Literature DB >> 29550519

Elevated DNA methylation across a 48-kb region spanning the HOXA gene cluster is associated with Alzheimer's disease neuropathology.

Rebecca G Smith1, Eilis Hannon1, Philip L De Jager2, Lori Chibnik3, Simon J Lott4, Daniel Condliffe5, Adam R Smith1, Vahram Haroutunian6, Claire Troakes4, Safa Al-Sarraj4, David A Bennett7, John Powell4, Simon Lovestone8, Leonard Schalkwyk9, Jonathan Mill10, Katie Lunnon11.   

Abstract

INTRODUCTION: Alzheimer's disease is a neurodegenerative disorder that is hypothesized to involve epigenetic dysregulation of gene expression in the brain.
METHODS: We performed an epigenome-wide association study to identify differential DNA methylation associated with neuropathology in prefrontal cortex and superior temporal gyrus samples from 147 individuals, replicating our findings in two independent data sets (N = 117 and 740).
RESULTS: We identify elevated DNA methylation associated with neuropathology across a 48-kb region spanning 208 CpG sites within the HOXA gene cluster. A meta-analysis of the top-ranked probe within the HOXA3 gene (cg22962123) highlighted significant hypermethylation across all three cohorts (P = 3.11 × 10-18). DISCUSSION: We present robust evidence for elevated DNA methylation associated with Alzheimer's disease neuropathology spanning the HOXA gene cluster on chromosome 7. These data add to the growing evidence highlighting a role for epigenetic variation in Alzheimer's disease, implicating the HOX gene family as a target for future investigation.
Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Alzheimer's disease (AD); Braak stage; DNA methylation; Epigenetics; Epigenome-wide association study (EWAS); HOXA; Illumina Infinium 450K BeadChip (450K array); Meta-analysis; Neuropathology; Prefrontal cortex (PFC); Superior temporal gyrus (STG)

Mesh:

Substances:

Year:  2018        PMID: 29550519      PMCID: PMC6438205          DOI: 10.1016/j.jalz.2018.01.017

Source DB:  PubMed          Journal:  Alzheimers Dement        ISSN: 1552-5260            Impact factor:   21.566


Introduction

Alzheimer’s disease (AD), the most common form of dementia, is a progressive neurodegenerative disorder that is making an increasing contribution to the global burden of disease as the population ages [1]. AD pathology is characterized by the accumulation of amyloid-β plaques and tau tangles, ultimately leading to neuronal cell loss. The neurodegeneration associated with AD is believed to start many decades before clinical onset; during this “preclinical” phase, the plaque and tangle loads in the brain increase until a person-specific threshold level is reached and behavioral changes and cognitive impairment become manifest [2-4]. At present, there are no disease-modifying treatments available, with existing medications only alleviating certain symptoms of AD. A better understanding of the underlying mechanisms precipitating the onset and progression of pathology is required to enable the design of new, more effective medications. Increased knowledge about the functional complexity of the genome has led to speculation about the role of epigenetic variation in health and disease, including for neurodegenerative diseases such as AD [5]. Two epigenome-wide association studies (EWAS) of AD [6,7] recently identified consistent patterns of DNA methylation associated with neuropathology. Of particular interest was replicated evidence for cortex-specific hypermethylation at multiple 5′-C-phosphate-G-3′ (CpG) sites within ANK1, although differences at a number of other loci were identified in one or both studies [8]. One of the previously reported neuropathology-associated differentially methylated positions (DMPs), cg22962123, is located within the HOXA gene cluster on chromosome 7 [7]. Here, we present further evidence to support a role for altered DNA methylation in AD-associated neuropathology across an extensive region spanning the HOXA gene cluster.

Methods

Samples and subjects

Our discovery (Mount Sinai) cohort consisted of brain tissue from 147 individuals obtained from the Mount Sinai Alzheimer’s Disease and Schizophrenia Brain Bank (http://icahn.mssm.edu/research/labs/neuropathology-and-brain-banking). From the 147 donors, two cortical regions (prefrontal cortex [PFC, N = 144] and superior temporal gyrus [STG, N = 142]) were used for the purposes of the study. All samples were dissected by trained specialists, snap-frozen and stored at − 80°C. Further information about the samples is given in Supplementary Table 1. Ethical approval for the project was provided by the University of Exeter Medical School Research Ethics Committee under application number 14/02/041. Genomic DNA was isolated from ~ 100 mg of each dissected brain region using a standard phenol-chloroform extraction protocol and tested for purity and degradation before analysis. For replication purposes, we used previously published EWAS data collected in two independent cohorts on the Illumina Infinium Human Methylation 450K BeadChip (450K array): (1) the “London” (Lunnon et al.) cohort, consisting of PFC, STG, entorhinal cortex, cerebellum (CER), and premortem blood DNA methylation data from 117 individuals from the Medical Research Council London Neurodegenerative Disease Brain Bank [6] and (2) the “Religious Orders Study/Memory and Aging Project (ROS/MAP)” (De Jager et al.) cohort, consisting of PFC DNA methylation data from 740 individuals from the Religious Orders Study and the Rush Memory and Aging Project [7]. All samples were assigned a unique code number for the experiment, which was independent of age, gender, or diagnosis. This code was used throughout the experiment and analysis.

