Quick search in Citations
This JournalAnywhereCitation
Advanced Search
Research Article
Originally Published 8 February 2018
Free Access

Effects of Increasing Exercise Intensity and Dose on Multiple Measures of HDL (High-Density Lipoprotein) Function

Mark A. Sarzynski, Jonathan J. Ruiz-Ramie, Jacob L. Barber, Cris A. Slentz, John W. Apolzan, Robert W. McGarrah, Melissa N. Harris, … Show All … , Timothy S. Church, Mark S. Borja, Yumin He, Michael N. Oda, Corby K. Martin, William E. Kraus, and Anand RohatgiAuthor Info & Affiliations
Arteriosclerosis, Thrombosis, and Vascular Biology
Volume 38, Number 4
https://doi.org/10.1161/ATVBAHA.117.310307
Track CitationsAdd to favorites
PDF/EPUB
This article has been corrected.
VIEW CORRECTION

Abstract

Objective—

Measures of HDL (high-density lipoprotein) function are associated with cardiovascular disease. However, the effects of regular exercise on these measures is largely unknown. Thus, we examined the effects of different doses of exercise on 3 measures of HDL function in 2 randomized clinical exercise trials.

Approach and Results—

Radiolabeled and boron dipyrromethene difluoride–labeled cholesterol efflux capacity and HDL-apoA-I (apolipoprotein A-I) exchange were assessed before and after 6 months of exercise training in 2 cohorts: STRRIDE-PD (Studies of Targeted Risk Reduction Interventions through Defined Exercise, in individuals with Pre-Diabetes; n=106) and E-MECHANIC (Examination of Mechanisms of exercise-induced weight compensation; n=90). STRRIDE-PD participants completed 1 of 4 exercise interventions differing in amount and intensity. E-MECHANIC participants were randomized into 1 of 2 exercise groups (8 or 20 kcal/kg per week) or a control group. HDL-C significantly increased in the high-amount/vigorous-intensity group (3±5 mg/dL; P=0.02) of STRRIDE-PD, whereas no changes in HDL-C were observed in E-MECHANIC. In STRRIDE-PD, global radiolabeled efflux capacity significantly increased 6.2% (SEM, 0.06) in the high-amount/vigorous-intensity group compared with all other STRRIDE-PD groups (range, −2.4 to −8.4%; SEM, 0.06). In E-MECHANIC, non-ABCA1 (ATP-binding cassette transporter A1) radiolabeled efflux significantly increased 5.7% (95% CI, 1.2–10.2%) in the 20 kcal/kg per week group compared with the control group, with no change in the 8 kcal/kg per week group (2.6%; 95% CI, −1.4 to 6.7%). This association was attenuated when adjusting for change in HDL-C. Exercise training did not affect BODIPY-labeled cholesterol efflux capacity or HDL-apoA-I exchange in either study.

Conclusions—

Regular prolonged vigorous exercise improves some but not all measures of HDL function. Future studies are warranted to investigate whether the effects of exercise on cardiovascular disease are mediated in part by improving HDL function.

Clinical Trial Registration—

URL: https://www.clinicaltrials.gov. Unique identifiers: NCT00962962 and NCT01264406.

Graphical Abstract

Introduction

HDL (high-density lipoproteins) consist of a wide spectrum of heterogeneous particles that differ in size, density, composition, and biological function. HDL particles have multiple atheroprotective activities, with reverse cholesterol transport thought to be one of the most important.1 A critical first step in reverse cholesterol transport is the efflux of cholesterol from macrophage foam cells in the artery to HDL. This critical first step has been interrogated in multiple observational human studies with an ex vivo macrophage-specific cholesterol efflux assay. Cholesterol efflux capacity has been inversely associated with both prevalent and incident cardiovascular disease (CVD), independent of traditional risk factors including HDL-C (HDL cholesterol) levels.2–5 Furthermore, the rate of HDL-apoA-I (apolipoprotein A-I) exchange (HAE), an indirect measure of cholesterol efflux capacity that measures the ability of apoA-I to exchange on and off HDL,6–8 has been shown to be reduced in patients with metabolic syndrome or acute coronary syndrome (ACS).7,9 These results along with the inability of recent randomized, controlled drug trials, and Mendelian randomization studies to demonstrate a causal relationship between HDL-C and CVD has led to a focus on identifying therapies that improve HDL function (ie, quality) rather than HDL-C quantity.10
Although regular exercise increases HDL-C levels11,12 and alters HDL particle subclass concentrations13,14 in a dose-response manner, its effects on HDL functionality are less well known. Several exercise training studies have demonstrated the beneficial effects of regular exercise on various HDL functions, including endothelial,15 antioxidative,16,17 and anti-inflammatory properties18,19 in adults with CVD, diabetes mellitus, and metabolic syndrome. However, these studies only included one exercise dose and thus the dose-response relationship of exercise and HDL function is currently unknown. Furthermore, few studies have examined the effects of regular exercise on HDL-mediated cholesterol efflux, with mixed results.19–23 These studies were limited by small sample sizes and differing intervention durations, study populations, efflux assays, and cell lines. To date, only 2 studies in patients with CVD20,21 have examined the effects of regular exercise on cholesterol efflux capacity measured using the validated assays from recent longitudinal studies,2,5 namely the efflux of 3H-labeled cholesterol from J774 macrophages to apoB (apolipoprotein B)-depleted plasma or serum. To our knowledge, no study has examined the effects of exercise training on efflux capacity using the fluorescence-labeled (boron dipyrromethene difluoride [BODIPY]) cholesterol4 or HAE assays,7 nor has any study examined these associations in healthy adults. Therefore, the purpose of the present study was to examine the effects of different intensities and doses of exercise on cholesterol efflux capacity and HAE in 2 randomized clinical exercise trials of healthy and prediabetic adults.

Materials and Methods

The effects of standardized, regular endurance exercise on cholesterol efflux capacity were examined across 2 exercise training studies (STRRIDE-PD [Studies of Targeted Risk Reduction Interventions through Defined Exercise, in individuals with Pre-Diabetes] and E-MECHANIC [Examination of Mechanisms of exercise-induced weight compensation]) with 5 distinct exercise interventions, including a lifestyle intervention, which are described below.

STRRIDE-PD Study

The STRRIDE-PD study compared 3 six-month exercise-only groups differing in amount or intensity to a lifestyle intervention group (diet plus exercise group similar to the first 6 months of the Diabetes Prevention Program). Specifically, sedentary, moderately overweight/obese (body mass index, 25–35 kg/m2), nonsmoking adults (n=237) aged 45 to 75 years old with prediabetes (ie, impaired fasting glucose, 100–125 mg/dL; or in up to 20% of the subject population, high normal fasting glucose, 95–99), but no history of diabetes mellitus or CVD, were randomly assigned to 1 of 4 groups (1) low-amount/moderate-intensity exercise (10 kcal/kg per week [KKW] at 50% 2reserve); (2) high-amount/moderate-intensity exercise (16 KKW at 50% 2reserve); (3) high-amount/vigorous-intensity exercise (16 KKW at 75% 2reserve); and (4) clinical lifestyle intervention (diet+exercise): 10 KKW at 50% 2reserve (same as group 1) plus a diet designed to reduce body weight by 7%.24 Overall, 175 participants completed the intervention. The present study included 106 participants that completed the exercise training program and had data for all 3 measures of HDL function. There were no differences in baseline characteristics between subjects with and without HDL function data (data not shown).

E-MECHANIC Study

The E-MECHANIC study was a 3-arm, 6-month randomized (1:1:1) controlled trial. Sedentary, overweight/obese (body mass index, 25–45 kg/m2), nondiabetic (fasting plasma glucose, 76–106 mg/dL), nonsmoking adults with no history of diabetes mellitus or CVD aged 18 to 65 years (n=198) were randomly assigned to a control group or 1 of 2 exercise groups that reflect the current recommendations for (1) general health (8 KKW, or ≈800–1000 kcal/wk) or (2) weight loss (20 KKW, or ≈2000–2500 kcal/wk). In the 2 exercise groups, the exercise intensity for each participant was set at a target heart rate associated with 65% to 85% of peak oxygen uptake (2peak).25 The present study included 90 participants that completed the study and had data for all 3 measures of HDL function.

Blood Draws and Lipids

In STRRIDE-PD, blood samples were taken after a 10-hour fast at baseline and between 16 to 24 hours after the last exercise training session. In E-MECHANIC, blood was collected after a 12-hour fast at baseline and during the last week of exercise (24–72 hours after last exercise session). In both studies, measurement of total cholesterol, HDL-C, and triglycerides was performed on a Beckman Coulter DXC 600 Pro system (Brea, CA) using standardized methods. In STRRIDE-PD, comprehensive lipoprotein subfraction analysis was also performed before and after exercise training via nuclear magnetic resonance (NMR) spectroscopy using the LipoProfile-3 algorithm (LipoScience, Inc, now LabCorp, Morrisville, NC) as previously described.26 GlycA concentration was also assessed via NMR spectroscopy as described previously.27

Assessment of HDL Function

All assays were performed on stored (−80°C) baseline and post-training plasma (STRRIDE-PD) or serum (E-MECHANIC) samples. Change in each individual HDL function was calculated as the absolute difference between the post-training and baseline values.

