Alternative Splicing in White Blood Cells: A Biomarker for Fragile X Syndrome
Sneha Shah | Richter Lab | FRAXA Research Foundation Award
A long-sought goal in Fragile X Syndrome (FXS) research is the development of stable, robust, easily accessible, and quantifiable biomarkers for the disorder. Reliable biomarkers for FXS would address a number of issues that have hampered successful outcomes of some therapeutic trials. For example, several drugs used to treat FXS have been based on results from animal models, particularly one or two in-bred strains of mice. Although such therapeutics often strongly mitigate FXS-like pathophysiologies in mice, similar achievements have been noticeably less frequent in diverse human populations. These observations indicate that human-based biomarkers would more reliably predict outcomes of clinical trials. Human-based biomarkers could help stratify patient populations so that therapies could be targeted to certain individuals that would be most likely to respond in a positive way. Additionally, biomarkers that can be frequently tested and monitored are very helpful in determining drug response more effectively.
Our collaboration has sought to identify multiple strong FXS biomarkers in human white blood cells (WBCs) using a blood test. We find that FXS individuals (ages 12-38 years) display about 1600 statistically significant changes in RNA levels and alternative pre-mRNA processing (splicing) events. One of our goals is to determine whether similar RNA alterations are also detected in FXS children. Another goal is to assess whether WBC RNA levels and/or splicing can be predictive of cognitive ability. WBC RNA from FXS patients that have been stratified based on IQ scores will be deep sequenced and analyzed for differential expression and splicing. If we are able to successfully co-stratify IQ with RNA mis-regulation in WBCs, we will explore several new avenues of investigation. For example, we will ascertain whether drugs used to treat FXS patients alter the WBC RNA population and correlate with success of the drug and whether a specific RNA signature might be predictive of a drug therapy outcome.
