Portrait de Julie Hussin

Julie Hussin

Membre académique associé
Professeure adjointe, Université de Montréal
Sujets de recherche
Apprentissage automatique médical
Apprentissage multimodal
Apprentissage profond
Biologie computationnelle
Exploration des données
Site web
Google Scholar
LinkedIn
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Biographie

Julie Hussin est professeure agrégée à la Faculté de médecine de l'Université de Montréal (UdeM) et chercheuse à l'Institut de cardiologie de Montréal (ICM). Elle est aussi chercheuse-boursière junior 2 du Fonds de recherche du Québec - Santé (FRQS) et responsable des programmes d'études supérieures en bio-informatique à l'UdeM.

Julie Hussin a été formée en génomique statistique et évolutive et possède une vaste expérience dans l'analyse de données multi-omiques issues de vastes cohortes populationnelles. Ses travaux en biologie computationnelle se concentrent principalement sur la génomique médicale et des populations, contribuant à plusieurs avancées méthodologiques dans ces domaines. Son travail interdisciplinaire vise à développer des outils novateurs pour la médecine de précision.

Ses projets de recherche se focalisent sur l'amélioration de la prédiction de risques et la gestion des maladies cardiométaboliques, en particulier dans le cas de l'insuffisance cardiaque. Les méthodologies utilisées dans son groupe intègrent différentes sources de données, notamment des données cliniques, génétiques, transcriptomiques, protéomiques et métabolomiques, pour permettre la découverte de nouvelles informations sur les déterminants biologiques des maladies cardiaques, notamment par des techniques d’apprentissage non supervisé. Dans le contexte de la pandémie de COVID-19, son équipe a également développé des approches d’analyse de données génétiques des virus, pour la surveillance virale et l’étude des interactions hôte-pathogène ainsi que l'évolution virale.

Ses intérêts de recherche comprennent également l'interprétabilité, la généralisation et l'équité des algorithmes d'apprentissage automatique dans la recherche en santé. Julie Hussin s'engage à promouvoir activement une IA équitable, sûre et transparente dans la recherche en santé et s'efforce d'assurer l'inclusivité et la représentativité des individus dans sa recherche, pour que son travail bénéficie à l'ensemble de la population. Elle partage son expertise en donnant plusieurs cours de bio-informatique et de génétique des populations, ainsi que d’apprentissage automatique en génomique. Avant de se joindre à l'Université de Montréal en tant que professeure, elle a été boursière postdoctorale du Human Frontier Science Program au Wellcome Trust Centre for Human Genetics de l'Université d'Oxford (Linacre College) et chercheuse postdoctorale invitée à l'Université McGill.

Étudiants actuels

Cantin Baron
Doctorat - UdeM
Site web
Google Scholar
David Hamelin
Doctorat - UdeM
Fatima Mostefai
Doctorat - UdeM
Alexis Nolin-Lapalme
Doctorat - UdeM
Simon Paquette
Maîtrise recherche - UdeM
Github
Camille Rochefort-Boulanger
Doctorat - UdeM
Co-superviseur⋅e :
Yoshua Bengio
Github
Matthew Scicluna
Doctorat - UdeM
Co-superviseur⋅e :
Guy Wolf
Github
Google Scholar

