Abstract
Context
Patients with mutations of the insulin receptor gene (INSR) have extreme insulin resistance and are at risk for early morbidity and mortality from diabetes complications. A case report suggested that thyroid hormone could improve glycemia in INSR mutation in part by increasing brown adipose tissue (BAT) activity and volume.
Objective
To determine if thyroid hormone increases tissue glucose uptake and improves hyperglycemia in INSR mutation.
Design
Single-arm, open-label study of liothyronine.
Setting
National Institutes of Health.
Participants
Patients with homozygous (n = 5) or heterozygous (n = 2) INSR mutation.
Intervention
Liothyronine every 8 hours for 2 weeks (n = 7); additional 6 months’ treatment in those with hemoglobin A1c (HbA1c) > 7% (n = 4).
Outcomes
Whole-body glucose uptake by isotopic tracers; tissue glucose uptake in muscle, white adipose tissue (WAT) and BAT by dynamic [18F] fluorodeoxyglucose positron emission tomography/computed tomography; HbA1c.
Results
There was no change in whole-body, muscle, or WAT glucose uptake from baseline to 2 weeks of liothyronine. After 6 months, there was no change in HbA1c (8.3 ± 1.2 vs 9.1 ± 3.0%, P = 0.27), but there was increased whole-body glucose disposal (22.8 ± 4.9 vs 30.1 ± 10.0 µmol/kg lean body mass/min, P = 0.02), and muscle (0.7 ± 0.1 vs 2.0 ± 0.2 µmol/min/100 mL, P < 0.0001) and WAT glucose uptake (1.2 ± 0.2 vs 2.2 ± 0.3 µmol/min/100 mL, P < 0.0001). BAT glucose uptake could not be quantified because of small volume. There were no signs or symptoms of hyperthyroidism.
Conclusion
Liothyronine administered at well-tolerated doses did not improve HbA1c. However, the observed increases in muscle and WAT glucose uptake support the proposed mechanism that liothyronine increases tissue glucose uptake. More selective agents may be effective at increasing tissue glucose uptake without thyroid hormone–related systemic toxicity.
Clinical Trial Registration Number: NCT02457897; https://clinicaltrials.gov/ct2/show/NCT02457897.
Keywords: extreme insulin resistance, INSR mutation, liothyronine
Genetic syndromes of extreme insulin resistance caused by mutations of the insulin receptor gene (INSR) are characterized by high morbidity and mortality resulting from microvascular complications of diabetes and diabetic ketoacidosis (1). These disorders exist on a spectrum of severity related to the degree of residual activity of the insulin receptor, with more severe autosomal recessive forms (Donohue and Rabson Mendenhall syndromes) and less severe autosomal dominant forms (type A insulin resistance).
Treatment of diabetes in patients with extreme insulin resistance is challenging and is largely directed at maximizing residual insulin signaling and increasing tissue sensitivity to insulin. Available treatment options that can improve hyperglycemia include high doses of concentrated U500 insulin (as high as 100 units/kg/d), metreleptin, recombinant insulin-like growth factor-1, and insulin sensitizers (1–3). However, targets for diabetes control are often not achieved. Thus, alternative glucose-lowering treatments that do not require signaling through the insulin receptor are critical for improvement of glycemia and diabetes-related complications.
In a single patient with homozygous mutation of the insulin receptor and poorly controlled diabetes despite maximal therapy, iatrogenic hyperthyroidism for treatment of thyroid cancer resulted in normalization of glycemia control and activation of brown adipose tissue (BAT) (4), suggesting that thyroid hormone treatment could have therapeutic benefit in this rare disease. Hyperthyroidism, whether endogenous (eg, Graves’ disease) or exogenous, increases energy expenditure, activates BAT, and enhances skeletal muscle perfusion, leading to enhanced glucose disposal (5–8). Patients with normal insulin receptor function typically experience elevated blood glucose with thyroid hormone treatment resulting from worsening of hepatic insulin resistance (5, 9); however, this effect may be less relevant in patients with INSR mutation in whom insulin resistance is largely a function of the genetic defect.
In the current study, we tested the hypothesis that, in patients with extreme insulin resistance resulting from INSR mutations, mild iatrogenic hyperthyroidism would enhance glucose disposal without worsening insulin resistance, resulting in a net improvement in glucose homeostasis.
Materials and Methods
Study design
The study was a phase 2 clinical trial with a prospective nonrandomized within-subject design. The study was conducted in 2 sequential parts (Figs 1, 2): part 1 was a short-term (2-week) proof-of-principle study to test whether thyroid hormone would increase glucose disposal in patients with INSR mutation (with or without diabetes) and explore the potential mechanisms by which increased glucose disposal occurred. Part 2 was a long-term (6-month) therapeutic study to test whether thyroid hormone would improve glycemia control in patients with INSR mutations and inadequately controlled diabetes based on hemoglobin A1c (HbA1c) ≥7%. The study was approved by the institutional review board of the National Institute of Diabetes and Digestive and Kidney Diseases (NCT02457897). All subjects or their legal guardians provided written informed consent before participation. Minors provided written assent.
Figure 1.
Study design. Abbreviations: DEXA, dual energy x-ray absorptiometry; EKG, electrocardiogram; FDG PET, fluorodeoxyglucose positron emission tomography; T3, triiodothyronine.
1TSH, free thyroxine, total thyroxine, free triiodothyronine, total triiodothyronine, reverse triiodothyronine.
2Free fatty acids, lipid panel, osteocalcin, sex hormone–binding globulin.
Figure 2.
CONSORT flow chart. F18-FDG PET, [18F] fluorodeoxyglucose positron emission tomography; HbA1c, hemoglobin A1c.
Patients
Patients age 12 to 65 years of age with proven heterozygous or homozygous INSR mutation who were taking stable doses of diabetes medications (eg, insulin, metformin, thiazolidinediones, metreleptin) for the preceding 10 weeks were eligible for the study. Patients were excluded if they had any condition associated with thyroid dysfunction, conditions that would alter absorption or measurement of thyroid hormone, or conditions that might increase risks associated with thyroid hormone administration.
Patients were admitted to the Metabolic Research Unit in the National Institutes of Health (NIH) Clinical Center where they initially stayed as inpatients for 19 days (short-term study). Patients with HbA1c ≥7% who chose to participate in the long-term study were readmitted after 3 months for safety monitoring, and after 6 months for assessment of study endpoints.
Primary and secondary outcomes
The primary outcome of the short-term study was total body glucose disposal in the fasting state measured by isotopic tracers. The short-term study had 80% power with a 2-sided alpha of 0.05 to detect a change in glucose disposal of 0.39 mg/kg-1/min-1 with a standard deviation of 0.27 with 6 subjects. The primary outcome for the long-term study was HbA1c. The long-term study had 80% power with a 2-sided alpha of 0.05 to detect a HbA1c change of 2% with a standard deviation of 1.5 with 7 subjects. The principal secondary endpoint for both short- and long-term studies was change in muscle glucose uptake using positron emission tomography (PET). This endpoint had 80% power with a 2-sided alpha to detect a change 1.4 µmol/min/100 mL of tissue with a standard deviation of 0.6 with only 4 subjects.
Additional glycemic outcomes included tissue-specific glucose disposal in the fasting state in BAT, white adipose tissue (WAT), and muscle quantified using PET, glucose area under the curve (AUC) measured using 7-point daily plasma glucose and oral glucose tolerance testing. Measurements of energy expenditure included resting energy expenditure and core and peripheral body temperature. Metabolic targets of thyroid hormone were assessed including lipids, lipolysis, free fatty acids (FFA), osteocalcin, and sex hormone–binding globulin (SHBG). Safety measures included heart rate, blood pressure, bone mineral density, echocardiography, body weight, and symptom assessment. In adult subjects, optional biopsies of the muscle and WAT were performed for gene expression analysis.
Diet
During the short-term study, subjects were placed on an ad libitum metabolic diet provided by the NIH metabolic research kitchen with a fixed food quotient (40% carbohydrates, 20% protein, and 40% fat). Diet during the long-term study was ad libitum for both caloric and macronutrient content.
