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Using expression quantitative-trait association studies (eGWAS) to identify loci for mesial temporal lobe epilepsy

Grant number: 18/03254-7
Support type:Scholarships in Brazil - Post-Doctorate
Effective date (Start): September 01, 2018
Effective date (End): August 31, 2020
Field of knowledge:Health Sciences - Medicine
Principal Investigator:Iscia Teresinha Lopes Cendes
Grantee:Estela Maria Bruxel
Home Institution: Faculdade de Ciências Médicas (FCM). Universidade Estadual de Campinas (UNICAMP). Campinas, SP, Brazil
Associated research grant:13/07559-3 - BRAINN - The Brazilian Institute of Neuroscience and Neurotechnology, AP.CEPID

Abstract

Epilepsy is defined as a neurological disorder characterized by the permanent predisposition of the brain to generate spontaneous epileptic seizures. Temporal lobe epilepsy is the most common form of focal epilepsy in the adult population, accounting for approximately 40% of all cases of epilepsy in this population. The understanding of the basic mechanisms, including genetic predisposition, leading to epilepsy has grown rapidly in the last few decades; however, in complex inherited epilepsies, which are the most frequent forms, the genetic basis remains largely unknown. Mainly in focal epilepsies the challenge of identifying susceptibility loci using genome-wide association studies (GWAS) has been unsuccessful. Therefore, the proposed research aims to identify susceptibility loci for mesial temporal lobe epilepsy (MTLE), the most frequent form of temporal lobe epilepsy, using new strategy called gene expression-based association study (eGWAS). For the development of the project, GWAS data will be generated from a sample of 500 patients with MTLE and 500 controls, using a genomic SNP-array. In addition, gene expression data will be generated in surgical material from patients with MTLE (n = 5) and controls obtained from autopsy (n = 5) to perform an eQTL study. Subsequently, statistical analyzes will be performed to integrate GWAS and eQTL data to identify the susceptibility loci. The eGWAS strategy has never been used to study MTLE but has led to success in other complex inherited diseases. The literature has shown that by integrating gene expression data into association analysis it is possible to increase sensitivity by incorporating functional data, which in turn reduces the number of multiple comparisons, and statistical corrections, that makes it difficult to find positive results in GWAS.

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