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Austin TR, Nethander M, Fink HA, Törnqvist AE, Jalal DI, Buzkova P, Barzilay JI, Carbone L, Gabrielsen ME, Grahnemo L, Lu T, Hveem K, Jonasson C, Kizer JR, Langhammer A, Mukamal KJ, Gerszten RE, Psaty BM, Robbins JA, Sun YV, Skogholt AH, Kanis JA, Johansson H, Åsvold BO, Valderrabano RJ, Zheng J, Richards JB, Coward E, Ohlsson C. A plasma protein-based risk score to predict hip fractures. NATURE AGING 2024:10.1038/s43587-024-00639-7. [PMID: 38802582 DOI: 10.1038/s43587-024-00639-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2024] [Accepted: 05/01/2024] [Indexed: 05/29/2024]
Abstract
As there are effective treatments to reduce hip fractures, identification of patients at high risk of hip fracture is important to inform efficient intervention strategies. To obtain a new tool for hip fracture prediction, we developed a protein-based risk score in the Cardiovascular Health Study using an aptamer-based proteomic platform. The proteomic risk score predicted incident hip fractures and improved hip fracture discrimination in two Trøndelag Health Study validation cohorts using the same aptamer-based platform. When transferred to an antibody-based proteomic platform in a UK Biobank validation cohort, the proteomic risk score was strongly associated with hip fractures (hazard ratio per s.d. increase, 1.64; 95% confidence interval 1.53-1.77). The proteomic risk score, but not available polygenic risk scores for fractures or bone mineral density, improved the C-index beyond the fracture risk assessment tool (FRAX), which integrates information from clinical risk factors (C-index, FRAX 0.735 versus FRAX + proteomic risk score 0.776). The developed proteomic risk score constitutes a new tool for stratifying patients according to hip fracture risk; however, its improvement in hip fracture discrimination is modest and its clinical utility beyond FRAX with information on femoral neck bone mineral density remains to be determined.
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Affiliation(s)
- Thomas R Austin
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, US
| | - Maria Nethander
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Bioinformatics and Data Center, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Howard A Fink
- Geriatric Research Education and Clinical Center, VA Health Care System, Minneapolis, MN, US
- Department of Medicine, University of Minnesota, Minneapolis, MN, US
| | - Anna E Törnqvist
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Diana I Jalal
- Division of Nephrology, Department of Internal Medicine, Carver College of Medicine, Iowa City, IA, US
- Iowa City VA Medical Center, Iowa City, IA, US
| | - Petra Buzkova
- Department of Biostatistics, University of Washington, Seattle, WA, US
| | - Joshua I Barzilay
- Division of Endocrinology, Kaiser Permanente of Georgia, Atlanta, GA, US
| | - Laura Carbone
- Charlie Norwood VAMC, Augusta, GA, US
- Division of Rheumatology, Department of Medicine, Medical College of Georgia, Augusta University, Augusta, GA, US
| | - Maiken E Gabrielsen
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Louise Grahnemo
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Tianyuan Lu
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Quantitative Life Sciences Program, McGill University, Montreal, Quebec, Canada
- 5 Prime Sciences Inc, Montreal, Quebec, Canada
| | - Kristian Hveem
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- HUNT Research Centre, NTNU, Levanger, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Christian Jonasson
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Jorge R Kizer
- Cardiology Section, San Francisco VA Health Care System, San Francisco, CA, US
- Department of Medicine, Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, US
| | - Arnulf Langhammer
- HUNT Research Centre, NTNU, Levanger, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Kenneth J Mukamal
- Department of Medicine, Beth Israel Deaconess Medical Center, Brookline, MA, US
| | - Robert E Gerszten
- Department of Medicine, Beth Israel Deaconess Medical Center, Brookline, MA, US
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, US
- Departments of Medicine, Epidemiology, and Health Systems and Population Health, University of Washington, Seattle, WA, US
| | - John A Robbins
- Department of Medicine, University of California, Davis, CA, US
| | - Yan V Sun
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, US
| | - Anne Heidi Skogholt
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - John A Kanis
- Centre for Metabolic Bone Diseases, University of Sheffield Medical School, Sheffield, UK
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
| | - Helena Johansson
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Mary McKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
| | - Bjørn Olav Åsvold
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
- Department of Endocrinology, Clinic of Medicine, St. Olavs Hospital, Trondheim University Hospital, Trondheim, Norway
| | - Rodrigo J Valderrabano
- Research Program in Men's Health, Aging and Metabolism, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, US
| | - Jie Zheng
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, Shanghai Digital Medicine Innovation Center, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- MRC Integrative Epidemiology Unit (IEU), Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - J Brent Richards
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
- Quantitative Life Sciences Program, McGill University, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
- Department of Epidemiology, Biostatistics, and Occupational Health, McGill University, Montreal, Quebec, Canada
- Department of Medicine, McGill University, Montreal, Quebec, Canada
- Department of Twin Research, King's College London, London, UK
| | - Eivind Coward
- HUNT Center for Molecular and Clinical Epidemiology, Department of Public Health and Nursing, Norwegian University of Science and Technology, Trondheim, Norway
| | - Claes Ohlsson
- Department of Internal Medicine and Clinical Nutrition, Institute of Medicine, Sahlgrenska Osteoporosis Centre, Centre for Bone and Arthritis Research at the Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
- Region Västra Götaland, Sahlgrenska University Hospital, Department of Drug Treatment, Gothenburg, Sweden.
