Increased bone turnover is associated with protein and energy metabolism in adolescents with sickle cell anemia

Maciej S. Buchowski1,3, F. Alexander de la Fuente1, Paul J. Flakoll4, Kong Y. Chen3, and Ernest A. Turner2

1 Center for Nutrition and Department of Family Medicine, and 2 Comprehensive Sickle Cell Center, Meharry Medical College, Nashville 37208; and Departments of 3 Medicine and 4 Surgery at Vanderbilt University Medical Center, Nashville, Tennessee 37232


    ABSTRACT
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

Contribution of bone turnover to the hypercatabolic state observed in sickle cell anemia is unknown. We examined the association between markers of bone turnover and basal rates of whole body protein turnover and energy expenditure in 28 adolescents with homozygous sickle cell anemia (HbSS) and in 26 matched controls with normal phenotype (HbAA). Whole body protein breakdown and synthesis were measured using a stable isotope of [15N]glycine, resting energy expenditure was measured by whole room indirect calorimetry, and the rate of pyridinoline cross-link (PYD) excretion in urine and fasting serum levels of the type I procollagen carboxy-terminal propeptide (PICP) were measured with commercial kits. Urinary PYD and serum PICP were significantly elevated in HbSS patients. The increase in procollagen synthesis, indicated by high levels of PICP, was significantly correlated with increased whole body protein synthesis. The increase in type I collagen degradation, indicated by high PYD excretion, was significantly correlated with increased protein breakdown. We conclude that increased rates of bone turnover contribute to the increased rates of protein turnover and energy expenditure observed in adolescents with homozygous sickle cell anemia.

sickle cell disease; protein turnover; energy expenditure; bone remodeling


    INTRODUCTION
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

THE RESEARCH PROBLEM that this study addressed was to quantify a potential contribution of bone turnover to the hypermetabolic state observed in sickle cell anemia. This genetic disorder is caused by a single point mutation that leads to the replacement of glutamic acid with valine in position 6 on the beta -chain of hemoglobin (17). This altered hemoglobin (HbS) tends to polymerize when deoxygenated, distorting erythrocytes into a rigid, fragile sickle shape characteristic of a group of disorders known as sickle cell disease. Individuals who are homozygous for HbS have sickle cell anemia (HbSS). The cardinal pathophysiological feature of HbSS is a chronic hemolytic anemia and intracellular gelation or polymerization of the erythrocyte, resulting in shorter cell survival compared with the normal red blood cell (16). Resulting tissue injury is usually produced by hypoxia secondary to the obstruction of blood vessels by an accumulation of sickled erythrocytes (15). The effects of this injury are widespread and severe but can be particularly significant in the skeletal system. The most dramatic skeletal effects of sickle cell disease are marrow infarction (11, 22), osteonecrosis (13, 22), and expansion of the medullary bone space (22), all of which may increase the turnover of bone.

Previously, we (7-9) and others (2, 3, 31, 34) have reported that resting energy expenditure is higher in sickle cell disease. The increased rates of whole body protein breakdown and synthesis likely contribute to this increase. The clinical consequences of this hypermetabolic state are the slower growth rate and delayed sexual development often seen in children and adolescents with HbSS. We have shown that ~50% of the increase in resting energy expenditure in sickle cell disease patients could be accounted for by the enhanced energy cost of protein turnover (7). We have also estimated that Hb synthesis accounts for <20% of this increase. Therefore, it is reasonable to assume that higher whole body protein turnover in HbSS may be related to other metabolic events, including the elevated metabolic demands of an expanded bone mass caused by chronic hemolytic anemia. However, the potential contribution of bone remodeling to the observed increase in protein turnover and to the consequent increase in energy expenditure in HbSS has not been elucidated. Thus the null hypothesis was that rates of bone formation and resorption are not statistically different in HbSS and HbAA adolescents and are not related to whole body protein turnover and resting energy expenditure. To test this hypothesis, we measured basal rates of whole body protein synthesis and breakdown and resting energy expenditure, and rates of bone formation and resorption in a group of adolescents with HbSS and in a group of control subjects with a normal (HbAA) phenotype. Plasma concentration of type I procollagen carboxy-terminal propeptide (PICP), the major collagen produced by osteoblasts during bone formation, and urinary excretion of urinary pyridinoline cross-links (PYD) formed from type I collagen during bone resorption were used as biomarkers of bone turnover.


