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1. Sparse Factor Analysis for Categorical Data with the Group-Sparse Generalized Singular Value Decomposition

Author

Yu, Ju-Chi, Borgne, Julie Le, Krishnan, Anjali, Gloaguen, Arnaud, Yang, Cheng-Ta, Rabin, Laura A, Abdi, Hervé, and Guillemot, Vincent

Subjects
Mathematics - Statistics Theory
Abstract

Correspondence analysis, multiple correspondence analysis and their discriminant counterparts (i.e., discriminant simple correspondence analysis and discriminant multiple correspondence analysis) are methods of choice for analyzing multivariate categorical data. In these methods, variables are integrated into optimal components computed as linear combinations whose weights are obtained from a generalized singular value decomposition (GSVD) that integrates specific metric constraints on the rows and columns of the original data matrix. The weights of the linear combinations are, in turn, used to interpret the components, and this interpretation is facilitated when components are 1) pairwise orthogonal and 2) when the values of the weights are either large or small but not intermediate-a pattern called a simple or a sparse structure. To obtain such simple configurations, the optimization problem solved by the GSVD is extended to include new constraints that implement component orthogonality and sparse weights. Because multiple correspondence analysis represents qualitative variables by a set of binary variables, an additional group constraint is added to the optimization problem in order to sparsify the whole set representing one qualitative variable. This new algorithm-called group-sparse GSVD (gsGSVD)-integrates these constraints via an iterative projection scheme onto the intersection of subspaces where each subspace implements a specific constraint. In this paper, we expose this new algorithm and show how it can be adapted to the sparsification of simple and multiple correspondence analysis, and illustrate its applications with the analysis of four different data sets-each illustrating the sparsification of a particular CA-based analysis.

Published
2024

2. covSTATIS: a multi-table technique for network neuroscience

Author

Baracchini, Giulia, Yu, Ju-Chi, Rieck, Jenny, Beaton, Derek, Guillemot, Vincent, Grady, Cheryl, Abdi, Herve, and Spreng, R. Nathan

Subjects
Quantitative Biology - Quantitative Methods
Abstract

Similarity analyses between multiple correlation or covariance tables constitute the cornerstone of network neuroscience. Here, we introduce covSTATIS, a versatile, linear, unsupervised multi-table method designed to identify structured patterns in multi-table data, and allow for the simultaneous extraction and interpretation of both individual and group-level features. With covSTATIS, multiple similarity tables can now be easily integrated, without requiring a priori data simplification, complex black-box implementations, user-dependent specifications, or supervised frameworks. Applications of covSTATIS, a tutorial with Open Data and source code are provided. CovSTATIS offers a promising avenue for advancing the theoretical and analytic landscape of network neuroscience., Comment: The first two authors contributed equally to this work

Published
2024

3. IL-23 tunes inflammatory functions of human mucosal-associated invariant T cells

Author

Camard, Laetitia, Stephen, Tharshana, Yahia-Cherbal, Hanane, Guillemot, Vincent, Mella, Sébastien, Baillet, Victoire, Lopez-Maestre, Hélène, Capocefalo, Daniele, Cantini, Laura, Leloup, Claire, Marsande, Julie, Garro, Katherine, Sienes Bailo, Juan, Dangien, Ambre, Pietrosemoli, Natalia, Hasan, Milena, Wang, Huimeng, Eckle, Sidonia B.G., Fourie, Anne M., Greving, Carrie, Joyce-Shaikh, Barbara, Parker, Raphaelle, Cua, Daniel J., Bianchi, Elisabetta, and Rogge, Lars

Published
2025
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4. Adjusting for Principal Components of Molecular Phenotypes Induces Replicating False Positives

Author

Dahl, Andy, Guillemot, Vincent, Mefford, Joel, Aschard, Hugues, and Zaitlen, Noah

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Human Genome, Animals, Genome-Wide Association Study, Humans, Models, Genetic, Phenotype, Principal Component Analysis, Quantitative Trait Loci, Reproducibility of Results, confounder, molecular trait, quantitative trait loci, eigenvector perturbation, Developmental Biology, Biochemistry and cell biology
Abstract

High-throughput measurements of molecular phenotypes provide an unprecedented opportunity to model cellular processes and their impact on disease. These highly structured datasets are usually strongly confounded, creating false positives and reducing power. This has motivated many approaches based on principal components analysis (PCA) to estimate and correct for confounders, which have become indispensable elements of association tests between molecular phenotypes and both genetic and nongenetic factors. Here, we show that these correction approaches induce a bias, and that it persists for large sample sizes and replicates out-of-sample. We prove this theoretically for PCA by deriving an analytic, deterministic, and intuitive bias approximation. We assess other methods with realistic simulations, which show that perturbing any of several basic parameters can cause false positive rate (FPR) inflation. Our experiments show the bias depends on covariate and confounder sparsity, effect sizes, and their correlation. Surprisingly, when the covariate and confounder have [Formula: see text], standard two-step methods all have [Formula: see text]-fold FPR inflation. Our analysis informs best practices for confounder correction in genomic studies, and suggests many false discoveries have been made and replicated in some differential expression analyses.

Published
2019

7. Behavioural disinhibition in frontotemporal dementia investigated within an ecological framework

Author

Batrancourt, Bénédicte, Azuar, Carole, Dubois, Bruno, Lecouturier, Karen, Araujo, Carla M., Janvier, Estelle, Jourdain, Aline, Rametti-Lacroux, Armelle, Coriou, Sophie, Brochard, Vanessa B., Gaudebout, Cécile, Ferrand-Verdejo, Johan, Bonnefous, Louis, Pochan-Leva, Flore, Jeanne, Lucie, Joulié, Mathilde, Provost, Myriam, Renaud, Rozenn, Hachemi, Sarah, Guillemot, Vincent, Bendetowicz, David, Carle, Guilhem, Socha, Julie, Pineau, Fanny, Marin, Frédéric, Liu, Yongjian, Mullot, Pierre, Mousli, Aymen, Blossier, Armelle, Visentin, Giulia, Tanguy, Delphine, Godefroy, Valérie, Sezer, Idil, Boucly, Mathilde, Cabrol-Douat, Blandine, Odobez, Raphaëlle, Marque, Constance, Tessereau-Barbot, Daphné, Raud, Anaïs, Funkiewiez, Aurélie, Chamayou, Céline, Cognat, Emmanuel, Le Bozec, Manon, Bouzigues, Arabella, Le Du, Vincent, Bombois, Stéphanie, Simard, Camille, Fulcheri, Paolo, Guitton, Hortense, Peltier, Caroline, Lejeune, François-Xavier, Jorgensen, Lars, Mariani, Louise-Laure, Corvol, Jean-Christophe, Valero-Cabre, Antoni, Garcin, Béatrice, Volle, Emmanuelle, Le Ber, Isabelle, Migliaccio, Raffaella, Levy, Richard, Saracino, Dario, Morandi, Xavier, and Jannin, Pierre

