The Journal of Clinical Endocrinology & Metabolism Vol. 85, No. 8 2801-2804
Copyright © 2000 by The Endocrine Society
The T 54 Allele of the Intestinal Fatty Acid-Binding Protein 2 Is Associated with a Parental History of Stroke1
Martin Carlsson,
Marju Orho-Melander,
Jan Hedenbro,
Peter Almgren and
Leif C. Groop
Department of Endocrinology, Malmo University Hospital (M.C.,
M.O.-M., P.A., L.C.G.), S-205 02 Malmo, Sweden; and
Department of Surgery, Lund University Hospital, University of Lund
(J.H.), S-221 85 Lund, Sweden
Address all correspondence and requests for reprints to: Martin Carlsson, M.D., Department of Medicine, Kalmar Hospital, S-391 85 Kalmar, Sweden. E-mail: martinC{at}ltkalmar.se
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Abstract
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To test the hypothesis that the A/T polymorphism of the fatty
acid-binding protein 2 gene (FABP2) is associated with
impaired lipid metabolism and cardiovascular disease, we compared
clinical characteristics and a parental history of cardiovascular
disease between 213 sibling pairs discordant for the polymorphism.
Siblings with an excess of the T54 allele had higher triglyceride
(P = 0.002) and cholesterol (P
= 0.019) concentrations than siblings with the A54 allele. Parents of
offspring with the T54T and T54A genotypes reported an increased
prevalence of stroke compared to parents of offspring with the A54A
genotype (P = 0.007). In summary, we have confirmed
the association of the FABP2 T54 allele with increased concentrations
of cholesterol and triglycerides in genotype-discordant sibling pairs.
We also present novel evidence that genetic variation in the FABP2 gene
may increase susceptibility to stroke.
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Introduction
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FATTY ACID-BINDING proteins (FABP)
represent a family of proteins that is thought to be involved in
intestinal fatty acid (FFA) absorption and intracellular metabolism of
long-chain FFA (1, 2). Several different isoforms of FABP have been
described; each encoded by different genes. A FABP2 gene on chromosome
4q encodes an intestinal isoform (IFABP) that is expressed in
enterocytes (3) and has a high affinity for long-chain fatty acids (4).
A common polymorphism at codon 54 of this gene results in replacement
of alanine with threonine. A complete tertiary structure has been
reported for the alanine 54 variant (2). In vitro, the
threonine-containing protein has a greater affinity for long-chain
fatty acids than the alanine-containing protein (4, 5). In addition,
subjects with the threonine-encoding allele (T54) have been shown to be
more insulin resistant (4, 6) and more obese (7, 8) than carriers of
the alanine-encoding allele (A54). The T54 allele has also been
associated with elevated triglyceride concentrations after a fat meal
(9) and reduced secretion of fecal bile acids in response to different
dietary fiber (10).
However, all studies have not confirmed a role for the T54 allele in
lipid and glucose metabolism (11, 12, 13). In a study from Finland, the
polymorphism did not modify the fatty acid composition of serum lipids
(11), nor did the polymorphism affect basal metabolic rate, insulin,
glucose, or lipid concentrations (12, 13). Population-based association
studies are often biased by the selection of the control group. To
circumvent this problem, we tested the hypothesis that the FABP2 T54
allele is associated with obesity, dyslipidemia, insulin resistance,
hypertension, and diabetes in siblings discordant for the A54T
polymorphism. This approach using genotype-discordant sibling pairs has
earlier been shown to be a valid test of association in the presence of
linkage (14, 15, 16, 17). We further investigated the possibility that the T54
allele could contribute to the risk of cardiovascular disease (CVD) by
relating the parental history of CVD with the genotype status in the
offspring.
