Cardiovascular and metabolic risk••

Pre-impaired fasting glucose state is a risk factor for endothelial dysfunction: Flow-mediated Dilation Japan (FMD-J) study

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Abstract

Introduction Diabetes mellitus is associated with endothelial dysfunction. However, there is little information on the relationships of fasting blood glucose (FBG), including high normal blood glucose and impaired fasting glucose (IFG) with endothelial function. The purpose of this study was to evaluate the relationship between FBG level and flow-mediated vasodilation (FMD) using a large sample size.

Research design and methods This study was a cross-sectional study. We measured FMD in 7265 subjects at 31 general hospitals. The subjects were divided into four groups based on FBG levels: <100, 100–109, 110–125, and ≥126 mg/dL or known diabetes. The subjects were also divided into six groups based on FBG levels: <90, 90–94, 95–99, 100–109, 110–125, and ≥126 mg/dL or known diabetes.

Results FMD decreased in relation to increase in FBG level. There was a significant difference in FMD between the FBG of <100 mg/dL group and the other three groups (6.7±3.1% vs 5.9±2.8%, 5.7±3.1%, and 5.1±2.6%, respectively; p<0.001). After adjustment for confounding factors, the odds of having the lowest quartile of FMD were significantly higher in the FBG of 95–99, 100–104, 105–109, 110–125, and ≥126 mg/dL or known diabetes groups than in the FBG of the <90 mg/dL group.

Conclusions These findings suggest that FBG of 100–109 mg/dL and FBG of 110–125 mg/dL are similarly associated with endothelial dysfunction and that a pre-IFG state (FBG of 95–99 mg/dL) is also a risk for endothelial dysfunction compared with FBG of <90 mg/dL.

Trial registration number UMIN000012950, UMIN000012951, UMIN000012952, and UMIN000003409.

Significance of this study

What is already known about this subject?

Diabetes is associated with endothelial dysfunction.
The relationship between impaired fasting glucose and endothelial function is still controversial.

What are the new findings?

A preimpaired fasting glucose (IFG) state (fasting blood glucose (FBG) of 95–99 mg/dL) is a risk for endothelial dysfunction compared with an FBG of <90 mg/dL.

How might these results change the focus of research or clinical practice?

Intensive lifestyle modification is needed in subjects with a pre-IFG state (FBG of 95–99 mg/dL).

Introduction

Diabetes mellitus (DM) is a well-established risk factor for cardiovascular events.1 It is well known that cardiovascular risk is increased before the onset of DM as a state of pre-diabetes.2 In the American Diabetes Association (ADA) classification, a fasting blood glucose (FBG) range of 100–125 mg/dL is categorized as impaired fasting glucose (IFG).3 However, before 2003, an FBG range of 110–125 mg/dL was categorized as IFG in the ADA classification. In WHO criteria, an FBG range of 110–125 mg/dL is categorized as IFG. In the Japan Diabetes Society criteria, an FBG range of 110–125 mg/dL is categorized as pre-diabetes, and a range of 100–109 mg/dL is categorized as high normal blood glucose.4 The definition of IFG differs between countries and eras.

Endothelial dysfunction is known as the first step in the pathogenesis of atherosclerosis and is also known as a marker of cardiovascular events.5 6 Measurement of flow-mediated vasodilation (FMD) in the brachial artery is widely used for assessment of endothelial function. FMD is also well known as an independent predictor of cardiovascular events.7–11 In addition, measurement of FMD is an independent predictor of cardiovascular events in the general population, including individuals with DM. It has been established that DM is associated with endothelial dysfunction.12–14 However, the relationship between IFG and endothelial function is still controversial. Some investigators have shown that IFG is associated with endothelial dysfunction.15–18 On the other hand, Henry et al reported that IFG was not associated with endothelial dysfunction.13

There has been no study on the detailed relationships of FBG, including a normal range of glucose, pre-IFG range, and IFG range with endothelial function. First, we divided subjects into four groups according to the ADA classification, the WHO criteria and the Japan Diabetes Society criteria, FBG of <100, 100–109, 110–125, and ≥126 mg/dL or known DM, and assessed the FMD values. Furthermore, there is no information on from what level of FBG adversely affects endothelial function. Therefore, we divided FBG of <100 mg/dL, which was previously classified as normal blood glucose, into three groups, FBG of <90 md/dL, FBG of 90–94 mg/dL and FBG of 95–99 mg/dL, and evaluated the relationships of FBG levels of <90, 90–94, 95–99, 100–109, 110–125 and ≥126 mg/dL or known DM with FMD in multiple centers using a large sample size.

