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Insulin sensitivity index (ISI0, 120) potentially linked to carbon isotopes of breath CO2 for pre-diabetes and type 2 diabetes.

Ghosh C, Mukhopadhyay P, Ghosh S, Pradhan M - Sci Rep (2015)

Bottom Line: Conversely, the strongest correlation was observed between 1/ISI0,120 and breath CO2 isotopes.Consequently, we determined several optimal diagnostic cut-off points of 1/ISI0,120 and (13)CO2/(12)CO2-isotope ratios to distinctively track the evolution of PD prior to the onset of T2D.Our findings suggest that isotopic breath CO2 is a novel method for accurate estimation of ISI0,120 and thus may open new perspectives into the isotope-specific non-invasive evaluation of insulin resistance for large-scale real-time diabetes screening purposes.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical, Biological and Macromolecular Sciences, S. N. Bose National Centre for Basic Sciences, Salt Lake, JD Block, Sector III, Kolkata-700098, India.

ABSTRACT
New strategies for an accurate and early detection of insulin resistance are important to delay or prevent the acute onset of type 2 diabetes (T2D). Currently, insulin sensitivity index (ISI0,120) is considered to be a viable invasive method of whole-body insulin resistance for use in clinical settings in comparison with other invasive sensitivity indexes like homeostasis model assessment (HOMA), and quantitative insulin sensitivity check index (QUICKI). To investigate how these sensitivity indexes link the (13)C/(12)C-carbon isotopes of exhaled breath CO2 to pre-diabetes (PD) and type 2 diabetes in response to glucose ingestion, we studied excretion dynamics of (13)C/(12)C-isotopic fractionations of breath CO2. Here, we show that (13)C/(12)C-isotope ratios of breath CO2 were well correlated with blood glucose, insulin, glycosylated-hemoglobin as well as with HOMA-IR and 1/QUICKI. Conversely, the strongest correlation was observed between 1/ISI0,120 and breath CO2 isotopes. Consequently, we determined several optimal diagnostic cut-off points of 1/ISI0,120 and (13)CO2/(12)CO2-isotope ratios to distinctively track the evolution of PD prior to the onset of T2D. Our findings suggest that isotopic breath CO2 is a novel method for accurate estimation of ISI0,120 and thus may open new perspectives into the isotope-specific non-invasive evaluation of insulin resistance for large-scale real-time diabetes screening purposes.

No MeSH data available.


Related in: MedlinePlus

Linear regression plots to show the correlations of δDOB13C (‰) in breath with different invasive parameters.a, breath δDOB13C(‰) with glycosylated haemoglobin (HbA1c %). b, plasma insulin levels (∆ Insulin Level) from the baseline during 2 h-OGTT. c, shows correlation of blood glucose concentrations (∆ Blood Glucose). The data are statistically significant different (p < 0.001).
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f2: Linear regression plots to show the correlations of δDOB13C (‰) in breath with different invasive parameters.a, breath δDOB13C(‰) with glycosylated haemoglobin (HbA1c %). b, plasma insulin levels (∆ Insulin Level) from the baseline during 2 h-OGTT. c, shows correlation of blood glucose concentrations (∆ Blood Glucose). The data are statistically significant different (p < 0.001).

Mentions: We next explored whether there were any correlations of δDOB13C‰ values in exhaled breath at 120 min with the variables related to the insulin resistance, such as absolute changes in blood glucose levels, and plasma insulin levels at the particular time during the OGTT, in addition to glycated haemoglobin (HbA1c) measurements. Figure 2 depicts the inverse correlations of δDOB13C‰ values with all these measured parameters. The correlation of δDOB13C (t = 120 min)‰ with HbA1c (%) was strong with a correlation coefficient of r = −0.71 (p < 0.001) compared with the blood glucose (r = −0.64, p < 0.001) and plasma insulin levels (r = −0.5, p < 0.001).


