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Jeon S, Park J, Likhite S, Moon JH, Shin D, Li L, Meyer KC, Lee JW, Lee SK. The postnatal injection of AAV9-FOXG1 rescues corpus callosum agenesis and other brain deficits in the mouse model of FOXG1 syndrome. Mol Ther Methods Clin Dev 2024; 32:101275. [PMID: 39022742 PMCID: PMC11253142 DOI: 10.1016/j.omtm.2024.101275] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 05/31/2024] [Indexed: 07/20/2024]
Abstract
Heterozygous mutations in the FOXG1 gene manifest as FOXG1 syndrome, a severe neurodevelopmental disorder characterized by structural brain anomalies, including agenesis of the corpus callosum, hippocampal reduction, and myelination delays. Despite the well-defined genetic basis of FOXG1 syndrome, therapeutic interventions targeting the underlying cause of the disorder are nonexistent. In this study, we explore the therapeutic potential of adeno-associated virus 9 (AAV9)-mediated delivery of the FOXG1 gene. Remarkably, intracerebroventricular injection of AAV9-FOXG1 to Foxg1 heterozygous mouse model at the postnatal stage rescues a wide range of brain pathologies. This includes the amelioration of corpus callosum deficiencies, the restoration of dentate gyrus morphology in the hippocampus, the normalization of oligodendrocyte lineage cell numbers, and the rectification of myelination anomalies. Our findings highlight the efficacy of AAV9-based gene therapy as a viable treatment strategy for FOXG1 syndrome and potentially other neurodevelopmental disorders with similar brain malformations, asserting its therapeutic relevance in postnatal stages.
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Affiliation(s)
- Shin Jeon
- Department of Biological Sciences, College of Arts and Sciences, FOXG1 Research Center, University at Buffalo, The State University of New York (SUNY), Buffalo, NY 14260, USA
- Department of Systems Pharmacology & Translational Therapeutics, Institute for Immunology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Jaein Park
- Department of Biological Sciences, College of Arts and Sciences, FOXG1 Research Center, University at Buffalo, The State University of New York (SUNY), Buffalo, NY 14260, USA
| | - Shibi Likhite
- The Research Institute at Nationwide Children’s Hospital, Columbus, OH 43205, USA
| | - Ji Hwan Moon
- Department of Biological Sciences, College of Arts and Sciences, FOXG1 Research Center, University at Buffalo, The State University of New York (SUNY), Buffalo, NY 14260, USA
- Samsung Genome Institute, Samsung Medical Center, Seoul 06351, Korea
| | - Dongjun Shin
- Department of Biological Sciences, College of Arts and Sciences, FOXG1 Research Center, University at Buffalo, The State University of New York (SUNY), Buffalo, NY 14260, USA
| | - Liwen Li
- Department of Biological Sciences, College of Arts and Sciences, FOXG1 Research Center, University at Buffalo, The State University of New York (SUNY), Buffalo, NY 14260, USA
| | - Kathrin C. Meyer
- The Research Institute at Nationwide Children’s Hospital, Columbus, OH 43205, USA
| | - Jae W. Lee
- Department of Biological Sciences, College of Arts and Sciences, FOXG1 Research Center, University at Buffalo, The State University of New York (SUNY), Buffalo, NY 14260, USA
| | - Soo-Kyung Lee
- Department of Biological Sciences, College of Arts and Sciences, FOXG1 Research Center, University at Buffalo, The State University of New York (SUNY), Buffalo, NY 14260, USA
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2
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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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Pivirotto A, Peles N, Hey J. Allele age estimators designed for whole genome datasets show only a modest decrease in accuracy when applied to whole exome datasets. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.01.578465. [PMID: 38370640 PMCID: PMC10871225 DOI: 10.1101/2024.02.01.578465] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Personalized genomics in the healthcare system is becoming increasingly accessible as the costs of sequencing decreases. With the increase in number of genomes, larger numbers of rare variants are being discovered and much work is being done to identify their functional impacts in relation to disease phenotypes. One way to characterize these variants is to estimate the time the mutation entered the population. However, allele age estimators such as Relate, Genealogical Estimator of Variant Age, and time of coalescence, were developed based on the assumption that datasets include the entire genome. We examined the performance of each of these estimators on simulated exome data under a neutral constant population size model and found that each provides usable estimates of allele age from whole-exome datasets. To test the robustness of these methods, analyses were undertaken to simulate data under a population expansion model and background selection. Relate performs the best amongst all three estimators with Pearson coefficients of 0.64 and 0.68 (neutral constant and expansion population model) with a 17 percent and 15 percent drop in accuracy between whole genome and whole exome estimations. Of the three estimators, Relate is best able to parallelize to yield quick results with little resources, however even Relate is only able to scale to thousands of samples making it unable to match the hundreds of thousands of samples being currently released. While more work is needed to expand the capabilities of current methods of estimating allele age, these methods estimate the age of mutations with a modest decrease in performance.
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Affiliation(s)
- Alyssa Pivirotto
- Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA USA
| | - Noah Peles
- Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA USA
| | - Jody Hey
- Center for Computational Genetics and Genomics, Temple University, Philadelphia, PA USA
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4
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Logue MW, Dasgupta S, Farrer LA. Genetics of Alzheimer's Disease in the African American Population. J Clin Med 2023; 12:5189. [PMID: 37629231 PMCID: PMC10455208 DOI: 10.3390/jcm12165189] [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: 06/26/2023] [Revised: 08/02/2023] [Accepted: 08/06/2023] [Indexed: 08/27/2023] Open
Abstract
Black/African American (AA) individuals have a higher risk of Alzheimer's disease (AD) than White non-Hispanic persons of European ancestry (EUR) for reasons that may include economic disparities, cardiovascular health, quality of education, and biases in the methods used to diagnose AD. AD is also heritable, and some of the differences in risk may be due to genetics. Many AD-associated variants have been identified by candidate gene studies, genome-wide association studies (GWAS), and genome-sequencing studies. However, most of these studies have been performed using EUR cohorts. In this paper, we review the genetics of AD and AD-related traits in AA individuals. Importantly, studies of genetic risk factors in AA cohorts can elucidate the molecular mechanisms underlying AD risk in AA and other populations. In fact, such studies are essential to enable reliable precision medicine approaches in persons with considerable African ancestry. Furthermore, genetic studies of AA cohorts allow exploration of the ways the impact of genes can vary by ancestry, culture, and economic and environmental disparities. They have yielded important gains in our knowledge of AD genetics, and increasing AA individual representation within genetic studies should remain a priority for inclusive genetic study design.
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Affiliation(s)
- Mark W. Logue
- National Center for PTSD, Behavioral Sciences Division, VA Boston Healthcare System, Boston, MA 02130, USA;
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA;
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Shoumita Dasgupta
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA;
- Department of Medical Sciences and Education, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA;
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Ophthalmology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA 02118, USA
- Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA 02118, USA
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5
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Lambert JC, Ramirez A, Grenier-Boley B, Bellenguez C. Step by step: towards a better understanding of the genetic architecture of Alzheimer's disease. Mol Psychiatry 2023; 28:2716-2727. [PMID: 37131074 PMCID: PMC10615767 DOI: 10.1038/s41380-023-02076-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 04/12/2023] [Accepted: 04/14/2023] [Indexed: 05/04/2023]
Abstract
Alzheimer's disease (AD) is considered to have a large genetic component. Our knowledge of this component has progressed over the last 10 years, thanks notably to the advent of genome-wide association studies and the establishment of large consortia that make it possible to analyze hundreds of thousands of cases and controls. The characterization of dozens of chromosomal regions associated with the risk of developing AD and (in some loci) the causal genes responsible for the observed disease signal has confirmed the involvement of major pathophysiological pathways (such as amyloid precursor protein metabolism) and opened up new perspectives (such as the central role of microglia and inflammation). Furthermore, large-scale sequencing projects are starting to reveal the major impact of rare variants - even in genes like APOE - on the AD risk. This increasingly comprehensive knowledge is now being disseminated through translational research; in particular, the development of genetic risk/polygenic risk scores is helping to identify the subpopulations more at risk or less at risk of developing AD. Although it is difficult to assess the efforts still needed to comprehensively characterize the genetic component of AD, several lines of research can be improved or initiated. Ultimately, genetics (in combination with other biomarkers) might help to redefine the boundaries and relationships between various neurodegenerative diseases.
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Affiliation(s)
- Jean-Charles Lambert
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, Lille, France.
| | - Alfredo Ramirez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Department of Neurodegenerative diseases and Geriatric Psychiatry, University Hospital Bonn, Medical Faculty, Bonn, Germany
- Department of Psychiatry & Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, San Antonio, TX, USA
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Cluster of Excellence Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Benjamin Grenier-Boley
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, Lille, France
| | - Céline Bellenguez
- Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, Lille, France
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6
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Al-Khannaq M, Lytton J. Regulation of K +-Dependent Na +/Ca 2+-Exchangers (NCKX). Int J Mol Sci 2022; 24:ijms24010598. [PMID: 36614039 PMCID: PMC9820825 DOI: 10.3390/ijms24010598] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 12/23/2022] [Accepted: 12/24/2022] [Indexed: 12/31/2022] Open
Abstract
Potassium-dependent sodium-calcium exchangers (NCKX) have emerged as key determinants of calcium (Ca2+) signaling and homeostasis, especially in environments where ion concentrations undergo large changes, such as excitatory cells and transport epithelia. The regulation of NCKX transporters enables them to respond to the changing cellular environment thereby helping to shape the extent and kinetics of Ca2+ signals. This review examines the current knowledge of the different ways in which NCKX activity can be modulated. These include (i) cellular and dynamic subcellular location (ii); changes in protein expression mediated at the gene, transcript, or protein level (iii); genetic changes resulting in altered protein structure or expression (iv); regulation via changes in substrate concentration (v); and post-translational modification, partner protein interactions, and allosteric regulation. Detailed mechanistic understanding of NCKX regulation is an emerging area of research with the potential to provide important new insights into transporter function, the control of Ca2+ signals, and possible interventions for dysregulated Ca2+ homeostasis.
