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Tan MS, Cheah PL, Chin AV, Looi LM, Chang SW. A multi-ethnic proteomic profiling analysis in Alzheimer's disease identifies the disparities in dysregulation of proteins and pathogenesis. PeerJ 2024; 12:e17643. [PMID: 39035156 PMCID: PMC11260413 DOI: 10.7717/peerj.17643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 06/06/2024] [Indexed: 07/23/2024] Open
Abstract
Background Alzheimer's disease (AD) is the most common type of dementia that affects the elderly population. Lately, blood-based proteomics have been intensively sought in the discovery of AD biomarkers studies due to the capability to link external environmental factors with the development of AD. Demographic differences have been shown to affect the expression of the proteins in different populations which play a vital role in the degeneration of cognitive function. Method In this study, a proteomic study focused on Malaysian Chinese and Malay prospects was conducted. Differentially expressed proteins (DEPs) in AD patients and normal controls for Chinese and Malays were identified. Functional enrichment analysis was conducted to further interpret the biological functions and pathways of the DEPs. In addition, a survey investigating behavioural practices among Chinese and Malay participants was conducted to support the results from the proteomic analysis. Result The variation of dysregulated proteins identified in Chinese and Malay samples suggested the disparities of pathways involved in this pathological condition for each respective ethnicity. Functional enrichment analysis supported this assumption in understanding the protein-protein interactions of the identified protein signatures and indicate that differentially expressed proteins identified from the Chinese group were significantly enriched with the functional terms related to Aβ/tau protein-related processes, oxidative stress and inflammation whereas neuroinflammation was associated with the Malay group. Besides that, a significant difference in sweet drinks/food intake habits between these two groups implies a relationship between sugar levels and the dysregulation of protein APOA4 in the Malay group. Additional meta-analysis further supported the dysregulation of proteins TF, AHSG, A1BG, APOA4 and C4A among AD groups. Conclusion These findings serve as a preliminary understanding in the molecular and demographic studies of AD in a multi-ethnic population.
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Affiliation(s)
- Mei Sze Tan
- Bioinformatics Programme, Institute of Biological Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Phaik-Leng Cheah
- Department of Pathology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Ai-Vyrn Chin
- Department of Medicine, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Lai-Meng Looi
- Department of Pathology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur, Malaysia
| | - Siow-Wee Chang
- Bioinformatics Programme, Institute of Biological Sciences, Faculty of Science, Universiti Malaya, Kuala Lumpur, Malaysia
- Centre of Research in System Biology, Structural, Bioinformatics and Human Digital Imaging (CRYSTAL), Universiti Malaya, Kuala Lumpur, Malaysia
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2
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Alvarado CX, Makarious MB, Weller CA, Vitale D, Koretsky MJ, Bandres-Ciga S, Iwaki H, Levine K, Singleton A, Faghri F, Nalls MA, Leonard HL. omicSynth: An open multi-omic community resource for identifying druggable targets across neurodegenerative diseases. Am J Hum Genet 2024; 111:150-164. [PMID: 38181731 PMCID: PMC10806756 DOI: 10.1016/j.ajhg.2023.12.006] [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: 07/19/2023] [Revised: 12/04/2023] [Accepted: 12/04/2023] [Indexed: 01/07/2024] Open
Abstract
Treatments for neurodegenerative disorders remain rare, but recent FDA approvals, such as lecanemab and aducanumab for Alzheimer disease (MIM: 607822), highlight the importance of the underlying biological mechanisms in driving discovery and creating disease modifying therapies. The global population is aging, driving an urgent need for therapeutics that stop disease progression and eliminate symptoms. In this study, we create an open framework and resource for evidence-based identification of therapeutic targets for neurodegenerative disease. We use summary-data-based Mendelian randomization to identify genetic targets for drug discovery and repurposing. In parallel, we provide mechanistic insights into disease processes and potential network-level consequences of gene-based therapeutics. We identify 116 Alzheimer disease, 3 amyotrophic lateral sclerosis (MIM: 105400), 5 Lewy body dementia (MIM: 127750), 46 Parkinson disease (MIM: 605909), and 9 progressive supranuclear palsy (MIM: 601104) target genes passing multiple test corrections (pSMR_multi < 2.95 × 10-6 and pHEIDI > 0.01). We created a therapeutic scheme to classify our identified target genes into strata based on druggability and approved therapeutics, classifying 41 novel targets, 3 known targets, and 115 difficult targets (of these, 69.8% are expressed in the disease-relevant cell type from single-nucleus experiments). Our novel class of genes provides a springboard for new opportunities in drug discovery, development, and repurposing in the pre-competitive space. In addition, looking at drug-gene interaction networks, we identify previous trials that may require further follow-up such as riluzole in Alzheimer disease. We also provide a user-friendly web platform to help users explore potential therapeutic targets for neurodegenerative diseases, decreasing activation energy for the community.
