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Epigenome-wide association studies of Alzheimer’s disease have highlighted neuropathology-associated DNA methylation differences, although existing studies have been limited in sample size and utilized different brain regions. Here, we combine data from six DNA methylomic studies of Alzheimer’s disease ( N  = 1453 unique individuals) to identify differential methylation associated with Braak stage in different brain regions and across cortex. We identify 236 CpGs in the prefrontal cortex, 95 CpGs in the temporal gyrus and ten CpGs in the entorhinal cortex at Bonferroni significance, with none in the cerebellum. Our cross-cortex meta-analysis ( N  = 1408 donors) identifies 220 CpGs associated with neuropathology, annotated to 121 genes, of which 84 genes have not been previously reported at this significance threshold. We have replicated our findings using two further DNA methylomic datasets consisting of a further >600 unique donors. The meta-analysis summary statistics are available in our online data resource ( www.epigenomicslab.com/ad-meta-analysis/ ). Although epigenome-wide association studies of Alzheimer’s disease have highlighted neuropathology-associated DNA methylation differences, previous studies have been limited in sample size and brain region used. Here, the authors combine data from six DNA methylomic studies of Alzheimer’s disease ( N  = 1453 unique individuals) to identify differentially methylated loci across cortex.

Background As the most stable and experimentally accessible epigenetic mark, DNA methylation is of great interest to the research community. The landscape of DNA methylation across tissues, through development and in disease pathogenesis is not yet well characterized. Thus there is a need for rapid and cost effective methods for assessing genome-wide levels of DNA methylation. The Illumina Infinium HumanMethylation450 (450K) BeadChip is a very useful addition to the available methods for DNA methylation analysis but its complex design, incorporating two different assay methods, requires careful consideration. Accordingly, several normalization schemes have been published. We have taken advantage of known DNA methylation patterns associated with genomic imprinting and X-chromosome inactivation (XCI), in addition to the performance of SNP genotyping assays present on the array, to derive three independent metrics which we use to test alternative schemes of correction and normalization. These metrics also have potential utility as quality scores for datasets. Results The standard index of DNA methylation at any specific CpG site is β = M /( M + U + 100) where M and U are methylated and unmethylated signal intensities, respectively. Betas ( β s) calculated from raw signal intensities (the default GenomeStudio behavior) perform well, but using 11 methylomic datasets we demonstrate that quantile normalization methods produce marked improvement, even in highly consistent data, by all three metrics. The commonly used procedure of normalizing betas is inferior to the separate normalization of M and U, and it is also advantageous to normalize Type I and Type II assays separately. More elaborate manipulation of quantiles proves to be counterproductive. Conclusions Careful selection of preprocessing steps can minimize variance and thus improve statistical power, especially for the detection of the small absolute DNA methylation changes likely associated with complex disease phenotypes. For the convenience of the research community we have created a user-friendly R software package called wateRmelon, downloadable from bioConductor, compatible with the existing methylumi, minfi and IMA packages, that allows others to utilize the same normalization methods and data quality tests on 450K data.

Alzheimer’s disease (AD) is a chronic neurodegenerative disease characterized by the progressive accumulation of amyloid-beta and neurofibrillary tangles of tau in the neocortex. We profiled DNA methylation in two regions of the cortex from 631 donors, performing an epigenome-wide association study of multiple measures of AD neuropathology. We meta-analyzed our results with those from previous studies of DNA methylation in AD cortex (total n  = 2013 donors), identifying 334 cortical differentially methylated positions (DMPs) associated with AD pathology including methylomic variation at loci not previously implicated in dementia. We subsequently profiled DNA methylation in NeuN+ (neuronal-enriched), SOX10+ (oligodendrocyte-enriched) and NeuN–/SOX10– (microglia- and astrocyte-enriched) nuclei, finding that the majority of DMPs identified in ‘bulk’ cortex tissue reflect DNA methylation differences occurring in non-neuronal cells. Our study highlights the power of utilizing multiple measures of neuropathology to identify epigenetic signatures of AD and the importance of characterizing disease-associated variation in purified cell-types. Here the authors identify differences in cortical DNA methylation associated with Alzheimer’s disease pathology, and profiling nuclei from specific cell-types, find that most of these differences reflect variation occurring in non-neuronal cells.

