1 Department of Endocrinology and Metabolism M, Aarhus University Hospital, 8000 Aarhus, Denmark; 2 Department of Medicine, University of Virginia, and National Science Foundation Center for Biological Timing, Charlottesville, Virginia 22908; and 3 Department of Medicine, The University of Edinburgh, Edinburgh EH4 2XU, Scotland, United Kingdom
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ABSTRACT |
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Detection of insulin secretory bursts in
peripheral blood is hampered by hepatic insulin extraction, dilution in
the systemic insulin pool, and time-delayed damping of secretory burst
amplitude. Previous studies in dogs in vivo and other experiments in
vitro have shown that ~70% of all insulin is released within
distinct insulin secretory bursts. To establish a method for detection and quantification of pulsatile insulin release in humans on the basis
of peripheral insulin concentration measurements, we used a
high-sensitivity, -specificity, and -precision insulin enzyme-linked immunosorbent assay (ELISA) and optimized an established deconvolution methodology to quantify the frequency, mass, and amplitude of insulin
secretory bursts as well as to estimate the relative contribution of
pulsatile insulin release to overall insulin secretion. By use of
minutely sampled serum insulin concentrations measured by a highly
sensitive insulin ELISA, and insulin kinetics of 2.8 min (first
half-life), 5.0 min (second half-life), and a fractional slow component
of 0.28, the deconvolved insulin secretion rates in 20 healthy subjects
during glucose infusion (4.5 mg · kg1 · min
1)
could be resolved into a series (4.7 ± 0.1 min/pulse) of
approximately symmetric insulin secretory bursts with a mean mass of 87 ± 12 pmol · l
1 · pulse
1
and a mean amplitude (maximal release rate) of 35 ± 4.7 pmol · l
1 · min
1.
The relative contribution of pulsatile to overall insulin secretion was
75 ± 1.6% (range 59-85%). We conclude that in vivo insulin secretion in humans during nominal glucose stimulation consists of a
series of punctuated insulin secretory bursts accounting for
75% of
total insulin secretion.
oscillations; glucose; C-peptide; amplitude
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INTRODUCTION |
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IT IS WELL ESTABLISHED that insulin is secreted in a pulsatile manner (2, 8). This pulsatile mode of insulin release is discernible in the systemic circulation as small oscillations in the serum insulin concentration (8). Quantification of pulsatile insulin secretion in humans presents several difficulties. Insulin secretory bursts are delivered into the portal circulation in relatively high frequency and undergo both waveform damping and extensive first-pass extraction before presentation in the systemic circulation. These problems were recently overcome in a canine model in which pulsatile insulin secretion was measured directly in the portal vein by catheterization across the pancreas (15). This study provided the opportunity to validate an established deconvolution program for measurement of pulsatile insulin secretion and apply this technique to quantitate pulsatile insulin secretion from peripheral blood measurements.
To date, pulsatile insulin secretion has not been quantified extensively in humans. Because canine in vivo and other in vitro studies suggest that ~70% of insulin is secreted in a pulsatile manner (15) and that modulation of insulin pulses represents a dominant mechanism by which insulin secretion is regulated (14), it is important to understand the regulation of pulsatile insulin secretion in humans.
We therefore undertook the present studies to optimize the recently validated deconvolution technique for detection and quantification of pulsatile insulin secretion in humans (protocols 1-3). We then applied this method to determine the frequency, amplitude, and mass of insulin secretory bursts and to quantify the contribution of pulsatile insulin secretion to its overall release in humans.
