Association between total bilirubin and sarcopenia in people with type 2 diabetes: The KAMOGAWA-A study

Abstract

Bilirubin is associated with vascular complications in diabetes. However, the correlation between bilirubin and sarcopenia or muscle strength has not been investigated. This study aimed to investigate the association between total bilirubin and skeletal muscle mass index (SMI), hand grip strength (HGS), and sarcopenia in patients with type 2 diabetes. This cross-sectional study included 1,108 patients with type 2 diabetes from three hospitals in Japan. Multiple and logistic regression analyses were used to examine the relationships between total bilirubin and SMI, HGS, and sarcopenia. Of the participants, 473 (43%) were women. The median (interquartile range) age, and glycated hemoglobin were 67 (59–73) years, and 7.4 (6.7–8.6) %, respectively. The median SMIs for women and men were 6.32 (5.73–7.04) kg/m² and 7.53 (7.02–8.19) kg/m², respectively. The median HGS for women and men were 21.5 (17.5–25.0) kg and 36.0 (30.0–41.5) kg, respectively. Sarcopenia was present in 11% and 12% of women and men, respectively. No correlation was observed between total bilirubin and SMI in both sexes. No significant association was observed between total bilirubin and HGS in men, whereas a positive correlation was observed in women (β = 0.18, p = 0.01). Total bilirubin was negatively associated with sarcopenia in women (odds ratio = 0.80, 95% confidence interval: 0.64–0.98, interaction p = 0.02). The total bilirubin was significantly associated with HGS and sarcopenia in women with type 2 diabetes. Total bilirubin may serve as a useful indicator of sarcopenia in Japanese women.

Introduction

Type 2 diabetes causes secondary sarcopenia, which results from insulin secretion failure, inflammation from persistent hyperglycemia, and oxidative stress from high levels of advanced glycation end products. These factors contribute to the inhibition of muscle protein anabolism or catabolism, causing mitochondrial dysfunction [1, 2]. Patients with diabetes who develop sarcopenia have twice the risk of mortality [3] making it crucial to identify the factors related to the onset of sarcopenia.

Bilirubin, a product of heme catabolism in mammals produced by heme oxygenase, possesses antioxidant properties. It is associated with vascular complications in diabetes and affects muscle mass and strength [4, 5]. A positive correlation has been observed between bilirubin and skeletal muscle mass [6, 7]. However, the correlation between bilirubin and sarcopenia or muscle strength has not been investigated. This study aimed to investigate the correlation between total bilirubin and hand grip strength (HGS), skeletal muscle mass, and sarcopenia in Japanese patients with type 2 diabetes.

Method

Study design

This study utilized data from the KAMOGAWA-A cohort. This retrospective cross-sectional study included 1,310 patients with diabetes who underwent body composition analysis at Kyoto Prefectural University of Medicine Hospital, Matsushita Memorial Hospital, and Kameoka City Hospital between January 1, 2014, and November 30, 2021. The ethics committee approved the study (approval number: ERB-C-1876; approval date: 27/11/2020), which was conducted in accordance with the Declaration of Helsinki. Patient consent was obtained through an opt-out process.

Participants

This study enrolled 1,310 patients aged 18 years or older diagnosed with diabetes based on the ADA diagnostic criteria [8]. After applying the exclusion criteria, 20 patients without total bilirubin measurements, 69 with type 1 diabetes, 2 with gestational diabetes, 38 with impaired glucose tolerance, and 51 with AST or ALT levels of more than twice the normal value were excluded. Consequently, 1,108 patients were included in the final analysis (Fig. 1).

Fig. 1  Flow diagram showing the selection of the study population.

Data collection

Blood tests were performed during cohort registration. Patient information such as sex, age, duration of illness, body mass index (BMI), smoking history, drinking history, and medication history were assessed through questionnaires and medical records.

