The aim of this study was to examine the association between myocardial strain and arterial thickness and stiffness in young adults. Increased common carotid artery intima media thickness and peripheral arterial stiffness are known to precede coronary artery disease and cardiovascular (CV) events such as myocardial infarction and congestive heart failure. However, subclinical cardiac dysfunction can be detected in high-risk adults by myocardial strain echocardiography. The authors hypothesized that increased carotid artery intima media thickness would be associated with abnormal myocardial strain in young subjects who had obesity and type 2 diabetes mellitus.
CV risk factors were collected in 338 young adults participating in a prospective, cross-sectional study. The CV parameters collected included intima-media thickness, peripheral arterial stiffness by brachial distensibility, and myocardial strain and strain rate. General linear models were constructed to determine if vascular structure and function measures were independently associated with myocardial strain and strain rate.
A linear relationship was found between global longitudinal strain obtained from the four-chamber view and global strain rate in systole and carotid intima-media thickness (four-chamber global longitudinal strain: β = 3.0, CV risk factor–adjusted R 2 = 0.34; global strain rate in systole: β = 0.0053, R 2 = 0.21; P ≤ .0001) and between four-chamber global longitudinal strain and lower brachial distensibility (β = −0.42, R 2 = 0.22; P < .001).
Adverse changes in vascular structure and function are simultaneously present with reduced myocardial systolic function.
Reduced strain and strain rate can be identified in adolescents and young adults with obesity and T2DM.
Arterial thickness and stiffness are independently associated with cardiac strain.
CV risk factors such as demographics, BP, and lipids are associated with adverse strain in young subjects.
Obesity, hypertension, and diabetes mellitus are known to lead to cardiovascular (CV) events, which may be preceded by subclinical cardiac dysfunction.
The importance of evaluating left ventricular (LV) systolic mechanics in risk stratification is demonstrated in the work of Stanton et al. , who studied 546 subjects, of whom half were hypertensive, half had dyslipidemia, 20% had diabetes, and one third had previous myocardial infarctions. In these high-risk adults, global longitudinal strain was a better predictor of outcome after 5 years compared with ejection fraction or wall motion score index, and the superiority of strain to traditional echocardiographic measures in predicting incident CV disease was demonstrated.
It is hypothesized that cardiac abnormalities may be due to arterial stiffening caused by CV risk factors. Lembo et al. found that global longitudinal strain was lower in adults in the highest tertile of pulse pressure, a rough estimate of arterial stiffness, and in our previous study of adolescents, global arterial stiffness index was an independent correlate of LV mass in adolescents and young adults. Whether subtle reduction in systolic function (less negative values for strain) related to arterial dysfunction can be demonstrated in adolescents and young adults with normal ejection fractions is not well described. In these analyses, we tested the hypothesis that CV risk factor–related changes in arterial measures would be independently associated with reduced myocardial strain and strain rate in young subjects.
Data were collected from 338 subjects in a prospective longitudinal study designed to evaluate the CV effects of obesity and type 2 diabetes mellitus (T2DM) on adolescents and young adults. Although risk factors, vascular data, and limited echocardiographic parameters were obtained at baseline, cardiac strain was added at the follow-up visit, when subjects had a mean age of 22 years (38% male, 63% non-Caucasian). For the initial study, all subjects with T2DM between 10 and 23 years of age seen at the Cincinnati Children’s Hospital endocrinology clinic were eligible. Subjects with diabetes who were recruited were matched by age, race, and gender to both lean (body mass index [BMI] < 85th percentile) and obese (BMI ≥ 95th percentile) control subjects. The BMI percentiles were obtained from the Centers for Disease Control and Prevention growth charts. All obese patients were proved nondiabetic by a 2-hour oral glucose tolerance test. Pregnant women and subjects with preexisting cardiac disease were excluded from enrollment in the original cohort. Institutional review board approval was obtained and consent obtained from all subjects or their guardians (if subjects were <18 years of age).
