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Introduction
Type 2 diabetes is a progressive and complex metabolic
disorder, which is characterized by chronic hyperglycemia
resulting from insulin resistance (IR) and deficiency in
insulin secretion[1]. Reduced insulin action in the liver, adipose
tissue, and skeletal muscle plays a major role in the
pathogenesis of type 2 diabetes[2]. Insulin sensitizer
thiazolidine-diones (TZDs) are oral hypoglycemic agents acting
predominantly by enhancing peripheral insulin sensitivity, reducing
glucolipotoxicity, and endogenous insulin secretory
demands, and preserving β-cell
function[3]. They are agonists of nuclear transcription factor peroxisome
proliferator-activated receptor γ (PPARγ) that heterodimerizes with the
retinoid X receptor, thereby leading to the transcription of
genes involved in glucose and lipid
homeostasis[4]. As a new generation of oral antidiabetic drug, TZDs improve
insulin sensitivity and reduce glycemia, insulinemia, and
dyslipidemia in patients with type 2
diabetes[5].
However, it is reported that the clinical response to
TZDs varies. The Prevention of Diabetes study observed that
approximately 36% patients did not respond to troglitazone
treatment effectively[6]. Wide interindividual variability in
drug response may be due to multiple factors, including age,
sex, race, accommodation, organ function, placebo effect,
clinical stage, and the severity of disease. Genetic
polymorphisms in the targets of drug therapy have been
increasingly recognized as an important mechanism responsible for
the interindividual differences in drug
efficacy[7]. Previous pharmacogenetical research of TZDs analyzed single
nucleotide polymorphisms (SNPs) on PPARG,
ADIPOQ, and CYP2C8[8_14], indicating that genetic variants might be
related to variations in the response to TZD treatment.
The ATP-binding cassette transporter subfamily A
number 1 (ABCA1) gene is located on chromosome 9q31.1 and
is composed of 50 exons extending across a genomic region of
147 kb. The encoded transmembrane protein functions as a
transporter of cellular cholesterol and phospholipid to
lipid-poor apolipoproteins, especially apolipoprotein A1, which
is crucial for high-density lipoprotein biogenesis, as well as
the reverse cholesterol transport[15]. Genetic studies have
shown that ABCA1 might be a candidate gene of type 2
diabetes. Several genetic variants were associated with
diabetes and prediabetic intermediate
traits[16,17]. A recent study by Brunham
et al[18] further investigated its functional role
in β cells. They demonstrated that Abca1 probably had an
effect on islet cholesterol homeostasis, subsequently
influencing glucose tolerance and insulin secretion. In addition,
they found that Abca1 influenced rosiglitazone response in
mice. However, whether ABCA1 plays a similar role in
humans is yet an unanswered question. Thus, we hypothesized
that variants of ABCA1 might contribute to interindividual
variation in response to rosiglitazone therapy. In this study,
we selected 3 non-synonymous variants of
ABCA1, R219K, M883I, and R1587K, to evaluate their effects on rosiglitazone
treatment in newly diagnosed patients with type 2 diabetes.
Materials and methods
Patients and study design A total of 105 newly
diagnosed patients with type 2 diabetes, defined according to
the World Health Organization
criteria[19], were derived from the outpatient clinics at 10 hospitals in Shanghai. All
patients were naive to prior antidiabetic therapy and treated
with rosiglitazone for 48 weeks. We enrolled patients 30_70
years of age, glycated hemoglobin ¡Ý6.5%, and a body mass
index (BMI) ¡Ý18.5 kg/m2. For the female patients,
post-menopause, surgical sterilization, or effective contraception
was required. Excluded criteria were: (i) type 1 diabetes,
gestational diabetes, or other specific types; (ii) acute or
chronic complications in need of insulin therapy; (iii)
significant cardiocerebral, hepatic or nephric disease; (iv)
malignant tumor, hematological disease, autoimmune disease,
psychiatric disease, or significant digestion and absorption
disturbances; (v) current exposure to medication affecting
glucose metabolism, such as glucocorticoid; (vi) long-term
alcohol or drug abuse; (vii) fasting plasma glucose >13
mmol/L (234 mg/dL) and/or 2 h post-load plasma glucose >18 mmol/L
(364 mg/dL ); and (viii) blood pressure >180/110 mmHg.
