Cited by 594Epigenetics and DNA MethylationAlzheimer's disease research and treatmentsDementia and Cognitive Impairment Research

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

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Lunnon, Katie, Smith, Rebecca, Hannon, Eilis, De Jager, Philip L, Srivastava, Gyan, Volta, Manuela, Troakes, Claire, Al-Sarraj, Safa, Burrage, Joe, Macdonald, Ruby, Condliffe, Daniel, Harries, Lorna W, Katsel, Pavel, Haroutunian, Vahram, Kaminsky, Zachary, Joachim, Catharine, Powell, John, Lovestone, Simon, Bennett, David A, Schalkwyk, Leonard C, Mill, Jonathan·2014·Nature Neuroscience

DOI 10.1038/nn.3782PMC PMC4410018

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Abstract

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.

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R: A Language and Environment for Statistical Computing
R Core Team (2000) · doi:10.32614/r.manuals · Cited by 355,893
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
Neuropathological stageing of Alzheimer-related changes.
Braak, H., & Braak, E. (1991) · Acta Neuropathologica · doi:10.1007/bf00308809 · Cited by 16,123
The Amyloid Hypothesis of Alzheimer’s Disease: Progress and Problems on the Road to Therapeutics
Hardy, J., & Selkoe, D. J. (2002) · Science · doi:10.1126/science.1072994 · Cited by 13,864
Bioconductor: open software development for computational biology and bioinformatics
Gentleman, R. C., Carey, V. J., Bates, D. M., Bolstad, B., Dettling, M., Dudoit, S., Ellis, B., Gautier, L., Ge, Y., Gentry, J., et al. (2004) · Genome biology · doi:10.1186/gb-2004-5-10-r80 · Cited by 12,082
Amyloid oligomers exacerbate tau pathology in a mouse model of tauopathy
Selenica, M.-L. B., Brownlow, M., Jimenez, J. P., Lee, D. C., Pena, G., Dickey, C. A., Gordon, M. N., & Morgan, D. (2013) · Neurodegenerative Diseases · doi:10.1159/000337230 · Cited by 10,359
Alzheimer's disease: the amyloid cascade hypothesis
Hardy, J. A., & Higgins, G. A. (1992) · Science · doi:10.1126/science.1566067 · Cited by 7,484
Meta-Analysis of 74,046 Individuals Identifies 11 New Susceptibility Loci for Alzheimer’s Disease
(EADI), E. A. D. I., Lambert, J.-C., (GERAD), G. A. E. R. I. A. D., Alzheimer's Disease Genetic Consortium (ADGC), (CHARGE), C. F. H. A. A. R. I. G. E., Ibrahim-Verbaas, C. A., Harold, D., Naj, A. C., Sims, R., Bellenguez, C., et al. (2013) · Nature Genetics · doi:10.1038/ng.2802 · Cited by 4,336
Self-citation
Forecasting the global burden of Alzheimer's disease
Brookmeyer, R., Johnson, E., Ziegler‐Graham, K., & Arrighi, H. M. (2007) · Alzheimer's & Dementia · doi:10.1016/j.jalz.2007.04.381 · Cited by 3,370
The projected effect of risk factor reduction on Alzheimer's disease prevalence
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Sun, Y., & Li, Q. S. (2018) · doi:10.35841/neurology-neurorehabilitation.3.1.22-25
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Additional file 3 of Longitudinal data in peripheral blood confirm that PM20D1 is a quantitative trait locus (QTL) for Alzheimer’s disease and implicate its dynamic role in disease progression
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Additional file 2 of Prediction of differentially expressed microRNAs in blood as potential biomarkers for Alzheimer’s disease by meta-analysis and adaptive boosting ensemble learning
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Additional file 7 of Longitudinal data in peripheral blood confirm that PM20D1 is a quantitative trait locus (QTL) for Alzheimer’s disease and implicate its dynamic role in disease progression
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Additional file 3 of Leveraging biological and statistical covariates improves the detection power in epigenome-wide association testing
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Additional file 2 of Leveraging biological and statistical covariates improves the detection power in epigenome-wide association testing
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Additional file 5 of Leveraging biological and statistical covariates improves the detection power in epigenome-wide association testing
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Additional file 1 of Longitudinal data in peripheral blood confirm that PM20D1 is a quantitative trait locus (QTL) for Alzheimer’s disease and implicate its dynamic role in disease progression
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Additional file 1 of Prediction of differentially expressed microRNAs in blood as potential biomarkers for Alzheimer’s disease by meta-analysis and adaptive boosting ensemble learning
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Additional file 5 of Longitudinal data in peripheral blood confirm that PM20D1 is a quantitative trait locus (QTL) for Alzheimer’s disease and implicate its dynamic role in disease progression
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Additional file 1 of Leveraging biological and statistical covariates improves the detection power in epigenome-wide association testing
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Additional file 4 of Longitudinal data in peripheral blood confirm that PM20D1 is a quantitative trait locus (QTL) for Alzheimer’s disease and implicate its dynamic role in disease progression
