Publications by authors named "Aurélie Labbe"

76 Publications

Massive GNSS data for road safety analysis: Comparing crash models for several Canadian cities and data sources.

Accid Anal Prev 2021 Sep 26;159:106232. Epub 2021 Jun 26.

Department of Civil Engineering and Applied Mechanics, McGill University, Room 268, Macdonald Engineering Building, 817 Sherbrooke Street West, Montréal, Québec H3A 0C3, Canada; Interuniversity Research Centre on Enterprise Networks, Logistics and Transportation (CIRRELT) Pavillon André Aisenstadt, Room 3520 2920 Chemin de la Tour Université de Montréal, Montréal, Quebec H3T 1J4, Canada. Electronic address:

Mobile sensors are a useful data source with applications in several transportation fields. Though cost of collection, transmission, and storage has limited studies on driving data and safety, this can be overcome through usage-based insurance (UBI). In UBI programs, drivers are monitored, and their premiums are adjusted based on driver-level surrogate safety measures (SSMs) related to exposure and driving style. Contextual link-level SSMs (volume, speed, or density) could further improve discount calibration. This study quantifies relationships between contextual SSMs and crashes and includes the validation of previous results (correlations between SSMs and crashes and statistical models estimated using smartphone-collected data from Quebec City) and the comparison of three Canadian cities (using UBI data from Quebec City, Montreal, and Ottawa). Extracted SSMs were compared to large volumes of historical crash frequency data using Spearman's Rank Correlation Coefficient and then implemented into spatial Bayesian crash models. Results from the UBI data generally matched those from the previous study, with observed correlations mirroring previous results in direction (braking, congestion, and speed variation are positively associated with crash frequency while mean speed is negatively associated) while correlation strength was slightly higher. Furthermore, these results were consistent between cities. For the crash modelling, repeatability of previous results in Quebec City was moderately good for the UBI data. Importantly for large-scale implementation, models estimated using UBI data were largely consistent between cities. This work provides an important contribution to the existing literature, clearly demonstrating how contextual safety measures could be applied to benefit UBI practices.
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http://dx.doi.org/10.1016/j.aap.2021.106232DOI Listing
September 2021

Evaluating safety-influencing factors at stop-controlled intersections using automated video analysis.

J Safety Res 2021 06 24;77:311-323. Epub 2021 Mar 24.

Department of Civil Engineering and Applied Mechanics, McGill University, Room 268, Macdonald Engineering Building, 817 Sherbrooke Street West, Montréal, Québec H3A 0C3, Canada. Electronic address:

Introduction: Although stop signs are popular in North America, they have become controversial in cities like Montreal, Canada where they are often installed to reduce vehicular speeds and improve pedestrian safety despite limited evidence demonstrating their effectiveness. The purpose of this study is to evaluate the impact of stop-control configuration (and other features) on safety using statistical models and surrogate measures of safety (SMoS), namely vehicle speed, time-to-collision (TTC), and post-encroachment time (PET), while controlling for features of traffic, geometry, and built environment.

Methods: This project leverages high-resolution user trajectories extracted from video data collected for 100 intersections, 336 approaches, and 130,000 road users in Montreal to develop linear mixed-effects regression models to account for within-site and within-approach correlations. This research proposes the Intersection Exposure Group (IEG) indicator, an original method for classifying microscopic exposure of pedestrians and vehicles.

Results: Stop signs were associated with an average decrease in approach speed of 17.2 km/h and 20.1 km/h, at partially and fully stop-controlled respectively. Cyclist or pedestrian presence also significantly lower vehicle speeds. The proposed IEG measure was shown to successfully distinguish various types of pedestrian-vehicle interactions, allowing for the effect of each interaction type to vary in the model.

Conclusions: The presence of stop signs significantly reduced approach speeds compared to uncontrolled approaches. Though several covariates were significantly related to TTC and PET for vehicle pairs, the models were unable to demonstrate a significant relationship between stop signs and vehicle-pedestrian interactions. Therefore, drawing conclusions regarding pedestrian safety is difficult. Practical Applications: As pedestrian safety is frequently used to justify new stop sign installations, this result has important policy implications. Policies implementing stop signs to reduce pedestrian crashes may be less effective than other interventions. Enforcement and education efforts, along with geometric design considerations, should accompany any changes in traffic control.
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http://dx.doi.org/10.1016/j.jsr.2021.03.006DOI Listing
June 2021

Maturational trajectories of pericortical contrast in typical brain development.

Neuroimage 2021 07 22;235:117974. Epub 2021 Mar 22.

Montreal Neurological Institute, McGill University, 3801 Rue University, Montréal, QC H3A 2B4, Canada; Douglas Institute, McGill University, 6875 Boulevard LaSalle, Verdun, QC H4H 1R3, Canada. Electronic address:

In the last few years, a significant amount of work has aimed to characterize maturational trajectories of cortical development. The role of pericortical microstructure putatively characterized as the gray-white matter contrast (GWC) at the pericortical gray-white matter boundary and its relationship to more traditional morphological measures of cortical morphometry has emerged as a means to examine finer grained neuroanatomical underpinnings of cortical changes. In this work, we characterize the GWC developmental trajectories in a representative sample (n = 394) of children and adolescents (~4 to ~22 years of age), with repeated scans (1-3 scans per subject, total scans n = 819). We tested whether linear, quadratic, or cubic trajectories of contrast development best described changes in GWC. A best-fit model was identified vertex-wise across the whole cortex via the Akaike Information Criterion (AIC). GWC across nearly the whole brain was found to significantly change with age. Cubic trajectories were likeliest for 63% of vertices, quadratic trajectories were likeliest for 20% of vertices, and linear trajectories were likeliest for 16% of vertices. A main effect of sex was observed in some regions, where males had a higher GWC than females. However, no sex by age interactions were found on GWC. In summary, our results suggest a progressive decrease in GWC at the pericortical boundary throughout childhood and adolescence. This work contributes to efforts seeking to characterize typical, healthy brain development and, by extension, can help elucidate aberrant developmental trajectories.
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http://dx.doi.org/10.1016/j.neuroimage.2021.117974DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8278832PMC
July 2021

Machine Learning-Based Individualized Survival Prediction Model for Total Knee Replacement in Osteoarthritis: Data From the Osteoarthritis Initiative.

Arthritis Care Res (Hoboken) 2021 Mar 21. Epub 2021 Mar 21.

Laval University Hospital Research Centre, Quebec, Canada.

Objective: By using machine learning, our study aimed to build a model to predict risk and time to total knee replacement (TKR) of an osteoarthritic knee.

Methods: Features were from the Osteoarthritis Initiative (OAI) cohort at baseline. Using the lasso method for variable selection in the Cox regression model, we identified the 10 most important characteristics among 1,107 features. The prognostic power of the selected features was assessed by the Kaplan-Meier method and applied to 7 machine learning methods: Cox, DeepSurv, random forests algorithm, linear/kernel support vector machine (SVM), and linear/neural multi-task logistic regression models. As some of the 10 first-found features included similar radiographic measurements, we further looked at using the least number of features without compromising the accuracy of the model. Prediction performance was assessed by the concordance index, Brier score, and time-dependent area under the curve (AUC).

