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

2017· article· en· W2766503838 on OpenAlexfundno aff
Yuri Milaneschi, Femke Lamers, Wouter J. Peyrot, Bernhard T. Baune, Gerome Breen, Abbas Dehghan, Andreas J. Forstner, Hans J. Grabe, Georg Homuth, Carol Kan, Cathryn M. Lewis, Niamh Mullins, Matthias Nauck, Giorgio Pistis, Martin Preisig, Margarita Rivera, Marcella Rietschel, Fabian Streit, Jana Strohmaier, Alexander Teumer, Sandra Van der Auwera, Naomi R. Wray, Dorret I. Boomsma, Brenda W.J.H. Penninx

Bibliographic record

VenueJAMA Psychiatry · 2017
Typearticle
Languageen
FieldNeuroscience
TopicTryptophan and brain disorders
Canadian institutionsnot available
FundersDivision of Cancer Epidemiology and Genetics, National Cancer InstituteNational Institute of Mental HealthNHLBI Division of Intramural ResearchInstitute of Molecular and Cell BiologyStanley Center for Psychiatric Research, Broad InstituteUniversity of North Carolina at Chapel HillSchool of Medicine, Emory UniversityNational Institutes of HealthMinistry of Cultural AffairsH. Lundbeck A/SMedical Research CouncilSiemens HealthineersTartu ÜlikoolLeids Universitair Medisch CentrumWestfälische Wilhelms-Universität MünsterDokuz Eylül ÜniversitesiVetenskapsrådetNovo NordiskUniversity of TorontoNederlands Instituut voor Onderzoek van de GezondheidszorgMedizinische Fakultät der Albert-Ludwigs-Universität FreiburgRegion HovedstadenGGZ DrentheInstitute of GeneticsDepartment of Psychiatry, University of TorontoUniversität GreifswaldGGZ FrieslandStatens Serum InstitutGGZ inGeestHáskóli ÍslandsBundesministerium für Bildung und ForschungJanssen Research and DevelopmentZonMwRijksuniversiteit GroningenNederlandse Organisatie voor Wetenschappelijk OnderzoekGentofte HospitalDeutsche ForschungsgemeinschaftAustralian Research CouncilTrinity College DublinUniversiteit LeidenSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungUniversity of GlasgowRheinische Friedrich-Wilhelms-Universität BonnUniversitair Medisch Centrum GroningenUniversità degli Studi di TrentoNewcastle UniversityVrije Universiteit AmsterdamStiftelsen för Strategisk ForskningUniversity of OxfordNational Cancer InstituteLundbeckfondenUniversity College LondonAlbert-Ludwigs-Universität FreiburgKing's College LondonAarhus UniversitetMassachusetts Institute of TechnologyUniversität BaselQIMR Berghofer Medical Research InstituteSouth London and Maudsley NHS Foundation TrustVirginia Commonwealth UniversityJames Cook UniversityCardiff UniversityUniversity of Texas Southwestern Medical CenterUniversity of Southern CaliforniaFoundation for the National Institutes of HealthBroad InstituteF. Hoffmann-La RocheQueensland University of TechnologyBrigham and Women's HospitalKaiser PermanenteQueensland Brain InstituteKarolinska InstitutetUniversity of QueenslandEmory UniversityNational Institute for Health and Care ResearchUniversidad de GranadaRigshospitaletAarhus UniversitetshospitalDalhousie UniversityUniversitätsmedizin GöttingenGlaxoSmithKlineCentre for Cognitive Ageing and Cognitive EpidemiologyWashington University in St. LouisEuropean CommissionWellcome TrustNational Science FoundationMassachusetts General HospitalRivierduinenPfizerMcDonnell Center for Systems NeuroscienceUniversity of California, San DiegoJohns Hopkins UniversityChinese Society of Clinical OncologyAmgen
KeywordsDepression (economics)Association (psychology)ObesityMedicineGenome-wide association studyPsychiatryPsychologyGeneticsBiologyInternal medicineSingle-nucleotide polymorphismGenotypeGenePsychotherapist

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.234
Teacher spread0.228 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations247
Published2017
Admission routes1
Has abstractyes

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