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. Author manuscript; available in PMC: 2019 Nov 1.
Published in final edited form as: J Diabetes Complications. 2018 Aug 9;32(11):995–999. doi: 10.1016/j.jdiacomp.2018.08.004

Inflammation, adiposity, and progression of arterial stiffness in adolescents with type 1 diabetes: The SEARCH CVD Study

Amy C Alman 1, Jennifer W Talton 2, R Paul Wadwa 3, Elaine M Urbina 4, Lawrence M Dolan 4, Richard F Hamman 5, Ralph B D’ Agostino Jr 2, Santica M Marcovina 6, Dana M Dabelea 5
PMCID: PMC6174105  NIHMSID: NIHMS1506213  PMID: 30209019

Abstract

Aims:

We examined the association between inflammation and progression of arterial stiffness in a population of youth with type 1 diabetes (T1D).

Methods:

A total of 287 youth with T1D (median age 13 years) from SEARCH CVD, an ancillary study to the SEARCH for Diabetes in Youth, were included. Markers of inflammation (CRP, IL-6, fibrinogen, leptin, and adiponectin) and measures of pulse wave velocity (PWV) of the arm (PWV-R), trunk (PWV-T), and lower extremity (PWV-LE) were measured at baseline. Measures of PWV were repeated approximately five years later.

Results:

PWV-R(0.50 m/s), PWV-T (0.65 m/s), and PWV-LE (1.0 m/s) significantly increased over the follow-up (p<0.001 for each). A significant interaction was found between waist circumference and fibrinogen (p=0.036) on the progression of PWV-T, suggesting that fibrinogen is more strongly associated with PWV progression in lean participants.

Conclusions:

Improved understanding of adiposity, inflammation, and functional changes in the vascular system in patients with T1D is crucial.

Keywords: Type 1 diabetes mellitus, inflammation, pulse wave analysis, waist circumference

1. Introduction

Type 1 diabetes is known to greatly increase the risk of cardiovascular disease in adults 1. Cardiovascular abnormalities in structure and function are observable in adolescents and young adults with type 1 diabetes 2–5. Arterial stiffness is an indicator of functional changes within the arterial wall and is an early manifestation of atherosclerosis 6. Altered vascular stiffness [as measured by increased pulse wave velocity (PWV)] has been reported in adolescent and young adult populations with type 1 diabetes 7–10.

Atherosclerosis is the result of a chronic inflammatory process 11 and increased levels of inflammatory mediators have been associated with hard outcomes, such as future myocardial infarction 12. Inflammation is increased in adolescents and young adults with type 1 diabetes, and could play a role in the increased cardiovascular risk seen in this population 3,5,13.

Increased adipose tissue mass, particularly central obesity, is associated with elevated levels of some pro-inflammatory cytokines (such as fibrinogen, leptin, C-reactive protein (CRP), interleukin 6 (IL-6)) and decreased levels of the anti-inflammatory adipose-derived protein adiponectin 14–16. The resulting chronic inflammatory state may promote insulin resistance and endothelial dysfunction, an early stage in the atherosclerotic process 16,17. A study by Martin, et al. found that adiposity modified the relationship between adiponectin and insulin resistance where a significant negative linear relationship existed in only obese adolescents 18.

While the reports cited above suggest a role for adipose-derived inflammation in the increased risk of cardiovascular disease seen in patients with type 1 diabetes, there are no reports on the longitudinal relationship between inflammation and progression of arterial stiffness in youth with or without type 1 diabetes. Here, we examine the relationships of inflammatory markers and adipose-derived cytokines with progression of PWV, and the potential role of central adiposity in modifying this relationship, in a population of adolescents and young adults with type 1 diabetes.

2. Subjects, Materials and Methods

2.1. Study design and participants

SEARCH CVD is an ancillary study to the SEARCH for Diabetes in Youth. SEARCH is a multicenter study that conducts population-based ascertainment of non-gestational cases of physician-diagnosed diabetes in youth age < 20 years at diagnosis19. Eligible subjects for enrollment in SEARCH CVD were SEARCH participants from Colorado and Ohio with physician-diagnosed type 1 diabetes, a baseline SEARCH research visit and duration of diabetes of at least 5 years. All SEARCH CVD participants had a baseline visit completed between 2004 and 2005 during which data on demographic, anthropometric and metabolic factors were collected, and a follow up visit in 2009–2011. A total of 298 adolescents with type 1 diabetes, age 13 years (interquartile range 12–16 years) at baseline (out of 402 SEARCH CVD participants) had measures of arterial stiffness obtained at both baseline and follow up visits, (on average after approximately 5 years). Age-specific reference values for waist-circumference (WC) z-scores were available up to age 19 years. To maintain consistency across analyses, those older than 19 at baseline (n = 11) were excluded from all analyses in this report. The study was reviewed and approved by the local institutional review boards that had jurisdiction over the local study population and all participants provided signed informed consent or assent.

