ArticleBone2018
Integration of summary data from GWAS and eQTL studies identified novel causal BMD genes with functional predictions.
Article in Bone, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 32 citations in OpenAlex.
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- Identifying Thyroid Carcinoma-Related Genes by Integrating GWAS and eQTL Data.Frontiers in cell and developmental biology · 2021Article
- A novel computational strategy for DNA methylation imputation using mixture regression model (MRM).BMC bioinformatics · 2020Article
- Approximation of bias and mean-squared error in two-sample Mendelian randomization analyses.Biometrics · 2020Article
- A road map for understanding molecular and genetic determinants of osteoporosis.Nature reviews. Endocrinology · 2020Review
- Identification of Gingivitis-Related Genes Across Human Tissues Based on the Summary Mendelian Randomization.Frontiers in cell and developmental biology · 2020Article
- Comprehensive Analysis of the Genetic and Epigenetic Mechanisms of Osteoporosis and Bone Mineral Density.Frontiers in cell and developmental biology · 2020Article
- SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studies.BMC genetics · 2019Article
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Corrections and comments
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
Abstract
purposeOsteoporosis 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.
methodsAfter 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.
resultsWe 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.
conclusionOur 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.
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Registered trials
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