Project description:Endometriosis is associated with increased risk of epithelial ovarian cancers (EOCs). Using data from large endometriosis and EOC genome-wide association meta-analyses we estimate the genetic correlation and evaluate the causal relationship between genetic liability to endometriosis and EOC histotypes, and identify shared susceptibility loci. We estimate a significant genetic correlation (rg) between endometriosis and clear cell (rg=0.71), endometrioid (rg=0.48) and high-grade serous (rg=0.19) ovarian cancer, associations supported by Mendelian randomization analyses. Bivariate meta-analysis identify 28 loci associated with both endometriosis and EOC, including 19 with evidence for a shared underlying association signal. Differences in the shared risk suggest different underlying pathways may contribute to the relationship between endometriosis and the different histotypes. Functional annotation using transcriptomic and epigenomic profiles of relevant tissues/cells highlights several target genes. This comprehensive analysis reveals profound genetic overlap between endometriosis and EOC histotypes with valuable genomic targets for understanding the biological mechanisms linking the diseases.
Project description:Intestinal inflammation, which is often observed in farmed salmon, is caused by anti nutrient in feed ingredients of plant origin. The aim of this study is to increase knowledge of this patholology and to assess effects of physiologically active compounds applied as feed additives.Feeding trial was followed with metabolomic, transcriptomic and bacterial meta genomic analyses.
Project description:A transcriptomic meta-analysis of over 400 microarrays was undertaken to compare LPC lines against datasets of; muscle and embryonic stem cell lines, embryonic and developed liver (DL), and HCC. Uploaded here, is the array data from seven of the ten LPC lines used. These seven were prepared in our laboratory. The remaining LPC arrays and arrays from other tissues/cells were obtained from the GEO. A total of 405 microarrays were analysed in a meta analysis. This included the 381 publically-sourced arrays (13 of which were LPC arrays) and 24 LPC arrays performed within our lab. This data was mined to obtain signature LPC pathways and novel markers.