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Sci Rep
Sci Rep
Scientific Reports
2045-2322
Nature Publishing Group UK London

72665
10.1038/s41598-024-72665-9
Article
Association between serum uric acid levels and cardio-ankle vascular index stratified by circulating level of CD34-positive cells among elderly Japanese men: a cross-sectional study
http://orcid.org/0000-0002-3381-9288
Shimizu Yuji simizu@iph.osaka.jp

12
Kawashiri Shin-Ya 34
Yamanashi Hirotomo 14
Nakamichi Seiko 1
Hayashida Naomi 46
Nagata Yasuhiro 34
Maeda Takahiro 145
1 grid.174567.6 0000 0000 8902 2273 Department of General Medicine, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
2 grid.416993.0 0000 0004 0629 2067 Epidemiology Section, Division of Public Health, Osaka Institute of Public Health, Osaka, Japan
3 grid.174567.6 0000 0000 8902 2273 Department of Community Medicine, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
4 grid.174567.6 0000 0000 8902 2273 Leading Medical Research Core Unit, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
5 grid.174567.6 0000 0000 8902 2273 Department of Islands and Community Medicine, Nagasaki University Graduate School of Biomedical Sciences, Nagasaki, Japan
6 https://ror.org/058h74p94 grid.174567.6 0000 0000 8902 2273 Division of Strategic Collaborative Research, Atomic Bomb Disease Institute, Nagasaki University, Nagasaki, Japan
20 9 2024
20 9 2024
2024
14 2196517 7 2024
9 9 2024
© The Author(s) 2024
2024
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Although serum uric acid (UA) has been reported to be positively associated with increased arterial stiffness as evaluated by cardio-ankle vascular index (CAVI), UA also has an antioxidative effect that prevents endothelial damage. Therefore, the status of endothelial repair induced by endothelial damage might affect the correlation between UA and CAVI. To clarify the correlation between UA and CAVI in relation to endothelial repair activity, we performed a cross-sectional study with 246 Japanese men aged 60–69 years undergoing a general health check-up. The analysis was stratified by the median circulating level of CD34-positive cells because circulating levels of CD34-positive cells could indicate the degree of endothelial repair activity. Independent of known cardiovascular risk factors, among participants with high circulating levels of CD34-positive cells (0.95 cells/μL ≤), UA was significantly positively correlated with CAVI (standardized parameter estimate β = 0.23, p = 0.009), but not among participants with low circulating levels of CD34-positive cells (< 0.95 cells/μL) (β = 0.07, p = 0.445). Independent of established cardiovascular risk factors, UA levels were significantly positively correlated with increased arterial stiffness only among participants with aggressive endothelial repair as evaluated by circulating levels of CD34-positive cells. These results might help clarify some background mechanisms related to endothelial activity.

Subject terms

Diagnostic markers
Atherosclerosis
MEXT | Japan Society for the Promotion of Science (JSPS)22K06421 21H02575 Shimizu Yuji Maeda Takahiro issue-copyright-statement© Springer Nature Limited 2024
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pmcIntroduction

Increased arterial stiffness as evaluated by cardio-ankle vascular index (CAVI) is reported to be positively associated with oxidative stress1. Uric acid (UA) is an end product of purine metabolism. UA helps protect against oxidative stress2, but increased UA levels are associated with increased arterial stiffness as evaluated by CAVI3,4. UA is also known to activate inflammation5,6. Since inflammation increases CAVI7, UA might be positively associated with CAVI as an indicator of inflammation.

Endothelial damage stimulates endothelial repair; the antioxidative effect and development of atherosclerosis are known endothelial repair processes. The antioxidative effect of UA is mainly intended to reduce the risk of endothelial damage. The development of atherosclerosis is associated with aggressive endothelial repair.

Recently, endothelial progenitor cells such as CD34-positive cells were revealed to contribute to endothelial repair, including the development of atherosclerosis8,9. Circulating levels of CD34-positive cells could indicate the degree of endothelial repair activity when categorized based on the median value; individuals with high levels of CD34-positive cells have higher endothelial repair activity than individuals with low levels of CD34-positive cells10–13.

Those studies suggest a positive correlation between UA and CAVI only in participants with high circulating levels of CD34-positive cells, who have active endothelial repair. Therefore, we hypothesized that independent of known cardiovascular risk factors, UA is significantly positively correlated with CAVI among participants with high circulating CD34-positive cell count categorized based on the median value, but not among participants with low circulating CD34-positive count.

