Body mass index and inflammation in depression and treatment-resistant depression: a Mendelian randomisation study
dc.contributor.author | Karageorgiou, V | |
dc.contributor.author | Casanova, F | |
dc.contributor.author | O'Loughlin, J | |
dc.contributor.author | Green, H | |
dc.contributor.author | McKinley, TJ | |
dc.contributor.author | Bowden, J | |
dc.contributor.author | Tyrrell, J | |
dc.date.accessioned | 2023-11-14T10:27:31Z | |
dc.date.issued | 2023-09-14 | |
dc.date.updated | 2023-11-14T08:31:10Z | |
dc.description.abstract | BACKGROUND: Major depressive disorder (MDD) has a significant impact on global burden of disease. Complications in clinical management can occur when response to pharmacological modalities is considered inadequate and symptoms persist (treatment-resistant depression (TRD)). We aim to investigate inflammation, proxied by C-reactive protein (CRP) levels, and body mass index (BMI) as putative causal risk factors for depression and subsequent treatment resistance, leveraging genetic information to avoid confounding via Mendelian randomisation (MR). METHODS: We used the European UK Biobank subcohort ([Formula: see text]), the mental health questionnaire (MHQ) and clinical records. For treatment resistance, a previously curated phenotype based on general practitioner (GP) records and prescription data was employed. We applied univariable and multivariable MR models to genetically predict the exposures and assess their causal contribution to a range of depression outcomes. We used a range of univariable, multivariable and mediation MR models techniques to address our research question with maximum rigour. In addition, we developed a novel statistical procedure to apply pleiotropy-robust multivariable MR to one sample data and employed a Bayesian bootstrap procedure to accurately quantify estimate uncertainty in mediation analysis which outperforms standard approaches in sparse binary outcomes. Given the flexibility of the one-sample design, we evaluated age and sex as moderators of the effects. RESULTS: In univariable MR models, genetically predicted BMI was positively associated with depression outcomes, including MDD ([Formula: see text] ([Formula: see text] CI): 0.133(0.072, 0.205)) and TRD (0.347(0.002, 0.682)), with a larger magnitude in females and with age acting as a moderator of the effect of BMI on severity of depression (0.22(0.050, 0.389)). Multivariable MR analyses suggested an independent causal effect of BMI on TRD not through CRP (0.395(0.004, 0.732)). Our mediation analyses suggested that the effect of CRP on severity of depression was partly mediated by BMI. Individuals with TRD ([Formula: see text]) observationally had higher CRP and BMI compared with individuals with MDD alone and healthy controls. DISCUSSION: Our work supports the assertion that BMI exerts a causal effect on a range of clinical and questionnaire-based depression phenotypes, with the effect being stronger in females and in younger individuals. We show that this effect is independent of inflammation proxied by CRP levels as the effects of CRP do not persist when jointly estimated with BMI. This is consistent with previous evidence suggesting that overweight contributed to depression even in the absence of any metabolic consequences. It appears that BMI exerts an effect on TRD that persists when we account for BMI influencing MDD. | en_GB |
dc.description.sponsorship | National Institute for Health and Care Research (NIHR) | en_GB |
dc.format.extent | 355- | |
dc.format.medium | Electronic | |
dc.identifier.citation | Vol. 21, article 355 | en_GB |
dc.identifier.doi | https://doi.org/10.1186/s12916-023-03001-7 | |
dc.identifier.uri | http://hdl.handle.net/10871/134520 | |
dc.identifier | ORCID: 0000-0002-9256-6065 (Tyrrell, Jessica) | |
dc.language.iso | en | en_GB |
dc.publisher | BMC | en_GB |
dc.relation.url | https://www.ncbi.nlm.nih.gov/pubmed/37710313 | en_GB |
dc.rights | © The Author(s) 2023. Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data | en_GB |
dc.subject | Body mass index | en_GB |
dc.subject | Depression | en_GB |
dc.subject | Mendelian randomisation | en_GB |
dc.title | Body mass index and inflammation in depression and treatment-resistant depression: a Mendelian randomisation study | en_GB |
dc.type | Article | en_GB |
dc.date.available | 2023-11-14T10:27:31Z | |
dc.identifier.issn | 1741-7015 | |
exeter.article-number | 355 | |
exeter.place-of-publication | England | |
dc.description | This is the final version. Available on open access from BMC via the DOI in this frecord | en_GB |
dc.identifier.eissn | 1741-7015 | |
dc.identifier.journal | BMC Medicine | en_GB |
dc.relation.ispartof | BMC Med, 21(1) | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | en_GB |
dcterms.dateAccepted | 2023-07-24 | |
dc.rights.license | CC BY | |
rioxxterms.version | VoR | en_GB |
rioxxterms.licenseref.startdate | 2023-09-14 | |
rioxxterms.type | Journal Article/Review | en_GB |
refterms.dateFCD | 2023-11-14T10:26:22Z | |
refterms.versionFCD | VoR | |
refterms.dateFOA | 2023-11-14T10:27:36Z | |
refterms.panel | A | en_GB |
refterms.dateFirstOnline | 2023-09-14 |
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