Skip to main content
Download PDF

Association between bone mineral metabolism and vascular calcification in end-stage renal disease

BMC Nephrology volume 23, Article number: 12 (2022) Cite this article

Abstract

Background

Development of vascular calcification is accelerated in patients with end-stage renal disease. In addition to traditional risk factors of cardiovascular disease (CVD) abnormal bone and mineral metabolism together with many other factors contribute to the excess cardiovascular burden in patients on dialysis. Aortic calcification score and coronary calcification score are predictive of CVD and mortality. The aim of this study was to evaluate the possible relationship between arterial calcification and bone metabolism.

Methods

Thirty two patients on dialysis were included. All patients underwent a bone biopsy to assess bone histomorphometry and a 18F-NaF PET scan. Fluoride activity was measured in the lumbar spine (L1 – L4) and at the anterior iliac crest. Arterial calcification scores were assessed by computerized tomography for quantification of coronary artery calcification score and lateral lumbar radiography for aortic calcification score.

Results

This study group showed high prevalence of arterial calcification and 59% had verified CVD. Both CAC and AAC were significantly higher in patients with verified CVD. Only 22% had low turnover bone disease. There was a weak association between fluoride activity, which reflects bone turnover, measured in the lumbar spine, and CAC and between PTH and CAC. There was also a weak association between erosion surfaces and AAC. No significant association was found between calcification score and any other parameter measured.

Conclusions

The results in this study highlight the complexity, when evaluating the link between bone remodeling and vascular calcification in patients with multiple comorbidities and extensive atherosclerosis. Several studies suggest an impact of bone turnover on development of arterial calcification and there is some evidence of reduced progression of vascular calcification with improvement in bone status. The present study indicates an association between vascular calcification and bone turnover, even though many parameters of bone turnover failed to show significance. In the presence of multiple other factors contributing to the development of calcification, the impact of bone remodeling might be diminished.

Trial registration

The study is registered in ClinicalTrials.gov protocol registration and result system, ID is NCT02967042. Date of registration is 17/11/2016. 

Peer Review reports

Introduction

Patients with end-stage renal disease (ESRD) have increased risk of death due to high prevalence of cardiovascular disease (CVD) [1,2,3]. Development of atherosclerosis and vascular calcification is accelerated in this patient group [4, 5]. In addition to traditional risk factors of CVD [6], abnormal bone and mineral metabolism together with uremic toxins, oxidative stress and inflammation contribute to the excess cardiovascular burden in patients on dialysis [7, 8].

Aortic calcification (AAC) increases with age [9] and has been associated with an increased risk of cardiovascular outcomes [10, 11]. The presence of arterial calcification is predictive of CVD and mortality [12,13,14,15,16]. AAC is an independent predictor of obstructive coronary disease and correlates with coronary artery calcification (CAC) [15, 17, 18]. Up to 80 – 90% prevalence of vascular calcification in ESRD patients has been reported [19]. Coronary calcification is associated with CVD, myocardial infarction and all-cause mortality also in the CKD population, including patients on dialysis [20,21,22]. CAC assessed by non-contrast cardiac computed tomography (CT) is highly sensitive for detection of coronary artery disease [23, 24].

Impaired bone metabolism and vascular calcification are intricately interconnected in patients with chronic kidney disease. Lower bone formation rate is associated with coronary calcification in CKD patients not yet on dialysis [25]. A few studies have suggested a link between low bone activity and arterial calcification and aortic stiffening in ESRD patients [26, 27], although the specific mechanisms are not yet fully understood. Improvement of turnover in both high and low turnover bone disorders, is associated with lower CAC progression in hemodialysis patients [25]. An inverse association between arterial calcifications and bone mineral density (BMD), trabecular bone score and trabecular bone volume has also been documented in uremic patients [20, 25, 28]. Calcium overload is associated with both the presence and the progression of arterial calcification [29, 30].

Bone metabolism is commonly assessed by measuring biomarkers or histomorphometric parameters obtained by bone biopsy. 18F- Sodium Fluoride positron emission tomography (18F-NaF PET) is a novel imaging technique that allows assessment of regional bone turnover [31,32,33]. 18F-NaF PET is the preferred imaging technology when studying quantitative molecular imaging of bone [34]. We have previously shown that 18F-NaF PET correlates with both static and dynamic histomorphometric parameters and can distinguish between low and high turnover bone disease [35, 36].

The purpose of this study was to evaluate the possible relationship between aortic and coronary calcification and bone qualities such as bone mineral metabolism and bone density measured by 18F-fluoride PET, bone histomorphometry and DXA in patients on dialysis.

Methods

The study was approved by the Ethics committee of the Hospital District of South Western Finland and was conducted in accordance with the Declaration of Helsinki as revised 1964. The study is registered in ClinicalTrials.gov protocol registration and result system, ID is NCT02967042 and date of registration is 22/09/2016. All subjects gave written informed consent.

