Abstract
Background and Objective:
The premise of effective closed-loop insulin therapy for type 1 diabetes (T1D) relies on the accuracy of continuous interstitial fluid glucose sensing that represents the crucial afferent arm of such a system. An important determinant of sensor accuracy is the physiological time lag of glucose transport from the vascular to the interstitial space. The purpose of current studies was to determine the physiological time lag of glucose transport from the vascular to the abdominal subcutaneous interstitial space in T1D.
Method:
Four microdialysis catheters were inserted into the abdominal subcutaneous space in 6 T1D subjects under overnight fasted conditions. Plasma glucose was maintained at 113.7 ± 6.3 mg/dl using a continuous intravenous insulin infusion. After sequential intravenous bolus administrations of glucose isotopes, timed plasma and interstitial fluid samples were collected chronologically and analyzed for tracer enrichments.
Results:
We observed a median (range) time lag of tracer appearance (time to detection) into the interstitial space after intravenous bolus of 6.8 (4.8-9.8) minutes, with all participants having detectable values by 9.8 minutes.
Conclusions:
We conclude that in the overnight fasted state in T1D adults, the delay of glucose appearance from the vascular to the interstitial space is less than 10 minutes, thereby implying that this minimal physiological time lag should not be a major impediment to the development of an effective closed-loop control system for T1D.
Keywords: interstitial glucose concentration, subcutaneous glucose transport, type 1 diabetes, microdialysis, continuous glucose monitors
Insulin therapy for management of type 1 diabetes (T1D) and in insulin requiring patients with type 2 diabetes have improved significantly since the iconic discovery of insulin almost a century ago. This progress has been due to multiple reasons that include but are not limited to newer insulin analogs, user-friendly and sophisticated insulin delivery devices, improved accuracy of glucose meters to self- monitor finger-stick blood glucose, and so on. Over the past decade, automated closed loop control (CLC) systems and algorithms have been tested in clinical research trials that utilize subcutaneously delivered insulin through insulin pumps coupled with glucose measurements obtained from the interstitial fluid (ISF) through subcutaneously placed continuous glucose monitor (CGM) probes. Such artificial endocrine pancreas (AEP) systems, where the afferent glucose signal that drives insulin delivery is obtained from the CGM, is critically dependent on precise knowledge of the physiological time lag of glucose transport from the intravascular to ISF compartments. A recent critique of the AEP suggested that lag times between plasma and ISF glucose was a significant limiting factor in the ability of CLC systems to successfully manage T1D.1
There have been a number of studies sponsored by CGM manufacturers to investigate the physiological lag time between blood glucose measurements and CGM measurements of interstitial fluid glucose. Studies done at Medtronic identified numerical processing algorithms as the single most important factor in contributing to the appearance of lag time between blood glucose and CGM measurements of interstitial glucose.2,3 Studies done by Dexcom Inc, on this issue with the earlier generation Dexcom SEVEN™ continuous glucose monitor in which they found an average sensor time lag of only 5.7 minutes compared with venous blood reference measurements.4 Additional studies have been done by Steil et al using Medtronic minimed sensors in both human and animal models under hyperglycemic clamp conditions without direct corroboration with ISF by microdialysis techniques.5-7 Studies done by researchers at CGM manufacturers inferred the physiological lag time between blood glucose and interstitial fluid glucose from comparison of CGM measurements to blood glucose measurements. In the study reported here, we use the more sensitive glucose tracer method to directly determine the true physiological lag time between blood glucose and interstitial fluid glucose independent of CGM measurements.
However, we have recently reported that under steady-state postabsorptive conditions, in healthy nondiabetic individuals, the time lag of glucose transport from plasma to ISF compartments is ~5-6 minutes.8 Applying a similar study design utilizing glucose isotopes and microdialysis techniques, we conducted this study to examine the time lag of glucose transport from plasma to ISF in T1D subjects under steady-state postabsorptive conditions. We reasoned that the time lag could be different from that observed in healthy subjects for a variety of reasons that include, among others, altered anatomy of the subcutaneous space in T1D subjects due to repeated trauma of insulin injections, local lipohypertrophy, possible direct local insulin effects on glucose transport, and glucose uptake by adipose tissue when insulin is also administered into the abdominal subcutaneous space.
