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Mutation analysis of peroxisome proliferator-activated receptor-gamma coactivator-1 (PGC-1) and relationships of identified amino acid polymorphisms to Type II diabetes mellitus

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This study aimed to investigate if variability in the peroxisome proliferator-activated receptor-gamma coactivator-1 (PGC-1) gene is associated with Type II (non-insulin-dependent) diabetes mellitus. The PGC-1 gene was examined in 53 Type II diabetic patients applying single strand conformational polymorphism analysis followed by nucleotide sequencing. Identified variants were genotyped in an association study comprising 483 Type II diabetic patients and 216 glucose-tolerant control subjects. A replication study was done in an additional 201 Type II diabetic patients and 293 glucose-tolerant subjects. Furthermore, a potential interaction between the Pro12Ala polymorphism of PPAR-gamma2 and the PGC-1 Gly482Ser variant on risk of Type II diabetes was investigated. A total of seven variants (Ser74Leu, IVS2 + 52C-->A, Thr394Thr, Asp475Asp, Gly482Ser, Thr528Thr, and Thr612Met) were identified and investigated in an association study. Six of the variants showed no association with Type II diabetes in the initial study. However, the Gly482Ser polymorphism, was more frequent among Type II diabetic patients (37.0 %) than among glucose-tolerant subjects (30.8 %) (p = 0.032). In a replication study the difference in allele frequencies of the Gly482Ser variant remained significant (p = 0.0135). The combined study yielded an allele frequency of 37.3 % (34.7-39.9) for Type II diabetic patients and 30.5 % (27.7-33.4) for glucose-tolerant subjects (p = 0.0007). No interaction between this variant and the Pro12Ala polymorphism of PPAR-gamma2 was observed. A widespread Gly482Ser polymorphism of PGC-1 is associated with a 1.34 genotype relative risk of Type II diabetes.
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Peroxisome proliferator-activated receptor-gcoacti-
vator-1 (PGC-1) is a novel transcriptional co-activa-
tor of a series of nuclear receptors including peroxi-
some proliferator-activated receptor-g(PPAR-g), a
transcription factor involved in adipogenesis and
a functional receptor for thiazolidinediones [1, 2].
Similarly, PGC-1 is a coactivator of peroxisome pro-
liferator-activated receptor-a(PPAR-a), which plays
a key role in the transcriptional control of genes en-
coding mitochondrial fatty acid beta-oxidation en-
zymes [3]. Studies in cultured muscle-cell lines show
that PGC-1 stimulates mitochondrial biogenesis and
respiration through an induction of uncoupling pro-
tein 2 and through regulation of the nuclear respira-
tory factors [2]. Thus, PGC-1 is a key factor in the
stimulation of adaptive thermogenesis, e. g. during
high caloric diets or cold exposure. It has recently
Diabetologia (2001) 44: 2220±2226
Mutation analysis of peroxisome proliferator-activated
receptor-gcoactivator-1 (
PGC-1
) and relationships of identified
amino acid polymorphisms to Type II diabetes mellitus
J. Ek1, G. Andersen1, S. A. Urhammer1, P. H. Gñde1, T. Drivsholm2, K. Borch-Johnsen1, T. Hansen1, O. Pedersen1
1Steno Diabetes Center and Hagedorn Research Institute, Gentofte, Copenhagen, Denmark
2Centre of Preventive Medicine, Glostrup University Hospital, Denmark
ÓSpringer-Verlag 2001
Abstract
Aim/hypothesis. This study aimed to investigate if
variability in the peroxisome proliferator-activated
receptor-gcoactivator-1 (PGC-1) gene is associated
with Type II (non-insulin-dependent) diabetes melli-
tus.
Methods. The PGC-1 gene was examined in 53 Type
II diabetic patients applying single strand conforma-
tional polymorphism analysis followed by nucleotide
sequencing. Identified variants were genotyped in an
association study comprising 483 Type II diabetic pa-
tients and 216 glucose-tolerant control subjects. A
replication study was done in an additional 201 Type
II diabetic patients and 293 glucose-tolerant subjects.
Furthermore, a potential interaction between the
Pro12Ala polymorphism of PPAR-g2 and the PGC-
1 Gly482Ser variant on risk of Type II diabetes was
investigated.
Results. A total of seven variants (Ser74Leu,
IVS2 + 52C®A,Thr394Thr,Asp475Asp,Gly482Ser,
Thr528Thr, and Thr612Met) were identified and in-
vestigated in an association study. Six of the variants
showed no association with Type II diabetes in the
initial study. However, the Gly482Ser polymorphism,
was more frequent among Type II diabetic patients
(37.0%) than among glucose-tolerant subjects
(30.8%) (p= 0.032). In a replication study the differ-
ence in allele frequencies of the Gly482Ser variant re-
mained significant (p= 0.0135). The combined study
yielded an allele frequency of 37.3 % (34.7±39.9) for
Type II diabetic patients and 30.5 % (27.7±33.4) for
glucose-tolerant subjects (p= 0.0007). No interaction
between this variant and the Pro12Ala polymorphism
of PPAR-g2 was observed.
Conclusion/interpretation. A widespread Gly482Ser
polymorphism of PGC-1 is associated with a 1.34
genotype relative risk of Type II diabetes. [Dia-
betologia (2001) 44: 2220±2226]
Keywords PPAR-gcoactivator-1, mutations, Type II
diabetes, genetic epidemiology, association study.
