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1. DNA methylation aging clocks: challenges and recommendations

Author

Bell, Christopher G, Lowe, Robert, Adams, Peter D, Baccarelli, Andrea A, Beck, Stephan, Bell, Jordana T, Christensen, Brock C, Gladyshev, Vadim N, Heijmans, Bastiaan T, Horvath, Steve, Ideker, Trey, Issa, Jean-Pierre J, Kelsey, Karl T, Marioni, Riccardo E, Reik, Wolf, Relton, Caroline L, Schalkwyk, Leonard C, Teschendorff, Andrew E, Wagner, Wolfgang, Zhang, Kang, and Rakyan, Vardhman K

Subjects
Human Genome, Genetics, Aging, Generic health relevance, Animals, Biological Clocks, DNA Methylation, Epigenesis, Genetic, Genome, Human, Genome-Wide Association Study, Humans, Environmental Sciences, Biological Sciences, Information and Computing Sciences, Bioinformatics
Abstract

Epigenetic clocks comprise a set of CpG sites whose DNA methylation levels measure subject age. These clocks are acknowledged as a highly accurate molecular correlate of chronological age in humans and other vertebrates. Also, extensive research is aimed at their potential to quantify biological aging rates and test longevity or rejuvenating interventions. Here, we discuss key challenges to understand clock mechanisms and biomarker utility. This requires dissecting the drivers and regulators of age-related changes in single-cell, tissue- and disease-specific models, as well as exploring other epigenomic marks, longitudinal and diverse population studies, and non-human models. We also highlight important ethical issues in forensic age determination and predicting the trajectory of biological aging in an individual.

Published
2019

2. Genome-wide DNA methylation profiling identifies convergent molecular signatures associated with idiopathic and syndromic autism in post-mortem human brain tissue

Author

Wong, Chloe CY, Smith, Rebecca G, Hannon, Eilis, Ramaswami, Gokul, Parikshak, Neelroop N, Assary, Elham, Troakes, Claire, Poschmann, Jeremie, Schalkwyk, Leonard C, Sun, Wenjie, Prabhakar, Shyam, Geschwind, Daniel H, and Mill, Jonathan

Subjects
Human Genome, Neurosciences, Intellectual and Developmental Disabilities (IDD), Autism, Genetics, Pediatric, Mental Health, Brain Disorders, Aetiology, 1.1 Normal biological development and functioning, Underpinning research, 2.1 Biological and endogenous factors, Mental health, Neurological, Autistic Disorder, Case-Control Studies, Cerebellum, DNA Methylation, Epigenome, Female, Gene Ontology, Gene Regulatory Networks, Genome, Human, Humans, Immune System, Male, Neural Pathways, Prefrontal Cortex, Synaptic Transmission, Temporal Lobe, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Autism spectrum disorder (ASD) encompasses a collection of complex neuropsychiatric disorders characterized by deficits in social functioning, communication and repetitive behaviour. Building on recent studies supporting a role for developmentally moderated regulatory genomic variation in the molecular aetiology of ASD, we quantified genome-wide patterns of DNA methylation in 223 post-mortem tissues samples isolated from three brain regions [prefrontal cortex, temporal cortex and cerebellum (CB)] dissected from 43 ASD patients and 38 non-psychiatric control donors. We identified widespread differences in DNA methylation associated with idiopathic ASD (iASD), with consistent signals in both cortical regions that were distinct to those observed in the CB. Individuals carrying a duplication on chromosome 15q (dup15q), representing a genetically defined subtype of ASD, were characterized by striking differences in DNA methylationacross a discrete domain spanning an imprinted gene cluster within the duplicated region. In addition to the dramatic cis-effects on DNA methylation observed in dup15q carriers, we identified convergent methylomic signatures associated with both iASD and dup15q, reflecting the findings from previous studies of gene expression and H3K27ac. Cortical co-methylation network analysis identified a number of co-methylated modules significantly associated with ASD that are enriched for genomic regions annotated to genes involved in the immune system, synaptic signalling and neuronal regulation. Our study represents the first systematic analysis of DNA methylation associated with ASD across multiple brain regions, providing novel evidence for convergent molecular signatures associated with both idiopathic and syndromic autism.

