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Yang X, Wang Z, Li H, Qin W, Liu N, Liu Z, Wang S, Xu J, Wang J. Polygenic Score for Conscientiousness Is a Protective Factor for Reversion from Mild Cognitive Impairment to Normal Cognition. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024; 11:e2309889. [PMID: 38838096 PMCID: PMC11304237 DOI: 10.1002/advs.202309889] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2023] [Revised: 05/21/2024] [Indexed: 06/07/2024]
Abstract
Spontaneous reversion from mild cognitive impairment (MCI) to normal cognition (NC) is little known. Based on the data of the Genetics of Personality Consortium and MCI participants from Alzheimer's Disease Neuroimaging Initiative, the authors investigate the effect of polygenic scores (PGS) for personality traits on the reversion of MCI to NC and its underlying neurobiology. PGS analysis reveals that PGS for conscientiousness (PGS-C) is a protective factor that supports the reversion from MCI to NC. Gene ontology enrichment analysis and tissue-specific enrichment analysis indicate that the protective effect of PGS-C may be attributed to affecting the glutamatergic synapses of subcortical structures, such as hippocampus, amygdala, nucleus accumbens, and caudate nucleus. The structural covariance network (SCN) analysis suggests that the left whole hippocampus and its subfields, and the left whole amygdala and its subnuclei show significantly stronger covariance with several high-cognition relevant brain regions in the MCI reverters compared to the stable MCI participants, which may help illustrate the underlying neural mechanism of the protective effect of PGS-C.
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Affiliation(s)
- Xuan Yang
- Department of RadiologyTianjin Key Lab of Functional Imaging & Tianjin Institute of RadiologyTianjin Medical University General HospitalTianjin300052P. R. China
- Department of RadiologyJining No.1 People's HospitalJiningShandong272000P. R. China
| | - Zirui Wang
- Department of RadiologyTianjin Key Lab of Functional Imaging & Tianjin Institute of RadiologyTianjin Medical University General HospitalTianjin300052P. R. China
| | - Haonan Li
- Department of RadiologyTianjin Key Lab of Functional Imaging & Tianjin Institute of RadiologyTianjin Medical University General HospitalTianjin300052P. R. China
| | - Wen Qin
- Department of RadiologyTianjin Key Lab of Functional Imaging & Tianjin Institute of RadiologyTianjin Medical University General HospitalTianjin300052P. R. China
| | - Nana Liu
- Department of RadiologyTianjin Key Lab of Functional Imaging & Tianjin Institute of RadiologyTianjin Medical University General HospitalTianjin300052P. R. China
| | - Zhixuan Liu
- Department of RadiologyTianjin Key Lab of Functional Imaging & Tianjin Institute of RadiologyTianjin Medical University General HospitalTianjin300052P. R. China
| | - Siqi Wang
- Department of RadiologyTianjin Key Lab of Functional Imaging & Tianjin Institute of RadiologyTianjin Medical University General HospitalTianjin300052P. R. China
| | - Jiayuan Xu
- Department of RadiologyTianjin Key Lab of Functional Imaging & Tianjin Institute of RadiologyTianjin Medical University General HospitalTianjin300052P. R. China
| | - Junping Wang
- Department of RadiologyTianjin Key Lab of Functional Imaging & Tianjin Institute of RadiologyTianjin Medical University General HospitalTianjin300052P. R. China
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Lista S, Imbimbo BP, Grasso M, Fidilio A, Emanuele E, Minoretti P, López-Ortiz S, Martín-Hernández J, Gabelle A, Caruso G, Malaguti M, Melchiorri D, Santos-Lozano A, Imbimbo C, Heneka MT, Caraci F. Tracking neuroinflammatory biomarkers in Alzheimer's disease: a strategy for individualized therapeutic approaches? J Neuroinflammation 2024; 21:187. [PMID: 39080712 PMCID: PMC11289964 DOI: 10.1186/s12974-024-03163-y] [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: 05/29/2024] [Accepted: 06/28/2024] [Indexed: 08/02/2024] Open
Abstract
