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Song Y, Kim H, Lee J, Kim K. Oxygen-enriching triphase platform for reliable sensing of femtomolar Alzheimer's neurofilament lights. Biosens Bioelectron 2024; 260:116431. [PMID: 38815462 DOI: 10.1016/j.bios.2024.116431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Revised: 05/21/2024] [Accepted: 05/24/2024] [Indexed: 06/01/2024]
Abstract
Accurate quantification of neurofilament lights (NfLs), a prognostic blood biomarker, is highly required to predict neurodegeneration in the presymptomatic stages of Alzheimer's disease. Here, we report self-oxygen-enriching coral structures with triphase interfaces for the label-free photocathodic detection of NfLs in blood plasma with femtomolar sensitivities and high reliability. In conventional photocathodic immunoassays, the poor solubility and sluggish diffusion rate of the dissolved oxygen serving as electron acceptors have necessitated the incorporation of additional electron acceptors or aeration procedures. To address the challenge, we designed the coral-like copper bismuth oxides (CBO) with robust solid-liquid-air contact boundaries that enrich the interfacial oxygen levels without an external aeration source. By optimally assembling the perfluorododecyltrichlorosilane (FTCS) and platinum (Pt) co-catalysts into the silver-doped CBO (Ag:CBO), the stable solid-liquid-air contact boundaries were formed within the sensor interfaces, which allowed for the abundant supply of air phase oxygen through an air pocket connected to the atmosphere. The Pt/FTCS-Ag:CBO exhibited the stable background signals independent of the dissolved oxygen fluctuations and amplified photocurrent signals by 1.76-fold, which were attributed to the elevated interfacial oxygen levels and 11.15 times-lowered mass transport resistance. Under the illumination of white light-emitting diode, the oxygen-enriching photocathodic sensor composed of Pt/FTCS-Ag:CBO conjugated with NfLs-specific antibodies precisely quantified the NfLs in plasma with a low coefficient of variation (≤2.97%), a high degree of recovery (>97.0%), and a limit of detection of 40.38 fg/mL, which was 140 times lower than the typical photocathodic sensor with diphase interfaces.
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Affiliation(s)
- Yunji Song
- Department of Fiber Convergence Material Engineering, Dankook University, Gyeonggi-Do, 16890, Republic of Korea
| | - Hayeon Kim
- Department of Fiber Convergence Material Engineering, Dankook University, Gyeonggi-Do, 16890, Republic of Korea
| | - Joonseok Lee
- Department of Chemistry, Hanyang University, Seoul, 04763, Republic of Korea.
| | - Kayoung Kim
- Department of Fiber Convergence Material Engineering, Dankook University, Gyeonggi-Do, 16890, Republic of Korea.
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Li A, Zhao R, Zhang M, Sun P, Cai Y, Zhu L, Kung H, Han Y, Wang X, Guo T. [ 18F]-D3FSP β-amyloid PET imaging in older adults and alzheimer's disease. Eur J Nucl Med Mol Imaging 2024:10.1007/s00259-024-06835-2. [PMID: 38976036 DOI: 10.1007/s00259-024-06835-2] [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: 12/06/2023] [Accepted: 07/04/2024] [Indexed: 07/09/2024]
Abstract
PURPOSE [18F]-D3FSP is a new β-amyloid (Aβ) PET imaging tracer designed to decrease nonspecific signals in the brain by reducing the formation of the N-demethylated product. However, its optimal reference region for calculating the standardized uptake value ratio (SUVR) and its relation to the well-established biomarkers of Alzheimer's disease (AD) are still unclear. METHODS We recruited 203 participants from the Greater Bay Area Healthy Aging Brain Study (GHABS) to undergo [18F]-D3FSP Aβ PET imaging. We analyzed plasma Aβ42/Aβ40, p-Tau181, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) using the Simoa platform. We compared the standardized uptake value (SUV) of five reference regions (cerebellum, cerebellum cortex, brainstem/PONs, white matter, composite of the four regions above) and AD typical cortical region (COMPOSITE) SUVR among different clinical groups. The association of D3FSP SUVR with plasma biomarkers, imaging biomarkers, and cognition was also investigated. RESULTS Brainstem/PONs SUV showed the lowest fluctuation across diagnostic groups, and COMPOSITE D3FSP SUVR had an enormous effect distinguishing cognitively impaired (CI) individuals from cognitively unimpaired (CU) individuals. COMPOSITE SUVR (Referred to brainstem/PONs) was positively correlated with p-Tau181 (p < 0.001), GFAP (p < 0.001), NfL (p = 0.014) in plasma and temporal-metaROI tau deposition (p < 0.001), and negatively related to plasma Aβ42/Aβ40 (p < 0.001), temporal-metaROI cortical thickness (p < 0.01), residual hippocampal volume (p < 0.001) and cognition (p < 0.001). The voxel-wise analysis replicated these findings. CONCLUSION This study suggests brainstem/PONs as an optimal reference region for calculating D3FSP SUVR to quantify cortical Aβ plaques in the brain. [18F]-D3FSP could distinguish CI from CU and strongly correlates with well-established plasma biomarkers, tau PET, neurodegeneration, and cognitive decline. However, future head-to-head comparisons of [18F]-D3FSP PET images with other validated Aβ PET tracers or postmortem results are crucial.
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Affiliation(s)
- Anqi Li
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Ruiyue Zhao
- Department of Nuclear Medicine, The First Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510120, China
| | - Mingkai Zhang
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
| | - Pan Sun
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Yue Cai
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Lin Zhu
- Beijing Normal University, Beijing, 100875, China
| | - Hank Kung
- University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Ying Han
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
- Department of Neurology, Xuanwu Hospital of Capital Medical University, Beijing, 100053, China
- School of Biomedical Engineering, Hainan University, Haikou, 570228, China
- National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China
| | - Xinlu Wang
- Department of Nuclear Medicine, The First Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510120, China.
- Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, 100053, China.
| | - Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China.
- Institute of Biomedical Engineering, Shenzhen Graduate School, Peking University, Shenzhen, 518055, China.
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Hu Q, Shi M, Li Y, Zhao X. Elevated plasma neurofilament light was associated with multi-modal neuroimaging features in Alzheimer's disease signature regions and predicted future tau deposition. BMC Neurol 2024; 24:236. [PMID: 38971733 PMCID: PMC11227162 DOI: 10.1186/s12883-024-03728-7] [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: 02/10/2024] [Accepted: 06/14/2024] [Indexed: 07/08/2024] Open
Abstract
BACKGROUND Neurofilament Light (NfL) is a biomarker for early neurodegeneration in Alzheimer's disease (AD). This study aims to examine the association between plasma NfL and multi-modal neuroimaging features across the AD spectrum and whether NfL predicts future tau deposition. METHODS The present study recruited 517 participants comprising Aβ negative cognitively normal (CN-) participants (n = 135), Aβ positive cognitively normal (CN +) participants (n = 64), individuals with amnestic mild cognitive impairment (aMCI) (n = 212), and those diagnosed with AD dementia (n = 106). All the participants underwent multi-modal neuroimaging examinations. Cross-sectional and longitudinal associations between plasma NfL and multi-modal neuro-imaging features were evaluated using partial correlation analysis and linear mixed effects models. We also used linear regression analysis to investigate the association of baseline plasma NfL with future PET tau load. Mediation analysis was used to explore whether the effect of NfL on cognition was mediated by these imaging biomarkers. RESULTS The results showed that baseline NfL levels and the rate of change were associated with Aβ deposition, brain atrophy, brain connectome, glucose metabolism, and brain perfusion in AD signature regions (P<0.05). In both Aβ positive CN and MCI participants, baseline NfL showed a significant predictive value of elevating tau burden in the left medial orbitofrontal cortex and para-hippocampus (β = 0.336, P = 0.032; β = 0.313, P = 0.047). Lastly, the multi-modal neuroimaging features mediated the association between plasma NfL and cognitive performance. CONCLUSIONS The study supports the association between plasma NfL and multi-modal neuroimaging features in AD-vulnerable regions and its predictive value for future tau deposition.
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Affiliation(s)
- Qili Hu
- Department of Imaging, The Fifth People's Hospital of Shanghai, Fudan University, No.128 Ruili Road, Minhang District, Shanghai, 200240, China
| | - Mengqiu Shi
- Department of Imaging, The Fifth People's Hospital of Shanghai, Fudan University, No.128 Ruili Road, Minhang District, Shanghai, 200240, China
| | - Yunfei Li
- Department of Imaging, The Fifth People's Hospital of Shanghai, Fudan University, No.128 Ruili Road, Minhang District, Shanghai, 200240, China
| | - Xiaohu Zhao
- Department of Imaging, The Fifth People's Hospital of Shanghai, Fudan University, No.128 Ruili Road, Minhang District, Shanghai, 200240, China.
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Singh NA, Alnobani A, Graff‐Radford J, Machulda MM, Mielke MM, Schwarz CG, Senjem ML, Jack CR, Lowe VJ, Kanekiyo T, Josephs KA, Whitwell JL. Relationships between PET and blood plasma biomarkers in corticobasal syndrome. Alzheimers Dement 2024; 20:4765-4774. [PMID: 38885334 PMCID: PMC11247700 DOI: 10.1002/alz.13914] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 04/26/2024] [Accepted: 04/28/2024] [Indexed: 06/20/2024]
Abstract
INTRODUCTION Corticobasal syndrome (CBS) can result from underlying Alzheimer's disease (AD) pathologies. Little is known about the utility of blood plasma metrics to predict positron emission tomography (PET) biomarker-confirmed AD in CBS. METHODS A cohort of eighteen CBS patients (8 amyloid beta [Aβ]+; 10 Aβ-) and 8 cognitively unimpaired (CU) individuals underwent PET imaging and plasma analysis. Plasma concentrations were compared using a Kruskal-Wallis test. Spearman correlations assessed relationships between plasma concentrations and PET uptake. RESULTS CBS Aβ+ group showed a reduced Aβ42/40 ratio, with elevated phosphorylated tau (p-tau)181, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) concentrations, while CBS Aβ- group only showed elevated NfL concentration compared to CU. Both p-tau181 and GFAP were able to differentiate CBS Aβ- from CBS Aβ+ and showed positive associations with Aβ and tau PET uptake. DISCUSSION This study supports use of plasma p-tau181 and GFAP to detect AD in CBS. NfL shows potential as a non-specific disease biomarker of CBS regardless of underlying pathology. HIGHLIGHTS Plasma phosphorylated tau (p-tau)181 and glial fibrillary acidic protein (GFAP) concentrations differentiate corticobasal syndrome (CBS) amyloid beta (Aβ)- from CBS Aβ+. Plasma neurofilament light concentrations are elevated in CBS Aβ- and Aβ+ compared to controls. Plasma p-tau181 and GFAP concentrations were associated with Aβ and tau positron emission tomography (PET) uptake. Aβ42/40 ratio showed a negative correlation with Aβ PET uptake.
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Affiliation(s)
| | - Alla Alnobani
- Department of Neuroscience, Mayo ClinicJacksonvilleFloridaUSA
| | | | - Mary M. Machulda
- Department of Psychiatry & Psychology, Mayo ClinicRochesterMinnesotaUSA
| | - Michelle M. Mielke
- Department of Epidemiology and PreventionWake Forest UniversityWinston‐SalemNorth CarolinaUSA
| | | | | | | | - Val J. Lowe
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
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Rudolph MD, Sutphen CL, Register TC, Whitlow CT, Solingapuram Sai KK, Hughes TM, Bateman JR, Dage JL, Russ KA, Mielke MM, Craft S, Lockhart SN. Associations among plasma, MRI, and amyloid PET biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities in a community-dwelling cohort. Alzheimers Dement 2024; 20:4159-4173. [PMID: 38747525 PMCID: PMC11180870 DOI: 10.1002/alz.13835] [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: 11/08/2023] [Revised: 03/18/2024] [Accepted: 03/19/2024] [Indexed: 06/05/2024]
Abstract
INTRODUCTION We evaluated associations between plasma and neuroimaging-derived biomarkers of Alzheimer's disease and related dementias and the impact of health-related comorbidities. METHODS We examined plasma biomarkers (neurofilament light chain, glial fibrillary acidic protein, amyloid beta [Aβ] 42/40, phosphorylated tau 181) and neuroimaging measures of amyloid deposition (Aβ-positron emission tomography [PET]), total brain volume, white matter hyperintensity volume, diffusion-weighted fractional anisotropy, and neurite orientation dispersion and density imaging free water. Participants were adjudicated as cognitively unimpaired (CU; N = 299), mild cognitive impairment (MCI; N = 192), or dementia (DEM; N = 65). Biomarkers were compared across groups stratified by diagnosis, sex, race, and APOE ε4 carrier status. General linear models examined plasma-imaging associations before and after adjusting for demographics (age, sex, race, education), APOE ε4 status, medications, diagnosis, and other factors (estimated glomerular filtration rate [eGFR], body mass index [BMI]). RESULTS Plasma biomarkers differed across diagnostic groups (DEM > MCI > CU), were altered in Aβ-PET-positive individuals, and were associated with poorer brain health and kidney function. DISCUSSION eGFR and BMI did not substantially impact associations between plasma and neuroimaging biomarkers. HIGHLIGHTS Plasma biomarkers differ across diagnostic groups (DEM > MCI > CU) and are altered in Aβ-PET-positive individuals. Altered plasma biomarker levels are associated with poorer brain health and kidney function. Plasma and neuroimaging biomarker associations are largely independent of comorbidities.
