Unraveling Multimorbidity Patterns of Psoriasis Using Network Analysis

Abstract

Background

Psoriasis is a chronic disease with a prevalence of 3% in the general population. The high prevalence of psoriasis has prompted the study of its comorbidities in recent decades. However, no studies have ever analyzed comorbidity patterns including all chronic diseases in psoriatic patients.

Objectives

To identify comorbidity patterns in psoriatic patients using network analysis and describe them from a clinical point of view.

Methods

We conducted an observational and retrospective study with individuals of the EpiChron Cohort (Aragón, Spain) diagnosed with psoriasis from January 1st, 2010 through December 31st, 2019. The population was stratified by sex and age intervals (0–11, 12–17, 18–44, 45–64, ≥65). We built a network for each stratum (i.e., 5 for each sex), calculating the tetrachoric correlations of each pair of diseases. We used a cut-off threshold for statistical significance of p-value <0.01. We applied the Louvain community detection algorithm to identify clusters of diseases.

Results

The prevalence of psoriasis in Aragón was found to be 2.84%. We identified a total of 31,178 psoriatic patients (54% men, 61% from metropolitan areas). The most common comorbidities were respiratory diseases, cardiometabolic conditions (such as hypertension and dyslipidemia), and mental health disorders (including anxiety and mood disorders). A total of 21 comorbidity patterns were identified, varying by sex and age group.

Conclusions

This is the first study ever conducted with a comprehensive analysis of the disease patterns of psoriatic patients. Our results are a comprehensive map of possible psoriasis-related comorbidities. Further studies should confirm these associations and their pathophysiological relationship with psoriasis, which could help to detect and prevent comorbidities and modifiable risk factors.