Hyper-IgE Syndrome due to an Elusive Novel Intronic Homozygous Variant in DOCK8

Current genetic diagnostics in inborn errors of immunity

New technologies in genetic diagnostics have revolutionized the understanding and management of rare diseases. This review highlights the significant advances and latest developments in genetic diagnostics in inborn errors of immunity (IEI), which encompass a diverse group of disorders characterized by defects in the immune system, leading to increased susceptibility to infections, autoimmunity, autoinflammatory diseases, allergies, and malignancies. Various diagnostic approaches, including targeted gene sequencing panels, whole exome sequencing, whole genome sequencing, RNA sequencing, or proteomics, have enabled the identification of causative genetic variants of rare diseases. These technologies not only facilitated the accurate diagnosis of IEI but also provided valuable insights into the underlying molecular mechanisms. Emerging technologies, currently mainly used in research, such as optical genome mapping, single cell sequencing or the application of artificial intelligence will allow even more insights in the aetiology of hereditary immune defects in the near future. The integration of genetic diagnostics into clinical practice significantly impacts patient care. Genetic testing enables early diagnosis, facilitating timely interventions and personalized treatment strategies. Additionally, establishing a genetic diagnosis is necessary for genetic counselling and prognostic assessments. Identifying specific genetic variants associated with inborn errors of immunity also paved the way for the development of targeted therapies and novel therapeutic approaches. This review emphasizes the challenges related with genetic diagnosis of rare diseases and provides future directions, specifically focusing on IEI. Despite the tremendous progress achieved over the last years, several obstacles remain or have become even more important due to the increasing amount of genetic data produced for each patient. This includes, first and foremost, the interpretation of variants of unknown significance (VUS) in known IEI genes and of variants in genes of unknown significance (GUS). Although genetic diagnostics have significantly contributed to the understanding and management of IEI and other rare diseases, further research, exchange between experts from different clinical disciplines, data integration and the establishment of comprehensive guidelines are crucial to tackle the remaining challenges and maximize the potential of genetic diagnostics in the field of rare diseases, such as IEI.

ASACO: Automatic and Serial Analysis of CO-expression to discover gene modifiers with potential use in drug repurposing

Massive gene expression analyses are widely used to find differentially expressed genes under specific conditions. The results of these experiments are often available in public databases that are undergoing a growth similar to that of molecular sequence databases in the past. This now allows novel secondary computational tools to emerge that use such information to gain new knowledge. If several genes have a similar expression profile across heterogeneous transcriptomics experiments, they could be functionally related. These associations are usually useful for the annotation of uncharacterized genes. In addition, the search for genes with opposite expression profiles is useful for finding negative regulators and proposing inhibitory compounds in drug repurposing projects. Here we present a new web application, Automatic and Serial Analysis of CO-expression (ASACO), which has the potential to discover positive and negative correlator genes to a given query gene, based on thousands of public transcriptomics experiments. In addition, examples of use are presented, comparing with previous contrasted knowledge. The results obtained propose ASACO as a useful tool to improve knowledge about genes associated with human diseases and noncoding genes. ASACO is available at http://www.bioinfocabd.upo.es/asaco/.

Inborn Errors of Immunity: A Role for Functional Testing and Flow Cytometry in Aiding Clinical Diagnosis

With the exponential discovery of new inborn errors of immunity (IEI), it is becoming increasingly difficult to differentiate between a number of the more recently defined disorders. This is compounded by the fact that although IEI primarily present with immunodeficiency, the spectrum of disease is broad and often extends to features typical of autoimmunity, autoinflammation, atopic disease, and/or malignancy. Here we use case studies to discuss the laboratory and genetic tests used that ultimately led to the specific diagnoses.

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

Advances in next-generation sequencing technology have identified many genes responsible for inborn errors of immunity (IEI). However, there is still room for improvement in the efficiency of genetic diagnosis. Recently, RNA sequencing and proteomics using peripheral blood mononuclear cells (PBMCs) have gained attention, but only some studies have integrated these analyses in IEI. Moreover, previous proteomic studies for PBMCs have achieved limited coverage (approximately 3000 proteins). More comprehensive data are needed to gain valuable insights into the molecular mechanisms underlying IEI. Here, we propose a state-of-the-art method for diagnosing IEI using PBMCs proteomics integrated with targeted RNA sequencing (T-RNA-seq), providing unique insights into the pathogenesis of IEI. This study analyzed 70 IEI patients whose genetic etiology had not been identified by genetic analysis. In-depth proteomics identified 6498 proteins, which covered 63% of 527 genes identified in T-RNA-seq, allowing us to examine the molecular cause of IEI and immune cell defects. This integrated analysis identified the disease-causing genes in four cases undiagnosed in previous genetic studies. Three of them could be diagnosed by T-RNA-seq, while the other could only be diagnosed by proteomics. Moreover, this integrated analysis showed high protein-mRNA correlations in B- and T-cell-specific genes, and their expression profiles identified patients with immune cell dysfunction. These results indicate that integrated analysis improves the efficiency of genetic diagnosis and provides a deep understanding of the immune cell dysfunction underlying the etiology of IEI. Our novel approach demonstrates the complementary role of proteogenomic analysis in the genetic diagnosis and characterization of IEI.

De Novo Somatic Mosaicism of CYBB Caused by Intronic LINE-1 Element Insertion Resulting in Chronic Granulomatous Disease

Chronic granulomatosis disease (CGD) is a rare inborn error of immunity, characterized by phagocytic respiratory outbreak dysfunction. Mutations causing CGD occur in CYBB on the X chromosome and in the autosomal genes CYBA, NCF1, NCF2, NCF4, RAC2, and CYBC1. Nevertheless, some patients are clinically diagnosed with CGD, due to abnormal respiratory outbursts, while the pathogenic gene mutation is unidentified. Here, we report a patient with CGD who first presented with Bacillus Calmette-Guérin disease and had recurrent pneumonia. He was diagnosed with CGD by nitro blue tetrazolium and respiratory burst tests. Detailed assessment of neutrophil activity revealed that patient neutrophils were almost entirely nonfunctional. Sanger sequencing detected a 6-kb insertion of a LINE-1 transposable element in the third intron of CYBB, leading to abnormal splicing and pseudoexon insertion, as well as introduction of a premature termination codon, resulting in predicted protein truncation. Clonal analysis demonstrated that the patient had somatic mosaicism, and the phagocytes were almost all variant CYBB, while the mosaicism rate of PBMC was about 65%. Finally, deep RNA sequencing and gp91^phox expression analysis confirmed the pathogenicity of the mutation. In conclusion, we demonstrate that insertion of a LINE-1 transposon in a CYBB intron was responsible for CGD in our patient. Intron LINE-1 transposon element insertion should be examined in CGD patients without any known disease-causing gene mutation, in addition to identification of new genes.