BACKGROUND Recent trials of anti-amyloid-β (Aβ) monoclonal antibodies, including lecanemab and donanemab, in early Alzheimer disease (AD) showed that these drugs have limited clinical benefits and their use comes with a significant risk of serious adverse events. Thus, it seems crucial to explore complementary therapeutic approaches. Genome-wide association studies identified robust associations between AD and several AD risk genes related to immune response, including but not restricted to CD33 and TREM2. Here, we critically reviewed the current knowledge on candidate neuroinflammatory biomarkers and their role in characterizing the pathophysiology of AD. MAIN BODY Neuroinflammation is recognized to be a crucial and contributing component of AD pathogenesis. The fact that neuroinflammation is most likely present from earliest pre-stages of AD and co-occurs with the deposition of Aβ reinforces the need to precisely define the sequence and nature of neuroinflammatory events. Numerous clinical trials involving anti-inflammatory drugs previously yielded unfavorable outcomes in early and mild-to-moderate AD. Although the reasons behind these failures remain unclear, these may include the time and the target selected for intervention. Indeed, in our review, we observed a stage-dependent neuroinflammatory process in the AD brain. While the initial activation of glial cells counteracts early brain Aβ deposition, the downregulation in the functional state of microglia occurs at more advanced disease stages. To address this issue, personalized neuroinflammatory modulation therapy is required. The emergence of reliable blood-based neuroinflammatory biomarkers, particularly glial fibrillary acidic protein, a marker of reactive astrocytes, may facilitate the classification of AD patients based on the ATI(N) biomarker framework. This expands upon the traditional classification of Aβ ("A"), tau ("T"), and neurodegeneration ("N"), by incorporating a novel inflammatory component ("I"). CONCLUSIONS The present review outlines the current knowledge on potential neuroinflammatory biomarkers and, importantly, emphasizes the role of longitudinal analyses, which are needed to accurately monitor the dynamics of cerebral inflammation. Such a precise information on time and place will be required before anti-inflammatory therapeutic interventions can be considered for clinical evaluation. We propose that an effective anti-neuroinflammatory therapy should specifically target microglia and astrocytes, while considering the individual ATI(N) status of patients.
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Affiliation(s)
- Simone Lista
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), 47012, Valladolid, Spain.
| | - Bruno P Imbimbo
- Department of Research and Development, Chiesi Farmaceutici, 43122, Parma, Italy
| | | | | | | | | | - Susana López-Ortiz
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), 47012, Valladolid, Spain
| | - Juan Martín-Hernández
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), 47012, Valladolid, Spain
| | - Audrey Gabelle
- CMRR, Memory Resources and Research Center, Montpellier University of Excellence i-site, 34295, Montpellier, France
| | - Giuseppe Caruso
- Oasi Research Institute-IRCCS, 94018, Troina, Italy
- Department of Drug and Health Sciences, University of Catania, 95125, Catania, Italy
| | - Marco Malaguti
- Department for Life Quality Studies, Alma Mater Studiorum, University of Bologna, 40126, Bologna, Italy
| | - Daniela Melchiorri
- Department of Physiology and Pharmacology, Sapienza University, 00185, Rome, Italy
| | - Alejandro Santos-Lozano
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), 47012, Valladolid, Spain
- Physical Activity and Health Research Group (PaHerg), Research Institute of the Hospital, 12 de Octubre ('imas12'), 28041, Madrid, Spain
| | - Camillo Imbimbo
- Department of Brain and Behavioral Sciences, University of Pavia, 27100, Pavia, Italy
| | - Michael T Heneka
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, 4367, Esch-Belval, Luxembourg.
| | - Filippo Caraci
- Oasi Research Institute-IRCCS, 94018, Troina, Italy.
- Department of Drug and Health Sciences, University of Catania, 95125, Catania, Italy.
