Biomarkers panels can predict fatigue, depression and pain in persons living with HIV: A pilot study.

ABSTRACT

BACKGROUND: Persons living with HIV experience high symptom burden that can negatively impact medication adherence, work productivity, and quality of life. Symptoms are highly subjective, which can lead to under- or improper treatment. The purpose of this exploratory study was to examine relationships between circulating biomarkers representative of inflammatory, coagulation, and vascular function pathways and prevalent HIV symptoms. SETTING AND SAMPLE Adults >18 years who were diagnosed with HIV and spoke English for this cross-sectional study were recruited from community clinics and organizations. METHODS: Symptom burden was measured with the HIV Symptom Index; depression with the Patient Health Questionnaire. Human multiplex kits were used to determine serum concentrations of select biomarkers representing inflammatory, coagulation, and vascular function pathways. The biomarkers were included as features in machine learning models to determine which biomarkers predicted the most prevalent HIV symptoms (fatigue and muscle/joint pain) and the symptom of depression. RESULTS: Participants (N = 32) were representative of the local population of people with HIV, being mostly Black (54.4%) and male (60.6%). Depression was predicted by age, gender, glucose, hemoglobin A1c, and inflammation. Muscle/joint pain was predicted by adiponectin, C-reactive protein, and serum amyloid A (SAA). Fatigue was predicted by adiponectin, SAA, and soluble interleukin-1 receptor type II (sIL-1RII). CONCLUSION: Biomarker clusters can be a tool to monitor symptoms. Adding an objective measure to subjective patient experiences could improve management and monitoring of symptoms. Defining a biomarker cluster for the objective assessment of HIV symptoms warrants further investigation; however, the presence of comorbid conditions needs to be controlled.