People around the world are continuously exposed to toxic substances in the air. Some contaminants are anthropogenic, such as automobile and factory emissions; others come from natural sources, including wildfires, and sand and dust storms. Some natural contaminants, such as allergens and microorganisms, are becoming more common as global temperatures rise.
The conventional approach to evaluating the impact of air pollution is to focus on a single exposure during a fixed period of time. But evidence suggests that contaminants work together, magnifying the damage to people’s lungs. Conventional studies fail to probe synergistic effects. They also ignore the cumulative effects of lifelong exposures to pollutants, known as the exposome. Researchers need to shift away from single-pollutant studies and towards those involving a broad range of exposures.
Nature Outlook: Lung health
Exposomics can be integrated with genomics, epigenomics and metabolomics to reveal how gene–environment interactions contribute to lung-disease risk. This mode of analysis provides information, for example, on how the environment modulates gene expression through epigenetic alterations, and how these changes affect health. Exposomics also tracks the impact of exposures over time and across lifespan at a population level, thereby mapping cumulative and time-dependent effects. For example, an analysis of longitudinal data from the European Human Early-Life Exposome (HELIX) cohort found that childhood exposure to copper, ethyl-paraben, five phthalate metabolites, overcrowding at home and increased density of non-residential development around schools were associated with reduced lung function1.
In one large study2, a total of 7,428 new cases of asthma were identified among about 350,000 participants. In adults, the risk of asthma was higher for clusters of cases associated with high particulate matter and nitrogen dioxide exposure. Areas that were highly built-up and had low levels of greenness were also associated with a risk of asthma for adults and children. Multiple exposures, such as these, showcase the strength of exposomic analysis.
Advances in digital exposomic technologies, such as wearable sensors and geospatial monitoring, allow the capture of high-resolution real-time data. Furthermore, improved computational analytics and increasingly sophisticated statistical tools are enabling the development of robust associations between environmental pollutants and disease. Exposome-wide association studies allow researchers to screen for associations between the environment and disease.
Numerous analytical tools are being used to discover mechanistic links and predict health risks. These tools can assist with isolating the most harmful compounds in a mixture, enable the discovery of biomarkers for diagnosis, determine social factors associated with increased risk of disease, address health disparities, personalize monitoring, help to tailor interventions and assist with policy decisions on key pollutants.
One study3 applied an exposomic approach to evaluate the health effects of pollutants on children living near a major landfill site in Athens. Using exposome-analysis tools and integrating diverse data sets, the study found that proximity to a site was associated with lower neurodevelopment scores in children, which was related to heavy-metal exposure. The study also found that this effect was significantly modified by factors such as parental education level, socioeconomic status and nutrition.
Numerous barriers impede broader use of exposomics, however. One is the conceptual and practical challenge of defining and measuring the exposome — largely because it varies temporally and geographically. Moreover, the sheer volume and diversity of exposures requires tools and technologies that are not always available or affordable, including high-throughput ‘omics’ techniques, environmental sensors and advanced data processing. Exposomic measurements can also have low specificity and sensitivity, increasing the risk of false positives and spurious associations. Detaching the data from theory can also mean that the results of exposomic studies can be difficult to translate into clinical practice.
If exposomic research is to fulfil its promise, progress is required on several fronts. First, scientists should collect data on exposures and not discount them from their experiments. Second, regulations to safeguard privacy on location, metadata in health records and medication records should be put in place to protect personal data. Third, a network of hubs such as databases and data centres must be put in place to enable comprehensive data for exposures and analysis across all ethnicities and backgrounds. This can be done through collaborations by scientists and clinicians across a range of disciplines, such as meteorology, nutrition and environmental science. There has been progress — most notably the establishment of large databases such as HELIX, the European Human Exposome Network (EHEN) and the International Human Exposome Network (IHEN).
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