Potential Peripheral Blood Biomarkers Research Articles

Characterization of lncRNA-associated ceRNA network to uncover novel potential biomarkers in coronary artery disease.

The purpose of this study was to construct a competitive endogenous RNA (ceRNA) network related to long non-coding RNA (lncRNAs) via the bioinformatics analysis, reveal the pathogenesis of coronary heart disease (CAD) and develop new biomarkers for CAD. The gene expression datasets of peripheral blood of CAD were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed mRNAs, miRNAs and lncRNAs (DEmRNAs, DEmiRNAs and DElncRNAs) were identified. Subsequently, a ceRNA network involving lncRNAs, miRNAs, and mRNAs was built. Moreover, DElncRNAs in the cytoplasm were screened and a DElncRNA-associated ceRNA network was established. In total, 1860 DEmRNAs, 393 DElncRNAs and 20 DEmiRNAs were filtrated in patients with CAD compared with normal controls. Functional analysis suggested that DEmRNAs significantly enriched in CAD-related pathways, such as PI3K-Akt signaling pathways and MAPK signaling pathway. The ceRNA network contained 12 DEmiRNAs, 30 DElncRNAs and 537 DEmRNAs. Afterwards, the cytoplasm ceRNA network was consisted of 537 DEmRNAs, 12 DEmiRNAs and 12 DElncRNAs. Such as, up-regulated LncRNA-HOX transcript antisense RNA (HOTAIR) was interacted with down-regulated has-miR-326 and has-miR-1. The successful construction of lncRNA-associated ceRNA network is helpful to better clarify the pathogenesis of CAD and provide potential peripheral blood biomarkers for CAD.

Aberrantly Expressed Hsa_circ_0060762 and CSE1L as Potential Peripheral Blood Biomarkers for ALS.

Amyotrophic lateral sclerosis (ALS) is a rapidly progressive adult-onset neurodegenerative disease that is often diagnosed with a delay due to initial non-specific symptoms. Therefore, reliable and easy-to-obtain biomarkers are an absolute necessity for earlier and more accurate diagnostics. Circular RNAs (circRNAs) have already been proposed as potential biomarkers for several neurodegenerative diseases. In this study, we further investigated the usefulness of circRNAs as potential biomarkers for ALS. We first performed a microarray analysis of circRNAs on peripheral blood mononuclear cells of a subset of ALS patients and controls. Among the differently expressed circRNA by microarray analysis, we selected only the ones with a host gene that harbors the highest level of conservation and genetic constraints. This selection was based on the hypothesis that genes under selective pressure and genetic constraints could have a major role in determining a trait or disease. Then we performed a linear regression between ALS cases and controls using each circRNA as a predictor variable. With a False Discovery Rate (FDR) threshold of 0.1, only six circRNAs passed the filtering and only one of them remained statistically significant after Bonferroni correction: hsa_circ_0060762 and its host gene CSE1L. Finally, we observed a significant difference in expression levels between larger sets of patients and healthy controls for both hsa_circ_0060762 and CSE1L. CSE1L is a member of the importin β family and mediates inhibition of TDP-43 aggregation; the central pathogenicity in ALS and hsa_circ_0060762 has binding sites for several miRNAs that have been already proposed as biomarkers for ALS. In addition, receiver operating characteristics curve analysis showed diagnostic potential for CSE1L and hsa_circ_0060762. Hsa_circ_0060762 and CSE1L thus represent novel potential peripheral blood biomarkers and therapeutic targets for ALS.