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Yadav S, Deepika, Moar K, Kumar A, Khola N, Pant A, Kakde GS, Maurya PK. Reconsidering red blood cells as the diagnostic potential for neurodegenerative disorders. Biol Cell 2024; 116:e2400019. [PMID: 38822416 DOI: 10.1111/boc.202400019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 04/12/2024] [Accepted: 04/29/2024] [Indexed: 06/03/2024]
Abstract
BACKGROUND Red blood cells (RBCs) are usually considered simple cells and transporters of gases to tissues. HYPOTHESIS However, recent research has suggested that RBCs may have diagnostic potential in major neurodegenerative disorders (NDDs). RESULTS This review summarizes the current knowledge on changes in RBC in Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, and other NDDs. It discusses the deposition of neuronal proteins like amyloid-β, tau, and α-synuclein, polyamines, changes in the proteins of RBCs like band-3, membrane transporter proteins, heat shock proteins, oxidative stress biomarkers, and altered metabolic pathways in RBCs during neurodegeneration. It also highlights the comparison of RBC diagnostic markers to other in-market diagnoses and discusses the challenges in utilizing RBCs as diagnostic tools, such as the need for standardized protocols and further validation studies. SIGNIFICANCE STATEMENT The evidence suggests that RBCs have diagnostic potential in neurodegenerative disorders, and this study can pave the foundation for further research which may lead to the development of novel diagnostic approaches and treatments.
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Affiliation(s)
- Somu Yadav
- Department of Biochemistry, Central University of Haryana, Mahendergarh, India
| | - Deepika
- Department of Biochemistry, Central University of Haryana, Mahendergarh, India
| | - Kareena Moar
- Department of Biochemistry, Central University of Haryana, Mahendergarh, India
| | - Akshay Kumar
- Department of Biochemistry, Central University of Haryana, Mahendergarh, India
| | - Nikhila Khola
- Department of Biochemistry, Central University of Haryana, Mahendergarh, India
| | - Anuja Pant
- Department of Biochemistry, Central University of Haryana, Mahendergarh, India
| | - Ganseh S Kakde
- Department of Biochemistry, Central University of Haryana, Mahendergarh, India
| | - Pawan Kumar Maurya
- Department of Biochemistry, Central University of Haryana, Mahendergarh, India
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Dark HE, Duggan MR, Walker KA. Plasma biomarkers for Alzheimer's and related dementias: A review and outlook for clinical neuropsychology. Arch Clin Neuropsychol 2024; 39:313-324. [PMID: 38520383 DOI: 10.1093/arclin/acae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 02/05/2024] [Indexed: 03/25/2024] Open
Abstract
Recent technological advances have improved the sensitivity and specificity of blood-based biomarkers for Alzheimer's disease and related dementias. Accurate quantification of amyloid-ß peptide, phosphorylated tau (pTau) isoforms, as well as markers of neurodegeneration (neurofilament light chain [NfL]) and neuro-immune activation (glial fibrillary acidic protein [GFAP] and chitinase-3-like protein 1 [YKL-40]) in blood has allowed researchers to characterize neurobiological processes at scale in a cost-effective and minimally invasive manner. Although currently used primarily for research purposes, these blood-based biomarkers have the potential to be highly impactful in the clinical setting - aiding in diagnosis, predicting disease risk, and monitoring disease progression. Whereas plasma NfL has shown promise as a non-specific marker of neuronal injury, plasma pTau181, pTau217, pTau231, and GFAP have demonstrated desirable levels of sensitivity and specificity for identification of individuals with Alzheimer's disease pathology and Alzheimer's dementia. In this forward looking review, we (i) provide an overview of the most commonly used blood-based biomarkers for Alzheimer's disease and related dementias, (ii) discuss how comorbid medical conditions, demographic, and genetic factors can inform the interpretation of these biomarkers, (iii) describe ongoing efforts to move blood-based biomarkers into the clinic, and (iv) highlight the central role that clinical neuropsychologists may play in contextualizing and communicating blood-based biomarker results for patients.
