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Heyer S, Simon M, Doyen M, Mortada A, Roch V, Jeanbert E, Thilly N, Malaplate C, Kearney-Schwartz A, Jonveaux T, Bannay A, Verger A. 18F-FDG PET can effectively rule out conversion to dementia and the presence of CSF biomarker of neurodegeneration: a real-world data analysis. Alzheimers Res Ther 2024; 16:182. [PMID: 39135067 PMCID: PMC11320856 DOI: 10.1186/s13195-024-01535-3] [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: 03/05/2024] [Accepted: 07/16/2024] [Indexed: 08/15/2024]
Abstract
BACKGROUND Precisely defining the delay in onset of dementia is a particular challenge for early diagnosis. Brain [18F] fluoro-2-deoxy-2-D-glucose (18F-FDG) Positron Emission Tomography (PET) is a particularly interesting tool for the early diagnosis of neurodegenerative diseases, through the measurement of the cerebral glucose metabolic rate. There is currently a lack of longitudinal studies under real-life conditions, with sufficient patients, to accurately evaluate the predictive values of brain 18F-FDG PET scans. Here, we aimed to estimate the value of brain 18F-FDG PET for predicting the risk of dementia conversion and the risk of occurrence of a neurodegenerative pathology. METHODS Longitudinal data for a cohort of patients with no diagnosis of dementia at the time of recruitment referred by a tertiary memory clinic for brain 18F-FDG PET were matched with (Prince M, Wimo A, Guerchet Maëlenn, Ali G-C, Wu Y-T et al. World Alzheimer Report 2015. The Global Impact of Dementia: An analysis of prevalence, incidence, cost and trends. [Research Report] Alzheimer's Disease International. 2015. 2015.) data from the French National Health Data System (NHDS), (Jack CR, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, et al. NIA-AA Research Framework: Toward a biological definition of Alzheimer's disease. Alzheimers Dement. 2018;14(4):535-62.) data from the National Alzheimer Bank (NAB), and (Davis M, O`Connell T, Johnson S, Cline S, Merikle E, Martenyi F, et al. Estimating Alzheimer's Disease Progression Rates from Normal Cognition Through Mild Cognitive Impairment and Stages of Dementia. CAR. 2018;15(8):777-88.) lumbar puncture (LP) biomarker data. The criteria for dementia conversion were the designation, within the three years after the brain 18F-FDG PET scan, of a long-term condition for dementia in the NHDS and a dementia stage of cognitive impairment in the NAB. The criterion for the identification of a neurodegenerative disease in the medical records was the determination of LP biomarker levels. RESULTS Among the 403 patients (69.9 ± 11.4 years old, 177 women) from the initial cohort with data matched with the NHDS data, 137 were matched with the NAB data, and 61 were matched with LP biomarker data. Within three years of the scan, a 18F-FDG PET had negative predictive values of 85% for dementia conversion (according to the NHDS and NAB datasets) and 95% for the presence of LP neurodegeneration biomarkers. CONCLUSION A normal brain 18F-FDG PET scan can help rule out the risk of dementia conversion and the presence of cerebrospinal fluid (CSF) biomarker of neurodegeneration early with high certainty, allowing modifications to patient management regimens in the short term. TRIAL REGISTRATION Clinical Trials database (NCT04804722). March 18, 2021. Retrospectively registered.
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Affiliation(s)
- Sébastien Heyer
- Department of Nuclear Medicine and Nancyclotep Imaging Platform, Université de Lorraine, CHRU Nancy, Nancy, F-54000, France
| | - Maïa Simon
- Department of Methodology, Promotion and Investigation, Université de Lorraine, CHRU-Nancy, Nancy, F-54000, France
| | - Matthieu Doyen
- Department of Nuclear Medicine and Nancyclotep Imaging Platform, Université de Lorraine, CHRU Nancy, Nancy, F-54000, France
- Université de Lorraine, IADI, INSERM U1254, Nancy, F-54000, France
| | - Ali Mortada
- Department of Nuclear Medicine and Nancyclotep Imaging Platform, Université de Lorraine, CHRU Nancy, Nancy, F-54000, France
| | - Véronique Roch
- Department of Nuclear Medicine and Nancyclotep Imaging Platform, Université de Lorraine, CHRU Nancy, Nancy, F-54000, France
| | - Elodie Jeanbert
- Department of Methodology, Promotion and Investigation, Université de Lorraine, CHRU-Nancy, Nancy, F-54000, France
| | - Nathalie Thilly
- Department of Methodology, Promotion and Investigation, Université de Lorraine, CHRU-Nancy, Nancy, F-54000, France
| | - Catherine Malaplate
- Department of Biochemistry, Université de Lorraine, CHRU-Nancy, Nancy, F-54000, France
| | - Anna Kearney-Schwartz
- Department of Geriatrics, Université de Lorraine, CHRU-Nancy, Nancy, F-54000, France
- CMRR, University Hospital Nancy, Nancy, F-54000, France
| | - Thérèse Jonveaux
- CMRR, University Hospital Nancy, Nancy, F-54000, France
- Department of Neurology, University Hospital Nancy, Nancy, F-54000, France
| | - Aurélie Bannay
- Medical Assessment and Information Department, Université de Lorraine, CHRU-Nancy, Nancy, 54000, France
| | - Antoine Verger
- Department of Nuclear Medicine and Nancyclotep Imaging Platform, Université de Lorraine, CHRU Nancy, Nancy, F-54000, France.
- Université de Lorraine, IADI, INSERM U1254, Nancy, F-54000, France.
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Charisis S, Short MI, Bernal R, Kautz TF, Treviño HA, Mathews J, Dediós AGV, Muhammad JAS, Luckey AM, Aslam A, Himali JJ, Shipp EL, Habes M, Beiser AS, DeCarli C, Scarmeas N, Ramachandran VS, Seshadri S, Maillard P, Satizabal CL. Leptin bioavailability and markers of brain atrophy and vascular injury in the middle age. Alzheimers Dement 2024. [PMID: 39132759 DOI: 10.1002/alz.13879] [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: 12/14/2023] [Revised: 03/01/2024] [Accepted: 03/24/2024] [Indexed: 08/13/2024]
Abstract
INTRODUCTION We investigated the associations of leptin markers with cognitive function and magnetic resonance imaging (MRI) measures of brain atrophy and vascular injury in healthy middle-aged adults. METHODS We included 2262 cognitively healthy participants from the Framingham Heart Study with neuropsychological evaluation; of these, 2028 also had available brain MRI. Concentrations of leptin, soluble leptin receptor (sOB-R), and their ratio (free leptin index [FLI]), indicating leptin bioavailability, were measured using enzyme-linked immunosorbent assays. Cognitive and MRI measures were derived using standardized protocols. RESULTS Higher sOB-R was associated with lower fractional anisotropy (FA, β = -0.114 ± 0.02, p < 0.001), and higher free water (FW, β = 0.091 ± 0.022, p < 0.001) and peak-width skeletonized mean diffusivity (PSMD, β = 0.078 ± 0.021, p < 0.001). Correspondingly, higher FLI was associated with higher FA (β = 0.115 ± 0.027, p < 0.001) and lower FW (β = -0.096 ± 0.029, p = 0.001) and PSMD (β = -0.085 ± 0.028, p = 0.002). DISCUSSION Higher leptin bioavailability was associated with better white matter (WM) integrity in healthy middle-aged adults, supporting the putative neuroprotective role of leptin in late-life dementia risk. HIGHLIGHTS Higher leptin bioavailability was related to better preservation of white matter microstructure. Higher leptin bioavailability during midlife might confer protection against dementia. Potential benefits might be even stronger for individuals with visceral obesity. DTI measures might be sensitive surrogate markers of subclinical neuropathology.
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Affiliation(s)
- Sokratis Charisis
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Meghan I Short
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, Massachusetts, USA
| | - Rebecca Bernal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Tiffany F Kautz
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Hector A Treviño
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Julia Mathews
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Angel Gabriel Velarde Dediós
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Jazmyn A S Muhammad
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Alison M Luckey
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Asra Aslam
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Jayandra J Himali
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
- The Framingham Heart Study, Framingham, Massachusetts, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Eric L Shipp
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Mohamad Habes
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
| | - Alexa S Beiser
- The Framingham Heart Study, Framingham, Massachusetts, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Charles DeCarli
- Department of Neurology, University of California, Davis, Sacramento, California, USA
| | - Nikolaos Scarmeas
- 1st Department of Neurology, National and Kapodistrian University of Athens, Athens, Greece
- Taub Institute for Research in Alzheimer's Disease and the Aging Brain, the Gertrude H. Sergievsky Center, Columbia University, New York, New York, USA
| | - Vasan S Ramachandran
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
- The Framingham Heart Study, Framingham, Massachusetts, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
- The Framingham Heart Study, Framingham, Massachusetts, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
| | - Pauline Maillard
- Department of Neurology, University of California, Davis, Sacramento, California, USA
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, Texas, USA
- The Framingham Heart Study, Framingham, Massachusetts, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts, USA
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Guo Y, Huang L, Kuang J, Sun T, Zhang X, Tian H, Xie F, Chen T, Guo Q. Physical function is associated with cognitive status, brain amyloid-beta deposition, and blood biomarkers in Chinese Han population. CNS Neurosci Ther 2024; 30:e14921. [PMID: 39155519 PMCID: PMC11330986 DOI: 10.1111/cns.14921] [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: 10/16/2023] [Revised: 07/17/2024] [Accepted: 08/02/2024] [Indexed: 08/20/2024] Open
Abstract
BACKGROUND The physical function of elderly individuals reflects whether they have had a history of regular physical activity over the long term. Such indicators have been found to have a certain connection with cognitive function these years. However, there is limited research that associates it with mechanisms such as cerebral Aβ deposition. We aim to investigate this relationship and unveil the underlying mechanisms. METHOD Physical function and cognition data of 4189 participants were obtained from the Chinese preclinical Alzheimer's disease study. Participants were divided into six groups according to disease severity. Among them, 1048 participants underwent the positron emission tomography-computed tomography (PET-CT) and plasma biomarker test. Grip strength and gait were combined into a score indicating physical function. Multiple linear regression models and logistic regression models were mainly used to conduct the analysis. RESULTS There was a significant positive correlation between physical function and cognitive function (R = 0.48, p < 0.001), independent of sex, age, apolipoprotein E-ε4 genotype, and disease stages (p < 0.001). Physical function was effective in distinguishing individuals with cognitive impairment from those without (AUC = 0.835). Physical function was negatively associated with brain Aβ deposition (p = 0.008) and brain Aβ had an intermediary effect (p < 0.01) on the association between physical function and cognition in women. This association was mainly evident in the lateral parietal, lateral temporal, posterior cingulate, frontal, occipital, and precuneus regions. Physical function was negatively associated with plasma neurofilament light-chain (Nfl) level (p < 0.001). CONCLUSIONS Physical function is strongly associated with cognitive function in the Chinese elderly, and brain Aβ deposition partly mediates the linkage in women. Plasma Nfl can be used as a potential target for exercise intervention in cognitive function. Improving physical function will contribute to the alleviation of cognition decline.
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Affiliation(s)
- Yuhuai Guo
- Department of GerontologyShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
- Center for Translational Medicine and Shanghai Key Laboratory of Diabetes MellitusShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
- School of Exercise and HealthShanghai University of SportShanghaiChina
| | - Lin Huang
- Department of GerontologyShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Junliang Kuang
- Center for Translational Medicine and Shanghai Key Laboratory of Diabetes MellitusShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Tao Sun
- Center for Translational Medicine and Shanghai Key Laboratory of Diabetes MellitusShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Xiaoyan Zhang
- Department of GerontologyShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Haili Tian
- School of Exercise and HealthShanghai University of SportShanghaiChina
| | - Fang Xie
- PET Center, Huashan HospitalFudan UniversityShanghaiChina
| | - Tianlu Chen
- Center for Translational Medicine and Shanghai Key Laboratory of Diabetes MellitusShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
| | - Qihao Guo
- Department of GerontologyShanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of MedicineShanghaiChina
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Bermudez C, Lesnick TG, More SS, Ramanan VK, Knopman DS, Rabinstein AA, Cogswell PM, Jack CR, Vemuri P, Petersen RC, Graff-Radford J, Chen JJ. Optical Coherence Tomography Angiography Retinal Imaging Associations With Burden of Small Vessel Disease and Amyloid Positivity in the Brain. J Neuroophthalmol 2024:00041327-990000000-00691. [PMID: 39085998 DOI: 10.1097/wno.0000000000002230] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/02/2024]
Abstract
BACKGROUND Alzheimer disease (AD) and other dementias are associated with vascular changes and amyloid deposition, which may be reflected as density changes in the retinal capillaries. These changes may can be directly visualized and quantified with optical coherence tomography angiography (OCTA), making OCTA a potential noninvasive preclinical biomarker of small vessel disease and amyloid positivity. Our objective was to investigate the feasibility of retinal imaging metrics as noninvasive biomarkers of small vessel disease and amyloid positivity in the brain. METHODS We investigated associations between OCTA and neuroimaging and cognitive metrics in 41 participants without dementia from the Mayo Clinic Study of Aging and Alzheimer's Disease Research Center. OCTA metrics included superficial, deep, and full retina capillary density of the fovea, parafovea, and macula as well as the area of the foveal avascular zone (FAZ). Neuroimaging metrics included a high burden of white matter hyperintensity (WMH), presence of cerebral microbleeds (CMB), lacunar infarcts, and amyloid positivity as evidenced on positron emission tomography (PET), whereas cognitive metrics included mini-mental status examination (MMSE) score. We performed generalized estimating equations to account for measurements in each eye while controlling for age and sex to estimate associations between OCTA metrics and neuroimaging and cognitive scores. RESULTS Associations between OCTA and neuroimaging metrics were restricted to the fovea. OCTA showed decreased capillary density with high burden of WMH in both the superficial (P = 0.003), deep (P = 0.004), and full retina (P = 0.01) in the fovea but not the parafovea or whole macula. Similarly, participants with amyloid PET positivity had significantly decreased capillary density in the superficial fovea (P = 0.027) and deep fovea (P = 0.03) but higher density in the superficial parafovea (P = 0.038). Participants with amyloid PET positivity also had a significantly larger FAZ (P = 0.031), whereas in those with high WMH burden the difference did not reach statistical significance (P = 0.075). There was also a positive association between MMSE and capillary density of the full retina within the fovea (P = 0.037) and in the superficial parafovea (P = 0.046). No associations were found between OCTA metrics and presence of CMB or presence of lacunar infarcts. CONCLUSION The associations of lower foveal capillary density with cerebral WMH and amyloid positivity suggest that further research is warranted to evaluate for shared mechanisms of disease between small vessel disease and AD pathologies.
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Affiliation(s)
- Camilo Bermudez
- Department of Neurology (CB, VKR, DSK, AAR, RCP, JG-R, JJC), Mayo Clinic, Rochester, Minnesota; Center for Drug Design (SSM), College of Pharmacy, University of Minnesota, Minneapolis, Minnesota; Departments of Radiology (PMC, CRJ, PV) and Ophthalmology (JJC), Mayo Clinic, Rochester, Minnesota; and Department of Quantitative Health Sciences (TGL), Mayo Clinic, Rochester, Minnesota
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Parvizi T, Wurm R, König T, Silvaieh S, Altmann P, Klotz S, Regelsberger G, Traub‐Weidinger T, Gelpi E, Stögmann E. Real-world performance of plasma p-tau181 in a heterogeneous memory clinic cohort. Ann Clin Transl Neurol 2024; 11:1988-1998. [PMID: 38965832 PMCID: PMC11330220 DOI: 10.1002/acn3.52116] [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] [Received: 12/27/2023] [Revised: 04/22/2024] [Accepted: 05/23/2024] [Indexed: 07/06/2024] Open
Abstract
OBJECTIVE In light of clinical trials and disease-modifying therapies, an early identification of patients at-risk of developing Alzheimer's disease (AD) is crucial. Blood-based biomarkers have shown promising results regarding the in vivo detection of the earliest neuropathological changes in AD. Herein, we investigated the ability of plasma p-tau181 to act as a prescreening marker for amyloid positivity in a heterogeneous memory clinic-based cohort. METHODS In this retrospective cross-sectional study, we included a total of 115 patients along the clinical AD continuum (mild cognitive impairment [MCI] due to AD, n = 62, probable AD dementia, n = 53). Based on their biomarker status, they were stratified into an amyloid-positive (Aβ+, n = 88) or amyloid-negative cohort (Aβ-, n = 27). Plasma and CSF p-tau181 concentrations were quantified using an ultrasensitive single-molecule array (SIMOA©). Furthermore, age- and sex-adjusted receiver operating characteristic (ROC) curves were calculated and the area under the curve (AUC) of each model was compared using DeLong's test for correlated AUC curves. RESULTS The median (interquartile range [IQR]) concentration of plasma p-tau181 was significantly higher in Aβ+ patients (3.6 pg/mL [2.5-4.6]), compared with Aβ- patients (1.7 pg/mL [1.2-1.9], p < 0.001). Regarding the distinction between Aβ+ and Aβ- patients and the prediction of amyloid positivity, a high diagnostic accuracy for plasma p-tau181 with an AUC of 0.89 (95% CI = 0.82-0.95) was calculated. Adding the risk factors, age and APOE4, to the model did not significantly improve its performance. INTERPRETATION Our findings demonstrate that plasma p-tau181 could be a noninvasive and feasible prescreening marker for amyloid positivity in a heterogeneous clinical AD cohort and therefore help in identifying those who would benefit from more invasive assessment of amyloid pathology.
