From www.bloodjournal.org by guest on June 14, 2017. For personal use only.
CLINICAL OBSERVATIONS, INTERVENTIONS, AND THERAPEUTIC TRIALS
Relationship between transferrin saturation and iron stores in the African
American and US Caucasian populations: analysis of data from the
third National Health and Nutrition Examination Survey
Christine E. McLaren, Kuo-Tung Li, Victor R. Gordeuk, Victor Hasselblad, and Gordon D. McLaren
In previous analyses of transferrin saturation data in African Americans and Caucasians from the second National Health
and Nutrition Examination Survey
(NHANES II), subpopulations were found
consistent with population genetics for
common loci that influence iron metabolism. The goal of this new study was to
determine if these transferrin saturation
subpopulations have different levels of
iron stores. Statistical mixture modeling
was applied to transferrin saturation data
for African Americans and Caucasians
from the third National Health and Nutri-
tion Examination Survey (NHANES III),
and then the mean serum ferritin concentrations were determined for the transferrin saturation subpopulations that were
identified. After adjustment for diurnal
variation, 3 subpopulations of transferrin
saturation were identified in each racial
group. Satisfying Hardy-Weinberg conditions for major locus effects, in both
racial groups the sum of the square roots
of the proportion with the lowest mean
transferrin saturation and the proportion
with the highest mean transferrin saturation was approximately 1. When weighted
to reflect the US adult population as a
whole, these subpopulations of increasing transferrin saturations had progressively increasing mean age-adjusted serum ferritin concentration values in each
ethnic grouping as stratified by sex (trend
test, P < .002 for all). These results are
consistent with the concept that population transferrin saturation subpopulations reflect different levels of storage
iron. (Blood. 2001;98:2345-2351)
© 2001 by The American Society of Hematology
Introduction
We previously used mixture modeling of transferrin saturations
measured in the second National Health and Nutrition Examination
Survey (NHANES II) to study possible genetic influences on iron
metabolism in the African American population1 and the Caucasian
population2 of the United States. In the study of NHANES II
Caucasian data, we analyzed the distribution of transferrin saturation after removing values for individuals possibly homozygous for
the gene responsible for hemochromatosis and found evidence for
2 subpopulations, one postulated to be predominantly unaffected
by the gene for hemochromatosis and the other predominantly
heterozygous for hemochromatosis.2 More recently, we examined
NHANES II data from African Americans from which markedly
elevated transferrin saturation values were not removed, and
mixture modeling provided evidence for 3 subpopulations of
transferrin saturation. Although the type of hemochromatosis found
in Caucasians may be rare in African Americans, our findings for
African Americans were consistent with population genetics for a
common locus that influences iron metabolism.1
Transferrin saturation can be reduced with inflammation as well
as iron deficiency3 and the same measurement can be elevated by
increased iron stores and a variety of other conditions.4 Therefore,
it is not completely clear that, on a population basis, elevated
transferrin saturation reflects increased iron stores. In fact, in a
recent analysis of data from the third National Health and Nutrition
Examination Survey (NHANES III), only 11% to 22% of adults
with elevated serum transferrin saturation as defined by various
cutoff values had a concurrently elevated serum ferritin level.5 In
the present study, we analyzed data from the NHANES III to
determine if subpopulations based on transferrin saturation have
different levels of storage iron as assessed by measurements of
serum ferritin concentration.
Materials and methods
Sources of data
The primary source of data for this study was NHANES III, which surveyed
a representative sample of the noninstitutionalized US population in
1988–1994. There were 31 311 persons examined from 89 primary
sampling units (county or small group of contiguous counties). The lower
age limit was set at 2 months with no upper limit in age. Based on an
interviewer’s observation, each person was classified by race as nonHispanic black, non-Hispanic white, Mexican American, or other.6 For the
purposes of this study, we did not analyze data from Mexican Americans
because of the lack of estimates of the admixture of Caucasian genes in this
population. Although NHANES III provides the categories of non-Hispanic
From the Divisions of Epidemiology and Hematology/Oncology, University of
California, Irvine, College of Medicine, Irvine; Biostatistics Shared Resource,
Chao Family Comprehensive Cancer Center, University of California, Irvine;
Center for Sickle Cell Disease, Howard University, Washington, DC; Center for
Health Policy Research and Education, Duke University, Durham, NC; and
Veterans Affairs Long Beach Health Care System, Long Beach, CA.
provided by the Department of Veterans Affairs (to G.D.M. and C.E.M.) and the
National Center for Health Statistics (to C.E.M. and V.H.).
Submitted February 2, 2001; accepted June 15, 2001.
The publication costs of this article were defrayed in part by page charge
payment. Therefore, and solely to indicate this fact, this article is hereby
marked ‘‘advertisement’’ in accordance with 18 U.S.C. section 1734.
Supported in part by grants and contracts from the National Institutes of Health,
HL-508203 (to C.E.M.), N01-HC-05190 (to C.E.M. and G.D.M.), UH1
HL03679-03 (to V.R.G.), and N01-HC-05186 (to V.R.G). Additional support was
BLOOD, 15 OCTOBER 2001 䡠 VOLUME 98, NUMBER 8
Reprints: Christine E. McLaren, University of California, Irvine, Epidemiology
Division, Dept of Medicine, 224 Irvine Hall, Irvine, CA 92697-7550; e-mail:
[email protected].
© 2001 by The American Society of Hematology
2345
From www.bloodjournal.org by guest on June 14, 2017. For personal use only.
2346
MCLAREN et al
black and non-Hispanic white, in this paper we refer to these categories as
African American and Caucasian, respectively.
