Project 1: Development of Luminex Beads and Project 2: Microarray Assay and Data Analysis - immunological understanding

Project 1: Development of Luminex Beads and Project 2: Microarray Assay and Data Analysis - immunological understanding Project 1: Development of Luminex Beads through preparation of purified protein and protein selection to develop & test diagnostic tools and immunological understanding for combating Lyme disease. Development of Luminex Beads through preparation of purified protein and protein selection to develop & test diagnostic tools and immunological understanding for combating Lyme disease. Project 2: Microarray Assay and Data Analysis - immunological understanding for combating Lyme disease Microarray Assay and Data Analysis - immunological understanding for combating Lyme disease Project 3: Algorithm Validation Background: Lyme Disease is a tickborne illness with increasing prevalence in the United States and an urgent need for improved diagnostics in its early stages, when treatment is most efficient. While classic clinical presentation of the early illness is the presence of the erythema migrans (EM), or bullseye rash, surrounding the tick bite site, 20-30% of patients do not present with EM. Further complicating diagnosis is a proportion of patients who present with EM, but are seronegative on the current standard two-tiered test algorithm (STTTA). To address this unmet need for improved diagnostics, we recently developed a diagnostic algorithm for Acute Lyme Disease using well characterized samples from the Lyme Disease Biobank [1] that gave 97% sensitivity and 100% specificity for clinically confirmed samples compared to endemic healthy donors (75 donors each). Our approach accommodates the person-to-person differences in the antibody response to Borrelia burgdorferi not covered by current clinical tests and provides 93% sensitivity and 100% specificity for patients suspected to have Lyme Disease compared to endemic healthy donors (75 donors each). Objective: A next generation Lyme Disease diagnostic will need to perform with high accuracy on previously undiagnosed patients and provide meaningful information to influence the physicians selected treatment. Here we will validate the accuracy of the developed algorithm in distinguishing Lyme Disease patients from healthy donors. We will further evaluate and refine the ability of the developed algorithm to distinguish Lyme Disease patients from those with diagnostically confounding diseases that require different treatments. Proposed Experiment: A set of new donor samples who have been either diagnosed with Acute Lyme Disease, have confounding look-alike diseases or are endemic healthy controls will be obtained. The sample population is expanded to include pediatric samples to assess utility across the intended use population. About one third (33%) of the Lyme disease and endemic controls samples will be provided blinded to mask the disease-state from the analysts. Also, 10 of the look-alike samples will be provided blinded. The rest of the samples will be provided unblinded, with ground truth and all relevant demographic and clinical data. All samples will be assayed on the V13 Antibody Profiling arrays using both anti-IgM and anti-IgG secondary antibodies for readout alongside a small set of representative samples from the training and control sets used in the original study. Assay control samples include a reference LD sample, a normal donor pool and secondary antibody alone to assess reproducibility and to enable normalization schemes to be evaluated. Representative samples are included from the training set to assess how generalizable the model is in a larger patient population. The use of both anti-IgG and anti-IgM secondary antibodies is proposed to assess the known variation in response in IgG and IgM antibodies in acute LD patients over time. Deliverable: Performance metrics (accuracy, sensitivity, and specificity) for the candidate classification algorithms/approaches to enable a go/no go decision on whether to advance the candidate algorithm from Feasibility Stage to Development Stage activities. Additional Analysis: The new data set will be used in combination with the existing data to potentially improve the existing models or examine the feasibility of potential other classification algorithms and biomarker discovery. Microarray Assay and Data Analysis - Revision 2 Choice 1: We run using the current binary analysis: Acute Lyme vs. Endemic Control and dont do the multiclass analysis with the different diseases and the human proteome Choice 2, we add the analysis of the other diseases and the human proteome as a multiclass approach One round of Luminex assays is defined as 50 antigens assayed using 300 samples in duplicates. There are currently 48 MagPlex bead addresses available for immediate shipment