Growth Hormone Mediators and Glycemic Control in Youths With Type 2 Diabetes: A Secondary Analysis of a Randomized Clinical Trial

Chang Lu; Danielle Wolfs; Laure El ghormli; Lynne L Levitsky; Lorraine E Levitt Katz; Lori M Laffel; Mary-Elizabeth Patti; Elvira Isganaitis

doi:10.1001/jamanetworkopen.2024.0447

. 2024 Feb 29;7(2):e240447. doi: 10.1001/jamanetworkopen.2024.0447

Growth Hormone Mediators and Glycemic Control in Youths With Type 2 Diabetes

A Secondary Analysis of a Randomized Clinical Trial

Chang Lu ^1,², Danielle Wolfs ², Laure El ghormli ³, Lynne L Levitsky ⁴, Lorraine E Levitt Katz ⁵, Lori M Laffel ^1,², Mary-Elizabeth Patti ², Elvira Isganaitis ^2,^✉

¹Division of Endocrinology, Boston Children’s Hospital, Harvard Medical School, Boston, Massachusetts

²Joslin Diabetes Center, Harvard Medical School, Boston, Massachusetts

³The Biostatistics Center, George Washington University, Washington, DC

⁴Division of Pediatric Endocrinology and Diabetes, Massachusetts General Hospital, Harvard Medical School, Boston

⁵Division of Endocrinology and Diabetes, Children’s Hospital of Philadelphia, The Perelman School of Medicine at the University of Pennsylvania, Philadelphia

Accepted for Publication: January 6, 2024.

Published: February 29, 2024. doi:10.1001/jamanetworkopen.2024.0447

^✉

Corresponding Author: Elvira Isganaitis, MD, MPH, Joslin Diabetes Center, Harvard Medical School, One Joslin Place, Room 655A, Boston, MA 02215 (elvira.isganaitis@joslin.harvard.edu).

Author Contributions: Dr Isganaitis had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Concept and design: Lu, Patti, Isganaitis.

Acquisition, analysis, or interpretation of data: All authors.

Drafting of the manuscript: Lu, El ghormli, Levitsky, Isganaitis.

Critical review of the manuscript for important intellectual content: Lu, Wolfs, Levitsky, Levitt Katz, Laffel, Patti, Isganaitis.

Statistical analysis: Lu, El ghormli, Isganaitis.

Obtained funding: Isganaitis.

Administrative, technical, or material support: Wolfs, Patti, Isganaitis.

Supervision: Levitsky, Laffel, Patti, Isganaitis.

Conflict of Interest Disclosures: Dr Levitsky reported receiving grants from the National Institutes of Health during the conduct of the study; and personal fees from Eli Lilly Co outside the submitted work. Dr Laffel reported receiving grants from Boehringer Ingelheim; and personal fees from Lilly, NovoNordisk, Vertex, Mannkind, Roche, Janssen, Dexccom, and Medtronic outside the submitted work. Dr Patti reported receiving grants from Dexcom; personal fees from Hanmi, MBX, and AstraZeneca; and serving on the data safety monitoring board for Fractyl outside the submitted work. Dr Isganaitis reported receiving grants from the National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) during the conduct of the study; and grants from the NIDDK, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, Insulet, the Helmsley Foundation, Tandem, and MannKind outside the submitted work. No other disclosures were reported.

Data Sharing Statement: See Supplement 3.

Additional Contributions: We thank all members of the TODAY Study Group. A complete list of individuals can be found in the appendix of the original publication at https://www.nejm.org/doi/suppl/10.1056/NEJMoa2100165/suppl_file/nejmoa2100165_appendix.pdf. The TODAY Study Group thanks the following companies for donations in support of the study’s efforts: Becton, Dickinson and Co; Bristol Myers Squibb; Eli Lilly and Co; GlaxoSmithKline; LifeScan Inc; Pfizer; and Sanofi Aventis. We gratefully acknowledge the participation and guidance of the American Indian partners associated with the clinical center located at the University of Oklahoma Health Sciences Center, including members of the Absentee Shawnee Tribe, Cherokee Nation, Chickasaw Nation, Choctaw Nation of Oklahoma, and Oklahoma City Area Indian Health Service; the opinions expressed in this article are those of the authors and do not necessarily reflect the views of the respective Tribes and the Indian Health Service.

^✉

Corresponding author.

PMCID: PMC10905312 PMID: 38421647

Key Points

Question

Are changes in mediators of growth hormone signaling during puberty associated with characteristics of youth-onset type 2 diabetes (T2D)?

Findings

In this post hoc secondary analysis of a randomized clinical trial of 398 participants with youth-onset T2D, changes from baseline to 3 years in plasma concentrations of growth hormone mediators, including insulin-like growth factor-1, growth hormone receptor, and insulin-like growth factor binding protein 1, were associated with glycemic failure and measures of insulin resistance and beta cell function.

Meaning

These data suggest that growth hormone mediators may be associated with the unique phenotype of pediatric T2D.

Abstract

Importance

Youth-onset type 2 diabetes (T2D) has a more aggressive phenotype than adult-onset T2D, including rapid loss of glycemic control and increased complication risk.

Objective

To identify associations of growth hormone mediators with glycemic failure, beta cell function, and insulin sensitivity in youth-onset T2D.

Design, Setting, and Participants

This post hoc secondary analysis of the Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) randomized clinical trial, which enrolled participants from July 2004 to February 2009, included 398 participants from 15 university-affiliated medical centers with available plasma samples from baseline and 36 months. Participants were youths aged 10 to 17 years with a duration of T2D of less than 2 years who were randomized to metformin, metformin plus lifestyle intervention, or metformin plus rosiglitazone. Participants were followed up for a mean (SD) of 3.9 (1.5) years during the trial, ending in 2011. Statistical analysis was performed from August 2022 to November 2023.

Exposure

Plasma insulin-like growth factor-1 (IGF-1), growth hormone receptor (GHR), and insulin-like growth factor binding protein 1 (IGFBP-1).

Main Outcomes and Measures

Main outcomes were (1) loss of glycemic control during the TODAY study, defined as hemoglobin A_1c (HbA_1c) level of 8% or more for 6 months or inability to wean from insulin therapy, and (2) baseline and 36-month measures of glycemia (fasting glucose, HbA_1c), insulin sensitivity (1/fasting C-peptide), high-molecular-weight adiponectin, and beta cell function (C-peptide index, C-peptide oral disposition index).

Results

This analysis included 398 participants (mean [SD] age, 13.9 [2.0] years; 248 girls [62%]; 166 Hispanic participants [42%]; 134 non-Hispanic Black participants [34%], and 84 non-Hispanic White participants [21%]). A greater increase in IGF-1 level between baseline and 36 months was associated with lower odds of glycemic failure (odds ratio [OR], 0.995 [95% CI, 0.991-0.997]; P < .001) and higher C-peptide index per 100-ng/mL increase in IGF-1 (β [SE], 0.015 [0.003]; P < .001). A greater increase in log₂ GHR level between baseline and 36 months was associated with higher odds of glycemic failure (OR, 1.75 [95% CI, 1.05-2.99]; P = .04) and lower C-peptide index (β [SE], −0.02 [0.006]; P < .001). A greater increase in log₂ IGFBP-1 level between baseline and 36 months was associated with higher odds of glycemic failure (OR, 1.37 [95% CI, 1.09-1.74]; P = .007) and higher high-molecular-weight adiponectin (β [SE], 431 [156]; P = .007).

Conclusions and Relevance

This study suggests that changes in plasma growth hormone mediators are associated with loss of glycemic control in youth-onset T2D, with IGF-1 associated with lower risk and GHR and IGFBP-1 associated with increased risk.

Trial Registration

ClinicalTrials.gov Identifier: NCT00081328

This secondary analysis of a randomized clinical trial examines associations of growth hormone mediators with glycemic failure, beta cell function, and insulin sensitivity in youth-onset type 2 diabetes.

Introduction

Type 2 diabetes (T2D), once considered a disease of aging, has reached unprecedented levels among children and adolescents and disproportionately affects Black, Hispanic, and socioeconomically disadvantaged youths.¹ Compared with adults with T2D, children with T2D have more severe insulin resistance and accelerated beta cell failure, yet therapies for children are limited and less effective.^2,3 Treatment Options for Type 2 Diabetes in Adolescents and Youth (TODAY) was a multicenter, longitudinal study of youth-onset T2D.⁴ In the primary randomized clinical trial phase of the study (N = 699), nearly half the participants reached the primary outcome of glycemic failure within 4 years.⁵ In the observational phase of the study (termed TODAY2), 60% of participants developed complications in the 10-year follow-up period, highlighting the aggressive natural history of youth-onset T2D.⁶

The mechanisms underlying rapidly worsening glycemia and beta cell function in youth-onset T2D remain unclear. Among children, T2D occurs almost exclusively during or after puberty, suggesting that hormonal dynamics may play a role in the pathogenesis and/or progression.^7,8,9 Puberty is marked by activation of sex hormones and peak secretion of growth hormone (GH) and its effectors.¹⁰ Growth hormone signaling may have complex effects on carbohydrate metabolism through several mediators, including insulin-like growth factor-1 (IGF-1), growth hormone receptor (GHR), and IGF binding proteins (IGFBPs).^11,12,13 These GH mediators may directly or indirectly affect body composition, insulin sensitivity, and insulin secretion, potentially influencing the emergence of T2D and its natural history.

