Complex trait methylation scores in the prediction of major depressive disorder

Genetics of DNA Methylation Consortium

doi:10.1016/j.ebiom.2022.104000

Complex trait methylation scores in the prediction of major depressive disorder

Genetics of DNA Methylation Consortium

Research output: Contribution to Journal › Article › Academic › peer-review

Abstract

Background: DNA methylation (DNAm) is associated with time-varying environmental factors that contribute to major depressive disorder (MDD) risk. We sought to test whether DNAm signatures of lifestyle and biochemical factors were associated with MDD to reveal dynamic biomarkers of MDD risk that may be amenable to lifestyle interventions. Methods: Here, we calculated methylation scores (MS) at multiple p-value thresholds for lifestyle (BMI, smoking, alcohol consumption, and educational attainment) and biochemical (high-density lipoprotein (HDL) and total cholesterol) factors in Generation Scotland (GS) (N=9,502) and in a replication cohort (ALSPAC_adults, N=565), using CpG sites reported in previous well-powered methylome-wide association studies. We also compared their predictive accuracy for MDD to a MDD MS in an independent GS sub-sample (N=4,432). Findings: Each trait MS was significantly associated with its corresponding phenotype in GS (β_range=0.089–1.457) and in ALSPAC (β_range=0.078–2.533). Each MS was also significantly associated with MDD before and after adjustment for its corresponding phenotype in GS (β_range=0.053–0.145). After accounting for relevant lifestyle factors, MS for educational attainment (β=0.094) and alcohol consumption (MS_p-value<0.01–0.5; β_range=-0.069–0.083) remained significantly associated with MDD in GS. Smoking (AUC=0.569) and educational attainment (AUC=0.585) MSs could discriminate MDD from controls better than the MDD MS (AUC=0.553) in the independent GS sub-sample. Analyses implicating MDD did not replicate across ALSPAC, although the direction of effect was consistent for all traits when adjusting for the MS corresponding phenotypes. Interpretation: We showed that lifestyle and biochemical MS were associated with MDD before and after adjustment for their corresponding phenotypes (p_nominal<0.05), but not when smoking, alcohol consumption, and BMI were also included as covariates. MDD results did not replicate in the smaller, female-only independent ALSPAC cohort (N_ALSPAC=565; N_GS=9,502), potentially due to demographic differences or low statistical power, but effect sizes were consistent with the direction reported in GS. DNAm scores for modifiable MDD risk factors may contribute to disease vulnerability and, in some cases, explain additional variance to their observed phenotypes. Funding: Wellcome Trust.

Original language	English
Article number	104000
Pages (from-to)	1-19
Number of pages	19
Journal	Ebiomedicine
Volume	79
Early online date	28 Apr 2022
DOIs	https://doi.org/10.1016/j.ebiom.2022.104000
Publication status	Published - May 2022

Bibliographical note

Funding Information:
MCB has received financial support from Edinburgh Neuroscience Researcher's Fund, Wellcome Trust Institutional Translational Partnership Award Innovation Competition, and Research Adaptation Fund to attend courses and conferences in the past. RMW has received financial support from Alzheimer's Research UK (ARUK) to attend the ARUK annual conference (2021 and 2022). JLM is supported by the UK Medical Research Council Integrative Epidemiology Unit at the University of Bristol. AC is a University of Edinburgh Medical Research Ethics Committee member. JvdD was supported by NWO Large Scale infrastructures, X-Omics (184.034.019). Remaining authors report no conflicts of interest.

