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Grande G, Valletta M, Rizzuto D, Xia X, Qiu C, Orsini N, Dale M, Andersson S, Fredolini C, Winblad B, Laukka EJ, Fratiglioni L, Vetrano DL. Blood-based biomarkers of Alzheimer's disease and incident dementia in the community. Nat Med 2025:10.1038/s41591-025-03605-x. [PMID: 40140622 DOI: 10.1038/s41591-025-03605-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 02/21/2025] [Indexed: 03/28/2025]
Abstract
Evidence regarding the clinical validity of blood biomarkers of Alzheimer's disease (AD) in the general population is limited. We estimated the hazard and predictive performance of six AD blood biomarkers for incident all-cause and AD dementia-the ratio of amyloid-β 42 to amyloid-β 40 and levels of tau phosphorylated at T217 (p-tau217), tau phosphorylated at T181 (p-tau181), total tau, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP)-in a cohort of 2,148 dementia-free older adults from Sweden, who were followed for up to 16 years. In multi-adjusted Cox regression models, elevated baseline levels of p-tau181, p-tau217, NfL, and GFAP were associated with a significantly increased hazard for all-cause and AD dementia, displaying a non-linear dose-response relationship. Elevated concentrations of p-tau181, p-tau217, NfL, and GFAP demonstrated strong predictive performance (area under the curve ranging from 70.9% to 82.6%) for 10-year all-cause and AD dementia, with negative predictive values exceeding 90% but low positive predictive values (PPVs). Combining p-tau217 with NfL or GFAP further improved prediction, with PPVs reaching 43%. Our findings suggest that these biomarkers have the potential to rule out impending dementia in community settings, but they might need to be combined with other biological or clinical markers to be used as screening tools.
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Affiliation(s)
- Giulia Grande
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden.
- Stockholm Gerontology Research Center, Stockholm, Sweden.
| | - Martina Valletta
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Debora Rizzuto
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
- Stockholm Gerontology Research Center, Stockholm, Sweden
| | - Xin Xia
- Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Chengxuan Qiu
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Nicola Orsini
- Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden
| | - Matilda Dale
- Affinity Proteomics Stockholm, Science for Life Laboratory, Department of Protein Science, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Royal Institute of Technology (KTH), Solna, Sweden
| | - Sarah Andersson
- Affinity Proteomics Stockholm, Science for Life Laboratory, Department of Protein Science, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Royal Institute of Technology (KTH), Solna, Sweden
| | - Claudia Fredolini
- Affinity Proteomics Stockholm, Science for Life Laboratory, Department of Protein Science, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Royal Institute of Technology (KTH), Solna, Sweden
| | - Bengt Winblad
- Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Huddinge, Sweden
| | - Erika J Laukka
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
- Stockholm Gerontology Research Center, Stockholm, Sweden
| | - Laura Fratiglioni
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
- Stockholm Gerontology Research Center, Stockholm, Sweden
| | - Davide L Vetrano
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
- Stockholm Gerontology Research Center, Stockholm, Sweden
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Dhana A, DeCarli CS, Dhana K, Desai P, Krueger K, Evans DA, Rajan KB. Association of subjective memory complaints with serum biomarkers of neurodegeneration and cognition: A population-based study. J Am Geriatr Soc 2025; 73:859-866. [PMID: 39625703 PMCID: PMC11908938 DOI: 10.1111/jgs.19300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2024] [Revised: 10/29/2024] [Accepted: 11/06/2024] [Indexed: 12/08/2024]
Abstract
BACKGROUND Subjective memory complaints (SMCs) refer to memory concerns reported by an individual, regardless of objective test impairment. We conducted a study to evaluate the association of SMCs with serum biomarkers of neurodegeneration, including neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP), and total tau (t-tau). In addition, we evaluated the association of SMCs with the rate of cognitive decline. METHODS This study included 1096 individuals participating in the Chicago Health and Aging Project, with data on SMCs, neurodegenerative biomarkers (NfL, GFAP, and t-tau), and global cognitive scores. The SMC score ranges from 0 to 8 and higher scores reflect more memory complaints. Linear regression models were developed to investigate the association of SMCs with serum biomarkers, adjusted by age, sex, race, education, and APOE e4. Linear mixed-effects models were used to examine the independent association of SMCs with cognitive decline in a multivariable model that was additionally adjusted by biomarkers of neurodegeneration. RESULTS Of the 1096 individuals, 665 (60.7%) were female, 643 (58.7%) were African Americans, and the mean (SD) age at the baseline was 78.0 (5.8) years. Compared to individuals with fewer memory complaints (i.e., people in the first tertile of SMCs), those reporting more memory complaints (i.e., people in the third tertile of SMCs) had a 12.0% increase in serum concentrations of NfL and an 9.4% increase in GFAP. In addition, individuals reporting more memory complaints (i.e., those in the 3rd versus the 1st tertile of SMCs) had a faster rate of cognitive decline by 0.029 ( β -0.029, 95% CI -0.046 to -0.013) standardized units per year. CONCLUSIONS Individuals who reported more memory complaints had higher levels of biomarkers of neurodegeneration and a faster rate of cognitive decline, suggesting that SMCs may be valuable for identifying people at high risk of cognitive impairment.
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Affiliation(s)
- Anisa Dhana
- Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, Illinois, USA
- Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois, USA
| | - Charles S DeCarli
- Department of Neurology, University of California at Davis, Sacramento, California, USA
| | - Klodian Dhana
- Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, Illinois, USA
- Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois, USA
| | - Pankaja Desai
- Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, Illinois, USA
- Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois, USA
| | - Kristin Krueger
- Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, Illinois, USA
- Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois, USA
| | - Denis A Evans
- Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, Illinois, USA
- Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois, USA
| | - Kumar B Rajan
- Rush Institute for Healthy Aging, Rush University Medical Center, Chicago, Illinois, USA
- Department of Internal Medicine, Rush University Medical Center, Chicago, Illinois, USA
- Department of Neurology, University of California at Davis, Sacramento, California, USA
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Yingmei H, Chaojie W, Yi Z, Yijie L, Heng Z, Ze F, Weiqing L, Bingyuan C, Feng W. Research progress on brain network imaging biomarkers of subjective cognitive decline. Front Neurosci 2025; 19:1503955. [PMID: 40018359 PMCID: PMC11865231 DOI: 10.3389/fnins.2025.1503955] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2024] [Accepted: 01/21/2025] [Indexed: 03/01/2025] Open
Abstract
Purpose Subjective cognitive decline (SCD) is an early manifestation of the Alzheimer's disease (AD) continuum, and accurately diagnosing SCD to differentiate it from neurotypical aging in older adults is a common challenge for researchers. Methods This review examines and summarizes relevant studies regarding the neuroimaging of the AD continuum, and comprehensively summarizes and outlines the SCD clinical features characterizing along with the corresponding neuroimaging changes involving structural, functional, and metabolic networks. Results The clinical characteristics of SCD include a subjective decline in self-perceived cognitive function, and there are significant imaging changes, such as reductions in gray matter volume in certain brain regions, abnormalities in the integrity of white matter tracts and diffusion metrics, alterations in functional connectivity between different sub-networks or within networks, as well as abnormalities in brain metabolic networks and cerebral blood flow perfusion. Conclusion The 147 referenced studies in this paper indicate that exploring the structural, functional, and metabolic network changes in the brain related to SCD through neuroimaging aims to enhance the goals and mission of brain science development programs: "Understanding the Brain," "Protecting the Brain," and "Creating the Brain," thereby strengthening researchers' investigation into the mechanisms of brain function. Early diagnosis of SCD, along with prompt intervention, can reduce the incidence of AD spectrum while improving patients' quality of life, even integrating numerous scientific research achievements into unified and established standards and applying them in clinical practice by doctors, thus all encouraging researchers to further investigate SCD issues in older adults.
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Affiliation(s)
- Han Yingmei
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Wang Chaojie
- Acupuncture and Moxibustion Massage College, Liaoning University of Traditional Chinese Medicine, Shenyang, Liaoning, China
| | - Zhang Yi
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Li Yijie
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Zhang Heng
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Feng Ze
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Li Weiqing
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Chu Bingyuan
- Graduate School of Heilongjiang University of Chinese Medicine, Harbin, China
| | - Wang Feng
- Division of CT and MRI, First Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin, China
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Pérez-Millan A, Lal-Trehan Estrada UM, Falgàs N, Guillén N, Borrego-Écija S, Juncà-Parella J, Bosch B, Tort-Merino A, Sarto J, Augé JM, Antonell A, Bargalló N, Ruiz-García R, Naranjo L, Balasa M, Lladó A, Sala-Llonch R, Sánchez-Valle R. The Cortical Asymmetry Index for subtyping dementia patients. Eur Radiol 2025:10.1007/s00330-025-11400-y. [PMID: 39934339 DOI: 10.1007/s00330-025-11400-y] [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: 06/07/2024] [Revised: 12/19/2024] [Accepted: 01/02/2025] [Indexed: 02/13/2025]
Abstract
OBJECTIVES Frontotemporal dementia (FTD) usually shows more asymmetric atrophy patterns than Alzheimer's disease (AD). We aim to quantify this asymmetry to differentiate FTD, AD, and FTD subtypes. METHODS We studied T1-MRI scans, including FTD (different phenotypes), AD, and healthy controls (CTR). We defined the Cortical Asymmetry Index (CAI) using measures based on a metric derived from information theory with the cortical thickness measures. Some participants had additional follow-up MRIs, cerebrospinal fluid (CSF), or plasma measures. We analysed differences at cross-sectional and longitudinal levels. We then clustered FTD and AD participants based on the CAI values and studied the patients' fluid biomarker characteristics within each cluster. RESULTS A total of 101 FTD patients (64 ± 8 years, 53 men), 230 AD patients (65 ± 10 years, 84 men), and 173 CTR (59 ± 15 years, 67 men) were studied. CAI differentiated FTD, AD, and CTR. It also distinguished the semantic variant primary progressive aphasia (svPPA) from the other FTD phenotypes. In FTD, the CAI increased over time. The cluster analysis identified two subgroups within FTD, characterised by different neurofilament-light (NfL) levels, and two subgroups within AD, with different plasma glial fibrillary acidic protein (GFAP) levels. In AD, CAI correlated with GFAP and Mini-Mental State Examination (MMSE); in FTD, the CAI was associated with NfL levels. CONCLUSIONS The proposed method quantifies asymmetries previously described visually. The CAI could define clinically and biologically meaningful disease subgroups in the differential diagnosis of AD and FTD and its subtypes. CAI could also be of interest in tracking disease progression in FTD. KEY POINTS Question There is a need to find quantitative metrics from MRI that can identify disease subgroups, and that could be useful for diagnosis and tracking. Findings We propose a Cortical Asymmetry Index that differentiates Alzheimer's disease (AD) from Frontotemporal dementia (FTD), distinguishes FTD subtypes, correlates with NFL and GFAP levels, and monitors FTD progression. Clinical relevance Our proposed index holds the potential to support clinical applications for diagnosis and disease tracking in AD and FTD, using a quantitative summary metric from MRI data. It also contributes to the understanding of these diseases.
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Affiliation(s)
- Agnès Pérez-Millan
- Alzheimer's Disease and Other Cognitive Disorders Group, Service of Neurology, Hospital Clínic de Barcelona, Fundació Recerca Clínic Barcelona-IDIBAPS, 08036, Barcelona, Spain
- Institut de Neurociències, University of Barcelona, 08036, Barcelona, Spain
- Department of Biomedicine, University of Barcelona, 08036, Barcelona, Spain
| | - Uma Maria Lal-Trehan Estrada
- Institut de Neurociències, University of Barcelona, 08036, Barcelona, Spain
- Department of Biomedicine, University of Barcelona, 08036, Barcelona, Spain
| | - Neus Falgàs
- Alzheimer's Disease and Other Cognitive Disorders Group, Service of Neurology, Hospital Clínic de Barcelona, Fundació Recerca Clínic Barcelona-IDIBAPS, 08036, Barcelona, Spain
| | - Núria Guillén
- Alzheimer's Disease and Other Cognitive Disorders Group, Service of Neurology, Hospital Clínic de Barcelona, Fundació Recerca Clínic Barcelona-IDIBAPS, 08036, Barcelona, Spain
| | - Sergi Borrego-Écija
- Alzheimer's Disease and Other Cognitive Disorders Group, Service of Neurology, Hospital Clínic de Barcelona, Fundació Recerca Clínic Barcelona-IDIBAPS, 08036, Barcelona, Spain
| | - Jordi Juncà-Parella
- Alzheimer's Disease and Other Cognitive Disorders Group, Service of Neurology, Hospital Clínic de Barcelona, Fundació Recerca Clínic Barcelona-IDIBAPS, 08036, Barcelona, Spain
| | - Beatriz Bosch
- Alzheimer's Disease and Other Cognitive Disorders Group, Service of Neurology, Hospital Clínic de Barcelona, Fundació Recerca Clínic Barcelona-IDIBAPS, 08036, Barcelona, Spain
| | - Adrià Tort-Merino
- Alzheimer's Disease and Other Cognitive Disorders Group, Service of Neurology, Hospital Clínic de Barcelona, Fundació Recerca Clínic Barcelona-IDIBAPS, 08036, Barcelona, Spain
| | - Jordi Sarto
- Alzheimer's Disease and Other Cognitive Disorders Group, Service of Neurology, Hospital Clínic de Barcelona, Fundació Recerca Clínic Barcelona-IDIBAPS, 08036, Barcelona, Spain
| | - Josep Maria Augé
- Biochemistry and Molecular Genetics Department, Hospital Clínic de Barcelona, 08036, Barcelona, Spain
| | - Anna Antonell
- Alzheimer's Disease and Other Cognitive Disorders Group, Service of Neurology, Hospital Clínic de Barcelona, Fundació Recerca Clínic Barcelona-IDIBAPS, 08036, Barcelona, Spain
| | - Núria Bargalló
- Image Diagnostic Centre, Hospital Clínic de Barcelona, Barcelona, Spain
- CIBER de Salud Mental, Instituto de Salud Carlos III, Magnetic Resonance Image Core Facility, IDIBAPS, 08036, Barcelona, Spain
| | - Raquel Ruiz-García
- Immunology Service, Biomedical Diagnostic Center, Hospital Clínic de Barcelona, 08036, Barcelona, Spain
| | - Laura Naranjo
- Immunology Service, Biomedical Diagnostic Center, Hospital Clínic de Barcelona, 08036, Barcelona, Spain
| | - Mircea Balasa
- Alzheimer's Disease and Other Cognitive Disorders Group, Service of Neurology, Hospital Clínic de Barcelona, Fundació Recerca Clínic Barcelona-IDIBAPS, 08036, Barcelona, Spain
| | - Albert Lladó
- Alzheimer's Disease and Other Cognitive Disorders Group, Service of Neurology, Hospital Clínic de Barcelona, Fundació Recerca Clínic Barcelona-IDIBAPS, 08036, Barcelona, Spain
- Institut de Neurociències, University of Barcelona, 08036, Barcelona, Spain
| | - Roser Sala-Llonch
- Institut de Neurociències, University of Barcelona, 08036, Barcelona, Spain
- Department of Biomedicine, University of Barcelona, 08036, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), Barcelona, Spain
- Institute of Biomedical Research August Pi i Sunyer (IDIBAPS), 08036, Barcelona, Spain
| | - Raquel Sánchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders Group, Service of Neurology, Hospital Clínic de Barcelona, Fundació Recerca Clínic Barcelona-IDIBAPS, 08036, Barcelona, Spain.
- Institut de Neurociències, University of Barcelona, 08036, Barcelona, Spain.
- Departament de Medicina, Facultat de Medicina i Ciències de la Salut, Universitat de Barcelona, 08036, Barcelona, Spain.
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Sim MA, Doecke JD, Liew OW, Wong LL, Tan ESJ, Chan SP, Chong JRF, Cai Y, Hilal S, Venketasubramanian N, Tan BY, Lai MKP, Choi H, Masters CL, Richards AM, Chen CLH. Plasma proteomics for cognitive decline and dementia-A Southeast Asian cohort study. Alzheimers Dement 2025; 21:e14577. [PMID: 39998981 PMCID: PMC11854348 DOI: 10.1002/alz.14577] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2024] [Revised: 12/27/2024] [Accepted: 01/12/2025] [Indexed: 02/27/2025]
Abstract
INTRODUCTION The prognostic utility of plasma proteomics for cognitive decline and dementia in a Southeast Asian population characterized by high cerebrovascular disease (CeVD) burden is underexplored. METHODS We examined this in a Singaporean memory clinic cohort of 528 subjects (n = 300, CeVD; n = 167, incident cognitive decline) followed-up for 4 years. RESULTS Of 1441 plasma proteins surveyed, a 12-protein signature significantly predicted cognitive decline (q-value < .05). Sixteen diverse biological processes were implicated in cognitive decline. Ten proteins independently predicted incident dementia (q-value < .05). A unified prediction model combining plasma proteins with clinical risk factors increased the area under the curve for outcome prediction from 0.62 to 0.85. External validation in the cerebrospinal fluid proteome of an independent Caucasian cohort replicated four of the significantly predictive plasma markers for cognitive decline namely: GFAP, NEFL, AREG, and PPY. DISCUSSION The prognostic proteins prioritized in our study provide robust signals in two different biological matrices, representing potential mechanistic targets for dementia and cognitive decline. HIGHLIGHTS A total of 1441 plasma proteins were profiled in a Singaporean memory clinic cohort. We report prognostic plasma protein signatures for cognitive decline and dementia. External validation was performed in the cerebrospinal fluid proteome of a Caucasian cohort. A concordant proteomic signature was identified across both biofluids and cohorts. Further studies are needed to explore the therapeutic implications of these proteins for dementia.