Thus, our objective was to study associations of GH mediators with measures of glycemic control, insulin sensitivity, and beta cell function, using samples from the TODAY study cohort at baseline and at 36 months—a time point at which most of the cohort had completed puberty and approximately half the participants had a loss of glycemic control.⁵ We hypothesized that baseline concentrations of, and changes in, IGF-1, GHR, and IGFBP-1 from baseline to 36 months may be associated with the primary outcome of glycemic failure in the TODAY trial. Secondarily, we hypothesized that plasma IGF-1, GHR, and IGFBP-1 concentrations would be associated with measures of glycemia, insulin sensitivity, and beta cell function.

Methods

TODAY Study Design and Cohort

The TODAY study design, methods, and results have been previously reported (study protocol in Supplement 1).⁵ In brief, TODAY was a randomized clinical trial in which 699 youths were enrolled from 15 US clinical centers between July 2004 and February 2009, based on inclusion criteria of age 10 to 17 years, T2D duration less than 2 years, body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) in the 85th percentile or higher, negative pancreatic autoantibodies, and plasma C-peptide level greater than 0.6 ng/mL (to convert to nanomoles per liter, multiply by 0.331) (eFigure 1 in Supplement 2). Participants were randomized to metformin monotherapy, metformin plus lifestyle intervention, or metformin plus rosiglitazone. Participants were followed up for 2 to 6.5 years (mean [SD] follow-up, 3.9 [1.5] years) within the initial TODAY trial; the primary outcome was time to glycemic failure, defined as hemoglobin A_1c (HbA_1c) level of 8% or more (to convert to proportion of total hemoglobin, multiply by 0.01; to convert to mmol/mol, multiply by 10.93 and subtract 23.5) for 6 months, or acute metabolic decompensation requiring insulin. Participants were then transitioned from study medications to diabetes care in the community. Physical examinations and anthropometric measurements were obtained throughout the study. Tanner stage was based on physical examination of breasts and pubic hair for girls and testicular volume and pubic hair for boys and dichotomized to Tanner stage 1, 2, and 3 vs Tanner stage 4 and 5. The following post hoc analyses used all remaining stored plasma samples from the baseline and 36-month time points (n = 398). Time-to-event survival analysis of this substudy cohort demonstrated similar rates of glycemic failure as reported in the full cohort (N = 699) (eFigure 2 in Supplement 2).⁵ Of the subset, 310 participants had available samples at both baseline and 36 months. To assess potential effects of missing data, we compared the subgroup of 310 individuals with paired samples vs the 88 individuals with only baseline samples (eTables 2 and 4 in Supplement 2) and performed sensitivity analyses with the full subcohort (n = 398) vs those with paired samples (n = 310). All 15 TODAY study centers (Baylor College of Medicine, Case Western Reserve University, Children's Hospital Los Angeles, Children's Hospital of Philadelphia, Children's Hospital of Pittsburgh, Columbia University Medical Center, Joslin Diabetes Center, Massachusetts General Hospital, Saint Louis University, State University of New York Upstate Medical University, University of Colorado Denver, University of Oklahoma Health Sciences Center, University of Texas Health Science Center at San Antonio, Washington University in St Louis, and Yale University) obtained institutional review board approval and written informed assent and/or consent from participants and parents or guardians. This report followed the Consolidated Standards of Reporting Trials (CONSORT) reporting guideline for randomized studies.

Measures of Glycemia, Insulin Sensitivity, and Insulin Secretion

Assessments of glycemia in TODAY included HbA_1c level and a 2-hour oral glucose tolerance test (OGTT) every 6 months during the first year and annually thereafter, at the time of the primary outcome, and at study end. Plasma glucose and C-peptide measurements during the OGTT were used to calculate insulin secretion and sensitivity indices. Insulin sensitivity was assessed as 1/fasting C-peptide.^14,15 Given that fasting C-peptide may be affected by beta cell function, we used high-molecular-weight adiponectin (HMWA) as an additional insulin sensitivity measure.^14,16 C-peptide index, a measure of beta cell function, is calculated as a change in C-peptide from 0 to 30 minutes/change in glucose from 0 to 30 minutes during the OGTT.¹⁷ The C-peptide oral disposition index (CODI), a measure of beta cell insulin secretion in response to insulin resistance, is calculated as the product of 1/fasting insulin × C-peptide index.¹⁷ Wherever possible, we used C-peptide–based indices rather than insulin-based indices to avoid potential confounding by exogenous insulin.

IGF-1, GHR, and IGFBP-1 Assays

We measured IGF-1 using a commercial enzyme-linked immunosorbent assay (ELISA) kit (No. 22-IGFHU-E01; ALPCO) according to manufacturer instructions. Study samples were run once, and standard curves were run in duplicate on 96-well plates. The standards for IGF-1 were fitted to a trinomial curve using a BioTek Gen5 Microplate Reader and Imager Software (No. BTGENSCPRIM; Agilent Technologies Inc). We similarly measured GHR levels using a commercial ELISA kit (No. ab260060; Abcam plc); standards for GHR were fitted to a 4-parameter curve. For IGF-1 and GHR, concentrations were determined by interpolating blank-subtracted absorbances against the standard curve, then multiplying by the dilution factor. Intra-assay and interassay coefficients of variation for control samples were 2.2% and 9.1%, respectively, for IGF-1 and 6.5% and 14.0%, respectively, for GHR. To account for higher inter-assay coefficients of variation, each IGF-1 and GHR sample concentration was scaled to a control sample run in duplicate on all plates. Assays for IGF-1 and GHR were performed between March and August 2022. Insulin-like growth factor binding protein 1 was measured using a magnetic bead-based multiplex protein array (R&D Systems), as reported previously.¹⁸ For IGFBP-1, intra-assay and interassay coefficients of variation were 4.6% to 5.5% and 7.1% to 10.8%, respectively.

Statistical Analysis

Statistical analysis was performed from August 2022 to November 2023. For between-group comparisons of participants with glycemic failure vs glycemic control, we used the t test for continuous variables and the χ² test for categorical variables. We used a paired t test when comparing baseline and 36-month values for the same participant. Growth hormone receptor and IGFBP-1 concentrations were log₂ transformed because the data were not normally distributed. Logged concentrations of GHR and IGFBP-1 were used in all analyses. We performed multivariable logistic regression with covariate adjustment to assess associations of baseline levels or a 36-month change in levels of each hormone (IGF-1, log₂ GHR, and log₂ IGFBP-1) with the odds of glycemic failure. All logistic regression models included sex, age, race and ethnicity, BMI z score, treatment group, baseline HbA_1c level, and Tanner stage; 36-month models additionally adjusted for baseline hormone level. The participant and parent or another knowledgeable adult reported race and ethnicity to a study interviewer. The race and ethnicity categories were determined based on National Institutes of Health reporting guidelines. Race and ethnicity were recorded to corroborate that the demographic characteristics of our cohort are representative of the epidemiology of T2D in youths. In addition, reporting of race and ethnicity allowed us to include these as covariates in adjusted models. We used multivariable linear regression to assess the association of baseline levels or a 36-month change in levels of each hormone with metabolic measures, including HbA_1c level, fasting glucose, 1/fasting C-peptide, HMWA, C-peptide index, and CODI. All linear models adjusted for sex, age, race and ethnicity, BMI z score, and Tanner stage, and 36-month models additionally adjusted for treatment group, baseline glycemic measure, and baseline hormone levels. In reporting analyses including IGF-1, a ×100 multiplier was applied to the β coefficients and SEs to facilitate interpretation of the results. P < .05 was considered statistically significant. Statistical analyses were performed using R, version 2023.03.0+386 (R Project for Statistical Computing) and Prism, version 9.5.0 (GraphPad).

Results

Demographic Characteristics

A subset of 398 participants (mean [SD] age, 13.9 [2.0] years; 248 girls [62%]; 166 Hispanic participants [42%]; 134 non-Hispanic Black participants [34%], and 84 non-Hispanic White participants [21%]) from the TODAY study were included in this ancillary analysis (eTable 1 in Supplement 2). Of these, 310 participants had both baseline and 36-month samples, and 88 participants had only baseline samples available for analysis. A total of 182 participants (46%) reached the primary outcome of glycemic failure, whereas 216 participants (54%) maintained glycemic control. By 36 months, 164 of 182 participants (90%) in the glycemic failure group had reached the primary outcome (mean [SD] time to primary outcome, 15.2 [9.8] months); 18 of 182 participants (10%) in this group had a loss of glycemic control by the end of the 5-year randomized clinical trial phase of the TODAY study. At baseline, participants had a mean (SD) BMI z score of 2.2 (0.5) and 353 of 392 participants (90%) had a Tanner stage of 4 or 5. Compared with the glycemic control group, the glycemic failure group included more Hispanic and non-Hispanic Black participants (Hispanic, 45% [82 of 182] vs 39% [84 of 216]; non-Hispanic Black, 37% [68 of 1820] vs 31% [66 of 216]; P = .02) and had a longer T2D duration (mean [SD] duration, 8.2 [6.0] months vs 7.0 [5.4] months; P = .04). Subgroup analysis comparing participants with samples at both time points (n = 310) with those with only baseline samples (n = 88) showed that the 2 subgroups were similar except for slightly older age and lower height among those with baseline samples only (eTable 2 in Supplement 2). Given these differences, we performed sensitivity analyses in which we repeated all analyses for the 310 participants with paired samples; we found similar associations of GH mediators with glycemic measures, with any differences noted.