Received: 4 April 2001 and in revised form: 19 July 2001
Corresponding author: Oluf Pedersen, Professor, M.D.,
D. M.Sc., Steno Diabetes Center, Niels Steensens Vej 2,
DK-2820 Gentofte, Copenhagen, Denmark,
E-mail: oluf.p@dadlnet.dk
Abbreviations: PPAR, peroxisome proliferator-activated re-
ceptor; PGC-1, PPAR-gcoactivator-1; MEF2C, myocyte en-
hancer factor 2C; OHA, oral hypoglycaemic agent; SSCP, sin-
gle strand conformational polymorphism; GRR, genotype re-
lative risk.
been shown that PGC-1 by binding to myocyte en-
hancer factor 2C (MEF2C) also controls the expres-
sion of the endogenous glucose transporter
(GLUT4) gene in muscle cells [4]. In humans PGC-1
is expressed in high quantities in liver, heart, kidney,
and skeletal muscle and to a lesser extent in white
adipose tissue, pancreas, and brain [5, 6]. Given the
critical roles of PGC-1 in several aspects of adipo-
genesis, oxidative metabolism, thermogenesis and
glucose uptake and the fact that human PGC-1 is
mapped to a chromosomal region (4p15.1) that in
Pima Indians has been shown to be linked to fasting
serum insulin concentrations [7] we hypothesized
that variability in the PGC-1 gene confers suscepti-
bility to Type II diabetes. This study reports the re-
sults of the mutation analysis of the entire coding re-
gion of the PGC-1 gene and the identification of a
widespread amino acid polymorphism, which is re-
producibly associated with Type II diabetes among
Danish Caucasians.
Subjects and methods
Subjects. Mutation analysis was completed in 53 Type II dia-
betic patients (30 men, 23 women) recruited from the outpa-
tient clinic at Steno Diabetes Center. The age of the patients
was 64  9 years, age of diagnosis 57  9 years, body mass in-
dex (BMI) 29.7  4.9 kg/m2, and HbA1C 8.3 1.7 % (means
SD). More than 70% of the patients fulfilled the 1998
WHO criteria for the metabolic syndrome [8], 31 % of the pa-
tients were treated with diet alone, 65 % with oral hypo-
glycaemic agents (OHA), and 4 % with insulin alone or in
combination with OHA.
The initial association studies were done in a group of unre-
lated Type II diabetic patients recruited from the outpatient
clinic at Steno Diabetes Center during 1994±1997 and a group
of unrelated glucose-tolerant subjects without a known family
history of diabetes sampled at random during 1994±1997 from
the Danish Central Population Register and all living in the
same area of Copenhagen as the Type II diabetic patients. In
the group of Type II diabetic patients (n= 483, 278 men, 205
women) the age was 61  11 years, age of diagnosis
55  11 years, BMI 29.0  5.3 kg/m2, and HbA1C 8.1 1.6 %.
The patients were treated with diet alone (27%), with OHA
(58 %), or with insulin in combination with OHA (15 %). In
the group of glucose tolerant subjects (n= 216, 105 men, 111
women) the age was 52  14 years, and BMI 25.3  3.8 kg/m2.
Theassociationstudy used forreplicationcomprised unrelat-
ed Type II diabetic patients recruited from the outpatient clinic
at Steno Diabetes Center during 1992±1993 and a population
based sample of unrelated glucose-tolerant subjects without a
known family history of diabetes born in 1936 and examined dur-
ing 1996±1997 at the Copenhagen County Center of Preventive
Medicine. In the group of Type II diabetic patients (n= 201,
152 men, 49 women) the age was 55  7 years, age of diagnosis
48  8 years, BMI 29.8  4.4 kg/m2, and HbA1C 8.6 1.7 %. The
patients were treate d with diet alone (29 %), with OHA (60 %),
or with insulin in combination with OHA (11 %). In the group
of glucose-tolerant subjects (n= 293, 134 men, 159 women) the
age was 60.5  0.4 years andBMI 26.2  3.7 kg/m2.
Diabetes was diagnosed according to 1998 WHO criteria
[8]. All glucose-tolerant subjects underwent a 75 g oral glu-
cose tolerance test (OGTT). All participants were Danish
Caucasians by self-report. Informed written consent was ob-
tained from all subjects before participation. The study was
approved by the Ethical Committee of Copenhagen and was
in accordance with the principles of the Declaration of Hel-
sinki II.
Biochemical assays. Blood samples for measurement of serum
concentrations of insulin, total cholesterol, high-density lipo-
protein (HDL) cholesterol, triglycerides and plasma glucose
and non-esterified fatty acids (NEFA) were drawn after a
12-h overnight fast. Serum triglycerides, total serum cholesterol,
serum HDL-cholesterol, and plasma NEFAwere analysed using
enzymatic colorimetric methods (GPO-PAP and CHOD-PAP,
Roche Molecular Biochemicals, Germany and NEFA C, Wako,
Neuss, Germany). The plasma glucose concentration was analy-
sed by a glucose oxidase method (Granutest, Merck, Darmstadt,
Germany) and serum specific insulin (excluding des(31,32)- and
intact proinsulin) was measured by ELISA (Dako insulin kit
K6219, Dako Diagnostics, Ely, UK). HbA1C was measured by
ion-exchange high performance liquid chromatography (non-
diabetic reference range: 4.1±6.4 %).
