ABSTRACT
A subset of spondyloarthritis (SpA) called ‘reactive arthritis’ is triggered by causal pathogens, usually bacteria related to venereal disease or gastrointestinal infection. During the outbreak of coronavirus disease 2019 (COVID-19), there have been case reports about SpA after COVID-19, but the causality is still elusive. We described cases of 23-year-old monozygotic twins both diagnosed with SpA after COVID-19. The probable linkage between SpA and COVID-19 was elaborated with our cases as well as literature reviews. Of note, shared genetic traits by monozygotic twins, particularly HLA-B27 positivity, might have contributed to their susceptibility to COVID-19-induced SpA. Moreover, single-cell transcriptome analysis revealed that the transcriptomic profile of peripheral compartment of SpA after COVID-19 was distinctive from that of typical radiographic axial SpA as shown by differential expression of ribosomal protein S26 (RPS26) and small nucleolar RNA host gene 5 (SNHG5) in nearly all subsets of peripheral blood mononuclear cells.
ABSTRACT
Next-generation sequencing (NGS) is widely used to identify the causative mutations underlying diverse human diseases, including cancers, which can be useful for discovering the diagnostic and therapeutic targets. Currently, a number of single-nucleotide variant (SNV)-calling algorithms are available; however, there is no tool for visualizing the recurrent and phenotype-specific mutations for general researchers. In this study, in order to support defining the recurrent mutations or phenotype-specific mutations from NGS data of a group of cancers with diverse phenotypes, we aimed to develop a user-friendly tool, named mutation arranger for defining phenotype-related SNV (MAP). MAP is a user-friendly program with multiple functions that supports the determination of recurrent or phenotype-specific mutations and provides graphic illustration images to the users. Its operation environment, the Microsoft Windows environment, enables more researchers who cannot operate Linux to define clinically meaningful mutations with NGS data from cancer cohorts.