Publications by authors named "Lapierre N"

To identify genes involved in regulating the behavioral and brain transcriptomic response to the potentially addictive drug cocaine, we performed genome-wide association studies (GWASs) for intravenous self-administration of cocaine or saline (as a control) over 10 days using a panel of inbred and recombinant inbred mice. A linear mixed model increased statistical power for these longitudinal data and identified 145 loci for responding when saline only was delivered, compared to 17 for the corresponding cocaine GWAS. Only one locus overlapped.

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Knowing the genes involved in quantitative traits provides an entry point to understanding the biological bases of behavior, but there are very few examples where the pathway from genetic locus to behavioral change is known. To explore the role of specific genes in fear behavior, we mapped three fear-related traits, tested fourteen genes at six quantitative trait loci (QTLs) by quantitative complementation, and identified six genes. Four genes, Lamp, Ptprd, Nptx2, and Sh3gl, have known roles in synapse function; the fifth, Psip1, was not previously implicated in behavior; and the sixth is a long non-coding RNA, 4933413L06Rik, of unknown function.

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Background: People with disabilities (PWD) commonly experience difficulties in accessing their environments, which can lead to restricted participation in outdoor leisure-time physical activity. Participating in outdoor leisure-time physical activity (OLTPA) provides health and social benefits to PWD and benefits to the communities in which they live.

Objective: The aim of the study was to identify features existing in digital platforms that facilitate access to OLTPA for PWD.

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Methods for analyzing the full complement of a biomolecule type, e.g., proteomics or metabolomics, generate large amounts of complex data.

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Aim: During the COVID-19 pandemic, many community organizations offering services to people with disabilities (PWD) changed their service delivery, switching from in-person to remote services. However, little is known about what it was like for organizations to quickly pivot their service delivery. The study explored barriers and facilitators to access community services for PWD and identified potential improvements to these services.

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A core problem in genetics is molecular quantitative trait locus (QTL) mapping, in which genetic variants associated with changes in the molecular phenotypes are identified. One of the most-studied molecular QTL mapping problems is expression QTL (eQTL) mapping, in which the molecular phenotype is gene expression. It is common in eQTL mapping to compute gene expression by aggregating the expression levels of individual isoforms from the same gene and then performing linear regression between SNPs and this aggregated gene expression level.

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Knowing the genes involved in quantitative traits provides a critical entry point to understanding the biological bases of behavior, but there are very few examples where the pathway from genetic locus to behavioral change is known. Here we address a key step towards that goal by deploying a test that directly queries whether a gene mediates the effect of a quantitative trait locus (QTL). To explore the role of specific genes in fear behavior, we mapped three fear-related traits, tested fourteen genes at six QTLs, and identified six genes.

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To identify addiction genes, we evaluate intravenous self-administration of cocaine or saline in 84 inbred and recombinant inbred mouse strains over 10 days. We integrate the behavior data with brain RNA-seq data from 41 strains. The self-administration of cocaine and that of saline are genetically distinct.

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Mendelian randomization (MR) has emerged as a powerful approach to leverage genetic instruments to infer causality between pairs of traits in observational studies. However, the results of such studies are susceptible to biases owing to weak instruments, as well as the confounding effects of population stratification and horizontal pleiotropy. Here, we show that family data can be leveraged to design MR tests that are provably robust to confounding from population stratification, assortative mating, and dynastic effects.

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Municipalities and nonprofit organizations play a major role in administrating services that support individuals with disabilities. The purpose of this study was to explore how these organizations responded to the COVID-19 pandemic in regards to service delivery and programming for people with disabilities. This qualitative interpretative description study used semi-structured individual interviews for data collection.

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Mendelian Randomization (MR) has emerged as a powerful approach to leverage genetic instruments to infer causality between pairs of traits in observational studies. However, the results of such studies are susceptible to biases due to weak instruments as well as the confounding effects of population stratification and horizontal pleiotropy. Here, we show that family data can be leveraged to design MR tests that are provably robust to confounding from population stratification, assortative mating, and dynastic effects.

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Introduction: Exergaming is increasingly employed in rehabilitation for older adults. However, their effects on fall rate and fall risk remain unclear.