Measures of Glycemia, Insulin Sensitivity, and Beta Cell Function

Glycemic measures in the TODAY study have been reported previously.¹⁷ The mean (SD) HbA_1c level was 6.1% (0.8%) at baseline and 7.7% (2.6%) at 36 months. Compared with the glycemic control group at baseline, the glycemic failure group had higher HbA_1c levels, fasting glucose levels, and 2-hour OGTT glucose values and lower C-peptide levels, C-peptide indexes, and CODI values. At 36 months, all measures of glycemia, insulin sensitivity, and beta cell function were worse in the glycemic failure group compared with the glycemic control group (eTable 3 in Supplement 2).

GH Mediators and Loss of Glycemic Control

We tested whether GH mediators changed between baseline and 36 months and whether they differed based on glycemic outcome. Levels of GH mediators did not differ based on TODAY treatment group assignment but did differ between the glycemic control and glycemic failure groups. Compared with the glycemic control group, the glycemic failure group had lower plasma IGF-1 levels at baseline (mean [SD] level, 367 [141] ng/mL vs 396 [132] ng/mL; P = .03) and at 36 months (mean [SD] level, 282 [106] ng/mL vs 332 [124] ng/mL; P < .001) (Figure, A). The mean IGF-1 level was lower at 36 months than at baseline in both the glycemic failure group (mean [SD] level, 282 [106] ng/mL vs 367 [141] ng/mL; P < .001) and glycemic control group (mean [SD] level, 332 [124] ng/mL vs 396 [132] ng/mL; P < .001). The mean plasma log₂ GHR level was higher in the glycemic failure group than in the glycemic control group at 36 months only (mean [SD] level, 5.5 [0.6] ng/mL vs 5.3 [0.6] ng/mL; P = .03) and did not differ between baseline and 36 months for either group (Figure, B). The mean plasma log₂ IGFBP-1 levels increased from baseline to 36 months within each outcome group (mean [SD] level, 1.6 [1.5] ng/mL vs 2.3 [1.7] ng/L in the glycemic failure group; P < .001; mean [SD] level, 1.4 [1.2] vs 1.8 [1.6] ng/mL in the glycemic control group; P < .001), but they were higher in the glycemic failure group compared with the glycemic control group at 36 months only (mean [SD] level, 2.3 [1.7] ng/L vs 1.8 [1.6] ng/mL; P = .009) (Figure, C).

Figure. — Plasma concentrations of insulin-like growth factor-1 (IGF-1) (n = 310), growth hormone receptor (GHR) (n = 310), and insulin-like growth factor binding protein 1 (IGFBP-1) (n = 286) between trial outcome groups that lost glycemic control vs maintained glycemic control at baseline and 36 months. P values refer to the 2-tailed paired t test (for baseline vs 36-month comparisons) and the unpaired t test (for glycemic failure vs glycemic control groups).

^aP < .001.

^bP < .05.

^cP < .01.

We next used logistic regression to determine whether GH mediator concentrations were associated with the odds of glycemic failure during the TODAY trial, adjusting for sex, age, race and ethnicity, BMI z score, treatment group, baseline HbA_1c level, and Tanner stage in all models and additionally for baseline hormone level in the 36-month model. Baseline IGF-1, log₂ GHR, and log₂ IGFBP-1 levels were not associated with odds of glycemic failure. By contrast, changes in GH mediators between baseline and 36 months were significantly associated with odds of glycemic failure. An increase in IGF-1 level from baseline to 36 months was associated with lower odds of glycemic failure (odds ratio [OR], 0.995 [95% CI, 0.991-0.997]; P < .001; Table 1) and higher C-peptide index per 100-ng/mL increase in IGF-1 level (β [SE], 0.015 [0.003]; P < .001; Table 2). An increase in log₂ GHR level from baseline to 36 months was associated with higher odds of glycemic failure (OR, 1.75 [95% CI, 1.05-2.99]; P = .04; Table 1) and lower C-peptide index (β [SE], −0.02 [0.006]; P < .001; Table 3). Similarly, an increase in log₂ IGFBP-1 level between baseline and 36 months was associated with higher odds of glycemic failure (OR, 1.37 [95% CI, 1.09-1.74]; P = .007; Table 1) and higher high-molecular-weight adiponectin (β [SE], 431 [156]; P = .007; Table 4).

Table 1. Associations of Plasma Hormone Levels With Odds of Primary Outcome in the Treatment Options for Type 2 Diabetes in Adolescents and Youth Study.

Multivariable model	Odds ratio (95% CI)	P value^a
IGF-1 level
Baseline^b	0.999 (0.997-1.000)	.18
Change from baseline to 36 mo^c	0.995 (0.991-0.997)	<.001
Log² GHR level
Baseline^b	1.17 (0.68-2.01)	.57
Change from baseline to 36 mo^c	1.75 (1.05-2.99)	.04
Log₂ IGFBP-1 level
Baseline^b	1.07 (0.90-1.29)	.44
Change from baseline to 36 mo^c	1.37 (1.09-1.74)	.007

Open in a new tab

Abbreviations: GHR, growth hormone receptor; IGF-1, insulin-like growth factor-1; IGFBP-1, insulin-like growth factor binding protein 1.

^{^a}

From logistic regression models with covariate adjustments.

^{^b}

Adjusted for sex, age, race, body mass index z score, treatment group, baseline hemoglobin A_1c, and Tanner stage.

^{^c}

Adjusted for sex, age, race, body mass index z score, treatment group, baseline hemoglobin A_1c, Tanner stage, and baseline hormone level.

Table 2. Associations of Plasma IGF-1 Levels With Glycemic Measures at Baseline and 36 Months^a.

Glycemic measure	Baseline IGF-1 vs baseline glycemic measures^b		Change in IGF-1 vs 36-mo glycemic measures^c
Glycemic measure	β (SE) × 100	P value	β (SE) × 100	P value
Hemoglobin A_1c, %	−0.08 (0.03)	.01	−0.66 (0.14)	<.001
Fasting glucose, mg/dL	−2.0 (1.0)	.06	−20.0 (4.0)	<.001
1/Fasting C-peptide, mL/ng	−0.008 (0.005)	.14	−0.08 (0.09)	.40
HMWA, ng/mL	58 (76)	.44	620 (212)	.004
C-peptide index, ng/mL per mg/dL	0.005 (0.003)	.12	0.015 (0.003)	<.001
CODI, mL/uU × ng/mL per mg/dL	0.0002 (0.0002)	.32	0.0008 (0.0002)	<.001

Open in a new tab

Abbreviations: CODI, C-peptide oral disposition index; HMWA, high-molecular-weight adiponectin; IGF-1, insulin-like growth factor-1.

^{^a}

Data are β coefficients and SE from linear regression models, multiplied by 100, with associated P values.

^{^b}

Adjusted for sex, age, race, baseline body mass index z score, and Tanner stage.

^{^c}

Adjusted for sex, age, race, baseline body mass index z score, Tanner stage, treatment group, baseline glycemic measure, and baseline IGF-1.

Table 3. Associations of Plasma Log₂ GHR Levels With Glycemic Measures at Baseline and 36 Months^a.

Glycemic measure	Baseline log₂ GHR vs baseline glycemic measures^b		Change in log₂ GHR vs 36-mo glycemic measures^c
Glycemic measure	β (SE)	P value	β (SE)	P value
Hemoglobin A_1c, %	0.36 (0.09)	<.001	0.96 (0.26)	<.001
Fasting glucose, mg/dL	11.4 (2.7)	<.001	43.4 (7.9)	<.001
1/Fasting C-peptide, mL/ng	−0.09 (−0.01)	<.001	−0.02 (0.17)	.93
HMWA, ng/mL	−735 (204)	<.001	−1340 (390)	<.001
C-peptide index, ng/mL per mg/dL	−0.01 (0.008)	.19	−0.02 (0.006)	<.001
CODI, mL/uU × ng/mL per mg/dL	−0.001 (0.0005)	.01	−0.002 (0.0003)	<.001

Open in a new tab

Abbreviations: CODI, C-peptide oral disposition index; GHR, growth hormone receptor; HMWA, high-molecular-weight adiponectin.

^{^a}

Data are β coefficients, SE, and P values from linear regression models with covariate adjustments.

^{^b}

Adjusted for sex, age, race, baseline body mass index z score, and Tanner stage.

^{^c}

Adjusted for sex, age, race, baseline body mass index z score, Tanner stage, treatment group, baseline glycemic measure, and baseline GHR.

Table 4. Associations of Plasma Log₂ IGFBP-1 Levels With Glycemic Measures at Baseline and 36 Months^a.

Glycemic measure	Baseline log₂ IGFBP-1 vs baseline glycemic measures^b		Change in log₂ IGFBP-1 vs 36-mo glycemic measures^c
Glycemic measure	β (SE)	P value	β (SE)	P value
Hemoglobin A_1c, %	0.02 (0.03)	.50	0.43 (0.11)	<.001
Fasting glucose, mg/dL	1.6 (1.0)	.10	19.6 (3.3)	<.001
1/Fasting C-peptide, mL/ng	0.04 (0.005)	<.001	−0.01 (0.07)	.88
HMWA, ng/mL	150 (71)	<.001	431 (156)	.007
C-peptide index, ng/mL per mg/dL	−0.002 (0.003)	.40	−0.007 (0.003)	.15
CODI, mL/uU × ng/mL per mg/dL	0.0001 (0.0002)	.55	0.0001 (0.0002)	.76

Open in a new tab

Abbreviations: CODI, C-peptide oral disposition index; HMWA, high-molecular-weight adiponectin; IGFBP-1, insulin-like growth factor binding protein 1.

^{^a}

Data are β coefficients, SE, and P values from linear regression models with covariate adjustments.

