Transcriptome Analysis of Peripheral Blood Mononuclear Cells in Pulmonary Sarcoidosis

The immunopathogenesis of sarcoidosis

Sarcoidosis is a granulomatous multiorgan disease, thought to result from exposure to yet unidentified antigens in genetically susceptible individuals. The exaggerated inflammatory response that leads to granuloma formation is highly complex and involves the innate and adaptive immune system. Consecutive immunological studies using advanced technology have increased our understanding of aberrantly activated immune cells, mediators and pathways that influence the formation, maintenance and resolution of granulomas. Over the years, it has become increasingly clear that disease immunopathogenesis can only be understood if the clinical heterogeneity of sarcoidosis is taken into consideration, along with the distribution of immune cells in peripheral blood and involved organs. Most studies offer an immunological snapshot during disease course, while the cellular composition of both the circulation and tissue microenvironment may change over time. Despite these challenges, novel insights on the role of the immune system are continuously published, thus bringing the field forward. This review highlights current knowledge on the innate and adaptive immune responses involved in sarcoidosis pathogenesis, as well as the pathways involved in non-resolving disease and fibrosis development. Additionally, we describe proposed immunological mechanisms responsible for drug-induced sarcoid like reactions. Although many aspects of disease immunopathogenesis remain to be unraveled, the identification of crucial immune reactions in sarcoidosis may help identify new treatment targets. We therefore also discuss potential therapies and future strategies based on the latest immunological findings.

Genetic predisposition to sarcoidosis

Sarcoidosis is a complex systemic disease with clinical heterogeneity based on varying phenotypes and natural history. The detailed etiology of sarcoidosis remains unknown, but genetic predisposition as well as environmental exposures play a significant role in disease pathogenesis. We performed a comprehensive review of germline genetic (DNA) and transcriptomic (RNA) studies of sarcoidosis, including both previous studies and more recent findings. In this review, we provide an assessment of the following: genetic variants in sarcoidosis susceptibility and phenotypes, ancestry- and sex-specific genetic variants in sarcoidosis, shared genetic architecture between sarcoidosis and other diseases, and gene-environment interactions in sarcoidosis. We also highlight the unmet needs in sarcoidosis genetic studies, including the pressing requirement to include diverse populations and have consistent definitions of phenotypes in the sarcoidosis research community to help advance the application of genetic predisposition to sarcoidosis disease risk and manifestations.

Integrative single-cell analysis of cardiac and pulmonary sarcoidosis using publicly available cardiac and bronchoalveolar lavage fluid sequencing datasets

Introduction

Cardiac presentation of autoimmune sarcoidosis, known as cardiac sarcoidosis (CS), is a poorly understood disease with high mortality and low diagnosis rate. While CS is an immunological syndrome, little is known about how cardiac parenchymal and stromal cells mediate its pathogenesis. Moreover, while most current sarcoidosis research is based on research in pulmonary sarcoidosis (PS), it remains unclear how much both presentations of sarcoidosis overlap. To tackle these concerns, we leveraged publicly available sarcoidosis transcriptomic datasets.

Methods

Two publicly available bronchoalveolar lavage single-cell RNA sequencing datasets were integrated to analyze PS relative to control. Additionally, two publicly available cardiac single-nucleus RNA sequencing datasets were integrated to analyze CS relative to control. Following integration, we ran cell-cell communication, transcription factor, and differential expression analyses on parenchymal, stromal, and immune subsets identified in our analysis.

Results

Our analysis revealed that there was an expansion of stromal and immune cells in PS and CS. We also observed upregulation of Th17.1 and attenuated activation transcriptional profiles in the immune cells of CS and PS relative to control. Additionally, we found upregulation of pro-inflammatory and pro-fibrotic transcriptional profiles in the cardiac stromal cells of CS relative to control. We also found that cardiomyocytes exhibited upregulated cardiac stress and proliferation transcriptional profiles in CS relative to control.

Conclusions

Our integrative transcriptomic analysis shows that despite tissue-specific differences, there are shared transcriptional trends between CS and PS. It also shows that stromal and parenchymal populations exhibit transcriptional trends that could explain their pathogenic role in CS.

Pulmonary Sarcoidosis: Experimental Models and Perspectives of Molecular Diagnostics Using Quantum Dots

Sarcoidosis is a complex inflammatory multisystem disease of unknown etiology that is characterised by epithelioid cell granulomatous lesions affecting various organs, mainly the lungs. In general, sarcoidosis is asymptomatic, but some cases result in severe complications and organ failure. So far, no accurate and validated modelling for clinical and pathohistological manifestations of sarcoidosis is suggested. Moreover, knowledge about disease-specific diagnostic markers for sarcoidosis is scarce. For instance, pulmonary granulomatosis is associated with the upregulated production of proinflammatory molecules: TNF-α, IL-6, CXCL1, CCL2, CCL18, CD163, serum angiotensin-converting enzyme (sACE), lysozyme, neopterin, and serum amyloid A (SAA). Quantum dots (QDs) are widely applied for molecular diagnostics of various diseases. QDs are semiconductor nanoparticles of a few nanometres in size, made from ZnS, CdS, ZnSe, etc., with unique physical and chemical properties that are useful for the labelling and detection in biological experiments. QDs can conjugate with various antibodies or oligonucleotides, allowing for high-sensitivity detection of various targets in organs and cells. Our review describes existing experimental models for sarcoidosis (in vitro, in vivo, and in silico), their advantages and restrictions, as well as the physical properties of quantum dots and their potential applications in the molecular diagnostics of sarcoidosis. The most promising experimental models include mice with TSC2 deletion and an in silico multiscale computational model of sarcoidosis (SarcoidSim), developed using transcriptomics and flow cytometry of human sarcoid biopsies. Both models are most efficient to test different candidate drugs for sarcoidosis.