Funding Information:
This research was funded in whole, or in part, by the Wellcome Trust [216767/Z/19/Z]. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. Generation Scotland is currently supported by the Wellcome Trust [216767/Z/19/Z] and by the Wellcome Trust Investigator Award in Science 01/06/2021 to 31/05/26 ‘Exploiting genomic approaches to identify the environmental basis of depression’. (Reference: 220857/Z/20/Z) to McIntosh AM (PI). The DNA methylation profiling and data preparation was supported by Wellcome Investigator Award 220857/Z/20/Z and Grant 104036/Z/14/Z (PI for both grants: McIntosh AM) and through funding from NARSAD (Ref: 27404; PI: Dr DM Howard and Ref: 21956; PI Dr Kathryn Evans) and the Royal College of Physicians of Edinburgh (Sim Fellowship; PI: Dr HC Whalley). Genotyping of the GS:SFHS samples was funded by the MRC and Wellcome Trust [104036/Z/14/Z]. Generation Scotland also receives support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006]. Dr DM Howard is supported by a Sir Henry Wellcome Postdoctoral Fellowship (Reference 213674/Z/18/Z). Dr M Barbu is supported by a Guarantors of Brain Non-clinical Post-Doctoral Fellowship.

Funding Information:
The UK Medical Research Council and Wellcome (Grant Ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. A comprehensive list of grants funding is available on the ALSPAC website ( http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf ).

Publisher Copyright:
© 2022 The Authors

Funding

MCB has received financial support from Edinburgh Neuroscience Researcher's Fund, Wellcome Trust Institutional Translational Partnership Award Innovation Competition, and Research Adaptation Fund to attend courses and conferences in the past. RMW has received financial support from Alzheimer's Research UK (ARUK) to attend the ARUK annual conference (2021 and 2022). JLM is supported by the UK Medical Research Council Integrative Epidemiology Unit at the University of Bristol. AC is a University of Edinburgh Medical Research Ethics Committee member. JvdD was supported by NWO Large Scale infrastructures, X-Omics (184.034.019). Remaining authors report no conflicts of interest. This research was funded in whole, or in part, by the Wellcome Trust [216767/Z/19/Z]. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. Generation Scotland is currently supported by the Wellcome Trust [216767/Z/19/Z] and by the Wellcome Trust Investigator Award in Science 01/06/2021 to 31/05/26 ‘Exploiting genomic approaches to identify the environmental basis of depression’. (Reference: 220857/Z/20/Z) to McIntosh AM (PI). The DNA methylation profiling and data preparation was supported by Wellcome Investigator Award 220857/Z/20/Z and Grant 104036/Z/14/Z (PI for both grants: McIntosh AM) and through funding from NARSAD (Ref: 27404; PI: Dr DM Howard and Ref: 21956; PI Dr Kathryn Evans) and the Royal College of Physicians of Edinburgh (Sim Fellowship; PI: Dr HC Whalley). Genotyping of the GS:SFHS samples was funded by the MRC and Wellcome Trust [104036/Z/14/Z]. Generation Scotland also receives support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006]. Dr DM Howard is supported by a Sir Henry Wellcome Postdoctoral Fellowship (Reference 213674/Z/18/Z). Dr M Barbu is supported by a Guarantors of Brain Non-clinical Post-Doctoral Fellowship. The UK Medical Research Council and Wellcome (Grant Ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. A comprehensive list of grants funding is available on the ALSPAC website ( http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf ).