^{^b}

Adjusted for sex, age, race, baseline body mass index z score, and Tanner stage.

^{^c}

Adjusted for sex, age, race, baseline body mass index z score, Tanner stage, treatment group, baseline glycemic measure, and baseline IGFBP-1.

GH Mediators and Glycemic Measures

Insulin-Like Growth Factor-1

We next used linear regression to model the associations of GH mediators with glycemic measures at baseline and 36 months, adjusting for sex, age, race and ethnicity, BMI z score, and Tanner stage. In addition, the 36-month models adjusted for treatment group, baseline glycemic measure, and baseline hormone levels. The β coefficients and SEs were multiplied by 100 to reflect changes in glycemic measures per every 100-ng/mL change in IGF-1 concentration. At baseline, a higher IGF-1 level was associated with a lower HbA_1c level (Table 2). A greater increase in IGF-1 level from baseline to 36 months was associated with lower HbA_1c and fasting glucose levels and higher HMWA, C-peptide index, and CODI at 36 months (Table 2).

Growth Hormone Receptor

At baseline, higher log₂ GHR concentrations were associated with higher HbA_1c and fasting glucose levels and lower 1/fasting C-peptide, HMWA, and CODI (Table 3). A greater increase in log₂ GHR level from baseline to 36 months was associated with higher HbA_1c and fasting glucose levels and lower HMWA, C-peptide index, and CODI at 36 months.

Insulin-Like Growth Factor Binding Protein 1

At baseline, a higher log₂ IGFBP-1 level was associated with higher 1/fasting C-peptide and HMWA (Table 4). A greater increase in log₂ IGFBP-1 level between baseline and 36 months was associated with higher HbA_1c level, fasting glucose level, and HMWA at 36 months. In the sensitivity analysis restricted to the 310 participants with paired samples, the association of baseline log₂ IGFBP-1 level with HMWA was no longer statistically significant; however, the direction of the association remained the same.

Correlations of IGF-1, GHR, and IGFBP-1 Levels

We explored the association between pairs of GH mediators using a Pearson correlation of hormone concentrations at baseline (eFigure 3 in Supplement 2). The log₂ GHR level was inversely correlated with the IGF-1 level (r = −0.33; P < .001) and the log₂ IGFBP-1 level (r = −0.19; P < .001), and the IGF-1 level was inversely correlated with the log₂ IGFBP-1 level (r = −0.13; P = .02).

Discussion

In children, T2D usually emerges during or after puberty, a period of rapid growth. Youth-onset T2D is typically more aggressive than adult-onset T2D, yet no prior studies have tested whether GH or its mediators are associated with glycemic outcomes in youth-onset T2D. Using the TODAY study, one of the largest studies on treatment and natural history of pediatric T2D to our knowledge, we chose to study 3 GH mediators: (1) IGF-1, the primary mediator of GH action; (2) GHR, a surrogate of GH bioavailability and action; and (3) IGFBP-1, a regulator of IGF-1 bioavailability and potential mediator of insulin sensitivity. We identified significant associations between these GH mediators and glycemic outcomes in youths with T2D.

In our analysis, youths with a loss of glycemic control in the TODAY study had lower IGF-1 levels, higher IGFBP-1 levels, and higher GHR levels at 36 months than participants who maintained glycemic control. A greater increase in IGF-1 level between baseline and 36 months was associated with lower odds of glycemic failure, while greater increases in IGFBP-1 and GHR levels were associated with increased odds of glycemic failure. In addition, we found significant correlations among the 3 hormones, which may reflect a direct association between glucose metabolism and GH signaling or a common upstream mechanism causing changes in both processes, such as puberty, obesity, or hepatic insulin resistance. Future studies of the combined signaling effects of GH mediators on glucose metabolism will be important to elucidate the mechanisms underlying these associations.

A greater increase in IGF-1 level between baseline and 36 months was associated with a lower HbA_1c level and higher measures of beta cell function (insulinogenic index, oral disposition index). Although we are not aware of any prior analyses of IGF-1 levels in youth-onset T2D, lower IGF-1 levels have been reported previously in youths with obesity (compared with youths with normal weight) and in adults with obesity and diabetes.^19,20 However, whether a lower IGF-1 level is the cause or result of obesity and diabetes is unclear. In adults with T2D, plasma IGF-1 and C-peptide levels have been reported to be positively correlated.²¹ In a cohort of low-birth-weight children without diabetes, a higher IGF-1 level at 5 years was associated with higher insulin secretion (insulinogenic index) at 8 years.²² Together, these data suggest a potential role of IGF-1 in preserving beta cell function. Consistent with this possibility, rodent studies have shown that IGF-1 overexpression in beta cells increases beta cell mass through neogenesis and replication.²³ Insulin-like growth factor-1 may also enhance insulin action based on homology to insulin and binding to the insulin receptor,²⁴ and administration of recombinant human IGF-1 in adults with obesity improves glycemia and insulin sensitivity.^25,26 Whether modulating the IGF-1 pathway in youths with T2D may be beneficial remains an important question with implications for future therapies.

We found that a higher baseline GHR level and a greater increase in GHR level between baseline and 36 months were positively associated with hyperglycemia, insulin resistance, and lower measures of beta cell function in youths with T2D. To our knowledge, no previous studies have examined GHR levels in youth-onset T2D. Growth hormone has direct effects on glucose metabolism independent of its primary effector IGF-1, including increased hepatic gluconeogenesis, increased adipocyte lipolysis, decreased peripheral glucose uptake, and modulation of IGFBPs.^{27,28,29,30,31,32,33} Growth hormone binding protein, the extracellular ligand-binding domain of GHR, has been shown to prolong the half-life of GH and attenuate receptor binding to stimulate IGF-1 synthesis in the liver, and thus it may affect glucose metabolism indirectly.³⁴ This may explain the inverse association between GHR and IGF-1 that we observed. Increased GHR signaling in pancreatic islets has been shown to regulate pubertal beta cell expansion in rats.³⁵ However, little is known about the association of plasma GHR levels with systemic metabolism. Plasma GHR levels were recently reported to be associated with incident T2D in a large cohort study,³⁶ and reductions in GHR levels were identified as a causal mediator of improvements in glycemia after bariatric surgery in adults with T2D.³⁷ Prior studies showed that circulating GHR positively correlates with hepatosteatosis and adiposity in children with obesity,³⁸ and we did find in our exploratory analyses that GHR level is positively associated with both BMI z score and fat mass in both sexes. Therefore, it is possible that an increase in GHR level due to increased BMI and insulin resistance in individuals with T2D may attenuate GH activity in the liver to stimulate IGF-1 synthesis. However, our analysis included an adjustment for BMI z score, suggesting that associations between GHR level and glycemic outcomes exist independent of BMI. Our study has identified GHR level as a novel biomarker of decrease in glycemic control in youths with T2D. Future studies to elucidate mechanisms are needed.

At baseline in the TODAY trial, IGFBP-1 level was positively associated with insulin sensitivity (1/C-peptide). This finding is consistent with prior studies indicating that insulin directly suppresses hepatocyte IGFBP-1 production³⁹ and that IGFBP-1 level is associated with insulin sensitivity.^20,40 One study previously demonstrated that IGFBP-1 levels are lower in youths with new-onset T2D and hyperinsulinemia.⁴¹ As previously reported in the TODAY trial, IGFBP-1 level was inversely associated with BMI.¹⁸ Increases in IGFBP-1 levels between baseline and 36 months were associated with higher glycemic measures (HbA_1c and fasting glucose levels), likely due to loss of beta cell function and consequent loss of the inhibitory association of insulin with IGFBP-1 production.⁴² Insulin-like growth factor binding protein 1 modulates IGF-1 bioavailability and has been shown to inhibit IGF-1 effects, which may explain the inverse association between the 2 hormones in our analysis.⁴³ Insulin-like growth factor binding protein 1, as well as IGFBP-2 through 5, may have IGF-independent associations with glucose uptake and insulin sensitivity and have been associated with the pathogenesis of metabolic syndrome, diabetes, and diabetes complications.^{11,12,44,45,46,47,48,49}

Strengths and Limitations

Our study has some strengths, including the use of the TODAY cohort, which captures a large and diverse population of youths with T2D with longitudinal glycemic assessments. Paired comparisons at baseline and 36 months minimized potential confounding due to interindividual differences. We additionally performed linear and logistic regression models to adjust for confounders.

Our study also has several limitations. First, the TODAY study compared treatment options for youths with T2D and therefore did not include a control group without diabetes. Second, a large proportion of the cohort was in late puberty or after puberty at baseline, which limited our ability to perform subgroup analyses based on Tanner staging. However, analyses with adjustment for Tanner stage did not alter the significance of associations. Third, we examined hormone levels only at baseline and at 36 months, and most of our subcohort reached the primary outcome prior to the second measurement of GH mediators. As such, we cannot infer a direction of causality between GH mediator changes and glycemic outcome in the logistic regressions using primary outcome as the outcome measure. Analysis of additional time points earlier in the disease course would help to answer this important question. Furthermore, we noted baseline differences in glycemia and beta cell function between the glycemic failure and glycemic control groups; however, we accounted for baseline HbA_1c and beta cell measures as a covariate in our regression analyses. For measurement of insulin sensitivity, we used 1/fasting C-peptide, which correlates well with criterion standard insulin sensitivity measures¹⁵ but may be suboptimal in individuals with decreased beta cell function. As such, we corroborated our analysis by using adiponectin as a secondary measure of insulin sensitivity. Fourth, our study is limited to the measurement of circulating GH mediators, so we are unable to directly identify the source tissue and target organs of hormone action. Future studies should aim to assess gene expression of IGF-1, GHR, and IGFBP-1 in liver, fat, and other tissues in association with glycemic measures.

