Imprinting methylation predicts hippocampal volumes and hyperintensities and the change with age in later life

Marlene Ritchie, Alison Murray, Roger Staff, Anne C. Ferguson-Smith, Marcus Richards, Graham W. Horgan, Louise Phillips, Gwen Hoad, Christopher McNeil, Antonio Ribeiro, Paul Haggarty* (Corresponding Author)

*Corresponding author for this work

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Epigenetic imprinting is important for neurogenesis and brain function. Hippocampal volumes and brain hyperintensities in late life have been associated with early life circumstances. Epigenetic imprinting may underpin these associations. Methylation was measured at 982 sites in 13 imprinted locations in blood samples from a longitudinal cohort by bisulphite amplicon sequencing. Hippocampal volumes and hyperintensities were determined at age 64y and 72y using MRI. Hyperintensities were determined in white matter, grey matter and infratentorial regions. Permutation methods were used to adjust for multiple testing. At 64y, H19/IGF2 and NESPAS methylation predicted hippocampal volumes. PEG3 predicted hyperintensities in hippocampal grey matter, and white matter. GNASXL predicted grey matter hyperintensities. Changes with age were predicted for hippocampal volume (MEST1, KvDMR, L3MBTL, GNASXL), white matter (MEST1, PEG3) and hippocampal grey matter hyperintensities (MCTS2, GNASXL, NESPAS, L3MBTL, MCTS2, SNRPN, MEST1). Including childhood cognitive ability, years in education, or socioeconomic status as additional explanatory variables in regression analyses did not change the overall fndings. Imprinting methylation in multiple genes predicts brain structures, and their change over time. These fndings are potentially relevant to the development of novel tests of brain structure and function across the lifecourse, strategies to improve cognitive outcomes, and our understanding of early infuences on brain
development and function.
Original languageEnglish
Article number943
Number of pages12
JournalScientific Reports
Publication statusPublished - 13 Jan 2021

Bibliographical note

This work was supported by the Economic and Social Research Council/Biotechnology and Biological Sciences Research Council BioSocial initiative (Grant Number ES/N00048X/1; PH, ADM, LHP, RS, AF-S, MR). PH, GWH, and GH acknowledge the support of the Scottish Government’s Rural and Environment Science and Analytical Services Division (RESAS). The sequencing was carried out at the Aberdeen Centre for Genome-Enabled Biology and Medicine. The authors would like to acknowledge the support of the Maxwell Compute Cluster funded by the University of Aberdeen. The authors would also like to thank the participants of the Aberdeen 1936 Birth Cohort, without whom this research would not have been possible.




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