The Association Between Serum Mature and Precursor Brain-Derived Neurotrophic Factor and Neurocognitive Function in People With Human Immunodeficiency Virus: A Longitudinal Study
Bibliographic record
Abstract
Abstract Background Despite antiretroviral therapy (ART), human immunodeficiency virus (HIV)–associated neurocognitive impairment persists. We investigated the association between serum levels of mature brain-derived neurotrophic factor (mBDNF), precursor brain-derived neurotrophic factor (proBDNF), and neurocognitive changes over time among adults with HIV in sub-Saharan Africa, seeking to elucidate the interplay between neurotrophic factors and neurocognitive outcomes post-ART. Methods Utilizing data from the ACTG 5199 study in Johannesburg and Harare, serum mBDNF and proBDNF levels were measured via enzyme-linked immunosorbent assay. Neurocognitive performance was assessed at baseline and 24, 48, and 96 weeks using neuropsychological tests. The Friedman test and linear mixed-effects models were used to assess changes in mBDNF, proBDNF, and neurocognitive performance over time, accounting for individual variability and adjusting for multiple comparisons. Results Among 155 participants, there were significant cognitive improvements (P < .001) and a rise in mBDNF levels from baseline to 96 weeks. The proBDNF levels initially remained stable (P = .57) but notably increased by 48 weeks (P = .04). Higher mBDNF levels were positively associated with enhanced neurocognitive performance at 48 weeks (β = .16, P = .01) and 96 weeks (β = .32, P < .001). Similarly, higher proBDNF levels were positively associated with neurocognitive performance at 96 weeks (β = .25, P < .001). Conclusions This study highlights the significant association between serum BDNF levels and neurocognitive improvement post-ART in adults with HIV. However, more research is needed to replicate these findings, establish causal relationships, and explore whether BDNF-enhancing activities can improve neurocognitive outcomes in people with HIV.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".