Results: Ten features were identified and included radiographs, bone marrow lesions of the medial condyle on magnetic resonance imaging, hyaluronic acid injection, performance measure, medical history, and knee-related symptoms. The methodologies Cox, DeepSurv, and linear SVM demonstrated the highest accuracy (concordance index scores of 0.85, Brier score of 0.02, and an AUC of 0.87). DeepSurv was chosen to build the prediction model to estimate the time to TKR for a given knee. Moreover, we were able to decrease the features to only 3 and maintain the high accuracy (concordance index of 0.85, Brier score of 0.02, and AUC of 0.86), which included bone marrow lesions, Kellgren/Lawrence grade, and knee-related symptoms, to predict risk and time of a TKR event.

Conclusion: For the first time, we developed a model using the OAI cohort to predict with high accuracy if a given osteoarthritic knee would require TKR, when a TKR would be required, and who would likely progress fast toward this event.
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http://dx.doi.org/10.1002/acr.24601DOI Listing
March 2021

Conditional canonical correlation estimation based on covariates with random forests.

Bioinformatics 2021 Mar 8. Epub 2021 Mar 8.

Department of Decision Sciences, HEC Montréal, Montréal, QC H3T 2A7, Canada.

Motivation: Investigating the relationships between two sets of variables helps to understand their interactions and can be done with canonical correlation analysis (CCA). However, the correlation between the two sets can sometimes depend on a third set of covariates, often subject-related ones such as age, gender, or other clinical measures. In this case, applying CCA to the whole population is not optimal and methods to estimate conditional CCA, given the covariates, can be useful.

Results: We propose a new method called Random Forest with Canonical Correlation Analysis (RFCCA) to estimate the conditional canonical correlations between two sets of variables given subject-related covariates. The individual trees in the forest are built with a splitting rule specifically designed to partition the data to maximize the canonical correlation heterogeneity between child nodes. We also propose a significance test to detect the global effect of the covariates on the relationship between two sets of variables. The performance of the proposed method and the global significance test is evaluated through simulation studies that show it provides accurate canonical correlation estimations and well-controlled Type-1 error. We also show an application of the proposed method with EEG data.

Availability: RFCCA is implemented in a freely available R package on CRAN (https://CRAN.R-project.org/package=RFCCA).

Supplementary Information: Supplementary material are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btab158DOI Listing
March 2021

Sex-dependent complex association of TPH2 with multiple dimensions of ADHD.

Prog Neuropsychopharmacol Biol Psychiatry 2021 Aug 4;110:110296. Epub 2021 Mar 4.

Douglas Mental Health University Institute, Montreal, Quebec, Canada; Department of Human Genetics, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada. Electronic address:

Background: Tryptophan hydroxylase 2 (TPH2) is a key enzyme in the biosynthesis of serotonin in the brain. This study aims to investigate the role of a functional variant in TPH2 (rs17110747) in the pathophysiology of ADHD. This variant has been implicated in mood disorders in recent meta-analysis. This study uses a comprehensive approach that combines association testing and pharmaco-dynamic evaluation of behaviour, in a large sample of children with ADHD (n = 570).

Methods: The association between various ADHD relevant traits and rs17110747 was analyzed using family-based association tests (FBAT). Children were assessed by parents, teachers and research staff under three experimental conditions (EC): baseline, placebo, and methylphenidate using a double-blind placebo-controlled crossover trial.

Outcomes: FBAT analysis conducted in a sample stratified based on sex of the proband, showed that there was a highly significant overtransmission of the G allele from parents to affected girls. In addition, significant association with several behavioral and cognitive dimensions of ADHD was observed only when the proband was female. Further, girls with the G/G genotype (rs17110747) had greater response to placebo when evaluated by parents.

Interpretation: These results suggest that there may be a complex association of TPH2 in the etiology of ADHD, with a sex-specific effect.
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http://dx.doi.org/10.1016/j.pnpbp.2021.110296DOI Listing
August 2021

Association between COMT methylation and response to treatment in children with ADHD.

J Psychiatr Res 2021 03 7;135:86-93. Epub 2021 Jan 7.

Douglas Mental Health University Institute, Montreal, Quebec, Canada; Department of Human Genetics, McGill University, Montreal, Quebec, Canada; Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada. Electronic address:

Background: COMT had been considered a promising candidate gene in pharmacogenetic studies in ADHD; yet the findings from these studies have been inconsistent. Part of these inconsistencies could be related to epigenetic mechanisms (including DNA methylation). Here we investigated the role of genetic variants of the COMT gene on the methylation levels of CpG sites in the same gene and explored the effect of methylation on methylphenidate (MPH) and placebo (PBO) response in children with ADHD.

Methods: Two hundred and thirty children with ADHD (6-12 years) participated in a randomized, double-blind, placebo-controlled crossover trial with MPH. Univariate analysis was performed to examine the associations between genotypes in the COMT gene and DNA methylation in the same genetic loci. Association between the DNA methylation of 11 CpG sites and PBO/MPH responses were then assessed using spearman's correlation analysis in 212 children. Multiple linear regression analyses were performed to test the interaction between these factors while accounting for sex.

Results: Associations were observed between specific genetic variants and methylation level of cg20709110. Homozygous genotypes of GG (rs6269), CC (rs4633), GG (rs4818), Val/Val (rs4680) and the haplotype (ACCVal/GCGVal) were significantly associated with higher level of methylation. This CpG showed a significant correlation with placebo response (r = -0.15, P = 0.045) according to the teachers' evaluation, and a close-to significance correlation with response to MPH according to parents' evaluation (r = -0.134, p = 0.051). Regression analysis showed that in the model including rs4818, sex and DNA methylation of cg20709110 contributed significantly to treatment response.

Conclusions: These preliminary results could provide evidence for the effect of genetic variations on methylation level and the involvement of the epigenetic variation of COMT loci in modulating the response to treatment in ADHD.

Trial Registration: clinicaltrials.gov, number NCT00483106.
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http://dx.doi.org/10.1016/j.jpsychires.2021.01.008DOI Listing
March 2021

Genome-wide analysis of gene dosage in 24,092 individuals estimates that 10,000 genes modulate cognitive ability.

Mol Psychiatry 2021 Jun 7;26(6):2663-2676. Epub 2021 Jan 7.

The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada.

Genomic copy number variants (CNVs) are routinely identified and reported back to patients with neuropsychiatric disorders, but their quantitative effects on essential traits such as cognitive ability are poorly documented. We have recently shown that the effect size of deletions on cognitive ability can be statistically predicted using measures of intolerance to haploinsufficiency. However, the effect sizes of duplications remain unknown. It is also unknown if the effect of multigenic CNVs are driven by a few genes intolerant to haploinsufficiency or distributed across tolerant genes as well. Here, we identified all CNVs > 50 kilobases in 24,092 individuals from unselected and autism cohorts with assessments of general intelligence. Statistical models used measures of intolerance to haploinsufficiency of genes included in CNVs to predict their effect size on intelligence. Intolerant genes decrease general intelligence by 0.8 and 2.6 points of intelligence quotient when duplicated or deleted, respectively. Effect sizes showed no heterogeneity across cohorts. Validation analyses demonstrated that models could predict CNV effect sizes with 78% accuracy. Data on the inheritance of 27,766 CNVs showed that deletions and duplications with the same effect size on intelligence occur de novo at the same frequency. We estimated that around 10,000 intolerant and tolerant genes negatively affect intelligence when deleted, and less than 2% have large effect sizes. Genes encompassed in CNVs were not enriched in any GOterms but gene regulation and brain expression were GOterms overrepresented in the intolerant subgroup. Such pervasive effects on cognition may be related to emergent properties of the genome not restricted to a limited number of biological pathways.
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http://dx.doi.org/10.1038/s41380-020-00985-zDOI Listing
June 2021

Stage-specific links between plasma neurofilament light and imaging biomarkers of Alzheimer's disease.