Funders	Funder number
University of Otago
Det Sundhedsvidenskabelige Fakultet, Københavns Universitet
Health and Medical Sciences, University of Copenhagen
Broad Institute
Sir Henry Wellcome Postdoctoral Fellowship
Menzies Institute for Medical Research
Bradford Institute for Health Research
College of Health and Medicine, University of Tasmania
80 Hospital del Mar Medical Research Institute
Bellvitge Biomedical Research Institute
Louise Arseneault60
Leids Universitair Medisch Centrum
Beatrix Children's Hospital
Barcelona Institute of Science and Technology
Erasmus Universiteit Rotterdam
University of Edinburgh
Department of Psychiatry and Behavioral Sciences, School of Medicine, Stanford University
74 Centre of Women's, Family and Child Health, University of South-Eastern Norway
Instituto de Parasitología y Biomedicina López Neyra
Zhongshan School of Medicine, Sun Yat-Sen University
Institut Hospital del Mar d'Investigacions Mèdiques
King's College Hospital, London, UK, 56 United Kingdom Dementia Research Institute
Institut national de la santé et de la recherche médicale
Royal College of Physicians of Edinburgh
31 Guangdong Province Key Laboratory of Brain Function and Disease
College of Medicine and Health, University of Exeter
Avera Institute for Human Genetics, Sioux Falls
Institute of Genetics and Molecular Medicine, Western General Hospital
University of Toronto
68 Department of Social and Behavioral Science
National Institute of Public Health, University of Southern Denmark
Harvard T.H. Chan School of Public Health
School of Medicine, Emory University
College of Health, Medicine and Wellbeing
Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement
University of Granada - Andalusian Government Center for Genomics and Oncological Research
Rijksuniversiteit Groningen
Illinois Department of Public Health
Dorret I Boomsma43
Helsingin Yliopisto
Children's Health
Tartu Ülikool
Universitair Medisch Centrum Groningen
Department of Pediatric Pulmonology and Pediatric Allergology
Aix-Marseille Université
Telethon Kids Institute
83 Division of Epidemiology, Biostatistics, and Environmental Health Sciences
University of Newcastle, Newcastle, Australia
Consejo Superior de Investigaciones Científicas
University of Southampton
University of Queensland
Universität Basel
Centro Pfizer-Universidad de Granada-Junta de Andalucía de Genómica e Investigación Oncológic
Karolinska Institutet
University of Aberdeen
Helmholtz Centre for Infection Research
Department of Biomedical Data Sciences
Syddansk Universitet
Institute of Genetics and Molecular Medicine, University of Edinburgh
Sun Yat-Sen University
Medizinischen Hochschule Hannover
Österreichischen Akademie der Wissenschaften
TWINCORE
University of Western Australia
3 University of Exeter Medical School
Institute for Molecular Bioscience
Hospital for Sick Children
Department of Biostatistics and Health Informatics, King's College London
Novo Nordisk Fonden
Queensland Brain Institute
University of Bristol
King's College London
Public Health Institute
Hacettepe Üniversitesi
85 Alzheimer Scotland Dementia Research Centre
Department of Epidemiology
Bristol Medical School, University of Bristol
81 Human Development and Health, Faculty of Medicine, University of Southampton
Medizinische Universität Wien
Wellcome Trust	104036/Z/14/Z, 220857, 213674, 216767/Z/19/Z, 217065, 01/06/2021, 220857/Z/20/Z
Scottish Funding Council	HR03006, 213674/Z/18/Z
Allan F McRae18	W Montgomery18
Medical Research Council	217065/Z/19/Z
Alzheimer’s Research UK	2022
National Alliance for Research on Schizophrenia and Depression	27404, 21956
Chief Scientist Office of the Scottish Government Health Directorates	CZD/16/6
NWO	184.034.019

Keywords

Avon longitudinal study of parents and children
DNA methylation
Environmental factors
Generation Scotland
Major depressive disorder
Methylation score

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10.1016/j.ebiom.2022.104000

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Cite this

@article{3320587a171b46a6ab66efa4221efa5f,

title = "Complex trait methylation scores in the prediction of major depressive disorder",

abstract = "Background: DNA methylation (DNAm) is associated with time-varying environmental factors that contribute to major depressive disorder (MDD) risk. We sought to test whether DNAm signatures of lifestyle and biochemical factors were associated with MDD to reveal dynamic biomarkers of MDD risk that may be amenable to lifestyle interventions. Methods: Here, we calculated methylation scores (MS) at multiple p-value thresholds for lifestyle (BMI, smoking, alcohol consumption, and educational attainment) and biochemical (high-density lipoprotein (HDL) and total cholesterol) factors in Generation Scotland (GS) (N=9,502) and in a replication cohort (ALSPACadults, N=565), using CpG sites reported in previous well-powered methylome-wide association studies. We also compared their predictive accuracy for MDD to a MDD MS in an independent GS sub-sample (N=4,432). Findings: Each trait MS was significantly associated with its corresponding phenotype in GS (βrange=0.089–1.457) and in ALSPAC (βrange=0.078–2.533). Each MS was also significantly associated with MDD before and after adjustment for its corresponding phenotype in GS (βrange=0.053–0.145). After accounting for relevant lifestyle factors, MS for educational attainment (β=0.094) and alcohol consumption (MSp-value<0.01–0.5; βrange=-0.069–0.083) remained significantly associated with MDD in GS. Smoking (AUC=0.569) and educational attainment (AUC=0.585) MSs could discriminate MDD from controls better than the MDD MS (AUC=0.553) in the independent GS sub-sample. Analyses implicating MDD did not replicate across ALSPAC, although the direction of effect was consistent for all traits when adjusting for the MS corresponding phenotypes. Interpretation: We showed that lifestyle and biochemical MS were associated with MDD before and after adjustment for their corresponding phenotypes (pnominal<0.05), but not when smoking, alcohol consumption, and BMI were also included as covariates. MDD results did not replicate in the smaller, female-only independent ALSPAC cohort (NALSPAC=565; NGS=9,502), potentially due to demographic differences or low statistical power, but effect sizes were consistent with the direction reported in GS. DNAm scores for modifiable MDD risk factors may contribute to disease vulnerability and, in some cases, explain additional variance to their observed phenotypes. Funding: Wellcome Trust.",

