Page 1 of 50 Diabetes
1
Title: Iatrogenic Hyperinsulinemia, not Hyperglycemia, Drives Insulin Resistance in Type 1
Diabetes as Revealed by Comparison to GCK-MODY (MODY2).
Running title: Insulin Resistance in Type 1 Diabetes
Justin M. Gregory, M.D.1, T. Jordan Smith, B.S.N. 1, James C. Slaughter, Dr.P.H.2, Holly R.
Mason, M.S.3, Curtis C. Hughey, Ph.D.4, Marta S. Smith, M.S.4, Balamurugan Kandasamy,
Ph.D.5, Siri Atma W. Greeley, M.D., Ph.D.5, Louis H. Philipson, M.D., Ph.D.5, Rochelle N.
Naylor, M.D.5, Lisa R. Letourneau, M.P.H.5 Naji N. Abumrad, M.D.6, Alan D. Cherrington
Ph.D.4, and Daniel J. Moore, M.D., Ph.D.1
1Ian Burr Division of Pediatric Endocrinology and Diabetes, Vanderbilt University School of
Medicine, Nashville, TN
2Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN
3Diet, Body Composition, and Human Metabolism Core, Vanderbilt University, Nashville, TN
4Department of Molecular Physiology and Biophysics, Vanderbilt University, Nashville, TN
5Section of Adult and Pediatric Endocrinology, Diabetes, and Metabolism and the Kovler
Diabetes Center, University of Chicago, Chicago, IL
6Department of Surgery, Vanderbilt University School of Medicine, Nashville, TN
Corresponding author: Justin M. Gregory,
Division of Pediatric Endocrinology
1500 21st Ave., Suite 1514
Nashville, TN 37232
Diabetes Publish Ahead of Print, published online May 15, 2019 Diabetes Page 2 of 50
2
Phone: (615) 322-7427
Fax: (615) 343-5845
Abstract word count: 200/200
Main body word count: 3,999/4,000
Number of references: 50
Number of figures: 5
Number of tables: 0 Page 3 of 50 Diabetes
3
ABSTRACT
Although insulin resistance consistently occurs with type 1 diabetes, its predominant driver is
uncertain. We therefore determined the relative contributions of hyperglycemia and iatrogenic
hyperinsulinemia to insulin resistance using hyperinsulinemic-euglycemic clamps in three
participant groups (n=10/group) with differing insulinemia and glycemia: healthy controls
(euinsulinemia, euglycemia), glucokinase maturity-onset of the young (GCK-MODY;
euinsulinemia, hyperglycemia), and type 1 diabetes (hyperinsulinemia, hyperglycemia matching
GCK-MODY). We assessed the contribution of hyperglycemia by comparing insulin sensitivity
in control and GCK-MODY and the contribution of hyperinsulinemia by comparing GCK-MODY
and type 1 diabetes. HbA1c was normal in controls and similarly elevated for type 1 diabetes and
GCK-MODY. Basal insulin levels in control and GCK-MODY were nearly equal but were 2.5-
fold higher in type 1 diabetes. Low-dose insulin infusion suppressed endogenous glucose
production similarly in all groups and suppressed nonesterified fatty acids similarly between
control and GCK-MODY, but to a lesser extent for type 1 diabetes. High-dose insulin infusion
stimulated glucose disposal similarly in control and GCK-MODY, but was 29% and 22% less
effective in type 1 diabetes, respectively. Multivariable linear regression showed insulinemia—
but not glycemia—was significantly associated with muscle insulin sensitivity. These data suggest
iatrogenic hyperinsulinemia predominates in driving insulin resistance in type 1 diabetes.
Clinicaltrials.gov:NCT02971202. Diabetes Page 4 of 50
4
INTRODUCTION:
Insulin resistance consistently occurs in type 1 diabetes, even among patients who lack traditional insulin resistance risk factors.(1-5) Individuals with type 1 diabetes typically have 35-55% lower insulin sensitivity than matched controls.(1-6) Because insulin resistance is strongly correlated with macrovascular disease in this condition,(6-9) a better understanding of its root cause is needed. Early investigations attributed type 1 diabetes insulin resistance to hyperglycemia(10-15); however, more recent studies show little correlation between hyperglycemia and insulin resistance.(3; 4; 6; 16; 17) Thus, the magnitude of hyperglycemia’s contribution to insulin resistance in type 1 diabetes is uncertain, suggesting other factors may predominate.
Insulin resistance in type 1 diabetes can be alternatively hypothesized to be a homeostatic response to iatrogenic peripheral hyperinsulinemia. In the physiologic state, the liver clears ≈50% of secreted insulin before it reaches the peripheral circulation. As a result, insulin levels at the liver are ≈2-3 fold higher than insulin levels at peripheral tissues. By contrast, in type 1 diabetes the insulin injected into subcutaneous tissue is directly absorbed into the peripheral circulation. Thus, patients with type 1 diabetes have insulin concentrations that are higher in the peripheral circulation and lower in the hepatic portal blood compared to non-diabetic individuals.(18-20) This chronic peripheral circulation hyperinsulinemia could be the predominant contributor to insulin resistance and is an abnormality that could be remedied by hepatopreferential insulin analogs or intraperitoneal insulin delivery.
To distinguish the relative contributions of hyperinsulinemia vs. hyperglycemia to type 1 diabetes insulin resistance, we quantified tissue-specific insulin sensitivity using a two-step Page 5 of 50 Diabetes
5
hyperinsulinemic, euglycemic clamp technique in a cross-section of three groups of age and BMI-
matched participants (n=10/group): 1) non-diabetic controls, 2) subjects with type 1 diabetes, and
3) individuals with glucokinase mutations causing glucokinase–maturity-onset diabetes of the
young, (GCK-MODY, also known as MODY2). The three groups possess key differences and
similarities in glycemia and insulin distribution, allowing us to assess each factor’s contribution to
insulin resistance (figure 1A). Individuals with GCK-MODY retain pancreatic insulin secretion,
but their GCK mutation raises their glycemic “set point,” resulting in mild hyperglycemia (fasting
plasma glucose 104-137 mg/dL, hemoglobin A1c (HbA1c) 5.8-7.6% [40-60 mmol/mol]).(21)
Thus, whereas the GCK-MODY and control groups both have normal and similar portal-to-
peripheral insulin distributions, hyperglycemia in the GCK-MODY group is greater than in the
controls, thereby potentially reducing insulin sensitivity in the GCK-MODY subjects. We also
recruited type 1 diabetes participants with glycemia matching that of the GCK-MODY group.
Because glycemia was matched between groups, the presence of iatrogenic hyperinsulinemia in
subjects with type 1 diabetes is the key difference affecting insulin sensitivity between the two
groups. Our study exploited these key between-group differences to test the hypothesis that
iatrogenic hyperinsulinemia plays a larger role than hyperglycemia in driving insulin resistance. Diabetes Page 6 of 50
6
RESEARCH DESIGN AND METHODS:
Participants
Supplemental table 1 details inclusion and exclusion criteria for study participants. Briefly, volunteers were between ages 13-51, were non-obese, had no recent episodes of severe hypoglycemia nor diabetes comorbidities, were taking no medications affecting insulin sensitivity, had reached Tanner stage 5, and were not pregnant. Type 1 diabetes and GCK-MODY participants were required to have a HbA1c between 5.9-7.5% (41-58 mmol/mol). Participants were recruited from the Vanderbilt Eskind Diabetes Clinic and from the University of Chicago Monogenic
Diabetes Registry (http://monogenicdiabetes.uchicago.edu).(22) The study team recruited type 1 diabetes volunteers to match GCK-MODY volunteers within a HbA1c ± 0.3% (3.3 mmol/mol), age ± 5 years, and BMI ± 1.5 kg/m2. Control volunteers were recruited to match GCK-MODY volunteers within a BMI of ± 1.5 kg/m2 and age ± 5 years.
Screening visit
Potential participants fasted overnight then reported to the Vanderbilt Clinical Research Center
(CRC) for a screening visit to determine whether each individual met inclusion criteria. To quantify potential covariates differentially affecting insulin sensitivity between groups, the study team also measured several metabolic parameters. These factors included resting energy expenditure (REE), body composition, reactive hyperemia-peripheral artery tonometry (RH-PAT) score, VO2max, and fasting blood concentrations of lipids, HbA1c, insulin, and C-peptide.
The research team elicited each participant’s clinical history, conducted a physical exam, and made anthropometric measurements. REE was determined using a metabolic cart system (ParvoMedics Page 7 of 50 Diabetes
7
TrueOne 2400, Sandy, UT) under thermoneutral conditions.(23) REE was calculated using the
Weir equation.(24) RH-PAT score was measured to assess risk of endothelial dysfunction (Endo-
PAT, Itamar Medical Ltd.).(25; 26) Body composition was measured using dual-energy X-ray
absorptiometry (DEXA) (Lunar Prodigy, enCore software version 10.5, GE Medical Systems).