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7
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Aerqin Q, Wang ZT, Wu KM, He XY, Dong Q, Yu JT. Omics-based biomarkers discovery for Alzheimer's disease. Cell Mol Life Sci 2022; 79:585. [PMID: 36348101 DOI: 10.1007/s00018-022-04614-6] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Revised: 10/22/2022] [Accepted: 10/26/2022] [Indexed: 11/09/2022]
Abstract
Alzheimer's disease (AD) is the most common neurodegenerative disorders presenting with the pathological hallmarks of amyloid plaques and tau tangles. Over the past few years, great efforts have been made to explore reliable biomarkers of AD. High-throughput omics are a technology driven by multiple levels of unbiased data to detect the complex etiology of AD, and it provides us with new opportunities to better understand the pathophysiology of AD and thereby identify potential biomarkers. Through revealing the interaction networks between different molecular levels, the ultimate goal of multi-omics is to improve the diagnosis and treatment of AD. In this review, based on the current AD pathology and the current status of AD diagnostic biomarkers, we summarize how genomics, transcriptomics, proteomics and metabolomics are all conducing to the discovery of reliable AD biomarkers that could be developed and used in clinical AD management.
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Affiliation(s)
- Qiaolifan Aerqin
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Zuo-Teng Wang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Kai-Min Wu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Xiao-Yu He
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, 200040, China.
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8
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Kassani PH, Lu F, Guen YL, Belloy ME, He Z. Deep neural networks with controlled variable selection for the identification of putative causal genetic variants. NAT MACH INTELL 2022; 4:761-771. [PMID: 37859729 PMCID: PMC10586424 DOI: 10.1038/s42256-022-00525-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Accepted: 07/26/2022] [Indexed: 11/09/2022]
Abstract
Deep neural networks (DNNs) have been successfully utilized in many scientific problems for their high prediction accuracy, but their application to genetic studies remains challenging due to their poor interpretability. Here we consider the problem of scalable, robust variable selection in DNNs for the identification of putative causal genetic variants in genome sequencing studies. We identified a pronounced randomness in feature selection in DNNs due to its stochastic nature, which may hinder interpretability and give rise to misleading results. We propose an interpretable neural network model, stabilized using ensembling, with controlled variable selection for genetic studies. The merit of the proposed method includes: flexible modelling of the nonlinear effect of genetic variants to improve statistical power; multiple knockoffs in the input layer to rigorously control the false discovery rate; hierarchical layers to substantially reduce the number of weight parameters and activations, and improve computational efficiency; and stabilized feature selection to reduce the randomness in identified signals. We evaluate the proposed method in extensive simulation studies and apply it to the analysis of Alzheimer's disease genetics. We show that the proposed method, when compared with conventional linear and nonlinear methods, can lead to substantially more discoveries.
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Affiliation(s)
- Peyman H. Kassani
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Fred Lu
- Department of Statistics, Stanford University, Stanford, CA, USA
| | - Yann Le Guen
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Michael E. Belloy
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Zihuai He
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
- Quantitative Sciences Unit, Department of Medicine (Biomedical Informatics Research), Stanford University, Stanford, CA, USA
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9
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Gardner OK, Van Booven D, Wang L, Gu T, Hofmann NK, Whitehead PL, Nuytemans K, Hamilton-Nelson KL, Adams LD, Starks TD, Cuccaro ML, Martin ER, Vance JM, Bush WS, Byrd GS, Haines JL, Beecham GW, Pericak-Vance MA, Griswold AJ. Genetic architecture of RNA editing regulation in Alzheimer's disease across diverse ancestral populations. Hum Mol Genet 2022; 31:2876-2886. [PMID: 35383839 PMCID: PMC9433728 DOI: 10.1093/hmg/ddac075] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2021] [Revised: 03/24/2022] [Accepted: 03/27/2022] [Indexed: 11/14/2022] Open
Abstract
Most Alzheimer's disease (AD)-associated genetic variants do not change protein coding sequence and thus likely exert their effects through regulatory mechanisms. RNA editing, the post-transcriptional modification of RNA bases, is a regulatory feature that is altered in AD patients that differs across ancestral backgrounds. Editing QTLs (edQTLs) are DNA variants that influence the level of RNA editing at a specific site. To study the relationship of DNA variants genome-wide, and particularly in AD-associated loci, with RNA editing, we performed edQTL analyses in self-reported individuals of African American (AF) or White (EU) race with corresponding global genetic ancestry averaging 82.2% African ancestry (AF) and 96.8% European global ancestry (EU) in the two groups, respectively. We used whole-genome genotyping array and RNA sequencing data from peripheral blood of 216 AD cases and 212 age-matched, cognitively intact controls. We identified 2144 edQTLs in AF and 3579 in EU, of which 1236 were found in both groups. Among these, edQTLs in linkage disequilibrium (r2 > 0.5) with AD-associated genetic variants in the SORL1, SPI1 and HLA-DRB1 loci were associated with sites that were differentially edited between AD cases and controls. While there is some shared RNA editing regulatory architecture, most edQTLs had distinct effects on the rate of RNA editing in different ancestral populations suggesting a complex architecture of RNA editing regulation. Altered RNA editing may be one possible mechanism for the functional effect of AD-associated variants and may contribute to observed differences in the genetic etiology of AD between ancestries.
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Affiliation(s)
- Olivia K Gardner
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Derek Van Booven
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Lily Wang
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
- Department of Public Health Sciences, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Tianjie Gu
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Natalia K Hofmann
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Patrice L Whitehead
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Karen Nuytemans
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
- Maya Angelou Center for Health Equity, Wake Forest University, Winston-Salem, NC 27101, USA
| | - Kara L Hamilton-Nelson
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Larry D Adams
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Takiyah D Starks
- Maya Angelou Center for Health Equity, Wake Forest University, Winston-Salem, NC 27101, USA
| | - Michael L Cuccaro
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
- Department of Human Genetics, Dr. John T Macdonald Foundation, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Eden R Martin
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
- Department of Human Genetics, Dr. John T Macdonald Foundation, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Jeffery M Vance
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
- Department of Human Genetics, Dr. John T Macdonald Foundation, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - William S Bush
- Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
- Cleveland Institute for Computational Biology, Cleveland, OH 44106, USA
| | - Goldie S Byrd
- Maya Angelou Center for Health Equity, Wake Forest University, Winston-Salem, NC 27101, USA
| | - Jonathan L Haines
- Department of Population & Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH 44106, USA
- Cleveland Institute for Computational Biology, Cleveland, OH 44106, USA
| | - Gary W Beecham
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
- Department of Human Genetics, Dr. John T Macdonald Foundation, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Margaret A Pericak-Vance
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
- Department of Human Genetics, Dr. John T Macdonald Foundation, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Anthony J Griswold
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
- Department of Human Genetics, Dr. John T Macdonald Foundation, Miller School of Medicine, University of Miami, Miami, FL 33136, USA
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10
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Belloy ME, Le Guen Y, Eger SJ, Napolioni V, Greicius MD, He Z. A Fast and Robust Strategy to Remove Variant-Level Artifacts in Alzheimer Disease Sequencing Project Data. Neurol Genet 2022; 8:e200012. [PMID: 35966919 PMCID: PMC9372872 DOI: 10.1212/nxg.0000000000200012] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 05/31/2022] [Indexed: 02/02/2023]
Abstract
Background and Objectives Exome sequencing (ES) and genome sequencing (GS) are expected to be critical to further elucidate the missing genetic heritability of Alzheimer disease (AD) risk by identifying rare coding and/or noncoding variants that contribute to AD pathogenesis. In the United States, the Alzheimer Disease Sequencing Project (ADSP) has taken a leading role in sequencing AD-related samples at scale, with the resultant data being made publicly available to researchers to generate new insights into the genetic etiology of AD. To achieve sufficient power, the ADSP has adapted a study design where subsets of larger AD cohorts are collected and sequenced across multiple centers, using a variety of sequencing platforms. This approach may lead to variable variant quality across sequencing centers and/or platforms. In this study, we sought to implement and evaluate filters that can be applied fast to robustly remove variant-level artifacts in the ADSP data. Methods We implemented a robust quality control procedure to handle ADSP data. We evaluated this procedure while performing exome-wide and genome-wide association analyses on AD risk using the latest ADSP whole ES (WES) and whole GS (WGS) data releases (NG00067.v5). Results We observed that many variants displayed large variation in allele frequencies across sequencing centers/platforms and contributed to spurious association signals with AD risk. We also observed that sequencing platform/center adjustment in association models could not fully account for these spurious signals. To address this issue, we designed and implemented variant filters that could capture and remove these center-specific/platform-specific artifactual variants. Discussion We derived a fast and robust approach to filter variants that represent sequencing center-related or platform-related artifacts underlying spurious associations with AD risk in ADSP WES and WGS data. This approach will be important to support future robust genetic association studies on ADSP data, as well as other studies with similar designs.