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Affiliation(s)
- Heather E Dark
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
| | - Michael R Duggan
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
| | - Keenan A Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
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Silva-Spínola A, Leitão MJ, Nadal A, Le Bastard N, Santana I, Baldeiras I. Exploring the potential of fully automated LUMIPULSE G plasma assays for detecting Alzheimer's disease pathology. Alzheimers Res Ther 2024; 16:51. [PMID: 38454502 PMCID: PMC10918996 DOI: 10.1186/s13195-024-01397-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 01/26/2024] [Indexed: 03/09/2024]
Abstract
BACKGROUND LUMIPULSE G-automated immunoassays represent a widely used method for the quantification of Alzheimer's disease (AD) biomarkers in the cerebrospinal fluid (CSF). Less invasive blood-based markers confer a promising tool for AD diagnosis at prodromal stages (mild cognitive impairment (MCI)). Highly sensitive assays for the quantification of amyloid-beta (Aβ) and phosphorylated Tau-181 (p-Tau181) in the blood are showing promising results. In this study, we evaluated the clinical performance of the recently available fully automated LUMIPULSE plasma marker assays for detecting brain AD pathology and for predicting progression from MCI to AD dementia stage. METHODS A retrospective exploratory cohort of 138 individuals (22 neurological controls [NC], 72 MCI, and 44 AD dementia patients) was included. Data regarding baseline CSF concentrations of Aβ42, Aβ40, t-Tau, and p-Tau181 was available and used to establish the presence of AD brain pathology. Baseline Aβ42, Aβ40, and p-Tau181 concentrations were determined in stored plasma samples using high-throughput fully automated LUMIPULSE assays. Progression from MCI to AD dementia was evaluated during follow-up (mean 6.4 ± 2.5 years). Moreover, a prospective validation cohort of 72 individuals with memory complaints underwent AD biomarker quantification, closely mirroring typical clinical practice. This cohort aimed to confirm the study's main findings. RESULTS In the exploratory cohort, correlations between CSF and plasma were moderate for p-Tau181 (ρ = 0.61, p < 0.001) and weak for Aβ42/Aβ40 ratio (ρ = 0.39, p < 0.001). Plasma p-Tau181 and p-Tau181/Aβ42 concentrations were significantly increased while Aβ42/Aβ40 was significantly decreased (p < 0.001) in patients with AD dementia and prodromal AD, as well as in individuals with CSF abnormal amyloid concentrations (A +). Plasma p-Tau181 showed a robust performance in differentiating patients clinically diagnosed as AD (AUC = 0.89; 95% CI 0.83-0.94); A + vs. A - (AUC = 0.84, 95% CI 0.77-0.91) and also in predicting conversion to AD dementia in MCI patients (AUC = 0.89, 95% CI 0.81-0.96). When tested in the validation cohort, plasma p-Tau181 displayed 83.3% of the overall percentage of agreement according to amyloid status. CONCLUSIONS Our results show that the measurement of p-Tau181 in plasma has great potential as a non-invasive prognostic screening tool for implementation in a clinical setting.
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Affiliation(s)
- Anuschka Silva-Spínola
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal.
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.
- Centre for Informatics and Systems, Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal.
- Neurochemistry Laboratory, Neurology Department, Coimbra University Hospital, Praceta Mota Pinto, 3004-561, Coimbra, Portugal.
| | - Maria João Leitão
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
- Neurochemistry Laboratory, Neurology Department, Coimbra University Hospital, Praceta Mota Pinto, 3004-561, Coimbra, Portugal
| | | | | | - Isabel Santana
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
- Neurology Department, Centro Hospitalar E Universitário de Coimbra, Coimbra, Portugal
| | - Inês Baldeiras
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
- Neurochemistry Laboratory, Neurology Department, Coimbra University Hospital, Praceta Mota Pinto, 3004-561, Coimbra, Portugal
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Jack CR, Wiste HJ, Algeciras‐Schimnich A, Weigand SD, Figdore DJ, Lowe VJ, Vemuri P, Graff‐Radford J, Ramanan VK, Knopman DS, Mielke MM, Machulda MM, Fields J, Schwarz CG, Cogswell PM, Senjem ML, Therneau TM, Petersen RC. Comparison of plasma biomarkers and amyloid PET for predicting memory decline in cognitively unimpaired individuals. Alzheimers Dement 2024; 20:2143-2154. [PMID: 38265198 PMCID: PMC10984437 DOI: 10.1002/alz.13651] [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: 09/01/2023] [Revised: 11/22/2023] [Accepted: 11/27/2023] [Indexed: 01/25/2024]
Abstract
BACKGROUND We compared the ability of several plasma biomarkers versus amyloid positron emission tomography (PET) to predict rates of memory decline among cognitively unimpaired individuals. METHODS We studied 645 Mayo Clinic Study of Aging participants. Predictor variables were age, sex, education, apolipoprotein E (APOE) ε4 genotype, amyloid PET, and plasma amyloid beta (Aβ)42/40, phosphorylated tau (p-tau)181, neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and p-tau217. The outcome was a change in a memory composite measure. RESULTS All plasma biomarkers, except NfL, were associated with mean memory decline in models with individual biomarkers. However, amyloid PET and plasma p-tau217, along with age, were key variables independently associated with mean memory decline in models combining all predictors. Confidence intervals were narrow for estimates of population mean prediction, but person-level prediction intervals were wide. DISCUSSION Plasma p-tau217 and amyloid PET provide useful information about predicting rates of future cognitive decline in cognitively unimpaired individuals at the population mean level, but not at the individual person level.