Publications

Refining SARS-CoV-2 Intra-host Variation by Leveraging Large-scale Sequencing Data
Fatima Mostefai
Jean-Christophe Grenier
Raphael Poujol
Julie Hussin
2024-11-12
NAR Genomics and Bioinformatics (publié)
doi.org
Temperature-dependent Spike-ACE2 interaction of Omicron subvariants is associated with viral transmission
Mehdi Benlarbi
Shilei Ding
Étienne Bélanger
Alexandra Tauzin
Raphael Poujol
Halima Medjahed
Omar El Ferri
Yuxia Bo
Catherine Bourassa
Julie Hussin
Judith Fafard
Marzena Pazgier
Inès Levade
Cameron Abrams
Marceline Côté
Andrés Finzi
The continued evolution of SARS-CoV-2 requires persistent monitoring of its subvariants. Omicron subvariants are responsible for the vast ma… (voir plus)jority of SARS-CoV-2 infections worldwide, with XBB and BA.2.86 sublineages representing more than 90% of circulating strains as of January 2024. In this study, we characterized the functional properties of Spike glycoproteins from BA.2.75, CH.1.1, DV.7.1, BA.4/5, BQ.1.1, XBB, XBB.1, XBB.1.16, XBB.1.5, FD.1.1, EG.5.1, HK.3 BA.2.86 and JN.1. We tested their capacity to evade plasma-mediated recognition and neutralization, ACE2 binding, their susceptibility to cold inactivation, Spike processing, as well as the impact of temperature on Spike-ACE2 interaction. We found that compared to the early wild-type (D614G) strain, most Omicron subvariants Spike glycoproteins evolved to escape recognition and neutralization by plasma from individuals who received a fifth dose of bivalent (BA.1 or BA.4/5) mRNA vaccine and improve ACE2 binding, particularly at low temperatures. Moreover, BA.2.86 had the best affinity for ACE2 at all temperatures tested. We found that Omicron subvariants Spike processing is associated with their susceptibility to cold inactivation. Intriguingly, we found that Spike-ACE2 binding at low temperature was significantly associated with growth rates of Omicron subvariants in humans. Overall, we report that Spikes from newly emerged Omicron subvariants are relatively more stable and resistant to plasma-mediated neutralization, present improved affinity for ACE2 which is associated, particularly at low temperatures, with their growth rates.
2024-07-02
mBio (publié)
doi.org
A responsible framework for applying artificial intelligence on medical images and signals at the point-of-care: the PACS-AI platform.
Pascal Thériault-Lauzier
Denis Cobin
Olivier Tastet
Élodie Labrecque Langlais
B. Taji
Guson Kang
A. Chong
Derek So
An Tang
J. W. Gichoya
Sarath Chandar
Pierre-Luc Deziel
Julie Hussin
Samuel Kadoury
Robert Avram
2024-06-01
Canadian Journal of Cardiology (publié)
doi.org
A responsible framework for applying artificial intelligence on medical images and signals at the point-of-care: the PACS-AI platform.
Pascal Thériault-Lauzier
Denis Cobin
Olivier Tastet
Élodie Labrecque Langlais
B. Taji
Guson Kang
A. Chong
Derek So
An Tang
J. W. Gichoya
Sarath Chandar
Pierre-Luc Deziel
Julie Hussin
Samuel Kadoury
Robert Avram
2024-06-01
Canadian Journal of Cardiology (publié)
doi.org
A responsible framework for applying artificial intelligence on medical images and signals at the point-of-care: the PACS-AI platform.
Pascal Thériault-Lauzier
Denis Cobin
Olivier Tastet
Élodie Labrecque Langlais
B. Taji
Guson Kang
A. Chong
Derek So
An Tang
J. W. Gichoya
Sarath Chandar
Pierre-Luc Deziel
Julie Hussin
Samuel Kadoury
Robert Avram
2024-06-01
Canadian Journal of Cardiology (publié)
doi.org
The Canadian VirusSeq Data Portal & Duotang: open resources for SARS-CoV-2 viral sequences and genomic epidemiology
Erin E. Gill
Baofeng Jia
Carmen Lia Murall
Raphael Poujol
Muhammad Zohaib Anwar
Nithu Sara John
Justin Richardsson
Ashley Hobb
Abayomi S. Olabode
Alexandru Lepsa
Ana T. Duggan
Andrea D. Tyler
Arnaud N’Guessan
Atul Kachru
Brandon Chan
Catherine Yoshida
Christina K. Yung
David Bujold
Dusan Andric
Edmund Su … (voir 50 de plus)