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METHODS |
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Subjects and Design
The protocol was approved by the Ethical Committee of the County of Aarhus and was in accordance with the Declaration of Helsinki. A total of 32 (14 female, 18 male) healthy volunteers were studied. Insulin kinetics were examined in six persons (4 male, 2 female) (protocol 1), and the appropriate stringencies for detection of pulsatile insulin secretory events were based on analysis of an insulin concentration time series obtained from three male subjects during constant suppression of endogenous insulin secretion (by somatostatin) and a known constant comcomitant insulin infusion (protocol 2). Having established optimal stringencies and insulin kinetic parameters, we examined optimal sampling frequencies in three (1 female, 2 male) subjects by sampling every 30 s and using every sample vs. every second sample for pulse detection purposes (protocol 3). The above stringencies, insulin kinetic parameters, and optimal sampling frequency were applied to insulin concentration time series obtained from 20 volunteers (11 female, 9 male; age 35 ± 1.6 yr; body mass index 25 ± 0.6 kg/m2; waist-to-hip ratio 0.88 ± 0.02) to examine pulsatile and nonpulsatile insulin secretion (protocol 4). None of the volunteers was on medication or had concurrent diseases or any family history of diabetes. In each protocol the subjects were studied after an overnight fast (10 h). After catheter placement in both antecubital veins for sampling and infusion purposes, the study protocol was commenced as described in Protocols.Protocols
Protocol 1: Insulin kinetics.
The disappearance of insulin infused into the systemic circulation was
examined in six subjects. At time 0 a
bolus injection of crystalline human insulin (Actrapid, Novo Nordisk,
Bagsvaerd, Denmark; 0.04 U/kg) was injected intravenously. At 60 min a
constant insulin infusion (1 mU · kg1 · min
1)
was started and continued for 120 min, at which time the infusion was
discontinued. The decay of insulin was examined for an additional 60 min. To avoid symptomatic hypoglycemia and to prevent hyperglycemia, a
variable glucose infusion was given to achieve plasma glucose concentrations between 3.5 and 5.0 mM. At these glucose concentrations, endogenous insulin secretion was assumed to be trivial, and
counterregulatory mechanisms would not influence insulin disappearance.
Blood was collected at frequent intervals (initially every 15 s, and at late decay every 5 min) for the purpose of analyzing insulin kinetics. The decay of the serum insulin concentration after constant insulin infusion was used to estimate the second (slow) component insulin half-life, because complete distribution of insulin in the sampling pool was assumed and endogenous insulin secretion was likely to be
minimal.
Protocol 2: Pulse detection stringencies.
To define the optimal stringencies for pulse detection, one must avoid
detection of fluctuations in insulin concentrations arising from assay
noise and biological noise (fluctuations arising from sampling
technique, changes in blood flow, and the like). Deconvolution
stringencies (statistical criteria for allowing changes in the insulin
concentration to be defined as pulses) were adjusted to ensure minimal
false-positive pulse detection (type I statistical error) when applied
to insulin concentration changes due to assay
(SDassay) and biological
(SDbiol) noise. To determine the
optimal stringencies to avoid false positives due to assay variability
(SDassay), we assayed 75 plasma
samples obtained from pooled plasma collected from three normal
volunteers. The pooled plasma was collected at the fasting state and at
various times postprandially to achieve a range of representative
plasma insulin concentrations. The 75 samples were assayed in
triplicate and analyzed by deconvolution as a mock plasma insulin
concentration time series to define signal-free false-positive pulse
detection. Similarly, to account for
SDbiol, we sampled plasma from
three volunteers during suppression of endogenous insulin secretion (plasma C-peptide concentrations fully suppressed) by high-dose somatostatin infusion (300 µg/h), during continuous insulin infusion (0.35 mU · kg1 · min
1),
and during a variable glucose infusion to achieve plasma glucose concentrations of 5 mM (euglycemic clamp). The samples were analyzed for plasma insulin concentrations in triplicate, and the plasma insulin
concentration time series was subjected to deconvolution analysis.
Protocol 3: Sampling frequency.
To examine whether a sampling frequency of 30 s vs. 1, 2, or 3 min per
sample would yield improved pulse detection during endogenous pulsatile
insulin secretion, we sampled every 30 s for 75 min during a constant
glucose infusion (2.5 mg · kg1 · min
1)
in three healthy volunteers. We then employed either every data point
(thirty s per sample) or every second (1 min per sample), fourth (2 min
per sample), or sixth (3 min per sample) data point to calculate
pulsatile insulin secretion in the face of different sampling
densities.