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Affiliation(s)
| | - Heather J. Wiste
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | | | - Stephen D. Weigand
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | - Dan J. Figdore
- Department of Laboratory MedicineMayo ClinicRochesterMinnesotaUSA
| | - Val J. Lowe
- Department of Nuclear MedicineMayo ClinicRochesterMinnesotaUSA
| | | | | | | | | | - Michelle M. Mielke
- Department of Epidemiology and PreventionWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Mary M. Machulda
- Department of Psychiatry and PsychologyMayo ClinicRochesterMinnesotaUSA
| | - Julie Fields
- Department of Psychiatry and PsychologyMayo ClinicRochesterMinnesotaUSA
| | | | | | | | - Terry M. Therneau
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
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Mazzeo S, Ingannato A, Giacomucci G, Bagnoli S, Cavaliere A, Moschini V, Balestrini J, Morinelli C, Galdo G, Emiliani F, Piazzesi D, Crucitti C, Frigerio D, Polito C, Berti V, Padiglioni S, Sorbi S, Nacmias B, Bessi V. The role of plasma neurofilament light chain and glial fibrillary acidic protein in subjective cognitive decline and mild cognitive impairment. Neurol Sci 2024; 45:1031-1039. [PMID: 37723371 PMCID: PMC10857957 DOI: 10.1007/s10072-023-07065-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 09/06/2023] [Indexed: 09/20/2023]
Abstract
INTRODUCTION AND AIM NfL and GFAP are promising blood-based biomarkers for Alzheimer's disease. However, few studies have explored plasma GFAP in the prodromal and preclinical stages of AD. In our cross-sectional study, our aim is to investigate the role of these biomarkers in the earliest stages of AD. MATERIALS AND METHODS We enrolled 40 patients (11 SCD, 21 MCI, 8 AD dementia). All patients underwent neurological and neuropsychological examinations, analysis of CSF biomarkers (Aβ42, Aβ42/Aβ40, p-tau, t-tau), Apolipoprotein E (APOE) genotype analysis and measurement of plasma GFAP and NfL concentrations. Patients were categorized according to the ATN system as follows: normal AD biomarkers (NB), carriers of non-Alzheimer's pathology (non-AD), prodromal AD, or AD with dementia (AD-D). RESULTS GFAP was lower in NB compared to prodromal AD (p = 0.003, d = 1.463) and AD-D (p = 0.002, d = 1.695). NfL was lower in NB patients than in AD-D (p = 0.011, d = 1.474). NfL demonstrated fair accuracy (AUC = 0.718) in differentiating between NB and prodromal AD, with a cut-off value of 11.65 pg/mL. GFAP showed excellent accuracy in differentiating NB from prodromal AD (AUC = 0.901) with a cut-off level of 198.13 pg/mL. CONCLUSIONS GFAP exhibited excellent accuracy in distinguishing patients with normal CSF biomarkers from those with prodromal AD. Our results support the use of this peripheral biomarker for detecting AD in patients with subjective and objective cognitive decline.
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Affiliation(s)
- Salvatore Mazzeo
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
- Research and Innovation Centre for Dementia-CRIDEM, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Assunta Ingannato
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Giulia Giacomucci
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Arianna Cavaliere
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Valentina Moschini
- Research and Innovation Centre for Dementia-CRIDEM, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Juri Balestrini
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Carmen Morinelli
- Research and Innovation Centre for Dementia-CRIDEM, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Giulia Galdo
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Filippo Emiliani
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Diletta Piazzesi
- Research and Innovation Centre for Dementia-CRIDEM, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Chiara Crucitti
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Daniele Frigerio
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | | | - Valentina Berti
- Department of Biomedical, Experimental and Clinical Sciences "Mario Serio", University of Florence, 50134, Florence, Italy
| | - Sonia Padiglioni
- Research and Innovation Centre for Dementia-CRIDEM, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
- Regional Referral Centre for Relational Criticalities- 50139, Tuscany Region, Italy
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
- Research and Innovation Centre for Dementia-CRIDEM, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy.
