RABC: Rheumatoid Arthritis Bioinformatics Center.

Advances in sequencing technologies have led to the rapid growth of multi-omics data on rheumatoid arthritis (RA). However, a comprehensive database that systematically collects and classifies the scattered data is still lacking. Here, we developed the Rheumatoid Arthritis Bioinformatics Center (RABC, http://www.onethird-lab.com/RABC/), the first multi-omics data resource platform (data hub) for RA. There are four categories of data in RABC: (i) 175 multi-omics sample sets covering transcriptome, epigenome, genome, and proteome; (ii) 175 209 differentially expressed genes (DEGs), 105 differentially expressed microRNAs (DEMs), 18 464 differentially DNA methylated (DNAm) genes, 1 764 KEGG pathways, 30 488 GO terms, 74 334 SNPs, 242 779 eQTLs, 105 m6A-SNPs and 18 491 669 meta-mQTLs; (iii) prior knowledge on seven types of RA molecular markers from nine public and credible databases; (iv) 127 073 literature information from PubMed (from 1972 to March 2022). RABC provides a user-friendly interface for browsing, searching and downloading these data. In addition, a visualization module also supports users to generate graphs of analysis results by inputting personalized parameters. We believe that RABC will become a valuable resource and make a significant contribution to the study of RA.

Effects of genetic variation on the structure of RNA and protein.

Changes in the structure of RNA and protein, have an important impact on biological functions and are even important determinants of disease pathogenesis and treatment. Some genetic variations, including copy number variation, single nucleotide variation, and so on, can lead to changes in biological function and increased susceptibility to certain diseases by changing the structure of RNA or protein. With the development of structural biology and sequencing technology, a large amount of RNA and protein structure data and genetic variation data resources has emerged to be used to explain biological processes. Here, we reviewed the effects of genetic variation on the structure of RNAs and proteins, and investigated their impact on several diseases. An online resource (http://www.onethird-lab.com/gems/) to support convenient retrieval of common tools is also built. Finally, the challenges and future development of the effects of genetic variation on RNA and protein were discussed.

A review of disease risk prediction methods and applications in the omics era.

Risk prediction and disease prevention are the innovative care challenges of the 21st century. Apart from freeing the individual from the pain of disease, it will lead to low medical costs for society. Until very recently, risk assessments have ushered in a new era with the emergence of omics technologies, including genomics, transcriptomics, epigenomics, proteomics, and so on, which potentially advance the ability of biomarkers to aid prediction models. While risk prediction has achieved great success, there are still some challenges and limitations. We reviewed the general process of omics-based disease risk model construction and the applications in four typical diseases. Meanwhile, we highlighted the problems in current studies and explored the potential opportunities and challenges for future clinical practice.

Contribution of structural accessibility to the cooperative relationship of TF-lncRNA in myopia.

Transcriptional regulation is associated with complicated mechanisms including multiple molecular interactions and collaborative drive. Long noncoding RNAs (lncRNAs) have highly structured characteristics and play vital roles in the regulation of transcription in organisms. However, the specific contributions of conformation feature and underlying molecular mechanisms are still unclear. In the present paper, a hypothesis regarding molecular structure effect is presented, which proposes that lncRNAs fold into a complex spatial architecture and act as a skeleton to recruit transcription factors (TF) targeted binding, and which is involved in cooperative regulation. A candidate set of TF-lncRNA coregulation was constructed, and it was found that structural accessibility affected molecular binding force. In addition, transcription factor binding site (TFBS) regions of myopia-related lncRNA transcripts were disturbed, and it was discovered that base mutations affected the occurrence of significant molecular allosteric changes in important elements and variable splicing regions, mediating the onset and development of myopia. The results originated from structureomics and interactionomics and created conditions for systematic research on the mechanisms of structure-mediated TF-lncRNA coregulation in transcriptional regulation. Finally, these findings will help further the understanding of key regulatory roles of molecular allostery in cell physiological and pathological processes.