Research Design and Methods
After approval from the Mayo Institutional Review Board and signed informed consent, 6 subjects with T1D were enrolled (4 on insulin pump and 2 on multiple daily insulin injections). Subjects reported to the Clinical Research Unit (CRU) of the Mayo Center for Clinical and Translational Science (CCaTS) in the morning after an overnight fast for the screen visit. Inclusion criteria include age 18-60 years, BMI 19-30 kg/m2, HbA1c ≤ 10 %, and serum creatinine ≤1.5 mg/dl. Exclusion criteria included pregnancy, breast-feeding or other comorbidities (eg, nephropathy, neuropathy, macrovascular disease, hypertension) that precluded participation. Those with stable background diabetic retinopathy were included. Medications that could influence glucose tolerance were exclusionary. After history and physical examination, fasting blood samples were drawn to ensure that subjects met enrollment criteria. A negative pregnancy test was obtained in women with child-bearing capabilities before enrollment. A dual-energy X-ray absorptiometry (DXA) scan was performed to measure body composition.8 Subjects who met the enrollment criteria were asked to return for the study visit within 2-3 weeks.
Participants were admitted to the CRU at ~1600 hours, consumed a standard 10 kcal/kg evening meal (50% carbohydrate, 20% protein, and 30% fat) at ~1700 hours and remained nil per oral except water for remainder of the study. Subjects administered a premeal insulin bolus according to their customary insulin: carbohydrate ratio adjusted for the prevailing glucose concentrations. Intravenous insulin infusion was started at ~2100 hours and continued throughout the rest of the study as per protocol to maintain euglycemia.9 Insulin pump was discontinued for those on the insulin pump when the intravenous insulin infusion was started and those who were on multiple daily insulin did not administer their night-time basal insulin dose. At ~0600 next morning, a cannula was inserted retrogradely into a dorsal hand vein. The heated hand vein method was utilized to periodically draw arterialized venous blood for glucose and tracer concentrations.8,10 A cannula was also inserted into a forearm vein on the contralateral arm for tracer infusions.
Experimental design was as described earlier.8 Briefly, 4 microdialysis catheters (CMA 63, 20 kDa M Dialysis Inc, North Chelmsford, MA) were inserted under local anesthesia and aseptic precautions into subcutaneous abdominal fat, 2 on each side of the abdomen and were infused with CMA perfusion fluid via CMA 107 microdialysis pump at a constant rate of ~1 µl/min for the study period. At periodic intervals, timed-pooled microdialysate effluent and blood samples were collected for glucose and tracer measurements simultaneously. Following insertion of the last microdialysis catheter, at least 1 hour was provided to allow catheters to reach steady state. At ~8 am (0 minutes), an intravenous bolus of [1-13C] glucose was administered over 10 seconds. Starting 4 minutes prior to the [1-13C] glucose bolus, microdialysate samples were collected every 5 minutes for the next 30 minutes and periodically thereafter until 9:57 am (117 minutes). Subsequent tracer glucose boluses and sequential timing of microdialysate and blood sample collections were as described previously.8 The rationale for using multiple glucose tracers was to maximize the timed collection frequency of the microdialysate samples. In preliminary in-vitro studies at different microdialysis pump infusion rates, we had observed that the recovery of the glucose tracer/s were optimal at a pump infusion rate of 1 µl/min. At this optimized low infusion rate, we needed to pool samples from 4 microdialysis catheters, simultaneously every 5 minutes, to obtain the minimum and adequate sample volume for glucose isotope analyses in duplicate. If we had used only 1 glucose tracer, our timed samples would have been restricted (eg, for tracer 1: –4 to 1, 1-6, 6-11, 11-16 minutes, etc). Hence we would not have been able to plot the time course of glucose appearance into ISF at more frequent intervals, for example, at 2 minutes, 3 minutes, and so on. Use of multiple glucose isotopes permitted more flexibility in timed collections (eg, for tracer 2: –3 to 2, 2-7, 7-12, 12-17 minutes and so on). Of course, ideally one would have preferred to use several more (up to 5) glucose tracers with sequential 5 minute collections so that the time course of glucose appearance could have been plotted for every minute from the time of injection, but that would have been impractical both for research subject comfort and convenience and would have added substantially to the study time, resources required for custom labeling such tracers or tags and the cost of the study. Importantly, the plasma sample collections were timed exactly to the end of each microdialysate sample collection times.
At the end of the study at ~4 pm, all infusions were discontinued, catheters and cannulae removed and subjects provided a meal. Those on insulin pump resumed their insulin rates at the customary settings and those on multiple dose insulin returned to their dosing schedule. They were then discharged from the CRU after ensuring that their fingerstick glucose values were clinically in the safe range.