Bisulfite treatment and Illumina Infinium BeadArray

Five hundred nanograms of genomic DNA was sodium bisulfite converted using the EZ-DNA methylation kit (Zymo Research, Orange, CA, USA), and DNA methylation was subsequently quantified using the 450K array (Illumina, USA) with arrays scanned using an Illumina iScan (software version 3.3.28). Samples were processed by tissue and randomized with respect to age and gender. The Illumina 450K array interrogates >485,000 probes covering 99% of reference sequence (RefSeq) genes, with an average of 17 CpG sites per gene region (distributed across promoter, 5′untranslated region, first exon, gene body, and 3′untranslated regions). It covers 96% of CpG islands, with additional coverage in island shores and their flanking regions.

Microarray quality control and data normalization

Initial quality control of data was conducted using GenomeStudio (version 2011.1) to determine the status of staining, extension, hybridization, target removal, sodium bisulfite conversion, specificity, and nonpolymorphic and negative controls. Probes previously reported to hybridize to multiple genomic regions or containing a singlenucleotide polymorphism at the single base extension site were removed from subsequent analyses [9,10], in addition to the 65 single-nucleotide polymorphisms used for sample identification on the array (total probes removed 72,067). For each probe, DNA methylation levels were indexed by b values, that is, the ratio of the methylated signal divided by the sum of the methylated and unmethylated signal (M/[M + U]).

Data analysis

All computations and statistical analyses were performed using R 3.0.2 and Bioconductor 2.13. Signal intensities were imported into R using the methylumi package. Initial quality control checks were performed using functions in the methylumi package to assess concordance between reported and genotyped gender. Non-CpG single-nucleotide polymorphism probes on the array were also used to confirm that both brain regions were sourced from the same individual where expected. Data were preprocessed and quantile normalized using the dasen function as part of the wateRmelon package (wateRmelon_1.0.3) [11] within the R statistical analysis environment and batch corrected using the ComBat package [12]. Array data for each of the tissues were normalized separately, and initial analyses were performed separately by tissue. Full Illumina 450K array data were available for the discovery (Mount Sinai) and London (Lunnon et al.) cohorts, and thus we were able to estimate neuronal proportions in the data using the R package CETS [13]. For the ROS/MAP (De Jager et al.) cohort, we only had Illumina 450K array data for probes in the HOXA region and thus could not calculate neuronal proportions. Therefore, the effects of age, gender, and cell type composition were regressed out of the discovery (Mount Sinai) and London (Lunnon et al.) cohorts, whereas the effects of age and gender only were regressed out of the ROS/MAP (De Jager et al.) cohort before subsequent analysis. For identification of DMPs specifically altered with respect to neuropathological measures of AD, we performed a quantitative analysis in which samples were analyzed separately in each brain region using linear regression models with respect to Braak stage, with probes ranked according to P values. The genic location of identified DMPs was annotated by GREAT annotation [14]. We have previously established the multiple testing threshold (experiment-wide significance) for EWAS data generated on the Illumina 450K array as P < 2.2 × 10−7 [15]. In brief, in this previous study, 5000 permutations were performed repeating a linear regression model for randomly selected groups of cases and controls (N = 675). For each permutation, P values from the EWAS were saved and the minimum identified. Across all permutations, the fifth percentile was calculated to generate the 5% of α significance threshold, which was deemed to be P < 2.2 × 10−7. To identify differentially methylated regions (DMRs), we identified spatially correlated P values in our data using the Python module comb-p to group ≥3 spatially correlated CpGs in a 500-bp sliding window [16]. The coMET package was used to identify regional comethylation patterns and regional EWAS results [17]. Fisher’s combined P value analysis was performed in the MetaDE package [18], and meta-analysis on correlation and case control status was performed with the meta package [19] within R [20]. Data are available for the discovery (Mount Sinai) cohort within Gene Expression Omnibus under accession number GSE80970. The discovery (Mount Sinai) EWAS data set has been previously used to validate the top 100 DMPs nominated in a previously published EWAS [6]. As such, we have not sought to replicate these top 100 DMPs in the present study.

