0595 Inflammatory Plasma Biomarker Cluster Associations with Sleep in People with and without HIV. (25th May 2022) - Bakewell, Nicholas; Mallon, Patrick; Sabin, Caroline; Winston, Alan; Post, Frank; Sachikonye, Memory; Doyle, Nicki; Redline, Susan; Kunisaki, Ken
Abstract: Introduction: Sleep problems are commonly reported in people with HIV (PWH) and may be exacerbated by HIV-induced inflammation. We determined associations between systemic inflammation and objective/subjective sleep measures in PWH and demographically/lifestyle similar HIV-negative controls. Methods: Objective sleep measures from 7-day actigraphy (e.g. mean/standard deviation (SD) of wake after sleep onset [WASO], sleep duration/efficiency), overnight oximetry (oxygen desaturation index [ODI]), and patient-reported measures (Insomnia Severity Index [ISI] and Patient-Reported Outcomes Measurement Information System [PROMIS] sleep questionnaires) were assessed in participants in the multicenter POPPY-Sleep Study in the UK and Ireland. Principal Component Analysis using 31 plasma inflammatory biomarkers followed by cluster analysis previously identified 3 distinct inflammatory clusters: 1 (low inflammation), 2 (immune activation) and 3 (systemic inflammation). Baseline characteristics and between-cluster differences in sleep outcomes were assessed using Kruskal-Wallis or logistic regression/Chi-squared tests. Results: The 465 participants (74% PWH, median [interquartile range] age 54 [50-60] years) were mainly male (80%), men having sex with men (71%) and white (88%). Among PWH, most (98%) were on antiretroviral therapy, 92% had viral load ≤50 cps/mL and CD4 cell count was 610 [470-785] cells/mm3. Overall, 18% met ISI criteria for insomnia (ISI≥ 15), and other sleep measures suggested generally good sleep (e.g., ODI 3.1/hr [1.5-6.4]). Clusters 1 (n=209), 2 (n=47) and 3 (n=209) differed significantly for HIV status (73%, 60%, 78%, p=0.03); BMI (24.8, 25.9, 26.2 kg/m2, p=0.002); systolic blood pressure (126, 135, 126 mmHg, p=0.002); cardiovascular disease (39%, 28%, 53%, p=0.001) and arthritis (8%, 9%, 16%, p=0.02) – all factors associated with sleep problems. There were no clinically relevant between-biomarker-cluster differences in the proportions with insomnia (17%, 18%, 20%) either before (p=0.76) or after (p=0.75) adjustment for potential confounders. Few associations were observed among other actigraphy, oximetry and PROMIS measures. Conclusion: Despite observed differences in clinical factors associated with sleep problems, we found no consistent or strong associations between inflammatory biomarker clusters and a range of sleep outcomes. Although associations could exist with other sleep outcomes (e.g. sleep architecture) or biomarker types (e.g. cerebrospinal fluid) not assessed, our findings do not support a strong association between sleep and plasma inflammatory biomarkers in this population. Support (If Any): NIH R01HL131049