Published
2022
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8. A general multiblock method for structured variable selection

Author

Löfstedt, Tommy, Hadj-Selem, Fouad, Guillemot, Vincent, Philippe, Cathy, Raymond, Nicolas, Duchesney, Edouard, Frouin, Vincent, and Tenenhaus, Arthur

Subjects
Statistics - Machine Learning
Abstract

Regularised canonical correlation analysis was recently extended to more than two sets of variables by the multiblock method Regularised generalised canonical correlation analysis (RGCCA). Further, Sparse GCCA (SGCCA) was proposed to address the issue of variable selection. However, for technical reasons, the variable selection offered by SGCCA was restricted to a covariance link between the blocks (i.e., with $\tau=1$). One of the main contributions of this paper is to go beyond the covariance link and to propose an extension of SGCCA for the full RGCCA model (i.e., with $\tau\in[0, 1]$). In addition, we propose an extension of SGCCA that exploits structural relationships between variables within blocks. Specifically, we propose an algorithm that allows structured and sparsity-inducing penalties to be included in the RGCCA optimisation problem. The proposed multiblock method is illustrated on a real three-block high-grade glioma data set, where the aim is to predict the location of the brain tumours, and on a simulated data set, where the aim is to illustrate the method's ability to reconstruct the true underlying weight vectors., Comment: 24 pages, 5 figures

Published
2016

9. Continuation of Nesterov's Smoothing for Regression with Structured Sparsity in High-Dimensional Neuroimaging

Author

Hadj-Selem, Fouad, Lofstedt, Tommy, Dohmatob, Elvis, Frouin, Vincent, Dubois, Mathieu, Guillemot, Vincent, and Duchesnay, Edouard

Subjects
Statistics - Machine Learning
Abstract

Predictive models can be used on high-dimensional brain images for diagnosis of a clinical condition. Spatial regularization through structured sparsity offers new perspectives in this context and reduces the risk of overfitting the model while providing interpretable neuroimaging signatures by forcing the solution to adhere to domain-specific constraints. Total Variation (TV) enforces spatial smoothness of the solution while segmenting predictive regions from the background. We consider the problem of minimizing the sum of a smooth convex loss, a non-smooth convex penalty (whose proximal operator is known) and a wide range of possible complex, non-smooth convex structured penalties such as TV or overlapping group Lasso. Existing solvers are either limited in the functions they can minimize or in their practical capacity to scale to high-dimensional imaging data. Nesterov's smoothing technique can be used to minimize a large number of non-smooth convex structured penalties but reasonable precision requires a small smoothing parameter, which slows down the convergence speed. To benefit from the versatility of Nesterov's smoothing technique, we propose a first order continuation algorithm, CONESTA, which automatically generates a sequence of decreasing smoothing parameters. The generated sequence maintains the optimal convergence speed towards any globally desired precision. Our main contributions are: To propose an expression of the duality gap to probe the current distance to the global optimum in order to adapt the smoothing parameter and the convergence speed. We provide a convergence rate, which is an improvement over classical proximal gradient smoothing methods. We demonstrate on both simulated and high-dimensional structural neuroimaging data that CONESTA significantly outperforms many state-of-the-art solvers in regard to convergence speed and precision., Comment: 11 pages, 6 figures, accepted in IEEE TMI, IEEE Transactions on Medical Imaging 2018

Published
2016

10. Covariate selection for association screening in multiphenotype genetic studies

Author

Aschard, Hugues, Guillemot, Vincent, Vilhjalmsson, Bjarni, Patel, Chirag J, Skurnik, David, Ye, Chun J, Wolpin, Brian, Kraft, Peter, and Zaitlen, Noah

Subjects
Biological Sciences, Genetics, Algorithms, Genetic Association Studies, Genetic Variation, Genome-Wide Association Study, Genotype, Humans, Models, Genetic, Multivariate Analysis, Phenotype, Reproducibility of Results, Sample Size, Medical and Health Sciences, Developmental Biology, Agricultural biotechnology, Bioinformatics and computational biology
Abstract

Testing for associations in big data faces the problem of multiple comparisons, wherein true signals are difficult to detect on the background of all associations queried. This difficulty is particularly salient in human genetic association studies, in which phenotypic variation is often driven by numerous variants of small effect. The current strategy to improve power to identify these weak associations consists of applying standard marginal statistical approaches and increasing study sample sizes. Although successful, this approach does not leverage the environmental and genetic factors shared among the multiple phenotypes collected in contemporary cohorts. Here we developed covariates for multiphenotype studies (CMS), an approach that improves power when correlated phenotypes are measured on the same samples. Our analyses of real and simulated data provide direct evidence that correlated phenotypes can be used to achieve increases in power to levels often surpassing the power gained by a twofold increase in sample size.

Published
2017

12. Sparse Multiple Factor Analysis, sparse STATIS, and sparse DiSTATIS with applications to sensory evaluation.

Author

Yu, Ju‐Chi, Gómez‐Corona, Carlos, Abdi, Hervé, and Guillemot, Vincent

Subjects
FACTOR analysis, SENSORY evaluation, APPRAISERS, DATA analysis, CHEMOMETRICS
Abstract

Component‐based multitable methods, such as multiple factor analysis (MFA), STATIS, and DiSTATIS, are routinely used to analyze multiblock data, which are now common in chemometrics and sensory evaluation studies. These blocks of data form data tables that—for example, in sensory evaluation—describe how different assessors evaluate a set of products either on a set of descriptors or on the similarity between products. To analyze these data, component‐based multitable methods extract orthogonal components explaining most of the variance of the data. However, when the data tables are heterogeneous or have complex structures, a single component space does not represent the data well and can give components that are difficult to interpret. Previous literature solved this interpretation problem by eliminating irrelevant variables—a process called sparsification—while keeping the components orthogonal. Here, we extended such methods to develop sparsification algorithms for three multitable methods, namely, "sparse MFA" (sMFA), "sparse STATIS" (sSTATIS), and "sparse DiSTATIS" (sDiSTATIS). In these sparse methods, we sparsified the data tables to identify the most informative assessors or products. In sMFA, we show how group sparsity can be used to sparsify whole tables (i.e., assessors or products), hereby greatly increasing the interpretability of sMFA's outcome. In sSTATIS and sDiSTATIS, we developed two different sparsification approaches: One approach creates subgroups of products and simplifies the components to facilitate interpretation; whereas the other approach creates subgroups of assessors and alleviates the problem of heterogeneity. We showed with three examples how these sparse methods increase interpretability of the results in sensory evaluation. Multitable data sets are becoming more and more common in chemometrics and sensory evaluation studies. The analysis of such data is complex, mostly due to the complex structure of each table combined with the complex interrelationships between tables. We present a way to sparsify three well‐known methods for analyzing multitable data: Multiple Factor Analysis, STATIS, and DiSTATIS. We show how sparsifying increases the interpretability of the results on two sensory evaluation data sets. [ABSTRACT FROM AUTHOR]