Published
2019

3. Quantifying the proportion of different cell types in the human cortex using DNA methylation profiles

Author

Hannon, Eilis, primary, Dempster, Emma L., additional, Davies, Jonathan P., additional, Chioza, Barry, additional, Blake, Georgina E. T., additional, Burrage, Joe, additional, Policicchio, Stefania, additional, Franklin, Alice, additional, Walker, Emma M., additional, Bamford, Rosemary A., additional, Schalkwyk, Leonard C., additional, and Mill, Jonathan, additional

Published
2024
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5. Alzheimer's disease: early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci

Author

De Jager, Philip L, Srivastava, Gyan, Lunnon, Katie, Burgess, Jeremy, Schalkwyk, Leonard C, Yu, Lei, Eaton, Matthew L, Keenan, Brendan T, Ernst, Jason, McCabe, Cristin, Tang, Anna, Raj, Towfique, Replogle, Joseph, Brodeur, Wendy, Gabriel, Stacey, Chai, High S, Younkin, Curtis, Younkin, Steven G, Zou, Fanggeng, Szyf, Moshe, Epstein, Charles B, Schneider, Julie A, Bernstein, Bradley E, Meissner, Alex, Ertekin-Taner, Nilufer, Chibnik, Lori B, Kellis, Manolis, Mill, Jonathan, and Bennett, David A

Subjects
Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), Brain Disorders, Alzheimer's Disease, Human Genome, Genetics, Dementia, Neurodegenerative, Acquired Cognitive Impairment, Aging, 2.1 Biological and endogenous factors, Aetiology, Neurological, Adaptor Proteins, Signal Transducing, Aged, Aged, 80 and over, Alzheimer Disease, Amyloidosis, Ankyrins, Brain, Carrier Proteins, CpG Islands, DNA Methylation, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Intracellular Signaling Peptides and Proteins, Male, Middle Aged, Nuclear Proteins, Protein Interaction Maps, Tumor Suppressor Proteins, Psychology, Cognitive Sciences, Neurology & Neurosurgery
Abstract

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.

Published
2014

19. Leveraging DNA-Methylation Quantitative-Trait Loci to Characterize the Relationship between Methylomic Variation, Gene Expression, and Complex Traits

Author

Hannon, Eilis, Gorrie-Stone, Tyler J., Smart, Melissa C., Burrage, Joe, Hughes, Amanda, Bao, Yanchun, Kumari, Meena, Schalkwyk, Leonard C., and Mill, Jonathan

Subjects
summary-data-based Mendelian randomization, genome-wide association study, DNA methylation, quantitative-trait loci, Transcription, Genetic, QTL, Quantitative Trait Loci, Genetic Variation, SNP, Gene Expression, DNA, SMR, single-nucleotide polymorphism, Article, Epigenesis, Genetic, complex traits, Phenotype, Quantitative Trait, Heritable, pleiotropy, GWAS, Humans, Longitudinal Studies, Transcriptome
Abstract

Characterizing the complex relationship between genetic, epigenetic, and transcriptomic variation has the potential to increase understanding about the mechanisms underpinning health and disease phenotypes. We undertook a comprehensive analysis of common genetic variation on DNA methylation (DNAm) by using the Illumina EPIC array to profile samples from the UK Household Longitudinal study. We identified 12,689,548 significant DNA methylation quantitative trait loci (mQTL) associations (p < 6.52 × 10−14) occurring between 2,907,234 genetic variants and 93,268 DNAm sites, including a large number not identified by previous DNAm-profiling methods. We demonstrate the utility of these data for interpreting the functional consequences of common genetic variation associated with > 60 human traits by using summary-data-based Mendelian randomization (SMR) to identify 1,662 pleiotropic associations between 36 complex traits and 1,246 DNAm sites. We also use SMR to characterize the relationship between DNAm and gene expression and thereby identify 6,798 pleiotropic associations between 5,420 DNAm sites and the transcription of 1,702 genes. Our mQTL database and SMR results are available via a searchable online database as a resource to the research community.

