Download Free PDF

European Review for Medical and Pharmacological Sciences
2010; 14: 89-95
Influence of Ala54Thr polymorphism of
fatty acid-binding protein 2 on insulin
resistance and adipocytokines in
patients with diabetes mellitus type 2
D.A. DE LUIS, M. GONZALEZ SAGRADO, R. ALLER, O. IZAOLA,
R. CONDE, B. DE LA FUENTE
Institute of Endocrinology and Nutrition, Medicine School and Unit of Investigation,
Hospital Rio Hortega, University of Valladolid, Valladolid (Spain)
Abstract. – Background: A transition G to
A at codon 54 of FABP2 results in an amino acid
substitution (ala 54 to Thr 54). This polymorphism could be associated with insulin resistance and adipocytokines in patients with diabetes mellitus type 2.
Objective: The aim of our study was to investigate the influence of Thr54 polymorphism in
the FABP2 gene on adipocytokines and insulin
resistance in the fasted state in naïve patients
with diabetes mellitus type 2.
Design: A population of 58 naïve patients
with diabetes mellitus type 2 (fasting glucose
>126 mg/dl) and obesity (body mass index >30)
was analyzed in a prospective way. An indirect
calorimetry, tetrapolar electrical bioimpedance,
blood pressure, a serial assessment of nutritional intake with 3 days written food records
and biochemical analysis (lipid profile, adipocytokines, insulin, CRP and HOMA) were performed. The statistical analysis was performed
for the combined Ala54/Thr54 and Thr54/Thr54
as a mutant group and wild type Ala54/Ala54 as
second group.
Results: Thirty-three patients (56.9%) had
genotype Ala54/Ala54 (wild type group) and 25
(43.1%) patients Ala54/Thr54 (19 patients,
32.8%) or Thr54/Thr54 (6 patients, 10.3%) (mutant group). C-reactive protein (5.6±4.2 vs
8.7±5.3 mg/dl: p<0.05), insulin (22.9±11 vs
6.6±12 mUI/L: p<0.05) and HOMA (7.65±5.3 vs
9.1±6.3: p<0.05) were higher in mutant group
than wild group. Anthropometric parameters,
dietary intakes and adipocytokines were similar
in both genotypes.
Conclusion: The novel finding of this study is
the association of the Thr54/Ala54 and Thr54/
Thr54 FABP2 genotypes with higher levels of C
reactive protein, insulin and HOMA.
Key Words:
Adipokines, Diabetes Mellitus, FABP2, Polymorphism, Insulin resistance.
Introduction
The current view of adipose tissue is that of an
active secretory organ, sending out and responding to signals that modulate appetite, insulin sensitivity, energy expenditure, inflammation and
immunity1-10.
The fatty acid (FA) binding protein 2(FABP2)
gene codes for intestinal FABP, which is a member of a family of small intracellular lipid-binding proteins. FABP plays an important role in
several steps of unsaturated and saturated long
chain fatty acids (LCFAs), protection of the cell
from the cytotoxic effects of FFAs, and modulation of the enzyme additive involved in lipid metabolism11-12. Recently, a group13 reported a new
G/A mutation. A transition G to A at codon 54 of
FABP2 results in an amino acid substitution (Ala
54 to Thr 54). This polymorphism is common,
with a Thr54 allelic frequency of 30% in most
populations. This amino acid substitution was associated with high insulin resistance, and fasting
insulin concentrations13. Carriers of the Thr54 allele have a 2-fold greater affinity for the longchain fatty acids than those with the Ala 54,
which supports the role of the FABP2 Ala54Thr
polymorphism in the etiology of metabolic disorders such as insulin resistance14.
Corresponding Author: Daniel A. de Luis, MD; e-mail: [email protected]
89
D.A. de Luis, M. Gonzalez Sagrado, R. Aller, O. Izaola, R. Conde, B. de La Fuente
The aim of our study was to investigate the influence of Thr54 polymorphism in the FABP2
gene on adipocytokines and insulin resistance in
the fasted state in naïve patients with diabetes
mellitus type 2.
