This technology is a method for detecting allelic expression biases that can be used to predict disease risk and discover therapeutic targets in monogenic disorders with incomplete clinical penetrance.
Testing for known disease-causing mutations in the DNA is used for both risk assessment and diagnosis in monogenic disorders, which are diseases caused by mutations in a single gene. However, many individuals with the disease-causing mutation do not develop the disease (termed incomplete penetrance) or exhibit variable symptoms, limiting the reliability of these genotype-based tests. A potential contributor to this variability is autosomal random monoallelic expression (aRMAE), which is the random commitment of somatic cells to expressing one allele. Understanding the role of aRMAE and incorporating it into genetics-based disease risk assessments could improve the accuracy and precision of these tests.
This technology is a method to detect the contribution of biased allelic expression or autosomal random monoallelic expression (aRMAE) to incomplete penetrance and variable expressivity in monogenic disorders. aRMAE genes for the monogenic immune disorders, called inborn errors of immunity (IEI), are identified by examining allelic-specific expression in clonal primary T cells derived from healthy individuals. By then comparing allelic-specific expression between immune cells of individuals with shared IEI mutations but discordant clinical phenotypes, selective or biased allelic expression patterns are observed to explain the incomplete penetrance and variability of phenotype severity in IEI.
This technology has been validated with immune clonal cell lines and/or immune cells from healthy individuals and patients in the context of IEI.
Patent Pending
IR CU25133
Licensing Contact: Jerry Kokoshka