Detection of Cancer-Associated Gene Mutations in Urinary Cell-Free DNA among Prostate Cancer Patients in South Africa.

Prostate cancer (PCa) is the most common cause of cancer death among African men. The presence of tumor-specific variations in cell-free DNA (cfDNA), such as mutations, microsatellite instability, and DNA methylation, has been explored as a source of biomarkers for cancer diagnosis. In this study, we investigated the diagnostic role of cfDNA among South African PCa patients. We performed whole exome sequencing (WES) of urinary cfDNA. We identified a novel panel of 31 significantly deregulated somatic mutated genes between PCa and benign prostatic hyperplasia (BPH). Additionally, we performed whole-genome sequencing (WGS) on matching PCa and normal prostate tissue in an independent PCa cohort from South Africa. Our results suggest that the mutations are of germline origin as they were also found in the normal prostate tissue. In conclusion, our study contributes to the knowledge of cfDNA as a biomarker for diagnosing PCa in the South African population.

Aptamer-Based Proteomics Measuring Preoperative Cerebrospinal Fluid Protein Alterations Associated with Postoperative Delirium.

Delirium is a common postoperative complication among older patients with many adverse outcomes. Due to a lack of validated biomarkers, prediction and monitoring of delirium by biological testing is not currently feasible. Circulating proteins in cerebrospinal fluid (CSF) may reflect biological processes causing delirium. Our goal was to discover and investigate candidate protein biomarkers in preoperative CSF that were associated with the development of postoperative delirium in older surgical patients. We employed a nested case-control study design coupled with high multiplex affinity proteomics analysis to measure 1305 proteins in preoperative CSF. Twenty-four matched delirium cases and non-delirium controls were selected from the Healthier Postoperative Recovery (HiPOR) cohort, and the associations between preoperative protein levels and postoperative delirium were assessed using t-test statistics with further analysis by systems biology to elucidate delirium pathophysiology. Proteomics analysis identified 32 proteins in preoperative CSF that significantly associate with delirium (t-test p < 0.05). Due to the limited sample size, these proteins did not remain significant by multiple hypothesis testing using the Benjamini-Hochberg correction and q-value method. Three algorithms were applied to separate delirium cases from non-delirium controls. Hierarchical clustering classified 40/48 case-control samples correctly, and principal components analysis separated 43/48. The receiver operating characteristic curve yielded an area under the curve [95% confidence interval] of 0.91 [0.80-0.97]. Systems biology analysis identified several key pathways associated with risk of delirium: inflammation, immune cell migration, apoptosis, angiogenesis, synaptic depression and neuronal cell death. Proteomics analysis of preoperative CSF identified 32 proteins that might discriminate individuals who subsequently develop postoperative delirium from matched control samples. These proteins are potential candidate biomarkers for delirium and may play a role in its pathophysiology.

Potential of miRNAs in Plasma Extracellular Vesicle for the Stratification of Prostate Cancer in a South African Population.

Prostate cancer (PCa) is the most common cause of cancer death among African men. The analysis of microRNAs (miRNAs) in plasma extracellular vesicles (EVs) can be utilized as a non-invasive tool for the diagnosis of PCa. In this study, we used small RNA sequencing to profile miRNAs cargo in plasma EVs from South African PCa patients. We evaluated the differential expression of miRNAs between low and high Gleason scores in the plasma EVs of South African patients and in the prostatic tissue from data available in the Cancer Genome Atlas (TCGA) Data Portal. We identified 7 miRNAs differently expressed in both EVs and prostatic tissues. We evaluated their expression using qPCR in a larger cohort of 10 patients with benign prostatic hyperplasia (BPH) and 24 patients with PCa. Here, we reported that the ratio between two of these miRNAs (i.e., miR-194-5p/miR-16-5p) showed a higher concentration in PCa compared to BPH and in metastatic PCa compared to localized PCa. We explored for the first time the profiling of miRNAs cargo in plasma EVs as a tool for the identification of putative markers in the South African population. Our finding indicated the ratio miR-194-5p/miR-16-5p as a non-invasive marker for the evaluation of PCa aggressiveness in this population.