The initial dose was 4 mg/d and escalated to 8 mg/d in
patients who failed to attain glycemic targets of fasting
plasma glucose >7 mmol/L (126 mg/dL) and/or 2 h plasma
glucose >11 mmol/L (200 mg/dL). Patients with glycated
hemoglobin was ¡Ý8% or fasting plasma glucose >13
mmol/L (234 mg/dL) or 2 h plasma glucose >18 mmol/L (364 mg/dL) twice (a maximal interval of 6 d) were withdrawn from
the study. This study was approved by the institutional
review board of Shanghai Jiao Tong University Affiliated
Sixth People's Hospital (Shanghai, China). Each patient
provided written informed consent before participating in the
study.
Anthropometric measurements General
anthropometric parameters, including height (in m), weight (in kg),
waist and hip circumferences (in cm), and systolic and
diastolic blood pressure (in mmHg) were measured in all
patients at baseline and 48 weeks after the initiation of
rosiglitazone therapy. BMI and waist_hip ratio were
calculated as weight/height2 and waist/hip, respectively.
Clinical laboratory tests Blood samples were collected
after an overnight fast and 2 h after a 75 g oral glucose
tolerance test (OGTT). Plasma glucose concentrations were
measured using the glucose oxidase-peroxidase method with
commercial kits (Shanghai Biological Products Institution,
Shanghai, China). Glycated hemoglobin values were
determined by high-performance liquid chromatography
performed on a Bio-Rad Variant II hemoglobin testing system
(Bio-Rad Laboratories, Hercules, CA, USA). Serum lipid
profiles, including total cholesterol, triglyceride,
high-density lipoprotein cholesterol (HDL-C), and low-density
lipoprotein cholesterol (LDL-C) were measured with a type
7600-020 Automated analyzer (Hitachi, Tokyo, Japan). An
arginine stimulation test was performed to estimate acute insulin
secretion of islet β cells. The serum levels of insulin and
proinsulin were measured in duplicate at 0, 2, 4, and 6 min
(insulin0, insulin2,
insulin4, insulin6;
proinsulin0, proinsulin2,
proinsulin4, proinsulin6) after an intravenous injection of 50
mL arginine solution at the concentration of 10%, using
radioimmunoassay (Linco Research, St Charles, MO, USA).
The intra-assay coefficients of variation were less than 10%.
The evaluation of IR and β-cell secretion at baseline was
calculated using the homeostasis model assessment (HOMA)
index[20], with the following formula: HOMA_IR=fasting
insulin×fasting plasma glucose/22.5, HOMA of
β-cell function (HOMA_B)=20×fasting insulin/(fasting plasma
glucose_3.5). The amount of acute phase insulin and proinsulin
secretion after arginine stimulation was calculated with the
following equation: Acute insulin
secretion=(insulin2+insulin4+
insulin6)/3_insulin0; acute proinsulin
secretion=(proinsulin2+
proinsulin4+proinsulin6)/3_proinsulin
0.
Genotyping Genomic DNA was extracted from
peripheral blood leucocytes in the whole-blood samples. The
SNPs were detected by the PCR restriction fragment length
polymorphism. PCR amplification was performed on the
GeneAmp PCR system 9700 (Applied Biosystems, Foster
City, CA, USA). Amplicons were subsequently digested
overnight with restriction enzymes. Following
electrophoresis in 12% polyacrylamide gels, the digestion products were
stained with ethidium bromide and visualized in the Gel Doc
2000 gel documentation system (Bio-Rad Laboratories, USA).
Sixteen random samples were duplicated to confirm the
genotyping accuracy, and no discrepancy was detected.
