Comparison with existing literature

Previous studies have explored the potential relationship between short-term exposure to air pollution and schizophrenia. However, the results were inconsistent. A systematic review conducted in 2022, which summarised 13 papers, found a positive correlation between short-term exposure to PM_2.5, PM_C (coarse fraction, diameter 2.5–10 μm) and PM₁₀ and the risk of schizophrenia.^{Reference Song, Liu, Wei, Li, Liu and Yuan22} In the current study, we found similar results that long-term exposure to air pollutants, including particulate matter and nitrogen oxides, is linked to increased risk of schizophrenia. However, completely contrary results have been found in other studies. For instance, a study carried out in three subtropical Chinese cities reported that short-term PM_2.5 exposure did not exhibit any association with schizophrenia risk.^{Reference Li, Zhang, Qian, Xie, Luo and Han10} Additionally, although some studies have identified a positive effect of NO₂ on the increased risk of schizophrenia,^{Reference Song, Liu, Wei, Li, Liu and Yuan22} others have observed no significant results regarding the association of short-term exposure to NO₂ and NO_x and the risk of schizophrenia.^{Reference Ji, Liu, Song, Pan, Cheng and Wang23} Unlike these studies on short-term pollution exposure, only one national study has used long-term air pollution exposure data and suggested positive associations between long-term exposure and schizophrenia in adults.^{Reference Antonsen, Mok, Webb, Mortensen, McGrath and Agerbo11}

In our study, we assessed air pollution exposure by matching it to residential addresses with a spatial resolution of 1 × 1 km. This method has been widely adopted in previous research to investigate the relationship between air pollution and various diseases, including mental disorders.^{Reference Liu, Lim, Pedersen, Jørgensen, Amini and Cole-Hunter5,Reference Li, Ma, Cui, Yang, Liu and Tang14} A Danish study matched children's addresses with air pollution information, confirming a positive relationship between air pollution and schizophrenia risk.^{Reference Antonsen, Mok, Webb, Mortensen, McGrath and Agerbo11} Similar results were observed in our study of adults. Moreover, the consistency in methodologies across these studies, including our own, reinforces the reliability and relevance of using address-matched air pollution data to probe the intricate association of air pollution and mental illness. Our findings for the four air pollutants and schizophrenia risk provide new evidence for future insights.

Potential confounders

There are other confounders that can influence the risk of schizophrenia. For instance, evidence shows that metropolitan indoor environments may contribute significantly to overall exposure to adverse environmental conditions, particularly for people in industrialised nations.^{Reference O'Lenick, Wilhelmi, Michael, Hayden, Baniassadi and Wiedinmyer24} Despite this, most population-based epidemiological studies have primarily focused on outdoor exposure, owing to data availability, neglecting indoor conditions. Quantifying relationships between indoor environments and health remains a substantial challenge. Furthermore, although the current study indicates a positive association between long-term air pollution exposure and increased schizophrenia risk, observational research design does not support the view that air pollutants causally affect the schizophrenia risk. Considering the facts that unmeasured and unknown potential covariates may exist and associations do not mean causality, the results should be interpreted with caution. Further research is warranted to examine the causality of air pollution in relation to schizophrenia risk using methods of causal inference such as intervention studies.

Derivation of the schizophrenia PRS

The PRS calculated by aggregating multiple variants has the capacity to evaluate genetic susceptibility and identify people with high genetic risk.^{Reference Lewis and Vassos13} The current study used a standard set of PRS for schizophrenia generated by the UK Biobank. The UK Biobank PRS Release provides well-validated PRS across multiple diseases. The UK Biobank's PRS algorithm was developed using trait-specific meta-analyses based on a Bayesian approach, appropriately pooling data across various ancestries and related traits; these tools are especially valuable as PRS algorithms move beyond simple linear combinations of variant weights.^{Reference Thompson, Wells, Selzam, Peneva, Moore and Sharp19} Furthermore, although validating the performance of PRS or comparing different PRS algorithms presents considerable challenges, the UK Biobank has developed and released a robust PRS evaluation tool to facilitate comprehensive and comparable assessments of predictive performance across various PRS in the UK Biobank data-set. Broad benchmark tests have shown that the PRS in the UK Biobank Release outperforms a series of published PRS. Additionally, the UK Biobank is set to routinely update its PRS Release, with goals to improve performance and enlarge the range of traits included. This approach anticipates the ongoing development of improved PRS scores as both data and methodologies progress, facilitating continuous research and advancements in clinical model development.

Biological mechanisms underlying the link between air pollution and schizophrenia

Suggested mechanisms underlying the increased schizophrenia risk due to air pollutants are currently limited and still being explored. Research indicates that air pollution can reach and affect the brain by various pathways, including through the nasal pathway and olfactory bulbs or through respiration, systemic circulation and the blood–brain barrier.^{Reference Genc, Zadeoglulari, Fuss and Genc25} Air pollutants have the potential to induce neuroinflammation, endothelial dysfunction and microglia activation and cause cerebrovascular injury,^{Reference Li, Han, Guo, Li and Sang7,Reference Genc, Zadeoglulari, Fuss and Genc25} thereby promoting mental disorders, including schizophrenia. Experimental studies conducted on mice have demonstrated that PM₁₀ can trigger inflammation and endothelial dysfunction in the brain.^{Reference Guo, Zhu, Guo, Li, Chen and Sang26} Air pollution has also been shown to affect central nervous system (CNS) function by activating microglia, with ensuing oxidative stress and neuroinflammation,^{Reference Genc, Zadeoglulari, Fuss and Genc25} which may increase the schizophrenia risk. Mice experiments have also found that NO₂ can generate reactive nitrogen species (RNS) and reactive oxygen species (ROS), damaging mitochondria in the brain.^{Reference Yan, Ji, Shi, Li and Sang27} Population studies have further revealed that environmental PM_2.5 can increase the risk of relapse in schizophrenia through the mediation of cytokines, including IL-17 and IL-13.^{Reference Gao, Wei, Pan, Yi, Xu and Duan6} The above evidence indicates that each pollutant may act through distinct mechanisms and have varying associations with schizophrenia. Future exploration is required to understand the specific biological mechanisms by which various air pollutants contribute to the pathogenesis of schizophrenia.

