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Published on: July 19, 2019
Cerebellar lesions as potential predictors of neurobehavioural phenotype in tuberous sclerosis complex
Irene Toldo1, Samuela Bugin1, Egle Perissinotto2
1Pediatric Neurology and Neurophysiology Unit, Department of Woman's and Child's Health, University of Padua, Padua, Italy.
Aim:
To improve the genetic, clinical, and neuroradiological characterization of cerebellar involvement in tuberous sclerosis complex (TSC) and determine whether cerebellar lesions could be a reliable biomarker of neurological impairment.
Method:
This retrospective cohort study, held at two tertiary paediatric university centres, was conducted on patients with a confirmed diagnosis of TSC who underwent brain magnetic resonance imaging between October 2009 and May 2016. The study population consisted of 112 patients with TSC (median age 10y; range 5mo-38y; 61 females, 51 males).
Results:
The results from multivariable statistical analysis indicated that cerebellar involvement (34 out of 112 patients, none carrying a TSC1 mutation) was the most powerful predictor of supratentorial cortical tuber load; however, cerebellar involvement was not the best predictor of clinical phenotype when supratentorial tuber load and TSC2 mutations were taken into consideration. The association between cerebellar lesions and a more severe clinical and neuroradiological phenotype was statistically significant and may be due to its strong association with TSC2 mutations and higher cortical tuber load.
Interpretation:
Cerebellar involvement is not the best predictor of neurobehavioural outcome, including TSC-related autism, after adjusting for TSC2 and the number of cortical tubers. Its role in the TSC clinical phenotype needs to be investigated further.
What This Paper Adds:
Cerebellar involvement is a powerful predictor of supratentorial cortical involvement and a potential biomarker of disease severity. Cerebellar lesions significantly correlate with a more severe clinical and neuroradiological phenotype. Cerebellar involvement is not the best predictor of neurobehavioural outcome.
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