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11
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Wesenhagen KE, Gobom J, Bos I, Vos SJ, Martinez‐Lage P, Popp J, Tsolaki M, Vandenberghe R, Freund‐Levi Y, Verhey F, Lovestone S, Streffer J, Dobricic V, Bertram L, Blennow K, Pikkarainen M, Hallikainen M, Kuusisto J, Laakso M, Soininen H, Scheltens P, Zetterberg H, Teunissen CE, Visser PJ, Tijms BM. Effects of age, amyloid, sex, and APOE ε4 on the CSF proteome in normal cognition. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12286. [PMID: 35571963 PMCID: PMC9074716 DOI: 10.1002/dad2.12286] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 11/30/2021] [Accepted: 12/03/2021] [Indexed: 11/07/2022]
Abstract
Introduction It is important to understand which biological processes change with aging, and how such changes are associated with increased Alzheimer's disease (AD) risk. We studied how cerebrospinal fluid (CSF) proteomics changed with age and tested if associations depended on amyloid status, sex, and apolipoprotein E Ɛ4 genotype. Methods We included 277 cognitively intact individuals aged 46 to 89 years from Alzheimer's Disease Neuroimaging Initiative, European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery, and Metabolic Syndrome in Men. In total, 1149 proteins were measured with liquid chromatography mass spectrometry with multiple reaction monitoring/Rules-Based Medicine, tandem mass tag mass spectrometry, and SOMAscan. We tested associations between age and protein levels in linear models and tested enrichment for Reactome pathways. Results Levels of 252 proteins increased with age independently of amyloid status. These proteins were associated with immune and signaling processes. Levels of 21 proteins decreased with older age exclusively in amyloid abnormal participants and these were enriched for extracellular matrix organization. Discussion We found amyloid-independent and -dependent CSF proteome changes with older age, perhaps representing physiological aging and early AD pathology.
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Affiliation(s)
- Kirsten E.J. Wesenhagen
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Johan Gobom
- Clinical Neurochemistry Lab, Institute of Neuroscience and PhysiologySahlgrenska University HospitalMölndalSweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and PhysiologyUniversity of GothenburgMölndalSweden
| | | | - Stephanie J.B. Vos
- Alzheimer Center Limburg, School for Mental Health and NeuroscienceMaastricht UniversityMaastrichtthe Netherlands
| | - Pablo Martinez‐Lage
- Center for Research and Advanced TherapiesCITA‐Alzheimers FoundationDonostia‐San SebastianSpain
| | - Julius Popp
- Geriatric Psychiatry, Department of Mental Health and PsychiatryGeneva University HospitalsGenevaSwitzerland
- Department of PsychiatryUniversity Hospital of LausanneLausanneSwitzerland
| | - Magda Tsolaki
- 1st Department of Neurology, AHEPA University Hospital, Medical School, Faculty of Health SciencesAristotle University of ThessalonikiMakedoniaThessalonikiGreece
| | - Rik Vandenberghe
- Neurology ServiceUniversity Hospitals LeuvenLeuvenBelgium
- Laboratory for Cognitive Neurology, Department of NeurosciencesKU LeuvenLeuvenBelgium
| | - Yvonne Freund‐Levi
- Department of Neurobiology, Care Sciences and Society, Division of NeurogeriatricsKarolinska InstitutetStockholmSweden
- School of Medical Sciences Örebro University and Dep of Psychiatry Örebro University HospitalÖrebroSweden
| | - Frans Verhey
- Alzheimer Center Limburg, School for Mental Health and NeuroscienceMaastricht UniversityMaastrichtthe Netherlands
| | - Simon Lovestone
- Janssen‐cilagHigh WycombeUK
- (at the time of study conduct)University of OxfordOxfordUK
| | - Johannes Streffer
- formerly Janssen R&D, LLC, Beerse, Belgium (at the time of study conduct)AC Immune SALausanneSwitzerland
- Department of Biomedical SciencesUniversity of AntwerpAntwerpBelgium
| | | | - Lars Bertram
- Lübeck UniversityLübeckGermany
- Center for Lifespan Changes in Brain and Cognition (LCBC), Department of PsychologyUniversity of OsloOsloNorway
| | | | - Kaj Blennow
- Clinical Neurochemistry Lab, Institute of Neuroscience and PhysiologySahlgrenska University HospitalMölndalSweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and PhysiologyUniversity of GothenburgMölndalSweden
| | - Maria Pikkarainen
- Institute of Clinical Medicine, NeurologyUniversity of Eastern FinlandKuopioFinland
| | - Merja Hallikainen
- Institute of Clinical MedicineInternal Medicineand Kuopio University HospitalUniversity of Eastern FinlandKuopioFinland
| | - Johanna Kuusisto
- Institute of Clinical MedicineInternal Medicineand Kuopio University HospitalUniversity of Eastern FinlandKuopioFinland
| | - Markku Laakso
- Institute of Clinical MedicineInternal Medicineand Kuopio University HospitalUniversity of Eastern FinlandKuopioFinland
| | - Hilkka Soininen
- Institute of Clinical Medicine, NeurologyUniversity of Eastern FinlandKuopioFinland
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
| | - Henrik Zetterberg
- Clinical Neurochemistry Lab, Institute of Neuroscience and PhysiologySahlgrenska University HospitalMölndalSweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and PhysiologyUniversity of GothenburgMölndalSweden
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyLondonUK
- UK Dementia Research InstituteLondonUK
| | - Charlotte E. Teunissen
- Neurochemistry Lab, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMCVrije UniversiteitAmsterdamthe Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
- Alzheimer Center Limburg, School for Mental Health and NeuroscienceMaastricht UniversityMaastrichtthe Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of NeurogeriatricsKarolinska InstitutetStockholmSweden
| | - Betty M. Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMCVrije Universiteit AmsterdamAmsterdamthe Netherlands
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12
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Wang J, Ma SF, Yun Q, Liu WJ, Zhai HR, Shi HZ, Xie LG, Qian JJ, Zhao CJ, Zhang WN. FOXG1 as a Potential Therapeutic Target for Alzheimer's Disease with a Particular Focus on Cell Cycle Regulation. J Alzheimers Dis 2022; 86:1255-1273. [PMID: 35180113 DOI: 10.3233/jad-215144] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND Several recent findings have revealed that targeting of cell cycle reentry and (or) progression may provide an opportunity for the therapeutic intervention of Alzheimer's disease (AD). FOXG1 has been shown to play important roles in pattern formation, cell proliferation, and cell specification. Thus far, the roles of FoxG1 and its involvement in AD are largely unknown. OBJECTIVE Our study aimed to explore the intervention effect of FOXG1 on AD pathology and its potential mechanism with a particular focus on cell cycle regulation. METHODS We investigated the association of Foxg1 gene variants with AD-like behavioral deficits, p21 expression, neuronal apoptosis, and amyloid-β (Aβ) aggregate formation; we further determined whether targeting FOXG1-regulated cell cycle has therapeutic potential in AD. RESULTS Paralleling AD-like behavioral abnormalities, neuronal apoptosis, and Aβ deposits, a significant reduction in the expression of FOXG1 was observed in APP/PS1 mice at 6 months of age. Using the APP/PS1;Foxg1fl/fl-CreAAV mouse line, we found that FOXG1 potentially antagonized cell cycle reentry by negatively regulating the levels of p21-activated kinase (PAK3). By reducing p21cip1-mediated arrest at the G2 stage and regulating cyclin A1- and cyclin B-dependent progression patterns of the cell cycle, FOXG1 blocked neuronal apoptosis and Aβ deposition. CONCLUSION These results indicate that FOXG1 contributes to the regulation of the neuronal cell cycle, thereby affecting brain abnormalities in AD. An elevation of the FOXG1 level, either pharmacologically or through other means, could present a therapeutic strategy for AD.
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Affiliation(s)
- Jia Wang
- The Fourth Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu Province, China.,School of Medicine, Jiangsu University, Zhenjiang, Jiangsu Province, China
| | - Si-Fei Ma
- School of Medicine, Jiangsu University, Zhenjiang, Jiangsu Province, China.,Changzhou Blood Center, Changzhou, Jiangsu Province, PR China
| | - Qi Yun
- School of Medicine, Jiangsu University, Zhenjiang, Jiangsu Province, China.,Changzhou Children's Hospital, Changzhou, Jiangsu Province, China
| | - Wen-Jun Liu
- School of Medicine, Jiangsu University, Zhenjiang, Jiangsu Province, China
| | - Hong-Ru Zhai
- School of Medicine, Jiangsu University, Zhenjiang, Jiangsu Province, China
| | - Hou-Zhen Shi
- School of Medicine, Jiangsu University, Zhenjiang, Jiangsu Province, China
| | - Lan-Gui Xie
- School of Chemistry and Materials Science, Jiangsu Collaborative Innovation Center of Biomedical Functional Materials, Nanjing Normal University, Nanjing, Jiangsu Province, China
| | - Jin-Jun Qian
- The Fourth Affiliated Hospital of Jiangsu University, Zhenjiang, Jiangsu Province, China
| | - Chun-Jie Zhao
- Key Laboratory of Developmental Genes and Human Diseases, MOE, School of Medicine, Southeast University, Nanjing, Jiangsu Province, China
| | - Wei-Ning Zhang
- School of Medicine, Jiangsu University, Zhenjiang, Jiangsu Province, China
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13
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Zhang X, Farrell JJ, Tong T, Hu J, Zhu C, Wang L, Mayeux R, Haines JL, Pericak‐Vance MA, Schellenberg GD, Lunetta KL, Farrer LA. Association of mitochondrial variants and haplogroups identified by whole exome sequencing with Alzheimer's disease. Alzheimers Dement 2022; 18:294-306. [PMID: 34152079 PMCID: PMC8764625 DOI: 10.1002/alz.12396] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2020] [Revised: 05/03/2021] [Accepted: 05/04/2021] [Indexed: 12/30/2022]
Abstract
INTRODUCTION Findings regarding the association between mitochondrial DNA (mtDNA) variants and Alzheimer's disease (AD) are inconsistent. METHODS We developed a pipeline for accurate assembly and variant calling in mitochondrial genomes embedded within whole exome sequences (WES) from 10,831 participants from the Alzheimer's Disease Sequencing Project (ADSP). Association of AD risk was evaluated with each mtDNA variant and variants located in 1158 nuclear genes related to mitochondrial function using the SCORE test. Gene-based tests were performed using SKAT-O. RESULTS Analysis of 4220 mtDNA variants revealed study-wide significant association of AD with a rare MT-ND4L variant (rs28709356 C>T; minor allele frequency = 0.002; P = 7.3 × 10-5 ) as well as with MT-ND4L in a gene-based test (P = 6.71 × 10-5 ). Significant association was also observed with a MT-related nuclear gene, TAMM41, in a gene-based test (P = 2.7 × 10-5 ). The expression of TAMM41 was lower in AD cases than controls (P = .00046) or mild cognitive impairment cases (P = .03). DISCUSSION Significant findings in MT-ND4L and TAMM41 provide evidence for a role of mitochondria in AD.