Serum iron concentration and total iron-binding capacity were measured colorimetrically by using an Alpkem RFA analyzer (Alpkem,
Clackamas, OR); a 1% thiourea solution was added to complex Cu⫹⫹ to
prevent copper interference. Serum transferrin saturation was calculated by
dividing the serum iron level by total iron-binding capacity and multiplying
by 100. Information regarding methodologic variation over the assays was
provided by Gunter and colleagues.7 The coefficients of variation for
analyses of control pools averaged 3.1% and 3.3% for serum iron and total
iron-binding capacity, respectively. Serum ferritin concentration was measured by using the Quantimmune IRMA kit (Biorad Laboratories, Hercules,
CA). The coefficient of variation for serum ferritin control pools covering a
range of medium to high concentrations (approximately 25-440 ng/mL)
was 5.4% on average, and for low-concentration pools (5-10 ng/mL) it was
10.5%.7
Selection criteria
Data were extracted from the NHANES CD-ROM.7 For the analysis, we
selected transferrin saturation and serum ferritin values from 19 263 men
and nonpregnant women who were at least 20 years of age. These included
10 507 Caucasians and 8756 African Americans. We excluded subjects with
abnormally low hemoglobin or hematocrit values because anemias of
various causes are associated with abnormally high8-10 or low3,11 transferrin
saturations and serum ferritin concentrations. We excluded subjects with
abnormally low mean corpuscular volume (MCV) levels because a low
MCV can be associated with iron deficiency and inflammation,3 either of
which can lead to altered transferrin saturation and serum ferritin values.10-13 It has been shown that hemochromatosis probands have mean
MCV values significantly higher than wild-type control subjects,14 and
therefore we did not exclude subjects with MCV values above the reference
range. We excluded subjects with elevated erythrocyte protoporphyrin
because this finding is associated with iron deficiency and inflammation.15,16 We excluded subjects whose liver function tests were twice the
upper limit of the normal reference range (serum alanine aminotransferase,
serum aspartate aminotransferase, serum ␥-glutamyl transferase, serum
total bilirubin, and serum lactate dehydrogenase) or who had a positive or
borderline serum hepatitis B surface antigen or positive serum hepatitis C
antibody because transferrin saturation and serum ferritin concentration
elevations can be associated with hepatocellular damage attributable to
concurrent viral disease and alcohol or drug usage.17 We excluded subjects
with an increased serum C-reactive protein level because inflammation can
affect measures of iron status.18,19 In this study we were unable to account
for intraindividual variation in transferrin saturation due, in part, to diet at
the time of the last meal before the blood collection.
Adjustment of transferrin saturations for diurnal variation
Because transferrin saturation has a diurnal variation,12,20 including
samples obtained at different times of the day, without appropriate
adjustment, might alter the distribution of transferrin saturation. To
address this possibility, regression methods were used to adjust transferrin saturation values for blood samples drawn in the afternoon or
evening to the predicted values for blood samples drawn in the morning
in the same individuals.1 For each data set, transferrin saturation values
were divided into deciles and a regression equation was determined to
predict the adjusted average value for morning transferrin saturation for
each decile. For blood samples drawn in the afternoon or evening, the
predicted average transferrin saturation value was computed. The final
race- and gender-specific data sets consisted of the actual transferrin
saturation values from samples drawn in the morning and the predicted
values for samples drawn in the afternoon or evening.
Adjustment of the data from African Americans to account for a
possible admixture of Caucasian hereditary
hemochromatosis genes
The data were modified to allow for the possibility that the distribution
of transferrin saturations among African Americans is affected by
BLOOD, 15 OCTOBER 2001 䡠 VOLUME 98, NUMBER 8
individuals who are heterozygotes or homozygotes for hereditary
hemochromatosis. The gene frequency for the hereditary hemochromatosis locus in the Caucasian population is estimated to be 0.067.4
Assuming a 25% admixture of Caucasian genes in the African American
population,21 the gene frequency for the hereditary hemochromatosis
locus in African Americans would be 25% of 0.067 or 0.017. The actual
frequency for the Cys282Tyr mutation among African Americans was
somewhat lower in 2 geographic areas of the United States, a reported
0.011 in San Diego, California22 and 0.007 in Jefferson County,
Alabama.23 Assuming a nationwide gene frequency of 0.017, population
genetics would then project a proportion of homozygotes for the
hereditary hemochromatosis gene of 3/10 000 (0.0172) and a proportion
of heterozygotes of 330/10 000. We assumed that for African Americans, the transferrin saturation values from heterozygotes for the
hereditary hemochromatosis locus would be normally distributed with
the same means and SDs as found in our previous study of Caucasian
Americans in NHANES II.2 Under this assumption, to adjust for
hemochromatosis heterozygosity, we removed 3.3% of the 1301 values
from the data set for men (n ⫽ 43) that were closest to 43 random values
generated from a normal distribution with a mean of 46.5% and an SD of
7%. Similarly, we removed 3.3% of the 1089 values from the data set for
women (n ⫽ 36) that were closest to 36 random values generated from a
normal distribution with a mean of 43.4% and an SD of 7%. In the case
when several transferrin saturation values were equidistant from a
randomly generated value, one of these values was selected randomly.
Because the number of transferrin saturations arising from homozygotes
for hereditary hemochromatosis was projected to be less than one for
men and women, no further adjustments for possible admixture were
made to the data sets.
Statistical modeling of transferrin saturations
Data sets for transferrin saturation modeling consisted of 1258 African
American men, 1053 African American women, 2328 Caucasian men,
and 2483 Caucasian women (Table 1). As described previously, mixture
distribution modeling was applied to determine the best fit of each
grouped frequency distribution1,2,24 using the DISFIT computer program.25 In brief, transferrin saturation values were sorted into intervals
of 2% and the frequency of values within each interval was computed.
