Decoding the exposome: data science methodologies and implications in exposome-wide association studies (ExWASs)
Ming Kei Chung, John S. House, Farida S. Akhtari, Konstantinos C. Makris, Michael A. Langston, Khandaker Talat Islam, Philip Holmes, Marc Chadeau‐Hyam, Alex I. Smirnov, Xiuxia Du, Anne Thessen, Yuxia Cui, Kai Zhang, Arjun K. Manrai, Alison A. Motsinger‐Reif, Chirag J. Patel, Yau Adamu, Clement Adebamowo, Farida Akhtari, Farida Akhtari, Maria Argos, Saravanan Arunachalam, Brittney Baumert, Emily Beglarian, Kimberly Berger, Jessie Bhutani, William Bisson, Carrie Breton, Lu Cai, Mu-rong Chao, Anastasia Chrysovalantou Chatziioannou, Qiwen Cheng, Ming Kei Chung, Ming Kei Chung, Ming Kei Chung, Robert Clark, Elaine Cohen Hubal, David Conti, Marcus Cooke, Elizabeth Costello, Yuxia Cui, Erin Dierickx, Dana Dolinoy, Xiuxia Du, Lawrence Engel, Peng Gao, Christopher Gaulke, Ryland T Giebelhaus, Jesse Goodrich, Katerina Grafanaki, Rama Gullapalli, Rima Habre, Ariana Haidari, Homero Harari, Jaime Hart, Jingxuan He, Philip Holmes, Darryl B Hood, John House, Hui Hu, Chiung-wen Hu, Peter James, Marta Jankowska, Hong Ji, Kannan Srimathi, Corina Konstantinou, Yunjia Lai, Mike Langston, Janine Lasalle, Amy Leang, Donghai Liang, Jiawen Liao, Jiajun Luo, Konstantinos C Makris, Katherine Manz, Gary Miller, Alison Motsinger-Reif, Marion Ouidir, Grier Page, Shudi Pan, Graham Parker, Kimberly Paul, Alina Peluso, Trevor Penning, Brandon Pierce, Nirmala Prajapati, Gail Prins, Penelope J E Quintana, Arcot (raja) Rajasekar, Aramandla Ramesh, Douglas Ruden, Blake Rushing, Elizabeth Scholl, Sophia Miryam Schüssler-Fiorenza Rose, Ruchir Shah, Mohammad Shahriar, Ram Siwakoti, Lissa Soares, Ghada Soliman, J Christopher States
Abstract
This paper explores the exposome concept and its role in elucidating the interplay between environmental exposures and human health. We introduce two key concepts critical for exposomics research. Firstly, we discuss the joint impact of genetics and environment on phenotypes, emphasizing the variance attributable to shared and nonshared environmental factors, underscoring the complexity of quantifying the exposome's influence on health outcomes. Secondly, we introduce the importance of advanced data-driven methods in large cohort studies for exposomic measurements. Here, we introduce the exposome-wide association study (ExWAS), an approach designed for systematic discovery of relationships between phenotypes and various exposures, identifying significant associations while controlling for multiple comparisons. We advocate for the standardized use of the term "exposome-wide association study, ExWAS," to facilitate clear communication and literature retrieval in this field. The paper aims to guide future health researchers in understanding and evaluating exposomic studies. Our discussion extends to emerging topics, such as FAIR Data Principles, biobanked healthcare datasets, and the functional exposome, outlining the future directions in exposomic research. This abstract provides a succinct overview of our comprehensive approach to understanding the complex dynamics of the exposome and its significant implications for human health.