The Lipidomics Reporting Checklist A framework for transparency of lipidomic experiments and repurposing resource data.

The rapid increase in lipidomic studies has led to a collaborative effort within the community to establish standards and criteria for producing, documenting, and disseminating data. Creating a dynamic easy-to-use checklist that condenses key information about lipidomic experiments into common terminology will enhance the field's consistency, comparability, and repeatability. Here, we describe the structure and rationale of the established Lipidomics Minimal Reporting Checklist to increase transparency in lipidomics research.

Hepatic-specific Pgc-1α ablation drives fibrosis in a MASH model.

BACKGROUND & AIMS: Metabolic dysfunction-associated steatohepatitis (MASH) is a growing cause of chronic liver disease, characterized by fat accumulation, inflammation and fibrosis, which development depends on mitochondrial dysfunction and oxidative stress. Highly expressed in the liver during fasting, peroxisome proliferator-activated receptor-γ coactivator-1α (PGC-1α) regulates mitochondrial and oxidative metabolism. Given the relevant role of mitochondrial function in MASH, we investigated the relationship between PGC-1α and steatohepatitis. METHODS: We measured the hepatic expression of Pgc-1α in both MASH patients and wild-type mice fed a western diet (WD) inducing steatosis and fibrosis. We then generated a pure C57BL6/J strain loss of function mouse model in which Pgc-1α is selectively deleted in the liver and we fed these mice with a WD supplemented with sugar water that accurately mimics human MASH. RESULTS: We observed that the hepatic expression of Pgc-1α is strongly reduced in MASH, in both humans and mice. Moreover, the hepatic ablation of Pgc-1α promotes a considerable reduction of the hepatic mitochondrial respiratory capacity, setting up a bioenergetic harmful environment for liver diseases. Indeed, the lack of Pgc-1α decreases mitochondrial function and increases inflammation, fibrosis and oxidative stress in the scenario of MASH. Intriguingly, this profibrotic phenotype is not linked with obesity, insulin resistance and lipid disbalance. CONCLUSIONS: In a MASH model the hepatic ablation of Pgc-1α drives fibrosis independently from lipid and glucose metabolism. These results add a novel mechanistic piece to the puzzle of the specific and crucial role of mitochondrial function in MASH development.

Pivotal role of intestinal cholesterol and nuclear receptor LXR in metabolic liver steatohepatitis and hepatocarcinoma.

Hepatocellular carcinoma (HCC) incidence is continuously increasing worldwide, due to the rise of metabolic dysfunction-associated steatohepatitis (MASH) cases. Cholesterol is an essential driver of the metabolic dysregulations that promote HCC progression. Liver X Receptor (LXR) is a nuclear receptor best known for the regulation of lipid and cholesterol homeostasis, with a prominent function in the liver and in the intestine. Here, we aimed to explore whether modifications in intestinal lipid metabolism may contribute to the onset of HCC, particularly taking into account cholesterol metabolism and LXRs. To study the progression of MASH to HCC, we induced metabolic HCC in wild-type male mice and mice carrying an intestinal chronic activation of LXRα. Also, we analysed human hepatic transcriptome datasets. The increased consumption of fat and carbohydrates drives the intestinal activation of LXRα and accelerates the onset of the hepatic tumours. Chronic intestinal-specific activation of LXRα enhances HCC progression only in the presence of a high cholesterol intake. In HCC, despite the increased hepatic cholesterol content, LXR is not active, thus driving liver cancer development. Intriguingly, in line with these results in the mouse model, LXR transcriptome is also downregulated in human hepatocarcinoma and its expression level in liver tumours directly correlates with a decreased survival rate in patients. Overall, our findings establish the relevance of the intestine in influencing the susceptibility to MASH-HCC and point to intestinal LXRα activation as a driver of metabolic liver cancer in the presence of dietary cholesterol.

Adverse effects of excessive dietary arachidonic acid on survival, PUFA-derived enzymatic and non-enzymatic oxylipins, stress response in rainbow trout fry.