Study subjects

The study subjects were recruited from the Kidney center in Turku. The inclusion criteria were: End-stage renal disease and dialysis treatment, biochemical abnormalities indicating mineral and bone disorder; long-term elevated PTH and hyperphosphatemia. Exclusion criteria were: pregnancy and bisphosphonate medication in the past 6 months. Ongoing medication for secondary hyperparathyroidism was continued, the medication remained unchanged during the study period. All patients underwent a 18F-NaF PET-CT scan including a CT scan of the heart. In addition, dual-energy X-ray absorptiometry (DXA) and a lateral lumbar x-ray were done. The bone biopsy was performed as a part of the study protocol within 4-6 weeks after the PET-scan.

Laboratory assessment

Serum ionized calcium, alkaline phosphatase, phosphate, 25-hydroxyvitamin D, 1,25-dihydroxyvitamin D, intact parathyroid hormone, albumin, acid-base balance, full blood count, and creatinine were performed in all patients. The coagulation status was obtained previous to the bone biopsy. All tests were performed and analyzed by the local University Hospital laboratory. Biochemical markers were obtained in the morning or right before dialysis sessions.

Abdominal aortic calcification score

Lateral lumbar radiography that included the abdominal aorta was performed using standard radiographic equipment. The AAC score was calculated using the scoring system described by Kauppila et al. [9]. In this method, the anterior and posterior aspects of the abdominal aorta are divided into four segments bound by the first four lumbar vertebrae. A total of 8 segments are evaluated (posterior and anterior wall). The degree of vascular calcification was graded 0, 1, 2 or 3, so that the total score can range from 0 - 24. In the anteroposterior severity score (0–24), the scores of individual aortic segments for the posterior and anterior walls were summed. All radiographs were analyzed by 2 independent researchers, and the mean AAC score was used in the analysis.

Coronary tomography

All participants underwent a CT scan of the heart and coronary arteries prior to the 18F-NaF PET. CT scans were performed with a GE Discovery VCT 48 -slice CT/ positron emission tomography device (GE Healthcare). The coronary artery calcification score was calculated using the Agatston method for each coronary artery [37], and expressed in modified Agaston units (AU). Absence of CAC was defined as Agatston score of 0. Presence of CAC was defined as Agatson score of 1 or greater. CAC grade: 0, 1-100, 101 - 399, ≥400.

Dual-energy X-ray absorptiometry (DXA)

DXA is an X-ray based imaging method, used widely for the diagnosis of osteoporosis [38]. BMD was measured with the use of dual X-ray absorptiometry (DXA) from the proximal femurs (femoral neck) and the lumbar spine (L1 – L4). DXA device (Hologic QDR 4500C, Hologic Inc., USA or Osteocore III, Medilink, France) was used. BMD was reported as grams per centimeter. Individual patient’s results were expressed as T-scores.

Bone biopsy and bone histomorphometry

Iliac crest biopsies were performed vertically under local anesthesia including one cortex. The patients underwent fluorochrome double labeling by receiving 500 mg tetracycline three times daily for two days per os, followed by a drug free interval of ten days and a further two days administration of tetracycline. Bone biopsy was completed 7-10 days after the second label. The investigator double-checked before the procedure that tetracycline was taken as ordinated. Bone biopsies were obtained using a Snarecoil Mermaid Medical RBN-86 8G (3.3 mm) x15cm needle. Bone biopsies were fixed in 70% ethanol for at least 48 h before embedding in polymethylmethacrylate. The samples were cut into 5-μm thick sections and then stained with modified Masson-Goldner trichrome stain for static parameters, unstained sections were used for dynamic parameters. A semiautomatic image analyzer (Bioquant Osteo II, Bioquant Image Analysis Corporation, Nashville, TN, USA) was used for analyzing all parameters. In two patients, with only a single tetracycline label, we used a value for MAR of 0.3 μm/day in line with ASBMR Histomorphometry Nomenclature Committee recommendations for biopsies with only single labels [39]. The values for normal turnover were set using the results of Recker et co (mean ± 1SD) [40, 41]. The range for normal turnover in men was: BFR/BS 3.6 – 18.8 μm/y and Ac.f 0.12 – 0.6, in postmenopausal women: BFR/BS 6-22 μm/y and Ac.f 0.11 – 0.49 /y and in premenopausal women: BFR/BS 3-13 μm/y and Ac.f 0.04-0.26 /y.

18F-sodium fluoride positron emission tomography imaging

The PET scans were acquired using a Discovery VCT scanner (GE Healthcare). The tracer 18F-Fluoride ([18F]F−) is produced by 11-MeV proton irradiation of 18O-water using a cyclotron. The quality control tests for the 18F-NaF are conforming to the European Pharmacopeia. The subjects were positioned supine with the lumbar vertebrae in the field of view. A 60 min scan of the lumbar spine (L1-L4) followed by a 10 min static scan of the pelvis was done. The 60 min dynamic scan was begun simultaneously with an intravenous injection of 200 MBq 18F-NaF. The dynamic scan consisted of twenty-four 5-s, four 30-s and fourteen 240-s time frames. Low-dose CT-scans were done for image segmentation and attenuation correction. To generate bone activity curves (kilo becquerels per milliliter), regions of interest (ROI) in the lumbar spine were defined by drawing a ROI within each vertebral body, avoiding the end-plates and disk space. In the static PET scan of the pelvis ROI was defined by drawing a ROI on the anterior iliac crest, in the same region the bone biopsy was later obtained. We used an image derived input function by placing a ROI over the abdominal aorta (arterial input function, AIF) [42]. Patlak analysis was used to estimate the plasma clearance of 18F-Fluoride (net influx rate, Ki) into the bone at the lumbar spine38. For the static scan of the pelvic bone; fractional uptake rate (FUR), which is an approximation of Patlak Ki [43], was calculated by dividing the bone activity concentration by area-under-curve of blood activity from 18F-Fluoride administration time to the time of static scan. Activity measurements were corrected for radioactive decay to the time of injection.