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Subjects and Methods
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Subjects
Three groups of subjects from southern Sweden were included in
the study. Group 1 consisted of 687 siblings from 210 families, 399 of
which had type 2 diabetes [200 males and 199 females; age, 60.1
± 12.3 yr; body mass index (BMI), 27.8 ± 4.7
kg/m2], 93 of whom had impaired glucose
tolerance (43 males and 50 females; age, 54.8 ± 16.4 yr; BMI,
26.8 ± 4.7 kg/m2) and 195 of whom had
normal glucose tolerance (84 males and 111 females; age, 48.9 ±
16.2 yr; BMI, 25.5 ± 3.9 kg/m2). All
subjects in the first group had first degree relatives with type 2
diabetes (siblings or parents), whereas 73% of the subjects had 1
parent with type 2 diabetes. Group 2 consisted of 59 unrelated,
morbidly obese, nondiabetic subjects without a family history of
diabetes undergoing bariatric surgery (15 males and 44 females; age,
40.5 ± 12.0 yr; BMI, 41.7 ± 5.
kg/m2).
For comparison of allele frequencies, we also included a third group of
59 unrelated lean nondiabetic subjects without a family history of
diabetes (28 males and 31 females; age, 58.5 ± 12.2 yr; BMI,
23.6 ± 2.6 kg/m2). To compare allele
frequencies between diabetic and control subjects, one diabetic patient
from each family was randomly selected. To compare differences in
personal and parental history of CVD, one subject from each family from
group 1 was randomly selected. Data on a parental history of CVD was
available from 210 unrelated subjects, all of whom had first degree
relatives with diabetes. We wanted to test the hypothesis that the
phenotypic difference between sibling pairs discordant for the FABP2
A54T polymorphism would differ significantly from zero. We advanced the
hypothesis that there will be a dose-dependent effect of the number of
T alleles on the phenotype by comparing the T54T and T54A genotypes
with the A54A genotype, or the T54T with the T54A genotype. A total of
213 sibling pairs discordant for the polymorphism from 97 families were
included. Of them, 158 sibling pairs had the same gender. Before
participating in the study, the purpose, nature, and potential risks
were explained, and informed written voluntary consent was obtained
from each subject. The study protocol was approved by the ethics
committee of Lund University.
Phenotypic characterization of the subjects
The studies were performed at 0800 h after a 12-h overnight
fast. Height and weight were measured with subjects in light clothing.
BMI was calculated as kilograms per m2. Waist was
measured with a flexible tape midway between the lowest rib and the
iliac crest and the hip circumference at the widest part of the gluteal
region. The waist to hip ratio was calculated. Blood pressure was
measured twice in the right arm with the subject in a supine position
after a 15-min rest, and the mean was calculated. If the fasting blood
glucose concentration was below 10 mmol/L, an oral glucose tolerance
test (OGTT) was performed. During the OGTT, the subjects ingested
75 g glucose in a volume of 300 mL, and venous samples for
measurement of blood glucose and serum insulin were drawn. For fasting
glucose and insulin concentrations, the mean of the -5 and 0 min
values was used. Venous fasting blood samples were drawn for the
measurements of serum concentrations of FFA, total cholesterol, and
triglycerides.
Questionnaire
Information on personal and family history of diabetes, stroke,
and myocardial infarction was based upon a standardized,
nurse-administered questionnaire. Myocardial infarction (MI) was
defined as either fatal or nonfatal myocardial infarction. Stroke was
defined as cerebral thrombosis or hemorrhage diagnosed in hospital or
primary health care. The majority of cases (>85%) represented
ischemic stroke. Hypertension was defined as systolic blood pressure of
160 mm Hg or more and/or a diastolic blood pressure of 95 mm Hg or more
or use of antihypertensive drugs.
Assays
Blood glucose during the OGTT was measured with a HemoCue Blood
Glucose Analyzer (HemoCue AB, Angelholm Sweden). Serum was separated
and kept at -20 C until analyzed. FFA were measured by an enzymatic
colorimetric method using a commercial kit (Wako Chemicals GmbH, Neuss,
Germany). Insulin concentrations were measured by specific RIAs
(DAKO Corp., Cambridgeshire, UK). Cholesterol and
triglyceride concentrations were analyzed with commercially available
kits using Technicon DAX 48 (Bayer Sverige AB, Gothenborg,
Sweden).