Thyroid hormone treatment
Thyroid hormone was administered as liothyronine (active thyroid hormone) to permit rapid dose titration to a hyperthyroid steady state. On day 1, liothyronine was administered at 0.57 mcg/kg/d divided every 8 hours (equal to physiologic replacement dosing in hypothyroid subjects (10, 11)). Dosing was increased to 1.5 times physiologic replacement on day 2, and to 2 times physiologic replacement on days 3 through 14. Further dose adjustments were made to achieve a plasma T3 peak target of 250 to 300 ng/dL (equal to 125%–150% of the upper normal limit) 3 hours after the morning dose of liothyronine and target total triiodothyronine (TT3) trough of 150 to 250 ng/dL just before the morning dose of liothyronine. Peak and trough levels were measured daily for the first week and every other day thereafter. For subjects participating in the long-term liothyronine treatment study, liothyronine was continued at the final dose from the short-term study for an additional 6 months. Compliance was assessed monthly by telephone calls, and pill counts were conducted at the 3- and 6-month study visits.
Glucose monitoring and insulin dosing
Bedside blood glucose monitoring was done before meals and at bedtime during the inpatient stays. Insulin doses were reduced as needed in case of hypoglycemia (blood glucose ≤70 mg/dL) but were not increased during the study (12). No other changes in medications were made during the study.
Standard exercise
Physical fitness during the 19-day hospitalization was maintained by walking on a treadmill each day with duration and intensity dependent on the preadmission physical activity level.
Tests
Laboratory methods
Except for peak triiodothyronine (T3), all laboratory measurements were performed on blood samples obtained after a 10- to 12-hour fast. TSH, free thyroxine (fT4), total thyroxine (TT4), free triiodothyronine (fT3), TT3, HbA1c, glucose, C-peptide, insulin, osteocalcin, free fatty acids, C-reactive protein, SHBG, albumin, and lipid panel were measured by the standard techniques of the NIH Clinical Center Laboratory. Immunoassay thyroid hormone reference intervals for TSH (0.27-4.20 mcIU/mL), fT3 (2.0-4.4 pg/mL), fT4 (0.9-1.7 ng/dL), TT3 (80-200 ng/dL), and TT4 (4.5-11.7 μg/dL) were suggested by the manufacturer.
Metabolic response to liothyronine
To assess predictors of metabolic response to liothyronine, linear mixed models were performed examining the relationships between potential predictors and metabolic outcome variables. Predictors tested included a measure of baseline diabetes control (baseline HbA1c), a measure of insulin resistance (fasting insulin), sex, a measure of body composition (lean body mass), and TSH (both baseline and during liothyronine treatment). The effect of genotype (heterozygous vs homozygous mutation) was assessed as a predictor only for 2-week responses to liothyronine because all subjects who continued liothyronine for 6 months had homozygous genotypes. The effect of compliance as a predictor was assessed only for 6-month responses to liothyronine because all subjects were 100% compliant with liothyronine during the 2-week inpatient portion of the study. Metabolic response variables included fructosamine, HbA1c, glucose rate of appearance, and tissue glucose uptake in WAT and muscle.
Tracer studies
Following a 10- to 12-hour fast, [6,6-2H2] glucose (Cambridge Isotope Laboratories) was used to measure glucose turnover using the tracer dilution method. One catheter was inserted into the forearm vein to infuse stable isotopically labeled tracers. A second catheter was inserted into a vein in the contralateral hand or arm to obtain blood samples. [6,6-2H2] glucose was continuously infused at 0.535 µmol per kilogram of lean body mass (LBM) for 3 hours after a priming dose of 32.1 µmol kgLBM-1 min-1. During the last 30 minutes of the [6,6-2H2] glucose infusion, blood samples were obtained every 10 minutes over a period of 30 minutes at steady state to measure isotope enrichment. Enrichment of [6,6-2H2] glucose was measured by liquid chromatography-mass spectrometry, as previously published (13). The rate of disposal (Rd) of glucose per kgLBM was calculated by measuring isotope enrichment using the single pool model (14).
Glucose uptake measured by [18F] fluorodeoxyglucose PET
To assess tissue glucose uptake, subjects ≥18 years of age fasted for 12 hours before dynamic PET imaging of the upper torso performed on a Siemens mCT PET/computed tomography (CT) scanner (Siemens Medical Solutions, Hoffman Estates, IL). An attenuation CT scan of the upper torso was performed first, followed by IV injection of 5 mCi of [18F] fluorodeoxyglucose (18F-FDG). Less than 30 seconds later, PET emission data acquisition on the same region was started and continued for approximately 71 minutes. The resulting data were split into 10 30-second duration frames, 10 3-minute frames, and 6 5-minute frames that were reconstructed into 26 upper torso images. For parametric modeling of the BAT, WAT, and muscle tracer kinetics, an arterial input function was derived from a left ventricular region of interest (ROI) drawn on the dynamic PET image. This input function curve, spanning the entire duration of the PET study, was used to calculate a fractional rate of 18F-FDG PET uptake (Ki), for each upper torso voxel, using the Patlak graphical method [15]. A voxel-wise metabolic rate of glucose uptake (MRGlu) image was calculated by multiplying Ki by the plasma glucose concentration of the study subject, sampled just before scanning, and dividing this by the lumped constant of adipose tissue (1.14) (15) (for BAT and WAT), or skeletal muscle (1.2) (16). Glucose uptake was expressed in units of µmol/min/100 mL of tissue. PXMOD and PBAS version 3.9 software (PMOD Technologies LLC, Zurich, Switzerland) was used for kinetic modeling and regional data analysis.
ROIs for glucose uptake included BAT in the cervical/supraclavicular, mediastinal, and paraspinal regions, WAT in subcutaneous tissue of the chest wall, and muscles in the deltoid and periscapular regions. Eighteen to 21 ROIs were measured in each subject. Activated BAT tissue was identified by requiring CT voxel values consistent with adipose tissue (-300 to -10 Hounsfield units) to coincide with PET voxels with standardized uptake value (SUV) values ≥1.0 in the PET image registered to the CT. SUV was computed by averaging the last 6 frames of the dynamic PET data, dividing by the injected dose 18F-FDG PET dose, and multiplying by patient body weight. Each ROI was defined manually on the subject’s CT image and applied to pre- and post-liothyronine treatment MRGlu images to calculate mean MRGlu for each tissue type.
Oral glucose tolerance test (OGTT)
OGTT was performed using a 75-g oral glucose solution (1.75 gm/kg in patients weighing less than 40 kg) after a 10- to 12-hour fast with measurement of glucose, insulin, and C-peptide at -10, 0, 30, 60, 90, 120, and 180 minutes relative to glucose ingestion. The AUCs for glucose, insulin, and C-peptide were calculated using the trapezoidal method.
7-point plasma glucose
Plasma glucose was measured before each meal, 2 hours after each meal, and at bedtime with calculation of glucose AUC by the trapezoidal method.
Body composition
Total and regional body fat and lean soft tissue masses, and bone mineral density (BMD) at the lumbar spine, hip, and 1/3 radius was measured using dual energy x-ray absorptiometry (DXA) (Hologic QDR 4500; Hologic, Bedford, MA). Because BMD changes with growth and development, and both adults and children with INSR mutation may have significant short stature, age-, sex-, and height-based SD scores (SDS) for BMD were calculated based on normative population data from the Bone Mineral Density in Childhood Study (17). For patients under the age of 20 years at the time of the DXA, SDS represent z scores (compared with age-matched controls). For patients over the age of 20 years, SDS represent T scores (compared with 20-year-old controls).
Energy expenditure
Resting energy expenditure (REE) was measured by a whole-room indirect calorimeter with ambient temperature of 25 to 27°C. Subjects wore standardized clothing with clothing insulation value 0.55. They entered the room calorimeter at 8 am after an 8- to 12-hour fast before and after 2 weeks and 6 months of liothyronine treatment. REE was assessed during 2 predefined time periods (10:30-11:00 am and 11:30-12:00 pm) when subjects were instructed to be minimally active but awake. This method has been shown to have better reproducibility compared with hood calorimetry for measurement of REE (18). The total stay in the metabolic chamber was 5 hours. Physical activity level was measured continuously through a wall-mounted monitoring device (microwave sensor), as published previously (14, 15, 19–21).