Published
2018

20. Recalibrating the epigenetic clock: implications for assessing biological age in the human cortex

Author

Shireby, Gemma L, primary, Davies, Jonathan P, additional, Francis, Paul T, additional, Burrage, Joe, additional, Walker, Emma M, additional, Neilson, Grant W A, additional, Dahir, Aisha, additional, Thomas, Alan J, additional, Love, Seth, additional, Smith, Rebecca G, additional, Lunnon, Katie, additional, Kumari, Meena, additional, Schalkwyk, Leonard C, additional, Morgan, Kevin, additional, Brookes, Keeley, additional, Hannon, Eilis, additional, and Mill, Jonathan, additional

Published
2020
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24. Genome-wide DNA methylation profiling identifies convergent molecular signatures associated with idiopathic and syndromic autism in post-mortem human brain tissue

Author

Wong, Chloe C Y, Smith, Rebecca G, Hannon, Eilis, Ramaswami, Gokul, Parikshak, Neelroop N, Assary, Elham, Troakes, Claire, Poschmann, Jeremie, Schalkwyk, Leonard C, Sun, Wenjie, Prabhakar, Shyam, Geschwind, Daniel H, Mill, Jonathan, King‘s College London, University of Exeter Medical School, University of Exeter, University of California [Los Angeles] (UCLA), University of California, Queen Mary University of London (QMUL), Centre de Recherche en Transplantation et Immunologie (U1064 Inserm - CRTI), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), Institut de transplantation urologie-néphrologie (ITUN), Université de Nantes (UN)-Centre hospitalier universitaire de Nantes (CHU Nantes), University of Essex, Genome Institute of Singapore (GIS), PsychENCODE (1R01MH094714 to D.H.G.), Medical ResearchCouncil (MR/R005176/1, MR/K013807/1, MR/M008924/1 to J.M.)., Le Bihan, Sylvie, and University of California (UC)

Subjects
Male, Genetics & Heredity, Genome, Human, [SDV]Life Sciences [q-bio], Prefrontal Cortex, DNA Methylation, Biological Sciences, Synaptic Transmission, Medical and Health Sciences, Temporal Lobe, [SDV] Life Sciences [q-bio], Epigenome, Gene Ontology, Case-Control Studies, Cerebellum, Immune System, Neural Pathways, Humans, Female, Gene Regulatory Networks, General Article, Autistic Disorder
Abstract

International audience; Autism spectrum disorder (ASD) encompasses a collection of complex neuropsychiatric disorders characterized by deficits in social functioning, communication and repetitive behaviour. Building on recent studies supporting a role for developmentally moderated regulatory genomic variation in the molecular aetiology of ASD, we quantified genome-wide patterns of DNA methylation in 223 post-mortem tissues samples isolated from three brain regions [prefrontal cortex, temporal cortex and cerebellum (CB)] dissected from 43 ASD patients and 38 non-psychiatric control donors. We identified widespread differences in DNA methylation associated with idiopathic ASD (iASD), with consistent signals in both cortical regions that were distinct to those observed in the CB. Individuals carrying a duplication on chromosome 15q (dup15q), representing a genetically defined subtype of ASD, were characterized by striking differences in DNA methylationacross a discrete domain spanning an imprinted gene cluster within the duplicated region. In addition to the dramatic cis-effects on DNA methylation observed in dup15q carriers, we identified convergent methylomic signatures associated with both iASD and dup15q, reflecting the findings from previous studies of gene expression and H3K27ac. Cortical co-methylation network analysis identified a number of co-methylated modules significantly associated with ASD that are enriched for genomic regions annotated to genes involved in the immune system, synaptic signalling and neuronal regulation. Our study represents the first systematic analysis of DNA methylation associated with ASD across multiple brain regions, providing novel evidence for convergent molecular signatures associated with both idiopathic and syndromic autism.