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Affiliation(s)
- Tandis Parvizi
- Department of NeurologyMedical University of ViennaViennaAustria
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
| | - Raphael Wurm
- Department of NeurologyMedical University of ViennaViennaAustria
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
| | - Theresa König
- Department of NeurologyMedical University of ViennaViennaAustria
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
| | - Sara Silvaieh
- Department of NeurologyMedical University of ViennaViennaAustria
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
| | - Patrick Altmann
- Department of NeurologyMedical University of ViennaViennaAustria
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
| | - Sigrid Klotz
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
- Division of Neuropathology and Neurochemistry, Department of NeurologyMedical University of ViennaViennaAustria
| | - Guenther Regelsberger
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
- Division of Neuropathology and Neurochemistry, Department of NeurologyMedical University of ViennaViennaAustria
| | - Tatjana Traub‐Weidinger
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | - Ellen Gelpi
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
- Division of Neuropathology and Neurochemistry, Department of NeurologyMedical University of ViennaViennaAustria
| | - Elisabeth Stögmann
- Department of NeurologyMedical University of ViennaViennaAustria
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
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Zhang S, Yuan J, Sun Y, Wu F, Liu Z, Zhai F, Zhang Y, Somekh J, Peleg M, Zhu YC, Huang Z. Machine learning on longitudinal multi-modal data enables the understanding and prognosis of Alzheimer's disease progression. iScience 2024; 27:110263. [PMID: 39040055 PMCID: PMC11261013 DOI: 10.1016/j.isci.2024.110263] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 03/01/2024] [Accepted: 06/11/2024] [Indexed: 07/24/2024] Open
Abstract
Alzheimer's disease (AD) is a complex pathophysiological disease. Allowing for heterogeneity, not only in disease manifestations but also in different progression patterns, is critical for developing effective disease models that can be used in clinical and research settings. We introduce a machine learning model for identifying underlying patterns in Alzheimer's disease (AD) trajectory using longitudinal multi-modal data from the ADNI cohort and the AIBL cohort. Ten biologically and clinically meaningful disease-related states were identified from data, which constitute three non-overlapping stages (i.e., neocortical atrophy [NCA], medial temporal atrophy [MTA], and whole brain atrophy [WBA]) and two distinct disease progression patterns (i.e., NCA → WBA and MTA → WBA). The index of disease-related states provided a remarkable performance in predicting the time to conversion to AD dementia (C-Index: 0.923 ± 0.007). Our model shows potential for promoting the understanding of heterogeneous disease progression and early predicting the conversion time to AD dementia.
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Affiliation(s)
- Suixia Zhang
- Zhejiang University, 866 Yuhangtang Rd, Hangzhou 310058, P.R. China
- Department of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830017, China
| | - Jing Yuan
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, P.R. China
| | - Yu Sun
- Zhejiang University, 866 Yuhangtang Rd, Hangzhou 310058, P.R. China
| | - Fei Wu
- Zhejiang University, 866 Yuhangtang Rd, Hangzhou 310058, P.R. China
| | - Ziyue Liu
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, P.R. China
| | - Feifei Zhai
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, P.R. China
| | - Yaoyun Zhang
- DAMO Academy, Alibaba Group, 969 Wenyixi Rd, Hangzhou 310058, P.R. China
| | - Judith Somekh
- Department of Information Systems, University of Haifa, Haifa 3303220, Israel
| | - Mor Peleg
- Department of Information Systems, University of Haifa, Haifa 3303220, Israel
| | - Yi-Cheng Zhu
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, P.R. China
| | - Zhengxing Huang
- Zhejiang University, 866 Yuhangtang Rd, Hangzhou 310058, P.R. China
| | - for the Alzheimer’s Disease Neuroimaging Initiative and the Australian Imaging Biomarkers and Lifestyle Study of Aging
- Zhejiang University, 866 Yuhangtang Rd, Hangzhou 310058, P.R. China
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing 100730, P.R. China
- DAMO Academy, Alibaba Group, 969 Wenyixi Rd, Hangzhou 310058, P.R. China
- Department of Information Systems, University of Haifa, Haifa 3303220, Israel
- Department of Medical Engineering and Technology, Xinjiang Medical University, Urumqi 830017, China
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Devanarayan V, Llano DA, Hu YH, Hampel H, Kramer L, Dhadda S, Irizarry M. Plasma pTau181 enhances the prediction of future clinical decline in amyloid-positive mild cognitive impairment. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12621. [PMID: 39045143 PMCID: PMC11263975 DOI: 10.1002/dad2.12621] [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: 03/15/2024] [Revised: 05/29/2024] [Accepted: 06/19/2024] [Indexed: 07/25/2024]
Abstract
Abstract Plasma pTau181, a marker of amyloid and tau burden, was evaluated as a prognostic predictor of clinical decline and Alzheimer's disease (AD) progression of amyloid-positive (Aβ+) patients with mild cognitive impairment (MCI). The training cohort for constructing the Bayesian prediction models comprised 135 Aβ+ MCI clinical trial placebo subjects. Performance was evaluated in two validation cohorts. An 18-month ≥1 increase in the Clinical Dementia Rating Sum of Boxes was the clinical decline criterion. Baseline plasma pTau181 concentration matched clinical assessments' prediction performance. Adding pTau181 to clinical assessments significantly improved the prediction of an 18-month clinical decline and the 36-month progression from Aβ+ MCI to AD. The area under the receiver operating characteristic curve for the latter increased from 71.8% to 79%, and the hazard ratio for time-to-progression improved from 2.26 to 3.11 (p < 0.0001). Baseline plasma pTau181 has the potential for identifying Aβ+ MCI subjects with faster clinical decline over time. Highlights This study assessed pTau181 as a prognostic predictor of 18-month clinical decline and extended progression to Alzheimer's disease (AD) in amyloid-positive patients with mild cognitive impairment (Aβ+ MCI).The research findings underscore the promise of baseline plasma pTau181 as a screening tool for identifying Aβ+ MCI individuals with accelerated clinical decline within a standard 18-month clinical trial period. The predictive accuracy is notably enhanced when combined with clinical assessments.Similar positive outcomes were noted in forecasting the extended progression of Aβ+ MCI subjects to AD.
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Affiliation(s)
- Viswanath Devanarayan
- Eisai Inc.Clinical Evidence GenerationNutleyNew JerseyUSA
- Department of MathematicsStatistics and Computer ScienceUniversity of Illinois ChicagoChicagoIllinoisUSA
| | - Daniel A. Llano
- Carle Illinois College of MedicineUrbanaIllinoisUSA
- Department of Molecular and Integrative PhysiologyUniversity of Illinois Urbana‐ChampaignUrbanaIllinoisUSA
- Beckman Institute for Advanced Science and TechnologyUrbanaIllinoisUSA
| | - Yan Helen Hu
- Eisai Inc.Clinical Evidence GenerationNutleyNew JerseyUSA
| | - Harald Hampel
- Eisai Inc.Clinical Evidence GenerationNutleyNew JerseyUSA
| | - Lynn Kramer
- Eisai Inc.Clinical Evidence GenerationNutleyNew JerseyUSA
| | - Shobha Dhadda
- Eisai Inc.Clinical Evidence GenerationNutleyNew JerseyUSA
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Womack CL, Perkins A, Arnold JM. Cognitive Impairment in the Primary Care Clinic. Prim Care 2024; 51:233-251. [PMID: 38692772 DOI: 10.1016/j.pop.2024.02.010] [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] [Indexed: 05/03/2024]
Abstract
Cognitive impairment is a common problem in the geriatric population and is characterized by variable symptoms of memory difficulties, executive dysfunction, language or visuospatial problems, and behavioral changes. It is imperative that primary care clinicians recognize and differentiate the variable symptoms associated with cognitive impairment from changes attributable to normal aging or secondary to other medical conditions. A thorough evaluation for potentially reversible causes of dementia is required before diagnosis with a neurodegenerative dementia. Other abnormal neurologic findings, rapid progression, or early age of onset are red flags that merit referral to neurology for more specialized evaluation and treatment.
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Affiliation(s)
- Cindy L Womack
- Department of Neurology, Neuroscience Institute, Southern Illinois University School of Medicine, 751 North Rutledge Street, PO 19643, Springfield, IL 62794, USA
| | - Andrea Perkins
- Department of Neurology, Neuroscience Institute, Southern Illinois University School of Medicine, 751 North Rutledge Street, PO 19643, Springfield, IL 62794, USA
| | - Jennifer M Arnold
- Department of Neurology, Neuroscience Institute, Southern Illinois University School of Medicine, 751 North Rutledge Street, PO 19643, Springfield, IL 62794, USA.
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9
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Jácome D, Cotrufo T, Andrés-Benito P, Lidón L, Martí E, Ferrer I, Del Río JA, Gavín R. miR-519a-3p, found to regulate cellular prion protein during Alzheimer's disease pathogenesis, as a biomarker of asymptomatic stages. Biochim Biophys Acta Mol Basis Dis 2024; 1870:167187. [PMID: 38653354 DOI: 10.1016/j.bbadis.2024.167187] [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: 12/14/2023] [Revised: 04/11/2024] [Accepted: 04/16/2024] [Indexed: 04/25/2024]
Abstract
Clinical relevance of miRNAs as biomarkers is growing due to their stability and detection in biofluids. In this, diagnosis at asymptomatic stages of Alzheimer's disease (AD) remains a challenge since it can only be made at autopsy according to Braak NFT staging. Achieving the objective of detecting AD at early stages would allow possible therapies to be addressed before the onset of cognitive impairment. Many studies have determined that the expression pattern of some miRNAs is dysregulated in AD patients, but to date, none has been correlated with downregulated expression of cellular prion protein (PrPC) during disease progression. That is why, by means of cross studies of miRNAs up-regulated in AD with in silico identification of potential miRNAs-binding to 3'UTR of human PRNP gene, we selected miR-519a-3p for our study. Then, in vitro experiments were carried out in two ways. First, we validated miR-519a-3p target on 3'UTR-PRNP, and second, we analyzed the levels of PrPC expression after using of mimic technology on cell culture. In addition, RT-qPCR was performed to analyzed miR-519a-3p expression in human cerebral samples of AD at different stages of disease evolution. Additionally, samples of other neurodegenerative diseases such as other non-AD tauopathies and several synucleinopathies were included in the study. Our results showed that miR-519a-3p overlaps with PRNP 3'UTR in vitro and promotes downregulation of PrPC. Moreover, miR-519a-3p was found to be up-regulated exclusively in AD samples from stage I to VI, suggesting its potential use as a novel label of preclinical stages of the disease.
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Affiliation(s)
- Dayaneth Jácome
- Molecular and Cellular Neurobiotechnology, Institute for Bioengineering of Catalonia, Barcelona, Spain; Department of Cell Biology, Physiology and Immunology, University of Barcelona, Barcelona, Spain.
| | - Tiziana Cotrufo
- Molecular and Cellular Neurobiotechnology, Institute for Bioengineering of Catalonia, Barcelona, Spain; Department of Cell Biology, Physiology and Immunology, University of Barcelona, Barcelona, Spain; Institute of Neuroscience, University of Barcelona, Barcelona, Spain.
| | - Pol Andrés-Benito
- Center for Networked Biomedical Research in Neurodegenerative Diseases (CIBERNED), Barcelona, Madrid, Spain; Neurologic Diseases and Neurogenetics Group, Bellvitge Institute for Biomedical Research (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain.
| | - Laia Lidón
- Molecular and Cellular Neurobiotechnology, Institute for Bioengineering of Catalonia, Barcelona, Spain; Department of Cell Biology, Physiology and Immunology, University of Barcelona, Barcelona, Spain; Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Center for Networked Biomedical Research in Neurodegenerative Diseases (CIBERNED), Barcelona, Madrid, Spain.
| | - Eulàlia Martí
- Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Functional Genomics of Neurodegenerative Diseases, Department of Biomedical Sciences, University of Barcelona, Barcelona, Spain; CIBERESP (Centro en Red de Epidemiología y Salud Pública), Spain.
| | - Isidre Ferrer
- Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Center for Networked Biomedical Research in Neurodegenerative Diseases (CIBERNED), Barcelona, Madrid, Spain; Department of Pathology and Experimental Therapeutics, University of Barcelona, Barcelona, Spain; Senior Consultant Neuropathology, Service of Pathology, Bellvitge University Hospital, Hospitalet de Llobregat, Spain.
| | - José Antonio Del Río
- Molecular and Cellular Neurobiotechnology, Institute for Bioengineering of Catalonia, Barcelona, Spain; Department of Cell Biology, Physiology and Immunology, University of Barcelona, Barcelona, Spain; Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Center for Networked Biomedical Research in Neurodegenerative Diseases (CIBERNED), Barcelona, Madrid, Spain.
| | - Rosalina Gavín
- Molecular and Cellular Neurobiotechnology, Institute for Bioengineering of Catalonia, Barcelona, Spain; Department of Cell Biology, Physiology and Immunology, University of Barcelona, Barcelona, Spain; Institute of Neuroscience, University of Barcelona, Barcelona, Spain; Center for Networked Biomedical Research in Neurodegenerative Diseases (CIBERNED), Barcelona, Madrid, Spain.
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10
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Boa Sorte Silva NC, Barha CK, Erickson KI, Kramer AF, Liu-Ambrose T. Physical exercise, cognition, and brain health in aging. Trends Neurosci 2024; 47:402-417. [PMID: 38811309 DOI: 10.1016/j.tins.2024.04.004] [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: 11/17/2023] [Revised: 03/20/2024] [Accepted: 04/17/2024] [Indexed: 05/31/2024]
Abstract
Exercise training is an important strategy to counteract cognitive and brain health decline during aging. Evidence from systematic reviews and meta-analyses supports the notion of beneficial effects of exercise in cognitively unimpaired and impaired older individuals. However, the effects are often modest, and likely influenced by moderators such as exercise training parameters, sample characteristics, outcome assessments, and control conditions. Here, we discuss evidence on the impact of exercise on cognitive and brain health outcomes in healthy aging and in individuals with or at risk for cognitive impairment and neurodegeneration. We also review neuroplastic adaptations in response to exercise and their potential neurobiological mechanisms. We conclude by highlighting goals for future studies, including addressing unexplored neurobiological mechanisms and the inclusion of under-represented populations.
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Affiliation(s)
- Nárlon C Boa Sorte Silva
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada; Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada; Centre for Aging SMART at Vancouver Coastal Health, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada
| | - Cindy K Barha
- Faculty of Kinesiology, University of Calgary, Calgary, Alberta, Canada; Department of Cell Biology and Anatomy, Hotchkiss Brain Institute, Calgary, Alberta, Canada
| | - Kirk I Erickson
- Department of Psychology, University of Pittsburgh, Pittsburgh, PA, USA; AdventHealth Research Institute, Neuroscience, Orlando, FL, USA
| | - Arthur F Kramer
- Center for Cognitive and Brain Health, Northeastern University, Boston, MA, USA; Beckman Institute, University of Illinois Urbana-Champaign, Champaign, IL, USA
| | - Teresa Liu-Ambrose
- Djavad Mowafaghian Centre for Brain Health, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada; Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, British Columbia, Canada; Centre for Aging SMART at Vancouver Coastal Health, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada.
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11
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Hsieh CH, Ko CA, Liang CS, Yeh PK, Tsai CK, Tsai CL, Lin GY, Lin YK, Tsai MC, Yang FC. Longitudinal assessment of plasma biomarkers for early detection of cognitive changes in subjective cognitive decline. Front Aging Neurosci 2024; 16:1389595. [PMID: 38828389 PMCID: PMC11140011 DOI: 10.3389/fnagi.2024.1389595] [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: 02/21/2024] [Accepted: 04/29/2024] [Indexed: 06/05/2024] Open
Abstract
Background Individuals experiencing subjective cognitive decline (SCD) are at an increased risk of developing mild cognitive impairment and dementia. Early identification of SCD and neurodegenerative diseases using biomarkers may help clinical decision-making and improve prognosis. However, few cross-sectional and longitudinal studies have explored plasma biomarkers in individuals with SCD using immunomagnetic reduction. Objective To identify plasma biomarkers for SCD. Methods Fifty-two participants [38 with SCD, 14 healthy controls (HCs)] underwent baseline assessments, including measurements of plasma Aβ42, Aβ40, t-tau, p-tau, and α-synuclein using immunomagnetic reduction (IMR) assays, cognitive tests and the Mini-Mental State Examination (MMSE). Following initial cross-sectional analysis, 39 individuals (29 with SCD, 10 HCs) entered a longitudinal phase for reassessment of these biomarkers and the MMSE. Biomarker outcomes across different individual categories were primarily assessed using the area under the receiver operating characteristic (ROC) curve. The SCD subgroup with an MMSE decline over one point was compared to those without such a decline. Results Higher baseline plasma Aβ1-42 levels significantly discriminated participants with SCD from HCs, with an acceptable area under the ROC curve (AUC) of 67.5% [95% confidence interval (CI), 52.7-80.0%]. However, follow-up and changes in MMSE and IMR data did not significantly differ between the SCD and HC groups (p > 0.05). Furthermore, lower baseline plasma Aβ1-42 levels were able to discriminate SCD subgroups with and without cognitive decline with a satisfied performance (AUC, 75.0%; 95% CI, 55.6-89.1%). At last, the changes in t-tau and Aβ42 × t-tau could differentiate between the two SCD subgroups (p < 0.05). Conclusion Baseline plasma Aβ42 may help identify people with SCD and predict SCD progression. The role of plasma Aβ42 levels as well as their upward trends from baseline in cases of SCD that progress to mild cognitive impairment and Alzheimer's disease require further investigation.
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Affiliation(s)
- Cheng-Hao Hsieh
- Department of Neurology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Chien-An Ko
- Department of Neurology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Chih-Sung Liang
- Department of Psychiatry, Beitou Branch, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Po-Kuan Yeh
- Department of Neurology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
- Department of Psychiatry, Beitou Branch, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Chia-Kuang Tsai
- Department of Neurology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Chia-Lin Tsai
- Department of Neurology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Guan-Yu Lin
- Department of Neurology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
- Department of Neurology, Songshan Branch, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Yu-Kai Lin
- Department of Neurology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Ming-Chen Tsai
- Department of Neurology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
| | - Fu-Chi Yang
- Department of Neurology, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan
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12
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Mendes AJ, Ribaldi F, Lathuiliere A, Ashton NJ, Zetterberg H, Abramowicz M, Scheffler M, Assal F, Garibotto V, Blennow K, Frisoni GB. Comparison of plasma and neuroimaging biomarkers to predict cognitive decline in non-demented memory clinic patients. Alzheimers Res Ther 2024; 16:110. [PMID: 38755703 PMCID: PMC11097559 DOI: 10.1186/s13195-024-01478-9] [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] [Received: 02/05/2024] [Accepted: 05/07/2024] [Indexed: 05/18/2024]
Abstract
BACKGROUND Plasma biomarkers of Alzheimer's disease (AD) pathology, neurodegeneration, and neuroinflammation are ideally suited for secondary prevention programs in self-sufficient persons at-risk of dementia. Plasma biomarkers have been shown to be highly correlated with traditional imaging biomarkers. However, their comparative predictive value versus traditional AD biomarkers is still unclear in cognitively unimpaired (CU) subjects and with mild cognitive impairment (MCI). METHODS Plasma (Aβ42/40, p-tau181, p-tau231, NfL, and GFAP) and neuroimaging (hippocampal volume, centiloid of amyloid-PET, and tau-SUVR of tau-PET) biomarkers were assessed at baseline in 218 non-demented subjects (CU = 140; MCI = 78) from the Geneva Memory Center. Global cognition (MMSE) was evaluated at baseline and at follow-ups up to 5.7 years. We used linear mixed-effects models and Cox proportional-hazards regression to assess the association between biomarkers and cognitive decline. Lastly, sample size calculations using the linear mixed-effects models were performed on subjects positive for amyloid-PET combined with tau-PET and plasma biomarker positivity. RESULTS Cognitive decline was significantly predicted in MCI by baseline plasma NfL (β=-0.55), GFAP (β=-0.36), hippocampal volume (β = 0.44), centiloid (β=-0.38), and tau-SUVR (β=-0.66) (all p < 0.05). Subgroup analysis with amyloid-positive MCI participants also showed that only NfL and GFAP were the only significant predictors of cognitive decline among plasma biomarkers. Overall, NfL and tau-SUVR showed the highest prognostic values (hazard ratios of 7.3 and 5.9). Lastly, we demonstrated that adding NfL to the inclusion criteria could reduce the sample sizes of future AD clinical trials by up to one-fourth in subjects with amyloid-PET positivity or by half in subjects with amyloid-PET and tau-PET positivity. CONCLUSIONS Plasma NfL and GFAP predict cognitive decline in a similar manner to traditional imaging techniques in amyloid-positive MCI patients. Hence, even though they are non-specific biomarkers of AD, both can be implemented in memory clinic workups as important prognostic biomarkers. Likewise, future clinical trials might employ plasma biomarkers as additional inclusion criteria to stratify patients at higher risk of cognitive decline to reduce sample sizes and enhance effectiveness.