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Affiliation(s)
- Ming Ann Sim
- Departments of Pharmacology and Psychological Medicine, Memory Aging and Cognition CentreNational University of SingaporeSingaporeSingapore
- Yong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore
- Department of AnesthesiaNational University Health SystemSingaporeSingapore
| | - James D. Doecke
- Australian E‐Health Research CentreCSIROHerstonQueenslandAustralia
| | - Oi Wah Liew
- Department of CardiologyNational University Heart CentreSingaporeSingapore
- Cardiovascular Research InstituteNational University of SingaporeSingaporeSingapore
| | - Lee Lee Wong
- Department of CardiologyNational University Heart CentreSingaporeSingapore
- Cardiovascular Research InstituteNational University of SingaporeSingaporeSingapore
| | - Eugene S. J. Tan
- Yong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore
- Department of CardiologyNational University Heart CentreSingaporeSingapore
| | - Siew Pang Chan
- Department of CardiologyNational University Heart CentreSingaporeSingapore
- Cardiovascular Research InstituteNational University of SingaporeSingaporeSingapore
| | - Joyce R. F. Chong
- Departments of Pharmacology and Psychological Medicine, Memory Aging and Cognition CentreNational University of SingaporeSingaporeSingapore
| | - Yuan Cai
- Department of Medicine and Therapeutics, Faculty of MedicineDivision of NeurologyThe Chinese University of Hong KongMa Liu ShuiHong Kong
| | - Saima Hilal
- Saw Swee Hock School of Public HealthNational University of Singapore and National University Health SystemSingaporeSingapore
| | | | - Boon Yeow Tan
- Department of MedicineSt Luke's HospitalSingaporeSingapore
| | | | - Mitchell K. P Lai
- Departments of Pharmacology and Psychological Medicine, Memory Aging and Cognition CentreNational University of SingaporeSingaporeSingapore
| | - Hyungwon Choi
- Cardiovascular Research InstituteNational University of SingaporeSingaporeSingapore
- Department of MedicineYong Loo Lin School of MedicineNational University of SingaporeSingaporeSingapore
- Singapore Lipidomics IncubatorLife Sciences InstituteNational University of SingaporeSingaporeSingapore
| | - Colin L. Masters
- The Florey Institute of Neuroscience and Mental HealthThe University of MelbourneParkvilleVictoriaAustralia
| | - Arthur Mark Richards
- Department of CardiologyNational University Heart CentreSingaporeSingapore
- Cardiovascular Research InstituteNational University of SingaporeSingaporeSingapore
- Christchurch Heart InstituteUniversity of OtagoDunedinNew Zealand
| | - Christopher L. H. Chen
- Departments of Pharmacology and Psychological Medicine, Memory Aging and Cognition CentreNational University of SingaporeSingaporeSingapore
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De Meyer S, Blujdea ER, Schaeverbeke JM, Adamczuk K, Vandenberghe R, Poesen K, Teunissen CE. Serum biomarkers as prognostic markers for Alzheimer's disease in a clinical setting. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2025; 17:e70071. [PMID: 39886322 PMCID: PMC11780118 DOI: 10.1002/dad2.70071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 12/06/2024] [Accepted: 12/15/2024] [Indexed: 02/01/2025]
Abstract
INTRODUCTION Blood-based glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and phosphorylated tau (pTau) have shown promising prognostic potential in Alzheimer's disease (AD), but their applicability in clinical settings where comorbidities are prevalent remains uncertain. METHODS Simoa assays quantified GFAP, NfL, and pTau181 in retrospectively retrieved prediagnostic serum samples from 102 AD patients and 21 non-AD controls. RESULTS Higher serum GFAP levels predicted earlier clinical presentation and faster subsequent Mini-Mental State Examination decline in AD patients. Serum NfL levels were increased in patients with arterial hypertension (AHT), kidney dysfunction, and a history of stroke and only demonstrated predictive value for time to clinical AD presentation after adjustment for these comorbidities. Serum pTau181 instability during long-term storage at -20°C prevented its prognostic evaluation in retrospectively retrieved serum samples. DISCUSSION Serum GFAP is a robust prognostic marker for AD progression, whereas NfL is impacted by various comorbidities, which complicates the interpretation of its prognostic value. Highlights Serum GFAP levels predict time to clinical AD presentation.Serum NfL levels are increased by hypertension, kidney disease, and stroke history.Prognostic value of serum NfL in AD is only evident after comorbidity correction.Serum levels of GFAP, but not NfL, increase over time within prediagnostic AD stages.
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Affiliation(s)
- Steffi De Meyer
- Laboratory for Molecular Neurobiomarker ResearchDepartment of NeurosciencesLeuven Brain Institute, KU LeuvenLeuvenBelgium
- Laboratory for Cognitive NeurologyDepartment of NeurosciencesLeuven Brain Institute, KU LeuvenLeuvenBelgium
| | - Elena R. Blujdea
- Neurochemistry LaboratoryDepartment of Laboratory MedicineAmsterdam UMCAmsterdamThe Netherlands
| | - Jolien M. Schaeverbeke
- Laboratory for Cognitive NeurologyDepartment of NeurosciencesLeuven Brain Institute, KU LeuvenLeuvenBelgium
- Laboratory for NeuropathologyDepartment of Imaging and PathologyLeuven Brain Institute, KU LeuvenLeuvenBelgium
| | - Katarzyna Adamczuk
- Laboratory for Cognitive NeurologyDepartment of NeurosciencesLeuven Brain Institute, KU LeuvenLeuvenBelgium
| | - Rik Vandenberghe
- Laboratory for Cognitive NeurologyDepartment of NeurosciencesLeuven Brain Institute, KU LeuvenLeuvenBelgium
- Neurology DepartmentUZ LeuvenLeuvenBelgium
| | - Koen Poesen
- Laboratory for Molecular Neurobiomarker ResearchDepartment of NeurosciencesLeuven Brain Institute, KU LeuvenLeuvenBelgium
- Laboratory Medicine DepartmentUZ LeuvenLeuvenBelgium
| | - Charlotte E. Teunissen
- Neurochemistry LaboratoryDepartment of Laboratory MedicineAmsterdam UMCAmsterdamThe Netherlands
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An C, Cai H, Ren Z, Fu X, Quan S, Jia L. Biofluid biomarkers for Alzheimer's disease: past, present, and future. MEDICAL REVIEW (2021) 2024; 4:467-491. [PMID: 39664082 PMCID: PMC11629312 DOI: 10.1515/mr-2023-0071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/31/2023] [Accepted: 09/04/2024] [Indexed: 12/13/2024]
Abstract
Alzheimer's disease (AD) is a gradually progressive neurodegenerative disease with tremendous social and economic burden. Therefore, early and accurate diagnosis is imperative for effective treatment or prevention of the disease. Cerebrospinal fluid and blood biomarkers emerge as favorable diagnostic tools due to their relative accessibility and potential for widespread clinical use. This review focuses on the AT(N) biomarker system, which includes biomarkers reflecting AD core pathologies, amyloid deposition, and pathological tau, as well as neurodegeneration. Novel biomarkers associated with inflammation/immunity, synaptic dysfunction, vascular pathology, and α-synucleinopathy, which might contribute to either the pathogenesis or the clinical progression of AD, have also been discussed. Other emerging candidates including non-coding RNAs, metabolites, and extracellular vesicle-based markers have also enriched the biofluid biomarker landscape for AD. Moreover, the review discusses the current challenges of biofluid biomarkers in AD diagnosis and offers insights into the prospective future development.
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Affiliation(s)
- Chengyu An
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Huimin Cai
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Ziye Ren
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Xiaofeng Fu
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Shuiyue Quan
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China
| | - Longfei Jia
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, Capital Medical University, National Clinical Research Center for Geriatric Diseases, Beijing, China
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Dubois B, Villain N, Schneider L, Fox N, Campbell N, Galasko D, Kivipelto M, Jessen F, Hanseeuw B, Boada M, Barkhof F, Nordberg A, Frolich L, Waldemar G, Frederiksen KS, Padovani A, Planche V, Rowe C, Bejanin A, Ibanez A, Cappa S, Caramelli P, Nitrini R, Allegri R, Slachevsky A, de Souza LC, Bozoki A, Widera E, Blennow K, Ritchie C, Agronin M, Lopera F, Delano-Wood L, Bombois S, Levy R, Thambisetty M, Georges J, Jones DT, Lavretsky H, Schott J, Gatchel J, Swantek S, Newhouse P, Feldman HH, Frisoni GB. Alzheimer Disease as a Clinical-Biological Construct-An International Working Group Recommendation. JAMA Neurol 2024; 81:1304-1311. [PMID: 39483064 PMCID: PMC12010406 DOI: 10.1001/jamaneurol.2024.3770] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2024]
Abstract
Importance Since 2018, a movement has emerged to define Alzheimer disease (AD) as a purely biological entity based on biomarker findings. The recent revision of the Alzheimer's Association (AA) criteria for AD furthers this direction. However, concerns about a purely biological definition of AD being applied clinically, the understanding of AD by society at large, and the translation of blood-based biomarkers into clinical practice prompt these International Working Group (IWG) updated recommendations. Objective To consider the revised AA criteria and to offer an alternative definitional view of AD as a clinical-biological construct for clinical use. The recommendations of the 2021 IWG diagnostic criteria are updated for further elaborating at-risk and presymptomatic states. Evidence Review PubMed was searched for articles published between July 1, 2020, and March 1, 2024, using the terms "biomarker" OR "amyloid" OR "tau" OR "neurodegeneration" OR "preclinical" OR "CSF" OR "PET" OR "plasma" AND "Alzheimer's disease." The references of relevant articles were also searched. Findings In the new AA diagnostic criteria, AD can be defined clinically as encompassing cognitively normal people having a core 1 AD biomarker. However, recent literature shows that the majority of biomarker-positive cognitively normal individuals will not become symptomatic along a proximate timeline. In the clinical setting, disclosing a diagnosis of AD to cognitively normal people with only core 1 AD biomarkers represents the most problematic implication of a purely biological definition of the disease. Conclusions and Relevance The ultimate aim of the field was to foster effective AD treatments, including preventing symptoms and dementia. The approach of diagnosing AD without a clinical and biological construct would be unwarranted and potentially concerning without a clear knowledge of when or whether symptoms will ever develop. It is recommended that those who are amyloid-positive only and, more generally, most biomarker-positive cognitively normal individuals, should not be labeled as having AD. Rather, they should be considered as being at risk for AD. The expansion of presymptomatic AD is viewed as a better diagnostic construct for those with a specific pattern of biomarkers, indicating that they are proximate to the expression of symptoms in the near future.
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Affiliation(s)
- Bruno Dubois
- AP-HP Sorbonne Université, Pitié-Salpêtrière Hospital, Department of Neurology, Institute of Memory and Alzheimer’s Disease, Paris, France
- Sorbonne Université, INSERM U1127, CNRS 7225, Institut du Cerveau - ICM, ‘FrontLab’, Paris, France
| | - Nicolas Villain
- AP-HP Sorbonne Université, Pitié-Salpêtrière Hospital, Department of Neurology, Institute of Memory and Alzheimer’s Disease, Paris, France
- Sorbonne Université, INSERM U1127, CNRS 7225, Institut du Cerveau - ICM, ‘Maladie d’Alzheimer, Maladies à prions’, Paris, France
| | - Lon Schneider
- Keck School of Medicine of the University of Southern California, Los Angeles, USA
| | - Nick Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, and the UK Dementia Research Institute, UCL Queen Square Institute of Neurology, London WC1N 3AR, UK
| | - Noll Campbell
- Purdue University College of Pharmacy, West Lafayette, Indiana, USA
- Purdue University Center for Aging and the Life Course, West Lafayette, Indiana, USA
- Indiana University Center for Aging Research, Indianapolis, Indiana, USA
| | - Douglas Galasko
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Miia Kivipelto
- Center for Alzheimer Research, Karolinska Institutet, Department of Geriatric Medicine, Karolinska University Hospital, Stockholm, Sweden
- Institute of Clinical Medicine/ Neurology, University of Eastern Finland, Kuopio, Finland
| | - Frank Jessen
- Department of Psychiatry, Medical Faculty, University of Cologne, Cologne, Germany
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Bernard Hanseeuw
- Department of Neurology, Cliniques Universitaires Saint-Luc, Brussels, Belgium
- Institute of Neurosciences, UCLouvain, Brussels, Belgium
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA Institute of Neuroscience, UC Louvain, Brussels, Belgium
| | - Mercè Boada
- Ace Alzheimer Center Barcelona – Universitat Internacional de Catalunya, Barcelona, Spain
- Networking Research Center on Neurodegenerative Diseases (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain
| | - Frederik Barkhof
- Centre for Medical Image Computing (CMIC), Department of Medical Physics and Bioengineering, University College London, London, United Kingdom
- Amsterdam UMC, location VUmc, Department of Radiology and Nuclear Medicine, Amsterdam, The Netherlands
- Queen Square Institute of Neurology, University College London, UK
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, The Aging Brain, Karolinska University Hospital. Stockholm, Sweden
| | - Lutz Frolich
- Department of Geriatric Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Gunhild Waldemar
- Danish Dementia Research Centre, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Dept. of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Kristian Steen Frederiksen
- Danish Dementia Research Centre, Department of Neurology, Copenhagen University Hospital - Rigshospitalet, Copenhagen, Denmark
- Dept. of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
| | - Alessandro Padovani
- Director Neurology and Neurophysiology Section, Department Clinical and Experimental Sciences, University of Brescia
- Director of the Hospital Department of “Continuità di Cura e Fragilità”, ASST Spedali Civili di Brescia
| | - Vincent Planche
- Univ. Bordeaux, CNRS, Institut des Maladies Neurodégénératives, UMR 5293, Bordeaux, France
- Pôle de Neurosciences Cliniques, Centre Mémoire de Ressources et de Recherche, CHU de Bordeaux, France
| | - Christopher Rowe
- Department of Molecular Imaging and Therapy, Austin Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Alexandre Bejanin
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
- Center of Biomedical Investigation Network for Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Agustin Ibanez
- Latin American Institute for Brain Health (BrainLat), Universidad Adolfo Ibanez, Santiago, Chile
- Global Brain Health Institute (GBHI), Trinity College Dublin, Dublin, Ireland
| | - Stefano Cappa
- University School for Advanced Studies (IUSS), Pavia, Italy
- RCCS Mondino Foundation, Pavia, Italy
| | - Paulo Caramelli
- Behavioral and Cognitive Neurology UNit, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte (MG), Brazil
| | - Ricardo Nitrini
- Department of Neurology, Faculdade de Medicina, Universidade de São Paulo, Brazil
| | - Ricardo Allegri
- Department of Cognitive Neurology, Fleni Neurological Institute, Buenos Aires, Argentina
- Department of Cognitive Neurosciences, Universidad de la Costa (CUC), Barranquilla, Colombia
| | - Andrea Slachevsky
- Geroscience Center for Brain Health and Metabolism (GERO), Santiago, Chile
- Memory and Neuropsychiatric Center (CMYN) Neurology Department, Hospital del Salvador and Neuropsychology and Clinical Neuroscience Laboratory (LANNEC), Institute of Biomedical Sciences (ICBM), Faculty of Medicine, University of Chile
- Neurology and Psychiatry Department, Clínica Alemana-Universidad Desarrollo, Santiago, Chile
| | - Leonardo Cruz de Souza
- Behavioral and Cognitive Neurology UNit, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte (MG), Brazil
| | - Andrea Bozoki
- Department of Neurology, University of North Carolina, Chapel Hill, North Carolina, USA
| | - Eric Widera
- Division of Geriatrics, University of California San Francisco
- Hospice & Palliative Care, San Francisco Veterans Affairs Health Care System
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Craig Ritchie
- Professor of Brain Health and Neurodegenerative Medicine, University of St Andrews, Scotland. UK
- Scottish Brain Sciences, Edinburgh, Scotland. UK
| | | | - Francisco Lopera
- Grupo de Neurociencias de Antioquia (GNA), Facultad de Medicina, Universidad de Antioquia, Medellín, Colombia
| | - Lisa Delano-Wood
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego Health, La Jolla, CA, USA
- Center for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
| | - Stéphanie Bombois
- AP-HP Sorbonne Université, Pitié-Salpêtrière Hospital, Department of Neurology, Institute of Memory and Alzheimer’s Disease, Paris, France
| | - Richard Levy
- AP-HP Sorbonne Université, Pitié-Salpêtrière Hospital, Department of Neurology, Institute of Memory and Alzheimer’s Disease, Paris, France
- Sorbonne Université, INSERM U1127, CNRS 7225, Institut du Cerveau - ICM, ‘FrontLab’, Paris, France
| | - Madhav Thambisetty
- Clinical and Translational Neuroscience Section, Laboratory of Behavioral Neuroscience, National Institute on Aging, National Institutes of Health Baltimore, MD 21224
| | | | - David T. Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | - Helen Lavretsky
- Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences
- David Geffen School of Medicine, University of California, Los Angeles (UCLA)
| | - Jonathan Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Jennifer Gatchel
- Massachusetts General Hospital Department of Psychiatry, Boston MA
- McLean Hospital, Belmont MA
- Harvard Medical School, Boston MA
- Baylor College of Medicine Department of Psychiatry, Houston TX USA
- Michael E. DeBakey VA Medical Center, Houston TX USA
| | | | - Paul Newhouse
- Vanderbilt University, 2301 Vanderbilt Place, Nashville, TN, 37235, USA
- Center for Cognitive Medicine, Department of Psychiatry, Vanderbilt University Medical Center, Nashville, TN, USA
- VA-TVHS Geriatric Research Education and Clinical Center, Nashville, TN, USA
| | - Howard H Feldman
- Department of Neurosciences University of California, San Diego, La Jolla, CA, USA
- Shiley-Marcos Alzheimer’s disease Research Center, University of California, San Diego, La Jolla, CA, USA
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Memory Clinic, University Hospital of Geneva, Geneva, Switzerland
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9
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Roveta F, Bonino L, Piella EM, Rainero I, Rubino E. Neuroinflammatory Biomarkers in Alzheimer's Disease: From Pathophysiology to Clinical Implications. Int J Mol Sci 2024; 25:11941. [PMID: 39596011 PMCID: PMC11593837 DOI: 10.3390/ijms252211941] [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: 10/01/2024] [Revised: 11/02/2024] [Accepted: 11/04/2024] [Indexed: 11/28/2024] Open
Abstract
The identification of neuroinflammation as a critical factor in Alzheimer's disease (AD) has expanded the focus of research beyond amyloid-β and tau pathology. The neuroinflammatory fluid biomarkers GFAP, sTREM2, and YKL-40 have gained attention for their potential in early detection and monitoring of disease progression. Plasma GFAP has demonstrated promise in predicting the conversion from mild cognitive impairment to AD dementia, while sTREM2 highlights microglial activation, although there are conflicting results regarding its dynamics in AD pathogenesis. Advanced imaging techniques, such as PET tracers targeting TSPO and MAO-B, have also been developed to visualize glial activation in vivo, offering spatial and temporal insights into neuroinflammatory processes. However, the clinical implementation of these biomarkers faces challenges due to their lack of specificity, as many of them can be elevated in other conditions. Therapeutic strategies targeting neuroinflammation are emerging, with TREM2-targeting therapies and antidiabetic drugs like GLP-1 receptor agonists showing potential in modulating microglial activity. Nevertheless, the complexity of neuroinflammation, which encompasses both protective and harmful responses, necessitates further research to fully unravel its role and optimize therapeutic approaches for AD.
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Affiliation(s)
| | | | | | | | - Elisa Rubino
- Aging Brain and Memory Clinic, Department of Neuroscience “Rita Levi-Montalcini”, University of Torino, 10126 Torino, Italy; (F.R.); (L.B.); (E.M.P.); (I.R.)
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10
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Mitolo M, Lombardi G, Manca R, Nacmias B, Venneri A. Association between blood-based protein biomarkers and brain MRI in the Alzheimer's disease continuum: a systematic review. J Neurol 2024; 271:7120-7140. [PMID: 39264441 PMCID: PMC11560990 DOI: 10.1007/s00415-024-12674-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2024] [Revised: 08/27/2024] [Accepted: 08/28/2024] [Indexed: 09/13/2024]
Abstract
Blood-based biomarkers (BBM) are becoming easily detectable tools to reveal pathological changes in Alzheimer's disease (AD). A comprehensive and up-to-date overview of the association between BBM and brain MRI parameters is not available. This systematic review aimed to summarize the literature on the associations between the main BBM and MRI markers across the clinical AD continuum. A systematic literature search was carried out on PubMed and Web of Science and a total of 33 articles were included. Hippocampal volume was positively correlated with Aβ42 and Aβ42/Aβ40 and negatively with Aβ40 plasma levels. P-tau181 and p-tau217 concentrations were negatively correlated with temporal grey matter volume and cortical thickness. NfL levels were negatively correlated with white matter microstructural integrity, whereas GFAP levels were positively correlated with myo-inositol values in the posterior cingulate cortex/precuneus. These findings highlight consistent associations between various BBM and brain MRI markers even in the pre-clinical and prodromal stages of AD. This suggests a possible advantage in combining multiple AD-related markers to improve accuracy of early diagnosis, prognosis, progression monitoring and treatment response.
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Affiliation(s)
- Micaela Mitolo
- Department of Medicine and Surgery, University of Parma, Parma, Italy
- IRCCS Istituto delle Scienze Neurologiche di Bologna, Bologna, Italy
| | - Gemma Lombardi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi Onlus, Florence, Italy
| | - Riccardo Manca
- Department of Medicine and Surgery, University of Parma, Parma, Italy.
- Department of Life Sciences, Brunel University London, Kingston Lane, Uxbridge, UB8 3PH, UK.