Methods: We conducted a systematic review and meta-analysis that included randomized controlled trials (RCTs) comparing exergame-assisted rehabilitation with control groups, published in French or English, from Web of Science, CINHAL, Embase, Medline, and CENTRAL (last search in June 2021).

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Community organisations and municipalities support people with disabilities by providing resources and services that are essential for their engagement in the community. Their services were particularly impacted by restrictions related to the COVID-19 pandemic. The aim of the study is to identify scientific literature that examines how community organisations and municipalities adapted services and resources provided to people with disabilities as a result of the COVID-19 pandemic.

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Purpose: To describe an artificial intelligence platform that detects thyroid eye disease (TED).

Design: Development of a deep learning model.

Methods: 1944 photographs from a clinical database were used to train a deep learning model.

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Article Synopsis
  • Evaluating metagenomic software is crucial for enhancing the interpretation of metagenomes, and the CAMI II challenge focused on this by using complex datasets from numerous genomes and plasmids.
  • The analysis of 5,002 results from 76 software versions showed significant advancements in assembly, especially with long-read data, although challenges remained with related strains and genome recovery.
  • Findings indicated that while taxon profilers improved, they struggled with viruses and Archaea, highlighting the need for better reproducibility in clinical pathogen detection and guiding researchers in method selection based on efficiency and performance metrics.
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Mendelian Randomization (MR) studies are threatened by population stratification, batch effects, and horizontal pleiotropy. Although a variety of methods have been proposed to mitigate those problems, residual biases may still remain, leading to highly statistically significant false positives in large databases. Here we describe a suite of sensitivity analysis tools that enables investigators to quantify the robustness of their findings against such validity threats.

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Background: Since the Covid-19 pandemic, many community-based services for people with traumatic brain injury (TBI) have been moved online, which may have hindered their accessibility. The study aims to assess the accessibility of online information and resources dedicated to people with TBI.

Methods: The websites of 14 organizations offering information and resources to people with TBI in Quebec were evaluated.

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Increasingly large Genome-Wide Association Studies (GWAS) have yielded numerous variants associated with many complex traits, motivating the development of "fine mapping" methods to identify which of the associated variants are causal. Additionally, GWAS of the same trait for different populations are increasingly available, raising the possibility of refining fine mapping results further by leveraging different linkage disequilibrium (LD) structures across studies. Here, we introduce multiple study causal variants identification in associated regions (MsCAVIAR), a method that extends the popular CAVIAR fine mapping framework to a multiple study setting using a random effects model.

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Background: Older adults often experience physical, sensory, and cognitive decline. Therefore, they have a high risk of falls, which leads to severe health and psychological consequences and can induce fear of falling. Rehabilitation programs using exergames to prevent falls are being increasingly studied.

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Frequent and widespread testing of members of the population who are asymptomatic for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is essential for the mitigation of the transmission of the virus. Despite the recent increases in testing capacity, tests based on quantitative polymerase chain reaction (qPCR) assays cannot be easily deployed at the scale required for population-wide screening. Here, we show that next-generation sequencing of pooled samples tagged with sample-specific molecular barcodes enables the testing of thousands of nasal or saliva samples for SARS-CoV-2 RNA in a single run without the need for RNA extraction.

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Introduction: In the U.S., children regularly consume foods from quick-service restaurants, but little is known about the marketing strategies currently used inside quick-service restaurants.

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Background: The COVID-19 pandemic has drastically changed the lives of countless members of the general population. Older adults are known to experience loneliness, age discrimination, and excessive worry. It is therefore reasonable to anticipate that they would experience greater negative outcomes related to the COVID-19 pandemic given their increased isolation and risk for complications than younger adults.

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Metagenomic profiling, predicting the presence and relative abundances of microbes in a sample, is a critical first step in microbiome analysis. Alignment-based approaches are often considered accurate yet computationally infeasible. Here, we present a novel method, Metalign, that performs efficient and accurate alignment-based metagenomic profiling.

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The rapid spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is due to the high rates of transmission by individuals who are asymptomatic at the time of transmission. Frequent, widespread testing of the asymptomatic population for SARS-CoV-2 is essential to suppress viral transmission. Despite increases in testing capacity, multiple challenges remain in deploying traditional reverse transcription and quantitative PCR (RT-qPCR) tests at the scale required for population screening of asymptomatic individuals.

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