Cited by 233Genetic Associations and EpidemiologyTryptophan and brain disordersTreatment of Major Depression

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Genetic Association of Major Depression With Atypical Features and Obesity-Related Immunometabolic Dysregulations

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Milaneschi, Yuri, Lamers, Femke, Peyrot, Wouter J., Baune, Bernhard T., Breen, Gerome, Dehghan, Abbas, Forstner, Andreas J., Grabe, Hans J., Homuth, Georg, Kan, Carol, Lewis, Cathryn, Mullins, Niamh, Nauck, Matthias, Pistis, Giorgio, Preisig, Martin, Rivera, Margarita, Rietschel, Marcella, Streit, Fabian, Strohmaier, Jana, Teumer, Alexander, Van der Auwera, Sandra, Wray, Naomi R., Boomsma, Dorret I., Penninx, Brenda W. J. H., for the CHARGE Inflammation Working Group and the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium·2017·JAMA Psychiatry

DOI 10.1001/jamapsychiatry.2017.3016PMC PMC6396812

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Abstract

Importance: The association between major depressive disorder (MDD) and obesity may stem from shared immunometabolic mechanisms particularly evident in MDD with atypical features, characterized by increased appetite and/or weight (A/W) during an active episode. Objective: To determine whether subgroups of patients with MDD stratified according to the A/W criterion had a different degree of genetic overlap with obesity-related traits (body mass index [BMI] and levels of C-reactive protein [CRP] and leptin). Design, Setting, and Patients: This multicenter study assembled genome-wide genotypic and phenotypic measures from 14 data sets of the Psychiatric Genomics Consortium. Data sets were drawn from case-control, cohort, and population-based studies, including 26 628 participants with established psychiatric diagnoses and genome-wide genotype data. Data on BMI were available for 15 237 participants. Data were retrieved and analyzed from September 28, 2015, through May 20, 2017. Main Outcomes and Measures: Lifetime DSM-IV MDD was diagnosed using structured diagnostic instruments. Patients with MDD were stratified into subgroups according to change in the DSM-IV A/W symptoms as decreased or increased. Results: Data included 11 837 participants with MDD and 14 791 control individuals, for a total of 26 628 participants (59.1% female and 40.9% male). Among participants with MDD, 5347 (45.2%) were classified in the decreased A/W and 1871 (15.8%) in the increased A/W subgroups. Common genetic variants explained approximately 10% of the heritability in the 2 subgroups. The increased A/W subgroup showed a strong and positive genetic correlation (SE) with BMI (0.53 [0.15]; P = 6.3 × 10-4), whereas the decreased A/W subgroup showed an inverse correlation (-0.28 [0.14]; P = .06). Furthermore, the decreased A/W subgroup had a higher polygenic risk for increased BMI (odds ratio [OR], 1.18; 95% CI, 1.12-1.25; P = 1.6 × 10-10) and levels of CRP (OR, 1.08; 95% CI, 1.02-1.13; P = 7.3 × 10-3) and leptin (OR, 1.09; 95% CI, 1.06-1.12; P = 1.7 × 10-3). Conclusions and Relevance: The phenotypic associations between atypical depressive symptoms and obesity-related traits may arise from shared pathophysiologic mechanisms in patients with MDD. Development of treatments effectively targeting immunometabolic dysregulations may benefit patients with depression and obesity, both syndromes with important disability.

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“Peripheral inflammation may lead to the stimulation of activate the vagus nerve, which subsequently stimulates an inflammatory response in neural circuits associated with depression [68–70].”
Background
No Evidence for Passive Gene-Environment Correlation or the Influence of Genetic Risk for Psychiatric Disorders on Adult Body Composition via the Adoption Design
Hunjan, A. K., Cheesman, R., Coleman, J. R. I., Hübel, C., Eley, T. C., & Breen, G. D. (2020) · Behavior Genetics · doi:10.1007/s10519-020-10028-6 · Cited by 5
Inflammation, Sickness Behaviour and Depression
Khandaker, G. M., Colasanti, A., & Harrison, N. A. (2021) · Cambridge University Press eBooks · doi:10.1017/9781108539623.008 · Cited by 5
Clinical phenotype and genetic risk factors for bipolar disorder with binge eating: an update
Barboza, A. B. C., Winham, S. J., Biernacka, J. M., Frye, M. A., & McElroy, S. L. (2019) · Expert Review of Neurotherapeutics · doi:10.1080/14737175.2019.1638764 · Cited by 6
“systemic lupus erythematosus [82], Alzheimer’s disease [83], and major depression [39], among others.”
