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Biomarker associations with insomnia and secondary sleep outcomes in persons with and without HIV in the POPPY-Sleep substudy: a cohort study

STUDY OBJECTIVES: We investigated associations between inflammatory profiles/clusters and sleep measures in people living with HIV and demographically-/lifestyle-similar HIV-negative controls in the Pharmacokinetic and clinical Observations in PeoPle over fiftY (POPPY)-Sleep substudy. METHODS: Prima...

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Detalles Bibliográficos
Autores principales: Bakewell, Nicholas, Sabin, Caroline A, Negi, Riya, Garcia-Leon, Alejandro, Winston, Alan, Sachikonye, Memory, Doyle, Nicki, Redline, Susan, Mallon, Patrick W G, Kunisaki, Ken M
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9742892/
https://www.ncbi.nlm.nih.gov/pubmed/36104003
http://dx.doi.org/10.1093/sleep/zsac212
Descripción
Sumario:STUDY OBJECTIVES: We investigated associations between inflammatory profiles/clusters and sleep measures in people living with HIV and demographically-/lifestyle-similar HIV-negative controls in the Pharmacokinetic and clinical Observations in PeoPle over fiftY (POPPY)-Sleep substudy. METHODS: Primary outcome was insomnia (Insomnia Severity Index [ISI]>15). Secondary sleep outcomes included 7-day actigraphy (e.g. mean/standard deviation of sleep duration/efficiency), overnight oximetry (e.g. oxygen desaturation index [ODI]) and patient-reported measures (Patient-Reported Outcomes Measurement Information System (PROMIS) sleep questionnaires). Participants were grouped using Principal Component Analysis of 31 biomarkers across several inflammatory pathways followed by cluster analysis. Between-cluster differences in baseline characteristics and sleep outcomes were assessed using Kruskal–Wallis/logistic regression/Chi-squared/Fisher’s exact tests. RESULTS: Of the 465 participants included (74% people with HIV, median [interquartile range] age 54 [50–60] years), only 18% had insomnia and secondary sleep outcomes suggested generally good sleep (e.g. ODI 3.1/hr [1.5–6.4]). Three clusters with distinct inflammatory profiles were identified: “gut/immune activation” (n = 47), “neurovascular” (n = 209), and “reference” (relatively lower inflammation; n = 209). The “neurovascular” cluster included higher proportions of people with HIV, obesity (BMI>30 kg/m(2)), and previous cardiovascular disease, mental health disorder, and arthritis of knee/hip relative to the other two clusters. No clinically relevant between-cluster differences were observed in proportions with insomnia (17%, 18%, 20%) before (p = .76) or after (p = .75) adjustment for potential confounders. Few associations were observed among actigraphy, oximetry, and PROMIS measures. CONCLUSIONS: Although associations could exist with other sleep measures or biomarker types not assessed, our findings do not support a strong association between sleep and inflammation in people with HIV.