Finally, the team determined VO2max by measuring respiratory gas exchange during treadmill
exercise per the Bruce protocol (MCG Diagnostics Ultima CardiO2 gas exchange analysis system,
St. Paul, MN).(27)
Participants avoided strenuous exercise and consumed a caloric intake equaling 1.2 x REE over
the three days preceding their clamp study. Individuals with type 1 diabetes and three individuals
with GCK-MODY also monitored and recorded blood glucose eight times daily over these three
days.
Hyperinsulinemic, Euglycemic Clamp Studies
Participants returned to the CRC within one month of the screening visit on the evening prior to
their clamp study. At 10 PM, all participants began an overnight fast. Upon beginning the overnight
fast, type 1 diabetes participants received an IV infusion of regular human insulin according to the
protocol of Goldberg et al.(28), modified for use in healthy patients with type 1 diabetes (see
supplemental appendix). The protocol targeted a plasma glucose concentration of 90-120 mg/dL
by the next morning. Patients taking long-acting basal insulin used either insulin glargine or
detemir, which was last given 24 hours prior to beginning the IV insulin infusion. Patients taking
continuous subcutaneous insulin infusions suspended and disconnected their pumps 15-30 minutes
before starting the IV insulin infusion. Participants with GCK-MODY required no overnight Diabetes Page 8 of 50
8 insulin, but CRC staff monitored glucose every two hours overnight. Female participants were studied on day 2-10 of their menstrual cycle.
Each clamp study commenced at 7:30 AM. Experiments consisted of a 90 minute equilibration
2 period for [6,6- H2]-glucose tracer infusion; a 60 minute basal sampling period; then two consecutive, 150 minute experimental periods (figure 1B).
Insulin was infused intravenously at 12 mU/m2/min in the first experimental period (period 1) and at 40 mU/m2/min in the second (period 2). These rates were chosen to partially suppress lipolysis and hepatic glucose production at the end of period 1 and to completely inhibit lipolysis and hepatic glucose production while near-maximally stimulating muscle glucose uptake in period 2. In both experimental periods, somatostatin and glucagon were infused intravenously at 60 ng/kg/min and
0.65 ng/kg/min, rates selected to ensure glucagon remained at basal levels and equal between participants. A glucose tracer solution was prepared by dissolving 2.19 gm (12.0 mmol) of [6,6-
2 H2]-glucose (Cambridge Isotope Laboratories, Tewksbury, MA) in 60 mL of isotonic saline.
2 Participants received a [6,6- H2]-glucose priming dose of 22 µmol/kg over the first 10 minutes of the equilibration period, followed by infusion at 0.22 µmol/kg/min through the end of the basal sampling period. This rate was lowered to 0.11 µmol/kg/min during period 1 and discontinued during period 2. A 0.5 mL aliquot of arterialized blood was drawn and centrifuged every ten minutes during period 1 and every five minutes during period 2 to sample plasma glucose and adjust a 20% dextrose solution infusion to maintain plasma glucose between 95-100 mg/dL. The
2 20% dextrose solution was spiked with glucose tracer by adding 6.9 gm (37.8 mmol) of [6,6- H2]- glucose to 1,500 mL of stock 20% dextrose solution. Page 9 of 50 Diabetes
9
Research staff drew blood to assess metabolic and hormonal parameters three times during each
of three 30 minutes steady-state sampling periods: during the basal sampling period and during the
last 30 minutes of both 150-minute experimental periods.
Analytical Procedures
The research team drew each arterialized venous blood sample from the upper extremity and
immediately added the blood into tubes containing potassium EDTA. Blood concentrations of
lactate, alanine, and glycerol were determined using a fluorometric method of Lloyd et al.(29)
modified for the Packard Multiprobe II (Meriden, CT).(30) Plasma NEFA concentrations were
quantified using a colorimetry kit (Wako Life Sciences, Mountain View, CA) modified for the
Packard Multiprobe II. Plasma catecholamine concentrations were measured using high-
performance liquid chromatography.(31) Plasma concentrations of insulin, glucagon, C-peptide,
and cortisol were determined using radioimmunoassay (MilliporeSigma, Burlington, MA).(30)
Plasma glucose concentrations were measured by the glucose oxidase method (YSI 2300 Stat Plus,
2 Yellow Springs, OH). To obtain a measure of [6,6- H2]-glucose enrichment, plasma samples were
derivatized to obtain a di-O-isopropylidene propionate derivative of glucose for gas
chromatography/mass spectrometry analysis, as previously described.(32) A custom Microsoft
Excel macro was then utilized to correct for the theoretical natural abundance of isotopes to
determine the plasma fractional enrichment of M+2 glucose. Diabetes Page 10 of 50
10
Calculations
2 Plasma enrichment of [6,6- H2]-glucose was steady during each sampling period (supplemental
figure 1) and glucose turnover was calculated using the steady-state assumption for glucose tracer
and tracee. Under these conditions,
∗ 푅푎 푅푎 = 푎 and 푅푎 = 푅푑
* where Ra is the glucose appearance rate in the plasma, Rd is the glucose utilization rate, Ra is the
2 infusion rate of [6,6- H2]-glucose tracer, and a is the plasma enrichment of tracer (i.e. the [6,6-
2 H2]-glucose isotopomer fraction of total plasma glucose). Endogenous glucose production (EGP) was calculated by subtracting the unlabeled glucose infusion rate (GIR) and the small but finite
2 [6,6- H2]-glucose tracer rate from Ra. Glucose turnover was normalized for fat-free mass (FFM) to account for gender related differences in fat mass.
To quantify insulin’s ability to suppress whole-body EGP (ΔEGP), i.e., the net suppressive effect of insulin directly at liver and indirectly in the periphery by restraining mobilization of gluconeogenic substrates and NEFA, we subtracted each participant’s mean EGP at the end of period 1 (when insulin partially suppressed EGP) from mean EGP during the basal period.
Similarly, to assess insulin sensitivity at fat tissue, we subtracted the mean levels for NEFA and glycerol at period 1 from mean NEFA and glycerol levels at baseline. Insulin-dependent Rd is largely (≈90%) reflective of glucose uptake by skeletal muscle during hyperinsulinemia (i.e. the net effect of insulin to facilitate muscle glucose disposal via microvascular, interstitial, intracellular, and neural mechanisms).(33) Thus, we subtracted mean Rd at the end of period 1 from mean Rd at the end of period 2 to quantify each participant’s muscle insulin sensitivity. Page 11 of 50 Diabetes
11
Statistics
The sample size in this cross-sectional study design (10 per group) was calculated to detect a 40%
difference in mean Rd between GCK-MODY and type 1 diabetes subjects during period 2 with a
two-sided α-level of 5% and 80% statistical power. The Rd variance and Rd for well-controlled
type 1 diabetes individuals utilized in sample size calculations were taken from Bergmann et al.
where a 55% difference in Rd was seen between type 1 diabetes and control groups.(3)
The research team collected and managed study data using REDCap electronic data capture tools
hosted at Vanderbilt University.(34) Statistical analyses were conducted using SPSS 25 (IBM
Corp. Armonk, NY). Statistically significant differences in continuous data were assessed using a
independent-samples Student t-test. A two-tailed p-value of less than 0.05 was considered
significant. HbA1c was used to quantify glycemia and mean fasting basal plasma insulin
concentration before the clamp was used to quantify insulinemia. Two separate bivariate linear
regression analyses quantified the effect of each of these two independent variables on the
dependent variable for muscle insulin sensitivity, mean Rd at the end of period 2. Then we used
standard multivariable linear regression analysis to determine each independent variable’s effect
on muscle insulin sensitivity adjusted for one another. Data are summarized as means ± SD unless
otherwise indicated.
Study Approval
Prior to participation, adult volunteers provided written, informed consent and adolescent
volunteers provided written, informed assent with both parents providing parental consent. The
Institutional Review Board of Vanderbilt University approved the study protocol. The U.S. Food Diabetes Page 12 of 50
12 and Drug Administration approved the use of somatostatin (IND #132209). ClinicalTrials.gov registered the study under NCT02971202.
Data and Resource Availability
The datasets generated during and/or analyzed during the current study are available from the corresponding author upon reasonable request. No applicable resources were generated or analyzed during the current study. Page 13 of 50 Diabetes
13
RESULTS:
Participant Characteristics
Potential confounders of insulin resistance between cohorts (n=10 per cohort) measured at
screening were well-matched between cohorts (figure 2, supplemental figure 2, supplemental table
2). HbA1c was 4.8 ± 0.4% (29 ± 4.4 mmol/mol), 6.2 ± 0.3% (44 ± 3.3 mmol/mol) and 6.6 ± 0.5%
(49 ± 5.5 mmol/mol) in control, GCK-MODY, and type 1 diabetes cohorts, respectively (figure
2A). Study participants included seven females in the control group, nine females in the GCK-
MODY group, and six females in the type 1 diabetes group. Subjects with type 1 diabetes had a
mean disease duration of 9.4 ± 5.1 years. Supplemental table 3 lists the GCK mutations affecting
each GCK-MODY participant.