Research design and methods

Study subjects

The Flow-mediated Dilation Japan (FMD-J) Registry was a prospective multicenter registry that was established between April 1, 2010, and August 31, 2018, at 31 institutes in Japan with the aim of determining the usefulness of FMD measurement. All of the subjects had an obligation to undergo health screening every year under the regulations of the society-managed health insurance union in Japan. The design of the FMD-J study has been described in detail.19 Subjects with severe chronic heart failure (New York Heart Association level of more than III), subjects with severe valvular disease, arrhythmia for which they were receiving treatment, dialysis, end-stage chronic kidney disease or malignancy, subjects taking steroids, non-steroidal anti-inflammatory drugs or immunosuppressive drugs, subjects over 80 years of age, and subjects without information on FBG or with unclear images of the brachial artery interfaces were excluded. Finally, we enrolled 7265 subjects in this study. Hypertension was defined as the use of antihypertensive drugs or systolic blood pressure of more than 140 mm Hg or diastolic blood pressure of more than 90 mm Hg measured in a sitting position on at least three occasions. Dyslipidemia was defined according to the third report of the National Cholesterol Education Program.20 DM was defined according to the ADA recommendation.21 Smokers were defined as those who were current smokers. Cardiovascular disease was defined as coronary heart disease and cerebrovascular disease. Coronary heart disease included angina pectoris, prior myocardial infarction, and unstable angina. Cerebrovascular disease included ischemic stroke, hemorrhagic stroke, and transient ischemic attack.

Study protocol

We measured the vascular response to reactive hyperemia in the brachial artery for assessment of endothelium-dependent FMD. The patients fasted overnight and abstained from alcohol, smoking, caffeine and antioxidant vitamins for at least 12 hours before the study. The participants were kept in the supine position in a quiet, dark, air-conditioned room (constant temperature from 22°C to 25°C) throughout the study. A 23-gauge polyethylene catheter was inserted into the deep antecubital vein to obtain blood samples for measurements, including measurement of FBG. After maintaining the supine position for 30 min, FMD was measured. The observers were blind to the form of examination.

Measurement of FMD

A high-resolution linear artery transducer (resolution of 10MHz and an H-shaped probe capturing two short-axis images and one long-axis image) was coupled to computer-assisted analysis software (UNEXEF18G; UNEX Corporation, Nagoya, Japan) that used an automated edge detection system for measurement of the brachial artery diameter.22 Online supplemental figure S1A shows the system for measurement of FMD. A blood pressure cuff was placed around the forearm of each subjects. The brachial artery was scanned longitudinally 5–10 cm above the elbow. When the clearest B-mode image of the anterior and posterior intimal interfaces between the lumen and the vessel wall was obtained, the transducer was held at the same point throughout the scan by using a special probe holder (UNEX Corporation) to ensure consistency of the imaging (online supplemental figure S1B). Depth and gain setting were set to optimize the images of the arterial lumen wall interface. When the tracking gate was placed on the intima, the artery diameter was automatically tracked, and the waveform of diameter changes over the cardiac cycle were displayed in real time using the FMD mode of the tracking system. This allowed the ultrasound images to be optimized at the start of the scan and the transducer position to be adjusted immediately for optimal tracking performance throughout the scan. Pulsed Doppler flow was assessed at baseline and during peak hyperemic flow, which was confirmed to occur within 15 s after cuff deflation. Blood flow velocity was calculated from the color Doppler data and was displayed as a waveform in real time (online supplemental figure S1B,C). Baseline longitudinal images of the artery were acquired for 30 s, and then the blood pressure cuff was inflated to 50 mm Hg above systolic pressure for 5 min. Blood flow volume was calculated by multiplying the Doppler flow velocity (corrected for the angle) by heart rate and vessel cross-sectional area (−r²). The longitudinal image of the artery was recorded continuously until 3 min after cuff deflation. Changes in brachial artery diameter were immediately expressed as percentage changes relative to the vessel diameter before cuff inflation. FMD was automatically calculated as the percentage change in peak vessel diameter from the baseline value. Percentage of FMD [(peak diameter-baseline diameter)/baseline diameter] was used for analysis. All of the sonographers specialized in FMD measurement at the participating institutions underwent training for a standard protocol of FMD measurement and training for scanning and analysis of the record at the core laboratory in the FMD-J study. All recordings of brachial artery scans obtained during the measurements of FMD were sent from the participant institutions to the core laboratory by universal serial bus flash drives and were individually analyzed by a well-experienced reader at the core laboratory without any information about the patients in the FMD-J study. We set outliers as FMD <−10% and FMD >25%. Reactive hyperemia was calculated as the maximum percentage increase in flow after cuff deflation compared with baseline flow. The correlation coefficient between FMD analyzed at the core laboratory and participant institutions was 0.84 (p<0.001). The intraobserver variabilities (coefficients of variation) were 10.1%–11.2%.23 Measurements for FMD were performed according to the guideline.24