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Butler AE, Lubbad W, Akbar S, Kilpatrick ES, Sathyapalan T, Atkin SL. A Cross-Sectional Study of Glomerular Hyperfiltration in Polycystic Ovary Syndrome. Int J Mol Sci 2024; 25:4899. [PMID: 38732117 PMCID: PMC11084759 DOI: 10.3390/ijms25094899] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 04/27/2024] [Accepted: 04/28/2024] [Indexed: 05/13/2024] Open
Abstract
Glomerular hyperfiltration (GH) has been reported to be higher in women with polycystic ovary syndrome (PCOS) and is an independent risk factor for renal function deterioration, metabolic, and cardiovascular disease. The aim of this study was to determine GH in type A PCOS subjects and to identify whether inflammatory markers, markers of CKD, renal tubule injury markers, and complement system proteins were associated. In addition, a secondary cohort study was performed to determine if the eGFR had altered over time. In this comparative cross-sectional analysis, demographic, metabolic, and proteomic data from Caucasian women aged 18-40 years from a PCOS Biobank (137 with PCOS, 97 controls) was analyzed. Slow Off-rate Modified Aptamer (SOMA)-scan plasma protein measurement was undertaken for inflammatory proteins, serum markers of chronic kidney disease (CKD), tubular renal injury markers, and complement system proteins. A total of 44.5% of the PCOS cohort had GH (eGFR ≥ 126 mL/min/1.73 m2 (n = 55)), and 12% (n = 17) eGFR ≥ 142 mL/min/1.73 m2 (super-GH(SGH)). PCOS-GH women were younger and had lower creatinine and urea versus PCOS-nonGH. C-reactive protein (CRP), white cell count (WCC), and systolic blood pressure (SBP) were higher in PCOS versus controls, but CRP correlated only with PCOS-SGH alone. Complement protein changes were seen between controls and PCOS-nonGH, and decay-accelerator factor (DAF) was decreased between PCOS-nonGH and PCOS-GSGH (p < 0.05). CRP correlated with eGFR in the PCOS-SGH group, but not with other inflammatory or complement parameters. Cystatin-c (a marker of CKD) was reduced between PCOS-nonGH and PCOS-GSGH (p < 0.05). No differences in tubular renal injury markers were found. A secondary cohort notes review of the biobank subjects 8.2-9.6 years later showed a reduction in eGFR: controls -6.4 ± 12.6 mL/min/1.73 m2 (-5.3 ± 11.5%; decrease 0.65%/year); PCOS-nonGH -11.3 ± 13.7 mL/min/1.73 m2 (-9.7 ± 12.2%; p < 0.05, decrease 1%/year); PCOS-GH (eGFR 126-140 mL/min/17.3 m2) -27.1 ± 12.8 mL/min/1.73 m2 (-19.1 ± 8.7%; p < 0.0001, decrease 2%/year); PCOS-SGH (eGFR ≥ 142 mL/min/17.3 m2) -33.7 ± 8.9 mL/min/17.3 m2 (-22.8 ± 6.0%; p < 0.0001, decrease 3.5%/year); PCOS-nonGH eGFR versus PCOS-GH and PCOS-SGH, p < 0.001; no difference PCOS-GH versus PCOS-SGH. GH was associated with PCOS and did not appear mediated through tubular renal injury; however, cystatin-c and DAF were decreased, and CRP correlated positively with PCOS-SGH, suggesting inflammation may be involved at higher GH. There were progressive eGFR decrements for PCOS-nonGH, PCOS-GH, and PCOS-SGH in the follow-up period which, in the presence of additional factors affecting renal function, may be clinically important in the development of CKD in PCOS.
