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Metabolites
Special Issues
Lipidomics: Insights into Lipid Metabolism and OMICS Research
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Lipidomics: Insights into Lipid Metabolism and OMICS Research

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Lipid Metabolism".

Deadline for manuscript submissions: closed (15 June 2021) | Viewed by 4936

Special Issue Editor

Prof. Dr. Harald C. Köfeler

E-Mail Website
Guest Editor
Center for Medical Research (ZMF), Medical University of Graz, Stiftingtalstrasse 24, 8010 Graz, Austria
Interests: lipidomics; mass spectrometry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The emerging field of lipidomics is amongst the fastest-growing life science research fields of the recent decade. This is, on one hand, the result of an increasing awareness in the biomedical community that lipidomics was, in terms of its scientific and diagnostic potential, highly underrated for a long time, when compared to other ‘omics’ technologies. On the other hand, technological progress, in particular, mass spectrometry, has revealed functional details of the lipidome which were previously hardly conceivable. The merging of these occurrences has resulted in a flourishing atmosphere which attracts an ever-growing interest in this research field.

This Special Issue intends to adequately address the increasing scientific significance of lipidomics. In this context, we would like to invite lipidomics contributions for this Special Issue on a variety of related topics, from pure technological aspects to all kinds of life science applications.

Prof. Dr. Harald C. Köfeler
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (1 paper)

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Research

17 pages, 2574 KiB  
Article
Diagnostic Potential of the Plasma Lipidome in Infectious Disease: Application to Acute SARS-CoV-2 Infection
by Nicola Gray, Nathan G. Lawler, Annie Xu Zeng, Monique Ryan, Sze How Bong, Berin A. Boughton, Maider Bizkarguenaga, Chiara Bruzzone, Nieves Embade, Julien Wist, Elaine Holmes, Oscar Millet, Jeremy K. Nicholson and Luke Whiley
Metabolites 2021, 11(7), 467; https://doi.org/10.3390/metabo11070467 - 20 Jul 2021
Cited by 29 | Viewed by 4376
Abstract
Improved methods are required for investigating the systemic metabolic effects of SARS-CoV-2 infection and patient stratification for precision treatment. We aimed to develop an effective method using lipid profiles for discriminating between SARS-CoV-2 infection, healthy controls, and non-SARS-CoV-2 respiratory infections. Targeted liquid chromatography–mass [...] Read more.
Improved methods are required for investigating the systemic metabolic effects of SARS-CoV-2 infection and patient stratification for precision treatment. We aimed to develop an effective method using lipid profiles for discriminating between SARS-CoV-2 infection, healthy controls, and non-SARS-CoV-2 respiratory infections. Targeted liquid chromatography–mass spectrometry lipid profiling was performed on discovery (20 SARS-CoV-2-positive; 37 healthy controls; 22 COVID-19 symptoms but SARS-CoV-2negative) and validation (312 SARS-CoV-2-positive; 100 healthy controls) cohorts. Orthogonal projection to latent structure-discriminant analysis (OPLS-DA) and Kruskal–Wallis tests were applied to establish discriminant lipids, significance, and effect size, followed by logistic regression to evaluate classification performance. OPLS-DA reported separation of SARS-CoV-2 infection from healthy controls in the discovery cohort, with an area under the curve (AUC) of 1.000. A refined panel of discriminant features consisted of six lipids from different subclasses (PE, PC, LPC, HCER, CER, and DCER). Logistic regression in the discovery cohort returned a training ROC AUC of 1.000 (sensitivity = 1.000, specificity = 1.000) and a test ROC AUC of 1.000. The validation cohort produced a training ROC AUC of 0.977 (sensitivity = 0.855, specificity = 0.948) and a test ROC AUC of 0.978 (sensitivity = 0.948, specificity = 0.922). The lipid panel was also able to differentiate SARS-CoV-2-positive individuals from SARS-CoV-2-negative individuals with COVID-19-like symptoms (specificity = 0.818). Lipid profiling and multivariate modelling revealed a signature offering mechanistic insights into SARS-CoV-2, with strong predictive power, and the potential to facilitate effective diagnosis and clinical management. Full article
(This article belongs to the Special Issue Lipidomics: Insights into Lipid Metabolism and OMICS Research)
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