Integration of Meta-Multi-Omics Data Using Probabilistic Graphs and External Knowledge.

Multi-omics has the promise to provide a detailed molecular picture of biological systems. Although obtaining multi-omics data is relatively easy, methods that analyze such data have been lagging. In this paper, we present an algorithm that uses probabilistic graph representations and external knowledge to perform optimal structure learning and deduce a multifarious interaction network for multi-omics data from a bacterial community. Kefir grain, a microbial community that ferments milk and creates kefir, represents a self-renewing, stable, natural microbial community. Kefir has been shown to have a wide range of health benefits. We obtained a controlled bacterial community using the two most abundant and well-studied species in kefir grains: Lentilactobacillus kefiri and Lactobacillus kefiranofaciens. We applied growth temperatures of 30 °C and 37 °C and obtained transcriptomic, metabolomic, and proteomic data for the same 20 samples (10 samples per temperature). We obtained a multi-omics interaction network, which generated insights that would not have been possible with single-omics analysis. We identified interactions among transcripts, proteins, and metabolites, suggesting active toxin/antitoxin systems. We also observed multifarious interactions that involved the shikimate pathway. These observations helped explain bacterial adaptation to different stress conditions, co-aggregation, and increased activation of L. kefiranofaciens at 37 °C.

Patterns and Persistence of Perioperative Plasma and Cerebrospinal Fluid Neuroinflammatory Protein Biomarkers After Elective Orthopedic Surgery Using SOMAscan.

BACKGROUND: The neuroinflammatory response to surgery can be characterized by peripheral acute plasma protein changes in blood, but corresponding, persisting alterations in cerebrospinal fluid (CSF) proteins remain mostly unknown. Using the SOMAscan assay, we define acute and longer-term proteome changes associated with surgery in plasma and CSF. We hypothesized that biological pathways identified by these proteins would be in the categories of neuroinflammation and neuronal function and define neuroinflammatory proteome changes associated with surgery in older patients. METHODS: SOMAscan analyzed 1305 proteins in blood plasma (n = 14) and CSF (n = 15) samples from older patients enrolled in the Role of Inflammation after Surgery for Elders (RISE) study undergoing elective hip and knee replacement surgery with spinal anesthesia. Systems biology analysis identified biological pathways enriched among the surgery-associated differentially expressed proteins in plasma and CSF. RESULTS: Comparison of postoperative day 1 (POD1) to preoperative (PREOP) plasma protein levels identified 343 proteins with postsurgical changes ( P < .05; absolute value of the fold change [|FC|] > 1.2). Comparing postoperative 1-month (PO1MO) plasma and CSF with PREOP identified 67 proteins in plasma and 79 proteins in CSF with altered levels ( P < .05; |FC| > 1.2). In plasma, 21 proteins, primarily linked to immune response and inflammation, were similarly changed at POD1 and PO1MO. Comparison of plasma to CSF at PO1MO identified 8 shared proteins. Comparison of plasma at POD1 to CSF at PO1MO identified a larger number, 15 proteins in common, most of which are regulated by interleukin-6 (IL-6) or transforming growth factor beta-1 (TGFB1) and linked to the inflammatory response. Of the 79 CSF PO1MO-specific proteins, many are involved in neuronal function and neuroinflammation. CONCLUSIONS: SOMAscan can characterize both short- and long-term surgery-induced protein alterations in plasma and CSF. Acute plasma protein changes at POD1 parallel changes in PO1MO CSF and suggest 15 potential biomarkers for longer-term neuroinflammation that warrant further investigation.

Serum Protein Signatures Using Aptamer-Based Proteomics for Minimal Change Disease and Membranous Nephropathy.

