Salīdzināt metodes

	Life-Course Epidemiology	Exposome-Wide Association Study
Nozare	Social Epidemiology	Social Epidemiology
Saime	Process / pipeline	Regression model
Izcelsmes gads	2002	2010
Autors	Yoav Ben-Shlomo & Diana Kuh	Chirag J. Patel, Jayanta Bhattacharya & Atul J. Butte (ExWAS); Christopher P. Wild (exposome concept)
Tips	Conceptual and analytic framework for long-term exposure-disease modeling	Agnostic high-throughput association scan over many environmental exposures
Pirmavots	Ben-Shlomo, Y., & Kuh, D. (2002). A life course approach to chronic disease epidemiology: conceptual models, empirical challenges and interdisciplinary perspectives. International Journal of Epidemiology, 31(2), 285-293.	Patel, C. J., Bhattacharya, J., & Butte, A. J. (2010). An Environment-Wide Association Study (EWAS) on Type 2 Diabetes Mellitus. PLoS ONE, 5(5), e10746.
Citi nosaukumi	Life Course Approach to Chronic Disease, Life-Course Framework, Developmental Origins Epidemiology, Biological and Social Programming Approach	ExWAS, Environment-Wide Association Study, EWAS (environmental), Agnostic Exposure Scan
Saistītās	3	3
Kopsavilkums	Life-course epidemiology is the study of how physical and social exposures across gestation, childhood, adolescence, and adult life shape later health and disease risk. Codified by Yoav Ben-Shlomo and Diana Kuh in their 2002 International Journal of Epidemiology paper and the 2003 glossary by Kuh, Ben-Shlomo, Lynch, Hallqvist, and Power, the framework supplies a set of competing conceptual models that specify how the timing and sequence of exposures matter. Rather than asking only what causes disease, it asks when exposures act and how their effects compound. Its three signature models — critical or sensitive periods, accumulation of risk, and chains of risk — give researchers a disciplined way to translate developmental and social theory into testable longitudinal hypotheses about the origins of adult chronic disease.	An exposome-wide association study (ExWAS), originally introduced as the Environment-Wide Association Study, applies the logic of the genome-wide association study to the environment. Where a GWAS scans hundreds of thousands of genetic variants for association with a trait, an ExWAS scans a broad panel of measured environmental exposures — nutrients, pollutants, chemical biomarkers, infectious markers, and behaviors — against a health outcome, fitting one adjusted regression per exposure and then rigorously controlling the multiple-testing burden across the whole set. The approach was demonstrated by Chirag Patel, Jayanta Bhattacharya, and Atul Butte in 2010 on type 2 diabetes using NHANES data, and it operationalizes Christopher Wild's 2005 concept of the 'exposome': the totality of environmental exposures complementing the genome. ExWAS turns environmental epidemiology from a one-exposure-at-a-time enterprise into a systematic, hypothesis-generating discovery scan.