Biology subjects

Girard, S. L.

Publications and source records attributed to Girard, S. L..

7 recordsLinked to original sources

bioRxiv2025

Fine-scale structure of a whole regional population through genetics and genealogies

The Saguenay-Lac-Saint-Jean (SLSJ) region of Quebec, Canada, a population shaped by a prominent founder effect, has long been considered genetically homogeneous. This study comprehensively investigates the fine-scale population structure within SLSJ by integrating genotype data from the CARTaGENE cohort with extensive genealogical records from the BALSAC population register. A time-efficient algorithm was developed to compute billions of kinship coefficients from genealogies in order to analyse an entire generation. We demonstrate a striking concordance between realised (genetic) and expected (genealogical) kinship (r = 0.78). From both kinship measures, we reveal fine-scale population structure at the municipal level within SLSJ, challenging the notion of regional homogeneity. Our analysis highlights an east-west genetic gradient and uncovers migratory streams and differential founders genetic contributions that shaped the genetic landscape of this population. This research provides insights into the interplay of genetics, demography, and historical events, underscoring the importance of fine-scale population structure in genetic studies and reaffirming the power of large-scale genealogical data.

genetics↗

bioRxiv2024

Fine-scale genetic structure and rare variant frequencies

In response to the current challenge in genetic studies to make new associations, we advocate for a shift toward leveraging population fine-scale structure. Our exploration brings to light distinct fine-structure within populations having undergone a founder effect, challenging the prior perception of homogeneity. This underscores that smaller, but well-defined cohorts, demonstrate an important increase in rare variant frequencies, offering a promising avenue for new genetic variants discovery.

genomics↗

bioRxiv2022

Deciphering the genetic structure of the Quebec founder population using genealogies

Using genealogy to study the demographic history of a population makes it possible to overcome the models and assumptions often used in population genetics. The Quebec founder population is one of the few populations in the World having access to the complete genealogy of the last 400 years. The goal of this paper is to follow the evolution of the Quebec population structure generation per generation from the beginning of European colonization until the present day. To do so, we calculated the kinship coefficients of all ancestors pairs in the ascending genealogy of 665 individuals from eight regional and ethnocultural groups per 25-year period. We show that the Quebec population structure appeared in the St. Lawrence valley as early as 1750. At that time, the ancestors of two groups, the Sagueneans and the Acadians from the Gaspe Peninsula, experienced a marked increase in kinship and inbreeding levels which have shaped the contemporary population structure. Interestingly, this structure arose before the colonization of the Saguenay region and at the very beginning of the Gaspe Peninsula settlement. The resulting regional founder effects in these two groups, but also in the other regional groups, led to differences in the present-day identity-by-descent sharing and are directly linked to the number of most recent common ancestors and their genetic contribution to the studied subjects.

genetics↗

bioRxiv2020

Global prevalence of potentially pathogenic short-tandem repeats in an epilepsy cohort

This study aims to decipher the role of short tandem repeats (STRs) in epilepsy patients. Whole genome short-read sequencing data of 734 epileptic patients was used to look for known STR expansions associated with increased risk of neurodevelopmental diseases or epilepsy using three different software. Results show one hit of particular interest on ARX gene associated with Early Infantile Encephalopathic Epilepsy that could be causal for one patient with developmental and epileptic encephalopathy. However, we show that the different software do not agree on most of the calls above the threshold and that experimental validation is still needed for diagnostic, although these algorithms could prove useful for pre-selection of samples to be validated.

genetics↗

bioRxiv2019

Polygenic risk scores of several subtypes of epilepsies in a founder population

ImportanceEpilepsy is defined as a group of neurological disorders characterized by epileptic seizures, brief episodes of symptoms that are caused by abnormal or excessive neuronal activity in the brain. Epilepsy affects around 3 percent of individuals. In the past 10 years, many groups have been working to better understand the complex genetic mechanisms underlying epilepsy. Together, they studied many different genetic mechanisms, but there is still a substantial missing heritability component in epilepsy genetics.\n\nObjectiveHere, we used polygenic risk scores (PRS) to quantify the cumulative effects of a number of variants, which may individually have a very small effect on susceptibility.\n\nDesignWe calculated PRS in 522 French-Canadian epilepsy patients divided into seven subtypes and French-Canadian controls.\n\nSettingAll study participants (cases and controls) were selected based on their French-Canadian ancestry.\n\nParticipantsThe epilepsy cohort was composed of families of at least three affected individuals with Idiopathic Generalized Epilepsy (IGE) or Non-acquired Focal Epilepsy (NAFE) previously collected and diagnosed by neurologists following the International League Against Epilepsy (ILAE) criteria.\n\nExposuresAll samples were processed on a common genotyping array.\n\nMain outcomes and ResultsWe show that the area under the curve (AUC) is almost always slightly greater than 0.5, especially in patients with IGE and subtypes. We also looked at the association of the PRS with the different phenotypes using a linear mixed effects model estimated by generalized estimating equation (GEE) with the pairwise identity-by-descent (IBD) matrix as a random effect. P-values of GEE were consistent with AUC calculations.\n\nConclusions and RelevanceGlobally, we support the notion that PRS and SNP-based heritability provide reliable measures to rightfully estimate the contribution of genetic factors to the pathophysiological mechanism of epilepsies, but further studies are needed on PRS before they can be used clinically.

