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Zhang W, Young JI, Gomez L, Schmidt MA, Lukacsovich D, Varma A, Chen XS, Kunkle B, Martin ER, Wang L. Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC v1.0 BeadChip microarrays. Epigenetics 2024; 19:2333660. [PMID: 38564759 PMCID: PMC10989698 DOI: 10.1080/15592294.2024.2333660] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Accepted: 03/18/2024] [Indexed: 04/04/2024] Open
Abstract
DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC v1.0 arrays. We conducted a comprehensive assessment of the EPIC v1.0 array probe reliability using 69 blood DNA samples, each measured twice, generated by the Alzheimer's Disease Neuroimaging Initiative study. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliability information for probes on the EPIC v1.0 array, will serve as a valuable resource for future DNAm studies.
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Affiliation(s)
- Wei Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL, USA
| | - Juan I. Young
- Dr. John T MacDonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL, USA
| | - Lissette Gomez
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL, USA
| | - Michael A. Schmidt
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL, USA
| | - David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL, USA
| | - Achintya Varma
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL, USA
| | - X. Steven Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL, USA
| | - Brian Kunkle
- Dr. John T MacDonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL, USA
| | - Eden R. Martin
- Dr. John T MacDonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL, USA
| | - Lily Wang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL, USA
- Dr. John T MacDonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL, USA
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Smith RG, Pishva E, Kouhsar M, Imm J, Dobricic V, Johannsen P, Wittig M, Franke A, Vandenberghe R, Schaeverbeke J, Freund-Levi Y, Frölich L, Scheltens P, Teunissen CE, Frisoni G, Blin O, Richardson JC, Bordet R, Engelborghs S, de Roeck E, Martinez-Lage P, Altuna M, Tainta M, Lleó A, Sala I, Popp J, Peyratout G, Winchester L, Nevado-Holgado A, Verhey F, Tsolaki M, Andreasson U, Blennow K, Zetterberg H, Streffer J, Vos SJB, Lovestone S, Visser PJ, Bertram L, Lunnon K. Blood DNA methylomic signatures associated with CSF biomarkers of Alzheimer's disease in the EMIF-AD study. Alzheimers Dement 2024. [PMID: 39193893 DOI: 10.1002/alz.14098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Revised: 05/15/2024] [Accepted: 05/30/2024] [Indexed: 08/29/2024]
Abstract
INTRODUCTION We investigated blood DNA methylation patterns associated with 15 well-established cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) pathophysiology, neuroinflammation, and neurodegeneration. METHODS We assessed DNA methylation in 885 blood samples from the European Medical Information Framework for Alzheimer's Disease (EMIF-AD) study using the EPIC array. RESULTS We identified Bonferroni-significant differential methylation associated with CSF YKL-40 (five loci) and neurofilament light chain (NfL; seven loci) levels, with two of the loci associated with CSF YKL-40 levels correlating with plasma YKL-40 levels. A co-localization analysis showed shared genetic variants underlying YKL-40 DNA methylation and CSF protein levels, with evidence that DNA methylation mediates the association between genotype and protein levels. Weighted gene correlation network analysis identified two modules of co-methylated loci correlated with several amyloid measures and enriched in pathways associated with lipoproteins and development. DISCUSSION We conducted the most comprehensive epigenome-wide association study (EWAS) of AD-relevant CSF biomarkers to date. Future work should explore the relationship between YKL-40 genotype, DNA methylation, and protein levels in the brain. HIGHLIGHTS Blood DNA methylation was assessed in the EMIF-AD MBD study. Epigenome-wide association studies (EWASs) were performed for 15 Alzheimer's disease (AD)-relevant cerebrospinal fluid (CSF) biomarker measures. Five Bonferroni-significant loci were associated with YKL-40 levels and seven with neurofilament light chain (NfL). DNA methylation in YKL-40 co-localized with previously reported genetic variation. DNA methylation potentially mediates the effect of single-nucleotide polymorphisms (SNPs) in YKL-40 on CSF protein levels.
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Affiliation(s)
- Rebecca G Smith
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, Devon, UK
| | - Ehsan Pishva
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, Devon, UK
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Faculty of Health, Medicine and Life Sciences (FHML), Maastricht University, Maastricht, The Netherlands
| | - Morteza Kouhsar
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, Devon, UK
| | - Jennifer Imm
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, Devon, UK
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany
| | - Peter Johannsen
- Danish Dementia Research Centre, Rigshospitalet, Copenhagen, Denmark
| | - Michael Wittig
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, KU Leuven, Leuven Brain Institute, Leuven, Belgium
| | - Jolien Schaeverbeke
- Laboratory for Cognitive Neurology, KU Leuven, Leuven Brain Institute, Leuven, Belgium
| | - Yvonne Freund-Levi
- Department of Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden
- School of Medical Sciences, Örebro University, Örebro, Sweden
- Department of Geriatrics, Södertälje Hospital, Södertälje, Sweden
| | - Lutz Frölich
- Department of Geriatric Psychiatry, Central Institut of Mental Health, Medical Faculty Mannheim/Heidelberg University, Mannheim, Germany
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Giovanni Frisoni
- Memory center, Geneva University and University Hospitals; on behalf of the AMYPAD consortium, Geneva, Switzerland
| | - Olivier Blin
- Aix-Marseille University-CNRS, Marseille, France
| | - Jill C Richardson
- Neuroscience Therapeutic Area, GlaxoSmithKline R&D, Stevenage, Hertfordshire, UK
| | | | - Sebastiaan Engelborghs
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Neuroprotection & Neuromodulation (NEUR) Research Group, Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Jette, Brussels, Belgium
| | - Ellen de Roeck
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Pablo Martinez-Lage
- Center for Research and Advanced Therapies, Fundación CITA-Alzhéimer Fundazioa, San Sebastian, Gipuzkoa, Spain
| | - Miren Altuna
- Center for Research and Advanced Therapies, Fundación CITA-Alzhéimer Fundazioa, San Sebastian, Gipuzkoa, Spain
| | - Mikel Tainta
- Center for Research and Advanced Therapies, Fundación CITA-Alzhéimer Fundazioa, San Sebastian, Gipuzkoa, Spain
| | - Alberto Lleó
- Servicio de Neurología, Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Hospital Sant Pau, Barcelona, Spain
| | - Isabel Sala
- Servicio de Neurología, Centre of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Hospital Sant Pau, Barcelona, Spain
| | - Julius Popp
- University Hospital of Psychiatry Zürich, University of Zürich, Zürich, Switzerland
| | - Gwendoline Peyratout
- Department of Psychiatry, University Hospital of Lausanne (CHUV), Lausanne, Switzerland
| | | | | | - Frans Verhey
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Faculty of Health, Medicine and Life Sciences (FHML), Maastricht University, Maastricht, The Netherlands
| | - Magda Tsolaki
- 1st Department of Neurology, School of Medicine, Laboratory of Neurodegenerative Diseases, Center for Interdisciplinary Research and Innovation, Aristotle University of Thessaloniki, and Alzheimer Hellas, Thessaloniki, Greece
| | - Ulf Andreasson
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at University of Gothenburg, Göteborg, Sweden
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at University of Gothenburg, Göteborg, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, PR China
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at University of Gothenburg, Göteborg, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, N.T., Shatin, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Johannes Streffer
- Translational Medicine Neuroscience, UCB Biopharma SRL, Brussels, Belgium
| | - Stephanie J B Vos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Faculty of Health, Medicine and Life Sciences (FHML), Maastricht University, Maastricht, The Netherlands
| | - Simon Lovestone
- Department of Psychiatry, University Hospital of Lausanne (CHUV), Lausanne, Switzerland
- Currently at: Johnson & Johnson Innovative Medicines, Beerse, Belgium
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Faculty of Health, Medicine and Life Sciences (FHML), Maastricht University, Maastricht, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Lübeck, Germany
| | - Katie Lunnon
- Department of Clinical and Biomedical Sciences, Faculty of Health and Life Sciences, University of Exeter, Exeter, Devon, UK
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Huang M, Jin H, Anantharam V, Kanthasamy A, Kanthasamy AG. Mitochondrial stress-induced H4K12 hyperacetylation dysregulates transcription in Parkinson's disease. Front Cell Neurosci 2024; 18:1422362. [PMID: 39188570 PMCID: PMC11345260 DOI: 10.3389/fncel.2024.1422362] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Accepted: 07/08/2024] [Indexed: 08/28/2024] Open
Abstract
Aberrant epigenetic modification has been implicated in the pathogenesis of Parkinson's disease (PD), which is characterized by the irreversible loss of dopaminergic (DAergic) neurons. However, the mechanistic landscape of histone acetylation (ac) in PD has yet to be fully explored. Herein, we mapped the proteomic acetylation profiling changes at core histones H4 and thus identified H4K12ac as a key epigenomic mark in dopaminergic neuronal cells as well as in MitoPark animal model of PD. Notably, the significantly elevated H4K12ac deposition in post-mortem PD brains highlights its clinical relevance to human PD. Increased histone acetyltransferase (HAT) activity and decreased histone deacetylase 2 (HDAC2) and HDAC4 were found in experimental PD cell models, suggesting the HAT/HDAC imbalance associated with mitochondrial stress. Following our delineation of the proteasome dysfunction that possibly contributes to H4K12ac deposition, we characterized the altered transcriptional profile and disease-associated pathways in the MitoPark mouse model of PD. Our study uncovers the axis of mitochondrial impairment-H4K12ac deposition-altered transcription/disease pathways as a neuroepigenetic mechanism underlying PD pathogenesis. These findings provide mechanistic information for the development of potential pharmacoepigenomic translational strategies for PD.
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Affiliation(s)
- Minhong Huang
- Parkinson Disorders Research Laboratory, Iowa Center for Advanced Neurotoxicology, Department of Biomedical Sciences, Iowa State University, Ames, IA, United States
| | - Huajun Jin
- Isakson Center for Neurological Disease Research, Department of Physiology and Pharmacology, University of Georgia, Athens, GA, United States
| | - Vellareddy Anantharam
- Isakson Center for Neurological Disease Research, Department of Physiology and Pharmacology, University of Georgia, Athens, GA, United States
| | - Arthi Kanthasamy
- Isakson Center for Neurological Disease Research, Department of Physiology and Pharmacology, University of Georgia, Athens, GA, United States
| | - Anumantha G. Kanthasamy
- Parkinson Disorders Research Laboratory, Iowa Center for Advanced Neurotoxicology, Department of Biomedical Sciences, Iowa State University, Ames, IA, United States
- Isakson Center for Neurological Disease Research, Department of Physiology and Pharmacology, University of Georgia, Athens, GA, United States
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4
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Bao J, Lee BN, Wen J, Kim M, Mu S, Yang S, Davatzikos C, Long Q, Ritchie MD, Shen L. Employing Informatics Strategies in Alzheimer's Disease Research: A Review from Genetics, Multiomics, and Biomarkers to Clinical Outcomes. Annu Rev Biomed Data Sci 2024; 7:391-418. [PMID: 38848574 DOI: 10.1146/annurev-biodatasci-102423-121021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/09/2024]
Abstract
Alzheimer's disease (AD) is a critical national concern, affecting 5.8 million people and costing more than $250 billion annually. However, there is no available cure. Thus, effective strategies are in urgent need to discover AD biomarkers for disease early detection and drug development. In this review, we study AD from a biomedical data scientist perspective to discuss the four fundamental components in AD research: genetics (G), molecular multiomics (M), multimodal imaging biomarkers (B), and clinical outcomes (O) (collectively referred to as the GMBO framework). We provide a comprehensive review of common statistical and informatics methodologies for each component within the GMBO framework, accompanied by the major findings from landmark AD studies. Our review highlights the potential of multimodal biobank data in addressing key challenges in AD, such as early diagnosis, disease heterogeneity, and therapeutic development. We identify major hurdles in AD research, including data scarcity and complexity, and advocate for enhanced collaboration, data harmonization, and advanced modeling techniques. This review aims to be an essential guide for understanding current biomedical data science strategies in AD research, emphasizing the need for integrated, multidisciplinary approaches to advance our understanding and management of AD.
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Affiliation(s)
- Jingxuan Bao
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA;
| | - Brian N Lee
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA;
| | - Junhao Wen
- Laboratory of AI and Biomedical Science (LABS), Stevens Neuroimaging and Informatics Institute, Keck School of Medicine of USC, University of Southern California, Los Angeles, California, USA
| | - Mansu Kim
- AI Graduate School, Gwangju Institute of Science and Technology, Gwangju, South Korea
| | - Shizhuo Mu
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA;
| | - Shu Yang
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA;
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Qi Long
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA;
| | - Marylyn D Ritchie
- Department of Genetics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA;
| | - Li Shen
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA;
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5
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Lukacsovich D, O’Shea D, Huang H, Zhang W, Young J, Chen XS, Dietrich ST, Kunkle B, Martin E, Wang L. MIAMI-AD (Methylation in Aging and Methylation in AD): an integrative knowledgebase that facilitates explorations of DNA methylation across sex, aging, and Alzheimer's disease. Database (Oxford) 2024; 2024:baae061. [PMID: 39028752 PMCID: PMC11259044 DOI: 10.1093/database/baae061] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Revised: 05/08/2024] [Accepted: 07/03/2024] [Indexed: 07/21/2024]
Abstract
Alzheimer's disease (AD) is a common neurodegenerative disorder with a significant impact on aging populations. DNA methylation (DNAm) alterations have been implicated in both the aging processes and the development of AD. Given that AD affects more women than men, it is also important to explore DNAm changes that occur specifically in each sex. We created MIAMI-AD, a comprehensive knowledgebase containing manually curated summary statistics from 98 published tables in 38 studies, all of which included at least 100 participants. MIAMI-AD enables easy browsing, querying, and downloading DNAm associations at multiple levels-at individual CpG, gene, genomic regions, or genome-wide, in one or multiple studies. Moreover, it also offers tools to perform integrative analyses, such as comparing DNAm associations across different phenotypes or tissues, as well as interactive visualizations. Using several use case examples, we demonstrated that MIAMI-AD facilitates our understanding of age-associated CpGs in AD and the sex-specific roles of DNAm in AD. This open-access resource is freely available to the research community, and all the underlying data can be downloaded. MIAMI-AD facilitates integrative explorations to better understand the interplay between DNAm across aging, sex, and AD. Database URL: https://miami-ad.org/.
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Affiliation(s)
- David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA
| | - Deirdre O’Shea
- Department of Neurology, Comprehensive Center for Brain Health, University of Miami, Miller School of Medicine, 7700 W Camino Real, Boca Raton, FL 33433, USA
| | - Hanchen Huang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA
| | - Wei Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA
| | - Juan Young
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
| | - X Steven Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, 1475 NW 12th Ave, Miami, FL 33136, USA
| | - Sven-Thorsten Dietrich
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
| | - Brian Kunkle
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
| | - Eden Martin
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
| | - Lily Wang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami, Miller School of Medicine, 1501 NW 10th Ave, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, 1475 NW 12th Ave, Miami, FL 33136, USA
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6
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BenDavid E, Ramezanian S, Lu Y, Rousseau J, Schroeder A, Lavertu M, Tremblay JP. Emerging Perspectives on Prime Editor Delivery to the Brain. Pharmaceuticals (Basel) 2024; 17:763. [PMID: 38931430 PMCID: PMC11206523 DOI: 10.3390/ph17060763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2024] [Revised: 06/02/2024] [Accepted: 06/03/2024] [Indexed: 06/28/2024] Open
Abstract
Prime editing shows potential as a precision genome editing technology, as well as the potential to advance the development of next-generation nanomedicine for addressing neurological disorders. However, turning in prime editors (PEs), which are macromolecular complexes composed of CRISPR/Cas9 nickase fused with a reverse transcriptase and a prime editing guide RNA (pegRNA), to the brain remains a considerable challenge due to physiological obstacles, including the blood-brain barrier (BBB). This review article offers an up-to-date overview and perspective on the latest technologies and strategies for the precision delivery of PEs to the brain and passage through blood barriers. Furthermore, it delves into the scientific significance and possible therapeutic applications of prime editing in conditions related to neurological diseases. It is targeted at clinicians and clinical researchers working on advancing precision nanomedicine for neuropathologies.