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Affiliation(s)
- Chelsea X Alvarado
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA
| | - Mary B Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA; Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK; UCL Movement Disorders Centre, University College London, London WC1N 3BG, UK
| | - Cory A Weller
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA
| | - Dan Vitale
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA
| | - Mathew J Koretsky
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
| | - Sara Bandres-Ciga
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
| | - Hirotaka Iwaki
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Kristin Levine
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA
| | - Andrew Singleton
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Faraz Faghri
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Mike A Nalls
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Hampton L Leonard
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA; Data Tecnica LLC, Washington, DC 20037, USA; Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA; German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany.
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3
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Alvarado CX, Makarious MB, Weller CA, Vitale D, Koretsky MJ, Bandres-Ciga S, Iwaki H, Levine K, Singleton A, Faghri F, Nalls MA, Leonard HL. omicSynth: an Open Multi-omic Community Resource for Identifying Druggable Targets across Neurodegenerative Diseases. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.06.23288266. [PMID: 37090611 PMCID: PMC10120805 DOI: 10.1101/2023.04.06.23288266] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Treatments for neurodegenerative disorders remain rare, although recent FDA approvals, such as Lecanemab and Aducanumab for Alzheimer's Disease, highlight the importance of the underlying biological mechanisms in driving discovery and creating disease modifying therapies. The global population is aging, driving an urgent need for therapeutics that stop disease progression and eliminate symptoms. In this study, we create an open framework and resource for evidence-based identification of therapeutic targets for neurodegenerative disease. We use Summary-data-based Mendelian Randomization to identify genetic targets for drug discovery and repurposing. In parallel, we provide mechanistic insights into disease processes and potential network-level consequences of gene-based therapeutics. We identify 116 Alzheimer's disease, 3 amyotrophic lateral sclerosis, 5 Lewy body dementia, 46 Parkinson's disease, and 9 Progressive supranuclear palsy target genes passing multiple test corrections (pSMR_multi < 2.95×10-6 and pHEIDI > 0.01). We created a therapeutic scheme to classify our identified target genes into strata based on druggability and approved therapeutics - classifying 41 novel targets, 3 known targets, and 115 difficult targets (of these 69.8% are expressed in the disease relevant cell type from single nucleus experiments). Our novel class of genes provides a springboard for new opportunities in drug discovery, development and repurposing in the pre-competitive space. In addition, looking at drug-gene interaction networks, we identify previous trials that may require further follow-up such as Riluzole in AD. We also provide a user-friendly web platform to help users explore potential therapeutic targets for neurodegenerative diseases, decreasing activation energy for the community [https://nih-card-ndd-smr-home-syboky.streamlit.app/].
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Affiliation(s)
- Chelsea X. Alvarado
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
| | - Mary B. Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London, UK, WC1N 3BG
- UCL Movement Disorders Centre, University College London, London, UK, WC1N 3BG
| | - Cory A. Weller
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
| | - Dan Vitale
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
| | - Mathew J. Koretsky
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Sara Bandres-Ciga
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Hirotaka Iwaki
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Kristin Levine
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
| | - Andrew Singleton
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Faraz Faghri
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Mike A. Nalls
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
| | - Hampton L. Leonard
- Center for Alzheimer’s and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, USA, 20814
- Data Tecnica International, Washington, DC, USA, 20037
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA, 20814
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
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4
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Prakash A, García-Seisdedos D, Wang S, Kundu DJ, Collins A, George N, Moreno P, Papatheodorou I, Jones AR, Vizcaíno JA. Integrated View of Baseline Protein Expression in Human Tissues. J Proteome Res 2023; 22:729-742. [PMID: 36577097 PMCID: PMC9990129 DOI: 10.1021/acs.jproteome.2c00406] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
The availability of proteomics datasets in the public domain, and in the PRIDE database, in particular, has increased dramatically in recent years. This unprecedented large-scale availability of data provides an opportunity for combined analyses of datasets to get organism-wide protein abundance data in a consistent manner. We have reanalyzed 24 public proteomics datasets from healthy human individuals to assess baseline protein abundance in 31 organs. We defined tissue as a distinct functional or structural region within an organ. Overall, the aggregated dataset contains 67 healthy tissues, corresponding to 3,119 mass spectrometry runs covering 498 samples from 489 individuals. We compared protein abundances between different organs and studied the distribution of proteins across these organs. We also compared the results with data generated in analogous studies. Additionally, we performed gene ontology and pathway-enrichment analyses to identify organ-specific enriched biological processes and pathways. As a key point, we have integrated the protein abundance results into the resource Expression Atlas, where they can be accessed and visualized either individually or together with gene expression data coming from transcriptomics datasets. We believe this is a good mechanism to make proteomics data more accessible for life scientists.