General Cholesterol Efflux Capacity Assay Procedures

The following procedures were common to both the radiolabeled (3H) and fluorescence-labeled cholesterol efflux capacity assays. Global and ABCA1 (ATP-binding cassette transporter A1)-mediated cholesterol efflux were measured using J774 mouse macrophage cells in the presence and absence of cAMP. Cells were incubated with 3H- or fluorescence-labeled cholesterol and 2 μg/mL acyl–coenzyme A:cholesterol acyltransferase inhibitor inhibitor (Sandoz, Sigma-Aldrich). Cells were then incubated overnight in 0.2% BSA with or without 8-(4-chlorophenylthio)-cAMP. After washing, the cholesterol-labeled cells were incubated with 2.8% apoB-depleted plasma/serum for 4 hours. The amount of 3H- or fluorescence-labeled cholesterol released was measured through liquid scintillation counting or spectrophotometry, respectively. Cholesterol efflux capacity is calculated as the amount of effluxed cholesterol expressed as a fraction (%) of the initial cell content of cholesterol. Results were normalized to the measured efflux by a pooled reference apoB-depleted sample evaluated on every plate. All samples were run in duplicate and the average value is reported.

3H-Cholesterol Efflux Capacity Assay

Measurement of the efflux of radiolabeled cholesterol from J774 macrophages to apoB depleted plasma/serum was performed with the use of a previously described method.2 This assay quantifies total efflux mediated by known pathways of cholesterol efflux from macrophages, including ABCA1 and G1 (ABCG1), scavenger receptor B1, and aqueous diffusion.28 Because of timing issues, the radiolabeled cholesterol efflux capacity assay was performed in different laboratories, with Dr Anand Rohatgi’s laboratory at the University of Texas Southwestern Medical Center analyzing plasma samples from STRRIDE-PD and Vascular Strategies (Plymouth Meeting, PA) analyzing serum samples from E-MECHANIC. As such, the methods slightly differed between the 2 laboratories. The assays in STRRIDE-PD were performed with stimulation by cAMP, which upregulates ABCA1 and thus represents global efflux. The assays in E-MECHANIC were performed with and without stimulation by cAMP, thus providing values for global efflux, as well as non-ABCA1 dependent efflux.29 ABCA1-dependent efflux was calculated as the difference between global (+cAMP) and non-ABCA1 (−cAMP) efflux.

BODIPY-Cholesterol Efflux Capacity Assay

The efflux of BODIPY-labeled cholesterol from J774 macrophages to apoB depleted plasma (STRRIDE-PD) or serum (E-MECHANIC) was measured using a high throughput cell-based assay performed in 96-well plates as described previously.4 The Rohatgi laboratory performed the BODIPY-efflux assays for both cohorts (STRRIDE-PD and E-MECHANIC). The BODIPY-efflux assays were performed with stimulation by cAMP, thus providing values for global cholesterol efflux only.

HDL-apoA-I Exchange Assay

HAE measures the ability of spin-labeled apoA-I to exchange on and off of HDL, thus representing HDL remodeling dynamics as well as potential cholesterol efflux capacity. The HAE assay was performed in Dr Michael Oda’s laboratory at Children’s Hospital Oakland Research Institute, as described previously.6,7 Briefly, apoB-depleted plasma or serum was prepared through polyethylene glycol precipitation and mixed with 3 mg/mL spin-labeled apoA-I30 in a 3:1 ratio. After incubation for 15 minutes at 37°C, electron paramagnetic resonance measurements were performed with Bruker eScan (STRRIDE-PD) or EMX Nano (E-MECHANIC) spectrometers. HAE activity represents the sample:internal standard signal ratio at 37°C. All samples were read in duplicate and averaged.

Assessment of Cardiometabolic Traits

The E-MECHANIC study included measures of body composition via dual-energy X-ray absorptiometry, fasting blood glucose, resting metabolic rate, and energy intake and expenditure through food intake tests and doubly labeled water.25 The STRRIDE-PD study measured body composition using air plethysmography (BodPod) and insulin and glucose traits through a 2-hour oral glucose tolerance test using standard protocols.24

Statistical Analysis

Paired t tests were used to examine the effects of exercise training on each of the measured HDL functions in all exercise groups combined, as well as within each exercise group. In E-MECHANIC, 2 sample t tests were used to compare changes in HDL function between 6-month follow-up and baseline between each exercise group and the control group. Normality and equal variance tests were performed on baseline and post-training measures of HDL function and revealed all but baseline HAE were normally distributed. Results were unchanged using nonparametric tests for HAE, thus all results for change in HAE with exercise are for parametric tests.
General linear models adjusted for age, sex, race, baseline body mass index, and baseline value (of dependent variable) were used to examine the effects of training on measures of cholesterol efflux capacity across exercise intervention groups. Pearson correlations were used to examine the relationships between all 3 measures of HDL function. Multivariable stepwise regression models were used to examine baseline predictors of exercise-induced changes in each measure of HDL function. Baseline predictors in STRRIDE-PD included baseline trait value, body composition, NMR-measured HDL subfraction concentrations, standard lipid panel, cardiorespiratory fitness, and measures of insulin and glucose homeostasis. Baseline predictors in E-MECHANIC included baseline value, body mass index, standard lipid panel, blood pressure, glucose, and energy intake and expenditure. All analyses were performed separately within each study cohort using SAS 9.4 (Cary, NC), with statistical significance set at a 2-tailed P<0.05.

Results

The basic characteristics of the participants from STRRIDE-PD and E-MECHANIC at baseline and in response to the interventions can be found in Tables 1 and 2, respectively. At baseline there were no differences between groups within each study for any of the variables presented. The use of cholesterol lowering medications was low and did not show much change during the intervention across both studies, as 21% and 17% of STRRIDE-PD subjects (Table 1) and 12% of E-MECHANIC subjects (Table 2) were taking cholesterol lowering medications at baseline and 6 months, respectively. Aside from 1 subject at baseline in STRRIDE-PD, at both time points in both studies all subjects listed as taking cholesterol lowering medications were taking a form of statin. Across both studies, women had higher baseline levels of HAE and HDL-C compared with men, whereas in E-MECHANIC women had higher baseline levels of radiolabeled non-ABCA1 efflux and lower triglycerides compared with men (data not shown).
Table 1. Basic Characteristics of STRRIDE-PD Participants
Variable STRRIDE-PD Group (n=106 total)
Low-Mod (n=29)High-Mod (n=27)High-Vig (n=24)Clinical Lifestyle (n=26)
Male/female, n11/1811/168/169/17
White, %79817177
Age, y56.8±8.161.0±6.558.6±6.757.0±7.9
Cholesterol medication use, n (%)Baseline6 (21%)3 (11%)6 (25%)7 (27%)
Post-training6 (21%)3 (11%)5 (21%)4 (15%)
Weight, kgBaseline87.4±11.586.6±11.984.9±9.988.4±16.0
Delta*−0.5±3.0−1.5±2.8†−1.5±3.2†−6.5±5.5‡
BMI, kg/m2Baseline31.3±1.131.6±5.130.4±4.431.6±6.8
Delta*−0.2±1.0−0.6±1.1†−0.6±1.1†−2.3±1.9‡
HDL-C, mg/dLBaseline48±2446±1345±1243±12
Delta−2±140±53±5†2±7
TG, mg/dLBaseline125±57116±36136±77119±58
Delta§1±4614±45−14±46−23±36†
Total cholesterol, mg/dLBaseline188±40190±27184±25177±33
Delta1±230±18−2±16−6±22
3H efflux (global)Baseline0.7±0.20.8±0.30.9±0.20.9±0.2
Delta−0.03±0.1−0.04±0.20.05±0.2−0.04±0.1
BODIPY effluxBaseline0.6±0.20.71±0.20.7±0.20.7±0.2
Delta0.04±0.2−0.02±0.1−0.02±0.2−0.06±0.2
HAEBaseline49.8±11.847.2±9.748.8±10.249.4±7.5
Delta−1.5±7.91.3±5.51.6±4.60.2±6.5
Data represented as mean±SD. Delta=post-training value−baseline value. BMI indicates body mass index; BODIPY, boron dipyrromethene difluoride; HAE, HDL-apoA-I exchange; HDL-C, HDL cholesterol; STRRIDE-PD, Studies of Targeted Risk Reduction Interventions through Defined Exercise, in individuals with Pre-Diabetes; and TG, triglycerides.
*
Clinical lifestyle mean value significantly different from all other groups. P<0.0001 for differences in mean values between groups.
†
P<0.05 for within group training response (paired t test of difference from baseline).
‡
P<0.0001 for within group training response (paired t test of difference from baseline).
§
High-Mod group different from Low-Mod and Clinical lifestyle groups. P=0.04 for differences in mean values between groups.
Table 2. Basic Characteristics of E-MECHANIC Participants
Variable E-MECHANIC Group (n=90 total)
Control (n=29)8 KKW (n=33)20 KKW (n=28)
Male/female, n9/206/278/20
White, %726771
Age, y50.2±11.048.9±10.745.7±13.9
Cholesterol medication use, n (%)Baseline5 (17%)3 (9%)3 (11%)
Post-training6 (21%)3 (9%)3 (11%)
Weight, kgBaseline90.3±15.490.7±17.483.4±13.8
Delta0.4±3.50.3±2.9−1.4±3.1*
BMI, kg/m2Baseline32.4±4.632.2±4.929.9±4.4
Delta†0.2±1.20.07±1.0−0.5±1.1*
HDL-C, mg/dLBaseline58±1560±1557±20
Delta−2±7−1±81±6
TG, mg/dLBaseline117±57106±4598±50
Delta−3±49−10±39−1±30
Total cholesterol, mg/dLBaseline209±27199±35189±40
Delta−16±31−2±172±20
3H efflux (global)Baseline0.87±0.20.82±0.20.83±0.2
Delta−0.03±0.10.01±0.2−0.01±0.1
BODIPY effluxBaseline0.94±0.30.87±0.30.86±0.3
Delta−0.08±0.2−0.06±0.2−0.03±0.3
HAEBaseline63.3±12.362.4±8.660.7±12.7
Delta−2.4±9.01.4±8.80.9±11.1
Data represented as mean±SD. Delta=post-training value−baseline value. BMI indicates body mass index; BODIPY, boron dipyrromethene difluoride; E-MECHANIC, Examination of Mechanisms of exercise-induced weight compensation; HAE, HDL-apoA-I exchange; HDL-C, HDL cholesterol; KKW, kcal/kg per wk; and TG, triglycerides.
*
P<0.05 for within group training response (paired t test of difference from baseline).
†
P=0.04 for differences in mean values between groups. Mean value for 20 KKW group significantly different from control and 8 KKW groups.

