Big data identifies lipids as signatures of health and disease

Scientists from EPFL and the University of Wisconsin-Madison have carried out one of the most extensive lipidomics studies to date, connecting almost 150 different lipid species to their respective genetic regulators, revealing signatures of metabolic health and disease. Published in two papers in Cell Systems, the study is a landmark for metabolic health science. Biology is swaddled in lipids: fats, oils, and even waxes envelop cells and their organelles, mediate the flow of vast biological information networks, protect fragile tissues, and store essential energy across multiple organisms. But despite their importance, lipids have traditionally been among the hardest biomolecules to study because of the diversity of their molecular structures, which are not determined by the well-defined building blocks and simple rules that govern DNA, RNA, and proteins. And this diversity means that, unlike building and analyzing genome and transcriptome databases, lipids require more customized analytic procedures. Because of this, it is very difficult to study either the physiological function of a vast majority of lipid species or the way they are so precisely regulated in cells. But while lipidomics technologies are progressing, translating their findings into medical applications and introducing them into clinical laboratories is still a considerable challenge.