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13 results on '"Hejblum, Boris"'

1. Using Population Based Kalman Estimator to Model COVID-19 Epidemic in France: Estimating the Effects of Non-Pharmaceutical Interventions on the Dynamics of Epidemic

Author

Collin, Annabelle, Hejblum, Boris P., Vignals, Carole, Lehot, Laurent, Thiébaut, Rodolphe, Moireau, Philippe, Prague, MéLanie, Institut de Mathématiques de Bordeaux (IMB), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), CHU de Bordeaux Pellegrin [Bordeaux], Laboratoire de mécanique des solides (LMS), École polytechnique (X)-MINES ParisTech - École nationale supérieure des mines de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS), Modélisation Mathématique pour l'Oncologie (MONC), Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Université Bordeaux Segalen - Bordeaux 2-Université Sciences et Technologies - Bordeaux 1 (UB)-Université de Bordeaux (UB)-Institut Polytechnique de Bordeaux (Bordeaux INP)-Centre National de la Recherche Scientifique (CNRS)-Institut Bergonié [Bordeaux], UNICANCER-UNICANCER-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Mathematical and Mechanical Modeling with Data Interaction in Simulations for Medicine (M3DISIM), École polytechnique (X)-Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-École polytechnique (X)-Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Inria Saclay - Ile de France, and Hejblum, Boris

Subjects
[SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases, [STAT.AP]Statistics [stat]/Applications [stat.AP], Epidemic modeling, [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, [MATH.MATH-ST]Mathematics [math]/Statistics [math.ST], Non-pharmaceutical interventions, COVID-19, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Population estimation, COVID-19 Epidemic modeling Non-pharmaceutical interventions Kalman filters Population estimation, Kalman filters, [MATH.MATH-ST] Mathematics [math]/Statistics [math.ST]
Abstract

International audience; In response to the ongoing COVID-19 pandemic caused by SARS-CoV-2, governments are taking a wide range of non-pharmaceutical interventions (NPI). These measures include interventions as stringent as strict lockdown but also school closure, bar and restaurant closure, curfews and barrier gestures i.e . social distancing. Disentangling the effectiveness of each NPI is crucial to inform response to future outbreaks. To this end, we first develop a multi-level estimation of the French COVID-19 epidemic over a period of one year. We rely on a global extended Susceptible-Infectious-Recovered (SIR) mechanistic model of the infection including a dynamical (over time) transmission rate containing a Wiener process accounting for modeling error. Random effects are integrated following an innovative population approach based on a Kalman-type filter where the log-likelihood functional couples data across French regions. We then fit the estimated time-varying transmission rate using a regression model depending on NPI, while accounting for vaccination coverage, apparition of variants of concern (VoC) and seasonal weather conditions. We show that all NPI considered have an independent significant effect on the transmission rate. We additionally demonstrate a strong effect from weather conditions which decrease transmission during the summer period, and also estimate increased transmissibility of VoCs.

Published
2021
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2. Long-lasting severe immune dysfunction in Ebola virus disease survivors

Author

WIEDEMANN, A., FOUCAT, E., Hocini, H., Lefebvre, C., Hejblum, Boris P., DURAND, Melany, KRUGER, Miriam, KEITA, A. K., Ayouba, A., MÉLY, S., FERNANDEZ, J. C., Touré, A., Fourati, S., LÉVY-MARCHAL, C., Raoul, H., Delaporte, E., Koivogui, L., THIEBAUT, Rodolphe, Lacabaratz, C., Levy, Y., Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), and Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, SISTM
Abstract

Long-term follow up studies from Ebola virus disease (EVD) survivors (EBOV_S) are lacking. Here, we evaluate immune and gene expression profiles in 35 Guinean EBOV_S from the last West African outbreak, a median of 23 months (IQR [18–25]) after discharge from treatment center. Compared with healthy donors, EBOV_S exhibit increases of blood markers of inflammation, intestinal tissue damage, T cell and B cell activation and a depletion of circulating dendritic cells. All survivors have EBOV-specific IgG antibodies and robust and polyfunctional EBOV-specific memory T-cell responses. Deep sequencing of the genes expressed in blood reveals an enrichment in ‘inflammation’ and ‘antiviral’ pathways. Integrated analyses identify specific immune markers associated with the persistence of clinical symptoms. This study identifies a set of biological and genetic markers that could be used to define a signature of “chronic Ebola virus disease (CEVD)”.