The physiologic models we considered were a single normal distribution, a mixture of 2 normal distributions, and a mixture of 3 normal
distributions. We have previously established that transferrin saturations
in a homogeneous population follow a normal distribution.2 The
expectation-maximization algorithm was applied to the distributions of
transferrin saturation values for parameter estimation.26,27 The statistical
test used to determine the best fitting model was based on the likelihood
ratio statistic. Using a hierarchical structure to analyze each observed
distribution, the maximized log-likelihood function for a mixture of 3
normal distributions was evaluated (Log L3) and compared with the
maximized log-likelihood function for 2 normal distributions (Log L2)
and for single normal distribution (Log L1). Significance of the
likelihood ratio statistics [⫺2Log (L3/L2)] and [⫺2Log (L3/L1)] at the
0.01 level was assessed using a resampling technique.28 For the
3-population model, the methods of Crump and Howe were used to
compute confidence intervals for proportions.29
Estimation of gene frequency for possible loci
that influence iron status
Accepting the possibility that our findings might represent the presence
of loci that influence iron metabolism, we assumed that the 3 normal
distributions of transferrin saturation in our analyses would represent
predominantly a subpopulation of normal homozygotes, a subpopulation
of heterozygotes, and a subpopulation of affected homozygotes. We
estimated the proportions of normal homozygotes, heterozygotes, and
affected homozygotes as the proportions in the populations with the
lowest, intermediate, and highest mean transferrin saturations, respectively. According to the Hardy-Weinberg equilibrium equation, p2 (the
From www.bloodjournal.org by guest on June 14, 2017. For personal use only.
BLOOD, 15 OCTOBER 2001 䡠 VOLUME 98, NUMBER 8
TRANSFERRIN SATURATION AND IRON STORES
2347
Table 1. Exclusions from the total sample of Caucasian and African Americans at least 20 y of age
African American
Exclusion
Caucasian
Men
Women
Men
Women
4121
4635
4921
5586
2002
2045
1634
1752
0
90
0
70
Transferrin saturation not measured
183
208
119
180
Abnormal hemoglobin level*
230
610
347
272
0
52
48
68
41
148
121
358
Total sample
Excluded for
Age younger than 20 y
Pregnant
Abnormal hematocrit†
Protoporphyrin greater than or equal to 70 ␮g/dL red blood cells
MCV less than 80 fL
127
96
50
55
Serum alanine aminotransferase greater than 80
15
15
11
20
Serum aspartate aminotransferase greater than 74 U/L
18
9
7
4
Serum ␥-glutamyl transferase greater than 102
71
82
64
90
Serum total bilirubin greater than 2.0 mg/dL
6
2
23
4
Serum lactate dehydrogenase greater than 546
0
0
1
1
Serum C-reactive protein greater than 1.0 mg/dL
69
163
124
207
Serum hepatitis B surface antigen positive or borderline
17
6
5
4
Serum hepatitis C antibody positive
41
20
39
18
1301
1089
2328
2483
43
36
0
0
1258
1053
2328
2483
Subtotal
Possible heterozygosity for hemochromatosis (non-Hispanic blacks only)
Sample for transferrin saturation modeling
Serum ferritin not measured
Sample for serum ferritin analysis
6
6
6
8
1252
1047
2322
2475
*Hemoglobin (Hb) level exclusions: African American men, Hb less than 13 g/dL; African American women, Hb less than 11.5 g/dL; Caucasian men, Hb less than 13.5 g/dL;
Caucasian women, Hb less than 12 g/dL.
†Hematocrit (Hct) exclusions: African American men, Hct less than 34%; African American women, Hct less than 30%; Caucasian men, Hct less than 40%; Caucasian
women, Hct less than 36%.
proportion of normal homozygotes) ⫹ 2pq (the proportion of heterozygotes) ⫹ q2 (the proportion of abnormal homozygotes) ⫽ 1. We
estimated the gene frequency of the abnormal allele (q) as the square
root of the proportion from the population with the highest mean
transferrin saturation. We estimated the gene frequency of the normal
homozygotes (p) as the square root of the proportion from the
population with the lowest mean transferrin saturation. We then
examined whether the model distributions were consistent with population genetics for a major locus effect in which p ⫹ q ⫽ 1.
The means for transferrin saturation within corresponding subpopulations were compared between African Americans and Caucasians of the
same gender using the independent sample t test.
Comparison of mean serum ferritin concentrations within
subpopulations determined on the basis of
transferrin saturation
A goal of our study was to determine if subpopulations of individuals,
determined on the basis of transferrin saturation, have significantly different
mean iron stores. Considering the transferrin saturation data sets used for
mixture modeling, 26 subjects did not have measurements of serum ferritin
concentration. After removal of values for these individuals, the data sets
for analysis of serum ferritin concentration consisted of 1252 African
American men, 1047 African American women, 2322 Caucasian men, and
2475 Caucasian women. Because of the marked skewness in the distributions of serum ferritin concentration, the square root transformation was
applied to each data set. Because serum ferritin concentration tends to
increase with age,30-37 we developed a method for age standardization based
on statistical regression analysis. Linear, piece-wise linear, and nonlinear
regression models, stratified by race and gender, were examined by
regressing the square root of the observed serum ferritin concentration on
the age at interview. The best fitting models showed an increase to middle
age followed by steady state or decline in serum ferritin. Because of the lack
of a biologic explanation for age-related decline in serum ferritin in terms of
reduction of iron stores, we adopted a conditional approach to the modeling.
For individuals below 60 years of age we used race- and gender-specific
linear regression equations to calculate the predicted serum ferritin at age
60. For individuals 60 years of age or older, the observed serum ferritin was
used in further analyses.
The probability that an individual serum ferritin concentration value
belonged to one of the 3 transferrin saturation subpopulations was
computed. Given the total sample size, the number of expected
observations within each transferrin saturation interval was calculated.
