Patterns and Predictors of Cognitive Function Among Virally Suppressed Women With HIV

• Main Authors: Raha M. Dastgheyb, Alison S. Buchholz, Kathryn C. Fitzgerald, Yanxun Xu, Dionna W. Williams, Gayle Springer, Kathryn Anastos, Deborah R. Gustafson, Amanda B. Spence, Adaora A. Adimora, Drenna Waldrop, David E. Vance, Joel Milam, Hector Bolivar, Kathleen M. Weber, Norman J. Haughey, Pauline M. Maki, Leah H. Rubin
• Format: Article
• Language: English
• Published: Frontiers Media S.A. 2021-02-01
• Series: Frontiers in Neurology
• Subjects: HIV; cognition; women; heterogeneity; phenotypes; random forest
• Online Access: https://www.frontiersin.org/articles/10.3389/fneur.2021.604984/full
• ISSN: 1664-2295

Cognitive impairment remains frequent and heterogeneous in presentation and severity among virally suppressed (VS) women with HIV (WWH). We identified cognitive profiles among 929 VS-WWH and 717 HIV-uninfected women from 11 Women's Interagency HIV Study sites at their first neuropsychological (NP) test battery completion comprised of: Hopkins Verbal Learning Test-Revised, Trail Making, Symbol Digit Modalities, Grooved Pegboard, Stroop, Letter/Animal Fluency, and Letter-Number Sequencing. Using 17 NP performance metrics (T-scores), we used Kohonen self-organizing maps to identify patterns of high-dimensional data by mapping participants to similar nodes based on T-scores and clustering those nodes. Among VS-WWH, nine clusters were identified (entropy = 0.990) with four having average T-scores ≥45 for all metrics and thus combined into an “unimpaired” profile (n = 311). Impaired profiles consisted of weaknesses in: (1) sequencing (Profile-1; n = 129), (2) speed (Profile-2; n = 144), (3) learning + recognition (Profile-3; n = 137), (4) learning + memory (Profile-4; n = 86), and (5) learning + processing speed + attention + executive function (Profile-5; n = 122). Sociodemographic, behavioral, and clinical variables differentiated profile membership using Random Forest models. The top 10 variables distinguishing the combined impaired vs. unimpaired profiles were: clinic site, age, education, race, illicit substance use, current and nadir CD4 count, duration of effective antiretrovirals, and protease inhibitor use. Additional variables differentiating each impaired from unimpaired profile included: depression, stress-symptoms, income (Profile-1); depression, employment (Profile 2); depression, integrase inhibitor (INSTI) use (Profile-3); employment, INSTI use, income, atazanavir use, non-ART medications with anticholinergic properties (Profile-4); and marijuana use (Profile-5). Findings highlight consideration of NP profile heterogeneity and potential modifiable factors contributing to impaired profiles.