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Liu L, Pei YF, Liu TL, Hu WZ, Yang XL, Li SC, Hai R, Ran S, Zhao LJ, Shen H, Tian Q, Xiao HM, Zhang K, Deng HW, Zhang L. Identification of a 1p21 independent functional variant for abdominal obesity. Int J Obes (Lond) 2019; 43:2480-2490. [PMID: 30944420 PMCID: PMC6776704 DOI: 10.1038/s41366-019-0350-z] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Revised: 12/08/2018] [Accepted: 01/25/2019] [Indexed: 12/11/2022]
Abstract
OBJECTIVES Aiming to uncover the genetic basis of abdominal obesity, we performed a genome-wide association study (GWAS) meta-analysis of trunk fat mass adjusted by trunk lean mass (TFMadj) and followed by a series of functional investigations. SUBJECTS A total of 11,569 subjects from six samples were included into the GWAS meta-analysis. METHODS Meta-analysis was performed by a weighted fixed-effects model. In silico replication analysis was performed in the UK-Biobank (UKB) sample (N = 331,093) and in the GIANT study (N up to 110,204). Cis-expression QTL (cis-eQTL) analysis, dual-luciferase reporter assay and electrophoresis mobility shift assay (EMSA) were conducted to examine the functional relevance of the identified SNPs. At last, differential gene expression analysis (DGEA) was performed. RESULTS We identified an independent SNP rs12409479 at 1p21 (MAF = 0.07, p = 7.26 × 10-10), whose association was replicated by the analysis of TFM in the UKB sample (one-sided p = 3.39 × 10-3), and was cross-validated by the analyses of BMI (one-sided p = 0.03) and WHRadj (one-sided p = 0.04) in the GIANT study. Cis-eQTL analysis demonstrated that allele A at rs12409479 was positively associated with PTBP2 expression level in subcutaneous adipose tissue (N = 385, p = 4.15 × 10-3). Dual-luciferase reporter assay showed that the region repressed PTBP2 gene expression by downregulating PTBP2 promoter activity (p < 0.001), and allele A at rs12409479 induced higher luciferase activity than allele G did (p = 4.15 × 10-3). EMSA experiment implied that allele A was more capable of binding to unknown transcription factors than allele G. Lastly, DGEA showed that the level of PTBP2 expression was higher in individuals with obesity than in individuals without obesity (N = 20 and 11, p = 0.04 and 9.22 × 10-3), suggesting a regulatory role in obesity development. CONCLUSIONS Taken together, we hypothesize a regulating path from rs12409479 to trunk fat mass development through its allelic specific regulation of PTBP2 gene expression, thus providing some novel insight into the genetic basis of abdominal obesity.
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Affiliation(s)
- Lu Liu
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Suzhou, China
| | - Yu-Fang Pei
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Suzhou, China
- Department of Epidemiology and Health Statistics, School of Public Health, Medical College of Soochow University, Suzhou, China
| | - Tao-Le Liu
- Center for Circadian Clock, School of Biology & Basic Medical Sciences, Medical College of Soochow University, Suzhou, China
| | - Wen-Zhu Hu
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Suzhou, China
| | - Xiao-Lin Yang
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, China
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Suzhou, China
| | - Shan-Cheng Li
- Department of Orthopedics, the Second Affiliated Hospital, Soochow University, Suzhou, China
| | - Rong Hai
- Inner Mongolia Autonomous Region People's Hospital, Hohhot, Inner Mongolia, China
| | - Shu Ran
- School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Lan Juan Zhao
- Tulane Center for Genomics and Bioinformatics, Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Hui Shen
- Tulane Center for Genomics and Bioinformatics, Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Qing Tian
- Tulane Center for Genomics and Bioinformatics, Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA
| | - Hong-Mei Xiao
- School of Basic Medical Sciences, Central South University, 410000, Changsha, China
| | - Kun Zhang
- Department of Computer Science, Bioinformatics Facility of Xavier NIH RCMI Cancer Research Center, Xavier University of Louisiana, New Orleans, LA, 70125, USA
| | - Hong-Wen Deng
- Tulane Center for Genomics and Bioinformatics, Department of Biostatistics and Bioinformatics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA, USA.
- School of Basic Medical Sciences, Central South University, 410000, Changsha, China.
| | - Lei Zhang
- Center for Genetic Epidemiology and Genomics, School of Public Health, Medical College of Soochow University, Suzhou, China.
- Jiangsu Key Laboratory of Preventive and Translational Medicine for Geriatric Diseases, Medical College of Soochow University, Suzhou, China.
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