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Ha MK, Bartholomeus E, Van Os L, Dandelooy J, Leysen J, Aerts O, Siozopoulou V, De Smet E, Gielen J, Guerti K, De Maeseneer M, Herregods N, Lechkar B, Wittoek R, Geens E, Claes L, Zaqout M, Dewals W, Lemay A, Tuerlinckx D, Weynants D, Vanlede K, van Berlaer G, Raes M, Verhelst H, Boiy T, Van Damme P, Jansen AC, Meuwissen M, Sabato V, Van Camp G, Suls A, Werff ten Bosch JVD, Dehoorne J, Joos R, Laukens K, Meysman P, Ogunjimi B. Blood transcriptomics to facilitate diagnosis and stratification in pediatric rheumatic diseases - a proof of concept study. Pediatr Rheumatol Online J 2022; 20:91. [PMID: 36253751 PMCID: PMC9575227 DOI: 10.1186/s12969-022-00747-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 09/24/2022] [Indexed: 11/21/2022] Open
Abstract
BACKGROUND Transcriptome profiling of blood cells is an efficient tool to study the gene expression signatures of rheumatic diseases. This study aims to improve the early diagnosis of pediatric rheumatic diseases by investigating patients' blood gene expression and applying machine learning on the transcriptome data to develop predictive models. METHODS RNA sequencing was performed on whole blood collected from children with rheumatic diseases. Random Forest classification models were developed based on the transcriptome data of 48 rheumatic patients, 46 children with viral infection, and 35 controls to classify different disease groups. The performance of these classifiers was evaluated by leave-one-out cross-validation. Analyses of differentially expressed genes (DEG), gene ontology (GO), and interferon-stimulated gene (ISG) score were also conducted. RESULTS Our first classifier could differentiate pediatric rheumatic patients from controls and infection cases with high area-under-the-curve (AUC) values (AUC = 0.8 ± 0.1 and 0.7 ± 0.1, respectively). Three other classifiers could distinguish chronic recurrent multifocal osteomyelitis (CRMO), juvenile idiopathic arthritis (JIA), and interferonopathies (IFN) from control and infection cases with AUC ≥ 0.8. DEG and GO analyses reveal that the pathophysiology of CRMO, IFN, and JIA involves innate immune responses including myeloid leukocyte and granulocyte activation, neutrophil activation and degranulation. IFN is specifically mediated by antibacterial and antifungal defense responses, CRMO by cellular response to cytokine, and JIA by cellular response to chemical stimulus. IFN patients particularly had the highest mean ISG score among all disease groups. CONCLUSION Our data show that blood transcriptomics combined with machine learning is a promising diagnostic tool for pediatric rheumatic diseases and may assist physicians in making data-driven and patient-specific decisions in clinical practice.
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Affiliation(s)
- My Kieu Ha
- Center for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium. .,Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium. .,Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium.