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Affiliation(s)
- Marc D. Rudolph
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Courtney L. Sutphen
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Thomas C. Register
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Christopher T. Whitlow
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Kiran K. Solingapuram Sai
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Timothy M. Hughes
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - James R. Bateman
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Jeffrey L. Dage
- Department Of NeurologyIndiana University School of MedicineIndianapolisIndianaUSA
| | - Kristen A. Russ
- Department Of NeurologyIndiana University School of MedicineIndianapolisIndianaUSA
| | - Michelle M. Mielke
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Suzanne Craft
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Samuel N. Lockhart
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
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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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Dark HE, An Y, Duggan MR, Joynes C, Davatzikos C, Erus G, Lewis A, Moghekar AR, Resnick SM, Walker KA. Alzheimer's and neurodegenerative disease biomarkers in blood predict brain atrophy and cognitive decline. Alzheimers Res Ther 2024; 16:94. [PMID: 38689358 PMCID: PMC11059745 DOI: 10.1186/s13195-024-01459-y] [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: 11/22/2023] [Accepted: 04/16/2024] [Indexed: 05/02/2024]
Abstract
BACKGROUND Although blood-based biomarkers have been identified as cost-effective and scalable alternatives to PET and CSF markers of neurodegenerative disease, little is known about how these biomarkers predict future brain atrophy and cognitive decline in cognitively unimpaired individuals. Using data from the Baltimore Longitudinal Study of Aging (BLSA), we examined whether plasma biomarkers of Alzheimer's disease (AD) pathology (amyloid-β [Aβ42/40], phosphorylated tau [pTau-181]), astrogliosis (glial fibrillary acidic protein [GFAP]), and neuronal injury (neurofilament light chain [NfL]) were associated with longitudinal brain volume loss and cognitive decline. Additionally, we determined whether sex, APOEε4 status, and plasma amyloid-β status modified these associations. METHODS Plasma biomarkers were measured using Quanterix SIMOA assays. Regional brain volumes were measured by 3T MRI, and a battery of neuropsychological tests assessed five cognitive domains. Linear mixed effects models adjusted for demographic factors, kidney function, and intracranial volume (MRI analyses) were completed to relate baseline plasma biomarkers to baseline and longitudinal brain volume and cognitive performance. RESULTS Brain volume analyses included 622 participants (mean age ± SD: 70.9 ± 10.2) with an average of 3.3 MRI scans over 4.7 years. Cognitive performance analyses included 674 participants (mean age ± SD: 71.2 ± 10.0) with an average of 3.9 cognitive assessments over 5.7 years. Higher baseline pTau-181 was associated with steeper declines in total gray matter volume and steeper regional declines in several medial temporal regions, whereas higher baseline GFAP was associated with greater longitudinal increases in ventricular volume. Baseline Aβ42/40 and NfL levels were not associated with changes in brain volume. Lower baseline Aβ42/40 (higher Aβ burden) was associated with a faster decline in verbal memory and visuospatial performance, whereas higher baseline GFAP was associated with a faster decline in verbal fluency. Results were generally consistent across sex and APOEε4 status. However, the associations of higher pTau-181 with increasing ventricular volume and memory declines were significantly stronger among individuals with higher Aβ burden, as was the association of higher GFAP with memory decline. CONCLUSIONS Among cognitively unimpaired older adults, plasma biomarkers of AD pathology (pTau-181) and astrogliosis (GFAP), but not neuronal injury (NfL), serve as markers of future brain atrophy and cognitive decline.
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Affiliation(s)
- Heather E Dark
- Laboratory of Behavioral Neuroscience, National Institute On Aging, NIH BRC BG RM 04B311, 251 Bayview Blvd, Baltimore, MD, 21224, USA.
| | - Yang An
- Laboratory of Behavioral Neuroscience, National Institute On Aging, NIH BRC BG RM 04B311, 251 Bayview Blvd, Baltimore, MD, 21224, USA
| | - Michael R Duggan
- Laboratory of Behavioral Neuroscience, National Institute On Aging, NIH BRC BG RM 04B311, 251 Bayview Blvd, Baltimore, MD, 21224, USA
| | - Cassandra Joynes
- Laboratory of Behavioral Neuroscience, National Institute On Aging, NIH BRC BG RM 04B311, 251 Bayview Blvd, Baltimore, MD, 21224, USA
| | | | - Guray Erus
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Alexandria Lewis
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Abhay R Moghekar
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute On Aging, NIH BRC BG RM 04B311, 251 Bayview Blvd, Baltimore, MD, 21224, USA
| | - Keenan A Walker
- Laboratory of Behavioral Neuroscience, National Institute On Aging, NIH BRC BG RM 04B311, 251 Bayview Blvd, Baltimore, MD, 21224, USA.
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Ferrari-Souza JP, Brum WS, Hauschild LA, Da Ros LU, Ferreira PCL, Bellaver B, Leffa DT, Bieger A, Tissot C, Lussier FZ, De Bastiani MA, Povala G, Benedet AL, Therriault J, Wang YT, Ashton NJ, Zetterberg H, Blennow K, Martins SO, Souza DO, Rosa-Neto P, Karikari TK, Pascoal TA, Zimmer ER. Vascular risk burden is a key player in the early progression of Alzheimer's disease. Neurobiol Aging 2024; 136:88-98. [PMID: 38335912 DOI: 10.1016/j.neurobiolaging.2023.12.008] [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: 02/14/2023] [Revised: 12/21/2023] [Accepted: 12/29/2023] [Indexed: 02/12/2024]
Abstract
Understanding whether vascular risk factors (VRFs) synergistically potentiate Alzheimer's disease (AD) progression is important in the context of emerging treatments for preclinical AD. In a group of 503 cognitively unimpaired individuals, we tested whether VRF burden interacts with AD pathophysiology to accelerate neurodegeneration and cognitive decline. Baseline VRF burden was calculated considering medical data and AD pathophysiology was assessed based on cerebrospinal fluid (CSF) amyloid-β1-42 (Aβ1-42) and tau phosphorylated at threonine 181 (p-tau181). Neurodegeneration was assessed with plasma neurofilament light (NfL) and global cognition with the modified version of the Preclinical Alzheimer's Cognitive Composite. The mean (SD) age of participants was 72.9 (6.1) years, and 220 (43.7%) were men. Linear mixed-effects models revealed that an elevated VRF burden synergistically interacted with AD pathophysiology to drive longitudinal plasma NfL increase and cognitive decline. Additionally, VRF burden was not associated with CSF Aβ1-42 or p-tau181 changes over time. Our results suggest that VRF burden and AD pathophysiology are independent processes; however, they synergistically lead to neurodegeneration and cognitive deterioration. In preclinical stages, the combination of therapies targeting VRFs and AD pathophysiology might potentiate treatment outcomes.
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Affiliation(s)
- João Pedro Ferrari-Souza
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil; Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Wagner S Brum
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil; Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Lucas A Hauschild
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Lucas U Da Ros
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Pâmela C L Ferreira
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Bruna Bellaver
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil; Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Douglas T Leffa
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andrei Bieger
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Cécile Tissot
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada
| | - Firoza Z Lussier
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada
| | - Marco Antônio De Bastiani
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Guilherme Povala
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Andréa L Benedet
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden; Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada
| | - Yi-Ting Wang
- Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden; Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway; Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 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; UW Department of Medicine, School of Medicine and Public Health, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Sheila O Martins
- Department of Neurology, Hospital de Clínicas de Porto Alegre, Porto Alegre, RS, Brazil
| | - Diogo O Souza
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, Alzheimer's Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest-de-l'Île-de-Montréal; Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, Canada
| | - Thomas K Karikari
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Tharick A Pascoal
- Department of Psychiatry, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA; Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Eduardo R Zimmer
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil; Department of Pharmacology, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil; Graduate Program in Biological Sciences: Pharmacology and Therapeuctis, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil.
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9
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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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10
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Mazzeo S, Ingannato A, Giacomucci G, Bagnoli S, Cavaliere A, Moschini V, Balestrini J, Morinelli C, Galdo G, Emiliani F, Piazzesi D, Crucitti C, Frigerio D, Polito C, Berti V, Padiglioni S, Sorbi S, Nacmias B, Bessi V. The role of plasma neurofilament light chain and glial fibrillary acidic protein in subjective cognitive decline and mild cognitive impairment. Neurol Sci 2024; 45:1031-1039. [PMID: 37723371 PMCID: PMC10857957 DOI: 10.1007/s10072-023-07065-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2023] [Accepted: 09/06/2023] [Indexed: 09/20/2023]
Abstract
INTRODUCTION AND AIM NfL and GFAP are promising blood-based biomarkers for Alzheimer's disease. However, few studies have explored plasma GFAP in the prodromal and preclinical stages of AD. In our cross-sectional study, our aim is to investigate the role of these biomarkers in the earliest stages of AD. MATERIALS AND METHODS We enrolled 40 patients (11 SCD, 21 MCI, 8 AD dementia). All patients underwent neurological and neuropsychological examinations, analysis of CSF biomarkers (Aβ42, Aβ42/Aβ40, p-tau, t-tau), Apolipoprotein E (APOE) genotype analysis and measurement of plasma GFAP and NfL concentrations. Patients were categorized according to the ATN system as follows: normal AD biomarkers (NB), carriers of non-Alzheimer's pathology (non-AD), prodromal AD, or AD with dementia (AD-D). RESULTS GFAP was lower in NB compared to prodromal AD (p = 0.003, d = 1.463) and AD-D (p = 0.002, d = 1.695). NfL was lower in NB patients than in AD-D (p = 0.011, d = 1.474). NfL demonstrated fair accuracy (AUC = 0.718) in differentiating between NB and prodromal AD, with a cut-off value of 11.65 pg/mL. GFAP showed excellent accuracy in differentiating NB from prodromal AD (AUC = 0.901) with a cut-off level of 198.13 pg/mL. CONCLUSIONS GFAP exhibited excellent accuracy in distinguishing patients with normal CSF biomarkers from those with prodromal AD. Our results support the use of this peripheral biomarker for detecting AD in patients with subjective and objective cognitive decline.
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Affiliation(s)
- Salvatore Mazzeo
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
- Research and Innovation Centre for Dementia-CRIDEM, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Assunta Ingannato
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Giulia Giacomucci
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Arianna Cavaliere
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Valentina Moschini
- Research and Innovation Centre for Dementia-CRIDEM, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Juri Balestrini
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Carmen Morinelli
- Research and Innovation Centre for Dementia-CRIDEM, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Giulia Galdo
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Filippo Emiliani
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Diletta Piazzesi
- Research and Innovation Centre for Dementia-CRIDEM, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
| | - Chiara Crucitti
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Daniele Frigerio
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | | | - Valentina Berti
- Department of Biomedical, Experimental and Clinical Sciences "Mario Serio", University of Florence, 50134, Florence, Italy
| | - Sonia Padiglioni
- Research and Innovation Centre for Dementia-CRIDEM, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
- Regional Referral Centre for Relational Criticalities- 50139, Tuscany Region, Italy
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
- Research and Innovation Centre for Dementia-CRIDEM, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy.
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy.
| | - Valentina Bessi
- Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
- Research and Innovation Centre for Dementia-CRIDEM, Azienda Ospedaliero-Universitaria Careggi, Florence, Italy
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11
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Vrillon A, Ashton NJ, Karikari TK, Götze K, Cognat E, Dumurgier J, Lilamand M, Zetterberg H, Blennow K, Paquet C. Comparison of CSF and plasma NfL and pNfH for Alzheimer's disease diagnosis: a memory clinic study. J Neurol 2024; 271:1297-1310. [PMID: 37950758 DOI: 10.1007/s00415-023-12066-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/11/2023] [Accepted: 10/13/2023] [Indexed: 11/13/2023]
Abstract
Plasma neurofilament light chain (NfL) is a promising biomarker of axonal damage for the diagnosis of neurodegenerative diseases. Phosphorylated neurofilament heavy chain (pNfH) has demonstrated its value in motor neuron diseases diagnosis, but has less been explored for dementia diagnosis. In a cross-sectional study, we compared cerebrospinal fluid (CSF) and plasma NfL and pNfH levels in n = 188 patients from Lariboisière Hospital, Paris, France, including AD patients at mild cognitive impairment stage (AD-MCI, n = 36) and dementia stage (n = 64), non-AD MCI (n = 38), non-AD dementia (n = 28) patients and control subjects (n = 22). Plasma NfL, plasma and CSF pNfH levels were measured using Simoa and CSF NfL using ELISA. The correlation between CSF and plasma levels was stronger for NfL than pNfH (rho = 0.77 and rho = 0.52, respectively). All neurofilament markers were increased in AD-MCI, AD dementia and non-AD dementia groups compared with controls. CSF NfL, CSF pNfH and plasma NfL showed high performance to discriminate AD at both MCI and dementia stages from control subjects [AUC (area under the curve) = 0.82-0.91]. Plasma pNfH displayed overall lower AUCs for discrimination between groups compared with CSF pNfH. Neurofilament markers showed similar moderate association with cognition. NfL levels displayed significant association with mediotemporal lobe atrophy and white matter lesions in the AD group. Our results suggest that CSF NfL and pNfH as well as plasma NfL levels display equivalent performance in both positive and differential AD diagnosis in memory clinic settings. In contrast to motoneuron disorders, plasma pNfH did not demonstrate added value as compared with plasma NfL.
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Affiliation(s)
- Agathe Vrillon
- Cognitive Neurology Center, Lariboisière Fernand Widal Hospital, Assistance Publique Hôpitaux de Paris, Université Paris Cité, Paris, France.
- INSERM U1144, Therapeutic Optimization in Neuropsychopharmacology, Paris, France.
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Maurice Wohl Institute Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Karl Götze
- INSERM U1144, Therapeutic Optimization in Neuropsychopharmacology, Paris, France
| | - Emmanuel Cognat
- Cognitive Neurology Center, Lariboisière Fernand Widal Hospital, Assistance Publique Hôpitaux de Paris, Université Paris Cité, Paris, France
- INSERM U1144, Therapeutic Optimization in Neuropsychopharmacology, Paris, France
| | - Julien Dumurgier
- Cognitive Neurology Center, Lariboisière Fernand Widal Hospital, Assistance Publique Hôpitaux de Paris, Université Paris Cité, Paris, France
| | - Matthieu Lilamand
- Cognitive Neurology Center, Lariboisière Fernand Widal Hospital, Assistance Publique Hôpitaux de Paris, Université Paris Cité, Paris, France
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Maurice Wohl Institute Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Claire Paquet
- Cognitive Neurology Center, Lariboisière Fernand Widal Hospital, Assistance Publique Hôpitaux de Paris, Université Paris Cité, Paris, France
- INSERM U1144, Therapeutic Optimization in Neuropsychopharmacology, Paris, France
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12
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Twait EL, Gerritsen L, Moonen JEF, Verberk IMW, Teunissen CE, Visser PJ, van der Flier WM, Geerlings MI. Plasma Markers of Alzheimer's Disease Pathology, Neuronal Injury, and Astrocytic Activation and MRI Load of Vascular Pathology and Neurodegeneration: The SMART-MR Study. J Am Heart Assoc 2024; 13:e032134. [PMID: 38353228 PMCID: PMC11010072 DOI: 10.1161/jaha.123.032134] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Accepted: 10/23/2023] [Indexed: 02/21/2024]
Abstract
BACKGROUND Two of the main causes for dementia are Alzheimer's disease (AD) and vascular pathology, with most patients showing mixed pathology. Plasma biomarkers for Alzheimer's disease-related pathology have recently emerged, including Aβ (amyloid-beta), p-tau (phosphorylated tau), NfL (neurofilament light), and GFAP (glial fibrillary acidic protein). There is a current gap in the literature regarding whether there is an association between these plasma biomarkers with vascular pathology and neurodegeneration. METHODS AND RESULTS Cross-sectional data from 594 individuals (mean [SD] age: 64 [8] years; 17% female) were included from the SMART-MR (Second Manifestations of Arterial Disease-Magnetic Resonance) study, a prospective cohort study of individuals with a history of arterial disease. Plasma markers were assessed using single molecular array assays (Quanterix). Magnetic resonance imaging markers included white matter hyperintensity volume, presence of infarcts (yes/no), total brain volume, and hippocampal volume assessed on 1.5T magnetic resonance imaging. Linear regressions were performed for each standardized plasma marker with white matter hyperintensity volume, total brain volume, and hippocampal volume as separate outcomes, correcting for age, sex, education, and intracranial volume. Logistic regressions were performed for the presence of lacunar and cortical infarcts. Higher p-tau181 was associated with larger white matter hyperintensity volume (b per SD increase=0.16 [95% CI, 0.06-0.26], P=0.015). Higher NfL (b=-5.63, [95% CI, -8.95 to -2.31], P=0.015) was associated with lower total brain volume and the presence of infarcts (odds ratio [OR], 1.42 [95% CI, 1.13-1.78], P=0.039). Higher GFAP levels were associated with cortical infarcts (OR, 1.45 [95% CI, 1.09-1.92], P=0.010). CONCLUSIONS Plasma biomarkers that have been associated with tau pathology, axonal injury, and astrocytic activation are related to magnetic resonance imagingmarkers of vascular pathology and neurodegeneration in patients with manifest arterial disease.
