Download Polymorphisms of the PSD3 gene are associated with obesity in two

1
POLYMORPHISMS OF THE
PSD3 GENE ARE
ASSOCIATED WITH OBESITY
IN TWO CAUCASIAN
SAMPLES
Gong S1, Xu C2, Wang L1, Li Y3, Owusu D1, Wang K1
1Biostatistics
and Epidemiology, East Tennessee State University, TN
2Texas Tech University Health, El Paso, TX
3School of Medicine, Emory University, Atlanta, GA
Outline
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Introduction
Objectives
Methods
Analysis
Results
Conclusions
Disclosure
references
Introduction
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Current efforts of intensive research to alleviate
obesity by diet, exercise, education, surgery, and
drug therapies only have not well offered effective
long-term solutions to the obesity epidemic.
There is a need to explore the genetic and
epigenetic mechanisms involved in obesity initiation
and development.
Introduction (cont.)
4
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The genome-wide association studies (GWAS)
approach has been successful in identifying loci
harboring common forms of obesity susceptibility
genes using single-nucleotide polymorphisms (SNPs).
Genetic variants are increasingly recognized to be
associated with obesity using candidate gene
approaches in addition to GWAS (Loos, 2009;
Hebebrand et al., 2010).
Introduction (cont.)
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The pleckstrin and Sec7 domain containing 3 gene
(PSD3) is located at 8p22 and decreased expression of
PSD3 has been detected in multiple types of cancer,
suggesting that PSD3 is a potential tumor suppressor
gene for cancer (Thomassen et al., 2009).
PSD3 gene is associated with immune diseases such as
systemic sclerosis (Jin et al., 2014).
The real functions of the PSD3 gene remain to be
further clarified especially its association with the
obesity.
Study Aims
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To understand the association of PSD3 gene and
obesity
 We specifically examined genetic associations of 163
SNPs within the PSD3 gene with obesity using the
Marshfield sample (McCarty et al., 2005, 2008) and
conducted the replication study using the Study of
Addiction - Genetics and Environment (SAGE) sample
(Bierut et al., 2010).
-- Hypothesis: PSD3 gene polymorphisms
play an important role in obesity.
Methods
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The Marshfield sample: The Marshfield sample is
from the publicly available data from A GWAS on
Cataract and HDL in the Personalized Medicine
Research Project Cohort - Study Accession:
phs000170.v1.p1 (dbGaP).
 Genotyping data using the Illumina Human660WQuad_v1_A are available for 3,564 individuals
(1,442 obese and 2,122 controls).
Methods (cont.)
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The SAGE sample: GENEVA: Study of Addiction Genetics and Environment (SAGE) is a
comprehensive GWAS using approximately 4,000
unrelated subjects of European and AfricanAmerican descent.
In this study,
 We calculated the BMI based on height and weight
measures. Obesity was determined as a body mass
index (BMI) ≥ 30 (254 obese and 776 non-obese).
 We used the SAGE sample for replication study.

Statistical analysis
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Hardy-Weinberg equilibrium was tested for
all the SNPs using the controls by using
HAPLOVIEW software (Barrett et al., 2005).
 The minor allele frequency (MAF) was
determined for each SNP using PLINK v1.07
(Purcell et al., 2007).
 Logistic regression analysis of obesity,
adjusted for age and sex, was performed
using PLINK v1.07.

