Tehran University of Medical Sciences

Science Communicator Platform

Stay connected! Follow us on X network (Twitter):
Share this content! On (X network) By
The Genetic Perspective of Familial Glucocorticoid Deficiency: In Silico Analysis of Two Novel Variants Publisher



Heshmatzad K1 ; Mahdieh N1, 2 ; Rabbani A1 ; Didban A3 ; Rabbani B1
Authors
Show Affiliations
Authors Affiliations
  1. 1. Growth and Development Research Center, Tehran University of Medical Sciences, Tehran, Iran
  2. 2. Rajaie Cardiovascular Medical and Research Center, Iran University of Medical Sciences, Tehran, Iran
  3. 3. Department of Pediatrics, Pediatric Endocrinologist, Qazvin University of Medical Sciences, Qazvin, Iran

Source: International Journal of Endocrinology Published:2020


Abstract

Familial glucocorticoid deficiency is a rare autosomal recessive genetic disorder which belongs to a group of primary adrenal insufficiency (PAI) and is mainly caused by mutations in the MC2R and MRAP genes. A comprehensive search was conducted to find the reported variants of MC2R and MRAP genes. In silico pathogenic analysis was performed for the reported variants. PCR amplification and sequencing were performed for three patients. Structural analysis, modeling, and interactome analysis were applied to characterize novel MC2R variants and their proteins. About 80% of MC2R-related cases showed the clinical symptoms which were diagnosed at <2 years old. 107 patients had MC2R mutations (85 homozygotes, 21 compound heterozygotes, and 1 simple heterozygote). 59 variants were found in the MC2R gene. Four mutations were responsible for half of patients. 39 homozygous patients had MRAP mutations; 14 variants were determined in the MRAP gene. Nine proteins were predicted by STRING to associate with the studied proteins. Two novel MC2R variants, c.128T > G (p.Leu43Arg) and c.251T > A (p.Ile84Asn), were found in two patients at the age of above and below 2 years, respectively. Mutations in MC2R and MRAP genes are the main cause of FGD. Genetic studies and in silico analysis will help to confirm the diagnosis. © 2020 Katayoun Heshmatzad et al.