Introduction:
There is a pressing need to develop non-invasive biomarkers that reflect underlying disease mechanisms and serve as substitutes for outcome-related digital pathology descriptors (DPDs). DPDs interstitial fibrosis (IF), tubular atrophy (TA), and mononuclear white blood cells (MWBC) strongly associate with kidney disease outcome in patients with nephrotic syndrome. Due to the invasive nature of kidney biopsy process, it is impractical to perform repeated assessments hence potentially missing crucial periods for early prognosis and intervention
Methods:
DPDs IF, TA, and MWBC from 64 patients with nephrotic syndrome from the NEPTUNE cohort were integrated with transcriptomic profiles and urine proteomics data (SomaScan assay v4.1). Statistical methods employed included Pearson correlation, linear regression with significance set at p ≤0.05. Ingenuity pathway analysis was used to identify enriched canonical pathways and Cox model was used to determine the association of markers with kidney composite endpoint of kidney failure and 40% reduction of GFR
Results:
2,031 tubulointerstitial genes were identified showing significant correlation with IF (adj. p ≤0.05) containing 480 IF-correlated genes significantly enriched for canonical pathways such as interleukin signaling, axonal guidance, and STAT3 known to be associated with kidney disease progression. Integrating the urine markers and the pathway representing genes, we identified urine protein signatures that predict IF (linear regression, p≤ 0.05) and a subset of these markers (n=27) also predicted the composite outcome. Similarly, we also identified TA and MWBC associated urinary biomarkers
Conclusions:
Pathway representing urine biomarkers can predict IF and clinical outcomes in patients with NS. Non-invasive disease monitoring for timely prognosis and targeted treatment should be improved through the use of pathway-specific biomarkers linked to structure and function. Our finding warrants further validation in larger and independent cohorts. This study was also submitted to the ASN kidney Week 2024
I have no potential conflict of interest to disclose.
I did not use generative AI and AI-assisted technologies in the writing process.