Body temperature
Core body temperature was measured daily during inpatient stays at 0600, 1400, and 2200 using a tympanic thermometer (Genius 2 Tympanic Thermometer, Cardinal Health, Dublin, OH). Skin temperature was measured while subjects were in the room calorimeter by wireless probes (iButtons, Maxim Inc., Sunnyvale, CA) at 5 sites (deltoid, hand, pectoralis major, anterior thigh, and shin).
Tissue sampling and gene expression
Muscle and adipose tissue biopsies
Muscle biopsies were performed in 2 adult subjects. Twenty milligrams of tissue were obtained under local anesthesia from the vastus lateralis using a Bard Magnum biopsy instrument (MG1522, Bard Medical Division, Covington, GA). WAT biopsy was performed in a single subject. Approximately 2 g of adipose tissue were removed from the abdominal region by aspiration using a blunt biopsy 12 G needle under local anesthesia. Muscle and adipose tissues were flash frozen and stored in liquid nitrogen at -80°C. Tissue biopsies were not performed in the fasting state. Analyses in muscle included mRNA for glucose transporters (GLUT1 and GLUT4), uncoupling protein 3 (UCP-3), and deiodinase type 3. Fat tissue analysis included mRNA for markers of WAT/beige adipose tissue/BAT including leptin (LEP), homeobox C8 (HOXC8), UCP1 transmembrane protein 26 (TMEM26), T-box 1 (TBX1), Zinc finger protein 1 (ZIC1), cluster of differentiation 137 (CD137), and GLUT1.
RNA was obtained by homogenizing ~50 to 100 mg of frozen tissue in 500 mL of TRI REAGENT (Molecular Research Center, Inc., Cincinnati, OH) on ice following the manufacturer’s instructions. Total RNA was digested with DNase I using DNA-free (Ambion, Austin, TX) and tested for the presence of DNA contamination using PCR. Total RNA concentration and purity were then determined by spectrophotometer at 260 nm (NanoDrop 2000 UV–Vis Spectrophotometer, Thermo Scientific). A total of 200 ng RNA was converted into cDNA using iScript cDNA Synthesis Kit (Bio-Rad Laboratories, Hercules, CA) and relative quantification of mRNAs was performed with 3.5 μL of cDNA used in each 11.5 μL real-time RT-PCR reaction using C1000 thermal cycler (Bio-Rad Laboratories). The PCR reactions were carried out using IQ Syber Green Supermix (Bio-Rad). Primers for the target genes are available on request. Thermal cycling parameters were as follows: an initial denaturing step (95°C for 10 minutes), followed by 40 cycles of denaturing (95°C for 45 seconds), annealing (58°C for 45 seconds), and extending (60°C for 1 minute) in a 96-well BioRad plate. The results were calculated by the comparative Ct method using Beta2 microglobulin as an endogenous reference gene, according to the Applied Biosystems ABI PRISM 7700 User Bulletin #2. The expression relative to Beta2 microglobulin was determined by calculating 2 − ΔCt.
Safety testing and follow-up
To monitor for side effects of liothyronine, the following tests were performed: 1) electrocardiogram and echocardiogram at baseline and after 6 months; 2) blood pressure and heart rate 3 times daily during the 2-week study and at 3 and 6 month inpatient visits; 3) body weights daily (mean of 3 measurements) during the inpatient stay and at 3 and 6 month inpatient visits; 4) DXA for bone densitometry at the anteroposterior spine, hip, and 1/3 radius at baseline and after 6 months; and 5) evaluation for clinical symptoms of liothyronine toxicity such symptomatic palpitations, anxiety, diarrhea, tremulousness, sweating/heat intolerance; tachycardia (defined as heart rate >110 beats/min over a 24-hour period); development of systolic hypertension (defined as >130 mm Hg and a ≥10 mm Hg over baseline); chest pain; congestive heart failure; weight loss >4 kg or >10% of body weight; and peak liothyronine >350 ng/dL. Toxicity symptoms/signs were evaluated daily during inpatient stays and monthly by telephone assessments between study visits.
Statistical analysis
Data are reported as mean ± standard deviation unless otherwise noted. All measured parameters were not different between home baseline (day 1 of admission) and hospital baseline (mean results of days 4 and 5). Therefore, 2-week and 6-month results were compared with hospital baseline. Variables with skewed distribution were Box-Cox transformed before analysis, if necessary. For parameters with repeated measures, linear mixed models were used with time as the fixed effect. If a significant difference across time points was detected, post hoc pairwise comparisons between baseline and each follow-up time point were conducted using Dunnett correction. To examine the difference in glucose uptake measured by 18F-FDG PET in different tissue types, a linear mixed model with timepoint by tissue type interaction was conducted. Because of significant timepoint by tissue type interaction, changes in glucose uptake among time points were examined in each tissue type separately. Correlations among multiple measurements of glucose uptake generated by multiple ROIs per time point as well as multiple time points were accounted for by adding a random effect of subject into the linear mixed model. Analyses were performed using GraphPad Prism, version 6 (GraphPad Software, La Jolla, CA), and SAS software, version 9.4 (SAS Institute Inc., Cary, NC). A P value < 0.05 was considered statistically significant.
Results
Demographic characteristics
Demographic characteristics of 7 patients with INSR mutation are shown in Table 1. Five patients had homozygous or compound heterozygous and 2 had heterozygous mutations in the INSR gene. All patients were taking metformin; 5 of 7 were taking metreleptin as an investigational drug (all with biallelic INSR mutations). Four patients (patient numbers 3, 5, 6, and 7) were on U500 insulin (140-1500 U/d). The dose of insulin was reduced in patient 7 (from 1500 to 950 U/d) and discontinued in patient 6 before liothyronine initiation based on hypoglycemia during the initial inpatient stay. In patient 7, the dose of insulin was further reduced from 950 to 150 U/d during the first 2 weeks of liothyronine because of hypoglycemia but was titrated back to the baseline dose of 1500 U/d after discharge and resumption of home diet. In patient 5, the dose of insulin was reduced from 1500 to 1000 U/d during the first 2 weeks of inpatient liothyronine treatment and continued at that dose for the next 6 months of liothyronine.
Table 1.
Baseline Characteristics of Patients With Mutations of the Insulin Receptor (INSR)
| Patient | Age (y) | Sex | Disease | Mutation Type | INSR Mutation Location | BMI (kg/m2) | Body Fat (%)a | HbA1c (%) | Diabetes Medications |
|---|---|---|---|---|---|---|---|---|---|
| 1 | 18 | F | Type A | Heterozygous | Val1029Gly | 23.5 | 27.0b | 4.8 | Metformin 2000 mg/d |
| 2 | 30 | F | Type A | Heterozygous | Val1029Gly | 36.3 | 44.2 | 5.8 | Metformin 1500 mg/d |
| 3 | 28 | M | RMS | Homozygous | Pro193Leu | 15.3 | 11.9 | 8.5 | Metformin 2000 mg/d |
| Leptin 3.5 mg twice/d | |||||||||
| Insulin 300 U/d | |||||||||
| 4 | 15 | M | RMS | Compound heterozygous | Leu136Arg and intronic deletion | 12.4 | 11.9 | 7.8 | Metformin 2000 mg/d |
| Leptin 3 mg twice/d | |||||||||
| 5 | 20 | M | RMS | Homozygous | Ser635Leu | 22.0 | 15.9 | 13.4 | Metformin 2000 mg/d |
| Leptin 4.6 mg twice/d | |||||||||
| Insulin 1500 U/d | |||||||||
| 6 | 17 | M | RMS | Compound heterozygous | Tyr3X and Glu238Lys | 15.2 | 11.0 | 7.1 | Metformin 2000 mg/d |
| Leptin 3.5 mg twice/d | |||||||||
| 7 | 26 | F | RMS | Homozygous | Pro193Leu | 14.2 | 14.6 | 9.8 | Metformin 2000 mg/d |
| Leptin 3.5 mg twice/d | |||||||||
| Insulin 950 U/d |
Abbreviations: HbA1c, hemoglobin A1c; RMS; Rabson-Mendenhall syndrome.
aMeasured by whole-body dual energy x-ray absorptiometry.
bDual energy x-ray absorptiometry scan was unavailable at time of study entry; data shown is from 3 years before study.