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi Onlus, Florence, Italy
| | - Annalena Venneri
- Department of Medicine and Surgery, University of Parma, Parma, Italy
- Department of Life Sciences, Brunel University London, Kingston Lane, Uxbridge, UB8 3PH, UK
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11
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Delvenne A, Gobom J, Schindler SE, Kate MT, Reus LM, Dobricic V, Tijms BM, Benzinger TLS, Cruchaga C, Teunissen CE, Ramakers I, Martinez‐Lage P, Tainta M, Vandenberghe R, Schaeverbeke J, Engelborghs S, Roeck ED, Popp J, Peyratout G, Tsolaki M, Freund‐Levi Y, Lovestone S, Streffer J, Barkhof F, Bertram L, Blennow K, Zetterberg H, Visser PJ, Vos SJB. CSF proteomic profiles of neurodegeneration biomarkers in Alzheimer's disease. Alzheimers Dement 2024; 20:6205-6220. [PMID: 38970402 PMCID: PMC11497678 DOI: 10.1002/alz.14103] [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: 04/03/2024] [Revised: 06/05/2024] [Accepted: 06/06/2024] [Indexed: 07/08/2024]
Abstract
INTRODUCTION We aimed to unravel the underlying pathophysiology of the neurodegeneration (N) markers neurogranin (Ng), neurofilament light (NfL), and hippocampal volume (HCV), in Alzheimer's disease (AD) using cerebrospinal fluid (CSF) proteomics. METHODS Individuals without dementia were classified as A+ (CSF amyloid beta [Aβ]42), T+ (CSF phosphorylated tau181), and N+ or N- based on Ng, NfL, or HCV separately. CSF proteomics were generated and compared between groups using analysis of covariance. RESULTS Only a few individuals were A+T+Ng-. A+T+Ng+ and A+T+NfL+ showed different proteomic profiles compared to A+T+Ng- and A+T+NfL-, respectively. Both Ng+ and NfL+ were associated with neuroplasticity, though in opposite directions. Compared to A+T+HCV-, A+T+HCV+ showed few proteomic changes, associated with oxidative stress. DISCUSSION Different N markers are associated with distinct neurodegenerative processes and should not be equated. N markers may differentially complement disease staging beyond amyloid and tau. Our findings suggest that Ng may not be an optimal N marker, given its low incongruency with tau pathophysiology. HIGHLIGHTS In Alzheimer's disease, neurogranin (Ng)+, neurofilament light (NfL)+, and hippocampal volume (HCV)+ showed differential protein expression in cerebrospinal fluid. Ng+ and NfL+ were associated with neuroplasticity, although in opposite directions. HCV+ showed few proteomic changes, related to oxidative stress. Neurodegeneration (N) markers may differentially refine disease staging beyond amyloid and tau. Ng might not be an optimal N marker, as it relates more closely to tau.
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12
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Park MK, Ahn J, Kim YJ, Lee JW, Lee JC, Hwang SJ, Kim KC. Predicting Longitudinal Cognitive Decline and Alzheimer's Conversion in Mild Cognitive Impairment Patients Based on Plasma Biomarkers. Cells 2024; 13:1085. [PMID: 38994939 PMCID: PMC11240497 DOI: 10.3390/cells13131085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2024] [Revised: 06/20/2024] [Accepted: 06/20/2024] [Indexed: 07/13/2024] Open
Abstract
The increasing burden of Alzheimer's disease (AD) emphasizes the need for effective diagnostic and therapeutic strategies. Despite available treatments targeting amyloid beta (Aβ) plaques, disease-modifying therapies remain elusive. Early detection of mild cognitive impairment (MCI) patients at risk for AD conversion is crucial, especially with anti-Aβ therapy. While plasma biomarkers hold promise in differentiating AD from MCI, evidence on predicting cognitive decline is lacking. This study's objectives were to evaluate whether plasma protein biomarkers could predict both cognitive decline in non-demented individuals and the conversion to AD in patients with MCI. This study was conducted as part of the Korean Longitudinal Study on Cognitive Aging and Dementia (KLOSCAD), a prospective, community-based cohort. Participants were based on plasma biomarker availability and clinical diagnosis at baseline. The study included MCI (n = 50), MCI-to-AD (n = 21), and cognitively unimpaired (CU, n = 40) participants. Baseline plasma concentrations of six proteins-total tau (tTau), phosphorylated tau at residue 181 (pTau181), amyloid beta 42 (Aβ42), amyloid beta 40 (Aβ40), neurofilament light chain (NFL), and glial fibrillary acidic protein (GFAP)-along with three derivative ratios (pTau181/tTau, Aβ42/Aβ40, pTau181/Aβ42) were analyzed to predict cognitive decline over a six-year follow-up period. Baseline protein biomarkers were stratified into tertiles (low, intermediate, and high) and analyzed using a linear mixed model (LMM) to predict longitudinal cognitive changes. In addition, Kaplan-Meier analysis was performed to discern whether protein biomarkers could predict AD conversion in the MCI subgroup. This prospective cohort study revealed that plasma NFL may predict longitudinal declines in Mini-Mental State Examination (MMSE) scores. In participants categorized as amyloid positive, the NFL biomarker demonstrated predictive performance for both MMSE and total scores of the Korean version of the Consortium to Establish a Registry for Alzheimer's Disease Assessment Packet (CERAD-TS) longitudinally. Additionally, as a baseline predictor, GFAP exhibited a significant association with cross-sectional cognitive impairment in the CERAD-TS measure, particularly in amyloid positive participants. Kaplan-Meier curve analysis indicated predictive performance of NFL, GFAP, tTau, and Aβ42/Aβ40 on MCI-to-AD conversion. This study suggests that plasma GFAP in non-demented participants may reflect baseline cross-sectional CERAD-TS scores, a measure of global cognitive function. Conversely, plasma NFL may predict longitudinal decline in MMSE and CERAD-TS scores in participants categorized as amyloid positive. Kaplan-Meier curve analysis suggests that NFL, GFAP, tTau, and Aβ42/Aβ40 are potentially robust predictors of future AD conversion.
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Affiliation(s)
- Min-Koo Park
- Department of Biological Sciences, College of Natural Sciences, Kangwon National University, Chuncheon 24341, Republic of Korea;
- Hugenebio Institute, Bio-Innovation Park, Erom, Inc., Chuncheon 24427, Republic of Korea; (J.-W.L.); (J.-C.L.)
| | - Jinhyun Ahn
- Department of Management Information Systems, College of Economics & Commerce, Jeju National University, Jeju 63243, Republic of Korea;
| | - Young-Ju Kim
- Department of Statistics, Division of Economics & Information Statistics, Kangwon National University, Chuncheon 24341, Republic of Korea;
| | - Ji-Won Lee
- Hugenebio Institute, Bio-Innovation Park, Erom, Inc., Chuncheon 24427, Republic of Korea; (J.-W.L.); (J.-C.L.)
| | - Jeong-Chan Lee
- Hugenebio Institute, Bio-Innovation Park, Erom, Inc., Chuncheon 24427, Republic of Korea; (J.-W.L.); (J.-C.L.)
| | - Sung-Joo Hwang
- Integrated Medicine Institute, Loving Care Hospital, Seongnam 463400, Republic of Korea;
| | - Keun-Cheol Kim
- Department of Biological Sciences, College of Natural Sciences, Kangwon National University, Chuncheon 24341, Republic of Korea;
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13
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Ly MT, Adler J, Ton Loy AF, Edmonds EC, Bondi MW, Delano-Wood L. Comparing neuropsychological, typical, and ADNI criteria for the diagnosis of mild cognitive impairment in Vietnam-era veterans. J Int Neuropsychol Soc 2024; 30:439-447. [PMID: 38263745 DOI: 10.1017/s135561772301144x] [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] [Indexed: 01/25/2024]
Abstract
OBJECTIVE Neuropsychological criteria for mild cognitive impairment (MCI) more accurately predict progression to Alzheimer's disease (AD) and are more strongly associated with AD biomarkers and neuroimaging profiles than ADNI criteria. However, research to date has been conducted in relatively healthy samples with few comorbidities. Given that history of traumatic brain injury (TBI) and post-traumatic stress disorder (PTSD) are risk factors for AD and common in Veterans, we compared neuropsychological, typical (Petersen/Winblad), and ADNI criteria for MCI in Vietnam-era Veterans with histories of TBI or PTSD. METHOD 267 Veterans (mean age = 69.8) from the DOD-ADNI study were evaluated for MCI using neuropsychological, typical, and ADNI criteria. Linear regressions adjusting for age and education assessed associations between MCI status and AD biomarker levels (cerebrospinal fluid [CSF] p-tau181, t-tau, and Aβ42) by diagnostic criteria. Logistic regressions adjusting for age and education assessed the effects of TBI severity and PTSD symptom severity simultaneously on MCI classification by each criteria. RESULTS Agreement between criteria was poor. Neuropsychological criteria identified more Veterans with MCI than typical or ADNI criteria, and were associated with higher CSF p-tau181 and t-tau. Typical and ADNI criteria were not associated with CSF biomarkers. PTSD symptom severity predicted MCI diagnosis by neuropsychological and ADNI criteria. History of moderate/severe TBI predicted MCI by typical and ADNI criteria. CONCLUSIONS MCI diagnosis using sensitive neuropsychological criteria is more strongly associated with AD biomarkers than conventional diagnostic methods. MCI diagnostics in Veterans would benefit from incorporation of comprehensive neuropsychological methods and consideration of the impact of PTSD.
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Affiliation(s)
- Monica T Ly
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego Health, La Jolla, CA, USA
| | - Jennifer Adler
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego Health, La Jolla, CA, USA
| | - Adan F Ton Loy
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
| | - Emily C Edmonds
- Banner Alzheimer's Institute, Tucson, AZ, USA
- Departments of Neurology and Psychology, University of Arizona, Tucson, AZ, USA
| | - Mark W Bondi
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego Health, La Jolla, CA, USA
| | - Lisa Delano-Wood
- Veterans Affairs San Diego Healthcare System, San Diego, CA, USA
- Department of Psychiatry, University of California San Diego Health, La Jolla, CA, USA
- Center for Stress and Mental Health, VA San Diego Healthcare System, San Diego, CA, USA
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14
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Giacomucci G, Mazzeo S, Ingannato A, Crucitti C, Bagnoli S, Padiglioni S, Romano L, Galdo G, Emiliani F, Frigerio D, Ferrari C, Moschini V, Morinelli C, Notarelli A, Sorbi S, Nacmias B, Bessi V. Future perspective and clinical applicability of the combined use of plasma phosphorylated tau 181 and neurofilament light chain in Subjective Cognitive Decline and Mild Cognitive Impairment. Sci Rep 2024; 14:11307. [PMID: 38760423 PMCID: PMC11101654 DOI: 10.1038/s41598-024-61655-6] [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: 03/01/2024] [Accepted: 05/08/2024] [Indexed: 05/19/2024] Open
Abstract
We aimed to assess diagnostic accuracy of plasma p-tau181 and NfL separately and in combination in discriminating Subjective Cognitive Decline (SCD) and Mild Cognitive Impairment (MCI) patients carrying Alzheimer's Disease (AD) pathology from non-carriers; to propose a flowchart for the interpretation of the results of plasma p-tau181 and NfL. We included 43 SCD, 41 MCI and 21 AD-demented (AD-d) patients, who underwent plasma p-tau181 and NfL analysis. Twenty-eight SCD, 41 MCI and 21 AD-d patients underwent CSF biomarkers analysis (Aβ1-42, Aβ1-42/1-40, p-tau, t-tau) and were classified as carriers of AD pathology (AP+) it they were A+/T+ , or non-carriers (AP-) when they were A-, A+/T-/N-, or A+/T-/N+ according to the A/T(N) system. Plasma p-tau181 and NfL separately showed a good accuracy (AUC = 0.88), while the combined model (NfL + p-tau181) showed an excellent accuracy (AUC = 0.92) in discriminating AP+ from AP- patients. Plasma p-tau181 and NfL results were moderately concordant (Coehn's k = 0.50, p < 0.001). Based on a logistic regression model, we estimated the risk of AD pathology considering the two biomarkers: 10.91% if both p-tau181 and NfL were negative; 41.10 and 76.49% if only one biomarker was positive (respectively p-tau18 and NfL); 94.88% if both p-tau181 and NfL were positive. Considering the moderate concordance and the risk of presenting an underlying AD pathology according to the positivity of plasma p-tau181 and NfL, we proposed a flow chart to guide the combined use of plasma p-tau181 and NfL and the interpretation of biomarker results to detect AD pathology.
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Affiliation(s)
- Giulia Giacomucci
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
| | - Salvatore Mazzeo
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
- Vita-Salute San Raffaele University, Milan, Italy
- IRCCS Policlinico San Donato, San Donato Milanese, Italy
| | - Assunta Ingannato
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
| | - Chiara Crucitti
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
| | - Sonia Padiglioni
- Regional Referral Centre for Relational Criticalities - Tuscany Region, University of Florence, Florence, Italy
- Research and Innovation Centre for Dementia-CRIDEM, AOU Careggi, Florence, Italy
| | | | - Giulia Galdo
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
| | - Filippo Emiliani
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
| | - Daniele Frigerio
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
| | - Camilla Ferrari
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
| | - Valentina Moschini
- SOD Neurologia I, Dipartimento Neuromuscolo-Scheletrico e degli Organi di Senso, AOU Careggi, Florence, Italy
| | - Carmen Morinelli
- SOD Neurologia I, Dipartimento Neuromuscolo-Scheletrico e degli Organi di Senso, AOU Careggi, Florence, Italy
| | - Antonella Notarelli
- Research and Innovation Centre for Dementia-CRIDEM, AOU Careggi, Florence, Italy
- SOD Neurologia I, Dipartimento Neuromuscolo-Scheletrico e degli Organi di Senso, AOU Careggi, Florence, Italy
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy.
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.
| | - Valentina Bessi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Azienda Ospedaliero-Universitaria Careggi, Largo Brambilla, 3, 50134, Florence, Italy
- Research and Innovation Centre for Dementia-CRIDEM, AOU Careggi, Florence, Italy
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15
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Riverol M, Ríos-Rivera MM, Imaz-Aguayo L, Solis-Barquero SM, Arrondo C, Montoya-Murillo G, Villino-Rodríguez R, García-Eulate R, Domínguez P, Fernández-Seara MA. Structural neuroimaging changes associated with subjective cognitive decline from a clinical sample. Neuroimage Clin 2024; 42:103615. [PMID: 38749146 PMCID: PMC11109886 DOI: 10.1016/j.nicl.2024.103615] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2023] [Revised: 05/01/2024] [Accepted: 05/03/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND Alzheimer's disease (AD) is characterized by progressive deterioration of cognitive functions. Some individuals with subjective cognitive decline (SCD) are in the early phase of the disease and subsequently progress through the AD continuum. Although neuroimaging biomarkers could be used for the accurate and early diagnosis of preclinical AD, the findings in SCD samples have been heterogeneous. This study established the morphological differences in brain magnetic resonance imaging (MRI) findings between individuals with SCD and those without cognitive impairment based on a clinical sample of patients defined according to SCD-Initiative recommendations. Moreover, we investigated baseline structural changes in the brains of participants who remained stable or progressed to mild cognitive impairment or dementia. METHODS This study included 309 participants with SCD and 43 healthy controls (HCs) with high-quality brain MRI at baseline. Among the 99 subjects in the SCD group who were followed clinically, 32 progressed (SCDp) and 67 remained stable (SCDnp). A voxel-wise statistical comparison of gray and white matter (WM) volume was performed between the HC and SCD groups and between the HC, SCDp, and SCDnp groups. XTRACT ATLAS was used to define the anatomical location of WM tract damage. Region-of-interest (ROI) analyses were performed to determine brain volumetric differences. White matter lesion (WML) burden was established in each group. RESULTS Voxel-based morphometry (VBM) analysis revealed that the SCD group exhibited gray matter atrophy in the middle frontal gyri, superior orbital gyri, superior frontal gyri, right rectal gyrus, whole occipital lobule, and both thalami and precunei. Meanwhile, ROI analysis revealed decreased volume in the left rectal gyrus, bilateral medial orbital gyri, middle frontal gyri, superior frontal gyri, calcarine fissure, and left thalamus. The SCDp group exhibited greater hippocampal atrophy (p < 0.001) than the SCDnp and HC groups on ROI analyses. On VBM analysis, however, the SCDp group exhibited increased hippocampal atrophy only when compared to the SCDnp group (p < 0.001). The SCD group demonstrated lower WM volume in the uncinate fasciculus, cingulum, inferior fronto-occipital fasciculus, anterior thalamic radiation, and callosum forceps than the HC group. However, no significant differences in WML number (p = 0.345) or volume (p = 0.156) were observed between the SCD and HC groups. CONCLUSIONS The SCD group showed brain atrophy mainly in the frontal and occipital lobes. However, only the SCDp group demonstrated atrophy in the medial temporal lobe at baseline. Structural damage in the brain regions was anatomically connected, which may contribute to early memory decline.
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Affiliation(s)
- Mario Riverol
- Department of Neurology, Clínica Universidad de Navarra, Pamplona 31008, Navarra, Spain; Instituto de Investigación Sanitaria de Navarra, Pamplona 31008, Navarra, Spain.
| | - Mirla M Ríos-Rivera
- Department of Neurology, Clínica Universidad de Navarra, Pamplona 31008, Navarra, Spain; School of Medicine, Universidad Autónoma de Chiriquí, David 4001, Chiriquí, Panama
| | - Laura Imaz-Aguayo
- Department of Neurology, Clínica Universidad de Navarra, Pamplona 31008, Navarra, Spain
| | | | - Carlota Arrondo
- Department of Neurology, Clínica Universidad de Navarra, Pamplona 31008, Navarra, Spain
| | | | | | - Reyes García-Eulate
- Department of Radiology, Clínica Universidad de Navarra, Pamplona 31008, Navarra, Spain
| | - Pablo Domínguez
- Department of Radiology, Clínica Universidad de Navarra, Pamplona 31008, Navarra, Spain; Instituto de Investigación Sanitaria de Navarra, Pamplona 31008, Navarra, Spain
| | - Maria A Fernández-Seara
- Department of Radiology, Clínica Universidad de Navarra, Pamplona 31008, Navarra, Spain; Instituto de Investigación Sanitaria de Navarra, Pamplona 31008, Navarra, Spain
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16
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Sarto J, Esteller-Gauxax D, Tort-Merino A, Guillén N, Pérez-Millan A, Falgàs N, Borrego-Écija S, Fernández-Villullas G, Bosch B, Juncà-Parella J, Antonell A, Naranjo L, Ruiz-García R, Augé JM, Sánchez-Valle R, Lladó A, Balasa M. Impact of demographics and comorbid conditions on plasma biomarkers concentrations and their diagnostic accuracy in a memory clinic cohort. J Neurol 2024; 271:1973-1984. [PMID: 38151575 DOI: 10.1007/s00415-023-12153-8] [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: 10/22/2023] [Revised: 12/05/2023] [Accepted: 12/07/2023] [Indexed: 12/29/2023]
Abstract
Plasma biomarkers have emerged as promising tools for identifying amyloid beta (Aβ) pathology. Before implementation in routine clinical practice, confounding factors modifying their concentration beyond neurodegenerative diseases should be identified. We studied the association of a comprehensive list of demographics, comorbidities, medication and laboratory parameters with plasma p-tau181, glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) on a prospective memory clinic cohort and studied their impact on diagnostic accuracy for discriminating CSF/amyloid PET-defined Aβ status. Three hundred sixty patients (mean age 66.5 years, 55% females, 53% Aβ positive) were included. Sex, age and Aβ status-adjusted models showed that only estimated glomerular filtration rate (eGFR, standardized β -0.115 [-0.192 to -0.035], p = 0.005) was associated with p-tau181 levels, although with a much smaller effect than Aβ status (0.685 [0.607-0.763], p < 0.001). Age, sex, body mass index (BMI), Charlson comorbidity index (CCI) and eGFR significantly modified GFAP concentration. Age, blood volume (BV) and eGFR were associated with NfL levels. p-tau181 predicted Aβ status with 87% sensitivity and specificity with no relevant increase in diagnostic performance by adding any of the confounding factors. Using two cut-offs, plasma p-tau181 could have spared 62% of amyloid-PET/CSF testing. Excluding patients with chronic kidney disease did not change the proposed cut-offs nor the diagnostic performance. In conclusion, in a memory clinic cohort, age, sex, eGFR, BMI, BV and CCI slightly modified plasma p-tau181, GFAP and NfL concentrations but their impact on the diagnostic accuracy of plasma biomarkers for Aβ status discrimination was minimal.