keywords = "Avon longitudinal study of parents and children, DNA methylation, Environmental factors, Generation Scotland, Major depressive disorder, Methylation score",

author = "Barbu, {Miruna C.} and Carmen Amador and Kwong, {Alex S.F.} and Xueyi Shen and Adams, {Mark J.} and Howard, {David M.} and Walker, {Rosie M.} and Morris, {Stewart W.} and Min, {Josine L.} and Chunyu Liu and {van Dongen}, Jenny and Mohsen Ghanbari and Caroline Relton and Porteous, {David J.} and Archie Campbell and Evans, {Kathryn L.} and Whalley, {Heather C.} and McIntosh, {Andrew M.} and {Genetics of DNA Methylation Consortium}",

note = "Funding Information: MCB has received financial support from Edinburgh Neuroscience Researcher's Fund, Wellcome Trust Institutional Translational Partnership Award Innovation Competition, and Research Adaptation Fund to attend courses and conferences in the past. RMW has received financial support from Alzheimer's Research UK (ARUK) to attend the ARUK annual conference (2021 and 2022). JLM is supported by the UK Medical Research Council Integrative Epidemiology Unit at the University of Bristol. AC is a University of Edinburgh Medical Research Ethics Committee member. JvdD was supported by NWO Large Scale infrastructures, X-Omics (184.034.019). Remaining authors report no conflicts of interest. Funding Information: This research was funded in whole, or in part, by the Wellcome Trust [216767/Z/19/Z]. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. Generation Scotland is currently supported by the Wellcome Trust [216767/Z/19/Z] and by the Wellcome Trust Investigator Award in Science 01/06/2021 to 31/05/26 {\textquoteleft}Exploiting genomic approaches to identify the environmental basis of depression{\textquoteright}. (Reference: 220857/Z/20/Z) to McIntosh AM (PI). The DNA methylation profiling and data preparation was supported by Wellcome Investigator Award 220857/Z/20/Z and Grant 104036/Z/14/Z (PI for both grants: McIntosh AM) and through funding from NARSAD (Ref: 27404; PI: Dr DM Howard and Ref: 21956; PI Dr Kathryn Evans) and the Royal College of Physicians of Edinburgh (Sim Fellowship; PI: Dr HC Whalley). Genotyping of the GS:SFHS samples was funded by the MRC and Wellcome Trust [104036/Z/14/Z]. Generation Scotland also receives support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006]. Dr DM Howard is supported by a Sir Henry Wellcome Postdoctoral Fellowship (Reference 213674/Z/18/Z). Dr M Barbu is supported by a Guarantors of Brain Non-clinical Post-Doctoral Fellowship. Funding Information: The UK Medical Research Council and Wellcome (Grant Ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. A comprehensive list of grants funding is available on the ALSPAC website ( http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf ). Publisher Copyright: {\textcopyright} 2022 The Authors",

year = "2022",

month = may,

doi = "10.1016/j.ebiom.2022.104000",

language = "English",

volume = "79",

pages = "1--19",

journal = "Ebiomedicine",

issn = "2352-3964",

publisher = "Elsevier BV",

}

TY - JOUR

T1 - Complex trait methylation scores in the prediction of major depressive disorder

AU - Barbu, Miruna C.

