TY - JOUR
T1 - Recognizable phenotypes in CDG
AU - Ferreira, Carlos R.
AU - Altassan, Ruqaia
AU - Marques-Da-Silva, Dorinda
AU - Francisco, Rita
AU - Jaeken, Jaak
AU - Morava, Eva
N1 - Funding Information:
Acknowledgements This study is supported by the 1805218 N FWO subsidie, in part by the Hayward Foundation and by 1 U54 GM104940 from the National Institute of General Medical Sciences of the National Institutes of Health, which funds the Louisiana Clinical and Translational Science Center. Additionally this work was supported by the European Union’s Horizon 2020 research and innovation program under the ERA-NET Cofund action N° 643578 –EURO-CDG-2.
Funding Information:
This study is supported by the 1805218?N FWO subsidie, in part by the Hayward Foundation and by 1?U54 GM104940 from the National Institute of General Medical Sciences of the National Institutes of Health, which funds the Louisiana Clinical and Translational Science Center. Additionally this work was supported by the European Union?s Horizon 2020 research and innovation program under the ERA-NET Cofund action N? 643578 ?EURO-CDG-2.
Publisher Copyright:
© 2018, SSIEM.
PY - 2018/5/1
Y1 - 2018/5/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85045261142&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85045261142&partnerID=8YFLogxK
U2 - 10.1007/s10545-018-0156-5
DO - 10.1007/s10545-018-0156-5
M3 - Review article
C2 - 29654385
AN - SCOPUS:85045261142
SN - 0141-8955
VL - 41
SP - 541
EP - 553
JO - Journal of Inherited Metabolic Disease
JF - Journal of Inherited Metabolic Disease
IS - 3
ER -