Key research priorities in methodological approaches for measuring the exposome and studying its role in the development of dementia
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| Publicado en: | Alzheimer's & Dementia vol. 21, no. 11 (Nov 1, 2025) |
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| Autor principal: | |
| Otros Autores: | , , , , , , , , , , , , , |
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John Wiley & Sons, Inc.
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| Acceso en línea: | Citation/Abstract Full Text Full Text - PDF |
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| 024 | 7 | |a 10.1002/alz.70928 |2 doi | |
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| 100 | 1 | |a Nichols, Emma |u Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA | |
| 245 | 1 | |a Key research priorities in methodological approaches for measuring the exposome and studying its role in the development of dementia | |
| 260 | |b John Wiley & Sons, Inc. |c Nov 1, 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a There is growing recognition regarding the importance of the exposome, or the totality of exposures one experiences across the life course, in research on Alzheimer's disease and related dementias. However, the measurement of numerous exposures at once and over time, as well as modeling their effects on dementia risk, presents significant methodological challenges. Through community engagement and consensus‐building processes integrating input from multidisciplinary panels of experts, we identified critical priority topics for methods used in studying links between the exposome and dementia risk, along with advances needed to address those priorities. We identified nine priority topics: high‐dimensional and multimodal data, measurement error, harmonization across studies, mixtures of exposures, effect heterogeneity, exposure timing, cumulative exposures, reverse causation, and sample composition. This paper describes these priority topics and highlights areas where future research or the dissemination of existing methods could advance the state of existing science. Highlights Inherent complexities central to the measurement and modeling of the exposome and its relationship to dementia pose methodological challenges. We identified nine priority topics, such as measurement error, mixtures of exposures, and cumulative exposures. Modeling approaches should consider complexity but provide useful simplifications when possible. Investments in the development and dissemination of innovative approaches and methodological guidance are needed. | |
| 653 | |a Causality | ||
| 653 | |a Mixtures | ||
| 653 | |a Measurement errors | ||
| 653 | |a Research | ||
| 653 | |a Dementia | ||
| 653 | |a Methodological problems | ||
| 653 | |a Harmonization | ||
| 653 | |a Information dissemination | ||
| 653 | |a Methodological approaches | ||
| 653 | |a Measurement | ||
| 653 | |a Dissemination | ||
| 653 | |a Research methodology | ||
| 653 | |a Topics | ||
| 653 | |a Interdisciplinary aspects | ||
| 653 | |a Alzheimer's disease | ||
| 653 | |a Life course | ||
| 700 | 1 | |a Keller, Kayleigh P. |u Department of Statistics, Colorado State University, Fort Collins, Colorado, USA | |
| 700 | 1 | |a Chang, Howard |u Department of Biostatistics, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA | |
| 700 | 1 | |a Chiang, Yao‐Yi |u Department of Computer Science and Engineering, University of Minnesota, Minneapolis, Minnesota, USA | |
| 700 | 1 | |a Gross, Alden L. |u Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA | |
| 700 | 1 | |a Hayes‐Larson, Eleanor |u Leonard Davis School of Gerontology, University of Southern California, Los Angeles, California, USA | |
| 700 | 1 | |a Claus Henn, Birgit |u Department of Environmental Health, Boston University School of Public Health, Boston, Massachusetts, USA | |
| 700 | 1 | |a Kezios, Katrina L. |u Department of Epidemiology, Boston University, Boston, Massachusetts, USA | |
| 700 | 1 | |a Meijer, Erik |u Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA | |
| 700 | 1 | |a Shih, Regina A. |u Department of Epidemiology, Emory Rollins School of Public Health, Atlanta, Georgia, USA | |
| 700 | 1 | |a Szpiro, Adam A. |u Department of Biostatistics, University of Washington, Seattle, Washington, USA | |
| 700 | 1 | |a Weiss, Jordan |u Optimal Aging Institute and Department of Medicine, New York University Grossman School of Medicine, New York, New York, USA | |
| 700 | 1 | |a Weuve, Jennifer |u Department of Epidemiology, Boston University, Boston, Massachusetts, USA | |
| 700 | 1 | |a Adar, Sara D. |u Department of Epidemiology, University of Michigan School of Public Health, Ann Arbor, Michigan, USA | |
| 700 | 1 | |a Lee, Jinkook |u Center for Economic and Social Research, University of Southern California, Los Angeles, California, USA | |
| 773 | 0 | |t Alzheimer's & Dementia |g vol. 21, no. 11 (Nov 1, 2025) | |
| 786 | 0 | |d ProQuest |t Consumer Health Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3274064165/abstract/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |
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| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3274064165/fulltextPDF/embedded/7BTGNMKEMPT1V9Z2?source=fedsrch |