AU - Amador, Carmen

AU - Kwong, Alex S.F.

AU - Shen, Xueyi

AU - Adams, Mark J.

AU - Howard, David M.

AU - Walker, Rosie M.

AU - Morris, Stewart W.

AU - Min, Josine L.

AU - Liu, Chunyu

AU - van Dongen, Jenny

AU - Ghanbari, Mohsen

AU - Relton, Caroline

AU - Porteous, David J.

AU - Campbell, Archie

AU - Evans, Kathryn L.

AU - Whalley, Heather C.

AU - McIntosh, Andrew M.

AU - Genetics of DNA Methylation Consortium

N1 - Funding Information: MCB has received financial support from Edinburgh Neuroscience Researcher's Fund, Wellcome Trust Institutional Translational Partnership Award Innovation Competition, and Research Adaptation Fund to attend courses and conferences in the past. RMW has received financial support from Alzheimer's Research UK (ARUK) to attend the ARUK annual conference (2021 and 2022). JLM is supported by the UK Medical Research Council Integrative Epidemiology Unit at the University of Bristol. AC is a University of Edinburgh Medical Research Ethics Committee member. JvdD was supported by NWO Large Scale infrastructures, X-Omics (184.034.019). Remaining authors report no conflicts of interest. Funding Information: This research was funded in whole, or in part, by the Wellcome Trust [216767/Z/19/Z]. For the purpose of open access, the author has applied a CC BY public copyright licence to any Author Accepted Manuscript version arising from this submission. Generation Scotland is currently supported by the Wellcome Trust [216767/Z/19/Z] and by the Wellcome Trust Investigator Award in Science 01/06/2021 to 31/05/26 ‘Exploiting genomic approaches to identify the environmental basis of depression’. (Reference: 220857/Z/20/Z) to McIntosh AM (PI). The DNA methylation profiling and data preparation was supported by Wellcome Investigator Award 220857/Z/20/Z and Grant 104036/Z/14/Z (PI for both grants: McIntosh AM) and through funding from NARSAD (Ref: 27404; PI: Dr DM Howard and Ref: 21956; PI Dr Kathryn Evans) and the Royal College of Physicians of Edinburgh (Sim Fellowship; PI: Dr HC Whalley). Genotyping of the GS:SFHS samples was funded by the MRC and Wellcome Trust [104036/Z/14/Z]. Generation Scotland also receives support from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006]. Dr DM Howard is supported by a Sir Henry Wellcome Postdoctoral Fellowship (Reference 213674/Z/18/Z). Dr M Barbu is supported by a Guarantors of Brain Non-clinical Post-Doctoral Fellowship. Funding Information: The UK Medical Research Council and Wellcome (Grant Ref: 217065/Z/19/Z) and the University of Bristol provide core support for ALSPAC. A comprehensive list of grants funding is available on the ALSPAC website ( http://www.bristol.ac.uk/alspac/external/documents/grant-acknowledgements.pdf ). Publisher Copyright: © 2022 The Authors

