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Most common NOTCH3 mutations causing CADASIL or CADASIL-like cerebral small vessel disease: A systematic review
Georgina Boston1, Dan Jobson1, Toshiki Mizuno2
1Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, UK.
Insights
This study identifies common NOTCH3 mutations in Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL). Certain genotypes correlate with white matter hyperintensities and disease severity, though overall phenotypes show similarities.
Area of Science:
- Genetics and Neurology
- Molecular Medicine
- Neuroimaging
Background:
- Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) is a genetic disorder impacting small cerebral arteries.
- It is caused by mutations in the NOTCH3 gene, leading to progressive neurological decline.
- Understanding genotype-phenotype correlations is crucial for predicting disease progression and management.
Purpose of the Study:
- To identify the most prevalent NOTCH3 mutations associated with CADASIL globally.
- To investigate the association between specific NOTCH3 genotypes and clinical phenotypes, particularly white matter hyperintensities on MRI.
- To compare disease severity and age of onset across different common NOTCH3 mutations.
Main Methods:
- Systematic literature review of clinical studies and genomic databases (1996-2023).
- Identification of common NOTCH3 missense mutations in CADASIL patients.
- Analysis of clinical records focusing on MRI findings (white matter hyperintensities) and disease characteristics for genotype-phenotype correlation.
Main Results:
- The six most common NOTCH3 mutations are p.R75P, p.R133C, p.R141C, p.R169C, p.R182C, and p.R544C, with p.R133C being the most frequent.
- Genotypes p.R75P, p.R141C, p.R182C, and p.R544C showed a strong association with white matter hyperintensities on MRI.
- The p.R141C mutation was linked to increased disease severity and earlier onset compared to p.R544C, although overall phenotypic differences between these two were not statistically significant.
Conclusions:
- Specific NOTCH3 mutations are strongly associated with key CADASIL phenotypes, particularly white matter changes visible on MRI.
- While some mutations like p.R141C may indicate greater disease severity, the phenotypic spectrum for common mutations like p.R141C and p.R544C is largely overlapping.
- Geographic distribution of mutations suggests potential founder effects or sampling biases in regions like China and Japan.
Abstract:
Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) is a monogenic disorder caused by mutations in the NOTCH3 gene. The main aim of our survey was to determine if there is an association between phenotypes and genotypes across the most common NOTCH3 mutations found in CADASIL patients. We systematically searched clinical studies and genomic databases from 1996 to 2023 to first identify the most common mutations responsible for CADASIL. We found the six most common NOTCH3 missense mutations globally were the p.R75P, p.R133C, p.R141C, p.R169C, p.R182C, and p.R544C, of which p.R133C was described to occur most often. Focusing on studies with comprehensive clinical records, our analysis further suggested that the p.R75P, p.R141C, p.R182C and p.R544C genotypes were highly congruent with the presence of white matter hyperintensities on magnetic resonance imaging (MRI), which was the most common phenotypic characteristic across all four mutations. We found the p.R141C mutation was associated with increased severity of disease. We also found the average age of onset in p.R544C carriers was more than a decade later compared to the p.R141C carriers. However, statistical analysis showed there were no overall differences between the phenotypic characteristics of the two common mutations, p.R141C and p.R544C. Geographically, China and Japan were the only two countries to report all the four common mutations vis a vis p.R75P, p.R141C, p.R182C and p.R544C. There is a possibility that this is due to a combination of a founder effect, but there also could be sampling biases.
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