Within a given transferrin saturation interval, each observation was then
assigned a probability by random assignment from a uniform (0,1)
distribution and these probabilities were used to assign individual serum
ferritin concentration values to a given subgroup according to the
expected proportions within transferrin saturation subpopulations. Two
hundred repetitions of the assignment of serum ferritin concentration
values to subpopulations were made and the average mean and variance
for serum ferritin concentration within subpopulations were computed.
The parametric trend test38 was used to compare the mean square root of
serum ferritin concentration within each of 3 transferrin saturation
subgroups, taking into account the unequal sample sizes for subgroups
of subjects.
Weighting the results to reflect the US population as a whole
The assumptions underlying our analysis were that transferrin saturation
values are independent and identically distributed; that is, each observation
has an equal chance of being selected and that all observations come from
the same distribution. However, because individuals in the NHANES III
sample did not have an equal probability of selection, sample weights must
be used to calculate parameter estimates that reflect the US population. For
NHANES III, a multistage estimation procedure was used to calculate
sample weights so that point estimates would reflect the US population. The
sampling weights were based on the March 1990 and March 1993 Current
Population Survey, adjusted for undercounts, for the civilian noninstitutionalized US population.39 The methods described above were used to
compute parameter estimates from the weighted transferrin saturation
distributions to reflect results for African American and Caucasian men and
women in the US population fitting our exclusion criteria. It was not
possible to adjust the variance estimates to account for the complex design
of NHANES III.
From www.bloodjournal.org by guest on June 14, 2017. For personal use only.
2348
BLOOD, 15 OCTOBER 2001 䡠 VOLUME 98, NUMBER 8
MCLAREN et al
Figure 1. Decile means for transferrin saturations.
The relationship is shown between decile means for
transferrin saturations determined from blood drawn in
morning examination sessions and those of corresponding afternoon (●●●●) and evening (ⴱⴱⴱⴱ) examination
sessions for African American men. Panel A shows
unweighted data and panel B data weighted to represent
the US population as a whole. The regression lines are
shown in each panel.
Results
Analysis of unweighted transferrin saturation data
The primary analysis was performed on transferrin saturations for
7122 individuals. The transferrin saturations had been adjusted for
diurnal variation and for the possible presence of an hereditary
hemochromatosis allele in African Americans. Figure 1 shows the
effect of diurnal variation on measurement of transferrin saturation
for African American men. The graphs indicate the relationship
between decile means for transferrin saturations, determined from
blood drawn in morning examination sessions, and the corresponding mean transferrin saturations determined from blood drawn in
afternoon sessions (Pearson correlation coefficient, r ⫽ 0.999) and
evening sessions (r ⫽ 0.997). The regression equations based on
the unweighted data (Figure 1A) are as follows:
Morning session transferrin saturation ⫽ 0.6 ⫹ 1.0 ⫻ (Afternoon
session transferrin saturation).
Morning session transferrin saturation ⫽ 1.5 ⫹ 1.2 ⫻ (Evening
session transferrin saturation).
These regression lines differed significantly as judged by the F
test for the equality of regression lines (F ⫽ 262.2 with numerator
and denominator degrees of freedom of 2 and 16, respectively;
P ⬍ .0001). Similar results were found for data from African
American women and Caucasian men and women. For each group,
the correlation between decile means for transferrin saturations,
determined from blood drawn in morning examination sessions,
and the corresponding mean transferrin saturations determined
from blood drawn in afternoon sessions and evening sessions was
strong (r ⬎ 0.99 for all) and the regression lines differed
significantly as judged by the F test for the equality of regression
lines (F test, P ⬍ .0001 for all).
Results of statistical mixture modeling indicated that the fit of
the unweighted data to a mixture of 3 normal populations with
unequal variances was significantly better than the fit to a mixture
of 2 normal populations for African American men (likelihood ratio
statistic, 24.1, P ⬍ .01) and women (18.8, P ⬍ .01) as well as for
Caucasian men (35.3, P ⬍ .01) and women (39.7, P ⬍ .01).
Similarly, the fit of the data to a mixture of 3 normal populations
was significantly better than the fit to a single normal population for
all: African American men, likelihood ratio statistic, 221.1, P ⬍ .01,
and women, 119.7, P ⬍ .01; Caucasian men, 416.9, P ⬍ .01, and
women, 469.4, P ⬍ .01. Figure 2 shows the distribution of
transferrin saturation for African American men (A) and women
(B) and for Caucasian men (C) and women (D). The fitted
subpopulations are superimposed over the histograms of the
observed data. Table 2 gives mixture model parameter estimates for
transferrin saturation subpopulations and shows that for each ethnic
subgroup and gender, transferrin saturation subpopulations were
identified with increasing means (trend test P ⬍ .0001 for all). The
findings are consistent with population genetics for single major
loci affecting the distribution of transferrin saturations. For example,
Table 2. Parameter estimates for transferrin saturation and age-standardized serum ferritin concentration from the unweighted samples
Transferrin saturation (%)
Serum ferritin concentration* (ng/mL)
Mixture distribution models
Ethnic subgroup
African American men
Caucasian men
African American women
Caucasian women
Subpopulation estimates
Percent of population
Mean
SD
N
72.9
25.0
6.21
914
231
(220, 240)
24.9
37.4
6.38
309
256
(240, 272)
2.1
63.8
8.54
29
313
(234, 404)
81.4
28.9
7.52
1898
174
(169, 180)
17.6
45.3
8.55
396
193
(180, 207)
0.9
77.5
11.09
28
289
(199, 396)
81.9
21.6
6.66
857
132
(125, 139)
17.2
35.6
6.85
182
156
(142, 172)
0.9
63.9
7.29
8
213
(135, 310)
86.0
25.9
7.66
2137
88
(85, 92)
13.5
45.7
8.73
318
117
(106, 128)
0.5
79.5
9.23
20
135
(100, 169)
*For individuals younger than 60 years, serum ferritin concentration values were standardized to those expected at age 60.