Subjects and Methods
Subjects
A population of 58 naïve patients with diabetes mellitus type 2 (fasting glucose >126
mg/dl) and obesity (body mass index >30) was
analyzed in a prospective way (research protocol
accepted by the Ethical Committee). These patients were recruited in a Nutrition Clinic Unit
and signed an informed consent. Exclusion criteria included history of cardiovascular disease or
stroke during the previous 36 months, total cholesterol >300 mg/dl, triglycerides >400 mg/dl,
blood pressure >140/90 mmHg, as well as the
use of sulphonylureas, thiazolidinediones, metformin, insulin, glucocorticoids, antineoplastic
agents, angiotensin receptor blockers, angiotensin converting enzyme inhibitors, psychoactive medications, drinking and/or smoking
habit.
Procedure
All patients with a 2 weeks weight-stabilization period before recruitment were enrolled.
Weight, blood pressure, basal glucose, c-reactive
protein (CRP), insulin, insulin resistance
(HOMA), total cholesterol, LDL-cholesterol,
HDL-cholesterol, triglycerides blood and
adipocytokines (leptin, adiponectin, resistin,
TNF-alpha, and interleukin 6) levels were measured at basal time. A tetrapolar bioimpedance,
an indirect calorimetry and a prospective serial
assessment of nutritional intake with 3 days written food records were realized. Genotype of
FABP2 gene polymorphism was studied.
Genotyping of FAPP2 Gene Polymorphism
Oligonucleotide primers and probes were designed with the Beacon Designer 4.0 (Premier
Biosoft International®, LA, CA). The polymerase
chain reaction (PCR) was carried out with 50 ng
of genomic DNA, 0.5 µL of each oligonucleotide
primer (primer forward: 5’-CAG TTC CGT CTG
CTA GAT TGT-3’; primer reverse: 5’-GCT GAC
AAT TAC ACA AGA AGG AA-3’), and 0.25 µL
of each probes (wild probe: 5’-Fam-CAA AGA
90
ATC AAG CAC TTT TCG AAA CA-BHQ-1-3’)
and (mutant probe: 5’-Hex-AGA ATC AAG
CGC TTT TCG AAA CA-BHQ-1-3’) in a 25 µL
final volume (Termociclador iCycler IQ (BioRad®), Hercules, CA). DNA was denaturated at
95ºC for 3 min; this was followed by 50 cycles of
denaturation at 95ºC for 15 s, and annealing at
59.3ºC for 45 s). The PCR were run in a 25 µL final volume containing 12.5 µL of IQTM Supermix (Bio-Rad®, Hercules, CA) with hot start Taq
DNA polymerase. Hardy Weimberger equilibrium was assessed.
Assays
Serum total cholesterol and triglyceride concentrations were determined by enzymatic colorimetric assay (Technicon Instruments, Ltd.,
New York, N.Y.), while HDL cholesterol was determined enzymatically in the supernatant after
precipitation of other lipoproteins with dextran
sulfate-magnesium. LDL cholesterol was calculated using Friedewald formula.
Haemoglobin A1c levels were measured by
using high-pressure liquid chromatography. Plasma glucose levels were determined by using an
automated glucose oxidase method (Glucose
analyser 2, Beckman Instruments, Fullerton,
CA). Insulin was measured by RIA (RIA Diagnostic Corporation, Los Angeles, CA) with a
sensitivity of 0.5 mUI/L (normal range 0.5-30
mUI/L)15 and the homeostasis model assessment
for insulin sensitivity (HOMA) was calculated
using these values16. CRP was measured by immunoturbimetry (Roche Diagnostcis GmbH,
Mannheim, Germany), with a normal range of
(0-7 mg/dl) and analytical sensivity 0.5 mg/dl.