We quantified genome-wide patterns of lysine H3K27 acetylation (H3K27ac) in entorhinal cortex samples from Alzheimer’s disease (AD) cases and matched controls using chromatin immunoprecipitation and highly parallel sequencing. We observed widespread acetylomic variation associated with AD neuropathology, identifying 4,162 differential peaks (false discovery rate < 0.05) between AD cases and controls. Differentially acetylated peaks were enriched in disease-related biological pathways and included regions annotated to genes involved in the progression of amyloid-β and tau pathology (for example, APP, PSEN1, PSEN2, and MAPT), as well as regions containing variants associated with sporadic late-onset AD. Partitioned heritability analysis highlighted a highly significant enrichment of AD risk variants in entorhinal cortex H3K27ac peak regions. AD-associated variable H3K27ac was associated with transcriptional variation at proximal genes including CR1, GPR22, KMO, PIM3, PSEN1, and RGCC. In addition to identifying molecular pathways associated with AD neuropathology, we present a framework for genome-wide studies of histone modifications in complex disease.

Alzheimer's disease (AD) is a chronic neurodegenerative disorder characterized by progressive neuropathology and cognitive decline. Here the authors describe an epigenome-wide association study (EWAS) of human post-mortem brain samples across multiple independent AD cohorts. They find consistent hypermethylation of the ANK1 gene associated with neuropathology. Alzheimer's disease (AD) is a chronic neurodegenerative disorder that is characterized by progressive neuropathology and cognitive decline. We performed a cross-tissue analysis of methylomic variation in AD using samples from four independent human post-mortem brain cohorts. We identified a differentially methylated region in the ankyrin 1 ( ANK1 ) gene that was associated with neuropathology in the entorhinal cortex, a primary site of AD manifestation. This region was confirmed as being substantially hypermethylated in two other cortical regions (superior temporal gyrus and prefrontal cortex), but not in the cerebellum, a region largely protected from neurodegeneration in AD, or whole blood obtained pre-mortem from the same individuals. Neuropathology-associated ANK1 hypermethylation was subsequently confirmed in cortical samples from three independent brain cohorts. This study represents, to the best of our knowledge, the first epigenome-wide association study of AD employing a sequential replication design across multiple tissues and highlights the power of this approach for identifying methylomic variation associated with complex disease.

Aging can lead to cognitive decline associated with neural pathology and Alzheimer's disease (AD). Here the authors scan the methylation status of CpGs across the entire genome of brain samples from aged subjects in an epigenome-wide association study (EWAS). Several loci, including ANK1, were associated with AD pathology, gene expression and AD genetic risk networks. We used a collection of 708 prospectively collected autopsied brains to assess the methylation state of the brain's DNA in relation to Alzheimer's disease (AD). We found that the level of methylation at 71 of the 415,848 interrogated CpGs was significantly associated with the burden of AD pathology, including CpGs in the ABCA7 and BIN1 regions, which harbor known AD susceptibility variants. We validated 11 of the differentially methylated regions in an independent set of 117 subjects. Furthermore, we functionally validated these CpG associations and identified the nearby genes whose RNA expression was altered in AD: ANK1 , CDH23 , DIP2A , RHBDF2 , RPL13 , SERPINF1 and SERPINF2 . Our analyses suggest that these DNA methylation changes may have a role in the onset of AD given that we observed them in presymptomatic subjects and that six of the validated genes connect to a known AD susceptibility gene network.

Identifying genes regulating the pace of epigenetic ageing represents a new frontier in genome-wide association studies (GWASs). Here using 1,796 brain samples from 1,163 individuals, we carry out a GWAS of two DNA methylation-based biomarkers of brain age: the epigenetic ageing rate and estimated proportion of neurons. Locus 17q11.2 is significantly associated ( P =4.5 × 10 −9 ) with the ageing rate across five brain regions and harbours a cis -expression quantitative trait locus for EFCAB5 ( P =3.4 × 10 −20 ). Locus 1p36.12 is significantly associated ( P =2.2 × 10 −8 ) with epigenetic ageing of the prefrontal cortex, independent of the proportion of neurons. Our GWAS of the proportion of neurons identified two genome-wide significant loci (10q26 and 12p13.31) and resulted in a gene set that overlaps significantly with sets found by GWAS of age-related macular degeneration ( P =1.4 × 10 −12 ), ulcerative colitis ( P <1.0 × 10 −20 ), type 2 diabetes ( P =2.8 × 10 −13 ), hip/waist circumference in men ( P =1.1 × 10 −9 ), schizophrenia ( P =1.6 × 10 −9 ), cognitive decline ( P =5.3 × 10 −4 ) and Parkinson’s disease ( P =8.6 × 10 −3 ). Studies on the ‘epigenetic clock’, a recently identified ageing biomarker, suggest that pathology might be linked to tissue-specific accelerated ageing. Here, the authors investigate ageing in the human brain and identify genetic loci associated with accelerated ageing in different brain regions.