Statistical analysis

Results are presented as mean±SD. All reported probability values were two-sided, and a probability value of <0.05 was considered statistically significant. Categorical values were compared by means of the χ² test. Continuous variables were compared by using analysis of variance (ANOVA) on multiple groups. Comparisons between the groups categorized according to FBG levels were carried out using repeated measures ANOVA with Tukey’s post hoc test. Univariate linear regression analyses were performed to assess the relationships among the variables. Multivariate regression analyses using ordinary least squares were performed to identify independent variables associated with FMD from the following covariates with p<0.05 for inclusion: age, body mass index, systolic blood pressure, heart rate, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, FBG, uric acid, and creatinine. Multivariate logistic regression analysis was performed to identify independent variables associated with lower quartiles of FMD (<4.2%). Age over 65 years old, gender, obesity (body mass index of 30 or higher), current smoking, presence of hypertension and presence of dyslipidemia were entered into the multivariate logistic regression analysis. All data were processed using JMP Pro V.14.0 software (SAS Institute, Cary, North Carolina, USA)

Results

Baseline characteristics of the subjects

The baseline characteristics of the 7265 subjects are summarized in table 1. The mean age of the subjects was 51±10 years. The 7265 subjects included 5804 men (79.9%) and 1461 women (20.1%). The mean FBG level in the subjects was 101±20mg/dL, and the mean HbA1c level was 5.7±0.7%. Among the subjects, 3188 (43.9%) had hypertension; 3760 (51.8%) had dyslipidemia; 685 (9.4%) had DM; 689 (9.5%) had previous cardiovascular disease; and 2189 (30.3%) were current smokers. The mean FMD value was 6.3±3.1%.

Table 1

Clinical characteristics of patients in four groups of FBG levels

Relationships among FMD, FBG and variables

Online supplemental table S1 shows univariate relationships among FMD, FBG level and variables. FMD was significantly correlated with age (r=−0.31, p<0.001), body mass index (r=−0.19, p<0.001), heart rate (r=0.06, p<0.001), systolic blood pressure (r=−0.15, p<0.001), diastolic blood pressure (r=−0.08, p<0.001), total cholesterol (r=−0.03, p=0.03), triglycerides (r=−0.11, p<0.001), high-density lipoprotein cholesterol (r=0.08, p<0.001), creatinine (r=−0.07, p<0.001), uric acid (r=−0.13, p<0.001), FBG level (r=−0.14, p<0.001) (online supplemental figure S2A) and HbA1c level (r=−0.16, p<0.001). FBG level was significantly correlated with age (r=−0.26, p<0.001), body mass index (r=0.23, p<0.001), heart rate (r=0.13, p<0.001), systolic blood pressure (r=0.19, p<0.001), diastolic blood pressure (r=0.11, p<0.001), triglyceride (r=0.18, p<0.001), high-density lipoprotein cholesterol (r=−0.15, p<0.001), uric acid (r=0.06, p<0.001), HbA1c level (r=0.77, p<0.001) and FMD (r=−0.14, p<0.001).