Definition of rosiglitazone responsiveness
As there are no generally accepted criteria to divide patients into
responders and non-responders, we used 2 methods to define the
response to rosiglitazone treatment based on previous
clinical studies[11,21_23]. Criterion 1 is a decrease of >15% in all
glycemic measures of glycated hemoglobin, fasting, and 2 h
plasma glucose after a 75 g glucose OGTT. Criterion 2 is a
decrease of 0.5% in glycated hemoglobin. The withdrawals
owning to inadequately controlled blood glucose or glycated
hemoglobin were defined as non-responders in the analysis.
Statistical analysis Data were shown as mean±SEM or
N (%). Allele frequencies were calculated by gene counting.
Tests of the Hardy_Weinberg equilibrium were
performed[24]. Pairwise linkage disequilibrium was determined by
calculating |D´| and
r2 using Haploview (version
3.32)[25]. The differences between groups were tested using
Student's t-test or Kruskal_Wallis test when appropriate. Genotype
distribution differences between responders and
non-responders were compared by Fisher's exact test
or χ2-test. Considering few subjects of rare allele homozygotes, the
genotype_phenotype associations were analyzed between
common allele homozygotes and rare allele carriers. A 2-tailed
P-value ¡Ü0.05 was considered statistically significant. All
statistical analyses were performed using SAS for Windows
(version 6.12; SAS Institute, Cary, NC, USA).
Results
Clinical characteristics of the patients before and
after rosiglitazone treatment Of the 105 patients
enrolled, 93 patients (65 men and 28 women, mean age
52.09±9.09 years) completed the entire study. Twelve patients
were withdrawn, among whom 5 patients were attributed to
inadequately controlled blood glucose or glycated
hemoglobin levels; 1 patient had abnormal liver function and 6
patients were lost to follow up.
The baseline and post-therapy clinical characteristics of
the study group are summarized in Table 1. After 48 weeks of
rosiglitazone therapy, the blood glucose and glycated
hemoglobin levels significantly decreased in comparison with
baseline (P<0.01). Meanwhile, significant improvements in
HOMA_IR (P<0.01), HOMA_B (P<0.01), and acute
proinsulin secretion after arginine stimulation
(P<0.01) were observed. With regards to the lipid profiles, only the
increase in HDL-C level was observed (P<0.01).
Association between ABCA1 genetic variants and the
response rate of rosiglitazone treatment The genotype
distributions of 3 SNPs were consistent with the
Hardy_Weinberg equilibrium. By calculating
|D´| and r2, a low extent
of linkage disequilibrium was detected among them (Table
2). Therefore, the effects of 3 SNPs on rosiglitazone
treatment were analyzed, respectively.
The total response rate of the cohort was 0.398 and 0.782
defined by the 2 criteria, respectively. The genotype
frequencies according to the therapeutic responses are shown
in Table 3. According to the first criterion, R219K was
associated with response to rosiglitazone treatment with more
treatment failures in the rare allele homozygotes KK.
Eighty-eight percent of the KK homozygotes failed compared with
only 52% of the RR homozygotes. The heterozygote RK
group showed an intermediate response rate. The per-allele
odds ratio for treatment failure was 2.04
(P<0.05). According to the second criterion, although not significant, the same
trend was observed; the KK homozygotes had a poor
response to rosiglitazone therapy. No significant effect of
M883I or R1587K on rosiglitazone therapy was observed.
Association between ABCA1 genetic variants and the
effect of rosiglitazone treatment on clinical features
The association between R219K and clinical features is shown in
Table 4. Here we detected a significantly higher 2-h plasma
glucose (P<0.05) and waist_hip ratio
(P<0.05) at baseline in the RR homozygotes compared with minor K allele carriers.
The RR homozygotes also showed greater though
non-significant reductions in fasting and 2-h plasma glucose as well
as the glycated hemoglobin level after 48 weeks' treatment.
With respect to insulin sensitivity, the decline in the
HOMA_IR value was significantly greater in RR homozygotes
(P<0.05). As for the lipid profiles, we found no significant differences
between the 2 groups. Neither M883I nor R1587K was
observed to be associated with clinical features at baseline or
after treatment (Tables 5 and 6).