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Affiliation(s)
- Augusto J Mendes
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland.
- Geneva Memory Center, Department of Rehabilitation and Geriatrics,, Geneva University Hospitals, Geneva, Switzerland.
| | - Federica Ribaldi
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics,, Geneva University Hospitals, Geneva, Switzerland
| | - Aurelien Lathuiliere
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics,, Geneva University Hospitals, Geneva, Switzerland
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Clinical Neuroscience Institute, 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
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 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, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer?s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Marc Abramowicz
- Genetic Medicine, Diagnostics Dept, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Max Scheffler
- Division of Radiology, Geneva University Hospitals, Geneva, Switzerland
| | - Frédéric Assal
- Division of Neurology, Department of Clinical Neurosciences, Faculty of Medicine, Geneva University Hospitals, University of Geneva, Geneva, Switzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Faculty of Medicine, Geneva University Neurocenter, University of Geneva, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
- CIBM Center for Biomedical Imaging, Geneva, Switzerland
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics,, Geneva University Hospitals, Geneva, Switzerland
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13
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Zeng X, Chen Y, Sehrawat A, Lee J, Lafferty TK, Kofler J, Berman SB, Sweet RA, Tudorascu DL, Klunk WE, Ikonomovic MD, Pfister A, Zetterberg H, Snitz BE, Cohen AD, Villemagne VL, Pascoal TA, Kamboh ML, Lopez OI, Blennow K, Karikari TK. Alzheimer blood biomarkers: practical guidelines for study design, sample collection, processing, biobanking, measurement and result reporting. Mol Neurodegener 2024; 19:40. [PMID: 38750570 PMCID: PMC11095038 DOI: 10.1186/s13024-024-00711-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 02/13/2024] [Indexed: 05/19/2024] Open
Abstract
Alzheimer's disease (AD), the most common form of dementia, remains challenging to understand and treat despite decades of research and clinical investigation. This might be partly due to a lack of widely available and cost-effective modalities for diagnosis and prognosis. Recently, the blood-based AD biomarker field has seen significant progress driven by technological advances, mainly improved analytical sensitivity and precision of the assays and measurement platforms. Several blood-based biomarkers have shown high potential for accurately detecting AD pathophysiology. As a result, there has been considerable interest in applying these biomarkers for diagnosis and prognosis, as surrogate metrics to investigate the impact of various covariates on AD pathophysiology and to accelerate AD therapeutic trials and monitor treatment effects. However, the lack of standardization of how blood samples and collected, processed, stored analyzed and reported can affect the reproducibility of these biomarker measurements, potentially hindering progress toward their widespread use in clinical and research settings. To help address these issues, we provide fundamental guidelines developed according to recent research findings on the impact of sample handling on blood biomarker measurements. These guidelines cover important considerations including study design, blood collection, blood processing, biobanking, biomarker measurement, and result reporting. Furthermore, the proposed guidelines include best practices for appropriate blood handling procedures for genetic and ribonucleic acid analyses. While we focus on the key blood-based AD biomarkers for the AT(N) criteria (e.g., amyloid-beta [Aβ]40, Aβ42, Aβ42/40 ratio, total-tau, phosphorylated-tau, neurofilament light chain, brain-derived tau and glial fibrillary acidic protein), we anticipate that these guidelines will generally be applicable to other types of blood biomarkers. We also anticipate that these guidelines will assist investigators in planning and executing biomarker research, enabling harmonization of sample handling to improve comparability across studies.
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Affiliation(s)
- Xuemei Zeng
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Yijun Chen
- Department of Chemistry, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Anuradha Sehrawat
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Jihui Lee
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Tara K Lafferty
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Julia Kofler
- Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Sarah B Berman
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Robert A Sweet
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Dana L Tudorascu
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - William E Klunk
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Milos D Ikonomovic
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Geriatric Research Education and Clinical Center, VA Pittsburgh HS, Pittsburgh, PA, USA
| | - Anna Pfister
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Beth E Snitz
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Anne D Cohen
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Victor L Villemagne
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Tharick A Pascoal
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - M Llyas Kamboh
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Oscar I Lopez
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Thomas K Karikari
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA.
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden.
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Abukuri DN. Novel Biomarkers for Alzheimer's Disease: Plasma Neurofilament Light and Cerebrospinal Fluid. Int J Alzheimers Dis 2024; 2024:6668159. [PMID: 38779175 PMCID: PMC11111307 DOI: 10.1155/2024/6668159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2023] [Revised: 03/18/2024] [Accepted: 04/24/2024] [Indexed: 05/25/2024] Open
Abstract
Neurodegenerative disorders such as Alzheimer's disease (AD) represent an increasingly significant public health concern. As clinical diagnosis faces challenges, biomarkers are becoming increasingly important in research, trials, and patient assessments. While biomarkers like amyloid-β peptide, tau proteins, CSF levels (Aβ, tau, and p-tau), and neuroimaging techniques are commonly used in AD diagnosis, they are often limited and invasive in monitoring and diagnosis. For this reason, blood-based biomarkers are the optimal choice for detecting neurodegeneration in brain diseases due to their noninvasiveness, affordability, reliability, and consistency. This literature review focuses on plasma neurofilament light (NfL) and CSF NfL as blood-based biomarkers used in recent AD diagnosis. The findings revealed that the core CSF biomarkers of neurodegeneration (T-tau, P-tau, and Aβ42), CSF NFL, and plasma T-tau were strongly associated with Alzheimer's disease, and the core biomarkers were strongly associated with mild cognitive impairment due to Alzheimer's disease. Elevated levels of plasma and cerebrospinal fluid NfL were linked to decreased [18F]FDG uptake in corresponding brain areas. In participants with Aβ positivity (Aβ+), NfL correlated with reduced metabolism in regions susceptible to Alzheimer's disease. In addition, CSF NfL levels correlate with brain atrophy and predict cognitive changes, while plasma total tau does not. Plasma P-tau, especially in combination with Aβ42/Aβ40, is promising for symptomatic AD stages. Though not AD-exclusive, blood NfL holds promise for neurodegeneration detection and assessing treatment efficacy. Given the consistent levels of T-tau, P-tau, Aβ42, and NFL in CSF, their incorporation into both clinical practice and research is highly recommended.
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15
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Mantellatto Grigoli M, Pelegrini LNC, Whelan R, Cominetti MR. Present and Future of Blood-Based Biomarkers of Alzheimer's Disease: Beyond the Classics. Brain Res 2024; 1830:148812. [PMID: 38369085 DOI: 10.1016/j.brainres.2024.148812] [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: 08/12/2023] [Revised: 11/13/2023] [Accepted: 02/13/2024] [Indexed: 02/20/2024]
Abstract
The field of blood-based biomarkers for Alzheimer's disease (AD) has advanced at an incredible pace, especially after the development of sensitive analytic platforms that can facilitate large-scale screening. Such screening will be important when more sophisticated diagnostic methods are scarce and expensive. Thus, blood-based biomarkers can potentially reduce diagnosis inequities among populations from different socioeconomic contexts. This large-scale screening can be performed so that older adults at risk of cognitive decline assessed using these methods can then undergo more complete assessments with classic biomarkers, increasing diagnosis efficiency and reducing costs to the health systems. Blood-based biomarkers can also aid in assessing the effect of new disease-modifying treatments. This paper reviews recent advances in the area, focusing on the following leading candidates for blood-based biomarkers: amyloid-beta (Aβ), phosphorylated tau isoforms (p-tau), neurofilament light (NfL), and glial fibrillary acidic (GFAP) proteins, as well as on new candidates, Neuron-Derived Exosomes contents (NDEs) and Transactive response DNA-binding protein-43 (TDP-43), based on data from longitudinal observational cohort studies. The underlying challenges of validating and incorporating these biomarkers into routine clinical practice and primary care settings are also discussed. Importantly, challenges related to the underrepresentation of ethnic minorities and socioeconomically disadvantaged persons must be considered. If these challenges are overcome, a new time of cost-effective blood-based biomarkers for AD could represent the future of clinical procedures in the field and, together with continued prevention strategies, the beginning of an era with a lower incidence of dementia worldwide.
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Affiliation(s)
| | | | - Robert Whelan
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland; School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Marcia R Cominetti
- Department of Gerontology, Federal University of São Carlos, Brazil; Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland.
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16
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Grasset L, Bouteloup V, Cacciamani F, Pellegrin I, Planche V, Chêne G, Dufouil C. Associations Between Blood-Based Biomarkers and Cognitive and Functional Trajectories Among Participants of the MEMENTO Cohort. Neurology 2024; 102:e209307. [PMID: 38626384 PMCID: PMC11175638 DOI: 10.1212/wnl.0000000000209307] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 02/05/2024] [Indexed: 04/18/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Elevated levels of Alzheimer disease (AD) blood-based biomarkers are associated with accelerated cognitive decline. However, their distinct relationships with specific cognitive and functional domains require further investigation. We aimed at estimating the associations between AD blood-based biomarkers and the trajectories of distinct cognitive and functional domains over a 5-year follow-up period. METHODS We conducted a clinic-based prospective study using data from the MEMENTO study, a nationwide French cohort. We selected dementia-free individuals at baseline aged 60 years or older. Baseline measurements of β-amyloid (Aβ) 40 and 42, phosphorylated tau (p-tau181), and neurofilament light chain (NfL) concentrations were obtained using the Simoa HD-X analyzer. Mini-Mental State Examination (MMSE), Free and Cued Selective Reminding Test (FCSRT), animal fluency, Trail Making Tests A and B, Short Physical Performance Battery (SPPB), and Instrumental Activities of Daily Living were administered annually for up to 5 years. We used linear mixed models, adjusted for potential confounders, to model AD biomarkers' relation with cognitive and functional decline. RESULTS A total of 1,938 participants were included in this study, with a mean (SD) baseline age of 72.8 (6.6) years, and 62% were women. Higher baseline p-tau181 and NfL were associated with significantly faster decline in most cognitive, physical, and functional outcomes (+1 SD p-tau181: βMMSE = -0.055, 95% CI -0.067 to -0.043, βFCSRT = -0.034, 95% CI -0.043 to -0.025, βfluency = -0.029, 95% CI -0.038 to -0.020, βSPPB = -0.040, 95% CI -0.057 to -0.022, and β4IADL = -0.115, 95% CI 0.091-0.140. +1 SD NfL: βMMSE = -0.039, 95% CI -0.053 to -0.025, βFCSRT = -0.022, 95% CI -0.032 to -0.012, βfluency = -0.014, 95% CI -0.024 to -0.004, and β4IADL = 0.077, 95% CI 0.048-0.105). A multiplicative association of p-tau181 and NfL with worsening cognitive and functional trajectories was evidenced. Lower Aβ42/40 ratio was only associated with slightly faster cognitive decline in FCSRT and semantic fluency (+1 SD: β = 0.011, 95% CI 0.002-0.020, and β = 0.011, 95% CI 0.003-0.020, respectively). These associations were not modified by APOE ε4, sex, nor education level. DISCUSSION In a memory clinic sample, p-tau181 and NfL, both independently and jointly, are linked to more pronounced cognitive, physical and functional declines. Blood-based biomarker measurement in AD research may provide useful insights regarding biological processes underlying cognitive, physical, and functional declines in at-risk individuals.
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Affiliation(s)
- Leslie Grasset
- From the UMR 1219 (L.G., V.B., F.C., G.C., C.D.), Bordeaux Population Health Center, University of Bordeaux, Inserm; CIC 1401-EC (L.G., V.B., F.C., G.C., C.D.), Inserm, University of Bordeaux, CHU de Bordeaux; Centre Hospitalier Universitaire (CHU) de Bordeaux (V.B., G.C., C.D.), Pole de sante publique; ARAMISLab (F.C.), Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière; Qairnel SAS (F.C.), Paris; Laboratory of Immunology and Immunogenetics (I.P.), Resources Biological Center (CRB), CHU Bordeaux; Univ. Bordeaux (I.P.), CNRS, ImmunoConcEpT, UMR 5164; and Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives, Centre Mémoire de Ressources et de Recherches, Pôle de Neurosciences Cliniques, CHU de Bordeaux, France
| | - Vincent Bouteloup
- From the UMR 1219 (L.G., V.B., F.C., G.C., C.D.), Bordeaux Population Health Center, University of Bordeaux, Inserm; CIC 1401-EC (L.G., V.B., F.C., G.C., C.D.), Inserm, University of Bordeaux, CHU de Bordeaux; Centre Hospitalier Universitaire (CHU) de Bordeaux (V.B., G.C., C.D.), Pole de sante publique; ARAMISLab (F.C.), Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière; Qairnel SAS (F.C.), Paris; Laboratory of Immunology and Immunogenetics (I.P.), Resources Biological Center (CRB), CHU Bordeaux; Univ. Bordeaux (I.P.), CNRS, ImmunoConcEpT, UMR 5164; and Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives, Centre Mémoire de Ressources et de Recherches, Pôle de Neurosciences Cliniques, CHU de Bordeaux, France
| | - Federica Cacciamani
- From the UMR 1219 (L.G., V.B., F.C., G.C., C.D.), Bordeaux Population Health Center, University of Bordeaux, Inserm; CIC 1401-EC (L.G., V.B., F.C., G.C., C.D.), Inserm, University of Bordeaux, CHU de Bordeaux; Centre Hospitalier Universitaire (CHU) de Bordeaux (V.B., G.C., C.D.), Pole de sante publique; ARAMISLab (F.C.), Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière; Qairnel SAS (F.C.), Paris; Laboratory of Immunology and Immunogenetics (I.P.), Resources Biological Center (CRB), CHU Bordeaux; Univ. Bordeaux (I.P.), CNRS, ImmunoConcEpT, UMR 5164; and Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives, Centre Mémoire de Ressources et de Recherches, Pôle de Neurosciences Cliniques, CHU de Bordeaux, France
| | - Isabelle Pellegrin
- From the UMR 1219 (L.G., V.B., F.C., G.C., C.D.), Bordeaux Population Health Center, University of Bordeaux, Inserm; CIC 1401-EC (L.G., V.B., F.C., G.C., C.D.), Inserm, University of Bordeaux, CHU de Bordeaux; Centre Hospitalier Universitaire (CHU) de Bordeaux (V.B., G.C., C.D.), Pole de sante publique; ARAMISLab (F.C.), Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière; Qairnel SAS (F.C.), Paris; Laboratory of Immunology and Immunogenetics (I.P.), Resources Biological Center (CRB), CHU Bordeaux; Univ. Bordeaux (I.P.), CNRS, ImmunoConcEpT, UMR 5164; and Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives, Centre Mémoire de Ressources et de Recherches, Pôle de Neurosciences Cliniques, CHU de Bordeaux, France
| | - Vincent Planche
- From the UMR 1219 (L.G., V.B., F.C., G.C., C.D.), Bordeaux Population Health Center, University of Bordeaux, Inserm; CIC 1401-EC (L.G., V.B., F.C., G.C., C.D.), Inserm, University of Bordeaux, CHU de Bordeaux; Centre Hospitalier Universitaire (CHU) de Bordeaux (V.B., G.C., C.D.), Pole de sante publique; ARAMISLab (F.C.), Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière; Qairnel SAS (F.C.), Paris; Laboratory of Immunology and Immunogenetics (I.P.), Resources Biological Center (CRB), CHU Bordeaux; Univ. Bordeaux (I.P.), CNRS, ImmunoConcEpT, UMR 5164; and Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives, Centre Mémoire de Ressources et de Recherches, Pôle de Neurosciences Cliniques, CHU de Bordeaux, France
| | - Geneviève Chêne
- From the UMR 1219 (L.G., V.B., F.C., G.C., C.D.), Bordeaux Population Health Center, University of Bordeaux, Inserm; CIC 1401-EC (L.G., V.B., F.C., G.C., C.D.), Inserm, University of Bordeaux, CHU de Bordeaux; Centre Hospitalier Universitaire (CHU) de Bordeaux (V.B., G.C., C.D.), Pole de sante publique; ARAMISLab (F.C.), Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière; Qairnel SAS (F.C.), Paris; Laboratory of Immunology and Immunogenetics (I.P.), Resources Biological Center (CRB), CHU Bordeaux; Univ. Bordeaux (I.P.), CNRS, ImmunoConcEpT, UMR 5164; and Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives, Centre Mémoire de Ressources et de Recherches, Pôle de Neurosciences Cliniques, CHU de Bordeaux, France
| | - Carole Dufouil
- From the UMR 1219 (L.G., V.B., F.C., G.C., C.D.), Bordeaux Population Health Center, University of Bordeaux, Inserm; CIC 1401-EC (L.G., V.B., F.C., G.C., C.D.), Inserm, University of Bordeaux, CHU de Bordeaux; Centre Hospitalier Universitaire (CHU) de Bordeaux (V.B., G.C., C.D.), Pole de sante publique; ARAMISLab (F.C.), Sorbonne Université, Institut du Cerveau-Paris Brain Institute-ICM, CNRS, Inria, Inserm, AP-HP, Hôpital de la Pitié Salpêtrière; Qairnel SAS (F.C.), Paris; Laboratory of Immunology and Immunogenetics (I.P.), Resources Biological Center (CRB), CHU Bordeaux; Univ. Bordeaux (I.P.), CNRS, ImmunoConcEpT, UMR 5164; and Univ. Bordeaux (V.P.), CNRS UMR 5293, Institut des Maladies Neurodégénératives, Centre Mémoire de Ressources et de Recherches, Pôle de Neurosciences Cliniques, CHU de Bordeaux, France
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Dark HE, Duggan MR, Walker KA. Plasma biomarkers for Alzheimer's and related dementias: A review and outlook for clinical neuropsychology. Arch Clin Neuropsychol 2024; 39:313-324. [PMID: 38520383 DOI: 10.1093/arclin/acae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 02/05/2024] [Indexed: 03/25/2024] Open
Abstract
Recent technological advances have improved the sensitivity and specificity of blood-based biomarkers for Alzheimer's disease and related dementias. Accurate quantification of amyloid-ß peptide, phosphorylated tau (pTau) isoforms, as well as markers of neurodegeneration (neurofilament light chain [NfL]) and neuro-immune activation (glial fibrillary acidic protein [GFAP] and chitinase-3-like protein 1 [YKL-40]) in blood has allowed researchers to characterize neurobiological processes at scale in a cost-effective and minimally invasive manner. Although currently used primarily for research purposes, these blood-based biomarkers have the potential to be highly impactful in the clinical setting - aiding in diagnosis, predicting disease risk, and monitoring disease progression. Whereas plasma NfL has shown promise as a non-specific marker of neuronal injury, plasma pTau181, pTau217, pTau231, and GFAP have demonstrated desirable levels of sensitivity and specificity for identification of individuals with Alzheimer's disease pathology and Alzheimer's dementia. In this forward looking review, we (i) provide an overview of the most commonly used blood-based biomarkers for Alzheimer's disease and related dementias, (ii) discuss how comorbid medical conditions, demographic, and genetic factors can inform the interpretation of these biomarkers, (iii) describe ongoing efforts to move blood-based biomarkers into the clinic, and (iv) highlight the central role that clinical neuropsychologists may play in contextualizing and communicating blood-based biomarker results for patients.