Analytical Techniques
Samples were placed on ice, aliquoted and stored at −20°C until assayed. Plasma glucose concentrations were analyzed as described previously.11 Microdialysis and plasma samples for stable tracer enrichment were analyzed by gas chromatography mass spectrometry (GCMS) as described previously.12
Statistical Considerations
The analysis of the tracer concentrations occurred in 2 steps and as described Basu et al.8 Briefly, the timings of sample collection were reindexed to represent time from infusion to appearance at the microdialysis catheter based on infusion setting and tubing volume to account for the lag time taken (6.2 minutes) to cover the catheter dead space. Thereafter, we performed descriptive statistics and concentration profiles and used a Kaplan–Meier product limit estimator to estimate the time to detectable levels in the ISF. That was defined as enrichment molar ratios (MR) > 0.3% as described.8 In the context of the time-to-event analysis, the time from infusion to appearance at the catheter with an enrichment of at least 0.3% was used in the modeling. The upper limit for 95% confidence interval of the 75th percentile of the failure distribution (ie, the estimated time for which 75% of the study subjects had detectable isotope levels beyond MR>0.3%) was used as a conservative estimate of the time required for appearance in the ISF. As reported earlier,8 [2-13C] glucose data was not used due to interference from the [1-13C] glucose administered at 8:00 am. Statistical analyses were conducted using the SAS System (version 9.3, Cary, NC).
Results
Subject Demographics
Table 1 shows the subject characteristics of the participants.
Table 1.
Baseline Characteristics of Participants.
Subject characteristic | Mean ± SD |
---|---|
Age (years) | 44 ± 14 |
Gender (M:F) | 5 : 1 |
Weight (kg) | 74.8 ± 10.6 |
Body mass index (kg/m2) | 25.2 ± 3.6 |
Waist hip ratio | 0.89 ± 0.07 |
Total body fat (%) | 25.3 ± 6.8 |
Fat free mass (kg) | 54.5 ± 8.2 |
Fasting plasma glucose (mg/dl) | 113.5 ± 6.3 |
HbA1c % (mmol/mol) | 7.8 ± 0.9 |
(61.7 ± 4.6) | |
Duration of diabetes (years) | 21 ± 10 |
Plasma Glucose Concentrations
Plasma glucose concentrations were 115.5 ± 7.4 mg/dl prior to start of study and were maintained at 113.7 ± 6.3 mg/dl during entire duration of the study (Figure 1).
Figure 1.
Plasma glucose concentrations observed during the study. Data are mean ± SD.
Plasma and Microdialysate Tracer Glucose Molar Ratio
The subject-specific profiles for [6,6-2H2] glucose (Figure 2) and [1-13C] glucose (Figure 3) are illustrated in plasma (A) and microdialysate (B) for the participants over the entire sampling period with the right panel showing higher resolution data over the first 10 minutes after isotope bolus. The estimated transit time was subtracted from sampling time as described.8 The time from isotope bolus infusion to appearance in the ISF appeared to be ~6 minutes for [6,6-2H2] glucose and slightly longer for [1-13C] glucose, although the frequency of measurements led to imprecision in these estimates. To better quantify the timing, the product limit estimator was used to estimate the mean (standard error) time to appearance for [6,6-2H2] glucose and [1-13C] glucose as 7.1 (0.8) and 8.1 (1.0) minutes respectively. The 95% confidence intervals for the 75th percentiles of the time-to-appearance distributions were 6.8 (5.8 to 10.8) and 9.8 (4.8 to 9.8) minutes, respectively. All participants had detectable values by 10.8 and 9.8 minutes for [6,6-2H2] glucose and [1-13C] glucose, respectively. Thus, 9.8 minutes provides a conservative estimate of the maximum overall time to appearance at the ISF.
Figure 2.
Temporal profile of [6,6-2H2] glucose molar ratios in plasma (A) and microdialysate (B) obtained in each participant over the sampling period of 120 minutes (left panel) and over the first 10 minutes (right panel) after the tracer bolus dose at time 0. The timed interstitial fluid collection includes a correction of 6.2 minutes to allow for transit from the catheter to the collection vial. Each colored symbol and corresponding dotted line represents the temporal profile in an individual subject.
Figure 3.
Temporal profiles of [1-13C] glucose molar ratios in plasma (A) and microdialysate (B) obtained in each participant over the sampling period of 120 minutes (left panel) and over the first 10 minutes (right panel) after the tracer bolus dose at time 0. The timed interstitial fluid collection includes a correction of 6.2 minutes to allow for transit from the catheter to the collection vial. Each colored symbol and the corresponding dotted line represents the temporal profile in an individual subject.