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Affiliation(s)
- Eli BenDavid
- Laboratory of Biomaterials and Tissue Engineering, Department of Chemical Engineering, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, QC H3C 3A7, Canada;
- Division of Human Genetics, Centre de Recherche du CHU de Québec—Université Laval, Québec, QC G1V 4G2, Canada
- Laboratory of Molecular Genetics and Gene Therapy, Department of Molecular Medicine, Faculty of Medicine, Laval University, Québec, QC G1V 0A6, Canada
- Laboratory of Nanopharmacology and Pharmaceutical Nanoscience, Faculty of Pharmacy, Laval University, Québec, QC G1V 4G2, Canada
- Rappaport Faculty of Medicine, Technion—Israel Institute of Technology, Haifa 3525433, Israel
| | - Sina Ramezanian
- Division of Human Genetics, Centre de Recherche du CHU de Québec—Université Laval, Québec, QC G1V 4G2, Canada
- Laboratory of Molecular Genetics and Gene Therapy, Department of Molecular Medicine, Faculty of Medicine, Laval University, Québec, QC G1V 0A6, Canada
| | - Yaoyao Lu
- Division of Human Genetics, Centre de Recherche du CHU de Québec—Université Laval, Québec, QC G1V 4G2, Canada
- Laboratory of Molecular Genetics and Gene Therapy, Department of Molecular Medicine, Faculty of Medicine, Laval University, Québec, QC G1V 0A6, Canada
| | - Joël Rousseau
- Division of Human Genetics, Centre de Recherche du CHU de Québec—Université Laval, Québec, QC G1V 4G2, Canada
| | - Avi Schroeder
- Laboratory for Targeted Drug Delivery and Personalized Medicine Technologies, Department of Chemical Engineering, Technion—Israel Institute of Technology, Haifa 3200003, Israel;
| | - Marc Lavertu
- Laboratory of Biomaterials and Tissue Engineering, Department of Chemical Engineering, Institute of Biomedical Engineering, Polytechnique Montréal, Montréal, QC H3C 3A7, Canada;
| | - Jacques P. Tremblay
- Division of Human Genetics, Centre de Recherche du CHU de Québec—Université Laval, Québec, QC G1V 4G2, Canada
- Laboratory of Molecular Genetics and Gene Therapy, Department of Molecular Medicine, Faculty of Medicine, Laval University, Québec, QC G1V 0A6, Canada
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7
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Ramos-Campoy O, Comas-Albertí A, Hervás D, Borrego-Écija S, Bosch B, Sandoval J, Fort-Aznar L, Moreno-Izco F, Fernández-Villullas G, Molina-Porcel L, Balasa M, Lladó A, Sánchez-Valle R, Antonell A. Genome-Wide DNA Methylation in Early-Onset-Dementia Patients Brain Tissue and Lymphoblastoid Cell Lines. Int J Mol Sci 2024; 25:5445. [PMID: 38791483 PMCID: PMC11121630 DOI: 10.3390/ijms25105445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 05/08/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
Epigenetics, a potential underlying pathogenic mechanism of neurodegenerative diseases, has been in the scope of several studies performed so far. However, there is a gap in regard to analyzing different forms of early-onset dementia and the use of Lymphoblastoid cell lines (LCLs). We performed a genome-wide DNA methylation analysis on sixty-four samples (from the prefrontal cortex and LCLs) including those taken from patients with early-onset forms of Alzheimer's disease (AD) and frontotemporal dementia (FTD) and healthy controls. A beta regression model and adjusted p-values were used to obtain differentially methylated positions (DMPs) via pairwise comparisons. A correlation analysis of DMP levels with Clariom D array gene expression data from the same cohort was also performed. The results showed hypermethylation as the most frequent finding in both tissues studied in the patient groups. Biological significance analysis revealed common pathways altered in AD and FTD patients, affecting neuron development, metabolism, signal transduction, and immune system pathways. These alterations were also found in LCL samples, suggesting the epigenetic changes might not be limited to the central nervous system. In the brain, CpG methylation presented an inverse correlation with gene expression, while in LCLs, we observed mainly a positive correlation. This study enhances our understanding of the biological pathways that are associated with neurodegeneration, describes differential methylation patterns, and suggests LCLs are a potential cell model for studying neurodegenerative diseases in earlier clinical phases than brain tissue.
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Affiliation(s)
- Oscar Ramos-Campoy
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Aina Comas-Albertí
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - David Hervás
- Department of Applied Statistics and Operations Research and Quality, Universitat Politècnica de València, 46022 Valencia, Spain
| | - Sergi Borrego-Écija
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Beatriz Bosch
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Juan Sandoval
- Epigenomics Core Facility, Health Research Institute La Fe, 46026 Valencia, Spain
| | - Laura Fort-Aznar
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Fermín Moreno-Izco
- Cognitive Disorders Unit, Department of Neurology, Hospital Universitario Donostia, 20014 San Sebastian, Spain
- Instituto de Investigación Sanitaria Biogipuzkoa, Neurosciences Area, Group of Neurodegenerative Diseases, 20014 San Sebastian, Spain
| | - Guadalupe Fernández-Villullas
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Laura Molina-Porcel
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
- Neurological Tissue Bank, Biobank-Hospital Clinic-IDIBAPS, 08036 Barcelona, Spain
| | - Mircea Balasa
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Albert Lladó
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Raquel Sánchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
- Facultat de Medicina i Ciències de la Salut, Institut de Neurociències, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Anna Antonell
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
- Facultat de Medicina i Ciències de la Salut, Institut de Neurociències, Universitat de Barcelona (UB), 08036 Barcelona, Spain
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8
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Dawood S, Natarajan V, Danchaivijitr P. Comprehensive molecular profiling identifies actionable biomarkers for patients from Thailand and the United Arab Emirates with advanced malignancies. Front Oncol 2024; 14:1374087. [PMID: 38800398 PMCID: PMC11116666 DOI: 10.3389/fonc.2024.1374087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2024] [Accepted: 04/03/2024] [Indexed: 05/29/2024] Open
Abstract
Background Comprehensive molecular profiling of tissue samples that can help guide therapy management is not widely available across the globe. Methods Comprehensive molecular profiling through Caris Molecular Intelligence involves the analysis of DNA through next-generation sequencing, chromogenic or fluorescent in situ hybridization, pyrosequencing, and copy number alterations; RNA through whole-transcriptome sequencing and multiplex PCR of RNA; and protein through immunohistochemistry. Results Here we describe the experience of molecular profiling of tumor tissue samples from patients diagnosed with advanced solid tumors and treated in two countries, the United Arab Emirates and Thailand. Tumor cancer cases submitted to Caris Life Sciences (Phoenix, Arizona, USA) for molecular profiling from the UAE and Thailand were retrospectively analyzed (data accessed between 2019 and 2020) for their molecular alterations and clinical biomarkers, without regard to ethnicity. A total of 451 samples from 35 distinct types of advanced cancers were examined for mutations, amplifications, overexpression, exon copy number alterations, microsatellite instability, deficient mismatch repair, tumor mutational burden, and fusions. Interrogating each step of the biological pathway, from DNA to RNA to distinct protein, identified an alteration with an associated therapy for 75% of these tumor samples. The most common alterations identified included elevated PDL-1 that can be targeted with an immune checkpoint inhibitors and amplification of HER2 for which a variety of anti HER2 therapies are available. Conclusion Comprehensive molecular profiling in patients with advanced malignancies can help optimize therapeutic management allowing for improved prognostic outcome.
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Affiliation(s)
- Shaheenah Dawood
- Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, United Arab Emirates
- Oncology Department, Mediclinic City Hospital, Dubai, United Arab Emirates
| | | | - Pongwut Danchaivijitr
- Division of Medical Oncology, Department of Medicine, Faculty of Medicine, Siriraj Hospital, Mahidol University, Bangkok, Thailand
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9
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Miller MW, Wolf EJ, Zhao X, Logue MW, Hawn SE. An EWAS of dementia biomarkers and their associations with age, African ancestry, and PTSD. Clin Epigenetics 2024; 16:38. [PMID: 38431614 PMCID: PMC10908031 DOI: 10.1186/s13148-024-01649-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2023] [Accepted: 02/20/2024] [Indexed: 03/05/2024] Open
Abstract
BACKGROUND Large-scale cohort and epidemiological studies suggest that PTSD confers risk for dementia in later life but the biological mechanisms underlying this association remain unknown. This study examined this question by assessing the influences of PTSD, APOE ε4 genotypes, DNA methylation, and other variables on the age- and dementia-associated biomarkers Aβ40, Aβ42, GFAP, NfL, and pTau-181 measured in plasma. Our primary hypothesis was that PTSD would be associated with elevated levels of these markers. METHODS Analyses were based on data from a PTSD-enriched cohort of 849 individuals. We began by performing factor analyses of the biomarkers, the results of which identified a two-factor solution. Drawing from the ATN research framework, we termed the first factor, defined by Aβ40 and Aβ42, "Factor A" and the second factor, defined by GFAP, NfL and pTau-181, "Factor TN." Next, we performed epigenome-wide association analyses (EWAS) of the two-factor scores. Finally, using structural equation modeling (SEM), we evaluated (a) the influence of PTSD, age, APOE ε4 genotype and other covariates on levels of the ATN factors, and (b) tested the mediating influence of the EWAS-significant DNAm loci on these associations. RESULTS The Factor A EWAS identified one significant locus, cg13053408, in FANCD2OS. The Factor TN analysis identified 3 EWAS-significant associations: cg26033520 near ASCC1, cg23156469 in FAM20B, and cg15356923 in FAM19A4. The SEM showed age to be related to both factors, more so with Factor TN (β = 0.581, p < 0.001) than Factor A (β = 0.330, p < 0.001). Genotype-determined African ancestry was associated with lower Factor A (β = 0.196, p < 0.001). Contrary to our primary hypothesis, we found a modest negative bivariate correlation between PTSD and the TN factor scores (r = - 0.133, p < 0.001) attributable primarily to reduced levels of GFAP (r = - 0.128, p < 0.001). CONCLUSIONS This study identified novel epigenetic associations with ATN biomarkers and demonstrated robust age and ancestral associations that will be essential to consider in future efforts to develop the clinical applications of these tests. The association between PTSD and reduced GFAP, which has been reported previously, warrants further investigation.
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Affiliation(s)
- Mark W Miller
- National Center for PTSD, VA Boston Healthcare System (116B-2), 150 S. Huntington Avenue, Boston, MA, 02130, USA.
- Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA.
| | - Erika J Wolf
- National Center for PTSD, VA Boston Healthcare System (116B-2), 150 S. Huntington Avenue, Boston, MA, 02130, USA
- Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
| | - Xiang Zhao
- National Center for PTSD, VA Boston Healthcare System (116B-2), 150 S. Huntington Avenue, Boston, MA, 02130, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Mark W Logue
- National Center for PTSD, VA Boston Healthcare System (116B-2), 150 S. Huntington Avenue, Boston, MA, 02130, USA
- Department of Psychiatry, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- Biomedical Genetics, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, 02118, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Sage E Hawn
- National Center for PTSD, VA Boston Healthcare System (116B-2), 150 S. Huntington Avenue, Boston, MA, 02130, USA
- Department of Psychology, Old Dominion University, Norfolk, VA, 23529, USA
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10
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Nazer N, Sepehri MH, Mohammadzade H, Mehrmohamadi M. A novel approach toward optimal workflow selection for DNA methylation biomarker discovery. BMC Bioinformatics 2024; 25:37. [PMID: 38262949 PMCID: PMC10804576 DOI: 10.1186/s12859-024-05658-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 01/15/2024] [Indexed: 01/25/2024] Open
Abstract
DNA methylation is a major epigenetic modification involved in many physiological processes. Normal methylation patterns are disrupted in many diseases and methylation-based biomarkers have shown promise in several contexts. Marker discovery typically involves the analysis of publicly available DNA methylation data from high-throughput assays. Numerous methods for identification of differentially methylated biomarkers have been developed, making the need for best practices guidelines and context-specific analyses workflows exceedingly high. To this end, here we propose TASA, a novel method for simulating methylation array data in various scenarios. We then comprehensively assess different data analysis workflows using real and simulated data and suggest optimal start-to-finish analysis workflows. Our study demonstrates that the choice of analysis pipeline for DNA methylation-based marker discovery is crucial and different across different contexts.
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Affiliation(s)
- Naghme Nazer
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
| | | | - Hoda Mohammadzade
- Department of Electrical Engineering, Sharif University of Technology, Tehran, Iran
| | - Mahya Mehrmohamadi
- Department of Biotechnology, College of Science, University of Tehran, Tehran, Iran.
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11
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Turiello R, Nouwairi RL, Keller J, Cunha LL, Dignan LM, Landers JP. A rotationally-driven dynamic solid phase sodium bisulfite conversion disc for forensic epigenetic sample preparation. LAB ON A CHIP 2023; 24:97-112. [PMID: 38019115 DOI: 10.1039/d3lc00867c] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/30/2023]
Abstract
The approaches to forensic human identification (HID) are largely comparative in nature, relying upon the comparison of short tandem repeat profiles to known reference materials and/or database profiles. However, many profiles are generated from evidence materials that either do not have a reference material for comparison or do not produce a database hit. As an alternative to individualizing analysis for HID, researchers of forensic DNA have demonstrated that the human epigenome can provide a wealth of information. However, epigenetic analysis requires sodium b̲is̲ulfite c̲onversion (BSC), a sample preparation method that is time-consuming, labor-intensive, prone to contamination, and characterized by DNA loss and fragmentation. To provide an alternative method for BSC that is more amenable to integration with the forensic DNA workflow, we describe a rotationally-driven, microfluidic method for dynamic solid phase-BSC (dSP-BSC) that streamlines the sample preparation process in an automated format, capable of preparing up to four samples in parallel. The method permitted decreased incubation intervals by ∼36% and was assessed for relative DNA recovery and conversion efficiency and compared to gold-standard and enzymatic approaches.
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Affiliation(s)
- R Turiello
- Department of Chemistry, University of Virginia, Charlottesville, VA, USA.
| | - R L Nouwairi
- Department of Chemistry, University of Virginia, Charlottesville, VA, USA.
| | - J Keller
- Department of Chemistry, University of Virginia, Charlottesville, VA, USA.
| | - L L Cunha
- Department of Chemistry, University of Virginia, Charlottesville, VA, USA.
| | - L M Dignan
- Department of Chemistry, University of Virginia, Charlottesville, VA, USA.
| | - J P Landers
- Department of Chemistry, University of Virginia, Charlottesville, VA, USA.
- Department of Mechanical Engineering, University of Virginia, Charlottesville, VA, USA
- Department of Pathology, University of Virginia, Charlottesville, VA, USA
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12
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Lukacsovich D, O’Shea D, Huang H, Zhang W, Young JI, Steven Chen X, Dietrich ST, Kunkle B, Martin ER, Wang L. MIAMI-AD (Methylation in Aging and Methylation in AD): an integrative knowledgebase that facilitates explorations of DNA methylation across sex, aging, and Alzheimer's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.04.23299412. [PMID: 38105943 PMCID: PMC10723513 DOI: 10.1101/2023.12.04.23299412] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Alzheimer's disease (AD) is a common neurodegenerative disorder with a significant impact on aging populations. DNA methylation (DNAm) alterations have been implicated in both the aging processes and the development of AD. Given that AD affects more women than men, it is also important to explore DNAm changes that occur specifically in each sex. We created MIAMI-AD, a comprehensive knowledge base containing manually curated summary statistics from 97 published tables in 37 studies, all of which included at least 100 participants. MIAMI-AD enables easy browsing, querying, and downloading DNAm associations at multiple levels - at individual CpG, gene, genomic regions, or genome-wide, in one or multiple studies. Moreover, it also offers tools to perform integrative analyses, such as comparing DNAm associations across different phenotypes or tissues, as well as interactive visualizations. Using several use case examples, we demonstrated that MIAMI-AD facilitates our understanding of age-associated CpGs in AD and the sex-specific roles of DNAm in AD. This open-access resource is freely available to the research community, and all the underlying data can be downloaded. MIAMI-AD (https://miami-ad.org/) facilitates integrative explorations to better understand the interplay between DNAm across aging, sex, and AD.
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Affiliation(s)
- David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Deirdre O’Shea
- Department of Neurology, Comprehensive Center for Brain Health, University of Miami Miller School of Medicine, Boca Raton, FL, 33433
| | - Hanchen Huang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Wei Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Juan I. Young
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - X. Steven Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Sven-Thorsten Dietrich
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Brian Kunkle
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Eden R. Martin
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Lily Wang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
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13
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Zhang J, Wang Y, Zhang Y, Yao J. Genome-wide association study in Alzheimer's disease: a bibliometric and visualization analysis. Front Aging Neurosci 2023; 15:1290657. [PMID: 38094504 PMCID: PMC10716290 DOI: 10.3389/fnagi.2023.1290657] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 11/08/2023] [Indexed: 02/23/2024] Open
Abstract
BACKGROUND Thousands of research studies concerning genome-wide association studies (GWAS) in Alzheimer's disease (AD) have been published in the last decades. However, a comprehensive understanding of the current research status and future development trends of GWAS in AD have not been clearly shown. In this study, we tried to gain a systematic overview of GWAS in AD by bibliometric and visualization analysis. METHODS The literature search terms are: ("genome-wide analysis" or "genome-wide association study" or "whole-genome analysis") AND ("Alzheimer's Disease" or "Alzheimer Disease"). Relevant publications were extracted from the Web of Science Core Collection (WoSCC) database. Collected data were further analyzed using VOSviewer, CiteSpace and R package Bibliometrix. The countries, institutions, authors and scholar collaborations were investigated. The co-citation analysis of publications was visualized. In addition, research hotspots and fronts were examined. RESULTS A total of 1,350 publications with 59,818 citations were identified. The number of publications and citations presented a significant rising trend since 2013. The United States was the leading country with an overwhelming number of publications (775) and citations (42,237). The University of Washington and Harvard University were the most prolific institutions with 101 publications each. Bennett DA was the most influential researcher with the highest local H-index. Neurobiology of Aging was the journal with the highest number of publications. Aβ, tau, immunity, microglia and DNA methylation were research hotspots. Disease and causal variants were research fronts. CONCLUSION The most frequently studied AD pathogenesis and research hotspots are (1) Aβ and tau, (2) immunity and microglia, with TREM2 as a potential immunotherapy target, and (3) DNA methylation. The research fronts are (1) looking for genetic similarities between AD and other neurological diseases and syndromes, and (2) searching for causal variants of AD. These hotspots suggest noteworthy directions for future studies on AD pathogenesis and genetics, in which basic research regarding immunity is promising for clinical conversion. The current under-researched directions are (1) GWAS in AD biomarkers based on large sample sizes, (2) studies of causal variants of AD, and (3) GWAS in AD based on non-European populations, which need to be strengthened in the future.