Adipocytokines
Resistin was measured by ELISA (Biovendor
Laboratory, Inc., Brno, Czech Republic) with a
sensitivity of 0.2 ng/ml with a normal range of
4-12 ng/ml17. Leptin was measured by ELISA
(Diagnostic Systems Laboratories, Inc., Minneapolis, TX) with a sensitivity of 0.05 ng/ml
and a normal range of 10-100 ng/ml 18 .
Adiponectin was measured by ELISA (R&D
Systems, Inc., Minneapolis, MN) with a sensitivity of 0.246 ng/ml and a normal range of 8.6521.43 ng/ml19. Interleukin 6 and TNF alpha were
measured by ELISA (R&D Systems, Inc., Minneapolis, MN) with a sensitivity of 0.7 pg/ml and
0.5 pg/ml, respectively. Normal values of IL6
was (1.12-12.5 pg/ml) and TNFalpha (0.5-15.6
pg/ml)20-21.
ALA54THR polymorphism and diabetes mellitus type 2
Indirect Calorimetry
For the measurement of resting energy expenditure, subjects were admitted to a metabolic
ward. After a 12 h overnight fast, resting metabolic rate was measured in the sitting awake subject in a temperature-controlled room over one
20 min period with an open-circuit indirect
calorimetry system (standardized for temperature, pressure and moisture) fitted with a face
mask (MedGem; Health Tech, Golden, USA),
coefficient of variation 5%. Resting metabolic
rate (kcal/day) and oxygen consumption
(ml/min) were calculated22.
Anthropometric Measurements
Body weight was measured to an accuracy of 0.5
kg and BMI computed as body weight/(height2).
Waist (narrowest diameter between xiphoid
process and iliac crest) and hip (widest diameter
over greater trochanters) circumferences to derive waist-to hip ratio (WHR) were measured,
too. Tetrapolar body electrical bioimpedance was
used to determine body composition with an accuracy of 5 g23. An electric current of 0.8 mA
and 50 kHz was produced by a calibrated signal
generator (Biodynamics Model 310e, Seattle,
WA) and applied to the skin using adhesive electrodes placed on right-side limbs. Resistance and
reactance were used to calculate total body water,
fat and fat-free mass.
Blood pressure was measured twice after a 10
minutes rest with a random zero mercury sphygmomanometer, and averaged.
Dietary Intake and Habits
Patients received prospective serial assessment
of nutritional intake with 3 days written food
records. All enrolled subjects received instruction
to record their daily dietary intake for three days
including a weekend day. Handling of the dietary
data was by means of a personal computer
equipped with personal software, incorporating
use of food scales and models to enhance portion
size accuracy. Records were reviewed by a registered dietitian and analyzed with a computerbased data evaluation system. National composition food tables were used as reference24.
Statistical Analysis
Sample size was calculated to detect differences over 5% in insulin resistance with 90%
power and 5% significance. The results were expressed as mean ± SD. The distribution of variables was analyzed with Kolmogorov-Smirnov
test. Quantitative variables with normal distribution were analyzed with a two-tailed Student’s-t
test. Non-parametric variables were analyzed
with the U-Mann-Whitney test. Qualitative variables were analyzed with the chi-square test,
with Yates correction as necessary, and Fisher’s
test. The statistical analysis was performed for
the combined Ala54/Thr54 and Thr54/Thr54 as a
group and wild type Ala54/Ala54 as second
group. Anova test was used to analized quantitative variables with three groups (Ala54/Thr54,
Thr54/Thr54 and Ala54/Ala54 patient groups). A
p-value under 0.05 was considered statistically
significant.
Results
Fifty eight patients gave informed consent and
were enrolled in the study. The mean age was
57.4±11.7 years and the mean BMI 37.8±6.5,
with 15 males and 43 females.
Thirty-three patients (56.9%) had genotype
Ala54/Ala54 (wild type group) and 25 (43.1%)
patients Ala54/Thr54 (19 patients, 32.8%) or
Thr54/Thr54 (6 patients, 10.3%) (mutant group).