To evaluate this hypothesis, we conducted a cross-sectional study of 246 elderly Japanese men aged 60–69 years who participated in a general health check-up in 2013–2015.

Methods

Study population

The methods related to the present risk survey, including CAVI and circulating CD34-positive cell count assessment, have been described elsewhere10–13.

This study was approved by the ethics committee of the Nagasaki University Graduate School of Biomedical Sciences (project registration number, 14051404). Written consent forms were available in Japanese to ensure comprehensive understanding of the study objectives. Participants provided written informed consent. All of the procedures involving human participants in this study were performed in accordance with the ethical standards of the institutional research committee, Helsinki Declaration of 1964, and its later amendments for comparable ethical standards.

The study population comprised 319 males aged 60–69 years residing on the Goto Islands in western Japan who underwent an annual medical check-up from 2013 to 2015 as recommended by the Japanese government. Participants without data on circulating level of CD34-positive cells (n = 2) or blood test results (n = 10) were excluded. Participants without data on CAVI (n = 61) were also excluded. The remaining 246 participants (mean age, 65.5 years; standard deviation (SD), 2.7 years; range, 60–69 years) were enrolled in the study.

Data collection and laboratory measurements

Trained interviewers obtained information on drinking status (non-drinker, drinks often, or drinks daily) and smoking status (never, former, or current smoker). Body weight and height were measured with an automatic body composition analyzer (BF-220; Tanita, Tokyo, Japan). Body mass index (BMI; kg/m2) was calculated. Systolic (SBP) and diastolic (DBP) blood pressure were measured in the right arm after at least 5 min of rest in a sitting position with a blood pressure measuring device (HEM-907; Omron, Kyoto, Japan) and recorded by a trained observer. Blood samples were collected in heparin sodium, EDTA-2K, siliconized, and sodium fluoride tubes. CD34-positive cells were measured in freshly drawn blood samples from the heparin sodium tube within 24 h of sample collection using BD Trucount™ technology (Becton Dickinson Biosciences, San Jose, CA), an accurate and reproducible single-platform assay cited in the International Society of Hematotherapy and Graft Engineering (ISHAGE) guidelines14 and supported by automated software in the BD FACSCanto™ II system.

Approximately 30 min are required to measure CD34-positive cells in each sample. Measurement of CD34-positive cells requires fresh samples, within 24 h after blood collection. Since a only limited number of FACSCanto™ II systems was available in our area, a maximum of 20 samples could be processed for CD34-positive cell count each day. Therefore, we limited the measurement of CD34-positive cells to men aged 60–69 years who participated in our general health check-up. A detailed description of circulating CD34-positive cell measurement in our study is available elsewhere15.

Samples from the EDTA-2K tubes were used to measure red blood cells (RBCs), platelets, and reticulocytes (per mille, ‰) using automated procedures at SRL, Inc. (Tokyo, Japan). Reticulocyte count was determined using the following formula: reticulocyte count (× 104 cells/μL) = (reticulocytes, ‰) × RBC (× 104 cells/μL)/1000. Serum triglycerides (TG), serum high-density lipoprotein cholesterol (HDLc), serum low-density lipoprotein cholesterol (LDLc), hemoglobin A1c (HbA1C), and serum creatinine were also measured at SRL, Inc., using standard laboratory procedures. The glomerular filtration rate (GFR) was estimated with an established method recently adapted by a working group of the Japanese Chronic Kidney Disease Initiative16: GFR (mL/min/1.73 m2) = 194 × (serum creatinine (enzyme method))−1.094 × (age)−0.287.

CAVI was determined using a Vasera VS-1000 vascular screening system (Fukuda Denshi, Tokyo, Japan), with the participant resting in a supine position. The underlying principles of CAVI have been described elsewhere by Yamabe et al.17.

