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. 2025 Feb 11;22(1):6.
doi: 10.1186/s12979-025-00500-4.

The relationship between biological aging and psoriasis: evidence from three observational studies

Zheng Lin #  1 , Hong-Fei Wang #  1 , Lu-Yan Yu #  1 , Jia Chen  1 , Cheng-Cheng Kong  2 , Bin Zhang  2 , Xuan Wu  1 , Hao-Nan Wang  1 , Yi Cao  3 , Ping Lin  4
Affiliations

The relationship between biological aging and psoriasis: evidence from three observational studies

Zheng Lin et al. Immun Ageing. .

Abstract

Background: The relationship between psoriasis and aging remains unclear. Biological age is considered as a tool for strong association with aging, but there is a lack of reports on the relationship between biological age and psoriasis. Therefore, this study aimed to explore the relationship between biological age and psoriasis.

Methods: Patients with psoriasis and non-psoriasis were recruited from National Health and Nutrition Examination Survey (NHANES) (12,973 cases), Medical Information Mart for Intensive Care (MIMIC-IV) (558 cases) and The First Clinical Medical College of Zhejiang Chinese Medical University (206 cases). Biological age was calculated using Klemera-Doubal method age (KDM-age) and phenotypic age (PhenoAge). Linear regression and logistic regression were used to explore the association between psoriasis and biological age advance. Cox regression was used to investigate the association between biological age advance and mortality. Finally, biological age advance was used to predict the death of psoriasis patients.

Results: In NHANES, linear regression showed that psoriasis led to a 0.54 advance in PhenoAge (Adjust Beta: 0.54, 95CI: 0.12-0.97, p = 0.018). The KDM-age advance due to psoriasis was not statistically significant (p = 0.754). Using data from China, we came to the new conclusion that for every unit rise in Psoriasis Area and Severity Index, PhenoAge advance rose by 0.12 (Beta: 0.12, 95CI: 0.01-0.22, p = 0.031). Using NHANES data, cox regression shows for every unit rise in PhenoAge advance patients had an 8% rise in mortality (Adjust hazard ratio: 1.08, 95CI: 1.04-1.12, p < 0.001). Using MIMIC-IV, logistic regression showed a 13% increase in mortality within 28 days of admission for every 1 unit rise in PhenoAge advance (odds ratio: 1.13, 95CI: 1.09-1.18, P < 0.001). Finally, we used PhenoAge advance to predict death, with an AUC of 0.71 in the NHANES, an ACU of 0.79 for predicting death within 1 years in the general ward of MIMIC-IV. In the ICU of MIMIC-IV, the AUC for predicting death within 28 days was 0.71.

Conclusion: Psoriasis leads to accelerated biological aging in patients, which is associated with the severity of psoriasis and more comorbidities. In addition, PhenoAge has the potential to monitor the health status of patients with psoriasis.

Keywords: Aging; Biological age; MIMIC-IV; NHANES; Phenotypic age; Psoriasis.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: All NHANES protocols were approved by the NCHS Research Ethics Review Board (Protocol #98- 12, Continuation of Protocol #2005–06, Continuation of Protocol #2011–23, http://www.cdc.gov/nchs/nhanes/irba98.htm ) and informed consent was obtained at participant enrollment. For compliance, author Zheng Lin obtained a Collaborative Institutional Training Initiative (CITI) (record ID: 13501620) and the necessary permissions to use the MIMIC-IV database. The database includes comprehensive information on each patient’s length of stay, laboratory tests, medication administration, and vital signs. To protect patient privacy, all personal information is de-identified and random codes are used instead of patient identifiers. Therefore, this section does not require patient consent or ethical approval. The research program carried out in The First Clinical Medical College of Zhejiang Chinese Medical University was approved by the Ethics Review Committee of The First Clinical Medical College of Zhejiang Chinese Medical University. Since we only reviewed the existing database, the Ethics Committee exempted patients from informed consent (2024-KLS-683–01). Consent for publication: This manuscript does not contain personal information about any of the study participants. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
Flow chart
Fig. 2
Fig. 2
Association between biological age advance and psoriasis in NHANES. A, B, C is weighted linear regression. D, E, F is weighted logistic regression
Fig. 3
Fig. 3
Restricted cubic spline between PhenoAge advance and psoriasis in NHANES
Fig. 4
Fig. 4
Correlation heat maps of variables associated with PhenoAge advance in psoriasis patients in NHANES
Fig. 5
Fig. 5
Association between biological age advance and psoriasis in China population. A is linear regression. B is logistic regression. C is restricted cubic spline between PhenoAge advance and PASI
Fig. 6
Fig. 6
Kaplan–Meier curve of psoriasis population in NHANES (according to PhenoAge advance accelerate)
Fig. 7
Fig. 7
Association between biological aging and mortality in patients with psoriasis in NHANES
Fig. 8
Fig. 8
Restricted cubic spline between PhenoAge advance and mortality in NHANES
Fig. 9
Fig. 9
Kaplan–Meier curve of psoriasis population in MIMIC (according to PhenoAge advance top 50%)
Fig. 10
Fig. 10
Association between biological aging and mortality in patients with psoriasis in MIMIC
Fig. 11
Fig. 11
ROC curve for biological age prediction of mortality. A—NHANES. B—MIMIC’s general ward. C—MIMIC’s ICU
Fig. 12
Fig. 12
A vision for including PhenoAge in the management of clinical psoriasis patients
See this image and copyright information in PMC

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