A multi-omics approach to investigate the inflammatory response to life course socioeconomic position

Aim: Inflammation represents a potential pathway through which socioeconomic position (SEP) is biologically embedded. Materials & methods: We analyzed inflammatory biomarkers in response to life course SEP by integrating multi-omics DNA-methylation, gene expression and protein level in 178 European Prospective Investigation into Cancer and Nutrition-Italy participants. Results & conclusion: We identified 61 potential cis acting CpG loci whose methylation levels were associated with gene expression at a Bonferroni correction. We examined the relationships between life course SEP and these 61 cis-acting regulatory methylation sites individually and jointly using several scores. Less-advantaged SEP participants exhibit, later in life, a lower inflammatory methylome score, suggesting an overall increased expression of the corresponding inflammatory genes or proteins, supporting the hypothesis that SEP impacts adult physiology through inflammation.

ToxDB: pathway-level interpretation of drug-treatment data

Motivation: Extensive drug treatment gene expression data have been generated in order to identify biomarkers that are predictive for toxicity or to classify compounds. However, such patterns are often highly variable across compounds and lack robustness. We and others have previously shown that supervised expression patterns based on pathway concepts rather than unsupervised patterns are more robust and can be used to assess toxicity for entire classes of drugs more reliably.

Results: We have developed a database, ToxDB, for the analysis of the functional consequences of drug treatment at the pathway level. We have collected 2694 pathway concepts and computed numerical response scores of these pathways for 437 drugs and chemicals and 7464 different experimental conditions. ToxDB provides functionalities for exploring these pathway responses by offering tools for visualization and differential analysis allowing for comparisons of different treatment parameters and for linking this data with toxicity annotation and chemical information.

Database URL:http://toxdb.molgen.mpg.de