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. 2024 May 4;6(3):100479.
doi: 10.1016/j.ocarto.2024.100479. eCollection 2024 Sep.

Transcriptomics and metabolomics: Challenges of studying obesity in osteoarthritis

Jason S Rockel  1   2 , Pratibha Potla  1   2 , Mohit Kapoor  1   2   3
Affiliations

Transcriptomics and metabolomics: Challenges of studying obesity in osteoarthritis

Jason S Rockel et al. Osteoarthr Cartil Open. .

Abstract

Objective: Obesity is a leading risk factor for both the incidence and progression of osteoarthritis (OA). Omic technologies, including transcriptomics and metabolomics are capable of identifying RNA and metabolite profiles in tissues and biofluids of OA patients. The objective of this review is to highlight studies using transcriptomics and metabolomics that contribute to our understanding of OA pathology in relation to obesity.

Design: We conducted a targeted search of PUBMED for articles, and GEO for datasets, published up to February 13, 2024, screening for those using high-throughput transcriptomic and metabolomic techniques to study human or pre-clinical animal model tissues or biofluids related to obesity-associated OA. We describe relevant studies and discuss challenges studying obesity as a disease-related factor in OA.

Results: Of the 107 publications identified by our search criteria, only 15 specifically used transcriptomics or metabolomics to study joint tissues or biofluids in obesity-related OA. Specific transcriptomic and metabolomic signatures associated with obesity-related OA have been defined in select local joint tissues, biofluids and other biological material. However, considerable challenges exist in understanding contributions of obesity-associated modifications of transcriptomes and metabolomes related to OA, including sociodemographic, anthropometric, dietary and molecular redundancy-related factors.

Conclusions: A number of additional transcriptomic and metabolomic studies are needed to comprehensively understand how obesity affects OA incidence, progression and outcomes. Integration of transcriptome and metabolome signatures from multiple tissues and biofluids, using network-based approaches will likely help to better define putative therapeutic targets that could enable precision medicine approaches to obese OA patients.

Keywords: Anthropometrics; Diet; Metabolomics; Obesity; Sociodemographics; Transcriptomics.

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Conflict of interest statement

The authors declare no conflicts of interest.

Figures

Fig. 1
Fig. 1
Challenges using transcriptomics and metabolomics to investigate obesity-related osteoarthritis (OA). Patients who are obese are already differentially categorized from normal BMI individuals, but additional sociodemographic and biological variables may impact the heterogeneity of transcriptomes and metabolomes that can be detected through omic technologies. This heterogeneity can be influenced by various interactions between joint tissues and local or systemic fluids, in addition to direct or indirect impacts of diet, ethnicity, environment, economic status and sex. Compounding these challenges is the variety of functional redundancy that exists in the transcriptome, metabolome, and other “omes”, where specific molecules can be exchanged for one another, resulting in similar effects. Created with BioRender.com.
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