Discussion
Applying a combination of glucose isotope analyses and microdialysis techniques, we have demonstrated that the maximum physiological time lag of glucose transport from the intravascular to subcutaneous interstitial fluid compartment in those with T1D is <10 minutes during resting overnight fasted steady-state conditions. There is good evidence that at least half of the participants had detectable values in as little as 6.8 minutes. As described recently8 in healthy subjects, we employed the same stringent criteria to account for isotope assay noise based on the limit of detectability of the isotopes by mass spectrometry. Plasma glucose concentrations were held at a steady state of ~114 mg/dl (~6.3 mM) with an intravenous insulin infusion throughout the study. It is noteworthy that at steady-state, the lag time cannot be estimated by simply super-posing ISF glucose to venous glucose, hence the need for glucose tracers. Furthermore, the effects of non-steady-state conditions and stimuli, that is, exercise and meals on time lag and equilibration times are currently being conducted to advance our knowledge in this area. We chose to administer insulin intravenously as opposed to subcutaneously to minimize confounding of local insulin delivery into the subcutaneous space affecting subcutaneous glucose transport and hence time lag by influencing glucose uptake by local adipose tissue. We did so to develop and establish a “clean” model of subcutaneous glucose kinetics in T1D subjects. Furthermore, to determine equilibration times of glucose in the ISF, sophisticated modeling of the data is currently being performed and will be reported in a separate manuscript. Needless to say, further studies are also necessary to determine the effects of subcutaneous insulin delivery, either continuously through an insulin pump or intermittently via insulin bolus injections, on time lag of glucose appearance in T1D subjects.
It is indeed surprising that the physiological time lag described here in T1D subjects was similar to our recent report in healthy subjects.8 Given well-established clinical factors of local anatomical abnormalities that exist in patients with T1D that include changes in micro-vasculature and lipo-hypertrophy13-15 which has been linked to poor glycemic control, trauma from repeated insulin injections, resultant fibrosis, and so on, we had anticipated that the time lag would be considerably greater than observed in healthy subjects. This is because, in theory, glucose molecules will have to traverse more barriers as they move across from the intravascular to the interstitial space. Microvascular involvement of subcutaneous fat could also pose an additional barrier to the time lag. In contrast, insulin induced lipoatrophy, an immune mediated process that continues to be observed with insulin analogs16,17 could influence glucose transport and hence the time lag. Although none of our T1D subjects had clinically obvious lipoatrophy or lipo-hypertrophy, it is highly likely that the anatomical structure of the abdominal subcutaneous space was different compared to those without diabetes due to insulin related changes in local adipogenesis and/or injection related trauma. Furthermore, the effects of duration of diabetes and degree of glycemic control on time lag will need to be evaluated in future studies.
The study had similar limitations as discussed in our recent report in healthy subjects.8 In particular, this related both to the unreliability of using [2-13C] glucose data due to interference from the [1-13C] glucose moiety infused earlier. However, the robustness of measurement of both [1-13C] and [6,6-2H2] glucose isotopes and the congruence of the results with both isotopes, strengthen our ultimate observations.
To conclude, we have demonstrated that the time lag of glucose appearance into the ISF from the intravascular compartment is between 7 and 8 minutes in overnight fasted T1D subjects, which is considerably shorter than many have hypothesized. Taken together, such information is critical to further refine and develop next generation algorithms for the CGM especially in the context of the closed-loop artificial pancreas systems currently being developed for T1D.
Acknowledgments
We are deeply indebted to the research participants. Our sincere thanks to Barbara Norby, RN, Cheryl Shonkwiler, RN, and Kelly Dunagan, RN, for the conduct of the studies, the staff of the Mayo Clinic Center for Clinical and Translational Science (CCaTS) Clinical Research Unit (CRU); the Mass Spectrometry Laboratory; CRU Immunochemical Core Laboratory; Pamela Reich (research assistant), Brent McConahey (research assistant), and Linda Kvall Boynton (secretary) for assistance with preparation of the manuscript. All persons mentioned above are at Endocrine Research Unit, Mayo Clinic, Rochester, MN.
Footnotes
Abbreviations: AEP, artificial endocrine pancreas; CCaTS, Center for Clinical and Translational Science; CLC, closed loop control; CGM, continuous glucose monitor; CRU, Clinical Research Unit; DXA, dual-energy X-ray absorptiometry; GCMS, gas chromatography mass spectrometry; ISF, interstitial fluid; MR, molar ratios; T1D, type 1 diabetes.
Declaration of Conflicting Interests: The author(s) declared the following potential conflicts of interest with respect to the research, authorship, and/or publication of this article: TP is a consultant with Dexcom and holds stock in the company.
Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The work was supported by funding from Helmsley Charitable Trust 2012PG-TID005 and Dexcom, Inc to RB, NIH DK29953, and DK 090541 to RB, DK085516 and DK DP3 094331 to AB and YCK, and UL1 TR000135 from the National Center for Advancing Translational Science (NCATS), a component of the National Institutes of Health (NIH). CC is partially funded by Italian Ministero dell’Istruzione, dell’Università e della Ricerca (Progetto FIRB 2009).
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