Dissecting mechanisms of molecular convergence and variable expressivity in inborn errors of immunity

The National Institute of Allergy and Infectious Diseases awarded The Trustees of Columbia University in the City of New York $105,232 on December 9, 2026, under the Allergy and Infectious Diseases Research program (CFDA 93.855) to dissect mechanisms of molecular convergence and variable expressivity in inborn errors of immunity.

The research investigates why individuals with identical pathogenic variants in monogenic immunodeficiency disorders present with different clinical phenotypes, and why mutations in different genes produce overlapping clinical syndromes. The recipient will employ cell engineering and computational techniques to study functional effects of single nucleotide variants. Under Aim 1, researchers will validate molecular convergence as a shared therapeutic target across genetically diverse immunodeficiency disorders, testing therapeutic sensitivity of variants converging on the PI3K/AKT signaling axis to an FDA-approved small molecule inhibitor, paired with high-plex flow cytometry and single-cell transcriptomics to identify novel pathway interactions and shared therapeutic vulnerabilities. Under Aim 2, researchers will decipher how polygenic variants modulate variable expressivity using published polygenic risk scores and immune-cell expression quantitative trait loci, leveraging machine learning approaches.

Work is performed in New York, New York. The period of performance runs through June 30, 2030. The assistance type is Project Grant.

Abstract

Inborn errors of immunity (IEIS) are a diverse group of over 500 monogenic disorders characterized by recurrent infections, autoinflammation, allergy, autoimmunity and malignancy. Despite their monogenic etiology, individuals with identical pathogenic variants often present with different clinical phenotypes. However, the mechanisms underlying this variable expressivity remain poorly understood. At the same time, many IEI arising from mutations in different genes exhibit overlapping clinical syndromes, suggesting shared pathogenic mechanisms that could be leveraged for mutation-agnostic therapies. These complexities expose a critical GAP in our ability to predict disease course and personalize treatment for IEIS based on genotype. To address this, we have developed novel cell engineering and computational techniques to study the functional effects of single nucleotide variants. In preliminary studies, we found that variant gene products converge on common molecular outputs. We also demonstrated that existing population-level polygenic risk scores can be repurposed to estimate risk of specific immunophenotypes in rare IEIS. Building on these insights, we now propose in aim 1 to validate molecular convergence as a shared therapeutic target across genetically diverse IEIS. Specifically, we will test therapeutic sensitivity of variants that converge on the PI3K/AKT signaling axis to an FDA-approved small molecule inhibitor of the pathway. We will also pair this with high-plex flow cytometry and single cell transcriptomics to identify novel pathway interactions that will highlight further shared therapeutic vulnerabilities. In aim 2, we will decipher how polygenic variants modulate variable expressivity. Using published polygenic risk scores and immune-cell expression quantitative trait loci (EQTLS), we will leverage an innovative machine learning framework to identify pathways through which polygenic variants shape immune dysregulation in IEIS. We will then validate key computational findings through both immunophenotype association studies in IEI cohorts and base-editing experiments in primary T cells. This integrative approach combines functional genomics, population genetics, and machine-learning to reveal how common variants intersect with monogenic lesions to influence immune phenotypes. By identifying pathway-convergent therapeutic targets and genetic modifiers of expressivity, the project aims to inform prognostic models and expand application of precision therapies. This aligns directly with the agency's mission to advance our understanding of immunologic disorders and improve health outcomes. With access to world-class mentorship in computational biology and immunology at columbia, this project will provide a strong foundation for a career as a future physician-scientist.