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The Journal of Clinical Endocrinology & Metabolism Vol. 82, No. 12 4088-4093
Copyright © 1997 by The Endocrine Society


Original Studies

Increased Disorderliness of Basal Insulin Release, Attenuated Insulin Secretory Burst Mass, and Reduced Ultradian Rhythmicity of Insulin Secretion in Older Individuals1

Graydon S. Meneilly, Alice S. Ryan, Johannes D. Veldhuis and Dariush Elahi

Division of Geriatric Medicine, Department of Medicine, University of British Columbia, Vancouver, British Columbia, Canada; the Department of Medicine and the Geriatric Research Education and Clinical Center, University of Maryland, Baltimore, Maryland 00000; the Department of Medicine, University of Virginia, Charlottesville, Virginia 00000; and the Department of Medicine, Harvard University, Boston, Massachusetts 00000

Address all correspondence and requests for reprints to: Dr. Graydon Meneilly, Division of Geriatric Medicine, Department of Medicine, VH&HSC-UBC Site–Room S139, Vancouver, British Columbia, Canada V6T 2B5.


    Abstract
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Insulin is secreted in a pulsatile fashion. Rapid pulses are considered to be important for inhibiting hepatic glucose output, and ultradian pulses for stimulating peripheral glucose disposal. Aging is characterized by a progressive impairment in carbohydrate tolerance. We undertook the current studies to determine whether alterations in pulsatile insulin release accompany the age-related changes in carbohydrate metabolism. Healthy young (n = 8; body mass index, 21 ± 1 kg/m2; age, 24 ± 1 yr) and old (n = 9; body mass index, 24 ± 1 kg/m2; age, 77 ± 2 yr) volunteers underwent two studies. In the first study, insulin was sampled every 1 min for 150 min, and pulse analysis was conducted using a recently validated multiparameter deconvolution technique. In the second study, insulin was sampled every 10 min for 600 min, and insulin release was evaluated by Cluster analysis. In the 150-min studies, insulin secretory burst mass (P < 0.05) and amplitude (P < 0.01) were reduced in the elderly. In addition, approximate entropy, a measure of irregularity or disorderliness of insulin release, was increased in the aged (P < 0.01). In the 600-min studies, interpulse interval was greater in the aged (P < 0.05), and burst number was less (P < 0.05).

We conclude that normal aging is characterized by more disorderly insulin release, a reduction in the amplitude and mass of rapid insulin pulses, and a decreased frequency of ultradian pulses. Whether these alterations in insulin pulsatility contribute directly to the age-related changes in carbohydrate metabolism will require further study.


    Introduction
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
NORMAL aging is characterized by a progressive impairment in carbohydrate tolerance. Two major contributing factors to age-related impairment in glucose tolerance are altered regulation of hepatic glucose output and resistance to insulin-mediated glucose disposal (1, 2, 3).

Insulin is secreted in a pulsatile fashion. There are rapid, low amplitude pulses that occur every 8–15 min and ultradian pulses that have a larger amplitude and a periodicity of 60–140 min (4, 5). Rapid pulses are important in inhibiting hepatic glucose production (6, 7, 8), whereas ultradian pulses are important in stimulating peripheral glucose disposal (9). Both types of pulses show disruption in disease states characterized by altered glucose metabolism, including impaired glucose tolerance, obesity, and type 2 diabetes (10, 11, 12). The orderliness of insulin release is also quantifiably reduced in nondiabetic relatives of patients with type 2 diabetes (13).

Here we tested the hypothesis that the impairment in carbohydrate metabolism with age is accompanied by alterations in pulsatile insulin secretion and/or the regularity of the insulin release process.


    Subjects and Methods
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Experimental subjects

These studies were performed in healthy nonobese young and elderly subjects (Table 1Go). Subjects had a normal history and physical examination, normal laboratory tests, normal electrocardiogram, and normal glucose tolerance test (glucose dose, 40 g/m2; National Diabetes Data Group criteria).


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Table 1. Subject characteristics

 
None of the subjects had a family history of diabetes or was taking medication. This study was approved by the committee on human investigation at the University of British Columbia. All subjects provided written informed consent before participation in the study.

