Genetic association between epigenetic aging-acceleration and the progression of mild cognitive impairment to Alzheimer's disease.

Abstract

Alzheimer's disease (AD) is a progressive neurodegenerative disorder and previous studies have showed its association with accelerated aging. In this study, we hypothesized that SNPs that contributed to aging acceleration are also associated with the progression from mild cognitive impairment (MCI) to AD. By applying genetic correlation analysis and single-locus survival analysis, we investigated the associations between intrinsic- and extrinsic-epigenetic-age-acceleration (IEAA and EEAA) related SNPs and the progression time from mild cognitive impairment (MCI) to AD dementia using the data of 767 MCI participants from the ADNI study and 1373 MCI patients from the NACC study. Genetic correlations were found between IEAA/EEAA and AD (positive for IEAA-AD and negative for EEAA-AD). We revealed that 70 IEAA and 81 EEAA SNPs had associations with the progression time from MCI to AD with Bayesian false-discovery probability (BFDP) ≤ 0.8 in the ADNI study, with 22 IEAA SNPs and 16 EEAA SNPs being replicated in the NACC study (P < 0.05). Polygenic risk score (PRS) analysis showed that EEAA PRS but not IEAA PRS was associated with AD progression and the trend of decreasing Fusiform gyrus volume in two datasets. Risk models incorporating both EAA PRSs did not show any significant improvement in predictive accuracy. Our results identified multiple genetic variants with pleiotropic effects on both EAA and AD, which suggested shared genetic architecture between epigenetic age acceleration and AD progression.

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Citation

Published Version (Please cite this version)

10.1093/gerona/glac138

Publication Info

Liu, Hongliang, Michael Lutz, Sheng Luo and undefined Alzheimer’s Disease Neuroimaging Initiative (2022). Genetic association between epigenetic aging-acceleration and the progression of mild cognitive impairment to Alzheimer's disease. The journals of gerontology. Series A, Biological sciences and medical sciences. p. glac138. 10.1093/gerona/glac138 Retrieved from https://hdl.handle.net/10161/25622.

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Scholars@Duke

Lutz

Michael William Lutz

Professor in Neurology

Developing and using computational biology methods to understand the genetic basis of disease with a focus on Alzheimer’s Disease.   Recent work has focused on identification and validation of clinically-relevant biomarkers for Alzheimer’s disease and Alzheimer’s disease with Lewy bodies.

Luo

Sheng Luo

Professor of Biostatistics & Bioinformatics

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