Prospective Analysis of Mannose-Binding Lectin Genotypes
and Coronary Artery Disease in American Indians
The Strong Heart Study
Lyle G. Best, MD; Michael Davidson, MD, MPH, PhD; Kari E. North, PhD; Jean W. MacCluer, PhD;
Ying Zhang, PhD; Elisa T. Lee, PhD; Barbara V. Howard, PhD; Susan DeCroo, MS; Robert E. Ferrell, PhD
Downloaded from http://circ.ahajournals.org/ by guest on June 16, 2017
Background—Mannose-binding lectin (MBL) is a circulating immune factor responsible for opsonization of pathogens
and directly activating complement. Common variations in the MBL gene are responsible for an opsonic deficiency that
affects 5% to 7% of whites and are associated with increased susceptibility to infections. After a preliminary report
associating these variations with coronary artery disease (CAD), we determined MBL genotypes in 3 American Indian
communities experiencing an increased mortality and morbidity from CAD.
Methods and Results—We examined DNA from 434 participants in a population-based cohort, the Strong Heart Study.
Genotypes for 3 common MBL coding variations and 1 promoter polymorphism were determined. The frequency of a
composite genotype that conferred low MBL levels was 20.7% in 217 cases and 11.1% in matched controls without
CAD. A conditional logistic regression model indicated a univariate OR for CAD of 2.3 (95% CI 1.3 to 4.2, P⫽0.005)
for the variant genotypes. After adjustment for demographic and CAD risk factors, including type 2 diabetes mellitus,
fibrinogen, triglycerides, and hypertension, the OR was 3.2 (95% CI 1.5 to 7.0, P⫽0.004).
Conclusions—Variant MBL genotypes coding for markedly diminished levels of MBL are predictive of CAD. After
adjustment for multiple traditional risk factors for ischemic heart disease, this association remains significant. A high
prevalence of variant MBL alleles and CAD in this population suggests that potentially important public health benefits
may accrue from future interventions based on these genotypes. (Circulation. 2004;109:471-475.)
Key Words: coronary disease 䡲 genetics 䡲 inflammation 䡲 immune system 䡲 epidemiology
T
here is recent evidence that the pathogenesis of atherosclerosis involves the altered control of inflammation by
innate immune defenses that include pattern-recognition molecules such as toll-like receptors and possibly mannosebinding lectin (MBL).1–3 The latter serum protein opsonizes a
variety of pathogenic microorganisms by binding mannose
moieties on their surface and activating complement via the
lectin pathway before antibody formation.4 Major decreases
in opsonization detected in 5% to 7% of whites5 and commonly among other populations result from markedly decreased levels of MBL related to variations of both structural
and promoter portions of this gene.5– 8 In both children and
adults, an increased risk of certain infectious conditions has
been associated with low levels of MBL or genotypes
predictive of low levels.9 –12
Deficiencies in MBL can be caused by 3 single nucleotide
polymorphisms within exon 1 of the MBL gene on chromosome 10: allele B at codon 54 (G54D), allele C at codon 57
(G57E), and allele D at codon 52 (R52C), with the most
common codon at these loci designated allele A.4 This effect
is substantially modulated by at least 4 promoter polymorphisms, including the H/L and X/Y systems, which show
reductions of MBL up to 85% among individuals homozygous for the LX (“low”) promoters.8 The structural variations
have typically been labeled “O” alleles in contrast to the most
common “A” allele. Thus, the OO genotype could represent,
for example, BB, BC, or CD genotypes, and an AO individual
is heterozygous for the common allele and 1 of the 3
structural variations. Those with an OO genotype have
virtually undetectable levels of MBL regardless of promoter
genotype. The presence of a heterozygous genotype (AO)
results in an approximate 8-fold reduction of MBL levels, but
there is considerable overlap in the distribution of MBL
levels in those with AA and AO genotypes.6,7,13,14 The
frequency of MBL alleles (rather than MBL concentration)
has been a preferred measurement of effect, because no clear
cutoff of MBL concentration defines deficiency.15 There is
some disparity in the limited reports examining direct associations of MBL with CAD.3,16 –18
Received June 16, 2003; de novo received September 18, 2003; accepted October 23, 2003.
From Missouri Breaks Industries Research Inc (L.G.B.), Timber Lake, SD; Medstar Research Institute (M.D., B.V.H.), Washington, DC; University
of North Carolina (K.E.N.), Chapel Hill, NC; Southwest Foundation for Biomedical Research (J.W.M.), San Antonio, Tex; University of Oklahoma
Health Sciences Center (Y.Z., E.T.L.), Oklahoma City, Okla; and University of Pittsburgh (S.D., R.E.F.), Pittsburgh, Pa.
