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Impairment of endothelial function in Parkinson’s disease

BMC Research Notes volume 15, Article number: 284 (2022) Cite this article

Abstract

Objective

There are conflicting data regarding the relationship between Parkinson’s disease (PD) and the atherosclerotic process. This study aimed to compare endothelial function in patients with PD and matched controls. In PD subjects, we searched for factors contributing to endothelial dysfunction as well. Traditional vascular risk factors, PD characteristics, and PD medication were considered.

Results

We prospectively enrolled 41 patients with PD and 41 controls matched for age, sex, body mass index, and vascular risk factors. Endothelial function (EF) was assessed using peripheral arterial tonometry (EndoPAT 2000 device) and expressed as reperfusion hyperemia index (RHI). Clinical characteristics including PD medication were recorded. RHI was non-significantly lower in the PD group than in controls (1.8 ± 0.5 vs. 1.9 ± 0.5, p = 0.478). In PD patients, in linear regression analysis, smoking (beta = −0.453, p = 0.008) and use of dopamine agonists (beta = -0.365, p = 0.030) were significant contributors in a model predicting RHI. Despite non-significant differences in endothelial dysfunction between PD patients and controls, our results suggest an association between smoking, dopamine agonists, and impaired EF in PD patients. The small sample size, as well as the absence of an extended search for traditional and non-traditional vascular risk factors, are the most important factors limiting the interpretation of the current results.

Introduction

Parkinson’s disease (PD) belongs to the most common neurodegenerative diseases. Resting tremor, rigidity, bradykinesia, and postural instability belong among classical motor symptoms of PD. PD is accompanied by the loss of dopaminergic neurons and Lewy pathology. Possible underlying mechanisms include oxidative stress, mitochondrial dysfunction, diminished neurotransmitter level, and perturbed protein homeostasis [1]. PD patients suffer from a variety of comorbidities including complications of atherosclerotic diseases [2]. There are conflicting data regarding the relationship between PD and the atherosclerotic process. Some studies have found a higher incidence of vascular disease in PD patients, while others described their similar or even lower incidence in comparison to the matched non-PD population [3,4,5,6]. Likewise, studies of the subclinical atherosclerotic process provide inconsistent results. Using the measurement of carotid intima-media thickness (IMT), some authors concluded that PD patients have a lower risk of atherosclerosis, while others reported that the IMT in PD patients was significantly higher than in controls [7,8,9]. Endothelial dysfunction (ED) is an initial process and a key component of atherogenesis [10]. Previous studies indicated that endothelial function (EF), as assessed by the flow-mediated dilation (FMD), was significantly decreased in PD patients [11, 12]. Several possible mechanisms are explaining the impairment of EF in PD. Both PD and endothelial dysfunction possibly share multiple underlying mechanisms including mitochondrial dysfunction and oxidative stress [13]. Additionally, many of the well-established cardiovascular risk factors promote atherogenesis. These include non-modifiable risk factors such as age, sex, and positive family history, as well as modifiable ones. Traditional vascular risk factors include smoking, hypertension, dyslipidemia, and diabetes mellitus. However, mechanisms are not always completely understood and multiple non-traditional vascular risk factors may play a role [14]. PD patients with L-dopa therapy exhibit increased levels of homocysteine. Hyperhomocysteinemia can lead to vascular disease [15]. Although the use of dopamine agonists might be associated with cardiovascular complications, their impact on EF has not been studied so far [16]. Both, FMD of the brachial artery and peripheral arterial tonometry (PAT) of digital arteries are non-invasive measures of endothelial function that assess vascular endothelium dilation in response to shear stress forces. FMD is the more widely used technique. However, PAT is a promising method offering the advantage of easier use, and relative operator independence [17]. To the best of our knowledge, this is the first study to investigate EF using PAT in PD patients. In this study, we aimed to compare EF in patients with PD and controls matched for age, sex, and traditional vascular risk factors. Impaired EF in PD subjects was suspected. In PD subjects, we additionally searched for factors contributing to endothelial dysfunction as well. Traditional vascular risk factors, PD characteristics, and PD medication were considered.

