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Objective Anti-TNF biologics have been widely used to ameliorate disease activity in patients with RA. However, a large fraction of patients show a poor response to these agents. Moreover, no clinically applicable predictive biomarkers have been established. This study aimed to identify response-associated biomarkers using longitudinal transcriptomic data in two independent RA cohorts. Methods RNA sequencing data from peripheral blood cell samples of Korean and Caucasian RA cohorts before and after initial treatment with anti-TNF biologics were analysed to assess treatment-induced expression changes that differed between highly reliable excellent responders and null responders. Weighted correlation network, immune cell composition, and key driver analyses were performed to understand response-associated transcriptomic networks and cell types and their correlation with disease activity indices. Results In total, 305 response-associated genes showed significantly different treatment-induced expression changes between excellent and null responders. Co-expression network construction and subsequent key driver analysis revealed that 41 response-associated genes played a crucial role as key drivers of transcriptomic alteration in four response-associated networks involved in various immune pathways: type I IFN signalling, myeloid leucocyte activation, B cell activation, and NK cell/lymphocyte–mediated cytotoxicity. Transcriptomic response scores that we developed to estimate the individual-level degree of expression changes in the response-associated key driver genes were significantly correlated with the changes in clinical indices in independent patients with moderate or ambiguous response outcomes. Conclusion This study provides response-specific treatment-induced transcriptomic signatures by comparing the transcriptomic landscape between patients with excellent and null responses to anti-TNF drugs at both gene and network levels. [ABSTRACT FROM AUTHOR]

Background and Aims Crohn's disease [CD] has a complex polygenic aetiology with high heritability. There is ongoing effort to identify novel variants associated with susceptibility to CD through a genome-wide association study [GWAS] in large Korean populations. Methods Genome-wide variant data from 902 Korean patients with CD and 72 179 controls were used to assess the genetic associations in a meta-analysis with previous Korean GWAS results from 1621 patients with CD and 4419 controls. Epistatic interactions between CD-risk variants of interest were tested using a multivariate logistic regression model with an interaction term. Results We identified two novel genetic associations with the risk of CD near ZBTB38 and within the leukocyte immunoglobulin-like receptor [LILR] gene cluster [ p  < 5 × 10−8], with highly consistent effect sizes between the two independent Korean cohorts. CD-risk variants in the LILR locus are known quantitative trait loci [QTL] for multiple LILR genes, of which LILRB2 directly interacts with various ligands including MHC class I molecules. The LILR lead variant exhibited a significant epistatic interaction with CD-associated regulatory variants for TAP2 involved in the antigen presentation of MHC class I molecules [ p  = 4.11 × 10−4], showing higher CD-risk effects of the TAP2 variant in individuals carrying more risk alleles of the LILR lead variant (odds ratio [OR] = 0.941, p  = 0.686 in non-carriers; OR = 1.45, p  = 2.51 × 10−4 in single-copy carriers; OR = 2.38, p  = 2.76 × 10−6 in two-copy carriers). Conclusions This study demonstrated that genetic variants at two novel susceptibility loci and the epistatic interaction between variants in LILR and TAP2 loci confer a risk of CD. [ABSTRACT FROM AUTHOR]