Protocol 4: In vivo measurement of human pulsatile insulin release.
Insulin secretion in healthy humans was examined during a low-dose
glucose infusion (4.5 mg · kg · min1)
subject to optimal pulse detection conditions (above)
during a known intermediate secretory stimulus. After 60 min of glucose infusion, 1 ml of blood was collected every minute for 75 min for
measurement of serum insulin concentrations. At 15-min intervals, an
additional 2-ml amount of blood was collected to allow measurement of
serum C-peptide.
Assays
Insulin. Serum insulin concentrations were measured in triplicate by a two-site immunospecific insulin enzyme-linked immunosorbent assay (ELISA), as previously described (1). Briefly, the assay uses two monoclonal murine antibodies (Novo Nordisk, Bagsvaerd, Denmark) specific for insulin. The detection range of this ELISA insulin assay is 5-600 pM. At medium (150 pM), medium-high (200 pM), and high (350 pM) plasma insulin concentrations, the interassay (among triplicate) variation coefficients are 3.7, 4.0, and 4.5%. Corresponding intra-assay variations are 2.3, 2.1, and 2.0%. There is no cross-reactivity with proinsulin, split (32, 33)-insulin, and des(31, 32)-proinsulin. The antibodies cross-react 30 and 63% with split (65-66)-proinsulin and des(64,65)-proinsulin, respectively. C-peptide, insulin-like growth factors I and II, and glucagon do not cross-react (1).
C-peptide. C-peptide measurements were performed using a commercially available kit (K6218, DAKO Diagnostics, Cambridgeshire, UK). The assay is a two-site ELISA, based on two monoclonal antibodies and employing the same principles referred to in Insulin. Each sample was assayed in duplicate, and the intra- and interassay (among triplicate) variation coefficients were 2.2 and 3.3%.
Calculations
Insulin kinetics. For examination of the disappearance of the insulin bolus injection, a two-compartment model with biexponential insulin decay was assumed. The estimate of the second (slower) half-life was based on insulin decay after a 60-min insulin infusion. This second half-life was then used as an initial estimate when the decay in insulin concentrations was fit after an insulin bolus injection. The effective volume of distribution under conditions of constant delivery into the sampling compartment was calculated from insulin concentration data during the constant insulin infusion. The insulin data were deconvolved using the measured insulin kinetics, resulting in insulin delivery rates per unit volume of distribution that should equal the known insulin infusion rates.
Deconvolution analysis. The plasma insulin concentration time series were analyzed by deconvolution for purposes of insulin secretory pulse detection and quantification. Deconvolution of venous insulin concentration data was performed with a multiparameter technique (20) that requires the following assumptions. The venous plasma insulin concentrations in any one subject measured in samples collected at frequent intervals were assumed to result from five determinable and correlated parameters: 1) a finite number of discrete insulin secretory bursts occurring at specific times and having 2) individual amplitudes (maximal rate of secretion attained within a burst); 3) a common half-duration (duration of an algebraically Gaussian secretory pulse at half-maximal amplitude), superimposed on a 4) basal time-invariant insulin secretory rate; and 5) a biexponential insulin disappearance model in the systemic circulation consisting of estimated half-lives of 2.8 and 5.0 min, and a fractional slow compartment of 0.28, measured as we have described. Assuming the foregoing nominal insulin disappearance values, we estimated the number, locations, amplitudes, and half-duration of insulin secretory bursts, as well as a nonnegative basal insulin secretory rate, for each data set by nonlinear least squares fitting of the multiparameter convolution integral for each insulin time series. A modified Gauss-Newton quadratically convergent iterative technique was employed with an inverse (sample variance) weighting function (21). Parameters were estimated until their predicted values and the total fitted variance both varied by <1 part in 100,000. Asymmetric highly correlated joint variance spaces were calculated for each parameter by the Monte Carlo support-plane procedure (21). Secretory rates were expressed as mass units of insulin (pmol) released per unit distribution volume (liter) per unit time (min). The mass of hormone secreted per burst (time integral of the calculated secretory burst) was thus computed as picomole insulin released per liter of systemic distribution volume. Because the calculated values truly represent hepatic vein insulin appearance, total insulin secretion was calculated from C-peptide concentrations (18). The serum insulin concentration time series obtained during a constant insulin infusion and ablation of endogenous insulin secretion (protocol 2) were subjected to deconvolution, and stringency for detection of insulin secretory bursts was increased progressively from, first, statistical confidence intervals of 67 to 95% for individual pulse amplitudes; second, for all pulse amplitudes, considered jointly; and, finally, for all pulse amplitudes and the pulse half-duration considered jointly. The use of confidence limits allowing <1 false positive pulse per 100 samples (min) was considered optimal. When the deconvolution analysis was performed, basal secretion was adjusted to allow accommodation of 95% of troughs. Likewise, the secretory burst half-duration was initially estimated as ~1 min, allowed to fit individual unimodal secretory bursts, and then fit iteratively with all amplitudes, positions, and baseline.
