Research and screening platform for Alzheimer?s and other chronic diseases

Period of Performance: 05/15/2017 - 04/30/2018

$300K

Phase 1 SBIR

Recipient Firm

Twistnostics
Baltimore, MD 21244
Principal Investigator

Abstract

Summary Early diagnosis of chronic diseases makes possible early treatment initiation. Bloodstream miRNA panels are being pursued for screening and diagnosis of the most important chronic diseases. Recently, there has been a particular interest in Alzheimer?s disease (AD) miRNA panels. If successful, these panels may become part of regular medical check-ups. However, their development and application is obstructed by the poor quantitative performance and complexity of available miRNA detection techniques such as reverse transcription quantitative polymerase chain reaction (RT-qPCR) and sequencing. Here, we propose the development of an accurate and simple platform for quantitative detection of miRNAs in blood that will accelerate the validation of miRNA panels and will be ideal for patient screening. We will validate the new platform by studying a specific miRNA panel associated with AD. We will develop a highly quantitative method to measure concentration of circulating miRNA based on direct detection, without purification and without enzymatic reactions. The method will be capable of highly quantitative measurements of miRNA in a variety of sample types. The first aim focuses on developing a method to detect 10 targets directly in unpurified samples. The second aim focuses on optimizing the quantitative performance of the assay, as well as validating the assay with clinical samples. This proposal will show that the new method can dramatically simplify and improve miRNA quantification. Our overall goal is to develop a powerful and flexible platform ideal for basic miRNA research and clinical diagnosis. In addition, the same platform will be useful to detect other targets, such as messenger-RNA and highly fragmented DNA with better quantitative performance, faster and easier to use than alternative methods.