2.2. Anthropometric and metabolic measurements

Baseline data included demographics, systolic and diastolic blood pressure, height, and weight. A z-score for BMI was calculated to adjust for age and sex differences. WC was measured using the National Health and Nutrition Examination Survey protocol which uses anatomical markers to improve accuracy in child and adolescent populations. Reference values for WC were obtained from Sharma, et al.20 in order to calculate WC z-scores by age (up to 19 years) and sex. Fasting blood samples (8-hr fast) were collected to measure lipids (total cholesterol, high-density lipoprotein, low-density lipoprotein, and triglycerides), hemoglobin A1c (HbA1c), and markers of inflammation, as previously described19,21. Blood samples were processed at the local sites and shipped within 24 hours to the central laboratory for analysis (Northwest Lipid Metabolism and Diabetes Research Laboratories, University of Washington, Seattle, WA). HbA1c was assayed using high-performance liquid chromatography (TOSOH Bioscience, San Francisco, CA). Measurements of total cholesterol, high-density lipoprotein-cholesterol and triglycerides were performed enzymatically using Roche reagent on the Roche Modular P autoanalyzer (Roche Diagnostics, Indiapanolis, IN). Levels of low-density lipoprotein-cholesterol were calculated by the Friedewald equation for subjects with a triglyceride concentration <400 mg/dl and measured by the Beta Quantification procedure for subjects with triglyceride concentrations ≥400 mg/dl. An estimated insulin sensitivity (IS) score was calculated from a previously validated formula using the WC, HbA1c, and triglyceride values [loge IS = 4.64725 – 0.02032 (waist, cm) – 0.09779 (HbA1c, %) – 0.00235 (TG, mg/dl)] 22. Leptin and adiponectin were measured by radioimmunoassay (Millipore Inc.) and IL-6 by a quintikine high sensitivity ELISA (R&D Systems Inc.). Levels of apolipoprotein B, fibrinogen and CRP were measured immunochemically using Siemens reagents on a BNII nephelometer autoanalyzer (Siemens Healthcare Diagnostics Inc.)

2.3. Arterial stiffness measures

PWV was measured with a SphygmoCor SCOR-PVx System and recorded as the difference in the carotid-to-distal path length divided by the difference in R-wave-to-waveform foot times, as previously described10. The average for each of the three different PWV values for the arm (carotid-radial; PWV-R), trunk (carotid-femoral; PWV-T), and the lower extremity (carotid-foot minus carotid-femoral; PWV-LE) were used in the analysis.

2.4. Statistical analyses

Continuous data are presented as the mean ± the standard deviation (SD) or the median and interquartile range (Q1, Q3), as appropriate for the distribution. Categorical data are presented as the number and percent of subjects for each category.

Adiponectin, fibrinogen, CRP, IL-6, leptin and triglycerides were not normally distributed and were log transformed for inclusion in the multivariable models. A composite score to represent the inflammatory burden was constructed by calculating a z-score ((x-µ)/σ) for each inflammatory marker and then summing the z-scores and dividing by the total number of markers. Composite scores such as this have been used in other studies where inflammatory markers were measured at a single point in time23.

