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Altmann A, Aksman LM, Oxtoby NP, Young AL, Alexander DC, Barkhof F, Shoai M, Hardy J, Schott JM. Towards cascading genetic risk in Alzheimer's disease. Brain 2024; 147:2680-2690. [PMID: 38820112 PMCID: PMC11292901 DOI: 10.1093/brain/awae176] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2023] [Revised: 04/22/2024] [Accepted: 05/06/2024] [Indexed: 06/02/2024] Open
Abstract
Alzheimer's disease typically progresses in stages, which have been defined by the presence of disease-specific biomarkers: amyloid (A), tau (T) and neurodegeneration (N). This progression of biomarkers has been condensed into the ATN framework, in which each of the biomarkers can be either positive (+) or negative (-). Over the past decades, genome-wide association studies have implicated ∼90 different loci involved with the development of late-onset Alzheimer's disease. Here, we investigate whether genetic risk for Alzheimer's disease contributes equally to the progression in different disease stages or whether it exhibits a stage-dependent effect. Amyloid (A) and tau (T) status was defined using a combination of available PET and CSF biomarkers in the Alzheimer's Disease Neuroimaging Initiative cohort. In 312 participants with biomarker-confirmed A-T- status, we used Cox proportional hazards models to estimate the contribution of APOE and polygenic risk scores (beyond APOE) to convert to A+T- status (65 conversions). Furthermore, we repeated the analysis in 290 participants with A+T- status and investigated the genetic contribution to conversion to A+T+ (45 conversions). Both survival analyses were adjusted for age, sex and years of education. For progression from A-T- to A+T-, APOE-e4 burden showed a significant effect [hazard ratio (HR) = 2.88; 95% confidence interval (CI): 1.70-4.89; P < 0.001], whereas polygenic risk did not (HR = 1.09; 95% CI: 0.84-1.42; P = 0.53). Conversely, for the transition from A+T- to A+T+, the contribution of APOE-e4 burden was reduced (HR = 1.62; 95% CI: 1.05-2.51; P = 0.031), whereas the polygenic risk showed an increased contribution (HR = 1.73; 95% CI: 1.27-2.36; P < 0.001). The marginal APOE effect was driven by e4 homozygotes (HR = 2.58; 95% CI: 1.05-6.35; P = 0.039) as opposed to e4 heterozygotes (HR = 1.74; 95% CI: 0.87-3.49; P = 0.12). The genetic risk for late-onset Alzheimer's disease unfolds in a disease stage-dependent fashion. A better understanding of the interplay between disease stage and genetic risk can lead to a more mechanistic understanding of the transition between ATN stages and a better understanding of the molecular processes leading to Alzheimer's disease, in addition to opening therapeutic windows for targeted interventions.
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Affiliation(s)
- Andre Altmann
- UCL Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, WC1E 6BT, UK
| | - Leon M Aksman
- Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Neil P Oxtoby
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, WC1E 6BT, UK
| | - Alexandra L Young
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, WC1E 6BT, UK
| | - Daniel C Alexander
- UCL Centre for Medical Image Computing, Department of Computer Science, University College London, London, WC1E 6BT, UK
| | - Frederik Barkhof
- UCL Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, University College London, London, WC1E 6BT, UK
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam, 1081 HV, The Netherlands
| | - Maryam Shoai
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- UK Dementia Research Institute, University College London, London, WC1E 6BT, UK
| | - John Hardy
- UCL Queen Square Institute of Neurology, University College London, London, WC1N 3BG, UK
- UK Dementia Research Institute, University College London, London, WC1E 6BT, UK
| | - Jonathan M Schott
- UK Dementia Research Institute, University College London, London, WC1E 6BT, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, WC1N 3AR, UK
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2
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Ge YJ, Chen SD, Wu BS, Zhang YR, Wang J, He XY, Liu WS, Chen YL, Ou YN, Shen XN, Huang YY, Gan YH, Yang L, Ma LZ, Ma YH, Chen KL, Chen SF, Cui M, Tan L, Dong Q, Zhao QH, Wang YJ, Jia JP, Yu JT. Genome-wide meta-analysis identifies ancestry-specific loci for Alzheimer's disease. Alzheimers Dement 2024. [PMID: 39023044 DOI: 10.1002/alz.14121] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 06/03/2024] [Accepted: 06/10/2024] [Indexed: 07/20/2024]
Abstract
INTRODUCTION Alzheimer's disease (AD) is a devastating neurological disease with complex genetic etiology. Yet most known loci have only identified from the late-onset type AD in populations of European ancestry. METHODS We performed a two-stage genome-wide association study (GWAS) of AD totaling 6878 Chinese and 63,926 European individuals. RESULTS In addition to the apolipoprotein E (APOE) locus, our GWAS of two independent Chinese samples uncovered three novel AD susceptibility loci (KIAA2013, SLC52A3, and TCN2) and a novel ancestry-specific variant within EGFR (rs1815157). More replicated variants were observed in the Chinese (31%) than in the European samples (15%). In combining genome-wide associations and functional annotations, EGFR and TCN2 were prioritized as two of the most biologically significant genes. Phenome-wide Mendelian randomization suggests that high mean corpuscular hemoglobin concentration might protect against AD. DISCUSSION The current study reveals novel AD susceptibility loci, emphasizes the importance of diverse populations in AD genetic research, and advances our understanding of disease etiology. HIGHLIGHTS Loci KIAA2013, SLC52A3, and TCN2 were associated with Alzheimer's disease (AD) in Chinese populations. rs1815157 within the EGFR locus was associated with AD in Chinese populations. The genetic architecture of AD varied between Chinese and European populations. EGFR and TCN2 were prioritized as two of the most biologically significant genes. High mean corpuscular hemoglobin concentrations might have protective effects against AD.
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Affiliation(s)
- Yi-Jun Ge
- 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Shi-Dong Chen
- 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Bang-Sheng 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Ya-Ru Zhang
- 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Jun Wang
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Wei-Shi Liu
- 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Yi-Lin Chen
- 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Xue-Ning Shen
- 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Yu-Yuan Huang
- 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Yi-Han Gan
- 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Liu Yang
- 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Ling-Zhi Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Ya-Hui Ma
- Department of Neurology, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Ke-Liang Chen
- 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Shu-Fen Chen
- 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Mei Cui
- 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Qian-Hua Zhao
- 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
| | - Yan-Jiang Wang
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, China
| | - Jian-Ping Jia
- Innovation Center for Neurological Disorders and Department of Neurology, National Clinical Research Center for Geriatric Diseases, Xuanwu Hospital, Capital Medical University, Beijing, 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, National Center for Neurological Disorders, Fudan University, Shanghai, China
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3
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Fernandez MV, Liu M, Beric A, Johnson M, Cetin A, Patel M, Budde J, Kohlfeld P, Bergmann K, Lowery J, Flynn A, Brock W, Sanchez Montejo B, Gentsch J, Sykora N, Norton J, Gentsch J, Valdez O, Gorijala P, Sanford J, Sun Y, Wang C, Western D, Timsina J, Mangetti Goncalves T, Do AN, Sung YJ, Zhao G, Morris JC, Moulder K, Holtzman DM, Bateman RJ, Karch C, Hassenstab J, Xiong C, Schindler SE, Balls-Berry JJ, Benzinger TLS, Perrin RJ, Denny A, Snider BJ, Stark SL, Ibanez L, Cruchaga C. Genetic and multi-omic resources for Alzheimer disease and related dementia from the Knight Alzheimer Disease Research Center. Sci Data 2024; 11:768. [PMID: 38997326 PMCID: PMC11245521 DOI: 10.1038/s41597-024-03485-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2024] [Accepted: 06/06/2024] [Indexed: 07/14/2024] Open
Abstract
The Knight-Alzheimer Disease Research Center (Knight-ADRC) at Washington University in St. Louis has pioneered and led worldwide seminal studies that have expanded our clinical, social, pathological, and molecular understanding of Alzheimer Disease. Over more than 40 years, research volunteers have been recruited to participate in cognitive, neuropsychologic, imaging, fluid biomarkers, genomic and multi-omic studies. Tissue and longitudinal data collected to foster, facilitate, and support research on dementia and aging. The Genetics and high throughput -omics core (GHTO) have collected of more than 26,000 biological samples from 6,625 Knight-ADRC participants. Samples available include longitudinal DNA, RNA, non-fasted plasma, cerebrospinal fluid pellets, and peripheral blood mononuclear cells. The GHTO has performed deep molecular profiling (genomic, transcriptomic, epigenomic, proteomic, and metabolomic) from large number of brain (n = 2,117), CSF (n = 2,012) and blood/plasma (n = 8,265) samples with the goal of identifying novel risk and protective variants, identify novel molecular biomarkers and causal and druggable targets. Overall, the resources available at GHTO support the increase of our understanding of Alzheimer Disease.
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Affiliation(s)
- Maria Victoria Fernandez
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Research Center and Memory Clinic, ACE Alzheimer Center, Barcelona, Spain
| | - Menghan Liu
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Aleksandra Beric
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Matt Johnson
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Arda Cetin
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Maulik Patel
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - John Budde
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Pat Kohlfeld
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Kristy Bergmann
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Joseph Lowery
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Allison Flynn
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - William Brock
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Brenda Sanchez Montejo
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Jen Gentsch
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Nicholas Sykora
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Joanne Norton
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Jen Gentsch
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Olga Valdez
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Priyanka Gorijala
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Jessie Sanford
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Yichen Sun
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Ciyang Wang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Dan Western
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | | | - Anh N Do
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Guoyan Zhao
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Pathology and Immunology Department, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Krista Moulder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
- Dominantly Inherited Alzheimer Disease Network (DIAN), St. Louis, USA
| | - Celeste Karch
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
- Dominantly Inherited Alzheimer Disease Network (DIAN), St. Louis, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Chengjie Xiong
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Dominantly Inherited Alzheimer Disease Network (DIAN), St. Louis, USA
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Joyce Joy Balls-Berry
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L S Benzinger
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Dominantly Inherited Alzheimer Disease Network (DIAN), St. Louis, USA
- Radiology Department, Washington University School of Medicine, St. Louis, MO, 63110, USA
| | - Richard J Perrin
- Pathology and Immunology Department, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Dominantly Inherited Alzheimer Disease Network (DIAN), St. Louis, USA
| | - Andrea Denny
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - B Joy Snider
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA
| | - Susan L Stark
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
- Occupational Therapy, Neurology and Social Work, St. Louis, USA
| | - Laura Ibanez
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- Dominantly Inherited Alzheimer Disease Network (DIAN), St. Louis, USA.
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA.
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, 63110, USA.
- Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA.
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO, USA.
- Dominantly Inherited Alzheimer Disease Network (DIAN), St. Louis, USA.
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4
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Delvenne A, Gobom J, Schindler SE, Kate MT, Reus LM, Dobricic V, Tijms BM, Benzinger TLS, Cruchaga C, Teunissen CE, Ramakers I, Martinez-Lage P, Tainta M, Vandenberghe R, Schaeverbeke J, Engelborghs S, Roeck ED, Popp J, Peyratout G, Tsolaki M, Freund-Levi Y, Lovestone S, Streffer J, Barkhof F, Bertram L, Blennow K, Zetterberg H, Visser PJ, Vos SJB. CSF proteomic profiles of neurodegeneration biomarkers in Alzheimer's disease. Alzheimers Dement 2024. [PMID: 38970402 DOI: 10.1002/alz.14103] [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: 04/03/2024] [Revised: 06/05/2024] [Accepted: 06/06/2024] [Indexed: 07/08/2024]
Abstract
INTRODUCTION We aimed to unravel the underlying pathophysiology of the neurodegeneration (N) markers neurogranin (Ng), neurofilament light (NfL), and hippocampal volume (HCV), in Alzheimer's disease (AD) using cerebrospinal fluid (CSF) proteomics. METHODS Individuals without dementia were classified as A+ (CSF amyloid beta [Aβ]42), T+ (CSF phosphorylated tau181), and N+ or N- based on Ng, NfL, or HCV separately. CSF proteomics were generated and compared between groups using analysis of covariance. RESULTS Only a few individuals were A+T+Ng-. A+T+Ng+ and A+T+NfL+ showed different proteomic profiles compared to A+T+Ng- and A+T+NfL-, respectively. Both Ng+ and NfL+ were associated with neuroplasticity, though in opposite directions. Compared to A+T+HCV-, A+T+HCV+ showed few proteomic changes, associated with oxidative stress. DISCUSSION Different N markers are associated with distinct neurodegenerative processes and should not be equated. N markers may differentially complement disease staging beyond amyloid and tau. Our findings suggest that Ng may not be an optimal N marker, given its low incongruency with tau pathophysiology. HIGHLIGHTS In Alzheimer's disease, neurogranin (Ng)+, neurofilament light (NfL)+, and hippocampal volume (HCV)+ showed differential protein expression in cerebrospinal fluid. Ng+ and NfL+ were associated with neuroplasticity, although in opposite directions. HCV+ showed few proteomic changes, related to oxidative stress. Neurodegeneration (N) markers may differentially refine disease staging beyond amyloid and tau. Ng might not be an optimal N marker, as it relates more closely to tau.
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Affiliation(s)
- Aurore Delvenne
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Johan Gobom
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA
- Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Mara Ten Kate
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Lianne M Reus
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Valerija Dobricic
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Tammie L S Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, USA
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam University Medical Centers (AUMC), Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Inez Ramakers
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | | | - Mikel Tainta
- Fundación CITA-Alzhéimer Fundazioa, Donostia, Spain
| | - Rik Vandenberghe
- Neurology Service, University Hospitals Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Jolien Schaeverbeke
- Neurology Service, University Hospitals Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Department of Neurology and Bru-BRAIN, Universitair Ziekenhuis Brussel and NEUR Research Group, Center for Neurosciences (C4N), Vrije Universiteit Brussel, Brussels, Belgium
| | - Ellen De Roeck
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Julius Popp
- Old Age Psychiatry, University Hospital Lausanne, Lausanne, Switzerland
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatry University Hospital Zürich, Zürich, Switzerland
| | | | - Magda Tsolaki
- 1st Department of Neurology, AHEPA University Hospital, Medical School, Faculty of Health Sciences, Aristotle University of Thessaloniki, Makedonia, Thessaloniki, Greece
| | - Yvonne Freund-Levi
- Department of Neurobiology, Caring Sciences and Society (NVS), Division of Clinical Geriatrics, Karolinska Institutet, Huddinge, Stockholm, Sweden
- Department of Psychiatry in Region Örebro County and School of Medical Sciences, Faculty of Medicine and Health, Örebro University, Örebro, Sweden
- Department of Old Age Psychiatry, Psychology & Neuroscience, King's College, London, UK
| | - Simon Lovestone
- University of Oxford, United Kingdom (currently at Johnson and Johnson Medical Ltd., Oxford, UK
| | - Johannes Streffer
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- H. Lundbeck A/S, Valby, Denmark
| | - Frederik Barkhof
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, P.R. China
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Pieter Jelle Visser
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Huddinge, Stockholm, Sweden
| | - Stephanie J B Vos
- Department of Psychiatry and Neuropsychology, Alzheimer Centrum Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
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5
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Curtis L, Piggins HD. Diverse genetic alteration dysregulates neuropeptide and intracellular signalling in the suprachiasmatic nuclei. Eur J Neurosci 2024; 60:3921-3945. [PMID: 38924215 DOI: 10.1111/ejn.16443] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Revised: 05/12/2024] [Accepted: 05/31/2024] [Indexed: 06/28/2024]
Abstract
In mammals, intrinsic 24 h or circadian rhythms are primarily generated by the suprachiasmatic nuclei (SCN). Rhythmic daily changes in the transcriptome and proteome of SCN cells are controlled by interlocking transcription-translation feedback loops (TTFLs) of core clock genes and their proteins. SCN cells function as autonomous circadian oscillators, which synchronize through intercellular neuropeptide signalling. Physiological and behavioural rhythms can be severely disrupted by genetic modification of a diverse range of genes and proteins in the SCN. With the advent of next generation sequencing, there is unprecedented information on the molecular profile of the SCN and how it is affected by genetically targeted alteration. However, whether the expression of some genes is more readily affected by genetic alteration of the SCN is unclear. Here, using publicly available datasets from recent RNA-seq assessments of the SCN from genetically altered and control mice, we evaluated whether there are commonalities in transcriptome dysregulation. This was completed for four different phases across the 24 h cycle and was augmented by Gene Ontology Molecular Function (GO:MF) and promoter analysis. Common differentially expressed genes (DEGs) and/or enriched GO:MF terms included signalling molecules, their receptors, and core clock components. Finally, examination of the JASPAR database indicated that E-box and CRE elements in the promoter regions of several commonly dysregulated genes. From this analysis, we identify differential expression of genes coding for molecules involved in SCN intra- and intercellular signalling as a potential cause of abnormal circadian rhythms.
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Affiliation(s)
- Lucy Curtis
- School of Biological Sciences, University of Bristol, Bristol, UK
- School of Physiology, Pharmacology, and Neuroscience, University of Bristol, Bristol, UK
| | - Hugh D Piggins
- School of Physiology, Pharmacology, and Neuroscience, University of Bristol, Bristol, UK
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6
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Narasimhan S, Holtzman DM, Apostolova LG, Cruchaga C, Masters CL, Hardy J, Villemagne VL, Bell J, Cho M, Hampel H. Apolipoprotein E in Alzheimer's disease trajectories and the next-generation clinical care pathway. Nat Neurosci 2024; 27:1236-1252. [PMID: 38898183 DOI: 10.1038/s41593-024-01669-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 04/18/2024] [Indexed: 06/21/2024]
Abstract
Alzheimer's disease (AD) is a complex, progressive primary neurodegenerative disease. Since pivotal genetic studies in 1993, the ε4 allele of the apolipoprotein E gene (APOE ε4) has remained the strongest single genome-wide associated risk variant in AD. Scientific advances in APOE biology, AD pathophysiology and ApoE-targeted therapies have brought APOE to the forefront of research, with potential translation into routine AD clinical care. This contemporary Review will merge APOE research with the emerging AD clinical care pathway and discuss APOE genetic risk as a conduit to genomic-based precision medicine in AD, including ApoE's influence in the ATX(N) biomarker framework of AD. We summarize the evidence for APOE as an important modifier of AD clinical-biological trajectories. We then illustrate the utility of APOE testing and the future of ApoE-targeted therapies in the next-generation AD clinical-diagnostic pathway. With the emergence of new AD therapies, understanding how APOE modulates AD pathophysiology will become critical for personalized AD patient care.
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Affiliation(s)
| | - David M Holtzman
- Department of Neurology, Hope Center for Neurological Disorders, Knight ADRC, Washington University in St. Louis, St. Louis, MO, USA
| | - Liana G Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Radiology and Imaging Neurosciences, Indiana University School of Medicine, Indianapolis, IN, USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Colin L Masters
- Florey Institute and the University of Melbourne, Parkville, Victoria, Australia
| | - John Hardy
- Department of Neurodegenerative Disease and Dementia Research Institute, Reta Lila Weston Research Laboratories, UCL Institute of Neurology, Queen Square, London, UK
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7
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Singh MK, Shin Y, Ju S, Han S, Kim SS, Kang I. Comprehensive Overview of Alzheimer's Disease: Etiological Insights and Degradation Strategies. Int J Mol Sci 2024; 25:6901. [PMID: 39000011 PMCID: PMC11241648 DOI: 10.3390/ijms25136901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 06/19/2024] [Accepted: 06/21/2024] [Indexed: 07/14/2024] Open
Abstract
Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and affects millions of individuals globally. AD is associated with cognitive decline and memory loss that worsens with aging. A statistical report using U.S. data on AD estimates that approximately 6.9 million individuals suffer from AD, a number projected to surge to 13.8 million by 2060. Thus, there is a critical imperative to pinpoint and address AD and its hallmark tau protein aggregation early to prevent and manage its debilitating effects. Amyloid-β and tau proteins are primarily associated with the formation of plaques and neurofibril tangles in the brain. Current research efforts focus on degrading amyloid-β and tau or inhibiting their synthesis, particularly targeting APP processing and tau hyperphosphorylation, aiming to develop effective clinical interventions. However, navigating this intricate landscape requires ongoing studies and clinical trials to develop treatments that truly make a difference. Genome-wide association studies (GWASs) across various cohorts identified 40 loci and over 300 genes associated with AD. Despite this wealth of genetic data, much remains to be understood about the functions of these genes and their role in the disease process, prompting continued investigation. By delving deeper into these genetic associations, novel targets such as kinases, proteases, cytokines, and degradation pathways, offer new directions for drug discovery and therapeutic intervention in AD. This review delves into the intricate biological pathways disrupted in AD and identifies how genetic variations within these pathways could serve as potential targets for drug discovery and treatment strategies. Through a comprehensive understanding of the molecular underpinnings of AD, researchers aim to pave the way for more effective therapies that can alleviate the burden of this devastating disease.