Introduction: Minimal change disease (MCD) and membranous nephropathy (MN) are glomerular diseases (glomerulonephritis [GN]) that present with the nephrotic syndrome. Although circulating PLA2R antibodies have been validated as a biomarker for MN, the diagnosis of MCD and PLA2R-negative MN still relies on the results of kidney biopsy or empirical corticosteroids in children. We aimed to identify serum protein biomarker signatures associated with MCD and MN pathogenesis using aptamer-based proteomics. Methods: Quantitative SOMAscan proteomics was applied to the serum of adult patients with MCD (n = 15) and MN (n = 37) and healthy controls (n = 20). Associations between the 1305 proteins detected with SOMAscan were assessed using multiple statistical tests, expression pattern analysis, and systems biology analysis. Results: A total of 208 and 244 proteins were identified that differentiated MCD and MN, respectively, with high statistical significance from the healthy controls (Benjamin-Hochberg [BH] P < 0.0001). There were 157 proteins that discriminated MN from MCD (BH P < 0.05). In MCD, 65 proteins were differentially expressed as compared with MN and healthy controls. When compared with MCD and healthy controls, 44 discriminatory proteins were specifically linked to MN. Systems biology analysis of these signatures identified cell death and inflammation as key pathways differentiating MN from MCD and healthy controls. Dysregulation of fatty acid metabolism pathways was confirmed in both MN and MCD as compared with the healthy subjects. Conclusion: SOMAscan represents a promising proteomic platform for biomarker development in GN. Validation of a greater number of discovery biomarkers in larger patient cohorts is needed before these data can be translated for clinical care.

Proteome-Wide Analysis Using SOMAscan Identifies and Validates Chitinase-3-Like Protein 1 as a Risk and Disease Marker of Delirium Among Older Adults Undergoing Major Elective Surgery.

BACKGROUND: Delirium (an acute change in cognition) is a common, morbid, and costly syndrome seen primarily in aging adults. Despite increasing knowledge of its epidemiology, delirium remains a clinical diagnosis with no established biomarkers to guide diagnosis or management. Advances in proteomics now provide opportunities to identify novel markers of risk and disease progression for postoperative delirium and its associated long-term consequences (eg, long-term cognitive decline and Alzheimer's disease [AD]). METHODS: In a nested matched case-control study (18 delirium/no-delirium pairs) within the Successful Aging after Elective Surgery study (N = 556), we evaluated the association of 1305 plasma proteins preoperatively [PREOP] and on postoperative day 2 [POD2]) with delirium using SOMAscan. Generalized linear models were applied to enzyme-linked immunosorbant assay (ELISA) validation data of one protein across the full cohort. Multi-protein modeling included delirium biomarkers identified in prior work (C-reactive protein, interleukin-6 [IL6]). RESULTS: We identified chitinase-3-like-protein-1 (CHI3L1/YKL-40) as the sole delirium-associated protein in both a PREOP and a POD2 predictor model, a finding confirmed by ELISA. Multi-protein modeling found high PREOP CHI3L1/YKL-40 and POD2 IL6 increased the risk of delirium (relative risk [95% confidence interval] Quartile [Q]4 vs Q1: 2.4[1.2-5.0] and 2.1[1.1-4.1], respectively). CONCLUSIONS: Our identification of CHI3L1/YKL-40 in postoperative delirium parallels reports of CHI3L1/YKL-40 and its association with aging, mortality, and age-related conditions including AD onset and progression. This highlights the type 2 innate immune response, involving CHI3L1/YKL-40, as an underlying mechanism of postoperative delirium, a common, morbid, and costly syndrome that threatens the independence of older adults.

Identifying large-scale interaction atlases using probabilistic graphs and external knowledge.

Introduction: Reconstruction of gene interaction networks from experimental data provides a deep understanding of the underlying biological mechanisms. The noisy nature of the data and the large size of the network make this a very challenging task. Complex approaches handle the stochastic nature of the data but can only do this for small networks; simpler, linear models generate large networks but with less reliability. Methods: We propose a divide-and-conquer approach using probabilistic graph representations and external knowledge. We cluster the experimental data and learn an interaction network for each cluster, which are merged using the interaction network for the representative genes selected for each cluster. Results: We generated an interaction atlas for 337 human pathways yielding a network of 11,454 genes with 17,777 edges. Simulated gene expression data from this atlas formed the basis for reconstruction. Based on the area under the curve of the precision-recall curve, the proposed approach outperformed the baseline (random classifier) by ∼15-fold and conventional methods by ∼5-17-fold. The performance of the proposed workflow is significantly linked to the accuracy of the clustering step that tries to identify the modularity of the underlying biological mechanisms. Conclusions: We provide an interaction atlas generation workflow optimizing the algorithm/parameter selection. The proposed approach integrates external knowledge in the reconstruction of the interactome using probabilistic graphs. Network characterization and understanding long-range effects in interaction atlases provide means for comparative analysis with implications in biomarker discovery and therapeutic approaches. The proposed workflow is freely available at http://otulab.unl.edu/atlas.