Mean
95% CI
From www.bloodjournal.org by guest on June 14, 2017. For personal use only.
BLOOD, 15 OCTOBER 2001 䡠 VOLUME 98, NUMBER 8
TRANSFERRIN SATURATION AND IRON STORES
2349
Table 3. Parameter estimates for transferrin saturation and serum ferritin concentration for weighted population data
Serum ferritin concentration*
(ng/mL)
Transferrin saturation (%)
Mixture distribution models
Ethnic subgroup
African American men
Caucasian men
African American women
Caucasian women
Subpopulation estimates
Percent of population
Mean
SD
No.
Mean
73.0
24.7
6.34
3 807 940
237.2
24.9
37.1
6.45
1 300 491
256.0
2.1
64.0
8.91
111 071
309.8
86.1
29.6
7.88
43 514 385
187.7
13.4
48.3
9.21
6 752 746
207.4
0.5
82.0
10.59
262 248
282.2
81.8
21.7
6.34
3 567 584
134.6
17.3
36.0
6.45
755 516
153.8
1.1
64.4
8.90
40 010
187.7
86.5
25.9
7.55
41 075 383
82.8
13.0
45.5
8.60
6 175 671
106.1
0.5
79.3
9.10
232 193
118.8
*For individuals younger than 60 years, serum ferritin concentration values were standardized to those expected at age 60.
for African American men the sum of the square roots of the
proportion with the lowest transferrin saturation (p ⫽ 0.854) and of
the proportion with the highest transferrin saturation (q ⫽ 0.146)
was approximately 1 (p⫹q ⫽ 1.000). Corresponding results were
found for African American women (p ⫽ 0.905, q ⫽ 0.095) and for
Caucasian men (p ⫽ 0.902, q ⫽ 0.098) and women (p ⫽ 0.927,
q ⫽ 0.073) where p⫹q ⫽ 1.000 for all.
Analysis of unweighted serum ferritin concentration data
Our analysis of transferrin saturations demonstrated that 3 subpopulations of individuals could be detected within each ethnic subgroup and gender. We then compared the age-standardized mean
serum ferritin concentrations for these subpopulations (Table 2).
Trend tests demonstrated an increase in mean serum ferritin
concentration, standardized to age 60, with increasing mean
transferrin saturation for African American men (trend test ␹2
statistic with 1 degree of freedom, 1385, P ⬍ .0001) and women
Figure 2. The observed and modeled distributions of transferrin saturation
values are shown for each ethnicity and sex. Distribution of transferrin saturation
values for 1301 African American men (A), 1089 African American women (B),
2328 Caucasian men (C), and 2483 Caucasian women (D). A histogram of the
observed data is given. The dashed lines represent the fitted normal distributions
representing 3 subpopulations. The overall fitted mixture distribution is shown
with a solid line.
(858, P ⬍ .0001) and for Caucasian men (1746, P ⬍ .0001) and
women (418, P ⬍ .0001). The mean transferrin saturations within
the middle and upper subpopulations for African American men
and women are significantly lower than those for Caucasians (Table
2). For the second subpopulation, the mean transferrin saturation
value for African American men was 8% lower in absolute value
than that of Caucasian men (95% confidence interval [CI] 6.8%,
9.1%). The mean transferrin saturation for African American
women was 10% lower in absolute value than that of Caucasian
women (8.7%, 11.6%). Considering the upper subpopulation, the
mean transferrin saturation values were 14% (8.2%, 19.2%) lower
in absolute value for African American men than in Caucasian men
and 16% (8.4%, 22.9%) lower in African American women
compared to Caucasian women.
Weighted results for African American and
Caucasian populations
Figure 1B confirms the effect of diurnal variation on measurement of transferrin saturation values using the weighted data.
For African American men, the regression lines differed significantly (F ⫽ 192.9 with numerator and denominator degrees of
freedom of 2 and 16, respectively; P ⬍ .0001). Table 3 gives the
mixture modeling results after the data (adjusted for diurnal
variation and age effects in African American and Caucasian
individuals and for the potential presence of hemochromatosis
in African Americans) were weighted to reflect the US population as a whole. The weighted results for transferrin saturation
are similar to our primary results using unweighted data, which
suggests that the unequal probability of selection in NHANES
III did not have a major input on the transferrin saturation and
serum ferritin concentration distributions. For example, for
African Americans, the findings for weighted data are consistent
with population genetics for a single major locus affecting the
distribution of transferrin saturations. For men, the sum of the
square roots of the proportion with the lowest transferrin
saturation (p ⫽ 0.854) and of the proportion with the highest
saturation (q ⫽ 0.146) is approximately 1 (1.000). Similarly, for
women the sum of the square roots of the proportion with the
lowest transferrin saturation (p ⫽ 0.904) and of the proportion
with the highest saturation (q ⫽ 0.104) is also approximately 1
(1.0085). For both ethnic subgroups and each gender, trend tests
demonstrated an increase in mean serum ferritin concentration,
From www.bloodjournal.org by guest on June 14, 2017. For personal use only.
2350
MCLAREN et al
standardized to age 60, with increasing mean transferrin saturation (Table 3; P ⬍ .002 for all).
An estimated proportion of 0.861 of Caucasian men studied
were included in a subpopulation with a mean transferrin saturation
of 29.6%, whereas 0.134 comprised a subpopulation with an
intermediate mean saturation of 48.3% and 0.005 formed a
subpopulation with a mean saturation of 82.0%. An estimated
proportion of 0.865 of Caucasian women studied were included in
a subpopulation with a mean saturation of 25.9%, whereas 0.130
comprised a subpopulation with an intermediate mean saturation of
45.5% and 0.005 formed a subpopulation with a mean saturation of
79.3%. From these results, the estimated gene frequencies for
hereditary hemochromatosis were 0.072 (0.070-0.075) for Caucasian men and 0.070 (0.060-0.081) for Caucasian women corresponding to prevalences of 5.2/1000 and 4.9/1000, respectively.