Results
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Table 1. Descriptive characteristics of cases and controls
Number
Sex, N (%)
Males
Females
Age, years
Mean ± SD
Range
Cases
Marshfield SAGE
1,442
254
Controls
Marshfield SAGE
2,122
776
623(43%)
819(57%)
852(40%) 198(26%)
1,270(60%) 578(74%)
73(29%)
181(71%)
65.2 ±10.4 41.5±8.9
46-90
24-65
67.1±11.8
46-90
39.2±9.1
24-65
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Genotype quality control and
descriptive statistics
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The mean age for participants are 65.2 years for
obese individuals and 67.1 for controls in
Marshfield sample (P<0.0001 based on KruskalWallis Test), and 41.5 years for cases and 39.2 for
controls in the SAGE sample (P=0.0004 based on
Kruskal-Wallis Test).
The range of age was 46-90 years for the
Marshfield sample and 24-65 years for the SAGE
sample.
Table 2. SNPs within PSD3 gene associated with obesity
in the Marshfield sample (P<0.05)
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Association with obesity in the
Marshfield sample
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Single marker analysis showed that
20 SNPs in the Marshfield sample
were associated with obesity (P <
0.05).
 SNP rs4921966 revealed strongest
association with obesity (P = 3.97 x
10-6).
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Replication study in the SAGE sample
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3 SNPs (rs11995692, rs7007413, and rs13256382)
were associated with obesity in the SAGE sample (P
< 0.05).
5 SNPs were associated with obesity with P<0.01 in
the SAGE sample (rs11204003, rs11783114,
rs1896201, rs11987871 and rs1025229 with P=
5.96 x10-5, 0.00525, 0.00699, 0.00819 and
0.0092, respectively).
Table 3. Haplotype analysis of the PSD3
gene in the Marshfield sample
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Frequencya
Haplotype
rs7007413
C
T
C
rs11988239
G
A
G
rs11995692
C
C
T
aHaplotype
rs11988239
A
G
G
rs11995692
C
T
T
rs748208
T
C
C
P-valuec
0.44
0.45
0.1
0.85
1.23
0.87
0.00141
3.23E-05
0.0842
0.45
0.44
0.11
1.23
0.85
0.87
3E-05
0.00119
0.0802
0.30
0.16
0.54
1.18
1.15
0.81
0.00235
0.0362
6.97E-06
frequency in the sample.
refers to the Odds ratio for each haplotype using PLINK.
cP-value for the haplotype.
bOR
ORb
Haplotype analysis in the Marshfield sample
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We identified a haplotype block for 6 SNPs using
HAPLOVIEW including rs11995692 and rs7007413
associated with obesity in both samples.
The T-G haplotype from rs7007413 and
rs11988239 (r2=0.64) revealed significant
association with obesity in the Marshfield sample (P
= 3.23 x 10-5).
The T-C haplotype from rs11995692 and rs748208
(r2=0.44) revealed significant association with
obesity in the Marshfield sample (P = 6.97 x 10-6).
Figure 1. Linkage disequilibrium structure of six SNPs. The
numbers indicate the r2 values between the corresponding
two SNPs.
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Discussion
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
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We first hypothesized and carried out the study on
the association of PSD3 with obesity.
Totally, 20 SNPs showed significant association
(P<0.05) with obesity in the Marshfield sample.
Haplotype analysis further supported the single
marker analysis results.
Several SNPs were replicated in the SAGE sample.
Discussion (cont.)
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We provide the preliminary basis for future studies
with focus on the effect of PSD3 particularly on the
obesity risk using longitudinal designs and diverse
population.
Future studies focusing on obesity-related geneenvironment interactions are warranted.
Limitations
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Although two samples were used to increase the
generalization, these findings may not be
generalizable to other populations in different
countries or ethnic groups (e.g., nonwhite).
 We only had two samples for the analysis, and
need to replicate in additional samples.
 Our current findings might be spurious or subject
to type I error.
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Conclusions
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We firstly observed the associations between the
PSD3 gene polymorphisms with obesity in two
Caucasian samples, providing a basis for replication
in other populations to elucidate the potential role
of these genetic variants.
Future functional study of this gene may help to
better characterize the genetic architecture of
obesity.
Disclosure

Originality
 Study
is original ideas of the authors and it has not
been published anywhere else

Conflict of interest
 The
authors declare that they have no conflict of
interest

Funding
 Authors
received no funding for the current study
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Thank you
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Questions