    MATERIALS AND METHODS
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

Study Population

A group of 28 African-American adolescents with HbSS was identified and screened for participation in the study at the Sickle Cell Clinic of the Comprehensive Sickle Cell Center at Meharry Medical College in Nashville, TN and from the MidSouth Sickle Cell Clinic in Memphis, TN. The group included 14 boys (14-18 yr old) and 14 girls (14-18 yr old). Additionally, 26 African-American adolescents who did not carry the HbS gene or any other hemoglobinopathy were matched for gender, Tanner stage, weight, and fat-free mass to serve as control subjects for the study. Each participant's Hb genotype was determined using standard electrophoretic methods (1) to confirm the presence of HbSS, in which both genes coding for the beta -chains of Hb produce HbS, or normal HbAA, in which both genes code for HbA (32). Subjects received written and verbal information about the nature and purpose of the study, and those who were eligible, and agreed, to participate signed informed consents according to the Declaration of Helsinki. The form was approved by both Meharry Medical College and Vanderbilt University School of Medicine for procedures to be performed at the Vanderbilt University General Clinical Research Center.

Before participating in the study, subjects gave a medical history and underwent a complete physical examination. Participants were free of any apparent metabolic, skeletal, hepatic, and renal dysfunction as confirmed by blood tests. They were not taking drugs known to affect energy metabolism and were nonsmokers. Female subjects were not pregnant, as determined by a serum pregnancy test, and were studied between days 3 and 12 after the onset of menses (follicular phase) to eliminate the influence of menstrual function on energy expenditure. HbSS subjects were studied in the steady state, i.e., they were not experiencing a sickle cell crisis during the study, nor had they experienced a painful crisis for 28 days before the study.

Study Protocol

All subjects reported to the General Clinical Research Center after a 10-h overnight fast. After initial admission, they were transferred to the whole room indirect calorimeter, where they were asked to engage in a 24-h protocol involving standard daily activities and a 2-h nonintensive exercise protocol. The room calorimeter is an airtight environmental room measuring 2.6×3.4×2.4 m3 and containing 19,500 liters in net air volume. Room temperature is precisely controlled (22.5 ± 0.2°C). Oxygen consumption (VO2), carbon dioxide production (VCO2), air flow rate, temperature (inside and ambient), barometric pressure, and humidity of air are sampled 60 times/s and integrated at the end of each minute to calculate energy expenditure (EE) (38). The room calorimeter is equipped with a bed, desk, chair, toilet, sink, telephone, television, VCR, and stereo system. A step exercise platform and a computer-monitored stationary bike are available inside the room. The exercise protocol included walking and stepping that were close in intensities to leisure activities that participants would perform in a free-living environment. All subjects exercised at the same pace and speed; however, they were instructed to shorten any exercise segment if the tasks were too difficult to perform. Subjects were free to view television, read, write, walk, and perform personal care activities or to exercise with the stationary bicycle, step platform, and aerobic tapes as much as they would in their normal daily routine. Subjects were not allowed to eat or drink after 2100 and were asked to go to bed between 2130 and 2200. On the following morning, resting energy expenditure was measured when the subject was still inside the calorimeter, and a fasting blood sample was drawn at 0700 after he or she left the calorimeter.

Body Composition

Body weight was measured to the nearest 0.05 kg with a digital scale. Fat mass and fat-free mass were determined by hydrodensitometry. The subjects were weighed underwater, and their residual lung volumes were measured using the nitrogen dilution technique while the subjects were submerged in water to chest level. Body fat percentage was calculated from body density using Schutte's equation; fat mass and fat-free mass were calculated from body mass (9).

Whole Body Protein Turnover

Protein kinetic studies were done on the basis of the method of Picou and Taylor-Roberts (23) by use of prime/intermittent oral doses of [15N]glycine tracer (99% atoms, Cambridge Isotopes, MA) and the measurement of enrichment urinary urea and ammonia (23). A priming dose of 3.75 mg of [15N]glycine per kg of body weight was given at 0800. Starting 5 h later, from 1300 until 2200, further doses of 0.6 mg [15N]glycine/kg were given every 3 h. A sample of urine was collected before [15N]glycine was given and then every 3 h. The volume was measured, and an aliquot was frozen at -80°C. The method requires that the abundances of 15N urinary urea and ammonia reach a plateau within 48 h (18). This determination was based on the isotopic enrichment curves and was defined as the first plateau that extended for at least four points (12 h). The mean coefficient of variation (CV) of plateau values was 4.1 and 4.8 for the HbSS and HbAA, respectively. The rate of entry of nitrogen (Q) into the metabolic nitrogen pool (flux) was calculated from the mean plateau value, with the assumption that the fraction of the administered isotope that was excreted as urinary 15N equaled the fraction of total amino nitrogen entering the metabolic pool excreted as urinary urea and ammonia nitrogen (39). Protein breakdown and synthesis were calculated from the equation of Picou and Taylor-Roberts (23): Q = I + B = S + E, where Q is nitrogen flux, I is nitrogen intake, B is protein breakdown, S is protein synthesis, and E is total urinary nitrogen. The rate of protein breakdown was calculated by subtracting the rate of nitrogen intake from nitrogen flux, and protein synthesis was estimated as the difference between nitrogen flux and the urinary excretion of urea and ammonia nitrogen. 15N enrichment of urea nitrogen was measured by a mass spectrometer (Metabolic Solutions, Nashua, NH) after correction for background values determined in a urine sample taken immediately before the test. Starting at 0800, food was given at times concomitant with tracer intake. The food provided 1.02 ± 0.04 g of protein and 141 ± 3.67 kJ · kg body wt-1 · day-1. Actual intake was determined by weighing all the foods eaten and analyzing their energy and nutrient content with Food Processor Professional Nutrition Analysis and Software System (ESHA Research, Salem, OR).

