The Biomarker Revolution in Kidney Transplantation

Since the first successful kidney transplant in 1954, transplant medicine has advanced significantly, achieving favorable one-year outcomes. However, despite excellent short-term outcomes, long-term renal allograft survival remains sub-optimal, with acute rejection continuing to be a major contributor to death-censored allograft loss. Current approaches for post-transplant surveillance and rejection monitoring rely on either nonspecific markers that often detect injury late in their course or invasive procedures associated with procedural risks and complications. To address these limitations, numerous non-invasive biomarkers have been introduced into solid organ transplantation research with the goal of improving allograft surveillance, facilitating earlier detection of rejection and complementing existing diagnostic approaches. Although several biomarkers have demonstrated clinical promise, none currently possess sufficient accuracy to replace kidney allograft biopsy. Biomarkers under investigation include blood-, tissue- and urine-based specimens. Their development and validation as independent markers have been limited by smaller sample size, heterogenous targets, variable performance characteristics and suboptimal sensitivity and specificity. In response, the field has increasingly shifted toward multimodal approaches that combine biomarkers and incorporate artificial intelligence to improve diagnostic accuracy and outcomes prediction. This review summarizes current biomarkers, discusses their limitations and explores future directions for biomarker development and clinical implementation.

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Publication Details

Journal
Journal of Clinical Medicine
Published
2026-09-30
DOI
https://doi.org/10.3390/jcm15197601
Primary Topic
Renal Transplantation Outcomes and Treatments
Type
article
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article

The Biomarker Revolution in Kidney Transplantation

Sami Alasfar, Elizabeth Cho, Yvette Y. Lopez
Journal of Clinical Medicine
Renal Transplantation Outcomes and Treatments
article

The Biomarker Revolution in Kidney Transplantation

Sami Alasfar, Elizabeth Cho, Yvette Y. Lopez
article en

Abstract

Since the first successful kidney transplant in 1954, transplant medicine has advanced significantly, achieving favorable one-year outcomes. However, despite excellent short-term outcomes, long-term renal allograft survival remains sub-optimal, with acute rejection continuing to be a major contributor to death-censored allograft loss. Current approaches for post-transplant surveillance and rejection monitoring rely on either nonspecific markers that often detect injury late in their course or invasive procedures associated with procedural risks and complications. To address these limitations, numerous non-invasive biomarkers have been introduced into solid organ transplantation research with the goal of improving allograft surveillance, facilitating earlier detection of rejection and complementing existing diagnostic approaches. Although several biomarkers have demonstrated clinical promise, none currently possess sufficient accuracy to replace kidney allograft biopsy. Biomarkers under investigation include blood-, tissue- and urine-based specimens. Their development and validation as independent markers have been limited by smaller sample size, heterogenous targets, variable performance characteristics and suboptimal sensitivity and specificity. In response, the field has increasingly shifted toward multimodal approaches that combine biomarkers and incorporate artificial intelligence to improve diagnostic accuracy and outcomes prediction. This review summarizes current biomarkers, discusses their limitations and explores future directions for biomarker development and clinical implementation.

Journal of Clinical MedicineVol. 15(19)
Mayo Clinic in Arizona (US), Mayo Clinic Hospital (US)
Good health and well-being
Openalex Percentile: Top 9%
Renal Transplantation Outcomes and Treatments
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The Biomarker Revolution in Kidney Transplantation — Sami Alasfar, Elizabeth Cho, et al. · Journal of Clinical Medicine (2026) | TGRS Research Map | TGRS