复合杂合度
产前诊断
遗传学
生物
关节病
胎儿
外显子组测序
等位基因
基因
医学
表型
怀孕
作者
Ebba Alkhunaizi,Nicole Martin,Angie C. Jelin,Mara Rosner,Diana Bailey,Laurie A. Steiner,Saquib A. Lakhani,Weizhen Ji,Philip J. Katzman,Katherine R Forster,Olga Jarinova,Patrick Shannon,David Chitayat
摘要
Arthrogryposis multiplex congenita (AMC) [also known as multiple joints contracture or Fetal Akinesia Deformation Sequence (FADS)] is etiologically a heterogeneous condition with an estimated incidence of approximately 1 in 3000 live births and much higher incidence when prenatally diagnosed cases are included. The condition can be acquired or secondary to fetal exposures and can also be caused by a variety of single-gene disorders affecting the brain, spinal cord, peripheral nerves, neuromuscular junction, muscle, and a variety of disorders affecting the connective tissues (Niles et al., Prenatal Diagnosis, 2019; 39:720-731). The introduction of next-generation gene sequencing uncovered many genes and causative variants of AMC but also identified genes that cause both dominant and recessive inherited conditions with the variability of clinical manifestations depending on the genes and variants. Molecular diagnosis in these cases is not only important for prognostication but also for the determination of recurrence risk and for providing reproductive options including preimplantation and prenatal diagnosis. TTN, the largest known gene in the human genome, has been known to be associated with autosomal dominant dilated cardiomyopathy. However, homozygote and compound heterozygote pathogenic variants with recessive inheritance have rarely been reported. We report the effect of recessive variants located within the fetal IC and/or N2BA isoforms in association with severe FADS in three families. All parents were healthy obligate carriers and none of them had cardiac or skeletal muscle abnormalities. This report solidifies FADS as an alternative phenotypic presentation associated with homozygote/compound heterozygous pathogenic variants in the TTN.
科研通智能强力驱动
Strongly Powered by AbleSci AI