PY - 2022/5

Y1 - 2022/5

N2 - Background: DNA methylation (DNAm) is associated with time-varying environmental factors that contribute to major depressive disorder (MDD) risk. We sought to test whether DNAm signatures of lifestyle and biochemical factors were associated with MDD to reveal dynamic biomarkers of MDD risk that may be amenable to lifestyle interventions. Methods: Here, we calculated methylation scores (MS) at multiple p-value thresholds for lifestyle (BMI, smoking, alcohol consumption, and educational attainment) and biochemical (high-density lipoprotein (HDL) and total cholesterol) factors in Generation Scotland (GS) (N=9,502) and in a replication cohort (ALSPACadults, N=565), using CpG sites reported in previous well-powered methylome-wide association studies. We also compared their predictive accuracy for MDD to a MDD MS in an independent GS sub-sample (N=4,432). Findings: Each trait MS was significantly associated with its corresponding phenotype in GS (βrange=0.089–1.457) and in ALSPAC (βrange=0.078–2.533). Each MS was also significantly associated with MDD before and after adjustment for its corresponding phenotype in GS (βrange=0.053–0.145). After accounting for relevant lifestyle factors, MS for educational attainment (β=0.094) and alcohol consumption (MSp-value<0.01–0.5; βrange=-0.069–0.083) remained significantly associated with MDD in GS. Smoking (AUC=0.569) and educational attainment (AUC=0.585) MSs could discriminate MDD from controls better than the MDD MS (AUC=0.553) in the independent GS sub-sample. Analyses implicating MDD did not replicate across ALSPAC, although the direction of effect was consistent for all traits when adjusting for the MS corresponding phenotypes. Interpretation: We showed that lifestyle and biochemical MS were associated with MDD before and after adjustment for their corresponding phenotypes (pnominal<0.05), but not when smoking, alcohol consumption, and BMI were also included as covariates. MDD results did not replicate in the smaller, female-only independent ALSPAC cohort (NALSPAC=565; NGS=9,502), potentially due to demographic differences or low statistical power, but effect sizes were consistent with the direction reported in GS. DNAm scores for modifiable MDD risk factors may contribute to disease vulnerability and, in some cases, explain additional variance to their observed phenotypes. Funding: Wellcome Trust.

AB - Background: DNA methylation (DNAm) is associated with time-varying environmental factors that contribute to major depressive disorder (MDD) risk. We sought to test whether DNAm signatures of lifestyle and biochemical factors were associated with MDD to reveal dynamic biomarkers of MDD risk that may be amenable to lifestyle interventions. Methods: Here, we calculated methylation scores (MS) at multiple p-value thresholds for lifestyle (BMI, smoking, alcohol consumption, and educational attainment) and biochemical (high-density lipoprotein (HDL) and total cholesterol) factors in Generation Scotland (GS) (N=9,502) and in a replication cohort (ALSPACadults, N=565), using CpG sites reported in previous well-powered methylome-wide association studies. We also compared their predictive accuracy for MDD to a MDD MS in an independent GS sub-sample (N=4,432). Findings: Each trait MS was significantly associated with its corresponding phenotype in GS (βrange=0.089–1.457) and in ALSPAC (βrange=0.078–2.533). Each MS was also significantly associated with MDD before and after adjustment for its corresponding phenotype in GS (βrange=0.053–0.145). After accounting for relevant lifestyle factors, MS for educational attainment (β=0.094) and alcohol consumption (MSp-value<0.01–0.5; βrange=-0.069–0.083) remained significantly associated with MDD in GS. Smoking (AUC=0.569) and educational attainment (AUC=0.585) MSs could discriminate MDD from controls better than the MDD MS (AUC=0.553) in the independent GS sub-sample. Analyses implicating MDD did not replicate across ALSPAC, although the direction of effect was consistent for all traits when adjusting for the MS corresponding phenotypes. Interpretation: We showed that lifestyle and biochemical MS were associated with MDD before and after adjustment for their corresponding phenotypes (pnominal<0.05), but not when smoking, alcohol consumption, and BMI were also included as covariates. MDD results did not replicate in the smaller, female-only independent ALSPAC cohort (NALSPAC=565; NGS=9,502), potentially due to demographic differences or low statistical power, but effect sizes were consistent with the direction reported in GS. DNAm scores for modifiable MDD risk factors may contribute to disease vulnerability and, in some cases, explain additional variance to their observed phenotypes. Funding: Wellcome Trust.

KW - Avon longitudinal study of parents and children

KW - DNA methylation

KW - Environmental factors

KW - Generation Scotland

KW - Major depressive disorder

KW - Methylation score

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U2 - 10.1016/j.ebiom.2022.104000

DO - 10.1016/j.ebiom.2022.104000

M3 - Article

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SN - 2352-3964

VL - 79

SP - 1

EP - 19

JO - Ebiomedicine

JF - Ebiomedicine

M1 - 104000

ER -

Complex trait methylation scores in the prediction of major depressive disorder

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