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

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

doi:10.1016/j.bone.2018.05.012

Cited by 24 publications

(18 citation statements)

References 60 publications

(87 reference statements)

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“…Data in cultured primary osteoclasts from 158 individuals were used to identify colocalizing eQTL for genes associated with BMD 123 . Moreover, eQTL analysis on other bone-related cells and tissues, such as circulating monocytes 120 , lymphocytes 124 or whole blood 124,125 , have also been widely applied to decipher the regulatory roles of GWAS variants in osteoporosis. For example, lymphocytes and peripheral blood eQTL were used to identify LINC00339 as a potentially causal gene for BMD GWAS 124 .…”

Section: An Integrative Approachmentioning

confidence: 99%

A road map for understanding molecular and genetic determinants of osteoporosis

et al. 2019

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Osteoporosis is a highly prevalent disorder characterized by low bone mineral density and an increased risk of fracture, termed osteoporotic fracture. Notably, bone mineral density, osteoporosis and osteoporotic fracture are highly heritable; however, determining the genetic architecture, and especially the underlying genomic and molecular mechanisms, of osteoporosis in vivo in humans is still challenging. In addition to susceptibility loci identified in genome-wide association studies, advances in various omics technologies, including genomics, transcriptomics, epigenomics, proteomics and metabolomics, have all been applied to dissect the pathogenesis of osteoporosis. However, each technology individually cannot capture the entire view of the disease pathology and thus fails to comprehensively identify the underlying pathological molecular mechanisms, especially the regulatory and signalling mechanisms. A change to the status quo calls for integrative multi-omics and inter-omics analyses with approaches in 'systems genetics and

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Section: An Integrative Approachmentioning

confidence: 99%

A road map for understanding molecular and genetic determinants of osteoporosis

et al. 2019

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“…To examine whether the GWAS variants associated with both AUD and DPW are mediated by changes in methylation and gene expression patterns, we conducted a summary data-based Mendelian randomization (SMR) analysis 59 on a set of mQTLs and eQTLs from fetal and adult brains. SMR is a Mendelian randomization-based analysis which integrates GWAS summary statistics with eQTL data in order to test whether the effect size of a SNP on the phenotype of interest is mediated by gene expression.…”

Section: Smr Analysismentioning

confidence: 99%

Multi-omics integration analysis identifies novel genes for alcoholism with potential link to neurodegenerative diseases

Kapoor

Chao

Johnson³

et al. 2020

Preprint

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Significance: Identification of causal variants and genes underlying genome-wide association study (GWAS) loci is essential to understanding the biology of alcohol use disorder (AUD). Methods: Integration of multi-omics data is often necessary to nominate candidate causal variants and genes and prioritize them for follow up studies. Here, we used Mendelian randomization to integrate AUD and drinks per week (DPW) GWAS summary statistics with the gene expression and methylation quantitative trait loci (eQTLs and mQTLs) in the largest brain and myeloid datasets. We also used AUD-related single cell epigenetic data to nominate candidate causal variants and genes associated with DPW and AUD. Results: Our multi-omics integration analyses prioritized unique as well as shared genes and pathways among AUD and DPW. The GWAS variants associated with both AUD and DPW showed significant enrichment in the promoter regions of fetal and adult brains. The integration of GWAS SNPs with mQTLs from fetal brain prioritized variants on chromosome 11 in both AUD and DPW GWASs. The co-localized variants were found to be overlapping with promoter marks for SPI1, specifically in human microglia, the myeloid cells of the brain. The co-localized SNPs were also strongly associated with SPI1 mRNA expression in myeloid cells from peripheral blood. The prioritized variant at this locus is predicted to alter the binding site for a transcription factor, RXRA, a key player in the regulation of myeloid cell function. Our analysis also identified MAPT as a candidate causal gene specifically associated with DPW. mRNA expression of MAPT was also correlated with daily amounts of alcohol intake in post-mortem brains (frontal cortex) from alcoholics and controls (N = 92). Results may be queried and visualized in an online public resource of these integrative analysis (https://lcad.shinyapps.io/alc_multiomics/). These results highlight overlap between causal genes for neurodegenerative diseases, alcohol use disorder and alcohol consumption. In conclusion, integrating GWAS summary statistics with multi-omics datasets from multiple sources identified biological similarities and differences between typical alcohol intake and disordered drinking highlighting molecular heterogeneity that might inform future targeted functional and cross-species studies. Interestingly, overlap was also observed with causal genes for neurodegenerative diseases.

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“…Integrating transcriptomics data from non-disease relevant sources has also been shown to provide insight given the expectation that some eQTL will be active across many different tissues [37]. For example, peripheral blood eQTL were recently used to identify ASB16 Antisense RNA 1( ASB16-AS1) and Synapsin II ( SYN2) as potentially causal BMD GWAS genes [42]. Furthermore, GTEx expression data from thyroid tissue was used in a recent study to link the expression of Microtubule Affinity Regulating Kinase 3 ( MARK3) to BMD-associated variants on Chr.…”

Section: Using Systems Genetics To Inform Bone Gwasmentioning

confidence: 99%

Dissecting the Genetics of Osteoporosis using Systems Approaches

Al‐Barghouthi

Farber

2019

Trends in Genetics

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Osteoporosis is a condition characterized by low bone mineral density and an increased risk of fracture. Traits contributing to osteoporotic fracture are highly heritable, indicating that a comprehensive understanding of bone requires a thorough understanding of the genetic basis of bone traits. Towards this goal, genome-wide association studies (GWASs) have identified over 500 loci associated with bone traits. However, few of the responsible genes have been identified, and little is known of how these genes work together to influence systems-level bone function. In this review, we describe how systems genetics approaches can be used to fill these knowledge gaps.

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

Abstract: 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.

Cited by 24 publications

References 60 publications

A road map for understanding molecular and genetic determinants of osteoporosis

A road map for understanding molecular and genetic determinants of osteoporosis

Multi-omics integration analysis identifies novel genes for alcoholism with potential link to neurodegenerative diseases

Dissecting the Genetics of Osteoporosis using Systems Approaches

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