Alexandre Bureau

Mylène Gagnon; Claudia Moreau; Jasmin Ricard; Marie-Claude Boisvert; Alexandre Bureau; Michel Maziade; Simon L Girard

Rare variants and founder effect in the Beauce region of Quebec Article de journal

Dans: Commun Biol, vol. 8, no 1, p. 1184, 2025, ISSN: 2399-3642.

Loïc Mangnier; Ingo Ruczinski; Jasmin Ricard; Claudia Moreau; Simon Girard; Michel Maziade; Alexandre Bureau

RetroFun-RVS: A Retrospective Family-Based Framework for Rare Variant Analysis Incorporating Functional Annotations Article de journal

Dans: Genet Epidemiol, vol. 49, no 2, p. e70001, 2025, ISSN: 1098-2272.

Liens | BibTeX

@article{pmid39876583,

title = {RetroFun-RVS: A Retrospective Family-Based Framework for Rare Variant Analysis Incorporating Functional Annotations},

author = {Loïc Mangnier and Ingo Ruczinski and Jasmin Ricard and Claudia Moreau and Simon Girard and Michel Maziade and Alexandre Bureau},

doi = {10.1002/gepi.70001},

issn = {1098-2272},

year  = {2025},

date = {2025-03-01},

journal = {Genet Epidemiol},

volume = {49},

number = {2},

pages = {e70001},

abstract = {A large proportion of genetic variations involved in complex diseases are rare and located within noncoding regions, making the interpretation of underlying biological mechanisms a daunting task. Although technical and methodological progress has been made to annotate the genome, current disease-rare-variant association tests incorporating such annotations suffer from two major limitations. First, they are generally restricted to case-control designs of unrelated individuals, which often require tens or hundreds of thousands of individuals to achieve sufficient power. Second, they were not evaluated with region-based annotations needed to interpret the causal regulatory mechanisms. In this work, we propose RetroFun-RVS, a new retrospective family-based score test, incorporating functional annotations. A critical feature of the proposed method is to aggregate genotypes to compare against rare variant-sharing expectations among affected family members. Through extensive simulations, we have demonstrated that RetroFun-RVS integrating networks based on 3D genome contacts as functional annotations reach greater power over the region-wide test, other strategies to include subregions and competing methods. Also, the proposed framework shows robustness to non-informative annotations, maintaining its power when causal variants are spread across regions. Asymptotic p-values are susceptible to Type I error inflation when the number of families with rare variants is small, and a bootstrap procedure is recommended in these instances. Application of RetroFun-RVS is illustrated on whole genome sequence in the Eastern Quebec Schizophrenia and Bipolar Disorder Kindred Study with networks constructed from 3D contacts and epigenetic data on neurons. In summary, the integration of functional annotations corresponding to regions or networks with transcriptional impacts in rare variant tests appears promising to highlight regulatory mechanisms involved in complex diseases.},

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Yuang Tian; Hong Zhang; Alexandre Bureau; Hagit Hochner; Jinbo Chen

Efficient inference of parent-of-origin effect using case-control mother-child genotype data Article de journal

Dans: J Stat Plan Inference, vol. 233, 2024, ISSN: 0378-3758.

Liens | BibTeX

@article{pmid38818512,

title = {Efficient inference of parent-of-origin effect using case-control mother-child genotype data},

author = {Yuang Tian and Hong Zhang and Alexandre Bureau and Hagit Hochner and Jinbo Chen},

doi = {10.1016/j.jspi.2024.106190},

issn = {0378-3758},

year  = {2024},

date = {2024-12-01},

urldate = {2024-12-01},

journal = {J Stat Plan Inference},

volume = {233},

abstract = {Parent-of-origin effect plays an important role in mammal development and disorder. Case-control mother-child pair genotype data can be used to detect parent-of-origin effect and is often convenient to collect in practice. Most existing methods for assessing parent-of-origin effect do not incorporate any covariates, which may be required to control for confounding factors. We propose to model the parent-of-origin effect through a logistic regression model, with predictors including maternal and child genotypes, parental origins, and covariates. The parental origins may not be fully inferred from genotypes of a target genetic marker, so we propose to use genotypes of markers tightly linked to the target marker to increase inference efficiency. A robust statistical inference procedure is developed based on a modified profile log-likelihood in a retrospective way. A computationally feasible expectation-maximization algorithm is devised to estimate all unknown parameters involved in the modified profile log-likelihood. This algorithm differs from the conventional expectation-maximization algorithm in the sense that it is based on a modified instead of the original profile log-likelihood function. The convergence of the algorithm is established under some mild regularity conditions. This expectation-maximization algorithm also allows convenient handling of missing child genotypes. Large sample properties, including weak consistency, asymptotic normality, and asymptotic efficiency, are established for the proposed estimator under some mild regularity conditions. Finite sample properties are evaluated through extensive simulation studies and the application to a real dataset.},

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Christina Nieuwoudt; Fabiha Binte Farooq; Angela Brooks-Wilson; Alexandre Bureau; Jinko Graham

Statistics to prioritize rare variants in family-based sequencing studies with disease subtypes Article de journal

Dans: Genet Epidemiol, vol. 48, no 7, p. 324–343, 2024, ISSN: 1098-2272.

