1
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Wang QS, Hasegawa T, Namkoong H, Saiki R, Edahiro R, Sonehara K, Tanaka H, Azekawa S, Chubachi S, Takahashi Y, Sakaue S, Namba S, Yamamoto K, Shiraishi Y, Chiba K, Tanaka H, Makishima H, Nannya Y, Zhang Z, Tsujikawa R, Koike R, Takano T, Ishii M, Kimura A, Inoue F, Kanai T, Fukunaga K, Ogawa S, Imoto S, Miyano S, Okada Y. Statistically and functionally fine-mapped blood eQTLs and pQTLs from 1,405 humans reveal distinct regulation patterns and disease relevance. Nat Genet 2024:10.1038/s41588-024-01896-3. [PMID: 39317738 DOI: 10.1038/s41588-024-01896-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 08/06/2024] [Indexed: 09/26/2024]
Abstract
Studying the genetic regulation of protein expression (through protein quantitative trait loci (pQTLs)) offers a deeper understanding of regulatory variants uncharacterized by mRNA expression regulation (expression QTLs (eQTLs)) studies. Here we report cis-eQTL and cis-pQTL statistical fine-mapping from 1,405 genotyped samples with blood mRNA and 2,932 plasma samples of protein expression, as part of the Japan COVID-19 Task Force (JCTF). Fine-mapped eQTLs (n = 3,464) were enriched for 932 variants validated with a massively parallel reporter assay. Fine-mapped pQTLs (n = 582) were enriched for missense variations on structured and extracellular domains, although the possibility of epitope-binding artifacts remains. Trans-eQTL and trans-pQTL analysis highlighted associations of class I HLA allele variation with KIR genes. We contrast the multi-tissue origin of plasma protein with blood mRNA, contributing to the limited colocalization level, distinct regulatory mechanisms and trait relevance of eQTLs and pQTLs. We report a negative correlation between ABO mRNA and protein expression because of linkage disequilibrium between distinct nearby eQTLs and pQTLs.
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Affiliation(s)
- Qingbo S Wang
- Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
| | - Takanori Hasegawa
- M&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan
| | - Ho Namkoong
- Department of Infectious Diseases, Keio University School of Medicine, Tokyo, Japan.
| | - Ryunosuke Saiki
- Department of Pathology and Tumor Biology, Kyoto University, Kyoto, Japan
| | - Ryuya Edahiro
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Respiratory Medicine and Clinical Immunology, Osaka University Graduate School of Medicine, Suita, Japan
| | - Kyuto Sonehara
- Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Hiromu Tanaka
- Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Shuhei Azekawa
- Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Shotaro Chubachi
- Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo, Japan
| | | | - Saori Sakaue
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Center for Data Sciences, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Divisions of Genetics and Rheumatology, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Shinichi Namba
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Kenichi Yamamoto
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan
- Laboratory of Children's Health and Genetics, Division of Health Science, Osaka University Graduate School of Medicine, Suita, Japan
- Department of Pediatrics, Osaka University Graduate School of Medicine, Suita, Japan
| | - Yuichi Shiraishi
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Kenichi Chiba
- Division of Genome Analysis Platform Development, National Cancer Center Research Institute, Tokyo, Japan
| | - Hiroko Tanaka
- M&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan
| | - Hideki Makishima
- Department of Pathology and Tumor Biology, Kyoto University, Kyoto, Japan
| | - Yasuhito Nannya
- Department of Pathology and Tumor Biology, Kyoto University, Kyoto, Japan
| | - Zicong Zhang
- Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan
| | - Rika Tsujikawa
- Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan
| | - Ryuji Koike
- Health Science Research and Development Center (HeRD), Tokyo Medical and Dental University, Tokyo, Japan
| | - Tomomi Takano
- Laboratory of Veterinary Infectious Disease, Department of Veterinary Medicine, Kitasato University, Tokyo, Japan
| | - Makoto Ishii
- Department of Respiratory Medicine, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Akinori Kimura
- Institute of Research, Tokyo Medical and Dental University, Tokyo, Japan
| | - Fumitaka Inoue
- Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan
| | - Takanori Kanai
- Division of Gastroenterology and Hepatology, Department of Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Koichi Fukunaga
- Division of Pulmonary Medicine, Department of Medicine, Keio University School of Medicine, Tokyo, Japan
| | - Seishi Ogawa
- Department of Pathology and Tumor Biology, Kyoto University, Kyoto, Japan
- Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto, Japan
| | - Seiya Imoto
- Division of Health Medical Intelligence, Human Genome Center, the Institute of Medical Science, University of Tokyo, Tokyo, Japan
| | - Satoru Miyano
- M&D Data Science Center, Tokyo Medical and Dental University, Tokyo, Japan
| | - Yukinori Okada
- Department of Genome Informatics, Graduate School of Medicine, University of Tokyo, Tokyo, Japan.
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, Japan.
- Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, Japan.
- Department of Immunopathology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan.
- Premium Research Institute for Human Metaverse Medicine (WPI-PRIMe), Osaka University, Suita, Japan.
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2
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Shen Y, Timsina J, Heo G, Beric A, Ali M, Wang C, Yang C, Wang Y, Western D, Liu M, Gorijala P, Budde J, Do A, Liu H, Gordon B, Llibre-Guerra JJ, Joseph-Mathurin N, Perrin RJ, Maschi D, Wyss-Coray T, Pastor P, Renton AE, Surace EI, Johnson ECB, Levey AI, Alvarez I, Levin J, Ringman JM, Allegri RF, Seyfried N, Day GS, Wu Q, Fernández MV, Tarawneh R, McDade E, Morris JC, Bateman RJ, Goate A, Ibanez L, Sung YJ, Cruchaga C. CSF proteomics identifies early changes in autosomal dominant Alzheimer's disease. Cell 2024:S0092-8674(24)00978-4. [PMID: 39332414 DOI: 10.1016/j.cell.2024.08.049] [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: 01/31/2024] [Revised: 07/02/2024] [Accepted: 08/23/2024] [Indexed: 09/29/2024]
Abstract
In this high-throughput proteomic study of autosomal dominant Alzheimer's disease (ADAD), we sought to identify early biomarkers in cerebrospinal fluid (CSF) for disease monitoring and treatment strategies. We examined CSF proteins in 286 mutation carriers (MCs) and 177 non-carriers (NCs). The developed multi-layer regression model distinguished proteins with different pseudo-trajectories between these groups. We validated our findings with independent ADAD as well as sporadic AD datasets and employed machine learning to develop and validate predictive models. Our study identified 137 proteins with distinct trajectories between MCs and NCs, including eight that changed before traditional AD biomarkers. These proteins are grouped into three stages: early stage (stress response, glutamate metabolism, neuron mitochondrial damage), middle stage (neuronal death, apoptosis), and late presymptomatic stage (microglial changes, cell communication). The predictive model revealed a six-protein subset that more effectively differentiated MCs from NCs, compared with conventional biomarkers.
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Affiliation(s)
- Yuanyuan Shen
- 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
| | - Gyujin Heo
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, USA
| | - Aleksandra Beric
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, USA
| | - Muhammad Ali
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, USA
| | - Ciyang Wang
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, USA
| | - Chengran Yang
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, USA
| | - Yueyao Wang
- 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
| | - Menghan Liu
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, USA
| | - Priyanka Gorijala
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, USA
| | - John Budde
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, USA
| | - Anh Do
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, USA
| | - Haiyan Liu
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Brian Gordon
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Jorge J Llibre-Guerra
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Nelly Joseph-Mathurin
- Mallinckrodt Institute of Radiology, Washington University St Louis, St Louis, MO 63110, USA
| | - Richard J Perrin
- Department of Pathology and Immunology, Washington University St. Louis, St. Louis, MO 63110, USA
| | - Dario Maschi
- Department of Cell Biology and Physiology, Washington University St. Louis, St. Louis, MO 63110, USA
| | - Tony Wyss-Coray
- Wu Tsai Neurosciences Institute, Stanford University, Stanford, CA 94305, USA; Department of Neurology & Neurological Sciences, Stanford University, Stanford, CA 94305, USA
| | - Pau Pastor
- Unit of Neurodegenerative Diseases, Department of Neurology, University Hospital Germans Trias i Pujol and The Germans Trias i Pujol Research Institute (IGTP), Badalona, Barcelona 08916, Spain
| | - Alan E Renton
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Nash Family Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Ezequiel I Surace
- Laboratory of Neurodegenerative Diseases, Institute of Neurosciences (INEU-Fleni-CONICET), Buenos Aires, Argentina
| | - Erik C B Johnson
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30307, USA; Department of Neurology, Emory University School of Medicine, Atlanta, GA 30307, USA
| | - Allan I Levey
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30307, USA
| | - Ignacio Alvarez
- Department of Neurology, University Hospital Mútua de Terrassa and Fundació Docència i Recerca Mútua de Terrassa, Terrassa 08221, Barcelona, Spain
| | - Johannes Levin
- Department of Neurology, LMU University Hospital, LMU Munich, Munich 80336, Germany; German Center for Neurodegenerative Diseases, site Munich, Munich 80336, Germany
| | - John M Ringman
- Alzheimer's Disease Research Center, Department of Neurology, Keck School of Medicine at USC, Los Angeles, CA 90033, USA
| | - Ricardo Francisco Allegri
- Department of Cognitive Neurology, Neuropsychology and Neuropsychiatry, FLENI, Buenos Aires, Argentina
| | - Nicholas Seyfried
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30307, USA
| | - Gregg S Day
- Department of Neurology, Mayo Clinic in Florida, Jacksonville, FL 32224, USA
| | - Qisi Wu
- Department of Neurology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | | | - Rawan Tarawneh
- The University of New Mexico, Albuquerque, NM 87131, USA
| | - Eric McDade
- Department of Neurology, 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
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Alison Goate
- Ronald M. Loeb Center for Alzheimer's Disease, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA
| | - Laura Ibanez
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO 63110, USA; NeuroGenomics and Informatics, Washington University, St. Louis, MO 63110, USA; Department of Neurology, Washington University School of Medicine, St. Louis, MO 63110, USA.
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3
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Pérez-González AP, García-Kroepfly AL, Pérez-Fuentes KA, García-Reyes RI, Solis-Roldan FF, Alba-González JA, Hernández-Lemus E, de Anda-Jáuregui G. The ROSMAP project: aging and neurodegenerative diseases through omic sciences. Front Neuroinform 2024; 18:1443865. [PMID: 39351424 PMCID: PMC11439699 DOI: 10.3389/fninf.2024.1443865] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2024] [Accepted: 08/26/2024] [Indexed: 10/04/2024] Open
Abstract
The Religious Order Study and Memory and Aging Project (ROSMAP) is an initiative that integrates two longitudinal cohort studies, which have been collecting clinicopathological and molecular data since the early 1990s. This extensive dataset includes a wide array of omic data, revealing the complex interactions between molecular levels in neurodegenerative diseases (ND) and aging. Neurodegenerative diseases (ND) are frequently associated with morbidity and cognitive decline in older adults. Omics research, in conjunction with clinical variables, is crucial for advancing our understanding of the diagnosis and treatment of neurodegenerative diseases. This summary reviews the extensive omics research-encompassing genomics, transcriptomics, proteomics, metabolomics, epigenomics, and multiomics-conducted through the ROSMAP study. It highlights the significant advancements in understanding the mechanisms underlying neurodegenerative diseases, with a particular focus on Alzheimer's disease.
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Affiliation(s)
- Alejandra P Pérez-González
- División de Genómica Computacional, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
- Programa de Doctorado en Ciencias Biomedicas, Unidad de Posgrado Edificio B Primer Piso, Ciudad Universitaria, Mexico City, Mexico
- Facultad de Estudios Superiores Iztacala UNAM, Mexico City, Mexico
| | | | | | | | | | | | - Enrique Hernández-Lemus
- División de Genómica Computacional, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Guillermo de Anda-Jáuregui
- División de Genómica Computacional, Instituto Nacional de Medicina Genómica, Mexico City, Mexico
- Centro de Ciencias de la Complejidad, Universidad Nacional Autónoma de México, Mexico City, Mexico
- Programa de Investigadoras e Investigadores por México Consejo Nacional de Humanidades, Ciencias y Tecnologías (CONAHCYT), Mexico City, Mexico
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4
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Beutgen VM, Shinkevich V, Pörschke J, Meena C, Steitz AM, Pogge von Strandmann E, Graumann J, Gómez-Serrano M. Secretome Analysis Using Affinity Proteomics and Immunoassays: A Focus on Tumor Biology. Mol Cell Proteomics 2024; 23:100830. [PMID: 39147028 PMCID: PMC11417252 DOI: 10.1016/j.mcpro.2024.100830] [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: 02/29/2024] [Revised: 07/20/2024] [Accepted: 08/12/2024] [Indexed: 08/17/2024] Open
Abstract
The study of the cellular secretome using proteomic techniques continues to capture the attention of the research community across a broad range of topics in biomedical research. Due to their untargeted nature, independence from the model system used, historically superior depth of analysis, as well as comparative affordability, mass spectrometry-based approaches traditionally dominate such analyses. More recently, however, affinity-based proteomic assays have massively gained in analytical depth, which together with their high sensitivity, dynamic range coverage as well as high throughput capabilities render them exquisitely suited to secretome analysis. In this review, we revisit the analytical challenges implied by secretomics and provide an overview of affinity-based proteomic platforms currently available for such analyses, using the study of the tumor secretome as an example for basic and translational research.
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Affiliation(s)
- Vanessa M Beutgen
- Institute of Translational Proteomics, Biochemical/Pharmacological Centre, Philipps University, Marburg, Germany; Core Facility Translational Proteomics, Biochemical/Pharmacological Centre, Philipps University, Marburg, Germany
| | - Veronika Shinkevich
- Institute of Pharmacology, Biochemical/Pharmacological Centre, Philipps University, Marburg, Germany
| | - Johanna Pörschke
- Institute for Tumor Immunology, Center for Tumor Biology and Immunology, Philipps University, Marburg, Germany
| | - Celina Meena
- Institute for Tumor Immunology, Center for Tumor Biology and Immunology, Philipps University, Marburg, Germany
| | - Anna M Steitz
- Translational Oncology Group, Center for Tumor Biology and Immunology, Philipps University, Marburg, Germany
| | - Elke Pogge von Strandmann
- Institute for Tumor Immunology, Center for Tumor Biology and Immunology, Philipps University, Marburg, Germany
| | - Johannes Graumann
- Institute of Translational Proteomics, Biochemical/Pharmacological Centre, Philipps University, Marburg, Germany; Core Facility Translational Proteomics, Biochemical/Pharmacological Centre, Philipps University, Marburg, Germany.
| | - María Gómez-Serrano
- Institute for Tumor Immunology, Center for Tumor Biology and Immunology, Philipps University, Marburg, Germany.
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5
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Thapa R, Ahmad Bhat A, Shahwan M, Ali H, PadmaPriya G, Bansal P, Rajotiya S, Barwal A, Siva Prasad GV, Pramanik A, Khan A, Hing Goh B, Dureja H, Kumar Singh S, Dua K, Gupta G. Proteostasis disruption and senescence in Alzheimer's disease pathways to neurodegeneration. Brain Res 2024; 1845:149202. [PMID: 39216694 DOI: 10.1016/j.brainres.2024.149202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Revised: 07/29/2024] [Accepted: 08/25/2024] [Indexed: 09/04/2024]
Abstract
Alzheimer's Disease (AD) is a progressive neurological disease associated with behavioral abnormalities, memory loss, and cognitive impairment that cause major causes of dementia in the elderly. The pathogenetic processes cause complex effects on brain function and AD progression. The proper protein homeostasis, or proteostasis, is critical for cell health. AD causes the buildup of misfolded proteins, particularly tau and amyloid-beta, to break down proteostasis, such aggregates are toxic to neurons and play a critical role in AD pathogenesis. The rise of cellular senescence is accompanied by aging, marked by irreversible cell cycle arrest and the release of pro-inflammatory proteins. Senescent cell build-up in the brains of AD patients exacerbates neuroinflammation and neuronal degeneration. These cells senescence-associated secretory phenotype (SASP) also disturbs the brain environment. When proteostasis failure and cellular senescence coalesce, a cycle is generated that compounds each other. While senescent cells contribute to proteostasis breakdown through inflammatory and degradative processes, misfolded proteins induce cellular stress and senescence. The principal aspects of the neurodegenerative processes in AD are the interaction of cellular senescence and proteostasis failure. This review explores the interconnected roles of proteostasis disruption and cellular senescence in the pathways leading to neurodegeneration in AD.
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Affiliation(s)
- Riya Thapa
- Uttaranchal Institute of Pharmaceutical Sciences, Uttaranchal University, Dehradun, India
| | - Asif Ahmad Bhat
- Uttaranchal Institute of Pharmaceutical Sciences, Uttaranchal University, Dehradun, India
| | - Moyad Shahwan
- Centre of Medical and Bio-allied Health Sciences Research, Ajman University, Ajman, UAE
| | - Haider Ali
- Centre for Global Health Research, Saveetha Medical College, Saveetha Institute of Medical and Technical Sciences, Saveetha University, India; Department of Pharmacology, Kyrgyz State Medical College, Bishkek, Kyrgyzstan
| | - G PadmaPriya
- Department of Chemistry and Biochemistry, School of Sciences, JAIN (Deemed to be University), Bangalore, Karnataka, India
| | - Pooja Bansal
- Department of Allied Healthcare and Sciences, Vivekananda Global University, Jaipur, Rajasthan-303012, India
| | - Sumit Rajotiya
- NIMS Institute of Pharmacy, NIMS University Rajasthan, Jaipur, India
| | - Amit Barwal
- Chandigarh Pharmacy College, Chandigarh Group of College, Jhanjeri, Mohali - 140307, Punjab, India
| | - G V Siva Prasad
- Department of Chemistry, Raghu Engineering College, Visakhapatnam, Andhra Pradesh-531162, India
| | - Atreyi Pramanik
- School of Applied and Life Sciences, Division of Research and Innovation, Uttaranchal University, Dehradun, India
| | - Abida Khan
- Department of Pharmaceutical Chemistry, Faculty of Pharmacy, Northern Border University, Rafha 91911, Saudi Arabia
| | - Bey Hing Goh
- Sunway Biofunctional Molecules Discovery Centre (SBMDC), School of Medical and Life Sciences, Sunway University, Sunway, Malaysia; Faculty of Health, Australian Research Centre in Complementary and Integrative Medicine, University of Technology Sydney, Ultimo, NSW, Australia; Biofunctional Molecule Exploratory Research Group (BMEX), School of Pharmacy, Monash University Malaysia, Bandar Sunway, Selangor Darul Ehsan, 47500, Malaysia
| | - Harish Dureja
- Department of Pharmaceutical Sciences, Maharshi Dayanand University, Rohtak, 124001, India
| | - Sachin Kumar Singh
- School of Pharmaceutical Sciences, Lovely Professional University, Phagwara, Punjab 144411, India; Faculty of Health, Australian Research Center in Complementary and Integrative Medicine, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Kamal Dua
- Faculty of Health, Australian Research Center in Complementary and Integrative Medicine, University of Technology Sydney, Ultimo, NSW 2007, Australia; Discipline of Pharmacy, Graduate School of Health, University of Technology Sydney, Ultimo, NSW 2007, Australia
| | - Gaurav Gupta
- Centre of Medical and Bio-allied Health Sciences Research, Ajman University, Ajman, UAE; Centre for Research Impact & Outcome, Chitkara College of Pharmacy, Chitkara University, Rajpura, Punjab 140401, India.