Abstract 5454: Peripheral blood biomarkers in Phase II study of pembrolizumab in combination with oral binimetinib in patients with unresectable locally advanced or metastatic triple-negative breast cancer

Abstract Background: Activation of the RAS/MAPK pathway is associated with reduced tumor-infiltrating lymphocytes and poor outcomes in triple-negative breast cancer (TNBC). This trial evaluated the efficacy of pembrolizumab and MEK inhibitor, binimetinib. Here we evaluated potential biomarkers in peripheral blood to predict response. Methods: Patients with unresectable locally advanced or metastatic TNBC with ≤ 3 prior lines of therapy were enrolled. Treatment includes a 2-week run-in with binimetinib followed by pembrolizumab. There were 2 dose levels (DL) with binimetinib at 45 mg at DL 0 and 30 mg at DL -1. A standard 3+3 design was used in phase I, and Simon’s two-stage Optimal design was used in phase II. Circulating tumor cells (CTC) and circulating cancer-associated macrophage-like cells (CAML) were isolated using CellSieve microfilters and immunofluorescently labeled with PD-L1 and p-ERK. Wilcoxon rank sum test and Cox regression model were used for analysis. Results: A total of 22 patients were enrolled, with a median age of 58 years old. Dose-limiting toxicity (DLT) was observed in 2 out of 4 patients in DL 0, with grade 3 ALT abnormality, flank pain, and nausea. In the next 6 patients in DL -1, there was 1 DLT with grade 3 AST/ALT abnormality. There were 17 patients treated with DL -1 and were evaluable for response. The objective response rate (ORR) was 29.41% (95% CI: 10.31-55.9) with 1 complete response (CR) and 4 partial responses (PR). The clinical benefit rate (CBR ≥ 24 weeks) was 35.29% (95% CI: 14.21-61.67). ORR in patients without liver metastases was 55.56% (95% CI: 21.20 - 86.30), and CBR was 66.67% (95% CI: 29.93-92.51). There was no response observed in all 5 patients with liver metastases. Baseline mean CTC count was 1.3 cells, and CAML count was 8.9 cells/7.5 mL. Baseline PD-L1 in CAML (p 0.04) and decline in CAML size (p 0.02) after 1 cycle were significantly associated with CBR. However, baseline CTC count, CAML count (p 0.64), CAML size (p 0.46), p-ERK in CAML (p 0.23), and changes in CTC count, CAML count (p 0.83), p-ERK (p 0.07), and PD-L1 (p 0.08) in CAML were not significantly associated with responses. Using Cox regression analysis, a reduction in CAML count (p 0.02), CAML size (p 0.01), and PD-L1 in CAML (p 0.03) were associated with significant improvement in overall survival but not the reduction in p-ERK (p 0.6). Conclusions: Pembrolizumab and binimetinib at 30 mg are safe with manageable toxicities. Promising activity was observed in patients without liver metastases. Baseline PD-L1 expression, early reduction in CAML count, size, and PD-L1 expression were significantly associated with subsequent responses, providing potential noninvasive biomarkers to predict response to this combination. Future larger clinical trials are warranted to further evaluate the efficacy of this combination. Citation Format: Saranya Chumsri, Joseph J. Larson, Daniel L. Adams, Kathleen S. Tenner, Cha-Mei Tang, Morgan T. Weidner, Amanda N. Arnold, Dana L. Haley, Pooja Advani, Kostandinos Sideras, Alvaro Moreno-aspitia, Edith A. Perez, Keith L. Knutson. Peripheral blood biomarkers in Phase II study of pembrolizumab in combination with oral binimetinib in patients with unresectable locally advanced or metastatic triple-negative breast cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5454.

Shared peripheral blood biomarkers for Alzheimer’s disease, major depressive disorder, and type 2 diabetes and cognitive risk factor analysis

