‘Omics’ are at the forefront of rheumatic disease treatment

Omics is an emerging area of research that has primarily focused on oncology. The promise of omics, however, extends to other fields, including rheumatology. 

The key is to determine how new research findings translate to the clinical setting, with the ultimate goal to improve patient care. 

Defining omics

The study of omics incorporates biological systems and interactions between these systems. Systems biology integrates molecular biology and biochemistry with pathophysiology. This approach has shed light on biologic mechanisms spanning various health conditions.^[] 

The suffix “omics” refers to the use of high-throughput and high-resolution technologies to study a five-tiered, hierarchical biological system, with each layer integrating with others.^[] The hierarchy from top to bottom is as follows:

• Epigenomics: The epigenome mediates the activation of cellular programs via chemical modifications of nucleic acids/histones that drive transcription. 

• Genomics: The genome refers to all the DNA within an organism.

• Transcriptomics: The transcriptome comprises all RNA molecules in a cell, including all those that are translated into proteins or remain untranslated (ie, noncoding RNA).

• Proteomics: The proteome is all the protein in a cell and is encoded by mRNA.

• Metabolomics: The metabolome refers to low molecular weight molecules (ie, metabolites) existing in a biological system, which play a role in or result from biochemical reactions.

Omics advances in rheumatology

Although no omics approaches in rheumatology are yet standard of care, the literature is rife with examples of omics in action. The hopes are high for the application of omics in rheumatology practice.

“Many recent studies have used ‘omics’ tools such as genomics, transcriptomics, proteomics, metabolomics, and microbiomics to approach ARD [autoimmune rheumatic disease] diagnosis and management objectively,” wrote the authors of an editorial published in Frontiers in Medicine.^[] “Due to the complexity of the information involved, multi-omics analysis has been recommended as providing a more comprehensive view of these diseases.” 

Gut microbiota are altered in a range of autoimmune diseases. In one example, US investigators publishing in Applied and Environmental Microbiology compared patients with active systemic lupus erythematosus (SLE) against a control group, and found that patients with SLE harbored an altered gut microbiota.^[]

This dysbiosis differed in the genera Odoribacter and Blautia and an unnamed genus in the family Rikenellaceae, as well as being less heterogeneous, with higher levels of Gram-negative bacteria. Differences in gut microbiota could someday tie to the utilization of nonselective immunosuppressive therapies, such as dexamethasone and azathioprine.

In a phase 2 trial of iberdomide, which is indicated for the treatment of moderate-to-severe SLE, molecular stratification was assessed, with study results published in the NEJM.^[]

“Iberdomide-induced degradation of Ikaros and Aiolos is known to affect B-cell and type I interferon pathways and increase levels of regulatory T cells, interleukin-2, and interleukin,” wrote the study authors. “This trial was not stratified according to gene signature at baseline, and more patients who received high-dose iberdomide had high Aiolos and type I interferon gene signatures at baseline, which potentially contributed to the greater clinical response in this group.” 

The authors noted, however, that individuals in the placebo group, per gene expression subgroup, responded similarly to the overall cohort, and that only patients receiving iberdomide with high signatures at baseline saw a reduction in interferon gene signatures. 

The study authors concluded that future research into “changes associated with immune response may help to generate hypotheses for validation in future trials.”

In a multi-omics analysis published in Arthritis Research & Therapy, Chinese researchers found that plasma metabolites, gut microbiota, transcript levels, and DNA were all altered in RA patients with different levels of disease activity, which could translate to the clinic.^[]

“Furthermore, the model constructed based on multi-omics could assist in the clinical evaluation of the disease status of RA patients,” the researchers concluded.