Discussion
In the present study, we identified 3 transferrin saturation subpopulations in African Americans and Caucasians by using specialized
modeling of data from NHANES III. The proportions of these
subpopulations are consistent with Hardy-Weinberg criteria for a
major, common genetic influence on iron metabolism in each of
these 2 broad ethnic groups.
We previously analyzed transferrin saturation data for African
Americans in the NHANES II study and obtained similar findings
regarding a possible major locus affecting iron metabolism.1 In this
regard, it is of interest that an iron-loading genetic defect, distinct
from the Cys282Tyr mutation in HFE that is responsible for most
hemochromatosis in Caucasians,40 may be present in the subSaharan African population,41,42 and that mutations in HFE are very
rare in the African American population.41 The present results are
also consistent with the possibility of an iron-loading genetic defect
in the African American population distinct from that in the
Caucasian population and producing different phenotypes. For
example, the mean transferrin saturations within the middle and
upper subpopulations for African American men and women were
from 8% (95% CI, 6.8%-9.1%) to 16% (8.4%-22.9%) lower,
whereas mean serum ferritin concentrations were substantially
higher than those for Caucasians of the same gender.
In the present study, the estimated gene frequencies for hereditary hemochromatosis in Caucasians based on transferrin saturation
subpopulations were 7.2% (7.0%-7.5%) for men and 7.0% (6.0%8.1%) for women corresponding to prevalence estimates of 5.2/
1000 for men and 4.9/1000 for women. These results are consistent
with the reported prevalence of hereditary hemochromatosis and
the frequency of the Csy282Tyr mutation in the HFE gene. For
example, a meta-analysis by Lucotte and Mercier, comprising the
results of recent studies conducted in 40 European populations,
showed an overall frequency of 5.5% for the Cys282Tyr allele,
corresponding to a prevalence estimate of 3/1000 (0.303%) for
Cys282Tyr homozygotes.43
Since NHANES III was conducted before the discovery of the
HFE gene, a limitation of this study is that testing for the
Cys282Tyr mutation and other mutations was not performed.
About 28% of Caucasians have the His63Asp mutation in the HFE
gene.22,44,45 Heterozygotes for His63Asp have only minor changes
in the transferrin saturation22 and are probably included in the
lower Caucasian subpopulation of the analysis of the present study,
whereas homozygotes for His63Asp and compound heterozygotes
(Cys282Tyr/His63Asp) have elevations in transferrin saturation
BLOOD, 15 OCTOBER 2001 䡠 VOLUME 98, NUMBER 8
similar to Cys282Tyr heterozygotes22,46 and are probably included
in the middle Caucasian subpopulation. Only about 10% of African
Americans have the His63Asp mutation with most being heterozygotes and less than 0.5% being homozygotes.22 In the present
analysis of transferrin saturations from African Americans, it is
possible that His63Asp heterozygotes were included in the lower
subpopulation, whereas His63Asp homozygotes were included in
the middle subpopulation. Among Caucasian women, our finding
of an elevation in mean serum ferritin for the middle subpopulation
is consistent with the results found for Cys282Tyr heterozygotes in
the large study conducted by Beutler and colleagues,22 but in
contrast to other investigations in which Caucasian women,
heterozygous for the Cys282Tyr mutation, did not have elevations
in ferritin as compared to normal homozygotes.44,46
We have considered the possibility that adjustment of transferrin saturations for diurnal variation potentially could introduce
an element of artifact in the analyses. To evaluate this possibility,
we reanalyzed the data using the unadjusted values. As in the
analyses of the adjusted data, these reanalyses identified 3 transferrin saturation subpopulations with increasing means for each
ethnic subgroup and gender (trend test P ⬍ .0001 for all), although
the estimated percentage of cells in corresponding subpopulations
differed slightly (results not shown). Similarly, before correction
for diurnal variation, the means for transferrin saturation within the
middle and upper subpopulations for African American men and
women were 5% (4.4%-6.4%) to 16% (7.3%-24.1%) lower, and the
means for serum ferritin concentration were substantially higher
than those for Caucasians of the same gender. Trend tests also
demonstrated an increase in mean serum ferritin concentration,
standardized to age 60, with increasing mean transferrin saturation
for each group (P ⬍ .0001 for all), consistent with the results
observed in the analyses of the adjusted data.
Even among Cys282Tyr homozygotes there is considerable
variability in disease expression,22,47 and the place of testing for the
Cys282Tyr mutation in screening for hemochromatosis has not
been determined. Although serum ferritin concentration was once
suggested as a screening marker for homozygosity for the hemochromatosis allele,48 transferrin saturation has been regarded for some
time as the best single screening test for hemochromatosis.49,50
Recent large studies of Caucasians in which both phenotypic
testing with transferrin saturation and genotypic testing for the
Cys282Tyr mutation were performed have shown that screening
with transferrin saturation does not identify all Cys282Tyr homozygotes,22,47 underscoring the fact that the ideal approach to phenotypic screening for hemochromatosis has not yet been developed.
In our study of NHANES III data using statistical modeling
methodology, subpopulations identified on the basis of increasing
transferrin saturation had progressively increasing mean ageadjusted serum ferritin levels in each ethnic group, stratified by
gender. These results suggest that it may be possible to develop a
practical approach to the initial screening for iron overload that
includes the combination of transferrin saturation and serum
ferritin concentration measurements.
Acknowledgments
We thank Lamman Doan for statistical computing support. We
gratefully acknowledge the contributions of Jacqueline Lovingood,
CDC analyst who performed specimen analyses for serum iron and
total iron-binding capacity in the NHANES Laboratory, and Della
Twite, CDC analyst who performed analyses for serum ferritin.