Published
2019

25. Highly polygenic architecture of antidepressant treatment response: Comparative analysis of SSRI and NRI treatment in an animal model of depression

Author

Malki, Karim, Tosto, Maria Grazia, Mouriño-Talín, Héctor, Rodríguez-Lorenzo, Sabela, Pain, Oliver, Jumhaboy, Irfan, Liu, Tina, Parpas, Panos, Newman, Stuart, Malykh, Arten, Carboni, Lucia, Uher, Rudolf, McGuffin, Peter, Schalkwyk, Leonard C., Bryson, Kevin, Herbster, Mark, Malki, Karim, Tosto, Maria Grazia, Mouriño-Talín, Héctor, Rodríguez-Lorenzo, Sabela, Pain, Oliver, Jumhaboy, Irfan, Liu, Tina, Parpas, Pano, Newman, Stuart, Malykh, Artem, Carboni, Lucia, Uher, Rudolf, Mcguffin, Peter, Schalkwyk, Leonard C., Bryson, Kevin, Herbster, Mark, and Engineering & Physical Science Research Council (EPSRC)

Subjects
Male, Multifactorial Inheritance, SVM, Antidepressant, Nortriptyline, Citalopram, Hippocampus, HIPPOCAMPAL NEUROGENESIS, CANDIDATE GENES, transcriptomics, Mice, Cellular and Molecular Neuroscience, Machine learning, WIDE ASSOCIATION, FACTOR CREB, Animals, SSRI, Serotonin and Noradrenaline Reuptake Inhibitors, Cyclic AMP Response Element-Binding Protein, Research Articles, Genetics (clinical), Genetics & Heredity, Psychiatry, Depressive Disorder, 0604 Genetics, Science & Technology, DRUG-TREATMENT, CONVERGENT FUNCTIONAL GENOMICS, MOLECULAR-MECHANISMS, Depression, 1103 Clinical Sciences, MAJOR DEPRESSION, ELEMENT-BINDING PROTEIN, Antidepressive Agents, FACTOR-KAPPA-B, Disease Models, Animal, Treatment Outcome, Transcriptomic, Pharmacogenetics, Psychiatry and Mental Health, antidepressants, Serotonin Uptake Inhibitors, Female, Transcriptome, 1109 Neurosciences, Life Sciences & Biomedicine, Selective Serotonin Reuptake Inhibitors, Research Article
Abstract

Response to antidepressant (AD) treatment may be a more polygenic trait than previously hypothesized, with many genetic variants interacting in yet unclear ways. In this study we used methods that can automatically learn to detect patterns of statistical regularity from a sparsely distributed signal across hippocampal transcriptome measurements in a large‐scale animal pharmacogenomic study to uncover genomic variations associated with AD. The study used four inbred mouse strains of both sexes, two drug treatments, and a control group (escitalopram, nortriptyline, and saline). Multi‐class and binary classification using Machine Learning (ML) and regularization algorithms using iterative and univariate feature selection methods, including InfoGain, mRMR, ANOVA, and Chi Square, were used to uncover genomic markers associated with AD response. Relevant genes were selected based on Jaccard distance and carried forward for gene‐network analysis. Linear association methods uncovered only one gene associated with drug treatment response. The implementation of ML algorithms, together with feature reduction methods, revealed a set of 204 genes associated with SSRI and 241 genes associated with NRI response. Although only 10% of genes overlapped across the two drugs, network analysis shows that both drugs modulated the CREB pathway, through different molecular mechanisms. Through careful implementation and optimisations, the algorithms detected a weak signal used to predict whether an animal was treated with nortriptyline (77%) or escitalopram (67%) on an independent testing set. The results from this study indicate that the molecular signature of AD treatment may include a much broader range of genomic markers than previously hypothesized, suggesting that response to medication may be as complex as the pathology. The search for biomarkers of antidepressant treatment response could therefore consider a higher number of genetic markers and their interactions. Through predominately different molecular targets and mechanisms of action, the two drugs modulate the same Creb1 pathway which plays a key role in neurotrophic responses and in inflammatory processes. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Published
2017