| | - Esther Bartholomeus
- grid.5284.b0000 0001 0790 3681Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium ,grid.411414.50000 0004 0626 3418Center of Medical Genetics, University of Antwerp, Antwerp University Hospital, Edegem, Belgium
| | - Luc Van Os
- grid.411414.50000 0004 0626 3418Ophthalmology Department, Antwerp University Hospital, Edegem, Belgium
| | - Julie Dandelooy
- grid.411414.50000 0004 0626 3418Dermatology Department, Antwerp University Hospital, Edegem, Belgium
| | - Julie Leysen
- grid.411414.50000 0004 0626 3418Dermatology Department, Antwerp University Hospital, Edegem, Belgium ,grid.5284.b0000 0001 0790 3681Department of Translational Research in Immunology and Inflammation, University of Antwerp, Wilrijk, Belgium
| | - Olivier Aerts
- grid.411414.50000 0004 0626 3418Dermatology Department, Antwerp University Hospital, Edegem, Belgium ,grid.5284.b0000 0001 0790 3681Department of Translational Research in Immunology and Inflammation, University of Antwerp, Wilrijk, Belgium
| | - Vasiliki Siozopoulou
- grid.411414.50000 0004 0626 3418Pathology Department, Antwerp University Hospital, Edegem, Belgium
| | - Eline De Smet
- grid.411414.50000 0004 0626 3418Radiology Department, Antwerp University Hospital, Edegem, Belgium
| | - Jan Gielen
- grid.411414.50000 0004 0626 3418Radiology Department, Antwerp University Hospital, Edegem, Belgium ,grid.5284.b0000 0001 0790 3681Department of Molecular – Morphology – Microscopy, University of Antwerp, Wilrijk, Belgium
| | - Khadija Guerti
- grid.411414.50000 0004 0626 3418Clinical Biology Department, Antwerp University Hospital, Edegem, Belgium
| | | | - Nele Herregods
- grid.410566.00000 0004 0626 3303Radiology Department, Ghent University Hospital, Ghent, Belgium
| | - Bouchra Lechkar
- grid.411414.50000 0004 0626 3418Department of Immunology, Allergology, and Rheumatology, Antwerp University Hospital, Edegem, Belgium
| | - Ruth Wittoek
- grid.410566.00000 0004 0626 3303Rheumatology Department, Ghent University Hospital, Ghent, Belgium ,grid.411414.50000 0004 0626 3418Rheumatology Department, Antwerp Hospital Network, Antwerp, Belgium
| | - Elke Geens
- grid.411414.50000 0004 0626 3418Rheumatology Department, Antwerp Hospital Network, Antwerp, Belgium
| | - Laura Claes
- grid.411414.50000 0004 0626 3418Pediatric Neurology Unit, Antwerp University Hospital, Edegem, Belgium
| | - Mahmoud Zaqout
- grid.411414.50000 0004 0626 3418Pediatric Cardiology Department, Antwerp University Hospital, Edegem, Belgium ,grid.411414.50000 0004 0626 3418Pediatric Cardiology Department, Antwerp Hospital Network, Antwerp, Belgium
| | - Wendy Dewals
- grid.411414.50000 0004 0626 3418Pediatric Cardiology Department, Antwerp University Hospital, Edegem, Belgium
| | - Annelies Lemay
- Department of Pediatrics, Turnhout General Hospital, Turnhout, Belgium
| | - David Tuerlinckx
- grid.7942.80000 0001 2294 713XDepartment of Pediatrics, Catholic University of Louvain, Louvain-la-Neuve, Belgium ,grid.6520.10000 0001 2242 8479Department of Pediatrics, Namur University Hospital Center, Site Dinant, Dinant, Belgium
| | - David Weynants
- grid.6520.10000 0001 2242 8479Department of Pediatrics, Namur University Hospital Center, Site Sainte-Elisabeth, Namur, Belgium
| | - Koen Vanlede
- Department of Pediatrics, Nikolaas General Hospital, Sint-Niklaas, Belgium
| | - Gerlant van Berlaer
- Department of Emergency Medicine/Pediatric Care, Brussels University Hospital, Jette, Belgium
| | - Marc Raes
- grid.414977.80000 0004 0578 1096Department of Pediatrics, Jessa Hospital, Hasselt, Belgium
| | - Helene Verhelst
- grid.410566.00000 0004 0626 3303Department of Pediatric Neurology, Ghent University Hospital, Ghent, Belgium
| | - Tine Boiy
- grid.411414.50000 0004 0626 3418Department of Pediatric Rheumatology, Antwerp University Hospital, Edegem, Belgium
| | - Pierre Van Damme
- grid.5284.b0000 0001 0790 3681Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681Center for the Evaluation of Vaccine, Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium
| | - Anna C. Jansen
- grid.411414.50000 0004 0626 3418Pediatric Neurology Unit, Antwerp University Hospital, Edegem, Belgium
| | - Marije Meuwissen
- grid.5284.b0000 0001 0790 3681Antwerp Center for Translational Immunology and Virology (ACTIV), Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium
| | - Vito Sabato
