Multi-scale OMICs analysis for novel pathways of coronary artery disease and ischemic stroke
The aim of subproject 2 of e:AtheroSysMed is to develop and apply novel tools for OMICs integration analyses in prospective cohort studies, in order to identify novel risk markers and pathways of coronary artery disease and ischemic stroke. Most study participants for subproject 2 come from the KORA study, a random population-based sample of about 18,000 individuals from the region of Augsburg, Germany. The study participants were followed up in regular intervals for 30 years and many are still actively participating in the study. The KORA OMICs database includes both rare and common genetic variation data, whole-blood methylome and transcriptome data, as well as serum metabolomics data.
We will integrate the multi-level OMICs data in KORA by combining graphical models with classical differential statistics to generate metabolic network models, and locate causal regulatory interaction networks linked to CAD and ischemic stroke. In subproject 2, we will also develop new tools tailored for these analyses, apply these approaches to newly collected KORA data and replicate our findings within e:Athero-Med (LURIC) and in SHIP, Twins-UK, MORGAM and other international datasets.
By applying systems biology tools to a prospective study design we will progress beyond current state-of-the-art, where OMICs data is often considered in isolation or cross-sectional settings. In close cooperation with the other scientists in e:AtheroSysMed this subproject will contribute substantially to bring about advances in understanding, predicting, and treating coronary artery disease and ischemic stroke.
Participants from the Helmholtz Zentrum München:
Annette Peters, Cavin Ward-Caviness - Institute of Epidemiology II
Christian Gieger, Elisabeth Altmaier - Research Unit Molecular Epidemiology
Fabian Theis, Jan Krumsiek, Kieu Trinh Do, Gökcen Eraslan, Nikola Müller - Institute of Computational Biology
Thomas Meitinger - Institute of Human Genetics
Keywords: omics, coronary artery disease, ischemic stroke, myocardial infarction, bioinformatics, epidemiology, molecular biology, statistics