Paired t-tests were used to determine if the PWV measures changed over the follow-up period. Multivariable linear regression models were developed to examine the relationship between each baseline inflammatory marker and the composite score as independent predictor variables and the progression in each measure of PWV (arm, trunk, and lower extremity) between baseline and follow-up as the dependent variable while controlling for other risk factors and confounders. Variables were selected to be included in the model based on their significance in previous work and their contribution to the model as either a significant explanatory variable or as a confounder. Baseline covariates entered into the models included demographics (age, sex, race/ethnicity, site), adiposity variables (BMI z-score), lipids (high-density lipoprotein, lowdensity lipoprotein, and triglycerides), blood pressure (systolic (SBP) and diastolic (DBP)), hemoglobin A1c (HbA1c), IS, and duration of diabetes (years). In addition, change in the BMI zscore, HbA1c, and IS between baseline and the follow-up were tested in the models as well. IS and change in IS were not included in models with HbA1c, WC, or triglycerides since IS is a function of these variables. To examine for differences by gender and race, we tested interaction terms between each of these variables and each inflammatory marker and the composite z-score, on progression of PWV. We also tested for differences by adiposity (WC z-score) with adiposity-by-inflammation interaction terms. Stratified models by the median of WC z-score (0.29) were run to compare the association between fibrinogen progression of PWV-T. Interaction terms were considered significant at p<0.1.

Model fit was verified by examining the adjusted R2 values for each model. Diagnostics were examined by looking at residual plots to see if model assumptions were met. In addition, influential observations were examined using standard regression diagnostics.

All analyses were performed using [SAS/STAT] software, Version [9.2] of the SAS System for [Windows] (SAS Institute Inc., Cary, NC, USA).

3. Results

3.1. Baseline characteristics

The median age of the population was 13 years (interquartile range 12–16). Slightly more than half were male (54.4%), and the majority were white, non-Hispanic (87.8%). The median duration of diabetes was 4 years (interquartile range 2–7). Mean BMI and WC were 21.9 kg/m2 (±4.4) and 74.4 cm (±11.7), respectively. Mean HbA1c was 8.2% (±1.4). Pulse wave velocity for all three measures increased significantly over the follow-up (arm: 0.50 m/sec, trunk: 0.65 m/sec, and foot: 1.0 m/sec; p < 0.001 for all). Values for baseline inflammatory measures are shown in Table 1.

Table 1.

Baseline measures of inflammation, n=287.

Measure
Adiponectin (ng/ml)a 17250 (1250–21600)
Fibrinogen (mg/dl)a 340 (307–375)
C-reactive protein (mg/dl)a 0.04 (0.02–0.08)
Interleukin-6 (pg/ml)a 10.0 (3.2–21.5)
Leptin (ng/dl)a 4.7 (2.1–8.8)
Inflammation composite z-scoreb -0.005 ±0.53
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a

Datapresented as median (interquartile range)

b

Data presented as mean ±SD

3.2. Inflammation and arterial stiffness

There were no associations between any of the inflammatory markers or the composite z-score and the progression in the PWV-R or PWV-LE (data not shown).

We found significant associations of baseline fibrinogen levels and the composite score with progression of PWV-T (Table 2, Model 1). Adjustment for BMI (Model 3), lipids (Model 4), and blood pressure (Model 5) attenuated this relationship, but it remained significant. Adjustment for HbA1c (Model 6), and IS (Model 7) attenuated this relationship to non-significance. In a model including BMI, HDL, LDL, log triglycerides, blood pressure, HbA1c, change in HbA1c, and ApoB (Model 8), fibrinogen was not significantly associated with progression of PWV-T. This attenuation was driven primarily by BMI, as removal of BMI from the model (Model 9) resulted in a significant association between fibrinogen and progression of PWV-T even after adjusting for lipids, blood pressure and HbA1c together. The composite score was significantly associated with the progression of PWV-T only in the first (unadjusted) model, but lost statistical significance after adjusting for any of the covariates (Models 2 through 9).

Table 2.

Associations between baseline inflammatory markers and change in PWV trunk at follow up, n=287.

 Model # Log fibrinogen Inflammation
composite z-score
β ±SE, p β ±SE, p
 Model 1a 0.76 ±0.26, 0.003 0.18 ±0.08, 0.034
 Model 2 – Demographicsb 0.64 ±0.27, 0.022 0.14 ±0.09, 0.130
 Model 3 – BMIc 0.60 ±0.28, 0.035 0.11 ±0.10, 0.296
 Model 4 – Lipdsd 0.68 ±0.29, 0.019 0.14 ±0.10, 0.143
 Model 5 - Blood pressuree 0.61 ±0.28, 0.033 0.14 ±0.10, 0.146
 Model 6 - HbA1cf 0.49 ±0.27, 0.075 0.07 ±0.09, 0.427
 Model 7 – Loge insulin sensitivity scoreg 0.29 ±0.27, 0.284 -0.08 ±0.10, 0.399
 Model 8- All significant covariatesh 0.46 ±0.28, 0.104 0.05 ±0.10, 0.575
 Model 9 – Model 8 excluding BMIi 0.57 ±0.28, 0.041 0.12 ±0.09, 0.203
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BMI: body mass index; HbA1c: hemoglobin A1c; PWV: pulse wave velocity; LDL: low-density lipoprotein; HDL: high-density lipoprotein; ApoB: apolipoprotein B