Analytical Procedures

After an overnight fast (>= 10 h) in the room calorimeter, blood was collected in evacuated blood collection tubes by venipuncture from an antecubital vein at 0700. The tubes were placed on ice, allowed to clot for 30 min, and directly centrifuged for 5 min in a refrigerated (4°C) centrifuge at a speed of 3,000 g. Serum samples were immediately stored at -80°C until analysis. Whole blood Hb concentration, ferritin, red blood cell folate, albumin, thyroid-stimulating hormone (TSH), testosterone, and estradiol were measured at Vanderbilt's Hospital Laboratory. These analyses were performed to make inter- and intragroup comparisons. Urine samples were collected at specified times for the 15N analyses, and after thorough mixing of the samples, aliquots of the 24-h urine collections were analyzed for urea nitrogen, creatinine, and electrolytes (sodium and potassium). Urinary urea and ammonia nitrogen and creatinine were measured in the Core Laboratory of the General Clinical Research Center. Creatinine served to ensure completeness of urine collection and to normalize concentrations of the PYD biomarker between subjects.

Biomarkers of Bone Metabolism

PICP assay. The Prolagen-C assay (Metra Biosystems, Mountain View, CA) for PICP was used to measure bone formation activity. Prolagen-C is a sandwich enzyme immunoassay that uses a monoclonal anti-PICP antibody coated on a microtiter plate, a rabbit anti-PICP antiserum, a goat anti-rabbit alkaline phosphatase conjugate, and a p-nitrophenyl phosphate substrate to measure human serum PICP. The within-assay CV was 6.7% and the between-assay CV was 8.5%.

PYD assay. The Pyrilinks assay (Metra Biosystems) was used to measure PYD, a marker of bone resorption activity. This is a competitive enzyme immunoassay in which cross-links in the urine sample compete for pyridinium cross-link-specific antibodies with pyridinium cross-links coated on a test strip. The reaction is detected with a p-nitrophenyl phosphate substrate, and the results are corrected for urinary concentration by creatinine. The within-assay CV was 7.1% and the between-assay CV was 4.4%.

Energy Balance

Total EE. Total EE was obtained by measuring the total amount of oxygen used (VO2) and carbon dioxide expelled (VCO2) during each subject's 24-h stay in the room calorimeter. The VO2 and VCO2 were calculated by multiplying measured changes in O2 and CO2 concentration in the air sampled from the inside of the room calorimeter by the flow rate of the purged air. This allowed variables such as energy expenditure to be calculated on a minute-by-minute basis. Detailed methodology of the room calorimeter has been previously reported (38).

Resting EE. Resting EE (REE; kJ/min) was defined as the average EE during a 30-min period while the subject lay quietly in bed on the morning after an overnight sleep and 10 h of fasting. The EE during periods when body motion was detected by a precision force platform was excluded from REE calculations (38). Regression models of resting EE based on predictors of fat-free mass and fat mass were used rather than division of REE by fat-free mass, because division by fat-free mass does not account for nonzero intercepts typically observed in these regressions (9).

Statistical Analysis

Sample size was calculated using data from our preliminary studies showing that protein synthesis was 5.23 ± 0.80 mg/min in HbAA and 6.89 ± 1.15 mg/min in HbSS adolescents. Using a two-sided t-test with alpha -level of 0.05, we calculated that 10 participants would provide 90% statistical power to detect differences between HbSS and HbAA within each gender. We used a conservative number of >= 12 adolescents in each HbSS status · gender subgroup because of uncertainty regarding the effect of other variables.