Genetic susceptibility to schizophrenia

Existing studies have established that schizophrenia's aetiology is multifactorial, with a substantial genetic component. GWAS have reported that numerous common variants, each with a minor impact, are associated with schizophrenia. Over 100 loci have been found to be significantly linked to schizophrenia.¹² PRS has been demonstrated to be associated with the risk of schizophrenia and it accounted for approximately 7.7% of the variability in schizophrenia case–control status.^{Reference Trubetskoy, Pardiñas, Qi, Panagiotaropoulou, Awasthi and Bigdeli28} In the current study, we examined the role of genetic factors in the connection between air pollution and schizophrenia, and observed that genetic susceptibility exacerbates the increased schizophrenia risk in relation to air pollution, especially in participants with high genetic susceptibility. The cellular mechanisms underlying the joint effect of air pollution and genetic factors on schizophrenia are not elucidated. However, previous studies have summarised the association of genetic factors and air pollutants in relation to other mental diseases,^{Reference Li, Ma, Cui, Yang, Liu and Tang14} and a few studies also indicated that genetic factors may affect schizophrenia through a common mechanism in air pollution such as the YWHA gene family,^{Reference Lei, Huang, Li, Zhong, Chen and Pan16} implying that air pollutants and genetic variations might lead to schizophrenia by means of shared mechanistic pathways such as oxidative stress, neuroinflammation and endothelial dysfunction.

Strengths and limitations

The study included some notable strengths that enhance its validity and reliability. A large sample and a prospective study design were employed to enhance the statistical power. Furthermore, reliable nationwide data on time-varying exposure to air pollutants were used. Finally, a novel aspect of the study was the investigation of the interaction and joint impact of air pollutants, genetic factors and schizophrenia risk, which has never been conducted previously. Based on these strengths, we discovered that air pollution has a more extensive impact than previously believed. It affects not only physical health but also significantly affects mental health. The findings emphasise the need for disease prevention and mental health improvement through reductions in air pollution. Moreover, our study reaffirms the positive correlation between air pollution exposure and schizophrenia risk. These findings offer new insights into managing schizophrenia, which is a hidden yet significant public health challenge causing daily difficulties and considerable societal expense. These findings enhance our understanding of the environmental factors linked to this condition and underscore the pressing need for better air pollution control measures.

Nevertheless, some limitations of our study need to be acknowledged. First, in the UK Biobank, a swift and efficient recruitment process yielded a sample of 500 000 participants. However, this efficiency was accompanied by a response rate of 5.5%, raising the possibility of selection bias. However, the actual difference in these estimates is small, and consequences of potentially underestimating such risks are expected to be minimal.^{Reference Stamatakis, Owen, Shepherd, Drayton, Hamer and Bauman29} Second, since we did not directly measure personal exposure to air pollution, there may be methodological issues regarding ecological fallacy and potential misclassification errors in exposure. One of the methods to reduce the ecological fallacy is the use of the smaller spatial units. In this study, we estimated the concentrations of ambient air pollution at a spatial resolution of 1 × 1 km, which is a reasonably fine precision of exposure modelling. However, it should be noted that the existence of an ecological fallacy cannot be completely avoided with this measure. Third, the UK Biobank data-set has only limited information on the composition of air pollution, and consequently, uncertainty remains regarding the specific components of air pollution that may be most harmful. Fourth, the identification of incident schizophrenia cases based only on registered medical information and healthcare records may not capture all cases accurately. It is possible that individuals with milder forms of schizophrenia may not seek medical attention, leading to underreporting of schizophrenia cases. Fifth, the identification of incident schizophrenia cases in the UK Biobank cohort relied on the ICD-10 coding system. The use of ICD-10 codes in administrative databases presents an opportunity for studying medical conditions and a variety of diseases in a large ‘real-world’ setting.^{Reference Pu, Ramani, Chen, Perry and Hong30} However, it is important to acknowledge inherent limitations in population studies using ICD-10 codes, which can include the possibility of misclassification or underdiagnosis. These inaccuracies are generally unrelated to air pollutant levels and often result in less precise estimates while also potentially biasing the risk estimates downwards.^{Reference Wellenius, Schwartz and Mittleman31} Sixth, despite adjusting for numerous potential confounding variables in our analysis, there is still a possibility of residual confounding from unmeasured or unknown factors. Seventh, although we used a time-varying analysis, which is an effective method of avoiding introducing immortal time bias, it remains possible that immortal time bias may have influenced the quantitative results, and caution should be exercised in extrapolating these findings. Eighth, all individuals included in the study were drawn from the UK Biobank, with the predominant proportion being White, which could potentially reduce the generalisation to diverse populations. Therefore, it is imperative to validate the existing results in other ethnicities. Finally, we did not account for the impact of indoor air pollution, owing to the lack of relevant data in the UK Biobank. Although ambient sources contribute the most to indoor air pollution levels and the effect of indoor sources may not be as significant as that of outdoor sources,^{Reference Liu, Zhou, Wang and Zhao32} we should be aware that the time spent indoors has continuously increased with the scale-up of cities, a better understanding of the contribution of the indoor environment on mental health is necessary to protect human health now and in the future.