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Affiliation(s)
- Manish Kumar Singh
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of Korea
- Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Yoonhwa Shin
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of Korea
- Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Songhyun Ju
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of Korea
- Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Sunhee Han
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of Korea
- Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Sung Soo Kim
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of Korea
- Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Republic of Korea
| | - Insug Kang
- Department of Biochemistry and Molecular Biology, School of Medicine, Kyung Hee University, Seoul 02447, Republic of Korea
- Biomedical Science Institute, Kyung Hee University, Seoul 02447, Republic of Korea
- Department of Biomedical Science, Graduate School, Kyung Hee University, Seoul 02447, Republic of Korea
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8
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Seo D, Lee CM, Apio C, Heo G, Timsina J, Kohlfeld P, Boada M, Orellana A, Fernandez MV, Ruiz A, Morris JC, Schindler SE, Park T, Cruchaga C, Sung YJ. Sex and aging signatures of proteomics in human cerebrospinal fluid identify distinct clusters linked to neurodegeneration. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.18.24309102. [PMID: 38947020 PMCID: PMC11213043 DOI: 10.1101/2024.06.18.24309102] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Sex and age are major risk factors for chronic diseases. Recent studies examining age-related molecular changes in plasma provided insights into age-related disease biology. Cerebrospinal fluid (CSF) proteomics can provide additional insights into brain aging and neurodegeneration. By comprehensively examining 7,006 aptamers targeting 6,139 proteins in CSF obtained from 660 healthy individuals aged from 43 to 91 years old, we subsequently identified significant sex and aging effects on 5,097 aptamers in CSF. Many of these effects on CSF proteins had different magnitude or even opposite direction as those on plasma proteins, indicating distinctive CSF-specific signatures. Network analysis of these CSF proteins revealed not only modules associated with healthy aging but also modules showing sex differences. Through subsequent analyses, several modules were highlighted for their proteins implicated in specific diseases. Module 2 and 6 were enriched for many aging diseases including those in the circulatory systems, immune mechanisms, and neurodegeneration. Together, our findings fill a gap of current aging research and provide mechanistic understanding of proteomic changes in CSF during a healthy lifespan and insights for brain aging and diseases.
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9
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Yan D, Hu B, Darst BF, Mukherjee S, Kunkle BW, Deming Y, Dumitrescu L, Wang Y, Naj A, Kuzma A, Zhao Y, Kang H, Johnson SC, Carlos C, Hohman TJ, Crane PK, Engelman CD, Lu Q. Biobank-wide association scan identifies risk factors for late-onset Alzheimer's disease and endophenotypes. eLife 2024; 12:RP91360. [PMID: 38787369 PMCID: PMC11126309 DOI: 10.7554/elife.91360] [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: 05/25/2024] Open
Abstract
Rich data from large biobanks, coupled with increasingly accessible association statistics from genome-wide association studies (GWAS), provide great opportunities to dissect the complex relationships among human traits and diseases. We introduce BADGERS, a powerful method to perform polygenic score-based biobank-wide association scans. Compared to traditional approaches, BADGERS uses GWAS summary statistics as input and does not require multiple traits to be measured in the same cohort. We applied BADGERS to two independent datasets for late-onset Alzheimer's disease (AD; n=61,212). Among 1738 traits in the UK biobank, we identified 48 significant associations for AD. Family history, high cholesterol, and numerous traits related to intelligence and education showed strong and independent associations with AD. Furthermore, we identified 41 significant associations for a variety of AD endophenotypes. While family history and high cholesterol were strongly associated with AD subgroups and pathologies, only intelligence and education-related traits predicted pre-clinical cognitive phenotypes. These results provide novel insights into the distinct biological processes underlying various risk factors for AD.
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Affiliation(s)
- Donghui Yan
- University of Wisconsin-MadisonMadisonUnited States
| | - Bowen Hu
- Department of Statistics, University of Wisconsin-MadisonMadisonUnited States
| | - Burcu F Darst
- Department of Population Health Sciences, University of Wisconsin-MadisonMadisonUnited States
| | - Shubhabrata Mukherjee
- Division of General Internal Medicine, Department of Medicine, University of WashingtonSeattleUnited States
| | - Brian W Kunkle
- University of Miami Miller School of MedicineMiamiUnited States
| | - Yuetiva Deming
- Department of Population Health Sciences, University of Wisconsin-MadisonMadisonUnited States
| | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Vanderbilt University School of MedicineNashvilleUnited States
| | - Yunling Wang
- University of Wisconsin-MadisonMadisonUnited States
| | - Adam Naj
- School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Amanda Kuzma
- School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Yi Zhao
- School of Medicine, University of PennsylvaniaPhiladelphiaUnited States
| | - Hyunseung Kang
- Department of Statistics, University of Wisconsin-MadisonMadisonUnited States
| | - Sterling C Johnson
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public HealthMadisonUnited States
- Geriatric Research Education and Clinical Center, Wm. S. Middleton Memorial VA HospitalMadisonUnited States
- Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public HealthMadisonUnited States
| | - Cruchaga Carlos
- Department of Psychiatry, Washington University in St. LouisSt. LouisUnited States
| | - Timothy J Hohman
- Vanderbilt Memory and Alzheimer’s Center, Vanderbilt University Medical Center, Vanderbilt University School of MedicineNashvilleUnited States
| | - Paul K Crane
- Division of General Internal Medicine, Department of Medicine, University of WashingtonSeattleUnited States
| | - Corinne D Engelman
- Department of Population Health Sciences, University of Wisconsin-MadisonMadisonUnited States
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public HealthMadisonUnited States
- Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public HealthMadisonUnited States
| | | | - Qiongshi Lu
- Department of Statistics, University of Wisconsin-MadisonMadisonUnited States
- Department of Biostatistics and Medical Informatics, University of Wisconsin-MadisonMadisonUnited States
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10
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Ramos-Campoy O, Comas-Albertí A, Hervás D, Borrego-Écija S, Bosch B, Sandoval J, Fort-Aznar L, Moreno-Izco F, Fernández-Villullas G, Molina-Porcel L, Balasa M, Lladó A, Sánchez-Valle R, Antonell A. Genome-Wide DNA Methylation in Early-Onset-Dementia Patients Brain Tissue and Lymphoblastoid Cell Lines. Int J Mol Sci 2024; 25:5445. [PMID: 38791483 PMCID: PMC11121630 DOI: 10.3390/ijms25105445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2024] [Revised: 05/08/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
Epigenetics, a potential underlying pathogenic mechanism of neurodegenerative diseases, has been in the scope of several studies performed so far. However, there is a gap in regard to analyzing different forms of early-onset dementia and the use of Lymphoblastoid cell lines (LCLs). We performed a genome-wide DNA methylation analysis on sixty-four samples (from the prefrontal cortex and LCLs) including those taken from patients with early-onset forms of Alzheimer's disease (AD) and frontotemporal dementia (FTD) and healthy controls. A beta regression model and adjusted p-values were used to obtain differentially methylated positions (DMPs) via pairwise comparisons. A correlation analysis of DMP levels with Clariom D array gene expression data from the same cohort was also performed. The results showed hypermethylation as the most frequent finding in both tissues studied in the patient groups. Biological significance analysis revealed common pathways altered in AD and FTD patients, affecting neuron development, metabolism, signal transduction, and immune system pathways. These alterations were also found in LCL samples, suggesting the epigenetic changes might not be limited to the central nervous system. In the brain, CpG methylation presented an inverse correlation with gene expression, while in LCLs, we observed mainly a positive correlation. This study enhances our understanding of the biological pathways that are associated with neurodegeneration, describes differential methylation patterns, and suggests LCLs are a potential cell model for studying neurodegenerative diseases in earlier clinical phases than brain tissue.
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Affiliation(s)
- Oscar Ramos-Campoy
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Aina Comas-Albertí
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - David Hervás
- Department of Applied Statistics and Operations Research and Quality, Universitat Politècnica de València, 46022 Valencia, Spain
| | - Sergi Borrego-Écija
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Beatriz Bosch
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Juan Sandoval
- Epigenomics Core Facility, Health Research Institute La Fe, 46026 Valencia, Spain
| | - Laura Fort-Aznar
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Fermín Moreno-Izco
- Cognitive Disorders Unit, Department of Neurology, Hospital Universitario Donostia, 20014 San Sebastian, Spain
- Instituto de Investigación Sanitaria Biogipuzkoa, Neurosciences Area, Group of Neurodegenerative Diseases, 20014 San Sebastian, Spain
| | - Guadalupe Fernández-Villullas
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Laura Molina-Porcel
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
- Neurological Tissue Bank, Biobank-Hospital Clinic-IDIBAPS, 08036 Barcelona, Spain
| | - Mircea Balasa
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Albert Lladó
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Raquel Sánchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
- Facultat de Medicina i Ciències de la Salut, Institut de Neurociències, Universitat de Barcelona (UB), 08036 Barcelona, Spain
| | - Anna Antonell
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, FRCB-IDIBAPS, Universitat de Barcelona (UB), 08036 Barcelona, Spain
- Facultat de Medicina i Ciències de la Salut, Institut de Neurociències, Universitat de Barcelona (UB), 08036 Barcelona, Spain
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11
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Sampatakakis SN, Mourtzi N, Charisis S, Kalligerou F, Mamalaki E, Ntanasi E, Hatzimanolis A, Koutsis G, Ramirez A, Lambert JC, Yannakoulia M, Kosmidis MH, Dardiotis E, Hadjigeorgiou G, Sakka P, Rouskas K, Patas K, Scarmeas N. Cerebral Amyloidosis in Individuals with Subjective Cognitive Decline: From Genetic Predisposition to Actual Cerebrospinal Fluid Measurements. Biomedicines 2024; 12:1053. [PMID: 38791015 PMCID: PMC11118196 DOI: 10.3390/biomedicines12051053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2024] [Revised: 04/30/2024] [Accepted: 05/09/2024] [Indexed: 05/26/2024] Open
Abstract
The possible relationship between Subjective Cognitive Decline (SCD) and dementia needs further investigation. In the present study, we explored the association between specific biomarkers of Alzheimer's Disease (AD), amyloid-beta 42 (Aβ42) and Tau with the odds of SCD using data from two ongoing studies. In total, 849 cognitively normal (CN) individuals were included in our analyses. Among the participants, 107 had available results regarding cerebrospinal fluid (CSF) Aβ42 and Tau, while 742 had available genetic data to construct polygenic risk scores (PRSs) reflecting their genetic predisposition for CSF Aβ42 and plasma total Tau levels. The associations between AD biomarkers and SCD were tested using logistic regression models adjusted for possible confounders such as age, sex, education, depression, and baseline cognitive test scores. Abnormal values of CSF Aβ42 were related to 2.5-fold higher odds of SCD, while higher polygenic loading for Aβ42 was associated with 1.6-fold higher odds of SCD. CSF Tau, as well as polygenic loading for total Tau, were not associated with SCD. Thus, only cerebral amyloidosis appears to be related to SCD status, either in the form of polygenic risk or actual CSF measurements. The temporal sequence of amyloidosis being followed by tauopathy may partially explain our findings.
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Affiliation(s)
- Stefanos N. Sampatakakis
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (F.K.); (E.M.); (E.N.)
| | - Niki Mourtzi
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (F.K.); (E.M.); (E.N.)
| | - Sokratis Charisis
- Department of Neurology, UT Health San Antonio, San Antonio, TX 78229, USA;
| | - Faidra Kalligerou
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (F.K.); (E.M.); (E.N.)
| | - Eirini Mamalaki
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (F.K.); (E.M.); (E.N.)
| | - Eva Ntanasi
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (F.K.); (E.M.); (E.N.)
| | - Alex Hatzimanolis
- Department of Psychiatry, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece;
| | - Georgios Koutsis
- Neurogenetics Unit, 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece;
| | - Alfredo Ramirez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Medical Faculty, University of Cologne, 50923 Cologne, Germany;
- Department of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, 53127 Bonn, Germany
- German Center for Neurodegenerative Diseases (DZNE Bonn), 53127 Bonn, Germany
- Department of Psychiatry, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, San Antonio, TX 78229, USA
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, 50923 Cologne, Germany
| | - Jean-Charles Lambert
- Inserm, CHU Lille, Institut Pasteur de Lille, U1167-RID-AGE Facteurs de Risque et Déterminants Moléculaires des Maladies Liés au Vieillissement, University of Lille, 59000 Lille, France;
| | - Mary Yannakoulia
- Department of Nutrition and Dietetics, Harokopio University, 17676 Athens, Greece;
| | - Mary H. Kosmidis
- Lab of Neuropsychology and Behavioral Neuroscience, School of Psychology, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece;
| | - Efthimios Dardiotis
- Department of Neurology, University Hospital of Larissa, Faculty of Medicine, School of Health Sciences, University of Thessaly, 41334 Larissa, Greece;
| | | | - Paraskevi Sakka
- Athens Association of Alzheimer’s Disease and Related Disorders, 11636 Marousi, Greece;
| | - Konstantinos Rouskas
- Institute of Applied Biosciences, Centre for Research & Technology Hellas, 54124 Thessaloniki, Greece;
| | - Kostas Patas
- Department of Medical Biopathology and Clinical Microbiology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece;
| | - Nikolaos Scarmeas
- 1st Department of Neurology, Aiginition Hospital, Athens Medical School, National and Kapodistrian University, 11528 Athens, Greece; (S.N.S.); (N.M.); (F.K.); (E.M.); (E.N.)
- Department of Neurology, The Gertrude H. Sergievsky Center, Taub Institute for Research in Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY 10027, USA
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12
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Lai Q, Dannenfelser R, Roussarie JP, Yao V. Disentangling associations between complex traits and cell types with seismic. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.04.592534. [PMID: 38765980 PMCID: PMC11100625 DOI: 10.1101/2024.05.04.592534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Integrating single-cell RNA sequencing (scRNA-seq) with Genome-Wide Association Studies (GWAS) can help reveal GWAS-associated cell types, furthering our understanding of the cell-type-specific biological processes underlying complex traits and disease. However, current methods have technical limitations that hinder them from making systematic, scalable, interpretable disease-cell-type associations. In order to rapidly and accurately pinpoint associations, we develop a novel framework, seismic, which characterizes cell types using a new specificity score. We compare seismic with alternative methods across over 1,000 cell type characterizations at different granularities and 28 traits, demonstrating that seismic both corroborates findings and identifies trait-relevant cell groups which are not apparent through other methodologies. Furthermore, as part of the seismic framework, the specific genes driving cell type-trait associations can easily be accessed and analyzed, enabling further biological insights. The advantages of seismic are particularly salient in neurodegenerative diseases such as Parkinson's and Alzheimer's, where disease pathology has not only cell-specific manifestations, but also brain region-specific differences. Interestingly, a case study of Alzheimer's disease reveals the importance of considering GWAS endpoints, as studies relying on clinical diagnoses consistently identify microglial associations, while GWAS with a tau biomarker endpoint reveals neuronal associations. In general, seismic is a computationally efficient, powerful, and interpretable approach for identifying associations between complex traits and cell type-specific expression.
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Affiliation(s)
- Qiliang Lai
- Department of Computer Science, Rice University
| | | | | | - Vicky Yao
- Department of Computer Science, Rice University
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13
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Malamon JS, Farrell JJ, Xia LC, Dombroski BA, Das RG, Way J, Kuzma AB, Valladares O, Leung YY, Scanlon AJ, Lopez IAB, Brehony J, Worley KC, Zhang NR, Wang LS, Farrer LA, Schellenberg GD, Lee WP, Vardarajan BN. A comparative study of structural variant calling in WGS from Alzheimer's disease families. Life Sci Alliance 2024; 7:e202302181. [PMID: 38418088 PMCID: PMC10902710 DOI: 10.26508/lsa.202302181] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 02/07/2024] [Accepted: 02/08/2024] [Indexed: 03/01/2024] Open
Abstract
Detecting structural variants (SVs) in whole-genome sequencing poses significant challenges. We present a protocol for variant calling, merging, genotyping, sensitivity analysis, and laboratory validation for generating a high-quality SV call set in whole-genome sequencing from the Alzheimer's Disease Sequencing Project comprising 578 individuals from 111 families. Employing two complementary pipelines, Scalpel and Parliament, for SV/indel calling, we assessed sensitivity through sample replicates (N = 9) with in silico variant spike-ins. We developed a novel metric, D-score, to evaluate caller specificity for deletions. The accuracy of deletions was evaluated by Sanger sequencing. We generated a high-quality call set of 152,301 deletions of diverse sizes. Sanger sequencing validated 114 of 146 detected deletions (78.1%). Scalpel excelled in accuracy for deletions ≤100 bp, whereas Parliament was optimal for deletions >900 bp. Overall, 83.0% and 72.5% of calls by Scalpel and Parliament were validated, respectively, including all 11 deletions called by both Parliament and Scalpel between 101 and 900 bp. Our flexible protocol successfully generated a high-quality deletion call set and a truth set of Sanger sequencing-validated deletions with precise breakpoints spanning 1-17,000 bp.
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Affiliation(s)
- John S Malamon
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - John J Farrell
- Biomedical Genetics Section, Department of Medicine, Boston University School of Medicine, Boston University, Boston, MA, USA
| | - Li Charlie Xia
- https://ror.org/03mtd9a03 Division of Oncology, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
| | - Beth A Dombroski
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Rueben G Das
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jessica Way
- Broad Institute, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Amanda B Kuzma
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Otto Valladares
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Yuk Yee Leung
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Allison J Scanlon
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Irving Antonio Barrera Lopez
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Jack Brehony
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kim C Worley
- https://ror.org/02pttbw34 Human Genome Sequencing Center, and Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Nancy R Zhang
- Department of Statistics, The Wharton School, University of Pennsylvania, Philadelphia, PA, USA
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Lindsay A Farrer
- Biomedical Genetics Section, Department of Medicine, Boston University School of Medicine, Boston University, Boston, MA, USA
- Departments of Neurology and Ophthalmology, Boston University School of Medicine, Boston University, Boston, MA, USA
- Departments of Epidemiology and Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Gerard D Schellenberg
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Wan-Ping Lee
- Department of Pathology and Laboratory Medicine, Penn Neurodegeneration Genomics Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Badri N Vardarajan
- https://ror.org/01esghr10 Gertrude H. Sergievsky Center and Taub Institute of Aging Brain, Department of Neurology, Columbia University Medical Center, New York, NY, USA
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14
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Sun W, Jon K, Zhu W. Multiple phenotype association tests based on sliced inverse regression. BMC Bioinformatics 2024; 25:144. [PMID: 38575890 PMCID: PMC10996256 DOI: 10.1186/s12859-024-05731-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Accepted: 03/05/2024] [Indexed: 04/06/2024] Open
Abstract
BACKGROUND Joint analysis of multiple phenotypes in studies of biological systems such as Genome-Wide Association Studies is critical to revealing the functional interactions between various traits and genetic variants, but growth of data in dimensionality has become a very challenging problem in the widespread use of joint analysis. To handle the excessiveness of variables, we consider the sliced inverse regression (SIR) method. Specifically, we propose a novel SIR-based association test that is robust and powerful in testing the association between multiple predictors and multiple outcomes. RESULTS We conduct simulation studies in both low- and high-dimensional settings with various numbers of Single-Nucleotide Polymorphisms and consider the correlation structure of traits. Simulation results show that the proposed method outperforms the existing methods. We also successfully apply our method to the genetic association study of ADNI dataset. Both the simulation studies and real data analysis show that the SIR-based association test is valid and achieves a higher efficiency compared with its competitors. CONCLUSION Several scenarios with low- and high-dimensional responses and genotypes are considered in this paper. Our SIR-based method controls the estimated type I error at the pre-specified level α .