Published
2020

3. Immune Alterations in a Patient with SARS-CoV-2-Related Acute Respiratory Distress Syndrome

Author

Bouadma, Lila, WIEDEMANN, A., PATRIER, J., SURENAUD, M., WICKY, P. H., FOUCAT, E., DIEHL, J. L., Hejblum, Boris P., SINNAH, F., DE MONTMOLLIN, E., Lacabaratz, C., THIEBAUT, Rodolphe, Timsit, J. F., Levy, Y., Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), and Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie
Abstract

International audience; We report a longitudinal analysis of the immune response associated with a fatal case of COVID-19 in Europe. This patient exhibited a rapid evolution towards multiorgan failure. SARS-CoV-2 was detected in multiple nasopharyngeal, blood, and pleural samples, despite antiviral and immunomodulator treatment. Clinical evolution in the blood was marked by an increase (2–3-fold) in differentiated effector T cells expressing exhaustion (PD-1) and senescence (CD57) markers, an expansion of antibody-secreting cells, a 15-fold increase in γδ T cell and proliferating NK-cell populations, and the total disappearance of monocytes, suggesting lung trafficking. In the serum, waves of a pro-inflammatory cytokine storm, Th1 and Th2 activation, and markers of T cell exhaustion, apoptosis, cell cytotoxicity, and endothelial activation were observed until the fatal outcome. This case underscores the need for well-designed studies to investigate complementary approaches to control viral replication, the source of the hyperinflammatory status, and immunomodulation to target the pathophysiological response. The investigation was conducted as part of an overall French clinical cohort assessing patients with COVID-19 and registered in clinicaltrials.gov under the following number: NCT04262921.

Published
2020
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4. Long-lasting severe immune dysfunction in Ebola virus disease survivors

Author

WIEDEMANN, A., FOUCAT, E., Hocini, H., Lefebvre, C., Hejblum, Boris P., DURAND, Melany, KRUGER, Miriam, KEITA, A. K., Ayouba, A., MÉLY, S., FERNANDEZ, J. C., Touré, A., Fourati, S., LÉVY-MARCHAL, C., Raoul, H., Delaporte, E., Koivogui, L., THIEBAUT, Rodolphe, Lacabaratz, C., Levy, Y., Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), and Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, SISTM
Abstract

Long-term follow up studies from Ebola virus disease (EVD) survivors (EBOV_S) are lacking. Here, we evaluate immune and gene expression profiles in 35 Guinean EBOV_S from the last West African outbreak, a median of 23 months (IQR [18–25]) after discharge from treatment center. Compared with healthy donors, EBOV_S exhibit increases of blood markers of inflammation, intestinal tissue damage, T cell and B cell activation and a depletion of circulating dendritic cells. All survivors have EBOV-specific IgG antibodies and robust and polyfunctional EBOV-specific memory T-cell responses. Deep sequencing of the genes expressed in blood reveals an enrichment in ‘inflammation’ and ‘antiviral’ pathways. Integrated analyses identify specific immune markers associated with the persistence of clinical symptoms. This study identifies a set of biological and genetic markers that could be used to define a signature of “chronic Ebola virus disease (CEVD)”.

Published
2020

5. Gene Expression Signatures Associated With Immune and Virological Responses to Therapeutic Vaccination With Dendritic Cells in HIV-Infected Individuals

Author

Thiébaut, Rodolphe, Hejblum, Boris P., Hocini, Hakim, Bonnabau, Henri, Skinner, Jason, Montes, Monica, Lacabaratz, Christine, Richert, Laura, Palucka, Karolina, Banchereau, Jacques, Lévy, Yves, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Neuroépidémiologie Tropicale (NET), CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), Université de Limoges (UNILIM)-Université de Limoges (UNILIM), Baylor Institute for Immunology Research (BIIR), 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), This study was supported by a grant from the Agence Nationale de Recherches sur le SIDA et les hépatites virales(ANRS). LR received a Ph.D. scholarship financed by Sidaction. This work was supported by the Investissements d’Avenir program managed by the ANR under reference ANR-10-LABX-77-01 funding the Vaccine ResearchInstitute (VRI)., Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institut Génomique, Environnement, Immunité, Santé, Thérapeutique (GEIST), and Université de Limoges (UNILIM)-Université de Limoges (UNILIM)-CHU Limoges-Institut d'Epidémiologie Neurologique et de Neurologie Tropicale-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
Adult, Male, HIV Antigens, dendritic cell, Immunology, HIV Infections, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Immunology and Allergy, Humans, Original Research, AIDS Vaccines, Blood Cells, Gene Expression Profiling, Vaccination, Computational Biology, HIV, systems biology, Dendritic Cells, Middle Aged, Viral Load, Texas, SISTM, Patient Outcome Assessment, Host-Pathogen Interactions, HIV-1, gene expression, Cytokines, [SDV.IMM]Life Sciences [q-bio]/Immunology, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Female, therapeutic vaccine, [SDV.IMM.VAC]Life Sciences [q-bio]/Immunology/Vaccinology, Transcriptome, antiretroviral therapy interruption
Abstract