Exercise Training and HDL-C

In STRRIDE-PD, exercise training resulted in a significant increase in HDL-C in the high-amount/vigorous group only (Table 1), whereas no significant changes in HDL-C were observed within exercise groups or between the exercise groups and the control group after exercise training in E-MECHANIC (Table 2).

Exercise Training and 3H-Labeled Cholesterol Efflux

STRRIDE-PD

There was a significant effect of intervention group (P=0.04) on change in global radiolabeled efflux capacity, with the high-amount/vigorous-intensity group showing significantly larger exercise-induced increases in global radiolabeled efflux compared with the other 3 groups (Figure 1). Specifically, the high-amount/vigorous-intensity group increased radiolabeled efflux by an average of 6.2% (SEM, 6.1) in adjusted models, whereas the adjusted mean change was −8.4% (SEM, 6.6) in the low amount/moderate intensity group, −4.2% (SEM, 6.5) in the high-amount/moderate intensity group, and −2.4% (SEM, 6.0) in the clinical lifestyle group, respectively. The overall group difference was attenuated when also adjusting for change in HDL-C (P=0.09), but the differences between the high-amount/vigorous-intensity group and the other groups remained (P<0.05).
Figure 1. Adjusted mean (SEM) percent change of radiolabeled global efflux (A) and BODIPY-labeled global efflux (B) in response to exercise training in STRRIDE-PD. Values adjusted for age, sex, race, baseline BMI, and baseline value. ap=0.005 and bp<0.05 for difference from High-Vig. BMI indicates body mass index; BODIPY, boron dipyrromethene difluoride; and STRRIDE-PD, Studies of Targeted Risk Reduction Interventions through Defined Exercise, in individuals with Pre-Diabetes.

E-MECHANIC

No significant changes in radiolabeled efflux capacity were observed after 6 months of exercise training compared with baseline in the individual exercise groups. However, there was a significant effect of group (P=0.046) on percent change in non-ABCA1 dependent efflux, as the 20 KKW group showed a 5.7% (95% CI, 1.2–10.2%) greater increase in non-ABCA1 efflux compared with the control group (Figure 2). This association was attenuated when also adjusting for change in HDL-C (P=0.07). No significant differences compared with the control group were found in either exercise group for radiolabeled global or ABCA1 efflux capacity.
Figure 2. Adjusted mean (SEM) percent change of radiolabeled global (A), ABCA1 (B), and non-ABCA1 (C) efflux, and BODIPY-labeled global efflux (D) in response to exercise training in E-MECHANIC. Values adjusted for age, sex, race, baseline BMI, and baseline value. ap=0.01 for difference from control group. ABCA1 indicates ATP-binding cassette transporter A1; BMI, body mass index; BODIPY, boron dipyrromethene difluoride; E-MECHANIC, Examination of Mechanisms of exercise-induced weight compensation; and KKW, kcal/kg per wk.

Exercise Training and BODIPY-Labeled Cholesterol Efflux

STRRIDE-PD

In STRRIDE-PD, there was no effect of exercise training on BODIPY-efflux capacity in any of the 4 groups, nor were there any group differences in BODIPY-efflux responses to training (Figure 1).

E-MECHANIC

No significant changes in BODIPY-labeled efflux capacity were observed after 6 months of exercise training in E-MECHANIC, with both exercise groups experiencing an average decrease (Figure 2). Similarly, there were no differences between the individual exercise groups and the control group for changes in BODIPY-efflux capacity in either unadjusted or adjusted models.

Exercise Training and HDL-apoA-I-Exchange

STRRIDE-PD and E-MECHANIC

No significant changes in HAE were observed after 6 months of exercise training in STRRIDE-PD or E-MECHANIC (Figure I in the online-only Data Supplement). In general, all exercise groups experienced a (nonsignificant) mean increase in HAE, except the low amount/moderate intensity group of STRRIDE-PD.

Baseline Predictors of Exercise-Induced Changes in HDL Function

STRRIDE-PD

In multivariable regression models in the combined exercise groups of STRRIDE-PD, baseline value was the strongest predictor of exercise-induced changes in all 3 measures of HDL function (Table I in the online-only Data Supplement). Specifically, baseline levels of radiolabeled cholesterol efflux, BODIPY-labeled cholesterol efflux, and HAE explained 8.5% (P=0.005), 19.6% (P<0.0001), and 17.4% (P<0.0001) of the variance in the exercise-induced change of each respective measure. The correlations between baseline and change values in the combined groups of STRRIDE-PD were −0.28 (P=0.004) for radiolabeled efflux, −0.44 (P<0.0001) for BODIPY efflux, and −0.39 (P<0.0001) for HAE.
Other significant baseline predictors in the models included concentration of medium HDL particles (HDL-P) and total cholesterol for change in radiolabeled efflux; total cholesterol, GlycA (NMR marker of inflammation), and insulin area under the curve for change in BODIPY efflux; and total HDL-P, VO2max, and exercise group for change in HAE (Table I in the online-only Data Supplement).

E-MECHANIC

In multivariable regression models in the combined exercise groups of E-MECHANIC, baseline levels of BODIPY-labeled cholesterol efflux and HAE explained 31.5% and 24.3% of the variance in the exercise-induced change of each respective measure (both P<0.0001; Table II in the online-only Data Supplement). However, baseline triglycerides level was the strongest and lone predictor of exercise-induced change in radiolabeled efflux, explaining 12.3% (P=0.006), 10.5% (P=0.01), and 12.0% (P=0.006) of the variance in change in global, ABCA1, and non-ABCA1 efflux capacity, respectively (Table II in the online-only Data Supplement). Baseline cholesterol medication use explained 4.2% (P=0.02) of the variance in change in BODIPY-labeled efflux.
In the combined exercise groups, the correlation between baseline and change values was only significant for BODIPY-labeled efflux at r=−0.64 (P<0.0001), with the correlation much stronger in the 8 KKW group (r=−0.81; P<0.0001) compared with the 20 KKW group (r=−0.39; P=0.01).

Correlation of 3 Measures of HDL Function

There was no correlation between baseline radiolabeled and BODIPY-labeled cholesterol efflux capacity in either study, whereas baseline global radiolabeled efflux capacity was significantly correlated with HAE in both studies (E-MECHANIC: r=0.50, P<0.0001; STRRIDE-PD: r=0.25, P=0.01). In E-MECHANIC the correlation between baseline HAE and ABCA1 and non-ABCA1 radiolabeled efflux was 0.48 (P<0.0001) and 0.36 (P=0.0005), respectively. In STRRIDE-PD, exercise training-induced change in global radiolabeled efflux capacity was positively correlated with change in HAE (r=0.25, P=0.009). In E-MECHANIC, there were no correlations between exercise-induced changes in any of the measures of HDL function.
There was large interindividual variation in the responsiveness of all 3 measures of HDL function to exercise training, as shown in Figure II in the online-only Data Supplement. Heat maps displaying the direction of exercise response (positive or negative) across the 3 HDL function traits, as well as HDL-C, are shown for each participant of STRRIDE-PD and E-MECHANIC in Figure III in the online-only Data Supplement. In both studies, there did not appear to be any clear patterns of exercise response across the 3 measures of HDL function, as 13% to 14% of participants were nonresponders across all 3 measures (ie, value did not change or decreased with training), 35% to 38% were nonresponders for 2 of 3 measures, 35% to 37% were responders (ie, value increased with training) for 2 of 3, and 12% to 14% were responders for all 3 measures (Figure IV in the online-only Data Supplement).