Mutation analysis and genotyping. The genetic analyses were
done on genomic DNA isolated from human leukocytes. The
coding region of the PGC-1 gene (EMBL AF106698) includ-
ing intron-exon boundaries (in total 3357 bp) was divided into
17 segments (sized 145±273 nucleotides) for SSCP and hetero-
duplex analysis. In our laboratory, this method has an estimat-
ed sensitivity of more than 95 % for detecting a variety of
known mutations. The segments also included the 5' untrans-
lated sequence of 90 bp. Primer sequences are listed in Table 1.
PCR amplification was carried out in a volume of 25 ml con-
taining 100 ng genomic DNA, 1 ´PCR-buffer, 0.2 mmol/l of
each primer, 0.2 mmol/l dNTP, 10 mCi/ml a-32P-dCTP, 0.6 units
AmpliTaq Gold polymerase (Perkin Elmer, Foster City, Calif.,
USA) and MgCl2concentration as shown in Table 1. The cy-
cling programme was a denaturation step at 95 C for 15 min
followed by 40 cycles of 94 C for 30 s, annealing at Tanneal for
30 s, and elongation at 72 C for 60 s with a final elongation
step at 72C for 9 min using a GeneAmp 9600 thermal cycler
(Perkin Elmer). The annealing temperatures are listed in Ta-
ble 1. SSCP was carried out at two different experimental set-
tings as reported [9] and aberrantly migrating samples were se-
quenced using fluorescent chemistry (Dye Primer Cycle Se-
quencing Ready Reaction Kit, Applied Biosystems, Calif.,
USA). The Ser74Leu and IVS2 + 52C®Avariants were geno-
typed by PCR with primers PC2F-PC2RNY followed by diges-
tion with DraI and ApaI, respectively. The Thr394Thr variant
was genotyped employing restriction site generating (RG)
PCR (2 mmol/l MgCl2,T
anneal 55 C) with upstream RG-primer
5'-GCC AGT CAA TTA ATT CCA AAC C-3' (mismatched
nucleotide is underlined) and downstream primer PC15R fol-
lowed by digestion with HpaII. The Asp475Asp variant was
genotyped using RG-PCR (2 mmol/l MgCl2,T
anneal 59 C)
with upstream RG-primer 5'-ATC CCA GTC AAG CTG
TTT TTC T-3' and downstream RG-primer 5'-GAA GAA
CAA GAA GGA GAC ACA TCG-3' followed by digestion
with TaqI. The Gly482Ser variant was amplified with primers
PC15F-PC17R and digested with HpaII. The Thr528Thr vari-
ant was genotyped using RG-PCR (2 mmol/l MgCl2,T
anneal
60 C, upstream RG-primer 5'-GAC GAC GAA GCA GGC
AAG-3', downstream primer 5'-GAT TTG GGT GGT GAC
ACA GA-3') with subsequent digestion with Cac8I. The
Thr612Met variant was amplified with primers PC8F-PC8R
and digested with NlaIII. The Pro12Ala polymorphism of
PPAR-g2 was genotyped by RG-PCR (3 mmol/l MgCl2,T
anneal
J. Ek et al.: Polymorphisms in PGC-1 and Type II diabetes 2221
53 C) with upstream primer 5'-CAA GCC CAG TCC TTT
CTG TG-3' and downstream RG-primer 5'-AGT GAA GGA
ATC GCT TTC CG-3' (derived from EMBL AB005520) fol-
lowed by digestion with HpaII. All restriction enzyme digests
were separated on 4 % agarose gels.
Statistical analysis. Fisher's exact test was applied to examine
differences in allele frequencies between diabetic and non-dia-
betic subjects. A general linear model was used to test variables
(or transformed variables) for differences between genotype
groups. Genotype and gender were considered as fixed factors
and age and BMI as covariates. A p-value of less than 0.05 was
considered significant. All analyses were done using Statistical
Package for Social Science (SPSS, Chicago. Ill., USA) version
10.0. The genotype relative risk (GRR) was estimated by logistic
regression from the genotype data using a log-additive model for
the risk. Test for additivity gave a likelihood ratio statistic of
0.285 on 1 df (p=0.593). Interaction between the Pro12Ala
polymorphism of PPAR-g2 and the Gly482Ser polymorphism
of PGC-1 was tested using logistic regression.
