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Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depression
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Abstract
Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype. A genome-wide association meta-analysis of individuals with clinically assessed or self-reported depression identifies 44 independent risk loci. Comparisons with other psychiatric disorders and candidate gene analyses provide new insights into major depressive disorder.
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“Many of these genetic correlations are similar to those reported by Wray, et al. 9 and Howard, et al. 5, including earlier age at menarche (rG = -0.12, s.e = 0.02).”
From Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions (2019) · cites this paper as [9]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“A GWAS meta-analysis of MDD published in 2018 identified 44 depression-associated loci and integrated genetic and mQTL data from two large studies to identify nine risk variants controlling local DNAm in blood.”
From Epigenetics and depression (2019) · cites this paper as [49]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“This overlap indicates that a subset of the risk variants for MDD could be responsible for the DMRs observed in patients with MDD.”
From Epigenetics and depression (2019) · cites this paper as [49]
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In the citing paper
“Interestingly, some of the nine mQTLs are located near genes encoding miRNAs; however, the function of these variants and DMRs must still be assessed.”
From Epigenetics and depression (2019) · cites this paper as [49]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
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“The major haplotype outside Africa was found significantly associated with greater susceptibility to major depression and other related psychiatric disorders [55,56] as well as with higher values for self-reported helping behavior [57].”
From Human genetic adaptation related to cellular zinc homeostasis (2023) · cites this paper as [56]
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“large consortia that have discovered and successfully replicated genome-wide associations of common gene variants (single nucleotide polymorphisms, SNPs) for several disorders including schizophrenia [2] and major depression [3–6].”
From Neandertal introgression partitions the genetic landscape of neuropsychiatric disorders and associated behavioral phenotypes (2022) · cites this paper as [3]
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In the citing paper
“and postmortem studies of patients with MDD have shown reduced densities of glial cells in the prefrontal cortex (PFC), hippocampus and amygdala. 19”
From Major depressive disorder: hypothesis, mechanism, prevention and treatment (2024) · cites this paper as [19]
Experimental — accuracy not yet measuredIn the citing paper
“DRD2 was included in all 14 of the putative Gene Ontology Consortium gene-sets identified (but not the somatosensory pyramidal neurons gene-set) and has been identified in previous studies of depression5, 9, 22.”
From Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions (2019) · cites this paper as [9]
In the citing paper
“All of the 102 variants associated with depression had an equivalent direction of allelic effect across the three studies5, 8, 9 that contributed to the meta-analysis and the replication sample (Supplementary Table 1), suggesting that these variants represent robust associations with depression.”
From Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions (2019) · cites this paper as [9]
In the citing paper
“The current study further reaffirms the genetic correlation between schizophrenia and depression observed by Wray, et al. 9.”
From Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions (2019) · cites this paper as [9]
In the citing paper
“Finally, a meta-analysis of 35 cohorts (total n = 461,134; 130,664 cases and 330,470 controls) conducted by Wray, et al. 9 (PGC) found 44 loci that were significantly associated with a spectrum of depression phenotypes, some obtained from structured clinical interview and others based on broader criteria.”
From Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions (2019) · cites this paper as [9]
In the citing paper
“The TCF4 gene coding region (Supplementary Figure 12) is also noteworthy as it contained two independently-associated variants for depression and has been identified in previous studies of depression 5, 9, 29.”
From Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions (2019) · cites this paper as [9]
In the citing paper
“No statistical methods were used to pre-determine sample sizes but our sample sizes are similar to those reported in previous publications 5, 8, 9.”
From Genome-wide meta-analysis of depression identifies 102 independent variants and highlights the importance of the prefrontal brain regions (2019) · cites this paper as [9]
In the citing paper
“MDD-associated genes overlap with genes that harbor rare de novo variation in ASD and developmental disorders (DD), suggesting that a recently reported genetic correlation between MDD and ASD GWAS43 may also apply for rare variation.”
From A computational tool (H-MAGMA) for improved prediction of brain-disorder risk genes by incorporating brain chromatin interaction profiles (2020) · cites this paper as [43]
In the citing paper
“Several prospective studies suggest that depression prior to completing education predicts substantially reduced income-earnings in adulthood after adjusting for level of educational attainment. 230,231”
From Time for united action on depression: a Lancet–World Psychiatric Association Commission (2022) · cites this paper as [230]
In the citing paper
“It is true that a large number of risk alleles are involved, and that the explanatory power of currently available polygenic risk scores for addictive disorders lags behind those for e.g., schizophrenia or major depression [47,48].”