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Affiliation(s)
- Ananth Prakash
- European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CambridgeCB10 1SD, United Kingdom.,Open Targets, Wellcome Genome Campus, Hinxton, CambridgeCB10 1SD, United Kingdom
| | - David García-Seisdedos
- European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CambridgeCB10 1SD, United Kingdom
| | - Shengbo Wang
- European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CambridgeCB10 1SD, United Kingdom
| | - Deepti Jaiswal Kundu
- European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CambridgeCB10 1SD, United Kingdom
| | - Andrew Collins
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, LiverpoolL69 7ZB, United Kingdom
| | - Nancy George
- European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CambridgeCB10 1SD, United Kingdom
| | - Pablo Moreno
- European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CambridgeCB10 1SD, United Kingdom
| | - Irene Papatheodorou
- European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CambridgeCB10 1SD, United Kingdom.,Open Targets, Wellcome Genome Campus, Hinxton, CambridgeCB10 1SD, United Kingdom
| | - Andrew R Jones
- Institute of Systems, Molecular and Integrative Biology, University of Liverpool, LiverpoolL69 7ZB, United Kingdom
| | - Juan Antonio Vizcaíno
- European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, CambridgeCB10 1SD, United Kingdom.,Open Targets, Wellcome Genome Campus, Hinxton, CambridgeCB10 1SD, United Kingdom
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5
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Clark C, Rabl M, Dayon L, Popp J. The promise of multi-omics approaches to discover biological alterations with clinical relevance in Alzheimer's disease. Front Aging Neurosci 2022; 14:1065904. [PMID: 36570537 PMCID: PMC9768448 DOI: 10.3389/fnagi.2022.1065904] [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: 10/10/2022] [Accepted: 11/21/2022] [Indexed: 12/12/2022] Open
Abstract
Beyond the core features of Alzheimer's disease (AD) pathology, i.e. amyloid pathology, tau-related neurodegeneration and microglia response, multiple other molecular alterations and pathway dysregulations have been observed in AD. Their inter-individual variations, complex interactions and relevance for clinical manifestation and disease progression remain poorly understood, however. Heterogeneity at both pathophysiological and clinical levels complicates diagnosis, prognosis, treatment and drug design and testing. High-throughput "omics" comprise unbiased and untargeted data-driven methods which allow the exploration of a wide spectrum of disease-related changes at different endophenotype levels without focussing a priori on specific molecular pathways or molecules. Crucially, new methodological and statistical advances now allow for the integrative analysis of data resulting from multiple and different omics methods. These multi-omics approaches offer the unique advantage of providing a more comprehensive characterisation of the AD endophenotype and to capture molecular signatures and interactions spanning various biological levels. These new insights can then help decipher disease mechanisms more deeply. In this review, we describe the different multi-omics tools and approaches currently available and how they have been applied in AD research so far. We discuss how multi-omics can be used to explore molecular alterations related to core features of the AD pathologies and how they interact with comorbid pathological alterations. We further discuss whether the identified pathophysiological changes are relevant for the clinical manifestation of AD, in terms of both cognitive impairment and neuropsychiatric symptoms, and for clinical disease progression over time. Finally, we address the opportunities for multi-omics approaches to help discover novel biomarkers for diagnosis and monitoring of relevant pathophysiological processes, along with personalised intervention strategies in AD.
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Affiliation(s)
- Christopher Clark
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Zürich, Switzerland,Geriatric Psychiatry, University Hospital of Psychiatry Zürich, Zürich, Switzerland,*Correspondence: Christopher Clark,
| | - Miriam Rabl
- Geriatric Psychiatry, University Hospital of Psychiatry Zürich, Zürich, Switzerland,University of Lausanne, Lausanne, Switzerland
| | - Loïc Dayon
- Nestlé Institute of Food Safety and Analytical Sciences, Nestlé Research, Lausanne, Switzerland,Institut des Sciences et Ingénierie Chimiques, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Julius Popp
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Zürich, Switzerland,Geriatric Psychiatry, University Hospital of Psychiatry Zürich, Zürich, Switzerland,Old Age Psychiatry, Department of Psychiatry, Lausanne University Hospital, Lausanne, Switzerland
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Sáez ME. Omics in Clinical Practice: How Far Are We? Diagnostics (Basel) 2022; 12:diagnostics12071692. [PMID: 35885596 PMCID: PMC9316511 DOI: 10.3390/diagnostics12071692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 07/07/2022] [Accepted: 07/09/2022] [Indexed: 11/16/2022] Open
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7
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MOMIC: A Multi-Omics Pipeline for Data Analysis, Integration and Interpretation. APPLIED SCIENCES-BASEL 2022. [DOI: 10.3390/app12083987] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Background and Objectives: The burst of high-throughput omics technologies has given rise to a new era in systems biology, offering an unprecedented scenario for deriving meaningful biological knowledge through the integration of different layers of information. Methods: We have developed a new software tool, MOMIC, that guides the user through the application of different analysis on a wide range of omic data, from the independent single-omics analysis to the combination of heterogeneous data at different molecular levels. Results: The proposed pipeline is developed as a collection of Jupyter notebooks, easily editable, reproducible and well documented. It can be modified to accommodate new analysis workflows and data types. It is accessible via momic.us.es, and as a docker project available at github that can be locally installed. Conclusions: MOMIC offers a complete analysis environment for analysing and integrating multi-omics data in a single, easy-to-use platform.
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