Predose Blood Gene Expression Profiles Might Identify the Individuals Susceptible to Carbon Tetrachloride–Induced Hepatotoxicity

AbstractRespiratory viruses are highly infectious; however, the variation of individuals’ physiologic responses to viral exposure is poorly understood. Most studies examining molecular predictors of response focus on late stage predictors, typically near the time of peak symptoms. To determine whether pre- or early post-exposure factors could predict response, we conducted a community-based analysis to identify predictors of resilience or susceptibility to several respiratory viruses (H1N1, H3N2, Rhinovirus, and RSV) using peripheral blood gene expression profiles collected from healthy subjects prior to viral exposure, as well as up to 24 hours following exposure. This analysis revealed that it is possible to construct models predictive of symptoms using profiles even prior to viral exposure. Analysis of predictive gene features revealed little overlap among models; however, in aggregate, these genes were enriched for common pathways. Heme Metabolism, the most significantly enriched pathway, was associated with higher risk of developing symptoms following viral exposure.

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Physical activity and blood gene expression profiles: the Norwegian Women and Cancer (NOWAC) Post-genome cohort

BMC Research Notes ◽

10.1186/s13104-020-05121-2 ◽

2020 ◽

Vol 13 (1) ◽

Author(s):

Karina Standahl Olsen ◽

Marko Lukic ◽

Kristin Benjaminsen Borch

Keyword(s):

Gene Expression ◽

Physical Activity ◽

Expression Profiles ◽

Single Gene ◽

Gene Expression Profiles ◽

R Package ◽

Middle Aged ◽

Blood Gene Expression ◽

Gene Sets ◽

Gene Level

Abstract Objectives The influence of physical activity (PA) on the immune system has emerged as a new field of research. Regular PA may promote an anti-inflammatory state in the body, thus contributing to the down-regulation of pro-inflammatory processes related to the onset and progression of multiple diseases. We aimed to assess whether overall PA levels were associated with differences in blood gene expression profiles, in a cohort of middle-aged Norwegian women. We used information from 977 women included in the Norwegian Women and Cancer (NOWAC) Post-genome cohort. Information on PA and covariates was extracted from the NOWAC database. Blood samples were collected using the PAXgene Blood RNA collection system, and gene expression profiles were measured using Illumina microarrays. The R-package limma was used for the single-gene level analysis. For a target gene set analysis, we used the global test R-package with 48 gene sets, manually curated from the literature and relevant molecular databases. Results We found no associations between overall PA levels and gene expression profiles at the single-gene level. Similarly, no gene sets reached statistical significance at adjusted p < 0.05. In our analysis of healthy, middle-aged Norwegian women, self-reported overall PA was not associated with differences in blood gene expression profiles.

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