Epigenome-wide association study (EWAS) has been applied to analyze DNA methylation variation in complex diseases for a decade, and epigenome as a research target has gradually become a hot topic of current studies. The DNA methylation microarrays, next-generation, and third-generation sequencing technologies have prepared a high-quality platform for EWAS. Here, the progress of EWAS research is reviewed, its contributions to clinical applications, and mainly describe the achievements of four typical diseases. Finally, the challenges encountered by EWAS and make bold predictions for its future development are presented.

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.

BACKGROUND Pedigree data (family history) are indispensable for genetics studies and the assessment of individuals' disease susceptibility. With the popularity of genetics testing, the collection of pedigree data is becoming more common. However, it can be time-consuming, laborious, and tedious for clinicians to investigate all pedigree data for each patient. A self-service robot could inquire about patients' family history in place of professional clinicians or genetic counselors. OBJECTIVE The aim of this study was to develop a mobile-based and self-service tool to collect and visualize pedigree data, not only for professionals but also for those who know little about genetics. METHODS There are 4 main aspects in the iPed construction, including interface building, data processing, data storage, and data visualization. The user interface was built using HTML, JavaScript libraries, and Cascading Style Sheets (version 3; Daniel Eden). Processing of the submitted data is carried out by PHP programming language. MySQL is used to document and manage the pedigree data. PHP calls the R script to accomplish the visualization. RESULTS iPed is freely available to all users through the iPed website. No software is required to be installed, no pedigree files need to be prepared, and no knowledge of genetics or programs is required. The users can easily complete their pedigree data collection and visualization on their own and through a dialogue with iPed. Meanwhile, iPed provides a database that stores all users’ information. Therefore, when the users need to construct new pedigree trees for other genetic traits or modify the pedigree trees that have already been created, unnecessary duplication of operations can be avoided. CONCLUSIONS iPed is a mobile-based and self-service tool that could be used by both professionals and nonprofessionals at any time and from any place. It reduces the amount of time required to collect, manage, and visualize pedigree data.

Background: To determine the relationship between gestational diabetes mellitus (GDM) and coagulation/fibrinolysis abnormality in antenatal Chinese women. Methods: Case control study. Fifty women had GDM and 132 did not (the NGDM group) grouping by the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria. Maternal plasma biochemistry and previous medical history were collected from perinatal health records. Antenatal coagulation/fibrinolysis activity(CFA) parameters was assessed using thromboelastography and routine CFA parameters respectively. Univariate and multiple regression analyses were used to evaluate the associations between GDM and CFA parameters. Results: The women with GDM were significantly older than those without GDM (30.3 vs. 28.6 years, P=0.012). Compared with the NGDM group, the GDM group had a significantly higher prevalence of cesarean delivery (56.0% vs. 37.9%, P=0.027) and higher values of fibrinogen (FIB) (4.7vs. 4.3 g/L P=0.001), activated partial thromboplastin time (APTT) (30.9 vs. 29.5 seconds P=0.010).There were no significant differences in the prevalence of maternal thrombotic events or neonatal events.GDM was significantly associated with higher APTT (β 1.41seconds, 95% CI 0.29–2.53), FIB (β 0.38g/L, 95% CI 0.14–0.61), and percentage reduction in clot lysis after 30 min(LY30)(β 1.14%, 95% CI 0.15–2.13) after adjustment for potential confounding factors. Conclusions: GDM is significantly associated with hypercoagulability and secondary hyperfibrinolysis in these antenatal Chinese women.

Epigenome‐Wide Association Study In article number 2100727 by Yongshuai Jiang, and co‐workers, the research process of Epigenome‐wide association study (EWAS), its application in biology and clinical translation are discussed. It concludes by analyzing the current limitations and forecasting the future of EWAS. A decade has passed since EWAS was applied to analyze complex diseases. The cover is full of blessings for the 10th anniversary of EWAS and expresses the dedication of researchers.