SDassay and SDbiol. The assay uncertainty, or SDassay, was determined from the intrasample variance of the triplicates in each data set. Furthermore, because of dilution from saline infusate, hemolysis, proteases, and unknown reasons, biological variation, or SDbiol, may occur. SDbiol under sampling conditions was calculated from the variation (SDtotal) in plasma insulin concentration time series obtained during constant insulin infusion and ablation of endogenous insulin secretion by high-dose somatostatin infusion, employing
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(1) |
Statistics
All data in texts and figures are given as means ± SE. Statistical methods related to detection of pulses are described in Calculations. Analysis of insulin decay is described in Insulin. ![]() |
RESULTS |
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Insulin Kinetics
The mean insulin decay after a constant insulin infusion was measured to be 5.0 ± 0.1 min. When this was used as the second half-life in fitting the decay after a bolus insulin injection, the first half-life was 2.8 ± 0.4 min, and the fractional slow component was 0.28 ± 0.04. In examining the second half-life on the basis of disappearance of a single bolus rather than after discontinuation of a constant infusion, similar measures of second half-life were obtained (5.2 ± 0.2 min). Examples of three individual decays obtained by use of these values after constant and bolus injections are shown in Fig. 1. The calculated effective volume of distribution at steady state was 206 ± 18 ml/kg body weight.
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Pulse Detection Stringencies
Application of 95% joint confidence limits to all pulse amplitudes resulted in two false-positive pulses per 225 min (P < 0.01 as desired). SDassay was calculated to be 2.2 ± 0.3%, whereas SDbiol under the study conditions was calculated to be 3.3 ± 0.4%. The variation(s) in insulin concentration due to assay alone and due to SDbiol and SDassay considered jointly are compared with a representative serum insulin concentration profile during endogenous insulin secretion in vivo in Fig. 2.
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Sampling Frequency
When the sampling intensity is varied from 1 sample/30 s to 1 sample/min, the detected insulin pulse frequency was unchanged (shown in Fig. 3). However, further increase of the sampling interval to 2 or 3 min significantly reduced the number of pulses detected, as shown in Fig. 3. Consequently, the optimal sampling intensity under the present conditions (glucose infusion, measurements in triplicate, present ELISA, healthy humans) was sampling by the minute.
