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Reclassification of PAPSS2 Missense Variants in Turkish Patients with Brachyolmia Type 4: Multi-Modal Computational
Serdar Bozlak1, Cuneyd Yavas1, Sajjad Eslamkhah1
1Department of Molecular Biology and Genetics, Biruni University, Istanbul 34015, Türkiye.
Medicina (Kaunas, Lithuania)
|July 28, 2026
Summary
Novel PAPSS2 variants causing brachyolmia type 4 were reclassified as likely pathogenic. This advances understanding of skeletal dysplasia and endocrine conditions, aiding genetic counseling.
Area of Science:
- Genetics
- Molecular Biology
- Endocrinology
Background:
- Loss-of-function variants in PAPSS2 gene cause autosomal recessive brachyolmia type 4, a skeletal dysplasia.
- Over 90 cases are documented, yet many variants remain of uncertain significance (VUS).
Purpose of the Study:
- To perform integrated in silico analysis of two novel PAPSS2 missense variants.
- To reclassify the significance of these variants using ACMG/AMP guidelines.
Main Methods:
- Whole-exome sequencing identified two homozygous missense variants: c.227T>A p.(Leu76Gln) and c.143C>G p.(Thr48Arg).
- Multi-modal in silico analysis included AlphaMissense, REVEL, CADD Phred, evolutionary conservation, and AlphaFold2 structural modeling.
- Variant reclassification followed 2015 ACMG/AMP guidelines.
Main Results:
- Both variants met criteria for reclassification from VUS to Likely Pathogenic (PS3, PM1, PM2, PP3).
- p.(Leu76Gln) disrupts hydrophobic core stability; p.(Thr48Arg) causes active-site steric hindrance.
- Probands exhibited platyspondyly, short stature, and DHEA-sulfate depletion; prepubertal cases had normal androgens.
Conclusions:
- Multi-modal computational analysis supports likely pathogenic classification of the studied PAPSS2 variants.
- This reclassification facilitates precision genetic counseling and deepens the understanding of skeletal and endocrine heterogeneity.
- The PAPSS2 variant registry is expanded to over 92 cases globally.
Keywords:
APS-kinase domain dysfunctionPAPSS2 deficiencyVUS reclassificationadrenal steroid metabolismandrogen phenotype variationdeep learning pathogenicity predictionmulti-modal computational analysisskeletal dysplasia genetic heterogeneity