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6
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Frick EA, Emilsson V, Jonmundsson T, Steindorsdottir AE, Johnson ECB, Puerta R, Dammer EB, Shantaraman A, Cano A, Boada M, Valero S, García-González P, Gudmundsson EF, Gudjonsson A, Pitts R, Qiu X, Finkel N, Loureiro JJ, Orth AP, Seyfried NT, Levey AI, Ruiz A, Aspelund T, Jennings LL, Launer LJ, Gudmundsdottir V, Gudnason V. Serum proteomics reveal APOE-ε4-dependent and APOE-ε4-independent protein signatures in Alzheimer's disease. NATURE AGING 2024:10.1038/s43587-024-00693-1. [PMID: 39169269 DOI: 10.1038/s43587-024-00693-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Accepted: 07/22/2024] [Indexed: 08/23/2024]
Abstract
A deeper understanding of the molecular processes underlying late-onset Alzheimer's disease (LOAD) could aid in biomarker and drug target discovery. Using high-throughput serum proteomics in the prospective population-based Age, Gene/Environment Susceptibility-Reykjavik Study (AGES) cohort of 5,127 older Icelandic adults (mean age, 76.6 ± 5.6 years), we identified 303 proteins associated with incident LOAD over a median follow-up of 12.8 years. Over 40% of these proteins were associated with LOAD independently of APOE-ε4 carrier status, were implicated in neuronal processes and overlapped with LOAD protein signatures in brain and cerebrospinal fluid. We identified 17 proteins whose associations with LOAD were strongly dependent on APOE-ε4 carrier status, with mostly consistent associations in cerebrospinal fluid. Remarkably, four of these proteins (TBCA, ARL2, S100A13 and IRF6) were downregulated by APOE-ε4 yet upregulated due to LOAD, a finding replicated in external cohorts and possibly reflecting a response to disease onset. These findings highlight dysregulated pathways at the preclinical stages of LOAD, including those both independent of and dependent on APOE-ε4 status.
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Affiliation(s)
| | - Valur Emilsson
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | | | - Erik C B Johnson
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Raquel Puerta
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Barcelona, Spain
| | - Eric B Dammer
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Anantharaman Shantaraman
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Amanda Cano
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Mercè Boada
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Sergi Valero
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Pablo García-González
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | | | | | | | | | | | | | | | - Nicholas T Seyfried
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Allan I Levey
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Agustin Ruiz
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Barcelona, Spain
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Thor Aspelund
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Bethesda, MD, USA
| | - Valborg Gudmundsdottir
- Icelandic Heart Association, Kopavogur, Iceland.
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland.
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland.
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland.
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7
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Levites Y, Dammer EB, Ran Y, Tsering W, Duong D, Abreha M, Gadhavi J, Lolo K, Trejo-Lopez J, Phillips J, Iturbe A, Erquizi A, Moore BD, Ryu D, Natu A, Dillon K, Torrellas J, Moran C, Ladd T, Afroz F, Islam T, Jagirdar J, Funk CC, Robinson M, Rangaraju S, Borchelt DR, Ertekin-Taner N, Kelly JW, Heppner FL, Johnson ECB, McFarland K, Levey AI, Prokop S, Seyfried NT, Golde TE. Integrative proteomics identifies a conserved Aβ amyloid responsome, novel plaque proteins, and pathology modifiers in Alzheimer's disease. Cell Rep Med 2024; 5:101669. [PMID: 39127040 PMCID: PMC11384960 DOI: 10.1016/j.xcrm.2024.101669] [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: 08/03/2023] [Revised: 04/15/2024] [Accepted: 07/10/2024] [Indexed: 08/12/2024]
Abstract
Alzheimer's disease (AD) is a complex neurodegenerative disorder that develops over decades. AD brain proteomics reveals vast alterations in protein levels and numerous altered biologic pathways. Here, we compare AD brain proteome and network changes with the brain proteomes of amyloid β (Aβ)-depositing mice to identify conserved and divergent protein networks with the conserved networks identifying an Aβ amyloid responsome. Proteins in the most conserved network (M42) accumulate in plaques, cerebrovascular amyloid (CAA), and/or dystrophic neuronal processes, and overexpression of two M42 proteins, midkine (Mdk) and pleiotrophin (PTN), increases the accumulation of Aβ in plaques and CAA. M42 proteins bind amyloid fibrils in vitro, and MDK and PTN co-accumulate with cardiac transthyretin amyloid. M42 proteins appear intimately linked to amyloid deposition and can regulate amyloid deposition, suggesting that they are pathology modifiers and thus putative therapeutic targets. We posit that amyloid-scaffolded accumulation of numerous M42+ proteins is a central mechanism mediating downstream pathophysiology in AD.
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Affiliation(s)
- Yona Levites
- Department of Pharmacology and Chemical Biology, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Eric B Dammer
- Department of Biochemistry, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Yong Ran
- Department of Pharmacology and Chemical Biology, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Wangchen Tsering
- Department of Pathology, College of Medicine, University of Florida, Gainesville, FL, USA; Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA; Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, USA
| | - Duc Duong
- Department of Biochemistry, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Measho Abreha
- Department of Biochemistry, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Joshna Gadhavi
- Department of Biochemistry, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Kiara Lolo
- Department of Pathology, College of Medicine, University of Florida, Gainesville, FL, USA; Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA; Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, USA
| | - Jorge Trejo-Lopez
- Department of Pathology, College of Medicine, University of Florida, Gainesville, FL, USA; Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA; Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, USA
| | - Jennifer Phillips
- Department of Pathology, College of Medicine, University of Florida, Gainesville, FL, USA; Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA; Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, USA
| | - Andrea Iturbe
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, USA; Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Aya Erquizi
- Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, USA; Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Brenda D Moore
- Department of Pharmacology and Chemical Biology, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Danny Ryu
- Department of Pharmacology and Chemical Biology, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Aditya Natu
- Department of Biochemistry, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Kristy Dillon
- Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA; Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, USA; Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Jose Torrellas
- Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA; Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, USA; Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Corey Moran
- Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA; Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, USA; Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Thomas Ladd
- Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA; Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, USA
| | - Farhana Afroz
- Department of Pharmacology and Chemical Biology, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Tariful Islam
- Department of Pharmacology and Chemical Biology, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Jaishree Jagirdar
- Department of Pathology and Laboratory Medicine, Emory University Hospital, Atlanta, GA, USA
| | - Cory C Funk
- Institute for Systems Biology, Seattle, WA, USA
| | | | | | - David R Borchelt
- Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA; Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, USA; Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
| | - Nilüfer Ertekin-Taner
- Mayo Clinic, Department of Neuroscience, Jacksonville, FL, USA; Mayo Clinic, Department of Neurology, Jacksonville, FL, USA
| | - Jeffrey W Kelly
- Department of Chemistry and The Skaggs Institute for Chemical Biology, The Scripps Research Institute, La Jolla, CA, USA
| | - Frank L Heppner
- Department of Neuropathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, 110117 Berlin, Germany; German Center for Neurodegenerative Diseases (DZNE) Berlin, 110117 Berlin, Germany; Cluster of Excellence, NeuroCure, Charitéplatz, 110117 Berlin, Germany
| | - Erik C B Johnson
- Department of Neurology, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Karen McFarland
- Department of Pharmacology and Chemical Biology, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Allan I Levey
- Department of Neurology, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA
| | - Stefan Prokop
- Department of Pathology, College of Medicine, University of Florida, Gainesville, FL, USA; Evelyn F. and William L. McKnight Brain Institute, University of Florida, Gainesville, FL, USA; Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, USA; Department of Neurology, College of Medicine, University of Florida, Gainesville, FL, USA.
| | - Nicholas T Seyfried
- Department of Biochemistry, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA.
| | - Todd E Golde
- Department of Pharmacology and Chemical Biology, School of Medicine, Emory University, Atlanta, GA, USA; Department of Neurology, School of Medicine, Emory University, Atlanta, GA, USA; Goizueta Brain Health Institute and Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA; Center for Neurodegenerative Disease Center, Emory University School of Medicine, Atlanta, GA, USA.
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8
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Hok-A-Hin YS, Vermunt L, Peeters CFW, van der Ende EL, de Boer SCM, Meeter LH, van Swieten JC, Hu WT, Lleó A, Alcolea D, Engelborghs S, Sieben A, Chen-Plotkin A, Irwin DJ, van der Flier WM, Pijnenburg YAL, Teunissen CE, Del Campo M. Large-scale CSF proteome profiling identifies biomarkers for accurate diagnosis of Frontotemporal Dementia. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.19.24312100. [PMID: 39228745 PMCID: PMC11370532 DOI: 10.1101/2024.08.19.24312100] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
Diagnosis of Frontotemporal dementia (FTD) and the specific underlying neuropathologies (frontotemporal lobar degeneration; FTLD- Tau and FTLD-TDP) is challenging, and thus fluid biomarkers are needed to improve diagnostic accuracy. We used proximity extension assays to analyze 665 proteins in cerebrospinal fluid (CSF) samples from a multicenter cohort including patients with FTD (n = 189), Alzheimer's Disease dementia (AD; n = 232), and cognitively unimpaired individuals (n = 196). In a subset, FTLD neuropathology was determined based on phenotype or genotype (FTLD-Tau = 87 and FTLD-TDP = 68). Forty three proteins were differentially regulated in FTD compared to controls and AD, reflecting axon development, regulation of synapse assembly, and cell-cell adhesion mediator activity pathways. Classification analysis identified a 14- and 13-CSF protein panel that discriminated FTD from controls (AUC: 0.96) or AD (AUC: 0.91). Custom multiplex panels confirmed the highly accurate discrimination between FTD and controls (AUCs > 0.96) or AD (AUCs > 0.88) in three validation cohorts, including one with autopsy confirmation (AUCs > 0.90). Six proteins were differentially regulated between FTLD-TDP and FTLD-Tau, but no reproducible classification model could be generated (AUC: 0.80). Overall, this study introduces novel FTD-specific biomarker panels with potential use in diagnostic setting.
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Affiliation(s)
- Yanaika S Hok-A-Hin
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Lisa Vermunt
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Alzheimer Center and Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, The Netherlands
| | - Carel F W Peeters
- Mathematical & Statistical Methods group - Biometris, Wageningen University & Research, Wageningen, The Netherlands
| | - Emma L van der Ende
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Sterre C M de Boer
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Alzheimer Center and Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, The Netherlands
- School of Psychology and Brain & Mind Centre, The University of Sydney, Sydney, Australia
| | - Lieke H Meeter
- Alzheimer center and department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - John C van Swieten
- Alzheimer center and department of Neurology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - William T Hu
- Department of Neurology, Center for Neurodegenerative Diseases Research, Emory University School of Medicine, Atlanta, USA
| | - Alberto Lleó
- Department of Neurology, Institut d'Investigacions Biomèdiques Sant Pau (IIB SANT PAU) - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Daniel Alcolea
- Department of Neurology, Institut d'Investigacions Biomèdiques Sant Pau (IIB SANT PAU) - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Hospital de la Santa Creu i Sant Pau, Barcelona, Catalunya, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Vrije Universiteit Brussel, Center for Neurosciences (C4N), Neuroprotection and Neuromodulation Research Group (NEUR), Brussels, Belgium
- Universitair Ziekenhuis Brussel, Department of Neurology, Brussels, Belgium
| | - Anne Sieben
- Lab of neuropathology, Neurobiobank, Institute Born-Bunge, Antwerp University, Edegem, Belgium
| | - Alice Chen-Plotkin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - David J Irwin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Wiesje M van der Flier
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Alzheimer Center and Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, The Netherlands
| | - Yolande A L Pijnenburg
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Alzheimer Center and Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, The Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Marta Del Campo
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam UMC, The Netherlands
- Barcelonaßeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- Departamento de Ciencias Farmacéuticas y de la Salud, Facultad de Farmacia, Universidad San PabloCEU, CEU Universities, Madrid, Spain
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9
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Kuchenbecker LA, Thompson KJ, Hurst CD, Opdenbosch BM, Heckman MG, Reddy JS, Nguyen T, Casellas HL, Sotelo KD, Reddy DJ, Lucas JA, Day GS, Willis FB, Graff-Radford N, Ertekin-Taner N, Kalari KR, Carrasquillo MM. Nomination of a novel plasma protein biomarker panel capable of classifying Alzheimer's disease dementia with high accuracy in an African American cohort. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.07.27.605373. [PMID: 39131392 PMCID: PMC11312441 DOI: 10.1101/2024.07.27.605373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Introduction African Americans (AA) are widely underrepresented in plasma biomarker studies for Alzheimer's disease (AD) and current diagnostic biomarker candidates do not reflect the heterogeneity of AD. Methods Untargeted proteome measurements were obtained using the SomaScan 7k platform to identify novel plasma biomarkers for AD in a cohort of AA clinically diagnosed as AD dementia (n=183) or cognitively unimpaired (CU, n=145). Machine learning approaches were implemented to identify the set of plasma proteins that yields the best classification accuracy. Results A plasma protein panel achieved an area under the curve (AUC) of 0.91 to classify AD dementia vs CU. The reproducibility of this finding was observed in the ANMerge plasma and AMP-AD Diversity brain datasets (AUC=0.83; AUC=0.94). Discussion This study demonstrates the potential of biomarker discovery through untargeted plasma proteomics and machine learning approaches. Our findings also highlight the potential importance of the matrisome and cerebrovascular dysfunction in AD pathophysiology.
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Affiliation(s)
- Lindsey A. Kuchenbecker
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Center for Clinical and Translational Science, Mayo Clinic, Rochester, MN, USA
| | - Kevin J. Thompson
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | | | - Michael G. Heckman
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Joseph S. Reddy
- Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, FL, USA
| | - Thuy Nguyen
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | | | - Katie D. Sotelo
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Delila J. Reddy
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - John A. Lucas
- Department of Psychiatry and Psychology, Mayo Clinic, Jacksonville, FL, USA
| | - Gregory S. Day
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - Floyd B. Willis
- Department of Family Medicine, Mayo Clinic, Jacksonville, FL USA
| | | | - Nilufer Ertekin-Taner
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - Krishna R. Kalari
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
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10
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Guo Y, Chen SD, You J, Huang SY, Chen YL, Zhang Y, Wang LB, He XY, Deng YT, Zhang YR, Huang YY, Dong Q, Feng JF, Cheng W, Yu JT. Multiplex cerebrospinal fluid proteomics identifies biomarkers for diagnosis and prediction of Alzheimer's disease. Nat Hum Behav 2024:10.1038/s41562-024-01924-6. [PMID: 38987357 DOI: 10.1038/s41562-024-01924-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Accepted: 06/10/2024] [Indexed: 07/12/2024]
Abstract
Recent expansion of proteomic coverage opens unparalleled avenues to unveil new biomarkers of Alzheimer's disease (AD). Among 6,361 cerebrospinal fluid (CSF) proteins analysed from the ADNI database, YWHAG performed best in diagnosing both biologically (AUC = 0.969) and clinically (AUC = 0.857) defined AD. Four- (YWHAG, SMOC1, PIGR and TMOD2) and five- (ACHE, YWHAG, PCSK1, MMP10 and IRF1) protein panels greatly improved the accuracy to 0.987 and 0.975, respectively. Their superior performance was validated in an independent external cohort and in discriminating autopsy-confirmed AD versus non-AD, rivalling even canonical CSF ATN biomarkers. Moreover, they effectively predicted the clinical progression to AD dementia and were strongly associated with AD core biomarkers and cognitive decline. Synaptic, neurogenic and infectious pathways were enriched in distinct AD stages. Mendelian randomization did not support the significant genetic link between CSF proteins and AD. Our findings revealed promising high-performance biomarkers for AD diagnosis and prediction, with implications for clinical trials targeting different pathomechanisms.
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Affiliation(s)
- Yu Guo
- 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
| | - Jia You
- 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
| | - Shu-Yi Huang
- 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-Lin 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
| | - 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
| | - Lin-Bo Wang
- Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, 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
| | - 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-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
| | - Yu-Yuan Huang
- 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
| | - 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
| | - 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
| | - 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, 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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11
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Gong Q, Fu M, Wang J, Zhao S, Wang H. Potential Immune-Inflammatory Proteome Biomarkers for Guiding the Treatment of Patients with Primary Acute Angle-Closure Glaucoma Caused by COVID-19. J Proteome Res 2024; 23:2587-2597. [PMID: 38836775 PMCID: PMC11232099 DOI: 10.1021/acs.jproteome.4c00325] [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: 04/16/2024] [Revised: 05/21/2024] [Accepted: 05/23/2024] [Indexed: 06/06/2024]
Abstract
Primary acute angle-closure glaucoma (PAACG) is a sight-threatening condition that can lead to blindness. With the increasing incidence of COVID-19, a multitude of people are experiencing acute vision loss and severe swelling of the eyes and head. These patients were then diagnosed with acute angle closure, with or without a history of PACG. However, the mechanism by which viral infection causes PACG has not been clarified. This is the first study to explore the specific inflammatory proteomic landscape in SARS-CoV-2-induced PAACG. The expression of 92 inflammation-related proteins in 19 aqueous humor samples from PAACGs or cataract patients was detected using the Olink Target 96 Inflammation Panel based on a highly sensitive and specific proximity extension assay technology. The results showed that 76 proteins were significantly more abundant in the PAACG group than in the cataract group. Notably, the top eight differentially expressed proteins were IL-8, MCP-1, TNFRSF9, DNER, CCL4, Flt3L, CXCL10, and CD40. Generally, immune markers are related to inflammation, macrophage activation, and viral infection, revealing the crucial role of macrophages in the occurrence of PAACGs caused by SARS-CoV-2.