Low-dose adropin stimulates inflammasome activation of macrophage via mitochondrial ROS involved in colorectal cancer progression.

Adropin is encoded by the energy homeostasis-associated (ENHO) gene and widely present in liver, pancreas, heart, kidney, brain, and vascular tissues. Abnormal adropin is associated with metabolic, inflammatory, immune, and central nervous disorders. Whether adropin is involved in the development of colorectal cancer (CRC) is still unclear. Here, decreased adropin expression of tumor-nest cells in advanced-stage CRC was demonstrated. Adropin expressed by carcinoma cells was negatively correlated with macrophage infiltration in the matrix of CRC tissues. However, tumor macrophages enhanced adropin expression and were positively correlated with tumor invasion and metastasis. ENHO gene transfection into colon cancer (MC38) cells inhibited tumor growth in vivo, accompanying the increase of M1 macrophages. Treatment with low-dose adropin (< 100 ng/mL) on macrophages ex vivo directly increased mitochondrial reactive oxygen species for inflammasome activation. Furthermore, ENHO-/- mice had less M1 macrophages in vivo, and ENHO-/- macrophages were inert to be induced into the M1 subset ex vivo. Finally, low-dose adropin promoted glucose utilization, and high-dose adropin enhanced the expression of CPT1α in macrophages. Therefore, variations of adropin level in carcinoma cells or macrophages in tumor tissues are differently involved in CRC progression. Low-dose adropin stimulates the antitumor activity of macrophages, but high-dose adropin facilitates the pro-tumor activity of macrophages. Increasing or decreasing the adropin level can inhibit tumor progression at different CRC stages.

Influence on therapeutic outcome of platelet count at diagnosis in patients with de novo non-APL acute myeloid leukemia.

BACKGROUND: Platelet (PLT) count at diagnosis plays an important role in cancer development and progression in solid tumors. However, it remains controversial whether PLT count at diagnosis influences therapeutic outcome in patients with non-acute promyelocytic leukemia (APL) acute myeloid leukemia (AML). METHODS: This study analyzed the relationship between PLT count at diagnosis and genetic mutations in a cohort of 330 newly diagnosed non-APL AML patients. The impact of PLT count on complete remission, minimal residual disease status and relapse-free survival (RFS) were evaluated after chemotherapy or allogeneic hematopoietic stem cell transplantation (allo-HSCT). RESULTS: Our studies showed that patients with DNMT3A mutations have a higher PLT count at diagnosis, while patients with CEBPA biallelic mutations or t(8;21)(q22; q22) translocation had lower PLT count at diagnosis. Furthermore, non-APL AML patients with high platelet count (> 65 × 109/L) at diagnosis had worse response to induction chemotherapy and RFS than those with low PLT count. In addition, allo-HSCT could not absolutely attenuated the negative impact of high PLT count on the survival of non-APL AML patients. CONCLUSION: PLT count at diagnosis has a predictive value for therapeutic outcome for non-APL AML patients.

Epigenome-wide methylation haplotype association analysis identified HLA-DRB1, HLA-DRB5 and HLA-DQB1 as risk factors for rheumatoid arthritis.

The aim of this study was to compare nonrandom associations between physically adjacent single methylation polymorphism loci among rheumatoid arthritis (RA) and normal subjects for investigating RA-risk methylation haplotypes (meplotype). With 354 ACPA-positive RA patients and 335 normal controls selected from a case-control study based on Swedish population, we conducted the first RA epigenome-wide meplotype association study using our software EWAS2.0, mainly including (i) converted the ß value to methylation genotype (menotype) data, (ii) identified methylation disequilibrium (MD) block, (iii) calculated frequent of each meplotypes in MD block and performed case-control association test and (iv) screened for RA-risk meplotypes by odd ratio (OR) and p-values. Ultimately, 545 meplotypes on 334 MD blocks were identified significantly associated with RA (p-value < .05). These meplotypes were mapped to 329 candidate genes related to RA. Subsequently, combined with gene optimization, eight RA-risk meplotypes were identified on three risk genes: HLA-DRB1, HLA-DRB5 and HLA-DQB1. Our results reported the relationship between DNA methylation pattern on HLA-DQB1 and the risk of RA for the first time, demonstrating the co-demethylation of 'cg22984282' and 'cg13423887' on HLA-DQB1 gene (meplotype UU, p-value = 2.90E - 6, OR = 1.68, 95% CI = [1.35, 2.10]) may increase the risk of RA. Our results demonstrates the potential of methylation haplotype analysis to identify RA-related genes from a new perspective and its applicability to the study of other disease.