Hyperinsulinemic, Euglycemic Clamp Studies
Glycemia Prior to Clamp Studies
Supplemental table 4 characterizes the insulin regimen of type 1 diabetes participants and
supplemental figure 3 summarizes their self-monitored blood glucose (SMBG) over the 3 days
prior to the clamp study. Sixty-eight percent of glucose readings were between 70-180 mg/dL.
Among the ten type 1 diabetes participants, six experienced a total of 18 episodes of a blood
glucose less than 70 mg/dL and four experienced none over the 3 days prior to the clamp study.
Two episodes of a blood glucose less than 50 mg/dL occurred. Supplemental figure 4 depicts
hourly plasma glucose concentrations and insulin infusion rates for type 1 diabetes participants
overnight before the clamp study. Diabetes Page 14 of 50
14
Hormone and Glucose Concentrations
Basal plasma insulin concentrations (figure 3A-B) were virtually identical between the control and
GCK-MODY cohorts (8.7 ± 2.9 vs. 8.5 ± 4.6 µU/mL) and 2½-fold higher in the type 1 diabetes cohort (21.2 ± 10.5 µU/mL). Plasma insulin concentrations in the control, GCK-MODY, and type
1 diabetes groups rose to 21.1 ± 4.5, 20.5 ± 4.3, and 28.1 ± 7.4 µU/mL, respectively, in period 1 and to 80.5 ± 17.3, 74.2 ± 11.9, and 79.0 ± 18.0 µU/mL in period 2. Basal C-peptide levels in the control and GCK-MODY groups suppressed to the lower limit of detection during the clamp
(owing to the somatostatin infusion) and for the type 1 diabetes group remained at the lower limit of detection throughout the study (figure 3C). Plasma glucagon concentrations (figure 3D) remained at basal levels in all three groups throughout study (as a consequence of the somatostatin and glucagon infusions).
Basal glucose concentrations immediately prior to the clamp study for the control, GCK-MODY, and type 1 diabetes cohorts were 89.7 ± 7.7, 119.7 ± 8.0, and 112.4 ± 12.4 mg/dL, respectively
(figure 3E). Each subject required IV glucose to maintain plasma glucose between 95-100 mg/dL during the clamp, except one GCK-MODY participant during period 1. Plasma concentrations of cortisol, epinephrine, and norepinephrine remained at basal levels throughout the study in all groups (figure 3F-H).
Metabolite Response
Blood concentrations of lactate rose minimally from basal to the end of period 1, then rose in all three groups in period 2 (figure 4A). Blood alanine levels changed negligibly in each group throughout the study (figure 4B). For the control and GCK-MODY cohorts, the lower insulin Page 15 of 50 Diabetes
15
infusion used in period 1 suppressed both non-esterified fatty acid (NEFA) and glycerol levels
dramatically, whereas the type 1 diabetes group saw only a modest decrease in these levels (figure
4C-F). When the insulin infusion rate increased during period 2, NEFA and glycerol in all groups
became fully suppressed.
Glucose turnover
Basal EGP was modestly higher for GCK-MODY compared with the other two groups (figure
5A). The lower insulin infusion used in period 1 suppressed EGP similarly for control, GCK-
MODY, and type 1 diabetes groups, decreasing from the basal period by 1.7, 2.1, and 1.9 mg/kg
FFM/min; 95% CIs [1.4, 2.0], [1.7, 2.4], and [1.5, 2.2], respectively (figure 5A-B). All participants
had near-complete suppression of EGP during the higher insulin infusion of period 2. Fractional
2 plasma enrichment of [6,6- H2]-glucose is shown in supplemental figure 1.
Rd for all groups was similar basally and increased only slightly during period 1 (figure 5C). The
increase in Rd during period 2 (figure 5D) was similar in control and GCK-MODY groups (12.1,
95% CI [10.3, 14.0] vs. 11.0, 95% CI [9.1, 13.0] mg/kg FFM/min, respectively; difference = 1.1,
95% CI [-1.5, 3.6], p=0.39). Rd for the type 1 diabetes group was stimulated to a lesser extent (8.5
mg/kg FFM/min 95% CI [6.1, 10.9]; difference vs. GCK-MODY = 2.5 mg/kg FFM/min, 95% CI
[-0.4, 5.4], p=0.086; difference vs. control = 3.6 mg/kg FFM/min, 95% CI [0.7, 6.4], p=0.018).
The coefficient of variation for SMBG among the ten type 1 diabetes and three GCK-MODY
participants who submitted a glucose log ranged from 0.17 to 0.51, yet had virtually no association
with period 2 Rd (supplemental figure 5A). Likewise, the coefficient of variation of blood glucose Diabetes Page 16 of 50
16 among GCK-MODY and type 1 diabetes participants overnight before the clamp had no appreciable association with period 2 Rd (supplemental figure 5B).
Bivariate analyses of the effect of glycemia (HbA1c) or insulinemia (mean basal insulin
2 concentration) on Rd revealed coefficients of determination (R ) of 0.093 and 0.356, respectively
(figure 5E-F). When the effect of both glycemia and insulinemia on Rd was examined using multivariable linear regression analysis, R2 was 0.356 (figure 5G). To assess colinearity between insulinemia and a series of potential factors that would cause both hyperinsulinemia and insulin resistance, we considered a series of adjusted multivariable linear models, but none appreciably altered the relationship between insulinemia and Rd (supplemental table 5). Page 17 of 50 Diabetes
17
DISCUSSION:
These results support the hypothesis that iatrogenic peripheral hyperinsulinemia contributes
substantially more to local-tissue insulin resistance than hyperglycemia. To our knowledge, this
study is the first to simultaneously compare the contribution of both factors to insulin resistance in
the type 1 diabetes and GCK-MODY populations. Insulin resistance has been closely linked with
macrovascular disease risk in type 1 diabetes.(6; 7; 35) Thus, these data imply therapeutic
approaches to modify hyperinsulinemia-mediated insulin resistance could mitigate macrovascular
disease in type 1 diabetes.
Our data suggest chronic exposure of insulin-sensitive tissues to iatrogenic hyperinsulinemia leads
to insulin resistance in those tissues. Further, clinical chronic hyperglycemia had little if any
association with insulin resistance at any tissue. In assessing muscle tissue insulin sensitivity
between groups, Rd in subjects with type 1 diabetes during period 2 was 22% lower than GCK-
MODY and 29% lower than controls. Linear regression analysis showed insulinemia alone
explained 36% of the variance in Rd, a factor that was virtually unchanged with the addition of
glycemia in multivariable linear regression analysis. Hyperglycemia also seemed to have little
effect on insulin sensitivity in fat tissue, as evidenced by the control and GCK-MODY groups
having nearly identical and complete insulin-mediated suppression of NEFA and glycerol during
period 1. By contrast, the type 1 diabetes group had only partial suppression of NEFA and glycerol
during period 1, suggesting hyperinsulinemia was the key element driving insulin resistance in fat
tissue. Diabetes Page 18 of 50
18
Although insulin sensitivity at muscle and fat were lower in the type 1 diabetes group compared to the other two groups, insulin-mediated suppression of whole-body EGP was nearly the same between each cohort regardless of glycemic and insulinemic status. One plausible explanation for this observation is that none of the groups experience chronic hepatic sinusoidal hyperinsulinemia.
Based on previous studies,(20; 36) when insulin enters the circulation via the portal vein, the hepatic sinusoidal insulin concentration is on average 2.7-fold higher than the arterial insulin concentration. On the other hand, when insulin enters the circulation via peripheral insulin delivery hepatic sinusoidal insulin concentrations are on average 16% lower than arterial insulin levels.
Thus, for the mean basal insulin concentrations of 8.7, 8.5, and 21.1 µU/mL seen in the control,
GCK-MODY, and type 1 diabetes groups, the corresponding estimated hepatic sinusoidal insulin concentrations are 23.5, 23.0, and 17.7 µU/mL.