Definitions

Diabetic nephropathy was defined as the presence of microalbuminuria or a urine albumin-to-creatinine ratio (UACR) of 30–300 mg/g·Cr, macroalbuminuria or a UACR of 300 mg/g·Cr or more, an estimated glomerular filtration rate of less than 30 mL/min/1.73 m² regardless of UACR, or the need for dialysis therapy [9]. Neuropathy was defined based on the criteria for diabetic neuropathy proposed by the diagnostic neuropathy study group [10]. Diabetic retinopathy was assessed using medical records.

HGS measurement

HGS was measured using a Smedley handgrip dynamometer. Measurements were obtained in the standing position, with two measurements taken for each hand, and the highest value was recorded. Because HGS is influenced by body weight, the HGS to weight ratio was used for statistical analysis [11, 12].

Body composition

Weight, skeletal muscle mass index (SMI), and body fat percentage were measured using a multifrequency impedance body composition analyzer. SMI and BMI (kg/m²) were calculated using the formulas: SMI (kg/m²) = limb skeletal muscle mass (kg)/height squared (m²) and BMI = weight (kg)/height squared (m²), respectively.

Definition of sarcopenia

Based on the latest Asian working group for sarcopenia criteria, the cutoff values for SMI and HGS used for diagnosing sarcopenia were 5.7 kg/m² for women, 7.0 kg/m² for men, 18 kg/m² for women, and 28 kg/m² for men, respectively [13]. Other criteria for sarcopenia diagnosis, including gait speed and physical performance, were not evaluated in this study. Therefore, sarcopenia was defined as meeting the cutoff values for SMI and HGS.

Statistical analysis

Baseline characteristics are expressed as medians and interquartile ranges or numbers.

Univariate (model 1) and multiple regression analyses to evaluate the effect of total bilirubin on SMI and HGS were performed separately for males and females. Model 2 was adjusted for age, as aging is a well-established risk factor for sarcopenia. Model 3 was further adjusted for smoking status, HbA1c levels, SGLT2 inhibitor use, insulin use and presence of neuropathy, as these factors have been reported to influence muscle mass and strength in patients with type 2 diabetes [14-18]. The distribution of bilirubin was right-skewed; therefore, a natural logarithm transformation was performed to improve normality, and linear regression analysis was subsequently applied. Logistic regression analysis was conducted to evaluate the association between total bilirubin and sarcopenia by sex, and the interaction effect was also investigated. In this analysis, bilirubin values were multiplied by 10 for calculation, for which a one-unit change corresponds to a 0.1 mg/dL change.

Statistical analyses were performed using JMP software version 17.2.0 (SAS Institute Inc.). Significance was set at p < 0.05. Interquartile ranges are represented as the difference between the 25th and 75th percentiles.

Results

In this study, 1,288 patients with diabetes (560 women and 728 men) who underwent body composition analysis between January 1, 2014, and November 30, 2021, were registered. Of these, 20 patients with unmeasured total bilirubin levels, 69 with type 1 diabetes, 2 with gestational diabetes, 38 with impaired glucose tolerance, and 51 with AST or ALT levels more than twice the normal range were excluded. The final study population consisted of 1,108 individuals (Fig. 1).

At baseline, among the 1,108 participants, 473 (43%) were women. The median (interquartile range) age, total bilirubin, SMI, HGS, HGS to weight ratio were 68 (60–73) years, 0.73 (0.60–0.96) mg/dL, 6.32 (5.73–7.04) kg/m², 21.5 (17.5–25.0) kg and 0.37 (0.30–0.44) respectively in women, and 67 (59–73) years, 0.70 (0.55–0.88) mg/dL, 7.53 (7.02–8.19) kg/m², 36.0 (30.0–41.5) kg, and 0.53 (0.49–0.61) in men (Table 1).

Table 1 Characteristics of study participants with type 2 diabetes.

