After decades of focusing primarily on genetics, the biomedical research community is shifting its attention toward a broader, more comprehensive framework known as the "exposome." Inspired by the mapping of the human genome, exposomics seeks to catalog the full range of environmental and lifestyle factors a person is exposed to throughout their life—chemical, physical, social, and biological. This emerging field represents a major evolution in understanding disease origins. Experts estimate that genetic factors account for only about 10% of diseases such as Parkinson’s, with the remaining 90% attributed to environmental influences. This realization has driven scientists to look beyond DNA and explore the complex web of external exposures that shape health and disease risk, according to the Association of American Medical Colleges (AAMC). Exposomic data encompasses a wide array of information, including air and water quality, light and temperature, dietary patterns, physical activity levels, income, education, stress, and even the presence of environmental chemicals in blood or other bodily fluids. The goal is to create a detailed, individualized "exposomic profile" that captures a person’s lifetime of environmental interactions. Researchers envision a future in which this profile is integrated into electronic health records, enabling more personalized and proactive healthcare. Gary Miller, vice dean for research strategy and innovation at Columbia University Mailman School of Public Health and a pioneer of the term, says the field is finally gaining momentum after two decades of conceptual development. Last year, the Network for Exposomics in the United States (NEXUS) was established as a national coordinating center to advance this work. Exposomics is inherently interdisciplinary, requiring collaboration among experts in genetics, environmental science, epidemiology, data science, and artificial intelligence. The challenge lies in capturing the full complexity of human exposure over time. Rather than focusing on isolated causes, exposomics aims to build a holistic picture of how multiple factors interact across a lifetime to influence health outcomes. Advances in technology are fueling this transformation. High-throughput analytical tools, such as non-targeted mass spectrometry, allow scientists to detect thousands of chemicals in biological samples simultaneously. Computational models and artificial intelligence are essential for processing and interpreting the vast datasets generated. Chirag Patel, an associate professor at Harvard Medical School and co-leader of NEXUS, explains that his team uses AI to sift through massive amounts of data, moving away from traditional hypothesis-driven research toward discovery-based approaches. “We’re shifting from asking specific questions to scanning everything and then exploring what we find,” Patel said. Rima Habre, also co-leader of NEXUS and associate professor at the University of Southern California Keck School of Medicine, believes exposomics can reduce reliance on clinical guesswork. By systematically analyzing exposures, researchers can uncover hidden patterns and generate new hypotheses for testing. As Miller emphasizes, the future of health science lies in integrating both genomics and exposomics. “They’re not competing—they’re complementary. Only by combining the two can we truly understand what drives disease and how to prevent it.”