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Scientific result | Brain | MRI | Cognition | Genomics
Using data from the UK Biobank, the world's largest general population imaging-genetics cohort, a collaboration led by a team at BAOBAB (NeuroSpin) has identified genes involved in the genetic architecture of language functional connectivity. These genes could be a priority for studying natural language.
Language is a unique trait of the human species, whose genetic architecture remains largely unknown. Studies of individual cases with language disorders have identified candidate genes. However, it is unlikely that only a few genes are responsible for language, which is a complex and multifactorial process. Like height or body mass index, language would rather be associated with many genes, interacting with each other and contributing to the establishment of neuronal pathways involved in its development. Thus, case-control studies suffer from a lack of statistical power and struggle to find genetic markers significantly associated with language.In parallel to genetic studies, neuroimaging and in particular functional MRI of cognitive tasks (TfMRI) has contributed significantly to the understanding of structural and functional aspects of language in the human brain. More recently, numerous studies have demonstrated the relevance of resting-state functional MRI (RfMRI), which is easier to acquire, to study cognitive processes. Indeed, the functional connectivity (FC) map obtained by this technique summarizes the networks of different cognitive processes including language. The availability of RfMRI data and genetic data in large-scale cohorts, such as the UK Biobank, has brought a new dimension to the study of genetic factors in language.In the present study, to analyze the genetic architecture of language functional connectivity, researchers performed a multivariate genome-wide association analysis between genetic variations and resting-state functional connectivity of 25 classic language brain areas extracted from a meta-analysis of 129 fMRI studies of language tasks in 32,186 UK Biobank participants. Three hundred FC were calculated between all pairs of the regions considered. Of these, 142 were found to be significantly heritable and were considered for the subsequent multivariate association study. Twenty genomic loci were found to be associated with language FC. Among them, the EPHA3 gene, putatively involved in dyspraxia, dyslexia and specific language disorders, is found to be associated with the fronto-parieto-temporal semantic network. The THBS1 gene, involved in synaptogenesis, proliferation and differentiation of neural progenitor cells is associated with the perceptual-motor interaction required for language. Finally, the PLCE1 gene has a potential role in the bilateral frontotemporal auditory-motor network.Using a multivariate approach, the researchers studied language using data from the largest imaging-genetics cohort to date, without language-related cognitive scores or language-oriented task fMRI. They identified potential key language-related genes that could provide new insights into the neurobiology of this complex process.Functional connectivities (FC) represent the correlations between the average fMRI signals of the regions considered.Genome-wide : study of all the genes present in individuals of the same species.
Contact: Cathy Philippe firstname.lastname@example.org See also our April 2021 news, a study based on UK Biobank data analysis.
Collaborations - Département de Biologie Computationnelle, Institut Pasteur ;- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR 5293, CEA - CNRS - Université de Bordeaux ;- Basque Center on Cognition, Brain and Language, San Sebastian, Spain
Yasmina Mekki , Vincent Guillemot , Herve Lemaitre, Amaia Carrion-Castillo, Stephanie Forkel, Vincent Frouin, Cathy Philippe. The genetic architecture of language functional connectivity. Neuroimage, vol 249 2022 https://doi.org/10.1016/j.neuroimage.2021.118795
CEA is a French government-funded technological research organisation in four main areas: low-carbon energies, defense and security, information technologies and health technologies. A prominent player in the European Research Area, it is involved in setting up collaborative projects with many partners around the world.