https://orcid.org/0000-0003-1142-395X
Figures
Abstract
Hypothesis
Glycaemic variability (GV) refers to fluctuations in the blood glucose level and may contribute to complications in patients suffering from Diabetes. Several studies show negative effects of GV on the cardiovascular system, however there is still a lack of conclusive evidence. Using an explorative cardiovascular panel, it is possible to simultaneously measure the effects on proteins relevant for cardiovascular processes. The aim of this study was to investigate the effects of rapid glucose excursions on cardiovascular and metabolic parameters in healthy individuals.
Methods
An explorative single-blinded cross-over study was performed in ten healthy men. Subjects received 3 times 20 grams of glucose i.v. over 5 minutes or 60 grams of glucose continuously over 3 hours. Blood was taken for repeated measurements of the cardiovascular panel over the following 6 hours and again after 24 and 48 hours.
Results
We observed a significant elevation of 7 cardiovascular biomarkers (BMP6, SLAMF7, LOX-1, ADAMTS13, IL-1RA, IL-4RA, PTX3) at t = 360min after rapid glucose infusion compared to a continuous glucose infusion.
Citation: Feldbauer R, Heinzl MW, Klammer C, Resl M, Pohlhammer J, Rosenberger K, et al. (2022) Effect of repeated bolus and continuous glucose infusion on a panel of circulating biomarkers in healthy volunteers. PLoS ONE 17(12): e0279308. https://doi.org/10.1371/journal.pone.0279308
Editor: Stephen L. Atkin, RCSI and MUB: Royal College of Surgeons in Ireland and Medical University of Bahrain, BAHRAIN
Received: August 29, 2022; Accepted: December 2, 2022; Published: December 27, 2022
Copyright: © 2022 Feldbauer et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the article and its Supporting Information files.
Funding: The author(s) received no specific funding for this work
Competing interests: The authors have declared that no competing interests exist.
Abbreviations: BMP6, Bone morphogenetic protein 6; SLAMF7, SLAM family member 7; LOX-1, Lectin-like oxidised LDL receptor 1; ADAMTS13, A Disintegrin and Metalloproteinase with a thrombospondin type I motif, member 13; IL-1RA, Interleukin-1 receptor antagonist protein; IL-4RA, Interleukin-4 receptor subunit alpha; PTX3, Pentraxin-related protein PTX3; GV, Glycaemic variability
Introduction
At the end of the 20th century, it became known that people with diabetes have a 2 to 3 times higher risk of dying of cardiovascular death than non-diabetics. This has been displayed in epidemiological studies as well as in the United Kingdom Prospective Diabetes Study (UKPDS) [1, 2].
Today there are approximately 400 million people living with diabetes and about 1.5 million deaths are related to this disease every year [3].
In addition to the indisputable proofs that chronic hyperglycaemia plays a part in the pathogenesis of cardiovascular diseases and glucose lowering therapy may have a benefit, glycaemic variability (GV) has recently been regarded as another risk factor for cardiovascular and microvascular complications [4–7].
Furthermore, it was shown that GV cannot be adequately represented by HbA1c, the gold standard for assessment of glucose control [8].
The term glycaemic or glucose variability refers to fluctuations in the blood sugar level. Its cause is assumed to be reduced or a lack of self-regulation, or incorrect drug self-control. Intermittent blood sugar excursions with pronounced fluctuations between high and low values instead of constant, even increased blood sugar exposure, have turned out to be more harmful, according to several studies [9–14].
GV may therefore be a factor in the development of diabetic complications. Although many studies have shown negative effects of GV on the cardiovascular system, there is still a lack of conclusive evidence [15–22].
To our knowledge, there have to date been no studies with acutely altered glucose concentrations in healthy volunteers investigating the effects on a wide range of cardiovascular and metabolic biomarkers. New analytical techniques using explorative panels allow the identification of a broader range of new biomarkers and relevant protein signatures that may reflect important biological processes.
