Next Article in Journal
Exploring Porcine Precision-Cut Kidney Slices as a Model for Transplant-Related Ischemia-Reperfusion Injury
Next Article in Special Issue
Updated Pathways in Cardiorenal Continuum after Kidney Transplantation
Previous Article in Journal / Special Issue
Kidney Re-Transplantation after Simultaneous Heart and Kidney Transplant: Case Study and Literature Review
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Nutritional Predictors of Cardiovascular Risk in Patients after Kidney Transplantation-Pilot Study

by
Sylwia Czaja-Stolc
1,
Paulina Wołoszyk
2,
Sylwia Małgorzewicz
1,3,*,
Andrzej Chamienia
2,3,
Michał Chmielewski
3,
Zbigniew Heleniak
3 and
Alicja Dębska-Ślizień
3
1
Department of Clinical Nutrition, Gdańsk Medical University, 80-211 Gdańsk, Poland
2
Department of Internal and Paediatric Nursing, Gdańsk Medical University, 80-211 Gdańsk, Poland
3
Department of Nephrology, Transplantology and Internal Diseases, Gdańsk Medical University, 80-211 Gdańsk, Poland
*
Author to whom correspondence should be addressed.
Transplantology 2022, 3(2), 130-138; https://doi.org/10.3390/transplantology3020014
Submission received: 23 February 2022 / Revised: 26 March 2022 / Accepted: 11 April 2022 / Published: 18 April 2022
(This article belongs to the Special Issue Advances in Cardiovascular Complications After Renal Transplantation)

Abstract

:
Asymmetric dimethylarginine (ADMA) is a marker of endothelial damage. Research confirms the association of ADMA with an increased cardiovascular risk (CVR) among kidney transplant recipients (KTRs). Additionally, increased circulating levels of fibroblast growth factor 23 (FGF-23) are associated with pathological cardiac remodeling and vascular alterations. The aim of the study is the analysis of the relationship between ADMA, FGF-23, nutritional, biochemical parameters in healthy subjects and KTRs. 46 KTRs and 23 healthy volunteers at mean age of 50.8 ± 15.4 and 62.5 ± 10.7 years were enrolled. The anthropometric and biochemical parameters such as ADMA, FGF-23, albumin, prealbumin were assessed. Fat tissue mass among KTRs was 30.28 ± 9.73%, lean body mass 64.5 ± 14.8%. Overweight and obesity was presented by 65.2% of recipients. Albumin level was 38.54 ± 3.80 g/L, prealbumin 27.83 ± 7.30 mg/dL and were significantly lower than in the control (p < 0.05). Patients with ADMA > 0.66 µmol/L had a lower concentration of prealbumin, albumin and increased concentration of oxidized low density lipoprotein (oxLDL), high sensitive C-reactive protein (hsCRP) and FGF-23. FGF-23 was significantly higher in patients with higher hsCRP (p < 0.05). KTRs with elevated ADMA had a longer transplantation vintage, lower eGFR and higher albuminuria. Diabetes mellitus (DM) was associated with higher levels of ADMA and FGF-23. Even in stable KTRs a relationship between inflammatory state, nutritional status, graft function and endothelial dysfunction biomarkers was observed.