Results

Hypermethylation associated with AD neuropathology is observed in a region spanning 48 kb across the HOXA gene cluster in the human cortex

Our primary analyses focused on matched PFC and STG tissues from 147 individuals (Supplementary Table 1). We used the 450K array to first quantify DNA methylation in the PFC and identify DMPs associated with the Braak score, a standardized measure of neurofibrillary tangle burden determined at autopsy, controlling for age, gender, and estimated neuronal cell proportion. We identified 10 experiment-wide significant (P < 2.2 × 10−7) DMPs (Table 1 and Fig. 1A), with 78 DMPs associated with Braak stage at a more relaxed threshold of P < 1 × 10−5 (Supplementary Table 2). Of these 78 DMPs, nine were located in the HOXA gene cluster on chromosome 7, most notably in the vicinity of HOXA3, with one HOXA DMP reaching experiment-wide significance (cg22962123: P = 1.2 × 10−7). We next used a sliding window approach (comb-p [16]) to identify spatially correlated regions of differential DNA methylation associated with neuropathology; Table 2 lists DMRs spanning at least three probes with a window size of 500 bp and a Sidak-corrected P value < .05. We identified six closely located DMRs within the HOXA gene region, with the most significant DMR in the HOXA region spanning seven probes in a 364-bp region within intron 1 of HOXA3 (Fig. 1B; Sidak-corrected P = 1.19 × 10−9). Of note, we observed an extended region of neuropathology-associated hypermethylation spanning 48,754 bp from upstream of the HOXA2 gene to the HOXA6 gene and covering 208 Illumina 450K array probes (Fig. 1C). Given that DNA methylation at nearby CpG sites can be highly correlated [21], we visualized comethylation patterns between CpG sites within HOXA3 using coMET [17] and observed highly correlated patterns of DNA methylation between CpG sites in this extended region (Supplementary Fig. 1). We next sought to test whether neuropathology-associated DNA methylation patterns across this 48,754-bp region were specific to the PFC, using the Illumina 450K array to profile STG samples from the same individuals. In total, seven probes in the region demonstrated significantly increased DNA methylation after correcting for 208 tests (P < 2.4 × 10−4), with the top PFC DMP (cg22962123) being similarly hypermethylated with respect to Braak stage (Fig. 1D; PFC: R = 0.36, P = 1.2 × 10−7; STG: R = 0.28, P = 2.78 × 10−4). There was an overall consistent pattern of effect sizes across both brain regions for the 208 probes in the HOXA neuropathology-associated region (Fig. 1E; R = 0.76, P = 2.66 × 10−40).
Table 1

The 10 DMPs associated with Braak stage in the PFC in the discovery (Mount Sinai) cohort that reached experiment-wide significance (P < 2.2 × 10−7) are shown, with annotation to chromosomal location (hg19), up/downstream genes (from GREAT annotation), P value from our quantitative association model, and corrected DNA methylation difference (Δ) from Braak score 0–VI (as a %). Also shown is the corresponding information in the matched STG samples in the same cohort, and the matched brain regions (PFC, STG) in the London (Lunnon et al.) cohort, demonstrating a nominally significant difference. A list of the 78 top-ranked PFC DMPs at a more relaxed threshold of P < 1 × 10−5 is given in Supplementary Table 2