KEGG2Net: Deducing gene interaction networks and acyclic graphs from KEGG pathways.

The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway database provides a manual curation of biological pathways that involve genes (or gene products), metabolites, chemical compounds, maps, and other entries. However, most applications and datasets involved in omics are gene or protein-centric requiring pathway representations that include direct and indirect interactions only between genes. Furthermore, special methodologies, such as Bayesian networks require acyclic representations of graphs. We developed KEGG2Net, a web resource that generates a network involving only the genes represented on a KEGG pathway with all of the direct and indirect gene-gene interactions deduced from the pathway. KEGG2Net offers four different methods to remove cycles from the resulting gene interaction network, converting them into directed acyclic graphs (DAGs). We generated synthetic gene expression data using the gene interaction networks deduced from the KEGG pathways and performed a comparative analysis of different cycle removal methods by testing the fitness of their DAGs to the data and by the number of edges they eliminate. Our results indicate that an ensemble method for cycle removal performs as the best approach to convert the gene interaction networks into DAGs. Resulting gene interaction networks and DAGs are represented in multiple user-friendly formats that can be used in other applications, and as images for quick and easy visualisation. The KEGG2Net web portal converts KEGG maps for any organism into gene-gene interaction networks and corresponding DAGS representing all of the direct and indirect interactions among the genes.

Targeted metabolomics analysis of postoperative delirium.

Postoperative delirium is the most common complication among older adults undergoing major surgery. The pathophysiology of delirium is poorly understood, and no blood-based, predictive markers are available. We characterized the plasma metabolome of 52 delirium cases and 52 matched controls from the Successful Aging after Elective Surgery (SAGES) cohort (N = 560) of patients ≥ 70 years old without dementia undergoing scheduled major non-cardiac surgery. We applied targeted mass spectrometry with internal standards and pooled controls using a nested matched case-control study preoperatively (PREOP) and on postoperative day 2 (POD2) to identify potential delirium risk and disease markers. Univariate analyses identified 37 PREOP and 53 POD2 metabolites associated with delirium and multivariate analyses achieved significant separation between the two groups with an 11-metabolite prediction model at PREOP (AUC = 83.80%). Systems biology analysis using the metabolites with differential concentrations rendered "valine, leucine, and isoleucine biosynthesis" at PREOP and "citrate cycle" at POD2 as the most significantly enriched pathways (false discovery rate < 0.05). Perturbations in energy metabolism and amino acid synthesis pathways may be associated with postoperative delirium and suggest potential mechanisms for delirium pathogenesis. Our results could lead to the development of a metabolomic delirium predictor.

Identification of Plasma Proteome Signatures Associated With Surgery Using SOMAscan.