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Affiliation(s)
- Jordi Sarto
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Diana Esteller-Gauxax
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Adrià Tort-Merino
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Núria Guillén
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Agnès Pérez-Millan
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Neus Falgàs
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Sergi Borrego-Écija
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Guadalupe Fernández-Villullas
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Beatriz Bosch
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Jordi Juncà-Parella
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Anna Antonell
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Laura Naranjo
- Immunology Service, Biomedical Diagnostic Center, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Raquel Ruiz-García
- Immunology Service, Biomedical Diagnostic Center, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Josep María Augé
- Biochemistry and Molecular Genetics Department, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Raquel Sánchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
- Department of Medicine, Faculty of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Albert Lladó
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
- Department of Medicine, Faculty of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Mircea Balasa
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain.
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17
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De Meyer S, Blujdea ER, Schaeverbeke J, Reinartz M, Luckett ES, Adamczuk K, Van Laere K, Dupont P, Teunissen CE, Vandenberghe R, Poesen K. Longitudinal associations of serum biomarkers with early cognitive, amyloid and grey matter changes. Brain 2024; 147:936-948. [PMID: 37787146 DOI: 10.1093/brain/awad330] [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: 04/01/2023] [Revised: 09/08/2023] [Accepted: 09/12/2023] [Indexed: 10/04/2023] Open
Abstract
Blood-based biomarkers have been extensively evaluated for their diagnostic potential in Alzheimer's disease. However, their relative prognostic and monitoring capabilities for cognitive decline, amyloid-β (Aβ) accumulation and grey matter loss in cognitively unimpaired elderly require further investigation over extended time periods. This prospective cohort study in cognitively unimpaired elderly [n = 185, mean age (range) = 69 (53-84) years, 48% female] examined the prognostic and monitoring capabilities of glial fibrillary acidic protein (GFAP), neurofilament light (NfL), Aβ1-42/Aβ1-40 and phosphorylated tau (pTau)181 through their quantification in serum. All participants underwent baseline Aβ-PET, MRI and blood sampling as well as 2-yearly cognitive testing. A subset additionally underwent Aβ-PET (n = 109), MRI (n = 106) and blood sampling (n = 110) during follow-up [median time interval (range) = 6.1 (1.3-11.0) years]. Matching plasma measurements were available for Aβ1-42/Aβ1-40 and pTau181 (both n = 140). Linear mixed-effects models showed that high serum GFAP and NfL predicted future cognitive decline in memory (βGFAP×Time = -0.021, PFDR = 0.007 and βNfL×Time = -0.031, PFDR = 0.002) and language (βGFAP×Time = -0.021, PFDR = 0.002 and βNfL×Time = -0.018, PFDR = 0.03) domains. Low serum Aβ1-42/Aβ1-40 equally but independently predicted memory decline (βAβ1-42/Aβ1-40×Time = -0.024, PFDR = 0.02). Whole-brain voxelwise analyses revealed that low Aβ1-42/Aβ1-40 predicted Aβ accumulation within the precuneus and frontal regions, high GFAP and NfL predicted grey matter loss within hippocampal regions and low Aβ1-42/Aβ1-40 predicted grey matter loss in lateral temporal regions. Serum GFAP, NfL and pTau181 increased over time, while Aβ1-42/Aβ1-40 decreased only in Aβ-PET-negative elderly. NfL increases associated with declining memory (βNfLchange×Time = -0.030, PFDR = 0.006) and language (βNfLchange×Time = -0.021, PFDR = 0.02) function and serum Aβ1-42/Aβ1-40 decreases associated with declining language function (βAβ1-42/Aβ1-40×Time = -0.020, PFDR = 0.04). GFAP increases associated with Aβ accumulation within the precuneus and NfL increases associated with grey matter loss. Baseline and longitudinal serum pTau181 only associated with Aβ accumulation in restricted occipital regions. In head-to-head comparisons, serum outperformed plasma Aβ1-42/Aβ1-40 (ΔAUC = 0.10, PDeLong, FDR = 0.04), while both plasma and serum pTau181 demonstrated poor performance to detect asymptomatic Aβ-PET positivity (AUC = 0.55 and 0.63, respectively). However, when measured with a more phospho-specific assay, plasma pTau181 detected Aβ-positivity with high performance (AUC = 0.82, PDeLong, FDR < 0.007). In conclusion, serum GFAP, NfL and Aβ1-42/Aβ1-40 are valuable prognostic and/or monitoring tools in asymptomatic stages providing complementary information in a time- and pathology-dependent manner.
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Affiliation(s)
- Steffi De Meyer
- Laboratory for Molecular Neurobiomarker Research, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
| | - Elena R Blujdea
- Neurochemistry Laboratory, Amsterdam UMC, 1081 HZ Amsterdam, The Netherlands
| | - Jolien Schaeverbeke
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
| | - Mariska Reinartz
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
| | - Emma S Luckett
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
| | - Katarzyna Adamczuk
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
| | - Koen Van Laere
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, 3000 Leuven, Belgium
- Division of Nuclear Medicine, UZ Leuven, 3000 Leuven, Belgium
| | - Patrick Dupont
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
| | | | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
- Department of Neurology, UZ Leuven, 3000 Leuven, Belgium
| | - Koen Poesen
- Laboratory for Molecular Neurobiomarker Research, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
- Department of Laboratory Medicine, UZ Leuven, 3000 Leuven, Belgium
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18
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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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19
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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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Vrillon A, Ashton NJ, Karikari TK, Götze K, Cognat E, Dumurgier J, Lilamand M, Zetterberg H, Blennow K, Paquet C. Comparison of CSF and plasma NfL and pNfH for Alzheimer's disease diagnosis: a memory clinic study. J Neurol 2024; 271:1297-1310. [PMID: 37950758 DOI: 10.1007/s00415-023-12066-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/11/2023] [Accepted: 10/13/2023] [Indexed: 11/13/2023]
Abstract
Plasma neurofilament light chain (NfL) is a promising biomarker of axonal damage for the diagnosis of neurodegenerative diseases. Phosphorylated neurofilament heavy chain (pNfH) has demonstrated its value in motor neuron diseases diagnosis, but has less been explored for dementia diagnosis. In a cross-sectional study, we compared cerebrospinal fluid (CSF) and plasma NfL and pNfH levels in n = 188 patients from Lariboisière Hospital, Paris, France, including AD patients at mild cognitive impairment stage (AD-MCI, n = 36) and dementia stage (n = 64), non-AD MCI (n = 38), non-AD dementia (n = 28) patients and control subjects (n = 22). Plasma NfL, plasma and CSF pNfH levels were measured using Simoa and CSF NfL using ELISA. The correlation between CSF and plasma levels was stronger for NfL than pNfH (rho = 0.77 and rho = 0.52, respectively). All neurofilament markers were increased in AD-MCI, AD dementia and non-AD dementia groups compared with controls. CSF NfL, CSF pNfH and plasma NfL showed high performance to discriminate AD at both MCI and dementia stages from control subjects [AUC (area under the curve) = 0.82-0.91]. Plasma pNfH displayed overall lower AUCs for discrimination between groups compared with CSF pNfH. Neurofilament markers showed similar moderate association with cognition. NfL levels displayed significant association with mediotemporal lobe atrophy and white matter lesions in the AD group. Our results suggest that CSF NfL and pNfH as well as plasma NfL levels display equivalent performance in both positive and differential AD diagnosis in memory clinic settings. In contrast to motoneuron disorders, plasma pNfH did not demonstrate added value as compared with plasma NfL.
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Affiliation(s)
- Agathe Vrillon
- Cognitive Neurology Center, Lariboisière Fernand Widal Hospital, Assistance Publique Hôpitaux de Paris, Université Paris Cité, Paris, France.
- INSERM U1144, Therapeutic Optimization in Neuropsychopharmacology, Paris, France.
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Maurice Wohl Institute Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Karl Götze
- INSERM U1144, Therapeutic Optimization in Neuropsychopharmacology, Paris, France
| | - Emmanuel Cognat
- Cognitive Neurology Center, Lariboisière Fernand Widal Hospital, Assistance Publique Hôpitaux de Paris, Université Paris Cité, Paris, France
- INSERM U1144, Therapeutic Optimization in Neuropsychopharmacology, Paris, France
| | - Julien Dumurgier
- Cognitive Neurology Center, Lariboisière Fernand Widal Hospital, Assistance Publique Hôpitaux de Paris, Université Paris Cité, Paris, France
| | - Matthieu Lilamand
- Cognitive Neurology Center, Lariboisière Fernand Widal Hospital, Assistance Publique Hôpitaux de Paris, Université Paris Cité, Paris, France
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Maurice Wohl Institute Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Claire Paquet
- Cognitive Neurology Center, Lariboisière Fernand Widal Hospital, Assistance Publique Hôpitaux de Paris, Université Paris Cité, Paris, France
- INSERM U1144, Therapeutic Optimization in Neuropsychopharmacology, Paris, France
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Foley KE, Winder Z, Sudduth TL, Martin BJ, Nelson PT, Jicha GA, Harp JP, Weekman EM, Wilcock DM. Alzheimer's disease and inflammatory biomarkers positively correlate in plasma in the UK-ADRC cohort. Alzheimers Dement 2024; 20:1374-1386. [PMID: 38011580 PMCID: PMC10917006 DOI: 10.1002/alz.13485] [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: 03/30/2023] [Revised: 08/17/2023] [Accepted: 08/20/2023] [Indexed: 11/29/2023]
Abstract
INTRODUCTION Protein-based plasma assays provide hope for improving accessibility and specificity of molecular diagnostics to diagnose dementia. METHODS Plasma was obtained from participants (N = 837) in our community-based University of Kentucky Alzheimer's Disease Research Center cohort. We evaluated six Alzheimer's disease (AD)- and neurodegeneration-related (Aβ40, Aβ42, Aβ42/40, p-tau181, total tau, and NfLight) and five inflammatory biomarkers (TNF𝛼, IL6, IL8, IL10, and GFAP) using the SIMOA-based protein assay platform. Statistics were performed to assess correlations. RESULTS Our large cohort reflects previous plasma biomarker findings. Relationships between biomarkers to understand AD-inflammatory biomarker correlations showed significant associations between AD and inflammatory biomarkers suggesting peripheral inflammatory interactions with increasing AD pathology. Biomarker associations parsed out by clinical diagnosis (normal, MCI, and dementia) reveal changes in strength of the correlations across the cognitive continuum. DISCUSSION Unique AD-inflammatory biomarker correlations in a community-based cohort reveal a new avenue for utilizing plasma-based biomarkers in the assessment of AD and related dementias. HIGHLIGHTS Large community cohorts studying sex, age, and APOE genotype effects on biomarkers are few. It is unknown how biomarker-biomarker associations vary through aging and dementia. Six AD (Aβ40, Aβ42, Aβ42/40, p-tau181, total tau, and NfLight) and five inflammatory biomarkers (TNFα, IL6, IL8, IL10, and GFAP) were used to examine associations between biomarkers. Plasma biomarkers suggesting increasing cerebral AD pathology corresponded to increases in peripheral inflammatory markers, both pro-inflammatory and anti-inflammatory. Strength of correlations, between pairs of classic AD and inflammatory plasma biomarker, changes throughout cognitive progression to dementia.
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Affiliation(s)
- Kate E. Foley
- Sanders Brown Center on AgingUniversity of KentuckyLexingtonKentuckyUSA
- Department of PhysiologyUniversity of KentuckyLexingtonKentuckyUSA
| | - Zachary Winder
- Department of PhysiologyUniversity of KentuckyLexingtonKentuckyUSA
- College of MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Tiffany L. Sudduth
- Sanders Brown Center on AgingUniversity of KentuckyLexingtonKentuckyUSA
- Department of PhysiologyUniversity of KentuckyLexingtonKentuckyUSA
| | - Barbara J. Martin
- Sanders Brown Center on AgingUniversity of KentuckyLexingtonKentuckyUSA
| | - Peter T. Nelson
- Sanders Brown Center on AgingUniversity of KentuckyLexingtonKentuckyUSA
- Pathology and Laboratory MedicineUniversity of KentuckyLexingtonKentuckyUSA
| | - Gregory A. Jicha
- Sanders Brown Center on AgingUniversity of KentuckyLexingtonKentuckyUSA
- Neurology, College of Public HealthUniversity of KentuckyLexingtonKentuckyUSA
| | - Jordan P. Harp
- Sanders Brown Center on AgingUniversity of KentuckyLexingtonKentuckyUSA
- Neurology, College of Public HealthUniversity of KentuckyLexingtonKentuckyUSA
| | - Erica M. Weekman
- Sanders Brown Center on AgingUniversity of KentuckyLexingtonKentuckyUSA
- Department of PhysiologyUniversity of KentuckyLexingtonKentuckyUSA
| | - Donna M. Wilcock
- Sanders Brown Center on AgingUniversity of KentuckyLexingtonKentuckyUSA
- Department of PhysiologyUniversity of KentuckyLexingtonKentuckyUSA
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Doering E, Antonopoulos G, Hoenig M, van Eimeren T, Daamen M, Boecker H, Jessen F, Düzel E, Eickhoff S, Patil K, Drzezga A. MRI or 18F-FDG PET for Brain Age Gap Estimation: Links to Cognition, Pathology, and Alzheimer Disease Progression. J Nucl Med 2024; 65:147-155. [PMID: 38050112 PMCID: PMC10755522 DOI: 10.2967/jnumed.123.265931] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Revised: 09/27/2023] [Indexed: 12/06/2023] Open
Abstract
Deviations of brain age from chronologic age, known as the brain age gap (BAG), have been linked to neurodegenerative diseases such as Alzheimer disease (AD). Here, we compare the associations of MRI-derived (atrophy) or 18F-FDG PET-derived (brain metabolism) BAG with cognitive performance, neuropathologic burden, and disease progression in cognitively normal individuals (CNs) and individuals with subjective cognitive decline (SCD) or mild cognitive impairment (MCI). Methods: Machine learning pipelines were trained to estimate brain age from 185 matched T1-weighted MRI or 18F-FDG PET scans of CN from the Alzheimer's Disease Neuroimaging Initiative and validated in external test sets from the Open Access of Imaging and German Center for Neurodegenerative Diseases-Longitudinal Cognitive Impairment and Dementia studies. BAG was correlated with measures of cognitive performance and AD neuropathology in CNs, SCD subjects, and MCI subjects. Finally, BAG was compared between cognitively stable and declining individuals and subsequently used to predict disease progression. Results: MRI (mean absolute error, 2.49 y) and 18F-FDG PET (mean absolute error, 2.60 y) both estimated chronologic age well. At the SCD stage, MRI-based BAG correlated significantly with beta-amyloid1-42 (Aβ1-42) in cerebrospinal fluid, whereas 18F-FDG PET BAG correlated with memory performance. At the MCI stage, both BAGs were associated with memory and executive function performance and cerebrospinal fluid Aβ1-42, but only MRI-derived BAG correlated with phosphorylated-tau181/Aβ1-42 Lastly, MRI-estimated BAG predicted MCI-to-AD progression better than 18F-FDG PET-estimated BAG (areas under the curve, 0.73 and 0.60, respectively). Conclusion: Age was reliably estimated from MRI or 18F-FDG PET. MRI BAG reflected cognitive and pathologic markers of AD in SCD and MCI, whereas 18F-FDG PET BAG was sensitive mainly to early cognitive impairment, possibly constituting an independent biomarker of brain age-related changes.
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Affiliation(s)
- Elena Doering
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany;
- German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Georgios Antonopoulos
- Brain and Behavior, Research Center Juelich, Juelich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University, Duesseldorf, Germany
| | - Merle Hoenig
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- Molecular Organization of the Brain, Research Center Juelich, Juelich, Germany
| | - Thilo van Eimeren
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Marcel Daamen
- German Center for Neurodegenerative Diseases, Bonn, Germany
| | | | - Frank Jessen
- German Center for Neurodegenerative Diseases, Bonn, Germany
- Department of Psychiatry, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany; and
| | - Emrah Düzel
- German Center for Neurodegenerative Diseases, Magdeburg, Germany
| | - Simon Eickhoff
- Brain and Behavior, Research Center Juelich, Juelich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University, Duesseldorf, Germany
| | - Kaustubh Patil
- Brain and Behavior, Research Center Juelich, Juelich, Germany
- Institute of Systems Neuroscience, Heinrich Heine University, Duesseldorf, Germany
| | - Alexander Drzezga
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany
- German Center for Neurodegenerative Diseases, Bonn, Germany
- Molecular Organization of the Brain, Research Center Juelich, Juelich, Germany
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Manjavong M, Kang JM, Diaz A, Ashford MT, Eichenbaum J, Aaronson A, Miller MJ, Mackin S, Tank R, Weiner M, Nosheny R. Performance of Plasma Biomarkers Combined with Structural MRI to Identify Candidate Participants for Alzheimer's Disease-Modifying Therapy. J Prev Alzheimers Dis 2024; 11:1198-1205. [PMID: 39350364 PMCID: PMC11436390 DOI: 10.14283/jpad.2024.110] [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: 04/19/2024] [Accepted: 06/01/2024] [Indexed: 10/04/2024]
Abstract
BACKGROUND Recently, two monoclonal antibodies that lower amyloid plaques have shown promising results for the treatment of Mild Cognitive Impairment (MCI) and mild dementia due to Alzheimer's disease (AD). These treatments require the identification of cognitively impaired older adults with biomarker evidence of AD pathology using CSF biomarkers or amyloid-PET. Previous studies showed plasma biomarkers (plasma Aβ42/Aβ40 and p-tau181) and hippocampal volume from structural MRI correlated with brain amyloid pathology. We hypothesized plasma biomarkers with hippocampal volume would identify patients who are suitable candidates for disease-modifying therapy. OBJECTIVES To evaluate the performance of plasma AD biomarkers and hippocampal atrophy to detect MCI or AD with amyloid pathology confirmed by amyloid-PET or CSF biomarkers in ADNI. DESIGN A cross-sectional and longitudinal study. SETTING AND PARTICIPANTS Data were from the Alzheimer's Disease Neuroimaging Initiative. Participants were aged 55-90 years old with plasma biomarker and structural MRI brain data. MEASUREMENTS The optimum cut-off point for plasma Aβ42/Aβ40, p-tau181, and NFL and the performance of combined biomarkers and hippocampal atrophy for detecting cognitive impairment with brain amyloid pathology were evaluated. The association between baseline plasma biomarkers and clinical progression, defined by CDR-Sum of Boxes (CDR-SB) and diagnostic conversion over two years, was evaluated using a Weibull time-to-event analysis. RESULTS A total of 428 participants were included; 167 had normal cognition, 245 had MCI, and 16 had mild AD. Among MCI and AD, 140 participants had elevated amyloid levels by PET or CSF. Plasma Aβ42/Aβ40 provided the best accuracy (sensitivity 79%, specificity 66%, AUC 0.73, 95% CI 0.68-0.77) to detect drug candidate participants at baseline. Combined plasma Aβ42/40, p-tau181, and hippocampal atrophy increased the specificity for diagnosis (96%), but had lower sensitivity (34%), and AUC (0.65). Hippocampal atrophy combined with the abnormal plasma p-tau181 or hippocampal atrophy alone showed high sensitivity to detect clinical progression (by CDR-SB worsening) of the drug-candidate participants within the next 2 years (sensitivity 93% and 89%, respectively). CONCLUSION Plasma biomarkers and structural MRI can help identify patients who are currently eligible for anti-amyloid treatment and are likely to progress clinically, in cases where amyloid-PET or CSF biomarkers are not available.