Experimental protocol

Studies were conducted at the Clinical Research Center at the University of British Columbia. Subjects ate a diet containing at least 150 g carbohydrate/day for 3 days before testing. All subjects underwent two studies, separated by at least 2 weeks. Studies commenced at 0730 h after an overnight fast. In each study, an iv catheter was inserted into a hand vein for sampling of arterialized venous blood (14). In the rapid pulse study, insulin was sampled every 1 min, and glucose was sampled every 2 min for 150 min. In the study to determine ultradian pulses, insulin and glucose were sampled every 10 min for 10 h.

As previously reported (15, 16), all subjects had undergone a 180-min euglycemic insulin clamp (insulin infusion, 40 mU/m2·min) within 1 yr of completing the pulsatile insulin protocol. The glucose infusion rate from 150–180 min of the clamp was used as a measure of insulin sensitivity.

VO2 max was determined in all subjects using a bicycle ergometer (15). Waist to hip ratio (WHR) was determined by dividing the abdominal girth at the greatest protuberance by the hip circumference at the greater trochanter (centimeters).

Analytic methods

An aliquot of the sample was used to measure plasma glucose by the glucose oxidase method using a YSI glucose analyzer (Yellow Springs Instruments, Yellow Springs, OH). Blood was placed in prechilled test tubes containing aprotonin (400 kallikrein inhibitor units/mL) and ethylenediamine tetraacetate (1.5 mg/mL) and centrifuged at 4 C. The plasma was stored promptly at -70 C until assay. All samples from each subject were analyzed in the same assay. For the rapid pulsatility analyses, equal numbers of young and old subjects were included in each of two assays. For the ultradian analyses, all samples from all subjects were measured in the same assay. Insulin assays were performed in duplicate using a human insulin kit from Linco Research (St. Louis, MO). This is a very specific and sensitive RIA that has less than 1% cross-reactivity with proinsulin. The interassay coefficient of variation was 11%, and the intraassay coefficient of variation was 6%. The sensitivity was 10 pmol/L.

Pulse analysis

Insulin pulse profiles were analyzed for rapid insulin pulsatility with a multiparameter deconvolution technique (17, 18). This technique quantitatively describes insulin profiles under the following assumptions: 1) a finite number of discrete insulin secretory bursts occurring at specific times, 2) individual secretory burst amplitudes (maximal rates of secretion in a burst), 3) a common half-duration (duration of an algebraically Gaussian secretory pulse at half-maximal amplitude) superimposed on 4) a basal time-invariant increased insulin secretory rate and 5) a nominal insulin half-life of 2.5 min. Parameters were estimated 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. Parameters were estimated until their values and the total fitted variance varied by less than 1 part in 100,000. Asymmetric, highly correlated variance spaces were calculated for each parameter by the Monte Carlo support-plane procedure. Optimal peak detection was defined as less than 1 false positive error/10 true pulses and 0 false negative errors/10 true pulses. Optimal peak detection was achieved by use of 95% joint confidence intervals. The following parameters were calculated: secretory burst number (the number of significant secretory pulses per 150 min), interpulse interval (time in minutes separating successive pulses), burst mass (the mass or area of the calculated secretory bursts), amplitude (maximal secretory rate within a pulse), and basal secretion rate. Cluster analysis was used to quantify the longer ultradian insulin rhythms, assuming that significant up- and downstrokes in plasma insulin concentrations denote peaks (19). Incremental peak height, peak frequency, basal (interpeak nadir) insulin concentration, and peak area above interpeak valley insulin concentrations were computed using this program. Threshold criteria included a t statistic of 2.0 and test clusters of 1, with dose-dependent within-assay variance.

In addition to Cluster and deconvolution analysis, the data were evaluated by a recently developed scale- and model-independent statistic, approximate entropy (ApEn) (13, 20, 21, 22, 23), which provides a test for regularity (orderliness) of insulin release that can be compared between groups. This estimate is complementary to pulse and deconvolution analysis. ApEn assigns a single nonnegative number to a time series in which larger values correspond to greater apparent process randomness, and smaller values correspond to more instances of recognizable patterns or consistent features in the data. ApEn measures the logarithmic likelihood that runs of patterns that are similar (within a certain distance, r) for n consecutive observations remain similar on next incremental comparisons. To limit nonstationarity, ApEn was applied after first differencing. A more complete definition of ApEn is contained in recent reports (13, 20, 21, 22, 23).

Cross-correlation analyses between glucose and insulin values were carried out with variable lag (24). r values were transformed to z-scores and compared against a null hypothesis of a zero mean with unit SD.