1. Introduction

The epidemics of overweight, obesity, diabetes mellitus (DM) and hypertension increase the risk of developing chronic kidney disease (CKD). According to Hill et al.’s meta-analysis from 2016, the worldwide CKD prevalence of stage 3–5 was 10.6% [1]. Unfortunately, many patients go undiagnosed and find out about the disease shortly before end-stage kidney disease (ESKD) when the renal replacement therapy (RRT) is required. RRT includes dialysis and kidney transplantation (KT), which is more effective. Kidney transplant recipients (KTRs) have a better quality of life and their prognosis is better compared to dialysis patients; however, compared to healthy people, KTRs have a three- to five-fold higher cardiovascular risk (CVR) [2,3,4,5]. It has been estimated that a 20-year-old healthy European will live for another 62 years, but KTRs only 44 years. The main cause of death in KTRs is cardiovascular disease (CVD), which results from the presence of traditional and non-traditional risk factors [6,7,8]. Traditional risk factors, that also apply to the general population, include, e.g., lipid disorders, obesity, DM, hypertension, hyperhomocysteinaemia and smoking. Non-traditional risk factors include, e.g., inflammation, oxidative stress, uremic toxins, disturbances of calcium-phosphorus levels, disorders of nutritional status, lipoprotein (a) and asymmetric dimethylarginine (ADMA). Similar risk factors exist in dialysis patients, but their severity is much greater. The risk of CVD in a dialysis patient who has undergone a successful transplant is significantly reduced, but not as low as in healthy subjects. CVR among KTRs is also influenced by the use of immunosuppressants, glucocorticosteroids and CKD progression [9,10,11].
Endothelial dysfunction (ED) is a major cause of CVD development. One of the mechanisms of ED is a defect in nitric oxide (NO) production [12]. ADMA is an endogenous inhibitor of endothelial nitric oxide synthase, a marker of endothelial damage and progression of atherosclerosis. Research confirms the association of ADMA with an increased risk of cardiac complications and an increased risk of death and graft loss among KTRs [13,14,15]. Additionally, CKD-mediated increased circulating levels of fibroblast growth factor 23 (FGF-23) are associated with pathological cardiac remodeling and vascular alterations. In addition, FGF-23 is independently associated with all-cause mortality. KT reduces FGF-23 levels, but the values are not as low as in healthy subjects. ADMA and FGF-23 levels can be associated with nutritional status [16,17], while obesity negatively affects graft survival and CVR [18,19].
CVD is the main cause of death in KTRs. Therefore, it is necessary to know the risk factors, which may allow for the introduction of modern treatment therapies in the future. The primary outcome of our study is finding risk factors for increased ADMA and FGF-23 concentration in the stable KTRs.
The aim of its study is the analysis of the relationship between ADMA, FGF-23, nutritional, biochemical parameters in KTRs and healthy subjects. The purpose of the research is also to compare KTRs with different levels of ADMA and with DM.

2. Materials and Methods

2.1. Study Participants

The study group consisted of clinically stable KTRs (26 men; mean age 50.8 ± 15.4 years). The transplantation vintage was 69.0 (median 51.0) months. None of the patients experienced any surgical or infectious complications related to the KT. There was also no allograft rejection. All patients were under care in the Outpatient Transplantation Unit at the Department of Nephrology, Transplantology and Internal Disease, Medical University of Gdansk, Poland and were treated with triple immunosuppressive therapy (glucocorticosteroids, calcineurin inhibitor, mycophenolate mofetil). The control group consisted of 23 healthy volunteers (8 men; mean age 62.5 ± 10.7 years). Other clinical data were based on the medical records. This study was approved by Independent Bioethics Committee for Scientific Research at Medical University of Gdańsk (NKBBN/291-367/2020, NKBBN/291-437/2018). The clinical and research activities were consistent with the Principles of the Declaration of Istanbul, as outlined in the Declaration of Istanbul on Organ Trafficking and Transplant Tourism.

2.2. Biochemistry

Plasma samples were taken after an overnight fast and stored at −80 °C until analyzed. High sensitive C-reactive protein (hsCRP) was measured in serum by the enzyme-linked immunoassay (ELISA) method. ADMA, FGF-23 and oxidized low-density lipoprotein (oxLDL) were measured in plasma also by the ELISA method. Albumin (serum albumin), creatinine, blood urea nitrogen (BUN), sodium, potassium, magnesium, total cholesterol and blood morphology were measured by routine laboratory methods.

2.3. Anthropometric Measurements and Nutritional Status

Body mass and height were assessed. Body Mass Index (BMI) was calculated according to the current body mass/height2 (kg/m2) and classified as: <18.5–underweight, 18.5–24.99–normal weight, 25–29, 99–overweight and ≥30–obesity. For the evaluation of body composition parameters such as lean tissue mass (LTM) and fat tissue mass (FAT), multi-frequency bioimpedance analysis (BIA) with Body Composition Monitor (BCM, Fresenius SA, Bad Homburg, Germany) was carried out. Nutritional status was assessed with the 7-points Subjective Global Assessment (SGA) and classified patients as well-nourished when they received 6–7 points, moderately/slightly malnourished when they had 4–5 points and malnourished when they had 1–3 points [20].

2.4. Statistical Analysis

Statistical analysis was performed using Statistica 13.3 version for Windows. All data are presented as mean ± SD or median. Comparisons of the groups were examined by Student’s t-test (for parametric data) and U Mann-Whitney Rank Sum Test (for non-parametric data). Spearman’s correlation was used for nonparametric measure of statistical dependence between two variables. Independent associations among variables were assessed with stepwise multiple regression analysis; it consisted of a constructing a model that includes all potential explanatory variables and then in the gradual elimination of variables so as to maintain the model with the highest value of the coefficient of determination while maintaining the significance of the parameters. For all performed analyses, p < 0.05 was considered statistically significant.