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In Vivo Measurement of Human Pulsatile Insulin Release
In all cases, inspection of peripheral insulin concentration profiles showed obvious oscillations in the serum insulin concentrations, consisting primarily of serial data points leading to peaks and to troughs (Figs. 2 and 4). Deconvolution analysis confirmed that the insulin concentration oscillations were due to pulsatile insulin release (Fig. 4). This insulin release was best described as serial insulin secretory bursts superimposed on a nonnegative basal insulin secretion rate. The frequency of insulin secretory events was 4.7 ± 0.1 min/pulse. The pulses had a mean amplitude of 35 ± 4.7 pmol · l
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DISCUSSION |
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In the present studies, we first established optimal parameters for detection of insulin secretory bursts in humans by deconvolution analysis of intensively sampled peripheral serum insulin concentration time series. We applied a highly sensitive and precise ELISA insulin assay for triplicate insulin measurements to minimize within-assay experimental uncertainty. Low-dose glucose infusion was imposed to facilitate the detection of insulin secretory events and to examine the significance and nature of stimulated pulsatile insulin secretion. We found that, overall, insulin secretion consisted predominantly of high-frequency insulin secretory bursts that were partially overlapping. The insulin secretion that was not detected as pulsatile accounted for no more than 25% of all insulin secreted.
The calculated insulin kinetic values were similar to literature values obtained after decay of an intravenously injected insulin bolus (6). To examine insulin kinetics a two-phase protocol was chosen that showed good agreement. Endogenously secreted insulin is unlikely to influence the calculations, because C-peptide concentrations were suppressed, and hyperinsulinemia in the absence of hyperglycemia (clamped glucose concentration 3.5-5.0 mM) is known to suppress insulin secretion (19). The deconvolution pulse detection criteria employed were carefully defined after sequential analysis of mock insulin concentration time series derived from repetitive triplicate insulin measurements of pooled plasma and from triplicate insulin concentration time series obtained during a constant insulin infusion with concomitantly ablated endogenous insulin secretion. As shown earlier for pulse-analysis optimization (22), different assay(s), number(s) of replicates, and sampling procedure(s) may influence the preferred criteria.
Further increase of the blood sampling intensity to every 30 s vs. every minute did not improve the detection of endogenous insulin secretory bursts significantly. This may also be the result of optimized methods for pulse detection, the use of stimulated insulin secretion, a highly sensitive and precise insulin assay, and the application of deconvolution analysis vs. conventional pulse detection. The former has been shown to improve pulse detection (13), particularly when pulses are partially overlapping. In studies employing less sensitive or less reproducible insulin assays, increased sampling frequency and replications could potentially be advantageous. Also, the relatively shorter half-life of insulin vs. C-peptide (18) favors the use of insulin vs. C-peptide for purposes of deconvolution analysis, because consecutive insulin secretory bursts may be easier to separate. The variable insulin half-lives among different subjects, in contrast to the fairly constant C-peptide half-lives (18), were dealt with by application of a waveform-independent deconvolution method that incorporates the population variability in the insulin half-life as obtained by protocol 1.
Sampling from peripheral blood results in an inherent time lag between the secretory event and detection of insulin concentration changes in peripheral blood. This time delay also is likely to cause damping of the insulin secretory burst (13) and thereby to underrepresent the pulsatile component of overall insulin secretion. However, the present data are similar to calculated relative contributions of pulsatile to total insulin secretion in dogs, in which blood was obtained directly from the portal vein, and independent mathematical analyses were applied (15).
We report a mean interpulse interval (time from pulse peak to pulse peak) of 5 min for glucose-stimulated pulsatile insulin secretion, which is less than previously inferred in humans during euglycemia (10). However, studies employing portal vein sampling report a similar frequency at similar glucose concentrations in dogs (14) and in humans with cirrhosis (16). Our combined use of high-sensitivity assay, high-intensity blood sampling (0.5-1.0 min/sample), glucose infusion, and validated deconvolution analysis likely improves pulse detection in vivo (13). Indeed, the in vivo frequency reported here is similar to that reported in the isolated perfused pancreas (7) and in the isolated perifused islet (11). Studies have shown oscillations in the intracellular calcium concentrations that have similar periodicity (9). In aggregate, therefore, the very similar oscillatory patterns observed for membrane potentials (5), intracellular calcium (9, 11), and insulin secretion in vitro (3, 11) in individual islets conform with the oscillatory nature of peripheral insulin concentrations in vivo inferred here. The in vitro frequency tends to be slightly higher, perhaps reflecting either pulse detection differences or a decrease in pacemaker activity in the in vivo milieu.