Discussion
Pharmacogenetics involve the study of contributions of
inherited differences in drug disposition or drug targets to
drug response, with the ultimate goal to select the optimal
drug therapy and dosages through the use of
genetically-guided, individualized
treatment[26]. Rosiglitazone, a member of TZDs, is a widely used insulin sensitizer. Data from
ADOPT[22] and DREAM[27] showed that initial treatment with
rosiglitazone could slow the progressive loss of glycemic
control in diabetic patients and reduce diabetes incidences,
as well as regress to normoglycemia in individuals with
impaired fasting glucose and/or impaired glucose tolerance.
In this study, we found that the R219K variant of the
ABCA1 gene was associated with response to rosiglitazone
therapy in newly diagnosed type 2 diabetes patients. The
RR homozygotes showed a lower failure rate and a better
improvement in insulin sensitivity after 48 weeks' treatment.
Rosiglitazone increases the expression of
ABCA1 through a PPARg-LXRa-ABCA1 pathway, thereby regulating
cholesterol homeostasis[28,29]. It is well recognized that
accumulation of lipids in tissues leads to β-cell dysfunction and
IR[30_32]. Brunham et
al[18] further demonstrated that
Abca1 had an effect on β-cell function through its role on cholesterol
accumulation in islets. Their results indicated that Abca1 mainly
affected insulin secretion. However, we failed to find any
association between ABCA1 genetic variants and acute
insulin or proinsulin secretion after arginine stimulation. The
main outcome of our study was that R219K was associated
with insulin sensitivity improvement. The underlying
mechanism is still unknown.
We did not detect significant differences in lipid
profiles between the RR homozygotes and minor K allele carriers,
although the latter were suggested to be associated with
decreased triglyceride and a trend toward increased HDL-C
in some[33,34], but not
all[35] association studies. As serum cholesterol levels are influenced by many factors, we
suppose that a small change in ABCA1 activity could affect
rosiglitazone response without markedly impacting
circulating cholesterol profiles.
There are several limitations of this study that should be
noted. First, the sample size of this study is relatively small,
thus we do not have enough statistical power to detect
effects of genetic variants and HDL-C levels. Although
previous studies reported that M883I had an impact on ABCA1
function[36] and R1587K was associated with HDL-C
level[33,37], we failed to detect any effect of these 2 variants on
rosiglitazone treatment. We cannot exclude the possibility that the sample
size may be one of the reasons. Second, as most variables of
our study are in skew distribution, the Kruskal_Wallis test
was the main method used to analyze the association
between genotypes and phenotypes, thus we could not adjust
for the effect of confounding factors, such as drug dose.
However, we did not detect a significant difference in drug
dose between groups. The K allele carriers of the R219K
variant showed a relatively higher mean drug dose compared
with the RR homozygotes, which may also reflect a poorer
response to rosiglitazone treatment. Third, a 48 week
follow-up period might be inadequate to see the thorough
therapeutic effect, but as documented in the ADOPT
study[22], the maximal treatment effect of rosiglitazone on glycated
hemoglobin was achieved within one year. Considering the
compliance of patients, the effect of genotypes on long-term
drug response would be better studied in a carefully
controlled clinical trial.
In conclusion, we provide evidence that the R219K
variant of the ABCA1 gene either directly or as a marker with
additional functional variant in linkage disequilibrium, has
an effect on response to rosiglitazone treatment. Never-theless,
we are at an early stage of defining
pharmacogenetic determinants of rosiglitazone treatment response. Long-term
follow-up studies with large samples are needed to further
confirm our findings and allow individualizing therapy based on
genomic information.
Acknowledgements
We thank all the patients taking part in this research. We
are grateful to the doctors and nurses who participated in
this study from Shanghai Jiao Tong University Affiliated
Sixth People's Hospital; First People's Hospital; Renji
Hospital; Ruijin Hospital, Xinhua Hospital, Fudan
University Affiliated Zhongshan Hospital; Huashan Hospital,
Se-cond Military Medical University Affiliated Changzheng
Hospital; Changhai Hospital, and Tongji University
Affiliated East Hospital.
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