Data analysis

All data are presented as the mean ± SEM. Differences between young and old subjects were determined by two-sided Student’s t test for unpaired samples and by repeated measures ANOVA, as appropriate. P values for the cross-correlation analyses were determined using the two-sided Kolmogorov-Smirnov statistic. Correlation coefficients were calculated by the method of least squares. P < 0.05 was considered significant in all analyses.


    Results
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Subject characteristics are shown in Table 1Go. The older volunteers had a greater body mass index (BMI) and WHR and a lower VO2 max (all P < 0.01).

Rapid pulses

Basal insulin secretion, interpulse interval, secretory burst number, and burst amplitude are shown in Table 2Go. Basal insulin secretion was not different between groups. Although the interpulse interval was longer in the elderly, and the burst number was reduced, the differences did not reach statistical significance. Burst amplitude was lower in the older subjects (P < 0.01). As shown in Fig. 1Go, burst mass (proportionate to amplitude and half-width of the pulse) was lower in the elderly. The ApEn value was greater in the elderly (Fig. 1Go).


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Table 2. Deconvolution analysis of rapid insulin pulses

 


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Figure 1. Mass of rapid insulin secretory bursts and ApEn values in young and old subjects.

 
Mean glucose and insulin concentrations in the young and old are shown in Fig. 2Go. Glucose values were higher in the elderly (P < 0.05, by ANOVA), but there was no significant change over time in either age group. Insulin concentrations were not significantly higher in the aged and did not change over time in either age group.



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Figure 2. Mean plasma insulin and glucose concentrations in the 150-min study.

 
Differences in body composition, rather than normal aging, could explain the differences between age groups. We compared the four young subjects with the highest BMI (23.2 ± 0.9 kg/m2) with the four older subjects with the lowest BMI (23.2 ± 0.8 kg/m2). The differences in insulin secretory burst mass (young, 52 ± 6; old, 30 ± 6 pmol/L), amplitude (young, 7.5 ± 0.7; old, 3.0 ± 0.8 pmol/L·min), and ApEn (young, 1.35 ± 0.12; old, 1.64 ± 0.01) were equivalent to those in the larger group.

There was no correlation between insulin sensitivity measured by the euglycemic clamp and burst mass, amplitude, or entropy. There was also no correlation between WHR or VO2 max and burst mass, amplitude, or entropy.

In the young there was a strongly positive correlation between glucose and insulin values at 0, 2, 4, and 6 min of lag (Fig. 3Go, upper panel). In contrast, in the elderly the correlation was weaker and restricted to only a 2-min lag (Fig. 3Go, lower panel).



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Figure 3. Cross-correlation values between glucose and insulin in the 150-min studies. Data are the median and range for the group.

 
Ultradian pulses

Cluster analysis was used to quantify ultradian peaks in plasma insulin concentrations (Table 3Go). Eight of nine older subjects underwent the ultradian study. Basal (interpeak nadir) plasma insulin concentrations were similar. Peak number was reduced in the aged subjects (P < 0.05). As shown in Fig. 4Go, interpeak interval was longer in the old subjects. Peak area, height, and ApEn values were not significantly different between groups.


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Table 3. Cluster analysis of ultradian plasma insulin concentration peaks

 


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Figure 4. Interpeak interval of ultradian insulin pulses in young and old subjects.

 
Mean glucose and insulin concentrations are shown in Fig. 5Go. Glucose values were higher in the aged subjects (P < 0.05, by ANOVA), but insulin values were similar. There was a significant decline in glucose and insulin values over time in both age groups (P < 0.05, by ANOVA), but there was no difference in the patterns of change over time between the two age groups.



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Figure 5. Mean plasma insulin and glucose concentrations in the 600-min study.

 
To assess the effect of differences in body composition, we compared the four young subjects with the four older subjects with the lowest BMI (young, 23.2 ± 0.9 kg/m2; old, 23.2 ± 0.8 kg/m2). Differences in peak number (young, 7.4 ± 0.7; old, 6.5 ± 0.5) and interpeak interval (young, 85 ± 8 min; old, 95 ± 8 min) were similar to those in the larger group.

There was a significant correlation between insulin sensitivity as measured by the euglycemic clamp and peak number (r = 0.67; P < 0.01) and interpeak interval (r = -0.66; P < 0.01). There was also a significant correlation between VO2 max and peak number (r = 0.53; P < 0.05) and interpeak interval (r = -0.50; P < 0.05). There was no correlation between WHR and peak number or interpeak interval.

Significant cross-correlations were found at all lag times from -60 to 60 min in both age groups.