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Affiliation(s)
- Qiaoyun Gong
- Department
of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
- National
Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai
Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai
Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai
Engineering Center for Precise Diagnosis and Treatment of Eye Disease, Shanghai 200080, China
| | - Mingshui Fu
- Department
of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
- National
Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai
Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai
Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai
Engineering Center for Precise Diagnosis and Treatment of Eye Disease, Shanghai 200080, China
| | - Jingyi Wang
- Department
of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
- National
Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai
Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai
Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai
Engineering Center for Precise Diagnosis and Treatment of Eye Disease, Shanghai 200080, China
| | - Shuzhi Zhao
- Department
of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
- National
Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai
Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai
Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai
Engineering Center for Precise Diagnosis and Treatment of Eye Disease, Shanghai 200080, China
| | - Haiyan Wang
- Department
of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University, Shanghai 200080, China
- National
Clinical Research Center for Eye Diseases, Shanghai 200080, China
- Shanghai
Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
- Shanghai
Engineering Center for Visual Science and Photomedicine, Shanghai 200080, China
- Shanghai
Engineering Center for Precise Diagnosis and Treatment of Eye Disease, Shanghai 200080, China
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12
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Debette S, Caro I, Western D, Namba S, Sun N, Kawaguchi S, He Y, Fujita M, Roshchupkin G, D'Aoust T, Duperron MG, Sargurupremraj M, Tsuchida A, Koido M, Ahmadi M, Yang C, Timsina J, Ibanez L, Matsuda K, Suzuki Y, Oda Y, Kanai A, Jandaghi P, Munter HM, Auld D, Astafeva I, Puerta R, Rotter J, Psaty B, Bis J, Longstreth W, Couffinhal T, Garcia-Gonzalez P, Pytel V, Marquié M, Cano A, Boada M, Joliot M, Lathrop M, Le Grand Q, Launer L, Wardlaw J, Heiman M, Ruiz A, Matthews P, Seshadri S, Fornage M, Adams H, Mishra A, Trégouët DA, Okada Y, Kellis M, De Jager P, Tzourio C, Kamatani Y, Matsuda F, Cruchaga C. Proteogenomics in cerebrospinal fluid and plasma reveals new biological fingerprint of cerebral small vessel disease. RESEARCH SQUARE 2024:rs.3.rs-4535534. [PMID: 39011113 PMCID: PMC11247936 DOI: 10.21203/rs.3.rs-4535534/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/17/2024]
Abstract
Cerebral small vessel disease (cSVD) is a leading cause of stroke and dementia with no specific mechanism-based treatment. We used Mendelian randomization to combine a unique cerebrospinal fluid (CSF) and plasma pQTL resource with the latest European-ancestry GWAS of MRI-markers of cSVD (white matter hyperintensities, perivascular spaces). We describe a new biological fingerprint of 49 protein-cSVD associations, predominantly in the CSF. We implemented a multipronged follow-up, across fluids, platforms, and ancestries (Europeans and East-Asian), including testing associations of direct plasma protein measurements with MRI-cSVD. We highlight 16 proteins robustly associated in both CSF and plasma, with 24/4 proteins identified in CSF/plasma only. cSVD-proteins were enriched in extracellular matrix and immune response pathways, and in genes enriched in microglia and specific microglial states (integration with single-nucleus RNA sequencing). Immune-related proteins were associated with MRI-cSVD already at age twenty. Half of cSVD-proteins were associated with stroke, dementia, or both, and seven cSVD-proteins are targets for known drugs (used for other indications in directions compatible with beneficial therapeutic effects. This first cSVD proteogenomic signature opens new avenues for biomarker and therapeutic developments.
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Affiliation(s)
| | | | - Daniel Western
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Na Sun
- MIT Computer Science and Artificial Intelligence Laboratory; Broad Institute of MIT and Harvard
| | | | - Yunye He
- Graduate School of Frontier Sciences, The University of Tokyo
| | | | | | - Tim D'Aoust
- Bordeaux Population Health, Inserm U1219, University of Bordeaux
| | | | - Murali Sargurupremraj
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, F-33000 Bordeaux, France; Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases Unive
| | | | - Masaru Koido
- Graduate School of Frontier Sciences, The University of Tokyo
| | | | | | - Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Koichi Matsuda
- Department of Computational Biology and Medical Sciences, Graduate school of Frontier Sciences, The University of Tokyo
| | | | - Yoshiya Oda
- Graduate School of Medicine, The University of Tokyo
| | | | | | | | - Dan Auld
- Victor Phillip Dahdaleh Institute of Genomic Medicine, McGill University
| | - Iana Astafeva
- Bordeaux Population Health, Inserm U1219, University of Bordeaux; Institute of Neurodegenerative Diseases
| | | | - Jerome Rotter
- The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center
| | | | | | | | - Thierry Couffinhal
- University of Bordeaux, The clinical unit of Exploration, Prevention and Care Center for Atherosclerosis (CEPTA), CHUB, Inserm U1034
| | | | - Vanesa Pytel
- Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya; CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III
| | | | | | | | | | - Mark Lathrop
- Department of Human Genetics, McGill University, 1205 Dr Penfield Avenue, Montreal, QC, H3A 1B1, Canada
| | - Quentin Le Grand
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, UMR 1219
| | - Lenore Launer
- National Institute on Aging, National Institutes of Health
| | | | | | - Agustin Ruiz
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center; Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya;CIBERN
| | - Paul Matthews
- UK Dementia Research Institute Centre at Imperial College London
| | | | - Myriam Fornage
- 1. Institute of Molecular Medicine, McGovern Medical School, The University of Texas Health Science Center 2. Human Genetics Center, Department of Epidemiology, School of Public Health
| | - Hieab Adams
- Department of Human Genetics, Radboud University Medical Center; Latin American Brain Health (BrainLat), Universidad Adolfo Ibáñez
| | | | | | - Yukinori Okada
- Department of Genome Informatics, Graduate School of Medicine, The Univ. of Tokyo; Department of Statistical Genetics, Osaka Univ. Graduate School of Medicine; Laboratory for Systems Genetic, RIKEN
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13
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Dammer EB, Shantaraman A, Ping L, Duong DM, Gerasimov ES, Ravindran SP, Gudmundsdottir V, Frick EA, Gomez GT, Walker KA, Emilsson V, Jennings LL, Gudnason V, Western D, Cruchaga C, Lah JJ, Wingo TS, Wingo AP, Seyfried NT, Levey AI, Johnson ECB. Proteomic analysis of Alzheimer's disease cerebrospinal fluid reveals alterations associated with APOE ε4 and atomoxetine treatment. Sci Transl Med 2024; 16:eadn3504. [PMID: 38924431 DOI: 10.1126/scitranslmed.adn3504] [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: 12/07/2023] [Accepted: 06/05/2024] [Indexed: 06/28/2024]
Abstract
Alzheimer's disease (AD) is currently defined by the aggregation of amyloid-β (Aβ) and tau proteins in the brain. Although biofluid biomarkers are available to measure Aβ and tau pathology, few markers are available to measure the complex pathophysiology that is associated with these two cardinal neuropathologies. Here, we characterized the proteomic landscape of cerebrospinal fluid (CSF) changes associated with Aβ and tau pathology in 300 individuals using two different proteomic technologies-tandem mass tag mass spectrometry and SomaScan. Integration of both data types allowed for generation of a robust protein coexpression network consisting of 34 modules derived from 5242 protein measurements, including disease-relevant modules associated with autophagy, ubiquitination, endocytosis, and glycolysis. Three modules strongly associated with the apolipoprotein E ε4 (APOE ε4) AD risk genotype mapped to oxidant detoxification, mitogen-associated protein kinase signaling, neddylation, and mitochondrial biology and overlapped with a previously described lipoprotein module in serum. Alterations of all three modules in blood were associated with dementia more than 20 years before diagnosis. Analysis of CSF samples from an AD phase 2 clinical trial of atomoxetine (ATX) demonstrated that abnormal elevations in the glycolysis CSF module-the network module most strongly correlated to cognitive function-were reduced by ATX treatment. Clustering of individuals based on their CSF proteomic profiles revealed heterogeneity of pathological changes not fully reflected by Aβ and tau.
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Affiliation(s)
- Eric B Dammer
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Anantharaman Shantaraman
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Lingyan Ping
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Duc M Duong
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Ekaterina S Gerasimov
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | | | - Valborg Gudmundsdottir
- Icelandic Heart Association, 201 Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | | | - Gabriela T Gomez
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA
| | - Keenan A Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD 21224, USA
| | - Valur Emilsson
- Icelandic Heart Association, 201 Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | | | - Vilmundur Gudnason
- Icelandic Heart Association, 201 Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, 101 Reykjavik, Iceland
| | - Daniel Western
- Department of Psychiatry, Washington University, St. Louis, MO 63108, USA
- NeuroGenomics and Informatics, Washington University, St. Louis, MO 63108, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO 63108, USA
- NeuroGenomics and Informatics, Washington University, St. Louis, MO 63108, USA
| | - James J Lah
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Thomas S Wingo
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Genetics, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Aliza P Wingo
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Psychiatry, Emory University School of Medicine, Atlanta, GA 30322, USA
- Division of Mental Health, Atlanta VA Medical Center, Decatur, GA 30033, USA
| | - Nicholas T Seyfried
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Allan I Levey
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
| | - Erik C B Johnson
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA 30322, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30322, USA
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14
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Wojtas AM, Dammer EB, Guo Q, Ping L, Shantaraman A, Duong DM, Yin L, Fox EJ, Seifar F, Lee EB, Johnson ECB, Lah JJ, Levey AI, Levites Y, Rangaraju S, Golde TE, Seyfried NT. Proteomic changes in the human cerebrovasculature in Alzheimer's disease and related tauopathies linked to peripheral biomarkers in plasma and cerebrospinal fluid. Alzheimers Dement 2024; 20:4043-4065. [PMID: 38713744 PMCID: PMC11180878 DOI: 10.1002/alz.13821] [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: 01/25/2024] [Revised: 02/21/2024] [Accepted: 03/02/2024] [Indexed: 05/09/2024]
Abstract
INTRODUCTION Cerebrovascular dysfunction is a pathological hallmark of Alzheimer's disease (AD). Nevertheless, detecting cerebrovascular changes within bulk tissues has limited our ability to characterize proteomic alterations from less abundant cell types. METHODS We conducted quantitative proteomics on bulk brain tissues and isolated cerebrovasculature from the same individuals, encompassing control (N = 28), progressive supranuclear palsy (PSP) (N = 18), and AD (N = 21) cases. RESULTS Protein co-expression network analysis identified unique cerebrovascular modules significantly correlated with amyloid plaques, cerebrovascular amyloid angiopathy (CAA), and/or tau pathology. The protein products within AD genetic risk loci were concentrated within cerebrovascular modules. The overlap between differentially abundant proteins in AD cerebrospinal fluid (CSF) and plasma with cerebrovascular network highlighted a significant increase of matrisome proteins, SMOC1 and SMOC2, in CSF, plasma, and brain. DISCUSSION These findings enhance our understanding of cerebrovascular deficits in AD, shedding light on potential biomarkers associated with CAA and vascular dysfunction in neurodegenerative diseases.
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Affiliation(s)
- Aleksandra M. Wojtas
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Eric B. Dammer
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Qi Guo
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Lingyan Ping
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Ananth Shantaraman
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Duc M. Duong
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Luming Yin
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Edward J. Fox
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Fatemeh Seifar
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
| | - Edward B. Lee
- Department of Pathology and Laboratory MedicineUniversity of PennsylvaniaPennsylvaniaUSA
| | - Erik C. B. Johnson
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
- Department of NeurologyEmory University School of MedicineAtlantaGeorgiaUSA
| | - James J. Lah
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
- Department of NeurologyEmory University School of MedicineAtlantaGeorgiaUSA
| | - Allan I. Levey
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
- Department of NeurologyEmory University School of MedicineAtlantaGeorgiaUSA
| | - Yona Levites
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
- Department of Pharmacology and Chemical BiologyEmory University School of MedicineAtlantaGeorgiaUSA
| | - Srikant Rangaraju
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
- Department of NeurologyEmory University School of MedicineAtlantaGeorgiaUSA
| | - Todd E. Golde
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
- Department of NeurologyEmory University School of MedicineAtlantaGeorgiaUSA
- Department of Pharmacology and Chemical BiologyEmory University School of MedicineAtlantaGeorgiaUSA
| | - Nicholas T. Seyfried
- Department of BiochemistryEmory University School of MedicineAtlantaGeorgiaUSA
- Center for Neurodegenerative DiseaseEmory University School of MedicineAtlantaGeorgiaUSA
- Department of NeurologyEmory University School of MedicineAtlantaGeorgiaUSA
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15
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Hidese S. Search for cerebrospinal fluid biomarkers in patients with major psychiatric disorders: Multiplex immunoassay findings and proximity extension assay prospects. Neuropsychopharmacol Rep 2024; 44:314-320. [PMID: 38686540 PMCID: PMC11144604 DOI: 10.1002/npr2.12439] [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: 01/08/2024] [Revised: 03/05/2024] [Accepted: 03/24/2024] [Indexed: 05/02/2024] Open
Abstract
Multiplex immunoassays have been developed to detect multiple proteins simultaneously and are used to search for biomarkers, including those present in major psychiatric disorders. This study aimed to review multiplex immunoassay studies on cerebrospinal fluid (CSF) biomarkers in patients with schizophrenia, bipolar disorder (BD), and major depressive disorder (MDD) and examine future research directions using improved proteomic techniques. According to the results of previous multiplex immunoassay studies, increased CSF IFN-β, IL-8, MCP-2, MMP-2, PAI-1, sICAM-1, and sVCAM-1 and decreased CSF ACE, APP, fibrinogen, and GDNF were observed in patients with schizophrenia, while CSF HGF and S100B were positively correlated with psychotic symptom and CSF IL-11, IL-29/IFN-λ1, and TSLP were negatively correlated. Increased CSF IFN-β and IL-1β and decreased CSF Aβ42, APP, IL-6, and NCAM-1 were observed, while CSF S100B was positively correlated with manic symptom in patients with BD. Increased CSF IL-4, MCP-1, MIP-1β, and MMP-2 were observed in patients with MDD, while CSF HGF and MMP-2 were positively correlated with depressive symptom and CSF IL-15 and MCP-1 were negatively correlated. However, signal cross-talk and cross-reactivity problems have been observed in previous studies using multiplex immunoassay. The proximity extension assay can be used to overcome cross-reactivity and enable ultrasensitive multiplexed detection and quantification of more than 1000 target proteins. However, proteomic studies using proximity extension assay technology in patients with schizophrenia, BD, or MDD are still scarce. Therefore, future high-quality proteomic studies are required to identify CSF biomarkers for larger sets of target proteins in patients with major psychiatric disorders.
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Affiliation(s)
- Shinsuke Hidese
- Department of PsychiatryTeikyo University School of MedicineTokyoJapan
- Department of Mental Disorder Research, National Center of Neurology and PsychiatryNational Institute of NeuroscienceKodaira, TokyoJapan
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16
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Almeida-Marques C, Rolfs F, Piersma SR, Bijnsdorp IV, Pham TV, Knol JC, Jimenez CR. Secretome processing for proteomics: A methods comparison. Proteomics 2024; 24:e2300262. [PMID: 38221716 DOI: 10.1002/pmic.202300262] [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: 06/26/2023] [Revised: 11/24/2023] [Accepted: 12/07/2023] [Indexed: 01/16/2024]
Abstract
The cancer cell secretome comprises a treasure-trove for biomarkers since it reflects cross-talk between tumor cells and their surrounding environment with high detectability in biofluids. In this study, we evaluated six secretome sample processing workflows coupled to single-shot mass spectrometry: (1) Protein concentration by ultrafiltration with a molecular weight cut-off (MWCO) filter and sample preparation through in-gel digestion (IGD); (2) Acetone protein precipitation coupled to IGD; (3) MWCO filter-based protein concentration followed by to in-solution digestion (ISD); (4) Acetone protein precipitation coupled to ISD; (5) Direct ISD; (6) Secretome lyophilization and ISD. To this end, we assessed workflow triplicates in terms of total number of protein identifications, unique identifications, reproducibility of protein identification and quantification and detectability of small proteins with important functions in cancer biology such as cytokines, chemokines, and growth factors. Our findings revealed that acetone protein precipitation coupled to ISD outperformed the other methods in terms of the number of identified proteins (2246) and method reproducibility (correlation coefficient between replicates (r = 0.94, CV = 19%). Overall, especially small proteins such as those from the classes mentioned above were better identified using ISD workflows. Concluding, herein we report that secretome protein precipitation coupled to ISD is the method of choice for high-throughput secretome proteomics via single shot nanoLC-MS/MS.
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Affiliation(s)
- Catarina Almeida-Marques
- Department Laboratory Medical Oncology, Amsterdam University Medical Center, Amsterdam, Netherlands
- Cancer Center Amsterdam, OncoProteomics Laboratory, Amsterdam, Netherlands
| | - Frank Rolfs
- Department Laboratory Medical Oncology, Amsterdam University Medical Center, Amsterdam, Netherlands
- Cancer Center Amsterdam, OncoProteomics Laboratory, Amsterdam, Netherlands
| | - Sander R Piersma
- Department Laboratory Medical Oncology, Amsterdam University Medical Center, Amsterdam, Netherlands
- Cancer Center Amsterdam, OncoProteomics Laboratory, Amsterdam, Netherlands
| | - Irene V Bijnsdorp
- Cancer Center Amsterdam, OncoProteomics Laboratory, Amsterdam, Netherlands
- Department Urology, Amsterdam University Medical Center, Amsterdam, Netherlands
| | - Thang V Pham
- Department Laboratory Medical Oncology, Amsterdam University Medical Center, Amsterdam, Netherlands
- Cancer Center Amsterdam, OncoProteomics Laboratory, Amsterdam, Netherlands
| | - Jaco C Knol
- Department Laboratory Medical Oncology, Amsterdam University Medical Center, Amsterdam, Netherlands
- Cancer Center Amsterdam, OncoProteomics Laboratory, Amsterdam, Netherlands
| | - Connie R Jimenez
- Department Laboratory Medical Oncology, Amsterdam University Medical Center, Amsterdam, Netherlands
- Cancer Center Amsterdam, OncoProteomics Laboratory, Amsterdam, Netherlands
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17
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Saloner R, Staffaroni A, Dammer E, Johnson ECB, Paolillo E, Wise A, Heuer H, Forsberg L, Lago AL, Webb J, Vogel J, Santillo A, Hansson O, Kramer J, Miller B, Li J, Loureiro J, Sivasankaran R, Worringer K, Seyfried N, Yokoyama J, Seeley W, Spina S, Grinberg L, VandeVrede L, Ljubenkov P, Bayram E, Bozoki A, Brushaber D, Considine C, Day G, Dickerson B, Domoto-Reilly K, Faber K, Galasko D, Geschwind D, Ghoshal N, Graff-Radford N, Hales C, Honig L, Hsiung GY, Huey E, Kornak J, Kremers W, Lapid M, Lee S, Litvan I, McMillan C, Mendez M, Miyagawa T, Pantelyat A, Pascual B, Paulson H, Petrucelli L, Pressman P, Ramos E, Rascovsky K, Roberson E, Savica R, Snyder A, Sullivan AC, Tartaglia C, Vandebergh M, Boeve B, Rosen H, Rojas J, Boxer A, Casaletto K. Large-scale network analysis of the cerebrospinal fluid proteome identifies molecular signatures of frontotemporal lobar degeneration. RESEARCH SQUARE 2024:rs.3.rs-4103685. [PMID: 38585969 PMCID: PMC10996789 DOI: 10.21203/rs.3.rs-4103685/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/09/2024]
Abstract
The pathophysiological mechanisms driving disease progression of frontotemporal lobar degeneration (FTLD) and corresponding biomarkers are not fully understood. We leveraged aptamer-based proteomics (> 4,000 proteins) to identify dysregulated communities of co-expressed cerebrospinal fluid proteins in 116 adults carrying autosomal dominant FTLD mutations (C9orf72, GRN, MAPT) compared to 39 noncarrier controls. Network analysis identified 31 protein co-expression modules. Proteomic signatures of genetic FTLD clinical severity included increased abundance of RNA splicing (particularly in C9orf72 and GRN) and extracellular matrix (particularly in MAPT) modules, as well as decreased abundance of synaptic/neuronal and autophagy modules. The generalizability of genetic FTLD proteomic signatures was tested and confirmed in independent cohorts of 1) sporadic progressive supranuclear palsy-Richardson syndrome and 2) frontotemporal dementia spectrum syndromes. Network-based proteomics hold promise for identifying replicable molecular pathways in adults living with FTLD. 'Hub' proteins driving co-expression of affected modules warrant further attention as candidate biomarkers and therapeutic targets.