Online supplemental table S2 shows multivariate linear relationships among FMD, FBG level and variables. Multiple linear regression analysis revealed that age (β=−0.23, p<0.001), body mass index (β=−0.10, p<0.001), heart rate (β=0.09, p<0.001), systolic blood pressure (β=−0.04, p=0.001), triglycerides (β=−0.04, p=0.001), high-density lipoprotein cholesterol (β=−0.03, p=0.02), uric acid (β=−0.07, p<0.001), FBG (β=−0.03, p=0.02), antihypertensive drug treatment (β=0.13, p<0.001), and current smoking (β=0.07, p<0.001) were independent predictors of FMD.

FMD values in four groups of FBG levels

The baseline characteristics of subjects with FBG levels of <100, 100–109, 110–125 and ≥126 mg/dL or known DM are also summarized in table 1. There were significant differences in age, gender, body mass index, heart rate, systolic blood pressure, diastolic blood pressure, levels of total cholesterol, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, creatinine, uric acid, FBG, and HbA1c, prevalences of hypertension, dyslipidemia, and cardiovascular disease, and use of antihypertensive drugs and lipid-lowering drugs among the four groups. FMD was significantly correlated with FBG level of 90–125 mg/dL (r=−0.12, p<0.001) (online supplemental figure S2B). Online supplemental figure S3 shows FMD values in the four groups. FMD values were 6.7±3.1% in the FBG of the <100 mg/dL group, 5.9±2.8% in the 100–109 mg/dL group, 5.7±3.1% in the 110–125 mg/dL group, and 5.1±2.6% in the ≥126 mg/dL or known DM group (p<0.001). FMD values in the FBG 100–109, 110–125 and ≥126 mg/dL or known DM groups were significantly smaller than the values in the FBG<100 mg/dL group (p<0.001, respectively). FMD values were similar in the FBG of the 100–109 group and 110–125 mg/dL group (p=0.80).

The division points for the lowest quartile and second quartile were FMD of 4.2%. Therefore, we defined small FMD as FMD of <4.2%. We took the FBG of <100 mg/dL group as a reference for deriving the low quartiles of FMD in the other groups. After adjustments for age over 65 years, gender, presence of hypertension, presence of dyslipidemia, presence of obesity (body mass index ≥30 m²/kg), and current smoking, the odds of having the lowest quartile of FMD were significantly higher in the FBG of 100–109 mg/dL group, 110–125 mg/dL group and ≥126 mg/dL or known DM group than in the reference group: 100–109 mg/dL (OR 1.26, 95% CI 1.10 to 1.45), 110–125 mg/dL (OR 1.42, 95% CI 1.16 to 1.74), and ≥126 mg/dL or known DM (OR 1.37, 95% CI 1.15 to 1.64) (online supplemental table S3).

FMD values in six groups of FBG levels

Finally, we divided the patients into six groups based on their FBG levels: <100 mg/dL (<90, 90–94, and 95–99 mg/dL), 100–109, 110–125 and ≥126 mg/dL or known DM, and assessed their endothelial function. There were significant differences in age, gender, body mass index, heart rate, systolic blood pressure, diastolic blood pressure, levels of total cholesterol, triglycerides, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, creatinine, uric acid, FBG, and HbA1c, prevalences of hypertension, dyslipidemia, and cardiovascular disease, and use of antihypertensive drugs and lipid-lowering drugs among the six groups (table 2). FMD values were 6.9±3.1% in the FBG of the <90 mg/dL group, 6.7±3.1% in the 90–94 mg/dL group, 6.3±3.1% in the 95–99 mg/dL group, 5.9±2.8% in the 100–109 mg/dL group, 5.7±3.1% in the 110–125 mg/dL group, and 5.1±2.6% in the ≥126 mg/dL or known DM group (p<0.001, figure 1). FMD values were similar in the FBG of <90 mg/dL group, 90–94 mg/dL group, 100–109 mg/dL group and 110–125 mg/dL group (figure 1).

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Figure 1

Bar graphs show flow-mediated vasodilation in subjects with FBG of <90, 90–94, 95–99, 100–109, 110–125, and ≥126 mg/dL or known diabetes. DM, diabetes mellitus; FBG, fasting blood glucose.