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Affiliation(s)
- Wenyuan Sun
- Key Laboratory for Applied Statistics of MOE, School of Mathematics and Statistics, Northeast Normal University, Changchun, 130024, Jilin, China
- Department of Mathematics, College of Science, Yanbian University, Yanji, 133002, Jilin, China
| | - Kyongson Jon
- Key Laboratory for Applied Statistics of MOE, School of Mathematics and Statistics, Northeast Normal University, Changchun, 130024, Jilin, China
- Faculty of Mathematics, Kim Il Sung University, Pyongyan , 999093, Democratic People's Republic of Korea
| | - Wensheng Zhu
- Key Laboratory for Applied Statistics of MOE, School of Mathematics and Statistics, Northeast Normal University, Changchun, 130024, Jilin, China.
- School of Mathematical Sciences, Harbin Normal University, Harbin, 150025, Heilongjiang, China.
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15
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Nasri A, Sghaier I, Neji A, Gharbi A, Abida Y, Mrabet S, Gargouri A, Djebara MB, Kacem I, Gouider R. Phenotypic Spectrum of Progressive Supranuclear Palsy: Clinical Study and Apolipoprotein E Effect. J Mov Disord 2024; 17:158-170. [PMID: 38290492 PMCID: PMC11082606 DOI: 10.14802/jmd.23178] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 12/08/2023] [Accepted: 01/30/2024] [Indexed: 02/01/2024] Open
Abstract
OBJECTIVE Progressive supranuclear palsy (PSP) is a rare neurodegenerative disorder encompassing several phenotypes with various motor and cognitive deficits. We aimed to study motor and cognitive characteristics across PSP phenotypes and to assess the influence of apolipoprotein E (APOE) gene variants on PSP phenotypic expression. METHODS In this 20-year cross-sectional study, we retrospectively reviewed the charts of all patients classified as PSP patients and recategorized them according to phenotype using the Movement Disorder Society criteria (2017). Phenotypes were divided into three subgroups, Richardson's syndrome (PSP-RS), PSP-cortical (PSP with predominant frontal presentation [PSP-F] + PSP with predominant speech/language disorder [PSP-SL] + PSP with predominant corticobasal syndrome [PSP-CBS]) and PSP-subcortical (PSP with predominant parkinsonism [PSP-P] + PSP with progressive gait freezing [PSP-PGF] + PSP with predominant postural instability [PSP-PI] + PSP with predominant ocular motor dysfunction [PSP-OM] + PSP with cerebellar ataxia [PSP-C] + PSP with primary lateral sclerosis [PSP-PLS]), based on clinical presentation during the first 3 years after symptom onset, which defines the early disease stage. Clinical and neuropsychological assessment data were collected. Genotyping of APOE was performed using restriction fragment length polymorphism polymerase chain reaction and verified by Sanger sequencing. RESULTS We included 112 PSP patients comprising 10 phenotypes classified into 48 PSP-RS, 34 PSP-cortical (PSP-CBS, 17.6%; PSP-F, 9.4%; PSP-SL, 8.2%) and 30 PSP-subcortical (PSP-P, 11.6%; PSP-PI, 8%; PSP-OM, 2.7%; PSP-PGF, 1.8%; PSP-C, 1.8%; PSP-PLS, 0.9%) subgroups. PSP-RS patients were older at disease onset (p = 0.009) and had more akinetic-rigid and levodopa-resistant parkinsonism (p = 0.006), while PSP-cortical patients had more tremors and asymmetric and/or levodopa-responsive parkinsonism (p = 0.025). Cognitive domains were significantly less altered in the PSP-subcortical subgroup. Overall, PSP-APOEε4 carriers developed parkinsonism earlier (p = 0.038), had earlier oculomotor dysfunction (p = 0.052) and had more altered cognitive profiles. The APOEε4 allele was also associated with a younger age of parkinsonism onset in the PSP-RS phenotype group (p = 0.026). CONCLUSION This study demonstrated the wide phenotypic spectrum of PSP among Tunisians. Disease onset and akinetic-rigid and levodopa-resistant parkinsonism were the hallmarks of the PSP-RS phenotype, while milder cognitive impairment was characteristic of the PSP-subcortical subgroup. The APOEε4 allele was associated with earlier parkinsonism and oculomotor dysfunction and seemed to play a role in defining a more altered cognitive profile in PSP patients.
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Affiliation(s)
- Amina Nasri
- Department of Neurology, LR18SP03, Razi University Hospital, Tunis, Tunisia
- Faculty of Medicine of Tunis, University of Tunis El Manar, Tunis, Tunisia
- Clinical Investigation Center (CIC) “Neurosciences and Mental Health”, Razi University Hospital, Tunis, Tunisia
| | - Ikram Sghaier
- Department of Neurology, LR18SP03, Razi University Hospital, Tunis, Tunisia
- Clinical Investigation Center (CIC) “Neurosciences and Mental Health”, Razi University Hospital, Tunis, Tunisia
| | - Anis Neji
- Department of Neurology, LR18SP03, Razi University Hospital, Tunis, Tunisia
| | - Alya Gharbi
- Department of Neurology, LR18SP03, Razi University Hospital, Tunis, Tunisia
- Faculty of Medicine of Tunis, University of Tunis El Manar, Tunis, Tunisia
- Clinical Investigation Center (CIC) “Neurosciences and Mental Health”, Razi University Hospital, Tunis, Tunisia
| | - Youssef Abida
- Department of Neurology, LR18SP03, Razi University Hospital, Tunis, Tunisia
- Faculty of Medicine of Tunis, University of Tunis El Manar, Tunis, Tunisia
- Clinical Investigation Center (CIC) “Neurosciences and Mental Health”, Razi University Hospital, Tunis, Tunisia
| | - Saloua Mrabet
- Department of Neurology, LR18SP03, Razi University Hospital, Tunis, Tunisia
- Faculty of Medicine of Tunis, University of Tunis El Manar, Tunis, Tunisia
- Clinical Investigation Center (CIC) “Neurosciences and Mental Health”, Razi University Hospital, Tunis, Tunisia
| | - Amina Gargouri
- Department of Neurology, LR18SP03, Razi University Hospital, Tunis, Tunisia
- Faculty of Medicine of Tunis, University of Tunis El Manar, Tunis, Tunisia
- Clinical Investigation Center (CIC) “Neurosciences and Mental Health”, Razi University Hospital, Tunis, Tunisia
| | - Mouna Ben Djebara
- Department of Neurology, LR18SP03, Razi University Hospital, Tunis, Tunisia
- Faculty of Medicine of Tunis, University of Tunis El Manar, Tunis, Tunisia
- Clinical Investigation Center (CIC) “Neurosciences and Mental Health”, Razi University Hospital, Tunis, Tunisia
| | - Imen Kacem
- Department of Neurology, LR18SP03, Razi University Hospital, Tunis, Tunisia
- Faculty of Medicine of Tunis, University of Tunis El Manar, Tunis, Tunisia
- Clinical Investigation Center (CIC) “Neurosciences and Mental Health”, Razi University Hospital, Tunis, Tunisia
| | - Riadh Gouider
- Department of Neurology, LR18SP03, Razi University Hospital, Tunis, Tunisia
- Faculty of Medicine of Tunis, University of Tunis El Manar, Tunis, Tunisia
- Clinical Investigation Center (CIC) “Neurosciences and Mental Health”, Razi University Hospital, Tunis, Tunisia
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16
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Chandrashekar H, Simandi Z, Choi H, Ryu HS, Waldman AJ, Nikish A, Muppidi SS, Gong W, Paquet D, Phillips-Cremins JE. A multi-looping chromatin signature predicts dysregulated gene expression in neurons with familial Alzheimer's disease mutations. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.27.582395. [PMID: 38463966 PMCID: PMC10925341 DOI: 10.1101/2024.02.27.582395] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Mammalian genomes fold into tens of thousands of long-range loops, but their functional role and physiologic relevance remain poorly understood. Here, using human post-mitotic neurons with rare familial Alzheimer's disease (FAD) mutations, we identify hundreds of reproducibly dysregulated genes and thousands of miswired loops prior to amyloid accumulation and tau phosphorylation. Single loops do not predict expression changes; however, the severity and direction of change in mRNA levels and single-cell burst frequency strongly correlate with the number of FAD-gained or -lost promoter-enhancer loops. Classic architectural proteins CTCF and cohesin do not change occupancy in FAD-mutant neurons. Instead, we unexpectedly find TAATTA motifs amenable to binding by DLX homeodomain transcription factors and changing noncoding RNAPolII signal at FAD-dynamic promoter-enhancer loops. DLX1/5/6 mRNA levels are strongly upregulated in FAD-mutant neurons coincident with a shift in excitatory-to-inhibitory gene expression and miswiring of multi-loops connecting enhancers to neural subtype genes. DLX1 overexpression is sufficient for loop miswiring in wildtype neurons, including lost and gained loops at enhancers with tandem TAATTA arrays and singular TAATTA motifs, respectively. Our data uncover a genome structure-function relationship between multi-loop miswiring and dysregulated excitatory and inhibitory transcriptional programs during lineage commitment of human neurons homozygously-engineered with rare FAD mutations.
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Affiliation(s)
- Harshini Chandrashekar
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA
- Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania
| | - Zoltan Simandi
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA
- Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania
| | - Heesun Choi
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA
- Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania
| | - Han-Seul Ryu
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA
- Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania
| | - Abraham J Waldman
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA
- Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania
| | - Alexandria Nikish
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA
- Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania
| | - Srikar S Muppidi
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA
- Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania
| | - Wanfeng Gong
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA
- Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania
| | - Dominik Paquet
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, 81377, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Jennifer E Phillips-Cremins
- Department of Bioengineering, University of Pennsylvania, Philadelphia, PA
- Epigenetics Institute, Perelman School of Medicine, University of Pennsylvania
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania
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17
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Timsina J, Ali M, Do A, Wang L, Western D, Sung YJ, Cruchaga C. Harmonization of CSF and imaging biomarkers in Alzheimer's disease: Need and practical applications for genetics studies and preclinical classification. Neurobiol Dis 2024; 190:106373. [PMID: 38072165 DOI: 10.1016/j.nbd.2023.106373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2023] [Revised: 10/06/2023] [Accepted: 12/05/2023] [Indexed: 12/19/2023] Open
Abstract
In Alzheimer's disease (AD) research, cerebrospinal fluid (CSF) Amyloid beta (Aβ), Tau and pTau are the most accepted and well validated biomarkers. Several methods and platforms exist to measure those biomarkers, leading to challenges in combining data across studies. Thus, there is a need to identify methods that harmonize and standardize these values. We used a Z-score based approach to harmonize CSF and amyloid imaging data from multiple cohorts and compared GWAS results using this approach with currently accepted methods. We also used a generalized mixture model to calculate the threshold for biomarker-positivity. Based on our findings, our normalization approach performed as well as meta-analysis and did not lead to any spurious results. In terms of dichotomization, cutoffs calculated with this approach were very similar to those reported previously. These findings show that the Z-score based harmonization approach can be applied to heterogeneous platforms and provides biomarker cut-offs consistent with the classical approaches without requiring any additional data.
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Affiliation(s)
- Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Muhammad Ali
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Anh Do
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA; Division of Biology and Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, USA
| | - Lihua Wang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Daniel Western
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA; Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA; NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA; Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA.
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18
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Ge YJ, Wu BS, Zhang Y, Chen SD, Zhang YR, Kang JJ, Deng YT, Ou YN, He XY, Zhao YL, Kuo K, Ma Q, Banaschewski T, Barker GJ, Bokde ALW, Desrivières S, Flor H, Grigis A, Garavan H, Gowland P, Heinz A, Brühl R, Martinot JL, Martinot MLP, Artiges E, Nees F, Orfanos DP, Lemaitre H, Paus T, Poustka L, Hohmann S, Millenet S, Fröhner JH, Smolka MN, Vaidya N, Walter H, Whelan R, Feng JF, Tan L, Dong Q, Schumann G, Cheng W, Yu JT. Genetic architectures of cerebral ventricles and their overlap with neuropsychiatric traits. Nat Hum Behav 2024; 8:164-180. [PMID: 37857874 DOI: 10.1038/s41562-023-01722-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2023] [Accepted: 09/12/2023] [Indexed: 10/21/2023]
Abstract
The cerebral ventricles are recognized as windows into brain development and disease, yet their genetic architectures, underlying neural mechanisms and utility in maintaining brain health remain elusive. Here we aggregated genetic and neuroimaging data from 61,974 participants (age range, 9 to 98 years) in five cohorts to elucidate the genetic basis of ventricular morphology and examined their overlap with neuropsychiatric traits. Genome-wide association analysis in a discovery sample of 31,880 individuals identified 62 unique loci and 785 candidate genes associated with ventricular morphology. We replicated over 80% of loci in a well-matched cohort of lateral ventricular volume. Gene set analysis revealed enrichment of ventricular-trait-associated genes in biological processes and disease pathogenesis during both early brain development and degeneration. We explored the age-dependent genetic associations in cohorts of different age groups to investigate the possible roles of ventricular-trait-associated loci in neurodevelopmental and neurodegenerative processes. We describe the genetic overlap between ventricular and neuropsychiatric traits through comprehensive integrative approaches under correlative and causal assumptions. We propose the volume of the inferior lateral ventricles as a heritable endophenotype to predict the risk of Alzheimer's disease, which might be a consequence of prodromal Alzheimer's disease. Our study provides an advance in understanding the genetics of the cerebral ventricles and demonstrates the potential utility of ventricular measurements in tracking brain disorders and maintaining brain health across the lifespan.
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Affiliation(s)
- Yi-Jun Ge
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Bang-Sheng Wu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yi Zhang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shi-Dong Chen
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ya-Ru Zhang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ju-Jiao Kang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Yue-Ting Deng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Xiao-Yu He
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yong-Li Zhao
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Kevin Kuo
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Qing Ma
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Tobias Banaschewski
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Gareth J Barker
- Department of Neuroimaging, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Arun L W Bokde
- Discipline of Psychiatry, School of Medicine and Trinity College Institute of Neuroscience, Trinity College Dublin, Dublin, Ireland
| | - Sylvane Desrivières
- Centre for Population Neuroscience and Precision Medicine, Institute of Psychiatry, Psychology & Neuroscience, SGDP Centre, King's College London, London, UK
| | - Herta Flor
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Department of Psychology, School of Social Sciences, University of Mannheim, Mannheim, Germany
| | - Antoine Grigis
- NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Hugh Garavan
- Departments of Psychiatry and Psychology, University of Vermont, Burlington, VT, USA
| | - Penny Gowland
- Sir Peter Mansfield Imaging Centre, School of Physics and Astronomy, University of Nottingham, Nottingham, UK
| | - Andreas Heinz
- Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Rüdiger Brühl
- Physikalisch-Technische Bundesanstalt, Braunschweig and Berlin, Germany
| | - Jean-Luc Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 'Trajectoires développementales & psychiatrie', University Paris-Saclay, CNRS; Ecole Normale Supérieure Paris-Saclay, Centre Borelli, Gif-sur-Yvette, France
| | - Marie-Laure Paillère Martinot
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 'Trajectoires développementales & psychiatrie', University Paris-Saclay, CNRS; Ecole Normale Supérieure Paris-Saclay, Centre Borelli, Gif-sur-Yvette, France
- AP-HP, Sorbonne University, Department of Child and Adolescent Psychiatry, Pitié-Salpêtrière Hospital, Paris, France
| | - Eric Artiges
- Institut National de la Santé et de la Recherche Médicale, INSERM U 1299 'Trajectoires développementales & psychiatrie', University Paris-Saclay, CNRS; Ecole Normale Supérieure Paris-Saclay, Centre Borelli, Gif-sur-Yvette, France
- Psychiatry Department, EPS Barthélémy Durand, Etampes, France
| | - Frauke Nees
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Institute of Cognitive and Clinical Neuroscience, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
- Institute of Medical Psychology and Medical Sociology, University Medical Center Schleswig Holstein, Kiel University, Kiel, Germany
| | | | - Herve Lemaitre
- NeuroSpin, CEA, Université Paris-Saclay, Gif-sur-Yvette, France
- Institut des Maladies Neurodégénératives, UMR 5293, CNRS, CEA, Université de Bordeaux, Bordeaux, France
| | - Tomáš Paus
- Departments of Psychiatry and Neuroscience, Faculty of Medicine and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, Quebec, Canada
- Departments of Psychiatry and Psychology, University of Toronto, Toronto, Ontario, Canada
| | - Luise Poustka
- Department of Child and Adolescent Psychiatry and Psychotherapy, University Medical Centre Göttingen, Göttingen, Germany
| | - Sarah Hohmann
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Sabina Millenet
- Department of Child and Adolescent Psychiatry and Psychotherapy, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Juliane H Fröhner
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Michael N Smolka
- Department of Psychiatry and Neuroimaging Center, Technische Universität Dresden, Dresden, Germany
| | - Nilakshi Vaidya
- Centre for Population Neuroscience and Stratified Medicine, Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Berlin, Germany
| | - Henrik Walter
- Department of Psychiatry and Psychotherapy CCM, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany
| | - Robert Whelan
- School of Psychology and Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Beijing, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Qiang Dong
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Gunter Schumann
- Centre for Population Neuroscience and Stratified Medicine, Department of Psychiatry and Neuroscience, Charité Universitätsmedizin Berlin, Berlin, Germany
- Centre for Population Neuroscience and Precision Medicine, Institute for Science and Technology of Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Beijing, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China.
- Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer 79 Center, Shanghai, China.
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
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Waszczuk MA, Jonas KG, Bornovalova M, Breen G, Bulik CM, Docherty AR, Eley TC, Hettema JM, Kotov R, Krueger RF, Lencz T, Li JJ, Vassos E, Waldman ID. Dimensional and transdiagnostic phenotypes in psychiatric genome-wide association studies. Mol Psychiatry 2023; 28:4943-4953. [PMID: 37402851 PMCID: PMC10764644 DOI: 10.1038/s41380-023-02142-8] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 05/17/2023] [Accepted: 06/16/2023] [Indexed: 07/06/2023]
Abstract
Genome-wide association studies (GWAS) provide biological insights into disease onset and progression and have potential to produce clinically useful biomarkers. A growing body of GWAS focuses on quantitative and transdiagnostic phenotypic targets, such as symptom severity or biological markers, to enhance gene discovery and the translational utility of genetic findings. The current review discusses such phenotypic approaches in GWAS across major psychiatric disorders. We identify themes and recommendations that emerge from the literature to date, including issues of sample size, reliability, convergent validity, sources of phenotypic information, phenotypes based on biological and behavioral markers such as neuroimaging and chronotype, and longitudinal phenotypes. We also discuss insights from multi-trait methods such as genomic structural equation modelling. These provide insight into how hierarchical 'splitting' and 'lumping' approaches can be applied to both diagnostic and dimensional phenotypes to model clinical heterogeneity and comorbidity. Overall, dimensional and transdiagnostic phenotypes have enhanced gene discovery in many psychiatric conditions and promises to yield fruitful GWAS targets in the years to come.