Seven patients were included in and completed the short-term study. Of these, 2 with HbA1c < 7% and heterozygous INSR mutations were not eligible for the long-term study. The 5 patients with biallelic INSR mutations all had HbA1c ≥7% and participated in the long-term study.
Pill counts revealed that liothyronine compliance among the 5 patients who completed the 6-month study were 38%, 84%, 91%, 100%, and 100%. The patient who had compliance of 38% was excluded from the 6-month analysis.
Thyroid status
All patients were euthyroid at hospital baseline. Thyroid hormones during the study are shown in Fig. 3 and Table 2. Suppression of TSH below the normal range was observed by day 4 of liothyronine (0.24 ± 0.2 mclU/mL; range, 0.05-0.52 mclU/mL). Target levels for fT3 and TT3 were achieved by days 3 and 4, respectively (fT3 5.25 ± 1.3; range, 3.4-7.29; TT3, 208 ± 41.4; range, 160.4-269.6). Free T4 and rT3 trended down during liothyronine treatment. Stable levels of thyroid hormones were maintained for 6 months for the 4 patients in the long-term treatment arm who were compliant with liothyronine.
Figure 3.
Thyroid panel before and during liothyronine administration. All measurements are trough values (before liothyronine dosing) except for peak TT3 (measured 3 hours after dosing). Dotted lines indicate upper (fT3, TT3) or lower (TSH, fT4, TT3) normal reference ranges. Data shown as mean ± SEM. Liothyronine was initiated after the day 1 trough measurement (indicated by black arrows). (A) A decrease in TSH consistent with mild hyperthyroidism was seen beginning on day 4 of liothyronine. (B) Increases in fT3 above the upper limit of normal, and (C, D) TT3 trough and TT3 peak above the target levels were seen on days 3, 2, and 3, respectively, of liothyronine. (E) fT4 and (F) rT3 were below the lower limit of normal on day 8. TT3 peak and rT3 were not measured at the 180-day time point. Abbreviations: fT3, free triiodothyronine; fT4, free thyroxine; rT3, reverse triiodothyronine; TT3, total triiodothyronine; TT4, total thyroxine.
Table 2.
Thyroid Panel During Liothyronine Therapy
| Parameter | Hospital Baseline (N = 7) | 2 Wk on Liothyronine (N = 7) | 6 Mo on Liothyronine (N = 4) | P Valuea |
|---|---|---|---|---|
| TSH, mcIU/mL | 2.02 ± 0.79 | 0.10 ± 0.16 | 0.12 ± 0.17 | <0.0001b,c |
| fT3, pg/mL | 3.00 ± 0.42 | 5.58 ± 0.59 | 5.47 ± 1.12 | <0.0001b,c |
| TT3 trough, ng/dL | 106.10 ± 16.96 | 207 ± 10.74 | 209 ± 43.01 | <0.0001b,c |
| fT4, ng/dL | 1.49 ± 0.34 | 0.66 ± 0.22 | 0.53 ± 0.05 | <0.0001b,c |
| TT4, mcg/dL | 8.08 ± 1.46 | 4.11 ± 1.12 | 2.88 ± 0.49 | <0.0001b,c |
Abbreviations: fT3, free triiodothyronine; fT4, free thyroxine; TT3, total triiodothyronine; TT4, total thyroxine.
aMixed model analysis comparing hospital baseline with 2 weeks and 6 months of liothyronine.
b P < 0.05 for hospital baseline vs 2 weeks.
c P < 0.05 for hospital baseline vs 6 months.
Glycemic parameters
Effects of liothyronine on glycemic parameters are shown in Fig. 4 and Table 3. Total body glucose disposal measured by stable isotope tracers did not change after 2 weeks of liothyronine (20.9 ± 5.5 vs 21.5 ± 6.0 µmol/kgLBM/min; n = 7; P = 0.9) but increased significantly after 6 months (30.1 ± 10.2 µmol/kgLBM/min, n = 4, P = 0.02). After 2 weeks of liothyronine, HbA1c trended down (from 8.2 ± 2.8% to 7.4 ± 2.2%, P = 0.06) and fructosamine significantly decreased (from 355.6 ± 147 to 284 ± 47.5 µmol/L, P = 0.03). There was no change in HbA1c (9.1 ± 3.0%) or fructosamine (368 ± 95 µmol/L) after 6 months in subjects who participated in the long-term study (P = 0.27 for both). A large increase in HbA1c at the 6-month time point was observed in 1 subject who was compliant with liothyronine but who mistakenly decreased her insulin dose by more than 50% before the 6-month time point. Fasting insulin was numerically lower during liothyronine treatment, but this change was not statistically significant (P = 0.13). There was no change in OGTT parameters or 7-point plasma glucose measurements after either 2 weeks or 6 months of liothyronine.
Figure 4.
Effects of liothyronine on glycemia. (A) Glucose disposal (Rd) did not change after 2 weeks but increased after 6 months of liothyronine. (B) Hemoglobin A1c (HbA1c) did not change after 2 weeks or 6 months of liothyronine. (C) Fructosamine significantly decreased after 2 weeks, but this was not maintained after 6 months. One patient (open square on graphs) had increased hemoglobin A1c and fructosamine at the 6-month visit in the context of an accidental >50% decrease in insulin dose. (D) Glucose levels before meals (pre) and 2 hours after meals (post) at baseline (closed circles) and after 2 weeks of liothyronine (open squares). Area under the curve for glucose did not change with liothyronine administration.
Table 3.
Effect of Liothyronine on Glycemic Parameters
| Parameter | Hospital Baseline (N = 7) | 2 Wk on Liothyronine (N = 7) | 6 Mo on Liothyronine (N = 4) | P Valuea |
|---|---|---|---|---|
| Fasting insulin, mcU/mL | 328 ± 122 | 201 ± 98 | 209 ± 107 | 0.1 |
| C-peptide, ng/mL | 2.2 ± 0.7 | 2.3 ± 0.5 | 1.3 ± 0.2 | 0.7 |
| Insulin AUC during OGTT, mcU/mL/190 min | 111 690 ± 19 443 | 113 487 ± 19 405 | 89 224 ± 29 281 | 0.8 |
| Glucose AUC during OGTT, mg/dL/190 min | 51 231 ± 5803 | 50 967 ± 5178 | 60 214 ± 9750 | 0.7 |
| C-peptide AUC during OGTT, ng/mL/190 min | 2160 ± 546 | 2438 ± 604 | 1322 ± 817 | 0.1 |
| 7-point blood glucose AUC, mg/dL/24 h | 2414 ± 467 | 2252 ± 203 | Not done | 0.7 |
| Glucose Rd, μmol/kgLBM/min | 20.9 ± 6 | 21.47 ± 6 | 30.05 ± 10 | 0.02b |
Abbreviations: AUC, area under the curve; OGTT, oral glucose tolerance test; Rd, rate of disappearance.
aMixed model analysis comparing hospital baseline with 2 weeks and 6 months of liothyronine.
b P < 0.05 for hospital baseline vs 6 months.
Metabolic response to liothyronine
As expected, baseline diabetes control (assessed by HbA1c) was a significant predictor of diabetes control (assessed by HbA1c and fructosamine) during liothyronine treatment. In addition, fasting insulin was a significant predictor of both higher fructosamine (0.0005) and higher HbA1c (P = 0.002). No other significant relationships between predictors and metabolic outcomes were identified.