In silico drug repositioning based on drug-miRNA associations.

Drug repositioning has become a prevailing tactic as this strategy is efficient, economical and low risk for drug discovery. Meanwhile, recent studies have confirmed that small-molecule drugs can modulate the expression of disease-related miRNAs, which indicates that miRNAs are promising therapeutic targets for complex diseases. In this study, we put forward and verified the hypothesis that drugs with similar miRNA profiles may share similar therapeutic properties. Furthermore, a comprehensive drug-drug interaction network was constructed based on curated drug-miRNA associations. Through random network comparison, topological structure analysis and network module extraction, we found that the closely linked drugs in the network tend to treat the same diseases. Additionally, the curated drug-disease relationships (from the CTD) and random walk with restarts algorithm were utilized on the drug-drug interaction network to identify the potential drugs for a given disease. Both internal validation (leave-one-out cross-validation) and external validation (independent drug-disease data set from the ChEMBL) demonstrated the effectiveness of the proposed approach. Finally, by integrating drug-miRNA and miRNA-disease information, we also explain the modes of action of drugs in the view of miRNA regulation. In summary, our work could determine novel and credible drug indications and offer novel insights and valuable perspectives for drug repositioning.

Location deviations of DNA functional elements affected SNP mapping in the published databases and references.

The recent extensive application of next-generation sequencing has led to the rapid accumulation of multiple types of data for functional DNA elements. With the advent of precision medicine, the fine-mapping of risk loci based on these elements has become of paramount importance. In this study, we obtained the human reference genome (GRCh38) and the main DNA sequence elements, including protein-coding genes, miRNAs, lncRNAs and single nucleotide polymorphism flanking sequences, from different repositories. We then realigned these elements to identify their exact locations on the genome. Overall, 5%-20% of all sequence element locations deviated among databases, on the scale of kilobase-pair to megabase-pair. These deviations even affected the selection of genome-wide association study risk-associated genes. Our results implied that the location information for functional DNA elements may deviate among public databases. Researchers should take care when using cross-database sources and should perform pilot sequence alignments before element location-based studies.

Dietary isoflavones intake is inversely associated with non-alcoholic fatty liver disease, hyperlipidaemia and hypertension.

This study investigated associations between total isoflavones and their categories (daidzein, genistein, glycitein) intake and the risks for metabolic disorders. We used the data of 6786 Chinese adults from the Nutrition Health Atlas Project. We performed multiple logistic regression and restricted cubic spline models assessing the risks for metabolic disorders (non-alcoholic fatty liver disease (NAFLD), hyperlipidaemia, hypertension, diabetes and overweight/obesity) in each category of isoflavones. Higher total isoflavones, daidzein and genistein intake were inversely associated with NAFLD (p < .05). Higher total isoflavones, daidzein, genistein and glycitein intake were also inversely associated with hyperlipidaemia (p < .01) and hypertension (p < .01). Dose-response analyses revealed that total isoflavones, daidzein, genistein and glycitein intakes were associated with the risks of metabolic disorders in a nonlinear trend. In conclusion, total isoflavones, daidzein and genistein intake were inversely associated with NAFLD, hyperlipidaemia and hypertension. Glycitein was inversely associated with hyperlipidaemia and hypertension.