These data clarify uncertainty regarding the degree to which hyperglycemia drives whole-body insulin resistance in type 1 diabetes and GCK-MODY. Multiple investigations of type 1 diabetes have shown an inverse relationship between hyperglycemia and insulin sensitivity when hyperglycemia was reduced,(37; 38) induced,(11; 12) or partially resolved during the
“Honeymoon phase.”(10) Likewise, a study investigating insulin sensitivity in GCK-MODY also attributed decreased insulin sensitivity to hyperglycemia.(39) By contrast, the primacy of hyperglycemia in driving type 1 diabetes insulin resistance was most strongly challenged by a series of studies that consistently showed little to no correlation between glycemia and whole-body insulin resistance.(3; 4; 6; 17) Interestingly, in some of the studies linking improved glycemia and improved insulin sensitivity, a reduction in hyperglycemia was also accompanied by reduced insulin doses(10; 37) or levels(11). Page 19 of 50 Diabetes
19
Whether iatrogenic hyperinsulinemia is a primary or secondary cause of insulin resistance among
patients with type 1 diabetes who are otherwise healthy has been a matter of significant debate.
Does hyperinsulinemia per se initiate and sustain insulin resistance or does another factor cause
insulin resistance, which then leads to higher insulin levels?(40) Although an observational study
with a limited sample size cannot completely exclude the possibility that an unmeasured, unknown
confounder caused insulin resistance that necessitated hyperinsulinemia, our analysis supports
iatrogenic hyperinsulinemia as a primary driver. First, numerous potential confounding
covariables were quantified and well balanced between cohorts. We considered the possibility that
differences in glycemic variability between type 1 diabetes participants and the other two groups
could influence insulin sensitivity such as through divergent hormonal responses. We did not find
any changes in the counter-regulatory hormones we measured during the study. In addition,
bivariate analyses examining subjects with recorded pre-study blood glucose monitoring revealed
there was essentially no relationship between glycemic variability and Rd (supplemental figure 5).
Although we were not able to monitor a long duration of pre-study glucose values, the variability
of glycemia within our well-controlled T1D subjects likely reflects their overall pattern of control
and did not account for changes in Rd. Second, when several multivariable linear regression models
were tested, none of the potential confounders diminished the effect of insulinemia on Rd. These
potential confounders included BMI, REE, age, body composition parameters, lipid levels, and
baseline NEFA concentrations. Because the distribution of age was different between control and
the other groups due to restrictions on testing healthy adolescent controls, we accounted for the
known effect of age (41) on insulin sensitivity using multivariable linear regression. Age did not
alter the relationship between insulinemia and Rd and the association between age and Rd did not Diabetes Page 20 of 50
20 reach statistical significance. Our analysis aligns with other studies in which investigators tested hyperinsulinemia as a primary driver. Transfecting mice with extra copies of the human insulin gene led to euglycemic hyperinsulinemia, which was associated with diminished insulin sensitivity during oral glucose and intravenous insulin tolerance tests.(40; 42) A 50% increase in basal insulinemia induced by 28 days of intraportal insulin infusion in the dog led to only a slight fall in fasting glucose but a 39% decrease in muscle insulin sensitivity.(43) In two separate studies, investigators infused intravenous insulin for 40(44) and 72(45) hours to raise basal insulin concentrations in healthy volunteers to levels typically seen in fasting, euglycemic type 1 diabetes patients. The mild hyperinsulinemia led to 16% and 20% reductions in muscle insulin sensitivity.
In another study, euglycemic type 1 diabetes patients who were recipients of a kidney-pancreas transplant with anastomosis into the systemic circulation had 2-fold higher basal insulin concentrations and 24% lower muscle insulin sensitivity than recipients with anastomosis into the portal circulation.(46) Thus, in addition to addressing the primary question of whether iatrogenic hyperinsulinemia or hyperglycemia has a greater association with insulin resistance, the unique study design addresses this long-debated question for patients with type 1 diabetes. By matching numerous potential confounders between groups and by showing the potential confounders did not diminish the linkage between hyperinsulinemia and Rd in multivariable linear regression modeling, this approach strengthens the case that iatrogenic hyperinsulinemia per se principally drives insulin resistance rather than an unmeasured or unknown covariable.
These findings underscore the importance of iatrogenic hyperinsulinemia as a potentially modifiable contributor to insulin resistance, a factor known to promote macrovascular disease in this population. (4; 7; 35; 47) Although hyperglycemia reduction remains profoundly important to Page 21 of 50 Diabetes
21
reduce macrovascular disease risk,(48) patients with a HbA1c ≤ 6.9% (52 mmol/mol) still have a
nearly three-fold risk for macrovascular disease death compared with matched controls.(49) By
contrast, in the largest study of vascular disease risk in adults with GCK-MODY (n=99), the
median HbA1c was 6.9% (52 mmol/mol) yet the prevalence of macrovascular complications was
no different from controls.(50) We suggest that the differences in macrovascular disease between
the type 1 diabetes population with HbA1c ≤ 6.9% (52 mmol/mol) and the GCK-MODY
population may be related to the differences in insulin sensitivities as identified in the present
study.
In conclusion, our results indicate iatrogenic hyperinsulinemia plays a much larger role in driving
insulin resistance at muscle and fat than hyperglycemia in type 1 diabetes. We propose that
therapies designed to restore the physiologic distribution of insulin between the liver and periphery
(e.g. hepatopreferential insulin analogs and intraperitoneal insulin delivery) will mitigate insulin
resistance significantly and improve long-term outcomes across the lifespan in type 1 diabetes. Diabetes Page 22 of 50
22
ACKNOWLEDGEMENTS:
The authors thank Kevin Niswender, M.D., Ph.D., for serving as this study’s data and safety monitor and are grateful to Lana Howard, B.S.N., and the staff of the Vanderbilt Clinical Research
Center and the Vanderbilt Diet, Body Composition, and Human Metabolism Core for their assistance in conducting the studies.
Author Contributions
J.M.G. designed the study, conducted experiments, gathered and analyzed data, and wrote the manuscript. T.J.S. conducted experiments, gathered data, and analyzed data. J.C.S. assisted with the study design and statistical analysis. H.R.M. conducted experiments. C.C.H. conducted isotopic tracer analyses, M.S.S performed hormonal and metabolite assays. B.K., S.A.W.G.,
L.H.P., R.N.N., and L.R.L. facilitated participant recruitment and conducted genotyping. N.N.A.,
A.D.C., and D.J.M. helped design the study, analyze the data, and write the manuscript. All authors critically reviewed the manuscript.
Guarantor Statement
J.M.G. 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.
Conflict of Interest Statement
J.M.G. reports consulting fees from InClinica. A.D.C. reports grants, personal fees, and other from
Metavention, Zafgen, and Abvance; grants and personal fees from Boston Scientific, Novo
Nordisk, vTv Therapeutics, Merck, Eli Lilly, and Galvani Bioelectronics; personal fees from Page 23 of 50 Diabetes
23
California Institute for Biomedical Research (Calibr) and MedImmune; personal fees and other
from Fractyl, Thetis Pharmaceuticals, and Sensulin Labs. Additionally, A.D.C. has patented a
method of treating overweight subjects that is issued to Zafgen, a method for treating diabetes
issued to Abvance, and a method of controlling postprandial glucose levels in diabetes issued to
Biocon. No other potential conflicts of interest relevant to this article were reported.
Funding
J.M.G. was supported by the Eunice Kennedy Shriver National Institute of Child Health & Human
Development of the National Institutes of Health under Award Number K12HD087023. DJM was
supported by a JDRF Career Development Award. The study was supported by a pilot and
feasibility grant from the Vanderbilt Diabetes Research and Training Center (P30 DK020593) and
by CTSA award No. UL1 TR002243 from the National Center for Advancing Translational
Sciences. The Vanderbilt Hormone Assay and Analytical Services Core, which is supported by
NIH grants DK059637 and DK020593, processed hormone assays. The Vanderbilt Mouse
Metabolic Phenotyping Core (DK059637) processed isotopic glucose tracer samples. The
University of Chicago Monogenic Diabetes Registry is supported by NIH grants R01 DK104942
and P30 DK020595. The content is solely the responsibility of the authors and does not necessarily
represent the official views of the National Center for Advancing Translational Sciences or the
National Institutes of Health.