Statistical analysis

Characteristics of the study population stratified by circulating level of CD34-positive cells were expressed as means ± standard deviation for continuous variables, except for TG. Since TG had skewed distributions, data were expressed as medians [interquartile range], followed by logarithmic transformation. For daily drinker, often drinker, current smoker, and former smoker status, n (%) was reported. Using a regression model, a trend test was performed to calculate the p value of each variable based on circulating level of CD34-positive cells. To evaluate the correlation between UA and CAVI, simple correlation analysis, simple linear regression analysis, and multiple linear regression analysis of CAVI with adjustment for relevant confounding factors among all participants and stratified by circulating level of CD34-positive cells were performed. In multiple regression analysis, adjustments were made for age, SBP (mmHg), daily drinker (yes/no), often drinker (yes/no), current smoker (yes/no), former smoker (yes/no), BMI (kg/m2), HDLc (mg/dL), LDLc (mg/dL), HbA1c (%), and GFR (mL/min/1.73 m2). The effect of the interaction of circulating level of CD34-positive cells on the correlation between UA and CAVI was evaluated using multiple regression analysis. Since the correlation between platelet count and circulating level of CD34-positive cell is an efficient tool for evaluating endothelial repair activity10–12,18, we also calculated the simple correlation coefficient by circulating level of CD34-positive cells. Levels of UA are reported to increase with advancing age19; aging also is known to be associated with decreased hematopoietic activity20. Therefore, to evaluate the effect of circulating level of CD34-positive cells on the correlation between reticulocyte count and UA, both crude and age-adjusted models were used.

All statistical analyses were performed with SAS for Windows (version 9.4; SAS Inc., Cary, NC). Probability values less than 0.05 were regarded as statistically significant.

Results

Clinical characteristics of the study population

The median circulating level of CD34-positive cells was 0.95 cells/μL. The clinical characteristics of the study population stratified by circulating level of CD34-positive cells are shown in Table 1. Participants with high circulating levels of CD34-positive cells had significantly higher platelet and reticulocyte counts and significantly lower GFR than participants with low levels of circulating CD34-positive cells. No significant differences in CAVI or UA were observed between participants with high versus low levels of CD34-positive cells.Table 1 Characteristics of the study population in terms of circulating CD34-positive cell levels.

	Circulating CD34-positive cells, cells/μL	p value	
Low (< 0.95 cells/μL)	High (0.95 cells/μL ≤)	
No. of participants	123	123		
Age, years	65.6 ± 2.6	65.3 ± 2.7	0.273	
SBP, mmHg	136 ± 16	138 ± 17	0.150	
DBP, mmHg	86 ± 11	87 ± 10	0.349	
Daily drinker, %	45.5	49.6	0.525	
Often drinker, %	15.4	18.7	0.500	
Current smoker, %	24.4	28.5	0.472	
Former smoker, %	46.3	48.0	0.799	
BMI, kg/m2	23.3 ± 3.2	24.0 ± 2.7	0.072	
TG, mg/dL	89 [65, 111]*1	95 [67, 137]*1	0.061*2	
HDLc, mg/dL	57 ± 15	57 ± 14	0.842	
LDLc, mg/dL	109 ± 29	120 ± 30	0.005	
HbA1c, %	5.6 ± 0.6	5.8 ± 0.6	0.051	
GFR, mL/min/1.73 m2	75.9 ± 15.3	71.9 ± 12.7	0.025	
Plt, ×104/μL	20.9 ± 5.4	22.9 ± 4.9	0.003	
Reticulocyte, ×104 cells/μL	5.2 ± 1.6	5.8 ± 1.9	0.009	
CAVI	8.55 ± 1.00	8.55 ± 0.96	0.979	
UA, mg/dL	5.8 ± 1.3	6.0 ± 1.3	0.269	
Values: mean ± standard deviation.

SBP: systolic blood pressure; DBP: diastolic blood pressure; BMI: body mass index; TG: triglycerides; HDLc: HDL-cholesterol; LDLc: LDL-cholesterol; HbA1c: hemoglobin A1c; GFR: glomerular filtration rate; Plt: platelet; CAVI: cardio-ankle vascular index; UA: uric acid.

*1: Values are median [the first quartile, the third quartile]. Regression model for mean values was used for determining p values. *2: Logarithmic transformation was used for evaluating p.

Correlation between cardio-ankle vascular index (CAVI) and serum uric acid (UA)

Simple correlation analysis and simple linear regression analysis showed that UA was significantly positively correlated with CAVI among all participants. When we stratified by circulating level of CD34-positive cells, positive correlation was only observed among participants with high circulating levels of CD34-positive cells (Table 2; Fig. 1). Correlations remained unchanged even after further adjustment for known cardiovascular risk factors (Table 3).Table 2 Simple correlation coefficients for cardio-ankle vascular index (CAVI) and other variables.