Emma J. Griffiths
Gary Van Domselaar
Gordon W. Jolly
Heather K.E. Ward
Henrich Feher
Jared Baker
Jared T. Simpson
Jaser Uddin
Jiannis Ragoussis
Jon Eubank
Jörg H. Fritz
José Héctor Gálvez
Karen Fang
Kim Cullion
Leonardo Rivera
Linda Xiang
Matthew A. Croxen
Mitchell Shiell
Natalie Prystajecky
Pierre-Olivier Quirion
Rosita Bajari
Samantha Rich
Samira Mubareka
Sandrine Moreira
Scott Cain
Steven G. Sutcliffe
Susanne A. Kraemer
Yann Joly
Yelizar Alturmessov
CPHLN consortium
CanCOGeN consortium
VirusSeq Data Portal Academic
Health Network
Marc Fiume
Terrance P. Snutch
Cindy Bell
Catalina Lopez-Correa
Julie Hussin
Jeffrey B. Joy
Caroline Colijin
Paul M.K. Gordon
William W.L. Hsiao
Art F.Y. Poon
Natalie C. Knox
Mélanie Courtot
Lincoln Stein
Sarah P. Otto
Guillaume Bourque
B. Jesse Shapiro
Fiona S.L. Brinkman
2024-05-08
ArXiv (prépublication)
arxiv.org
arxiv.org
Intra-Host Evolution Analyses in an Immunosuppressed Patient Supports SARS-CoV-2 Viral Reservoir Hypothesis
Dominique Fournelle
Fatima Mostefai
Elsa Brunet-Ratnasingham
Raphael Poujol
Jean-Christophe Grenier
José Héctor Gálvez
Amélie Pagliuzza
Inès Levade
Sandrine Moreira
Mehdi Benlarbi
Guillaume Beaudoin-Bussières
Gabrielle Gendron-Lepage
Catherine Bourassa
Alexandra Tauzin
Simon Grandjean Lapierre
Nicolas Chomont
Andrés Finzi
Daniel E. Kaufmann
Morgan Craig
Julie Hussin
Throughout the SARS-CoV-2 pandemic, several variants of concern (VOCs) have been identified, many of which share recurrent mutations in the … (voir plus)spike glycoprotein’s receptor-binding domain (RBD). This region coincides with known epitopes and can therefore have an impact on immune escape. Protracted infections in immunosuppressed patients have been hypothesized to lead to an enrichment of such mutations and therefore drive evolution towards VOCs. Here, we present the case of an immunosuppressed patient that developed distinct populations with immune escape mutations throughout the course of their infection. Notably, by investigating the co-occurrence of substitutions on individual sequencing reads in the RBD, we found quasispecies harboring mutations that confer resistance to known monoclonal antibodies (mAbs) such as S:E484K and S:E484A. These mutations were acquired without the patient being treated with mAbs nor convalescent sera and without them developing a detectable immune response to the virus. We also provide additional evidence for a viral reservoir based on intra-host phylogenetics, which led to a viral substrain that evolved elsewhere in the patient’s body, colonizing their upper respiratory tract (URT). The presence of SARS-CoV-2 viral reservoirs can shed light on protracted infections interspersed with periods where the virus is undetectable, and potential explanations for long-COVID cases.
2024-02-23
Viruses (publié)
doi.org
Intra-Host Evolution Analyses in an Immunosuppressed Patient Supports SARS-CoV-2 Viral Reservoir Hypothesis
Dominique Fournelle
Fatima Mostefai
Elsa Brunet-Ratnasingham
Raphael Poujol
Jean-Christophe Grenier
José Héctor Gálvez
Amélie Pagliuzza
Inès Levade
Sandrine Moreira
Mehdi Benlarbi
Guillaume Beaudoin-Bussières
Gabrielle Gendron-Lepage
Catherine Bourassa
Alexandra Tauzin
Simon Grandjean Lapierre
Nicolas Chomont
Andrés Finzi
Daniel E. Kaufmann
Morgan Craig
Julie Hussin
2024-02-23
Viruses (publié)
doi.org
Intra-Host Evolution Analyses in an Immunosuppressed Patient Supports SARS-CoV-2 Viral Reservoir Hypothesis
Dominique Fournelle
Fatima Mostefai
Elsa Brunet-Ratnasingham
Raphael Poujol
Jean-Christophe Grenier
José Héctor Gálvez
Amélie Pagliuzza
Inès Levade
Sandrine Moreira
Mehdi Benlarbi
Guillaume Beaudoin-Bussières
Gabrielle Gendron-Lepage
Catherine Bourassa
Alexandra Tauzin
Simon Grandjean Lapierre
Nicolas Chomont
Andrés Finzi
Daniel E. Kaufmann
Morgan Craig
Julie Hussin