OBJECTIVES: To characterize the proteomic signature of surgery in older adults and association with postoperative outcomes. SUMMARY OF BACKGROUND DATA: Circulating plasma proteins can reflect the physiological response to and clinical outcomes after surgery. METHODS: Blood plasma from older adults undergoing elective surgery was analyzed for 1305 proteins using SOMAscan. Surgery-associated proteins underwent Ingenuity Pathways Analysis. Selected surgery-associated proteins were independently validated using Luminex or enzyme-linked immunosorbent assay methods. Generalized linear models estimated correlations with postoperative outcomes. RESULTS: Plasma from a subcohort (n = 36) of the Successful Aging after Elective Surgery (SAGES) study was used for SOMAscan. Systems biology analysis of 110 proteins with Benjamini-Hochberg (BH) corrected P value ≤0.01 and an absolute foldchange (|FC|) ≥1.5 between postoperative day 2 (POD2) and preoperative (PREOP) identified functional pathways with major effects on pro-inflammatory proteins. Chitinase-3-like protein 1 (CHI3L1), C-reactive protein (CRP), and interleukin-6 (IL-6) were independently validated in separate validation cohorts from SAGES (n = 150 for CRP, IL-6; n = 126 for CHI3L1). Foldchange CHI3L1 and IL-6 were associated with increased postoperative complications [relative risk (RR) 1.50, 95% confidence interval (95% CI) 1.21-1.85 and RR 1.63, 95% CI 1.18-2.26, respectively], length of stay (RR 1.35, 95% CI 0.77-1.92 and RR 0.98, 95% CI 0.52-1.45), and risk of discharge to postacute facility (RR 1.15, 95% CI 1.04-1.26 and RR 1.11, 95% CI 1.04-1.18); POD2 and PREOP CRP difference was associated with discharge to postacute facility (RR 1.14, 95% CI 1.04-1.25). CONCLUSION: SOMAscan can identify novel and clinically relevant surgery-induced protein changes. Ultimately, proteomics may provide insights about pathways by which surgical stress contributes to postoperative outcomes.

Parenteral lipid emulsions induce unique ileal fatty acid and metabolomic profiles but do not increase the risk of necrotizing enterocolitis in preterm pigs.

Necrotizing enterocolitis (NEC) is a manifestation of maladaptive intestinal responses in preterm infants centrally medicated by unattenuated inflammation. Early in the postnatal period, preterm infants develop a deficit in arachidonic and docosahexaenoic acid, both potent regulators of inflammation. We hypothesized that the fatty acid composition of parenteral lipid emulsions uniquely induces blood and intestinal fatty acid profiles which, in turn, modifies the risk of NEC development. Forty-two preterm pigs were randomized to receive one of three lipid emulsions containing 100% soybean oil (SO), 15% fish oil (MO15), or 100% fish oil (FO100) with enteral feedings over an 8-day protocol. Blood and distal ileum tissue were collected for fatty acid analysis. The distal ileum underwent histologic, proteomic, and metabolomic analyses. Eight pigs [3/14 SO (21%), 3/14 MO15 (21%), and 2/14 FO100 (14%)] developed NEC. No differences in NEC risk were evident between groups despite differences in induced fatty acid profiles in blood and ileal tissue. Metabolomic analysis of NEC versus no NEC tissue revealed differences in tryptophan metabolism and arachidonic acid-containing glycerophospholipids. Proteomic analysis demonstrated no differences by lipid group; however, 15 proteins differentiated NEC versus no NEC in the domains of tissue injury, glucose uptake, and chemokine signaling. Exposure to parenteral lipid emulsions induces unique intestinal fatty acid and metabolomic profiles; however, these profiles are not linked to a difference in NEC development. Metabolomic and proteomic analyses of NEC versus no NEC intestinal tissue provide mechanistic insights into the pathogenesis of NEC in preterm infants.NEW & NOTEWORTHY Exposure to parenteral lipid emulsions induces unique intestinal fatty acid and metabolomic profiles; however, these profiles are not linked to a difference in NEC risk in preterm pigs. Metabolomic and proteomic analyses provide mechanistic insights into NEC pathogenesis. Compared with healthy ileal tissue, metabolites in tryptophan metabolism and arachidonic acid-containing glycerophospholipids are increased in NEC tissue. Proteomic analysis differentiates NEC versus no NEC in the domains of tissue injury, glucose uptake, and chemokine signaling.

Comparative analysis of single-cell transcriptomics in human and Zebrafish oocytes.

