Associations between serum total bilirubin levels and the prevalence of metabolic syndrome in elderly Chinese males

Abstract

Objective

Metabolic syndrome (MetS) is a complex cluster of metabolic abnormalities. Serum total bilirubin (TB) is a potent endogenous antioxidant and cytoprotectant. This study aimed to investigate the associations between serum TB levels within the physiological range and the prevalence of MetS and its components in elderly Chinese men.

Methods

A cross-sectional study involved 430 male participants aged ≥ 65 years. Participants were stratified into quartiles based on serum TB levels. The diagnosis of MetS was based on the criteria of the Chinese Diabetes Society.

Results

Serum TB levels were significantly lower in the MetS group than in the non-MetS group. An inverse trend was observed between TB levels and the number of concurrent metabolic abnormalities. After adjusting for confounders such as age, liver function, and renal function, higher physiological TB levels were independently associated with a lower prevalence of MetS, hypertension, dyslipidemia, and diabetes. No significant association was found with obesity. Stratified analysis by TB quartiles showed a gradual decrease in the prevalence of MetS and its components with increasing TB levels.

Conclusion

In elderly Chinese men, higher physiological levels of serum total bilirubin are inversely associated with the prevalence of MetS, hypertension, dyslipidemia, and diabetes, suggesting a potential protective role of bilirubin against these metabolic diseases.

Introduction

Metabolic syndrome (MetS) is a complex cluster of metabolic abnormalities, including insulin resistance, hypertension, dyslipidemia, and obesity (particularly central obesity) [1]. The development and progression of these metabolic diseases are closely associated with damage to target organs such as the heart, kidneys, brain, and peripheral arteries. As the number of metabolic abnormalities increases, patients may transition from a single metabolic disease to MetS. According to the National Cholesterol Education Program Adult Treatment Panel (NCEP ATP) criteria, approximately 34% of the global population is affected by MetS [2, 3]. Furthermore, given the increasing global prevalence of diabetes and obesity, the prevalence of MetS is also growing worldwide. With the advent of an aging society and the high incidence of chronic diseases among the elderly, the occurrence rate of metabolic syndrome gradually rises with age [4].

The pathophysiology of metabolic syndrome remains unclear. However, studies indicate that systemic inflammation, insulin resistance, alterations in adipokine levels, and oxidative stress play essential roles in the development and progression of MetS [5, 6]. Total bilirubin (TB), one of the metabolic products of heme degradation by heme oxygenase (HO), has been demonstrated to exert anti-inflammatory, antioxidant, and anti-apoptotic effects, as well as to improve leptin receptor deficiency and enhance insulin sensitivity [7, 8]. Multiple studies have also shown that TB levels are inversely correlated with hypertension, diabetes, and insulin resistance [9, 10]. Jenko-Pražnikar et al. previously proposed the potential role of bilirubin as an early biomarker for metabolic syndrome, reporting that total bilirubin levels decrease as the number of metabolic syndrome components increases [10].

Studies conducted in European countries have reported an occurrence rate of MetS of 36% in males and 22% in females [11]. A sex-specific analysis is warranted for several reasons. First, bilirubin metabolism is influenced by sex hormones, particularly estrogen, which can modulate the activity of enzymes such as uridine diphosphate-glucuronosyltransferase 1A1 (UGT1A1) and HO, potentially leading to divergent bilirubin levels and bioactivity between sexes [12]. Second, the prevalence, presentation, and pathophysiological drivers of MetS exhibit notable sexual dimorphism. For instance, men often exhibit a higher prevalence of cardiometabolic risk factors at a younger age, and the protective effects of certain factors may differ [13, 14].

Focusing on an elderly male population minimizes the confounding effect of cyclical hormonal fluctuations present in premenopausal women and allows for the examination of this association in a group with high baseline metabolic risk. A cross-sectional study from China indicated that serum TB levels within the physiological range were inversely associated with the prevalence of metabolic syndrome in elderly women in the community [15]. To date, no clinical studies have reported the relationship between serum TB levels within the physiological range and MetS in elderly Chinese men. This study aimed to investigate the correlation between serum TB levels within the physiological range and the prevalence of metabolic syndrome and its individual components in elderly men, to identify new targets for the clinical prevention and treatment of MetS and various metabolic diseases.

