Background The apolipoprotein E (APOE) ε4 allele is the strongest genetic risk factor for late onset Alzheimer’s disease, whilst the ε2 allele confers protection. Previous studies report differential DNA methylation of APOE between ε4 and ε2 carriers, but associations with epigenome-wide methylation have not previously been characterised. Methods Using the EPIC array, we investigated epigenome-wide differences in whole blood DNA methylation patterns between Alzheimer’s disease-free APOE ε4 (n = 2469) and ε2 (n = 1118) carriers from the two largest single-cohort DNA methylation samples profiled to date. Using a discovery, replication and meta-analysis study design, methylation differences were identified using epigenome-wide association analysis and differentially methylated region (DMR) approaches. Results were explored using pathway and methylation quantitative trait loci (meQTL) analyses. Results We obtained replicated evidence for DNA methylation differences in a ~ 169 kb region, which encompasses part of APOE and several upstream genes. Meta-analytic approaches identified DNA methylation differences outside of APOE: differentially methylated positions were identified in DHCR24, LDLR and ABCG1 (2.59 × 10−100 ≤ P ≤ 2.44 × 10−8) and DMRs were identified in SREBF2 and LDLR (1.63 × 10−4 ≤ P ≤ 3.01 × 10−2). Pathway and meQTL analyses implicated lipid-related processes and high-density lipoprotein cholesterol was identified as a partial mediator of the methylation differences in ABCG1 and DHCR24. Conclusions APOE ε4 vs. ε2 carrier status is associated with epigenome-wide methylation differences in the blood. The loci identified are located in trans as well as cis to APOE and implicate genes involved in lipid homeostasis.

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Harmful alcohol use is a leading cause of premature death and is associated with age‐related disease. Biological ageing is highly variable between individuals and may deviate from chronological ageing, suggesting that biomarkers of biological ageing (derived from DNA methylation or brain structural measures) may be clinically relevant. Here, we investigated the relationships between alcohol phenotypes and both brain and DNA methylation age estimates. First, using data from UK Biobank and Generation Scotland, we tested the association between alcohol consumption (units/week) or hazardous use (Alcohol Use Disorders Identification Test [AUDIT] scores) and accelerated brain and epigenetic ageing in 20,258 and 8051 individuals, respectively. Second, we used Mendelian randomisation (MR) to test for a causal effect of alcohol consumption levels and alcohol use disorder (AUD) on biological ageing. Alcohol use showed a consistent positive association with higher predicted brain age (AUDIT‐C: β = 0.053, p = 3.16 × 10−13; AUDIT‐P: β = 0.052, p = 1.6 × 10−13; total AUDIT score: β = 0.062, p = 5.52 × 10−16; units/week: β = 0.078, p = 2.20 × 10−16), and two DNA methylation‐based estimates of ageing, GrimAge (units/week: β = 0.053, p = 1.48 × 10−7) and PhenoAge (units/week: β = 0.077, p = 2.18x10−10). MR analyses revealed limited evidence for a causal effect of AUD on accelerated brain ageing (β = 0.118, p = 0.044). However, this result should be interpreted cautiously as the significant effect was driven by a single genetic variant. We found no evidence for a causal effect of alcohol consumption levels on accelerated biological ageing. Future studies investigating the mechanisms associating alcohol use with accelerated biological ageing are warranted.

Growing evidence supports a role for deficient Wnt signalling in Alzheimer’s disease (AD). First, the Wnt antagonist DKK1 is elevated in AD brains and is required for amyloid-β-induced synapse loss. Second, LRP6 Wnt co-receptor is required for synapse integrity and three variants of this receptor are linked to late-onset AD. However, the expression/role of other Wnt signalling components remain poorly explored in AD. Wnt receptors Frizzled1 (Fzd1), Fzd5, Fzd7 and Fzd9 are of interest due to their role in synapse formation/plasticity. Our analyses showed reduced FZD1 and FZD7 mRNA levels in the hippocampus of human early AD stages and in the hAPPNLGF/NLGF mouse model. This transcriptional downregulation was accompanied by reduced levels of the pro-transcriptional histone mark H4K16ac and a concomitant increase of its deacetylase Sirt2 at Fzd1 and Fzd7 promoters in AD. In vitro and in vivo inhibition of Sirt2 rescued Fzd1 and Fzd7 mRNA expression and H4K16ac levels at their promoters. In addition, we showed that Sirt2 recruitment to Fzd1 and Fzd7 promoters is dependent on FoxO1 activity in AD, thus acting as a co-repressor. Finally, we found reduced levels of SIRT2 inhibitory phosphorylation in nuclear samples from human early AD stages with a concomitant increase in the SIRT2 phosphatase PP2C. This results in hyperactive nuclear Sirt2 and favours Fzd1 and Fzd7 repression in AD. Collectively, our findings define a novel role for nuclear hyperactivated SIRT2 in repressing Fzd1 and Fzd7 expression via H4K16ac deacetylation in AD. We propose SIRT2 as an attractive target to ameliorate AD pathology.

