Molecular profiling reveals human biomarker signatures in patients after allogeneic stem cell transplantation suffering from invasive aspergillosis
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE174825 | GEO | 2022/03/02
REPOSITORIES: GEO
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Project description:Comprehensive proteomic analysis of the protein expression landscape of bronchoalveolar lavage fluid during invasive pulmonary aspergillosis in murine and human samples. 38 murine BALF samples (10 Aspergillus fumigatus infected mice without immunosuppression and without invasive pulmonary aspergillosis (IPA), 19 immunosuppressed and infected mice with IPA and 9 immunosuppressed animals without infection) were analysed for their global protein expression. In addition, 54 human BALF specimen from patients with probable IPA (23 samples), proven IPA (4 cases) and 27 control samples from patients with unrelated pulmonary diseases were analysed for their global protein composition. Host responses and Aspergillus fumigatus-specific proteins detectable in BALF were studied.
2020-10-14 | PXD016664 | Pride
Project description:Invasive aspergillosis (IA) is a devastating opportunistic infection and its treatment constitutes a considerable burden for the health care system. Immunocompromised patients are at an increased risk for IA, which is mainly caused by the species Aspergillus fumigatus. An early and reliable diagnosis is required to initiate the appropriate antifungal therapy. However, diagnostic sensitivity and accuracy still needs to be improved, which can be achieved at least partly by the definition of new biomarkers. Besides the direct detection of the pathogen by the current diagnostic methods, the analysis of the host response is a promising strategy towards this aim. Following this approach, we sought to identify new biomarkers for IA. For this purpose, we analyzed gene expression profiles of haematological patients and compared profiles of patients suffering from IA with non-IA patients. Based on microarray data, we applied a comprehensive feature selection using a random forest classifier. We identified the transcript coding for the S100 calcium-binding protein B (S100B) as a potential new biomarker for the diagnosis of IA. Considering the expression of this gene, we were able to classify samples from patients with IA with 82.3% sensitivity and 74.6% specificity. Moreover, we validated the expression of S100B in a real-time RT-PCR assay and we also found a down-regulation of S100B in A. fumigatus stimulated DCs. An influence on the IL1B and CXCL1 downstream levels was demonstrated by this S100B knockdown. In conclusion, this study covers an effective feature selection revealing a key regulator of the human immune response during IA. S100B may represent an additional diagnostic marker that in combination with the established techniques may improve the accuracy of IA diagnosis. The gene expression data of patients with invasive aspergillosis (IA) was compared to patients without IA. 23 samples of 8 IA patients, 13 samples from 7 unclassified patients and 1 patient with possible invasive fungal disease (IFD), and 9 control samples from 8 healthy donors were generated. Patients were classified according to the current EORTC/MSG criteria.
2016-03-31 | E-GEOD-78000 | biostudies-arrayexpress
Project description:More humans have died of tuberculosis (TB) than any other infectious disease and millions still die each year. Experts advocate for blood-based, protein biomarkers to help diagnosis TB, which is critical in high-burden countries. However, the protein biomarker pipeline is small. Here, we used the Diversity Outbred (DO) mouse population to address this gap, identifying five protein biomarker candidates. One biomarker, serum CXCL1, met the World Health Organization’s Targeted Product Profile for a triage test to diagnose active TB from latent M.tb infection (LTBI), non-TB lung disease, and normal sera in HIV-negative, adults from South Africa and Vietnam. To find the biomarker candidates, we quantified seven immune mediators and four proteins corresponding to a subset of highly expressed genes unique to progressor DO mice. Next, we applied statistical and machine learning methods to the data, i.e., 11 proteins in lungs from 453 infected and 29 non-infected mice. After searching all combinations of five algorithms and 239 protein subsets, validating, and testing the findings on independent data, two combinations accurately diagnosed progressor DO mice: Logistic Regression using MMP8; and Gradient Tree Boosting using a panel of 4: CXCL1, CXCL2, TNF, IL-10. Of those five protein biomarker candidates, two (MMP8 and CXCL1) were crucial for classifying DO mice; were above the limit of detection in most human serum samples; and had not been widely assessed for diagnostic performance in humans before. In patient sera, CXCL1 exceeded the triage diagnostic test criteria (>90% sensitivity; >70% specificity), while MMP8 did not. Using Area Under the Curve analyses, CXCL1 averaged 94.5% sensitivity and 88.8% specificity for active pulmonary TB (ATB) vs LTBI; 90.9% sensitivity and 71.4% specificity for ATB vs non-TB; and 100.0% sensitivity and 98.4% specificity for ATB vs normal sera. Our findings overall show that the DO mouse population can discover diagnostic-quality, serum protein biomarkers of human TB.