BackgroundAlzheimer's disease (AD), type 2 diabetes mellitus (T2DM), and Major Depressive Disorder (MDD) have a higher incidence rate in modern society. Although increasing evidence supports close associations between the three, the mechanisms underlying their interrelationships remain elucidated. ObjectiveThe primary purpose is to explore the shared pathogenesis and the potential peripheral blood biomarkers for AD, MDD, and T2DM. MethodsWe downloaded the microarray data of AD, MDD, and T2DM from the Gene Expression Omnibus database and constructed co-expression networks by Weighted Gene Co-Expression Network Analysis to identify differentially expressed genes. We took the intersection of differentially expressed genes to obtain co-DEGs. Then, we performed GO and KEGG enrichment analysis on the common genes in the AD, MDD, and T2DM-related modules. Next, we utilized the STRING database to find the hub genes in the protein-protein interaction network. ROC curves were constructed for co-DEGs to obtain the most diagnostic valuable genes and to make drug predictions against the target genes. Finally, we conducted a present condition survey to verify the correlation between T2DM, MDD and AD. ResultsOur findings indicated 127 diff co-DEGs, 19 upregulated co-DEGs, and 25 down-regulated co-DEGs. Functional enrichment analysis showed co-DEGs were mainly enriched in signaling pathways such as metabolic diseases and some neurodegeneration. Protein-protein interaction network construction identified hub genes in AD, MDD and T2DM shared genes. We identified seven hub genes of co-DEGs, namely, SMC4, CDC27, HNF1A, RHOD, CUX1, PDLIM5, and TTR. The current survey results suggest a correlation between T2DM, MDD and dementia. Moreover, logistic regression analysis showed that T2DM and depression increased the risk of dementia. ConclusionOur work identified common pathogenesis of AD, T2DM, and MDD. These shared pathways might provide novel ideas for further mechanistic studies and hub genes that may serve as novel therapeutic targets for diagnosing and treating.

C1QC, VSIG4, and CFD as Potential Peripheral Blood Biomarkers in Atrial Fibrillation-Related Cardioembolic Stroke.

Atrial fibrillation (AF) is a major risk factor for ischemic stroke. We aimed to identify novel potential biomarkers with diagnostic value in patients with atrial fibrillation-related cardioembolic stroke (AF-CE).Publicly available gene expression profiles related to AF, cardioembolic stroke (CE), and large artery atherosclerosis (LAA) were downloaded from the Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) were identified and then functionally annotated. The support vector machine recursive feature elimination (SVM-RFE) and least absolute shrinkage and selection operator (LASSO) regression analysis were conducted to identify potential diagnostic AF-CE biomarkers. Furthermore, the results were validated by using external data sets, and discriminability was measured by the area under the ROC curve (AUC). In order to verify the predictive results, the blood samples of 13 healthy controls, 20 patients with CE, and 20 patients with LAA stroke were acquired for RT-qPCR, and the correlation between biomarkers and clinical features was further explored. Lastly, a nomogram and the companion website were developed to predict the CE-risk rate. Three feature genes (C1QC, VSIG4, and CFD) were selected and validated in the training and the external datasets. The qRT-PCR evaluation showed that the levels of blood biomarkers (C1QC, VSIG4, and CFD) in patients with AF-CE can be used to differentiate patients with AF-CE from normal controls (P < 0.05) and can effectively discriminate AF-CE from LAA stroke (P < 0.05). Immune cell infiltration analysis revealed that three feature genes were correlated with immune system such as neutrophils. Clinical impact curve, calibration curves, ROC, and DCAs of the nomogram indicate that the nomogram had good performance. Our findings showed that C1QC, VSIG4, and CFD can potentially serve as diagnostic blood biomarkers of AF-CE; novel nomogram and the companion website can help clinicians to identify high-risk individuals, thus helping to guide treatment decisions for stroke patients.

Screening of potential biomarkers in peripheral blood of patients with depression based on weighted gene co-expression network analysis and machine learning algorithms.