Overall insulin secretion was resolved into a series of partially overlapping symmetric and discrete secretory events with little basal or nonpulsatile insulin secretion. To the extent that these bursts overlap, resolution of interpulse insulin secretion into basal secretion vs. ultra-high-frequency overlapping pulses is less achievable. The analysis applied here favors detection of some nonpulsatile insulin secretion if events partially overlap, and, of note, apparent basal secretion was inferred in all 20 studies. Thus our estimate of 75% pulsatile insulin secretion is likely to be a minimum value. In addition, analysis of the fitted variance ratios assuming zero vs. finite (positive) nonpulsatile insulin secretion did not consistently show a significantly better fit in the absence of assumed and/or calculated basal insulin secretion.
The quantification of insulin secretion as predominantly pulsatile also suggests that significant intrapancreatic coordination is necessary to govern the relative timing of insulin release from discrete islets. In theory, oscillating insulin release may be due to periodic stimulation, periodic inhibition, or both. For example, in the case of growth hormone (GH) release, balanced inhibition and stimulation by, respectively, GH-releasing hormone and somatostatin with concomitantly decreased inhibition and agonist-driven secretion serve to organize secretion into intermittent secretory bursts (17).
Impaired pulsatile insulin release has been reported in type II diabetics and first-degree relatives of patients with type II diabetes (12), underlining the possible importance of disrupted secretory patterns in these states. Furthermore, a blunted insulin secretory response to an oral or intravenous glucose challenge in type II diabetes is a hallmark of this disease (4). The central role of pulsatile secretion in overall insulin release suggests a link between impaired pulsatile insulin secretion and inappropriate glucose-stimulated insulin secretion in type II diabetes.
The insulin secretory pattern reported in this study implies that most
-cells secrete simultaneously over a 2- to 4-min period, with a
frequency of one burst every 5 min. The duration of nonsecretory "basal" intervals is inevitably dependent on the frequency of insulin secretory bursts. The latter may be increased with
hyperglycemia (14). If the nonsecretory phase is important for
restitution of
-cells and for their nonsecretory functions, then the
duration of this nonsecretory phase may be important for long-term
-cell performance.
For detailed analysis of pulsatile insulin secretion, mathematical methods based on merely measuring amplitudes of peripheral insulin oscillations may be hampered by changes in the frequency of isulin secretory bursts, because the latter will cause changes in the nadir levels between pulses and thus influence the incremental and maximal (absolute) amplitude of these oscillations. For example, studies comparing pulsatile insulin secretion during different glucose concentrations, in which circumstances of different frequencies may be assumed (14), will tend to favor detection of pulsatile insulin secretion at lower glucose concentrations. Deconvolution analysis to accommodate succession of peaks and troughs should improve the appreciation of insulin secretory bursts at higher glucose concentrations (22).
Whereas it thus appears that, in healthy humans, glucose-stimulated insulin secretion mainly consists of series of punctuated insulin secretory bursts rather than basal or nonpulsatile secretion, the mechanisms by which overall secretion is regulated through changes in frequency, mass, and/or shape of pulsatile insulin secretion require further study. Moreover, the mechanisms underlying the impaired pulsatile insulin secretion observed in type II diabetes are likely to be important in understanding the characteristically blunted insulin secretory responses to relevant challenges in this disease.
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ACKNOWLEDGEMENTS |
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The expert technical assistance of Anette Mengel, Lene Trudsø, and Elsebeth Hornemann is highly appreciated.
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FOOTNOTES |
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The present study was supported by the University of Aarhus, Aarhus, Denmark; Novo Nordisk, Bagsvaerd, Denmark; and the Dandy Foundation, Vejle, Denmark. N. Pørksen and B. Nyholm were supported by the University of Aarhus.
Address for reprint requests: N. Pørksen, Dept. of Endocrinology and Metabolism, Aarhus Univ. Hospital, 8000 Aarhus C, Denmark.
Received 27 February 1997; accepted in final form 21 July 1997.
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