    Discussion
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 
Although several studies have found that normal elderly individuals have preserved insulin responses to oral or iv glucose challenge (2, 3), recent data suggest that there are definable alterations in insulin release in the course of normal aging (25, 26). In the current study we demonstrate that normal aging is characterized by a reduction in the amplitude of rapid insulin pulses during fasting in combination with a quantifiably increased irregularity of insulin release (as defined by ApEn) and a partial uncoupling of insulin oscillations from glucose oscillation (as defined by cross-correlation analysis). One previous study has evaluated rapid (but not ultradian) insulin pulses in the elderly (27). Matthews et al. studied six subjects over age 60 yr and found that the apparent regularity of pulses was reduced in the aged compared to that in the healthy young subjects. These researchers also reported that interpulse interval increased from 13 min in the young to 20 min in the aged subjects. Using a novel ApEn statistic, we found alterations in the regularity of rapid insulin release in the aged subjects. Unlike Matthews et al., however, we found no difference in pulse interval between young and old subjects. Matthews et al. give no details regarding volunteers’ body composition, fitness, concomitant medications, or diseases; sampled for 60 min; and used a different method to analyze pulse profiles. Such differences may explain the discrepant inferences concerning rapid insulin pulse frequency.

Several studies have found that rapid insulin pulses inhibit hepatic glucose output (HGO), but do not significantly alter peripheral glucose utilization (6, 7, 8). Further evidence that rapid pulses are more important in regulating HGO than peripheral glucose disposal is that we found no correlation between insulin-mediated glucose disposal (as measured by the euglycemic clamp) and the alteration in rapid pulse parameters. In addition, rapid pulses are of considerably higher amplitude in the portal vein than in the peripheral circulation, and their extrahepatic effects on glucose utilization would be small. Given that postprandial suppression of HGO is reduced with age (1), we postulate that the reduced amplitude of rapid insulin pulses observed here in older subjects may contribute to the age-related alterations in the regulation of HGO. Further studies involving replacement of normal insulin pulses in the elderly and measurement of glucose turnover with tracer techniques will be required to test this hypothesis.

The orderliness of the insulin release process may be regulated by the neural network in the pancreas (28, 29, 30, 31), which coordinates secretion by thousands of islets. Our quantification of the orderliness of insulin secretion via an ApEn statistic indicates that the regularity of insulin release is reduced with age. This new finding is consistent with an alteration in neural regulation of pancreatic function in the elderly. We recently reported that pancreatic polypeptide responses to hypoglycemia are impaired in the elderly (32). This response is mediated by the vagus nerve. Thus, a deficient pancreatic polypeptide response to hypoglycemia in healthy elderly subjects is in accord with a postulated alteration of neural regulation of the pancreatic islets. In addition, it has recently been demonstrated that the orderliness of GH, LH, and testosterone secretion and the synchrony between LH and testosterone release as well as that between ACTH and cortisol release are impaired with normal aging (21, 33, 34), suggesting a more widespread alteration in the neural and/or feedback regulation of hormone secretion with age. The decrease in insulin pulse amplitude and mass that we report is consistent with previous studies, which have found similar reductions with aging in the pulsatile release of other hormones under basal conditions, including GH, TSH, and cortisol (33, 35, 36).

Factors that could explain differences between age groups in rapid insulin pulsatility include aerobic capacity and body composition, as our elderly subjects had a lower VO2 max, a higher BMI, and a greater WHR. It is unlikely that the increased fitness of our young subjects explains the difference in rapid insulin pulses we report, because there was no correlation between VO2 max and pulse parameters in these studies. In addition, increased physical fitness is accompanied by reduced spontaneous insulin burst amplitude in young subjects (18). The higher aerobic capacity of our young subjects would minimize differences between young and old. It is unlikely that the abdominal obesity in the elderly explains our results, as there was no correlation between WHR and pulse parameters. Abdominal obesity in younger subjects has been shown not to alter the frequency of rapid insulin pulses, but to decrease their relative and increase their absolute amplitude (37). The abdominal obesity (as measured by WHR) observed in our elderly subjects would serve to increase incremental burst amplitude and again minimize differences between the age groups. In addition, when we compared young and old subjects matched for BMI, the differences in pulse parameters between groups remained. Thus, we believe that the changes we observed in rapid insulin pulses are probably due to aging per se and not solely to differences in body composition or physical fitness between age groups.