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Affiliation(s)
| | | | | | | | | | - Amy Wise
- University of California, San Francisco
| | | | | | | | | | | | | | | | | | | | - Jingyao Li
- Novartis Institutes for Biomedical Research, Inc
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Suzee Lee
- University of California, San Francisco
| | | | - Corey McMillan
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Adam Boxer
- Memory and Aging Center, Department of Neurology, University of California, San Francisco
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18
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Yang F, Beltran-Lobo P, Sung K, Goldrick C, Croft CL, Nishimura A, Hedges E, Mahiddine F, Troakes C, Golde TE, Perez-Nievas BG, Hanger DP, Noble W, Jimenez-Sanchez M. Reactive astrocytes secrete the chaperone HSPB1 to mediate neuroprotection. SCIENCE ADVANCES 2024; 10:eadk9884. [PMID: 38507480 PMCID: PMC10954207 DOI: 10.1126/sciadv.adk9884] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 02/14/2024] [Indexed: 03/22/2024]
Abstract
Molecular chaperones are protective in neurodegenerative diseases by preventing protein misfolding and aggregation, such as extracellular amyloid plaques and intracellular tau neurofibrillary tangles in Alzheimer's disease (AD). In addition, AD is characterized by an increase in astrocyte reactivity. The chaperone HSPB1 has been proposed as a marker for reactive astrocytes; however, its astrocytic functions in neurodegeneration remain to be elucidated. Here, we identify that HSPB1 is secreted from astrocytes to exert non-cell-autonomous protective functions. We show that in human AD brain, HSPB1 levels increase in astrocytes that cluster around amyloid plaques, as well as in the adjacent extracellular space. Moreover, in conditions that mimic an inflammatory reactive response, astrocytes increase HSPB1 secretion. Concomitantly, astrocytes and neurons can uptake astrocyte-secreted HSPB1, which is accompanied by an attenuation of the inflammatory response in reactive astrocytes and reduced pathological tau inclusions. Our findings highlight a protective mechanism in disease conditions that encompasses the secretion of a chaperone typically regarded as intracellular.
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Affiliation(s)
- Fangjia Yang
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 5 Cutcombe Road, London SE5 9RX, UK
| | - Paula Beltran-Lobo
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 5 Cutcombe Road, London SE5 9RX, UK
| | - Katherine Sung
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 5 Cutcombe Road, London SE5 9RX, UK
| | - Caoimhe Goldrick
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 5 Cutcombe Road, London SE5 9RX, UK
| | - Cara L. Croft
- UK Dementia Research Institute, UCL Institute of Neurology, University College London, London, UK
- Centre for Neuroscience, Surgery and Trauma, Blizard Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK
| | - Agnes Nishimura
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 5 Cutcombe Road, London SE5 9RX, UK
| | - Erin Hedges
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 5 Cutcombe Road, London SE5 9RX, UK
| | - Farah Mahiddine
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 5 Cutcombe Road, London SE5 9RX, UK
| | - Claire Troakes
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 5 Cutcombe Road, London SE5 9RX, UK
- London Neurodegenerative Diseases Brain Bank, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Todd E. Golde
- Department of Neuroscience, College of Medicine, University of Florida, Gainesville, FL, USA
- Center for Translational Research in Neurodegenerative Disease, College of Medicine, University of Florida, Gainesville, FL, USA
- McKnight Brain Institute, College of Medicine, University of Florida, Gainesville, FL, USA
- Department of Pharmacology and Chemical Biology, Department of Neurology, Emory Center for Neurodegenerative Disease, Emory University, Atlanta, GA, USA
| | - Beatriz G. Perez-Nievas
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 5 Cutcombe Road, London SE5 9RX, UK
| | - Diane P. Hanger
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 5 Cutcombe Road, London SE5 9RX, UK
| | - Wendy Noble
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 5 Cutcombe Road, London SE5 9RX, UK
- Department of Biomedical and Clinical Sciences, University of Exeter, Exeter, UK
| | - Maria Jimenez-Sanchez
- Department of Basic and Clinical Neuroscience, Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, 5 Cutcombe Road, London SE5 9RX, UK
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19
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Singh B, Mayr M. Enhancing cardiovascular risk prediction through proteomics? Cardiovasc Res 2024; 120:e2-e4. [PMID: 38411603 PMCID: PMC10939458 DOI: 10.1093/cvr/cvae031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/02/2023] [Accepted: 01/08/2024] [Indexed: 02/28/2024] Open
Affiliation(s)
- Bhawana Singh
- King’s British Heart Foundation Centre, King’s College London, London SE5 9NU, UK
| | - Manuel Mayr
- National Heart and Lung Institute, Sir Michael Uren Hub, White City Campus, Imperial College London, London W12 7ED, UK
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20
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Arioz BI, Cotuk A, Yaka EC, Genc S. Proximity extension assay-based proteomics studies in neurodegenerative disorders and multiple sclerosis. Eur J Neurosci 2024; 59:1348-1358. [PMID: 38105531 DOI: 10.1111/ejn.16226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/19/2023] [Revised: 11/20/2023] [Accepted: 11/23/2023] [Indexed: 12/19/2023]
Abstract
Neurodegenerative diseases impact the structure and operation of the nervous system, causing progressive and irreparable harm. Efforts for distinguishing neurodegenerative diseases in their early stages are continuing. Despite several biomarkers being identified, there is always search for more accurate and abundant ones. Additionally, it can be difficult to pinpoint the precise neurodegenerative disorder affecting a patient as the symptoms of these conditions frequently overlap. Numerous studies have shown that pathological changes occur years before clinical signs appear. Therefore, it is crucial to discover blood-based biomarkers for neurodegenerative diseases for easier and earlier diagnosis. Proximity extension assay is a unique proteomics method that uses antibodies linked to oligonucleotides for quantifying proteins with real-time PCR. Proximity extension assay can identify even low-quantity proteins using a small volume of specimens with increased sensitivity compared to conventional methods. In this article, we reviewed the employment of proximity extension assay technology to detect biomarkers or protein profiles for several neurodegenerative diseases.
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Affiliation(s)
- Burak I Arioz
- Izmir Biomedicine and Genome Center, Izmir, Turkey
- Izmir Biomedicine and Genome Institute, Izmir, Turkey
| | - Aysen Cotuk
- Izmir Biomedicine and Genome Center, Izmir, Turkey
- Izmir Biomedicine and Genome Institute, Izmir, Turkey
| | - Emiş Cansu Yaka
- Health Sciences University, Izmir Tepecik Education and Research Hospital, Izmir, Turkey
| | - Sermin Genc
- Izmir Biomedicine and Genome Center, Izmir, Turkey
- Izmir Biomedicine and Genome Institute, Izmir, Turkey
- Department of Neuroscience, Institute of Health Sciences, Dokuz Eylul University, Izmir, Turkey
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21
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Abiose O, Rutledge J, Moran‐Losada P, Belloy ME, Wilson EN, He Z, Trelle AN, Channappa D, Romero A, Park J, Yutsis MV, Sha SJ, Andreasson KI, Poston KL, Henderson VW, Wagner AD, Wyss‐Coray T, Mormino EC. Post-translational modifications linked to preclinical Alzheimer's disease-related pathological and cognitive changes. Alzheimers Dement 2024; 20:1851-1867. [PMID: 38146099 PMCID: PMC10984434 DOI: 10.1002/alz.13576] [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: 08/01/2023] [Revised: 11/08/2023] [Accepted: 11/13/2023] [Indexed: 12/27/2023]
Abstract
INTRODUCTION In this study, we leverage proteomic techniques to identify communities of proteins underlying Alzheimer's disease (AD) risk among clinically unimpaired (CU) older adults. METHODS We constructed a protein co-expression network using 3869 cerebrospinal fluid (CSF) proteins quantified by SomaLogic, Inc., in a cohort of participants along the AD clinical spectrum. We then replicated this network in an independent cohort of CU older adults and related these modules to clinically-relevant outcomes. RESULTS We discovered modules enriched for phosphorylation and ubiquitination that were associated with abnormal amyloid status, as well as p-tau181 (M4: β = 2.44, p < 0.001, M7: β = 2.57, p < 0.001) and executive function performance (M4: β = -2.00, p = 0.005, M7: β = -2.39, p < 0.001). DISCUSSION In leveraging CSF proteomic data from individuals spanning the clinical spectrum of AD, we highlight the importance of post-translational modifications for early cognitive and pathological changes.
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Affiliation(s)
- Olamide Abiose
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
- Wu Tsai Neurosciences InstituteStanford University School of MedicineStanfordCaliforniaUSA
| | - Jarod Rutledge
- The Phil and Penny Knight Initiative for Brain ResilienceStanford UniversityStanfordCaliforniaUSA
- Department of GeneticsStanford UniversityStanfordCaliforniaUSA
| | - Patricia Moran‐Losada
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
- Wu Tsai Neurosciences InstituteStanford University School of MedicineStanfordCaliforniaUSA
- The Phil and Penny Knight Initiative for Brain ResilienceStanford UniversityStanfordCaliforniaUSA
| | - Michael E. Belloy
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - Edward N. Wilson
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
- Wu Tsai Neurosciences InstituteStanford University School of MedicineStanfordCaliforniaUSA
| | - Zihuai He
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
- Center for Biomedical Informatics ResearchStanford University School of MedicineStanfordCaliforniaUSA
| | - Alexandra N. Trelle
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - Divya Channappa
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - America Romero
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - Jennifer Park
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - Maya V. Yutsis
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - Sharon J. Sha
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
| | - Katrin I. Andreasson
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
- Wu Tsai Neurosciences InstituteStanford University School of MedicineStanfordCaliforniaUSA
- Chan Zuckerberg BiohubSan FranciscoCaliforniaUSA
| | - Kathleen L. Poston
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
- Wu Tsai Neurosciences InstituteStanford University School of MedicineStanfordCaliforniaUSA
- The Phil and Penny Knight Initiative for Brain ResilienceStanford UniversityStanfordCaliforniaUSA
| | - Victor W. Henderson
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
- Department of Epidemiology & Population HealthStanford University School of MedicineStanfordCaliforniaUSA
| | - Anthony D. Wagner
- Wu Tsai Neurosciences InstituteStanford University School of MedicineStanfordCaliforniaUSA
- Department of PsychologyStanford UniversityStanfordCaliforniaUSA
| | - Tony Wyss‐Coray
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
- Wu Tsai Neurosciences InstituteStanford University School of MedicineStanfordCaliforniaUSA
- The Phil and Penny Knight Initiative for Brain ResilienceStanford UniversityStanfordCaliforniaUSA
| | - Elizabeth C. Mormino
- Department of Neurology and Neurological SciencesStanford University School of MedicinePalo AltoCaliforniaUSA
- Wu Tsai Neurosciences InstituteStanford University School of MedicineStanfordCaliforniaUSA
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22
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Guo Q, Ping L, Dammer EB, Yin L, Xu K, Shantaraman A, Fox EJ, Golde TE, Johnson ECB, Roberts BR, Lah JJ, Levey AI, Seyfried NT. Heparin-enriched plasma proteome is significantly altered in Alzheimer's Disease. RESEARCH SQUARE 2024:rs.3.rs-3933136. [PMID: 38464223 PMCID: PMC10925398 DOI: 10.21203/rs.3.rs-3933136/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: 03/12/2024]
Abstract
Introduction Heparin binding proteins (HBPs) with roles in extracellular matrix assembly are strongly correlated to β-amyloid (Aβ) and tau pathology in Alzheimer's disease (AD) brain and cerebrospinal fluid (CSF). However, it remains challenging to detect these proteins in plasma using standard mass spectrometry-based proteomic approaches. Methods We employed heparin affinity chromatography, followed by off-line fractionation and tandem mass tag mass spectrometry (TMT-MS), to capture and enrich HBPs in plasma obtained from AD (n=62) and control (n=47) samples. These profiles were then correlated to a consensus AD brain proteome, as well as with Aβ, tau and phosphorylated tau (pTau) CSF biomarkers from the same individuals. We then leveraged published human postmortem brain proteome datasets to assess the overlap with the heparin-enriched plasma proteome. Results Heparin-enrichment from plasma was highly reproducible, enriched well-known HBPs like APOE and thrombin, and depleted high-abundance proteins such as albumin. A total of 2865 proteins, spanning 10 orders of magnitude were detectable. Utilizing a consensus AD brain protein co-expression network, we observed that specific plasma HBPs exhibited consistent direction of change in both brain and plasma, whereas others displayed divergent changes highlighting the complex interplay between the two compartments. Elevated HBPs in AD plasma, when compared to controls, included members of the matrisome module in brain that accumulate within Aβ deposits, such as SMOC1, SMOC2, SPON1, MDK, OLFML3, FRZB, GPNMB, and APOE. Additionally, heparin enriched plasma proteins demonstrated significant correlations with conventional AD CSF biomarkers, including Aβ, total tau, pTau, and plasma pTau from the same individuals. Conclusion These findings support the utility of a heparin-affinity approach for enriching amyloid-associated proteins, as well as a wide spectrum of plasma biomarkers that reflect pathological changes in the AD brain.
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Affiliation(s)
- Qi Guo
- Emory University School of Medicine
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23
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Fernández-Irigoyen J, Santamaría E. Special Issue "Deployment of Proteomics Approaches in Biomedical Research". Int J Mol Sci 2024; 25:1717. [PMID: 38338994 PMCID: PMC10855870 DOI: 10.3390/ijms25031717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 01/30/2024] [Indexed: 02/12/2024] Open
Abstract
Many angles of personalized medicine, such as diagnostic improvements, systems biology [...].
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Affiliation(s)
| | - Enrique Santamaría
- Proteomics Platform, Clinical Neuroproteomics Unit, Navarrabiomed, Hospitalario Universitario de Navarra (HUN), Navarra Institute for Health Research (IDISNA), Universidad Pública de Navarra (UPNA), Irunlarrea 3, 31008 Pamplona, Spain
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24
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Duijvelaar E, Gisby J, Peters JE, Bogaard HJ, Aman J. Longitudinal plasma proteomics reveals biomarkers of alveolar-capillary barrier disruption in critically ill COVID-19 patients. Nat Commun 2024; 15:744. [PMID: 38272877 PMCID: PMC10811341 DOI: 10.1038/s41467-024-44986-w] [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: 04/28/2023] [Accepted: 01/11/2024] [Indexed: 01/27/2024] Open
Abstract
The pathobiology of respiratory failure in COVID-19 consists of a complex interplay between viral cytopathic effects and a dysregulated host immune response. In critically ill patients, imatinib treatment demonstrated potential for reducing invasive ventilation duration and mortality. Here, we perform longitudinal profiling of 6385 plasma proteins in 318 hospitalised patients to investigate the biological processes involved in critical COVID-19, and assess the effects of imatinib treatment. Nine proteins measured at hospital admission accurately predict critical illness development. Next to dysregulation of inflammation, critical illness is characterised by pathways involving cellular adhesion, extracellular matrix turnover and tissue remodelling. Imatinib treatment attenuates protein perturbations associated with inflammation and extracellular matrix turnover. These proteomic alterations are contextualised using external pulmonary RNA-sequencing data of deceased COVID-19 patients and imatinib-treated Syrian hamsters. Together, we show that alveolar capillary barrier disruption in critical COVID-19 is reflected in the plasma proteome, and is attenuated with imatinib treatment. This study comprises a secondary analysis of both clinical data and plasma samples derived from a clinical trial that was registered with the EU Clinical Trials Register (EudraCT 2020-001236-10, https://www.clinicaltrialsregister.eu/ctr-search/trial/2020-001236-10/NL ) and Netherlands Trial Register (NL8491, https://www.trialregister.nl/trial/8491 ).
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Affiliation(s)
- Erik Duijvelaar
- Department of Pulmonary Medicine, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands.
| | - Jack Gisby
- Department of Immunology and Inflammation, Centre for Inflammatory Disease, Imperial College London, London, UK
| | - James E Peters
- Department of Immunology and Inflammation, Centre for Inflammatory Disease, Imperial College London, London, UK
| | - Harm Jan Bogaard
- Department of Pulmonary Medicine, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands
| | - Jurjan Aman
- Department of Pulmonary Medicine, Amsterdam University Medical Centers, Amsterdam Cardiovascular Sciences, Amsterdam, The Netherlands.
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25
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Ben Yellin, Lahav C, Sela I, Yahalom G, Shoval SR, Elon Y, Fuller J, Harel M. Analytical validation of the PROphet test for treatment decision-making guidance in metastatic non-small cell lung cancer. J Pharm Biomed Anal 2024; 238:115803. [PMID: 37871417 DOI: 10.1016/j.jpba.2023.115803] [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: 08/07/2023] [Revised: 09/22/2023] [Accepted: 10/16/2023] [Indexed: 10/25/2023]
Abstract
The blood proteome, consisting of thousands of proteins engaged in various biological processes, acts as a valuable source of potential biomarkers for various medical applications. PROphet is a plasma proteomics-based test that serves as a decision-support tool for non-small cell lung cancer (NSCLC) patients, combining proteomic profiling using SomaScan technology and subsequent computational algorithm. PROphet was implemented as a laboratory developed test (LDT). Under the Clinical Laboratory Improvement Amendments (CLIA) and Commission on Office Laboratory Accreditation (COLA) regulations, prior to releasing patient test results, a clinical laboratory located in the United States employing an LDT must examine its performance characteristics with regard to analytical validity. This study describes the experimental and computational analytical validity of the PROphet test, as required by CLIA/COLA regulations. Experimental precision analysis displayed a median coefficient of variation (CV) of 3.9 % and 4.7 % for intra-plate and inter-plate examination, respectively, and the median accuracy rate between sites was 88 %. Computational precision exhibited a high accuracy rate, with 93 % of samples displaying complete concordance in results. A cross-platform comparison between SomaScan and other proteomics platforms yielded a median Spearman's rank correlation coefficient of 0.51, affirming the consistency and reliability of the SomaScan platform as used under the PROphet test. Our study presents a robust framework for evaluating the analytical validity of a platform that combines an experimental assay with subsequent computational algorithms. When applied to the PROphet test, strong analytical performance of the test was demonstrated.
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Affiliation(s)
- Ben Yellin
- OncoHost LTD, Hamelacha 17 Binyamina, 3057324, Israel
| | - Coren Lahav
- OncoHost LTD, Hamelacha 17 Binyamina, 3057324, Israel
| | - Itamar Sela
- OncoHost LTD, Hamelacha 17 Binyamina, 3057324, Israel
| | - Galit Yahalom
- OncoHost LTD, Hamelacha 17 Binyamina, 3057324, Israel
| | | | | | - James Fuller
- OncoHost Inc., 1110 SE Cary Parkway, Suite 205, Cary, NC 27518, USA
| | - Michal Harel
- OncoHost LTD, Hamelacha 17 Binyamina, 3057324, Israel.
