Article (Scientific journals)
Longitudinal multi-omics analysis identifies early blood-based predictors of anti-TNF therapy response in inflammatory bowel disease.
Mishra, Neha; Aden, Konrad; Blase, Johanna I et al.
2022In Genome Medicine, 14 (1), p. 110
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Keywords :
Biologics; Biomarker; Intestinal inflammation; Personalized medicine; Therapy response; Biomarkers; Tumor Necrosis Factor Inhibitors; Tumor Necrosis Factor-alpha; RNA; Interferons; Infliximab; Humans; Infliximab/therapeutic use; Interferons/therapeutic use; Prospective Studies; Inflammatory Bowel Diseases/drug therapy; Inflammatory Bowel Diseases/genetics; Inflammatory Bowel Diseases; Molecular Medicine; Molecular Biology; Genetics; Genetics (clinical)
Abstract :
[en] [en] BACKGROUND AND AIMS: Treatment with tumor necrosis factor α (TNFα) antagonists in IBD patients suffers from primary non-response rates of up to 40%. Biomarkers for early prediction of therapy success are missing. We investigated the dynamics of gene expression and DNA methylation in blood samples of IBD patients treated with the TNF antagonist infliximab and analyzed the predictive potential regarding therapy outcome. METHODS: We performed a longitudinal, blood-based multi-omics study in two prospective IBD patient cohorts receiving first-time infliximab therapy (discovery: 14 patients, replication: 23 patients). Samples were collected at up to 7 time points (from baseline to 14 weeks after therapy induction). RNA-sequencing and genome-wide DNA methylation data were analyzed and correlated with clinical remission at week 14 as a primary endpoint. RESULTS: We found no consistent ex ante predictive signature across the two cohorts. Longitudinally upregulated transcripts in the non-remitter group comprised TH2- and eosinophil-related genes including ALOX15, FCER1A, and OLIG2. Network construction identified transcript modules that were coherently expressed at baseline and in non-remitting patients but were disrupted at early time points in remitting patients. These modules reflected processes such as interferon signaling, erythropoiesis, and platelet aggregation. DNA methylation analysis identified remission-specific temporal changes, which partially overlapped with transcriptomic signals. Machine learning approaches identified features from differentially expressed genes cis-linked to DNA methylation changes at week 2 as a robust predictor of therapy outcome at week 14, which was validated in a publicly available dataset of 20 infliximab-treated CD patients. CONCLUSIONS: Integrative multi-omics analysis reveals early shifts of gene expression and DNA methylation as predictors for efficient response to anti-TNF treatment. Lack of such signatures might be used to identify patients with IBD unlikely to benefit from TNF antagonists at an early time point.
Disciplines :
Genetics & genetic processes
Author, co-author :
Mishra, Neha;  Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel and University Medical Center Schleswig-Holstein, Kiel, Germany
Aden, Konrad;  Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel and University Medical Center Schleswig-Holstein, Kiel, Germany ; Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Kiel, Germany
Blase, Johanna I;  Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel and University Medical Center Schleswig-Holstein, Kiel, Germany
Baran, Nathan;  Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel and University Medical Center Schleswig-Holstein, Kiel, Germany
Bordoni, Dora;  Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel and University Medical Center Schleswig-Holstein, Kiel, Germany
Tran, Florian;  Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel and University Medical Center Schleswig-Holstein, Kiel, Germany ; Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Kiel, Germany
Conrad, Claudio;  Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Kiel, Germany
Avalos, Diana;  Institute of Genetics and Genomics of Geneva (iGE3), University of Geneva, Geneva, Switzerland
Jaeckel, Charlot;  Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Kiel, Germany
Scherer, Michael;  Department of Genetics, University of Saarland, Saarbrücken, Germany ; Present address: Department of Bioinformatics and Genomics, Centre for Genomic Regulation, The Barcelona Institute of Science and Technology, 08003, Barcelona, Spain
Sørensen, Signe B;  The Molecular Diagnostics and Clinical Research Unit, University Hospital of Southern Denmark, Aabenraa, Denmark ; Institute of Molecular Medicine, University of Southern Denmark, Odense, Denmark
Overgaard, Silja H;  The Molecular Diagnostics and Clinical Research Unit, University Hospital of Southern Denmark, Aabenraa, Denmark ; Section for Biostatistics and Evidence-Based Research, the Parker Institute, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark ; Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