The views expressed in this paper are those of the authors and do not necessarily reflect those of the Indian Health Service.
Reprint requests to Lyle Best, MD, #1 Airport Rd, RR1, Box 88, Rolette, ND 58366. E-mail [email protected]
© 2004 American Heart Association, Inc.
Circulation is available at http://www.circulationaha.org
DOI: 10.1161/01.CIR.0000109757.95461.10
471
472
Circulation
February 3, 2004
Coronary artery disease (CAD) accounts for a large proportion of mortality and morbidity in American Indian
communities.19 The Strong Heart Study (SHS) is a longitudinal cohort study of CAD and its risk factors in American
Indians of different ethnicity living in 3 different locations.
We sought to investigate prospectively whether the genotypes
previously associated with low MBL levels were independent
predictors of incident CAD among this population.
Methods
Downloaded from http://circ.ahajournals.org/ by guest on June 16, 2017
The American Indian communities participating in SHS and the
study design, survey methods, and laboratory techniques have been
described previously.20,21 Approval was obtained from relevant
Institutional Review Boards and tribes, and all participants gave
informed consent. The present study genotyped 434 participants
selected as cases or controls from among the 4549 individuals
originally enrolled at age 45 to 74 years in the SHS between July
1989 and January 1992. At enrollment and at 2 subsequent times, a
physical examination was conducted along with a fasting venipuncture, standardized blood pressure measurements, and ECGs, recorded and coded as described previously.20,21 American Diabetes
Association criteria were used to classify participant diabetic status.22 Participants were considered hypertensive if they were taking
antihypertensive medications and had a systolic blood pressure
⬎140 mm Hg or a diastolic blood pressure greater than 90 mm Hg.
Covariate measurements are from the examination just before the
defining event.
Ascertainment of fatal and nonfatal cardiovascular events occurring between examinations was accomplished by medical record
review and/or yearly participant contact.23 Trained medical record
abstractors reviewed medical records for all potential CAD events or
interventions, including procedures diagnostic of CAD (eg, treadmill
test and coronary angiography). Using information from these
medical records, death certificates, and standard criteria, physician
reviewers determined the specific CAD diagnosis. After an initial
review, a second physician independently abstracted records with a
diagnostic concordance rate ⬎90%. Discordant conclusions were
adjudicated by additional review and discussion.
Cases were identified by evidence of definite myocardial infarction (MI), definite CAD without MI, definite evidence of MI by
Minnesota ECG coding,23 or mortality codes indicating either
definite MI, sudden death due to coronary heart disease, or definite
coronary heart disease occurring after initial enrollment and DNA
collection through December 31, 1999.20 Participants with only a
diagnosis of possible CAD, “other cardiovascular disease,” stroke,
congestive heart failure, or peripheral vascular disease were excluded. Controls were those individuals without any of the above
diagnoses.
DNA Analysis and Assignment of Genotype Status
DNA was genotyped for the presence of the B, C, or D structural
variations and 1 promoter polymorphism, the G/C polymorphism at
⫺550 bp (the H and L alleles)7 of the MBL gene. MBL genotypes
were determined by the oligonucleotide ligation assay as described
by Nickerson and colleagues.24 Genotypes of quality-control samples were determined by direct DNA sequencing. Genotyping was
done in a manner that was blinded to case-control status. The
structural variations were assumed to occur on opposing chromosomes. A number of promoter variants and structural alleles have
been found to be in complete linkage disequilibrium. The B and C
structural and X promoter alleles are always associated with the L
promoter, whereas the D structural allele is invariably linked with the
H promoter.8 Inferred haplotypes were developed from these known
relationships.
Individuals were considered exposed to the effects of MBLdeficient genotype (LOW_1) in the primary analysis if they had
either 2 structural variations (OO) or an inferred LA/O genotype. In
a supplementary analysis, exposure to the LOW_2 composite genotype (OO or LA/O or LA/LA) was considered. These risk genotypes
TABLE 1.