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Affiliation(s)
- Monika A Waszczuk
- Department of Psychology, Rosalind Franklin University of Medicine and Science, North Chicago, IL, USA.
| | - Katherine G Jonas
- Department of Psychiatry, Stony Brook University School of Medicine, Stony Brook, NY, USA
| | | | - Gerome Breen
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Cynthia M Bulik
- Department of Psychiatry, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Nutrition, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Anna R Docherty
- Huntsman Mental Health Institute, Department of Psychiatry, University of Utah School of Medicine, Salt Lake City, UT, USA
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
| | - Thalia C Eley
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - John M Hettema
- Virginia Institute for Psychiatric and Behavioral Genetics, Virginia Commonwealth University School of Medicine, Richmond, VA, USA
- Department of Psychiatry, Texas A&M Health Sciences Center, Bryan, TX, USA
| | - Roman Kotov
- Department of Psychiatry, Stony Brook University School of Medicine, Stony Brook, NY, USA
| | - Robert F Krueger
- Psychology Department, University of Minnesota, Minneapolis, MN, USA
| | - Todd Lencz
- Department of Psychiatry, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Psychiatry, Division of Research, The Zucker Hillside Hospital Division of Northwell Health, Glen Oaks, NY, USA
- Institute for Behavioral Science, The Feinstein Institutes for Medical Research, Manhasset, NY, USA
| | - James J Li
- Department of Psychology, University of Wisconsin, Madison, WI, USA
- Waisman Center, University of Wisconsin, Madison, WI, USA
| | - Evangelos Vassos
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- UK National Institute for Health and Care Research (NIHR) Biomedical Research Centre, South London and Maudsley NHS Trust, London, UK
| | - Irwin D Waldman
- Department of Psychology, Emory University, Atlanta, GA, USA
- Center for Computational and Quantitative Genetics, Emory University, Atlanta, GA, USA
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20
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Zhang J, Wang Y, Zhang Y, Yao J. Genome-wide association study in Alzheimer's disease: a bibliometric and visualization analysis. Front Aging Neurosci 2023; 15:1290657. [PMID: 38094504 PMCID: PMC10716290 DOI: 10.3389/fnagi.2023.1290657] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 11/08/2023] [Indexed: 02/23/2024] Open
Abstract
BACKGROUND Thousands of research studies concerning genome-wide association studies (GWAS) in Alzheimer's disease (AD) have been published in the last decades. However, a comprehensive understanding of the current research status and future development trends of GWAS in AD have not been clearly shown. In this study, we tried to gain a systematic overview of GWAS in AD by bibliometric and visualization analysis. METHODS The literature search terms are: ("genome-wide analysis" or "genome-wide association study" or "whole-genome analysis") AND ("Alzheimer's Disease" or "Alzheimer Disease"). Relevant publications were extracted from the Web of Science Core Collection (WoSCC) database. Collected data were further analyzed using VOSviewer, CiteSpace and R package Bibliometrix. The countries, institutions, authors and scholar collaborations were investigated. The co-citation analysis of publications was visualized. In addition, research hotspots and fronts were examined. RESULTS A total of 1,350 publications with 59,818 citations were identified. The number of publications and citations presented a significant rising trend since 2013. The United States was the leading country with an overwhelming number of publications (775) and citations (42,237). The University of Washington and Harvard University were the most prolific institutions with 101 publications each. Bennett DA was the most influential researcher with the highest local H-index. Neurobiology of Aging was the journal with the highest number of publications. Aβ, tau, immunity, microglia and DNA methylation were research hotspots. Disease and causal variants were research fronts. CONCLUSION The most frequently studied AD pathogenesis and research hotspots are (1) Aβ and tau, (2) immunity and microglia, with TREM2 as a potential immunotherapy target, and (3) DNA methylation. The research fronts are (1) looking for genetic similarities between AD and other neurological diseases and syndromes, and (2) searching for causal variants of AD. These hotspots suggest noteworthy directions for future studies on AD pathogenesis and genetics, in which basic research regarding immunity is promising for clinical conversion. The current under-researched directions are (1) GWAS in AD biomarkers based on large sample sizes, (2) studies of causal variants of AD, and (3) GWAS in AD based on non-European populations, which need to be strengthened in the future.
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Affiliation(s)
- Junyao Zhang
- Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yinuo Wang
- Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yingying Zhang
- Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Junyan Yao
- Department of Anesthesiology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Department of Anesthesiology and Critical Care Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China
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21
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Su WM, Gu XJ, Dou M, Duan QQ, Jiang Z, Yin KF, Cai WC, Cao B, Wang Y, Chen YP. Systematic druggable genome-wide Mendelian randomisation identifies therapeutic targets for Alzheimer's disease. J Neurol Neurosurg Psychiatry 2023; 94:954-961. [PMID: 37349091 PMCID: PMC10579488 DOI: 10.1136/jnnp-2023-331142] [Citation(s) in RCA: 14] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2023] [Accepted: 06/05/2023] [Indexed: 06/24/2023]
Abstract
BACKGROUND Alzheimer's disease (AD) is the leading cause of dementia. Currently, there are no effective disease-modifying treatments for AD. Mendelian randomisation (MR) has been widely used to repurpose licensed drugs and discover novel therapeutic targets. Thus, we aimed to identify novel therapeutic targets for AD and analyse their pathophysiological mechanisms and potential side effects. METHODS A two-sample MR integrating the identified druggable genes was performed to estimate the causal effects of blood and brain druggable expression quantitative trait loci (eQTLs) on AD. A repeat study was conducted using different blood and brain eQTL data sources to validate the identified genes. Using AD markers with available genome-wide association studies data, we evaluated the causal relationship between established AD markers to explore possible mechanisms. Finally, the potential side effects of the druggable genes for AD treatment were assessed using a phenome-wide MR. RESULTS Overall, 5883 unique druggable genes were aggregated; 33 unique potential druggable genes for AD were identified in at least one dataset (brain or blood), and 5 were validated in a different dataset. Among them, three prior druggable genes (epoxide hydrolase 2 (EPHX2), SERPINB1 and SIGLEC11) reached significant levels in both blood and brain tissues. EPHX2 may mediate the pathogenesis of AD by affecting the entire hippocampal volume. Further phenome-wide MR analysis revealed no potential side effects of treatments targeting EPHX2, SERPINB1 or SIGLEC11. CONCLUSIONS This study provides genetic evidence supporting the potential therapeutic benefits of targeting the three druggable genes for AD treatment, which will be useful for prioritising AD drug development.
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Affiliation(s)
- Wei-Ming Su
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Institute of Brain Science and Brain-inspired Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Xiao-Jing Gu
- Department of Mental Health Center, West China Hospital, Sichuan University, Chengdu, China
| | - Meng Dou
- Chengdu Computer Application Institute, Chinese Academy of Sciences, Chengdu, China
| | - Qing-Qing Duan
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Institute of Brain Science and Brain-inspired Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Zheng Jiang
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Institute of Brain Science and Brain-inspired Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Kang-Fu Yin
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Institute of Brain Science and Brain-inspired Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wei-Chen Cai
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Institute of Brain Science and Brain-inspired Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Bei Cao
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Institute of Brain Science and Brain-inspired Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yi Wang
- Department of Pathophysiology, West China College of Basic medical sciences & Forensic Medicine, Sichuan University, Chengdu, China
| | - Yong-Ping Chen
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
- Institute of Brain Science and Brain-inspired Technology, West China Hospital, Sichuan University, Chengdu, Sichuan, China
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22
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Chung J, Sahelijo N, Maruyama T, Hu J, Panitch R, Xia W, Mez J, Stein TD, Saykin AJ, Takeyama H, Farrer LA, Crane PK, Nho K, Jun GR. Alzheimer's disease heterogeneity explained by polygenic risk scores derived from brain transcriptomic profiles. Alzheimers Dement 2023; 19:5173-5184. [PMID: 37166019 PMCID: PMC10638468 DOI: 10.1002/alz.13069] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 03/03/2023] [Accepted: 03/08/2023] [Indexed: 05/12/2023]
Abstract
INTRODUCTION Alzheimer's disease (AD) is heterogeneous, both clinically and neuropathologically. We investigated whether polygenic risk scores (PRSs) integrated with transcriptome profiles from AD brains can explain AD clinical heterogeneity. METHODS We conducted co-expression network analysis and identified gene sets (modules) that were preserved in three AD transcriptome datasets and associated with AD-related neuropathological traits including neuritic plaques (NPs) and neurofibrillary tangles (NFTs). We computed the module-based PRSs (mbPRSs) for each module and tested associations with mbPRSs for cognitive test scores, cognitively defined AD subgroups, and brain imaging data. RESULTS Of the modules significantly associated with NPs and/or NFTs, the mbPRSs from two modules (M6 and M9) showed distinct associations with language and visuospatial functioning, respectively. They matched clinical subtypes and brain atrophy at specific regions. DISCUSSION Our findings demonstrate that polygenic profiling based on co-expressed gene sets can explain heterogeneity in AD patients, enabling genetically informed patient stratification and precision medicine in AD. HIGHLIGHTS Co-expression gene-network analysis in Alzheimer's disease (AD) brains identified gene sets (modules) associated with AD heterogeneity. AD-associated modules were selected when genes in each module were enriched for neuritic plaques and neurofibrillary tangles. Polygenic risk scores from two selected modules were linked to the matching cognitively defined AD subgroups (language and visuospatial subgroups). Polygenic risk scores from the two modules were associated with cognitive performance in language and visuospatial domains and the associations were confirmed in regional-specific brain atrophy data.
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Affiliation(s)
- Jaeyoon Chung
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
| | - Nathan Sahelijo
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
| | - Toru Maruyama
- Department of Life Science and Medical Bioscience, Waseda University, 2-2 Wakamatsu-cho, Shinjuku-ku, Tokyo 162-8480, Japan
| | - Junming Hu
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
| | - Rebecca Panitch
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
| | - Weiming Xia
- Department of Pharmacology & Experimental Therapeutics, Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
- Department of Veterans Affairs Medical Center, Bedford, MA 01730, USA
| | - Jesse Mez
- Department of Neurology, Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
| | - Thor D. Stein
- Department of Veterans Affairs Medical Center, Bedford, MA 01730, USA
- Department of Pathology & Laboratory Medicine, Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
- Boston VA Healthcare Center, Boston, MA 02130, USA
| | | | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences and Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Haruko Takeyama
- Department of Life Science and Medical Bioscience, Waseda University, 2-2 Wakamatsu-cho, Shinjuku-ku, Tokyo 162-8480, Japan
- Computational Bio Big-Data Open Innovation Laboratory, AIST-Waseda University, Japan, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan
- Research Organization for Nano and Life Innovations, Waseda University, 513, Wasedatsurumaki-cho, Shinjuku-ku, Tokyo 162-0041, Japan
- Institute for Advanced Research of Biosystem Dynamics, Waseda Research Institute for Science and Engineering, Graduate School of Advanced Science and Engineering, Waseda University, 3-4-1 Okubo, Shinjuku-ku, Tokyo 169-8555, Japan
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
- Department of Neurology, Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
- Department of Ophthalmology, Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
- Department of Biostatistics, Boston University School of Public Health, 715 Albany Street, Boston, MA 02118, USA
- Department of Epidemiology, Boston University School of Public Health, 715 Albany Street, Boston, MA 02118, USA
| | - Paul K. Crane
- Department of Medicine, University of Washington, Seattle, WA, USA
| | - Kwangsik Nho
- Department of Radiology and Imaging Sciences and Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN 46202, USA
- Center for Computational Biology and Bioinformatics, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Gyungah R. Jun
- Department of Medicine (Biomedical Genetics), Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
- Department of Ophthalmology, Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118, USA
- Department of Biostatistics, Boston University School of Public Health, 715 Albany Street, Boston, MA 02118, USA
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23
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Xu M, Liu Q, Bi R, Li Y, Li H, Kang WB, Yan Z, Zheng Q, Sun C, Ye M, Xiang BL, Luo XJ, Li M, Zhang DF, Yao YG. Coexistence of Multiple Functional Variants and Genes Underlies Genetic Risk Locus 11p11.2 of Alzheimer's Disease. Biol Psychiatry 2023; 94:743-759. [PMID: 37290560 DOI: 10.1016/j.biopsych.2023.05.020] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/29/2022] [Revised: 05/25/2023] [Accepted: 05/26/2023] [Indexed: 06/10/2023]
Abstract
BACKGROUND Genome-wide association studies have identified dozens of genetic risk loci for Alzheimer's disease (AD), yet the underlying causal variants and biological mechanisms remain elusive, especially for loci with complex linkage disequilibrium and regulation. METHODS To fully untangle the causal signal at a single locus, we performed a functional genomic study of 11p11.2 (the CELF1/SPI1 locus). Genome-wide association study signals at 11p11.2 were integrated with datasets of histone modification, open chromatin, and transcription factor binding to distill potentially functional variants (fVars). Their allelic regulatory activities were confirmed by allele imbalance, reporter assays, and base editing. Expressional quantitative trait loci and chromatin interaction data were incorporated to assign target genes to fVars. The relevance of these genes to AD was assessed by convergent functional genomics using bulk brain and single-cell transcriptomic, epigenomic, and proteomic datasets of patients with AD and control individuals, followed by cellular assays. RESULTS We found that 24 potential fVars, rather than a single variant, were responsible for the risk of 11p11.2. These fVars modulated transcription factor binding and regulated multiple genes by long-range chromatin interactions. Besides SPI1, convergent evidence indicated that 6 target genes (MTCH2, ACP2, NDUFS3, PSMC3, C1QTNF4, and MADD) of fVars were likely to be involved in AD development. Disruption of each gene led to cellular amyloid-β and phosphorylated tau changes, supporting the existence of multiple likely causal genes at 11p11.2. CONCLUSIONS Multiple variants and genes at 11p11.2 may contribute to AD risk. This finding provides new insights into the mechanistic and therapeutic challenges of AD.
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Affiliation(s)
- Min Xu
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Qianjin Liu
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Rui Bi
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China; National Resource Center for Non-Human Primates, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Yu Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Hongli Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Wei-Bo Kang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Zhongjiang Yan
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Quanzhen Zheng
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Chunli Sun
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Maosen Ye
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Bo-Lin Xiang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Xiong-Jian Luo
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China
| | - Ming Li
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China
| | - Deng-Feng Zhang
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China; National Resource Center for Non-Human Primates, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
| | - Yong-Gang Yao
- Key Laboratory of Animal Models and Human Disease Mechanisms of the Chinese Academy of Sciences & Yunnan Province and KIZ/CUHK Joint Laboratory of Bioresources and Molecular Research in Common Diseases, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, China; National Resource Center for Non-Human Primates, National Research Facility for Phenotypic & Genetic Analysis of Model Animals (Primate Facility), Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, China; Center for Excellence in Animal Evolution and Genetics, Chinese Academy of Sciences, Kunming, China.
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Xue H, Xu X, Yan Z, Cheng J, Zhang L, Zhu W, Cui G, Zhang Q, Qiu S, Yao Z, Qin W, Liu F, Liang M, Fu J, Xu Q, Xu J, Xie Y, Zhang P, Li W, Wang C, Shen W, Zhang X, Xu K, Zuo XN, Ye Z, Yu Y, Xian J, Yu C. Genome-wide association study of hippocampal blood-oxygen-level-dependent-cerebral blood flow correlation in Chinese Han population. iScience 2023; 26:108005. [PMID: 37822511 PMCID: PMC10562876 DOI: 10.1016/j.isci.2023.108005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 07/29/2023] [Accepted: 09/18/2023] [Indexed: 10/13/2023] Open
Abstract
Correlation between blood-oxygen-level-dependent (BOLD) and cerebral blood flow (CBF) has been used as an index of neurovascular coupling. Hippocampal BOLD-CBF correlation is associated with neurocognition, and the reduced correlation is associated with neuropsychiatric disorders. We conducted the first genome-wide association study of the hippocampal BOLD-CBF correlation in 4,832 Chinese Han subjects. The hippocampal BOLD-CBF correlation had an estimated heritability of 16.2-23.9% and showed reliable genome-wide significant association with a locus at 3q28, in which many variants have been linked to neuroimaging and cerebrospinal fluid markers of Alzheimer's disease. Gene-based association analyses showed four significant genes (GMNC, CRTC2, DENND4B, and GATAD2B) and revealed enrichment for mast cell calcium mobilization, microglial cell proliferation, and ubiquitin-related proteolysis pathways that regulate different cellular components of the neurovascular unit. This is the first unbiased identification of the association of hippocampal BOLD-CBF correlation, providing fresh insights into the genetic architecture of hippocampal neurovascular coupling.
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Affiliation(s)
- Hui Xue
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Xiaojun Xu
- Department of Radiology, The Second Affiliated Hospital of Zhejiang University, School of Medicine, Hangzhou 310009, China
| | - Zhihan Yan
- Department of Radiology, The Second Affiliated Hospital and Yuying Children’s Hospital of Wenzhou Medical University, Wenzhou 325027, China
| | - Jingliang Cheng
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Longjiang Zhang
- Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210002, China
| | - Wenzhen Zhu
- Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Guangbin Cui
- Functional and Molecular Imaging Key Lab of Shaanxi Province & Department of Radiology, Tangdu Hospital, Air Force Medical University, Xi’an 710038, China
| | - Quan Zhang
- Department of Radiology, Characteristic Medical Center of Chinese People’s Armed Police Force, Tianjin 300162, China
| | - Shijun Qiu
- Department of Medical Imaging, the First Affiliated Hospital of Guangzhou University of Traditional Chinese Medicine, Guangzhou 510405, China
| | - Zhenwei Yao
- Department of Radiology, Huashan Hospital, Fudan University, Shanghai 200040, China
| | - Wen Qin
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Feng Liu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Meng Liang
- School of Medical Imaging and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University, Tianjin 300203, China
| | - Jilian Fu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Qiang Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Jiayuan Xu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Yingying Xie
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
| | - Peng Zhang
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
| | - Wei Li
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, Tianjin 300060, China
| | - Caihong Wang
- Department of Magnetic Resonance Imaging, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Wen Shen
- Department of Radiology, Tianjin First Center Hospital, Tianjin 300192, China
| | - Xiaochu Zhang
- Division of Life Science and Medicine, University of Science & Technology of China, Hefei 230027, China
| | - Kai Xu
- Department of Radiology, The Affiliated Hospital of Xuzhou Medical University, Xuzhou 221006, China
| | - Xi-Nian Zuo
- Developmental Population Neuroscience Research Center at IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China
- Institute of Psychology, Chinese Academy of Sciences, Beijing 100101, China
| | - Zhaoxiang Ye
- Department of Radiology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin’s Clinical Research Center for Cancer, Tianjin Medical University, Ministry of Education, Key Laboratory of Cancer Prevention and Therapy, Tianjin 300060, China
| | - Yongqiang Yu
- Department of Radiology, The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Junfang Xian
- Department of Radiology, Beijing Tongren Hospital, Capital Medical University, Beijing 100730, China
| | - Chunshui Yu
- Department of Radiology and Tianjin Key Laboratory of Functional Imaging, Tianjin Medical University General Hospital, Tianjin 300052, China
- CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai 200031, China
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25
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Neumann A, Ohlei O, Küçükali F, Bos IJ, Timsina J, Vos S, Prokopenko D, Tijms BM, Andreasson U, Blennow K, Vandenberghe R, Scheltens P, Teunissen CE, Engelborghs S, Frisoni GB, Blin O, Richardson JC, Bordet R, Lleó A, Alcolea D, Popp J, Marsh TW, Gorijala P, Clark C, Peyratout G, Martinez-Lage P, Tainta M, Dobson RJB, Legido-Quigley C, Van Broeckhoven C, Tanzi RE, Ten Kate M, Lill CM, Barkhof F, Cruchaga C, Lovestone S, Streffer J, Zetterberg H, Visser PJ, Sleegers K, Bertram L. Multivariate GWAS of Alzheimer's disease CSF biomarker profiles implies GRIN2D in synaptic functioning. Genome Med 2023; 15:79. [PMID: 37794492 PMCID: PMC10548686 DOI: 10.1186/s13073-023-01233-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 09/12/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified several risk loci, but many remain unknown. Cerebrospinal fluid (CSF) biomarkers may aid in gene discovery and we previously demonstrated that six CSF biomarkers (β-amyloid, total/phosphorylated tau, NfL, YKL-40, and neurogranin) cluster into five principal components (PC), each representing statistically independent biological processes. Here, we aimed to (1) identify common genetic variants associated with these CSF profiles, (2) assess the role of associated variants in AD pathophysiology, and (3) explore potential sex differences. METHODS We performed GWAS for each of the five biomarker PCs in two multi-center studies (EMIF-AD and ADNI). In total, 973 participants (n = 205 controls, n = 546 mild cognitive impairment, n = 222 AD) were analyzed for 7,433,949 common SNPs and 19,511 protein-coding genes. Structural equation models tested whether biomarker PCs mediate genetic risk effects on AD, and stratified and interaction models probed for sex-specific effects. RESULTS Five loci showed genome-wide significant association with CSF profiles, two were novel (rs145791381 [inflammation] and GRIN2D [synaptic functioning]) and three were previously described (APOE, TMEM106B, and CHI3L1). Follow-up analyses of the two novel signals in independent datasets only supported the GRIN2D locus, which contains several functionally interesting candidate genes. Mediation tests indicated that variants in APOE are associated with AD status via processes related to amyloid and tau pathology, while markers in TMEM106B and CHI3L1 are associated with AD only via neuronal injury/inflammation. Additionally, seven loci showed sex-specific associations with AD biomarkers. CONCLUSIONS These results suggest that pathway and sex-specific analyses can improve our understanding of AD genetics and may contribute to precision medicine.
