CROI 2024 Abstract eBook

Abstract eBook

Poster Abstracts

0.20]). There was no association between stunting and KABC MPI score in HIV negative adolescents. Conclusion: Cognitive function in ALWH was impaired across all domains, the effect was magnified in stunted individuals. ALWH faced a multitude of adverse childhood experiences including food insecurity and poverty which may have impacted on their cognitive and physical development. Future longitudinal studies are required to evaluate the impact of nutritional interventions on growth and cognition in ALWH. Development of Domain-General Cognition in Adolescents With HIV Is Slower Than Healthy Individuals Anantaporn Sena 1 , Sedthapong Chunamchai 2 , Akarin Hiransuthikul 1 , Phillip Chan 3 , Robert Paul 4 , Somchai Sriplienchan 5 , Thanyawee Puthanakit 2 , Serena Spudich 3 , Chaipat Chunharas 2 1 Chulalongkorn University, Bangkok, Thailand, 2 King Chulalongkorn Memorial Hospital, Bangkok, Thailand, 3 Yale University, New Haven, CT, USA, 4 University of Missouri St Louis, St Louis, MO, USA, 5 SEARCH, Bangkok, Thailand Background: While neuropsychological tests are designed to test specific cognitive abilities, a person who performs well in one task tends to perform well in others ("general cognitive ability" or g-factor). Previous studies showed that g-factor is associated with higher functional connectivity measuring by resting state fMRI. If perinatal HIV exposure can negatively affect white matter integrity, it's possible that the development of g-factor in these individuals might differ from individuals with no exposure. Here, we studied domain general cognitive ability and how it differed between older and younger adolescents with different HIV statuses. Methods: Data from the RESILIENCE study, a cohort conducted from 2015-2019, were analyzed to assess the correlation among 17 neuropsychological tests subscores across 6 cognitive domains. Participants were grouped by perinatal HIV status: HIV-exposed infected children group (HIV), HIV-exposed uninfected children group (HEU), and HIV-unexposed uninfected children group (HUU); and age: early adolescents (10-13 years) and middle adolescents (14-18) years. The number of moderate-to-strong correlations (Spearman's correlation coefficient ≥ 0.4) between cognitive tests were used as a marker of domain general cognitive ability. We used permutation methods for the test statistic. Connection strength within and between domains was also explored. Results: There were 96 HIV, 80 HEU, and 98 HUU in the early adolescent group and 105 HIV, 51 HEU, and 46 HUU in the middle adolescent group with matched genders. At the baseline, we found no difference in the number of connections. However, the HUU group showed a significantly greater increase in connections across age ranges (difference = 34) compared to the HIV (difference = 9, p<0.05) and HEU (difference = 5, p<0.001) groups. There was no difference in the increase of connections between the HIV and HEU groups. Additionally, only the HUU group had a significant decrease within-domain connection strength across age groups (average coefficient difference = 0.17, p<0.001). Conclusion: Our study reveals a slower progression of general cognitive ability among individuals exposed to HIV. This observation aligns with the well-documented impact of HIV on white matter integrity and extends our comprehension of cognitive development within the HIV-exposed population. Our future research will involve a direct exploration of functional connectivity and its relationship with the g-factor.