Two measures of height and weight were taken using a stadiometer (Holtain, Crymych, United Kingdom) and a digital scale (SECA, Hanover, MD), and the mean values were used. Blood pressure (BP) was measured with a mercury sphygmomanometer according to the 2011 National Institutes of Health CV risk reduction guidelines for adolescent or according to current adult recommendations. Careful attention was paid to cuff size and measurement technique. The average of three measures of systolic BP, diastolic BP, and heart rate were used in analyses.
Blood samples were obtained after a minimum 10-hour fast. Plasma glucose was measured with a Hitachi glucose analyzer with intra-assay and inter-assay coefficients of variation of 1.2% and 1.6%, respectively. Plasma insulin was measured by radioimmunoassay with an anti-insulin serum raised in guinea pigs, 125 I-labeled insulin (Linco, St. Louis, MO), and a double-antibody method to separate bound from free tracer. This assay has a sensitivity of 2 pmol and has intra-assay and inter-assay coefficients of variation of 5% and 8%, respectively. Lipid profile assays were performed in a laboratory standardized by the National Heart, Lung, and Blood Institute and the Centers for Disease Control and Prevention. The low-density lipoprotein (LDL) cholesterol concentration was calculated using the Friedewald equation. High-sensitivity C-reactive protein was measured using an enzyme-linked immunosorbent assay. Glycated hemoglobin (HbA 1c ) was measured in red blood cells using high-performance liquid chromatography.
All measurements were obtained by certified sonographers and vascular technicians blinded to study group assignment.
Echocardiography was performed on a GE Vivid 5 or 7 (GE Medical Systems, Milwaukee, WI) ultrasound system. All images were obtained with the participant in the left lateral decubitus position to acquire parasternal long-axis, parasternal short-axis, and apical four-chamber views for a total of three cardiac cycles. Absence of structural heart disease was confirmed, and the mean of three readings of LV end-diastolic intraventricular septal, end-diastolic septal thickness, and end-diastolic posterior wall thicknesses were measured offline by one sonographer using a Digiview Image Management and Reporting System (Digisonics, Houston, TX). LV mass was calculated using the Devereaux formula and normalized to height 2.7 as recommended by de Simone et al.
Cardiac Diastolic Function
Mitral inflow velocity was obtained with pulsed-wave Doppler parallel to mitral inflow in the apical four-chamber view and maximal velocity measured at the mitral valve leaflet tips. The mitral peak E (early filling) and A (inflow with atrial contraction) waves were measured offline, and the E/A ratio was calculated. Doppler tissue imaging of myocardial velocities was acquired in the apical four-chamber view, using color Doppler recordings. The peak and late velocities of mitral annular flow were recorded at both the septal annulus and lateral annulus. Ea/Aa ratios were calculated in addition to E/average of Ea lateral and E/Ea septal. The E/Ea ratio corrects for myocardial relaxation in transmitral flow (E) and has been shown to correlate with LV end-diastolic pressure. In adults, an E/Ea ratio <10 is normal.
Cardiac Systolic Function
Global longitudinal strain from the four-chamber view (GS 4-chamber) and global strain rate in systole (GSRs) were obtained with tissue velocity imaging using a Doppler tissue technique (not speckle-tracking) from the apical four-chamber view using high-resolution images (>80 frames/sec). Doppler tissue imaging was also obtained from the parasternal short-axis view for measurement of circumferential strain (circumferential shortening). Images were analyzed using GE EchoPAC (GE Medical Systems). The sonographer identified the medial mitral valve annulus, the apex, and the lateral mitral valve annulus and the software automatically traced the endocardial and epicardial borders. If two or more of the six segments averaged for global strain were missing, the image was reread until no or up to one segment was rejected by the software. Images with two or more rejected segments were excluded from the analyses. Reproducibility of global strain and strain rate in the four-chamber view was good, with coefficients of variation of 5.4% and 8.7%, respectively. Reproducibility of strain obtained from the parasternal short-axis views was lower (higher coefficients of variation of 17.5% and 15.3%, respectively).
