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Keywords:

  • CHRONIC KIDNEY DISEASE;
  • CORTICAL BONE;
  • RENAL OSTEODYSTROPHY;
  • HRpQCT;
  • DXA

ABSTRACT

  1. Top of page
  2. ABSTRACT
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgments
  9. References

Chronic kidney disease (CKD) patients may have high rates of bone loss and fractures, but microarchitectural and biochemical mechanisms of bone loss in CKD patients have not been fully described. In this longitudinal study of 53 patients with CKD Stages 2 to 5D, we used dual-energy X-ray absorptiometry (DXA), high-resolution peripheral quantitative computed tomography (HRpQCT), and biochemical markers of bone metabolism to elucidate effects of CKD on the skeleton. Median follow-up was 1.5 years (range 0.9 to 4.3 years); bone changes were annualized and compared with baseline. By DXA, there were significant declines in areal bone mineral density (BMD) of the total hip and ultradistal radius: −1.3% (95% confidence interval [CI] −2.1 to −0.6) and −2.4% (95% CI −4.0 to −0.9), respectively. By HRpQCT at the distal radius, there were significant declines in cortical area, density, and thickness and increases in porosity: −2.9% (95% CI −3.7 to −2.2), −1.3% (95% CI −1.6 to −0.6), −2.8% (95% CI −3.6 to −1.9), and +4.2% (95% CI 2.0 to 6.4), respectively. Radius trabecular area increased significantly: +0.4% (95% CI 0.2 to 0.6), without significant changes in trabecular density or microarchitecture. Elevated time-averaged levels of parathyroid hormone (PTH) and bone turnover markers predicted cortical deterioration. Higher levels of serum 25-hydroxyvitamin D predicted decreases in trabecular network heterogeneity. These data suggest that significant cortical loss occurs with CKD, which is mediated by hyperparathyroidism and elevated turnover. Future investigations are required to determine whether these cortical losses can be attenuated by treatments that reduce PTH levels and remodeling rates.


Introduction

  1. Top of page
  2. ABSTRACT
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgments
  9. References

Bone disease is a major complication of chronic kidney disease (CKD). Abnormal calcium-phosphate metabolism, decreased levels of circulating calcitriol, and increased levels of parathyroid hormone (PTH), in part and together, result in renal osteodystrophy (ROD). Fracture is the most important clinical outcome of the bone disorder that accompanies CKD. Compared with the general population, rates of spine[1] and hip[2-4] fractures are reported to be two- to fourfold greater, and rates of mortality after hip fracture are reported to be 60% greater.[5] Although fractures are more common and deadly in CKD patients than the general population, less is known about the biochemical and microarchitectural basis of increased fragility than for older women and men with osteoporosis. This is unfortunate because screening for and prevention of CKD-associated fractures will be inadequate until our understanding of their underlying pathogenetic mechanisms improves.

PTH levels increase as kidney function deteriorates.[6] Chronic PTH excess is catabolic for cortical bone, causing subperiosteal and intracortical erosion, and can be anabolic for trabecular bone, causing increased trabecular thickness and number.[7-9] Recently, cross-sectional investigations in CKD patients with and without fracture have used high-resolution peripheral quantitative computed tomography (HRpQCT, XtremeCT, nominal voxel size 82 µm),[10-12] calciotropic hormones, and bone turnover markers (BTM)[13] to evaluate mechanisms of increased fragility in CKD. These studies have shown that CKD patients with fracture have lower cortical and trabecular volumetric bone mineral density (BMD), thinner cortices, and abnormal trabecular microarchitecture of the distal radius and tibia.[10-13] In addition, higher levels of PTH and bone formation and resorption markers were associated both with abnormal cortical and trabecular density and microarchitecture and with fracture.[13] Prospective observational studies assessing areal BMD by dual-energy X-ray absorptiometry (DXA) have shown that severity of kidney disease is directly associated with the amount of bone loss at the total hip.[14-16] To date, no longitudinal studies have investigated the microstructural mechanisms of bone loss and their biochemical determinants in CKD patients.

We conducted a longitudinal study of 53 CKD patients to evaluate the extent and pathogenesis of bone loss in patients with moderate to severe kidney disease. All patients had baseline and follow-up measurements of areal BMD by DXA, cortical and trabecular volumetric BMD and microarchitecture by HRpQCT, and calciotropic hormones and BTMs. We hypothesized that CKD patients would experience progressive loss of cortical bone, characterized by decreases in cortical density, increases in cortical porosity, and cortical thinning. We also hypothesized that cortical deterioration would be related to more severe kidney dysfunction and elevated levels of PTH and turnover markers.

