A comprehensive multi-OMICS integration framework to address sample heterogeneity and identify causative genes and proteins in the pathogenesis of Keratoconus

Purpose:

Keratoconus (KC), a complex corneal disorder, requires a comprehensive understanding due to its multifactorial nature. Limited sample availability often confines us to single omics strategies. This study introduces an innovative framework for integrating multi-omics data, addressing the challenges of heterogeneity in sample type and aims to uncover causative mechanisms behind KC pathogenesis.

Methods:

WES was conducted using blood samples from familial KC cohort (n = 9 families). Transcriptomic analysis, based on microarray technology, was performed on corneal epithelium samples (KC = 60, control = 18) in a prior study, and mass-spectrometry-based Proteomics was conducted on tears (KC = 107, control = 40). An in-house gene-protein interaction network-based framework was developed using Python 3.7.

Results:

Individual omics analyses were performed, revealing genomics data identifying seven novel genes, including immunomodulatory metalloproteinases and transcription regulatory factors. Transcriptomics uncovered elevated reactive oxygen species expression, while proteomics identified proteins associated with ROS, inflammatory processes, and ECM remodelling. The inhouse integration framework revealed that the gene with pathogenic variant TPPP plays a regulatory role in various other genes associated with apoptotic functions, including S100A8 and S100A6. CTBP2 governed genes related to the ECM and proteins in oxidative stress, while the immune modulator KIR2DL1 induced alterations in IQGAP1 expression.

Conclusion:

Our framework was able to map dysregulated gene expression in corneal epithelium and corresponding protein expression in tears. These findings contribute novel insights into the potential mechanisms driving the pathogenesis of KC, offering a promising avenue for further research and clinical applications.