Genetic heterogeneity and subtypes of major depression.
Journal
Molecular psychiatry
ISSN: 1476-5578
Titre abrégé: Mol Psychiatry
Pays: England
ID NLM: 9607835
Informations de publication
Date de publication:
03 2022
03 2022
Historique:
received:
31
03
2021
accepted:
26
11
2021
revised:
25
11
2021
pubmed:
9
1
2022
medline:
18
5
2022
entrez:
8
1
2022
Statut:
ppublish
Résumé
Major depression (MD) is a heterogeneous disorder; however, the extent to which genetic factors distinguish MD patient subgroups (genetic heterogeneity) remains uncertain. This study sought evidence for genetic heterogeneity in MD. Using UK Biobank cohort, the authors defined 16 MD subtypes within eight comparison groups (vegetative symptoms, symptom severity, comorbid anxiety disorder, age at onset, recurrence, suicidality, impairment, and postpartum depression; N ~ 3000-47000). To compare genetic component of these subtypes, subtype-specific genome-wide association studies were performed to estimate SNP-heritability, and genetic correlations within subtype comparison and with other related disorders/traits. The findings indicated that MD subtypes were divergent in their SNP-heritability, and genetic correlations both within subtype comparisons and with other related disorders/traits. Three subtype comparisons (vegetative symptoms, age at onset, and impairment) showed significant differences in SNP-heritability; while genetic correlations within subtype comparisons ranged from 0.55 to 0.86, suggesting genetic profiles are only partially shared among MD subtypes. Furthermore, subtypes that are more clinically challenging, e.g., early-onset, recurrent, suicidal, more severely impaired, had stronger genetic correlations with other psychiatric disorders. MD with atypical-like features showed a positive genetic correlation (+0.40) with BMI while a negative correlation (-0.09) was found in those without atypical-like features. Novel genomic loci with subtype-specific effects were identified. These results provide the most comprehensive evidence to date for genetic heterogeneity within MD, and suggest that the phenotypic complexity of MD can be effectively reduced by studying the subtypes which share partially distinct etiologies.
Identifiants
pubmed: 34997191
doi: 10.1038/s41380-021-01413-6
pii: 10.1038/s41380-021-01413-6
pmc: PMC9106834
mid: NIHMS1771796
doi:
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Research Support, N.I.H., Extramural
Langues
eng
Sous-ensembles de citation
IM
Pagination
1667-1675Subventions
Organisme : Medical Research Council
ID : MC_PC_17228
Pays : United Kingdom
Organisme : NIMH NIH HHS
ID : R01 MH077139
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH123724
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH124871
Pays : United States
Organisme : NIMH NIH HHS
ID : U01 MH109528
Pays : United States
Organisme : Medical Research Council
ID : MC_QA137853
Pays : United Kingdom
Informations de copyright
© 2021. The Author(s), under exclusive licence to Springer Nature Limited.
Références
World Health O. Depression and other common mental disorders: global health estimates. 2017. Geneva: World Health Organization; 2017.
Fried EI, Nesse RM. Depression is not a consistent syndrome: an investigation of unique symptom patterns in the STAR*D study. J Affect Disord. 2015;172:96–102.
pubmed: 25451401
doi: 10.1016/j.jad.2014.10.010
Flint J, Kendler KS. The genetics of major depression. Neuron. 2014;81:484–503.
pubmed: 24507187
pmcid: 3919201
doi: 10.1016/j.neuron.2014.01.027
Beijers L, Wardenaar KJ, van Loo HM, Schoevers RA. Data-driven biological subtypes of depression: systematic review of biological approaches to depression subtyping. Mol Psychiatry. 2019;24:888–900.
pubmed: 30824865
doi: 10.1038/s41380-019-0385-5
Cai N, Choi KW, Fried EI. Reviewing the genetics of heterogeneity in depression: operationalizations, manifestations and etiologies. Hum Mol Genet. 2020;29:R10–R18.
pubmed: 32568380
pmcid: 7530517
doi: 10.1093/hmg/ddaa115
Harald B, Gordon P. Meta-review of depressive subtyping models. J Affect Disord. 2012;139:126–40.
pubmed: 21885128
doi: 10.1016/j.jad.2011.07.015
Polderman TJC, Benyamin B, de Leeuw CA, Sullivan PF, van Bochoven A, Visscher PM, et al. Meta-analysis of the heritability of human traits based on fifty years of twin studies. Nat Genet. 2015;47:702–9.