Dual effect of IL-7/IL-7R signalling on the osteoimmunological system: a potential therapeutic target for rheumatoid arthritis.

The IL-7/IL-7R pathway plays a vital role in the immune system, especially in the inflammatory response. Monocytes/macrophages (osteoclast precursors) have been recently recognized as important participants in the osteoclastogenesis of rheumatoid arthritis (RA) patients. Here, we aimed to investigate the therapeutic potential of IL-7/IL-7R pathway in RA and to determine whether it could restrain osteoclastogenic functions and therefore ameliorate RA. Firstly, collagen-induced arthritis (CIA) mice were administered with IL-7Rα-target antibodies to assess their therapeutic effect on arthritis. We found that blockade of the IL-7/IL-7R pathway protected CIA mice from bone destruction in addition to inducing inflammatory remission, by altering the RANKL/RANK/OPG ratio and consequently decreasing osteoclast formation. To explore the effect and mechanism of this pathway, bone marrow cells were induced to osteoclasts and treated with IL-7, a STAT5 inhibitor or supernatants from T cells. The results showed that the IL-7/IL-7R pathway played a direct inhibitory role in osteoclast differentiation via STAT5 signalling pathway in a RANKL-induced manner. We applied flow cytometry to analyse the effect of IL-7 on T-cell RANKL expression and found that IL-7/IL-7R pathway had an indirect role in the osteoclast differentiation process by enhancing the RANKL expression on T cells. In conclusion, the IL-7/IL-7R pathway exhibited a dual effect on osteoclastogenesis of CIA mice by interacting with osteoimmunology processes and could be a novel therapeutic target for autoimmune diseases such as RA.

EWASdb: epigenome-wide association study database.

DNA methylation, the most intensively studied epigenetic modification, plays an important role in understanding the molecular basis of diseases. Furthermore, epigenome-wide association study (EWAS) provides a systematic approach to identify epigenetic variants underlying common diseases/phenotypes. However, there is no comprehensive database to archive the results of EWASs. To fill this gap, we developed the EWASdb, which is a part of 'The EWAS Project', to store the epigenetic association results of DNA methylation from EWASs. In its current version (v 1.0, up to July 2018), the EWASdb has curated 1319 EWASs associated with 302 diseases/phenotypes. There are three types of EWAS results curated in this database: (i) EWAS for single marker; (ii) EWAS for KEGG pathway and (iii) EWAS for GO (Gene Ontology) category. As the first comprehensive EWAS database, EWASdb has been searched or downloaded by researchers from 43 countries to date. We believe that EWASdb will become a valuable resource and significantly contribute to the epigenetic research of diseases/phenotypes and have potential clinical applications. EWASdb is freely available at http://www.ewas.org.cn/ewasdb or http://www.bioapp.org/ewasdb.

Comparison of the general co-expression landscapes between human and mouse.

The murine model serves as an important experimental system in biomedical science because of its high degree of similarities at the sequence level with human. Recent studies have compared the transcriptional landscapes between human and mouse, but the general co-expression landscapes have not been characterized. Here, we calculated the general co-expression coefficients and constructed the general co-expression maps for human and mouse. The differences and similarities of the general co-expression maps between the two species were compared in detail. The results showed low similarities in the human and mouse, with only about 36.54% of the co-expression relationships conserved between the two species. These results indicate that researchers should pay attention to these differences when performing research using the expression data of human and mouse. To facilitate use of this information, we also developed the human-mouse general co-expression difference database (coexpressMAP) to search differences in co-expression between human and mouse. This database is freely available at http://www.bioapp.org/coexpressMAP.

The framework for population epigenetic study.