	All	Female	Male
Number of participants	1,108	473	635
Age, years	67 (59–73)	68 (60–73)	67 (58–73)
Duration diabetes, years	7 (0–16)	5 (0–15)	8 (1–17)
Body mass index, kg/m2	24.5 (22.0–27.6)	24.9 (22.3–28.2)	24.1 (21.8–26.9)
Systolic blood pressure, mmHg	134 (123–144)	134 (123–143)	134 (123–144)
Diastolic blood pressure, mmHg	78 (69–85)	76 (67–84)	80 (71–87)
Aspartate aminotransferase, IU/L	22 (17–28)	21 (17–28)	22 (18–28)
Alanine aminotransferase, IU/L	21 (15–32)	20 (14–30)	22 (16–33)
Total bilirubin, mg/dL	0.70 (0.60–0.90)	0.70 (0.55–0.88)	0.73 (0.60–0.96)
Hemoglobin A1c, %	7.4 (6.7–8.6)	7.3 (6.7–8.4)	7.4 (6.7–8.6)
Total cholesterol, mg/dL	189 (168–218)	194 (173–222)	186 (165.5–214)
HDL cholesterol, mg/dL	54 (46–65)	57 (49–70)	52 (44–62)
LDL cholesterol, mg/dL	105 (86–127)	106 (87–129)	104 (85–126)
Triglycerides, mg/dL	119 (83.25–179)	119 (87.5–169)	120 (80–186)
Creatinine, mg/dL	0.77 (0.63–0.94)	0.62 (0.54–0.74)	0.87 (0.74–1.03)
eGFR, mL/min/m2	70.5 (57.4–83.8)	73.0 (59.4–86.2)	69.4 (56.6–82.5)
SMI, kg/m2	7.11 (6.29–7.84)	6.32 (5.73–7.04)	7.53 (7.02–8.19)
Hand grip strength, kg	29.0 (22.0–37.0)	21.5 (17.5–25.0)	36.0 (30.0–41.5)
HGS to weight ratio	0.46 (0.37–0.55)	0.53 (0.49–0.61)	0.37 (0.30–0.44)
Administration of SGLT2 inhibitor, n (%)	333 (30)	139 (29)	194 (31)
Injection of insulin, n (%)	241 (22)	99 (21)	142 (22)
Smoking status, n (%)
Current	165 (15)	40 (8)	125 (20)
Past	318 (29)	48 (10)	270 (43)
Diabetes complication, n (%)
Nephropathy	491 (44)	215 (45)	276 (43)
Retinopathy	234 (21)	110 (23)	124 (20)
Neuropathy	198 (18)	100 (21)	98 (15)

Data are shown as medians (25th–75th quartile) or numbers (%).

Hand grip strength was assessed in a cohort of 582 participants, including 242 females.

Abbreviations: HDL; high density lipoprotein, LDL; low density lipoprotein, eGFR; estimated glomerular filtration rate, SMI; appendicular skeletal mass index, HGS; hand grip strength, SGLT2; sodium-glucose transporter 2.

No significant differences were observed between total bilirubin and SMI in both men and women after adjusting for age, smoking status, HbA1c level, SGLT2 inhibitor use, insulin use, and presence of neuropathy (Table 2).

Table 2 Unadjusted and adjusted associations of total bilirubin with appendicular skeletal mass index.

Independent variables	Female (n = 473)		Male (n = 635)
	Standardized β	p Value	Standardized β	p Value
Total bilirubin
Model 1 (crude)	–0.08	0.08	0.04	0.30
Model 2	–0.03	0.42	0.005	0.90
Model 3	–0.009	0.85	–0.006	0.88

Bilirubin was log-transformed and analyzed using linear regression.

Model 2: Adjusted for age.

Model 3: Adjusted for age, smoking status, administration of sodium-glucose transport protein 2 (SGLT2) inhibitor, injection of insulin, hemoglobin A1c level, Neuropathy.

The correlation between total bilirubin and HGS was assessed among 607 participants with available HGS data (249 women and 358 men) (Table 3). In the model adjusted for age, smoking status, HbA1c level, SGLT2 inhibitor use, insulin use, and presence of neuropathy (model 3), a positive correlation between total bilirubin and HGS was observed in women (p = 0.01). Logistic regression analysis was conducted to evaluate the impact of total bilirubin on sarcopenia in 582 patients with available SMI and HGS data (242 women and 340 men) (Table 4). Sarcopenia was diagnosed in 26 (11%) women and 40 (12%) men. Total bilirubin was negatively associated with sarcopenia only in women (odds ratio = 0.80, 95% confidence interval: 0.64–0.98, interaction p = 0.02), but not in men.

