Integrative Genome-Wide Association Studies of eQTL and GWAS Data for Gout Disease Susceptibility

Lee, Meng-tse Gabriel; Hsu, Tien-Pen; Chen, Shyr‐Chyr; Lee, Ya-Chin; Kuo, Po-Hsiu; Yang, Jing; Chang, Hong-Yeh; Lee, Chien‐Chang

doi:10.1038/s41598-019-41434-4

Cited by 15 publications

(15 citation statements)

References 35 publications

(34 reference statements)

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“…Furthermore, only based on the findings of GWAS analysis is impossible to infer whether the detected disease-associated SNPs contain regulatory functions. Thus, Sherlock integrative analysis is a good and effective method for combining the information of GWAS with eQTL data and has been applied to identify many novel risk genes of many complex diseases [15,[19][20][21][22], which cannot be detected by GWAS alone.…”

Section: Discussionmentioning

confidence: 99%

“…He et al [15] introduced a Bayesian statistical approach of Sherlock to systematically reveal the cis-and trans-regulatory effects of risk genes on complex diseases based on GWAS summary data and eQTL data. By using this bioinformatics tool, numerous studies have identified many novel risk genes, which cannot be found with the use of the GWAS approach alone, for different complex traits, such as schizophrenia [19], gout disease [20], and major depressive disorders [21,22].…”

Section: Introductionmentioning

confidence: 99%

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Integrative genomics analysis of eQTL and GWAS summary data identifies PPP1CB as a novel bone mineral density risk genes

Zhai

Shao

et al. 2020

Bioscience Reports

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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 (PeQTL = 1.42 × 10−17 and PGWAS = 1.40 × 10−11) and rs7475 (PeQTL = 2.10 × 10−6 and PGWAS = 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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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Integrative genomics analysis of eQTL and GWAS summary data identifies PPP1CB as a novel bone mineral density risk genes

Zhai

Shao

et al. 2020

Bioscience Reports

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“…Allopurinol indeed has the corresponding action in Drosophila; addition to the diet increases xanthine and hypoxanthine, and decreases urate and allantoin (Al Bratty et al 2011). A number of quantitative trait loci associated with gout have been identified in humans (Cheng et al 2004;Li et al 2007;Cummings et al 2010;Matsuo et al 2011;Lee et al 2019), and it will also be interesting to see whether Drosophila orthologs of these genes also play a role in maintaining fly urate levels.…”

Section: Modeling Disease Processesmentioning

confidence: 99%

Physiology, Development, and Disease Modeling in the Drosophila Excretory System

et al. 2020

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The insect excretory system contains two organ systems acting in concert: the Malpighian tubules and the hindgut perform essential roles in excretion and ionic and osmotic homeostasis. For over 350 years, these two organs have fascinated biologists as a model of organ structure and function. As part of a recent surge in interest, research on the Malpighian tubules and hindgut of Drosophila have uncovered important paradigms of organ physiology and development. Further, many human disease processes can be modeled in these organs. Here, focusing on discoveries in the past 10 years, we provide an overview of the anatomy and physiology of the Drosophila excretory system. We describe the major developmental events that build these organs during embryogenesis, remodel them during metamorphosis, and repair them following injury. Finally, we highlight the use of the Malpighian tubules and hindgut as accessible models of human disease biology. The Malpighian tubule is a particularly excellent model to study rapid fluid transport, neuroendocrine control of renal function, and modeling of numerous human renal conditions such as kidney stones, while the hindgut provides an outstanding model for processes such as the role of cell chirality in development, nonstem cell–based injury repair, cancer-promoting processes, and communication between the intestine and nervous system.

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“…Comparison of typical GWAS approach that generally abandon a large number of common genetic variants with moderate-to-small effects, Sherlock analysis is an effective and powerful tool for utilizing these abandoned common variants in GWAS. By using this tool, many novel risk genes, which are difficult to be identified by any single typical GWAS, were prioritized to involve in the pathogenesis of numerous complex diseases, including schizophrenia [ 31 ], major depressive disorders [ 32 , 33 ], and gout disease [ 34 ].…”

Section: Introductionmentioning

confidence: 99%

Integrative genomics analysis of various omics data and networks identify risk genes and variants vulnerable to childhood-onset asthma

Wang

et al. 2020

BMC Med Genomics

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Background Childhood-onset asthma is highly affected by genetic components. In recent years, many genome-wide association studies (GWAS) have reported a large group of genetic variants and susceptible genes associated with asthma-related phenotypes including childhood-onset asthma. However, the regulatory mechanisms of these genetic variants for childhood-onset asthma susceptibility remain largely unknown. Methods In the current investigation, we conducted a two-stage designed Sherlock-based integrative genomics analysis to explore the cis- and/or trans-regulatory effects of genome-wide SNPs on gene expression as well as childhood-onset asthma risk through incorporating a large-scale GWAS data (N = 314,633) and two independent expression quantitative trait loci (eQTL) datasets (N = 1890). Furthermore, we applied various bioinformatics analyses, including MAGMA gene-based analysis, pathway enrichment analysis, drug/disease-based enrichment analysis, computer-based permutation analysis, PPI network analysis, gene co-expression analysis and differential gene expression analysis, to prioritize susceptible genes associated with childhood-onset asthma. Results Based on comprehensive genomics analyses, we found 31 genes with multiple eSNPs to be convincing candidates for childhood-onset asthma risk; such as, PSMB9 (cis-rs4148882 and cis-rs2071534) and TAP2 (cis-rs9267798, cis-rs4148882, cis-rs241456, and trans-10,447,456). These 31 genes were functionally interacted with each other in our PPI network analysis. Our pathway enrichment analysis showed that numerous KEGG pathways including antigen processing and presentation, type I diabetes mellitus, and asthma were significantly enriched to involve in childhood-onset asthma risk. The co-expression patterns among 31 genes were remarkably altered according to asthma status, and 25 of 31 genes (25/31 = 80.65%) showed significantly or suggestively differential expression between asthma group and control group. Conclusions We provide strong evidence to highlight 31 candidate genes for childhood-onset asthma risk, and offer a new insight into the genetic pathogenesis of childhood-onset asthma.

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Integrative Genome-Wide Association Studies of eQTL and GWAS Data for Gout Disease Susceptibility

Cited by 15 publications

References 35 publications

Integrative genomics analysis of eQTL and GWAS summary data identifies PPP1CB as a novel bone mineral density risk genes

Integrative genomics analysis of eQTL and GWAS summary data identifies PPP1CB as a novel bone mineral density risk genes

Physiology, Development, and Disease Modeling in the Drosophila Excretory System

Integrative genomics analysis of various omics data and networks identify risk genes and variants vulnerable to childhood-onset asthma

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