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Affiliation(s)
- Junyao Zhang
- Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yinuo Wang
- Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yingying Zhang
- Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Junyan Yao
- Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Anesthesiology and Critical Care Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
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14
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Reis AHDEO, Figalo LB, Orsini M, Lemos B. The implications of DNA methylation for amyotrophic lateral sclerosis. AN ACAD BRAS CIENC 2023; 95:e20230277. [PMID: 37909610 DOI: 10.1590/0001-3765202320230277] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 07/11/2023] [Indexed: 11/03/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a complex and serious neurodegenerative disorder that develops in consequence of the progressive loss of the upper and lower motor neurons. Cases of ALS are classified as sporadic (sALS), or familial (fALS). Over 90% of cases are sALS, while roughly 10% are related to inherited genetic mutations (fALS). Approximately 70% of the genetic mutations that contribute to fALS have been identified. On the other hand, the majority of the sALS cases have an undetermined genetic contributor and few mutations have been described, despite the advanced genetic analysis methods. Also, several factors contribute to the onset and progression of ALS. Numerous lines of evidence indicate that epigenetic changes are linked to aging, as well as neurodegenerative disorders, such as ALS. In most cases, they act as the heritable regulation of transcription by DNA methylation, histone modification and expression of noncoding RNAs. Mechanisms involving aberrant DNA methylation could be relevant to human ALS pathobiology and therapeutic targeting. Despite advances in research to find factors associated with ALS and more effective treatments, this disease remains complex and has low patient survival. Here, we provide a narrative review of the role of DNA methylation for this complex neurodegenerative disorder.
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Affiliation(s)
- Adriana Helena DE Oliveira Reis
- Universidade do Estado do Rio de Janeiro, Instituto de Biologia Roberto Alcantara Gomes, Departamento de Genética, Pavilhão Haroldo Lisboa da Cunha, Rua São Francisco Xavier, 524, Sala 501F, 20550-900 Rio de Janeiro, RJ, Brazil
| | - Luna B Figalo
- Universidade do Estado do Rio de Janeiro, Instituto de Biologia Roberto Alcantara Gomes, Departamento de Genética, Pavilhão Haroldo Lisboa da Cunha, Rua São Francisco Xavier, 524, Sala 501F, 20550-900 Rio de Janeiro, RJ, Brazil
| | - Marco Orsini
- Programa de Pós-Graduação em Vigilância em Saúde, Universidade Iguaçu, Av. Abílio Augusto Távora, 2134, 26260-045 Nova Iguaçu, RJ, Brazil
- Universidade Federal do Rio de Janeiro, Departamento de Psiquiatria, Av. Venceslau Brás, 71, Botafogo, 22290-140 Rio de Janeiro, RJ, Brazil
| | - Bernardo Lemos
- Coit Center for longevity and Neurotheraéutics, Departament of pharmacology and toxicology, R Ken Coit College of Pharmacy, University of Arizona, 1703 E. Mabel St. PO Box 210207 Tucson, Arizona, USA
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15
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Zhang W, Young JI, Gomez L, Schmidt MA, Lukacsovich D, Varma A, Chen XS, Kunkle B, Martin ER, Wang L. Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC BeadChip microarrays. RESEARCH SQUARE 2023:rs.3.rs-3068938. [PMID: 37461726 PMCID: PMC10350239 DOI: 10.21203/rs.3.rs-3068938/v2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC arrays. We conducted a comprehensive assessment of the EPIC array probe reliability using 138 duplicated blood DNAm samples generated by the Alzheimer's Disease Neuroimaging Initiative study. We introduced a novel statistical measure, the modified intraclass correlation, to better account for the disagreement in duplicate measurements. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliable information for probes on the EPIC array, will serve as a valuable resource for future DNAm studies.
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Affiliation(s)
- Wei Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Juan I. Young
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Lissette Gomez
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Michael A. Schmidt
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Achintya Varma
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - X. Steven Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Brian Kunkle
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Eden R. Martin
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Lily Wang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
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16
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Zhang W, Young JI, Gomez L, Schmidt MA, Lukacsovich D, Varma A, Chen XS, Kunkle B, Martin ER, Wang L. Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC BeadChip microarrays. RESEARCH SQUARE 2023:rs.3.rs-3068938. [PMID: 37461726 PMCID: PMC10350239 DOI: 10.21203/rs.3.rs-3068938/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/24/2023]
Abstract
DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC arrays. We conducted a comprehensive assessment of the EPIC array probe reliability using 138 duplicated blood DNAm samples generated by the Alzheimer's Disease Neuroimaging Initiative study. We introduced a novel statistical measure, the modified intraclass correlation, to better account for the disagreement in duplicate measurements. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliable information for probes on the EPIC array, will serve as a valuable resource for future DNAm studies.
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Affiliation(s)
- Wei Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Juan I. Young
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Lissette Gomez
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Michael A. Schmidt
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Achintya Varma
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - X. Steven Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
| | - Brian Kunkle
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Eden R. Martin
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
| | - Lily Wang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
- John P. Hussman Institute for Human Genomics, the University of Miami Miller School of Medicine, Miami, FL 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136, USA
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17
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Shvetcov A, Thomson S, Spathos J, Cho AN, Wilkins HM, Andrews SJ, Delerue F, Couttas TA, Issar JK, Isik F, Kaur S, Drummond E, Dobson-Stone C, Duffy SL, Rogers NM, Catchpoole D, Gold WA, Swerdlow RH, Brown DA, Finney CA. Blood-Based Transcriptomic Biomarkers Are Predictive of Neurodegeneration Rather Than Alzheimer's Disease. Int J Mol Sci 2023; 24:15011. [PMID: 37834458 PMCID: PMC10573468 DOI: 10.3390/ijms241915011] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 10/06/2023] [Accepted: 10/07/2023] [Indexed: 10/15/2023] Open
Abstract
Alzheimer's disease (AD) is a growing global health crisis affecting millions and incurring substantial economic costs. However, clinical diagnosis remains challenging, with misdiagnoses and underdiagnoses being prevalent. There is an increased focus on putative, blood-based biomarkers that may be useful for the diagnosis as well as early detection of AD. In the present study, we used an unbiased combination of machine learning and functional network analyses to identify blood gene biomarker candidates in AD. Using supervised machine learning, we also determined whether these candidates were indeed unique to AD or whether they were indicative of other neurodegenerative diseases, such as Parkinson's disease (PD) and amyotrophic lateral sclerosis (ALS). Our analyses showed that genes involved in spliceosome assembly, RNA binding, transcription, protein synthesis, mitoribosomes, and NADH dehydrogenase were the best-performing genes for identifying AD patients relative to cognitively healthy controls. This transcriptomic signature, however, was not unique to AD, and subsequent machine learning showed that this signature could also predict PD and ALS relative to controls without neurodegenerative disease. Combined, our results suggest that mRNA from whole blood can indeed be used to screen for patients with neurodegeneration but may be less effective in diagnosing the specific neurodegenerative disease.
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Affiliation(s)
- Artur Shvetcov
- Department of Psychological Medicine, Sydney Children’s Hospitals Network, Sydney, NSW 2031, Australia
- Discipline of Psychiatry and Mental Health, School of Clinical Medicine, Faculty of Medicine and Health, University of New South Wales, Sydney, NSW 2052, Australia
| | - Shannon Thomson
- Neuroinflammation Research Group, Centre for Immunology and Allergy Research, Westmead Institute for Medical Research, Sydney, NSW 2145, Australia
- School of Medical Sciences, Faculty of Medicine Health, The University of Sydney, Sydney, NSW 2050, Australia
| | - Jessica Spathos
- Neuroinflammation Research Group, Centre for Immunology and Allergy Research, Westmead Institute for Medical Research, Sydney, NSW 2145, Australia
| | - Ann-Na Cho
- Dementia Research Centre, Macquarie Medical School, Faculty of Medicine, Health and Human Sciences, Macquarie University, Sydney, NSW 2109, Australia
| | - Heather M. Wilkins
- University of Kansas Alzheimer’s Disease Research Centre, Kansas City, KS 66160, USA
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Centre, Kansas City, KS 66160, USA
- Department of Neurology, University of Kansas Medical Centre, Kansas City, KS 66160, USA
| | - Shea J. Andrews
- Department of Psychiatry & Behavioral Sciences, University of California San Francisco, San Francisco, CA 94143, USA
| | - Fabien Delerue
- Department of Genetics, The University of Texas MD Anderson Cancer Center, Houston, TX 77030, USA
| | - Timothy A. Couttas
- Brain and Mind Centre, Translational Research Collective, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2050, Australia
| | - Jasmeen Kaur Issar
- Molecular Neurobiology Research Laboratory, Kids Research, Children’s Medical Research Institute, Children’s Hospital at Westmead, Westmead, NSW 2145, Australia
- Kids Neuroscience Centre, Kids Research, Children’s Hospital at Westmead, Westmead, NSW 2145, Australia
- Sydney Medical School, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2050, Australia
| | - Finula Isik
- Neuroinflammation Research Group, Centre for Immunology and Allergy Research, Westmead Institute for Medical Research, Sydney, NSW 2145, Australia
- School of Medical Sciences, Faculty of Medicine Health, The University of Sydney, Sydney, NSW 2050, Australia
| | - Simranpreet Kaur
- Murdoch Children’s Research Institute, Royal Children’s Hospital, Parkville, VIC 3052, Australia
- Department of Pediatrics, University of Melbourne, Parkville, VIC 3010, Australia
| | - Eleanor Drummond
- School of Medical Sciences, Faculty of Medicine Health, The University of Sydney, Sydney, NSW 2050, Australia
- Brain and Mind Centre, The University of Sydney, Sydney, NSW 2050, Australia
| | - Carol Dobson-Stone
- School of Medical Sciences, Faculty of Medicine Health, The University of Sydney, Sydney, NSW 2050, Australia
- Brain and Mind Centre, The University of Sydney, Sydney, NSW 2050, Australia
| | - Shantel L. Duffy
- Allied Health, Research and Strategic Partnerships, Nepean Blue Mountains Local Health District, Penrith, NSW 2750, Australia
| | - Natasha M. Rogers
- Centre for Transplant and Renal Research, Westmead Institute for Medical Research, Sydney, NSW 2145, Australia
- Renal and Transplant Medicine Unit, Westmead Hospital, Westmead, NSW 2145, Australia
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2050, Australia
| | - Daniel Catchpoole
- The Tumor Bank, Kids Research, Children’s Hospital at Westmead, Westmead, NSW 2145, Australia
- Children’s Cancer Research Institute, Children’s Hospital at Westmead, Westmead, NSW 2145, Australia
| | - Wendy A. Gold
- School of Medical Sciences, Faculty of Medicine Health, The University of Sydney, Sydney, NSW 2050, Australia
- Molecular Neurobiology Research Laboratory, Kids Research, Children’s Medical Research Institute, Children’s Hospital at Westmead, Westmead, NSW 2145, Australia
- Kids Neuroscience Centre, Kids Research, Children’s Hospital at Westmead, Westmead, NSW 2145, Australia
| | - Russell H. Swerdlow
- University of Kansas Alzheimer’s Disease Research Centre, Kansas City, KS 66160, USA
- Department of Biochemistry and Molecular Biology, University of Kansas Medical Centre, Kansas City, KS 66160, USA
- Department of Neurology, University of Kansas Medical Centre, Kansas City, KS 66160, USA
- Department of Molecular and Integrative Physiology, University of Kansas Medical Centre, Kansas City, KS 66160, USA
| | - David A. Brown
- Neuroinflammation Research Group, Centre for Immunology and Allergy Research, Westmead Institute for Medical Research, Sydney, NSW 2145, Australia
- Westmead Clinical School, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW 2050, Australia
- Department of Immunopathology, Institute for Clinical Pathology and Medical Research-New South Wales Health Pathology, Sydney, NSW 2145, Australia
| | - Caitlin A. Finney
- Neuroinflammation Research Group, Centre for Immunology and Allergy Research, Westmead Institute for Medical Research, Sydney, NSW 2145, Australia
- School of Medical Sciences, Faculty of Medicine Health, The University of Sydney, Sydney, NSW 2050, Australia
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18
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Gupta MK, Peng H, Li Y, Xu CJ. The role of DNA methylation in personalized medicine for immune-related diseases. Pharmacol Ther 2023; 250:108508. [PMID: 37567513 DOI: 10.1016/j.pharmthera.2023.108508] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2022] [Revised: 08/03/2023] [Accepted: 08/08/2023] [Indexed: 08/13/2023]
Abstract
Epigenetics functions as a bridge between host genetic & environmental factors, aiding in human health and diseases. Many immune-related diseases, including infectious and allergic diseases, have been linked to epigenetic mechanisms, particularly DNA methylation. In this review, we summarized an updated overview of DNA methylation and its importance in personalized medicine, and demonstrated that DNA methylation has excellent potential for disease prevention, diagnosis, and treatment in a personalized manner. The future implications and limitations of the DNA methylation study have also been well-discussed.
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Affiliation(s)
- Manoj Kumar Gupta
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany; TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - He Peng
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany; TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany
| | - Yang Li
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany; TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany; Department of Internal Medicine and Radboud Institute for Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Cheng-Jian Xu
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany; TWINCORE, Centre for Experimental and Clinical Infection Research, a joint venture between the Hannover Medical School and the Helmholtz Centre for Infection Research, Hannover, Germany; Department of Internal Medicine and Radboud Institute for Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, the Netherlands.
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19
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Maiarù M, Acton RJ, Woźniak EL, Mein CA, Bell CG, Géranton SM. A DNA methylation signature in the stress driver gene Fkbp5 indicates a neuropathic component in chronic pain. Clin Epigenetics 2023; 15:155. [PMID: 37777763 PMCID: PMC10543848 DOI: 10.1186/s13148-023-01569-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Accepted: 09/17/2023] [Indexed: 10/02/2023] Open
Abstract
BACKGROUND Epigenetic changes can bring insight into gene regulatory mechanisms associated with disease pathogenicity, including chronicity and increased vulnerability. To date, we are yet to identify genes sensitive to epigenetic regulation that contribute to the maintenance of chronic pain and with an epigenetic landscape indicative of the susceptibility to persistent pain. Such genes would provide a novel opportunity for better pain management, as their epigenetic profile could be targeted for the treatment of chronic pain or used as an indication of vulnerability for prevention strategies. Here, we investigated the epigenetic profile of the gene Fkbp5 for this potential, using targeted bisulphite sequencing in rodent pre-clinical models of chronic and latent hypersensitive states. RESULTS The Fkbp5 promoter DNA methylation (DNAm) signature in the CNS was significantly different between models of persistent pain, and there was a significant correlation between CNS and peripheral blood Fkbp5 DNAm, indicating that further exploration of Fkbp5 promoter DNAm as an indicator of chronic pain pathogenic origin is warranted. We also found that maternal separation, which promotes the persistency of inflammatory pain in adulthood, was accompanied by long-lasting reduction in Fkbp5 DNAm, suggesting that Fkbp5 DNAm profile may indicate the increased vulnerability to chronic pain in individuals exposed to trauma in early life. CONCLUSIONS Overall, our data demonstrate that the Fkbp5 promoter DNAm landscape brings novel insight into the differing pathogenic origins of chronic pain, may be able to stratify patients and predict the susceptibility to chronic pain.
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Affiliation(s)
- Maria Maiarù
- Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK
- Department of Pharmacology, School of Pharmacy, University of Reading, Reading, UK
| | - Richard J Acton
- MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton, UK
- Human Development and Health, Institute of Developmental Sciences, University of Southampton, Southampton, UK
- William Harvey Research Institute, Barts & The London Faculty of Medicine, Charterhouse Square, Queen Mary University of London, London, EC1M 6BQ, UK
- Cologne Excellence Cluster for Cellular Stress Responses in Ageing-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Eva L Woźniak
- Genome Centre, Faculty of Medicine and Dentistry, Queen Mary University of London, London, E1 2AT, UK
| | - Charles A Mein
- Genome Centre, Faculty of Medicine and Dentistry, Queen Mary University of London, London, E1 2AT, UK
| | - Christopher G Bell
- William Harvey Research Institute, Barts & The London Faculty of Medicine, Charterhouse Square, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Sandrine M Géranton
- Department of Cell and Developmental Biology, University College London, London, WC1E 6BT, UK.
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20
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Mortlock S, Houshdaran S, Kosti I, Rahmioglu N, Nezhat C, Vitonis AF, Andrews SV, Grosjean P, Paranjpe M, Horne AW, Jacoby A, Lager J, Opoku-Anane J, Vo KC, Manvelyan E, Sen S, Ghukasyan Z, Collins F, Santamaria X, Saunders P, Kober K, McRae AF, Terry KL, Vallvé-Juanico J, Becker C, Rogers PAW, Irwin JC, Zondervan K, Montgomery GW, Missmer S, Sirota M, Giudice L. Global endometrial DNA methylation analysis reveals insights into mQTL regulation and associated endometriosis disease risk and endometrial function. Commun Biol 2023; 6:780. [PMID: 37587191 PMCID: PMC10432557 DOI: 10.1038/s42003-023-05070-z] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Accepted: 06/23/2023] [Indexed: 08/18/2023] Open
Abstract
Endometriosis is a leading cause of pain and infertility affecting millions of women globally. Herein, we characterize variation in DNA methylation (DNAm) and its association with menstrual cycle phase, endometriosis, and genetic variants through analysis of genotype data and methylation in endometrial samples from 984 deeply-phenotyped participants. We estimate that 15.4% of the variation in endometriosis is captured by DNAm and identify significant differences in DNAm profiles associated with stage III/IV endometriosis, endometriosis sub-phenotypes and menstrual cycle phase, including opening of the window for embryo implantation. Menstrual cycle phase was a major source of DNAm variation suggesting cellular and hormonally-driven changes across the cycle can regulate genes and pathways responsible for endometrial physiology and function. DNAm quantitative trait locus (mQTL) analysis identified 118,185 independent cis-mQTLs including 51 associated with risk of endometriosis, highlighting candidate genes contributing to disease risk. Our work provides functional evidence for epigenetic targets contributing to endometriosis risk and pathogenesis. Data generated serve as a valuable resource for understanding tissue-specific effects of methylation on endometrial biology in health and disease.