Published
2024
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15. Behavioural disinhibition in frontotemporal dementia investigated within an ecological framework

Author

Tanguy, Delphine, primary, Rametti-Lacroux, Armelle, additional, Bouzigues, Arabella, additional, Saracino, Dario, additional, Le Ber, Isabelle, additional, Godefroy, Valérie, additional, Morandi, Xavier, additional, Jannin, Pierre, additional, Levy, Richard, additional, Batrancourt, Bénédicte, additional, Migliaccio, Raffaella, additional, Azuar, Carole, additional, Dubois, Bruno, additional, Lecouturier, Karen, additional, Araujo, Carla M., additional, Janvier, Estelle, additional, Jourdain, Aline, additional, Coriou, Sophie, additional, Brochard, Vanessa B., additional, Gaudebout, Cécile, additional, Ferrand-Verdejo, Johan, additional, Bonnefous, Louis, additional, Pochan-Leva, Flore, additional, Jeanne, Lucie, additional, Joulié, Mathilde, additional, Provost, Myriam, additional, Renaud, Rozenn, additional, Hachemi, Sarah, additional, Guillemot, Vincent, additional, Bendetowicz, David, additional, Carle, Guilhem, additional, Socha, Julie, additional, Pineau, Fanny, additional, Marin, Frédéric, additional, Liu, Yongjian, additional, Mullot, Pierre, additional, Mousli, Aymen, additional, Blossier, Armelle, additional, Visentin, Giulia, additional, Tanguy, Delphine, additional, Sezer, Idil, additional, Boucly, Mathilde, additional, Cabrol-Douat, Blandine, additional, Odobez, Raphaëlle, additional, Marque, Constance, additional, Tessereau-Barbot, Daphné, additional, Raud, Anaïs, additional, Funkiewiez, Aurélie, additional, Chamayou, Céline, additional, Cognat, Emmanuel, additional, Le Bozec, Manon, additional, Le Du, Vincent, additional, Bombois, Stéphanie, additional, Simard, Camille, additional, Fulcheri, Paolo, additional, Guitton, Hortense, additional, Peltier, Caroline, additional, Lejeune, François-Xavier, additional, Jorgensen, Lars, additional, Mariani, Louise-Laure, additional, Corvol, Jean-Christophe, additional, Valero-Cabre, Antoni, additional, Garcin, Béatrice, additional, and Volle, Emmanuelle, additional

Published
2023
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17. Multiblock data analysis with the RGCCA package

Author

Girka, Fabien, Camenen, Etienne, Peltier, Caroline, Guillemot, Vincent, Le Brusquet, Laurent, Tenenhaus, Arthur, Laboratoire des signaux et systèmes (L2S), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Institut du Cerveau = Paris Brain Institute (ICM), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Centre des Sciences du Goût et de l'Alimentation [Dijon] (CSGA), Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Dijon, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), Plateforme Chemosens [Dijon], Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Bourgogne (UB)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Dijon, Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB, Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), UDOPIA + the European Union’s Horizon 2020 research and innovation program + the AP-HP Foundation, within the framework of the AIRACLES Chair., Projet RGCCA, ANR-20-THIA-0013,UDOPIA,Programme Doctoral en Intelligence Artificielle de l'Université Paris-Saclay(2020), and European Project: 874583,H2020,H2020-EU.3.1.2.,ATHLETE(2020)

Subjects
[MATH.MATH-PR]Mathematics [math]/Probability [math.PR], RGCCA, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Multiblock component methods, data integration
Abstract

International audience; Multiblock component methods aim to study the relationships between several sets of variables. Regularized Generalized Canonical Correlation Analysis (RGCCA) is a unified and flexible framework that gathers fifty years of multiblock component methods. RGCCA offers a unified implementation strategy for all these methods. This implementation is made available within the RGCCA package. In addition, the RGCCA package produces graphical outputs and statistics to assess the robustness/significance of the analysis. The usefulness of the RGCCA package is illustrated in this paper on two real datasets. The RGCCA package is freely available on the ComprehensiveR Archive Network (CRAN) http://www.r-project.org/ and GitHub https://github.com/rgcca-factory/RGCCA.

Published
2023
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21. Etude de la Pénalisation GraphNet en Analyse de Données Multi-blocs

Author

Beaudoin, Annabelle, Pietrosemoli, Natalia, Philippe, Cathy, Abdi, Hervé, Guillemot, Vincent, Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics, Institut Pasteur [Paris] (IP), Building large instruments for neuroimaging: from population imaging to ultra-high magnetic fields (BAOBAB), Service NEUROSPIN (NEUROSPIN), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Centre National de la Recherche Scientifique (CNRS), and University of Texas at Dallas [Richardson] (UT Dallas)

Subjects
[STAT]Statistics [stat]
Abstract

International audience; L'intégration de données multiblocs est maintenant incontournable pour analyser des données complexes allant, par exemple, des données multi-omiques, aux données d'imagerie génétique. Par ailleurs, les bases de données biologiques de référence contiennent maintenant une information très riche qu'il convient d'intégrer dans de telles analyses.Nous proposons d'explorer la méthode netSGCCA qui permet l'intégration de réseaux dans le cadre de l'Analyse des Corrélations Canonique Généralisée pénalisée à l'aide d'une pénalité GraphNet. Plus particulièrement, nous souhaitons mettre en lumière un des désavantages de cette pénalité, qui est d'introduire des composantes ``haute-fréquence''.L'exemple que nous étudions est issu d'une étude clinique sur la Spondylarthrite ankylosante et comprend trois blocs : deux blocs de données d'expression, et un bloc de données cliniques. Le réseau de référence que nous utilisons est extrait de la base de données STRING-DB. Nous montrons sur cet exemple un moyen de ne conserver que les éléments ``basse fréquence'' induits par l'introduction de la pénalité GraphNet.

Published
2022

22. Integrating multiomics and prior knowledge: a study of the Graphnet penalty impact.

Author

Chegraoui, Hamza, Guillemot, Vincent, Rebei, Amine, Gloaguen, Arnaud, Grill, Jacques, Philippe, Cathy, and Frouin, Vincent

Subjects
*MULTIOMICS, *PRIOR learning, *STATISTICAL models, *SOURCE code, *BIOMARKERS, *FEATURE selection
Abstract

Motivation In the field of oncology, statistical models are used for the discovery of candidate factors that influence the development of the pathology or its outcome. These statistical models can be designed in a multiblock framework to study the relationship between different multiomic data, and variable selection is often achieved by imposing constraints on the model parameters. A priori graph constraints have been used in the literature as a way to improve feature selection in the model, yielding more interpretability. However, it is still unclear how these graphs interact with the models and how they impact the feature selection. Additionally, with the availability of different graphs encoding different information, one can wonder how the choice of the graph meaningfully impacts the results obtained. Results We proposed to study the graph penalty impact on a multiblock model. Specifically, we used the SGCCA as the multiblock framework. We studied the effect of the penalty on the model using the TCGA-LGG dataset. Our findings are 3-fold. We showed that the graph penalty increases the number of selected genes from this dataset, while selecting genes already identified in other works as pertinent biomarkers in the pathology. We demonstrated that using different graphs leads to different though consistent results, but that graph density is the main factor influencing the obtained results. Finally, we showed that the graph penalty increases the performance of the survival prediction from the model-derived components and the interpretability of the results. Availability and implementation Source code is freely available at https://github.com/neurospin/netSGCCA [ABSTRACT FROM AUTHOR]