Prior Presentations
A portion of these data was presented as an oral presentation at the European Association for the
Study of Diabetes Annual Meeting Oct. 1-5, 2018. Diabetes Page 24 of 50
24 Page 25 of 50 Diabetes
25
REFERENCES:
1. Yki-Jarvinen H, Taskinen MR, Kiviluoto T, Hilden H, Helve E, Koivisto VA, Nikkila EA: Site of insulin resistance in type 1 diabetes: insulin-mediated glucose disposal in vivo in relation to insulin binding and action in adipocytes in vitro. The Journal of clinical endocrinology and metabolism 1984;59:1183-1192 2. Yki-Jarvinen H, Sahlin K, Ren JM, Koivisto VA: Localization of rate-limiting defect for glucose disposal in skeletal muscle of insulin-resistant type I diabetic patients. Diabetes 1990;39:157-167 3. Bergman BC, Howard D, Schauer IE, Maahs DM, Snell-Bergeon JK, Eckel RH, Perreault L, Rewers M: Features of hepatic and skeletal muscle insulin resistance unique to type 1 diabetes. The Journal of clinical endocrinology and metabolism 2012;97:1663-1672 4. Nadeau KJ, Regensteiner JG, Bauer TA, Brown MS, Dorosz JL, Hull A, Zeitler P, Draznin B, Reusch JE: Insulin resistance in adolescents with type 1 diabetes and its relationship to cardiovascular function. The Journal of clinical endocrinology and metabolism 2010;95:513-521 5. Donga E, van Dijk M, Hoogma RP, Corssmit EP, Romijn JA: Insulin resistance in multiple tissues in patients with type 1 diabetes mellitus on long-term continuous subcutaneous insulin infusion therapy. Diabetes/metabolism research and reviews 2013;29:33-38 6. Schauer IE, Snell-Bergeon JK, Bergman BC, Maahs DM, Kretowski A, Eckel RH, Rewers M: Insulin resistance, defective insulin-mediated fatty acid suppression, and coronary artery calcification in subjects with and without type 1 diabetes: The CACTI study. Diabetes 2011;60:306-314 7. Orchard TJ, Olson JC, Erbey JR, Williams K, Forrest KY, Smithline Kinder L, Ellis D, Becker DJ: Insulin resistance-related factors, but not glycemia, predict coronary artery disease in type 1 diabetes: 10-year follow-up data from the Pittsburgh Epidemiology of Diabetes Complications Study. Diabetes Care 2003;26:1374-1379 8. Kilpatrick ES, Rigby AS, Atkin SL: Insulin resistance, the metabolic syndrome, and complication risk in type 1 diabetes: "double diabetes" in the Diabetes Control and Complications Trial. Diabetes care 2007;30:707-712 9. Orchard TJ, Costacou T, Kretowski A, Nesto RW: Type 1 diabetes and coronary artery disease. Diabetes Care 2006;29:2528-2538 10. Yki-Jarvinen H, Koivisto VA: Natural course of insulin resistance in type I diabetes. The New England journal of medicine 1986;315:224-230 11. Yki-Jarvinen H, Helve E, Koivisto VA: Hyperglycemia decreases glucose uptake in type I diabetes. Diabetes 1987;36:892-896 12. Vuorinen-Markkola H, Koivisto VA, Yki-Jarvinen H: Mechanisms of hyperglycemia-induced insulin resistance in whole body and skeletal muscle of type I diabetic patients. Diabetes 1992;41:571-580 13. Mathoo JM, Shi ZQ, Klip A, Vranic M: Opposite effects of acute hypoglycemia and acute hyperglycemia on glucose transport and glucose transporters in perfused rat skeletal muscle. Diabetes 1999;48:1281-1288 14. Revers RR, Kolterman OG, Scarlett JA, Gray RS, Olefsky JM: Lack of in vivo insulin resistance in controlled insulin-dependent, type I, diabetic patients. The Journal of clinical endocrinology and metabolism 1984;58:353-358 15. Baron AD, Zhu JS, Zhu JH, Weldon H, Maianu L, Garvey WT: Glucosamine induces insulin resistance in vivo by affecting GLUT 4 translocation in skeletal muscle. Implications for glucose toxicity. The Journal of clinical investigation 1995;96:2792-2801 Diabetes Page 26 of 50
26
16. Szadkowska A, Pietrzak I, Mianowska B, Bodalska-Lipinska J, Keenan HA, Toporowska- Kowalska E, Mlynarski W, Bodalski J: Insulin sensitivity in Type 1 diabetic children and adolescents. Diabetic medicine : a journal of the British Diabetic Association 2008;25:282-288 17. Cree-Green M, Stuppy JJ, Thurston J, Bergman BC, Coe GV, Baumgartner AD, Bacon S, Scherzinger A, Pyle L, Nadeau KJ: Youth With Type 1 Diabetes Have Adipose, Hepatic, and Peripheral Insulin Resistance. The Journal of clinical endocrinology and metabolism 2018;103:3647-3657 18. Horwitz DL, Starr JI, Mako ME, Blackard WG, Rubenstein AH: Proinsulin, insulin, and C- peptide concentrations in human portal and peripheral blood. The Journal of clinical investigation 1975;55:1278-1283 19. Blackard WG, Nelson NC: Portal and peripheral vein immunoreactive insulin concentrations before and after glucose infusion. Diabetes 1970;19:302-306 20. Gregory JM, Kraft G, Scott MF, Neal DW, Farmer B, Smith MS, Hastings JR, Allen EJ, Donahue EP, Rivera N, Winnick JJ, Edgerton DS, Nishimura E, Fledelius C, Brand CL, Cherrington AD: Insulin Delivery into the Peripheral Circulation: a Key Contributor to Hypoglycemia in Type 1 Diabetes. Diabetes 2015; 21. Chakera AJ, Steele AM, Gloyn AL, Shepherd MH, Shields B, Ellard S, Hattersley AT: Recognition and Management of Individuals With Hyperglycemia Because of a Heterozygous Glucokinase Mutation. Diabetes Care 2015;38:1383-1392 22. Greeley SA, Naylor RN, Cook LS, Tucker SE, Lipton RB, Philipson LH: Creation of the Web- based University of Chicago Monogenic Diabetes Registry: using technology to facilitate longitudinal study of rare subtypes of diabetes. J Diabetes Sci Technol 2011;5:879-886 23. Compher C, Frankenfield D, Keim N, Roth-Yousey L, Evidence Analysis Working G: Best practice methods to apply to measurement of resting metabolic rate in adults: a systematic review. J Am Diet Assoc 2006;106:881-903 24. Weir JB: New methods for calculating metabolic rate with special reference to protein metabolism. J Physiol 1949;109:1-9 25. Haller MJ, Stein J, Shuster J, Theriaque D, Silverstein J, Schatz DA, Earing MG, Lerman A, Mahmud FH: Peripheral artery tonometry demonstrates altered endothelial function in children with type 1 diabetes. Pediatr Diabetes 2007;8:193-198 26. Kuvin JT, Patel AR, Sliney KA, Pandian NG, Sheffy J, Schnall RP, Karas RH, Udelson JE: Assessment of peripheral vascular endothelial function with finger arterial pulse wave amplitude. Am Heart J 2003;146:168-174 27. Fletcher GF, Ades PA, Kligfield P, Arena R, Balady GJ, Bittner VA, Coke LA, Fleg JL, Forman DE, Gerber TC, Gulati M, Madan K, Rhodes J, Thompson PD, Williams MA, American Heart Association Exercise CR, Prevention Committee of the Council on Clinical Cardiology CoNPA, Metabolism CoC, Stroke N, Council on E, Prevention: Exercise standards for testing and training: a scientific statement from the American Heart Association. Circulation 2013;128:873- 934 28. Goldberg PA, Roussel MG, Inzucchi SE: Clinical Results of an Updated Insulin Infusion Protocol in Critically Ill Patients. Diabetes Spectrum 2005;18:188-191 29. Lloyd B, Burrin J, Smythe P, Alberti KG: Enzymic fluorometric continuous-flow assays for blood glucose, lactate, pyruvate, alanine, glycerol, and 3-hydroxybutyrate. Clin Chem 1978;24:1724-1729 Page 27 of 50 Diabetes
27