Circa-sesquihoral (ultradian) pulses of insulin release are present during fasting and nutrient ingestion (5, 28, 38, 39, 40, 41, 42, 43). In patients with impaired glucose tolerance and noninsulin-dependent diabetes mellitus, the amplitude is reduced, and regularity of the pulses is altered, but the frequency of insulin pulses is maintained (10, 12, 38, 44). In abdominal obesity, the frequency of pulses is unchanged, the absolute amplitude is increased, and the relative amplitude is diminished (5, 37). We found that the amplitude of ultradian insulin pulses was similar in young and old subjects, but their frequency was reduced in the aged. Previous studies have not evaluated ultradian insulin pulses during fasting in healthy elderly individuals. Scheen et al. administered glucose by continuous infusion for 53 h to eight moderately obese elderly subjects and compared the results to those in eight weight-matched young controls (45). They found no differences in insulin pulse frequency or amplitude, but observed a decreased responsiveness of insulin secretion to ultradian oscillations in plasma glucose in the elderly. Their results are consistent with ours with regard to pulse amplitude. The reason for the decrease in pulse frequency is unclear. Potential plausible explanations are that their elderly subjects were younger than ours and relatively more obese, their samples were obtained less frequently (every 20 min vs. every 10 min), and a different methodology was used to analyze insulin pulses. Studies in the dog using both deconvolution and Cluster analysis indicate that sampling frequency is a critical determinant of pulse detection (17). Moreover, glucose was infused by Scheen et al. (45), which in animals increases the frequency of insulin pulses (46).

We believe that our results regarding ultradian pulsatility also are likely due to aging rather than to differences in body composition between the two age groups, as there was no correlation between insulin pulse parameters and WHR. Differences between young and old subjects in pulse parameters were maintained when we matched subjects for BMI. In addition, in middle-aged subjects with abdominal obesity, ultradian pulse frequency was not altered (37). Of interest, there was a significant correlation between VO2 max and ultradian insulin pulse frequency. To our knowledge, no previous studies have evaluated the association of physical fitness with specific ultradian insulin pulse features.

To our knowledge, this is the first clinical study to report alterations in the frequency of ultradian insulin pulses in conditions characterized by abnormal carbohydrate metabolism. If ultradian pulses are important in regulating glucose disposal (9), and normal aging is characterized by resistance to insulin-mediated glucose disposal (2, 3), then alterations in ultradian insulin pulses may be relevant to the insulin resistance of aging. Support for this theory is the correlation we found between pulse frequency and insulin sensitivity measured by the euglycemic clamp. However, to prove this hypothesis, studies will have to be conducted with replacement of normal insulin pulses in the elderly and measurement of glucose turnover by tracer techniques.

We observed a reduction in the frequency of ultradian, but not rapid, insulin pulses in elderly subjects. Rapid pulses are regulated putatively by a local neural activity within the pancreas, whereas insulin/glucose feedback probably plays an important role in regulating ultradian insulin oscillations (28). Accordingly, age-related alterations in insulin dynamics are mechanistically distinct. It is entirely possible that the alterations we report would be different during stimulation of insulin secretion by glucose, amino acids, or a meal. This area should be the subject of further study.

In conclusion, we found that rapid and ultradian insulin pulses are altered with normal aging. The pathophysiological relationship of these disturbances in the dynamics of insulin release in elderly subjects to the known alterations in carbohydrate metabolism in older individuals will ultimately require further investigation.


    Acknowledgments
 
We thank Rosemarie Torressani, Eugene Mar, and Christine Lockhart for their assistance in conducting these studies. We also thank Joanne O’Connor for her invaluable assistance in the preparation of this manuscript. We are especially grateful to Igor Mekjavic, Ph.D., for performing the assessments of VO2 max.


    Footnotes
 
1 This work was supported by a grant from the Medical Research Council of Canada; in part by grants from the British Columbia Health Research Foundation, the University Hospital Foundation, the Pacific Command-Royal Canadian Legion, NIH Research Career Development Award 1K04-HD-00634 (to J.D.V.), and the NSF Center for Biological Timing (to J.D.V.); and by the Allan McGavin Geriatric Endowment at the University of British Columbia and the Jack Bell Geriatric Endowment Fund at Vancouver Hospital and Health Science Center. Back

Received December 24, 1996.

Revised August 6, 1997.

Accepted September 15, 1997.


    References
 Top
 Abstract
 Introduction
 Subjects and Methods
 Results
 Discussion
 References
 

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