Multi-omics molecular biomarkers and database of osteoarthritis

Abstract

Osteoarthritis (OA) is the most common form of arthritis in the adult population and is a leading cause of disability. OA-related genetic loci may play an important role in clinical diagnosis and disease progression. With the rapid development of diverse technologies and omics methods, many OA-related public data sets have been accumulated. Here, we retrieved a diverse set of omics experimental results from 159 publications, including genome-wide association study, differentially expressed genes and differential methylation regions, and 2405 classified OA-related gene markers. Meanwhile, based on recent single-cell RNA-seq data from different joints, 5459 cell-type gene markers of joints were collected. The information has been integrated into an online database named OAomics and molecular biomarkers (OAOB). The database (http://ibi.zju.edu.cn/oaobdb/) provides a web server for OA marker genes, omics features and so on. To our knowledge, this is the first database of molecular biomarkers for OA.

Dynamic regulation and key roles of ribonucleic acid methylation

“…Databases related to methylation modification are under development from comprehensive databases to more detailed and specialized ones. The following are the emerged databases of methylation modifications associated with some specific diseases and fields: (1) After m6A methylation-related genes based on The Cancer Genome Atlas (TCGA) were used to predict the prognosis of hepatocellular carcinoma ( Group et al, 2020 ; Liu et al, 2020b ; Li et al, 2021b ), cancer-related methylation modification databases have begun to emerge, including, Lnc2Cancer 3.0 and OncoDB ( Gao et al, 2021 ; Tang et al, 2022 ); (2) Osteoarthritis-omics and molecular biomarkers (OAOB), which are a group of database containing differential molecular biomarkers related to osteoarthritis ( Li et al, 2022a ); (3) Other than disease, Pan et al (2022) established an integrative multi-omic database (iMOMdb) of Asian pregnant women providing the first blood-based multi-omic analysis of pregnant women in Asia. This database contains high-resolution genotypes, DNA methylation, and transcriptome profiles, and fills the knowledge gap of complex traits in populations of Asian ancestry; (4) Gao et al (2022) developed AgingBank, an experimentally supported multiomics database of information related to aging in multiple species; (5) ProMetheusDB, a database generated by analyzing and sorting cell culture experiments data using ML tools from the protein perspective ( Massignani et al, 2022 ); (6) compendium of protein lysine modifications (CPLM 4.0), a post-translational modification (PTMs) database ( Zhang et al, 2022 ); (7) tRNA-related databases containing high-throughput tRNA sequencing data ( Sajek et al, 2020 ); (8) RNAWRE and RM2 Target are two databases focusing on information of writers, readers, and erasers ( Nie et al, 2020 ; Bao et al, 2022 ); and (9) SyStemCell, a multiple-levels experimental database for stem cell research ( Yu et al, 2012 ).…”

“…• RMDisease V2.0 (Song et al, 2022b), AgingBank (Gao et al, 2022), CPLM 4.0 (Zhang et al, 2022), OncoDB (Tang et al, 2022), ASMdb (Zhou et al, 2022), iMOMdb (Pan et al, 2022), OAOB (Li et al, 2022a), ProMetheusDB (Massignani et al, 2022), RM2Target (Bao et al, 2022(Bao et al, ) (2022 performance based on its SpinalNet architecture that was inspired by the human somatosensory system.…”

“…Databases related to methylation modification are under development from comprehensive databases to more detailed and specialized ones. The following are the emerged databases of methylation modifications associated with some specific diseases and fields: (1) After m6A methylation-related 10.3389/fncel.2022.1058083 genes based on The Cancer Genome Atlas (TCGA) were used to predict the prognosis of hepatocellular carcinoma (Group et al, 2020;Liu et al, 2020b;Li et al, 2021b), cancer-related methylation modification databases have begun to emerge, including, Lnc2Cancer 3.0 and OncoDB (Gao et al, 2021;Tang et al, 2022); (2) Osteoarthritis-omics and molecular biomarkers (OAOB), which are a group of database containing differential molecular biomarkers related to osteoarthritis (Li et al, 2022a);(3) Other than disease, Pan et al (2022) established an integrative multi-omic database (iMOMdb) of Asian pregnant women providing the first blood-based multiomic analysis of pregnant women in Asia. This database contains high-resolution genotypes, DNA methylation, and transcriptome profiles, and fills the knowledge gap of complex traits in populations of Asian ancestry; (4) Gao et al (2022) developed AgingBank, an experimentally supported multiomics database of information related to aging in multiple species;…”

Exploring the Feasibility of Circulating miRNAs as Diagnostic and Prognostic Biomarkers in Osteoarthritis: Challenges and Opportunities

“…Despite the identification of several genetic (e.g., COL6A3 and ACTG1 genes, DNA methylation, etc.) [21,22] and biochemical biomarkers (e.g., proinflammatory cytokines, Ctelopeptide fragments of type II collagen, hyaluronan, etc.) [23,24], miRNAs offer a unique advantage as biomarkers for OA.…”

High-Resolution N-Glycan MALDI Mass Spectrometry Imaging of Subchondral Bone Tissue Microarrays in Patients with Knee Osteoarthritis

“…In recent years, “omics” studies in KOA have expanded our understanding of disease pathogenesis. , Among the different “omics” approaches, glycomics studies have been steadily increasing over the past decade as the alterations in glycosylation are often seen in cancer cells which regulate tumor proliferation, invasion, metastasis, and angiogenesis . Glycosylation is a common post-translational protein modification involving the complex pathways in which glycan sugar moieties attach to proteins .…”