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Genotype-phenotype correlations in pathology caused by collagen type IV alpha 1 and 2 mutations

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MATRIX BIOLOGY
卷 57-58, 期 -, 页码 29-44

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ELSEVIER SCIENCE BV
DOI: 10.1016/j.matbio.2016.10.003

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资金

  1. American Heart Association [13POST14120019]
  2. National Institute of Neurological Disease and Stroke [NS083830]
  3. National Eye Institute [EY02162]
  4. Research to Prevent Blindness

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COL4A1 and COL4A2 are extracellular matrix proteins that form heterotrimers and are present in nearly all basement membranes in every organ. In the past decade, COL4A1 and COL4A2 mutations have been identified to cause a multi-system disorder for which penetrance and severity of constituent phenotypes can greatly vary. Here, we compare the outcomes of more than 100 mutations identified in patients and data from a murine allelic series to explore the presence of genotype phenotype correlations many of which are shared among other types of collagen. We find that there is a frequency bias for COL4A1 over COL4A2 mutations and that glycine (Gly) substitutions within the triple helical domain are the most common class of mutations. Glycine is most often replaced by a charged amino acid, however the position of the mutation, and not the properties of the substituting amino acid, appears to have a greater influence on disease severity. Moreover, the impact of position is not straightforward. Observations from a murine allelic series suggest that mutations in the NC1 domain may result in relatively mild phenotypes via a 'quantitative' mechanism similar to other types of collagens, however, this effect was not apparent in human reports. Importantly, other position-dependent effects had differential impacts depending on the phenotype of interest. For example, the severity of cerebrovascular disease correlated with an amino-to-carboxy severity gradient for triple-helical glycine substitutions whereas the penetrance and severity of myopathy and nephropathy appear to involve a functional sub-domain(s). Greater understanding of genotype phenotype correlations and the interaction of consequences of different mutations will be important for patient prognosis and care and for developing mechanism-based therapeutics to treat individual components of this emerging syndrome. (C) 2016 Elsevier B.V. All rights reserved.

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