|Year : 2017 | Volume
| Issue : 4 | Page : 115-118
Association of serum fibroblast growth factor-23 with conventional cardiovascular risk factors in hemodialysis patients
Walaa H Mohammad1, Ahmad Bahie Elden Ahmad2, Noha G Sayed3
1 Department of Internal Medicine and Nephrology, Nephrology Unit, Assiut University Hospital, Assiut, Egypt
2 Department of Internal Medicine and Cardiology, Cardiology and Critical Care Unit, Assiut University Hospital, Assiut, Egypt
3 Department of Clinical Pathology, South Oncology Institute, Assiut, Egypt
|Date of Submission||18-Oct-2017|
|Date of Acceptance||12-Nov-2017|
|Date of Web Publication||17-Jan-2018|
Dr. Walaa H Mohammad
MD in Internal Medicine, Department of Internal Medicine and Nephrology, Nephrology Unit, Assiut University Hospital, Assiut, 71515
Source of Support: None, Conflict of Interest: None
Objectives We aimed to study the association of fibroblast growth factor-23 (FGF-23) with conventional cardiovascular risk factors in hemodialysis (HD) patients.
Patients and methods This is a cross-sectional study, which was carried out on 90 HD patients. Demographic data were recorded in predefined data sheets. The blood samples for FGF-23 and other laboratory variables were collected and measured using the standard methods. The results and their relationships with FGF-23 were analyzed.
Results In our study, there were insignificant correlations between FGF-23 and all clinical cardiovascular variables apart from a significant positive correlation between FGF-23 and systolic blood pressure (r=−0.546, P=0.004). Multivariate analysis failed to show any significant association between FGF-23 and systolic blood pressure (B=0.749, T=1.659, P=0.067).
Conclusion Multiple linear regression analysis failed to show any significant association between FGF-23 and other conventional cardiovascular risk factors. We recommend using FGF-23 as an independent risk factor of cardiovascular morbidity and mortality, and searching for agents that control its level in HD patients.
Keywords: cardiovascular risk factors, fibroblast growth factor-23, hemodialysis, metabolic indices
|How to cite this article:|
Mohammad WH, Elden Ahmad AB, Sayed NG. Association of serum fibroblast growth factor-23 with conventional cardiovascular risk factors in hemodialysis patients. J Egypt Soc Nephrol Transplant 2017;17:115-8
|How to cite this URL:|
Mohammad WH, Elden Ahmad AB, Sayed NG. Association of serum fibroblast growth factor-23 with conventional cardiovascular risk factors in hemodialysis patients. J Egypt Soc Nephrol Transplant [serial online] 2017 [cited 2020 Feb 28];17:115-8. Available from: http://www.jesnt.eg.net/text.asp?2017/17/4/115/223414
| Introduction|| |
Bone cells secrete fibroblast growth factor-23 (FGF-23) to control phosphate and vitamin D metabolism. High levels of FGF-23 are associated with increased CV events , vascular calcification , left ventricular hypertrophy , arterial stiffness, endothelial dysfunction , and levels of inflammatory markers , suggesting that FGF-23 plays physiologic roles other than the regulation of bone-mineral metabolism, and can serve as a cardiovascular (CV) biomarker in chronic kidney disease (CKD) and stimulates interest in exploring the potential association between FGF-23 and other conventional cardiovascular (CCV) risk factors. The FGF-23 association with CV mortality and morbidity could be because of its association with other traditional risk factors. We aimed to study the association between FGF-23 and other CCV risk in HD patients, to test its independency as a novel CV risk factor.
| Patients and methods|| |
We carried out a cross-sectional study, carried out on 90 patients who undergo regular HD in the Nephrology Unite of Assiut University Hospital in 2016. Written consents were obtained from participants; illiterate participants provided their consent by fingerprints. The study was approved by the ethical committee of college of medicine in Assiut University. Patients’ demographic information and medical history including age, sex, BMI, history of smoking, hypertension, diabetes, hyperlipidemia, and drug history were recorded. Blood pressure of the patients was recorded. Venous blood samples were collected from our patients after dialysis sessions and analyzed in the Nephrology Unite Laboratory. The blood samples for FGF-23 were centrifuged, separated, and frozen immediately after collection and assessed using the ELISA method. Other laboratory measurements including serum levels of creatinine, blood urea nitrogen, triglyceride, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol, fasting blood glucose, serum levels of calcium, phosphorous, alkaline phosphatase, intact parathyroid hormone, 25-hydroxyvitamin D level, uric acid, and albumin were measured using standard kits.