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Affiliation(s)
- Xiaoling Zhang
- Department of Medicine (Biomedical Genetics)Boston University School of Medicine72 East Concord StreetBostonMassachusetts02118USA
- Department of BiostatisticsBoston University School of Public Health801 Massachusetts Avenue 3rd FloorBostonMassachusetts02118USA
| | - John J. Farrell
- Department of Medicine (Biomedical Genetics)Boston University School of Medicine72 East Concord StreetBostonMassachusetts02118USA
| | - Tong Tong
- Department of Medicine (Biomedical Genetics)Boston University School of Medicine72 East Concord StreetBostonMassachusetts02118USA
| | - Junming Hu
- Department of Medicine (Biomedical Genetics)Boston University School of Medicine72 East Concord StreetBostonMassachusetts02118USA
| | - Congcong Zhu
- Department of Medicine (Biomedical Genetics)Boston University School of Medicine72 East Concord StreetBostonMassachusetts02118USA
| | | | - Li‐San Wang
- Department of Pathology and Laboratory MedicineUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvania19104USA
| | - Richard Mayeux
- Department of NeurologyColumbia UniversityNew YorkNew York10032USA
| | - Jonathan L. Haines
- Department of Population and Quantitative Health Sciences Case Western Reserve UniversityClevelandOhio44106USA
| | | | - Gerard D. Schellenberg
- Department of Pathology and Laboratory MedicineUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPennsylvania19104USA
| | - Kathryn L. Lunetta
- Department of BiostatisticsBoston University School of Public Health801 Massachusetts Avenue 3rd FloorBostonMassachusetts02118USA
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics)Boston University School of Medicine72 East Concord StreetBostonMassachusetts02118USA
- Department of BiostatisticsBoston University School of Public Health801 Massachusetts Avenue 3rd FloorBostonMassachusetts02118USA
- Department of NeurologyBoston University School of MedicineBostonMassachusetts02118USA
- Department of OphthalmologyBoston University School of MedicineBostonMassachusetts02118USA
- Department of EpidemiologyBoston University School of Public Health715 Albany StreetBostonMassachusetts02118USA
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14
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Abstract
Alzheimer's disease (AD) is a complex and multifactorial neurodegenerative disease. Due to its long clinical course and lack of an effective treatment, AD has become a major public health problem in the USA and worldwide. Due to variation in age-at-onset, AD is classified into early-onset (< 60 years) and late-onset (≥ 60 years) forms with early-onset accounting for only 5-10% of all cases. With the exception of a small number of early-onset cases that are afflicted because of high penetrant single gene mutations in APP, PSEN1, and PSEN2 genes, AD is genetically heterogeneous, especially the late-onset form having a polygenic or oligogenic risk inheritance. Since the identification of APOE as the most significant risk factor for late-onset AD in 1993, the path to the discovery of additional AD risk genes had been arduous until 2009 when the use of large genome-wide association studies opened up the discovery gateways that led the identification of ~ 95 additional risk loci from 2009 to early 2022. This article reviews the history of AD genetics followed by the potential molecular pathways and recent application of functional genomics methods to identify the causal AD gene(s) among the many genes that reside within a single locus. The ultimate goal of integrating genomics and functional genomics is to discover novel pathways underlying the AD pathobiology in order to identify drug targets for the therapeutic treatment of this heterogeneous disorder.
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Affiliation(s)
- M Ilyas Kamboh
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
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15
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Prokopenko D, Lee S, Hecker J, Mullin K, Morgan S, Katsumata Y, Weiner MW, Fardo DW, Laird N, Bertram L, Hide W, Lange C, Tanzi RE. Region-based analysis of rare genomic variants in whole-genome sequencing datasets reveal two novel Alzheimer's disease-associated genes: DTNB and DLG2. Mol Psychiatry 2022; 27:1963-1969. [PMID: 35246634 PMCID: PMC9126808 DOI: 10.1038/s41380-022-01475-0] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 01/25/2022] [Accepted: 02/04/2022] [Indexed: 01/01/2023]
Abstract
Alzheimer's disease (AD) is a genetically complex disease for which nearly 40 loci have now been identified via genome-wide association studies (GWAS). We attempted to identify groups of rare variants (alternate allele frequency <0.01) associated with AD in a region-based, whole-genome sequencing (WGS) association study (rvGWAS) of two independent AD family datasets (NIMH/NIA; 2247 individuals; 605 families). Employing a sliding window approach across the genome, we identified several regions that achieved association p values <10-6, using the burden test or the SKAT statistic. The genomic region around the dystobrevin beta (DTNB) gene was identified with the burden and SKAT test and replicated in case/control samples from the ADSP study reaching genome-wide significance after meta-analysis (pmeta = 4.74 × 10-8). SKAT analysis also revealed region-based association around the Discs large homolog 2 (DLG2) gene and replicated in case/control samples from the ADSP study (pmeta = 1 × 10-6). In conclusion, in a region-based rvGWAS of AD we identified two novel AD genes, DLG2 and DTNB, based on association with rare variants.
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Affiliation(s)
- Dmitry Prokopenko
- grid.32224.350000 0004 0386 9924Genetics and Aging Research Unit and The Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
| | - Sanghun Lee
- grid.411982.70000 0001 0705 4288Department of Medical Consilience, Graduate School, Dankook University, Yongin, South Korea ,grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Julian Hecker
- grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA ,grid.62560.370000 0004 0378 8294Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, MA USA
| | - Kristina Mullin
- grid.32224.350000 0004 0386 9924Genetics and Aging Research Unit and The Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA USA
| | - Sarah Morgan
- grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA ,grid.239395.70000 0000 9011 8547Department of Pathology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA USA
| | - Yuriko Katsumata
- grid.266539.d0000 0004 1936 8438Department of Biostatistics, University of Kentucky, Lexington, KY USA ,grid.266539.d0000 0004 1936 8438Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY USA
| | | | - Michael W. Weiner
- grid.266102.10000 0001 2297 6811Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA USA
| | - David W. Fardo
- grid.266539.d0000 0004 1936 8438Department of Biostatistics, University of Kentucky, Lexington, KY USA ,grid.266539.d0000 0004 1936 8438Sanders-Brown Center on Aging, University of Kentucky, Lexington, KY USA
| | - Nan Laird
- grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Lars Bertram
- grid.4562.50000 0001 0057 2672Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany ,grid.5510.10000 0004 1936 8921Department of Psychology, University of Oslo, Oslo, Norway
| | - Winston Hide
- grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA ,grid.239395.70000 0000 9011 8547Department of Pathology, Beth Israel Deaconess Medical Center, 330 Brookline Avenue, Boston, MA USA
| | - Christoph Lange
- grid.38142.3c000000041936754XDepartment of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA USA
| | - Rudolph E. Tanzi
- grid.32224.350000 0004 0386 9924Genetics and Aging Research Unit and The Henry and Allison McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA USA ,grid.38142.3c000000041936754XHarvard Medical School, Boston, MA USA
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16
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Xue D, Bush WS, Renton AE, Marcora EA, Bis JC, Kunkle BW, Boerwinkle E, DeStefano AL, Farrer L, Goate A, Mayeux R, Pericak‐Vance M, Schellenberg G, Seshadri S, Wijsman E, Haines JL, Blue EE. Large-scale sequencing studies expand the known genetic architecture of Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12255. [PMID: 35005195 PMCID: PMC8720139 DOI: 10.1002/dad2.12255] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/09/2021] [Accepted: 09/21/2021] [Indexed: 11/12/2022]
Abstract
INTRODUCTION Genes implicated by genome-wide association studies and family-based studies of Alzheimer's disease (AD) are largely discordant. We hypothesized that genes identified by sequencing studies like the Alzheimer's Disease Sequencing Project (ADSP) may bridge this gap and highlight shared biological mechanisms. METHODS We performed structured literature review of genes prioritized by ADSP studies, genes underlying familial dementias, and genes nominated by genome-wide association studies. Gene set enrichment analyses of each list identified enriched pathways. RESULTS The genes prioritized by the ADSP, familial dementia studies, and genome-wide association studies minimally overlapped. Each gene set identified dozens of enriched pathways, several of which were shared (e.g., regulation of amyloid beta clearance). DISCUSSION Alternative study designs provide unique insights into AD genetics. Shared pathways enriched by different genes highlight their relevance to AD pathogenesis, while the patterns of pathway enrichment unique to each gene set provide additional targets for functional studies.