Statistical analysis

Statistical analyses for background variables were performed using SAS 9.4 for Windows and JMP Pro 14. Characteristics of the study population were expressed as median and interquartile range (IQR)/range or mean and standard deviation (SD). For estimating the difference between means in different groups we used one-way analysis of variance (ANOVA).

Association between aortic and coronary calcification score, different bone qualities and CAC (and AAC) was studied with linear model including bone turnover variables (one at the time) adjusted with also sex and age. Assumptions for the model were checked using studentized residuals. Logarithmic transformation was used to some variables to fulfill the model assumptions. Pearson correlation coefficients were calculated between two continuous variables. In addition, bone turnover variables were compared between diabetic and non-diabetic patients were performed with two-sample t-test. The same method was used to compare low and high CAC (and AAC) values. P-values less than 0.05 (two-tailed) were considered as statistically significant.

Results

Patient characteristics

The study group comprised 32 end-stage renal disease patients. 50% were on peritoneal dialysis and 50% on hemodialysis. 41% were female and the average age was 66 years. 38% had diabetes and 22% were smokers. Patient demographics, kidney disease characteristics and medication are presented in Table 1.

Table 1 Demographics, disease characteristics and medication of the study group
Full size table

All patients were submitted to undergo a bone biopsy. In two patients the biopsy was unsuccessful and in two patients the biopsy was not sufficient to reliable analyze histomorphometric parameters. The histomorphometric characteristics of the study group are shown in Table 2. According to histomorphometric parameters, 39% had high turnover/hyperparathyroid bone disease and 22% had low turnover/adynamic bone disease. 13% had a mineralization defect.

Table 2 Histomorphometric characteristics (n = 28)
Full size table

There was no statistically significant difference in histomorphometric markers obtained by bone biopsy, in turnover measured by 18F-NaF PET nor in T-scores measured in the lumbar spine and at the femoral neck when comparing patients with diabetes versus no diabetes and patient receiving hemodialysis versus peritoneal dialysis. tALP was significantly higher in patients with diabetes, the mean tALP in patients with DM was 146 (± 22) U/l and 84 (± 17) U/l in patients with no DM, p = 0.03. Pi was significantly higher in patients receiving hemodialysis treatment than in patients on peritoneal dialysis, Pi 1.8 (± 0.1) versus Pi 1.5 (± 0.1), p = 0.04.

Vascular calcification and cardiovascular disease

Coronary artery calcification (CAC) score was calculated in all patients. Only 6.3%, had CAC score = 0, 50% had CAC score ≥ 400, Fig. 1a. Aortic calcification score was estimated in 24/32 patients. 12.5% had AAC score = 0 and 62.5% had AAC score > 8/24, Fig. 1b. CAC and AAC correlated significantly, p < 000.1 and rs = 0.63.

Fig. 1
figure 1

Distribution of coronary artery and aortic calcification scores. CAC = 0, CAC 1-100 = mild risk, CAC 101 – 399 = moderate risk, CAC ≥  400 = high risk. AAC = 0, AAC 1- 8 = moderate risk, AAC 8-24 = high risk

Full size image

In this study population, 59% had a history of cardiovascular disease and 19% had a documented myocardial infarction. Both AAC and CAC score were significantly higher in patients with verified cardiovascular disease, p < 0.001 (CAC) and p = 0.03 (AAC). Also in the non-diabetic group, both AAC and CAC scores were significantly higher than in the group with verified cardiovascular disease, p < 0.001 (CAC) and p < 0.01 (AAC). DXA was obtained in 30/32 patients. 36% (5/14) of the patients with CAC ≥ 400 had osteoporosis. In patients with CAC 101 - 399 44% (4/9) had osteoporosis and in patients with CAC 1 - 100, 20% (1/5) had osteoporosis. 38% (5/13) of patients with AAC ≥ 8 had osteoporosis and 33% (2/6) of the patients with AAC 1 - 7.

We compared patients with high AAC score > 8 (n = 15) and patients with low AAC score (n = 9). We also compared patients with CAC > 400 (n = 16) to patients with CAC < 100 (n = 7), and patients with CAC > 100 (n = 25) to patients with CAC < 100 (n = 7). All histomorphometric markers (BFR, Ac.f, Ob.S/BS, Oc.S/BS, MS/BS, ES/BS, MAR, Mlt, OV/BV, O.Yh, Tb.Th, OV/BV), fluoride activity measured by 18F-NaF PET in the lumbar spine, Ki mean and the iliac crest FURmean, T-scores measured in the lumbar spine and at the femoral neck and laboratory parameters were analyzed. The only statistically significant finding vas, that BV/TV was slightly higher in patients with high AAC score, but no difference in patients with high or low CAC score.