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Jasmin Ricard; Nicolas Berthelot; Énora Fortin-Fabbro; Marie-Claude Boisvert; Julia Garon-Bissonnette; Eric Arsenault; Alexandre Bureau; Michel Maziade

Childhood trauma and altered response of retinal neurons as an early risk endophenotype of schizophrenia and mood disorder Article de journal

Dans: Biomarkers in Neuropsychiatry, vol. 10, 2024, ISSN: 2666-1446.

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Alexandre Bureau; Nicolas Berthelot; Jasmin Ricard; Camille Lafrance; Valérie Jomphe; Abdoulaye Dioni; Énora Fortin-Fabbro; Marie-Claude Boisvert; Michel Maziade

Heterogeneity in the longitudinal courses of global functioning in children at familial risk of major psychiatric disorders: Association with trauma and familial characteristics Article de journal

Dans: Bipolar Disord, vol. 26, no 3, p. 265–276, 2024, ISSN: 1399-5618.

Liens | BibTeX

@article{pmid37957788,

title = {Heterogeneity in the longitudinal courses of global functioning in children at familial risk of major psychiatric disorders: Association with trauma and familial characteristics},

author = {Alexandre Bureau and Nicolas Berthelot and Jasmin Ricard and Camille Lafrance and Valérie Jomphe and Abdoulaye Dioni and Énora Fortin-Fabbro and Marie-Claude Boisvert and Michel Maziade},

doi = {10.1111/bdi.13386},

issn = {1399-5618},

year  = {2024},

date = {2024-05-01},

journal = {Bipolar Disord},

volume = {26},

number = {3},

pages = {265--276},

abstract = {OBJECTIVES: The extent to which heterogeneity in childhood risk trajectories may underlie later heterogeneity in schizophrenia (SZ), bipolar disorder (BP), and major depressive disorder (MDD) remains a chief question. Answers may optimally be found by studying the longitudinal trajectories of children born to an affected parent. We aimed to differentiate trajectories of global functioning and their sensitive periods from the age of 6 to 17 years in children at familial risk (FHRs).nnMETHODS: First, a latent class mixed model analysis (LCMM) was applied to yearly ratings of the Children's Global Assessment Scale (CGAS) from the age of 6 to 17 years in 170 FHRs born to a parent affected by DSM-IV SZ (N = 37), BP (N = 82) or MDD (N = 51). Then, we compared the obtained Classes or trajectories of FHRs in terms of sex, parental diagnosis, IQ, child clinical status, childhood trauma, polygenic risk score (PRS), and outcome in transition to illness.nnRESULTS: The LCMM on yearly CGAS trajectories identified a 4-class solution showing markedly different childhood and adolescence dynamic courses and temporal vulnerability windows marked by a functioning decline and a degree of specificity in parental diagnosis. Moreover, IQ, trauma exposure, PRS level, and timing of later transition to illness differentiated the trajectories. Almost half (46%) of the FHRs exhibited a good and stable global functioning trajectory.nnCONCLUSIONS: FHRs of major psychiatric disorders show heterogeneous functional decline during development associated with parental diagnosis, polygenic risk loading, and childhood trauma.},

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Houssou R G Dossa; Alexandre Bureau; Michel Maziade; Lajmi Lakhal-Chaieb; Karim Oualkacha

A novel rare variants association test for binary traits in family-based designs via copulas Article de journal

Dans: Stat Methods Med Res, vol. 32, no 11, p. 2096–2122, 2023, ISSN: 1477-0334.

