Candidate disease genes identification in patients with congenital neutropenia and a new PID condition

Abstract

Background: Congenital neutropenia (CN) is a primary immunodeficiency disease (PID), which is associated with recurrent bacterial infections, autoimmunity, hematological malignancies, and neuropsychiatric symptoms. Understanding the protein-protein interaction (PPI) network of CN genes and finding candidate CN genes is crucial for early CN diagnosis. The purpose of current study was to investigate the PPI network of CN genes and use computational techniques to identify candidate CN genes.Methods: PPI data for CN and PID genes provided from the STRING database were examined using network density and biological distance. Gene expression data of patients with CN were obtained from the Gene Expression Omnibus, and then Pearson’s correlation coefficient, a PPI database, and Kyoto Encyclopedia of Genes and Genomes were used to identify candidate CN genes. We then assessed our hypotheses and discovered CN genes that were differently expressed. Results: Characterization of the majority of CN genes were done by high network density and low biological distance whereas low network density and large biological distance were used to characterize most PID genes. The CN genes are functionally relative to each other compared to PID genes. It showed that they are similar and closely related. Next, we found 15 candidate CN genes with biological functions comparable to known CN genes, and other genes have subsequently been identified as CN-related genes. The SRC gene reported in our study may be a good candidate gene for Heneekem syndrome. The candidate gene “STAT3” was downregulated in peripheral blood neutrophils and B cells in CN patients compared to healthy controls (HC), whereas in blood sample the level was up regulated in CN patients relative to HC. Conclusion: Our findings will contribute in the early diagnosis of CN by providing a better understanding of the CN gene complexity.