Pre-pregnancy gene expression signatures are associated with subsequent improvement/worsening of rheumatoid arthritis during pregnancy

Arthritis research & therapy(2023)

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摘要
Background While many women with rheumatoid arthritis (RA) improve during pregnancy and others worsen, there are no biomarkers to predict this improvement or worsening. In our unique RA pregnancy cohort that includes a pre-pregnancy baseline, we have examined pre-pregnancy gene co-expression networks to identify differences between women with RA who subsequently improve during pregnancy and those who worsen. Methods Blood samples were collected before pregnancy (T0) from 19 women with RA and 13 healthy women enrolled in our prospective pregnancy cohort. RA improvement/worsening between T0 and 3rd trimester was assessed by changes in the Clinical Disease Activity Index (CDAI). Pre-pregnancy expression profiles were examined by RNA sequencing and differential gene expression analysis. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules correlated with the improvement/worsening of RA during pregnancy and to assess their functional relevance. Results Of the 19 women with RA, 14 improved during pregnancy (RA improved ) while 5 worsened (RA worsened ). At the T0 baseline, however, the mean CDAI was similar between the two groups. WGCNA identified one co-expression module related to B cell function that was significantly correlated with the worsening of RA during pregnancy and was significantly enriched in genes differentially expressed between the RA improved and RA worsened groups. A neutrophil-related expression signature was also identified in the RA improved group at the T0 baseline. Conclusion The pre-pregnancy gene expression signatures identified represent potential biomarkers to predict the subsequent improvement/worsening of RA during pregnancy, which has important implications for the personalized treatment of RA during pregnancy.
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关键词
Rheumatoid arthritis,Pregnancy,Pre-pregnancy biomarkers,Gene expression,RNA sequencing (RNA-seq),Co-expression network analysis
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