Discovery (Mount Sinai)cohort
London (Lunnon et al.) cohort
Association with Braak stage
Association with Braak stage
GREAT annotation
PFC
STG
PFC
STG
ProbeLocationIlluminaannotationDownstreamUpstreamΔP valueΔP valueΔP valueΔP value
cg228678164:16081205PROM1FGFBP2 (−116347)PROM1 (+4118)−3.909.80E–09−2.045.21E–03----
cg069772857:18127468HDAC9 (−408457)PRPS1L1 (−59983)3.662.02E–082.681.84E–04--1.887.65E–03
cg057833842:218843735RUFY4 (−90242)TNS1 (−34885)7.424.46E–085.558.01E–053.267.76E–033.836.48E–04
cg073498153:123751269CCDC14 (−70706)KALRN (−62258)5.156.70E–08--2.15.021.837.35E–03
cg2180624211:72532891ATG16L2ATG16L2 (+7539)FCHSD2 (+320414)8.517.02E–085.554.08E–045.223.86E–044.621.10E–03
cg038347677:90794392CDK14FZD1 (−99390)CDK14 (+455681)−4.508.13E–08------
cg1393557712:107974897BTBD11PWP1 (−104611)BTBD11 (+262708)9.118.45E–085.271.49E–034.025.10E–033.73.02
cg2707889011:128457459ETS1ETS1 (−23)4.859.86E–08--2.09.02--
cg229621237:27153605HOXA3HOXA2 (−11176)HOXA3 (+5608)7.881.20E–075.122.78E–045.622.24E–055.185.21E–04
cg2619985712:54764265ZNF385AGPR84 (−5995)ZNF385A (+20,816)5.431.87E–074.441.02E–032.62.03--

Abbreviations: DMP, differentially methylated position; PFC, prefrontal cortex; STG, superior temporal gyrus.

Fig. 1.

HOXA3 hypermethylation is associated with neuropathological measures of AD in cortex. (A) A Manhattan plot of association between DNA methylation in the PFC with Braak stage highlights associations at loci across the genome, with a region on chromosome 7 in the HOXA3 gene showing the greatest number of probes associated with pathology. The red line indicates experiment-wide significance threshold (P = 2.2 × 10−7), with the green line indicating a more relaxed significance threshold (P = 1 × 10−5). (B) Using a sliding window approach to identify differentially methylated regions, we identified six within the HOXA gene cluster (Table 2), with the most significant region spanning 364 bp in the HOXA3 gene and containing seven CpG sites that showed increased methylation in late-stage AD (Braak stage VI) compared to healthy controls (Braak stage 0). (C) A mini-Manhattan plot across the HOXA gene cluster. Highlighted between gray dashed lines is a 48,754-bp region containing 208 probes characterized by neuropathology-associated hypermethylation. Red circles indicate increased DNA methylation in disease (≥1% between Braak 0 and Braak VI), green circles indicate decreased DNA methylation in disease (≥1% between Braak 0 and Braak VI), and black circles indicate DNA methylation differences <1% between Braak 0 and Braak VI. (D) The site demonstrating the greatest DNA methylation difference (cg22962123) in the PFC (R = 0.36, P = 1.2 × 10−7) also showed a similar but weaker association in the STG (R = 0.28, P = 2.78 × 10−4). (E) A quadrant plot of the effect size of the 208 probes identified in the PFC and their corresponding effect size in the STG highlights a significant correlation between brain regions (R = 0.76, P = 2.66 × 10−40). Abbreviations: AD, Alzheimer’s disease; CpG, 5′-C-phosphate-G-3′; PFC, prefrontal cortex; STG, superior temporal gyrus.

Table 2

DMRs associated with Braak stage in the PFC—Shown are all significantly associated regions (Sidak-corrected P value < .05) that contain three or more probes, with chromosomal location (hg19), up/downstream genes, number of probes in the significant region, and Sidak-corrected P value