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Affiliation(s)
- Alexandra E. Butler
- Research Department, Royal College of Surgeons in Ireland Bahrain, Busaiteen, Adliya P.O. Box 15503, Bahrain; (W.L.); (S.L.A.)
| | - Walaa Lubbad
- Research Department, Royal College of Surgeons in Ireland Bahrain, Busaiteen, Adliya P.O. Box 15503, Bahrain; (W.L.); (S.L.A.)
| | - Shahzad Akbar
- Allam Diabetes Centre, Hull University Teaching Hospitals NHS Trust, Hull HU3 2JZ, UK;
| | | | - Thozhukat Sathyapalan
- Academic Endocrinology, Diabetes and Metabolism, Hull York Medical School, Hull HU6 7RU, UK;
| | - Stephen L. Atkin
- Research Department, Royal College of Surgeons in Ireland Bahrain, Busaiteen, Adliya P.O. Box 15503, Bahrain; (W.L.); (S.L.A.)
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Myhre PL, Omland T, Shah AM. Ongoing Enigma of NT-proBNP in HFpEF: Insights From Proteomics. Circ Heart Fail 2024; 17:e011428. [PMID: 38299326 PMCID: PMC10963043 DOI: 10.1161/circheartfailure.123.011428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/02/2024]
Affiliation(s)
- Peder L. Myhre
- Department of Cardiology, Division of Medicine, Akershus University Hospital, Lørenskog, Norway
- K.G. Jebsen Center for Cardiac Biomarkers, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Torbjørn Omland
- Department of Cardiology, Division of Medicine, Akershus University Hospital, Lørenskog, Norway
- K.G. Jebsen Center for Cardiac Biomarkers, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Amil M. Shah
- Department of Internal Medicine, UT Southwestern Medical Center, Dallas, Texas, USA
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Chen TK, Estrella MM, Appel LJ, Surapaneni AL, Köttgen A, Obeid W, Parikh CR, Grams ME. Associations of Baseline and Longitudinal Serum Uromodulin With Kidney Failure and Mortality: Results From the African American Study of Kidney Disease and Hypertension (AASK) Trial. Am J Kidney Dis 2024; 83:71-78. [PMID: 37690632 DOI: 10.1053/j.ajkd.2023.05.017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 05/07/2023] [Accepted: 05/26/2023] [Indexed: 09/12/2023]
Abstract
RATIONALE & OBJECTIVE Uromodulin (UMOD) is the most abundant protein found in urine and has emerged as a promising biomarker of tubule health. Circulating UMOD is also detectable, but at lower levels. We evaluated whether serum UMOD levels were associated with the risks of incident kidney failure with replacement therapy (KFRT) and mortality. STUDY DESIGN Prospective cohort. SETTING & PARTICIPANTS Participants in AASK (the African American Study of Kidney Disease and Hypertension) with available stored serum samples from the 0-, 12-, and 24-month visits for biomarker measurement. PREDICTORS Baseline log-transformed UMOD and change in UMOD over 2 years. OUTCOMES KFRT and mortality. ANALYTICAL APPROACH Cox proportional hazards and mixed-effects models. RESULTS Among 500 participants with baseline serum UMOD levels (mean age, 54y; 37% female), 161 KFRT events occurred during a median of 8.5 years. After adjusting for baseline demographic factors, clinical factors, glomerular filtration rate, log-transformed urine protein-creatinine ratio, and randomized treatment groups, a 50% lower baseline UMOD level was independently associated with a 35% higher risk of KFRT (adjusted HR, 1.35; 95% CI, 1.07-1.70). For annual UMOD change, each 1-standard deviation lower change was associated with a 67% higher risk of KFRT (adjusted HR, 1.67; 95% CI, 1.41-1.99). Baseline UMOD and UMOD change were not associated with mortality. UMOD levels declined more steeply for metoprolol versus ramipril (P<0.001) as well as for intensive versus standard blood pressure goals (P = 0.002). LIMITATIONS Small sample size and limited generalizability. CONCLUSIONS Lower UMOD levels at baseline and steeper declines in UMOD over time were associated with a higher risk of subsequent KFRT in a cohort of African American adults with chronic kidney disease and hypertension. PLAIN-LANGUAGE SUMMARY Prior studies of uromodulin (UMOD), the most abundant protein in urine, and kidney disease have focused primarily on urinary UMOD levels. The present study evaluated associations of serum UMOD levels with the risks of kidney failure with replacement therapy (KFRT) and mortality in a cohort of African American adults with hypertension and chronic kidney disease. It found that participants with lower levels of UMOD at baseline were more likely to experience KFRT even after accounting for baseline kidney measures. Similarly, participants who experienced steeper annual declines in UMOD also had a heightened risk of kidney failure. Neither baseline nor annual change in UMOD was associated with mortality. Serum UMOD is a promising biomarker of kidney health.
