Heritability of the language network using resting state fMRI data

Abstract : Background: Language is a singularity of the human species. It is expected to have a genetic constituent. Estimation of the part of variance attributable to genetic variation across subjects in functional brain imaging within the regions of the language, provide us a quantification of the genetic influence. This part of variance -which corresponds to heritability- is important to prioritize the structural and functional brain features. Language specific tasks fMRI are generally used to achieve this decomposition of variance, but resting state fMRI remains also a valid alternative. Indeed, a growing evidence suggest that resting state functional connectivity pattern could be identified during cognitive task activation. UK Biobank with 19,336 subjects that underwent a rsfMRI, as well as Human Connectome Project (HCP) with 1113 subjects are a unique opportunity to study such a question. Methods: The present work consists in estimating the heritability of the language network, using region of interest, identified by (Pallier, 2011) during a task fMRI experience, based on resting state fMRI connectivity analysis. Imaging genetics data for both cohorts underwent a stringent quality control protocol, yielding 18,851 and 739 samples for UKB and HCP respectively. Results: Significant heritability, estimated via GCTA for UKB and SOLAR for HCP, were observed (UKB: h²=10%-14%, HCP: h²=22%-43%). Multiple test were corrected with Bonferroni correction. Conclusions: The obtained results suggest some genetic influence on the phenotype chosen which indicates that the human language brain organization is under relatively strong genetic control, strong enough to consider association studies with genotyping data.
Complete list of metadatas

Cited literature [6 references]  Display  Hide  Download

https://hal-cea.archives-ouvertes.fr/cea-02289470
Contributor : Yasmina Mekki <>
Submitted on : Monday, September 16, 2019 - 5:10:08 PM
Last modification on : Monday, January 13, 2020 - 5:08:19 PM

File

mekki_cognomics_poster.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : cea-02289470, version 1

Citation

Yasmina Mekki, Cathy Philippe, Vincent Guillemot, Hervé Lemaître, Vincent Frouin. Heritability of the language network using resting state fMRI data. COGNOMICS Conference 2019: Bridging Gaps, Sep 2019, Nijmegen, Netherlands. ⟨cea-02289470⟩

Share

Metrics

Record views

35

Files downloads

38