ChrStartEndIllumina annotationGREAT annotationNumber of probesŠidák-corrected P value
Chr112,321,7702,323,247C11ORF21TSPAN32 (−734)C11orf21 (+634)273.20E–11
Chr727,153,58027,153,944HOXA3HOXA2 (−11332)HOXA3 (+5452)71.19E–09
Chr727,154,26227,155,234HOXA3HOXA2 (−12318)HOXA3 (+4466)164.31E–09
Chr727,169,95727,171,401HOXA4HOXA4 (−261)212.13E–08
Chr113,15,9083,16,456IFITM1 ClosestIFITM1 (+2329)IFITM3 (+4868)54.02E–08
Chr1258,119,91558,120,237AGAP2AGAP2 (+11,953)OS9 (+32,172)61.22E–07
Chr727,183,13327,184,853HOXA5/HOXA-AS3HOXA5 (−706)422.19E–06
Chr578,985,42578,985,900CMYA5CMYA5 (−37)102.31E–06
Chr1910,736,00610,736,448SLC44A2SLC44A2 (+293)83.68E–06
Chr1939,086,73339,087,186MAP4K1MAP4K1 (+21,604)RYR1 (+162490)44.94E–06
Chr610,556,14710,556,523GCNT2GCNT6 (−77,658)GCNT2 (+27,746)32.93E–05
Chr3194,014,592194,015,171GRM2 ClosestCPN2 (+57,175)HES1 (+160,948)43.24E–05
Chr4184,908,351184,909,018STOX2STOX2 (+82,176)ENPP6 (+230,429)83.60E–05
Chr727,145,97227,146,445HOXA3HOXA2 (−3779)54.11E–05
Chr1746,388,39046,388,465SKAP1SKAP1 (+119,124)SNX11 (+203,508)34.77E–05
Chr1774,475,24074,475,402RHBDF2RHBDF2 (+22,168)AANAT (+25,888)58.13E–05
Chr351,740,74151,741,280GRM2GRM2 (−75)61.93E–04
Chr1741,363,50241,364,121NBR1/TMEM106ATMEM106 A (−82)113.04E–04
Chr1743,318,61043,319,371FMNL1FMNL1 (+19,835)SPATA32 (+20,488)64.51E–04
Chr7158,281,410158,281,613PTPRN2PTPRN2 (+98,859)34.66E–04
Chr1343,565,90143,566,496EPSTI1DNAJC15 (−31,140)TNFSF11 (+417,910)94.72E–04
Chr2057,582,78757,583,520CTSZ ClosestCTSZ (−852)186.82E–04
Chr193,179,5453,180,035S1PR4NCLN (−5808)S1PR4 (+1054)47.59E–04
Chr2237,608,61137,608,819SSTR3 ClosestSSTR3 (−353)38.84E–04
Chr13113,698,408113,699,016MCF2LF7 (−61,409)MCF2L (+75,177)139.15E–04
Chr934,457,12934,457,500FAM219ADNAI1 (−1518)41.05E–03
Chr1775,315,08175,315,567SEPT9TNRC6C (−685,813)SEPT9 (+37,832)81.28E–03
Chr1629,674,61829,675,214SPNSPN (+336)61.77E–03
Chr155,246,86755,247,408TTC22PARS2 (−16,951)DHCR24 (+105,753)52.45E–03
Chr1258,132,55858,133,008AGAP2 (−754)33.00E–03
Chr727,138,71227,138,974HOTAIRM1HOXA1 (−3250)43.19E–03
Chr1667,686,83267,687,392RLTRPACD (+7534)RLTPR (+8290)43.59E–03
Chr1258,129,85558,130,410AGAP2AGAP2 (+1896)OS9 (+42,229)44.42E–03
Chr1719,314,29919,314,618RNF112RNF112 (−48)69.80E–03
Chr1540,583,22740,583,422PLCB2PLCB2 (+16,798)PAK6 (+51,704)3.01922
Chr1538,988,53338,988,860C15ORF53THBS1 (−884,597)RASGRP1 (−131,690)4.01974
Chr161,482,9521,483,192CCDC154 ClosestC16orf91 (−3727)3.02843

Abbreviations: DMR, differentially methylated region; PFC, prefrontal cortex.

Cortical neuropathology-associated hypermethylation in HOXA3 is observed in independent study cohorts

We next sought to replicate the observation of neuropathology-associated hypermethylation across these 208 probes in two independent, previously published data sets. First, we examined the “London” (Lunnon et al. [6]) data set, comprising Illumina 450K array data generated using matched PFC, STG, entorhinal cortex, CER, and premortem blood samples obtained from 117 donors (described in [6]; Supplementary Table 1). We observed a similar pattern of Braak-associated DNA methylation across this 208-probe region in the replication cohort in both the PFC (Fig. 2A) and STG (Supplementary Fig. 2), with a highly correlated effect size between cohorts in both brain regions (PFC: Fig. 2B; R = 0.74, P = 2.27 × 10−37; STG: Supplementary Fig. 3; R = 0.68, P = 1.87 × 10−29)—15 probes in the PFC and 6 probes in the STG reaching our corrected significance threshold (P < 2.4 × 10−4). In contrast, no probes in this region reached the corrected significance threshold in the entorhinal cortex (Supplementary Fig. 4), although the effect size was still correlated (R = 0.41, P = 1.23 × 10−9). Similarly, no probes reached the significance threshold in the CER (Supplementary Fig. 5) or in premortem whole blood collected in a subset (N = 57) of the same individuals (Supplementary Fig. 6), with no correlation of effect sizes in either the CER (R = 0.03, P = .639) or blood (R = 0.11, P = .138). This indicates that the association may be specific to only particular regions of the cortex.
Fig. 2.

