Lipidomics analysis of fasting serum identifies novel lipid biomarkers specific for HCV genotype 3 and genotype 1 chronic hepatitis C virus infection

Sheridan, David, Romero-Gomez, Manuel, Bridge, Simon, Crossey, Mary, Shawa, Isaac Thom, Neely, Dermot, Felmlee, Daniel J., Holmes, Elaine, Bassendine, Margaret and Taylor-Robinson, Simon (2015) Lipidomics analysis of fasting serum identifies novel lipid biomarkers specific for HCV genotype 3 and genotype 1 chronic hepatitis C virus infection. In: International Liver Congress 2015: 50th Annual Meeting of the European Association for the Study of the Liver, 22nd - 26th April 2015, Vienna, Austria.

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Abstract

Background and Aims: HCV genotype 3 (G3) is now considered the most difficult to treat genotype in the era of new oral direct acting antiviral (DAAs) drugs, particularly in those with advanced liver disease. HCV-G3 is also associated with more rapid progression to cirrhosis. Evidence suggests that HCV-G3 has different effects on lipid metabolism compared to HCV-G1, associated with hepatic steatosis, low LDL cholesterol and distinct interactions in the formation of lipoviral particles. A lipidomic analysis was performed to identify lipid species differentially regulated in HCV-G3 compared to HCV-G1, to gain further insight into genotype-specific metabolic pathways.

Methods: Lipidomic analysis was performed on fasting sera [N = 112 (73 G1, 39 G3); 25% cirrhosis] using a UPLC system coupled to a QToF mass spectrometer. Profiles were acquired in positive and negative ion modes. System suitability and stability was confirmed by injection of a quality control (QC) sample at regular intervals throughout the analytical run, prepared by combining equal aliquots of all the study samples. Data was pre-processed (alignment, noise filtering, normalisation) using XCMS and inhouse developed scripts, and subjected to multivariate statistical analysis using Simca-P. Principal component analysis (PCA) and orthogonal projection on latent structures-discriminant analysis (OPLS-DA) were performed on all data after pareto scaling.

Results: Spectra were explored by PCA for initial visualisation to detect inherent trends and outliers. Samples clustered based on the differences between the HCV-G1 and HCV-G3. Pairwise analysis using OPLS-DA allowed establishing the lipids with the strongest contribution to the genotype separation in positive ion mode. Preliminary assignment based on mass, fragmentation pattern and retention time of lipid species upregulated in HCV-G3 included Cholesteryl linoleate [M+NH4] 666.621 m/z @ 15.47 min. Other lipid species were specifically increased in HCV genotype 1 [M+H] 784.588 m/z @ 6.29 min PC (36:30). In negative ion mode, additional novel lipid species were found to be differentially unregulated in HCV-G1. The novel lipid species are currently being identified and evaluated in an independent validation cohort.

Conclusions: UPLC MS lipidomics methods identify novel lipid species differentially regulated in HCV-G3 compared to HCV-G1. Understanding of the lipidome in HCV-G3 may help identify factors associated with DAA relapse.

Item Type:	Conference or Workshop Item (Poster)
Subjects:	B900 Others in Subjects allied to Medicine C700 Molecular Biology, Biophysics and Biochemistry
Department:	Faculties > Health and Life Sciences > Applied Sciences
Depositing User:	Paul Burns
Date Deposited:	19 Jul 2019 10:06
Last Modified:	10 Oct 2019 16:48
URI:	http://nrl.northumbria.ac.uk/id/eprint/40093

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