Abstract
Although large genome-wide association studies (GWAS) of major depressive disorder (MDD) have identified many significant loci, the SNP-based heritability remains notably low, which might be due to etiological heterogeneity in existing samples. Here, we test the utility of targeting the severe end of the MDD spectrum through genome-wide SNP genotyping of 2725 cases who received electroconvulsive therapy (ECT) for a major depressive episode (MDE) and 4035 controls. A subset of cases (n = 1796) met a narrow case definition (MDE occurring in the context of MDD). Standard GWAS quality control procedures and imputation were conducted. SNP heritability and genetic correlations with other traits were estimated using linkage disequilibrium score regression. Results were compared with MDD cases of mild-moderate severity receiving internet-based cognitive behavioral therapy (iCBT) and summary results from the Psychiatric Genomics Consortium (PGC). The SNP-based heritability was estimated at 29–34% (SE: 6%) for the narrow case definition, considerably higher than the 6.5–8.0% estimate in the most recent PGC MDD study. Our severe MDE cases had smaller genetic correlations with neurodevelopmental disorders and neuroticism than PGC MDD cases but higher genetic risk scores for bipolar disorder than iCBT MDD cases. One genome-wide significant locus was identified (rs114583506, P = 5e−8) in an intron of HLA-B in the major histocompatibility locus on chr6. These results indicate that individuals receiving ECT for an MDE have higher burden of common variant risk loci than individuals with mild-moderate MDD. Furthermore, severe MDE shows stronger relations with other severe adult-onset psychiatric disorders but weaker relations with personality and stress-related traits than mild-moderate MDD. These findings suggest a different genetic architecture at the severest end of the spectrum, and support further study of the severest MDD cases as an extreme phenotype approach to understand the etiology of MDD.
Similar content being viewed by others
Data availability
Summary statistics are available for download on the Psychiatric Genomic Consortium website.
References
Hasin DS, Sarvet AL, Meyers JL, Saha TD, Ruan WJ, Stohl M, et al. Epidemiology of adult DSM-5 major depressive disorder and its specifiers in the United States. JAMA Psychiatry. 2018;75:336–46.
Ekman M, Granström O, Omerov S, Jacob J, Landen M. The societal cost of depression: evidence from 10,000 Swedish patients in psychiatric care. J Affect Disord. 2013;150:790–7.
Levinson DF, Mostafavi S, Milaneschi Y, Rivera M, Ripke S, Wray NR, et al. Genetic studies of major depressive disorder: why are there no genome-wide association study findings and what can we do about it? Biol Psychiatry. 2014;76:510–2.
Sullivan PF, Neale MC, Kendler KS. Genetic epidemiology of major depression: review and meta-analysis. Am J Psychiatry. 2000;157:1552–62.
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.
McIntosh AM, Sullivan PF, Lewis CM. Uncovering the genetic architecture of major depression. Neuron. 2019;102:91–103.
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.
Sullivan PF, Geschwind DH. Defining the genetic, genomic, cellular, and diagnostic architectures of psychiatric disorders. Cell. 2019;177:162–83.
Hyde CL, Nagle MW, Tian C, Chen X, Paciga SA, Wendland JR, et al. Identification of 15 genetic loci associated with risk of major depression in individuals of European descent. Nat Genet. 2016;48:1031–6.
Howard DM, Adams MJ, Shirali M, Clarke T-K, Marioni RE, Davies G, et al. Genome-wide association study of depression phenotypes in UK Biobank identifies variants in excitatory synaptic pathways. Nat Commun. 2018;16:1470.
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.
Guey LT, Kravic J, Melander O, Burtt NP, Laramie JM, Lyssenko V, et al. Power in the phenotypic extremes: a simulation study of power in discovery and replication of rare variants. Genet Epidemiol. 2011;35:236–46.
Li D, Lewinger JP, Gauderman WJ, Murcray CE, Conti D. Using extreme phenotype sampling to identify the rare causal variants of quantitative traits in association studies. Genet Epidemiol. 2011;35:790–9.
Brus O, Cao Y, Gustafsson E, Hultén M, Landen M, Lundberg J, et al. Self-assessed remission rates after electroconvulsive therapy of depressive disorders. Eur Psychiatry. 2017;45:154–60.
Nordenskjöld A, Knorring L, von, Engström I. Predictors of the short-term responder rate of electroconvulsive therapy in depressive disorders—a population based study. BMC Psychiatry. 2012;12:115.
