Identification of candidate disease genes in patients with common variable immunodeficiency

Revealing disease subtypes and heterogeneity in common variable immunodeficiency through transcriptomic analysis

Common Variable Immunodeficiency (CVID) is a primary immunodeficiency characterized by reduced levels of specific immunoglobulins, resulting in frequent infections, autoimmune disorders, increased cancer risk, and diminished antibody production despite an adequate B cell count. With its clinical manifestations being highly variable, the classification of CVID, including the widely recognized Freiburg classification, is primarily based on clinical symptoms and genetic variations. Our study aims to refine the classification of CVID by analyzing transcriptomics data to identify distinct disease subtypes. We utilized the GSE51405 dataset, examining transcriptomic profiles from 30 CVID patients without complications. Employing a combination of clustering techniques-KMeans, hierarchical agglomerative clustering, spectral clustering, and Gaussian Mixture models-and differential gene expression analysis with R's limma package, we integrated molecular findings with demographic data (age and gender) through correlation analysis and identified common genes among clusters. Three distinct clusters of CVID patients were identified using KMeans, Agglomerative Clustering, and Gaussian Mixture Models, highlighting the disease's heterogeneity. Differential expression analysis unveiled 31 genes with variable expression levels across these clusters. Notably, nine genes (EIF5A, RPL21, ANP32A, DTX3L, NCF2, CDC42EP3, CHP1, FOLR3, and DEFA4) exhibited consistent differential expression across all clusters, independent of demographic factors. The study recommends categorizing patients based on the four genes, NCF2, CHP1, FOLR3, and DEFA4-as they may assist in prognostic prediction. Transcriptomic analysis of common variable immunodeficiency (CVID) patients identified three distinct clusters based on gene expression, independent of age and gender. Nine differentially expressed genes were identified across these clusters, suggesting potential biomarkers for CVID subtype classification. These findings highlight the genetic heterogeneity of CVID and provide novel insights into disease classification and potential personalized treatment approaches.

Exploring gastric cancer genetics: A turning point in common variable immunodeficiency

Background

Gastric cancer (GC) stands as a prominent cause of cancer-related mortality and ranks second among the most frequently diagnosed malignancies in individuals with common variable immunodeficiency (CVID).

Objective

We sought to conduct a comprehensive, large-scale genetic analysis to explore the CVID-associated germline variant landscape within gastric adenocarcinoma samples and to seek to delineate the transcriptomic similarities between GC and CVID.

Methods

We investigated the presence of CVID-associated germline variants in 1591 GC samples and assessed their impact on tumor mutational load. The progression of GC was evaluated in patients with and without these variants. Transcriptomic similarities were explored by matching differentially expressed genes in GC to healthy gastric tissue with a CVID transcriptomic signature.

Results

CVID-associated germline variants were found in 60% of GC samples. Our analysis revealed a significant association between the presence of CVID-related genetic variants and higher tumor mutational load in GC (P < .0001); high GC mutational load seems to be linked to immunotherapy response and worse prognosis. Transcriptomic similarities unveiled key genes and pathways implicated in innate immune responses and tumorigenesis. We identified upregulated genes related to oncogene drivers, inflammation, tumor suppression, DNA repair, and downregulated immunomodulatory genes shared between GC and CVID.

Conclusions

Our findings contribute to a deeper understanding of potential molecular modulators of GC and shed light on the intricate interplay between immunodeficiency and cancer. This study underscores the clinical relevance of CVID-related variants in influencing GC progression and opens avenues for further exploration into novel therapeutic approaches.

Genomic crossroads between non-Hodgkin's lymphoma and common variable immunodeficiency

Common variable immunodeficiency (CVID) represents the largest group of primary immunodeficiencies that may manifest with infections, inflammation, autoimmunity, and cancer, mainly B-cell non-Hodgkin's lymphoma (NHL). Indeed, NHL may result from chronic or recurrent infections and has, therefore, been recognized as a clinical phenotype of CVID, although rare. The more one delves into the mechanisms involved in CVID and cancer, the stronger the idea that both pathologies can be a reflection of the same primer events observed from different angles. The potential effects of germline variants on specific somatic modifications in malignancies suggest that it might be possible to anticipate critical events during tumor development. In the same way, a somatic alteration in NHL could be conditioning a similar response at the transcriptional level in the shared signaling pathways with genetic germline alterations in CVID. We aimed to explore the genomic substrate shared between these entities to better characterize the CVID phenotype immunodeficiency in NHL. By means of an in-silico approach, we interrogated the large, publicly available datasets contained in cBioPortal for the presence of genes associated with genetic pathogenic variants in a panel of 50 genes recurrently altered in CVID and previously described as causative or disease-modifying. We found that 323 (25%) of the 1,309 NHL samples available for analysis harbored variants of the CVID spectrum, with the most recurrent alteration presented in NHL occurring in PIK3CD (6%) and STAT3 (4%). Pathway analysis of common gene alterations showed enrichment in inflammatory, immune surveillance, and defective DNA repair mechanisms similar to those affected in CVID, with PIK3R1 appearing as a central node in the protein interaction network. The co-occurrence of gene alterations was a frequent phenomenon. This study represents an attempt to identify common genomic grounds between CVID and NHL. Further prospective studies are required to better know the role of genetic variants associated with CVID and their reflection on the somatic pathogenic variants responsible for cancer, as well as to characterize the CVID-like phenotype in NHL, with the potential to influence early CVID detection and therapeutic management.