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Affiliation(s)
- Sally Mortlock
- The Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
| | - Sahar Houshdaran
- Center for Reproductive Sciences, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Idit Kosti
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA
| | - Nilufer Rahmioglu
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Endometriosis CaRe Centre, Nuffield Department of Women's and Reproductive Health, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Camran Nezhat
- Stanford University Medical Center, Palo Alto, CA, USA
- University of California San Francisco, San Francisco, CA, USA
- Camran Nezhat Institute, Center for Special Minimally Invasive and Robotic Surgery, Woodside, CA, USA
| | - Allison F Vitonis
- Obstetrics and Gynecology Epidemiology Center, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Shan V Andrews
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA
| | - Parker Grosjean
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA
| | - Manish Paranjpe
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA
| | - Andrew W Horne
- MRC Centre for Reproductive Health, University of Edinburgh, QMRI, Edinburgh, UK
| | - Alison Jacoby
- Center for Reproductive Sciences, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Jeannette Lager
- Center for Reproductive Sciences, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Jessica Opoku-Anane
- Center for Reproductive Sciences, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Kim Chi Vo
- Center for Reproductive Sciences, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Evelina Manvelyan
- Center for Reproductive Sciences, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Sushmita Sen
- Center for Reproductive Sciences, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Zhanna Ghukasyan
- Center for Reproductive Sciences, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Frances Collins
- MRC Centre for Reproductive Health, University of Edinburgh, QMRI, Edinburgh, UK
| | - Xavier Santamaria
- Carlos Simon Foundation, Health Research Institute, Valencia, Spain
- Group of Biomedical Research in Gynecology, Vall d'Hebron Research Institute, Barcelona, Spain
| | - Philippa Saunders
- Centre for Inflammation Research, Institute for Regeneration and Repair University of Edinburgh, Edinburgh, UK
| | - Kord Kober
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA
- Department of Physiological Nursing, University of California San Francisco, San Francisco, CA, USA
| | - Allan F McRae
- The Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Kathryn L Terry
- Obstetrics and Gynecology Epidemiology Center, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Boston Center for Endometriosis, Boston Children's Hospital and Brigham and Women's Hospital, Boston, MA, USA
| | - Júlia Vallvé-Juanico
- Center for Reproductive Sciences, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, San Francisco, CA, USA
- Group of Biomedical Research in Gynecology, Vall d'Hebron Research Institute, Barcelona, Spain
| | - Christian Becker
- Oxford Endometriosis CaRe Centre, Nuffield Department of Women's and Reproductive Health, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Peter A W Rogers
- University of Melbourne Department of Obstetrics and Gynaecology, Royal Women's Hospital, Melbourne, Australia
| | - Juan C Irwin
- Center for Reproductive Sciences, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, San Francisco, CA, USA
| | - Krina Zondervan
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Oxford Endometriosis CaRe Centre, Nuffield Department of Women's and Reproductive Health, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Grant W Montgomery
- The Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Stacey Missmer
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Boston Center for Endometriosis, Boston Children's Hospital and Brigham and Women's Hospital, Boston, MA, USA
- Division of Adolescent and Young Adult Medicine, Department of Medicine, Boston Children's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Obstetrics, Gynecology, and Reproductive Biology, College of Human Medicine, Michigan State University, Grand Rapids, MI, USA
| | - Marina Sirota
- Bakar Computational Health Sciences Institute, University of California San Francisco, San Francisco, CA, USA
- Department of Pediatrics, Division of Neonatology, University of California San Francisco, San Francisco, CA, USA
| | - Linda Giudice
- Center for Reproductive Sciences, Department of Obstetrics, Gynecology & Reproductive Sciences, University of California San Francisco, San Francisco, CA, USA.
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Gaspar-Silva F, Trigo D, Magalhaes J. Ageing in the brain: mechanisms and rejuvenating strategies. Cell Mol Life Sci 2023; 80:190. [PMID: 37354261 DOI: 10.1007/s00018-023-04832-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2023] [Revised: 05/31/2023] [Accepted: 06/07/2023] [Indexed: 06/26/2023]
Abstract
Ageing is characterized by the progressive loss of cellular homeostasis, leading to an overall decline of the organism's fitness. In the brain, ageing is highly associated with cognitive decline and neurodegenerative diseases. With the rise in life expectancy, characterizing the brain ageing process becomes fundamental for developing therapeutic interventions against the increased incidence of age-related neurodegenerative diseases and to aim for an increase in human life span and, more importantly, health span. In this review, we start by introducing the molecular/cellular hallmarks associated with brain ageing and their impact on brain cell populations. Subsequently, we assess emerging evidence on how systemic ageing translates into brain ageing. Finally, we revisit the mainstream and the novel rejuvenating strategies, discussing the most successful ones in delaying brain ageing and related diseases.
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Affiliation(s)
- Filipa Gaspar-Silva
- i3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Rua Alfredo Allen 208, 4200-135, Porto, Portugal
| | - Diogo Trigo
- Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, 3810-193, Aveiro, Portugal
| | - Joana Magalhaes
- i3S-Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Rua Alfredo Allen 208, 4200-135, Porto, Portugal.
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22
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Zhang W, Young JI, Gomez L, Schmidt MA, Lukacsovich D, Varma A, Chen XS, Martin ER, Wang L. Distinct CSF biomarker-associated DNA methylation in Alzheimer's disease and cognitively normal subjects. Alzheimers Res Ther 2023; 15:78. [PMID: 37038196 PMCID: PMC10088180 DOI: 10.1186/s13195-023-01216-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 03/21/2023] [Indexed: 04/12/2023]
Abstract
BACKGROUND Growing evidence has demonstrated that DNA methylation (DNAm) plays an important role in Alzheimer's disease (AD) and that DNAm differences can be detected in the blood of AD subjects. Most studies have correlated blood DNAm with the clinical diagnosis of AD in living individuals. However, as the pathophysiological process of AD can begin many years before the onset of clinical symptoms, there is often disagreement between neuropathology in the brain and clinical phenotypes. Therefore, blood DNAm associated with AD neuropathology, rather than with clinical data, would provide more relevant information on AD pathogenesis. METHODS We performed a comprehensive analysis to identify blood DNAm associated with cerebrospinal fluid (CSF) pathological biomarkers for AD. Our study included matched samples of whole blood DNA methylation, CSF Aβ42, phosphorylated tau181 (pTau181), and total tau (tTau) biomarkers data, measured on the same subjects and at the same clinical visits from a total of 202 subjects (123 CN or cognitively normal, 79 AD) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. To validate our findings, we also examined the association between premortem blood DNAm and postmortem brain neuropathology measured on a group of 69 subjects in the London dataset. RESULTS We identified a number of novel associations between blood DNAm and CSF biomarkers, demonstrating that changes in pathological processes in the CSF are reflected in the blood epigenome. Overall, the CSF biomarker-associated DNAm is relatively distinct in CN and AD subjects, highlighting the importance of analyzing omics data measured on cognitively normal subjects (which includes preclinical AD subjects) to identify diagnostic biomarkers, and considering disease stages in the development and testing of AD treatment strategies. Moreover, our analysis revealed biological processes associated with early brain impairment relevant to AD are marked by DNAm in the blood, and blood DNAm at several CpGs in the DMR on HOXA5 gene are associated with pTau181 in the CSF, as well as tau-pathology and DNAm in the brain, nominating DNAm at this locus as a promising candidate AD biomarker. CONCLUSIONS Our study provides a valuable resource for future mechanistic and biomarker studies of DNAm in AD.
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Affiliation(s)
- Wei Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA
| | - Juan I Young
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Lissette Gomez
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Michael A Schmidt
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA
| | - Achintya Varma
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - X Steven Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Eden R Martin
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Lily Wang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA.
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA.
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA.
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, 33136, USA.
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23
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Zhang W, Young JI, Gomez L, Schmidt MA, Lukacsovich D, Varma A, Chen XS, Martin ER, Wang L. Distinct CSF biomarker-associated DNA methylation in Alzheimer's disease and cognitively normal subjects. RESEARCH SQUARE 2023:rs.3.rs-2391364. [PMID: 36865230 PMCID: PMC9980279 DOI: 10.21203/rs.3.rs-2391364/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
Background Growing evidence has demonstrated that DNA methylation (DNAm) plays an important role in Alzheimer's disease (AD) and that DNAm differences can be detected in the blood of AD subjects. Most studies have correlated blood DNAm with the clinical diagnosis of AD in living individuals. However, as the pathophysiological process of AD can begin many years before the onset of clinical symptoms, there is often disagreement between neuropathology in the brain and clinical phenotypes. Therefore, blood DNAm associated with AD neuropathology, rather than with clinical data, would provide more relevant information on AD pathogenesis. Methods We performed a comprehensive analysis to identify blood DNAm associated with cerebrospinal fluid (CSF) pathological biomarkers for AD. Our study included matched samples of whole blood DNA methylation, CSF Aβ 42 , phosphorylated tau 181 (pTau 181 ), and total tau (tTau) biomarkers data, measured on the same subjects and at the same clinical visits from a total of 202 subjects (123 CN or cognitively normal, 79 AD) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. To validate our findings, we also examined the association between premortem blood DNAm and postmortem brain neuropathology measured on a group of 69 subjects in the London dataset. Results We identified a number of novel associations between blood DNAm and CSF biomarkers, demonstrating that changes in pathological processes in the CSF are reflected in the blood epigenome. Overall, the CSF biomarker-associated DNAm is relatively distinct in CN and AD subjects, highlighting the importance of analyzing omics data measured on cognitively normal subjects (which includes preclinical AD subjects) to identify diagnostic biomarkers, and considering disease stages in the development and testing of AD treatment strategies. Moreover, our analysis revealed biological processes associated with early brain impairment relevant to AD are marked by DNAm in the blood, and blood DNAm at several CpGs in the DMR on HOXA5 gene are associated with pTau 181 in the CSF, as well as tau-pathology and DNAm in the brain, nominating DNAm at this locus as a promising candidate AD biomarker. Conclusions Our study provides a valuable resource for future mechanistic and biomarker studies of DNAm in AD.
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Affiliation(s)
- Wei Zhang
- University of Miami, Miller School of Medicine
| | - Juan I Young
- Dr. John T Macdonald Foundation, University of Miami, Miller School of Medicine
| | | | - Michael A Schmidt
- Dr. John T Macdonald Foundation, University of Miami, Miller School of Medicine
| | | | | | | | - Eden R Martin
- Dr. John T Macdonald Foundation, University of Miami, Miller School of Medicine
| | - Lily Wang
- University of Miami, Miller School of Medicine
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24
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Nabais MF, Gadd DA, Hannon E, Mill J, McRae AF, Wray NR. An overview of DNA methylation-derived trait score methods and applications. Genome Biol 2023; 24:28. [PMID: 36797751 PMCID: PMC9936670 DOI: 10.1186/s13059-023-02855-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 01/17/2023] [Indexed: 02/18/2023] Open
Abstract
Microarray technology has been used to measure genome-wide DNA methylation in thousands of individuals. These studies typically test the associations between individual DNA methylation sites ("probes") and complex traits or diseases. The results can be used to generate methylation profile scores (MPS) to predict outcomes in independent data sets. Although there are many parallels between MPS and polygenic (risk) scores (PGS), there are key differences. Here, we review motivations, methods, and applications of DNA methylation-based trait prediction, with a focus on common diseases. We contrast MPS with PGS, highlighting where assumptions made in genetic modeling may not hold in epigenetic data.
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Affiliation(s)
- Marta F Nabais
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
- University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW, UK
| | - Danni A Gadd
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Eilis Hannon
- University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW, UK
| | - Jonathan Mill
- University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW, UK
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia.
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25
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Navarro L, Gómez-Carballa A, Pischedda S, Montoto-Louzao J, Viz-Lasheras S, Camino-Mera A, Hinault T, Martinón-Torres F, Salas A. Sensogenomics of music and Alzheimer's disease: An interdisciplinary view from neuroscience, transcriptomics, and epigenomics. Front Aging Neurosci 2023; 15:1063536. [PMID: 36819725 PMCID: PMC9935844 DOI: 10.3389/fnagi.2023.1063536] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 01/11/2023] [Indexed: 02/05/2023] Open
Abstract
Introduction The relationship between music and Alzheimer's disease (AD) has been approached by different disciplines, but most of our outstanding comes from neuroscience. Methods First, we systematically reviewed the state-of-the-art of neuroscience and cognitive sciences research on music and AD (>100 studies), and the progress made on the therapeutic impact of music stimuli in memory. Next, we meta-analyzed transcriptomic and epigenomic data of AD patients to search for commonalities with genes and pathways previously connected to music in genome association, epigenetic, and gene expression studies. Results Our findings indicate that >93% of the neuroscience/ cognitive sciences studies indicate at least one beneficial effect of music on patients with neurodegenerative diseases, being improvements on memory and cognition the most frequent outcomes; other common benefits were on social behavior, mood and emotion, anxiety and agitation, quality of life, and depression. Out of the 334 music-related genes, 127 (38%) were found to be linked to epigenome/transcriptome analysis in AD (vs. healthy controls); some of them (SNCA, SLC6A4, ASCC2, FTH1, PLAUR and ARHGAP26) have been reported to be associated e.g. with musical aptitude and music effect on the transcriptome. Other music-related genes (GMPR, SELENBP1 and ADIPOR1) associated to neuropsychiatric, neurodegenerative diseases and music performance, emerged as hub genes in consensus co-expression modules detected between AD and music estimulated transcriptomes. In addition, we found connections between music, AD and dopamine related genes, with SCNA being the most remarkable - a gene previously associated with learning and memory, and neurodegenerative disorders (e.g., Parkinson's disease and AD). Discussion The present study indicate that the vast majority of neuroscientific studies unambiguously show that music has a beneficial effect on health, being the most common benefits relevant to Alzheimer's disease. These findings illuminate a new roadmap for genetic research in neurosciences, and musical interventions in AD and other neurodegenerative conditions.
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Affiliation(s)
- Laura Navarro
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago, Universidade de Santiago de Compostela, Santiago de Compostela, Galicia, Spain,Unidade de Xenética, Instituto de Ciencias Forenses, Facultade de Medicina, Universidade de Santiago de Compostela, and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Santiago de Compostela, Galicia, Spain,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBER-ES), Madrid, Spain
| | - Alberto Gómez-Carballa
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago, Universidade de Santiago de Compostela, Santiago de Compostela, Galicia, Spain,Unidade de Xenética, Instituto de Ciencias Forenses, Facultade de Medicina, Universidade de Santiago de Compostela, and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Santiago de Compostela, Galicia, Spain,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBER-ES), Madrid, Spain
| | - Sara Pischedda
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago, Universidade de Santiago de Compostela, Santiago de Compostela, Galicia, Spain,Unidade de Xenética, Instituto de Ciencias Forenses, Facultade de Medicina, Universidade de Santiago de Compostela, and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Santiago de Compostela, Galicia, Spain,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBER-ES), Madrid, Spain
| | - Julián Montoto-Louzao
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago, Universidade de Santiago de Compostela, Santiago de Compostela, Galicia, Spain,Unidade de Xenética, Instituto de Ciencias Forenses, Facultade de Medicina, Universidade de Santiago de Compostela, and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Santiago de Compostela, Galicia, Spain,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBER-ES), Madrid, Spain
| | - Sandra Viz-Lasheras
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago, Universidade de Santiago de Compostela, Santiago de Compostela, Galicia, Spain,Unidade de Xenética, Instituto de Ciencias Forenses, Facultade de Medicina, Universidade de Santiago de Compostela, and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Santiago de Compostela, Galicia, Spain,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBER-ES), Madrid, Spain
| | - Alba Camino-Mera
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago, Universidade de Santiago de Compostela, Santiago de Compostela, Galicia, Spain,Unidade de Xenética, Instituto de Ciencias Forenses, Facultade de Medicina, Universidade de Santiago de Compostela, and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Santiago de Compostela, Galicia, Spain,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBER-ES), Madrid, Spain
| | - Thomas Hinault
- Normandie Université, UNICAEN, PSL Université Paris, EPHE, Inserm, U1077, CHU de Caen, Centre Cyceron, Neuropsychologie et Imagerie de la Mémoire Humaine, Caen, France
| | - Federico Martinón-Torres
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago, Universidade de Santiago de Compostela, Santiago de Compostela, Galicia, Spain,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBER-ES), Madrid, Spain,Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, Santiago de Compostela, Galicia, Spain
| | - Antonio Salas
- Genetics, Vaccines and Infections Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago, Universidade de Santiago de Compostela, Santiago de Compostela, Galicia, Spain,Unidade de Xenética, Instituto de Ciencias Forenses, Facultade de Medicina, Universidade de Santiago de Compostela, and GenPoB Research Group, Instituto de Investigación Sanitaria (IDIS), Hospital Clínico Universitario de Santiago (SERGAS), Santiago de Compostela, Galicia, Spain,Centro de Investigación Biomédica en Red de Enfermedades Respiratorias (CIBER-ES), Madrid, Spain,*Correspondence: Antonio Salas, ✉
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26
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Greeson KW, Crow KMS, Edenfield RC, Easley CA. Inheritance of paternal lifestyles and exposures through sperm DNA methylation. Nat Rev Urol 2023:10.1038/s41585-022-00708-9. [PMID: 36653672 DOI: 10.1038/s41585-022-00708-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/12/2022] [Indexed: 01/19/2023]
Abstract
Many different lifestyle factors and chemicals present in the environment are a threat to the reproductive tracts of humans. The potential for parental preconception exposure to alter gametes and for these alterations to be passed on to offspring and negatively affect embryo growth and development is of concern. The connection between maternal exposures and offspring health is a frequent focus in epidemiological studies, but paternal preconception exposures are much less frequently considered and are also very important determinants of offspring health. Several environmental and lifestyle factors in men have been found to alter sperm epigenetics, which can regulate gene expression during early embryonic development. Epigenetic information is thought to be a mechanism that evolved for organisms to pass on information about their lived experiences to offspring. DNA methylation is a well-studied epigenetic regulator that is sensitive to environmental exposures in somatic cells and sperm. The continuous production of sperm from spermatogonial stem cells throughout a man's adult life and the presence of spermatogonial stem cells outside of the blood-testis barrier makes them susceptible to environmental insults. Furthermore, altered sperm DNA methylation patterns can be maintained throughout development and ultimately result in impairments, which could predispose offspring to disease. Innovations in human stem cell-based spermatogenic models can be used to elucidate the paternal origins of health and disease.