J. Ek et al.: Polymorphisms in PGC-1 and Type II diabetes2222
Table 1. Primer sequences and PCR conditions for mutational analysis of PGC-1
Primer Sequence, 5'®3' Location Tanneal MgCl2
PC1F
PC1R
CTG GGG ACT GTA GTA AGA C
AGG GAA GCG TCA GTT GTG G
5'UTR +
Exon 1 55C 1 mmol/l
PC2F
PC2RNY
CCT GTG GTT AAT GGA AGC
GCC CAA GCC AAA CTC AAT G Exon 2 50C 2 mmol/l
PC3F
PC3R
CTG CCT CCC AGG GTC AAC
CAA CTC CAA TTC CTG CTA AAC Exon 3 55C 1 mmol/l
PC4F
PC4R
GAT GCA TAA CTT TAC TTG
CTG CTT CAA GCC AAA ATC Exon 4 50C 2 mmol/l
PC5F
PC5R
CTG ATA AGG TTC AGT TCA C
CCT CAC CAA CAG CTC GT Exon 5 50C 2 mmol/l
PC6F
PC6R
CCA ACT TGA CTG TTG TGG AG
ACA AAC TGA AAT GGA GTT GC Exon 6 55C 2 mmol/l
PC7F
PC7R
GGG TTC TAA TAC ATT TGG C
CAC ATA GAC AGT ACA TCT Exon 7 50 C 2 mmol/l
PC8F
PC8R
GTT AAG TGG CAG TTG CAA ATG
GGG AGC TAA AGG AAA ATG AC Exon 9 55 C 2 mmol/l
PC9F
PC9R
GGT GGT TGA CTT AGT GAT AAA G
CAC AGA AAA AGA AGA AAC CCT AC Exon 10 55C 3 mmol/l
PC10F
PC10R
CCA CTC CAG AAC TCT CTC C
CAA CTC CCA TCC CAG TAA TC Exon 11 55C 1 mmol/l
PC11F
PC11R
GGT TAC AGT CCC ATATAC T
GAT TCC TCATTC CAC GTA C Exon 12 50C 3 mmol/l
PC12F
PC12R
GCC ATC AGC AAA GTG TGT
TGA GGT ATT CGC CAT CCC Exon 13 50 C 2 mmol/l
PC13F
PC14R
GAA ACA TGT GTC TTC GCA
CGC TTG GTC TTC CTT TCC TCG Exon 8 55 C 2 mmol/l
PC15F
PC15R
CAA GTC CTC AGT CCT CAC
CTT GCC TCC AAA GTC TCT C Exon 8 50 C 2 mmol/l
PC16F
PC16R
CAG ATT CAG ACC AGT G
CAT AGG TAG TTT GGA G Exon 8 45 C 1 mmol/l
PC17F
PC17R
GGG ACA GTG ATT TCA GTA ATG
GGG GTC TTT GAG AAA ATA AGG Exon 8 55 C 1 mmol/l
PC18F
PC18R
GTA GAG ATT CTG TGT CAC
CTT TTG TGT TAT TTA GGG Exon 8 45 C 2 mmol/l
All forward primers were extended with a 21M13 tail for sequencing (TGT AAA ACG ACG GCC AGT) and all reverse primers
with an M13 tail (CAG GAA ACA GCT AGT ACC)
Fig. 1. Schematic presentation of identified PGC-1 variants
and approximate positions relative to known functional do-
mains. LXXLL, recognition site (LXXLL motif); PKAP, pro-
tein kinase A phosphorylation consensus site; SRD, serine
and arginine rich domain; RRM, RNA recognition motif
Results
The mutation screening covered the coding region of
PGC-1. In the 53 Type II diabetic patients, we identi-
fied a total of 7 different variants (Fig.1): Ser74Leu
(identified in 2 out of 53 patients, nucleotide position
341: TCA®TTA), IVS2 + 52C®A(19 patients),
Thr394Thr (11 patients, 1302: ACG®ACA), Asp-
475Asp (13 patients, 1545: GAC®GAT), Gly482Ser
(24 patients, 1564: GGT®AGT), Thr528Thr (37 pa-
tients, 1704: ACA®ACG), and Thr612Met (3 pati-
ents, 1955: ACG®ATG). The variants were further
examined in an association study comprising 483
Type II diabetic patients and 216 glucose-tolerant
control subjects and in a replication study comprising
201 Type II diabetic patients and 293 glucose-tolerant
control subjects. All variants were in Hardy-Wein-
berg equilibrium. The allele frequencies of the Ser74-
Leu,IVS2 + 52C®A,Asp475Asp, and Thr528Thr
variants did not differ significantly between diabetic
and non-diabetic subjects (Table 2 and data not
shown). The common Gly-allele of codon 482 and
the common C-allele of the intronic variant segregat-
ed together (disequilibrium coefficient d= 0.04). The
allele frequencies of the Ser74Leu and Thr612Met
variants were not sufficiently high to provide reliable
estimates of linkage disequilibrium with the Gly482-
Ser polymorphism. The minor Ser-allele of codon
482 and the minor Asp-allele of codon 475 (allele fre-
quencies: NGT subjects, 5.6%; diabetic patients,
8.6%) segregated together (d= ±0.02). The common
Thr528Thr substitution allele (NGT subjects, 38.5 %;
diabetic patients, 45.3 %) segregated with the Ser-al-
lele of codon 482 (d= 0.21). The minor Ser-allele of
codon 482 and the minor Thr-allele of codon 394 seg-
regated together (d= ±0.07).