30. Edgerton DS, Cardin S, Emshwiller M, Neal D, Chandramouli V, Schumann WC, Landau BR, Rossetti L, Cherrington AD: Small Increases in Insulin Inhibit Hepatic Glucose Production Solely Caused by an Effect on Glycogen Metabolism. Diabetes 2001;50:1872-1882 31. Moghimzadeh E, Nobin A, Rosengren E: Fluorescence microscopical and chemical characterization of the adrenergic innervation in mammalian liver tissue. Cell Tissue Res 1983;230:605-613 32. Hughey CC, Trefts E, Bracy DP, James FD, Donahue EP, Wasserman DH: Glycine N- methyltransferase deletion in mice diverts carbon flux from gluconeogenesis to pathways that utilize excess methionine cycle intermediates. J Biol Chem 2018;293:11944-11954 33. DeFronzo RA, Gunnarsson R, Bjorkman O, Olsson M, Wahren J: Effects of insulin on peripheral and splanchnic glucose metabolism in noninsulin-dependent (type II) diabetes mellitus. The Journal of clinical investigation 1985;76:149-155 34. Harris PA, Taylor R, Thielke R, Payne J, Gonzalez N, Conde JG: Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform 2009;42:377-381 35. Rathsman B, Rosfors S, Sjoholm A, Nystrom T: Early signs of atherosclerosis are associated with insulin resistance in non-obese adolescent and young adults with type 1 diabetes. Cardiovasc Diabetol 2012;11:145 36. Edgerton DS, Lautz M, Scott M, Everett CA, Stettler KM, Neal DW, Chu CA, Cherrington AD: Insulin's direct effects on the liver dominate the control of hepatic glucose production. The Journal of clinical investigation 2006;116:521-527 37. Yki-Jarvinen H, Koivisto VA: Continuous subcutaneous insulin infusion therapy decreases insulin resistance in type 1 diabetes. The Journal of clinical endocrinology and metabolism 1984;58:659-666 38. Simonson DC, Tamborlane WV, Sherwin RS, Smith JD, DeFronzo RA: Improved insulin sensitivity in patients with type I diabetes mellitus after CSII. Diabetes 1985;34 Suppl 3:80-86 39. Clement K, Pueyo ME, Vaxillaire M, Rakotoambinina B, Thuillier F, Passa P, Froguel P, Robert JJ, Velho G: Assessment of insulin sensitivity in glucokinase-deficient subjects. Diabetologia 1996;39:82-90 40. Shanik MH, Xu Y, Skrha J, Dankner R, Zick Y, Roth J: Insulin resistance and hyperinsulinemia: is hyperinsulinemia the cart or the horse? Diabetes Care 2008;31 Suppl 2:S262- 268 41. Ehrhardt N, Cui J, Dagdeviren S, Saengnipanthkul S, Goodridge HS, Kim JK, Lantier L, Guo X, Chen YI, Raffel LJ, Buchanan TA, Hsueh WA, Rotter JI, Goodarzi MO, Peterfy M: Adiposity- Independent Effects of Aging on Insulin Sensitivity and Clearance in Mice and Humans. Obesity (Silver Spring) 2019;27:434-443 42. Marban SL, Deloia JA, Gearhart JD: Hyperinsulinemia in transgenic mice carrying multiple copies of the human insulin gene. Developmental Genetics 1989;10:356-364 43. McGuinness OP, Friedman A, Cherrington AD: Intraportal hyperinsulinemia decreases insulin-stimulated glucose uptake in the dog. Metabolism 1990;39:127-132 44. Rizza RA, Mandarino LJ, Genest J, Baker BA, Gerich JE: Production of insulin resistance by hyperinsulinaemia in man. Diabetologia 1985;28:70-75 45. Del Prato S, Leonetti F, Simonson DC, Sheehan P, Matsuda M, DeFronzo RA: Effect of sustained physiologic hyperinsulinaemia and hyperglycaemia on insulin secretion and insulin sensitivity in man. Diabetologia 1994;37:1025-1035 Diabetes Page 28 of 50
28
46. Carpentier A, Patterson BW, Uffelman KD, Giacca A, Vranic M, Cattral MS, Lewis GF: The effect of systemic versus portal insulin delivery in pancreas transplantation on insulin action and VLDL metabolism. Diabetes 2001;50:1402-1413 47. Rodrigues TC, Biavatti K, Almeida FK, Gross JL: Coronary artery calcification is associated with insulin resistance index in patients with type 1 diabetes. Brazilian Journal of Medical and Biological Research 2010;43:1084-1087 48. Diabetes C, Complications Trial /Epidemiology of Diabetes I, Complications Study Research G: Intensive Diabetes Treatment and Cardiovascular Outcomes in Type 1 Diabetes: The DCCT/EDIC Study 30-Year Follow-up. Diabetes Care 2016;39:686-693 49. Lind M, Svensson AM, Kosiborod M, Gudbjornsdottir S, Pivodic A, Wedel H, Dahlqvist S, Clements M, Rosengren A: Glycemic control and excess mortality in type 1 diabetes. The New England journal of medicine 2014;371:1972-1982 50. Steele AM, Shields BM, Wensley KJ, Colclough K, Ellard S, Hattersley AT: Prevalence of vascular complications among patients with glucokinase mutations and prolonged, mild hyperglycemia. JAMA 2014;311:279-286 Page 29 of 50 Diabetes
29
TABLES:
None (additional tables are in supplemental material) Diabetes Page 30 of 50
30
FIGURE LEGENDS
Figure 1
A) Key differences and similarities in chronic glycemia and insulin distribution affecting insulin sensitivity between participant group. GCK-MODY = glucokinase-maturity onset diabetes of the young. T1DM = type 1 diabetes. Pe. hyperinsulinemia = peripheral hyperinsulinemia. B)
Hyperinsulinemic, euglycemic clamp protocol. Insulin infusion rates were intended to cause a 3 and 10-fold rise in plasma insulin levels in control subjects. In a 70 kg, 1.73 m2 individual, 12 mU/m2/min would approximately equal 0.3 mU/kg/min and 40 mU/m2/min would approximately equal 1.0 mU/kg/min.
Figure 2
Baseline values for key factors affecting insulin sensitivity between cohorts. Data were collected during the screening visit after an overnight fast. GCK-MODY = Glucokinase Maturity-onset diabetes of the young (also known as MODY2). T1DM = type 1 diabetes. Figures depict mean values and standard deviation.
Figure 3
Arterialized plasma concentrations of: A) insulin, B) each participant’s mean basal insulin concentration grouped by cohort, C) C-peptide, D) glucagon, E) glucose, F) cortisol, G) epinephrine, H) norepinephrine. GCK-MODY = glucokinase-maturity onset diabetes of the young.
T1DM = type 1 diabetes. Figures depict mean values and the 95% CI. * denotes p < 0.05 vs.
T1DM. Page 31 of 50 Diabetes
31
Figure 4
Arterialized blood concentrations of: A) lactate, B) alanine, C) NEFA, D) insulin-mediated NEFA
suppression (each participant’s mean period 1 NEFA level minus mean basal NEFA level), E)
glycerol, F) insulin-mediated glycerol suppression (each participant’s mean period 1 glycerol level
minus mean basal glycerol level). T1DM = type 1 diabetes. Figures depict mean values and the
95% CI. * denotes p < 0.05 vs. T1DM.
Figure 5
Glucose turnover data. A) Endogenous glucose production (EGP), B) insulin-mediated EGP
suppression (each participant’s mean period 1 EGP level minus mean basal EGP level), C) Glucose
utilization (Rd), D) Increase in mean Rd for each individual from period 1 to period 2, E) Scatterplot
depicting bivariate analysis of the effect of glycemia (i.e. HbA1c) on muscle insulin sensitivity
(mean Rd during period 2), F) Scatterplot depicting bivariate analysis of the effect of insulinemia
(i.e. mean basal insulin concentration) on muscle insulin sensitivity (mean Rd during period 2), G)
Linear regression analyses assessing the effect of the independent variables for glycemia and
insulinemia on the dependent variable for muscle insulin sensitivity (mean Rd during period 2).
Figures depict mean values and the 95% CI. * denotes p < 0.05 vs. T1DM. Diabetes Page 32 of 50
A. Subject Chronic Key Differences Affecting Insulin Sensitivity Insulin Distribution Group Glycemia Between Groups Control Normal Normal Mild hyperglycemia Mild GCK- hyperglycemia ↑ Normal MODY AND Peripheral Peripheral Pe. hyperinsulinemia hyperinsulinemia T1DM ↑ hyperinsulinemia B. Min 0 90 150 270 300 420 450
Equilibration Control Period 1 Sample 1 SamplePeriod 2 2 SampleSample 32
2 6,6- H2 Glucose Peripheral Insulin 12 mU/m2/min Peripheral Insulin 40 mU/m2/min (3x basal) (10x basal) Basal Glucagon 0.65 ng/kg/min
Somatostatin 60 ng/kg/min
Peripheral Glucose to maintain plasma glucose at 95 mg/dL Page 33 of 50 Diabetes
Figure 2: Baseline values for key factors affecting insulin sensitivity between cohorts. Data were collected during the screening visit after an overnight fast. GCK-MODY = Glucokinase Maturity-onset diabetes of the young (also known as MODY2). T1DM = type 1 diabetes. Figures depict mean values and standard deviation.
189x218mm (300 x 300 DPI) Diabetes Page 34 of 50
Figure 3: Arterialized plasma concentrations of: A) insulin, B) each participant’s mean basal insulin concentration grouped by cohort, C) C-peptide, D) glucagon, E) glucose, F) cortisol, G) epinephrine, H) norepinephrine. GCK-MODY = glucokinase-maturity onset diabetes of the young. T1DM = type 1 diabetes. Figures depict mean values and the 95% CI. * denotes p < 0.05 vs. T1DM
182x249mm (300 x 300 DPI) Page 35 of 50 Diabetes
Figure 4: Arterialized blood concentrations of: A) lactate, B) alanine, C) NEFA, D) insulin-mediated NEFA suppression (each participant’s mean period 1 NEFA level minus mean basal NEFA level), E) glycerol, F) insulin-mediated glycerol suppression (each participant’s mean period 1 glycerol level minus mean basal glycerol level). T1DM = type 1 diabetes. Figures depict mean values and the 95% CI. * denotes p < 0.05 vs. T1DM.