International audience; The goal of HIV therapeutic vaccination is to induce HIV-specific immune response able to control HIV replication. We previously reported that vaccination with ex vivo generated Dendritic Cells (DC) loaded with HIV-lipopeptides in HIV-infected patients (n = 19) on antiretroviral therapy (ART) was well-tolerated and immunogenic. Vaccine-elicited HIV-specific T cell responses were associated with improved control of viral replication following antiretroviral interruption (ATI from w24 to w48). We show an inverse relationship between HIV-specific responses (production of IL-2, IL-13, IL-21, IFN-g, CD4 polyfunctionality, i.e., production of at least two cytokines) and the peak of viral load during ATI. Here we have performed an integrative systems vaccinology analysis including: (i) post vaccination (w16) immune responses assessed by cytometry, cytokine secretion, and Interferon-γ ELISPOT assays; (ii) whole blood and cellular gene expression measured during vaccination; and (iii) viral parameters following ATI, with the objective to disentangle the relationships between these markers and to identify vaccine signatures. During vaccination, 69 gene expression modules out of 260 varied significantly including (by order of significance) modules related to inflammation (Chaussabel Modules M3.2, M4.13, M4.6, M5.7, M7.1, M4.2), plasma cells (M4.11) and T cells (M4.1, 4.15). Cellular immune responses were positively correlated to genes belonging to T cell functional modules (M4.1, M4.15) at w16 and negatively correlated to genes belonging to inflammation modules (M7.1, M5.7, M3.2, M4.13, M4.2). More specifically, we show that prolonged increased abundance of inflammatory gene pathways related to toll-like receptor signaling (especially TLR4) are associated with both lower vaccine immune responses and control of viral replication post ATI. Further comparison of DC vaccine gene signatures with previously reported non-HIV vaccine signatures, such as flu and pneumococcal vaccines, revealed common pathways across vaccines. Overall, these results show that too long duration and too high intensity of vaccine inflammatory responses hamper the magnitude of effector responses. [ABSTRACT FROM AUTHOR] Copyright of Frontiers in Immunology is the property of Frontiers Media S.A. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.

Published
2019
Full Text
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6. Gene Expression Signatures Associated With Immune and Virological Responses to Therapeutic Vaccination With Dendritic Cells in HIV-Infected Individuals

Author

THIEBAUT, Rodolphe, Hejblum, Boris, Hocini, Hakim, Bonnabau, Henri, Skinner, Jason, Montes, Monica, Lacabaratz, Christine, Richert, Laura, Palucka, Karolina, Banchereau, Jacques, Lévy, Yves, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), and Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Université de Bordeaux (UB)

Subjects
[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, SISTM
Abstract

The goal of HIV therapeutic vaccination is to induce HIV-specific immune response able to control HIV replication. We previously reported that vaccination with ex vivo generated Dendritic Cells (DC) loaded with HIV-lipopeptides in HIV-infected patients (n = 19) on antiretroviral therapy (ART) was well-tolerated and immunogenic. Vaccine-elicited HIV-specific T cell responses were associated with improved control of viral replication following antiretroviral interruption (ATI from w24 to w48). We show an inverse relationship between HIV-specific responses (production of IL-2, IL-13, IL-21, IFN-g, CD4 polyfunctionality, i.e., production of at least two cytokines) and the peak of viral load during ATI. Here we have performed an integrative systems vaccinology analysis including: (i) post vaccination (w16) immune responses assessed by cytometry, cytokine secretion, and Interferon-γ ELISPOT assays; (ii) whole blood and cellular gene expression measured during vaccination; and (iii) viral parameters following ATI, with the objective to disentangle the relationships between these markers and to identify vaccine signatures. During vaccination, 69 gene expression modules out of 260 varied significantly including (by order of significance) modules related to inflammation (Chaussabel Modules M3.2, M4.13, M4.6, M5.7, M7.1, M4.2), plasma cells (M4.11) and T cells (M4.1, 4.15). Cellular immune responses were positively correlated to genes belonging to T cell functional modules (M4.1, M4.15) at w16 and negatively correlated to genes belonging to inflammation modules (M7.1, M5.7, M3.2, M4.13, M4.2). More specifically, we show that prolonged increased abundance of inflammatory gene pathways related to toll-like receptor signaling (especially TLR4) are associated with both lower vaccine immune responses and control of viral replication post ATI. Further comparison of DC vaccine gene signatures with previously reported non-HIV vaccine signatures, such as flu and pneumococcal vaccines, revealed common pathways across vaccines. Overall, these results show that too long duration and too high intensity of vaccine inflammatory responses hamper the magnitude of effector responses. [ABSTRACT FROM AUTHOR] Copyright of Frontiers in Immunology is the property of Frontiers Media S.A. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.