Subjects and methods

Subjects

The participants in this cross-sectional study were males ≥ 65 years of age who were treated in the Geriatrics Department of the Chinese PLA General Hospital. Enrollment took place from July 2023 to July 2024. The exclusion criteria were age less than 65 years, female sex, clinical or laboratory evidence of severe systemic diseases (such as cancer, renal failure, hematologic disease, or heart failure), goiter, liver dysfunction (alanine aminotransferase activity higher than 3-fold the upper limit of the normal range (120 U/L), total bilirubin level higher than 21 µmol/L), or HIV-AIDS.

Collection of demographic data

Basic demographic information, including age, educational level, and occupation, was recorded for all study subjects. Past medical history, such as a history of coronary heart disease, hypertension, diabetes mellitus, hyperlipidemia, peripheral atherosclerosis, and stroke, as well as corresponding treatment details, were also documented.

Anthropometric data

Participant anthropometric data were collected by trained medical staff in accordance with standard procedures. Blood pressure, height, and weight were measured. Blood pressure was measured for the second time after a 10-minute rest period, with the average value calculated for analysis. The body mass index (BMI) was calculated via the following formula: BMI = weight (kg)/height² (m²).

Biochemical data

All enrolled study subjects underwent fasting for 8 h, after which venous blood was drawn from the antecubital vein. The blood samples were collected via inert separation gel coagulant tubes and sent for laboratory analysis. Serum levels of TB, direct bilirubin, indirect bilirubin, high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), total cholesterol (TC), fasting plasma glucose (FPG), alanine aminotransferase (ALT), aspartate aminotransferase (AST), uric acid, urea, and serum creatinine were measured. On the basis of the serum TB levels within the physiological range, the subjects were divided into quartile groups: Q1 (2.9–7.5 µmol/L), Q2 (7.6–9.8 µmol/L), Q3 (9.9–13.2 µmol/L), and Q4 (13.3–21 µmol/L).

Definition of MetS

The diagnostic criteria for MetS and its individual components (adopting the recommendations of the Diabetes Branch of the Chinese Medical Association) were as follows [1]:

1. Overweight and/or obesity: BMI ≥ 25 kg/m²;

2. Hyperglycemia: FPG ≥ 6.1 mmol/L (≥ 110 mg/dl) and/or 2-hour postprandial plasma glucose ≥ 7.8 mmol/L (≥ 140 mg/dl), or previously diagnosed diabetes under treatment;

3. Hypertension: systolic/diastolic blood pressure ≥ 140/90 mmHg (1 mmHg = 0.133 kPa), or previously diagnosed hypertension under treatment;

4. Dyslipidemia: fasting serum TG ≥ 1.7 mmol/L (≥ 150 mg/dl), or fasting serum HDL-C < 0.9 mmol/L (< 35 mg/dl) in men and < 1.0 mmol/L (< 39 mg/dl) in women.

The diagnosis of MetS was confirmed when three or more of the above four components were present.

Statistical analyses

Statistical analysis was performed using SPSS v.17.0 software (USA). Continuous variables are expressed as mean ± standard deviations (x̄ ± s), while categorical data are presented as percentages. Since the data followed a normal distribution, comparisons between continuous variables were conducted using analysis of variance (ANOVA). Pairwise comparisons between groups were performed with the least significant difference (LSD) test. Correlation analysis was carried out using Spearman’s rank correlation, and regression analysis was conducted via logistic regression. A two-tailed test was adopted, with p < 0.05 considered statistically significant.

Results

Baseline characteristics

A total of 430 subjects, all elderly males aged between 65 and 102 years with a mean age of 86.58 ± 10.08 years, were included. A CONSORT flow diagram illustrated the participant screening and inclusion process in Fig. 1. The serum total bilirubin level ranged from 2.90 to 21.00 µmol/L, with a mean value of 10.49 ± 4.11 µmol/L. The BMI ranged from 14.71 to 34.82 kg/m², with a mean value of 24.33 ± 3.18 kg/m². Among the participants, 193 (44.9%) were diagnosed with obesity, 319 (74.2%) with hypertension, 296 (68.8%) with dyslipidemia, and 217 (50.4%) with glucose metabolism disorder. Serum total bilirubin levels for each metabolic disease are presented in Table 1.

Fig. 1.

