Updated Genotype-Phenotype Correlations in TSC

Tuberous sclerosis complex (TSC) is an autosomal dominant disorder characterized by the development of widespread hamartomatous lesions in various organs, including brain, skin, kidneys, heart, and eyes. Central nervous system is almost invariably involved, with up to 85% of patients presenting with epilepsy, and at least half of patients having intellectual disability or other neuropsychiatric disorders including autism spectrum disorder. TSC is caused by the mutation in one of the 2 genes TSC1, at 9q34, and TSC2, at 16p13.3. They respectively encode for hamartin and tuberin, which form an intracellular complex inhibiting the mammalian target of rapamycin. Mammalian target of rapamycin overactivation following the genetic defect determines the cell growth and proliferation responsible for TSC-related lesions, as well as the alterations in neuronal excitability and synaptogenesis leading to epilepsy and neuropsychiatric disorders. A causative mutation for the disorder is identified in about 85% of patients with a clinical diagnosis of TSC. Mosaicism and technology limits likely explain most of the no mutation identified cases. This review confirms that patients with TSC2 mutations considered as a group usually present a more severe phenotype, characterized by higher number of tubers, earlier age at seizure onset and higher prevalence of intellectual disability. However, the clinical phenotype of the disease presents a high variability, thus making the prediction of the phenotype on an individual basis still challenging. The increasing application of new molecular techniques to subjects with TSC has the potential to significantly reduce the rate of patients with no mutation demonstrated and to identify an increasing higher number of mutations. This would hopefully allow a better characterization of higher risk mutations, which might help clinicians to plan individualized surveillance plans. Furthermore, the increasing availability of disease registries to collect clinical and genetics data of patients help to define more valid and clinically oriented genotype or phenotype correlations.