Identification Of Plasma Biomarkers Research Articles

Identification of Plasma Biomarkers from Rheumatoid Arthritis Patients Using an Optimized Sequential Window Acquisition of All THeoretical Mass Spectra (SWATH) Proteomics Workflow.

Rheumatoid arthritis (RA) is a systemic autoimmune and inflammatory disease. Plasma biomarkers are critical for understanding disease mechanisms, treatment effects, and diagnosis. Mass spectrometry-based proteomics is a powerful tool for unbiased biomarker discovery. However, plasma proteomics is significantly hampered by signal interference from high-abundance proteins, low overall protein coverage, and high levels of missing data from data-dependent acquisition (DDA). To achieve quantitative proteomics analysis for plasma samples with a balance of throughput, performance, and cost, we developed a workflow incorporating plate-based high abundance protein depletion and sample preparation, comprehensive peptide spectral library building, and data-independent acquisition (DIA) SWATH mass spectrometry-based methodology. In this study, we analyzed plasma samples from both RA patients and healthy donors. The results showed that the new workflow performance exceeded that of the current state-of-the-art depletion-based plasma proteomic platforms in terms of both data quality and proteome coverage. Proteins from biological processes related to the activation of systemic inflammation, suppression of platelet function, and loss of muscle mass were enriched and differentially expressed in RA. Some plasma proteins, particularly acute-phase reactant proteins, showed great power to distinguish between RA patients and healthy donors. Moreover, protein isoforms in the plasma were also analyzed, providing even deeper proteome coverage. This workflow can serve as a basis for further application in discovering plasma biomarkers of other diseases.

Identification of Plasma Biomarkers in Drug-Naïve Schizophrenia Using Targeted Metabolomics.

Schizophrenia (SCZ) is a severe psychiatric disorder with unknown etiology and lacking specific biomarkers. Herein, we aimed to explore plasma biomarkers relevant to SCZ using targeted metabolomics. Sixty drug-naïve SCZ patients and 36 healthy controls were recruited. Psychotic symptoms were assessed using the Positive and Negative Syndrome Scale. We analyzed the levels of 271 metabolites in plasma samples from all subjects using targeted metabolomics, and identified metabolites that differed significantly between the two groups. Then we evaluated the diagnostic power of the metabolites based on receiver operating characteristic curves, and explored metabolites associated with the psychotic symptoms in SCZ patients. Twenty-six metabolites showed significant differences between SCZ patients and healthy controls. Among them, 12 metabolites were phosphatidylcholines and cortisol, ceramide (d18:1/22:0), acetylcarnitine, and γ-aminobutyric acid, which could significantly distinguish SCZ from healthy controls with the area under the curve (AUC) above 0.7. Further, a panel consisting of the above 4 metabolites had an excellent performance with an AUC of 0.867. In SCZ patients, phosphatidylcholines were positively related with positive symptoms, and cholic acid was positively associated with negative symptoms. Our study provides insights into the metabolite alterations associated with SCZ and potential biomarkers for its diagnosis and symptom severity assessment.

Biomarkers Associated with Thrombosis in Patients with Peripherally Inserted Central Catheter: A Systematic Review and Meta-Analysis.