The cardiovascular panel used in this study provides simultaneous analysis of 92 protein biomarkers. Selection of protein biomarker assays is designed to focus on proteins relevant for cardiovascular processes. The assays in this panel include biomarkers involved in different biological processes which play a role in cardiovascular disease, such as inflammation, cellular metabolic processes, cell adhesion, immune response and complement activation.
The aim of this study is to determine the effect of rapid glucose excursion as a surrogate for high glucose variability compared to continuously elevated glucose levels on cardiovascular and metabolic parameters in healthy volunteers.
Methods
Study participants and design
The study has been approved by the local joint research ethics committee of the St. John of God Hospital Linz. Informed consent was obtained in writing and orally from each subject before enrolment in the study. Ten healthy male volunteers were recruited via a notice at the local university (JKU Linz). After meeting the inclusion criteria (men aged 18 to 40 years, no disease history, no tobacco consumption, no diabetes history with fasting glucose and HbA1c within normal range) they were screened by medical history, physical examination, and electrocardiogram. Volunteers who suffered from any infectious disease or volunteers on any medication were excluded from the study (Fig 1). Baseline characteristics of the ten male volunteers can be found in Table 1.
The CONSORT Flow Diagram of the progress through the phases is depicted.
In a cross-over design each subject was monitored on two different study days, 7–21 days apart. In random order, all subjects received 3 times 20 grams of glucose intravenously over 5 minutes at intervals of one hour on one day, as opposed to 60 grams of glucose continuously over 3 hours on the other study day. In between these study days subjects consumed a weight-maintaining diet providing at least 200 grams of carbohydrate each day.
As our study was single-blinded the medical staff involved in this study was informed about the infusion protocol and timepoints of venous blood sample collection. Participants of this study were blinded and received no information about the infusion protocol on each study day.
Study days began at 08.00 a.m. after an overnight fast and restraining from smoking or caffeine-containing beverages for 24 hours before the respective study day. Subjects then rested quietly in a supine position for the remainder of the study. Catheters (Safety iv Catheter with injection port; Braun, Melsungen, Germany) were inserted into both arms (one for sampling, the other for infusion).
Subjects received 3 times 20 grams of glucose dissolved in 100 ml of Aqua intravenously over 5 minutes in intervals of one hour (at time point t0, t60, t120), or 60 grams of glucose solved in 300 ml of Aqua continuously over 3 hours (starting at timepoint t0).
Blood was taken repeatedly for measurements of the Cardiovascular II panel (OLINK) (starting before the beginning of infusions at time point t0) over the following 6 hours and again after 24 hours and 48 hours.
Subjects were monitored consistently by a study assistant during the two study days including non-invasive blood pressure, heart rate and temperature.
Laboratory measurements and statistical analysis
Venous blood samples were taken using VACUETTE polyethylene terephthalate glycol blood collection tubes (Greiner Bio-One). For measuring glucose levels the venous blood samples were analysed at the Department of Laboratory of the St. John of God Hospital Linz immediately, all other blood samples were centrifuged and stored.
EDTA-plasma samples (frozen at -80°C) were sent to OLINK Proteomics in Davos (Switzerland). By using the proximity extension assay (PEA), 92 biomarkers relevant for cardiovascular diseases were analysed. PEA works via matched pairs of antibodies carrying unique DNA tags that bind to the proteins in the probe. After binding to the protein DNA hybridization occurs. Using PCR amplification 96 biomarkers can be read out simultaneously [23, 24].
The concentrations of biomarkers are scaled in NPX (normalised protein expression) units. The NPX is Olink´s arbitrary unit on a log2-scale [25].
For statistical testing we used repeated-measures analysis of variance (RM-ANOVA). Whenever sphericity could not be assumed in RM-ANOVA (according to Mauchly´s test of sphericity) we used the Greenhouse-Geisser correction. When testing on singular timepoints we tested for normal distribution using Kolmogorov-Smirnov test. If data were normally distributed, we used paired t-test, otherwise we used Wilcoxon test.
For measuring glucose variability we used the coefficient of variation in our study. The coefficient of variation for each individual was calculated by dividing standard deviation through mean blood glucose which was then multiplied by 100 for receiving a percentage. We calculated the coefficient of variation for every test person on both study days.