Materials and Methods

  1. Top of page
  2. ABSTRACT
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgments
  9. References

Subjects

CKD patients with an estimated glomerular filtration rate (eGFR) <90 mL/minute and on hemodialysis were enrolled in a longitudinal study of relationships between kidney function and bone structure and strength (n = 53). Participants were recruited from the general nephrology clinics of Columbia University Medical Center (CUMC) between August 2006 and September 2010. All patients referred to the nephrology clinics and meeting study inclusion criteria were eligible. The CUMC nephrology clinics serve as a referral center for CKD patients from the northern Manhattan, Bronx, Queens, southern New York State and Connecticut, and northern and central New Jersey areas. We did not exclude patients on the basis of CKD etiologies, which were broadly represented and included diabetes-hypertension, glomerular diseases, and other etiologies, including polycystic kidney disease, lithium toxicity, nephrolithiasis, urinary tract abnormalities, and renal artery stenosis. eGFR was determined by the Modification of Diet in Renal Disease short formula.[17] Patients on hemodialysis had to have been on hemodialysis for at least 6 months. Patients with a history of malignancy; bilateral lower extremity amputations; residing in a nursing home; requiring a wheelchair; and those taking bisphosphonates, teriparitide, gonadal steroids, aromatase inhibitors, and anticonvulsants that induce hepatic cytochrome P450 enzymes were excluded. At baseline, 1 patient was using topical glucocorticoids and another had used oral prednisone more than 1 year before the baseline visit. At follow-up, 1 patient was using topical glucocorticoids, 1 patient was taking prednisone 5 mg daily for treatment of microscopic polyangiitis, and 1 patient was using an inhaled glucocorticoid. Therefore, the cohort included in this investigation represents the wide spectrum of ambulatory patients with CKD and is generalizable to those patients typically treated in a general nephrology clinic. The CUMC Institutional Review Board approved the study, and all subjects provided written informed consent.

Laboratory measurements

Routine laboratory parameters were measured by Quest Diagnostics (Teterboro, NJ, USA). Serum creatinine was determined by the Jaffe reaction, and serum calcium, phosphorus, and bicarbonate were measured by spectrophotometry. Calciotropic hormones and BTMs were measured at CUMC in a specialized research laboratory. Intact PTH, serum total 25-hydroxyvitmain D (25-OHD), bone-specific alkaline phosphatase (BSAP), N-Mid osteocalcin, procollagen of type-1 N-terminal propeptide (P1NP), tartrate-resistant acid phosphatase 5b (Trap5b), and C-terminal telopeptides of type I collagen (CTX) were measured by Roche Elecsys 2010 analyzer (Roche Diagnostics, Indianapolis, IN, USA). Intra- and interassay precisions are 1.0% and 4.4%, 6.0% and 8.0%, 0.8% and 2.9%, 1.1% and 5.5%, 5.0% and 9.0%, and 1.1% and 5.5% for intact PTH, BSAP, osteocalcin, PINP, Trap5b, and CTX, respectively. For 25-OHD, the normal range is >30 ng/mL, and the intra- and interassay precision are 3.5% and 11.0%, respectively. The reference ranges in premenopausal women are 11.5 to 29.6 U/L, 9.7 to 35.1 ng/mL, 1.03 to 4.15 U/L, and 0.162 to 0.573 ng/mL for BSAP, osteocalcin, Trap5b, and CTX, respectively. For P1NP, the reference range is 20 to 100 µg/L.

Assessment of CKD, factors associated with BMD, and definitions of hyperparathyroidism

Kidney disease was grouped into three etiologic categories: 1) diabetic and hypertensive kidney disease; 2) glomerular causes of CKD (nephritis or nephrosis); and 3) other causes of CKD (polycystic kidney disease, tubular-interstitial, or unknown. Parent vitamin D supplementation was defined as use of ergocalciferol or cholecalciferol, and active vitamin D supplementation was defined as use of paricalcitol, doxercalciferol, or calcitriol. Phosphate binders included calcium acetate, sevelamer, or lanthanum carbonate. At baseline and follow-up, 6 and 8 patients, respectively, were taking cinacalcet. No patient was taking an aluminum-containing phosphate binding agent. Ten patients were taking calcium carbonate.

Measurement of aBMD by DXA

aBMD by DXA was measured at the total lumbar spine (L1 to L4), total hip, femoral neck (FN), and nondominant one-third and ultradistal radius using a Hologic QDR 4500 densitometer (Hologic, Inc., Waltham, MA, USA) in the array (fan beam) mode. In our laboratory, short-term in vivo precision is 0.68% for the spine, 1.36% for the FN, and 0.70% for the radius. T-scores compared subjects to data from young-normal populations of the same race and sex provided by the manufacturer (spine and forearm) and by the National Health and Nutrition Examination Survey III (TH and FN).