Schulte, Berenice;  Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Kiel, Germany
Nikolaus, Susanna;  Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Kiel, Germany
Rey, Guillaume;  Institute of Genetics and Genomics of Geneva (iGE3), University of Geneva, Geneva, Switzerland
Gasparoni, Gilles;  Department of Genetics, University of Saarland, Saarbrücken, Germany
Lyons, Paul A;  Cambridge Institute of Therapeutic Immunology and Infectious Disease, Jeffrey Cheah Biomedical Centre, Cambridge Biomedical Campus, Cambridge, CB 0AW, UK ; Department of Medicine, University of Cambridge School of Clinical Medicine, Cambridge, CB2 0QQ, UK
Schultze, Joachim L;  Life &, Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany ; PRECISE Platform for Single Cell Genomics and Epigenomics, German Center for Neurodegenerative Diseases (DZNE), and University of Bonn, Bonn, Germany
Walter, Jörn;  Department of Genetics, University of Saarland, Saarbrücken, Germany
Andersen, Vibeke;  The Molecular Diagnostics and Clinical Research Unit, University Hospital of Southern Denmark, Aabenraa, Denmark ; Institute of Molecular Medicine, University of Southern Denmark, Odense, Denmark ; Institute of Regional Health Research, University of Southern Denmark, Odense, Denmark
SYSCID Consortium
Dermitzakis, Emmanouil T;  Institute of Genetics and Genomics of Geneva (iGE3), University of Geneva, Geneva, Switzerland
Schreiber, Stefan;  Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel and University Medical Center Schleswig-Holstein, Kiel, Germany. s.schreiber@mucosa.de ; Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Kiel, Germany. s.schreiber@mucosa.de
Rosenstiel, Philip ;  Institute of Clinical Molecular Biology, Christian-Albrechts-University Kiel and University Medical Center Schleswig-Holstein, Kiel, Germany. p.rosenstiel@mucosa.de ; Department of Internal Medicine I, University Medical Center Schleswig-Holstein, Kiel, Germany. p.rosenstiel@mucosa.de
More authors (14 more) Less
Other collaborator :
Georges, Michel  ;  Université de Liège - ULiège > GIGA > GIGA Medical Genomics - Unit of Animal Genomics ; Université de Liège - ULiège > Département de gestion vétérinaire des Ressources Animales (DRA) > Génomique animale ; SYSCID Consotium
Language :
English
Title :
Longitudinal multi-omics analysis identifies early blood-based predictors of anti-TNF therapy response in inflammatory bowel disease.
Publication date :
24 September 2022
Journal title :
Genome Medicine
eISSN :
1756-994X
Publisher :
BioMed Central Ltd, England
Volume :
14
Issue :
1
Pages :
110
Peer reviewed :
Peer Reviewed verified by ORBi
European Projects :
H2020 - 733100 - SYSCID - A Systems medicine approach to chronic inflammatory disease
Funders :
EU - European Union [BE]
IMI - Innovative Medicines Initiative [BE]
DFG - Deutsche Forschungsgemeinschaft [DE]
UKSH - Universitätsklinikum Schleswig-Holstein [DE]
Funding text :
Open Access funding enabled and organized by Projekt DEAL. This work was supported by the EU projects SYSCID (733100), IMI2 ImmUniverse (853995), the IMI2 Project 3TR (831434), the BMBF project iTREAT (01ZX1902A), and ExC 2167 Precision Medicine in Chronic Inflammation (RTF-VI).We thank K. Greve, M. Rohm, M. Hansen, S. Kock, D. Oelsner, S. Rentzow, M. Reffelmann, M. Schlapkohl, N. Braun, T. Wesse, M. Basso, Y. Dolschanskaya, X. Yi, C. Lancken, and M. Vollstedt for perfect technical assistance. We also thank the Popgen Biobank in Kiel for providing the storage and access of the biosamples and the Competence Centre for Genomic Analysis (CCGA), Kiel, for providing the infrastructure for next-generation sequencing. We are indebted to the patients, their families, and the hospital staff for support, without whom this study would not have been possible. Members of the SYSCID Consortium are as follows: Konrad Aden, Vibeke Andersen, Diana Avalos, Aggelos Banos, George Bertsias, Marc Beyer, Johanna I Blase, Dimitrios Boumpas, Emmanouil T Dermitzakis, Axel Finckh, Andre Franke, Gilles Gasparoni, Michel Georges, Wei Gu, Robert Häsler, Mohamad Jawhara, Amy Kenyon, Christina Kratsch, Roland Krause, Gordan Lauc, Paul A Lyons, Massimo Mangino, Neha Mishra, Gioacchino Natoli, Marek Ostaszewski, Silja H Overgaard, Marija Pezer, Jeroen Raes, Souad Rahmouni, Marilou Ramos-Pamplona, Benedikt Reiz, Elisa Rosati, Philip Rosenstiel, Despina Sanoudou, Venkata Satagopam, Reinhard Schneider, Jonas Schulte-Schrepping, Joachim L Schultze, Prodromos Sidiropoulos, Kenneth GC Smith, Signe B Sørensen, Timothy Spector, Doris Vandeputte, Sara Vieira-Silva, Aleksandar Vojta, Jörn Walter, Stefanie Warnat-Herresthal, and Vlatka Zoldoš.
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