Age was similar in both groups (wild type:
57.3±11.7 yrs vs mutant group: 56.1±11 yrs: ns).
Sex distribution was similar in both groups (wild
vs mutant group), males (27.3% vs 24%) and females (72.7% vs 76%).
Table I shows anthropometric variables, without statistical differences. Table II shows cardiovascular risk factors. C-reactive protein, insulin
and HOMA were higher in mutant group than
wild group.
Table III shows nutritional intake with 3 days
written food records. Calory, carbohydrate, fat,
and protein intakes were similar in both groups,
without differences between allelic groups.
Table IV shows levels of adipocytokines. No
differences were detected between genotypes.
Discussion
The novel finding of this study is the association of the Thr54/Ala54 and Thr54/Thr54 FABP2
genotypes with higher levels of insulin, HOMA
and C reactive protein.
One hypothesis to explain these data has been
shown in a previous study. Baier et al.13 concluded
91
D.A. de Luis, M. Gonzalez Sagrado, R. Aller, O. Izaola, R. Conde, B. de La Fuente
Table I. Anthropometric variables.
Characteristics
BMI
Weight (kg)
Fat free mass (kg)
Fat mass (kg)
WC (cm)
Waist to hip ratio
Systolic BP (mmHg)
Diastolic BP (mmHg)
RMR (kcal/day)
Ala54/Ala54
(n = 33)
(Ala54/Thr54 or Thr54/Thr54)
(n = 25)
37.4 ± 7.6
94.7 ± 20.4
53.1 ± 14.9
40.6 ± 17
112.1 ± 14
0.96 ± 0.1
135.4 ± 21.1
83.1 ± 9.1
1938 ± 421
37.4 ± 5.3
94.8 ± 15
51.2 ± 14.3
43.6 ± 14.8
118.9 ± 13.7
0.97 ± 0.09
138.5 ± 19
81.4 ± 9.1
2100 ± 805
RMR: resting metabolic rate. WC: Waist circumference. (*) p<0.05, in each group with basal values.
that threonine-containing protein may increase absorption and/or processing dietary fatty acids by
the intestine and therefore increase fat oxidation,
which has been shown to inhibit glucose uptake in
muscle and results in insulin resistance.
However, contradictory results have been described in the literature. Sipilainen et al.25 found
that obesity is not associated with specific variants in the FABP2 gene and that the Ala54-toThr polymorphism did not influence insulin levels in obese Finns.
The frequency of the Thr54 alele variant is
43% in our study. Slightly lower frequency have
been reported for other population as non diabetic Pima Indians (30%), Koreans (34%), Japanese
(35%), Swedish (30%) and white individuals
from USA (32%)26-30. Perhaps, these different
frequencies and outcomes could be explained by
inclusion criteria of subjects in previously studies
of the literature. For example, Carlsson et al31
have detected higher concentrations of triglyceride and cholesterol in the Thr54 allele patients,
in a population of obese patients with parenteral
history of cardiovascular disease. In a population
of type 2 diabetes mellitus32, a linear relationship
of mean fasting plasma triglyceride levels was
found and after fat ingestion, in homozygous for
the Thr54 allele than in wiltdtype patients. In
type 1 diabetes mellitus patients33 do not interact
with the codon 54 polymorphism of the FABP2
gene to cause dyslipemia. Other population association studies with insulin resistance and lipids
in patients with type 2 diabetes mellitus34,35 were
esentially negative. Perhaps, the type of diabetes,
the time course of this disease, pharmacological
treatments received by patients and comorbidities
Table II. Clasical cardiovascular risk factors.