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Affiliation(s)
- Diane Xue
- Institute for Public Health GeneticsUniversity of WashingtonSeattleWashingtonUSA
| | - William S. Bush
- Department of Population and Quantitative Health Sciences and Department of Genetics and Genome SciencesCase Western Reserve UniversityClevelandOhioUSA
- Cleveland Institute for Computational BiologyClevelandOhioUSA
| | - Alan E. Renton
- Department of Genetics and Genomic SciencesNash Family Department of Neuroscienceand Ronald M. Loeb Center for Alzheimer's DiseaseIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Edoardo A. Marcora
- Department of Genetics and Genomic SciencesNash Family Department of Neuroscienceand Ronald M. Loeb Center for Alzheimer's DiseaseIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
| | - Joshua C. Bis
- Cardiovascular Health Research UnitDepartment of MedicineUniversity of WashingtonSeattleWashingtonUSA
| | - Brian W. Kunkle
- The John P. Hussman Institute for Human GenomicsUniversity of MiamiMiamiFloridaUSA
- Dr. John T Macdonald Foundation Department of Human GeneticsMiller School of MedicineUniversity of MiamiMiamiFloridaUSA
| | | | - Eric Boerwinkle
- Human Genome Sequencing CenterDepartment of Molecular and Human GeneticsBaylor College of MedicineHoustonTexasUSA
- School of Public HealthUniversity of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Anita L. DeStefano
- Department of BiostatisticsBoston UniversityBostonMassachusettsUSA
- Department of NeurologyBoston UniversityBostonMassachusettsUSA
| | - Lindsay Farrer
- Department of BiostatisticsBoston UniversityBostonMassachusettsUSA
- Department of NeurologyBoston UniversityBostonMassachusettsUSA
- Division of Biomedical GeneticsDepartment of MedicineDepartment of Epidemiologyand Department of OphthalmologyBoston UniversityBostonMassachusettsUSA
| | - Alison Goate
- Department of Genetics and Genomic SciencesNash Family Department of Neuroscienceand Ronald M. Loeb Center for Alzheimer's DiseaseIcahn School of Medicine at Mount SinaiNew YorkNew YorkUSA
- Department of Genetics and Genomics Sciences and Friedman Brain InstituteMount Sinai School of MedicineNew YorkNew YorkUSA
| | - Richard Mayeux
- Taub Institute for Research on Alzheimer's Disease and the Aging BrainGertrude H. Sergievsky CenterDepartment of NeurologyDepartment of Psychiatryand EpidemiologyColumbia UniversityNew YorkNew YorkUSA
| | - Margaret Pericak‐Vance
- The John P. Hussman Institute for Human GenomicsUniversity of MiamiMiamiFloridaUSA
- Dr. John T Macdonald Foundation Department of Human GeneticsMiller School of MedicineUniversity of MiamiMiamiFloridaUSA
| | - Gerard Schellenberg
- Penn Neurodegeneration Genomics CenterDepartment of Pathology and Laboratory MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases and Department of NeurologyUniversity of Texas Health Science CenterSan AntonioTexasUSA
| | - Ellen Wijsman
- Institute for Public Health GeneticsUniversity of WashingtonSeattleWashingtonUSA
- Division of Medical GeneticsUniversity of WashingtonSeattleWashingtonUSA
- Department of BiostatisticsUniversity of WashingtonSeattleWashingtonUSA
| | - Jonathan L. Haines
- Department of Population and Quantitative Health Sciences and Department of Genetics and Genome SciencesCase Western Reserve UniversityClevelandOhioUSA
- Cleveland Institute for Computational BiologyClevelandOhioUSA
| | - Elizabeth E. Blue
- Institute for Public Health GeneticsUniversity of WashingtonSeattleWashingtonUSA
- Division of Medical GeneticsUniversity of WashingtonSeattleWashingtonUSA
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17
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Ma Y, Yu L, Olah M, Smith R, Oatman SR, Allen M, Pishva E, Zhang B, Menon V, Ertekin-Taner N, Lunnon K, Bennett DA, Klein HU, De Jager PL. Epigenomic features related to microglia are associated with attenuated effect of APOE ε4 on Alzheimer's disease risk in humans. Alzheimers Dement 2021; 18:688-699. [PMID: 34482628 DOI: 10.1002/alz.12425] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2020] [Revised: 05/07/2021] [Accepted: 05/12/2021] [Indexed: 11/10/2022]
Abstract
Not all apolipoprotein E (APOE) ε4 carriers who survive to advanced age develop Alzheimer's disease (AD); factors attenuating the risk of ε4 on AD may exist. Guided by the top ε4-attenuating signals from methylome-wide association analyses (N = 572, ε4+ and ε4-) of neurofibrillary tangles and neuritic plaques, we conducted a meta-analysis for pathological AD within the ε4+ subgroups (N = 235) across four independent collections of brains. Cortical RNA-seq and microglial morphology measurements were used in functional analyses. Three out of the four significant CpG dinucleotides were captured by one principal component (PC1), which interacts with ε4 on AD, and is associated with expression of innate immune genes and activated microglia. In ε4 carriers, reduction in each unit of PC1 attenuated the odds of AD by 58% (odds ratio = 2.39, 95% confidence interval = [1.64,3.46], P = 7.08 × 10-6 ). An epigenomic factor associated with a reduced proportion of activated microglia (epigenomic factor of activated microglia, EFAM) appears to attenuate the risk of ε4 on AD.
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Affiliation(s)
- Yiyi Ma
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, New York, USA
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA.,Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Marta Olah
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, New York, USA
| | - Rebecca Smith
- College of Medicine and Health, University of Exeter Medical School, Exeter University, Exeter, UK
| | - Stephanie R Oatman
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, Florida, USA
| | - Mariet Allen
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, Florida, USA
| | - Ehsan Pishva
- College of Medicine and Health, University of Exeter Medical School, Exeter University, Exeter, UK
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Vilas Menon
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, New York, USA
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, Florida, USA.,Department of Neurology, Mayo Clinic Florida, Jacksonville, Florida, USA
| | - Katie Lunnon
- College of Medicine and Health, University of Exeter Medical School, Exeter University, Exeter, UK
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, USA.,Department of Neurological Sciences, Rush University Medical Center, Chicago, Illinois, USA
| | - Hans-Ulrich Klein
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, New York, USA
| | - Philip L De Jager
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, New York, USA.,Cell Circuits Program, Broad Institute, Cambridge, Massachusetts, USA
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18
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Kang S, Gim J, Lee J, Gunasekaran TI, Choi KY, Lee JJ, Seo EH, Ko PW, Chung JY, Choi SM, Lee YM, Jeong JH, Park KW, Song MK, Lee HW, Kim KW, Choi SH, Lee DY, Kim SY, Kim H, Kim BC, Ikeuchi T, Lee KH. Potential Novel Genes for Late-Onset Alzheimer's Disease in East-Asian Descent Identified by APOE-Stratified Genome-Wide Association Study. J Alzheimers Dis 2021; 82:1451-1460. [PMID: 34151794 PMCID: PMC8461686 DOI: 10.3233/jad-210145] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
The present study reports two novel genome-wide significant loci for late-onset Alzheimer’s disease (LOAD) identified from APOE ε4 non-carrier subjects of East Asian origin. A genome-wide association study of Alzheimer’s disease was performed in 2,291 Korean seniors in the discovery phase, from the Gwangju Alzheimer’ and Related Dementias (GARD) cohort study. The study was replicated in a Japanese cohort of 1,956 subjects that suggested two novel susceptible SNPs in two genes: LRIG1 and CACNA1A. This study demonstrates that the discovery of AD-associated variants is feasible in non-European ethnic groups using samples comprising fewer subjects from the more homogeneous genetic background.