pubmed: 25985137
doi: 10.1038/ng.3285
Sullivan PF, Neale MC, Kendler KS. Genetic epidemiology of major depression: review and meta-analysis. Am J Psychiatry. 2000;157:1552–62.
pubmed: 11007705
doi: 10.1176/appi.ajp.157.10.1552
Kendler KS, Ohlsson H, Lichtenstein P, Sundquist J, Sundquist K. The genetic epidemiology of treated major depression in Sweden. Am J Psychiatry. 2018;175:1137–44.
pubmed: 30021458
doi: 10.1176/appi.ajp.2018.17111251
Fernandez-Pujals AM, Adams MJ, Thomson P, McKechanie AG, Blackwood DHR, Smith BH. et al. Epidemiology and heritability of major depressive disorder, stratified by age of onset, sex, and illness course in generation Scotland: Scottish Family Health Study (GS:SFHS). PLoS One. 2015;10:e0142197–e0142197.
pubmed: 26571028
pmcid: 4646689
doi: 10.1371/journal.pone.0142197
Power RA, Tansey KE, Buttenschøn HN, Cohen-Woods S, Bigdeli T, Hall LS, et al. Genome-wide association for major depression through age at onset stratification: major depressive disorder working group of the Psychiatric Genomics Consortium. Biol Psychiatry. 2017;81:325–35.
pubmed: 27519822
pmcid: 5262436
doi: 10.1016/j.biopsych.2016.05.010
Viktorin A, Meltzer-Brody S, Kuja-Halkola R, Sullivan PF, Landén M, Lichtenstein P, et al. Heritability of perinatal depression and genetic overlap with nonperinatal depression. Am J Psychiatry. 2016;173:158–65.
pubmed: 26337037
doi: 10.1176/appi.ajp.2015.15010085
Wray NR, Ripke S, Mattheisen M, Trzaskowski M, Byrne EM, Abdellaoui A, et al. Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression. Nat Genet. 2018;50:668–81.
pubmed: 29700475
pmcid: 5934326
doi: 10.1038/s41588-018-0090-3
Milaneschi Y, Lamers F, Peyrot WJ, Abdellaoui A, Willemsen G, Hottenga JJ, et al. Polygenic dissection of major depression clinical heterogeneity. Mol Psychiatry. 2016;21:516–22.
pubmed: 26122587
doi: 10.1038/mp.2015.86
Bycroft C, Freeman C, Petkova D, Band G, Elliott LT, Sharp K, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562:203–9.
pubmed: 30305743
pmcid: 6786975
doi: 10.1038/s41586-018-0579-z
Smith DJ, Nicholl BI, Cullen B, Martin D, Ul-Haq Z, Evans J. et al. Prevalence and characteristics of probable major depression and bipolar disorder within UK Biobank: cross-sectional study of 172,751 participants. PLOS One. 2013;8:e75362
pubmed: 24282498
pmcid: 3839907
doi: 10.1371/journal.pone.0075362
Cai N, Revez JA, Adams MJ, Andlauer TFM, Breen G, Byrne EM, et al. Minimal phenotyping yields genome-wide association signals of low specificity for major depression. Nat Genet. 2020;52:437–47.
pubmed: 32231276
pmcid: 7906795
doi: 10.1038/s41588-020-0594-5
Hall LS, Adams MJ, Arnau-Soler A, Clarke TK, Howard DM, Zeng Y, et al. Genome-wide meta-analyses of stratified depression in Generation Scotland and UK Biobank. Transl Psychiatry. 2018;8:9.
pubmed: 29317602
pmcid: 5802463
doi: 10.1038/s41398-017-0034-1
Howard DM, Adams MJ, Clarke T-K, Hafferty JD, Gibson J, Shirali M, et al. Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions. Nat Neurosci. 2019;22:343–52.
pubmed: 30718901
pmcid: 6522363
doi: 10.1038/s41593-018-0326-7
Price AL, Patterson NJ, Plenge RM, Weinblatt ME, Shadick NA, Reich D. Principal components analysis corrects for stratification in genome-wide association studies. Nat Genet. 2006;38:904–9.