	Total	Circulating CD34-positive cells, cells/μL	
Low (< 0.95 cells/μL)	High (0.95 cells/μL ≤)	
r	p	r	p	r	P	
No. of participants	246	123	123	
Age	0.19	0.003	0.06	0.482	0.31	 < 0.001	
SBP	0.33	 < 0.001	0.34	 < 0.001	0.33	 < 0.001	
DBP	0.26	 < 0.001	0.27	0.003	0.25	0.006	
Daily drinker	0.07	0.252	− 0.03	0.768	0.18	0.0496	
Often drinker	− 0.06	0.385	0.03	0.771	− 0.13	0.137	
Current smoker	0.03	0.608	0.07	0.468	0.004	0.997	
Former smoker	0.13	0.43	0.06	0.540	0.21	0.023	
BMI	− 0.02	0.804	− 0.05	0.598	0.04	0.633	
TG	0.09	0.153	0.12	0.197	0.07	0.458	
HDLc	− 0.08	0.240	− 0.09	0.309	− 0.06	0.540	
LDLc	− 0.10	0.101	− 0.22	0.015	0.01	0.914	
HbA1c	0.13	0.047	0.19	0.035	0.07	0.458	
GFR	− 0.05	0.405	0.06	0.944	− 0.13	0.149	
UA	0.15	0.015	0.09	0.307	0.22	0.014	
r: simple correlation coefficient; CAVI: cardio-ankle vascular index; SBP: systolic blood pressure; DBP: diastolic blood pressure; BMI: body mass index; TG: triglycerides; HDLc: HDL-cholesterol; LDLc: LDL-cholesterol; HbA1c: hemoglobin A1c; GFR: glomerular filtration rate; UA: uric acid; TG is calculated as logarithmic values.

Fig. 1 Simple linear regression analysis of cardio-ankle vascular index (CAVI) and uric acid among (a) total, (b) low circulating CD34-positive cell level, and (c) high circulating CD34-positive cell level. UA: serum uric acids.

Table 3 Results of multiple linear regression analysis of mean cardio-ankle vascular index (CAVI) with relevant factors.

	Total	Circulating CD34-positive cells, cells/μL	
Low (< 0.95 cells/μL)	High (0.95 cells/μL ≤)	
Β	β	p	Β	β	p	Β	β	P	
No. of participants	246	123	123	
Age	0.05	0.14	0.020	0.02	0.04	0.653	0.10	0.27	0.002	
SBP	0.02	0.30	 < 0.001	0.02	0.31	0.002	0.02	0.34	 < 0.0001	
Daily drinker	0.05	0.02	0.720	− 0.11	− 0.05	0.582	0.17	0.09	0.378	
Often drinker	0.03	0.01	0.867	0.23	0.08	0.388	0.01	0.004	0.965	
Current smoker	0.26	0.12	0.114	0.08	0.03	0.754	0.50	0.23	0.028	
Former smoker	0.28	0.14	0.048	0.07	0.04	0.725	0.52	0.27	0.009	
BMI	− 0.04	− 0.11	0.079	− 0.06	− 0.18	0.061	− 0.003	− 0.01	0.917	
HDLc	− 0.01	− 0.09	0.140	− 0.01	− 0.10	0.273	− 0.004	− 0.05	0.579	
LDLc	− 0.003	− 0.09	0.147	− 0.01	− 0.20	0.027	0.002	0.07	0.370	
HbA1C	0.18	0.11	0.061	0.25	0.15	0.103	0.13	0.08	0.304	
GFR	− 0.001	− 0.02	0.775	0.001	0.01	0.896	− 0.004	− 0.05	0.577	
UA	0.08	0.11	0.077	0.06	0.07	0.445	0.17	0.23	0.009	
SBP: systolic blood pressure; BMI: body mass index; TG: triglycerides; HDLc: HDL-cholesterol; LDLc: LDL-cholesterol; GFR: glomerular filtration rate; UA: uric acid; Β: parameter estimate; β: standardized parameter estimate. p: p factor for multivariable linear regression models.

Effect of the correlation between serum uric acid (UA) and circulating level of CD34-positive cells on cardio-ankle vascular index (CAVI)

The correlation between UA and circulating level of CD34-positive cells on CAVI had a significant effect on CAVI. The fully-adjusted p-value of the effect of this interaction was 0.041.