Conclusions

In this post hoc secondary analysis of the TODAY randomized clinical trial, we found novel associations of plasma GH mediator levels with glycemic failure, measures of glycemia, insulin sensitivity, and beta cell function in youths with T2D. However, additional mechanistic or longitudinal studies would help to elucidate the mechanism by which GH mediators affect glycemia, or vice versa. Whether alterations in GH mediators may facilitate progression from prediabetes to T2D or accelerated onset of diabetes complications in youth-onset T2D are important topics for future studies.

Supplement 1.

Study Protocol

jamanetwopen-e240447-s001.pdf^{(656KB, pdf)}

Supplement 2.

eFigure 1. CONSORT Study Flow Diagram of the TODAY Secondary Analysis

eFigure 2. Time-to-Event Survival Analysis of the TODAY Substudy Cohort

eTable 1. Anthropometric, Demographic, and Clinical Characteristics at Study Entry Based on Primary Outcome in TODAY

eTable 2. Anthropometric, Demographic, and Clinical Characteristics Compared Between Subcohort With Only Baseline Samples and Subcohort With Available Samples at Baseline and 36 Months

eTable 3. Glycemic Measures at 36-Month Study Timepoint Based on Primary Outcome in TODAY

eTable 4. Glycemic Measures at 36-Month Study Timepoint Compared Between Subcohort With Only Baseline Samples and Subcohort With Available Samples at Baseline and 36 Months

eFigure 3. Correlations Between GH Mediators

jamanetwopen-e240447-s002.pdf^{(567.1KB, pdf)}

Supplement 3.

