Afternoon Session: Identifying disease associated multi-gene networks with Synomics Studio. Case Studies on Bipolar Disease and Breast Cancer.
June 21, 2017 @ 4:00 pm - 5:00 pm BST| Free
Complex chronic diseases are usually polygenic, heterogeneous and have highly interrelated networks of metabolic processes. Multiple factors (including maybe 5 or 10 genes and many non-genomic factors such as co-morbidities, assay results, treatment history & environment) act in combination to determine the disease risk. Identifying clinically relevant networks of multi-modal biomarkers associated with specific outcomes, e.g. disease risk or therapy response, is hugely complex.
This talk will describe a new platform (Synomics) that enables very rapid discovery and validation of multi-omics biomarker networks, associating up to 30 features in combination across the largest genomics and clinical studies of complex diseases. An example association analysis of a breast cancer population of 14,777 people, all of whom had BRCA1 and/or BRCA2 mutations will be described. The most complex biomarker networks identified, with high clinical penetrance, contain 17 SNPs acting in combination. These results were found and validated in 6 days on a single 4 GPU POWER8 server.