2021-07-29 | GSE179417 | GEO
Project description:Despite more than a century fighting against tuberculosis, the World Health Organisation has estimated that around 1.7 million people died of tuberculosis in 2016 and over a quarter of the world’s population is infected. One of the critical hurdles for stopping tuberculosis transmission is early and effective diagnosis of patients with the active pulmonary disease. Although important innovations in molecular diagnosis have been recently developed (e.g. Xpert MTB/RIF, Cepheid Inc., USA), there are no suitable tests for population screening at point-of-care. The current tuberculosis diagnosis pipeline presents a highly variable performance and requires access to reference laboratory facilities. A non-sputum based rapid test with high specificity and sensitivity could save ~400,000 lives per year. Therefore, new biomarkers for diagnosis are urgently required for identifying patients with early symptoms and to expedite treatment. Variable sensitivity and specificity can be overcome using a combination of multiple biomarkers (5). Proteins, as ultimate biological effectors, are ideal candidates for diagnostic biomarkers; consequently, proteomic studies are a crucial platform for biomarker discovery in tuberculosis. This work aims to develop a multi-marker panel for tuberculosis diagnosis with high performance capable of differentiating tuberculosis patients from relevant controls. Quantitative Multidimensional Protein Identification Technology (qMudPIT) is applied for biomarker discovery identifying candidates for early diagnosis of tuberculosis. The multidimensional method optimised in this work led to the identification of 5022 plasma proteins and 3577 quantified proteins using iTRAQ labelling. Known and completely novel markers for active tuberculosis in plasma were identified including a peptide derived from Mycobacterium tuberculosis. Complementary statistical and bioinformatic analysis were applied to prioritise candidates for validation in one or two independent cohorts. The plasma proteomic profile here described represents a power strategy for biomarker discovery and the panel proposed has the potential to be translated to a rapid test and which might contribute to tuberculosis control.
2021-09-09 | PXD020212 | Pride
Project description:Sputum expectorated by the pulmonary tuberculosis patients still remains a primary diagnostic specimen. The expression pattern of mycobacteria in sputum will lead to an insight of bacterial adaptation at the most highly transmissible stage of infection and can also help in identifying newer diagnostic as well as drug targets. Further, the identification of crossreactive gene targets from the sputum samples of other lung diseases will help to find the diagnostic candidates which will be highly specific to pulmonary tuberculosis.
2017-04-18 | GSE93316 | GEO
Project description:To assess whether transcriptional differences exist in the epithelial tissue and the inflammatory infiltrate of invasive Aspergillus tracheobronchitis in patients with severe influenza or severe COVID-19, we performed GeoMx spatial transcriptomics on four biopsy samples in total: two of patients with influenza-associated pulmonary aspergillosis (IAPA) and two of patients with COVID-19-associated pulmonary aspergillosis (CAPA). Several regions of interest (ROIs) were delineated in each biopsy sample, and transcriptomic data was derived of each of these ROIs using GeoMx with a whole transcriptome atlas with SARS-CoV-2 spike-in.
2022-08-24 | GSE198096 | GEO
Project description:72 candidate biomarkers evaluated for TB diagnosis using mRNA purified from whole blood of Active TB patients recruited in the UK and India, LTB and two groups of controls from the UK (i) from a low incidence region and (ii) individuals variably domiciled in the UK and India. Tuberculosis (TB) remains a major global threat and diagnosis of active TB ((ATB) both extra-pulmonary (EPTB) and pulmonary (PTB)) and latent TB (LTBI) remains challenging, particularly in high-burden countries which still rely heavily on conventional methods. Although molecular diagnostic methods are available, e.g., Cepheid GeneXpert, they are not universally available in all high TB burden countries. There is intense focus on immune biomarkers for use in TB diagnosis, which could provide alternative low-cost, rapid diagnostic solutions. In our previous gene expression studies, we identified peripheral blood leukocyte (PBL) mRNA biomarkers in a non-human primate TB aerosol-challenge model. Here, we describe a study to further validate select mRNA biomarkers from this prior study in new cohorts of patients and controls, as a prerequisite for further development. PBL mRNA was purified from ATB patients recruited in the UK and India, LTBI and two groups of controls from the UK (i) a low TB incidence region (CNTRLA) and (ii) individuals variably-domiciled in the UK and Asia ((CNTRLB), the latter TB high incidence regions). Seventy-two mRNA biomarker gene targets were analyzed by qPCR using the Roche Lightcycler 480 qPCR platform and data analyzed using GeneSpring™ 14.9 bioinformatics software. Differential expression of fifty-three biomarkers was confirmed between MTB infected, LTBI groups and controls, seventeen of which were significant using analysis of variance (ANOVA): CALCOCO2, CD52, GBP1, GBP2, GBP5, HLA-B, IFIT3, IFITM3, IRF1, LOC400759 (GBP1P1), NCF1C, PF4V1, SAMD9L, S100A11, TAF10, TAPBP, and TRIM25. These were analyzed using receiver operating characteristic (ROC) curve analysis. Single biomarkers and biomarker combinations were further assessed using simple arithmetic algorithms. Minimal combination biomarker panels were delineated for primary diagnosis of ATB (both PTB and EPTB), LTBI and identifying LTBI individuals at high risk of progression which showed good performance characteristics. These were assessed for suitability for progression against the standards for new Tuberculosis diagnostic tests delineated in the published World Health Organization (WHO) technology product profiles (TPPs)