BACKGROUND: Zebrafish is a popular model organism, which is widely used in developmental biology research. Despite its general use, the direct comparison of the zebrafish and human oocyte transcriptomes has not been well studied. It is significant to see if the similarity observed between the two organisms at the gene sequence level is also observed at the expression level in key cell types such as the oocyte. RESULTS: We performed single-cell RNA-seq of the zebrafish oocyte and compared it with two studies that have performed single-cell RNA-seq of the human oocyte. We carried out a comparative analysis of genes expressed in the oocyte and genes highly expressed in the oocyte across the three studies. Overall, we found high consistency between the human studies and high concordance in expression for the orthologous genes in the two organisms. According to the Ensembl database, about 60% of the human protein coding genes are orthologous to the zebrafish genes. Our results showed that a higher percentage of the genes that are highly expressed in both organisms show orthology compared to the lower expressed genes. Systems biology analysis of the genes highly expressed in the three studies showed significant overlap of the enriched pathways and GO terms. Moreover, orthologous genes that are commonly overexpressed in both organisms were involved in biological mechanisms that are functionally essential to the oocyte. CONCLUSIONS: Orthologous genes are concurrently highly expressed in the oocytes of the two organisms and these genes belong to similar functional categories. Our results provide evidence that zebrafish could serve as a valid model organism to study the oocyte with direct implications in human.

Cdc42-Dependent Transfer of mir301 from Breast Cancer-Derived Extracellular Vesicles Regulates the Matrix Modulating Ability of Astrocytes at the Blood-Brain Barrier.

Breast cancer brain metastasis is a major clinical challenge and is associated with a dismal prognosis. Understanding the mechanisms underlying the early stages of brain metastasis can provide opportunities to develop efficient diagnostics and therapeutics for this significant clinical challenge. We have previously reported that breast cancer-derived extracellular vesicles (EVs) breach the blood-brain barrier (BBB) via transcytosis and can promote brain metastasis. Here, we elucidate the functional consequences of EV transport across the BBB. We demonstrate that brain metastasis-promoting EVs can be internalized by astrocytes and modulate the behavior of these cells to promote extracellular matrix remodeling in vivo. We have identified protein and miRNA signatures in these EVs that can lead to the interaction of EVs with astrocytes and, as such, have the potential to serve as targets for development of diagnostics and therapeutics for early detection and therapeutic intervention in breast cancer brain metastasis.

Placenta accreta spectrum: biomarker discovery using plasma proteomics.

BACKGROUND: Many cases of placenta accreta spectrum are not diagnosed antenatally, despite identified risk factors and improved imaging methods. Identification of plasma protein biomarkers could further improve the antenatal diagnosis of placenta accreta spectrum . OBJECTIVE: The purpose of this study was to determine if women with placenta accreta spectrum have a distinct plasma protein profile compared with control subjects. STUDY DESIGN: We obtained plasma samples before delivery from 16 participants with placenta accreta spectrum and 10 control subjects with similar gestational ages (35.1 vs 35.5 weeks gestation, respectively). We analyzed plasma samples with an aptamer-based proteomics platform for alterations in 1305 unique proteins. Heat maps of the most differentially expressed proteins (T test, P<.01) were generated with matrix visualization and analysis software. Principal component analysis was performed with the use of all 1305 proteins and the top 21 dysregulated proteins. We then confirmed dysregulated proteins using enzyme-linked immunosorbent assay and report significant differences between placenta accreta spectrum and control cases (Wilcoxon-rank sum test, P<.05). RESULTS: Many of the top 50 proteins that significantly dysregulated in participants with placenta accreta spectrum were inflammatory cytokines, factors that regulate vascular remodeling, and extracellular matrix proteins that regulate invasion. Placenta accreta spectrum, with the use of the top 21 proteins, distinctly separated the placenta accreta spectrum cases from control cases (P<.01). Using enzyme-linked immunosorbent assay, we confirmed 4 proteins that were dysregulated in placenta accreta spectrum compared with control cases: median antithrombin III concentrations (240.4 vs 150.3 mg/mL; P=.002), median plasminogen activator inhibitor 1 concentrations (4.1 vs 7.1 ng/mL; P<.001), soluble Tie2 (13.5 vs 10.4 ng/mL; P=.02), soluble vascular endothelial growth factor receptor 2 (9.0 vs 5.9 ng/mL; P=.003). CONCLUSION: Participants with placenta accreta spectrum had a unique and distinct plasma protein signature.

Unexpected effects of systemic steroids on the CRSwNP proteome: is protein upregulation more important than inhibition?