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Affiliation(s)
- Heather E Dark
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
| | - Michael R Duggan
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
| | - Keenan A Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
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18
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Delaby C, Lehmann S. [On the road to biological blood diagnosis of Alzheimer's disease?]. Med Sci (Paris) 2024; 40:351-360. [PMID: 38651960 DOI: 10.1051/medsci/2024037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2024] Open
Abstract
The growing number of people suffering from Alzheimer's disease (AD) represents a major public health problem. The diagnosis of AD is multidisciplinary and involves the use of amyloid and tau biomarkers measured in cerebrospinal fluid. Recent advances in analytical techniques now allow us to measure these biomarkers in blood. Blood biomarkers offer particularly promising potential for early, minimally invasive detection of AD, as well as for differential diagnosis of dementia and patient follow-up. The aim of this review is to provide an overview of current and candidate blood biomarkers for AD, their informative value, and their potential to be integrated into clinical practice in the near future.
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Affiliation(s)
- Constance Delaby
- LBPC-PPC, Université Montpellier, CHU Montpellier, INM Inserm U1298, Montpellier, France - Hospital de la Santa Creu i Sant Pau - Biomedical Research Institute Sant Pau - Universitat Autònoma de Barcelona, Barcelone, Espagne
| | - Sylvain Lehmann
- LBPC-PPC, Université Montpellier, CHU Montpellier, INM Inserm U1298, Montpellier, France
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19
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Schworer EK, Handen BL, Petersen M, O'Bryant S, Peven JC, Tudorascu DL, Lee L, Krinsky‐McHale SJ, Hom CL, Clare ICH, Christian BT, Schupf N, Lee JH, Head E, Mapstone M, Lott I, Ances BM, Zaman S, Brickman AM, Lai F, Rosas HD, Hartley SL. Cognitive and functional performance and plasma biomarkers of early Alzheimer's disease in Down syndrome. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12582. [PMID: 38623384 PMCID: PMC11016818 DOI: 10.1002/dad2.12582] [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: 05/12/2023] [Revised: 02/23/2024] [Accepted: 03/01/2024] [Indexed: 04/17/2024]
Abstract
INTRODUCTION People with Down syndrome (DS) have a 75% to 90% lifetime risk of Alzheimer's disease (AD). AD pathology begins a decade or more prior to onset of clinical AD dementia in people with DS. It is not clear if plasma biomarkers of AD pathology are correlated with early cognitive and functional impairments in DS, and if these biomarkers could be used to track the early stages of AD in DS or to inform inclusion criteria for clinical AD treatment trials. METHODS This large cross-sectional cohort study investigated the associations between plasma biomarkers of amyloid beta (Aβ)42/40, total tau, and neurofilament light chain (NfL) and cognitive (episodic memory, visual-motor integration, and visuospatial abilities) and functional (adaptive behavior) impairments in 260 adults with DS without dementia (aged 25-81 years). RESULTS In general linear models lower plasma Aβ42/40 was related to lower visuospatial ability, higher total tau was related to lower episodic memory, and higher NfL was related to lower visuospatial ability and lower episodic memory. DISCUSSION Plasma biomarkers may have utility in tracking AD pathology associated with early stages of cognitive decline in adults with DS, although associations were modest. Highlights Plasma Alzheimer's disease (AD) biomarkers correlate with cognition prior to dementia in Down syndrome.Lower plasma amyloid beta 42/40 was related to lower visuospatial abilities.Higher plasma total tau and neurofilament light chain were associated with lower cognitive performance.Plasma biomarkers show potential for tracking early stages of AD symptomology.
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Affiliation(s)
| | - Benjamin L. Handen
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Melissa Petersen
- Department of Family Medicine and Institute for Translational ResearchUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Sid O'Bryant
- Department of Family Medicine and Institute for Translational ResearchUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Jamie C. Peven
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Dana L. Tudorascu
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Laisze Lee
- Department of PsychiatryUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Sharon J. Krinsky‐McHale
- New York State Institute for Basic Research in Developmental DisabilitiesStaten IslandNew YorkUSA
| | - Christy L. Hom
- Department of Psychiatry and Human BehaviorUniversity of CaliforniaIrvineCaliforniaUSA
| | | | | | - Nicole Schupf
- Taub Institute for Research on Alzheimer's Disease and the Aging BrainSergievsky Centerand Department of NeurologyVagelos College of Physicians and SurgeonsColumbia UniversityNew YorkNew YorkUSA
| | - Joseph H. Lee
- Taub Institute for Research on Alzheimer's Disease and the Aging BrainSergievsky Centerand Department of NeurologyVagelos College of Physicians and SurgeonsColumbia UniversityNew YorkNew YorkUSA
| | - Elizabeth Head
- Department of Pathology & Laboratory MedicineUniversity of CaliforniaIrvine School of MedicineIrvineCaliforniaUSA
| | - Mark Mapstone
- Department of NeurologyUniversity of CaliforniaIrvine School of MedicineIrvineCaliforniaUSA
| | - Ira Lott
- Department of NeurologyUniversity of CaliforniaIrvine School of MedicineIrvineCaliforniaUSA
| | - Beau M. Ances
- Department of NeurologyWashington University at St. LouisSt. LouisMissouriUSA
| | - Shahid Zaman
- Department of PsychiatryUniversity of CambridgeCambridgeUK
| | - Adam M. Brickman
- Taub Institute for Research on Alzheimer's Disease and the Aging BrainSergievsky Centerand Department of NeurologyVagelos College of Physicians and SurgeonsColumbia UniversityNew YorkNew YorkUSA
| | - Florence Lai
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - H. Diana Rosas
- Department of NeurologyMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
- Center for Neuro‐imaging of Aging and Neurodegenerative DiseasesMassachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Sigan L. Hartley
- Waisman CenterUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
- School of Human EcologyUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
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20
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Lista S, Mapstone M, Caraci F, Emanuele E, López-Ortiz S, Martín-Hernández J, Triaca V, Imbimbo C, Gabelle A, Mielke MM, Nisticò R, Santos-Lozano A, Imbimbo BP. A critical appraisal of blood-based biomarkers for Alzheimer's disease. Ageing Res Rev 2024; 96:102290. [PMID: 38580173 DOI: 10.1016/j.arr.2024.102290] [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: 11/13/2023] [Revised: 03/18/2024] [Accepted: 03/31/2024] [Indexed: 04/07/2024]
Abstract
Biomarkers that predict the clinical onset of Alzheimer's disease (AD) enable the identification of individuals in the early, preclinical stages of the disease. Detecting AD at this point may allow for more effective therapeutic interventions and optimized enrollment for clinical trials of novel drugs. The current biological diagnosis of AD is based on the AT(N) classification system with the measurement of brain deposition of amyloid-β (Aβ) ("A"), tau pathology ("T"), and neurodegeneration ("N"). Diagnostic cut-offs for Aβ1-42, the Aβ1-42/Aβ1-40 ratio, tau and hyperphosphorylated-tau concentrations in cerebrospinal fluid have been defined and may support AD clinical diagnosis. Blood-based biomarkers of the AT(N) categories have been described in the AD continuum. Cross-sectional and longitudinal studies have shown that the combination of blood biomarkers tracking neuroaxonal injury (neurofilament light chain) and neuroinflammatory pathways (glial fibrillary acidic protein) enhance sensitivity and specificity of AD clinical diagnosis and improve the prediction of AD onset. However, no international accepted cut-offs have been identified for these blood biomarkers. A kit for blood Aβ1-42/Aβ1-40 is commercially available in the U.S.; however, it does not provide a diagnosis, but simply estimates the risk of developing AD. Although blood-based AD biomarkers have a great potential in the diagnostic work-up of AD, they are not ready for the routine clinical use.
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Affiliation(s)
- Simone Lista
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid 47012, Spain.
| | - Mark Mapstone
- Department of Neurology, Institute for Memory Impairments and Neurological Disorders, University of California, Irvine, Irvine, CA 92697, USA.
| | - Filippo Caraci
- Department of Drug and Health Sciences, University of Catania, Catania 95125, Italy; Neuropharmacology and Translational Neurosciences Research Unit, Oasi Research Institute-IRCCS, Troina 94018, Italy.
| | | | - Susana López-Ortiz
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid 47012, Spain.
| | - Juan Martín-Hernández
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid 47012, Spain.
| | - Viviana Triaca
- Institute of Biochemistry and Cell Biology (IBBC), National Research Council (CNR), Rome 00015, Italy.
| | - Camillo Imbimbo
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia 27100, Italy.
| | - Audrey Gabelle
- Memory Resources and Research Center, Montpellier University of Excellence i-site, Montpellier 34295, France.
| | - Michelle M Mielke
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA.
| | - Robert Nisticò
- School of Pharmacy, University of Rome "Tor Vergata", Rome 00133, Italy; Laboratory of Pharmacology of Synaptic Plasticity, EBRI Rita Levi-Montalcini Foundation, Rome 00143, Italy.
| | - Alejandro Santos-Lozano
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), Valladolid 47012, Spain; Physical Activity and Health Research Group (PaHerg), Research Institute of the Hospital 12 de Octubre ('imas12'), Madrid 28041, Spain.
| | - Bruno P Imbimbo
- Department of Research and Development, Chiesi Farmaceutici, Parma 43122, Italy.
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Abbatecola AM, Giuliani A, Biscetti L, Scisciola L, Battista P, Barbieri M, Sabbatinelli J, Olivieri F. Circulating biomarkers of inflammaging and Alzheimer's disease to track age-related trajectories of dementia: Can we develop a clinically relevant composite combination? Ageing Res Rev 2024; 96:102257. [PMID: 38437884 DOI: 10.1016/j.arr.2024.102257] [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: 11/08/2023] [Revised: 02/27/2024] [Accepted: 02/29/2024] [Indexed: 03/06/2024]
Abstract
Alzheimer's disease (AD) is a rapidly growing global concern due to a consistent rise of the prevalence of dementia which is mainly caused by the aging population worldwide. An early diagnosis of AD remains important as interventions are plausibly more effective when started at the earliest stages. Recent developments in clinical research have focused on the use of blood-based biomarkers for improve diagnosis/prognosis of neurodegenerative diseases, particularly AD. Unlike invasive cerebrospinal fluid tests, circulating biomarkers are less invasive and will become increasingly cheaper and simple to use in larger number of patients with mild symptoms or at risk of dementia. In addition to AD-specific markers, there is growing interest in biomarkers of inflammaging/neuro-inflammaging, an age-related chronic low-grade inflammatory condition increasingly recognized as one of the main risk factor for almost all age-related diseases, including AD. Several inflammatory markers have been associated with cognitive performance and AD development and progression. The presence of senescent cells, a key driver of inflammaging, has also been linked to AD pathogenesis, and senolytic therapy is emerging as a potential treatment strategy. Here, we describe blood-based biomarkers clinically relevant for AD diagnosis/prognosis and biomarkers of inflammaging associated with AD. Through a systematic review approach, we propose that a combination of circulating neurodegeneration and inflammatory biomarkers may contribute to improving early diagnosis and prognosis, as well as providing valuable insights into the trajectory of cognitive decline and dementia in the aging population.
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Affiliation(s)
- Angela Marie Abbatecola
- Alzheimer's Disease Day Clinic, Azienda Sanitaria Locale, Frosinone, Italy; Univesità degli Studi di Cassino e del Lazio Meridionale, Dipartimento di Scienze Umane, Sociali e della Salute, Cassino, Italy
| | - Angelica Giuliani
- Istituti Clinici Scientifici Maugeri IRCCS, Cardiac Rehabilitation Unit of Bari Institute, Italy.
| | | | - Lucia Scisciola
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Petronilla Battista
- Istituti Clinici Scientifici Maugeri IRCCS, Laboratory of Neuropsychology, Bari Institute, Italy
| | - Michelangela Barbieri
- Department of Advanced Medical and Surgical Sciences, University of Campania "Luigi Vanvitelli", Naples, Italy
| | - Jacopo Sabbatinelli
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Ancona, Italy; Clinic of Laboratory and Precision Medicine, IRCCS INRCA, Ancona, Italy
| | - Fabiola Olivieri
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica delle Marche, Ancona, Italy; Clinic of Laboratory and Precision Medicine, IRCCS INRCA, Ancona, Italy
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Sewell KR, Rainey-Smith SR, Pedrini S, Peiffer JJ, Sohrabi HR, Taddei K, Markovic SJ, Martins RN, Brown BM. The impact of exercise on blood-based biomarkers of Alzheimer's disease in cognitively unimpaired older adults. GeroScience 2024:10.1007/s11357-024-01130-2. [PMID: 38488949 DOI: 10.1007/s11357-024-01130-2] [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: 01/11/2024] [Accepted: 03/08/2024] [Indexed: 03/17/2024] Open
Abstract
Physical activity is a promising preventative strategy for Alzheimer's disease: it is associated with lower dementia risk, better cognition, greater brain volume and lower brain beta-amyloid. Blood-based biomarkers have emerged as a low-cost, non-invasive strategy for detecting preclinical Alzheimer's disease, however, there is limited literature examining the effect of exercise (a structured form of physical activity) on blood-based biomarkers. The current study investigated the influence of a 6-month exercise intervention on levels of plasma beta-amyloid (Aβ42, Aβ40, Aβ42/40), phosphorylated tau (p-tau181), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) chain in cognitively unimpaired older adults, and as a secondary aim, whether blood-based biomarkers related to cognition. Ninety-nine community-dwelling older adults (69.1 ± 5.2) were allocated to an inactive control, or to moderate or high intensity exercise groups where they cycled twice weekly for six months. At baseline and six months (post-intervention), fasted blood was collected and analysed using single molecule array (SIMOA) assays, and cognition was assessed. Results demonstrated no change in levels of any plasma biomarker from pre- to post-intervention. At baseline, higher NfL was associated with poorer cognition (β = -0.33, SE = 0.13, adjusted p = .042). Exploratory analyses indicated higher cardiorespiratory fitness was associated with higher NfL and GFAP levels in apolipoprotein E (APOE) ε4 non-carriers compared to ε4 carriers (NfL, β = -0.43, SE = 0.19, p = .029; GFAP, β = -0.41, SE = 0.20, p = .044), though this association was mediated by body mass index (BMI). These results highlight the importance of considering BMI in analysis of blood-based biomarkers, especially when investigating differences between APOE ε4 carriers and non-carriers. Our results also indicate that longer follow-up periods may be required to observe exercise-induced change in blood-based biomarkers.
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Affiliation(s)
- Kelsey R Sewell
- Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Murdoch, WA, Australia.
| | - Stephanie R Rainey-Smith
- Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Murdoch, WA, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, WA, Australia
- School of Psychological Science, University of Western Australia, Crawley, WA, Australia
| | - Steve Pedrini
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, WA, Australia
| | - Jeremiah J Peiffer
- Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Murdoch, WA, Australia
| | - Hamid R Sohrabi
- Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Murdoch, WA, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, WA, Australia
- Department of Biomedical Sciences, Macquarie University, North Ryde, New South Wales, Australia
| | - Kevin Taddei
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, WA, Australia
| | - Shaun J Markovic
- Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Murdoch, WA, Australia
- Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, WA, Australia
| | - Ralph N Martins
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, WA, Australia
- Department of Biomedical Sciences, Macquarie University, North Ryde, New South Wales, Australia
| | - Belinda M Brown
- Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Murdoch, WA, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, WA, Australia
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23
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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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24
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Tarawneh R. YKL-40 as a New Plasma Biomarker for Dementia Risk: Are We There Yet? Neurology 2024; 102:e209145. [PMID: 38546014 DOI: 10.1212/wnl.0000000000209145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2023] [Accepted: 11/16/2023] [Indexed: 05/09/2024] Open
Affiliation(s)
- Rawan Tarawneh
- From the Department of Neurology, University of New Mexico, Albuquerque
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25
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Koike R, Soeda Y, Kasai A, Fujioka Y, Ishigaki S, Yamanaka A, Takaichi Y, Chambers JK, Uchida K, Watanabe H, Takashima A. Path integration deficits are associated with phosphorylated tau accumulation in the entorhinal cortex. Brain Commun 2024; 6:fcad359. [PMID: 38347945 PMCID: PMC10859636 DOI: 10.1093/braincomms/fcad359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2023] [Revised: 11/14/2023] [Accepted: 01/04/2024] [Indexed: 02/15/2024] Open
Abstract
Alzheimer's disease is a devastating disease that is accompanied by dementia, and its incidence increases with age. However, no interventions have exhibited clear therapeutic effects. We aimed to develop and characterize behavioural tasks that allow the earlier identification of signs preceding dementia that would facilitate the development of preventative and therapeutic interventions for Alzheimer's disease. To this end, we developed a 3D virtual reality task sensitive to the activity of grid cells in the entorhinal cortex, which is the region that first exhibits neurofibrillary tangles in Alzheimer's disease. We investigated path integration (assessed by error distance) in a spatial navigation task sensitive to grid cells in the entorhinal cortex in 177 volunteers, aged 20-89 years, who did not have self-reported dementia. While place memory was intact even in old age, path integration deteriorated with increasing age. To investigate the relationship between neurofibrillary tangles in the entorhinal cortex and path integration deficit, we examined a mouse model of tauopathy (P301S mutant tau-overexpressing mice; PS19 mice). At 6 months of age, PS19 mice showed a significant accumulation of phosphorylated tau only in the entorhinal cortex, associated with impaired path integration without impairments in spatial cognition. These data are consistent with the idea that path integration deficit is caused by the accumulation of phosphorylated tau in the entorhinal cortex. This method may allow the early identification of individuals likely to develop Alzheimer's disease.