The prevalence of depression has been increasing worldwide in recent years, posing a heavy burden on patients and society. However, the diagnostic and therapeutic tools available for this disease are inadequate. Therefore, this research focused on the identification of potential biomarkers in the peripheral blood of patients with depression. The expression dataset GSE98793 of depression was provided by the Gene Expression Omnibus (GEO) (https://www.ncbi.nlm.nih.gov/gds). Initially, differentially expressed genes (DEGs) were detected in GSE98793. Subsequently, the most relevant modules for depression were screened according to weighted gene co-expression network analysis (WGCNA). Finally, the identified DEGs were mapped to the WGCNA module genes to obtain the intersection genes. In addition, Gene Ontology (GO), Disease Ontology (DO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional enrichment analyses were conducted on these genes. Moreover, biomarker screening was carried out by protein-protein interaction (PPI) network construction of intersection genes on the basis of various machine learning algorithms. Furthermore, the gene set enrichment analysis (GSEA), immune function analysis, transcription factor (TF) analysis, and the prediction of the regulatory mechanism were collectively performed on the identified biomarkers. In addition, we also estimated the clinical diagnostic ability of the obtained biomarkers, and performed Mfuzz expression pattern clustering and functional enrichment of the most potential biomarkers to explore their regulatory mechanisms. Finally, we also perform biomarker-related drug prediction. Differential analysis was used for obtaining a total of 550 DEGs and WGCNA for obtaining 1,194 significant genes. Intersection analysis of the two yielded 140 intersection genes. Biological functional analysis indicated that these genes had a major role in inflammation-related bacterial infection pathways and cardiovascular diseases such as atherosclerosis. Subsequently, the genes S100A12, SERPINB2, TIGIT, GRB10, and LHFPL2 in peripheral serum were identified as depression biomarkers by using machine learning algorithms. Among them, S100A12 is the most valuable biomarker for clinical diagnosis. Finally, antidepressants, including disodium selenite and eplerenone, were predicted. The genes S100A12, TIGIT, SERPINB2, GRB10, and LHFPL2 in peripheral serum are viable diagnostic biomarkers for depression. and contribute to the diagnosis and prevention of depression in clinical practice.

Identification of Potential Diagnoses Based on Immune Infiltration and Autophagy Characteristics in Major Depressive Disorder.

Background: Major depressive disorder (MDD) is a serious mental illness characterized by mood changes and high suicide rates. However, no studies are available to support a blood test method for MDD diagnosis. The objective of this research was to identify potential peripheral blood biomarkers for MDD and characterize the novel pathophysiology. Methods: We accessed whole blood microarray sequencing data for MDD and control samples from public databases. Biological functions were analysed by GO and KEGG pathway enrichment analyses using the clusterprofile R package. Infiltrated immune cell (IIC) proportions were identified using the CIBERSORT algorithm. Clustering was performed using the ConsensusClusterPlus R package. Protein–protein interactions (PPI) were assessed by constructing a PPI network using STRING and visualized using Cytoscape software. Rats were exposed to chronic unpredictable mild stress (CUMS) for 6 weeks to induce stress behaviour. Stress behaviour was evaluated by open field experiments and forced swimming tests. Flow cytometry was used to analyse the proportion of CD8+ T cells. The expression of the corresponding key genes was detected by qRT–PCR. Results: We divided MDD patients into CD8H and CD8L clusters. The functional enrichment of marker genes in the CD8H cluster indicated that autophagy-related terms and pathways were significantly enriched. Furthermore, we obtained 110 autophagy-related marker genes (ARMGs) in the CD8H cluster through intersection analysis. GO and KEGG analyses further showed that these ARMGs may regulate a variety of autophagy processes and be involved in the onset and advancement of MDD. Finally, 10 key ARMGs were identified through PPI analysis: RAB1A, GNAI3, VAMP7, RAB33B, MYC, LAMP2, RAB11A, HIF1A, KIF5B, and PTEN. In the CUMS model, flow cytometric analysis confirmed the above findings. qRT–PCR revealed significant decreases in the mRNA levels of Gnai3, Rab33b, Lamp2, and Kif5b in the CUMS groups. Conclusion: In this study, MDD was divided into two subtypes. We combined immune infiltrating CD8+ T cells with autophagy-related genes and screened a total of 10 ARMG genes. In particular, RAB1A, GNAI3, RAB33B, LAMP2, and KIF5B were first reported in MDD. These genes may offer new hope for the clinical diagnosis of MDD.

Comprehensive Analysis of ceRNA Regulation Network Involved in the Development of Coronary Artery Disease.

