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Integrative genomics analysis of eQTL and GWAS summary data identifies PPP1CB as a novel bone mineral density risk genes
Author(s) -
Yu Zhai,
Yu Lu,
Yang Shao,
Jianwei Wang
Publication year - 2020
Publication title -
bioscience reports
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.938
H-Index - 77
eISSN - 1573-4935
pISSN - 0144-8463
DOI - 10.1042/bsr20193185
Subject(s) - genome wide association study , expression quantitative trait loci , genomics , computational biology , bone mineral , biology , gene , genetics , bioinformatics , data science , genome , computer science , single nucleotide polymorphism , osteoporosis , genotype , endocrinology
In recent years, multiple genome-wide association studies (GWAS) have identified numerous susceptibility variants and risk genes that demonstrate significant associations with bone mineral density (BMD). However, exploring how these genetic variants contribute risk to BMD remains a major challenge. We systematically integrated two independent expression quantitative trait loci (eQTL) data ( N = 1890) and GWAS summary statistical data of BMD ( N = 142,487) using Sherlock integrative analysis to reveal whether expression-associated variants confer risk to BMD. By using Sherlock integrative analysis and MAGMA gene-based analysis, we found there existed 36 promising genes, for example, PPP1CB, XBP1 , and FDFT1 , whose expression alterations may contribute susceptibility to BMD. Through a protein–protein interaction (PPI) network analysis, we further prioritized the PPP1CB as a hub gene that has interactions with predicted genes and BMD-associated genes. Two eSNPs of rs9309664 ( P eQTL = 1.42 × 10 −17 and P GWAS = 1.40 × 10 −11 ) and rs7475 ( P eQTL = 2.10 × 10 −6 and P GWAS = 1.70 × 10 −7 ) in PPP1CB were identified to be significantly associated with BMD risk. Consistently, differential gene expression analysis found that the PPP1CB gene showed significantly higher expression in low BMD samples than that in high BMD samples based on two independent expression datasets ( P = 0.0026 and P = 0.043, respectively). Together, we provide a convergent line of evidence to support that the PPP1CB gene involves in the etiology of osteoporosis.

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