Table 3 Unadjusted and adjusted associations of total bilirubin with hand grip strength (n = 582).

Independent variables	Female (n = 242)		Male (n = 340)
	Standardized β	p Value	Standardized β	p Value
Total bilirubin
Model 1 (crude)	0.14	0.04	0.07	0.18
Model 2	0.15	0.02	0.05	0.40
Model 3	0.18	0.01	0.02	0.74

Bilirubin was log-transformed and analyzed using linear regression.

Model 2: Adjusted for age.

Model 3: Adjusted for age, smoking status, administration of SGLT2 inhibitor, injection of insulin, hemoglobin A1c level, Neuropathy.

Table 4  Logistic regression analysis of total bilirubin and sarcopenia (n = 582).

Low SMI (<5.7 kg/m2) and Low HGS (<18 kg) in females (n = 242)
	Model 1 OR (95%CI)	Model 2 aOR (95%CI)	Model 3 aOR (95%CI)	p for interaction
Total bilirubin	0.83 (0.69–1.01)	0.80 (0.66–0.98)	0.80 (0.64–0.98)	0.02
Low SMI (<7.0 kg/m2) and Low HGS (<28 kg) in males (n = 340)
	Model 1 OR (95%CI)	Model 2 aOR (95%CI)	Model 3 aOR (95%CI)	p for interaction
Total bilirubin	0.98 (0.88–1.10)	1.03 (0.92–1.16)	1.06 (0.94–1.19)	—

In the logistic regression analysis, bilirubin values were multiplied by 10 for calculation, where a one-unit change corresponds to a 0.1 mg/dL change.

Abbreviations: SMI; appendicular skeletal mass index, HGS; hand grip strength.

Model 1: crude.

Model 2: Adjusted for age.

Model 3: Adjusted for age, smoking status, administration of SGLT2 inhibitor, injection of insulin, hemoglobin A1clevel, Neuropathy.

Discussion

This study evaluated the association between total bilirubin and sarcopenia. In women, a positive correlation was observed between total bilirubin and HGS, and a negative correlation between total bilirubin and sarcopenia (Graphical Abstract). No significant associations were observed between total bilirubin and SMI, HGS, or sarcopenia in men.

Graphical Abstract 

Bilirubin is produced from the metabolism of free heme by heme oxygenase (HO) [4]. HO-1, a heme oxygenase isoform, exerts protective effects on tissues and organisms [19]. Bilirubin and its metabolite biliverdin have antioxidant properties, and the bilirubin-biliverdin cycle can efficiently remove reactive oxygen species (ROS) [20].

Epidemiological studies have shown that bilirubin is inversely related to the progression of diabetic nephropathy [21], severity of diabetic retinopathy [22], and diabetic neuropathy [23], among other microvascular complications. Additionally, bilirubin is associated with a decreased risk of coronary heart disease and other macrovascular complications [24].

In the present study, a positive correlation was observed between total bilirubin and HGS in women; however, no significant association was found with SMI. One possible explanation for this is that bilirubin’s antioxidant effects may primarily influence muscle quality, rather than quantity. The exact mechanism by which bilirubin affects the HGS is not fully understood; however, the antioxidant properties of bilirubin are hypothesized to neutralize excessive ROS, which contributes to the maintenance of muscle tissue homeostasis [25]. Chronic inflammation owing to insulin resistance and hyperglycemia in patients with type 2 diabetes influences HGS [26, 27]. Excessive ROS production induces oxidative stress, which promotes protease activity and alters gene expression, controlling muscle fiber structure, and muscle cell growth and repair, leading to muscle loss. Furthermore, oxidative stress can impair ryanodine receptor function and alter muscle fiber structure, which affects muscle quality. Oxidative stress affects muscle quantity and quality; however, the effect on muscle quality is more pronounced [28]. Therefore, bilirubin, with its antioxidant function, may correlate more with muscle quality (i.e., HGS), rather than with muscle quantity (i.e., SMI).