Background Coronary artery disease (CAD) is one of the most common causes of sudden death with high morbidity in recent years. This paper is aimed at exploring the early peripheral blood biomarkers of sudden death and providing a new perspective for clinical diagnosis and forensic pathology identification by integrated bioinformatics analysis. Methods Two microarray expression profiling datasets (GSE113079 and GSE31568) were downloaded from the Gene Expression Omnibus (GEO) database, and we identified differentially expressed lncRNAs, miRNAs, and mRNAs in CAD. Gene Ontology (GO) and KEGG pathway analyses of DEmRNAs were executed. A protein-protein interaction (PPI) network was constructed, and hub genes were identified. Finally, we constructed a competitive endogenous RNA (ceRNA) regulation network among lncRNAs, miRNAs, and mRNAs. Also, the 5 miRNAs of the ceRNA network were verified by RT-PCR. Results In total, 86 DElncRNAs, 148 DEmiRNAs, and 294 DEmRNAs were dysregulated in CAD. We received 12 GO terms and 5 pathways of DEmRNAs. 31 nodes and 78 edges were revealed in the PPI network. The top 10 genes calculated by degree method were identified as hub genes. Moreover, there were a total of 26 DElncRNAs, 5 DEmiRNAs, and 13 DEmRNAs in the ceRNA regulation network. We validated the 5 miRNAs of the ceRNA network by RT-PCR, which were consistent with the results of the microarray. Conclusions In this paper, a CAD-specific ceRNA network was successfully constructed, contributing to the understanding of the relationship among lncRNAs, miRNAs, and mRNAs. We identified potential peripheral blood biomarkers in CAD and provided novel insights into the development and progress of CAD.

Screening and Identification of Potential Peripheral Blood Biomarkers for Alzheimer's Disease Based on Bioinformatics Analysis.

BackgroundAlzheimer’s disease (AD) is the leading cause of dementia worldwide; however, the molecular mechanisms underlying its pathogenesis remain unclear. The present study aimed to discover some potential peripheral blood biomarkers for early detection of patients with AD.Material/MethodsPublicly available AD datasets – GSE18309 and GSE97760 – were obtained from the Gene Expression Omnibus database, and limma package from Bioconductor was employed to search for differently expressed genes (DEGs). Weighted correlation network analysis was performed to identify DEGs with highly synergistic changes, and functional annotation of DEGs was performed using gene set enrichment analysis and Metascape. STRING and Cytoscape were used to construct protein-protein interaction networks and analyze the most significant hub genes. Thereafter, the Comparative Toxicogenomics Database (CTD) was used to identify hub genes associated with AD pathology, and Connectivity Map was used to screen small molecule drugs for AD. Finally, hub genes coupled with corresponding predicted miRNAs involved in AD were assessed via TargetScan, and functional annotation of predicted miRNAs was performed using DIANA database.ResultsOur analyses revealed 5042 DEGs; based on functional analyses, these DEGs were mainly associated with oligosaccharide lipid intermediate biosynthetic process, cyclin binding, signaling pathways regulating pluripotency of ubiquitin mediated proteolysis, and extracellular matrix-receptor interaction. UBB, UBA52, SRC, MMP9, VWF, GP6, and PF4 were identified as the hub genes. The CTD showed that these hub genes are closely related with AD or cognition impairment.ConclusionsThe identified hub genes and corresponding miRNAs might be useful as potential peripheral blood biomarkers of AD.

Screening for Potential Biomarkers in Peripheral Blood From Miners Exposed to Radon Radiation.