Characteristics
Glucose (mg/dl)
Total ch. (mg/dl)
LDL-ch. (mg/dl)
HDL-ch. (mg/dl)
TG (mg/dl)
Insulin (mUI/L)
HOMA
CRP (mg/dl)
HbA1c (%)
Ala54/Ala54
(n = 33)
(Ala54/Thr54 or Thr54/Thr54)
(n = 25)
132.8 ± 28
211 ± 38
138.4 ± 39
51.4 ± 10.5
152.6 ± 58
22.9 ± 11
7.65 ± 5.3
5.6 ± 4.2
5.8 ± 0.9
131.8 ± 22
220 ± 44
144.9 ± 36
52.7 ± 11.6
163 ± 59
26.6 ± 12*
9.1 ± 6.3*
8.7 ± 5.3*
5.5 ± 0.7
Ch: Cholesterol. TG: Triglycerides CRP: c reactive protein. HOMA: Homeostasis model assessment. (*) p<0.05, in each group
with basal values.
92
ALA54THR polymorphism and diabetes mellitus type 2
Table III. Dietary intake.
Characteristics
Energy (kcal/day)
CH (g/day)
Fat (g/day)
S-fat (g/day)
M-fat(g/day)
P-fat (g/day)
Protein (g/day)
Exercise (hs./week)
Dietary fiber
Ala54/Ala54
(n = 33)
(Ala54/Thr54 or Thr54/Thr54)
(n = 25)
1682 ± 555
171.5 ± 72
72.9 ± 30
19.9 ± 11
35.1 ± 14.3
6.6 ± 3.2
82.4 ± 21
1.45 ± 2.8
15.3 ± 6.1
1550 ± 497
160.7 ± 66
66.7 ± 36
17.1 ± 9.2
30.9 ± 16.5
5.6 ± 3.4
78.9 ± 21
1.38 ± 2.9
14.7 ± 6.5
CH: Carbohydrate. S-fat: saturated fat. M-fat: monounsaturated fat. P-fat: polyunsaturated fat. No statistical differences.
could influence in these unclear previous results.
We propose studies with naïve diabetic patients
as our design.
The lack of association with cholesterol and
triglyceride levels is clear in our study. Other Authors have shown31,32 higher levels of cholesterol
and triglycerides in non-diabetic obese patients
with Thr allele. Nevertheles, Duarte et al36 have
shown a lower total and LDL cholesterol levels
in patients with Thr allele. These previous studies would have required composition analysis of
the dietary intake to determine whether dietary
components could be responsible for the lipid
profile modifications. For example, Marin et al37
have shown that insulin sensitivity decreased in
subjects with Thr54 allele of the FABP2 polymorphism when saturated fatty acids were replaced by monounsaturated fatty acids and carbohydrates. In our study dietary intake did not
show statistical differences between groups, in
this way our data have been controlled by dietary
intake and previous discrepancies could be explain by this uncontrolled factor (dietary intake).
In our study, the elevation of inflammation
markers (CRP) in patients with Thr allele, as
shown in previous studies38 could be related with
an altered postprandial response of fatty acids absorption (no measured in our design)39. Elevated
FFA increases the acummulation of triglycerides
in the adipocyte, related with imbalance of
lipoprotein lipase activity. The association of this
proimflammatory state with insulin resistance in
Th carriers could indicate the existence of complex gene-gene or gene-environment interactions
that may enhance metabolic abnormalities in
these patients.
In conclusion, the novel finding of this study is
the association of the Thr54/Ala54 and
Thr54/Thr54 FABP2 genotypes with higher levels of C reactive protein, insulin and HOMA.
Further studies are needed to elucidate the complex relationships40,41 among lipoprotein metabolism, fat storage, inflammation markers and Thr
allele. A role of Ala54Thr polymorphism on incidence of diabetes mellitus type 2 might be explored as a new association42.
Table IV. Circulating adypocitokines.
Characteristics
IL 6 (pg/ml)
TNF-alpha (pg/ml)
Adiponectin (ng/ml)
Resistin (ng/ml)
Leptin (ng/ml)
Ala54/Ala54
(n = 33)
(Ala54/Thr54 or Thr54/Thr54)
(n = 25)
3.34 ± 2.2
6.79 ± 3.8
33.3 ± 30
3.4 ± 1.8
82.7 ± 66
3.1 ± 2.5
6.4 ± 4.2
28.5 ± 23
3.7 ± 1.9
108.4 ± 68
IL-6: interleukin 6. (*) p<0.05, in each group with basal values.
