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https://hdl.handle.net/2440/110373
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Type: | Journal article |
Title: | Genetic association of major depression with atypical features and obesity-related immunometabolic dysregulations. |
Author: | 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. et al. |
Citation: | JAMA Psychiatry, 2017; 74(12):1214-1225 |
Publisher: | American Medical Association |
Issue Date: | 2017 |
ISSN: | 2168-6238 2168-6238 |
Statement of Responsibility: | Yuri Milaneschi, Femke Lamers, Wouter J. Peyrot,MD, Bernhard T. Baune,MD, Gerome Breen, Abbas Dehghan, Andreas J. Forstner, Hans J. Grabe, Georg Homuth, Carol Kan, Cathryn 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, for the CHARGE Inflammation Working Group and the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium |
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. |
Keywords: | CHARGE Inflammation Working Group and the Major Depressive Disorder Working Group of the Psychiatric Genomics Consortium |
Rights: | © 2017 American Medical Association. All rights reserved. |
DOI: | 10.1001/jamapsychiatry.2017.3016 |
Grant ID: | http://purl.org/au-research/grants/nhmrc/241944 http://purl.org/au-research/grants/nhmrc/339462 http://purl.org/au-research/grants/nhmrc/389927 http://purl.org/au-research/grants/nhmrc/389875 http://purl.org/au-research/grants/nhmrc/389891 http://purl.org/au-research/grants/nhmrc/389892 http://purl.org/au-research/grants/nhmrc/389938 http://purl.org/au-research/grants/nhmrc/442915 http://purl.org/au-research/grants/nhmrc/442981 http://purl.org/au-research/grants/nhmrc/496675 http://purl.org/au-research/grants/nhmrc/496739 http://purl.org/au-research/grants/nhmrc/552485 http://purl.org/au-research/grants/nhmrc/552498 http://purl.org/au-research/grants/nhmrc/613602 http://purl.org/au-research/grants/nhmrc/613608 http://purl.org/au-research/grants/nhmrc/613674 http://purl.org/au-research/grants/nhmrc/619667 http://purl.org/au-research/grants/arc/FT0991360 http://purl.org/au-research/grants/arc/FT0991022 |
Published version: | http://dx.doi.org/10.1001/jamapsychiatry.2017.3016 |
Appears in Collections: | Aurora harvest 3 Medicine publications |
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