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.
| | - Valentina Bessi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
- Research and Innovation Centre for Dementia-CRIDEM, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
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Mazzeo S, Ingannato A, Giacomucci G, Manganelli A, Moschini V, Balestrini J, Cavaliere A, Morinelli C, Galdo G, Emiliani F, Piazzesi D, Crucitti C, Frigerio D, Polito C, Berti V, Bagnoli S, Padiglioni S, Sorbi S, Nacmias B, Bessi V. Plasma neurofilament light chain predicts Alzheimer's disease in patients with subjective cognitive decline and mild cognitive impairment: A cross-sectional and longitudinal study. Eur J Neurol 2024; 31:e16089. [PMID: 37797300 PMCID: PMC11235835 DOI: 10.1111/ene.16089] [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: 06/15/2023] [Revised: 09/18/2023] [Accepted: 09/21/2023] [Indexed: 10/07/2023]
Abstract
BACKGROUND AND PURPOSE We aimed to evaluate the accuracy of plasma neurofilament light chain (NfL) in predicting Alzheimer's disease (AD) and the progression of cognitive decline in patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI). METHODS This longitudinal cohort study involved 140 patients (45 with SCD, 73 with MCI, and 22 with AD dementia [AD-D]) who underwent plasma NfL and AD biomarker assessments (cerebrospinal fluid, amyloid positron emission tomography [PET], and 18 F-fluorodeoxyglucose-PET) at baseline. The patients were rated according to the amyloid/tau/neurodegeneration (A/T/N) system and followed up for a mean time of 2.72 ± 0.95 years to detect progression from SCD to MCI and from MCI to AD. Forty-eight patients (19 SCD, 29 MCI) also underwent plasma NfL measurements 2 years after baseline. RESULTS At baseline, plasma NfL detected patients with biomarker profiles consistent with AD (A+/T+/N+ or A+/T+/N-) with high accuracy (area under the curve [AUC] 0.82). We identified cut-off values of 19.45 pg/mL for SCD and 20.45 pg/mL for MCI. During follow-up, nine SCD patients progressed to MCI (progressive SCD [p-SCD]), and 14 MCI patients developed AD dementia (progressive MCI [p-MCI]). The previously identified cut-off values provided good accuracy in identifying p-SCD (80% [95% confidence interval 65.69: 94.31]). The rate of NfL change was higher in p-MCI (3.52 ± 4.06 pg/mL) compared to non-progressive SCD (0.81 ± 1.25 pg/mL) and non-progressive MCI (-0.13 ± 3.24 pg/mL) patients. A rate of change lower than 1.64 pg/mL per year accurately excluded progression from MCI to AD (AUC 0.954). CONCLUSION Plasma NfL concentration and change over time may be a reliable, non-invasive tool to detect AD and the progression of cognitive decline at the earliest stages of the disease.
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Affiliation(s)
- Salvatore Mazzeo
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
| | - Assunta Ingannato
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Giulia Giacomucci
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Alberto Manganelli
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Valentina Moschini
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
| | - Juri Balestrini
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Arianna Cavaliere
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Carmen Morinelli
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
| | - Giulia Galdo
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Filippo Emiliani
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Diletta Piazzesi
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
| | - Chiara Crucitti
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Daniele Frigerio
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | | | - Valentina Berti
- Department of Biomedical, Experimental and Clinical Sciences "Mario Serio"University of FlorenceFlorenceItaly
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Sonia Padiglioni
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
- Regional Referral Centre for Relational Criticalities – 50139Tuscany RegionItaly
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
- IRCCS Fondazione Don Carlo GnocchiFlorenceItaly
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
- IRCCS Fondazione Don Carlo GnocchiFlorenceItaly
| | - Valentina Bessi
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
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9
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Fong TG, Vasunilashorn SM, Kivisäkk P, Metzger E, Schmitt EM, Marcantonio ER, Jones RN, Shanes H, Arnold SE, Inouye SK, Ngo LH. Biomarkers of neurodegeneration and neural injury as potential predictors for delirium. Int J Geriatr Psychiatry 2024; 39:e6044. [PMID: 38161287 PMCID: PMC10798573 DOI: 10.1002/gps.6044] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Accepted: 12/09/2023] [Indexed: 01/03/2024]
Abstract