In this cohort study of 144 miners, 72 miners worked underground (the study group) and 72 miners worked aboveground (the control group). Based on questionnaire data and of radon concentration measurements, the cumulative radon exposure dose was calculated for each miner using the parameters recommended in International Commission on Radiological Protection Publication 137. Hematological parameters such as lymphocyte count (LYM) and neutrophil count (NE) were assessed, cell cycle phases and regulatory proteins were detected by flow cytometry, and microRNA (miRNA) microarray screening and real-time polymerase chain reaction (PCR) were used to detect miRNAs in plasma. The interrelationships between various potential biomarkers were analyzed using bioinformatics and statistical methods. The mean cumulative exposure dose of underground miners and controls was 982 and 48 mSv, respectively. Hematological parameters (such as LYM and NE) were significantly lower in the underground group. Cyclin-dependent kinase (CDK)-2, CDK4, CDK6, CyclinA2, CyclinD1, and CyclinE1 were significantly higher in the underground group. MicroRNA microarray screening showed that 5 miRNAs were downregulated (fold-change >2) in the underground group. The real-time PCR detection results of miR-19a, miR-30e, miR-335, and miR-451a were consistent with the screening results. LYM, NE, CDK2, CDK4, CDK6, Cyclin A2, Cyclin D1, Cyclin E1, miR-19a, miR-30e, miR-335, and miR451a are potential biomarkers of radon radiation damage.

Blood Predictive Biomarkers for Nivolumab in Advanced Melanoma.

Nivolumab response rate is 40% in metastatic melanoma. Few studies have evaluated pre-treatment biomarkers predictive of response. The aim of this study was to identify potential peripheral blood biomarkers associated with survival in patients with advanced melanoma treated with nivolumab. All advanced melanoma cases treated with anti-programmed cell death protein 1 (anti-PD1) over a 3-year period in the Dermato-Oncology Department, Nantes, France were identified. For each case, 9 potential blood biomarkers were identified. Bivariate and multivariate analyses, adjusted for the American Joint Committee on Cancer (AJCC) classification stage, Eastern Cooperative Oncology Group (ECOG) performance status, lactate dehydrogenase (LDH) level and failure to respond to first-line therapy, were used to test the association between biomarkers and overall survival (primary outcome) or progression-free survival (secondary outcome). Increased monocyte count, leukocyte/lymphocyte ratio and neutrophil/lymphocyte ratio were significantly associated with decreased overall survival after bivariate and multivariate analyses. Increased monocyte count was also significantly associated with decreased progression-free survival. These blood variables are easily measured and could help to predict patient response before the introduction of anti-PD1 therapy.

Redox Proteomic Profiling of Specifically Carbonylated Proteins in the Serum of Triple Transgenic Alzheimer's Disease Mice.

Oxidative stress is a key event in the onset and progression of neurodegenerative diseases, including Alzheimer’s disease (AD). To investigate the role of oxidative stress in AD and to search for potential biomarkers in peripheral blood, serums were collected in this study from the 3-, 6-, and 12-month-old triple transgenic AD mice (3×Tg-AD mice) and the age- and sex-matched non-transgenic (non-Tg) littermates. The serum oxidized proteins were quantified by slot-blot analysis and enzyme-linked immunosorbent assay (ELISA) to investigate the total levels of serum protein carbonyl groups. Western blotting, in conjunction with two-dimensional gel electrophoresis (2D-Oxyblot), was employed to identify and quantify the specifically-carbonylated proteins in the serum of 3×Tg-AD mice. The results showed that the levels of serum protein carbonyls were increased in the three month old 3×Tg-AD mice compared with the non-Tg control mice, whereas no significant differences were observed in the six and 12 months old AD mice, suggesting that oxidative stress is an early event in AD progression. With the application of 2D-Oxyblot analysis, (immunoglobin) Ig gamma-2B chain C region (IGH-3), Ig lambda-2 chain C region (IGLC2), Ig kappa chain C region (IGKC), and Ig kappa chain V-V region HP R16.7 were identified as significantly oxidized proteins compared with the control. Among them IGH-3 and IGKC were validated via immunoprecipitation and Western blot analysis. Identification of oxidized proteins in the serums of 3×Tg-AD mice can not only reveal potential roles of those proteins in the pathogenesis of AD but also provide potential biomarkers of AD at the early stage.

Establishment of Elevated Serum Levels of IL-10, IL-8 and TNF-β as Potential Peripheral Blood Biomarkers in Tubercular Lymphadenitis: A Prospective Observational Cohort Study.