Sample means are presented ± 1 SD. Continuous variables between subjects were evaluated using independent sample t-tests. Multiple linear regression analysis was performed on protein breakdown, protein synthesis, and REE by use of a backward elimination approach. Covariates that were considered for inclusion in the modeling were HbSS status (0 = HbAA control, 1 = HbSS patient), gender (0 = male, 1 = female), fat-free mass, fat mass, age, PYD, PICP, and plausible interactions among these. Age was treated as a continuous variable. Covariate centering and multiplication by a constant were used for ease of regression coefficient interpretation. Fat-free mass was centered at 45 kg and divided by 10, and age was centered at 16. Thus the intercept term in a model that includes fat-free mass is the fitted dependent variable response for a 16-yr-old subject with fat-free mass equal to 45 kg (and other covariates equal to zero, e.g., HbAA boy). Furthermore, the coefficient for fat-free mass covariate in such models represents fitted differences in the dependent variable per 10-kg differences in fat-free mass. Residual analysis was performed for evaluation of model adequacy and outliers. A P value <0.05 was used for inclusion of terms in the regression and to indicate statistical significance.


    RESULTS
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

Subject Characteristics

Descriptive data for study participants are presented in Table 1. There were no differences between HbSS patients and controls in body weight, age, fat-free mass, and fat mass. Hb concentration was significantly (P < 0.001) lower in HbSS patients than in HbAA controls (average 8.9 ± 1.8 vs. 13.7 ± 1.1 g/dl, respectively). Plasma levels of red blood cell folate, albumin, and thyroid-stimulating hormone were similar in HbSS and controls. There was no difference between HbSS and HbAA controls in plasma levels of testosterone in boys and estradiol in girls.

                              
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Table 1.   Subject characteristics

Serum PICP Concentration and HbSS

Results of the multiple regression analysis of serum PICP levels are summarized in Table 2. On average, serum PICP levels were higher in HbSS patients than in HbAA controls (537.9 ± 172.5 and 189.1 ± 45.2 ng/ml, respectively; P < 0.0001). On the basis of this analysis, predicted serum PICP levels adjusted for age and gender were higher in HbSS boys and girls compared with HbAA controls (difference = 1,578 and 928 ng/ml for boys and girls, respectively; both P < 0.0001). The regression equation is PICP = 163.6 + 452.7 · HbSS for a 16-yr-old boy and PICP = 197.1 + 261.4 · HbSS for a 16-yr-old girl. A negative linear association was observed between serum PICP levels and age in HbSS boys and girls, with adjustment for fat-free mass. The strength of this association was greater in HbSS boys compared with girls (slope -72.01 and -41.1 ng · ml-1 · yr-1 of age, respectively; P = 0.002). This difference was not observed in HbAA controls. The overall fitted equation is PICP = 198.34 + 1,287 · SCD - 186.87 · gender - 120.4 · HbSS · gender - 21.46 · (age - 16) - 55.7 · HbSS · (age - 16). Results of this analysis are presented in Fig. 1.

                              
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Table 2.   Results of multiple regression models for type I procollagen carboxy-terminal propeptides



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Fig. 1.   Serum concentration of type I procollagen carboxy-terminal propeptide (PICP) vs. age in boys (A) and in girls (B). Regression equations: A: for HbSS boys, PICP = 2,029.1* - 88.2* · age; for HbAA boys, PICP = 509.2 - 20.3 · age. B: for HbSS girls, PICP = 1,235.3* - 49.8* · age; for HbAA girls, PICP = 379.0 - 11.9 · age. *Significantly different from HbAA controls (P < 0.001).

Urinary PYD Excretion and HbSS

Table 3 presents the results of the multiple regression analysis of PYD excretion. Urinary PYD excretion was higher in HbSS patients than in HbAA controls (89.6 ± 19.3 and 38.5 ± 14.5 nmol/mmol creatinine, respectively; P < 0.0001). Predicted difference between HbSS and HbAA, adjusted for age and fat-free mass, was significant in both genders (difference = 45.6 and 55.5 nmol/mmol creatinine for boys and girls, respectively; both P < 0.0001). The regression equation is PYD = 32.6 + 3.72 · HbSS for a 16-yr-old boy and PYD = 43.6 + 16.2 · HbSS for a 16-yr-old girl. A negative linear association between urinary PYD and age was observed in both genders, with adjustment for HbSS status (P < 0.0001). The strength of this association was similar in boys and girls (slope = -4.66 and -5.95 nmol · mmol creatinine-1 · yr of age-1, respectively; P = 0.537). The overall fitted regression equation is PYD = 29.9 - 8.41 · (age - 16) + 5.53 · (fat-free mass - 45/10) + 14.4 · gender + 3.32 · HbSS · (age - 16). These results are illustrated in Fig. 2.