Association between AAC and CAC and bone metabolism and density measured by 18F-fluoride PET, bone histomorphometry, DXA and laboratory parameters

In the non-diabetic group, there was a correlation between CAC and age (p = 0.02, rs = 0.52), indications of correlation between AAC and age was also observed, but did not reach statistical significance (p = 0.07. rs = 0.51). Albumin correlated negatively with AAC (p < 0.01, rs = −0.57), but not with CAC (p = 0.17, rs = −0.25). No correlation could be shown between calcification scores and dialysis vintage, BMI and CRP.

Associations between aortic and coronary calcification score and different bone qualities were tested direct and with a model adjusted to age and sex. Tested bone qualities were turnover measured by 18F-NaF PET, histomorphometric markers (bone formation rate, BFR/BS, activation frequency, Ac.f, osteoclast and osteoblast activity, Ob.S/BS, Oc.S/BS, erosion surface, ES/BS, mineral apposition rate, MAR, mineralized surface, MS/BS, osteoid volume of bone volume. OV/BV), bone volume of tissue volume (BV/TV), osteoid thickness (O.th), mineralization lag time (Mlt) and trabecular thickness (Tb.th)), bone density (T-score at the lumbar spine and the femoral neck) and laboratory parameters. Calcifications scores and log-transformed calcifications scores were tested. There was a weak positive, but significant association between CAC and Ki, adjusted with age and sex, p = 0.01. There was also a weak positive association between CAC and PTH, p = 0.04 and between ES/BS and AAC, p = 0.04, when adjusted with age and sex.

Discussion

The link between impaired bone metabolism and arterial calcification in patients with chronic kidney disease is well acknowledged, but still a matter of controversy. A recent study showed that the presence of vascular calcification affects several pathways in bone and is associated with lower bone density and impaired bone metabolism [44]. Several studies have suggested a link between bone turnover and vascular calcification in patients on hemodialysis, especially low turnover bone disease [26, 27, 45], but also contradictory results have been published [46,47,48]. In this study, there was a weak association between fluoride activity measured in the lumbar spine by 18F-NaF PET and CAC. There was also a weak association between erosion surfaces and AAC and between PTH and CAC.

Our cohort is a valid example of the current dialysis patients in Western countries. The patients in this cohort were rather elderly, median age 66 years and more than one third had a history of diabetes. More than 50% of the study population had manifested cardiovascular disease. The prevalence of coronary artery and aortic calcification was high and arterial calcification scores, both CAC and AAC, were significantly higher in patients with cardiovascular disease. 50% had CAC > 400, which suggest severe and extensive atherosclerotic disease. A half of the patients were on peritoneal dialysis and this differs from previous studies. This was a cross-sectional study. Both the bone biopsy and 18F-NaF PET was part of the study protocol and the range of PTH was narrow, with only a few very low or high values. According to histomorphometric markers obtained by bone biopsy, only 22% had low turnover/adynamic bone disease, which diverge from other studies indicating an association between arterial calcification and bone metabolism.

In the studies reporting a link between turnover and calcification score, London et co [26, 27] found that high arterial calcification score was associated with bone histomorphometry suggestive of adynamic bone disease. In this study, 43% of the patients had previously underwent parathyroidectomy. Furthermore, calcification score was evaluated ultrasonographically, which has relatively low sensitivity. They also reported that adynamic bone disease was associated with greater aortic stiffening and that aortic calcification scores were higher in this group. In the latter cohort, the study population was significantly younger than in our cohort. In addition, 50% had adynamic bone disease. Noteworthy is, that the subgroups of renal osteodystrophy were classified based on only tetracycline labels. In both cohorts, the study population was larger than in our study and the patients were nondiabetic and on hemodialysis treatment. In the study of Asci et co [45], over 200 patients on hemodialysis underwent a bone biopsy and CAC score was assessed. They found a significant positive correlation between histomorphometric bone turnover markers (BFR and Ac.f) and CAC in the whole study population. When analyzing only patients with CAC score > 0, there was a negative association between CAC and bone turnover markers (Ac.f and BFR) in low turnover patients, which was not found in patients with normal turnover. In addition, a positive correlation in high turnover patients was observed. Noteworthy is, that as much as 71% of the patients had low turnover bone disease, 27% had manifested cardiovascular disease compared to 50% in our study group and less than a third were diabetic.

In the studies published by Barreto and Coen [47, 48] there was no association between bone turnover parameters and CAC score. In the study of Barreto et al., the study population was rather young with a high prevalence of coronary calcification and 31% had a CAC score > 400. They found that higher osteoprotegerin was associated with coronary artery calcification, but no association with histomorphometric parameters of bone turnover. The cohort of the study of Coen was more similar to the present study population including 32 patients with a mean age of 55 years. Only 9% had low turnover bone disease. After multiregression analysis, no association between CAC score and bone turnover was observed.

