Interplay between Immune Deposits, Complement Activation, and APOL1 Renal Risk Variants in Patients with FSGS
Bibliographic record
Abstract
Background: The mechanisms by which APOL1 renal risk variants (RRVs) carry a worse prognosis in FSGS is debated. Whether glomerular immune deposits and complement activation participate in APOL1 mediated FSGS is unknown. Using the large CureGN cohort, we evaluated the association APOL1 RRVs and immunofluorescence (IF) findings and urinary complement fragment measurements (sC5b9). Methods: We studied the associations of glomerular IgG, IgM and C3 localization and intensity, biopsy findings, urinary sC5b9 and clinical data in CureGN FSGS cohort, regardless of self-reported race. Patients were categorized by two APOL1 RRVs [high risk (HR)] versus zero to one risk alleles [low risk (LR)] groups. The association between histopathological findings, urinary sC5b9 levels and APOL1 RRVs were analyzed. Results: Of 175 participants, 148 (85%) had genetic testing, among whom 31 were HR and 117 were LR participants. The percentage of patients with active disease (UPCR>1 g/g) at enrollment was higher in HR patients compared to LR patients (74% vs 51%, p=0.07). Collapsing FSGS is the dominant type in HR group (45% vs 11%, p<0.001). Mesangial IgG deposition was significantly more frequent in HR group compared to LR group [10 (32%) vs 4 (3%), p<0.001]. Interstitial fibrosis/tubular atrophy and tubular microcystic changes were found at a significantly higher rate in HR group (84% vs 64%, p=0.033; 29% vs 12%, p<0.001, respectively). Urinary sC5b9 levels (median, IQR) were higher in HR patients enrolled within 6 months of biopsy compared to LR group [0.15 (0.08-0.31) vs 0.03 (0-0.20) μg/g, p=0.08] (Fig.1). Proteinuria levels were similar in both groups (p=0.79). Conclusion: Patients with FSGS and high-risk APOL1 genotype have more frequent mesangial IgG deposition and a trend towards higher urinary membrane attack complex levels compared to patients with non-risk genotype.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".