                              
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Table 3.   Results of multiple regression models for pyridinium cross-links



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Fig. 2.   Urinary pyridinium cross-links (PYD) vs. age in boys (A) and in girls (B). Regression equations: A: for HbSS boys, PYD = 156.7* - 4.7 · age; for HbAA boys, PYD = 107.8 - 4.5 · age. B: for HbSS girls, PYD = 191.4 - 5.8 · age; for HbAA girls, PYD = 182.1 - 8.8 · age. *Significantly different from HbAA controls (P < 0.01).

Serum PICP and Whole Body Protein Synthesis

Table 4 presents a multiple regression analysis of the relationship between whole body protein synthesis and serum PICP. In HbSS patients, there was a positive linear relationship between PICP and whole body protein synthesis after adjustment for fat-free mass and age (overall R2 = 0.918, P < 0.0001). The strength of this association was similar in HbSS boys and girls. The difference between HbSS and HbAA controls was significant (P < 0.0001) and was similar for boys and girls (difference = 0.175 and 0.194 g · day-1 · PICP-1, respectively). In both genders, fat-free mass was a significant predictor of protein synthesis, as expected (P < 0.0001). Protein synthesis was higher in HbSS patients than in HbAA controls (difference = 62.8 g/day; P < 0.0001). The overall regression equation: whole body protein synthesis (g/day) = 196.13 + 62.8 · (fat-free mass - 45/10) + 62.78 · HbSS + 0.124 · PICP. These results are illustrated in Fig. 3.

                              
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Table 4.   Results of multiple regression model for whole body protein synthesis



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Fig. 3.   Residual-residual plot between whole body protein synthesis and serum PICP, after both have been adjusted for effects of fat-free mass and age. Regression equations: for HbSS, residual protein synthesis = 0.39* + 0.57 · residual PICP; for HbAA, residual protein synthesis = - 0.43 + 0.55 · residual PICP. *Significantly different from HbAA controls (P < 0.001).

Urinary PYD Excretion and Whole Body Protein Breakdown

Results of the multiple regression analysis of urinary PYD excretion and protein breakdown are presented in Table 5. In HbSS patients, there was a linear relationship between PYD and protein breakdown, with adjustment for fat-free mass and age, whereas no such relationship was observed in HbAA controls. The strength of this association was similar in HbSS boys and girls. In both genders, the difference between HbSS and HbAA controls was significant (difference = 1.17 and 0.846 g · day-1 · PYD-1 for boys and girls, respectively; both P < 0.0001). Fat-free mass was an important predictor of protein breakdown (P < 0.0001). On average, HBSS patients demonstrated a higher protein breakdown than HbAA controls, with adjustment for fat-free mass and age (difference = 66.9 g/day; P < 0.0001). The overall fitted regression equation: whole body protein breakdown (g/day) = 205.7 + 55.6 · (fat-free mass - 45/10) - 16.1 · (age - 16) + 3.94 · HbSS - 0.803 · gender + 0.204 · PYD + 0.592 · HbSS · PYD + 0.253 · PYD · (age -16). These results are illustrated in Fig. 4.

                              
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Table 5.   Results of multiple regression model for whole body protein breakdown



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Fig. 4.   Residual-residual plot between whole body protein breakdown and PYD excretion, after both have been adjusted for effects of fat-free mass and age. Regression equations: for HbSS, residual protein breakdown = 0.41* + 0.51* · residual PYD; for HbAA, residual protein breakdown = - 0.74 + 0.13 · residual PICP. *Significantly different from HbAA controls (P < 0.001).

Bone Turnover, Protein Turnover, and REE

Correlations of PYD, PICP, protein breakdown and synthesis, and REE are presented in Table 6. REE was significantly correlated with protein synthesis and breakdown, as expected (both P < 0.0001). Both markers of bone turnover were correlated with REE (P < 0.001). A multiple regression analysis showed that REE was higher in HbSS than in HbAA after adjustment for fat-free mass, fat mass, gender, and age (difference = 0.843 ± 0.107 kJ/min, R2 = 0.813, P < 0.0001). The overall regression equation: REE (kJ/min) = 4.109 + 0.916 · HbSS + 0.609 · fat-free mass, in boys, and REE (kJ/min) = 3.565 + 0.504 · HbSS + 0.627 · fat-free mass + 0.042 · fat mass - 0.215 · (age - 16) in girls. Results of the multiple regression analyses showed a linear relationship between protein synthesis and protein breakdown and REE after adjustment for fat-free mass and age (both P < 0.0001). The relationship between REE and protein synthesis is presented in Fig. 5.