Published
2023
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23. Hypomorphic variants of cationic amino acid transporter 3 in males with autism spectrum disorders

Author

Nava, Caroline, Rupp, Johanna, Boissel, Jean-Paul, Mignot, Cyril, Rastetter, Agnès, Amiet, Claire, Jacquette, Aurélia, Dupuits, Céline, Bouteiller, Delphine, Keren, Boris, Ruberg, Merle, Faudet, Anne, Doummar, Diane, Philippe, Anne, Périsse, Didier, Laurent, Claudine, Lebrun, Nicolas, Guillemot, Vincent, Chelly, Jamel, Cohen, David, Héron, Delphine, Brice, Alexis, Closs, Ellen I., and Depienne, Christel

Published
2015
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26. Immune response profiling of patients with spondyloarthritis reveals signalling networks mediating TNF-blocker function in vivo

Author

Menegatti, Silvia, Guillemot, Vincent, Latis, Eleonora, Yahia-Cherbal, Hanane, Mittermüller, Daniela, Rouilly, Vincent, Mascia, Elena, Rosine, Nicolas, Koturan, Surya, Millot, Gaël, Leloup, Claire, Duffy, Darragh, Gleizes, Aude, Hacein-Bey-Abina, Salima, The Milieu Interieur, Consortium, Sellam, Jérémie, Berenbaum, Francis, Miceli-Richard, Corinne, Dougados, Maxime, Bianchi, Elisabetta, Rogge, Lars, Immunorégulation - Immunoregulation, Institut Pasteur [Paris], Université Sorbonne Paris Cité (USPC), Immunité et cancer (U932), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Curie [Paris], Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Datactix, Immunologie Translationnelle - Translational Immunology lab, Service de Médecine Interne - Immunologie Clinique [AP-HP Bicêtre], AP-HP Hôpital Bicêtre (Le Kremlin-Bicêtre), Unité de Technologies Chimiques et Biologiques pour la Santé (UTCBS - UM 4 (UMR 8258 / U1022)), Institut de Chimie du CNRS (INC)-Université de Paris (UP)-Centre National de la Recherche Scientifique (CNRS)-Institut National de la Santé et de la Recherche Médicale (INSERM), Service de rhumatologie [CHU Saint-Antoine], CHU Saint-Antoine [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Centre de Recherche Saint-Antoine (CR Saint-Antoine), Sorbonne Université (SU)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Saint-Antoine [AP-HP], Université Paris Descartes - Paris 5 (UPD5), Service de rhumatologie [CHU Cochin], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Cochin [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Equipe 2 : ECSTRA - Epidémiologie Clinique, STatistique, pour la Recherche en Santé (CRESS - U1153), Centre de Recherche Épidémiologie et Statistique Sorbonne Paris Cité (CRESS (U1153 / UMR_A_1125 / UMR_S_1153)), Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), SM was a scholar of the Pasteur-Paris University (PPU) International PhD programme and supported by a grant from the Fondation pour la Recherche Médicale. EL was supported by a fellowship from the Université Paris Diderot. This study was Institut Pasteur, the French Government’s Investissement d’Avenir Programme, Laboratoire d’Excellence 'Milieu Intérieur' (ANR-10-LABX-69-01), FOREUM Foundation for Research in Rheumatology, the Fondation Arthritis, MSD Avenir (Project iCARE-SpA), a Bourse Passerelle from Pfizer., Milieu Intérieur Consortium: Laurent Abel, Andres Alcover, Hugues Aschard, Kalla Astrom, Philippe Bousso, Pierre Bruhns, Ana Cumano, Caroline Demangel, Ludovic Deriano, James Di Santo, Françoise Dromer, Gérard Eberl, Jost Enninga, Jacques Fellay, Ivo Gomperts-Boneca, Milena Hasan, Serge Hercberg, Olivier Lantz, Hugo Mouquet, Etienne Patin, Sandra Pellegrini, Stanislas Pol, Antonio Rausell, Lars Rogge, Anavaj Sakuntabhai, Olivier Schwartz, Benno Schwikowski, Spencer Shorte, Frédéric Tangy, Antoine Toubert, Mathilde Trouvier, Marie-Noëlle Ungeheuer, Darragh Duffy, Matthew L. Albert, Lluis Quintana-Murci., ANR-10-LABX-0069,MILIEU INTERIEUR,GENETIC & ENVIRONMENTAL CONTROL OF IMMUNE PHENOTYPE VARIANCE: ESTABLISHING A PATH TOWARDS PERSONALIZED MEDICINE(2010), Institut Pasteur [Paris] (IP), Institut Curie [Paris]-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Centre de Recherche Saint-Antoine (CRSA), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU), Conservatoire National des Arts et Métiers [CNAM] (CNAM), HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), and HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-HESAM Université - Communauté d'universités et d'établissements Hautes écoles Sorbonne Arts et métiers université (HESAM)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)

Subjects
rheumatoid arthritis, 0301 basic medicine, Chemokine, anti-TNF therapy, [SDV]Life Sciences [q-bio], tumor necrosis factor inhibitors, immune system diseases, Immunology, Inflammation, General Biochemistry, Genetics and Molecular Biology, TNF inhibitors, 03 medical and health sciences, 0302 clinical medicine, Immune system, Rheumatology, Immunity, Spondylarthritis, Spondyloarthritis, Humans, Immunology and Allergy, Medicine, Spondylitis, Ankylosing, 030203 arthritis & rheumatology, Innate immune system, biology, Tumor Necrosis Factor-alpha, business.industry, Interleukin, spondylitis, Chemotaxis, 3. Good health, chronic inflammatory diseases, ankylosing, 030104 developmental biology, biological therapy, biology.protein, [SDV.IMM]Life Sciences [q-bio]/Immunology, Cytokines, Tumor necrosis factor alpha, medicine.symptom, business
Abstract