Published
2019

7. Sequential Dirichlet process mixture of skew $t$-distributions for model-based clustering of flow cytometry data

Author

Hejblum, Boris P., Alkhassim, Chariff, Gottardo, Raphael, Caron, François, Thiébaut, Rodolphe, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Fred Hutchinson Cancer Research Center [Seattle] (FHCRC), Department of Statistics [Oxford], University of Oxford [Oxford], Part of this work has been supported by the BNPSI ANR project ANR-13-BS03-0006-01. Part of this work has been supported by the IMI2 grant EBOVAC2., ANR-13-BS03-0006,BNPSI,Méthodes bayésiennes non paramétriques pour le traitement du signal et de l'image(2013), Admin, Oskar, Blanc 2013 - Méthodes bayésiennes non paramétriques pour le traitement du signal et de l'image - - BNPSI2013 - ANR-13-BS03-0006 - Blanc 2013 - VALID, and University of Oxford

Subjects
Automatic gating, Dirichlet process, Mixture model, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, HIV, Bayesian Nonparametrics, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Flow cytometry
Abstract

International audience; Flow cytometry is a high-throughput technology used to quantify multiple surface and intracellular markers at the level of a single cell. This enables us to identify cell sub-types, and to determine their relative proportions. Improvements of this technology allow us to describe millions of individual cells from a blood sample using multiple markers. This results in high-dimensional datasets, whose manual analysis is highly time-consuming and poorly reproducible. While several methods have been developed to perform automatic recognition of cell populations, most of them treat and analyze each sample independently. However, in practice, individual samples are rarely independent, especially in longitudinal studies. Here we analyze new longitudinal flow-cytometry data from the DALIA-1 trial which evaluates a therapeutic vaccine against HIV, by proposing a new Bayesian nonparametric approach with Dirichlet process mixture (DPM) of multivariate skew t-distributions to perform model based clustering of flow-cytometry data. DPM models directly estimate the number of cell populations from the data, avoiding model selection issues, and skew $t$-distributions provides robustness to outliers and non-elliptical shape of cell populations. To accommodate repeated measurements, we propose a sequential strategy relying on a parametric approximation of the posterior. We illustrate the good performance of our method on simulated data and on an experimental benchmark dataset. This sequential strategy outperforms all other methods evaluated on the benchmark dataset, and leads to improved performance on the DALIA-1 data.

Published
2019

8. Gene Expression Signatures Associated With Immune and Virological Responses to Therapeutic Vaccination With Dendritic Cells in HIV-Infected Individuals

Author

Thiébaut, Rodolphe, Hejblum, Boris P., Hocini, Hakim, Bonnabau, Henri, Skinner, Jason, Montes, Monica, Lacabaratz, Christine, Richert, Laura, Palucka, Karolina, Banchereau, Jacques, Lévy, Yves, Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Baylor Institute for Immunology Research (BIIR), This study was supported by a grant from the Agence Nationale de Recherches sur le SIDA et les hépatites virales(ANRS). LR received a Ph.D. scholarship financed by Sidaction. This work was supported by the Investissements d’Avenir program managed by the ANR under reference ANR-10-LABX-77-01 funding the Vaccine ResearchInstitute (VRI)., and Admin, Oskar

Subjects
Antiretroviral therapy interruption, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, HIV, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Gene expression, Therapeutic vaccine, Systems biology, Dendritic cell, SISTM
Abstract

