Project description:In this study, we evaluated the utility of proteomics to identify plasma proteins in healthy participants from a phase I clinical trial with IFNβ-1a and pegIFNβ-1a biologics to identify potential pharmacodynamic (PD) biomarkers. Using a linear mixed-effects model with repeated measurement for product-time interaction, we found that 248 and 528 analytes detected by the SOMAscan® assay were differentially expressed (p-value < 6.86E-06) between therapeutic doses of IFNβ-1a or pegIFNβ-1a, and placebo, respectively. We further prioritized signals based on peak change, area under the effect curve over the study duration, and overlap in signals from the two products. Analysis of prioritized datasets indicated activation of IFNB1 signaling and an IFNB signaling node with IL-6 as upstream regulators of the plasma protein patterns from both products. Increased TNF, IL-1B, IFNG, and IFNA signaling also occurred early in response to each product suggesting a direct link between each product and these upstream regulators. In summary, we identified longitudinal global PD changes in a large array of new and previously reported circulating proteins in healthy participants treated with IFNβ-1a and pegIFNβ-1a that may help identify novel single proteomic PD biomarkers and/or composite PD biomarker signatures as well as provide insight into the mechanism of action of these products. Independent replication is needed to confirm present proteomic results and to support further investigation of the identified candidate PD biomarkers for biosimilar product development.
Project description:Fatal COVID-19 is often complicated by hypoxemic respiratory failure and acute respiratory distress syndrome (ARDS). Mechanisms governing lung injury and repair in ARDS remain poorly understood because there are no biomarker-targeted therapeutics for patients with ARDS. We hypothesized that plasma proteomics may uncover unique biomarkers that correlate with disease severity in COVID-19 ARDS. We analyzed the circulating plasma proteome from 32 patients with ARDS and COVID-19 using an aptamer-based platform, which measures 7289 proteins, and correlated protein measurements with sequential organ failure assessment (SOFA) scores at 2 time points (Days 1 and 7 following ICU admission). We compared differential protein abundance and SOFA scores at each individual time point and identified 119 proteins at Day 1 and 46 proteins at Day 7 that correlated with patient SOFA scores. We modeled the relationship between dynamic protein abundance and changes in SOFA score between Days 1 and 7 and identified 39 proteins that significantly correlated with changes in SOFA score. Using Ingenuity Pathway Analysis, we identified increased ephrin signaling and acute phase response signaling correlated with increased SOFA scores over time, while pathways related to pulmonary fibrosis signaling and wound healing had an inverse relationship with SOFA scores between Days 1 and 7. These findings suggest that persistent inflammation may drive worsened disease severity, while repair processes correlate with improvements in organ dysfunction over time. This approach is generalizable to more diverse ARDS cohorts for identification of protein biomarkers and disease mechanisms as we strive towards targeted therapies in ARDS.
Project description:Background: Macrophage-based immune dysregulation plays a critical role in development of delayed gastric emptying in animal models of diabetes. Human studies have also revealed loss of anti-inflammatory macrophages and increased expression of genes associated with pro-inflammatory macrophages in full thickness gastric biopsies from gastroparesis patients. Aim: We aimed to determine broader protein expression (proteomics) and protein-based signaling pathways in full thickness gastric biopsies of diabetic (DG) and idiopathic gastroparesis (IG) patients. Additionally, we determined correlations between protein expressions, gastric emptying and symptoms. Methods: Full-thickness gastric antrum biopsies were obtained from nine DG, seven IG patients and five non-diabetic controls. Aptamer-based SomaLogic tissue scan that quantitatively identifies 1300 human proteins was used. Protein fold changes were computed, and differential expressions were calculated using Limma. Ingenuity Pathway Analysis and correlations were carried out. Multiple-testing corrected p-values <0.05 were considered statistically significant. Results: 73 proteins were differentially expressed in DG, 132 proteins in IG and 40 proteins were common to DG and IG. In both DG and IG, “Role of Macrophages, Fibroblasts and Endothelial Cells” was the most statistically significant altered pathway (DG FDR: 7.9x10-9; IG FDR: 6.3x10-12). In DG, properdin expression correlated with GCSI-bloating (r: -0.99, FDR: 0.02) and expressions of prostaglandin G/H synthase 2, protein kinase C zeta type and complement C2 correlated with 4 hr gastric retention (r: -0.97, FDR: 0.03 for all). No correlations were found between proteins and symptoms or gastric emptying in IG. Conclusions: Protein expression changes suggest a central role of macrophage-driven immune dysregulation and complement activation in gastroparesis.
