Integration of summary data from GWAS and eQTL studies identified novel causal BMD genes with functional predictions

Xiang-He Meng; Xiang-Ding Chen; Jonathan Greenbaum; Qin Zeng; Sheng-Lan You; Hong-Mei Xiao; Li-Jun Tan; Hong-Wen Deng

doi:10.1016/j.bone.2018.05.012

Integration of summary data from GWAS and eQTL studies identified novel causal BMD genes with functional predictions

Bone. 2018 Aug:113:41-48. doi: 10.1016/j.bone.2018.05.012. Epub 2018 May 12.

Authors

Xiang-He Meng¹, Xiang-Ding Chen¹, Jonathan Greenbaum², Qin Zeng¹, Sheng-Lan You¹, Hong-Mei Xiao³, Li-Jun Tan⁴, Hong-Wen Deng⁵

Affiliations

¹ Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, China.
² Center of Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA.
³ Institute of Reproduction and Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan 410013, China.
⁴ Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, China. Electronic address: ljtan@hunnu.edu.cn.
⁵ Laboratory of Molecular and Statistical Genetics, College of Life Sciences, Hunan Normal University, Changsha, Hunan 410081, China; Center of Bioinformatics and Genomics, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA; Institute of Reproduction and Stem Cell Engineering, School of Basic Medical Science, Central South University, Changsha, Hunan 410013, China. Electronic address: hdeng2@tulane.edu.

Abstract

Purpose: Osteoporosis is a common global health problem characterized by low bone mineral density (BMD) and increased risk of fracture. Genome-wide association studies (GWAS) have identified >100 genetic loci associated with BMD. However, the functional genes responsible for most associations remain largely unknown. We conducted an innovative summary statistic data-based Mendelian randomization (SMR) analysis to identify novel causal genes associated with BMD and explored their potential functional significance.

Methods: After quality control of the largest GWAS meta-analysis data of BMD and the largest expression quantitative trait loci (eQTL) meta-analysis data from peripheral blood samples, 5967 genes were tested using the SMR method. Another eQTL data was used to verify the results. Next we performed a fine-mapping association analysis to investigate the functional SNP in the identified loci. Weighted gene co-expression network analysis (WGCNA) was used to explore functional relationships for the identified novel genes with known putative osteoporosis genes. Further, we assessed functions of the identified genes through in vitro cellular study or previous functional studies.

Results: We identified two potentially causal genes (ASB16-AS1 and SYN2) associated with BMD. SYN2 was a novel osteoporosis candidate gene and ASB16-AS1 locus was known to be associated with BMD but was not the nearest gene to the top GWAS SNP. Fine-mapping association analysis showed that rs184478 and rs795000 was predicted to be possible causal SNPs in ASB16-AS1 and SYN2, respectively. ASB16-AS1 co-expressed with several known putative osteoporosis risk genes. In vitro cellular study showed that over-expressed ASB16-AS1 increased the expression of osteoblastogenesis related genes (BMP2 and ALPL), indicating its functional significance.

Conclusion: Our findings support that ASB16-AS1 and SYN2 may represent two novel functional genes underlying BMD variation. The findings provide a basis for further functional mechanistic studies.

Keywords: BMD; Osteoporosis; Summary data-based Mendelian randomization (SMR); Weighted gene co-expression network analysis (WGCNA).

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Bone Density / genetics*
Gene Expression Profiling / methods
Genetic Predisposition to Disease / genetics*
Genome-Wide Association Study
Humans
Osteoporosis / genetics*
Quantitative Trait Loci
Synapsins / genetics*

Substances

SYN2 protein, human
Synapsins

Abstract

Publication types

MeSH terms

Substances

Grants and funding