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Affiliation(s)
- Emma L. Twait
- Julius Center for Health Sciences and Primary CareUniversity Medical Center Utrecht and Utrecht UniversityUtrechtThe Netherlands
- Amsterdam UMC location Vrije Universiteit Amsterdam, Department of General PracticeAmsterdamThe Netherlands
- Amsterdam Public Health, Aging & Later Life, and Personalized MedicineAmsterdamThe Netherlands
- Amsterdam Neuroscience, Neurodegeneration, and Mood, Anxiety, Psychosis, Stress, and SleepAmsterdamThe Netherlands
| | - Lotte Gerritsen
- Department of PsychologyUtrecht UniversityUtrechtThe Netherlands
| | - Justine E. F. Moonen
- Alzheimer Center Amsterdam, Amsterdam UMC location Vrije Universiteit Amsterdam, Neurology, Epidemiology and Data ScienceAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands
| | - Inge M. W. Verberk
- Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands
- Amsterdam UMC location Vrije Universiteit Amsterdam, Neurochemistry Laboratory, Department of Laboratory Medicine,AmsterdamThe Netherlands
| | - Charlotte E. Teunissen
- Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands
- Amsterdam UMC location Vrije Universiteit Amsterdam, Neurochemistry Laboratory, Department of Laboratory Medicine,AmsterdamThe Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Amsterdam UMC location Vrije Universiteit Amsterdam, Neurology, Epidemiology and Data ScienceAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands
| | - Wiesje M. van der Flier
- Alzheimer Center Amsterdam, Amsterdam UMC location Vrije Universiteit Amsterdam, Neurology, Epidemiology and Data ScienceAmsterdamThe Netherlands
- Amsterdam Neuroscience, NeurodegenerationAmsterdamThe Netherlands
- Amsterdam UMC location Vrije Universiteit Amsterdam, Epidemiology and Data ScienceAmsterdamThe Netherlands
| | - Mirjam I. Geerlings
- Julius Center for Health Sciences and Primary CareUniversity Medical Center Utrecht and Utrecht UniversityUtrechtThe Netherlands
- Amsterdam Public Health, Aging & Later Life, and Personalized MedicineAmsterdamThe Netherlands
- Amsterdam Neuroscience, Neurodegeneration, and Mood, Anxiety, Psychosis, Stress, and SleepAmsterdamThe Netherlands
- Amsterdam UMC location University of Amsterdam, Department of General PracticeAmsterdamThe Netherlands
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13
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Hu Q, Shi M, Li Y, Zhao X. Elevated plasma neurofilament light was associated with multi-modal neuroimaging features in Alzheimer's Disease signature regions and predicted future tau deposition. RESEARCH SQUARE 2024:rs.3.rs-3946421. [PMID: 38464117 PMCID: PMC10925409 DOI: 10.21203/rs.3.rs-3946421/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Background Neurofilament Light (NfL) is a biomarker for early neurodegeneration in Alzheimer's disease (AD). This study aims to examine the association between plasma NfL and multi-modal neuroimaging features across the AD spectrum and whether NfL predicts future tau deposition. Methods The present study recruited 517 participants comprising Aβ negative cognitively normal (CN-) participants (n = 135), CN + participants (n = 64), individuals with mild cognitive impairment (MCI) (n = 212), and those diagnosed with AD dementia (n = 106). All the participants underwent multi-modal neuroimaging examinations. Cross-sectional and longitudinal associations between plasma NfL and multi-modal neuro-imaging features were evaluated using partial correlation analysis and linear mixed effects models. We also used linear regression analysis to investigate the association of baseline plasma NfL with future PET tau load. Mediation analysis was used to explore whether the effect of NfL on cognition was mediated by these MRI markers. Results The results showed that baseline NfL levels and the rate of change were associated with Aβ deposition, brain atrophy, brain connectome, glucose metabolism, and brain perfusion in AD signature regions. In both Aβ positive CN and MCI participants, baseline NfL showed a significant predictive value of elevating tau burden in the left medial orbitofrontal cortex and para-hippocampus. Lastly, the multi-modal neuroimaging features mediated the association between plasma NfL and cognitive performance. Conclusions The study supports the association between plasma NfL and multi-modal neuroimaging features in AD-vulnerable regions and its predictive value for future tau deposition.
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Affiliation(s)
- Qili Hu
- The Fifth People's Hospital of Shanghai, Fudan University
| | - Mengqiu Shi
- The Fifth People's Hospital of Shanghai, Fudan University
| | - Yunfei Li
- The Fifth People's Hospital of Shanghai, Fudan University
| | - Xiaohu Zhao
- The Fifth People's Hospital of Shanghai, Fudan University
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14
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Yao W, Zhou H, Zhang X, Chen H, Bai F. Inflammation affects dynamic functional network connectivity pattern changes via plasma NFL in cognitive impairment patients. CNS Neurosci Ther 2024; 30:e14391. [PMID: 37545369 PMCID: PMC10848064 DOI: 10.1111/cns.14391] [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: 05/02/2023] [Revised: 07/03/2023] [Accepted: 07/26/2023] [Indexed: 08/08/2023] Open
Abstract
BACKGROUND Plasma neurofilament light chain (NFL) is a biomarker of inflammation and neurodegenerative diseases such as Alzheimer's disease (AD). However, the underlying neural mechanisms by which NFL affects cognitive function remain unclear. In this study, we investigated the effects of inflammation on cognitive integrity in patients with cognitive impairment through the functional interaction of plasma NFL with large-scale brain networks. METHODS This study included 29 cognitively normal, 55 LowNFL patients, and 55 HighNFL patients. Group independent component analysis (ICA) was applied to the resting-state fMRI data, and 40 independent components (IC) were extracted for the whole brain. Next, the dynamic functional network connectivity (dFNC) of each subject was estimated using the sliding-window method and k-means clustering, and five dynamic functional states were identified. Finally, we applied mediation analysis to investigate the relationship between plasma NFL and dFNC indicators and cognitive scales. RESULTS The present study explored the dynamics of whole-brain FNC in controls and LowNFL and HighNFL patients and highlighted the temporal properties of dFNC states in relation to psychological scales. A potential mechanism for the association between dFNC indicators and NFL levels in cognitively impaired patients. CONCLUSIONS Our findings suggested the decreased ability of information processing and communication in the HighNFL group, which helps us to understand their abnormal cognitive functions clinically. Characteristic changes in the inflammation-coupled dynamic brain network may provide alternative biomarkers for the assessment of disease severity in cognitive impairment patients.
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Affiliation(s)
- Weina Yao
- Department of NeurologyZhongnan Hospital of Wuhan UniversityWuhanChina
- Geriatric Medicine CenterTaikang Xianlin Drum Tower Hospital Clinical College of Wuhan UniversityNanjingChina
| | - Huijuan Zhou
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western MedicineNanjing University of Chinese MedicineNanjingChina
| | - Xiao Zhang
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western MedicineNanjing University of Chinese MedicineNanjingChina
| | - Haifeng Chen
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western MedicineNanjing University of Chinese MedicineNanjingChina
| | - Feng Bai
- Geriatric Medicine CenterTaikang Xianlin Drum Tower Hospital Clinical College of Wuhan UniversityNanjingChina
- Geriatric Medicine CenterTaikang Xianlin Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing UniversityNanjingChina
- Department of NeurologyNanjing Drum Tower Hospital, Affiliated Hospital of Medical School, Nanjing UniversityNanjingChina
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15
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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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16
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Jung Y, Damoiseaux JS. The potential of blood neurofilament light as a marker of neurodegeneration for Alzheimer's disease. Brain 2024; 147:12-25. [PMID: 37540027 DOI: 10.1093/brain/awad267] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 07/22/2023] [Accepted: 07/28/2023] [Indexed: 08/05/2023] Open
Abstract
Over the past several years, there has been a surge in blood biomarker studies examining the value of plasma or serum neurofilament light (NfL) as a biomarker of neurodegeneration for Alzheimer's disease. However, there have been limited efforts to combine existing findings to assess the utility of blood NfL as a biomarker of neurodegeneration for Alzheimer's disease. In addition, we still need better insight into the specific aspects of neurodegeneration that are reflected by the elevated plasma or serum concentration of NfL. In this review, we survey the literature on the cross-sectional and longitudinal relationships between blood-based NfL levels and other, neuroimaging-based, indices of neurodegeneration in individuals on the Alzheimer's continuum. Then, based on the biomarker classification established by the FDA-NIH Biomarker Working group, we determine the utility of blood-based NfL as a marker for monitoring the disease status (i.e. monitoring biomarker) and predicting the severity of neurodegeneration in older adults with and without cognitive decline (i.e. a prognostic or a risk/susceptibility biomarker). The current findings suggest that blood NfL exhibits great promise as a monitoring biomarker because an increased NfL level in plasma or serum appears to reflect the current severity of atrophy, hypometabolism and the decline of white matter integrity, particularly in the brain regions typically affected by Alzheimer's disease. Longitudinal evidence indicates that blood NfL can be useful not only as a prognostic biomarker for predicting the progression of neurodegeneration in patients with Alzheimer's disease but also as a susceptibility/risk biomarker predicting the likelihood of abnormal alterations in brain structure and function in cognitively unimpaired individuals with a higher risk of developing Alzheimer's disease (e.g. those with a higher amyloid-β). There are still limitations to current research, as discussed in this review. Nevertheless, the extant literature strongly suggests that blood NfL can serve as a valuable prognostic and susceptibility biomarker for Alzheimer's disease-related neurodegeneration in clinical settings, as well as in research settings.
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Affiliation(s)
- Youjin Jung
- Department of Psychology, Wayne State University, Detroit, MI 48202, USA
- Institute of Gerontology, Wayne State University, Detroit, MI 48202, USA
| | - Jessica S Damoiseaux
- Department of Psychology, Wayne State University, Detroit, MI 48202, USA
- Institute of Gerontology, Wayne State University, Detroit, MI 48202, USA
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17
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Chimthanawala NMA, Haria A, Sathaye S. Non-invasive Biomarkers for Early Detection of Alzheimer's Disease: a New-Age Perspective. Mol Neurobiol 2024; 61:212-223. [PMID: 37596437 DOI: 10.1007/s12035-023-03578-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 08/14/2023] [Indexed: 08/20/2023]
Abstract
Alzheimer's disease (AD) is a progressive neurodegenerative disorder that primarily affects the elderly population. It gradually leads to memory loss, loss of thinking ability, and an overall cognitive decline. However, exhaustive literature is available to suggest that pathological changes in the brain occur decades before the first clinical symptoms appear. This review provides insight into the non-invasive biomarkers for early detection of AD that have been successfully studied in populations across the globe. These biomarkers have been detected in the blood, saliva, breath, and urine samples. Retinal imaging techniques are also reported. In this study, PubMed and Google scholar were the databases employed using keywords "Alzheimer's disease," "neurodegeneration," "non-invasive biomarkers," "early diagnosis," "blood-based biomarkers," and "preclinical AD," among others. The evaluation of these biomarkers will provide early diagnosis of AD in the preclinical stages due to their positive correlation with brain pathology in AD. Early diagnosis with reliable and timely intervention can effectively manage this disease.
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Affiliation(s)
- Niyamat M A Chimthanawala
- Department of Pharmaceutical Sciences & Technology, Institute of Chemical Technology, Nathalal Parekh Marg, Mumbai, 400019, Maharashtra, India
| | - Akash Haria
- Department of Pharmaceutical Sciences & Technology, Institute of Chemical Technology, Nathalal Parekh Marg, Mumbai, 400019, Maharashtra, India
| | - Sadhana Sathaye
- Department of Pharmaceutical Sciences & Technology, Institute of Chemical Technology, Nathalal Parekh Marg, Mumbai, 400019, Maharashtra, India.
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18
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Mazzeo S, Ingannato A, Giacomucci G, Manganelli A, Moschini V, Balestrini J, Cavaliere A, Morinelli C, Galdo G, Emiliani F, Piazzesi D, Crucitti C, Frigerio D, Polito C, Berti V, Bagnoli S, Padiglioni S, Sorbi S, Nacmias B, Bessi V. Plasma neurofilament light chain predicts Alzheimer's disease in patients with subjective cognitive decline and mild cognitive impairment: A cross-sectional and longitudinal study. Eur J Neurol 2024; 31:e16089. [PMID: 37797300 PMCID: PMC11235835 DOI: 10.1111/ene.16089] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 09/18/2023] [Accepted: 09/21/2023] [Indexed: 10/07/2023]
Abstract
BACKGROUND AND PURPOSE We aimed to evaluate the accuracy of plasma neurofilament light chain (NfL) in predicting Alzheimer's disease (AD) and the progression of cognitive decline in patients with subjective cognitive decline (SCD) and mild cognitive impairment (MCI). METHODS This longitudinal cohort study involved 140 patients (45 with SCD, 73 with MCI, and 22 with AD dementia [AD-D]) who underwent plasma NfL and AD biomarker assessments (cerebrospinal fluid, amyloid positron emission tomography [PET], and 18 F-fluorodeoxyglucose-PET) at baseline. The patients were rated according to the amyloid/tau/neurodegeneration (A/T/N) system and followed up for a mean time of 2.72 ± 0.95 years to detect progression from SCD to MCI and from MCI to AD. Forty-eight patients (19 SCD, 29 MCI) also underwent plasma NfL measurements 2 years after baseline. RESULTS At baseline, plasma NfL detected patients with biomarker profiles consistent with AD (A+/T+/N+ or A+/T+/N-) with high accuracy (area under the curve [AUC] 0.82). We identified cut-off values of 19.45 pg/mL for SCD and 20.45 pg/mL for MCI. During follow-up, nine SCD patients progressed to MCI (progressive SCD [p-SCD]), and 14 MCI patients developed AD dementia (progressive MCI [p-MCI]). The previously identified cut-off values provided good accuracy in identifying p-SCD (80% [95% confidence interval 65.69: 94.31]). The rate of NfL change was higher in p-MCI (3.52 ± 4.06 pg/mL) compared to non-progressive SCD (0.81 ± 1.25 pg/mL) and non-progressive MCI (-0.13 ± 3.24 pg/mL) patients. A rate of change lower than 1.64 pg/mL per year accurately excluded progression from MCI to AD (AUC 0.954). CONCLUSION Plasma NfL concentration and change over time may be a reliable, non-invasive tool to detect AD and the progression of cognitive decline at the earliest stages of the disease.