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26
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Shen Y, Ali M, Timsina J, Wang C, Do A, Western D, Liu M, Gorijala P, Budde J, Liu H, Gordon B, McDade E, Morris JC, Llibre-Guerra JJ, Bateman RJ, Joseph-Mathurin N, Perrin RJ, Maschi D, Wyss-Coray T, Pastor P, Goate A, Renton AE, Surace EI, Johnson ECB, Levey AI, Alvarez I, Levin J, Ringman JM, Allegri RF, Seyfried N, Day GS, Wu Q, Fernández MV, Ibanez L, Sung YJ, Cruchaga C. Systematic proteomics in Autosomal dominant Alzheimer's disease reveals decades-early changes of CSF proteins in neuronal death, and immune pathways. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.12.24301242. [PMID: 38260583 PMCID: PMC10802763 DOI: 10.1101/2024.01.12.24301242] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Background To date, there is no high throughput proteomic study in the context of Autosomal Dominant Alzheimer's disease (ADAD). Here, we aimed to characterize early CSF proteome changes in ADAD and leverage them as potential biomarkers for disease monitoring and therapeutic strategies. Methods We utilized Somascan® 7K assay to quantify protein levels in the CSF from 291 mutation carriers (MCs) and 185 non-carriers (NCs). We employed a multi-layer regression model to identify proteins with different pseudo-trajectories between MCs and NCs. We replicated the results using publicly available ADAD datasets as well as proteomic data from sporadic Alzheimer's disease (sAD). To biologically contextualize the results, we performed network and pathway enrichment analyses. Machine learning was applied to create and validate predictive models. Findings We identified 125 proteins with significantly different pseudo-trajectories between MCs and NCs. Twelve proteins showed changes even before the traditional AD biomarkers (Aβ42, tau, ptau). These 125 proteins belong to three different modules that are associated with age at onset: 1) early stage module associated with stress response, glutamate metabolism, and mitochondria damage; 2) the middle stage module, enriched in neuronal death and apoptosis; and 3) the presymptomatic stage module was characterized by changes in microglia, and cell-to-cell communication processes, indicating an attempt of rebuilding and establishing new connections to maintain functionality. Machine learning identified a subset of nine proteins that can differentiate MCs from NCs better than traditional AD biomarkers (AUC>0.89). Interpretation Our findings comprehensively described early proteomic changes associated with ADAD and captured specific biological processes that happen in the early phases of the disease, fifteen to five years before clinical onset. We identified a small subset of proteins with the potentials to become therapy-monitoring biomarkers of ADAD MCs. Funding Proteomic data generation was supported by NIH: RF1AG044546.
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27
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Wojtas AM, Dammer EB, Guo Q, Ping L, Shantaraman A, Duong DM, Yin L, Fox EJ, Seifar F, Lee EB, Johnson ECB, Lah JJ, Levey AI, Levites Y, Rangaraju S, Golde TE, Seyfried NT. Proteomic Changes in the Human Cerebrovasculature in Alzheimer's Disease and Related Tauopathies Linked to Peripheral Biomarkers in Plasma and Cerebrospinal Fluid. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.10.24301099. [PMID: 38260316 PMCID: PMC10802758 DOI: 10.1101/2024.01.10.24301099] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Dysfunction of the neurovascular unit stands as a significant pathological hallmark of Alzheimer's disease (AD) and age-related neurodegenerative diseases. Nevertheless, detecting vascular changes in the brain within bulk tissues has proven challenging, limiting our ability to characterize proteomic alterations from less abundant cell types. To address this challenge, we conducted quantitative proteomic analyses on both bulk brain tissues and cerebrovascular-enriched fractions from the same individuals, encompassing cognitively unimpaired control, progressive supranuclear palsy (PSP), and AD cases. Protein co-expression network analysis identified modules unique to the cerebrovascular fractions, specifically enriched with pericytes, endothelial cells, and smooth muscle cells. Many of these modules also exhibited significant correlations with amyloid plaques, cerebral amyloid angiopathy (CAA), and/or tau pathology in the brain. Notably, the protein products within AD genetic risk loci were found concentrated within modules unique to the vascular fractions, consistent with a role of cerebrovascular deficits in the etiology of AD. To prioritize peripheral AD biomarkers associated with vascular dysfunction, we assessed the overlap between differentially abundant proteins in AD cerebrospinal fluid (CSF) and plasma with a vascular-enriched network modules in the brain. This analysis highlighted matrisome proteins, SMOC1 and SMOC2, as being increased in CSF, plasma, and brain. Immunohistochemical analysis revealed SMOC1 deposition in both parenchymal plaques and CAA in the AD brain, whereas SMOC2 was predominantly localized to CAA. Collectively, these findings significantly enhance our understanding of the involvement of cerebrovascular abnormalities in AD, shedding light on potential biomarkers and molecular pathways associated with CAA and vascular dysfunction in neurodegenerative diseases.
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Affiliation(s)
- Aleksandra M. Wojtas
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - Eric B. Dammer
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - Qi Guo
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - Lingyan Ping
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - Ananth Shantaraman
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - Duc M. Duong
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - Luming Yin
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - Edward J. Fox
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
- Department of Pharmacology and Chemical Biology, Emory University School of Medicine, Atlanta, GA, USA
| | - Fatemeh Seifar
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
- Department of Pharmacology and Chemical Biology, Emory University School of Medicine, Atlanta, GA, USA
| | - Edward B. Lee
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, PA, USA
| | - Erik C. B. Johnson
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - James J. Lah
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - Allan I. Levey
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - Yona Levites
- Department of Pharmacology and Chemical Biology, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - Srikant Rangaraju
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - Todd E. Golde
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Department of Pharmacology and Chemical Biology, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
| | - Nicholas T. Seyfried
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Center for Neurodegenerative Disease, Emory University School of Medicine, Atlanta, GA, USA
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Gudmundsdottir V, Frick E, Emilsson V, Jonmundsson T, Steindorsdottir A, Johnson ECB, Puerta R, Dammer E, Shantaraman A, Cano A, Boada M, Valero S, Garcia-Gonzalez P, Gudmundsson E, Gudjonsson A, Pitts R, Qiu X, Finkel N, Loureiro J, Orth A, Seyfried N, Levey A, Ruiz A, Aspelund T, Jennings L, Launer L, Gudnason V. Serum proteomics reveals APOE dependent and independent protein signatures in Alzheimer's disease. RESEARCH SQUARE 2024:rs.3.rs-3706206. [PMID: 38260284 PMCID: PMC10802738 DOI: 10.21203/rs.3.rs-3706206/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: 01/24/2024]
Abstract
The current demand for early intervention, prevention, and treatment of late onset Alzheimer's disease (LOAD) warrants deeper understanding of the underlying molecular processes which could contribute to biomarker and drug target discovery. Utilizing high-throughput proteomic measurements in serum from a prospective population-based cohort of older adults (n = 5,294), we identified 303 unique proteins associated with incident LOAD (median follow-up 12.8 years). Over 40% of these proteins were associated with LOAD independently of APOE-ε4 carrier status. These proteins were implicated in neuronal processes and overlapped with protein signatures of LOAD in brain and cerebrospinal fluid. We found 17 proteins which LOAD-association was strongly dependent on APOE-ε4 carrier status. Most of them showed consistent associations with LOAD in cerebrospinal fluid and a third had brain-specific gene expression. Remarkably, four proteins in this group (TBCA, ARL2, S100A13 and IRF6) were downregulated by APOE-ε4 yet upregulated as a consequence of LOAD as determined in a bi-directional Mendelian randomization analysis, reflecting a potential response to the disease onset. Accordingly, the direct association of these proteins to LOAD was reversed upon APOE-ε4 genotype adjustment, a finding which we replicate in an external cohort (n = 719). Our findings provide an insight into the dysregulated pathways that may lead to the development and early detection of LOAD, including those both independent and dependent on APOE-ε4. Importantly, many of the LOAD-associated proteins we find in the circulation have been found to be expressed - and have a direct link with AD - in brain tissue. Thus, the proteins identified here, and their upstream modulating pathways, provide a new source of circulating biomarker and therapeutic target candidates for LOAD.
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Affiliation(s)
| | | | | | | | | | | | | | | | | | | | - Merce Boada
- Research Center and Memory Clinic of Fundació ACE, Institut Català de Neurociències Aplicades-UIC, Barcelona
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Lenore Launer
- National Institute on Aging, National Institutes of Health
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Cartas-Cejudo P, Cortés A, Lachén-Montes M, Anaya-Cubero E, Peral E, Ausín K, Díaz-Peña R, Fernández-Irigoyen J, Santamaría E. Mapping the human brain proteome: opportunities, challenges, and clinical potential. Expert Rev Proteomics 2024; 21:55-63. [PMID: 38299555 DOI: 10.1080/14789450.2024.2313073] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 01/24/2024] [Indexed: 02/02/2024]
Abstract
INTRODUCTION Due to the segmented functions and complexity of the human brain, the characterization of molecular profiles within specific areas such as brain structures and biofluids is essential to unveil the molecular basis for structure specialization as well as the molecular imbalance associated with neurodegenerative and psychiatric diseases. AREAS COVERED Much of our knowledge about brain functionality derives from neurophysiological, anatomical, and transcriptomic approaches. More recently, laser capture and imaging proteomics, technological and computational developments in LC-MS/MS, as well as antibody/aptamer-based platforms have allowed the generation of novel cellular, spatial, and posttranslational dimensions as well as innovative facets in biomarker validation and druggable target identification. EXPERT OPINION Proteomics is a powerful toolbox to functionally characterize, quantify, and localize the extensive protein catalog of the human brain across physiological and pathological states. Brain function depends on multi-dimensional protein homeostasis, and its elucidation will help us to characterize biological pathways that are essential to properly maintain cognitive functions. In addition, comprehensive human brain pathological proteomes may be the basis in computational drug-repositioning methods as a strategy for unveiling potential new therapies in neurodegenerative and psychiatric disorders.
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Affiliation(s)
- Paz Cartas-Cejudo
- Clinical Neuroproteomics Unit, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Adriana Cortés
- Clinical Neuroproteomics Unit, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Mercedes Lachén-Montes
- Clinical Neuroproteomics Unit, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Elena Anaya-Cubero
- Clinical Neuroproteomics Unit, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Erika Peral
- Proteomics Platform, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Karina Ausín
- Proteomics Platform, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Ramón Díaz-Peña
- Proteomics Platform, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Joaquín Fernández-Irigoyen
- Proteomics Platform, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
| | - Enrique Santamaría
- Clinical Neuroproteomics Unit, Navarrabiomed, Hospital Universitario de Navarra (HUN), Universidad Pública de Navarra (UPNA), Instituto de Investigación Sanitaria de Navarra (IdiSNA), Pamplona, Spain
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30
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Tijms BM, Vromen EM, Mjaavatten O, Holstege H, Reus LM, van der Lee S, Wesenhagen KEJ, Lorenzini L, Vermunt L, Venkatraghavan V, Tesi N, Tomassen J, den Braber A, Goossens J, Vanmechelen E, Barkhof F, Pijnenburg YAL, van der Flier WM, Teunissen CE, Berven FS, Visser PJ. Cerebrospinal fluid proteomics in patients with Alzheimer's disease reveals five molecular subtypes with distinct genetic risk profiles. NATURE AGING 2024; 4:33-47. [PMID: 38195725 PMCID: PMC10798889 DOI: 10.1038/s43587-023-00550-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 11/29/2023] [Indexed: 01/11/2024]
Abstract
Alzheimer's disease (AD) is heterogenous at the molecular level. Understanding this heterogeneity is critical for AD drug development. Here we define AD molecular subtypes using mass spectrometry proteomics in cerebrospinal fluid, based on 1,058 proteins, with different levels in individuals with AD (n = 419) compared to controls (n = 187). These AD subtypes had alterations in protein levels that were associated with distinct molecular processes: subtype 1 was characterized by proteins related to neuronal hyperplasticity; subtype 2 by innate immune activation; subtype 3 by RNA dysregulation; subtype 4 by choroid plexus dysfunction; and subtype 5 by blood-brain barrier impairment. Each subtype was related to specific AD genetic risk variants, for example, subtype 1 was enriched with TREM2 R47H. Subtypes also differed in clinical outcomes, survival times and anatomical patterns of brain atrophy. These results indicate molecular heterogeneity in AD and highlight the need for personalized medicine.
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Affiliation(s)
- Betty M Tijms
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands.
| | - Ellen M Vromen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Olav Mjaavatten
- Proteomics Unit at the University of Bergen, Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Henne Holstege
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Lianne M Reus
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sven van der Lee
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Kirsten E J Wesenhagen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Luigi Lorenzini
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neuroimaging, Amsterdam, the Netherlands
| | - Lisa Vermunt
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Neurochemistry Laboratory, Department of Laboratory Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Vikram Venkatraghavan
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Niccoló Tesi
- Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, Delft, the Netherlands
| | - Jori Tomassen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Anouk den Braber
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | | | | | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Yolande A L Pijnenburg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Epidemiology & Data Science, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Charlotte E Teunissen
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Neurochemistry Laboratory, Department of Laboratory Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Frode S Berven
- Proteomics Unit at the University of Bergen, Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
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31
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Levites Y, Dammer EB, Ran Y, Tsering W, Duong D, Abreha M, Gadhavi J, Lolo K, Trejo-Lopez J, Phillips JL, Iturbe A, Erqiuzi A, Moore BD, Ryu D, Natu A, Dillon KD, Torrellas J, Moran C, Ladd TB, Afroz KF, Islam T, Jagirdar J, Funk CC, Robinson M, Borchelt DR, Ertekin-Taner N, Kelly JW, Heppner FL, Johnson EC, McFarland K, Levey AL, Prokop S, Seyfried NT, Golde TE. Aβ Amyloid Scaffolds the Accumulation of Matrisome and Additional Proteins in Alzheimer's Disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.29.568318. [PMID: 38076912 PMCID: PMC10705437 DOI: 10.1101/2023.11.29.568318] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/14/2024]
Abstract
We report a highly significant correlation in brain proteome changes between Alzheimers disease (AD) and CRND8 APP695NL/F transgenic mice. However, integrating protein changes observed in the CRND8 mice with co-expression networks derived from human AD, reveals both conserved and divergent module changes. For the most highly conserved module (M42, matrisome) we find many proteins accumulate in plaques, cerebrovascular amyloid (CAA), dystrophic processes, or a combination thereof. Overexpression of two M42 proteins, midkine (Mdk) and pleiotrophin (PTN), in CRND8 mice brains leads to increased accumulation of A β ; in plaques and in CAA; further, recombinant MDK and PTN enhance A β ; aggregation into amyloid. Multiple M42 proteins, annotated as heparan sulfate binding proteins, bind to fibrillar A β 42 and a non-human amyloid fibril in vitro. Supporting this binding data, MDK and PTN co-accumulate with transthyretin (TTR) amyloid in the heart and islet amyloid polypeptide (IAPP) amyloid in the pancreas. Our findings establish several critical insights. Proteomic changes in modules observed in human AD brains define an A β ; amyloid responsome that is well conserved from mouse model to human. Further, distinct amyloid structures may serve as scaffolds, facilitating the co-accumulation of proteins with signaling functions. We hypothesize that this co-accumulation may contribute to downstream pathological sequalae. Overall, this contextualized understanding of proteomic changes and their interplay with amyloid deposition provides valuable insights into the complexity of AD pathogenesis and potential biomarkers and therapeutic targets.
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32
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Dey KK, Yarbro JM, Liu D, Han X, Wang Z, Jiao Y, Wu Z, Yang S, Lee D, Dasgupta A, Yuan ZF, Wang X, Zhu L, Peng J. Identifying Sex-Specific Serum Patterns of Alzheimer's Mice through Deep TMT Profiling and a Concentration-Dependent Concatenation Strategy. J Proteome Res 2023; 22:3843-3853. [PMID: 37910662 PMCID: PMC10872962 DOI: 10.1021/acs.jproteome.3c00496] [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: 11/03/2023]
Abstract
Alzheimer's disease (AD) is the most prevalent form of dementia, disproportionately affecting women in disease prevalence and progression. Comprehensive analysis of the serum proteome in a common AD mouse model offers potential in identifying possible AD pathology- and gender-associated biomarkers. Here, we introduce a multiplexed, nondepleted mouse serum proteome profiling via tandem mass-tag (TMTpro) labeling. The labeled sample was separated into 475 fractions using basic reversed-phase liquid chromatography (RPLC), which were categorized into low-, medium-, and high-concentration fractions for concatenation. This concentration-dependent concatenation strategy resulted in 128 fractions for acidic RPLC-tandem mass spectrometry (MS/MS) analysis, collecting ∼5 million MS/MS scans and identifying 3972 unique proteins (3413 genes) that cover a dynamic range spanning at least 6 orders of magnitude. The differential expression analysis between wild type and the commonly used AD model (5xFAD) mice exhibited minimal significant protein alterations. However, we detected 60 statistically significant (FDR < 0.05), sex-specific proteins, including complement components, serpins, carboxylesterases, major urinary proteins, cysteine-rich secretory protein 1, pregnancy-associated murine protein 1, prolactin, amyloid P component, epidermal growth factor receptor, fibrinogen-like protein 1, and hepcidin. The results suggest that our platform possesses the sensitivity and reproducibility required to detect sex-specific differentially expressed proteins in mouse serum samples.
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Affiliation(s)
- Kaushik Kumar Dey
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - Jay M. Yarbro
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
- Integrated Biomedical Sciences Program, University of Tennessee Health Science Center, Memphis, Tennessee, TN 38163, USA
| | - Danting Liu
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - Xian Han
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - Zhen Wang
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - Yun Jiao
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - Zhiping Wu
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - Shu Yang
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - DongGeun Lee
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - Abhijit Dasgupta
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - Zuo-Fei Yuan
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
- Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - Xusheng Wang
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
- Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - Liqin Zhu
- Department of Pharmacy and Pharmaceutical Sciences, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
| | - Junmin Peng
- Departments of Structural Biology and Developmental Neurobiology, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
- Center for Proteomics and Metabolomics, St. Jude Children’s Research Hospital, 262 Danny Thomas Place, Memphis, TN 38105, USA
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33
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Chen X, Xie L, Sheehy R, Xiong Y, Muneer A, Wrobel J, Park KS, Liu J, Velez J, Luo Y, Li YD, Quintanilla L, Li Y, Xu C, Wen Z, Song J, Jin J, Deshmukh M. Novel brain-penetrant inhibitor of G9a methylase blocks Alzheimer's disease proteopathology for precision medication. RESEARCH SQUARE 2023:rs.3.rs-2743792. [PMID: 38045363 PMCID: PMC10690335 DOI: 10.21203/rs.3.rs-2743792/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
Current amyloid beta-targeting approaches for Alzheimer's disease (AD) therapeutics only slow cognitive decline for small numbers of patients. This limited efficacy exists because AD is a multifactorial disease whose pathological mechanism(s) and diagnostic biomarkers are largely unknown. Here we report a new mechanism of AD pathogenesis in which the histone methyltransferase G9a noncanonically regulates translation of a hippocampal proteome that defines the proteopathic nature of AD. Accordingly, we developed a novel brain-penetrant inhibitor of G9a, MS1262, across the blood-brain barrier to block this G9a-regulated, proteopathologic mechanism. Intermittent MS1262 treatment of multiple AD mouse models consistently restored both cognitive and noncognitive functions to healthy levels. Comparison of proteomic/phosphoproteomic analyses of MS1262-treated AD mice with human AD patient data identified multiple pathological brain pathways that elaborate amyloid beta and neurofibrillary tangles as well as blood coagulation, from which biomarkers of early stage of AD including SMOC1 were found to be affected by MS1262 treatment. Notably, these results indicated that MS1262 treatment may reduce or avoid the risk of blood clot burst for brain bleeding or a stroke. This mouse-to-human conservation of G9a-translated AD proteopathology suggests that the global, multifaceted effects of MS1262 in mice could extend to relieve all symptoms of AD patients with minimum side effect. In addition, our mechanistically derived biomarkers can be used for stage-specific AD diagnosis and companion diagnosis of individualized drug effects.