The CONSORT flow diagram illustrates the participant screening and inclusion process. Out of 520 initially assessed elderly male patients, 430 met the inclusion criteria and were enrolled in the final analysis

Table 1.

Serum TB levels for various metabolic diseases

Metabolic disease	Serum TB level (µmol/L)
Obesity	10.48 ± 3.96
Hypertension	10.26 ± 4.18
Dyslipidemia	10.04 ± 3.92
Abnormal sugar metabolism	9.68 ± 3.75

In Table 2, compared with the non-MetS group of elderly male patients, the MetS group exhibited significantly elevated levels of systolic blood pressure (SBP), BMI, FPG, TG, and uric acid (p < 0.05). In contrast, serum TB levels were significantly lower in the elderly male MetS group than in the non-MetS group (p < 0.05).

Table 2.

Characteristics of the male participants according to metabolic syndrome status

	Metabolic syndrome		p
	YES(n = 227)	NO(n = 203)
Age(years) SBP (mmHg) DBP (mmHg) BMI (kg/m2) FPG (mmol/L) TC (mmol/L) TG (mmol/L) LDL-C (mmol/L) HDL-C (mmol/L) UA (µmol/L) TB (µmol/L)	84.52 ± 9.87 136.27 ± 12.51 69.36 ± 8.33 25.4 ± 2.84 6.02 ± 1.52 3.77 ± 0.74 1.59 ± 0.86 2.25 ± 0.69 1.16 ± 0.78 343.05 ± 95.38 10.11 ± 3.92	83.17 ± 11.07 131.75 ± 13.01a 69.43 ± 7.52 23.13 ± 3.11 a 5.47 ± 1.26a 3.86 ± 0.87 1.29 ± 0.74a 2.36 ± 0.71 1.17 ± 0.37 321.91 ± 91.56 b 10.93 ± 4.28b	0.187 < 0.001 0.935 < 0.001 < 0.001 0.288 < 0.001 0.105 0.826 0.02 0.039

SBP systolic blood pressure, DBP diastolic blood pressure, BMI body mass index, FPG fasting plasma glucose, TC total cholesterol, TG triglyceride, LDL-C low-density lipoprotein cholesterol, HDL-C high-density lipoprotein cholesterol, UA uric acid, TB total bilirubin

Comparison of total bilirubin levels among the five groups with different numbers of concurrent metabolic abnormalities

The participants were categorized into five groups based on the number of metabolic abnormalities according to the diagnostic criteria for metabolic syndrome. Serum TB levels were compared among these groups, and the results indicated a statistically significant difference (P < 0.001, Table 3). These findings suggest that serum TB levels vary significantly across the five groups. Furthermore, it was observed that groups with a higher number of coexisting metabolic abnormalities exhibited lower serum TB levels compared to those with fewer metabolic abnormalities. Pairwise comparisons revealed that the group with two metabolic abnormalities had significantly higher serum TB levels than the other groups did (p < 0.001), as shown in Fig. 2. No significant difference in the serum TB level was found between the group with no metabolic abnormalities and the group with one metabolic abnormality (p = 0.536), or between the groups with four or three metabolic abnormalities (p = 0.066).

Table 3.

Comparison of total bilirubin levels among the five metabolic abnormality groups

	n	± s	F	p
Four MA group	63	8.27 ± 2.03	34.07	<0.001
Three MA group	164	9.29 ± 3.26
Two MA group	95	14.24 ± 4.38
One MA group	83	10.8 ± 4.51
No MA group	25	11.34 ± 4.39

MA Metabolic Abnormality

Fig. 2.

Comparison of total bilirubin levels among the five metabolic abnormality groups. *<0.05 (A Comparison of TB levels between the group with no metabolic abnormalities and the other groups. B Comparison of TB levels between the group with one metabolic abnormality and the other groups. C Comparison of TB levels between the group with two metabolic abnormalities and the other groups)

Associations between various metabolic diseases and serum total bilirubin levels

An analysis was conducted to examine the correlation between serum TB levels within the physiological range and the prevalence of various metabolic diseases, with the results as follows: serum TB levels within the physiological range were significantly negatively correlated with the prevalence of hyperlipidemia, diabetes, and hypertension, as shown in Table 4 (r = −0.181, p = 0.001; r = −0.21, p = 0.001; and r = −0.155, p = 0.001, respectively). No significant correlation was detected between serum TB levels within the physiological range and obesity.

