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Strategic interrogation of the exome for metabolic and glycomic variants in the setting of undiagnosed disease

Wednesday, September 14, 2016 — Poster Session I

3:00 p.m. – 4:30 p.m.
FAES Terrace


  • CJ Adams
  • DR Johnson
  • TS Frisby
  • KR Chao
  • M Davids
  • LA Wolfe
  • H Ho
  • CL Hoppel
  • WA Gahl
  • DR Adams


The NIH Undiagnosed Diseases Program (UDP) evaluates patients with illnesses that remain undiagnosed despite extensive medical investigation. Exome analyses are undertaken on UDP patients with the objective of identifying DNA sequence variants that may contribute to the presenting illness. For any given case, several such candidates may be found, with varying levels of bioinformatic evidence. Ancillary data sets, including metabolic and glycomic testing, may augment variant prioritization by revealing biochemical pathway associations. For instance, variants in a gene with a predicted biochemical function but no disease association can be prioritized if metabolic testing reveals abnormalities consistent with dysfunction of the given gene. Such associations may be detected even when metabolic or glycomic disease was not present in the original differential diagnosis, since clearly-apparent metabolic or glycomic diseases are likely to have been identified prior to presentation to the UDP. Here we present in-progress examples of cases where synergy between metabolic and molecular data from UDP cases prompted follow up investigation. For instance, a UDP patient presenting with developmental regression, seizures, CNS and neuromuscular findings was found to have an abnormal metabolic profile. The metabolic profile did not clearly match any known metabolic disease. However, several acylcarnitine profile abnormalities supported the presence of a defect in fatty acid oxidation. This finding was used to support the prioritization of compound heterozygous variants in ACSM5, a fatty acid synthetase gene with a presumptive but unproven role in fatty acid activation for the metabolism of medium-chain fatty acids.

Category: Genetics and Genomics