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Rajendran K, Krishnan UM. Biomarkers in Alzheimer's disease. Clin Chim Acta 2024; 562:119857. [PMID: 38986861 DOI: 10.1016/j.cca.2024.119857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2024] [Revised: 07/05/2024] [Accepted: 07/06/2024] [Indexed: 07/12/2024]
Abstract
Alzheimer's disease (AD) is among the most common neurodegenerative disorders. AD is characterized by deposition of neurofibrillary tangles and amyloid plaques, leading to associated secondary pathologies, progressive neurodegeneration, and eventually death. Currently used diagnostics are largely image-based, lack accuracy and do not detect early disease, ie, prior to onset of symptoms, thus limiting treatment options and outcomes. Although biomarkers such as amyloid-β and tau protein in cerebrospinal fluid have gained much attention, these are generally limited to disease progression. Unfortunately, identification of biomarkers for early and accurate diagnosis remains a challenge. As such, body fluids such as sweat, serum, saliva, mucosa, tears, and urine are under investigation as alternative sources for biomarkers that can aid in early disease detection. This review focuses on biomarkers identified through proteomics in various biofluids and their potential for early and accurate diagnosis of AD.
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Affiliation(s)
- Kayalvizhi Rajendran
- Centre for Nanotechnology & Advanced Biomaterials, SASTRA Deemed University, Thanjavur, India; School of Chemical & Biotechnology, SASTRA Deemed University, Thanjavur, India
| | - Uma Maheswari Krishnan
- Centre for Nanotechnology & Advanced Biomaterials, SASTRA Deemed University, Thanjavur, India; School of Arts, Sciences, Humanities, & Education, SASTRA Deemed University, Thanjavur, India.
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Lalwani RC, Volmar CH, Wahlestedt C, Webster KA, Shehadeh LA. Contextualizing the Role of Osteopontin in the Inflammatory Responses of Alzheimer's Disease. Biomedicines 2023; 11:3232. [PMID: 38137453 PMCID: PMC10741223 DOI: 10.3390/biomedicines11123232] [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: 10/25/2023] [Revised: 12/01/2023] [Accepted: 12/03/2023] [Indexed: 12/24/2023] Open
Abstract
Alzheimer's disease (AD) is characterized by progressive accumulations of extracellular amyloid-beta (Aβ) aggregates from soluble oligomers to insoluble plaques and hyperphosphorylated intraneuronal tau, also from soluble oligomers to insoluble neurofibrillary tangles (NFTs). Tau and Aβ complexes spread from the entorhinal cortex of the brain to interconnected regions, where they bind pattern recognition receptors on microglia and astroglia to trigger inflammation and neurotoxicity that ultimately lead to neurodegeneration and clinical AD. Systemic inflammation is initiated by Aβ's egress into the circulation, which may be secondary to microglial activation and can confer both destructive and reparative actions. Microglial activation pathways and downstream drivers of Aβ/NFT neurotoxicity, including inflammatory regulators, are primary targets for AD therapy. Osteopontin (OPN), an inflammatory cytokine and biomarker of AD, is implicated in Aβ clearance and toxicity, microglial activation, and inflammation, and is considered to be a potential therapeutic target. Here, using the most relevant works from the literature, we review and contextualize the evidence for a central role of OPN and associated inflammation in AD.
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Affiliation(s)
- Roshni C. Lalwani
- Interdisciplinary Stem Cell Institute, Leonard M. Miller School of Medicine, University of Miami, Miami, FL 33136, USA;
| | - Claude-Henry Volmar
- Department of Psychiatry, Leonard M. Miller School of Medicine, University of Miami, Miami, FL 33136, USA; (C.-H.V.); (C.W.)
- Center for Therapeutic Innovation, Leonard M. Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Claes Wahlestedt
- Department of Psychiatry, Leonard M. Miller School of Medicine, University of Miami, Miami, FL 33136, USA; (C.-H.V.); (C.W.)
- Center for Therapeutic Innovation, Leonard M. Miller School of Medicine, University of Miami, Miami, FL 33136, USA
| | - Keith A. Webster
- Integene International Holdings, LLC, Miami, FL 33137, USA;
- Department of Ophthalmology, Baylor College of Medicine, Houston, TX 77030, USA
- Everglades BioPharma, Houston, TX 77098, USA
| | - Lina A. Shehadeh
- Interdisciplinary Stem Cell Institute, Leonard M. Miller School of Medicine, University of Miami, Miami, FL 33136, USA;
- Department of Medicine, Leonard M. Miller School of Medicine, University of Miami, Miami, FL 33136, USA
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3
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Winchester LM, Harshfield EL, Shi L, Badhwar A, Khleifat AA, Clarke N, Dehsarvi A, Lengyel I, Lourida I, Madan CR, Marzi SJ, Proitsi P, Rajkumar AP, Rittman T, Silajdžić E, Tamburin S, Ranson JM, Llewellyn DJ. Artificial intelligence for biomarker discovery in Alzheimer's disease and dementia. Alzheimers Dement 2023; 19:5860-5871. [PMID: 37654029 PMCID: PMC10840606 DOI: 10.1002/alz.13390] [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: 04/04/2023] [Revised: 06/13/2023] [Accepted: 06/19/2023] [Indexed: 09/02/2023]
Abstract
With the increase in large multimodal cohorts and high-throughput technologies, the potential for discovering novel biomarkers is no longer limited by data set size. Artificial intelligence (AI) and machine learning approaches have been developed to detect novel biomarkers and interactions in complex data sets. We discuss exemplar uses and evaluate current applications and limitations of AI to discover novel biomarkers. Remaining challenges include a lack of diversity in the data sets available, the sheer complexity of investigating interactions, the invasiveness and cost of some biomarkers, and poor reporting in some studies. Overcoming these challenges will involve collecting data from underrepresented populations, developing more powerful AI approaches, validating the use of noninvasive biomarkers, and adhering to reporting guidelines. By harnessing rich multimodal data through AI approaches and international collaborative innovation, we are well positioned to identify clinically useful biomarkers that are accurate, generalizable, unbiased, and acceptable in clinical practice. HIGHLIGHTS: Artificial intelligence and machine learning approaches may accelerate dementia biomarker discovery. Remaining challenges include data set suitability due to size and bias in cohort selection. Multimodal data, diverse data sets, improved machine learning approaches, real-world validation, and interdisciplinary collaboration are required.
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Affiliation(s)
| | - Eric L Harshfield
- Department of Clinical Neurosciences, Stroke Research Group, University of Cambridge, Cambridge, UK
| | - Liu Shi
- Novo Nordisk Research Centre Oxford (NNRCO), Headington, UK
| | - AmanPreet Badhwar
- Département de Pharmacologie et Physiologie, Institut de Génie Biomédical, Faculté de Médecine, Université de Montréal, Montreal, Canada
- Centre de recherche de l'Institut Universitaire de Gériatrie (CRIUGM), Montreal, Canada
| | - Ahmad Al Khleifat
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Natasha Clarke
- Centre de recherche de l'Institut Universitaire de Gériatrie (CRIUGM), Montreal, Canada
| | - Amir Dehsarvi
- School of Medicine, Medical Sciences, and Nutrition, University of Aberdeen, Aberdeen, UK
| | - Imre Lengyel
- Wellcome-Wolfson Institute of Experimental Medicine, Queen's University, Belfast, UK
| | - Ilianna Lourida
- Health and Community Sciences, University of Exeter Medical School, Exeter, UK
| | | | - Sarah J Marzi
- UK Dementia Research Institute at Imperial College London, London, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Petroula Proitsi
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Anto P Rajkumar
- Institute of Mental Health, Mental Health and Clinical Neurosciences academic unit, University of Nottingham, Nottingham, UK, Mental health services of older people, Nottinghamshire healthcare NHS foundation trust, Nottingham, UK
| | - Timothy Rittman
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK
| | - Edina Silajdžić
- Department of Basic and Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Stefano Tamburin
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Janice M Ranson
- Health and Community Sciences, University of Exeter Medical School, Exeter, UK
| | - David J Llewellyn
- Health and Community Sciences, University of Exeter Medical School, Exeter, UK
- The Alan Turing Institute, London, UK
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4
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Wang Y, Sun Y, Wang Y, Jia S, Qiao Y, Zhou Z, Shao W, Zhang X, Guo J, Zhang B, Niu X, Wang Y, Peng D. Identification of novel diagnostic panel for mild cognitive impairment and Alzheimer's disease: findings based on urine proteomics and machine learning. Alzheimers Res Ther 2023; 15:191. [PMID: 37925455 PMCID: PMC10625308 DOI: 10.1186/s13195-023-01324-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 10/04/2023] [Indexed: 11/06/2023]
Abstract
BACKGROUND Alzheimer's disease is a prevalent disease with a heavy global burden. Proteomics is the systematic study of proteins and peptides to provide comprehensive descriptions. Aiming to obtain a more accurate and convenient clinical diagnosis, researchers are working for better biomarkers. Urine is more convenient which could reflect the change of disease at an earlier stage. Thus, we conducted a cross-sectional study to investigate novel diagnostic panels. METHODS We firstly enrolled participants from China-Japan Friendship Hospital from April 2022 to November 2022, collected urine samples, and conducted an LC-MS/MS analysis. In parallel, clinical data were collected, and clinical examinations were performed. After statistical and bioinformatics analyses, significant risk factors and differential urinary proteins were determined. We attempt to investigate diagnostic panels based on machine learning including LASSO and SVM. RESULTS Fifty-seven AD patients, 43 MCI patients, and 62 CN subjects were enrolled. A total of 3366 proteins were identified, and 608 urine proteins were finally included in the analysis. There were 33 significantly differential proteins between the AD and CN groups and 15 significantly differential proteins between the MCI and CN groups. AD diagnostic panel included DDC, CTSC, EHD4, GSTA3, SLC44A4, GNS, GSTA1, ANXA4, PLD3, CTSH, HP, RPS3, CPVL, age, and APOE ε4 with an AUC of 0.9989 in the training test and 0.8824 in the test set while MCI diagnostic panel included TUBB, SUCLG2, PROCR, TCP1, ACE, FLOT2, EHD4, PROZ, C9, SERPINA3, age, and APOE ε4 with an AUC of 0.9985 in the training test and 0.8143 in the test set. Besides, diagnostic proteins were weakly correlated with cognitive functions. CONCLUSIONS In conclusion, the procedure is convenient, non-invasive, and useful for diagnosis, which could assist physicians in differentiating AD and MCI from CN.
