Literature DB >> 23806237

Molecular diagnostic testing for congenital disorders of glycosylation (CDG): detection rate for single gene testing and next generation sequencing panel testing.

Melanie A Jones1, Devin Rhodenizer, Cristina da Silva, Israel J Huff, Lisa Keong, Lora J H Bean, Bradford Coffee, Christin Collins, Alice K Tanner, Miao He, Madhuri R Hegde.   

Abstract

Congenital disorders of glycosylation (CDG) are comprised of over 60 disorders with the majority of defects residing within the N-glycosylation pathway. Approximately 20% of patients do not survive beyond five years of age due to widespread organ dysfunction. A diagnosis of CDG is based on abnormal glycosylation of transferrin but this method cannot identify the specific gene defect. For many individuals diagnosed with CDG the gene defect remains unknown. To improve the molecular diagnosis of CDG we developed molecular testing for 25 CDG genes including single gene testing and next generation sequencing (NGS) panel testing. From March 2010 through November 2012, a total of 94 samples were referred for single gene testing and 68 samples were referred for NGS panel testing. Disease causing mutations were identified in 24 patients resulting in a molecular diagnosis rate of 14.8%. Coverage of the 24 CDG genes using panel testing and whole exome sequencing (WES) was compared and it was determined that many exons of these genes were not adequately covered using a WES approach and a panel approach may be the preferred first option for CDG patients. A collaborative effort between physicians, researchers and diagnostic laboratories will be very important as NGS testing using panels and exome becomes more widespread. This technology will ultimately improve the molecular diagnosis of patients with CDG in hard to solve cases.
Copyright © 2013 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Congenital disorders of glycosylation; Diagnostic testing; Metabolic disorder; Next generation sequencing; Whole exome sequencing

Mesh:

Year:  2013        PMID: 23806237     DOI: 10.1016/j.ymgme.2013.05.012

Source DB:  PubMed          Journal:  Mol Genet Metab        ISSN: 1096-7192            Impact factor:   4.797


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