From www.bloodjournal.org by guest on June 14, 2017. For personal use only.
BLOOD, 15 OCTOBER 2001 䡠 VOLUME 98, NUMBER 8
TRANSFERRIN SATURATION AND IRON STORES
2351
References
1. Gordeuk VR, McLaren, CE, Looker AC, Hasselblad V, Brittenham GM. Distribution of transferrin
saturations in the African-American population.
Blood. 1998;91:2175-2179.
17. Bell H, Skinningsrud A, Raknerud N, Try K. Serum ferritin and transferrin saturation in patients
with chronic alcoholic and non-alcoholic liver diseases. J Intern Med. 1994;236:315-322.
2. McLaren CE, Gordeuk VR, Looker AC, et al.
Prevalence of heterozygotes for hemochromatosis in the white population of the United States.
Blood. 1995;86:2021-2027.
18. Brendstrup P. Serum copper, serum iron and total
iron binding capacity of serum in patients with
chronic rheumatoid arthritis. Acta Med Scand.
1953;146:384-392.
3. Jandl JH. Blood. Boston: Little, Brown; 1987.
19. Cartwright GE. The anemia of chronic disorders.
Semin Haematol. 1966;3:351-375.
4. Edwards CQ, Griffen LM, Goldgar D, et al. Prevalence of hemochromatosis among 11,065 presumably healthy blood donors. N Engl J Med.
1988;318:1355-1362.
5. Looker AC, Johnson CL. Prevalence of elevated serum transferrin saturation in adults in the United
States. Ann Intern Med. 1998;129:940-945.
6. Plan and operation of the Third National Health
and Nutrition Examination Survey, 1988–94.
DHHS publication no. (PHS) 94-1308, (Vital and
Health Statistics; series 1; no. 32). Hyattsville,
MD: U.S. Department of Health and Human Services, Public Health Service, Centers for Disease
Control and Prevention, National Center for
Health Statistics; 1994.
7. Gunter EW, Lewis BL, Koncikowski SM. Laboratory procedures used for the third National Health
and Nutrition Examination Survey (NHANES III),
1988–1994 [CD-ROM]. Atlanta, GA: U.S. Department of Health and Human Services, Public
Health Service, Centers for Disease Control and
Prevention, Center for Environmental Health, and
Hyattsville, MD: National Center for Health Statistics; 1996. Available from National Technical Information Service, Springfield, VA.
8. Finch CA, Deubelbeiss K, Cook JD, et al. Ferrokinetics in man. Medicine. 1970;49:17-53.
9. Hershko C, Graham G, Bates GW, Rachmilewitz
EA. Non-specific serum iron in thalassaemia: an
abnormal serum iron fraction of potential toxicity.
Br J Haematol. 1978;40:255-263.
10. Cartwright GE, Wintrobe MM. Chemical, clinical,
and immunological studies on the products of human plasma fractionation; XXXIX, the anemia of
infection. Studies on the iron-binding capacity of
serum. J Clin Invest. 1949;28:86-98.
11. Bainton DF, Finch CA. The diagnosis of iron deficiency anemia. Am J Med. 1964;37:62-70.
12. Edwards CQ, Griffen LM, Kaplan J, Kushner JP.
Twenty-four hour variation of transferrin saturation in treated and untreated hemochromatosis
homozygotes. J Intern Med. 1989;226:173-179.
13. Gordeuk VR, Brittenham GM, McLaren GD,
Spagnuolo PJ. Hyperferremia in immmunosuppressed patients with acute nonlymphocytic leukemia and the risk of infection. J Lab Clin Med.
1986;108:466-472.
14. Barton JC, Bertoli LF, Rothenberg BE. Peripheral
blood erythrocyte parameters in hemochromatosis: evidence for increased erythrocyte hemoglobin content. J Lab Clin Med 2000;135:96-104.
15. Cartwright GE, Hugeley CM, Ashenbrucker H, et
al. Studies on free erythrocyte protoporphyrin,
plasma iron and plasma copper in normal and
anemic subjects. Blood. 1948;3:501-525.
16. Devasthali SD, Gordeuk VR, Brittenham GM, et
al. Bioavailability of carbonyl iron: a randomized,
double-blind study. Eur J Haematol. 1991;46:272278.
20. Hamilton LD, Gubler CJ, Cartwright GE, Wintrobe
MM. Diurnal variation in the plasma iron level of
man. Proc Soc Exp Biol Med. 1950;75:65-68.
21. Chakraborty R, Kamboh MI, Nwankwo M, Ferrell
RE. Caucasian genes in American blacks. New
data. Am J Hum Genet. 1992;50:145-155.
22. Beutler E, Felitti V, Gelbart T, Ho N. The effect of
HFE genotypes on measurements of iron overload in patients attending a health appraisal
clinic. Ann Intern Med 2000;133:329-337.
23. Barton JC, Acton RT. Transferrin saturation phemotype and HFE genotype screening for hemochromatosis and primary iron overload: predictions from a model based on national, racial, and
ethnic group composition in central Alabama.
Genet Test. 2000;4:199-206.
24. McLaren CE, McLachlan GJ, Halliday JW, et al.
Distribution of transferrin saturation in an Australian population: relevance to the early diagnosis
of hemochromatosis. Gastroenterology. 1998;
114:543-549.
25. Hasselblad V. Manual for the grouped DISFIT
software. Version 1.1. Durham, NC: Duke University; 1992.
26. McLaren CE, Brittenham GM, Hasselblad V. Analysis of the volume of red blood cells: application
of the expectation-maximization algorithm to
grouped data from the doubly-truncated lognormal distribution. Biometrics. 1986;42:143-158.
a healthy Australian population. Clin Chem. 1990;
36:1350-1355.