Liens | BibTeX

@article{pmid37832140,

title = {A novel rare variants association test for binary traits in family-based designs via copulas},

author = {Houssou R G Dossa and Alexandre Bureau and Michel Maziade and Lajmi Lakhal-Chaieb and Karim Oualkacha},

doi = {10.1177/09622802231197977},

issn = {1477-0334},

year  = {2023},

date = {2023-11-01},

journal = {Stat Methods Med Res},

volume = {32},

number = {11},

pages = {2096--2122},

abstract = {With the cost-effectiveness technology in whole-genome sequencing, more sophisticated statistical methods for testing genetic association with both rare and common variants are being investigated to identify the genetic variation between individuals. Several methods which group variants, also called gene-based approaches, are developed. For instance, advanced extensions of the sequence kernel association test, which is a widely used variant-set test, have been proposed for unrelated samples and extended for family data. Family data have been shown to be powerful when analyzing rare variants. However, most of such methods capture familial relatedness using a random effect component within the generalized linear mixed model framework. Therefore, there is a need to develop unified and flexible methods to study the association between a set of genetic variants and a trait, especially for a binary outcome. Copulas are multivariate distribution functions with uniform margins on the  interval and they provide suitable models to capture familial dependence structure. In this work, we propose a flexible family-based association test for both rare and common variants in the presence of binary traits. The method, termed novel rare variant association test (NRVAT), uses a marginal logistic model and a Gaussian Copula. The latter is employed to model the dependence between relatives. An analytic score-type test is derived. Through simulations, we show that our method can achieve greater power than existing approaches. The proposed model is applied to investigate the association between schizophrenia and bipolar disorder in a family-based cohort consisting of 17 extended families from Eastern Quebec.},

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Meriem Bahda; Jasmin Ricard; Simon L Girard; Michel Maziade; Maripier Isabelle; Alexandre Bureau

Multivariate extension of penalized regression on summary statistics to construct polygenic risk scores for correlated traits Article de journal

Dans: HGG Adv, vol. 4, no 3, p. 100209, 2023, ISSN: 2666-2477.

Liens | BibTeX

@article{pmid37333772,

title = {Multivariate extension of penalized regression on summary statistics to construct polygenic risk scores for correlated traits},

author = {Meriem Bahda and Jasmin Ricard and Simon L Girard and Michel Maziade and Maripier Isabelle and Alexandre Bureau},

doi = {10.1016/j.xhgg.2023.100209},

issn = {2666-2477},

year  = {2023},

date = {2023-07-01},

journal = {HGG Adv},

volume = {4},

number = {3},

pages = {100209},

abstract = {Genetic correlations between human traits and disorders such as schizophrenia (SZ) and bipolar disorder (BD) diagnoses are well established. Improved prediction of individual traits has been obtained by combining predictors of multiple genetically correlated traits derived from summary statistics produced by genome-wide association studies, compared with single trait predictors. We extend this idea to penalized regression on summary statistics in Multivariate Lassosum, expressing regression coefficients for the multiple traits on single nucleotide polymorphisms (SNPs) as correlated random effects, similarly to multi-trait summary statistic best linear unbiased predictors (MT-SBLUPs). We also allow the SNP contributions to genetic covariance and heritability to depend on genomic annotations. We conducted simulations with two dichotomous traits having polygenic architecture similar to SZ and BD, using genotypes from 29,330 subjects from the CARTaGENE cohort. Multivariate Lassosum produced polygenic risk scores (PRSs) more strongly correlated with the true genetic risk predictor and had better discrimination power between affected and non-affected subjects than previously published sparse multi-trait (PANPRS) and univariate (Lassosum, sparse LDpred2, and the standard clumping and thresholding) methods in most simulation settings. Application of Multivariate Lassosum to predict SZ, BD, and related psychiatric traits in the Eastern Quebec SZ and BD kindred study revealed associations with every trait stronger than those obtained with univariate sparse PRSs, particularly when heritability and genetic covariance depended on genomic annotations. Multivariate Lassosum thus appears promising to improve prediction of genetically correlated traits with summary statistics for a selected subset of SNPs.},

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Yang You; David Simonyan; Alexandre Bureau; Edith Gagnon; Caroline Albert; Jason R Guertin; Jean-Eric Tarride; Jacques P Brown; Laëtitia Michou

Molecular test of Paget’s disease of bone in families not linked to gene mutations Article de journal

Dans: Bone Rep, vol. 18, p. 101670, 2023, ISSN: 2352-1872.

Liens | BibTeX

@article{pmid36915391,

title = {Molecular test of Paget's disease of bone in families not linked to  gene mutations},

author = {Yang You and David Simonyan and Alexandre Bureau and Edith Gagnon and Caroline Albert and Jason R Guertin and Jean-Eric Tarride and Jacques P Brown and Laëtitia Michou},

