The candidate proteins associated with keratoconus: A meta-analysis and bioinformatic analysis

Purpose: Keratoconus (KC) is a multifactorial disorder. This study aimed to conduct a systematic meta-analysis to exclusively explore the candidate proteins associated with KC pathogenesis. Methods: Relevant literature published in the last ten years in Pubmed, Web of Science, Cochrane, and Embase databases were searched. Protein expression data were presented as the standard mean difference (SMD) and 95% confidence intervals (CI). The meta-analysis is registered on PROSPERO, registration number CRD42022332442 and was conducted in accordance with the Preferred Reporting Items for Systematic reviews and Meta-Analyses statement (PRISMA). GO and KEGG enrichment analysis were performed, as well as the miRNAs and chemicals targeting the candidate proteins were predicted. PPI was analyzed to screen the hub proteins, and their expression was verified by RT-qPCR. Results: A total of 21 studies were included in the meta-analysis, involving 346 normal eyes and 493 KC eyes. 18 deregulated proteins with significant SMD values were subjected to further analysis. In which, 7 proteins were up-regulated in KC compared with normal controls, including IL6 (SMD 1.54, 95%CI [0.85, 2.24]), IL1B (SMD 2.07, 95%CI [0.98, 3.16]), TNF (SMD 2.1, 95%CI [0.24, 3.96]), and MMP9 (SMD 1.96, 95%CI [0.68, 3.24]). While 11 proteins were down-regulated in KC including LOX (SMD 2.54, 95%CI [-4.51, -0.57]). GO and KEGG analysis showed that the deregulated proteins were involved in inflammation, extracellular matrix (ECM) remodeling, and apoptosis. MMP9, IL6, LOX, TNF, and IL1B were regarded as hub proteins according to the PPI analysis, and their transcription changes in stromal fibroblasts of KC were consistent with the results of the meta-analysis. Moreover, 10 miRNAs and two natural polyphenols interacting with hub proteins were identified. Conclusion: This study obtained 18 candidate proteins and demonstrated altered cytokine profiles, ECM remodeling, and apoptosis in KC patients through meta-analysis and bioinformatic analysis. It will provide biomarkers for further understanding of KC pathogenesis, and potential therapeutic targets for the drug treatment of KC.