Blog Archives

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During this webinar, we will talk about the role of the lipidome in risk prediction and differential diagnosis of cardiovascular diseases. The webinar will start with a general introduction to cardiovascular diseases. We will then talk about using lipidomics to differentiate between various cardiovascular and inflammatory diseases. Further, we will discuss the pivotal role lipids play in cardiovascular disease risk prediction in addition to the routinely measured clinical parameters and explore the role of multiomics in the prediction of cardiovascular risk development. Finally, we will review the application of lipidomics to translational heart failure research in mice and humans.

Here is what you can learn

• Lipidomics data for CVD differential diagnosis
• Lipidomics risk score for CVD risk estimation
• Multiomics analyses for risk factors discovery
• Translational lipidomics applied to heart failure

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This webinar is dedicated to skin lipids and their role in skin health and disease and will discuss lipid composition and function in different skin structures. The webinar will begin with an overview of skin anatomy with a focus on the stratum corneum. The lipidome of normal skin will be discussed next, emphasizing the importance of ceramides. Our scientific talk will focus on the pivotal role ceramides play in skin physiology and their relevance in context of skin research and product claim support. During the webinar, factors contributing to variability in skin lipidome and ceramidome will be discussed, including age, sex, body part, pigmentation, depth of skin sampling, and seasonal differences. Finally, we will examine the alterations in the skin lipidome caused by various pathological conditions, such as xerosis, atopic dermatitis, and psoriasis, and explore the relationship between the skin lipidome and the skin microbiome.

Here is what you can learn

• Skin lipids and how they can be quantified
• Variability of healthy skin lipidome
• Lipids in skin diseases and disorders
• How lipidomics can be used in skin biology research and marketing claim support

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Failure of regeneration capacity limits the restoration of nervous system functionality in demyelinating diseases such as multiple sclerosis. Yet, the responsible mechanisms are only partially understood. I will present data supporting a key role for lipid metabolisms (that is, lipid droplet biogenesis and cholesterol efflux) in phagocytes for regeneration of myelin. Stimulation of the lipid sensing Triggering receptor expressed on myeloid cells or nuclear liver X receptor are possible therapeutic strategies of how to enhance the capacity to regenerate lesioned tissue.

Here is what you can learn

• Lipid metabolism in myelin regeneration
• Lipidomics in molecular neurobiology
• Neuroimmunological processes related to lipids

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The plasma membrane is the interface between a cell and its environment and is therefore responsible for a myriad of parallel processing tasks that must be tightly regulated to avoid aberrant signaling. To achieve this functional complexity, mammalian cells produce hundreds of lipid species that are actively turned over and trafficked to produce spatial and temporal gradients between cellular compartments. In addition to the plethora of regulatory roles performed by individual lipid molecules, membrane physiology is strictly dependent on the biophysical phenotypes – including membrane fluidity, rigidity, lipid packing, and lateral organization – arising from the collective behaviors of lipids.

Here, we will present the results of several projects that address the lipidomic, biophysical, and functional aspects of mammalian plasma membranes. These projects explore the relationship between membrane organization and cellular function, ultimately demonstrating that membrane phenotypes are central regulators of cell physiology.

Here is what you can learn

• The complexity of lipid species that give rise to intracellular gradients
• Lipidomic, biophysical, and functional aspects of plasma membranes
• The role of membrane phenotypes in regulation of cell physiology

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Today we are under threat not only from Covid-19 but another even worse pandemic is spreading worldwide and that is obesity, unhealthy weight. This disease does not only cause serious health problems globally but it can also lead to other diseases such as diabetes type 2, cardiovascular disease, liver disease, dementia and cancer. Obesity is driven by the consumption of processed foods, snacks, and soft drinks that are designed so that they even can become addictive. Metabolic parameters can long be maintained in a physiological range. However, once the metabolic overload has overwhelmed the homeostatic control systems, the damage leads to disease.

It is here that the lipids come into play. Lipid homeostasis is central to health. When lipid metabolism becomes dysfunctional, it can turn into a driver for the gamut of obesity-related complications. Amazingly, what is lacking are diagnostic tests that can recognize dysmetabolism before it turns into disease and becomes irreversible. The situation for obesity is like trying to combat Covid without an assay for the virus.

Most excitingly, our studies demonstrate that lipids could provide a means to monitor dysmetabolism. Plasma cholesterol and triglycerides have already proven their worth as useful biomarkers. When you add the complement of lipids in our lipidomes to the analysis, then the differentiation power becomes formidable. The fact that pathological changes occurring in our body organs seem to be mirrored in the blood lipidome could provide the basis for the diagnosis of dysmetabolism. Strangely neglected, lipid metabolism is now emerging as a research area with great potential.