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Affiliation(s)
- Katherine W Greeson
- Department of Environmental Health Science, College of Public Health, University of Georgia, Athens, GA, USA.,Regenerative Bioscience Center, University of Georgia, Athens, GA, USA
| | - Krista M S Crow
- Department of Environmental Health Science, College of Public Health, University of Georgia, Athens, GA, USA.,Regenerative Bioscience Center, University of Georgia, Athens, GA, USA
| | - R Clayton Edenfield
- Department of Environmental Health Science, College of Public Health, University of Georgia, Athens, GA, USA.,Regenerative Bioscience Center, University of Georgia, Athens, GA, USA
| | - Charles A Easley
- Department of Environmental Health Science, College of Public Health, University of Georgia, Athens, GA, USA. .,Regenerative Bioscience Center, University of Georgia, Athens, GA, USA.
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27
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Gunasekara CJ, MacKay H, Scott CA, Li S, Laritsky E, Baker MS, Grimm SL, Jun G, Li Y, Chen R, Wiemels JL, Coarfa C, Waterland RA. Systemic interindividual epigenetic variation in humans is associated with transposable elements and under strong genetic control. Genome Biol 2023; 24:2. [PMID: 36631879 PMCID: PMC9835319 DOI: 10.1186/s13059-022-02827-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Accepted: 12/01/2022] [Indexed: 01/13/2023] Open
Abstract
BACKGROUND Genetic variants can modulate phenotypic outcomes via epigenetic intermediates, for example at methylation quantitative trait loci (mQTL). We present the first large-scale assessment of mQTL at human genomic regions selected for interindividual variation in CpG methylation, which we call correlated regions of systemic interindividual variation (CoRSIVs). These can be assayed in blood DNA and do not reflect interindividual variation in cellular composition. RESULTS We use target-capture bisulfite sequencing to assess DNA methylation at 4086 CoRSIVs in multiple tissues from each of 188 donors in the NIH Gene-Tissue Expression (GTEx) program. At CoRSIVs, DNA methylation in peripheral blood correlates with methylation and gene expression in internal organs. We also discover unprecedented mQTL at these regions. Genetic influences on CoRSIV methylation are extremely strong (median R2=0.76), cumulatively comprising over 70-fold more human mQTL than detected in the most powerful previous study. Moreover, mQTL beta coefficients at CoRSIVs are highly skewed (i.e., the major allele predicts higher methylation). Both surprising findings are independently validated in a cohort of 47 non-GTEx individuals. Genomic regions flanking CoRSIVs show long-range enrichments for LINE-1 and LTR transposable elements; the skewed beta coefficients may therefore reflect evolutionary selection of genetic variants that promote their methylation and silencing. Analyses of GWAS summary statistics show that mQTL polymorphisms at CoRSIVs are associated with metabolic and other classes of disease. CONCLUSIONS A focus on systemic interindividual epigenetic variants, clearly enhanced in mQTL content, should likewise benefit studies attempting to link human epigenetic variation to the risk of disease.
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Affiliation(s)
- Chathura J. Gunasekara
- grid.508989.50000 0004 6410 7501USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX USA
| | - Harry MacKay
- grid.508989.50000 0004 6410 7501USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX USA
| | - C. Anthony Scott
- grid.508989.50000 0004 6410 7501USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX USA
| | - Shaobo Li
- grid.42505.360000 0001 2156 6853Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Eleonora Laritsky
- grid.508989.50000 0004 6410 7501USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX USA
| | - Maria S. Baker
- grid.508989.50000 0004 6410 7501USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX USA
| | - Sandra L. Grimm
- grid.39382.330000 0001 2160 926XDepartment of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX USA
| | - Goo Jun
- grid.267308.80000 0000 9206 2401Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX USA
| | - Yumei Li
- grid.39382.330000 0001 2160 926XDepartment of Molecular & Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - Rui Chen
- grid.39382.330000 0001 2160 926XDepartment of Molecular & Human Genetics, Baylor College of Medicine, Houston, TX USA
| | - Joseph L. Wiemels
- grid.42505.360000 0001 2156 6853Keck School of Medicine, University of Southern California, Los Angeles, CA USA
| | - Cristian Coarfa
- grid.39382.330000 0001 2160 926XDepartment of Molecular and Cellular Biology, Baylor College of Medicine, Houston, TX USA ,grid.39382.330000 0001 2160 926XDan L Duncan Comprehensive Cancer Center, Baylor College of Medicine, Houston, TX USA
| | - Robert A. Waterland
- grid.508989.50000 0004 6410 7501USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX USA ,grid.39382.330000 0001 2160 926XDepartment of Molecular & Human Genetics, Baylor College of Medicine, Houston, TX USA
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28
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Schäfer Hackenhaar F, Josefsson M, Nordin Adolfsson A, Landfors M, Kauppi K, Porter T, Milicic L, Laws SM, Hultdin M, Adolfsson R, Degerman S, Pudas S. Sixteen-Year Longitudinal Evaluation of Blood-Based DNA Methylation Biomarkers for Early Prediction of Alzheimer's Disease. J Alzheimers Dis 2023; 94:1443-1464. [PMID: 37393498 PMCID: PMC10473121 DOI: 10.3233/jad-230039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/30/2023] [Indexed: 07/03/2023]
Abstract
BACKGROUND DNA methylation (DNAm), an epigenetic mark reflecting both inherited and environmental influences, has shown promise for Alzheimer's disease (AD) prediction. OBJECTIVE Testing long-term predictive ability (>15 years) of existing DNAm-based epigenetic age acceleration (EAA) measures and identifying novel early blood-based DNAm AD-prediction biomarkers. METHODS EAA measures calculated from Illumina EPIC data from blood were tested with linear mixed-effects models (LMMs) in a longitudinal case-control sample (50 late-onset AD cases; 51 matched controls) with prospective data up to 16 years before clinical onset, and post-onset follow-up. Novel DNAm biomarkers were generated with epigenome-wide LMMs, and Sparse Partial Least Squares Discriminant Analysis applied at pre- (10-16 years), and post-AD-onset time-points. RESULTS EAA did not differentiate cases from controls during the follow-up time (p > 0.05). Three new DNA biomarkers showed in-sample predictive ability on average 8 years pre-onset, after adjustment for age, sex, and white blood cell proportions (p-values: 0.022-<0.00001). Our longitudinally-derived panel replicated nominally (p = 0.012) in an external cohort (n = 146 cases, 324 controls). However, its effect size and discriminatory accuracy were limited compared to APOEɛ4-carriership (OR = 1.38 per 1 SD DNAm score increase versus OR = 13.58 for ɛ4-allele carriage; AUCs = 77.2% versus 87.0%). Literature review showed low overlap (n = 4) across 3275 AD-associated CpGs from 8 published studies, and no overlap with our identified CpGs.
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Affiliation(s)
- Fernanda Schäfer Hackenhaar
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
| | - Maria Josefsson
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
- Department of Statistics, USBE, Umeå University, Umeå, Sweden
- Center for Ageing and Demographic Research, Umeå University, Umeå, Sweden
| | | | - Mattias Landfors
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
| | - Karolina Kauppi
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Tenielle Porter
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Curtin Medical School, Curtin University, Bentley, WA, Australia
| | - Lidija Milicic
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Simon M. Laws
- Centre for Precision Health, Edith Cowan University, Joondalup, WA, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Curtin Medical School, Curtin University, Bentley, WA, Australia
| | - Magnus Hultdin
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
| | - Rolf Adolfsson
- Department of Clinical Sciences, Umeå University, Umeå, Sweden
| | - Sofie Degerman
- Department of Medical Biosciences, Pathology, Umeå University, Umeå, Sweden
- Department of Clinical Microbiology, Umeå University, Umeå, Sweden
| | - Sara Pudas
- Department of Integrative Medical Biology, Umeå University, Umeå, Sweden
- Umeå Center for Functional Brain Imaging, Umeå University, Umeå, Sweden
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29
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Harvey J, Reijnders RA, Cavill R, Duits A, Köhler S, Eijssen L, Rutten BPF, Shireby G, Torkamani A, Creese B, Leentjens AFG, Lunnon K, Pishva E. Machine learning-based prediction of cognitive outcomes in de novo Parkinson's disease. NPJ Parkinsons Dis 2022; 8:150. [PMID: 36344548 PMCID: PMC9640625 DOI: 10.1038/s41531-022-00409-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 10/11/2022] [Indexed: 11/09/2022] Open
Abstract
Cognitive impairment is a debilitating symptom in Parkinson's disease (PD). We aimed to establish an accurate multivariate machine learning (ML) model to predict cognitive outcome in newly diagnosed PD cases from the Parkinson's Progression Markers Initiative (PPMI). Annual cognitive assessments over an 8-year time span were used to define two cognitive outcomes of (i) cognitive impairment, and (ii) dementia conversion. Selected baseline variables were organized into three subsets of clinical, biofluid and genetic/epigenetic measures and tested using four different ML algorithms. Irrespective of the ML algorithm used, the models consisting of the clinical variables performed best and showed better prediction of cognitive impairment outcome over dementia conversion. We observed a marginal improvement in the prediction performance when clinical, biofluid, and epigenetic/genetic variables were all included in one model. Several cerebrospinal fluid measures and an epigenetic marker showed high predictive weighting in multiple models when included alongside clinical variables.
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Affiliation(s)
- Joshua Harvey
- Medical School, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Rick A Reijnders
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands
| | - Rachel Cavill
- Department of Advanced Computing Sciences, FSE, Maastricht University, Maastricht, The Netherlands
| | - Annelien Duits
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands
- Department of Medical Psychology, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Sebastian Köhler
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands
| | - Lars Eijssen
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands
- Department of Bioinformatics-BiGCaT, School of Nutrition and Translational Research in Metabolism (NUTRIM), Maastricht University, Maastricht, The Netherlands
| | - Bart P F Rutten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands
| | - Gemma Shireby
- Medical School, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Ali Torkamani
- Department of Integrative Structural and Computational Biology, Scripps Research, La Jolla, CA, 92037, USA
| | - Byron Creese
- Medical School, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Albert F G Leentjens
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands
| | - Katie Lunnon
- Medical School, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK
| | - Ehsan Pishva
- Medical School, Faculty of Health and Life Sciences, University of Exeter, Exeter, UK.
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience (MHeNs), Maastricht University, Maastricht, The Netherlands.
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30
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Sommerer Y, Ohlei O, Dobricic V, Oakley DH, Wesse T, Sedghpour Sabet S, Demuth I, Franke A, Hyman BT, Lill CM, Bertram L. A correlation map of genome-wide DNA methylation patterns between paired human brain and buccal samples. Clin Epigenetics 2022; 14:139. [PMID: 36320053 PMCID: PMC9628033 DOI: 10.1186/s13148-022-01357-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Accepted: 10/17/2022] [Indexed: 11/06/2022] Open
Abstract
Epigenome-wide association studies (EWAS) assessing the link between DNA methylation (DNAm) and phenotypes related to structural brain measures, cognitive function, and neurodegenerative diseases are becoming increasingly more popular. Due to the inaccessibility of brain tissue in humans, several studies use peripheral tissues such as blood, buccal swabs, and saliva as surrogates. To aid the functional interpretation of EWAS findings in such settings, there is a need to assess the correlation of DNAm variability across tissues in the same individuals. In this study, we performed a correlation analysis between DNAm data of a total of n = 120 matched post-mortem buccal and prefrontal cortex samples. We identified nearly 25,000 (3% of approximately 730,000) cytosine-phosphate-guanine (CpG) sites showing significant (false discovery rate q < 0.05) correlations between buccal and PFC samples. Correlated CpG sites showed a preponderance to being located in promoter regions and showed a significant enrichment of being determined by genetic factors, i.e. methylation quantitative trait loci (mQTL), based on buccal and dorsolateral prefrontal cortex mQTL databases. Our novel buccal-brain DNAm correlation map will provide a valuable resource for future EWAS using buccal samples for studying DNAm effects on phenotypes relating to the brain. All correlation results are made freely available to the public online.
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Affiliation(s)
- Yasmine Sommerer
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany
| | - Olena Ohlei
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany
| | - Derek H Oakley
- Department of Pathology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
| | - Tanja Wesse
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Sanaz Sedghpour Sabet
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Ilja Demuth
- Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität zu Berlin, Berlin, Germany
- Division of Lipid Metabolism, Department of Endocrinology and Metabolic Diseases, Berlin Institute of Health, Berlin, Germany
- BCRT - Berlin Institute of Health Center for Regenerative Therapies, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Andre Franke
- Institute of Clinical Molecular Biology, Christian-Albrechts-University of Kiel, Kiel, Germany
| | - Bradley T Hyman
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Charlestown, MA, USA
- Massachusetts Alzheimer's Disease Research Center, Charlestown, MA, USA
- Harvard Medical School, Boston, MA, USA
| | - Christina M Lill
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany
- Ageing Epidemiology Unit (AGE), School of Public Health, Imperial College London, London, UK
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, Haus V50, 1St Floor, Room 319, 23562, Lübeck, Germany.
- Department of Psychology, Center for Lifespan Changes in Brain and Cognition (LCBC), University of Oslo, Oslo, Norway.
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Kalyakulina A, Yusipov I, Bacalini MG, Franceschi C, Vedunova M, Ivanchenko M. Disease classification for whole-blood DNA methylation: Meta-analysis, missing values imputation, and XAI. Gigascience 2022; 11:giac097. [PMID: 36259657 PMCID: PMC9718659 DOI: 10.1093/gigascience/giac097] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 08/01/2022] [Accepted: 09/15/2022] [Indexed: 07/25/2023] Open
Abstract
BACKGROUND DNA methylation has a significant effect on gene expression and can be associated with various diseases. Meta-analysis of available DNA methylation datasets requires development of a specific workflow for joint data processing. RESULTS We propose a comprehensive approach of combined DNA methylation datasets to classify controls and patients. The solution includes data harmonization, construction of machine learning classification models, dimensionality reduction of models, imputation of missing values, and explanation of model predictions by explainable artificial intelligence (XAI) algorithms. We show that harmonization can improve classification accuracy by up to 20% when preprocessing methods of the training and test datasets are different. The best accuracy results were obtained with tree ensembles, reaching above 95% for Parkinson's disease. Dimensionality reduction can substantially decrease the number of features, without detriment to the classification accuracy. The best imputation methods achieve almost the same classification accuracy for data with missing values as for the original data. XAI approaches have allowed us to explain model predictions from both populational and individual perspectives. CONCLUSIONS We propose a methodologically valid and comprehensive approach to the classification of healthy individuals and patients with various diseases based on whole-blood DNA methylation data using Parkinson's disease and schizophrenia as examples. The proposed algorithm works better for the former pathology, characterized by a complex set of symptoms. It allows to solve data harmonization problems for meta-analysis of many different datasets, impute missing values, and build classification models of small dimensionality.
