Comparison of Aptamer-Based and Antibody-Based Assays for Protein Quantification in Chronic Kidney Disease.

AASK (African American Study of Kidney Disease and Hypertension) antibodies biological assay chronic inflammation chronic kidney disease end-stage renal disease mortality

Journal

Clinical journal of the American Society of Nephrology : CJASN
ISSN: 1555-905X
Titre abrégé: Clin J Am Soc Nephrol
Pays: United States
ID NLM: 101271570

Informations de publication

Date de publication:
03 2022
Historique:
received: 02 09 2021
accepted: 14 01 2022
pubmed: 25 2 2022
medline: 23 4 2022
entrez: 24 2 2022
Statut: ppublish

Résumé

Novel aptamer-based technologies can identify >7000 analytes per sample, offering a high-throughput alternative to traditional immunoassays in biomarker discovery. However, the specificity for distinct proteins has not been thoroughly studied in the context of CKD. We assessed the use of SOMAscan, an aptamer-based technology, for the quantification of eight immune activation biomarkers and cystatin C among 498 African American Study of Kidney Disease and Hypertension (AASK) participants using immunoassays as the gold standard. We evaluated correlations of serum proteins as measured by SOMAscan versus immunoassays with each other and with iothalamate-measured GFR. We then compared associations between proteins measurement with risks of incident kidney failure and all-cause mortality. Six biomarkers (IL-8, soluble TNF receptor superfamily member 1B [TNFRSF1B], cystatin C, soluble TNF receptor superfamily member 1A [TNFRSF1A], IL-6, and soluble urokinase-type plasminogen activator receptor [suPAR]) had non-negligible correlations ( SOMAscan is an efficient and relatively reliable technique for quantifying IL-8, TNFRSF1B, cystatin C, and TNFRSF1A in CKD and detecting their potential associations with clinical outcomes. This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2022_02_23_CJN11700921.mp3.

Sections du résumé

BACKGROUND AND OBJECTIVES
Novel aptamer-based technologies can identify >7000 analytes per sample, offering a high-throughput alternative to traditional immunoassays in biomarker discovery. However, the specificity for distinct proteins has not been thoroughly studied in the context of CKD.
DESIGN, SETTING, PARTICIPANTS, & MEASUREMENTS
We assessed the use of SOMAscan, an aptamer-based technology, for the quantification of eight immune activation biomarkers and cystatin C among 498 African American Study of Kidney Disease and Hypertension (AASK) participants using immunoassays as the gold standard. We evaluated correlations of serum proteins as measured by SOMAscan versus immunoassays with each other and with iothalamate-measured GFR. We then compared associations between proteins measurement with risks of incident kidney failure and all-cause mortality.
RESULTS
Six biomarkers (IL-8, soluble TNF receptor superfamily member 1B [TNFRSF1B], cystatin C, soluble TNF receptor superfamily member 1A [TNFRSF1A], IL-6, and soluble urokinase-type plasminogen activator receptor [suPAR]) had non-negligible correlations (
CONCLUSIONS
SOMAscan is an efficient and relatively reliable technique for quantifying IL-8, TNFRSF1B, cystatin C, and TNFRSF1A in CKD and detecting their potential associations with clinical outcomes.
PODCAST
This article contains a podcast at https://www.asn-online.org/media/podcast/CJASN/2022_02_23_CJN11700921.mp3.

Identifiants

pubmed: 35197258
pii: 01277230-202203000-00006
doi: 10.2215/CJN.11700921
pmc: PMC8975030
doi:

Substances chimiques

Biomarkers 0
Cystatin C 0
Interleukin-8 0
Receptors, Tumor Necrosis Factor 0
Receptors, Urokinase Plasminogen Activator 0

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

350-360

Subventions

Organisme : NIDDK NIH HHS
ID : U01 DK048689
Pays : United States
Organisme : NCRR NIH HHS
ID : P20 RR011104
Pays : United States
Organisme : NIDDK NIH HHS
ID : P30 DK079310
Pays : United States
Organisme : NIDDK NIH HHS
ID : U01 DK106962
Pays : United States
Organisme : NIDDK NIH HHS
ID : K08 DK117068
Pays : United States
Organisme : NCRR NIH HHS
ID : M01 RR000071
Pays : United States
Organisme : NCRR NIH HHS
ID : P20 RR011145
Pays : United States
Organisme : NHLBI NIH HHS
ID : K24 HL155861
Pays : United States
Organisme : NIDDK NIH HHS
ID : R01 DK057867
Pays : United States
Organisme : NCRR NIH HHS
ID : M01 RR000052
Pays : United States
Organisme : NCRR NIH HHS
ID : UL1 RR029887
Pays : United States
Organisme : NIDDK NIH HHS
ID : K24 DK002818
Pays : United States
Organisme : NCRR NIH HHS
ID : M01 RR000827
Pays : United States
Organisme : NCRR NIH HHS
ID : M01 RR000080
Pays : United States

Informations de copyright

Copyright © 2022 by the American Society of Nephrology.

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Auteurs

Carolina Lopez-Silva (C)

Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.

Aditya Surapaneni (A)

Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, Maryland.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.

Josef Coresh (J)

Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, Maryland.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.

Jochen Reiser (J)

Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois.

Chirag R Parikh (CR)

Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, Maryland.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.

Wassim Obeid (W)

Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.

Morgan E Grams (ME)

Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, Maryland.
Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.

Teresa K Chen (TK)

Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Medical Institutions, Baltimore, Maryland.

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