Descriptive Statistics of Population
Variables
Case
(n⫽217)
Control
(n⫽217)
Female gender, %
48.9
48.9
Age, y (mean⫾SD)
60.8⫾8.2
60.5⫾8.3
60.8
35.5
Hypertension, %
Current or former smoking, %
P*
0.2
⬍0.0001
71.7
69.3
Total cholesterol, mg/dL
203.7⫾46.1
190.9⫾37
LDL cholesterol, mg/dL
125.8⫾39.6
120.9⫾31.7
0.15
HDL cholesterol, mg/dL
40.2⫾12.6
43.3⫾12.6
0.01
Total triglyceride, mg/dL
154.9⫾0.7
120.6⫾0.5
69
37
Diabetes, %
0.6
⬍0.0012
0.0001
⬍0.0001
Body mass index, kg/m2
30.4⫾5.1
30.4⫾6.4
1.0
American Indian heritage
(median)
100 (25–100)
100 (6.3–100)
0.2
Fibrinogen, mg/dL
368.9⫾100.7
328.2⫾73.8
⬍0.0001
48.3
23.8
⬍0.0001
Albuminuria, %
*Comparison between case and control pairs.
were compared with reference genotypes categorized as ALL_1 or
ALL_2 (all genotypes not included in either LOW_1 or LOW_2,
respectively) or HIGH (either HA/HA or HA/LA). There is ample
documentation of the biological effect of these various genotypes on
basal MBL levels,8 although unidentified background genetic influences in unique populations are always possible.
Statistical Analysis
Cases (n⫽217) were individually matched with controls for SHS
center, gender, and age (within 5 years) by a computer algorithm.
Descriptive statistics of cardiovascular covariates used paired t test,
McNemar’s ␹2 test, and sign rank test for comparisons. The covariates included hypertension (HTN; yes/no), cigarette smoking status
(current or ex-smoker versus nonsmoker), type 2 diabetes mellitus
(DM2) status, total cholesterol, LDL cholesterol, HDL cholesterol,
triglycerides, body mass index, self-reported American Indian heritage (%), albuminuria, and fibrinogen. Those with normal glucose
tolerance and impaired glucose tolerance were categorized as nondiabetic, and the presence of either microalbuminuria (urinary
albumin/creatinine ratio ⱖ30 mg/g) or macroalbuminuria was combined for analysis.
McNemar’s test was used to compare numbers of discordant pairs.
Conditional logistic regression models (SAS/STAT 8.1 by SAS
Institute Inc) were also used to evaluate the relation between MBL
genotypes and CAD, with adjustment for covariates known to
influence the risk of CAD. Models were conditioned on the original
matched variables, and additional covariates were reduced by forward selection if covariates were found insignificant at the P⬎0.05
level. In analyses with HIGH as the referent genotype, indicator
variables were used to create 3 composite genotypes, LOW, HIGH,
and “other.” Results were not statistically significant for “other”
genotypes and are not shown.
Results
Characteristics of the 217 matched pairs are summarized in
Table 1. Among cases, 66 were defined by mortal events, 28
by a single morbid event, and the remaining 123 by multiple
morbid events. Cardiovascular risk factors such as HTN, total
cholesterol, low HDL cholesterol, triglycerides, DM2, fibrinogen, and albuminuria were increased in cases compared with
controls. Table 2 shows that the prevalence of OO genotypes
among both cases and controls (4.6%) was similar to that
reported for both northern Europeans3 (3%) and indigenous
Best et al
TABLE 2.
Mannose-Binding Lectin and Coronary Artery Disease
Distribution of MBL Alleles
TABLE 4. Genotypes in Matched Pairs of CVD Cases and
Controls (nⴝ217 Pairs)
Variables
Case
(n⫽217)
Control
(n⫽217)
P†
A/A
139 (64)
150 (69)
0.29
A/B
57 (26)
47 (22)
0.28
A/C
4 (1.8)
2 (1.0)
0.41
A/D
6 (2.7)
9 (4.1)
0.44
SUM A/O
67 (31)
58 (27)
B/B
9 (4.1)
8 (3.7)
B/C
0 (0)
0 (0)
B/D
2 (1.0)
1 (0.5)
C/C
0 (0)
0 (0)
C/D
0 (0)
0 (0)
D/D
0 (0)
0 (0)
SUM O/O
11 (5.1)
119 Pairs
Controls*
Cases
Controls†
ALL_1
LOW_1
HIGH
LOW_1
ALL_1
167
18
䡠䡠䡠
䡠䡠䡠
0.34
LOW_1
30
2
0.81
HIGH
䡠䡠䡠
䡠䡠䡠
䡠䡠䡠
81
䡠䡠䡠
12
LOW_1
䡠䡠䡠
䡠䡠䡠
24
2
135 Pairs
0.56
Controls‡
Cases
9 (4.1)
473
Controls§
ALL_2
LOW_2
HIGH
LOW_2
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0.65
ALL_2
156
16
䡠䡠䡠
䡠䡠䡠
37
8
䡠䡠䡠
䡠䡠䡠
䡠䡠䡠
81
䡠䡠䡠
14
Allele Freq A
345/434 (79)
358/434 (82)
0.31
LOW_2
Allele Freq O
89/434 (21)
76/434 (18)
0.31
HIGH
H/H
99 (46)
93 (43)
0.58
H/L
78 (36)
102 (47)
0.02
L/L
40 (18)
22 (10)
0.009
Allele Freq H
276/434 (64)
288/434 (66)
0.42
Allele Freq L
158/434 (37)
146/434 (34)
0.42
LOW_2
32
8
䡠䡠䡠
䡠䡠䡠
LOW_1 indicates OO or LA/O; LOW_2, OO or LA/O or LA/LA; HIGH, HA/HA or
HA/LA; ALL_1, any genotype that is not LOW_1; and ALL_2, any genotype that
is not LOW_2.
