@article{pmid40781540,

title = {Rare variants and founder effect in the Beauce region of Quebec},

author = {Mylène Gagnon and Claudia Moreau and Jasmin Ricard and Marie-Claude Boisvert and Alexandre Bureau and Michel Maziade and Simon L Girard},

doi = {10.1038/s42003-025-08630-7},

issn = {2399-3642},

year  = {2025},

date = {2025-08-01},

journal = {Commun Biol},

volume = {8},

number = {1},

pages = {1184},

abstract = {Founder events influenced the genetic diversity within the province of Quebec, increasing the frequency of certain rare pathogenic variants in regional populations. Some regions, such as Beauce, remain understudied despite evidence of a regional founder effect. Leveraging extensive genealogical data, we observe a specific regional structure emerging in Beauce following the initial settlement. It is characterised by a gradual increase in inbreeding and kinship coefficients and a low diversity of ancestors. Taking advantage of the region's genetic distinctiveness, we describe 36 rare pathogenic variants with higher carrier rates in Beauce than in urban regions, likely due to the regional founder effect. This provides the first in-depth study of Beauce's genetic and genealogical landscape, revealing a distinct structure and suggesting that other overlooked regions, in Quebec and elsewhere, could benefit from fine-scale population structure studies to improve the understanding and management of rare diseases.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid41661916,

title = {Analyzing service descriptors and patients' clinical characteristics may help understand heterogeneity in long-term trajectory of patients with schizophrenia, bipolar and major depressive disorder},

author = {Vittorio Nicoletta and Angel Ruiz and Valérie Bélanger and Thomas Paccalet and Maripier Isabelle and Michel Maziade},

doi = {10.1371/journal.pmen.0000327},

issn = {2837-8156},

year  = {2025},

date = {2025-01-01},

journal = {PLOS Ment Health},

volume = {2},

number = {5},

pages = {e0000327},

abstract = {One major obstacle to advancing research and treatment for major psychiatric disorders is their substantial within-diagnosis heterogeneity in patient lifetime trajectories. Adapted research methods such as cluster analysis to define subgroups of patients are currently used. However few studies have included service delivery descriptors in cluster analysis to investigate the determinants of heterogeneity in long-term trajectories. The aim of this study was to test whether patterns of service delivery could help in defining subgroups in terms of trajectories and clinical profiles in schizophrenia, bipolar disorder or major depressive disorder patients. Hierarchical Agglomerative Clustering (HAC) algorithms were used on a sample extracted from a Quebec government (Canada) transactional database to group and classify patients according to their interactions with the service delivery system. The resulting clusters were analyzed using statistical tools to characterize service trajectories. We observed three distinct trajectories that were not specific to any one of the three lifetime psychiatric diagnoses. Clusters were particularly affected by varying rates of clinician changes across the trajectory and changes of diagnoses. Results suggest that incorporating service delivery characteristics in future longitudinal studies of heterogeneity might be useful as a complement to studies that solely examine patients' clinical features. The inclusion of service delivery elements may also be a useful tool for acquiring knowledge to adapt services to patients' needs in public mental health and mental health economics research.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Ricard2024d,

title = {Childhood trauma and altered response of retinal neurons as an early risk endophenotype of schizophrenia and mood disorder},

author = {Jasmin Ricard and Nicolas Berthelot and Énora Fortin-Fabbro and Marie-Claude Boisvert and Julia Garon-Bissonnette and Eric Arsenault and Alexandre Bureau and Michel Maziade},

doi = {10.1016/j.bionps.2024.100095},

issn = {2666-1446},

year  = {2024},

date = {2024-06-01},

journal = {Biomarkers in Neuropsychiatry},

volume = {10},

publisher = {Elsevier BV},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@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.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39144791,

title = {Childhood Trauma May Increase Risk of Psychosis and Mood Disorder in Genetically High-risk Children and Adolescents by Enhancing the Accumulation of Risk Indicators},

author = {Nicolas Berthelot and Julia Garon-Bissonnette and Valérie Jomphe and Hélène Doucet-Beaupré and Alexandre Bureau and Michel Maziade},