International audience; The goal of HIV therapeutic vaccination is to induce HIV-specific immune response able to control HIV replication. We previously reported that vaccination with ex vivo generated Dendritic Cells (DC) loaded with HIV-lipopeptides in HIV-infected patients (n = 19) on antiretroviral therapy (ART) was well-tolerated and immunogenic. Vaccine-elicited HIV-specific T cell responses were associated with improved control of viral replication following antiretroviral interruption (ATI from w24 to w48). We show an inverse relationship between HIV-specific responses (production of IL-2, IL-13, IL-21, IFN-g, CD4 polyfunctionality, i.e., production of at least two cytokines) and the peak of viral load during ATI. Here we have performed an integrative systems vaccinology analysis including: (i) post vaccination (w16) immune responses assessed by cytometry, cytokine secretion, and Interferon-γ ELISPOT assays; (ii) whole blood and cellular gene expression measured during vaccination; and (iii) viral parameters following ATI, with the objective to disentangle the relationships between these markers and to identify vaccine signatures. During vaccination, 69 gene expression modules out of 260 varied significantly including (by order of significance) modules related to inflammation (Chaussabel Modules M3.2, M4.13, M4.6, M5.7, M7.1, M4.2), plasma cells (M4.11) and T cells (M4.1, 4.15). Cellular immune responses were positively correlated to genes belonging to T cell functional modules (M4.1, M4.15) at w16 and negatively correlated to genes belonging to inflammation modules (M7.1, M5.7, M3.2, M4.13, M4.2). More specifically, we show that prolonged increased abundance of inflammatory gene pathways related to toll-like receptor signaling (especially TLR4) are associated with both lower vaccine immune responses and control of viral replication post ATI. Further comparison of DC vaccine gene signatures with previously reported non-HIV vaccine signatures, such as flu and pneumococcal vaccines, revealed common pathways across vaccines. Overall, these results show that too long duration and too high intensity of vaccine inflammatory responses hamper the magnitude of effector responses. [ABSTRACT FROM AUTHOR] Copyright of Frontiers in Immunology is the property of Frontiers Media S.A. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.

Published
2019
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9. Early blood lipid signature predicting accelerated cognitive decline in older persons

Author

Lefevre-Arbogast, Sophie, Thuret, Sandrine, Helmer, Catherine, Proust-Lima, Cécile, Hejblum, Boris P., Samieri, Cecilia, Bordeaux population health (BPH), and Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
[SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Biostatistics, LEHA, SISTM
Published
2018
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10. Immune Alterations in a Patient with SARS-CoV-2-Related Acute Respiratory Distress Syndrome

Author

Mathieu Surenaud, Etienne de Montmollin, Yves Levy, Boris P. Hejblum, Rodolphe Thiébaut, Paul-Henri Wicky, Emile Foucat, Juliette Patrier, Lila Bouadma, Jean-Luc Diehl, Jean-François Timsit, Aurélie Wiedemann, Christine Lacabaratz, Fabrice Sinnah, AP-HP - Hôpital Bichat - Claude Bernard [Paris], Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), Statistics In System biology and Translational Medicine (SISTM), Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), This work was financially supported by the Investissements d’Avenir program, Vaccine Research Institute (VRI), managed by the ANR under reference ANR-10-LABX-77-01., Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Université de Bordeaux (UB), 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), Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Paris (UP)-Université Sorbonne Paris Nord, Groupe Henri Mondor-Albert Chenevier, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Henri Mondor-Hôpital Albert Chenevier, and Hejblum, Boris

Subjects
Male, 0301 basic medicine, Lymphocyte Activation, [SDV.MHEP.PSR]Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, [SDV.IMM.II]Life Sciences [q-bio]/Immunology/Innate immunity, Severity of Illness Index, Fatal Outcome, 0302 clinical medicine, [STAT.AP] Statistics [stat]/Applications [stat.AP], [SDV.MHEP.MI]Life Sciences [q-bio]/Human health and pathology/Infectious diseases, Immunology and Allergy, Longitudinal Studies, Prospective Studies, Aged, 80 and over, [SDV.MHEP.ME]Life Sciences [q-bio]/Human health and pathology/Emerging diseases, Respiratory Distress Syndrome, [STAT.AP]Statistics [stat]/Applications [stat.AP], SISTM, 3. Good health, Cytokine release syndrome, medicine.anatomical_structure, [SDV.IMM.IA]Life Sciences [q-bio]/Immunology/Adaptive immunology, 030220 oncology & carcinogenesis, [SDV.IMM]Life Sciences [q-bio]/Immunology, Original Article, France, Coronavirus Infections, Cytokine Release Syndrome, Senescence, [SDV.IMM] Life Sciences [q-bio]/Immunology, Multiple Organ Failure, T cell, Pneumonia, Viral, Immunology, T cells, Endothelial activation, Betacoronavirus, immune dysfunction, 03 medical and health sciences, Th2 Cells, Immune system, medicine, Humans, Pandemics, Lung, SARS-CoV-2, business.industry, COVID-19, Th1 Cells, medicine.disease, cytokines, 030104 developmental biology, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, Apoptosis, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, business, Cytokine storm, T-Lymphocytes, Cytotoxic
Abstract

We report a longitudinal analysis of the immune response associated with a fatal case of COVID-19 in Europe. This patient exhibited a rapid evolution towards multiorgan failure. SARS-CoV-2 was detected in multiple nasopharyngeal, blood, and pleural samples, despite antiviral and immunomodulator treatment. Clinical evolution in the blood was marked by an increase (2–3-fold) in differentiated effector T cells expressing exhaustion (PD-1) and senescence (CD57) markers, an expansion of antibody-secreting cells, a 15-fold increase in γδ T cell and proliferating NK-cell populations, and the total disappearance of monocytes, suggesting lung trafficking. In the serum, waves of a pro-inflammatory cytokine storm, Th1 and Th2 activation, and markers of T cell exhaustion, apoptosis, cell cytotoxicity, and endothelial activation were observed until the fatal outcome. This case underscores the need for well-designed studies to investigate complementary approaches to control viral replication, the source of the hyperinflammatory status, and immunomodulation to target the pathophysiological response. The investigation was conducted as part of an overall French clinical cohort assessing patients with COVID-19 and registered in clinicaltrials.gov under the following number: NCT04262921.