35. Custer EM, Finch CA, Sobel RE, et al. Population
norms for serum ferritin. J Lab Clin Med. 1995;
126:88-94.
36. Pilch SM, Senti FR. Assessment of the iron nutritional status of the US population based on data
collected in the Second National Health and Nutrition Examination Survey, 1976–80. Bethesda,
MD: Life Sciences Research Office, Federation of
American Societies for Experimental Biology; August 1984.
37. Zacharski LR, Ornstein DL, Woloshin S,
Schwartz LM. Association of age, sex, and race
with body iron stores in adults: analysis of
NHANES III data. Am Heart J. 2000;140:98-104.
38. Cuzick, Jack. Trend tests. In: Kotz S, Johnson N,
eds. Encyclopedia of Statistical Sciences. Vol 9.
New York, NY: John Wiley; 1988:336-342.
39. Mohadjer L, Montaquila J, Waksberg J, et al. National Health and Nutrition Examination Survey
III. Weighting and Estimation Methodology. Rockville, MD: WESTAT; 1996.
40. Feder JN, Gnirke A, Thomas W, et al. A novel
MHC class I-like gene is mutated n patients with
hereditary haemochromatosis. Nat Genet. 1996;
13:399-408.
41. Gordeuk VR, Mukiibi J, Hasstedt SJ, et al. Iron
overload in Africa: interaction between and gene
and dietary iron content. N Engl J Med. 1992;326:
95-100.
42. McNamara L, MacPhail AP, Gordeuk VR, Hasstedt SJ, Rouault T. Is there a link between African iron overload and the described mutations of
the hereditary haemochromatosis gene? Br J
Haematol. 1998;102:1176-1178.
43. Lucotte G, Mercier G. Celtic origin of the C282Y
mutation of hemochromatosis. Genet Test. 2000;
4:163-169.
27. McLaren CE, Brittenham GM, Hasselblad V. Statistical and graphical evaluation of erythrocyte
volume distributions. Am J Physiol. 1987;252:
H857–H866.
44. Burt MJ, George PM, Upton JD, et al. The significance of haemochromatosis gene mutations in
the general population: implications for screening. Gut. 1998;43:830-836.
28. McLachlan GJ, Basford KE. Mixture models: inference and applications to clustering. New York,
NY: Marcel Dekker; 1988.
45. Guttridge MG, Carter K, Worwood M, Darke C.
Population screening for hemochromatosis by
PCR using sequence-specific primers. Genet
Test. 2000;4:111-114.
29. Crump KS, Howe R. A preview of methods for
calculating confidence limits in low dose extrapolation. In: Clayton DB, Krewski D, Munro IC, eds.
Toxicological risk assessment. Boca Raton, FL:
CRC Press; 1985.
46. Rossi E, Olynyk JK, Cullen DJ, et al. Compound
heterozygous hemochromatosis genotype predicts increased iron and erythrocyte indices in
women. Clin Chem. 2000;46:162-166.
30. Expert Scientific Working Group. Summary of a
report on assessment of the iron nutritional status
of the United States population. Am J Clin Nutr.
1985;42:1318-1330.
31. Milman N. Serum ferritin in Danes: studies of iron
status from infancy to old age, during blood donation and pregnancy. Int J Hematol. 1996;63:103135.
32. McCord JM. Iron, free radicals, and oxidative injury. Semin Hematol. 1998;35:5-12.
33. Cook JD, Finch CA, Smith NJ. Evaluation of the
iron status of a population. Blood. 1976;48:449455.
34. Leggett BA, Brown NN, Bryant SJ, et al. Factors
affecting the concentrations of ferritin in serum in
47. Adams PC, Kertesz AE, McLaren CE, Barr R,
Bamford A, Chakrabarti S. Population screening
for hemochromatosis: a comparison of unbound
iron-binding capacity, transferrin saturation, and
C282Y genotyping in 5,211 voluntary blood donors. Hepatology. 2000;31:1160-1164.
48. Beaumont C, Simon M, Fauchet R, et al. Serum
ferritin as a possible marker of the hemochromatosis allele. N Engl J Med. 1979;301:169-174.
49. Dadone MM, Kushner JP, Edwards CQ, et al. Hereditary hemochromatosis: analysis of laboratory
expression of the disease by genotype in 18 pedigrees. Am J Clin Pathol. 1982;78:196-207.
50. Edwards CQ, Kushner JP. Screening for hemochromatosis. N Engl J Med. 1993;328:16161620.
From www.bloodjournal.org by guest on June 14, 2017. For personal use only.
2001 98: 2345-2351
doi:10.1182/blood.V98.8.2345
Relationship between transferrin saturation and iron stores in the African
American and US Caucasian populations: analysis of data from the third
National Health and Nutrition Examination Survey
Christine E. McLaren, Kuo-Tung Li, Victor R. Gordeuk, Victor Hasselblad and Gordon D. McLaren
Updated information and services can be found at:
http://www.bloodjournal.org/content/98/8/2345.full.html
Articles on similar topics can be found in the following Blood collections
Clinical Trials and Observations (4553 articles)
Red Cells (1159 articles)
Information about reproducing this article in parts or in its entirety may be found online at:
http://www.bloodjournal.org/site/misc/rights.xhtml#repub_requests
Information about ordering reprints may be found online at:
http://www.bloodjournal.org/site/misc/rights.xhtml#reprints
Information about subscriptions and ASH membership may be found online at:
http://www.bloodjournal.org/site/subscriptions/index.xhtml
Blood (print ISSN 0006-4971, online ISSN 1528-0020), is published weekly by the American Society of
Hematology, 2021 L St, NW, Suite 900, Washington DC 20036.
Copyright 2011 by The American Society of Hematology; all rights reserved.