                              
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Table 6.   Pearson correlations: PICP, PYD, protein breakdown, protein synthesis, and resting energy expenditure



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Fig. 5.   Residual-residual plot between whole body protein synthesis and resting energy expenditure, after both have been adjusted for the effect of fat-free mass. Regression equations: for HbSS, residual protein synthesis = 0.53* + 0.42* · residual resting energy expenditure; for HbAA, residual protein synthesis = - 0.77 + 0.13 · residual resting energy expenditure. *Significantly different from HbAA controls (P < 0.001).


    DISCUSSION
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
REFERENCES

In this study we examined the association between biomarkers of bone metabolism, protein turnover, and REE in adolescents with HbSS. Plasma concentration of PICP, a marker of bone formation, and urinary excretion of PYD, a marker of bone breakdown, were higher in HbSS than in HbAA matched controls. These results demonstrate that the rate of bone turnover is more rapid in adolescent patients with HbSS. Furthermore, the results of this study support the hypothesis that, in adolescents with HbSS, higher rates of bone formation and resorption are associated with the higher rates of whole body protein turnover and resting energy expenditure.

Type I collagen is the major collagen produced by osteoblasts, representing >90% of the organic matrix. Deposition of type I collagen can be assessed by measuring the serum concentration of PICP, a heterotrimeric, globular glycoprotein of molecular weight 100,000 (4, 12, 36). PICP is removed by specific endoproteinases from the collagen molecule proper during synthesis (4, 12, 36). Some studies have shown that serum PICP is significantly correlated with rates of bone deposition and could be used as a sensitive indicator of bone formation (12). In the present study, we found that PICP levels were significantly higher in HbSS adolescents than in HbAA controls. These results are in contrast to a study by Bolarin et al. (5), who showed a lack of similar increases in HbSS adults. This discrepancy is most likely related to the subjects' age, because it has been demonstrated that age can affect serum levels of collagen markers, including PYD and PICP, particularly during the pubertal development and parallel growth spurt in boys and girls (4, 30, 36). Rotteveel et al. (30) recently reported that PICP levels in girls tended to be higher during midpuberty, whereas in boys they peaked at the end of puberty. This observation may explain the significant gender difference in PICP levels adjusted for age found in HbSS adolescents in our study.

Previous studies also suggested a possible relationship between biomarkers of synthesis and deposition of collagen and sex hormones in growing adolescents. Some of these studies have shown a significant correlation between PICP and testosterone in boys and estradiol in girls (4), but another found no such correlation (30). However, because there was no significant difference in testosterone and estradiol levels between HbSS and HbAA boys and girls, respectively, these hormones most likely were not a significant factor in the present study. On the basis of these data, we postulate that bone formation might be higher in HbSS adolescents compared with matched HbAA controls.

Bone resorption can be assessed by measuring urinary excretion of pyridinium cross-links (PYD). These cross-links are formed by lysyl oxidase between certain lysine and hydroxylysine side chains on adjacent collagen molecules; they are present in mature type I collagen and, when it is broken down, released into the circulation (10). Fragments containing PYD are readily cleared by the kidney and are not degraded in vivo (10). Therefore, it has been concluded that excretion of PYD in urine is a useful index in assessing bone resorption (10, 19). In the present study, we found that PYD excretion was higher in HbSS adolescents than in HbAA controls. These results are difficult to compare with others, because we are not aware of similar data reported. We also found that PYD excretion is independent of gender and is negatively correlated with age. These relationships, present in both HbSS and HbAA control groups, are parallel to results reported by Rauch et al. (25) in healthy children, showing that, after reaching a peak at ~14 yr, the excretion of PYD decreases with advancing adolescence to reach nearly adult levels by age 18. Similarly to previously reported results, we did not find significant gender differences in PYD excretion (25). It has also been postulated that gonadal hormones might be related to PYD excretion (4); however, we did not find significant differences in the level of estradiol in girls and testosterone in boys between HbSS and HbAA. Thus the observed difference in PYD excretion between HbSS and HbAA is related to the disease status rather than gonadal hormone level, suggesting higher bone resorption in HbSS.