Here is what you can learn

• What are the drivers of the obesity pandemic
• Lipid metabolism homeostasis as a key to dysmetabolism diagnostics
• Lipidomics analysis as a quick and reliable tool to monitor dysmetabolism

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Liquid biopsies (e.g. plasma or serum) is an available clinical resource extensively exploited by lipidomics. However, plasma lipidome changes reflect the diseases progressing elsewhere in different organs only indirectly. The direct analysis of tissue biopsies could be in a better position to elucidate molecular details of pathophysiological mechanisms.

Biopsies lipidomics requires careful standardization, the collection of abundant meta- and histological data together with robust normalization of lipid abundances. By providing absolute (molar) abundances of lipid species in whole biopsies, it creates a generic and expandable lipidomics resource. Furthermore, shotgun lipidomics could address spatial distribution of lipids by analyzing histological features isolated by laser capture microdissection (LCM). Combining the material from many similar features increases the lipidome coverage and enables to complement lipidomics with proteomics to confirm the dissection specificity by quantifying histologically specific markers.

Systematic shotgun analysis of whole and LCM-dissected liver, colon and pancreas biopsies suggested that, in general, tissues tend to preserve their lipid composition even when histological analyses indicate profound changes in their morphology. Significant lipidome perturbation are specific to a few individual species within spatially defined zones and offer new and often unexpected look at the pathophysiological role of lipid metabolism.

Here is what you can learn

• Handling of tissue biopsies for lipidomics analysis
• Lipidomics of histological features isolated by laser capture microdissection
• Lipidome perturbation within spatially defined zones of tissue biopsies

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The yeast Saccharomyces cerevisiae is a powerful model system for cell and molecular biology research. This is mostly due to the availability of simple and straightforward genetic and molecular tools and methods to manipulate almost any cell biological process.

Lipidomics has become an indispensable method for the quantitative assessment of lipid metabolism and membrane biology in studies employing yeast as an experimental system. Here we show how lipidomics is applied to investigate the influence of a variety of commonly used growth conditions on the yeast lipidome, including glycerophospholipids, triglycerides, ergosterol as well as complex sphingolipids, establishing a baseline for future lipidomic experiments in yeast.

Based on this work, we review acyl chain remodeling as a fundamental aspect of membrane biology, the roles of lipids in the unfolded protein response (UPR) in both endoplasmic reticulum (ER) and mitochondria, as well as the lipid-based regulation of key biological process like control of cell size and growth rate. These studies provide mechanistic insights into the amazing diversity of lipid functions in essential cellular processes conserved throughout the eukaryotic domain of life.

Here is what you can learn

• Lipidomic flexibility of yeast under various standard laboratory conditions
• Use of yeast lipidomics in understanding fundamental aspects of membrane biology
• The role of lipids in UPR and regulation of cell size and growth rate

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Lipidomics provide unprecedented phenotypic details by accumulating large amounts of data. While these are potentially of great value, the amount and complexity of the data can be intimidating initially.

This webinar is designed to show the basics of lipidomics analysis. It will cover the characteristics of the datasets, e.g. their lipid substructure and multicollinearity, and how to deal with them. We will go through data preparation, how to calculate new features and how to use principal component analysis as a first impression. Then we will focus on univariate and correlation analysis combined with enrichment analysis.

Here is what you can learn

• General properties of lipidomics datasets
• Data cleaning and generation of new features
• How to perform univariate analysis
• What is enrichment analysis and how is it applied

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In the past century, population health studies have proven a powerful approach to reveal connections between diseases and their risk factors in epidemiology. We have now moved into an era, in which population health studies frequently rely on omics technologies (such as genomics, transcriptomics, metabolomics, and lipidomics) to identify disease risk factors at the molecular level.

Omics technologies provide unprecedented phenotypic details by accumulating vast amounts of data. While these are potentially of enormous value, biomarker identification studies benefit only if the data are of high quality and reliably reproducible. Fortunately, shotgun lipidomics fulfills these requirements and can therefore successfully be applied in biomarker identification studies covering indications such as obesity, diabetes, cardiovascular, and neurodegenerative diseases. Most importantly, human plasma lipidomics seems to reflect the body metabolism and has the potential to fill a hole in clinical diagnostics that lacks methods to measure metabolism.

Besides revealing promising potential multiparametric diagnostic and prognostic markers, large population health studies have proven that lipidomics is a powerful approach to shed light on disease mechanisms or relationships between genotype and phenotype in studies run over several years and involving tens of thousands of participants.

Here is what you can learn

• Power of lipidomics in human biomarker studies
• Lipidomics combined with other omics technologies (multi-omics)
• Contribution to research on obesity, diabetes, CVD, neurodegeneration etc.
• Translational value of lipidomics biomarkers & challenges in diagnostics

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