Background
Using the Power of a Giant Wisely: Confirming Inflammation in Depression
Penninx, B. W. J. H. (2021) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2021.21040332 · Cited by 4
Genetic structure of major depression symptoms across clinical and community cohortsPreprint
Adams, M. J., Thorp, J. G., Jermy, B. S., Kwong, A. S. F., Kõiv, K., Grotzinger, A. D., Nivard, M. G., Marshall, S., Milaneschi, Y., Baune, B. T., et al. (2023) · medRxiv · doi:10.1101/2023.07.05.23292214 · Cited by 4
Major depression and atherosclerotic disease: Linking shared genetics to pathways in blood, brain, heart, and atherosclerotic plaques
Pruin, E., Bartels, M., Benavente, E. D., van den Dungen, N. A. M., Hoekstra, J. K. R., de Kleijn, D. P. V., Landsmeer, L. P. L., Mokrý, M., Pasterkamp, G., Penninx, B. W. J. H., et al. (2026) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2026.112780 · Cited by 3
Interrelationships between dissatisfaction with teaching work and depressive symptoms: Structural equation modelling
Vieira, M. R. M., de Magalhães, T. A., Vieira, M. M., Prates, T. E. C., Silva, R. R. V., de Paula, A. M. B., Silveira, M. F., & Haikal, D. S. (2023) · Ciência & Saúde Coletiva · doi:10.1590/1413-81232023287.16362022en · Cited by 3
Correlation analysis between clinical effective emotional treatment and plasma N-methyl-D-aspartate receptor function-related indexes
Feng, Z., Li, Y., Cai, Y., Yang, F., Zhou, X., Feng, M., & Li, W. (2025) · Frontiers in Neuroscience · doi:10.3389/fnins.2025.1608722 · Cited by 3
Retracted
Examining Features of Atypical Depression in Youth From the Texas Youth Depression and Suicide Research Network Research Registry
Ayvaci, E. R., Lamers, F., Gorman, A., Minhajuddin, A., Nandy, K., Goodman, L. C., Trinh, A., Farias, R., Shahidullah, J. D., Storch, E. A., et al. (2025) · Journal of the American Academy of Child & Adolescent Psychiatry · doi:10.1016/j.jaac.2025.08.015 · Cited by 3
The role of immunometabolism in HIV-associated depression and cognitive impairment
Andalibi, M. S. S., & Ellis, R. J. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-99744-7.00028-6 · Cited by 3
Genetic comorbidity between major depression and cardio-metabolic disease, stratified by age at onset of major depressionPreprint
Hagenaars, S., Coleman, J., Choi, S., Gaspar, H., Adams, M., Howard, D., Hodgson, K., Traylor, M., Air, T., Andlauer, T., et al. (2019) · bioRxiv · doi:10.1101/645077 · Cited by 1
“Previous studies have identified genetic overlap between MDD and BMI using polygenic risk scores(19), but not based on genetic correlations(20).”
Background
Investigating shared genetic architecture between major depressive disorder and central obesity
Zhan, Y., Zhao, N., Zhao, Q., Wu, C., Yuan, S., Yu, X., Zheng, X., Liu, C., Hai, R., Liu, Z., et al. (2025) · Obesity · doi:10.1002/oby.24333 · Cited by 2
Exploration of Novel Biomarkers Through a Precision Medicine Approach Using Multi‐Omics and Brain Organoids in Patients With Atypical Depression and Psychotic Symptoms
Ahn, I., Chang, S., Lee, J., Choi, S. H., Han, J., & Kim, Y. (2025) · Advanced Science · doi:10.1002/advs.202508383 · Cited by 2
The moderating role of diet and physical activity in insulin resistance and immunometabolic depression
Gruber, J., Schiweck, C., Ruf, A., Süß, E. D., Japtok, P., Schouler, N., Thanarajah, S. E., Reif, A., & Matura, S. (2025) · Scientific Reports · doi:10.1038/s41598-025-32454-4 · Cited by 2
“Models applied to the total sample were adjusted for age, sex (0 = male, 1 = female), smoking status (0 = non-smoking, 1 = smoking), BMI, hormonal contraceptive use (0 = no intake, 1 = intake) and menopause (0 = no, 1 = yes).”