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Affiliation(s)
- Salvatore Mazzeo
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
| | - Assunta Ingannato
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Giulia Giacomucci
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Alberto Manganelli
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Valentina Moschini
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
| | - Juri Balestrini
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Arianna Cavaliere
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Carmen Morinelli
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
| | - Giulia Galdo
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Filippo Emiliani
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Diletta Piazzesi
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
| | - Chiara Crucitti
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Daniele Frigerio
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | | | - Valentina Berti
- Department of Biomedical, Experimental and Clinical Sciences "Mario Serio"University of FlorenceFlorenceItaly
| | - Silvia Bagnoli
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
| | - Sonia Padiglioni
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
- Regional Referral Centre for Relational Criticalities – 50139Tuscany RegionItaly
| | - Sandro Sorbi
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
- IRCCS Fondazione Don Carlo GnocchiFlorenceItaly
| | - Benedetta Nacmias
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
- IRCCS Fondazione Don Carlo GnocchiFlorenceItaly
| | - Valentina Bessi
- Department of Neuroscience, Psychology, Drug Research and Child HealthUniversity of FlorenceFlorenceItaly
- Research and Innovation Centre for Dementia‐CRIDEMAzienda Ospedaliero‐Universitaria CareggiFlorenceItaly
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19
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Du Y, Zhang Y, Diao J, Fu P, Jiang R, Wang P, Yang H, Zheng X, Zhang L, Bi J, Zhou Q. Decoding the diagnostic potential of T cell repertoires in peripheral blood of patients from amnestic mild cognitive impairment to Alzheimer's disease. FASEB J 2024; 38:e23317. [PMID: 38095240 DOI: 10.1096/fj.202301485r] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 10/13/2023] [Accepted: 11/06/2023] [Indexed: 12/18/2023]
Abstract
Alzheimer's disease (AD) is currently an incurable neurodegenerative disorder and is the most common etiological cause of dementia. Consequently, it has severe burden on its patients and on their caregivers and represents a global health concern. Clinical investigations have indicated that a dysregulation of peripheral T cell immune homeostasis may be involved in the pathogenesis of AD, as well as in the early stages of AD, characterized by mild cognitive impairment (MCI). However, the characteristics and concomitant feasibility of the use of T-cell receptor (TCR) typing for disease diagnosis remains largely unknown. We employed a high-throughput sequencing and multidimensional bioinformatics analyses for the identification of TCR repertoires present in peripheral blood samples of 10 patients with amnestic MCI (aMCI), 10 patients with AD, and 10 healthy controls (HCs). Based on the characteristics of the TCR repertoires in the amount and diversity of combinations of V-J, the spectrum of immune defense, and differentially expressed genes (DEGs), single and specific TCR profiles were observed in the patient samples of aMCI and AD compared to profiles of HCs. In particular, the diversity of TCR clonotypes manifested a pattern of "decreased first and then increased" pattern during the progression from aMCI to AD, a pattern that was not observed in HC samples. Additionally, a total of 46 and 35 amino acid CDR3 sequences with consistent and reverse expressive abundance with diversity of TCR clonotypes were identified, respectively. Taken together, we provide novel and essential preliminary evidence demonstrating the presence of diversity of T cell repertoires from differentially expressed V-J gene segments and amino acid clonotypes using peripheral blood samples from patients with AD, aMCI, and from HC. Such findings have the potential to reveal potential mechanisms through which aMCI progresses to AD and provide a reference for the future development of immune-related diagnoses and therapies for AD.
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Affiliation(s)
- Yansheng Du
- Department of Neurology Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Yichen Zhang
- Department of Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Jiuzhou Diao
- Department of Neurology Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Pengrui Fu
- Department of Neurology Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Runze Jiang
- Department of Translational Medicine Research Institute, Shandong Jingwei Biotechnology Co. Ltd, Jinan, China
| | - Ping Wang
- Department of Neurology Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Hui Yang
- Department of Neurology Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Xiaolei Zheng
- Department of Neurology Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Leisheng Zhang
- Key Laboratory of Molecular Diagnostics and Precision Medicine for Surgical Oncology in Gansu Province & NHC Key Laboratory of Diagnosis and Therapy of Gastrointestinal Tumor, Gansu Provincial Hospital, Lanzhou, China
- Key Laboratory of Radiation Technology and Biophysics, Hefei Institute of Physical Science, Chinese Academy of Sciences, Hefei, China
| | - Jianzhong Bi
- Department of Neurology Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
| | - Qingbo Zhou
- Department of Neurology Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, China
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20
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Srikrishna M, Ashton NJ, Moscoso A, Pereira JB, Heckemann RA, van Westen D, Volpe G, Simrén J, Zettergren A, Kern S, Wahlund L, Gyanwali B, Hilal S, Ruifen JC, Zetterberg H, Blennow K, Westman E, Chen C, Skoog I, Schöll M. CT-based volumetric measures obtained through deep learning: Association with biomarkers of neurodegeneration. Alzheimers Dement 2024; 20:629-640. [PMID: 37767905 PMCID: PMC10916947 DOI: 10.1002/alz.13445] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Revised: 06/29/2023] [Accepted: 08/01/2023] [Indexed: 09/29/2023]
Abstract
INTRODUCTION Cranial computed tomography (CT) is an affordable and widely available imaging modality that is used to assess structural abnormalities, but not to quantify neurodegeneration. Previously we developed a deep-learning-based model that produced accurate and robust cranial CT tissue classification. MATERIALS AND METHODS We analyzed 917 CT and 744 magnetic resonance (MR) scans from the Gothenburg H70 Birth Cohort, and 204 CT and 241 MR scans from participants of the Memory Clinic Cohort, Singapore. We tested associations between six CT-based volumetric measures (CTVMs) and existing clinical diagnoses, fluid and imaging biomarkers, and measures of cognition. RESULTS CTVMs differentiated cognitively healthy individuals from dementia and prodromal dementia patients with high accuracy levels comparable to MR-based measures. CTVMs were significantly associated with measures of cognition and biochemical markers of neurodegeneration. DISCUSSION These findings suggest the potential future use of CT-based volumetric measures as an informative first-line examination tool for neurodegenerative disease diagnostics after further validation. HIGHLIGHTS Computed tomography (CT)-based volumetric measures can distinguish between patients with neurodegenerative disease and healthy controls, as well as between patients with prodromal dementia and controls. CT-based volumetric measures associate well with relevant cognitive, biochemical, and neuroimaging markers of neurodegenerative diseases. Model performance, in terms of brain tissue classification, was consistent across two cohorts of diverse nature. Intermodality agreement between our automated CT-based and established magnetic resonance (MR)-based image segmentations was stronger than the agreement between visual CT and MR imaging assessment.
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21
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Chong JSX, Tan YJ, Koh AJ, Ting SKS, Kandiah N, Ng ASL, Zhou JH. Plasma Neurofilament Light Relates to Divergent Default and Salience Network Connectivity in Alzheimer's Disease and Behavioral Variant Frontotemporal Dementia. J Alzheimers Dis 2024; 99:965-980. [PMID: 38759005 PMCID: PMC11191491 DOI: 10.3233/jad-231251] [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: 03/27/2024] [Indexed: 05/19/2024]
Abstract
Background Alzheimer's disease (AD) and behavioral variant frontotemporal dementia (bvFTD) show differential vulnerability to large-scale brain functional networks. Plasma neurofilament light (NfL), a promising biomarker of neurodegeneration, has been linked in AD patients to glucose metabolism changes in AD-related regions. However, it is unknown whether plasma NfL would be similarly associated with disease-specific functional connectivity changes in AD and bvFTD. Objective Our study examined the associations between plasma NfL and functional connectivity of the default mode and salience networks in patients with AD and bvFTD. Methods Plasma NfL and neuroimaging data from patients with bvFTD (n = 16) and AD or mild cognitive impairment (n = 38; AD + MCI) were analyzed. Seed-based functional connectivity maps of key regions within the default mode and salience networks were obtained and associated with plasma NfL in these patients. RESULTS We demonstrated divergent associations between NfL and functional connectivity in AD + MCI and bvFTD patients. Specifically, AD + MCI patients showed lower default mode network functional connectivity with higher plasma NfL, while bvFTD patients showed lower salience network functional connectivity with higher plasma NfL. Further, lower NfL-related default mode network connectivity in AD + MCI patients was associated with lower Montreal Cognitive Assessment scores and higher Clinical Dementia Rating sum-of-boxes scores, although NfL-related salience network connectivity in bvFTD patients was not associated with Neuropsychiatric Inventory Questionnaire scores. CONCLUSIONS Our findings indicate that plasma NfL is differentially associated with brain functional connectivity changes in AD and bvFTD.
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Affiliation(s)
- Joanna Su Xian Chong
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Human Potential Translational Research Programme and Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Yi Jayne Tan
- Department of Neurology, National Neuroscience Institute, Tan Tock Seng Hospital, Singapore
| | - Amelia Jialing Koh
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Human Potential Translational Research Programme and Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
| | - Simon Kang Seng Ting
- Department of Neurology, National Neuroscience Institute, Tan Tock Seng Hospital, Singapore
| | - Nagaendran Kandiah
- Department of Neurology, National Neuroscience Institute, Tan Tock Seng Hospital, Singapore
| | - Adeline Su Lyn Ng
- Department of Neurology, National Neuroscience Institute, Tan Tock Seng Hospital, Singapore
| | - Juan Helen Zhou
- Centre for Sleep and Cognition & Centre for Translational Magnetic Resonance Research, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Human Potential Translational Research Programme and Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, Singapore
- Integrative Sciences and Engineering Programme (ISEP), NUS Graduate School, National University of Singapore, Singapore
- Department of Electrical and Computer Engineering, National University of Singapore, Singapore
- Neuroscience and Behavioural Disorders Programme, Duke-NUS Medical School, Singapore
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22
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Nabizadeh F, Ward RT, Balabandian M, Kankam SB, Pourhamzeh M. Plasma neurofilament light chain associated with impaired regional cerebral blood flow in healthy individuals. CURRENT JOURNAL OF NEUROLOGY 2023; 22:221-230. [PMID: 38425361 PMCID: PMC10899537 DOI: 10.18502/cjn.v22i4.14526] [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: 06/09/2023] [Accepted: 08/11/2023] [Indexed: 03/02/2024]
Abstract
Background: Recent findings suggest that the plasma axonal structural protein, neurofilament light (NFL) chain, may serve as a potential blood biomarker for early signs of neurodegenerative diseases, such as Alzheimer's disease (AD). Given the need for early detection of neurodegenerative disorders, the current study investigated the associations between regional cerebral blood flow (rCBF) in brain regions associated with neurodegenerative disorders and memory function with plasma NFL in AD, mild cognitive impairment (MCI), and healthy controls (HCs). Methods: We recruited 29 AD, 76 MCI, and 39 HCs from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database in the current cross-sectional study. We used Pearson's correlation models adjusted for the effect of age, sex, and APOE genotype to investigate the association between plasma NFL and rCBF. Results: We found non-significant differences in age (F(2, 141) = 1.304; P = 0.275) and years of education (F(2, 141) = 0.013; P = 0.987). Additionally, we found significant differences between groups in terms of MMSE scores (F(2, 141) = 100.953; P < 0.001). Despite the observation of significantly reduced rCBF in AD and MCI groups versus HCs, we did not detect significant differences in plasma NFL between these groups. We found significant negative associations between plasma NFL and rCBF in various AD-related regions, these findings were only observed after analyses in all participants, and were observed in HCs alone and no significant associations were observed in the AD or MCI groups. Conclusion: These outcomes add to our current understanding surrounding the use of rCBF and plasma NFL biomarkers as tools for early detection and diagnosis of neurodegenerative diseases. A conclusion might be that the association between NFL and impaired rCBF exists before the clinical symptoms appear. Further longitudinal studies with a large sample size should be performed to examine the correlation between plasma NFL and rCBF in order to understand these complex relationships.
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Affiliation(s)
- Fardin Nabizadeh
- Neuroscience Research Group, Universal Scientific Education and Research Network, Tehran, Iran
- School of Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Richard T. Ward
- Center for the Study of Emotion and Attention, University of Florida, Florida, USA
- Department of Psychology, University of Florida, Florida, USA
| | - Mohammad Balabandian
- Neuroscience Research Group, Universal Scientific Education and Research Network, Tehran, Iran
| | | | - Mahsa Pourhamzeh
- Division of Neuroscience, Cellular and Molecular Research Center, Iran University of Medical Sciences, Tehran, Iran
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23
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Ferreira PCL, Therriault J, Tissot C, Ferrari-Souza JP, Benedet AL, Povala G, Bellaver B, Leffa DT, Brum WS, Lussier FZ, Bezgin G, Servaes S, Vermeiren M, Macedo AC, Cabrera A, Stevenson J, Triana-Baltzer G, Kolb H, Rahmouni N, Klunk WE, Lopez O, Villemagne VL, Cohen A, Tudorascu DL, Zimmer ER, Karikari TK, Ashton NJ, Zetterberg H, Blennow K, Gauthier S, Rosa-Neto P, Pascoal TA. Plasma p-tau231 and p-tau217 inform on tau tangles aggregation in cognitively impaired individuals. Alzheimers Dement 2023; 19:4463-4474. [PMID: 37534889 PMCID: PMC10592380 DOI: 10.1002/alz.13393] [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: 02/24/2023] [Revised: 06/15/2023] [Accepted: 06/19/2023] [Indexed: 08/04/2023]
Abstract
INTRODUCTION Phosphorylated tau (p-tau) biomarkers have been recently proposed to represent brain amyloid-β (Aβ) pathology. Here, we evaluated the plasma biomarkers' contribution beyond the information provided by demographics (age and sex) to identify Aβ and tau pathologies in individuals segregated as cognitively unimpaired (CU) and impaired (CI). METHODS We assessed 138 CU and 87 CI with available plasma p-tau231, 217+ , and 181, Aβ42/40, GFAP and Aβ- and tau-PET. RESULTS In CU, only plasma p-tau231 and p-tau217+ significantly improved the performance of the demographics in detecting Aβ-PET positivity, while no plasma biomarker provided additional information to identify tau-PET positivity. In CI, p-tau217+ and GFAP significantly contributed to demographics to identify both Aβ-PET and tau-PET positivity, while p-tau231 only provided additional information to identify tau-PET positivity. DISCUSSION Our results support plasma p-tau231 and p-tau217+ as state markers of early Aβ deposition, but in later disease stages they inform on tau tangle accumulation. HIGHLIGHTS It is still unclear how much plasma biomarkers contribute to identification of AD pathology across the AD spectrum beyond the information already provided by demographics (age + sex). Plasma p-tau231 and p-tau217+ contribute to demographic information to identify brain Aβ pathology in preclinical AD. In CI individuals, plasma p-tau231 contributes to age and sex to inform on the accumulation of tau tangles, while p-tau217+ and GFAP inform on both Aβ deposition and tau pathology.
