Untangling the influence of depression on clinical risks: role of leukocytes and somatic symptoms

Abstract

Abstract Background Depression has been associated with increased hospitalization and mortality risk, especially for cardiovascular causes. We previously found a composite circulating inflammation score (INFLA-score) to explain part of this link, although the role of its component and of depressive symptoms domains in this relationship is unexplored. Methods In an Italian population cohort (N = 13,191; age≥35 years; 51.7 % women; 4,856 hospitalizations and 471 deaths, median follow-up 7.28/8.24 years), we estimated the proportion of association explained by C-reactive protein levels (CRP), platelet count, granulocyte-to-lymphocyte ratio (GLR) and white blood cell counts (WBC), in multivariable Cox regressions modelling first hospitalization/mortality for all and cardiovascular (CVD), ischemic heart (IHD) and cerebrovascular disease (CeVD) causes vs depression severity based on an alternative validated version of PHQ-9. We also estimated the proportion of association explained by INFLA-score in the associations of polychoric factors tagging somatic and cognitive depressive symptoms with clinical risks. Results In models adjusted for age, sex and education, significant proportions of the positive influence of depression on clinical risks were explained by CRP (4.8% on IHD hospitalizations), GLR (11% on all-cause mortality) and WBC (24% on IHD/CeVD hospitalizations). Stable associations of somatic but not of cognitive depressive symptoms were observed with increased hospitalization risk (+16% for all causes, +14% for CVD causes), with INFLA-score again explaining small but significant proportions of these associations (2.5% for all causes, 8.6% for IHD causes). Conclusions These findings suggest a prominent explanatory role of leukocytes in the link between depression and clinical (especially CVD) risks, and highlight the importance of inflammation in the influence of somatic depressive symptoms. Therefore, acting on these factors may reduce clinical risks associated with depression. Key messages