Table 4.

Association between various metabolic diseases and serum total bilirubin Levels

Metabolic Diseases	r	p
Obesity	−0.002	0.968
Hypertension	−0.155	0.001
Dyslipidemia	−0.181	0.001
Diabetes	−0.21	0.001

Multivariate logistic regression analysis of risk factors for metabolic diseases

Multivariate logistic regression analyses were conducted using the prevalence of metabolic syndrome and its individual components as dependent variables, and serum TB levels within the physiological range, age, ALT, AST, creatinine, and blood urea nitrogen as independent variables (Table 5). The results revealed that serum TB levels within the physiological range were inversely associated with the prevalence of metabolic syndrome (OR: 0.943, 95% CI: 0.892–0.997; p = 0.04, Table 6); inversely associated with the prevalence of hypertension (OR: 0.948, 95% CI: 0.940–0.999; p = 0.048); inversely associated with the prevalence of dyslipidemia (OR: 0.943, 95% CI: 0.898–0.991; p = 0.021); and inversely associated with the prevalence of diabetes mellitus (OR: 0.953, 95% CI: 0.909–0.998; p = 0.042). Furthermore, the findings indicated that serum TB levels within the physiological range were not significantly associated with obesity.

Table 5.

Multivariate logistic regression analysis of risk factors for metabolic diseases

Metabolic Diseases	β	SE	OR	95%CI	p
MetS	−0.059	0.028	0.943	0.892–0.997	0.04
Obesity Hypertension Dyslipidemia Diabetes	0.041 −0.053 −0.058 −0.049	0.024 0.027 0.025 0.024	1.042 0.948 0.943 0.953	0.995–1.092 0.940–0.999 0.898–0.991 0.909–0.998	0.081 0.048 0.021 0.042

Table 6.

Prevalence of metabolic syndrome and its components per quartile of total bilirubin (%)

	Q1	Q2	Q3	Q4	p
MetS	67.5	66.9	60.2	19.1	< 0.001
Obesity	44.7	41.7	53.1	40.9	0.283
Hypertension	78.9	82.5	72.4	63.5	0.004
Dyslipidemia	74.6	71.8	81.6	49.6	< 0.001
Diabetes	58.7	58.2	52	33.9	< 0.001

Associations between total bilirubin level within the physiological range and the risk of MetS

The prevalence rates of metabolic syndrome and its individual components were calculated according to quartile groups of serum total bilirubin (Table 6). The Q1 group comprised 114 subjects, the Q2 group comprised 103 subjects, the Q3 group comprised 98 subjects, and the Q4 group comprised 115 subjects. Analysis of the differences in the prevalence rates of MetS and its components among the four groups revealed that serum TB levels within the physiological range were generally inversely associated with the incidence of MetS, hypertension, dyslipidemia, and diabetes mellitus (p < 0.001, p = 0.004, p < 0.001, p < 0.001, respectively). Although the prevalence of dyslipidemia in the highest quartile (Q4) was markedly lower, it was somewhat higher in Q3 compared to Q1 and Q2. Notably, the lowest prevalence rates for MetS and all its components (except obesity) were consistently observed in the highest TB quartile (Q4).

Discussion

Our cross-sectional study demonstrated an independent inverse association between physiological serum total bilirubin levels and the prevalence of MetS and its components (hypertension, dyslipidemia, and diabetes) in elderly Chinese men. It is important to note, however, that due to the cross-sectional design, this study can reveal associations but cannot establish a causal relationship between bilirubin and metabolic diseases. The association between serum total bilirubin levels and the risk of MetS remains controversial. Shiraishi et al. reported a correlation between total bilirubin and the incidence of MetS in a cohort of middle-aged Japanese patients without metabolic syndrome [16]. A study conducted in the United States revealed that serum total bilirubin levels were negatively associated not only with the risk of MetS, but also with central obesity and low HDL levels among adolescents aged 12–17 years. However, no intergender comparison was performed in that study [17]. A Japanese study demonstrated that serum total bilirubin levels were negatively associated with the risk of MetS only in males, with no significant association observed in females [18]. However, since the participants in this Japanese study were all aged 20 years or older, this may account for the discrepancy.

