Single-Cell Sequencing: High-Resolution Analysis of Cellular Heterogeneity in Autoimmune Diseases

Clin Rev Allergy Immunol. 2024 Jun;66(3):376-400. doi: 10.1007/s12016-024-09001-6. Epub 2024 Aug 26.

Abstract

Autoimmune diseases (AIDs) are complex in etiology and diverse in classification but clinically show similar symptoms such as joint pain and skin problems. As a result, the diagnosis is challenging, and usually, only broad treatments can be available. Consequently, the clinical responses in patients with different types of AIDs are unsatisfactory. Therefore, it is necessary to conduct more research to figure out the pathogenesis and therapeutic targets of AIDs. This requires research technologies with strong extraction and prediction capabilities. Single-cell sequencing technology analyses the genomic, epigenomic, or transcriptomic information at the single-cell level. It can define different cell types and states in greater detail, further revealing the molecular mechanisms that drive disease progression. These advantages enable cell biology research to achieve an unprecedented resolution and scale, bringing a whole new vision to life science research. In recent years, single-cell technology especially single-cell RNA sequencing (scRNA-seq) has been widely used in various disease research. In this paper, we present the innovations and applications of single-cell sequencing in the medical field and focus on the application contributing to the differential diagnosis and precise treatment of AIDs. Despite some limitations, single-cell sequencing has a wide range of applications in AIDs. We finally present a prospect for the development of single-cell sequencing. These ideas may provide some inspiration for subsequent research.

Keywords: Autoimmune diseases; Heterogeneity; Multi-omics analysis; Single-cell sequencing.

Publication types

  • Review

MeSH terms

  • Animals
  • Autoimmune Diseases* / diagnosis
  • Autoimmune Diseases* / genetics
  • Autoimmune Diseases* / immunology
  • Gene Expression Profiling
  • High-Throughput Nucleotide Sequencing / methods
  • Humans
  • Sequence Analysis, RNA / methods
  • Single-Cell Analysis* / methods
  • Transcriptome