Alexandre Bureau, Ph.D.
Researcher, CERVO Brain Research Centre
Professor, Université Laval
Development of statistical methods to identify the genetic causes of complex diseases.
Many psychiatric illnesses have complex causes, which may include multiple genetic factors, and significant environmental contributions. In addition, the symptoms associated with different psychiatric illnesses are sometimes variable from one individual to another. Alexandre Bureau's team aims to develop and apply statistical methods to identify the genes involved in these complex diseases.
The statistical approaches developed by Dr. Bureau make it possible to analyze whole genomes of people affected by psychiatric illnesses and members of their families. This type of complex genetic analysis can detect rare genetic variations that are associated with diseases.
Dr. Bureau’s studies have recently suggested that two genes could contribute to the manic and depressive dimensions of mood disorders. This type of analysis has also identified genetic factors involved in suicide, dyslexia and the development of schizophrenia.
The usefulness of the methods developed by Dr. Bureau is not limited to complex psychiatric disorders. His team also contributes to studies of other complex phenomena, such as fetal growth and facial deformities.
Identifying the genes involved in complex diseases is one way of identifying potential therapeutic targets and improving the prediction of disease risk. Recent work by Dr. Bureau aims to evaluate the usefulness of accumulated knowledge on the genetics of schizophrenia and bipolar disorder to predict the risk of these diseases in children of affected parents.
I am developing statistical methods for data analyses aiming to identify the genetic causes of complex diseases in familial studies, exploiting the advantages of this type of designs. Methods I develop also take into account multidimensional phenotypes and the simultaneous effects of multiple genes, as well as the interactions between genes and environmental factors.
Abdoulaye Dioni, PhD student in biostatistics
Loïc Mangnier, PhD student in biostatistics
Samir Oubninte, PhD student in biostatistics
Meriem Bahda, MSc student in biostatistics
Chaymae Yousfi, MSc student in statistics
Mangnier L, Joly-Beauparlant C, Droit A, Bilodeau S, Bureau A. (2022). Cis-regulatory hubs: a new 3D model of complex disease genetics with an application to schizophrenia. Life Sci Alliance. 5(5):e202101156.
Chagnon YC, Maziade M, Paccalet T, Croteau J, Fournier A, Roy M-A, Bureau A. (2020). A multimodal attempt to follow-up linkage regions using RNA expression, SNPs and CpG methylation in schizophrenia and bipolar disorder kindreds. Eur J Hum Genet. 28(4): 499-507.
Bureau A, Begum F, Taub M A, Hetmanski J B, Parker M M, Albacha-Hejazi H, Scott A F, Murray J C, Marazita M L, Bailey-Wilson J E, Beaty T H and Ruczinski I. (2019). Inferring Disease Risk Genes from Sequencing Data in Multiplex Pedigrees Through Sharing of Rare Variants. Genetic Epidemiology. 43(1):37-49.
Boies S , Mérette C , Paccalet T , Maziade M , Bureau A. (2018). Polygenic risk scores distinguish patients from non-affected adult relatives and from normal controls in schizophrenia and bipolar disorder multiaffected kindreds.American journal of medical genetics. Part B, Neuropsychiatric genetics. 177(3): 329-336.
Bonou SG, Levallois P , Giguère Y , Rodriguez M , Bureau A. (2017). Prenatal exposure to drinking water chlorination by-products, cytochrome P450 gene polymorphisms and small-for-gestational-age neonates. Reproductive toxicology (Elmsford, N.Y.). 73: 75-86.
Bureau A , Beaulieu JM , Paccalet T , Chagnon YC , Maziade M. (2017). The interaction of GSK3B and FXR1 genotypes may influence the mania and depression dimensions in mood disorders.Journal of affective disorders. 213: 172-177.
Levallois, P., Y. Giguere, M. Nguile-Makao, M. Rodriguez, C. Campagna, R. Tardif and A. Bureau (2016). "Disinfection by-products exposure and intra-uterine growth restriction: Do genetic polymorphisms of CYP2E1or deletion of GSTM1 or GSTT1 modify the association?" Environ Int 92-93: 220-231.
Nguile-Makao, M, and Bureau, A. Semi-Parametric Maximum Likelihood Method for Interaction in Case-Mother Control-Mother Designs: Package SPmlficmcm. Journal of Statistical Software 2015, 68(10):1-17. CRAN R package: SPmlficmcm
Bureau, A and Duchesne, T. On the validity of within-nuclear-family genetic association analysis in samples of extended families. Stat Appl Genet Mol Biol 2015, 14 : 533-549.
Bureau, A, Croteau, J, Couture, C, et al. Estimating genetic effect sizes under joint disease-endophenotype models in presence of gene-environment interactions. Front Genet 2015, 6: 248.
Mascheretti, S, Bureau, A, Trezzi, V, et al. An assessment of gene-by-gene interactions as a tool to unfold missing heritability in dyslexia. Hum Genet 2015, 134(7): 749-760.
Bureau, A, Younkin, S, Parker, MM, et al. Inferring rare disease risk variants based on exact probabilities of sharing by multiple affected relatives. Bioinformatics 2014, 30(15): 2189-2196. CRAN R package: RVsharing
Bureau, A., Parker, M.M., Ruczinski, I, et al. Whole exome sequencing of distant relatives in multiplex families implicates rare variants in candidate genes for oral clefts. Genetics 2014, 197(3): 1039-1044.
Bureau, A, Croteau, J, Chagnon, YC, et al. Extension of the generalized disequilibrium test to polytomous phenotypes and two-locus models. Frontiers in Genetics 2014, 5: Article 258. CRAN R package: fat2Lpoly
Bureau, A, Chagnon, YC, Croteau, J, et al. Follow-up of a Major Psychosis Linkage Site in 13q13-q14 Reveals Significant Association in Both Case-Control and Family Samples. Biol Psychiatry 2013, 74(6).
Mascheretti, S, Bureau, A, Battaglia, et al. An Assessment of Gene-by-Environment Interactions in Developmental Dyslexia-Related Phenotypes. Genes Brain Behav 2013, 12(1):47-55.
Labonté, B, Suderman, M, Maussion, G, Navaro, L, Yerko, V, Mahar, I, Bureau, A, et al. Genome-wide Epigenetic Regulation by Early-Life Trauma. Archives of general psychiatry 2012, 69(7): 722-31.
Tayeb, A, Labbe, A, Bureau, A, and Merette, C. Solving genetic heterogeneity in extended families by identifying sub-types of complex diseases. Comput Stat 2011, 26(3): 539-560. CRAN R package: LCAextend
Article “Bureau, A., Dupuis, J., Falls, K., Lunetta, K.L., Hayward, B., Keith, T. and Van Eerdewegh, P. (2005). Identifying SNPs predictive of phenotype using Random Forests. Genet Epidemiol, 28(2): 171-82”. 246 citations. The oral presentation of part of this work at the 2002 meeting of the International Genetic Epidemiology Society was nominated for the Neel Award.
2601 Chemin de la Canardière