26. O4-10-06: INTEGRATED GENETIC-EPIGENETIC ANALYSES OF ALZHEIMER'S DISEASE

Author

Smith, Rebecca G., primary, Pishva, Ehsan, additional, Shireby, Gemma, additional, Smith, Adam R., additional, Hannon, Eilis, additional, Sharp, Andrew J., additional, f Mastroeni, Diego, additional, Schalkwyk, Leonard C., additional, Haroutunian, Vahram, additional, Coleman, Paul D., additional, Bennett, David A., additional, van den Hove, Daniel L.A., additional, De Jager, Philip L., additional, Mill, Jonathan, additional, and Lunnon, Katie, additional

Published
2019
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27. Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation

Author

Min, Josine L., Hemani, Gibran, Hannon, Eilis, Dekkers, Koen F., Castillo-Fernandez, Juan, Luijk, René, Carnero-Montoro, Elena, Lawson, Daniel J., Burrows, Kimberley, Suderman, Matthew, Bretherick, Andrew D., Richardson, Tom G., Klughammer, Johanna, Iotchkova, Valentina, Sharp, Gemma, Al Khleifat, Ahmad, Shatunov, Aleksey, Iacoangeli, Alfredo, McArdle, Wendy L., Ho, Karen M., Kumar, Ashish, Söderhäll, Cilla, Soriano-Tárraga, Carolina, Giralt-Steinhauer, Eva, Kazmi, Nabila, Mason, Dan, McRae, Allan F., Corcoran, David L., Sugden, Karen, Kasela, Silva, Cardona, Alexia, Day, Felix R., Cugliari, Giovanni, Viberti, Clara, Guarrera, Simonetta, Lerro, Michael, Gupta, Richa, Bollepalli, Sailalitha, Mandaviya, Pooja, Zeng, Yanni, Clarke, Toni-Kim, Walker, Rosie M., Schmoll, Vanessa, Czamara, Darina, Ruiz-Arenas, Carlos, Rezwan, Faisal I., Marioni, Riccardo E., Lin, Tian, Awaloff, Yvonne, Germain, Marine, Aïssi, Dylan, Zwamborn, Ramona, van Eijk, Kristel, Dekker, Annelot, van Dongen, Jenny, Hottenga, Jouke-Jan, Willemsen, Gonneke, Xu, Cheng-Jian, Barturen, Guillermo, Català-Moll, Francesc, Kerick, Martin, Wang, Carol, Melton, Phillip, Elliott, Hannah R., Shin, Jean, Bernard, Manon, Yet, Idil, Smart, Melissa, Gorrie-Stone, Tyler, Shaw, Chris, Al Chalabi, Ammar, Ring, Susan M., Pershagen, Göran, Melén, Erik, Jiménez-Conde, Jordi, Roquer, Jaume, Lawlor, Deborah A., Wright, John, Martin, Nicholas G., Montgomery, Grant W., Moffitt, Terrie E., Poulton, Richie, Esko, Tõnu, Milani, Lili, Metspalu, Andres, Perry, John R. B., Ong, Ken K., Wareham, Nicholas J., Matullo, Giuseppe, Sacerdote, Carlotta, Panico, Salvatore, Caspi, Avshalom, Arseneault, Louise, Gagnon, France, Ollikainen, Miina, Kaprio, Jaakko, Felix, Janine F., Rivadeneira, Fernando, Tiemeier, Henning, van IJzendoorn, Marinus H., Uitterlinden, André G., Jaddoe, Vincent W. V., Haley, Chris, McIntosh, Andrew M., Evans, Kathryn L., Murray, Alison, Räikkönen, Katri, Lahti, Jari, Nohr, Ellen A., Sørensen, Thorkild I. A., Hansen, Torben, Morgen, Camilla S., Binder, Elisabeth B., Lucae, Susanne, Gonzalez, Juan Ramon, Bustamante, Mariona, Sunyer, Jordi, Holloway, John W., Karmaus, Wilfried, Zhang, Hongmei, Deary, Ian J., Wray, Naomi R., Starr, John M., Beekman, Marian, van Heemst, Diana, Slagboom, P. Eline, Morange, Pierre-Emmanuel, Trégouët, David-Alexandre, Veldink, Jan H., Davies, Gareth E., de Geus, Eco J. C., Boomsma, Dorret I., Vonk, Judith M., Brunekreef, Bert, Koppelman, Gerard H., Alarcón-Riquelme, Marta E., Huang, Rae-Chi, Pennell, Craig E., van Meurs, Joyce, Ikram, M. Arfan, Hughes, Alun D., Tillin, Therese, Chaturvedi, Nish, Pausova, Zdenka, Paus, Tomas, Spector, Timothy D., Kumari, Meena, Schalkwyk, Leonard C., Visscher, Peter M., Davey Smith, George, Bock, Christoph, Gaunt, Tom R., Bell, Jordana T., Heijmans, Bastiaan T., Mill, Jonathan, and Relton, Caroline L.