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Affiliation(s)
- Yuye Wang
- China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Department of Neurology, China-Japan Friendship Hospital, Beijing, 100029, China
| | - Yu Sun
- Department of Neurology, China-Japan Friendship Hospital, Beijing, 100029, China
| | - Yu Wang
- Department of Neurology, China-Japan Friendship Hospital, Beijing, 100029, China
| | - Shuhong Jia
- Department of Neurology, China-Japan Friendship Hospital, Beijing, 100029, China
| | - Yanan Qiao
- Department of Neurology, China-Japan Friendship Hospital, Beijing, 100029, China
| | - Zhi Zhou
- Department of Neurology, China-Japan Friendship Hospital, Beijing, 100029, China
| | - Wen Shao
- Department of Neurology, China-Japan Friendship Hospital, Beijing, 100029, China
| | - Xiangfei Zhang
- Department of Neurology, China-Japan Friendship Hospital, Beijing, 100029, China
| | - Jing Guo
- Department of Neurology, China-Japan Friendship Hospital, Beijing, 100029, China
| | - Bin Zhang
- China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
- Department of Neurology, China-Japan Friendship Hospital, Beijing, 100029, China
| | - Xiaoqian Niu
- Department of Neurology, China-Japan Friendship Hospital, Beijing, 100029, China
- Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China
| | - Yi Wang
- State Key Laboratory of Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences (Beijing), Beijing Institute of Lifeomics, Beijing, 102206, China.
| | - Dantao Peng
- China-Japan Friendship Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
- Department of Neurology, China-Japan Friendship Hospital, Beijing, 100029, China.
- Peking University China-Japan Friendship School of Clinical Medicine, Beijing, China.
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Ye Q, Xu G, Xue C, Pang S, Xie B, Huang G, Li H, Chen X, Yang R, Li W. Urinary SPP1 has potential as a non-invasive diagnostic marker for focal segmental glomerulosclerosis. FEBS Open Bio 2023; 13:2061-2080. [PMID: 37696527 PMCID: PMC10626280 DOI: 10.1002/2211-5463.13704] [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: 06/06/2023] [Revised: 08/26/2023] [Accepted: 09/08/2023] [Indexed: 09/13/2023] Open
Abstract
Focal segmental glomerulosclerosis (FSGS) is a type of chronic glomerular nephropathy showing characteristic glomerular sclerosis, diagnosed by kidney biopsy. However, it is difficult and expensive to monitor disease progression with repeated renal biopsy in clinical practice, and thus here we explored the feasibility of urine biomarkers as non-invasive diagnostic tools. We downloaded scRNA-seq datasets of 20 urine cell samples and 3 kidney tissues and obtained two gene lists encoding extracellular proteins for bioinformatic analysis; in addition, we identified key EP-Genes by immunohistochemical staining and performed bulk RNA sequencing with 12 urine samples. We report that urine cells and kidney cells were correlated. A total of 64 EP-Genes were acquired by intersecting genes of distal tubular cluster with extracellular proteins. Function enrichment analysis showed that EP-Genes might be involved in the immune response and extracellular components. Six key EP-Genes were identified and correlated with renal function. IMC showed that key EP-Genes were located mainly in tubules. Cross verification and examination of a urine RNAseq dataset showed that SPP1 had diagnostic potential for FSGS. The presence of urine SPP1 was primarily associated with macrophage infiltration in kidney, and the pathogenesis of FSGS may be related to innate immunity. Urinary cells seemed to be strongly similar to kidney cells. In summary, SPP1 levels reflect renal function and may have potential as a biomarker for non-invasive diagnosis of FSGS.
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Affiliation(s)
- Qinglin Ye
- Department of NephrologyThe Second Affiliated Hospital of Guangxi Medical UniversityNanningChina
| | - Guiling Xu
- Department of NephrologyThe Second Affiliated Hospital of Guangxi Medical UniversityNanningChina
| | - Chao Xue
- Department of NephrologyThe Second Affiliated Hospital of Guangxi Medical UniversityNanningChina
| | - Shuting Pang
- Department of NephrologyThe Second Affiliated Hospital of Guangxi Medical UniversityNanningChina
| | - Boji Xie
- Department of NephrologyThe Second Affiliated Hospital of Guangxi Medical UniversityNanningChina
| | - Guanwen Huang
- Department of NephrologyThe Second Affiliated Hospital of Guangxi Medical UniversityNanningChina
| | - Haoyu Li
- Department of NephrologyThe Second Affiliated Hospital of Guangxi Medical UniversityNanningChina
| | - Xuesong Chen
- Department of NephrologyThe Second Affiliated Hospital of Guangxi Medical UniversityNanningChina
| | - Rirong Yang
- Centre for Genomic and Personalized MedicineDepartment of ImmunologySchool of Basic Medical SciencesGuangxi Medical UniversityNanning530021China
| | - Wei Li
- Department of NephrologyThe Second Affiliated Hospital of Guangxi Medical UniversityNanningChina
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O’Connor LM, O’Connor BA, Zeng J, Lo CH. Data Mining of Microarray Datasets in Translational Neuroscience. Brain Sci 2023; 13:1318. [PMID: 37759919 PMCID: PMC10527016 DOI: 10.3390/brainsci13091318] [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: 07/25/2023] [Revised: 09/04/2023] [Accepted: 09/10/2023] [Indexed: 09/29/2023] Open
Abstract
Data mining involves the computational analysis of a plethora of publicly available datasets to generate new hypotheses that can be further validated by experiments for the improved understanding of the pathogenesis of neurodegenerative diseases. Although the number of sequencing datasets is on the rise, microarray analysis conducted on diverse biological samples represent a large collection of datasets with multiple web-based programs that enable efficient and convenient data analysis. In this review, we first discuss the selection of biological samples associated with neurological disorders, and the possibility of a combination of datasets, from various types of samples, to conduct an integrated analysis in order to achieve a holistic understanding of the alterations in the examined biological system. We then summarize key approaches and studies that have made use of the data mining of microarray datasets to obtain insights into translational neuroscience applications, including biomarker discovery, therapeutic development, and the elucidation of the pathogenic mechanisms of neurodegenerative diseases. We further discuss the gap to be bridged between microarray and sequencing studies to improve the utilization and combination of different types of datasets, together with experimental validation, for more comprehensive analyses. We conclude by providing future perspectives on integrating multi-omics, to advance precision phenotyping and personalized medicine for neurodegenerative diseases.
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Affiliation(s)
- Lance M. O’Connor
- College of Biological Sciences, University of Minnesota, Minneapolis, MN 55455, USA;
| | - Blake A. O’Connor
- School of Pharmacy, University of Wisconsin, Madison, WI 53705, USA;
| | - Jialiu Zeng
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore;
| | - Chih Hung Lo
- Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore 308232, Singapore;
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7
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Hällqvist J, Pinto RC, Heywood WE, Cordey J, Foulkes AJM, Slattery CF, Leckey CA, Murphy EC, Zetterberg H, Schott JM, Mills K, Paterson RW. A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer's Disease Diagnosis Using Targeted Proteomics and Machine Learning. Int J Mol Sci 2023; 24:13758. [PMID: 37762058 PMCID: PMC10531486 DOI: 10.3390/ijms241813758] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 08/24/2023] [Accepted: 08/28/2023] [Indexed: 09/29/2023] Open
Abstract
As disease-modifying therapies are now available for Alzheimer's disease (AD), accessible, accurate and affordable biomarkers to support diagnosis are urgently needed. We sought to develop a mass spectrometry-based urine test as a high-throughput screening tool for diagnosing AD. We collected urine from a discovery cohort (n = 11) of well-characterised individuals with AD (n = 6) and their asymptomatic, CSF biomarker-negative study partners (n = 5) and used untargeted proteomics for biomarker discovery. Protein biomarkers identified were taken forward to develop a high-throughput, multiplexed and targeted proteomic assay which was tested on an independent cohort (n = 21). The panel of proteins identified are known to be involved in AD pathogenesis. In comparing AD and controls, a panel of proteins including MIEN1, TNFB, VCAM1, REG1B and ABCA7 had a classification accuracy of 86%. These proteins have been previously implicated in AD pathogenesis. This suggests that urine-targeted mass spectrometry has potential utility as a diagnostic screening tool in AD.
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Affiliation(s)
- Jenny Hällqvist
- Translational Mass Spectrometry Research Group, Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; (J.H.); (K.M.)
| | - Rui C. Pinto
- Faculty of Medicine, School of Public Health, Imperial College London, London SW7 2BX, UK
| | - Wendy E. Heywood
- Translational Mass Spectrometry Research Group, Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; (J.H.); (K.M.)
| | - Jonjo Cordey
- Translational Mass Spectrometry Research Group, Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; (J.H.); (K.M.)
| | | | | | - Claire A. Leckey
- Translational Mass Spectrometry Research Group, Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; (J.H.); (K.M.)
