Increased Circulating suPAR Levels in African Patients with HIV
Bibliographic record
Abstract
Background: Decline in kidney function associated with APOL1 risk alleles is dependent on circulating suPAR levels in African American (AA) patients. Yet, little is known among HIV infected persons in sub-Saharan Africa, and epidemiological data from this region regarding APOL1 risk status is scarce. We aimed to determine APOL1 risk variants, plasma suPAR levels and estimated kidney function in HIV patients in Zambia. Methods: We performed a cross-sectional study with 480 adult HIV infected persons on anti-retroviral treatment (ART) (women, 64.8%) in Lusaka, Zambia. APOL1 genotyping was done to determine the prevalence of the risk alleles; plasma suPAR levels were assayed and estimated GFR (eGFR) was calculated by CKD-EPI creatinine-based formula. Results: Plasma suPAR levels were increased and were negatively correlated to eGFR, whether less than 60 or not (r=-0.15, p=0.001). Women while younger (42 vs 46 years old for men, p=0.0003), had higher suPAR than men (3.68 ng/ml vs 3.07 ng/ml, p<0.0001). Ten out of 480 patients (2.1%) had CKD, and their suPAR levels were higher than patients without CKD (5.6 ng/ml vs 3.44 ng/ml, p<0.0001). Fifty patients (10.4%) had 2 APOL1 risk alleles (35 for women vs 15 for men); among those, 3 (6%) developed CKD (p=0.07). No difference in suPAR levels or eGFR was observed between patients who carried 2 APOL1 risk alleles and those with 1 or 0 risk allele. Conclusions: HIV infected persons in Zambia on ART have increased suPAR levels. The prevalence of two APOL1 risk alleles is similar as with AA HIV patients. A longitudinal study with a bigger cohort should reveal the relationship between suPAR, APOL1 risk alleles and kidney function. Funding: NIDDK Support
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".