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Affiliation(s)
- Riki Koike
- Laboratory for Alzheimer’s Disease, Department of Life Science, Faculty of Science, Gakushuin University, Toshima-ku, Tokyo 171-8588, Japan
| | - Yoshiyuki Soeda
- Laboratory for Alzheimer’s Disease, Department of Life Science, Faculty of Science, Gakushuin University, Toshima-ku, Tokyo 171-8588, Japan
| | - Atsushi Kasai
- Deapartment of Research and Development, MIG (Medical Innovation Group) Inc, Shibuya, Tokyo 150-0031, Japan
| | - Yusuke Fujioka
- Molecular Neuroscience Research Center, Shiga University of Medical Science, Otsu, Shiga 520-2192, Japan
| | - Shinsuke Ishigaki
- Molecular Neuroscience Research Center, Shiga University of Medical Science, Otsu, Shiga 520-2192, Japan
| | - Akihiro Yamanaka
- Department of Neuroscience II, Research Institute of Environmental Medicine, Nagoya University, Nagoya, Aichi 464-8601, Japan
| | - Yuta Takaichi
- Laboratory of Veterinary Pathology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Bunkyo-ku, Tokyo 113-8657, Japan
| | - James K Chambers
- Laboratory of Veterinary Pathology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Bunkyo-ku, Tokyo 113-8657, Japan
| | - Kazuyuki Uchida
- Laboratory of Veterinary Pathology, Graduate School of Agricultural and Life Sciences, The University of Tokyo, Bunkyo-ku, Tokyo 113-8657, Japan
| | - Hirohisa Watanabe
- Department of Neurology, Fujita Health University, Toyoake, Aichi 470-1192, Japan
| | - Akihiko Takashima
- Laboratory for Alzheimer’s Disease, Department of Life Science, Faculty of Science, Gakushuin University, Toshima-ku, Tokyo 171-8588, Japan
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26
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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: 2] [Impact Index Per Article: 2.0] [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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27
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Muir RT, Ismail Z, Black SE, Smith EE. Comparative methods for quantifying plasma biomarkers in Alzheimer's disease: Implications for the next frontier in cerebral amyloid angiopathy diagnostics. Alzheimers Dement 2024; 20:1436-1458. [PMID: 37908054 PMCID: PMC10916950 DOI: 10.1002/alz.13510] [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: 03/12/2023] [Revised: 08/09/2023] [Accepted: 08/13/2023] [Indexed: 11/02/2023]
Abstract
Plasma amyloid beta (Aβ) and tau are emerging as accessible biomarkers for Alzheimer's disease (AD). However, many assays exist with variable test performances, highlighting the need for a comparative assessment to identify the most valid assays for future use in AD and to apply to other settings in which the same biomarkers may be useful, namely, cerebral amyloid angiopathy (CAA). CAA is a progressive cerebrovascular disease characterized by deposition of Aβ40 and Aβ42 in cortical and leptomeningeal vessels. Novel immunotherapies for AD can induce amyloid-related imaging abnormalities resembling CAA-related inflammation. Few studies have evaluated plasma biomarkers in CAA. Identifying a CAA signature could facilitate diagnosis, prognosis, and a safer selection of patients with AD for emerging immunotherapies. This review evaluates studies that compare the diagnostic test performance of plasma biomarker techniques in AD and cerebrovascular and plasma biomarker profiles of CAA; it also discusses novel hypotheses and future avenues for plasma biomarker research in CAA.
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Affiliation(s)
- Ryan T. Muir
- Calgary Stroke ProgramDepartment of Clinical NeurosciencesUniversity of CalgaryCalgaryAlbertaCanada
- Department of Community Health SciencesUniversity of CalgaryCalgaryAlbertaCanada
- Hotchkiss Brain InstituteUniversity of CalgaryCalgaryAlbertaCanada
| | - Zahinoor Ismail
- Department of Community Health SciencesUniversity of CalgaryCalgaryAlbertaCanada
- Hotchkiss Brain InstituteUniversity of CalgaryCalgaryAlbertaCanada
- Department of PsychiatryUniversity of CalgaryCalgaryAlbertaCanada
| | - Sandra E. Black
- Division of NeurologyDepartment of MedicineSunnybrook Health Sciences CentreTorontoOntarioCanada
- LC Campbell Cognitive Neurology Research UnitDr Sandra Black Centre for Brain Resilience and Recovery, and Hurvitz Brain Sciences ProgramSunnybrook Research InstituteUniversity of TorontoTorontoOntarioCanada
| | - Eric E. Smith
- Calgary Stroke ProgramDepartment of Clinical NeurosciencesUniversity of CalgaryCalgaryAlbertaCanada
- Department of Community Health SciencesUniversity of CalgaryCalgaryAlbertaCanada
- Hotchkiss Brain InstituteUniversity of CalgaryCalgaryAlbertaCanada
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28
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Guo Y, You J, Zhang Y, Liu WS, Huang YY, Zhang YR, Zhang W, Dong Q, Feng JF, Cheng W, Yu JT. Plasma proteomic profiles predict future dementia in healthy adults. NATURE AGING 2024; 4:247-260. [PMID: 38347190 DOI: 10.1038/s43587-023-00565-0] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Accepted: 12/22/2023] [Indexed: 02/22/2024]
Abstract
The advent of proteomics offers an unprecedented opportunity to predict dementia onset. We examined this in data from 52,645 adults without dementia in the UK Biobank, with 1,417 incident cases and a follow-up time of 14.1 years. Of 1,463 plasma proteins, GFAP, NEFL, GDF15 and LTBP2 consistently associated most with incident all-cause dementia (ACD), Alzheimer's disease (AD) and vascular dementia (VaD), and ranked high in protein importance ordering. Combining GFAP (or GDF15) with demographics produced desirable predictions for ACD (area under the curve (AUC) = 0.891) and AD (AUC = 0.872) (or VaD (AUC = 0.912)). This was also true when predicting over 10-year ACD, AD and VaD. Individuals with higher GFAP levels were 2.32 times more likely to develop dementia. Notably, GFAP and LTBP2 were highly specific for dementia prediction. GFAP and NEFL began to change at least 10 years before dementia diagnosis. Our findings strongly highlight GFAP as an optimal biomarker for dementia prediction, even more than 10 years before the diagnosis, with implications for screening people at high risk for dementia and for early intervention.
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Affiliation(s)
- Yu Guo
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jia You
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
| | - Yi Zhang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wei-Shi Liu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Yu-Yuan Huang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ya-Ru Zhang
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wei Zhang
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China
| | - Qiang Dong
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jian-Feng Feng
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
| | - Wei Cheng
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
- Institute of Science and Technology for Brain-inspired Intelligence, Fudan University, Shanghai, China.
- Key Laboratory of Computational Neuroscience and Brain-inspired Intelligence, Fudan University, Ministry of Education, Shanghai, China.
| | - Jin-Tai Yu
- Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
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29
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van Arendonk J, Wolters FJ, Neitzel J, Vinke EJ, Vernooij MW, Ghanbari M, Ikram MA. Plasma neurofilament light chain in relation to 10-year change in cognition and neuroimaging markers: a population-based study. GeroScience 2024; 46:57-70. [PMID: 37535203 PMCID: PMC10828339 DOI: 10.1007/s11357-023-00876-5] [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: 03/04/2022] [Accepted: 07/10/2023] [Indexed: 08/04/2023] Open
Abstract
Neurofilament light chain (NfL) is a promising biomarker for risk stratification and disease monitoring of dementia, but its utility in the preclinical disease stage remains uncertain. We determined the association of plasma NfL with (change in) neuroimaging markers and cognition in the population-based Rotterdam Study, using linear and logistic regression and mixed-effects models. Plasma NfL levels were measured using the Simoa NF-light™ assay in 4705 dementia-free participants (mean age 71.9 years, 57% women), who underwent cognitive assessment and brain MRI with repeated assessments over a 10-year follow-up period. Higher plasma NfL was associated with worse cognitive performance at baseline (g-factor: β = - 0.12 (- 0.15; - 0.09), p < 0.001), and accelerated cognitive decline during follow-up on the Stroop color naming task (β = 0.04 (0.02; 0.06), p < 0.001), with a smaller trend for decline in global cognition (g-factor β = - 0.02 (- 0.04; 0.00), p = 0.044). In the subset of 975 participants with brain MRI, higher NfL was associated with poorer baseline white matter integrity (e.g., global mean diffusivity: β = 0.12 (0.06; 0.19), p < 0.001), with similar trends for volume of white matter hyperintensities (β = 0.09 (0.02; 0.16), p = 0.011) and presence of lacunes (OR = 1.55 (1.13; 2.14), p = 0.007). Plasma NfL was not associated with volumes or thickness of the total gray matter, hippocampus, or Alzheimer signature regions. In conclusion, higher plasma NfL levels are associated with cognitive decline and larger burden of primarily white matter pathology in the general population.
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Affiliation(s)
- Joyce van Arendonk
- Department of Radiology and Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC-University Medical Center Rotterdam, PO Box 2040, Rotterdam, 3000 CA, the Netherlands
| | - Frank J Wolters
- Department of Radiology and Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC-University Medical Center Rotterdam, PO Box 2040, Rotterdam, 3000 CA, the Netherlands
| | - Julia Neitzel
- Department of Radiology and Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC-University Medical Center Rotterdam, PO Box 2040, Rotterdam, 3000 CA, the Netherlands
- Department of Epidemiology, Harvard T.H Chan School of Public Health, Boston, MA, USA
| | - Elisabeth J Vinke
- Department of Radiology and Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC-University Medical Center Rotterdam, PO Box 2040, Rotterdam, 3000 CA, the Netherlands
| | - Meike W Vernooij
- Department of Radiology and Nuclear Medicine, Erasmus MC-University Medical Center Rotterdam, Rotterdam, the Netherlands
- Department of Epidemiology, Erasmus MC-University Medical Center Rotterdam, PO Box 2040, Rotterdam, 3000 CA, the Netherlands
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus MC-University Medical Center Rotterdam, PO Box 2040, Rotterdam, 3000 CA, the Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus MC-University Medical Center Rotterdam, PO Box 2040, Rotterdam, 3000 CA, the Netherlands.
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30
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Cheng YW, Lin YJ, Lin YS, Hong WP, Kuan YC, Wu KY, Hsu JL, Wang PN, Pai MC, Chen CS, Fuh JL, Hu CJ, Chiu MJ. Application of blood-based biomarkers of Alzheimer's disease in clinical practice: Recommendations from Taiwan Dementia Society. J Formos Med Assoc 2024:S0929-6646(24)00051-2. [PMID: 38296698 DOI: 10.1016/j.jfma.2024.01.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 11/29/2023] [Accepted: 01/14/2024] [Indexed: 02/02/2024] Open
Abstract
Blood-based biomarkers (BBM) are potentially powerful tools that assist in the biological diagnosis of Alzheimer's disease (AD) in vivo with minimal invasiveness, relatively low cost, and good accessibility. This review summarizes current evidence for using BBMs in AD, focusing on amyloid, tau, and biomarkers for neurodegeneration. Blood-based phosphorylated tau and the Aβ42/Aβ40 ratio showed consistent concordance with brain pathology measured by CSF or PET in the research setting. In addition, glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are neurodegenerative biomarkers that show the potential to assist in the differential diagnosis of AD. Other pathology-specific biomarkers, such as α-synuclein and TAR DNA-binding protein 43 (TDP-43), can potentially detect AD concurrent pathology. Based on current evidence, the working group from the Taiwan Dementia Society (TDS) achieved consensus recommendations on the appropriate use of BBMs for AD in clinical practice. BBMs may assist clinical diagnosis and prognosis in AD subjects with cognitive symptoms; however, the results should be interpreted by dementia specialists and combining biochemical, neuropsychological, and neuroimaging information. Further studies are needed to evaluate BBMs' real-world performance and potential impact on clinical decision-making.
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Affiliation(s)
- Yu-Wen Cheng
- Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan
| | - Yen-Ju Lin
- Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Yung-Shuan Lin
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan; Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Wei-Pin Hong
- Department of Neurology, National Cheng Kung University Hospital, Tainan, Taiwan
| | - Yi-Chun Kuan
- Taipei Neuroscience Institute, Taipei Medical University, Taipei, Taiwan; Department of Neurology and Dementia Center, Taipei Medical University-Shuang Ho Hospital, New Taipei City, Taiwan; Department of Neurology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Kuan-Yi Wu
- Department of Psychiatry, Chang Gung Memorial Hospital and College of Medicine, Chang Gung University, Tao-Yuan, Taiwan
| | - Jung-Lung Hsu
- Department of Neurology, New Taipei Municipal TuCheng Hospital, Chang Gung Memorial Hospital and Chang Gung University, New Taipei City, Taiwan; Graduate Institute of Mind, Brain, & Consciousness, Taipei Medical University, Taipei, Taiwan; Brain & Consciousness Research Center, Shuang Ho Hospital, New Taipei City, Taiwan
| | - Pei-Ning Wang
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ming-Chyi Pai
- Division of Behavioral Neurology, Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Alzheimer's Disease Research Center, National Cheng Kung University Hospital, Tainan, Taiwan; Institute of Gerontology, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Cheng-Sheng Chen
- Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan; Department of Psychiatry, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Jong-Ling Fuh
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chaur-Jong Hu
- Taipei Neuroscience Institute, Taipei Medical University, Taipei, Taiwan; Department of Neurology and Dementia Center, Taipei Medical University-Shuang Ho Hospital, New Taipei City, Taiwan; Department of Neurology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Ming-Jang Chiu
- Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan.
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31
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Wang S, Deng R, Chen Z, Huang L, Song Y, Yuan D, Li Y, Liu H, Yang F, Fan B, Xu Y, Zhao Z, Li Y, Zhang Y. High-Performance Plasma Biomarker Panel for Alzheimer's Disease Screening Using a Femtomolar-Level Label-Free Biosensing System. ACS NANO 2024; 18:2117-2130. [PMID: 38117205 DOI: 10.1021/acsnano.3c09311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Alzheimer's disease (AD) is the most common cause of dementia in older people. However, diagnosing AD through noncognitive methods, such as invasive cerebrospinal fluid sampling or radioactive positron emission tomography, has limited applications. Herein, the femtomolar levels of AD biomarkers amyloid β 40 (Aβ40), amyloid β 42 (Aβ42), phosphorylated tau 181 (P-tau181), phosphorylated tau 217 (P-tau217), and neurofilament light chain (NfL) were determined in human plasma in multicenter clinical cohorts using an ultrasensitive graphene field-effect transistor sensor. A machine-learning algorithm was also used to assemble these plasma biomarkers and optimize their performance in discriminating individual stages of Alzheimer's dementia progression. The "composite-info" biomarker panel, which combines these biomarkers and clinical information, considerably improved the staging performance in AD progression. It achieved an area under the curve of >0.94 in the receiver operator characteristic (ROC) curve. In addition, the panel demonstrated an advantage in the individual-based stage assessment compared with that of the Mini-Mental State Examination/Montreal Cognitive Assessment and nuclear magnetic resonance imaging. This study provides a composite biomarker panel for the screening and early diagnosis of AD using a rapid detection system.
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Affiliation(s)
- Shicai Wang
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing 100871, China
- Central Research Institute, BOE Technology Group Co., Ltd, Beijing 1000176, China
| | - Ruijun Deng
- Central Research Institute, BOE Technology Group Co., Ltd, Beijing 1000176, China
| | - Zhiya Chen
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing 100871, China
- Yiwu Boya Rehabilitation Hospital, Yiwu 322006, China
| | - Lili Huang
- Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China
| | - Yang Song
- Central Research Institute, BOE Technology Group Co., Ltd, Beijing 1000176, China
| | - Dan Yuan
- Central Research Institute, BOE Technology Group Co., Ltd, Beijing 1000176, China
| | - Yu Li
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing 100871, China
| | - Haonan Liu
- Central Research Institute, BOE Technology Group Co., Ltd, Beijing 1000176, China
| | - Fan Yang
- Central Research Institute, BOE Technology Group Co., Ltd, Beijing 1000176, China
| | - Beiyuan Fan
- Central Research Institute, BOE Technology Group Co., Ltd, Beijing 1000176, China
| | - Yun Xu
- Nanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing 210008, China
| | - Zijian Zhao
- Central Research Institute, BOE Technology Group Co., Ltd, Beijing 1000176, China
| | - Yanzhao Li
- Central Research Institute, BOE Technology Group Co., Ltd, Beijing 1000176, China
| | - Yan Zhang
- State Key Laboratory of Membrane Biology, School of Life Sciences, Peking University, Beijing 100871, China
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Gutierrez-Tordera L, Papandreou C, Novau-Ferré N, García-González P, Rojas M, Marquié M, Chapado LA, Papagiannopoulos C, Fernàndez-Castillo N, Valero S, Folch J, Ettcheto M, Camins A, Boada M, Ruiz A, Bulló M. Exploring small non-coding RNAs as blood-based biomarkers to predict Alzheimer's disease. Cell Biosci 2024; 14:8. [PMID: 38229129 PMCID: PMC10790437 DOI: 10.1186/s13578-023-01190-5] [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: 09/29/2023] [Accepted: 12/27/2023] [Indexed: 01/18/2024] Open
Abstract
BACKGROUND Alzheimer's disease (AD) diagnosis relies on clinical symptoms complemented with biological biomarkers, the Amyloid Tau Neurodegeneration (ATN) framework. Small non-coding RNA (sncRNA) in the blood have emerged as potential predictors of AD. We identified sncRNA signatures specific to ATN and AD, and evaluated both their contribution to improving AD conversion prediction beyond ATN alone. METHODS This nested case-control study was conducted within the ACE cohort and included MCI patients matched by sex. Patients free of type 2 diabetes underwent cerebrospinal fluid (CSF) and plasma collection and were followed-up for a median of 2.45-years. Plasma sncRNAs were profiled using small RNA-sequencing. Conditional logistic and Cox regression analyses with elastic net penalties were performed to identify sncRNA signatures for A+(T|N)+ and AD. Weighted scores were computed using cross-validation, and the association of these scores with AD risk was assessed using multivariable Cox regression models. Gene ontology (GO) and Kyoto encyclopaedia of genes and genomes (KEGG) enrichment analysis of the identified signatures were performed. RESULTS The study sample consisted of 192 patients, including 96 A+(T|N)+ and 96 A-T-N- patients. We constructed a classification model based on a 6-miRNAs signature for ATN. The model could classify MCI patients into A-T-N- and A+(T|N)+ groups with an area under the curve of 0.7335 (95% CI, 0.7327 to 0.7342). However, the addition of the model to conventional risk factors did not improve the prediction of AD beyond the conventional model plus ATN status (C-statistic: 0.805 [95% CI, 0.758 to 0.852] compared to 0.829 [95% CI, 0.786, 0.872]). The AD-related 15-sncRNAs signature exhibited better predictive performance than the conventional model plus ATN status (C-statistic: 0.849 [95% CI, 0.808 to 0.890]). When ATN was included in this model, the prediction further improved to 0.875 (95% CI, 0.840 to 0.910). The miRNA-target interaction network and functional analysis, including GO and KEGG pathway enrichment analysis, suggested that the miRNAs in both signatures are involved in neuronal pathways associated with AD. CONCLUSIONS The AD-related sncRNA signature holds promise in predicting AD conversion, providing insights into early AD development and potential targets for prevention.
