Enrichment of genomic pathways based on differential DNA methylation profiles associated with knee osteoarthritis pain

Methods in DNA methylation array dataset analysis: A review

Understanding the intricate relationships between gene expression levels and epigenetic modifications in a genome is crucial to comprehending the pathogenic mechanisms of many diseases. With the advancement of DNA Methylome Profiling techniques, the emphasis on identifying Differentially Methylated Regions (DMRs/DMGs) has become crucial for biomarker discovery, offering new insights into the etiology of illnesses. This review surveys the current state of computational tools/algorithms for the analysis of microarray-based DNA methylation profiling datasets, focusing on key concepts underlying the diagnostic/prognostic CpG site extraction. It addresses methodological frameworks, algorithms, and pipelines employed by various authors, serving as a roadmap to address challenges and understand changing trends in the methodologies for analyzing array-based DNA methylation profiling datasets derived from diseased genomes. Additionally, it highlights the importance of integrating gene expression and methylation datasets for accurate biomarker identification, explores prognostic prediction models, and discusses molecular subtyping for disease classification. The review also emphasizes the contributions of machine learning, neural networks, and data mining to enhance diagnostic workflow development, thereby improving accuracy, precision, and robustness.

Elevated circulating soluble interleukin-2 receptor (sCD25) level is associated with prefrontal excitatory-inhibitory imbalance in individuals with chronic pain: A proton MRS study

Aberrant neuronal excitability in the anterior cingulate cortex (ACC) is implicated in cognitive and affective pain processing. Such excitability may be amplified by activated circulating immune cells, including T lymphocytes, that interact with the central nervous system. Here, we conducted a study of individuals with chronic pain using magnetic resonance spectroscopy (MRS) to investigate the clinical evidence for the interaction between peripheral immune activation and prefrontal excitatory-inhibitory imbalance. In thirty individuals with chronic musculoskeletal pain, we assessed markers of peripheral immune activation, including soluble interleukin-2 receptor alpha chain (sCD25) levels, as well as brain metabolites, including Glx (glutamate + glutamine) to GABA+ (γ-aminobutyric acid + macromolecules/homocarnosine) ratio in the ACC. We found that the circulating level of sCD25 was associated with prefrontal Glx/GABA+. Greater prefrontal Glx/GABA+ was associated with higher pain catastrophizing, evaluative pain ratings, and anxiodepressive symptoms. Further, the interaction effect of sCD25 and prefrontal Glx/GABA+ on pain catastrophizing was significant, indicating the joint association of these two markers with pain catastrophizing. Our results provide the first evidence suggesting that peripheral T cellular activation, as reflected by elevated circulating sCD25 levels, may be linked to prefrontal excitatory-inhibitory imbalance in individuals with chronic pain. The interaction between these two systems may play a role as a potential mechanism underlying pain catastrophizing. Further prospective and treatment studies are needed to elucidate the specific role of the immune and brain interaction in pain catastrophizing.

Epigenetic Landscapes of Pain: DNA Methylation Dynamics in Chronic Pain

Chronic pain is a prevalent condition with a multifaceted pathogenesis, where epigenetic modifications, particularly DNA methylation, might play an important role. This review delves into the intricate mechanisms by which DNA methylation and demethylation regulate genes associated with nociception and pain perception in nociceptive pathways. We explore the dynamic nature of these epigenetic processes, mediated by DNA methyltransferases (DNMTs) and ten-eleven translocation (TET) enzymes, which modulate the expression of pro- and anti-nociceptive genes. Aberrant DNA methylation profiles have been observed in patients with various chronic pain syndromes, correlating with hypersensitivity to painful stimuli, neuronal hyperexcitability, and inflammatory responses. Genome-wide analyses shed light on differentially methylated regions and genes that could serve as potential biomarkers for chronic pain in the epigenetic landscape. The transition from acute to chronic pain is marked by rapid DNA methylation reprogramming, suggesting its potential role in pain chronicity. This review highlights the importance of understanding the temporal dynamics of DNA methylation during this transition to develop targeted therapeutic interventions. Reversing pathological DNA methylation patterns through epigenetic therapies emerges as a promising strategy for pain management.

Evolution and advancements in genomics and epigenomics in OA research: How far we have come

OBJECTIVE

Osteoarthritis (OA) is the most prevalent musculoskeletal disease affecting articulating joint tissues, resulting in local and systemic changes that contribute to increased pain and reduced function. Diverse technological advancements have culminated in the advent of high throughput "omic" technologies, enabling identification of comprehensive changes in molecular mediators associated with the disease. Amongst these technologies, genomics and epigenomics - including methylomics and miRNomics, have emerged as important tools to aid our biological understanding of disease.