Insulin sensitivity index (ISI0, 120) potentially linked to carbon isotopes of breath CO2 for pre-diabetes and type 2 diabetes.

Ghosh C, Mukhopadhyay P, Ghosh S, Pradhan M - Sci Rep (2015)

Linear regression plots to show the correlations of δDOB13C (‰) in breath with different invasive parameters.a, breath δDOB13C(‰) with glycosylated haemoglobin (HbA1c %). b, plasma insulin levels (∆ Insulin Level) from the baseline during 2 h-OGTT. c, shows correlation of blood glucose concentrations (∆ Blood Glucose). The data are statistically significant different (p < 0.001).
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4493706&req=5

f2: Linear regression plots to show the correlations of δDOB13C (‰) in breath with different invasive parameters.a, breath δDOB13C(‰) with glycosylated haemoglobin (HbA1c %). b, plasma insulin levels (∆ Insulin Level) from the baseline during 2 h-OGTT. c, shows correlation of blood glucose concentrations (∆ Blood Glucose). The data are statistically significant different (p < 0.001).
Mentions: We next explored whether there were any correlations of δDOB13C‰ values in exhaled breath at 120 min with the variables related to the insulin resistance, such as absolute changes in blood glucose levels, and plasma insulin levels at the particular time during the OGTT, in addition to glycated haemoglobin (HbA1c) measurements. Figure 2 depicts the inverse correlations of δDOB13C‰ values with all these measured parameters. The correlation of δDOB13C (t = 120 min)‰ with HbA1c (%) was strong with a correlation coefficient of r = −0.71 (p < 0.001) compared with the blood glucose (r = −0.64, p < 0.001) and plasma insulin levels (r = −0.5, p < 0.001).

Bottom Line: Conversely, the strongest correlation was observed between 1/ISI0,120 and breath CO2 isotopes.Consequently, we determined several optimal diagnostic cut-off points of 1/ISI0,120 and (13)CO2/(12)CO2-isotope ratios to distinctively track the evolution of PD prior to the onset of T2D.Our findings suggest that isotopic breath CO2 is a novel method for accurate estimation of ISI0,120 and thus may open new perspectives into the isotope-specific non-invasive evaluation of insulin resistance for large-scale real-time diabetes screening purposes.

View Article: PubMed Central - PubMed

Affiliation: Department of Chemical, Biological and Macromolecular Sciences, S. N. Bose National Centre for Basic Sciences, Salt Lake, JD Block, Sector III, Kolkata-700098, India.

ABSTRACT
New strategies for an accurate and early detection of insulin resistance are important to delay or prevent the acute onset of type 2 diabetes (T2D). Currently, insulin sensitivity index (ISI0,120) is considered to be a viable invasive method of whole-body insulin resistance for use in clinical settings in comparison with other invasive sensitivity indexes like homeostasis model assessment (HOMA), and quantitative insulin sensitivity check index (QUICKI). To investigate how these sensitivity indexes link the (13)C/(12)C-carbon isotopes of exhaled breath CO2 to pre-diabetes (PD) and type 2 diabetes in response to glucose ingestion, we studied excretion dynamics of (13)C/(12)C-isotopic fractionations of breath CO2. Here, we show that (13)C/(12)C-isotope ratios of breath CO2 were well correlated with blood glucose, insulin, glycosylated-hemoglobin as well as with HOMA-IR and 1/QUICKI. Conversely, the strongest correlation was observed between 1/ISI0,120 and breath CO2 isotopes. Consequently, we determined several optimal diagnostic cut-off points of 1/ISI0,120 and (13)CO2/(12)CO2-isotope ratios to distinctively track the evolution of PD prior to the onset of T2D. Our findings suggest that isotopic breath CO2 is a novel method for accurate estimation of ISI0,120 and thus may open new perspectives into the isotope-specific non-invasive evaluation of insulin resistance for large-scale real-time diabetes screening purposes.

No MeSH data available.


Related in: MedlinePlus