Replication of neuropathology-associated DNA methylation differences across the HOXA gene cluster in additional study cohorts. (A) We identified a consistent pattern of increased DNA methylation across the HOXA cluster in the London (Lunnon et al.) cohort in the PFC (B) with a strong correlation in effect size across the 208 probes in the region between data sets (R = 0.74, P = 2.24 × 10−37). (C) A similar pattern of DNA methylation changes was observed in the PFC in the ROS/MAP (De Jager et al.) cohort, (D) with a strong correlation in effect size across the 208 probes in the region between data sets (R = 0.80, P = 2.39 × 10−48). (E) A Fisher’s combined P value meta-analysis of the PFC with respect to Braak stage across all three cohorts showed striking patterns of increased DNA methylation with many probes in the HOXA3 region reaching experiment-wide significance. (F) The most significant probe identified from the discovery cohort (cg22962123) was also the most significant probe in the meta-analysis (P = 3.11 × 10−18) and characterized by neuropathology-associated hypermethylation across all three cohorts. In plots (A) and (C) red circles indicate increased DNA methylation in disease (≥1% between Braak 0 and Braak VI), green circles indicate decreased DNA methylation in disease (≥1% between Braak 0 and Braak VI), and black circles indicate DNA methylation differences <1% between Braak 0 and Braak VI. In plots (A), (C), and (E), the red line indicates experiment-wide significance (P = 2.2 × 10−7), whereas the blue line indicates significance after correcting for 208 tests (P = 2.4 × 10−4). In plots (A), (C), and (E), the gray dashed lines indicate the same region across the graphs for reference. These show the probes in the extended DMR. In plot (F), red denotes the PFC and green denotes the STG. Abbreviations: DMR, differentially methylated region; PFC, prefrontal cortex; ROS/MAP, Religious Orders Study/Memory and Aging Project; STG, superior temporal gyrus.

We subsequently assessed this region in the “ROS/MAP” (De Jager et al.) data set comprising of 740 PFC samples profiled on the Illumina 450K array (as described in De Jager et al. [7]; Supplementary Table 1) observing a similar pattern of effects with highly significant neuropathology-associated hypermethylation across probes in the HOXA genic region (Fig. 2C), and a significant correlation of effect size with the same 208 probes in the PFC in the discovery cohort (Fig. 2D; R = 0.80, P = 2.39 × 10−48). A Fisher’s combined P value of DNA methylation differences across this region in all three PFC data sets confirmed a clearly defined region of significant neuropathology-associated elevated DNA methylation, with many individual DMPs passing the threshold for experiment-wide significance (Fig. 2E), and a consistent pattern of effects across the three cohorts (Supplementary Fig. 7). The most significant DMP identified within the HOXA3 gene in our discovery cohort (cg22962123; Table 1) was also the most significant DMP in our Fisher’s combined P value analysis (P = 1 × 10−20). A metaanalysis comparing Braak 0 to VI demonstrated increased DNA methylation with respect to Braak stage across all cohorts in the PFC (Fig. 2F; P = 3.11 × 10−18). Together, our data suggest that DNA hypermethylation across the extended HOXA gene region is robustly associated with AD-related neuropathology in both the PFC and STG, with the strongest effects in the vicinity of HOXA3.

Discussion

We identified an extended region of elevated DNA methylation in the HOXA gene cluster that is associated with AD neuropathology, with consistent effects seen across three independent postmortem brain sample cohorts. Although one previous study had demonstrated differential methylation at a single CpG within the HOXA gene cluster [7] and another identified a DMR spanning seven CpG sites [6], this represents the first study to illustrate that hypermethylation in this region extends to 208 DMPs, spanning approximately 48.7 Kb. Differential DNA methylation in the HOXA gene cluster has been previously reported in blood collected from Down syndrome individuals [22], which is interesting given that many Down syndrome individuals develop AD resulting from an additional copy of the APP gene due to trisomy on chromosome 21. The Down syndrome study demonstrated differential DNA methylation in 20 probes largely located within HOXA2. Of note, 17 of these probes were significantly hypermethylated in the PFC in our discovery (Mount Sinai) cohort. However, none were differentially methylated in premortem blood in the London (Lunnon et al.) cohort. In the context of other neurodegenerative disorders, one study that investigated microRNAs targeting HOX genes in Huntington’s disease demonstrated increased levels of micro-RNAs related to HOXA5, HOXA10, HOXA11, HOXA11AS, HOXA13, and HOTAIRM1 in the PFC in Huntington’s disease [23]. Although HOX genes encode potent transcription factors that play a critical role in embryonic development [24], a recent study in Drosophila also highlighted a potent protective function for HOX genes in neurons, implicating a role in neuroprotection [25]. Interestingly, this study also highlighted how HOX genes act to maintain expression of the ankyrin locus, an important observation given our previous finding of altered DNA methylation in ANK1 in AD [6]. Indeed, to further explore this hypothesis, we examined the correlation between DNA methylation levels at the most significant HOX probe identified in the present study (cg22962123) with the two ANK1 DMPs that we previously identified to be associated with AD neuropathology (cg11823178 and cg05066959) [6,7] in the PFC, identifying a significant correlation with both ANK1 probes (cg11823178: R = 0.24, P = 5.15 × 10−10; cg05066959:R = 0.20, P = 2.93 × 10−8). Although this correlation could reflect the association between both HOXA3 and ANK1 probes with Braak stage, it could highlight a novel physiological mechanism, particularly as we still observed significant hypermethylation (P =1.67 × 10−5) at our top HOXA probe (cg22962123), when controlling for levels of DNA methylation in the top ANK1 probe (cg11823178). Looking to the future, analyses of gene expression levels should be performed to facilitate the interpretation of the DNA methylation differences we observe in HOXA. To conclude, this study provides further evidence for altered epigenetic processes in the pathophysiology of AD and suggests that further work on the neuroprotective functions of HOX genes is warranted.
  22 in total