ObjectivesAntitumour necrosis factor (TNF) therapy has revolutionised treatment of several chronic inflammatory diseases, including spondyloarthritis (SpA). However, TNF inhibitors (TNFi) are not effective in all patients and the biological basis for treatment failure remains unknown. We have analysed induced immune responses to define the mechanism of action of TNF blockers in SpA and to identify immunological correlates of responsiveness to TNFi.MethodsImmune responses to microbial and pathway-specific stimuli were analysed in peripheral blood samples from 80 patients with axial SpA before and after TNFi treatment, using highly standardised whole-blood stimulation assays. Cytokines and chemokines were measured in a Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory, and gene expression was monitored using nCounter assays.ResultsAnti-TNF therapy induced profound changes in patients’ innate immune responses. TNFi action was selective, and had only minor effects on Th1/Th17 immunity. Modular transcriptional repertoire analysis identified prostaglandin E2 synthesis and signalling, leucocyte recirculation, macrophage polarisation, dectin and interleukin (IL)-1 signalling, as well as the nuclear factor kappa B (NF-kB) transcription factor family as key pathways targeted by TNF blockers in vivo. Analysis of induced immune responses before treatment initiation revealed that expression of molecules associated with leucocyte adhesion and invasion, chemotaxis and IL-1 signalling are correlated with therapeutic responses to anti-TNF.ConclusionsWe show that TNFi target multiple immune cell pathways that cooperate to resolve inflammation. We propose that immune response profiling provides new insight into the biology of TNF-blocker action in patients and can identify signalling pathways associated with therapeutic responses to biological therapies.

Published
2020
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28. Alterations of the axon initial segment in multiple sclerosis

Author

Senol, Aysegul Dilsizoglu, primary, Pinto, Giulia, additional, Beau, Maxime, additional, Guillemot, Vincent, additional, Dupree, Jeff L., additional, Stadelmann, Christine, additional, Ranft, Jonas, additional, Lubetzki, Catherine, additional, and Davenne, Marc, additional

Published
2022
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29. High prevalence of small intestine bacteria overgrowth and asymptomatic carriage of enteric pathogens in stunted children in Antananarivo, Madagascar

Author

Collard, Jean-Marc, Andrianonimiadana, Lova, Habib, Azimdine, Rakotondrainipiana, Maheninasy, Andriantsalama, Prisca, Randriamparany, Ravaka, Rabenandrasana, M., Weill, François-Xavier, Sauvonnet, Nathalie, Randremanana, Rindra Vatosoa, Guillemot, Vincent, Vonaesch, Pascale, Sansonetti, Philippe, Bidault, Floran, Unité de Bactériologie Expérimentale [Antananarivo, Madagascar] (IPM), Institut Pasteur de Madagascar, Réseau International des Instituts Pasteur (RIIP)-Réseau International des Instituts Pasteur (RIIP), Unité d’Épidémiologie et de Recherche clinique [Antananarivo, Madagascar], Bactéries pathogènes entériques (BPE), Institut Pasteur [Paris] (IP), Pathogénie microbienne moléculaire, Institut Pasteur [Paris] (IP)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics, This project was funded by the Total and Petram Foundations and by Institut Pasteur. LA, PA and RR wages were supported by the Total Foundation and MR wage by the Petram Foundation. PV was supported by an Early Postdoctoral Fellowship (P2EZP3_152159), an Advanced Postdoctoral Fellowship (P300PA_177876) as well as a Return Grant (P3P3PA_17877) from the Swiss National Science Foundation, a Roux-Cantarini Fellowship (2016), a L'Oréal-UNESCO for Women in Science France Fellowship (2017) and an Excellence Scholarship from the University of Basel (Forschungsfonds, 2019)., We wish to thank all participating families, the AFRIBIOTA Consortium, the participating hospitals in Antananarivo, as well as the Institut Pasteur, the Institut Pasteur de Madagascar, and members of the scientific advisory board for their continuous support, Prof. Jean-Louis Demarquez for training sessions to teach the local health professionals the methods used for duodenal aspirations, Aurélie Etienne for precious help with the clinical procedures and first aspirations performed, the field workers Tseheno Harisoa and Rado Andrianantenaina, as well as all implicated community health workers, for countless hours spent in the field, and the Centre de Recherche Translationelle and the Direction Internationale of the Institut Pasteur, and especially Paméla Palvadeau, Jane Lynda Deuve, Marc Rovatiana Ranarijesy, Kanto Liantsoa Razanakolona, Cécile Artaud, Nathalie Jolly, Sophie Jarrijon, Mamy Ratsialonina, Jean-François Damaras, Marie-Noelle Ungeheuer, and Laurence Arowas for precious help in setting up and steering the AFRIBIOTA project and managing the funds and the biobank. We would like to thank the staff of the 'Plateforme de Microbiologie Mutualisée (P2M)' at Institut Pasteur Paris where the whole genome sequencing was performed, Sophie Lefevre from the Centre National de Référence des Escherichia coli, Shigella et Salmonella in Paris, France for Shigella serotyping, and Claude Parsot and Alexandre Grassart for the interesting discussions on Shigella.

Subjects
Adult, Diarrhea, MESH: Intestine, Small, MESH: Bacterial Infections, MESH: Shigella, MESH: Madagascar, Feces, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, MESH: Child, Intestine, Small, Escherichia coli, Madagascar, Prevalence, Humans, Child, MESH: Prevalence, MESH: Humans, Bacteria, MESH: Escherichia coli, digestive, oral, and skin physiology, Public Health, Environmental and Occupational Health, MESH: Feces, MESH: Adult, Bacterial Infections, [SDV.MP.BAC]Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology, MESH: Bacteria, MESH: Diarrhea, Infectious Diseases, [SDV.MHEP.MI] Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Shigella, [SDV.MP.BAC] Life Sciences [q-bio]/Microbiology and Parasitology/Bacteriology
Abstract

Environmental Enteric Dysfunction (EED) refers to an incompletely defined syndrome of inflammation, reduced absorptive capacity, and reduced barrier function in the small intestine. It is widespread among children and adults in low- and middle-income countries and is also associated with poor sanitation and certain gut infections possibly resulting in an abnormal gut microbiota, small intestinal bacterial overgrowth (SIBO) and stunting. We investigated bacterial pathogen exposure in stunted and non-stunted children in Antananarivo, Madagascar by collecting fecal samples from 464 children (96 severely stunted, 104 moderately stunted and 264 non-stunted) and the prevalence of SIBO in 109 duodenal aspirates from stunted children (61 from severely stunted and 48 from moderately stunted children). SIBO assessed by both aerobic and anaerobic plating techniques was very high: 85.3% when selecting a threshold of ≥105 CFU/ml of bacteria in the upper intestinal aspirates. Moreover, 58.7% of the children showed more than 106 bacteria/ml in these aspirates. The most prevalent cultivated genera recovered were Streptococcus, Neisseria, Staphylococcus, Rothia, Haemophilus, Pantoea and Branhamella. Feces screening by qPCR showed a high prevalence of bacterial enteropathogens, especially those categorized as being enteroinvasive or causing mucosal disruption, such as Shigella spp., enterotoxigenic Escherichia coli, enteropathogenic E. coli and enteroaggregative E. coli. These pathogens were detected at a similar rate in stunted children and controls, all showing no sign of severe diarrhea the day of inclusion but both living in a highly contaminated environment (slum-dwelling). Interestingly Shigella spp. was the most prevalent enteropathogen found in this study (83.3%) without overrepresentation in stunted children.