Since this is an explorative study, no calculation of sample size was performed.
All calculations were performed using Statistical Package for the Social Sciences computer software (SPSS) in Version 26.
Results
Blood glucose (in mg/dl) was measured on both study days (continuous vs bolus) (Tables 2 and 3). For better representation of glucose variability, additional glucose measurements were taken on days of bolus application at time points t = 5min, t = 10min, t = 15min as well as t = 65min, t = 70min, t = 75min and t = 125min, t = 130min, t = 135min (Figs 2–4).
Mean levels of blood glucose and standard deviation are depicted.
Mean levels of blood glucose and standard deviation are depicted. Of note, additionally timepoints (t = 5min, t = 10min, t = 15min, t = 65min, t = 70min, t = 75min, t = 125min, t = 130min, t = 135min) are depicted.
Mean levels of blood glucose after continuous or bolus glucose infusion are depicted for each timepoint. Of note, additionally timepoints (t = 5min, t = 10min, t = 15min, t = 65min, t = 70min, t = 75min, t = 125min, t = 130min, t = 135min) for bolus infusion are depicted.
Glucose variability was measured by using the coefficient of variation. We calculated the coefficient of variation for every test person on both study days (Table 4).
For better representation of glucose variability in between both study days we calculated the mean coefficient of variation for days of continuous glucose infusion and of bolus glucose infusion (Fig 5). The mean CV on days of continuous glucose infusion was 18,59% with a SD of 7,43. Mean CV on days of bolus infusion was 39,98% with a SD of 6,93.
Mean Coefficient of Variation (in %) for both study days with SD is depicted.
Of the 92 biomarkers analysed in the Cardiovascular II Panel of OLINK, 85 could be utilised for statistical analysis. For 7 biomarkers (STK 4, IL-17D, FGF-23, ITGB1BP2, BNP, CA5A, PARP-1) data was unusable due to missing values and these proteins were excluded from the statistical analysis. Of the remaining 85 biomarkers, 7 biomarkers showed significant differences at t = 360min between the two study days (rapid vs continuous protocol) (Table 5).
The focus of our analysis was therefore on the following biomarkers:
- Bone morphogenetic protein 6 (BMP-6)
Comparing the two study days, BMP-6 showed no relevant increase during and after the administration of glucose (p = 0,104, as calculated by RM-ANOVA), whereas at time point t = 360min a relevant increase of the protein was observed after rapid glucose administration (Fig 6). The increase was not detectable after 24h or 48h. Using a paired t-test for the time point t = 360min, a significant difference was found (p = 0.033).Fig 6. BMP6 values on a NPX scale after administration of rapid glucose (bolus) vs. continuous glucose.Whereas RM-ANOVA did not reveal significant differences between continuous and bolus administration of glucose (p = 0,104), there is a marked increase at 360 minutes after bolus administration, which was statistically significant using paired t-test (p = 0,033). Of note, the NPX format is an arbitrary log2 unit. Therefore, the depicted values do not reflect actual concentrations.
- Interleukin-4 receptor subunit alpha (IL-4RA)
After both continuous and rapid administration of glucose, IL-4RA showed an increase after 24h and 48h compared to the beginning of the measurements (Fig 7). Overall there was no significant difference between the two study days (p = 0,147). By paired t-test at t = 360min, there was a significant increase with rapid glucose infusion compared to continuous administration (p = 0.033).Fig 7. IL4RA values on a NPX scale after administration of rapid glucose (bolus) vs. continuous glucose.Whereas RM-ANOVA did not reveal significant differences between continuous and bolus administration of glucose (p = 0,147), there is a significant difference at 360 minutes after bolus administration regarding paired t-test (p = 0,033). Of note, the NPX format is an arbitrary log2 unit. Therefore, the depicted values do not reflect actual concentrations.