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Affiliation(s)
- Alena Kalyakulina
- Correspondence author. Alena Kalyakulina, Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, Gagarin avenue 22, Nizhny Novgorod 603022, Russia. E-mail:
| | | | | | - Claudio Franceschi
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, 603022 Nizhny Novgorod, Russia
| | - Maria Vedunova
- Institute of Biology and Biomedicine, Lobachevsky State University, 603022 Nizhny Novgorod, Russia
| | - Mikhail Ivanchenko
- Institute of Information Technologies, Mathematics and Mechanics, Lobachevsky State University, 603022 Nizhny Novgorod, Russia
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C. Silva T, Zhang W, Young JI, Gomez L, Schmidt MA, Varma A, Chen XS, Martin ER, Wang L. Distinct sex-specific DNA methylation differences in Alzheimer's disease. Alzheimers Res Ther 2022; 14:133. [PMID: 36109771 PMCID: PMC9479371 DOI: 10.1186/s13195-022-01070-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Accepted: 08/30/2022] [Indexed: 01/17/2023]
Abstract
BACKGROUND Sex is increasingly recognized as a significant factor contributing to the biological and clinical heterogeneity in AD. There is also growing evidence for the prominent role of DNA methylation (DNAm) in Alzheimer's disease (AD). METHODS We studied sex-specific DNA methylation differences in the blood samples of AD subjects compared to cognitively normal subjects, by performing sex-specific meta-analyses of two large blood-based epigenome-wide association studies (ADNI and AIBL), which included DNA methylation data for a total of 1284 whole blood samples (632 females and 652 males). Within each dataset, we used two complementary analytical strategies, a sex-stratified analysis that examined methylation to AD associations in male and female samples separately, and a methylation-by-sex interaction analysis that compared the magnitude of these associations between different sexes. After adjusting for age, estimated immune cell type proportions, batch effects, and correcting for inflation, the inverse-variance fixed-effects meta-analysis model was used to identify the most consistent DNAm differences across datasets. In addition, we also evaluated the performance of the sex-specific methylation-based risk prediction models for AD diagnosis using an independent external dataset. RESULTS In the sex-stratified analysis, we identified 2 CpGs, mapped to the PRRC2A and RPS8 genes, significantly associated with AD in females at a 5% false discovery rate, and an additional 25 significant CpGs (21 in females, 4 in males) at P-value < 1×10-5. In methylation-by-sex interaction analysis, we identified 5 significant CpGs at P-value < 10-5. Out-of-sample validations using the AddNeuroMed dataset showed in females, the best logistic prediction model included age, estimated immune cell-type proportions, and methylation risk scores (MRS) computed from 9 of the 23 CpGs identified in AD vs. CN analysis that are also available in AddNeuroMed dataset (AUC = 0.74, 95% CI: 0.65-0.83). In males, the best logistic prediction model included only age and MRS computed from 2 of the 5 CpGs identified in methylation-by-sex interaction analysis that are also available in the AddNeuroMed dataset (AUC = 0.70, 95% CI: 0.56-0.82). CONCLUSIONS Overall, our results show that the DNA methylation differences in AD are largely distinct between males and females. Our best-performing sex-specific methylation-based prediction model in females performed better than that for males and additionally included estimated cell-type proportions. The significant discriminatory classification of AD samples with our methylation-based prediction models demonstrates that sex-specific DNA methylation could be a predictive biomarker for AD. As sex is a strong factor underlying phenotypic variability in AD, the results of our study are particularly relevant for a better understanding of the epigenetic architecture that underlie AD and for promoting precision medicine in AD.
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Affiliation(s)
- Tiago C. Silva
- grid.26790.3a0000 0004 1936 8606Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136 USA
| | - Wei Zhang
- grid.26790.3a0000 0004 1936 8606Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136 USA
| | - Juan I. Young
- grid.26790.3a0000 0004 1936 8606Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Lissette Gomez
- grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Michael A. Schmidt
- grid.26790.3a0000 0004 1936 8606Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Achintya Varma
- grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - X. Steven Chen
- grid.26790.3a0000 0004 1936 8606Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136 USA
| | - Eden R. Martin
- grid.26790.3a0000 0004 1936 8606Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Lily Wang
- grid.26790.3a0000 0004 1936 8606Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, 1120 NW 14th Street, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136 USA
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Pihlstrøm L, Shireby G, Geut H, Henriksen SP, Rozemuller AJM, Tunold JA, Hannon E, Francis P, Thomas AJ, Love S, Mill J, van de Berg WDJ, Toft M. Epigenome-wide association study of human frontal cortex identifies differential methylation in Lewy body pathology. Nat Commun 2022; 13:4932. [PMID: 35995800 PMCID: PMC9395387 DOI: 10.1038/s41467-022-32619-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2021] [Accepted: 08/09/2022] [Indexed: 11/09/2022] Open
Abstract
Parkinson's disease (PD) and dementia with Lewy bodies (DLB) are closely related progressive disorders with no available disease-modifying therapy, neuropathologically characterized by intraneuronal aggregates of misfolded α-synuclein. To explore the role of DNA methylation changes in PD and DLB pathogenesis, we performed an epigenome-wide association study (EWAS) of 322 postmortem frontal cortex samples and replicated results in an independent set of 200 donors. We report novel differentially methylated replicating loci associated with Braak Lewy body stage near TMCC2, SFMBT2, AKAP6 and PHYHIP. Differentially methylated probes were independent of known PD genetic risk alleles. Meta-analysis provided suggestive evidence for a differentially methylated locus within the chromosomal region affected by the PD-associated 22q11.2 deletion. Our findings elucidate novel disease pathways in PD and DLB and generate hypotheses for future molecular studies of Lewy body pathology.
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Affiliation(s)
- Lasse Pihlstrøm
- Department of Neurology, Oslo University Hospital, Oslo, Norway.
| | - Gemma Shireby
- University of Exeter Medical School, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Hanneke Geut
- Amsterdam UMC, Vrije Universiteit, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Netherlands Brain Bank, Netherlands Institute of Neurosciences, Amsterdam, The Netherlands
| | | | - Annemieke J M Rozemuller
- Amsterdam UMC, Vrije Universiteit, Department of Pathology, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Jon-Anders Tunold
- Department of Neurology, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Eilis Hannon
- University of Exeter Medical School, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Paul Francis
- University of Exeter Medical School, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Alan J Thomas
- Translational and Clinical Research Institute, Newcastle University, Newcastle Upon Tyne, UK
| | - Seth Love
- Dementia Research Group, Bristol Medical School, University of Bristol, Bristol, UK
| | - Jonathan Mill
- University of Exeter Medical School, College of Medicine and Health, University of Exeter, Exeter, UK
| | - Wilma D J van de Berg
- Amsterdam UMC, Vrije Universiteit, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Mathias Toft
- Department of Neurology, Oslo University Hospital, Oslo, Norway
- Institute of Clinical Medicine, University of Oslo, Oslo, Norway
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Schaffner SL, Kobor MS. DNA methylation as a mediator of genetic and environmental influences on Parkinson's disease susceptibility: Impacts of alpha-Synuclein, physical activity, and pesticide exposure on the epigenome. Front Genet 2022; 13:971298. [PMID: 36061205 PMCID: PMC9437223 DOI: 10.3389/fgene.2022.971298] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 07/25/2022] [Indexed: 12/15/2022] Open
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder with a complex etiology and increasing prevalence worldwide. As PD is influenced by a combination of genetic and environment/lifestyle factors in approximately 90% of cases, there is increasing interest in identification of the interindividual mechanisms underlying the development of PD as well as actionable lifestyle factors that can influence risk. This narrative review presents an outline of the genetic and environmental factors contributing to PD risk and explores the possible roles of cytosine methylation and hydroxymethylation in the etiology and/or as early-stage biomarkers of PD, with an emphasis on epigenome-wide association studies (EWAS) of PD conducted over the past decade. Specifically, we focused on variants in the SNCA gene, exposure to pesticides, and physical activity as key contributors to PD risk. Current research indicates that these factors individually impact the epigenome, particularly at the level of CpG methylation. There is also emerging evidence for interaction effects between genetic and environmental contributions to PD risk, possibly acting across multiple omics layers. We speculated that this may be one reason for the poor replicability of the results of EWAS for PD reported to date. Our goal is to provide direction for future epigenetics studies of PD to build upon existing foundations and leverage large datasets, new technologies, and relevant statistical approaches to further elucidate the etiology of this disease.
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Affiliation(s)
- Samantha L. Schaffner
- Edwin S. H. Leong Healthy Aging Program, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Medical Genetics, British Columbia Children’s Hospital Research Institute, University of British Columbia, Vancouver, BC, Canada
| | - Michael S. Kobor
- Edwin S. H. Leong Healthy Aging Program, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
- Department of Medical Genetics, British Columbia Children’s Hospital Research Institute, University of British Columbia, Vancouver, BC, Canada
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35
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C. Silva T, Young JI, Zhang L, Gomez L, Schmidt MA, Varma A, Chen XS, Martin ER, Wang L. Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer's disease. Nat Commun 2022; 13:4852. [PMID: 35982059 PMCID: PMC9388493 DOI: 10.1038/s41467-022-32475-x] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2021] [Accepted: 08/01/2022] [Indexed: 01/17/2023] Open
Abstract
To better understand DNA methylation in Alzheimer's disease (AD) from both mechanistic and biomarker perspectives, we performed an epigenome-wide meta-analysis of blood DNA methylation in two large independent blood-based studies in AD, the ADNI and AIBL studies, and identified 5 CpGs, mapped to the SPIDR, CDH6 genes, and intergenic regions, that are significantly associated with AD diagnosis. A cross-tissue analysis that combined these blood DNA methylation datasets with four brain methylation datasets prioritized 97 CpGs and 10 genomic regions that are significantly associated with both AD neuropathology and AD diagnosis. An out-of-sample validation using the AddNeuroMed dataset showed the best performing logistic regression model includes age, sex, immune cell type proportions, and methylation risk score based on prioritized CpGs in cross-tissue analysis (AUC = 0.696, 95% CI: 0.616 - 0.770, P-value = 2.78 × 10-5). Our study offers new insights into epigenetics in AD and provides a valuable resource for future AD biomarker discovery.
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Affiliation(s)
- Tiago C. Silva
- grid.26790.3a0000 0004 1936 8606Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136 USA
| | - Juan I. Young
- grid.26790.3a0000 0004 1936 8606Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Lanyu Zhang
- grid.26790.3a0000 0004 1936 8606Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136 USA
| | - Lissette Gomez
- grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Michael A. Schmidt
- grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Achintya Varma
- grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - X. Steven Chen
- grid.26790.3a0000 0004 1936 8606Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136 USA
| | - Eden R. Martin
- grid.26790.3a0000 0004 1936 8606Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA
| | - Lily Wang
- grid.26790.3a0000 0004 1936 8606Division of Biostatistics, Department of Public Health Sciences, University of Miami, Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami, Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL 33136 USA ,grid.26790.3a0000 0004 1936 8606Sylvester Comprehensive Cancer Center, University of Miami, Miller School of Medicine, Miami, FL 33136 USA
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36
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Identification of COVID-19-Associated DNA Methylation Variations by Integrating Methylation Array and scRNA-Seq Data at Cell-Type Resolution. Genes (Basel) 2022; 13:genes13071109. [DOI: 10.3390/genes13071109] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Revised: 06/16/2022] [Accepted: 06/17/2022] [Indexed: 01/27/2023] Open
Abstract
Single-cell transcriptome studies have revealed immune dysfunction in COVID-19 patients, including lymphopenia, T cell exhaustion, and increased levels of pro-inflammatory cytokines, while DNA methylation plays an important role in the regulation of immune response and inflammatory response. The specific cell types of immune responses regulated by DNA methylation in COVID-19 patients will be better understood by exploring the COVID-19 DNA methylation variation at the cell-type level. Here, we developed an analytical pipeline to explore single-cell DNA methylation variations in COVID-19 patients by transferring bulk-tissue-level knowledge to the single-cell level. We discovered that the methylation variations in the whole blood of COVID-19 patients showed significant cell-type specificity with remarkable enrichment in gamma-delta T cells and presented a phenomenon of hypermethylation and low expression. Furthermore, we identified five genes whose methylation variations were associated with several cell types. Among them, S100A9, AHNAK, and CX3CR1 have been reported as potential COVID-19 biomarkers previously, and the others (TRAF3IP3 and LFNG) are closely associated with the immune and virus-related signaling pathways. We propose that they might serve as potential epigenetic biomarkers for COVID-19 and could play roles in important biological processes such as the immune response and antiviral activity.
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Milicic L, Vacher M, Porter T, Doré V, Burnham SC, Bourgeat P, Shishegar R, Doecke J, Armstrong NJ, Tankard R, Maruff P, Masters CL, Rowe CC, Villemagne VL, Laws SM. Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume. GeroScience 2022; 44:1807-1823. [PMID: 35445885 PMCID: PMC9213584 DOI: 10.1007/s11357-022-00558-8] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 03/30/2022] [Indexed: 12/21/2022] Open
Abstract
The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer's Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer's disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes.
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Affiliation(s)
- Lidija Milicic
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia
| | - Michael Vacher
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia
- CSIRO Health and Biosecurity, Australian E-Health Research Centre, Floreat, Western Australia, 6014, Australia
| | - Tenielle Porter
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia
- School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, 6102, Australia
| | - Vincent Doré
- Australian E-Health Research Centre, CSIRO, Parkville, Victoria, 3052, Australia
- Department of Molecular Imaging and Therapy and Centre for PET, Austin Health, Heidelberg, Victoria, Australia
| | - Samantha C Burnham
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Australian E-Health Research Centre, CSIRO, Parkville, Victoria, 3052, Australia
| | - Pierrick Bourgeat
- Australian E-Health Research Centre, CSIRO, Herston, Queensland, 4029, Australia
| | - Rosita Shishegar
- Australian E-Health Research Centre, CSIRO, Parkville, Victoria, 3052, Australia
- School of Psychological Sciences and Turner Institute for Brain and Mental Health, Monash University, Melbourne, VIC, Australia
| | - James Doecke
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Australian E-Health Research Centre, CSIRO, Herston, Queensland, 4029, Australia
| | - Nicola J Armstrong
- Department of Mathematics and Statistics, Curtin University, Bentley, Western Australia, Australia
| | - Rick Tankard
- School of Mathematics and Statistics, Murdoch University, Perth, Western Australia, Australia
| | - Paul Maruff
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3052, Australia
- Cogstate Ltd, Melbourne, VIC, Australia
| | - Colin L Masters
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3052, Australia
| | - Christopher C Rowe
- Department of Molecular Imaging and Therapy and Centre for PET, Austin Health, Heidelberg, Victoria, Australia
- Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, VIC, 3052, Australia
| | - Victor L Villemagne
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
- Department of Molecular Imaging and Therapy and Centre for PET, Austin Health, Heidelberg, Victoria, Australia
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Simon M Laws
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia.
- Collaborative Genomics and Translation Group, School of Medical and Health Sciences, Edith Cowan University, Joondalup, Western Australia, 6027, Australia.
- School of Pharmacy and Biomedical Sciences, Faculty of Health Sciences, Curtin Health Innovation Research Institute, Curtin University, Bentley, Western Australia, 6102, Australia.
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Hop PJ, Zwamborn RA, Hannon E, Shireby GL, Nabais MF, Walker EM, van Rheenen W, van Vugt JJ, Dekker AM, Westeneng HJ, Tazelaar GH, van Eijk KR, Moisse M, Baird D, Khleifat AA, Iacoangeli A, Ticozzi N, Ratti A, Cooper-Knock J, Morrison KE, Shaw PJ, Basak AN, Chiò A, Calvo A, Moglia C, Canosa A, Brunetti M, Grassano M, Gotkine M, Lerner Y, Zabari M, Vourc’h P, Corcia P, Couratier P, Pardina JSM, Salas T, Dion P, Ross JP, Henderson RD, Mathers S, McCombe PA, Needham M, Nicholson G, Rowe DB, Pamphlett R, Mather KA, Sachdev PS, Furlong S, Garton FC, Henders AK, Lin T, Ngo ST, Steyn FJ, Wallace L, Williams KL, Neto MM, Cauchi RJ, Blair IP, Kiernan MC, Drory V, Povedano M, de Carvalho M, Pinto S, Weber M, Rouleau GA, Silani V, Landers JE, Shaw CE, Andersen PM, McRae AF, van Es MA, Pasterkamp RJ, Wray NR, McLaughlin RL, Hardiman O, Kenna KP, Tsai E, Runz H, Al-Chalabi A, van den Berg LH, Van Damme P, Mill J, Veldink JH. Genome-wide study of DNA methylation shows alterations in metabolic, inflammatory, and cholesterol pathways in ALS. Sci Transl Med 2022; 14:eabj0264. [PMID: 35196023 PMCID: PMC10040186 DOI: 10.1126/scitranslmed.abj0264] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with an estimated heritability between 40 and 50%. DNA methylation patterns can serve as proxies of (past) exposures and disease progression, as well as providing a potential mechanism that mediates genetic or environmental risk. Here, we present a blood-based epigenome-wide association study meta-analysis in 9706 samples passing stringent quality control (6763 patients, 2943 controls). We identified a total of 45 differentially methylated positions (DMPs) annotated to 42 genes, which are enriched for pathways and traits related to metabolism, cholesterol biosynthesis, and immunity. We then tested 39 DNA methylation-based proxies of putative ALS risk factors and found that high-density lipoprotein cholesterol, body mass index, white blood cell proportions, and alcohol intake were independently associated with ALS. Integration of these results with our latest genome-wide association study showed that cholesterol biosynthesis was potentially causally related to ALS. Last, DNA methylation at several DMPs and blood cell proportion estimates derived from DNA methylation data were associated with survival rate in patients, suggesting that they might represent indicators of underlying disease processes potentially amenable to therapeutic interventions.
