The Association Between APOL1 Risk Alleles and Longitudinal Kidney Function Differs by HIV Viral Suppression Status
Bibliographic record
Abstract
BACKGROUND: Existing data suggest that human immunodeficiency virus (HIV)-infected African Americans carrying 2 copies of the APOL1 risk alleles have greater risk of kidney disease than noncarriers. We sought to determine whether HIV RNA suppression mitigates APOL1-related kidney function decline among African Americans enrolled in the Multicenter AIDS Cohort Study. METHODS: We genotyped HIV-infected men for the G1 and G2 risk alleles and ancestry informative markers. Mixed-effects models were used to estimate the annual rate of estimated glomerular filtration rate (eGFR) decline, comparing men carrying 2 (high-risk) vs 0-1 risk allele (low-risk). Effect modification by HIV suppression status (defined as HIV type 1 RNA level <400 copies/mL for >90% of follow-up time) was evaluated using interaction terms and stratified analyses. RESULTS: Of the 333 African American men included in this study, 54 (16%) carried the APOL1 high-risk genotype. Among HIV-infected men with unsuppressed viral loads, those with the high-risk genotype had a 2.42 mL/minute/1.73 m(2) (95% confidence interval [CI], -3.52 to -1.32) faster annual eGFR decline than men with the low-risk genotype. This association was independent of age, comorbid conditions, baseline eGFR, ancestry, and HIV-related factors. In contrast, the rate of decline was similar by APOL1 genotype among men with sustained viral suppression (-0.16 mL/minute/1.73 m(2)/year; 95% CI, -.59 to .27; P for interaction <.001). CONCLUSIONS: Unsuppressed HIV-infected African Americans with the APOL1 high-risk genotype experience an accelerated rate of kidney function decline; HIV suppression with antiretroviral therapy may reduce these deleterious renal effects.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".