Correlation of HDL Function With Cardiometabolic Traits

The correlation of HDL function traits with cardiometabolic traits, including NMR-measured lipoprotein subfractions, body composition, cardiorespiratory fitness, and insulin- and glucose-related traits, at baseline and in response to exercise training for both studies are shown by sex in Tables III through VI in the online-only Data Supplement.

STRRIDE-PD

Changes With Training
In men, changes in radiolabeled global efflux were positively correlated with change in body weight (r=0.41, P=0.01) and waist circumference (r=0.44, P=0.01), whereas change in BODIPY-labeled efflux was positively correlated with change in hip circumference (r=0.41, P=0.02). In women, change in radiolabeled global efflux was negatively correlated with change in the Matsuda Index of insulin sensitivity (r=−0.32, P=0.01) and positively with change in total HDL-P, HDL-P size, and HDL-C (range: r=0.25 to 035, P<0.05; Table IV in the online-only Data Supplement).

E-MECHANIC

Changes With Training (Exercise Groups Only)
Change in HAE was correlated with change in percent body fat (r=−0.41, P=0.04) and change in total daily energy expenditure (r=0.50, P=0.009) in men. Change in radiolabeled global, ABCA1, and non-ABCA1 (range: r=−0.57 to −0.63, P≤0.03) efflux were negatively correlated with change in proportion of calories from fat, whereas non-ABCA1 efflux was negatively correlated with change in total caloric intake (r=−0.57, P=0.03) in men. No significant correlations between change variables were found in women (Table VI in the online-only Data Supplement).

Discussion

The present study is the first to examine the effects of exercise training on radiolabeled efflux, BODIPY-labeled efflux, and HAE in the same individuals. The major finding was that across 2 randomized trials comprising 6 different exercise interventions, regular endurance exercise improved radiolabeled cholesterol efflux capacity only when a high amount of vigorous exercise was performed. Specifically, global radiolabeled cholesterol efflux capacity increased with exercise training in the high-amount, vigorous-intensity group of STRRIDE-PD, whereas non-ABCA1 radiolabeled cholesterol efflux capacity increased in the 20 KKW group of E-MECHANIC. Alternatively, regular endurance exercise nor regular endurance exercise plus weight loss (ie, clinical lifestyle group of STRRIDE-PD) resulted in significant improvements in ABCA1 radiolabeled efflux, BODIPY-labeled efflux, or HAE.
Our results are in general agreement with those from 2 recent investigations of the effects of exercise training on radiolabeled cholesterol efflux capacity from J774 macrophage cells in subjects with peripheral artery disease20 and ACS.21 A 6-month treadmill exercise program in 33 patients and 26 controls with peripheral artery disease found no effects of training on radiolabeled cholesterol efflux capacity.20 However, it is possible that the peripheral artery disease patients did not reach a sufficient intensity of exercise to induce changes in efflux, as the program began with walking at 2.0 mph or lower. Conversely, Koba et al15 found that 6 months of cardiac rehabilitation (intensity of 40% to 60% of heart rate reserve) significantly increased radiolabeled cholesterol efflux capacity in 57 patients with ACS compared with baseline levels, but not in comparison to 11 controls who did not undergo the rehabilitation program. Further subgroup analysis found that the significant increases in cholesterol efflux capacity were only observed in ACS patients (n=10) with high exercise tolerance and complete risk factor control.21
Taken together with the present results, these findings suggest that an exercise intensity and dose threshold may need to be exceeded to improve radiolabeled cholesterol efflux capacity. The existing literature on the effects of exercise training on HDL-C and HDL-P subclass traits indicates that exercise volume, rather than intensity, has the greatest influence on the HDL profile. Specifically, it is well-established that a dose-response relationship exists between exercise training volume and changes in HDL-C, with the literature suggesting an exercise threshold of 1200 to 2200 kcal/week to elicit favorable changes in HDL-C.11 Furthermore, the STRRIDE I study found that increases in the mean size of HDL-P and concentration of large HDL-P were related to the amount of exercise and not the intensity of exercise.13 The present study suggests that exercise intensity may be more important than volume in terms of improving cholesterol efflux capacity, however further dose-response studies are needed to verify these results across diverse exercise interventions and populations.
Both of the previously mentioned studies differ from the present study in terms of their inclusion of CVD patients and their high rate of statin usage. In the study of peripheral artery disease patients, 75% were on statins during the trial, although statin use was controlled for in the analyses.20 In the cardiac rehabilitation study, 70% of the ACS patients started or strengthened their statin treatment over the course of the intervention and the authors found increases in cholesterol efflux capacity were limited to this subgroup.21 In the present study statin use was low, with only 11 (5 controls, 6 exercise group) of 90 subjects (12%) in E-MECHANIC and 22 of 106 subjects in STRRIDE-PD (21%) on cholesterol lowering medications (mostly statins) at baseline. This small sample size of subjects taking cholesterol medications precluded us from performing stratified analyses. Overall, although statins cause modest increases in HDL-C and apoA-I, the impact of statin therapy on cholesterol efflux capacity is likely insignificant as studies have shown both small positive31–34 and null2,35–38 associations of statins on efflux capacity.
Our findings of increases in global and non-ABCA1 radiolabeled cholesterol efflux capacity, but no changes in ABCA1 radiolabeled efflux, BODIPY-labeled efflux, and HAE agree with the known effects of exercise on HDL metabolism and remodeling. Namely, on average exercise increases HDL particle size, the concentration of large HDL particles, HDL-C, and apoA-I.11,14 These findings also reflect the inherent differences in the radiolabeled and BODIPY-labeled efflux assays. The efflux of cholesterol from macrophages is mediated by 4 known pathways: ABCA1, ATP-binding cassette transporter G1, scavenger receptor B1, and aqueous diffusion. In J774 macrophage cells stimulated with cAMP and labeled with 3H-cholesterol, global cholesterol efflux represents all 4 pathways (ABCA1: 34%, scavenger receptor B1: 20%, aqueous diffusion: 46%, ATP-binding cassette transporter G1: negligible).39 In contrast, J774 macrophage cells stimulated with cAMP and labeled with BODIPY-cholesterol primarily measures ABCA1-mediated cholesterol efflux.40 ABCA1-mediated efflux is associated with lipid-poor apoA-I acceptor particles (pre-β–HDL), whereas ATP-binding cassette transporter G1 mediates cholesterol efflux to mature HDL particles.41 HAE provides a measure of the ability of HDL to remodel and release lipid-poor apoA-I.7,8 A recent study found HAE was a significant contributor to global- and ABCA1-specific radiolabeled efflux, independent of HDL-C, explaining ≈25% of the variance in both measures.6
Given that exercise is known to increase HDL size and the concentration of large HDL particles, it is more likely that the global and non-ABCA1 efflux pathways would be increased with exercise as compared with ABCA1-mediated efflux, as found in our study. It is also thought that pre-β–HDL rapidly remodels to α-HDL with exercise.42 This may also explain why we only observed changes in radiolabeled efflux measures and not BODIPY efflux or HAE with exercise training. In STRRIDE-PD, the concentration of large HDL-P significantly increased and small HDL-P significantly decreased in response to exercise training, which was reflected by a significant increase in mean HDL-P size (data not shown). Given that the concentration of total HDL-P did not change with training, the exercise-induced changes in NMR-based HDL subfractions likely reflect a shift of pre-β1–HDL to larger HDL particles (as opposed to de novo large HDL-P synthesis) and thus may correspond to the absence of changes in ABCA1-mediated radiolabeled and BODIPY-labeled efflux and HAE observed in the present study.
Previous studies have used other cellular models to examine the effects of exercise on cholesterol efflux capacity with mostly null results. One study found that a 4-month aerobic exercise training program did not alter HDL3-mediated 14C-labeled cholesterol efflux from Swiss mouse peritoneal macrophages in 11 healthy and 11 diabetic subjects.23 A 10-week walk/run interval program in 27 subjects with metabolic syndrome found no changes in the efflux of 3H-labeled cholesterol from RAW264.7 macrophages to HDL3.19 Last, a study of 15 obese women found that a 9-week lifestyle intervention significantly increased cholesterol efflux of 14C-labeled cholesterol from macrophages (derived from THP1 monocytes) to whole serum in only the 13 women that exhibited significant weight loss.22 Although the confluence of results from the existing literature, including the present study, suggest little to no effects of regular endurance exercise on cholesterol efflux capacity, differences in efflux assay, study populations, study duration, and exercise programs make it difficult to directly compare results across studies. As described by Ronsein and Vaisar,39 existing assays of efflux capacity differ by cell type and cholesterol acceptor and can vary widely between different laboratories. The absence of standards and controls (eg, normalizing efflux values relative to a pooled control sample in each assay) may affect the accuracy and comparability of the assays. To date, only the radio- and BODIPY-labeled efflux assays using J774 macrophages have been validated in clinical populations.2–5 Despite both efflux capacity assays showing agreement in their association with CVD outcomes, we found no correlation between the 2 measures in either training cohort. However, we did replicate the strong to moderate correlations between radiolabeled efflux and HAE as previously shown by Borja et al.6
The present study represents the largest examination to date of the effects of exercise interventions on validated measures of HDL function and is further aided by the inclusion of different doses of exercise and high adherence rates in both cohorts. However, our study also has several limitations. Radiolabeled cholesterol efflux capacity was measured in 2 different laboratories with slightly different methods (±cAMP stimulation). Furthermore, both studies were lacking measures of apoA-I, whereas the E-MECHANIC study lacked NMR measures of lipoprotein subfractions, for correlation with the HDL function measures.
In conclusion, HDL dysfunction likely manifests before the diagnosis of CVD. Thus, treatments that can attenuate or prevent HDL dysfunction are highly desirable. Although exercise represents a promising therapeutic option in combating HDL dysfunction (more so than weight loss based on our results), the jury is still out on whether exercise produces beneficial effects on clinically relevant measures of HDL functionality. We found little effect of 6 months of exercise training on cholesterol efflux capacity and HAE, with only the highest doses of exercise improving radiolabeled efflux capacity. Future studies using standardized methodologies in diverse populations are needed to determine the effects of exercise on the atheroprotective properties of HDL and the mechanisms mediating these effects.

