Circulating metabolites associated with psoriasis in the UK Biobank and the HUNT Study: A cross-sectional study of 270,848 participants

Background

Psoriasis is recognized as a systemic inflammatory disease associated with metabolic dysregulation. Understanding these metabolic changes may reveal biomarkers to elucidate disease mechanisms and predict comorbidities. While previous studies have identified psoriasis-associated metabolites, findings are often limited by sample sizes and lack validation.

Objectives

We aimed to identify circulating metabolites associated with psoriasis, including cutaneous activity, severity, and psoriatic arthritis. Further, we investigated whether the metabolic signature was disease-specific compared to other immune-mediated inflammatory diseases (IMIDs).

Methods

We performed a cross-sectional analysis of 270,848 White/European individuals from the UK Biobank (n=253,924) and HUNT (n=16,924). Both cohorts used nuclear magnetic resonance spectroscopy to quantify metabolite levels, covering lipoprotein fractions and subfractions, fatty acids, and small-molecular metabolites. For each metabolite, we performed multivariable linear regression adjusting for age, sex, BMI, smoking status, and use of lipid-lowering medications.

Results

The metabolomic profile of psoriasis was largely consistent across the two cohorts. In the model adjusted for age and sex, 116 metabolic measures were associated with psoriasis in both cohorts. After full adjustment, only Glycoprotein acetyls (GlycA) remained associated with psoriasis (coefficient [95% CI]: 0.09 [0.07-0.11] in UK Biobank and 0.11 [0.06-0.17] in HUNT). Despite more substantial metabolic alterations in cutaneous-active psoriasis, GlycA was also elevated in HUNT participants reporting no active psoriasis rash (coefficient [95% CI]: 0.12 [0.04-0.20] in non-cutaneous-active and 0.11 [0.03-0.19] in cutaneous-active psoriasis). In HUNT, severe psoriasis exhibited more pronounced metabolic alterations compared to non-severe psoriasis. Across both cohorts, phenylalanine levels were highly elevated in psoriatic arthritis compared to cutaneous psoriasis (coefficient [95% CI]: 0.41 [0.20-0.62] in UK Biobank and 0.47 [0.28-0.67] in HUNT). All IMIDs showed elevated GlycA and reduced albumin, with milder changes in atopic dermatitis. Notably, psoriasis in the HUNT cohort exhibited a distinct lipoprotein profile compared to other IMIDs.

Conclusions

This large-scale, cross-cohort study confirms metabolic alterations in individuals with psoriasis and highlights elevated GlycA levels regardless of cutaneous activity. The distinct metabolomic profile of psoriasis relative to other IMIDs suggests a potentially unique systemic profile. These findings offer a foundation for advancing biomarker research and mechanistic studies for psoriasis.

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