3. Results

The biochemical and anthropometric characteristics of the study and control group are presented in Table 1.

3.1. Anthropometry and Nutritional Status

In KTRs, group mean BMI was 26.25 ± 3.51, fat tissue mass 30.28 ± 9.73% and 22.51 ± 8.72 kg, LBM 64.5 ± 14.8%. Excessive body weight (BMI > 25) was presented by 65.2% of KTRs; 23.2% of KTRs presented obesity (Figure 1). In comparison to the control group, KTRs presented significantly higher contents of body fat.
Based on 7-point SGA, 39% of KTRs were moderately/slightly malnourished (Figure 2). 36.2% of moderately/slightly malnourished KTRs (with SGA ≤ 5) were overweight or obese.
Albumin level was 38.54 ± 3.80 g/L and prealbumin 27.83 ± 7.30 mg/dL and were significantly lower than in the control group (p < 0.05).

3.2. Markers of Endothelial Dysfunction and Inflammatory State

As presented in Table 1, the concentrations of ADMA, FGF-23 and hsCRP were significantly higher in KTRs in comparison to the control group. Patients with ADMA > 0.66 µmol/L had a lower concentration of prealbumin, albumin and increased concentration of oxLDL, hsCRP and FGF-23 (Table 2). However, KTRs with an elevated ADMA level had a longer transplantation vintage, lower eGFR and higher albuminuria.
Malnourished KTRs were significantly older and had a higher prevalence of DM (Table 3). Additionally, DM was associated with higher levels of ADMA and FGF-23 in comparison to KTRs without DM (Figure 3).
FGF-23 was significantly associated with hsCRP (correlation coefficient R Sperman = 0.4; p < 0.05) and were negatively correlated with eGFR (CKD EPI) (R Sperman = 0.5, p < 0.05; Figure 4).

3.3. Multivariate Regression Analysis

The multivariate regression model shows (Table 4) that the adjusted R2 of the model was 0.10; p < 0.02), the association between DM and high levels of ADMA and hsCRP, but not FGF-23 (dependent variable DM; independent variables hsCRP, ADMA, FGF-23).

4. Discussion

Although KT is the best method of RRT, KTRs have a higher CVR compared to healthy people. The presence of traditional risk factors does not explain the high mortality rate. For this reason, more and more attention is paid to non-traditional factors, such as nutritional status, calcium-phosphate metabolism, oxidative stress and chronic inflammation [3,9,11].
In this study, we assessed the relationship between ADMA, FGF-23, nutritional, and biochemical parameters among KTRs and in the control group. The nutritional status was evaluated by BMI, body composition and 7-point SGA. According to the results of our previous studies conducted in larger populations, many KTRs were overweight and obese [21,22]. Excessive body weight usually occurs in approximately 40% of KTRs [23], but in this study, almost two-thirds of the patients were overweight or obese. Moreover, KTRs presented significantly higher contents of body fat in comparison to healthy volunteers (30.28 ± 9.73 vs. 26.41 ± 6.7%). Obesity increases the risk of the deterioration of the graft function, e.g., by glomerular hyperfiltration, lipotoxicity, altered secretion from adipose tissue and also obesity increases CVR [24]. Despite excessive body weight, based on 7-point SGA, 36.2% of patients were moderately/slightly malnourished. Biochemical parameters of nutritional status such as albumin and prealbumin were significantly lower in the KTRs compared to the control group. Sezer et al. reported that, based on SGA, 23.4% of KTRs were moderately/slightly malnourished and 10.6% were malnourished [25].
ADMA is the product of proteolysis of proteins containing methylated arginine, which disrupts endothelial function by reducing the phosphorylation of arterial endothelial nitric oxide synthase (eNOS). It is a marker of endothelial damage, progression of atherosclerosis and its elevated levels are connected to CVR [13,15,26]. In this study, KTRs had a significantly higher concentration of ADMA and lower eGFR than healthy volunteers, which has also been observed in other studies [27]. Renal function impairment leads to an increase in plasma ADMA concentration due to disturbances in its urinary excretion [28]. KTRs were divided into two groups depending on ADMA concentration (ADMA ≤ 0.66 and > 0.66 µmol/L). This division was made on the basis of the study by Frenay et al. in which the risk of death was estimated at 686 KTRs. During 3 years of follow-up, 12% of patients died and 7% lost their graft function, defined as a new need for dialysis therapy or retransplantation. The highest risk of death was in the group of patients with ADMA > 0.66 µmol/L [29]. In this study, ADMA > 0.66 µmol/L, among transplant recipients, was associated with a lower eGFR, albumin, prealbumin levels and increased of oxLDL, hsCRP and FGF-23 concentration. DM was associated with higher ADMA levels. In our other study, ADMA was associated with the nutritional status of peritoneal dialysis patients [30]. There are no studies on the relationship between ADMA and nutritional status in patients after KT.
FGF-23 is a protein hormone secreted by osteocyte in response to 1.25(OH)2D3, parathyroid hormone (PTH) and elevated phosphate concentration. Inflammation probably also increases bone-released hormones. FGF-23 reduces renal phosphate reabsorption. The progression of CKD leads to an increase in the concentration of FGF-23 and in consequence to CVD development by vascular calcification. KT reduces FGF-23 levels, but the values are not as low as in healthy subjects, which we also observed in this study [17,31,32]. The control group had a significantly lower level of FGF-23 and hsCRP compared to KTRs (64.11 ± 18.58 vs. 115.71 ± 66.18). Asicioglu et al. also observed a similar dependence [33]. In our study, we observed the correlation between FGF-23 and eGFR. FGF-23 was significantly higher in patients with a higher hsCRP. FGF-23 is associated with all-cause and cardiovascular mortality among KTRs; therefore, it is classified as a non-traditional risk factor [16].
The limitation of our study is a small group of patients and control subjects, but despite its limitations, the results of the present study are valuable because they indicate a problem of occurrence non-traditional risk factors of CVD, also in patients after KT, such as inflammation and nutritional status.

5. Conclusions

Even in stable KTRs, a relationship between inflammatory state, nutritional status, graft function and endothelial dysfunction biomarkers was observed. Further studies in KTRs (e.g., multicenter) are needed to confirm our preliminary results.

Author Contributions

Conceptualization: S.M. and A.C.; methodology: M.C., S.M., A.C.; software, validation, formal analysis: P.W., S.M.; investigation: Z.H., resources: Z.H., data curation: P.W., A.C., A.D.-Ś.; writing—original draft preparation: S.C.-S., S.M., P.W.; writing—review and editing: M.C., A.C.; visualization: S.C.-S.; supervision: A.D.-Ś.; project administration: A.C.; funding acquisition: A.D.-Ś. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Independent Bioethics Committee for Scientific Research at Medical University of Gdańsk (NKBBN/291-367/2020, NKBBN/291-437/2018).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data are not publicly available due to patient privacy concerns.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Hill, N.R.; Fatoba, S.T.; Oke, J.L.; Hirst, J.A.; O’Collaghan, C.A.; Lasserson, D.S.; Hobbs, F.D. Global Prevalence of Chronic Kidney Disease—A Systematic Review and Meta-Analysis. PLoS ONE 2016, 11, 0158765. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  2. Yamada, Y.; Ikenoue, T.; Saito, Y.; Fukuma, S. Undiagnosed and untreated chronic kidney disease and its impact on renal outcomes in the Japanese middle-aged general population. J. Epidemiol. Community Health 2019, 73, 1122–1127. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Rangaswami, J.; OMathew, R.; Parasuraman, R.; Tantisattamo, E.; Lubetzky, M.; Rao, S.; Yaqub, M.S.; Birdwell, K.A.; Bennett, W.; Dalal, P.; et al. Cardiovascular disease in the kidney transplant recipient: Epidemiology, diagnosis and management strategies. Nephrol. Dial. Transplant. 2019, 34, 760–773. [Google Scholar] [CrossRef] [PubMed]
  4. Collins, A.J.; Foley, R.N.; Gilbertson, D.T.; Chen, S.C. United States Renal Data System public health surveillance of chronic kidney disease and end-stage renal disease. Kidney Int. Suppl. 2015, 5, 2–7. [Google Scholar] [CrossRef] [Green Version]
  5. Landreneau, K.; Lee, K.; Landreneau, M.D. Quality of life in patients undergoing hemodialysis and renal transplantation-a meta-analytic review. Nephrol Nurs. J. 2010, 37, 37–44. [Google Scholar]
  6. Pippias, M.; Kramer, A.; Noordzij, M.; Afentakis, N.; Alonso de la Torre, R.; Ambühl, P.M.; Aparicio Madre, M.I.; Arribas Monzón, F.; Åsberg, A.; Bonthuis, M.; et al. The European Renal Association—European Dialysis and Transplant Association Registry Annual Report 2014: A summary. Clin. Kidney J. 2017, 10, 154–169. [Google Scholar] [CrossRef]
  7. Gansevoort, R.T.; Correa-Rotter, R.; Hemmelgarn, B.R.; Jafar, T.H.; Heerspink, H.J.; Mann, J.F.; Matsushita, K.; Wen, C.P. Chronic kidney disease and cardiovascular risk: Epidemiology, mechanisms, and prevention. Lancet 2013, 382, 339–352. [Google Scholar] [CrossRef]
  8. Saran, R.; Robinson, B.; Abbott, K.C.; Agodoa, L.Y.C.; Bhave, N.; Bragg-Gresham, J.; Balkrishnan, R.; Dietrich, X.; Eckard, A.; Eggers, P.W.; et al. US Renal Data System 2017 Annual Data Report: Epidemiology of Kidney Disease in the United States. Am. J. Kidney Dis. 2018, 71 (Suppl. 1), A7. [Google Scholar] [CrossRef]
  9. Seoane-Pillado, M.T.; Pita-Fernández, S.; Valdés-Cañedo, F.; Seijo-Bestilleiro, R.; Pértega-Díaz, S.; Fernández-Rivera, C.; Alonso-Hernández, Á.; González-Martín, C.; Balboa-Barreiro, V. Incidence of cardiovascular events and associated risk factors in kidney transplant patients: A competing risks survival analysis. BMC Cardiovasc. Disord. 2017, 17, 72. [Google Scholar] [CrossRef] [Green Version]
