LONGITUDINAL RELATIONSHIPS BETWEEN DEPRESSIVE SYMPTOM CLUSTERS AND INFLAMMATORY BIOMARKERS IMPLICATED IN CARDIOVASCULAR DISEASE IN PEOPLE WITH DEPRESSION

Systemic inflammation is one potential mechanism underlying the depression to cardiovascular disease (CVD) relationship. In addition, somatic rather than cognitive/affective symptoms of depression may be more predictive of poorer CVD outcomes due to systemic inflammation. However, the small existing literature in this area has yielded mixed results. Therefore, the present study aimed to examine longitudinal associations between depressive symptom clusters and inflammatory biomarkers implicated in CVD (i.e., interleukin-6, IL-6; and C-reactive protein, CRP) using data from the eIMPACT trial. In addition, race was examined as a moderator given findings from two previous studies.

The eIMPACT trial was a phase II, single-center randomized controlled trial comparing 12 months of the eIMPACT intervention to usual primary care for depression. Participants were 216 primary care patients aged ≥ 50 years with a depressive disorder and CVD risk factors but no clinical CVD from a safety net healthcare system (M_age = 58.7 years, 78% female, 50% Black, M_education = 12.8 years). Depressive symptoms clusters (i.e., somatic and cognitive/affective clusters) were assessed using the Patient Health Questionnaire-9 (PHQ-9). IL-6 and high-sensitivity CRP were assessed by the local clinical research laboratory using R&D Systems ELISA kits. Change variables were modeled in MPlus using a latent difference score approach.

The results of this study were largely null. Very few associations between depressive symptom clusters and inflammatory biomarkers implicated in CVD were observed, and the detected relationships may be due to type I error. Similarly, only one association was observed for race as a moderator, and the detected relationship may be due to type I error. The present findings do not provide strong support for the longitudinal associations between depressive symptom clusters and inflammatory biomarkers implicated in CVD nor the moderating effects of race. However, the present findings do not rule out the possibility of these relationships given important study limitations, such as study design and power. Future prospective cohort studies with multiple waves of data collection are needed to determine the longitudinal associations between depression facets and various inflammatory biomarkers implicated in CVD. In addition, a biologically-based approach to identifying facets of depression – e.g., the endophenotype model – may provide a clearer understanding of the depression-inflammation relationship.