- Pentraxin-related protein PTX3 (PTX3)
While there was no significant change between the two study days for PTX3 (p = 0,297), a significant increase was seen at time point t = 360min with rapid glucose infusion in comparison to continuous infusion (p = 0.033) (Fig 8).Fig 8. PTX3 values on a NPX scale after administration of rapid glucose (bolus) vs. continuous glucose.Whereas RM-ANOVA did not reveal significant differences between continuous and bolus administration of glucose (p = 0,297), there is a marked increase at 360 minutes after bolus administration, which was statistically significant using paired t-test (p = 0,033). Of note, the NPX format is an arbitrary log2 unit. Therefore, the depicted values do not reflect actual concentrations.
- Lectin-like oxidised LDL receptor 1 (LOX-1)
After rapid glucose infusion, there was a significant increase at t = 360min compared to continuous administration (p = 0.015) (Fig 9). There were no significant differences between the two study days (p = 0,233).Fig 9. LOX1 values on a NPX scale after administration of rapid glucose (bolus) vs. continuous glucose.Whereas RM-ANOVA did not reveal significant differences between continuous and bolus administration of glucose (p = 0,233), there is a marked increase at 360 minutes after bolus administration, which was statistically significant using paired t-test (p = 0,015). Of note, the NPX format is an arbitrary log2 unit. Therefore, the depicted values do not reflect actual concentrations.
- Interleukin-1 receptor antagonist protein (IL-1RA)
IL-1RA showed no significant increase or decrease after continuous glucose administration, whereas there was a significant upward deflection after rapid glucose infusion at t = 360min (p = 0.044) (Fig 10). There were no significant differences comparing the two study days (p = 0,085).Fig 10. IL1RA values on a NPX scale after administration of rapid glucose (bolus) vs. continuous glucose.Whereas RM-ANOVA did not reveal significant differences between continuous and bolus administration of glucose (p = 0,085), there is a marked increase at 360 minutes after bolus administration, which was statistically significant using paired t-test (p = 0,044). Of note, the NPX format is an arbitrary log2 unit. Therefore, the depicted values do not reflect actual concentrations.
- A Disintegrin and Metalloproteinase with a thrombospondin type I motif, member 13 (ADAMTS13)
At time point t = 360min, there was a significant increase in ADAMTS13 following rapid glucose infusion compared to continuous glucose infusion using Wilcoxon test (p = 0,020) (Fig 11). There were no significant differences at the other timepoints (p = 0,204).Fig 11. ADAMTS13 values on a NPX scale after administration of rapid glucose (bolus) vs. continuous glucose.Whereas RM-ANOVA did not reveal significant differences between continuous and bolus administration of glucose (p = 0,204), there is a marked increase at 360 minutes after bolus administration, which was statistically significant using Wilcoxon test (p = 0,020). Of note, the NPX format is an arbitrary log2 unit. Therefore, the depicted values do not reflect actual concentrations.
- SLAM family member 7 (SLAMF7)
From time point t = 360min onwards, SLAMF7 showed higher values in the rapid glucose intake group. The difference at t = 360min was significant between the two study days using Wilcoxon test (p = 0.039) (Fig 12). Overall there was no significant difference between the two study days (p = 0,096).Fig 12. SLAMF7 values on a NPX scale after administration of rapid glucose (bolus) vs. continuous glucose.Whereas RM-ANOVA did not reveal significant differences between continuous and bolus administration of glucose (p = 0,096), there is an increase at 360 minutes after bolus administration, which was statistically significant using Wilcoxon test (p = 0,039). Of note, the NPX format is an arbitrary log2 unit. Therefore, the depicted values do not reflect actual concentrations.
Discussion
Diabetes mellitus increases cardiovascular mortality 2 to 3-fold compared to a healthy control population via microvascular and macrovascular complications [1, 2].
The aim of our study was to evaluate the effects of rapid glucose excursions by measuring the difference between bolus glucose infusion compared to slow continuous glucose infusion in a broad panel of 92 biomarkers involved in cardiovascular processes.
In a similarly designed study, administration of LPS, which induces sepsis, showed significantly stronger effects on cardiovascular biomarkers in comparison to the experimental glucose excursions in this study [26]. It was expected that glucose administration (both bolus and continuous) would have a much smaller effect on cardiovascular biomarkers than artificial inflammation exerted by LPS administration. In this respect, the focus of our study was to detect those biomarkers that already react measurably to short-term changes in blood glucose levels.
