Current and emerging biomarkers for ulcerative colitis

Figures & data

Figure 1. Biomarkers may support patient management throughout the disease course, from primary ulcerative colitis prevention to minimization of adverse event risk. The optimal selection of accurate biomarkers is the foundation of personalized medicine.

Table 1. The diversity of biomarker identification strategies in ulcerative colitis (UC) from the perspective of adoption and/or development in the near future.

Analytical method	Perspectives
Individual proteins or autoantibodies	Their adoption into clinical practice can be swift due to existing infrastructure. PR3-ANCA has high diagnostic specificity for UC. Candidates include SAA and galectin.
Protein panels	Multi-variable models, including proteomic panels, are sensitive to variations in laboratory methods and sample handling. They could probably only be provided using strictly respected, uniform methodology from one vendor, increasing the price and imposing other limitations.
Clinical feature engineering	Adding clinical features to models using genes, proteins, or metabolites strengthens predictive models. However, it requires user input and the development of scores or computing tools, which may be a barrier to adoption.
Genetics	Polygenic risk scores may be available for many patients in the near future due to the low cost and the usefulness of genome analysis in multiple applications. They might then provide the first step for subclinical UC screening, which could hypothetically be achieved with anti-αvβ6 autoantibodies.
DNA methylation	Methylome-based analysis has thus far demonstrated moderate prognostication value. New methods of analysis are used to exploit rich methylomic datasets and deal with confounding factors.
Gene expression	Transcriptome-based panels can prognosticate treatment escalation in the mid-term. Adoption of gene-expression qPCR panels is methodologically difficult and costly. Simpler markers have not been validated.
Protein glycosylation	Glycome analysis provides very promising results, but glycomic technologies are not widely available, and translation to more accessible methods is not straightforward. Glycomic analyses provide interesting insights into UC biology.
Metabolomics	Metabolomics is more easily accessible than glycomics, and there are a number of promising metabolite sets and signatures. They require validation, which would show that the same accuracies can be achieved with different pipelines.
Microbiota	If specific bacteria were targeted, fast adoption worldwide could be achieved. However, the data are still insufficient, and studies are ongoing. Applying predictive models using the complete microbiome or metagenome would require uniform methodology, limiting use in some locations.
Complete blood count	Easily accessible markers that are not used often because of uncertainty about the exact performance or added value of calculating ratios proposed in the literature. Further research is needed to understand their value and provide sufficient data for potential inclusion in guidelines.
Other	Ultrasound scores, blood spectroscopy, endoscopic fluorescent markers, retinal optical coherence tomography, exposome assessment, mobile technologies, and other methods may provide unexpected breakthroughs.

Figure 2. Comparison of the area under the receiver-operating characteristic curve (AUC) for some of the established and investigational ulcerative colitis biomarkers in various clinical contexts. The AUC values are presented to illustrate general trends in the field and not to compare individual studies, which strongly differ in design, e.g. a higher AUC is more easily achieved for short-term prognostication or when patients diagnosed with UC had more active disease. Only studies that reported an AUC are included, and in some cases, multiple studies provided data on the value of the same marker in the same application.

Anti-αvβ6 – anti-integrin αvβ6 autoantibody; CA – cholic acid; CDH2 – cadherin 2; CLEC5A – C-Type lectin domain containing 5A; CPa9-HNE – human neutrophil elastase-derived calprotectin neo-epitope; CRP – C-reactive protein; DCA – deoxycholic acid; DPP-4 – dipeptidyl peptidase 4, LRG1 – leucine-rich alpha-2-glycoprotein 1; MALT1 – mucosa-associated lymphoid tissue lymphoma translocation protein 1 paracaspase; MMP9 – matrix metallopeptidase 9; OSM – oncostatin M; PR3-ANCA – proteinase 3 antineutrophil cytoplasmic antibodies; TFF3 – trefoil factor 3; VICM – citrullinated and MMP-degraded vimentin.