In the present study, there was a weak association between fluoride uptake in the lumbar spine and CAC. Quantitative dynamic 18F-NaF PET measures bone turnover at multiple sites and gives a more extensive evaluation of the skeleton. However, there was no association between CAC and fluoride uptake at the iliac crest and no association between CAC and any of the histomorphometric parameters measured. There was a weak association between PTH and CAC. PTH is a biomarker of turnover, but it has limited ability to correctly estimate bone turnover except for the extreme high or low PTH levels [49]. The range of PTH in this study population was narrow and the significance of this result remain unclear. Overall, one should be cautious when interpreting the results keeping in mind that this was a cross-sectional rather small study. Still these results strengthen the assumption, that there is a link between vascular calcification and bone metabolism.

A strength of the present study is that bone turnover was measured with both bone histomorphometry and 18F-NaF PET imaging. Also the fact, that both coronary artery and aortic calcification were measured, is a strength. Both imaging methods are established and precise to detect arterial calcification. When it comes to the comparability of the studies evaluating bone metabolism and arterial calcification, one problem is the variability of the methods used to define calcification score and the variability in the classification of renal osteodystrophy.

A few studies have also reported a link between lower bone mineral density and vascular calcification in patients with CKD [19, 28, 50]. In this study, we did not find an association between bone density and vascular calcification. High prevalence of high risk arterial calcification, the heterogeneity of the study populations and the rather high median age, might diminish the association between bone density and vascular calcification.

The limitations of this study is the cross-sectional nature of the study, the relatively low number of patients and the heterogeneity of the study group. Also the small number of patients with low turnover bone disease and the fact, that only PTH was measured as a biomarker of turnover, are limitations.

Conclusions

In summary, one can state that the association between arterial calcification and bone turnover still is controversial. The results of this study strengthen the assumption of a link between bone remodeling and arterial calcification, but also highlight the complexity, when evaluating patients with multiple comorbidities and extensive atherosclerosis. Also the fact, that only 22% had low turnover/adynamic bone disease in this study, might impact the significance of the results. Evidence of improvement in turnover and reduced progression of vascular calcification25 and the association between low turnover and vascular calcification45 strengthen the assumption of a link between vascular calcification and bone remodeling also in end-stage renal disease patients. However, in the presence of multiple other factors contributing to the development of calcification, the impact of bone remodeling might be diminished. Prospective studies are needed to verify the impact of changes in bone turnover on the progression of vascular calcification.

Availability of data and materials

The data that support the findings of this study are available from the corresponding author upon reasonable request.

Abbreviations

CVD :

Cardiovascular disease

AAC :

Aortic calcification score

CAC :

Coronary calcification score

18F-NaF PET :

18F-Sodium Fluoride Positron Emission Tomography imaging

CT :

Computerized tomography

DXA :

Dual-energy X-ray absorptiometry

BMD :

Bone mineral density

ESRD :

End-stage renal disease

CKD :

Chronic kidney disease

PTH :

Parathyroid hormone

BFR/BS :

Bone formation rate per bone surface

Ac.f:

Activation frequency

Ob.S/BS :

Osteoblast surface per bone surface

Oc.S/BS :

Osteoclast surface per bone surface

ES/BS :

Erosion surface per bone surface

MAR :

Mineral apposition rate

MS/BS :

Mineralized surface per bone surface

OV/BV :

Osteoid volume per bone volume

BV/TV :

Bone volume per tissue volume

O.th:

Osteoid thickness

Tb.th :

Trabecular thickness

References

  1. Cozzolino M, Galassi A, Pivari F, Ciceri P, Conte F. The cardiovascular burden in end-stage renal disease. Contrib Nephrol. 2017;191:44–57. https://doi.org/10.1159/000479250.

    Article  PubMed  Google Scholar 

  2. Mahmoodi BK, Matsushita K, Woodward M, et al. Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without hypertension: a meta-analysis. Lancet. 2012;380(9854):1649–61. https://doi.org/10.1016/S0140-6736(12)61272-0.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Fox CS, Matsushita K, Woodward M, et al. Associations of kidney disease measures with mortality and end-stage renal disease in individuals with and without diabetes: a meta-analysis. Lancet. 2012;380(9854):1662–73. https://doi.org/10.1016/S0140-6736(12)61350-6.

    Article  PubMed  PubMed Central  Google Scholar 

  4. Russo D, Palmiero G, De Blasio AP, Balletta MM, Andreucci VE. Coronary artery calcification in patients with CRF not undergoing dialysis. Am J Kidney Dis. 2004;44(6):1024–30.

    Article  Google Scholar 

  5. Tomiyama C, Higa A, Dalboni MA, et al. The impact of traditional and non-traditional risk factors on coronary calcification in pre-dialysis patients. Nephrol Dial Transplant. 2006;21(9):2464–71.

    Article  Google Scholar 

  6. Wilson PW, D'Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97(18):1837–47. https://doi.org/10.1161/01.cir.97.18.1837.

    Article  CAS  PubMed  Google Scholar 

  7. Guerin AP, London GM, Marchais SJ, Metivier F. Arterial stiffening and vascular calcifications in end-stage renal disease. Nephrol Dial Transplant. 2000;15(7):1014–21. https://doi.org/10.1093/ndt/15.7.1014.

