Project description:Introduction: Sepsis is a complex immunological response to infection characterized by early hyperinflammation followed by severe and protracted immunosuppression, suggesting that a multi-marker approach has the greatest clinical utility for early detection, within a clinical environment focused on SIRS differentiation. Pre-clinical research using an equine sepsis model identified a panel of gene expression biomarkers that define the early aberrant immune activation. Thus, the primary objective was to apply these gene expression biomarkers to distinguish patients with sepsis from those who had undergone major open surgery and had clinical outcomes consistent with systemic inflammation due to physical trauma and wound healing. Methods: This was a multi-centre, prospective clinical trial conducted across 4 tertiary critical care settings in Australia. Sepsis patients were recruited if they met the 1992 Consensus Statement criteria and had clinical evidence of systemic infection based on microbiology diagnoses (n=27). Participants in the post-surgical (PS) group were recruited pre-operatively and blood samples collected within 24 hours following surgery (n=38). Healthy controls (HC) included hospital staff with no known concurrent illnesses (n=20). Each participant had minimally 5ml of PAXgene blood collected for leucocyte RNA isolation and gene expression analyses. Affymetrix array and multiplex tandem (MT)-PCR studies were conducted to evaluate transcriptional profiles in circulating white blood cells applying a set of 42 molecular markers that had been identified a priori. A LogitBoost algorithm was used to create a machine learning diagnostic rule to predict sepsis outcomes. Results: Based on preliminary microarray analyses comparing HC and sepsis groups. A panel of 42-gene expression markers were identified that represented key innate and adaptive immune function, cell cycling, WBC differentiation, extracellular remodelling and immune modulation pathways. Comparisons against GEO data confirmed the definitive separation of the sepsis cohort. Quantitative PCR results suggest the capacity for this test to differentiate severe systemic inflammation from HC is 92%. AUC ROC curve findings demonstrated sepsis prediction within a mixed inflammatory population, was between 86 - 92%. Conclusions: This novel molecular biomarker test has a clinically relevant sensitivity and specificity profile, and has the capacity for early detection of sepsis via the monitoring of critical care patients. GEO Note: Data made available represents the preliminary microarray investigation performed on Human U133 Plus 2.0 GeneChips (Affymetrix), assaying 41 patient samples (Sepsis n=10, Post-Surgical n=11, Control n=20).

Project description:Introduction: Sepsis is a complex immunological response to infection characterized by early hyperinflammation followed by severe and protracted immunosuppression, suggesting that a multi-marker approach has the greatest clinical utility for early detection, within a clinical environment focused on SIRS differentiation. Pre-clinical research using an equine sepsis model identified a panel of gene expression biomarkers that define the early aberrant immune activation. Thus, the primary objective was to apply these gene expression biomarkers to distinguish patients with sepsis from those who had undergone major open surgery and had clinical outcomes consistent with systemic inflammation due to physical trauma and wound healing. Methods: This was a multi-centre, prospective clinical trial conducted across 4 tertiary critical care settings in Australia. Sepsis patients were recruited if they met the 1992 Consensus Statement criteria and had clinical evidence of systemic infection based on microbiology diagnoses (n=27). Participants in the post-surgical (PS) group were recruited pre-operatively and blood samples collected within 24 hours following surgery (n=38). Healthy controls (HC) included hospital staff with no known concurrent illnesses (n=20). Each participant had minimally 5ml of PAXgene blood collected for leucocyte RNA isolation and gene expression analyses. Affymetrix array and multiplex tandem (MT)-PCR studies were conducted to evaluate transcriptional profiles in circulating white blood cells applying a set of 42 molecular markers that had been identified a priori. A LogitBoost algorithm was used to create a machine learning diagnostic rule to predict sepsis outcomes. Results: Based on preliminary microarray analyses comparing HC and sepsis groups. A panel of 42-gene expression markers were identified that represented key innate and adaptive immune function, cell cycling, WBC differentiation, extracellular remodelling and immune modulation pathways. Comparisons against GEO data confirmed the definitive separation of the sepsis cohort. Quantitative PCR results suggest the capacity for this test to differentiate severe systemic inflammation from HC is 92%. AUC ROC curve findings demonstrated sepsis prediction within a mixed inflammatory population, was between 86 - 92%. Conclusions: This novel molecular biomarker test has a clinically relevant sensitivity and specificity profile, and has the capacity for early detection of sepsis via the monitoring of critical care patients. GEO Note: Data made available represents the preliminary microarray investigation performed on Human U133 Plus 2.0 GeneChips (Affymetrix), assaying 41 patient samples (Sepsis n=10, Post-Surgical n=11, Control n=20). This was a multi-centre, prospective clinical trial conducted across 4 tertiary critical care settings in Australia. Sepsis patients were recruited if they met the 1992 Consensus Statement criteria and had clinical evidence of systemic infection based on microbiology diagnoses (n=27). Participants in the post-surgical (PS) group were recruited pre-operatively and blood samples collected within 24 hours following surgery (n=38). Healthy controls (HC) included hospital staff with no known concurrent illnesses (n=20). Each participant had minimally 5ml of PAXgene blood collected for leucocyte RNA isolation and gene expression analyses. The GEO data represents the preliminary microarray investigation performed on Human U133 Plus 2.0 GeneChips (Affymetrix), assaying 41 patient samples (Sepsis n=10, Post-Surgical n=11, Control n=20).