Influential
Genetic and Phenotypic Associations With Sustained Antidepressant Use in Major Depressive Disorder
Walker, A., Mitchell, B. L., Lin, T., Crouse, J. J., Albiñana, C., Yap, C. X., Lynall, M.-E., Lind, P. A., Cipriani, A., Byrne, E. M., et al. (2026) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2025.4372 · Cited by 2
Non-melancholic depressive symptoms are associated with above average fat mass index in the Helsinki birth cohort study
Eriksson, M. D., Eriksson, J. G., Korhonen, P. E., Salonen, M. K., Mikkola, T. M., Kajantie, E., Wasenius, N., von Bonsdorff, M. B., Kautiainen, H., & Laine, M. K. (2022) · Scientific Reports · doi:10.1038/s41598-022-10592-3 · Cited by 2
Obesity and depression: A molecular and epidemiological view of two comorbid disorders
Cuenca-Ecuador., U. C. D. C., Guzmán, M. G. V., Garzón, M., & Ortíz, R. (2022) · Gaceta Médica de Caracas · doi:10.47307/gmc.2022.130.s3.25 · Cited by 2
“In fact, these factors are equally involved during the development of these pathologies, with an additive genetic effect accounting for 40 % of these conditions’ heritability (45,46).”
Background
Association between serum 25 (OH) D levels and depression symptoms in adults with prediabetes
Quynh, V. T., Tran, Q. K., & Niu, K. (2022) · Diabetes & Metabolic Syndrome Clinical Research & Reviews · doi:10.1016/j.dsx.2022.102642 · Cited by 2
Depression Subtypes in Patients with Systolic Heart Failure: A Secondary Analysis from the Randomized Controlled Hopeful Heart Trial
Sadlonova, M., Chavanon, M.-L., Kwonho, J., Abebe, K., Celano, C., Huffman, J., Belnap, B. H., & Rollman, B. (2023) · Journal of the Academy of Consultation-Liaison Psychiatry · doi:10.1016/j.jaclp.2023.03.008 · Cited by 1
Characteristics of blood biomarkers and eating behavior among older community-dwelling adults with typical and atypical depression
Takeuchi, T., Hashimoto, K., Ihara, K., Obuchi, S. P., Hirano, H., Fujiwara, Y., Kawai, H., Kojima, M., & Hashizume, M. (2023) · Clinical Nutrition Open Science · doi:10.1016/j.nutos.2023.05.004 · Cited by 2
Genetic architecture of DCC and influence on psychological, psychiatric and cardiometabolic traits in multiple ancestry groups in UK Biobank
Forsyth, L., Aman, A., Cullen, B., Graham, N., Lyall, D. M., Lyall, L. M., Pell, J. P., Ward, J., Smıth, D. J., & Strawbridge, R. J. (2023) · Journal of Affective Disorders · doi:10.1016/j.jad.2023.07.052 · Cited by 2
L’asse dello stress: regolazione neuro-endocrino-immuno-metabolica e ruolo nello sviluppo della sindrome metabolica e della depressione
Lombardo, G., Belcastro, S., Mondelli, V., & Gianotti, L. (2023) · L Endocrinologo · doi:10.1007/s40619-023-01379-3 · Cited by 4
“Inoltre, Milaneschi e colleghi riportano una forte correla-zione tra le caratteristiche atipiche della depressione, come ipersonnia e iperfagia, e le disfunzioni immunometaboliche e suggeriscono la presenza di una speciﬁca condizione di “depressione immunometabolica” [38].”