Published
2022
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30. Susceptibilities of CNS Cells towards Rabies Virus Infection Is Linked to Cellular Innate Immune Responses.

Author

Feige, Lena, Kozaki, Tatsuya, Dias de Melo, Guilherme, Guillemot, Vincent, Larrous, Florence, Ginhoux, Florent, and Bourhy, Hervé

Subjects
VIRAL tropism, RABIES virus, VIRUS diseases, IMMUNE response, NEUROGLIA, EXTRACELLULAR matrix proteins
Abstract

Rabies is caused by neurotropic rabies virus (RABV), contributing to 60,000 human deaths annually. Even though rabies leads to major public health concerns worldwide, we still do not fully understand factors determining RABV tropism and why glial cells are unable to clear RABV from the infected brain. Here, we compare susceptibilities and immune responses of CNS cell types to infection with two RABV strains, Tha and its attenuated variant Th2P-4M, mutated on phospho- (P-protein) and matrix protein (M-protein). We demonstrate that RABV replicates in human stem cell-derived neurons and astrocytes but fails to infect human iPSC-derived microglia. Additionally, we observed major differences in transcription profiles and quantification of intracellular protein levels between antiviral immune responses mediated by neurons, astrocytes (IFNB1, CCL5, CXCL10, IL1B, IL6, and LIF), and microglia (CCL5, CXCL10, ISG15, MX1, and IL6) upon Tha infection. We also show that P- and M-proteins of Tha mediate evasion of NF-κB- and JAK-STAT-controlled antiviral host responses in neuronal cell types in contrast to glial cells, potentially explaining the strong neuron-specific tropism of RABV. Further, Tha-infected astrocytes and microglia protect neurons from Tha infection via a filtrable and transferable agent. Overall, our study provides novel insights into RABV tropism, showing the interest in studying the interplay of CNS cell types during RABV infection. [ABSTRACT FROM AUTHOR]

Published
2023
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31. Multitrait GWAS to connect disease variants and biological mechanisms

Author

Julienne, Hanna, Laville, Vincent, Mccaw, Zachary, He, Zihuai, Guillemot, Vincent, Lasry, Carla, Ziyatdinov, Andrey, Nerin, Cyril, Vaysse, Amaury, Lechat, Pierre, Ménager, Hervé, Le Goff, Wilfried, Dube, Marie-Pierre, Kraft, Peter, Ionita-Laza, Iuliana, Vilhjálmsson, Bjarni, Aschard, Hugues, Département de Biologie Computationnelle - Department of Computational Biology, Institut Pasteur [Paris] (IP)-Université Paris Cité (UPCité), Harvard T.H. Chan School of Public Health, Stanford University School of Medicine [CA, USA], Stanford University, Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Institut de Cardiométabolisme et Nutrition = Institute of Cardiometabolism and Nutrition [CHU Pitié Salpêtrière] (IHU ICAN), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Montreal Heart Institute - Institut de Cardiologie de Montréal, Columbia University [New York], Aarhus University [Aarhus], This work has been conducted as part of the INCEPTION program (ANR-16-CONV-0005) (HA). It was also supported by NIH grant R03DE025665 to HA. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript., ANR-16-CONV-0005,INCEPTION,Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs(2016), Aschard, hugues, and Institut Convergences pour l'étude de l'Emergence des Pathologies au Travers des Individus et des populatiONs - - INCEPTION2016 - ANR-16-CONV-0005 - CONV - VALID

Subjects
Single Nucleotide Polymorphisms, QH426-470, Biochemistry, [STAT.AP] Statistics [stat]/Applications [stat.AP], Medicine and Health Sciences, Genetics of the Immune System, Cluster Analysis, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM], RISK, [STAT.AP]Statistics [stat]/Applications [stat.AP], [STAT.ME] Statistics [stat]/Methodology [stat.ME], Covariance, MESH: Polymorphism, Single Nucleotide, MESH: Genetic Predisposition to Disease, Genomics, Lipids, STATISTICS, Phenotypes, Cholesterol, Phenotype, DENSITY-LIPOPROTEIN CHOLESTEROL, Physical Sciences, [STAT.ME]Statistics [stat]/Methodology [stat.ME], MESH: Computational Biology, TRIGLYCERIDES, Research Article, Immunology, Quantitative Trait Loci, [SDV.GEN.GH] Life Sciences [q-bio]/Genetics/Human genetics, MESH: Phenotype, Polymorphism, Single Nucleotide, ESTER TRANSFER PROTEIN, Genetics, Genome-Wide Association Studies, Humans, Genetic Predisposition to Disease, GENOME-WIDE ASSOCIATION, METAANALYSIS, MESH: Humans, CORRELATED TRAITS, MORTALITY, Biology and Life Sciences, Computational Biology, Human Genetics, Random Variables, Genome Analysis, Probability Theory, MESH: Cluster Analysis, MESH: Quantitative Trait Loci, MODEL, [SDV.GEN.GH]Life Sciences [q-bio]/Genetics/Human genetics, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, MESH: Genome-Wide Association Study, Genetics of Disease, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Clinical Immunology, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], Clinical Medicine, Mathematics, Genome-Wide Association Study
Abstract

Genome-wide association studies (GWASs) have uncovered a wealth of associations between common variants and human phenotypes. Here, we present an integrative analysis of GWAS summary statistics from 36 phenotypes to decipher multitrait genetic architecture and its link with biological mechanisms. Our framework incorporates multitrait association mapping along with an investigation of the breakdown of genetic associations into clusters of variants harboring similar multitrait association profiles. Focusing on two subsets of immunity and metabolism phenotypes, we then demonstrate how genetic variants within clusters can be mapped to biological pathways and disease mechanisms. Finally, for the metabolism set, we investigate the link between gene cluster assignment and the success of drug targets in randomized controlled trials., Author summary Genome-wide association studies (GWAS) established numerous associations between genetic variants and human traits. The anonymized summary of GWAS results is generally made publicly available to the scientific community and can be explored further. Amongst the many possible secondary analyses, one is to study the effect of a genetic variant on several traits (multi-trait GWAS) rather than a unique trait. We compared several tests to conduct multi-trait GWAS on simulated and real data. We detected 322 new associations that were not previously reported by standard univariate GWAS. We then detected clusters of genetic variants having a similar effect across several traits. Focusing on two subsets of immunity and metabolism traits, we demonstrate how genetic variants within clusters can be mapped to biological pathways and disease mechanisms. Finally, for the metabolism set, we investigate the link between gene cluster and success of drug targets in randomized controlled trials. We propose this method for improving the functional interpretation of GWAS results.

