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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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Mitsunaga S, Fujito N, Nakaoka H, Imazeki R, Nagata E, Inoue I. Detection of APP gene recombinant in human blood plasma. Sci Rep 2023; 13:21703. [PMID: 38066066 PMCID: PMC10709617 DOI: 10.1038/s41598-023-48993-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Accepted: 12/02/2023] [Indexed: 12/18/2023] Open
Abstract
The pathogenesis of Alzheimer's disease (AD) is believed to involve the accumulation of amyloid-β in the brain, which is produced by the sequential cleavage of amyloid precursor protein (APP) by β-secretase and γ-secretase. Recently, analysis of genomic DNA and mRNA from postmortem brain neurons has revealed intra-exonic recombinants of APP (gencDNA), which have been implicated in the accumulation of amyloid-β. In this study, we computationally analyzed publicly available sequence data (SRA) using probe sequences we constructed to screen APP gencDNAs. APP gencDNAs were detected in SRAs constructed from both genomic DNA and RNA obtained from the postmortem brain and in the SRA constructed from plasma cell-free mRNA (cf-mRNA). The SRA constructed from plasma cf-mRNA showed a significant difference in the number of APP gencDNA reads between SAD and NCI: the p-value from the Mann-Whitney U test was 5.14 × 10-6. The transcripts were also found in circulating nucleic acids (CNA) from our plasma samples with NGS analysis. These data indicate that transcripts of APP gencDNA can be detected in blood plasma and suggest the possibility of using them as blood biomarkers for Alzheimer's disease.
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Affiliation(s)
- Shigeki Mitsunaga
- Laboratory of Human Genetics, National Institute of Genetics, 1111 Yata, Mishima, Shizuoka, 411-8540, Japan.
| | - Naoko Fujito
- Laboratory of Human Genetics, National Institute of Genetics, 1111 Yata, Mishima, Shizuoka, 411-8540, Japan
- Department of Genetics, The Graduate University for Advanced Studies (SOKENDAI), Mishima, 411-8540, Japan
| | - Hirofumi Nakaoka
- Department of Cancer Genome Research, Sasaki Institute, Sasaki Foundation, Chiyoda-ku, Tokyo, 101-0062, Japan
| | - Ryoko Imazeki
- Department of Neurology, Tokai University School of Medicine, Isehara, Japan
| | - Eiichiro Nagata
- Department of Neurology, Tokai University School of Medicine, Isehara, Japan
| | - Ituro Inoue
- Laboratory of Human Genetics, National Institute of Genetics, 1111 Yata, Mishima, Shizuoka, 411-8540, Japan.
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Valdes P, Henry KW, Fitzgerald MQ, Muralidharan K, Caldwell AB, Ramachandran S, Goldstein LSB, Mobley WC, Galasko DR, Subramaniam S. Limitations of the human iPSC-derived neuron model for early-onset Alzheimer's disease. Mol Brain 2023; 16:75. [PMID: 37924159 PMCID: PMC10623777 DOI: 10.1186/s13041-023-01063-5] [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: 10/07/2023] [Indexed: 11/06/2023] Open
Abstract
Non-familial Alzheimer's disease (AD) occurring before 65 years of age is commonly referred to as early-onset Alzheimer's disease (EOAD) and constitutes ~ 5-6% of all AD cases (Mendez et al. in Continuum 25:34-51, 2019). While EOAD exhibits the same clinicopathological changes such as amyloid plaques, neurofibrillary tangles (NFTs), brain atrophy, and cognitive decline (Sirkis et al. in Mol Psychiatry 27:2674-88, 2022; Caldwell et al. in Mol Brain 15:83, 2022) as observed in the more prevalent late-onset AD (LOAD), EOAD patients tend to have more severe cognitive deficits, including visuospatial, language, and executive dysfunction (Sirkis et al. in Mol Psychiatry 27:2674-88, 2022). Patient-derived induced pluripotent stem cells (iPSCs) have been used to model and study penetrative, familial AD (FAD) mutations in APP, PSEN1, and PSEN2 (Valdes et al. in Research Square 1-30, 2022; Caldwell et al. in Sci Adv 6:1-16, 2020) but have been seldom used for sporadic forms of AD that display more heterogeneous disease mechanisms. In this study, we sought to characterize iPSC-derived neurons from EOAD patients via RNA sequencing. A modest difference in expression profiles between EOAD patients and non-demented control (NDC) subjects resulted in a limited number of differentially expressed genes (DEGs). Based on this analysis, we provide evidence that iPSC-derived neuron model systems, likely due to the loss of EOAD-associated epigenetic signatures arising from iPSC reprogramming, may not be ideal models for studying sporadic AD.