INTRODUCTION: Dementia pathogenesis begins years before clinical symptom onset, necessitating the understanding of premorbid risk mechanisms. Here, we investigated potential pathogenic mechanisms by assessing DNA methylation associations with dementia risk factors in Alzheimer's disease (AD)-free participants. METHODS: Associations between dementia risk measures (family history, genetic risk score (GRS), and dementia risk scores (combining lifestyle, demographic and genetic factors) and whole-blood DNA methylation were assessed in discovery and replication samples (n=~400-~5,000) from Generation Scotland. RESULTS: AD genetic risk and two risk scores were associated with differential methylation. The GRS predominantly associated with methylation differences in cis but also identified a genomic region implicated in Parkinson's disease. Loci associated with the risk scores were enriched for those previously associated with body mass index and alcohol consumption. DISCUSSION: Dementia risk measures show widespread association with blood-based methylation, which indicates differences in the processes affected by genetic and demographic/lifestyle risk factors.

Introduction Dementia pathogenesis begins years before clinical symptom onset, necessitating the understanding of premorbid risk mechanisms. Here we investigated potential pathogenic mechanisms by assessing DNA methylation associations with dementia risk factors in Alzheimer's disease (AD)–free participants. Methods Associations between dementia risk measures (family history, AD genetic risk score [GRS], and dementia risk scores [combining lifestyle, demographic, and genetic factors]) and whole‐blood DNA methylation were assessed in discovery and replication samples (n = ~400 to ~5000) from Generation Scotland. Results AD genetic risk and two dementia risk scores were associated with differential methylation. The GRS associated predominantly with methylation differences in cis but also identified a genomic region implicated in Parkinson disease. Loci associated with dementia risk scores were enriched for those previously associated with body mass index and alcohol consumption. Discussion Dementia risk measures show widespread association with blood‐based methylation, generating several hypotheses for assessment by future studies.

Preterm birth is closely associated with diffuse white matter dysmaturation inferred from diffusion MRI and neurocognitive impairment in childhood. Diffusion tensor imaging (DTI) and neurite orientation dispersion and density imaging (NODDI) are distinct dMRI modalities, yet metrics derived from these two methods share variance across tracts. This raises the hypothesis that dimensionality reduction approaches may provide efficient whole-brain estimates of white matter microstructure that capture (dys)maturational processes. To investigate the optimal model for accurate classification of generalised white matter dysmaturation in preterm infants we assessed variation in DTI and NODDI metrics across 16 major white matter tracts using principal component analysis and structural equation modelling, in 79 term and 141 preterm infants at term equivalent age. We used logistic regression models to evaluate performances of single-metric and multimodality general factor frameworks for efficient classification of preterm infants based on variation in white matter microstructure. Single-metric general factors from DTI and NODDI capture substantial shared variance (41.8-72.5%) across 16 white matter tracts, and two multimodality factors captured 93.9% of variance shared between DTI and NODDI metrics themselves. General factors associate with preterm birth and a single model that includes all seven DTI and NODDI metrics provides the most accurate prediction of microstructural variations associated with preterm birth. This suggests that despite global covariance of dMRI metrics in neonates, each metric represents information about specific (and additive) aspects of the underlying microstructure that differ in preterm compared to term subjects.HighlightsWe measured variation of 7 DTI and NODDI metrics across 16 major tractsGeneral factors for DTI and NODDI capture substantial shared variance across tractsGeneral factors also capture substantial shared variance between DTI and NODDISingle-metric and multimodality factors associate with gestational age at birthThe best preterm prediction model contains all 7 single-metric g-factors

Importance: Preterm birth and socioeconomic status (SES) are associated with brain structure in childhood, but the relative contributions of each during the neonatal period are unknown. Objective: To investigate associations of gestational age (GA) and SES with neonatal brain morphology, by testing 3 hypotheses: GA and SES are associated with brain morphology; associations between SES and brain morphology vary across the GA range, and; associations between SES and brain structure/morphology depend on how SES is operationalized. Design: Cohort study, recruited 2016-2021. Setting: Single center, UK. Participants: 170 preterm infants and 91 term infants with median (range) birth GA 30+0 (22+1-32+6) and 39+4 (36+3-42+1) weeks, respectively. Exclusion criteria: major congenital malformation, chromosomal abnormality, congenital infection, cystic periventricular leukomalacia, hemorrhagic parenchymal infarction, post-hemorrhagic ventricular dilatation. Exposures: Using linear ridge regression models, we investigated associations of GA and SES, operationalized at the neighborhood-level (Scottish Index of Multiple Deprivation), family-level (parental education and occupation) and subjectively (WHO Quality of Life), with regional brain volumes and cortical morphology. Main outcomes/measures: Brain volume (85 parcels) and 5 whole-brain cortical morphology measures (gyrification index, thickness, sulcal depth, curvature, surface area) at term-equivalent age. Results: In fully adjusted models, GA associated with a higher proportion of brain volumes (22/85 [26%], β range |-0.13| to |0.22|) than neighborhood SES (1/85 [1%], β=0.17). GA associated with cortical surface area (β=0.10 [95% confidence interval (CI) 0.02-0.18]) and gyrification index (β=0.16 [95% CI 0.07-0.25]); neighborhood SES did not. Family-level SES associated with the volumes of more parcels than neighborhood SES, but it did not have as extensive associations with brain structure as GA. There were interactions between GA and both family- and subjective-level SES measures on brain structure. Conclusions/relevance: In a UK cohort, GA and SES impact neonatal brain morphology, but low GA has more widely distributed effects on neonatal brain structure than neighborhood-level, family-level and subjective measures of SES. Further work is warranted to elucidate the mechanisms embedding GA and level-specific SES in early brain development.