The allele frequency of the Gly482Ser variant was
higher among Type II diabetic patients compared
to glucose-tolerant subjects (37.0% vs 30.8%,
p=0.032) (Table 2). In a replication study the differ-
ences in allele frequencies remained significant
(38.1% vs 30.4%, p=0.0135). The combined study
yielded an allelic frequency of 37.3% for the Type
II diabetic patients and 30.5 % for the glucose-toler-
ant subjects (p= 0.0007). The genotype relative risk
for diabetes was estimated to 1.34 (95 %-CI:
1.13±1.59) corresponding to a population attributa-
ble risk of 18%. In the combined group of diabetic
subjects, carriers of the Gly482Ser polymorphism
did not differ significantly from wildtype carriers in
clinical or biochemical values including age of diabe-
tes onset, BMI, waist circumference, treatment, de-
gree and prevalence of micro- and macrovascular
complications, HbA1C or fasting serum lipids (data
not shown). Moreover, in the glucose-tolerant sub-
jects there was no evidence of a relation between
J. Ek et al.: Polymorphisms in PGC-1 and Type II diabetes 2223
Table 2. Genotype and allele frequencies of the examined variants in the PGC-1 gene in Type II diabetic patients and glucose tol-
erant subjects
Initial association study Replication study Combined study
Type II
diabetic
patients
Glucose-
tolerant
subjects
pType II
diabetic
patients
Glucose-
tolerant
subjects
pType II
diabetic
subjects
Glucose-
tolerant
subjects
p
Ser 74Leu
Ser/Ser 466 (99) 197 (99) 223 (99) 290 (99) 689 (99) 487 (99)
Ser/Leu 3 (1) 1 (1) 2 (1) 2 (1) 5 (1) 3 (1)
Leu/Leu 0 (0) 0 (0) 1.0a0 (0) 0 (0) 1.0a0 (0) 0 (0) 1.0a
Allele frequency 0.3 (0±0.7) 0.3 (0±0.7) 1.0 0.4 (0±1.0) 0.3 (0±0.8) 1.0 0.4 (0±0.7) 0.3 (0±0.7) 1.0
IVS2 + 52C®A
C/C 178 (37) 62 (30) 74 (33) 107 (37) 252 (36) 169 (34)
C/A 221 (46) 102 (50) 110 (49) 142 (49) 331 (47) 244 (49)
A/A 79 (17) 40 (20) 0.2a39 (17) 42 (14) 0.5a118 (17) 82 (17) 0.8a
Allele frequency 39.6
(36.6±42.7)
44.6
(39.8±49.4)
0.09 42.2
(37.6±46.7)
38.8
(34.9±42.8)
0.3 40.4
(37.9±43.0)
41.2
(38. 1±44.3)
0.7
Gly482Ser
Gly/Gly 186 (41) 97 (49) 76 (38) 146 (50) 262 (40) 243 (49)
Gly/Ser 200 (44) 80 (40) 97 (48) 116 (40) 297 (45) 196 (40)
Ser/Ser 68 (15) 21 (11) 0.11a28 (14) 31 (10) 0.03a96 (15) 52 (11) 0.0035a
Allele frequency 37.0
(33.8±40.1)
30.8
(26.2±35.3)
0.032 38. 1
(33.3±42.8)
30.4
(26.7±34.0)
0.0135 37.3
(34.7±39.9)
30.5
(27.7±33.4)
0.0007
Thr612Met
Thr/Thr 443 (93) 183 (90) 211 (96) 260 (89) 654 (94) 443 (90)
Thr/Met 31 (7) 20 (10) 9 (4) 31 (11) 40 (6) 51 (10)
Met/Met 1 (0) 0 (0) 0.2a0 (0) 0 (0) 0.007a1 (0) 0 (0) 0.005a
Allele frequency 3.5 (2.3±4.6) 4.9 (2.8±7.0) 0.2 2.1 (0.7±3.0) 5.3 (3.5±7.2) 0.009 3.0 (2.1±3.9) 5.2 (3.8±6.5) 0.01
Data are number of subjects with each genotype (% of each group) and allele frequencies of minor allele in % (95 %-CI). The p
values compare genotype distribution (a) and allele frequencies between Type II diabetic patients and glucose tolerant subjects
the codon 482 variant and estimates of BMI, waist
circumference, fasting serum triglycerides, plasma
free fatty acids or plasma glucose, serum insulin and
serum C-peptide in the fasting state or during an
OGTT (Table 3 and data not given). There was a
strong association of the Gly482Ser variant with fast-
ing serum total and HDL-cholesterol (p=0.015 and
p=0.006, respectively) in the initial study. However,
this association was not observed in the replication
study (Table 3).
When stratifying the examined study population
according to the Gly482Ser genotype for Pro12Ala
genotype of PPAR-g2 the genotype distribution and
allele frequencies of the Ser-allele in relation to
Type II diabetes remained unchanged (Table 4). No
interaction of the two polymorphisms on risk of
Type II diabetes was observed (p= 0.7).
The allele frequency of the Thr612Met variant was
lower among Type II diabetic patients than among
normal glucose-tolerant control subjects in the repli-
cation study (2.1 % vs 5.3 %, p=0.009) but not in the
initial study (3.5 % vs 4.9 %, p=0.2) (Table 2). The
combined study yielded an allele frequency of 3.0%
among Type II diabetic patients and 5.2 % among
glucose-tolerant control subjects (p=0.01). The gen-
otype relative risk for diabetes was estimated to 0.57
(95 %-CI: 0.37 ± 0.86). In the combined group of dia-
betic subjects, carriers of the Thr612Met variant did
not differ significantly from wildtype carriers in clini-
cal or biochemical values (data not shown). More-
over, in the glucose-tolerant subjects there was no ev-
idence of a relation between the codon 612 variant
and clinical or biochemical estimates (data not
shown).