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Affiliation(s)
- Alexander Neumann
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Olena Ohlei
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, V50.2M, Lübeck, 23562, Germany
| | - Fahri Küçükali
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Isabelle J Bos
- Netherlands Institute for Health Services Research, Utrecht, Netherlands
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Stephanie Vos
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, Netherlands
| | - Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Ulf Andreasson
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Neurology Service, University Hospital Leuven, Leuven, Belgium
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Sebastiaan Engelborghs
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Department of Neurology and Memory Clinic, Universitair Ziekenhuis Brussel (UZ Brussel) and Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Giovanni B Frisoni
- Memory Center, Department of Rehabilitation and Geriatrics, Geneva University and University Hospitals, Geneva, Switzerland
| | - Oliver Blin
- Clinical Pharmacology & Pharmacovigilance Department, Marseille University Hospital, Marseille, France
| | | | - Régis Bordet
- Neuroscience & Cognition, CHU de Lille, University of Lille, Inserm, France
| | - Alberto Lleó
- Memory Unit, Neurology Department, Hospital de Sant Pau, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Daniel Alcolea
- Memory Unit, Neurology Department, Hospital de Sant Pau, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Julius Popp
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Zurich, Switzerland
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Thomas W Marsh
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- Division of Biology & Biomedical Sciences, Washington University in St. Louis, St Louis, MO, USA
| | - Priyanka Gorijala
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Christopher Clark
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Zurich, Switzerland
| | - Gwendoline Peyratout
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Pablo Martinez-Lage
- Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
| | - Mikel Tainta
- Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
- Zumarraga Hospital, Osakidetza, Integrated Health Organization (OSI) Goierri-Urola Garia, Basque Country, Spain
| | - Richard J B Dobson
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, Boston, UK
- NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK
- Health Data Research UK London, University College London, London, UK
- Institute of Health Informatics, University College London, London, UK
- The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK
| | - Cristina Legido-Quigley
- Steno Diabetes Center, Copenhagen, Denmark
- Institute of Pharmaceutical Science, King's College London, London, UK
| | - Christine Van Broeckhoven
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Neurodegenerative Brain Diseases Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
| | - Rudolph E Tanzi
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Mara Ten Kate
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, Netherlands
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, Netherlands
| | - Christina M Lill
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, V50.2M, Lübeck, 23562, Germany
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
- Ageing Epidemiology Research Unit, School of Public Health, Imperial College, London, UK
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Simon Lovestone
- Janssen Medical Ltd, Wycombe, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Johannes Streffer
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- AC Immune SA, Lausanne, Switzerland
- Janssen R&D, LLC, Beerse, Belgium
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute, University College London, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Pieter Jelle Visser
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, Netherlands
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, Netherlands
| | - Kristel Sleegers
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, V50.2M, Lübeck, 23562, Germany.
- Centre for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
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Sneha NP, Dharshini SAP, Taguchi YH, Gromiha MM. Investigating Neuron Degeneration in Huntington's Disease Using RNA-Seq Based Transcriptome Study. Genes (Basel) 2023; 14:1801. [PMID: 37761940 PMCID: PMC10530489 DOI: 10.3390/genes14091801] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2023] [Revised: 09/02/2023] [Accepted: 09/11/2023] [Indexed: 09/29/2023] Open
Abstract
Huntington's disease (HD) is a progressive neurodegenerative disorder caused due to a CAG repeat expansion in the huntingtin (HTT) gene. The primary symptoms of HD include motor dysfunction such as chorea, dystonia, and involuntary movements. The primary motor cortex (BA4) is the key brain region responsible for executing motor/movement activities. Investigating patient and control samples from the BA4 region will provide a deeper understanding of the genes responsible for neuron degeneration and help to identify potential markers. Previous studies have focused on overall differential gene expression and associated biological functions. In this study, we illustrate the relationship between variants and differentially expressed genes/transcripts. We identified variants and their associated genes along with the quantification of genes and transcripts. We also predicted the effect of variants on various regulatory activities and found that many variants are regulating gene expression. Variants affecting miRNA and its targets are also highlighted in our study. Co-expression network studies revealed the role of novel genes. Function interaction network analysis unveiled the importance of genes involved in vesicle-mediated transport. From this unified approach, we propose that genes expressed in immune cells are crucial for reducing neuron death in HD.
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Affiliation(s)
- Nela Pragathi Sneha
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India; (N.P.S.); (S.A.P.D.)
| | - S. Akila Parvathy Dharshini
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India; (N.P.S.); (S.A.P.D.)
| | - Y.-h. Taguchi
- Department of Physics, Chuo University, Kasuga, Bunkyo-ku, Tokyo 112-8551, Japan;
| | - M. Michael Gromiha
- Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600036, Tamil Nadu, India; (N.P.S.); (S.A.P.D.)
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27
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Ta M, Blauwendraat C, Antar T, Leonard HL, Singleton AB, Nalls MA, Iwaki H. Genome-Wide Meta-Analysis of Cerebrospinal Fluid Biomarkers in Alzheimer's Disease and Parkinson's Disease Cohorts. Mov Disord 2023; 38:1697-1705. [PMID: 37539664 DOI: 10.1002/mds.29511] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 04/14/2023] [Accepted: 05/30/2023] [Indexed: 08/05/2023] Open
Abstract
BACKGROUND Amyloid-β, phosphorylated tau (p-tau), and total tau (t-tau) in cerebrospinal fluid are established biomarkers for Alzheimer's disease (AD). In other neurodegenerative diseases, such as Parkinson's disease (PD), these biomarkers have also been found to be altered, and the molecular mechanisms responsible for these alterations are still under investigation. Moreover, the interplay between these mechanisms and the diverse underlying disease states remains to be elucidated. OBJECTIVE To investigate genetic contributions to the AD biomarkers and assess the commonality and heterogeneity of the associations per underlying disease status. METHODS We conducted genome-wide association studies (GWASs) for the AD biomarkers on subjects from the Parkinson's Progression Markers Initiative, the Fox Investigation for New Discovery of Biomarkers, and the Alzheimer's Disease Neuroimaging Initiative, and meta-analyzed with the largest AD GWAS. We tested heterogeneity of associations of interest between different disease statuses (AD, PD, and control). RESULTS We observed three GWAS signals: the APOE locus for amyloid-β, the 3q28 locus between GEMC1 and OSTN for p-tau and t-tau, and the 7p22 locus (top hit: rs60871478, an intronic variant for DNAAF5, also known as HEATR2) for p-tau. The 7p22 locus is novel and colocalized with the brain DNAAF5 expression. Although no heterogeneity from underlying disease status was observed for the earlier GWAS signals, some disease risk loci suggested disease-specific associations with these biomarkers. CONCLUSIONS Our study identified a novel association at the intronic region of DNAAF5 associated with increased levels of p-tau across all diseases. We also observed some disease-specific genetic associations with these biomarkers. Published 2023. This article is a U.S. Government work and is in the public domain in the USA.
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Affiliation(s)
- Michael Ta
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
- Data Tecnica International, Washington, District of Columbia, USA
- Center for Alzheimer's and Related Dementias, National Institute of Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Cornelis Blauwendraat
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
- Center for Alzheimer's and Related Dementias, National Institute of Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Tarek Antar
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
- Center for Alzheimer's and Related Dementias, National Institute of Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Hampton L Leonard
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
- Data Tecnica International, Washington, District of Columbia, USA
- Center for Alzheimer's and Related Dementias, National Institute of Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Andrew B Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
- Center for Alzheimer's and Related Dementias, National Institute of Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
- Data Tecnica International, Washington, District of Columbia, USA
- Center for Alzheimer's and Related Dementias, National Institute of Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
| | - Hirotaka Iwaki
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, Maryland, USA
- Data Tecnica International, Washington, District of Columbia, USA
- Center for Alzheimer's and Related Dementias, National Institute of Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, Maryland, USA
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28
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Cochran JN, Acosta-Uribe J, Esposito BT, Madrigal L, Aguillón D, Giraldo MM, Taylor JW, Bradley J, Fulton-Howard B, Andrews SJ, Acosta-Baena N, Alzate D, Garcia GP, Piedrahita F, Lopez HE, Anderson AG, Rodriguez-Nunez I, Roberts K, Dominantly Inherited Alzheimer Network, Absher D, Myers RM, Beecham GW, Reitz C, Rizzardi LF, Fernandez MV, Goate AM, Cruchaga C, Renton AE, Lopera F, Kosik KS. Genetic associations with age at dementia onset in the PSEN1 E280A Colombian kindred. Alzheimers Dement 2023; 19:3835-3847. [PMID: 36951251 PMCID: PMC10514237 DOI: 10.1002/alz.13021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 02/03/2023] [Accepted: 02/07/2023] [Indexed: 03/24/2023]
Abstract
INTRODUCTION Genetic associations with Alzheimer's disease (AD) age at onset (AAO) could reveal genetic variants with therapeutic applications. We present a large Colombian kindred with autosomal dominant AD (ADAD) as a unique opportunity to discover AAO genetic associations. METHODS A genetic association study was conducted to examine ADAD AAO in 340 individuals with the PSEN1 E280A mutation via TOPMed array imputation. Replication was assessed in two ADAD cohorts, one sporadic early-onset AD study and four late-onset AD studies. RESULTS 13 variants had p<1×10-7 or p<1×10-5 with replication including three independent loci with candidate associations with clusterin including near CLU. Other suggestive associations were identified in or near HS3ST1, HSPG2, ACE, LRP1B, TSPAN10, and TSPAN14. DISCUSSION Variants with suggestive associations with AAO were associated with biological processes including clusterin, heparin sulfate, and amyloid processing. The detection of these effects in the presence of a strong mutation for ADAD reinforces their potentially impactful role.
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Affiliation(s)
| | - Juliana Acosta-Uribe
- Neuroscience Research Institute, University of California, Santa Barbara, California, and Department of Molecular Cellular and Developmental Biology University of California, Santa Barbara, California, USA
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Bianca T Esposito
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Lucia Madrigal
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - David Aguillón
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Margarita M Giraldo
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Jared W Taylor
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | - Joseph Bradley
- Washington University School of Medicine, St. Louis, Missouri, USA
| | - Brian Fulton-Howard
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Shea J Andrews
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Natalia Acosta-Baena
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Diana Alzate
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Gloria P Garcia
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Francisco Piedrahita
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Hugo E Lopez
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | | | | | - Kevin Roberts
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | | | - Devin Absher
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | - Richard M Myers
- HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
| | - Gary W Beecham
- The John P. Hussman Institute for Human Genomics, University of Miami, Miami, Florida, USA
| | - Christiane Reitz
- Department of Epidemiology, Sergievsky Center, Taub Institute for Research on the Aging Brain, Columbia University, New York, New York, USA
| | | | | | - Alison M Goate
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Carlos Cruchaga
- Washington University School of Medicine, St. Louis, Missouri, USA
| | - Alan E Renton
- Department of Genetics & Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Francisco Lopera
- Grupo de Neurociencias de Antioquia. School of Medicine. Universidad de Antioquia, Medellín, Antioquia, Colombia
| | - Kenneth S Kosik
- Neuroscience Research Institute, University of California, Santa Barbara, California, and Department of Molecular Cellular and Developmental Biology University of California, Santa Barbara, California, USA
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Ray NR, Ayodele T, Jean-Francois M, Baez P, Fernandez V, Bradley J, Crane PK, Dalgard CL, Kuzma A, Nicaretta H, Sims R, Williams J, Cuccaro ML, Pericak-Vance MA, Mayeux R, Wang LS, Schellenberg GD, Cruchaga C, Beecham GW, Reitz C. The Early-Onset Alzheimer's Disease Whole-Genome Sequencing Project: Study design and methodology. Alzheimers Dement 2023; 19:4187-4195. [PMID: 37390458 PMCID: PMC10527497 DOI: 10.1002/alz.13370] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2023] [Revised: 06/01/2023] [Accepted: 06/02/2023] [Indexed: 07/02/2023]
Abstract
INTRODUCTION Sequencing efforts to identify genetic variants and pathways underlying Alzheimer's disease (AD) have largely focused on late-onset AD although early-onset AD (EOAD), accounting for ∼10% of cases, is largely unexplained by known mutations, resulting in a lack of understanding of its molecular etiology. METHODS Whole-genome sequencing and harmonization of clinical, neuropathological, and biomarker data of over 5000 EOAD cases of diverse ancestries. RESULTS A publicly available genomics resource for EOAD with extensive harmonized phenotypes. Primary analysis will (1) identify novel EOAD risk loci and druggable targets; (2) assess local-ancestry effects; (3) create EOAD prediction models; and (4) assess genetic overlap with cardiovascular and other traits. DISCUSSION This novel resource complements over 50,000 control and late-onset AD samples generated through the Alzheimer's Disease Sequencing Project (ADSP). The harmonized EOAD/ADSP joint call will be available through upcoming ADSP data releases and will allow for additional analyses across the full onset range. HIGHLIGHTS Sequencing efforts to identify genetic variants and pathways underlying Alzheimer's disease (AD) have largely focused on late-onset AD although early-onset AD (EOAD), accounting for ∼10% of cases, is largely unexplained by known mutations. This results in a significant lack of understanding of the molecular etiology of this devastating form of the disease. The Early-Onset Alzheimer's Disease Whole-genome Sequencing Project is a collaborative initiative to generate a large-scale genomics resource for early-onset Alzheimer's disease with extensive harmonized phenotype data. Primary analyses are designed to (1) identify novel EOAD risk and protective loci and druggable targets; (2) assess local-ancestry effects; (3) create EOAD prediction models; and (4) assess genetic overlap with cardiovascular and other traits. The harmonized genomic and phenotypic data from this initiative will be available through NIAGADS.
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Affiliation(s)
- Nicholas R. Ray
- Gertrude H. Sergievsky Center, Columbia University, New
York, NY 10032, USA
- Taub Institute for Research on Alzheimer’s Disease
and the Aging Brain, Columbia University, New York, NY 10032, USA
| | - Temitope Ayodele
- Gertrude H. Sergievsky Center, Columbia University, New
York, NY 10032, USA
| | - Melissa Jean-Francois
- The John P. Hussman Institute for Human Genomics,
University of Miami, Miami, FL 33136, USA
- Dr. John T. MacDonald Foundation Department of Human
Genetics, University of Miami, Coral Gables, FL 33146, USA
| | - Penelope Baez
- Gertrude H. Sergievsky Center, Columbia University, New
York, NY 10032, USA
| | - Victoria Fernandez
- Department of Psychiatry, Neurology and Genetics,
Washington University School of Medicine, St. Louis, MO 63130, USA
- Neurogenomics and Informatic (NGI) Center, Washington
University School of Medicine, St. Louis, MO 63130, USA
| | - Joseph Bradley
- Department of Psychiatry, Neurology and Genetics,
Washington University School of Medicine, St. Louis, MO 63130, USA
- Neurogenomics and Informatic (NGI) Center, Washington
University School of Medicine, St. Louis, MO 63130, USA
| | - Paul K. Crane
- Division of General Internal Medicine, University of
Washington, Seattle, WA 98195, USA
| | - Clifton L. Dalgard
- Department of Anatomy, Physiology & Genetics,
Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
- The American Genome Center, Uniformed Services University
of the Health Sciences, Bethesda, MD 20814, USA
| | - Amanda Kuzma
- Penn Neurodegeneration Genomics Center, Department of
Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of
Medicine, Philadelphia, PA 19104, USA
| | - Heather Nicaretta
- Penn Neurodegeneration Genomics Center, Department of
Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of
Medicine, Philadelphia, PA 19104, USA
| | - Rebecca Sims
- Division of Psychological Medicine and Clinical
Neurosciences, School of Medicine, Cardiff University, Cardiff CF10 3AT, UK
| | - Julie Williams
- UK Dementia Research Institute, Cardiff University,
Cardiff CF10 3AT, UK
- Division of Psychological Medicine and Clinical
Neurosciences, School of Medicine, Cardiff University, Cardiff CF10 3AT, UK
| | - Michael L. Cuccaro
- The John P. Hussman Institute for Human Genomics,
University of Miami, Miami, FL 33136, USA
- Dr. John T. MacDonald Foundation Department of Human
Genetics, University of Miami, Coral Gables, FL 33146, USA
| | - Margaret A. Pericak-Vance
- The John P. Hussman Institute for Human Genomics,
University of Miami, Miami, FL 33136, USA
- Dr. John T. MacDonald Foundation Department of Human
Genetics, University of Miami, Coral Gables, FL 33146, USA
| | - Richard Mayeux
- Gertrude H. Sergievsky Center, Columbia University, New
York, NY 10032, USA
- Taub Institute for Research on Alzheimer’s Disease
and the Aging Brain, Columbia University, New York, NY 10032, USA
- Department of Neurology, Columbia University, New York, NY
10032, USA
- Department of Epidemiology, Columbia University, New York,
NY 10032, USA
| | - Li-San Wang
- Penn Neurodegeneration Genomics Center, Department of
Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of
Medicine, Philadelphia, PA 19104, USA
| | - Gerard D. Schellenberg
- Penn Neurodegeneration Genomics Center, Department of
Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of
Medicine, Philadelphia, PA 19104, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Neurology and Genetics,
Washington University School of Medicine, St. Louis, MO 63130, USA
- Neurogenomics and Informatic (NGI) Center, Washington
University School of Medicine, St. Louis, MO 63130, USA
| | - Gary W. Beecham
- The John P. Hussman Institute for Human Genomics,
University of Miami, Miami, FL 33136, USA
- Dr. John T. MacDonald Foundation Department of Human
Genetics, University of Miami, Coral Gables, FL 33146, USA
| | - Christiane Reitz
- Gertrude H. Sergievsky Center, Columbia University, New
York, NY 10032, USA
- Taub Institute for Research on Alzheimer’s Disease
and the Aging Brain, Columbia University, New York, NY 10032, USA
- Department of Neurology, Columbia University, New York, NY
10032, USA
- Department of Epidemiology, Columbia University, New York,
NY 10032, USA
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Yang LG, March ZM, Stephenson RA, Narayan PS. Apolipoprotein E in lipid metabolism and neurodegenerative disease. Trends Endocrinol Metab 2023; 34:430-445. [PMID: 37357100 PMCID: PMC10365028 DOI: 10.1016/j.tem.2023.05.002] [Citation(s) in RCA: 30] [Impact Index Per Article: 30.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Revised: 05/05/2023] [Accepted: 05/09/2023] [Indexed: 06/27/2023]
Abstract
Dysregulation of lipid metabolism has emerged as a central component of many neurodegenerative diseases. Variants of the lipid transport protein, apolipoprotein E (APOE), modulate risk and resilience in several neurodegenerative diseases including late-onset Alzheimer's disease (LOAD). Allelic variants of the gene, APOE, alter the lipid metabolism of cells and tissues and have been broadly associated with several other cellular and systemic phenotypes. Targeting APOE-associated metabolic pathways may offer opportunities to alter disease-related phenotypes and consequently, attenuate disease risk and impart resilience to multiple neurodegenerative diseases. We review the molecular, cellular, and tissue-level alterations to lipid metabolism that arise from different APOE isoforms. These changes in lipid metabolism could help to elucidate disease mechanisms and tune neurodegenerative disease risk and resilience.