    Article  CAS  PubMed  Google Scholar 

  8. Zimmermann J, Herrlinger S, Pruy A, Metzger T, Wanner C. Inflammation enhances cardiovascular risk and mortality in hemodialysis patients. Kidney Int. 1999;55(2):648–58. https://doi.org/10.1046/j.1523-1755.1999.00273.x.

    Article  CAS  PubMed  Google Scholar 

  9. Kauppila LI, Polak JF, Cupples LA, Hannan MT, Kiel DP, Wilson PW. New indices to classify location, severity and progression of calcific lesions in the abdominal aorta: a 25-year follow-up study. Atherosclerosis. 1997;132(2):245–50.

    Article  CAS  Google Scholar 

  10. Wilson PW, Kauppila LI, O'Donnell CJ, et al. Abdominal aortic calcific deposits are an important predictor of vascular morbidity and mortality. Circulation. 2001;103(11):1529–34. https://doi.org/10.1161/01.cir.103.11.1529.

    Article  CAS  PubMed  Google Scholar 

  11. van der Meer IM, Bots ML, Hofman A, del Sol AI, van der Kuip DA, Witteman JC. Predictive value of noninvasive measures of atherosclerosis for incident myocardial infarction: the Rotterdam study. Circulation. 2004;109(9):1089–94. https://doi.org/10.1161/01.CIR.0000120708.59903.1B.

    Article  PubMed  Google Scholar 

  12. Blacher J, Guerin AP, Pannier B, Marchais SJ, London GM. Arterial calcifications, arterial stiffness, and cardiovascular risk in end-stage renal disease. Hypertension. 2001;38(4):938–42. https://doi.org/10.1161/hy1001.096358.

    Article  CAS  PubMed  Google Scholar 

  13. London GM, Guerin AP, Marchais SJ, Metivier F, Pannier B, Adda H. Arterial media calcification in end-stage renal disease: impact on all-cause and cardiovascular mortality. Nephrol Dial Transplant. 2003;18(9):1731–40. https://doi.org/10.1093/ndt/gfg414.

    Article  PubMed  Google Scholar 

  14. Okuno S, Ishimura E, Kitatani K, et al. Presence of abdominal aortic calcification is significantly associated with all-cause and cardiovascular mortality in maintenance hemodialysis patients. Am J Kidney Dis. 2007;49(3):417–25.

    Article  Google Scholar 

  15. Cho A, Jung HY, Park HC, Oh J, Kim J, Lee YK. Relationship between abdominal aortic calcification on plain radiograph and coronary artery calcification detected by computed tomography in hemodialysis patients. Clin Nephrol. 2020;93(3):123–9. https://doi.org/10.5414/CN109988.

    Article  CAS  PubMed  Google Scholar 

  16. Peeters MJ, van den Brand JA, van Zuilen AD, et al. Abdominal aortic calcification in patients with CKD. J Nephrol. 2017;30(1):109–18. https://doi.org/10.1007/s40620-015-0260-7.

    Article  CAS  PubMed  Google Scholar 

  17. Zweig BM, Sheth M, Simpson S, Al-Mallah MH. Association of abdominal aortic calcium with coronary artery calcium and obstructive coronary artery disease: a pilot study. Int J Card Imaging. 2012;28(2):399–404. https://doi.org/10.1007/s10554-011-9818-1.

    Article  Google Scholar 

  18. Bellasi A, Ferramosca E, Muntner P, et al. Correlation of simple imaging tests and coronary artery calcium measured by computed tomography in hemodialysis patients. Kidney Int. 2006;70(9):1623–8.

    Article  CAS  Google Scholar 

  19. Toussaint ND, Lau KK, Strauss BJ, Polkinghorne KR, Kerr PG. Determination and validation of aortic calcification measurement from lateral bone densitometry in dialysis patients. Clin J Am Soc Nephrol. 2009;4(1):119–27. https://doi.org/10.2215/CJN.03410708.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Braun J, Oldendorf M, Moshage W, Heidler R, Zeitler E, Luft FC. Electron beam computed tomography in the evaluation of cardiac calcification in chronic dialysis patients. Am J Kidney Dis. 1996;27(3):394–401.

    Article  CAS  Google Scholar 

  21. Goodman WG, Goldin J, Kuizon BD, et al. Coronary-artery calcification in young adults with end-stage renal disease who are undergoing dialysis. N Engl J Med. 2000;342(20):1478–83. https://doi.org/10.1056/NEJM200005183422003.

    Article  CAS  PubMed  Google Scholar 

  22. Chen J, Budoff MJ, Reilly MP, et al. Coronary artery calcification and risk of cardiovascular disease and death among patients with chronic kidney disease. JAMA Cardiol. 2017;2(6):635–43. https://doi.org/10.1001/jamacardio.2017.0363.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Thompson GR, Forbat S, Underwood R. Electron-beam CT scanning for detection of coronary calcification and prediction of coronary heart disease. QJM. 1996;89(8):565–70. https://doi.org/10.1093/qjmed/89.8.565.

    Article  CAS  PubMed  Google Scholar 

  24. Rumberger JA, Brundage BH, Rader DJ, Kondos G. Electron beam computed tomographic coronary calcium scanning: a review and guidelines for use in asymptomatic persons. Mayo Clin Proc. 1999;74(3):243–52.