Another study indicated that total bilirubin is an independent risk factor for metabolic syndrome in an Egyptian obese population. Higher bilirubin levels were independently associated with a reduced risk of metabolic syndrome, whereas lower bilirubin levels were linked to increased risk [19]. A cross-sectional study involving 12,342 Korean adults aged 20 years and above revealed that, within the physiological range, serum total bilirubin levels were inversely correlated with MetS in subjects without significant metabolic or cardiovascular diseases [20]. A meta-analysis suggested that elevated bilirubin levels may have a significant protective effect against the development of diabetes and metabolic syndrome [21].

Our findings demonstrated that serum TB levels were significantly lower in the elderly MetS group than in the non-MetS group. This finding is consistent with previous domestic and international studies that support the potential role of bilirubin as a protective factor against the development of MetS. The present results demonstrated that the highest serum TB levels were observed in obese patients, followed by hypertensive patients, whereas patients with dyslipidemia and diabetes presented relatively lower levels. Furthermore, the serum TB levels were significantly greater in groups with two metabolic diseases than in those with three metabolic abnormalities. This result may seem counterintuitive, but may suggest a potential non-linear or threshold relationship. It is plausible that a moderate elevation in bilirubin, as an antioxidant and anti-inflammatory agent, could represent a compensatory physiological response in the early stages of metabolic dysregulation, attempting to counteract the onset of additional abnormalities. This compensatory rise might not be sustained as metabolic burden increases to three or four components, leading to the lower levels seen in more advanced groups. Analysis of groups with three coexisting metabolic diseases revealed that the combination of obesity, hypertension, and dyslipidemia was the most prevalent, which aligns with findings from other studies and reflects the disease spectrum of elderly males [22, 23]. Correlation and regression analyses showed that serum TB levels were negatively correlated with the incidence of MetS, hypertension, dyslipidemia, and diabetes. When participants were stratified by quartiles of serum TB levels, as physiological serum TB levels increased, the prevalence rates of MetS, hypertension, dyslipidemia, and diabetes gradually decreased, with the highest serum TB quartile showing a more pronounced reduction in prevalence than the other groups did. However, the elevated prevalence of obesity and hyperlipidemia specifically in the third TB quartile (Q3, 9.9–13.2 µmol/L), which interrupts the otherwise inverse trend, highlights the complexity of these associations. This pattern could be influenced by unmeasured confounders specific to this mid-range bilirubin stratum, or it may indicate that the protective relationship between bilirubin and specific metabolic components is not monotonic across its entire physiological range. These observations underscore that while an overall inverse association is statistically supported, the interplay between bilirubin and metabolic health is likely multifactorial and may involve dynamic, component-specific responses. Therefore, the findings of this study regarding the relationship between bilirubin and the components of MetS differ from those of other studies [15, 20].

In the elderly male population, serum total bilirubin levels are negatively correlated with MetS, which may be partly attributable to the inverse associations between total bilirubin levels and hypertension, hyperlipidemia, and diabetes. Current studies propose several potential mechanisms through which serum bilirubin may exert protective effects in metabolic diseases. Hyperbilirubinemia reduces visceral obesity and insulin resistance by inhibiting inflammatory cytokines, thereby preventing the development of obesity [24, 25]. This is primarily achieved through direct activation of peroxisome proliferator-activated receptor (PPAR) α, which upregulates target genes that mitigate obesity and decreases the expression of de novo lipogenic enzymes. Furthermore, the reduction in bilirubin levels observed in obese individuals may be attributed to increased bilirubin consumption as a compensatory response to elevated oxidative stress [26].

Animal studies have demonstrated that bilirubin can improve insulin synthesis and sensitivity, increase the expression of GLUT4, and protect pancreatic β-cells from oxidative stress and damage, further supporting the potential role of bilirubin in reducing the risk of type 2 diabetes [27, 28]. However, it should be noted that findings from animal studies are not necessarily applicable to humans, and further research is needed to confirm the potential therapeutic effects of bilirubin in humans. Bilirubin has been shown to possess anti-inflammatory and antioxidant properties, which may help reduce systemic oxidative stress and inflammation—both of which are known contributors to insulin resistance. By mitigating oxidative stress and inflammation, bilirubin may contribute to improved insulin sensitivity and a reduced risk of insulin resistance and type 2 diabetes. Bilirubin enhances insulin sensitivity through the modulation of cholesterol metabolism, adipokines, and PPAR [29, 30]. The study by Abbasi et al. provides additional evidence for the potential protective role of bilirubin in the development of T2DM. This study revealed that a common genetic variant (rs6742078) in the UGT1A1 gene, which is involved in bilirubin metabolism, is strongly associated with increased circulating total bilirubin levels and a reduced risk of T2DM. This finding suggests that elevated bilirubin levels may have a causal relationship with a decreased risk of developing T2DM [31].