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Affiliation(s)
- Sarang Kang
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Integrative Biological Sciences, Chosun University, Gwangju, Republic of Korea
| | - Jungsoo Gim
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Integrative Biological Sciences, Chosun University, Gwangju, Republic of Korea.,Neurozen Inc., Seoul, Republic of Korea.,Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea
| | - Jiwoon Lee
- Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea
| | - Tamil Iniyan Gunasekaran
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea
| | - Kyu Yeong Choi
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea
| | - Jang Jae Lee
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea
| | - Eun Hyun Seo
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Premedical Science, Chosun University College of Medicine, Gwangju, Republic of Korea
| | - Pan-Woo Ko
- Department of Neurology, Kyungpook National University School of Medicine, Daegu, Republic of Korea
| | - Ji Yeon Chung
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Neurology, Chosun University Hospital, Gwangju, Republic of Korea
| | - Seong-Min Choi
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Neurology, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Young Min Lee
- Department of Psychiatry, Pusan National University School of Medicine, Busan, Republic of Korea
| | - Jee Hyang Jeong
- Department of Neurology, Ewha Womans University Mokdong Hospital, Ewha WomansUniversity School of Medicine, Seoul, Republic of Korea
| | - Kyung Won Park
- Department of Neurology, Donga University College of Medicine, Busan, Republic of Korea
| | - Min Kyung Song
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Chonnam National University Gwangju 2nd Geriatric Hospital, Gwangju, Republic of Korea
| | - Ho-Won Lee
- Department of Neurology, Kyungpook National University School of Medicine, Daegu, Republic of Korea
| | - Ki Woong Kim
- Department of Neuropsychiatry, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Seong Hye Choi
- Department of Neurology, Inha University School of Medicine, Incheon, Republic of Korea
| | - Dong Young Lee
- Department of Neuropsychiatry, Seoul National University Hospital, Seoul, Republic of Korea
| | - Sang Yun Kim
- Department of Neurology, Seoul National University Bundang Hospital, Seongnam, Republic of Korea
| | - Hoowon Kim
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Neurology, Chosun University Hospital, Gwangju, Republic of Korea
| | - Byeong C Kim
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Neurology, Chonnam National University Medical School, Gwangju, Republic of Korea
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Kun Ho Lee
- Gwangju Alzheimer's & Related Dementias Cohort Research Center, Chosun University, Gwangju, Republic of Korea.,Department of Integrative Biological Sciences, Chosun University, Gwangju, Republic of Korea.,Neurozen Inc., Seoul, Republic of Korea.,Department of Biomedical Science, Chosun University, Gwangju, Republic of Korea.,Korea Brain Research Institute, Daegu, Republic of Korea
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19
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Monk B, Rajkovic A, Petrus S, Rajkovic A, Gaasterland T, Malinow R. A Machine Learning Method to Identify Genetic Variants Potentially Associated With Alzheimer's Disease. Front Genet 2021; 12:647436. [PMID: 34194466 PMCID: PMC8238203 DOI: 10.3389/fgene.2021.647436] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2020] [Accepted: 04/06/2021] [Indexed: 01/17/2023] Open
Abstract
There is hope that genomic information will assist prediction, treatment, and understanding of Alzheimer's disease (AD). Here, using exome data from ∼10,000 individuals, we explore machine learning neural network (NN) methods to estimate the impact of SNPs (i.e., genetic variants) on AD risk. We develop an NN-based method (netSNP) that identifies hundreds of novel potentially protective or at-risk AD-associated SNPs (along with an effect measure); the majority with frequency under 0.01. For case individuals, the number of "protective" (or "at-risk") netSNP-identified SNPs in their genome correlates positively (or inversely) with their age of AD diagnosis and inversely (or positively) with autopsy neuropathology. The effect measure increases correlations. Simulations suggest our results are not due to genetic linkage, overfitting, or bias introduced by netSNP. These findings suggest that netSNP can identify SNPs associated with AD pathophysiology that may assist with the diagnosis and mechanistic understanding of the disease.
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Affiliation(s)
- Bradley Monk
- Department of Neurosciences, Center for Neural Circuits and Behavior, School of Medicine, University of California, San Diego, San Diego, CA, United States
- Cognitive Science & Psychology IDP, University of California, San Diego, San Diego, CA, United States
| | - Andrei Rajkovic
- Department of Computer Science, Royal Holloway, University of London, Egham, United Kingdom
| | - Semar Petrus
- Institute for Genomic Medicine, Scripps Institution of Oceanography, University of California, San Diego, San Diego, CA, United States
| | - Aleks Rajkovic
- Department of Pathology, Department of Obstetrics, Gynecology and Reproductive Sciences, University of California, San Francisco, San Francisco, CA, United States
| | - Terry Gaasterland
- Institute for Genomic Medicine, Scripps Institution of Oceanography, University of California, San Diego, San Diego, CA, United States
| | - Roberto Malinow
- Department of Neurosciences, Center for Neural Circuits and Behavior, School of Medicine, University of California, San Diego, San Diego, CA, United States
- Section of Neurobiology, Division of Biological Sciences, University of California, San Diego, San Diego, CA, United States
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20
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Novel Alzheimer's disease risk variants identified based on whole-genome sequencing of APOE ε4 carriers. Transl Psychiatry 2021; 11:296. [PMID: 34011927 PMCID: PMC8134477 DOI: 10.1038/s41398-021-01412-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/08/2021] [Revised: 04/16/2021] [Accepted: 04/22/2021] [Indexed: 02/01/2023] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disease associated with a complex genetic etiology. Besides the apolipoprotein E ε4 (APOE ε4) allele, a few dozen other genetic loci associated with AD have been identified through genome-wide association studies (GWAS) conducted mainly in individuals of European ancestry. Recently, several GWAS performed in other ethnic groups have shown the importance of replicating studies that identify previously established risk loci and searching for novel risk loci. APOE-stratified GWAS have yielded novel AD risk loci that might be masked by, or be dependent on, APOE alleles. We performed whole-genome sequencing (WGS) on DNA from blood samples of 331 AD patients and 169 elderly controls of Korean ethnicity who were APOE ε4 carriers. Based on WGS data, we designed a customized AD chip (cAD chip) for further analysis on an independent set of 543 AD patients and 894 elderly controls of the same ethnicity, regardless of their APOE ε4 allele status. Combined analysis of WGS and cAD chip data revealed that SNPs rs1890078 (P = 6.64E-07) and rs12594991 (P = 2.03E-07) in SORCS1 and CHD2 genes, respectively, are novel genetic variants among APOE ε4 carriers in the Korean population. In addition, nine possible novel variants that were rare in individuals of European ancestry but common in East Asia were identified. This study demonstrates that APOE-stratified analysis is important for understanding the genetic background of AD in different populations.
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21
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La Cognata V, Morello G, Cavallaro S. Omics Data and Their Integrative Analysis to Support Stratified Medicine in Neurodegenerative Diseases. Int J Mol Sci 2021; 22:ijms22094820. [PMID: 34062930 PMCID: PMC8125201 DOI: 10.3390/ijms22094820] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Revised: 04/23/2021] [Accepted: 04/29/2021] [Indexed: 12/17/2022] Open
Abstract
Molecular and clinical heterogeneity is increasingly recognized as a common characteristic of neurodegenerative diseases (NDs), such as Alzheimer's disease, Parkinson's disease and amyotrophic lateral sclerosis. This heterogeneity makes difficult the development of early diagnosis and effective treatment approaches, as well as the design and testing of new drugs. As such, the stratification of patients into meaningful disease subgroups, with clinical and biological relevance, may improve disease management and the development of effective treatments. To this end, omics technologies-such as genomics, transcriptomics, proteomics and metabolomics-are contributing to offer a more comprehensive view of molecular pathways underlying the development of NDs, helping to differentiate subtypes of patients based on their specific molecular signatures. In this article, we discuss how omics technologies and their integration have provided new insights into the molecular heterogeneity underlying the most prevalent NDs, aiding to define early diagnosis and progression markers as well as therapeutic targets that can translate into stratified treatment approaches, bringing us closer to the goal of personalized medicine in neurology.
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22
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Madrid L, Moreno-Grau S, Ahmad S, González-Pérez A, de Rojas I, Xia R, Martino Adami PV, García-González P, Kleineidam L, Yang Q, Damotte V, Bis JC, Noguera-Perea F, Bellenguez C, Jian X, Marín-Muñoz J, Grenier-Boley B, Orellana A, Ikram MA, Amouyel P, Satizabal CL, Real LM, Antúnez-Almagro C, DeStefano A, Cabrera-Socorro A, Sims R, Van Duijn CM, Boerwinkle E, Ramírez A, Fornage M, Lambert JC, Williams J, Seshadri S, Ried JS, Ruiz A, Saez ME. Multiomics integrative analysis identifies APOE allele-specific blood biomarkers associated to Alzheimer's disease etiopathogenesis. Aging (Albany NY) 2021; 13:9277-9329. [PMID: 33846280 PMCID: PMC8064208 DOI: 10.18632/aging.202950] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Accepted: 03/26/2021] [Indexed: 02/06/2023]
Abstract
Alzheimer's disease (AD) is the most common form of dementia, currently affecting 35 million people worldwide. Apolipoprotein E (APOE) ε4 allele is the major risk factor for sporadic, late-onset AD (LOAD), which comprises over 95% of AD cases, increasing the risk of AD 4-12 fold. Despite this, the role of APOE in AD pathogenesis is still a mystery. Aiming for a better understanding of APOE-specific effects, the ADAPTED consortium analysed and integrated publicly available data of multiple OMICS technologies from both plasma and brain stratified by APOE haplotype (APOE2, APOE3 and APOE4). Combining genome-wide association studies (GWAS) with differential mRNA and protein expression analyses and single-nuclei transcriptomics, we identified genes and pathways contributing to AD in both APOE dependent and independent fashion. Interestingly, we characterised a set of biomarkers showing plasma and brain consistent protein profiles and opposite trends in APOE2 and APOE4 AD cases that could constitute screening tools for a disease that lacks specific blood biomarkers. Beside the identification of APOE-specific signatures, our findings advocate that this novel approach, based on the concordance across OMIC layers and tissues, is an effective strategy for overcoming the limitations of often underpowered single-OMICS studies.