Background
Divergent transcriptomic profiles in depressed individuals with hyper- and hypophagia implicating inflammatory status
Dan, S., Hall, J. R., Holsen, L. M., & Klengel, T. (2023) · Journal of Psychiatric Research · doi:10.1016/j.jpsychires.2024.09.020 · Cited by 2
Leptin and leptin receptor gene polymorphisms and depression treatment response
Tavast, I.-M., Solismaa, A., Lyytikäinen, L., Mononen, N., Moilanen, E., Hämäläinen, M., Lehtimäki, T. J., & Kampman, O. (2024) · Acta Neuropsychiatrica · doi:10.1017/neu.2024.43 · Cited by 3
Association of aberrant gray matter neurite density with neurovegetative symptom in atypical depression
Zhang, H., Zhou, R., Lu, W., Su, Y., Cai, Y., Huang, J., Shen, H., Ding, L., Wang, Y., Zhang, M., et al. (2025) · Journal of Affective Disorders · doi:10.1016/j.jad.2025.04.064 · Cited by 2
Differential Expression of Lipid Metabolism Genes, CROT and ABCG1, in Obese Patients with Comorbid Depressive Disorder and Risk of MASLD
Jurek, J. M., Rusu, E. C., Camaron, J., Clavero-Mestres, H., Aguilar, C., Riesco, D., Xifré, B., Chicote, J. U., Martínez, S., Vives, M., et al. (2025) · Metabolites · doi:10.3390/metabo15060392 · Cited by 2
“There is growing evidence to suggest a bidirectional link between depression and metabolic complications such as dyslipidemia [6], arising from obesity [4,32], including MASLD [3], with a proposed role of perturbed lipid metabolism [15,33–35].”
Impact of obesity on immune function and depressive disorder: integrative review
Bezerra, T. P. T., dos Santos, R. M., Minervino, A. J., & Dejani, N. N. (2023) · Debates em Psiquiatria · doi:10.25118/2763-9037.2023.v13.631 · Cited by 2
Stratifying depression by neuroticism: revisiting a diagnostic tradition using GWAS dataPreprint
Adams, M. J., Howard, D. M., Michelle Luciano, A., Clarke, T., Davies, G., Hill, W. D., Smıth, D. J., Deary, I. J., Porteous, D. J., & McIntosh, A. M. (2019) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/547828 · Cited by 2
Refining the scope of genetic influences on alcohol misuse through environmental stratification and gene–environment interaction
Savage, J. E., de Leeuw, C., Werme, J., Spit for Science Working Group, Dick, D. M., Danielle Posthuma, B., & van der Sluis, S. (2024) · Alcoholism Clinical and Experimental Research · doi:10.1111/acer.15425 · Cited by 1
Obesity mediate associations between depression and wet overactive bladder: Results from 2005 to 2020 NHANES
Zhang, J., Huang, S., Hu, C., Liao, C., Tang, Z., Li, N., Qian, Y., Luo, H., Tang, F., & He, Z. (2025) · Obesity Research & Clinical Practice · doi:10.1016/j.orcp.2025.05.002 · Cited by 1
Obesity in Children and Adolescents and its Impact on Mental Health
Sethy, G., Samal, P., & Panda, M. (2025) · IntechOpen eBooks · doi:10.5772/intechopen.1010240 · Cited by 1
Dysosmobacter welbionis J115T reduces stress-like phenotype in high-fat diet-induced obese female mice
Wong, G. C., Delzenne, N. M., Hul, M. V., & Cani, P. D. (2025) · Beneficial Microbes · doi:10.1163/18762891-bja00091 · Cited by 1
Obesity and Depression
Ho, D., Won, H. Y., Kim, Y., & Lim, W. (2026) · Advances in experimental medicine and biology · doi:10.1007/978-981-95-6872-7_12 · Cited by 1
Depression and Hopelessness as Possible Predictors of Weight Change among Obese Day-Hospital Patients: A 6-Months Follow-Up Study.