Brain 2020 12;143(12):3793-3804

Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.

Neurofilament light (NfL) is a marker of neuroaxonal injury, a prominent feature of Alzheimer's disease. It remains uncertain, however, how it relates to amyloid and tau pathology or neurodegeneration across the Alzheimer's disease continuum. The aim of this study was to investigate how plasma NfL relates to amyloid and tau PET and MRI measures of brain atrophy in participants with and without cognitive impairment. We retrospectively examined the association between plasma NfL and MRI measures of grey/white matter volumes in the Alzheimer's Disease Neuroimaging Initiative [ADNI: n = 1149; 382 cognitively unimpaired control subjects and 767 cognitively impaired participants (mild cognitive impairment n = 420, Alzheimer's disease dementia n = 347)]. Longitudinal plasma NfL was measured using single molecule array (Simoa) technology. Cross-sectional associations between plasma NfL and PET amyloid and tau measures were independently assessed in two cohorts: ADNI [n = 198; 110 cognitively unimpaired, 88 cognitively impaired (MCI n = 67, Alzheimer's disease dementia n = 21), data accessed October 2018]; and Translational Biomarkers in Aging and Dementia [TRIAD, n = 116; 74 cognitively unimpaired, 42 cognitively impaired (MCI n = 16, Alzheimer's disease dementia n = 26), data obtained November 2017 to January 2019]. Associations between plasma NfL and imaging-derived measures were examined voxel-wise using linear regression (cross-sectional) and linear mixed effect models (longitudinal). Cross-sectional analyses in both cohorts showed that plasma NfL was associated with PET findings in brain regions typically affected by Alzheimer's disease; associations were specific to amyloid PET in cognitively unimpaired and tau PET in cognitively impaired (P < 0.05). Longitudinal analyses showed that NfL levels were associated with grey/white matter volume loss; grey matter atrophy in cognitively unimpaired was specific to APOE ε4 carriers (P < 0.05). These findings suggest that plasma NfL increases in response to amyloid-related neuronal injury in preclinical stages of Alzheimer's disease, but is related to tau-mediated neurodegeneration in symptomatic patients. As such, plasma NfL may a useful measure to monitor effects in disease-modifying drug trials.
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http://dx.doi.org/10.1093/brain/awaa342DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7805809PMC
December 2020

Mutations associated with neuropsychiatric conditions delineate functional brain connectivity dimensions contributing to autism and schizophrenia.

Nat Commun 2020 10 19;11(1):5272. Epub 2020 Oct 19.

Sainte Justine Hospital Research Center, University of Montreal, 3175 Chemin de la Côte-Sainte-Catherine, Montreal, QC, H3T 1C5, Canada.

16p11.2 and 22q11.2 Copy Number Variants (CNVs) confer high risk for Autism Spectrum Disorder (ASD), schizophrenia (SZ), and Attention-Deficit-Hyperactivity-Disorder (ADHD), but their impact on functional connectivity (FC) remains unclear. Here we report an analysis of resting-state FC using magnetic resonance imaging data from 101 CNV carriers, 755 individuals with idiopathic ASD, SZ, or ADHD and 1,072 controls. We characterize CNV FC-signatures and use them to identify dimensions contributing to complex idiopathic conditions. CNVs have large mirror effects on FC at the global and regional level. Thalamus, somatomotor, and posterior insula regions play a critical role in dysconnectivity shared across deletions, duplications, idiopathic ASD, SZ but not ADHD. Individuals with higher similarity to deletion FC-signatures exhibit worse cognitive and behavioral symptoms. Deletion similarities identified at the connectivity level could be related to the redundant associations observed genome-wide between gene expression spatial patterns and FC-signatures. Results may explain why many CNVs affect a similar range of neuropsychiatric symptoms.
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http://dx.doi.org/10.1038/s41467-020-18997-2DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7573583PMC
October 2020

Effect Sizes of Deletions and Duplications on Autism Risk Across the Genome.

Am J Psychiatry 2021 01 11;178(1):87-98. Epub 2020 Sep 11.

Université de Montréal, Montreal (Douard, Zeribi, Schramm, Tamer, Loum, Nowak, Lord, Moreau, Huguet, Jacquemont); UHC Sainte-Justine Research Center, Montreal (Douard, Zeribi, Schramm, Tamer, Loum, Nowak, Saci, Lord, Rodríguez-Herreros, Jean-Louis, Moreau, Huguet, Jacquemont); Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal (Schramm, Greenwood); Sensory-Motor Laboratory, Jules-Gonin Eye Hospital, University of Lausanne, Lausanne, Switzerland (Rodríguez-Herreros); Department of Forensic and Neurodevelopmental Sciences (Loth) and Center for Population Neuroscience and Stratified Medicine (Schumann), Institute of Psychiatry, Psychology, and Neuroscience, King's College London; Hospital for Sick Children and Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto (Pausova); Departments of Neurology and Neurosurgery, Montreal Neurological Institute and Hospital, McGill University, Montreal (Elsabbagh); Department of Biomedical and Health Informatics, Children's Hospital of Philadelphia, Philadelphia, and Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia (Almasy); Department of Psychiatry, Boston Children's Hospital and Harvard Medical School, Boston (Glahn); Human Genetics and Cognitive Functions, Institut Pasteur, Université de Paris, Paris (Bourgeron); Département de Sciences de la Décision, HEC Montreal, Montreal (Labbe); Bloorview Research Institute, Holland Bloorview Kids Rehabilitation Hospital, Toronto (Paus); Departments of Psychology and Psychiatry, University of Toronto, Toronto (Paus); Centre de Recherche de CIUSSS-NIM, Montreal (Mottron); Département de Psychiatrie, Université de Montréal, Montreal (Mottron); Department of Epidemiology, Biostatistics, and Occupational Health, Gerald Bronfman Department of Oncology, and Department of Human Genetics, McGill University, Montreal (Greenwood).

Objective: Deleterious copy number variants (CNVs) are identified in up to 20% of individuals with autism. However, levels of autism risk conferred by most rare CNVs remain unknown. The authors recently developed statistical models to estimate the effect size on IQ of all CNVs, including undocumented ones. In this study, the authors extended this model to autism susceptibility.

Methods: The authors identified CNVs in two autism populations (Simons Simplex Collection and MSSNG) and two unselected populations (IMAGEN and Saguenay Youth Study). Statistical models were used to test nine quantitative variables associated with genes encompassed in CNVs to explain their effects on IQ, autism susceptibility, and behavioral domains.