Genotyping
The G to A nucleotide substitution in exon 2 of the FABP2 gene,
which changes an alanine at codon 54 to a threonine (A54T), was
genotyped using an earlier described PCR-restriction fragment length
polymorphism method (4) with the following changes: exon 2 was
PCR amplified from 25 ng genomic DNA in a 20-µL volume consisting of
1 x PCR buffer (Perkin-Elmer Corp., Foster City,
CA), 0.25 mmol/L of each deoxy-NTP, 10 pmol of each primer, 2.5 mmol/L
MgCl2, and 0.5 U Taq polymerase
(Amersham Pharmacia Biotech, Sweden). PCR reactions
were initiated by an initial denaturation (30 s at 94 C), followed by
amplification for 30 cycles of denaturation (30 s at 94 C), annealing
(30 s at 55 C), and extension (30 s at 72 C) and by a final extension
step (10 min at 72 C). The amplified 180-bp product was digested with
HhaI according to the manufacturers instructions
(Amersham Pharmacia Biotech) and separated on a 3%
agarose gel. The T54 allele lacking the HhaI site migrated
as a 180-bp fragment, whereas the A54 allele was cleaved and appeared
as 99- and 81-bp fragments. Twelve percentage of all samples was
genotyped twice to exclude genotyping errors.
Statistical analysis
Frequency differences between the groups were tested by Pearson
2 test using a BMDP statistical package
(Biomedical Data processing version 7.0, 1992, Los Angeles, CA).
Differences between the genotype discordant sibling pairs were
estimated using a permutation test for paired replicates based upon a
modified program (17, 18). The differences between continuous variables
were computed as the value in sibling 1 with and excess of T54 alleles
minus the value in sibling 2. In a permutation test for 213 sibling
pairs, there are 2213 equally likely outcomes for
each variable under the assumption of no difference between the pairs.
Because of computational limitations, the two-tailed P
values were estimated using a large (107) random
sample from all possible permutations. If the observed sum of
differences entered into the 5% region of rejection, the difference
between the pairs was considered significant. Finally, for testing
differences in diabetes prevalence, the McNemar test of symmetry for
paired replicates was performed for a randomly chosen one
genotype-discordant sibling pair per family. All statistical tests were
two-sided, and P < 0.05 was considered statistically
significant.
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Results
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Allele and genotype frequencies in different groups
Allele and genotype frequencies did not differ among unrelated
type 2 diabetes patients (TT, 6%; TA, 40%; AA, 55%), obese subjects
(TT, 8%; TA, 39%; AA, 53%), and lean controls (TT, 12%; TA, 36%;
AA, 52%; P = NS), nor did the prevalence of diabetes
differ between siblings discordant for the FABP2 polymorphism. None of
the observed genotype frequency distributions deviated from
Hardy-Weinberg equilibrium.
Sibling pair analysis
Of sibling pairs discordant for the T54A polymorphism, the sibling
with more T54 alleles had higher triglyceride (P =
0.002) and higher cholesterol (P = 0.019)
concentrations than the sibling with two A54 alleles (Table 1
). When only siblings of the same gender
were considered, the differences remained statistically significant
(cholesterol, P = 0.053; triglyceride,
P = 0.013).
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Table 1. Observed sum of differences between 213 sibling
pairs discordant for the FABP2 codon 54 polymorphism analyzed by a
permutation test
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Personal and parental history of diabetes, MI, and stroke
There were only a few subjects with a personal history of MI
and/or stroke (MI: TT, 0%; TA, 2.9%; AA, 2.9%; stroke: TT, 0%; TA,
1.4%; AA, 2.4%), and there was no difference in the prevalence of
hypertension among the different genotype carriers (TT, 2.4%; TA,
13.8%; AA, 17%; P = NS). Given the low prevalence of
CVD in the subjects, we related the genotype in the offspring to a
parental history of MI, stroke, or diabetes (Table 2
). There was a statistically significant
association between parental history of stroke and the T54T and T54A
genotypes in the offspring. Of subjects with a parental history of
stroke, 67% were either heterozygous or homozygous for the T54 allele
(P = 0.0071). Among the parents with stroke, 35% had
diabetes. If only nondiabetic parents were included, 69% of the
offspring had either the T54T or the T54A genotype (P =
0.011 vs. expected). If we include all subjects from the
families (n = 683), stroke was more common among parents of
homozygous T54T than among homozygous A54A carriers (P
= 0.041) and was more common among heterozygous A54T carriers than
among homozygous A54A carriers (P = 0.0011), suggesting
that the T allele must have been transmitted from the parent with
stroke.
