MacPhail, K. | bioRxiv Science

bioRxiv2025

Single Cell Transcriptome Signatures of Sarcoidosis in Lung Immune Cell Populations

RationaleTo identify cell specific molecular changes associated with sarcoidosis risk and progression, we aimed to characterize the cellular composition, gene expression patterns, and cell-cell interactions in BAL cells from patients with sarcoidosis (both progressive and non-progressive) and healthy controls. MethodsSingle cell RNA-seq data were collected on 12 sarcoidosis and 4 control participants. We combined scRNA-seq data from these participants with our previously collected data on 4 sarcoidosis and 10 control participants for a final sample size of 16 sarcoidosis cases (8 progressive and 8 non-progressive) and 14 controls. Following initial preprocessing in CellRanger, data were quality controlled, combined, and clustered in Seurat. We tested differences in cell proportions by disease group using F-tests on cell proportions and differences in gene expression using pseudobulk analysis. Cell to cell communication and pathway analysis were performed using CellChat. ResultsWe identified five macrophage populations: resident, high metallothionein (MT) resident, recruited, profibrotic recruited, and proliferating macrophages. Each subpopulation displayed unique gene expression profiles, with notable differential expression of genes and pathways linked to sarcoidosis in resident macrophages, recruited macrophages, and proliferating macrophages. We also observed changes in gene expression associated with disease progression in resident and recruited macrophages. In non-macrophages cells, we observed a significant reduction in the number of B cells in sarcoidosis patients compared to controls. Among T cell populations, we identified specific transcriptional alterations at gene and pathway level. Additionally, we observed distinct differences in cell-to-cell interactions of macrophages and T cells between sarcoidosis patients and healthy controls. ConclusionsThese findings underscore the complexity of immune cell involvement in sarcoidosis and highlight potential cellular and molecular targets for further investigation.

genomics↗

bioRxiv2023

Multi-Omic Signatures of Sarcoidosis and Progression in Bronchoalveolar Lavage Cells

IntroductionSarcoidosis is a heterogeneous, granulomatous disease that can prove difficult to diagnose, with no accurate biomarkers of disease progression. Therefore, we profiled and integrated the DNA methylome, mRNAs, and microRNAs to identify molecular changes associated with sarcoidosis and disease progression that might illuminate underlying mechanisms of disease and potential genomic biomarkers. MethodsBronchoalveolar lavage cells from 64 sarcoidosis subjects and 16 healthy controls were used. DNA methylation was profiled on Illumina HumanMethylationEPIC arrays, mRNA by RNA-sequencing, and miRNAs by small RNA-sequencing. Linear models were fit to test for effect of diagnosis and phenotype, adjusting for age, sex, and smoking. We built a supervised multi-omics model using a subset of features from each dataset. ResultsWe identified 46,812 CpGs, 1,842 mRNAs, and 5 miRNAs associated with sarcoidosis versus controls and 1 mRNA, SEPP1 - a protein that supplies selenium to cells, associated with disease progression. Our integrated model emphasized the prominence of the PI3K/AKT1 pathway in sarcoidosis, which is important in T cell and mTOR function. Novel immune related genes and miRNAs including LYST, RGS14, SLFN12L, and hsa-miR-199b-5p, distinguished sarcoidosis from controls. Our integrated model also demonstrated differential expression/methylation of IL20RB, ABCC11, SFSWAP, AGBL4, miR-146a-3p, and miR-378b between non-progressive and progressive sarcoidosis. ConclusionsLeveraging the DNA methylome, transcriptome, and miRNA-sequencing in sarcoidosis BAL cells, we detected widespread molecular changes associated with disease, many which are involved in immune response. These molecules may serve as diagnostic/prognostic biomarkers and/or drug targets, although future testing will be required for confirmation.

genomics↗