Impact of urinary PAHs on psoriasis risk in U.S. adults: Insights from NHANES.

Psoriasis is a common, chronic inflammatory skin condition that impacts approximately 2–3 percent of the world’s population [ 1 ]. Psoriasis is distinguished by well-defined red patches covered in silvery-white scales. These patches often appear symmetrically on the scalp or trunk and can cause varying degrees of itching [ 2 – 4 ]. Psoriasis has detrimental effects on both the skin and overall quality of life. It also decreases life expectancy and leads to several other health conditions, including psoriatic arthritis, diabetes, metabolic syndrome, and cardiovascular disease [ 5 ]. The precise cause of psoriasis is not completely understood. However, it is believed to be influenced by various variables including genetic predisposition, immunological dysregulation, and possible environmental influences [ 6 ]. Humans are exposed to an extensive range of pollutants originating from both human activities and natural sources. According to the World Health Organization (WHO), over 4.2 million individuals perish each year due to the effects of air pollution in the environment [ 7 ]. Polycyclic aromatic hydrocarbons (PAHs) are a significant part of the air pollutants found in the environment. They are produced and emitted into the air during the procedure of burning coal and oil, transportation, incinerating garbage, and steaming meals [ 8 ]. People’s lives and environmental exposure patterns have altered substantially as the world grows more urbanized and pollution levels rise. PAHs can be identified in water, soil, and air in trace amounts, and they are regularly encountered by humans through inhalation, ingestion, and skin contact in their daily environment. Furthermore, changes in environmental policy may have an impact on PAH emission and control, with potentially far-reaching consequences for public health. The impact of PAHs on the human body is mediated by intricate pathways, primarily through the Aryl hydrocarbon Receptor (AhR) pathway, oxidative stress pathway, and associated immunological issues [ 9 ]. Recent studies have shown that PAHs may increase the risk of several disorders, such as cardiovascular diseases [ 10 ], lung and skin cancers [ 11 ], hyperlipidemia [ 12 ], endometriosis [ 13 ], and neuropsychiatric abnormalities [ 14 ]. Prior NHANES studies demonstrated that exposure to elevated air pollution heightens the risk of inflammatory skin diseases such as psoriasis [ 15 , 16 ]. However, they were unable to examine urinary concentrations for specific PAHs and the potential correlation between various subgroups and psoriasis. Hence, understanding the link between PAH exposure and psoriasis is therefore critical in today’s context. Exploring their relationship can help us identify high-risk communities and provide data to politicians in order to enhance environmental quality and population health. This study made use of the NHANES dataset, which contains a wealth of information on the health status, nutritional intake, and environmental exposures of the United States population and serves as an important foundation for analyzing the relationship between PAH and the risk of psoriasis.