- grid.411414.50000 0004 0626 3418Department of Immunology, Allergology, and Rheumatology, Antwerp University Hospital, Edegem, Belgium ,Antwerp Center for Pediatric Rheumatology and Autoinflammatory Diseases, Antwerp, Belgium
| | - Guy Van Camp
- grid.411414.50000 0004 0626 3418Center of Medical Genetics, University of Antwerp, Antwerp University Hospital, Edegem, Belgium
| | - Arvid Suls
- grid.5284.b0000 0001 0790 3681Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium
| | | | - Joke Dehoorne
- grid.410566.00000 0004 0626 3303Department of Pediatric Rheumatology, Ghent University Hospital, Ghent, Belgium
| | - Rik Joos
- grid.411414.50000 0004 0626 3418Rheumatology Department, Antwerp Hospital Network, Antwerp, Belgium ,grid.411414.50000 0004 0626 3418Department of Pediatric Rheumatology, Antwerp University Hospital, Edegem, Belgium ,Antwerp Center for Pediatric Rheumatology and Autoinflammatory Diseases, Antwerp, Belgium ,grid.410566.00000 0004 0626 3303Department of Pediatric Rheumatology, Ghent University Hospital, Ghent, Belgium
| | - Kris Laukens
- grid.5284.b0000 0001 0790 3681Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681ADREM Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681Biomedical Informatics Research Network Antwerp, University of Antwerp, Antwerp, Belgium
| | - Pieter Meysman
- grid.5284.b0000 0001 0790 3681Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681ADREM Data Lab, Department of Mathematics and Computer Science, University of Antwerp, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681Biomedical Informatics Research Network Antwerp, University of Antwerp, Antwerp, Belgium
| | - Benson Ogunjimi
- Center for Health Economics Research and Modelling Infectious Diseases (CHERMID), Vaccine and Infectious Disease Institute, University of Antwerp, Wilrijk, Belgium. .,Antwerp Unit for Data Analysis and Computation in Immunology and Sequencing (AUDACIS), University of Antwerp, Antwerp, Belgium. .,Rheumatology Department, Antwerp Hospital Network, Antwerp, Belgium. .,Department of Pediatric Rheumatology, Antwerp University Hospital, Edegem, Belgium. .,Antwerp Center for Pediatric Rheumatology and Autoinflammatory Diseases, Antwerp, Belgium. .,Department of Pediatric Rheumatology, Brussels University Hospital, Jette, Belgium.
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Leyssens K, Van Regenmortel N, Roelant E, Guerti K, Couttenye MM, Jorens PG, Verbrugghe W, Van Craenenbroeck AH. Beta-Trace Protein as a Potential Marker of Acute Kidney Injury: A Pilot Study. Kidney Blood Press Res 2021; 46:185-195. [PMID: 33784671 DOI: 10.1159/000514173] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2020] [Accepted: 12/24/2020] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION Acute kidney injury (AKI) is a frequent complication among patients in the intensive care unit (ICU). The limitations of serum Cr (sCr) in timely detecting AKI are well known. Beta-trace protein (BTP) is emerging as a novel endogenous glomerular filtration rate marker. The aim of this study was to explore the role of BTP as a marker of AKI. METHODS Patients admitted to the ICU undergoing surgery were included. BTP, sCr, Cystatin C (CysC), and neutrophil gelatinase-associated lipocalin (NGAL) were measured preoperatively, postoperatively (post-op), and at the first (D1) and second (D2) post-op day. AKI was defined as an increase of sCr to ≥1.5-fold from baseline within 2 days after surgery. RESULTS Of the 52 patients studied, 10 patients (19%) developed AKI. Patients with AKI were older (69.6 ± 10.7 vs. 58.1 ± 16.7 years, p = 0.043) and had a longer length of ICU stay (13 [IQR 6-49] vs. 6 [IQR 5-8] days, p = 0.032). Between the 2 groups, the evolution of BTP, sCr, CysC, and NGAL over time differed significantly, with overall higher values in the AKI group. ROC analysis for the detection of AKI within 2 days after surgery showed a great accuracy for BTP. The area under the curve (AUC) for BTP post-op; D1; and D2 was, respectively, 0.869 ± 0.049; 0.938 ± 0.035; and 0.943 ± 0.032. The discriminative power of a BTP measurement on D1 was superior in detecting AKI compared to NGAL (adjusted p value = 0.027). We could not detect a significant difference between the AUCs of other biomarkers (NGAL, sCr, and CysC). CONCLUSION Serum BTP is a promising marker for diagnosing AKI in ICU patients undergoing surgery.