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Eimear C. Murphy
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, S-431 80 Mölndal, Sweden
- UK Dementia Research Institute, UCL, London WC1E 6BT, UK
| | - Jonathan M. Schott
- National Hospital for Neurology and Neurosurgery, Queen Square London, London WC1N 3BG, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Kevin Mills
- Translational Mass Spectrometry Research Group, Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; (J.H.); (K.M.)
| | - Ross W. Paterson
- National Hospital for Neurology and Neurosurgery, Queen Square London, London WC1N 3BG, UK
- Darent Valley Hospital, Dartford DA2 8DA, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, S-431 80 Mölndal, Sweden
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8
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Pistollato F, Campia I, Daskalopoulos EP, Bernasconi C, Desaintes C, Di Virgilio S, Kyriakopoulou C, Whelan M, Deceuninck P. Gauging innovation and health impact from biomedical research: survey results and interviews with recipients of EU-funding in the fields of Alzheimer's disease, breast cancer and prostate cancer. Health Res Policy Syst 2023; 21:66. [PMID: 37386455 DOI: 10.1186/s12961-023-00981-z] [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: 10/03/2022] [Accepted: 04/05/2023] [Indexed: 07/01/2023] Open
Abstract
Biomedical research on Alzheimer's disease (AD), breast cancer (BC) and prostate cancer (PC) has globally improved our understanding of the etiopathological mechanisms underlying the onset of these diseases, often with the goal to identify associated genetic and environmental risk factors and develop new medicines. However, the prevalence of these diseases and failure rate in drug development remain high. Being able to retrospectively monitor the major scientific breakthroughs and impact of such investment endeavors is important to re-address funding strategies if and when needed. The EU has supported research into those diseases via its successive framework programmes for research, technological development and innovation. The European Commission (EC) has already undertaken several activities to monitor research impact. As an additional contribution, the EC Joint Research Centre (JRC) launched in 2020 a survey addressed to former and current participants of EU-funded research projects in the fields of AD, BC and PC, with the aim to understand how EU-funded research has contributed to scientific innovation and societal impact, and how the selection of the experimental models may have underpinned the advances made. Further feedback was also gathered through in-depth interviews with some selected survey participants representative of the diverse pre-clinical models used in the EU-funded projects. A comprehensive analysis of survey replies, complemented with the information derived from the interviews, has recently been published in a Synopsis report. Here we discuss the main findings of this analysis and propose a set of priority actions that could be considered to help improving the translation of scientific innovation of biomedical research into societal impact.
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Affiliation(s)
- Francesca Pistollato
- European Commission, Joint Research Centre (JRC), Directorate F-Health, Consumers and Reference Materials, Via E. Fermi 2749, 21027, Ispra, VA, Italy
| | - Ivana Campia
- European Commission, Joint Research Centre (JRC), Directorate F-Health, Consumers and Reference Materials, Via E. Fermi 2749, 21027, Ispra, VA, Italy
| | - Evangelos P Daskalopoulos
- European Commission, Joint Research Centre (JRC), Directorate F-Health, Consumers and Reference Materials, Via E. Fermi 2749, 21027, Ispra, VA, Italy
| | - Camilla Bernasconi
- European Commission, Joint Research Centre (JRC), Directorate F-Health, Consumers and Reference Materials, Via E. Fermi 2749, 21027, Ispra, VA, Italy
| | | | - Sergio Di Virgilio
- European Commission, DG Research & Innovation (DG RTD), Brussels, Belgium
| | | | - Maurice Whelan
- European Commission, Joint Research Centre (JRC), Directorate F-Health, Consumers and Reference Materials, Via E. Fermi 2749, 21027, Ispra, VA, Italy
| | - Pierre Deceuninck
- European Commission, Joint Research Centre (JRC), Directorate F-Health, Consumers and Reference Materials, Via E. Fermi 2749, 21027, Ispra, VA, Italy.
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9
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Baldan-Martin M, Chaparro M, Gisbert JP. Systematic Review: Urine Biomarker Discovery for Inflammatory Bowel Disease Diagnosis. Int J Mol Sci 2023; 24:10159. [PMID: 37373307 DOI: 10.3390/ijms241210159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 06/12/2023] [Accepted: 06/13/2023] [Indexed: 06/29/2023] Open
Abstract
Inflammatory bowel diseases (IBDs) are chronic, heterogeneous, and inflammatory conditions mainly affecting the gastrointestinal tract. Currently, endoscopy is the gold standard test for assessing mucosal activity and healing in clinical practice; however, it is a costly, time-consuming, invasive, and uncomfortable procedure for the patients. Therefore, there is an urgent need for sensitive, specific, fast and non-invasive biomarkers for the diagnosis of IBD in medical research. Urine is an excellent biofluid for discovering biomarkers because it is non-invasive to sample. In this review, we aimed to summarize proteomics and metabolomics studies performed in both animal models of IBD and humans that identify urinary biomarkers for IBD diagnosis. Future large-scale multi-omics studies should be conducted in collaboration with clinicians, researchers, and industry to make progress toward the development of sensitive and specific diagnostic biomarkers, thereby making personalized medicine possible.
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Affiliation(s)
- Montse Baldan-Martin
- Gastroenterology Unit, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria Princesa (IIS-Princesa), Universidad Autónoma de Madrid, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), 28006 Madrid, Spain
| | - María Chaparro
- Gastroenterology Unit, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria Princesa (IIS-Princesa), Universidad Autónoma de Madrid, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), 28006 Madrid, Spain
| | - Javier P Gisbert
- Gastroenterology Unit, Hospital Universitario de La Princesa, Instituto de Investigación Sanitaria Princesa (IIS-Princesa), Universidad Autónoma de Madrid, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), 28006 Madrid, Spain
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10
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Sequeira-Antunes B, Ferreira HA. Urinary Biomarkers and Point-of-Care Urinalysis Devices for Early Diagnosis and Management of Disease: A Review. Biomedicines 2023; 11:biomedicines11041051. [PMID: 37189669 DOI: 10.3390/biomedicines11041051] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Revised: 03/10/2023] [Accepted: 03/27/2023] [Indexed: 03/31/2023] Open
Abstract
Biosensing and microfluidics technologies are transforming diagnostic medicine by accurately detecting biomolecules in biological samples. Urine is a promising biological fluid for diagnostics due to its noninvasive collection and wide range of diagnostic biomarkers. Point-of-care urinalysis, which integrates biosensing and microfluidics, has the potential to bring affordable and rapid diagnostics into the home to continuing monitoring, but challenges still remain. As such, this review aims to provide an overview of biomarkers that are or could be used to diagnose and monitor diseases, including cancer, cardiovascular diseases, kidney diseases, and neurodegenerative disorders, such as Alzheimer’s disease. Additionally, the different materials and techniques for the fabrication of microfluidic structures along with the biosensing technologies often used to detect and quantify biological molecules and organisms are reviewed. Ultimately, this review discusses the current state of point-of-care urinalysis devices and highlights the potential of these technologies to improve patient outcomes. Traditional point-of-care urinalysis devices require the manual collection of urine, which may be unpleasant, cumbersome, or prone to errors. To overcome this issue, the toilet itself can be used as an alternative specimen collection and urinalysis device. This review then presents several smart toilet systems and incorporated sanitary devices for this purpose.
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11
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Watanabe Y, Hirao Y, Kasuga K, Kitamura K, Nakamura K, Yamamoto T. Urinary proteome profiles associated with cognitive decline in community elderly residents—A pilot study. Front Neurol 2023; 14:1134976. [PMID: 37006491 PMCID: PMC10061132 DOI: 10.3389/fneur.2023.1134976] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2022] [Accepted: 02/27/2023] [Indexed: 03/18/2023] Open
Abstract
Non-invasive and simple methods enabling easy identification of individuals at high risk of cognitive decline are needed as preventive measures against dementia. This pilot study aimed to explore protein biomarkers that can predict cognitive decline using urine, which can be collected non-invasively. Study subjects were selected from participants in a cohort study of middle-aged and older community-dwelling adults who underwent cognitive testing using the Mini-Mental State Examination and provided spot urine samples at two time points with an interval of approximately 5 years. Seven participants whose cognitive function declined 4 or more points from baseline (Group D) and 7 sex- and age-matched participants whose cognitive function remained within the normal range during the same period (Group M) were selected. Urinary proteomics using mass spectrometry was performed and discriminant models were created using orthogonal partial least squares-discriminant analysis (OPLS-DA). OPLS-DA yielded two models that significantly discriminated between the two groups at baseline and follow-up. Both models had ORM1, ORM2, and SERPINA3 in common. A further OPLS-DA model using baseline ORM1, ORM2, and SERPINA3 data showed similar predictive performance for data at follow-up as it did for baseline data (sensitivity: 0.85, specificity: 0.85), with the receiver operating characteristic curve analysis yielding an area under the curve of 0.878. This prospective study demonstrated the potential for using urine to identify biomarkers of cognitive decline.
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Affiliation(s)
- Yumi Watanabe
- Division of Preventive Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
- *Correspondence: Yumi Watanabe
| | - Yoshitoshi Hirao
- Biofluid and Biomarker Center, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
| | - Kensaku Kasuga
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Kaori Kitamura
- Division of Preventive Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Kazutoshi Nakamura
- Division of Preventive Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Tadashi Yamamoto
- Biofluid and Biomarker Center, Graduate School of Medical and Dental Sciences, Niigata University, Niigata, Japan
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12
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Sharma V, Nikolajeff F, Kumar S. Employing nanoparticle tracking analysis of salivary neuronal exosomes for early detection of neurodegenerative diseases. Transl Neurodegener 2023; 12:7. [PMID: 36747288 PMCID: PMC9903484 DOI: 10.1186/s40035-023-00339-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 01/23/2023] [Indexed: 02/08/2023] Open
Abstract
Neurodegenerative diseases are a set of progressive and currently incurable diseases that are primarily caused by neuron degeneration. Neurodegenerative diseases often lead to cognitive impairment and dyskinesias. It is now well recognized that molecular events precede the onset of clinical symptoms by years. Over the past decade, intensive research attempts have been aimed at the early diagnosis of these diseases. Recently, exosomes have been shown to play a pivotal role in the occurrence and progression of many diseases including cancer and neurodegenerative diseases. Additionally, because exosomes can cross the blood-brain barrier, they may serve as a diagnostic tool for neural dysfunction. In this review, we detail the mechanisms and current challenges of these diseases, briefly review the role of exosomes in the progression of neurodegenerative diseases, and propose a novel strategy based on salivary neuronal exosomes and nanoparticle tracking analysis that could be employed for screening the early onset of neurodegenerative diseases.