Results: The "probability of being loss-of-function intolerant" (pLI) best explains the effect of CNVs on IQ and autism risk. Deleting 1 point of pLI decreases IQ by 2.6 points in autism and unselected populations. The effect of duplications on IQ is threefold smaller. Autism susceptibility increases when deleting or duplicating any point of pLI. This is true for individuals with high or low IQ and after removing de novo and known recurrent neuropsychiatric CNVs. When CNV effects on IQ are accounted for, autism susceptibility remains mostly unchanged for duplications but decreases for deletions. Model estimates for autism risk overlap with previously published observations. Deletions and duplications differentially affect social communication, behavior, and phonological memory, whereas both equally affect motor skills.

Conclusions: Autism risk conferred by duplications is less influenced by IQ compared with deletions. The model applied in this study, trained on CNVs encompassing >4,500 genes, suggests highly polygenic properties of gene dosage with respect to autism risk and IQ loss. These models will help to interpret CNVs identified in the clinic.
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http://dx.doi.org/10.1176/appi.ajp.2020.19080834DOI Listing
January 2021

Identification of the most important features of knee osteoarthritis structural progressors using machine learning methods.

Ther Adv Musculoskelet Dis 2020 13;12:1759720X20933468. Epub 2020 Aug 13.

Osteoarthritis Research Unit, University of Montreal Hospital Research Centre (CRCHUM), 900 Saint-Denis, Suite R11.412, Montreal, Quebec H2X 0A9, Canada.

Objectives: The aim was to identify the most important features of structural knee osteoarthritis (OA) progressors and classification using machine learning methods.

Methods: Participants, features and outcomes were from the Osteoarthritis Initiative. Features were from baseline (1107), including articular knee tissues (135) assessed by quantitative magnetic resonance imaging (MRI). OA progressors were ascertained by four outcomes: cartilage volume loss in medial plateau at 48 and 96 months (Prop_CV_48M, 96M), Kellgren-Lawrence (KL) grade ⩾ 2 and medial joint space narrowing (JSN) ⩾ 1 at 48 months. Six feature selection models were used to identify the common features in each outcome. Six classification methods were applied to measure the accuracy of the selected features in classifying the subjects into progressors and non-progressors. Classification of the best features was done using an automatic machine learning interface and the area under the curve (AUC). To prioritize the top five features, sparse partial least square (sPLS) method was used.

Results: For the classification of the best common features in each outcome, Multi-Layer Perceptron (MLP) achieved the highest AUC in Prop_CV_96M, KL and JSN (0.80, 0.88, 0.95), and Gradient Boosting Machine for Prop_CV_48M (0.70). sPLS showed the baseline top five features to predict knee OA progressors are the joint space width, mean cartilage thickness of the medial tibial plateau and sub-regions and JSN.

Conclusion: In this comprehensive study using a large number of features ( = 1107) and MRI outcomes in addition to radiological outcomes, we identified the best features and classification methods for knee OA structural progressors. Data revealed baseline X-ray and MRI-based features could predict early OA knee progressors and that MLP is the best classification method.
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http://dx.doi.org/10.1177/1759720X20933468DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7427139PMC
August 2020

A novel statistical method for modeling covariate effects in bisulfite sequencing derived measures of DNA methylation.

Biometrics 2021 06 5;77(2):424-438. Epub 2020 Jun 5.

Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC, Canada.

Identifying disease-associated changes in DNA methylation can help us gain a better understanding of disease etiology. Bisulfite sequencing allows the generation of high-throughput methylation profiles at single-base resolution of DNA. However, optimally modeling and analyzing these sparse and discrete sequencing data is still very challenging due to variable read depth, missing data patterns, long-range correlations, data errors, and confounding from cell type mixtures. We propose a regression-based hierarchical model that allows covariate effects to vary smoothly along genomic positions and we have built a specialized EM algorithm, which explicitly allows for experimental errors and cell type mixtures, to make inference about smooth covariate effects in the model. Simulations show that the proposed method provides accurate estimates of covariate effects and captures the major underlying methylation patterns with excellent power. We also apply our method to analyze data from rheumatoid arthritis patients and controls. The method has been implemented in R package SOMNiBUS.
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http://dx.doi.org/10.1111/biom.13307DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8359306PMC
June 2021

Methylation of the OXTR gene in women with anorexia nervosa: Relationship to social behavior.

Eur Eat Disord Rev 2020 01 10;28(1):79-86. Epub 2019 Dec 10.

Eating Disorders Continuum, Douglas Mental Health University Institute, Montreal West Island Integrated University Health & Social Service Centre (IUHSSC), Montreal, Quebec, Canada.

DNA methylation allows for the environmental regulation of gene expression and is believed to link environmental stressors to psychiatric disorder phenotypes, such as anorexia nervosa (AN). The oxytocin receptor (OXTR) gene is epigenetically regulated, and studies have shown associations between OXTR and social behaviours in various samples, including women with AN. The present study examined differential levels of methylation at various CG sites of the OXTR gene in 69 women with active AN (AN-Active), 21 in whom AN was in remission (AN-Rem) and 35 with no eating disorder (NED). Within each group, we explored the correlation between methylation and measures of social behaviour such as insecure attachment and social avoidance. Hypermethylation of a number of CG sites was seen in AN-Active participants as compared with AN-Rem and NED participants. In the AN-Rem sample, methylation at CG27501759 was significantly positively correlated with insecure attachment (r = .614, p = .003, permutation Q = 0.008) and social avoidance (r = .588, p = .005, permutation Q = 0.0184). Our results highlight differential methylation of the OXTR gene among women with AN, those in remission from AN, and those who never had AN and provide some evidence of associations between OXTR methylation and social behaviour in women remitted from AN.
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http://dx.doi.org/10.1002/erv.2703DOI Listing
January 2020

Pedestrian safety at signalized intersections: Modelling spatial effects of exposure, geometry and signalization on a large urban network.

Accid Anal Prev 2020 Jan 5;134:105265. Epub 2019 Nov 5.

Department of Decision Sciences, HEC Montréal, 3000 Chemin de la Côte-Sainte-Catherine, Montréal, Québec, H3T 2A7, Canada. Electronic address:

Intersections represent the most dangerous sites in the road network for pedestrians: not only is modal separation often impossible, but elements of geometry, traffic control, and built environment further exacerbate crash risk. Evaluating the safety impact of intersection features requires methods to quantify relationships between different factors and pedestrian injuries. The purpose of this paper is to model the effects of exposure, geometry, and signalization on pedestrian injuries at urban signalized intersections using a Full Bayes spatial Poisson Log-Normal model that accounts for unobserved heterogeneity and spatial correlation. Using the Integrated Nested Laplace Approximation (INLA) technique, this work leverages a rich database of geometric and signalization variables for 1864 intersections in Montreal, Quebec. To collect exposure data, short-term pedestrian and vehicle counts were extrapolated to AADT using developed expansion factors. Results of the model confirmed the positive relationship between pedestrian and vehicle volumes and pedestrian injuries. Curb extensions, raised medians, and exclusive left turn lanes were all found to reduce pedestrian injuries, while the total number of lanes and the number of commercial entrances were found to increase them. Pedestrian priority phases reduced injuries while the green straight arrow increased injuries. Lastly, the posterior expected number of crashes was used to identify hotspots. The proposed ranking criteria identified many intersections close to the city centre where the expected number of crashes is highest and intersections along arterials with lower pedestrian volumes where individual pedestrian risk is elevated. Understanding the effects of intersection geometry and pedestrian signalization will aid in ensuring the safety of pedestrians at signalized intersections.
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http://dx.doi.org/10.1016/j.aap.2019.105265DOI Listing
January 2020

MDiNE: a model to estimate differential co-occurrence networks in microbiome studies.

