Digital epigenetics: At the crossroads of data, the epigenome, and artificial intelligence

I n recent decades, traditional epidemiology, which emphasizes the systematic collection of clinical and questionnaire-based data, has significantly transformed in response to a remarkable influx of largescale digital data, social network analytics, and sensorbased information. 1,2This transformation, known as digital epidemiology, has changed the landscape of identifying disease trends and tracking public health.In parallel, epigenetics-a field that combines molecular biology and epidemiology to elucidate the impact of environmental factors on gene expression-has become increasingly important in the realms of public health research and precision medicine. 3Populationbased epigenetic studies, or epigenetic epidemiology, offer a profound understanding of how environmental, social, and behavioral exposures shape disease risk.Advanced molecular techniques such as epigenome-wide association studies (EWAS) have been established to assess and interpret epigenetic markers at scale. [4][5]][6] In this editorial, we present a forward-looking vision for epigenetics, drawing upon a synthesis of significant literature in digital epidemiology, epigenetics, and artificial intelligence (AI).Our central thesis is that the field must move beyond isolated approaches and explicitly promote the integration of large-scale digital data with population-level epigenetic profiles via advanced AI.We assert that this is not solely an incremental step, but an essential convergence to unveil previously unattainable insights into gene-environment interactions and evolving exposure patterns, influencing the future direction of this emerging field.The convergence of these two domains-scalable digital data and molecular epigenetic signals-promises the advent of a novel discipline that we may call digital epigenetics.This emerging field seeks to generate large data sets that encompass environmental, neurobiological, and epigenetic data, collected from a wide variety of digital sources including electronic health records, real-time monitoring via wearable devices such as smartwatches, and large omics databases, all analyzed through advanced Digital epigenetics: At the crossroads of data, the epigenome, and artificial intelligence