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Journal:  Aging (Albany NY)       Date:  2015-02       Impact factor: 5.682

6.  Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray.

Authors:  Yi-an Chen; Mathieu Lemire; Sanaa Choufani; Darci T Butcher; Daria Grafodatskaya; Brent W Zanke; Steven Gallinger; Thomas J Hudson; Rosanna Weksberg
Journal:  Epigenetics       Date:  2013-01-11       Impact factor: 4.528

7.  Additional annotation enhances potential for biologically-relevant analysis of the Illumina Infinium HumanMethylation450 BeadChip array.

Authors:  Magda E Price; Allison M Cotton; Lucia L Lam; Pau Farré; Eldon Emberly; Carolyn J Brown; Wendy P Robinson; Michael S Kobor
Journal:  Epigenetics Chromatin       Date:  2013-03-03       Impact factor: 4.954

8.  Methylomic profiling implicates cortical deregulation of ANK1 in Alzheimer's disease.

Authors:  Katie Lunnon; Rebecca Smith; Eilis Hannon; Philip L De Jager; Gyan Srivastava; Manuela Volta; Claire Troakes; Safa Al-Sarraj; Joe Burrage; Ruby Macdonald; Daniel Condliffe; Lorna W Harries; Pavel Katsel; Vahram Haroutunian; Zachary Kaminsky; Catharine Joachim; John Powell; Simon Lovestone; David A Bennett; Leonard C Schalkwyk; Jonathan Mill
Journal:  Nat Neurosci       Date:  2014-08-17       Impact factor: 24.884

9.  MicroRNAs located in the Hox gene clusters are implicated in huntington's disease pathogenesis.

Authors:  Andrew G Hoss; Vinay K Kartha; Xianjun Dong; Jeanne C Latourelle; Alexandra Dumitriu; Tiffany C Hadzi; Marcy E Macdonald; James F Gusella; Schahram Akbarian; Jiang-Fan Chen; Zhiping Weng; Richard H Myers
Journal:  PLoS Genet       Date:  2014-02-27       Impact factor: 5.917

10.  An integrated genetic-epigenetic analysis of schizophrenia: evidence for co-localization of genetic associations and differential DNA methylation.

Authors:  Eilis Hannon; Emma Dempster; Joana Viana; Joe Burrage; Adam R Smith; Ruby Macdonald; David St Clair; Colette Mustard; Gerome Breen; Sebastian Therman; Jaakko Kaprio; Timothea Toulopoulou; Hilleke E Hulshoff Pol; Marc M Bohlken; Rene S Kahn; Igor Nenadic; Christina M Hultman; Robin M Murray; David A Collier; Nick Bass; Hugh Gurling; Andrew McQuillin; Leonard Schalkwyk; Jonathan Mill
Journal:  Genome Biol       Date:  2016-08-30       Impact factor: 13.583

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  47 in total

Review 1.  Promoter DNA hypermethylation - Implications for Alzheimer's disease.

Authors:  Yiyuan Liu; Minghui Wang; Edoardo M Marcora; Bin Zhang; Alison M Goate
Journal:  Neurosci Lett       Date:  2019-07-24       Impact factor: 3.046

2.  coMethDMR: accurate identification of co-methylated and differentially methylated regions in epigenome-wide association studies with continuous phenotypes.

