Method for determining the probability of detection of IgA antibodies to deamidated gliadin peptides in patients with IgA nephropathy

Backgraund: IgA nephropathy (IgA-N) is one of the leading causes of terminal renal failure requiring renal replacement therapy. The etiopathogenesis of the disease is not fully understood. Some studies suggest an association with diseases and conditions that are accompanied by inflammation and increased permeability of the intestinal wall. A number of studies indicate a high prevalence of certain antibodies (AB) in the blood specific and sensitive for celiac disease in IgA-N patients. These IgA AB are thought to influence the activity and risks of glomerular disease progression. Aims: to develop a tool (predictive model) to determine the probability of detecting of IgA AB to deamidated gliadin peptides (IgA DGP AB) in IgA-N patients serum. Materials and methods: the study included 105 patients aged 18 to 64 years with morphologically confirmed IgA-N. The median duration of the disease before nephrobiopsy was 17 (6–48) months. Distribution by sex: men – 92 (87.6%), women – 13 (12.4%). All patients underwent a complex clinical examination. Results: on the basis of the obtained data a prognostic model for determining the probability of detecting IgA DGP AB in IgA-N patients serum depending on proteinuria, systolic blood pressure and total IgA was constructed by the method of binary logistic regression. The regression model obtained has high statistical significance (the area under the ROC curve was 0.860; 95% CI: 0.744 to 0.976; p<0.001). The sensitivity and specificity of the model were 82.4% and 83.1%, respectively. Conclusions: the developed predictive model for determining the probability of detecting IgA DGP AB in IgA-N patients serum, which has high sensitivity and specificity, may reduce the cost of diagnostic measures in selecting patients for AB testing; improve risk assessment of IgA-N progression; and create new opportunities for personalized clinical approach and optimization of treatment strategies, which in turn may lead to improved renal outcomes for IgA-N patients.