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Exome sequencing reveals pathogenic mutations in the LARS2 and HSD17B4 genes associated with Perrault syndrome and D-bifunctional protein deficiency in Moroccan families. | LitMetric

AI Article Synopsis

  • Syndromic hearing loss (SHL) is a condition involving hearing impairment and other health issues, with over 400 known syndromes, making early diagnosis crucial for managing associated risks.
  • This study analyzed the genetic causes of hearing loss in three Moroccan patients using whole exome sequencing, discovering specific mutations linked to Perrault syndrome and D-bifunctional protein deficiency.
  • The findings emphasize the power of whole exome sequencing and bioinformatics in identifying harmful genetic mutations and understanding their impacts on protein function.

Article Abstract

Background: Syndromic hearing loss (SHL) is characterized by hearing impairment accompanied by other clinical manifestations, reaching over 400 syndromes. Early and accurate diagnosis is essential to understand the progression of hearing loss and associated systemic complications.

Methods And Results: In this study, we investigated the genetic etiology of sensorineural hearing loss in three Moroccan patients using whole exome sequencing (WES). The results revealed in two families Perrault syndrome caused by LARS2, p. Asn153His; p. Thr629Met compound heterozygous variants in two siblings in one family; and p. Thr522Asn, a homozygous variant in two sisters in another. The patient in the third family was diagnosed with D-bifunctional protein deficiency (D-BPD), linked to compound heterozygous mutations p. Asn457Tyr and p. Val643Argfs*5 in HSD17B4. Molecular dynamic simulation results showed that Val643Argfs*5 does not prevent HSD17B4 protein from binding to the PEX5 receptor, but further studies are recommended to verify its effect on HSD17B4 protein functionality.

Conclusion: These results highlight the effectiveness of WES in identifying pathogenic mutations involved in heterogeneous disorders and the usefulness of bioinformatics in predicting their effects on protein structure.

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Source
http://dx.doi.org/10.1007/s11033-024-09740-xDOI Listing

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