Early detection of metabolic dysregulation using water T2 analysis of biobanked samples

Ina Mishra,1,2 Clinton Jones,1,3 Vipulkumar Patel,1,2 Sneha Deodhar,1 David P Cistola1,2 1Nanoparticle Diagnostics Laboratory, Institute for Cardiovascular and Metabolic Diseases, Department of Physiology & Anatomy, University of North Texas Health Science Center, Fort Worth, TX, 76107, USA;...

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Autores principales:	Mishra I, Jones C, Patel V, Deodhar S, Cistola DP
Formato:	article
Lenguaje:	EN
Publicado:	Dove Medical Press 2018
Materias:	metabolic syndrome insulin resistance hyperinsulinemia dyslipidemia inflammation nuclear magnetic resonance relaxometry Specialties of internal medicine RC581-951
Acceso en línea:	https://doaj.org/article/b10f546211ea4bbdb638392b1a1e57ef
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spelling	oai:doaj.org-article:b10f546211ea4bbdb638392b1a1e57ef2021-12-02T01:41:20ZEarly detection of metabolic dysregulation using water T2 analysis of biobanked samples1178-7007https://doaj.org/article/b10f546211ea4bbdb638392b1a1e57ef2018-11-01T00:00:00Zhttps://www.dovepress.com/early-detection-of-metabolic-dysregulation-using-water-t2-analysis-of--peer-reviewed-article-DMSOhttps://doaj.org/toc/1178-7007Ina Mishra,1,2 Clinton Jones,1,3 Vipulkumar Patel,1,2 Sneha Deodhar,1 David P Cistola1,2 1Nanoparticle Diagnostics Laboratory, Institute for Cardiovascular and Metabolic Diseases, Department of Physiology & Anatomy, University of North Texas Health Science Center, Fort Worth, TX, 76107, USA; 2Center of Emphasis in Diabetes & Metabolism, Department of Biomedical Sciences, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center El Paso, El Paso, TX, 79905, USA; 3Texas College of Osteopathic Medicine, University of North Texas Health Science Center, Fort Worth, TX, 76107, USA Background: The ability to use frozen biobanked samples from cohort studies and clinical trials is critically important for biomarker discovery and validation. Here we investigated whether plasma and serum water transverse relaxation times (T2) from frozen biobanked samples could be used as biomarkers for metabolic syndrome (MetS) and its underlying conditions, specifically insulin resistance, dyslipidemia, and subclinical inflammation. Methods: Plasma and serum aliquots from 44 asymptomatic, non-diabetic human subjects were biobanked at –80°C for 7–9 months. Water T2 measurements were recorded at 37°C on 50 µL of unmodified plasma or serum using benchtop nuclear magnetic resonance relaxometry. The T2 values for freshly drawn and once-frozen-thawed (“frozen”) samples were compared using Huber M-values (M), Lin concordance correlation coefficients (ρc), and Bland–Altman plots. Water T2 values from frozen plasma and serum samples were compared with >130 metabolic biomarkers and analyzed using multi-variable linear/logistic regression and ROC curves. Results: Frozen plasma water T2 values were highly correlated with fresh (M=0.94, 95% CI 0.89, 0.97) but showed a lower level of agreement (ρc=0.74, 95% CI 0.62, 0.82) because of an average offset of –5.6% (−7.1% for serum). Despite the offset, frozen plasma water T2 was strongly correlated with markers of hyperinsulinemia, dyslipidemia, and inflammation and detected these conditions with 89% sensitivity and 91% specificity (100%/63% for serum). Using optimized cut points, frozen plasma and serum water T2 detected hyperinsulinemia, dyslipidemia, and inflammation in 23 of 44 subjects, including nine with an early stage of metabolic dysregulation that did not meet the clinical thresholds for prediabetes or MetS. Conclusion: Plasma and serum water T2 values from once-frozen-thawed biobanked samples detect metabolic dysregulation with high sensitivity and specificity. However, the cut points for frozen biobanked samples must be calibrated independent of those for freshly drawn plasma and serum. Keywords: metabolic syndrome, insulin resistance, hyperinsulinemia, dyslipidemia, inflammation, nuclear magnetic resonance relaxometry, metabolic health screening, diabetes preventionMishra IJones CPatel VDeodhar SCistola DPDove Medical Pressarticlemetabolic syndromeinsulin resistancehyperinsulinemiadyslipidemiainflammationnuclear magnetic resonance relaxometrySpecialties of internal medicineRC581-951ENDiabetes, Metabolic Syndrome and Obesity: Targets and Therapy, Vol Volume 11, Pp 807-818 (2018)