Vuksan-Ćusa, B., Jakšić, N., Matovinović, M., Baretić, M., Vuksan-Ćusa, Z., Mustač, F., Tudor, K. I., Šagud, M., & Marčinko, D. (2020) · PubMed · Cited by 1
Les premiers succès de la piste immuno-métabolique en psychiatrie de précision
Godin, O., Frajerman, A., Lengvenytė, A., Bernard, J., Andreazza, A. C., Étain, B., & Leboyer, M. (2025) · médecine/sciences · doi:10.1051/medsci/2025063 · Cited by 1
The Relationship Between Percentage Weight Loss and World Health Organization-Five Wellbeing Index (WHO-5) in Patients Having Bariatric Surgery
Wahab, R. A., Alruwaili, H., Coleman, T., Heneghan, H., Neff, K., le Roux, C. W., & Fallon, F. (2022) · Obesity Surgery · doi:10.1007/s11695-022-06010-2 · Cited by 2
S.02.01 Immune-metabolic depression: evidence for a subtype of depression
Lamers, F., Milaneschi, Y., & Penninx, B. W. J. H. (2019) · European Neuropsychopharmacology · doi:10.1016/j.euroneuro.2019.09.022 · Cited by 1
Decoding Treatment Choice: Genetic and Phenotypic Analyses of Long-term Antidepressant AcceptabilityPreprint
Walker, A., Mitchell, B. L., Lin, T., Crouse, J. J., Albiñana, C., Yap, C. X., Lynall, M.-E., Lind, P. A., Cipriani, A., Byrne, E. M., et al. (2025) · medRxiv · doi:10.1101/2025.08.19.25333784 · Cited by 1
Estimating the genetic distance between subtypes of Major Depressive Disorder and their relationships with other traits using GDISPreprint
Thijssen, A. B., Milaneschi, Y., Bartels, M., Penninx, B. W. J. H., Pasman, J. A., Verweij, K. J. H., & Peyrot, W. J. (2025) · medRxiv · doi:10.1101/2025.11.18.25340484 · Cited by 2
Convergent Metabolic Dysregulations But Divergent Contributing Pathways Across Severe Mental Disorders: The Power of Combining Genetics and Metabolomics
Penninx, B. W. J. H., & Milaneschi, Y. (2026) · American Journal of Psychiatry · doi:10.1176/appi.ajp.20260392 · Cited by 1
Leveraging Molecular Genetic Approaches to Yield Insights Into Major Depression Etiology and Clinical Presentation
Peterson, R. E. (2017) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2017.3017
Interações entre depressão, qualidade de sono e hábitos de vida:
dos Santos, I. S. F., Luna, I. B. D. S., Silva, M. G. G., Silva, V. N. D. C., & dos Santos, E. R. R. (2020) · Jornal Memorial da Medicina · doi:10.37085/jmmv1.n2.2019.pp.18-23
The Relationship Between Body Composition, Glucose Metabolism, and Subtypes of Depressive Symptoms – Findings From the Helsinki Birth Cohort StudyPreprint
Eriksson, M. D., Eriksson, J. G., Korhonen, P. E., Salonen, M. K., Mikkola, T. M., Kajantie, E., Wasenius, N., von Bonsdorff, M. B., Kautiainen, H., & Laine, M. K. (2021) · Research Square · doi:10.21203/rs.3.rs-911998/v1
Impacto da dieta hiperlipídica e hipocalórica rica em ômega-3 na resposta clínica e no risco cardiometabólico de pacientes com depressão e obesidade
de Souza, I. M. (2021) · Digital Library of Theses and Dissertations (Universidade de São Paulo) · doi:10.11606/d.6.2021.tde-07012022-122626
Functional connectivity of the reward circuit predicts changes in appetite in depressionPreprint
Kroemer, N. B., Opel, N., Teckentrup, V., Li, M., Grotegerd, D., Meinert, S. L., Lemke, H., Kircher, T. T. J., Nenadić, I., Krug, A., et al. (2022) · doi:10.31234/osf.io/4ua8x
Sex and genetic specific effects on behavioral, but not metabolic, responses to a high fat diet in heterogeneous stock ratsPreprint
Deal, A. W., Thurman, A. L., Seshie, O., Szalanczy, A., Beeson, A., Cockerham, M., Risemberg, E. L., Lenzo, A., Ozimek, N., Langefeld, C. D., et al. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.03.25.485743
Characterisation and Genetic Architecture of Major Depressive Disorder Subgroups Defined by Weight and Sleep ChangesPreprint
Marshall, S., Adams, M. J., Evans, K. L., Strawbridge, R. J., Campbell, A., Hayward, C., McIntosh, A. M., & Thomson, P. A. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.08.30.504498
“Thus, it is becoming increasingly common for both genetic(7-9) and epidemiological studies(10-12) to utilise these symptoms over the full DSM-V criteria when examining atypical depression.”
BackgroundResultInfluential

Authors: Milaneschi, Y., Lamers, F., Peyrot, W. J., Baune, B. T., Breen, G., Dehghan, A., Forstner, A. J., Grabe, H. J., Homuth, G., Kan, C., Lewis, C., Mullins, N., Nauck, M., Pistis, G., Preisig, M., Rivera, M., Rietschel, M., Streit, F., Strohmaier, J., Teumer, A., Van der Auwera, S., Wray, N. R., Boomsma, D. I., Penninx, B. W. J. H., & for the CHARGE Inflammation Working Group and the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium
Affiliations: Amsterdam Neuroscience (NL)
The University of Adelaide (AU)
King's College London (GB)
Imperial College London (GB)
University of Bonn (DE)
Universitätsmedizin Greifswald (DE)
Centre Hospitalier Universitaire Vaudois (CH)
Universidad de Granada (ES)
Heidelberg University (DE)
Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
The University of Queensland (AU)
Vrije Universiteit Amsterdam (NL)
Corresponding author: Milaneschi, Yuri
ORCID: Milaneschi, Yuri
Lamers, Femke
Peyrot, Wouter J.