Carney S, Cowen P, Geddes J, Goodwin G, Rogers R, Dearness K, et al. Efficacy and safety of electroconvulsive therapy in depressive disorders: a systematic review and meta-analysis. Lancet. 2003;361:799–808.
Lisanby SH. Electroconvulsive therapy for depression. N Engl J Med. 2007;357:1939–45.
Pagnin D, de Queiroz V, Pini S, Cassano GB. Efficacy of ECT in depression: a meta-analytic review. J ECT. 2004;20:13.
Soda T, McLoughlin DM, Clark SR, Oltedal L, Kessler U, Haavik J, et al. International Consortium on the Genetics of Electroconvulsive Therapy and Severe Depressive Disorders (Gen-ECT-ic). Eur Arch Psychiatry Clin Neurosci. 2019. https://doi.org/10.1007/s00406-019-01087-w.
Zabaneh D, Krapohl E, Gaspar HA, Curtis C, Lee SH, Patel H, et al. A genome-wide association study for extremely high intelligence. Mol Psychiatry. 2018;23:1226–32.
Benyamin B, Pourcain BS, Davis OS, Davies G, Hansell NK, Brion M-JA, et al. Childhood intelligence is heritable, highly polygenic and associated with FNBP1L. Mol Psychiatry. 2014;19:253–8.
CONVERGE Consortium. Sparse whole-genome sequencing identifies two loci for major depressive disorder. Nature. 2015;523:588–91.
Nordenskjöld A. Kvalitetsregister ECT—Årsrapport 2014. Region Örebro län; Örebro, Sweden. 2014.
Nordanskog P, Hultén M, Landén M, Lundberg J, von Knorring L, Nordenskjöld A. Electroconvulsive therapy in Sweden 2013: data From the National Quality Register for ECT. J ECT. 2015;31:263–7.
Svanborg P, Åsberg M. A comparison between the Beck Depression Inventory (BDI) and the self-rating version of the Montgomery Åsberg Depression Rating Scale (MADRS). J Affect Disord. 2001;64:203–16.
Ahmad I. Validity of diagnoses and treatment dates in the Swedish National Quality Register for Electroconvulsive Therapy. Örebro: Örebro University; 2020.
Ludvigsson JF, Andersson E, Ekbom A, Feychting M, Kim J-L, Reuterwall C, et al. External review and validation of the Swedish national inpatient register. BMC Public Health. 2011;11:450.
Ludvigsson JF, Svedberg P, Olén O, Bruze G, Neovius M. The longitudinal integrated database for health insurance and labour market studies (LISA) and its use in medical research. Eur J Epidemiol. 2019;34:423–37.
Thornton LM, Munn-Chernoff MA, Baker JH, Juréus A, Parker R, Henders AK, et al. The Anorexia Nervosa Genetics Initiative (ANGI): overview and methods. Contemp Clin Trials. 2018;74:61–9.
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.
Almqvist C, Adami H-O, Franks PW, Groop L, Ingelsson E, Kere J, et al. LifeGene—a large prospective population-based study of global relevance. Eur J Epidemiol. 2011;26:67–77.
Andersson E, Crowley JJ, Lindefors N, Ljótsson B, Hedman-Lagerlöf E, Boberg J, et al. Genetics of response to cognitive behavior therapy in adults with major depression: a preliminary report. Mol Psychiatry. 2019;24:484–90.
Lam M, Awasthi S, Watson HJ, Goldstein J, Panagiotaropoulou G, Trubetskoy V, et al. RICOPILI: rapid imputation for COnsortias PIpeLIne. Bioinformatics. 2020;36:930–3.
McCarthy S, Das S, Kretzschmar W, Delaneau O, Wood AR, Teumer A, et al. A reference panel of 64,976 haplotypes for genotype imputation. Nat Genet. 2016;48:1279–83.
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.
Yang J, Lee SH, Goddard ME, Visscher PM. GCTA: a tool for genome-wide complex trait analysis. Am J Hum Genet. 2011;88:76–82.
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.
Pardiñas AF, Holmans P, Pocklington AJ, Escott-Price V, Ripke S, Carrera N, et al. Common schizophrenia alleles are enriched in mutation-intolerant genes and in regions under strong background selection. Nat Genet. 2018;50:381–9.
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.
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.
Salk RH, Hyde JS, Abramson LY. Gender differences in depression in representative national samples: meta-analyses of diagnoses and symptoms. Psychol Bull. 2017;143:783–822.
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.