Main text

Methods

Study subjects were recruited from patients attending an Outpatient Clinic of the 1st Department of Neurology and the 2nd Department of Neurology, University Hospital in Bratislava, Slovakia. PD patients fulfilled the UK Brain Bank Criteria for idiopathic Parkinson’s disease. Patients with clinical signs of vascular parkinsonism, parkinsonian plus syndromes, and PD dementia were excluded [18, 19]. Clinical and demographic characteristics including age, sex, body mass index (BMI), medical history, duration of disease, and PD medication were recorded. The modified Hoehn–Yahr scale (H&Y) was used for staging PD while patients were in the ‘‘on’’ state [20]. The control population consisted of patients without PD, who were recruited from participants of our previous studies [21, 22]. Controls matched to the PD patients by age, sex, and traditional vascular risk factors (including the history of hypertension, diabetes mellitus, coronary heart disease, dyslipidemia, and smoking habit). Our study was approved by the Institutional Review Boards and patients provided informed consent before testing.

EF was assessed using PAT (EndoPAT 2000 device, Itamar Medical, Caesarea, Israel) and expressed as a reperfusion hyperemia index (RHI) as previously described [21]. The values of RHI below 1.67 were considered as ED [23].

The statistical analyses were performed using SPSS version 25 (SPSS Inc., Chicago, USA). Continuous variables were expressed as means ± standard deviation or median, interquartile range (IQR), minimal and maximal values, categorical variables as numbers, and proportions (%). To compare groups, Student's t-test, Mann–Whitney test, and Chi-squared test were used for particular variables. Pearson or Spearman correlation coefficients were used to determine the relationships between RHI and baseline characteristics. Stepwise multiple linear regression was used to create the prediction model and identify the most important contributors to this model. A model including the highest number of significant predictors was chosen. The dependent variable in the model was RHI. In the model, we included the following baseline characteristics as independent variables: age, gender, BMI, presence of arterial hypertension, coronary artery disease, diabetes mellitus, dyslipidemia, smoking, orthostatic hypotension, H&Y, duration of PD, use of l-dopa, levodopa equivalent dose (LED), use of catechol-O-methyl transferase (COMT) inhibitors, dopamine agonists, monoamine oxidase B (MAO-B) inhibitors, and use of amantadine. Each model was assessed for the presence of multicollinearity of included variables. Variance inflation factors (VIF) ≥ 5 were indicative of multicollinearity. P values < 0.05 were considered statistically significant.

Results

The study population consisted of 41 PD patients and 41 controls matched for age, sex, BMI, and traditional vascular risk factors. Characteristics of the studied subjects are shown in Table 1. RHI was non-significantly lower in the PD group than in controls (1.8 ± 0.5 vs. 1.9 ± 0.5, p = 0.478). Presence of ED was more frequent (but not significant) in PD patients compared to controls (46.3% vs. 34.1%, p = 0.260).

Table 1 Characteristics of the study population
Full size table

In PD patients, we failed to find any significant correlation of RHI with age, BMI, H&Y, duration of the disease or LED, see Table 2. Similarly, among PD patients, RHI did not significantly differ between males and females (1.8 ± 0.5 vs. 1.8 ± 0.6, p = 0.700), in subjects with hypertension (1.7 ± 0.5 vs. 1.8 ± 0.6, p = 0.545), coronary artery disease (1.6 ± 0.5 vs. 1.8 ± 0.5, p = 0.450), diabetes mellitus (1.9 ± 0.6 vs. 1.8 ± 0.5, p = 0.605), dyslipidemia (1.5 ± 0.6 vs. 1.8 ± 0.5, p = 0.148), smoking habit (1.4 ± 0.4 vs. 1.8 ± 0.5, p = 0.084). No significant difference was found in subjects with postural hypotension (1.5 ± 0.4 vs. 1.8 ± 0.5, p = 0.149), using L-dopa (1.8 ± 0.5 vs. 1.6 ± 0.6, p = 0.327), dopamine agonists (1.7 ± 0.6 vs. 1.9 ± 0.5, p = 0.208), COMT inhibitors (1.9 ± 0.5 vs. 1.7 ± 0.6, p = 0.433), MAO-B inhibitors (1.9 ± 0.6 vs. 1.7 ± 0.5, p = 0.444), and amantadine (1.7 ± 0.7 vs. 1.8 ± 0.5, p = 0.533).

Table 2 Correlations between reperfusion hyperemia index (RHI) and baseline characteristics of the PD subjects
Full size table

In PD patients, the model predicting RHI in stepwise multiple linear regression analysis had R2 = 0.255, p = 0.030. Smoking (beta = −0.453, p = 0.008) and use of dopamine agonist (beta = −0.365, p = 0.030) were significant contributors in this model. VIF of all variables assessed in this model were ˂ 5.