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Affiliation(s)
- Linda G Yang
- Genetics and Biochemistry Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health, Bethesda, MD, USA
| | - Zachary M March
- Genetics and Biochemistry Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health, Bethesda, MD, USA
| | - Roxan A Stephenson
- Genetics and Biochemistry Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health, Bethesda, MD, USA
| | - Priyanka S Narayan
- Genetics and Biochemistry Branch, National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health, Bethesda, MD, USA.; National Institute of Neurological Disorders and Stroke (NINDS), National Institutes of Health, Bethesda, MD, USA; Center for Alzheimer's and Related Dementias (CARD), National Institutes of Health, Bethesda, MD, USA.
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31
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Bradley J, Gorijala P, Schindler SE, Sung YJ, Ances B, Fernandez MV, Cruchaga C. Genetic architecture of plasma Alzheimer disease biomarkers. Hum Mol Genet 2023; 32:2532-2543. [PMID: 37208024 PMCID: PMC10360384 DOI: 10.1093/hmg/ddad087] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 04/29/2023] [Accepted: 05/16/2023] [Indexed: 05/21/2023] Open
Abstract
Genome-wide association studies (GWAS) of cerebrospinal fluid (CSF) Alzheimer's Disease (AD) biomarker levels have identified novel genes implicated in disease risk, onset and progression. However, lumbar punctures have limited availability and may be perceived as invasive. Blood collection is readily available and well accepted, but it is not clear whether plasma biomarkers will be informative for genetic studies. Here we perform genetic analyses on concentrations of plasma amyloid-β peptides Aβ40 (n = 1,467) and Aβ42 (n = 1,484), Aβ42/40 (n = 1467) total tau (n = 504), tau phosphorylated (p-tau181; n = 1079) and neurofilament light (NfL; n = 2,058). GWAS and gene-based analysis was used to identify single variant and genes associated with plasma levels. Finally, polygenic risk score and summary statistics were used to investigate overlapping genetic architecture between plasma biomarkers, CSF biomarkers and AD risk. We found a total of six genome-wide significant signals. APOE was associated with plasma Aβ42, Aβ42/40, tau, p-tau181 and NfL. We proposed 10 candidate functional genes on the basis of 12 single nucleotide polymorphism-biomarker pairs and brain differential gene expression analysis. We found a significant genetic overlap between CSF and plasma biomarkers. We also demonstrate that it is possible to improve the specificity and sensitivity of these biomarkers, when genetic variants regulating protein levels are included in the model. This current study using plasma biomarker levels as quantitative traits can be critical to identification of novel genes that impact AD and more accurate interpretation of plasma biomarker levels.
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Affiliation(s)
- Joseph Bradley
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurologic Diseases, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Priyanka Gorijala
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Suzanne E Schindler
- Hope Center for Neurologic Diseases, Washington University in St. Louis, St. Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Yun J Sung
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurologic Diseases, Washington University in St. Louis, St. Louis, MO 63110, USA
| | - Beau Ances
- Hope Center for Neurologic Diseases, Washington University in St. Louis, St. Louis, MO 63110, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Maria V Fernandez
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurologic Diseases, Washington University in St. Louis, St. Louis, MO 63110, USA
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Vasiljevic E, Koscik RL, Jonaitis E, Betthauser T, Johnson SC, Engelman CD. Cognitive trajectories diverge by genetic risk in a preclinical longitudinal cohort. Alzheimers Dement 2023; 19:3108-3118. [PMID: 36723444 PMCID: PMC10390653 DOI: 10.1002/alz.12920] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 12/06/2022] [Accepted: 12/12/2022] [Indexed: 02/02/2023]
Abstract
INTRODUCTION We sought to characterize the timing of changes in cognitive trajectories related to genetic risk using the apolipoprotein E (APOE) score, a continuous measure of Alzheimer's disease (AD) risk. We also aimed to determine whether that timing was different when genetic risk was measured using an AD polygenic risk score (PRS) that contains APOE. METHODS We analyzed trajectories (N ≈1135) for four neuropsychological composite scores using mixed effects regression for longitudinal change across APOE scores and PRS of participants in the Wisconsin Registry for Alzheimer's Prevention, a longitudinal study of adults aged 40 to 70 at baseline, with a median participant follow-up time of 7.8 years. RESULTS We found a significant non-linear age-by-APOE score interaction in predicting cognitive decline. Cognitive trajectories diverged by APOE score at approximately 65 years of age. A 0.5 standard deviation difference in cognition between extreme percentiles of the PRS was predicted to occur 1 to 2 years before that of the APOE score. DISCUSSION Cognitive decline differs across time and APOE score. Estimates did not substantially shift with the AD PRS. HIGHLIGHTS The apolipoprotein E (APOE) score, a continuous measure, accounts for non-linear genetic risk of Alzheimer's disease. Non-linear age interacts with the APOE score to affect cognition. Cognitive decline starts to differ by APOE score levels at approximately age 65. Cognitive decline timing by polygenic risk (including APOE) is similar to APOE alone.
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Affiliation(s)
- Eva Vasiljevic
- Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, 610 Walnut Dr., Madison, WI 53726, USA
- Center for Demography of Health and Aging, University of Wisconsin-Madison, 1180 Observatory Drive Madison, WI 53706, USA
| | - Rebecca Langhough Koscik
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, 610 Walnut Street, 9th Floor, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, 600 Highland Avenue, MC 2420, Madison, Wisconsin 53792, USA
| | - Erin Jonaitis
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, 610 Walnut Street, 9th Floor, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, 600 Highland Avenue, MC 2420, Madison, Wisconsin 53792, USA
| | - Tobey Betthauser
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, 600 Highland Avenue, MC 2420, Madison, Wisconsin 53792, USA
- Department of Medicine, University of Wisconsin-Madison, 1685 Highland Avenue, 5158 Medical Foundation Centennial Building, Madison, WI 53705, USA
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, 610 Walnut Street, 9th Floor, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, 600 Highland Avenue, MC 2420, Madison, Wisconsin 53792, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, 2500 Overlook Terrace, Madison, WI 53705, USA
| | - Corinne D. Engelman
- Department of Population Health Sciences, University of Wisconsin School of Medicine and Public Health, 610 Walnut Dr., Madison, WI 53726, USA
- Wisconsin Alzheimer’s Institute, University of Wisconsin School of Medicine and Public Health, 610 Walnut Street, 9th Floor, Madison, WI 53726, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, 600 Highland Avenue, MC 2420, Madison, Wisconsin 53792, USA
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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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Kang M, Ang TFA, Devine SA, Sherva R, Mukherjee S, Trittschuh EH, Gibbons LE, Scollard P, Lee M, Choi SE, Klinedinst B, Nakano C, Dumitrescu LC, Durant A, Hohman TJ, Cuccaro ML, Saykin AJ, Kukull WA, Bennett DA, Wang LS, Mayeux RP, Haines JL, Pericak-Vance MA, Schellenberg GD, Crane PK, Au R, Lunetta KL, Mez JB, Farrer LA. A genome-wide search for pleiotropy in more than 100,000 harmonized longitudinal cognitive domain scores. Mol Neurodegener 2023; 18:40. [PMID: 37349795 PMCID: PMC10286470 DOI: 10.1186/s13024-023-00633-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 06/06/2023] [Indexed: 06/24/2023] Open
Abstract
BACKGROUND More than 75 common variant loci account for only a portion of the heritability for Alzheimer's disease (AD). A more complete understanding of the genetic basis of AD can be deduced by exploring associations with AD-related endophenotypes. METHODS We conducted genome-wide scans for cognitive domain performance using harmonized and co-calibrated scores derived by confirmatory factor analyses for executive function, language, and memory. We analyzed 103,796 longitudinal observations from 23,066 members of community-based (FHS, ACT, and ROSMAP) and clinic-based (ADRCs and ADNI) cohorts using generalized linear mixed models including terms for SNP, age, SNP × age interaction, sex, education, and five ancestry principal components. Significance was determined based on a joint test of the SNP's main effect and interaction with age. Results across datasets were combined using inverse-variance meta-analysis. Genome-wide tests of pleiotropy for each domain pair as the outcome were performed using PLACO software. RESULTS Individual domain and pleiotropy analyses revealed genome-wide significant (GWS) associations with five established loci for AD and AD-related disorders (BIN1, CR1, GRN, MS4A6A, and APOE) and eight novel loci. ULK2 was associated with executive function in the community-based cohorts (rs157405, P = 2.19 × 10-9). GWS associations for language were identified with CDK14 in the clinic-based cohorts (rs705353, P = 1.73 × 10-8) and LINC02712 in the total sample (rs145012974, P = 3.66 × 10-8). GRN (rs5848, P = 4.21 × 10-8) and PURG (rs117523305, P = 1.73 × 10-8) were associated with memory in the total and community-based cohorts, respectively. GWS pleiotropy was observed for language and memory with LOC107984373 (rs73005629, P = 3.12 × 10-8) in the clinic-based cohorts, and with NCALD (rs56162098, P = 1.23 × 10-9) and PTPRD (rs145989094, P = 8.34 × 10-9) in the community-based cohorts. GWS pleiotropy was also found for executive function and memory with OSGIN1 (rs12447050, P = 4.09 × 10-8) and PTPRD (rs145989094, P = 3.85 × 10-8) in the community-based cohorts. Functional studies have previously linked AD to ULK2, NCALD, and PTPRD. CONCLUSION Our results provide some insight into biological pathways underlying processes leading to domain-specific cognitive impairment and AD, as well as a conduit toward a syndrome-specific precision medicine approach to AD. Increasing the number of participants with harmonized cognitive domain scores will enhance the discovery of additional genetic factors of cognitive decline leading to AD and related dementias.
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Affiliation(s)
- Moonil Kang
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street E200, Boston, MA 02118 USA
| | - Ting Fang Alvin Ang
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Slone Epidemiology Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
| | - Sherral A. Devine
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
| | - Richard Sherva
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street E200, Boston, MA 02118 USA
| | - Shubhabrata Mukherjee
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Emily H. Trittschuh
- Geriatric Research, Education, and Clinical Center, Veterans Affairs Puget Sound Health Care System, Seattle, WA USA
- Department of Psychiatry and Behavioral Sciences, University of Washington School of Medicine, Seattle, WA USA
| | - Laura E. Gibbons
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Phoebe Scollard
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Michael Lee
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Seo-Eun Choi
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Brandon Klinedinst
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Connie Nakano
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Logan C. Dumitrescu
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN USA
| | - Alaina Durant
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN USA
| | - Timothy J. Hohman
- Vanderbilt Memory & Alzheimer’s Center, Vanderbilt University Medical Center, Nashville, TN USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN USA
| | - Michael L. Cuccaro
- John P. Hussman Institute for Human Genomics, Miller School of Medicine, Miami, FL USA
| | - Andrew J. Saykin
- Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology and Imaging Services, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN USA
| | - Walter A. Kukull
- Department of Epidemiology, University of Washington, Seattle, WA USA
| | - David A. Bennett
- Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL USA
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA USA
| | - Richard P. Mayeux
- Department of Neurology, Columbia University School of Medicine, New York, NY USA
| | - Jonathan L. Haines
- Cleveland Institute for Computational Biology, Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH USA
| | | | - Gerard D. Schellenberg
- Department of Pathology and Laboratory Medicine, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA USA
| | - Paul K. Crane
- Department of Medicine, University of Washington School of Medicine, Seattle, WA USA
| | - Rhoda Au
- Department of Anatomy and Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Slone Epidemiology Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA USA
| | - Kathryn L. Lunetta
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA USA
| | - Jesse B. Mez
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
| | - Lindsay A. Farrer
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, 72 East Concord Street E200, Boston, MA 02118 USA
- Framingham Heart Study, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Boston University Alzheimer’s Disease Research Center, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
- Department of Ophthalmology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA USA
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Ta M, Blauwendraat C, Antar T, Leonard HL, Singleton AB, Nalls MA, Iwaki H. Genome-wide meta-analysis of CSF biomarkers in Alzheimer's disease and Parkinson's disease cohorts. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.13.23291354. [PMID: 37398091 PMCID: PMC10312859 DOI: 10.1101/2023.06.13.23291354] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
Background Amyloid beta (Aβ), phosphorylated tau (p-tau), and total tau (t-tau) in cerebrospinal fluid are established biomarkers for Alzheimer's disease (AD). In other neurodegenerative diseases, such as Parkinson's disease (PD), these biomarkers have also been found to be altered, and the molecular mechanisms responsible for these alterations are still under investigation. Moreover, the interplay between these mechanisms and the diverse underlying disease states remains to be elucidated. Objectives To investigate genetic contributions to the AD biomarkers and assess the commonality and heterogeneity of the associations per underlying disease status. Methods We conducted GWAS for the AD biomarkers on subjects from the Parkinson's Progression Markers Initiative (PPMI), the Fox Investigation for New Discovery of Biomarkers (BioFIND), and the Alzheimer's Disease Neuroimaging Initiative (ADNI) and meta-analyzed with the largest AD GWAS.[7] We tested heterogeneity of associations of interest between different disease statuses (AD, PD, and control). Results We observed three GWAS signals: the APOE locus for Aβ, the 3q28 locus between GEMC1 and OSTN for p-tau and t-tau, and the 7p22 locus (top hit: rs60871478, an intronic variant for DNAAF5 , also known as HEATR2 ) for p-tau. The 7p22 locus is novel and co-localized with the brain DNAAF5 expression. While no heterogeneity from underlying disease status was observed for the above GWAS signals, some disease risk loci suggested disease specific associations with these biomarkers. Conclusions Our study identified a novel association at the intronic region of DNAAF5 associated with increased levels of p-tau across all diseases. We also observed some disease specific genetic associations with these biomarkers.
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Trindade D, Cachide M, Soares Martins T, Guedes S, Rosa IM, da Cruz e Silva OA, Henriques AG. Monitoring clusterin and fibrillar structures in aging and dementia. AGING BRAIN 2023; 3:100080. [PMID: 37346145 PMCID: PMC10279921 DOI: 10.1016/j.nbas.2023.100080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 05/25/2023] [Accepted: 05/26/2023] [Indexed: 06/23/2023] Open
Abstract
Objective Clusterin is involved in a variety of physiological processes, including proteostasis. Several clusterin polymorphisms were associated with an increased risk of developing Alzheimer's disease, the world-leading cause of dementia. Herein, the effect of a clusterin polymorphism, aging and dementia in the levels of clusterin in human plasma were analysed in a primary care-based cohort, and the association of this chaperone with fibrillar structures discussed. Methods 64 individuals with dementia (CDR≥1) and 64 age- and sex-matched Controls from a Portuguese cohort were genotyped for CLU rs1136000 polymorphism, and the plasma levels of clusterin and fibrils were assessed. Results An increased prevalence of the CC genotype was observed for the dementia group, although no significant robustness was achieved. CLU rs11136000 SNP did not significantly change plasma clusterin levels in demented individuals. Instead, clusterin levels decreased with aging and even more in individuals with dementia. Importantly, plasma clusterin levels correlated with the presence of fibrillar structures in Control individuals, but not in those with dementia. Conclusion This study reveals a significant decrease in plasma clusterin in demented individuals with aging, which related to altered clusterin-fibrils dynamics. Potentially, plasma clusterin and its association with fibrillar structures can be used to monitor dementia progression along aging.
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Affiliation(s)
| | | | | | | | | | | | - Ana Gabriela Henriques
- Corresponding author at: Neuroscience and Signaling Group, Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, 3810-193 Aveiro, Portugal.
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Ou YN, Ge YJ, Wu BS, Zhang Y, Jiang YC, Kuo K, Yang L, Tan L, Feng JF, Cheng W, Yu JT. The genetic architecture of fornix white matter microstructure and their involvement in neuropsychiatric disorders. Transl Psychiatry 2023; 13:180. [PMID: 37236919 DOI: 10.1038/s41398-023-02475-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/26/2022] [Revised: 05/03/2023] [Accepted: 05/12/2023] [Indexed: 05/28/2023] Open
Abstract
The fornix is a white matter bundle located in the center of the hippocampaldiencephalic limbic circuit that controls memory and executive functions, yet its genetic architectures and involvement in brain disorders remain largely unknown. We carried out a genome-wide association analysis of 30,832 UK Biobank individuals of the six fornix diffusion magnetic resonance imaging (dMRI) traits. The post-GWAS analysis allowed us to identify causal genetic variants in phenotypes at the single nucleotide polymorphisms (SNP), locus, and gene levels, as well as genetic overlap with brain health-related traits. We further generalized our GWAS in adolescent brain cognitive development (ABCD) cohort. The GWAS identified 63 independent significant variants within 20 genomic loci associated (P < 8.33 × 10-9) with the six fornix dMRI traits. Geminin coiled-coil domain containing (GMNC) and NUAK family SNF1-like kinase 1 (NUAK1) gene were highlighted, which were found in UKB and replicated in ABCD. The heritability of the six traits ranged from 10% to 27%. Gene mapping strategies identified 213 genes, where 11 were supported by all of four methods. Gene-based analyses revealed pathways relating to cell development and differentiation, with astrocytes found to be significantly enriched. Pleiotropy analyses with eight neurological and psychiatric disorders revealed shared variants, especially with schizophrenia under the conjFDR threshold of 0.05. These findings advance our understanding of the complex genetic architectures of fornix and their relevance in neurological and psychiatric disorders.
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Affiliation(s)
- Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Yi-Jun Ge
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Bang-Sheng 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, National Center for Neurological Disorders, Shanghai, China
| | - Yi Zhang
- 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, National Center for Neurological Disorders, Shanghai, China
| | - Yu-Chao Jiang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
| | - Kevin Kuo
- 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, National Center for Neurological Disorders, Shanghai, China
| | - Liu Yang
- 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, National Center for Neurological Disorders, Shanghai, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, China
- MOE Frontiers Center for Brain Science, Fudan University, Shanghai, China
- Zhangjiang Fudan International Innovation Center, Shanghai, China
| | - Wei Cheng
- 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, National Center for Neurological Disorders, Shanghai, China.
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence (Fudan University), Ministry of Education, Shanghai, China.
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-Inspired Intelligence, Zhejiang Normal University, Jinhua, 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, National Center for Neurological Disorders, Shanghai, China.
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Timsina J, Ali M, Do A, Wang L, Sung YJ, Cruchaga C. Harmonization of CSF and imaging biomarkers for Alzheimer's disease biomarkers: need and practical applications for genetics studies and preclinical classification. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.24.542118. [PMID: 37292823 PMCID: PMC10245826 DOI: 10.1101/2023.05.24.542118] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
INTRODUCTION In Alzheimer's disease (AD) research, cerebrospinal fluid (CSF) Amyloid beta (Aβ), Tau and pTau are the most accepted and well validated biomarkers. Several methods and platforms exist to measure those biomarkers which leads to challenges in combining data across studies. Thus, there is a need to identify methods that harmonize and standardize these values. METHODS We used a Z-score based approach to harmonize CSF and amyloid imaging data from multiple cohorts and compared GWAS result using this method with currently accepted methods. We also used a generalized mixture modelling to calculate the threshold for biomarker-positivity. RESULTS Z-scores method performed as well as meta-analysis and did not lead to any spurious results. Cutoffs calculated with this approach were found to be very similar to those reported previously. DISCUSSION This approach can be applied to heterogeneous platforms and provides biomarker cut-offs consistent with the classical approaches without requiring any additional data.