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Affiliation(s)
- Vaibhav Sharma
- Department of Health, Education and Technology, Lulea University of Technology, Lulea, Sweden.
| | - Fredrik Nikolajeff
- grid.6926.b0000 0001 1014 8699Department of Health, Education and Technology, Lulea University of Technology, Lulea, Sweden
| | - Saroj Kumar
- Department of Health, Education and Technology, Lulea University of Technology, Lulea, Sweden. .,Department of Biophysics, All India Institute of Medical Sciences, New Delhi, India.
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13
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Ramesh M, Govindaraju T. Multipronged diagnostic and therapeutic strategies for Alzheimer's disease. Chem Sci 2022; 13:13657-13689. [PMID: 36544728 PMCID: PMC9710308 DOI: 10.1039/d2sc03932j] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 10/13/2022] [Indexed: 12/24/2022] Open
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder and a major contributor to dementia cases worldwide. AD is clinically characterized by learning, memory, and cognitive deficits. The accumulation of extracellular amyloid β (Aβ) plaques and neurofibrillary tangles (NFTs) of tau are the pathological hallmarks of AD and are explored as targets for clinical diagnosis and therapy. AD pathology is poorly understood and there are no fully approved diagnosis and treatments. Notwithstanding the gap, decades of research in understanding disease mechanisms have revealed the multifactorial nature of AD. As a result, multipronged and holistic approaches are pertinent to targeting multiple biomarkers and targets for developing effective diagnosis and therapeutics. In this perspective, recent developments in Aβ and tau targeted diagnostic and therapeutic tools are discussed. Novel indirect, combination, and circulating biomarkers as potential diagnostic targets are highlighted. We underline the importance of multiplexing and multimodal detection of multiple biomarkers to generate biomarker fingerprints as a reliable diagnostic strategy. The classical therapeutics targeting Aβ and tau aggregation pathways are described with bottlenecks in the strategy. Drug discovery efforts targeting multifaceted toxicity involving protein aggregation, metal toxicity, oxidative stress, mitochondrial damage, and neuroinflammation are highlighted. Recent efforts focused on multipronged strategies to rationally design multifunctional modulators targeting multiple pathological factors are presented as future drug development strategies to discover potential therapeutics for AD.
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Affiliation(s)
- Madhu Ramesh
- Bioorganic Chemistry Laboratory, New Chemistry Unit, Jawaharlal Nehru Centre for Advanced Scientific Research Jakkur P.O. Bengaluru Karnataka 560064 India
| | - Thimmaiah Govindaraju
- Bioorganic Chemistry Laboratory, New Chemistry Unit, Jawaharlal Nehru Centre for Advanced Scientific Research Jakkur P.O. Bengaluru Karnataka 560064 India
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14
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Gong X, Zhang H, Liu X, Liu Y, Liu J, Fapohunda FO, Lü P, Wang K, Tang M. Is liquid biopsy mature enough for the diagnosis of Alzheimer's disease? Front Aging Neurosci 2022; 14:977999. [PMID: 35992602 PMCID: PMC9389010 DOI: 10.3389/fnagi.2022.977999] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2022] [Accepted: 07/18/2022] [Indexed: 01/10/2023] Open
Abstract
The preclinical diagnosis and clinical practice for Alzheimer's disease (AD) based on liquid biopsy have made great progress in recent years. As liquid biopsy is a fast, low-cost, and easy way to get the phase of AD, continual efforts from intense multidisciplinary studies have been made to move the research tools to routine clinical diagnostics. On one hand, technological breakthroughs have brought new detection methods to the outputs of liquid biopsy to stratify AD cases, resulting in higher accuracy and efficiency of diagnosis. On the other hand, diversiform biofluid biomarkers derived from cerebrospinal fluid (CSF), blood, urine, Saliva, and exosome were screened out and biologically verified. As a result, more detailed knowledge about the molecular pathogenesis of AD was discovered and elucidated. However, to date, how to weigh the reports derived from liquid biopsy for preclinical AD diagnosis is an ongoing question. In this review, we briefly introduce liquid biopsy and the role it plays in research and clinical practice. Then, we summarize the established fluid-based assays of the current state for AD diagnostic such as ELISA, single-molecule array (Simoa), Immunoprecipitation-Mass Spectrometry (IP-MS), liquid chromatography-MS, immunomagnetic reduction (IMR), multimer detection system (MDS). In addition, we give an updated list of fluid biomarkers in the AD research field. Lastly, the current outstanding challenges and the feasibility to use a stand-alone biomarker in the joint diagnostic strategy are discussed.
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Affiliation(s)
- Xun Gong
- Department of Rheumatology and Immunology, Affiliated Hospital of Jiangsu University, Zhenjiang, China
| | - Hantao Zhang
- School of Life Sciences, Jiangsu University, Zhenjiang, China
| | - Xiaoyan Liu
- School of Life Sciences, Jiangsu University, Zhenjiang, China
| | - Yi Liu
- School of Life Sciences, Jiangsu University, Zhenjiang, China
- Institute of Animal Husbandry, Jiangsu Academy of Agricultural Sciences, Nanjing, China
| | - Junlin Liu
- School of Life Sciences, Jiangsu University, Zhenjiang, China
| | | | - Peng Lü
- School of Life Sciences, Jiangsu University, Zhenjiang, China
| | - Kun Wang
- Children’s Center, The Affiliated Taian City Central Hospital of Qingdao University, Taian, China
| | - Min Tang
- School of Life Sciences, Jiangsu University, Zhenjiang, China
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15
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Non-Invasive Nasal Discharge Fluid and Other Body Fluid Biomarkers in Alzheimer’s Disease. Pharmaceutics 2022; 14:pharmaceutics14081532. [PMID: 35893788 PMCID: PMC9330777 DOI: 10.3390/pharmaceutics14081532] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/12/2022] [Accepted: 07/19/2022] [Indexed: 02/04/2023] Open
Abstract
The key to current Alzheimer’s disease (AD) therapy is the early diagnosis for prompt intervention, since available treatments only slow the disease progression. Therefore, this lack of promising therapies has called for diagnostic screening tests to identify those likely to develop full-blown AD. Recent AD diagnosis guidelines incorporated core biomarker analyses into criteria, including amyloid-β (Aβ), total-tau (T-tau), and phosphorylated tau (P-tau). Though effective, the accessibility of screening tests involving conventional cerebrospinal fluid (CSF)- and blood-based analyses is often hindered by the invasiveness and high cost. In an attempt to overcome these shortcomings, biomarker profiling research using non-invasive body fluid has shown the potential to capture the pathological changes in the patients’ bodies. These novel non-invasive body fluid biomarkers for AD have emerged as diagnostic and pathological targets. Here, we review the potential peripheral biomarkers, including non-invasive peripheral body fluids of nasal discharge, tear, saliva, and urine for AD.
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16
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Faldu KG, Shah JS. Alzheimer's disease: a scoping review of biomarker research and development for effective disease diagnosis. Expert Rev Mol Diagn 2022; 22:681-703. [PMID: 35855631 DOI: 10.1080/14737159.2022.2104639] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Alzheimer's disease (AD) is regarded as the foremost reason for neurodegeneration that prominently affects the geriatric population. Characterized by extracellular accumulation of amyloid-beta (Aβ), intracellular aggregation of hyperphosphorylated tau (p-tau), and neuronal degeneration that causes impairment of memory and cognition. Amyloid/tau/neurodegeneration (ATN) classification is utilized for research purposes and involves amyloid, tau, and neuronal injury staging through MRI, PET scanning, and CSF protein concentration estimations. CSF sampling is invasive, and MRI and PET scanning requires sophisticated radiological facilities which limit its widespread diagnostic use. ATN classification lacks effectiveness in preclinical AD. AREAS COVERED This publication intends to collate and review the existing biomarker profile and the current research and development of a new arsenal of biomarkers for AD pathology from different biological samples, microRNA (miRNA), proteomics, metabolomics, artificial intelligence, and machine learning for AD screening, diagnosis, prognosis, and monitoring of AD treatments. EXPERT OPINION It is an accepted observation that AD-related pathological changes occur over a long period of time before the first symptoms are observed providing ample opportunity for detection of biological alterations in various biological samples that can aid in early diagnosis and modify treatment outcomes.
