Improved Diagnosis of Primary Immunodeficiency
AIFA Primary Immunodeficiencies Research Grant 2019 (supported by CSL Behring)
Dr Tri Giang Phan, Garvan Institute of Medical Research, New South Wales.
Using machine-learning to improve the diagnostic accuracy and genotype-phenotype correlations in Primary Immunodeficiency Diseases.
Primary immunodeficiency diseases (PIDs) are rare inborn errors of immunity that are extremely difficult to diagnose and treat. Whole genome sequencing has revolutionised the diagnosis and treatment of many PID patients with the discovery of >354 disease-causing genes. This has enabled mechanism-based precision treatments that target the underlying genetic defect. However, as many as 58% of the 150 patients who have undergone whole genome sequencing by the Clinical Immunogenomics Research Consortium Australasia (CIRCA) still remain undiagnosed. A major reason for this has been the onerous, labour-intensive task of analysing the genomes which has resulted in slow turn-around-time to reporting of the genomes.
This project will use new machine-learning based bioinformatic tools to mine the patients' genomic data to discover new disease-causing mutations. Understanding how these mutations cause disease will provide opportunities to discover new ways to treat immune diseases and cancer.
Dr Tri Giang Phan was awarded $25,000.