Biology subjects

Mekki, Y. N.

Publications and source records attributed to Mekki, Y. N..

2 recordsLinked to original sources

bioRxiv2025

Polygenic Associations between Motor Behaviour, Neuromotor Traits, and Active Music Engagement in Four Cohorts

Phenotypic investigations have shown that actively engaging with music, i.e., playing a musical instrument or singing may be protective of motor decline in aging. For example, music training associated with enhanced sensorimotor skills accompanied by changes in brain structure and function. Although it is possible that the benefits of active music engagement "transfer" to benefits in the motor domain, it is also possible that the genetic architecture of motor behaviour and the motor system structure may influence active music engagement. This study investigated whether polygenic scores (PGS) for five behavioural motor traits, 12 neuromotor structural brain traits, and seven rates of change in brain structure traits trained from existing discovery genome-wide association studies (GWAS) predict active music engagement outcomes in four independent cohorts of unrelated individuals of European ancestry: the Canadian Longitudinal Study on Aging (CLSA; N=22,198), Wisconsin Longitudinal Study (WLS; N=4,605), Vanderbilts BioVU Repository (BioVU; N=6,150), and Vanderbilts Online Musicality study (OM; N=1,559). Results were meta-analyzed for each PGS main effect across outcomes and cohorts, revealing that PGS for a faster walking pace was associated with higher amounts of active music engagement. Within CLSA, a higher PGS for walking pace was associated with greater odds of engaging with music. Findings suggest a shared genetic architecture between motor function and active music engagement. Future intervention-based research should consider the genetic underpinnings of motor behavior when evaluating the effects of music engagement on motor function across the lifespan.

neuroscience↗

bioRxiv2021

The genetic architecture of language functional connectivity

Language is a unique trait of the human species, of which the genetic architecture remains largely unknown. Through language disorders studies, many candidate genes were identified. However, such complex and multifactorial trait is unlikely to be driven by only few genes and case-control studies, suffering from a lack of power, struggle to uncover significant variants. In parallel, neuroimaging has significantly contributed to the understanding of structural and functional aspects of language in the human brain and the recent availability of large scale cohorts like UK Biobank have made possible to study language via image-derived endophenotypes in the general population. Because of its strong relationship with task-based fMRI activations and its easiness of acquisition, resting-state functional MRI have been more popularised, making it a good surrogate of functional neuronal processes. Taking advantage of such a synergistic system by aggregating effects across spatially distributed traits, we performed a multivariate genome-wide association study (mvGWAS) between genetic variations and resting-state functional connectivity (FC) of classical brain language areas in the inferior frontal (pars opercularis, triangularis and orbitalis), temporal and inferior parietal lobes (angular and supramarginal gyri), in 32,186 participants from UK Biobank. Twenty genomic loci were found associated with language FCs, out of which three were replicated in an independent replication sample. A locus in 3p11.1, regulating EPHA3 gene expression, is found associated with FCs of the semantic component of the language network, while a locus in 15q14, regulating THBS1 gene expression is found associated with FCs of the perceptualmotor language processing, bringing novel insights into the neurobiology of language.

genetics↗