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Affiliation(s)
- Khushboo Govind Faldu
- Department of Pharmacology, Institute of Pharmacy, Nirma University, Ahmedabad, Gujarat, India
| | - Jigna Samir Shah
- Department of Pharmacology, Institute of Pharmacy, Nirma University, Ahmedabad, Gujarat, India
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17
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Sarafidis M, Lambrou GI, Zoumpourlis V, Koutsouris D. An Integrated Bioinformatics Analysis towards the Identification of Diagnostic, Prognostic, and Predictive Key Biomarkers for Urinary Bladder Cancer. Cancers (Basel) 2022; 14:cancers14143358. [PMID: 35884419 PMCID: PMC9319344 DOI: 10.3390/cancers14143358] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 07/03/2022] [Accepted: 07/06/2022] [Indexed: 02/04/2023] Open
Abstract
Simple Summary Bladder cancer is evidently a challenge as far as its prognosis and treatment are concerned. The investigation of potential biomarkers and therapeutic targets is indispensable and still in progress. Most studies attempt to identify differential signatures between distinct molecular tumor subtypes. Therefore, keeping in mind the heterogeneity of urinary bladder tumors, we attempted to identify a consensus gene-related signature between the common expression profile of bladder cancer and control samples. In the quest for substantive features, we were able to identify key hub genes, whose signatures could hold diagnostic, prognostic, or therapeutic significance, but, primarily, could contribute to a better understanding of urinary bladder cancer biology. Abstract Bladder cancer (BCa) is one of the most prevalent cancers worldwide and accounts for high morbidity and mortality. This study intended to elucidate potential key biomarkers related to the occurrence, development, and prognosis of BCa through an integrated bioinformatics analysis. In this context, a systematic meta-analysis, integrating 18 microarray gene expression datasets from the GEO repository into a merged meta-dataset, identified 815 robust differentially expressed genes (DEGs). The key hub genes resulted from DEG-based protein–protein interaction and weighted gene co-expression network analyses were screened for their differential expression in urine and blood plasma samples of BCa patients. Subsequently, they were tested for their prognostic value, and a three-gene signature model, including COL3A1, FOXM1, and PLK4, was built. In addition, they were tested for their predictive value regarding muscle-invasive BCa patients’ response to neoadjuvant chemotherapy. A six-gene signature model, including ANXA5, CD44, NCAM1, SPP1, CDCA8, and KIF14, was developed. In conclusion, this study identified nine key biomarker genes, namely ANXA5, CDT1, COL3A1, SPP1, VEGFA, CDCA8, HJURP, TOP2A, and COL6A1, which were differentially expressed in urine or blood of BCa patients, held a prognostic or predictive value, and were immunohistochemically validated. These biomarkers may be of significance as prognostic and therapeutic targets for BCa.
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Affiliation(s)
- Michail Sarafidis
- Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou Str., 15780 Athens, Greece;
- Correspondence: ; Tel.: +30-210-772-2430
| | - George I. Lambrou
- Choremeio Research Laboratory, First Department of Pediatrics, National and Kapodistrian University of Athens, 8 Thivon & Levadeias Str., 11527 Athens, Greece;
- University Research Institute of Maternal and Child Health and Precision Medicine, National and Kapodistrian University of Athens, 8 Thivon & Levadeias Str., 11527 Athens, Greece
| | - Vassilis Zoumpourlis
- Biomedical Applications Unit, Institute of Chemical Biology, National Hellenic Research Foundation, 48 Vas. Konstantinou Ave., 11635 Athens, Greece;
| | - Dimitrios Koutsouris
- Biomedical Engineering Laboratory, School of Electrical and Computer Engineering, National Technical University of Athens, 9 Iroon Polytechniou Str., 15780 Athens, Greece;
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18
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Pomilio AB, Vitale AA, Lazarowski AJ. Uncommon Noninvasive Biomarkers for the Evaluation and Monitoring of the Etiopathogenesis of Alzheimer's Disease. Curr Pharm Des 2022; 28:1152-1169. [DOI: 10.2174/1381612828666220413101929] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2021] [Accepted: 02/25/2022] [Indexed: 11/22/2022]
Abstract
Background:
Alzheimer´s disease (AD) is the most widespread dementia in the world, followed by vascular dementia. Since AD is a heterogeneous disease that shows several varied phenotypes, it is not easy to make an accurate diagnosis, so it arises when the symptoms are clear and the disease is already very advanced. Therefore, it is important to find out biomarkers for AD early diagnosis that facilitate treatment or slow down the disease. Classic biomarkers are obtained from cerebrospinal fluid and plasma, along with brain imaging by positron emission tomography. Attempts have been made to discover uncommon biomarkers from other body fluids, which are addressed in this update.
Objective:
This update aims to describe recent biomarkers from minimally invasive body fluids for the patients, such as saliva, urine, eye fluid or tears.
Methods:
Biomarkers were determined in patients versus controls by single tandem mass spectrometry, and immunoassays. Metabolites were identified by nuclear magnetic resonance, and microRNAs with genome-wide high-throughput real-time polymerase chain reaction-based platforms.
Results:
Biomarkers from urine, saliva, and eye fluid were described, including peptides/proteins, metabolites, and some microRNAs. The association with AD neuroinflammation and neurodegeneration was analyzed, highlighting the contribution of matrix metalloproteinases, the immune system and microglia, as well as the vascular system.
Conclusion:
Unusual biomarkers have been developed, which distinguish each stage and progression of the disease, and are suitable for the early AD diagnosis. An outstanding relationship of biomarkers with neuroinflammation and neurodegeneration was assessed, clearing up concerns of the etiopathogenesis of AD.
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Affiliation(s)
- Alicia B. Pomilio
- Departamento de Bioquímica Clínica, Área Hematología, Hospital de Clínicas “José de San Martín”, Universidad de Buenos Aires, Av. Córdoba 2351, C1120AAF Buenos Aires, Argentina
| | - Arturo A. Vitale
- Departamento de Bioquímica Clínica, Área Hematología, Hospital de Clínicas “José de San Martín”, Universidad de Buenos Aires, Av. Córdoba 2351, C1120AAF Buenos Aires, Argentina
| | - Alberto J. Lazarowski
- Departamento de Bioquímica Clínica, Facultad de Farmacia y Bioquímica, Instituto de Fisiopatología y Bioquímica Clínica (INFIBIOC), Universidad de Buenos Aires, Córdoba 2351, C1120AAF Buenos Aires, Argentina
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Lindbohm JV, Mars N, Walker KA, Singh‐Manoux A, Livingston G, Brunner EJ, Sipilä PN, Saksela K, Ferrie JE, Lovering RC, Williams SA, Hingorani AD, Gottesman RF, Zetterberg H, Kivimäki M. Plasma proteins, cognitive decline, and 20-year risk of dementia in the Whitehall II and Atherosclerosis Risk in Communities studies. Alzheimers Dement 2022; 18:612-624. [PMID: 34338426 PMCID: PMC9292245 DOI: 10.1002/alz.12419] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2021] [Revised: 05/21/2021] [Accepted: 06/09/2021] [Indexed: 11/20/2022]
Abstract
INTRODUCTION Plasma proteins affect biological processes and are common drug targets but their role in the development of Alzheimer's disease and related dementias remains unclear. We examined associations between 4953 plasma proteins and cognitive decline and risk of dementia in two cohort studies with 20-year follow-ups. METHODS In the Whitehall II prospective cohort study proteins were measured using SOMAscan technology. Cognitive performance was tested five times over 20 years. Linkage to electronic health records identified incident dementia. The results were replicated in the Atherosclerosis Risk in Communities (ARIC) study. RESULTS Fifteen non-amyloid/non-tau-related proteins were associated with cognitive decline and dementia, were consistently identified in both cohorts, and were not explained by known dementia risk factors. Levels of six of the proteins are modifiable by currently approved medications for other conditions. DISCUSSION This study identified several plasma proteins in dementia-free people that are associated with long-term risk of cognitive decline and dementia.
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Affiliation(s)
- Joni V. Lindbohm
- Department of Epidemiology and Public HealthUniversity College LondonLondonUK
- Department of Public Health ClinicumUniversity of HelsinkiHelsinkiFinland
| | - Nina Mars
- Institute for Molecular Medicine Finland (FIMM) HiLIFEUniversity of HelsinkiHelsinkiFinland
| | - Keenan A. Walker
- Laboratory of Behavioral NeuroscienceIntramural Research ProgramNational Institute on AgingBaltimoreMarylandUSA
| | - Archana Singh‐Manoux
- Department of Epidemiology and Public HealthUniversity College LondonLondonUK
- Epidemiology of Ageing and Neurodegenerative diseasesUniversité de ParisParisFrance
| | - Gill Livingston
- Division of PsychiatryUniversity College LondonLondonUK
- Camden and Islington Foundation TrustLondonUK
| | - Eric J. Brunner
- Department of Epidemiology and Public HealthUniversity College LondonLondonUK
| | - Pyry N. Sipilä
- Department of Public Health ClinicumUniversity of HelsinkiHelsinkiFinland
| | - Kalle Saksela
- Department of VirologyUniversity of Helsinki and HUSLAB, Helsinki University HospitalHelsinkiFinland
| | - Jane E. Ferrie
- Department of Epidemiology and Public HealthUniversity College LondonLondonUK
- Bristol Medical School (PHS)University of BristolBristolUK
| | - Ruth C. Lovering
- Functional Gene AnnotationInstitute of Cardiovascular ScienceUniversity College LondonLondonUK
| | | | - Aroon D. Hingorani
- Institute of Cardiovascular ScienceUniversity College LondonLondonUK
- British Heart Foundation Research AcceleratorUniversity College LondonLondonUK
- Health Data ResearchLondonUK
| | | | - Henrik Zetterberg
- Department of Neurodegenerative Disease and UK Dementia Research InstituteUniversity College LondonLondonUK
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologyThe Sahlgrenska AcademyUniversity of GothenburgGothenburgSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Mika Kivimäki
- Department of Epidemiology and Public HealthUniversity College LondonLondonUK
- Department of Public Health ClinicumUniversity of HelsinkiHelsinkiFinland
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20
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Nam D, Lee JY, Lee M, Kim J, Seol W, Son I, Ho DH. Detection and Assessment of α-Synuclein Oligomers in the Urine of Parkinson's Disease Patients. JOURNAL OF PARKINSONS DISEASE 2021; 10:981-991. [PMID: 32444560 DOI: 10.3233/jpd-201983] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND α-Synuclein (α-syn) is a major component of Lewy bodies, a pathologic marker of Parkinson's disease (PD) in post-mortem studies. The use of α-syn as a practical PD biomarker has been investigated by numerous researchers. However, reports of differences in α-syn levels in biofluids, such as cerebrospinal fluid, plasma, and saliva, between PD patients and controls are inconsistent. Recently, the measurement of α-syn oligomer levels has emerged as a novel approach to diagnose PD. OBJECTIVE Lysates and culture media from two different types of dopaminergic neuronal cells or urine samples from 11 non-PD and 21 PD patients were collected and analyzed. METHODS We developed and performed an enzyme-linked immuno-absorbent assay (ELISA) to detect various oligomeric α-syn using distinct pairs of antibodies. RESULTS We validated our ELISA using rotenone-induced alterations of α-syn levels in human dopaminergic neurons. Total urinary α-syn levels, measured using our ELISA method, showed no difference between PD and non-PD individuals, but a higher level of α-syn oligomer recognized by MJFR-14-6-5-2 in PD urine samples was observed. Levels of distinct oligomeric α-syn detected by ASyO5 were lower in PD urine samples. Three different α-syn ELISA results were analyzed with respect to the severity of PD, but only the correlation between total α-syn levels and PD index was significant. CONCLUSION Our findings suggest that detection of distinct oligomeric formations of α-syn and measurement of their levels in urine might be feasible for use in PD diagnostics.
