Pretransplant Gut Microbiome Signatures Predict Early Acute Rejection After Kidney Transplantation.

Authors

Ji Eun Kim, Hyunjeong Cho, Jangwook Lee, Ji In Park, Jung Hun Koh, Sehoon Park, Eunjeong Kang, Yong Chul Kim, Dong Ki Kim, Yon Su Kim, Sangil Min, Eun Young Song, Kyung Chul Moon, Bong-Soo Kim, Hajeong Lee

Published in

American journal of transplantation : official journal of the American Society of Transplantation and the American Society of Transplant Surgeons. Jul 25, 2026. Epub Jul 25, 2026.

Abstract

Early identification of rejection remains a critical unmet need in kidney transplantation, as conventional tools detect rejection only after irreversible allograft injury. The pre-transplant gut microbiome may provide novel predictive signals by modulating immune homeostasis. Pre-transplant stool samples underwent shotgun metagenomic sequencing. Composition, functional profiles, and networks were compared between rejection and non-rejection (protocol biopsy ≤ 2 weeks). A pre-specified SCFA biosynthetic KO panel was tested with FDR correction. Stepwise Random Forest models were developed with subgroup analyses and tested in a temporal validation cohort. Of 78 recipients, 26 (33.3%) developed biopsy-proven early acute rejection. Three taxa including Phascolarctobacterium faecium were FDR-significantly reduced. At the gene level, mcmB (a key propionate-biosynthetic enzyme) was the only KO reaching FDR significance in the pre-specified SCFA panel (q = 0.018). Network analysis revealed selective microstructural reorganization. AUC improved stepwise (0.565 → 0.681 → 0.765), was preserved across rejection subtypes (TCMR-spectrum 0.74; ABMR 0.85), and reached 0.721 in temporal validation with improved reclassification (NRI 0.11; IDI 0.055) and clinical net benefit at thresholds 0.2-0.5. Pre-transplant gut microbiome signatures were independently associated with early acute rejection. Microbiome-augmented models outperformed clinical-only models and remained robust in temporal validation, supporting microbiome-based pre-transplant risk stratification.

PMID:
42501920
Bibliographic data and abstract were imported from PubMed on 26 Jul 2026.

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