In this era of genomics, transcriptomics, and proteomics, metabolomics is emerging as an important component of the omics evolution ( 1 ). Of the four kinds of biological molecules that comprise the human body, i.e., nucleic acids, amino acids (proteins), carbohydrates (sugars), and lipids (fats), lipids stand out among the various cellular metabolites in the sheer number of distinct molecular species. Using state-of-the-art lipidomics approaches made possible by newly developed instrumentation, protocols, and bioinformatics tools ( 2 ), the LIPID MAPS Consortium Abstract The focus of the present study was to defi ne the human plasma lipidome and to establish novel analytical methodologies to quantify the large spectrum of plasma lipids. Partial lipid analysis is now a regular part of every patient's blood test and physicians readily and regularly prescribe drugs that alter the levels of major plasma lipids such as cholesterol and triglycerides. Plasma contains many thousands of distinct lipid molecular species that fall into six main categories including fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, sterols, and prenols. The physiological contributions of these diverse lipids and how their levels change in response to therapy remain largely unknown. As a fi rst step toward answering these questions, we provide herein an in-depth lipidomics analysis of a pooled human plasma obtained from healthy individuals after overnight fasting and with a gender balance and an ethnic distribution that is representative of the US population. In total, we quantitatively assessed the levels of over 500 distinct molecular species distributed among the main lipid categories. As more information is obtained regarding the roles of individual lipids in health and disease, it seems likely that future blood tests will include an ever increasing number of these lipid molecules. -Quehenberger, O., A.

As the lipidomics field continues to advance, self-evaluation within the community is critical. Here, we performed an interlaboratory comparison exercise for lipidomics using Standard Reference Material (SRM) 1950-Metabolites in Frozen Human Plasma, a commercially available reference material. The interlaboratory study comprised 31 diverse laboratories, with each laboratory using a different lipidomics workflow. A total of 1,527 unique lipids were measured across all laboratories and consensus location estimates and associated uncertainties were determined for 339 of these lipids measured at the sum composition level by five or more participating laboratories. These evaluated lipids detected in SRM 1950 serve as community-wide benchmarks for intra- and interlaboratory quality control and method validation. These analyses were performed using nonstandardized laboratory-independent workflows. The consensus locations were also compared with a previous examination of SRM 1950 by the LIPID MAPS consortium. While the central theme of the interlaboratory study was to provide values to help harmonize lipids, lipid mediators, and precursor measurements across the community, it was also initiated to stimulate a discussion regarding areas in need of improvement.

Nonalcoholic fatty liver disease (NAFLD) is rapidly becoming one of the most common forms of liver disease in Abstract The spectrum of nonalcoholic fatty liver disease (NAFLD) includes steatosis, nonalcoholic steatohepatitis (NASH), and cirrhosis. Recognition and timely diagnosis of these different stages, particularly NASH, is important for both potential reversibility and limitation of complications. Liver biopsy remains the clinical standard for defi nitive diagnosis. Diagnostic tools minimizing the need for invasive procedures or that add information to histologic data are important in novel management strategies for the growing epidemic of NAFLD. We describe an "omics" approach to detecting a reproducible signature of lipid metabolites, aqueous intracellular metabolites, SNPs, and mRNA transcripts in a double-blinded study of patients with different stages of NAFLD that involves profi ling liver biopsies, plasma, and urine samples. Using linear discriminant analysis, a panel of 20 plasma metabolites that includes glycerophospholipids, sphingolipids, sterols, and various aqueous small molecular weight components involved in cellular metabolic pathways, can be used to differentiate between NASH and steatosis. This identifi cation of differential biomolecular signatures has the potential to improve clinical diagnosis and facilitate therapeutic intervention of

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Summary Small-molecule inhibitors targeting growth factor receptors have failed to show efficacy for brain cancers, potentially due to inability to achieve sufficient drug levels in the CNS. Targeting non-oncogene tumor co-dependencies provides an alternative approach, particularly if drugs with high brain penetration can be identified. Here we demonstrate that the highly lethal brain cancer glioblastoma (GBM) is remarkably dependent on cholesterol for survival, rendering these tumors sensitive to Liver X receptor (LXR) agonist-dependent cell death. We show that LXR-623, a clinically viable, highly brain-penetrant LXRα-partial/LXRβ-full agonist selectively kills GBM cells in an LXRβ- and cholesterol-dependent fashion, causing tumor regression and prolonged survival in mouse models. Thus, a metabolic co-dependency provides a pharmacological means to kill growth factor-activated cancers in the CNS.