    Article  CAS  Google Scholar 

  25. Barreto DV, Barreto Fde C, Carvalho AB, et al. Association of changes in bone remodeling and coronary calcification in hemodialysis patients: a prospective study. Am J Kidney Dis. 2008;52(6):1139–50. https://doi.org/10.1053/j.ajkd.2008.06.024.

    Article  CAS  PubMed  Google Scholar 

  26. London GM, Marty C, Marchais SJ, Guerin AP, Metivier F, de Vernejoul MC. Arterial calcifications and bone histomorphometry in end-stage renal disease. J Am Soc Nephrol. 2004;15(7):1943–51. https://doi.org/10.1097/01.asn.0000129337.50739.48.

    Article  PubMed  Google Scholar 

  27. London GM, Marchais SJ, Guerin AP, Boutouyrie P, Metivier F, de Vernejoul MC. Association of bone activity, calcium load, aortic stiffness, and calcifications in ESRD. J Am Soc Nephrol. 2008;19(9):1827–35. https://doi.org/10.1681/ASN.2007050622.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Aleksova J, Kurniawan S, Vucak-Dzumhur M, et al. Aortic vascular calcification is inversely associated with the trabecular bone score in patients receiving dialysis. Bone. 2018;113:118–23.

    Article  CAS  Google Scholar 

  29. Chertow GM, Burke SK, Raggi P. Treat to goal working group. Sevelamer attenuates the progression of coronary and aortic calcification in hemodialysis patients. Kidney Int. 2002;62(1):245–52.

    Article  CAS  Google Scholar 

  30. Block GA, Spiegel DM, Ehrlich J, et al. Effects of sevelamer and calcium on coronary artery calcification in patients new to hemodialysis. Kidney Int. 2005;68(4):1815–24.

    Article  CAS  Google Scholar 

  31. Al-Beyatti Y, Siddique M, Frost ML, Fogelman I, Blake GM. Precision of (1)(8)F-fluoride PET skeletal kinetic studies in the assessment of bone metabolism. Osteoporos Int. 2012;23(10):2535–41. https://doi.org/10.1007/s00198-011-1889-2.

    Article  CAS  PubMed  Google Scholar 

  32. Even-Sapir E. (1)(8)F-fluoride PET/computed tomography imaging. PET Clin. 2014;9(3):277–85. https://doi.org/10.1016/j.cpet.2014.03.003.

    Article  PubMed  Google Scholar 

  33. Frost ML, Compston JE, Goldsmith D, et al. (18)F-fluoride positron emission tomography measurements of regional bone formation in hemodialysis patients with suspected adynamic bone disease. Calcif Tissue Int. 2013;93(5):436–47. https://doi.org/10.1007/s00223-013-9778-7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Blake GM, Siddique M, Frost ML, Moore AE, Fogelman I. Imaging of site specific bone turnover in osteoporosis using positron emission tomography. Curr Osteoporos Rep. 2014;12(4):475–85. https://doi.org/10.1007/s11914-014-0231-2.

    Article  PubMed  Google Scholar 

  35. Aaltonen L, Koivuviita N, Seppanen M, et al. Correlation between (18)F-sodium fluoride positron emission tomography and bone histomorphometry in dialysis patients. Bone. 2020;134:115267.

    Article  CAS  Google Scholar 

  36. Aaltonen L, Koivuviita N, Seppanen M, et al. Bone histomorphometry and (18)F-sodium fluoride positron emission tomography imaging: comparison between only bone turnover-based and unified TMV-based classification of renal osteodystrophy. Calcif Tissue Int. 2021;109(6):605–14. https://doi.org/10.1007/s00223-021-00874-9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990;15(4):827–32.

    Article  CAS  Google Scholar 

  38. Kanis JA, Melton LJ, Christiansen C, Johnston CC, Khaltaev N. The diagnosis of osteoporosis. J Bone Miner Res. 1994;9(8):1137–41. https://doi.org/10.1002/jbmr.5650090802.

    Article  CAS  PubMed  Google Scholar 

  39. Dempster DW, Compston JE, Drezner MK, et al. Standardized nomenclature, symbols, and units for bone histomorphometry: a 2012 update of the report of the ASBMR histomorphometry nomenclature committee. J Bone Miner Res. 2013;28(1):2–17. https://doi.org/10.1002/jbmr.1805.

    Article  PubMed  Google Scholar 

  40. Recker RR, Akhter MP, Lappe JM, Watson P. Bone histomorphometry in transiliac biopsies from 48 normal, healthy men. Bone. 2018;111:109–15.

    Article  Google Scholar 

  41. Recker RR, Lappe JM, Davies M, Kimmel D. Perimenopausal bone histomorphometry before and after menopause. Bone. 2018;108:55–61.

    Article  Google Scholar 

  42. Cook GJ, Lodge MA, Marsden PK, Dynes A, Fogelman I. Non-invasive assessment of skeletal kinetics using fluorine-18 fluoride positron emission tomography: evaluation of image and population-derived arterial input functions. Eur J Nucl Med. 1999;26(11):1424–9.

