TY - JOUR
T1 - Comparison of Aptamer-Based and Antibody-Based Assays for Protein Quantification in Chronic Kidney Disease
AU - Lopez-Silva, Carolina
AU - Surapaneni, Aditya
AU - Coresh, Josef
AU - Reiser, Jochen
AU - Parikh, Chirag R.
AU - Obeid, Wassim
AU - Grams, Morgan E.
AU - Chen, Teresa K.
N1 - Funding Information:
AASK was conducted by the AASK investigators and supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). The data and samples from the AASK trial reported here were supplied by the NIDDK Central Repositories. The AASK trial and cohort were supported by National Institutes of Health (NIH), NIDDK institutional grants M01 RR-00080, M01 RR-00071, M0100032, P20-RR11145, M01 RR00827, M01 RR00052, 2P20 RR11104, RR029887, DK 2818-02, DK057867, and DK048689 and the following pharmaceutical companies: AstraZeneca, Forest Laboratories, GlaxoSmithKline, King Pharmaceuticals, Pfizer, Pharmacia, and Upjohn.
Funding Information:
T.K. Chen is supported by a George M. O?Brien Center for Kidney Research Pilot and Feasibility Grant from Yale University (National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases grant P30DK079310) and National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases grant K08DK117068. M.E. Grams is supported by National Institutes of Health, National Heart, Lung and Blood Institute grant K24HL155861 and National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases grant R01DK108803. C.R. Parikh is supported by National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases grant U01DK106962. Data and samples for TNFRSF1A, TNFRSF1B, TNF-?, IFN-?, IL-6, IL-8, and IL-10 immunoassay measurements were supplied by the National Institute of Diabetes and Digestive and Kidney Diseases Central Repositories via National Institute of Diabetes and Digestive and Kidney Diseases grant X01DK118497 and measured by the Translational Research Core of the George M. O?Brien Kidney Center. Acknowledgments The authors thank the staff and participants of AASK. Portions of this work were presented at the 2021 American Society of Nephrology Kidney Week (November 2021). AASK was conducted by the AASK investigators and supported by the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK). The data and samples from the AASK trial reported here were supplied by the NIDDK Central Repositories. The AASK trial and cohort were supported by National Institutes of Health (NIH), NIDDK institutional grants M01 RR-00080, M01 RR-00071, M0100032, P20-RR11145, M01 RR00827, M01 RR00052, 2P20 RR11104, RR029887, DK 2818-02, DK057867, and DK048689 and the following pharmaceutical companies: AstraZeneca, Forest Laborato-ries, GlaxoSmithKline, King Pharmaceuticals, Pfizer, Pharmacia, and Upjohn. This manuscript was not prepared in collaboration with investigators of AASK and does not necessarily reflect the opinions or views of AASK, the NIDDK Central Repositories, NIH, or NIDDK.
Funding Information:
T.K. Chen is supported by a George M. O’Brien Center for Kidney Research Pilot and Feasibility Grant from Yale University (National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases grant P30DK079310) and National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases grant K08DK117068. M.E. Grams is supported by National Institutes of Health, National Heart, Lung and Blood Institute grant K24HL155861 and National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases grant R01DK108803. C.R. Parikh is supported by National Institutes of Health, National Institute of Diabetes and Digestive and Kidney Diseases grant U01DK106962. Data and samples for TNFRSF1A, TNFRSF1B, TNF-a, IFN-g, IL-6, IL-8, and IL-10 immunoassay measurements were supplied by the National Institute of Diabetes and Digestive and Kidney Diseases Central Repositories via National Institute of Diabetes and Digestive and Kidney Diseases grant X01DK118497 and measured by the Translational Research Core of the George M. O’Brien Kidney Center.
