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Features of immunometabolic depression as predictors of antidepressant treatment outcomes: pooled analysis of four clinical trials

  • Amsterdam UMC - University of Amsterdam
  • Amsterdam Public Health
  • University of Texas Southwestern Medical Center
  • Stanford University
  • Faculty of Medicine and Health
  • The George Institute for Global Health
  • Department of Pediatrics, The University of Texas at Austin Dell Medical School, Austin, TX, USA
  • Duke University
  • National University of Singapore
  • Dalhousie University
  • University of Alberta
  • Aarhus University
  • Heidelberg University 
  • Amsterdam UMC
  • University of Texas Southwestern Medical Center, Metroplex Research Center , Dallas, Texas , USA.
  • DDepartment of Chemical and Systems Biology, Stanford University, Palo Alto, CA 94305, USA; Institute for Stem Cell Biology and Regenerative Medicine, Stanford University, Palo Alto, California 94305, USA; Department of Developmental Biology, Stanford University, Palo Alto, California 94305, USA; Howard Hughes Medical Institute, Stanford School of Medicine, Stanford University, Palo Alto...
  • Sydney School of Public Health, Sydney Medical School, University of Sydney, Sydney, Australia.
  • Human Genetics Center, The University of Texas School of Public Health, The University of Texas Graduate School of Biomedical Sciences at Houston, The University of Texas Health Science Center at Houston, Houston, Texas 77030, USA.
  • National Heart Centre Singapore and, Duke-National University of Singapore Graduate School Medicine, Singapore.
  • Department of Medicine, University of Alberta, Edmonton, Alberta, Canada.
  • Department of Clinical Medicine
  • University of Heidelberg, Heidelberg, Germany

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Background Profiling patients on a proposed 'immunometabolic depression' (IMD) dimension, described as a cluster of atypical depressive symptoms related to energy regulation and immunometabolic dysregulations, may optimise personalised treatment. Aims To test the hypothesis that baseline IMD features predict poorer treatment outcomes with antidepressants. Method Data on 2551 individuals with depression across the iSPOT-D (n = 967), CO-MED (n = 665), GENDEP (n = 773) and EMBARC (n = 146) clinical trials were used. Predictors included baseline severity of atypical energy-related symptoms (AES), body mass index (BMI) and C-reactive protein levels (CRP, three trials only) separately and aggregated into an IMD index. Mixed models on the primary outcome (change in depressive symptom severity) and logistic regressions on secondary outcomes (response and remission) were conducted for the individual trial data-sets and pooled using random-effects meta-analyses. Results Although AES severity and BMI did not predict changes in depressive symptom severity, higher baseline CRP predicted smaller reductions in depressive symptoms (n = 376, βpooled = 0.06, P = 0.049, 95% CI 0.0001-0.12, I2 = 3.61%); this was also found for an IMD index combining these features (n = 372, βpooled = 0.12, s.e. = 0.12, P = 0.031, 95% CI 0.01-0.22, I2 = 23.91%), with a higher - but still small - effect size compared with CRP. Confining analyses to selective serotonin reuptake inhibitor users indicated larger effects of CRP (βpooled = 0.16) and the IMD index (βpooled = 0.20). Baseline IMD features, both separately and combined, did not predict response or remission. Conclusions Depressive symptoms of people with more IMD features improved less when treated with antidepressants. However, clinical relevance is limited owing to small effect sizes in inconsistent associations. Whether these patients would benefit more from treatments targeting immunometabolic pathways remains to be investigated.
Original languageEnglish
Pages (from-to)89-97
Number of pages9
JournalBritish journal of psychiatry
Volume224
Issue number3
Early online date22 Dec 2023
DOIs
Publication statusPublished - 22 Mar 2024

Keywords

  • Antidepressants
  • depressive disorders
  • inflammation
  • profiling
  • treatment

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