Published
2021
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32. Introducing group-sparsity and orthogonality constraints in RGCCA

Author

Guillemot, Vincent, Gloaguen, Arnaud, Tenenhaus, Arthur, Philippe, Cathy, Abdi, Hervé, Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB, Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des signaux et systèmes (L2S), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Service NEUROSPIN (NEUROSPIN), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), University of Texas at Dallas [Richardson] (UT Dallas), Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay

Subjects
RGCCA, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], sparsity, structure, group-sparsity
Abstract

International audience; RGCCA-a fast and flexible method-generalizes many other well-known methods in order to analyze data-sets comprising multiple blocks of variables. Here we extend RGCCA by adding two new constraints to the RCCCA optimization problem: 1) group sparsity and 2) orthogonality of the block weight vectors. These two constraints facilitate the interpretability of the results when analyzing high dimensional data with a group structure. We illustrate this new method-called gSGCCA-with the analysis of pediatric high-grade glioma data: a set comprising three data blocks. This analysis shows that these new constraints greatly improve the interpretability of the statistical analysis.; RGCCA est une méthode flexible et rapide qui-généralisant de nombreuses méthodes existantes-permet l'analyse de données structurées en plusieurs blocs hétérogènes. Nous présentons l'ajout dans RGCCA de deux nouvelles contraintes : une contrainte de parcimonie de groupes et une contrainte d'orthogonalité sur les poids de RGCCA. Ces deux contraintes ont pour but d'augmenter l'interprétabilité de l'analyse de données de grande dimension qui possèdent une structure de groupe. Nous appliquons cette nouvelle méthode-abrégée en gSGCCA-à l'analyse de données de gliome malin pédiatrique structurées en trois blocs. Nous montrons sur ces données le gain en interprétabilité apporté par les contraintes de parcimonie et d'orthogonalité.

Published
2021

33. Dichotomous metabolic networks govern human ILC2 proliferation and function

Author

Surace, Laura, primary, Doisne, Jean-Marc, additional, Croft, Carys A., additional, Thaller, Anna, additional, Escoll, Pedro, additional, Marie, Solenne, additional, Petrosemoli, Natalia, additional, Guillemot, Vincent, additional, Dardalhon, Valerie, additional, Topazio, Davide, additional, Cama, Antonia, additional, Buchrieser, Carmen, additional, Taylor, Naomi, additional, Amit, Ido, additional, Musumeci, Olimpia, additional, and Di Santo, James P., additional

Published
2021
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37. Sparse Multiple Correspondence Analysis

Author

Guillemot, Vincent, Le Borgne, Julie, Gloaguen, Arnaud, Tenenhaus, Arthur, Saporta, Gilbert, Chollet, Sylvie, Beaton, Derek, Abdi, Hervé, Hub Bioinformatique et Biostatistique - Bioinformatics and Biostatistics HUB, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Laboratoire des signaux et systèmes (L2S), CentraleSupélec-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Unité Baobab (BAOBAB), Service NEUROSPIN (NEUROSPIN), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, CEDRIC. Méthodes statistiques de data-mining et apprentissage (CEDRIC - MSDMA), Centre d'études et de recherche en informatique et communications (CEDRIC), Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM)-Ecole Nationale Supérieure d'Informatique pour l'Industrie et l'Entreprise (ENSIIE)-Conservatoire National des Arts et Métiers [CNAM] (CNAM), Institut Supérieur d'Agriculture de Lille (ISA), Rotman Research Institute at the Baycrest Centre (RRI), and University of Texas at Dallas [Richardson] (UT Dallas)

Subjects
[STAT]Statistics [stat], Multivariate Analysis, Parcimonie, Multiple Correspondence Analysis, Analyse Multivariée, Sparsity, Analyse des Correspondances Multiples
Abstract

International audience; Multiple Correspondence Analysis (MCA) is the method of choicefor themultivariate analysis of categorical data. In MCA each qualitative variable is representedby a group of binary variables (with a coding scheme called “complete disjunctive coding”)and each binary variable has a weight inversely proportional to its frequency. The datamatrix concatenates all these binary variables, and once normalized and centered thisdata matrix is analyzed with a generalized singular value decomposition (GSVD) thatincorporates the variable weights as constraints (or “metric”). The GSVD is, of course,based on the plain SVD and so MCA can be sparsified by extending algorithms designedto sparsify the SVD. To do so requires two additional features: to include weights andto be able to sparsify entire groups of variables at once. Another important feature ofsuch a sparsification should be to preserve the orthogonality of the components, Here, weintegrate all these constraints by using an exact projection scheme onto the intersectionof subspaces (i.e., balls) where each ball represents a specific type of constraints. Weillustrate our procedure with the data from a questionnaire survey on the perception ofcheese in two French cities.

Published
2020

38. Multitrait genetic-phenotype associations to connect disease variants and biological mechanisms

Author

Julienne, Hanna, primary, Laville, Vincent, additional, McCaw, Zachary R., additional, He, Zihuai, additional, Guillemot, Vincent, additional, Lasry, Carla, additional, Ziyatdinov, Andrey, additional, Vaysse, Amaury, additional, Lechat, Pierre, additional, Ménager, Hervé, additional, Goff, Wilfried Le, additional, Dube, Marie-Pierre, additional, Kraft, Peter, additional, Ionita-Laza, Iuliana, additional, Vilhjálmsson, Bjarni J., additional, and Aschard, Hugues, additional

Published
2020
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40. Heritability of the language network using resting state fMRI data

Author

Mekki, Yasmina, Philippe, Cathy, Guillemot, Vincent, Lemaître, Hervé, Frouin, Vincent, Service NEUROSPIN (NEUROSPIN), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Centre de Bioinformatique, Biostatistique et Biologie Intégrative (C3BI), Institut Pasteur [Paris] (IP)-Centre National de la Recherche Scientifique (CNRS), Neuroimagerie en psychiatrie (U1000), Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université Paris Descartes - Paris 5 (UPD5), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Institut Pasteur [Paris]-Centre National de la Recherche Scientifique (CNRS), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Sud - Paris 11 (UP11), and Université Paris-Sud - Paris 11 (UP11)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Descartes - Paris 5 (UPD5)

Subjects
[SCCO]Cognitive science, [SDV.GEN]Life Sciences [q-bio]/Genetics, [SCCO.NEUR]Cognitive science/Neuroscience, [SDV]Life Sciences [q-bio], [SDV.NEU]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]
Abstract

International audience; Background: Language is a singularity of the human species. It is expected to have a genetic constituent. Estimation of the part of variance attributable to genetic variation across subjects in functional brain imaging within the regions of the language, provide us a quantification of the genetic influence. This part of variance -which corresponds to heritability- is important to prioritize the structural and functional brain features. Language specific tasks fMRI are generally used to achieve this decomposition of variance, but resting state fMRI remains also a valid alternative. Indeed, a growing evidence suggest that resting state functional connectivity pattern could be identified during cognitive task activation. UK Biobank with 19,336 subjects that underwent a rsfMRI, as well as Human Connectome Project (HCP) with 1113 subjects are a unique opportunity to study such a question.Methods: The present work consists in estimating the heritability of the language network, using region of interest, identified by (Pallier, 2011) during a task fMRI experience, based on resting state fMRI connectivity analysis. Imaging genetics data for both cohorts underwent a stringent quality control protocol, yielding 18,851 and 739 samples for UKB and HCP respectively.Results: Significant heritability, estimated via GCTA for UKB and SOLAR for HCP, were observed (UKB: h²=10%-14%, HCP: h²=22%-43%). Multiple test were corrected with Bonferroni correction.Conclusions: The obtained results suggest some genetic influence on the phenotype chosen which indicates that the human language brain organization is under relatively strong genetic control, strong enough to consider association studies with genotyping data.