93
D.A. de Luis, M. Gonzalez Sagrado, R. Aller, O. Izaola, R. Conde, B. de La Fuente
References
1) ARANCETA J, PEREZ RODRIGO C, SERRA MAJEM L. Prevalencia de la obesidad en España: estudio SEEDO
97. Med Clin (Barc) 1998; 111: 441-445.
2) MATSUDA M, SHIMOMURA I, SATA M, ARITA Y, NISHIDA
M, MAEDA N, KUMADA M, OKAMOTO Y, NAGARETANI H,
NISHIZAWA H, KISHIDA K, KOMURO R, OUCHI N, KIHARA
S, N AGAI R, F UNAHASHI T, M ATSUZAWA Y. Role of
adiponectin in preventing vascular stenosis. The
missing link of adipo-vascular axis. J Biol Chem
2002; 277: 37487-37491.
3) KUMADA M, KIHARA S, SUMITSUJI S, KAWAMOTO T, MATSUMOTO S, OUCHI N, ARITA Y, OKAMOTO Y, SHIMOMURA
I, HIRAOKA H, NAKAMURA T, FUNAHASHI T, MATSUZAWA
Y; OSAKA CAD STUDY GROUP. Coronary artery disease. Association of hypoadiponectinemia with
coronary artery disease in men. Arterioscler
Thromb Vasc Biol 2003; 23: 85-89.
4) FANTUZZI G. Adipose tissue, adipokines, and inflammation. J Allergy Clin Immunol 2005; 115;
911-919.
5) MATSUZAWA Y. Adipocytokines: emerging therapeutic targets. Curr Atherosclerosis Rep 2005; 7: 5862.
6) SHIMOMURA I, HAMMER RE, IKEMOTO S, BROWN MS,
GOLDSTEIN JL. Leptin reverses insulin resistance
and diabetes mellitus in mice with congenital
lipodystrophy. Nature 1999; 401: 73-76.
7) STEPPAN CM, BAILEY ST, BHAT S, BROWN EJ, BANERJEE
RR, WRIGHT CM, PATEL HR, AHIMA RS, LAZAR MA. The
hormone resistin links obesity to diabetes. Nature
2001; 409: 307-312.
8) MATSUZAWA Y. Adipocytokines: emerging therapeutic targets. Curr Atheroscler Rep 2005; 7: 58-62.
9) OKAZAKI T, HIMENO E, NANRI H, OGATA H, IKEDA M.
Effects of mild aerobic exercise and a mild
hypocaloric diet on plasma leptin in sedentary
women. Clin Exp Pharmacol Physiol 1999; 26:
415-420.
10) XENACHIS C, SAMOJLIK E, RAGHUWANSHI MP, KIRSCHNER
MA. Leptin, insulin and TNF-alpha in weight loss.
J Endocrinol Invest 2001; 24: 865-870.
11) BESNARD P. Cellular and molecular aspects of fat
metabolism in the small intestine. Proc Nutr Soc
1996; 5: 19-37.
12) VAN NIEUWENHOVEN FA, VAR DER VUSSE GJ, GLATZ
JFC. Membrane associated and cytoplasmatic fatty acid binding proteins. Lipids 1996: 30: s223227.
13) B AIER LJ, S ACCHETTINI JC, K NOWLER WC, E ADS J,
PAOLISSO G, TATARANNI PA, MOCHIZUKI H, BENNETT
PH, B OGARDUS C, P ROCHAZKA M. An amino acid
substitution in the human intestinal fatty acid
binding protein is associated with increased fatty acid binding, increased fat oxidation, and insulin resistance. J Clin Invest 1995; 95: 12811287.
94
14) ALBALA C, SANTOS JL, CIFUENTES M, VILLARROEL AC,
LERA L, LIBERMAN C, ANGEL B, PÉREZ-BRAVO F. Intestinal FABP2 A54T polymorphism: Association with
insulin resistance and obesity in women. Obes
Res 2004; 12: 340-345.