Authors:  Lissette Gomez; Gabriel J Odom; Juan I Young; Eden R Martin; Lizhong Liu; Xi Chen; Anthony J Griswold; Zhen Gao; Lanyu Zhang; Lily Wang
Journal:  Nucleic Acids Res       Date:  2019-09-26       Impact factor: 16.971

3.  Epigenomic features related to microglia are associated with attenuated effect of APOE ε4 on Alzheimer's disease risk in humans.

Authors:  Yiyi Ma; Lei Yu; Marta Olah; Rebecca Smith; Stephanie R Oatman; Mariet Allen; Ehsan Pishva; Bin Zhang; Vilas Menon; Nilüfer Ertekin-Taner; Katie Lunnon; David A Bennett; Hans-Ulrich Klein; Philip L De Jager
Journal:  Alzheimers Dement       Date:  2021-09-05       Impact factor: 16.655

4.  EPIGENOMIC FEATURES RELATED TO MICROGLIA ARE ASSOCIATED WITH ATTENUATED EFFECT OF APOE ε4 ON ALZHEIMER'S DISEASE RISK IN HUMANS.

Authors:  Yiyi Ma; Lei Yu; Marta Olah; Rebecca Smith; Stephanie R Oatman; Mariet Allen; Ehsan Pishva; Bin Zhang; Vilas Menon; Nilüfer Ertekin-Taner; Katie Lunnon; David A Bennett; Hans-Ulrich Klein; Philip L De Jager
Journal:  Alzheimers Dement       Date:  2020-12-07       Impact factor: 16.655

5.  DNA methylation variability in Alzheimer's disease.

Authors:  Zhiguang Huo; Yun Zhu; Lei Yu; Jingyun Yang; Philip De Jager; David A Bennett; Jinying Zhao
Journal:  Neurobiol Aging       Date:  2018-12-21       Impact factor: 4.673

6.  Identification of a foetal epigenetic compartment in adult human kidney.

Authors:  John K Wiencke; Ze Zhang; Devin C Koestler; Lucas A Salas; Annette M Molinaro; Brock C Christensen; Karl T Kelsey
Journal:  Epigenetics       Date:  2021-03-30       Impact factor: 4.528

7.  Mendelian randomization integrating GWAS and mQTL data identified novel pleiotropic DNA methylation loci for neuropathology of Alzheimer's disease.

Authors:  Di Liu; Youxin Wang; Huiquan Jing; Qun Meng; Jingyun Yang
Journal:  Neurobiol Aging       Date:  2020-10-01       Impact factor: 4.673

8.  A meta-analysis of epigenome-wide association studies in Alzheimer's disease highlights novel differentially methylated loci across cortex.

Authors:  Rebecca G Smith; Ehsan Pishva; Gemma Shireby; Adam R Smith; Janou A Y Roubroeks; Eilis Hannon; Gregory Wheildon; Diego Mastroeni; Gilles Gasparoni; Matthias Riemenschneider; Armin Giese; Andrew J Sharp; Leonard Schalkwyk; Vahram Haroutunian; Wolfgang Viechtbauer; Daniel L A van den Hove; Michael Weedon; Danielle Brokaw; Paul T Francis; Alan J Thomas; Seth Love; Kevin Morgan; Jörn Walter; Paul D Coleman; David A Bennett; Philip L De Jager; Jonathan Mill; Katie Lunnon
Journal:  Nat Commun       Date:  2021-06-10       Impact factor: 14.919

9.  A machine learning approach to brain epigenetic analysis reveals kinases associated with Alzheimer's disease.

Authors:  Yanting Huang; Xiaobo Sun; Huige Jiang; Shaojun Yu; Chloe Robins; Matthew J Armstrong; Ronghua Li; Zhen Mei; Xiaochuan Shi; Ekaterina Sergeevna Gerasimov; Philip L De Jager; David A Bennett; Aliza P Wingo; Peng Jin; Thomas S Wingo; Zhaohui S Qin
Journal:  Nat Commun       Date:  2021-07-22       Impact factor: 17.694

10.  Decreased MEF2A Expression Regulated by Its Enhancer Methylation Inhibits Autophagy and May Play an Important Role in the Progression of Alzheimer's Disease.

Authors:  Hui Li; Feng Wang; Xuqi Guo; Yugang Jiang
Journal:  Front Neurosci       Date:  2021-06-16       Impact factor: 4.677

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