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Affiliation(s)
- Laia Gutierrez-Tordera
- Nutrition and Metabolic Health Research Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), 43201, Reus, Spain
- Institute of Health Pere Virgili (IISPV), 43204, Reus, Spain
- Center of Environmental, Food and Toxicological Technology-TecnATox, Rovira i Virgili University, 43201, Reus, Spain
| | - Christopher Papandreou
- Nutrition and Metabolic Health Research Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), 43201, Reus, Spain.
- Institute of Health Pere Virgili (IISPV), 43204, Reus, Spain.
- Center of Environmental, Food and Toxicological Technology-TecnATox, Rovira i Virgili University, 43201, Reus, Spain.
| | - Nil Novau-Ferré
- Nutrition and Metabolic Health Research Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), 43201, Reus, Spain
- Institute of Health Pere Virgili (IISPV), 43204, Reus, Spain
- Center of Environmental, Food and Toxicological Technology-TecnATox, Rovira i Virgili University, 43201, Reus, Spain
| | - Pablo García-González
- ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), 08028, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
| | - Melina Rojas
- Nutrition and Metabolic Health Research Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), 43201, Reus, Spain
- Institute of Health Pere Virgili (IISPV), 43204, Reus, Spain
- Center of Environmental, Food and Toxicological Technology-TecnATox, Rovira i Virgili University, 43201, Reus, Spain
| | - Marta Marquié
- ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), 08028, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
| | - Luis A Chapado
- Laboratory of Epigenetics of Lipid Metabolism, Instituto Madrileño de Estudios Avanzados (IMDEA)-Alimentación, CEI UAM+CSIC, 28049, Madrid, Spain
| | - Christos Papagiannopoulos
- Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, 45500, Ioannina, Greece
| | - Noèlia Fernàndez-Castillo
- Department de Genetics, Microbiology and Statistics, Faculty of Biology, Universitat de Barcelona, 08007, Barcelona, Spain
| | - Sergi Valero
- ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), 08028, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
| | - Jaume Folch
- Nutrition and Metabolic Health Research Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), 43201, Reus, Spain
- Institute of Health Pere Virgili (IISPV), 43204, Reus, Spain
- Center of Environmental, Food and Toxicological Technology-TecnATox, Rovira i Virgili University, 43201, Reus, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
| | - Miren Ettcheto
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
- Department of Pharmacology, Toxicology and Therapeutic Chemistry, Faculty of Pharmacy and Food Science, Universitat de Barcelona, 08028, Barcelona, Spain
- Institute of Neuroscience, Universitat de Barcelona, 08035, Barcelona, Spain
| | - Antoni Camins
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
- Department of Pharmacology, Toxicology and Therapeutic Chemistry, Faculty of Pharmacy and Food Science, Universitat de Barcelona, 08028, Barcelona, Spain
- Institute of Neuroscience, Universitat de Barcelona, 08035, Barcelona, Spain
| | - Mercè Boada
- ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), 08028, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
| | - Agustín Ruiz
- ACE Alzheimer Center Barcelona, Universitat Internacional de Catalunya (UIC), 08028, Barcelona, Spain
- Biomedical Research Networking Centre in Neurodegenerative Diseases (CIBERNED), Carlos III Health Institute, 28031, Madrid, Spain
| | - Mònica Bulló
- Nutrition and Metabolic Health Research Group, Department of Biochemistry and Biotechnology, Rovira i Virgili University (URV), 43201, Reus, Spain.
- Institute of Health Pere Virgili (IISPV), 43204, Reus, Spain.
- Center of Environmental, Food and Toxicological Technology-TecnATox, Rovira i Virgili University, 43201, Reus, Spain.
- CIBER Physiology of Obesity and Nutrition (CIBEROBN), Carlos III Health Institute, 28029, Madrid, Spain.
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Garcia-Escobar G, Manero RM, Fernández-Lebrero A, Ois A, Navalpotro-Gómez I, Puente-Periz V, Contador-Muñana J, Estragués-Gazquez I, Puig-Pijoan A, Jiménez-Balado J. Blood Biomarkers of Alzheimer's Disease and Cognition: A Literature Review. Biomolecules 2024; 14:93. [PMID: 38254693 PMCID: PMC10813472 DOI: 10.3390/biom14010093] [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: 10/31/2023] [Revised: 01/02/2024] [Accepted: 01/09/2024] [Indexed: 01/24/2024] Open
Abstract
Recent advances in blood-based biomarkers of Alzheimer's Disease (AD) show great promise for clinical applications, offering a less invasive alternative to current cerebrospinal fluid (CSF) measures. However, the relationships between these biomarkers and specific cognitive functions, as well as their utility in predicting longitudinal cognitive decline, are not yet fully understood. This descriptive review surveys the literature from 2018 to 2023, focusing on the associations of amyloid-β (Aβ), Total Tau (t-Tau), Phosphorylated Tau (p-Tau), Neurofilament Light (NfL), and Glial Fibrillary Acidic Protein (GFAP) with cognitive measures. The reviewed studies are heterogeneous, varying in design and population (cognitively unimpaired, cognitively impaired, or mixed populations), and show results that are sometimes conflicting. Generally, cognition positively correlates with Aβ levels, especially when evaluated through the Aβ42/Aβ40 ratio. In contrast, t-Tau, p-Tau, Nfl, and GFAP levels typically show a negative correlation with cognitive performance. While p-Tau measures generally exhibit stronger associations with cognitive functions compared to other biomarkers, no single blood marker has emerged as being predominantly linked to a specific cognitive domain. These findings contribute to our understanding of the complex relationship between blood biomarkers and cognitive performance and underscore their potential utility in clinical assessments of cognition.
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Affiliation(s)
- Greta Garcia-Escobar
- Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (G.G.-E.); (R.M.M.); (A.F.-L.); (I.N.-G.); (V.P.-P.); (J.C.-M.); (I.E.-G.); (A.P.-P.); (J.J.-B.)
| | - Rosa Maria Manero
- Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (G.G.-E.); (R.M.M.); (A.F.-L.); (I.N.-G.); (V.P.-P.); (J.C.-M.); (I.E.-G.); (A.P.-P.); (J.J.-B.)
- Neurology Department, Hospital del Mar, 08003 Barcelona, Spain
| | - Aida Fernández-Lebrero
- Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (G.G.-E.); (R.M.M.); (A.F.-L.); (I.N.-G.); (V.P.-P.); (J.C.-M.); (I.E.-G.); (A.P.-P.); (J.J.-B.)
- Neurology Department, Hospital del Mar, 08003 Barcelona, Spain
- Department of Health and Experimental Sciences, Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Angel Ois
- Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (G.G.-E.); (R.M.M.); (A.F.-L.); (I.N.-G.); (V.P.-P.); (J.C.-M.); (I.E.-G.); (A.P.-P.); (J.J.-B.)
- Neurology Department, Hospital del Mar, 08003 Barcelona, Spain
- Department of Health and Experimental Sciences, Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Irene Navalpotro-Gómez
- Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (G.G.-E.); (R.M.M.); (A.F.-L.); (I.N.-G.); (V.P.-P.); (J.C.-M.); (I.E.-G.); (A.P.-P.); (J.J.-B.)
- Neurology Department, Hospital del Mar, 08003 Barcelona, Spain
- Department of Health and Experimental Sciences, Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Victor Puente-Periz
- Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (G.G.-E.); (R.M.M.); (A.F.-L.); (I.N.-G.); (V.P.-P.); (J.C.-M.); (I.E.-G.); (A.P.-P.); (J.J.-B.)
- Neurology Department, Hospital del Mar, 08003 Barcelona, Spain
| | - José Contador-Muñana
- Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (G.G.-E.); (R.M.M.); (A.F.-L.); (I.N.-G.); (V.P.-P.); (J.C.-M.); (I.E.-G.); (A.P.-P.); (J.J.-B.)
- Neurology Department, Hospital del Mar, 08003 Barcelona, Spain
| | - Isabel Estragués-Gazquez
- Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (G.G.-E.); (R.M.M.); (A.F.-L.); (I.N.-G.); (V.P.-P.); (J.C.-M.); (I.E.-G.); (A.P.-P.); (J.J.-B.)
- Neurology Department, Hospital del Mar, 08003 Barcelona, Spain
| | - Albert Puig-Pijoan
- Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (G.G.-E.); (R.M.M.); (A.F.-L.); (I.N.-G.); (V.P.-P.); (J.C.-M.); (I.E.-G.); (A.P.-P.); (J.J.-B.)
- Neurology Department, Hospital del Mar, 08003 Barcelona, Spain
- Department of Medicine, Universitat Autònoma de Barcelona, 08193 Barcelona, Spain
| | - Joan Jiménez-Balado
- Hospital del Mar Medical Research Institute, 08003 Barcelona, Spain; (G.G.-E.); (R.M.M.); (A.F.-L.); (I.N.-G.); (V.P.-P.); (J.C.-M.); (I.E.-G.); (A.P.-P.); (J.J.-B.)
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Thompson LI, Cummings M, Emrani S, Libon DJ, Ang A, Karjadi C, Au R, Liu C. Digital Clock Drawing as an Alzheimer's Disease Susceptibility Biomarker: Associations with Genetic Risk Score and APOE in Older Adults. J Prev Alzheimers Dis 2024; 11:79-87. [PMID: 38230720 PMCID: PMC10794851 DOI: 10.14283/jpad.2023.48] [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: 01/18/2024]
Abstract
BACKGROUND Alzheimer's disease (AD) is the leading cause of dementia in older adults, but most people are not diagnosed until significant neuronal loss has likely occurred along with a decline in cognition. Non-invasive and cost-effective digital biomarkers for AD have the potential to improve early detection. OBJECTIVE We examined the validity of DCTclockTM (a digitized clock drawing task) as an AD susceptibility biomarker. DESIGN We used two primary independent variables, Apolipoprotein E (APOE) ε4 allele carrier status and polygenic risk score (PRS). We examined APOE and PRS associations with DCTclockTM composite scores as dependent measures. SETTING We used existing data from the Framingham Heart Study (FHS), a community-based study with the largest dataset of digital clock drawing data to date. PARTICIPANTS The sample consisted of 2,398 older adults ages 60-94 with DCTclockTM data (mean age of 72.3, 55% female and 92% White). MEASUREMENTS PRS was calculated using 38 variants identified in a recent large genome-wide association study (GWAS) and meta-analysis of late-onset AD (LOAD). RESULTS Results showed that DCTclockTM performance decreased with advancing age, lower education, and the presence of one or more copies of APOE ε4. Lower DCTclockTM Total Score as well as lower composite scores for Information Processing Speed (both command and copy conditions) and Drawing Efficiency (command condition) were significantly associated with higher PRS levels and more copies of APOE ε4. APOE and PRS associations displayed similar effect sizes in both men and women. CONCLUSIONS Our results indicate that higher AD genetic risk is associated with poorer DCTclockTM performance in older adults without dementia. This is the first study to demonstrate significant differences in clock drawing performance on the basis of APOE status or PRS.
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Affiliation(s)
- L I Thompson
- Louisa Thompson, Department of Psychiatry, Alpert Medical School, Brown University, Providence, RI. Address: 345 Blackstone Blvd., Providence, RI 02906, USA. Phone: 401-455-6402. E-mail:
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35
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Ramos-Cejudo J, Scott MR, Tanner JA, Pase MP, McGrath ER, Ghosh S, Osorio RS, Thibault E, El Fakhri G, Johnson KA, Beiser A, Seshadri S. Associations of Plasma Tau with Amyloid and Tau PET: Results from the Community-Based Framingham Heart Study. J Alzheimers Dis 2024; 100:487-494. [PMID: 38875034 DOI: 10.3233/jad-231320] [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] [Indexed: 06/16/2024]
Abstract
Background Associations of plasma total tau levels with future risk of AD have been described. Objective To examine the extent to which plasma tau reflects underlying AD brain pathology in cognitively healthy individuals. Methods We examined cross-sectional associations of plasma total tau with 11C-Pittsburgh Compound-B (PiB)-PET and 18F-Flortaucipir (FTP)-PET in middle-aged participants at the community-based Framingham Heart Study. Results Our final sample included 425 participants (mean age 57.6± 9.9, 50% F). Plasma total tau levels were positively associated with amyloid-β deposition in the precuneus region (β±SE, 0.11±0.05; p = 0.025). A positive association between plasma total tau and tau PET in the rhinal cortex was suggested in participants with higher amyloid-PET burden and in APOEɛ4 carriers. Conclusions Our study highlights that plasma total tau is a marker of amyloid deposition as early as in middle-age.
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Affiliation(s)
- Jaime Ramos-Cejudo
- Department of Psychiatry, New York University (NYU) Grossman School of Medicine, New York, NY, USA
| | - Matthew R Scott
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jeremy A Tanner
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
| | - Matthew P Pase
- Turner Institute for Brain and Mental Health, School of Psychological Sciences, Monash University, Clayton, VIC, Australia
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Emer R McGrath
- HRB Clinical Research Facility, University of Galway, Galway, Ireland
- The Framingham Study, Boston, MA, USA
- School of Medicine, University of Galway, Galway, Ireland
| | | | - Ricardo S Osorio
- Department of Psychiatry, New York University (NYU) Grossman School of Medicine, New York, NY, USA
| | - Emma Thibault
- Department of Radiology, Harvard Medical School, Boston, MA, USA
| | | | - Keith A Johnson
- Department of Radiology, Harvard Medical School, Boston, MA, USA
- Department of Neurology, Harvard Medical School, Boston, MA, USA
| | - Alexa Beiser
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- The Framingham Study, Boston, MA, USA
- Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, USA
- The Framingham Study, Boston, MA, USA
- Department of Neurology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
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Rehman H, Ang TFA, Tao Q, Espenilla AL, Au R, Farrer LA, Zhang X, Qiu WQ. Comparison of Commonly Measured Plasma and Cerebrospinal Fluid Proteins and Their Significance for the Characterization of Cognitive Impairment Status. J Alzheimers Dis 2024; 97:621-633. [PMID: 38143358 DOI: 10.3233/jad-230837] [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] [Indexed: 12/26/2023]
Abstract
BACKGROUND Although cerebrospinal fluid (CSF) amyloid-β42 peptide (Aβ42) and phosphorylated tau (p-tau) and blood p-tau are valuable for differential diagnosis of Alzheimer's disease (AD) from cognitively normal (CN) there is a lack of validated biomarkers for mild cognitive impairment (MCI). OBJECTIVE This study sought to determine how plasma and CSF protein markers compared in the characterization of MCI and AD status. METHODS This cohort study included Alzheimer's Disease Neuroimaging Initiative (ADNI) participants who had baseline levels of 75 proteins measured commonly in plasma and CSF (257 total, 46 CN, 143 MCI, and 68 AD). Logistic regression, least absolute shrinkage and selection operator (LASSO) and Random Forest (RF) methods were used to identify the protein candidates for the disease classification. RESULTS We observed that six plasma proteins panel (APOE, AMBP, C3, IL16, IGFBP2, APOD) outperformed the seven CSF proteins panel (VEGFA, HGF, PRL, FABP3, FGF4, CD40, RETN) as well as AD markers (CSF p-tau and Aβ42) to distinguish the MCI from AD [area under the curve (AUC) = 0.75 (plasma proteins), AUC = 0.60 (CSF proteins) and AUC = 0.56 (CSF p-tau and Aβ42)]. Also, these six plasma proteins performed better than the CSF proteins and were in line with CSF p-tau and Aβ42 in differentiating CN versus MCI subjects [AUC = 0.89 (plasma proteins), AUC = 0.85 (CSF proteins) and AUC = 0.89 (CSF p-tau and Aβ42)]. These results were adjusted for age, sex, education, and APOEϵ4 genotype. CONCLUSIONS This study suggests that the combination of 6 plasma proteins can serve as an effective marker for differentiating MCI from AD and CN.
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Affiliation(s)
- Habbiburr Rehman
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Ting Fang Alvin Ang
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Qiushan Tao
- Department of Pharmacology & Experimental Therapeutics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
| | - Arielle Lauren Espenilla
- Department of Biostatistics and Boston University School of Public Health, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
| | - Rhoda Au
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Boston University School of Medicine, Framingham, MA, USA
- Alzheimer's Disease Research Center, Boston University School of Medicine, Boston, MA, USA
| | - Lindsay A Farrer
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Ophthalmology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Biostatistics and Boston University School of Public Health, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Boston University School of Medicine, Framingham, MA, USA
- Alzheimer's Disease Research Center, Boston University School of Medicine, Boston, MA, USA
| | - Xiaoling Zhang
- Department of Medicine (Biomedical Genetics), Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Biostatistics and Boston University School of Public Health, Boston, MA, USA
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, USA
- Framingham Heart Study, Boston University School of Medicine, Framingham, MA, USA
- Alzheimer's Disease Research Center, Boston University School of Medicine, Boston, MA, USA
| | - Wei Qiao Qiu
- Department of Anatomy & Neurobiology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Neurology, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Pharmacology & Experimental Therapeutics, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Department of Psychiatry, Boston University Chobanian & Avedisian School of Medicine, Boston, MA, USA
- Alzheimer's Disease Research Center, Boston University School of Medicine, Boston, MA, USA
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Perneczky R, Hansen N, Hofmann A, Laske C, Priller J, Grimmer T, Frölich L, Düzel E, Jessen F, Wiltfang J. Blood-Based Biomarkers for Early Alzheimer's Disease Diagnosis in Real-World Settings. Methods Mol Biol 2024; 2785:3-14. [PMID: 38427184 DOI: 10.1007/978-1-0716-3774-6_1] [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] [Indexed: 03/02/2024]
Abstract
As our knowledge about the biology of Alzheimer's disease (AD) expands and we recognize the significance of early intervention for effective treatment, there is a shift in focus toward detecting the disease at an early stage. AD is characterized by the accumulation of misfolded amyloid-β (Aβ) and phosphorylated tau proteins in the brain, leading to the formation of senile plaques and neurofibrillary tangles. While a definitive diagnosis of AD can only be confirmed through autopsy by examining these pathological features, there are now reliable methods available for diagnosing the disease in living individuals. These methods involve analyzing cerebrospinal fluid and using positron emission tomography to accurately assess the presence of Aβ and tau proteins. While these diagnostic markers have shown high accuracy in memory-clinic populations, they do have limitations such as the requirement for invasive lumbar puncture or exposure to ionizing radiation. Additionally, they are not easily accessible outside of specialized healthcare settings. Blood-based biomarkers of the core pathological features of AD are being developed, showing promise for less invasive, scalable identification of AD cases in the community. The advantages for the healthcare systems of this development are obvious, but the diagnostic performance of blood-based biomarkers in broader, non-selected populations outside of retrospective analyses and research cohorts still requires further investigation, including the combination with more effective neuropsychological assessments such as digital cognitive test solutions.