Highlights

This article has been corrected.
VIEW CORRECTION
•
A high dose of vigorous-intensity exercise maintained over 6 months increased radiolabeled cholesterol efflux capacity in previously sedentary adults.
•
Baseline levels were the strongest predictors of exercise-induced changes in HDL (high-density lipoprotein) function.
•
Future dose-response studies are needed to verify these results and examine whether exercise-induced improvements in HDL function reduce the risk of cardiovascular disease.

Footnote

Nonstandard Abbreviations and Acronyms

ABCA1
ATP-binding cassette transporter A1
ACS
acute coronary syndrome
apo
apolipoprotein
BMI
body mass index
BODIPY
boron dipyrromethene difluoride
CVD
cardiovascular disease
E-MECHANIC
Examination of Mechanisms of exercise-induced weight compensation
HDL
high-density lipoprotein
HDL-C
HDL cholesterol
HDL-P
HDL particle
HAE
HDL-apoA-I exchange
KKW
kilocalories per kilogram per week
NMR
nuclear magnetic resonance
STRRIDE-PD
Studies of Targeted Risk Reduction Interventions through Defined Exercise, in individuals with Pre-Diabetes

References

1.
deGoma EM, deGoma RL, Rader DJ. Beyond high-density lipoprotein cholesterol levels evaluating high-density lipoprotein function as influenced by novel therapeutic approaches. J Am Coll Cardiol. 2008;51:2199–2211. doi: 10.1016/j.jacc.2008.03.016.
Crossref
PubMed
Google Scholar
2.
Khera AV, Cuchel M, de la Llera-Moya M, Rodrigues A, Burke MF, Jafri K, French BC, Phillips JA, Mucksavage ML, Wilensky RL, Mohler ER, Rothblat GH, Rader DJ. Cholesterol efflux capacity, high-density lipoprotein function, and atherosclerosis. N Engl J Med. 2011;364:127–135. doi: 10.1056/NEJMoa1001689.
Crossref
PubMed
Google Scholar
3.
Ritsch A, Scharnagl H, März W. HDL cholesterol efflux capacity and cardiovascular events. N Engl J Med. 2015;372:1870–1871. doi: 10.1056/NEJMc1503139#SA3.
Crossref
PubMed
Google Scholar
4.
Rohatgi A, Khera A, Berry JD, Givens EG, Ayers CR, Wedin KE, Neeland IJ, Yuhanna IS, Rader DR, de Lemos JA, Shaul PW. HDL cholesterol efflux capacity and incident cardiovascular events. N Engl J Med. 2014;371:2383–2393. doi: 10.1056/NEJMoa1409065.
Crossref
PubMed
Google Scholar
5.
Saleheen D, Scott R, Javad S, Zhao W, Rodrigues A, Picataggi A, Lukmanova D, Mucksavage ML, Luben R, Billheimer J, Kastelein JJ, Boekholdt SM, Khaw KT, Wareham N, Rader DJ. Association of HDL cholesterol efflux capacity with incident coronary heart disease events: a prospective case-control study. Lancet Diabetes Endocrinol. 2015;3:507–513. doi: 10.1016/S2213-8587(15)00126-6.
Crossref
PubMed
Google Scholar
6.
Borja MS, Ng KF, Irwin A, Hong J, Wu X, Isquith D, Zhao XQ, Prazen B, Gildengorin V, Oda MN, Vaisar T. HDL-apolipoprotein A-I exchange is independently associated with cholesterol efflux capacity. J Lipid Res. 2015;56:2002–2009. doi: 10.1194/jlr.M059865.
Crossref
PubMed
Google Scholar
7.
Borja MS, Zhao L, Hammerson B, Tang C, Yang R, Carson N, Fernando G, Liu X, Budamagunta MS, Genest J, Shearer GC, Duclos F, Oda MN. HDL-apoA-I exchange: rapid detection and association with atherosclerosis. PLoS One. 2013;8:e71541. doi: 10.1371/journal.pone.0071541.
Crossref
PubMed
Google Scholar
8.
Cavigiolio G, Geier EG, Shao B, Heinecke JW, Oda MN. Exchange of apolipoprotein A-I between lipid-associated and lipid-free states: a potential target for oxidative generation of dysfunctional high density lipoproteins. J Biol Chem. 2010;285:18847–18857. doi: 10.1074/jbc.M109.098434.
Crossref
PubMed
Google Scholar
9.
Borja MS, Hammerson B, Tang C, Savinova OV, Shearer GC, Oda MN. Apolipoprotein A-I exchange is impaired in metabolic syndrome patients asymptomatic for diabetes and cardiovascular disease. PLoS One. 2017;12:e0182217. doi: 10.1371/journal.pone.0182217.
Crossref
PubMed
Google Scholar
10.
Toth PP, Barter PJ, Rosenson RS, Boden WE, Chapman MJ, Cuchel M, D’Agostino RB, Davidson MH, Davidson WS, Heinecke JW, Karas RH, Kontush A, Krauss RM, Miller M, Rader DJ. High-density lipoproteins: a consensus statement from the National Lipid Association. J Clin Lipidol. 2013;7:484–525. doi: 10.1016/j.jacl.2013.08.001.
Crossref
PubMed
Google Scholar
11.
Durstine JL, Grandjean PW, Davis PG, Ferguson MA, Alderson NL, DuBose KD. Blood lipid and lipoprotein adaptations to exercise: a quantitative analysis. Sports Med. 2001;31:1033–1062.
Crossref
PubMed
Google Scholar
12.
Kodama S, Tanaka S, Saito K, Shu M, Sone Y, Onitake F, Suzuki E, Shimano H, Yamamoto S, Kondo K, Ohashi Y, Yamada N, Sone H. Effect of aerobic exercise training on serum levels of high-density lipoprotein cholesterol: a meta-analysis. Arch Intern Med. 2007;167:999–1008. doi: 10.1001/archinte.167.10.999.
Crossref
PubMed
Google Scholar
13.
Kraus WE, Houmard JA, Duscha BD, Knetzger KJ, Wharton MB, McCartney JS, Bales CW, Henes S, Samsa GP, Otvos JD, Kulkarni KR, Slentz CA. Effects of the amount and intensity of exercise on plasma lipoproteins. N Engl J Med. 2002;347:1483–1492. doi: 10.1056/NEJMoa020194.
Crossref
PubMed
Google Scholar
14.
Sarzynski MA, Burton J, Rankinen T, et al. The effects of exercise on the lipoprotein subclass profile: a meta-analysis of 10 interventions. Atherosclerosis. 2015;243:364–372. doi: 10.1016/j.atherosclerosis.2015.10.018.
Crossref
PubMed
Google Scholar
15.
Adams V, Besler C, Fischer T, et al. Exercise training in patients with chronic heart failure promotes restoration of high-density lipoprotein functional properties. Circ Res. 2013;113:1345–1355. doi: 10.1161/CIRCRESAHA.113.301684.
Crossref
PubMed
Google Scholar
16.
Casella-Filho A, Chagas AC, Maranhão RC, Trombetta IC, Cesena FH, Silva VM, Tanus-Santos JE, Negrão CE, da Luz PL. Effect of exercise training on plasma levels and functional properties of high-density lipoprotein cholesterol in the metabolic syndrome. Am J Cardiol. 2011;107:1168–1172. doi: 10.1016/j.amjcard.2010.12.014.
Crossref
PubMed
Google Scholar
17.
Iborra RT, Ribeiro IC, Neves MQ, Charf AM, Lottenberg SA, Negrão CE, Nakandakare ER, Passarelli M. Aerobic exercise training improves the role of high-density lipoprotein antioxidant and reduces plasma lipid peroxidation in type 2 diabetes mellitus. Scand J Med Sci Sports. 2008;18:742–750. doi: 10.1111/j.1600-0838.2007.00748.x.
Crossref
PubMed
Google Scholar
18.
Roberts CK, Ng C, Hama S, Eliseo AJ, Barnard RJ. Effect of a short-term diet and exercise intervention on inflammatory/anti-inflammatory properties of HDL in overweight/obese men with cardiovascular risk factors. J Appl Physiol (1985). 2006;101:1727–1732. doi: 10.1152/japplphysiol.00345.2006.
Crossref
PubMed
Google Scholar
19.
Sang H, Yao S, Zhang L, Li X, Yang N, Zhao J, Zhao L, Si Y, Zhang Y, Lv X, Xue Y, Qin S. Walk-run training improves the anti-inflammation properties of high-density lipoprotein in patients with metabolic syndrome. J Clin Endocrinol Metab. 2015;100:870–879. doi: 10.1210/jc.2014-2979.
Crossref
PubMed
Google Scholar
20.
Albaghdadi MS, Wang Z, Gao Y, Mutharasan RK, Wilkins J. High-density lipoprotein subfractions and cholesterol efflux capacity are not affected by supervised exercise but are associated with baseline interleukin-6 in patients with peripheral artery disease. Front Cardiovasc Med. 2017;4:9. doi: 10.3389/fcvm.2017.00009.