The statistical analysis was carried out using SPSS (version 19.0; SPSS Inc., Chicago, Illinois, USA). The Kolmogorov–Smirnov test was used to test normality. Continuous variables were presented as the mean±SD, whereas categorical variables were reported as percentages. Spearman’s correlation was done to measure correlation among quantitative variables. Multivariate analysis was carried out to test the association between FGF-23 as an independent variable and other conventional CV risk factors as dependent variables. A P value less than 0.05 was considered statistically significant.
| Results|| |
The study was carried out on 90 regular HD patients. The mean age of our patients was 43.30±12.40 years, the mean BMI was 23.55±3.62 kg/m2, and the mean duration of dialysis was 5.46±4.17 years ([Table 1]).
The mean FGF-23 in our sample was 43.08±35.58 pg/ml. Other laboratory data are shown in [Table 1].
[Table 2] shows the association between FGF-23 and various clinical and laboratory parameters. Briefly, there were insignificant correlations between FGF-23 and all clinical CV risk factors, except for a significant positive correlation between FGF-23 and systolic blood pressure (BP) (r=−0.546, P=0.004), but not with diastolic BP. All laboratory variables including lipid profile, bone-mineral variables, serum electrolyte, and hemoglobin, and iron metabolic profile showed insignificant correlations with FGF-23.
|Table 2 Correlation of fibroblast growth factor-23 and conventional cardiovascular risk factors|
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[Table 3] shows the multiple linear regression analysis models that failed to show any association between FGF-23 and any of the CCV risk factors.
| Discussion|| |
CKD and end-stage renal disease (ESRD) patients have several CCV risk factors . Also, the decline in glomerular filtration rate is a strong and independent predictor of CV events and death in these patients . The adverse outcomes and mortality in ESRD patients have been associated with elevated FGF-23 levels . However, the underlying mechanism of that association is still not understood. Our current study attempted to test the interaction of FGF-23 level and other CCV risk factors aiming to explore the underlying mechanisms of FGF-23 association with mortality in ESRD patients. Clinical studies testing the association FGF-23 with CVD in patients with normal renal function showed a positive correlation between FGF-23 and metabolic syndrome , triglyceride and total cholesterol , and all-cause mortality, but not with incident CVD . Clinical study in nondialysis CKD patients showed a positive correlation between FGF-23 and blood pressure and serum albumin .
The FGF-23 association with CV mortality and morbidity could be because of its association with other traditional risk factors. Our aim was to test the independency of FGF-23 as a novel CV risk factor. Apart from systolic BP, we found insignificant correlations between FGF-23 and all other CV risk factors. The mechanisms that could explain the association between FGF-23 and systolic BP include FGF-23 suppression of vitamin D metabolism with the subsequent release of renin–angiotensin–aldosterone system from inhibition , FGF-23 suppression of angiotensin-converting enzyme-2 expression in the kidneys , and FGF-23 augmentation of renal Na+ reabsorption in CKD .
However, our multivariate analysis model failed to show any association between FGF-23 and any of the CCV risk factors. This finding might highlight the unique interaction of FGF-23 and other CV risk factors in HD patients. Moreover, some clinical studies showed that some CCV risk factors such as African–American race, hypertension, hypercholesterolemia, and obesity are paradoxically associated with better outcomes in CKD and ESRD patients ,, and other few trials targeting modification of the conventional CV risk factors have yielded disappointing results in these patients ,.
| Conclusion|| |
In our study, there was a significant correlation between FGF-23 and systolic BP. However, multivariate analysis failed to show any significant association between FGF-23 and any of the CCV risk factors.
Study limitations and recommendations
Our study had some limitations; first, financial constraints interfered with the recruitment of more patients to increase our study power and lower type II error. Second, our study was monoethnic cross-sectional with no control group and we suggest carrying out a multiethnic case–control study for better assessment of the role of FGF-23in HD patients. We recommend using FGF-23 as an independent CV risk factor, and we recommend searching for agents that control its level in HD patients to decrease CV morbidity and mortality in these patients.
The authors would like to thank the workers and nursing stuff of Nephrology Unit of Internal Medicine Department at Assiut University Hospitals for their support of this study. They also thank the technicians in the labs of South Egypt Oncology Institute for their work.
The manuscript has been read and approved by all the authors, the requirements for authorship have been met, and each author believes that the manuscript represents honest work.
Financial support and sponsorship
The authors acknowledge Research Grant Office in Faculty of Medicine, Assiut University, for their financial support of the research.
Conflicts of interest
There are no conflicts of interest.
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[Table 1], [Table 2], [Table 3]