Table 2

Clinical characteristics of patients in six groups of FBG levels

We took the FBG of the <90 mg/dL group as a reference and for deriving for the low quartiles of FMD in the other groups. After adjustments for confounding factors, the odds of having lowest quartile of FMD were significantly higher in FBG of the 95–99 mg/dL group, the 100–109 mg/dL group, the 110–125 mg/dL group and the ≥126 mg/dL or known DM group than in the reference group: 95–99 mg/dL group (OR 1.28, 95% CI 1.07 to 1.55), 100–109 mg/dL group (OR 1.41, 95% CI 1.18 to 1.68), 110–125 mg/dL group (OR 1.59, 95% CI 1.26 to 2.01), and ≥126 mg/dL or known DM group (OR 1.54, 95% CI 1.25 to 1.91). The odds of having the lowest quartile of FMD in subjects with FBG of <90 md/dL and subjects with FBG of 90–94 mg/dL were similar (OR 1.07, 95% CI 0.89 to 1.29) (table 3).

Table 3

Multivariate analysis of relationships among low quartiles of FMD and FBG levels

Discussion

In the present study, we demonstrated that FBG was an independent predictor of FMD, that FMD was similarly impaired in the FBG of 100–109 and 110–125 mg/dL groups compared with that in the FBG of the <100 mg/dL group, and that after adjustments for confounding factors, FMD values in the FBG of the 100–109 mg/dL group, the 110–125 mg/dL group, and the ≥126 mg/dL or known DM group were significantly smaller than the value in the FBG of the <100 mg/dL group. We also demonstrated for the first time that FMD was significantly smaller in the FBG of the 95–99 mg/dL group than in the FBG of the <90 mg/dL group.

First, to evaluate the relationships between FBG levels and endothelial function in more detail, we divided the subjects into four groups of FBG levels. Endothelial function was similarly impaired in the FBG of the 100–109 mg/dL group and in the FBG of the 110–125 mg/dL group compared with that in the FBG of the <100 mg/dL group. Previous studies showing that subjects in the FBG of the 100–125 mg/dL group and FBG of 110–125 mg/dL group have endothelial dysfunction support our findings.15–18 25 These finding suggest that FBG of ≥100 mg/dL is a risk factor of endothelial dysfunction. In 2003, ADA proposed that the lower limit of IFG should be lowered from 110 mg/dL to 100 mg/dL since an IFG cut-off value of 100 mg/dL is better than an IFG cut-off value of 110 mg/dL for predicting future type 2 DM onset.26 From the aspect of vascular function, endothelial function in subjects with FBG of 100–109 mg/dL was similarly impaired in the FBG of 110–125 mg/dL group.

Next, there is no information on from what level of FBG adversely affects endothelial function. Therefore, we divided FBG of <100 mg/dL, which was previously classified as normal blood glucose, into the three groups, FBG of <90 md/dL, FBG of 90–94 mg/dL and FBG of 95–99 mg/dL, and evaluated the relationships between FBG levels of <90, 90–94, 95–99, 100–109, 110–125 and ≥126 mg/dL or known DM and FMD. In the present study, the odds of having the lowest quartile of FMD was significantly higher in the FBG of 95–99 mg/dL group than in the FBG of <90 mg/dL group. A pre-IFG state, FBG of 95–99 mg/dL, was also associated with endothelial dysfunction. It is likely that endothelial function is almost simultaneously impaired when FBG level increases over 95 mg/dL, while it is unclear whether the association of elevation of FBG with the existence of endothelial dysfunction is a cause or consequence.

It is thought that the mechanisms by which hyperglycemia impairs endothelial function are increases in oxidative stress and inflammation. Hyperglycemia-induced increase in reactive oxygen species plays a critical role in oxidative stress through several pathways, including overproduction of mitochondria-derived superoxide anion, polyol pathway, advanced glycation end products/receptor for advanced glycation end-product pathway, protein kinase C pathway and hexosamine pathway, leading to a decrease in nitric oxide bioavailability and resulting in endothelial dysfunction.27–31 Hyperglycemia involves not only a high blood glucose state but also metabolic disorders, including obesity, dyslipidemia, insulin resistance and hypertension. Under the condition of hyperglycemia, obesity-induced hypertrophic adipocytes produce inflammatory cytokines, such as tumor necrosis factor-α and interleukin-6, and reduce anti-inflammatory cytokine adiponectin, leading to an increase in inflammation and resulting in endothelial dysfunction. It is well known that hypertension and dyslipidemia induce increases in oxidative stress and inflammation.32–34 Oxidative stress and inflammation make a vicious circle and contribute to endothelial dysfunction.35 In the present study, we found associations of FBS with obesity and with increases in blood pressure and low-density lipoprotein cholesterol level. FMD decreased in relation to an increase in FBG, and FBG was an independent predictor of FMD.

