Identification and Validation of a Urinary Biomarker Panel to Accurately Diagnose and Predict Response to Therapy in Lupus Nephritis.

Adiponectin Biomarkers / urine Cross-Sectional Studies Humans Kidney / pathology Lupus Nephritis / diagnosis
predictors of response biomarkers lupus nephritis systemic lupus erythematosus urinary biomarker

Journal

Frontiers in immunology
ISSN: 1664-3224
Titre abrégé: Front Immunol
Pays: Switzerland
ID NLM: 101560960

Informations de publication

Date de publication:
2022
Historique:
received: 04 03 2022
accepted: 02 05 2022
entrez: 17 6 2022
pubmed: 18 6 2022
medline: 22 6 2022
Statut: epublish

Résumé

We have previously shown that 15 urinary biomarkers (of 129 tested by Luminex), discriminate between active Lupus Nephritis (ALN) and non-LN patients. The aim of this study was to evaluate the ability of these 15 previously-identified urinary biomarkers to predict treatment responses to conventional therapy, and for the most predictive of these biomarkers to validate their utility to identify ALN patients in an independent prospectively-acquired lupus cohort. Our study had a 3-stage approach. In stage 1, we used Luminex to examine whether our previously identified urinary biomarkers at the time of the renal flare ( ± 3 months) or 12 ± 3 months after treatment of biopsy-proven ALN could predict treatment responses. In stage 2, a larger prospectively-acquired cross-sectional cohort was used to further validate the utility of the most predictive urinary biomarkers (identified in stage 1) to detect ALN patients. In this 2 Twenty-one patients were included in stage 1. Twelve (57.1%), 4 (19.1%), and 5 (23.8%) patients had a complete (CR), partial (PR) and no (NR) remission at 24 ± 3 months, respectively. The percentage decrease following 12 ± 3 months of treatment for Adiponectin, MCP-1, sVCAM-1, PF4, IL-15 and vWF was significantly higher in patients with CR in comparison to those with PR/NR. In stage 2, a total of 247 SLE patients were included, of which 24 (9.7%) had ALN, 79 (31.9%) had LN in remission (RLN) and 144 (58.3%) were non-LN (NLN) patients. Based on the combinations of biomarkers with the best operating characteristics we propose "rule out" and "rule in" ALN criteria. In stage 3, 53 biopsy-proven ALN patients were included, 35 with proliferative LN and 18 with non-proliferative ALN, demonstrating that our "rule in ALN" criteria operate better in detecting active proliferative than non-proliferative classes. Our results provide further evidence to support the role of Adiponectin, MCP-1, sVCAM-1 and PF4 in the detection of proliferative ALN cases. We further show the clinical utility of measuring multiple rather than a single biomarker and we propose novel "rule in" and "rule out" criteria for the detection of proliferative ALN with excellent operating characteristics.

Sections du résumé

Background
We have previously shown that 15 urinary biomarkers (of 129 tested by Luminex), discriminate between active Lupus Nephritis (ALN) and non-LN patients. The aim of this study was to evaluate the ability of these 15 previously-identified urinary biomarkers to predict treatment responses to conventional therapy, and for the most predictive of these biomarkers to validate their utility to identify ALN patients in an independent prospectively-acquired lupus cohort.
Methods
Our study had a 3-stage approach. In stage 1, we used Luminex to examine whether our previously identified urinary biomarkers at the time of the renal flare ( ± 3 months) or 12 ± 3 months after treatment of biopsy-proven ALN could predict treatment responses. In stage 2, a larger prospectively-acquired cross-sectional cohort was used to further validate the utility of the most predictive urinary biomarkers (identified in stage 1) to detect ALN patients. In this 2
Results
Twenty-one patients were included in stage 1. Twelve (57.1%), 4 (19.1%), and 5 (23.8%) patients had a complete (CR), partial (PR) and no (NR) remission at 24 ± 3 months, respectively. The percentage decrease following 12 ± 3 months of treatment for Adiponectin, MCP-1, sVCAM-1, PF4, IL-15 and vWF was significantly higher in patients with CR in comparison to those with PR/NR. In stage 2, a total of 247 SLE patients were included, of which 24 (9.7%) had ALN, 79 (31.9%) had LN in remission (RLN) and 144 (58.3%) were non-LN (NLN) patients. Based on the combinations of biomarkers with the best operating characteristics we propose "rule out" and "rule in" ALN criteria. In stage 3, 53 biopsy-proven ALN patients were included, 35 with proliferative LN and 18 with non-proliferative ALN, demonstrating that our "rule in ALN" criteria operate better in detecting active proliferative than non-proliferative classes.
Conclusions
Our results provide further evidence to support the role of Adiponectin, MCP-1, sVCAM-1 and PF4 in the detection of proliferative ALN cases. We further show the clinical utility of measuring multiple rather than a single biomarker and we propose novel "rule in" and "rule out" criteria for the detection of proliferative ALN with excellent operating characteristics.

