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Introduction: Sarcoidosis is a multi-system inflammatory disease of unknown origin with heterogeneous clinical manifestations varying from a single organ non-caseating granuloma site to chronic systemic inflammation and fibrosis. Gene expression studies have suggested several genes and pathways implicated in the pathogenesis of sarcoidosis, however, due to differences in study design and variable statistical approaches, results were frequently not reproducible or concordant. Therefore, meta-analysis of sarcoidosis gene-expression datasets is of great importance to robustly establish differentially expressed genes and signalling pathways. Methods: We performed meta-analysis on 22 published gene-expression studies on sarcoidosis. Datasets were analysed systematically using same statistical cut-offs. Differentially expressed genes were identified by pooling of p-values using Edgington's method and analysed for pathways using Ingenuity Pathway Analysis software. Results: A consistent and significant signature of novel and well-known genes was identified, those collectively implicated both type I and type II interferon mediated signalling pathways in sarcoidosis. In silico functional analysis showed consistent downregulation of eukaryotic initiation factor 2 signalling, whereas cytokines like interferons and transcription factor STAT1 were upregulated. Furthermore, we analysed affected tissues to detect differentially expressed genes likely to be involved in granuloma biology. This revealed that matrix metallopeptidase 12 was exclusively upregulated in affected tissues, suggesting a crucial role in disease pathogenesis. Discussion: Our analysis provides a concise gene signature in sarcoidosis and expands our knowledge about the pathogenesis. Our results are of importance to improve current diagnostic approaches and monitoring strategies as well as in the development of targeted therapeutics.
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OBJECTIVES: To test the hypothesis that ROSAH (retinal dystrophy, optic nerve oedema, splenomegaly, anhidrosis and headache) syndrome, caused by dominant mutation in ALPK1, is an autoinflammatory disease. METHODS: This cohort study systematically evaluated 27 patients with ROSAH syndrome for inflammatory features and investigated the effect of ALPK1 mutations on immune signalling. Clinical, immunologic and radiographical examinations were performed, and 10 patients were empirically initiated on anticytokine therapy and monitored. Exome sequencing was used to identify a new pathogenic variant. Cytokine profiling, transcriptomics, immunoblotting and knock-in mice were used to assess the impact of ALPK1 mutations on protein function and immune signalling. RESULTS: The majority of the cohort carried the p.Thr237Met mutation but we also identified a new ROSAH-associated mutation, p.Tyr254Cys.Nearly all patients exhibited at least one feature consistent with inflammation including recurrent fever, headaches with meningeal enhancement and premature basal ganglia/brainstem mineralisation on MRI, deforming arthritis and AA amyloidosis. However, there was significant phenotypic variation, even within families and some adults lacked functional visual deficits. While anti-TNF and anti-IL-1 therapies suppressed systemic inflammation and improved quality of life, anti-IL-6 (tocilizumab) was the only anticytokine therapy that improved intraocular inflammation (two of two patients).Patients' primary samples and in vitro assays with mutated ALPK1 constructs showed immune activation with increased NF-κB signalling, STAT1 phosphorylation and interferon gene expression signature. Knock-in mice with the Alpk1 T237M mutation exhibited subclinical inflammation.Clinical features not conventionally attributed to inflammation were also common in the cohort and included short dental roots, enamel defects and decreased salivary flow. CONCLUSION: ROSAH syndrome is an autoinflammatory disease caused by gain-of-function mutations in ALPK1 and some features of disease are amenable to immunomodulatory therapy.
Subject(s)
Hereditary Autoinflammatory Diseases , NF-kappa B , Protein Kinases/genetics , Amyloidosis , Animals , Cohort Studies , Gain of Function Mutation , Hereditary Autoinflammatory Diseases/genetics , Humans , Inflammation/genetics , Mice , Mutation , NF-kappa B/genetics , NF-kappa B/metabolism , Protein Kinases/metabolism , Quality of Life , Serum Amyloid A Protein , Syndrome , Tumor Necrosis Factor InhibitorsABSTRACT
INTRODUCTION: Non-small-cell lung cancer exhibits a range of transcriptional and epigenetic patterns that not only define distinct phenotypes, but may also govern immune related genes, which have a major impact on survival. METHODS: We used open-source RNA expression and DNA methylation data of the Cancer Genome Atlas with matched non-cancerous tissue to evaluate whether these pretreatment molecular patterns also influenced genes related to the immune system and overall survival. RESULTS: The distinction between lung adenocarcinoma and squamous cell carcinoma are determined by 1083 conserved methylation loci and RNA expression of 203 genes which differ for >80 % of patients between the two subtypes. Using the RNA expression profiles of 6 genes, more than 95 % of patients could be correctly classified as having either adeno or squamous cell lung cancer. Comparing tumor tissue with matched normal tissue, no differences in RNA expression were found for costimulatory and co-inhibitory genes, nor genes involved in cytokine release. However, genes involved in antigen presentation had a lower expression and a wider distribution in tumor tissue. DISCUSSION: Only a small number of genes, influenced by DNA methylation, determine the lung cancer subtype. The antigen presentation of cancer cells is dysfunctional, while other T cell immune functions appear to remain intact.
