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© 2003 The American Society for Nutritional Sciences J. Nutr. 133:1224-1226, April 2003

Nutritional Methodology
Research Communication

Quantifying Human Calcium Absorption Using Pharmacokinetic Methods

Robert P. Heaney2

Osteoporosis Research Center, Creighton University, Omaha, NE

2To whom correspondence should be addressed. E-mail: rheaney{at}creighton.edu.


   ABSTRACT
TOP
 ABSTRACT
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 
Calcium absorption was measured simultaneously by tracer and pharmacokinetic methods in 12 men. The purpose of the study was to calibrate the area under the curve (AUC) for absorptive calcemia to permit comparison or pooling of pharmacokinetic data with tracer-derived estimates. Each subject was studied twice during intake of 500 mg calcium loads (as the carbonate salt), once without excipients, and once with a binder that impeded dissolution of the salt, reducing its absorbability and thereby providing a broad range of absorption values over which to calibrate the method. Various time periods were evaluated, with the best prediction being given by the AUC for the increment in serum calcium calculated over 9 h (AUC9). For net absorbed calcium (mmol) the relationship was given by 4.358 x AUC9 ± 0.820. The empirical regression coefficient was significant and the error of the estimate (0.820 mmol) acceptably small.

KEY WORDS: • calcium absorption • calcium absorption measurement • pharmacokinetic methods • area under the curve

True calcium absorption, i.e., unidirectional flux of calcium from gut lumen into blood, is most accurately measured using an oral calcium source intrinsically labeled with a suitable calcium isotope and quantifying the tracer that appears in blood, urine or body compartments after absorption is complete. The basic theory for this approach was devised by Bronner (1 ), an applied method described by deGrazia et al. (2 ) and various short-cut approximations developed by Heaney, Recker and others (3 –5 ). But tracer methods are not applicable to marketed products nor to many food sources of calcium because they often cannot be easily labeled.

Although extracellular fluid calcium concentration is tightly regulated, calcium absorption nevertheless does produce a measurable, if small, degree of calcemia that can be captured by pharmacokinetic methods [specifically, measurement of the area under the curve (AUC)]. The relationship between the quantity of calcium absorbed and such pharmacokinetic variables as AUC is more complex than usually encountered when measuring, for example, drug absorption. This is the case because the calcemia of absorption evokes physiologic responses that reduce calcium input into the blood from bone, thereby damping the calcemia of absorption. Nevertheless, the degree of calcemia that does occur would be expected to reflect the amount of calcium absorbed. Our goal in this investigation was to determine how well that relationship holds and to derive suitable parameters for estimating the absorption fraction from calcium pharmacokinetic data.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 LITERATURE CITED
 
Subjects.

Participants were 12 healthy men, 35.9 ± 5.1 y old, each studied twice using sources with differing absorbability (see below). The protocol was approved by the Creighton University Institutional Review Board and each participant gave written consent.

Protocol.

The test calcium source was ingested in the morning, midway through a low calcium breakfast providing ~1.88 MJ and 1.4 mmol calcium. Blood was drawn just before feeding and then at frequent intervals throughout the day (0.5, 2, 3, 5, 7, 9, 12 and 24 h). A low calcium lunch (<2.3 mmol) was consumed after the 5-h sample was taken. The median interval between duplicate tests in any given subject was 14 d. Except for control of calcium intake during the test day, there were no other dietary restrictions. The test calcium load was 12.5 mmol (500 mg), given as calcium carbonate formulated either as the pure salt loosely packed into gelatin capsules or as calcium tablets containing a resin binder that interfered with calcium carbonate disintegration/dissolution, thereby lowering its absorbability. The calcium carbonate for both sources was intrinsically labeled by the addition of 45CaCl2 to a solution of calcium chloride and then by precipitating the salt with a slight stoichiometric excess of sodium carbonate. The resulting powder was captured on a fritted glass filter, washed with distilled water and dried at 100°C before encapsulation or tableting. Tracer doses were on the order of 5 µCi (0.185 MBq) per test.

Measurements.

Serum stable calcium was measured in duplicate by atomic absorption spectrophotometry [AAnalyst 100, Perkin-Elmer, Norwalk, CT (within-assay precision: 0.73%)] and serum 45Ca by liquid scintillation counting (LS-3150T counter, Beckman Instruments, Fullerton, CA). The serum 45Ca values were expressed as specific radioactivity [i.e., as fraction of the administered dose (fxdose) of tracer/mmol calcium)]. True fractional calcium absorption was measured from the 5-h serum 45Ca concentration using established methods (3 ,4 ). Areas under the curves at various times after dosing (AUCt) for both 45Ca and stable calcium were calculated using the trapezoidal method. For both stable and radioactive calcium, we plotted the increment above baseline after source ingestion as the basis for calculating AUC. The dimensions of the AUC are (mmol · h)/L for stable calcium and (fxdose · h)/mmol for 45Ca.

Data analysis.