Carotid Intima-Media Thickness
The carotid arteries were evaluated with high-resolution B-mode ultrasonography using a Vivid 7 (GE Vingmed Ultrasound, Horten, Norway) ultrasound imaging system with multifrequency linear-array transducers at 7 to 14 MHz. The thickest carotid intima-media thickness (cIMT) of the far wall of each carotid segment was measured using a manual trace (Vericis Merge; Emageon, Birmingham, AL) technique of the common carotid, carotid bulb, and internal carotid artery. cIMT measurement inter-observer variability in our laboratory has been documented at <5% and intraobserver variability at 1.9% (unpublished data).
Brachial Artery Distensibility
Brachial artery distensibility (BrachD) was measured using a DynaPulse device (PulseMetric, San Diego, CA) using a validated and reproducible method of pulse waveform analysis that is independent of body size and baseline brachial artery diameter. The average values of three resting measures of BrachD were used in analyses. This is a reproducible measure with coefficients of variability of <9%.
Statistical analyses were performed using SAS version 9.3 (SAS Institute, Cary, NC). Average values for the demographic, anthropometric, and laboratory data were obtained by group. Analysis of variance was performed for continuous variables and χ 2 tests for categorical variables to determine statistically significant differences by group. Variance-stabilizing transformations were performed as necessary for analyses. Associations between strain variables and risk factors were assessed by correlation analysis. Variables that were significant in bivariate analyses (age, sex, race, BMI Z score, mean arterial pressure [MAP], study group, triglycerides, high-density lipoprotein [HDL] cholesterol, LDL, HbA 1c , high-sensitivity C-reactive protein, and medication use) were included in the final general linear models constructed to determine if vascular function and/or structure were independent correlates of GS four-chamber and GSRs. Bonferroni correction was used to adjust for multiple comparisons. To illustrate the effect of obesity on strain, subjects were stratified by tertiles of obesity, and analysis of variance was performed to determine differences in strain by BMI tertile.
The characteristics of the study population stratified into three subgroups (lean, n = 112; obese, n = 121; T2DM, n = 105) are presented in Table 1 . There were no differences in race, but there were a higher proportion of male subjects in the lean group. By design, the differences in weight and BMI were significantly different between the lean and both the obese and T2DM groups. In general, CV risk profile (adiposity, BP, lipids, glycemic control, and inflammation) worsened from lean to obese to T2DM subjects. There was a graded increase in systolic BP from lean to obese to diabetic groups (112.2 vs 117 vs 121 mm Hg, P < .05). The lean group had more favorable diastolic BP, HDL cholesterol, insulin, and high-sensitivity C-reactive protein compared with the obese and diabetic groups. Both the lean and obese groups had lower heart rate, LDL cholesterol, triglycerides, glucose, and HbA 1c compared with the diabetic group ( P ≤ .05 for all).
|Variable||Lean ( n = 112)||Obese ( n = 121)||T2DM ( n = 105)|
|Age (y)||21.8 ± 3.9||22.1 ± 3.3||22.8 ± 3.8|