BackgroundTubercular lymphadenitis (TL) is the most common form of extra-pulmonary tuberculosis (TB) consisting about 15–20% of all TB cases. The currently available diagnostic modalities for (TL), are invasive and involve a high index of suspicion, having limited accuracy. We hypothesized that TL would have a distinct cytokine signature that would distinguish it from pulmonary TB (PTB), peripheral tubercular lymphadenopathy (LNTB), healthy controls (HC), other lymphadenopathies (LAP) and cancerous LAP. To assess this twelve cytokines (Tumor Necrosis Factor (TNF)—α, Interferon (IFN) -γ, Interleukin (IL)-2, IL-12, IL-18, IL-1β, IL-10, IL-6, IL-4, IL-1Receptor antagonist (IL-1Ra), IL-8 and TNF-β, which have a role in pathogenesis of tuberculosis, were tested as potential peripheral blood biomarkers to aid the diagnosis of TL when routine investigations prove to be of limited value.Methods and FindingsA prospective observational cohort study carried out during 2010–2013. This was a multi-center study with three participating hospitals in Delhi, India where through random sampling cohorts were established. The subjects were above 15 years of age, HIV-negative with no predisposing ailments to TB (n = 338). The discovery cohort (n = 218) had LNTB (n = 50), PTB (n = 84) and HC (n = 84). The independent validation cohort (n = 120) composed of patients with cancerous LAP (n = 35), other LAP (n = 20) as well as with independent PTB (n = 30), LNTB (n = 15) and HC (n = 20). Eight out of twelve cytokines achieved statistical relevance upon evaluation by pairwise and ROC analysis. Further, variable selection using random forest backward elimination revealed six serum biosignatures including IL-12, IL-4, IL-6, IL-10, IL-8 and TNF-β as optimal for classifying the LNTB status of an individual. For the sake of clinical applicability we further selected a three analyte panel (IL-8, IL-10 and TNF-β) which was subjected to multinomial modeling in the independent validation cohort which was randomised into training and test cohorts, achieving an overwhelming 95.9% overall classifying accuracy for correctly classifying LNTB cases with a minimal (7%) misclassification error rate in the test cohort.ConclusionsIn our study, a three analyte serum biosignatures and probability equations were established which can guide the physician in their clinical decision making and step wise management of LNTB patients. This set of biomarkers has the potential to be a valuable adjunct to the diagnosis of TL in cases where AFB positivity and granulomatous findings elude the clinician.

Pancreatic Allografts: Identification of Useful Biomarkers of Rejection and Beyond

Since organ transplantation became routine more than threedecades ago, there has been a need to obtain useful infor-mation regarding graft health, with assessment of the pre-sence of progressive immune-mediated graft rejection ofparticular importance for planning intervention. Althoughthe recommended method is to obtain sequential biopsiesfrom the graft itself, this procedure is invasive and risky,particularly if more than one sample is needed. Therefore,identification of less invasive markers, ideally measureablein the blood of transplant recipients, has been activelyinvestigated. Because of the large number of losses ofpancreatic grafts, it is particularly important to discoversurrogate markers of immune rejection.In this issue of Digestive Diseases and Sciences, Donget al. [1] describe a porcine model of pancreaticoduodenaltransplantation with or without immunosuppression thatwas used to evaluate the effectiveness of three potentialperipheral blood biomarkers of acute rejection for up toseven days post-transplant. The authors selected intercel-lular adhesion molecule (ICAM)-1, Fas cell surface deathreceptor (Fas), and its ligand FasL, all reported previouslyto be involved in the acute rejection response after solidorgan transplantation in humans and in animal models.ICAM-1 is an adhesion molecule involved in firmendothelial adhesion and trans-endothelial migration ofleukocytes, including T cells, monocytes, and neutro-phils, at sites of immune response and immunologicalsynapse formation (reviewed elsewhere [7]). ICAM-1 isconstitutively expressed on the surface of human endo-thelial cells and its expression is increased in the presenceof pro-inflammatory cytokines including tumor necrosisfactor (TNF)-a, interferon (IFN)-c and interleukin (IL)-1b.The most important ligand for ICAM-1 is the b-2 integrinlymphocyte function-associated (LFA)-1 (aLb2); it isexpressed on all types of leukocyte but requires a Ca

