Literature DB >> 26729777

Inborn Errors of Metabolism (Metabolic Disorders).

Gregory M Rice1, Robert D Steiner2.   

Abstract

By their very nature, rare inborn errors of metabolism challenge the generation and application of evidence-based medicine. • On the basis of limited research evidence as well as consensus, newborn screening for select metabolic disorders, including phenylketonuria, medium-chain acyl CoA dehydrogenase deficiency, and glutaric acidemia type I, may improve long-term outcomes for affected children. • On the basis of primarily consensus, due to lack of relevant clinical studies, inborn errors due to defects in the metabolism of energy sources (protein, fatty acids, and carbohydrates) may present in infancy with overwhelming metabolic decompensation, and initial laboratory evaluations may reveal hyperammonemia, nonketotic hypoglycemia, or a metabolic acidosis with an elevated anion gap, depending on the disorder. • On the basis of primarily consensus, due to lack of relevant clinical studies, specific laboratory testing for inborn errors of metabolism should include plasma amino acids, urine organic acids, plasma carnitine, and plasma acylcarnitine profile. • On the basis of primarily consensus, due to lack of relevant clinical studies, disorders of cellular organelles, such as lysosomal and peroxisomal disorders, may present with progressive organomegaly, developmental regression, dysmorphic facial characteristics. or sensory loss.

Entities:  

Mesh:

Year:  2016        PMID: 26729777     DOI: 10.1542/pir.2014-0122

Source DB:  PubMed          Journal:  Pediatr Rev        ISSN: 0191-9601


  2 in total

Review 1.  Hyperammonaemia in classic organic acidaemias: a review of the literature and two case histories.

Authors:  Johannes Häberle; Anupam Chakrapani; Nicholas Ah Mew; Nicola Longo
Journal:  Orphanet J Rare Dis       Date:  2018-12-06       Impact factor: 4.123

2.  Clinical utility in infants with suspected monogenic conditions through next-generation sequencing.

Authors:  Sha Hong; Li Wang; Dongying Zhao; Yonghong Zhang; Yan Chen; Jintong Tan; Lili Liang; Tianwen Zhu
Journal:  Mol Genet Genomic Med       Date:  2019-04-09       Impact factor: 2.183

  2 in total

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