Header

UZH-Logo

Maintenance Infos

Multiomics tools for the diagnosis and treatment of rare neurological disease


Crowther, L M; Poms, M; Plecko, Barbara (2018). Multiomics tools for the diagnosis and treatment of rare neurological disease. Journal of Inherited Metabolic Disease, 41(3):425-434.

Abstract

Conventional workup of rare neurological disease is frequently hampered by diagnostic delay or lack of diagnosis. While biomarkers have been established for many neurometabolic disorders, improved methods are required for diagnosis of previously unidentified or underreported causes of rare neurological disease. This would result in a higher diagnostic yield and increased patient numbers required for interventional studies. Recent studies using next-generation sequencing and metabolomics have led to identification of novel disease-causing genes and biomarkers. This combined approach can assist in overcoming challenges associated with analyzing and interpreting the large amount of data obtained from each technique. In particular, metabolomics can support the pathogenicity of sequence variants in genes encoding enzymes or transporters involved in metabolic pathways. Moreover, metabolomics can show the broader perturbation caused by inborn errors of metabolism and identify a metabolic fingerprint of metabolic disorders. As such, using "omics" has great potential to meet the current needs for improved diagnosis and elucidation of rare neurological disease.

Abstract

Conventional workup of rare neurological disease is frequently hampered by diagnostic delay or lack of diagnosis. While biomarkers have been established for many neurometabolic disorders, improved methods are required for diagnosis of previously unidentified or underreported causes of rare neurological disease. This would result in a higher diagnostic yield and increased patient numbers required for interventional studies. Recent studies using next-generation sequencing and metabolomics have led to identification of novel disease-causing genes and biomarkers. This combined approach can assist in overcoming challenges associated with analyzing and interpreting the large amount of data obtained from each technique. In particular, metabolomics can support the pathogenicity of sequence variants in genes encoding enzymes or transporters involved in metabolic pathways. Moreover, metabolomics can show the broader perturbation caused by inborn errors of metabolism and identify a metabolic fingerprint of metabolic disorders. As such, using "omics" has great potential to meet the current needs for improved diagnosis and elucidation of rare neurological disease.

Statistics

Citations

Dimensions.ai Metrics
10 citations in Web of Science®
13 citations in Scopus®
Google Scholar™

Altmetrics

Downloads

31 downloads since deposited on 15 Feb 2019
14 downloads since 12 months
Detailed statistics

Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > University Children's Hospital Zurich > Medical Clinic
Dewey Decimal Classification:610 Medicine & health
Scopus Subject Areas:Life Sciences > Genetics
Health Sciences > Genetics (clinical)
Language:English
Date:May 2018
Deposited On:15 Feb 2019 10:36
Last Modified:29 Jul 2020 09:25
Publisher:Springer
ISSN:0141-8955
OA Status:Hybrid
Free access at:PubMed ID. An embargo period may apply.
Publisher DOI:https://doi.org/10.1007/s10545-018-0154-7
PubMed ID:29536202

Download

Hybrid Open Access

Download PDF  'Multiomics tools for the diagnosis and treatment of rare neurological disease'.
Preview
Content: Published Version
Filetype: PDF
Size: 679kB
View at publisher
Licence: Creative Commons: Attribution 4.0 International (CC BY 4.0)