Additionally, prior studies have reported that aging-related muscle weakness in women is primarily caused by qualitative changes in muscle fibers, particularly a decline in type II fibers [29]. Type II fibers have lower mitochondrial content and antioxidant enzyme activity than type I fibers, making them more susceptible to oxidative stress [30]. Further, the aging-linked changes in type II fibers have been associated with decreased muscle strength rather than reduced muscle mass. Given that bilirubin acts as an antioxidant, it is possible that it exerts more pronounced protective effects on muscle strength than quantity, which may explain the observed association with HGS but not SMI.

In this study, a correlation between total bilirubin and HGS was observed only in women. The precise mechanisms underlying sex differences in the relationship between bilirubin and HGS remain unclear; however, several explanations are proposed. A close relationship exists between sex hormones and muscle mass/strength, with decreased estrogen and testosterone levels associated with reduced muscle mass and strength [29, 31]. Conversely, sex hormones influence bilirubin levels. Estrogen, a female hormone, increases bilirubin clearance [32] and inhibits bilirubin production by blocking glucuronide conjugation [33]. In contrast, testosterone, a male hormone, positively correlates with bilirubin [34]. The median ages of the participants in this study were 67 and 68 years for men and women, respectively, and the age-related decline in sex hormones may have contributed to the observed sex differences in the relationship between bilirubin and HGS.

Other factors, such as smoking, a risk factor for sarcopenia [35], may also contribute to these findings. Particularly, men had a higher prevalence of smoking than women, which could be another confounding factor affecting the results.

In addition to hormonal influences, these findings may also be explained by differences in nutritional status, physical activity levels, and comorbidities between men and women. Indeed, nutritional factors, such as protein intake and vitamin D levels, are crucial for maintaining muscle function [36, 37]. Women, particularly postmenopausal women, may have different dietary habits than men, potentially influencing muscle strength. Similarly, physical activity patterns differ by sex, with men generally engaging in more resistance-based training, while women may have lower overall muscle-loading activity [38].

Furthermore, the prevalence of comorbid conditions, such as osteoporosis and anemia, is higher in women than men [39, 40]. These conditions are associated with increased oxidative stress and muscle weakness, which the antioxidant properties of bilirubin may help counteract. This could explain why bilirubin was associated with muscle strength in women, but not in men.

Previous study reported that a positive association was observed between bilirubin and muscle mass only in men aged 75 and older [7]. This discrepancy may be because of differences in sample size and age. Similarly, other studies reported no significant correlation between total bilirubin and muscle mass in individuals aged 60–74, consistent with our findings.

The strengths of this study include the assessment of SMI and HGS, which allows for a more accurate evaluation of sarcopenia. This aspect has not been extensively studied and may provide useful insights for future research on the impact of bilirubin on muscle mass and strength. The study accounted for significant factors, such as SGLT2 inhibitors and insulin usage, which affect muscle mass and sarcopenia [17, 18], highlighting the unique contribution of the antioxidant properties of bilirubin to muscle strength in women.

However, this study had several limitations. First, our analysis only evaluated the relationship between total bilirubin and sarcopenia, without assessing direct or indirect bilirubin. Future studies should therefore investigate the differential effects of direct and indirect bilirubin on muscle strength and sarcopenia to provide a more comprehensive understanding of their roles. Second, the focus of this study on the Japanese population may limit its applicability to other regions or ethnic groups. Further research with diverse populations should be conducted to determine whether these findings are generalizable across different ethnic backgrounds. Third, the effects of energy intake and exercise habits, which are thought to be associated with sarcopenia, were not accounted for in this study. Future studies should therefore incorporate dietary assessments and physical activity measurements to evaluate their potential impact on the relationship between bilirubin and muscle strength.