DESIGN

In this narrative review, we selected articles discussing advancements and applications of these technologies to OA biology and pathology. We discuss how genomics, deoxyribonucleic acid (DNA) methylomics, and miRNomics have uncovered disease-related molecular markers in the local and systemic tissues or fluids of OA patients.

RESULTS

Genomics investigations into the genetic links of OA, including using genome-wide association studies, have evolved to identify 100+ genetic susceptibility markers of OA. Epigenomic investigations of gene methylation status have identified the importance of methylation to OA-related catabolic gene expression. Furthermore, miRNomic studies have identified key microRNA signatures in various tissues and fluids related to OA disease.

CONCLUSIONS

Sharing of standardized, well-annotated omic datasets in curated repositories will be key to enhancing statistical power to detect smaller and targetable changes in the biological signatures underlying OA pathogenesis. Additionally, continued technological developments and analysis methods, including using computational molecular and regulatory networks, are likely to facilitate improved detection of disease-relevant targets, in-turn, supporting precision medicine approaches and new treatment strategies for OA.

Three decades of advancements in osteoarthritis research: insights from transcriptomic, proteomic, and metabolomic studies

OBJECTIVE

Osteoarthritis (OA) is a complex disease involving contributions from both local joint tissues and systemic sources. Patient characteristics, encompassing sociodemographic and clinical variables, are intricately linked with OA rendering its understanding challenging. Technological advancements have allowed for a comprehensive analysis of transcripts, proteomes and metabolomes in OA tissues/fluids through omic analyses. The objective of this review is to highlight the advancements achieved by omic studies in enhancing our understanding of OA pathogenesis over the last three decades.

DESIGN

We conducted an extensive literature search focusing on transcriptomics, proteomics and metabolomics within the context of OA. Specifically, we explore how these technologies have identified individual transcripts, proteins, and metabolites, as well as distinctive endotype signatures from various body tissues or fluids of OA patients, including insights at the single-cell level, to advance our understanding of this highly complex disease.

RESULTS

Omic studies reveal the description of numerous individual molecules and molecular patterns within OA-associated tissues and fluids. This includes the identification of specific cell (sub)types and associated pathways that contribute to disease mechanisms. However, there remains a necessity to further advance these technologies to delineate the spatial organization of cellular subtypes and molecular patterns within OA-afflicted tissues.

CONCLUSIONS

Leveraging a multi-omics approach that integrates datasets from diverse molecular detection technologies, combined with patients' clinical and sociodemographic features, and molecular and regulatory networks, holds promise for identifying unique patient endophenotypes. This holistic approach can illuminate the heterogeneity among OA patients and, in turn, facilitate the development of tailored therapeutic interventions.

Osteoarthritis year in review 2023: genetics, genomics, and epigenetics

OBJECTIVE

To elucidate the scientific advances made in the last 12 months within the realm of osteoarthritis genetics, genomics, and epigenetics. This review paper highlights major research publications that enhance our current understanding of the role of genetics, genomics, and epigenetics in osteoarthritis.

METHODS

A systematic literature search was conducted on pubmed.ncbi.nlm.nih.gov on "March 17, 2023", using the following keywords: "osteoarthritis" in combination with any of these terms: "genetic(s)", "mutation(s)", "genomic(s)", "epigenetic(s)", "DNA methylation", "noncoding RNA", "lncRNA", "circular RNA", "microRNA", "transcriptomic(s)", "RNA sequencing", "single cell RNA sequencing", or "single nucleus RNA sequencing". The selection comprised original research articles published in the English language between the OARSI congresses of 2022 and 2023.

RESULTS

A total of 2178 research articles were identified, which subsequently reduced to 67 unique articles relevant to the field. Current trends in osteoarthritis genetics research involve meta-analyses of various cohorts to explore the impact of gene variants on osteoarthritis-related outcomes, such as pain. Early developmental changes within the joint were also found to influence osteoarthritis through genetic variations. Researchers also prioritize testing the mechanisms and functions of miRNAs, circRNAs, and lncRNAs. Potential drug targets began to emerge; however, independent validation studies are lacking. Single cell RNA sequencing studies revealed unique immune cell populations in the knee; however, no study reported single nucleus RNA sequencing analysis.

CONCLUSIONS

This review focused on recent advances in the above-mentioned themes within the field of osteoarthritis. These advances improve our understanding of the disease's complexity and guide us toward functional assessments of genetic/epigenetic outcomes and toward their translational and clinical applications.