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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, TN2Texas Tech University Health, El Paso, TX3School of Medicine, Emory University, Atlanta, GA

Outline

Introduction Objectives Methods Analysis Results Conclusions Disclosure references

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Introduction

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.

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Introduction (cont.)

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).

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Introduction (cont.)

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.

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Study Aims

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.

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Methods

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

Human660W-Quad_v1_A are available for 3,564 individuals (1,442 obese and 2,122 controls).

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Methods (cont.)

The SAGE sample: GENEVA: Study of Addiction - Genetics and Environment (SAGE) is a comprehensive GWAS using approximately 4,000 unrelated subjects of European and African-American 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.

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Statistical analysis

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.

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Table 1. Descriptive characteristics of cases and controls

  Cases Controls  Marshfiel

dSAGE Marshfiel

dSAGE

Number 1,442 254 2,122 776Sex, N (%)

       

Males 623(43%) 73(29%) 852(40%) 198(26%)Female

s819(57%) 181(71%) 1,270(60

%)578(74%)

Age, years

       

Mean ± SD

65.2 ±10.4

41.5±8.9 67.1±11.8

39.2±9.1

Range 46-90 24-65 46-90 24-65

Results

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Genotype quality control and descriptive statistics

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 Kruskal-Wallis 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.

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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

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

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).

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Table 3. Haplotype analysis of the PSD3 gene in the Marshfield sample

Haplotype

 

 Frequencya ORb P-valuec  

rs7007413 rs11988239

 

C A 0.44 0.85 0.00141T G 0.45 1.23 3.23E-05C G 0.1 0.87 0.0842rs11988239 rs11995692      G C 0.45 1.23 3E-05A T 0.44 0.85 0.00119G T 0.11 0.87 0.0802rs11995692 rs748208      C T 0.30 1.18 0.00235C C 0.16 1.15 0.0362T C 0.54 0.81 6.97E-06aHaplotype frequency in the sample. bOR refers to the Odds ratio for each haplotype using PLINK.cP-value for the haplotype.

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 Haplotype analysis in the Marshfield sample

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).

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Figure 1. Linkage disequilibrium structure of six SNPs. The numbers indicate the r2 values between the corresponding two SNPs.

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Discussion

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.

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Discussion (cont.)

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 gene-environment interactions are warranted.

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Limitations

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

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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References

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Jin J, Chou C, Lima M, Zhou D, Zhou X (2014) Systemic Sclerosis is a Complex Disease Associated Mainly with Immune Regulatory and Inflammatory Genes. Open Rheumatol J 8:29-42.

Thomassen M, Tan Q, Kruse TA (2009) Gene expression metaanalysis identifies chromosomal regions and candidate genes involved in breast cancer metastasis. Breast Cancer Res Treat 113:239-249.

Saar K, Geller F, Rüschendorf F, et al. (2003) Genome scan for childhood and adolescent obesity in German families. Pediatrics 111(2):321-7.

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Thank you

Questions