The allele frequency of the Ser74Leu and the
IVS2 + 52C®Avariants were not statistically differ-
ent between diabetic and control subjects (Table 2).
The allele frequencies of the Thr394Thr variant did
not differ significantly between diabetic and non-dia-
betic subjects in the initial study (19.8 % vs 23.4 %,
p=0.1) or in the replication study (19.7 % vs 24.3 %,
p= 0.08). However, in the combined study the allele
frequency was lower among Type II diabetic patients
compared to glucose-tolerant control subjects
(19.7% vs. 23.9%, p= 0.02) (data not shown).
J. Ek et al.: Polymorphisms in PGC-1 and Type II diabetes2224
Table 3. Clinical and biochemical characteristics of two normal glucose-tolerant Danish Caucasian study samples classified accord-
ing to PGC-1 Gly482Ser genotype
Gly/Gly Gly/Ser Ser/Ser p
Glucose-tolerant subjects (n= 198)
n(men/ women) 97 (45/52) 80 (38/42) 21 (10/11)
Age (years) 51  14 53  13 50  14
BMI (kg/m2) 25.4  4.0 25.3  3.7 24.2  3.6 0.5
Fasting-plasma-glucose (mmol/l) 5.1  0.4 5.1  0.5 5.1  0.5 0.8
Fasting-serum-insulin (pmol/l) 42.1  21.2 37.1  18.0 44.1  21.3 0.06
Fasting-serum-triglyceride (mmol/l) 1.2  0.7 1.2  0.7 1.0  0.5 0.7
Fasting-serum-total cholesterol (mmol/l) 5.4  1.0 5.7  1.1 4.9  1.3 0.015
Fasting-serum-HDL-cholesterol (mmol/l) 1.4  0.4 1.5  0.4 1.3  0.3 0.006
Glucose-tolerant subjects (n= 293)
n(men/women) 146 (68/78) 116 (49/67) 31 (17/14)
Age (years) 61  0.5 61  0.4 60  0.4
BMI (kg/m2) 25.9  3.2 26.5  4.2 26.0  3.6 0.4
Fasting-plasma-glucose (mmol/l) 5.2  0.5 5.1  0.5 5.1  0.5 0.08
Fasting-serum-insulin (pmol/l) 39.1  19.2 39.9  25.1 37.6  16.0 0.9
Fasting-serum-triglyceride (mmol/l) 1.3  0.7 1.4  0.9 1.3  0.6 0.3
Fasting-serum-total cholesterol (mmol/l) 6.3  0.9 6.2  1.0 6.2  1.3 0.5
Fasting-serum-HDL-cholesterol (mmol/l) 1.5  0.4 1.5  0.5 1.4  0.4 0.3
Data are means  standard deviation. Values of insulin were logarithmically transformed. pvalues were adjusted for age, gender,
and BMI
Table 4. Distribution of genotypes defined by the Gly482Ser variant of PGC-1 and the Pro12Ala variant of PPAR-g2 among Type
II diabetic patients and glucose tolerant subjects
PPAR-g2Pro12Ala genotype Protective PPAR-g2 variant Ala/X Diabetogenic PPAR-g2 variant Pro/Pro
PGC-1 Gly482Ser genotype Gly/Gly Gly/Ser Ser/Ser Gly/Gly Gly/Ser Ser/Ser
Type II diabetic patients 43 (41) 48 (46) 13 (13) 134 (42) 140 (43) 48 (15)
Glucose-tolerant subjects 56 (46) 55 (45) 10 (8) 183 (50) 139 (38) 42 (12)
Data are number of subjects with each genotype combination (% of each group). A test for synergistic effect for risk of Type II di-
abetes using logistic regression was not significant (p= 0.7)
Discussion
There is extensive circumstantial evidence from fam-
ily investigations including studies in twins and from
studies of hybrid populations descended from high-
risk and low-risk ancestral populations in favour of
genetic determinants for the common late onset
form of Type II diabetes. It is also likely that Type II
diabetes in many cases is polygenic and it is suggested
that subsets of patients display changes in various dia-
betes susceptibility genes thereby adding to the heter-
ogeneity of Type II diabetes.
Among the few Type II diabetes susceptibility
gene variants, which have been reproducibly report-
ed to be associated with Type II diabetes are the
Pro12Ala polymorphism of PPAR-gand polymor-
phisms in the CAPN10 gene, the SUR gene, and the
KIR6.2 gene [10±20]. In a study of more than 3000
subjects the common Pro-allele of PPAR-g2 has
been shown to confer a 1.25-fold increase in risk of
Type II diabetes [12]. The diabetogenic effect of this
variant appears to be mediated through a weak im-
pairment of whole body insulin sensitivity [10, 11].
These findings prompted us to examine the PGC-1
gene for variability, which might be associated with
Type II diabetes because PGC-1, besides being a co-
activator of PPAR-gand -a, has a critical role in glu-
cose uptake and adaptive thermogenesis [1]. Only
one out of seven tested gene variants ± the Gly482Ser
polymorphism ± showed nominal allelic association
in the initial association study. Testing of this variant
in a replication sample confirmed the association of
the polymorphism to Type II diabetes. Combining
the initial and the replication samples showed a 1.34-
fold increase in diabetes risk associated with the Ser-
allele of Gly482Ser. Although this diabetes-suscept-
ibility effect seems to be small, it translates into a
considerable population attributable risk of 18 %
due to the high frequency of the risk allele.