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Affiliation(s)
- Teresa K Chen
- Kidney Health Research Collaborative and Division of Nephrology, Department of Medicine, University of California, San Francisco, San Francisco, California; San Francisco VA Health Care System, San Francisco, California; Division of Nephrology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland.
| | - Michelle M Estrella
- Kidney Health Research Collaborative and Division of Nephrology, Department of Medicine, University of California, San Francisco, San Francisco, California; San Francisco VA Health Care System, San Francisco, California
| | - Lawrence J Appel
- General Internal Medicine, 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
| | - Aditya L Surapaneni
- Department of Medicine, New York University Langone School of Medicine, New York, New York
| | - Anna Köttgen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Institute of Genetic Epidemiology, Faculty of Medicine and Medical Center, University of Freiburg, Freiburg, Germany
| | - Wassim Obeid
- Division of Nephrology, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Chirag R Parikh
- Division of Nephrology, 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
| | - Morgan E Grams
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland; Department of Medicine, New York University Langone School of Medicine, New York, New York
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Maddali P, Ambesi A, McKeown-Longo PJ. Induction of pro-inflammatory genes by fibronectin DAMPs in three fibroblast cell lines: Role of TAK1 and MAP kinases. PLoS One 2023; 18:e0286390. [PMID: 37228128 DOI: 10.1371/journal.pone.0286390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 05/13/2023] [Indexed: 05/27/2023] Open
Abstract
Changes in the organization and structure of the fibronectin matrix are believed to contribute to dysregulated wound healing and subsequent tissue inflammation and tissue fibrosis. These changes include an increase in the EDA isoform of fibronectin as well as the mechanical unfolding of fibronectin type III domains. In previous studies using embryonic foreskin fibroblasts, we have shown that fibronectin's EDA domain (FnEDA) and the partially unfolded first Type III domain (FnIII-1c) function as Damage Associated Molecular Pattern (DAMP) molecules to stimulate the induction of inflammatory cytokines by serving as agonists for Toll-Like Receptor-4 (TLR4). However, the role of signaling molecules downstream of TLR-4 such as TGF-β Activated Kinase 1 (TAK1) and Mitogen activated protein kinases (MAPK) in regulating the expression of fibronectin DAMP induced inflammatory genes in specific cell types is not known. In the current study, we evaluate the molecular steps regulating the fibronectin driven induction of inflammatory genes in three human fibroblast cell lines: embryonic foreskin, adult dermal, and adult kidney. The fibronectin derived DAMPs each induce the phosphorylation and activation of TAK1 which results in the activation of two downstream signaling arms, IKK/NF-κB and MAPK. Using the specific inhibitor 5Z-(7)-Oxozeanol as well as siRNA, we show TAK1 to be a crucial signaling mediator in the release of cytokines in response to fibronectin DAMPs in all three cell types. Finally, we show that FnEDA and FnIII-1c induce several pro-inflammatory cytokines whose expression is dependent on both TAK1 and JNK MAPK and highlight cell-type specific differences in the gene-expression profiles of the fibroblast cell-lines.