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Affiliation(s)
- Phoebe Valdes
- Department of Bioengineering, University of California, La Jolla, San Diego, CA, USA
- Bioengineering Graduate Program, University of California, La Jolla, San Diego, CA, USA
| | - Kenneth W Henry
- Department of Cellular and Molecular Medicine, University of California, La Jolla, San Diego, CA, USA
- Sanford Consortium for Regenerative Medicine, La Jolla, CA, USA
| | - Michael Q Fitzgerald
- Department of Bioengineering, University of California, La Jolla, San Diego, CA, USA
- Bioengineering Graduate Program, University of California, La Jolla, San Diego, CA, USA
| | - Koushik Muralidharan
- Medical Scientist Training Program, University of California, La Jolla, San Diego, CA, USA
- School of Medicine, University of California, La Jolla, San Diego, CA, USA
| | - Andrew B Caldwell
- Department of Bioengineering, University of California, La Jolla, San Diego, CA, USA
| | | | - Lawrence S B Goldstein
- Department of Cellular and Molecular Medicine, University of California, La Jolla, San Diego, CA, USA
- Sanford Stem Cell Clinical Center, University of California, La Jolla, San Diego, CA, USA
| | - William C Mobley
- Department of Neurosciences, University of California, La Jolla, San Diego, CA, USA
| | - Douglas R Galasko
- Department of Neurosciences, University of California, La Jolla, San Diego, CA, USA
| | - Shankar Subramaniam
- Department of Bioengineering, University of California, La Jolla, San Diego, CA, USA.
- Department of Cellular and Molecular Medicine, University of California, La Jolla, San Diego, CA, USA.
- Department of Nanoengineering, University of California, La Jolla, San Diego, CA, USA.
- Department of Computer Science and Engineering, University of California, La Jolla, San Diego, CA, USA.
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Patel AO, Caldwell AB, Ramachandran S, Subramaniam S. Endotype Characterization Reveals Mechanistic Differences Across Brain Regions in Sporadic Alzheimer's Disease. J Alzheimers Dis Rep 2023; 7:957-972. [PMID: 37849634 PMCID: PMC10578327 DOI: 10.3233/adr-220098] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 07/21/2023] [Indexed: 10/19/2023] Open
Abstract
Background While Alzheimer's disease (AD) pathology is associated with altered brain structure, it is not clear whether gene expression changes mirror the onset and evolution of pathology in distinct brain regions. Deciphering the mechanisms which cause the differential manifestation of the disease across different regions has the potential to help early diagnosis. Objective We aimed to identify common and unique endotypes and their regulation in tangle-free neurons in sporadic AD (SAD) across six brain regions: entorhinal cortex (EC), hippocampus (HC), medial temporal gyrus (MTG), posterior cingulate (PC), superior frontal gyrus (SFG), and visual cortex (VCX). Methods To decipher the states of tangle-free neurons across different brain regions in human subjects afflicted with AD, we performed analysis of the neural transcriptome. We explored changes in differential gene expression, functional and transcription factor target enrichment, and co-expression gene module detection analysis to discern disease-state transcriptomic variances and characterize endotypes. Additionally, we compared our results to tangled AD neuron microarray-based study and the Allen Brain Atlas. Results We identified impaired neuron function in EC, MTG, PC, and VCX resulting from REST activation and reversal of mature neurons to a precursor-like state in EC, MTG, and SFG linked to SOX2 activation. Additionally, decreased neuron function and increased dedifferentiation were linked to the activation of SUZ12. Energetic deficit connected to NRF1 inactivation was found in HC, PC, and VCX. Conclusions Our findings suggest that SAD manifestation varies in scale and severity in different brain regions. We identify endotypes, such as energetic shortfalls, impaired neuronal function, and dedifferentiation.
