Browsing by Author "Li, Ruei-Nian"

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GADD45a and GADD45b Genes in Rheumatoid Arthritis and Systemic Lupus Erythematosus Patients
(2019-06-01)
Li, Ruei-Nian
;
Lin, Yuan-Zhao
;
Pan, Ya-Chun
;
Lin, Chia-Hui
;
Tseng, Chia-Chun
Background: GADD45 genes are stress sensors in response to cellular stress response, activated signal pathways leading to the stimulation of inflammatory cytokines. This study is to examine the associations of GADD45a and GADD45b genes with rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE) patients. Methods: 230 patients of RA, 140 patients of SLE, and 191 healthy controls were enrolled. Genomic DNA was extracted from peripheral blood mononuclear cells and gene polymorphisms were genotyped by TaqMan assay. RNA expression was quantitated with real-time polymerase chain reaction. Results: The RNA expression of the GADD45b gene was significantly lower in RA patients than the control cases (p = 0.03). The odds ratio of GADD45a genotype -589 CC (rs581000) was significantly low (OR = 0.36, 95% CI, 0.15-0.87) in DR4-negative RA patients. The odds ratio of GADD45b genotype -712CT (rs3795024) in DR4-negative RA patients was 0.41 (95% CI, 0.18-0.95). In clinical manifestation, the odds ratio of GADD45b -712CT genotype with anti-RNP antibody was 4.14 (95% CI, 1.10-15.63) in SLE patients. GADD45a genotype -589GG+GC was associated with rheumatoid factor (RF) in SLE patients. Conclusions: Genotypes GADD45a -589CC and GADD45b -712CT were shown to be less susceptible to RA and related to the disease state in SLE patients.
Next-Generation Sequencing Profiles of the Methylome and Transcriptome in Peripheral Blood Mononuclear Cells of Rheumatoid Arthritis
(2019-09-01)
Tseng, Chia-Chun
;
Lin, Yuan-Zhao
;
Lin, Chia-Hui
;
Li, Ruei-Nian
;
Yen, Chang-Yi
Using next-generation sequencing to decipher methylome and transcriptome and underlying molecular mechanisms contributing to rheumatoid arthritis (RA) for improving future therapies, we performed methyl-seq and RNA-seq on peripheral blood mononuclear cells (PBMCs) from RA subjects and normal donors. Principal component analysis and hierarchical clustering revealed distinct methylation signatures in RA with methylation aberrations noted across chromosomes. Methylation alterations varied with CpG features and genic characteristics. Typically, CpG islands and CpG shores were hypermethylated and displayed the greatest methylation variance. Promoters were hypermethylated and enhancers/gene bodies were hypomethylated, with methylation variance associated with expression variance. RA genetically associated genes preferentially displayed differential methylation and differential expression or interacted with differentially methylated and differentially expressed genes. These differentially methylated and differentially expressed genes were enriched with several signaling pathways and disease categories. 10 genes (CD86, RAB20, XAF1, FOLR3, LTBR, KCNH8, DOK7, PDGFA, PITPNM2, CELSR1) with concomitantly differential methylation in enhancers/promoters/gene bodies and differential expression in B cells were validated. This integrated analysis of methylome and transcriptome identified novel epigenetic signatures associated with RA and highlighted the interaction between genetics and epigenetics in RA. These findings help our understanding of the pathogenesis of RA and advance epigenetic studies in regards to the disease.