PuSH - Publication Server of Helmholtz Zentrum München: Integrative multiomics study for validation of mechanisms in radiation-induced ischemic heart disease in Mayak workers.

Information

Clues to quality of journals

Open Access Policy of Helmholtz Association 2016

CC Licencences

Publication Metrics

Navigation

Home

Deutsch

EVA: Electronic Publishing

New EVA Application

Research

Advanced Search

Browse by ...

... HMGU-Authors/Consortia

... Organizational Structure

... Journal

... Publication Type

... Research Data

... Arbeitsgruppen

... Publication Year

Publication overview

Statistics

Statistics (last 5 years)

OA Publications

Publish

Submit Publication

Import publication from...

...EVA

Report missing publication

Highlights

Support & Contact

Contact persons

Help

Data protection

Helmholtz Open Science

JANE Journal Estimator

SHERPA/RoMEO

DOAJ

Export:

Text

Endnote (RIS) BIB

BibTeX

Papiez, A.* ; Azimzadeh, O. ; Azizova, T.* ; Moseeva, M.* ; Anastasov, N. ; Smida, J. ; Tapio, S. ; Polanska, J.*

Integrative multiomics study for validation of mechanisms in radiation-induced ischemic heart disease in Mayak workers.

PLoS ONE 13:e0209626 (2018)

Publ. Version/Full Text

Research data

DOI

PMC

	Open Access Gold

Abstract
Metrics
Extra information

Previous studies have suggested that exposure to ionizing radiation increases the risk of ischemic heart disease (IHD). The data from the Mayak nuclear worker cohort have indicated enhanced risk for IHD incidence. The goal of this study was to elucidate molecular mechanisms of radiation-induced IHD by integrating proteomics data with a transcriptomics study on post mortem cardiac left ventricle samples from Mayak workers categorized in four radiation dose groups (0 Gy, < 100 mGy, 100-500 mGy, > 500 mGy). The proteomics data that were newly analysed here, originated from a label-free analysis of cardiac samples. The transcriptomics analysis was performed on a subset of these samples. Stepwise linear regression analyses were used to correct the age-dependent changes in protein expression, enabling the separation of proteins, the expression of which was dependent only on the radiation dose, age or both of these factors. Importantly, the majority of the proteins showed only dose-dependent expression changes. Hierarchical clustering of the proteome and transcriptome profiles confirmed the separation of control and high-dose samples. Restrictive (separate p-values) and integrative (combined p-value) approaches were used to investigate the enrichment of biological pathways. The integrative method proved superior in the validation of the key biological pathways found in the proteomics analysis, namely PPAR signalling, TCA cycle and glycolysis/gluconeogenesis. This study presents a novel, improved, and comprehensive statistical approach of analysing biological effects on a limited number of samples.

Impact Factor

Scopus SNIP

Web of Science
Times Cited

Scopus
Cited By

Altmetric

2.766

1.111