  10. Devine, P.A.; Courtney, A.E.; Maxwell, A.P. Cardiovascular risk in renal transplant recipients. J. Nephrol. 2019, 32, 389–399. [Google Scholar] [CrossRef] [Green Version]
  11. Neale, J.; Smith, A.C. Cardiovascular risk factors following renal transplant. World J. Transplant. 2015, 5, 183–195. [Google Scholar] [CrossRef] [PubMed]
  12. Deanfield, J.E.; Halcox, J.P.; Rabelink, T.J. Endothelial function and dysfunction: Testing and clinical relevance. Circulation 2007, 115, 1285–1295. [Google Scholar] [CrossRef] [PubMed]
  13. Post, A.; Bollenbach, A.J.L.; Bakker, S.; Tsikas, D. Whole-body arginine dimethylation is associated with all-cause mortality in adult renal transplant recipients. Amino. Acids. 2021, 53, 541–554. [Google Scholar] [CrossRef] [PubMed]
  14. Oliva-Damaso, E.; Oliva-Damaso, N.; Rodriguez-Esparragon, F.; Payan, J.; Baamonde-Laborda, E.; Gonzalez-Cabrera, F.; Santana-Estupiñan, R.; Rodriguez-Perez, J.C. Asymmetric (ADMA) and Symmetric (SDMA) Dimethylarginines in Chronic Kidney Disease: A Clinical Approach. Int. J. Mol. Sci. 2019, 20, 3668. [Google Scholar] [CrossRef] [Green Version]
  15. Schlesinger, S.; Sonntag, S.R.; Lieb, W.; Maas, R. Asymmetric and Symmetric Dimethylarginine as Risk Markers for Total Mortality and Cardiovascular Outcomes: A Systematic Review and Meta-Analysis of Prospective Studies. PLoS ONE 2016, 11, e0165811. [Google Scholar] [CrossRef]
  16. Baia, L.C.; Humalda, J.K.; Vervloet, M.G.; Navis, G.; Bakker, S.J.; de Borst, M.H. Fibroblast growth factor 23 and cardiovascular mortality after kidney transplantation. Clin. J. Am. Soc. Nephrol. 2013, 8, 1968–1978. [Google Scholar] [CrossRef]
  17. Baia, L.C.; Heilberg, I.P.; Navis, G.; Nov de Borst, M.H. Phosphate and FGF-23 homeostasis after kidney transplantation. Nat. Rev. Nephrol. 2015, 11, 656–666. [Google Scholar] [CrossRef]
  18. Wu, D.A.; Robb, M.L.; Forsythe, J.L.R.; Bradley, C.; Cairns, J.; Draper, H.; Dudley, C.; Johnson, R.J.; Metcalfe, W.; Ravanan, R.; et al. Recipient Comorbidity and Survival Outcomes After Kidney Transplantation: A UK-wide Prospective Cohort Study. Transplantation 2020, 104, 1246–1255. [Google Scholar] [CrossRef]
  19. Lafranca, J.A.; IJermans, J.N.; Betjes, M.G.; Dor, F.J. Body mass index and outcome in renal transplant recipients: A systematic review and meta-analysis. BMC. Med. 2015, 13, 111. [Google Scholar] [CrossRef] [Green Version]
  20. Visser, R.; Dekker, F.W.; Boeschoten, E.W.; Stevens, P.; Krediet, R.T. Reliability of the 7-point subjective global assessment scale in assessing nutritional status of dialysis patients. Adv. Perit. Dial. Conf. Perit. Dial. 1999, 15, 222–225. [Google Scholar]
  21. Wołoszyk, P.; Małgorzewicz, S.; Chamienia, A.; Dębska-Ślizień, A. Obesity After Successful Kidney Transplantation. Transplant. Proc. 2020, 52, 2352–2356. [Google Scholar] [CrossRef] [PubMed]
  22. Małgorzewicz, S.; Wołoszyk, P.; Chamienia, A.; Jankowska, M.; Dębska-Ślizień, A. Obesity Risk Factors in Patients After Kidney Transplantation. Transplant. Proc. 2018, 50, 1786–1789. [Google Scholar] [CrossRef] [PubMed]
  23. Martin-Taboada, M.; Vila-Bedmar, R.; Medina-Gómez, G. From Obesity to Chronic Kidney Disease: How Can Adipose Tissue Affect Renal Function? Nephron 2021, 145, 609–613. [Google Scholar] [CrossRef] [PubMed]
  24. De Giorgi, A.; Storari, A.; Forcellini, S.; Manfredini, F.; Lamberti, N.; Todeschini, P.; La Manna, G.; Manfredini, R.; Fabbian, F. Body mass index and metabolic syndrome impact differently on major clinical events in renal transplant patients. Eur. Rev. Med. Pharmacol. Sci. 2017, 21, 4654–4660. [Google Scholar] [PubMed]