The measurement and identification of plasma biomarkers can support the estimation of risk and diagnosis of deep vein thrombosis (DVT) associated with the use of a peripherally inserted central catheter (PICC). This systematic review and meta-analysis aimed to identify the association between the levels of potential biomarkers that reflect the activation of the blood system, long-term vascular complications, inflammatory system, and the occurrence of PICC-related DVT. Seven electronic databases (Embase, Web of Science, Medline, Scopus, Cinahl, Cochrane Central Register of Controlled Trials, and ERIC) were searched to identify literature published until December 2022. Studies were required to report: (I) adult and pediatric patients, outpatient or admitted to clinical, surgical, or ICU with PICC; (II) patients with PICC-related DVT and patients without PICC-related DVT as a comparator; and (III) at least one biomarker available. The Newcastle-Ottawa Scale was used to evaluate the quality of the studies. Study precision was evaluated by using a funnel plot for platelets level. We provided a narrative synthesis and meta-analysis of the findings on the biomarkers' outcomes of the studies. We pooled the results using random effects meta-analysis. The meta-analysis was conducted using Review Manager software v5.4. This systematic review is registered in PROSPERO (CRD42018108871). Of the 3564 studies identified (after duplication removal), 28 were included. PICC-related DVT was associated with higher D-dimers (0.37 μg/mL, 95% CI 0.02, 0.72; p = 0.04, I2 = 92%; p for heterogeneity < 0.00001) and with higher platelets (8.76 × 109/L, 95% CI 1.62, 15.91; p = 0.02, I2 = 41%; p for heterogeneity = 0.06). High levels of D-dimer and platelet were associated with DVT in patients with PICC. However, biomarkers such as APTT, fibrinogen, FDP, glucose, hemoglobin, glycated hemoglobin, INR, prothrombin time, prothrombin fragment 1.2, the thrombin-antithrombin complex, and WBC were not related to the development of DVT associated with PICC.

Identification of Plasma Biomarkers Involved in Regulation of Inflammatory Pain

Physicians are challenged in treating pain patients due to the lack of quantifiable, objective methods of measuring pain in the clinic; pain sensation is multifaceted and subjective to each individual. There is a critical need for point-of-care quantification of accessible biomarkers to provide objective analyses beyond the subjective pain scales currently employed in clinical care settings. In the present experiment, we employed an animal model to test the hypothesis that blood-born regulators of the inflammatory response directly associate with an objective behavioral response to inflammatory pain. Upon induction of localized paw inflammation, we measured various cytokines and matrix metalloproteinases (MMPs) that are known to participate in the inflammatory response and investigated their relationship to the behavioral response across a 24-hour period. Methods MaleSprague-Dawley rats (n=6/group) outfitted with indwelling jugular catheters were injected with 0.1 ml of saline or 0.1 ml of the pro-inflammatory compound λ-carrageenan (1%) into the left hindpaw. Quantification of carrageenan-evoked paw inflammation (paw thickness) and locomotor activity, as well as collection of blood (500 µl) for later biochemical analyses occurred 24 hrs prior to intraplantar injection (baseline) and at four timepoints post-injection (1-24 hrs). Plasma was aliquoted from each sample for detection of cytokines (BioPlex Rat Cytokine Panel) and MMPs. Results Intraplantar injection with 1% λ-carrageenan induced a significant increase in paw thickness across 24 hrs, with peak inflammation observed at 8 hrs (p<0.05 vs saline). Pearson's correlation analyses revealed that locomotor activity counts negatively correlated with paw inflammation at 8 hrs (r2=0.5645, p<0.05), demonstrating impaired locomotion at the peak of paw inflammation. Expression of the chemokines C-X-C motif chemokine ligand 1 (Gro KC) (r2=0.7061, p<0.05) and monocyte chemoattractant protein-1 (MCP-1) (r2=0.5050, p<0.05) positively correlated with paw inflammation and negatively correlated with locomotor activity at 8 hrs (Gro KC, r2=0.6386, p<0.05; MCP-1, r2=0.4150, p<0.05). The ratio of MMP9 to MMP2 activity negatively correlated with paw inflammation (r2=0.4759, p<0.05) at 8 hrs. No relationship between MMP9/MMP2 activity and locomotor activity was observed this timepoint. Interestingly, a mixed model ANOVA of the time course of MMP9/MMP2 activity revealed a significant increase at 1 hr (p<0.05 vs saline). Conclusions We postulate that the chemokines Gro KC and MCP-1 as well as the ratio of MMP9 to MMP2 activity may serve as predictive biomarkers for the timecourse of inflammation-associated behavioral deficits. These data define opportunities for the future development of a point-of-care device to objectively quantify biomarkers for inflammatory pain states.

Metabolomic profiling reveals novel biomarkers of alcohol intake and alcohol-induced liver injury in community-dwelling men.