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Affiliation(s)
- Paul J. Hop
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands
| | - Ramona A.J. Zwamborn
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands
| | - Eilis Hannon
- University of Exeter Medical School, College of Medicine and Health, University of Exeter, Exeter EX1 2LU, UK
| | - Gemma L. Shireby
- University of Exeter Medical School, College of Medicine and Health, University of Exeter, Exeter EX1 2LU, UK
| | - Marta F. Nabais
- University of Exeter Medical School, College of Medicine and Health, University of Exeter, Exeter EX1 2LU, UK
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD4072, Australia
| | - Emma M. Walker
- University of Exeter Medical School, College of Medicine and Health, University of Exeter, Exeter EX1 2LU, UK
| | - Wouter van Rheenen
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands
| | - Joke J.F.A. van Vugt
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands
| | - Annelot M. Dekker
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands
| | - Henk-Jan Westeneng
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands
| | - Gijs H.P. Tazelaar
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands
| | - Kristel R. van Eijk
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands
| | - Matthieu Moisse
- KU Leuven–University of Leuven, Department of Neurosciences, Experimental Neurology and Leuven Brain Institute (LBI), Leuven 3000, Belgium
- VIB, Center for Brain and Disease Research, Leuven 3000, Belgium
- University Hospitals Leuven, Department of Neurology, Leuven 3000, Belgium
| | - Denis Baird
- Translational Biology, Biogen, Boston, MA 02142, USA
- MRC Integrative Epidemiology Unit (IEU), Population Health Sciences, University of Bristol, Bristol BS8 2BN, UK
| | - Ahmad Al Khleifat
- Maurice Wohl Clinical Neuroscience Institute, Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Alfredo Iacoangeli
- Maurice Wohl Clinical Neuroscience Institute, Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
- National Institute for Health Research Biomedical Research Centre and Dementia Unit, South London and Maudsley NHS Foundation Trust and King’s College London, London SE5 8AZ, UK
| | - Nicola Ticozzi
- Department of Neurology-Stroke Unit and Laboratory of Neuroscience, Istituto Auxologico Italiano IRCCS, Milan 20149, Italy
- Department of Pathophysiology and Transplantation, “Dino Ferrari” Center, Università degli Studi di Milano, Milan 20122, Italy
| | - Antonia Ratti
- Department of Neurology-Stroke Unit and Laboratory of Neuroscience, Istituto Auxologico Italiano IRCCS, Milan 20149, Italy
- Department of Medical Biotechnology and Translational Medicine, Università degli Studi di Milano, Milano 20145, Italy
| | - Jonathan Cooper-Knock
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield S10 2HQ, UK
| | - Karen E. Morrison
- School of Medicine, Dentistry, and Biomedical Sciences, Queen’s University Belfast, Belfast BT9 7BL, UK
| | - Pamela J. Shaw
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield S10 2HQ, UK
| | - A. Nazli Basak
- Koc University, School of Medicine, Translational Medicine Research Center, NDAL, Istanbul, 34450, Turkey
| | - Adriano Chiò
- “Rita Levi Montalcini” Department of Neuroscience, ALS Centre, University of Torino, Turin 10126, Italy
- Azienda Ospedaliero-Universitaria Città della Salute e della Scienza, SC Neurologia 1U, Turin 10126, Italy
| | - Andrea Calvo
- “Rita Levi Montalcini” Department of Neuroscience, ALS Centre, University of Torino, Turin 10126, Italy
- Azienda Ospedaliero-Universitaria Città della Salute e della Scienza, SC Neurologia 1U, Turin 10126, Italy
| | - Cristina Moglia
- “Rita Levi Montalcini” Department of Neuroscience, ALS Centre, University of Torino, Turin 10126, Italy
- Azienda Ospedaliero-Universitaria Città della Salute e della Scienza, SC Neurologia 1U, Turin 10126, Italy
| | - Antonio Canosa
- “Rita Levi Montalcini” Department of Neuroscience, ALS Centre, University of Torino, Turin 10126, Italy
- Azienda Ospedaliero-Universitaria Città della Salute e della Scienza, SC Neurologia 1U, Turin 10126, Italy
| | - Maura Brunetti
- “Rita Levi Montalcini” Department of Neuroscience, ALS Centre, University of Torino, Turin 10126, Italy
| | - Maurizio Grassano
- “Rita Levi Montalcini” Department of Neuroscience, ALS Centre, University of Torino, Turin 10126, Italy
| | - Marc Gotkine
- Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91904, Israel
- Agnes Ginges Center for Human Neurogenetics, Department of Neurology, Hadassah Medical Center, Jerusalem 91120, Israel
| | - Yossef Lerner
- Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91904, Israel
- Agnes Ginges Center for Human Neurogenetics, Department of Neurology, Hadassah Medical Center, Jerusalem 91120, Israel
| | - Michal Zabari
- Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem 91904, Israel
- Agnes Ginges Center for Human Neurogenetics, Department of Neurology, Hadassah Medical Center, Jerusalem 91120, Israel
| | - Patrick Vourc’h
- Service de Biochimie et Biologie moléculaire, CHU de Tours, Tours 37044, France
- UMR 1253, Université de Tours, Inserm, Tours 37044, France
| | - Philippe Corcia
- UMR 1253, Université de Tours, Inserm, Tours 37044, France
- Centre de référence sur la SLA, CHU de Tours, Tours 37044, France
| | - Philippe Couratier
- Centre de référence sur la SLA, CHRU de Limoges, Limoges 87042, France
- UMR 1094, Université de Limoges, Inserm, Limoges 87025, France
| | | | - Teresa Salas
- Department of Neurology, Hospital La Paz-Carlos III, Madrid 28046, Spain
| | - Patrick Dion
- Montréal Neurological Institute and Hospital, McGill University, Montréal, QC H3A 2B4, Canada
| | - Jay P. Ross
- Montréal Neurological Institute and Hospital, McGill University, Montréal, QC H3A 2B4, Canada
- Department of Human Genetics, McGill University, Montréal, QC H3A 0C7, Canada
| | - Robert D. Henderson
- Department of Neurology, Royal Brisbane and Women’s Hospital, Brisbane, QLD 4029, Australia
| | - Susan Mathers
- Calvary Health Care Bethlehem, Parkdale, VIC 3195, Australia
| | - Pamela A. McCombe
- Centre for Clinical Research, University of Queensland, Brisbane, QLD 4019, Australia
| | - Merrilee Needham
- Fiona Stanley Hospital, Perth, WA 6150, Australia
- Notre Dame University, Fremantle, WA 6160, Australia
- Institute for Immunology and Infectious Diseases, Murdoch University, Perth, WA 6150, Australia
| | - Garth Nicholson
- ANZAC Research Institute, Concord Repatriation General Hospital, Sydney, NSW 2139, Australia
| | - Dominic B. Rowe
- Centre for Motor Neuron Disease Research, Macquarie University, NSW 2109, Australia
| | - Roger Pamphlett
- Discipline of Pathology and Department of Neuropathology, Brain and Mind Centre, University of Sydney, Sydney, NSW 2050, Australia
| | - Karen A. Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW 2031, Australia
- Neuroscience Research Australia Institute, Randwick, NSW 2031, Australia
| | - Perminder S. Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW 2031, Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, UNSW, Randwick, NSW 2031, Australia
| | - Sarah Furlong
- Centre for Motor Neuron Disease Research, Macquarie University, NSW 2109, Australia
| | - Fleur C. Garton
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD4072, Australia
| | - Anjali K. Henders
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD4072, Australia
| | - Tian Lin
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD4072, Australia
| | - Shyuan T. Ngo
- Centre for Clinical Research, University of Queensland, Brisbane, QLD 4019, Australia
- Australian Institute for Bioengineering and Nanotechnology, University of Queensland, Brisbane, QLD 4072, Australia
- Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072, Australia
| | - Frederik J. Steyn
- Centre for Clinical Research, University of Queensland, Brisbane, QLD 4019, Australia
- School of Biomedical Sciences, University of Queensland, Brisbane, QLD 4072, Australia
| | - Leanne Wallace
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD4072, Australia
| | - Kelly L. Williams
- Centre for Motor Neuron Disease Research, Macquarie University, NSW 2109, Australia
| | | | | | | | - Ruben J. Cauchi
- Center for Molecular Medicine and Biobanking and Department of Physiology and Biochemistry, Faculty of Medicine and Surgery, University of Malta, 2023 Msida, Malta
| | - Ian P. Blair
- Centre for Motor Neuron Disease Research, Macquarie University, NSW 2109, Australia
| | - Matthew C. Kiernan
- Brain and Mind Centre, University of Sydney, Sydney, NSW, 2050, Australia
- Department of Neurology, Royal Prince Alfred Hospital, Sydney, NSW 2050, Australia
| | - Vivian Drory
- Department of Neurology, Tel-Aviv Sourasky Medical Centre, Tel-Aviv 64239, Israel
- Sackler Faculty of Medicine, Tel-Aviv University, Tel-Aviv 6997801, Israel
| | - Monica Povedano
- Functional Unit of Amyotrophic Lateral Sclerosis (UFELA), Service of Neurology, Bellvitge University Hospital, L’Hospitalet de Llobregat, Barcelona 08907, Spain
| | - Mamede de Carvalho
- Instituto de Fisiologia, Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon 1649-028, Portugal
| | - Susana Pinto
- Instituto de Fisiologia, Instituto de Medicina Molecular João Lobo Antunes, Faculdade de Medicina, Universidade de Lisboa, Lisbon 1649-028, Portugal
| | - Markus Weber
- Neuromuscular Diseases Unit/ALS Clinic, Kantonsspital St. Gallen, 9007 St. Gallen, Switzerland
| | - Guy A. Rouleau
- Montréal Neurological Institute and Hospital, McGill University, Montréal, QC H3A 2B4, Canada
| | - Vincenzo Silani
- Department of Neurology-Stroke Unit and Laboratory of Neuroscience, Istituto Auxologico Italiano IRCCS, Milan 20149, Italy
- Department of Pathophysiology and Transplantation, “Dino Ferrari” Center, Università degli Studi di Milano, Milan 20122, Italy
| | - John E. Landers
- Department of Neurology, University of Massachusetts Medical School, Worcester, MA 01655, USA
| | - Christopher E. Shaw
- Maurice Wohl Clinical Neuroscience Institute, Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
| | - Peter M. Andersen
- Department of Clinical Science, Umeå University, Umeå SE-901 85, Sweden
| | - Allan F. McRae
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD4072, Australia
| | - Michael A. van Es
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands
| | - R. Jeroen Pasterkamp
- Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, 3584 CX, Netherlands
| | - Naomi R. Wray
- Institute for Molecular Bioscience, University of Queensland, Brisbane, QLD4072, Australia
- Queensland Brain Institute, University of Queensland, Brisbane, QLD 4072, Australia
| | - Russell L. McLaughlin
- Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Dublin D02 PN40, Ireland
| | - Orla Hardiman
- Academic Unit of Neurology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin D02 PN40, Ireland
| | - Kevin P. Kenna
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands
- Department of Translational Neuroscience, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht, 3584 CX, Netherlands
| | - Ellen Tsai
- Translational Biology, Biogen, Boston, MA 02142, USA
| | - Heiko Runz
- Translational Biology, Biogen, Boston, MA 02142, USA
| | - Ammar Al-Chalabi
- Maurice Wohl Clinical Neuroscience Institute, Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London SE5 8AF, UK
- King’s College Hospital, Denmark Hill, London SE5 9RS, UK
| | - Leonard H. van den Berg
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands
| | - Philip Van Damme
- KU Leuven–University of Leuven, Department of Neurosciences, Experimental Neurology and Leuven Brain Institute (LBI), Leuven 3000, Belgium
- VIB, Center for Brain and Disease Research, Leuven 3000, Belgium
- University Hospitals Leuven, Department of Neurology, Leuven 3000, Belgium
| | - Jonathan Mill
- University of Exeter Medical School, College of Medicine and Health, University of Exeter, Exeter EX1 2LU, UK
| | - Jan H. Veldink
- Department of Neurology, UMC Utrecht Brain Center, University Medical Center Utrecht, Utrecht 3584 CX, Netherlands
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Nowicka N, Szymańska K, Juranek J, Zglejc-Waszak K, Korytko A, Załęcki M, Chmielewska-Krzesińska M, Wąsowicz K, Wojtkiewicz J. The Involvement of RAGE and Its Ligands during Progression of ALS in SOD1 G93A Transgenic Mice. Int J Mol Sci 2022; 23:ijms23042184. [PMID: 35216298 PMCID: PMC8880540 DOI: 10.3390/ijms23042184] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 02/10/2022] [Accepted: 02/12/2022] [Indexed: 02/05/2023] Open
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease characterized by a progressive degeneration of upper and lower motor neurons that causes paralysis and muscle atrophy. The pathogenesis of the disease is still not elucidated. Receptor for Advanced Glycation End Product (RAGE) is a major component of the innate immune system and has implications in ALS pathogenesis. Multiple studies suggest the role of RAGE and its ligands in ALS. RAGE and its ligands are overexpressed in human and murine ALS motor neurons, astrocytes, and microglia. Here, we demonstrated the expression of RAGE and its ligands during the progression of the disease in the transgenic SOD1 G93A mouse lumbar spinal cord. We observed the highest expression of HMGB1 and S100b proteins at ALS onset. Our results highlight the potential role of RAGE and its ligands in ALS pathogenesis and suggest that some of the RAGE ligands might be used as biomarkers in early ALS diagnosis and potentially be useful in targeted therapeutic interventions at the early stage of this devastating disease.
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Affiliation(s)
- Natalia Nowicka
- Department of Human Physiology and Pathophysiology, School of Medicine, University of Warmia and Mazury, 10-082 Olsztyn, Poland; (K.S.); (K.Z.-W.); (A.K.); (J.W.)
- Correspondence: (N.N.); (J.J.)
| | - Kamila Szymańska
- Department of Human Physiology and Pathophysiology, School of Medicine, University of Warmia and Mazury, 10-082 Olsztyn, Poland; (K.S.); (K.Z.-W.); (A.K.); (J.W.)
| | - Judyta Juranek
- Department of Human Physiology and Pathophysiology, School of Medicine, University of Warmia and Mazury, 10-082 Olsztyn, Poland; (K.S.); (K.Z.-W.); (A.K.); (J.W.)
- Correspondence: (N.N.); (J.J.)
| | - Kamila Zglejc-Waszak
- Department of Human Physiology and Pathophysiology, School of Medicine, University of Warmia and Mazury, 10-082 Olsztyn, Poland; (K.S.); (K.Z.-W.); (A.K.); (J.W.)
| | - Agnieszka Korytko
- Department of Human Physiology and Pathophysiology, School of Medicine, University of Warmia and Mazury, 10-082 Olsztyn, Poland; (K.S.); (K.Z.-W.); (A.K.); (J.W.)
| | - Michał Załęcki
- Department of Animal Anatomy, Faculty of Veterinary Medicine, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland;
| | - Małgorzata Chmielewska-Krzesińska
- Department of Pathophysiology, Forensic Veterinary Medicine and Administration, Faculty of Veterinary Medicine, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland; (M.C.-K.); (K.W.)
| | - Krzysztof Wąsowicz
- Department of Pathophysiology, Forensic Veterinary Medicine and Administration, Faculty of Veterinary Medicine, University of Warmia and Mazury in Olsztyn, 10-719 Olsztyn, Poland; (M.C.-K.); (K.W.)
| | - Joanna Wojtkiewicz
- Department of Human Physiology and Pathophysiology, School of Medicine, University of Warmia and Mazury, 10-082 Olsztyn, Poland; (K.S.); (K.Z.-W.); (A.K.); (J.W.)
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Qiu H, Weng Q. Screening of Crucial Differentially-Methylated/Expressed Genes for Alzheimer's Disease. Am J Alzheimers Dis Other Demen 2022; 37:15333175221116220. [PMID: 35848539 PMCID: PMC10624077 DOI: 10.1177/15333175221116220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Background: We aimed to make an integrated analysis of published transcriptome and DNA methylation dataset to ascertain the key differentially methylated and differentially expressed genes for Alzherimer's disease (AD). Methods: Two gene expression microarrays and 1 gene methylation microarray were downloaded for identification of differentially expressed genes and differentially methylated genes. Then, we used various biological information databases to annotate the functions of the differentially-methylated/expressed genes, and screen out key genes and important signaling pathways. Finally, we validate the differentially-methylated/expressed genes in the additional online datasets and in blood from AD patients.Results: A total of 8 hub hypomethylated-high expression genes were obtained, including Rac family small GTPase 2, FGR proto-oncogene, Src family tyrosine kinase, LYN proto-oncogene, Src family tyrosine kinase, protein kinase C delta, myosin IF, integrin subunit alpha 5, semaphorin 4D, and growth arrest specific protein 7. Some enriched signaling pathways of hypomethylated-high expression genes were identified, including regulation of actin cytoskeleton, chemokine signaling pathway, Fc gamma R-mediated phagocytosis, and axon guidance. Conclusion: Differentially-methylated/expressed genes are likely to be associated with AD.