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34
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Frick EA, Emilsson V, Jonmundsson T, Steindorsdottir AE, Johnson ECB, Puerta R, Dammer EB, Shantaraman A, Cano A, Boada M, Valero S, García-González P, Gudmundsson EF, Gudjonsson A, Loureiro JJ, Orth AP, Seyfried NT, Levey AI, Ruiz A, Aspelund T, Jennings LL, Launer LJ, Gudmundsdottir V, Gudnason V. Serum proteomics reveals APOE dependent and independent protein signatures in Alzheimer's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.11.08.23298251. [PMID: 37986771 PMCID: PMC10659486 DOI: 10.1101/2023.11.08.23298251] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
The current demand for early intervention, prevention, and treatment of late onset Alzheimer's disease (LOAD) warrants deeper understanding of the underlying molecular processes which could contribute to biomarker and drug target discovery. Utilizing high-throughput proteomic measurements in serum from a prospective population-based cohort of older adults (n=5,294), we identified 303 unique proteins associated with incident LOAD (median follow-up 12.8 years). Over 40% of these proteins were associated with LOAD independently of APOE-ε4 carrier status. These proteins were implicated in neuronal processes and overlapped with protein signatures of LOAD in brain and cerebrospinal fluid. We found 17 proteins which LOAD-association was strongly dependent on APOE-ε4 carrier status. Most of them showed consistent associations with LOAD in cerebrospinal fluid and a third had brain-specific gene expression. Remarkably, four proteins in this group (TBCA, ARL2, S100A13 and IRF6) were downregulated by APOE-ε4 yet upregulated as a consequence of LOAD as determined in a bi-directional Mendelian randomization analysis, reflecting a potential response to the disease onset. Accordingly, the direct association of these proteins to LOAD was reversed upon APOE-ε4 genotype adjustment, a finding which we replicate in an external cohort (n=719). Our findings provide an insight into the dysregulated pathways that may lead to the development and early detection of LOAD, including those both independent and dependent on APOE-ε4. Importantly, many of the LOAD-associated proteins we find in the circulation have been found to be expressed - and have a direct link with AD - in brain tissue. Thus, the proteins identified here, and their upstream modulating pathways, provide a new source of circulating biomarker and therapeutic target candidates for LOAD.
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Affiliation(s)
| | - Valur Emilsson
- Icelandic Heart Association, Kopavogur, 200, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland
| | | | | | - Erik C B Johnson
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, 30329, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, 30329, GA, USA
| | - Raquel Puerta
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, 08028, Spain, Barcelona
| | - Eric B Dammer
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, 30329, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, 30329, GA, USA
| | - Anantharaman Shantaraman
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, 30329, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, 30329, GA, USA
| | - Amanda Cano
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, 08028, Spain, Barcelona
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, 28029, Spain
| | - Mercè Boada
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, 08028, Spain, Barcelona
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, 28029, Spain
| | - Sergi Valero
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, 08028, Spain, Barcelona
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, 28029, Spain
| | - Pablo García-González
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, 08028, Spain, Barcelona
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, 28029, Spain
| | | | | | | | | | - Nicholas T Seyfried
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, 30329, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, 30329, GA, USA
| | - Allan I Levey
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, 30329, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, 30329, GA, USA
| | - Agustin Ruiz
- Research Center and Memory Clinic. Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, 08028, Spain, Barcelona
- CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, 28029, Spain
| | - Thor Aspelund
- Icelandic Heart Association, Kopavogur, 200, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland
| | | | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research Program, National Institute on Aging, Bethesda, 20892, MD, USA
| | - Valborg Gudmundsdottir
- Icelandic Heart Association, Kopavogur, 200, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland
| | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, 200, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, 101, Iceland
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35
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van der Ende EL, In ‘t Veld SGJG, Hanskamp I, van der Lee S, Dijkstra JIR, Hok-A-Hin YS, Blujdea ER, van Swieten JC, Irwin DJ, Chen-Plotkin A, Hu WT, Lemstra AW, Pijnenburg YAL, van der Flier WM, del Campo M, Teunissen CE, Vermunt L. CSF proteomics in autosomal dominant Alzheimer's disease highlights parallels with sporadic disease. Brain 2023; 146:4495-4507. [PMID: 37348871 PMCID: PMC10629764 DOI: 10.1093/brain/awad213] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2023] [Revised: 05/10/2023] [Accepted: 05/11/2023] [Indexed: 06/24/2023] Open
Abstract
Autosomal dominant Alzheimer's disease (ADAD) offers a unique opportunity to study pathophysiological changes in a relatively young population with few comorbidities. A comprehensive investigation of proteome changes occurring in ADAD could provide valuable insights into AD-related biological mechanisms and uncover novel biomarkers and therapeutic targets. Furthermore, ADAD might serve as a model for sporadic AD, but in-depth proteome comparisons are lacking. We aimed to identify dysregulated CSF proteins in ADAD and determine the degree of overlap with sporadic AD. We measured 1472 proteins in CSF of PSEN1 or APP mutation carriers (n = 22) and age- and sex-matched controls (n = 20) from the Amsterdam Dementia Cohort using proximity extension-based immunoassays (PEA). We compared protein abundance between groups with two-sided t-tests and identified enriched biological pathways. Using the same protein panels in paired plasma samples, we investigated correlations between CSF proteins and their plasma counterparts. Finally, we compared our results with recently published PEA data from an international cohort of sporadic AD (n = 230) and non-AD dementias (n = 301). All statistical analyses were false discovery rate-corrected. We detected 66 differentially abundant CSF proteins (65 increased, 1 decreased) in ADAD compared to controls (q < 0.05). The most strongly upregulated proteins (fold change >1.8) were related to immunity (CHIT1, ITGB2, SMOC2), cytoskeletal structure (MAPT, NEFL) and tissue remodelling (TMSB10, MMP-10). Significant CSF-plasma correlations were found for the upregulated proteins SMOC2 and LILR1B. Of the 66 differentially expressed proteins, 36 had been measured previously in the sporadic dementias cohort, 34 of which (94%) were also significantly upregulated in sporadic AD, with a strong correlation between the fold changes of these proteins in both cohorts (rs = 0.730, P < 0.001). Twenty-nine of the 36 proteins (81%) were also upregulated among non-AD patients with suspected AD co-pathology. This CSF proteomics study demonstrates substantial biochemical similarities between ADAD and sporadic AD, suggesting involvement of the same biological processes. Besides known AD-related proteins, we identified several relatively novel proteins, such as TMSB10, MMP-10 and SMOC2, which have potential as novel biomarkers. With shared pathophysiological CSF changes, ADAD study findings might be translatable to sporadic AD, which could greatly expedite therapy development.
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Affiliation(s)
- Emma L van der Ende
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Sjors G J G In ‘t Veld
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Iris Hanskamp
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Sven van der Lee
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
- Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Janna I R Dijkstra
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
- Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Yanaika S Hok-A-Hin
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Elena R Blujdea
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - John C van Swieten
- Alzheimer Center and Department of Neurology, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
| | - David J Irwin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Alice Chen-Plotkin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - William T Hu
- Department of Neurology, Emory University School of Medicine, Atlanta, GA 30307, USA
| | - Afina W Lemstra
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Yolande A L Pijnenburg
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
- Department of Epidemiology and Data Science, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Marta del Campo
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
- Departamento de Ciencias Farmacéuticas y de la Salud, Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, 28003 Madrid, Spain
- Barcelonabeta Brain Research Center (BBRC), Pasqual Maragall Foundation, 08005 Barcelona, Spain
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
| | - Lisa Vermunt
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, 1081 HV Amsterdam, The Netherlands
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36
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Cordon J, Duggan MR, Gomez GT, Pucha K, Peng Z, Dark HE, Davatzikos C, Erus G, Lewis A, Moghekar A, Candia J, Ferrucci L, Kapogiannis D, Walker KA. Identification of Clinically Relevant Brain Endothelial Cell Biomarkers in Plasma. Stroke 2023; 54:2853-2863. [PMID: 37814955 PMCID: PMC10608795 DOI: 10.1161/strokeaha.123.043908] [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: 05/15/2023] [Accepted: 09/12/2023] [Indexed: 10/11/2023]
Abstract
BACKGROUND Proteins expressed by brain endothelial cells (BECs), the primary cell type of the blood-brain barrier, may serve as sensitive plasma biomarkers for neurological and neurovascular conditions, including cerebral small vessel disease. METHODS Using data from the BLSA (Baltimore Longitudinal Study of Aging; n=886; 2009-2020), BEC-enriched proteins were identified among 7268 plasma proteins (measured with SomaScanv4.1) using an automated annotation algorithm that filtered endothelial cell transcripts followed by cross-referencing with BEC-specific transcripts reported in single-cell RNA-sequencing studies. To identify BEC-enriched proteins in plasma most relevant to the maintenance of neurological and neurovascular health, we selected proteins significantly associated with 3T magnetic resonance imaging-defined white matter lesion volumes. We then examined how these candidate BEC biomarkers related to white matter lesion volumes, cerebral microhemorrhages, and lacunar infarcts in the ARIC study (Atherosclerosis Risk in Communities; US multisite; 1990-2017). Finally, we determined whether these candidate BEC biomarkers, when measured during midlife, were related to dementia risk over a 25-year follow-up period. RESULTS Of the 28 proteins identified as BEC-enriched, 4 were significantly associated with white matter lesion volumes (CDH5 [cadherin 5], CD93 [cluster of differentiation 93], ICAM2 [intracellular adhesion molecule 2], GP1BB [glycoprotein 1b platelet subunit beta]), while another approached significance (RSPO3 [R-Spondin 3]). A composite score based on 3 of these BEC proteins accounted for 11% of variation in white matter lesion volumes in BLSA participants. We replicated the associations between the BEC composite score, CDH5, and RSPO3 with white matter lesion volumes in ARIC, and further demonstrated that the BEC composite score and RSPO3 were associated with the presence of ≥1 cerebral microhemorrhages. We also showed that the BEC composite score, CDH5, and RSPO3 were associated with 25-year dementia risk. CONCLUSIONS In addition to identifying BEC proteins in plasma that relate to cerebral small vessel disease and dementia risk, we developed a composite score of plasma BEC proteins that may be used to estimate blood-brain barrier integrity and risk for adverse neurovascular outcomes.
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Affiliation(s)
- Jenifer Cordon
- Multimodal Imaging of Neurodegenerative Disease (MIND) Unit, NIA
| | | | | | | | - Zhongsheng Peng
- Multimodal Imaging of Neurodegenerative Disease (MIND) Unit, NIA
| | - Heather E. Dark
- Multimodal Imaging of Neurodegenerative Disease (MIND) Unit, NIA
| | | | | | | | | | | | | | | | - Keenan A. Walker
- Multimodal Imaging of Neurodegenerative Disease (MIND) Unit, NIA
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37
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Dammer EB, Shantaraman A, Ping L, Duong DM, Gerasimov ES, Ravindran SP, Gudmundsdottir V, Frick EA, Gomez GT, Walker KA, Emilsson V, Jennings LL, Gudnason V, Western D, Cruchaga C, Lah JJ, Wingo TS, Wingo AP, Seyfried NT, Levey AI, Johnson EC. Proteomic Network Analysis of Alzheimer's Disease Cerebrospinal Fluid Reveals Alterations Associated with APOE ε4 Genotype and Atomoxetine Treatment. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.29.23297651. [PMID: 37961720 PMCID: PMC10635242 DOI: 10.1101/2023.10.29.23297651] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Alzheimer's disease (AD) is currently defined at the research level by the aggregation of amyloid-β (Aβ) and tau proteins in brain. While biofluid biomarkers are available to measure Aβ and tau pathology, few biomarkers are available to measure the complex pathophysiology that is associated with these two cardinal neuropathologies. Here we describe the proteomic landscape of cerebrospinal fluid (CSF) changes associated with Aβ and tau pathology in 300 individuals as assessed by two different proteomic technologies-tandem mass tag (TMT) mass spectrometry and SomaScan. Harmonization and integration of both data types allowed for generation of a robust protein co-expression network consisting of 34 modules derived from 5242 protein measurements, including disease-relevant modules associated with autophagy, ubiquitination, endocytosis, and glycolysis. Three modules strongly associated with the apolipoprotein E ε4 (APOE ε4) AD risk genotype mapped to oxidant detoxification, mitogen associated protein kinase (MAPK) signaling, neddylation, and mitochondrial biology, and overlapped with a previously described lipoprotein module in serum. Neddylation and oxidant detoxification/MAPK signaling modules had a negative association with APOE ε4 whereas the mitochondrion module had a positive association with APOE ε4. The directions of association were consistent between CSF and blood in two independent longitudinal cohorts, and altered levels of all three modules in blood were associated with dementia over 20 years prior to diagnosis. Dual-proteomic platform analysis of CSF samples from an AD phase 2 clinical trial of atomoxetine (ATX) demonstrated that abnormal elevations in the glycolysis CSF module-the network module most strongly correlated to cognitive function-were reduced by ATX treatment. Individuals who had more severe glycolytic changes at baseline responded better to ATX. Clustering of individuals based on their CSF proteomic network profiles revealed ten groups that did not cleanly stratify by Aβ and tau status, underscoring the heterogeneity of pathological changes not fully reflected by Aβ and tau. AD biofluid proteomics holds promise for the development of biomarkers that reflect diverse pathologies for use in clinical trials and precision medicine.
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Affiliation(s)
- Eric B. Dammer
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Anantharaman Shantaraman
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Lingyan Ping
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Duc M. Duong
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | | | | | - Valborg Gudmundsdottir
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | - Gabriela T. Gomez
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Keenan A. Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
| | - Valur Emilsson
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | | | - Vilmundur Gudnason
- Icelandic Heart Association, Kopavogur, Iceland
- Faculty of Medicine, University of Iceland, Reykjavik, Iceland
| | - Daniel Western
- Department of Psychiatry, Washington University, St. Louis, MO, USA
- NeuroGenomics and Informatics, Washington University, St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University, St. Louis, MO, USA
- NeuroGenomics and Informatics, Washington University, St. Louis, MO, USA
| | - James J. Lah
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Thomas S. Wingo
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Department of Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Aliza P. Wingo
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Psychiatry, Emory University School of Medicine, Atlanta, GA, USA
- Division of Mental Health, Atlanta VA Medical Center, GA, USA
| | - Nicholas T. Seyfried
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Allan I. Levey
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Erik C.B. Johnson
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
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38
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Xie L, Sheehy RN, Xiong Y, Muneer A, Wrobel JA, Park KS, Velez J, Liu J, Luo YJ, Li YD, Quintanilla L, Li Y, Xu C, Deshmukh M, Wen Z, Jin J, Song J, Chen X. Novel brain-penetrant inhibitor of G9a methylase blocks Alzheimer's disease proteopathology for precision medication. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.10.25.23297491. [PMID: 37961307 PMCID: PMC10635198 DOI: 10.1101/2023.10.25.23297491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Current amyloid beta-targeting approaches for Alzheimer's disease (AD) therapeutics only slow cognitive decline for small numbers of patients. This limited efficacy exists because AD is a multifactorial disease whose pathological mechanism(s) and diagnostic biomarkers are largely unknown. Here we report a new mechanism of AD pathogenesis in which the histone methyltransferase G9a noncanonically regulates translation of a hippocampal proteome that defines the proteopathic nature of AD. Accordingly, we developed a novel brain-penetrant inhibitor of G9a, MS1262, across the blood-brain barrier to block this G9a-regulated, proteopathologic mechanism. Intermittent MS1262 treatment of multiple AD mouse models consistently restored both cognitive and noncognitive functions to healthy levels. Comparison of proteomic/phosphoproteomic analyses of MS1262-treated AD mice with human AD patient data identified multiple pathological brain pathways that elaborate amyloid beta and neurofibrillary tangles as well as blood coagulation, from which biomarkers of early stage of AD including SMOC1 were found to be affected by MS1262 treatment. Notably, these results indicated that MS1262 treatment may reduce or avoid the risk of blood clot burst for brain bleeding or a stroke. This mouse-to-human conservation of G9a-translated AD proteopathology suggests that the global, multifaceted effects of MS1262 in mice could extend to relieve all symptoms of AD patients with minimum side effect. In addition, our mechanistically derived biomarkers can be used for stage-specific AD diagnosis and companion diagnosis of individualized drug effects. One-Sentence Summary A brain-penetrant inhibitor of G9a methylase blocks G9a translational mechanism to reverse Alzheimer's disease related proteome for effective therapy.
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39
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Ren X, Wu L, Zhang L, Liu Y, Wang G, Lu H. Discovery of age-related early-stage glycated proteins based on deep quantitative serum glycated proteome analysis. Acta Biochim Biophys Sin (Shanghai) 2023; 55:1659-1667. [PMID: 37654074 PMCID: PMC10577472 DOI: 10.3724/abbs.2023222] [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: 07/22/2023] [Accepted: 08/15/2023] [Indexed: 09/02/2023] Open
Abstract
Aging is a pressing global health issue that is linked to various diseases, such as diabetes and Alzheimer's disease. It is well known that glycation plays a pathological role in the aging process and age-related diseases. Thus, it is of great significance to discover protein glycation at an early stage for monitoring and intervention in the aging process. However, the endogenous age-related early-stage glycated proteome remains insufficiently profiled. To address this research gap, our study focuses on assessing glycated proteomics profiles in the serum of mice. We employ a robust and quantitative strategy previously developed by our team, to analyze endogenous glycated proteome in serum samples of 4 age groups of mice (10 weeks, 16 weeks, 48 weeks and 80 weeks). In total, 2959 endogenous glycated peptides corresponding to 296 serum proteins are identified from 48 runs of serum samples from 16 mice across the four age groups. By comparing these glycated peptides between adjacent age groups, we discover 49 glycated peptides from 35 proteins that show significant upregulation between the 48-week and 80-week age groups. Furthermore, we identify 10 glycated proteins (or protein groups) that are significantly upregulated only between the 48-week and 80-week age groups, including lecithin-cholesterol acyltransferase (LCAT) and apolipoprotein A-II (Apo A-II). These novel findings provide unique signatures for understanding the aging process and age-related diseases. By shedding light on the early-stage glycated proteome, our study contributes valuable insights that may have implications for future interventions and therapeutic approaches.