  25. Sezer, S.; Ozdemir, F.N.; Afsar, B.; Colak, T.; Kizay, U.; Haberal, M. Subjective global assessment is a useful method to detect malnutrition in renal transplant patients. Transplant. Proc. 2006, 38, 517–520. [Google Scholar] [CrossRef] [PubMed]
  26. Shirakawa, T.; Kako, K.; Shimada, T.; Nagashima, Y.; Nakamura, A.; Ishida, J.; Fukamizu, A. Production of free methylarginines via the proteasome and autophagy pathways in cultured cells. Mol. Med. Rep. 2011, 4, 615–620. [Google Scholar] [CrossRef]
  27. Fleck, C.; Schweitzer, F.; Karge, E.; Busch, M.; Stein, G. Serum concentrations of asymmetric (ADMA) and symmetric (SDMA) dimethylarginine in patients with chronic kidney diseases. Clin. Chim. Acta. 2003, 336, 1–12. [Google Scholar] [CrossRef]
  28. Said, M.Y.; Douwes, R.M.; van Londen, M.; Minović, I.; Frenay, A.R.; de Borst, M.H.; van den Berg, E.; Heiner-Fokkema, M.R.; Kayacelebi, A.A.; Bollenbach, A.; et al. Effect of renal function on homeostasis of asymmetric dimethylarginine (ADMA): Studies in donors and recipients of renal transplants. Amino. Acids. 2019, 51, 565–575. [Google Scholar] [CrossRef]
  29. Frenay, A.R.; van den Berg, E.; de Borst, M.H.; Beckmann, B.; Tsikas, D.; Feelisch, M.; Navis, G.; Bakker, S.J.; van Goor, H. Plasma ADMA associates with all-cause mortality in renal transplant recipients. Amino. Acids. 2015, 47, 1941–1949. [Google Scholar] [CrossRef] [Green Version]
  30. Małgorzewicz, S.; Heleniak, Z.; Lichodziejewska-Niemierko, M.; Rutkowski, R.; Aleksandrowicz-Wrona, E.; Dębska-Ślizień, A. Protein-energy wasting and asymmetric dimethylarginine in peritoneal dialysis patients. Acta. Biochim. Pol. 2018, 65, 581–584. [Google Scholar] [CrossRef]
  31. David, V.; Martin, A.; Isakova, T.; Spaulding, C.; Qi, L.; Ramirez, V.; Zumbrennen-Bullough, K.B.; Sun, C.C.; Lin, H.Y.; Babitt, J.L.; et al. Inflammation and functional iron deficiency regulate fibroblast growth factor 23 production. Kidney. Int. 2016, 89, 135–146. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Vogt, I.; Haffner, D.; Leifheit-Nestler, M. FGF23 and Phosphate-Cardiovascular Toxins in CKD. Toxins 2019, 11, 647. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  33. Asicioglu, E.; Kahveci, A.; Arikan, H.; Koc, M.; Tuglular, S.; Ozener, C. Fibroblast growth factor-23 levels are associated with uric acid but not carotid intima media thickness in renal transplant recipients. Transplant. Proc. 2014, 46, 180–183. [Google Scholar] [CrossRef] [PubMed]
Figure 1. The percentage of BMI categories in KTRs.
Figure 1. The percentage of BMI categories in KTRs.
Transplantology 03 00014 g001
Figure 2. The nutritional status according 7-point SGA in KTRs.
Figure 2. The nutritional status according 7-point SGA in KTRs.
Transplantology 03 00014 g002
Figure 3. ADMA concentration in KTRs with and without diabetes mellitus (p < 0.05).
Figure 3. ADMA concentration in KTRs with and without diabetes mellitus (p < 0.05).
Transplantology 03 00014 g003
Figure 4. The correlation between FGF-23 and eGFR (CKD EPI) in KTRs group (R Sperman = 0.5; p < 0.05).
Figure 4. The correlation between FGF-23 and eGFR (CKD EPI) in KTRs group (R Sperman = 0.5; p < 0.05).
Transplantology 03 00014 g004
Table 1. The comparison between KTRs and control group.
Table 1. The comparison between KTRs and control group.
ParametersKTRs
n = 46
Control Group
n = 23
Gender (M/F)26/208/15
Age (years)50.8 ± 15.462.5 ± 10.7
Type of transplantation
(Deceased donor)
n = 46-
Triple drug immunosuppression **n = 46-
