
- Depression and cancer risk: A systematic review and meta-analysis.Public Health. 2017; 149: 138-148
- Depression and anxiety in relation to cancer incidence and mortality: A systematic review and meta-analysis of cohort studies.Mol Psychiatry. 2020; 25: 1487-1499
- Cancer and Alzheimer’s disease inverse relationship: An age-associated diverging derailment of shared pathways.Mol Psychiatry. 2021; 26: 280-295
- Heterogeneity in polygenic scores for common human traits.bioRxiv. 2017; https://doi.org/10.1101/106062
- Phenotypic annotation: Using polygenic scores to translate discoveries from genome-wide association studies from the top down.Curr Dir Psychol Sci. 2019; 28: 82-90
Article info
Publication history
Published online: June 10, 2022
Accepted:
June 2,
2022
Received in revised form:
April 1,
2022
Received:
October 17,
2021
Identification
Copyright
© 2022 Society of Biological Psychiatry.
ScienceDirect
Access this article on ScienceDirectLinked Article
- Depression Genetics as a Window Into Physical and Mental HealthBiological PsychiatryVol. 92Issue 12
- PreviewPreventing depression and its concomitant health issues is critical to promote healthy aging and extend the lifespan. It is well known that depression and poor health are intertwined (1), but why they are intertwined remains an area of active inquiry. The idea that depression may share underlying biology—including common genetic mechanisms—with other health conditions is appealing, as knowledge of such mechanisms could inform treatments to ameliorate both. To that end, year upon year we are learning more about the complex genetic architecture of major depression (2), which provides us in theory with increasingly powerful genome-wide tools to study the relationship between depression and health.
- Full-Text
- Preview