Bioinformatics 2020 03;36(6):1840-1847

Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montréal, QC, Canada.

Motivation: The human microbiota is the collection of microorganisms colonizing the human body, and plays an integral part in human health. A growing trend in microbiome analysis is to construct a network to estimate the co-occurrence patterns among taxa through precision matrices. Existing methods do not facilitate investigation into how these networks change with respect to covariates.

Results: We propose a new model called Microbiome Differential Network Estimation (MDiNE) to estimate network changes with respect to a binary covariate. The counts of individual taxa in the samples are modeled through a multinomial distribution whose probabilities depend on a latent Gaussian random variable. A sparse precision matrix over all the latent terms determines the co-occurrence network among taxa. The model fit is obtained and evaluated using Hamiltonian Monte Carlo methods. The performance of our model is evaluated through an extensive simulation study and is shown to outperform existing methods in terms of estimation of network parameters. We also demonstrate an application of the model to estimate changes in the intestinal microbial network topology with respect to Crohn's disease.

Availability And Implementation: MDiNE is implemented in a freely available R package: https://github.com/kevinmcgregor/mdine.

Supplementary Information: Supplementary data are available at Bioinformatics online.
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http://dx.doi.org/10.1093/bioinformatics/btz824DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7075537PMC
March 2020

Plasma neurofilament light associates with Alzheimer's disease metabolic decline in amyloid-positive individuals.

Alzheimers Dement (Amst) 2019 Dec 27;11:679-689. Epub 2019 Sep 27.

Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, Quebec, Canada.

Introduction: Neurofilament light chain (NfL) is a promising blood biomarker to detect neurodegeneration in Alzheimer's disease (AD) and other brain disorders. However, there are limited reports of how longitudinal NfL relates to imaging biomarkers. We herein investigated the relationship between blood NfL and brain metabolism in AD.

Methods: Voxelwise regression models tested the cross-sectional association between [F]fluorodeoxyglucose ([F]FDG) and both plasma and cerebrospinal fluid NfL in cognitively impaired and unimpaired subjects. Linear mixed models were also used to test the longitudinal association between NfL and [F]FDG in amyloid positive (Aβ+) and negative (Aβ-) subjects.

Results: Higher concentrations of plasma and cerebrospinal fluid NfL were associated with reduced [F]FDG uptake in correspondent brain regions. In Aβ+ participants, NfL associates with hypometabolism in AD-vulnerable regions. Longitudinal changes in the association [F]FDG-NfL were confined to cognitively impaired Aβ+ individuals.

Discussion: These findings indicate that plasma NfL is a proxy for neurodegeneration in AD-related regions in Aβ+ subjects.
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http://dx.doi.org/10.1016/j.dadm.2019.08.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6816316PMC
December 2019

Assessing the role of transmission chains in the spread of HIV-1 among men who have sex with men in Quebec, Canada.

PLoS One 2019 6;14(3):e0213366. Epub 2019 Mar 6.

Department of Mathematics and Statistics, McGill University, Montréal, Québec, Canada.

Background: Phylogenetics has been used to investigate HIV transmission among men who have sex with men. This study compares several methodologies to elucidate the role of transmission chains in the dynamics of HIV spread in Quebec, Canada.

Methods: The Quebec Human Immunodeficiency Virus (HIV) genotyping program database now includes viral sequences from close to 4,000 HIV-positive individuals classified as Men who have Sex with Men (MSMs), collected between 1996 and early 2016. Assessment of chain expansion may depend on the partitioning scheme used, and so, we produce estimates from several methods: the conventional Bayesian and maximum likelihood-bootstrap methods, in combination with a variety of schemes for applying a maximum distance criterion, and two other algorithms, DM-PhyClus, a Bayesian algorithm that produces a measure of uncertainty for proposed partitions, and the Gap Procedure, a fast non-phylogenetic approach. Sequences obtained from individuals in the Primary HIV Infection (PHI) stage serve to identify incident cases. We focus on the period ranging from January 1st 2012 to February 1st 2016.

Results And Conclusion: The analyses reveal considerable overlap between chain estimates obtained from conventional methods, thus leading to similar estimates of recent temporal expansion. The Gap Procedure and DM-PhyClus suggest however moderately different chains. Nevertheless, all estimates stress that longer older chains are responsible for a sizeable proportion of the sampled incident cases among MSMs. Curbing the HIV epidemic will require strategies aimed specifically at preventing such growth.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0213366PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6402664PMC
December 2019

Network screening for large urban road networks: Using GPS data and surrogate measures to model crash frequency and severity.

Accid Anal Prev 2019 Apr 25;125:290-301. Epub 2019 Feb 25.

Department of Decision Sciences, HEC Montréal, 3000 Chemin de la Côte-Sainte-Catherine, Montréal, Québec, H3T 2A7, Canada. Electronic address:

Crash frequency and injury severity are independent dimensions defining crash risk in road safety management and network screening. Traditional screening techniques model crashes using regression and historical crash data, making them intrinsically reactive. In response, surrogate measures of safety have become a popular proactive alternative. The purpose of this paper is to develop models for crash frequency and severity incorporating GPS-derived surrogate safety measures (SSMs) as predictive variables. SSMs based on vehicle manoeuvres and traffic flow were extracted from data collected in Quebec City. The mixed multivariate outcome is estimated using two models; a Full Bayes Spatial Negative Binomial model for crash frequency estimated using the Integrated Nested Laplace Approximation approach and a fractional Multinomial Logit model for crash severity. Model outcomes are combined to generate posterior expected crash frequency at each severity level and rank sites based on crash cost. The crash frequency model was accurate at the network scale, with the majority of proposed SSMs statistically significant at 95% confidence and the direction of their effect generally consistent with previous research. In the crash severity model, fewer variables were significant, yet the direction of the effect of all significant variables was again consistent with previous research. Correlations between rankings predicted by the mixed multivariate model and by the crash data were adequate for intersections (0.46) but were poorer for links (0.25). The ability to prioritize sites based on GPS data and SSMs rather than historical crash data represents a substantial contribution to the field of road safety.
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http://dx.doi.org/10.1016/j.aap.2019.02.016DOI Listing
April 2019

A longitudinal, epigenome-wide study of DNA methylation in anorexia nervosa: results in actively ill, partially weight-restored, long-term remitted and non-eating-disordered women

J Psychiatry Neurosci 2019 05;44(3):205-213

From the Eating Disorders Program, Douglas University Institute (Steiger, Kahan, Thaler, Fletcher, Israël, St-Hilaire, Rossi); the Research Centre, Douglas University Institute (Steiger, Kahan, Thaler, Fletcher, Joober, Israël, St-Hilaire, Rossi); the Department of Psychiatry, McGill University (Steiger, Booij, Thaler, Joober, Israël, St-Hilaire); the Department of Psychology, Concordia University (Booij); the Sainte-Justine Hospital Research Centre, University of Montreal (Booij); the Department of Epidemiology, Biostatistics, and Occupational Health, McGill University (McGregor); the Department of Decision Sciences, HEC Montreal (Labbe); the Department of Pharmacology and Therapeutics, McGill University (Szyf); the School of Human Nutrition, McGill University (Agellon); and the Centre de recherche du Centre Hospitalier, de l’Université de Montréal (CRCHUM) (Gauvin), Montreal, Que., Canada.