Because the sampling unit in this investigation was the individual test, not the participant, we used both tests in each subject to produce a total sample size of 24 tests, with a nearly continuous range of fractional absorption values varying from 0.131 to 0.439. AUC were calculated for different time intervals, and standard Pearsonian regression was used to derive parameters for the relationship between AUC and the true absorption fraction, as well as to test for the AUC interval that produced the best fit.


   RESULTS
TOP
 ABSTRACT
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 LITERATURE CITED
 
Serum calcium began to rise by 1 h, peaked at 5 h, and had returned to within 1.5% of the starting baseline value by 12 h (Fig. 1A ), when the calcemia was no longer significantly different from baseline. At its peak, the calcemia averaged only slightly >0.125 mmol/L (0.5 mg/dL), or a rise of ~5%. The serum tracer pattern was similar except that residual tracer remained easily detectable after the total calcium had returned to baseline (Fig. 1 B).



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  		FIGURE 1 Plot of the incremental calcemia in men after ingestion of a 12.5 mmol Ca load (A) for the 12 tests employing plain calcium carbonate and (B) for the incremental Ca specific activity (SpecAct) after ingestion of a 45Ca-labeled 12.5 mmol load. The error bars represent 1 SEM. The dimension for SpecAct is fraction of dose of tracer per mmol Ca. (Copyright Robert P. Heaney, 2003. Used with permission.)

 
When the 5-h calcium specific activity value was plotted against the 24-h AUC for the tracer specific activity (Fig. 2 ), r2 was 0.92, and the residual variation around the regression line was within the precision error of the 45Ca measurement at the tracer dose used. This very close fit indicates that the 5-h value captured essentially all of the information available from a full computation of the AUC. Such validation is useful in this context because it is the 5-h method that has been calibrated (3 ,4 ) against the double tracer method of deGrazia et al. (2 ), rather than the AUC.



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  		FIGURE 2 Plot of absorption fraction (AbsFx) calculated from the 5-h specific activity value against area under the curve to 24 h (AUC24) for serum specific radioactivity for all 24 tests in 12 men. (Copyright Robert P. Heaney, 2003. Used with permission.)

 
AUC for serum stable calcium was calculated over periods of 5, 7, 9 and 12 h, by which time, any residual calcemia had all but completely dissipated (Fig. 1 A). The true absorption fraction (AbsFx), calculated in each individual from the 5-h specific activity value, was plotted against the AUC calculated for the four time intervals. Although all correlations were significant, the best fit was given for AUC at 9 h (Fig. 3 ). The corresponding linear regression equation is as follows:



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  		FIGURE 3 Plot of absorption fraction (AbsFx) calculated from the 5-h calcium specific activity value against area under the curve to 9 h (AUC9) calculated for the rise in total serum calcium for all 24 tests in 12 men. (Copyright Robert P. Heaney, 2003. Used with permission.)

 
The coefficient of correlation was +0.66 (P < 0.001). Additionally, AUC9 provided the lowest estimate for the y-axis intercept of any of the AUC intervals tested. This intercept should, in theory, be zero. In fact, for AUC9, the calculated intercept was not different from zero; thus the equation could be recomputed by forcing the line through the origin, resulting in the following equation:

The resulting degradation in the coefficient of correlation was minor (from +0.66 to +0.63).

If all calcium sources were tested at a 12.5 mmol load size, Equation 2 would suffice, because it produces results directly commensurate with the tracer methods at that load. However, the calcemia after absorption is produced by the absolute quantity absorbed, and not by the fraction absorbed. To make provision for different load sizes, it is necessary to apply a scaling factor having a dimension of mass equivalents (mmol or g) to the factors in Equation 2. Here a distinction between gross absorption (unidirectional) and net absorption (net difference between bidirectional fluxes) is necessary. The former is what is measured by the tracer methods, whereas the latter (if >0) is what elevates serum calcium. Because digestive juices contain appreciable quantities of calcium, the enteral load is always higher than the ingested load. We have shown elsewhere that total flux into the gut from endogenous calcium pools varies with height (m) and is ~2.16 mmol/(m · d) (6 ), or, for the participants in this study with a mean height of 1.81 m, 3.91 mmol/d. On the assumption that digestive juice calcium flux into the lumen is proportionate to food intake, and further assuming that the breakfast (at 1.88 MJ) was ~20% of total daily energy intake for these men, 20% of the daily digestive juice calcium (i.e., 0.78 mmol) would have entered the gut from the blood, for a total enteral load of 12.5 + 0.78 mmol, or 13.28 mmol. In these experiments, with a mean true absorption fraction of 0.283, transfer from lumen into blood would be given by 0.283 x 13.28, or 3.76 mmol. The offsetting digestive juice flux (0.78 mmol) reduces the mean net inward flux to 2.98 mmol. It is this net absorbed quantity that produces the calcemia measured as AUC.

The foregoing calculations were performed for each test in each participant, using the subject’s actual height and true absorption fraction.