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Affiliation(s)
- Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Muhammad Ali
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Anh Do
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Lihua Wang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
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Merchant JP, Zhu K, Henrion MYR, Zaidi SSA, Lau B, Moein S, Alamprese ML, Pearse RV, Bennett DA, Ertekin-Taner N, Young-Pearse TL, Chang R. Predictive network analysis identifies JMJD6 and other potential key drivers in Alzheimer's disease. Commun Biol 2023; 6:503. [PMID: 37188718 PMCID: PMC10185548 DOI: 10.1038/s42003-023-04791-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 03/31/2023] [Indexed: 05/17/2023] Open
Abstract
Despite decades of genetic studies on late-onset Alzheimer's disease, the underlying molecular mechanisms remain unclear. To better comprehend its complex etiology, we use an integrative approach to build robust predictive (causal) network models using two large human multi-omics datasets. We delineate bulk-tissue gene expression into single cell-type gene expression and integrate clinical and pathologic traits, single nucleotide variation, and deconvoluted gene expression for the construction of cell type-specific predictive network models. Here, we focus on neuron-specific network models and prioritize 19 predicted key drivers modulating Alzheimer's pathology, which we then validate by knockdown in human induced pluripotent stem cell-derived neurons. We find that neuronal knockdown of 10 of the 19 targets significantly modulates levels of amyloid-beta and/or phosphorylated tau peptides, most notably JMJD6. We also confirm our network structure by RNA sequencing in the neurons following knockdown of each of the 10 targets, which additionally predicts that they are upstream regulators of REST and VGF. Our work thus identifies robust neuronal key drivers of the Alzheimer's-associated network state which may represent therapeutic targets with relevance to both amyloid and tau pathology in Alzheimer's disease.
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Affiliation(s)
- Julie P Merchant
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Neuroscience Graduate Group, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Kuixi Zhu
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA
| | - Marc Y R Henrion
- Liverpool School of Tropical Medicine, Pembroke Place, Liverpool, Pembroke Place, L3 5QA, UK
- Malawi-Liverpool-Wellcome Trust Clinical Research Programme, PO Box 30096, Blantyre, Malawi
| | - Syed S A Zaidi
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA
| | - Branden Lau
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA
- Arizona Research Labs, Genetics Core, University of Arizona, Tucson, AZ, USA
| | - Sara Moein
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA
| | - Melissa L Alamprese
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA
| | - Richard V Pearse
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, FL, USA
- Department of Neurology, Mayo Clinic Florida, Jacksonville, FL, USA
| | - Tracy L Young-Pearse
- Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Harvard Stem Cell Institute, Harvard University, Boston, MA, USA.
| | - Rui Chang
- The Center for Innovation in Brain Sciences, University of Arizona, Tucson, AZ, USA.
- Department of Neurology, University of Arizona, Tucson, AZ, USA.
- INTelico Therapeutics LLC, Tucson, AZ, USA.
- PATH Biotech LLC, Tucson, AZ, USA.
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Reitz C, Pericak-Vance MA, Foroud T, Mayeux R. A global view of the genetic basis of Alzheimer disease. Nat Rev Neurol 2023; 19:261-277. [PMID: 37024647 PMCID: PMC10686263 DOI: 10.1038/s41582-023-00789-z] [Citation(s) in RCA: 29] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/21/2023] [Indexed: 04/08/2023]
Abstract
The risk of Alzheimer disease (AD) increases with age, family history and informative genetic variants. Sadly, there is still no cure or means of prevention. As in other complex diseases, uncovering genetic causes of AD could identify underlying pathological mechanisms and lead to potential treatments. Rare, autosomal dominant forms of AD occur in middle age as a result of highly penetrant genetic mutations, but the most common form of AD occurs later in life. Large-scale, genome-wide analyses indicate that 70 or more genes or loci contribute to AD. One of the major factors limiting progress is that most genetic data have been obtained from non-Hispanic white individuals in Europe and North America, preventing the development of personalized approaches to AD in individuals of other ethnicities. Fortunately, emerging genetic data from other regions - including Africa, Asia, India and South America - are now providing information on the disease from a broader range of ethnicities. Here, we summarize the current knowledge on AD genetics in populations across the world. We predominantly focus on replicated genetic discoveries but also include studies in ethnic groups where replication might not be feasible. We attempt to identify gaps that need to be addressed to achieve a complete picture of the genetic and molecular factors that drive AD in individuals across the globe.
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Affiliation(s)
- Christiane Reitz
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA
- The Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA
- Department of Neurology, Columbia University, New York, NY, USA
- Department of Epidemiology, Columbia University, New York, NY, USA
| | - Margaret A Pericak-Vance
- The John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, USA
- The Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Tatiana Foroud
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, USA
- National Centralized Repository for Alzheimer's Disease and Related Dementias, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Richard Mayeux
- The Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Columbia University, New York, NY, USA.
- The Gertrude H. Sergievsky Center, Columbia University, New York, NY, USA.
- Department of Neurology, Columbia University, New York, NY, USA.
- Department of Epidemiology, Columbia University, New York, NY, USA.
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Ali M, Archer DB, Gorijala P, Western D, Timsina J, Fernández MV, Wang TC, Satizabal CL, Yang Q, Beiser AS, Wang R, Chen G, Gordon B, Benzinger TLS, Xiong C, Morris JC, Bateman RJ, Karch CM, McDade E, Goate A, Seshadri S, Mayeux RP, Sperling RA, Buckley RF, Johnson KA, Won HH, Jung SH, Kim HR, Seo SW, Kim HJ, Mormino E, Laws SM, Fan KH, Kamboh MI, Vemuri P, Ramanan VK, Yang HS, Wenzel A, Rajula HSR, Mishra A, Dufouil C, Debette S, Lopez OL, DeKosky ST, Tao F, Nagle MW, Hohman TJ, Sung YJ, Dumitrescu L, Cruchaga C. Large multi-ethnic genetic analyses of amyloid imaging identify new genes for Alzheimer disease. Acta Neuropathol Commun 2023; 11:68. [PMID: 37101235 PMCID: PMC10134547 DOI: 10.1186/s40478-023-01563-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2023] [Accepted: 04/05/2023] [Indexed: 04/28/2023] Open
Abstract
Amyloid PET imaging has been crucial for detecting the accumulation of amyloid beta (Aβ) deposits in the brain and to study Alzheimer's disease (AD). We performed a genome-wide association study on the largest collection of amyloid imaging data (N = 13,409) to date, across multiple ethnicities from multicenter cohorts to identify variants associated with brain amyloidosis and AD risk. We found a strong APOE signal on chr19q.13.32 (top SNP: APOE ɛ4; rs429358; β = 0.35, SE = 0.01, P = 6.2 × 10-311, MAF = 0.19), driven by APOE ɛ4, and five additional novel associations (APOE ε2/rs7412; rs73052335/rs5117, rs1081105, rs438811, and rs4420638) independent of APOE ɛ4. APOE ɛ4 and ε2 showed race specific effect with stronger association in Non-Hispanic Whites, with the lowest association in Asians. Besides the APOE, we also identified three other genome-wide loci: ABCA7 (rs12151021/chr19p.13.3; β = 0.07, SE = 0.01, P = 9.2 × 10-09, MAF = 0.32), CR1 (rs6656401/chr1q.32.2; β = 0.1, SE = 0.02, P = 2.4 × 10-10, MAF = 0.18) and FERMT2 locus (rs117834516/chr14q.22.1; β = 0.16, SE = 0.03, P = 1.1 × 10-09, MAF = 0.06) that all colocalized with AD risk. Sex-stratified analyses identified two novel female-specific signals on chr5p.14.1 (rs529007143, β = 0.79, SE = 0.14, P = 1.4 × 10-08, MAF = 0.006, sex-interaction P = 9.8 × 10-07) and chr11p.15.2 (rs192346166, β = 0.94, SE = 0.17, P = 3.7 × 10-08, MAF = 0.004, sex-interaction P = 1.3 × 10-03). We also demonstrated that the overall genetic architecture of brain amyloidosis overlaps with that of AD, Frontotemporal Dementia, stroke, and brain structure-related complex human traits. Overall, our results have important implications when estimating the individual risk to a population level, as race and sex will needed to be taken into account. This may affect participant selection for future clinical trials and therapies.
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Affiliation(s)
- Muhammad Ali
- Department of Psychiatry, Washington University, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University, St. Louis, MO, 63110, USA
| | - Derek B Archer
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Priyanka Gorijala
- Department of Psychiatry, Washington University, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University, St. Louis, MO, 63110, USA
| | - Daniel Western
- Department of Psychiatry, Washington University, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University, St. Louis, MO, 63110, USA
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University, St. Louis, MO, 63110, USA
| | - Maria V Fernández
- Department of Psychiatry, Washington University, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University, St. Louis, MO, 63110, USA
| | - Ting-Chen Wang
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health, San Antonio, TX, 78229, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | - Qiong Yang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Alexa S Beiser
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- Framingham Heart Study, Framingham, MA, USA
| | | | - Gengsheng Chen
- Knight Alzheimer's Disease Research Center, Washington University, St Louis, MO, USA
- Mallinckrodt Institute of Radiology, Washington University, St Louis, MO, USA
| | - Brian Gordon
- Knight Alzheimer's Disease Research Center, Washington University, St Louis, MO, USA
- Mallinckrodt Institute of Radiology, Washington University, St Louis, MO, USA
| | - Tammie L S Benzinger
- Knight Alzheimer's Disease Research Center, Washington University, St Louis, MO, USA
- Mallinckrodt Institute of Radiology, Washington University, St Louis, MO, USA
| | - Chengjie Xiong
- Knight Alzheimer's Disease Research Center, Washington University, St Louis, MO, USA
| | - John C Morris
- Knight Alzheimer's Disease Research Center, Washington University, St Louis, MO, USA
- Department of Neurology, Washington University, St Louis, MO, USA
| | - Randall J Bateman
- Knight Alzheimer's Disease Research Center, Washington University, St Louis, MO, USA
- Department of Neurology, Washington University, St Louis, MO, USA
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Celeste M Karch
- Department of Psychiatry, Washington University, St. Louis, MO, 63110, USA
| | - Eric McDade
- Department of Neurology, Washington University, St Louis, MO, USA
| | - Alison Goate
- Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Sudha Seshadri
- Framingham Heart Study, Framingham, MA, USA
- Boston University School of Medicine, Boston, MA, USA
| | - Richard P Mayeux
- The Department of Neurology, Columbia University, New York, NY, USA
| | - Reisa A Sperling
- Department of Neurology, Harvard Medical School, Boston, MA, USA
- Brigham and Women's Hospital and Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Rachel F Buckley
- Brigham and Women's Hospital and Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Charlestown, MA, USA
| | - Keith A Johnson
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Hong-Hee Won
- Department of Digital Health, Samsung Medical Center, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
| | - Sang-Hyuk Jung
- Department of Digital Health, Samsung Medical Center, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
| | - Hang-Rai Kim
- Department of Neurology, Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang, Republic of Korea
| | - Sang Won Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Hee Jin Kim
- Department of Digital Health, Samsung Medical Center, SAIHST, Sungkyunkwan University, Seoul, Republic of Korea
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Elizabeth Mormino
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, USA
| | - Simon M Laws
- Centre for Precision Health, Edith Cowan University, 270 Joondalup Dr, Joondalup, WA, 6027, Australia
| | - Kang-Hsien Fan
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - M Ilyas Kamboh
- Department of Human Genetics, University of Pittsburgh, Pittsburgh, PA, USA
| | - Prashanthi Vemuri
- Department of Radiology, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Vijay K Ramanan
- Department of Neurology, Mayo Clinic-Minnesota, Rochester, MN, 55905, USA
| | - Hyun-Sik Yang
- Department of Neurology, Brigham and Women's Hospital, Boston, MA, USA
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, USA
| | - Allen Wenzel
- Wisconsin Alzheimer's Institute, Madison, WI, USA
| | - Hema Sekhar Reddy Rajula
- UMR 1219, University of Bordeaux, INSERM, Bordeaux Population Health Research Centre, Team ELEANOR, 33000, Bordeaux, France
| | - Aniket Mishra
- UMR 1219, University of Bordeaux, INSERM, Bordeaux Population Health Research Centre, Team ELEANOR, 33000, Bordeaux, France
| | - Carole Dufouil
- UMR 1219, University of Bordeaux, INSERM, Bordeaux Population Health Research Centre, Team ELEANOR, 33000, Bordeaux, France
| | - Stephanie Debette
- UMR 1219, University of Bordeaux, INSERM, Bordeaux Population Health Research Centre, Team ELEANOR, 33000, Bordeaux, France
- Department of Neurology, Boston University School of Medicine, Boston, MA, 2115, USA
- Department of Neurology, CHU de Bordeaux, 33000, Bordeaux, France
| | - Oscar L Lopez
- Department of Neurology, University of Pittsburgh, Pittsburgh, PA, USA
| | - Steven T DeKosky
- Department of Neurology and McKnight Brain Institute, University of Florida, Gainesville, FL, USA
| | - Feifei Tao
- Neurogenomics, Genetics-Guided Dementia Discovery, Eisai, Inc, Cambridge, MA, USA
| | - Michael W Nagle
- Neurogenomics, Genetics-Guided Dementia Discovery, Eisai, Inc, Cambridge, MA, USA
| | - Timothy J Hohman
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University, St. Louis, MO, 63110, USA
- NeuroGenomics and Informatics, Washington University, St. Louis, MO, 63110, USA
| | - Logan Dumitrescu
- Vanderbilt Memory and Alzheimer's Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO, 63110, USA.
- NeuroGenomics and Informatics, Washington University, St. Louis, MO, 63110, USA.
- Knight Alzheimer's Disease Research Center, Washington University, St Louis, MO, USA.
- Hope Center for Neurologic Diseases, Washington University, St. Louis, MO, 63110, USA.
- Department of Genetics, Washington University School of Medicine, St Louis, MO, 63110, USA.
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Iguchi A, Takatori S, Kimura S, Muneto H, Wang K, Etani H, Ito G, Sato H, Hori Y, Sasaki J, Saito T, Saido TC, Ikezu T, Takai T, Sasaki T, Tomita T. INPP5D modulates TREM2 loss-of-function phenotypes in a β-amyloidosis mouse model. iScience 2023; 26:106375. [PMID: 37035000 PMCID: PMC10074152 DOI: 10.1016/j.isci.2023.106375] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 02/24/2023] [Accepted: 03/07/2023] [Indexed: 03/18/2023] Open
Abstract
The genetic associations of TREM2 loss-of-function variants with Alzheimer disease (AD) indicate the protective roles of microglia in AD pathogenesis. Functional deficiencies of TREM2 disrupt microglial clustering around amyloid β (Aβ) plaques, impair their transcriptional response to Aβ, and worsen neuritic dystrophy. However, the molecular mechanism underlying these phenotypes remains unclear. In this study, we investigated the pathological role of another AD risk gene, INPP5D, encoding a phosphoinositide PI(3,4,5)P3 phosphatase expressed in microglia. In a Tyrobp-deficient TREM2 loss-of-function mouse model, Inpp5d haplodeficiency restored the association of microglia with Aβ plaques, partially restored plaque compaction, and astrogliosis, and reduced phosphorylated tau+ dystrophic neurites. Mechanistic analyses suggest that TREM2/TYROBP and INPP5D exert opposing effects on PI(3,4,5)P3 signaling pathways as well as on phosphoproteins involved in the actin assembly. Our results suggest that INPP5D acts downstream of TREM2/TYROBP to regulate the microglial barrier against Aβ toxicity, thereby modulates Aβ-dependent pathological conversion of tau.
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Affiliation(s)
- Akihiro Iguchi
- Laboratory of Neuropathology and Neuroscience, Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Sho Takatori
- Laboratory of Neuropathology and Neuroscience, Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Shingo Kimura
- Laboratory of Neuropathology and Neuroscience, Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Hiroki Muneto
- Laboratory of Neuropathology and Neuroscience, Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Kai Wang
- Laboratory of Neuropathology and Neuroscience, Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Hayato Etani
- Laboratory of Neuropathology and Neuroscience, Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Genta Ito
- Department of Biomolecular Chemistry, Faculty of Pharma-Science, Teikyo University, 2-11-1 Kaga, Itabashi-ku, Tokyo 173-8605, Japan
| | - Haruaki Sato
- Laboratory of Neuropathology and Neuroscience, Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Yukiko Hori
- Laboratory of Neuropathology and Neuroscience, Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
| | - Junko Sasaki
- Department of Lipid Biology, Medical Research Institute, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan
| | - Takashi Saito
- Laboratory for Proteolytic Neuroscience, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
- Department of Neurocognitive Science, Institute of Brain Science, Nagoya City University Graduate School of Medical Science, 1 Kawasumi, Mizuho-cho, Mizuho-ku, Nagoya, Aichi 467-8601, Japan
| | - Takaomi C. Saido
- Laboratory for Proteolytic Neuroscience, RIKEN Center for Brain Science, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
| | - Tsuneya Ikezu
- Department of Neuroscience, Mayo Clinic Florida, Jacksonville, FL 32224, USA
| | - Toshiyuki Takai
- Department of Experimental Immunology, Institute of Development, Aging and Cancer, Tohoku University, 4-1 Seiryo, Sendai 980-8575, Japan
| | - Takehiko Sasaki
- Department of Lipid Biology, Medical Research Institute, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan
| | - Taisuke Tomita
- Laboratory of Neuropathology and Neuroscience, Graduate School of Pharmaceutical Sciences, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
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43
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Zhang W, Young JI, Gomez L, Schmidt MA, Lukacsovich D, Varma A, Chen XS, Martin ER, Wang L. Distinct CSF biomarker-associated DNA methylation in Alzheimer's disease and cognitively normal subjects. Alzheimers Res Ther 2023; 15:78. [PMID: 37038196 PMCID: PMC10088180 DOI: 10.1186/s13195-023-01216-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/18/2022] [Accepted: 03/21/2023] [Indexed: 04/12/2023]
Abstract
BACKGROUND Growing evidence has demonstrated that DNA methylation (DNAm) plays an important role in Alzheimer's disease (AD) and that DNAm differences can be detected in the blood of AD subjects. Most studies have correlated blood DNAm with the clinical diagnosis of AD in living individuals. However, as the pathophysiological process of AD can begin many years before the onset of clinical symptoms, there is often disagreement between neuropathology in the brain and clinical phenotypes. Therefore, blood DNAm associated with AD neuropathology, rather than with clinical data, would provide more relevant information on AD pathogenesis. METHODS We performed a comprehensive analysis to identify blood DNAm associated with cerebrospinal fluid (CSF) pathological biomarkers for AD. Our study included matched samples of whole blood DNA methylation, CSF Aβ42, phosphorylated tau181 (pTau181), and total tau (tTau) biomarkers data, measured on the same subjects and at the same clinical visits from a total of 202 subjects (123 CN or cognitively normal, 79 AD) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. To validate our findings, we also examined the association between premortem blood DNAm and postmortem brain neuropathology measured on a group of 69 subjects in the London dataset. RESULTS We identified a number of novel associations between blood DNAm and CSF biomarkers, demonstrating that changes in pathological processes in the CSF are reflected in the blood epigenome. Overall, the CSF biomarker-associated DNAm is relatively distinct in CN and AD subjects, highlighting the importance of analyzing omics data measured on cognitively normal subjects (which includes preclinical AD subjects) to identify diagnostic biomarkers, and considering disease stages in the development and testing of AD treatment strategies. Moreover, our analysis revealed biological processes associated with early brain impairment relevant to AD are marked by DNAm in the blood, and blood DNAm at several CpGs in the DMR on HOXA5 gene are associated with pTau181 in the CSF, as well as tau-pathology and DNAm in the brain, nominating DNAm at this locus as a promising candidate AD biomarker. CONCLUSIONS Our study provides a valuable resource for future mechanistic and biomarker studies of DNAm in AD.
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Affiliation(s)
- Wei Zhang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA
| | - Juan I Young
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Lissette Gomez
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Michael A Schmidt
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - David Lukacsovich
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA
| | - Achintya Varma
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - X Steven Chen
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Eden R Martin
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA
| | - Lily Wang
- Division of Biostatistics, Department of Public Health Sciences, University of Miami Miller School of Medicine, 1120 NW 14Th Street, Miami, FL, 33136, USA.
- Dr. John T Macdonald Foundation Department of Human Genetics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA.