BACKGROUND: Oral steroids, traditionally thought of as immunosuppressive agents that are broad in their immunomodulatory effects, are a mainstay of treatment to reduce disease burden in chronic rhinosinusitis with nasal polyps (CRSwNP). The purpose of this study was to determine how differentially expressed proteins in CRSwNP are affected by oral steroid therapy. METHODS: Matched exosomal proteomic arrays were quantified using aptamer-based methods in systemic steroid-naive CRSwNP patients before and after a standardized oral prednisone course (n = 12). Previously identified differentially expressed proteins in CRSwNP patients were compared to determine the effect of steroids on expression. Fisher's exact test and t test were applied to normalized protein expression profiles to determine significance. RESULTS: Of 18 proteins previously identified to be highly underexpressed in CRSwNP, 16 (89%) had an average increase after systemic steroid treatment (p < 0.05). Lactoperoxidase, initially present at 9-fold lower concentrations in CRSwNP subjects, increased by 209% after steroid treatment. A similar trend was observed with other proteins of interest, including platelet factor 4 and C-C motif ligand 28. The converse of this steroid effect was not true; of the 53 proteins that are highly overexpressed in CRSwNP, only 22 (42%) decreased in quantity with steroid use. CONCLUSION: Proteomic analysis of differentially expressed proteins in CRSwNP demonstrates that systemic steroids cause almost uniform upregulation of transcriptionally decreased proteins, whereas the effects of steroids on transcriptionally increased proteins are more heterogeneous. Thus, proteomic analysis may be an effective tool to understand specific therapeutic benefits of steroid use in polyp disease and to create more targeted treatments.

FQStat: a parallel architecture for very high-speed assessment of sequencing quality metrics.

BACKGROUND: High throughput DNA/RNA sequencing has revolutionized biological and clinical research. Sequencing is widely used, and generates very large amounts of data, mainly due to reduced cost and advanced technologies. Quickly assessing the quality of giga-to-tera base levels of sequencing data has become a routine but important task. Identification and elimination of low-quality sequence data is crucial for reliability of downstream analysis results. There is a need for a high-speed tool that uses optimized parallel programming for batch processing and simply gauges the quality of sequencing data from multiple datasets independent of any other processing steps. RESULTS: FQStat is a stand-alone, platform-independent software tool that assesses the quality of FASTQ files using parallel programming. Based on the machine architecture and input data, FQStat automatically determines the number of cores and the amount of memory to be allocated per file for optimum performance. Our results indicate that in a core-limited case, core assignment overhead exceeds the benefit of additional cores. In a core-unlimited case, there is a saturation point reached in performance by increasingly assigning additional cores per file. We also show that memory allocation per file has a lower priority in performance when compared to the allocation of cores. FQStat's output is summarized in HTML web page, tab-delimited text file, and high-resolution image formats. FQStat calculates and plots read count, read length, quality score, and high-quality base statistics. FQStat identifies and marks low-quality sequencing data to suggest removal from downstream analysis. We applied FQStat on real sequencing data to optimize performance and to demonstrate its capabilities. We also compared FQStat's performance to similar quality control (QC) tools that utilize parallel programming and attained improvements in run time. CONCLUSIONS: FQStat is a user-friendly tool with a graphical interface that employs a parallel programming architecture and automatically optimizes its performance to generate quality control statistics for sequencing data. Unlike existing tools, these statistics are calculated for multiple datasets and separately at the "lane," "sample," and "experiment" level to identify subsets of the samples with low quality, thereby preventing the loss of complete samples when reliable data can still be obtained.

Neutrophil activation in systemic capillary leak syndrome (Clarkson disease).

Systemic capillary leak syndrome (SCLS; Clarkson disease) is a rare orphan disorder characterized by transient yet recurrent episodes of hypotension and peripheral oedema due to diffuse vascular leakage of fluids and proteins into soft tissues. Humoral mediators, cellular responses and genetic features accounting for the clinical phenotype of SCLS are virtually unknown. Here, we searched for factors altered in acute SCLS plasma relative to matched convalescent samples using multiplexed aptamer-based proteomic screening. Relative amounts of 612 proteins were changed greater than twofold and 81 proteins were changed at least threefold. Among the most enriched proteins in acute SCLS plasma were neutrophil granule components including bactericidal permeability inducing protein, myeloperoxidase and matrix metalloproteinase 8. Neutrophils isolated from blood of subjects with SCLS or healthy controls responded similarly to routine pro-inflammatory mediators. However, acute SCLS sera activated neutrophils relative to remission sera. Activated neutrophil supernatants increased permeability of endothelial cells from both controls and SCLS subjects equivalently. Our results suggest systemic neutrophil degranulation during SCLS acute flares, which may contribute to the clinical manifestations of acute vascular leak.