Project description:BackgroundScreening for opisthorchiasis, a parasitic worm infection affecting many millions of people in Southeast Asia, has traditionally relied on faecal egg examination such as the formalin-ethyl acetate concentration technique (FECT) and Kato-Katz method. Although the urinary enzyme-linked immunosorbent assay (ELISA) has been used more recently, we developed a urinary antigen-based rapid diagnostic test (RDT) to simplify diagnosis and as a point-of-care testing (POCT) and field applications for surveillance and control of opisthorchiasis.MethodsA urinary Opisthorchis viverrini (OV)-RDT was developed using immunochromatographic methodology with a specific monoclonal antibody against OV. The diagnostic performance of the urinary OV-RDT was compared to that of quantitative faecal FECT and urinary antigen ELISA (n = 493). Cross-reactivities of urinary OV-RDT with other helminthiases coexisted with O. viverrini were determined (n = 96). A field trial in the application of urinary OV-RDT was compared with urinary antigen ELISA at baseline screening and assessment of drug treatment outcomes in opisthorchiasis (n = 1629). The McNemar chi-square, Kruskal-Wallis and Cohen's kappa coefficient (κ-value) tests were used for statistical analyses.ResultsUrinary OV-RDT had sensitivity of 94.2% and specificity of 93.2%, compared to faecal FECT. Urinary OV-RDT had high diagnostic agreement (Kappa = 0.842-0.874, P < 0.001) and quantitative correlation with urinary antigen ELISA (Kruskal-Wallis tests = 316.2, P < 0.0001) and faecal FECT (Kruskal-Wallis tests = 362.3, P < 0.0001). The positive rates by OV-RDT, ELISA and FECT were 48.9%, 52.5% and 49.3%, respectively. Cross-reactions of urinary OV-RDT with other helminthiases were few (2%). Field trials of urinary OV-RDT yielded comparable prevalence of O. viverrini between urinary OV-RDT (53.2%) and urinary antigen ELISA (54.0%). OV screening showed high diagnostic agreement (kappa > 0.8, P < 0.0001) between urinary OV-RDT and urinary antigen ELISA. The cure rates of opisthorchiasis at 1 month post-praziquantel treatment determined by urinary OV-RDT (86.6%) and urinary antigen ELISA (80.5%) were similar (P > 0.05).ConclusionsThe urinary OV-RDT test has high potential as a new tool for screening and evaluating treatment outcomes in opisthorchiasis. The ease of sample collection and simplicity of urinary OV-RDT may facilitate mass screening, control and elimination of opisthorchiasis, thereby contributing to a reduction in the disease burden in Southeast Asia.

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Characterization and analytical validation of a new antigenic rapid diagnostic test for Ebola virus disease detection.

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Characterization and analytical validation of a new antigenic rapid diagnostic test for Ebola virus disease detection.

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