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Affiliation(s)
- Laura Madrid
- Andalusion Bioiformatics Research Centre (CAEBi), Sevilla, Spain
| | - Sonia Moreno-Grau
- Research Center and Memory Clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Shahzad Ahmad
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | | | - Itziar de Rojas
- Research Center and Memory Clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Rui Xia
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Pamela V. Martino Adami
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Medical Faculty, University of Cologne, Cologne, Germany
| | - Pablo García-González
- Research Center and Memory Clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Luca Kleineidam
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Medical Faculty, University of Cologne, Cologne, Germany
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Vincent Damotte
- University Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque Et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, France
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98195, USA
| | - Fuensanta Noguera-Perea
- Unidad de Demencias, Hospital Clínico Universitario Virgen de la Arrixaca, Carretera de Madrid-Cartagena s/n, 30120 El Palmar, Murcia, España
| | - Céline Bellenguez
- University Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque Et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, France
| | - Xueqiu Jian
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Juan Marín-Muñoz
- Unidad de Demencias, Hospital Clínico Universitario Virgen de la Arrixaca, Carretera de Madrid-Cartagena s/n, 30120 El Palmar, Murcia, España
| | - Benjamin Grenier-Boley
- University Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque Et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, France
| | - Adela Orellana
- Research Center and Memory Clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Philippe Amouyel
- University Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque Et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, France
| | - Claudia L. Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX 78229, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
| | - Alzheimer’s Disease Neuroimaging Initiative (ADNI)*
- Andalusion Bioiformatics Research Centre (CAEBi), Sevilla, Spain
- Research Center and Memory Clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Medical Faculty, University of Cologne, Cologne, Germany
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- University Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque Et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, France
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98195, USA
- Unidad de Demencias, Hospital Clínico Universitario Virgen de la Arrixaca, Carretera de Madrid-Cartagena s/n, 30120 El Palmar, Murcia, España
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX 78229, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- Unit of Infectious Diseases and Microbiology, Hospital Universitario de Valme, Sevilla, Spain
- Department of Surgery, Biochemistry and Immunology, University of Malaga, Spain
- Janssen Research and Development, a Division of Janssen Pharmaceutica N.V., Beerse, Belgium
- Division of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- UKDRI@Cardiff, School of Medicine, Cardiff University, Cardiff, UK
- AbbVie Deutschland GmbH & Co. KG, Genomics Research Center, Knollstrasse, Ludwigshafen, Germany
| | - EADI consortium, CHARGE consortium, GERAD consortium, GR@ACE/DEGESCO consortium
- Andalusion Bioiformatics Research Centre (CAEBi), Sevilla, Spain
- Research Center and Memory Clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Medical Faculty, University of Cologne, Cologne, Germany
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- University Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque Et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, France
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98195, USA
- Unidad de Demencias, Hospital Clínico Universitario Virgen de la Arrixaca, Carretera de Madrid-Cartagena s/n, 30120 El Palmar, Murcia, España
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX 78229, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- Unit of Infectious Diseases and Microbiology, Hospital Universitario de Valme, Sevilla, Spain
- Department of Surgery, Biochemistry and Immunology, University of Malaga, Spain
- Janssen Research and Development, a Division of Janssen Pharmaceutica N.V., Beerse, Belgium
- Division of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- UKDRI@Cardiff, School of Medicine, Cardiff University, Cardiff, UK
- AbbVie Deutschland GmbH & Co. KG, Genomics Research Center, Knollstrasse, Ludwigshafen, Germany
| | - Luis Miguel Real
- Unit of Infectious Diseases and Microbiology, Hospital Universitario de Valme, Sevilla, Spain
- Department of Surgery, Biochemistry and Immunology, University of Malaga, Spain
| | - Carmen Antúnez-Almagro
- Unidad de Demencias, Hospital Clínico Universitario Virgen de la Arrixaca, Carretera de Madrid-Cartagena s/n, 30120 El Palmar, Murcia, España
| | - Anita DeStefano
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
| | | | - Rebecca Sims
- Division of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
| | | | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Alfredo Ramírez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Medical Faculty, University of Cologne, Cologne, Germany
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Myriam Fornage
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Jean-Charles Lambert
- University Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque Et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, France
| | - Julie Williams
- Division of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
- UKDRI@Cardiff, School of Medicine, Cardiff University, Cardiff, UK
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX 78229, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
| | - ADAPTED consortium
- Andalusion Bioiformatics Research Centre (CAEBi), Sevilla, Spain
- Research Center and Memory Clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
- Institute of Molecular Medicine and Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Medical Faculty, University of Cologne, Cologne, Germany
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
- University Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE-Facteurs de Risque Et Déterminants Moléculaires des Maladies Liées au Vieillissement, Lille, France
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA 98195, USA
- Unidad de Demencias, Hospital Clínico Universitario Virgen de la Arrixaca, Carretera de Madrid-Cartagena s/n, 30120 El Palmar, Murcia, España
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX 78229, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA 02118, USA
- Unit of Infectious Diseases and Microbiology, Hospital Universitario de Valme, Sevilla, Spain
- Department of Surgery, Biochemistry and Immunology, University of Malaga, Spain
- Janssen Research and Development, a Division of Janssen Pharmaceutica N.V., Beerse, Belgium
- Division of Psychological Medicine and Clinical Neuroscience, School of Medicine, Cardiff University, Cardiff, UK
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- UKDRI@Cardiff, School of Medicine, Cardiff University, Cardiff, UK
- AbbVie Deutschland GmbH & Co. KG, Genomics Research Center, Knollstrasse, Ludwigshafen, Germany
| | - Janina S. Ried
- AbbVie Deutschland GmbH & Co. KG, Genomics Research Center, Knollstrasse, Ludwigshafen, Germany
| | - Agustín Ruiz
- Research Center and Memory Clinic Fundació ACE, Institut Català de Neurociències Aplicades, Universitat Internacional de Catalunya, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
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23
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Qin W, Zhou A, Zuo X, Jia L, Li F, Wang Q, Li Y, Wei Y, Jin H, Cruchaga C, Benitez BA, Jia J. Exome sequencing revealed PDE11A as a novel candidate gene for early-onset Alzheimer's disease. Hum Mol Genet 2021; 30:811-822. [PMID: 33835157 PMCID: PMC8161517 DOI: 10.1093/hmg/ddab090] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 03/25/2021] [Accepted: 03/26/2021] [Indexed: 11/14/2022] Open
Abstract
To identify novel risk genes and better understand the molecular pathway underlying Alzheimer's disease (AD), whole-exome sequencing was performed in 215 early-onset AD (EOAD) patients and 255 unrelated healthy controls of Han Chinese ethnicity. Subsequent validation, computational annotation and in vitro functional studies were performed to evaluate the role of candidate variants in EOAD. We identified two rare missense variants in the phosphodiesterase 11A (PDE11A) gene in individuals with EOAD. Both variants are located in evolutionarily highly conserved amino acids, are predicted to alter the protein conformation and are classified as pathogenic. Furthermore, we found significantly decreased protein levels of PDE11A in brain samples of AD patients. Expression of PDE11A variants and knockdown experiments with specific short hairpin RNA (shRNA) for PDE11A both resulted in an increase of AD-associated Tau hyperphosphorylation at multiple epitopes in vitro. PDE11A variants or PDE11A shRNA also caused increased cyclic adenosine monophosphate (cAMP) levels, protein kinase A (PKA) activation and cAMP response element-binding protein phosphorylation. In addition, pretreatment with a PKA inhibitor (H89) suppressed PDE11A variant-induced Tau phosphorylation formation. This study offers insight into the involvement of Tau phosphorylation via the cAMP/PKA pathway in EOAD pathogenesis and provides a potential new target for intervention.
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Affiliation(s)
- Wei Qin
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Aihong Zhou
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Xiumei Zuo
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Longfei Jia
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Fangyu Li
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Qi Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Ying Li
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Yiping Wei
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Hongmei Jin
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University, St. Louis, MO 63110, USA
- Department of Genetics, Washington University, St. Louis, MO 63110, USA
| | - Bruno A Benitez
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University, St. Louis, MO 63110, USA
| | - Jianping Jia
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
- Beijing Key Laboratory of Geriatric Cognitive Disorders, Capital Medical University, Beijing 10053, China
- Clinical Center for Neurodegenerative Disease and Memory Impairment, Capital Medical University, Beijing 10053, China
- Center of Alzheimer’s Disease, Beijing Institute of Brain Disorders, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing 10053, China
- To whom correspondence should be addressed at: Innovation Center for Neurological Disorders, Xuanwu Hospital, Capital Medical University, 45 Changchun Street, Beijing 100053, P.R. China. Tel: 0086 10 83199449; Fax: 0086 10 83128678; ,
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24
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Weißbach S, Sys S, Hewel C, Todorov H, Schweiger S, Winter J, Pfenninger M, Torkamani A, Evans D, Burger J, Everschor-Sitte K, May-Simera HL, Gerber S. Reliability of genomic variants across different next-generation sequencing platforms and bioinformatic processing pipelines. BMC Genomics 2021; 22:62. [PMID: 33468057 PMCID: PMC7814447 DOI: 10.1186/s12864-020-07362-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2020] [Accepted: 12/30/2020] [Indexed: 12/14/2022] Open
Abstract
Background Next Generation Sequencing (NGS) is the fundament of various studies, providing insights into questions from biology and medicine. Nevertheless, integrating data from different experimental backgrounds can introduce strong biases. In order to methodically investigate the magnitude of systematic errors in single nucleotide variant calls, we performed a cross-sectional observational study on a genomic cohort of 99 subjects each sequenced via (i) Illumina HiSeq X, (ii) Illumina HiSeq, and (iii) Complete Genomics and processed with the respective bioinformatic pipeline. We also repeated variant calling for the Illumina cohorts with GATK, which allowed us to investigate the effect of the bioinformatics analysis strategy separately from the sequencing platform’s impact. Results The number of detected variants/variant classes per individual was highly dependent on the experimental setup. We observed a statistically significant overrepresentation of variants uniquely called by a single setup, indicating potential systematic biases. Insertion/deletion polymorphisms (indels) were associated with decreased concordance compared to single nucleotide polymorphisms (SNPs). The discrepancies in indel absolute numbers were particularly prominent in introns, Alu elements, simple repeats, and regions with medium GC content. Notably, reprocessing sequencing data following the best practice recommendations of GATK considerably improved concordance between the respective setups. Conclusion We provide empirical evidence of systematic heterogeneity in variant calls between alternative experimental and data analysis setups. Furthermore, our results demonstrate the benefit of reprocessing genomic data with harmonized pipelines when integrating data from different studies. Supplementary Information The online version contains supplementary material available at 10.1186/s12864-020-07362-8.