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Affiliation(s)
- Pamela C. L Ferreira
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Cécile Tissot
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - João Pedro Ferrari-Souza
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
| | - Andréa L. Benedet
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
| | - Guilherme Povala
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Bruna Bellaver
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
| | - Douglas T. Leffa
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Wagner S. Brum
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
| | - Firoza Z. Lussier
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Gleb Bezgin
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Marie Vermeiren
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Arthur C. Macedo
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Arlec Cabrera
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Gallen Triana-Baltzer
- Neuroscience Biomarkers, Janssen Research and Development, La Jolla, CA, 92121-1126, USA
| | - Hartmuth Kolb
- Neuroscience Biomarkers, Janssen Research and Development, La Jolla, CA, 92121-1126, USA
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Alzheimer’s Disease Research Unit, Douglas Research Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l’Ouest-de-l’Île-de-Montréal, QC H4H 1R3, Canada
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - William E. Klunk
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Oscar Lopez
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Victor L. Villemagne
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Ann Cohen
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Dana L. Tudorascu
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Eduardo R. Zimmer
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
- Department of Pharmacology, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
- Graduate Program in Biological Sciences: Pharmacology and Therapeuctis, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
- Brain Insitute of Rio Grande do Sul, PUCRS, Porto Alegre, 90619-900, Brazil
| | - Thomas K. Karikari
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
| | - Nicholas J. Ashton
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg, 431 41, Sweden
- Department of Old Age Psychiatry, Institute of Psychiatry, Psychology & Neuroscience, King’s College London, London, WC1N 3BG, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WC1N 3BG, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, HKG, China
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, 53792, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, 431 41, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, 431 41, Sweden
| | - Serge Gauthier
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
| | - Pedro Rosa-Neto
- Department of Neurology and Neurosurgery, Psychiatry and Pharmacology and Therapeutics, McGill University, Montreal, QC, QC H4H 1R3, Canada
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, 90035-003, Brazil
| | - Tharick A. Pascoal
- Department of Psychiatry, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Department of Neurology, School of medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
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24
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Cho K. Neutrophil-Mediated Progression of Mild Cognitive Impairment to Dementia. Int J Mol Sci 2023; 24:14795. [PMID: 37834242 PMCID: PMC10572848 DOI: 10.3390/ijms241914795] [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: 09/05/2023] [Revised: 09/26/2023] [Accepted: 09/29/2023] [Indexed: 10/15/2023] Open
Abstract
Cognitive impairment is a serious condition that begins with amnesia and progresses to cognitive decline, behavioral dysfunction, and neuropsychiatric impairment. In the final stage, dysphagia and incontinence occur. There are numerous studies and developed drugs for cognitive dysfunction in neurodegenerative diseases, such as Alzheimer's disease (AD); however, their clinical effectiveness remains equivocal. To date, attempts have been made to overcome cognitive dysfunction and understand and delay the aging processes that lead to degenerative and chronic diseases. Cognitive dysfunction is involved in aging and the disruption of inflammation and innate immunity. Recent reports have indicated that the innate immune system is prevalent in patients with AD, and that peripheral neutrophil markers can predict a decline in executive function in patients with mild cognitive impairment (MCI). Furthermore, altered levels of pro-inflammatory interleukins have been reported in MCI, which have been suggested to play a role in the peripheral immune system during the process from early MCI to dementia. Neutrophils are the first responders of the innate immune system. Neutrophils eliminate harmful cellular debris via phagocytosis, secrete inflammatory factors to activate host defense systems, stimulate cytokine production, kill pathogens, and regulate extracellular proteases and inhibitors. This review investigated and summarized the regulation of neutrophil function during cognitive impairment caused by various degenerative diseases. In addition, this work elucidates the cellular mechanism of neutrophils in cognitive impairment and what is currently known about the effects of activated neutrophils on cognitive decline.
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Affiliation(s)
- KyoungJoo Cho
- Department of Life Science, Kyonggi University, Suwon 16227, Republic of Korea
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25
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Mengel D, Wellik IG, Schuster KH, Jarrah SI, Wacker M, Ashraf NS, Öz G, Synofzik M, Costa MDC, McLoughlin HS. Blood levels of neurofilament light are associated with disease progression in a mouse model of spinocerebellar ataxia type 3. Dis Model Mech 2023; 16:dmm050144. [PMID: 37664882 PMCID: PMC10499033 DOI: 10.1242/dmm.050144] [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: 02/23/2023] [Accepted: 08/15/2023] [Indexed: 09/05/2023] Open
Abstract
Increased neurofilament light (NfL; NEFL) protein in biofluids is reflective of neurodegeneration and has gained interest as a biomarker across neurodegenerative diseases. In spinocerebellar ataxia type 3 (SCA3), the most common dominantly inherited ataxia, patients exhibit progressive NfL increases in peripheral blood when becoming symptomatic, and NfL remains stably elevated throughout further disease course. However, progressive NfL changes are not yet validated in relevant preclinical SCA3 animal models, hindering its application as a biomarker during therapeutic development. We used ultra-sensitive single-molecule array (Simoa) to measure blood NfL over disease progression in YACQ84 mice, a model of SCA3, assessing relationships with measures of disease severity including age, CAG repeat size and magnetic resonance spectroscopy. YACQ84 mice exhibited plasma NfL increases that were concomitant with ataxia-related motor deficits as well as increased serum NfL, which correlated with previously established neurometabolite abnormalities, two relevant measures of disease in patients with SCA3. Our findings establish the progression of NfL increases in the preclinical YACQ84 mouse, further supporting the utility of blood NfL as a peripheral neurodegeneration biomarker and informing on coinciding timelines of different measures of SCA3 pathogenesis.
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Affiliation(s)
- David Mengel
- Research Division Translational Genomics of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen 72076,Germany
- German Center for Neurodegenerative Diseases (DZNE), University of Tübingen, Tübingen 72076, Germany
| | - Isabel G. Wellik
- Department of Neurology, University of Michigan, Ann Arbor, MI 48109-2200, USA
| | - Kristen H. Schuster
- Department of Neurology, University of Michigan, Ann Arbor, MI 48109-2200, USA
| | - Sabrina I. Jarrah
- Department of Neurology, University of Michigan, Ann Arbor, MI 48109-2200, USA
| | - Madeleine Wacker
- Research Division Translational Genomics of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen 72076,Germany
- German Center for Neurodegenerative Diseases (DZNE), University of Tübingen, Tübingen 72076, Germany
| | - Naila S. Ashraf
- Department of Neurology, University of Michigan, Ann Arbor, MI 48109-2200, USA
| | - Gülin Öz
- Center for Magnetic Resonance Research, Department of Radiology, Medical School, University of Minnesota, Minneapolis, MN 55455, USA
| | - Matthis Synofzik
- Research Division Translational Genomics of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen 72076,Germany
- German Center for Neurodegenerative Diseases (DZNE), University of Tübingen, Tübingen 72076, Germany
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26
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Vila-Castelar C, Chen Y, Langella S, Lopera F, Zetterberg H, Hansson O, Dage JL, Janelidzde S, Su Y, Chen K, McDowell CP, Martinez JE, Ramirez-Gomez L, Garcia G, Aguillon D, Baena A, Giraldo-Chica M, Protas HD, Ghisays V, Rios-Romenets S, Tariot PN, Blennow K, Reiman EM, Quiroz YT. Sex differences in blood biomarkers and cognitive performance in individuals with autosomal dominant Alzheimer's disease. Alzheimers Dement 2023; 19:4127-4138. [PMID: 37279390 PMCID: PMC10527358 DOI: 10.1002/alz.13314] [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: 03/03/2023] [Revised: 05/05/2023] [Accepted: 05/09/2023] [Indexed: 06/08/2023]
Abstract
INTRODUCTION Plasma tau phosphorylated at threonine 217 (P-tau217) and neurofilament light (NfL) have emerged as markers of Alzheimer's disease (AD) pathology. Few studies have examined the role of sex in plasma biomarkers in sporadic AD, yielding mixed findings, and none in autosomal dominant AD. METHODS We examined the effects of sex and age on plasma P-tau217 and NfL, and their association with cognitive performance in a cross-sectional study of 621 Presenilin-1 E280A mutation carriers (PSEN1) and non-carriers. RESULTS As plasma P-tau217 levels increase, cognitively unimpaired female carriers showed better cognitive performance than cognitively unimpaired male carriers. Yet, as disease progresses, female carriers had a greater plasma NfL increase than male carriers. There were no sex differences in the association between age and plasma biomarkers among non-carriers. DISCUSSION Our findings suggest that, among PSEN1 mutation carriers, females had a greater rate of neurodegeneration than males, yet it did not predict cognitive performance. HIGHLIGHTS We examined sex differences in plasma P-tau217 and NfL in Presenilin-1 E280A (PSEN1) mutation carriers and non-carriers. Female carriers had a greater plasma NfL increase, but not P-tau217, than male carriers. As plasma P-tau217 levels increase, cognitively unimpaired female carriers showed better cognitive performance than cognitively unimpaired male carriers. The interaction effect of sex by plasma NfL levels did not predict cognition among carriers.
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Affiliation(s)
- Clara Vila-Castelar
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA
| | - Yinghua Chen
- Banner Alzheimer’s Institute, Phoenix, AZ, 85718, USA
| | - Stephanie Langella
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA
| | - Francisco Lopera
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin, 1226, Colombia
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, 405 30, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, 405 30, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WC1E 6BT, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Oskar Hansson
- Memory Clinic, Skåne University Hospital, Malmö, 214 28, Sweden
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 205 02, Sweden
| | - Jeffrey L. Dage
- Indiana University School of Medicine, Indianapolis, IN, 46202, USA
| | | | - Yi Su
- Banner Alzheimer’s Institute, Phoenix, AZ, 85718, USA
| | - Kewei Chen
- Banner Alzheimer’s Institute, Phoenix, AZ, 85718, USA
| | - Celina Pluim McDowell
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA
- Department of Psychological and Brain Sciences, Boston University, Boston, 02215, MA
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, 02115, MA
| | - Jairo E. Martinez
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA
- Department of Psychological and Brain Sciences, Boston University, Boston, 02215, MA
| | | | - Gloria Garcia
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin, 1226, Colombia
| | - David Aguillon
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin, 1226, Colombia
| | - Ana Baena
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin, 1226, Colombia
| | | | | | | | - Silvia Rios-Romenets
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin, 1226, Colombia
| | | | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, 405 30, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, 405 30, Sweden
| | | | - Yakeel T. Quiroz
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, 02129, USA
- Grupo de Neurociencias de Antioquia, Universidad de Antioquia, Medellin, 1226, Colombia
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27
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Jack CR, Wiste HJ, Algeciras-Schimnich A, Figdore DJ, Schwarz CG, Lowe VJ, Ramanan VK, Vemuri P, Mielke MM, Knopman DS, Graff-Radford J, Boeve BF, Kantarci K, Cogswell PM, Senjem ML, Gunter JL, Therneau TM, Petersen RC. Predicting amyloid PET and tau PET stages with plasma biomarkers. Brain 2023; 146:2029-2044. [PMID: 36789483 PMCID: PMC10151195 DOI: 10.1093/brain/awad042] [Citation(s) in RCA: 28] [Impact Index Per Article: 28.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 12/20/2022] [Accepted: 01/21/2023] [Indexed: 02/16/2023] Open
Abstract
Staging the severity of Alzheimer's disease pathology using biomarkers is useful for therapeutic trials and clinical prognosis. Disease staging with amyloid and tau PET has face validity; however, this would be more practical with plasma biomarkers. Our objectives were, first, to examine approaches for staging amyloid and tau PET and, second, to examine prediction of amyloid and tau PET stages using plasma biomarkers. Participants (n = 1136) were enrolled in either the Mayo Clinic Study of Aging or the Alzheimer's Disease Research Center; had a concurrent amyloid PET, tau PET and blood draw; and met clinical criteria for cognitively unimpaired (n = 864), mild cognitive impairment (n = 148) or Alzheimer's clinical syndrome with dementia (n = 124). The latter two groups were combined into a cognitively impaired group (n = 272). We used multinomial regression models to estimate discrimination [concordance (C) statistics] among three amyloid PET stages (low, intermediate, high), four tau PET stages (Braak 0, 1-2, 3-4, 5-6) and a combined amyloid and tau PET stage (none/low versus intermediate/high severity) using plasma biomarkers as predictors separately within unimpaired and impaired individuals. Plasma analytes, p-tau181, Aβ1-42 and Aβ1-40 (analysed as the Aβ42/Aβ40 ratio), glial fibrillary acidic protein and neurofilament light chain were measured on the HD-X Simoa Quanterix platform. Plasma p-tau217 was also measured in a subset (n = 355) of cognitively unimpaired participants using the Lilly Meso Scale Discovery assay. Models with all Quanterix plasma analytes along with risk factors (age, sex and APOE) most often provided the best discrimination among amyloid PET stages (C = 0.78-0.82). Models with p-tau181 provided similar discrimination of tau PET stages to models with all four plasma analytes (C = 0.72-0.85 versus C = 0.73-0.86). Discriminating a PET proxy of intermediate/high from none/low Alzheimer's disease neuropathological change with all four Quanterix plasma analytes was excellent but not better than p-tau181 only (C = 0.88 versus 0.87 for unimpaired and C = 0.91 versus 0.90 for impaired). Lilly p-tau217 outperformed the Quanterix p-tau181 assay for discriminating high versus intermediate amyloid (C = 0.85 versus 0.74) but did not improve over a model with all Quanterix plasma analytes and risk factors (C = 0.85 versus 0.83). Plasma analytes along with risk factors can discriminate between amyloid and tau PET stages and between a PET surrogate for intermediate/high versus none/low neuropathological change with accuracy in the acceptable to excellent range. Combinations of plasma analytes are better than single analytes for many staging predictions with the exception that Quanterix p-tau181 alone usually performed equivalently to combinations of Quanterix analytes for tau PET discrimination.
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Affiliation(s)
- Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Heather J Wiste
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Dan J Figdore
- Department of Laboratory Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Val J Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | - Vijay K Ramanan
- Department of Neurology, 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
| | | | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | - Terry M Therneau
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
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28
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Binette AP, Janelidze S, Cullen N, Dage JL, Bateman RJ, Zetterberg H, Blennow K, Stomrud E, Mattsson-Carlgren N, Hansson O. Confounding factors of Alzheimer's disease plasma biomarkers and their impact on clinical performance. Alzheimers Dement 2023; 19:1403-1414. [PMID: 36152307 PMCID: PMC10499000 DOI: 10.1002/alz.12787] [Citation(s) in RCA: 55] [Impact Index Per Article: 55.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 07/27/2022] [Accepted: 07/31/2022] [Indexed: 11/10/2022]
Abstract
INTRODUCTION Plasma biomarkers will likely revolutionize the diagnostic work-up of Alzheimer's disease (AD) globally. Before widespread use, we need to determine if confounding factors affect the levels of these biomarkers, and their clinical utility. METHODS Participants with plasma and CSF biomarkers, creatinine, body mass index (BMI), and medical history data were included (BioFINDER-1: n = 748, BioFINDER-2: n = 421). We measured beta-amyloid (Aβ42, Aβ40), phosphorylated tau (p-tau217, p-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP). RESULTS In both cohorts, creatinine and BMI were the main factors associated with NfL, GFAP, and to a lesser extent with p-tau. However, adjustment for BMI and creatinine had only minor effects in models predicting either the corresponding levels in CSF or subsequent development of dementia. DISCUSSION Creatinine and BMI are related to certain plasma biomarkers levels, but they do not have clinically relevant confounding effects for the vast majority of individuals. HIGHLIGHTS Creatinine and body mass index (BMI) are related to certain plasma biomarker levels. Adjusting for creatinine and BMI has minor influence on plasma-cerebrospinal fluid (CSF) associations. Adjusting for creatinine and BMI has minor influence on prediction of dementia using plasma biomarkers.
