Exposure to Air Pollution, Genetic Susceptibility, and Psoriasis Risk in the UK
Open accessAbstract
Importance: Psoriasis is a common autoinflammatory disease influenced by complex interactions between environmental and genetic factors. The influence of long-term air pollution exposure on psoriasis remains underexplored. Objective: To examine the association between long-term exposure to air pollution and psoriasis and the interaction between air pollution and genetic susceptibility for incident psoriasis. Design, Setting, and Participants: This prospective cohort study used data from the UK Biobank. The analysis sample included individuals who were psoriasis free at baseline and had available data on air pollution exposure. Genetic analyses were restricted to White participants. Data were analyzed between November 1 and December 10, 2023. Exposures: Exposure to nitrogen dioxide (NO 2), nitrogen oxides (NO x), fine particulate matter with a diameter less than 2.5 µm (PM 2.5), and particulate matter with a diameter less than 10 µm (PM 10) and genetic susceptibility for psoriasis. Main Outcomes and Measures: To ascertain the association of long-term exposure to NO 2, NO x, PM 2.5, and PM 10 with the risk of psoriasis, a Cox proportional hazards model with time-varying air pollution exposure was used. Cox models were also used to explore the potential interplay between air pollutant exposure and genetic susceptibility for the risk of psoriasis incidence. Results: A total of 474 055 individuals were included, with a mean (SD) age of 56.54 (8.09) years and 257 686 (54.36%) female participants. There were 9186 participants (1.94%) identified as Asian or Asian British, 7542 (1.59%) as Black or Black British, and 446 637 (94.22%) as White European. During a median (IQR) follow-up of 11.91 (11.21-12.59) years, 4031 incident psoriasis events were recorded. There was a positive association between the risk of psoriasis and air pollutant exposure. For every IQR increase in PM 2.5, PM 10, NO 2, and NO x, the hazard ratios (HRs) were 1.41 (95% CI, 1.35-1.46), 1.47 (95% CI, 1.41-1.52), 1.28 (95% CI, 1.23-1.33), and 1.19 (95% CI, 1.14-1.24), respectively. When comparing individuals in the lowest exposure quartile (Q1) with those in the highest exposure quartile (Q4), the multivariate-adjusted HRs were 2.01 (95% CI, 1.83-2.20) for PM 2.5, 2.21 (95% CI, 2.02-2.43) for PM 10, 1.64 (95% CI, 1.49-1.80) for NO 2, and 1.34 (95% CI, 1.22-1.47) for NO x. Moreover, significant interactions between air pollution and genetic predisposition for incident psoriasis were observed. In the subset of 446 637 White individuals, the findings indicated a substantial risk of psoriasis development in participants exposed to the highest quartile of air pollution levels concomitant with high genetic risk compared with those in the lowest quartile of air pollution levels with low genetic risk (PM 2.5: HR, 4.11; 95% CI, 3.46-4.90; PM 10: HR, 4.29; 95% CI, 3.61-5.08; NO 2: HR, 2.95; 95% CI, 2.49-3.50; NO x: HR, 2.44; 95% CI, 2.08-2.87). Conclusions and Relevance: In this prospective cohort study of the association between air pollution and psoriasis, long-term exposure to air pollution was associated with increased psoriasis risk. There was an interaction between air pollution and genetic susceptibility on psoriasis risk.
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The long-term association of psoriasis was mainly stronger with particulate pollutants.
“while the long-term association of psoriasis was mainly stronger with particulate pollutants [34, 70].”
From Air Pollution and Skin Diseases: A Systematic Review of Epidemiological Evidence (2026) · cites this paper as [70]
The interactive effect between genetic risks and air pollution showed a higher risk of atopic dermatitis and incident psoriasis at higher genetic risk/genetic susceptibility and higher air pollution levels.
“The interactive effect between genetic risks and AP showed a higher risk of AD and incident psoriasis at higher genetic risk/genetic susceptibility and higher AP levels [32, 70].”
From Air Pollution and Skin Diseases: A Systematic Review of Epidemiological Evidence (2026) · cites this paper as [70]
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- Authors
- Wu, J., Ma, Y., Yang, J., & Tian, Y.
- Affiliations
- Peking University (CN)
- Huazhong University of Science and Technology (CN)
- China Three Gorges University (CN)
- Corresponding author
- Yang, Jian
- Tian, Yaohua
- Venue
- JAMA Network Open
- Publisher
- American Medical Association (AMA)
- Published
- 2024-07-16
- Volume
- 7
- Issue
- 7
- Pages
- e2421665
- ISSN
- 2574-3805 (ISSN-L)
- PMC
- PMC11252902
- OpenAlex
- W4400683151
- Cited by
- 38
- References
- 44
- Citations by year
- 2026: 12 · 2025: 20 · 2024: 6
- FWCI
- 6.71
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- JAMA Network Open (publishedVersion, cc-by)
- PubMed (publishedVersion)
- PubMed Central (publishedVersion, cc-by)
- Funders
- China Postdoctoral Science Foundation (2022TQ0017, 2022M720303)
- Topics
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Air Quality and Health Impacts
- Life Sciences › Immunology and Microbiology › Immunology › Psoriasis: Treatment and Pathogenesis
- Health Sciences › Medicine › Dermatology › Dermatology and Skin Diseases
- Keywords
- psoriasis, air pollution, long-term exposure, genetic susceptibility, nitrogen dioxide, nitrogen oxides, PM2.5, PM10, gene-environment interaction, autoinflammatory disease, UK Biobank, environmental risk factors, genetic risk variants, urban-rural differences
- MeSH terms
- Adult, Aged, Air Pollutants, Air Pollution, Environmental Exposure, Female, United Kingdom, Humans, Male, Middle Aged, Nitrogen Dioxide, Nitrogen Oxides, Prospective Studies, Psoriasis, Risk Factors, Incidence, Proportional Hazards Models, Genetic Predisposition to Disease, Particulate Matter
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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