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Affiliation(s)
- M Manjavong
- Rachel L. Nosheny, Ph.D., Assistant Professor, University of California, San Francisco, Department of Psychiatry, San Francisco VA Medical Center, 4150 Clement Street (114M), San Francisco, CA 94121, Tel: 650-468-0619, Fax: 415-668-2864,
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24
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Allen AT, Cole WR, Walton SR, Kerr ZY, Chandran A, Mannix R, Guskiewicz KM, Meehan WP, Echemendia RJ, McCrea MA, Brett BL. Subjective and Performance-Based Cognition and Their Associations with Head Injury History in Older Former National Football League Players. Med Sci Sports Exerc 2023; 55:2170-2179. [PMID: 37443456 PMCID: PMC10787800 DOI: 10.1249/mss.0000000000003256] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/15/2023]
Abstract
PURPOSE Investigate the association between self-reported subjective and performance-based cognition among older (50-70 years) former professional American football players, as well as the relationship of cognitive measures with concussion history and years of football participation, as a proxy for repetitive head impact exposure. METHODS Among older former National Football League (NFL) players ( N = 172; mean age = 60.69 ± 5.64), associations of subjective (Patient Reported Outcome Measurement Information System Cognitive Function-Short Form) and performance-based cognitive measures (Brief Test of Adult Cognition by Telephone [BTACT] Executive Function and Episodic Memory indices) were assessed via univariable and multivariable regression models, with a priori covariates of depression and race. A similar univariate and multivariable regression approach assessed associations between concussion history and years of football participation with subjective and performance-based cognitive measures. In a sample subset ( n = 114), stability of subjective cognitive rating was assessed via partial correlation. RESULTS Subjective ratings of cognition were significantly associated with performance-based assessment, with moderate effect sizes (episodic memory ηp2 = 0.12; executive function ηp2 = 0.178). These associations were weakened, but remained significant ( P s < 0.05), with the inclusion of covariates. Greater concussion history was associated with lower subjective cognitive function ( ηp2 = 0.114, P < 0.001), but not performance-based cognition. The strength of association between concussion history and subjective cognition was substantially weakened with inclusion of covariates ( ηp2 = 0.057). Years of participation were not associated with measures of subjective or objective cognition ( P s > 0.05). CONCLUSIONS These findings reinforce the importance of comprehensive evaluation reflecting both subjective and objective measures of cognition, as well as the consideration of patient-specific factors, as part of a comprehensive neurobehavioral and health assessment of older former contact sport athletes.
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Affiliation(s)
- Andrew T. Allen
- Department of Neurosurgery, Medical College of Wisconsin, Wauwatosa, WI
| | - Wesley R. Cole
- Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Samuel R. Walton
- Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University School of Medicine, Richmond, VA
| | - Zachary Yukio Kerr
- Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Avinash Chandran
- Department of Physical Medicine and Rehabilitation, Virginia Commonwealth University School of Medicine, Richmond, VA
- Datalys Center for Sports Injury Research and Prevention, Indianapolis, IN
| | - Rebekah Mannix
- Division of Emergency Medicine, Boston Children’s Hospital, Boston, MA
- Department of Pediatrics and Emergency Medicine, Harvard Medical School, Boston, MA
| | - Kevin M. Guskiewicz
- Department of Exercise and Sport Science, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - William P. Meehan
- Sports Medicine Division, Boston Children’s Hospital, Boston, MA
- Department of Pediatrics and Orthopedics, Harvard Medical School, Boston, MA
| | - Ruben J. Echemendia
- Psychological and Neurobehavioral Associates, Inc, State College, PA
- University Orthopedics Center Concussion Clinic, State College, PA
| | - Michael A. McCrea
- Department of Neurosurgery, Medical College of Wisconsin, Wauwatosa, WI
- Department of Neurology, Medical College of Wisconsin, Wauwatosa, WI
| | - Benjamin L. Brett
- Department of Neurosurgery, Medical College of Wisconsin, Wauwatosa, WI
- Department of Neurology, Medical College of Wisconsin, Wauwatosa, WI
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Perna L, Stocker H, Burow L, Beyer L, Trares K, Kurz C, Gürsel S, Holleczek B, Tatò M, Beyreuther K, Mons U, Gerwert K, Perneczky R, Schöttker B, Brenner H. Subjective cognitive complaints and blood biomarkers of neurodegenerative diseases: a longitudinal cohort study. Alzheimers Res Ther 2023; 15:198. [PMID: 37951931 PMCID: PMC10638700 DOI: 10.1186/s13195-023-01341-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Accepted: 10/25/2023] [Indexed: 11/14/2023]
Abstract
BACKGROUND Subjective cognitive complaints (SCC) have been mostly studied in the context of Alzheimer's disease in memory clinic settings. The potential of combining SCC with genetic information and blood biomarkers of neurodegenerative diseases for risk assessment of dementia and depression in the absence of dementia among community-dwelling older adults has so far not been explored. METHODS Data were based on a population-based cohort of 6357 participants with a 17-year follow-up (ESTHER study) and a clinic-based cohort of 422 patients. Participants of both cohorts were grouped according to the diagnosis of dementia (yes/no) and the diagnosis of depression in the absence of dementia (yes/no). Participants without dementia included both cognitively unimpaired participants and cognitively impaired participants. Genetic information (APOE ε4 genotype) and blood-based biomarkers of neurodegenerative diseases (glial fibrillary acidic protein; GFAP, neurofilament light chain; NfL, phosphorylated tau181; p-tau181) were available in the ESTHER study and were determined with Simoa Technology in a nested case-control design. Logistic regression models adjusted for relevant confounders were run for the outcomes of all-cause dementia and depression in the absence of dementia. RESULTS The results showed that persistent SCC were associated both with increased risk of all-cause dementia and of depression without dementia, independently of the diagnostic setting. However, the results for the ESTHER study also showed that the combination of subjective complaints with APOE ε4 and with increased GFAP concentrations in the blood yielded a substantially increased risk of all-cause dementia (OR 5.35; 95%CI 3.25-8.81, p-value < 0.0001 and OR 7.52; 95%CI 2.79-20.29, p-value < 0.0001, respectively) but not of depression. Associations of NfL and p-tau181 with risk of all-cause dementia and depression were not statistically significant, either alone or in combination with SCC, but increased concentrations of p-tau181 seemed to be associated with an increased risk for depression. CONCLUSION In community and clinical settings, SCC predict both dementia and depression in the absence of dementia. The addition of GFAP could differentiate between the risk of all-cause dementia and the risk of depression among individuals without dementia.
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Affiliation(s)
- Laura Perna
- Department Genes and Environment, Max Planck Institute of Psychiatry, 80804, Munich, Germany.
- Division of Mental Health of Older Adults, Department of Psychiatry and Psychotherapy, University Hospital, LMU, Munich, Germany.
| | - Hannah Stocker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research (NAR), Heidelberg University, Heidelberg, Germany
| | - Lena Burow
- Division of Mental Health of Older Adults, Department of Psychiatry and Psychotherapy, University Hospital, LMU, Munich, Germany
| | - Léon Beyer
- Faculty of Biology and Biotechnology, Department of Biophysics, Ruhr-University Bochum, 44801, Bochum, Germany
- Center for Protein Diagnostics (ProDi), Ruhr-University Bochum, 44801, Bochum, Germany
| | - Kira Trares
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Carolin Kurz
- Division of Mental Health of Older Adults, Department of Psychiatry and Psychotherapy, University Hospital, LMU, Munich, Germany
| | - Selim Gürsel
- Division of Mental Health of Older Adults, Department of Psychiatry and Psychotherapy, University Hospital, LMU, Munich, Germany
| | - Bernd Holleczek
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Saarland Cancer Registry, 66117, Saarbrücken, Germany
| | - Maia Tatò
- Division of Mental Health of Older Adults, Department of Psychiatry and Psychotherapy, University Hospital, LMU, Munich, Germany
| | - Konrad Beyreuther
- Network Aging Research (NAR), Heidelberg University, Heidelberg, Germany
| | - Ute Mons
- Department of Cardiology, Faculty of Medicine, University Hospital Cologne, University of Cologne, Cologne, Germany
| | - Klaus Gerwert
- Faculty of Biology and Biotechnology, Department of Biophysics, Ruhr-University Bochum, 44801, Bochum, Germany
- Center for Protein Diagnostics (ProDi), Ruhr-University Bochum, 44801, Bochum, Germany
| | - Robert Perneczky
- Division of Mental Health of Older Adults, Department of Psychiatry and Psychotherapy, University Hospital, LMU, Munich, Germany
- Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, UK
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
- Sheffield Institute for Translational Neurology (SITraN), University of Sheffield, Sheffield, UK
| | - Ben Schöttker
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research (NAR), Heidelberg University, Heidelberg, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Network Aging Research (NAR), Heidelberg University, Heidelberg, Germany
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26
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Yang Z, Sreenivasan K, Toledano Strom EN, Osse AML, Pasia LG, Cosme CG, Mugosa MRN, Chevalier EL, Ritter A, Miller JB, Cordes D, Cummings JL, Kinney JW. Clinical and biological relevance of glial fibrillary acidic protein in Alzheimer's disease. Alzheimers Res Ther 2023; 15:190. [PMID: 37924152 PMCID: PMC10623866 DOI: 10.1186/s13195-023-01340-4] [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: 05/06/2023] [Accepted: 10/24/2023] [Indexed: 11/06/2023]
Abstract
INTRODUCTION There is a tremendous need for identifying reliable blood-based biomarkers for Alzheimer's disease (AD) that are tied to the biological ATN (amyloid, tau and neurodegeneration) framework as well as clinical assessment and progression. METHODS One hundred forty-four elderly participants underwent 18F-AV45 positron emission tomography (PET) scan, structural magnetic resonance imaging (MRI) scan, and blood sample collection. The composite standardized uptake value ratio (SUVR) was derived from 18F-AV45 PET to assess brain amyloid burden, and the hippocampal volume was determined from structural MRI scans. Plasma glial fibrillary acidic protein (GFAP), phosphorylated tau-181 (ptau-181), and neurofilament light (NfL) measured by single molecular array (SIMOA) technology were assessed with respect to ATN framework, genetic risk factor, age, clinical assessment, and future functional decline among the participants. RESULTS Among the three plasma markers, GFAP best discriminated participants stratified by clinical diagnosis and brain amyloid status. Age was strongly associated with NfL, followed by GFAP and ptau-181 at much weaker extent. Brain amyloid was strongly associated with plasma GFAP and ptau-181 and to a lesser extent with plasma NfL. Moderate association was observed between plasma markers. Hippocampal volume was weakly associated with all three markers. Elevated GFAP and ptau-181 were associated with worse cognition, and plasma GFAP was the most predictive of future functional decline. Combining GFAP and ptau-181 together was the best model to predict brain amyloid status across all participants (AUC = 0.86) or within cognitively impaired participants (AUC = 0.93); adding NfL as an additional predictor only had a marginal improvement. CONCLUSION Our findings indicate that GFAP is of potential clinical utility in screening amyloid pathology and predicting future cognitive decline. GFAP, NfL, and ptau-181 were moderately associated with each other, with discrepant relevance to age, sex, and AD genetic risk, suggesting their relevant but differential roles for AD assessment. The combination of GFAP with ptau-181 provides an accurate model to predict brain amyloid status, with the superior performance of GFAP over ptau-181 when the prediction is limited to cognitively impaired participants.
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Affiliation(s)
- Zhengshi Yang
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA.
- Department of Brain Health, University of Nevada Las Vegas, Las Vegas, NV, USA.
| | - Karthik Sreenivasan
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA
- Department of Brain Health, University of Nevada Las Vegas, Las Vegas, NV, USA
| | | | | | | | - Celica Glenn Cosme
- Kirk Kerkorian School of Medicine, University of Nevada Las Vegas, Las Vegas, NV, USA
| | - Maya Rae N Mugosa
- Department of Brain Health, University of Nevada Las Vegas, Las Vegas, NV, USA
| | - Emma Léa Chevalier
- Department of Brain Health, University of Nevada Las Vegas, Las Vegas, NV, USA
| | - Aaron Ritter
- Hoag's Pickup Family Neurosciences Institute, Newport Beach, CA, USA
| | - Justin B Miller
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA
| | - Dietmar Cordes
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA
- Department of Brain Health, University of Nevada Las Vegas, Las Vegas, NV, USA
- Department of Psychology and Neuroscience, University of Colorado, Boulder, CO, 80309, USA
| | - Jeffrey L Cummings
- Department of Brain Health, University of Nevada Las Vegas, Las Vegas, NV, USA
- Chambers-Grundy Center for Transformative Neuroscience, Pam Quirk Brain Health and Biomarker Laboratory, Department of Brain Health, University of Nevada Las Vegas, Las Vegas, NV, USA
| | - Jefferson W Kinney
- Department of Brain Health, University of Nevada Las Vegas, Las Vegas, NV, USA
- Chambers-Grundy Center for Transformative Neuroscience, Pam Quirk Brain Health and Biomarker Laboratory, Department of Brain Health, University of Nevada Las Vegas, Las Vegas, NV, USA
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Harrington EE, Graham-Engeland JE, Sliwinski MJ, Van Bogart K, Mogle JA, Katz MJ, Lipton RB, Engeland CG. Older adults' self-reported prospective memory lapses in everyday life: Connections to inflammation and gender. J Psychosom Res 2023; 174:111489. [PMID: 37690333 PMCID: PMC10591850 DOI: 10.1016/j.jpsychores.2023.111489] [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: 05/04/2023] [Revised: 09/04/2023] [Accepted: 09/04/2023] [Indexed: 09/12/2023]
Abstract
OBJECTIVE Limited research has focused on the association between inflammatory markers and features of subjective cognitive functioning among older adults. The present work examined links between inflammation and a specific subjective cognitive report: prospective memory (PM), or our memory for future intentions, such as attending an appointment or taking medication. METHOD We assessed self-reported PM lapses using a two-week ecological momentary assessment (EMA) diary protocol via smartphone as well as levels of blood-based inflammation among 231 dementia-free older adults (70-90 years, 66% women) enrolled in the Einstein Aging Study. RESULTS Overall, PM lapses were largely unrelated to inflammatory markers. However, a significant gender difference was observed in the link between basal levels of interleukin (IL)-8 and PM lapses: higher levels of basal IL-8 were associated with more PM lapses among men (estimate = 0.98, 95%CI: [0.43, 1.53], p < .001) but not women (estimate = -0.03, 95%CI: [-0.45, 0.39], p = .826). No other significant relationships between PM lapses and basal or stimulated (ex vivo) cytokine levels (IL-1β, IL-4, IL-6, IL-8, IL-10, tumor necrosis factor-alpha [TNF-α]) or C-reactive protein (CRP) emerged. CONCLUSION Elevated levels of IL-8 in older men may possibly be an early indicator of neurodegeneration that relates to PM performance. Future studies should continue to examine PM and inflammation across genders to identify possible mechanisms through which these constructs may indicate neurodegeneration and dementia risk.
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Affiliation(s)
- Erin E Harrington
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA 16802, USA; Center for Healthy Aging, The Pennsylvania State University, University Park, PA 16802, USA; Department of Psychology, University of Wyoming, Laramie, WY 82070, USA.
| | - Jennifer E Graham-Engeland
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA 16802, USA; Center for Healthy Aging, The Pennsylvania State University, University Park, PA 16802, USA
| | - Martin J Sliwinski
- Center for Healthy Aging, The Pennsylvania State University, University Park, PA 16802, USA; Department of Human Development and Family Studies, The Pennsylvania State University, University Park, PA 16802, USA
| | - Karina Van Bogart
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA 16802, USA
| | | | - Mindy J Katz
- Department of Neurology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Richard B Lipton
- Department of Psychiatry and Behavioral Sciences, Albert Einstein College of Medicine, Bronx, NY 10461, USA; Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Christopher G Engeland
- Department of Biobehavioral Health, The Pennsylvania State University, University Park, PA 16802, USA; Center for Healthy Aging, The Pennsylvania State University, University Park, PA 16802, USA; Ross and Carol Nese College of Nursing, The Pennsylvania State University, University Park, PA, USA
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Cai Y, Fan X, Zhao L, Liu W, Luo Y, Lau AYL, Au LWC, Shi L, Lam BYK, Ko H, Mok VCT. Comparing machine learning-derived MRI-based and blood-based neurodegeneration biomarkers in predicting syndromal conversion in early AD. Alzheimers Dement 2023; 19:4987-4998. [PMID: 37087687 DOI: 10.1002/alz.13083] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Revised: 03/13/2023] [Accepted: 03/20/2023] [Indexed: 04/24/2023]
Abstract
INTRODUCTION We compared the machine learning-derived, MRI-based Alzheimer's disease (AD) resemblance atrophy index (AD-RAI) with plasma neurofilament light chain (NfL) level in predicting conversion of early AD among cognitively unimpaired (CU) and mild cognitive impairment (MCI) subjects. METHODS We recruited participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) who had the following data: clinical features (age, gender, education, Montreal Cognitive Assessment [MoCA]), structural MRI, plasma biomarkers (p-tau181 , NfL), cerebrospinal fluid biomarkers (CSF) (Aβ42, p-tau181 ), and apolipoprotein E (APOE) ε4 genotype. We defined AD using CSF Aβ42 (A+) and p-tau181 (T+). We defined conversion (C+) if a subject progressed to the next syndromal stage within 4 years. RESULTS Of 589 participants, 96 (16.3%) were A+T+C+. AD-RAI performed better than plasma NfL when added on top of clinical features, plasma p-tau181 , and APOE ε4 genotype (area under the curve [AUC] = 0.832 vs. AUC = 0.650 among CU, AUC = 0.853 vs. AUC = 0.805 among MCI) in predicting A+T+C+. DISCUSSION AD-RAI outperformed plasma NfL in predicting syndromal conversion of early AD. HIGHLIGHTS AD-RAI outperformed plasma NfL in predicting syndromal conversion among early AD. AD-RAI showed better metrics than volumetric hippocampal measures in predicting syndromal conversion. Combining clinical features, plasma p-tau181 and apolipoprotein E (APOE) with AD-RAI is the best model for predicting syndromal conversion.