HR-pQCT imaging of the radius and tibia

All subjects were scanned with HR-pQCT (XtremeCT; Scanco Medical, Brüttisellen, Switzerland) at the nondominant forearm and leg unless there was previous fracture or an arteriovenous fistula or graft at the desired site in which case the opposite limb was scanned. All scan acquisition was performed in our laboratory by a single dedicated research densitometrist according to the standard manufacturer's protocols described previously.[10, 13] The arm or leg was positioned in the scanner and a 9.02-mm region of interest was defined on a scout film by manual placement of a reference line at the endplate of the radius or tibia, with the first slice 9.5 mm and 22.5 mm proximal to the reference line at the radius and tibia, respectively. Attenuation data were converted to equivalent hydroxyapatite (HA) densities. A phantom was scanned daily for quality control. To analyze the same region in the longitudinal scans, the manufacturer's software was used to find the overlapping regions between the baseline and follow-up scans.[18] This is performed by matching the cross-sectional areas of the individual slices to find the common region between the two scans. A single technician performed all image analysis using the standard manufacturer's software (Scanco Medical). From this standard analysis, trabecular bone mineral density is defined as the average bone density within the trabecular volume of interest, and the ratio of bone volume to total volume (BV/TV, %) is derived from trabecular density assuming that the density of fully mineralized bone is 1.2 g HA/cm3 (BV/TV = 100 × Dtrab/1200 mg HA/cm3). Because measurements of trabecular microstructure are limited by the resolution of HR-pQCT, which approximates the width of individual trabeculae, trabecular structure is assessed using semiderived algorithms.[19, 20] Trabecular number is defined as the inverse of the mean spacing of the mid-axes. Trabecular separation is derived from BV/TV and trabecular number using formulas from traditional quantitative histomorphometry: trabecular thickness = (BV/TV)/trabecular number and trabecular separation = (1–BV/TV)/trabecular number. The intra-individual distribution of separation (µm), a parameter that reflects the heterogeneity of the trabecular network, is also measured. In addition to the standard analysis, a validated auto-segmentation method[21] was applied to segment the cortical and trabecular compartments in order to measure cortical porosity (%), direct cortical thickness (mm), and cortical BMD (mg HA/cm3).[22, 23] Cortical porosity was calculated as the number of void voxels in the cortex using Image Processing Language (IPL, Version 5.08b, Scanco Medical). Cortical thickness was measured directly using a distance transform,[24] and cortical BMD was defined as the average mineral density in the auto-segmentation cortical bone mask.

In vivo precision of HR-pQCT measurements have been reported to be <1% for density measurements and <4.5% for morphologic measurements;[25] in our laboratory, density measurements were <1.06% and morphologic measurements <5.22% (data not shown).

Image quality assessment

All HRpQCT images were assessed for image quality and motion artifact before analysis and were graded on a scale of 0 (no imaging abnormalities) to 5 (severe abnormalities).[26, 27] Any image scoring 4 or 5 was excluded from analyses. At the radius and tibia, six and three image sets were excluded, respectively.

Statistical analysis

Statistical analyses were conducted using SAS (version 9.2, SAS Institute, Cary, NC, USA). Categorical data were compared using the chi-square test. Continuous data were evaluated for normality before statistical testing and log-transformed when appropriate. Time-averaged levels of body mass index and biochemical markers of bone metabolism were calculated from the baseline and follow-up measurements. Effects of biomarkers on changes in bone parameters were analyzed as unit changes of: PTH 10 pg/mL; 25-OHD 10 ng/mL; BSAP 5 U/L; osteocalcin 5 ng/mL; P1NP 10 µg/L; Trap5b 0.05 U/L; and CTX 0.05 ng/mL. Mixed linear regression models were used to determine changes in areal and volumetric bone density and microarchitecture, adjusted for baseline bone measures, and linear regression models were used to determine the effects of biochemical markers of bone metabolism on bone changes, adjusted for age, sex, body mass index, and hemodialysis status.

Results

  1. Top of page
  2. ABSTRACT
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgments
  9. References

Baseline and follow-up cohort characteristics

Fifty-three patients from the general nephrology clinics of CUMC were enrolled into this study. All had baseline and follow-up imaging and blood work (Table 1). About half were female (51%), 64% were white, and 32% had a prevalent fracture. CKD etiologies were broadly represented. Nine patients were on hemodialysis. In nondialyzed patients, eGFR was 36.5 ± 16.8 mL/minute. Mean levels of calcium and phosphate were in the normal range. Mean levels of PTH, BSAP, osteocalcin, P1NP, Trap5b, and CTX were greater than or equal to 1-times the upper limit of their reference ranges, and mean 25-OHD levels were low. Slightly more than 40% of patients were taking a parent vitamin D formulation, about 25% were taking an active vitamin D preparation, and about 25% were taking a phosphate binder. Only 6% and 4% of patients were taking a calcimimetic or glucocorticoids, respectively. On average, patients were osteopenic at the femoral neck and forearm. Over a median follow-up of 1.5 years (range 0.9 to 4.3 years), 1 patient progressed to dialysis. In those patients who did not progress to end-stage disease, eGFR did not change significantly (percent change in eGFR −2.4 ± 12.9%; p value NS). There were no new fracture events, mean levels of calcium and phosphorus did not change significantly, and differences in medication usage were not significant. Levels of PTH, 25-OHD, and the formation markers BSAP, osteocalcin, and P1NP increased significantly; levels of resorption markers did not change significantly. T-scores at the total hip and ultradistal radius decreased significantly.

