Current status of use of high throughput nucleotide sequencing in rheumatology

Abstract

ObjectiveHere, we assess the usage of high throughput sequencing (HTS) in rheumatic research and the availability of public HTS data of rheumatic samples.MethodsWe performed a semiautomated literature review on PubMed, consisting of an R-script and manual curation as well as a manual search on the Sequence Read Archive for public available HTS data.ResultsOf the 699 identified articles, rheumatoid arthritis (n=182 publications, 26%), systemic lupus erythematous (n=161, 23%) and osteoarthritis (n=152, 22%) are among the rheumatic diseases with the most reported use of HTS assays. The most represented assay is RNA-Seq (n=457, 65%) for the identification of biomarkers in blood or synovial tissue. We also find, that the quality of accompanying clinical characterisation of the sequenced patients differs dramatically and we propose a minimal set of clinical data necessary to accompany rheumatological-relevant HTS data.ConclusionHTS allows the analysis of a broad spectrum of molecular features in many samples at the same time. It offers enormous potential in novel personalised diagnosis and treatment strategies for patients with rheumatic diseases. Being established in cancer research and in the field of Mendelian diseases, rheumatic diseases are about to become the third disease domain for HTS, especially the RNA-Seq assay. However, we need to start a discussion about reporting of clinical characterisation accompany rheumatological-relevant HTS data to make clinical meaningful use of this data.

Application of NGS Technology in Understanding the Pathology of Autoimmune Diseases

“…According to the authors, the most studied entities among the rheumatic diseases are rheumatoid arthritis, systemic lupus erythematous and osteoarthritis (OA). Whole exome sequencing (WES) and target panels are estimated to consist about 24% of applications used in high throughput methods used in research in rheumatology [ 72 ]. However, especially WES reveals high diagnostic potential.…”

Genetic variants related to systemic lupus erythematosus revealed using bioinformatics

“…Despite the large number of microarray SLE sequencing studies, most of the data are underutilized, leaving substantial information that has not been mined in-depth. 7 Therefore, in the present study, we conducted an integrated analysis by combining reported gene profile and immunochip data 8 to screen for SLE-related SNPs. This analysis can yield new reliable biomarkers to better understand the pathogenesis of SLE.…”