a

Model 1= adjusted for baseline PWV trunk

b

Model 2= Model 1 + age at baseline, gender, race/ethnicity, site, duration of diabetes (months)

c

Model 3= Model 2 + BMI z-score + change in BMI z-score

d

Model 4= Model 2 + lipids (LDL, HDL, log triglycerides)

e

Model 5= Model 2 + blood pressure (systolic and diastolic blood pressure)

f

Model 6= Model 2 + HbA1c + change in HbA1c

g

Model 7 = Model 2 + loge insulin sensitivity score + change in insulin sensitivity score

h

Model 8=adjusted for age, BMI z-score, HDL, LDL, log triglycerides, systolic and diastolic blood pressure, HbA1c, change in HbA1c, and ApoB

i

Model 9= adjusted for age, HDL, LDL, log triglycerides, systolic and diastolic blood pressure, HbA1c, change in HbA1c, and ApoB

We found a significant interaction between WC z-score and fibrinogen on the progression in PWV-T (p = 0.036). Figure 1 presents the regression lines for the association between baseline fibrinogen levels and progression of PWV-T by WC z-score category at baseline (<50th percentile and ≥50th percentile). The linear relationship between fibrinogen and progression of PWV-T was stronger among individuals with a WC lower than the median (β=0.62 ±0.37, p=0.093) than among individuals with a WC that was equal to or higher than the median (β=0.25 ±0.472, p=0.603). Neither gender nor race/ethnicity modified the association between fibrinogen and PVW-T progression.

Figure 1.

Figure 1.

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Linear regression lines of fibrinogen on the predicted change in pulse wave velocity (PWV) of the trunk by median waist circumference z-score. The dashed line represents the regression line for subjects with a waist circumference z-score <50th percentile. The solid line represents the regression line for subjects with a waist circumference z-score ≥50th percentile. The analysis was adjusted for age, high density lipoprotein, low density lipoprotein, log triglycerides, systolic and diastolic blood pressure, hemoglobin A1c, change in hemoglobin A1c, continuous waist circumference z-score, and apolipoprotein B.

4. Discussion

We found significant progression of arterial stiffness as measured by PWV at three sites (arm, trunk, and lower extremity) over approximately 5 years among youth with type 1 diabetes. The significant progression of PWV-T has been noted in this population previously24. In addition, PWV has previously been shown to be higher in youth with type 1 diabetes compared to nondiabetic controls10,25. For this report, we examined whether inflammation was associated with progression of PWV in youth with type 1 diabetes.

While studies have shown that markers of inflammation, including fibrinogen, MCP-1, hsCRP, fibrinogen, and IL-6 are higher in those with type 1 diabetes compared to those without3,5,24,26, there are few studies that have looked at the association between inflammation and arterial stiffness in youth. Comparisons across studies are difficult given lack of consistency in populations under study, outcome measures, and in the inflammatory markers measured. A recent study found that hsCRP was associated with increased PWV-T in youth aged 10–24 that were recently diagnosed with type 2 diabetes27, however, studies in youth with type 1 diabetes have found no association between MCP-1 and augmentation index26, or hsCRP and flowmediated dilatation3. In a prior report from SEARCH CVD, it was shown that adiponectin was not associated with PWV28. Similarly, we did not find a significant association between CRP, IL-6, leptin, or adiponectin and progression of PWV (data not shown). In adults, a composite score for inflammation (incorporating measures for hsCRP, IL-6, and soluble TNF-α receptors 1 and 2) was found to be significantly associated with PWV-T in men, but not in women 29. In our study, a composite score for inflammation was not independently associated with progression of PWV-T and there was no effect modification by gender.