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Affiliation(s)
- Alexa Pichet Binette
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Nicholas Cullen
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Jeffrey L. Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Randall J. Bateman
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, 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, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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29
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Gonzalez-Ortiz F, Turton M, Kac PR, Smirnov D, Premi E, Ghidoni R, Benussi L, Cantoni V, Saraceno C, Rivolta J, Ashton NJ, Borroni B, Galasko D, Harrison P, Zetterberg H, Blennow K, Karikari TK. Brain-derived tau: a novel blood-based biomarker for Alzheimer's disease-type neurodegeneration. Brain 2023; 146:1152-1165. [PMID: 36572122 PMCID: PMC9976981 DOI: 10.1093/brain/awac407] [Citation(s) in RCA: 62] [Impact Index Per Article: 62.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2022] [Revised: 09/23/2022] [Accepted: 09/25/2022] [Indexed: 12/28/2022] Open
Abstract
Blood-based biomarkers for amyloid beta and phosphorylated tau show good diagnostic accuracies and agreements with their corresponding CSF and neuroimaging biomarkers in the amyloid/tau/neurodegeneration [A/T/(N)] framework for Alzheimer's disease. However, the blood-based neurodegeneration marker neurofilament light is not specific to Alzheimer's disease while total-tau shows lack of correlation with CSF total-tau. Recent studies suggest that blood total-tau originates principally from peripheral, non-brain sources. We sought to address this challenge by generating an anti-tau antibody that selectively binds brain-derived tau and avoids the peripherally expressed 'big tau' isoform. We applied this antibody to develop an ultrasensitive blood-based assay for brain-derived tau, and validated it in five independent cohorts (n = 609) including a blood-to-autopsy cohort, CSF biomarker-classified cohorts and memory clinic cohorts. In paired samples, serum and CSF brain-derived tau were significantly correlated (rho = 0.85, P < 0.0001), while serum and CSF total-tau were not (rho = 0.23, P = 0.3364). Blood-based brain-derived tau showed equivalent diagnostic performance as CSF total-tau and CSF brain-derived tau to separate biomarker-positive Alzheimer's disease participants from biomarker-negative controls. Furthermore, plasma brain-derived tau accurately distinguished autopsy-confirmed Alzheimer's disease from other neurodegenerative diseases (area under the curve = 86.4%) while neurofilament light did not (area under the curve = 54.3%). These performances were independent of the presence of concomitant pathologies. Plasma brain-derived tau (rho = 0.52-0.67, P = 0.003), but not neurofilament light (rho = -0.14-0.17, P = 0.501), was associated with global and regional amyloid plaque and neurofibrillary tangle counts. These results were further verified in two memory clinic cohorts where serum brain-derived tau differentiated Alzheimer's disease from a range of other neurodegenerative disorders, including frontotemporal lobar degeneration and atypical parkinsonian disorders (area under the curve up to 99.6%). Notably, plasma/serum brain-derived tau correlated with neurofilament light only in Alzheimer's disease but not in the other neurodegenerative diseases. Across cohorts, plasma/serum brain-derived tau was associated with CSF and plasma AT(N) biomarkers and cognitive function. Brain-derived tau is a new blood-based biomarker that outperforms plasma total-tau and, unlike neurofilament light, shows specificity to Alzheimer's disease-type neurodegeneration. Thus, brain-derived tau demonstrates potential to complete the AT(N) scheme in blood, and will be useful to evaluate Alzheimer's disease-dependent neurodegenerative processes for clinical and research purposes.
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Affiliation(s)
- Fernando Gonzalez-Ortiz
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg 405 30, Sweden
| | - Michael Turton
- Bioventix Plc, Romans Business Park, Farnham, Surrey GU9 7SX, UK
| | - Przemysław R Kac
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg 405 30, Sweden
| | - Denis Smirnov
- University of California, San Diego and Shiely-Marcos Alzheimer’s Disease Research Center, La Jolla, CA 92037, USA
| | - Enrico Premi
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, BS 25121, Italy
| | - Roberta Ghidoni
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia 25121, Italy
| | - Luisa Benussi
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia 25121, Italy
| | - Valentina Cantoni
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, BS 25121, Italy
| | - Claudia Saraceno
- Molecular Markers Laboratory, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia 25121, Italy
| | - Jasmine Rivolta
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, BS 25121, Italy
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg 405 30, Sweden
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Gothenburg 405 30, Sweden
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, SE5 8AF, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, SE5 8AF, UK
| | - Barbara Borroni
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, BS 25121, Italy
| | - Douglas Galasko
- University of California, San Diego and Shiely-Marcos Alzheimer’s Disease Research Center, La Jolla, CA 92037, USA
| | - Peter Harrison
- Bioventix Plc, Romans Business Park, Farnham, Surrey GU9 7SX, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg 405 30, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, 431 80, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, WC1N 3BG, UK
- UK Dementia Research Institute at UCL, London, WC1E 6BT, UK
- Hong Kong Center for Neurodegenerative Diseases, Shatin, N.T., Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg 405 30, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, 431 80, Sweden
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg 405 30, Sweden
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA 15213, USA
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30
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Mengel D, Wellik IG, Schuster KH, Jarrah SI, Wacker M, Ashraf NS, Öz G, Synofzik M, do Carmo Costa M, McLoughlin HS. Blood neurofilament light chain levels are associated with disease progression in a transgenic SCA3 mouse model. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.28.530463. [PMID: 36909535 PMCID: PMC10002656 DOI: 10.1101/2023.02.28.530463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/06/2023]
Abstract
Increased neurofilament light (NfL) protein in biofluids is reflective of neurodegeneration and has gained interest as a biomarker across neurodegenerative diseases. In spinocerebellar ataxia type 3 (SCA3), the most common dominantly inherited ataxia, patients exhibit progressive NfL increases in peripheral blood when becoming symptomatic, remaining stably elevated throughout further disease course. However, progressive NfL changes are not yet validated in relevant preclinical SCA3 animal models, hindering its application as a biomarker during therapeutic development. We used ultra-sensitive single-molecule array (Simoa) to measure blood NfL over disease progression in the YACQ84 mouse, assessing relationships with measures of disease severity including age, CAG repeat size, and magnetic resonance spectroscopy. We show that YACQ84 mice exhibit increased blood NfL, concomitant with ataxia-related motor deficits and correlated with neurometabolite abnormalities. Our findings establish natural history progression of NfL increases in the preclinical YACQ84 mouse, further supporting the utility of blood NfL as a peripheral neurodegeneration biomarker and informing coinciding timelines of different measures of SCA3 pathogenesis. Summary statement Peripheral blood of SCA3 YACQ84 mice exhibits increased abundance of neuronal-specific NfL protein directly associating with disease progression, providing an accessible disease biofluid biomarker to interrogate in preclinical therapeutic studies.
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Affiliation(s)
- David Mengel
- Research Division Translational Genomics of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), University of Tübingen, Tübingen, Germany
| | - Isabel G. Wellik
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | | | | | - Madeleine Wacker
- Research Division Translational Genomics of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), University of Tübingen, Tübingen, Germany
| | - Naila S. Ashraf
- Department of Neurology, University of Michigan, Ann Arbor, MI, USA
| | - Gülin Öz
- Center for Magnetic Resonance Research, Department of Radiology, Medical School, University of Minnesota, Minneapolis, MN, USA
| | - Matthis Synofzik
- Research Division Translational Genomics of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany
- German Center for Neurodegenerative Diseases (DZNE), University of Tübingen, Tübingen, Germany
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31
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Assessment of Plasma and Cerebrospinal Fluid Biomarkers in Different Stages of Alzheimer's Disease and Frontotemporal Dementia. Int J Mol Sci 2023; 24:ijms24021226. [PMID: 36674742 PMCID: PMC9864037 DOI: 10.3390/ijms24021226] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 12/23/2022] [Accepted: 01/05/2023] [Indexed: 01/11/2023] Open
Abstract
Alzheimer's disease (AD) is the primary type of dementia, followed by frontotemporal lobar degeneration (FTLD). They share some clinical characteristics, mainly at the early stages. So, the identification of early, specific, and minimally invasive biomarkers is required. In this study, some plasma biomarkers (Amyloid β42, p-Tau181, t-Tau, neurofilament light (NfL), TAR DNA-binding protein 43 (TDP-43)) were determined by single molecule array technology (SIMOA®) in control subjects (n = 22), mild cognitive impairment due to AD (MCI-AD, n = 33), mild dementia due to AD (n = 12), and FTLD (n = 11) patients. The correlations between plasma and cerebrospinal fluid (CSF) levels and the accuracy of plasma biomarkers for AD early diagnosis and discriminating from FTLD were analyzed. As result, plasma p-Tau181 and NfL levels correlated with the corresponding CSF levels. Additionally, plasma p-Tau181 showed good accuracy for distinguishing between the controls and AD, as well as discriminating between AD and FTLD. Moreover, plasma NfL could discriminate dementia-AD vs. controls, FTLD vs. controls, and MCI-AD vs. dementia-AD. Therefore, the determination of these biomarkers in plasma is potentially helpful in AD spectrum diagnosis, but also discriminating from FTLD. In addition, the accessibility of these potential early and specific biomarkers may be useful for AD screening protocols in the future.
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32
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Ashton NJ, Janelidze S, Mattsson-Carlgren N, Binette AP, Strandberg O, Brum WS, Karikari TK, González-Ortiz F, Di Molfetta G, Meda FJ, Jonaitis EM, Koscik RL, Cody K, Betthauser TJ, Li Y, Vanmechelen E, Palmqvist S, Stomrud E, Bateman RJ, Zetterberg H, Johnson SC, Blennow K, Hansson O. Differential roles of Aβ42/40, p-tau231 and p-tau217 for Alzheimer's trial selection and disease monitoring. Nat Med 2022; 28:2555-2562. [PMID: 36456833 PMCID: PMC9800279 DOI: 10.1038/s41591-022-02074-w] [Citation(s) in RCA: 122] [Impact Index Per Article: 61.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 10/03/2022] [Indexed: 12/03/2022]
Abstract
Blood biomarkers indicative of Alzheimer's disease (AD) pathology are altered in both preclinical and symptomatic stages of the disease. Distinctive biomarkers may be optimal for the identification of AD pathology or monitoring of disease progression. Blood biomarkers that correlate with changes in cognition and atrophy during the course of the disease could be used in clinical trials to identify successful interventions and thereby accelerate the development of efficient therapies. When disease-modifying treatments become approved for use, efficient blood-based biomarkers might also inform on treatment implementation and management in clinical practice. In the BioFINDER-1 cohort, plasma phosphorylated (p)-tau231 and amyloid-β42/40 ratio were more changed at lower thresholds of amyloid pathology. Longitudinally, however, only p-tau217 demonstrated marked amyloid-dependent changes over 4-6 years in both preclinical and symptomatic stages of the disease, with no such changes observed in p-tau231, p-tau181, amyloid-β42/40, glial acidic fibrillary protein or neurofilament light. Only longitudinal increases of p-tau217 were also associated with clinical deterioration and brain atrophy in preclinical AD. The selective longitudinal increase of p-tau217 and its associations with cognitive decline and atrophy was confirmed in an independent cohort (Wisconsin Registry for Alzheimer's Prevention). These findings support the differential association of plasma biomarkers with disease development and strongly highlight p-tau217 as a surrogate marker of disease progression in preclinical and prodromal AD, with impact for the development of new disease-modifying treatments.
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Affiliation(s)
- Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute 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
| | - Shorena Janelidze
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Wagner S Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Fernándo González-Ortiz
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Francisco J Meda
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Erin M Jonaitis
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Rebecca Langhough Koscik
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Karly Cody
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Tobey J Betthauser
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Yan Li
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Sebastian Palmqvist
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Sterling C Johnson
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
- ADx NeuroSciences, Technologiepark 94, Ghent, Belgium.
| | - Oskar Hansson
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, Malmö, Sweden.
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Aschenbrenner AJ, Li Y, Henson RL, Volluz K, Hassenstab J, Verghese P, West T, Meyer MR, Kirmess KM, Fagan AM, Xiong C, Holtzman D, Morris JC, Bateman RJ, Schindler SE. Comparison of plasma and CSF biomarkers in predicting cognitive decline. Ann Clin Transl Neurol 2022; 9:1739-1751. [PMID: 36183195 PMCID: PMC9639639 DOI: 10.1002/acn3.51670] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 09/07/2022] [Indexed: 11/07/2022] Open
Abstract
OBJECTIVES Concentrations of amyloid-β peptides (Aβ42/Aβ40) and neurofilament light (NfL) can be measured in plasma or cerebrospinal fluid (CSF) and are associated with Alzheimer's disease brain pathology and cognitive impairment. This study directly compared plasma and CSF measures of Aβ42/Aβ40 and NfL as predictors of cognitive decline. METHODS Participants were 65 years or older and cognitively normal at baseline with at least one follow-up cognitive assessment. Analytes were measured with the following types of assays: plasma Aβ42/Aβ40, immunoprecipitation-mass spectrometry; plasma NfL, Simoa; CSF Aβ42/Aβ40, automated immunoassay; CSF NfL plate-based immunoassay. Mixed effects models evaluated the global cognitive composite score over a maximum of 6 years as predicted by the fluid biomarkers. RESULTS Analyses included 371 cognitively normal participants, aged 72.7 ± 5.2 years (mean ± standard deviation) with an average length of follow-up of 3.9 ± 1.6 years. Standardized concentrations of biomarkers were associated with annualized cognitive change: plasma Aβ42/Aβ40, 0.014 standard deviations (95% confidence intervals 0.002 to 0.026); CSF Aβ42/Aβ40, 0.020 (0.008 to 0.032); plasma Nfl, -0.018 (-0.030 to -0.005); and CSF NfL, -0.024 (-0.036 to -0.012). Power analyses estimated that 266 individuals in each treatment arm would be needed to detect a 50% slowing of decline if identified by abnormal plasma measures versus 229 for CSF measures. INTERPRETATION Both plasma and CSF measures of Aβ42/Aβ40 and NfL predicted cognitive decline. A clinical trial that enrolled individuals based on abnormal plasma Aβ42/Aβ40 and NfL levels would require only a marginally larger cohort than if CSF measures were used.
