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Objective To determine the small vessel disease spectrum associated with cysteine-altering NOTCH3 variants in community-dwelling individuals by analyzing the clinical and neuroimaging features of UK Biobank participants harboring such variants. Methods The exome and genome sequencing datasets of the UK Biobank (n = 50,000) and cohorts of cognitively healthy elderly (n = 751) were queried for cysteine-altering NOTCH3 variants. Brain MRIs of individuals harboring such variants were scored according to Standards for Reporting Vascular Changes on Neuroimaging criteria, and clinical information was extracted with ICD-10 codes. Clinical and neuroimaging data were compared to age- and sex-matched UK Biobank controls and clinically diagnosed patients from the Dutch cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) registry. Results We identified 108 individuals harboring a cysteine-altering NOTCH3 variant (2.2 of 1,000), of whom 75% have a variant that has previously been reported in CADASIL pedigrees. Almost all variants were located in 1 of the NOTCH3 protein epidermal growth factor–like repeat domains 7 to 34. White matter hyperintensity lesion load was higher in individuals with NOTCH3 variants than in controls (p = 0.006) but lower than in patients with CADASIL with the same variants (p < 0.001). Almost half of the 24 individuals with brain MRI had a Fazekas score of 0 or 1 up to age 70 years. There was no increased risk of stroke. Conclusions Although community-dwelling individuals harboring a cysteine-altering NOTCH3 variant have a higher small vessel disease MRI burden than controls, almost half have no MRI abnormalities up to age 70 years. This shows that NOTCH3 cysteine altering variants are associated with an extremely broad phenotypic spectrum, ranging from CADASIL to nonpenetrance.

Figure S1. Brain alignment summary. (PDF 116 kb)

Figure S4. number of reads and quality of blood RNA sequencing. A Number of reads obtained for each mouse is depicted per time point. RNA sequencing reads were aligned to mouse reference genome build 10 (GRCm38/mm10) using star aligner. B Distribution of reads for blood RNA sequencing indicate that globin reduction was efficient (1st rank gene account for

Table S2. Lipid classes altered at 4, 12 and 16Â months in SCA3 mice. Only lipid classes with at least one significantly altered unique lipid at any time are shown. (DOCX 14 kb)

Figure S5. distribution of metabolite classes and lipid families identified from mass-spec analysis of plasma samples. LC-HRMS analysis of plasma samples led to identification of 148 unique metabolites and 491 lipids. (PDF 88 kb)

Figure S2. Brain PCA. (PDF 141 kb)

Figure S6. principal component analysis (PCA) of measured metabolites. Individual barcodes of mice are depicted, plasma was obtained for each mouse at 3 time points A) Age is significantly correlated with PC1 (ρ = − 0.586, p

Table S1. Primers used for qPCR validation of RNA sequencing results. (DOCX 13 kb)

Table S1. Primers used for qPCR validation of RNA sequencing results. (DOCX 13 kb)