The MYH9/APOL1 region and chronic kidney disease in European-Americans
Bibliographic record
Abstract
Polymorphisms in the MYH9 and adjacent APOL1 gene region demonstrate a strong association with non-diabetic kidney disease in African-Americans. However, it is not known to what extent these polymorphisms are present in other ethnic groups. To examine the association of genetic polymorphisms in this region with chronic kidney disease (CKD; estimated glomerular filtration rate <60 ml/min/1.73 m(2)) in individuals of European ancestry, we examined rs4821480, an MYH9 single-nucleotide polymorphism (SNP) recently identified as associated with kidney disease in African-Americans, in 13 133 participants from the Framingham Heart Study (FHS) and Atherosclerosis Risk in Communities (ARIC) Study. In addition, we further interrogated the MYH9/APOL1 gene region using 282 SNPs for association with CKD using age-, sex- and center-adjusted models and performed a meta-analysis of the results from both studies. Because of prior data linking rs4821480 and kidney disease, we used a P-value of <0.05 to test the association with CKD. In the meta-analysis, rs4821480 (minor allele frequency 4.45 and 3.96% in FHS and ARIC, respectively) was associated with higher CKD prevalence in participants free of diabetes (odds ratio 1.44; 95% confidence interval 1.15-1.80; P = 0.001). No other SNPs achieved significance after adjusting for multiple testing. Results utilizing directly genotyped data confirmed the results of the primary analysis. Recently identified APOL1 risk variants were also directly genotyped, but did not account for the observed MYH9 signal. These data suggest that the MYH9 polymorphism rs4821480 is associated with an increased risk of non-diabetic CKD in individuals of European ancestry.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".