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Table 2. Prevalence of FABP2 genotypes by parental history of
diabetes, myocardial infarction, and stroke in 210 subjects
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Discussion
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To test the hypothesis put forward in association and in
vitro studies that the T54 allele of the FABP2 gene influences
phenotypic expression, we used a genotype-discordant sibling pair
approach. The study provided conclusive evidence for a dose-dependent
effect of the number of T54 alleles on triglyceride and cholesterol
concentrations. In contrast to population-based association studies,
this approach can control for the genetic background of the control
population. The common T54 allele appears to affect the intracellular
transport and intestinal affinity for long-chain fatty acids (4, 5).
Increased levels of FFA have been associated with insulin resistance
(19, 20, 21, 22) and diabetes (23, 24, 25), and increased delivery of FFA to the
liver stimulates very low density lipoprotein production. Although the
T54 allele was associated with high triglyceride concentrations, we
could not detect any significant association with FFA concentrations.
This may be due to the fact that the subjects were tested in the
fasting state. We also found an association between the T54 allele and
high cholesterol concentrations. Cholesterol is either absorbed from
the diet or synthesized by cells in the body. It is eliminated by the
body through excretion as free cholesterol in the bile or is converted
to bile acids and secreted into the intestine (26). The finding of
elevated cholesterol concentrations in carriers of the T54 allele is in
accordance with earlier reports showing that subjects with the T54
allele have reduced excretion of fecal bile acids (10). In a Finnish
study, variants of the FABP2 gene were not associated with coronary
heart disease (27), and we did not find an association with FABP2 T54
allele and MI; instead, we found a strong correlation to stroke in the
parents. Although there are abundant data on the familial clustering of
stroke (28, 29), we are not aware of any earlier study that has
evaluated the risk of stroke in relation to any polymorphism in the
FABP2 gene. However, a similar approach has been used to search for an
association between the angiotensin converting enzyme gene and
parental history of CVD (30). It is likely that the parental prevalence
of stroke and MI in our study population was higher than that in the
general population, because all subjects had first degree relatives
with type 2 diabetes. However, the association between the FABP2 T54
allele and stroke was not restricted to the parents with diabetes. In
fact, the association was seen even though parents with diabetes and
stroke were excluded.
Stroke was more common among parents of homozygous T54T carriers than
among parents of heterozygous A54T carriers and was more common among
parents of heterozygous A54T carriers than among parents of homozygous
A54A carriers, suggesting that the T allele must have been transmitted
from the parent with stroke.
In conclusion, using a genotype-discordant sibling pair approach, we
demonstrate an association between the number of T54 alleles of the
FABP2 gene and elevated triglyceride and cholesterol concentrations. We
also show that the T54 allele may influence the susceptibility to
cardiovascular disease, as parents of offspring with the T54 allele
reported an increased prevalence of stroke.
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Acknowledgments
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We are indebted to the study subjects for their participation
and to Ms. Ylva Wessman and Ms. M. Åberg for excellent technical
assistance.
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Footnotes
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1 This work was supported by grants from the Swedish Medical Research
Council, the Sigrid Juselius Foundation, the Swedish Diabetes Research
Foundation, the Juvenile Diabetes Foundation (Juvenile Diabetes
Foundation-Wallenberg Grant K 98-990-12812-01A), the Albert Påhlssons
Foundation, Malmo University Hospital, the Ernhold Lundström
Foundation, the Diabetes Association in Malmo, the Anna-Lisa and
Sven-Eric Lundgren Foundation, the Swedish Foundation for the Study of
Diabetes, and an European Economic Community Paradigm BMH-4-CT95-0662
grant. 
Received September 29, 1999.
Revised May 15, 2000.
Accepted May 15, 2000.
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