ArticleCommunications biology2021
Transcriptomic analysis of immune cells in a multi-ethnic cohort of systemic lupus erythematosus patients identifies ethnicity- and disease-specific expression signatures.
Article in Communications biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 47 citations in OpenAlex.
- High-throughput transcriptome analyses from ASPIRO, a phase 1/2/3 study of gene replacement therapy for X-linked myotubular myopathy.American journal of human genetics · 2023Trial
- Artificial intelligence-enabled precision medicine for inflammatory skin diseases.The Journal of investigative dermatology · 2026Review
- Review
- Transcriptomic analysis reveals immune signatures associated with specific cutaneous manifestations of lupus in systemic lupus erythematosus.bioRxiv : the preprint server for biology · 2025Article
- Optical sorting: past, present and future.Light, science & applications · 2025Review
- Article
- Cell-Specific Transposable Element and Gene Expression Analysis Across Systemic Lupus Erythematosus Phenotypes.ACR open rheumatology · 2024Article
- Method of moments framework for differential expression analysis of single-cell RNA sequencing data.Cell · 2024Article
- Article
- Novel potential lncRNA biomarker in B cells indicates essential pathogenic pathway activation in patients with SLE.Lupus science & medicine · 2024Article
- Systemic lupus in the era of machine learning medicine.Lupus science & medicine · 2024Review
- Analysis of transcriptomic features reveals molecular endotypes of SLE with clinical implications.Genome medicine · 2023Article
- Glucose oxidation-dependent survival of activated B cells provides a putative novel therapeutic target for lupus treatment.iScience · 2023Article
- Differential regulation of the interferon response in systemic lupus erythematosus distinguishes patients of Asian ancestry.RMD open · 2023Article
- Molecular pathways identified from single nucleotide polymorphisms demonstrate mechanistic differences in systemic lupus erythematosus patients of Asian and European ancestry.Scientific reports · 2023Article
- Making inroads to precision medicine for the treatment of autoimmune diseases: Harnessing genomic studies to better diagnose and treat complex disorders.Cambridge prisms. Precision medicine · 2023Review
- Longitudinal Immune Cell Profiling in Patients With Early Systemic Lupus Erythematosus.Arthritis & rheumatology (Hoboken, N.J.) · 2022Article
- Multi-context genetic modeling of transcriptional regulation resolves novel disease loci.Nature communications · 2022Article
- The promise of precision medicine in rheumatology.Nature medicine · 2022Review
- Research perspectives-Pipelines to human tendon transcriptomics.Journal of orthopaedic research : official publication of the Orthopaedic Research Society · 2022Review
Corrections and comments
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Authors and funding
15 authors at 1 institution in 1 country.
Funding
Abstract
Systemic lupus erythematosus (SLE) is an autoimmune disease in which outcomes vary among different racial groups. We leverage cell-sorted RNA-seq data (CD14+ monocytes, B cells, CD4+ T cells, and NK cells) from 120 SLE patients (63 Asian and 57 White individuals) and apply a four-tier approach including unsupervised clustering, differential expression analyses, gene co-expression analyses, and machine learning to identify SLE subgroups within this multiethnic cohort. K-means clustering on each cell-type resulted in three clusters for CD4 and CD14, and two for B and NK cells. To understand the identified clusters, correlation analysis revealed significant positive associations between the clusters and clinical parameters including disease activity as well as ethnicity. We then explored differentially expressed genes between Asian and White groups for each cell-type. The shared differentially expressed genes across cells were involved in SLE or other autoimmune-related pathways. Co-expression analysis identified similarly regulated genes across samples and grouped these genes into modules. Finally, random forest classification of disease activity in the White and Asian cohorts showed the best classification in CD4+ T cells in White individuals. The results from these analyses will help stratify patients based on their gene expression signatures to enable SLE precision medicine.
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Registered trials
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