Previous work has demonstrated that a cohort-based WGS approach to PID diagnosis can discover new PID-associated genes in a previously genetically inaccessible patient group, increasing diagnostic yield while deepening our understanding of the key pathways influencing human immune responsiveness [1]. It shows it is possible to discover monogenic causes of sporadic PID, and to explain the contribution of common and non-coding variants to its variable penetrance and phenotypic complexity. We now aim to build on this foundation, through the development of novel integrative methodology, to better understand the genetic underpinning of PID and related diseases while, at the same time, refining a cohort-based WGS approach to deliver PID diagnosis in the clinic.
Project aims:
- Develop new analytic methodologies for WGS data in sporadic PID.
- Understand the genetic complexity of PID, discovering new monogenic causes and defining the roles of both non-coding and rare variants.
- Provide a blueprint for diagnostic use of WGS in the health care system
- Develop a publicly-accessible database, enabling exploration of new genes and pathways.
- Deliver potentially life-changing genetic diagnoses.
- Prime development of novel personalised therapeutic approaches.
- Provide a health economic assessment of the use of WGS for PID
Our research is split into 6 work packages
WP1:
Clinical Phenotype and Diagnostic Yield in WGS Analysis from a PID Cohort
Leads: Siobhan Burns, Adrian Thrasher
WP2:
Immune-Phenotyping
Lead: Christoph Hess
WP3:
B Cell and T Cell Repertoire Analysis
Lead: Rachael Bashford-Rogers
WP4:
Statistical Integration of WGS, Clinical and Immune Phenotype Data in PID
Lead: Sylvia Richardson.
Co-lead: Ernest Turro
WP5:
Exploiting Large Datasets to Understand the Genetics and Clinical Heterogeneity of PID
Co-leads: Chris Wallace, Ken Smith.
WP6:
Health Economic Assessment of WGS as a Diagnostic Service for PID
Lead: Sarah Wordsworth.