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Affiliation(s)
- Pranav Maddali
- Department of Regenerative & Cancer Cell Biology, Albany Medical College, Albany, New York, United States of America
| | - Anthony Ambesi
- Department of Regenerative & Cancer Cell Biology, Albany Medical College, Albany, New York, United States of America
| | - Paula J McKeown-Longo
- Department of Regenerative & Cancer Cell Biology, Albany Medical College, Albany, New York, United States of America
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Dubin RF, Deo R, Ren Y, Lee H, Shou H, Feldman H, Kimmel P, Waikar SS, Rhee EP, Tin A, Chen J, Coresh J, Go AS, Kelly T, Rao PS, Chen TK, Segal MR, Ganz P. Analytical and Biological Variability of a Commercial Modified Aptamer Assay in Plasma Samples of Patients with Chronic Kidney Disease. J Appl Lab Med 2023; 8:491-503. [PMID: 36705086 DOI: 10.1093/jalm/jfac145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 11/28/2022] [Indexed: 01/28/2023]
Abstract
BACKGROUND We carried out a study of the aptamer proteomic assay, SomaScan V4, to evaluate the analytical and biological variability of the assay in plasma samples of patients with moderate to severe chronic kidney disease (CKD). METHODS Plasma samples were selected from 2 sources: (a) 24 participants from the Chronic Renal Insufficiency Cohort (CRIC) and (b) 49 patients from the Brigham and Women's Hospital-Kidney/Renal Clinic. We calculated intra-assay variability from both sources and examined short-term biological variability in samples from the Brigham clinic. We also measured correlations of aptamer measurements with traditional biomarker assays. RESULTS A total of 4656 unique proteins (4849 total aptamer measures) were analyzed in all samples. Median (interquartile range [IQR] intra-assay CV) was 3.7% (2.8-5.3) in CRIC and 5.0% (3.8-7.0) in Brigham samples. Median (IQR) biological CV among Brigham samples drawn from one individual on 2 occasions separated by median (IQR) 7 (4-14) days was 8.7% (6.2-14). CVs were independent of CKD stage, diabetes, or albuminuria but were higher in patients with systemic lupus erythematosus. Rho correlations between aptamer and traditional assays for biomarkers of interest were cystatin C = 0.942, kidney injury model-1 = 0.905, fibroblast growth factor-23 = 0.541, tumor necrosis factor receptors 1 = 0.781 and 2 = 0.843, P < 10-100 for all. CONCLUSIONS Intra-assay and within-subject variability for SomaScan in the CKD setting was low and similar to assay variability reported from individuals without CKD. Intra-assay precision was excellent whether samples were collected in an optimal research protocol, as were CRIC samples, or in the clinical setting, as were the Brigham samples.
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Affiliation(s)
- Ruth F Dubin
- Division of Nephrology, University of Texas Southwestern Medical Center, San Francisco, CA, USA
| | - Rajat Deo
- Division of Cardiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Yue Ren
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Hongzhe Lee
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Haochang Shou
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Harold Feldman
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine at the University of Pennsylvania, Philadelphia, PA, USA
| | - Paul Kimmel
- Division of Kidney, Urologic, and Hematologic Diseases, National Institute of Diabetes and Digestive and Kidney Diseases, Washington, DC, USA
| | - Sushrut S Waikar
- Division of Nephrology, Boston University School of Medicine, Boston, MA, USA
| | - Eugene P Rhee
- Division of Nephrology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Adrienne Tin
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Jingsha Chen
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Joseph Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA
| | - Alan S Go
- Division of Research, Kaiser Permanente Northern California Division of Research, Oakland, CA, USA
| | - Tanika Kelly
- Department of Epidemiology, Tulane University, New Orleans, LA, USA
| | - Paduranga S Rao
- Department of Medicine, University of Michigan Ann Arbor, Ann Arbor, MI, USA
| | - Teresa K Chen
- Division of Nephrology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Mark R Segal
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Peter Ganz
- Division of Cardiology, University of California, San Francisco, San Francisco, CA, USA
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Park JH, Eom YS, Kim TH. Recent Advances in Aptamer-Based Sensors for Sensitive Detection of Neurotransmitters. BIOSENSORS 2023; 13:bios13040413. [PMID: 37185488 PMCID: PMC10136356 DOI: 10.3390/bios13040413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Revised: 03/20/2023] [Accepted: 03/21/2023] [Indexed: 05/17/2023]
Abstract
In recent years, there has been an increased demand for highly sensitive and selective biosensors for neurotransmitters, owing to advancements in science and technology. Real-time sensing is crucial for effective prevention of neurological and cardiovascular diseases. In this review, we summarise the latest progress in aptamer-based biosensor technology, which offers the aforementioned advantages. Our focus is on various biomaterials utilised to ensure the optimal performance and high selectivity of aptamer-based biosensors. Overall, this review aims to further aptamer-based biosensor technology.