It has been shown previously in our studies (7, 8) and by others (2) that whole body protein turnover is elevated by 40-100% in HbSS and is responsible, in part, for the hypermetabolic state observed in sickle cell disease. The 45% increase in protein breakdown and 49% increase in protein synthesis observed in the present study fall in this range. Elevated protein turnover in HbSS has been linked to increased hematopoiesis (2, 7) and marrow hyperplasia (2), both caused by the significantly reduced life span of the red blood cell in sickle cell disease (21). This increase, however, does not account for the entire increase in protein turnover observed in sickle cell disease. In fact, it has been calculated in different studies that hemoglobin synthesis contributes 2-4% and 12% of total protein synthesis in HbAA and HbSS individuals, respectively (2, 3, 7). Other postulated mechanisms include increased turnover of non-red blood cell proteins, such as those found in skeletal muscle, cardiac muscle, liver, or the gastrointestinal tract (2). There are no consistent data available, however, that would either support or refute the contribution of these tissues to the increased whole body protein turnover in HbSS. In the present study, we tested the hypothesis that elevated protein turnover in HbSS adolescents is associated with increased bone turnover. Our results (see Figs. 3 and 4) clearly support this hypothesis, because whole body protein turnover, as measured by whole body protein synthesis and breakdown, was indeed positively correlated with biomarkers of both bone resorption (PYD) and bone formation (PICP) (both P < 0.0001). Although it is difficult to determine the contribution of bone to whole body protein synthesis in our study, investigators using an animal model demonstrated that bone protein accounts for ~8% of whole body protein synthesis (24). Thus a substantial increase in bone protein synthesis would have significant impact on whole body protein turnover.

Several factors could potentially contribute to the postulated increase in bone resorption and formation in HbSS adolescents. First, hemolytic anemia can lead to a compensatory marrow hyperplasia and expansion of the medullar bone space (22). Second, bone capillaries could be blocked by sickled red cells causing infarction, a common occurrence in sickle cell disease. Bone marrow infarcts would exacerbate hemolytic anemia and lead to swelling and extreme tenderness over the affected bone (22). Furthermore, repair of marrow infarction involves deposition of bone on the medullar side of the cortex (13). Third, osteonecrosis can result from infarction of the cancellous trabecullae and adjacent marrow, usually in the femoral and humeral heads. The dead bone is gradually removed by osteoclasts and replaced by osteoblasts, and this may result in significant deformation and distortion of the bone (22). If any of these events occurs, the final metabolic consequence could be elevated protein breakdown and synthesis, generated by an increased rate of bone turnover. Our data support this notion, because both markers of bone turnover and rates of protein breakdown and synthesis were elevated in HbSS adolescents.

Previously we (7-9) and others (2, 3, 31, 34) have shown that REE is 15-20% higher in sickle cell disease patients than in normal controls. In this study, REE difference between HbSS and HbAA (adjusted for gender, fat-free mass, fat mass, and age) averaged 21%. Postulated mechanisms of this increase include elevated cardiac output, necessitated by the low oxygen-carrying capacity of the blood in sickle cell disease (2), and increased protein turnover (2, 7, 8). For example, we have estimated that ~50% of the increase in resting metabolic rate is due to increased protein synthesis requirements (8).

We explored the contribution of increased bone remodeling to elevated REE by calculating its contribution as a percentage of protein synthesis. The mean urinary excretion of PYD in HbSS patients was, on average, nearly twice as high as in the control group, whereas the concentration of PICP in HbSS adolescents was 2.7 times higher. Deposition of one molecule of type I collagen in the tissues leads to the release of one molecule of PICP into the circulation (27); thus serum PICP concentration should approximately parallel type I collagen synthesis. If we assume that our results indicate approximately a doubling of bone turnover, and that bones contribute 8% to total protein synthesis in normal humans, as animal studies would suggest (24), ~11% of total protein synthesis in HbSS adolescents can be attributed to bone metabolism. This would make the contribution of increased bone turnover to total body protein turnover similar to the postulated 12% contribution of increased Hb synthesis to total protein synthesis in HbSS (2). In the present study, the estimated daily energy cost of protein synthesis was 1,364 ± 353 vs. 1,050 ± 180 kJ/day in HbSS and HbAA, respectively. On the assumption that five molecules of ATP are required for each peptide bond, the energy cost of synthesis of 1 g of collagen would require 4.5 kJ or 1.076 kcal. Therefore, total daily energy cost of collagen synthesis (33 g in HbSS and 19 g in HbAA) would be ~150 ± 38 kJ in HbSS and 84 ± 14 kJ in HbAA. Because the increase in energy cost of collagen synthesis was 64 kJ and the increase in energy cost of whole body protein synthesis was ~314 kJ, ~20% of the increase in energy cost of protein synthesis was due to collagen synthesis.