OBJECTIVES Determine if biomarkers of Alzheimer's disease and neural injury may play a role in the prediction of delirium risk. METHODS In a cohort of older adults who underwent elective surgery, delirium case-no delirium control pairs (N = 70, or 35 matched pairs) were matched by age, sex and vascular comorbidities. Biomarkers from CSF and plasma samples collected prior to surgery, including amyloid beta (Aβ)42 , Aβ40 , total (t)-Tau, phosphorylated (p)-Tau181 , neurofilament-light (NfL), and glial fibrillary acid protein (GFAP) were measured in cerebrospinal fluid (CSF) and plasma using sandwich enzyme-linked immunosorbent assays (ELISAs) or ultrasensitive single molecule array (Simoa) immunoassays. RESULTS Plasma GFAP correlated significantly with CSF GFAP and both plasma and CSF GFAP values were nearly two-fold higher in delirium cases. The median paired difference between delirium case and control without delirium for plasma GFAP was not significant (p = 0.074) but higher levels were associated with a greater risk for delirium (odds ratio 1.52, 95% confidence interval 0.85, 2.72 per standard deviation increase in plasma GFAP concentration) in this small study. No matched pair differences or associations with delirium were observed for NfL, p-Tau 181, Aβ40 and Aβ42 . CONCLUSIONS These preliminary findings suggest that plasma GFAP, a marker of astroglial activation, may be worth further investigation as a predictive risk marker for delirium.
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Affiliation(s)
- Tamara G. Fong
- Department of Neurology, Beth Israel Deaconess Medical Center, Boston, MA
- Aging Brain Center, Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA
- Harvard Medical School, Boston, MA
| | - Sarinnapha M. Vasunilashorn
- Harvard Medical School, Boston, MA
- Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, MA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Pia Kivisäkk
- Harvard Medical School, Boston, MA
- MGH Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Charlestown, MA
| | - Eran Metzger
- Aging Brain Center, Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA
- Harvard Medical School, Boston, MA
| | - Eva M. Schmitt
- Aging Brain Center, Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA
| | - Edward R. Marcantonio
- Harvard Medical School, Boston, MA
- Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, MA
- Division of Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Richard N. Jones
- Departments of Psychiatry and Human Behavior and Neurology, Warren Alpert Medical School, Brown University, Providence, RI, USA
| | - Hannah Shanes
- Aging Brain Center, Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA
| | - Steven E. Arnold
- Harvard Medical School, Boston, MA
- MGH Institute for Neurodegenerative Disease, Department of Neurology, Massachusetts General Hospital, Charlestown, MA
| | - Sharon K. Inouye
- Aging Brain Center, Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA
- Harvard Medical School, Boston, MA
- Division of Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, MA
| | - Long H. Ngo
- Harvard Medical School, Boston, MA
- Division of General Medicine, Beth Israel Deaconess Medical Center, Boston, MA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
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10
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Inoue M, Suzuki H, Meno K, Liu S, Korenaga T, Uchida K. Identification of Plasma Proteins as Biomarkers for Mild Cognitive Impairment and Alzheimer's Disease Using Liquid Chromatography-Tandem Mass Spectrometry. Int J Mol Sci 2023; 24:13064. [PMID: 37685872 PMCID: PMC10488247 DOI: 10.3390/ijms241713064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2023] [Revised: 08/11/2023] [Accepted: 08/19/2023] [Indexed: 09/10/2023] Open
Abstract
Blood proteins can be used for biomarkers to monitor the progression of cognitive decline, even in the early stages of disease. In this study, we developed a liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based blood test to identify plasma proteins that can be used to detect mild cognitive impairment (MCI) and Alzheimer's disease (AD). Using this system, we quantified plasma proteins using isotope-labeled synthetic peptides. A total of 192 patients, including 63 with AD, 71 with MCI, and 58 non-demented controls (NDCs), were analyzed. Multinomial regression and receiver operating characteristic (ROC) analyses were performed to identify specific combinations of plasma protein panels that could differentiate among NDCs, those with MCI, and those with AD. We identified eight plasma protein biomarker candidates that can be used to distinguish between MCI and AD. These biomarkers were associated with coagulation pathways, innate immunity, lipid metabolism, and nutrition. The clinical potential to differentiate cognitive impairment from NDC was assessed using area under the curve values from ROC analysis, which yielded values of 0.83 for males and 0.71 for females. This LC-MS-based plasma protein panel allows the pathophysiology of AD to be followed through detection of cognitive decline and disease progression markers.