From Addiction as a brain disease revised: why it still matters, and the need for consilience (2021) · cites this paper as [48]
In the citing paper
“Power analyses indicate that additional SNPs associated with AD are likely to have small effect sizes, smaller than schizophrenia47 and more consistent with more common psychiatric disorders (e.g. major depression48).”
From Transancestral GWAS of alcohol dependence reveals common genetic underpinnings with psychiatric disorders (2018) · cites this paper as [48]
In the citing paper
“and has been previously associated with both MD and neuroticism (Turley et al., 2018; Wray et al., 2018).”
From Genomic Relationships, Novel Loci, and Pleiotropic Mechanisms across Eight Psychiatric Disorders (2019) · cites this paper as Wray et al., 2018
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Metadata
- Authors
- eQTLGen, Wray, N. R., 23andMe, the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium, Ripke, S., Mattheisen, M., Trzaskowski, M., Byrne, E. M., Abdellaoui, A., Adams, M. J., Agerbo, E., Air, T. M., Andlauer, T. M. F., Bacanu, S.-A., Bækvad-Hansen, M., Beekman, A. F. T., Bigdeli, T. B., Binder, E. B., Blackwood, D. R. H., Bryois, J., Buttenschøn, H. N., Bybjerg-Grauholm, J., Cai, N., Castelao, E., Christensen, J. H., Clarke, T.-K., Coleman, J. I. R., Colodro-Conde, L., Couvy-Duchesne, B., Craddock, N., Crawford, G. E., Crowley, C. A., Dashti, H. S., Davies, G., Deary, I. J., Degenhardt, F., Derks, E. M., Direk, N., Dolan, C. V., Dunn, E. C., Eley, T. C., Eriksson, N., Escott-Price, V., Kiadeh, F. H. F., Finucane, H. K., Forstner, A. J., Frank, J., Gaspar, H. A., Gill, M., Giusti-Rodríguez, P., Goes, F. S., Gordon, S. D., Grove, J., Hall, L. S., Hannon, E., Hansen, C. S., Hansen, T. F., Herms, S., Hickie, I. B., Hoffmann, P., Homuth, G., Horn, C., Hottenga, J.-J., Hougaard, D. M., Hu, M., Hyde, C. L., Ising, M., Jansen, R., Jin, F., Jorgenson, E., Knowles, J. A., Kohane, I. S., Kraft, J., Kretzschmar, W. W., Krogh, J., Kutalik, Z., Lane, J. M., Li, Y., Li, Y., Lind, P. A., Liu, X., Lu, L., MacIntyre, D. J., MacKinnon, D. F., Maier, R. M., Maier, W., Marchini, J., Mbarek, H., McGrath, P., McGuffin, P., Medland, S. E., Mehta, D., Middeldorp, C. M., Mihailov, E., Milaneschi, Y., Milani, L., Mill, J., Mondimore, F. M., Montgomery, G. W., Mostafavi, S., Mullins, N., Nauck, M., Ng, B., Nivard, M. G., Nyholt, D. R., O’Reilly, P. F., Oskarsson, H., Owen, M. J., Painter, J. N., Pedersen, C. B., Pedersen, M. G., Peterson, R. E., Pettersson, E., Peyrot, W. J., Pistis, G., Posthuma, D., Purcell, S. M., Quiroz, J. A., Qvist, P., Rice, J. P., Riley, B. P., Rivera, M., Saeed Mirza, S., Saxena, R., Schoevers, R., Schulte, E. C., Shen, L., Shi, J., Shyn, S. I., Sigurdsson, E., Sinnamon, G. B. C., Smit, J. H., Smith, D. J., Stefansson, H., Steinberg, S., Stockmeier, C. A., Streit, F., Strohmaier, J., Tansey, K. E., Teismann, H., Teumer, A., Thompson, W., Thomson, P. A., Thorgeirsson, T. E., Tian, C., Traylor, M., Treutlein, J., Trubetskoy, V., Uitterlinden, A. G., Umbricht, D., Van der Auwera, S., van Hemert, A. M., Viktorin, A., Visscher, P. M., Wang, Y., Webb, B. T., Weinsheimer, S. M., Wellmann, J., Willemsen, G., Witt, S. H., Wu, Y., Xi, H. S., Yang, J., Zhang, F., Arolt, V., Baune, B. T., Berger, K., Boomsma, D. I., Cichon, S., Dannlowski, U., de Geus, E. C. J., DePaulo, J. R., Domenici, E., Domschke, K., Esko, T., Grabe, H. J., Hamilton, S. P., Hayward, C., Heath, A. C., Hinds, D. A., Kendler, K. S., Kloiber, S., Lewis, G., Li, Q. S., Lucae, S., Madden, P. F. A., Magnusson, P. K., Martin, N. G., McIntosh, A. M., Metspalu, A., Mors, O., Mortensen, P. B., Müller-Myhsok, B., Nordentoft, M., Nöthen, M. M., O’Donovan, M. C., Paciga, S. A., Pedersen, N. L., Penninx, B. W. J. H., Perlis, R. H., Porteous, D. J., Potash, J. B., Preisig, M., Rietschel, M., Schaefer, C., Schulze, T. G., Smoller, J. W., Stefansson, K., Tiemeier, H., Uher, R., Völzke, H., Weissman, M. M., Werge, T., Winslow, A. R., Lewis, C. M., Levinson, D. F., Breen, G., Børglum, A. D., & Sullivan, P. F.