Crossref
PubMed
Google Scholar
21.
Koba S, Ayaori M, Uto-Kondo H, Furuyama F, Yokota Y, Tsunoda F, Shoji M, Ikewaki K, Kobayashi Y. Beneficial effects of exercise-based cardiac rehabilitation on high-density lipoprotein-mediated cholesterol efflux capacity in patients with acute coronary syndrome. J Atheroscler Thromb. 2016;23:865–877. doi: 10.5551/jat.34454.
Crossref
PubMed
Google Scholar
22.
Králová Lesná I, Suchánek P, Kovár J, Poledne R. Life style change and reverse cholesterol transport in obese women. Physiol Res. 2009;58(suppl 1):S33–S38.
Crossref
PubMed
Google Scholar
23.
Ribeiro IC, Iborra RT, Neves MQ, Lottenberg SA, Charf AM, Nunes VS, Negrão CE, Nakandakare ER, Quintão EC, Passarelli M. HDL atheroprotection by aerobic exercise training in type 2 diabetes mellitus. Med Sci Sports Exerc. 2008;40:779–786. doi: 10.1249/MSS.0b013e3181632d2d.
Crossref
PubMed
Google Scholar
24.
Slentz CA, Bateman LA, Willis LH, Granville EO, Piner LW, Samsa GP, Setji TL, Muehlbauer MJ, Huffman KM, Bales CW, Kraus WE. Effects of exercise training alone vs a combined exercise and nutritional lifestyle intervention on glucose homeostasis in prediabetic individuals: a randomised controlled trial. Diabetologia. 2016;59:2088–2098. doi: 10.1007/s00125-016-4051-z.
Crossref
PubMed
Google Scholar
25.
Myers CA, Johnson WD, Earnest CP, Rood JC, Tudor-Locke C, Johannsen NM, Cocreham S, Harris M, Church TS, Martin CK. Examination of mechanisms (E-MECHANIC) of exercise-induced weight compensation: study protocol for a randomized controlled trial. Trials. 2014;15:212. doi: 10.1186/1745-6215-15-212.
Crossref
PubMed
Google Scholar
26.
Jeyarajah EJ, Cromwell WC, Otvos JD. Lipoprotein particle analysis by nuclear magnetic resonance spectroscopy. Clin Lab Med. 2006;26:847–870. doi: 10.1016/j.cll.2006.07.006.
Crossref
PubMed
Google Scholar
27.
Otvos JD, Shalaurova I, Wolak-Dinsmore J, Connelly MA, Mackey RH, Stein JH, Tracy RP. GlycA: a composite nuclear magnetic resonance biomarker of systemic inflammation. Clin Chem. 2015;61:714–723. doi: 10.1373/clinchem.2014.232918.
Crossref
PubMed
Google Scholar
28.
de la Llera-Moya M, Drazul-Schrader D, Asztalos BF, Cuchel M, Rader DJ, Rothblat GH. The ability to promote efflux via ABCA1 determines the capacity of serum specimens with similar high-density lipoprotein cholesterol to remove cholesterol from macrophages. Arterioscler Thromb Vasc Biol. 2010;30:796–801.
Crossref
PubMed
Google Scholar
29.
Kempen HJ, Gomaraschi M, Bellibas SE, Plassmann S, Zerler B, Collins HL, Adelman SJ, Calabresi L, Wijngaard PL. Effect of repeated apoA-IMilano/POPC infusion on lipids, (apo)lipoproteins, and serum cholesterol efflux capacity in cynomolgus monkeys. J Lipid Res. 2013;54:2341–2353. doi: 10.1194/jlr.M033779.
Crossref
PubMed
Google Scholar
30.
Oda MN, Forte TM, Ryan RO, Voss JC. The C-terminal domain of apolipoprotein A-I contains a lipid-sensitive conformational trigger. Nat Struct Biol. 2003;10:455–460. doi: 10.1038/nsb931.
Crossref
PubMed
Google Scholar
31.
Franceschini G, Calabresi L, Colombo C, Favari E, Bernini F, Sirtori CR. Effects of fenofibrate and simvastatin on HDL-related biomarkers in low-HDL patients. Atherosclerosis. 2007;195:385–391. doi: 10.1016/j.atherosclerosis.2006.10.017.
Crossref
PubMed
Google Scholar
32.
Guerin M, Egger P, Soudant C, Le Goff W, van Tol A, Dupuis R, Chapman MJ. Dose-dependent action of atorvastatin in type IIB hyperlipidemia: preferential and progressive reduction of atherogenic apoB-containing lipoprotein subclasses (VLDL-2, IDL, small dense LDL) and stimulation of cellular cholesterol efflux. Atherosclerosis. 2002;163:287–296.
Crossref
PubMed
Google Scholar
33.
Miyamoto-Sasaki M, Yasuda T, Monguchi T, Nakajima H, Mori K, Toh R, Ishida T, Hirata K. Pitavastatin increases HDL particles functionally preserved with cholesterol efflux capacity and antioxidative actions in dyslipidemic patients. J Atheroscler Thromb. 2013;20:708–716.
Crossref
PubMed
Google Scholar
34.
Triolo M, Annema W, de Boer JF, Tietge UJ, Dullaart RP. Simvastatin and bezafibrate increase cholesterol efflux in men with type 2 diabetes. Eur J Clin Invest. 2014;44:240–248. doi: 10.1111/eci.12226.
Crossref
PubMed
Google Scholar
35.
de Vries R, Kerstens MN, Sluiter WJ, Groen AK, van Tol A, Dullaart RP. Cellular cholesterol efflux to plasma from moderately hypercholesterolaemic type 1 diabetic patients is enhanced, and is unaffected by simvastatin treatment. Diabetologia. 2005;48:1105–1113. doi: 10.1007/s00125-005-1760-0.
Crossref
PubMed
Google Scholar
36.
Khera AV, Demler OV, Adelman SJ, Collins HL, Glynn RJ, Ridker PM, Rader DJ, Mora S. Cholesterol efflux capacity, high-density lipoprotein particle number, and incident cardiovascular events: an analysis from the JUPITER Trial (Justification for the Use of Statins in Prevention: An Intervention Trial Evaluating Rosuvastatin). Circulation. 2017;135:2494–2504. doi: 10.1161/CIRCULATIONAHA.116.025678.
Crossref
PubMed
Google Scholar
37.
Ronsein GE, Hutchins PM, Isquith D, Vaisar T, Zhao XQ, Heinecke JW. Niacin therapy increases high-density lipoprotein particles and total cholesterol efflux capacity but not ABCA1-specific cholesterol efflux in statin-treated subjects. Arterioscler Thromb Vasc Biol. 2016;36:404–411. doi: 10.1161/ATVBAHA.115.306268.
Crossref
PubMed
Google Scholar
38.
Sviridov D, Hoang A, Ooi E, Watts G, Barrett PH, Nestel P. Indices of reverse cholesterol transport in subjects with metabolic syndrome after treatment with rosuvastatin. Atherosclerosis. 2008;197:732–739. doi: 10.1016/j.atherosclerosis.2007.07.007.
Crossref
PubMed
Google Scholar
39.
Ronsein GE, Vaisar T. Inflammation, remodeling, and other factors affecting HDL cholesterol efflux. Curr Opin Lipidol. 2017;28:52–59. doi: 10.1097/MOL.0000000000000382.
Crossref
PubMed
Google Scholar
40.
Sankaranarayanan S, Kellner-Weibel G, de la Llera-Moya M, Phillips MC, Asztalos BF, Bittman R, Rothblat GH. A sensitive assay for ABCA1-mediated cholesterol efflux using BODIPY-cholesterol. J Lipid Res. 2011;52:2332–2340. doi: 10.1194/jlr.D018051.
Crossref
PubMed
Google Scholar
41.
Jessup W, Gelissen IC, Gaus K, Kritharides L. Roles of ATP binding cassette transporters A1 and G1, scavenger receptor BI and membrane lipid domains in cholesterol export from macrophages. Curr Opin Lipidol. 2006;17:247–257. doi: 10.1097/01.mol.0000226116.35555.eb.
Crossref
PubMed
Google Scholar
42.
Trejo-Gutierrez JF, Fletcher G. Impact of exercise on blood lipids and lipoproteins. J Clin Lipidol. 2007;1:175–181. doi: 10.1016/j.jacl.2007.05.006.
Crossref
PubMed
Google Scholar

eLetters(0)

eLetters should relate to an article recently published in the journal and are not a forum for providing unpublished data. Comments are reviewed for appropriate use of tone and language. Comments are not peer-reviewed. Acceptable comments are posted to the journal website only. Comments are not published in an issue and are not indexed in PubMed. Comments should be no longer than 500 words and will only be posted online. References are limited to 10. Authors of the article cited in the comment will be invited to reply, as appropriate.