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Affiliation(s)
- Makoto Inoue
- Research Division, MCBI, 5-4-2 Toukoudai, Tsukuba 300-2635, Ibaraki, Japan (H.S.)
| | - Hideaki Suzuki
- Research Division, MCBI, 5-4-2 Toukoudai, Tsukuba 300-2635, Ibaraki, Japan (H.S.)
| | - Kohji Meno
- Research Division, MCBI, 5-4-2 Toukoudai, Tsukuba 300-2635, Ibaraki, Japan (H.S.)
| | - Shan Liu
- Research Division, MCBI, 5-4-2 Toukoudai, Tsukuba 300-2635, Ibaraki, Japan (H.S.)
| | - Tatsumi Korenaga
- Research Division, MCBI, 5-4-2 Toukoudai, Tsukuba 300-2635, Ibaraki, Japan (H.S.)
| | - Kazuhiko Uchida
- Clinical Bioinformatics Initiative, Institute for Biomedical Research, MCBI, 5-4-2 Toukoudai, Tsukuba 300-2635, Ibaraki, Japan
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11
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Loveland PM, Yu JJ, Churilov L, Yassi N, Watson R. Investigation of Inflammation in Lewy Body Dementia: A Systematic Scoping Review. Int J Mol Sci 2023; 24:12116. [PMID: 37569491 PMCID: PMC10418754 DOI: 10.3390/ijms241512116] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 07/24/2023] [Accepted: 07/26/2023] [Indexed: 08/13/2023] Open
Abstract
Inflammatory mechanisms are increasingly recognized as important contributors to the pathogenesis of neurodegenerative diseases, including Lewy body dementia (LBD). Our objectives were to, firstly, review inflammation investigation methods in LBD (dementia with Lewy bodies and Parkinson's disease dementia) and, secondly, identify alterations in inflammatory signals in LBD compared to people without neurodegenerative disease and other neurodegenerative diseases. A systematic scoping review was performed by searching major electronic databases (MEDLINE, Embase, Web of Science, and PSYCHInfo) to identify relevant human studies. Of the 2509 results screened, 80 studies were included. Thirty-six studies analyzed postmortem brain tissue, and 44 investigated living subjects with cerebrospinal fluid, blood, and/or brain imaging assessments. Largely cross-sectional data were available, although two longitudinal clinical studies investigated prodromal Lewy body disease. Investigations were focused on inflammatory immune cell activity (microglia, astrocytes, and lymphocytes) and inflammatory molecules (cytokines, etc.). Results of the included studies identified innate and adaptive immune system contributions to inflammation associated with Lewy body pathology and clinical disease features. Different signals in early and late-stage disease, with possible late immune senescence and dystrophic glial cell populations, were identified. The strength of these associations is limited by the varying methodologies, small study sizes, and cross-sectional nature of the data. Longitudinal studies investigating associations with clinical and other biomarker outcomes are needed to improve understanding of inflammatory activity over the course of LBD. This could identify markers of disease activity and support therapeutic development.
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Affiliation(s)
- Paula M. Loveland
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3000, Australia
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Parkville 3000, Australia
| | - Jenny J. Yu
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3000, Australia
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Parkville 3000, Australia
| | - Leonid Churilov
- Department of Neurology, Melbourne Brain Centre, The Royal Melbourne Hospital, University of Melbourne, Parkville 3000, Australia
- Melbourne Medical School, University of Melbourne, Parkville 3000, Australia
| | - Nawaf Yassi
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3000, Australia
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Parkville 3000, Australia
- Department of Neurology, Melbourne Brain Centre, The Royal Melbourne Hospital, University of Melbourne, Parkville 3000, Australia
| | - Rosie Watson
- Population Health and Immunity Division, The Walter and Eliza Hall Institute of Medical Research, Parkville 3000, Australia
- Department of Medicine, The Royal Melbourne Hospital, University of Melbourne, Parkville 3000, Australia
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