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Affiliation(s)
- Daleum Nam
- InAm Neuroscience Research Center, Sanbon Medical Center, College of Medicine, Wonkwang University, Gunposi, Gyeonggido, Republic of Korea
| | - Jee-Young Lee
- Department of Neurology, Seoul National University Boramae Medical Center, Seoul, Republic of Korea
| | - Minhyung Lee
- Stem Cell Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea.,Department of Functional Genomics, KRIBB School of Bioscience, University of Science and Technology, Daejeon, Republic of Korea
| | - Janghwan Kim
- Stem Cell Convergence Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea.,Department of Functional Genomics, KRIBB School of Bioscience, University of Science and Technology, Daejeon, Republic of Korea
| | - Wongi Seol
- InAm Neuroscience Research Center, Sanbon Medical Center, College of Medicine, Wonkwang University, Gunposi, Gyeonggido, Republic of Korea
| | - Ilhong Son
- InAm Neuroscience Research Center, Sanbon Medical Center, College of Medicine, Wonkwang University, Gunposi, Gyeonggido, Republic of Korea.,Department of Neurology, Sanbon Medical Center, College of Medicine, Wonkwang University, Gunposi, Gyeonggido, Republic of Korea
| | - Dong Hwan Ho
- InAm Neuroscience Research Center, Sanbon Medical Center, College of Medicine, Wonkwang University, Gunposi, Gyeonggido, Republic of Korea
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21
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Gallo A, Pillet LE, Verpillot R. New frontiers in Alzheimer's disease diagnostic: Monoamines and their derivatives in biological fluids. Exp Gerontol 2021; 152:111452. [PMID: 34182050 DOI: 10.1016/j.exger.2021.111452] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2020] [Revised: 04/29/2021] [Accepted: 06/08/2021] [Indexed: 10/21/2022]
Abstract
Current diagnosis of Alzheimer's disease (AD) relies on a combination of neuropsychological evaluations, biomarker measurements and brain imaging. Nevertheless, these approaches are either expensive, invasive or lack sensitivity to early AD stages. The main challenge of ongoing research is therefore to identify early non-invasive biomarkers to diagnose AD at preclinical stage. Accumulating evidence support the hypothesis that initial degeneration of profound monoaminergic nuclei may trigger a transneuronal spread of AD pathology towards hippocampus and cortex. These studies aroused great interest on monoamines, i.e. noradrenaline (NA), dopamine (D) ad serotonin (5-HT), as early hallmarks of AD pathology. The present work reviews current literature on the potential role of monoamines and related metabolites as biomarkers of AD. First, morphological changes in the monoaminergic systems during AD are briefly described. Second, we focus on concentration changes of these molecules and their derivatives in biological fluids, including cerebrospinal fluid, obtained by lumbar puncture, and blood or urine, sampled via less invasive procedures. Starting from initial observations, we then discuss recent insights on metabolomics-based analysis, highlighting the promising clinical utility of monoamines for the identification of a molecular AD signature, aimed at improving early diagnosis and discrimination from other dementia.
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22
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Jain AP, Sathe G. Proteomics Landscape of Alzheimer's Disease. Proteomes 2021; 9:proteomes9010013. [PMID: 33801961 PMCID: PMC8005944 DOI: 10.3390/proteomes9010013] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2021] [Revised: 03/02/2021] [Accepted: 03/08/2021] [Indexed: 01/22/2023] Open
Abstract
Alzheimer’s disease (AD) is the most prevalent form of dementia, and the numbers of AD patients are expected to increase as human life expectancy improves. Deposition of β-amyloid protein (Aβ) in the extracellular matrix and intracellular neurofibrillary tangles are molecular hallmarks of the disease. Since the precise pathophysiology of AD has not been elucidated yet, effective treatment is not available. Thus, understanding the disease pathology, as well as identification and development of valid biomarkers, is imperative for early diagnosis as well as for monitoring disease progression and therapeutic responses. Keeping this goal in mind several studies using quantitative proteomics platform have been carried out on both clinical specimens including the brain, cerebrospinal fluid (CSF), plasma and on animal models of AD. In this review, we summarize the mass spectrometry (MS)-based proteomics studies on AD and discuss the discovery as well as validation stages in brief to identify candidate biomarkers.
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Affiliation(s)
- Ankit P. Jain
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India;
| | - Gajanan Sathe
- Institute of Bioinformatics, International Technology Park, Bangalore 560066, India;
- Manipal Academy of Higher Education (MAHE), Manipal 576104, India
- Correspondence:
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23
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Menne F, Schipke CG. Diagnose it yourself: will there be a home test kit for Alzheimer's disease? Neurodegener Dis Manag 2021; 11:167-176. [PMID: 33596691 DOI: 10.2217/nmt-2020-0065] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022] Open
Abstract
Alzheimer's disease is the most common neurodegenerative process leading to dementia. To date, there is no curative approach; thus, establishing a diagnosis as early as possible is necessary to implement preventive measures. However, today's gold standard for diagnosing Alzheimer's disease is high in both cost and effort and is not readily available. This defines the need for low-effort and economic alternatives that give patients low-threshold access to testing systems at their general practitioners or even at home for an independent retrieval of a biologic specimen. This perspective gives an overview of established and novel approaches in the field and speculates on the future of test strategies eventually technically implementable at home.
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Affiliation(s)
- Felix Menne
- Predemtec AG, Rudower Chaussee 29, Berlin 12489, Germany
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Forloni G. Alzheimer's disease: from basic science to precision medicine approach. BMJ Neurol Open 2020; 2:e000079. [PMID: 33681801 PMCID: PMC7903168 DOI: 10.1136/bmjno-2020-000079] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2020] [Revised: 08/24/2020] [Accepted: 10/16/2020] [Indexed: 12/14/2022] Open
Abstract
Alzheimer’s disease (AD) is the most common form of dementia in the elderly. Together with cerebral amyloid accumulation, several factors contribute to AD pathology including vascular alterations, systemic inflammation, genetic/epigenetic status and mitochondrial dysfunction. Much is now being devoted to neuroinflammation. However, anti-inflammatory drugs as numerous other therapies, mainly targeted on β-amyloid, have failed to show efficacious effects in AD. Timing, proper selection of patients, and the need for a multitarget approach appear to be the main weak points of current therapeutic efforts. The efficacy of a treatment could be better evaluate if efficient biomarkers are available. We propose here the application of precision medicine principles in AD to simultaneously verify the efficacy of a treatment and the reliability of specific biomarkers according to individually tailored biomarker-guided targeted therapies. People at risk of developing AD or in the very early phase of the disease should be stratified according to: (1) neuropsychological tests; (2) apolipoprotein E (ApoE) genotyping; (3) biochemical analysis of plasma and cerebrospinal fluid (CSF); (4) MRI and positron emission tomography and (5) assessment of their inflammatory profile by an integration of various genetic and biochemical parameters in plasma, CSF and an analysis of microbiota composition. The selected population should be treated with antiamyloidogenic and anti-inflammatory drugs in randomised, longitudinal, placebo-controlled studies using ad hoc profiles (eg, vascular profile, mitochondrial profile, etc…) If these criteria are adopted widely and the results shared, it may be possible to rapidly develop innovative and personalised drug treatment protocols with more realistic chances of being efficacious.
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Affiliation(s)
- Gianluigi Forloni
- Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri, Milano, Lombardia, Italy
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Bistaffa E, Tagliavini F, Matteini P, Moda F. Contributions of Molecular and Optical Techniques to the Clinical Diagnosis of Alzheimer's Disease. Brain Sci 2020; 10:E815. [PMID: 33153223 PMCID: PMC7692713 DOI: 10.3390/brainsci10110815] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2020] [Revised: 10/29/2020] [Accepted: 10/31/2020] [Indexed: 01/28/2023] Open
Abstract
Alzheimer's disease (AD) is the most common neurodegenerative disorder worldwide. The distinctive neuropathological feature of AD is the intracerebral accumulation of two abnormally folded proteins: β-amyloid (Aβ) in the form of extracellular plaques, and tau in the form of intracellular neurofibrillary tangles. These proteins are considered disease-specific biomarkers, and the definite diagnosis of AD relies on their post-mortem identification in the brain. The clinical diagnosis of AD is challenging, especially in the early stages. The disease is highly heterogeneous in terms of clinical presentation and neuropathological features. This phenotypic variability seems to be partially due to the presence of distinct Aβ conformers, referred to as strains. With the development of an innovative technique named Real-Time Quaking-Induced Conversion (RT-QuIC), traces of Aβ strains were found in the cerebrospinal fluid of AD patients. Emerging evidence suggests that different conformers may transmit their strain signature to the RT-QuIC reaction products. In this review, we describe the current challenges for the clinical diagnosis of AD and describe how the RT-QuIC products could be analyzed by a surface-enhanced Raman spectroscopy (SERS)-based systems to reveal the presence of strain signatures, eventually leading to early diagnosis of AD with the recognition of individual disease phenotype.