Baune, Bernhard T.
Breen, Gerome
Dehghan, Abbas
Grabe, Hans J.
Homuth, Georg
Kan, Carol
Lewis, Cathryn
Mullins, Niamh
Pistis, Giorgio
Preisig, Martin
Rivera, Margarita
Rietschel, Marcella
Streit, Fabian
Strohmaier, Jana
Teumer, Alexander
Wray, Naomi R.
Boomsma, Dorret I.
Penninx, Brenda W. J. H.
Venue: JAMA Psychiatry
Publisher: American Medical Association (AMA)
Published: 2017-12-01
Volume: 74
Issue: 12
Pages: 1214
ISSN: 2168-622X (ISSN-L)
DOI: 10.1001/jamapsychiatry.2017.3016
PMC: PMC6396812
OpenAlex: W2766503838
Cited by: 233
References: 56
Citations by year: 2026: 15 · 2025: 30 · 2024: 15 · 2023: 29 · 2022: 33 · 2021: 41 · 2020: 31 · 2019: 29 · 2018: 9 · 2017: 1
FWCI: 12.71
Type: journal article
Language: en
Open access: bronze
doi.org
Locations: JAMA Psychiatry (publishedVersion)
Europe PMC (PubMed Central) (publishedVersion)
PubMed Central (publishedVersion)
PubMed (publishedVersion)
Amsterdam UMC (VU Amsterdam) - Institutional Repository (publishedVersion)
EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
VU Research Portal (publishedVersion, other-oa)
ResearchOnline - JCU (James Cook University) (submittedVersion)
Research Portal (King's College London) (submittedVersion, other-oa)
Pure Amsterdam UMC (submittedVersion, cc-by)
RISalud Institutional Health Repository of Andalucía (submittedVersion, other-oa)
EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (submittedVersion)
UCL Discovery (University College London) (submittedVersion)
IRIS (submittedVersion)
Iris (University of Trento) (submittedVersion)
Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
SERVAL (Université de Lausanne) (submittedVersion)
Data Archiving and Networked Services (DANS) (submittedVersion)
Funders: National Science Foundation (33CS30-139468, 33CS30-148401, 33CSCO-122661)
Foundation for the National Institutes of Health (1RC2 MH089995)
Amgen
Pfizer
GlaxoSmithKline (3200B0–105993, 33CSCO-122661, 3200B0-118308, 33CS30-148401, 33CS30-139468)
Brigham and Women's Hospital
Massachusetts General Hospital
University of Southern California
Kaiser Permanente
Massachusetts Institute of Technology
Emory University
F. Hoffmann-La Roche
Washington University in St. Louis
Aarhus Universitet
Aarhus Universitetshospital
Johns Hopkins University
University of Texas Southwestern Medical Center
Universität Basel
Virginia Commonwealth University
South London and Maudsley NHS Foundation Trust
Wellcome Trust (104036/Z/14/Z)
QIMR Berghofer Medical Research Institute
Broad Institute
Universitätsmedizin Göttingen
National Institute for Health and Care Research (CL-2017-17-003)
King's College London
University College London
University of Oxford
Newcastle University
European Commission (QLG2-CT-2002-01254, LSHB-CT-2003–503428, 503428, 230374, 01ZZ0103, 01ZZ0403, 01254, 03ZIK012, 01ZZ9603, 334065, LSHB-CT-2003)
University of Glasgow
Cardiff University
Trinity College Dublin
Deutsche Forschungsgemeinschaft (Gr1912/5‐1, 01ZZ0403, 01ZZ9603, 03ZIK012, 01ZZ0103)
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (148401, 122661, 33CSCO, 118308, 105993, 230374, 3200B0, 33CS30, 139468)
Universiteit Leiden (10‐000‐1002)
Rijksuniversiteit Groningen (10‐000‐1002)
Stiftelsen för Strategisk Forskning
James Cook University
Queensland University of Technology
University of Queensland
ZonMw (Middelgroot‐911‐09‐032, 56-464-14192, 184.021.007, 911‐09‐032, 1RC2 MH089995, 10‐000‐1002)
Vrije Universiteit Amsterdam (2008.024)