- Affiliations
- The University of Queensland (AU)
- Broad Institute (US)
- Aarhus University (DK)
- Amsterdam Public Health (NL)
- The University of Adelaide (AU)
- Virginia Commonwealth University (US)
- Emory University (US)
- Statens Serum Institut (DK)
- European Bioinformatics Institute (GB)
- Centre Hospitalier Universitaire Vaudois (CH)
- King's College London (GB)
- QIMR Berghofer Medical Research Institute (AU)
- University of North Carolina at Chapel Hill (US)
- University of Bonn (DE)
- University of British Columbia (CA)
- Harvard University (US)
- Trinity College Dublin (IE)
- Johns Hopkins University (US)
- University of Exeter (GB)
- The University of Sydney (AU)
- F. Hoffmann-La Roche AG (CH)
- Universitätsmedizin Greifswald (DE)
- Cleveland Clinic (US)
- Pfizer (United States) (US)
- Max Planck Institute of Psychiatry (DE)
- Kaiser Permanente (US)
- University of Southern California (US)
- Brigham and Women's Hospital (US)
- University of Copenhagen (DK)
- SIB Swiss Institute of Bioinformatics (CH)
- Case Western Reserve University (US)
- University of Oxford (GB)
- Queensland University of Technology (AU)
- University of Tartu (EE)
- GGZ inGeest (NL)
- Washington University in St. Louis (US)
- Universidad de Granada (ES)
- University Medical Center Groningen (NL)
- National Cancer Institute (US)
- University of Iceland (IS)
- University of Glasgow (GB)
- deCODE Genetics (Iceland) (IS)
- Heidelberg University (DE)
- Oslo University Hospital (NO)
- 23andMe (United States) (US)
- University of Cambridge (GB)
- Mental Health Services (DK)
- University of Münster (DE)
- University of Basel (CH)
- University of Trento (IT)
- University of Freiburg (DE)
- Centre for Addiction and Mental Health (CA)
- Karolinska Institutet (SE)
- Aarhus University Hospital (DK)
- University of Liverpool (GB)
- Copenhagen University Hospital (DK)
- University of Iowa (US)
- National Institutes of Health (US)
- Dalhousie University (CA)
- Corresponding author
- Wray, Naomi R.
- Sullivan, Patrick F.
- ORCID
- Wray, Naomi R.
- Ripke, Stephan
- Mattheisen, Manuel
- Trzaskowski, Maciej
- Byrne, Enda M.
- Abdellaoui, Abdel
- Adams, Mark J.
- Agerbo, Esben
- Air, Tracy M.
- Bacanu, Silviu-Alin
- Bigdeli, Tim B.
- Binder, Elisabeth B.
- Bryois, Julien
- Buttenschøn, Henriette N.
- Cai, Na
- Castelao, Enrique
- Christensen, Jane Hvarregaard
- Clarke, Toni-Kim
- Craddock, Nick
- Crawford, Gregory E.
- Crowley, Cheynna A.
- Dashti, Hassan S.
- Davies, Gail
- Deary, Ian J.
- Degenhardt, Franziska
- Derks, Eske M.
- Dolan, Conor V.
- Dunn, Erin C.
- Eley, Thalia C.
- Eriksson, Nicholas
- Finucane, Hilary K.
- Forstner, Andreas J.
- Frank, Josef
- Gaspar, Héléna A.
- Gill, Michael
- Goes, Fernando S.
- Gordon, Scott D.
- Grove, Jakob
- Hall, Lynsey S.
