Beyond DNA: How Exposomics Maps Lifetime Environmental Risks to Transform Medicine

Researchers are expanding the focus of biomedical science beyond genes to a growing discipline called exposomics, which seeks to catalog the full range of chemical, physical, social and biological exposures a person encounters across their life. Proponents argue that combining this "exposomic" view with genomics will give clinicians a more complete understanding of disease risk and better tools for prevention and personalized care.

What is exposomics?

Exposomics aims to create a comprehensive map of lifetime exposures—everything from air pollution, diet and biomarkers measured in blood or urine to temperature, light, socioeconomic status and physical activity. Experts cite analyses suggesting that genetic mutations may account for only about 10% of the risk for some conditions (for example, Parkinson's disease), with the remaining burden shaped by environmental and lifestyle factors. That gap has driven interest in systematically measuring and interpreting exposures across the life course.

Why it matters

Instead of searching for single, isolated causes of disease, exposomics focuses on the complex set of interacting influences that shape health. The ultimate goal is to translate the resulting data into practical, personalized interventions—potentially by including an "exposomic profile" in electronic health records alongside genetic information.

Tools and technologies driving progress

• Geospatial data: Satellite imagery and social-determinants datasets quantify location-specific exposures such as air pollution, green space and water quality.
• High-resolution mass spectrometry: Advanced chemical analysis can detect thousands of molecular markers in biological samples, revealing previously unseen exposure signals.
• Wearable samplers: Devices like Stanford Medicine's "exposometer" can collect environmental and biological samples from people as they go about daily life.
• Computational methods: Machine learning and systems-level models help integrate heterogeneous data streams and identify meaningful exposure–disease relationships.

Collaboration, progress and challenges

Exposomics is inherently interdisciplinary, requiring collaboration among geneticists, environmental scientists, epidemiologists, data scientists and clinicians. Last year, the National Institutes of Health awarded a $7.7 million grant to establish the Network for Exposomics in the United States (NEXUS), a national coordinating center that will support shared methods, data standards and collaborative studies.

Leaders in the field emphasize discovery-based approaches made possible by non-targeted mass spectrometry and advanced analytics. Chirag Patel, associate professor at Harvard Medical School and a NEXUS co-leader, notes that his lab uses computational models and artificial intelligence to sort through vast, heterogeneous datasets. Rima Habre, NEXUS co-leader and associate professor at USC, describes exposomics as a way to scan broadly for signals and then follow up with focused hypothesis testing. Gary Miller, vice dean for research strategy and innovation at Columbia University's Mailman School of Public Health, stresses that genomics and exposomics are complementary.

Important hurdles remain: managing and standardizing enormous datasets, ensuring privacy and ethical use of personal exposure information, addressing disparities in who is studied, and translating research findings into clinical practice. Nonetheless, rapid technological advances and new funding initiatives are accelerating progress toward integrating exposomic data into health decision-making.

Looking ahead

As exposomics matures, clinicians may have access to richer exposure histories to inform prevention, early detection and personalized treatment plans. By pairing genetic and exposomic profiles, researchers hope to reveal the environmental and social contributors to disease that genomics alone cannot explain.