Plasma proteomic profile of inflammatory depressive symptoms
Source: PubMed Central Open Access, NCBI / U.S. National Library of Medicine
Background Previous studies suggest that specific depressive symptoms such as low energy, fatigue, sleep and appetite disturbances are associated with systemic low-grade inflammation. In this study, we investigated associations between an inflammatory symptom profile of depression and proteomic markers spanning inflammatory and metabolic pathways. Methods We analyzed 158 proteins related to inflammation and metabolism using proximity extension assay in blood samples from 165 patients with Major Depressive Disorder (MDD). Severity of inflammatory depressive symptoms was assessed using a composite score summarizing Patient Health Questionnaire-9 (PHQ-9) items related to fatigue and sleep/appetite disturbances. We used partial least squares (PLS), PLS discriminant analysis (PLS-DA) and linear regression models to identify proteins related to inflammatory depressive symptom severity. Results Out of the 158 proteins, 14 were selected by either PLS or PLS-DA. After false discovery rate correction, proteins identified by PLS or PLS-DA that remained significantly associated with more severe inflammatory depressive symptoms included several immunometabolic biomarkers, namelyinterleukin-6 (IL-6), hepatocyte growth factor, oncostatin M, thrombospondin-4, low affinity immunoglobulin gamma Fc region receptor II-a and intercellular adhesion molecule 1. With the exception of IL-6, none of these markers showed significant associations with the remaining PHQ-9 items that were not classified a
Abstract
Background Previous studies suggest that specific depressive symptoms such as low energy, fatigue, sleep and appetite disturbances are associated with systemic low-grade inflammation. In this study, we investigated associations between an inflammatory symptom profile of depression and proteomic markers spanning inflammatory and metabolic pathways. Methods We analyzed 158 proteins related to inflammation and metabolism using proximity extension assay in blood samples from 165 patients with Major Depressive Disorder (MDD). Severity of inflammatory depressive symptoms was assessed using a composite score summarizing Patient Health Questionnaire-9 (PHQ-9) items related to fatigue and sleep/appetite disturbances. We used partial least squares (PLS), PLS discriminant analysis (PLS-DA) and linear regression models to identify proteins related to inflammatory depressive symptom severity. Results Out of the 158 proteins, 14 were selected by either PLS or PLS-DA. After false discovery rate correction, proteins identified by PLS or PLS-DA that remained significantly associated with more severe inflammatory depressive symptoms included several immunometabolic biomarkers, namelyinterleukin-6 (IL-6), hepatocyte growth factor, oncostatin M, thrombospondin-4, low affinity immunoglobulin gamma Fc region receptor II-a and intercellular adhesion molecule 1. With the exception of IL-6, none of these markers showed significant associations with the remaining PHQ-9 items that were not classified as inflammatory depressive symptoms. Conclusions These findings support the growing body of evidence linking inflammatory and metabolic protein alterations to specific depressive symptoms. abs0010 Highlights • Inflammation is known to be selectively associated with specific depressive symptoms. u0010 • Advances in proteomics allow simultaneous assays of large numbers of proteins. u0015 • We found links between immunometabolic markers and specific depressive symptoms. u0020 • We highlight depression heterogeneity and possible differences in pathophysiology. u0025 simple ulist0010 author-highlights abs0015