The individuals’ characteristics are presented in Table 1 . The study encompassed a total of 3,673 participants, ranging in age from 20 to 80. These subjects provided information about their psoriasis status and also underwent tests to measure urinary PAHs metabolites. Out of the entire participant group, 127 (3.5%) individuals were diagnosed with psoriasis, whereas the remaining 3,546 (96.5%) people did not have psoriasis. The mean age of the participants was 48.28 ± 16.58 years, with 51.18% being male. The majority of the participants were non-Hispanic whites (47.54%), held an AA or Some College degree (30.85%), and were unmarried (75.52%). Significant differences were observed between the psoriasis groups in terms of race, the prevalence of hyperlipidemia, serum cotinine levels, and urinary PAH metabolites including 2-NAP, 2-FLU, 3-FLU, 1-PHE, 2-PHE, 3-PHE, and 1-Hydroxypyrene (PYR). PIR, poverty income ratio; BMI, body mass index; NAP, Hydroxynaphthalene; FLU, Hydroxyfluorene; PHE, Hydroxyphenanthrene; PYR, Hydroxypyrene. The Pearson correlation analysis demonstrated significant associations among all metabolites, except for 1-NAP. Furthermore, the investigation showed a substantial correlation within the FLU and PHE metabolites. This was apparent from the heightened color intensity in their respective data representations, which indicated a more robust and dependable correlation ( Fig 2 ). The connection was statistically significant for all metabolites ( P 0.05. We utilized multivariate logistic regression modeling to establish the association between concentrations of PAHs and psoriasis ( Table 2 ). After doing calculations on the eight PAHs as continuous variables, we found a significant correlation between all PAH metabolites and the occurrence of psoriasis in crude Model 1, except for 1-NAP which had no link with psoriasis. Model 2 revealed that there was no correlation between 1-PHE and psoriasis. Similarly, the results were stable for model 3 even after considering all covariates. To be precise, when stratified by tertiles, compared to the lowest tertile: tertile 3 for 2-NAP (OR 1.63, 95% CI 1.02, 2.61), tertile 3 for 2-FLU (OR 1.83, 95% CI 1.14, 2.96), tertile 2 (OR 1.65, 95% CI 1.01, 2.69) and tertile 3 (OR 1.85, 95% CI 1.14, 3.00) for 3-PHE showed greater odds of psoriasis prevalence. This implies that when concentrations of these metabolites increase, so does the likelihood of acquiring psoriasis. Model 1 did not adjust any covariables. Model 2 adjusted for age, sex, and race. Model 3 adjusted for all covariates, including age, sex, race, education level, marital status, household income, PIR, BMI, alcohol use, presence of hypertension, diabetes, hyperlipidemia, and serum cotinine levels. OR, odds ratios; CI, confidence interval. In general, there was a positive correlation between the likelihood of getting psoriasis and urine PAH concentrations, as shown by the smoothed curve fit in Fig 3 . This correlation remained significant after accounting for all covariables. NAP, Hydroxynaphthalene; FLU, Hydroxyfluorene; PHE, Hydroxyphenanthrene; PYR, Hydroxypyrene. All PAH values were subjected to a log 2 transformation. In order to conduct a more thorough examination of the relationship between urinary PAHs and psoriasis, we conducted subgroup analyses by taking into account multiple factors such as gender, age, race, PIR, BMI, serum cotinine, and hyperlipidemia status. The findings of these analyses are displayed in Table 3 . Subgroup analyses demonstrated varying correlations between levels of urine PAH metabolites and psoriasis in different groups. In comparison, participants who were male, aged between 40–60 years, with a BMI >30, and suffered from hyperlipidemia showed a significant correlation between urinary PAH metabolite levels and psoriasis. Nevertheless, the correlation between urinary PAHs and psoriasis did not reveal a noteworthy interaction among the aforementioned variables ( P interaction > 0.05). NAP, Hydroxynaphthalene; FLU, Hydroxyfluorene; PHE, Hydroxyphenanthrene; PYR, Hydroxypyrene. The results are expressed as OR (95% CI). P value here is equivalent to P interaction. After accounting for all covariates, the WQS regression analysis revealed a significant positive correlation between the mixture of urine PAH metabolites and psoriasis (OR 1.43, 95% CI 1.11, 1.84). Among the mixes, 2-FLU had the most significant impact on psoriasis with a value of 0.297, followed by 2-NAP at 0.252 and 1-PHE at 0.177. This suggests that these substances have a crucial role in influencing the odds of psoriasis, as seen in Fig 4 . To minimize weakness in the distribution of concentrations, all urinary PAH metabolites underwent log 2 transformation. WQS, weighted quantile sum. NAP, Hydroxynaphthalene; FLU, Hydroxyfluorene; PHE, Hydroxyphenanthrene; PYR, Hydroxypyrene.

Urinary PAHs metabolite concentrations, including 2-NAP, 2-FLU, 3-FLU, 2-PHE, 3-PHE, and 1-PYR, were found to significantly positively associate with the odds of psoriasis prevalence. Significantly, out of all the compounds, 2-FLU had the greatest impact among the combination of urine PAH metabolites. Future research could use a longitudinal study design to track individuals’ PAH exposure and health changes over time in order to understand the dynamic link between the two better. Furthermore, mechanistic studies will be required to investigate how PAH influences the development of psoriasis via specific biological pathways. Combining these findings will contribute to a more complete knowledge and a scientific foundation for psoriasis preventive and intervention techniques.