Table 1. Cohort Characteristics at Baseline and Follow-Up (N = 53; Median Follow-Up 1.5 Years, Range 0.9 to 4.3 Years)
 BaselinePercent changeap Value
Demographics
Age, mean (SD) years69.2 ± 10−1.5 ± 0.2<0.0001
BMI, mean (SD)29.2 ± 5.9−0.4 ± 4.6NS
Female (%)510 
White (%)640 
Hispanic (%)450 
Prevalent Fx (%)320 
Kidney function
HD (%)17 (9)2NS
GFR (mL/minute)36.5 ± 16.8−2.4 ± 12.9NS
Serum creatinine2.1 ± 1.24.7 ± 12.90.02
Biochemical measures
Calcium (reference range 8.6–10.2 mg/dL)9.5 ± 0.6−0.8 ± 6.3NS
Phosphorus (reference range 2.5–4.5 mg/dL)4.0 ± 1.1−1.8 ± 10.9NS
Parathyroid hormone (reference range 15–65 pg/mL)132 ± 13619.4 ± 53.50.04
Vitamin D 25 (normal range >40 ng/mL)27 ± 1528.6 ± 690.02
BSAP (reference range 11.5–29.6 U/L)38.7 ± 14.514.4 ± 39.30.04
Osteocalcin (reference range 9.7–35.1 ng/mL)91 ± 12915.0 ± 340.02
P1NP (reference range 20–100 µL/L)196 ± 42619.0 ± 480.03
Trab5b (reference range 1.03–4.15 U/L)3.89 ± 1.571.14 ± 28.6NS
CTX (reference range 0.162–0.573 ng/mL)1.05 ± 1.0614.8 ± 53.6NS
 BaselineFollow-upp Value
  1. NS = not significant.

  2. a

    Percent changes are adjusted for baseline measurement.

  3. b

    Comparisons made by paired t test.

Kidney disease etiologies, % (n)
Nephritic/nephrotic6 (3)6 (3) 
Diabetes/hypertension68 (36)68 (36) 
Other26 (14)26 (14) 
Medications, % (n)
Calcium or calcium-containing phosphate binders26 (14)17 (9)NS
Non-calcium-containing phosphate binders23 (12)30 (16)NS
Parent Vitamin D43 (23)49 (26)NS
Active Vitamin D25 (13)30 (16)NS
Cinacalcet6 (3)8 (4)NS
Glucocorticoids4 (2)6 (3)NS
T-score by DXAb
Lumbar spine−0.4 ± 1.9−0.4 ± 2.0NS
Total hip−0.9 ± 1.1−1.0 ± 1.10.0003
Femoral neck−1.5 ± 1.0−1.5 ± 1.0NS
One-third radius−1.5 ± 1.6−1.6 ± 1.7NS
Ultradistal radius−1.3 ± 1.3−1.5 ± 1.30.001

Longitudinal changes in bone geometry, mass and microarchitecture

Baseline adjusted annualized changes in areal BMD at the spine, hip, and forearm were assessed by DXA, and in bone geometry, volumetric BMD and microarchitecture at the distal radius and tibia were assessed by HRpQCT (Fig. 1). Adjustment for baseline age, body mass index, sex, hemodialysis status, and biochemical parameters did not appreciably alter the rate or significance of bone loss at any skeletal site.

image

Figure 1. Annual percent change from baseline in areal BMD by DXA (A) and volumetric BMD and bone geometry and microarchitecture by HRpQCT at the distal radius (B) and tibia (C) (mean ± SEM).

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Total hip and ultradistal radius areal BMD decreased significantly by −1.3% (95% confidence interval [CI] −2.1 to −0.6; p < 0.0001) and −2.4% (95% CI −4.0 to −0.9; p = 0.003) per year, respectively. There were no significant changes in areal BMD at the spine, femoral neck, or one-third radius in either baseline adjusted or multivariable mixed models.

By HRpQCT, we detected significant deterioration of cortical bone at the radius. Cortical area, density, and thickness decreased significantly by −1.7% (95% CI −2.5 to −0.8; p = 0.0003), −1.2% (95% CI −1.6 to −0.7; p < 0.0001) and −1.4% (95% CI −2.2 to −0.6; p = 0.0009), and cortical porosity increased significantly by 4.2% (95% CI 2.0 to 6.4; p = 0.0005). There was a small but significant increase in trabecular area by 0.4% (95% CI 0.2 to 0.6; p = 0.0007) but no significant changes in trabecular density, number, or heterogeneity of the trabecular network.