Frontotemporal lobar degeneration (FTLD) is an umbrella term describing the neuropathology of a clinically, genetically and pathologically heterogeneous group of diseases, including frontotemporal dementia (FTD) and progressive supranuclear palsy (PSP). Among the major FTLD pathological subgroups, FTLD with TDP-43 positive inclusions (FTLD-TDP) and FTLD with tau-positive inclusions (FTLD-tau) are the most common, representing about 90% of the cases. Although alterations in DNA methylation have been consistently associated with neurodegenerative diseases, including Alzheimer’s disease and Parkinson’s disease, little is known for FTLD and its heterogeneous subgroups and subtypes. The main goal of this study was to investigate DNA methylation variation in FTLD-TDP and FTLD-tau. We used frontal cortex genome-wide DNA methylation profiles from three FTLD cohorts (142 FTLD cases and 92 controls), generated using the Illumina 450K or EPIC microarrays. We performed epigenome-wide association studies (EWAS) for each cohort followed by meta-analysis to identify shared differentially methylated loci across FTLD subgroups/subtypes. In addition, we used weighted gene correlation network analysis to identify co-methylation signatures associated with FTLD and other disease-related traits. Wherever possible, we also incorporated relevant gene/protein expression data. After accounting for a conservative Bonferroni multiple testing correction, the EWAS meta-analysis revealed two differentially methylated loci in FTLD, one annotated to OTUD4 (5’UTR-shore) and the other to NFATC1 (gene body-island) . Of these loci, OTUD4 showed consistent upregulation of mRNA and protein expression in FTLD. In addition, in the three independent co-methylation networks, OTUD4 -containing modules were enriched for EWAS meta-analysis top loci and were strongly associated with the FTLD status. These co-methylation modules were enriched for genes implicated in the ubiquitin system, RNA/stress granule formation and glutamatergic synaptic signalling. Altogether, our findings identified novel FTLD-associated loci, and support a role for DNA methylation as a mechanism involved in the dysregulation of biological processes relevant to FTLD, highlighting novel potential avenues for therapeutic development.

Alzheimer's disease (AD) is a multi-factorial and complex disease, with the risk of developing disease still largely unknown despite numerous genetic and epidemiological studies over recent years. Several genetic and modifiable lifestyle risk factors are known to contribute to disease etiology, and epigenetic mechanisms are suggested to also contribute my mediating their interaction. It is now ten years since we published the first cross-tissue epigenome-wide association study (EWAS) of DNA methylation in AD post-mortem brain samples, with subsequent studies nominating robust and reproducible alterations in genes such as ANK1, HOXA3 and RHBDF2. We have leveraged these studies to perform large-scale epigenomic meta-analyses, reporting 220 differentially methylated loci that are altered in AD cortex, and which we are currently comparing to signatures in other neurodegenerative diseases. More recently we have undertaken DNA methylomic studies in blood in a quest to identify disease-associated alterations in an easily accessible tissue, which could be potentially explored from a biomarker perspective. Finally, our most recent work has explored the contribution of non-coding RNAs to regulating gene expression in AD cortex, where we have meta-analyzed microRNA expression in ∼1,000 post-mortem cortical brain samples, establishing cell-type specific disease-associated signatures.

Alzheimer’s disease (AD) is a multi‐factorial and complex disease, with the risk of developing disease still largely unknown despite numerous genetic and epidemiological studies over recent years. Several genetic and modifiable lifestyle risk factors are known to contribute to disease etiology, and epigenetic mechanisms are suggested to also contribute my mediating their interaction. It is now ten years since we published the first cross‐tissue epigenome‐wide association study (EWAS) of DNA methylation in AD post‐mortem brain samples, with subsequent studies nominating robust and reproducible alterations in genes such as ANK1, HOXA3 and RHBDF2. We have leveraged these studies to perform large‐scale epigenomic meta‐analyses, reporting 220 differentially methylated loci that are altered in AD cortex, and which we are currently comparing to signatures in other neurodegenerative diseases. More recently we have undertaken DNA methylomic studies in blood in a quest to identify disease‐associated alterations in an easily accessible tissue, which could be potentially explored from a biomarker perspective. Finally, our most recent work has explored the contribution of non‐coding RNAs to regulating gene expression in AD cortex, where we have meta‐analyzed microRNA expression in ∼1,000 post‐mortem cortical brain samples, establishing cell‐type specific disease‐associated signatures.