Correlation between platelet count and circulating level of CD34-positive cells stratified by circulating level of CD34-positive cells

Platelet count was significantly positively correlated with circulating level of CD34-positive cells among participants with low circulating levels of CD34-positive cells (simple correlation coefficient r = 0.23, p = 0.011), but not among participants with high circulating levels of CD34-positive cells (r = − 0.02, p = 0.859).

Correlation between reticulocyte count and uric acid (UA) by circulating level of CD34-positive cells

For participants with low circulating levels of CD34-positive cells, there was a positive tendency between reticulocyte count and UA (r = 0.17, p = 0.057), but the correlation was not statistically significant. After adjusting for age, the correlation became significant (age-adjusted partial correlation coefficient r = 0.20, p = 0.026). For participants with high circulating levels of CD34-positive cells, no correlation was observed; the corresponding values were r = 0.03 and p = 0.760 in the crude model and r = 0.03 and p = 0.759 in the age-adjusted model.

Discussion

The major finding of the present study was that independent of known cardiovascular risk factors, UA is positively correlated with CAVI. This correlation was limited to participants with high circulating levels of CD34-positive cells.

Independent correlations between UA and CAVI were reported in a previous Japanese cross-sectional study3. A Chinese study reported a positive linear correlation between UA and CAVI4. Results from these studies are partly consistent with the results of the present study, which showed a non-independent positive correlation between UA and CAVI among all participants.

Our present study provides further evidence that this positive correlation is limited to participants with high circulating levels of CD34-positive cells. However, the mechanism underlying these associations were unknown. UA activates inflammation5,6 and protects against oxidative stress2. Since inflammation7 and oxidative stress1 increase CAVI, inflammation, oxidative stress, and antioxidative stress are the most likely candidate mechanisms underlying the present results.

The possible mechanisms underlying the present results are summarized in Fig. 2. Relationships marked in red (I−IX) were observed in the present study.Fig. 2 Possible mechanism that underlying the association between serum uric acid and cardio-ankle vascular index (CAVI). Relations marked in red (I–IX) were observed in present study. *: Observed in age-adjusted model. UA: serum uric acids. CD34+: CD34-positive cell. Plt: Platelet. CAVI: cardio-ankle vascular index. High CD34+: participants with a high circulating CD34-posistive cell count. Low CD34+: participants with a low circulating CD34-posistive cell count.

Both endothelial repair deficiency and aggressive endothelial repair increase arterial stiffness as evaluated by CAVI. The former condition occurs in participants with low circulating levels of CD34-positive cells while the latter condition occurs in participants with high circulating levels of CD34-positive cells10.

Therefore, aggressive endothelial repair might be responsible for the positive correlation between UA and CAVI; high circulating levels of CD34-positive cells indicate aggressive endothelial repair. Since the status of endothelial repair itself could not act as a determinant of UA levels and the status of arterial stiffness which was evaluated by CAVI, essentially the same values of UA and CAVI were observed in patients with low versus high levels of circulating CD34-positive cells (Table 1, Fig. 2-(IX)).

Platelets play an important role as an initial actor in aggressive endothelial repair i.e., development of atherosclerosis21. Platelet count act as an indicator of endothelial repair activity22; the production of CD34-positive cells and platelets is stimulated by endothelial damage. Aggressive endothelial repair causes a reduction in circulating levels of CD34-positive cells and platelets due to consumption, but the degree of reduction is much smaller for platelets. In addition, CD34-positive cells were also reported to differentiate into megakaryocytes, the source of platelets23. Therefore, platelet count was significantly positively correlated with circulating level of CD34-positive cells among participants without aggressive endothelial repair while no significant correlation was observed for participants with aggressive endothelial repair. These concepts have been described elsewhere10–12,18. In the present study, platelet count was found to be significantly positively correlated with circulating level of CD34-positive cells among participants with low circulating levels of CD34-positive cells but not among participants with high circulating levels of CD34-positive cells (Fig. 2-(V,VII)). Furthermore, participants with high circulating levels of CD34-positive cells had significantly higher platelet count than participants with low circulating levels of CD34-positive cells (Table 1) (Fig. 2-(IV)). These results support the aforementioned mechanism underlying the correlation between UA and CAVI.

UA induces endothelial dysfunction by activating inflammation5,6. Active inflammation as evaluated by high-sensitivity C-reactive protein is positively associated with CAVI7. Since active endothelial injury stimulates endothelial repair by inducing more circulating CD34-positive cells via platelet activation21,24, UA could be positively associated with CAVI among participants with high circulating levels of CD34-positive cells (Table 2, 3; Fig. 2-(VIII)).

