Dataset Information

Prediction and Subtyping of Hypertension from Pan-Tissue Transcriptomic and Genetic Analyses.

ABSTRACT: Hypertension (HT) is a complex systemic disease involving transcriptional changes in multiple organs. Here we systematically investigate the pan-tissue transcriptional and genetic landscape of HT spanning dozens of tissues in hundreds of individuals. We find that in several tissues, previously identified HT-linked genes are dysregulated and the gene expression profile is predictive of HT. Importantly, many expression quantitative trait loci (eQTL) SNPs associated with the population variance of the dysregulated genes are linked with blood pressure in an independent genome-wide association study, suggesting that the functional effect of HT-associated SNPs may be mediated through tissue-specific transcriptional dysregulation. Analyses of pan-tissue transcriptional dysregulation profile, as well as eQTL SNPs underlying the dysregulated genes, reveals substantial heterogeneity among the HT patients, revealing two broad groupings - a Diffused group where several tissues exhibit HT-associated molecular alterations and a Localized group where such alterations are localized to very few tissues. These two patient subgroups differ in several clinical phenotypes including respiratory, cerebrovascular, diabetes, and heart disease. These findings suggest that the Diffused and Localized subgroups may be driven by different molecular mechanisms and have different genetic underpinning.

SUBMITTER: Basu M

PROVIDER: S-EPMC5676229 | biostudies-literature | 2017 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Prediction and Subtyping of Hypertension from Pan-Tissue Transcriptomic and Genetic Analyses.

Basu Mahashweta M Sharmin Mahfuza M Das Avinash A Nair Nishanth Ulhas NU Wang Kun K Lee Joo Sang JS Chang Yen-Pei Christy YC Ruppin Eytan E Hannenhalli Sridhar S

Genetics 20170912 3

<i>Hypertension</i> (HT) is a complex systemic disease involving transcriptional changes in multiple organs. Here we systematically investigate the pan-tissue transcriptional and genetic landscape of HT spanning dozens of tissues in hundreds of individuals. We find that in several tissues, previously identified HT-linked genes are dysregulated and the gene expression profile is predictive of HT. Importantly, many expression quantitative trait loci (eQTL) SNPs associated with the population varia ...[more]

PMID: 28899996

Similar Datasets

Project description:Molecular subtyping is expected to enable bladder cancer (BC) precise treatment. However, reliable subtyping strategies for clinical application remains defective and controversial. Given the significance of tumor immune dysfunction and exclusion (TIDE) in tumor immune escape and immunotherapy, we aimed to develop a novel TIDE-based subtyping method to facilitate personalized management. Transcriptome data of BC was used to evaluate the heterogeneity and the status of TIDE patterns. We identified 69 TIDE biomarker genes and classified BC samples into three subtypes using consensus clustering. Subtype I showed the lowest TIDE status and malignancy with the best prognosis and highest sensitivity to immune checkpoint blockade (ICB) treatment, which was enriched of metabolic related signaling pathways. Subtype III represented the highest TIDE status and malignancy with the poorest prognosis and resistance to ICB treatment, resulting from its inhibitory immune microenvironment and T cell terminal exhaustion. Subtype II was in a transitional state with intermediate TIDE level, malignancy, and prognosis. We further confirmed the existence and characteristics of our novel TIDE subtypes using real-world BC samples. This subtyping method was proved to be more efficient than previous known methods in identifying non-responders to immunotherapy. We also propose that combining our TIDE subtypes with known biomarkers can potentially improve the sensitivity and specificity of these biomarkers. Moreover, besides guiding ICB treatment, this classification approach can assist in selecting the frontline or recommended drugs. Finally, we confirmed that the TIDE subtypes are conserved across the pan-tumors. In conclusion, our novel TIDE-based subtyping method can serve as a powerful clinical tool for BC and pan-cancer patients, and potentially guiding personalized therapy decisions for selecting potential beneficiaries and excluding resistant patients of ICB therapy.

Dataset Information

Prediction and Subtyping of Hypertension from Pan-Tissue Transcriptomic and Genetic Analyses.

Publications

Prediction and Subtyping of Hypertension from Pan-Tissue Transcriptomic and Genetic Analyses.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets