*Purpose: Preconditioning of donor kidneys and clinical assessment for need of dialysis early post-transplant vary per each case and are crucial for improving transplant outcomes. All kidney allografts do not have the same pathways effected and thus understanding the plethora of molecular response patterns is needed for advancement towards precision medicine. The current study focusses on kidney allografts grouped and studied based on their molecular patterns.

*Methods: A total of 150 pre-implantation (PI) and post-reperfusion (PR) renal allograft gene expression patterns were studied and unsupervised cluster analysis was done. Comparative networks were built and differential and common molecular patterns and enriched cell types were identified between high and low risk groups for delayed graft function and recovery at 3 months post-transplant. Paired PR-plasma miRNA arrays were done. Genes were filtered for gene ontology terms related to Mitochondria, inflammation and metabolism.

*Results: Three distinct molecular response patterns to ischemia reperfusion injury were observed. Of the 3 subgroups of patients one was low risk group with good short term outcomes. They show cell type enrichment of CD105+ endothelial cells among others which help in angiogenesis and repair. Transcription factors like SOX9 and FOSL2, ADM, BTG2, RRAD were upregulated that are responsible for regulated undertaking of processes like cellular differentiation, proliferation, angiogenesis, channel regulation and inflammatory reactions necessary for repair. The two additional subgroups of allografts were high risk groups with more number of clinically determined cases of DGF and non-recovery at 3 months post-transplant and these showed different molecular patterns. One group had more representation of 721 B lymphoblasts and they showed a lot of mitochondrial genes differentially expressed and high BAX/BCL2 ratio that results in more apoptosis. Ten times more differentially expressed genes were present compared to other groups and exclusively include differential metabolism and mitochondrial gene expression. Finally, the other high risk group showed more inflammatory genes like IL-1, LIF, and TNFα.

*Conclusions: Worse short-term outcomes result from different molecular response patterns either due to low metabolism and mitochondrial insufficiency or unregulated and exacerbated inflammation within allografts. These need to be clinically addressed differently with preconditioning treatments designed accordingly.

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