Bundesministerium für Bildung und Forschung (01ZZ9603, 01ZZ0103, and 01ZZ0403, 01ZX1314G, 01GS08147, 03ZIK012, 01ZZ0403, and 01ZZ0403, 01ZX1314D, 01GS08144, 01ZZ0103, 01ZX1314A, 01ZZ9603)
Albert-Ludwigs-Universität Freiburg
Gentofte Hospital
Dalhousie University
Nederlandse Organisatie voor Wetenschappelijk Onderzoek (184021007, 10-000-1002, 56‐464‐14192, Spinozapremie 56-464-14192)
GGZ inGeest
Rivierduinen
GGZ Friesland
GGZ Drenthe
Nederlands Instituut voor Onderzoek van de Gezondheidszorg (10-000-1002)
Lundbeckfonden
University of Toronto
Università degli Studi di Trento
Karolinska Institutet
Novo Nordisk
Vetenskapsrådet (M-2005-1112)
Westfälische Wilhelms-Universität Münster
Leids Universitair Medisch Centrum
Universitair Medisch Centrum Groningen
Rigshospitalet
Region Hovedstaden
Háskóli Íslands
Dokuz Eylül Üniversitesi
Universidad de Granada
Tartu Ülikool
Rheinische Friedrich-Wilhelms-Universität Bonn
Chinese Society of Clinical Oncology
Siemens Healthineers (01ZZ0103, 01ZZ0403, 01ZZ9603)
H. Lundbeck A/S
Centre for Cognitive Ageing and Cognitive Epidemiology
Universität Greifswald
Ministry of Cultural Affairs
National Institutes of Health (184.021.007, 389875, EU/QLRT-2001-01254, 1s10od018164-01, 1r01mh081802-01, MH66206, N01MH90003, AA13321, MH059542, AA13320, MH059541, DA12854)
School of Medicine, Emory University
University of North Carolina at Chapel Hill
University of California, San Diego
McDonnell Center for Systems Neuroscience
Stanley Center for Psychiatric Research, Broad Institute
Department of Psychiatry, University of Toronto
Medical Research Council (G0701420, MR/K026992/1)
Australian Research Council (FT0991360, FT0991022, 389875, QLG2-CT-2002-01254)
Queensland Brain Institute
Institute of Molecular and Cell Biology
Statens Serum Institut
Medizinische Fakultät der Albert-Ludwigs-Universität Freiburg
National Institute on Alcohol Abuse and Alcoholism (R01AA014041, R01AA007535)
National Institute of Mental Health (MH66206, MH068457, N01‐MH‐90003, U01MH109528, MH-081802, RC2MH089995, MH089951, MH109532, U24MH068457, MH085520, R01MH060912, U01MH109532, R01MH059552, RC2MH089951, R01MH061686, MH089995, R01MH080403)
National Institute on Drug Abuse (K08DA019951)
National Cancer Institute
National Institute of Diabetes and Digestive and Kidney Diseases (U01DK066134)
Janssen Research and Development
Institute of Genetics
Division of Cancer Epidemiology and Genetics, National Cancer Institute
NHLBI Division of Intramural Research
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
Life Sciences › Neuroscience › Biological Psychiatry › Tryptophan and brain disorders
Health Sciences › Medicine › Pharmacology (medical) › Treatment of Major Depression
Keywords: major depressive disorder, atypical depression, obesity, genetic correlation, body mass index, C-reactive protein, leptin, polygenic risk, genetic overlap, Psychiatric Genomics Consortium, heritability
MeSH terms: Adult, C-Reactive Protein, Depressive Disorder, Major, Major Depressive Disorder, Female, Humans, International Cooperation, Male, Obesity, Psychiatric Status Rating Scales, Weight Gain, Body Mass Index, Genetic Predisposition to Disease, Diagnostic and Statistical Manual of Mental Disorders, Genome-Wide Association Study, Craving

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.

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Genetic Association of Major Depression With Atypical Features and Obesity-Related Immunometabolic Dysregulations

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