Data Sharing Statement

jamanetwopen-e240447-s003.pdf^{(15.3KB, pdf)}

References

1.Divers J, Mayer-Davis EJ, Lawrence JM, et al. Trends in incidence of type 1 and type 2 diabetes among youths—selected counties and Indian reservations, United States, 2002-2015. MMWR Morb Mortal Wkly Rep. 2020;69(6):161-165. doi: 10.15585/mmwr.mm6906a3 [DOI] [PMC free article] [PubMed] [Google Scholar]
2.RISE Consortium; RISE Consortium Investigators . Effects of treatment of impaired glucose tolerance or recently diagnosed type 2 diabetes with metformin alone or in combination with insulin glargine on β-cell function: comparison of responses in youth and adults. Diabetes. 2019;68(8):1670-1680. doi: 10.2337/db19-0299 [DOI] [PMC free article] [PubMed] [Google Scholar]
3.RISE Consortium . Obesity and insulin sensitivity effects on cardiovascular risk factors: comparisons of obese dysglycemic youth and adults. Pediatr Diabetes. 2019;20(7):849-860. doi: 10.1111/pedi.12883 [DOI] [PMC free article] [PubMed] [Google Scholar]
4.Zeitler P, Epstein L, Grey M, et al. ; TODAY Study Group . Treatment options for type 2 diabetes in adolescents and youth: a study of the comparative efficacy of metformin alone or in combination with rosiglitazone or lifestyle intervention in adolescents with type 2 diabetes. Pediatr Diabetes. 2007;8(2):74-87. doi: 10.1111/j.1399-5448.2007.00237.x [DOI] [PMC free article] [PubMed] [Google Scholar]
5.Zeitler P, Hirst K, Pyle L, et al. ; TODAY Study Group . A clinical trial to maintain glycemic control in youth with type 2 diabetes. N Engl J Med. 2012;366(24):2247-2256. doi: 10.1056/NEJMoa1109333 [DOI] [PMC free article] [PubMed] [Google Scholar]
6.Bjornstad P, Drews KL, Caprio S, et al. ; TODAY Study Group . Long-term complications in youth-onset type 2 diabetes. N Engl J Med. 2021;385(5):416-426. doi: 10.1056/NEJMoa2100165 [DOI] [PMC free article] [PubMed] [Google Scholar]
7.Amiel SA, Sherwin RS, Simonson DC, Lauritano AA, Tamborlane WV. Impaired insulin action in puberty: a contributing factor to poor glycemic control in adolescents with diabetes. N Engl J Med. 1986;315(4):215-219. doi: 10.1056/NEJM198607243150402 [DOI] [PubMed] [Google Scholar]
8.Cheng TS, Day FR, Lakshman R, Ong KK. Association of puberty timing with type 2 diabetes: a systematic review and meta-analysis. PLoS Med. 2020;17(1):e1003017. doi: 10.1371/journal.pmed.1003017 [DOI] [PMC free article] [PubMed] [Google Scholar]
9.Klingensmith GJ, Connor CG, Ruedy KJ, et al. ; Pediatric Diabetes Consortium . Presentation of youth with type 2 diabetes in the Pediatric Diabetes Consortium. Pediatr Diabetes. 2016;17(4):266-273. doi: 10.1111/pedi.12281 [DOI] [PubMed] [Google Scholar]
10.Shah AS, Nadeau KJ, Dabelea D, Redondo MJ. Spectrum of phenotypes and causes of type 2 diabetes in children. Annu Rev Med. 2022;73:501-515. doi: 10.1146/annurev-med-042120-012033 [DOI] [PMC free article] [PubMed] [Google Scholar]
11.Wheatcroft SB, Kearney MT. IGF-dependent and IGF-independent actions of IGF-binding protein-1 and -2: implications for metabolic homeostasis. Trends Endocrinol Metab. 2009;20(4):153-162. doi: 10.1016/j.tem.2009.01.002 [DOI] [PubMed] [Google Scholar]
12.Dong X, Su L, Patti ME. Growth hormone and counterregulation in the pathogenesis of diabetes. Curr Diab Rep. 2022;22(10):511-524. doi: 10.1007/s11892-022-01488-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
13.Dehkhoda F, Lee CMM, Medina J, Brooks AJ. The growth hormone receptor: mechanism of receptor activation, cell signaling, and physiological aspects. Front Endocrinol (Lausanne). 2018;9:35. doi: 10.3389/fendo.2018.00035 [DOI] [PMC free article] [PubMed] [Google Scholar]
14.Arslanian S, El ghormli L, Bacha F, et al. ; TODAY Study Group . Adiponectin, insulin sensitivity, β-cell function, and racial/ethnic disparity in treatment failure rates in TODAY. Diabetes Care. 2017;40(1):85-93. doi: 10.2337/dc16-0455 [DOI] [PMC free article] [PubMed] [Google Scholar]
15.George L, Bacha F, Lee S, Tfayli H, Andreatta E, Arslanian S. Surrogate estimates of insulin sensitivity in obese youth along the spectrum of glucose tolerance from normal to prediabetes to diabetes. J Clin Endocrinol Metab. 2011;96(7):2136-2145. doi: 10.1210/jc.2010-2813 [DOI] [PMC free article] [PubMed] [Google Scholar]
16.Hara K, Horikoshi M, Yamauchi T, et al. Measurement of the high-molecular weight form of adiponectin in plasma is useful for the prediction of insulin resistance and metabolic syndrome. Diabetes Care. 2006;29(6):1357-1362. doi: 10.2337/dc05-1801 [DOI] [PubMed] [Google Scholar]
17.TODAY Study Group . Effects of metformin, metformin plus rosiglitazone, and metformin plus lifestyle on insulin sensitivity and β-cell function in TODAY. Diabetes Care. 2013;36(6):1749-1757. doi: 10.2337/dc12-2393 [DOI] [PMC free article] [PubMed] [Google Scholar]
18.Levitsky LL, Drews KL, Haymond M, et al. ; TODAY Study Group . The obesity paradox: retinopathy, obesity, and circulating risk markers in youth with type 2 diabetes in the TODAY study. J Diabetes Complications. 2022;36(11):108259. doi: 10.1016/j.jdiacomp.2022.108259 [DOI] [PMC free article] [PubMed] [Google Scholar]
19.Aleidi SM, Shayeb E, Bzour J, et al. Serum level of insulin-like growth factor-I in type 2 diabetic patients: impact of obesity. Horm Mol Biol Clin Investig. Published online August 9, 2019. doi: 10.1515/hmbci-2019-0015 [DOI] [PubMed] [Google Scholar]
20.Katz LEL, Gralewski KA, Abrams P, et al. Insulin-like growth factor-I and insulin-like growth factor binding protein-1 are related to cardiovascular disease biomarkers in obese adolescents. Pediatr Diabetes. 2016;17(2):77-86. doi: 10.1111/pedi.12242 [DOI] [PMC free article] [PubMed] [Google Scholar]
21.Fraenkel E, Lazurova I. IGF-1 and IGFBP3 as indirect markers of hepatic insulin resistance and their relation to metabolic syndrome parameters in liver steatosis patients. Endocr Regul. 2023;57(1):69-79. doi: 10.2478/enr-2023-0009 [DOI] [PubMed] [Google Scholar]
22.Ong KK, Petry CJ, Emmett PM, et al. ; ALSPAC study team . Insulin sensitivity and secretion in normal children related to size at birth, postnatal growth, and plasma insulin-like growth factor-I levels. Diabetologia. 2004;47(6):1064-1070. doi: 10.1007/s00125-004-1405-8 [DOI] [PubMed] [Google Scholar]
23.George M, Ayuso E, Casellas A, Costa C, Devedjian JC, Bosch F. β Cell expression of IGF-I leads to recovery from type 1 diabetes. J Clin Invest. 2002;109(9):1153-1163. doi: 10.1172/JCI0212969 [DOI] [PMC free article] [PubMed] [Google Scholar]
24.Rechler MM, Nissley SP. Insulin-like growth factor (IGF)/somatomedin receptor subtypes: structure, function, and relationships to insulin receptors and IGF carrier proteins. Horm Res. 1986;24(2-3):152-159. doi: 10.1159/000180554 [DOI] [PubMed] [Google Scholar]
25.Moses AC, Young SC, Morrow LA, O’Brien M, Clemmons DR. Recombinant human insulin-like growth factor I increases insulin sensitivity and improves glycemic control in type II diabetes. Diabetes. 1996;45(1):91-100. doi: 10.2337/diab.45.1.91 [DOI] [PubMed] [Google Scholar]
26.Clemmons DR, Moses AC, McKay MJ, Sommer A, Rosen DM, Ruckle J. The combination of insulin-like growth factor I and insulin-like growth factor-binding protein-3 reduces insulin requirements in insulin-dependent type 1 diabetes: evidence for in vivo biological activity. J Clin Endocrinol Metab. 2000;85(4):1518-1524. [DOI] [PubMed] [Google Scholar]
27.Jo JR, An S, Ghosh S, Nedumaran B, Kim YD. Growth hormone promotes hepatic gluconeogenesis by enhancing BTG2-YY1 signaling pathway. Sci Rep. 2021;11(1):18999. doi: 10.1038/s41598-021-98537-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
28.Vijayakumar A, Novosyadlyy R, Wu Y, Yakar S, LeRoith D. Biological effects of growth hormone on carbohydrate and lipid metabolism. Growth Horm IGF Res. 2010;20(1):1-7. doi: 10.1016/j.ghir.2009.09.002 [DOI] [PMC free article] [PubMed] [Google Scholar]
29.Chen XL, Lee K, Hartzell DL, et al. Adipocyte insensitivity to insulin in growth hormone–transgenic mice. Biochem Biophys Res Commun. 2001;283(4):933-937. doi: 10.1006/bbrc.2001.4882 [DOI] [PubMed] [Google Scholar]
30.Tai PK, Liao JF, Chen EH, Dietz J, Schwartz J, Carter-Su C. Differential regulation of two glucose transporters by chronic growth hormone treatment of cultured 3T3-F442A adipose cells. J Biol Chem. 1990;265(35):21828-21834. doi: 10.1016/S0021-9258(18)45814-0 [DOI] [PubMed] [Google Scholar]
31.Ghanaat F, Tayek JA. Growth hormone administration increases glucose production by preventing the expected decrease in glycogenolysis seen with fasting in healthy volunteers. Metabolism. 2005;54(5):604-609. doi: 10.1016/j.metabol.2004.12.003 [DOI] [PubMed] [Google Scholar]
32.Kaplan W, Sunehag AL, Dao H, Haymond MW. Short-term effects of recombinant human growth hormone and feeding on gluconeogenesis in humans. Metabolism. 2008;57(6):725-732. doi: 10.1016/j.metabol.2008.01.009 [DOI] [PMC free article] [PubMed] [Google Scholar]
33.Allard JB, Duan C. IGF-binding proteins: why do they exist and why are there so many? Front Endocrinol (Lausanne). 2018;9:117. doi: 10.3389/fendo.2018.00117 [DOI] [PMC free article] [PubMed] [Google Scholar]
34.Schilbach K, Bidlingmaier M. Growth hormone binding protein—physiological and analytical aspects. Best Pract Res Clin Endocrinol Metab. 2015;29(5):671-683. doi: 10.1016/j.beem.2015.06.004 [DOI] [PubMed] [Google Scholar]
35.Castell AL, Goubault C, Ethier M, et al. β Cell mass expansion during puberty involves serotonin signaling and determines glucose homeostasis in adulthood. JCI Insight. 2022;7(21):e160854. doi: 10.1172/jci.insight.160854 [DOI] [PMC free article] [PubMed] [Google Scholar]
36.Carrasco-Zanini J, Pietzner M, Lindbohm JV, et al. Proteomic signatures for identification of impaired glucose tolerance. Nat Med. 2022;28(11):2293-2300. doi: 10.1038/s41591-022-02055-z [DOI] [PMC free article] [PubMed] [Google Scholar]
37.Dreyfuss JM, Yuchi Y, Dong X, et al. High-throughput mediation analysis of human proteome and metabolome identifies mediators of post-bariatric surgical diabetes control. Nat Commun. 2021;12(1):6951. doi: 10.1038/s41467-021-27289-2 [DOI] [PMC free article] [PubMed] [Google Scholar]
38.Kempf E, Landgraf K, Vogel T, et al. Associations of GHR, IGF-1 and IGFBP-3 expression in adipose tissue cells with obesity-related alterations in corresponding circulating levels and adipose tissue function in children. Adipocyte. 2022;11(1):630-642. doi: 10.1080/21623945.2022.2148886 [DOI] [PMC free article] [PubMed] [Google Scholar]
39.Orlowski CC, Ooi GT, Brown DR, Yang YW, Tseng LY, Rechler MM. Insulin rapidly inhibits insulin-like growth factor–binding protein-1 gene expression in H4-II-E rat hepatoma cells. Mol Endocrinol. 1991;5(8):1180-1187. doi: 10.1210/mend-5-8-1180 [DOI] [PubMed] [Google Scholar]
40.Travers SH, Labarta JI, Gargosky SE, Rosenfeld RG, Jeffers BW, Eckel RH. Insulin-like growth factor binding protein-I levels are strongly associated with insulin sensitivity and obesity in early pubertal children. J Clin Endocrinol Metab. 1998;83(6):1935-1939. doi: 10.1210/jc.83.6.1935 [DOI] [PubMed] [Google Scholar]
41.Katz LEL, Jawad AF, Ganesh J, Abraham M, Murphy K, Lipman TH. Fasting c-peptide and insulin-like growth factor–binding protein-1 levels help to distinguish childhood type 1 and type 2 diabetes at diagnosis. Pediatr Diabetes. 2007;8(2):53-59. doi: 10.1111/j.1399-5448.2007.00236.x [DOI] [PubMed] [Google Scholar]
42.Clauson PG, Brismar K, Hall K, Linnarsson R, Grill V. Insulin-like growth factor-I and insulin-like growth factor binding protein-1 in a representative population of type 2 diabetic patients in Sweden. Scand J Clin Lab Invest. 1998;58(4):353-360. doi: 10.1080/00365519850186544 [DOI] [PubMed] [Google Scholar]
43.Lewitt MS, Denyer GS, Cooney GJ, Baxter RC. Insulin-like growth factor–binding protein-1 modulates blood glucose levels. Endocrinology. 1991;129(4):2254-2256. doi: 10.1210/endo-129-4-2254 [DOI] [PubMed] [Google Scholar]
44.Haywood NJ, Cordell PA, Tang KY, et al. Insulin-like growth factor binding protein 1 could improve glucose regulation and insulin sensitivity through its RGD domain. Diabetes. 2017;66(2):287-299. doi: 10.2337/db16-0997 [DOI] [PubMed] [Google Scholar]
45.Drogan D, Schulze MB, Boeing H, Pischon T. Insulin-like growth factor 1 and insulin-like growth factor–binding protein 3 in relation to the risk of type 2 diabetes mellitus: results from the EPIC-Potsdam Study. Am J Epidemiol. 2016;183(6):553-560. doi: 10.1093/aje/kwv188 [DOI] [PubMed] [Google Scholar]
46.Ezzat VA, Duncan ER, Wheatcroft SB, Kearney MT. The role of IGF-I and its binding proteins in the development of type 2 diabetes and cardiovascular disease. Diabetes Obes Metab. 2008;10(3):198-211. doi: 10.1111/j.1463-1326.2007.00709.x [DOI] [PubMed] [Google Scholar]
47.Rauzier C, Chartrand DJ, Alméras N, et al. Associations of insulin-like growth factor binding protein-2 with metabolic profile and hepatic fat deposition in asymptomatic men and women. Am J Physiol Endocrinol Metab. 2023;325(1):E99-E105. doi: 10.1152/ajpendo.00108.2023 [DOI] [PubMed] [Google Scholar]
48.Moin ASM, Sathyapalan T, Atkin SL, Butler AE. Diagnostic and prognostic protein biomarkers of β-cell function in type 2 diabetes and their modulation with glucose normalization. Metabolites. 2022;12(3):196. doi: 10.3390/metabo12030196 [DOI] [PMC free article] [PubMed] [Google Scholar]
49.Rojas-Rodriguez R, Ziegler R, DeSouza T, et al. PAPPA-mediated adipose tissue remodeling mitigates insulin resistance and protects against gestational diabetes in mice and humans. Sci Transl Med. 2020;12(571):eaay4145. doi: 10.1126/scitranslmed.aay4145 [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplement 1.

Study Protocol

jamanetwopen-e240447-s001.pdf^{(656KB, pdf)}

Supplement 2.

eFigure 1. CONSORT Study Flow Diagram of the TODAY Secondary Analysis

eFigure 2. Time-to-Event Survival Analysis of the TODAY Substudy Cohort

eTable 1. Anthropometric, Demographic, and Clinical Characteristics at Study Entry Based on Primary Outcome in TODAY

eTable 2. Anthropometric, Demographic, and Clinical Characteristics Compared Between Subcohort With Only Baseline Samples and Subcohort With Available Samples at Baseline and 36 Months

eTable 3. Glycemic Measures at 36-Month Study Timepoint Based on Primary Outcome in TODAY

eTable 4. Glycemic Measures at 36-Month Study Timepoint Compared Between Subcohort With Only Baseline Samples and Subcohort With Available Samples at Baseline and 36 Months

eFigure 3. Correlations Between GH Mediators

jamanetwopen-e240447-s002.pdf^{(567.1KB, pdf)}

Supplement 3.