- John P. Hussman Institute for Human Genomics, University of Miami Miller School of Medicine, Miami, FL, 33136, USA.
- Sylvester Comprehensive Cancer Center, University of Miami Miller School of Medicine, Miami, FL, 33136, USA.
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Nho K, Risacher SL, Apostolova L, Bice PJ, Brosch J, Deardorff R, Faber K, Farlow MR, Foroud T, Gao S, Rosewood T, Kim JP, Nudelman K, Yu M, Aisen P, Sperling R, Hooli B, Shcherbinin S, Svaldi D, Jack CR, Jagust WJ, Landau S, Vasanthakumar A, Waring JF, Doré V, Laws SM, Masters CL, Porter T, Rowe CC, Villemagne VL, Dumitrescu L, Hohman TJ, Libby JB, Mormino E, Buckley RF, Johnson K, Yang HS, Petersen RC, Ramanan VK, Vemuri P, Cohen AD, Fan KH, Kamboh MI, Lopez OL, Bennett DA, Ali M, Benzinger T, Cruchaga C, Hobbs D, De Jager PL, Fujita M, Jadhav V, Lamb BT, Tsai AP, Castanho I, Mill J, Weiner MW, Saykin AJ. Novel CYP1B1-RMDN2 Alzheimer's disease locus identified by genome-wide association analysis of cerebral tau deposition on PET. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.27.23286048. [PMID: 36993271 PMCID: PMC10055458 DOI: 10.1101/2023.02.27.23286048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/31/2023]
Abstract
Determining the genetic architecture of Alzheimer's disease (AD) pathologies can enhance mechanistic understanding and inform precision medicine strategies. Here, we performed a genome-wide association study of cortical tau quantified by positron emission tomography in 3,136 participants from 12 independent studies. The CYP1B1-RMDN2 locus was associated with tau deposition. The most significant signal was at rs2113389, which explained 4.3% of the variation in cortical tau, while APOE4 rs429358 accounted for 3.6%. rs2113389 was associated with higher tau and faster cognitive decline. Additive effects, but no interactions, were observed between rs2113389 and diagnosis, APOE4 , and Aβ positivity. CYP1B1 expression was upregulated in AD. rs2113389 was associated with higher CYP1B1 expression and methylation levels. Mouse model studies provided additional functional evidence for a relationship between CYP1B1 and tau deposition but not Aβ. These results may provide insight into the genetic basis of cerebral tau and novel pathways for therapeutic development in AD.
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45
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Sensi SL, Russo M, Tiraboschi P. Biomarkers of diagnosis, prognosis, pathogenesis, response to therapy: Convergence or divergence? Lessons from Alzheimer's disease and synucleinopathies. HANDBOOK OF CLINICAL NEUROLOGY 2023; 192:187-218. [PMID: 36796942 DOI: 10.1016/b978-0-323-85538-9.00015-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/16/2023]
Abstract
Alzheimer's disease (AD) is the most common disorder associated with cognitive impairment. Recent observations emphasize the pathogenic role of multiple factors inside and outside the central nervous system, supporting the notion that AD is a syndrome of many etiologies rather than a "heterogeneous" but ultimately unifying disease entity. Moreover, the defining pathology of amyloid and tau coexists with many others, such as α-synuclein, TDP-43, and others, as a rule, not an exception. Thus, an effort to shift our AD paradigm as an amyloidopathy must be reconsidered. Along with amyloid accumulation in its insoluble state, β-amyloid is becoming depleted in its soluble, normal states, as a result of biological, toxic, and infectious triggers, requiring a shift from convergence to divergence in our approach to neurodegeneration. These aspects are reflected-in vivo-by biomarkers, which have become increasingly strategic in dementia. Similarly, synucleinopathies are primarily characterized by abnormal deposition of misfolded α-synuclein in neurons and glial cells and, in the process, depleting the levels of the normal, soluble α-synuclein that the brain needs for many physiological functions. The soluble to insoluble conversion also affects other normal brain proteins, such as TDP-43 and tau, accumulating in their insoluble states in both AD and dementia with Lewy bodies (DLB). The two diseases have been distinguished by the differential burden and distribution of insoluble proteins, with neocortical phosphorylated tau deposition more typical of AD and neocortical α-synuclein deposition peculiar to DLB. We propose a reappraisal of the diagnostic approach to cognitive impairment from convergence (based on clinicopathologic criteria) to divergence (based on what differs across individuals affected) as a necessary step for the launch of precision medicine.
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Affiliation(s)
- Stefano L Sensi
- Department of Neuroscience, Imaging, and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Molecular Neurology Unit, Center for Advanced Studies and Technology-CAST and ITAB Institute for Advanced Biotechnology, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy.
| | - Mirella Russo
- Department of Neuroscience, Imaging, and Clinical Sciences, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy; Molecular Neurology Unit, Center for Advanced Studies and Technology-CAST and ITAB Institute for Advanced Biotechnology, "G. d'Annunzio" University of Chieti-Pescara, Chieti, Italy
| | - Pietro Tiraboschi
- Division of Neurology V-Neuropathology, Fondazione IRCCS Istituto Neurologico Carlo Besta, Milan, Italy
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46
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Zhang W, Young JI, Gomez L, Schmidt MA, Lukacsovich D, Varma A, Chen XS, Martin ER, Wang L. Distinct CSF biomarker-associated DNA methylation in Alzheimer's disease and cognitively normal subjects. RESEARCH SQUARE 2023:rs.3.rs-2391364. [PMID: 36865230 PMCID: PMC9980279 DOI: 10.21203/rs.3.rs-2391364/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/23/2023]
Abstract
Background Growing evidence has demonstrated that DNA methylation (DNAm) plays an important role in Alzheimer's disease (AD) and that DNAm differences can be detected in the blood of AD subjects. Most studies have correlated blood DNAm with the clinical diagnosis of AD in living individuals. However, as the pathophysiological process of AD can begin many years before the onset of clinical symptoms, there is often disagreement between neuropathology in the brain and clinical phenotypes. Therefore, blood DNAm associated with AD neuropathology, rather than with clinical data, would provide more relevant information on AD pathogenesis. Methods We performed a comprehensive analysis to identify blood DNAm associated with cerebrospinal fluid (CSF) pathological biomarkers for AD. Our study included matched samples of whole blood DNA methylation, CSF Aβ 42 , phosphorylated tau 181 (pTau 181 ), and total tau (tTau) biomarkers data, measured on the same subjects and at the same clinical visits from a total of 202 subjects (123 CN or cognitively normal, 79 AD) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. To validate our findings, we also examined the association between premortem blood DNAm and postmortem brain neuropathology measured on a group of 69 subjects in the London dataset. Results We identified a number of novel associations between blood DNAm and CSF biomarkers, demonstrating that changes in pathological processes in the CSF are reflected in the blood epigenome. Overall, the CSF biomarker-associated DNAm is relatively distinct in CN and AD subjects, highlighting the importance of analyzing omics data measured on cognitively normal subjects (which includes preclinical AD subjects) to identify diagnostic biomarkers, and considering disease stages in the development and testing of AD treatment strategies. Moreover, our analysis revealed biological processes associated with early brain impairment relevant to AD are marked by DNAm in the blood, and blood DNAm at several CpGs in the DMR on HOXA5 gene are associated with pTau 181 in the CSF, as well as tau-pathology and DNAm in the brain, nominating DNAm at this locus as a promising candidate AD biomarker. Conclusions Our study provides a valuable resource for future mechanistic and biomarker studies of DNAm in AD.
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Affiliation(s)
- Wei Zhang
- University of Miami, Miller School of Medicine
| | - Juan I Young
- Dr. John T Macdonald Foundation, University of Miami, Miller School of Medicine
| | | | - Michael A Schmidt
- Dr. John T Macdonald Foundation, University of Miami, Miller School of Medicine
| | | | | | | | - Eden R Martin
- Dr. John T Macdonald Foundation, University of Miami, Miller School of Medicine
| | - Lily Wang
- University of Miami, Miller School of Medicine
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Welikovitch LA, Dujardin S, Dunn AR, Fernandes AR, Khasnavis A, Chibnik LB, Kaczorowski CC, Hyman BT. Rate of tau propagation is a heritable disease trait in genetically diverse mouse strains. iScience 2023; 26:105983. [PMID: 36756365 PMCID: PMC9900390 DOI: 10.1016/j.isci.2023.105983] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 12/04/2022] [Accepted: 01/11/2023] [Indexed: 01/15/2023] Open
Abstract
The speed and scope of cognitive deterioration in Alzheimer's disease is highly associated with the advancement of tau neurofibrillary lesions across brain networks. We tested whether the rate of tau propagation is a heritable disease trait in a large, well-characterized cohort of genetically divergent mouse strains. Using an AAV-based model system, P301L-mutant human tau (hTau) was introduced into the entorhinal cortex of mice derived from 18 distinct lines. The extent of tau propagation was measured by distinguishing hTau-producing cells from neurons that were recipients of tau transfer. Heritability calculation revealed that 43% of the variability in tau spread was due to genetic variants segregating across background strains. Strain differences in glial markers were also observed, but did not correlate with tau propagation. Identifying unique genetic variants that influence the progression of pathological tau may uncover novel molecular targets to prevent or slow the pace of tau spread and cognitive decline.
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Affiliation(s)
- Lindsay A. Welikovitch
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Simon Dujardin
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Harvard Medical School, Boston, MA 02115, USA
| | - Amy R. Dunn
- The Jackson Laboratory, Bar Harbor, ME 04609, USA
| | | | - Anita Khasnavis
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA 02129, USA
| | - Lori B. Chibnik
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | | | - Bradley T. Hyman
- Department of Neurology, Massachusetts General Hospital, Charlestown, MA 02129, USA
- Harvard Medical School, Boston, MA 02115, USA
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48
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Chen Y, Zhang Y, Li S, Zhou L, Li H, Li D, Wang Y, Yang H. Cardiometabolic diseases, polygenic risk score, APOE genotype, and risk of incident dementia: A population-based prospective cohort study. Arch Gerontol Geriatr 2023; 105:104853. [PMID: 36347157 DOI: 10.1016/j.archger.2022.104853] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2022] [Revised: 10/27/2022] [Accepted: 10/29/2022] [Indexed: 11/07/2022]
Abstract
Objective We aimed to prospective investigate the association between cardiometabolic diseases (CMDs) with dementia, and to examine whether genetic factors and CMDs jointly contribute to the incidence of dementia. Methods We used data from the UK biobank of 204,646 adults aged 37-73 free of dementia at baseline. Genetic risk for dementia including APOE ε4 status and polygenic risk score (PRS) categorized as low, intermediate, and high. CMDs including ischemic heart disease (IHD), stroke, and type 2 diabetes (T2D) were confirmed by touchscreen questionnaires, medical examinations, and hospital inpatient records. Results Over the follow-up (median: 12.5 years), 5,750 participants developed dementia. The HRs (95% CI) of those with APOE ε4 carriers and high PRS were 3.16 (3.00-3.33) and 1.50 (1.41-1.60), respectively. The risk of dementia was 70% higher among those with CMDs (HR: 1.70; 95% CI: 1.60-1.82). In joint effect analyses, compared to no CMDs and APOE ε4 non-carriers, the HRs (95% CIs) of dementia were 3.53 (3.31-3.76)/2.06 (1.89-2.23) in participants with only APOE ε4 carriers and CMDs, and 5.06 (4.64-5.53) for those with APOE ε4 carriers plus CMDs. Compared to no CMDs and low PRS, the HRs (95% CIs) of dementia were 1.29 (1.19-1.40)/1.60 (1.48-1.73) in participants with only intermediate and high PRS, and 2.00 (1.79-2.23)/2.63 (2.38-2.92) for those with intermediate, and high PRS plus CMDs. Moreover, there were significant additive and multiplication interactions between CMDs and APOE ε4 carriers of dementia, but only multiplication interaction was observed for PRS. Conclusions CMDs were associated with higher risk of dementia regardless of genetic risk for dementia.
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Affiliation(s)
- Yanchun Chen
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Yuan Zhang
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Shu Li
- School of Management, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Lihui Zhou
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Huiping Li
- School of Public Health, Tianjin Medical University, Tianjin, China
| | - Dun Li
- The Discipline of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Yaogang Wang
- School of Public Health, Tianjin Medical University, Tianjin, China; The Discipline of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China
| | - Hongxi Yang
- Department of Bioinformatics, School of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
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49
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Hansson O, Kumar A, Janelidze S, Stomrud E, Insel PS, Blennow K, Zetterberg H, Fauman E, Hedman ÅK, Nagle MW, Whelan CD, Baird D, Mälarstig A, Mattsson‐Carlgren N. The genetic regulation of protein expression in cerebrospinal fluid. EMBO Mol Med 2023; 15:e16359. [PMID: 36504281 PMCID: PMC9832827 DOI: 10.15252/emmm.202216359] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2022] [Revised: 11/12/2022] [Accepted: 11/14/2022] [Indexed: 12/14/2022] Open
Abstract
Studies of the genetic regulation of cerebrospinal fluid (CSF) proteins may reveal pathways for treatment of neurological diseases. 398 proteins in CSF were measured in 1,591 participants from the BioFINDER study. Protein quantitative trait loci (pQTL) were identified as associations between genetic variants and proteins, with 176 pQTLs for 145 CSF proteins (P < 1.25 × 10-10 , 117 cis-pQTLs and 59 trans-pQTLs). Ventricular volume (measured with brain magnetic resonance imaging) was a confounder for several pQTLs. pQTLs for CSF and plasma proteins were overall correlated, but CSF-specific pQTLs were also observed. Mendelian randomization analyses suggested causal roles for several proteins, for example, ApoE, CD33, and GRN in Alzheimer's disease, MMP-10 in preclinical Alzheimer's disease, SIGLEC9 in amyotrophic lateral sclerosis, and CD38, GPNMB, and ADAM15 in Parkinson's disease. CSF levels of GRN, MMP-10, and GPNMB were altered in Alzheimer's disease, preclinical Alzheimer's disease, and Parkinson's disease, respectively. These findings point to pathways to be explored for novel therapies. The novel finding that ventricular volume confounded pQTLs has implications for design of future studies of the genetic regulation of the CSF proteome.
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Affiliation(s)
- Oskar Hansson
- Clinical Memory Research Unit, Faculty of MedicineLund UniversityLundSweden
- Memory ClinicSkåne University Hospital, Lund UniversityLundSweden
| | - Atul Kumar
- Clinical Memory Research Unit, Faculty of MedicineLund UniversityLundSweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Faculty of MedicineLund UniversityLundSweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Faculty of MedicineLund UniversityLundSweden
- Memory ClinicSkåne University Hospital, Lund UniversityLundSweden
| | - Philip S Insel
- Clinical Memory Research Unit, Faculty of MedicineLund UniversityLundSweden
- Department of Psychiatry and Behavioral SciencesUniversity of California, San FranciscoSan FranciscoCAUSA
| | - Kaj Blennow
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska AcademyUniversity of GothenburgMölndalSweden
| | - Henrik Zetterberg
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska AcademyUniversity of GothenburgMölndalSweden
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyLondonUK
- UK Dementia Research Institute at UCLLondonUK
- Hong Kong Center for Neurodegenerative DiseasesHong KongChina
| | - Eric Fauman
- Internal Medicine Research UnitPfizer Worldwide Research, Development and MedicalCambridgeMAUSA
| | - Åsa K Hedman
- Pfizer Worldwide Research, Development and MedicalStockholmSweden
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Michael W Nagle
- Neurogenomics, Genetics‐Guided Dementia DiscoveryEisai, IncCambridgeMAUSA
| | | | - Denis Baird
- Department of Neurology, Skåne University HospitalLund UniversityLundSweden
| | - Anders Mälarstig
- Pfizer Worldwide Research, Development and MedicalStockholmSweden
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Niklas Mattsson‐Carlgren
- Clinical Memory Research Unit, Faculty of MedicineLund UniversityLundSweden
- Department of Neurology, Skåne University HospitalLund UniversityLundSweden
- Wallenberg Center for Molecular MedicineLund UniversityLundSweden
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50
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Oatman SR, Reddy JS, Quicksall Z, Carrasquillo MM, Wang X, Liu CC, Yamazaki Y, Nguyen TT, Malphrus K, Heckman M, Biswas K, Nho K, Baker M, Martens YA, Zhao N, Kim JP, Risacher SL, Rademakers R, Saykin AJ, DeTure M, Murray ME, Kanekiyo T, Dickson DW, Bu G, Allen M, Ertekin-Taner N. Genome-wide association study of brain biochemical phenotypes reveals distinct genetic architecture of Alzheimer's disease related proteins. Mol Neurodegener 2023; 18:2. [PMID: 36609403 PMCID: PMC9825010 DOI: 10.1186/s13024-022-00592-2] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2022] [Accepted: 12/19/2022] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Alzheimer's disease (AD) is neuropathologically characterized by amyloid-beta (Aβ) plaques and neurofibrillary tangles. The main protein components of these hallmarks include Aβ40, Aβ42, tau, phosphor-tau, and APOE. We hypothesize that genetic variants influence the levels and solubility of these AD-related proteins in the brain; identifying these may provide key insights into disease pathogenesis. METHODS Genome-wide genotypes were collected from 441 AD cases, imputed to the haplotype reference consortium (HRC) panel, and filtered for quality and frequency. Temporal cortex levels of five AD-related proteins from three fractions, buffer-soluble (TBS), detergent-soluble (Triton-X = TX), and insoluble (Formic acid = FA), were available for these same individuals. Variants were tested for association with each quantitative biochemical measure using linear regression, and GSA-SNP2 was used to identify enriched Gene Ontology (GO) terms. Implicated variants and genes were further assessed for association with other relevant variables. RESULTS We identified genome-wide significant associations at seven novel loci and the APOE locus. Genes and variants at these loci also associate with multiple AD-related measures, regulate gene expression, have cell-type specific enrichment, and roles in brain health and other neuropsychiatric diseases. Pathway analysis identified significant enrichment of shared and distinct biological pathways. CONCLUSIONS Although all biochemical measures tested reflect proteins core to AD pathology, our results strongly suggest that each have unique genetic architecture and biological pathways that influence their specific biochemical states in the brain. Our novel approach of deep brain biochemical endophenotype GWAS has implications for pathophysiology of proteostasis in AD that can guide therapeutic discovery efforts focused on these proteins.
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Affiliation(s)
- Stephanie R. Oatman
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Joseph S. Reddy
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL USA
| | - Zachary Quicksall
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL USA
| | | | - Xue Wang
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL USA
| | - Chia-Chen Liu
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Yu Yamazaki
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Thuy T. Nguyen
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Kimberly Malphrus
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Michael Heckman
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL USA
| | - Kristi Biswas
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Kwangsik Nho
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN USA
- School of Informatics and Computing, Indiana University School of Medicine, Indianapolis, IN USA
| | - Matthew Baker
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Yuka A. Martens
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Na Zhao
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Jun Pyo Kim
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN USA
| | - Shannon L. Risacher
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN USA
| | - Rosa Rademakers
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
- VIB-UA Center for Molecular Neurology, VIB, University of Antwerp, Antwerp, Belgium
| | - Andrew J. Saykin
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN USA
| | - Michael DeTure
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Melissa E. Murray
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Takahisa Kanekiyo
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - for the Alzheimer’s Disease Neuroimaging Initiative
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL USA
- Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN USA
- School of Informatics and Computing, Indiana University School of Medicine, Indianapolis, IN USA
- VIB-UA Center for Molecular Neurology, VIB, University of Antwerp, Antwerp, Belgium
- Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN USA
- Department of Neurology, Mayo Clinic, 4500 San Pablo Road, Birdsall 3, Jacksonville, FL 32224 USA
| | - Dennis W. Dickson
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Guojun Bu
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Mariet Allen
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
| | - Nilüfer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic, 4500 San Pablo Road, Jacksonville, FL 32224 USA
- Department of Neurology, Mayo Clinic, 4500 San Pablo Road, Birdsall 3, Jacksonville, FL 32224 USA
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