Comments and feedback on AHA/ASA Scientific Statements and Guidelines should be directed to the AHA/ASA Manuscript Oversight Committee via its Correspondence page.

Sign In to Submit a Response to This Article

Information & Authors

Information

Published In

Go to Arteriosclerosis, Thrombosis, and Vascular Biology
Go to Arteriosclerosis, Thrombosis, and Vascular Biology

Longitudinal section through a thrombus in the murine inferior vena cava after flow reduction and application of L3.6pl pancreatic adenocarcinoma microvesicles, showing the layering of fibrin(-ogen) during thrombus growth. Staining for fibrin(-ogen) is shown in red, nuclei stained in blue by DAPI. (See pages 772–786.)

Arteriosclerosis, Thrombosis, and Vascular Biology
Volume 38 • Number 4 • April 2018
Pages: 943 - 952
PubMed: 29437573

Copyright

© 2018 American Heart Association, Inc.

Versions

You are viewing the most recent version of this article.

History

Received: 2 October 2017
Accepted: 24 January 2018
Published online: 8 February 2018
Published in print: April 2018

Permissions

Request permissions for this article.

Keywords

  1. apolipoproteins
  2. cholesterol
  3. clinical trial
  4. longitudinal studies
  5. metabolic syndrome
  6. overweight
  7. prediabetic state

Subjects

  1. Clinical Studies
  2. Exercise
  3. Lifestyle
  4. Lipids and Cholesterol
  5. Risk Factors

Authors

Affiliations

Mark A. Sarzynski
From the Department of Exercise Science, University of South Carolina, Columbia (M.A.S., J.J.R.-R., J.L.B.); Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC (C.A.S., R.W.M., W.E.K.); Ingestive Behavior and Preventive Medicine Laboratories, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA (J.W.A., M.N.H., T.S.C., C.K.M.); Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, Children’s Hospital Oakland Research Institute, Oakland, CA (M.S.B., Y.H., M.N.O.); and Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas (A.R.).
View all articles by this author
Jonathan J. Ruiz-Ramie
From the Department of Exercise Science, University of South Carolina, Columbia (M.A.S., J.J.R.-R., J.L.B.); Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC (C.A.S., R.W.M., W.E.K.); Ingestive Behavior and Preventive Medicine Laboratories, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA (J.W.A., M.N.H., T.S.C., C.K.M.); Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, Children’s Hospital Oakland Research Institute, Oakland, CA (M.S.B., Y.H., M.N.O.); and Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas (A.R.).
View all articles by this author
Jacob L. Barber
From the Department of Exercise Science, University of South Carolina, Columbia (M.A.S., J.J.R.-R., J.L.B.); Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC (C.A.S., R.W.M., W.E.K.); Ingestive Behavior and Preventive Medicine Laboratories, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA (J.W.A., M.N.H., T.S.C., C.K.M.); Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, Children’s Hospital Oakland Research Institute, Oakland, CA (M.S.B., Y.H., M.N.O.); and Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas (A.R.).
View all articles by this author
Cris A. Slentz
From the Department of Exercise Science, University of South Carolina, Columbia (M.A.S., J.J.R.-R., J.L.B.); Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC (C.A.S., R.W.M., W.E.K.); Ingestive Behavior and Preventive Medicine Laboratories, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA (J.W.A., M.N.H., T.S.C., C.K.M.); Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, Children’s Hospital Oakland Research Institute, Oakland, CA (M.S.B., Y.H., M.N.O.); and Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas (A.R.).
View all articles by this author
John W. Apolzan
From the Department of Exercise Science, University of South Carolina, Columbia (M.A.S., J.J.R.-R., J.L.B.); Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC (C.A.S., R.W.M., W.E.K.); Ingestive Behavior and Preventive Medicine Laboratories, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA (J.W.A., M.N.H., T.S.C., C.K.M.); Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, Children’s Hospital Oakland Research Institute, Oakland, CA (M.S.B., Y.H., M.N.O.); and Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas (A.R.).
View all articles by this author
Robert W. McGarrah
From the Department of Exercise Science, University of South Carolina, Columbia (M.A.S., J.J.R.-R., J.L.B.); Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC (C.A.S., R.W.M., W.E.K.); Ingestive Behavior and Preventive Medicine Laboratories, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA (J.W.A., M.N.H., T.S.C., C.K.M.); Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, Children’s Hospital Oakland Research Institute, Oakland, CA (M.S.B., Y.H., M.N.O.); and Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas (A.R.).
View all articles by this author
Melissa N. Harris
From the Department of Exercise Science, University of South Carolina, Columbia (M.A.S., J.J.R.-R., J.L.B.); Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC (C.A.S., R.W.M., W.E.K.); Ingestive Behavior and Preventive Medicine Laboratories, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA (J.W.A., M.N.H., T.S.C., C.K.M.); Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, Children’s Hospital Oakland Research Institute, Oakland, CA (M.S.B., Y.H., M.N.O.); and Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas (A.R.).
View all articles by this author
Timothy S. Church
From the Department of Exercise Science, University of South Carolina, Columbia (M.A.S., J.J.R.-R., J.L.B.); Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC (C.A.S., R.W.M., W.E.K.); Ingestive Behavior and Preventive Medicine Laboratories, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA (J.W.A., M.N.H., T.S.C., C.K.M.); Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, Children’s Hospital Oakland Research Institute, Oakland, CA (M.S.B., Y.H., M.N.O.); and Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas (A.R.).
View all articles by this author
Mark S. Borja
From the Department of Exercise Science, University of South Carolina, Columbia (M.A.S., J.J.R.-R., J.L.B.); Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC (C.A.S., R.W.M., W.E.K.); Ingestive Behavior and Preventive Medicine Laboratories, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA (J.W.A., M.N.H., T.S.C., C.K.M.); Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, Children’s Hospital Oakland Research Institute, Oakland, CA (M.S.B., Y.H., M.N.O.); and Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas (A.R.).
View all articles by this author
Yumin He
From the Department of Exercise Science, University of South Carolina, Columbia (M.A.S., J.J.R.-R., J.L.B.); Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC (C.A.S., R.W.M., W.E.K.); Ingestive Behavior and Preventive Medicine Laboratories, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA (J.W.A., M.N.H., T.S.C., C.K.M.); Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, Children’s Hospital Oakland Research Institute, Oakland, CA (M.S.B., Y.H., M.N.O.); and Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas (A.R.).
View all articles by this author
Michael N. Oda
From the Department of Exercise Science, University of South Carolina, Columbia (M.A.S., J.J.R.-R., J.L.B.); Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC (C.A.S., R.W.M., W.E.K.); Ingestive Behavior and Preventive Medicine Laboratories, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA (J.W.A., M.N.H., T.S.C., C.K.M.); Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, Children’s Hospital Oakland Research Institute, Oakland, CA (M.S.B., Y.H., M.N.O.); and Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas (A.R.).
View all articles by this author
Corby K. Martin
From the Department of Exercise Science, University of South Carolina, Columbia (M.A.S., J.J.R.-R., J.L.B.); Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC (C.A.S., R.W.M., W.E.K.); Ingestive Behavior and Preventive Medicine Laboratories, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA (J.W.A., M.N.H., T.S.C., C.K.M.); Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, Children’s Hospital Oakland Research Institute, Oakland, CA (M.S.B., Y.H., M.N.O.); and Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas (A.R.).
View all articles by this author
William E. Kraus
From the Department of Exercise Science, University of South Carolina, Columbia (M.A.S., J.J.R.-R., J.L.B.); Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC (C.A.S., R.W.M., W.E.K.); Ingestive Behavior and Preventive Medicine Laboratories, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA (J.W.A., M.N.H., T.S.C., C.K.M.); Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, Children’s Hospital Oakland Research Institute, Oakland, CA (M.S.B., Y.H., M.N.O.); and Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas (A.R.).
View all articles by this author
Anand Rohatgi
From the Department of Exercise Science, University of South Carolina, Columbia (M.A.S., J.J.R.-R., J.L.B.); Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, NC (C.A.S., R.W.M., W.E.K.); Ingestive Behavior and Preventive Medicine Laboratories, Pennington Biomedical Research Center, Louisiana State University System, Baton Rouge, LA (J.W.A., M.N.H., T.S.C., C.K.M.); Center for Prevention of Obesity, Cardiovascular Disease & Diabetes, Children’s Hospital Oakland Research Institute, Oakland, CA (M.S.B., Y.H., M.N.O.); and Division of Cardiology, Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas (A.R.).
View all articles by this author

Notes

The online-only Data Supplement is available with this article at http://atvb.ahajournals.org/lookup/suppl/doi:10.1161/ATVBAHA.117.310307/-/DC1.
Correspondence to Mark A. Sarzynski, PhD, Department of Exercise Science, University of South Carolina, 921 Assembly St, Columbia, SC 29201. E-mail [email protected]

Disclosures

M.A. Sarzynski is a consultant for Genetic Direction, LLC. M.N. Oda is a founder of and owns a significant stake in Seer Biologics, Inc. A. Rohatgi has a research grant from Merck and is a consultant for Merck, CSL Limited, HDL Diagnostics, and Cleveland HeartLabs. The other authors report no conflicts.