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Affiliation(s)
- Yuan Cai
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Xiang Fan
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Lei Zhao
- BrainNow Research Institute, Hong Kong Science and Technology Park, Hong Kong SAR, China
| | - Wanting Liu
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Yishan Luo
- BrainNow Research Institute, Hong Kong Science and Technology Park, Hong Kong SAR, China
| | - Alexander Yuk Lun Lau
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Lisa Wing Chi Au
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Lin Shi
- BrainNow Research Institute, Hong Kong Science and Technology Park, Hong Kong SAR, China
- Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Bonnie Y K Lam
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, UK
| | - Ho Ko
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
| | - Vincent Chung Tong Mok
- Lau Tat-chuen Research Centre of Brain Degenerative Diseases in Chinese, Therese Pei Fong Chow Research Centre for Prevention of Dementia, Lui Che Woo Institute of Innovative Medicine, Gerald Choa Neuroscience Institute, Li Ka Shing Institute of Health Science, Division of Neurology, Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Prince of Wales Hospital, Hong Kong SAR, China
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Caprihan A, Hillmer L, Erhardt EB, Adair JC, Knoefel JE, Prestopnik J, Rosenberg GA. A trichotomy method for defining homogeneous subgroups in a dementia population. Ann Clin Transl Neurol 2023; 10:1802-1815. [PMID: 37602520 PMCID: PMC10578887 DOI: 10.1002/acn3.51869] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 07/11/2023] [Accepted: 07/22/2023] [Indexed: 08/22/2023] Open
Abstract
INTRODUCTION Diagnosis of dementia in the aging brain is confounded by the presence of multiple pathologies. Mixed dementia (MX), a combination of Alzheimer's disease (AD) proteins with vascular disease (VD), is frequently found at autopsy, and has been difficult to diagnose during life. This report develops a method for separating the MX group and defining preclinical AD (presence of AD factors with normal cognition) and preclinical VD subgroups (presence of white matter damage with normal cognition). METHODS Clustering was based on three diagnostic axes: (1) AD factor (ADF) derived from cerebrospinal fluid proteins (Aβ42 and pTau), (2) VD factor (VDF) calculated from mean free water and peak width of skeletonized mean diffusivity in the white matter, and (3) Cognition (Cog) based on memory and executive function. The trichotomy method was applied to an Alzheimer's Disease Neuroimaging Initiative cohort (N = 538). RESULTS Eight biologically defined subgroups were identified which included the MX group with both high ADF and VDF (9.3%) and a preclinical VD group (3.9%), and a preclinical AD group (13.6%). Cog is significantly associated with both ADF and VDF, and the partial-correlation remains significant even when the effect of the other variable is removed (r(Cog, ADF/VDF removed) = 0.46, p < 10-28 and r(Cog, VDF/ADF removed) = 0.24, p < 10-7 ). DISCUSSION The trichotomy method creates eight biologically characterized patient groups, which includes MX, preclinical AD, and preclinical VD subgroups. Further longitudinal studies are needed to determine the utility of the 3-way clustering method with multimodal biological biomarkers.
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Affiliation(s)
| | - Laura Hillmer
- Center for Memory and AgingUniversity of New Mexico School of MedicineAlbuquerqueNew Mexico87106USA
| | - Erik Barry Erhardt
- Departments of Mathematics and StatisticsUniversity of New Mexico College of Arts and SciencesAlbuquerqueNew Mexico87106USA
| | - John C. Adair
- Center for Memory and AgingUniversity of New Mexico School of MedicineAlbuquerqueNew Mexico87106USA
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew Mexico87106USA
| | - Janice E. Knoefel
- Center for Memory and AgingUniversity of New Mexico School of MedicineAlbuquerqueNew Mexico87106USA
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew Mexico87106USA
| | - Jillian Prestopnik
- Center for Memory and AgingUniversity of New Mexico School of MedicineAlbuquerqueNew Mexico87106USA
| | - Gary A. Rosenberg
- Center for Memory and AgingUniversity of New Mexico School of MedicineAlbuquerqueNew Mexico87106USA
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew Mexico87106USA
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Ally M, Sugarman MA, Zetterberg H, Blennow K, Ashton NJ, Karikari TK, Aparicio HJ, Frank B, Tripodis Y, Martin B, Palmisano JN, Steinberg EG, Simkin I, Farrer LA, Jun GR, Turk KW, Budson AE, O'Connor MK, Au R, Goldstein LE, Kowall NW, Killiany R, Stern RA, Stein TD, McKee AC, Qiu WQ, Mez J, Alosco ML. Cross-sectional and longitudinal evaluation of plasma glial fibrillary acidic protein to detect and predict clinical syndromes of Alzheimer's disease. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12492. [PMID: 37885919 PMCID: PMC10599277 DOI: 10.1002/dad2.12492] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 09/15/2023] [Accepted: 09/26/2023] [Indexed: 10/28/2023]
Abstract
Introduction This study examined plasma glial fibrillary acidic protein (GFAP) as a biomarker of cognitive impairment due to Alzheimer's disease (AD) with and against plasma neurofilament light chain (NfL), and phosphorylated tau (p-tau)181+231. Methods Plasma samples were analyzed using Simoa platform for 567 participants spanning the AD continuum. Cognitive diagnosis, neuropsychological testing, and dementia severity were examined for cross-sectional and longitudinal outcomes. Results Plasma GFAP discriminated AD dementia from normal cognition (adjusted mean difference = 0.90 standard deviation [SD]) and mild cognitive impairment (adjusted mean difference = 0.72 SD), and demonstrated superior discrimination compared to alternative plasma biomarkers. Higher GFAP was associated with worse dementia severity and worse performance on 11 of 12 neuropsychological tests. Longitudinally, GFAP predicted decline in memory, but did not predict conversion to mild cognitive impairment or dementia. Discussion Plasma GFAP was associated with clinical outcomes related to suspected AD and could be of assistance in a plasma biomarker panel to detect in vivo AD.
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Affiliation(s)
- Madeline Ally
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of PsychologyUniversity of ArizonaTucsonArizonaUSA
| | - Michael A. Sugarman
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyMedical University of South CarolinaCharlestonSouth CarolinaUSA
| | - Henrik Zetterberg
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyLondonUK
- UK Dementia Research Institute at UCL, UCL Institute of NeurologyUniversity College LondonLondonUK
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgGothenburgSweden
| | - Kaj Blennow
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgGothenburgSweden
| | - Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgGothenburgSweden
- Maurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology, and NeuroscienceKing's College LondonLondonUK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and MaudsleyNHS FoundationLondonUK
- Centre for Age‐Related MedicineStavanger University HospitalStavangerNorway
| | - Thomas K. Karikari
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgGothenburgSweden
- Department of PsychiatryUniversity of Pittsburgh School of MedicinePittsburghPennsylvaniaUSA
| | - Hugo J. Aparicio
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Brandon Frank
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Boston Healthcare SystemJamaica PlainMassachusettsUSA
| | - Yorghos Tripodis
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
| | - Brett Martin
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Biostatistics and Epidemiology Data Analytics CenterBoston University School of Public HealthBostonMassachusettsUSA
| | - Joseph N. Palmisano
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Biostatistics and Epidemiology Data Analytics CenterBoston University School of Public HealthBostonMassachusettsUSA
| | - Eric G. Steinberg
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Irene Simkin
- Department of MedicineBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Lindsay A. Farrer
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusettsUSA
- Department of MedicineBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Department of EpidemiologyBoston University School of Public HealthBostonMassachusettsUSA
- Department of OphthalmologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Gyungah R. Jun
- Department of MedicineBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Katherine W. Turk
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Boston Healthcare SystemJamaica PlainMassachusettsUSA
| | - Andrew E. Budson
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Boston Healthcare SystemJamaica PlainMassachusettsUSA
| | - Maureen K. O'Connor
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeuropsychologyEdith Nourse Rogers Memorial Veterans HospitalBedfordMassachusettsUSA
| | - Rhoda Au
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Department of EpidemiologyBoston University School of Public HealthBostonMassachusettsUSA
- Department of Anatomy and NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Lee E. Goldstein
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Biostatistics and Epidemiology Data Analytics CenterBoston University School of Public HealthBostonMassachusettsUSA
- Department of OphthalmologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of Biomedical, Electrical, and Computer EngineeringBoston University College of EngineeringBostonMassachusettsUSA
| | - Neil W. Kowall
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Boston Healthcare SystemJamaica PlainMassachusettsUSA
- Department of Pathology and Laboratory MedicineBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Ronald Killiany
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of Anatomy and NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Center for Biomedical ImagingBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Robert A. Stern
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of Anatomy and NeurobiologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurosurgeryBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Thor D. Stein
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Boston Healthcare SystemJamaica PlainMassachusettsUSA
- Department of Pathology and Laboratory MedicineBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Bedford Healthcare SystemBedfordMassachusettsUSA
| | - Ann C. McKee
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Boston Healthcare SystemJamaica PlainMassachusettsUSA
- Department of Pathology and Laboratory MedicineBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- US Department of Veterans AffairsVA Bedford Healthcare SystemBedfordMassachusettsUSA
| | - Wei Qiao Qiu
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of PsychiatryBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of Pharmacology and Experimental TherapeuticsBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Jesse Mez
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
| | - Michael L. Alosco
- Boston University Alzheimer's Disease Research Center and CTE CenterBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
- Department of NeurologyBoston University Chobanian & Avedisian School of MedicineBostonMassachusettsUSA
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Luebke M, Parulekar M, Thomas FP. Fluid biomarkers for the diagnosis of neurodegenerative diseases. Biomark Neuropsychiatry 2023. [DOI: 10.1016/j.bionps.2023.100062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/29/2023] Open
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Kim KY, Shin KY, Chang KA. GFAP as a Potential Biomarker for Alzheimer's Disease: A Systematic Review and Meta-Analysis. Cells 2023; 12:cells12091309. [PMID: 37174709 PMCID: PMC10177296 DOI: 10.3390/cells12091309] [Citation(s) in RCA: 82] [Impact Index Per Article: 41.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 04/26/2023] [Accepted: 04/29/2023] [Indexed: 05/15/2023] Open
Abstract
Blood biomarkers have been considered tools for the diagnosis, prognosis, and monitoring of Alzheimer's disease (AD). Although amyloid-β peptide (Aβ) and tau are primarily blood biomarkers, recent studies have identified other reliable candidates that can serve as measurable indicators of pathological conditions. One such candidate is the glial fibrillary acidic protein (GFAP), an astrocytic cytoskeletal protein that can be detected in blood samples. Increasing evidence suggests that blood GFAP levels can be used to detect early-stage AD. In this systematic review and meta-analysis, we aimed to evaluate GFAP in peripheral blood as a biomarker for AD and provide an overview of the evidence regarding its utility. Our analysis revealed that the GFAP level in the blood was higher in the Aβ-positive group than in the negative groups, and in individuals with AD or mild cognitive impairment (MCI) compared to the healthy controls. Therefore, we believe that the clinical use of blood GFAP measurements has the potential to accelerate the diagnosis and improve the prognosis of AD.
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Affiliation(s)
- Ka Young Kim
- Department of Nursing, College of Nursing, Gachon University, Incheon 21936, Republic of Korea
- Neuroscience Research Institute, Gachon University, Incheon 21565, Republic of Korea
| | - Ki Young Shin
- Bio-MAX Institute, Seoul National University, Seoul 08826, Republic of Korea
| | - Keun-A Chang
- Neuroscience Research Institute, Gachon University, Incheon 21565, Republic of Korea
- Department of Pharmacology, College of Medicine, Gachon University, Incheon 21936, Republic of Korea
- Bio-Medical Sciences, Gachon Advanced Institute for Health Sciences and Technology, Gachon University, Incheon 21936, Republic of Korea
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van Dam M, de Jong BA, Willemse EAJ, Nauta IM, Huiskamp M, Klein M, Moraal B, de Geus-Driessen S, Geurts JJG, Uitdehaag BMJ, Teunissen CE, Hulst HE. A multimodal marker for cognitive functioning in multiple sclerosis: the role of NfL, GFAP and conventional MRI in predicting cognitive functioning in a prospective clinical cohort. J Neurol 2023:10.1007/s00415-023-11676-4. [PMID: 37101095 DOI: 10.1007/s00415-023-11676-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 03/16/2023] [Accepted: 03/17/2023] [Indexed: 04/28/2023]
Abstract
BACKGROUND Cognitive impairment in people with MS (PwMS) has primarily been investigated using conventional imaging markers or fluid biomarkers of neurodegeneration separately. However, the single use of these markers do only partially explain the large heterogeneity found in PwMS. OBJECTIVE To investigate the use of multimodal (bio)markers: i.e., serum and cerebrospinal fluid (CSF) levels of neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) and conventional imaging markers in predicting cognitive functioning in PwMS. METHODS Eighty-two PwMS (56 females, disease duration = 14 ± 9 years) underwent neuropsychological and neurological examination, structural magnetic resonance imaging, blood sampling and lumbar puncture. PwMS were classified as cognitively impaired (CI) if scoring ≥ 1.5SD below normative scores on ≥ 20% of test scores. Otherwise, PwMS were defined as cognitively preserved (CP). Association between fluid and imaging (bio)markers were investigated, as well as binary logistics regression to predict cognitive status. Finally, a multimodal marker was calculated using statistically important predictors of cognitive status. RESULTS Only higher NfL levels (in serum and CSF) correlated with worse processing speed (r = - 0.286, p = 0.012 and r = - 0.364, p = 0.007, respectively). sNfL added unique variance in the prediction of cognitive status on top of grey matter volume (NGMV), p = 0.002). A multimodal marker of NGMV and sNfL yielded most promising results in predicting cognitive status (sensitivity = 85%, specificity = 58%). CONCLUSION Fluid and imaging (bio)markers reflect different aspects of neurodegeneration and cannot be used interchangeably as markers for cognitive functioning in PwMS. The use of a multimodal marker, i.e., the combination of grey matter volume and sNfL, seems most promising for detecting cognitive deficits in MS.
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Affiliation(s)
- Maureen van Dam
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.
| | - Brigit A de Jong
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Eline A J Willemse
- Neurochemistry Lab, Department of Clinical Chemistry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
- Neurology Clinic and Policlinic, Departments of Head, Spine and Neuromedicine, Biomedicine and Clinical Research, Research Center for Clinical Neuroimmunology and Neuroscience (RC2NB), University Hospital Basel, University of Basel, Basel, Switzerland
| | - Ilse M Nauta
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Marijn Huiskamp
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Martin Klein
- Department of Medical Psychology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Bastiaan Moraal
- Department of Radiology and Nuclear Medicine, MS Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Sanne de Geus-Driessen
- Department of Medical Psychology, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Jeroen J G Geurts
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Bernard M J Uitdehaag
- MS Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Lab, Department of Clinical Chemistry, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Hanneke E Hulst
- MS Center Amsterdam, Anatomy and Neurosciences, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands
- Institute of Psychology, Health, Medical and Neuropsychology Unit, Leiden University, Wassenaarseweg 52, Leiden, The Netherlands
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Xie L, Das SR, Wisse LEM, Ittyerah R, de Flores R, Shaw LM, Yushkevich PA, Wolk DA. Baseline structural MRI and plasma biomarkers predict longitudinal structural atrophy and cognitive decline in early Alzheimer's disease. Alzheimers Res Ther 2023; 15:79. [PMID: 37041649 PMCID: PMC10088234 DOI: 10.1186/s13195-023-01210-z] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 03/13/2023] [Indexed: 04/13/2023]
Abstract
BACKGROUND Crucial to the success of clinical trials targeting early Alzheimer's disease (AD) is recruiting participants who are more likely to progress over the course of the trials. We hypothesize that a combination of plasma and structural MRI biomarkers, which are less costly and non-invasive, is predictive of longitudinal progression measured by atrophy and cognitive decline in early AD, providing a practical alternative to PET or cerebrospinal fluid biomarkers. METHODS Longitudinal T1-weighted MRI, cognitive (memory-related test scores and clinical dementia rating scale), and plasma measurements of 245 cognitively normal (CN) and 361 mild cognitive impairment (MCI) patients from ADNI were included. Subjects were further divided into β-amyloid positive/negative (Aβ+/Aβ-)] subgroups. Baseline plasma (p-tau181 and neurofilament light chain) and MRI-based structural medial temporal lobe subregional measurements and their association with longitudinal measures of atrophy and cognitive decline were tested using stepwise linear mixed effect modeling in CN and MCI, as well as separately in the Aβ+/Aβ- subgroups. Receiver operating characteristic (ROC) analyses were performed to investigate the discriminative power of each model in separating fast and slow progressors (first and last terciles) of each longitudinal measurement. RESULTS A total of 245 CN (35.0% Aβ+) and 361 MCI (53.2% Aβ+) participants were included. In the CN and MCI groups, both baseline plasma and structural MRI biomarkers were included in most models. These relationships were maintained when limited to the Aβ+ and Aβ- subgroups, including Aβ- CN (normal aging). ROC analyses demonstrated reliable discriminative power in identifying fast from slow progressors in MCI [area under the curve (AUC): 0.78-0.93] and more modestly in CN (0.65-0.73). CONCLUSIONS The present data support the notion that plasma and MRI biomarkers, which are relatively easy to obtain, provide a prediction for the rate of future cognitive and neurodegenerative progression that may be particularly useful in clinical trial stratification and prognosis. Additionally, the effect in Aβ- CN indicates the potential use of these biomarkers in predicting a normal age-related decline.
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Affiliation(s)
- Long Xie
- Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, 3700 Hamilton Walk, Suite D600, Richards Building 6th floor, Philadelphia, PA, 19104, USA.
| | - Sandhitsu R Das
- Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, 3700 Hamilton Walk, Suite D600, Richards Building 6th floor, Philadelphia, PA, 19104, USA
- Penn Memory Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Laura E M Wisse
- Department of Diagnostic Radiology, Lund University, Lund, Sweden
| | - Ranjit Ittyerah
- Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, 3700 Hamilton Walk, Suite D600, Richards Building 6th floor, Philadelphia, PA, 19104, USA
| | - Robin de Flores
- Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, 3700 Hamilton Walk, Suite D600, Richards Building 6th floor, Philadelphia, PA, 19104, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Paul A Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, 3700 Hamilton Walk, Suite D600, Richards Building 6th floor, Philadelphia, PA, 19104, USA
| | - David A Wolk
- Penn Memory Center, University of Pennsylvania, Philadelphia, PA, USA
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Claus CC, Staekenborg SS, Verweij KHW, Schuur J, van der Werf SP, Scheltens P, Claus JJ. The clock drawing test is an important contribution to the Mini Mental State Examination in screening for cognitive impairment. Int J Geriatr Psychiatry 2023; 38:e5914. [PMID: 37083937 DOI: 10.1002/gps.5914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2022] [Accepted: 04/11/2023] [Indexed: 04/22/2023]
Abstract
BACKGROUND The clock drawing test (CDT) and the Mini Mental State Examination (MMSE) are frequently used screening instruments for cognitive impairment, however, the precise contribution of the CDT to the MMSE is largely unknown. METHODS We studied patients with subjective cognitive impairment (SCI, n = 481), mild cognitive impairment (MCI, n = 628) and Alzheimer's disease (AD, n = 1099). Discrimination between patients was examined with multiple logistic regression, adjusted for age, sex, and education. Four groups were constructed based on a normal/abnormal MMSE (cut-off <24/30) versus normal/abnormal CDT (cut-off ≤2/3). Visually rated medial temporal lobe atrophy (MTA) on CT was used as parameter of neurodegeneration. RESULTS The CDT significantly contributed to the MMSE in discriminating SCI from both MCI and AD patients. Our four group analyses showed that of those patients with a normal MMSE and incorrectly classified as SCI, an abnormal CDT could significantly identify 10.0% as MCI and 13.2% as AD. Among those with an abnormal MMSE, the percentage AD patients shifted from 53.1% to 82.1% due to an abnormal CDT. Presence of an abnormal CDT was significantly related to MTA increase, regardless of the MMSE score. CONCLUSION The CDT is an important additional screening tool to the MMSE. An abnormal CDT with a normal MMSE is an indicator for cognitive impairment. An abnormal CDT in combination with an abnormal MMSE can be considered as an indicator of disease progression.