Background: This study explored state-related tendencies in DNA methylation in people with anorexia nervosa.

Methods: We measured genome-wide DNA methylation in 75 women with active anorexia nervosa (active), 31 women showing stable remission of anorexia nervosa (remitted) and 41 women with no eating disorder (NED). We also obtained post-intervention methylation data from 52 of the women from the active group.

Results: Comparisons between members of the active and NED groups showed 58 differentially methylated sites (Q < 0.01) that corresponded to genes relevant to metabolic and nutritional status (lipid and glucose metabolism), psychiatric status (serotonin receptor activity) and immune function. Methylation levels in members of the remitted group differed from those in the active group on 265 probes that also involved sites associated with genes for serotonin and insulin activity, glucose metabolism and immunity. Intriguingly, the direction of methylation effects in remitted participants tended to be opposite to those seen in active participants. The chronicity of Illness correlated (usually inversely, at Q < 0.01) with methylation levels at 64 sites that mapped onto genes regulating glutamate and serotonin activity, insulin function and epigenetic age. In contrast, body mass index increases coincided (at Q < 0.05) with generally increased methylation-level changes at 73 probes associated with lipid and glucose metabolism, immune and inflammatory processes, and olfaction.

Limitations: Sample sizes were modest for this type of inquiry, and findings may have been subject to uncontrolled effects of medication and substance use.

Conclusion: Findings point to the possibility of reversible epigenetic alterations in anorexia nervosa, and suggest that an adequate pathophysiological model would likely need to include psychiatric, metabolic and immune components.
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http://dx.doi.org/10.1503/jpn.170242DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6488489PMC
May 2019

What interests young autistic children? An exploratory study of object exploration and repetitive behavior.

PLoS One 2018 31;13(12):e0209251. Epub 2018 Dec 31.

Autism Research Group, CIUSSS du Nord-de-l'île-de-Montréal, Montréal, Québec, Canada.

Behaviors characterized as restricted and repetitive (RRBs) in autism manifest in diverse ways, from motor mannerisms to intense interests, and are diagnostically defined as interfering with functioning. A variety of early autism interventions target RRBs as preoccupying young autistic children to the detriment of exploration and learning opportunities. In an exploratory study, we developed a novel stimulating play situation including objects of potential interest to autistic children, then investigated repetitive behaviors and object explorations in 49 autistic and 43 age-matched typical young children (20-69 months). Autistic children displayed significantly increased overall frequency and duration of repetitive behaviors, as well as increased specific repetitive behaviors. However, groups did not significantly differ in frequency and duration of overall object explorations, in number of different objects explored, or in explorations of specific objects. Exploratory analyses found similar or greater exploration of literacy-related objects in autistic compared to typical children. Correlations between repetitive behaviors and object explorations (their frequency and duration) revealed positive, not negative, associations in both groups. Our findings, from a novel situation incorporating potential autistic interests, suggest that RRBs do not necessarily displace exploration and its possibilities for learning in autism.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0209251PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6312372PMC
May 2019

DM-PhyClus: a Bayesian phylogenetic algorithm for infectious disease transmission cluster inference.

BMC Bioinformatics 2018 Sep 14;19(1):324. Epub 2018 Sep 14.

Department of Mathematics and Statistics, McGill University, 805 rue Sherbrooke Ouest, Montreal, H3A 0B9, QC, Canada.

Background: Conventional phylogenetic clustering approaches rely on arbitrary cutpoints applied a posteriori to phylogenetic estimates. Although in practice, Bayesian and bootstrap-based clustering tend to lead to similar estimates, they often produce conflicting measures of confidence in clusters. The current study proposes a new Bayesian phylogenetic clustering algorithm, which we refer to as DM-PhyClus (Dirichlet-Multinomial Phylogenetic Clustering), that identifies sets of sequences resulting from quick transmission chains, thus yielding easily-interpretable clusters, without using any ad hoc distance or confidence requirement.

Results: Simulations reveal that DM-PhyClus can outperform conventional clustering methods, as well as the Gap procedure, a pure distance-based algorithm, in terms of mean cluster recovery. We apply DM-PhyClus to a sample of real HIV-1 sequences, producing a set of clusters whose inference is in line with the conclusions of a previous thorough analysis.

Conclusions: DM-PhyClus, by eliminating the need for cutpoints and producing sensible inference for cluster configurations, can facilitate transmission cluster detection. Future efforts to reduce incidence of infectious diseases, like HIV-1, will need reliable estimates of transmission clusters. It follows that algorithms like DM-PhyClus could serve to better inform public health strategies.
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http://dx.doi.org/10.1186/s12859-018-2347-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6137936PMC
September 2018

Dissecting genetic cross-talk between ADHD and other neurodevelopmental disorders: Evidence from behavioural, pharmacological and brain imaging investigations.

Psychiatry Res 2018 11 28;269:652-657. Epub 2018 Aug 28.

Douglas Mental Health University Institute, 6875 LaSalle Blvd, Verdun, Quebec H4H 1R3, Canada; Department of Psychiatry, McGill University, Montreal, Quebec, Canada; Department of Human Genetics, McGill University, Montreal, Quebec, Canada; Department of Neurology and Neurosurgery, McGill University, Canada.

Several epidemiological and genetic studies have provided evidence of an overlap between neurodevelopmental disorders. However, the details of the etiological pathways remain to be elucidated. In this study, we garnered the findings of previous GWAS, conducted with schizophrenia and bipolar disorder. We conducted an exploratory study to examine the association between these SNPs and quantitative clinical/ behavioural/ cognitive/ structural brain parameters, as well as response to treatment with a fixed dose of methylphenidate, in a relatively large sample of children with ADHD. Family-based association tests were conducted with nine tag SNPs with 602 nuclear families. In addition, structural magnetic resonance imaging (sMRI) was conducted in a subset of children with ADHD (n = 76). Of the 9 tag SNPs examined, rs1602565 showed a significant association with ADHD, several dimensional measures and response to treatment. An association was also observed between rs1006737 (CACNA1C) and performance IQ. In addition, significant reductions in cortical thickness measurements were observed with the risk allele in rs1006737. These results provide preliminary evidence for putative shared genetic vulnerability between childhood ADHD and other neurodevelopmental disorders.
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http://dx.doi.org/10.1016/j.psychres.2018.08.080DOI Listing
November 2018

A hidden markov model for identifying differentially methylated sites in bisulfite sequencing data.

Biometrics 2019 03 9;75(1):210-221. Epub 2018 Oct 9.

Department of Decision Sciences, HEC Montreal, Quebec, Canada.