Abstract

Characterizing genetic influences on DNA methylation (DNAm) provides an opportunity to understand mechanisms underpinning gene regulation and disease. In the present study, we describe results of DNAm quantitative trait locus (mQTL) analyses on 32,851 participants, identifying genetic variants associated with DNAm at 420,509 DNAm sites in blood. We present a database of >270,000 independent mQTLs, of which 8.5% comprise long-range (trans) associations. Identified mQTL associations explain 15–17% of the additive genetic variance of DNAm. We show that the genetic architecture of DNAm levels is highly polygenic. Using shared genetic control between distal DNAm sites, we constructed networks, identifying 405 discrete genomic communities enriched for genomic annotations and complex traits. Shared genetic variants are associated with both DNAm levels and complex diseases, but only in a minority of cases do these associations reflect causal relationships from DNAm to trait or vice versa, indicating a more complex genotype–phenotype map than previously anticipated.

Published
2021
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29. Genome-wide DNA methylation profiling identifies convergent molecular signatures associated with idiopathic and syndromic forms of autism in post-mortem human brain tissue

Author

Wong, Chloe C.Y., primary, Smith, Rebecca G., additional, Hannon, Eilis, additional, Ramaswami, Gokul, additional, Parikshak, Neelroop N., additional, Assary, Elham, additional, Troakes, Claire, additional, Poschmann, Jeremie, additional, Schalkwyk, Leonard C., additional, Sun, Wenjie, additional, Prabhakar, Shyam, additional, Geschwind, Daniel H., additional, and Mill, Jonathan, additional

Published
2018
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30. Properties of the epigenetic clock and age acceleration

Author

Khoury, Louis El, primary, Gorrie-Stone, Tyler, additional, Smart, Melissa, additional, Hughes, Amanda, additional, Bao, Yanchun, additional, Andrayas, Alexandria, additional, Burrage, Joe, additional, Hannon, Eilis, additional, Kumari, Meena, additional, Mill, Jonathan, additional, and Schalkwyk, Leonard C, additional

Published
2018
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33. A histone acetylome-wide association study of Alzheimer’s disease: neuropathology-associated regulatory variation in the human entorhinal cortex

Author

Marzi, Sarah J., primary, Ribarska, Teodora, additional, Smith, Adam R., additional, Hannon, Eilis, additional, Poschmann, Jeremie, additional, Moore, Karen, additional, Troakes, Claire, additional, Al-Sarraj, Safa, additional, Beck, Stephan, additional, Newman, Stuart, additional, Lunnon, Katie, additional, Schalkwyk, Leonard C., additional, and Mill, Jonathan, additional

Published
2017
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35. Schizophrenia-associated methylomic variation: molecular signatures of disease and polygenic risk burden across multiple brain regions

Author

Viana, Joana, primary, Hannon, Eilis, additional, Dempster, Emma, additional, Pidsley, Ruth, additional, Macdonald, Ruby, additional, Knox, Olivia, additional, Spiers, Helen, additional, Troakes, Claire, additional, Al-Saraj, Safa, additional, Turecki, Gustavo, additional, Schalkwyk, Leonard C, additional, and Mill, Jonathan, additional

Published
2016
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36. Highly polygenic architecture of antidepressant treatment response: Comparative analysis of SSRI and NRI treatment in an animal model of depression

Author

Malki, Karim, primary, Tosto, Maria Grazia, additional, Mouriño-Talín, Héctor, additional, Rodríguez-Lorenzo, Sabela, additional, Pain, Oliver, additional, Jumhaboy, Irfan, additional, Liu, Tina, additional, Parpas, Panos, additional, Newman, Stuart, additional, Malykh, Artem, additional, Carboni, Lucia, additional, Uher, Rudolf, additional, McGuffin, Peter, additional, Schalkwyk, Leonard C., additional, Bryson, Kevin, additional, and Herbster, Mark, additional

Published
2016
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37. Bigmelon: tools for analysing large DNA methylation datasets.