Fourth, physical function assessments, such as gait speed, were not included. This was because gait speed measurement was not routinely performed in outpatient settings, leading to an insufficient number of cases for analysis. Instead, we applied HGS and SMI as surrogate measures to assess sarcopenia. To strengthen the accuracy of sarcopenia diagnosis, future research should incorporate comprehensive physical function assessments, including gait speed and other performance tests.

Additionally, due to data limitations, other potential confounders, such as nutritional status, physical activity levels, and inflammatory markers, were not included in the present study. Future studies should incorporate these factors to further refine the analysis.

Finally, as this was a cross-sectional study, causal relationships could not be determined. Prospective cohort studies or interventional trials are therefore required to clarify the causal role of bilirubin in muscle function and sarcopenia progression over time.

Conclusion

In this study, total bilirubin was found to be positively associated with hand grip strength and negatively associated with sarcopenia in women with type 2 diabetes. Total bilirubin may thus serve as a useful indicator of sarcopenia in Japanese women.

Acknowledgments

Ethical guideline statement

The ethics committee approved the study (approval number: ERB-C-1876; approval date: 27/11/2020), which was conducted in accordance with the Declaration of Helsinki. Patient consent was obtained through an opt-out process.

Conflict of interest

Okada H received grants from the Japan Diabetes Foundation and received personal fees from Mochida Pharma Co. Ltd., Teijin Pharma Ltd., MSD K.K., Mitsubishi Tanabe Pharma Corporation, AstraZeneca K.K., Sumitomo Dainippon Pharma Co., Ltd., Novo Nordisk Pharma Ltd., Daiichi Sankyo Co., Ltd, Eli Lilly Japan K.K, Kyowa Hakko Kirin Company Ltd, Kissei Pharmaceutical Co., Ltd, Takeda Pharmaceutical Co., Ltd, Kowa Pharmaceutical Co., Ltd, Ono Pharmaceutical Co., Ltd., and Sanofi K.K.

Ushigome E received grant support from the Japanese Study Group for Physiology and Management of Blood Pressure, the Astellas Foundation for Research on Metabolic Disorders (Grant number: 4024) Mishima Kaiun Memorial Foundation and received personal fees from Nippon Boehringer Ingelheim Co., Ltd., Mitsubishi Tanabe Pharma Corporation, Daiichi Sankyo Co., Ltd, MSD K.K., Kyowa Hakko Kirin Co., Ltd., Sumitomo Dainippon Pharma Co., Ltd., Kowa Pharmaceutical Co., Ltd., Novo Nordisk Pharma Ltd., Ono Pharmaceutical Co., Ltd., Taisho Pharmaceutical Co., Ltd., and Sanofi K.K., outside the submitted work.. Donated Fund Laboratory of Diabetes therapeutics is an endowment department, supported with an unrestricted grant from Ono Pharmaceutical Co., Ltd., Taiyo Kagaku Co. Ltd. and Taisho Pharmaceutical Co., Ltd.

Hamaguchi M received grants from AstraZeneca K.K., Ono Pharma Co. Ltd., and Kowa Pharma Co. Ltd, and. received personal fees from AstraZeneca K.K., Ono Pharma Co. Ltd., Eli Lilly, Japan, Sumitomo Dainippon Pharma Co., Ltd., Daiichi Sankyo Co. Ltd., Mitsubishi Tanabe Pharma Corp., Sanofi K.K., K.K., and Kowa Pharma Co. Ltd. outside of the submitted work.

Hasegawa Y received personal fees from Taisho Pharma Co. Ltd., Mitsubishi Tanabe Pharma Corp., and Kowa Pharma Co. Ltd. outside of the submitted work..

Nakajima H received personal fees from Kowa Pharmaceutical Co. Ltd., Kyowa Hakko Kirin Co., Ltd., and Nippon Boehringer Ingelheim Co. Ltd.

