Analyzing Genome-Wide Association Study Dataset Highlights Immune Pathways in Lip Bone Mineral Density

Liu, Xiaodong; Zhang, Yiwei; Tian, Jian; Gao, Feng

doi:10.3389/fgene.2020.00004

Cited by 3 publications

(2 citation statements)

References 43 publications

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“…We analyzed the 36 GWASs of European ancestry ( S1 – S3 Tables ) using the aforementioned multitrait approaches applied to seven phenotype sets: five medical-based sets ( Immunity , Anthropometry , Metabolism , Cardiovascular and Psychiatric ), a BMI related set including anthropometry traits and lipids (referred further as the Composite set), and finally all 36 phenotypes jointly ( Fig 2 ). Note that we included bone mineral density traits in the Immunity set because an enrichment of BMD genome wide significant loci in immune pathways and immune cell regulatory regions has been previously reported[ 34 , 35 ]. We derived the overlap of significant loci of the multitrait tests per phenotype set ( S15 – S21 Figs ), and after merging all analyses ( Fig 3A ).…”

Section: Resultsmentioning

confidence: 99%

Multitrait GWAS to connect disease variants and biological mechanisms

et al. 2021

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Genome-wide association studies (GWASs) have uncovered a wealth of associations between common variants and human phenotypes. Here, we present an integrative analysis of GWAS summary statistics from 36 phenotypes to decipher multitrait genetic architecture and its link with biological mechanisms. Our framework incorporates multitrait association mapping along with an investigation of the breakdown of genetic associations into clusters of variants harboring similar multitrait association profiles. Focusing on two subsets of immunity and metabolism phenotypes, we then demonstrate how genetic variants within clusters can be mapped to biological pathways and disease mechanisms. Finally, for the metabolism set, we investigate the link between gene cluster assignment and the success of drug targets in randomized controlled trials.

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Section: Resultsmentioning

confidence: 99%

Multitrait GWAS to connect disease variants and biological mechanisms

et al. 2021

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“…Recently developed tools and databases of GWA studies have enabled the collective analysis of diseases’ genetic variants across many samples, which facilitates the discovery of the molecular bases of this association between various diseases and genetic polymorphisms ( 11 – 13 ). This is particularly relevant for reconstructing upstream signals that lead to disease specific gene signatures.…”

Section: Introductionmentioning

confidence: 99%

Comprehensive Integration of Genome-Wide Association and Gene Expression Studies Reveals Novel Gene Signatures and Potential Therapeutic Targets for Helicobacter pylori-Induced Gastric Disease

2021

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Helicobacter pylori is a gram-negative bacterium that colonizes the human gastric mucosa and can lead to gastric inflammation, ulcers, and stomach cancer. Due to the increase in H. pylori antimicrobial resistance new methods to identify the molecular mechanisms of H. pylori-induced pathology are urgently needed. Here we utilized a computational biology approach, harnessing genome-wide association and gene expression studies to identify genes and pathways determining disease development. We mined gene expression data related to H. pylori-infection and its complications from publicly available databases to identify four human datasets as discovery datasets and used two different multi-cohort analysis pipelines to define a H. pylori-induced gene signature. An initial Helicobacter-signature was curated using the MetaIntegrator pipeline and validated in cell line model datasets. With this approach we identified cell line models that best match gene regulation in human pathology. A second analysis pipeline through NetworkAnalyst was used to refine our initial signature. This approach defined a 55-gene signature that is stably deregulated in disease conditions. The 55-gene signature was validated in datasets from human gastric adenocarcinomas and could separate tumor from normal tissue. As only a small number of H. pylori patients develop cancer, this gene-signature must interact with other host and environmental factors to initiate tumorigenesis. We tested for possible interactions between our curated gene signature and host genomic background mutations and polymorphisms by integrating genome-wide association studies (GWAS) and known oncogenes. We analyzed public databases to identify genes harboring single nucleotide polymorphisms (SNPs) associated with gastric pathologies and driver genes in gastric cancers. Using this approach, we identified 37 genes from GWA studies and 61 oncogenes, which were used with our 55-gene signature to map gene-gene interaction networks. In conclusion, our analysis defines a unique gene signature driven by H. pylori-infection at early phases and that remains relevant through different stages of pathology up to gastric cancer, a stage where H. pylori itself is rarely detectable. Furthermore, this signature elucidates many factors of host gene and pathway regulation in infection and can be used as a target for drug repurposing and testing of infection models suitability to investigate human infection.

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Multitrait genetic-phenotype associations to connect disease variants and biological mechanisms

Julienne

Laville

McCaw

et al. 2020

Preprint

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Genome-wide association studies (GWAS) uncovered a wealth of association between common variants and human phenotypes. Here, we present an integrative analysis of GWAS summary statistics from 36 phenotypes to decipher multitrait genetic architecture and its link to biological mechanisms. Our framework incorporates multitrait association mapping along with an investigation of the breakdown of genetic association into clusters of variants harboring similar multitrait association profile. Focusing on two subsets of immunity and metabolism phenotypes, we then demonstrate how SNPs within clusters can be mapped to biological pathways and disease mechanisms. Finally, for the metabolism set, we investigate the link between gene cluster assignment and success of drug targets in random control trials.

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Analyzing Genome-Wide Association Study Dataset Highlights Immune Pathways in Lip Bone Mineral Density

Cited by 3 publications

References 43 publications

Multitrait GWAS to connect disease variants and biological mechanisms

Multitrait GWAS to connect disease variants and biological mechanisms

Comprehensive Integration of Genome-Wide Association and Gene Expression Studies Reveals Novel Gene Signatures and Potential Therapeutic Targets for Helicobacter pylori-Induced Gastric Disease

Multitrait genetic-phenotype associations to connect disease variants and biological mechanisms

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