Clinical epigenetics · 2025
Protein epigenetic scores and overall mortality in the longitudinal Swedish Adoption/Twin Study of Aging (SATSA).
СтатьяTwin StudyНазвание и аннотация: Перевод в очереди
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Lopes De Oliveira Thaís, March Arianna, Mak Jonathan K L, Pedersen Nancy L, Hägg Sara
Аннотация
INTRODUCTION: DNA methylation (DNAm) has a functional role in gene regulation, and it has been used to estimate various human characteristics. Variation in DNAm is associated with aging and variability of the proteome. Therefore, understanding the relationship between blood circulating proteins, aging, and mortality is critical to identify disease-causing pathways. We aimed to estimate the association between protein epigenetic scores (EpiScores) and overall mortality in the Swedish Adoption/Twin Study of Aging (SATSA).
METHODS: We included information from 374 individuals collected between 1992 and 2014. Our exposures were 109 protein EpiScores generated using DNAm data and prediction models by the MethylDetectR shiny app. All-cause mortality was the outcome of interest. To estimate the protein EpiScores associations with all-cause mortality, we fitted Cox proportional hazard models adjusted for age, sex, education, smoking status, body mass index, and occupation. We also conducted co-twin control analyses to control for shared familial factors.
RESULTS: The mean age of participants at the first assessment was 68.6 years. In total, nine protein EpiScores (e.g., Stanniocalcin 1) were associated with a higher risk for all-cause mortality. In contrast, five protein EpiScores (e.g., Prolyl endopeptidase) were associated with a lower risk for all-cause mortality.
CONCLUSION: The protein EpiScores associated with an increased mortality risk represent proteins involved in metabolic functions, immune response, and inflammation. Conversely, those associated with a lower risk represent proteins involved in neurogenesis and cellular functions. Overall, it is possible to predict protein levels from DNAm data that could have clinical relevance.
METHODS: We included information from 374 individuals collected between 1992 and 2014. Our exposures were 109 protein EpiScores generated using DNAm data and prediction models by the MethylDetectR shiny app. All-cause mortality was the outcome of interest. To estimate the protein EpiScores associations with all-cause mortality, we fitted Cox proportional hazard models adjusted for age, sex, education, smoking status, body mass index, and occupation. We also conducted co-twin control analyses to control for shared familial factors.
RESULTS: The mean age of participants at the first assessment was 68.6 years. In total, nine protein EpiScores (e.g., Stanniocalcin 1) were associated with a higher risk for all-cause mortality. In contrast, five protein EpiScores (e.g., Prolyl endopeptidase) were associated with a lower risk for all-cause mortality.
CONCLUSION: The protein EpiScores associated with an increased mortality risk represent proteins involved in metabolic functions, immune response, and inflammation. Conversely, those associated with a lower risk represent proteins involved in neurogenesis and cellular functions. Overall, it is possible to predict protein levels from DNAm data that could have clinical relevance.