|Sex (male) ∗||54 (48%)||40 (33%)||36 (34%)|
|Race (non-Caucasian)||62 (55%)||79 (65%)||72 (69%)|
|Height (cm)||170.6 ± 9.7||169.8 ± 10.0||170.3 ± 9.7|
|Weight (kg) †||67.9 ± 11.7||110.3 ± 26.7||106.9 ± 25.2|
|BMI (kg/m 2 ) †||23.2 ± 3.3||38 ± 9.1||36.6 ± 7.3|
|SBP (mm Hg) ‡||112.2 ± 11.0||117 ± 11.5||121 ± 14.7|
|DBP (mm Hg) †||70 ± 8.7||74.2 ± 10.2||75.8 ± 10.4|
|HR (beats/min) §||64.5 ± 10.0||67.4 ± 11.3||75.5 ± 12.7|
|Tchol (mg/dL)||168 ± 34.3||168.7 ± 32.6||178.6 ± 43.2|
|LDL (mg/dL) ‖||99.2 ± 28.9||105.8 ± 28.3||114.6 ± 38.1|
|HDL (mg/dL) ∗||60.4 ± 16.5||51.4 ± 12.3||47.8 ± 13.4|
|TG (mg/dL) §||84.5 ± 40.4||102 ± 64.4||137.2 ± 81.3|
|Glucose (mg/dl) §||91.5 ± 7.3||92.7 ± 10.3||199.7 ± 127.3|
|Insulin (μU/mL) †||8.5 ± 6.8||18.4 ± 13.1||21 ± 17.6|
|HbA 1c (%) §||5 ± 0.6||5 ± 0.5||8.5 ± 3.3|
|hs-CRP (mg/L) †||1.5 ± 2.3||4.2 ± 4.6||5.2 ± 4.6|
Table 2 shows the results of cardiac and vascular parameters by group. LV mass index was lower in lean versus obese and diabetic subjects (lean, 29.5 g/m 2.7 ; obese, 38.3 g/m 2.7 ; T2DM, 38.7 g/m 2.7 ). There was no difference in shortening fraction. Diastolic function worsened across groups, with a significant difference in mitral E/e′ ratio (lean, 5.9; obese, 6.7; T2DM, 8.0) and e′/a′ ratio (lean, 11.0; obese, 10.3; T2DM, 9.8). GS four-chamber (lean, −18.0%; obese, −15.7%; T2DM, −14.9%) and GSRs (lean, −0.91 sec −1 ; obese, −0.79 sec −1 ; T2DM, −0.79 sec −1 ) were worse (lower absolute magnitude of shortening) in the obese and T2DM groups compared with the lean group. The global strain rate in systole (GSRs) showed a trend of worsening in the T2DM group compared with the obese group ( P = .08). Circumferential strain measured from the parasternal short axis also demonstrated less shortening in diabetic versus lean subjects (lean, −16.1%; T2DM, −14.7%). There was no difference in circumferential strain rate. BrachD was lower from lean to obese to T2DM (lean, 6.38%/mm Hg; obese, 5.62%/mm Hg; T2DM, 5.23%/mm Hg), reflecting increased arterial stiffness. In the common carotid (lean, 0.469 mm; obese, 0.496 mm; T2DM, 0.531 mm) and the carotid bulb (lean, 0.496 mm; obese, 0.520 mm; T2DM, 0.573 mm), intima-media thickness was lower in the lean and obese groups compared with the T2DM group. In the internal carotid (lean, 0.394 mm; obese, 0.434 mm; T2DM, 0.448 mm), lean subjects had lower cIMT than the obese and T2DM subjects ( P < .05 for all).
|Variable||Lean ( n = 112)||Obese ( n = 121)||T2DM ( n = 105)|
|LVM index (g/m 2.7 ) ∗||29.5 ± 8.9||38.3 ± 11.1||38.7 ± 12.2|
|Shortening fraction (%)||33.9 ± 7.0||34.7 ± 6.8||34.5 ± 7.1|
|Mitral E/A ratio §||2.2 ± 0.7||2.0 ± 0.7||1.7 ± 0.6|
|Mitral E/e′ ratio †||5.9 ± 1.2||6.7 ± 1.3||7.9 ± 2.3|
|Mitral e′/a′ ratio §||2.5 ± 0.7||2.1 ± 0.7||1.7 ± 0.6|
|GS four-chamber (%) ∗||−18.0 ± 2.9||−15.7 ± 3.4||−14.9 ± 3.1|
|GSRs four-chamber (sec −1 ) ∗||−0.91 ± 0.17||−0.79 ± 0.17||−0.79 ± 0.17|
|GS short-axis (%) ‖||−16.1 ± 3.6||−15.5 ± 3.7||−14.7 ± 4.5|
|GSRs short-axis (sec −1 )||−0.92 ± 0.22||−0.97 ± 0.22||−0.96 ± 0.29|
|BrachD (%/mm Hg) §||6.38 ± 1.04||5.62 ± 1.13||5.23 ± 0.91|
|Common cIMT (mm) ‡||0.469 ± 0.080||0.496 ± 0.091||0.531 ± 0.104|
|Bulb cIMT (mm) ‡||0.496 ± 0.103||0.520 ± 0.116||0.573 ± 0.166|
|Internal cIMT (mm) ∗||0.394 ± 0.088||0.434 ± 0.114||0.448 ± 0.103|