In this study, we failed to relate the Gly482Ser
polymorphism to subphenotypes like BMI, waist cir-
cumference, plasma glucose, serum insulin and serum
C-peptide during an OGTT in the glucose tolerant
subjects. Similarly, we were not able to associate the
PGC-1 variant with biochemical and anthropometric
characteristics or age of clinical disease onset in the
two groups of diabetic subjects. However, in the ini-
tial study of glucose-tolerant subjects we did observe
a significant association of the Gly482Ser polymor-
phism with fasting serum cholesterol levels, which
could be consistent with the role of PGC-1 as a coac-
tivator of PPAR-a, in which genetic variability con-
fers alterations in circulating cholesterol levels [21].
Even though the PGC-1 Gly482Ser variant is asso-
ciated with Type II diabetes in the examined popula-
tions this variant might not be the causative polymor-
phism but could be in linkage disequilibrium with an
as yet unidentified aetiological variant. Gly482Ser is
located in a part of the protein whose function is not
known and glycine at residue 482 is not conserved be-
tween human beings and mice. However, a recent
study showed that residues 403±570 of PGC-1 are
critical for its interaction with MEF2C and thereby
the ability of PGC-1 to restore insulin sensitive
GLUT4 expression [4].
Intriguingly, homozygosity for the intronic variant
IVS2 + 52C®Aof the PGC-1 gene has been reported
to be associated with a decrease in age-adjusted and
sex-adjusted BMI in a study of 964 American Cauca-
sian subjects suggesting that this noncoding variant
could act protectively against fat accumulation [22].
Because stimulation of the b-3 adrenergic receptor
(b3AR) has been shown to induce PGC-1 expression
[2], the same authors also tested the interaction be-
tween the intronic PGC-1 variant and the Trp64Arg
variant in b3AR [22], which has been shown to be as-
sociated with features of the metabolic syndrome
[23±25]. They found that the IVS2 + 52C®Avariant
of PGC-1 decreased the odds of obesity in the ab-
sence of the Arg-allele but not in the presence of the
Arg-allele. In this study, the IVS2 + 52C®Avariant
was not associated with Type II diabetes nor was ho-
mozygosity of the variant associated with a higher
BMI in the diabetic or the normal glucose-tolerant
subjects.
In the initial association study, the Thr612Met
variant was not associated with Type II diabetes. In
contrast, the variant was found to be associated
with Type II diabetes both in the replication study
and in the combined study. It is not clear whether
this observation is due to linkage disequilibrium
with the Gly482Ser variant or whether it is a true
functional variant providing a reduced risk of devel-
oping Type II diabetes or a chance finding due to
multiple testing of various gene variants. Thr612Met
is located in a part of the protein whose function is
not known and is conserved between human beings
and mice.
In this study a test for interaction between the
Gly482Ser variant and the Pro12Ala variant in
PPAR-g2 gave no indication for additive effects on
diabetes status. However, due to the polygenic nature
of the common forms of Type II diabetes, future stud-
ies should examine the potential interactions of the
PGC-1 Gly482Ser,PPAR-gPro12Ala and b3AR
Trp64Arg polymorphisms to see if they have additive
or synergistic impact on the susceptibility to common
subsets of Type II diabetes mellitus.
Acknowledgements. The authors would like to thank A. For-
man, L. Aabo, I. L. Wantzin, and C. B. P. Sùholm for their ded-
icated technical assistance, and G. Lademann for secretarial
support. The study was supported by the Danish Medical Re-
search Council, the Danish Diabetes Association, the Danish
Heart Foundation, the Velux Foundation, and EEC (BMH4-
CT98±3084 and QLRT-CT-1999±00 546).
J. Ek et al.: Polymorphisms in PGC-1 and Type II diabetes 2225
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J. Ek et al.: Polymorphisms in PGC-1 and Type II diabetes2226
... PPARGC1A also plays a critical role in the maintenance of glucose and energy homeostasis and is likely involved in pathological disorders such as diabetes, neurodegeneration, obesity and cardiomyopathy [23]. Along this line, recent reports have suggested that the PPARGC1A Gly482Ser (rs 8192678; G/A coding sequence) missense polymorphism is associated with the onset of T2DM [24,25]. PPARD and PPARGC1A interact in the regulation of insulin action and modulate glucose and lipid metabolism in mitochondria during aerobic exercise [20]. ...
... The PPARGC1A SNP rs 8192678 (in exon 8, G1444A/Gly482Ser; C is the most important polymorphism identified to date in PPARGC1A [49]. The Gly482 (T) allele has been associated with poorer mitochondrial function in skeletal muscle [2 with an increased risk of T2DM [24], and the presence of the minor T allele seems to The functional pathways overrepresented in genotype PPARGC1A-1 versus genotype PPARGC1A-2 were as follows: gluconeogenesis I, adenosine nucleotides degradation II, gondoate biosynthesis and phosphopantothenate biosynthesis I. By contrast, the functional pathways more present in genotype PPARGC1A-2 and less represented in genotype PPARGC1A-1 were as follows: peptidoglycan biosynthesis IV, sucrose degradation IV, nitrate reduction VI, reductive TCA cycle I and CMP-legionaminate biosynthesis I. Analysis of the KEGG metabolic pathways predicted from metagenomes revealed an overrepresentation of ABC sugar transporters in participants with the PPARG1A-2 genotype when compared with those presenting the PPARG1A-1 genotype (Figure 4). ...