Published
2020
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11. Automatic phenotyping of electronical health record: PheVis algorithm

Author

Boris P. Hejblum, Vianney Jouhet, Thomas Ferté, Sébastien Cossin, Thierry Schaeverbeke, Thomas Barnetche, Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Université Bordeaux Segalen - Bordeaux 2, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hôpital Haut-Lévêque [CHU Bordeaux], CHU Bordeaux [Bordeaux], Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), and Hejblum, Boris

Subjects
Chronic condition, 020205 medical informatics, Computer science, Health Informatics, 02 engineering and technology, Health records, Machine learning, computer.software_genre, Arthritis, Rheumatoid, Machine Learning, 03 medical and health sciences, Annotation, 0302 clinical medicine, 0202 electrical engineering, electronic engineering, information engineering, Humans, Electronic health records, 030212 general & internal medicine, Natural Language Processing, 030304 developmental biology, 0303 health sciences, Past medical history, business.industry, Medical record, Precision medicine, Data warehouse, Computer Science Applications, 3. Good health, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, High-throughput phenotyping, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Diagnosis code, Artificial intelligence, White box, business, computer, Algorithms, Natural language processing, Phenotypic big data
Abstract

Electronic Health Records (EHRs) often lack reliable annotation of patient medical conditions. Yu et al. recently proposed PheNorm, an automated unsupervised algorithm to identify patient medical conditions from EHR data. PheVis extends PheNorm at the visit resolution. PheVis combines diagnosis codes together with medical concepts extracted from medical notes, incorporating past history in a machine learning approach to provide an interpretable “white box” predictor of the occurrence probability for a given medical condition at each visit. PheVis is applied to two real-world use-cases using the datawarehouse of the University Hospital of Bordeaux: i) rheumatoid arthritis, a chronic condition; ii) tuberculosis, an acute condition (cross-validated AUROC were respectively 0.947 [0.944; 0.948] and 0.987 [0.983; 0.990]). PheVis performs well for chronic conditions, though absence of exclusion of past medical history by natural language processing tools limits its performance in French for acute conditions. It achieves significantly better performance than state-of-the-art methods especially for chronic diseases.

Published
2021
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12. Predicting Progression to Advanced Age-Related Macular Degeneration from Clinical, Genetic, and Lifestyle Factors Using Machine Learning