Wallner et al. previously proposed a potential mechanism underlying the association between bilirubin and blood lipids [32]. In Gilbert syndrome, mild hyperbilirubinemia is associated with reduced circulating TC, LDL-C, and triacylglycerol levels and an elevated HDL/LDL ratio [33, 34]. On the other hand, HDL-C can induce the expression of HO-1. Our prior animal experiments demonstrated that upregulating HO-1 via the administration of an HO-1 inducer significantly increased serum bilirubin levels in rats, suggesting that HO-1 plays a profound role in the protective mechanism of elevated bilirubin against MetS [35, 36]. Indeed, bilirubin promotes fatty acid β-oxidation and reduces fatty acid synthesis by activating PPARα and its associated pathways [24].

Therefore, our findings regarding the relationship between bilirubin and components of metabolic syndrome differ from those of other related studies, which may be attributed to sex differences, lifestyle variations, or ethnic diversity. Bilirubin levels are influenced by estrogen in females, and sex-related differences in HO-1 activity associated with stress may serve as a potential explanation [12]. Lifestyle factors, including high dietary intake of heme iron, cigarette smoking, alcohol consumption, and the consumption of antioxidant vitamins, must also be considered. A pro-oxidant/antioxidant imbalance in the blood and tissue may be induced by these factors [37–39].

This study has several limitations. First, only total bilirubin was measured in this study; therefore, the observed association reflects the relationship between serum total bilirubin levels and metabolic diseases, and does not necessarily represent the associations of indirect or direct bilirubin with these conditions. Second, although not conclusively confirmed, some reports suggest that serum bilirubin levels may be influenced by smoking and alcohol consumption [37]. Since the study participants were elderly men and data on smoking and drinking habits were not collected, these unrecorded factors may have introduced bias into the results. Furthermore, while a statistically significant inverse association was observed, the absolute difference in TB levels between the MetS and non-MetS groups was modest. The clinical utility of TB as an individual-level diagnostic marker requires further evaluation in longitudinal settings.

Conclusions

In conclusion, our findings indicate that within the physiological range, higher serum total bilirubin levels are independently associated with a reduced prevalence of metabolic syndrome and its key components—hypertension, dyslipidemia, and diabetes—in elderly Chinese men. This consistent inverse association supports the view that bilirubin may act as an intrinsic protective factor against metabolic diseases, highlighting its potential as a clinically relevant biomarker for risk stratification.

Abbreviations

MetS

Metabolic syndrome

NCEP ATP

National Cholesterol Education Program Adult Treatment Panel

TB

Total bilirubin

HO

Heme oxygenase

UGT1A1

Uridine diphosphate-glucuronosyltransferase 1A1

BMI

Body mass index

HDL-C

High-density lipoprotein cholesterol

LDL-C

Low-density lipoprotein cholesterol

TG

Triglyceride

TC

Total cholesterol

FPG

Fasting plasma glucose

ALT

Alanine aminotransferase

AST

Aspartate aminotransferase

ANOVA

Analysis of variance

LSD

Least significant difference

SBP

Systolic blood pressure

PPAR

Peroxisome proliferator-activated receptor

Authors’ contributions

Y D, S L, P H and J C conceived and designed the research. Y D, S L, X H and P H collected the data. Y D, S L and X H analyzed the data. Y D and S L drafted the manuscript. Y D, S L, P H and J C revised the manuscript. All authors contributed to this study and approved the submitted version.

Funding

This research did not receive funding.

Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Declarations

Ethics approval and consent to participate

The Ethics Committee of Chinese PLA General Hospital approved this study (No. S2021-276-01) following an internal, independent peer-review process. The research was conducted in accordance with Declaration of Helsinki (as revised in 2013). Written informed consent will be obtained from all participants. Permission will also be sought for the collection, storage, and future use of biological samples.

Consent for publication

The results of this study have obtained consent from all patients for publication, and no personal data or confidential information will be disclosed.

Competing interests

The authors declare no competing interests.