Discussion

Our data suggest no significant ED in patients with PD when compared to controls matched for traditional vascular risk factors. Values of RHI in the PD group were non-significantly lower than in controls and ED was non-significantly more frequent in PD patients compared to controls. In PD patients, according to linear regression analysis, smoking and the use of dopamine agonists were significant contributors in the model predicting RHI.

ED is an initial process and a key component of atherogenesis [10]. To the best of our knowledge, there have been only two previous studies regarding the EF in PD patients and controls, both using flow-mediated dilation (FMD). Our study is the first that used peripheral arterial tonometry (PAT). Our results are consistent with FMD studies, showing lower RHI in PD subjects compared to controls [11, 12].

Several possible mechanisms are explaining the impairment of EF in PD. l-dopa therapy exhibits increased levels of homocysteine that is considered a modest independent risk factor for vascular disease, causing endothelial damage and atherogenesis [15, 24]. Yoon et al. concluded that EF, as assessed by the FMD, may be associated with chronic l-dopa treatment in patients with PD [11]. Our results suggest no significant association between RHI and l-dopa treatment. Absence of the homocysteine testing is a limitation of our study. However, it is not clear whether hyperhomocysteinemia is a cause or just an epiphenomenon of ED [25]. Similarly, elevated plasma homocysteine was found in PD patients, particularly in those under l-dopa treatment, and there was no correlation between homocysteine and certain markers of endothelial dysfunction [26].

Dopamine agonists can be also involved in the process of atherogenesis. Their use could be associated with cardiovascular complications including heart failure and orthostatic hypotension (OH) [16]. Patients with OH can develop supine hypertension and fluctuations in blood pressure associated with OH can also contribute to atherogenesis [27]. Repeated bouts of hypertension and non-dipping patterns of hypertension may lead to shear stress and consequent endothelial damage [28, 29]. Also in prospective studies, the presence of OH was associated with an increased risk of subsequent vascular disease [30, 31]. The use of dopamine agonists is also associated with significant elevations in systolic blood pressure and heart rate, which can be involved in the development of ED [16]. Our results suggest that the use of dopamine agonists belongs among significant contributors in a model predicting RHI. OH was non-significantly more frequent in subjects using dopamine agonists compared to the rest of PD patients (24% vs. 12.5%, p = 0.365). However, potential mechanisms linking the use of dopamine agonists in PD patients should be elucidated by future prospective studies.

Except for dopamine agonists, smoking was another significant contributor in the model predicting RHI. The association of smoking with atherosclerosis is well-known and smoking belongs among traditional vascular risk factors [14].

Despite no significant difference in EF between PD patients and controls, pathomechanisms underlying PD could be also involved in atherogenesis. Oxidative stress is a well-known phenomenon associated with pathogenic mechanisms of several diseases including atherosclerosis, neurodegenerative disorders, and aging processes [32]. Both PD and atherosclerosis possibly share multiple underlying pathomechanisms including mitochondrial dysfunction and oxidative stress. Several substances affecting these mechanisms (including Mucuna pruriens, ursolic acid, and chlorogenic acid) demonstrated the neuroprotective effect in the Parkinsonian mice model [33,34,35]. However, future studies are needed to demonstrate the atheroprotective effect of such substances.

Conclusion

Our data suggest no significant impairment of EF in PD patients compared to controls matched by age, sex, and traditional vascular risk factors. However, our study included “real world” PD patients suffering from multiple comorbidities. The Association of PD with ED should be explored more closely in populations with a lower burden of vascular risk factors to elucidate possible links between neurodegeneration and atherosclerosis. It could also help to explore the potential atherogenic effects of PD medications.

Limitations

Except for the relatively small sample size, we have to admit several other limitations. Impairment of EF in PD patients can be influenced by multiple other underlying mechanisms, including traditional and non-traditional vascular risk factors. Smoking, a well-known traditional risk factor, was identified as a significant contributor in a model predicting RHI in this study. However, several non-traditional risk factors could be also involved in atherogenesis in the PD population. Physical inactivity, sleep disorders, or even vitamin D deficiency are common in PD patients and all of them can be associated with atherogenesis [12, 21, 36, 37]. The lack of search for non-traditional risk factors, including atherogenic amino acids testing, belongs to the limitations of a current study, and their role should be considered in future studies.