DNA methylation studies have enabled researchers to understand methylation patterns and their regulatory roles in biological processes and disease. However, only a limited number of statistical approaches have been developed to provide formal quantitative analysis. Specifically, a few available methods do identify differentially methylated CpG (DMC) sites or regions (DMR), but they suffer from limitations that arise mostly due to challenges inherent in bisulfite sequencing data. These challenges include: (1) that read-depths vary considerably among genomic positions and are often low; (2) both methylation and autocorrelation patterns change as regions change; and (3) CpG sites are distributed unevenly. Furthermore, there are several methodological limitations: almost none of these tools is capable of comparing multiple groups and/or working with missing values, and only a few allow continuous or multiple covariates. The last of these is of great interest among researchers, as the goal is often to find which regions of the genome are associated with several exposures and traits. To tackle these issues, we have developed an efficient DMC identification method based on Hidden Markov Models (HMMs) called "DMCHMM" which is a three-step approach (model selection, prediction, testing) aiming to address the aforementioned drawbacks. Our proposed method is different from other HMM methods since it profiles methylation of each sample separately, hence exploiting inter-CpG autocorrelation within samples, and it is more flexible than previous approaches by allowing multiple hidden states. Using simulations, we show that DMCHMM has the best performance among several competing methods. An analysis of cell-separated blood methylation profiles is also provided.
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http://dx.doi.org/10.1111/biom.12965DOI Listing
March 2019

Surrogate safety and network screening: Modelling crash frequency using GPS travel data and latent Gaussian Spatial Models.

Accid Anal Prev 2018 Nov 22;120:174-187. Epub 2018 Aug 22.

Department of Decision Sciences, HEC Montréal, 3000 Chemin de la Côte-Sainte-Catherine, Montréal, Québec, H3T 2A7, Canada. Electronic address:

Improving road safety requires accurate network screening methods to identify and prioritize sites in order to maximize the effectiveness of implemented countermeasures. In screening, hotspots are commonly identified using statistical models and ranking criteria derived from observed crash data. However, collision databases are subject to errors, omissions, and underreporting. More importantly, crash-based methods are reactive and require years of crash data. With the arrival of new technologies including Global Positioning System (GPS) trajectory data, proactive surrogate safety methods have gained popularity as an alternative approach for screening. GPS-enabled smartphones can collect reliable and spatio-temporally rich driving data from regular drivers using an inexpensive, simple, and user-friendly tool. However, few studies to date have analyzed large volumes of smartphone GPS data and considered surrogate-safety modelling techniques for network screening. The purpose of this paper is to propose a surrogate safety screening approach based on smartphone GPS data and a Full Bayesian modelling framework. After processing crash data and GPS data collected in Quebec City, Canada, several surrogate safety measures (SSMs), including vehicle manoeuvres (hard braking) and measures of traffic flow (congestion, average speed, and speed variation), were extracted. Then, spatial crash frequency models incorporating the extracted SSMs were proposed and validated. A Latent Gaussian Spatial Model was estimated using the Integrated Nested Laplace Approximation (INLA) technique. While the INLA Negative Binomial models outperformed alternative models, incorporating spatial correlations provided the greatest improvement in model fit. Relationships between SSMs and crash frequency established in previous studies were generally supported by the modelling results. For example, hard braking, congestion, and speed variation were all positively linked to crash counts at the intersection level. Network screening based on SSMs presents a substantial contribution to the field of road safety and works towards the elimination of crash data in evaluation and monitoring.
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http://dx.doi.org/10.1016/j.aap.2018.07.013DOI Listing
November 2018

DRD3 Gene and ADHD: A Pharmaco-Behavioural Genetic Study.

Neuromolecular Med 2018 12 26;20(4):515-524. Epub 2018 Jul 26.

Douglas Mental Health University Institute, Montreal, QC, Canada.

Results of candidate gene investigations in ADHD have been difficult to replicate. The complexity of the phenotypes and their underlying determinants, and the relatively small effect sizes of genetic variants may, in part, be contributing to these inconsistencies. The objective of this study is to conduct an exploratory analysis using a comprehensive approach to investigate the role of candidate genes. This approach combines a dimensional behavioural approach akin to Research Domain Criteria (RDoC), a pharmaco-dynamic evaluation of behaviours relevant to ADHD, together with association and linkage testing in a large sample of children with ADHD. Parents, teachers, and research staff evaluated children with ADHD under three experimental conditions (EC): 1 week of baseline observation, followed by 1 week of methylphenidate (MPH) and 1 week of placebo, administered in a double-blind crossover order. Several quantitative behavioural and cognitive dimensions relevant for ADHD were also assessed. We combined family-based (FBAT) and quantitative trait genetic analyses (n = 575 probands with members of their nuclear families) to investigate the role of DRD3 (Ser-9-Gly) in ADHD and its relevant behavioural dimensions. Comparing the behaviours of children with different genotypes under the three EC showed a nominal association between the T allele and poorer behavioural scores during the MPH week (as assessed by teachers), particularly in boys. With the family-based analysis, the T allele showed a nominal association with increased risk for ADHD, response to placebo and MPH as assessed by research staff, and the modulation of other behavioural and cognitive dimensions. These results provide convergent, albeit preliminary evidence for the implication of the DRD3 (Ser-9-Gly) polymorphism in the aetiology of ADHD and the modulation of its various behavioural dimensions, including RDoC cognitive constructs and response to pharmacological probes. This illustrative example suggests that this research paradigm might help to reliably uncover the role of other candidate genes in ADHD.
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http://dx.doi.org/10.1007/s12017-018-8504-zDOI Listing
December 2018

Measuring and Estimating the Effect Sizes of Copy Number Variants on General Intelligence in Community-Based Samples.

JAMA Psychiatry 2018 05;75(5):447-457

Department of Pediatrics, Université de Montréal, Montreal, Quebec, Canada.

Importance;: Copy number variants (CNVs) classified as pathogenic are identified in 10% to 15% of patients referred for neurodevelopmental disorders. However, their effect sizes on cognitive traits measured as a continuum remain mostly unknown because most of them are too rare to be studied individually using association studies.

Objective: To measure and estimate the effect sizes of recurrent and nonrecurrent CNVs on IQ.

Design, Setting, And Participants: This study identified all CNVs that were 50 kilobases (kb) or larger in 2 general population cohorts (the IMAGEN project and the Saguenay Youth Study) with measures of IQ. Linear regressions, including functional annotations of genes included in CNVs, were used to identify features to explain their association with IQ. Validation was performed using intraclass correlation that compared IQ estimated by the model with empirical data.

Main Outcomes And Measures: Performance IQ (PIQ), verbal IQ (VIQ), and frequency of de novo CNV events.

Results: The study included 2090 European adolescents from the IMAGEN study and 1983 children and parents from the Saguenay Youth Study. Of these, genotyping was performed on 1804 individuals from IMAGEN and 977 adolescents, 445 mothers, and 448 fathers (484 families) from the Saguenay Youth Study. We observed 4928 autosomal CNVs larger than 50 kb across both cohorts. For rare deletions, size, number of genes, and exons affect IQ, and each deleted gene is associated with a mean (SE) decrease in PIQ of 0.67 (0.19) points (P = 6 × 10-4); this is not so for rare duplications and frequent CNVs. Among 10 functional annotations, haploinsufficiency scores best explain the association of any deletions with PIQ with a mean (SE) decrease of 2.74 (0.68) points per unit of the probability of being loss-of-function intolerant (P = 8 × 10-5). Results are consistent across cohorts and unaffected by sensitivity analyses removing pathogenic CNVs. There is a 0.75 concordance (95% CI, 0.39-0.91) between the effect size on IQ estimated by our model and IQ loss calculated in previous studies of 15 recurrent CNVs. There is a close association between effect size on IQ and the frequency at which deletions occur de novo (odds ratio, 0.86; 95% CI, 0.84-0.87; P = 2.7 × 10-88). There is a 0.76 concordance (95% CI, 0.41-0.91) between de novo frequency estimated by the model and calculated using data from the DECIPHER database.

