ObjectiveThe causality and pathogenic mechanism of microbiome composition remain elusive in many diseases, including autoimmune diseases such as rheumatoid arthritis (RA). This study aimed to elucidate gut microbiome’s role in RA pathology by a comprehensive metagenome-wide association study (MWAS).MethodsWe conducted MWAS of the RA gut microbiome in the Japanese population (n case=82, n control=42) by using whole-genome shotgun sequencing of high depth (average 13 Gb per sample). Our MWAS consisted of three major bioinformatic analytic pipelines (phylogenetic analysis, functional gene analysis and pathway analysis).ResultsPhylogenetic case–control association tests showed high abundance of multiple species belonging to the genus Prevotella (e.g., Prevotella denticola) in the RA case metagenome. The non-linear machine learning method efficiently deconvoluted the case–control phylogenetic discrepancy. Gene functional assessments showed that the abundance of one redox reaction-related gene (R6FCZ7) was significantly decreased in the RA metagenome compared with controls. A variety of biological pathways including those related to metabolism (e.g., fatty acid biosynthesis and glycosaminoglycan degradation) were enriched in the case–control comparison. A population-specific link between the metagenome and host genome was identified by comparing biological pathway enrichment between the RA metagenome and the RA genome-wide association study results. No apparent discrepancy in alpha or beta diversities of metagenome was found between RA cases and controls.ConclusionOur shotgun sequencing-based MWAS highlights a novel link among the gut microbiome, host genome and pathology of RA, which contributes to our understanding of the microbiome’s role in RA aetiology.

It has recently become clear that signals mediated by members of the TNFR superfamily, including lymphotoxin-β receptor (LTβR), receptor activator for NF-κB (RANK), and CD40, play essential roles in organizing the integrity of medullary thymic epithelial cells (mTECs) required for the establishment of self-tolerance. However, details of the mechanism responsible for the unique and cooperative action of individual and multiple TNFR superfamily members during mTEC differentiation still remain enigmatic. In this study, we show that the LTβR signal upregulates expression of RANK in the thymic stroma, thereby promoting accessibility to the RANK ligand necessary for mTEC differentiation. Cooperation between the LTβR and RANK signals for optimal mTEC differentiation was underscored by the exaggerated defect of thymic organogenesis observed in mice doubly deficient for these signals. In contrast, we observed little cooperation between the LTβR and CD40 signals. Thus, the LTβR signal exhibits a novel and unique function in promoting RANK activity for mTEC organization, indicating a link between thymic organogenesis mediated by multiple cytokine signals and the control of autoimmunity.

Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge1–5. Here we conducted a genome-wide association study (GWAS) involving 2,393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3,289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target.

MicroRNAs (miRNAs) modulate the post-transcriptional regulation of target genes and are related to biology of complex human traits, but genetic landscape of miRNAs remains largely unknown. Given the strikingly tissue-specific miRNA expression profiles, we here expand a previous method to quantitatively evaluate enrichment of genome-wide association study (GWAS) signals on miRNA–target gene networks (MIGWAS) to further estimate tissue-specific enrichment. Our approach integrates tissue-specific expression profiles of miRNAs (∼1800 miRNAs in 179 cells) with GWAS to test whether polygenic signals enrich in miRNA–target gene networks and whether they fall within specific tissues. We applied MIGWAS to 49 GWASs (nTotal = 3 520 246), and successfully identified biologically relevant tissues. Further, MIGWAS could point miRNAs as candidate biomarkers of the trait. As an illustrative example, we performed differentially expressed miRNA analysis between rheumatoid arthritis (RA) patients and healthy controls (n = 63). We identified novel biomarker miRNAs (e.g. hsa-miR-762) by integrating differentially expressed miRNAs with MIGWAS results for RA, as well as novel associated loci with significant genetic risk (rs56656810 at MIR762 at 16q11; n = 91 482, P = 3.6 × 10−8). Our result highlighted that miRNA–target gene network contributes to human disease genetics in a cell type-specific manner, which could yield an efficient screening of miRNAs as promising biomarkers.