A novel multiplex biomarker panel for profiling human acute and chronic kidney disease
Abstract Acute and chronic kidney disease continues to confer significant morbidity and mortality in the clinical setting. Despite high prevalence of these conditions, few validated biomarkers exist to predict kidney dysfunction. In this study, we utilized a novel kidney multiplex panel to measure 2...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-12-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-023-47418-9 |
| _version_ | 1797415576853807104 |
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| author | Logan R. Van Nynatten Michael R. Miller Maitray A. Patel Mark Daley Guido Filler Sigrun Badrnya Markus Miholits Brian Webb Christopher W. McIntyre Douglas D. Fraser |
| author_facet | Logan R. Van Nynatten Michael R. Miller Maitray A. Patel Mark Daley Guido Filler Sigrun Badrnya Markus Miholits Brian Webb Christopher W. McIntyre Douglas D. Fraser |
| author_sort | Logan R. Van Nynatten |
| collection | DOAJ |
| description | Abstract Acute and chronic kidney disease continues to confer significant morbidity and mortality in the clinical setting. Despite high prevalence of these conditions, few validated biomarkers exist to predict kidney dysfunction. In this study, we utilized a novel kidney multiplex panel to measure 21 proteins in plasma and urine to characterize the spectrum of biomarker profiles in kidney disease. Blood and urine samples were obtained from age-/sex-matched healthy control subjects (HC), critically-ill COVID-19 patients with acute kidney injury (AKI), and patients with chronic or end-stage kidney disease (CKD/ESKD). Biomarkers were measured with a kidney multiplex panel, and results analyzed with conventional statistics and machine learning. Correlations were examined between biomarkers and patient clinical and laboratory variables. Median AKI subject age was 65.5 (IQR 58.5–73.0) and median CKD/ESKD age was 65.0 (IQR 50.0–71.5). Of the CKD/ESKD patients, 76.1% were on hemodialysis, 14.3% of patients had kidney transplant, and 9.5% had CKD without kidney replacement therapy. In plasma, 19 proteins were significantly different in titer between the HC versus AKI versus CKD/ESKD groups, while NAG and RBP4 were unchanged. TIMP-1 (PPV 1.0, NPV 1.0), best distinguished AKI from HC, and TFF3 (PPV 0.99, NPV 0.89) best distinguished CKD/ESKD from HC. In urine, 18 proteins were significantly different between groups except Calbindin, Osteopontin and TIMP-1. Osteoactivin (PPV 0.95, NPV 0.95) best distinguished AKI from HC, and β2-microglobulin (PPV 0.96, NPV 0.78) best distinguished CKD/ESKD from HC. A variety of correlations were noted between patient variables and either plasma or urine biomarkers. Using a novel kidney multiplex biomarker panel, together with conventional statistics and machine learning, we identified unique biomarker profiles in the plasma and urine of patients with AKI and CKD/ESKD. We demonstrated correlations between biomarker profiles and patient clinical variables. Our exploratory study provides biomarker data for future hypothesis driven research on kidney disease. |
| first_indexed | 2024-03-09T05:50:44Z |
| format | Article |
| id | doaj.art-e0badcdf9b7d4abe999b40d86cbb7ae5 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-03-09T05:50:44Z |
| publishDate | 2023-12-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-e0badcdf9b7d4abe999b40d86cbb7ae52023-12-03T12:18:11ZengNature PortfolioScientific Reports2045-23222023-12-0113111710.1038/s41598-023-47418-9A novel multiplex biomarker panel for profiling human acute and chronic kidney diseaseLogan R. Van Nynatten0Michael R. Miller1Maitray A. Patel2Mark Daley3Guido Filler4Sigrun Badrnya5Markus Miholits6Brian Webb7Christopher W. McIntyre8Douglas D. Fraser9Medicine, Western UniversityPediatrics, Western UniversityEpidemiology and Biostatistics, Western UniversityEpidemiology and Biostatistics, Western UniversityMedicine, Western UniversityThermo Fisher ScientificThermo Fisher ScientificThermo Fisher ScientificMedicine, Western UniversityPediatrics, Western UniversityAbstract Acute and chronic kidney disease continues to confer significant morbidity and mortality in the clinical setting. Despite high prevalence of these conditions, few validated biomarkers exist to predict kidney dysfunction. In this study, we utilized a novel kidney multiplex panel to measure 21 proteins in plasma and urine to characterize the spectrum of biomarker profiles in kidney disease. Blood and urine samples were obtained from age-/sex-matched healthy control subjects (HC), critically-ill COVID-19 patients with acute kidney injury (AKI), and patients with chronic or end-stage kidney disease (CKD/ESKD). Biomarkers were measured with a kidney multiplex panel, and results analyzed with conventional statistics and machine learning. Correlations were examined between biomarkers and patient clinical and laboratory variables. Median AKI subject age was 65.5 (IQR 58.5–73.0) and median CKD/ESKD age was 65.0 (IQR 50.0–71.5). Of the CKD/ESKD patients, 76.1% were on hemodialysis, 14.3% of patients had kidney transplant, and 9.5% had CKD without kidney replacement therapy. In plasma, 19 proteins were significantly different in titer between the HC versus AKI versus CKD/ESKD groups, while NAG and RBP4 were unchanged. TIMP-1 (PPV 1.0, NPV 1.0), best distinguished AKI from HC, and TFF3 (PPV 0.99, NPV 0.89) best distinguished CKD/ESKD from HC. In urine, 18 proteins were significantly different between groups except Calbindin, Osteopontin and TIMP-1. Osteoactivin (PPV 0.95, NPV 0.95) best distinguished AKI from HC, and β2-microglobulin (PPV 0.96, NPV 0.78) best distinguished CKD/ESKD from HC. A variety of correlations were noted between patient variables and either plasma or urine biomarkers. Using a novel kidney multiplex biomarker panel, together with conventional statistics and machine learning, we identified unique biomarker profiles in the plasma and urine of patients with AKI and CKD/ESKD. We demonstrated correlations between biomarker profiles and patient clinical variables. Our exploratory study provides biomarker data for future hypothesis driven research on kidney disease.https://doi.org/10.1038/s41598-023-47418-9 |
| spellingShingle | Logan R. Van Nynatten Michael R. Miller Maitray A. Patel Mark Daley Guido Filler Sigrun Badrnya Markus Miholits Brian Webb Christopher W. McIntyre Douglas D. Fraser A novel multiplex biomarker panel for profiling human acute and chronic kidney disease Scientific Reports |
| title | A novel multiplex biomarker panel for profiling human acute and chronic kidney disease |
| title_full | A novel multiplex biomarker panel for profiling human acute and chronic kidney disease |
| title_fullStr | A novel multiplex biomarker panel for profiling human acute and chronic kidney disease |
| title_full_unstemmed | A novel multiplex biomarker panel for profiling human acute and chronic kidney disease |
| title_short | A novel multiplex biomarker panel for profiling human acute and chronic kidney disease |
| title_sort | novel multiplex biomarker panel for profiling human acute and chronic kidney disease |
| url | https://doi.org/10.1038/s41598-023-47418-9 |
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