doi = {10.1016/j.bonr.2023.101670},

issn = {2352-1872},

year  = {2023},

date = {2023-06-01},

journal = {Bone Rep},

volume = {18},

pages = {101670},

abstract = {PURPOSE: Paget's disease of bone (PDB) is a focal metabolic bone disorder characterized by an increased bone remodeling. Fifteen to 40 % of PDB patients have a familial form with an autosomal dominant inheritance. Disease-causing mutations of the  gene have been linked to PDB in about 40 % of families whereas genes linked to the remaining families are unknown. Several single nucleotide polymorphisms (SNPs) have been associated with PDB in unrelated patient non-carriers of a  mutation. The current clinical practice guidelines still recommend the measure of serum total alkaline phosphatase (sALP) for PDB screening. In unrelated individual non-carriers of  mutations, we previously developed a genetic test combining male sex with five genetic markers (rs499345, rs5742915, rs2458413, rs3018362, rs2234968), giving rise to an area under the curve (AUC) for PDB phenotype of 0.73 (0.69; 0.77). A combination of male sex with total calcium corrected for albumin and Procollagen type I N-terminal propeptide (P1NP), had an AUC of 0.82 (0.73; 0.92). Combining both genetic and biochemical tests increased the AUC to 0.89 (0.83; 0.95).nnOBJECTIVE: This study aimed at estimating the performance of our previous test of PDB, in families not linked to  mutations with disease-causing genes yet unknown, and at developing a new algorithm if the performance is not satisfactory.nnMETHODS: We genotyped the five SNPs cited above, and measured calcium corrected for albumin and P1NP in 181 relatives, with PDB or not, from 19 PDB families not linked to  mutations. Bivariate and multivariate logistic regression models including male sex were fitted to search for a molecular test that could best detect PDB in these families. A receiving operating characteristics analysis was done to establish a cut-off point for continuous variables.nnRESULTS: Logistic regression estimates of our previous molecular test gave rise to a high sensitivity of 78 %, 97 % and 88 % for the genetic, biochemical, and combined test but the specificity was very low, 35 %, 11 % and 21 %, respectively. This poor specificity persisted even when the cut-off point was changed. We then generated in these families, new logistic regression estimates but on the same parameters as mentioned above, giving rise to an AUC of 0.65 (0.55; 0.75) for the genetic test, of 0.84 (0.74; 0.94) for the biochemical test, and 0.89 (0.82; 0.96) for the combination test, the latter having a sensitivity of 96 % and specificity of 57 %. By comparison serum P1NP alone gave rise to an AUC of 0.84 (0.73; 0.94), with a sensitivity of 71 % and a specificity of 79 %.nnCONCLUSION: In PDB families not linked to  mutations, the estimates of our previous molecular test gave rise to a poor specificity. Using new estimates, the biochemical and combined tests have similar predictive abilities than our former test. Serum P1NP is a bone marker of interest for the screening for PDB in families not linked to  mutations.},

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Alexandre Bureau; Yuang Tian; Patrick Levallois; Yves Giguère; Jinbo Chen; Hong Zhang

Methods and Software to Analyze Gene-Environment Interactions under a Case-Mother-Control-Mother Design with Partially Missing Child Genotype Article de journal

Dans: Hum Hered, vol. 88, no 1, p. 38–49, 2023, ISSN: 1423-0062.

Liens | BibTeX

@article{pmid37100044,

title = {Methods and Software to Analyze Gene-Environment Interactions under a Case-Mother-Control-Mother Design with Partially Missing Child Genotype},

author = {Alexandre Bureau and Yuang Tian and Patrick Levallois and Yves Giguère and Jinbo Chen and Hong Zhang},

doi = {10.1159/000529559},

issn = {1423-0062},

year  = {2023},

date = {2023-01-01},

journal = {Hum Hered},

volume = {88},

number = {1},

pages = {38--49},

abstract = {INTRODUCTION: The case-mother-control-mother design allows to study fetal and maternal genetic factors together with environmental exposures on early life outcomes. Mendelian constraints and conditional independence between child genotype and environmental factors enabled semiparametric likelihood methods to estimate logistic models with greater efficiency than standard logistic regression. Difficulties in child genotype collection require methods handling missing child genotype.nnMETHODS: We review a stratified retrospective likelihood and two semiparametric likelihood approaches: a prospective one and a modified retrospective one, the latter either modeling the maternal genotype as a function of covariates or leaving their joint distribution unspecified (robust version). We also review software implementing these modeling alternatives, compare their statistical properties in a simulation study, and illustrate their application, focusing on gene-environment interactions and partially missing child genotype.nnRESULTS: The robust retrospective likelihood provides generally unbiased estimates, with standard errors only slightly larger than when modeling maternal genotype based on exposure. The prospective likelihood encounters maximization problems. In the application to the association of small-for-gestational-age babies with CYP2E1 and drinking water disinfection by-products, the retrospective likelihood allowed a full array of covariates, while the prospective likelihood was limited to few covariates.nnCONCLUSION: We recommend the robust version of the modified retrospective likelihood.},

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