All data are accessible on the NHANES website, a nationally representative cross-sectional survey of diet and health status in the United States. Each participant in the study provided their affirmative consent, and the NHANES protocol underwent a comprehensive evaluation and received permission from the National Center for Health Statistics Research Ethics Review Board. The study utilized data from the NHANES cycles of 2003–2006 and 2009–2012 to investigate the association between urine PAH concentrations and the odds of psoriasis. At the beginning, a total of 43,481 participants were included in the analysis across the four study cycles. The final study group comprised 3,673 participants after excluding 37,660 individuals without data on both urinary PAHs metabolites and psoriasis, as well as 400 participants under the age of 20 and 1,748 with incomplete information on education level, poverty income ratio (PIR), BMI, alcohol consumption, hypertension, diabetes, and hyperlipidemia. Fig 1 illustrates the precise criteria used to determine whether participants should be included or excluded from this study. Individuals who were at least 6 years old were eligible to take part in the test. We conducted a study on the quantification of eight urinary PAH metabolites: 1- Hydroxynaphthalene (NAP), 2-NAP, 2-Hydroxyfluorene (FLU), 3-FLU, 1-Hydroxyphenanthrene (PHE), 2-PHE, 3-PHE, 1-Hydroxypyrene(PYR). The results of this study were obtained in 2003–2006 based on capillary gas chromatography with high-resolution mass spectrometry (GC-HRMS), 2009–2012 based on isotope dilution capillary gas chromatography-tandem mass spectrometry (GC-MS/MS). Proficient technicians collected urine samples, which were then stored at a temperature of -20°C. The NHANES webpage offers comprehensive information regarding measurements. In accordance with NHANES laboratory guidelines, values below the lower limit of detection (LLOD) were computed as LLOD/√2. The concentration of PAHs (ng/L) in urine was normalized by dividing it by the urinary creatinine level (mg/dL) multiplied by 0.01. This normalization allows the data to be reported as nanograms per gram of creatinine and helps to minimize errors in the data. In order to facilitate analysis, the data were logarithmically converted. The diagnosis of psoriasis was ascertained through self-report on health questionnaires based on participants’ responses to the following question, “{Have you/Has SP} ever been told by a doctor or other health care professional that {you/s/he} had psoriasis?". If the subject answered "Yes," they were diagnosed with psoriasis. According to prior research on the prevalence of PAH and psoriasis [ 17 , 18 ], confounding factors such as an individual’s health management, socioeconomic status, and environmental exposures may influence the results. Thus, we chose the following variables as covariates, including age, gender, race, education level, marital status, PIR, BMI, alcohol consumption, serum cotinine levels, and the presence of hypertension, diabetes mellitus, and hyperlipidemia. The participants’ marital status was categorized as either unmarried or married. The poverty income ratio was categorized as either 0–4.99 or ≥5. The participants’ BMI was categorized into three groups: normal weight (30 kg/m 2 ) [ 19 ]. Hypertension was diagnosed based on systolic/diastolic blood pressure readings ≥ 130/80 mmHg, self-reported clinician diagnosis, or self-reported use of hypertension medications [ 20 ]. Glycosylated hemoglobin ≥6.5%, fasting blood glucose ≥ 7.0 mmol/L, self-reported medical diagnosis, or self-reported insulin use were used to identify diabetes [ 21 ]. The National Cholesterol Education Program (NCEP) Adult Treatment Panel III established the following criteria for hyperlipidemia: LDL-C ≥130 mg/dL, TC ≥200 mg/dL, TG ≥150 mg/dL, or HDL-C ≤50 mg/dL in women and ≤40 mg/dL in men [ 22 ]. Hyperlipidemia was also deemed to exist in those on anti-hyperlipidemic medications. Continuous variables are represented as mean ± standard deviation (SD), while categorical data is stated as percentage (%). The participants were classified into two distinct groups: those with psoriasis and those without psoriasis. The baseline characteristics of the population were assessed by employing linear regression models and chi-square tests, conducted separately for each group. Pearson correlation analysis was utilized to determine the correlation coefficients between PAH metabolites. A multivariate logistic regression model was created to explain the relationship between the eight urine PAH metabolites and the risk of psoriasis. In this analysis, we categorized the eight PAHs into three groups based on their distribution across tertiles: tertile 1, tertile 2, and tertile 3. Model 1 did not include any covariables. Model 2 adjusted for age, sex, and race, while Model 3 adjusted for all covariates, including age, sex, race, education level, marital status, PIR, BMI, alcohol use, presence of hypertension, diabetes, hyperlipidemia, and serum cotinine levels. The strength of the link was measured by calculating odds ratios (ORs) and 95% confidence intervals (CIs). We utilized smoothed curve-fitting to depict the connection between urine PAH metabolite concentrations and the risk of acquiring psoriasis. Furthermore, we conducted an interaction analysis to evaluate the correlation between levels of urine PAH metabolites and the odds of psoriasis in specific subgroups, with the aim of identifying potential risk factors. Lastly, we used the "gWQS" R package to execute a WQS regression in order to evaluate the impact of combining urine PAH metabolites on the prevalence of psoriasis. The cumulative impact of mixed urine PAH metabolites on psoriasis was demonstrated by this study, and the proportionate contribution of each exposure variable to the total effect was ascertained. The statistical analyses were conducted using R 4.3.1 and EmpowerStats 4.2 software. All tests were conducted using a two-sided approach, and a P -value <0.05 is considered to be significant. This study was based on a publicly available database and did not require ethical approval or consent. Studies involving humans were approved by the National Center for Health Statistics (NCHS). The studies were conducted in accordance with local legislation and institutional requirements. Participants provided written informed consent to participate in this study.

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