Subject(s)
Adenocarcinoma of Lung , Carcinoma, Non-Small-Cell Lung , Lung Neoplasms , Adenocarcinoma of Lung/genetics , Carcinoma, Non-Small-Cell Lung/diagnosis , Carcinoma, Non-Small-Cell Lung/genetics , DNA , DNA Methylation , Gene Expression Regulation, Neoplastic , Humans , Lung Neoplasms/diagnosis , Lung Neoplasms/geneticsABSTRACT
Background: Genetic tests for primary immunodeficiency disorders (PIDs) are expensive, time-consuming, and not easily accessible in developing countries. Therefore, we studied the feasibility of a customized single nucleotide variant (SNV) microarray that we developed to detect disease-causing variants and copy number variation (CNV) in patients with PIDs for only 40 Euros. Methods: Probes were custom-designed to genotype 9,415 variants of 277 PID-related genes, and were added to the genome-wide Illumina Global Screening Array (GSA). Data analysis of GSA was performed using Illumina GenomeStudio 2.0, Biodiscovery Nexus 10.0, and R-3.4.4 software. Validation of genotype calling was performed by comparing the GSA with whole-genome sequencing (WGS) data of 56 non-PID controls. DNA samples of 95 clinically diagnosed PID patients, of which 60 patients (63%) had a genetically established diagnosis (by Next-Generation Sequencing (NGS) PID panels or Sanger sequencing), were analyzed to test the performance of the GSA. The additional SNVs detected by GSA were validated by Sanger sequencing. Results: Genotype calling of the customized array had an accuracy rate of 99.7%. The sensitivity for detecting rare PID variants was high (87%). The single sample replication in two runs was high (94.9%). The customized GSA was able to generate a genetic diagnosis in 37 out of 95 patients (39%). These 37 patients included 29 patients in whom the genetic variants were confirmed by conventional methods (26 patients by SNV and 3 by CNV analysis), while in 8 patients a new genetic diagnosis was established (6 patients by SNV and 2 patients suspected for leukemia by CNV analysis). Twenty-eight patients could not be detected due to the limited coverage of the custom probes. However, the diagnostic yield can potentially be increased when newly updated variants are added. Conclusion: Our robust customized GSA seems to be a promising first-line rapid screening tool for PIDs at an affordable price, which opens opportunities for low-cost genetic testing in developing countries. The technique is scalable, allows numerous new genetic variants to be added, and offers the potential for genetic testing not only in PIDs, but also in many other genetic diseases.
Subject(s)
Genetic Testing/methods , Genotyping Techniques/methods , High-Throughput Nucleotide Sequencing/methods , Primary Immunodeficiency Diseases/genetics , Costs and Cost Analysis , DNA Copy Number Variations , Genotyping Techniques/economics , Humans , Polymorphism, Single Nucleotide , Reproducibility of ResultsABSTRACT
BACKGROUND: The atopic syndrome consists of heterogeneous manifestations, in which multiple associated genetic loci have recently been identified. It is hypothesized that immune dysregulation plays a role in the pathogenesis. In primary immunodeficiency diseases (PIDs), which are often monogenic immunodysregulation disorders, the atopic syndrome is a frequently occurring comorbidity. Based on the genetic defects in PIDs, novel gene/pathway-targeted therapies have been evaluated, which could be relevant in the atopic syndrome as well. Therefore, we aimed to define subclasses within the atopic syndrome based on the expression profiles of immune cell lineages of healthy mice. METHODS: Overlap between known atopy-related genes as described in the Human Gene Mutation Database and disease-causing genes of monogenic PIDs was evaluated. Clusters of atopy-related genes were based on the overlap in their co-expressed genes using the gene expression profiles of immune cell lineages of healthy mice from the Immunological Genome Project. We analyzed pathways involved in the atopic syndrome using Ingenuity Pathway Analysis. RESULTS: Twenty-two (5.3%) genes were overlapping between the atopy-related genes (n = 160) and PID-related genes (n = 278). We identified seven distinct clusters of atopy-related genes. Functional pathway analysis of all atopy-related genes showed relevance of T helper cell-mediated pathways. CONCLUSIONS: This study shows a model to define clusters within the atopic syndrome based on gene expression profiles of immune cell lineages. Our results support the hypothesis that both genetic mechanisms and immune dysregulation play a role in the pathogenesis. It also opens up the possibility for novel therapeutic targets and a more tailored approach towards personalized medicine.