On the other hand, we found no significant correlation between UA and CAVI among participants with low circulating levels of CD34-positive cells. Even when UA levels indicate inflammatory activity5, UA has an antioxidative effect2 that can prevent endothelial damage. Therefore, in participants without aggressive endothelial repair, serum UA concentration not only indicates the risk of endothelial dysfunction but also the prevention of endothelial damage. Thus, there might be no significant correlation between UA and CAVI (Tables 2, 3; Fig. 2-(VI)). In the age-adjusted model, no significant correlation between UA and reticulocyte count was observed among participants with high circulating levels of CD34-positive cells, but there was a significant positive correlation between those two factors among participants with low circulating levels of CD34-positive cells. Reticulocytes reportedly play an important role in antioxidative stress25,26 and reticulocyte count was found to be inversely associated with carotid atherosclerosis27. Therefore, the positive correlation between UA and reticulocyte count partly indicates the activity of antioxidative stress while no correlation between UA and reticulocyte indicates that UA no longer acts as an indicator of antioxidative related to reticulocytes (Fig. 2-(I,II)).

Furthermore, it is known that hematopoietic activity in the bone marrow declines with age28. Declining hematopoietic activity influences levels of CD34-positive cells, platelets, and reticulocytes (Table 1, Fig. 2-(III,IV)). Age-related decline in bone marrow activity induces endothelial repair deficiency, which might act as a strong confounding factor on the correlation between UA and CAVI among participants with low circulating levels of CD34-positive cells.

In the present study, a multifaceted analysis was performed with a single study population that could illustrate the potential mechanism underlying the main results. One strength of the present study is that it was not limited to reporting a circulating CD34-positive cell level–specific association between UA and CAVI.

The clinical implication of the present study is that although UA is correlated with increased arterial stiffness as evaluated by CAVI3,4, the negative effect of high UA levels on the endothelium is limited to subjects with aggressive endothelial repair.

This study has some limitations that warrant consideration. First, while UA plays an important role in antioxidative stress2, no data concerning oxidative stress were available. Further investigation using data such as levels of reactive oxygen species, superoxide dismutase, and catalase are necessary. Because of technical problems, no data were available for women in this study. Since there are differences in the causes of hyperuricemia and gout by sex29, further investigation with data on circulating CD34-positive cell levels in women is necessary. Unknown confounders such as medications, genetic characteristics, and socioeconomic status might also influence the main results. Further investigations with data on those variables are necessary. Due to the cross-sectional nature of this study, causal relationships could not be established. However, multifaceted analysis could illustrate the potential mechanism underlying the main results.

Conclusions

In conclusion, our study revealed that, in addition to established cardiovascular risk factors, UA levels are significantly positively correlated with increased arterial stiffness only among participants with aggressive endothelial repair as evaluated by circulating level of CD34-positive cells. These results may help clarify some background mechanisms related to endothelial activity.

Acknowledgements

We are grateful to staff from Goto city hall for their outstanding support.

Author contributions

YS designed the study, performed the statistical analyses, interpreted the data, and drafted and revised the manuscript. YS, SY.K, HY, SN, NH, YN, and TM assisted with the study design, were involved in data collection, and checked the manuscript. HY, YN, and TM participated in the study concept and checked the manuscript. TM was the general coordinator and designed the study.

Funding

This study was supported by Grants-in-Aids for Scientific Research from Japan Society for the Promotion of Science (No.21H02575, No.22K06421). This funding source had no role in the design of this study and will not have any role during its execution, analyses, interpretation of the data, or decision to submit results.

Data availability

For our studies described in this review, we cannot publicly provide individual data due to participant confidentiality, according to ethical guidelines in Japan. Additionally, obtaining informed consent does not include a provision for publicity sharing data. Qualifying researchers may apply to access a minimal dataset. Please contact the office of data management at ritouken@vc.fctv-net.jp. Information for where the data request is also available at http://www.med.nagasaki-u.ac.jp/cm/.

Declarations

Competing interests

The authors declare no competing interests.

Ethical approval and consent to participants

This study was approved by the Ethics Committee of Nagasaki University Graduate School of Biomedical Sciences (project registration number 14051404). All procedures involving human participants were performed in accordance with the ethical standards of the institution research committee and with the 1964 Helsinki Declaration and its later amendments for comparable ethical standards.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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