Our measurements showed significant changes in seven biomarkers in the comparison between rapid and slow glucose intake, which will be examined in more detail below.
Bone morphogenetic protein 6 (BMP6). The effects of bone morphogenetic proteins (BMPs) range from bone and cartilage formation to influences on cellular differentiation and organ development. In macrophage cell lines, it was shown in mice that cells treated with BMP6 had a similar morphology to cells activated by LPS (lipopolysaccharide). This may indicate the role of BMP6 as a potential regulator of macrophages [27].
In another study, mice were treated with BMP-6 and it was proven that during the 6-day treatment plasma glucose levels were lowered and glucose excursions during an OGTT were minimised [28].
In patients with chronic heart failure, levels of BMP6 were elevated compared to controls, with higher levels in patients of more advanced disease [29].
Furthermore, in another study BMP6 was shown to be a significant biomarker for the development of coronary heart disease—patients with low BMP6 levels showed an increased risk of developing CHD [30].
Pentraxin-related protein PTX3 (PTX3). PTX3, together with other acute phase proteins (such as CRP) is a member of the pentraxins superfamily. While under normal circumstances there are low concentrations in the blood of healthy subjects, PTX3 levels increase rapidly during inflammation [31]. Generally speaking, in studies high levels of PTX3 have been associated with an unfavourable outcome (and increased mortality) and PTX3 was elevated in systemic inflammatory response syndrome and septic shock [32, 33]. In the first days during bacteraemia in patients, PTX3 was even superior to CRP as a prognostic marker [31]. It should be mentioned that PTX3 initiates both protective and harmful processes and accordingly gives contradictory results in studies [34, 35].
PTX3 is likely to be an independent risk factor for the development of vascular events and atherosclerosis [36]. After myocardial infarction, PTX3 plasma levels peaked at 7.5 h, providing evidence that PTX3 is a strong prognostic marker for cardiovascular mortality [36].
In studies with patients suffering from gestational diabetes, a connection is suspected between PTX3 and the pathophysiology of GDM [37]. Furthermore, a significant correlation was found between the maternal sera of PTX3 levels and high blood glucose levels [38].
Lectin-like oxidised LDL receptor 1 (LOX-1). LOX-1 represents one of several scavenger receptors that play an important role in the formation of atherosclerosis via oxidised LDL (ox-LDL). LOX-1 itself is a transmembrane glycoprotein that binds and takes up ox-LDL [39].
Studies have shown SLox-1 (soluble LOX-1), a measurable fragment of the LOX-1 molecule, to increase as a diagnostic marker in patients with coronary artery disease, diabetes, hypertension and metabolic syndrome [39]. Thus, an increased expression of LOX-1 was shown in inflammatory processes, which could not be detected under physiological conditions [40, 41].
Further studies indicated that LOX-1 was elevated in the setting of acute coronary syndromes and showed faster increases than troponin T [42, 43].
LOX-1 was found to be significantly higher in biopsies of epicardial adipose tissue in patients with type 2 diabetes and ischemic heart disease compared to control groups without type 2diabetes mellitus. No significant association was found between the duration of diabetes and increased LOX-1 [44].
It has already been shown in vitro that high glucose concentrations can induce the expression of endothelial LOX-1 [45].
Interleukin-1 receptor antagonist protein (IL-1Ra). There is a close relationship between IL-1α, IL-1β - which increases nitrooxidative stress—and IL-1Ra in the activation and suppression of inflammation in the body [46, 47].
According to studies, the administration of an IL-1 receptor antagonist (anakinra) reduced nitrooxidative stress and improved cardiac left ventricular function compared to control groups [47].
Higher plasma IL-1RA concentrations are associated with an increased risk of developing type 2 diabetes mellitus, whereas in manifest diabetes IL-1RA concentrations are lower compared to controls. It is possible that the higher concentrations represent attempts by the organism to prevent the harmful processes of IL-1 β and to maintain both insulin production and insulin sensitivity [48].