Author

Gorrie-Stone, Tyler J, Smart, Melissa C, Saffari, Ayden, Malki, Karim, Hannon, Eilis, Burrage, Joe, Mill, Jonathan, Kumari, Meena, and Schalkwyk, Leonard C

Subjects
DNA methylation, EPIGENETICS, BIOINFORMATICS, DATA mining, BIG data
Abstract

Motivation The datasets generated by DNA methylation analyses are getting bigger. With the release of the HumanMethylationEPIC micro-array and datasets containing thousands of samples, analyses of these large datasets using R are becoming impractical due to large memory requirements. As a result there is an increasing need for computationally efficient methodologies to perform meaningful analysis on high dimensional data. Results Here we introduce the bigmelon R package, which provides a memory efficient workflow that enables users to perform the complex, large scale analyses required in epigenome wide association studies (EWAS) without the need for large RAM. Building on top of the CoreArray Genomic Data Structure file format and libraries packaged in the gdsfmt package, we provide a practical workflow that facilitates the reading-in, preprocessing, quality control and statistical analysis of DNA methylation data. We demonstrate the capabilities of the bigmelon package using a large dataset consisting of 1193 human blood samples from the Understanding Society: UK Household Longitudinal Study, assayed on the EPIC micro-array platform. Availability and implementation The bigmelon package is available on Bioconductor (http://bioconductor.org/packages/bigmelon/). The Understanding Society dataset is available at https://www.understandingsociety.ac.uk/about/health/data upon request. Supplementary information Supplementary data are available at Bioinformatics online. [ABSTRACT FROM AUTHOR]

Published
2019
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38. INTEGRATED GENETIC-EPIGENETIC ANALYSES OF ALZHEIMER'S DISEASE

Author

Smith, Rebecca G., Pishva, Ehsan, Shireby, Gemma, Smith, Adam R., Hannon, Eilis, Sharp, Andrew J., Mastroeni, Diego f, Schalkwyk, Leonard C., Haroutunian, Vahram, Coleman, Paul D., Bennett, David A., van den Hove, Daniel L.A., De Jager, Philip L., Mill, Jonathan, and Lunnon, Katie

Published
2019
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39. Alzheimer's disease: early alterations in brain DNA methylation at ANK1, BIN1, RHBDF2 and other loci

Author

Srivastava, Gyan, Lunnon, Katie, Burgess, Jeremy, Yu, Lei, Ernst, Jason, McCabe, Cristin, Tang, Anna, Raj, Towfique, Replogle, Joseph, Brodeur, Wendy, Gabriel, Stacey, Younkin, Curtis, Zou, Fanggeng, Szyf, Moshe, Meissner, Alexander, Ertekin-Taner, Nilufer, Kellis, Manolis, Mill, Jonathan, De Jager, Philip L., Schalkwyk, Leonard C., Eaton, Matthew Lucas, Eaton, Matthew L., Keenan, Brendan T., Chai, High S., Younkin, Steven G., Epstein, Charles B., Schneider, Julie A., Bernstein, Bradley E., Chibnik, Lori B., Bennett, David A., Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science, Eaton, Matthew Lucas, Ernst, Jason, Meissner, Alexander, and Kellis, Manolis

