Common variable immunodeficiency disorders(CVID),a heterogeneous group of inborn errors of immunity,is the most common symptomatic primary immunodeficiency disorder.Patients with CVID have highly variable clinical pre...Common variable immunodeficiency disorders(CVID),a heterogeneous group of inborn errors of immunity,is the most common symptomatic primary immunodeficiency disorder.Patients with CVID have highly variable clinical presentation.With the advent of whole genome sequencing and genome wide association studies(GWAS),there has been a remarkable improvement in understanding the genetics of CVID.This has also helped in understanding the pathogenesis of CVID and has drastically improved the management of these patients.A multiomics approach integrating the DNA sequencing along with RNA sequencing,proteomics,epigenetic and metabolomics profile is the need of the hour to unravel specific CVID associated disease pathways and novel therapeutic targets.In this review,we elaborate various techniques that have helped in understanding the genetics of CVID.展开更多
Backgrounds Common variable immunodeficiency(CVID),the most prevalent form of primary immunodeficiency(PID),is characterized by hypogammaglobulinemia and recurrent infections.Understanding protein-protein interaction(...Backgrounds Common variable immunodeficiency(CVID),the most prevalent form of primary immunodeficiency(PID),is characterized by hypogammaglobulinemia and recurrent infections.Understanding protein-protein interaction(PPI)networks of CVID genes and identifying candidate CVID genes are critical steps in facilitating the early diagnosis of CVID.Here,the aim was to investigate PPI networks of CVID genes and identify candidate CVID genes using computation techniques.Methods:Network density and biological distance were used to study PPI data for CVID and PID genes obtained from the STRING database.Gene expression data of patients with CVID 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 CVID genes.We then evaluated our predictions and identified differentially expressed CVID genes.Results:The majority of CVID genes are characterized by a high network density and small biological distance,whereas most PID genes are characterized by a low network density and large biological distance,indicating that CVID genes are more functionally similar to each other and closely interact with one other compared with PID genes.Subsequently,we identified 172 CVID candidate genes that have similar biological functions to known CVID genes,and eight genes were recently reported as CVID-related genes.MYC,a candidate gene,was down-regulated in CVID duodenal biopsies,but up-regulated in blood samples compared with levels in healthy controls.Conclusion:Our findings will aid in a better understanding of the complex of CVID genes,possibly further facilitating the early diagnosis of CVID.展开更多
文摘Common variable immunodeficiency disorders(CVID),a heterogeneous group of inborn errors of immunity,is the most common symptomatic primary immunodeficiency disorder.Patients with CVID have highly variable clinical presentation.With the advent of whole genome sequencing and genome wide association studies(GWAS),there has been a remarkable improvement in understanding the genetics of CVID.This has also helped in understanding the pathogenesis of CVID and has drastically improved the management of these patients.A multiomics approach integrating the DNA sequencing along with RNA sequencing,proteomics,epigenetic and metabolomics profile is the need of the hour to unravel specific CVID associated disease pathways and novel therapeutic targets.In this review,we elaborate various techniques that have helped in understanding the genetics of CVID.
文摘Backgrounds Common variable immunodeficiency(CVID),the most prevalent form of primary immunodeficiency(PID),is characterized by hypogammaglobulinemia and recurrent infections.Understanding protein-protein interaction(PPI)networks of CVID genes and identifying candidate CVID genes are critical steps in facilitating the early diagnosis of CVID.Here,the aim was to investigate PPI networks of CVID genes and identify candidate CVID genes using computation techniques.Methods:Network density and biological distance were used to study PPI data for CVID and PID genes obtained from the STRING database.Gene expression data of patients with CVID 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 CVID genes.We then evaluated our predictions and identified differentially expressed CVID genes.Results:The majority of CVID genes are characterized by a high network density and small biological distance,whereas most PID genes are characterized by a low network density and large biological distance,indicating that CVID genes are more functionally similar to each other and closely interact with one other compared with PID genes.Subsequently,we identified 172 CVID candidate genes that have similar biological functions to known CVID genes,and eight genes were recently reported as CVID-related genes.MYC,a candidate gene,was down-regulated in CVID duodenal biopsies,but up-regulated in blood samples compared with levels in healthy controls.Conclusion:Our findings will aid in a better understanding of the complex of CVID genes,possibly further facilitating the early diagnosis of CVID.
