A Pilot Investigation of the Association Between Vpr Amino Acid Substitutions and Peripheral Immune Marker Levels in People With Human Immunodeficiency Virus: Implications for Neurocognitive Impairment
Bibliographic record
Abstract
Abstract Background Subtype-specific amino acid variations in viral proteins of human immunodeficiency virus type 1 (HIV-1) influence disease progression. Furthermore, Vpr sequence variation correlates with chronic inflammation, a central mechanism in HIV-1 (neuro)pathogenesis. Nevertheless, no clinical study has investigated the link between Vpr sequence variation and peripheral inflammation in people with HIV (PWH). The aim of this pilot study was to ascertain whether specific Vpr amino acid variants were associated with immune markers in PWH. Methods We included a unique cohort of 48 treatment-naive South African PWH to determine the association between blood-derived Vpr sequence variation and peripheral immune marker levels using Sanger sequencing and enzyme-linked immunosorbent assay analysis, respectively. Results Our findings indicate that among the many neuropathogenic Vpr amino acid variants and immune markers examined, after applying Bonferroni corrections (P = .05/3) and adjusting for sex and locality, soluble urokinase plasminogen activator receptor (suPAR) was nearing significance for higher levels in participants with the G41 amino acid variant compared to those with the S41 variant (P = .035). Furthermore, amino acid variations at position 41 (between G41 and S41) exhibited a significant association with suPAR (adjusted R2 = 0.089, β = .386 [95% confidence interval, .125–3.251]; P = .035). Conclusions These findings suggest that Vpr amino acid sequence variations might contribute to dysregulated inflammation, which could explain the observed association between specific Vpr variants and HIV-1 (neuro)pathogenesis found in prior research. These Vpr variants merit further investigation to fully understand their roles in HIV-1 pathogenesis and neuropathogenesis.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".