Arachidonic acid (C20: 4n-6, AA) plays a fundamental role in fish physiology, influencing growth, survival and stress resistance. However, imbalances in dietary AA can have detrimental effects on fish health and performance. Optimal AA requirements for rainbow trout have not been established. This study aimed to elucidate the effects of varying dietary AA levels on survival, growth, long-chain polyunsaturated fatty acid (LC-PUFA) biosynthetic capacity, oxylipin profiles, lipid peroxidation, and stress resistance of rainbow trout fry. Over a period of eight weeks, 4000 female rainbow trout fry at the resorptive stage (0.12 g) from their first feeding were fed diets with varying levels of AA (0.6%, 1.1% or 2.5% of total fatty acids) while survival and growth metrics were closely monitored. The dietary trial was followed by an acute confinement stress test. Notably, while the fatty acid profiles of the fish reflected dietary intake, those fed an AA-0.6% diet showed increased expression of elongase5, highlighting their inherent ability to produce LC-PUFAs from C18 PUFAs and suggesting potential AA or docosapentaenoic acidn-6 (DPAn-6) biosynthesis. However, even with this biosynthetic capacity, the trout fed reduced dietary AA had higher mortality rates. The diet had no effect on final weight (3.38 g on average for the three diets). Conversely, increased dietary AA enhanced eicosanoid production from AA, suggesting potential inflammatory and oxidative consequences. This was further evidenced by an increase in non-enzymatic lipid oxidation metabolites, particularly in the AA-2.5% diet group, which had higher levels of phytoprostanes and isoprostanes, markers of cellular oxidative damage. Importantly, the AA-1.1% diet proved to be particularly beneficial for stress resilience. This was evidenced by higher post-stress turnover rates of serotonin and dopamine, neurotransmitters central to the fish's stress response. In conclusion, a dietary AA intake of 1.1% of total fatty acids appears to promote overall resilience in rainbow trout fry.

Energy Resolved Mass Spectrometry for Interoperable Non-resonant Collisional Spectra in Metabolomics.

In untargeted metabolomics, the unambiguous identification of metabolites remains a major challenge. This requires high-quality spectral libraries for reliable metabolite identification, which is essential for translating metabolomics data into meaningful biological information. Several attempts have been made to generate reproducible product ion spectra (PIS) under a low collision energy (ELab) regime and nonresonant collisional conditions but have not fully succeeded. We examined the ERMS (energy-resolved mass spectrometry) breakdown curves of two lipo-amino acids and showed the possibility to highlight "singular points", called descriptors hereafter (linked to respective ELab depending on the instrument), for each of the monomodal product ion profiles. Using several instruments based on different technologies, the PIS recorded at these specific ELab sites shows remarkable similarities. The descriptors appeared as being independent of the fragmentation mechanisms and can be used to overcome the main instrumental effects that limit the interoperability of spectral libraries. This proof-of-concept study, performed on two particular lipo-amino acids, demonstrates the high potential of ERMS-derived information to determine the instrument-specific ELab at which PIS recorded in nonresonant conditions become highly similar and instrument-independent, thus comparable across platforms. This innovative but straightforward approach could help remove some of the obstacles to metabolite identification in nontargeted metabolomics, putting an end to a challenging chimera.

Integrative Multimodal Metabolomics to Early Predict Cognitive Decline Among Amyloid Positive Community-Dwelling Older Adults.

Alzheimer's disease is strongly linked to metabolic abnormalities. We aimed to distinguish amyloid-positive people who progressed to cognitive decline from those who remained cognitively intact. We performed untargeted metabolomics of blood samples from amyloid-positive individuals, before any sign of cognitive decline, to distinguish individuals who progressed to cognitive decline from those who remained cognitively intact. A plasma-derived metabolite signature was developed from Supercritical Fluid chromatography coupled with high-resolution mass spectrometry (SFC-HRMS) and nuclear magnetic resonance (NMR) metabolomics. The 2 metabolomics data sets were analyzed by Data Integration Analysis for Biomarker discovery using Latent approaches for Omics studies (DIABLO), to identify a minimum set of metabolites that could describe cognitive decline status. NMR or SFC-HRMS data alone cannot predict cognitive decline. However, among the 320 metabolites identified, a statistical method that integrated the 2 data sets enabled the identification of a minimal signature of 9 metabolites (3-hydroxybutyrate, citrate, succinate, acetone, methionine, glucose, serine, sphingomyelin d18:1/C26:0 and triglyceride C48:3) with a statistically significant ability to predict cognitive decline more than 3 years before decline. This metabolic fingerprint obtained during this exploratory study may help to predict amyloid-positive individuals who will develop cognitive decline. Due to the high prevalence of brain amyloid-positivity in older adults, identifying adults who will have cognitive decline will enable the development of personalized and early interventions.

Challenges and perspectives for naming lipids in the context of lipidomics.

INTRODUCTION: Lipids are key compounds in the study of metabolism and are increasingly studied in biology projects. It is a very broad family that encompasses many compounds, and the name of the same compound may vary depending on the community where they are studied. OBJECTIVES: In addition, their structures are varied and complex, which complicates their analysis. Indeed, the structural resolution does not always allow a complete level of annotation so the actual compound analysed will vary from study to study and should be clearly stated. For all these reasons the identification and naming of lipids is complicated and very variable from one study to another, it needs to be harmonized. METHODS & RESULTS: In this position paper we will present and discuss the different way to name lipids (with chemoinformatic and semantic identifiers) and their importance to share lipidomic results. CONCLUSION: Homogenising this identification and adopting the same rules is essential to be able to share data within the community and to map data on functional networks.