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Affiliation(s)
- Stephan Weißbach
- Institute of Human Genetics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.,Institute of Developmental Biology and Neurobiology, Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Stanislav Sys
- Institute of Human Genetics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Charlotte Hewel
- Institute of Human Genetics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Hristo Todorov
- Institute of Human Genetics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany
| | - Susann Schweiger
- Institute of Human Genetics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.,Leibniz Institute for Resilience Research, Mainz, Germany
| | - Jennifer Winter
- Institute of Human Genetics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.,Leibniz Institute for Resilience Research, Mainz, Germany
| | - Markus Pfenninger
- Department of Molecular Ecology, Senckenberg Biodiversity and Climate Research Centre, Senckenberganlage 25, 60325, Frankfurt am Main, Germany.,Institute for Molecular and Organismic Evolution, Johannes Gutenberg-University Mainz, Johann-Joachim-Becher-Weg 7, 55128, Mainz, Germany.,LOEWE Centre for Translational Biodiversity Genomics, Senckenberg Biodiversity, and Climate Research Centre, Senckenberganlage 25, 60325, Frankfurt am Main, Germany
| | - Ali Torkamani
- Department of Integrative Structural and Computational Biology, Scripps Research Translational Institute, California Campus, San Diego, USA
| | - Doug Evans
- Department of Integrative Structural and Computational Biology, Scripps Research Translational Institute, California Campus, San Diego, USA
| | - Joachim Burger
- Institute of Anthropology, Johannes Gutenberg-University Mainz, Mainz, Germany
| | | | | | - Susanne Gerber
- Institute of Human Genetics, University Medical Center of the Johannes Gutenberg-University Mainz, Mainz, Germany.
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25
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Serrano-Pozo A, Das S, Hyman BT. APOE and Alzheimer's disease: advances in genetics, pathophysiology, and therapeutic approaches. Lancet Neurol 2021; 20:68-80. [PMID: 33340485 PMCID: PMC8096522 DOI: 10.1016/s1474-4422(20)30412-9] [Citation(s) in RCA: 413] [Impact Index Per Article: 137.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/07/2020] [Revised: 10/02/2020] [Accepted: 10/26/2020] [Indexed: 12/14/2022]
Abstract
The APOE ε4 allele remains the strongest genetic risk factor for sporadic Alzheimer's disease and the APOE ε2 allele the strongest genetic protective factor after multiple large scale genome-wide association studies and genome-wide association meta-analyses. However, no therapies directed at APOE are currently available. Although initial studies causally linked APOE with amyloid-β peptide aggregation and clearance, over the past 5 years our understanding of APOE pathogenesis has expanded beyond amyloid-β peptide-centric mechanisms to tau neurofibrillary degeneration, microglia and astrocyte responses, and blood-brain barrier disruption. Because all these pathological processes can potentially contribute to cognitive impairment, it is important to use this new knowledge to develop therapies directed at APOE. Several therapeutic approaches have been successful in mouse models expressing human APOE alleles, including increasing or reducing APOE levels, enhancing its lipidation, blocking the interactions between APOE and amyloid-β peptide, and genetically switching APOE4 to APOE3 or APOE2 isoforms, but translation to human clinical trials has proven challenging.
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Affiliation(s)
- Alberto Serrano-Pozo
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Massachusetts Alzheimer's Disease Research Center, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Sudeshna Das
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Massachusetts Alzheimer's Disease Research Center, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Bradley T Hyman
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA; Massachusetts Alzheimer's Disease Research Center, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA.
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26
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Ma Y, Yu L, Olah M, Smith R, Oatman SR, Allen M, Pishva E, Zhang B, Menon V, Ertekin-Taner N, Lunnon K, Bennett DA, Klein HU, De Jager PL. EPIGENOMIC FEATURES RELATED TO MICROGLIA ARE ASSOCIATED WITH ATTENUATED EFFECT OF APOE ε4 ON ALZHEIMER'S DISEASE RISK IN HUMANS. Alzheimers Dement 2020; 16. [PMID: 34393677 DOI: 10.1002/alz.043533] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Not all APOE ε4 carriers who survive to advanced age develop Alzheimer's disease (AD); factors attenuating the risk of ε4 on AD may exist. Guided by the top ε4-attenuating signals from methylome-wide association analyses (N=572, ε4+ and ε4-) of neurofibrillary tangles and neuritic plaques, we conducted a meta-analysis for pathological AD within the ε4+ subgroups (N=235) across four independent collections of brains. Cortical RNA-seq and microglial morphology measurements were used in functional analyses. Three out of the four significant CpG dinucleotides were captured by one principle component (PC1), which interacts with ε4 on AD, and is associated with expression of innate immune genes and activated microglia. In ε4 carriers, reduction in each unit of PC1 attenuated the odds of AD by 58% (OR=2.39, 95%CI=[1.64,3.46], P=7.08x10-6). An epigenomic factor associated with a reduced proportion of activated microglia (microglial epigenomic factor 1) appears to attenuate the risk of ε4 on AD.
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Affiliation(s)
- Yiyi Ma
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, 630 West 168 street, New York, NY, USA
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA.,Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Marta Olah
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, 630 West 168 street, New York, NY, USA
| | - Rebecca Smith
- University of Exeter Medical School, College of Medicine and Health, Exeter University, Exeter, UK
| | - Stephanie R Oatman
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL 32224, USA
| | - Mariet Allen
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL 32224, USA
| | - Ehsan Pishva
- University of Exeter Medical School, College of Medicine and Health, Exeter University, Exeter, UK
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA.,Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029, USA
| | - Vilas Menon
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, 630 West 168 street, New York, NY, USA
| | - Nilüfer Ertekin-Taner
- Mayo Clinic Florida, Department of Neuroscience, Jacksonville, FL 32224, USA.,Mayo Clinic Florida, Department of Neurology, Jacksonville, FL 32224, USA
| | - Katie Lunnon
- University of Exeter Medical School, College of Medicine and Health, Exeter University, Exeter, UK
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA.,Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Hans-Ulrich Klein
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, 630 West 168 street, New York, NY, USA
| | - Philip L De Jager
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, 630 West 168 street, New York, NY, USA.,Cell Circuits Program, Broad Institute, 415 Main street, Cambridge MA, USA
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27
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Wang Z, Tang Z, Zhu Y, Pettigrew C, Soldan A, Gross A, Albert M. AD risk score for the early phases of disease based on unsupervised machine learning. Alzheimers Dement 2020; 16:1524-1533. [PMID: 32729964 PMCID: PMC7666001 DOI: 10.1002/alz.12140] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2019] [Revised: 05/28/2020] [Accepted: 06/08/2020] [Indexed: 11/06/2022]
Abstract
INTRODUCTION Identifying cognitively normal individuals at high risk for progression to symptomatic Alzheimer's disease (AD) is critical for early intervention. METHODS An AD risk score was derived using unsupervised machine learning. The score was developed using data from 226 cognitively normal individuals and included cerebrospinal fluid, magnetic resonance imaging, and cognitive measures, and validated in an independent cohort. RESULTS Higher baseline AD progression risk scores (hazard ratio = 2.70, P < 0.001) were associated with greater risks of progression to clinical symptoms of mild cognitive impairment (MCI). Baseline scores had an area under the curve of 0.83 (95% confidence interval: 0.75 to 0.91) for identifying subjects who progressed to MCI/dementia within 5 years. The validation procedure, using data from the Alzheimer's Disease Neuroimaging Initiative, demonstrated accuracy of prediction across the AD spectrum. DISCUSSION The derived risk score provides high predictive accuracy for identifying which individuals with normal cognition are likely to show clinical decline due to AD within 5 years.
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Affiliation(s)
- Zheyu Wang
- Division of Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biostatistics, Johns Hopkins University School of Public Health, Baltimore, MD, USA
| | - Zhuojun Tang
- Division of Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Yuxin Zhu
- Division of Biostatistics and Bioinformatics, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Biostatistics, Johns Hopkins University School of Public Health, Baltimore, MD, USA
| | - Corinne Pettigrew
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Anja Soldan
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Alden Gross
- Department of Epidemiology, Johns Hopkins University School of Public Health, Baltimore, MD, USA
- Johns Hopkins University Center on Aging and Health, Baltimore, MD, USA
| | - Marilyn Albert
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - BIOCARD research team and the Alzheimer’s Disease Neuroimaging Initiative
- Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf
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28
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Bellenguez C, Grenier-Boley B, Lambert JC. Genetics of Alzheimer’s disease: where we are, and where we are going. Curr Opin Neurobiol 2020; 61:40-48. [DOI: 10.1016/j.conb.2019.11.024] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2019] [Revised: 11/27/2019] [Accepted: 11/27/2019] [Indexed: 12/31/2022]
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29
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Fossel M. A unified model of dementias and age-related neurodegeneration. Alzheimers Dement 2020; 16:365-383. [PMID: 31943780 DOI: 10.1002/alz.12012] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2019] [Revised: 11/09/2019] [Accepted: 11/25/2019] [Indexed: 12/14/2022]
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