Our study must be interpreted within the context of our experimental design. First, assessment of protein metabolism with [15N]glycine must be interpreted along with the understanding that flux of 15N into the urea pool is relatively slow. However, by use of a priming dose at the beginning of the study, steady state is achieved more rapidly and significantly reduces the study time. This method has previously been used successfully in HbSS (2) and under a variety of conditions such as surgery, aging, or malnutrition (37).

Another potential caveat concerns the reported circadian variations in urinary excretion of bone collagen cross-links and creatinine (6). However, our samples included 24-h collection of urine, thus eliminating the influence of possible circadian variations in PYD excretion.

Some reports have suggested that sickle cell disease is associated with hypogonadism, retarded sexual development, and delayed growth (14, 20), and that these associations have the potential to decrease bone turnover in adolescents. The sickle cell patients in this study, however, did not exhibit any developmental abnormalities, as determined by the Tanner staging and measurement of serum sex hormone levels. Furthermore, HbSS subjects were matched for weight- and height-limiting potential differences. Although including age in our analyses may have explained some of the association between HbSS, bone metabolism, protein turnover, and REE, including prepubertal and pubertal adolescents in future studies would be beneficial. These studies should also include a control group of patients with beta +-thalassemia intermedia who are also anemic and have a major expansion of the marrow space due to hyperactive hematopoiesis.

Finally, we have assumed that measured biomarker levels were directly linked to bone turnover. These markers, however, are indirect measures of bone deposition and resorption, and some caution must be used when evaluating their significance. For example, clearance of PICP depends on a liver endothelial cell mannose receptor (35); it is therefore possible that no simple linear relationship between serum PICP concentration and the rate of type I collagen synthesis exists. Although PYD in urine is thought to originate primarily from bone resorption, it could also contain cross-links from nonbone sources. Nevertheless, as pointed out by others (11, 38), using a combination of PICP and PYD allowed us evaluate both resorptive and formative events and to assess differences between HbSS and HbAA. Including other biomarkers of bone turnover and calcium and phosphorus balance, however, would be beneficial. In addition, we did not perform any histomorphometric or densitometric analysis of the skeleton of our study participants that could link our findings to changes in bones structure and density.

The knowledge gained from this study provides additional elements to our understanding of metabolic events occurring in sickle cell anemia. It also provides knowledge necessary for designing optimal nutritional regimens for adolescents with HbSS. Data clearly showed that markers of bone resorption and formation are elevated in HbSS adolescents. This increase is associated with increased whole body protein synthesis and breakdown, thereby suggesting increase in bone protein formation and breakdown. Furthermore, our data suggest that the increase in rates of bone turnover is associated with simultaneously observed elevation in REE. Thus observed increase in bone breakdown and formation most likely contributes to the elevated rates of protein turnover and EE in adolescents with HbSS. Future research is required to explain the mechanism of the observed increase in bone remodeling activity and to understand how these aberrations may affect the overall health status of HbSS children and adolescents, especially during puberty and growth spurts.


    ACKNOWLEDGEMENTS

We thank Dr. Winfred Wang and Ruth Williams from the St. Jude Hospital in Memphis for referral of sickle cell patients and for input regarding this research project. We also thank staff of the General Clinical Research Center at Vanderbilt University for help with this project, and Dr. Weiji Gao, Brenda Jarvis, Tiffany Chavous, LeMonica Lewis, and Karen Townsend for their technical help and expertise. Finally, we acknowledge our volunteers for their enthusiasm and participation in this study.


    FOOTNOTES

Funding for this research was provided by National Institutes of Health Grants HL-03530 (to M. S. Buchowski), HL-56867 (to P. J. Flakoll), General Clinical Research Center Grants RR-00095 (to Vanderbilt University) and RR-1179204 (to Meharry Medical College), Clinical Nutrition Research Unit Grant DK-26657 (to Vanderbilt University), and a Meharry Center of Excellence grant (to M. S. Buchowski and F. A. de la Fuente).

Address for reprint requests and other correspondence: M. S. Buchowski, Associate Professor, Center for Nutrition, Meharry Medical College, 1005 D. B. Todd Blvd., Nashville, TN 37208 (E-mail: maciej.buchowski{at}mcmail.vanderbilt.edu).

The costs of publication of this article were defrayed in part by the payment of page charges. The article must therefore be hereby marked "advertisement" in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

Received 16 August 2000; accepted in final form 27 November 2000.


    REFERENCES
TOP
ABSTRACT
INTRODUCTION
MATERIALS AND METHODS
RESULTS
DISCUSSION
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Am J Physiol Endocrinol Metab 280(3):E518-E527
0193-1849/01 $5.00 Copyright © 2001 the American Physiological Society




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