    Article  CAS  Google Scholar 

  43. Thie JA. Clarification of a fractional uptake concept. J Nucl Med. 1995;36(4):711–2.

    CAS  PubMed  Google Scholar 

  44. Mace ML, Gravesen E, Nordholm A, et al. Chronic kidney disease-induced vascular calcification impairs bone metabolism. J Bone Miner Res. 2021;36(3):510–22. https://doi.org/10.1002/jbmr.4203.

    Article  CAS  PubMed  Google Scholar 

  45. Asci G, Ok E, Savas R, et al. The link between bone and coronary calcifications in CKD-5 patients on haemodialysis. Nephrol Dial Transplant. 2011;26(3):1010–5. https://doi.org/10.1093/ndt/gfq491.

    Article  PubMed  Google Scholar 

  46. Salam S, Gallagher O, Gossiel F, Paggiosi M, Eastell R, Khwaja A. Vascular calcification relationship to vascular biomarkers and bone metabolism in advanced chronic kidney disease. Bone. 2021;143:115699.

    Article  CAS  Google Scholar 

  47. Barreto DV, Barreto FC, Carvalho AB, et al. Coronary calcification in hemodialysis patients: the contribution of traditional and uremia-related risk factors. Kidney Int. 2005;67(4):1576–82.

    Article  Google Scholar 

  48. Coen G, Ballanti P, Mantella D, et al. Bone turnover, osteopenia and vascular calcifications in hemodialysis patients. A histomorphometric and multislice CT study. Am J Nephrol. 2009;29(3):145–52. https://doi.org/10.1159/000151769.

    Article  CAS  PubMed  Google Scholar 

  49. Sprague SM, Bellorin-Font E, Jorgetti V, et al. Diagnostic accuracy of bone turnover markers and bone histology in patients with CKD treated by dialysis. Am J Kidney Dis. 2016;67(4):559–66. https://doi.org/10.1053/j.ajkd.2015.06.023.

    Article  PubMed  Google Scholar 

  50. Aoki A, Kojima F, Uchida K, Tanaka Y, Nitta K. Associations between vascular calcification, arterial stiffness and bone mineral density in chronic hemodialysis patients. Geriatr Gerontol Int. 2009;9(3):246–52. https://doi.org/10.1111/j.1447-0594.2009.00528.x.

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

Grants were received from the Finska Läkaresällskapet, Munuaissäätiö and the Perklén Foundation, Helsinki, Finland.

Author information

Authors and Affiliations

  1. Kidney Center, Department of Medicine, Turku University Hospital, PL 52, Kiinamyllynkatu 4-8, 20521, Turku, Finland

    Louise Aaltonen, Niina Koivuviita & Kaj Metsärinne

  2. Turku PET Centre, University of Turku, Kiinamyllynkatu 4-8, 20521, Turku, Finland

    Marko Seppänen

  3. Department of Clinical Physiology, Nuclear Medicine, Turku University Hospital, PL 52, Kiinamyllynkatu 4-8, 20521, Turku, Finland

    Marko Seppänen

  4. Kuopio Musculoskeletal Research Unit (KMRU) Institute of Clinical Medicine, University of Eastern Finland, POB 1627, Kuopio, Finland

    Heikki Kröger & Xiaoyu Tong

  5. Kuopio University Hospital, Kuopio, Finland

    Heikki Kröger

  6. Department of Biostatistics, University of Turku, Kiinamyllynkatu 10, 20014, Turku, Finland

    Eliisa Löyttyniemi

Authors
  1. Louise Aaltonen
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Niina Koivuviita
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Marko Seppänen
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Heikki Kröger
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Xiaoyu Tong
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Eliisa Löyttyniemi
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kaj Metsärinne
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

LA: Conceptualization, Data curation, Formal analysis, Investigation, Visualization, Writing-original draft. NK: Conceptualization, Supervision, Writing-review & editing. MS: Methodology, Writing-review & editing. XT: Methodology, HK: Methodology, Validation, Writing-review & editing. EL: Formal analysis. KM: Conceptualization, Funding acquisition, Project administration, Supervision, Writing-review & editing. The authors read and approved the final manuscript.

Corresponding author

Correspondence to Louise Aaltonen.

Ethics declarations

Ethics approval and consent to participate

All the procedures performed in this study were in accordance with ethical standards of the institutional review board. The study was approved by the Ethics committee of the Hospital District of South Western Finland and was conducted in accordance with the 1964 Declaration of Helsinki and its later amendments. All subjects gave written informed consent.

Consent for publication

Not applicable.

Competing interests

The results presented in this paper have not been published previously in whole or part. Louise Aaltonen, Niina Koivuviita, Marko Seppänen, Xiaoyu Tong, Heikki Kröger, Eliisa Löyttyniemi and Kaj Metsärinne declare no competing interests.

Additional information

Publisher’s Note

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

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Aaltonen, L., Koivuviita, N., Seppänen, M. et al. Association between bone mineral metabolism and vascular calcification in end-stage renal disease. BMC Nephrol 23, 12 (2022). https://doi.org/10.1186/s12882-021-02652-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s12882-021-02652-z

Keywords

BMC Nephrology

ISSN: 1471-2369

Contact us