ObjectiveMetabolomics is a promising approach to the identification of biomarkers in plasma. Here, we performed a population-based, cross-sectional study to identify potential biomarkers of alcohol intake and alcohol-induced liver injury by metabolomic profiling using capillary electrophoresis-mass spectrometry (CE-MS).MethodsFasting plasma samples were collected from 896 Japanese men who participated in the baseline survey of the Tsuruoka Metabolomics Cohort Study, and 115 polar metabolites were identified and absolutely quantified by CE-MS. Information on daily ethanol intake was collected through a standardized, self-administered questionnaire. The associations between ethanol intake and plasma concentration of metabolites were examined. Relationships between metabolite concentrations or their ratios and serum liver enzyme levels in the highest ethanol intake group (>46.0 g/day) were then examined by linear regression analysis. Replication analysis was conducted in 193 samples collected from independent population of this cohort.ResultsNineteen metabolites were identified to have an association with daily alcohol consumption both in the original and replication population. Three of these metabolites (threonine, glutamine, and guanidinosuccinate) were found to associate well with elevated levels of serum liver enzymes in the highest ethanol intake group, but not in the non-drinker group. We also found that the glutamate/glutamine ratio had a much stronger relation to serum γ-glutamyltransferase, aspartate transaminase, and alanine transaminase than glutamate or glutamine alone (standardized beta = 0.678, 0.558, 0.498, respectively).ConclusionsWe found 19 metabolites associated with alcohol intake, and three biomarker candidates (threonine, guanidinosuccinate and glutamine) of alcohol-induced liver injury. Glutamate/glutamine ratio might also be good biomarker.Electronic supplementary materialThe online version of this article (doi:10.1007/s12199-015-0494-y) contains supplementary material, which is available to authorized users.

The WAP Four-Disulfide Core Domain Protein HE4: A Novel Biomarker for Heart Failure

This study investigated clinical determinants and added prognostic value of HE4 as a biomarker not previously described in heart failure (HF). Identification of plasma biomarkers that help to risk stratify HF patients may help to improve treatment. Plasma HE4 levels were determined in 567 participants of the COACH (Coordinating study evaluating outcomes of Advising and Counseling in Heart failure). Patients had been hospitalized for HF and were followed for 18 months. The primary endpoint of this study was a composite of all-cause mortality and HF hospitalization. HE4 showed a strong correlation with HF severity, according to New York Heart Association functional class and brain natriuretic peptide (BNP) levels (p &lt; 0.001). HE4 also showed a positive correlation with GDF15 (p &lt; 0.001) and, in addition, correlated with kidney function (estimated glomerular filtration rate [eGFR]; p &lt; 0.001). Cox regression analysis revealed that a doubling of HE4 levels was associated with a hazard ratio (HR) of 1.73 (95% confidence interval [CI]: 1.53 to 1.95) for the primary outcome (p &lt; 0.001). After correction for age, gender, BNP, and eGFR, the HR was 1.46 (95% CI: 1.23 to 1.72; p &lt; 0.001), and after additional adjustment for GDF15, the HR lowered to 1.30 (95% CI: 1.07 to 1.59; p = 0.009). The area under the curve in the receiver-operating characteristic curve analysis increased from 0.727 to 0.752 when HE4 was included in the clinical evaluation (p = 0.051). The integrated discrimination improvement and net reclassification index for reclassification showed significant improvements when HE4 was added to the clinical model, and this remained significant after BNP inclusion in the model. HE4 plasma levels are correlated with markers of HF severity, show prognostic value, and can improve risk assessment in HF.