At present, understanding of DNA methylation at the population level is still limited. Here, we first extended the classical framework of population genetics, such as single nucleotide polymorphism allele frequency, linkage disequilibrium (LD), LD block and haplotype, to epigenetics. Then, as an example, we compared the DNA methylation disequilibrium (MD) maps between HapMap CEU (Caucasian residents of European ancestry from Utah) population and YRI (Yoruba people from Ibadan) population (lymphoblastoid cell lines). We analyzed the differences and similarities between CEU and YRI from the following aspects: SMP (single methylation polymorphism) allele frequency, SMP allele association, MD, MD block and methylation haplotype (meplotype) frequency. The results showed that CEU and YRI had similar distribution of SMP allele frequency, and shared many MD block region. We believe that the framework of population genetics can be used in the population epigenetics. The population epigenetic framework also has potential prospects in the study of complex diseases, such as epigenome-wide association study.

RIscoper: a tool for RNA-RNA interaction extraction from the literature.

MOTIVATION: Numerous experimental and computational studies in the biomedical literature have provided considerable amounts of data on diverse RNA-RNA interactions (RRIs). However, few text mining systems for RRIs information extraction are available. RESULTS: RNA Interactome Scoper (RIscoper) represents the first tool for full-scale RNA interactome scanning and was developed for extracting RRIs from the literature based on the N-gram model. Notably, a reliable RRI corpus was integrated in RIscoper, and more than 13 300 manually curated sentences with RRI information were recruited. RIscoper allows users to upload full texts or abstracts, and provides an online search tool that is connected with PubMed (PMID and keyword input), and these capabilities are useful for biologists. RIscoper has a strong performance (90.4% precision and 93.9% recall), integrates natural language processing techniques and has a reliable RRI corpus. AVAILABILITY AND IMPLEMENTATION: The standalone software and web server of RIscoper are freely available at www.rna-society.org/riscoper/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

EWAS: epigenome-wide association study software 2.0.

Motivation: With the development of biotechnology, DNA methylation data showed exponential growth. Epigenome-wide association study (EWAS) provide a systematic approach to uncovering epigenetic variants underlying common diseases/phenotypes. But the EWAS software has lagged behind compared with genome-wide association study (GWAS). To meet the requirements of users, we developed a convenient and useful software, EWAS2.0. Results: EWAS2.0 can analyze EWAS data and identify the association between epigenetic variations and disease/phenotype. On the basis of EWAS1.0, we have added more distinctive features. EWAS2.0 software was developed based on our 'population epigenetic framework' and can perform: (i) epigenome-wide single marker association study; (ii) epigenome-wide methylation haplotype (meplotype) association study and (iii) epigenome-wide association meta-analysis. Users can use EWAS2.0 to execute chi-square test, t-test, linear regression analysis, logistic regression analysis, identify the association between epi-alleles, identify the methylation disequilibrium (MD) blocks, calculate the MD coefficient, the frequency of meplotype and Pearson's correlation coefficients and carry out meta-analysis and so on. Finally, we expect EWAS2.0 to become a popular software and be widely used in epigenome-wide associated studies in the future. Availability and implementation: The EWAS software is freely available at http://www.ewas.org.cn or http://www.bioapp.org/ewas.

Both WHR and FLI as Better Algorithms for Both Lean and Overweight/Obese NAFLD in a Chinese Population.

GOALS: To compare current nonalcoholic fatty liver disease (NAFLD)-related algorithms to find suitable algorithms for NAFLD, especially lean NAFLD in middle-aged and elderly Chinese population. BACKGROUND: NAFLD is the most common cause of chronic liver disease in the world today. Various algorithms based on obesity indicators, blood lipids, and liver enzymes, etc. have been developed to screen NAFLD. MATERIALS AND METHODS: General, anthropometric and biochemical characteristics were collected. One-way analysis of variance and the χ test were applied to test the differences in continuous and categorical variables, respectively. Multivariable logistic regression analyses, adjusted by age, gender, body mass index, tobacco use, alcohol consumption, and physical activities, were used to investigate the associations between NAFLD-related algorithms and NAFLD. The accuracy and cut-off point of NAFLD-related algorithms to detect NAFLD were evaluated by area under the receiver operator characteristic curve and the maximum Youden index analysis, respectively. RESULTS: In 8 NAFLD-related algorithms, the receiver operator characteristic of fatty liver index (FLI) and waist circumstance-to-height ratio (WHR) for NAFLD were in the whole (0.83 and 0.84), lean (0.74 and 0.74), and overweight/obese (0.71 and 0.72) population, respectively, which were higher than those of other algorithms. The cut-off points of WHR and FLI for NAFLD were different in the overall (0.50 and 20), lean (0.47 and 10), and overweight/obese (0.53 and 45) population. CONCLUSIONS: WHR and FLI could be the most accurate of 8 algorithms for the noninvasive diagnosis of NAFLD in both lean and overweight/obese population.

