Biology subjects

Le Guen, Y.

Publications and source records attributed to Le Guen, Y..

3 recordsLinked to original sources

bioRxiv2018

Shared genetic aetiology between cognitive performance and brain activations in language and math tasks

Cognitive performance is highly heritable. However, little is known about common genetic influences on cognitive ability and brain activation when engaged in a cognitive task. The Human Connectome Project (HCP) offers a unique opportunity to study this shared genetic etiology with an extended pedigree of 785 individuals. To investigate this common genetic origin, we took advantage of the HCP dataset, which includes both language and mathematics activation tasks. Using the HCP multimodal parcellation, we identified areals in which inter-individual functional MRI (fMRI) activation variance was significantly explained by genetics. Then, we performed bivariate genetic analyses between the neural activations and behavioral scores, corresponding to the fMRI task accuracies, fluid intelligence, working memory and language performance. We observed that several parts of the language network along the superior temporal sulcus, as well as the angular gyrus belonging to the math processing network, are significantly genetically correlated with these indicators of cognitive performance. This shared genetic etiology provides insights into the brain areas where the human-specific genetic repertoire is expressed. Studying the association of polygenic risk scores, using variants associated with human cognitive ability and brain activation, would provide an opportunity to better understand where these variants are influential.

neuroscience↗

bioRxiv2018

eQTL of KCNK2 regionally influences the brain sulcal widening: evidence from 15,597 UK Biobank participants with neuroimaging data

The grey and white matter volumes are known to reduce with age. This cortical shrinkage is visible on magnetic resonance images and is conveniently identified by the increased volume of cerebrospinal fluid in the sulci between two gyri. Here, we replicated this finding using the UK Biobank dataset and studied the genetic influence on these cortical features of aging. We divided all individuals genetically confirmed of British ancestry into two sub-cohorts (12,162 and 3,435 subjects for discovery and replication samples, respectively). We found that the heritability of the sulcal opening ranges from 15 to 45% (s.e.= 4.8%). We identified 4 new loci that contribute to this opening, including one that also affects the sulci grey matter thickness. We identified the most significant variant (rs864736) on this locus as being an expression quantitative trait locus (eQTL) for the KCNK2 gene. This gene regulates the immune-cell into the central nervous system (CNS) and controls the CNS inflammation, which is implicated in cortical atrophy and cognitive decline. These results expand our knowledge of the genetic contribution to cortical shrinking and promote further investigation into these variants and genes in pathological context such as Alzheimers disease in which brain shrinkage is a key biomarker.

genetics↗

bioRxiv2017

Multiscale simulation of peripheral neural signaling

Bioelectronic Medicines that modulate the activity patterns on peripheral nerves have promise as a new way of treating diverse medical conditions from epilepsy to rheumatism. Progress in the field builds upon time consuming and expensive experiments in living organisms to evaluate spontaneous activity patterns, stimulation efficiency, and organ responses. To reduce experimentation load and allow for a faster, more detailed analysis of both recording from and stimulation of peripheral nerves, adaptable computational models incorporating insights won in experiments will be of great help. We present a peripheral nerve simulator that combines biophysical axon models and numerically solved and idealized extracellular space models in one environment. Two different scales of abstraction were merged. On the one hand we modeled the extracellular space in a finite element solver as a three dimensional resistive continuum governed by the electro-quasistatic approximation of the Maxwell equations. Potential distributions were precomputed for different media (homogeneous, nerve in saline, nerve in cuff). Axons, on the other hand, were modeled at a higher level of abstraction as one dimensional chains of compartments; each consisting of lumped linear elements and, for some, channels with non-linear dynamics. Unmyelinated fibres were based on the Hodgkin-Huxley model; for myelinated fibers, we instead adapted the model proposed by McIntyre et al. in 2002 to smaller diameters. To obtain realistic axon shapes, an iterative algorithm positioned fibers along the nerve with variable tortuosity, with tortuosity values fit to imaged trajectories. We validated our model with data from the stimulated rat vagus nerve. Simulation results predicted that tortuosity leads to differentiation in recorded signal shapes, with unmyelinated axons being the most affected. Tortuosity was further shown to increase the stimulation threshold. The model we developed can easily be adapted to different nerves, and may be of use for Bioelectronic Medicine research in the future.

neuroscience↗