At the tibia, we detected significant declines in cortical density and increases in cortical porosity: −1.4% (95% CI −2.0 to −0.8; p < 0.0001) and 3.9% (95% CI 1.9 to 5.9; p = 0.0003), respectively, but there were no significant changes in area or thickness. Furthermore, there were no significant changes in any of the trabecular parameters.

Relationships between bone loss calciotropic hormones and bone remodeling markers

We used linear regression to determine longitudinal associations between biochemical markers of bone metabolism and bone loss. All models were adjusted for baseline bone measure, hemodialysis status, and demographic characteristics (baseline age, sex, and body mass index) (Table 2). All analyses were conducted using time-averaged levels of body mass index and biochemical markers of bone metabolism. Relationships between changes in bone and biochemical measures are reported with the following cutoffs: PTH per 10 pg/mL; 25-OHD per 10 ng/mL; BSAP per 5 U/L; osteocalcin per 5 ng/mL; P1NP per 10 µg/L; Trap5b per 0.05 U/L; and CTX per 0.05 ng/mL.

Table 2. Linear Regression Models: Associations Between Time-Averaged Levels of Biochemical Markers of Bone Metabolism and the Annualized Percent Change in Cortical and Trabecular Geometry, Mass, and Microarchitecturea
ModelVariableCortical areaCortical BMDCortical thicknessCortical porosityTrabecular areaTrabecular BMDTrabecular numberTrabecular network heterogeneity
  1. a

    All models are adjusted for baseline bone measurement, age, sex, BMI, and dialysis status.

  2. b

    All biochemical measurements were time-averaged and then natural log transformed.

  3. c

    Data are presented as β-coefficient (SE).

Radius
1PTH (per 10 pg/mL)−2.2 (0.7); p = 0.002−0.5 (0.4); p = 0.1−2.0 (0.6); p = 0.002−0.2 (1.9); p = 0.90.5 (0.2); p = 0.0090.1 (1.0); p = 0.9−1.3 (1.9); p = 0.52.2 (2.4); p = 0.3
225-OHD (per 10 ng/mL)0.9 (0.9); p = 0.30.4 (0.4); p = 0.31.2 (0.8); p = 0.10.7 (2.1); p = 0.8−0.2 (0.2); p = 0.2−0.2 (1.0); p = 0.81.4 (1.9); p = 0.5−1.4 (2.5); p = 0.6
3BSAP (per 5 U/L)−2.8 (1.1); p = 0.01−0.2 (0.6); p = 0.7−2.5 (1.0); p = 0.02−3.7 (3.1); p = 0.20.5 (0.3); p = 0.07−1.3 (1.5); p = 0.40.4 (2.9); p = 0.9−0.5 (3.8); p = 0.9
4Osteocalcin (per 5 pg/mL)−2.4 (0.8); p = 0.006−0.6 (0.4); p = 0.2−2.2 (0.8); p = 0.007−3.6 (2.3); p = 0.10.4 (0.2); p = 0.07−0.3 (1.2); p = 0.8−2.7 (2.3); p = 0.23.2 (2.9); p = 0.3
5P1NP (per 10 µL/L)−1.5 (0.7); p = 0.04−0.4 (0.3); p = 0.2−1.4 (0.6); p = 0.03−1.9 (1.9); p = 0.30.4 (0.2); p = 0.02−1.0 (0.9); p = 0.3−0.9 (1.8); p = 0.60.5 (2.3); p = 0.8
6Trap (0.05 U/L)−4.6 (1.5); p = 0.005−2.0 (0.7); p = 0.01−3.9 (1.4); p = 0.012.9 (4.4); p = 0.51.3 (0.4); p = 0.001−0.7 (2.2); p = 0.70.1 (4.2); p = 12.4 (5.4); p = 0.7
7CTX (per 0.05 ng/mL)−2.4 (0.7); p = 0.002−0.8 (0.4); p = 0.047−1.9 (0.7); p = 0.01−0.1 (2.2); p = 1.00.5 (0.2); p = 0.02−0.4 (1.1); p = 0.71.4 (2.2); p = 0.5−1.3 (2.7); p = 0.7
Tibia
1PTH (per 10 pg/mL)0.3 (0.9); p = 0.7−0.7 (0.5); p = 0.20.3 (1.2); p = 0.83.3 (1.8); p = 0.08−0.1 (0.1); p = 0.50.6 (1.2); p = 0.6−1.6 (1.6); p = 0.34.6 (2.9); p = 0.1
225-OHD (per 10 ng/mL)−0.1 (1.0); p = 0.90.4 (0.6); p = 0.50.0 (1.3); p = 1.0−0.8 (2.1); p = 0.7−0.1 (0.1); p = 0.33.0 (1.3); p = 0.032.0 (1.8); p = 0.3−7.2 (3.1); p = 0.03
3BSAP (per 5 U/L)−0.2 (1.4); p = 0.9−0.9 (0.8); p = 0.30.3 (0.3); p = 0.9−0.8 (3.0); p = 0.8−0.09 (0.2); p = 0.4−0.4 (2.0); p = 0.80.5 (2.5); p = 0.81.0 (4.7); p = 0.8
4Osteocalcin (per 5 pg/mL)−0.3 (1.0); p = 0.8−1.2 (0.6); p = 0.04−0.2 (1.3); p = 0.94.1 (2.1); p = 0.06−0.01 (0.1); p = 0.90.3 (1.4); p = 0.8−0.9 (1.8); p = 0.65.0 (3.3); p = 0.1
5P1NP (per 10 µL/L)0.5 (0.8); p = 0.6−0.6 (0.5); p = 0.20.7 (1.1); p = 0.53.1 (1.8); p = 0.08−0.02 (0.1); p = 0.81.5 (1.2); p = 0.21.2 (1.5); p = 0.4−0.8 (2.8); p = 0.8
6Trap (0.05 U/L)−1.7 (1.9); p = 0.4−2.5 (1.1); p = 0.02−1.8 (2.5); p = 0.57.7 (4.0); p = 0.0580.05 (0.3); p = 0.04−0.3 (2.9); p = 0.93.8 (3.4); p = 0.3−1.1 (6.4); p = 0.9
7CTX (per 0.05 ng/mL)−0.4 (1.0); p = 0.7−1.0 (0.5); p = 0.07−0.2 (1.2); p = 0.94.4 (1.9); p = 0.030.1 (0.1); p = 0.70.6 (1.3); p = 0.61.8 (1.7); p = 0.3−0.8 (3.2); p = 0.8

