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

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

PROVIDER: PRJNA1271497 | ENA |

REPOSITORIES: ENA

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			Action	DRS
	SRR33813100.fastq.gz	Fastqsanger.gz
	SRR33813101.fastq.gz	Fastqsanger.gz
	SRR33813102.fastq.gz	Fastqsanger.gz
	SRR33813103.fastq.gz	Fastqsanger.gz
	SRR33813104.fastq.gz	Fastqsanger.gz

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

Project description: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 validated 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.

2025-06-05 | GSE298853 | GEO

Demonstration of a complementary approach for genetic diagnosis of inborn errors of immunity using proteogenomic analysis

Project description:Genetic diagnosis plays a central role in the clinical management of patients with inborn errors of immunity (IEI). We proposed a novel method for diagnosing IEI using PBMC proteomics integrated with targeted RNA sequencing, providing notable insights into the pathogenesis of IEI. Data-independent acquisition mass spectrometry was performed on PBMC from 70 IEI patients without genetic diagnosis and six healthy controls.

2023-11-25 | PXD038352 | JPOST Repository

The NIH MINI Study: Metabolism, Infection, and Immunity in Inborn Errors of Mitochondrial Metabolism

Project description:The NIH MINI Study: Metabolism, Infection, and Immunity in Inborn Errors of Mitochondrial Metabolism

| PRJNA971742 | ENA

The NIH MINI Study: Metabolism, Infection, and Immunity in Inborn Errors of Mitochondrial Metabolism

Project description:The NIH MINI Study: Metabolism, Infection, and Immunity in Inborn Errors of Mitochondrial Metabolism

| PRJNA971743 | ENA

Molecular Assessment of S. aureus strains in patients with inborn errors of immunity by WGS

Project description:Molecular Assessment of S. aureus strains in patients with inborn errors of immunity by WGS

| PRJEB52061 | ENA

cGAS-mediated induction of type I interferon due to inborn errors of histone pre-mRNA processing

Project description:cGAS-mediated induction of type I interferon due to inborn errors of histone pre-mRNA processing

| PRJNA641394 | ENA

Human Inborn Errors of Immunity: 2019 Update of the IUIS Phenotypical Classification.

Project description:Since 2013, the International Union of Immunological Societies (IUIS) expert committee (EC) on Inborn Errors of Immunity (IEI) has published an updated phenotypic classification of IEI, which accompanies and complements their genotypic classification into ten tables. This phenotypic classification is user-friendly and serves as a resource for clinicians at the bedside. There are now 430 single-gene IEI underlying phenotypes as diverse as infection, malignancy, allergy, autoimmunity, and autoinflammation. We herein report the 2019 phenotypic classification, including the 65 new conditions. The diagnostic algorithms are based on clinical and laboratory phenotypes for each of the ten broad categories of IEI.

| S-EPMC7082388 | biostudies-literature

Genetic diagnosis of inborn errors of immunity using clinical exome sequencing.

Project description:Inborn errors of immunity (IEI) include a variety of heterogeneous genetic disorders in which defects in the immune system lead to an increased susceptibility to infections and other complications. Accurate, prompt diagnosis of IEI is crucial for treatment plan and prognostication. In this study, clinical utility of clinical exome sequencing (CES) for diagnosis of IEI was evaluated. For 37 Korean patients with suspected symptoms, signs, or laboratory abnormalities associated with IEI, CES that covers 4,894 genes including genes related to IEI was performed. Their clinical diagnosis, clinical characteristics, family history of infection, and laboratory results, as well as detected variants, were reviewed. With CES, genetic diagnosis of IEI was made in 15 out of 37 patients (40.5%). Seventeen pathogenic variants were detected from IEI-related genes, BTK, UNC13D, STAT3, IL2RG, IL10RA, NRAS, SH2D1A, GATA2, TET2, PRF1, and UBA1, of which four variants were previously unreported. Among them, somatic causative variants were identified from GATA2, TET2, and UBA1. In addition, we identified two patients incidentally diagnosed IEI by CES, which was performed to diagnose other diseases of patients with unrecognized IEI. Taken together, these results demonstrate the utility of CES for the diagnosis of IEI, which contributes to accurate diagnosis and proper treatments.

| S-EPMC10264570 | biostudies-literature

"Transcriptomics": molecular diagnosis of inborn errors of metabolism via RNA-sequencing.

Project description:Exome wide sequencing techniques have revolutionized molecular diagnostics in patients with suspected inborn errors of metabolism or neuromuscular disorders. However, the diagnostic yield of 25-60% still leaves a large fraction of individuals without a diagnosis. This indicates a causative role for non-exonic regulatory variants not covered by whole exome sequencing. Here we review how systematic RNA-sequencing analysis (RNA-seq, "transcriptomics") lead to a molecular diagnosis in 10-35% of patients in whom whole exome sequencing failed to do so. Importantly, RNA-sequencing based discoveries cannot only guide molecular diagnosis but might also unravel therapeutic intervention points such as antisense oligonucleotide treatment for splicing defects as recently reported for spinal muscular atrophy.

| S-EPMC5959960 | biostudies-literature

Rare genetic variants affecting urine metabolite levels link population variation to inborn errors of metabolism

Project description:We investigated the cumulative contribution of rare, exonic genetic variants on the concentration of 1,487 metabolites and 53,714 metabolite ratios in urine by performing gene-based tests based on 226,233 variants from up to 4,864 participants of the German Chronic Kidney Disease (GCKD) study. There were 128 significant associations (53 metabolite-gene and 75 metabolite ratio-gene pairs) involving 30 unique genes, 16 of which are known to underlie recessively inherited inborn errors of metabolism (IEMs). Across the 30 genes, 47% of individuals carried at least one rare missense, stop or splice variant. The 30 genes were strongly enriched for shared high expression in liver and kidney (OR=65, p-FDR=3e-7), with hepatocytes and proximal tubule cells as driving cell types. Use of whole-exome sequencing data in the UK Biobank allowed for linking genes to diseases that could plausibly be explained by the identified metabolites. In silico constraint-based modeling of knockouts of the implicated genes in a virtual whole-body, organ-resolved metabolic human correctly predicted the observed direction of metabolite changes in urine and blood, highlighting the potential of linking population genetics to modeling to validate associations and to predict metabolic consequences of yet unknown IEMs. Our study extends the map of genes influencing urine metabolite concentrations, reveals metabolic processes and connected health outcomes, and implicates novel candidate variants and genes for IEMs. Further links;<a href='https://www.gckd.org/' rel='noopener noreferrer' target='_blank'>German Chronic Kidney Disease (GCKD)</a>

2021-03-09 | MTBLS284 | MetaboLights

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