Progression of Focal Segmental Glomerulosclerosis in Patients With High Risk APOL1 Genotypes: A CureGN Study
Bibliographic record
Abstract
Background: Polymorphism in APOL1 is a risk factor for disease progression in FSGS. This study evaluated the association of APOL1 genotypes on kidney disease progression in patients with FSGS. Methods: Cure Glomerulonephropathy participants with a biopsy diagnosis of FSGS were included. Whole genome sequencing was performed with 150 bp paired end reads on Illumina NovaSeq 6000 instruments targeting 30X read depth. eGFR decline was categorized as ≤-5, 0 to -5, and >0ml/min/yr. Multivariable ordinal logistic regression was used to assess the association with APOL1 high-risk (HR, 2 risk alleles) vs low risk (LR, 0-1 risk alleles). Results: Of 650 participants, 13% were HR, 60% were LR (APOL1 status missing for 27%, Table). HR participants' biopsies showed more collapsing FSGS (p<0.001), greater interstitial inflammation (p<0.001) and interstitial fibrosis and tubular atrophy (p=0.02). The odds of rapid progression was 2.76 times higher in the HR group after adjustment. Proteinuria at biopsy was not associated with progression category, however, within the first year post-enrollment, higher nadir proteinuria (OR=1.09, p=0.02), need for multiple immunosuppressive agents (OR=1.35, p=0.001) and uncontrolled hypertension (OR=1.61, p=0.04) were associated with rapid progression.Table:: Demographic and clinical characteristics of subjects per APOL1 status.Conclusions: In addition to APOL1 genotype, degree of proteinuria reduction, use of multiple immunosuppressive agents and uncontrolled hypertension are additional risk factors for rapid progression of FSGS. A better understanding of the natural history of FSGS in the context of high risk APOL1 genotypes will improve patient care and inform the design of interventional studies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".