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Use of Correct and Incorrect Methods of Accounting for Age in Studies of Epigenetic Accelerated Aging: Implications and Recommendations for Best Practices

Motivated by our conduct of a literature review on social exposures and accelerated aging as measured by a growing number of epigenetic “clocks” (which estimate age via DNA methylation (DNAm) patterns), we report on 3 different approaches in the epidemiologic literature—1 incorrect and 2 correct—on...

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Detalles Bibliográficos
Autores principales: Krieger, Nancy, Chen, Jarvis T, Testa, Christian, Diez Roux, Ana, Tilling, Kate, Watkins, Sarah, Simpkin, Andrew J, Suderman, Matthew, Davey Smith, George, De Vivo, Immaculata, Waterman, Pamela D, Relton, Caroline
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10160768/
https://www.ncbi.nlm.nih.gov/pubmed/36721372
http://dx.doi.org/10.1093/aje/kwad025
Descripción
Sumario:Motivated by our conduct of a literature review on social exposures and accelerated aging as measured by a growing number of epigenetic “clocks” (which estimate age via DNA methylation (DNAm) patterns), we report on 3 different approaches in the epidemiologic literature—1 incorrect and 2 correct—on the treatment of age in these and other studies using other common exposures (i.e., body mass index and alcohol consumption). Among the 50 empirical articles reviewed, the majority (n = 29; 58%) used the incorrect method of analyzing accelerated aging detrended for age as the outcome and did not control for age as a covariate. By contrast, only 42% used correct methods, which are either to analyze accelerated aging detrended for age as the outcome and control for age as a covariate (n = 16; 32%) or to analyze raw DNAm age as the outcome and control for age as a covariate (n = 5; 10%). In accord with prior demonstrations of bias introduced by use of the incorrect approach, we provide simulation analyses and additional empirical analyses to illustrate how the incorrect method can lead to bias towards the null, and we discuss implications for extant research and recommendations for best practices.