Data Sharing Statement

jamanetwopen-e240447-s003.pdf^{(15.3KB, pdf)}

[zoi240038r1] 1.Divers J, Mayer-Davis EJ, Lawrence JM, et al. Trends in incidence of type 1 and type 2 diabetes among youths—selected counties and Indian reservations, United States, 2002-2015. MMWR Morb Mortal Wkly Rep. 2020;69(6):161-165. doi: 10.15585/mmwr.mm6906a3 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r2] 2.RISE Consortium; RISE Consortium Investigators . Effects of treatment of impaired glucose tolerance or recently diagnosed type 2 diabetes with metformin alone or in combination with insulin glargine on β-cell function: comparison of responses in youth and adults. Diabetes. 2019;68(8):1670-1680. doi: 10.2337/db19-0299 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r3] 3.RISE Consortium . Obesity and insulin sensitivity effects on cardiovascular risk factors: comparisons of obese dysglycemic youth and adults. Pediatr Diabetes. 2019;20(7):849-860. doi: 10.1111/pedi.12883 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r4] 4.Zeitler P, Epstein L, Grey M, et al. ; TODAY Study Group . Treatment options for type 2 diabetes in adolescents and youth: a study of the comparative efficacy of metformin alone or in combination with rosiglitazone or lifestyle intervention in adolescents with type 2 diabetes. Pediatr Diabetes. 2007;8(2):74-87. doi: 10.1111/j.1399-5448.2007.00237.x [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r5] 5.Zeitler P, Hirst K, Pyle L, et al. ; TODAY Study Group . A clinical trial to maintain glycemic control in youth with type 2 diabetes. N Engl J Med. 2012;366(24):2247-2256. doi: 10.1056/NEJMoa1109333 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r6] 6.Bjornstad P, Drews KL, Caprio S, et al. ; TODAY Study Group . Long-term complications in youth-onset type 2 diabetes. N Engl J Med. 2021;385(5):416-426. doi: 10.1056/NEJMoa2100165 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r7] 7.Amiel SA, Sherwin RS, Simonson DC, Lauritano AA, Tamborlane WV. Impaired insulin action in puberty: a contributing factor to poor glycemic control in adolescents with diabetes. N Engl J Med. 1986;315(4):215-219. doi: 10.1056/NEJM198607243150402 [DOI] [PubMed] [Google Scholar]

[zoi240038r8] 8.Cheng TS, Day FR, Lakshman R, Ong KK. Association of puberty timing with type 2 diabetes: a systematic review and meta-analysis. PLoS Med. 2020;17(1):e1003017. doi: 10.1371/journal.pmed.1003017 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r9] 9.Klingensmith GJ, Connor CG, Ruedy KJ, et al. ; Pediatric Diabetes Consortium . Presentation of youth with type 2 diabetes in the Pediatric Diabetes Consortium. Pediatr Diabetes. 2016;17(4):266-273. doi: 10.1111/pedi.12281 [DOI] [PubMed] [Google Scholar]

[zoi240038r10] 10.Shah AS, Nadeau KJ, Dabelea D, Redondo MJ. Spectrum of phenotypes and causes of type 2 diabetes in children. Annu Rev Med. 2022;73:501-515. doi: 10.1146/annurev-med-042120-012033 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r11] 11.Wheatcroft SB, Kearney MT. IGF-dependent and IGF-independent actions of IGF-binding protein-1 and -2: implications for metabolic homeostasis. Trends Endocrinol Metab. 2009;20(4):153-162. doi: 10.1016/j.tem.2009.01.002 [DOI] [PubMed] [Google Scholar]

[zoi240038r12] 12.Dong X, Su L, Patti ME. Growth hormone and counterregulation in the pathogenesis of diabetes. Curr Diab Rep. 2022;22(10):511-524. doi: 10.1007/s11892-022-01488-7 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r13] 13.Dehkhoda F, Lee CMM, Medina J, Brooks AJ. The growth hormone receptor: mechanism of receptor activation, cell signaling, and physiological aspects. Front Endocrinol (Lausanne). 2018;9:35. doi: 10.3389/fendo.2018.00035 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r14] 14.Arslanian S, El ghormli L, Bacha F, et al. ; TODAY Study Group . Adiponectin, insulin sensitivity, β-cell function, and racial/ethnic disparity in treatment failure rates in TODAY. Diabetes Care. 2017;40(1):85-93. doi: 10.2337/dc16-0455 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r15] 15.George L, Bacha F, Lee S, Tfayli H, Andreatta E, Arslanian S. Surrogate estimates of insulin sensitivity in obese youth along the spectrum of glucose tolerance from normal to prediabetes to diabetes. J Clin Endocrinol Metab. 2011;96(7):2136-2145. doi: 10.1210/jc.2010-2813 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r16] 16.Hara K, Horikoshi M, Yamauchi T, et al. Measurement of the high-molecular weight form of adiponectin in plasma is useful for the prediction of insulin resistance and metabolic syndrome. Diabetes Care. 2006;29(6):1357-1362. doi: 10.2337/dc05-1801 [DOI] [PubMed] [Google Scholar]

[zoi240038r17] 17.TODAY Study Group . Effects of metformin, metformin plus rosiglitazone, and metformin plus lifestyle on insulin sensitivity and β-cell function in TODAY. Diabetes Care. 2013;36(6):1749-1757. doi: 10.2337/dc12-2393 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r18] 18.Levitsky LL, Drews KL, Haymond M, et al. ; TODAY Study Group . The obesity paradox: retinopathy, obesity, and circulating risk markers in youth with type 2 diabetes in the TODAY study. J Diabetes Complications. 2022;36(11):108259. doi: 10.1016/j.jdiacomp.2022.108259 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r19] 19.Aleidi SM, Shayeb E, Bzour J, et al. Serum level of insulin-like growth factor-I in type 2 diabetic patients: impact of obesity. Horm Mol Biol Clin Investig. Published online August 9, 2019. doi: 10.1515/hmbci-2019-0015 [DOI] [PubMed] [Google Scholar]

[zoi240038r20] 20.Katz LEL, Gralewski KA, Abrams P, et al. Insulin-like growth factor-I and insulin-like growth factor binding protein-1 are related to cardiovascular disease biomarkers in obese adolescents. Pediatr Diabetes. 2016;17(2):77-86. doi: 10.1111/pedi.12242 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r21] 21.Fraenkel E, Lazurova I. IGF-1 and IGFBP3 as indirect markers of hepatic insulin resistance and their relation to metabolic syndrome parameters in liver steatosis patients. Endocr Regul. 2023;57(1):69-79. doi: 10.2478/enr-2023-0009 [DOI] [PubMed] [Google Scholar]

[zoi240038r22] 22.Ong KK, Petry CJ, Emmett PM, et al. ; ALSPAC study team . Insulin sensitivity and secretion in normal children related to size at birth, postnatal growth, and plasma insulin-like growth factor-I levels. Diabetologia. 2004;47(6):1064-1070. doi: 10.1007/s00125-004-1405-8 [DOI] [PubMed] [Google Scholar]

[zoi240038r23] 23.George M, Ayuso E, Casellas A, Costa C, Devedjian JC, Bosch F. β Cell expression of IGF-I leads to recovery from type 1 diabetes. J Clin Invest. 2002;109(9):1153-1163. doi: 10.1172/JCI0212969 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r24] 24.Rechler MM, Nissley SP. Insulin-like growth factor (IGF)/somatomedin receptor subtypes: structure, function, and relationships to insulin receptors and IGF carrier proteins. Horm Res. 1986;24(2-3):152-159. doi: 10.1159/000180554 [DOI] [PubMed] [Google Scholar]

[zoi240038r25] 25.Moses AC, Young SC, Morrow LA, O’Brien M, Clemmons DR. Recombinant human insulin-like growth factor I increases insulin sensitivity and improves glycemic control in type II diabetes. Diabetes. 1996;45(1):91-100. doi: 10.2337/diab.45.1.91 [DOI] [PubMed] [Google Scholar]

[zoi240038r26] 26.Clemmons DR, Moses AC, McKay MJ, Sommer A, Rosen DM, Ruckle J. The combination of insulin-like growth factor I and insulin-like growth factor-binding protein-3 reduces insulin requirements in insulin-dependent type 1 diabetes: evidence for in vivo biological activity. J Clin Endocrinol Metab. 2000;85(4):1518-1524. [DOI] [PubMed] [Google Scholar]

[zoi240038r27] 27.Jo JR, An S, Ghosh S, Nedumaran B, Kim YD. Growth hormone promotes hepatic gluconeogenesis by enhancing BTG2-YY1 signaling pathway. Sci Rep. 2021;11(1):18999. doi: 10.1038/s41598-021-98537-0 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r28] 28.Vijayakumar A, Novosyadlyy R, Wu Y, Yakar S, LeRoith D. Biological effects of growth hormone on carbohydrate and lipid metabolism. Growth Horm IGF Res. 2010;20(1):1-7. doi: 10.1016/j.ghir.2009.09.002 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r29] 29.Chen XL, Lee K, Hartzell DL, et al. Adipocyte insensitivity to insulin in growth hormone–transgenic mice. Biochem Biophys Res Commun. 2001;283(4):933-937. doi: 10.1006/bbrc.2001.4882 [DOI] [PubMed] [Google Scholar]