pubmed: 16862161
doi: 10.1038/ng1847
Jiang L, Zheng Z, Qi T, Kemper KE, Wray NR, Visscher PM, et al. A resource-efficient tool for mixed model association analysis of large-scale data. Nat Genet. 2019;51:1749–55.
pubmed: 31768069
doi: 10.1038/s41588-019-0530-8
Watanabe K, Taskesen E, van Bochoven A, Posthuma D. Functional mapping and annotation of genetic associations with FUMA. Nat Commun. 2017;8:1826.
pubmed: 29184056
pmcid: 5705698
doi: 10.1038/s41467-017-01261-5
Bulik-Sullivan BK, Loh P-R, Finucane HK, Ripke S, Yang J, Patterson N, et al. LD Score regression distinguishes confounding from polygenicity in genome-wide association studies. Nat Genet. 2015;47:291–5.
pubmed: 25642630
pmcid: 4495769
doi: 10.1038/ng.3211
Peyrot WJ, Price AL. Identifying loci with different allele frequencies among cases of eight psychiatric disorders using CC-GWAS. Nat Genet. 2021;53:445–54.
pubmed: 33686288
pmcid: 8038973
doi: 10.1038/s41588-021-00787-1
Lee SH, Wray NR, Goddard ME, Visscher PM. Estimating missing heritability for disease from genome-wide association studies. Am J Hum Genet. 2011;88:294–305.
pubmed: 21376301
pmcid: 3059431
doi: 10.1016/j.ajhg.2011.02.002
Yap CX, Sidorenko J, Marioni RE, Yengo L, Wray NR, Visscher PM. Misestimation of heritability and prediction accuracy of male-pattern baldness. Nat Commun. 2018;9:2537.
pubmed: 29959328
pmcid: 6026149
doi: 10.1038/s41467-018-04807-3
Ning Z, Pawitan Y, Shen X. High-definition likelihood inference of genetic correlations across human complex traits. Nat Genet. 2020;52:859–64.
pubmed: 32601477
doi: 10.1038/s41588-020-0653-y
Demontis D, Walters RK, Martin J, Mattheisen M, Als TD, Agerbo E, et al. Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder. Nat Genet. 2019;51:63–75.
pubmed: 30478444
doi: 10.1038/s41588-018-0269-7
Grove J, Ripke S, Als TD, Mattheisen M, Walters RK, Won H, et al. Identification of common genetic risk variants for autism spectrum disorder. Nat Genet. 2019;51:431–44.
pubmed: 30804558
pmcid: 6454898
doi: 10.1038/s41588-019-0344-8
Watson HJ, Yilmaz Z, Thornton LM, Hübel C, Coleman JRI, Gaspar HA, et al. Genome-wide association study identifies eight risk loci and implicates metabo-psychiatric origins for anorexia nervosa. Nat Genet. 2019;51:1207–14.
pubmed: 31308545
pmcid: 6779477
doi: 10.1038/s41588-019-0439-2
Stahl EA, Breen G, Forstner AJ, McQuillin A, Ripke S, Trubetskoy V, et al. Genome-wide association study identifies 30 loci associated with bipolar disorder. Nat Genet. 2019;51:793–803.
pubmed: 31043756
pmcid: 6956732
doi: 10.1038/s41588-019-0397-8
Lee JJ, Wedow R, Okbay A, Kong E, Maghzian O, Zacher M, et al. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals. Nat Genet. 2018;50:1112–21.
pubmed: 30038396
pmcid: 6393768
doi: 10.1038/s41588-018-0147-3
Savage JE, Jansen PR, Stringer S, Watanabe K, Bryois J, de Leeuw CA, et al. Genome-wide association meta-analysis in 269,867 individuals identifies new genetic and functional links to intelligence. Nat Genet. 2018;50:912–9.
pubmed: 29942086
pmcid: 6411041
doi: 10.1038/s41588-018-0152-6
Ripke S, Walters JTR, Donovan MC. Mapping genomic loci prioritises genes and implicates synaptic biology in schizophrenia. medRxiv 2020: 2020.2009.2012.20192922.