*␹2⫽3.0, P⫽0.08; †␹2⫽4.0, P ⫽0.046; ‡␹2⫽8.32, P⫽0.0039; §␹2⫽7.04,
P⫽0.008.
Allele Freq indicates frequency of allele. Values are n (%).
groups (2% to 4%) in Greenland12,14 and Canada.25 Among
both cases and controls, the LL genotype frequency in the
present study (14.3%) was midway between that reported for
European (38%) and Eskimo (3%) populations.8 Heterozygous AO and HL individuals made up 28.8% and 41.5% of
total cases and controls, respectively. Table 3 indicates the
proportion of various inferred haplotypes and combined
genotypes in cases and controls, with significant differences
between cases and controls of HA/LA, LA/LA, and LOW_2
composite genotypes. Control population genotypes showed
no significant deviation from expected Hardy-Weinberg distributions (data not shown).
Table 4 shows a univariate analysis of differences in
discordant case-control pairs. Significant differences in discordant pairs were seen in comparison of LOW_2 and both
reference genotypes, but LOW_1 genotype was only signifTABLE 3.
Inferred Haplotypes and Combined Genotypes
Variables
Case
(n⫽217),
n (%)
Control
(n⫽217),
n (%)
HA/HA
96 (44)
85 (39)
0.3
HA/LA
30 (14)
61 (28)
0.0003
LA/LA
13 (5.9)
4 (1.8)
HA/O
46 (21)
47 (21)
0.91
LA/O
21 (9.7)
11 (5.1)
0.058
O/O
11 (5.1)
9 (4.1)
0.65
HIGH (HA/HA or HA/LA)
126 (58.1)
146 (67.3)
0.057
LOW_1 (O/O or LA/O)
32 (14.8)
20 (9.2)
0.083
LOW_2 (O/O or LA/O or LA/LA)
45 (20.7)
24 (11.1)
0.004
P†
0.029
icant compared with the HIGH group. Results of conditional
logistic regression models that tested associations between
the outcome of CAD and both genotypic risk groups are
found in Table 5. Unadjusted, the LOW_1 genotype compared with the HIGH reference group was marginally significant as a predictor of CAD, with an OR of 1.8 (95% CI 0.98
to 3.24, P⫽0.057), but when adjusted for the significant
covariates of DM2, fibrinogen, triglycerides, and HTN, the
OR was 3.3 (95% CI 1.4 to 7.7, P⫽0.005). The LOW_2 risk
genotype showed highly significant predictive value compared with either the HIGH or ALL_2 reference groups, in
both univariate and adjusted models (Table 5).
TABLE 5. Conditional Logistic Regression Models Comparing
Various Risk and Reference Genotypes
Risk
Genotype
LOW_1
LOW_1
LOW_2
LOW_2
Reference
Genotype
Adjusted
OR
CI
P
ALL_1
No
1.67
0.93–2.99
0.087
Yes*
2.97
1.31–6.72
0.009
No
1.79
0.98–3.24
0.057
Yes*
3.32
1.43–7.73
0.005
HIGH
ALL_2
No
2.31
1.29–4.16
0.005
Yes*
3.19
1.45–7.02
0.004
No
2.33
1.29–4.20
0.005
Yes*
3.42
1.52–7.69
0.003
HIGH
*A total of 170 pairs with available covariates were compared. Significant
covariates retained were HTN, DM2, triglycerides, and fibrinogen.
474
Circulation
February 3, 2004
Discussion
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The present study is the first of prospective design and shows
a strong, independent association between variant MBL
genotypes predictive of lower MBL levels and incident CAD.
This is particularly remarkable in this population of American
Indians given the marked presence of other CAD risk factors
such as DM2, HTN, and albuminuria, for which we were able
to adjust in our analysis. These results suggest that MBL
variant alleles are determinants of CAD for a subset of
individuals, independent of other risk factors.
