Genetic Determinants of Lupus Nephritis and Kidney Function in Systemic Lupus Erythematosus
Bibliographic record
Abstract
Background: Lupus nephritis (LN) is one of the most common and severe manifestations of SLE. We completed an LN genome wide association study (GWAS) in a multi-ethnic cohort of children and adults with SLE. Methods: We included SLE patients from dedicated Lupus clinics and the SLICC cohort. All patients met ACR and/or SLICC SLE classification criteria and were genotyped on a multi-ethnic Illumina array. LN was defined by SLE criteria. Kidney function (eGFR) was estimated using the Schwartz Bedside formula for measures <18 years and CKD-EPI (without ancestry) for >18 years of age, collected longitudinally over time. Wilcoxon rank sum or Chi-square test were used for significance between LN and Non-LN patients. We completed GWAS of LN in marginal and multivariable adjusted regression models with principal components for ancestry, sex and cohort site. Results: We included 2981 patients with SLE, 88% female, 46% of European ancestry, 27% childhood-onset SLE. LN was present in 45%. People at time of LN diagnosis were younger and more likely of African American or East Asian ancestry. People with LN had significantly lower within-person mean eGFR, greater eGFR variability and slope over time compared to those without LN (Table). GWAS of LN demonstrated a peak on chromosome 8, yet did not reach a genome-wide significance (p < 5x10-8). Conclusions: Our GWAS did not identify a significant locus for LN. We plan to repeat GWAS of repeated eGFR measures, as it is a more informative outcome that may improve power for detecting genetic loci for LN. Funding: Government Support - Non-U.S. Characteristics of LN and Non-LN patients - Patient Characteristics All SLE Patients (n=2981) LN SLE Patients (n=1351) Non-LN SLE Patients (n=1630) P-value Sex, Female 2628 (88.2) 1138 (84.2) 1490 (91.4) 1.6e-09 Age at SLE diagnosis (years) 25.6 [16.4, 37.8] 22.6 [15.7, 33.0] 28.3 [17.3, 41.3] 2.2e-16 cSLE diagnosis 814 (27.3) 484 (35.8) 440 (27.0) 2.1e-07 Inferred Ancestry European East Asian African American South Asian Admixed 1367 (45.9) 459 (15.4) 555 (18.6) 151 (5.1) 131 (4.4) 317 (10.6) 493 (36.5) 252 (18.6) 316 (23.3) 80 (5.9) 68 (5.0) 141 (10.4) 874 (53.6) 207 (12.7) 239 (14.7) 71 (4.4) 63 (3.9) 176 (10.8) 2.2e-16 Hypertension* 1017 (37.1) 659 (52.6) 358 (23.8) 2.2e-16 Kidney failure (chronic dialysis or transplant)* 25 (0.9) 25 (2.0) 0 (0.0) 3.0e-08 Time from diagnosis to 1st eGFR (years)* Time from 1st eGFR measurement to last (years)* 0.6 [0.06, 3.4] 8.9 [4.1, 14.8] 0.6 [0.08, 3.8] 10.0 [5.1, 16.1] 0.5 [0.04, 3.0] 7.8 [3.4, 13.7] 3.3e-01 4.4e-13 Within-Person No. eGFR Measures* 16 [8, 35] 21 [10, 45] 13 [6, 29] 2.2e-16 Within-Person mean* Within-Person eGFR Variance* eGFR slope ml/min/1.73m2/y* 100.8 [86.0, 113.1] 106.6 [51.4, 198.7] -0.53 [-2.00, 0.48] 100.2 [81.3, 113.4] 137.2 [69.6, 268.6] -0.67 [-2.26, 0.36] 101.2 [88.6, 112.7] 87.2 [43.1, 156.4] -0.53 [-1.83, 0.67] 7.7e-02 2.2e-16 2.3e-02 * data available for N= 2740
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".