<i>APOL1</i> variants affect APOL1 plasma protein concentration: a UK Biobank study
Bibliographic record
Abstract
Abstract The APOL1 gene is associated with chronic kidney disease progression. Circulating APOL1 protein levels are likely to play a critical role. Using UK Biobank data from 43,330 participants with APOL1 protein concentration levels, we found that individuals self-reporting as Black or Black British individuals had significantly higher serum APOL1 levels than all other ethnicities. To investigate the genetic factors underlying this difference, we explored the impact of APOL1 genotypes and other potential modifiers on circulating APOL1 protein levels. We analysed APOL1 protein concentration data in 1,050 UK Biobank participants of recent sub-Saharan African ancestry, focusing on the APOL1 G1, G2, and N264K variants. APOL1 concentration showed a clear genotype-dependent effect: individuals with the G0/G0 genotype had the lowest levels, heterozygotes (G0/G1 and G0/G2), had intermediate levels, and individuals with the G2/G2 genotype had the highest levels, demonstrating a dose-dependent relationship. The N264K variant reduced protein levels on a G2 background (p = 6 x 10 −5 ). However, even after accounting for genotype, APOL1 protein levels in Black or Black British individuals was still higher than other ethnicities. A genome-wide association study on this population identified no genome-wide significant loci, other than the APOL1 gene itself (p = 3 x 10 −155 ) associated with APOL1 protein levels. Findings confirm APOL1 genotype as the major genetic determinant of circulating protein levels and provide new insights into the potential phenotypic effects of the G1, G2, and N264K variants.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".