Lipidomics unveils the complexity of the lipidome in metabolic diseases

Lydic, Todd A.; Goo, Young‐Hwa

doi:10.1186/s40169-018-0182-9

Cited by 124 publications

(105 citation statements)

References 99 publications

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“…The lipidome is a dynamic part of cells that will actively respond to changes in physiologic conditions [54,55]. The downstream effects of an altered lipidome, though, are complex and could potentially result in dysfunction or disease, or simply reflect a downstream effect of dysfunction or disease.…”

Section: Lipid Homeostasismentioning

confidence: 99%

An Integrative Overview of Non-Amyloid and Non-Tau Pathologies in Alzheimer’s Disease

Menta

Swerdlow

2018

Neurochem Res

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Alzheimer's disease (AD) is a neurodegenerative disease that devastates the lives of its victims, and challenges the family members and health care infrastructures that care for them. Clinically, attempts to understand AD have focused on trying to predict the presence of, and more recently demonstrate the presence of, its characteristic amyloid plaque and neurofibrillary tangle pathologies. Fundamental research has also traditionally focused on understanding the generation, content, and pathogenicity of plaques and tangles, but in addition to this there is now an emerging independent interest in other molecular phenomena including apolipoprotein E, lipid metabolism, neuroinflammation, and mitochondrial function. While studies emphasizing the role of these phenomena have provided valuable AD insights, it is interesting that at the molecular level these entities extensively intertwine and interact. In this review, we provide a brief overview of why apolipoprotein E, lipid metabolism, neuroinflammation, and mitochondrial research have become increasingly ascendant in the AD research field, and present the case for studying these phenomena from an integrated perspective.

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Section: Lipid Homeostasismentioning

confidence: 99%

An Integrative Overview of Non-Amyloid and Non-Tau Pathologies in Alzheimer’s Disease

Menta

Swerdlow

2018

Neurochem Res

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“…All animals were allowed 7 days of acclimatization. The room temperature was regulated at [22][23][24][25][26] C. 12 h diurnal cycles and access to standard rodent pellets and water were provided in pathogen-free cages. Aer environmental adaptation, 16 male Wistar rats were randomized into control (8 rats) or model (8 rats) groups.…”

Section: Animal Treatments and Sepsis Modelmentioning

confidence: 99%

“…26 First of all, although there have been many studies on lipids, there are no uniform and reliable standards for the method for extracting total lipids or various lipids from biological samples. Using different lipid preparation methods, the results of different research groups differ greatly which will result in differences in interpretation.…”

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confidence: 99%

Retracted Article: High performance liquid chromatography coupled with high resolution mass spectrometry-based characterization of lipidomic responses from rats with kidney injuries

Liu

et al. 2018

RSC Adv.

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a Metabolism of lipids is essential for the regulation of a variety of key cellular functions. Recent advances in high performance liquid chromatography coupled with high resolution mass spectrometry have expanded our knowledge of lipid metabolism in diseases. Currently, sepsis is one of the most important public health problems all over the world, which is a serious systemic inflammatory syndrome leading to infection by various agents or trauma and subsequently to a multiple organ dysfunction response. However, little is known about the lipids affected by sepsis and their roles in kidney injuries. In this study, we present targeted and non-targeted lipidomics strategies to discover the lipid metabolism variation in serum in rats with sepsis-induced kidney injuries. Liquid chromatography (LC) coupled with mass spectrometry (MS) and multivariate data analysis were used to obtain the global lipid metabolic profiles. In addition, biochemical parameters and histopathological examination results for the kidney were analyzed to support the pathological changes during sepsis-induced kidney injury. The identification of ten proposed lipids and five relevant pathways will promote a better understanding of lipid profile alterations in kidney injury. The results suggested that lipid metabolism in sepsis-induced kidney injury had changed significantly and contribute by offering potential targets for clinical diagnosis and therapy in the future, which would be worth further studies to broaden the applications of high performance liquid chromatography coupled with high resolution mass spectrometry in the study of lipid metabolism.

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“…By virtue of this structural and chemical diversity, which often confers amphipathic properties, seemingly every life process involves lipids, including but not limited to: maintenance of cellular structure (Singer and Nicolson, 1972); membrane fluidity (Clamp et al, 1997) (Chen and Yu, 1994); intracellular , extracellular, and hormonal signaling (Zechner et al, 2012) (Morrison and Farmer, 2000); energy metabolism (J R Neely and Morgan, 1974) (Adeva-Andany et al, 2018); and disease processes (De Pablo and De Cienfuegos, 2000) including cancer (Zhang and Du, 2012) (Ray and Roy, 2018). Thus, through lipidomics, more complete modeling of cellular metabolism and a better understanding of physiological and pathological processes at the mechanistic level can be achieved (Lydic and Goo, 2018).…”

Section: Introductionmentioning

confidence: 99%

Deriving Accurate Lipid Classification based on Molecular Formula

Mitchell

Moseley

2019

Preprint

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IntroductionAlthough Fourier-transform mass spectrometry has substantially improved our ability to detect lipids and other metabolites; the untargeted and accurate assignment of detected metabolites remains an unsolved problem in metabolomics. New assignment methods such as our SMIRFE algorithm can assign elemental molecular formula to observed spectral features in an untargeted manner without orthogonal information from tandem MS or chromatography. However, for many lipidomics applications, it is necessary to know at least the lipid category or class that is associated with a detected spectral feature in order to derive biochemical interpretation. ObjectivesOur goal is to develop a method for robustly classifying elemental molecular formula assignments into lipid categories for application to SMIRFE-generated assignments. ResultsUsing machine learning, we developed a method that can predict lipid category and class from SMIRFE molecular formula assignments. Our methods achieve high accuracy (>90%) and precision (>83%) for all eight of the lipid categories in the LIPIDMAPS database. Model performance was evaluated using sets of theoretical, data-derived, and artifactual molecular formulas. Our models were generalizable, applicable to real-world datasets, and very discriminating with most molecular formulas classified to the "not lipid" category. Lipid categories with the highest classification propensities were glycerophospholipids and sphingolipids, matching the highest category prevalence in LIPIDMAPS. ConclusionsOur methods enable the lipid classification of untargeted molecular formula assignments generated by SMIRFE without orthogonal information, facilitating biochemical interpretation of highly untargeted lipidomics experiments. However, this lipid classification appears insufficient for validating single-spectrum assignments, but could be useful in cross-spectrum assignment validation. Author ContributionsJMM designed and implemented the machine learning models and the convex hull analysis. HNBM designed the m/z shifted formula analysis and JMM implemented it.The primary manuscript writers were JMM and HNBM. Abstract:These pages contain supporting information including descriptions of the tissue samples from which the experimental set of formulas was derived, additional result tables for the machine learning models, and a figure showing the distribution of molecular formulas across our training datasets with respect to m/z.

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Lipidomics unveils the complexity of the lipidome in metabolic diseases

Cited by 124 publications

References 99 publications

An Integrative Overview of Non-Amyloid and Non-Tau Pathologies in Alzheimer’s Disease

An Integrative Overview of Non-Amyloid and Non-Tau Pathologies in Alzheimer’s Disease

Retracted Article: High performance liquid chromatography coupled with high resolution mass spectrometry-based characterization of lipidomic responses from rats with kidney injuries

Deriving Accurate Lipid Classification based on Molecular Formula

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