182x218mm (300 x 300 DPI) A. DiabetesB. Page 36 of 50
C. D.
E. F.
G. Linear Independent Standardized β- regression p-value R2 Variable(s) coefficients model Bivariate Glycemia (HbA1c, %) 0.101 0.093 Bivariate Insulinemia (μU/mL) 0.001 0.356 Glycemia (HbA1c, %) 0.867 -0.025 Multivariable 0.356 Insulinemia (μU/mL) 0.003 -0.584 Page 37 of 50 Diabetes
1
SUPPLEMENTAL MATERIAL
1. Supplemental Tables
2. Supplemental Figures
3. Overnight intravenous insulin infusion protocol for type 1 diabetes participants Diabetes Page 38 of 50
2
Supplemental Tables
Supplemental Table 1:
Inclusion and Exclusion Criteria for Study Participants Page 39 of 50 Diabetes
3
Supplemental Table 2:
Baseline values for key factors affecting insulin sensitivity between cohorts. Data were collected
during the screening visit after an overnight fast. GCK-MODY = Glucokinase Maturity-onset
diabetes of the young (also known as MODY2). T1DM = type 1 diabetes. RH-PAT = reactive
hyperemia-peripheral artery tonometry. Table reports mean values ± standard deviation.
Control GCK-MODY T1DM Parameter (n=10) (n=10) (n=10) HbA1c (%) 4.8 ± 0.4 6.2 ± 0.3 6.6 ± 0.5 HbA1c (mmol/mol) 29 ± 4.4 44 ± 3.3 49 ± 5.5 Age (years) 25.3 ± 3.0 24.8 ± 9.1 26.3 ± 7.8 BMI (kg/m2) 22.5 ± 2.6 21.5 ± 1.9 23.0 ± 1.5 Body fat (%) 29.1 ± 9.8 30.7 ± 6.8 26.7 ± 5.8 VO2 max (mL/kg/min) 38.1 ± 5.3 39.9 ± 9.3 38.8 ± 5.7 Resting energy expenditure (kcal/day) 1531 ± 337 1415 ± 207 1639 ± 235 Systolic blood pressure (mmHg) 114 ± 10 116 ± 13 116 ± 10 RH-PAT score 2.03 ± 0.64 2.16 ± 0.63 1.99 ± 0.41 Triglycerides (mg/dL) 65 ± 26 65 ± 39 73 ± 24 HDL (mg/dL) 56 ± 9 55 ± 10 64 ± 11 LDL (mg/dL) 101 ± 26 101 ± 23 102 ± 30 Total cholesterol (mg/dL) 170 ± 36 168 ± 33 179 ± 39 Diabetes Page 40 of 50
4
Supplemental Table 3:
Glucokinase mutations in the GCK-MODY participants
Participant Nucleotide Protein Effect Reference Number change 1 c.659G>A p.Cys220Tyr (1-3) 2 c.215G>A p.Gly72Glu novel 3 c.1174C>T p.Arg392Cys (4) 4 c.556C>G p.Arg186Gly (5) 5 c.787T>C p.Ser263Pro (6) 6 c.572G>A p.Arg191Gln (7) 7 c.572G>A p.Arg191Gln (7) 8 c.619G>T p. Val207Leu novel 9 c.661G>A p. Glu221Lys (8) 10 c.863+1G>A * (9) * c.863+1 G>A represents a nucleotide substitution in the canonical donor splice site of intron 7 that would be predicted to cause skipping of the exon 7 coding sequence and significant disruption to the protein sequence. Page 41 of 50 Diabetes
5
Supplemental Table 4:
Characteristics of insulin regimens for type 1 diabetes participants (n=10). MDI = participants
taking multiple daily injections, CSII = participants using continuous subcutaneous insulin therapy
(a.k.a. insulin pump). Data presented as means ± SD.
Weight (kg) 72.0 ± 12.5 Prandial insulin dose (units/kg/day) 0.38 ± 0.19 Basal insulin dose (units/kg/day) 0.33 ± 0.10 Total daily dose (units/kg/day) 0.71 ± 0.25 Breakfast insulin to carbohydrate ratio 1 : 8.3 ± 2.7 Lunch insulin to carbohydrate ratio 1 : 8.2 ± 2.3 Supper insulin to carbohydrate ratio 1 : 9.0 ± 2.2 Insulin sensitivity factor (mg/kg/unit) 42.7 ± 12.5 MDI / CSII 3 / 7 Diabetes Page 42 of 50
6
Supplemental Table 5:
Multivariate linear regression models testing which independent variables were most associated with muscle insulin sensitivity.
Standardized Standardized coefficient for basal Standardized β Linear regression coefficient for 3 Model insulin coefficient (p- models HbA1c, β (p- R2 concentration, β (p- 2 value) 1 value) value) Adjusted for basal insulin (β1) and -0.58 (p=0.003) -0.030 (p=0.87) -- 0.356 HbA1c (β2) Adjusted for basal insulin (β1), HbA1c -0.56 (p=0.003) -0.065 (p=0.72) 0.18 (p=0.25) 0.391 (β2), and BMI (β3) Adjusted for basal insulin (β1), HbA1c -0.55 (p=0.009) -0.087 (p=0.65) 0.061 (0.72) 0.378 (β2), and REE (β3) Adjusted for basal insulin (β1), HbA1c -0.59 (p=0.003) -0.038 (p=0.83) -0.10 (p=0.53) 0.369 (β2), and age (β3) Adjusted for basal insulin (β ), HbA1c 1 -0.57 (p=0.005) -0.036 (p=0.85) 0.031 (p=0.85) 0.359 (β2), and percent fat mass (β3) Adjusted for basal insulin (β ), HbA1c 1 -0.58 (p=0.006) -0.079 (p=0.70) -0.28 (p=0.13) 0.455 (β2), and waist-to- hip ratio (β3) Adjusted for basal insulin (β ), HbA1c 1 -0.58 (p=0.003) -0.034 (p=0.85) 0.026 (p=0.87) 0.359 (β2), and triglycerides (β3) Adjusted for basal insulin (β1), HbA1c -0.59 (p=0.003) -0.025 (p=0.89) -0.053 (p=0.74) 0.361 (β2), and LDL (β3) Adjusted for basal insulin (β1), HbA1c -0.59 (p=0.003) -0.041 (p=0.82) -0.058 (p=0.73) 0.362 (β2), and HDL (β3) Adjusted for basal insulin (β ), HbA1c 1 -0.59 (p=0.003) -0.031 (p=0.86) 0.085 (p=0.59) 0.366 (β2), and VO2max (β3) Adjusted for basal insulin (β ), HbA1c 1 -0.62 (p=0.007) -0.02 (p=0.902) -0.05 (p=0.778) 0.358 (β2), and basal NEFA (β3) Page 43 of 50 Diabetes
7
Supplemental Figures
Supplemental Figure 1:
Fractional enrichment of the M+2 glucose isotope in plasma. Data depict means and SD. Diabetes Page 44 of 50
8
Supplemental Figure 2: A) Percent body fat, B) percent lean body mass, C) anoid/gyneoid ratio, D) bone mineral density, E) blood aspartate aminotransferase (AST) concentrations, and F) blood alanine aminotransferase (ALT) concentrations for control, glucokinase maturity-onset diabetes of the young (GCK- MODY), and type 1 diabetes (T1DM) groups. Body composition parameters determined by dual- energy X-ray absorptiometry. Figures depict mean values and standard deviation. Page 45 of 50 Diabetes
9
Supplemental Figure 3:
Box and whiskers plot depicting type 1 diabetes participants’ self-monitored blood glucose in the
three days prior to the clamp study. Horizontal line indicates median glucose, box represents the
25%-75% intra-quartile range, and vertical line represents minimum and maximum self-monitored
blood glucose. Diabetes Page 46 of 50
10
Supplemental Figure 4:
Plasma glucose concentrations (means and SD) and insulin infusion rates (means) during the overnight insulin infusion for type 1 diabetes and GCK-MODY participants. The participants began the overnight insulin infusion at 22:00 prior to the clamp study. Page 47 of 50 Diabetes
11
Supplemental Figure 5:
Bivariate analyses of the effect of: A) coefficient of variation of self-monitored blood glucose
(SMBG) on Rd during period 2 of the hyperinsulinemic euglycemic clamp, B) coefficient of
variation of serial blood glucose readings overnight before the clamp on period 2 Rd.
Corresponding Pearson product-moment correlation coefficients and two-tailed p-values are: A) r
= -0.114 (p = 0.71), B) r = - 0.199 (p = 0.40). Diabetes Page 48 of 50
12
Overnight IV Insulin Infusion Protocol for Type 1 Diabetes Participants Overnight Insulin Infusion Protocol
The following insulin infusion protocol is intended for use in T1DM and GCK-MODY participants in the setting of the overnight insulin infusion prior to hyperinsulinemic clamp studies. Target blood glucose is 90-119 mg/dL.