MicroRNA Expression Aberration as Potential Peripheral Blood Biomarkers for Schizophrenia

Since brain tissue is not readily accessible, a new focus in search of biomarkers for schizophrenia is blood-based expression profiling of non-protein coding genes such as microRNAs (miRNAs), which regulate gene expression by inhibiting the translation of messenger RNAs. This study aimed to identify potential miRNA signature for schizophrenia by comparing genome-wide miRNA expression profiles in patients with schizophrenia vs. healthy controls. A genome-wide miRNA expression profiling was performed using a Taqman array of 365 human miRNAs in the mononuclear leukocytes of a learning set of 30 cases and 30 controls. The discriminating performance of potential biomarkers was validated in an independent testing set of 60 cases and 30 controls. The expression levels of the miRNA signature were then evaluated for their correlation with the patients' clinical symptoms, neurocognitive performances, and neurophysiological functions. A seven-miRNA signature (hsa-miR-34a, miR-449a, miR-564, miR-432, miR-548d, miR-572 and miR-652) was derived from a supervised classification with internal cross-validation, with an area under the curve (AUC) of receiver operating characteristics of 93%. The putative signature was then validated in the testing set, with an AUC of 85%. Among these miRNAs, miR-34a was differentially expressed between cases and controls in both the learning (P = 0.005) and the testing set (P = 0.002). These miRNAs were differentially correlated with patients' negative symptoms, neurocognitive performance scores, and event-related potentials. The results indicated that the mononuclear leukocyte-based miRNA profiling is a feasible way to identify biomarkers for schizophrenia, and the seven-miRNA signature warrants further investigation.

MMP1 and MMP7 as Potential Peripheral Blood Biomarkers in Idiopathic Pulmonary Fibrosis

BackgroundIdiopathic pulmonary fibrosis (IPF) is a chronic progressive fibrotic lung disease associated with substantial morbidity and mortality. The objective of this study was to determine whether there is a peripheral blood protein signature in IPF and whether components of this signature may serve as biomarkers for disease presence and progression.Methods and FindingsWe analyzed the concentrations of 49 proteins in the plasma of 74 patients with IPF and in the plasma of 53 control individuals. We identified a combinatorial signature of five proteins—MMP7, MMP1, MMP8, IGFBP1, and TNFRSF1A—that was sufficient to distinguish patients from controls with a sensitivity of 98.6% (95% confidence interval [CI] 92.7%–100%) and specificity of 98.1% (95% CI 89.9%–100%). Increases in MMP1 and MMP7 were also observed in lung tissue and bronchoalveolar lavage fluid obtained from IPF patients. MMP7 and MMP1 plasma concentrations were not increased in patients with chronic obstructive pulmonary disease or sarcoidosis and distinguished IPF compared to subacute/chronic hypersensitivity pneumonitis, a disease that may mimic IPF, with a sensitivity of 96.3% (95% CI 81.0%–100%) and specificity of 87.2% (95% CI 72.6%–95.7%). We verified our results in an independent validation cohort composed of patients with IPF, familial pulmonary fibrosis, subclinical interstitial lung disease (ILD), as well as with control individuals. MMP7 and MMP1 concentrations were significantly higher in IPF patients compared to controls in this cohort. Furthermore, MMP7 concentrations were elevated in patients with subclinical ILD and negatively correlated with percent predicted forced vital capacity (FVC%) and percent predicted carbon monoxide diffusing capacity (DLCO%).ConclusionsOur experiments provide the first evidence for a peripheral blood protein signature in IPF to our knowledge. The two main components of this signature, MMP7 and MMP1, are overexpressed in the lung microenvironment and distinguish IPF from other chronic lung diseases. Additionally, increased MMP7 concentration may be indicative of asymptomatic ILD and reflect disease progression.