- Hannon, Eilis
- Hansen, Christine Søholm
- Hansen, Thomas F.
- Herms, Stefan
- Hickie, Ian B.
- Hoffmann, Per
- Homuth, Georg
- Hottenga, Jouke-Jan
- Hougaard, David M.
- Hu, Ming
- Hyde, Craig L.
- Jansen, Rick
- Jin, Fulai
- Jorgenson, Eric
- Knowles, James A.
- Kohane, Isaac S.
- Kraft, Julia
- Kretzschmar, Warren W.
- Krogh, Jesper
- Kutalik, Zoltán
- Lane, Jacqueline M.
- Li, Yihan
- Li, Yun
- Lind, Penelope A.
- Liu, Xiaoxiao
- Lu, Leina
- MacIntyre, Donald J.
- MacKinnon, Dean F.
- Marchini, Jonathan
- Mbarek, Hamdi
- McGrath, Patrick
- McGuffin, Peter
- Medland, Sarah E.
- Mehta, Divya
- Middeldorp, Christel M.
- Milaneschi, Yuri
- Milani, Lili
- Mill, Jonathan
- Mondimore, Francis M.
- Montgomery, Grant W.
- Mostafavi, Sara
- Mullins, Niamh
- Nauck, Matthias
- Ng, Bernard
- Nivard, Michel G.
- Nyholt, Dale R.
- O’Reilly, Paul F.
- Owen, Michael J.
- Painter, Jodie N.
- Pedersen, Carsten Bøcker
- Peterson, Roseann E.
- Pettersson, Erik
- Peyrot, Wouter J.
- Pistis, Giorgio
- Purcell, Shaun M.
- Quiroz, Jorge A.
- Qvist, Per
- Rice, John P.
- Riley, Brien P.
- Rivera, Margarita
- Saxena, Richa
- Schoevers, Robert
- Schulte, Eva C.
- Shi, Jianxin
- Shyn, Stanley I.
- Sinnamon, Grant B. C.
- Smit, Johannes H.
- Steinberg, Stacy
- Stockmeier, Craig A.
- Streit, Fabian
- Strohmaier, Jana
- Tansey, Katherine E.
- Teismann, Henning
- Teumer, Alexander
- Thompson, Wesley
- Thomson, Pippa A.
- Thorgeirsson, Thorgeir E.
- Traylor, Matthew
- Treutlein, Jens
- Trubetskoy, Vassily
- Uitterlinden, André G.
- Umbricht, Daniel
- Viktorin, Alexander
- Visscher, Peter M.
- Wang, Yunpeng
- Webb, Bradley T.
- Weinsheimer, Shantel Marie
- Wellmann, Jürgen
- Willemsen, Gonneke
- Witt, Stephanie H.
- Wu, Yang
- Xi, Hualin S.
- Yang, Jian
- Zhang, Futao
- Arolt, Volker
- Baune, Bernhard T.
- Boomsma, Dorret I.
- Cichon, Sven
- Dannlowski, Udo
- DePaulo, J. Raymond
- Domenici, Enrico
- Domschke, Katharina
- Esko, Tõnu
- Grabe, Hans J.
- Hamilton, Steven P.
- Hayward, Caroline
- Heath, Andrew C.
- Hinds, David A.
- Kendler, Kenneth S.
- Kloiber, Stefan
- Lewis, Glyn
- Li, Qingqin S.
- Lucae, Susanne
- Magnusson, Patrik K.
- Martin, Nicholas G.
- McIntosh, Andrew M.
- Metspalu, Andres
- Mors, Ole
- Mortensen, Preben Bo
- Nordentoft, Merete
- Nöthen, Markus M.
- O’Donovan, Michael C.
- Paciga, Sara A.
- Pedersen, Nancy L.
- Penninx, Brenda W. J. H.
- Perlis, Roy H.
- Porteous, David J.
- Potash, James B.
- Preisig, Martin
- Rietschel, Marcella
- Schulze, Thomas G.
- Smoller, Jordan W.
- Tiemeier, Henning
- Uher, Rudolf
- Völzke, Henry
- Weissman, Myrna M.
- Werge, Thomas
- Winslow, Ashley R.
- Lewis, Cathryn M.
- Levinson, Douglas F.
- Breen, Gerome
- Børglum, Anders D.
- Sullivan, Patrick F.
