With an ever-increasing pool of accessible information and new tools to mine huge data sets, biology and medicine are moving from intervention to prevention. Omics sciences such as genomics and lipidomics are strong contributors to this paradigm shift. Being major players in cardiovascular disease research, genomics and lipidomics make a great multiomics pair. It matches the capacity to identify genetic predestinations with one or multiple snapshots of the lipid metabolic status to investigate cardiovascular diseases.
The symposium on the regional innovative Wachstumskern Praemed.Bio will take place on-line and in English on 29.10.2020.
Just in time of Christmas, scientists from the German Institute for Human Nutrition (DIfE) and Lipotype GmbH have published their results of their research on the influence of fatty breakfasts and dinners on lipid metabolism. Their newly discovered “biological lipid metabolism clock” fills a gap in nutritional medicine to activate nutrition for prevention and intervention, and to research how specific foods at specific times of the day can contribute to our health or disease.
Obesity is a prime threat to human health. In daily healthcare practice, the go-to indicator of overweight and obesity is the body mass index (BMI). Now, an international team of scientists led by Lipotype introduces a revolutionary A.I. BMI approach towards personalized and precision medicine.
Multiomics approaches harness synergies and eliminate shortcomings to effectively deliver what one omics science alone cannot achieve. Lipotype’s new whitepaper “Unlocking the Power of Multiomics” highlights why combining genomics with lipidomics makes for a great omics pair.
Lipidomics is the large-scale investigation of lipids in biological systems. Venturing into the analysis of large dataset, with potential thousands of lipidomes, by advanced multiparametric statistical approaches is a challenging endeavor.
In the latest issue of the Journal of the American Heart Association, Lipotype and Lund University published a paper in which high-throughput lipidomic screening was successfully applied to reveal molecular lipid profiles in blood serum specific for Diabetes mellitus and myocardial infarction.