The initial report of an association between MBL genotypes and CAD from Norway indicated that the prevalence of
homozygous structural (but not heterozygous) genotypes
predicting low levels of MBL was increased among those
with prior coronary artery bypass procedures compared with
normal blood donors, although other risk factors for cardiovascular disease were not reported.3 Other attempts to explore
possible relationships between CAD and MBL function have
yielded somewhat conflicting results either because of the
absence of control for other cardiovascular risk factors in
small study samples or the use of less specific outcomes.
These include the association of MBL variants with a slightly
higher mean area of plaque detected in the carotid artery in
whites at high risk for CAD, although the more common
parameter of carotid atherosclerosis, arterial wall thickness,
was not reported.16 In another study of US physicians, no
relationship was noted between MBL levels and self-reported
peripheral arterial disease.17 Most recently, a significant
association between persistent infection with Chlamydia
pneumoniae and CAD was reported, but only in the context of
OO or AO structural MBL genotypes.18 In contrast, the
present study showed a strong association of the MBL variant
structural and promoter alleles directly with CAD.
The theoretical basis of an increased risk of CAD due to
low levels of MBL is that inflammation can initiate atherosclerosis1 and insufficient MBL can increase the risk and
duration of inflammatory infections.9 –12 Paradoxically, elevated levels of MBL may enhance tissue damage during acute
injury, because its inhibition with monoclonal antibody limited myocardial complement deposition and ischemic injury
in an experimental model of reperfusion injury.26
Differences in MBL expression have been recognized as
common and important immune modulating effects on the
human response to infectious agents.5,9,10,12,27 A possible
example of these interactions may be the high prevalence of
the HYA haplotype in the Eskimo population of Greenland
and the very low prevalence of this haplotype in African
populations.8 Thus, the nonconcordant studies of MBL and
CAD to date may reflect different population prevalence rates
of infectious agents, as well as host responses. Our inability
to observe an association between heterozygous variant MBL
structural alleles and CAD, consistent with the original report
by Madsen et al,3 may reflect differing thresholds for the
influence of MBL on the various outcomes of CAD versus
clinical infections, as previously suggested.27 Alternatively,
the dynamic response of promoter alleles to infectious exposures may be more important than the presumably static
effect of structural variants on basal MBL levels. Although
the prevalence of MBL genotypes among the Canadian Inuit
and the relationship of MBL genotypes to acute infections
among the Inuit of Greenland have been established, little is
known about the prevalence of MBL polymorphisms and
their potential relationship to CAD in other indigenous
populations.12,25
The strengths of the present study include its prospective
design; a large, population-based sample; the systematic
adjudication of CAD events; a high probability of ascertainment of all events; and adjustment for multiple known CAD
risk factors. Analyses of the additional affects of the 3
remaining promoter MBL variations that were not assayed
may have been useful. Future studies should examine whether
genotype is associated with CAD in younger individuals or
with exposure to various infectious agents.
In the present study, a prevalence of at least 11% for MBL
genotypes, which confers an adjusted OR of 3.2 for CAD,
suggests that future interventions guided by MBL genotypes
that predict deficiencies in this innate immune defense may
offer important public health benefits for this and possibly
other populations. Much additional work needs to be done,
however, to confirm the relationship between MBL and
CAD, determine proper screening methods, and explore
potential modulators of MBL action.
Acknowledgments
This work was supported by cooperative agreement grants U01HL65520, U01-HL41642, U01-HL41652, U01-HL41654, U01HL65521, and R01HL62233 from the National Heart, Lung, and
Blood Institute, Bethesda, Md. We thank the SHS participants,
Indian Health Service facilities, and participating tribal communities
for their extraordinary cooperation and involvement, which has
contributed to the success of the Strong Heart Study. Lyle Best,
Michael Davidson, Kari North, and Ying Zhang were responsible for
study design, data analysis, and manuscript preparation. Robert
Ferrell and Susan DeCroo were responsible for laboratory test design
and analysis. Jean MacCluer, Elisa Lee, and Barbara Howard
contributed to manuscript preparation.
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Prospective Analysis of Mannose-Binding Lectin Genotypes and Coronary Artery Disease
in American Indians: The Strong Heart Study
Lyle G. Best, Michael Davidson, Kari E. North, Jean W. MacCluer, Ying Zhang, Elisa T. Lee,
Barbara V. Howard, Susan DeCroo and Robert E. Ferrell
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Circulation. 2004;109:471-475; originally published online January 19, 2004;
doi: 10.1161/01.CIR.0000109757.95461.10
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