Calciotropic hormones, remodeling markers, and demographic characteristics did not predict changes in areal BMD measured by DXA (data not shown). In contrast, at the distal radius, higher levels of PTH, the formation markers BSAP, osteocalcin and P1NP, and the resorption markers Trap5b and CTX predicted a significant 2.2%, 2.8%, 2.4%, 1.5%, 4.6%, and 2.4% decrease in cortical area, and 2.0%, 2.5%, 2.2%, 1.4%, 3.9%, and 1.9% decrease in cortical thickness, respectively. Cortical density decreased by 2.0% and 0.8% for each unit increase in Trap5b and CTX, respectively. Calciotropic hormones and remodeling markers did not predict changes in cortical porosity. For trabecular area, significant 0.5%, 0.4%, 1.3%, and 0.5% increases occurred for increased levels of PTH, P1NP, Trap5b, and CTX, respectively. Neither calciotropic hormones nor remodeling markers were associated with changes in trabecular density, number, and heterogeneity.

At the tibia, levels of calciotropic hormones were not associated with changes in cortical area, density, or microarchitecture. However, higher levels of osteocalcin and Trap5b were associated with significant decreases in cortical density (1.1% and 2.5%, respectively), and higher levels of Trap5b and CTX were associated with significant increases in cortical porosity (7.7% and 4.3%, respectively). For trabecular measures, each 10 ng/mL increase in 25-OHD was associated with a 3.0% increase in trabecular density and 7.5% decrease in the heterogeneity of the trabecular network, and each 0.05 U/L increase in Trap5b was associated with a 0.05% decrease in trabecular area.

The effect of hemodialysis status on longitudinal changes in bone

To evaluate the effects of kidney function on longitudinal changes in bone mass and microarchitecture, we conducted univariate analyses only on those bone measures that decreased significantly over time stratified by hemodialysis status (Fig. 2). Measurement of changes in areal BMD by DXA at the total hip and ultradistal radius suggested that hemodialysis status did not affect bone loss because the linear trend was not significant. However, at the radius by HRpQCT, patients on hemodialysis had more severe decreases in cortical density and greater increases in cortical porosity, and there was a significant linear trend for the association between hemodialysis and bone loss. At the tibia, differences in cortical density trended toward significance. In multivariable regression modeling, with adjustments for baseline bone measure, biochemical parameters, and demographic characteristics, hemodialysis status independently predicted 6% to 7% (p = 0.01 to 0.04) yearly increases in radius cortical porosity compared with CKD patients not on hemodialysis. However, there was no independent effect of hemodialysis status on cortical density.

image

Figure 2. Comparison of bone loss by DXA and HRpQCT by severity of kidney dysfunction.

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Discussion

  1. Top of page
  2. ABSTRACT
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgments
  9. References

In this prospective study, we found that CKD patients experienced deterioration in cortical bone over time, which was driven by hyperparathyroidism and increased bone turnover. By DXA, we detected small but significant losses of areal BMD at the total hip and ultradistal radius of −1.3% and −2.4%, respectively. By HRpQCT, we determined the underlying mechanisms for the bone loss detected by DXA. At the radius, there were decreases in cortical area, density, and thickness and increases in cortical porosity, whereas at the tibia, there was a decrease in cortical density and an increase in cortical porosity. Although time-averaged levels of biochemical markers of bone metabolism did not predict changes in areal BMD by DXA, higher concentrations of PTH, BSAP, osteocalcin, P1NP, Trap5b, and CTX did predict cortical deterioration by HRpQCT, albeit more so at the radius than at the tibia. The increase in trabecular area was predicted by increased PTH and remodeling markers, suggesting it was likely the result of endocortical cancellization, a consequence of hyperparathyroidism. Higher serum 25-OHD cancellization (i.e. trabecularization), predicted an increase in trabecular density and decrease in the heterogeneity of the trabecular network. The annual rates of bone loss in our study are similar to those reported in women during early menopause,[28] up to 3% per year for the first 3 to 5 years. However, cortical loss predominated in our CKD patients.

