Dermatology
Plaque Psoriasis
Current Status of Biomarkers in Plaque Psoriasis
Current research on biomarkers in plaque psoriasis focuses on trying to identify potential genetic variants, inflammatory cytokines, and molecular signatures to help guide personalized treatments. However, despite major discoveries, few candidate indicators have achieved routine use status in clinical practice. Ongoing studies aim to validate these tools to better predict patient responses and to monitor disease severity.
Biomarkers are a hot topic, but they are also simultaneously one of the most misunderstood areas of plaque psoriasis research today. If you are attending recent major dermatology meetings, you will likely leave them with the very optimistic impression that precision medicine for plaque psoriasis is right around the corner. Further, every month, there is another publication discussing novel genetic markers, circulating cytokines, transcriptomic signatures, and microbiome profiles. Artificial intelligence is in the background as well, with the goal of predicting disease severity and/or therapeutic response.
An ideal biomarker could help us predict an individual patient’s disease severity, predict their likely response to a given treatment, and identify their risk of developing future comorbidities. This is why the enthusiasm is certainly warranted. The challenge is that enthusiasm does not necessarily equal utility. Current research is fascinating from a scientific perspective and is likely helping us to better understand the pathophysiology of psoriasis.
Regarding whether these biomarkers should be in our current routine guidelines or should affect our clinical management, my answer is not yet. When I am seeing a patient with plaque psoriasis in clinic, I am still making my treatment decisions based primarily on the patient in front of me—not on a readout. I am evaluating not only the degree of body surface area involvement but also the location of the plaque psoriasis. Is it involving high-impact areas or areas that could lead to an increased risk for comorbid psoriatic arthritis, such as the scalp, nails, or intertriginous areas? Does the patient have early signs of psoriatic arthritis calculated by using a validated tool? Have they responded to previous topicals and systemics? Does the patient have comorbid diseases? How much is their plaque psoriasis impacting their quality of life? And, most importantly, what does the patient want? What is their expectation, and what are they hoping to accomplish? These are my clinical biomarkers. This does not mean that molecular biomarkers are not worthwhile; in fact, it is quite the opposite. I think that biomarkers can transform how we understand psoriasis, and, one day, they might guide us a bit better. However, that is the future, not the present.
Dermatology is unique in that clinicians can directly observe the patient’s disease. This is one of our greatest strengths. The psoriasis is right there in front of us. We do not need imaging to diagnose psoriasis, and we do not need a biopsy in most cases. So, the physical examination is extremely powerful.
I do not envision a future in which molecular testing replaces the skin examination. Ideally, it becomes another layer of information that complements what we already do. In the future, I predict that molecular biomarkers will be able to help guide our decision making regarding the type of drug that a patient should receive by helping us predict responses to therapy for an individual patient, as well as give us the ability to use a patient’s unique molecular signature to predict whether they are at higher risk for a particular comorbid disease.
Cruz CJG, Yang CC. Clinical application of serum biomarkers for detecting and monitoring chronic plaque psoriasis. Front Mol Biosci. 2023;10:1196323. doi:10.3389/fmolb.2023.1196323
Edwar SQ, Irawan Y, Budianti WK, Novianto E, Fitri EM. Biomarkers for diagnosis, disease progression, and therapeutic response in psoriasis vulgaris: a mini-review. Narra J. 2026;6(1):e3017. doi:10.52225/narra.v6i1.3017
Kar BR, Sathishkumar D, Tahiliani S, et al. Biomarkers in psoriasis: the future of personalised treatment. Indian J Dermatol. 2024;69(3):256-263. doi:10.4103/ijd.ijd_167_24
Li S, Qi Y, Qiao D, Hu X, Yao L, Cui X. Machine learning meets psoriasis: identifying key lactylation biomarkers as potential targets for diagnosis and therapies. Front Immunol. 2026;17:1791693. doi:10.3389/fimmu.2026.1791693
Rider A, Grantham HJ, Smith GR, et al; PSORT Consortium. Transcriptomic profiling and machine learning uncover gene signatures of psoriasis endotypes and disease severity. Commun Med (Lond). 2026;6(1):65. doi:10.1038/s43856-025-01325-4



