The genomic and clinical landscape of fetal akinesia

Pergande M., Motameny S., Oezdemir O., Kreutzer M., Wang H., Daimagueler H., ...Daha Fazla

GENETICS IN MEDICINE, cilt.22, sa.3, ss.511-523, 2020 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 22 Sayı: 3
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1038/s41436-019-0680-1
  • Dergi Adı: GENETICS IN MEDICINE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, BIOSIS, CAB Abstracts, EMBASE, MEDLINE
  • Sayfa Sayıları: ss.511-523
  • Anahtar Kelimeler: fetal akinesia, arthrogryposis, myopathy, exome, copy-number variation, DISTAL ARTHROGRYPOSIS, NEMALINE MYOPATHY, MUTATIONS, GENETICS, VARIANTS
  • Marmara Üniversitesi Adresli: Evet

Özet

Purpose Fetal akinesia has multiple clinical subtypes with over 160 gene associations, but the genetic etiology is not yet completely understood. Methods In this study, 51 patients from 47 unrelated families were analyzed using next-generation sequencing (NGS) techniques aiming to decipher the genomic landscape of fetal akinesia (FA). Results We have identified likely pathogenic gene variants in 37 cases and report 41 novel variants. Additionally, we report putative pathogenic variants in eight cases including nine novel variants. Our work identified 14 novel disease-gene associations for fetal akinesia: ADSSL1, ASAH1, ASPM, ATP2B3, EARS2, FBLN1, PRG4, PRICKLE1, ROR2, SETBP1, SCN5A, SCN8A, and ZEB2. Furthermore, a sibling pair harbored a homozygous copy-number variant in TNNT1, an ultrarare congenital myopathy gene that has been linked to arthrogryposis via Gene Ontology analysis. Conclusion Our analysis indicates that genetic defects leading to primary skeletal muscle diseases might have been underdiagnosed, especially pathogenic variants in RYR1. We discuss three novel putative fetal akinesia genes: GCN1, IQSEC3 and RYR3. Of those, IQSEC3, and RYR3 had been proposed as neuromuscular disease-associated genes recently, and our findings endorse them as FA candidate genes. By combining NGS with deep clinical phenotyping, we achieved a 73% success rate of solved cases.