Genetic Determinants of Ultrafiltration With Peritoneal Dialysis
Bibliographic record
Abstract
Background: The inter-individual variability in the peritoneal dialysis (PD) ultrafiltration (UF) capacity is largely unexplained by demographic and clinical variables. We tested the hypothesis that common genetic variants are associated with variability in UF. Methods: The Bio-PD study enrolled participants from 69 centers in 6 countries. The phenotype of UF volume at 4 hours was obtained from the 1st peritoneal equilibration test (PET) when starting PD. Genotyping was done with the Illumina InfiniumOmni2-5 array and imputed using the Michigan Imputation Server. Heritability was estimated using genomic-restricted maximum likelihood analysis, genome-wide association was performed for single nucleotide variants (SNVs) with minor allele frequency >2%, and gene-wise analyses were done with the Generalized Berk-Jones test. Analyses were adjusted for sex, age, body mass index, country, diabetes, dialysate dextrose concentration, interval between PD start and PET, and principal components of ancestry. Additional analyses included 4-h Dialysate/Plasma (D/P) creatinine ratio as covariate. Results: Analysis included 2413 participants (64% men, 32% diabetes, 82% White). The PETs were done at a median of 63 days (IQR 36-121) from PD start, 78% were completed with 2.5% dextrose, with a mean 4-h D/P creatinine of 0.70 and a median UF of 250mL (IQR 0-494). The heritability of UF was estimated at 58% and 42% in models without and with 4-h D/P creatinine, respectively (p=6x10-4 and 0.01). No SNV reached genome-wide significance using 7,052,235 SNVs. Analyses testing association with 18,330 genes showed significant association of 3 genes at a false discovery rate (FDR) <10% (PTGES FDR=0.02, GPHN FDR=0.04, SLC24A3 FDR=0.05). Further adjustment for 4-h D/P creatinine showed association with 2 genes remained significant (PTGES and SLC24A3). Conclusions: Common genetic variants account for a substantial proportion of the variability in UF and these analyses suggest a potential association with variation in PTGES and SLC24A3 genes. Funding: NIDDK Support, Government Support - Non-U.S.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".