Cluster analysis as a new approach to the phenotyping of hypermobility syndrome

Introduction. Joint hypermobility (JH) is a heterogeneous condition that is considered as an isolated condition and in combination with connective tissue dysplasia (CTD), nevertheless, patients with JH have high risks of developing associated conditions, but do not receive proper treatment and appropriate prevention due to difficulties in diagnosis and classification.

Aim. Conduct phenotyping of the JH in order to optimize diagnostics.

Materials and methods. The study involved 262 young men (n = 35) and women (n = 227); the average age was 21.86 ± 0.22 years. JH was determined on a 9-point Beighton scale (1998). Phenotypic signs of CTD were determined by the point‒quantitative method (T.I. Kadurina), JH and control groups were formed. Statistical data processing was carried out in Microsoft Excel 2021, Statistica 13, R Studio. The association search was carried out using the Fisher criterion X2, with the Yates correction. To perform cluster analysis (CA), the R Studio environment, the k-medoids algorithm, the “pam” function in R, the libraries “cluster”, “tidyverse”, “factoextra”, “NbClust”, for validation “clValid” were used.

Results. JH was associated with phenotypic signs of CTD, such as dolichostenomelia, joint crunch, hyperkyphosis/hyperlordosis, low body mass index (BMI), skin’s hyperelasticity, ptosis of internal organs, hypotension, severe myopia. Next, a survey was conducted, as a result of which three clusters were identified. Cluster No. 1 included JH, hyperkyphosis/hyperlordosis, and low BMI. Cluster No. 2 includes JH, hyperelasticity of the skin and low BMI, and the third group includes subjects without JH, ptosis, hyperelasticity of the skin, hyperkyphosis/hyperlordosis and with a BMI >18.5.

Conclusion. The heterogeneity found by CA among the subjects with JH suggests that the phenotypes of JH in the general sample may be close to subtypes of Ehlers-Danlos syndrome or represent their incomplete clinical forms.

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