Tacrolimusn = 16 -
Cyclosporinen = 20 -
Dialysis vintage before TX (months)31.0 ± 27.1-
Warm ischemic time (minutes)30.0 ± 8.5-
Cold ischemic time (minutes)950.0 ± 398.4-
BMI (kg/m2)26.25 ± 3.5124.39 ± 4.25
Fat tissue mass (%)30.28 ± 9.7326.41 ± 6.7 *
Lean Body Mass (%)64.5 ± 14.866.3 ± 9.8
Prealbumin (mg/dL)27.83 ± 7.333.52 ± 9.23 *
Albumin (g/L)38.54 ± 3.843.56 ± 2.43 *
ADMA (µmol/L)0.75 ± 0.360.32 ± 0.17 *
FGF-23 (pg/mL)115.71 ± 66.1864.11 ± 18.58 *
oxLDL (mg/mL)617.22 ± 535.36206.48 ± 61.13
Creatinine (mg/dL)
median
1.44 ± 0.42
1.37
0.83 ± 0.21
0.7
eGFR CKD-EPI (mL/min/1.73 m2)
median
42.32 ± 10.97
41.0
78.0 ± 5.0 *
80.0
Total cholesterol (mg/dL)196.03 ± 35.2186.3 ± 23.11
HDL (mg/dL)50.0 ± 14.4152.1 ± 15.1
LDL (mg/dL)125.55 ± 32.2130.15 ± 47.41
TG (mg/dL)135.9 ± 62.5100.78 ± 52.2
hsCRP (mg/L)4.2 ± 3.961.8 ± 1.5 *
* p < 0.05, ** glucocorticosteroids, calcineurin inhibitor, mycophenolate mofetil BMI—body mass index; ADMA—asymmetric dimethylarginine; FGF-23—fibroblast growth factor 23; oxLDL—oxidized low density lipoprotein; eGFR—estimated glomerular filtration rate; HDL—high density lipoprotein; LDL—low density lipoprotein; TG—triglyceride; hsCRP—high sensitive C-reactive protein.
Table 2. The comparison between KTRs with ADMA ≤ 0.66 and > 0.66 µmol/L.
Table 2. The comparison between KTRs with ADMA ≤ 0.66 and > 0.66 µmol/L.
ParametersADMA ≤ 0.66 µmol/L
n = 29
ADMA > 0.66 µmol/L
n = 17
Transplantation vintage (months)68.2 ± 64.770.7 ± 55.0
Creatinine (mg/dL)/
median
1.37 ± 0.40
1.3
1.56 ± 0.46 */
1.5
eGFR CKD-EPI (ml/min/1.73 m2)/
median
44.0 ± 9.5/
55.5
39.3 ± 13.2
48.0
oxLDL (mg/mL) 674.12 ± 569.66332.75 ± 112.41
hsCRP (mg/L)3.7 ± 3.666.75 ± 5.0
ADMA (µmol/L)0.51 ± 0.081.1 ± 0.32 *
FGF–23 (pg/mL)128.49 ± 74.07105.86 ± 50.55
* p < 0.05 eGFR—estimated glomerular filtration rate; oxLDL—oxidized low-density lipoprotein, hsCRP—high sensitive C-reactive protein; ADMA—asymmetric dimethylarginine; FGF-23—fibroblast growth factor 23.
Table 3. The comparison between well-nourished and malnourished KTRs.
Table 3. The comparison between well-nourished and malnourished KTRs.
ParametersWell-Nourished
n = 28
Malnourished
n = 19
Malnourished with BMI > 25
n = 6
Age (years)44.7 ± 13.460.2 ± 13.5 *59.1 ± 14.7 *
DM (n,%)4, 14.210, 52.6 *6, 100 *
eGFR CKD EPI (ml/min /1.73 m2)/median60.4 ± 17.3/
56.3
48.0 ± 21.7/
42.6
47.8 ± 18.4/
44.0
BMI26.9 ± 4.726.1 ± 3.429.8 ± 3.9
S-albumin (g/L)38.1 ± 3.837.1 ± 3.837.5 ± 3.6
Time after TX (months)64.4 ± 59.476.3 ± 63.571.6 ± 58.1
ADMA (µM/L)0.81 ± 0.350.70 ± 0.360.70 ± 0.30
FGF-23 (pg/mL)106.6 ± 52.1244.4 ± 516.9139.4 ± 87.3
hs-CRP (mg/L)4.6 ± 4.03.8 ± 4.14.6 ± 4.9
* p = 0.00 well-nourished vs malnourished DM diabetes mellitus, eGFR—estimated glomerular filtration rate; hsCRP—high sensitive C-reactive protein; ADMA—asymmetric dimethylarginine; FGF-23—fibroblast growth factor 23.
Table 4. The prevalence of elevated ADMA and hs-CRP depending on DM diagnosis.
Table 4. The prevalence of elevated ADMA and hs-CRP depending on DM diagnosis.
Regression ModelBStandard ErrorBetap-Value
Constant1.340.39 0.000
ADMA0.790.39−0.20.04 *
FGF-230.060.100.060.53
hsCRP0.010.000.260.01 *
* p < 0.05 ADMA—asymmetric dimethylarginine; FGF-23—fibroblast growth factor 23; hsCRP—high sensitive C-reactive protein.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Czaja-Stolc, S.; Wołoszyk, P.; Małgorzewicz, S.; Chamienia, A.; Chmielewski, M.; Heleniak, Z.; Dębska-Ślizień, A. Nutritional Predictors of Cardiovascular Risk in Patients after Kidney Transplantation-Pilot Study. Transplantology 2022, 3, 130-138. https://doi.org/10.3390/transplantology3020014