Lean non-alcoholic fatty liver disease patients had comparable total caloric, carbohydrate, protein, fat, iron, sleep duration and overtime work as obese non-alcoholic fatty liver disease patients.

BACKGROUND AND AIM: Non-alcoholic fatty liver disease (NAFLD) is a multifactorial disease that involves a complex interaction between genetics, diet, and lifestyle. Although closely related with obese subjects, it is also common in lean humans. This study aimed to characterize the diet and lifestyle of lean and obese NAFLD patients in China. METHODS: To characterize the diet and lifestyle of lean and obese NAFLD patients, we conducted a matched case-control study that included 351 Chinese adults. General characteristics, dietary intake, and lifestyle were gathered by using a valid and reliable dietary questionnaire. We compared the dietary intake and lifestyle between lean and obese NAFLD patients. RESULTS: All NAFLD patients had more total caloric, calorigenic nutrients (carbohydrate, fat, and protein), grain, potato, fruit, and iron with higher levels of waist circumference and overtime work but shorter sleep duration than their corresponding controls. Particularly, lean NAFLD patients consumed comparable total caloric, calorigenic nutrients, iron, sleep duration, and overtime work as obese NAFLD patients, though they consumed lower levels of grain, potato, and fruit (lean NAFLD patients vs. obese NAFLD patients: mean ± SD, g/day grain: 291.8 ± 83.8, 365.2 ± 89.0; potato: 63.5 ± 33.1, 80.4 ± 37.6; fruit: 324.3 ± 148.4, 414.0 ± 220.4; P < 0.0001). CONCLUSION: Non-alcoholic fatty liver disease patients had higher total caloric, calorigenic nutrients, grain, potato, fruit, iron, and overtime work but shorter sleep duration. Lean NAFLD patients had comparable total caloric, calorigenic nutrients, iron, sleep duration, and overtime work as obese NAFLD patients. These features could be used to the nutritional education and therapeutic guidance for lean NAFLD patients in the future.

Paeoniflorin ameliorates collagen-induced arthritis via suppressing nuclear factor-κB signalling pathway in osteoclast differentiation.

Paeoniflorin (PF), extracted from the root of Paeonia lactiflora Pall, exhibits anti-inflammatory properties in several autoimmune diseases. Osteoclast, the only somatic cell with bone resorbing capacity, was the direct cause of bone destruction in rheumatoid arthritis (RA) and its mouse model, collagen-induced arthritis (CIA). The objective of this study was to estimate the effect of PF on CIA mice, and explore the mechanism of PF in bone destruction. We demonstrated that PF treatment significantly ameliorated CIA through inflammatory response inhibition and bone destruction suppression. Furthermore, PF treatment markedly decreased osteoclast number through the altered RANKL/RANK/OPG ratio and inflammatory cytokines profile. Consistently, we found that osteoclast differentiation was significantly inhibited by PF through down-regulation of nuclear factor-κB activation in vitro. Moreover, we found that PF suppressed nuclear factor-κB activation by decreasing its translocation to the nucleus in osteoclast precursor cells. Taken together, our new findings provide insights into a novel function of PF in osteoclastogenesis and demonstrate that PF would be a new therapeutic modality as a natural agent for RA treatment and other autoimmune conditions with bone erosion.