Enhancing Research Through the Use of the Genotype-Tissue Expression (GTEx) Database

Stanfill, Ansley Grimes; Cao, Xueyuan

doi:10.1177/1099800421994186

Cited by 32 publications

(19 citation statements)

References 19 publications

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“…The current version of the GTEx database accessed on February 01th stores 17382 samples of 54 tissues of 948 donors, see at https://gtexportal.org/home/tissueSummaryPage. It is available thorugh a web interface offering easy and efficient data querying and visualisation [37,10,38,39]. Data may also be downloaded and analysed through an ad hoc realised script.…”

Section: Methodsmentioning

confidence: 99%

Differential network analysis between sex of thegenes related to comorbidities of type 2 mellitusdiabetes.

Guzzi

Cortese

Mannino

et al. 2023

Preprint

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Background Some phenotypical changes may be related to changes in the associations among genes. The set of such associations is referred to as gene interaction (or association) networks. An association network represent the set of association among genes in a given condition. Given two experimental conditions, Differential network analysis (DNA) algorithms analyse these differences by deriving a novel network representing the differences. Such algorithms receive as input experimental gene-expression data of two different conditions (e.g. healthy vs diseased), then they derive experimental networks of associations among genes and, finally, they analyse differences among networks using statistical approaches. We explore the possibility to study possible rewiring due to sex factors, differently from classical approaches. Methods We apply DNA methods to evidence possible sex based differences on genes responsible for comorbidities of type 2 diabetes mellitus. Results Our analysis evidences the presence of differential networks in tissues that may explain difference in the insurgence of comorbidities between males and females. Conclusion Main contributions of this work are: (i) the definition of a novel framework of analysis able to shed out light on the differences betweeen males and females; (ii) the identification of differential networks related to diabetes comorbidities. Availability and implementation: All the datasets underlying this article are publicly available. Data and source code can be accessed through the web at https://github.com/hguzzi/DifferentialNetworkDiabetes.

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Section: Methodsmentioning

confidence: 99%

Differential network analysis between sex of thegenes related to comorbidities of type 2 mellitusdiabetes.

Guzzi

Cortese

Mannino

et al. 2023

Preprint

View full text Add to dashboard Cite

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“…Variant-phenotypes associations were explored using FUMA eQTL (81), LDtrait (83) and PhenoScanner (84,85). Gene functions were explored in GeneCards database (86), tissue expression using GTEx portal (87,88), and gene-phenotype associations in the Online Mendelian Inheritance in Man database (OMIM) (89).…”

Section: In Silico Functional Analysismentioning

confidence: 99%

Genome-wide association study of blood mercury in European pregnant women and children

Dack

Taylor

Llop

et al. 2023

Preprint

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Background: Mercury (Hg) is a toxic heavy metal which humans are most commonly exposed to through food chain contamination, especially via fish consumption. Even low-level exposure can be harmful because of the poor clearance rate, particularly for methylmercury. It is likely that genetic variation modifies exposure through changes in the absorption, metabolism, and/or removal of mercury. Associations have been reported between Hg and variants at multiple genetic loci, but in many cases these results are not yet replicated. Methods: This study included two populations: pregnant women from the Avon Longitudinal Study of Parents and Children (ALSPAC, n=2,893) and children from the Human Early Life Exposome (HELIX, n=1,042). Genome-wide testing by cohort was performed by fitting linear regressions models on whole blood Hg levels and Haplotype Reference Consortium imputed single-nucleotide polymorphisms (SNPs). SNP heritability was estimated using linkage disequilibrium (LD)- score regression, and the biological functions of the top variants were investigated using resources which aggregate prior literature. Results: Hg SNP heritability was estimated to be 24.0% (95% CI: 16.9% to 46.4%) for pregnant women. The number of genetic variants independently associated with whole blood mercury levels above a suggestive p-value threshold (P < 1x10-5) was 16 for pregnant women and 21 for children. However, none were replicated in both populations, nor did any pass a stronger genome-wide significant threshold (P < 5x10-8). Several suggestive variants had possible biological links to Hg such as rs146099921 in metal transporterSLC39A14, and two variants (rs28618224, rs7154700) in potassium voltage-gated channels genes. Discussion: There was evidence for a considerable proportion of Hg variance being attributed to genome-wide variation in pregnant women. However, results between pregnant women and children were highly discordant which could reflect differences in metabolism and a gene-age interaction with Hg levels. There were a large number of SNPs suggestively associated with Hg levels, which likely include both true associations and false positives. These interim findings will be expanded following collaboration with additional study groups.

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“…GTEx has a web interface which offers query interfaces and visualisation. In recent years many independent studies used GTEx data to perform ageing-based analysis [18,[28][29][30].…”

Section: Related Workmentioning

confidence: 99%

Sex Age Annotated Omics Data: Enabling Powerful Omics Studies

Guzzi¹,

Cortese²,

Giancotti³

et al. 2023

Preprint

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There is increasing evidence that many molecular processes exhibit differences with age 1 and sex. Such differences produces also differences in the insurgence and progression of many 2 complex diseases. For instances, demographic data on insurgence of comorbidities of mellitus 3 diabetes, on lethality of COVID-19, and on some cancers, shows differences between sex and age 4 groups. Therefore, the growing interest on such area requires the management of related data as 5 well as the development of algorithms and tool for the analysis. The availability of omics data 6 annotated with metadata related to age and sex is mandatory for building pipeline of the analysis. 7 The number of databases containing data related to age and sex is hencefort growing. We here show 8 some databases and tools storing such data. Finally, future research direction are highlighte

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Enhancing Research Through the Use of the Genotype-Tissue Expression (GTEx) Database

Cited by 32 publications

References 19 publications

Differential network analysis between sex of thegenes related to comorbidities of type 2 mellitusdiabetes.

Differential network analysis between sex of thegenes related to comorbidities of type 2 mellitusdiabetes.

Genome-wide association study of blood mercury in European pregnant women and children

Sex Age Annotated Omics Data: Enabling Powerful Omics Studies

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