Availability of data and materials

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

Abbreviations

COMT:

Catechol-O-methyl transferase

ED:

Endothelial dysfunction

FMD:

Flow-mediated dilation

H&Y:

Hoehn–Yahr scale

IMT:

Carotid intima-media thickness

IQR:

Interquartile range

LED:

Levodopa equivalent dose

MAO-B:

Monoamine oxidase B

OH:

Orthostatic hypotension

PAT:

Peripheral arterial tonometry

PD:

Parkinson’s disease

RHI:

Reperfusion hyperemia index

VIF:

Variance inflation factors

References

  1. Raza C, Anjum R, Shakeel NUA. Parkinson’s disease: mechanisms, translational models and management strategies. Life Sci. 2019;226:77–90. https://doi.org/10.1016/j.lfs.2019.03.057.

    CAS  Article  PubMed  Google Scholar 

  2. Perju-Dumbrava L, Muntean ML, Muresanu DF. Cerebrovascular profile assessment in Parkinson’s disease patients. CNS Neurol Disord Drug Targets. 2014;13(4):712–7.

    CAS  Article  Google Scholar 

  3. Gorell JM, Johnson CC, Rybicki BA. Parkinson’s disease and its comorbid disorders: an analysis of Michigan mortality data, 1970 to 1990. Neurology. 1994;44(10):1865–8.

    CAS  Article  Google Scholar 

  4. Jellinger KA. Prevalence of cerebrovascular lesions in Parkinson’s disease. A postmortem study. Acta Neuropathol. 2003;105(5):415–9.

    Article  Google Scholar 

  5. Nataraj A, Rajput AH. Parkinson’s disease, stroke, and related epidemiology. Mov Disord. 2005;20(11):1476–80.

    Article  Google Scholar 

  6. Scigliano G, Musicco M, Soliveri P, Piccolo I, Ronchetti G, Girotti F. Reduced risk factors for vascular disorders in Parkinson disease patients: a case-control study. Stroke. 2006;37(5):1184–8.

    Article  Google Scholar 

  7. Lee JM, Park KW, Seo WK, Park MH, Han C, Jo I, et al. Carotid intima-media thickness in Parkinson’s disease. Mov Disord. 2007;22(16):2446–9.

    Article  Google Scholar 

  8. Alexa D, Constantinescu A, Baltag D, Ignat B, Bolbocean O, Popescu CD. Parkinson’s disease and carotid intima-media thickness. Rev Med Chir Soc Med Nat Iasi. 2014;118(1):52–6.

    CAS  PubMed  Google Scholar 

  9. Nakaso K, Yasui K, Kowa H, Kusumi M, Ueda K, Yoshimoto Y, et al. Hypertrophy of IMC of carotid artery in Parkinson’s disease is associated with L-DOPA, homocysteine, and MTHFR genotype. J Neurol Sci. 2003;207(1–2):19–23.

    CAS  Article  Google Scholar 

  10. Bonetti PO, Lerman LO, Lerman A. Endothelial dysfunction: a marker of atherosclerotic risk. Arterioscler Thromb Vasc Biol. 2003;23(2):168–75. https://doi.org/10.1161/01.atv.0000051384.43104.fc.

    CAS  Article  PubMed  Google Scholar 

  11. Yoon JH, Lee JS, Yong SW, Hong JM, Lee PH. Endothelial dysfunction and hyperhomocysteinemia in Parkinson’s disease: flow-mediated dilation study. Mov Disord. 2014;29(12):1551–5.

    CAS  Article  Google Scholar 

  12. Yoon JH, Park DK, Yong SW, Hong JM. Vitamin D deficiency and its relationship with endothelial dysfunction in patients with early Parkinson’s disease. J Neural Transm (Vienna). 2015;122(12):1685–91.

    CAS  Article  Google Scholar 

  13. Victor VM, Apostolova N, Herance R, Hernandez-Mijares A, Rocha M. Oxidative stress and mitochondrial dysfunction in atherosclerosis: mitochondria-targeted antioxidants as potential therapy. Curr Med Chem. 2009;16(35):4654–67. https://doi.org/10.2174/092986709789878265.

    CAS  Article  PubMed  Google Scholar 

  14. Lechner K, von Schacky C, McKenzie AL, Worm N, Nixdorff U, Lechner B, et al. Lifestyle factors and high-risk atherosclerosis: pathways and mechanisms beyond traditional risk factors. Eur J Prev Cardiol. 2020;27(4):394–406. https://doi.org/10.1177/2047487319869400.