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Affiliation(s)
- Robert Perneczky
- Department of Psychiatry and Psychotherapy, LMU Hospital, Ludwig-Maximilians-University Munich, Munich, Germany.
- German Center for Neurodegenerative Diseases (DZNE) Munich, Munich, Germany.
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
- Ageing Epidemiology (AGE) Research Unit, School of Public Health, Imperial College London, London, UK.
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK.
| | - Niels Hansen
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
| | - Anna Hofmann
- Hertie Institute for Clinical Brain Research, University of Tuebingen, Tuebingen, Germany
- Department of Neurology, University Hospital Tuebingen, Tuebingen, Germany
- German Center for Neurodegenerative Diseases (DZNE) Tuebingen, Tuebingen, Germany
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE) Tuebingen, Tuebingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research, University of Tuebingen, Tuebingen, Germany
- Department of Psychiatry and Psychotherapy, University of Tuebingen, Tuebingen, Germany
| | - Josef Priller
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE) Berlin, Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charite University Medicine, Berlin, Germany
- Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Timo Grimmer
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, Technical University Munich, Munich, Germany
| | - Lutz Frölich
- Department of Geriatric Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Emrah Düzel
- Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE) Magdeburg, Magdeburg, Germany
| | - Frank Jessen
- Department of Psychiatry and Psychotherapy, University of Cologne, Medical Faculty, Cologne, Germany
- German Center for Neurodegenerative Diseases (DZNE) Bonn, Bonn, Germany
- Excellence Cluster on Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Göttingen, Göttingen, Germany
- German Center for Neurodegenerative Diseases (DZNE) Goettingen, Goettingen, Germany
- Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
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Zhang M, Chen H, Huang W, Guo T, Ma G, Han Y, Shu N. Relationship between topological efficiency of white matter structural connectome and plasma biomarkers across the Alzheimer's disease continuum. Hum Brain Mapp 2024; 45:e26566. [PMID: 38224535 PMCID: PMC10785192 DOI: 10.1002/hbm.26566] [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: 08/23/2023] [Revised: 11/11/2023] [Accepted: 11/30/2023] [Indexed: 01/17/2024] Open
Abstract
Both plasma biomarkers and brain network topology have shown great potential in the early diagnosis of Alzheimer's disease (AD). However, the specific associations between plasma AD biomarkers, structural network topology, and cognition across the AD continuum have yet to be fully elucidated. This retrospective study evaluated participants from the Sino Longitudinal Study of Cognitive Decline cohort between September 2009 and October 2022 with available blood samples or 3.0-T MRI brain scans. Plasma biomarker levels were measured using the Single Molecule Array platform, including β-amyloid (Aβ), phosphorylated tau181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light chain (NfL). The topological structure of brain white matter was assessed using network efficiency. Trend analyses were carried out to evaluate the alterations of the plasma markers and network efficiency with AD progression. Correlation and mediation analyses were conducted to further explore the relationships among plasma markers, network efficiency, and cognitive performance across the AD continuum. Among the plasma markers, GFAP emerged as the most sensitive marker (linear trend: t = 11.164, p = 3.59 × 10-24 ; quadratic trend: t = 7.708, p = 2.25 × 10-13 ; adjusted R2 = 0.475), followed by NfL (linear trend: t = 6.542, p = 2.9 × 10-10 ; quadratic trend: t = 3.896, p = 1.22 × 10-4 ; adjusted R2 = 0.330), p-tau181 (linear trend: t = 8.452, p = 1.61 × 10-15 ; quadratic trend: t = 6.316, p = 1.05 × 10-9 ; adjusted R2 = 0.346) and Aβ42/Aβ40 (linear trend: t = -3.257, p = 1.27 × 10-3 ; quadratic trend: t = -1.662, p = 9.76 × 10-2 ; adjusted R2 = 0.101). Local efficiency decreased in brain regions across the frontal and temporal cortex and striatum. The principal component of local efficiency within these regions was correlated with GFAP (Pearson's R = -0.61, p = 6.3 × 10-7 ), NfL (R = -0.57, p = 6.4 × 10-6 ), and p-tau181 (R = -0.48, p = 2.0 × 10-4 ). Moreover, network efficiency mediated the relationship between general cognition and GFAP (ab = -0.224, 95% confidence interval [CI] = [-0.417 to -0.029], p = .0196 for MMSE; ab = -0.198, 95% CI = [-0.42 to -0.003], p = .0438 for MOCA) or NfL (ab = -0.224, 95% CI = [-0.417 to -0.029], p = .0196 for MMSE; ab = -0.198, 95% CI = [-0.42 to -0.003], p = .0438 for MOCA). Our findings suggest that network efficiency mediates the association between plasma biomarkers, specifically GFAP and NfL, and cognitive performance in the context of AD progression, thus highlighting the potential utility of network-plasma approaches for early detection, monitoring, and intervention strategies in the management of AD.
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Affiliation(s)
- Mingkai Zhang
- Department of NeurologyXuanwu Hospital, Capital Medical UniversityBeijingChina
| | - Haojie Chen
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain ResearchBeijing Normal UniversityBeijingChina
- BABRI CentreBeijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and ConnectomicsBeijing Normal UniversityBeijingChina
| | - Weijie Huang
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain ResearchBeijing Normal UniversityBeijingChina
- BABRI CentreBeijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and ConnectomicsBeijing Normal UniversityBeijingChina
| | - Tengfei Guo
- Institute of Biomedical EngineeringShenzhen Bay LaboratoryShenzhenChina
| | - Guolin Ma
- Department of RadiologyChina‐Japan Friendship HospitalBeijingChina
| | - Ying Han
- Department of NeurologyXuanwu Hospital, Capital Medical UniversityBeijingChina
- Institute of Biomedical EngineeringShenzhen Bay LaboratoryShenzhenChina
- School of Biomedical EngineeringHainan UniversityHaikouChina
- National Clinical Research Center for Geriatric DiseasesBeijingChina
- Center of Alzheimer's DiseaseBeijing Institute for Brain DisordersBeijingChina
| | - Ni Shu
- State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain ResearchBeijing Normal UniversityBeijingChina
- BABRI CentreBeijing Normal UniversityBeijingChina
- Beijing Key Laboratory of Brain Imaging and ConnectomicsBeijing Normal UniversityBeijingChina
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Asken BM, Wang W, McFarland K, Arias F, Fiala J, Velez‐Uribe I, Mayrand RP, Sawada LO, Freytes C, Adeyosoye M, Marsiske M, Rosselli M, Barker WW, Curiel Cid R, Loewenstein DA, DeKosky ST, Armstrong MJ, Smith GE, Adjouadi M, Vaillancourt DE, Duara R. Plasma Alzheimer's biomarkers and brain amyloid in Hispanic and non-Hispanic older adults. Alzheimers Dement 2024; 20:437-446. [PMID: 37671801 PMCID: PMC10865106 DOI: 10.1002/alz.13456] [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: 05/03/2023] [Revised: 08/01/2023] [Accepted: 08/04/2023] [Indexed: 09/07/2023]
Abstract
INTRODUCTION Alzheimer's disease studies often lack ethnic diversity. METHODS We evaluated associations between plasma biomarkers commonly studied in Alzheimer's (p-tau181, GFAP, and NfL), clinical diagnosis (clinically normal, amnestic MCI, amnestic dementia, or non-amnestic MCI/dementia), and Aβ-PET in Hispanic and non-Hispanic older adults. Hispanics were predominantly of Cuban or South American ancestry. RESULTS Three-hundred seventy nine participants underwent blood draw (71.9 ± 7.8 years old, 60.2% female, 57% Hispanic of which 88% were Cuban or South American) and 240 completed Aβ-PET. P-tau181 was higher in amnestic MCI (p = 0.004, d = 0.53) and dementia (p < 0.001, d = 0.97) than in clinically normal participants and discriminated Aβ-PET[+] and Aβ-PET[-] (AUC = 0.86). P-tau181 outperformed GFAP and NfL. There were no significant interactions with ethnicity. Among amnestic MCI, Hispanics had lower odds of elevated p-tau181 than non-Hispanic (OR = 0.41, p = 0.006). DISCUSSION Plasma p-tau181 informs etiological diagnosis of cognitively impaired Hispanic and non-Hispanic older adults. Hispanic ethnicity may relate to greater likelihood of non-Alzheimer's contributions to memory loss. HIGHLIGHTS Alzheimer's biomarkers were measured in Hispanic and non-Hispanic older adults. Plasma p-tau181 related to amnestic cognitive decline and brain amyloid burden. AD biomarker associations did not differ between Hispanic and non-Hispanic ethnicity. Hispanic individuals may be more likely to have non-Alzheimer causes of memory loss.
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Nallapu BT, Petersen KK, Lipton RB, Davatzikos C, Ezzati A. Plasma Biomarkers as Predictors of Progression to Dementia in Individuals with Mild Cognitive Impairment. J Alzheimers Dis 2024; 98:231-246. [PMID: 38393899 PMCID: PMC11044769 DOI: 10.3233/jad-230620] [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: 02/25/2024]
Abstract
Background Blood-based biomarkers (BBMs) are of growing interest in the field of Alzheimer's disease (AD) and related dementias. Objective This study aimed to assess the ability of plasma biomarkers to 1) predict disease progression from mild cognitive impairment (MCI) to dementia and 2) improve the predictive ability of magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) measures when combined. Methods We used data from the Alzheimer's Disease Neuroimaging Initiative. Machine learning models were trained using the data from participants who remained cognitively stable (CN-s) and with Dementia diagnosis at 2-year follow-up visit. The models were used to predict progression to dementia in MCI individuals. We assessed the performance of models with plasma biomarkers against those with CSF and MRI measures, and also in combination with them. Results Our models with plasma biomarkers classified CN-s individuals from AD with an AUC of 0.75±0.03 and could predict conversion to dementia in MCI individuals with an AUC of 0.64±0.03 (17.1% BP, base prevalence). Models with plasma biomarkers performed better when combined with CSF and MRI measures (CN versus AD: AUC of 0.89±0.02; MCI-to-AD: AUC of 0.76±0.03, 21.5% BP). Conclusions Our results highlight the potential of plasma biomarkers in predicting conversion to dementia in MCI individuals. While plasma biomarkers could improve the predictive ability of CSF and MRI measures when combined, they also show the potential to predict non-progression to AD when considered alone. The predictive ability of plasma biomarkers is crucially linked to reducing the costly and effortful collection of CSF and MRI measures.
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Affiliation(s)
- Bhargav T. Nallapu
- Saul B. Korey Department of Neurology, Albert Einstein College of Medicine, New York City, NY, USA
| | - Kellen K. Petersen
- Saul B. Korey Department of Neurology, Albert Einstein College of Medicine, New York City, NY, USA
| | - Richard B. Lipton
- Saul B. Korey Department of Neurology, Albert Einstein College of Medicine, New York City, NY, USA
| | - Christos Davatzikos
- Radiology Department, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Ali Ezzati
- Saul B. Korey Department of Neurology, Albert Einstein College of Medicine, New York City, NY, USA
- Department of Neurology, University of California, Irvine, Irvine, CA, USA
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Bruno D, Gicas KM, Jauregi‐Zinkunegi A, Mueller KD, Lamar M. Delayed primacy recall performance predicts post mortem Alzheimer's disease pathology from unimpaired ante mortem cognitive baseline. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12524. [PMID: 38239330 PMCID: PMC10795090 DOI: 10.1002/dad2.12524] [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: 06/14/2023] [Revised: 10/31/2023] [Accepted: 12/19/2023] [Indexed: 01/22/2024]
Abstract
We propose a novel method to assess delayed primacy in the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) memory test. We then examine whether this measure predicts post mortem Alzheimer's disease (AD) neuropathology in individuals who were clinically unimpaired at baseline. A total of 1096 individuals were selected from the Rush Alzheimer's Disease Center database registry. All participants were clinically unimpaired at baseline, and had subsequently undergone brain autopsy. Average age at baseline was 78.8 (6.92). A Bayesian regression analysis was carried out with global pathology as an outcome; demographic, clinical, and apolipoprotein E (APOE) data as covariates; and cognitive predictors, including delayed primacy. Global AD pathology was best predicted by delayed primacy. Secondary analyses showed that delayed primacy was mostly associated with neuritic plaques, whereas total delayed recall was associated with neurofibrillary tangles. Sex differential associations were observed. We conclude that CERAD-derived delayed primacy is a useful metric for early detection and diagnosis of AD in unimpaired individuals. Highlights We propose a novel method to analyse serial position in the CERAD memory test.We analyse data from 1096 individuals who were cognitively unimpaired at baseline.Delayed primacy predicts post mortem pathology better than traditional metrics.
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Affiliation(s)
- Davide Bruno
- School of PsychologyLiverpool John Moores UniversityLiverpoolUK
| | | | | | - Kimberly D. Mueller
- Wisconsin Alzheimer's InstituteSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Wisconsin Alzheimer's Disease Research CenterSchool of Medicine and Public HealthUniversity of Wisconsin – MadisonMadisonWisconsinUSA
- Department of Communication Sciences and DisordersUniversity of Wisconsin – MadisonMadisonWisconsinUSA
| | - Melissa Lamar
- Rush Alzheimer's Disease Center and the Department of Psychiatry and Behavioral SciencesRush University Medical CenterChicagoIllinoisUSA
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Du L, Hermann BP, Jonaitis EM, Cody KA, Rivera-Rivera L, Rowley H, Field A, Eisenmenger L, Christian BT, Betthauser TJ, Larget B, Chappell R, Janelidze S, Hansson O, Johnson SC, Langhough R. Harnessing cognitive trajectory clusterings to examine subclinical decline risk factors. Brain Commun 2023; 5:fcad333. [PMID: 38107504 PMCID: PMC10724051 DOI: 10.1093/braincomms/fcad333] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 10/23/2023] [Accepted: 11/30/2023] [Indexed: 12/19/2023] Open
Abstract
Cognitive decline in Alzheimer's disease and other dementias typically begins long before clinical impairment. Identifying people experiencing subclinical decline may facilitate earlier intervention. This study developed cognitive trajectory clusters using longitudinally based random slope and change point parameter estimates from a Preclinical Alzheimer's disease Cognitive Composite and examined how baseline and most recently available clinical/health-related characteristics, cognitive statuses and biomarkers for Alzheimer's disease and vascular disease varied across these cognitive clusters. Data were drawn from the Wisconsin Registry for Alzheimer's Prevention, a longitudinal cohort study of adults from late midlife, enriched for a parental history of Alzheimer's disease and without dementia at baseline. Participants who were cognitively unimpaired at the baseline visit with ≥3 cognitive visits were included in trajectory modelling (n = 1068). The following biomarker data were available for subsets: positron emission tomography amyloid (amyloid: n = 367; [11C]Pittsburgh compound B (PiB): global PiB distribution volume ratio); positron emission tomography tau (tau: n = 321; [18F]MK-6240: primary regions of interest meta-temporal composite); MRI neurodegeneration (neurodegeneration: n = 581; hippocampal volume and global brain atrophy); T2 fluid-attenuated inversion recovery MRI white matter ischaemic lesion volumes (vascular: white matter hyperintensities; n = 419); and plasma pTau217 (n = 165). Posterior median estimate person-level change points, slopes' pre- and post-change point and estimated outcome (intercepts) at change point for cognitive composite were extracted from Bayesian Bent-Line Regression modelling and used to characterize cognitive trajectory groups (K-means clustering). A common method was used to identify amyloid/tau/neurodegeneration/vascular biomarker thresholds. We compared demographics, last visit cognitive status, health-related factors and amyloid/tau/neurodegeneration/vascular biomarkers across the cognitive groups using ANOVA, Kruskal-Wallis, χ2, and Fisher's exact tests. Mean (standard deviation) baseline and last cognitive assessment ages were 58.4 (6.4) and 66.6 (6.6) years, respectively. Cluster analysis identified three cognitive trajectory groups representing steep, n = 77 (7.2%); intermediate, n = 446 (41.8%); and minimal, n = 545 (51.0%) cognitive decline. The steep decline group was older, had more females, APOE e4 carriers and mild cognitive impairment/dementia at last visit; it also showed worse self-reported general health-related and vascular risk factors and higher amyloid, tau, neurodegeneration and white matter hyperintensity positive proportions at last visit. Subtle cognitive decline was consistently evident in the steep decline group and was associated with generally worse health. In addition, cognitive trajectory groups differed on aetiology-informative biomarkers and risk factors, suggesting an intimate link between preclinical cognitive patterns and amyloid/tau/neurodegeneration/vascular biomarker differences in late middle-aged adults. The result explains some of the heterogeneity in cognitive performance within cognitively unimpaired late middle-aged adults.