Glucose uptake measured by 18F-FDG PET technique
Muscle glucose uptake did not change from baseline to 2 weeks of liothyronine (1.0 ± 0.3 vs 0.9 ± 0.08 µmol/min/100 mL; n = 5; P = 0.3) but increased significantly after 6 months on liothyronine (2.0 ± 0.2 µmol/min/100 mL; n = 2; P < 0.0001; Fig. 5A). Glucose uptake by WAT decreased from baseline to 2 weeks of liothyronine (1.2 ± 0.08 vs 1.0 ± 0.07 µmol/min/100 mL; n = 5; P < 0.0001) but then increased after 6 months compared with baseline (2.2 ± 0.3 µmol/min/100 mL; n = 2) P < 0.0001) (Fig. 5B). Small amounts of BAT were detectable at baseline and during 2 weeks (n = 5) and 6 months (n = 2) of liothyronine in cervical, supraclavicular, axillary, and paravertebral regions with no visually apparent increase in BAT activity or volume after liothyronine (Fig. 5C). BAT glucose uptake in ROI was not quantified because of the small volume of tissue.
Figure 5.
Tissue glucose uptake based on fluorodeoxyglucose positron emission tomography studies. (A) Glucose uptake by muscle did not change after 2 weeks of liothyronine, but significantly increased after 6 months. (B) Glucose uptake by WAT significantly decreased after 2 weeks but increased after 6 months of liothyronine. Data are presented in mean ± standard error of the mean of within-subject replicates. (C) Small amounts of BAT were detectable at baseline and during liothyronine treatment with no visually apparent increase in BAT after 2 weeks or 6 months of liothyronine. Red color pointed to by black arrows represents the areas that met criteria for BAT (computed tomography voxel values consistent with adipose tissue -300 to -10 Hounsfield units) and positron emission tomography standardized uptake value values ≥1.0 in the positron emission tomography image registered to the computed tomography). Glucose uptake in regions meeting criteria for BAT was not quantified because of the small volume of tissue. Abbreviations: BAT, brown adipose tissue; WAT, white adipose tissue.
Metabolic targets of liothyronine
Lipid panel, osteocalcin, SHBG, FFA, REE, and respiratory quotient
As expected, total cholesterol, low-density lipoprotein, and high-density lipoprotein significantly decreased after 2 weeks of liothyronine, and the effect was consistent thereafter for 6 months (P < 0.0002) (Table 4). Triglycerides significantly decreased after 2 weeks and then increased after 6 months of therapy (P < 0.0001). FFA did not change with liothyronine. There was a significant increase in SHBG after 2 weeks and 6 months of liothyronine (P < 0.0001) but no change in osteocalcin. Respiratory quotient and REE did not change after liothyronine treatment (Table 4).
Table 4.
Thyroid Hormone Metabolic Targets and Energy Expenditure
| Parameter | Hospital Baseline (N = 7) | 2 Wk on Liothyronine (N = 7) | 6 Mo on Liothyronine (N = 4) | P Valuea |
|---|---|---|---|---|
| Osteocalcin, ng/mL | 34 ± 11 | 38 ± 11 | 44 ± 13 | 0.8 |
| SHBG, nmol/L | 83 ± 23 | 102 ± 35 | 122 ± 23 | <0.0001b,c |
| FFA, mEq/L | 0.6 ± 0.1 | 0.6 ± 0.1 | 0.5 ± 0.1 | 0.2 |
| Total cholesterol, mg/dL | 145 ± 6.6 | 122 ± 3.0 | 120 ± 1.6 | 0.0002b,c |
| Triglycerides, mg/dL | 62 ± 7 | 51 ± 4 | 66 ± 23 | <0.0001b,c |
| HDL-C, mg/dL | 62 ± 5 | 54 ± 5 | 60 ± 5 | <0.0001b,c |
| LDL-C, mg/dL | 71 ± 5 | 58 ± 6 | 47 ± 7 | <0.0001b,c |
| RQ | 0.81 ± 0.02 | 0.82 ± 0.03 | 0.84 ± 0.04 | 0.3 |
| REE, kcal/24 h | 1537 ± 465 | 1540 ± 306 | 1326 ± 60 | 0.9 |
Abbreviations: FFA, free fatty acids; HDL-C, high-density lipoprotein cholesterol; LBM, lean body mass; LDL-C, low-density lipoprotein cholesterol; REE, resting energy expenditure; RQ, respiratory quotient; SHBG, sex hormone–binding globulin.
aMixed model analysis comparing hospital baseline with 2 weeks and 6 months of liothyronine.
b P < 0.05 for hospital baseline vs 2 weeks.
c P < 0.05 for hospital baseline vs 6 months.
Body composition
There was no change in body composition during liothyronine treatment. In the short-term study, fat mass was 11.5 ± 4.8 at baseline and 11.9 ± 5.2 kg after 2 weeks (n = 7; P > 0.99); and lean mass was 36.9 ± 4.1 at baseline and 36.9 ± 4.0 after 2 weeks (n = 7, P = 0.4). In the long-term study, fat mass was 4.7 ± 2.0 at baseline and 5.0 ± 4.5 kg after 6 months (n = 4; P = 0.9) and lean mass was 30.3 ± 2.4 at baseline and 29.2 ± 21.1 kg after 6 months (n = 4; P = 0.1).
Tissue sampling results
After 2 weeks of liothyronine, muscle tissue showed a 4-fold increase in GLUT4 expression, a 3-fold increased UCP1 expression, no change in UCP3 expression, and a decrease in GLUT1 and deiodinase type 3 expression (Fig. 6). In WAT tissue, neither GLUT4 nor GLUT1 upregulation was observed, WAT markers (LEP and HOXC8) were downregulated, and no change in beige adipocyte markers (CD137, TMEM16, TBX1) was seen. Analysis of BAT markers showed no change in UCP1 expression but an 11-fold increase in ZIC1. Because of the small sample size, no statistical analysis was performed.
Figure 6.
Relative expression of mRNA in muscle (n = 2) and WAT (n = 1) after 2 weeks of liothyronine compared with baseline. No statistical comparisons were performed because of small sample size. The most marked changes were a 4-fold increase in expression of the glucose transporter GLUT4 in muscle (but not WAT), and a 12-fold increase in the brown adipose tissue marker ZIC1 in WAT after liothyronine. Abbreviations: CD137 – cluster of differentiation 137; GLUT 1 and 4, glucose transporters 1 and 4; HOXC8, homeobox C8; LEP, leptin; TBX1, T-box 1; TMEM26, transmembrane protein 26; UCP1 and 3, uncoupling proteins 1 and 3; ZIC1, Zinc finger protein 1; WAT, white adipose tissue.
Safety monitoring
There was slight but significant decrease in weight after 2 weeks of liothyronine from 48.6 ± 9 at baseline to 47.9 ± 9 kg (P = 0.03). In subjects participating in the long-term study, no weight change was observed after 6 months of liothyronine (34 ± 3 at baseline vs 35 ± 3 kg after 6 months; P = 0.3). No difference in heart rate or blood pressure was observed during 2 weeks or 6 months of liothyronine. BMD did not change before vs after 6 months of liothyronine (0.74 ± 0.08 vs 0.72 ± 0.06 g/m2 for spine; 0.62 ± 0.1 vs 0.62 ± 0.1 g/m2 for femoral neck; 0.68 ± 0.09 vs 0.67 ± 0.1 g/m2 for total hip; 0.60 ± 0.09 vs 0.62 ± 0.07 g/m2 for 1/3 forearm. Likewise, there were no significant changes in height-adjusted z score between baseline and 6 months at the spine (-1.14 ± 0.6 vs -1.56 ± 0.7, P = 0.1), total hip (-1.64 ± 0.6 vs -1.92 ± 0.9, P = 0.4), femoral neck (-1.86 ± 0.5 vs -2.1 ± 0.6, P = 0.1), or forearm (-1.6 ± 1.7 vs -1.1 ± 1.1, P = 0.3).
Discussion
Anecdotal evidence suggests that therapeutic administration of thyroid hormone to patients with insulin receptor mutation can enhance glycemic control and activate brown adipose tissue. Thus, we hypothesized that a dose of liothyronine used achieve a state of mild hyperthyroidism without toxicity or patient-reported symptoms would enhance whole-body glucose disposal by increasing skeletal muscle and adipose tissue glucose uptake. We did not find convincing evidence of improvement in the primary outcomes of whole-body glucose disposal after 2 weeks of liothyronine, or in diabetes control measured by HbA1c after 6 months of liothyronine. However, we did observe significant increases in secondary outcomes of whole-body glucose disposal and muscle and WAT glucose uptake after 6 months, but not 2 weeks, of liothyronine treatment.