    Article  PubMed  Google Scholar 

  15. Vermeer SE, van Dijk EJ, Koudstaal PJ, Oudkerk M, Hofman A, Clarke R, et al. Homocysteine, silent brain infarcts, and white matter lesions: The Rotterdam Scan Study. Ann Neurol. 2002;51(3):285–9.

    CAS  Article  Google Scholar 

  16. Abou Farha K, Balje-Volkers C, Tamminga W, den Daas I, van Os S. Dopamine D2R agonist-induced cardiovascular effects in healthy male subjects: potential implications in clinical settings. ISRN Neurol. 2014;2014: 956353. https://doi.org/10.1155/2014/956353.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  17. Xu Y, Arora RC, Hiebert BM, Lerner B, Szwajcer A, McDonald K, et al. Non-invasive endothelial function testing and the risk of adverse outcomes: a systematic review and meta-analysis. Eur Heart J Cardiovasc Imaging. 2014;15(7):736–46. https://doi.org/10.1093/ehjci/jet256.

    Article  PubMed  Google Scholar 

  18. Gibb WR, Lees AJ. The relevance of the Lewy body to the pathogenesis of idiopathic Parkinson’s disease. J Neurol Neurosurg Psychiatry. 1988;51(6):745–52.

    CAS  Article  Google Scholar 

  19. Rektor I, Rektorova I, Kubova D. Vascular parkinsonism–an update. J Neurol Sci. 2006;248(1–2):185–91.

    Article  Google Scholar 

  20. Hoehn MM, Yahr MD. Parkinsonism: onset, progression and mortality. Neurology. 2001;57:S11.

    CAS  PubMed  Google Scholar 

  21. Siarnik P, Carnicka Z, Krizova L, Wagnerova H, Sutovsky S, Klobucnikova K, et al. Predictors of impaired endothelial function in obstructive sleep apnea syndrome. Neuro Endocrinol Lett. 2014;35(2):142–8.

    CAS  PubMed  Google Scholar 

  22. Kemenyova P, Siarnik P, Sutovsky S, Blaho A, Turcani P, Kollar B. Impairment of endothelial function in patients with multiple sclerosis. Neuro Endocrinol Lett. 2015;36(1):67–71.

    CAS  PubMed  Google Scholar 

  23. Syvänen K, Korhonen P, Partanen A, Aarnio P. Endothelial function in a cardiovascular risk population with borderline ankle-brachial index. Vasc Health Risk Manag. 2011;7:97–101. https://doi.org/10.2147/vhrm.s17249.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Chambers JC, Seddon MD, Shah S, Kooner JS. Homocysteine—a novel risk factor for vascular disease. J R Soc Med. 2001;94(1):10–3.

    CAS  Article  Google Scholar 

  25. Linnebank M, Moskau S, Farmand S, Fliessbach K, Kolsch H, Bos M, et al. Homocysteine and carotid intima-media thickness in a german population: lack of clinical relevance. Stroke. 2006;37(11):2840–2.

    CAS  Article  Google Scholar 

  26. Bostantjopoulou S, Katsarou Z, Frangia T, Hatzizisi O, Papazisis K, Kyriazis G, et al. Endothelial function markers in parkinsonian patients with hyperhomocysteinemia. J Clin Neurosci. 2005;12(6):669–72.

    CAS  Article  Google Scholar 

  27. Morley JF, Duda JE. Parkinson’s disease and the risk of cerebrovascular pathology. Mov Disord. 2012;27(12):1471–2.

    Article  Google Scholar 

  28. Boyd GW. Stress and disease: the missing link. A vasospastic theory. II. The nature of degenerative arterial disease. Med Hypotheses. 1978;4(5):420–31.

    CAS  Article  Google Scholar 

  29. Johansson BB. Hypertension mechanisms causing stroke. Clin Exp Pharmacol Physiol. 1999;26(7):563–5.

    CAS  Article  Google Scholar 

  30. Eigenbrodt ML, Rose KM, Couper DJ, Arnett DK, Smith R, Jones D. Orthostatic hypotension as a risk factor for stroke: the atherosclerosis risk in communities (ARIC) study, 1987–1996. Stroke. 2000;31(10):2307–13.

    CAS  Article  Google Scholar 

  31. Rose KM, Tyroler HA, Nardo CJ, Arnett DK, Light KC, Rosamond W, et al. Orthostatic hypotension and the incidence of coronary heart disease: the Atherosclerosis Risk in Communities study. Am J Hypertens. 2000;13(6):571–8.