Fibrinogen is an acute phase protein that increases plasma viscosity and platelet aggregation, and has been implicated in endothelial dysfunction and smooth muscle proliferation and migration 30. In meta-analyses, it has been shown to be significantly associated with major cardiovascular disease events and non-vascular mortality 31. Fibrinogen was found to be a significant predictor of progression of carotid intima-media thickness in the DCCT/EDIC cohort of adults with type 1 diabetes 32. Fibrinogen was also significantly associated with coronary artery calcification in the MESA study 33. We did find a modest association between fibrinogen and progression of PWV of the trunk that was attenuated by IS and BMI. Insulin resistance may be associated with arterial stiffness via the renin-angiotensin system34, although a recent study did not find any association between insulin resistance and PWV in children35. The attenuation of the association between fibrinogen and progression of PWV-T in our study may be due to mediation by IS.

Weight gain after diagnosis with type 1 diabetes can occur due to intensive insulin therapy and due to factors associated with weight gain in the general population36,37. The prevalence of overweight in the SEARCH population has been shown to be higher than the general population38. In adolescents with type 1 diabetes, adiposity has previously been shown to be associated with PWV25, although another recent report did not find an association between adiposity and PWV in a non-diabetic population. In the current study, BMI and WC z-scores were of borderline significance in multivariable models with progression of PWV-T as the dependent variable and adjusting for blood pressure, lipids, and HbA1c (data not shown). We did find that the relationship between fibrinogen and progression of PWV-T was stronger among individuals with a smaller WC than among those with a larger WC.

Significant effect modification by adiposity of the relationship between fibrinogen levels and progression of arterial stiffness in adolescents with type 1 diabetes has not previously been reported. However, Martin, et al. 18 did show that adiposity significantly modified the relationship between adiponectin and insulin-resistance with a significant relationship only in obese subjects. In addition, Wang, et al. 39 found a significant inverse relationship between dairy fatty acids and CRP only in overweight adolescents. The results of these works suggest that adiposity may modify the metabolic milieu such that the function of inflammatory markers is enhanced in the presence of increasing adipose tissues. In contrast, in our study, the association between fibrinogen and progression of PWV-T was stronger in those with a smaller WC than in those with a larger WC, suggesting that stronger risk factors in those with greater adiposity may dilute the effect of fibrinogen on progression of PWV-T. In addition, the association between fibrinogen and progression of PWV-T was modest in our population, and confounded by IS, HbA1c, and overall body mass (BMI), suggesting that, in youth with type 1 diabetes, inflammation is not a clinically important determinant of vascular stiffness progression.

This study has several limitations and important strengths. The study population consisted only of youth with type 1 diabetes, and we did not have a comparison group of adolescents without diabetes with longitudinal measurements of arterial stiffness. In addition, we only had measures of the inflammatory markers at the baseline visit. This may have resulted in an underestimate of the relationship between the inflammatory markers and arterial stiffness. We attempted to use a composite score as a measure of inflammatory burden, but this may have diluted the effect if inflammatory markers without an association with arterial stiffness were included. We were unable to examine the effect of pubertal status on these associations as that measure was not available. The strengths of this study include the longitudinal design, the relatively large sample size in an adolescent population, and the novelty of the research question with few published reports on the role of inflammation in the progression of arterial stiffness in adolescents and young adults with type 1 diabetes.

4.1. Conclusion

We found a significant increase in arterial stiffness in youth with type 1 diabetes over a relatively short period of time. Although makers of inflammation and especially fibrinogen levels predicted progression of PWV, this association was primarily driven by other cardiovascular risk factors, especially BMI. We also found that central adiposity modifies the relationship between fibrinogen and progression of PWV-T. Longitudinal follow up of this cohort is necessary to provide improved understanding of the inter-relationships between adiposity, inflammation, and structural and functional changes in the vascular system. Such knowledge is important, as the burden of obesity increases in youth with type 1 diabetes, and may contribute to their increased cardiovascular risk over the lifecourse.

Acknowledgements

Parts of this work were presented as a poster (# 1431-P) at the American Diabetes Association’s 72nd Scientific Sessions, Philadelphia, PA and printed in abstract form in the Scientific Sessions Abstract Book, the June 2012 supplement to Diabetes.

Funding

This study was funded by National Institutes of Health Grant R01-DK-078542 (to D.D.). No potential conflicts of interest relevant to this article were reported.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

The SEARCH for Diabetes in Youth Study is indebted to the many youth, and their families and their health care providers, whose participation made this study possible.

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