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Affiliation(s)
- Ashay O. Patel
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Andrew B. Caldwell
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | | | - Shankar Subramaniam
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
- Department of Cellular and Molecular Medicine, University of California, San Diego, La Jolla, CA, USA
- Department of Nanoengineering, University of California, San Diego, La Jolla, CA, USA
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, USA
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Guo W, Gou X, Yu L, Zhang Q, Yang P, Pang M, Pang X, Pang C, Wei Y, Zhang X. Exploring the interaction between T-cell antigen receptor-related genes and MAPT or ACHE using integrated bioinformatics analysis. Front Neurol 2023; 14:1129470. [PMID: 37056359 PMCID: PMC10086260 DOI: 10.3389/fneur.2023.1129470] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 03/10/2023] [Indexed: 03/30/2023] Open
Abstract
Alzheimer's disease (AD) is a neurodegenerative disease that primarily occurs in elderly individuals with cognitive impairment. Although extracellular β-amyloid (Aβ) accumulation and tau protein hyperphosphorylation are considered to be leading causes of AD, the molecular mechanism of AD remains unknown. Therefore, in this study, we aimed to explore potential biomarkers of AD. Next-generation sequencing (NGS) datasets, GSE173955 and GSE203206, were collected from the Gene Expression Omnibus (GEO) database. Analysis of differentially expressed genes (DEGs), gene ontology (GO) functional enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment, and protein-protein networks were performed to identify genes that are potentially associated with AD. Analysis of the DEG based protein-protein interaction (PPI) network using Cytoscape indicated that neuroinflammation and T-cell antigen receptor (TCR)-associated genes (LCK, ZAP70, and CD44) were the top three hub genes. Next, we validated these three hub genes in the AD database and utilized two machine learning models from different AD datasets (GSE15222) to observe their general relationship with AD. Analysis using the random forest classifier indicated that accuracy (78%) observed using the top three genes as inputs differed only slightly from that (84%) observed using all genes as inputs. Furthermore, another data set, GSE97760, which was analyzed using our novel eigenvalue decomposition method, indicated that the top three hub genes may be involved in tauopathies associated with AD, rather than Aβ pathology. In addition, protein-protein docking simulation revealed that the top hub genes could form stable binding sites with acetylcholinesterase (ACHE). This suggests a potential interaction between hub genes and ACHE, which plays an essential role in the development of anti-AD drug design. Overall, the findings of this study, which systematically analyzed several AD datasets, illustrated that LCK, ZAP70, and CD44 may be used as AD biomarkers. We also established a robust prediction model for classifying patients with AD.
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Affiliation(s)
- Wenbo Guo
- College of Computer Science, Sichuan Normal University, Chengdu, China
| | - Xun Gou
- College of Life Science, Sichuan Normal University, Chengdu, China
| | - Lei Yu
- College of Computer Science, Sichuan Normal University, Chengdu, China
| | - Qi Zhang
- College of Computer Science, Sichuan Normal University, Chengdu, China
| | - Ping Yang
- College of Computer Science, Sichuan Normal University, Chengdu, China
| | - Minghui Pang
- College of Mathematics and Physics, Chengdu University of Technology, Chengdu, China
| | - Xinping Pang
- West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu, China
| | - Chaoyang Pang
- College of Computer Science, Sichuan Normal University, Chengdu, China
- *Correspondence: Chaoyang Pang
| | - Yanyun Wei
- National Key Laboratory of Science and Technology on Vacuum Electronics, School of Electronic Science and Engineering, University of Electronic Science and Technology of China, Chengdu, China
- Yanyun Wei
| | - XiaoYu Zhang
- College of Life Science, Sichuan Normal University, Chengdu, China
- XiaoYu Zhang
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