Biometrics and Biomarkers in Patients With Psoriasis

Abstract

Psoriasis (PsO) is a chronic, systemic, and autoimmune dermatologic condition characterized by dry, scaly, and erythematous plaques on the skin. PsO can present in various forms, including guttate (small, round lesions commonly over the upper trunk and extremities that can be raised and scaly), inverse (smooth plaques of inflamed skin within skin folds of the groin, buttock, and breasts), pustular (white painful pustules within red inflamed blotches widespread over the body), and erythrodermic (red rash present over most of the body). Individuals with PsO can present differently, with unique symptoms and patterns on the skin. These diverse manifestations make PsO a complex condition with mild to severe symptoms affecting different body areas. Researchers have identified intrinsic risk factors (and comorbidities) tied to PsO, including genetics, obesity, metabolic syndrome, infection, cardiovascular disease, stress, and type 2 diabetes mellitus (T2DM). In addition, several extrinsic risk factors have also been shown to be tied to PsO onset and progression, such as ultraviolet (UV) light, air pollution, and various pharmacological treatments. While these intrinsic and extrinsic factors have been tied to disease pathophysiology, the underlying mechanisms of disease activity have yet to be elucidated fully, making diagnosis and treatment cumbersome. Currently, PsO is diagnosed clinically with no definitive test. Noninvasive tools such as dermoscopy aid in diagnosis, while the biopsy is reserved for difficult-to-characterize psoriatic-like lesions. The reliance on clinical presentation and the lack of diagnostic testing available have led to the underdiagnosis of PsO, particularly in minority communities. The goal of this study is to utilize data from the National Health and Nutrition Examination Survey (NHANES) to improve the diagnosis of PsO and target treatment more effectively, and biometric measurements associated with PsO should be studied to aid clinical practitioners in better understanding the disease pathophysiology and improve patient diagnosis, management, and prognosis. Using the dataset, we conducted a retrospective cohort study to find which variables are significantly associated with PsO. These objective measurements can complement clinical assessments by providing quantifiable data that could improve accuracy by detecting PsO in its early stages or distinguishing it from other skin conditions with similar presentations. This enables healthcare providers to adjust management strategies based on measurable changes in disease markers, rather than relying solely on subjective clinical observations.