| Title: | Immune and metabolic disturbance as a function of genetic risk and phase of illness in major depression |
| Journal: | Brain Behavior & Immunity - Health |
| Published: | 27 Nov 2025 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/41431700/ |
| DOI: | https://doi.org/10.1016/j.bbih.2025.101144 |
Publication 16781
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Abstract
Immune and metabolic factors are important in the pathophysiology of major depressive disorder (MDD) but we know little about how these factors manifest in relation to the status of depressive illness-from genetic risk for MDD, to a depressive episode, to depression in remission. Using genetic, diagnostic, biometric, and blood-bioassay data from the UK Biobank, we examined measures of pro-inflammatory signaling (C-reactive protein) and metabolic dysfunction (metabolic syndrome symptomatology) in females (N = 37,806) and males (N = 17,946) as a function of polygenic load for MDD (high versus low) interacting with depression status (never depressed, currently depressed, or depression in remission). We examined socioeconomic status (SES) as an exploratory factor in this design. Groups were matched for several confounders using a propensity-matching algorithm (females: n = 6301 per group for N = 37,806; n = 2991 per group for N = 17,946). In females we found increased inflammation and metabolic dysfunction in the higher-versus-lower PRS quartile, in those below-versus-above the median SES, and in those suffering currently from depression relative to their remitted depressed and healthy counterparts. This association remained when considering only non-psychotropic-medicated persons. Nonetheless, we also saw in both male and female samples that measures of immunological and metabolic dysfunction increased with increasing anti-depressant medication load. We discuss these findings in terms of the epidemiological significance of immune and metabolic functioning in depression and their paradoxical relation with antidepressant treatment.</p>
8 Authors
- David M. Howard
- Lachlan Gilchrist
- Petroula Proitsi
- Elisabeth R. Paul
- Markus Heilig
- Lars Östman
- Robin Kämpe
- J. Paul Hamilton
1 Application
| Application ID | Title |
|---|---|
| 49037 | Reliable neural signatures in major depressive disorder: A machine-learning investigation of a large dataset. |
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