Introduction Liver damage caused by excessive alcohol consumption or a metabolic disorder can lead to serious diseases such as NAFLD, cirrhosis and liver cancer. Diagnosis often relies on biopsy, an invasive procedure that carries a major risk of complications, while current non-invasive biomarkers lack accuracy at an early stage. In this context, it is therefore essential to develop highly sensitive and minimally invasive diagnostic approaches. The goal of this study was to investigate proteome variation in plasma samples from patients with liver disease using both untargeted and targeted LC-MS/MS bottom-up proteomics and employing either DiscoveryEdgeTM 175 (ProteomEdge) and Nanotrap® Protein Enrichment Affinity Kits (CERES) technologies. Tear samples were also assessed and compared to plasma proteomic results.
Methods Plasma samples was processed using the DiscoveryEdge™ 175 (ProteomEdge) workflow and the Nanotrap® Protein Enrichment Affinity Kits (CERES). In the ProteomEdge workflow, neat plasma was digested with trypsin in a 96-well plate containing 175 heavy-labeled recombinant human protein fragments for absolute quantification. The CERES Nanotrap® workflow included enrichment of low-abundance proteins, followed by on-bead tryptic digestion. For tear samples, proteins underwent direct reduction, alkylation, and tryptic digestion. An EVOSEP One LC system coupled to a Sciex ZenoTOF 7600+ (QqTOF) was used under low-microflow conditions with a 44-minute gradient (SPD30 method) in data-independent acquisition mode (DIA-SWATH) for untargeted bottom-up proteomics. Protein identification and label-free quantification (LFQ) were performed using PEAKS software (Bioinformatics Solutions) and peak integrations verified with Sciex OS-Q.
Preliminary Data An initial set of plasma samples, with 4 healthy controls and 4 patients with late-stage liver disease (LD) were analyzed. Tear samples were analyzed (with healthy and LD patients, from a variety of disease stages). For protein identification and quantification, DIA-SWATH data was searched against the human reference proteome database and label-free quantification (LFQ) was performed, in PEAKS 13.0. Statistical analysis was performed in Markerview 3.0 (Sciex). In the untargeted analysis of plasma samples, ProteomEdge confidently identified and quantified 480 proteins (1% FDR), while CERES identified and quantified 1221 proteins, with approximately 64% of them being unique to the CERES workflow. LFQ data from ProteomEdge revealed 124 proteins significantly altered in the disease group compared to healthy controls, with 61 decreased and 63 increased. Absolute quantification was enabled with the ProteomEdge Discovery 175 kit due to the presence of isotopically labelled peptides produced through the digestion step. This workflow will be further assessed by targeted LC-MRMHR analysis based on isotopically matched peptide transitions. From the CERES workflow, 313 proteins were significantly affected, including 79 decreasing and 234 increasing. Untargeted tear proteomics identified 2,908 proteins, with 328 significantly altered in liver disease patients, including 22 upregulated ribosomal proteins. When comparing putative plasma biomarkers to those of tears, only 7 increased proteins were found in common between both matrices, when comparing the initial cohort of plasma samples. For decreased proteins, sixteen were shared across all three workflows, and three were shared between tears and plasma. The results obtained in this study show the potential of tears as an interesting alternative sample matrix for studying liver diseases. Comparison of results from tears with those from plasma samples revealed specific variations in both fluids, providing complementarity for biomarker detection. Results presented here will be further validated with a second cohort of patients.