Identifiants

DOI: 10.3389/fimmu.2022.889931 PMID: 35711439 PMC: PMC9196040
pubmed: 35711439
doi: 10.3389/fimmu.2022.889931
pmc: PMC9196040
doi:

Substances chimiques

Adiponectin 0
Biomarkers 0

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

889931

Subventions

Organisme : CIHR
Pays : Canada

Informations de copyright

Copyright © 2022 Whittall-Garcia, Goliad, Kim, Bonilla, Gladman, Urowitz, Fortin, Atenafu, Touma and Wither.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Laura Whittall-Garcia (L)

Division of Rheumatology, Department of Medicine, Toronto Western Hospital, University of Toronto, Toronto, ON, Canada.
Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, ON, Canada.
University of Toronto Lupus Clinic, Centre for Prognosis Studies in the Rheumatic Diseases, Toronto Western Hospital, University Health Network, Toronto, ON, Canada.

Kirubel Goliad (K)

Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, ON, Canada.
Department of Immunology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.

Michael Kim (M)

Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, ON, Canada.

Dennisse Bonilla (D)

Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, ON, Canada.
University of Toronto Lupus Clinic, Centre for Prognosis Studies in the Rheumatic Diseases, Toronto Western Hospital, University Health Network, Toronto, ON, Canada.

Dafna Gladman (D)

Division of Rheumatology, Department of Medicine, Toronto Western Hospital, University of Toronto, Toronto, ON, Canada.
Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, ON, Canada.
University of Toronto Lupus Clinic, Centre for Prognosis Studies in the Rheumatic Diseases, Toronto Western Hospital, University Health Network, Toronto, ON, Canada.

Murray Urowitz (M)

Division of Rheumatology, Department of Medicine, Toronto Western Hospital, University of Toronto, Toronto, ON, Canada.
Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, ON, Canada.
University of Toronto Lupus Clinic, Centre for Prognosis Studies in the Rheumatic Diseases, Toronto Western Hospital, University Health Network, Toronto, ON, Canada.

Paul R Fortin (PR)

Division of Rheumatology, Department of Medicine, Centre de recherche du CHU de Québec-Université Laval, Quebec City, QC, Canada.

Eshetu G Atenafu (EG)

Department of Biostatistics, University Health Network, Toronto, ON, Canada.

Zahi Touma (Z)

Division of Rheumatology, Department of Medicine, Toronto Western Hospital, University of Toronto, Toronto, ON, Canada.
Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, ON, Canada.
University of Toronto Lupus Clinic, Centre for Prognosis Studies in the Rheumatic Diseases, Toronto Western Hospital, University Health Network, Toronto, ON, Canada.

Joan Wither (J)

Division of Rheumatology, Department of Medicine, Toronto Western Hospital, University of Toronto, Toronto, ON, Canada.
Schroeder Arthritis Institute, Krembil Research Institute, University Health Network, Toronto, ON, Canada.
University of Toronto Lupus Clinic, Centre for Prognosis Studies in the Rheumatic Diseases, Toronto Western Hospital, University Health Network, Toronto, ON, Canada.
Department of Immunology, Faculty of Medicine, University of Toronto, Toronto, ON, Canada.

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Classifications MeSH

questionsmedicales.fr › Facteurs biologiques › Protéines et peptides de signalisation intercellulaire › Adipokines › Adiponectine › Identification and Validation of a Urinary...
questionsmedicales.fr › Facteurs biologiques › Marqueurs biologiques › Identification and Validation of a Urinary...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Caractéristiques des études épidémiologiques › Études épidémiologiques › Études transversales › Identification and Validation of a Urinary...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Identification and Validation of a Urinary...
questionsmedicales.fr › Appareil urogénital › Voies urinaires › Rein › Identification and Validation of a Urinary...
questionsmedicales.fr › Maladies du système immunitaire › Maladies auto-immunes › Lupus érythémateux disséminé › Glomérulonéphrite lupique › Identification and Validation of a Urinary...