Initiating the Insulin Infusion 1. START TIME: the overnight infusion should begin at 2200 the night before the clamp study unless directed otherwise 2. TRANSITIONING FROM HOME INSULIN REGIMEN: GCK-MODY participants in this study will not be taking insulin at home. T1DM participants will either use a basal insulin analog that is usually given every 24 hours or they will be on an insulin pump. Instructions for coming off the home insulin regimen is as follows: a. BASAL INSULIN: the study team will have instructed participants taking a basal insulin analog to transition to nightly dosing. On the night prior to the study, this basal insulin dose will simply be withheld and the IV insulin infusion will be started at 2200. b. INSULIN PUMP: those T1DM using an insulin pump should be asked to suspend and disconnect their insulin pump 15-20 minutes before starting the overnight insulin infusion (i.e. at 2140-2145). 3. PREPARATION FOR INFUSION: insulin will be dispensed as 50 units diluted in 50 mL of 0.9% NaCl. a. PRIMING: flush 10 mL of insulin infusion through all IV tubing before insulin infusion begins (to saturate insulin binding sites in the tubing). b. CARRIER FLUID: 0.9% NaCl fluid at 20 mL/hr can be run with the IV insulin infusion to keep the vein open. c. HYPOGLYCEMIA PREVENTION: 20% dextrose solution should be hung and ready in case of hypoglycemia. Glucagon should be within easy reach. 4. INITIAL IV INSULIN INFUSION RATE: initial infusion rate will be determined based on whether the participant is taking a basal insulin analog, is on an insulin pump, or has GCK-MODY. Please record the insulin infusion rate in the space provided on page 1 of the Task Flowsheet. a. BASAL INSULIN: divide the participants total daily basal insulin dose by 24 and round down to the nearest 0.25 unit/hr. Examples: 1) basal insulin dose = Lantus 30 units SQ q HS initial IV insulin infusion rate = 30 ÷ 24 = 1.25 unit/hr 2) basal insulin dose = Levemir 8 units SQ q 12 hours total daily basal insulin dose = 16 units initial IV insulin infusion rate = 16 ÷ 24 = 0.6667 = 0.5 unit/hr b. INSULIN PUMP: start the IV insulin infusion at a rate equal to the home insulin pump basal rate. Examples: 1) home insulin pump basal rate = Humalog 0.8 units/hr Initial IV insulin infusion rate = 0.75 unit/hr c. GCK-MODY: the PI will provide the initial IV insulin infusion rate. Blood glucose (BG) Monitoring 1. Check BG hourly on the hour and record BG and insulin infusion rate on the task flowsheet on the designated line. Page 49 of 50 Diabetes
13
Changing the Insulin Infusion Rate With each subsequent BG check, change the insulin infusion rate as follows:
IF BG < 55 mg/dL: STOP INSULIN INFUSION - Bolus 100 mL of D20 (20 gm of glucose) immediately -Contact PI -Check BG q 15 minutes -When BG is ≥ 90 mg/dL, wait 1 hour, recheck BG. If still ≥ 90 mg/dL, restart insulin infusion at 50% of the most recent rate IF BG 55-69 mg/dL: STOP INSULIN INFUSION - Contact PI immediately -Prepare to give D20 at approximately 3.0 mg/kg/min after discussing with PI. -Check BG q 15 minutes -When BG is ≥ 90 mg/dL, wait 1 hour, recheck BG. If still ≥ 90 mg/dL, restart insulin infusion at 75% of the most recent rate IF BG ≥ 70 mg/dL: STEP 1: Determine the CURRENT BG LEVEL. This identifies a COLUMN in the table:
BG 70-89 mg/dL BG 90-119 mg/dL BG 120-179 mg/dL BG ≥ 180 mg/dL STEP 2: Determine the RATE OF CHANGE from the prior BG level. This identifies a CELL in the table. Then move to the right for INSTRUCTIONS. (Note: if the last BG was measured less than an hour before the current BG, calculate the hourly rate of change. Example: if the BG at 0200 was 85 mg/dL and an additional BG is checked early at 0230 was 70 mg/dL, the total change over 30 minutes is -15 mg/dL; however, the hourly rate of change is - 15 mg/dL x 2 = -30 mg/dL).
BG 70-89 mg/dL BG 90-119 mg/dL BG 120-179 mg/dL BG ≥ 180 mg/dL INSTRUCTIONS* BG ↑ by > 40 BG ↑ ↑ INFUSION by “2Δ” mg/dL/hr BG ↑ by 1-40 BG UNCHANGED BG ↑ by > 20 mg/dL/hr OR ↑ INFUSION by “Δ” mg/dL/hr OR BG ↓ by 1-40 BG UNCHANGED mg/dL/hr BG ↑ by 1-20 mg/dL/hr, BG UNCHANGED, BG ↓ by 1-40 BG ↓ by 41-80 NO INFUSION BG ↑ OR mg/dL/hr mg/dL/hr CHANGE BG ↓ by 1-20 mg/dL/hr BG unchanged OR BG ↓ by 21-40 BG ↓ by 41-80 BG ↓ by 81-120 ↓ INFUSION by “Δ” BG↓ by 1-20 mg/dL/hr mg/dL/hr mg/dL/hr mg/dL/hr BG ↓ by > 20 BG ↓ by > 40 BG ↓ by > 80 BG ↓ by > 120 HOLD x 30 min, then mg/dL/hr see mg/dL/hr mg/dL/hr mg/dL/hr ↓ INFUSION by “2Δ” below†
*CHANGES IN INSULIN INFUSION RATE (“Δ”) are determined by the current rate:
Current Rate (units/hr) Δ = Rate Change 2Δ = 2X Rate Change (units/hr) (units/hr) ≤ 1 0.25 0.5 >1-3 0.5 1 > 3 1 2 † DISCONTINUE insulin infusion . Check BG q 30 min; when BG is ≥ 90 mg/dL restart insulin infusion at 75% of most recent rate Diabetes Page 50 of 50
14
REFERENCES:
1. Osbak KK, Colclough K, Saint‐Martin C, Beer NL, Bellanné‐Chantelot C, Ellard S, Gloyn AL: Update on mutations in glucokinase (GCK), which cause maturity‐onset diabetes of the young, permanent neonatal diabetes, and hyperinsulinemic hypoglycemia. Human Mutation 2009;30:1512-1526 2. Inoue M, Sakuraba Y, Motegi H, Kubota N, Toki H, Matsui J, Toyoda Y, Miwa I, Terauchi Y, Kadowaki T, Shigeyama Y, Kasuga M, Adachi T, Fujimoto N, Matsumoto R, Tsuchihashi K, Kagami T, Inoue A, Kaneda H, Ishijima J, Masuya H, Suzuki T, Wakana S, Gondo Y, Minowa O, Shiroishi T, Noda T: A series of maturity onset diabetes of the young, type 2 (MODY2) mouse models generated by a large-scale ENU mutagenesis program. Hum Mol Genet 2004;13:1147- 1157 3. Shoemaker AH, Zienkiewicz J, Moore DJ: Clinical assessment of HNF1A and GCK variants and identification of a novel mutation causing MODY2. Diabetes Res Clin Pract 2012;96:e36-39 4. Hattersley AT, Beards F, Ballantyne E, Appleton M, Harvey R, Ellard S: Mutations in the glucokinase gene of the fetus result in reduced birth weight. Nat Genet 1998;19:268-270 5. Gloyn AL, van de Bunt M, Stratton IM, Lonie L, Tucker L, Ellard S, Holman RR: Prevalence of GCK mutations in individuals screened for fasting hyperglycaemia. Diabetologia 2009;52:172- 174 6. Gloyn AL: Glucokinase (GCK) mutations in hyper- and hypoglycemia: Maturity-onset diabetes of the young, permanent neonatal diabetes, and hyperinsulinemia of infancy. Human Mutation 2003;22:353-362 7. Li X, Hwu Ting T, Sheng H, Li Liang C, Shao Y, Jiang M, Xu A, Lin Y, Liu L: Genetic and clinical characteristics of Chinese children with Glucokinase-maturity-onset diabetes of the young (GCK-MODY). 2018 8. Caetano LA, Jorge AA, Malaquias AC, Trarbach EB, Queiroz MS, Nery M, Teles MG: Incidental mild hyperglycemia in children: two MODY 2 families identified in Brazilian subjects. Arq Bras Endocrinol Metabol 2012;56:519-524 9. Alkorta-Aranburu G, Carmody D, Cheng YW, Nelakuditi V, Ma L, Dickens JT, Das S, Greeley SAW, Del Gaudio D: Phenotypic heterogeneity in monogenic diabetes: the clinical and diagnostic utility of a gene panel-based next-generation sequencing approach. Mol Genet Metab 2014;113:315-320