Development and nationwide validation of kidney graft injury markers using urinary exosomes and microvesicles

Non-invasive, prompt, and proper detection tools for kidney graft injuries (KGIs) are awaited to ensure graft longevity. Researchers at the Sapporo City General Hospital screened diagnostic biomarkers for KGIs following kidney transplantation using extracellular vesicles (EVs; exosomes and microvesicles) from the urine samples of patients.

One hundred and twenty-seven kidney recipients at 11 Japanese institutions were enrolled in this study; urine samples were obtained prior to protocol/episode biopsies. EVs were isolated from urine samples, and EV RNA markers were assayed using quantitative reverse transcription polymerase chain reaction. Diagnostic performance of EV RNA markers and diagnostic formulas comprising these markers were evaluated by comparison with the corresponding pathological diagnoses.

EV CXCL9, CXCL10, and UMOD were elevated in T-cell-mediated rejection samples compared with other KGI samples, while SPNS2 was elevated in chronic antibody-mediated rejection (cABMR) samples. A diagnostic formula developed through Sparse Logistic Regression analysis using EV RNA markers allowed us to accurately (with an area under the receiver operator characteristic curve [AUC] of 0.875) distinguish cABMR from other KGI samples. EV B4GALT1 and SPNS2 were also elevated in cABMR, and a diagnostic formula using these markers was able to distinguish between cABMR and chronic calcineurin toxicity accurately (AUC 0.886). In interstitial fibrosis and tubular atrophy (IFTA) urine samples and those with high Banff chronicity score sums (BChS), POTEM levels may reflect disease severity, and diagnostic formulas using POTEM detected IFTA (AUC 0.830) and high BChS (AUC 0.850).

RT-qPCR analysis of candidate genes (CXCL9, CXCL10, UMOD, SPDEF, SPNS2, and ANXA1) for all kidney graft injuries (KGIs), Borderline, Borderline change; CNIT, aCNIT+cCNIT

Fig. 1

(A) and evaluation of the performance of the diagnostic formula in distinguishing cABMR from other KGIs by Sparse logistic regression (SLR) analysis (B)

KGIs could be diagnosed with urinary EV mRNA analysis with relatively high accuracy.

Harada H, Fukuzawa N, Abe T, Imamura R, Masaki N, Fujiyama N, Sato S, Hatakeyama S, Nishimura K, Kishikawa H, Iwami D, Hotta K, Miura M, Ide K, Nakamura M, Kosoku A, Uchida J, Murakami T, Tsuji T. (2023) Development and nationwide validation of kidney graft injury markers using urinary exosomes and microvesicles. BMC Nephrol 24(1):158. [article]

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