Dataset Information

Correlation of Immunological Markers with Disease and Clinical Outcome Measures in Patients with Autoimmune Retinopathy.

ABSTRACT: Purpose:To determine if immunological markers (1) are significantly different between autoimmune retinopathy (AIR) patients and controls and (2) correlate with disease progression in AIR patients. Methods:We enrolled patients with a possible AIR diagnosis, as well as control participants without eye disease, autoimmunity, or cancer. Immunological markers were tested in all participants. In addition, AIR patients had up to three blood draws for testing over their disease course. For AIR patients, clinical measures, including visual acuity (VA) and Goldmann visual field (GVF) area, were recorded at each draw. We used the Mann-Whitney U test to compare the immunological markers between AIR patients and controls. We used multilevel mixed-effect regression to investigate the correlation between markers and clinical parameters over time in AIR patients. Results:Seventeen patients with AIR and 14 controls were included. AIR patients had a higher percent of monocytes (Z = 3.076, P = 0.002). An increase in immunoglobulin G against recoverin was correlated with a VA decrease (? = 0.0044, P < 0.0001). An increase in monocyte proportion was correlated with a decrease in GVF area (? = -7.27, P = 0.0021). Several markers of B-cell depletion were correlated with GVF improvement. Conclusions:Monocytes may play a role in AIR pathophysiology and be a disease activity marker. B-cell depletion markers correlated with clinical parameter improvement, particularly GVF. Translational Relevance:This work elucidates immunologic markers that may improve the accuracy of diagnosis and treatment of AIR.

SUBMITTER: Stanwyck LK

PROVIDER: S-EPMC7414616 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Correlation of Immunological Markers with Disease and Clinical Outcome Measures in Patients with Autoimmune Retinopathy.

Stanwyck Lynn K LK Chan Weilin W Sood Arjun A Susarla Gayatri G Romano John J Pefkianaki Maria M Jayasundera Kanishka Thiran KT Heckenlively John R JR Lundy Steven K SK Sobrin Lucia L

Translational vision science & technology 20200616 7

<h4>Purpose</h4>To determine if immunological markers (1) are significantly different between autoimmune retinopathy (AIR) patients and controls and (2) correlate with disease progression in AIR patients.<h4>Methods</h4>We enrolled patients with a possible AIR diagnosis, as well as control participants without eye disease, autoimmunity, or cancer. Immunological markers were tested in all participants. In addition, AIR patients had up to three blood draws for testing over their disease course. Fo ...[more]

PMID: 32832222

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Project description:Background Published multi-gene classifiers suggested outcome prediction for patients with stage UICC II colon cancer based on different gene expression signatures. However, there is currently no translation of these classifiers for application in routine diagnostic. Therefore, we aimed at validating own and published gene expression signatures employing methods which enable RNA and protein detection in routine diagnostic specimens. Results Immunohistochemistry was applied to 68 stage UICC II colon cancers to determine the protein expression of five selected previously published classifier genes (CDH17, LAT, CA2, EMR3, and TNFRSF11A). Correlation of protein expression data with clinical outcome within a 5-year post-surgery course failed to separate patients with a disease-free follow-up [Group DF] and relapse [Group R]). In addition, RNA from macrodissected tumor samples from 53 of these 68 patients was profiled on Affymetrix GeneChips (HG-U133 Plus 2.0). Prognostic signatures were generated by Nearest Shrunken Centroids with cross-validation. Although gene expression profiling allowed the identification of differentially expressed genes between the groups DF and R, a stable classification and prognosis signature was not discernable in our data. Furthermore, the application of previously published gene signatures consisting of 22 and 19 genes, respectively, to our gene expression data set using ‘global tests’ and leave-one-out cross-validation was unable to predict clinical outcome (prediction rate 75.5% and 64.2%; n.s.). T-stage was the only independent prognostic factor for relapse in multivariate analysis with established clinical and pathological parameters including microsatellite status. Conclusions Our protein and gene expression analyses currently do not support application of molecular classifiers for prediction of clinical outcome in routine diagnostic as a basis for patient-orientated therapy in stage UICC II colon cancer. Further studies are needed to develop prognosis signatures applicable in patient care.

Project description:BackgroundA detailed sensorimotor evaluation is essential in planning effective, individualized therapy post-stroke. Robotic kinematic assay may offer better accuracy and resolution to understand stroke recovery. Here we investigate the added value of distal wrist measurement to a proximal robotic kinematic assay to improve its correlation with clinical upper extremity measures in chronic stroke. Secondly, we compare linear and nonlinear regression models.MethodsData was sourced from a multicenter randomized controlled trial conducted from 2012 to 2016, investigating the combined effect of robotic therapy and transcranial direct current stimulation (tDCS). 24 kinematic metrics were derived from 4 shoulder-elbow tasks and 35 metrics from 3 wrist and forearm evaluation tasks. A correlation-based feature selection was performed, keeping only features substantially correlated with the target attribute (R > 0.5.) Nonlinear models took the form of a multilayer perceptron neural network: one hidden layer and one linear output.ResultsShoulder-elbow metrics showed a significant correlation with the Fugl Meyer Assessment (upper extremity, FMA-UE), with a R = 0.82 (P < 0.001) for the linear model and R = 0.88 (P < 0.001) for the nonlinear model. Similarly, a high correlation was found for wrist kinematics and the FMA-UE (R = 0.91 (P < 0.001) and R = 0.92 (P < 0.001) for the linear and nonlinear model respectively). The combined analysis produced a correlation of R = 0.91 (P < 0.001) for the linear model and R = 0.91 (P < 0.001) for the nonlinear model.ConclusionsDistal wrist kinematics were highly correlated to clinical outcomes, warranting future investigation to explore our nonlinear wrist model with acute or subacute stroke populations.Trial registrationhttp://www.clinicaltrials.gov . Actual study start date September 2012. First registered on 15 November 2012. Retrospectively registered. Unique identifiers: NCT01726673 and NCT03562663 .

Dataset Information

Correlation of Immunological Markers with Disease and Clinical Outcome Measures in Patients with Autoimmune Retinopathy.

Publications

Correlation of Immunological Markers with Disease and Clinical Outcome Measures in Patients with Autoimmune Retinopathy.

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