Funding Information:
T.K. Chen reports research funding from the National Institutes of Health (NIH)/the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) and Yale University. J. Coresh reports consultancy agreements with Healthy.io; ownership interest in Healthy.io; research funding from the National Kidney Foundation (NKF; which receives industry support) and NIH; an approximately $3000 honorarium from Abbott on May 23, 2012 for a presentation on the topic of the interaction of eGFR and renal cardiovascular disease; and serving as a scientific advisor or member of Healthy.io and NKF. M.E. Grams reports honoraria from academic institutions for giving grand rounds and American Diabetes Association for reviewing abstracts; serving in an advisory or leadership role for American Journal of Kidney Diseases, CJASN, the JASN Editorial Fellowship Committee, the Kidney Disease Improving Global Outcomes Executive Committee, the NKF Scientific Advisory Board, and the United States Renal Data System Scientific Advisory Board; and other interests or relationships with NKF, which in turn receives funding from Abbvie, Relypsa, and Thrasos, among others. C. Lopez-Silva received Dean’s Summer Research Funding from Johns Hopkins University School of Medicine while completing this manuscript. C.R. Parikh reports consultancy agreements with Genfit Biopharmaceutical Company and Novartis; is a member of the advisory board of and owns equity in RenalytixAI; reports research funding from the National Heart, Lung and Blood Institute and NIDDK; and reports serving in an advisory or leadership role for Genfit Biopharmaceutical Company. J. Reiser reports consultancy agreements with Mantra Bio, Visterra, and Walden Biosciences; ownership interest in Walden Biosciences; research funding from Walden Biosciences; honoraria from Visterra; serving in an advisory or leadership role for Walden Biosciences (cochair of the scientific advisory board); and other interests or relationships with Nephcure Kidney International. J. Reiser is an inventor on issued and pending patents pertinent to novel methods and treatments for proteinuric kidney diseases and stands to gain royalties from future commercialization. J. Reiser is also a scientific cofounder and shareholder of Walden Biosciences (formerly TRISAQ), a biotechnology company. Parts of J. Reiser’s intellectual property have been outlicensed to Miltenyi Biotech. All remaining authors have nothing to disclose.
Publisher Copyright:
© 2022 by the American Society of Nephrology.
PY - 2022/3
Y1 - 2022/3
N2 - 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 (r=0.94, 0.93, 0.89, 0.85, 0.46, and 0.23, respectively) between SOMAscan and immunoassay measurements, and three (IL-10, IFN-γ, and TNF-α) were uncorrelated (r=0.08, 0.07, and 0.02, respectively). Of the six biomarkers with non-negligible correlations, TNFRSF1B, cystatin C, TNFRSF1A, and suPAR were negatively correlated with measured GFR and associated with higher risk of kidney failure. IL-8, TNFRSF1B, cystatin C, TNFRSF1A, and suPAR were associated with a higher risk of mortality via both methods. On average, immunoassay measurements were more strongly associated with adverse outcomes than their SOMAscan counterparts. 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.
AB - 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 (r=0.94, 0.93, 0.89, 0.85, 0.46, and 0.23, respectively) between SOMAscan and immunoassay measurements, and three (IL-10, IFN-γ, and TNF-α) were uncorrelated (r=0.08, 0.07, and 0.02, respectively). Of the six biomarkers with non-negligible correlations, TNFRSF1B, cystatin C, TNFRSF1A, and suPAR were negatively correlated with measured GFR and associated with higher risk of kidney failure. IL-8, TNFRSF1B, cystatin C, TNFRSF1A, and suPAR were associated with a higher risk of mortality via both methods. On average, immunoassay measurements were more strongly associated with adverse outcomes than their SOMAscan counterparts. 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.
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U2 - 10.2215/CJN.11700921
DO - 10.2215/CJN.11700921
M3 - Article
C2 - 35197258
AN - SCOPUS:85125964698
SN - 1555-9041
VL - 17
SP - 350
EP - 360
JO - Clinical journal of the American Society of Nephrology : CJASN
JF - Clinical journal of the American Society of Nephrology : CJASN
IS - 3
ER -