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Affiliation(s)
- Joon-Ha Park
- School of Integrative Engineering, Chung-Ang University, Seoul 06974, Republic of Korea
| | - Yun-Sik Eom
- School of Integrative Engineering, Chung-Ang University, Seoul 06974, Republic of Korea
| | - Tae-Hyung Kim
- School of Integrative Engineering, Chung-Ang University, Seoul 06974, Republic of Korea
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Rooney MR, Chen J, Ballantyne CM, Hoogeveen RC, Tang O, Grams ME, Tin A, Ndumele CE, Zannad F, Couper DJ, Tang W, Selvin E, Coresh J. Comparison of Proteomic Measurements Across Platforms in the Atherosclerosis Risk in Communities (ARIC) Study. Clin Chem 2023; 69:68-79. [PMID: 36508319 PMCID: PMC9812856 DOI: 10.1093/clinchem/hvac186] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2022] [Accepted: 09/12/2022] [Indexed: 12/14/2022]
Abstract
BACKGROUND The plasma proteome can be quantified using different types of highly multiplexed technologies, including aptamer-based and proximity-extension immunoassay methods. There has been limited characterization of how these protein measurements correlate across platforms and with absolute measures from targeted immunoassays. METHODS We assessed the comparability of (a) highly multiplexed aptamer-based (SomaScan v4; Somalogic) and proximity-extension immunoassay (OLINK Proseek® v5003; Olink) methods in 427 Atherosclerosis Risk in Communities (ARIC) Study participants (Visit 5, 2011-2013), and (b) 18 of the SomaScan protein measurements against targeted immunoassays in 110 participants (55 cardiovascular disease cases, 55 controls). We calculated Spearman correlations (r) between the different measurements and compared associations with case-control status. RESULTS There were 417 protein comparisons (366 unique proteins) between the SomaScan and Olink platforms. The average correlation was r = 0.46 (range: -0.21 to 0.97; 79 [19%] with r ≥ 0.8). For the comparison of SomaScan and targeted immunoassays, 6 of 18 assays (growth differentiation factor 15 [GDF15], interleukin-1 receptor-like 1 [ST2], interstitial collagenase [MMP1], adiponectin, leptin, and resistin) had good correlations (r ≥ 0.8), 2 had modest correlations (0.5 ≤ r < 0.8; osteopontin and interleukin-6 [IL6]), and 10 were poorly correlated (r < 0.5; metalloproteinase inhibitor 1 [TIMP1], stromelysin-1 [MMP3], matrilysin [MMP7], C-C motif chemokine 2 [MCP1], interleukin-10 [IL10], vascular cell adhesion protein 1 [VCAM1], intercellular adhesion molecule 1 [ICAM1], interleukin-18 [IL18], tumor necrosis factor [TNFα], and visfatin) overall. Correlations for SomaScan and targeted immunoassays were similar according to case status. CONCLUSIONS There is variation in the quantitative measurements for many proteins across aptamer-based and proximity-extension immunoassays (approximately 1/2 showing good or modest correlation and approximately 1/2 poor correlation) and also for correlations of these highly multiplexed technologies with targeted immunoassays. Design and interpretation of protein quantification studies should be informed by the variation across measurement techniques for each protein.
