Dataset Information

Neurometabolic disorders: Five new things.

ABSTRACT:

Purpose of review

To present emerging issues in neurometabolic disorders, with an emphasis on the diagnostic workup of patients with suspected neurometabolic disorders and some future challenges in the care for these patients.

Recent findings

Next-generation sequencing and next-generation metabolic screening increase the speed and yield of the diagnostic process in neurometabolic disorders. Furthermore, they deepen our insights into the underlying disease mechanisms. Care of adult patients with neurometabolic disorders is an expanding subspecialty, especially in internal medicine and neurology.

Summary

We briefly discuss some novel genetic and biochemical laboratory techniques and changing insights in the molecular basis of disease, and illustrate the importance of MRI pattern recognition in the diagnostic process. Furthermore, we discuss gene therapy that is cautiously entering the field, and pay attention to the new field of (transition of) care for adult patients with inborn errors of metabolism.

SUBMITTER: Willemsen MA

PROVIDER: S-EPMC5727707 | biostudies-literature | 2016 Aug

REPOSITORIES: biostudies-literature

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Publications

Neurometabolic disorders: Five new things.

Willemsen Michèl A MA Harting Inga I Wevers Ron A RA

Neurology. Clinical practice 20160801 4

<h4>Purpose of review</h4>To present emerging issues in neurometabolic disorders, with an emphasis on the diagnostic workup of patients with suspected neurometabolic disorders and some future challenges in the care for these patients.<h4>Recent findings</h4>Next-generation sequencing and next-generation metabolic screening increase the speed and yield of the diagnostic process in neurometabolic disorders. Furthermore, they deepen our insights into the underlying disease mechanisms. Care of adult ...[more]

PMID: 29443118

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Project description:BackgroundWhole-exome sequencing has transformed gene discovery and diagnosis in rare diseases. Translation into disease-modifying treatments is challenging, particularly for intellectual developmental disorder. However, the exception is inborn errors of metabolism, since many of these disorders are responsive to therapy that targets pathophysiological features at the molecular or cellular level.MethodsTo uncover the genetic basis of potentially treatable inborn errors of metabolism, we combined deep clinical phenotyping (the comprehensive characterization of the discrete components of a patient's clinical and biochemical phenotype) with whole-exome sequencing analysis through a semiautomated bioinformatics pipeline in consecutively enrolled patients with intellectual developmental disorder and unexplained metabolic phenotypes.ResultsWe performed whole-exome sequencing on samples obtained from 47 probands. Of these patients, 6 were excluded, including 1 who withdrew from the study. The remaining 41 probands had been born to predominantly nonconsanguineous parents of European descent. In 37 probands, we identified variants in 2 genes newly implicated in disease, 9 candidate genes, 22 known genes with newly identified phenotypes, and 9 genes with expected phenotypes; in most of the genes, the variants were classified as either pathogenic or probably pathogenic. Complex phenotypes of patients in five families were explained by coexisting monogenic conditions. We obtained a diagnosis in 28 of 41 probands (68%) who were evaluated. A test of a targeted intervention was performed in 18 patients (44%).ConclusionsDeep phenotyping and whole-exome sequencing in 41 probands with intellectual developmental disorder and unexplained metabolic abnormalities led to a diagnosis in 68%, the identification of 11 candidate genes newly implicated in neurometabolic disease, and a change in treatment beyond genetic counseling in 44%. (Funded by BC Children's Hospital Foundation and others.).

Dataset Information

Neurometabolic disorders: Five new things.

Purpose of review

Recent findings

Summary

Publications

Neurometabolic disorders: Five new things.

Similar Datasets

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