doi = {10.1093/schizbullopen/sgac017},

issn = {2632-7899},

year  = {2022},

date = {2022-01-01},

journal = {Schizophr Bull Open},

volume = {3},

number = {1},

pages = {sgac017},

abstract = {BACKGROUND: Genetically high-risk children carry indicators of brain dysfunctions that adult patients with schizophrenia or bipolar disorder display. The accumulation of risk indicators would have a higher predictive value of a later transition to psychosis or mood disorder than each individual risk indicator. Since more than 50% of adult patients report having been exposed to childhood trauma, we investigated whether exposure to trauma during childhood was associated with the early accumulation of risk indicators in youths at genetic risk.nnMETHODS: We first inspected the characteristics of childhood trauma in 200 young offspring (51% male) born to a parent affected by DSM-IV schizophrenia, bipolar disorder, or major depressive disorder. A subsample of 109 offspring (51% male) had measurements on four risk indicators: cognitive impairments, psychotic-like experiences, nonpsychotic nonmood childhood DSM diagnoses, poor global functioning. Trauma was assessed from direct interviews and reviews of lifetime medical and school records of offspring.nnRESULTS: Trauma was present in 86 of the 200 offspring (43%). The relative risk of accumulating risk indicators in offspring exposed to trauma was 3.33 (95% CI 1.50, 7.36), but more pronounced in males (RR = 4.64, 95% CI 1.71, 12.6) than females (RR = 2.01, 95% CI 0.54, 7.58).nnCONCLUSION: Childhood trauma would be related to the accumulation of developmental precursors of major psychiatric disorders and more so in young boys at high genetic risk. Our findings may provide leads for interventions targeting the early mechanisms underlying the established relation between childhood trauma and adult psychiatric disorders.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid39144760,

title = {The Electroretinogram as a Potential Biomarker of Psychosis in Children at Familial Risk},

author = {Isabel Moreau and Marc Hébert and Michel Maziade and Alexandra Painchaud and Chantal Mérette},

doi = {10.1093/schizbullopen/sgac016},

issn = {2632-7899},

year  = {2022},

date = {2022-01-01},

journal = {Schizophr Bull Open},

volume = {3},

number = {1},

pages = {sgac016},

abstract = {We previously proposed the electroretinogram (ERG) as a promising biomarker of major psychiatric disorders such as schizophrenia (SZ) and bipolar disorder (BP), given that we found anomalies in the ERG parameters of patients with these diagnoses as well as in their children who are at high risk (HR) of developing such disorders. The aim of the present study is to investigate the usefulness of the ERG for individual detection, among HR children, of an ERG profile resembling that of a SZ patient, as this may indicate a stronger likelihood of transition to psychosis. Using a logistic regression model previously derived from the ERG assessments of SZ patients and control (CT) subjects, individual risk scores were obtained for 61 HR and 80 CT youth. Those with a very high individual risk score were classified as "schizophrenia-like" (). We found that the HR subjects were 3.5 times more likely to be classified as  than the CT subjects (95% CI [1.1-11.8]). Furthermore, among the HR subjects, we studied the relationship between the  classification and psychotic-like experiences and found that HR subjects classified as  were 2.7 times more likely than all remaining HR subjects to have experienced psychotic-like symptoms (95% CI [1.3-4.6]), and 6.8 times more likely than those with a very low individual risk score (95% CI [1.4-40.4]). Our results suggest that a model previously derived from ERG data on SZ patients could be a potential tool for early detection of the susceptibility to a psychotic-like disorder among familial HR children.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid32677491,

title = {Characterising phospholipids and free fatty acids in patients with schizophrenia: A case-control study},

author = {Dongfang Wang and Xiaoyu Sun and Michel Maziade and Wei Mao and Chuanbo Zhang and Jingyu Wang and Bing Cao},

doi = {10.1080/15622975.2020.1769188},

issn = {1814-1412},

year  = {2021},

date = {2021-03-01},

journal = {World J Biol Psychiatry},

volume = {22},

number = {3},

pages = {161--174},

abstract = {OBJECTIVES: Previous studies have indicated that schizophrenia (SCZ) is linked to abnormal phospholipid and fatty acid metabolism. However, comprehensive analysis of phospholipids and free fatty acids (FFAs) for SCZ is very limited. Herein, we sought to compare serum levels of phospholipids and FFAs between patients with SCZ and healthy controls (HCs).nnMETHODS: One hundred and nineteen SCZ patients and 109 HCs were enrolled in the study. The levels of 177 phospholipids and FFAs were measured in serum samples using a targeted liquid chromatography-mass spectrometry (LC-MS)-based platform.nnRESULTS: One hundred and ten metabolites, including 16 FFAs, 25 phosphatidylcholines, 23 lysophosphatidylcholines, 11 phosphatidylcholine plasmalogens, 7 phosphatidylethanolamines, 9 lysophosphatidylethanolamines, 6 phosphatidylethanolamine plasmalogens, and 13 sphingomyelins, were observed to be significantly altered in SCZ patients compared to HCs. These disturbances may represent underlying pathophysiology, including but not limited to altered activity of phospholipases and acyltransferases, increased oxidative stress, dysfunctional oligodendrocyte glycosynapses, and elevated lipid mobilisation and β-oxidation.nnCONCLUSIONS: Our findings suggest that complex lipid profile abnormalities are associated with SCZ. This study may contribute to investigating the role of phospholipid and FFA alterations in the pathoetiology of SCZ.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}