This study has some limitations. First, although this study was conducted by multiple centers (31 institutes) and used a large sample size, this study was a cross-sectional study. Therefore, we were able to evaluate the association but not causality between FBG level and FMD. Second, we did not have information on results of 75 g oral glucose tolerance tests. Therefore, we could not obtain data on impaired glucose tolerance (IGT). Previous studies have shown that IGT is a predictor of cardiovascular events and that it is potentially a better predictor than IFG of cardiovascular events,36 while it is controversial whether IFG is an independent predictor of cardiovascular events.36 37 There have been a few studies showing a relationship between high-normal blood glucose (pre-IFG) and diabetic vascular complications. Shaye et al38 showed that subjects with an FBG of 95–99 mg/dL had a higher incidence of cardiovascular events than subjects with an FBG of <80 mg/dL. On the other hand, although Pereg et al39 showed the relationships between FBG levels and coronary revascularization in subjects with an FBG of <100 mg/dL and with previous percutaneous coronary intervention or coronary artery bypass graft, after adjustment for coronary risk factors, there were no significant associations of FBG of 92–99 and ≤80 mg/dL with cardiovascular events. It is still controversial whether pre-IFG is associated with cardiovascular events. In the present study, we clearly showed that endothelial function is impaired not only in subjects with IFG but also even in subjects with pre-IFG. Third, this study was conducted in Japan. It is well known that insulin sensitivity is lower in Asians, including Japanese, than in Caucasians and that Asians are more likely to have an increased risk of DM.40 We cannot deny the possibility that our results are not applicable to other races. Fourth, we have no information on serum insulin levels. Therefore, we could not discuss the relationships among insulin levels, insulin resistance and endothelial function. Fifth, it is well known that oxidative stress and inflammation contribute to endothelial dysfunction and make a vicious circle between oxidative stress and inflammation and endothelial dysfunction.35 In addition, previous studies have shown that lifestyle (eg, physical activity and diet) other than smoking status influences endothelial function.41–44 Unfortunately, in the present study, the FMD-J database did not include data on chemical biomarkers of oxidative stress and inflammation and physical activity and diet. Assessment of oxidative stress and inflammatory markers and assessment of physical activity and diet would enable more specific conclusions concerning the role of FBG in endothelial function to be drawn. Finally, the latest guideline recommends measurement of shear rate.45 Unfortunately, we had no information on shear rate. Assessment of shear rate would enable more specific conclusions concerning the role of FBG in endothelial function to be drawn.

In conclusion, high normal blood glucose of 95–99 mg/dL as well as an FBG of 110–125 mg/dL was associated with endothelial dysfunction. Endothelial dysfunction may begin from an FBG of 95–99 mg/dL, a so-called pre-IFG state. It is thought that intensive lifestyle modification or pharmacological intervention is needed to decrease FBG in individuals with pre-IFG who have an FBG of more than 95 mg/dL.

Contributors: TY and YHig: drafting of the article and conception of the study; TY, TH, YHas, YT, MK, YHan, TM, SK, CG, AN, and FMY: acquisition of subjects and/or data; EH, KC and YK: revision of the article critically for important intellectual content. YHig was the guarantor of this work and, as such, had full access to all of the data in the study and took responsibility for the integrity of the data and the accuracy of data analysis.
Funding: A grant-in-aid for scientific research from the Ministry of Education, Science and Culture of Japan (18590815 and 21590898) and a grant-in-aid from the Japanese Arteriosclerosis Prevention Fund were awarded to YHig.
Competing interests: None declared.
Patient consent for publication: Not required.
Ethics approval: The ethics committee of Hiroshima University approved the study protocol. Written informed consent for participation in this study was obtained from all participants before data collection.
Provenance and peer review: Not commissioned; externally peer reviewed.
Data availability statement: Data are available upon reasonable request. There is no additional information.
Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.