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Affiliation(s)
- Xinyue Ren
- Shanghai Medical CollegeFudan UniversityShanghai200032China
| | - Linlin Wu
- Shanghai Medical CollegeFudan UniversityShanghai200032China
- Institutes of Biomedical Sciences and Department of Chemistry and NHC Key Laboratory of Glycoconjugates ResearchFudan UniversityShanghai200032China
| | - Lei Zhang
- Shanghai Medical CollegeFudan UniversityShanghai200032China
- Institutes of Biomedical Sciences and Department of Chemistry and NHC Key Laboratory of Glycoconjugates ResearchFudan UniversityShanghai200032China
| | - Yang Liu
- Shanghai Medical CollegeFudan UniversityShanghai200032China
- Institutes of Biomedical Sciences and Department of Chemistry and NHC Key Laboratory of Glycoconjugates ResearchFudan UniversityShanghai200032China
| | - Guoli Wang
- Shanghai Medical CollegeFudan UniversityShanghai200032China
- Institutes of Biomedical Sciences and Department of Chemistry and NHC Key Laboratory of Glycoconjugates ResearchFudan UniversityShanghai200032China
| | - Haojie Lu
- Shanghai Medical CollegeFudan UniversityShanghai200032China
- Institutes of Biomedical Sciences and Department of Chemistry and NHC Key Laboratory of Glycoconjugates ResearchFudan UniversityShanghai200032China
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40
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Beaudin M, Kamali T, Tang W, Hagerman KA, Dunaway Young S, Ghiglieri L, Parker DM, Lehallier B, Tesi-Rocha C, Sampson JB, Duong T, Day JW. Cerebrospinal Fluid Proteomic Changes after Nusinersen in Patients with Spinal Muscular Atrophy. J Clin Med 2023; 12:6696. [PMID: 37892834 PMCID: PMC10607664 DOI: 10.3390/jcm12206696] [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: 09/01/2023] [Revised: 10/13/2023] [Accepted: 10/18/2023] [Indexed: 10/29/2023] Open
Abstract
Disease-modifying treatments have transformed the natural history of spinal muscular atrophy (SMA), but the cellular pathways altered by SMN restoration remain undefined and biomarkers cannot yet precisely predict treatment response. We performed an exploratory cerebrospinal fluid (CSF) proteomic study in a diverse sample of SMA patients treated with nusinersen to elucidate therapeutic pathways and identify predictors of motor improvement. Proteomic analyses were performed on CSF samples collected before treatment (T0) and at 6 months (T6) using an Olink panel to quantify 1113 peptides. A supervised machine learning approach was used to identify proteins that discriminated patients who improved functionally from those who did not after 2 years of treatment. A total of 49 SMA patients were included (10 type 1, 18 type 2, and 21 type 3), ranging in age from 3 months to 65 years. Most proteins showed a decrease in CSF concentration at T6. The machine learning algorithm identified ARSB, ENTPD2, NEFL, and IFI30 as the proteins most predictive of improvement. The machine learning model was able to predict motor improvement at 2 years with 79.6% accuracy. The results highlight the potential application of CSF biomarkers to predict motor improvement following SMA treatment. Validation in larger datasets is needed.
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Affiliation(s)
- Marie Beaudin
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA 94304, USA (T.K.); (W.T.); (K.A.H.); (B.L.); (C.T.-R.)
- Department of Neurology, Stanford Health Care, Stanford, CA 94304, USA
| | - Tahereh Kamali
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA 94304, USA (T.K.); (W.T.); (K.A.H.); (B.L.); (C.T.-R.)
| | - Whitney Tang
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA 94304, USA (T.K.); (W.T.); (K.A.H.); (B.L.); (C.T.-R.)
| | - Katharine A. Hagerman
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA 94304, USA (T.K.); (W.T.); (K.A.H.); (B.L.); (C.T.-R.)
| | - Sally Dunaway Young
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA 94304, USA (T.K.); (W.T.); (K.A.H.); (B.L.); (C.T.-R.)
- Department of Neurology, Stanford Health Care, Stanford, CA 94304, USA
| | - Lisa Ghiglieri
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA 94304, USA (T.K.); (W.T.); (K.A.H.); (B.L.); (C.T.-R.)
| | - Dana M. Parker
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA 94304, USA (T.K.); (W.T.); (K.A.H.); (B.L.); (C.T.-R.)
| | - Benoit Lehallier
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA 94304, USA (T.K.); (W.T.); (K.A.H.); (B.L.); (C.T.-R.)
| | - Carolina Tesi-Rocha
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA 94304, USA (T.K.); (W.T.); (K.A.H.); (B.L.); (C.T.-R.)
- Department of Neurology, Stanford Health Care, Stanford, CA 94304, USA
| | - Jacinda B. Sampson
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA 94304, USA (T.K.); (W.T.); (K.A.H.); (B.L.); (C.T.-R.)
- Department of Neurology, Stanford Health Care, Stanford, CA 94304, USA
| | - Tina Duong
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA 94304, USA (T.K.); (W.T.); (K.A.H.); (B.L.); (C.T.-R.)
- Department of Neurology, Stanford Health Care, Stanford, CA 94304, USA
| | - John W. Day
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, Stanford, CA 94304, USA (T.K.); (W.T.); (K.A.H.); (B.L.); (C.T.-R.)
- Department of Neurology, Stanford Health Care, Stanford, CA 94304, USA
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41
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Teunissen CE, Kimble L, Bayoumy S, Bolsewig K, Burtscher F, Coppens S, Das S, Gogishvili D, Fernandes Gomes B, Gómez de San José N, Mavrina E, Meda FJ, Mohaupt P, Mravinacová S, Waury K, Wojdała AL, Abeln S, Chiasserini D, Hirtz C, Gaetani L, Vermunt L, Bellomo G, Halbgebauer S, Lehmann S, Månberg A, Nilsson P, Otto M, Vanmechelen E, Verberk IMW, Willemse E, Zetterberg H. Methods to Discover and Validate Biofluid-Based Biomarkers in Neurodegenerative Dementias. Mol Cell Proteomics 2023; 22:100629. [PMID: 37557955 PMCID: PMC10594029 DOI: 10.1016/j.mcpro.2023.100629] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 07/24/2023] [Accepted: 07/31/2023] [Indexed: 08/11/2023] Open
Abstract
Neurodegenerative dementias are progressive diseases that cause neuronal network breakdown in different brain regions often because of accumulation of misfolded proteins in the brain extracellular matrix, such as amyloids or inside neurons or other cell types of the brain. Several diagnostic protein biomarkers in body fluids are being used and implemented, such as for Alzheimer's disease. However, there is still a lack of biomarkers for co-pathologies and other causes of dementia. Such biofluid-based biomarkers enable precision medicine approaches for diagnosis and treatment, allow to learn more about underlying disease processes, and facilitate the development of patient inclusion and evaluation tools in clinical trials. When designing studies to discover novel biofluid-based biomarkers, choice of technology is an important starting point. But there are so many technologies to choose among. To address this, we here review the technologies that are currently available in research settings and, in some cases, in clinical laboratory practice. This presents a form of lexicon on each technology addressing its use in research and clinics, its strengths and limitations, and a future perspective.
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Affiliation(s)
- Charlotte E Teunissen
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands.
| | - Leighann Kimble
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; KIN Center for Digital Innovation, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Sherif Bayoumy
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Katharina Bolsewig
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Felicia Burtscher
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Salomé Coppens
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; National Measurement Laboratory at LGC, Teddington, United Kingdom
| | - Shreyasee Das
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; ADx NeuroSciences, Gent, Belgium
| | - Dea Gogishvili
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Bárbara Fernandes Gomes
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Nerea Gómez de San José
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Neurology, University of Ulm, Ulm, Germany
| | - Ekaterina Mavrina
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; KIN Center for Digital Innovation, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Francisco J Meda
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Pablo Mohaupt
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; LBPC-PPC, IRMB CHU Montpellier, INM INSERM, Université de Montpellier, Montpellier, France
| | - Sára Mravinacová
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
| | - Katharina Waury
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Anna Lidia Wojdała
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Sanne Abeln
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Davide Chiasserini
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Section of Physiology and Biochemistry, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Christophe Hirtz
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; LBPC-PPC, IRMB CHU Montpellier, INM INSERM, Université de Montpellier, Montpellier, France
| | - Lorenzo Gaetani
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Lisa Vermunt
- Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Giovanni Bellomo
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Section of Neurology, Department of Medicine and Surgery, University of Perugia, Perugia, Italy
| | - Steffen Halbgebauer
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Neurology, University of Ulm, Ulm, Germany; German Center for Neurodegenerative Diseases (DZNE e.V.), Ulm, Germany
| | - Sylvain Lehmann
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; LBPC-PPC, IRMB CHU Montpellier, INM INSERM, Université de Montpellier, Montpellier, France
| | - Anna Månberg
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
| | - Peter Nilsson
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Division of Affinity Proteomics, Department of Protein Science, KTH Royal Institute of Technology, SciLifeLab, Stockholm, Sweden
| | - Markus Otto
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Neurology, University of Ulm, Ulm, Germany; Department of Neurology, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Eugeen Vanmechelen
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; ADx NeuroSciences, Gent, Belgium
| | - Inge M W Verberk
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Eline Willemse
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Neurochemistry Lab, Department of Laboratory Medicine, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
| | - Henrik Zetterberg
- MIRIADE Consortium, Multiomics Interdisciplinary Research Integration to Address DEmentia diagnosis, Amsterdam, The Netherlands; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 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
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Dillon ST, Vasunilashorn SM, Otu HH, Ngo L, Fong T, Gu X, Cavallari M, Touroutoglou A, Shafi M, Inouye SK, Xie Z, Marcantonio ER, Libermann TA. Aptamer-Based Proteomics Measuring Preoperative Cerebrospinal Fluid Protein Alterations Associated with Postoperative Delirium. Biomolecules 2023; 13:1395. [PMID: 37759795 PMCID: PMC10526755 DOI: 10.3390/biom13091395] [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: 08/10/2023] [Revised: 09/09/2023] [Accepted: 09/13/2023] [Indexed: 09/29/2023] Open
Abstract
Delirium is a common postoperative complication among older patients with many adverse outcomes. Due to a lack of validated biomarkers, prediction and monitoring of delirium by biological testing is not currently feasible. Circulating proteins in cerebrospinal fluid (CSF) may reflect biological processes causing delirium. Our goal was to discover and investigate candidate protein biomarkers in preoperative CSF that were associated with the development of postoperative delirium in older surgical patients. We employed a nested case-control study design coupled with high multiplex affinity proteomics analysis to measure 1305 proteins in preoperative CSF. Twenty-four matched delirium cases and non-delirium controls were selected from the Healthier Postoperative Recovery (HiPOR) cohort, and the associations between preoperative protein levels and postoperative delirium were assessed using t-test statistics with further analysis by systems biology to elucidate delirium pathophysiology. Proteomics analysis identified 32 proteins in preoperative CSF that significantly associate with delirium (t-test p < 0.05). Due to the limited sample size, these proteins did not remain significant by multiple hypothesis testing using the Benjamini-Hochberg correction and q-value method. Three algorithms were applied to separate delirium cases from non-delirium controls. Hierarchical clustering classified 40/48 case-control samples correctly, and principal components analysis separated 43/48. The receiver operating characteristic curve yielded an area under the curve [95% confidence interval] of 0.91 [0.80-0.97]. Systems biology analysis identified several key pathways associated with risk of delirium: inflammation, immune cell migration, apoptosis, angiogenesis, synaptic depression and neuronal cell death. Proteomics analysis of preoperative CSF identified 32 proteins that might discriminate individuals who subsequently develop postoperative delirium from matched control samples. These proteins are potential candidate biomarkers for delirium and may play a role in its pathophysiology.
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Affiliation(s)
- Simon T. Dillon
- Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA; (S.T.D.); (X.G.)
- Beth Israel Deaconess Medical Center Genomics, Proteomics, Bioinformatics and Systems Biology Center, Boston, MA 02215, USA
- Harvard Medical School, Boston, MA 02215, USA; (S.M.V.); (L.N.); (T.F.); (M.C.); (A.T.); (M.S.); (Z.X.); (E.R.M.)
| | - Sarinnapha M. Vasunilashorn
- Harvard Medical School, Boston, MA 02215, USA; (S.M.V.); (L.N.); (T.F.); (M.C.); (A.T.); (M.S.); (Z.X.); (E.R.M.)
- Divisions of General Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
- Departments of Epidemiology and Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Hasan H. Otu
- Department of Electrical and Computer Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USA;
| | - Long Ngo
- Harvard Medical School, Boston, MA 02215, USA; (S.M.V.); (L.N.); (T.F.); (M.C.); (A.T.); (M.S.); (Z.X.); (E.R.M.)
- Divisions of General Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Tamara Fong
- Harvard Medical School, Boston, MA 02215, USA; (S.M.V.); (L.N.); (T.F.); (M.C.); (A.T.); (M.S.); (Z.X.); (E.R.M.)
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
- Aging Brain Center, Marcus Institute for Aging Research, Hebrew Senior Life, Boston, MA 02131, USA;
| | - Xuesong Gu
- Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA; (S.T.D.); (X.G.)
- Beth Israel Deaconess Medical Center Genomics, Proteomics, Bioinformatics and Systems Biology Center, Boston, MA 02215, USA
- Harvard Medical School, Boston, MA 02215, USA; (S.M.V.); (L.N.); (T.F.); (M.C.); (A.T.); (M.S.); (Z.X.); (E.R.M.)
| | - Michele Cavallari
- Harvard Medical School, Boston, MA 02215, USA; (S.M.V.); (L.N.); (T.F.); (M.C.); (A.T.); (M.S.); (Z.X.); (E.R.M.)
- Center for Neurological Imaging, Department of Radiology, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Alexandra Touroutoglou
- Harvard Medical School, Boston, MA 02215, USA; (S.M.V.); (L.N.); (T.F.); (M.C.); (A.T.); (M.S.); (Z.X.); (E.R.M.)
- Frontotemporal Disorders Unit, Department of Neurology, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Mouhsin Shafi
- Harvard Medical School, Boston, MA 02215, USA; (S.M.V.); (L.N.); (T.F.); (M.C.); (A.T.); (M.S.); (Z.X.); (E.R.M.)
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
- Berenson-Allen Center for Noninvasive Brain Stimulation, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Sharon K. Inouye
- Aging Brain Center, Marcus Institute for Aging Research, Hebrew Senior Life, Boston, MA 02131, USA;
- Divisions of Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Zhongcong Xie
- Harvard Medical School, Boston, MA 02215, USA; (S.M.V.); (L.N.); (T.F.); (M.C.); (A.T.); (M.S.); (Z.X.); (E.R.M.)
- Department of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA 02114, USA
| | - Edward R. Marcantonio
- Harvard Medical School, Boston, MA 02215, USA; (S.M.V.); (L.N.); (T.F.); (M.C.); (A.T.); (M.S.); (Z.X.); (E.R.M.)
- Divisions of General Medicine, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
- Divisions of Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA
| | - Towia A. Libermann
- Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, Boston, MA 02215, USA; (S.T.D.); (X.G.)
- Beth Israel Deaconess Medical Center Genomics, Proteomics, Bioinformatics and Systems Biology Center, Boston, MA 02215, USA
- Harvard Medical School, Boston, MA 02215, USA; (S.M.V.); (L.N.); (T.F.); (M.C.); (A.T.); (M.S.); (Z.X.); (E.R.M.)
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Ma S, Wang D, Xie D. Identification of disulfidptosis-related genes and subgroups in Alzheimer's disease. Front Aging Neurosci 2023; 15:1236490. [PMID: 37600517 PMCID: PMC10436325 DOI: 10.3389/fnagi.2023.1236490] [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: 06/07/2023] [Accepted: 07/17/2023] [Indexed: 08/22/2023] Open
Abstract
Background Alzheimer's disease (AD), a common neurological disorder, has no effective treatment due to its complex pathogenesis. Disulfidptosis, a newly discovered type of cell death, seems to be closely related to the occurrence of various diseases. In this study, through bioinformatics analysis, the expression and function of disulfidptosis-related genes (DRGs) in Alzheimer's disease were explored. Methods Differential analysis was performed on the gene expression matrix of AD, and the intersection of differentially expressed genes and disulfidptosis-related genes in AD was obtained. Hub genes were further screened using multiple machine learning methods, and a predictive model was constructed. Finally, 97 AD samples were divided into two subgroups based on hub genes. Results In this study, a total of 22 overlapping genes were identified, and 7 hub genes were further obtained through machine learning, including MYH9, IQGAP1, ACTN4, DSTN, ACTB, MYL6, and GYS1. Furthermore, the diagnostic capability was validated using external datasets and clinical samples. Based on these genes, a predictive model was constructed, with a large area under the curve (AUC = 0.8847), and the AUCs of the two external validation datasets were also higher than 0.7, indicating the high accuracy of the predictive model. Using unsupervised clustering based on hub genes, 97 AD samples were divided into Cluster1 (n = 24) and Cluster2 (n = 73), with most hub genes expressed at higher levels in Cluster2. Immune infiltration analysis revealed that Cluster2 had a higher level of immune infiltration and immune scores. Conclusion A close association between disulfidptosis and Alzheimer's disease was discovered in this study, and a predictive model was established to assess the risk of disulfidptosis subtype in AD patients. This study provides new perspectives for exploring biomarkers and potential therapeutic targets for Alzheimer's disease.
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Affiliation(s)
- Shijia Ma
- The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, China
| | - Dan Wang
- Encephalopathy Center, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, China
| | - Daojun Xie
- Encephalopathy Center, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, China
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44
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Events in the brain during the evolution of Alzheimer's disease. Nat Med 2023; 29:1916-1917. [PMID: 37550418 DOI: 10.1038/s41591-023-02477-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/09/2023]
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45
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Mi MY, Barber JL, Rao P, Farrell LA, Sarzynski MA, Bouchard C, Robbins JM, Gerszten RE. Plasma Proteomic Kinetics in Response to Acute Exercise. Mol Cell Proteomics 2023; 22:100601. [PMID: 37343698 PMCID: PMC10460691 DOI: 10.1016/j.mcpro.2023.100601] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 05/09/2023] [Accepted: 06/11/2023] [Indexed: 06/23/2023] Open
Abstract
Regular exercise has many favorable effects on human health, which may be mediated in part by the release of circulating bioactive factors during each bout of exercise. Limited data exist regarding the kinetic responses of plasma proteins during and after acute exercise. Proteomic profiling of 4163 proteins was performed using a large-scale, affinity-based platform in 75 middle-aged adults who were referred for treadmill exercise stress testing. Plasma proteins were quantified at baseline, peak exercise, and 1-h postexercise, and those with significant changes at both exercise timepoints were further examined for their associations with cardiometabolic traits and change with aerobic exercise training in the Health, Risk Factors, Exercise Training and Genetics Family Study, a 20-week exercise intervention study. A total of 765 proteins changed (false discovery rate < 0.05) at peak exercise compared to baseline, and 128 proteins changed (false discovery rate < 0.05) at 1-h postexercise. The 56 proteins that changed at both timepoints included midkine, brain-derived neurotrophic factor, metalloproteinase inhibitor 4, and coiled-coil domain-containing protein 126 and were enriched for secreted proteins. The majority had concordant direction of change at both timepoints. Across all proteins assayed, gene set enrichment analysis showed increased abundance of coagulation-related proteins at 1-h postexercise. Forty-five proteins were associated with at least one measure of adiposity, lipids, glucose homeostasis, or cardiorespiratory fitness in Health, Risk Factors, Exercise Training and Genetics Family Study, and 20 proteins changed with aerobic exercise training. We identified hundreds of novel proteins that change during acute exercise, most of which resolved by 1 h into recovery. Proteins with sustained changes during exercise and recovery may be of particular interest as circulating biomarkers and pathways for further investigation in cardiometabolic diseases. These data will contribute to a biochemical roadmap of acute exercise that will be publicly available for the entire scientific community.
