ZFIN ID: ZDB-PUB-200115-5
Phenome-based approach identifies RIC1-linked Mendelian syndrome through zebrafish models, biobank associations and clinical studies
Unlu, G., Qi, X., Gamazon, E.R., Melville, D.B., Patel, N., Rushing, A.R., Hashem, M., Al-Faifi, A., Chen, R., Li, B., Cox, N.J., Alkuraya, F.S., Knapik, E.W.
Date: 2020
Source: Nature medicine   26: 98-109 (Journal)
Registered Authors: Knapik, Ela W., Melville, David, Rushing, Amy Rene, Unlu, Gokhan
Keywords: none
MeSH Terms:
  • Abnormalities, Multiple/pathology*
  • Animals
  • Behavior, Animal
  • Biological Specimen Banks*
  • Chondrocytes/pathology
  • Chondrocytes/ultrastructure
  • Disease Models, Animal
  • Extracellular Matrix/metabolism
  • Fibroblasts/metabolism
  • Fibroblasts/pathology
  • Fibroblasts/ultrastructure
  • Guanine Nucleotide Exchange Factors/genetics*
  • Humans
  • Models, Biological
  • Musculoskeletal System/pathology
  • Osteogenesis
  • Phenomics*
  • Phenotype
  • Procollagen/metabolism
  • Protein Transport
  • Secretory Pathway
  • Syndrome
  • Zebrafish
  • Zebrafish Proteins/genetics*
PubMed: 31932796 Full text @ Nat. Med.
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ABSTRACT
Discovery of genotype-phenotype relationships remains a major challenge in clinical medicine. Here, we combined three sources of phenotypic data to uncover a new mechanism for rare and common diseases resulting from collagen secretion deficits. Using a zebrafish genetic screen, we identified the ric1 gene as being essential for skeletal biology. Using a gene-based phenome-wide association study (PheWAS) in the EHR-linked BioVU biobank, we show that reduced genetically determined expression of RIC1 is associated with musculoskeletal and dental conditions. Whole-exome sequencing identified individuals homozygous-by-descent for a rare variant in RIC1 and, through a guided clinical re-evaluation, it was discovered that they share signs with the BioVU-associated phenome. We named this new Mendelian syndrome CATIFA (cleft lip, cataract, tooth abnormality, intellectual disability, facial dysmorphism, attention-deficit hyperactivity disorder) and revealed further disease mechanisms. This gene-based, PheWAS-guided approach can accelerate the discovery of clinically relevant disease phenome and associated biological mechanisms.
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