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Additional file 4 of Leveraging biological and statistical covariates improves the detection power in epigenome-wide association testing
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Additional file 2 of Longitudinal data in peripheral blood confirm that PM20D1 is a quantitative trait locus (QTL) for Alzheimer’s disease and implicate its dynamic role in disease progression
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Additional file 8 of Longitudinal data in peripheral blood confirm that PM20D1 is a quantitative trait locus (QTL) for Alzheimer’s disease and implicate its dynamic role in disease progression
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Additional file 2 of Sex-specific DNA methylation differences in Alzheimer’s disease pathology
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Additional file 7 of Leveraging biological and statistical covariates improves the detection power in epigenome-wide association testing
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Additional file 1 of Sex-specific DNA methylation differences in Alzheimer’s disease pathology
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Additional file 6 of Leveraging biological and statistical covariates improves the detection power in epigenome-wide association testing
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Additional file 1 of Blood-based epigenome-wide analyses of cognitive abilities
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Additional file 1 of Distinct sex-specific DNA methylation differences in Alzheimer’s disease
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Additional file 9 of Longitudinal data in peripheral blood confirm that PM20D1 is a quantitative trait locus (QTL) for Alzheimer’s disease and implicate its dynamic role in disease progression
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Additional file 2 of Identification of epigenome-wide DNA methylation differences between carriers of APOE ε4 and APOE ε2 alleles
Walker, R. M., Vaher, K., Bermingham, M. L., Morris, S. W., Bretherick, A. D., Zeng, Y., Rawlik, K., Amador, C., Campbell, A., Haley, C. S., et al. (2021) · Figshare · doi:10.6084/m9.figshare.13521102
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Authors: Lunnon, K., Smith, R., Hannon, E., De Jager, P. L., Srivastava, G., Volta, M., Troakes, C., Al-Sarraj, S., Burrage, J., Macdonald, R., Condliffe, D., Harries, L. W., Katsel, P., Haroutunian, V., Kaminsky, Z., Joachim, C., Powell, J., Lovestone, S., Bennett, D. A., Schalkwyk, L. C., & Mill, J.
Affiliations: University of Exeter (GB)
King's College London (GB)
Broad Institute (US)
Icahn School of Medicine at Mount Sinai (US)
Johns Hopkins University (US)
John Radcliffe Hospital (GB)
Rush University Medical Center (US)
Corresponding author: Mill, Jonathan
ORCID: Lunnon, Katie
Smith, Rebecca
Hannon, Eilis
Srivastava, Gyan
Volta, Manuela
Troakes, Claire
Burrage, Joe
Harries, Lorna W
Katsel, Pavel
Haroutunian, Vahram
Kaminsky, Zachary
Powell, John
Lovestone, Simon
Bennett, David A
Schalkwyk, Leonard C
Mill, Jonathan
Venue: Nature Neuroscience
Publisher: Springer Science and Business Media LLC
Published: 2014-08-17
Volume: 17
Issue: 9
Pages: 1164-1170
ISSN: 1097-6256 (ISSN-L)
1546-1726
DOI: 10.1038/nn.3782
PMC: PMC4410018
OpenAlex: W1991244004
Cited by: 574
References: 47
Citations by year: 2026: 26 · 2025: 38 · 2024: 43 · 2023: 46 · 2022: 49 · 2021: 56 · 2020: 65 · 2019: 46 · 2018: 56 · 2017: 41 · 2016: 56 · 2015: 37 · 2014: 15
FWCI: 20.38
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: www.springer.com/tdm (tdm)
www.springer.com/tdm (vor)
Locations: Nature Neuroscience (publishedVersion)
PubMed (publishedVersion)
PubMed Central (acceptedVersion)
Open Access at Essex (University of Essex) (acceptedVersion)
Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
Figshare (submittedVersion)
Research Portal (King's College London) (submittedVersion, other-oa)
Open Research Exeter (University of Exeter) (submittedVersion)
Funders: Medical Research Council (MR/L022656/1)
National Institute on Aging (R01AG017917, P30-AG 10161, K25AG041906, R01AG036039, AG-02219, R01‐AG17917, R01 AG15819, R01AG018023, R01AG036836, AG 05138, P50AG005138, R01-AG18023, R01AG036042, R01AG015819, P30AG010161, RC2AG036547, R01AG032990, P01AG002219, RF1AG036042, P50AG016574)
National Institute of Mental Health (R01MH064673, MH-064673)
National Institute of Environmental Health Sciences (U01ES017155)
National Center for Research Resources (KL2RR024151)
Topics: Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Alzheimer's disease research and treatments
Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
Keywords: Alzheimer's disease, ANK1, DNA methylation, hypermethylation, differentially methylated regions, entorhinal cortex, superior temporal gyrus, prefrontal cortex, cerebellum, epigenome-wide association study, postmortem brain
MeSH terms: Aged, Aged, 80 and over, Alzheimer Disease, Cerebral Cortex, Female, Humans, Male, Middle Aged, Temporal Lobe, Prefrontal Cortex, Ankyrins, Entorhinal Cortex, DNA Methylation, Epigenesis, Genetic, Genome-Wide Association Study, Transcriptome

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

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