    CAS  Article  Google Scholar 

  32. Durackova Z. Some current insights into oxidative stress. Physiol Res. 2010;59(4):459–69.

    CAS  Article  Google Scholar 

  33. Yadav SK, Rai SN, Singh SP. Mucuna pruriens reduces inducible nitric oxide synthase expression in Parkinsonian mice model. J Chem Neuroanat. 2017;80:1–10. https://doi.org/10.1016/j.jchemneu.2016.11.009.

    CAS  Article  PubMed  Google Scholar 

  34. Rai SN, Zahra W, Singh SS, Birla H, Keswani C, Dilnashin H, et al. Anti-inflammatory activity of ursolic acid in MPTP-induced parkinsonian mouse model. Neurotox Res. 2019;36(3):452–62. https://doi.org/10.1007/s12640-019-00038-6.

    CAS  Article  PubMed  Google Scholar 

  35. Singh SS, Rai SN, Birla H, Zahra W, Rathore AS, Dilnashin H, et al. Neuroprotective effect of chlorogenic acid on mitochondrial dysfunction-mediated apoptotic death of DA neurons in a Parkinsonian mouse model. Oxid Med Cell Longev. 2020;2020:6571484. https://doi.org/10.1155/2020/6571484.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  36. Leoni LA, Fukushima AR, Rocha LY, Maifrino LB, Rodrigues B. Physical activity on endothelial and erectile dysfunction: a literature review. Aging Male. 2014;17(3):125–30. https://doi.org/10.3109/13685538.2014.923836.

    Article  PubMed  Google Scholar 

  37. Cochen De Cock V, Benard-Serre N, Driss V, Granier M, Charif M, Carlander B, et al. Supine sleep and obstructive sleep apnea syndrome in Parkinson’s disease. Sleep Med. 2015;16(12):1497–501.

    Article  Google Scholar 

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Acknowledgements

Not applicable.

Funding

This work was supported by the Framework Programme for Research and Technology Development, Project: Building of Centre of Excellency for Sudden Cerebral Vascular Events, Comenius University Faculty of Medicine in Bratislava (ITMS:26240120023), co-financed by the European Regional Development Fund and by APVV-15-0253 Grant.

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Authors and Affiliations

  1. 1st Department of Neurology, Faculty of Medicine, Comenius University, Mickiewiczova 13, 813 69, Bratislava, Slovakia

    Branislav Kollár, Katarína Valovičová, Peter Turčáni & Pavel Šiarnik

  2. AB Neuro, Jilemnickeho 547/10, 911 01, Trencin, Slovakia

    Andrej Blaho

  3. Department of Neurology, General Hospital, Palucanska 25, 031 23, Liptovsky Mikulas, Slovakia

    Michal Poddaný

  4. 2nd Department of Neurology, Faculty of Medicine, Comenius University, Limbova 5, 83305, Bratislava, Slovakia

    Peter Valkovič & Igor Straka

  5. Institute of Normal and Pathological Physiology, Centre of Experimental Medicine, Slovak Academy of Sciences, Sienkiewiczova 1, 813 71, Bratislava, Slovakia

    Peter Valkovič

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Contributions

(1) Research project: A. Conception: PŠ, BK; B. Organization: BK, PŠ; C. Execution: AB, PŠ, MP, PV, IS; (2) Statistical Analysis: PŠ, KV; (3) Manuscript: A. Writing of the first draft: BK, PŠ; B. Review and Critique: PT, IS, PV. All authors read and approved the final manuscript.

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Correspondence to Pavel Šiarnik.

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All procedures performed in the study were in accordance with the 1964 Helsinki declaration and its later amendments or comparable ethical standards. The study was approved by the Ethics Committee of the Faculty of Medicine, Comenius University, and the University Hospital in Bratislava (Old Town Hospital), and written informed consent was obtained from all individual participants included in the study before the enrollment.

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Kollár, B., Blaho, A., Valovičová, K. et al. Impairment of endothelial function in Parkinson’s disease. BMC Res Notes 15, 284 (2022). https://doi.org/10.1186/s13104-022-06176-z

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Keywords

  • Atherosclerosis
  • Dopamine agonist
  • Endothelial function
  • Parkinson’s disease

BMC Research Notes

ISSN: 1756-0500

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