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01.12.2019 | Research | Ausgabe 1/2019 Open Access

Orphanet Journal of Rare Diseases 1/2019

Genetic, clinical and biochemical characterization of a large cohort of patients with hyaline fibromatosis syndrome

Zeitschrift:
Orphanet Journal of Rare Diseases > Ausgabe 1/2019
Autoren:
Claudia Cozma, Marina Hovakimyan, Marius-Ionuț Iurașcu, Nawal Makhseed, Laila A. Selim, Amal M. Alhashem, Tawfeg Ben-Omran, Iman G. Mahmoud, Nihal M. Al Menabawy, Mariam Al-Mureikhi, Magi Martin, Laura Demuth, Zafer Yüksel, Christian Beetz, Peter Bauer, Arndt Rolfs
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Electronic supplementary material

The online version of this article (https://​doi.​org/​10.​1186/​s13023-019-1183-5) contains supplementary material, which is available to authorized users.

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Abstract

Background

Hyaline fibromatosis syndrome (HFS) is a rare clinical condition in which bi-allelic variants in ANTXR2 are associated with extracellular hyaline deposits. It manifests as multiple skin nodules, patchy hyperpigmentation, joint contractures and severe pain with movement. HFS shows some clinical overlap to Farber disease (FD), a recessive lysosomal storage disorder.

Results

We here present the largest cohort of independent, genetically confirmed HFS cases reported to date: in 19 unrelated index patients, we identified ten distinct homozygous ANTXR2 mutations, three of which are novel frame-shift variants. The associated clinical data are consistent with the previous hypothesis of non-truncating variants in the terminal exons 13–17 to confer rather mild phenotypes. The novel observation of gender-dependent disease manifestation in our cohort received support from a meta-analysis of all previously published cases. Untargeted blood-based metabolomics revealed patient samples to be biochemically distinct from control samples. Numerous potential HFS biomarker metabolites could thus be identified. We also found metabolomics profiles of HFS patients to highly overlap with those from FD patients.

Conclusions

Our study extends the mutational spectrum for HFS, suggests gender-dependency of manifestation, and provides pilot metabolomics data for biomarker identification and a better pathomechanistic understanding of the disorder.
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