Several studies have used DXA to assess longitudinal associations between kidney function and areal BMD at the hip[14-16, 29] and spine.[29] In 614 community-dwelling participants aged 65 years and older from the Cardiovascular Health Study, Fried and collegues[16] reported that kidney function was significantly associated with declines in BMD, and patients with the most severe kidney dysfunction had annualized rates of bone loss at the total hip (women −0.7% per year; men −0.9% per year), twice as high as those reported in the placebo groups of several bisphosphonate trials.[28, 30] In 1023 men in the Rancho Bernardo Study, Jassal and colleagues[15] reported that average annual bone loss at the total hip was −0.6%, which was significantly associated with decreased kidney function. In 404 men in the Mr Os Study,[14] the lowest quartile of eGFR (≤65 mL/minute) was associated with the highest annual BMD losses (−0.6%) at the total hip compared with the three highest quartiles of kidney function; the linear trend between severity of kidney dysfunction and bone loss was significant (p = 0.02). Finally, in 635 participants of the Canadian Multicenter Osteoporosis Study, Jamal and colleagues[29] investigated relationships between kidney dysfunction and 5-year bone loss at the lumbar spine, total hip, and femoral neck; annualized rates of bone loss were in the range of 1.4% to 1.6%, 1.2% to 1.3%, and 1.6% to 1.7%, respectively.

Our study confirms and extends these previous investigations. Participants were representative of patients cared for in a general nephrology practice, in that they had a broad range of kidney failure, including end-stage disease, and they had biochemical evidence of renal osteodystrophy. DXA detected annual rates of bone loss at the total hip in the range reported by previous investigations[14-16, 29] and at the upper limit of that reported for women in early postmenopause.[28] We also reported that at the ultradistal radius site, average bone loss was −2.4% per year, more than 4 times higher than that reported in bisphosphonate trials.[28] However, we did not detect a trend between kidney disease severity and loss of areal BMD. This is likely because the sample size of our hemodialysis population was small.

Our study also clarifies that the bone loss detected by DXA was localized to the cortical compartment. These findings are relevant because cortical bone is an important component of bone mechanical competence.[10, 12, 13, 31-40] Using transiliac crest bone biopsies and quantitative histomorphometry in postmenopausal women with and without vertebral fracture, Qiu and colleagues[35] demonstrated that low cortical thickness is at least as good as any index of cancellous bone at discriminating between subjects with and without fracture and that if both cortical and cancellous mass are reduced, the effect on fracture risk is synergistic. Melton and colleagues[36] used central QCT of the lumbar spine in postmenopausal women with and without vertebral facture and demonstrated that the thin cortical envelope of the vertebral bodies carried one-half the compressive load, similar to a study of cadaveric vertebral bone.[37] Pistoia and colleagues[40] simulated bone atrophy affecting multiple combinations of bone compartments. Reductions in cortical thickness had a greater negative impact on whole bone strength than reductions in either trabecular number or thickness. Previous studies by our group[10, 13] and others[12, 38] in CKD patients with and without fracture have demonstrated cross-sectional associations between cortical bone and fracture. In a seminal cross-sectional study by Jamal and colleagues,[38] cortical geometry and volumetric BMD assessed by conventional pQCT was associated with fracture in hemodialysis patients, although associations between cortical and trabecular microarchitecture and fracture could not be assessed because of the low resolution of pQCT (∼350 µm). Studies using HRpQCT have reported that smaller cortical area and thinner cortices at the radius[10-13] and tibia[10, 11, 13] and lower cortical density at the tibia[10, 13] were significantly associated with fracture; the area under the curve for fracture discrimination was highest for tibia cortical thickness (0.78).[13] A recent small study of men and women on hemodialysis compared with age- and sex-matched controls reported that hemodialysis patients had decreased cortical BMD and thinner cortices, and women had increased cortical porosity.[41] Application of finite element analysis, a computational measure of bone mechanical competence, to HRpQCT data sets demonstrated that trabecular load share was increased in both men and women on hemodialysis compared with controls, suggesting decreased cortical contribution to overall bone mechanical competence.[41] Our current study demonstrates that CKD is associated with cortical loss at both weight-bearing and non-weight-bearing sites. These findings are concerning, especially considering that the peripheral skeleton is 85% cortical bone and that cortical bone has important contributions to whole bone strength.[39, 40] It is also important to note that we did not detect progressive defects in trabecular bone. This may have been owing to our cohort's older age or to the postmenopausal status of all enrolled women.