Sources of Funding

This study was supported by multiple grants from the National Institutes of Health (NIH) and other programs. The E-MECHANIC study (Examination of Mechanisms of exercise-induced weight compensation; URL: http://www.clinicaltrials.gov. Unique identifier: NCT01264406) was funded by NHLBI R01 HL102166 and a NIDDK Nutrition and Obesity Research Center grant P30DK072476. The STRRIDE-PD study (Studies of Targeted Risk Reduction Interventions through Defined Exercise, in individuals with Pre-Diabetes) was funded by National Institute of Diabetes and Digestive and Kidney Diseases R01 DK081559 (URL: http://www.clinicaltrials.gov. Unique identifier: NCT00962962). J.W. Apolzan and M.A. Sarzynski were supported in part by U54 GM104940 from the National Institute of General Medical Sciences (NIGMS), which funds the Louisiana Clinical and Translational Science Center. M.A. Sarzynski was supported by NIGMS Centers of Biomedical Research Excellence center grant 8P20 GM-1033528. M.N. Oda was supported by California Tobacco Related Disease Research Program 21RT-0125. A. Rohatgi was supported by NIH/NHLBI R01HL136724, NIH/NHLBI K08HL118131, and AHA 15CVGPSD27030013.

Metrics & Citations

Metrics

Citations

Download Citations

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Select your manager software from the list below and click Download.

    • Jose C. Nicolau,
    • Talia F. Dalcoquio,
    • Roberto R. Giraldez,
    • Fatima R. Freitas,
    • Andre M. Nicolau,
    • Remo H. M. Furtado,
    • Thauany M. Tavoni,
    • Luciano M. Baracioli,
    • Felipe G. Lima,
    • Aline G. Ferrari,
    • Maria U. P. B. Rondon,
    • Rocio Salsoso,
    • Maria J. N. N. Alves,
    • Flavia B. B. Arantes,
    • Mayara A. Santos,
    • Leandro S. Alves,
    • Carlos E. Negrao,
    • Raul C. Maranhão,
    The Role of Exercise-Based Cardiac Rehabilitation After Myocardial Infarction on Cholesterol Transfer to HDL, International Journal of Molecular Sciences, 26, 1, (419), (2025).https://doi.org/10.3390/ijms26010419
    Crossref
    • Kenneth E. Westerman,
    • Tuomas O. Kilpeläinen,
    • Magdalena Sevilla‐Gonzalez,
    • Margery A. Connelly,
    • Alexis C. Wood,
    • Michael Y. Tsai,
    • Kent D. Taylor,
    • Stephen S. Rich,
    • Jerome I. Rotter,
    • James D. Otvos,
    • Amy R. Bentley,
    • Samia Mora,
    • Hugues Aschard,
    • D. C. Rao,
    • Charles Gu,
    • Daniel I. Chasman,
    • Alisa K. Manning,
    Refinement of a Published Gene‐Physical Activity Interaction Impacting HDL‐Cholesterol: Role of Sex and Lipoprotein Subfractions, Genetic Epidemiology, 49, 1, (2025).https://doi.org/10.1002/gepi.22607
    Crossref
    • Sameer Badri Al-mhanna,
    • César Leão,
    • Wan Syaheedah Wan Ghazali,
    • Mahaneem Mohamed,
    • Alexios Batrakoulis,
    • Hafeez Abiola Afolabi,
    • Bishir Daku Abubakar,
    • Monira I. Aldhahi,
    • Mehmet Gülü,
    • Fatma Hilal Yagin,
    • Pantelis T. Nikolaidis,
    Impact of Exercise on High-Density Lipoprotein Cholesterol in Adults with Overweight and Obesity: A Narrative Review, Annals of Applied Sport Science, 12, 2, (0-0), (2024).https://doi.org/10.61186/aassjournal.1300
    Crossref
    • John M. Giacona,
    • Ursa B. Petric,
    • Weerapat Kositanurit,
    • Jijia Wang,
    • Suzanne Saldanha,
    • Benjamin E. Young,
    • Ghazi Khan,
    • Margery A. Connelly,
    • Scott A. Smith,
    • Anand Rohatgi,
    • Wanpen Vongpatanasin,
    HDL-C and apolipoprotein A-I are independently associated with skeletal muscle mitochondrial function in healthy humans, American Journal of Physiology-Heart and Circulatory Physiology, 326, 4, (H916-H922), (2024).https://doi.org/10.1152/ajpheart.00017.2024
    Crossref
    • Giuseppe Di Gioia,
    • Lorenzo Buzzelli,
    • Viviana Maestrini,
    • Maria Rosaria Squeo,
    • Erika Lemme,
    • Sara Monosilio,
    • Andrea Serdoz,
    • Roberto Fiore,
    • Domenico Zampaglione,
    • Andrea Segreti,
    • Antonio Pelliccia,
    Long-Term Evaluation of Lipid Profile Changes in Olympic Athletes, International Journal of Sport Nutrition and Exercise Metabolism, 34, 5, (267-274), (2024).https://doi.org/10.1123/ijsnem.2023-0266
    Crossref
    • Laura Díez-Ricote,
    • Esther Cuadrado-Soto,
    • Andrés Pastor-Fernández,
    • Gema de la Peña,
    • Javier Martinez-Botas,
    • Olga Castañer,
    • M. A. Martínez-González,
    • Jordi Salas-Salvado,
    • Pablo J. Fernández-Marcos,
    • Diego Gómez-Coronado,
    • Jose Ordovas,
    • Lidia Daimiel,
    Effect of a Multifactorial Weight Loss Intervention on HDL Cholesterol Efflux Capacity and Immunosenescence: A Randomized Controlled Trial, Journal of the American Nutrition Association, (1-14), (2024).https://doi.org/10.1080/27697061.2024.2407942
    Crossref
    • Jack David Beazer,
    • Anne Sillars,
    • Sally Beck,
    • Christina Christoffersen,
    • Maria J. Ferraz,
    • Monique T. Mulder,
    • Delyth Graham,
    • Helen Karlsson,
    • Stefan Ljunggren,
    • Jason Gill,
    • Dilys J. Freeman,
    Favourable HDL composition in endurance athletes is not associated with changes in HDL in vitro antioxidant and endothelial anti-inflammatory function , Bioscience Reports, 44, 10, (2024).https://doi.org/10.1042/BSR20241165
    Crossref
    • Beata Franczyk,
    • Anna Gluba-Brzózka,
    • Aleksandra Ciałkowska-Rysz,
    • Janusz Ławiński,
    • Jacek Rysz,
    The Impact of Aerobic Exercise on HDL Quantity and Quality: A Narrative Review, International Journal of Molecular Sciences, 24, 5, (4653), (2023).https://doi.org/10.3390/ijms24054653
    Crossref
    • Dominik Strikić,
    • Andro Vujević,
    • Dražen Perica,
    • Dunja Leskovar,
    • Kristina Paponja,
    • Ivan Pećin,
    • Iveta Merćep,
    Importance of Dyslipidaemia Treatment in Individuals with Type 2 Diabetes Mellitus—A Narrative Review, Diabetology, 4, 4, (538-552), (2023).https://doi.org/10.3390/diabetology4040048
    Crossref
    • Yasuhiro Endo,
    • Masanori Fujita,
    • Katsunori Ikewaki,
    HDL Functions—Current Status and Future Perspectives, Biomolecules, 13, 1, (105), (2023).https://doi.org/10.3390/biom13010105
    Crossref
  11. See more

View Options

View options

PDF and All Supplements

Download PDF and All Supplements

PDF/EPUB

View PDF/EPUB
Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Personal login Institutional Login
Save for later Item saved, go to cart
Purchase Options

Purchase this article to access the full text.

Purchase access to this article for 24 hours

Effects of Increasing Exercise Intensity and Dose on Multiple Measures of HDL (High-Density Lipoprotein) Function
Arteriosclerosis, Thrombosis, and Vascular Biology
  • Vol. 38
  • No. 4

Purchase access to this journal for 24 hours

Arteriosclerosis, Thrombosis, and Vascular Biology
  • Vol. 38
  • No. 4
Restore your content access

Enter your email address to restore your content access:

Note: This functionality works only for purchases done as a guest. If you already have an account, log in to access the content to which you are entitled.

Figures

Tables

Media

Share

Share

Share article link

Share

View full text|Download PDF

Comment Response