Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging.

ABSTRACT:

Background

Aging affects the incidence of diseases such as cancer and dementia, so the development of biomarkers for aging is an important research topic in medical science. While such biomarkers have been mainly identified based on the assumption of a linear relationship between phenotypic parameters, including molecular markers, and chronological age, numerous nonlinear changes between markers and aging have been identified. However, the overall landscape of the patterns in nonlinear changes that exist in aging is unknown.

Result

We propose a novel computational method, Data-driven Identification and Classification of Nonlinear Aging Patterns (DICNAP), that is based on functional data analysis to identify biomarkers for aging and potential patterns of change during aging i

SUBMITTER: Okada D 

PROVIDER: S-EPMC9922449 | biostudies-literature | 2023 Feb

REPOSITORIES: biostudies-literature