Scalable generation and functional classification of genetic variants in inborn errors of immunity to accelerate clinical diagnosis and treatment

Abstract

Next-generation sequencing is pivotal for diagnosing inborn errors of immunity (IEI) but predominantly yields variants of uncertain significance (VUS), creating clinical ambiguity. Activated PI3Kδ syndrome (APDS) is caused by gain-of-function (GOF) variants in PIK3CD or PIK3R1, which encode the PI3Kδ heterodimer. We performed massively parallel base editing of PIK3CD/PIK3R1 in human T cells and mapped thousands of variants to a clinically important readout (phospho-AKT/S6), nominating >100 VUS and unannotated variants for functional classification and validating 27 hits. Leniolisib, an FDA-approved PI3Kδ inhibitor, rescued aberrant signaling and dysfunction in GOF-harboring T cells and revealed partially drug-resistant PIK3R1 hotspots that responded to novel combination therapies of leniolisib with mTORC1/2 inhibition. We confirmed these findings in T cells from APDS patients spanning the functional spectrum discovered in the screen. Integrating our screens with population-level genomic studies revealed that APDS may be more prevalent than previously estimated. This work exemplifies a broadly applicable framework for removing ambiguity from sequencing in IEI.

Keywords: APDS; CRISPR base editing; VUS; activated PI3K delta syndrome; clinical NGS; genome engineering; inborn errors of immunity; precision medicine; primary T cells; variant classification.