... The PPARGC1A SNP rs 8192678 (in exon 8, G1444A/Gly482Ser; C/T) is the most important polymorphism identified to date in PPARGC1A [49]. The Gly482Ser (T) allele has been associated with poorer mitochondrial function in skeletal muscle [20], with an increased risk of T2DM [24], and the presence of the minor T allele seems to be ...
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... The PPARG gene encodes the peroxisome proliferator-activated receptor γ, which plays a fundamental role in adipogen esis and insulin sensitivity by regulating transcriptional activi ty of various genes [13]. A frequent substitution of a glycine to serine amino acid at residue 482 in human PPARGC1A was described in 2001 [14] and it has been demonstrated to be associated with diabetes [14,15]. In the present study, a significant association of PGC 1 Alpha (Gly482Ser) polymorphism with T2DM was observed in three ethnic groups (Brahmins, Khatris and Guptas) of Jammu region of Jammu and Kashmir state as the statistically significant difference was observed between patients and controls in all the three ethnic groups. ...
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Le peptide atrial natriurétique (ANP) est une hormone sécrétée par le cœur qui, en se liant à son récepteur guanylyl cyclase A (GC-A), régule l'homéostasie des fluides et la fonction cardiaque. Ces 20 dernières années, son rôle en dehors des sphères cardiovasculaires et rénales a été étudié. Il s'est avéré que l'ANP a un effet lipolytique puissant dans le tissu adipeux et qu'il augmente les capacités oxydatives dans le muscle squelettique. De plus, les patients diabétiques de type 2 et les individus obèses présentent une diminution des niveaux plasmatiques d'ANP ainsi qu'une diminution du ratio GC-A/NPRC (natriuretic peptide receptor C ; un récepteur de clairance de l'ANP) dans leurs tissu adipeux et leurs muscles squelettiques. Dans la première partie de cette thèse, nous avons démontré que l'ANP est une hormone endocrine qui orchestre une réponse physiologique à une exposition au froid pour activer la thermogénèse sans frisson. Dans la deuxième partie de cette thèse, nous avons d'abord déterminé à 2h le temps de jeune optimal avant la réalisation d'un test de tolérance à l'insuline chez la souris. En effet, des temps de jeûne plus longs induisent une perte de poids importante ainsi que des stress métaboliques. Par la suite, nous avons démontré que lors d'un déficit du système ANP/GC-A, les souris présentent une dysfonction mitochondriale musculaire qui est associée à une intolérance à l'insuline sous régime hyperlipidique, une diminution des capacités d'endurance ainsi qu'une absence d'adaptation à un entrainement physique. Le déficit du système ANP/GC-A joue alors un rôle causal dans l'insulinorésistance et est nécessaire pour la fonction musculaire. L'ensemble de ces travaux démontre que le cœur, par sa fonction endocrine, joue un rôle important dans le contrôle du métabolisme énergétique et que le système ANP/GC-A représente un cible intéressante pour la prévention et/ou le traitement du diabète de type 2.
... However, it is important to notice that single nucleotide polymorphisms (SNPs) primarily associated with obesity tend to have a positive correlation between the effect size on BMI and the effect of the same SNP on T2D, yet SNPs primarily associated with T2D have no impact on BMI per se (15). Importantly, both GWAS and gene candidate approaches have led to the identification of genes implicated in the pathogenesis of obesity and/or T2D (14,16), which are involved in critical pathways for glucose regulatory processes, such as insulin signaling (INSR, IRS1, IRS2) (16)(17)(18)(19)(20), beta-cell differentiation and insulin secretion (PDX1, HNF4A, TCF7L2, SLC2A4, GLP1R, KCNQ1) (16,17,(21)(22)(23)(24), adipocyte differentiation (PPARG, PPARGC1A, LEP, ADIPOQ) (17,19,20,25,26), mitochondrial biogenesis and function (PGC1) (27), lipid and glucose homeostasis (SREBF1) (28) and cytokine signaling and inflammation (ADIPOQ) (29). ...
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... Most of these studies did not stratify their analysis by gender. More conclusively, the P12A allele has been associated with lower fasting insulin levels [58], increased insulin sensitivity [49,[58][59][60][61][62] and reduced risk of T2D [63][64][65][66][67][68][69]. In addition, we have previously associated the C248T SNP with statistically significant higher blood levels of total cholesterol and LDL-C (unpublished data), suggesting that CD24 may also play a role in dyslipidemia, possibly through regulation of PPARγ expression. ...
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... Several studies reported an association between PGC-1a polymorphism at position ?1564G/A (rs8192678) with NAFLD, T2DM and metabolic syndrome, which is associated with the substitution of Gly with Ser (Gly482Ser) (Ek et al. 2001;Kunej et al. 2004;Vohl et al. 2005;Yoneda et al. 2008;Burgueno et al. 2013;Saremi et al. 2019). In addition, rs12640088 had a significant interaction with body mass index (BMI) (Barroso et al. 2006;Villegas et al. 2014). ...
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