Genome-wide scan for five brain oscillatory phenotypes identifies a new qtl associated with theta eeg band

• Autor(a) principal: Rebelo, MÂ
• Data de Publicação: 2020
• Outros Autores: Gómez, C, Gomes, I, Poza, J, Martins, S, Maturana-Candelas, A, Ruiz-Gómez, SJ, Durães, L, Sousa, P, Figueruelo, M, Rodríguez, M, Pita, C, Arenas, M, Alvarez, L, Hornero, R, Pinto, N, Lopes, AM
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: https://hdl.handle.net/10216/145237
• topic: Alzheimer’s disease; Brain electrophysiology; Brain QTL; Electroencephalography rhythms; Endophenotype; Frequency spectrum relative power; Genome-wide association study; Neurological disorders

Brain waves, measured by electroencephalography (EEG), are a powerful tool in the investigation of neurophysiological traits and a noninvasive and cost-effective alternative in the diagnostic of some neurological diseases. In order to identify novel Quantitative Trait Loci (QTLs) for brain wave relative power (RP), we collected resting state EEG data in five frequency bands (d, ¿, a, ß1, and ß2) and genome-wide data in a cohort of 105 patients with late onset Alzheimer’s disease (LOAD), 41 individuals with mild cognitive impairment and 45 controls from Iberia, correcting for disease status. One novel association was found with an interesting candidate for a role in brain wave biology, CLEC16A (C-type lectin domain family 16), with a variant at this locus passing the adjusted genome-wide significance threshold after Bonferroni correction. This finding reinforces the importance of immune regulation in brain function. Additionally, at a significance cutoff value of 5 × 10-6, 18 independent association signals were detected. These signals comprise brain expression Quantitative Loci (eQTLs) in caudate basal ganglia, spinal cord, anterior cingulate cortex and hypothalamus, as well as chromatin interactions in adult and fetal cortex, neural progenitor cells and hippocampus. Moreover, in the set of genes showing signals of association with brain wave RP in our dataset, there is an overrepresentation of loci previously associated with neurological traits and pathologies, evidencing the pleiotropy of the genetic variation modulating brain function.