Translating transcription: proteomics in chronic rhinosinusitis with nasal polyps reveals significant discordance with messenger RNA expression.

BACKGROUND: Much of the literature examining chronic rhinosinusitis with nasal polyps (CRSwNP) immunopathology has been predicated on messenger RNA (mRNA) analysis with the assumption that transcriptional changes would reflect end-effector protein expression. The purpose of this study was to test this hypothesis using matched transcriptomic and proteomic data sets. METHODS: Matched tissue proteomic and transcriptomic arrays were quantified in CRSwNP polyp tissue and control inferior turbinate tissue (n = 10/group). Mucus samples were additionally collected in 6 subjects from each group. Proteins were grouped into functional categories by bioinformatics and differential expression analyses. Log-log regression and Pearson correlations were performed to determine the level of agreement between data sets. RESULTS: Of the 1310 proteins examined, 393 were significantly differentially expressed in CRSwNP. On regression analysis, differences in protein expression were poorly predicted by differences in mRNA expression (R2 = 0.020, p < 0.05). Several genes canonically thought to be overexpressed in CRSwNP, including IL-5, IL-13, TSLP, CCL13, and CCL26, showed substantial increases in mRNA transcription, but had minimally or unchanged protein expression. Others, including IgE, periostin, CCL18, and CST1/2, were increased at both the transcriptomic and proteomic levels. Among differentially regulated proteins, tissue and mucus protein levels showed weak correlation (r = 0.26, p < 0.0001). CONCLUSION: Proteomic analysis in CRSwNP has revealed novel disease-associated proteins and pathways, yet correlates poorly with transcriptomic data. The increasing availability of proteomic arrays opens the door to new potential explanatory mechanisms in CRSwNP and suggests that mRNA based studies should be validated with protein analysis.

Development of a Dynamic Multi-Protein Signature of Postoperative Delirium.

Background: Delirium is common, morbid, and costly, yet its biology is poorly understood. We aimed to develop a multi-protein signature of delirium by identifying proteins associated with delirium from unbiased proteomics and combining them with delirium biomarkers identified in our prior work (interleukin [IL]-6 and IL-2). Methods: We used the Successful Aging after Elective Surgery (SAGES) Study of adults age ≥70 undergoing major noncardiac surgery (N = 560; 24% delirium). Plasma was collected preoperatively (PREOP) and on postoperative day 2 (POD2). In a nested matched case-control study involving 12 pairs of delirium cases and no-delirium controls, isobaric tags for relative and absolute quantitation-based (iTRAQ) mass spectrometry proteomics was applied to identify the top set of delirium-related proteins. With these proteins, we then conducted enzyme-linked immunosorbent assay (ELISA) confirmation, and if confirmed, ELISA validation in 75 matched pairs. Multi-marker conditional logistic regression was used to select the "best" PREOP and POD2 models for delirium. Results: We identified three proteins from iTRAQ: C-reactive protein (CRP), zinc alpha-2 glycoprotein (AZGP1), and alpha-1 antichymotrypsin (SERPINA3). The "best" multi-protein models of delirium included: PREOP: CRP and AZGP1 (Bayesian information criteria [BIC]: 93.82, c-statistic: 0.77); and POD2: IL-6, IL-2, and CRP (BIC: 87.11, c-statistic: 0.84). Conclusion: The signature of postoperative delirium is dynamic, with some proteins important before surgery (risk markers) and others at the time of delirium (disease markers). Our dynamic, multi-protein signature for delirium improves our understanding of delirium pathophysiology and may identify patients at-risk of this devastating disorder that threatens independence of older adults.