institution	DOAJ
collection	DOAJ
language	EN
topic	metabolic syndrome insulin resistance hyperinsulinemia dyslipidemia inflammation nuclear magnetic resonance relaxometry Specialties of internal medicine RC581-951
spellingShingle	metabolic syndrome insulin resistance hyperinsulinemia dyslipidemia inflammation nuclear magnetic resonance relaxometry Specialties of internal medicine RC581-951 Mishra I Jones C Patel V Deodhar S Cistola DP Early detection of metabolic dysregulation using water T2 analysis of biobanked samples
description	Ina Mishra,1,2 Clinton Jones,1,3 Vipulkumar Patel,1,2 Sneha Deodhar,1 David P Cistola1,2 1Nanoparticle Diagnostics Laboratory, Institute for Cardiovascular and Metabolic Diseases, Department of Physiology & Anatomy, University of North Texas Health Science Center, Fort Worth, TX, 76107, USA; 2Center of Emphasis in Diabetes & Metabolism, Department of Biomedical Sciences, Paul L. Foster School of Medicine, Texas Tech University Health Sciences Center El Paso, El Paso, TX, 79905, USA; 3Texas College of Osteopathic Medicine, University of North Texas Health Science Center, Fort Worth, TX, 76107, USA Background: The ability to use frozen biobanked samples from cohort studies and clinical trials is critically important for biomarker discovery and validation. Here we investigated whether plasma and serum water transverse relaxation times (T2) from frozen biobanked samples could be used as biomarkers for metabolic syndrome (MetS) and its underlying conditions, specifically insulin resistance, dyslipidemia, and subclinical inflammation. Methods: Plasma and serum aliquots from 44 asymptomatic, non-diabetic human subjects were biobanked at –80°C for 7–9 months. Water T2 measurements were recorded at 37°C on 50 µL of unmodified plasma or serum using benchtop nuclear magnetic resonance relaxometry. The T2 values for freshly drawn and once-frozen-thawed (“frozen”) samples were compared using Huber M-values (M), Lin concordance correlation coefficients (ρc), and Bland–Altman plots. Water T2 values from frozen plasma and serum samples were compared with >130 metabolic biomarkers and analyzed using multi-variable linear/logistic regression and ROC curves. Results: Frozen plasma water T2 values were highly correlated with fresh (M=0.94, 95% CI 0.89, 0.97) but showed a lower level of agreement (ρc=0.74, 95% CI 0.62, 0.82) because of an average offset of –5.6% (−7.1% for serum). Despite the offset, frozen plasma water T2 was strongly correlated with markers of hyperinsulinemia, dyslipidemia, and inflammation and detected these conditions with 89% sensitivity and 91% specificity (100%/63% for serum). Using optimized cut points, frozen plasma and serum water T2 detected hyperinsulinemia, dyslipidemia, and inflammation in 23 of 44 subjects, including nine with an early stage of metabolic dysregulation that did not meet the clinical thresholds for prediabetes or MetS. Conclusion: Plasma and serum water T2 values from once-frozen-thawed biobanked samples detect metabolic dysregulation with high sensitivity and specificity. However, the cut points for frozen biobanked samples must be calibrated independent of those for freshly drawn plasma and serum. Keywords: metabolic syndrome, insulin resistance, hyperinsulinemia, dyslipidemia, inflammation, nuclear magnetic resonance relaxometry, metabolic health screening, diabetes prevention
format	article
author	Mishra I Jones C Patel V Deodhar S Cistola DP
author_facet	Mishra I Jones C Patel V Deodhar S Cistola DP
author_sort	Mishra I
title	Early detection of metabolic dysregulation using water T2 analysis of biobanked samples
title_short	Early detection of metabolic dysregulation using water T2 analysis of biobanked samples
title_full	Early detection of metabolic dysregulation using water T2 analysis of biobanked samples
title_fullStr	Early detection of metabolic dysregulation using water T2 analysis of biobanked samples
title_full_unstemmed	Early detection of metabolic dysregulation using water T2 analysis of biobanked samples
title_sort	early detection of metabolic dysregulation using water t2 analysis of biobanked samples
publisher	Dove Medical Press
publishDate	2018
url	https://doaj.org/article/b10f546211ea4bbdb638392b1a1e57ef
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Early detection of metabolic dysregulation using water T2 analysis of biobanked samples

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