Published
2019

41. Multidimensional Approaches in the Study of Autistic Traits using Behavioral and Imaging Data

Author

Mihailov, Angeline, Philippe, Cathy, Grigis, Antoine, Guillemot, Vincent, Laidi, Charles, Piguet, Camille, Abdi, Hervé, Houenou, Josselin, Frouin, Vincent, Service NEUROSPIN (NEUROSPIN), Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Unité Analyse et Traitement de l'Information (UNATI), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), UNATI - Unité Analyse et Traitement de l'Information, Institut Pasteur [Paris], Université de Genève (UNIGE), The University of Texas Health Science Center at Houston (UTHealth), Institut Mondor de Recherche Biomédicale (IMRB), Institut National de la Santé et de la Recherche Médicale (INSERM)-IFR10-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Institut Pasteur [Paris] (IP), Université de Genève = University of Geneva (UNIGE), and Mihailov, Angeline

Subjects
[SDV] Life Sciences [q-bio], [SCCO]Cognitive science, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [SCCO.NEUR]Cognitive science/Neuroscience, [SDV]Life Sciences [q-bio], [SCCO.NEUR] Cognitive science/Neuroscience, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, [SCCO] Cognitive science, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2019

42. Supplemental Material for Dahl et al., 2018

Author

Dahl, Andy, Guillemot, Vincent, Mefford, Joel, Aschard, Hugues, and Zaitlen, Noah

Subjects
10401 Applied Statistics, 60412 Quantitative Genetics (incl. Disease and Trait Mapping Genetics), FOS: Biological sciences, mental disorders, Statistics, Genetics, FOS: Mathematics, nutritional and metabolic diseases, 60404 Epigenetics (incl. Genome Methylation and Epigenomics), psychological phenomena and processes, nervous system diseases
Abstract

Supplementary Material for: ``Adjusting for principal components of molecular phenotypes induces replicating false positives''

Published
2019
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43. Approche Multidimensionnelle pour l'étude des traits autistique utilisant des données d'imagerie et de comportement

Author

Mihailov, Angeline, Philippe, Cathy, Grigis, Antoine, Guillemot, Vincent, Laidi, Charles, Piguet, Camille, Abdi, Hervé, Houenou, Josselin, Frouin, Vincent, and Mihailov, Angeline

Subjects
[SDV] Life Sciences [q-bio], [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [SCCO.NEUR] Cognitive science/Neuroscience, [SCCO] Cognitive science
Published
2019

48. A constrained singular value decomposition method that integrates sparsity and orthogonality

Author

Guillemot, Vincent, Beaton, Derek, Gloaguen, Arnaud, Löfstedt, Tommy, Levine, Brian, Raymond, Nicolas, Tenenhaus, Arthur, Abdi, Hervé, Guillemot, Vincent, Beaton, Derek, Gloaguen, Arnaud, Löfstedt, Tommy, Levine, Brian, Raymond, Nicolas, Tenenhaus, Arthur, and Abdi, Hervé

Abstract

We propose a new sparsification method for the singular value decomposition—called the constrained singular value decomposition (CSVD)—that can incorporate multiple constraints such as sparsification and orthogonality for the left and right singular vectors. The CSVD can combine different constraints because it implements each constraint as a projection onto a convex set, and because it integrates these constraints as projections onto the intersection of multiple convex sets. We show that, with appropriate sparsification constants, the algorithm is guaranteed to converge to a stable point. We also propose and analyze the convergence of an efficient algorithm for the specific case of the projection onto the balls defined by the norms L1 and L2. We illustrate the CSVD and compare it to the standard singular value decomposition and to a non-orthogonal related sparsification method with: 1) a simulated example, 2) a small set of face images (corresponding to a configuration with a number of variables much larger than the number of observations), and 3) a psychometric application with a large number of observations and a small number of variables. The companion R-package, csvd, that implements the algorithms described in this paper, along with reproducible examples, are available for download from https://github.com/vguillemot/csvd.

Published
2019
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49. Immune response profiling of patients with spondyloarthritis reveals signalling networks mediating TNF-blocker function in vivo.

Author

Menegatti, Silvia, Guillemot, Vincent, Latis, Eleonora, Yahia-Cherbal, Hanane, Mittermüller, Daniela, Rouilly, Vincent, Mascia, Elena, Rosine, Nicolas, Koturan, Surya, Millot, Gael A., Leloup, Claire, Duffy, Darragh, Gleizes, Aude, Hacein-Bey-Abina, Salima, Consortium, Milieu Intérieur, Sellam, Jérémie, Berenbaum, Francis, Miceli-Richard, Corinne, Dougados, Maxime, and Bianchi, Elisabetta

Abstract

Objectives: Antitumour necrosis factor (TNF) therapy has revolutionised treatment of several chronic inflammatory diseases, including spondyloarthritis (SpA). However, TNF inhibitors (TNFi) are not effective in all patients and the biological basis for treatment failure remains unknown. We have analysed induced immune responses to define the mechanism of action of TNF blockers in SpA and to identify immunological correlates of responsiveness to TNFi.Methods: Immune responses to microbial and pathway-specific stimuli were analysed in peripheral blood samples from 80 patients with axial SpA before and after TNFi treatment, using highly standardised whole-blood stimulation assays. Cytokines and chemokines were measured in a Clinical Laboratory Improvement Amendments (CLIA)-certified laboratory, and gene expression was monitored using nCounter assays.Results: Anti-TNF therapy induced profound changes in patients' innate immune responses. TNFi action was selective, and had only minor effects on Th1/Th17 immunity. Modular transcriptional repertoire analysis identified prostaglandin E2 synthesis and signalling, leucocyte recirculation, macrophage polarisation, dectin and interleukin (IL)-1 signalling, as well as the nuclear factor kappa B (NF-kB) transcription factor family as key pathways targeted by TNF blockers in vivo. Analysis of induced immune responses before treatment initiation revealed that expression of molecules associated with leucocyte adhesion and invasion, chemotaxis and IL-1 signalling are correlated with therapeutic responses to anti-TNF.Conclusions: We show that TNFi target multiple immune cell pathways that cooperate to resolve inflammation. We propose that immune response profiling provides new insight into the biology of TNF-blocker action in patients and can identify signalling pathways associated with therapeutic responses to biological therapies. [ABSTRACT FROM AUTHOR]

Published
2021
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