Conclusions And Relevance: Models trained on nonpathogenic deletions in the general population reliably estimate the effect size of pathogenic deletions and suggest omnigenic associations of haploinsufficiency with IQ. This represents a new framework to study variants too rare to perform individual association studies and can help estimate the cognitive effect of undocumented deletions in the neurodevelopmental clinic.
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http://dx.doi.org/10.1001/jamapsychiatry.2018.0039DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5875373PMC
May 2018

variant mitigates Alzheimer disease pathophysiology in vivo and postmortem.

Neurol Genet 2018 Feb 30;4(1):e216. Epub 2018 Jan 30.

Translational Neuroimaging Laboratory (A.L.B., S.M., T.A.P., M.S., M.-S.K., P.R.-N.), and Alzheimer's Disease Research Unit (S.G., P.R.-N.), McGill University Research Centre for Studies in Aging, Montreal, Canada; CAPES Foundation (A.L.B.), Ministry of Education of Brazil, Brasília, Brazil; Rush Alzheimer's Disease Center (L.Y., D.A.B.), Rush University Medical Center, Chicago, IL; Department of Decision Sciences (A.L.), HEC Montreal, Montreal, Canada; Department of Epidemiology (A.L.), Biostatistics & Occupational Health, McGill University, Montreal, Canada; Department of Neurology and Neurosurgery (G.A.R., J.P., P.R.-N.), Douglas Hospital Research Centre (J.P., P.R.-N.), and Department of Psychiatry (J.P.), McGill University, Montreal, Canada; and Montreal Neurological Institute (G.A.R., P.R.-N.), Canada.

Objective: To verify whether polymorphisms are associated with amyloid-β (Aβ) pathology across the spectrum of clinical Alzheimer disease using in vivo and postmortem data from 2 independent cohorts.

Methods: A candidate-gene approach tested the association between 5 genes (28 single nucleotide polymorphisms) and Aβ load measured in vivo by the global [F]florbetapir PET standardized uptake value ratio (SUVR) in 338 Alzheimer's Disease Neuroimaging Initiative participants. Significant results were then tested using plasma Aβ and CSF Aβ and Aβ/phosphorylated tau (Aβ/p-tau) ratio in the same cohort. The significant association was also generalized to postmortem Aβ load measurement in the Rush Religious Orders Study/Memory and Aging Project cohorts. In addition, global cognition was used as a phenotype in the analysis in both cohorts.

Results: Analysis of Aβ PET identified a variant in the gene (rs4388808; = 0.0006), in which carriers of the minor allele (MA) had a lower global SUVR. A voxel-wise analysis revealed that the variant is associated with a lower Aβ load in the frontal, inferior temporal, and posterior cingulate cortices. MA carriers also had higher CSF Aβ ( = 0.003) and Aβ/p-tau ratio ( = 0.02) but had no association with Aβ plasma levels. In postmortem brains, MA carriers had a lower Aβ load ( = 0.03). Global cognition was higher in MA carriers, which was found to be mediated by Aβ.

Conclusions: Together, these findings point to an association between polymorphism and Aβ pathology, suggesting a protective effect of the MA of rs4388808. Despite the several possibilities in which affects brain Aβ, the biological mechanism by which this genetic variation may act as a protective factor merits further investigation.
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http://dx.doi.org/10.1212/NXG.0000000000000216DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5820598PMC
February 2018

Evaluation of the "non-epileptic" patient in a tertiary center epilepsy clinic.

Epilepsy Behav 2018 02 19;79:100-105. Epub 2017 Dec 19.

Department of Neurology and Neurosurgery, Montreal Neurological Institute, McGill University, Montreal, Canada. Electronic address:

Purpose: The epilepsy clinic at the Montreal Neurological Institute receives a high volume of referrals. Despite most patients assessed in the clinic eventually being diagnosed with epilepsy, other disorders causing alteration of consciousness or paroxystic symptoms that could be misdiagnosed as seizures are seen frequently. The incidence and clinical characteristics of such patients have not yet been determined. We aimed to determine the proportion and clinical characteristics of patients referred to our epilepsy clinic who had a final diagnosis other than epilepsy.

Methods: We performed a retrospective chart analysis of consecutive patient referrals to the epilepsy clinic from January 2013 to January 2015, inclusively.

Results: Four hundred four patient referrals were evaluated, 106 (or 26%) had a final diagnosis other than epilepsy. Referrals came primarily from general practitioners and nonneurology specialists. Although most patients had a normal routine electroencephalography (EEG) prior to the clinic visit, sleep-deprived EEG and cardiac investigations were rarely performed. Patients received a final diagnosis other than epilepsy after 1 to 2 visits in 92% of cases and with minimal paraclinical investigations. Prolonged video-EEG recording was required in 27% of patients. The most common diagnoses were syncope (33%), psychiatric symptoms (20%), followed by migraine (10%), and psychogenic nonepileptic seizures (9%).

Conclusions: A significant proportion of patients seen in our tertiary care epilepsy clinic is in fact, not patients with epilepsy. Enhanced knowledge of these differential diagnosis and important anamnesis components to rule out seizures will help improve guidelines for referral to Epilepsy clinic and cost-effectively optimize the use of paraclinical investigations.
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http://dx.doi.org/10.1016/j.yebeh.2017.11.001DOI Listing
February 2018

Placebo response and its determinants in children with ADHD across multiple observers and settings: A randomized clinical trial.

Int J Methods Psychiatr Res 2018 03 30;27(1). Epub 2017 Jun 30.

Douglas Mental Health University Institute, Montreal, Quebec, Canada.

This study aims to quantify placebo response (PR) in children with attention deficit hyperactivity disorder (ADHD) as assessed by parents and teachers and to explore some of its determinants. Five hundred and forty children with ADHD (ages 6-12) were recruited to a randomized, double-blind, placebo-controlled crossover trial with methylphenidate. The main outcome variable was Conners' Global Index (CGI), based on assessment of behaviour by parents (CGI-P) and teacher (CGI-T). PR was calculated as the difference between CGI-P/T scores at baseline and placebo week. There was a highly significant PR as assessed by the parents' and teachers' (p < 0.001). The magnitude of PR as assessed by parents was greater (10.57 points) compared to that assessed by teachers (3.93 points). The determinants of PR were different between parents and teachers. For parents, income, marital status, education, maternal smoking during pregnancy, and prior psychostimulant exposure (PPE) showed a significant effect on PR. For teachers, only ethnicity and PPE had an effect. The pattern of PR revealed two distinct profiles that may shed some light on the mechanisms involved in PR. PR in children with ADHD varies depending on the setting of the observations and the evaluator. Several psychosocial factors have been identified as modulators of PR. This is relevant for the design and interpretation of clinical trials and for clinical practice.
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http://dx.doi.org/10.1002/mpr.1572DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6877247PMC
March 2018
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