Project description:Prokaryotes are, due to their moderate complexity, particularly amenable to the comprehensive identification of the protein repertoire expressed under different conditions. We applied a generic strategy to identify a complete expressed prokaryotic proteome, which is based on the analysis of RNA and proteins extracted from matched samples. Saturated transcriptome profiling by RNA-seq provided an endpoint estimate of the protein-coding genes expressed under two conditions which mimic the interaction of Bartonella henselae with its mammalian host. Directed shotgun proteomics experiments were carried out on four subcellular fractions. By specifically targeting proteins which are short, basic, low abundant and membrane localized, we could eliminate their initial under-representation compared to the estimated endpoint. A total of 1,250 proteins were identified with an estimated false discovery rate below 1%. This represents 85% of all distinct annotated proteins and around 90% of the expressed protein-coding genes. Genes, whose transcripts were detected, but not their corresponding protein products, were found highly enriched in several genomic islands. Additionally, genes that lacked an ortholog and a functional annotation were not detected at the protein level, and possibly include over-predicted genes in genome annotations. Furthermore, a dramatic membrane proteome re-organization was observed including differential regulation of autotransporters, adhesins and hemin binding proteins. Particularly noteworthy was the complete membrane proteome coverage which included expression of all members of the VirB/D4 type IV secretion system, a key virulence factor. Transcriptome and proteome analysis of B.henselae in two conditions and duplicates: uninduced and induced for host invasion.
Project description:Parkinson disease (PD) is a neurodegenerative disease characterized by the accumulation of alpha-synuclein (SNCA) and other proteins in aggregates termed âLewy Bodiesâ within neurons. PD has both genetic and environmental risk factors, and while processes leading to aberrant protein aggregation are unknown, past work points to abnormal levels of SNCA and other proteins. Although several genome-wide studies have been performed for PD, these have focused on DNA sequence variants by genome-wide association studies (GWAS) and on RNA levels (microarray transcriptomics), while genome-wide proteomics analysis has been lacking. After appropriate filters, proteomics identified 3,558 unique proteins and 283 of these (7.9%) were significantly different between PD and controls (q-value<0.05). RNA-sequencing identified 17,580 protein-coding genes and 1,095 of these (6.2%) were significantly different (FDR p-value<0.05), but only 166 of the FDR significant protein-coding genes (0.94%) were present among the 3,558 proteins characterized. Of these 166, eight genes (4.8%) were significant in both studies, with the same direction of effect. Functional enrichment analysis of the proteomics results strongly supports mitochondrial-related pathways, while comparable analysis of the RNA-sequencing results implicates protein folding pathways and metallothioneins. Ten of the implicated genes or proteins co-localized to GWAS loci. Evidence implicating SNCA was stronger in proteomics than in RNA-sequencing analyses. Notably, differentially expressed protein-coding genes were more likely to not be characterized in the proteomics analysis, which lessens the ability to compare across platforms. Combining multiple genome-wide platforms offers novel insights into the pathological processes responsible for this disease by identifying pathways implicated across methodologies. The study consists of mRNA-Seq (29 PD, 44 neurologically normal controls) and three-stage Mass Spectrometry Tandem Mass Tag Proteomics (12 PD, 12 neurologically normal controls) performed in post-mortem BA9 brain tissue. The proteomics samples are a subset of the RNA-Seq samples.