D03 Circular rnas as potential biomarkers in huntington’s disease pathogenesis

Abstract

<h3>Background</h3> With the development of new therapies entering clinical trials for HD, there is an increasing need to develop and validate biomarkers in accessible biofluids, such as blood, to follow disease progression and predict treatment outcomes. Some biomarkers do exist; however, reliable and readily available additional ones will be crucial in assessing the pathogenic process and pharmacologic responses to therapeutic interventions. <h3>Aims</h3> For the first time in HD, we detect and characterize circRNAs in peripheral blood of a cohort of gender and age-matched controls and HD patients at various stages of the disease. We studied their potential as biomarkers by evaluating their correlation with disease progression and the size of the CAG repeat. <h3>Methods</h3> 50 blood samples were collected from both HD patients and a healthy cohort of individuals. Total RNA was used for RNA sequencing, and the obtained data were aligned with STAR. DCC program was used to quantify circRNAs and CircTest (R package) to identify differentially expressed circRNA between different disease stages and controls. CAG repeat size correlation was also tested. To validate our findings, candidate circRNAs were quantified via RT-qPCR in our samples. <h3>Results</h3> Our study led to the discovery of 7, stringently defined circRNAs that possess 3 characteristics: differentially expressed in HD patients (all up-regulated, p-value &lt; 0.05), correlated to CAG repeat size (|Pearson’s R| &gt; 0.3 and p-value &lt; 0.05) and have higher expression as the disease progresses. Using divergent primers, we quantified and validated via RT-qPCR the expression of subsets of circRNA candidates. <h3>Conclusions</h3> We identified for the first time circRNAs whose expression increases in the blood of HD patients. Currently, we aim to validate these circular molecules in independent blood cohorts as well as in cerebrospinal fluid and plasma samples to fully elucidate whether these highly stable RNA molecules could be used as disease biomarkers.