Subjects
Male, Aging, Genome-wide association study, Neurodegenerative, Alzheimer's Disease, 80 and over, 2.1 Biological and endogenous factors, Psychology, Protein Interaction Maps, Aetiology, Epigenomics, Genetics, Aged, 80 and over, General Neuroscience, Intracellular Signaling Peptides and Proteins, Brain, Adaptor Proteins, Nuclear Proteins, Methylation, Amyloidosis, Middle Aged, 3. Good health, CpG site, Neurological, DNA methylation, Female, Cognitive Sciences, Alzheimer's disease, Ankyrins, and over, Biology, Article, Alzheimer Disease, Acquired Cognitive Impairment, medicine, Humans, Genetic Predisposition to Disease, Gene, Adaptor Proteins, Signal Transducing, Aged, Neurology & Neurosurgery, Tumor Suppressor Proteins, Human Genome, Signal Transducing, Neurosciences, Alzheimer's Disease including Alzheimer's Disease Related Dementias (AD/ADRD), DNA Methylation, medicine.disease, Brain Disorders, Differentially methylated regions, Dementia, CpG Islands, Carrier Proteins, Genome-Wide Association Study
Abstract

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., National Institutes of Health (U.S.) (Grant R01 AG036042), National Institutes of Health (U.S.) (Grant R01AG036836), National Institutes of Health (U.S.) (Grant R01 AG17917), National Institutes of Health (U.S.) (Grant R01AG15819), National Institutes of Health (U.S.) (Grant R01 AG032990), National Institutes of Health (U.S.) (Grant R01 AG18023), National Institutes of Health (U.S.) (Grant RC2 AG036547), National Institutes of Health (U.S.) (Grant P30 AG10161), National Institutes of Health (U.S.) (Grant P50 AG016574), National Institutes of Health (U.S.) (Grant U01 ES017155), National Institutes of Health (U.S.) (Grant KL2 RR024151), National Institutes of Health (U.S.) (Grant K25 AG041906-01)

Published
2014

40. Transcriptome analysis of genes and gene networks involved in aggressive behavior in mouse and zebrafish

Author

Malki, Karim, primary, Du Rietz, Ebba, additional, Crusio, Wim E., additional, Pain, Oliver, additional, Paya-Cano, Jose, additional, Karadaghi, Rezhaw L., additional, Sluyter, Frans, additional, de Boer, Sietse F., additional, Sandnabba, Kenneth, additional, Schalkwyk, Leonard C., additional, Asherson, Philip, additional, and Tosto, Maria Grazia, additional

Published
2016
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41. Genome-wide DNA methylation levels and altered cortisol stress reactivity following childhood trauma in humans

Author

Houtepen, Lotte C., primary, Vinkers, Christiaan H., additional, Carrillo-Roa, Tania, additional, Hiemstra, Marieke, additional, van Lier, Pol A., additional, Meeus, Wim, additional, Branje, Susan, additional, Heim, Christine M., additional, Nemeroff, Charles B., additional, Mill, Jonathan, additional, Schalkwyk, Leonard C., additional, Creyghton, Menno P., additional, Kahn, René S., additional, Joëls, Marian, additional, Binder, Elisabeth B., additional, and Boks, Marco P. M., additional

Published
2016
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42. Tissue-specific patterns of allelically-skewed DNA methylation

Author

Marzi, Sarah J., primary, Meaburn, Emma L., additional, Dempster, Emma L., additional, Lunnon, Katie, additional, Paya-Cano, Jose L., additional, Smith, Rebecca G., additional, Volta, Manuela, additional, Troakes, Claire, additional, Schalkwyk, Leonard C., additional, and Mill, Jonathan, additional

Published
2016
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46. Intermediate DNA methylation is a conserved signature of genome regulation

Author

Elliott, GiNell, primary, Hong, Chibo, additional, Xing, Xiaoyun, additional, Zhou, Xin, additional, Li, Daofeng, additional, Coarfa, Cristian, additional, Bell, Robert J.A., additional, Maire, Cecile L., additional, Ligon, Keith L., additional, Sigaroudinia, Mahvash, additional, Gascard, Philippe, additional, Tlsty, Thea D., additional, Harris, R. Alan, additional, Schalkwyk, Leonard C., additional, Bilenky, Misha, additional, Mill, Jonathan, additional, Farnham, Peggy J., additional, Kellis, Manolis, additional, Marra, Marco A., additional, Milosavljevic, Aleksandar, additional, Hirst, Martin, additional, Stormo, Gary D., additional, Wang, Ting, additional, and Costello, Joseph F., additional

Published
2015
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