Pulit SL, Stoneman C, Morris AP, Wood AR, Glastonbury CA, Tyrrell J, et al. Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. Hum Mol Genet. 2019;28:166–74.
pubmed: 30239722
doi: 10.1093/hmg/ddy327
Okbay A, Baselmans BM, De Neve JE, Turley P, Nivard MG, Fontana MA, et al. Genetic variants associated with subjective well-being, depressive symptoms, and neuroticism identified through genome-wide analyses. Nat Genet. 2016;48:624–33.
pubmed: 27089181
pmcid: 4884152
doi: 10.1038/ng.3552
Nagel M, Jansen PR, Stringer S, Watanabe K, de Leeuw CA, Bryois J, et al. Meta-analysis of genome-wide association studies for neuroticism in 449,484 individuals identifies novel genetic loci and pathways. Nat Genet. 2018;50:920–7.
pubmed: 29942085
doi: 10.1038/s41588-018-0151-7
Glanville KP, Coleman JRI, Howard DM, Pain O, Hanscombe KB, Jermy B, et al. Multiple measures of depression to enhance validity of major depressive disorder in the UK Biobank. BJPsych Open. 2021;7:e44.
pubmed: 33541459
pmcid: 8058908
doi: 10.1192/bjo.2020.145
Badini I, Coleman JRI, Hagenaars SP, Hotopf M, Breen G, Lewis CM, et al. Depression with atypical neurovegetative symptoms shares genetic predisposition with immuno-metabolic traits and alcohol consumption. Psychol Med 2020: 1–11. https://www.cambridge.org/core/journals/psychological-medicine/article/depression-with-atypical-neurovegetative-symptoms-shares-genetic-predisposition-with-immunometabolic-traits-and-alcohol-consumption/1CEB0F0450730158C53A8E55C18F9EE6 .
Milaneschi Y, Lamers F, Penninx BWJH. Dissecting depression biological and clinical heterogeneity—the importance of symptom assessment resolution. JAMA Psychiatry 2021;78:341.
pubmed: 33471038
doi: 10.1001/jamapsychiatry.2020.4373
Kaufman J, Charney D. Comorbidity of mood and anxiety disorders. Depress Anxiety. 2000;12:69–76.
pubmed: 11098417
doi: 10.1002/1520-6394(2000)12:1+<69::AID-DA9>3.0.CO;2-K
Thorp JG, Marees AT, Ong J-S, An J, MacGregor S, Derks EM. Genetic heterogeneity in self-reported depressive symptoms identified through genetic analyses of the PHQ-9. Psychol Med. 2020;50:2385–96.
pubmed: 31530331
doi: 10.1017/S0033291719002526
Lam M, Chen CY, Li Z, Martin AR, Bryois J, Ma X, et al. Comparative genetic architectures of schizophrenia in East Asian and European populations. Nat Genet. 2019;51:1670–8.
pubmed: 31740837
pmcid: 6885121
doi: 10.1038/s41588-019-0512-x
Baselmans BML, Yengo L, van Rheenen W, Wray NR. Risk in relatives, heritability, SNP-based heritability, and genetic correlations in psychiatric disorders: a review. Biol Psychiatry 2021;89:11–9.
pubmed: 32736793
doi: 10.1016/j.biopsych.2020.05.034
Milaneschi Y, Lamers F, Peyrot WJ, Baune BT, Breen G, Dehghan A, et al. Genetic association of major depression with atypical features and obesity-related immunometabolic dysregulations. JAMA Psychiatry. 2017;74:1214–25.
pubmed: 29049554
pmcid: 6396812
doi: 10.1001/jamapsychiatry.2017.3016
Tyrrell J, Zheng J, Beaumont R, Hinton K, Richardson TG, Wood AR, et al. Genetic predictors of participation in optional components of UK Biobank. Nat Commun. 2021;12:886.
pubmed: 33563987
pmcid: 7873270
doi: 10.1038/s41467-021-21073-y
Schwabe I, Milaneschi Y, Gerring Z, Sullivan PF, Schulte E, Suppli NP, et al. Unraveling the genetic architecture of major depressive disorder: merits and pitfalls of the approaches used in genome-wide association studies. Psychol Med. 2019;49:2646–56.
pubmed: 31559935
pmcid: 6877467
doi: 10.1017/S0033291719002502
Fry A, Littlejohns TJ, Sudlow C, Doherty N, Adamska L, Sprosen T, et al. Comparison of sociodemographic and health-related characteristics of UK biobank participants with those of the general population. Am J Epidemiol. 2017;186:1026–34.
pubmed: 28641372
pmcid: 5860371
doi: 10.1093/aje/kwx246