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Recognizable phenotypes in CDG.
- Source :
-
Journal of inherited metabolic disease [J Inherit Metab Dis] 2018 May; Vol. 41 (3), pp. 541-553. Date of Electronic Publication: 2018 Apr 13. - Publication Year :
- 2018
-
Abstract
- Pattern recognition, using a group of characteristic, or discriminating features, is a powerful tool in metabolic diagnostic. A classic example of this approach is used in biochemical analysis of urine organic acid analysis, where the reporting depends more on the correlation of pertinent positive and negative findings, rather than on the absolute values of specific markers. Similar uses of pattern recognition in the field of biochemical genetics include the interpretation of data obtained by metabolomics, like glycomics, where a recognizable pattern or the presence of a specific glycan sub-fraction can lead to the direct diagnosis of certain types of congenital disorders of glycosylation. Another indispensable tool is the use of clinical pattern recognition-or syndromology-relying on careful phenotyping. While genomics might uncover variants not essential in the final clinical expression of disease, and metabolomics could point to a mixture of primary but also secondary changes in biochemical pathways, phenomics describes the clinically relevant manifestations and the full expression of the disease. In the current review we apply phenomics to the field of congenital disorders of glycosylation, focusing on recognizable differentiating findings in glycosylation disorders, characteristic dysmorphic features and malformations in PMM2-CDG, and overlapping patterns among the currently known glycosylation disorders based on their pathophysiological basis.
- Subjects :
- Congenital Disorders of Glycosylation genetics
Diagnosis, Differential
Genomics methods
Glycomics methods
Humans
Metabolomics methods
Pattern Recognition, Automated methods
Pattern Recognition, Visual
Congenital Disorders of Glycosylation diagnosis
Congenital Disorders of Glycosylation pathology
Phenotype
Subjects
Details
- Language :
- English
- ISSN :
- 1573-2665
- Volume :
- 41
- Issue :
- 3
- Database :
- MEDLINE
- Journal :
- Journal of inherited metabolic disease
- Publication Type :
- Academic Journal
- Accession number :
- 29654385
- Full Text :
- https://doi.org/10.1007/s10545-018-0156-5