Connective tissue deficiency in the pathogenesis of anterior abdominal wall hernias and modern diagnostic approaches to improve hernioplasty outcomes

Objective: To develop a method for predicting the risk of primary and recurrent anterior abdominal wall hernias based on the analysis of currently available diagnostic tools for assessing connective tissue status in patients. Material and methods. A comprehensive study of genome-wide association study (GWAS)-significant genetic markers, skin autofluorescence indices, and morphological changes in the skin was conducted in a cohort of 577 patients, including 299 individuals with anterior abdominal wall hernias and 278 without hernias or clinical signs of connective tissue dysplasia. An artificial neural network model was developed based on the collected data to determine the relative significance of the investigated etiopathogenetic factors. Additionally, a correlation analysis of independent variables was performed to identify associations with the diagnosis of anterior abdominal wall hernia. Binary logistic regression was used to calculate the probability of hernia occurrence or recurrence based on the identified variables. Results. Patients with anterior abdominal wall hernias demonstrated significantly lower collagen type I to type III ratios and decreased skin autofluorescence indices. Genotypic association analysis revealed a statistically significant link between the rs2009262 polymorphism of the EFEMP1 gene and increased hernia risk (p=0.033). Further evaluation using neural network analysis and correlation studies identified three independent and statistically significant predictors for hernia development: the rs2009262 EFEMP1 polymorphism, skin autofluorescence index, and collagen type I/III ratio. Conclusion: The developed predictive approach allows for individualized assessment of anterior abdominal wall hernia risk and the likelihood of recurrence in each patient.