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Affiliation(s)
- Katrien Leyssens
- Department of Nephrology and Hypertension, Antwerp University Hospital, Edegem, Belgium
| | | | - Ella Roelant
- Clinical Trial Center (CTC), Antwerp University Hospital, Edegem, Belgium
| | - Khadija Guerti
- Department of Clinical Chemistry, Antwerp University Hospital, Edegem, Belgium
| | - Marie Madeleine Couttenye
- Department of Nephrology and Hypertension, Antwerp University Hospital, Edegem, Belgium.,Laboratory of Experimental Medicine and Pediatrics, University of Antwerp, Antwerp, Belgium
| | - Philippe G Jorens
- Department of Intensive Care Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Walter Verbrugghe
- Department of Intensive Care Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Amaryllis H Van Craenenbroeck
- Department of Nephrology and Renal Transplantation, University Hospital Leuven, Leuven, Belgium.,Laboratory of Experimental Medicine and Pediatrics, University of Antwerp, Antwerp, Belgium
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Abstract
The aim of this study was to determine the time to positivity (TTP) of neonatal blood cultures, to investigate differences between early onset versus late-onset sepsis, and non-proven versus proven sepsis, and to examine differences in TTP by organism type using a retrospective observational study at the Neonatal Intensive Care Unit, Antwerp University Hospital, Belgium. The subjects were 1828 neonates with suspected sepsis who were treated with antimicrobials for at least 3 days. The TTP was recorded for all episodes of suspected sepsis in an approximately 6.5 year period. A total of 2916 blood cultures were collected, of which 437 (15%) became positive. The overall TTP was 21.33 h (Q1-Q3 13.17-32.46). The difference between the median TTP in early onset versus late-onset sepsis was 0.83 h (22.00 versus 21.17 h, P=0.75). The median TTP for Gram-negative organisms was 11.17 h (Q1-Q3 8.84-15.67), whereas the median TTP for Gram-positive organisms was 23.59 h (Q1-Q3 15.29-34.58, P<0.001). In Gram-positive isolates, the median TTP for coagulase-negative staphylococci (CNS) was 26.67 h (Q1-Q3 19.00-38.17), whereas the median TTP for non-CNS was 12.83 h (Q1-Q3 10.50-18.17, P<0.001). The median TTP in proven sepsis was 20.17 h (Q1-Q3 13.00-30.37), whereas it was 29.67 h (Q1-Q3 21.17-50.63, P<0.001) in non-proven sepsis. TTP of neonatal blood cultures was significantly shorter for Gram-negative organisms. We suggest shortening the total incubation time of neonatal blood cultures to a maximum of 3 days. However, blood cultures collected in infants<72 h of age might require a longer incubation time. According to our results, it may be safe to narrow the antimicrobial spectrum to solely target Gram-positive bacteria when the culture is still negative after 48 h, and to cease antimicrobial therapy when the culture is still negative after 72 h in clinically well infants.
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Affiliation(s)
- Khadija Guerti
- Department of Laboratory Medicine, Division of Immunology, Antwerp University Hospital and Faculty of Medicine, Antwerp University, B-2650 Edegem, Belgium
| | - Helena Devos
- Department of Laboratory Medicine, Division of Immunology, Antwerp University Hospital and Faculty of Medicine, Antwerp University, B-2650 Edegem, Belgium
| | - Margareta M Ieven
- Department of Laboratory Medicine, Division of Microbiology, Antwerp University Hospital and Faculty of Medicine, Antwerp University, B-2650 Edegem, Belgium
| | - Ludo M Mahieu
- Department of Pediatrics, Division of Neonatology, Antwerp University Hospital and Faculty of Medicine, Antwerp University, B-2650 Edegem, Belgium
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