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Affiliation(s)
- Andrew J. Aschenbrenner
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
| | - Yan Li
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
- Division of BiostatisticsWashington University School of MedicineSt. LouisMOUSA
| | - Rachel L. Henson
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
| | - Katherine Volluz
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
| | - Jason Hassenstab
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
| | | | | | | | | | - Anne M. Fagan
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
- Hope Center for Neurological DisordersWashington University School of MedicineSt. LouisMOUSA
| | - Chengjie Xiong
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
- Division of BiostatisticsWashington University School of MedicineSt. LouisMOUSA
| | - David Holtzman
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
- Hope Center for Neurological DisordersWashington University School of MedicineSt. LouisMOUSA
| | - John C. Morris
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
- Hope Center for Neurological DisordersWashington University School of MedicineSt. LouisMOUSA
| | - Randall J. Bateman
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
- Hope Center for Neurological DisordersWashington University School of MedicineSt. LouisMOUSA
| | - Suzanne E. Schindler
- Department of NeurologyWashington University School of MedicineSt. LouisMOUSA
- Knight Alzheimer Disease Research CenterWashington University School of MedicineSt. LouisMOUSA
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Zhang P, Chen J, Cai T, He C, Li Y, Li X, Chen Z, Wang L, Zhang Y. Quantitative susceptibility mapping and blood neurofilament light chain differentiate between parkinsonian disorders. Front Aging Neurosci 2022; 14:909552. [PMID: 35992605 PMCID: PMC9389149 DOI: 10.3389/fnagi.2022.909552] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 06/27/2022] [Indexed: 11/13/2022] Open
Abstract
Objectives We employed quantitative susceptibility mapping (QSM) to assess iron deposition in parkinsonian disorders and explored whether combining QSM values and neurofilament light (NfL) chain levels can improve the accuracy of distinguishing Parkinson’s disease (PD) from multiple system atrophy (MSA) and progressive supranuclear palsy (PSP). Materials and methods Forty-seven patients with PD, 28 patients with MSA, 18 patients with PSP, and 28 healthy controls (HC) were enrolled, and QSM data were reconstructed. Susceptibility values in the bilateral globus pallidus (GP), putamen (PUT), caudate nucleus (CN), red nucleus (RN), substantia nigra (SN), and dentate nucleus (DN) were obtained. Plasma NfL levels of 47 PD, 18 MSA, and 14 PSP patients and 22 HC were measured by ultrasensitive Simoa technology. Results The highest diagnostic accuracy distinguishing MSA from PD patients was observed with increased susceptibility values in CN (AUC: 0.740). The susceptibility values in RN yielded the highest diagnostic performance for distinguishing PSP from PD patients (AUC: 0.829). Plasma NfL levels were significantly higher in the MSA and PSP groups than in PD and HC groups. Combining the susceptibility values in the RN and plasma NfL levels improved the diagnostic performance for PSP vs. PD (AUC: 0.904), whereas plasma NfL levels had higher diagnostic accuracy for MSA vs. PD (AUC: 0.877). Conclusion The exploratory study indicates different patterns of iron accumulation in deep gray matter nuclei in Parkinsonian disorders. Combining QSM values with NfL levels may be a promising biomarker for distinguishing PSP from PD, whereas plasma NfL may be a reliable biomarker for differentiating MSA from PD. QSM and NfL measures appeared to have low accuracy for separating PD from controls.
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Affiliation(s)
- Piao Zhang
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Junling Chen
- Department of Neurology, Shantou Central Hospital, Shantou, China
| | - Tongtong Cai
- Department of Neurology, Shantou Central Hospital, Shantou, China
| | - Chentao He
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yan Li
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Xiaohong Li
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Zhenzhen Chen
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Lijuan Wang
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
| | - Yuhu Zhang
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
- Department of Neurology, Guangdong Neuroscience Institute, Guangdong Provincial People’s Hospital, Guangdong Academy of Medical Sciences, Guangzhou, China
- *Correspondence: Yuhu Zhang,
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Zhou S, Liu D, Chen J, Xiang C, Xiang J, Yang M. Electrochemical Quantitation of the Glycosylation Level of Serum Neurofilament Light Chain for the Diagnosis of Neurodegeneration: An Interface-Solution Dual-Path Amplification Strategy. Anal Chem 2022; 94:11433-11440. [PMID: 35913270 DOI: 10.1021/acs.analchem.2c02753] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Serum neurofilament light chain (NFL), a potential general biomarker for neurodegenerative diseases, is not specific enough to differentiate neurodegenerative diseases from other brain diseases such as cerebral thrombosis (CT). According to the importance of glycosylation in neurodegenerative pathogenesis, the NFL glycosylation level (oNFL/tNFL), defined as the ratio of glycosylated NFL (oNFL) to total NFL (tNFL), may be a more effective index. The major challenge in serum oNFL/tNFL detection is the ultra-low abundance of both NFL forms. In this paper, we achieved a convenient one-step electrochemical quantitation of oNFL/tNFL based on an interface-solution dual-path amplification strategy. Two amplified electrochemical signals─the reduction of Cu2+ from adsorbed porous nanoparticles on the sensor interface and the reduction of O2 from horseradish peroxidase-catalyzed H2O2 disproportionation in solution─were adopted to quantify tNFL and oNFL, respectively. The electrochemical sensor displayed good sensitivity, selectivity, and reproducibility. The dynamic range is 1-25 pg mL-1 for tNFL and 0.25-25 pg mL-1 for oNFL, respectively. By analyzing the clinic serum samples, for the first time, our work provided the abundance of oNFL in human serum and revealed that the oNFL/tNFL is effective not only in differentiating three kinds of brain damage patients from healthy people but also in differentiating neurodegeneration from non-neurodegeneration CT patients. As a general biomarker, the oNFL/tNFL is more specific than NFL, which is hoped to be a new and valid indicator for the diagnosis, progression, prediction, and treatment evaluation of neurodegenerative diseases.
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Affiliation(s)
- Siqiuyue Zhou
- Hunan Provincial Key Laboratory of Micro & Nano Materials Interface Science, College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, P. R. China.,National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Central South University, Changsha 410083, P. R. China
| | - Dan Liu
- Eye Center of Xiangya Hospital, Central South University, Changsha 410083, P. R. China
| | - Jia Chen
- Hunan Provincial Key Laboratory of Micro & Nano Materials Interface Science, College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, P. R. China
| | - Chao Xiang
- Wuhan Red Cross Hospital, Wuhan 430015, P. R. China
| | - Juan Xiang
- Hunan Provincial Key Laboratory of Micro & Nano Materials Interface Science, College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, P. R. China.,National Engineering Research Center of Personalized Diagnostic and Therapeutic Technology, Central South University, Changsha 410083, P. R. China
| | - Minghui Yang
- Hunan Provincial Key Laboratory of Micro & Nano Materials Interface Science, College of Chemistry and Chemical Engineering, Central South University, Changsha 410083, P. R. China
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Yao W, Zhang X, Zhao H, Xu Y, Bai F. Inflammation Disrupts Cognitive Integrity via Plasma Neurofilament Light Chain Coupling Brain Networks in Alzheimer’s Disease. J Alzheimers Dis 2022; 89:505-518. [PMID: 35871350 DOI: 10.3233/jad-220475] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Objective: Background: Plasma neurofilament light chain (NFL) is a recognized biomarker for Alzheimer’s disease (AD) and inflammation. Intrinsically organized default mode network core subsystem and frontoparietal network (FPN) and their interactions support complex cognitive function. The present study investigated the inflammatory effect on cognitive integrity via plasma NFL coupling internetwork interactions in AD. Objective: Objective: This study investigates the hypothesis that inflammation-related plasma NFL could affect the interactions of the core subsystem and FPN, which leads to the aggravation of the clinical symptoms of AD-spectrum patients. Objective: Methods: A total of 112 AD-spectrum participants underwent complete resting-state fMRI, neuropsychological tests, and plasma NFL at baseline (n = 112) and after approximately 17 months of follow-up (n = 112). The specific intersystem changes in the core subsystem and FPN were calculated and compared across groups. Then, the classifications of different AD-spectrum groups were analyzed using the association of plasma NFL and the changed intersystem interacting regions. Finally, mediation analysis was applied to investigate the significance of plasma NFL coupling networks on cognitive impairments in these subjects. Objective: Results: Discrimination of disease-related interactions of the core subsystem and FPN was found in AD-spectrum patients, which was the neural circuit fundamental to plasma NFL disrupting cognitive integrity. Furthermore, the clinical significance of plasma NFL coupling networks on AD identification and monitoring cognitive impairments were revealed in these subjects. Conclusion: The characteristic change in inflammation-related plasma NFL coupled with brain internetwork interactions could be used as a potential observation indicator in the progression of AD patients.
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Affiliation(s)
- Weina Yao
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Xiao Zhang
- Department of Neurology, Nanjing Drum Tower Hospital Clinical College of Traditional Chinese and Western Medicine, Nanjing University of Chinese Medicine, Nanjing, China
| | - Hui Zhao
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Yun Xu
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Feng Bai
- Department of Neurology, Nanjing Drum Tower Hospital of The Affiliated Hospital of Nanjing University Medical School, and The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China
- Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China
- Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
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37
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Park SA, Jang YJ, Kim MK, Lee SM, Moon SY. Promising Blood Biomarkers for Clinical Use in Alzheimer's Disease: A Focused Update. J Clin Neurol 2022; 18:401-409. [PMID: 35796265 PMCID: PMC9262460 DOI: 10.3988/jcn.2022.18.4.401] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 04/29/2022] [Accepted: 04/29/2022] [Indexed: 12/11/2022] Open
Abstract
Alzheimer’s disease (AD) is the most-common cause of neurodegenerative dementia, and it is characterized by abnormal amyloid and tau accumulation, which indicates neurodegeneration. AD has mostly been diagnosed clinically. However, ligand-specific positron emission tomography (PET) imaging, such as amyloid PET, and cerebrospinal fluid (CSF) biomarkers are needed to accurately diagnose AD, since they supplement the shortcomings of clinical diagnoses. Using biomarkers that represent the pathology of AD is essential (particularly when disease-modifying treatment is available) to identify the corresponding pathology of targeted therapy and for monitoring the treatment response. Although imaging and CSF biomarkers are useful, their widespread use is restricted by their high cost and the discomfort during the lumbar puncture, respectively. Recent advances in AD blood biomarkers shed light on their future use for clinical purposes. The amyloid β (Aβ)42/Aβ40 ratio and the concentrations of phosphorylated tau at threonine 181 and at threonine 217, and of neurofilament light in the blood were found to represent the pathology of Aβ, tau, and neurodegeneration in the brain when using automatic electrochemiluminescence technologies, single-molecule arrays, immunoprecipitation coupled with mass spectrometry, etc. These blood biomarkers are imminently expected to be incorporated into clinical practice to predict, diagnose, and determine the stage of AD. In this review we focus on advancements in the measurement technologies for blood biomarkers and the promising biomarkers that are approaching clinical application. We also discuss the current limitations, the needed further investigations, and the perspectives on their use.
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Affiliation(s)
- Sun Ah Park
- Lab for Neurodegenerative Dementia, Department of Anatomy, Ajou University School of Medicine, Suwon, Korea.,Department of Neurology, Ajou University School of Medicine, Suwon, Korea.,Neuroscience Graduate Program, Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea.
| | - Yu Jung Jang
- Lab for Neurodegenerative Dementia, Department of Anatomy, Ajou University School of Medicine, Suwon, Korea.,Neuroscience Graduate Program, Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea
| | - Min Kyoung Kim
- Lab for Neurodegenerative Dementia, Department of Anatomy, Ajou University School of Medicine, Suwon, Korea.,Neuroscience Graduate Program, Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea
| | - Sun Min Lee
- Department of Neurology, Ajou University School of Medicine, Suwon, Korea
| | - So Young Moon
- Department of Neurology, Ajou University School of Medicine, Suwon, Korea
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38
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Fernandez-Alvarez M, Atienza M, Zallo F, Matute C, Capetillo-Zarate E, Cantero JL. Linking Plasma Amyloid Beta and Neurofilament Light Chain to Intracortical Myelin Content in Cognitively Normal Older Adults. Front Aging Neurosci 2022; 14:896848. [PMID: 35783126 PMCID: PMC9247578 DOI: 10.3389/fnagi.2022.896848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 05/23/2022] [Indexed: 11/29/2022] Open
Abstract
Evidence suggests that lightly myelinated cortical regions are vulnerable to aging and Alzheimer’s disease (AD). However, it remains unknown whether plasma markers of amyloid and neurodegeneration are related to deficits in intracortical myelin content, and whether this relationship, in turn, is associated with altered patterns of resting-state functional connectivity (rs-FC). To shed light into these questions, plasma levels of amyloid-β fragment 1–42 (Aβ1–42) and neurofilament light chain (NfL) were measured using ultra-sensitive single-molecule array (Simoa) assays, and the intracortical myelin content was estimated with the ratio T1-weigthed/T2-weighted (T1w/T2w) in 133 cognitively normal older adults. We assessed: (i) whether plasma Aβ1–42 and/or NfL levels were associated with intracortical myelin content at different cortical depths and (ii) whether cortical regions showing myelin reductions also exhibited altered rs-FC patterns. Surface-based multiple regression analyses revealed that lower plasma Aβ1–42 and higher plasma NfL were associated with lower myelin content in temporo-parietal-occipital regions and the insular cortex, respectively. Whereas the association with Aβ1–42 decreased with depth, the NfL-myelin relationship was most evident in the innermost layer. Older individuals with higher plasma NfL levels also exhibited altered rs-FC between the insula and medial orbitofrontal cortex. Together, these findings establish a link between plasma markers of amyloid/neurodegeneration and intracortical myelin content in cognitively normal older adults, and support the role of plasma NfL in boosting aberrant FC patterns of the insular cortex, a central brain hub highly vulnerable to aging and neurodegeneration.