Acknowledgements

The authors thank all of the patients who participated in this study, including Miki Kumiji, Megumi Wakisaka, Ki-ichiro Kawano and Satoko Michiyama for their excellent secretarial assistance; FMD-J investigators Takayuki Hidaka, MD, PhD; Shuji Nakamura, MD, PhD; Junko Soga, MD, PhD; Yuichi Fujii, MD, PhD; Naomi Idei, MD; Noritaka Fujimura, MD, PhD; Shinsuke Mikami, MD, PhD; Yumiko Iwamoto, MD; Akimichi Iwamoto, MD, PhD; Takeshi Matsumoto, MD, PhD; Nozomu Oda, MD, PhD (Department of Cardiovascular Medicine, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan); Kana Kanai, PhD; Haruka Morimoto, PhD (Department of Cardiovascular Regeneration and Medicine, Research Institute for Radiation Biology and Medicine, Hiroshima University, Hiroshima, Japan); Tomohisa Sakashita, MD, PhD; Yoshiki Kudo, MD, PhD (Department of Obstetrics and Gynecology, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan); Taijiro Sueda, MD, PhD (Department of Surgery, Hiroshima University Graduate School of Biomedical Sciences, Hiroshima, Japan); Hirofumi Tomiyama, MD, PhD, FAHA; Akira Yamashina, MD, PhD (Department of Cardiology, Tokyo Medical University, Tokyo, Japan); Bonpei Takase, MD, PhD, FAHA (Division of Biomedical Engineering, National Defense Medical College Research Institute, Tokorozawa, Japan); Takahide Kohro, MD, PhD (Department of Cardiology, Tokyo Medical University, Tokyo, Japan); Toru Suzuki, MD, PhD (Cardiovascular Medicine, University of Leicester, Leicester, UK); Tomoko Ishizu, MD, PhD (Cardiovascular Division, Institute of Clinical Medicine, University of Tsukuba, Ibaraki, Japan); Shinichiro Ueda, MD, PhD (Department of Clinical Pharmacology and Therapeutics, University of the Ryukyu School of Medicine, Okinawa, Japan); Tsutomu Yamazaki, MD, PhD (Clinical Research Support Center, Faculty of Medicine, The University of Tokyo, Tokyo, Japan); Tomoo Furumoto, MD, PhD (Department of Cardiovascular Medicine, Hokkaido University Graduate School of Medicine, Hokkaido, Japan); Kazuomi Kario, MD, PhD (Division of Cardiovascular Medicine, Jichi Medical University School of Medicine, Tochigi, Japan); Teruo Inoue, MD, PhD (Department of Cardiovascular Medicine, Dokkyo Medical University, Mibu, Tochigi, Japan); Shinji Koba, MD, PhD (Department of Medicine, Division of Cardiology, Showa University School of Medicine, Tokyo, Japan); Kentaro Watanabe, MD, PhD (Department of Neurology, Hematology, Metaboism, Endocrinology and Diabetology (DNHMED), Yamagata University School of Medicine, Yamagata, Japan); Yasuhiko Takemoto, MD, PhD (Department of Internal Medicine and Cardiology, Osaka City University Graduate School of Medicine, Osaka, Japan); Takuzo Hano, MD, PhD (Department of Medical Education and Population-based Medicine, Postgraduate School of Medicine, Wakayama Medical University, Wakayama, Japan); Masataka Sata, MD, PhD (Department of Cardiovascular Medicine, Institute of Health Biosciences, The University of Tokushima Graduate School, Tokushima, Japan); Yutaka Ishibashi, MD, PhD (Department of General Medicine, Shimane University Faculty of Medicine, Izumo, Japan); Koichi Node, MD, PhD (Department of Cardiovascular and Renal Medicine, Saga University, Saga, Japan); Koji Maemura, MD, PhD (Department of Cardiovascular Medicine, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan); Yusuke Ohya, MD, PhD (The Third Department of Internal Medicine, University of the Ryukyus, Okinawa, Japan); Taiji Furukawa, MD, PhD (Department of Internal Medicine, Teikyo University School of Medicine, Tokyo, Japan); Hiroshi Ito, MD, PhD (Department of Cardiovascular Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Japan); and Hisao Ikeda, MD, PhD (Faculty of Fukuoka Medical Technology, Teikyo University, Omuta, Japan).

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