[zoi240038r30] 30.Tai PK, Liao JF, Chen EH, Dietz J, Schwartz J, Carter-Su C. Differential regulation of two glucose transporters by chronic growth hormone treatment of cultured 3T3-F442A adipose cells. J Biol Chem. 1990;265(35):21828-21834. doi: 10.1016/S0021-9258(18)45814-0 [DOI] [PubMed] [Google Scholar]

[zoi240038r31] 31.Ghanaat F, Tayek JA. Growth hormone administration increases glucose production by preventing the expected decrease in glycogenolysis seen with fasting in healthy volunteers. Metabolism. 2005;54(5):604-609. doi: 10.1016/j.metabol.2004.12.003 [DOI] [PubMed] [Google Scholar]

[zoi240038r32] 32.Kaplan W, Sunehag AL, Dao H, Haymond MW. Short-term effects of recombinant human growth hormone and feeding on gluconeogenesis in humans. Metabolism. 2008;57(6):725-732. doi: 10.1016/j.metabol.2008.01.009 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r33] 33.Allard JB, Duan C. IGF-binding proteins: why do they exist and why are there so many? Front Endocrinol (Lausanne). 2018;9:117. doi: 10.3389/fendo.2018.00117 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r34] 34.Schilbach K, Bidlingmaier M. Growth hormone binding protein—physiological and analytical aspects. Best Pract Res Clin Endocrinol Metab. 2015;29(5):671-683. doi: 10.1016/j.beem.2015.06.004 [DOI] [PubMed] [Google Scholar]

[zoi240038r35] 35.Castell AL, Goubault C, Ethier M, et al. β Cell mass expansion during puberty involves serotonin signaling and determines glucose homeostasis in adulthood. JCI Insight. 2022;7(21):e160854. doi: 10.1172/jci.insight.160854 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r36] 36.Carrasco-Zanini J, Pietzner M, Lindbohm JV, et al. Proteomic signatures for identification of impaired glucose tolerance. Nat Med. 2022;28(11):2293-2300. doi: 10.1038/s41591-022-02055-z [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r37] 37.Dreyfuss JM, Yuchi Y, Dong X, et al. High-throughput mediation analysis of human proteome and metabolome identifies mediators of post-bariatric surgical diabetes control. Nat Commun. 2021;12(1):6951. doi: 10.1038/s41467-021-27289-2 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r38] 38.Kempf E, Landgraf K, Vogel T, et al. Associations of GHR, IGF-1 and IGFBP-3 expression in adipose tissue cells with obesity-related alterations in corresponding circulating levels and adipose tissue function in children. Adipocyte. 2022;11(1):630-642. doi: 10.1080/21623945.2022.2148886 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r39] 39.Orlowski CC, Ooi GT, Brown DR, Yang YW, Tseng LY, Rechler MM. Insulin rapidly inhibits insulin-like growth factor–binding protein-1 gene expression in H4-II-E rat hepatoma cells. Mol Endocrinol. 1991;5(8):1180-1187. doi: 10.1210/mend-5-8-1180 [DOI] [PubMed] [Google Scholar]

[zoi240038r40] 40.Travers SH, Labarta JI, Gargosky SE, Rosenfeld RG, Jeffers BW, Eckel RH. Insulin-like growth factor binding protein-I levels are strongly associated with insulin sensitivity and obesity in early pubertal children. J Clin Endocrinol Metab. 1998;83(6):1935-1939. doi: 10.1210/jc.83.6.1935 [DOI] [PubMed] [Google Scholar]

[zoi240038r41] 41.Katz LEL, Jawad AF, Ganesh J, Abraham M, Murphy K, Lipman TH. Fasting c-peptide and insulin-like growth factor–binding protein-1 levels help to distinguish childhood type 1 and type 2 diabetes at diagnosis. Pediatr Diabetes. 2007;8(2):53-59. doi: 10.1111/j.1399-5448.2007.00236.x [DOI] [PubMed] [Google Scholar]

[zoi240038r42] 42.Clauson PG, Brismar K, Hall K, Linnarsson R, Grill V. Insulin-like growth factor-I and insulin-like growth factor binding protein-1 in a representative population of type 2 diabetic patients in Sweden. Scand J Clin Lab Invest. 1998;58(4):353-360. doi: 10.1080/00365519850186544 [DOI] [PubMed] [Google Scholar]

[zoi240038r43] 43.Lewitt MS, Denyer GS, Cooney GJ, Baxter RC. Insulin-like growth factor–binding protein-1 modulates blood glucose levels. Endocrinology. 1991;129(4):2254-2256. doi: 10.1210/endo-129-4-2254 [DOI] [PubMed] [Google Scholar]

[zoi240038r44] 44.Haywood NJ, Cordell PA, Tang KY, et al. Insulin-like growth factor binding protein 1 could improve glucose regulation and insulin sensitivity through its RGD domain. Diabetes. 2017;66(2):287-299. doi: 10.2337/db16-0997 [DOI] [PubMed] [Google Scholar]

[zoi240038r45] 45.Drogan D, Schulze MB, Boeing H, Pischon T. Insulin-like growth factor 1 and insulin-like growth factor–binding protein 3 in relation to the risk of type 2 diabetes mellitus: results from the EPIC-Potsdam Study. Am J Epidemiol. 2016;183(6):553-560. doi: 10.1093/aje/kwv188 [DOI] [PubMed] [Google Scholar]

[zoi240038r46] 46.Ezzat VA, Duncan ER, Wheatcroft SB, Kearney MT. The role of IGF-I and its binding proteins in the development of type 2 diabetes and cardiovascular disease. Diabetes Obes Metab. 2008;10(3):198-211. doi: 10.1111/j.1463-1326.2007.00709.x [DOI] [PubMed] [Google Scholar]

[zoi240038r47] 47.Rauzier C, Chartrand DJ, Alméras N, et al. Associations of insulin-like growth factor binding protein-2 with metabolic profile and hepatic fat deposition in asymptomatic men and women. Am J Physiol Endocrinol Metab. 2023;325(1):E99-E105. doi: 10.1152/ajpendo.00108.2023 [DOI] [PubMed] [Google Scholar]

[zoi240038r48] 48.Moin ASM, Sathyapalan T, Atkin SL, Butler AE. Diagnostic and prognostic protein biomarkers of β-cell function in type 2 diabetes and their modulation with glucose normalization. Metabolites. 2022;12(3):196. doi: 10.3390/metabo12030196 [DOI] [PMC free article] [PubMed] [Google Scholar]

[zoi240038r49] 49.Rojas-Rodriguez R, Ziegler R, DeSouza T, et al. PAPPA-mediated adipose tissue remodeling mitigates insulin resistance and protects against gestational diabetes in mice and humans. Sci Transl Med. 2020;12(571):eaay4145. doi: 10.1126/scitranslmed.aay4145 [DOI] [PMC free article] [PubMed] [Google Scholar]

PERMALINK

Growth Hormone Mediators and Glycemic Control in Youths With Type 2 Diabetes

Chang Lu, MD

Danielle Wolfs, MPH

Laure El ghormli, MS

Lynne L Levitsky, MD

Lorraine E Levitt Katz, MD

Lori M Laffel, MD, MPH

Mary-Elizabeth Patti, MD

Elvira Isganaitis, MD, MPH

Key Points

Question

Findings

Meaning

Abstract

Importance

Objective

Design, Setting, and Participants

Exposure

Main Outcomes and Measures

Results

Conclusions and Relevance

Trial Registration

Introduction

Methods

TODAY Study Design and Cohort

Measures of Glycemia, Insulin Sensitivity, and Insulin Secretion

IGF-1, GHR, and IGFBP-1 Assays

Statistical Analysis

Results

Demographic Characteristics

Measures of Glycemia, Insulin Sensitivity, and Beta Cell Function

GH Mediators and Loss of Glycemic Control

Figure. Growth Hormone Mediator Levels at Baseline and 36-Month Visits Based on Outcome in the Treatment Options for Type 2 Diabetes in Adolescents and Youth Study.

Table 1. Associations of Plasma Hormone Levels With Odds of Primary Outcome in the Treatment Options for Type 2 Diabetes in Adolescents and Youth Study.

Table 2. Associations of Plasma IGF-1 Levels With Glycemic Measures at Baseline and 36 Monthsa.

Table 3. Associations of Plasma Log2 GHR Levels With Glycemic Measures at Baseline and 36 Monthsa.

Table 4. Associations of Plasma Log2 IGFBP-1 Levels With Glycemic Measures at Baseline and 36 Monthsa.

GH Mediators and Glycemic Measures

Insulin-Like Growth Factor-1

Growth Hormone Receptor

Insulin-Like Growth Factor Binding Protein 1

Correlations of IGF-1, GHR, and IGFBP-1 Levels

Discussion

Strengths and Limitations

Conclusions

References

Associated Data

Supplementary Materials

ACTIONS

PERMALINK

RESOURCES

Similar articles

Cited by other articles

Links to NCBI Databases

Table 2. Associations of Plasma IGF-1 Levels With Glycemic Measures at Baseline and 36 Months^a.

Table 3. Associations of Plasma Log₂ GHR Levels With Glycemic Measures at Baseline and 36 Months^a.

Table 4. Associations of Plasma Log₂ IGFBP-1 Levels With Glycemic Measures at Baseline and 36 Months^a.