Applying Bioinformatics to Research in Immune, Muscle, and Bone Diseases

National Institute Of Arthritis And Musculoskeletal And Skin Diseases

Investigators

Linked publications & trials

Abstract

The Biodata Mining and Discovery Section projects are listed below, including major accomplishments: - Study of constitutively active Lyn kinase in autoinflammatory diseases Monogenic autoinflammatory diseases are often caused by mutations in signaling molecules. In this study, three unrelated boys were found to have mutations leading to constitutively active Lyn tyrosine kinase with small vessel vasculitis and liver fibrosis. A SRC family kinase inhibitor, dasatinib, was found to effectively reverse liver transcriptome dysregulation which led to reduction in symptoms. - Chromatin landscape governing murine epidermal differentiation Epidermal differentiation is driven by changes in transcriptome that are regulated by changes in chromatin landscape and regulatory networks. This study provides a comprehensive view of transcriptome, chromatin accessibility, chromatin architecture, histone modification and Dlx3 regulation in mouse epidermal development. - Role of Mitomycin C in corneal wound repair Mitomycin C is a chemotherapeutic agent used to treat various types of cancers. It is also known to reduce scarring and fibrosis in response to eye surgery. In this study, we show that corneal epithelial cells respond to soluble secretions from transient treatment with Mitomycin C. Among these are IL-1a and TGFb1. These lead to increased expression of phagocytosis related genes. - Role of STAT5 in transcriptional programming of T helper cell metabolism Activation of T helper cells leads to rapid changes in transcriptome related to metabolism in order to meet the energetic and biosynthetic demands required by rapid growth and proliferation. In this study, genome, transcriptome and metabolome analysis were used to determine that STAT5 is a master regulator of energy and amino acid metabolism in CD4+ T helper cells. - Gene expression studies of arthritis patients treated with different drugs Gene expression profiles from peripheral blood mononuclear cell (PBMC) samples of 101 arthritis patients treated with three distinct drugs were examined using RNA-seq. Data were collected at multiple time points, encompassing both treatment cessation and three months thereafter. The gene expression data were employed to construct computational models aimed at predicting patients' status, whether experiencing flares or remaining in remission, three months after drug treatment cessation. Additionally, these models were utilized to pinpoint potential biomarkers. This project is currently ongoing, with plans to include and analyze additional samples. - Natural history of coronavirus (COVID-19) in systemic autoimmune diseases: an observational prospective study This study aims to understand the immune drivers and the clinical consequences of autoimmune disease patients exposed to either COVID infection or COVID vaccine. We are currently processing RNA-Seq data from over 200 patients and healthy controls. Both inference statistics and machine learning will be employed for downstream data analysis. - Chromatin landscape and regulatory networks in lineage specification and differentiation Through the analysis of datasets that profiled expression dynamics (RNA-seq), chromatin accessibility (ATAC-seq), architecture (Hi-C), and histone modifications (ChIP-seq) in the epidermis, the temporospatial differentiation axis in murine epidermal cells was defined in vivo. - Exploratory analysis to identify the putative role of a novel JAK1 mutation in the onset of Lupus The onset of Lupus is typically seen in females. In this unique case, a male in his 40s was diagnosed. Sequencing found a novel JAK1 variant. scRNA-seq explored impact, including data from the patient, as well as healthy and patient (without the mutation) controls. It was found that JAK1 variant cells resembled the healthy control more than the patient control. Differentially expressed genes on a JAK1-centered PPI network showed 80% perturbation, hinting at the variant's role in disease. - Exploring cellular dynamics through scRNA-Seq in Systemic Juvenile Idiopathic Arthritis (SJIA). Systemic Juvenile Idiopathic Arthritis (SJIA) affects children. PBMCs from patients and controls were studied with scRNA-seq. Azimuth R package ensured confident cell cluster annotations. Differential gene expression analysis highlighted new pathways in SJIA samples. Patient transcriptome diversity challenged conventional analysis. Innovative pipeline identified patient-specific gene markers against controls. Enrichment analysis revealed pathways underlying the onset of SJIA. - Role of RNA G-quadruplex structures in cancer Bioinformatics analysis of the human genome sequence identified genes with high (>4) and low (<3) numbers of G-quadruplex structures. Conservation analysis across seven mammals, as obtained from the UCSC Genome Browser, revealed that genes with a high number of G-quadruplex structures are more highly conserved. Currently, we are investigating the role of these highly conserved structures in gene expression within cancer cells. - Regulation of PRMT1 gene in B cell fate in germinal center We have hypothesized that positively selected germinal center B cells determine their fate for proliferation or differentiation. Based on the observed high-level expression of PRMT1 in germinal B cells, a PRMT1-specific knockout mouse model was generated, elucidating PRMT1's necessity in expanding germinal center B cells, advancing affinity maturation, and contributing to memorial B cell formation, plasma cell differentiation, and B cell lymphoma differentiation. Analysis of the publicly available scRNA-seq data revealed the up-regulation of PRMT1 in positively selected germinal center B cells after infection. - Deciphering transcriptional regulation in diffuse large B cell lymphoma (DLBCL) using genome-wide CRISPR/Cas9 screens To better understand gene regulation in DLBCL, the most common aggressive lymphoma, 47 super-enhancer-controlled genes important for B cell biology were screened in the DLBCL cell line SU-DHL-4 using CRISPR/Cas9. Around 1500 activators and repressors were found across the genes, along with 884 dual-function regulators. This reveals complex multilayered gene regulation in DLBCL, providing insights into the disease while identifying potential therapeutic targets. One key finding is AFF2 as a regulator highly expressed in germinal center B cells. - Investigation of rare variants in NIAMS Stills disease cohort We performed WES joint variant calling in 964 NIAMS sJIA/Adult-onset Still disease patients and 2952 NIH database of Genotypes and Phenotypes controls. We also performed data Quality Control (QC) and initial analysis, providing guidance on rare variant enrichment analysis for the cohort. - Family-based mutation analysis in NIAMS Whole Exome Sequencing (WES) cohort We performed trio-based and custom-made mutation analysis in more than 30 NIAMS patients with various diseases. And we identified mutations in biologically interesting genes such as FANCM, TLR7, KMT2D and CSK. - Investigation of somatic mutations in vasculitis patients We performed somatic and germline variant calls in patients with medium vessel vasculitis, blood clots, and hypereosinophilia with a CD3-CD4+ T cell clone. And we developed a variant prioritization strategy and provided consultation on mutation analysis. - Enhancing the current RNA-seq pipeline We have enhanced the existing RNA-seq data processing and analysis pipeline by incorporating comprehensive QC checks and visualization techniques. This pipeline is powered by the SNAKEMAKE framework, offering efficient workflow management. It encompasses over 15 Python and R scripts for data parsing and visualization throughout multiple data generation and analysis stages.