The idea that thyroid hormone could be used to increase non–insulin-mediated glucose disposal in patients with INSR mutation was derived from a case reported by Skarulis and colleagues (4). In this patient with homozygous INSR mutation, TSH-suppressing doses of levothyroxine for treatment of papillary thyroid cancer for 3 years were associated with improved HbA1c from 9.9% to 5.6% despite discontinuation of insulin and metformin; there was no change in insulin sensitivity assessed by hyperinsulinemic euglycemic clamp. 18F-FDG PET imaging revealed activated BAT during levothyroxine treatment, and biopsy of a supraclavicular focus of 18F-FDG PET uptake showed BAT histologic and gene expression patterns and biopsy of subcutaneous WAT showed gene expression patterns suggestive of “browning.” This observation suggested that the remarkable improvement in hyperglycemia in the presence of INSR mutation was associated with activation of BAT and/or browning of WAT by thyroid hormones. In addition to cold and beta-adrenergic receptor (primarily ß3) stimulation, thyroid hormones are one of the major activators of BAT (22–24). Although the primary substrate used by BAT is FFAs, BAT also takes up glucose, and BAT activation has the potential to increase glucose utilization in individuals with diabetes. Thyroid hormones play an important role in regulation of glucose metabolism. Patients with hyperthyroidism have increased blood glucose in the fasting and postprandial states (25) because of worsening of postreceptor insulin resistance, particularly at the level of the liver (5, 9). In addition to these hyperglycemic effects, thyroid hormones have glucose-lowering effects mediated by increased glucose uptake. In humans, patients with clinically significant hyperthyroidism had a 3-fold increase in glucose uptake in BAT and 1.9-fold increase in glucose uptake in muscle compared with euthyroid controls, which normalized once patients returned to a euthyroid state (26). If we assume that an average human possesses ~50 g of BAT and ~30 000 g of muscle, then BAT would be expected to take up an excess of 0.9 µmol/min of glucose in the hyperthyroid vs the euthyroid state, and muscle to take up an excess of 270 µmol/min of glucose in the hyperthyroid vs the euthyroid state. Thus, in this study, muscle tissue was anticipated to be the major organ taking up excess glucose in the presence of liothyronine treatment. As expected, patients with INSR mutation had increased uptake of labeled glucose by muscle tissue and WAT. Based on our results, muscle glucose uptake doubled after 6 months of liothyronine compared with baseline, similar to the prior report (26). We were not able to quantify the BAT glucose uptake because of the small amount of visible tissue on 18F-FDG PET images.
In the current study, improved fructosamine after 2 weeks of liothyronine was likely an effect of the hospital diet. Similarly, all 4 patients taking insulin required dose reductions during the hospital stay, likely because of the hospital diet. We observed no effect of 2 weeks of liothyronine on glucose uptake by the whole body, muscle, or fat, whereas significant increases in glucose uptake were observed after 6 months without clinically relevant improvement of glycemia. This finding suggests that a prolonged duration of thyroid hormone excess may be required to increase glucose uptake. A 2-week period was chosen as the duration of therapy for the proof-of-concept component of the study based on data showing effects of T3 after 8 to 14 days (5, 9). In the index case, no follow-up data on glycemia were available until 2 years after levothyroxine initiation, and levothyroxine was administered for 3 years before normalization of glycemia. In this study, liothyronine treatment was limited to 6 months to avoid potential adverse effects of long-term hyperthyroidism on bone mineral density and cardiac function. The mild degree of hyperthyroidism achieved in the current study may also have contributed to the lack of clinically relevant glycemic improvement. All patients in the current study had detectable TSH and lacked clinical features of hyperthyroidism including tachycardia, elevated blood pressure, or weight loss. Finally, the lack of clinically relevant changes in glucose disposal in this study might relate to the use of liothyronine, vs levothyroxine used in the index case. Liothyronine was used in this study to permit rapid dose titration during the short-term component of the study. Because the glycemic actions of thyroid hormones are mediated through T3 (27–29), it is unlikely that the use of liothyronine (vs levothyroxine) was responsible for lack of improvement in glycemia. We did observe that insulin doses decreased in some patients undergoing long-term treatment with liothyronine. However, the small number of observations preclude making causal inferences about whether liothyronine decreases insulin requirements, or the mechanism by which this occurs.
Thyroid hormone can also increase blood glucose disposal by upregulation of GLUT4 (30–32). Increased muscle sensitivity to insulin and increased GLUT4 translocation was demonstrated after 10 days of liothyronine in rodents (33). GLUT4 is the predominant insulin-dependent glucose transporter; however, about 30% of GLUT4 expression is insulin-independent (34). We observed a 4-fold increase in GLUT4 mRNA after 2 weeks of liothyronine. Muscle biopsies were not obtained after 6 months of liothyronine, but if GLUT4 upregulation was maintained or further enhanced, this could account for the increased muscle glucose uptake observed after 6 months of liothyronine in this study. Another glucose transporter, GLUT1, is also known to be upregulated by T3 (35, 36) but not T4 (37). However, we did not observe changes in GLUT 1 mRNA expression in muscle or fat tissue in this study.
It is well known that thyroid hormones can cause browning of WAT with overexpression of UCP1 and increased fatty acid oxidation (38). A cross-sectional study in humans demonstrated positive correlations between serum free T4 and browning-related mRNAs (PRDM16, CIDEA, UCP1) in WAT as well as upregulation of BAT markers in WAT after induction of hyperthyroidism in rodents (39). Thus, thyroid hormones can shift WAT toward a more BAT-like gene expression profile. In our study, analysis of mRNA in WAT from a single subject before and after 2 weeks of liothyronine showed downregulation of the WAT markers LEP and HOXC8; no change in the beige adipocyte markers CD137, TMEM16, and TBX1; and an 11-fold increase in ZIC1, a marker of BAT, but with no change in UCP1. These data suggest a possible upregulation of brown, but not beige, adipocytes in WAT after liothyronine.
Thyroid hormone has metabolic actions on lipids, FFA, SHBG, and osteocalcin. Because it was not known if these effects would be present in patients with INSR mutations, we measured metabolic markers of thyroid hormone action. Liothyronine had the expected effects on lipids and SHBG in patients with INSR mutation. However, no changes in FFA or osteocalcin were observed. Osteocalcin is inversely correlated with glycemia in patients with diabetes (40). Thus, any effects of thyroid hormone might be overshadowed by effects of glycemia in our patient cohort. A prior study showed that patients with heterozygous INSR mutation had elevated fasting FFA with impaired FFA suppression after a glucose load, suggesting that lipolysis is already elevated in this condition, presumably resulting from impaired insulin-mediated suppression of lipolysis (41). In this context, the added effects of liothyronine to increase lipolysis may not be measurable.
The strengths of the study are a unique design that can help in understanding of the metabolic effects of thyroid hormone in patients with coexisting metabolic disorders such as extreme insulin resistance, as well as the interactions between thyroid hormone and insulin signaling. The major limitation of this study was small sample size, which was further limited by nonadherence of some patients with liothyronine or antidiabetes medications. Hyperinsulinemic clamps to measure insulin resistance were not performed because a prior publication showed no measurable insulin-mediated glucose disposal in a patient with INSR mutation (4). The lack of improvement in glycemia despite increased glucose uptake may be secondary to increased hepatic glucose production, which was observed after 6 months in this study and is a known effect of thyroid hormone in the general population. In addition, the doses of liothyronine used did not lead to clinical hyperthyroidism and thus may have been inadequate to cause clinically important changes in glycemia. However, to maximize patient safety, we were not able to give doses that led to clinical symptoms or potential adverse long-term effects of liothyronine on the myocardium or bones. Another potential explanation for the lack of improvement in glycemia is the short (6-month) duration of treatment. In the index case, normalization of glycemia was not observed until after 3 years of treatment. Less likely factors for the lack of clinical efficacy include baseline metabolic and adaptive changes in patients with INSR mutation (such as decreased anabolic state or low-fat mass) that might blunt expected responses to thyroid hormones. Finally, it is possible that the dramatic improvement in diabetes after levothyroxine treatment in the index case was due to levothyroxine (vs liothyronine) or not related to thyroid hormone effects. We attempted to identify predictors of response to liothyronine. Only the expected relationships between baseline diabetes control and insulin resistance, and diabetes control during liothyronine treatment, were observed. However, these analyses were limited by small sample size.