Throughout the SARS-CoV-2 pandemic, several variants of concern (VOCs) have been identified, many of which share recurrent mutations in the … (voir plus)spike glycoprotein’s receptor-binding domain (RBD). This region coincides with known epitopes and can therefore have an impact on immune escape. Protracted infections in immunosuppressed patients have been hypothesized to lead to an enrichment of such mutations and therefore drive evolution towards VOCs. Here, we present the case of an immunosuppressed patient that developed distinct populations with immune escape mutations throughout the course of their infection. Notably, by investigating the co-occurrence of substitutions on individual sequencing reads in the RBD, we found quasispecies harboring mutations that confer resistance to known monoclonal antibodies (mAbs) such as S:E484K and S:E484A. These mutations were acquired without the patient being treated with mAbs nor convalescent sera and without them developing a detectable immune response to the virus. We also provide additional evidence for a viral reservoir based on intra-host phylogenetics, which led to a viral substrain that evolved elsewhere in the patient’s body, colonizing their upper respiratory tract (URT). The presence of SARS-CoV-2 viral reservoirs can shed light on protracted infections interspersed with periods where the virus is undetectable, and potential explanations for long-COVID cases.
2024-02-23
Viruses (publié)
doi.org
Signatures of Co-evolution and Co-regulation in the CYP3A and CYP4F Genes in Humans
Alex Richard-St-Hilaire
Isabel Gamache
Justin Pelletier
Jean-Christophe Grenier
Raphael Poujol
Julie Hussin
2024-01-11
Genome Biology and Evolution (publié)
doi.org
Genetic landscape of an in vivo protein interactome
Savandara Besse
Tatsuya Sakaguchi
Louis Gauthier
Zahra Sahaf
Olivier Péloquin
Lidice Gonzalez
Xavier Castellanos-Girouard
Nazli Koçatug
Chloé Matta
Julie Hussin
Stephen W. Michnick
Adrian W.R. Serohijos
2023-12-15
bioRxiv (prépublication)
doi.org
Gene-metabolite annotation with shortest reactional distance enhances metabolite genome-wide association studies results
Cantin Baron
Sarah Cherkaoui
Sandra Therrien-Laperriere
Yann Ilboudo
Raphael Poujol
Pamela Mehanna
Melanie E. Garrett
Marilyn J. Telen
Allison E. Ashley-Koch
Pablo Bartolucci
John D. Rioux
Guillaume Lettre
Christine Des Rosiers
Matthieu Ruiz
Julie Hussin
Studies combining metabolomics and genetics, known as metabolite genome-wide association studies (mGWAS), have provided valuable insights in… (voir plus)to our understanding of the genetic control of metabolite levels. However, the biological interpretation of these associations remains challenging due to a lack of existing tools to annotate mGWAS gene-metabolite pairs beyond the use of conservative statistical significance threshold. Here, we computed the shortest reactional distance (SRD) based on the curated knowledge of the KEGG database to explore its utility in enhancing the biological interpretation of results from three independent mGWAS, including a case study on sickle cell disease patients. Results show that, in reported mGWAS pairs, there is an excess of small SRD values and that SRD values and p-values significantly correlate, even beyond the standard conservative thresholds. The added-value of SRD annotation is shown for identification of potential false negative hits, exemplified by the finding of gene-metabolite associations with SRD ≤1 that did not reach standard genome-wide significance cut-off. The wider use of this statistic as an mGWAS annotation would prevent the exclusion of biologically relevant associations and can also identify errors or gaps in current metabolic pathway databases. Our findings highlight the SRD metric as an objective, quantitative and easy-to-compute annotation for gene-metabolite pairs that can be used to integrate statistical evidence to biological networks.
2023-11-01
iScience (publié)
doi.org