adverse outcomes remain poorly understood. This study seeks to examine factors that can predict resilience at both baseline and after a 2-year period. Methods: The RESILIENCE study is a 2-year cohort investigation that enrolled youth with perinatal HIV infection and controls. We collected data on various factors, including biological (age, HIV serostatus, viral load), neurological (regional brain volumes), and social (family and financial status). Resilient outcomes were assessed through cognitive function (intelligence, executive function, visuomotor, and memory), mental health (the symptom checklist SCL-90), risk-taking behavior (the behavioral health outcome questionnaire ACASI), and behavioral issues (the child behavior checklist). Multivariable logistic regression analysis with nested model comparisons was employed to identify predictors for each outcome. Results: The study comprised 30 youth living with HIV and 62 controls, with a median (IQR) age of 15 (13-16) years. At baseline, regional brain volumes emerged as the primary predictor of resilience for cognitive (AUC = 0.65, p<0.001) and mental health outcomes (AUC = 0.74, p<0.001). For resilience in risk-taking behavior, a combination of all biological and social factors proved to be the most effective predictor (AUC = 0.70, p<0.001), while resilience in behavioral issues was best predicted by a combination of regional brain volumes and social factors (AUC = 0.64, p<0.001). At week 96, regional brain volumes alone were the strongest predictors of cognitive problems (AUC = 0.71, p<0.001), mental health problems (AUC = 0.74, p<0.001), and risk-taking behavior (AUC = 0.66, p<0.001). In contrast, resilience in behavioral issues was predicted by a combination of regional brain volumes and biological factors (AUC = 0.75, p<0.001). Conclusion: Our findings reveal distinct predictors associated with resilience to various adverse outcomes in youth living with HIV. Cognitive and mental health outcomes are closely linked to regional brain volume, while behavioral issues and risk-taking behaviors are more strongly associated with a combination of biological and social factors. Recognizing these distinctions could enable targeted identification, monitoring, and intervention strategies for populations at special risk. Neurocognitive Performance in Adolescents Living With HIV in Zimbabwe Nyasha V Dzavakwa 1 , Annalie Shears 2 , Nicol Redzo 1 , Tsitsi Bandason 1 , Hilda A. Mujuru 3 , Joseph Piper 4 , Victoria Simms 5 , Rashida A. Ferrand 5 , for the VITALITY Mind Team 1 Biomedical Research and Training Institute, Harare, Zimbabwe, 2 Royal Manchester Children's Hospital, Manchester, United Kingdom, 3 University of Zimbabwe, Harare, Zimbabwe, 4 Queen Mary University of London, London, United Kingdom, 5 London School of Hygiene & Tropical Medicine, London, United Kingdom Background: Neurocognitive impairment in children and adolescents is complex and multifactorial. This study aimed to characterise the extent and nature of cognitive impairment in adolescents living with HIV (ALWH) in Harare, Zimbabwe and describe interactions between HIV, cognition and stunting. Methods: In this cross-sectional study, ALWH aged 11-19 years, who established on ART for at least 6 months, were recruited from a public sector HIV clinic. An age-matched HIV negative (HIV-) comparison group was recruited from the same catchment area. Neurocognitive function was evaluated using the Kaufman Assessment Battery for Children 2nd Edition (KABC-II). Anthropometry measurements alongside questionnaires assessing socioeconomic status (SES), school performance and food security were completed. SES was assessed using household asset ownership questions. Results: 503 participants (251 ALWH, 252 HIV-) were recruited from September 2022 to June 2023 and completed a KABC-II. ALWH median age 16 years, 45% male. HIV negative group median age 15 years, 50.4% male. Most participants aged 11-16 years were in education (95.3% ALWH, 91.2% HIV-). Among those in school, 38.0% of ALWH vs 17.9% of HIV negative participants were below expected school grade for age (p=0.001). 32% (n = 80) of ALWH were stunted compared to 10.8% (n = 27) of HIV-. More ALWH than the HIV-negative group were in the poorest SES group (29.1% vs 11.1%, p< 0.001) and experienced food insecurity (23.6 % vs 13.1 %, p=0.017). Adjusting for age, sex and SES, ALWH scored lower than HIV negative peers on KABC Mental Processing Index (MPI) -3.42 [95%CI -5.33, -1.51] and across all KABC subdomains (Sequential -2.49 [95%CI -4.68, -0.31], Simultaneous -3.83 [95%CI -6.15, 1.5], Learning -1.37 [95%CI -3.96, 1.21] and Planning -5.74 [95%CI -7.93, -3.55]). There was evidence of interaction of lower KABC MPI with stunting in ALWH (-4.71 [95%CI -9.62,

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Poster Abstracts

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