- Venue
- Nature Genetics
- Published
- 2018-04-26
- Volume
- 50
- Issue
- 5
- Pages
- 668-681
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC5934326
- OpenAlex
- W2738082385
- Cited by
- 3,005
- References
- 142
- Citations by year
- 2026: 183 · 2025: 323 · 2024: 407 · 2023: 406 · 2022: 360 · 2021: 407 · 2020: 400 · 2019: 355 · 2018: 143
- FWCI
- 197.01
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Nature Genetics (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Pure Amsterdam UMC (publishedVersion, cc-by)
- Research at the University of Copenhagen (University of Copenhagen) (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (publishedVersion, other-oa)
- VU Research Portal (publishedVersion, other-oa)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion, cc-by-sa)
- ORCA Online Research @Cardiff (Cardiff University) (acceptedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- SERVAL (Université de Lausanne) (acceptedVersion, other-oa)
- QUT ePrints (Queensland University of Technology) (submittedVersion)
- ResearchOnline at James Cook University (James Cook University) (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- IRIS (submittedVersion)
- JuSER (Forschungszentrum Jülich) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion, other-oa)
- UCL Discovery (University College London) (submittedVersion)
- Iris (University of Trento) (submittedVersion, other-oa)
- Research Portal (King's College London) (submittedVersion, other-oa)
- SUNY Digital Repository Support (State University of New York System) (submittedVersion, cc-by-nc-nd)
- Amsterdam UMC (VU Amsterdam) - Institutional Repository (submittedVersion, other-oa)
- Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
- MPG.PuRe (Max Planck Society) (submittedVersion)
- Royal Devon and Exeter Research Repository (Royal Devon and Exeter) (submittedVersion)
- VUBIR (Vrije Universiteit Brussel) (submittedVersion)
- University of Groningen research database (University of Groningen / Centre for Information Technology) (submittedVersion, other-oa)
- Newcastle University ePrints (Newcastle Univesity)
- Funders
- Amgen
- Pfizer
- GlaxoSmithKline
- Northwestern University
- South London and Maudsley NHS Foundation Trust
- Wellcome Trust (104036/Z/14/Z)
- QIMR Berghofer Medical Research Institute
- National Institute for Health and Care Research
- King's College London
- Bundesministerium für Bildung und Forschung (01GS0481, 01ER0816, NGFN-2, 03ZIK012, 01ZZ0403, FKZ 01GS0481, 01ES0811, 01ZZ0103, 01ZZ9603)
- Erasmus Medisch Centrum
- Lundbeckfonden (R155-2014-1724, R102‐A9118, R248‐2017‐2003, U01 MH109528)
- Karolinska Institutet
- Max-Planck-Gesellschaft
- Novo Nordisk
- Westfälische Wilhelms-Universität Münster
- Siemens Healthineers (01ZZ0103, 01ZZ0403, 01ZZ9603)
- H. Lundbeck A/S
- Universität Greifswald
- National Institutes of Health (1s10od018164-01, CA093459)
- Gillings School of Public Health
- Medical Research Council (MR/L023784/2, MR/K026992/1, MR/N015746/1, MC_PC_17228, MR/L010305/1, MC_UU_00007/10)
- NODAI Genome Research Center, Tokyo University of Agriculture
- National Heart, Lung, and Blood Institute (T32HL007901)
- National Institute of Mental Health (K01MH109772, U01MH046276, U01MH109528, U01MH085520, R01MH059566, U01MH046318, R01MH059571, R01MH060879, R01MH059565, U01MH109536, R01MH081800, R01MH060870, MH109532, U01MH094421, U01MH046289, U01MH079469, R01MH061675, R01MH059586, R01MH059588, R01MH067257, U01MH079470, U01MH109532, R01MH059587)
- National Institute on Drug Abuse (R01DA034076)
- National Human Genome Research Institute (R01HG009658)
- National Cancer Institute (P50CA097007, R01CA133996, P50CA093459)
- National Institute of General Medical Sciences (P30GM103328)
- National Institute of Neurological Disorders and Stroke
- National Institute of Environmental Health Sciences (R01ES011740)
- FP7 Ideas: European Research Council (294838)
- Cilag
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Pharmacology (medical) › Treatment of Major Depression
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurotransmitter Receptor Influence on Behavior
- Keywords
- major depressive disorder, genetic susceptibility loci, genetic architecture, educational attainment, body mass, schizophrenia, shared genetic etiology, antidepressant targets, gene splicing, clinical phenotype
- MeSH terms
- Major Depressive Disorder, Female, Humans, Male, Phenotype, Risk Factors, Schizophrenia, Case-Control Studies, Genetic Predisposition to Disease, Multifactorial Inheritance, Polymorphism, Single Nucleotide, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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