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Affiliation(s)
- Caroline C Claus
- Department of Neurology, Tergooi Medical Center, Hilversum, The Netherlands
- Department of Medical Psychology, Tergooi Medical Center, Hilversum, The Netherlands
| | | | - Kim H W Verweij
- Department of Medical Psychology, Tergooi Medical Center, Hilversum, The Netherlands
| | - Jacqueline Schuur
- Department of Geriatrics, Tergooi Medical Center, Hilversum, The Netherlands
| | - Sieberen P van der Werf
- Faculty of Social and Behavioral Sciences, University of Amsterdam, Amsterdam, The Netherlands
| | - Philip Scheltens
- Department of Neurology, Alzheimer Center, Amsterdam Neuroscience, Amsterdam University Medical Center, Amsterdam, The Netherlands
| | - Jules J Claus
- Department of Neurology, Tergooi Medical Center, Hilversum, The Netherlands
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Hernández C, Simó-Servat O, Porta M, Grauslund J, Harding SP, Frydkjaer-Olsen U, García-Arumí J, Ribeiro L, Scanlon P, Cunha-Vaz J, Simó R. Serum glial fibrillary acidic protein and neurofilament light chain as biomarkers of retinal neurodysfunction in early diabetic retinopathy: results of the EUROCONDOR study. Acta Diabetol 2023; 60:837-844. [PMID: 36959506 DOI: 10.1007/s00592-023-02076-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 03/11/2023] [Indexed: 03/25/2023]
Abstract
AIMS Neurodegeneration and glial activation are primary events in the pathogenesis of diabetic retinopathy. Serum glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are biomarkers of underlying neuroinflammatory and neurodegenerative disease processes. The aim of the present study was to assess the usefulness of these serum biomarkers for the identification and monitoring of retinal neurodysfunction in subjects with type 2 diabetes. METHODS A case-control study was designed including 38 patients from the placebo arm of the EUROCONDOR clinical trial: 19 with and 19 without retinal neurodysfunction assessed by multifocal electroretinography. GFAP and NfL were measured by Simoa. RESULTS Serum levels of GFAP and NfL directly correlated with age (r = 0.37, p = 0.023 and r = 0.54, p < 0.001, respectively). In addition, a direct correlation between GFAP and NfL was observed (r = 0.495, p = 0.002). Serum levels of GFAP were significantly higher at baseline in those subjects in whom neurodysfunction progressed after the 2 years of follow-up (139.1 ± 52.5 pg/mL vs. 100.2 ± 54.6 pg/mL; p = 0.04). CONCLUSIONS GFAP could be a useful serum biomarker for retinal neurodysfunction. Monitoring retinal neurodysfunction using blood samples would be of benefit in clinical decision-making. However, further research is needed to validate this result as well as to establish the best cutoff values.
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Affiliation(s)
- Cristina Hernández
- Diabetes and Metabolism Research Unit and CIBERDEM, Vall d'Hebron Research Institute, Vall d'Hebron Barcelona Hospital Campus, Passeig de La Vall d'Hebron, 119-129, 08035, Barcelona, Spain.
| | - Olga Simó-Servat
- Diabetes and Metabolism Research Unit and CIBERDEM, Vall d'Hebron Research Institute, Vall d'Hebron Barcelona Hospital Campus, Passeig de La Vall d'Hebron, 119-129, 08035, Barcelona, Spain
| | - Massimo Porta
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Jakob Grauslund
- Research Unit of Ophthalmology, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Simon P Harding
- Department of Eye and Vision Science, Institute of Life Course and Medical Sciences, University of Liverpool, and St. Paul's Eye Unit. Liverpool University Hospitals, Liverpool, UK
| | - Ulrik Frydkjaer-Olsen
- Research Unit of Ophthalmology, Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - José García-Arumí
- Department of Ophthalmology, Vall d'Hebron University Hospital, Barcelona, Spain
| | - Luísa Ribeiro
- Association for Innovation and Biomedical Research on Light and Image (AIBILI), Coimbra, Portugal
| | - Peter Scanlon
- Gloucestershire Hospitals National Health Service Foundation Trust, Cheltenham, UK
| | - José Cunha-Vaz
- Association for Innovation and Biomedical Research on Light and Image (AIBILI), Coimbra, Portugal
| | - Rafael Simó
- Diabetes and Metabolism Research Unit and CIBERDEM, Vall d'Hebron Research Institute, Vall d'Hebron Barcelona Hospital Campus, Passeig de La Vall d'Hebron, 119-129, 08035, Barcelona, Spain
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Salvadó G, Ossenkoppele R, Ashton NJ, Beach TG, Serrano GE, Reiman EM, Zetterberg H, Mattsson-Carlgren N, Janelidze S, Blennow K, Hansson O. Specific associations between plasma biomarkers and postmortem amyloid plaque and tau tangle loads. EMBO Mol Med 2023; 15:e17123. [PMID: 36912178 PMCID: PMC10165361 DOI: 10.15252/emmm.202217123] [Citation(s) in RCA: 90] [Impact Index Per Article: 45.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 02/21/2023] [Accepted: 02/21/2023] [Indexed: 03/14/2023] Open
Abstract
Several promising plasma biomarkers for Alzheimer's disease have been recently developed, but their neuropathological correlates have not yet been fully determined. To investigate and compare independent associations between multiple plasma biomarkers (p-tau181, p-tau217, p-tau231, Aβ42/40, GFAP, and NfL) and neuropathologic measures of amyloid and tau, we included 105 participants from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) with antemortem plasma samples and a postmortem neuropathological exam, 48 of whom had longitudinal p-tau217 and p-tau181. When simultaneously including plaque and tangle loads, the Aβ42/40 ratio and p-tau231 were only associated with plaques (ρAβ42/40 [95%CI] = -0.53[-0.65, -0.35], ρp-tau231 [95%CI] = 0.28[0.10, 0.43]), GFAP was only associated with tangles (ρGFAP [95%CI] = 0.39[0.17, 0.57]), and p-tau217 and p-tau181 were associated with both plaques (ρp-tau217 [95%CI] = 0.40[0.21, 0.56], ρp-tau181 [95%CI] = 0.36[0.15, 0.50]) and tangles (ρp-tau217 [95%CI] = 0.52[0.34, 0.66]; ρp-tau181 [95%CI] = 0.36[0.17, 0.52]). A model combining p-tau217 and the Aβ42/40 ratio showed the highest accuracy for predicting the presence of Alzheimer's disease neuropathological change (ADNC, AUC[95%CI] = 0.89[0.82, 0.96]) and plaque load (R2 = 0.55), while p-tau217 alone was optimal for predicting tangle load (R2 = 0.45). Our results suggest that high-performing assays of plasma p-tau217 and Aβ42/40 might be an optimal combination to assess Alzheimer's-related pathology in vivo.
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Affiliation(s)
- Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.,Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, King's College London, London, UK.,NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley, NHS Foundation, London, UK
| | | | | | - Eric M Reiman
- Banner Alzheimer's Institute, Arizona State University and University of Arizona, Phoenix, AZ, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK.,UK Dementia Research Institute at UCL, London, UK.,Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden.,Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
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38
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Silva-Spínola A, Lima M, Leitão MJ, Bernardes C, Durães J, Duro D, Tábuas-Pereira M, Santana I, Baldeiras I. Blood biomarkers in mild cognitive impairment patients: Relationship between analytes and progression to Alzheimer disease dementia. Eur J Neurol 2023; 30:1565-1573. [PMID: 36880887 DOI: 10.1111/ene.15762] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Revised: 02/23/2023] [Accepted: 02/24/2023] [Indexed: 03/08/2023]
Abstract
BACKGROUND AND PURPOSE Blood-based biomarkers are promising tools for the diagnosis of Alzheimer disease (AD) at prodromal stages (mild cognitive impairment [MCI]) and are hoped to be implemented as screening tools for patients with cognitive complaints. In this work, we evaluated the potential of peripheral neurological biomarkers to predict progression to AD dementia and the relation between blood and cerebrospinal fluid (CSF) AD markers in MCI patients referred from a general neurological department. METHODS A group of 106 MCI patients followed at the Neurology Department of Coimbra University Hospital was included. Data regarding baseline neuropsychological evaluation, CSF levels of amyloid β 42 (Aβ42), Aβ40, total tau (t-Tau), and phosphorylated tau 181 (p-Tau181) were available for all the patients. Aβ42, Aβ40, t-Tau, p-Tau181, glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL) levels were determined in baseline stored serum and plasma samples by commercial SiMoA (Single Molecule Array) assays. Progression from MCI to AD dementia was assessed at follow-up (mean = 5.8 ± 3.4 years). RESULTS At baseline, blood markers NfL, GFAP, and p-Tau181 were significantly increased in patients who progressed to AD at follow-up (p < 0.001). In contrast, plasma Aβ42/40 ratio and t-Tau showed no significant differences between groups. NfL, GFAP, and p-Tau181 demonstrated good diagnostic accuracy to identify progression to AD dementia (area under the curve [AUC] = 0.81, 0.80, and 0.76, respectively), which improved when combined (AUC = 0.89). GFAP and p-Tau181 were correlated with CSF Aβ42. Association of p-Tau181 with NfL was mediated by GFAP, with a significant indirect association of 88% of the total effect. CONCLUSIONS Our findings highlight the potential of combining blood-based GFAP, NfL, and p-Tau181 to be applied as a prognostic tool in MCI.
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Affiliation(s)
- Anuschka Silva-Spínola
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.,Center for Informatics and Systems, Department of Informatics Engineering, University of Coimbra, Coimbra, Portugal.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Marisa Lima
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.,Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal.,Center for Research in Neuropsychology and Cognitive Behavioral Intervention, Faculty of Psychology and Educational Sciences, University of Coimbra, Coimbra, Portugal
| | - Maria João Leitão
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal
| | - Catarina Bernardes
- Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - João Durães
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal.,Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Diana Duro
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.,Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Miguel Tábuas-Pereira
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal.,Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Isabel Santana
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal.,Neurology Department, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Inês Baldeiras
- Center for Innovative Biomedicine and Biotechnology, University of Coimbra, Coimbra, Portugal.,Faculty of Medicine, University of Coimbra, Coimbra, Portugal
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39
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Yu X, Shao K, Wan K, Li T, Li Y, Zhu X, Han Y. Progress in blood biomarkers of subjective cognitive decline in preclinical Alzheimer's disease. Chin Med J (Engl) 2023; 136:505-521. [PMID: 36914945 PMCID: PMC10106168 DOI: 10.1097/cm9.0000000000002566] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Indexed: 03/15/2023] Open
Abstract
ABSTRACT Alzheimer's disease (AD) is a neurodegenerative disease that gradually impairs cognitive functions. Recently, there has been a conceptual shift toward AD to view the disease as a continuum. Since AD is currently incurable, effective intervention to delay or prevent pathological cognitive decline may best target the early stages of symptomatic disease, such as subjective cognitive decline (SCD), in which cognitive function remains relatively intact. Diagnostic methods for identifying AD, such as cerebrospinal fluid biomarkers and positron emission tomography, are invasive and expensive. Therefore, it is imperative to develop blood biomarkers that are sensitive, less invasive, easier to access, and more cost effective for AD diagnosis. This review aimed to summarize the current data on whether individuals with SCD differ reliably and effectively in subjective and objective performances compared to cognitively normal elderly individuals, and to find one or more convenient and accessible blood biomarkers so that researchers can identify SCD patients with preclinical AD in the population as soon as possible. Owing to the heterogeneity and complicated pathogenesis of AD, it is difficult to make reliable diagnoses using only a single blood marker. This review provides an overview of the progress achieved to date with the use of SCD blood biomarkers in patients with preclinical AD, highlighting the key areas of application and current challenges.
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Affiliation(s)
- Xianfeng Yu
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
| | - Kai Shao
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
| | - Ke Wan
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China
| | - Taoran Li
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
| | - Yuxia Li
- Department of Neurology, Tangshan Central Hospital, Tangshan, Hebei 063000, China
| | - Xiaoqun Zhu
- Department of Neurology, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing 100053, China
- School of Biomedical Engineering, Hainan University, Haikou, Hainan 570228, China
- Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing 100053, China
- National Clinical Research Center for Geriatric Diseases, Beijing 100053, China
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40
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Bermejo-Bescós P, Jiménez-Aliaga KL, Benedí J, Martín-Aragón S. A Diet Containing Rutin Ameliorates Brain Intracellular Redox Homeostasis in a Mouse Model of Alzheimer's Disease. Int J Mol Sci 2023; 24:ijms24054863. [PMID: 36902309 PMCID: PMC10003355 DOI: 10.3390/ijms24054863] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2023] [Revised: 02/18/2023] [Accepted: 02/22/2023] [Indexed: 03/06/2023] Open
Abstract
Quercetin has been studied extensively for its anti-Alzheimer's disease (AD) and anti-aging effects. Our previous studies have found that quercetin and in its glycoside form, rutin, can modulate the proteasome function in neuroblastoma cells. We aimed to explore the effects of quercetin and rutin on intracellular redox homeostasis of the brain (reduced glutathione/oxidized glutathione, GSH/GSSG), its correlation with β-site APP cleaving enzyme 1 (BACE1) activity, and amyloid precursor protein (APP) expression in transgenic TgAPP mice (bearing human Swedish mutation APP transgene, APPswe). On the basis that BACE1 protein and APP processing are regulated by the ubiquitin-proteasome pathway and that supplementation with GSH protects neurons from proteasome inhibition, we investigated whether a diet containing quercetin or rutin (30 mg/kg/day, 4 weeks) diminishes several early signs of AD. Genotyping analyses of animals were carried out by PCR. In order to determine intracellular redox homeostasis, spectrofluorometric methods were adopted to quantify GSH and GSSG levels using o-phthalaldehyde and the GSH/GSSG ratio was ascertained. Levels of TBARS were determined as a marker of lipid peroxidation. Enzyme activities of SOD, CAT, GR, and GPx were determined in the cortex and hippocampus. ΒACE1 activity was measured by a secretase-specific substrate conjugated to two reporter molecules (EDANS and DABCYL). Gene expression of the main antioxidant enzymes: APP, BACE1, a Disintegrin and metalloproteinase domain-containing protein 10 (ADAM10), caspase-3, caspase-6, and inflammatory cytokines were determined by RT-PCR. First, overexpression of APPswe in TgAPP mice decreased GSH/GSSG ratio, increased malonaldehyde (MDA) levels, and, overall, decreased the main antioxidant enzyme activities in comparison to wild-type (WT) mice. Treatment of TgAPP mice with quercetin or rutin increased GSH/GSSG, diminished MDA levels, and favored the enzyme antioxidant capacity, particularly with rutin. Secondly, both APP expression and BACE1 activity were diminished with quercetin or rutin in TgAPP mice. Regarding ADAM10, it tended to increase in TgAPP mice with rutin treatment. As for caspase-3 expression, TgAPP displayed an increase which was the opposite with rutin. Finally, the increase in expression of the inflammatory markers IL-1β and IFN-γ in TgAPP mice was lowered by both quercetin and rutin. Collectively, these findings suggest that, of the two flavonoids, rutin may be included in a day-to-day diet as a form of adjuvant therapy in AD.
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41
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Gorelick PB. Blood and Cerebrospinal Fluid Biomarkers in Vascular Dementia and Alzheimer's Disease: A Brief Review. Clin Geriatr Med 2023; 39:67-76. [PMID: 36404033 DOI: 10.1016/j.cger.2022.08.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
The Maintenance of brain health is a lifelong process whereby potentially deleterious exposures such as cardiovascular risks, amyloid beta, and phosphorylated tau may adversely affect the brain decades before there are clinical manifestations. Thus, the early structural and neuropathological foundation for the development of cognitive impairment and its allied features later in life may provide precursor targets such that interventions may be applied to prevent or slow cognitively impairing processes if the underlying mechanism(s) can be addressed in time.
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Affiliation(s)
- Philip B Gorelick
- Section of Stroke and Neurocritical Care, Davee Department of Neurology, Northwestern University Feinberg School of Medicine, 625 North Michigan Avenue Suite 1150, Chicago, IL 60611, USA.
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Morris JC, Weiner M, Xiong C, Beckett L, Coble D, Saito N, Aisen PS, Allegri R, Benzinger TLS, Berman SB, Cairns NJ, Carrillo MC, Chui HC, Chhatwal JP, Cruchaga C, Fagan AM, Farlow M, Fox NC, Ghetti B, Goate AM, Gordon BA, Graff-Radford N, Day GS, Hassenstab J, Ikeuchi T, Jack CR, Jagust WJ, Jucker M, Levin J, Massoumzadeh P, Masters CL, Martins R, McDade E, Mori H, Noble JM, Petersen RC, Ringman JM, Salloway S, Saykin AJ, Schofield PR, Shaw LM, Toga AW, Trojanowski JQ, Vöglein J, Weninger S, Bateman RJ, Buckles VD. Autosomal dominant and sporadic late onset Alzheimer's disease share a common in vivo pathophysiology. Brain 2022; 145:3594-3607. [PMID: 35580594 PMCID: PMC9989348 DOI: 10.1093/brain/awac181] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2021] [Revised: 04/12/2022] [Accepted: 04/27/2022] [Indexed: 11/13/2022] Open
Abstract
The extent to which the pathophysiology of autosomal dominant Alzheimer's disease corresponds to the pathophysiology of 'sporadic' late onset Alzheimer's disease is unknown, thus limiting the extrapolation of study findings and clinical trial results in autosomal dominant Alzheimer's disease to late onset Alzheimer's disease. We compared brain MRI and amyloid PET data, as well as CSF concentrations of amyloid-β42, amyloid-β40, tau and tau phosphorylated at position 181, in 292 carriers of pathogenic variants for Alzheimer's disease from the Dominantly Inherited Alzheimer Network, with corresponding data from 559 participants from the Alzheimer's Disease Neuroimaging Initiative. Imaging data and CSF samples were reprocessed as appropriate to guarantee uniform pipelines and assays. Data analyses yielded rates of change before and after symptomatic onset of Alzheimer's disease, allowing the alignment of the ∼30-year age difference between the cohorts on a clinically meaningful anchor point, namely the participant age at symptomatic onset. Biomarker profiles were similar for both autosomal dominant Alzheimer's disease and late onset Alzheimer's disease. Both groups demonstrated accelerated rates of decline in cognitive performance and in regional brain volume loss after symptomatic onset. Although amyloid burden accumulation as determined by PET was greater after symptomatic onset in autosomal dominant Alzheimer's disease than in late onset Alzheimer's disease participants, CSF assays of amyloid-β42, amyloid-β40, tau and p-tau181 were largely overlapping in both groups. Rates of change in cognitive performance and hippocampal volume loss after symptomatic onset were more aggressive for autosomal dominant Alzheimer's disease participants. These findings suggest a similar pathophysiology of autosomal dominant Alzheimer's disease and late onset Alzheimer's disease, supporting a shared pathobiological construct.
