Mary-Ellen Lynall1, Lorinda Turner2, Junaid Bhatti3, Jonathan Cavanagh4, Peter de Boer5, Valeria Mondelli6, Declan Jones7, Wayne C Drevets8, Philip Cowen9, Neil A Harrison10, Carmine M Pariante11, Linda Pointon3, Menna R Clatworthy12, Edward Bullmore13. 1. Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom; Department of Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom; Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, United Kingdom. Electronic address: mel41@cam.ac.uk. 2. Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom; Department of Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom. 3. Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom. 4. Centre for Immunobiology, University of Glasgow and Sackler Institute of Psychobiological Research, Queen Elizabeth University Hospital, Glasgow, United Kingdom. 5. Neuroscience, Janssen Research & Development, Janssen Pharmaceutica NV, Beerse, Belgium. 6. Institute of Psychiatry, Psychology and Neuroscience, Department of Psychological Medicine, King's College London, London, United Kingdom; National Institute for Health Research Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, King's College London, London, United Kingdom. 7. Neuroscience External Innovation, Janssen Pharmaceuticals, London, United Kingdom. 8. Neuroscience Therapeutic Area, Janssen Research & Development, San Diego, California. 9. Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford, United Kingdom. 10. School of Medicine, School of Psychology, Cardiff University Brain Research Imaging Centre, Cardiff, United Kingdom. 11. Stress, Psychiatry and Immunology Laboratory & Perinatal Psychiatry, Maurice Wohl Clinical Neuroscience Institute, King's College London, London, United Kingdom. 12. Department of Medicine, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom. 13. Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, United Kingdom; Cambridgeshire and Peterborough National Health Service Foundation Trust, Cambridge, United Kingdom.
Abstract
BACKGROUND: Depression has been associated with increased inflammatory proteins, but changes in circulating immune cells are less well defined. METHODS: We used multiparametric flow cytometry to count 14 subsets of peripheral blood cells in 206 depression cases and 77 age- and sex-matched controls (N = 283). We used univariate and multivariate analyses to investigate the immunophenotypes associated with depression and depression severity. RESULTS: Depression cases, compared with controls, had significantly increased immune cell counts, especially neutrophils, CD4+ T cells, and monocytes, and increased inflammatory proteins (C-reactive protein and interleukin-6). Within-group analysis of cases demonstrated significant associations between the severity of depressive symptoms and increased myeloid and CD4+ T-cell counts. Depression cases were partitioned into 2 subgroups by forced binary clustering of cell counts: the inflamed depression subgroup (n = 81 out of 206; 39%) had increased monocyte, CD4+, and neutrophil counts; increased C-reactive protein and interleukin-6; and more severe depression than the uninflamed majority of cases. Relaxing the presumption of a binary classification, data-driven analysis identified 4 subgroups of depression cases, 2 of which (n = 38 and n = 100; 67% collectively) were associated with increased inflammatory proteins and more severe depression but differed in terms of myeloid and lymphoid cell counts. Results were robust to potentially confounding effects of age, sex, body mass index, recent infection, and tobacco use. CONCLUSIONS: Peripheral immune cell counts were used to distinguish inflamed and uninflamed subgroups of depression and to indicate that there may be mechanistically distinct subgroups of inflamed depression.
BACKGROUND: Depression has been associated with increased inflammatory proteins, but changes in circulating immune cells are less well defined. METHODS: We used multiparametric flow cytometry to count 14 subsets of peripheral blood cells in 206 depression cases and 77 age- and sex-matched controls (N = 283). We used univariate and multivariate analyses to investigate the immunophenotypes associated with depression and depression severity. RESULTS: Depression cases, compared with controls, had significantly increased immune cell counts, especially neutrophils, CD4+ T cells, and monocytes, and increased inflammatory proteins (C-reactive protein and interleukin-6). Within-group analysis of cases demonstrated significant associations between the severity of depressive symptoms and increased myeloid and CD4+ T-cell counts. Depression cases were partitioned into 2 subgroups by forced binary clustering of cell counts: the inflamed depression subgroup (n = 81 out of 206; 39%) had increased monocyte, CD4+, and neutrophil counts; increased C-reactive protein and interleukin-6; and more severe depression than the uninflamed majority of cases. Relaxing the presumption of a binary classification, data-driven analysis identified 4 subgroups of depression cases, 2 of which (n = 38 and n = 100; 67% collectively) were associated with increased inflammatory proteins and more severe depression but differed in terms of myeloid and lymphoid cell counts. Results were robust to potentially confounding effects of age, sex, body mass index, recent infection, and tobacco use. CONCLUSIONS: Peripheral immune cell counts were used to distinguish inflamed and uninflamed subgroups of depression and to indicate that there may be mechanistically distinct subgroups of inflamed depression.
Authors: Elizabeth Torres; Katelynn B Zumpf; Jody D Ciolino; Crystal T Clark; Dorothy K Sit; Emily S Miller; Katherine L Wisner Journal: Arch Womens Ment Health Date: 2022-03-22 Impact factor: 3.633
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Authors: Rebecca T Veenhuis; Dionna W Williams; Erin N Shirk; Celina M Abreu; Edna A Ferreira; Jennifer M Coughlin; Todd T Brown; Pauline M Maki; Kathryn Anastos; Joan W Berman; Janice E Clements; Leah H Rubin Journal: JCI Insight Date: 2021-06-08