Archetypal Analysis of Deceased Donor Kidneys: A Molecular Approach for Posttransplant Outcomes

. 2025 Oct 04 ; () : . [epub] 20251004

Status Publisher Jazyk angličtina Země Spojené státy americké Médium print-electronic

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid41052637
Odkazy

PubMed 41052637
DOI 10.1016/j.ajt.2025.09.024
PII: S1600-6135(25)03004-7
Knihovny.cz E-zdroje

Donor kidney tissue based transcriptomics may represent new dimension for prediction of kidney transplant outcomes. In this prospective, single-center study, 276 kidneys from 174 deceased brain-death donors were assessed by microarrays to identify phenotypes of procurement biopsies. Molecular classifiers (extreme gradient boosting, logistic and Poisson regression) with 10-fold cross-validation were employed to categorize donors based on clinical variables (age, BMI, hypertension, ECD kidney) and histological scores (vascular fibrous intimal thickening, interstitial fibrosis, tubular atrophy, arteriolar hyaline thickening). Archetypal analysis and linear mixed model were applied to determine molecular phenotypes and their association with posttransplant 1-year eGFR in 234 donor kidneys. Three molecular archetypes were identified. The "ideal" archetype (median donor age 42 years, low KDRI, minimal chronic histological changes) was associated with the highest 1-year eGFR, while the "marginal" archetype (68 years, extensive chronic changes, high KDRI) with the lowest one. The "intermediate" archetype yielded better 1-year eGFR despite donor profiles similar to the marginal group. While KDRI predicted 1-year eGFR, adding molecular archetypes improved model performance (AIC 80.0 vs. 83.7;p<0.05). External validation in an independent dataset (n=174, GSE147451) confirmed predictive value of the model. Molecular profiling of procurement biopsies may help to identify donor kidneys with higher posttransplant eGFR.

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