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. 2022 Jan 17;23(1):26.
doi: 10.1186/s13059-021-02596-5.

Blood-based epigenome-wide analyses of cognitive abilities

Daniel L McCartney  1 , Robert F Hillary  2 , Eleanor L S Conole  3   4 , Daniel Trejo Banos  5   6 , Danni A Gadd  2 , Rosie M Walker  2   4 , Cliff Nangle  2 , Robin Flaig  2 , Archie Campbell  2 , Alison D Murray  7 , Susana Muñoz Maniega  3   4 , María Del C Valdés-Hernández  3   4 , Mathew A Harris  3 , Mark E Bastin  3   4 , Joanna M Wardlaw  3   4 , Sarah E Harris  3 , David J Porteous  2 , Elliot M Tucker-Drob  8   9 , Andrew M McIntosh  2   10 , Kathryn L Evans  2 , Ian J Deary  3 , Simon R Cox  11 , Matthew R Robinson  12 , Riccardo E Marioni  13
Affiliations

Blood-based epigenome-wide analyses of cognitive abilities

Daniel L McCartney et al. Genome Biol. .

Abstract

Background: Blood-based markers of cognitive functioning might provide an accessible way to track neurodegeneration years prior to clinical manifestation of cognitive impairment and dementia.

Results: Using blood-based epigenome-wide analyses of general cognitive function, we show that individual differences in DNA methylation (DNAm) explain 35.0% of the variance in general cognitive function (g). A DNAm predictor explains ~4% of the variance, independently of a polygenic score, in two external cohorts. It also associates with circulating levels of neurology- and inflammation-related proteins, global brain imaging metrics, and regional cortical volumes.

Conclusions: As sample sizes increase, the ability to assess cognitive function from DNAm data may be informative in settings where cognitive testing is unreliable or unavailable.

Keywords: Cognitive ability; DNA methylation; EWAS; Epidemiology; Prediction.

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Conflict of interest statement

R.E.M has received a speaker fee from Illumina and is an advisor to the Epigenetic Clock Development Foundation. A.M.M has previously received speaker fees from Janssen and Illumina and research funding from The Sackler Trust. All other authors declare no competing interests.

Figures

Fig. 1
Fig. 1
An epigenetic score for cognitive ability associates with measured cognitive ability, health and lifestyle factors and neuro-inflammatory protein levels. Variance explained for general cognitive ability (g) by a cognitive Epigenetic Score (EpiScore; green), polygenic score (purple) and in combination (orange) (A). Age- and sex-adjusted associations between risk factors for cognitive decline and dementia and the EpiScore (red) and measured g (turquoise) with 95% confidence intervals—deprivation and 6-m walk have been reverse coded such that higher values correspond to less deprivation and faster walking speed (B). Comparison of age- and sex-adjusted associations between the EpiScore and measured g score with 70 inflammation-related (C) and 90 neurology-related (D) proteins. Coloured points in C and D are significant after Bonferroni-correction: orange—common to both, pink—unique to EpiScore, blue—unique to measured g; dashed lines show perfect correlation (y=x)—the grey lines show the linear regression slope with 95% confidence interval
Fig. 2
Fig. 2
Measured and epigenetic cognitive ability associate with brain structure and show regional overlap with cortical loci. Cognitive ability measures with global brain imaging associations in LBC1936 with 95% confidence intervals; measured g (turquoise triangle), Epigenetic Score (EpiScore; orange circle) (A). Results of cortical volume at age 73 years regressed against cognitive g EpiScore (orange), measured g (turquoise) and the spatial extent of overlap (pink) in cortical loci. Colours, representing q values, are superimposed on an average surface template. A false discovery rate threshold of 0.05 is used to control for multiple comparisons; results are corrected for sex, age in days at brain scanning and intracranial volume (n=551) (B)
See this image and copyright information in PMC

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