Based on these data, liothyronine is unlikely to be an effective therapy for diabetes in patients with INSR mutation when administered at safe doses. However, the increased glucose uptake observed in skeletal muscle and fat tissue after liothyronine support this mechanism as a way to increase insulin-independent glucose disposal. Future studies are needed with more selective agents to increase thyroid hormone effects on tissue glucose uptake without systemic toxicity. One possible candidate is thyroid hormone 3,5-diiodo-L-thyronine, which in rodents reduced body mass and improved glucose tolerance without significant toxicity (42). Thus, further studies exploring effects of 3,5-diiodo-L-thyronine on glucose disposal may be warranted. Using an optimized thyroid hormone–based treatment strategy, it may be possible to achieve clinically meaningful reduction in blood glucose in patients who are genetically incapable of responding to insulin treatment.
Acknowledgments
The authors are grateful to Dr. Phillip Gorden for his expertise and assistance throughout all aspects of this study. The authors are also immensely grateful to the patients who participated in this study, and their families, for their dedication and contribution to science.
Financial Support: This study was supported by the intramural research programs of the National Institute of Diabetes and Digestive and Kidney Diseases, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, and the National Institutes of Health Clinical Center.
Disclosure Summary: The authors have nothing to disclose.
Data Availability: All data generated or analyzed during this study are included in this published article or in the data repositories listed in References.
Glossary
Abbreviations
- 18F-FDG
[18F] fluorodeoxyglucose
- AUC
area under the curve
- BAT
brown adipose tissue
- BMD
bone mineral density
- CD137
cluster of differentiation 137
- CT
computed tomography
- DXA
dual energy x-ray absorptiometry
- FFA
free fatty acid
- fT3
free triiodothyronine
- fT4
free thyroxine
- HbA1c
hemoglobin A1c
- HOXC8
homeobox C8
- LBM
lean body mass
- LEP
leptin
- MRGlu
metabolic rate of glucose uptake
- OGTT
oral glucose tolerance test
- PET
positron emission tomography
- REE
resting energy expenditure
- ROI
region of interest
- SDS
SD score
- SHBG
sex hormone–binding globulin
- SUV
standardized uptake value
- T3
triiodothyronine
- TBX1
T-box 1
- TT3
total triiodothyronine
- TT4
total thyroxine
- TMEM26
transmembrane protein 26
- UCP-3
uncoupling protein 3
- WAT
white adipose tissue
- ZIC1
Zinc finger protein 1
References
- 1. Musso C, Cochran E, Moran SA, Skarulis MC, Oral EA, Taylor S, Gorden P. Clinical course of genetic diseases of the insulin receptor (type A and Rabson-Mendenhall syndromes): a 30-year prospective. Medicine (Baltimore). 2004;83(4):209–222. [DOI] [PubMed] [Google Scholar]
- 2. Cochran E, Musso C, Gorden P. The use of U-500 in patients with extreme insulin resistance. Diabetes Care. 2005;28(5):1240–1244. [DOI] [PubMed] [Google Scholar]
- 3. Brown RJ, Cochran E, Gorden P. Metreleptin improves blood glucose in patients with insulin receptor mutations. J Clin Endocrinol Metab. 2013;98(11):E1749–E1756. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4. Skarulis MC, Celi FS, Mueller E, Zemskova M, Malek R, Hugendubler L, Cochran C, Solomon J, Chen C, Gorden P. Thyroid hormone induced brown adipose tissue and amelioration of diabetes in a patient with extreme insulin resistance. J Clin Endocrinol Metab. 2010;95(1):256–262. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5. Bratusch-Marrain PR, Gasić S, Waldhäusl WK. Triiodothyronine increases splanchnic release and peripheral uptake of glucose in healthy humans. Am J Physiol. 1984;247(5 Pt 1):E681–E687. [DOI] [PubMed] [Google Scholar]
- 6. Segal J. A rapid, extranuclear effect of 3,5,3’-triiodothyronine on sugar uptake by several tissues in the rat in vivo. Evidence for a physiological role for the thyroid hormone action at the level of the plasma membrane. Endocrinology. 1989;124(6):2755–2764. [DOI] [PubMed] [Google Scholar]
- 7. Segal J, Ingbar SH. 3,5,3’-Triiodothyronine increases cellular adenosine 3’,5’-monophosphate concentration and sugar uptake in rat thymocytes by stimulating adenylate cyclase activity: studies with the adenylate cyclase inhibitor MDL 12330A. Endocrinology. 1989;124(5):2166–2171. [DOI] [PubMed] [Google Scholar]
- 8. McAllister RM, Sansone JC Jr, Laughlin MH. Effects of hyperthyroidism on muscle blood flow during exercise in rats. Am J Physiol. 1995;268(1 Pt 2):H330–H335. [DOI] [PubMed] [Google Scholar]
- 9. Dimitriadis G, Baker B, Marsh H, Mandarino L, Rizza R, Bergman R, Haymond M, Gerich J. Effect of thyroid hormone excess on action, secretion, and metabolism of insulin in humans. Am J Physiol. 1985;248(5 Pt 1):E593–E601. [DOI] [PubMed] [Google Scholar]
- 10. Celi FS, Zemskova M, Linderman JD, Smith S, Drinkard B, Sachdev V, Skarulis MC, Kozlosky M, Csako G, Costello R, Pucino F. Metabolic effects of liothyronine therapy in hypothyroidism: a randomized, double-blind, crossover trial of liothyronine versus levothyroxine. J Clin Endocrinol Metab. 2011;96(11):3466–3474. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11. Celi FS, Zemskova M, Linderman JD, Babar NI, Skarulis MC, Csako G, Wesley R, Costello R, Penzak SR, Pucino F. The pharmacodynamic equivalence of levothyroxine and liothyronine: a randomized, double blind, cross-over study in thyroidectomized patients. Clin Endocrinol (Oxf). 2010;72(5):709–715. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12. Summary of revisions: standards of medical care in diabetes-2019. Diabetes Care. 2019;42(Suppl 1):S4–S6. doi:10.2337/dc19-Srev01 [DOI] [PubMed] [Google Scholar]
- 13. Brown RJ, Valencia A, Startzell M, Cochran E, Walter PJ, Garraffo HM, Cai H, Gharib AM, Ouwerkerk R, Courville AB, Bernstein S, Brychta RJ, Chen KY, Walter M, Auh S, Gorden P. Metreleptin-mediated improvements in insulin sensitivity are independent of food intake in humans with lipodystrophy. J Clin Invest. 2018;128(8):3504–3516. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14. Wolfe R, Chinkes DL.. Isotopic Tracers in Metabolic Research: Principles and Practice of Kinetic Analysis. 2nd ed Hoboken, NJ: John Wiley & Sons, Inc; 2005. [Google Scholar]
- 15. Virtanen KA, Peltoniemi P, Marjamäki P, Asola M, Strindberg L, Parkkola R, Huupponen R, Knuuti J, Lönnroth P, Nuutila P. Human adipose tissue glucose uptake determined using [(18)F]-fluoro-deoxy-glucose ([(18)F]FDG) and PET in combination with microdialysis. Diabetologia. 2001;44(12):2171–2179. [DOI] [PubMed] [Google Scholar]
- 16. Peltoniemi P, Lönnroth P, Laine H, Oikonen V, Tolvanen T, Grönroos T, Strindberg L, Knuuti J, Nuutila P. Lumped constant for [(18)F]fluorodeoxyglucose in skeletal muscles of obese and nonobese humans. Am J Physiol Endocrinol Metab. 2000;279(5):E1122–E1130. [DOI] [PubMed] [Google Scholar]