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Affiliation(s)
- Edoardo Bistaffa
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Division of Neurology 5 and Neuropathology, 20133 Milan, Italy;
| | - Fabrizio Tagliavini
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Scientific Directorate, 20133 Milan, Italy;
| | - Paolo Matteini
- IFAC-CNR, Institute of Applied Physics “Nello Carrara”, National Research Council, 50019 Sesto Fiorentino, Italy
| | - Fabio Moda
- Fondazione IRCCS Istituto Neurologico Carlo Besta, Division of Neurology 5 and Neuropathology, 20133 Milan, Italy;
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Seol W, Kim H, Son I. Urinary Biomarkers for Neurodegenerative Diseases. Exp Neurobiol 2020; 29:325-333. [PMID: 33154195 PMCID: PMC7649089 DOI: 10.5607/en20042] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2020] [Revised: 10/12/2020] [Accepted: 10/19/2020] [Indexed: 12/13/2022] Open
Abstract
Global incidence of neurodegenerative diseases (NDDs) such as Alzheimer's disease (AD) and Parkinson's disease (PD) is rapidly increasing, but the diagnosis of these diseases at their early stage is challenging. Therefore, the availability of reproducible and reliable biomarkers to diagnose such diseases is more critical than ever. In addition, biomarkers could be used not only to diagnose diseases but also to monitor the development of disease therapeutics. Urine is an excellent biofluid that can be utilized as a source of biomarker to diagnose not only several renal diseases but also other diseases because of its abundance in invasive sampling. However, urine was conventionally regarded as inappropriate as a source of biomarker for neurodegenerative diseases because it is anatomically distant from the central nervous system (CNS), a major pathologic site of NDD, in comparison to other biofluids such as cerebrospinal fluid (CSF) and plasma. However, recent studies have suggested that urine could be utilized as a source of NDD biomarker if an appropriate marker is predetermined by metabolomic and proteomic approaches in urine and other samples. In this review, we summarize such studies related to NDD.
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Affiliation(s)
- Wongi Seol
- InAm Neuroscience Research Center, Gunpo 15865, Korea
| | - Hyejung Kim
- InAm Neuroscience Research Center, Gunpo 15865, Korea
| | - Ilhong Son
- InAm Neuroscience Research Center, Gunpo 15865, Korea
- Department of Neurology, Sanbon Medical Center, College of Medicine, Wonkwang University, Gunpo 15865, Korea
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Ausó E, Gómez-Vicente V, Esquiva G. Biomarkers for Alzheimer's Disease Early Diagnosis. J Pers Med 2020; 10:E114. [PMID: 32899797 PMCID: PMC7563965 DOI: 10.3390/jpm10030114] [Citation(s) in RCA: 48] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 08/27/2020] [Accepted: 09/01/2020] [Indexed: 12/11/2022] Open
Abstract
Alzheimer's disease (AD) is the most common cause of dementia, affecting the central nervous system (CNS) through the accumulation of intraneuronal neurofibrillary tau tangles (NFTs) and β-amyloid plaques. By the time AD is clinically diagnosed, neuronal loss has already occurred in many brain and retinal regions. Therefore, the availability of early and reliable diagnosis markers of the disease would allow its detection and taking preventive measures to avoid neuronal loss. Current diagnostic tools in the brain, such as magnetic resonance imaging (MRI), positron emission tomography (PET) imaging, and cerebrospinal fluid (CSF) biomarkers (Aβ and tau) detection are invasive and expensive. Brain-secreted extracellular vesicles (BEVs) isolated from peripheral blood have emerged as novel strategies in the study of AD, with enormous potential as a diagnostic evaluation of therapeutics and treatment tools. In addition; similar mechanisms of neurodegeneration have been demonstrated in the brain and the eyes of AD patients. Since the eyes are more accessible than the brain, several eye tests that detect cellular and vascular changes in the retina have also been proposed as potential screening biomarkers. The aim of this study is to summarize and discuss several potential markers in the brain, eye, blood, and other accessible biofluids like saliva and urine, and correlate them with earlier diagnosis and prognosis to identify individuals with mild symptoms prior to dementia.
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Affiliation(s)
| | | | - Gema Esquiva
- Department of Optics, Pharmacology and Anatomy, University of Alicante, 03690 Alicante, Spain; (E.A.); (V.G.-V.)
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Watanabe Y, Hirao Y, Kasuga K, Tokutake T, Kitamura K, Niida S, Ikeuchi T, Nakamura K, Yamamoto T. Urinary Apolipoprotein C3 Is a Potential Biomarker for Alzheimer's Disease. Dement Geriatr Cogn Dis Extra 2020; 10:94-104. [PMID: 33082773 PMCID: PMC7548924 DOI: 10.1159/000509561] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2020] [Accepted: 06/18/2020] [Indexed: 11/19/2022] Open
Abstract
INTRODUCTION Biomarkers of Alzheimer's disease (AD) that can easily be measured in routine health checkups are desirable. Urine is a source of biomarkers that can be collected easily and noninvasively. We previously reported on the comprehensive profile of the urinary proteome of AD patients and identified proteins estimated to be significantly increased or decreased in AD patients by a label-free quantification method. The present study aimed to validate urinary levels of proteins that significantly differed between AD and control samples from our proteomics study (i.e., apolipoprotein C3 [ApoC3], insulin-like growth factor-binding protein 3 [Igfbp3], and apolipoprotein D [ApoD]). METHODS Enzyme-linked immunosorbent assays (ELISAs) were performed using urine samples from the same patient and control groups analyzed in the previous proteomics study (18 AD and 18 controls, set 1) and urine samples from an independent group of AD patients and controls (13 AD, 5 mild cognitive impairment [MCI], and 32 controls) from the National Center for Geriatrics and Gerontology Biobank (set 2). RESULTS In set 1, the crude urinary levels of ApoD, Igfbp3, and creatinine-adjusted ApoD were significantly higher in the AD group relative to the control group (p = 0.003, p = 0.002, and p = 0.019, respectively), consistent with our previous proteomics results. In set 2, however, the crude urinary levels of Igfbp3 were significantly lower in the AD+MCI group than in the control group (p = 0.028), and the levels of ApoD and ApoC3 did not differ significantly compared to the control group. Combined analysis of all samples revealed creatinine-adjusted ApoC3 levels to be significantly higher in the AD+MCI group (p = 0.015) and the AD-only group (p = 0.011) relative to the control group. CONCLUSION ApoC3 may be a potential biomarker for AD, as validated by ELISA. Further analysis of ApoC3 as a urinary biomarker for AD is warranted.
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Affiliation(s)
- Yumi Watanabe
- aDivision of Preventive Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Yoshitoshi Hirao
- bBiofluid Biomarker Center, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Kensaku Kasuga
- cDepartment of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Takayoshi Tokutake
- dDepartment of Neurology, Brain Research Institute, Niigata University, Niigata, Japan
| | - Kaori Kitamura
- aDivision of Preventive Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Shumpei Niida
- eResearch Institute, National Center for Geriatrics and Gerontology, Obu, Japan
| | - Takeshi Ikeuchi
- cDepartment of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Kazutoshi Nakamura
- aDivision of Preventive Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Tadashi Yamamoto
- bBiofluid Biomarker Center, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
- fDepartment of Clinical Laboratory, Shinrakuen Hospital, Niigata, Japan
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Pistollato F, Bernasconi C, McCarthy J, Campia I, Desaintes C, Wittwehr C, Deceuninck P, Whelan M. Alzheimer's Disease, and Breast and Prostate Cancer Research: Translational Failures and the Importance to Monitor Outputs and Impact of Funded Research. Animals (Basel) 2020; 10:E1194. [PMID: 32674379 PMCID: PMC7401638 DOI: 10.3390/ani10071194] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 07/10/2020] [Accepted: 07/10/2020] [Indexed: 12/24/2022] Open
Abstract
Dementia and cancer are becoming increasingly prevalent in Western countries. In the last two decades, research focused on Alzheimer's disease (AD) and cancer, in particular, breast cancer (BC) and prostate cancer (PC), has been substantially funded both in Europe and worldwide. While scientific research outcomes have contributed to increase our understanding of the disease etiopathology, still the prevalence of these chronic degenerative conditions remains very high across the globe. By definition, no model is perfect. In particular, animal models of AD, BC, and PC have been and still are traditionally used in basic/fundamental, translational, and preclinical research to study human disease mechanisms, identify new therapeutic targets, and develop new drugs. However, animals do not adequately model some essential features of human disease; therefore, they are often unable to pave the way to the development of drugs effective in human patients. The rise of new technological tools and models in life science, and the increasing need for multidisciplinary approaches have encouraged many interdisciplinary research initiatives. With considerable funds being invested in biomedical research, it is becoming pivotal to define and apply indicators to monitor the contribution to innovation and impact of funded research. Here, we discuss some of the issues underlying translational failure in AD, BC, and PC research, and describe how indicators could be applied to retrospectively measure outputs and impact of funded biomedical research.