The corresponding plot of net absorbed calcium (NetAbsCa, given as AbsFx x load) is presented as Figure 4 . The equation is as follows:



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  		FIGURE 4 Plot of net absorbed calcium (NetAbsCa) against area under the curve to 9 h (AUC9) for the rise in total serum calcium for all 24 tests in 12 men. (Copyright Robert P. Heaney, 2003. Used with permission.)

 

   DISCUSSION
TOP
 ABSTRACT
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
LITERATURE CITED
 
The results presented here provide a means for quantifying calcium absorption from sources that are not easily labeled, and for producing values that can be compared or integrated with those derived using tracer methods. This approach may be particularly applicable to commercially marketed products, such as supplements or heavily fortified foods, as well as to natural food sources, none of which may be readily susceptible to labeling.

Although in this study we utilized AUC calculated out to 24 h, it was clear that 9 h suffices, and that the curve of absorptive calcemia can be captured by approximately six blood samples (e.g., 0, 1, 3, 5, 7 and 9 h). At the same time it must be noted that this pharmacokinetic approach is inherently more time consuming and expensive than the simplified tracer methods, which require only a single blood sample at 5 h (the method applied in this study), or a urine specimen pooled over a 48-h period [the method used by Yergey et al. (5 )]. On the plus side, measurement of absorptive calcemia is unaffected by the inverse relationship between load size and absorption fraction described previously (7 ,8 ), which is a characteristic feature of the tracer-based estimates.

Although the load employed in this study was constant at 12.5 mmol, the amount absorbed varied from as little as 0.95 to as much as 5.03 mmol (the extreme values on the y-axis in Fig. 4 ). This range was a result of differences intrinsic to both the source and the subjects. Because it is the amount absorbed that produces the calcemia, the approach described in this paper should be applicable to virtually any size load producing calcemia within this range, so long as it produces a measurable degree of calcemia. However, although applicable in theory to loads of any size, it is apparent that smaller loads will inevitably produce less calcemia, and hence will require correspondingly larger sample sizes to produce detectable signals with sufficiently narrow ranges of uncertainty to permit useful analysis. Even at the 12.5 mmol load that we employed, AUC9 varied from a low of 1.41 (mmol · h)/L (theoretical minimum AUC: 0.0) to a high of 4.14 (mmol · h)/L. An AUC9 of 1.41 (mmol · h)/L means an average calcemia over the 9 h after ingestion of only 0.04 mmol/dL (0.16 mg/dL), or just 1.7% above baseline. With a signal this small and inevitably some fluctuation in baseline, low AUC values carry a relatively much broader uncertainty range. The degree of dispersion of the values around the regression line is shown graphically in Figures 3 and 4 . Note how much larger this dispersion is, relative to the corresponding dispersion for the tracer data in Figure 2 . The reasons for the contrast are first that the signal-to-noise ratio for the detection of the isotope is very much higher than for the detection of the absolute calcemia, and second because the body does not regulate calcium isotope concentration as such. Hence the rise in tracer concentration is due mainly to absorption and is less influenced by offsetting effects from intrabody calcium sources, as is the case with carrier calcium.

Finally, because the 5-h absorption method incorporates an empirical correction for body size and has itself been validated only for individuals with body mass indices mainly in the range from 17 to 32 kg/m2, it follows that the calibration described here is itself valid only within that same range.


   FOOTNOTES
 
1 Supported by Creighton University research funds. Back

3 Abbreviations used: AbsFx, absorption fraction; AUC, area under the curve; fxdose, fraction of the administered dose. Back

Manuscript received 14 November 2002. Initial review completed 20 December 2002. Revision accepted 8 January 2003.


   LITERATURE CITED
TOP
 ABSTRACT
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 LITERATURE CITED
 

1. Bronner, F. (1962) Experimental studies of calcium absorption in man. Bibl. Nutr. Dieta. 3:22-31.

2. DeGrazia, J. A., Ivanovich, P., Fellows, H. & Rich, C. (1965) A double-isotope method for measurement of intestinal absorption of calcium in man. J. Lab. Clin. Med. 66:822-829.[Medline]

3. Heaney, R. P. & Recker, R. R. (1985) Estimation of true calcium absorption. Ann. Intern. Med. 103:516-521.

4. Heaney, R. P. & Recker, R. R. (1988) Estimating true fractional calcium absorption. Ann. Intern. Med. 108:905-906.

5. Yergey, A. L., Abrams, S. A., Vieira, N. E., Aldroubi, A., Marini, J. & Sidbury, J. B. (1994) Determination of fractional absorption of dietary calcium in humans. J. Nutr. 124:674-682.

6. Heaney, R. P. & Recker, R. R. (1994) Determinants of endogenous fecal calcium in healthy women. J. Bone Miner. Res. 9:1621-1627.[Medline]

7. Heaney, R. P., Weaver, C. M. & Fitzsimmons, M. L. (1990) The influence of calcium load on absorption fraction. J. Bone Miner. Res. 11:1135-1138.

8. Blanchard, J. & Aeschlimann, J. M. (1989) Calcium absorption in man—some dosing recommendations. J. Pharmacokinet. Biopharm. 17:641-644.




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