Omics data integration analysis identified new biological insights into chronic antibody-mediated rejection (CAMR).

Abstract

Background: In the last two decades, many studies based on omics technologies have contributed to defining the clinical, immunological, and histological fingerprints of chronic antibody-mediated rejection (CAMR), the leading cause of long-term kidney allograft failure. However, the full biological machinery underlying CAMR has only been partially defined, likely due to the fact thatsingle-omics technologies capture only specific aspects of the biological system and fail to provide a comprehensive understanding of this clinical complication.

Methods: This study integrated mass spectrometry-based proteomic profiling of serum samples from 19 patients with clinical and histological evidence of CAMR and 26 kidney transplant recipients with normal graft function and histology (CTR) with transcriptomic analysis of peripheral blood mononuclear cells (PBMCs) from an independent cohort of 10 CAMR and 8 CTR patients. Data analysis was conducted using unsupervised hierarchical clustering (multidimensional scaling with k-means) and Spearman's correlation test. Partial least squares discriminant analysis (PLS-DA) with the importance in projection (VIP) score identified key proteins differentiating CAMR from CTR. ELISA was used to validate the omics results.

Results: Proteomic analysis identified 18 proteins that significantly differentiated CAMR from CTR (p < 0.01): five were more abundant (CHI3L1, LYZ, PRSS2, CPQ, IGLV3-32), while 13 were less abundant (SERPINA5, SERPING1, KNG1, CAMP, VNN1, BTD, WDR1, PON3, AHNAK2, MELTF, CA1, CD44, CUL1). Transcriptomic profiling revealed 6 downregulated and 33 upregulated genes in CAMR versus CTR (p < 0.01). Notably, only 2 biological elements were significantly deregulated in both omics analyses: chitinase-3-like protein 1 (CHI3L1) and plasma protease inhibitor C1 (SERPING1). CHI3L1, previously associated with the severity of tissue damage in kidney diseases, was up-regulated in CAMR in both transcriptomics and proteomics, while SERPING1, a serine esterase inhibitor that blocks the classical and lectin pathway of complement, was up-regulated in CAMR in transcriptomics but down-regulated in proteomics. ELISA validated the omics results, and the ROC curve showed that CHI3L1 has good discrimination power between CAMR and CTR (AUC of ROC curve of 0.81).

Conclusions: Our multi-omics data, although performed in a relatively small cohort of patients, revealed new systemic biological elements involved in the pathogenesis of CAMR and identified CHI3L1 as a new potential biomarker and/or therapeutic target for this important clinical complication. Future validation of these findings in larger patient cohorts should be conducted to better evaluate their clinical utility.