No abstract

Nonalcoholic fatty liver disease (NAFLD) comprises fat-accumulating conditions within hepatocytes that can cause severe liver damage and metabolic comorbidities. Studies suggest that mitochondrial dysfunction contributes to its development and progression and that the hepatic lipidome changes extensively in obesity and in NAFLD. To gain insight into the relationship between lipid metabolism and disease progression through different stages of NAFLD, we performed lipidomic analysis of plasma and liver biopsy samples from obese patients with nonalcoholic fatty liver (NAFL) or nonalcoholic steatohepatitis (NASH) and from those without NAFLD. Congruent with earlier studies, hepatic lipid levels overall increased with NAFLD. Lipid species that differed with NAFLD severity were related to mitochondrial dysfunction; specifically, hepatic cardiolipin and ubiquinone accumulated in NAFL, and levels of acylcarnitine increased with NASH. We propose that increased levels of cardiolipin and ubiquinone may help to preserve mitochondrial function in early NAFLD, but that mitochondrial function eventually fails with progression to NASH, leading to increased acylcarnitine. We also found a negative association between hepatic odd-chain phosphatidylcholine and NAFLD, which may result from mitochondrial dysfunction-related impairment of branched-chain amino acid catabolism. Overall, these data suggest a close link between accumulation of specific hepatic lipid species, mitochondrial dysfunction, and the progression of NAFLD.

Changes to lipid metabolism are tightly associated with the onset and pathology of Alzheimer’s disease (AD). Lipids are complex molecules comprising many isomeric and isobaric species, necessitating detailed analysis to enable interpretation of biological significance. Our expanded targeted lipidomics platform (569 species across 32 classes) allows for detailed lipid separation and characterisation. In this study we examined peripheral samples of two cohorts (AIBL, n = 1112 and ADNI, n = 800). We are able to identify concordant peripheral signatures associated with prevalent AD arising from lipid pathways including; ether lipids, sphingolipids (notably GM3 gangliosides) and lipid classes previously associated with cardiometabolic disease (phosphatidylethanolamine and triglycerides). We subsequently identified similar lipid signatures in both cohorts with future disease. Lastly, we developed multivariate lipid models that improved classification and prediction. Our results provide a holistic view between the lipidome and AD using a comprehensive approach, providing targets for further mechanistic investigation.

In patients with metastatic melanoma, the identification and validation of accurate prognostic biomarkers will assist rational treatment planning. Studies based on "-omics" technologies have focussed on a single high-throughput data type such as gene or microRNA transcripts. Occasionally, these features have been evaluated in conjunction with limited clinico-pathologic data. With the increased availability of multiple data types, there is a pressing need to tease apart which of these sources contain the most valuable prognostic information. We evaluated and integrated several data types derived from the same tumor specimens in AJCC stage III melanoma patients-gene, protein, and microRNA expression as well as clinical, pathologic and mutation information-to determine their relative impact on prognosis. We used classification frameworks based on prevalidation and bootstrap multiple imputation to compare the prognostic power of each data source, both individually as well as integratively. We found that the prognostic utility of clinico-pathologic information was not out-performed by any of the various "-omics" platforms. Rather, a combination of clinico-pathologic variables and mRNA expression data performed best. Furthermore, a patient-based classification analysis revealed that the prognostic accuracy of various data types was not the same for different patients. This indicates that ongoing development in the individualized evaluation of melanoma patients must take account of the value of both traditional and novel "-omics" measurements.

Dysregulation of lipid homeostasis is a precipitating event in the pathogenesis and progression of hepatosteatosis and metabolic syndrome. These conditions are highly prevalent in developed societies and currently have limited options for diagnostic and therapeutic intervention. Here, using a proteomic and lipidomic-wide systems genetic approach, we interrogated lipid regulatory networks in 107 genetically distinct mouse strains to reveal key insights into the control and network structure of mammalian lipid metabolism. These include the identification of plasma lipid signatures that predict pathological lipid abundance in the liver of mice and humans, defining subcellular localization and functionality of lipid-related proteins, and revealing functional protein and genetic variants that are predicted to modulate lipid abundance. Trans-omic analyses using these datasets facilitated the identification and validation of PSMD9 as a previously unknown lipid regulatory protein. Collectively, our study serves as a rich resource for probing mammalian lipid metabolism and provides opportunities for the discovery of therapeutic agents and biomarkers in the setting of hepatic lipotoxicity. There is an increasingly urgent need to understand the causal factors that contribute to excess lipid accumulation in the liver known as hepatosteatosis, and an equally important need to discover biomarkers and interventions for its early diagnosis and treatment. A major proportion of current and predicted global health burden stems from conditions in which hepatosteatosis is an underlying pathology 1. Defining the mechanisms that causally influence hepatosteatosis has historically proven challenging, largely owing to an ill-defined interaction between genetic and environmental factors 2. This, together with the insufficient ability for standard genome-wide association studies to capture the effect of environment on complex traits, probably explains why only a small fraction of the estimated 30% heritability for hepatosteatosis has been assigned to specific gene variants 3. Genetic reference panels (GRPs) have become a more tractable way of studying the influence of genetics and environment on complex traits, because unlike studies in humans, GRPs allow for accurate control of environment as well as access to critical metabolic tissues. Importantly, integrating intermediate phenotypes such as transcriptomics, Parker et al.