AMA Style

Czaja-Stolc S, Wołoszyk P, Małgorzewicz S, Chamienia A, Chmielewski M, Heleniak Z, Dębska-Ślizień A. Nutritional Predictors of Cardiovascular Risk in Patients after Kidney Transplantation-Pilot Study. Transplantology. 2022; 3(2):130-138. https://doi.org/10.3390/transplantology3020014

Chicago/Turabian Style

Czaja-Stolc, Sylwia, Paulina Wołoszyk, Sylwia Małgorzewicz, Andrzej Chamienia, Michał Chmielewski, Zbigniew Heleniak, and Alicja Dębska-Ślizień. 2022. "Nutritional Predictors of Cardiovascular Risk in Patients after Kidney Transplantation-Pilot Study" Transplantology 3, no. 2: 130-138. https://doi.org/10.3390/transplantology3020014

APA Style

Czaja-Stolc, S., Wołoszyk, P., Małgorzewicz, S., Chamienia, A., Chmielewski, M., Heleniak, Z., & Dębska-Ślizień, A. (2022). Nutritional Predictors of Cardiovascular Risk in Patients after Kidney Transplantation-Pilot Study. Transplantology, 3(2), 130-138. https://doi.org/10.3390/transplantology3020014

Article Metrics

Back to TopTop