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Affiliation(s)
- Lianlian Du
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bruce P Hermann
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Neurology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
| | - Erin M Jonaitis
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Karly Alex Cody
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Leonardo Rivera-Rivera
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
| | - Howard Rowley
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Aaron Field
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Laura Eisenmenger
- Department of Radiology, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bradley T Christian
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medical Physics, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53705, USA
- Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, WI 53705, USA
| | - Tobey J Betthauser
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Bret Larget
- Department of Statistics, University of Wisconsin-Madison, Madison, WI 53706, USA
| | - Rick Chappell
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI 53726, USA
| | | | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund 205 02, Sweden
| | - Sterling C Johnson
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
| | - Rebecca Langhough
- Wisconsin Alzheimer’s Institute, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
- Department of Medicine, University of Wisconsin-Madison School of Medicine and Public Health, Madison, WI 53792, USA
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Dong Q, Li Z, Liu W, Chen K, Su Y, Wu J, Caselli RJ, Reiman EM, Wang Y, Shen J. Correlation studies of Hippocampal Morphometry and Plasma NFL Levels in Cognitively Unimpaired Subjects. IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL SYSTEMS 2023; 10:3602-3608. [PMID: 38084365 PMCID: PMC10713345 DOI: 10.1109/tcss.2023.3313819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
Alzheimer's disease(AD) is being the burden of society and family. Applying computing-aided strategies to reveal its pathology is one of the research highlights. Plasma neurofilament light (NFL) is an emerging noninvasive and economic biomarker for AD molecular pathology. It is valuable to reveal the correlations between the plasma NFL levels and neurodegeneration, especially hippcampal deformations at the preclinical stage. The negative correlation between plasma NFL levels and hippocampal volumes has been documented. However, the relationship between the plasma NFL levels and the hippocampal morphometry details at the preclinical stage is still elusive. This study seeks to demonstrate the capacity of our proposed surface-based hippocampal morphometry system to discern the plasma NFL positive (NFL+>41.9 pg/L) level and plasma NFL negative (NFL-<41.9pg/L) level and illustrate its superiority to the hippocampal volume measurement by drawing the cohort of 154 CU middle aged and elderly adults. We also apply this morphometry measure and a proposed sparse coding based classification algorithm to classify CU individuals with NFL+ and NFL- levels. Experimental results show that the proposed hippocampal morphometry system offers stronger statistical power to discriminate CU subjects with NFL+ and NFL- levels, comparing with the hippocampal volume measure. Furthermore, this system can discriminate plasma NFL levels in CU individuals (Accuracy=0.86). Both the group level and individual level analysis results indicate that the association between plasma NFL levels and the hippocampal shapes can be mapped at the preclinical stage.
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Affiliation(s)
- Qunxi Dong
- School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, China
| | - Zhigang Li
- School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, China
| | - Weijia Liu
- School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, China
| | - Kewei Chen
- Banner Alzheimer's Institute, Phoenix, AZ, USA
| | - Yi Su
- Banner Alzheimer's Institute, Phoenix, AZ, USA
| | - Jianfeng Wu
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State Univ., Tempe, AZ, USA
| | | | | | - Yalin Wang
- School of Computing, Informatics, and Decision Systems Engineering, Arizona State Univ., Tempe, AZ, USA
| | - Jian Shen
- School of Medical Technology, Beijing Institute of Technology, Beijing, 100081, China
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Saeed A, Lopez O, Cohen A, Reis SE. Cardiovascular Disease and Alzheimer's Disease: The Heart-Brain Axis. J Am Heart Assoc 2023; 12:e030780. [PMID: 37929715 PMCID: PMC10727398 DOI: 10.1161/jaha.123.030780] [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: 11/07/2023]
Abstract
Cardiovascular disease (CVD) remains one of the leading causes of morbidity and mortality in aging adults across the United States. Prior studies indicate that the presence of atherosclerosis, the pathogenic basis of CVD, is linked with dementias. Alzheimer's disease (AD) and AD-related dementias are a major public health challenge in the United States. Recent studies indicate that ≈3.7 million Americans ≥65 years of age had clinical AD in 2017, with projected increases to 9.3 million by 2060. Treatment options for AD remain limited. Development of disease-modifying therapies are challenging due, in part, to the long preclinical window of AD. The preclinical incubation period of AD starts in midlife, providing a critical window for identification and optimization of AD risk factors. Studies link AD with CVD risk factors such as hypertension, inflammation, and dyslipidemia. Both AD and CVD are progressive diseases with decades-long development periods. CVD can clinically manifest several years earlier than AD, making CVD and its risk factors a potential predictor of future AD. The current review focuses on the state of literature on molecular and metabolic pathways modulating the heart-brain axis underlying the potential association of midlife CVD risk factors and their effect on AD and related dementias. Further, we explore potential CVD/dementia preventive strategies during the window of opportunity in midlife and the future of research in the field in the multiomics and novel biomarker use era.
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Affiliation(s)
- Anum Saeed
- University of Pittsburgh School of MedicinePittsburghPAUSA
- Heart and Vascular InstituteUniversity of Pittsburgh Medical CenterPAPittsburghUSA
| | - Oscar Lopez
- University of Pittsburgh School of MedicinePittsburghPAUSA
- Cognitive and Behavioral and Neurology DivisionUniversity of Pittsburgh Medical CenterPAPittsburghUSA
| | - Ann Cohen
- University of Pittsburgh School of MedicinePittsburghPAUSA
- Division of PsychiatryUniversity of Pittsburgh Medical CenterPAPittsburghUSA
| | - Steven E. Reis
- University of Pittsburgh School of MedicinePittsburghPAUSA
- Heart and Vascular InstituteUniversity of Pittsburgh Medical CenterPAPittsburghUSA
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Ramanan VK, Gebre RK, Graff-Radford J, Hofrenning E, Algeciras-Schimnich A, Figdore DJ, Lowe VJ, Mielke MM, Knopman DS, Ross OA, Jack CR, Petersen RC, Vemuri P. Genetic risk scores enhance the diagnostic value of plasma biomarkers of brain amyloidosis. Brain 2023; 146:4508-4519. [PMID: 37279785 PMCID: PMC10629762 DOI: 10.1093/brain/awad196] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2023] [Revised: 05/02/2023] [Accepted: 05/14/2023] [Indexed: 06/08/2023] Open
Abstract
Blood-based biomarkers offer strong potential to revolutionize diagnosis, trial enrolment and treatment monitoring in Alzheimer's disease (AD). However, further advances are needed before these biomarkers can achieve wider deployment beyond selective research studies and specialty memory clinics, including the development of frameworks for optimal interpretation of biomarker profiles. We hypothesized that integrating Alzheimer's disease genetic risk score (AD-GRS) data would enhance the diagnostic value of plasma AD biomarkers by better capturing extant disease heterogeneity. Analysing 962 individuals from a population-based sample, we observed that an AD-GRS was independently associated with amyloid PET levels (an early marker of AD pathophysiology) over and above APOE ε4 or plasma p-tau181, amyloid-β42/40, glial fibrillary acidic protein or neurofilament light chain. Among individuals with a high or moderately high plasma p-tau181, integrating AD-GRS data significantly improved classification accuracy of amyloid PET positivity, including the finding that the combination of a high AD-GRS and high plasma p-tau181 outperformed p-tau181 alone in classifying amyloid PET positivity (88% versus 68%; P = 0.001). A machine learning approach incorporating plasma biomarkers, demographics and the AD-GRS was highly accurate in predicting amyloid PET levels (90% training set; 89% test set) and Shapley value analyses (an explainer method based in cooperative game theory) indicated that the AD-GRS and plasma biomarkers had differential importance in explaining amyloid deposition across individuals. Polygenic risk for AD dementia appears to account for a unique portion of disease heterogeneity, which could non-invasively enhance the interpretation of blood-based AD biomarker profiles in the population.
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Affiliation(s)
- Vijay K Ramanan
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Robel K Gebre
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Ekaterina Hofrenning
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Daniel J Figdore
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL 32224, USA
- Department of Clinical Genomics, Mayo Clinic, Jacksonville, FL 32224, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Ronald C Petersen
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
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46
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Sen A, Tai XY. Sleep Duration and Executive Function in Adults. Curr Neurol Neurosci Rep 2023; 23:801-813. [PMID: 37957525 PMCID: PMC10673787 DOI: 10.1007/s11910-023-01309-8] [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] [Accepted: 09/26/2023] [Indexed: 11/15/2023]
Abstract
PURPOSE OF REVIEW To review the literature examining the relationship between sleep and cognition, specifically examining the sub-domain of executive function. We explore the impact of sleep deprivation and the important question of how much sleep is required for optimal cognitive performance. We consider how other sleep metrics, such as sleep quality, may be a more meaningful measure of sleep. We then discuss the putative mechanisms between sleep and cognition followed by their contribution to developing dementia. RECENT FINDINGS Sleep duration and executive function display a quadratic relationship. This suggests an optimal amount of sleep is required for daily cognitive processes. Poor sleep efficiency and sleep fragmentation are linked with poorer executive function and increased risk of dementia during follow-up. Sleep quality may therefore be more important than absolute duration. Biological mechanisms which may underpin the relationship between sleep and cognition include brain structural and functional changes as well as disruption of the glymphatic system. Sleep is an important modifiable lifestyle factor to improve daily cognition and, possibly, reduce the risk of developing dementia. The impact of optimal sleep duration and sleep quality may have important implications for every ageing individual.
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Affiliation(s)
- Aayushi Sen
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
- Division of Clinical Neurology, John Radcliffe Hospital, Oxford University Hospitals Trust, Level 6 West Wing, Oxford, UK.
| | - Xin You Tai
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Division of Clinical Neurology, John Radcliffe Hospital, Oxford University Hospitals Trust, Level 6 West Wing, Oxford, UK
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47
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Cai H, Pang Y, Fu X, Ren Z, Jia L. Plasma biomarkers predict Alzheimer's disease before clinical onset in Chinese cohorts. Nat Commun 2023; 14:6747. [PMID: 37875471 PMCID: PMC10597998 DOI: 10.1038/s41467-023-42596-6] [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: 12/07/2022] [Accepted: 10/17/2023] [Indexed: 10/26/2023] Open
Abstract
Plasma amyloid-β (Aβ)42, phosphorylated tau (p-tau)181, and neurofilament light chain (NfL) are promising biomarkers of Alzheimer's disease (AD). However, whether these biomarkers can predict AD in Chinese populations is yet to be fully explored. We therefore tested the performance of these plasma biomarkers in 126 participants with preclinical AD and 123 controls with 8-10 years of follow-up from the China Cognition and Aging Study. Plasma Aβ42, p-tau181, and NfL were significantly correlated with cerebrospinal fluid counterparts and significantly altered in participants with preclinical AD. Combining plasma Aβ42, p-tau181, and NfL successfully discriminated preclinical AD from controls. These findings were validated in a replication cohort including 51 familial AD mutation carriers and 52 non-carriers from the Chinese Familial Alzheimer's Disease Network. Here we show that plasma Aβ42, p-tau181, and NfL may be useful for predicting AD 8 years before clinical onset in Chinese populations.
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Affiliation(s)
- 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
| | - Yana Pang
- 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
| | - 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
| | - 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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48
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Hampel H, Hu Y, Cummings J, Mattke S, Iwatsubo T, Nakamura A, Vellas B, O'Bryant S, Shaw LM, Cho M, Batrla R, Vergallo A, Blennow K, Dage J, Schindler SE. Blood-based biomarkers for Alzheimer's disease: Current state and future use in a transformed global healthcare landscape. Neuron 2023; 111:2781-2799. [PMID: 37295421 PMCID: PMC10720399 DOI: 10.1016/j.neuron.2023.05.017] [Citation(s) in RCA: 31] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 03/03/2023] [Accepted: 05/19/2023] [Indexed: 06/12/2023]
Abstract
Timely detection of the pathophysiological changes and cognitive impairment caused by Alzheimer's disease (AD) is increasingly pressing because of the advent of biomarker-guided targeted therapies that may be most effective when provided early in the disease. Currently, diagnosis and management of early AD are largely guided by clinical symptoms. FDA-approved neuroimaging and cerebrospinal fluid biomarkers can aid detection and diagnosis, but the clinical implementation of these testing modalities is limited because of availability, cost, and perceived invasiveness. Blood-based biomarkers (BBBMs) may enable earlier and faster diagnoses as well as aid in risk assessment, early detection, prognosis, and management. Herein, we review data on BBBMs that are closest to clinical implementation, particularly those based on measures of amyloid-β peptides and phosphorylated tau species. We discuss key parameters and considerations for the development and potential deployment of these BBBMs under different contexts of use and highlight challenges at the methodological, clinical, and regulatory levels.
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Affiliation(s)
- Harald Hampel
- Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA.
| | - Yan Hu
- Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA.
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Pam Quirk Brain Health and Biomarker Laboratory, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas (UNLV), Las Vegas, NV, USA
| | - Soeren Mattke
- Center for Improving Chronic Illness Care, University of Southern California, Los Angeles, CA, USA
| | - Takeshi Iwatsubo
- Department of Neuropathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Akinori Nakamura
- Department of Biomarker Research, National Center for Geriatrics and Gerontology, Obu, Japan; Department of Cognition and Behavior Science, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Bruno Vellas
- University Paul Sabatier, Gérontopôle, Toulouse University Hospital, UMR INSERM 1285, Toulouse, France
| | - Sid O'Bryant
- Institute for Translational Research, Texas College of Osteopathic Medicine, Department of Family Medicine, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Leslie M Shaw
- Perelman School of Medicine, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Min Cho
- Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA
| | - Richard Batrla
- Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA
| | - Andrea Vergallo
- Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Jeffrey Dage
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
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49
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Taneva SG, Todinova S, Andreeva T. Morphometric and Nanomechanical Screening of Peripheral Blood Cells with Atomic Force Microscopy for Label-Free Assessment of Alzheimer's Disease, Parkinson's Disease, and Amyotrophic Lateral Sclerosis. Int J Mol Sci 2023; 24:14296. [PMID: 37762599 PMCID: PMC10531602 DOI: 10.3390/ijms241814296] [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: 08/11/2023] [Revised: 09/09/2023] [Accepted: 09/16/2023] [Indexed: 09/29/2023] Open
Abstract
Neurodegenerative disorders (NDDs) are complex, multifactorial disorders with significant social and economic impact in today's society. NDDs are predicted to become the second-most common cause of death in the next few decades due to an increase in life expectancy but also to a lack of early diagnosis and mainly symptomatic treatment. Despite recent advances in diagnostic and therapeutic methods, there are yet no reliable biomarkers identifying the complex pathways contributing to these pathologies. The development of new approaches for early diagnosis and new therapies, together with the identification of non-invasive and more cost-effective diagnostic biomarkers, is one of the main trends in NDD biomedical research. Here we summarize data on peripheral biomarkers, biofluids (cerebrospinal fluid and blood plasma), and peripheral blood cells (platelets (PLTs) and red blood cells (RBCs)), reported so far for the three most common NDDs-Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). PLTs and RBCs, beyond their primary physiological functions, are increasingly recognized as valuable sources of biomarkers for NDDs. Special attention is given to the morphological and nanomechanical signatures of PLTs and RBCs as biophysical markers for the three pathologies. Modifications of the surface nanostructure and morphometric and nanomechanical signatures of PLTs and RBCs from patients with AD, PD, and ALS have been revealed by atomic force microscopy (AFM). AFM is currently experiencing rapid and widespread adoption in biomedicine and clinical medicine, in particular for early diagnostics of various medical conditions. AFM is a unique instrument without an analog, allowing the generation of three-dimensional cell images with extremely high spatial resolution at near-atomic scale, which are complemented by insights into the mechanical properties of cells and subcellular structures. Data demonstrate that AFM can distinguish between the three pathologies and the normal, healthy state. The specific PLT and RBC signatures can serve as biomarkers in combination with the currently used diagnostic tools. We highlight the strong correlation of the morphological and nanomechanical signatures between RBCs and PLTs in PD, ALS, and AD.
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Affiliation(s)
- Stefka G. Taneva
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, “Acad. G. Bontchev” Str. 21, 1113 Sofia, Bulgaria; (S.T.); (T.A.)
| | - Svetla Todinova
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, “Acad. G. Bontchev” Str. 21, 1113 Sofia, Bulgaria; (S.T.); (T.A.)
| | - Tonya Andreeva
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, “Acad. G. Bontchev” Str. 21, 1113 Sofia, Bulgaria; (S.T.); (T.A.)
- Faculty of Life Sciences, Reutlingen University, Alteburgstraße 150, D-72762 Reutlingen, Germany
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50
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Brum WS, Cullen NC, Janelidze S, Ashton NJ, Zimmer ER, Therriault J, Benedet AL, Rahmouni N, Tissot C, Stevenson J, Servaes S, Triana-Baltzer G, Kolb HC, Palmqvist S, Stomrud E, Rosa-Neto P, Blennow K, Hansson O. A two-step workflow based on plasma p-tau217 to screen for amyloid β positivity with further confirmatory testing only in uncertain cases. NATURE AGING 2023; 3:1079-1090. [PMID: 37653254 PMCID: PMC10501903 DOI: 10.1038/s43587-023-00471-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 07/18/2023] [Indexed: 09/02/2023]
Abstract
Cost-effective strategies for identifying amyloid-β (Aβ) positivity in patients with cognitive impairment are urgently needed with recent approvals of anti-Aβ immunotherapies for Alzheimer's disease (AD). Blood biomarkers can accurately detect AD pathology, but it is unclear whether their incorporation into a full diagnostic workflow can reduce the number of confirmatory cerebrospinal fluid (CSF) or positron emission tomography (PET) tests needed while accurately classifying patients. We evaluated a two-step workflow for determining Aβ-PET status in patients with mild cognitive impairment (MCI) from two independent memory clinic-based cohorts (n = 348). A blood-based model including plasma tau protein 217 (p-tau217), age and APOE ε4 status was developed in BioFINDER-1 (area under the curve (AUC) = 89.3%) and validated in BioFINDER-2 (AUC = 94.3%). In step 1, the blood-based model was used to stratify the patients into low, intermediate or high risk of Aβ-PET positivity. In step 2, we assumed referral only of intermediate-risk patients to CSF Aβ42/Aβ40 testing, whereas step 1 alone determined Aβ-status for low- and high-risk groups. Depending on whether lenient, moderate or stringent thresholds were used in step 1, the two-step workflow overall accuracy for detecting Aβ-PET status was 88.2%, 90.5% and 92.0%, respectively, while reducing the number of necessary CSF tests by 85.9%, 72.7% and 61.2%, respectively. In secondary analyses, an adapted version of the BioFINDER-1 model led to successful validation of the two-step workflow with a different plasma p-tau217 immunoassay in patients with cognitive impairment from the TRIAD cohort (n = 84). In conclusion, using a plasma p-tau217-based model for risk stratification of patients with MCI can substantially reduce the need for confirmatory testing while accurately classifying patients, offering a cost-effective strategy to detect AD in memory clinic settings.
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Affiliation(s)
- Wagner S Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
| | - Nicholas C Cullen
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience, King's College London, London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia, South London and Maudsley NHS Foundation, London, UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Eduardo R Zimmer
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Department of Pharmacology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Graduate Program in Biological Sciences: Pharmacology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- McGill Centre for Studies in Aging, McGill University, Montreal, Québec, Canada
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Québec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Québec, Canada
| | - Andrea L Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Québec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Québec, Canada
| | - Cécile Tissot
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Québec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Québec, Canada
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Québec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Québec, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Québec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Québec, Canada
| | | | - Hartmuth C Kolb
- Neuroscience Biomarkers, Janssen Research & Development, La Jolla, CA, USA
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Québec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Québec, Canada
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, 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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