- 17. Zemel BS, Leonard MB, Kelly A, Lappe JM, Gilsanz V, Oberfield S, et al. Height adjustment in assessing dual energy x-ray absorptiometry measurements of bone mass and density in children. J Clin Endocrinol Metab. 2010;95(3):1265–73. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18. Chen KY, Muniyappa R, Abel BS, Mullins KP, Staker P, Brychta RJ, Zhao X, Ring M, Psota TL, Cone RD, Panaro BL, Gottesdiener KM, Van der Ploeg LH, Reitman ML, Skarulis MC. RM-493, a melanocortin-4 receptor (MC4R) agonist, increases resting energy expenditure in obese individuals. J Clin Endocrinol Metab. 2015;100(4):1639–1645. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19. de Jonge L, Nguyen T, Smith SR, Zachwieja JJ, Roy HJ, Bray GA. Prediction of energy expenditure in a whole body indirect calorimeter at both low and high levels of physical activity. Int J Obes Relat Metab Disord. 2001;25(7):929–934. [DOI] [PubMed] [Google Scholar]
- 20. Brychta RJ, Rothney MP, Skarulis MC, Chen KY. Optimizing energy expenditure detection in human metabolic chambers. Conf Proc IEEE Eng Med Biol Soc. 2009;2009:6864–6868. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21. Rothney MP, Brychta RJ, Schaefer EV, Chen KY, Skarulis MC. Body composition measured by dual-energy X-ray absorptiometry half-body scans in obese adults. Obesity (Silver Spring). 2009;17(6):1281–1286. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22. Harms M, Seale P. Brown and beige fat: development, function and therapeutic potential. Nat Med. 2013;19(10):1252–1263. [DOI] [PubMed] [Google Scholar]
- 23. Virtanen KA, Lidell ME, Orava J, Heglind M, Westergren R, Niemi T, Taittonen M, Laine J, Savisto NJ, Enerbäck S, Nuutila P. Functional brown adipose tissue in healthy adults. N Engl J Med. 2009;360(15):1518–1525. [DOI] [PubMed] [Google Scholar]
- 24. Bianco AC, Silva JE. Intracellular conversion of thyroxine to triiodothyronine is required for the optimal thermogenic function of brown adipose tissue. J Clin Invest. 1987;79(1):295–300. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25. Maratou E, Hadjidakis DJ, Peppa M, Alevizaki M, Tsegka K, Lambadiari V, Mitrou P, Boutati E, Kollias A, Economopoulos T, Raptis SA, Dimitriadis G. Studies of insulin resistance in patients with clinical and subclinical hyperthyroidism. Eur J Endocrinol. 2010;163(4):625–630. [DOI] [PubMed] [Google Scholar]
- 26. Lahesmaa M, Orava J, Schalin-Jäntti C, Soinio M, Hannukainen JC, Noponen T, Kirjavainen A, Iida H, Kudomi N, Enerbäck S, Virtanen KA, Nuutila P. Hyperthyroidism increases brown fat metabolism in humans. J Clin Endocrinol Metab. 2014;99(1):E28–E35. [DOI] [PubMed] [Google Scholar]
- 27. Brenta G. Why can insulin resistance be a natural consequence of thyroid dysfunction? J Thyroid Res. 2011;2011:152850. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28. Cheng SY, Leonard JL, Davis PJ. Molecular aspects of thyroid hormone actions. Endocr Rev. 2010;31(2):139–170. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29. Lin HY, Sun M, Tang HY, Lin C, Luidens MK, Mousa SA, Incerpi S, Drusano GL, Davis FB, Davis PJ. L-Thyroxine vs. 3,5,3’-triiodo-L-thyronine and cell proliferation: activation of mitogen-activated protein kinase and phosphatidylinositol 3-kinase. Am J Physiol Cell Physiol. 2009;296(5):C980–C991. [DOI] [PubMed] [Google Scholar]
- 30. Casla A, Rovira A, Wells JA, Dohm GL. Increased glucose transporter (GLUT4) protein expression in hyperthyroidism. Biochem Biophys Res Commun. 1990;171(1):182–188. [DOI] [PubMed] [Google Scholar]
- 31. Weinstein SP, O’Boyle E, Haber RS. Thyroid hormone increases basal and insulin-stimulated glucose transport in skeletal muscle. The role of GLUT4 glucose transporter expression. Diabetes. 1994;43(10):1185–1189. [DOI] [PubMed] [Google Scholar]
- 32. Brunetto EL, Teixeira Sda S, Giannocco G, Machado UF, Nunes MT. T3 rapidly increases SLC2A4 gene expression and GLUT4 trafficking to the plasma membrane in skeletal muscle of rat and improves glucose homeostasis. Thyroid. 2012;22(1):70–79. [DOI] [PubMed] [Google Scholar]
- 33. Dimitriadis G, Parry-Billings M, Bevan S, Leighton B, Krause U, Piva T, Tegos K, Challiss RA, Wegener G, Newsholme EA. The effects of insulin on transport and metabolism of glucose in skeletal muscle from hyperthyroid and hypothyroid rats. Eur J Clin Invest. 1997;27(6):475–483. [DOI] [PubMed] [Google Scholar]
- 34. Boersma GJ, Johansson E, Pereira MJ, Heurling K, Skrtic S, Lau J, Katsogiannos P, Panagiotou G, Lubberink M, Kullberg J, Ahlström H, Eriksson JW. Altered glucose uptake in muscle, visceral adipose tissue, and brain predict whole-body insulin resistance and may contribute to the development of type 2 diabetes: a combined PET/MR study. Horm Metab Res. 2018;50(8):627–639. [DOI] [PubMed] [Google Scholar]
- 35. Ulisse S, Jannini EA, Pepe M, De Matteis S, D’Armiento M. Thyroid hormone stimulates glucose transport and GLUT1 mRNA in rat Sertoli cells. Mol Cell Endocrinol. 1992;87(1-3):131–137. [DOI] [PubMed] [Google Scholar]
- 36. Teixeira SS, Tamrakar AK, Goulart-Silva F, Serrano-Nascimento C, Klip A, Nunes MT. Triiodothyronine acutely stimulates glucose transport into L6 muscle cells without increasing surface GLUT4, GLUT1, or GLUT3. Thyroid. 2012;22(7):747–754. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37. Ding Y, Tian Y, Guo M, Liu J, Heng D, Zhu B, Yang Y, Zhang C. Regulation of glucose transport by thyroid hormone in rat ovary. Cell Tissue Res. 2016;366(2):455–466. [DOI] [PubMed] [Google Scholar]
- 38. Weiner J, Kranz M, Klöting N, Kunath A, Steinhoff K, Rijntjes E, Köhrle J, Zeisig V, Hankir M, Gebhardt C, Deuther-Conrad W, Heiker JT, Kralisch S, Stumvoll M, Blüher M, Sabri O, Hesse S, Brust P, Tönjes A, Krause K. Thyroid hormone status defines brown adipose tissue activity and browning of white adipose tissues in mice. Sci Rep. 2016;6:38124. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39. Martínez-Sánchez N, Moreno-Navarrete JM, Contreras C, Rial-Pensado E, Fernø J, Nogueiras R, Diéguez C, Fernández-Real JM, López M. Thyroid hormones induce browning of white fat. J Endocrinol. 2017;232(2):351–362. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40. Guarneri MP, Weber G, Gallia P, Chiumello G. Effect of insulin treatment on osteocalcin levels in diabetic children and adolescents. J Endocrinol Invest. 1993;16(7):505–509. [DOI] [PubMed] [Google Scholar]
- 41. Semple RK, Sleigh A, Murgatroyd PR, Adams CA, Bluck L, Jackson S, Vottero A, Kanabar D, Charlton-Menys V, Durrington P, Soos MA, Carpenter TA, Lomas DJ, Cochran EK, Gorden P, O’Rahilly S, Savage DB. Postreceptor insulin resistance contributes to human dyslipidemia and hepatic steatosis. J Clin Invest. 2009;119(2):315–322. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42. Senese R, de Lange P, Petito G, Moreno M, Goglia F, Lanni A. 3,5-Diiodothyronine: a novel thyroid hormone metabolite and potent modulator of energy metabolism. Front Endocrinol (Lausanne). 2018;9:427. [DOI] [PMC free article] [PubMed] [Google Scholar]