2021-03-05 | GSE168247 | GEO
Project description:Hepatitis B virus (HBV)-associated acute on chronic liver failure (HBV-ACLF), characterized by an acute deterioration of liver function in the patients with chronic hepatitis B (CHB), is lack of predicting biomarkers for prognosis. To explore potential biomarkers of HBV-ACLF for clinical applications, immuno-depletion of high-abundance plasma proteins followed by iTRAQ-based quantitative proteomic approach was employed to analyze plasma samples from 20 healthy control people, 20 CHB patients and 20 HBV-ACLF patients, respectively. As a result, a total of 427 proteins were identified and quantified from these samples, and 42 proteins were differentially expressed in HBV-ACLF patients as compared to both CHB patients and healthy controls. According to bioinformatics analysis results, 6 proteins related to immune response (MMR), inflammatory response (OPN, HPX), blood coagulation (ATIII) and lipid metabolism (APO-CII, GP73) were selected as biomarker candidates. Further ELISA analysis confirmed the significant up-regulation of GP73, MMR, OPN and down-regulation of ATIII, HPX, APO-CII in HBV-ACLF plasma samples (p<0.01). Moreover, receiver operating characteristic (ROC) curve analysis revealed high diagnostic value of these candidates in assessing HBV-ACLF. In conclusion, present quantitative proteomic study identified 6 novel HBV-ACLF biomarker candidates and might provide fundamental information for development of HBV-ACLF biomarker.
2018-10-23 | PXD007975 | Pride
Project description:Background: Cerebral cavernous angiomas with a symptomatic hemorrhage (CASH) have a high-risk of recurrent hemorrhage and serious morbidity. Methods: Eighteen plasma molecules with postulated mechanistic roles in cavernous angioma (CA) pathobiology were investigated in 114 patients and 12 healthy subjects. The diagnostic biomarker of a CASH in the prior year was derived as minimizing the Akaike Information Criterion (AIC) and validated using machine-learning, and then compared to the prognostic CASH biomarker predicting bleeding in the subsequent year. Both biomarkers were longitudinally followed in a subset of cases. The biomarkers were queried in the transcriptome of human lesional micro-dissected neurovascular units (NVUs) and in relation to plasma miRNAs from CASH and non-CASH patients. Results: The diagnostic CASH biomarker included a weighted combination of four molecules (sCD14, VEGF, CRP, and IL-10) distinguishing CASH patients with 76% sensitivity and 80% specificity (p=0.0003). The prognostic CASH biomarker included two of these molecules (sCD14 and VEGF) and two others (IL-1β and sROBO-4) was confirmed to predict a bleed in the subsequent year, with 83% sensitivity and 93% specificity (p=0.001). Genes associated with the diagnostic and prognostic CASH biomarkers were differentially expressed in CASH lesional NVUs. Thirteen miRNAs were also differentially expressed in the plasma of CASH patients compared to non-CASH. Conclusion: There are shared and unique biomarkers of recent symptomatic hemorrhage and of future bleeding in CA, and are mechanistically linked to the lesional transcriptome and miRNA regulation. The biomarkers may be applied for risk stratification in clinical trials and developed as a tool in clinical practice.
2019-05-13 | GSE130175 | GEO
Project description:Background: Cerebral cavernous angiomas with a symptomatic hemorrhage (CASH) have a high-risk of recurrent hemorrhage and serious morbidity. Methods: Eighteen plasma molecules with postulated mechanistic roles in cavernous angioma (CA) pathobiology were investigated in 114 patients and 12 healthy subjects. The diagnostic biomarker of a CASH in the prior year was derived as minimizing the Akaike Information Criterion (AIC) and validated using machine-learning, and then compared to the prognostic CASH biomarker predicting bleeding in the subsequent year. Both biomarkers were longitudinally followed in a subset of cases. The biomarkers were queried in the transcriptome of human lesional micro-dissected neurovascular units (NVUs) and in relation to plasma miRNAs from CASH and non-CASH patients. Results: The diagnostic CASH biomarker included a weighted combination of four molecules (sCD14, VEGF, CRP, and IL-10) distinguishing CASH patients with 76% sensitivity and 80% specificity (p=0.0003). The prognostic CASH biomarker included two of these molecules (sCD14 and VEGF) and two others (IL-1β and sROBO-4) was confirmed to predict a bleed in the subsequent year, with 83% sensitivity and 93% specificity (p=0.001). Genes associated with the diagnostic and prognostic CASH biomarkers were differentially expressed in CASH lesional NVUs. Thirteen miRNAs were also differentially expressed in the plasma of CASH patients compared to non-CASH. Conclusion: There are shared and unique biomarkers of recent symptomatic hemorrhage and of future bleeding in CA, and are mechanistically linked to the lesional transcriptome and miRNA regulation. The biomarkers may be applied for risk stratification in clinical trials and developed as a tool in clinical practice.
2019-05-13 | GSE130174 | GEO