15) DUART DUART MJ, ARROYO CO, MORENO FRÍGOLS JL.
Validation of a insulin model for the reactions in
RIA. Clin Chem Lab Med 2002; 40: 1161-1167.
16) MATTHEWS DR, HOSKER JP, RUDENSKI AS, NAYLOR BA,
TREACHER DF, TURNER RC. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 1985; 28: 412419.
17) PFÜTZNER A, LANGENFELD M, KUNT T, LÖBIG M, FORST
T. Evaluation of human resistin assays with serum
from patients with type 2 diabetes and different
degrees of insulin resistance. Clin Lab 2003; 49:
571-576.
18) MEIER U, GRESSNER M. Endocrine regulation of energy metabolism: review of pathobiochemical and
clinical chemical aspects of leptin, ghrelin,
adiponectin, and resistin. Clin Chem 2004; 50:
1511-1525.
19) SUOMINEN P. Evaluation of an enzyme immunometric assay to measure serum adiponectin concentrations. Clin Chem 2004; 50: 219-221.
20) LUBRANO V, COCCI F, BATTAGLIA D, PAPA A. Usefulness
of high–sensitivity IL6 measurment for clinical
characterization of patients with coronary artery
disease. J Clin Lab Anal 2005; 19: 110-114.
21) KHAN SS, SMITH MS, REDA D, SUFFREDINI AF, MC COY
JP. Multiplex bead array assays for detection of
soluble cytokines: comparisons of sensitivity and
quantitative values among kits from multiple manufactures. Cytometry B Clin Cytom 2004; 61: 3539.
22) FEURER ID, MULLEN JL. Bedside measurement of
resting energy expenditure and respiratory quotient via indirect calorimetry. Nutr Clin Pract 1986;
1: 43-49.
23) PICHARD C, SLOSMAN D, HIRSCHEL B, KYLE U. Bioimpedance analysis: an improved method for nutritional follow up. Clin Res 1993: 41: 53.
24) MATAIX J, MAÑAS M. Tablas de composición de alimentos españoles. Ed: University of Granada,
2003.
25) SIPILAINEN R, UUSITUPA M, HEIKKINEN S, RISSANEN A,
LAAKSO M. Variants in the human intestinal fatty
acid binding protein 2 gene in obese subjects. J
Clin Endocrinol Metab 1997: 82: 2629-2632.
26) PROCHAZKA M, LILLIOJA S, TAIT JF. Linkage of chromosomal markers on 4q with a putative gene determining maximal insulin action in Pima Indians. Diabetes 1993:42:514-519.
27) MITCHELL BD, KAMMERER CM, O'CONNELL P, HARRISON
CR, MANIRE M, SHIPMAN P, MOYER MP, STERN MP, FRAZIER ML. Evidence for linkage of postchallenge in-
ALA54THR polymorphism and diabetes mellitus type 2
sulin levels with intestinal fatty acid-binding protein (FABP2) in Mexican-Americans. Diabetes
1995; 44: 1046-1053.
ics of NIDDM in France: studies with 19 candidate
genes in affected sib pairs. Diabetes 1997; 46:
1062-1068.
28) CHIU KC, CHUANG LM, YOON C. The A54T polymorphism at the intestinal fatty acid binding protein 2
is associated with insulin resistance in glucose
tolerant Caucasians. BMC Genet 2001; 2: 7-13.
36) DUARTE NL, COLAGIURI S, PALU T, WANG XL, WILCKEN
DE. Obesity, Type II diabetes and the Ala54Thr
polymorphism of fatty acid binding protein 2 in the
Tongan population. Mol Genet Metab 2003: 79:
183-189.
29) YAMADA K, YUAN X, ISHIMAYAMA S. Association between Ala 54Thr subsitution of the fatty acid binding protein 2 gene with insulin resistance and intra abdominal fat thickness in Japanese men. Diabetologia 1997; 40: 706-710.