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Affiliation(s)
- Michael Y Mi
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA; CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA.
| | - Jacob L Barber
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Prashant Rao
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA; CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Laurie A Farrell
- CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Mark A Sarzynski
- Department of Exercise Science, Arnold School of Public Health, University of South Carolina, Columbia, South Carolina, USA
| | - Claude Bouchard
- Human Genomics Laboratory, Pennington Biomedical Research Center, Baton Rouge, Louisiana, USA
| | - Jeremy M Robbins
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA; CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Robert E Gerszten
- Division of Cardiovascular Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA; CardioVascular Institute, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
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Johnson ECB, Bian S, Haque RU, Carter EK, Watson CM, Gordon BA, Ping L, Duong DM, Epstein MP, McDade E, Barthélemy NR, Karch CM, Xiong C, Cruchaga C, Perrin RJ, Wingo AP, Wingo TS, Chhatwal JP, Day GS, Noble JM, Berman SB, Martins R, Graff-Radford NR, Schofield PR, Ikeuchi T, Mori H, Levin J, Farlow M, Lah JJ, Haass C, Jucker M, Morris JC, Benzinger TLS, Roberts BR, Bateman RJ, Fagan AM, Seyfried NT, Levey AI. Cerebrospinal fluid proteomics define the natural history of autosomal dominant Alzheimer's disease. Nat Med 2023; 29:1979-1988. [PMID: 37550416 PMCID: PMC10427428 DOI: 10.1038/s41591-023-02476-4] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 06/27/2023] [Indexed: 08/09/2023]
Abstract
Alzheimer's disease (AD) pathology develops many years before the onset of cognitive symptoms. Two pathological processes-aggregation of the amyloid-β (Aβ) peptide into plaques and the microtubule protein tau into neurofibrillary tangles (NFTs)-are hallmarks of the disease. However, other pathological brain processes are thought to be key disease mediators of Aβ plaque and NFT pathology. How these additional pathologies evolve over the course of the disease is currently unknown. Here we show that proteomic measurements in autosomal dominant AD cerebrospinal fluid (CSF) linked to brain protein coexpression can be used to characterize the evolution of AD pathology over a timescale spanning six decades. SMOC1 and SPON1 proteins associated with Aβ plaques were elevated in AD CSF nearly 30 years before the onset of symptoms, followed by changes in synaptic proteins, metabolic proteins, axonal proteins, inflammatory proteins and finally decreases in neurosecretory proteins. The proteome discriminated mutation carriers from noncarriers before symptom onset as well or better than Aβ and tau measures. Our results highlight the multifaceted landscape of AD pathophysiology and its temporal evolution. Such knowledge will be critical for developing precision therapeutic interventions and biomarkers for AD beyond those associated with Aβ and tau.
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Affiliation(s)
- Erik C B Johnson
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA.
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA.
| | - Shijia Bian
- Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Rafi U Haque
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
| | - E Kathleen Carter
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Caroline M Watson
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Brian A Gordon
- Mallinckrodt Institute of Radiology, Washington University in St Louis, St Louis, MO, USA
| | - Lingyan Ping
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Duc M Duong
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Michael P Epstein
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Eric McDade
- Department of Neurology, Washington University in St Louis, St Louis, MO, USA
| | | | - Celeste M Karch
- Department of Psychiatry, Washington University in St Louis, St Louis, MO, USA
| | - Chengjie Xiong
- Department of Neurology, Washington University in St Louis, St Louis, MO, USA
- Division of Biostatistics, Washington University in St Louis, St Louis, MO, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University in St Louis, St Louis, MO, USA
| | - Richard J Perrin
- Department of Neurology, Washington University in St Louis, St Louis, MO, USA
- Department of Pathology and Immunology, Washington University in St Louis, St Louis, MO, USA
| | - Aliza P Wingo
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Psychiatry, Emory University School of Medicine, Atlanta, GA, USA
- Division of Mental Health, Atlanta VA Medical Center, Atlanta, GA, USA
| | - Thomas S Wingo
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Department of Human Genetics, Emory University School of Medicine, Atlanta, GA, USA
| | - Jasmeer P Chhatwal
- Massachusetts General and Brigham & Women's Hospitals, Harvard Medical School, Boston, MA, USA
| | - Gregory S Day
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - James M Noble
- Department of Neurology, Taub Institute for Research on Alzheimer's Disease and the Aging Brain, and GH Sergievsky Center, Columbia University Irving Medical Center, New York, NY, USA
| | - Sarah B Berman
- Departments of Neurology and Clinical and Translational Science, Pittsburgh Institute for Neurodegenerative Diseases, University of Pittsburgh, Pittsburgh, PA, USA
| | - Ralph Martins
- Edith Cowan University, Perth, Western Australia, Australia
| | | | - Peter R Schofield
- Neuroscience Research Australia, Sydney, New South Wales, Australia
- School of Biomedical Sciences, University of New South Wales, Sydney, New South Wales, Australia
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Hiroshi Mori
- Osaka Metropolitan University Medical School, Nagaoka Sutoku University, Nagaoka, Japan
| | - Johannes Levin
- Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | | | - James J Lah
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Christian Haass
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Metabolic Biochemistry, Biomedical Center (BMC), Ludwig-Maximilians University, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Mathias Jucker
- Department of Cellular Neurology, Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - John C Morris
- Department of Neurology, Washington University in St Louis, St Louis, MO, USA
| | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University in St Louis, St Louis, MO, USA
| | - Blaine R Roberts
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Randall J Bateman
- Department of Neurology, Washington University in St Louis, St Louis, MO, USA
| | - Anne M Fagan
- Department of Neurology, Washington University in St Louis, St Louis, MO, USA
| | - Nicholas T Seyfried
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Allan I Levey
- Goizueta Alzheimer's Disease Research Center, Emory University School of Medicine, Atlanta, GA, USA
- Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
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Modeste ES, Ping L, Watson CM, Duong DM, Dammer EB, Johnson ECB, Roberts BR, Lah JJ, Levey AI, Seyfried NT. Quantitative proteomics of cerebrospinal fluid from African Americans and Caucasians reveals shared and divergent changes in Alzheimer's disease. Mol Neurodegener 2023; 18:48. [PMID: 37468915 PMCID: PMC10355042 DOI: 10.1186/s13024-023-00638-z] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 06/21/2023] [Indexed: 07/21/2023] Open
Abstract
BACKGROUND Despite being twice as likely to get Alzheimer's disease (AD), African Americans have been grossly underrepresented in AD research. While emerging evidence indicates that African Americans with AD have lower cerebrospinal fluid (CSF) levels of Tau compared to Caucasians, other differences in AD CSF biomarkers have not been fully elucidated. Here, we performed unbiased proteomic profiling of CSF from African Americans and Caucasians with and without AD to identify both common and divergent AD CSF biomarkers. METHODS Multiplex tandem mass tag-based mass spectrometry (TMT-MS) quantified 1,840 proteins from 105 control and 98 AD patients of which 100 identified as Caucasian while 103 identified as African American. We used differential protein expression and co-expression approaches to assess how changes in the CSF proteome are related to race and AD. Co-expression network analysis organized the CSF proteome into 14 modules associated with brain cell-types and biological pathways. A targeted mass spectrometry method, selected reaction monitoring (SRM), with heavy labeled internal standards was used to measure a panel of CSF module proteins across a subset of African Americans and Caucasians with or without AD. A receiver operating characteristic (ROC) curve analysis assessed the performance of each protein biomarker in differentiating controls and AD by race. RESULTS Consistent with previous findings, the increase of Tau levels in AD was greater in Caucasians than in African Americans by both immunoassay and TMT-MS measurements. CSF modules which included 14-3-3 proteins (YWHAZ and YWHAG) demonstrated equivalent disease-related elevations in both African Americans and Caucasians with AD, whereas other modules demonstrated more profound disease changes within race. Modules enriched with proteins involved with glycolysis and neuronal/cytoskeletal proteins, including Tau, were more increased in Caucasians than in African Americans with AD. In contrast, a module enriched with synaptic proteins including VGF, SCG2, and NPTX2 was significantly lower in African Americans than Caucasians with AD. Following SRM and ROC analysis, VGF, SCG2, and NPTX2 were significantly better at classifying African Americans than Caucasians with AD. CONCLUSIONS Our findings provide insight into additional protein biomarkers and pathways reflecting underlying brain pathology that are shared or differ by race.
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Affiliation(s)
- Erica S. Modeste
- School of Medicine, Department of Biochemistry, Emory University, Atlanta, GA USA
| | - Lingyan Ping
- School of Medicine, Department of Biochemistry, Emory University, Atlanta, GA USA
| | - Caroline M. Watson
- School of Medicine, Department of Neurology, Emory University, Atlanta, GA USA
| | - Duc M. Duong
- School of Medicine, Department of Biochemistry, Emory University, Atlanta, GA USA
| | - Eric B. Dammer
- School of Medicine, Department of Biochemistry, Emory University, Atlanta, GA USA
| | - Erik C. B. Johnson
- School of Medicine, Department of Neurology, Emory University, Atlanta, GA USA
| | - Blaine R. Roberts
- School of Medicine, Department of Biochemistry, Emory University, Atlanta, GA USA
| | - James J. Lah
- School of Medicine, Department of Neurology, Emory University, Atlanta, GA USA
| | - Allan I. Levey
- School of Medicine, Department of Neurology, Emory University, Atlanta, GA USA
| | - Nicholas T. Seyfried
- School of Medicine, Department of Biochemistry, Emory University, Atlanta, GA USA
- School of Medicine, Department of Neurology, Emory University, Atlanta, GA USA
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Leitner DF, Kanshin E, Faustin A, Thierry M, Friedman D, Devore S, Ueberheide B, Devinsky O, Wisniewski T. Localized proteomic differences in the choroid plexus of Alzheimer's disease and epilepsy patients. Front Neurol 2023; 14:1221775. [PMID: 37521285 PMCID: PMC10379643 DOI: 10.3389/fneur.2023.1221775] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2023] [Accepted: 06/22/2023] [Indexed: 08/01/2023] Open
Abstract
Introduction Alzheimer's disease (AD) and epilepsy are reciprocally related. Among sporadic AD patients, clinical seizures occur in 10-22% and subclinical epileptiform abnormalities occur in 22-54%. Cognitive deficits, especially short-term memory impairments, occur in most epilepsy patients. Common neurophysiological and molecular mechanisms occur in AD and epilepsy. The choroid plexus undergoes pathological changes in aging, AD, and epilepsy, including decreased CSF turnover, amyloid beta (Aβ), and tau accumulation due to impaired clearance and disrupted CSF amino acid homeostasis. This pathology may contribute to synaptic dysfunction in AD and epilepsy. Methods We evaluated control (n = 8), severe AD (n = 8; A3, B3, C3 neuropathology), and epilepsy autopsy cases (n = 12) using laser capture microdissection (LCM) followed by label-free quantitative mass spectrometry on the choroid plexus adjacent to the hippocampus at the lateral geniculate nucleus level. Results Proteomics identified 2,459 proteins in the choroid plexus. At a 5% false discovery rate (FDR), 616 proteins were differentially expressed in AD vs. control, 1 protein in epilepsy vs. control, and 438 proteins in AD vs. epilepsy. There was more variability in the epilepsy group across syndromes. The top 20 signaling pathways associated with differentially expressed proteins in AD vs. control included cell metabolism pathways; activated fatty acid beta-oxidation (p = 2.00 x 10-7, z = 3.00), and inhibited glycolysis (p = 1.00 x 10-12, z = -3.46). For AD vs. epilepsy, the altered pathways included cell metabolism pathways, activated complement system (p = 5.62 x 10-5, z = 2.00), and pathogen-induced cytokine storm (p = 2.19 x 10-2, z = 3.61). Of the 617 altered proteins in AD and epilepsy vs. controls, 497 (81%) were positively correlated (p < 0.0001, R2 = 0.27). Discussion We found altered signaling pathways in the choroid plexus of severe AD cases and many correlated changes in the protein expression of cell metabolism pathways in AD and epilepsy cases. The shared molecular mechanisms should be investigated further to distinguish primary pathogenic changes from the secondary ones. These mechanisms could inform novel therapeutic strategies to prevent disease progression or restore normal function. A focus on dual-diagnosed AD/epilepsy cases, specific epilepsy syndromes, such as temporal lobe epilepsy, and changes across different severity levels in AD and epilepsy would add to our understanding.
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Affiliation(s)
- Dominique F. Leitner
- Comprehensive Epilepsy Center, New York University Grossman School of Medicine, New York, NY, United States
- Center for Cognitive Neurology, Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
| | - Evgeny Kanshin
- Proteomics Laboratory, Division of Advanced Research Technologies, New York University Grossman School of Medicine, New York, NY, United States
- Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY, United States
| | - Arline Faustin
- Center for Cognitive Neurology, Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
- Department of Pathology, New York University Grossman School of Medicine, New York, NY, United States
| | - Manon Thierry
- Center for Cognitive Neurology, Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
| | - Daniel Friedman
- Comprehensive Epilepsy Center, New York University Grossman School of Medicine, New York, NY, United States
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
| | - Sasha Devore
- Comprehensive Epilepsy Center, New York University Grossman School of Medicine, New York, NY, United States
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
| | - Beatrix Ueberheide
- Center for Cognitive Neurology, Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
- Proteomics Laboratory, Division of Advanced Research Technologies, New York University Grossman School of Medicine, New York, NY, United States
- Department of Biochemistry and Molecular Pharmacology, New York University Grossman School of Medicine, New York, NY, United States
| | - Orrin Devinsky
- Comprehensive Epilepsy Center, New York University Grossman School of Medicine, New York, NY, United States
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
| | - Thomas Wisniewski
- Center for Cognitive Neurology, Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
- Department of Neurology, New York University Grossman School of Medicine, New York, NY, United States
- Department of Pathology, New York University Grossman School of Medicine, New York, NY, United States
- Department of Psychiatry, New York University Grossman School of Medicine, New York, NY, United States
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Sung YJ, Yang C, Norton J, Johnson M, Fagan A, Bateman RJ, Perrin RJ, Morris JC, Farlow MR, Chhatwal JP, Schofield PR, Chui H, Wang F, Novotny B, Eteleeb A, Karch C, Schindler SE, Rhinn H, Johnson EC, Se-Hwee Oh H, Rutledge JE, Dammer EB, Seyfried NT, Wyss-Coray T, Harari O, Cruchaga C. Proteomics of brain, CSF, and plasma identifies molecular signatures for distinguishing sporadic and genetic Alzheimer's disease. Sci Transl Med 2023; 15:eabq5923. [PMID: 37406134 PMCID: PMC10803068 DOI: 10.1126/scitranslmed.abq5923] [Citation(s) in RCA: 20] [Impact Index Per Article: 20.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 06/13/2023] [Indexed: 07/07/2023]
Abstract
Proteomic studies for Alzheimer's disease (AD) are instrumental in identifying AD pathways but often focus on single tissues and sporadic AD cases. Here, we present a proteomic study analyzing 1305 proteins in brain tissue, cerebrospinal fluid (CSF), and plasma from patients with sporadic AD, TREM2 risk variant carriers, patients with autosomal dominant AD (ADAD), and healthy individuals. We identified 8 brain, 40 CSF, and 9 plasma proteins that were altered in individuals with sporadic AD, and we replicated these findings in several external datasets. We identified a proteomic signature that differentiated TREM2 variant carriers from both individuals with sporadic AD and healthy individuals. The proteins associated with sporadic AD were also altered in patients with ADAD, but with a greater effect size. Brain-derived proteins associated with ADAD were also replicated in additional CSF samples. Enrichment analyses highlighted several pathways, including those implicated in AD (calcineurin and Apo E), Parkinson's disease (α-synuclein and LRRK2), and innate immune responses (SHC1, ERK-1, and SPP1). Our findings suggest that combined proteomics across brain tissue, CSF, and plasma can be used to identify markers for sporadic and genetically defined AD.
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Affiliation(s)
- Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63108, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63108, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Chengran Yang
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63108, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Joanne Norton
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63108, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Matt Johnson
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63108, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Anne Fagan
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63108, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63108, USA
| | - Randall J. Bateman
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63108, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63108, USA
| | - Richard J. Perrin
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63108, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63108, USA
- Department of Pathology & Immunology, Washington University School of Medicine, St Louis, MO 63108, USA
| | - John C. Morris
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63108, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63108, USA
- Department of Pathology & Immunology, Washington University School of Medicine, St Louis, MO 63108, USA
| | - Martin R. Farlow
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN 46202, USA
| | - Jasmeer P. Chhatwal
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Peter R. Schofield
- Neuroscience Research Australia, Randwick, NSW, 2031, Australia
- School of Biomedical Sciences, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Helena Chui
- Department of Neurology, University of Southern California, Los Angeles, CA 90089, USA
| | - Fengxian Wang
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63108, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Brenna Novotny
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63108, USA
| | - Abdallah Eteleeb
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63108, USA
| | - Celeste Karch
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63108, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Suzanne E. Schindler
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63108, USA
- Department of Neurology, Washington University School of Medicine, St Louis, MO 63108, USA
| | - Herve Rhinn
- Department of Bioinformatics. Alector, Inc. 151 Oyster Point Blvd. #300 South San Francisco CA 94080, USA
| | - Erik C.B. Johnson
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA 30329, USA
| | - Hamilton Se-Hwee Oh
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Jarod Evert Rutledge
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Eric B Dammer
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA 30329, USA
| | - Nicholas T. Seyfried
- Goizueta Alzheimer’s Disease Research Center, Emory University School of Medicine, Atlanta, GA 30329, USA
- Department of Biochemistry, Emory School of Medicine, Atlanta, GA 30329, USA
| | - Tony Wyss-Coray
- Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA 94304, USA
| | - Oscar Harari
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63108, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO 63108, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63108, USA
- The Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO 63108, USA
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Weiner S, Blennow K, Zetterberg H, Gobom J. Next-generation proteomics technologies in Alzheimer's disease: from clinical research to routine diagnostics. Expert Rev Proteomics 2023; 20:143-150. [PMID: 37701966 DOI: 10.1080/14789450.2023.2255752] [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: 05/21/2023] [Accepted: 08/18/2023] [Indexed: 09/14/2023]
Abstract
INTRODUCTION Clinical proteomics studies of Alzheimer's disease (AD) research aim to identify biomarkers useful for clinical research, diagnostics, and improve our understanding of the pathological processes involved in the disease. The rapidly increasing performance of proteomics technologies is likely to have great impact on AD research. AREAS COVERED We review recent proteomics approaches that have advanced the field of clinical AD research. Specifically, we discuss the application of targeted mass spectrometry (MS), labeling-based and label-free MS-based as well as affinity-based proteomics to AD biomarker development, underpinning their importance with the latest impactful clinical studies. We evaluate how proteomics technologies have been adapted to meet current challenges. Finally, we discuss the limitations and potential of proteomics techniques and whether their scope might extend beyond current research-based applications. EXPERT OPINION To date, proteomics technologies in the AD field have been largely limited to AD biomarker discovery. The recent development of the first successful disease-modifying treatments of AD will further increase the need for blood biomarkers for early, accurate diagnosis, and CSF biomarkers that reflect specific pathological processes. Proteomics has the potential to meet these requirements and to progress into clinical routine practice, provided that current limitations are overcome.
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Affiliation(s)
- Sophia Weiner
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Dementia Research Institute at UCL, London, UK
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Johan Gobom
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
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