Osaka T received personal fees from Nippon Boehringer Ingelheim Co., Ltd., Mitsubishi Tanabe Pharma Corp., Daiichi Sankyo Co. Ltd., Sanofi K.K., Takeda Pharma Co. Ltd., MSD K.K., Sumitomo Dainippon Pharma Co. Ltd., Kowa Pharma Co. Ltd., Novo Nordisk Pharma Ltd., Ono Pharma Co. Ltd., Eli Lilly Japan K.K., Taisho Pharma Co., Ltd., AstraZeneca K.K., Abbott Japan Co. Ltd., Teijin Pharma Ltd., Medtronic Japan Co. Ltd., Otsuka Pharma Co. Ltd., and TERUMO CORPORATION, outside the submitted work.

Hashimoto Y received personal fees from Novo Nordisk Pharma Ltd., Sanofi K.K., Sumitomo Dainippon Pharma Co., Ltd., Nippon Boehringer Ingelheim Co., Mitsubishi Tanabe Pharma Corp., Kowa Company, Ltd., Taisho Pharma Co., Eli Lilly Japan K.K. and Daiichi Sankyo Co.

Senmaru T received personal fees from Eli Lilly Japan K.K., Mitsubishi Tanabe Pharma Co, Daiichi Sankyo Co. Ltd., Kowa Pharma Co., Ltd., Astellas Pharma Inc., Takeda Pharma Co., Ltd., Sanofi K.K., Taisho Toyama Pharma Co., Ltd., Kyowa Kirin Co., Ltd., Kissei Pharma Co., Ltd., MSD K.K., Novo Nordisk Pharma Ltd., Ono Pharma Co., Ltd., AstraZeneca K.K., Mochida Pharma Co. Ltd., TERUMO CORPORATION, Abbott Japan Co. Ltd., outside the submitted work.

Nakanishi N received personal fees from Kowa Pharmaceutical Co. Ltd., and Novo Nordisk Pharma Ltd., Nippon Boehringer Ingelheim Co. Ltd., TERUMO CORPORATION.

Fukui M received grants from Ono Pharma Co. Ltd., Oishi Kenko inc., Yamada Bee Farm, Nippon Boehringer Ingelheim Co. Ltd., Kissei Pharma Co. Ltd., Mitsubishi Tanabe Pharma Corp., Daiichi Sankyo Co. Ltd., Sanofi K.K., Takeda Pharma Co. Ltd., Astellas Pharma Inc., MSD K.K., Kyowa Kirin Co., Ltd., Sumitomo Dainippon Pharma Co., Ltd., Kowa Pharma Co. Ltd., Novo Nordisk Pharma Ltd., Sanwa Kagagu Kenkyusho CO., Ltd., Eli Lilly, Japan, K.K., Taisho Pharma Co., Ltd., Terumo Corp., Tejin Pharma Ltd., Nippon Chemiphar Co., Ltd., Abbott Japan Co. Ltd., Johnson & Johnson K.K. Medical Co., and TERUMO CORPORATION and received personal fees from Nippon Boehringer Ingelheim Co., Ltd., Kissei Pharma Co., Ltd., Mitsubishi Tanabe Pharma Corp., Daiichi Sankyo Co. Ltd., Sanofi K.K., Takeda Pharma Co. Ltd., Astellas Pharma Inc., MSD K.K., Kyowa Kirin Co. Ltd., Sumitomo Dainippon Pharma Co. Ltd., Kowa Pharma Co. Ltd., Novo Nordisk Pharma Ltd., Ono Pharma Co. Ltd., Sanwa Kagaku Kenkyusho Co. Ltd., Eli Lilly Japan K.K., Taisho Pharma Co., Ltd., Bayer Yakuhin, Ltd., AstraZeneca K.K., Mochida Pharma Co. Ltd., Abbott Japan Co. Ltd., Teijin Pharma Ltd., Arkray Inc., Medtronic Japan Co. Ltd., and Nipro Corp., TERUMO CORPORATION, outside the submitted work.

The other authors declare that they have no competing interests.

Funding

No funding was received for this research.

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