Peripheral Blood Transcriptome in Patients with Sarcoidosis-Associated Uveitis
| Autor: | Jaskirat S Takhar, Cindi Chen, Ashlin Joye, Nisha R. Acharya, John A. Gonzales, Armin Hinterwirth, Thuy Doan |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Sarcoidosis
Immunology Central nervous system Inflammation Disease Ophthalmology & Optometry Autoimmune Disease Article Uveitis Transcriptome 03 medical and health sciences Rare Diseases 0302 clinical medicine Clinical Research Genetics medicine Humans 2.1 Biological and endogenous factors Immunology and Allergy Aetiology transcrioptome 030203 arthritis & rheumatology metagenomic deep sequencing business.industry Inflammatory and immune system medicine.disease eye diseases Peripheral blood Pathophysiology Ophthalmology medicine.anatomical_structure 030221 ophthalmology & optometry medicine.symptom Uveomeningoencephalitic Syndrome business |
| Zdroj: | Ocular immunology and inflammation, vol 30, iss 5 Ocul Immunol Inflamm |
| ISSN: | 1744-5078 0927-3948 |
| DOI: | 10.1080/09273948.2020.1861306 |
| Popis: | INTRODUCTION: Sarcoidosis has traditionally been thought of as a compartmentalized disease – the inflammatory milieu within pulmonary granulomas harbors products of activated genes leading to the manifestation of the autoimmune process. However, recent research has shown that such a compartmentalized view of sarcoidosis may not be entirely accurate and that distinguishing biomarkers may be identified from the peripheral blood.(1) METHODS: Twenty participants were recruited from a convenience sample from the Francis I. Proctor Foundation at the University of California, San Francisco (UCSF). This study was approved by the UCSF Institutional Review Board and adhered to the tenets of the Declaration of Helsinki. Participants had peripheral whole blood drawn into PAXgene blood RNA tubes (QIAGEN, Germantown, MD) and prepared and stored at −80C according to manufacturer’s recommendations. Samples were deidentified and laboratory personnel handing samples and interpreting data were masked. Differential gene expression was performed to identify host transcriptome signatures.(2) Briefly, analysis of sequenced data was made using a rapid computational pipeline developed in-house to classify host genes. Quality filtered RNA transcripts were aligned to the ENSEMBL CRCh38 human genome using STAR2. Genes were filtered to include only protein-coding genes that were expressed in at least 25% of the patients. Gene count data were analyzed with DESeq2.(3) Differentially expressed genes with false discovery rate (FDR) |
| Databáze: | OpenAIRE |
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