186 - Utilizing Whole Exome Sequencing for the Assessment of Unclassified Glycogen Storage Diseases and Disorders of Energy Metabolism

Saturday, April 29, 2023

3:30 PM – 6:00 PM ET

Poster Number: 186
Publication Number: 186.213

Corbinian Wanner, University of Connecticut School of Medicine, Farmington, CT, United States; Louisa R. Kalsner, Connecticut Children's Medical Center and University of Connecticut School of Medicine, Farmington, CT, United States; Julieta Bonvin Sallago, Connecticut Children/ University of Connecticut, Hartford, CT, United States; Julie L.. Vigil, University of Connecticut Health Center, Farmington, CT, United States; Youngmok Lee, UConn Health, Farmington, CT, United States

Presenting Author(s)

Corbinian Wanner (he/him/his)

Medical Student
University of Connecticut School of Medicine & Connecticut Children's
Farmington, Connecticut, United States

Background:

There are currently 15 types of glycogen storage disease (GSD), each associated with an enzyme defect. A cohort of patients followed by the Connecticut Children’s GSD Program (CCGP) have liver biopsy-proven GSD, hypoglycemia, hepatomegaly, metabolic acidosis or other phenotypic characteristics consistent with GSD, but targeted genetic testing has failed to elucidate an underlying genetic etiology.

Objective:

To identify the genetic etiology of un-typed GSDs using whole exome sequencing.

Design/Methods:

Patients were enrolled at the CCGP. The analysis focused on the initial cohort of 10 patients and 24 biologic parents and siblings. Blood samples were collected from all subjects and the DNA was extracted and sent out for research-grade sequencing at Novogene, Co. The analysis utilized a software program created by Congenica, Ltd where a 443-gene panel, curated by the study team, was applied to the sequencing data. The panel included genes related to energy metabolism or cell signaling pathways in order to explore more generalized energy metabolism defects. All de novo and homozygous variants were prioritized and individually explored via SIFT or PolyPhen scoring, previous documentation of the variant, and inheritance pattern in order to generate the primary data list.

Results:

No de novo variants were found in the genes analyzed. 22 homozygous variants were identified in 16 genes. Eight of these variants had a >50% population frequency and were considered common polymorphisms. Four variants have been previously reported: DBH, DMXL2, RAI1 as benign and TBX19 as variant of unknown significance. Two variants had PolyPhen and SIFT classifications predicted as damaging or deleterious: DMXL2 and PFRAME10. Six variants have not been previously recorded, five are found in the mitochondria ACADSB, DGKB, ETFA, GATB, and NDUFA10, and one is related to signaling processes primarily seen in neurons, ATN1.

Conclusion(s):

In this analysis, several homozygous variants were identified in genes with crucial roles in energy metabolism or signaling processes indirectly related to metabolism. We report a potential role for homozygous variants in DMXL2, a gene involved in insulin secretion, and PFRAME10, a gene involved in transcription. In addition, we report discovery of five previously unreported variants in genes with roles in electron transport, fatty acid metabolism, and mitochondrial protein synthesis. Future directions will include correlation of these genetic variants with patient phenotypes, identification of de novo variants throughout the exome and exploration of any compound heterozygous variants.