Bat ASC2 suppresses inflammasomes and ameliorates inflammatory diseases

Bats are special in their ability to live long and host many emerging viruses. Our previous studies showed that bats have altered inflammasomes, which are central players in aging and infection. However, the role of inflammasome signaling in combating inflammatory diseases remains poorly understood. Here, we report bat ASC2 as a potent negative regulator of inflammasomes. Bat ASC2 is highly expressed at both the mRNA and protein levels and is highly potent in inhibiting human and mouse inflammasomes. Transgenic expression of bat ASC2 in mice reduced the severity of peritonitis induced by gout crystals and ASC particles. Bat ASC2 also dampened inflammation induced by multiple viruses and reduced mortality of influenza A virus infection. Importantly, it also suppressed SARS-CoV-2-immune-complex-induced inflammasome activation. Four key residues were identified for the gain of function of bat ASC2. Our results demonstrate that bat ASC2 is an important negative regulator of inflammasomes with therapeutic potential in inflammatory diseases.

Integrative bioinformatics analysis to explore a robust diagnostic signature and landscape of immune cell infiltration in sarcoidosis

Background

The unknown etiology of sarcoidosis with variable clinical features leads to delayed diagnosis and limited therapeutic strategies. Hence, exploring the latent mechanisms and constructing an accessible and reliable diagnostic model of sarcoidosis is vital for innovative therapeutic approaches to improve prognosis.

Methods

This retrospective study analyzed transcriptomes from 11 independent sarcoidosis cohorts, comprising 313 patients and 400 healthy controls. The weighted gene co-expression network analysis (WGCNA) and differentially expressed gene (DEG) analysis were performed to identify molecular biomarkers. Machine learning was employed to fit a diagnostic model. The potential pathogenesis and immune landscape were detected by bioinformatics tools.

Results

A 10-gene signature SARDS consisting of GBP1, LEF1, IFIT3, LRRN3, IFI44, LHFPL2, RTP4, CD27, EPHX2, and CXCL10 was further constructed in the training cohorts by the LASSO algorithm, which performed well in the four independent cohorts with the splendid AUCs ranging from 0.938 to 1.000. The findings were validated in seven independent publicly available gene expression datasets retrieved from whole blood, PBMC, alveolar lavage fluid cells, and lung tissue samples from patients with outstanding AUCs ranging from 0.728 to 0.972. Transcriptional signatures associated with sarcoidosis revealed a potential role of immune response in the development of the disease through bioinformatics analysis.

Conclusions

Our study identified and validated molecular biomarkers for the diagnosis of sarcoidosis and constructed the diagnostic model SARDS to improve the accuracy of early diagnosis of the disease.

Exome Sequencing Reveals Genetic Variability and Identifies Chronic Prognostic Loci in Chinese Sarcoidosis Patients

Background

Sarcoidosis is an inflammatory disease characterized by non-caseating granuloma formation in various organs, with several recognized genetic and environmental risk factors. Despite substantial progress, the genetic determinants associated with its prognosis remain largely unknown.

Objectives

This study aimed to identify the genetic changes involved in sarcoidosis and evaluate their clinical relevance.

Methods

We performed whole-exome sequencing (WES) in 116 sporadic sarcoidosis patients (acute sarcoidosis patients, n=58; chronic sarcoidosis patients, n=58). In addition, 208 healthy controls were selected from 1000 G East Asian population data. To identify genes enriched in sarcoidosis, Fisher exact tests were performed. The identified genes were included for further pathway analysis using Gene Ontology (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). Additionally, we used the STRING database to construct a protein network of rare variants and Cytoscape to identify hub genes of signaling pathways.

Results

WES and Fisher’s exact test identified 1,311 variants in 439 protein-coding genes. A total of 135 single nucleotide polymorphisms (SNPs) on 30 protein-coding genes involved in the immunological process based on the GO and KEGG enrichment analysis. Pathway enrichment analysis showed osteoclast differentiation and cytokine–cytokine receptor interactions. Three missense mutations (rs76740888, rs149664918, and rs78251590) in two genes (PRSS3 and CNN2) of immune-related genes showed significantly different mutation frequencies between the disease group and healthy controls. The correlation of genetic abnormalities with clinical outcomes using multivariate analysis of the clinical features and mutation loci showed that the missense variant (rs76740888, Chr9:33796673 G>A) of PRSS3 [p=0.04, odds ratio (OR) = 2.49] was significantly associated with chronic disease prognosis. Additionally, the top two hub genes were CCL4 and CXCR4 based on protein–protein interaction (PPI) network analysis.

Conclusion

Our study provides new insights into the molecular pathogenesis of sarcoidosis and identifies novel genetic alterations in this disease, especially PRSS3, which may be promising targets for future therapeutic strategies for chronic sarcoidosis.