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Affiliation(s)
- Francesca Pistollato
- European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy; (C.B.); (I.C.); (C.W.); (P.D.); (M.W.)
| | - Camilla Bernasconi
- European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy; (C.B.); (I.C.); (C.W.); (P.D.); (M.W.)
| | - Janine McCarthy
- European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy; (C.B.); (I.C.); (C.W.); (P.D.); (M.W.)
- Physicians Committee for Responsible Medicine (PCRM), Washington, DC 20016, USA;
| | - Ivana Campia
- European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy; (C.B.); (I.C.); (C.W.); (P.D.); (M.W.)
| | - Christian Desaintes
- European Commission, Directorate General for Research and Innovation (RTD), 1000 Brussels, Belgium;
| | - Clemens Wittwehr
- European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy; (C.B.); (I.C.); (C.W.); (P.D.); (M.W.)
| | - Pierre Deceuninck
- European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy; (C.B.); (I.C.); (C.W.); (P.D.); (M.W.)
| | - Maurice Whelan
- European Commission, Joint Research Centre (JRC), 21027 Ispra, Italy; (C.B.); (I.C.); (C.W.); (P.D.); (M.W.)
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Villa C, Lavitrano M, Salvatore E, Combi R. Molecular and Imaging Biomarkers in Alzheimer's Disease: A Focus on Recent Insights. J Pers Med 2020; 10:jpm10030061. [PMID: 32664352 PMCID: PMC7565667 DOI: 10.3390/jpm10030061] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/25/2020] [Revised: 06/28/2020] [Accepted: 07/07/2020] [Indexed: 12/15/2022] Open
Abstract
Alzheimer’s disease (AD) is the most common neurodegenerative disease among the elderly, affecting millions of people worldwide and clinically characterized by a progressive and irreversible cognitive decline. The rapid increase in the incidence of AD highlights the need for an easy, efficient and accurate diagnosis of the disease in its initial stages in order to halt or delay the progression. The currently used diagnostic methods rely on measures of amyloid-β (Aβ), phosphorylated (p-tau) and total tau (t-tau) protein levels in the cerebrospinal fluid (CSF) aided by advanced neuroimaging techniques like positron emission tomography (PET) and magnetic resonance imaging (MRI). However, the invasiveness of these procedures and the high cost restrict their utilization. Hence, biomarkers from biological fluids obtained using non-invasive methods and novel neuroimaging approaches provide an attractive alternative for the early diagnosis of AD. Such biomarkers may also be helpful for better understanding of the molecular mechanisms underlying the disease, allowing differential diagnosis or at least prolonging the pre-symptomatic stage in patients suffering from AD. Herein, we discuss the advantages and limits of the conventional biomarkers as well as recent promising candidates from alternative body fluids and new imaging techniques.
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Affiliation(s)
- Chiara Villa
- School of Medicine and Surgery, University of Milano-Bicocca, 20900 Monza, Italy
- Correspondence: (C.V.); (R.C.)
| | - Marialuisa Lavitrano
- School of Medicine and Surgery, University of Milano-Bicocca, 20900 Monza, Italy
- Institute for the Experimental Endocrinology and Oncology, National Research Council (IEOS-CNR), 80131 Naples, Italy;
| | - Elena Salvatore
- Department of Neurosciences and Reproductive and Odontostomatological Sciences, Federico II University, 80131 Naples, Italy;
| | - Romina Combi
- School of Medicine and Surgery, University of Milano-Bicocca, 20900 Monza, Italy
- Correspondence: (C.V.); (R.C.)
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Sancesario G, Bernardini S. AD biomarker discovery in CSF and in alternative matrices. Clin Biochem 2019; 72:52-57. [DOI: 10.1016/j.clinbiochem.2019.08.008] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2019] [Revised: 08/08/2019] [Accepted: 08/15/2019] [Indexed: 12/31/2022]
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Watanabe Y, Hirao Y, Kasuga K, Tokutake T, Semizu Y, Kitamura K, Ikeuchi T, Nakamura K, Yamamoto T. Molecular Network Analysis of the Urinary Proteome of Alzheimer's Disease Patients. Dement Geriatr Cogn Dis Extra 2019; 9:53-65. [PMID: 31043964 PMCID: PMC6477484 DOI: 10.1159/000496100] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Accepted: 12/07/2018] [Indexed: 12/27/2022] Open
Abstract
Background/Aims The identification of predictive biomarkers for Alzheimer's disease (AD) from urine would aid in screening for the disease, but information about biological and pathophysiological changes in the urine of AD patients is limited. This study aimed to explore the comprehensive profile and molecular network relations of urinary proteins in AD patients. Methods Urine samples collected from 18 AD patients and 18 age- and sex-matched cognitively normal controls were analyzed by mass spectrometry and semiquantified with the normalized spectral index method. Bioinformatics analyses were performed on proteins which significantly increased by more than 2-fold or decreased by less than 0.5-fold compared to the control (p < 0.05) using DAVID bioinformatics resources and KeyMolnet software. Results The levels of 109 proteins significantly differed between AD patients and controls. Among these, annotation clusters related to lysosomes, complement activation, and gluconeogenesis were significantly enriched. The molecular relation networks derived from these proteins were mainly associated with pathways of lipoprotein metabolism, heat shock protein 90 signaling, matrix metalloproteinase signaling, and redox regulation by thioredoxin. Conclusion Our findings suggest that changes in the urinary proteome of AD patients reflect systemic changes related to AD pathophysiology.
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Affiliation(s)
- Yumi Watanabe
- Division of Preventive Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | | | - Kensaku Kasuga
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Takayoshi Tokutake
- Department of Neurology, Brain Research Institute, Niigata University, Niigata, Japan
| | - Yuka Semizu
- Division of Preventive Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Kaori Kitamura
- Division of Preventive Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Kazutoshi Nakamura
- Division of Preventive Medicine, Niigata University Graduate School of Medical and Dental Sciences, Niigata, Japan
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Yao F, Zhang K, Zhang Y, Guo Y, Li A, Xiao S, Liu Q, Shen L, Ni J. Identification of Blood Biomarkers for Alzheimer's Disease Through Computational Prediction and Experimental Validation. Front Neurol 2019; 9:1158. [PMID: 30671019 PMCID: PMC6331438 DOI: 10.3389/fneur.2018.01158] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2018] [Accepted: 12/14/2018] [Indexed: 12/15/2022] Open
Abstract
Background: Alzheimer's disease (AD) is the major cause of dementia in population aged over 65 years, accounting up to 70% dementia cases. However, validated peripheral biomarkers for AD diagnosis are not available up to present. In this study, we adopted a new strategy of combination of computational prediction and experimental validation to identify blood protein biomarkers for AD. Methods: First, we collected tissue-based gene expression data of AD patients and healthy controls from GEO database. Second, we analyzed these data and identified differentially expressed genes for AD. Third, we applied a blood-secretory protein prediction program on these genes and predicted AD-related proteins in blood. Finally, we collected blood samples of AD patients and healthy controls to validate the potential AD biomarkers by using ELISA experiments and Western blot analyses. Results: A total of 2754 genes were identified to express differentially in brain tissues of AD, among which 296 genes were predicted to encode AD-related blood-secretory proteins. After careful analysis and literature survey on these predicted blood-secretory proteins, ten proteins were considered as potential AD biomarkers, five of which were experimentally verified with significant change in blood samples of AD vs. controls by ELISA, including GSN, BDNF, TIMP1, VLDLR, and APLP2. ROC analyses showed that VLDLR and TIMP1 had excellent performance in distinguishing AD patients from controls (area under the curve, AUC = 0.932 and 0.903, respectively). Further validation of VLDLR and TIMP1 by Western blot analyses has confirmed the results obtained in ELISA experiments. Conclusion: VLDLR and TIMP1 had better discriminative abilities between ADs and controls, and might serve as potential blood biomarkers for AD. To our knowledge, this is the first time to identify blood protein biomarkers for AD through combination of computational prediction and experimental validation. In addition, VLDLR was first reported here as potential blood protein biomarker for AD. Thus, our findings might provide important information for AD diagnosis and therapies.
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Affiliation(s)
- Fang Yao
- Shenzhen Key Laboratory of Marine Biotechnology and Ecology, College of Life Science and Oceanography, Shenzhen University, Shenzhen, China.,Key Laboratory of Optoelectronic Devices and Systems of Ministry of Education and Guangdong Province, College of Optoelectronic Engineering, Shenzhen University, Shenzhen, China
| | - Kaoyuan Zhang
- Shenzhen Key Laboratory of Marine Biotechnology and Ecology, College of Life Science and Oceanography, Shenzhen University, Shenzhen, China
| | - Yan Zhang
- Shenzhen Key Laboratory of Marine Biotechnology and Ecology, College of Life Science and Oceanography, Shenzhen University, Shenzhen, China
| | - Yi Guo
- Department of Neurology, Shenzhen People's Hospital, Shenzhen, China
| | - Aidong Li
- Department of Rehabilitation, The Eighth Affiliated Hospital of Sun Yat-sen University, Shenzhen, China
| | - Shifeng Xiao
- Shenzhen Key Laboratory of Marine Biotechnology and Ecology, College of Life Science and Oceanography, Shenzhen University, Shenzhen, China
| | - Qiong Liu
- Shenzhen Key Laboratory of Marine Biotechnology and Ecology, College of Life Science and Oceanography, Shenzhen University, Shenzhen, China
| | - Liming Shen
- Shenzhen Key Laboratory of Marine Biotechnology and Ecology, College of Life Science and Oceanography, Shenzhen University, Shenzhen, China
| | - Jiazuan Ni
- Shenzhen Key Laboratory of Marine Biotechnology and Ecology, College of Life Science and Oceanography, Shenzhen University, Shenzhen, China
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