{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,12]],"date-time":"2026-09-12T06:37:09Z","timestamp":1789195029238,"version":"build-2803163510"},"reference-count":107,"publisher":"BMJ","issue":"1","license":[{"start":{"date-parts":[[2021,1,4]],"date-time":"2021-01-04T00:00:00Z","timestamp":1609718400000},"content-version":"unspecified","delay-in-days":3,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"We wish to acknowledge the RARENET EU-Interreg for supporting this study."}],"content-domain":{"domain":["bmj.com"],"crossmark-restriction":true},"short-container-title":["RMD Open"],"accepted":{"date-parts":[[2020,11,24]]},"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:sec>\n                  <jats:title>Objective<\/jats:title>\n                  <jats:p>Here, we assess the usage of high throughput sequencing (HTS) in rheumatic research and the availability of public HTS data of rheumatic samples.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Methods<\/jats:title>\n                  <jats:p>We 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.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Of 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.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Conclusion<\/jats:title>\n                  <jats:p>HTS 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.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1136\/rmdopen-2020-001324","type":"journal-article","created":{"date-parts":[[2021,1,6]],"date-time":"2021-01-06T12:10:21Z","timestamp":1609935021000},"page":"e001324","update-policy":"https:\/\/doi.org\/10.1136\/crossmarkpolicy","source":"Crossref","is-referenced-by-count":6,"title":["Current status of use of high throughput nucleotide sequencing in rheumatology"],"prefix":"10.1136","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5425-8304","authenticated-orcid":false,"given":"Sebastian","family":"Boegel","sequence":"first","affiliation":[{"name":"Department of Internal Medicine, University Center of Autoimmunity, University Medical Center Mainz, Mainz, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"John C","family":"Castle","sequence":"additional","affiliation":[{"name":"Monte Rosa Therapeutics, Basel, Switzerland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andreas","family":"Schwarting","sequence":"additional","affiliation":[{"name":"Department of Internal Medicine, University Center of Autoimmunity, University Medical Center Mainz, Mainz, Germany"},{"name":"Division of Rheumatology and Clinical Immunology, University Hospital Mainz, Mainz, Germany"},{"name":"Acura Rheumatology Center Rhineland Palatinate, Bad Kreuznach, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"239","published-online":{"date-parts":[[2021,1,6]]},"reference":[{"key":"2025090312153736000_7.1.e001324.1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMp1500523"},{"key":"2025090312153736000_7.1.e001324.2","doi-asserted-by":"publisher","DOI":"10.1038\/nrg.2016.86"},{"key":"2025090312153736000_7.1.e001324.3","doi-asserted-by":"publisher","DOI":"10.1038\/nrg.2016.10"},{"key":"2025090312153736000_7.1.e001324.4","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0078644"},{"key":"2025090312153736000_7.1.e001324.5","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/bs.pmbts.2019.06.016","article-title":"Bioinformatic methods for cancer neoantigen prediction","volume":"164","author":"Boegel","year":"2019","journal-title":"Prog Mol Biol Transl Sci"},{"key":"2025090312153736000_7.1.e001324.6","doi-asserted-by":"publisher","DOI":"10.1016\/j.coi.2015.12.001"},{"key":"2025090312153736000_7.1.e001324.7","doi-asserted-by":"publisher","DOI":"10.1093\/nar\/gkq1019"},{"key":"2025090312153736000_7.1.e001324.8","unstructured":"SRA statistics . 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