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Affiliation(s)
- Mary R. Rooney
- Department of Epidemiology and Welch Center for Prevention, Epidemiology, & Clinical Research; Johns Hopkins Bloomberg School of Public Health; Baltimore, Maryland, USA
| | - Jingsha Chen
- Department of Epidemiology and Welch Center for Prevention, Epidemiology, & Clinical Research; Johns Hopkins Bloomberg School of Public Health; Baltimore, Maryland, USA
| | | | - Ron C. Hoogeveen
- Department of Medicine, Baylor College of Medicine, Houston, Texas, USA
| | - Olive Tang
- Department of Epidemiology and Welch Center for Prevention, Epidemiology, & Clinical Research; Johns Hopkins Bloomberg School of Public Health; Baltimore, Maryland, USA
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Morgan E. Grams
- Department of Epidemiology and Welch Center for Prevention, Epidemiology, & Clinical Research; Johns Hopkins Bloomberg School of Public Health; Baltimore, Maryland, USA
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Adrienne Tin
- Memory Impairment and Neurodegenerative Dementia (MIND) Center and Department of Medicine, University of Mississippi Medical Center; Jackson, Mississippi, USA
| | - Chiadi E. Ndumele
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Faiez Zannad
- Université de Lorraine, Centre d’Investigation Clinique-Plurithématique Inserm CIC-P 1433, Inserm U1116, CHRU Nancy Brabois, F-CRIN INI-CRCT (Cardiovascular and Renal Clinical Trialists), Nancy, France
| | - David J. Couper
- Department of Biostatistics, Gillings School of Global Public Health; University of North Carolina, USA
| | - Weihong Tang
- Division of Epidemiology & Community Health; University of Minnesota; Minneapolis, Minnesota, USA
| | - Elizabeth Selvin
- Department of Epidemiology and Welch Center for Prevention, Epidemiology, & Clinical Research; Johns Hopkins Bloomberg School of Public Health; Baltimore, Maryland, USA
| | - Josef Coresh
- Department of Epidemiology and Welch Center for Prevention, Epidemiology, & Clinical Research; Johns Hopkins Bloomberg School of Public Health; Baltimore, Maryland, USA
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9
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Zaghlool SB, Halama A, Stephan N, Gudmundsdottir V, Gudnason V, Jennings LL, Thangam M, Ahlqvist E, Malik RA, Albagha OME, Abou-Samra AB, Suhre K. Metabolic and proteomic signatures of type 2 diabetes subtypes in an Arab population. Nat Commun 2022; 13:7121. [PMID: 36402758 PMCID: PMC9675829 DOI: 10.1038/s41467-022-34754-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 11/07/2022] [Indexed: 11/20/2022] Open
Abstract
Type 2 diabetes (T2D) has a heterogeneous etiology influencing its progression, treatment, and complications. A data driven cluster analysis in European individuals with T2D previously identified four subtypes: severe insulin deficient (SIDD), severe insulin resistant (SIRD), mild obesity-related (MOD), and mild age-related (MARD) diabetes. Here, the clustering approach was applied to individuals with T2D from the Qatar Biobank and validated in an independent set. Cluster-specific signatures of circulating metabolites and proteins were established, revealing subtype-specific molecular mechanisms, including activation of the complement system with features of autoimmune diabetes and reduced 1,5-anhydroglucitol in SIDD, impaired insulin signaling in SIRD, and elevated leptin and fatty acid binding protein levels in MOD. The MARD cluster was the healthiest with metabolomic and proteomic profiles most similar to the controls. We have translated the T2D subtypes to an Arab population and identified distinct molecular signatures to further our understanding of the etiology of these subtypes.
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Affiliation(s)
- Shaza B Zaghlool
- Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Anna Halama
- Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Nisha Stephan
- Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Doha, Qatar
| | - Valborg Gudmundsdottir
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Icelandic Heart Association, Kopavogur, Iceland
| | - Vilmundur Gudnason
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
- Icelandic Heart Association, Kopavogur, Iceland
| | - Lori L Jennings
- Novartis Institutes for Biomedical Research, Cambridge, MA, USA
| | | | - Emma Ahlqvist
- Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | | | - Omar M E Albagha
- College of Health and Life Sciences, Hamad Bin Khalifa University, Education City, Doha, Qatar
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | | | - Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medicine-Qatar, Doha, Qatar.
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10
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Nishi H. Aptamer-Based Proteomic Platform for Human Immune-Mediated Kidney Diseases. Kidney Int Rep 2022; 7:1450-1452. [PMID: 35812268 PMCID: PMC9263405 DOI: 10.1016/j.ekir.2022.05.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Affiliation(s)
- Hiroshi Nishi
- Division of Nephrology and Endocrinology, University of Tokyo Graduate School of Medicine, Tokyo, Japan
- Correspondence: Hiroshi Nishi, Division of Nephrology and Endocrinology, University of Tokyo Graduate School of Medicine, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655, Japan.
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