30) K IM CH, Y UN SK, B YUN DW. Codon 4 polymorphism of the fatty acid binding protein 2 gene is
associated with increased fat oxidation and hyperinsulinemia but not with intestinal fatty acid
absorption in Korean Men. Metabolism 2001; 50:
473-476.
31) CARLSSON M, ORHO MELANDER M, HEDENBRO J, ALEGREN P, GROOP LC. The T54 allele of the intestinal
fatty acid-binding protein 2 is associated with parenteral history of stroke. J Clin Endocr Metab
2000: 85: 2801-2804.
32) GEORGOPOULOS A, ARAS O, TSAI MY. Codon 54 polymorphism of the fatty acid binding protein 2 gene
is associated with elavation of fasting and postprandial triglyceride in type 2 diabetes. J Clin Endocr Metab 2000; 85: 3155-3160.
33) GEORGOPOULOS A, ARAS O, NOUTSOU M, TSAI MY. Unlike type 2 diabetes, type 1 does not interact with
the codon 54 polymorphism of the fatty acid binding protein 2 gene. J Clin Endocr 2002; 87: 37353739.
34) STEM MP, MITCHELL DB BAGLERO J, REINHART L, KRAMMERER CM; H ARRISON CR. Evidence for a major
gene type II diabetes and linkage analysis with
selected candidates genes in Mexican Americans. Diabetes 1996: 45: 563-568.
35) VIONNET N, HANI EH, LESAGE S, PHILIPPI A, HAGER J,
VARRET M, STOFFEL M, TANIZAWA Y, CHIU KC, GLASER B,
PERMUTT MA, PASSA P, DEMENAIS F, FROGUEL P. Genet-
37) MARÍN C, PÉREZ-JIMÉNEZ F, GÓMEZ P, DELGADO J, PANIAGUA JA, L OZANO A, C ORTÉS B, J IMÉNEZ -G ÓMEZ Y,
GÓMEZ MJ, LÓPEZ-MIRANDA J. The Ala54Thr polymorphism of the fatty acid-binding protein 2 gene
is associated with a change in insulin sensitivity
after a change in the type of dietary fat. Am J Clin
Nutr 2005; 82: 196-200.
38)
LUIS DA, SAGRADO MG, ALLER R, IZAOLA O, CONDE
R. Influence of ALA54THR polymorphism of fatty
acid-binding protein 2 on obesity and cardiovascular risk factors. Horm Metab Res 2007: 39: 830834
DE
39) AGREN JJ, VIDGREN HM, VALVE RS, LAAKSO M, UUSITUPA MI. Postprandial responses of individual fatty
acids in subjects homozygous for the threonine or
alanine-encoding allele in codon 54 of the intestinal fatty acid binding protein 2 gene. Am J Clin
Nutr 2001: 73: 31-35.
40) L I Y, F ISHER E, K LAPPER M, B OEING H, P FEIFFER A,
HAMPE J, SCHREIBER S, BURWINKEL B, SCHREZENMEIR J,
DÖRING F. Association between functional FABP2
promoter haplotype and type 2 diabetes. Horm
Metab Res 2006; 38: 300-307
41) FISHER E, LI Y, BURWINKEL B, KÜHR V, HOFFMANN K,
M ÖHLIG M, S PRANGER J, P FEIFFER A, B OEING H,
SCHREZENMEIR J, DÖRING F. Preliminary evidence of
FABP2 A54T polymorphism associated with reduced risk of type 2 diabetes and obesity in
women from a German Cohort. Horm Metab Res
2006; 38: 341-345.
42) ALBALA C, VILLARROEL A, SANTOS JL, ANGEL B, LERA L,
L IBERMAN C, S ANCHEZ H, P ÉREZ -B RAVO F. FABP2
Ala54Thr polymorphism and diabetes in Chilean elders. Diabetes Res Clin Pract 2007; 77: 245-250.
95