Our study also sheds light on the biochemical mechanisms of cortical loss, namely hyperparathyroidism and increased remodeling rates. Cross-sectional studies of CKD patients have reported that hyperparathyroidism and increased levels of remodeling markers are associated with low areal BMD by DXA,[13, 42] low cortical and trabecular volumetric BMD both by conventional[43] and high-resolution[13, 44] pQCT, and abnormal bone geometry and microarchitecture by HRpQCT.[13, 44] Few longitudinal studies have assessed the impact of biochemical markers on bone loss. Jamal and colleagues[29] reported that elevated PTH concentrations did not predict bone loss at the spine or hip in CKD patients participating in the Canadian Multicenter Osteoporosis Study. We report the novel finding that levels of PTH, 25-OHD, BSAP, osteocalcin, P1NP, Trap5b, and CTX predicted cortical deterioration at the radius and tibia as assessed by HRpQCT.

In an exploratory analysis, we reported that severity of CKD was associated with more rapid bone loss. Cross-sectional studies have been discrepant, reporting that severity of kidney dysfunction may[42] or may not[45] be related to lower areal BMD measured by DXA. Rix and colleagues[42] reported that patients with the most severe kidney dysfunction had the lowest areal BMD at the spine, hip, and forearm. However, in an analysis of the National Health and Nutrition Examination Survey, Hsu and colleagues[45] reported that low total hip areal BMD in patients with more severe CKD was because of traditional osteoporosis risk factors rather than kidney function per se. Longitudinal epidemiologic studies of community-dwelling participants have reported that loss of areal BMD at the spine and hip are directly related to severity of kidney failure.[14-16, 29] By HRpQCT, we detected an independent effect of hemodialysis on increased severity of cortical porosity.

Our study has several limitations. Although our cohort included a large number of patients, its sample size was insufficient to perform multivariable analysis within each CKD stage. However, we demonstrated significant trends in bone loss according to hemodialysis status. DXA imaging of the central skeleton does not have sufficient resolution to measure cortical and trabecular changes separately. Therefore, the lack of associations between changes in areal BMD of the spine and hip and biochemical markers of bone metabolism may reflect technical limitations of DXA rather than a true lack of associations. Future investigations should use central QCT imaging to measure cortical and trabecular changes separately. We did not obtain longitudinal data in a healthy control group. However, it is unlikely that rates of bone loss would differ significantly between a locally recruited healthy control group and the thousands of participants who have been enrolled in numerous prospective epidemiologic and bisphosphonate trials. Although significant bone loss at the femoral neck and the predominantly cortical one-third radius was not detected, the rates of loss at those sites were less than or near the limit of DXA precision in our laboratory. Thus, a larger sample size would be needed to detect significant bone loss at those skeletal sites. However, regardless of sample size, these data attest to the relevance of using high-resolution imaging methodologies to describe microstructural mechanisms of bone loss, particularly when there may be differential effects on the cortical and trabecular compartments. The P1NP assay used in our investigation detects both trimeric and monomeric forms. Monomeric P1NP accumulates with more severe kidney dysfunction, which may be problematic in HD patients.[46-48] However, despite this limitation, P1NP, adjusted for HD status, remained an independent predictor of bone loss. This finding requires confirmation in larger studies. Finally, we did not measure FGF-23 and sclerostin, which may also affect bone turnover in CKD.

In conclusion, we have found that CKD is associated with significant cortical loss that is related to hyperparathyroidism and higher serum concentrations of bone turnover markers. Future studies are needed to assess the skeletal impact of treatments that lower levels of PTH and/or decrease bone turnover on cortical thickness and porosity and overall bone strength in patients on and off dialysis. In addition, the impact of cortical loss at the central skeleton and its association with vertebral and hip fracture risk remains to be explored.

Acknowledgments

  1. Top of page
  2. ABSTRACT
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgments
  9. References

This research was supported by grants from the National Institutes of Health: K23 DK080139 (TLN), K24 AR052665 (ES), and the National Center for Advancing Translational Sciences through Grant Number UL1 TR000040. In addition, this work was supported by an Amgen Young Investigator Award (TLN), the International Society for Clinical Densitometry (TLN), and a Columbia University Herbert Irving Award (TLN).

Authors' roles: Study design and conduct: TLN, DJM, and ES. Patient recruitment and data interpretation: TLN, EMS, AZ, KKN, DJM, SC, and ES. Data collection and QA: TLN, ED, SC, KKN, XSL, and SB. Drafting manuscript: TLN, DJM, and ED. Revising manuscript content: TLN and ES. Approving final version of manuscript: TLN and ES. TLN and DJM take responsibility for the integrity of the data analysis.

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  4. Materials and Methods
  5. Results
  6. Discussion
  7. Disclosures
  8. Acknowledgments
  9. References
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