Author

Soufiane Ajana, Audrey Cougnard-Grégoire, Johanna M. Colijn, Bénédicte M.J. Merle, Timo Verzijden, Paulus T.V.M. de Jong, Albert Hofman, Johannes R. Vingerling, Boris P. Hejblum, Jean-François Korobelnik, Magda A. Meester-Smoor, Marius Ueffing, Hélène Jacqmin-Gadda, Caroline C.W. Klaver, Cécile Delcourt, Erkin I. Acar, Blanca Arango-Gonzalez, Angela Armento, Franz Badura, Vaibhav Bhatia, Shomi S. Bhattacharya, Marc Biarnés, Anna Borrell, Sofia M. Calado, Sascha Dammeier, Anita de Breuk, Berta De la Cerda, Anneke I. den Hollander, Francisco J. Diaz-Corrales, Sigrid Diether, Eszter Emri, Tanja Endermann, Lucia L. Ferraro, Míriam Garcia, Thomas J. Heesterbeek, Sabina Honisch, Carel B. Hoyng, Ellen Kilger, Elod Kortvely, Claire Lastrucci, Hanno Langen, Imre Lengyel, Phil Luthert, Jordi Monés, Everson Nogoceke, Tunde Peto, Frances M. Pool, Eduardo Rodriguez-Bocanegra, Luis Serrano, Jose Sousa, Eric Thee, Karl U. Ulrich Bartz-Schmidt, Markus Zumbansen, Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Erasmus University Medical Center [Rotterdam] (Erasmus MC), University of Amsterdam [Amsterdam] (UvA), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), Institut de Santé Publique, d'Epidémiologie et de Développement (ISPED), Université Bordeaux Segalen - Bordeaux 2, The EYE-RISK project was supported by the European Union’s Horizon 2020 Research and Innovation Programme (grant n°: 634479). The Rotterdam Study is funded by Erasmus Medical Center and Erasmus University, Rotterdam, The Netherlands, the Organization for the Health Research and Development (ZonMw), the Research Institute for Diseases in the Elderly (RIDE), the Ministry of Education, Culture and Science, the Ministry for Health, Welfare and Sports, the European Commission (DG XII), and the Municipality of Rotterdam, Rotterdam, The Netherlands. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Additionally, the ophthalmic research within the Rotterdam Study was supported by the following foundations: Oogfonds, Bartiméus Sonneheerdt Vereniging, LandelijkeStichting voor Blinden en Slechtzienden, Algemene Nederlandse Vereniging Ter Voorkoming Van Blindheid, Novartis Foundation, and MaculaFonds, which contributed through UitZicht (grant nos.: 2015-36 and 2016-19). The Antioxydants, Lipides Essentiels, Nutrition et Maladies Oculaires (ALIENOR) Study was funded by Laboratoires Théa, Fondation Voir et Entendre, Retina France, Agence Nationale de la Recherche (ANR-2010-PRSP-011 VISA), Programme Hospitalier de Recherche Clinique (PHRC) (ECLAIR project-2012), CFSR Recherche, the French Speaking Retina Specialists’ Club and Caisse Nationale pour la Solidarité et l’Autonomie. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Laboratoires Théa participated in the design of the Antioxydants, Lipides Essentiels, Nutrition et Maladies Oculaires (ALIENOR) Study, but none of the sponsors of this study participated in the collection, management, statistical analysis, or interpretation of the data, or in the preparation, review, or approval of the present manuscript., European Project: 634479,H2020,H2020-PHC-2014-two-stage,EYE-RISK(2015), Hejblum, Boris, Exploring the combined role of genetic and non-genetic factors for developing Age-Related Macular Degeneration: A systems level analysis of disease subgroups, risk factors, and pathways - EYE-RISK - - H20202015-05-01 - 2019-04-30 - 634479 - VALID, Ophthalmology, Epidemiology, Netherlands Institute for Neuroscience (NIN), and Vaccine Research Institute [Créteil, France] (VRI)

Subjects
Male, computer.software_genre, Sensory disorders Donders Center for Medical Neuroscience [Radboudumc 12], Machine Learning, Rotterdam Study, Macular Degeneration, 0302 clinical medicine, [STAT.AP] Statistics [stat]/Applications [stat.AP], Risk Factors, Cumulative incidence, ComputingMilieux_MISCELLANEOUS, 0303 health sciences, education.field_of_study, [STAT.AP]Statistics [stat]/Applications [stat.AP], Smoking, Middle Aged, 3. Good health, Phenotype, Area Under Curve, Disease Progression, Female, Cohort study, Genotype, Population, Clinical Decision-Making, Retinal Drusen, Machine learning, 03 medical and health sciences, medicine, Genetics, Humans, education, Life Style, Survival analysis, 030304 developmental biology, Aged, Nutrition, Receiver operating characteristic, business.industry, Age-related macular degeneration, Macular degeneration, Models, Theoretical, medicine.disease, Lifestyle, Personalized medicine, Confidence interval, eye diseases, Ophthalmology, [SDV.SPEE] Life Sciences [q-bio]/Santé publique et épidémiologie, 030221 ophthalmology & optometry, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Artificial intelligence, business, Prediction, computer
Abstract

Contains fulltext : 245098.pdf (Publisher’s version ) (Closed access) PURPOSE: Current prediction models for advanced age-related macular degeneration (AMD) are based on a restrictive set of risk factors. The objective of this study was to develop a comprehensive prediction model applying a machine learning algorithm allowing selection of the most predictive risk factors automatically. DESIGN: Two population-based cohort studies. PARTICIPANTS: The Rotterdam Study I (RS-I; training set) included 3838 participants 55 years of age or older, with a median follow-up period of 10.8 years, and 108 incident cases of advanced AMD. The Antioxydants, Lipids Essentiels, Nutrition et Maladies Oculaires (ALIENOR) study (test set) included 362 participants 73 years of age or older, with a median follow-up period of 6.5 years, and 33 incident cases of advanced AMD. METHODS: The prediction model used the bootstrap least absolute shrinkage and selection operator (LASSO) method for survival analysis to select the best predictors of incident advanced AMD in the training set. Predictive performance of the model was assessed using the area under the receiver operating characteristic curve (AUC). MAIN OUTCOME MEASURES: Incident advanced AMD (atrophic, neovascular, or both), based on standardized interpretation of retinal photographs. RESULTS: The prediction model retained (1) age, (2) a combination of phenotypic predictors (based on the presence of intermediate drusen, hyperpigmentation in one or both eyes, and Age-Related Eye Disease Study simplified score), (3) a summary genetic risk score based on 49 single nucleotide polymorphisms, (4) smoking, (5) diet quality, (6) education, and (7) pulse pressure. The cross-validated AUC estimation in RS-I was 0.92 (95% confidence interval [CI], 0.88-0.97) at 5 years, 0.92 (95% CI, 0.90-0.95) at 10 years, and 0.91 (95% CI, 0.88-0.94) at 15 years. In ALIENOR, the AUC reached 0.92 at 5 years (95% CI, 0.87-0.98). In terms of calibration, the model tended to underestimate the cumulative incidence of advanced AMD for the high-risk groups, especially in ALIENOR. CONCLUSIONS: This prediction model reached high discrimination abilities, paving the way toward making precision medicine for AMD patients a reality in the near future.