In studies, the administration of recombinant IL-1RA (anakinra) over several weeks was not only able to stop inflammatory processes but also to reduce HbA1c values by 0.5% compared to the placebo group [49, 50].
ADAMTS13. ADAMTS13 is a metalloproteinase that is primarily synthesized in the liver. One of its major functions is cleaving Von Willebrand Factor protein (vWF) [51]. Due to its antithrombotic properties, low ADAMTS13 activity seems to be a risk factor for the development of ischemic stroke and myocardial infarction [52, 53].
Apart from its role as a regulator of thrombosis, ADAMTS13 also seems to have an impact on inflammatory processes and angiogenesis [51].
Low ADAMTS13 levels have been associated with increased mortality in patients suffering from sepsis or in septic shock [54].
In the plasma of patients with diabetes some studies have seen significantly lower concentrations of ADAMTS13 activity compared to control groups [55]. In other studies, the ADAMTS13 activity was higher in patients with type 2 diabetes [56]. In the same study ADAMTS13 activity was furthermore associated with a higher risk of incident diabetes and suggested that ADAMTS13 has a role in the occurrence of type 2 diabetes at earlier stages–even before a rise in glucose [56].
Signalling lymphocytic activation molecule-F7 (SLAMF7). Studies have shown that SLAMF7 is overexpressed on multiple myeloma cell surfaces in studies and is therefore considered a target of multiple myeloma therapy [57].
SLAMF7 as a biomarker could also provide information on the progression of multiple myeloma [58].
Interleukin-4 receptor subunit alpha (IL-4Rα). As Interleukin-4 or Interleukin-13 bind to the Interleukin-4 receptor on macrophages, this leads to macrophage activation. IL-4Rα is one component of the interleukin-4 receptor [59, 60].
Interleukin 4 has been linked in studies to allergic reactions as well as inflammatory and malignant processes [59].
Limitations
The relatively small number of participants is a possible limitation of our study. However, due to the cross-over design with all subjects receiving both continuous as well as bolus glucose infusions on two different study days, sufficient power to identify biomarkers influenced by glucose excursions can be assumed. Importantly, this study integrated male, healthy subjects only; female subjects were excluded due to potential hormonal effects on cardiovascular biomarkers during menstruation.
Another limitation of this study is the design regarding glucose intake—we chose to administer 20 grams of glucose i.v. three times compared to 1x60 grams of glucose i.v.. It seems possible that higher doses and thus greater rapid glucose excursions would show stronger effects on the biomarkers of interest.
Impact
The effects of glucose variability on cardiovascular processes are currently still the subject of controversy. Although there are already some studies providing evidence that glucose variability (independent of HbA1c) is a relevant risk factor for the development of cardiovascular complications, there is still a lack of clear definitions of how glucose variability should be measured and described.
In this study, we have focused on glucose variability intraday, i.e. within a short period of time. It was surprising for us that even such short-acting changes in blood glucose levels, which certainly could not be reflected in HbA1c measurements, had an effect on some of the biomarkers already described in detail here.
Thus two major conclusions can be drawn from our work.
First, the measurement of HbA1c reflects only part of the risk on cardiovascular processes.
Second, even small and short-term excursions in blood glucose levels can induce an effect on cardiovascular biomarkers in healthy subjects without diabetes mellitus.
The PCR measurements of the broad panels available now make it possible to measure the effects of glucose variability on many biomarkers that are integrated in a variety of processes.
Conclusion
In this prospective study, we have been able to show for the first time that rapid glucose administration of 3x20g glucose i.v. compared to the continuous administration of 1x60g i.v. in healthy male volunteers has effects on cardiovascular biomarkers and has shown significant changes in BMP6, SLAMF7, ADAMTS13, IL1RA, PTX3, IL-4RA and LOX-1.
Supporting information
S1 Checklist. Consort 2010 checklist of information.
https://doi.org/10.1371/journal.pone.0279308.s001
(DOC)
S1 Data. Dataset including cardiovascular biomarkers (NPX values) and glucose values.
https://doi.org/10.1371/journal.pone.0279308.s003
(XLSX)
Acknowledgments
Guarantor: Martin Clodi is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
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