Segerstrom SC, Tsao JCI, Alden LE, Craske MG. Worry and rumination: repetitive thought as a concomitant and predictor of negative mood. Cogn Ther Res. 2000;24:671–88.
Coleman JRI, Gaspar HA, Bryois J, Bipolar Disorder Working Group of the Psychiatric Genomics Consortium, Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Breen G. The genetics of the mood disorder spectrum: genome-wide association analyses of more than 185,000 cases and 439,000 controls. Biol Psychiatry. 2020;88:169–84.
Caspi A, Moffitt TE. All for one and one for all: mental disorders in one dimension. Am J Psychiatry. 2018;175:831–44.
Brainstorm Consortium, Anttila V, Bulik-Sullivan B, Finucane HK, Walters RK, Bras J, et al. Analysis of shared heritability in common disorders of the brain. Science. 2018;360:eaap8757.
Selzam S, Coleman JRI, Caspi A, Moffitt TE, Plomin R. A polygenic p factor for major psychiatric disorders. Transl Psychiatry. 2018;8:1–9.
Nievergelt CM, Maihofer AX, Klengel T, Atkinson EG, Chen C-Y, Choi KW, et al. International meta-analysis of PTSD genome-wide association studies identifies sex- and ancestry-specific genetic risk loci. Nat Commun. 2019;10:4558.
Khramtsova EA, Davis LK, Stranger BE. The role of sex in the genomics of human complex traits. Nat Rev Genet. 2019;20:173–90.
Acknowledgements
We first thank the study participants. We also thank the staff at participating ECT-units in Danderyd, Huddinge, Hudiksvall, Sahlgrenska, Umeå, Uppsala, and Örebro for recruiting patients; the Swedish National Quality Register for ECT (Q-ECT) for providing data; and the BBMRI.se and KI Biobank at Karolinska Institutet for professional biobank service. We thank PREFECT data collectors Marie Lundin, Birgitta Ohlander, Milka Krestelica, Radja Dawoud, Martina Wennberg, and PREFECT data manager Bozenna Illadou. The PREFECT study was funded by the Swedish foundation for Strategic Research (KF10-0039), and grants from the Swedish Research Council (2018-02653). PFS was supported by the Swedish Research Council (Vetenskapsrådet, award D0886501), the Horizon 2020 Program of the European Union (COSYN, RIA Grant Agreement No. 610307), and US NIMH (U01 MH109528 and R01 MH077139). CMB was supported by Swedish Research Council (Vetenskapsrådet, award: 538-2013-8864) and US NIMH (R01MH120170, R01MH119084, and U01 MH109528). CR was supported by the Swedish Research Council (2018-02487) and the Swedish Research Council for Health, Working Life and Welfare (2018-00221). CCC was supported by a US Fulbright grant. YL is in part supported by a 2018 NARSAD Young Investigator Grant from the Brain & Behaviour Research Foundation and US NIMH (R01 MH123724).
Author information
Authors and Affiliations
Corresponding authors
Ethics declarations
Conflict of interest
ML declares that, over the past 36 months, he has received lecture honoraria from Lundbeck pharmaceutical. PFS reports the following potentially competing financial interests. Current: Lundbeck (advisory committee, grant recipient), RBNC Therapeutics (advisory committee, stock ownership). CMB reports: Shire (grant recipient, Scientific Advisory Board member); Idorsia (consultant); Pearson (author, royalty recipient). AJ is currently employed at the Swedish Medical Products Agency, SE-75103 Uppsala, Sweden. The views expressed in this paper are the personal views of the authors and not necessarily the views of the government agency. AJ’s contribution to this work was done before he started his employment at the MPA.
Additional information
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary information
Rights and permissions
About this article
Cite this article
Clements, C.C., Karlsson, R., Lu, Y. et al. Genome-wide association study of patients with a severe major depressive episode treated with electroconvulsive therapy. Mol Psychiatry 26, 2429–2439 (2021). https://doi.org/10.1038/s41380-020-00984-0
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1038/s41380-020-00984-0
- Springer Nature Limited
This article is cited by
-
The genetic basis of major depressive disorder
Molecular Psychiatry (2023)
-
Towards a multilevel model of major depression: genes, immuno-metabolic function, and cortico-striatal signaling
Translational Psychiatry (2023)
-
Polygenic risk scores of lithium response and treatment resistance in major depressive disorder
Translational Psychiatry (2023)
-
Ten challenges for clinical translation in psychiatric genetics
Nature Genetics (2022)
-
Exploring the genetic heterogeneity in major depression across diagnostic criteria
Molecular Psychiatry (2021)