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Affiliation(s)
- John C Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Michael Weiner
- Department of Radiology, University of California at San Francisco, San Francisco, CA, USA
| | - Chengjie Xiong
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Laurel Beckett
- Department of Public Health Sciences, School of Medicine, University of California; Davis, Davis, CA, USA
| | - Dean Coble
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Naomi Saito
- Department of Public Health Sciences, School of Medicine, University of California; Davis, Davis, CA, USA
| | - Paul S Aisen
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Ricardo Allegri
- Department of Cognitive Neurology, Neuropsychology and Neuropsychiatry, Institute for Neurological Research (FLENI), Buenos Aires, Argentina
| | - Tammie L S Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Sarah B Berman
- Department of Neurology and Clinical and Translational Science, University of Pittsburgh, Pittsburgh, PA, USA
| | - Nigel J Cairns
- College of Medicine and Health and the Living Systems Institute, University of Exeter, Exeter, UK
| | | | - Helena C Chui
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Jasmeer P Chhatwal
- Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Anne M Fagan
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Martin Farlow
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Nick C Fox
- Department of Neurodegenerative Disease and UK Dementia Research Institute, UCL Institute of Neurology, London, UK
| | - Bernardino Ghetti
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Alison M Goate
- Ronald M. Loeb Center for Alzheimer’s Disease, Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Brian A Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Gregory S Day
- Department of Neurology, Mayo Clinic, Jacksonville, FL, USA
| | - Jason Hassenstab
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | | | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Mathias Jucker
- Cell Biology of Neurological Diseases Group, German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Hertie Institute for Clinical Brain Research, University of Tübingen, Tübingen, Germany
| | - Johannes Levin
- DZNE Munich, Munich Cluster of Systems Neurology (SyNergy) and Ludwig-Maximilians-Universität, Munich, Germany
| | - Parinaz Massoumzadeh
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Colin L Masters
- Florey Institute, University of Melbourne, Melbourne, Australia
| | - Ralph Martins
- Sir James McCusker Alzheimer’s Disease Research Unit, Edith Cowan University, Nedlands, Australia
| | - Eric McDade
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Hiroshi Mori
- Department of Neuroscience, Osaka City University Medical School, Osaka City, Japan
| | - James M Noble
- Department of Neurology, Taub Institute for Research on Aging Brain, Columbia University Irving Medical Center, New York, NY, USA
| | | | - John M Ringman
- Department of Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Stephen Salloway
- Department of Neurology, Butler Hospital and Alpert Medical School of Brown University, Providence, RI, 02906, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences and the Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Peter R Schofield
- Neuroscience Research Australia and School of Medical Sciences, University of New South Wales, Sydney, Australia
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Arthur W Toga
- Laboratory of Neuro Imaging, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, Institute on Aging, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jonathan Vöglein
- German Center for Neurodegenerative Diseases (DZNE) and Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | | | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Virginia D Buckles
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
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Baiardi S, Quadalti C, Mammana A, Dellavalle S, Zenesini C, Sambati L, Pantieri R, Polischi B, Romano L, Suffritti M, Bentivenga GM, Randi V, Stanzani-Maserati M, Capellari S, Parchi P. Diagnostic value of plasma p-tau181, NfL, and GFAP in a clinical setting cohort of prevalent neurodegenerative dementias. Alzheimers Res Ther 2022; 14:153. [PMID: 36221099 PMCID: PMC9555092 DOI: 10.1186/s13195-022-01093-6] [Citation(s) in RCA: 77] [Impact Index Per Article: 25.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 09/29/2022] [Indexed: 11/07/2022]
Abstract
Background Increasing evidence supports the use of plasma biomarkers of neurodegeneration and neuroinflammation to screen and diagnose patients with dementia. However, confirmatory studies are required to demonstrate their usefulness in the clinical setting. Methods We evaluated plasma and cerebrospinal fluid (CSF) samples from consecutive patients with frontotemporal dementia (FTD) (n = 59), progressive supranuclear palsy (PSP) (n = 31), corticobasal syndrome (CBS) (n = 29), dementia with Lewy bodies (DLB) (n = 49), Alzheimer disease (AD) (n = 97), and suspected non-AD physiopathology (n = 51), as well as plasma samples from 60 healthy controls (HC). We measured neurofilament light chain (NfL), phospho-tau181 (p-tau181), and glial fibrillary acid protein (GFAP) using Simoa (all plasma biomarkers and CSF GFAP), CLEIA (CSF p-tau181), and ELISA (CSF NfL) assays. Additionally, we stratified patients according to the A/T/N classification scheme and the CSF α-synuclein real-time quaking-induced conversion assay (RT-QuIC) results. Results We found good correlations between CSF and plasma biomarkers for NfL (rho = 0.668, p < 0.001) and p-tau181 (rho = 0.619, p < 0.001). Plasma NfL was significantly higher in disease groups than in HC and showed a greater increase in FTD than in AD [44.9 (28.1–68.6) vs. 21.9 (17.0–27.9) pg/ml, p < 0.001]. Conversely, plasma p-tau181 and GFAP levels were significantly higher in AD than in FTD [3.2 (2.4–4.3) vs. 1.1 (0.7–1.6) pg/ml, p < 0.001; 404.7 (279.7–503.0) vs. 198.2 (143.9–316.8) pg/ml, p < 0.001]. GFAP also allowed discriminating disease groups from HC. In the distinction between FTD and AD, plasma p-tau181 showed better accuracy (AUC 0.964) than NfL (AUC 0.791) and GFAP (AUC 0.818). In DLB and CBS, CSF amyloid positive (A+) subjects had higher plasma p-tau181 and GFAP levels than A− individuals. CSF RT-QuIC showed positive α-synuclein seeding activity in 96% DLB and 15% AD patients with no differences in plasma biomarker levels in those stratified by RT-QuIC result. Conclusions In a single-center clinical cohort, we confirm the high diagnostic value of plasma p-tau181 for distinguishing FTD from AD and plasma NfL for discriminating degenerative dementias from HC. Plasma GFAP alone differentiates AD from FTD and neurodegenerative dementias from HC but with lower accuracy than p-tau181 and NfL. In CBS and DLB, plasma p-tau181 and GFAP levels are significantly influenced by beta-amyloid pathology. Supplementary Information The online version contains supplementary material available at 10.1186/s13195-022-01093-6.
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Affiliation(s)
- Simone Baiardi
- grid.6292.f0000 0004 1757 1758Department of Experimental, Diagnostic and Specialty Medicine (DIMES) University of Bologna, Bologna, Italy ,grid.492077.fIRCCS Istituto delle Scienze Neurologiche di Bologna, Via Altura 1/8, 40139 Bologna, Italy
| | - Corinne Quadalti
- grid.492077.fIRCCS Istituto delle Scienze Neurologiche di Bologna, Via Altura 1/8, 40139 Bologna, Italy
| | - Angela Mammana
- grid.6292.f0000 0004 1757 1758Department of Experimental, Diagnostic and Specialty Medicine (DIMES) University of Bologna, Bologna, Italy ,grid.492077.fIRCCS Istituto delle Scienze Neurologiche di Bologna, Via Altura 1/8, 40139 Bologna, Italy
| | - Sofia Dellavalle
- grid.492077.fIRCCS Istituto delle Scienze Neurologiche di Bologna, Via Altura 1/8, 40139 Bologna, Italy
| | - Corrado Zenesini
- grid.492077.fIRCCS Istituto delle Scienze Neurologiche di Bologna, Via Altura 1/8, 40139 Bologna, Italy
| | - Luisa Sambati
- grid.492077.fIRCCS Istituto delle Scienze Neurologiche di Bologna, Via Altura 1/8, 40139 Bologna, Italy
| | - Roberta Pantieri
- grid.492077.fIRCCS Istituto delle Scienze Neurologiche di Bologna, Via Altura 1/8, 40139 Bologna, Italy
| | - Barbara Polischi
- grid.492077.fIRCCS Istituto delle Scienze Neurologiche di Bologna, Via Altura 1/8, 40139 Bologna, Italy
| | - Luciano Romano
- grid.6292.f0000 0004 1757 1758Department of Biomedical and Neuromotor Sciences University of Bologna (DIBINEM), Bologna, Italy
| | - Matteo Suffritti
- grid.6292.f0000 0004 1757 1758Department of Biomedical and Neuromotor Sciences University of Bologna (DIBINEM), Bologna, Italy
| | - Giuseppe Mario Bentivenga
- grid.6292.f0000 0004 1757 1758Department of Biomedical and Neuromotor Sciences University of Bologna (DIBINEM), Bologna, Italy
| | - Vanda Randi
- Emilia-Romagna Regional Blood Bank, Immunohematology and Transfusion Medicine Service, Bologna Metropolitan Area, Bologna, Italy
| | | | - Sabina Capellari
- grid.492077.fIRCCS Istituto delle Scienze Neurologiche di Bologna, Via Altura 1/8, 40139 Bologna, Italy ,grid.6292.f0000 0004 1757 1758Department of Biomedical and Neuromotor Sciences University of Bologna (DIBINEM), Bologna, Italy
| | - Piero Parchi
- grid.492077.fIRCCS Istituto delle Scienze Neurologiche di Bologna, Via Altura 1/8, 40139 Bologna, Italy ,grid.6292.f0000 0004 1757 1758Department of Biomedical and Neuromotor Sciences University of Bologna (DIBINEM), Bologna, Italy
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Alvarez M, Trent E, Goncalves BDS, Pereira DG, Puri R, Frazier NA, Sodhi K, Pillai SS. Cognitive dysfunction associated with COVID-19: Prognostic role of circulating biomarkers and microRNAs. Front Aging Neurosci 2022; 14:1020092. [PMID: 36268187 PMCID: PMC9577202 DOI: 10.3389/fnagi.2022.1020092] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2022] [Accepted: 09/13/2022] [Indexed: 01/08/2023] Open
Abstract
COVID-19 is renowned as a multi-organ disease having subacute and long-term effects with a broad spectrum of clinical manifestations. The evolving scientific and clinical evidence demonstrates that the frequency of cognitive impairment after COVID-19 is high and it is crucial to explore more clinical research and implement proper diagnostic and treatment strategies. Several central nervous system complications have been reported as comorbidities of COVID-19. The changes in cognitive function associated with neurodegenerative diseases develop slowly over time and are only diagnosed at an already advanced stage of molecular pathology. Hence, understanding the common links between COVID-19 and neurodegenerative diseases will broaden our knowledge and help in strategizing prognostic and therapeutic approaches. The present review focuses on the diverse neurodegenerative changes associated with COVID-19 and will highlight the importance of major circulating biomarkers and microRNAs (miRNAs) associated with the disease progression and severity. The literature analysis showed that major proteins associated with central nervous system function, such as Glial fibrillary acidic protein, neurofilament light chain, p-tau 181, Ubiquitin C-terminal hydrolase L1, S100 calcium-binding protein B, Neuron-specific enolase and various inflammatory cytokines, were significantly altered in COVID-19 patients. Furthermore, among various miRNAs that are having pivotal roles in various neurodegenerative diseases, miR-146a, miR-155, Let-7b, miR-31, miR-16 and miR-21 have shown significant dysregulation in COVID-19 patients. Thus the review consolidates the important findings from the numerous studies to unravel the underlying mechanism of neurological sequelae in COVID-19 and the possible association of circulatory biomarkers, which may serve as prognostic predictors and therapeutic targets in future research.
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Affiliation(s)
| | | | | | | | | | | | | | - Sneha S. Pillai
- Department of Surgery, Biomedical Sciences and Medicine, Joan C. Edwards School of Medicine, Marshall University, Huntington, WV, United States
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45
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van der Flier WM, Scheltens P. The ATN Framework—Moving Preclinical Alzheimer Disease to Clinical Relevance. JAMA Neurol 2022; 79:968-970. [DOI: 10.1001/jamaneurol.2022.2967] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
- Wiesje M. van der Flier
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Epidemiology and Data Science, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- EQT Life Sciences, Amsterdam, the Netherlands
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46
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Parvizi T, König T, Wurm R, Silvaieh S, Altmann P, Klotz S, Rommer PS, Furtner J, Regelsberger G, Lehrner J, Traub-Weidinger T, Gelpi E, Stögmann E. Real-world applicability of glial fibrillary acidic protein and neurofilament light chain in Alzheimer's disease. Front Aging Neurosci 2022; 14:887498. [PMID: 36072480 PMCID: PMC9441692 DOI: 10.3389/fnagi.2022.887498] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Accepted: 07/04/2022] [Indexed: 11/13/2022] Open
Abstract
Background: Blood-based biomarkers may add a great benefit in detecting the earliest neuropathological changes in patients with Alzheimer's disease (AD). We examined the utility of neurofilament light chain (NfL) and glial fibrillary acidic protein (GFAP) regarding clinical diagnosis and differentiation between amyloid positive and negative patients. To evaluate the practical application of these biomarkers in a routine clinical setting, we conducted this study in a heterogeneous memory-clinic population. Methods: We included 167 patients in this retrospective cross-sectional study, 123 patients with an objective cognitive decline [mild cognitive impairment (MCI) due to AD, n = 63, and AD-dementia, n = 60] and 44 age-matched healthy controls (HC). Cerebrospinal fluid (CSF) and plasma concentrations of NfL and GFAP were measured with single molecule array (SIMOA®) technology using the Neurology 2-Plex B kit from Quanterix. To assess the discriminatory potential of different biomarkers, age- and sex-adjusted receiver operating characteristic (ROC) curves were calculated and the area under the curve (AUC) of each model was compared. Results: We constructed a panel combining plasma NfL and GFAP with known AD risk factors (Combination panel: age+sex+APOE4+GFAP+NfL). With an AUC of 91.6% (95%CI = 0.85-0.98) for HC vs. AD and 81.7% (95%CI = 0.73-0.90) for HC vs. MCI as well as an AUC of 87.5% (95%CI = 0.73-0.96) in terms of predicting amyloid positivity, this panel showed a promising discriminatory power to differentiate these populations. Conclusion: The combination of plasma GFAP and NfL with well-established risk factors discerns amyloid positive from negative patients and could potentially be applied to identify patients who would benefit from a more invasive assessment of amyloid pathology. In the future, improved prediction of amyloid positivity with a noninvasive test may decrease the number and costs of a more invasive or expensive diagnostic approach.
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Affiliation(s)
- Tandis Parvizi
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Theresa König
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Raphael Wurm
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Sara Silvaieh
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Patrick Altmann
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Sigrid Klotz
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria
| | | | - Julia Furtner
- Division of Neuroradiology and Musculoskeletal Radiology, Department of Biomedical Imaging and Image-Guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Günther Regelsberger
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Johann Lehrner
- Department of Neurology, Medical University of Vienna, Vienna, Austria
| | - Tatjana Traub-Weidinger
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-Guided Therapy, University of Vienna, Vienna, Austria
| | - Ellen Gelpi
- Division of Neuropathology and Neurochemistry, Department of Neurology, Medical University of Vienna, Vienna, Austria
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Oberstein TJ, Schmidt MA, Florvaag A, Haas AL, Siegmann EM, Olm P, Utz J, Spitzer P, Doerfler A, Lewczuk P, Kornhuber J, Maler JM. Amyloid-β levels and cognitive trajectories in non-demented pTau181-positive subjects without amyloidopathy. Brain 2022; 145:4032-4041. [PMID: 35973034 DOI: 10.1093/brain/awac297] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2022] [Revised: 07/11/2022] [Accepted: 07/24/2022] [Indexed: 11/13/2022] Open
Abstract
Phosphorylated Tau181 (pTau181) in cerebrospinal fluid (CSF) and recently in plasma has been associated with Alzheimer's disease. In the absence of amyloidopathy, individuals with increased total Tau levels and/or temporal lobe atrophy experience no or only mild cognitive decline compared with biomarker-negative controls, leading to the proposal to categorize this constellation as Suspected non-Alzheimer disease pathophysiology (SNAP). We investigated whether the characteristics of SNAP also applied to individuals with increased CSF-pTau181 without amyloidopathy. In this long-term observational study, 285 non-demented individuals, including 76 individuals with subjective cognitive impairment and 209 individuals with mild cognitive impairment, were classified based on their CSF-levels of pTau181 (T), total Tau (N), Amyloid-beta-(Aβ)-42 and Aβ42/Aβ40 ratio (A) into A + T+N±, A + T-N±, A-T + N±, and A-T-N-. The longitudinal analysis included 154 subjects with a follow-up of more than 12 months who were followed to a median of 4.6 years (interquartile range = 4.3 years). We employed linear mixed models on psychometric tests and region of interest analysis of structural MRI data. Cognitive decline and hippocampal atrophy rate were significantly higher in A + T+N ± compared to A-T + N±, whereas there was no difference between A-T + N ± and A-T-N-. Furthermore, there was no significant difference between A-T + N ± and controls in dementia risk (Hazard ratio 0.3, 95% confidence interval [0.1, 1.9]). However, A-T + N ± and A-T-N- could be distinguished based on their Aβ42 and Aβ40 levels. Both Aβ40 and Aβ42 levels were significantly increased in A-T + N ± compared to controls. Long term follow-up of A-T + N ± individuals revealed no evidence that this biomarker constellation was associated with dementia or more severe hippocampal atrophy rates compared to controls. However, because of the positive association of pTau181 with Aβ in the A-T + N ± group, a link to the pathophysiology of Alzheimer´s disease cannot be excluded in this case. We propose to refer to these individuals in the SNAP group as "pTau and Aβ surge with subtle deterioration" (PASSED). The investigation of the circumstances of simultaneous elevation of pTau and Aβ might provide a deeper insight into the process under which Aβ becomes pathological.
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Affiliation(s)
- Timo Jan Oberstein
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Manuel Alexander Schmidt
- Institute of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Anna Florvaag
- Department of Radiology and Nuclear Medicine, Klinikum Nuremberg, Nuremberg, Germany
| | - Anna Lena Haas
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Eva Maria Siegmann
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Pauline Olm
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Janine Utz
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Philipp Spitzer
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Arnd Doerfler
- Institute of Neuroradiology, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Piotr Lewczuk
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany.,Department of Neurodegeneration Diagnostics, Medical University of Bialystok, University Hospital of Bialystok, Bialystok, Poland.,Department of Biochemical Diagnostics, University Hospital of Bialystok, Bialystok, Poland
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Juan Manuel Maler
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander-Universität Erlangen-Nürnberg, Erlangen, Germany
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48
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Tondo G, De Marchi F. From Biomarkers to Precision Medicine in Neurodegenerative Diseases: Where Are We? J Clin Med 2022; 11:jcm11154515. [PMID: 35956130 PMCID: PMC9369634 DOI: 10.3390/jcm11154515] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Accepted: 07/30/2022] [Indexed: 01/05/2023] Open
Abstract
The biomarkers era grew in the last two decades when several technical and methodological advances have improved the research in neurodegenerative diseases [...]
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Affiliation(s)
- Giacomo Tondo
- Neurology Unit, S. Andrea Hospital, Department of Translational Medicine, University of Piemonte Orientale, 13100 Vercelli, Italy;
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, 20132 Milan, Italy
| | - Fabiola De Marchi
- ALS Centre, Neurology Unit, Maggiore della Carità Hospital, Department of Translational Medicine, University of Piemonte Orientale, 28100 Novara, Italy
- Correspondence: ; Tel.: +39-0321-3732137
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49
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Cummings J, Kinney J. Biomarkers for Alzheimer's Disease: Context of Use, Qualification, and Roadmap for Clinical Implementation. MEDICINA (KAUNAS, LITHUANIA) 2022; 58:952. [PMID: 35888671 PMCID: PMC9318582 DOI: 10.3390/medicina58070952] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 07/13/2022] [Accepted: 07/15/2022] [Indexed: 12/30/2022]
Abstract
Background and Objectives: The US Food and Drug Administration (FDA) defines a biomarker as a characteristic that is measured as an indicator of normal biological processes, pathogenic processes, or responses to an exposure or intervention. Biomarkers may be used in clinical care or as drug development tools (DDTs) in clinical trials. The goal of this review and perspective is to provide insight into the regulatory guidance for the use of biomarkers in clinical trials and clinical care. Materials and Methods: We reviewed FDA guidances relevant to biomarker use in clinical trials and their transition to use in clinical care. We identified instructive examples of these biomarkers in Alzheimer's disease (AD) drug development and their application in clinical practice. Results: For use in clinical trials, biomarkers must have a defined context of use (COU) as a risk/susceptibility, diagnostic, monitoring, predictive, prognostic, pharmacodynamic, or safety biomarker. A four-stage process defines the pathway to establish the regulatory acceptance of the COU for a biomarker including submission of a letter of intent, description of the qualification plan, submission of a full qualification package, and acceptance through a qualification recommendation. Biomarkers used in clinical care may be companion biomarkers, in vitro diagnostic devices (IVDs), or laboratory developed tests (LDTs). A five-phase biomarker development process has been proposed to structure the biomarker development process. Conclusions: Biomarkers are increasingly important in drug development and clinical care. Adherence to regulatory guidance for biomarkers used in clinical trials and patient care is required to advance these important drug development and clinical tools.
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Affiliation(s)
- Jeffrey Cummings
- Pam Quirk Brain Health and Biomarker Laboratory, Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV 89154, USA;
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Association of CSF, Plasma, and Imaging Markers of Neurodegeneration With Clinical Progression in People With Subjective Cognitive Decline. Neurology 2022; 99:86. [PMID: 35387857 PMCID: PMC11387099 DOI: 10.1212/wnl.0000000000200734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
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