Identification of plasma biomarkers in human diabetic retinopathy

Identification of plasma biomarkers in human diabetic retinopathy

Abstract 18278: The Prognostic Value Of WFDC2, a New Biomarker for Heart Failure

Aim s: Identification of plasma biomarkers that help to stratify heart failure (HF) patients may help to improve treatment. We investigated the prognostic value of WAP four-disulfide core domain protein 2 (WFDC2, also termed HE4), a biomarker not previously described in HF. Methods: Data of 567 patients participating in the Coordinating study evaluating outcomes of Advising and Counselling in Heart failure (COACH) study were analysed. Patients had been hospitalized for HF and were followed for 18 months. Several plasma biomarker levels were determined using an ELISA platform. The primary endpoint of this study was a composite of all-cause mortality and HF hospitalization. Results: Mean age was 71±11 years, 62% were males, mean LVEF was 33±14%, and mean eGFR was 54±20 mL/minute. WFDC2 was identified as a biomarker that showed strong correlation with HF severity, according to NYHA functional class and BNP levels ( P &lt; 0.001). WFDC2 also showed a strong positive correlation with GDF15 ( P &lt;0.001). In addition, WFDC2 levels correlated with kidney function (BUN, creatinine, and eGFR; all P &lt;0.001). Cox regression analysis revealed that a doubling of WFDC2 levels was associated with a hazard ratio (HR) of 1.73 (1.53-1.95) for the primary outcome ( P &lt;0.001). After correction for age, gender, BNP and eGFR the HR was 1.46 (1.23-1.72) ( P &lt;0.001) and after additional adjustment for GDF15 the HR lowered to 1.30 (1.07-1.59) ( P =0.009). The AUC in the ROC curve analysis increased from 0.7123 to 0.7375 when WFDC2 was included to the clinical model ( P =0.068). The IDI and NRI metrics for reclassification showed highly significant improvements when WFDC2 was added to the clinical model (NRI=0.12, P &lt;0.001) and this remained significant after inclusion of BNP to this model. Conclusion: WFDC2 plasma levels are correlated with markers of HF severity, show prognostic value, and improve risk assessment in HF.

Proteomic identification of plasma biomarkers in type 2 diabetic nephropathy

Recent advances in quantitative proteomics have offered opportunities to discover plasma proteins as biomarkers for tracking the progression and for understanding the molecular mechanisms of diabetes. We used quantitative proteomic analysis to identify novel biomarkers of nephropathy in plasma from type 2 diabetic patients. Plasma samples were analyzed by fluorescence two-dimensional differential gel electrophoresis (2D-DIGE), and differentially expressed proteins identification was performed by matrix assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS). Proteomics analysis of the plasma proteome in type 2 diabetes mellitus with nephropathy identified 34 protein spots representing 31 unique proteins. These proteins mainly belonged to metabolic (such as 5'-AMP-activated protein kinase subunit beta-1) and growth regulatory (such as LIM homeobox protein 6) proteins. Additionally, our quantitative proteomic approach has identified numerous previous reported plasma markers of type 2 diabetes mellitus such as apolipoprotein A-I and ficolin-3. On the contrary, we have presented several putative type 2 diabetes mellitus biomarkers including calpain-7 and choline/ethanolamine kinase which have not been reported and may be associated with the progression and development of the disease. The potential of utilizing these markers for screening and treating type 2 diabetes mellitus warrants further investigation. Collectively, our results show that the proteins identified in this study may constitute potential biomarkers for the diagnosis of type 2 diabetics with nephropathy.

Biomarkers for optimal requirements of amino acids by animals and humans

Amino acids are building blocks of proteins and key regulators of nutrient metabolism in cells. However, excessive intake of amino acids can be toxic to the body. Therefore, it is important to precisely determine amino acid requirements by organisms. To date, none of the methods is completely satisfactory to generate comprehensive data on amino acid requirements of animals or humans. Because of many influencing factors, amino acid requirements remain a complex and controversial issue in nutrition that warrants further investigations. Benefiting from the rapid advances in the emerging omics technologies and bioinformatics, biomarker discovery shows great potential in obtaining in-depth understanding of regulatory networks in protein metabolism. This review summarizes the current approaches to assess amino acid requirements of animals and humans, as well as the recent development of biomarkers as potentially functional parameters for recommending requirements of individual amino acids in health and disease. Identification of biomarkers in plasma or serum, which is a noninvasive approach, holds great promise in rapidly advancing the field of protein nutrition.

Identification of plasma biomarkers that predict breast cancer bone metastasis

Identification of plasma biomarkers that predict breast cancer bone metastasis

A proteomic approach for identification of plasma biomarkers of Hepatocellular Carcinoma in The Gambia

A proteomic approach for identification of plasma biomarkers of Hepatocellular Carcinoma in The Gambia