genetics↗

bioRxiv2019

Genome-wide estimates of heritability and genetic correlations in Essential Tremor

Despite considerable efforts to identify disease-causing and risk factors contributing to essential tremor (ET), no comprehensive assessment of heritable risk has been performed to date. We use GREML-LDMS to estimate narrow-sense heritability due to additive effects (h2) and GREMLd to calculate non-additive heritability due to dominance variance ({delta}2) using data from 1,748 ET cases and 5,302 controls. We evaluate heritability per 10Mb segments across the genome and assess the impact of Parkinsons disease (PD) misdiagnosis on heritability estimates. We apply genetic risk score (GRS) from PD and restless legs syndrome (RLS) to explore its contribution to ET risk and further assess genetic correlations with 832 traits by Linkage disequilibrium score regression. Our results show for the first time that ET is a highly heritable condition (h2=0.755, s.e=0.075) in which additive common variability plays a prominent role. In contrast, dominance variance shows insignificant effect on the overall estimates. Heritability split by 10Mb regions revealed increased estimates at chromosomes 6 and 21 suggesting that these may contain causative risk variants influencing susceptibility to ET. The proportion of genetic variance due to PD misdiagnosed cases was estimated to be 5.33%. PD and RLS GRS were not significantly predictive of ET case-control status demonstrating that despite overlapping symptomatology, ET does not seem to share genetic etiologies with PD or RLS. Our study suggests that most of ET genetic component is yet to be discovered and future GWAS will reveal additional risk factors that will improve our understanding of this disabling disorder.

genetics↗

bioRxiv2017

Genome-wide characterization of copy number variants in epilepsy patients

Epilepsy will affect nearly 3% of people at some point during their lifetime. Previous copy number variants (CNVs) studies of epilepsy have used array-based technology and were restricted to the detection of large or exonic events. In contrast, whole-genome sequencing (WGS) has the potential to more comprehensively profile CNVs but existing analytic methods suffer from limited accuracy. We show that this is in part due to the non-uniformity of read coverage, even after intra-sample normalization. To improve on this, we developed PopSV, an algorithm that uses multiple samples to control for technical variation and enables the robust detection of CNVs. Using WGS and PopSV, we performed a comprehensive characterization of CNVs in 198 individuals affected with epilepsy and 301 controls. For both large and small variants, we found an enrichment of rare exonic events in epilepsy patients, especially in genes with predicted loss-of-function intolerance. Notably, this genome-wide survey also revealed an enrichment of rare non-coding CNVs near previously known epilepsy genes. This enrichment was strongest for non-coding CNVs located within 100 Kbp of an epilepsy gene and in regions associated with changes in the gene expression, such as expression QTLs or DNase I hypersensitive sites. Finally, we report on 21 potentially damaging events that could be associated with known or new candidate epilepsy genes. Our results suggest that comprehensive sequence-based profiling of CNVs could help explain a larger fraction of epilepsy cases.\n\nAuthor summaryEpilepsy is a common neurological disorder affecting around 3% of the population. In some cases, epilepsy is caused by brain trauma or other brain anomalies but there are often no clear causes. Genetic factors have been associated with epilepsy in the past such as rare genetic variations found by linkage studies as well as common genetic variations found by genome-wide association studies and large copy-number variants. We sequenced the genome of[~] 200 epilepsy patients and[~] 300 healthy controls and compared the distribution of deletion (loss of a copy) and duplication (additional copy) of genomic regions. Thanks to the sequencing technology and a new method that takes advantage of the large sample size, we could compare the distribution of small copy- number variants between epilepsy patients and controls. Overall, we found that small variants are also associated with epilepsy. Indeed, the genome of epilepsy patients had more exonic copy- number variants, especially when rare or affecting genes with predicted loss-of-function intolerance. Focusing on regions around genes that have been previously associated with epilepsy, we also found more non-coding variants in epilepsy patients, especially deletions or variants in regulatory regions. Finally, we provide a list of 21 regions in which we found likely pathogenic variants.

genomics↗