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Affiliation(s)
- Haiyuan Qiu
- Internal Medicine Department, Ningbo Psychiatric Hospital, Ningbo, China
| | - Qiuyan Weng
- Neurolog Department, Affiliated Hospital of Medical School Ningbo University, Ningbo, China
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Boice JD, Quinn B, Al-Nabulsi I, Ansari A, Blake PK, Blattnig SR, Caffrey EA, Cohen SS, Golden AP, Held KD, Jokisch DW, Leggett RW, Mumma MT, Samuels C, Till JE, Tolmachev SY, Yoder RC, Zhou JY, Dauer LT. A million persons, a million dreams: a vision for a national center of radiation epidemiology and biology. Int J Radiat Biol 2021; 98:795-821. [PMID: 34669549 PMCID: PMC10594603 DOI: 10.1080/09553002.2021.1988183] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2021] [Revised: 09/27/2021] [Accepted: 09/28/2021] [Indexed: 02/07/2023]
Abstract
BACKGROUND Epidemiologic studies of radiation-exposed populations form the basis for human safety standards. They also help shape public health policy and evidence-based health practices by identifying and quantifying health risks of exposure in defined populations. For more than a century, epidemiologists have studied the consequences of radiation exposures, yet the health effects of low levels delivered at a low-dose rate remain equivocal. MATERIALS AND METHODS The Million Person Study (MPS) of U.S. Radiation Workers and Veterans was designed to examine health effects following chronic exposures in contrast with brief exposures as experienced by the Japanese atomic bomb survivors. Radiation associations for rare cancers, intakes of radionuclides, and differences between men and women are being evaluated, as well as noncancers such as cardiovascular disease and conditions such as dementia and cognitive function. The first international symposium, held November 6, 2020, provided a broad overview of the MPS. Representatives from four U.S. government agencies addressed the importance of this research for their respective missions: U.S. Department of Energy (DOE), the Centers for Disease Control and Prevention (CDC), the U.S. Department of Defense (DOD), and the National Aeronautics and Space Administration (NASA). The major components of the MPS were discussed and recent findings summarized. The importance of radiation dosimetry, an essential feature of each MPS investigation, was emphasized. RESULTS The seven components of the MPS are DOE workers, nuclear weapons test participants, nuclear power plant workers, industrial radiographers, medical radiation workers, nuclear submariners, other U.S. Navy personnel, and radium dial painters. The MPS cohorts include tens of thousands of workers with elevated intakes of alpha particle emitters for which organ-specific doses are determined. Findings to date for chronic radiation exposure suggest that leukemia risk is lower than after acute exposure; lung cancer risk is much lower and there is little difference in risks between men and women; an increase in ischemic heart disease is yet to be seen; esophageal cancer is frequently elevated but not myelodysplastic syndrome; and Parkinson's disease may be associated with radiation exposure. CONCLUSIONS The MPS has provided provocative insights into the possible range of health effects following low-level chronic radiation exposure. When the 34 MPS cohorts are completed and combined, a powerful evaluation of radiation-effects will be possible. This final article in the MPS special issue summarizes the findings to date and the possibilities for the future. A National Center for Radiation Epidemiology and Biology is envisioned.
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Affiliation(s)
- John D. Boice
- National Council on Radiation Protection and Measurements, Bethesda, MD, USA
- Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Brian Quinn
- Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | | | - Armin Ansari
- Centers for Disease Control and Prevention, Atlanta, GA, USA
| | | | - Steve R. Blattnig
- National Aeronautics and Space Administration Langley Research Center, Hampton, VA, USA
| | - Emily A. Caffrey
- Radian Scientific, LLC, Huntsville, AL, and Risk Assessment Corporation, Neeses, SC, USA
| | - Sarah S. Cohen
- EpidStrategies, a division of ToxStrategies, Inc, Cary, NC, USA
| | | | - Kathryn D. Held
- National Council on Radiation Protection and Measurements, Bethesda, MD, USA
- Massachusetts General Hospital/Harvard Medical School, Boston, MA, USA
| | - Derek W. Jokisch
- Francis Marion University, Florence, SC, USA
- Oak Ridge National Laboratory, Oak Ridge, TN, USA
| | | | - Michael T. Mumma
- Vanderbilt University School of Medicine, Nashville, TN, USA
- International Epidemiology Institute, Rockville, MD, USA
| | | | | | | | | | - Joey Y. Zhou
- United States Department of Energy, Gaithersburg, MD, USA
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Zhu X, Zhang Y, Yang X, Hao C, Duan H. Gene Therapy for Neurodegenerative Disease: Clinical Potential and Directions. Front Mol Neurosci 2021; 14:618171. [PMID: 34194298 PMCID: PMC8236824 DOI: 10.3389/fnmol.2021.618171] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Accepted: 05/07/2021] [Indexed: 12/21/2022] Open
Abstract
The pathogenesis of neurodegenerative diseases (NDDs) is complex and diverse. Over the decades, our understanding of NDD has been limited to pathological features. However, recent advances in gene sequencing have facilitated elucidation of NDD at a deeper level. Gene editing techniques have uncovered new genetic links to phenotypes, promoted the development of novel treatment strategies and equipped researchers with further means to construct effective cell and animal models. The current review describes the history of evolution of gene editing tools, with the aim of improving overall understanding of this technology, and focuses on the four most common NDD disorders to demonstrate the potential future applications and research directions of gene editing.
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Affiliation(s)
- Xiaolin Zhu
- Department of Neurosurgery, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Yu Zhang
- Department of Neurosurgery, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Xin Yang
- Department of Neurosurgery, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Chunyan Hao
- Department of Geriatrics, First Hospital of Shanxi Medical University, Taiyuan, China
| | - Hubin Duan
- Department of Neurosurgery, First Hospital of Shanxi Medical University, Taiyuan, China.,Department of Neurosurgery, Lvliang People's Hospital, Lvliang, China
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Nabais MF, Laws SM, Lin T, Vallerga CL, Armstrong NJ, Blair IP, Kwok JB, Mather KA, Mellick GD, Sachdev PS, Wallace L, Henders AK, Zwamborn RAJ, Hop PJ, Lunnon K, Pishva E, Roubroeks JAY, Soininen H, Tsolaki M, Mecocci P, Lovestone S, Kłoszewska I, Vellas B, Furlong S, Garton FC, Henderson RD, Mathers S, McCombe PA, Needham M, Ngo ST, Nicholson G, Pamphlett R, Rowe DB, Steyn FJ, Williams KL, Anderson TJ, Bentley SR, Dalrymple-Alford J, Fowder J, Gratten J, Halliday G, Hickie IB, Kennedy M, Lewis SJG, Montgomery GW, Pearson J, Pitcher TL, Silburn P, Zhang F, Visscher PM, Yang J, Stevenson AJ, Hillary RF, Marioni RE, Harris SE, Deary IJ, Jones AR, Shatunov A, Iacoangeli A, van Rheenen W, van den Berg LH, Shaw PJ, Shaw CE, Morrison KE, Al-Chalabi A, Veldink JH, Hannon E, Mill J, Wray NR, McRae AF. Meta-analysis of genome-wide DNA methylation identifies shared associations across neurodegenerative disorders. Genome Biol 2021; 22:90. [PMID: 33771206 PMCID: PMC8004462 DOI: 10.1186/s13059-021-02275-5] [Citation(s) in RCA: 42] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2020] [Accepted: 01/20/2021] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND People with neurodegenerative disorders show diverse clinical syndromes, genetic heterogeneity, and distinct brain pathological changes, but studies report overlap between these features. DNA methylation (DNAm) provides a way to explore this overlap and heterogeneity as it is determined by the combined effects of genetic variation and the environment. In this study, we aim to identify shared blood DNAm differences between controls and people with Alzheimer's disease, amyotrophic lateral sclerosis, and Parkinson's disease. RESULTS We use a mixed-linear model method (MOMENT) that accounts for the effect of (un)known confounders, to test for the association of each DNAm site with each disorder. While only three probes are found to be genome-wide significant in each MOMENT association analysis of amyotrophic lateral sclerosis and Parkinson's disease (and none with Alzheimer's disease), a fixed-effects meta-analysis of the three disorders results in 12 genome-wide significant differentially methylated positions. Predicted immune cell-type proportions are disrupted across all neurodegenerative disorders. Protein inflammatory markers are correlated with profile sum-scores derived from disease-associated immune cell-type proportions in a healthy aging cohort. In contrast, they are not correlated with MOMENT DNAm-derived profile sum-scores, calculated using effect sizes of the 12 differentially methylated positions as weights. CONCLUSIONS We identify shared differentially methylated positions in whole blood between neurodegenerative disorders that point to shared pathogenic mechanisms. These shared differentially methylated positions may reflect causes or consequences of disease, but they are unlikely to reflect cell-type proportion differences.
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Grants
- U24 AG021886 NIA NIH HHS
- U01 AG016976 NIA NIH HHS
- Department of Health
- U01 AG024904 NIA NIH HHS
- 108890/Z/15/Z Wellcome Trust
- 503480 Medical Research Council
- TURNER/OCT15/972-797 Motor Neurone Disease Association
- U01 AG032984 NIA NIH HHS
- R01 HL105756 NHLBI NIH HHS
- 082604/2/07/Z Wellcome Trust
- R01 AG033193 NIA NIH HHS
- National Health and Medical Research Council
- Motor Neurone Disease Research Institute of Australia Ice Bucket Challenge
- Medical Research Council (UK)
- Economic and Social Research Council
- National Institute for Health Research (NIHR)
- the European Community’s Health Seventh Framework Programme
- Horizon 2020 Programme
- MND Association and the Wellcome Trust.
- European Research Council (ERC)
- EU Joint Programme – Neurodegenerative Disease Research ()
- EU Joint Programme - Neurodegenerative Disease Research (JPND)
- Australian Research Council
- Mater Foundation
- ForeFront - NHMRC
- Australian National Health and Medical Research Council
- University of Otago Research Grant, together with financial support from the Jim and Mary Carney Charitable Trust
- Commonwealth Scientific Industrial and research Organization (CSIRO), Edith Cowan University (ECU), Mental Health Research institute (MHRI), National Ageing Research Institute (NARI), Austin Health, CogState Ltd
- National Health and Medical Research Council and the Dementia Collaborative Research Centres program (DCRC2), as well as funding from the Science and Industry Endowment Fund (SIEF) and the Cooperative Research Centre (CRC) for Mental Health – funded throug
- EU Joint Programme - Neurodegenerative Disease Research (JPND), co-funded through the Australian National Health and Medical Research (NHMRC) Council, Motor Neurone Disease Research Institute of Australia Ice Bucket Challenge,
- EU Joint Programme - Neurodegenerative Disease Research (JPND), United Kingdom Medical Research Council, Economic and Social Research Council, Motor Neuro Disease Association (GB), National Institute for Health Research (NIHR) Biomedical Research Centre at
- EU Joint Programme - Neurodegenerative Disease Research (JPND), European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program, PPP Allowance made available by Health~Holland, Top Sector Life Sciences & Health, Unit
- National Health and Medical Research Council, Australian Research Council, Mater Foundation,
- Australian National Health and Medical Research Council (
- University of Otago Research Grant, Jim and Mary Carney Charitable Trust
- Commonwealth Scientific Industrial and research Organization (CSIRO), Edith Cowan University (ECU), Mental Health Research institute (MHRI), National Ageing Research Institute (NARI), Austin Health, CogState Ltd., National Health and Medical Research Counc
- EFPIA companies and SMEs as part of InnoMed (Innovative Medicines in Europe), an Integrated Project funded by the European Union of the Sixth Framework program
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Affiliation(s)
- Marta F Nabais
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
- University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW, UK
| | - Simon M Laws
- School of Medical and Health Sciences, Edith Cowan University, 270 Joondalup Dr, Joondalup, WA, 6027, Australia
| | - Tian Lin
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Costanza L Vallerga
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
- Department of Internal Medicine, Erasmus MC, University Medical Center, 3015GD, Rotterdam, The Netherlands
| | | | - Ian P Blair
- Australian Centre for Precision Health, University of South Australia Cancer Research Institute, School of Health Sciences, University of South Australia, Adelaide, SA, 5001, Australia
| | - John B Kwok
- Brain and Mind Centre, Sydney Medical School, The University of Sydney, Sydney, Australia
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, 2031, Australia
- Neuroscience Research Australia Institute, Randwick, NSW, 2031, Australia
| | - George D Mellick
- Griffith Institute for Drug Discovery (GRIDD), Griffith University, Brisbane, Australia
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, 2031, Australia
- Neuropsychiatric Institute, The Prince of Wales Hospital, UNSW, Randwick, NSW, 2031, Australia
| | - Leanne Wallace
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Anjali K Henders
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Ramona A J Zwamborn
- Department of Neurology, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Paul J Hop
- Department of Neurology, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Katie Lunnon
- University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW, UK
| | - Ehsan Pishva
- University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW, UK
| | - Janou A Y Roubroeks
- University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW, UK
| | - Hilkka Soininen
- Institute of Clinical Medicine, Neurology, University of Eastern Finland, Kuopio, Finland
| | - Magda Tsolaki
- 1st Department of Neurology, Memory and Dementia Unit, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Patrizia Mecocci
- Department of Medicine, Institute of Gerontology and Geriatrics, University of Perugia, Perugia, Italy
| | - Simon Lovestone
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
| | | | - Bruno Vellas
- INSERM U 558, University of Toulouse, Toulouse, France
| | - Sarah Furlong
- Centre for Motor Neuron Disease Research, Macquarie University, Sydney, NSW, 2109, Australia
| | - Fleur C Garton
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Robert D Henderson
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia
- Centre for Clinical Research, The University of Queensland, Brisbane, QLD, 4019, Australia
- Department of Neurology, Royal Brisbane and Women's Hospital, Brisbane, QLD, 4029, Australia
| | - Susan Mathers
- Calvary Health Care Bethlehem, Parkdale, VIC, 3195, Australia
| | - Pamela A McCombe
- Centre for Clinical Research, The University of Queensland, Brisbane, QLD, 4019, Australia
- Department of Neurology, Royal Brisbane and Women's Hospital, Brisbane, QLD, 4029, Australia
| | - Merrilee Needham
- Fiona Stanley Hospital, Perth, WA, 6150, Australia
- Notre Dame University, Fremantle, WA, 6160, Australia
- Institute for Immunology and Infectious Diseases, Murdoch University, Perth, WA, 6150, Australia
| | - Shyuan T Ngo
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia
- Centre for Clinical Research, The University of Queensland, Brisbane, QLD, 4019, Australia
- The Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Garth Nicholson
- ANZAC Research Institute, Concord Repatriation General Hospital, Sydney, NSW, 2139, Australia
| | - Roger Pamphlett
- Discipline of Pathology and Department of Neuropathology, Brain and Mind Centre, The University of Sydney, Sydney, NSW, 2050, Australia
| | - Dominic B Rowe
- Centre for Motor Neuron Disease Research, Macquarie University, Sydney, NSW, 2109, Australia
| | - Frederik J Steyn
- Department of Neurology, Royal Brisbane and Women's Hospital, Brisbane, QLD, 4029, Australia
- School of Biomedical Sciences, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Kelly L Williams
- Centre for Motor Neuron Disease Research, Macquarie University, Sydney, NSW, 2109, Australia
| | - Tim J Anderson
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Steven R Bentley
- Eskitis Institute for Drug Discovery, Griffith University, Brisbane, Australia
| | - John Dalrymple-Alford
- New Zealand Brain Research Institute, Christchurch, New Zealand
- School of Psychology, Speech and Hearing, University of Canterbury, Christchurch, New Zealand
| | - Javed Fowder
- Griffith Institute for Drug Discovery (GRIDD), Griffith University, Brisbane, Australia
| | - Jacob Gratten
- Mater Research, Translational Research Institute, Brisbane, Australia
- Mater Research Institute, The University of Queensland, Brisbane, Australia
| | - Glenda Halliday
- Brain and Mind Research Centre, Sydney Medical School, The University of Sydney, Sydney, Australia
| | - Ian B Hickie
- Brain and Mind Research Centre, Sydney Medical School, The University of Sydney, Sydney, Australia
| | - Martin Kennedy
- Department of Pathology and Biomedical Science, University of Otago, Christchurch, New Zealand
| | - Simon J G Lewis
- Brain and Mind Research Centre, Sydney Medical School, The University of Sydney, Sydney, Australia
| | - Grant W Montgomery
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - John Pearson
- Department of Pathology, University of Otago, Christchurch, New Zealand
| | - Toni L Pitcher
- New Zealand Brain Research Institute, Christchurch, New Zealand
- Department of Medicine, University of Otago, Christchurch, New Zealand
| | - Peter Silburn
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Futao Zhang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Peter M Visscher
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Jian Yang
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
- School of Life Sciences, Westlake University, Hangzhou, Zhejiang, China
- Westlake Laboratory of Life Sciences and Biomedicine, Hangzhou, Zhejiang, China
| | - Anna J Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, EH4 2XU, UK
| | - Sarah E Harris
- Department of Psychology, Lothian Birth Cohorts group, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Ian J Deary
- Department of Psychology, Lothian Birth Cohorts group, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Ashley R Jones
- Department of Basic and Clinical Neuroscience, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, SE5 9RX, UK
| | - Aleksey Shatunov
- Department of Basic and Clinical Neuroscience, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, SE5 9RX, UK
| | - Alfredo Iacoangeli
- Department of Basic and Clinical Neuroscience, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, SE5 9RX, UK
| | - Wouter van Rheenen
- Department of Neurology, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Leonard H van den Berg
- Department of Neurology, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | | | - Cristopher E Shaw
- Department of Basic and Clinical Neuroscience, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, SE5 9RX, UK
| | | | - Ammar Al-Chalabi
- Department of Basic and Clinical Neuroscience, King's College London, Institute of Psychiatry, Psychology and Neuroscience, London, SE5 9RX, UK
- King's College Hospital, London, SE5 9RS, UK
| | - Jan H Veldink
- Department of Neurology, University Medical Center Utrecht Brain Center, Utrecht University, Utrecht, The Netherlands
| | - Eilis Hannon
- University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW, UK
| | - Jonathan Mill
- University of Exeter Medical School, RILD Building, RD&E Hospital Wonford, Barrack Road, Exeter, EX2 5DW, UK
- Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | - Naomi R Wray
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia
- Queensland Brain Institute, The University of Queensland, Brisbane, QLD, 4072, Australia
| | - Allan F McRae
- Institute for Molecular Bioscience, The University of Queensland, Brisbane, QLD, 4072, Australia.
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