CATCHing putative causative variants in consanguineous families

Area of Science:

• Genetics
• Genomics
• Bioinformatics

Background:

• Consanguinity increases the risk of autosomal recessive (AR) disorders due to homozygous pathogenic variants.
• Many genetic disorders in offspring of consanguineous couples remain undiagnosed.
• High-throughput sequencing offers potential for molecular diagnosis and novel gene discovery.

Purpose of the Study:

• To develop an algorithm for identifying causative variants in consanguineous families.
• To leverage family structure and genomic data for improved genetic diagnosis.

Main Methods:

• Developed CATCH, an algorithm integrating genotyped SNPs and exome sequencing data.
• Applied CATCH to analyze genetic data from consanguineous families with unexplained phenotypes.
• Focused on detecting Runs of Homozygosity (ROH) and identifying homozygous variants.

Main Results:

• CATCH successfully identified causative variants in 43 out of 50 consanguineous families.
• Discovered novel variants responsible for familial thrombocytopenia and sclerosis bone dysplasia.
• Identified the first homozygous loss-of-function mutation in FGFR3, causing severe skeletal deformities.

Conclusions:

• The CATCH algorithm is effective for molecular diagnosis in consanguineous families.
• Enables identification of known and novel disease-causing variants.
• Advances understanding of genetic disorders associated with consanguinity.