Published
2020
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13. Analyzing cellular immunogenicity in vaccine clinical trials: a new statistical method including non-specific responses for accurate estimation of vaccine effect

Author

Jean-Daniel Lelièvre, Rodolphe Thiébaut, Aurélie Wiedemann, Edouard Lhomme, Christine Lacabaratz, Laura Richert, Boris P. Hejblum, Yves Levy, CHU de Bordeaux Pellegrin [Bordeaux], Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Statistics In System biology and Translational Medicine (SISTM), Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)- Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), Vaccine Research Institute (VRI), Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12), 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), Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Université de Bordeaux (UB), Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Est Créteil Val-de-Marne - Paris 12 (UPEC UP12)-IFR10, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Epidémiologie et Biostatistique [Bordeaux], Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Bordeaux Segalen - Bordeaux 2-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM), and Hejblum, Boris

Subjects
0301 basic medicine, Adult, Male, Computer science, T-Lymphocytes, Immunology, Datasets as Topic, HIV Infections, Computational biology, Bivariate analysis, Models, Biological, Statistical power, 03 medical and health sciences, 0302 clinical medicine, [SDV.IMM.VAC] Life Sciences [q-bio]/Immunology/Vaccinology, Immunogenicity, Vaccine, Antigen, Linear regression, Immunology and Allergy, Humans, Computer Simulation, HIV vaccine, Randomized Controlled Trials as Topic, AIDS Vaccines, Immunity, Cellular, [STAT.ME] Statistics [stat]/Methodology [stat.ME], Immunogenicity, Subtraction, Flow Cytometry, Healthy Volunteers, 3. Good health, SISTM, Clinical trial, Benchmarking, 030104 developmental biology, Treatment Outcome, Research Design, HIV-1, Linear Models, [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie, Female, [SDV.IMM.VAC]Life Sciences [q-bio]/Immunology/Vaccinology, [STAT.ME]Statistics [stat]/Methodology [stat.ME], 030215 immunology
Abstract

International audience; Evaluation of immunogenicity is a key step in the clinical development of novel vaccines. T-cell responses to vaccine candidates are typically assessed by intracellular cytokine staining (ICS) using multiparametric flow cytometry. A conventional statistical approach to analyze ICS data is to compare, between vaccine regimens or between baseline and post-vaccination of the same regimen depending on the trial design, the percentages of cells producing a cytokine of interest after ex vivo stimulation of peripheral blood mononuclear cells (PBMC) with vaccineantigens, after subtracting the non-specific response (of unstimulated cells) of each sample. Subtraction of the non-specific response is aimed at capturing the specific response to the antigen, but raises methodological issues related to measurement error and statistical power. We describe here a new statistical approach to analyze ICS data from vaccine trials. We propose a bivariate linear random-effect regression model for estimating the nonspecificand antigen-specific ICS responses. We benchmarked the performance of the model in terms of both bias and control of type-I and -II errors in comparison with conventional approaches, and applied it to simulated data as well as real pre- and post-vaccination data from two recent HIV vaccine trials (ANRS VRI01 in healthy volunteers and therapeutic VRI02 ANRS 149 LIGHT in HIV-infected participants). The model was as good as the conventional approaches (with or without subtraction of the non-specific response) in all simulation scenarios in terms of statistical performance, whereas the conventional approaches did not provide robust results across all scenarios. The proposed model estimated the T-cell responses to the antigens without any effect of the nonspecific response on the specific response, irrespective of the correlation between the nonspecific and specific responses. This novel method of analyzing T-cell immunogenicity data based on bivariate modelling allows consideration of all T-cell data and is more flexible than conventional methods, and so yields more detailed results and enables accurate interpretation of vaccine efficacy.

Published
2020
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