A multivariate disease progression model for identifying subtypes in CADASIL

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Kaisaridi, Sofia | Chabriat, Hugues | Tezenas Du Montcel, Sophie

Edité par CCSD -

International audience. Cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL) is a monogenic form of cerebral small artery disease caused by mutations in the NOTCH3 gene. The multifaceted clinical presentation of this disorder can be assessed using various measures that allow us to describe patients' cognitive efficiency, memory performance, disability, neurological deficits, daily activities, and quality of life [1]. We implemented the multivariate version of a bayesian mixed-effects model (Leaspy), which includes a time reparametrisation to analyse the evolution of the disease. We were also able to identify different subgroups of individual evolution using a GMM classification algorithm on the individual parameters and to evaluate the influence of baseline covariates such as gender, education level, hypertension, and location of the mutation.

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