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Affiliation(s)
- Marina Fernandez-Alvarez
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Mercedes Atienza
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Fatima Zallo
- Departamento de Neurociencias, Achucarro Basque Center for Neuroscience, Universidad del País Vasco, Leioa, Spain
| | - Carlos Matute
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Departamento de Neurociencias, Achucarro Basque Center for Neuroscience, Universidad del País Vasco, Leioa, Spain
| | - Estibaliz Capetillo-Zarate
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- Departamento de Neurociencias, Achucarro Basque Center for Neuroscience, Universidad del País Vasco, Leioa, Spain
- Ikerbasque, Basque Foundation for Science, Bilbao, Spain
| | - Jose L. Cantero
- Laboratory of Functional Neuroscience, Pablo de Olavide University, Seville, Spain
- Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
- *Correspondence: Jose L. Cantero,
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39
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Schindler SE, Ney DE, Goss AL, Rabinovici G. ANA Investigates: The Future of Biomarkers in Alzheimer Disease. Ann Neurol 2022; 92:159-160. [PMID: 35689567 DOI: 10.1002/ana.26437] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 06/09/2022] [Indexed: 11/10/2022]
Affiliation(s)
- Suzanne E Schindler
- Deparment of Neurology, Washington University School of Medicine, St. Louis, MO & Knight Alzheimer Research Center, Washington University School of Medicine, St. Louis, MO
| | - Douglas E Ney
- Departments of Neurology and Neurosurgery, University of Colorado School of Medicine, Aurora, CO
| | - Adeline L Goss
- Department of Neurology, University of California San Francisco, San Francisco, CA
| | - Gil Rabinovici
- Departments of Neurology, Radiology & Biomedical Imaging, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA
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40
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Sanchez JD, Martirosian RA, Mun KT, Chong DS, Llorente IL, Uphaus T, Gröschel K, Wölfer TA, Tiedt S, Hinman JD. Temporal Patterning of Neurofilament Light as a Blood-Based Biomarker for Stroke: A Systematic Review and Meta-Analysis. Front Neurol 2022; 13:841898. [PMID: 35651349 PMCID: PMC9149427 DOI: 10.3389/fneur.2022.841898] [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: 12/22/2021] [Accepted: 04/20/2022] [Indexed: 11/13/2022] Open
Abstract
Damage to axons is a core feature of ischemic stroke and cerebrovascular disease. The burden of axonal injury is correlated with the acute clinical deficits, the underlying burden of ischemic brain injury, the prognosis of recovery, and may be a meaningful therapeutic target for brain repair. Neurofilament light chain (NfL) has been identified as a blood-based biomarker that reflects neuroaxonal damage resulting from stroke. However, the utility of NfL as a blood-based biomarker in stroke is confounded by studies examining different temporal windows and patient populations. We conducted a systematic review and meta-analysis to verify the utility of blood NfL as a diagnostic, prognostic, and monitoring stroke biomarker. Nineteen studies reporting serum/plasma NfL values for a total of 4,237 distinct patients with stroke were identified. Using available summary data from the 10 studies that employed a common immunoassay platform, we utilized random effects linear mixed modeling and weighted averages to create a phasic model of serum/plasma NfL values in distinct time periods of acute stroke. Weighted averages show that blood NfL levels vary significantly across three distinct temporal epochs of acute (0–7 days), subacute (9–90 days), and chronic (>90 days) stroke with a steep peak in the early subacute period between 14 and 21 days after stroke. Blood NfL values can function as a diagnostic biomarker in distinguishing acute ischemic stroke from transient ischemic attack as well as amongst other cerebrovascular subtypes. Release of NfL into the bloodstream after stroke follows a distinct temporal dynamic that lags several weeks behind stroke onset and reliably associates with a stroke diagnosis despite some variability based on stroke subtype and severity. Identification of these temporal dynamics and the contribution of co- existent cerebrovascular disease states can improve the value of NfL as a stroke biomarker.
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Affiliation(s)
- Jasmin D Sanchez
- Indiana University School of Medicine, Indianapolis, IN, United States
| | | | - Katherine T Mun
- David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Davis S Chong
- David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Irene Lorenzo Llorente
- David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
| | - Timo Uphaus
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Klaus Gröschel
- Department of Neurology, University Medical Center of the Johannes Gutenberg University Mainz, Mainz, Germany
| | - Teresa A Wölfer
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universitat (LMU) Munich, Munich, Germany
| | - Steffen Tiedt
- Institute for Stroke and Dementia Research, University Hospital, Ludwig-Maximilians-Universitat (LMU) Munich, Munich, Germany
| | - Jason D Hinman
- David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, United States
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41
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Therriault J, Pascoal TA, Lussier FZ, Tissot C, Chamoun M, Bezgin G, Servaes S, Benedet AL, Ashton NJ, Karikari TK, Lantero-Rodriguez J, Kunach P, Wang YT, Fernandez-Arias J, Massarweh G, Vitali P, Soucy JP, Saha-Chaudhuri P, Blennow K, Zetterberg H, Gauthier S, Rosa-Neto P. Biomarker modeling of Alzheimer's disease using PET-based Braak staging. NATURE AGING 2022; 2:526-535. [PMID: 37118445 PMCID: PMC10154209 DOI: 10.1038/s43587-022-00204-0] [Citation(s) in RCA: 80] [Impact Index Per Article: 40.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 03/08/2022] [Indexed: 04/30/2023]
Abstract
Gold-standard diagnosis of Alzheimer's disease (AD) relies on histopathological staging systems. Using the topographical information from [18F]MK6240 tau positron-emission tomography (PET), we applied the Braak tau staging system to 324 living individuals. We used PET-based Braak stage to model the trajectories of amyloid-β, phosphorylated tau (pTau) in cerebrospinal fluid (pTau181, pTau217, pTau231 and pTau235) and plasma (pTau181 and pTau231), neurodegeneration and cognitive symptoms. We identified nonlinear AD biomarker trajectories corresponding to the spatial extent of tau-PET, with modest biomarker changes detectable by Braak stage II and significant changes occurring at stages III-IV, followed by plateaus. Early Braak stages were associated with isolated memory impairment, whereas Braak stages V-VI were incompatible with normal cognition. In 159 individuals with follow-up tau-PET, progression beyond stage III took place uniquely in the presence of amyloid-β positivity. Our findings support PET-based Braak staging as a framework to model the natural history of AD and monitor AD severity in living humans.
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Affiliation(s)
- Joseph Therriault
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada.
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada.
| | - Tharick A Pascoal
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
| | - Firoza Z Lussier
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Cécile Tissot
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Mira Chamoun
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Gleb Bezgin
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Andrea L Benedet
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Nicholas J Ashton
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, UK
- Biomedical Research Unit for Dementia at South London, NIHR Biomedical Research Centre for Mental Health and Maudsley NHS Foundation, London, UK
| | - Thomas K Karikari
- Department of Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Juan Lantero-Rodriguez
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Peter Kunach
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Yi-Ting Wang
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Jaime Fernandez-Arias
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Gassan Massarweh
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Paolo Vitali
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Jean-Paul Soucy
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | | | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Henrik Zetterberg
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Serge Gauthier
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Douglas Mental Health Institute, Le Centre intégré universitaire de santé et de services sociaux (CIUSSS) de l'Ouest de l'Île de Montréal, Montreal, Quebec, Canada.
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada.
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42
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Hawksworth J, Fernández E, Gevaert K. A new generation of AD biomarkers: 2019 to 2021. Ageing Res Rev 2022; 79:101654. [PMID: 35636691 DOI: 10.1016/j.arr.2022.101654] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2021] [Revised: 05/17/2022] [Accepted: 05/25/2022] [Indexed: 12/14/2022]
Abstract
Alzheimer's disease (AD) is the most common form of dementia and cases are rising worldwide. The effort to fight this disease is hampered by a lack of disease-modifying treatments and the absence of an early, accurate diagnostic tool. Neuropathology begins years or decades before symptoms occur and, upon onset of symptoms, diagnosis can take a year or more. Such delays postpone treatment and make research into the early stages of the disease difficult. Ideally, clinicians require a minimally invasive test that can detect AD in its early stages, before cognitive symptoms occur. Advances in proteomic technologies have facilitated the study of promising biomarkers of AD. Over the last two years (2019-2021) studies have identified and validated many species which can be measured in cerebrospinal fluid (CSF), plasma, or in both fluids, and which have a high predictive value for AD. We herein discuss proteins which have been highlighted as promising biomarkers of AD in the last two years, and consider implications for future research within the research framework of the amyloid (A), tau (T), neurodegeneration (N) scoring system. We review recently identified species of amyloid and tau which may improve diagnosis when used in combination with current measures such as amyloid-beta-42 (Aβ42), total tau (t-tau) and phosphorylated tau (p-tau). In addition, several proteins have been identified as likely proxies for neurodegeneration, including neurofilament light (NfL), synaptosomal-associated protein 25 (SNAP-25) and neurogranin (NRGN). Finally, proteins originating from diverse processes such as neuroinflammation, lipid transport and mitochondrial dysfunction could aid in both AD diagnosis and patient stratification.
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43
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Salvadó G, Shekari M, Falcon C, Operto G, Milà-Alomà M, Sánchez-Benavides G, Cacciaglia R, Arenaza-Urquijo E, Niñerola-Baizán A, Perissinotti A, Minguillon C, Fauria K, Kollmorgen G, Suridjan I, Molinuevo JL, Zetterberg H, Blennow K, Suárez-Calvet M, Gispert JD. Brain alterations in the early Alzheimer's continuum with amyloid-β, tau, glial and neurodegeneration CSF markers. Brain Commun 2022; 4:fcac134. [PMID: 35702732 PMCID: PMC9185381 DOI: 10.1093/braincomms/fcac134] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Revised: 03/03/2022] [Accepted: 05/20/2022] [Indexed: 11/15/2022] Open
Abstract
Higher grey matter volumes/cortical thickness and fluorodeoxyglucose uptake have been consistently found in cognitively unimpaired individuals with abnormal Alzheimer’s disease biomarkers compared with those with normal biomarkers. It has been hypothesized that such transient increases may be associated with neuroinflammatory mechanisms triggered in response to early Alzheimer’s pathology. Here, we evaluated, in the earliest stages of the Alzheimer’s continuum, associations between grey matter volume and fluorodeoxyglucose uptake with CSF biomarkers of several pathophysiological mechanisms known to be altered in preclinical Alzheimer’s disease stages. We included 319 cognitively unimpaired participants from the ALFA+ cohort with available structural MRI, fluorodeoxyglucose PET and CSF biomarkers of amyloid-β and tau pathology (phosphorylated tau and total tau), synaptic dysfunction (neurogranin), neuronal and axonal injury (neurofilament light), glial activation (soluble triggering receptor on myeloid cells 2, YKL40, GFAP, interleukin-6 and S100b) and α-synuclein using the Roche NeuroToolKit. We first used the amyloid-β/tau framework to investigate differences in the neuroimaging biomarkers between preclinical Alzheimer’s disease stages. Then, we looked for associations between the neuroimaging markers and all the CSF markers. Given the non-negative nature of the concentrations of CSF biomarkers and their high collinearity, we clustered them using non-negative matrix factorization approach (components) and sought associations with the imaging markers. By groups, higher grey matter volumes were found in the amyloid-β-positive tau-negative participants with respect to the reference amyloid-β-negative tau-negative group. Both amyloid-β and tau-positive participants showed higher fluorodeoxyglucose uptake than tau-negative individuals. Using the obtained components, we observed that tau pathology accompanied by YKL-40 (astrocytic marker) was associated with higher grey matter volumes and fluorodeoxyglucose uptake in extensive brain areas. Higher grey matter volumes in key Alzheimer-related regions were also found in association with two other components characterized by a higher expression of amyloid-β in combination with different glial markers: one with higher GFAP and S100b levels (astrocytic markers) and the other one with interleukin-6 (pro-inflammatory). Notably, these components’ expression had different behaviours across amyloid-β/tau stages. Taken together, our results show that CSF amyloid-β and phosphorylated tau, in combination with different aspects of glial response, have distinctive associations with higher grey matter volumes and increased glucose metabolism in key Alzheimer-related regions. These mechanisms combine to produce transient higher grey matter volumes and fluorodeoxyglucose uptake at the earliest stages of the Alzheimer’s continuum, which may revert later on the course of the disease when neurodegeneration drives structural and metabolic cerebral changes.
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Affiliation(s)
- Gemma Salvadó
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
| | - Mahnaz Shekari
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
| | - Carles Falcon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
| | - Grégory Operto
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Marta Milà-Alomà
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Gonzalo Sánchez-Benavides
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Raffaele Cacciaglia
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Eider Arenaza-Urquijo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Aida Niñerola-Baizán
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
- Nuclear Medicine Department, Hospital Clínic Barcelona, Barcelona, Spain
| | - Andrés Perissinotti
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
- Nuclear Medicine Department, Hospital Clínic Barcelona, Barcelona, Spain
| | - Carolina Minguillon
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | - Karine Fauria
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
| | | | | | - José Luis Molinuevo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Fragilidad y Envejecimiento Saludable (CIBERFES), Madrid, Spain
- Servei de Neurologia, Hospital del Mar, Barcelona, Spain
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain
- IMIM (Hospital del MarMedical Research Institute), Barcelona, Spain
- Centro de Investigación Biomédica en Red Bioingeniería, Biomateriales y Nanomedicina, (CIBER-BBN), Barcelona, Spain
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Veitch DP, Weiner MW, Aisen PS, Beckett LA, DeCarli C, Green RC, Harvey D, Jack CR, Jagust W, Landau SM, Morris JC, Okonkwo O, Perrin RJ, Petersen RC, Rivera‐Mindt M, Saykin AJ, Shaw LM, Toga AW, Tosun D, Trojanowski JQ. Using the Alzheimer's Disease Neuroimaging Initiative to improve early detection, diagnosis, and treatment of Alzheimer's disease. Alzheimers Dement 2022; 18:824-857. [PMID: 34581485 PMCID: PMC9158456 DOI: 10.1002/alz.12422] [Citation(s) in RCA: 53] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Revised: 06/08/2021] [Accepted: 06/09/2021] [Indexed: 02/06/2023]
Abstract
INTRODUCTION The Alzheimer's Disease Neuroimaging Initiative (ADNI) has accumulated 15 years of clinical, neuroimaging, cognitive, biofluid biomarker and genetic data, and biofluid samples available to researchers, resulting in more than 3500 publications. This review covers studies from 2018 to 2020. METHODS We identified 1442 publications using ADNI data by conventional search methods and selected impactful studies for inclusion. RESULTS Disease progression studies supported pivotal roles for regional amyloid beta (Aβ) and tau deposition, and identified underlying genetic contributions to Alzheimer's disease (AD). Vascular disease, immune response, inflammation, resilience, and sex modulated disease course. Biologically coherent subgroups were identified at all clinical stages. Practical algorithms and methodological changes improved determination of Aβ status. Plasma Aβ, phosphorylated tau181, and neurofilament light were promising noninvasive biomarkers. Prognostic and diagnostic models were externally validated in ADNI but studies are limited by lack of ethnocultural cohort diversity. DISCUSSION ADNI has had a profound impact in improving clinical trials for AD.
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Affiliation(s)
- Dallas P. Veitch
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA,Department of Veterans Affairs Medical CenterNorthern California Institute for Research and Education (NCIRE)San FranciscoCaliforniaUSA
| | - Michael W. Weiner
- Department of Veterans Affairs Medical CenterCenter for Imaging of Neurodegenerative DiseasesSan FranciscoCaliforniaUSA,Department of RadiologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA,Department of MedicineUniversity of California, San FranciscoSan FranciscoCaliforniaUSA,Department of PsychiatryUniversity of California, San FranciscoSan FranciscoCaliforniaUSA,Department of NeurologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - Paul S. Aisen
- Alzheimer's Therapeutic Research InstituteUniversity of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Laurel A. Beckett
- Division of Biostatistics, Department of Public Health SciencesUniversity of California DavisDavisCaliforniaUSA
| | - Charles DeCarli
- Department of Neurology and Center for NeuroscienceUniversity of California DavisDavisCaliforniaUSA
| | - Robert C. Green
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Broad Institute, Ariadne Labsand Harvard Medical SchoolBostonMassachusettsUSA
| | - Danielle Harvey
- Division of Biostatistics, Department of Public Health SciencesUniversity of California DavisDavisCaliforniaUSA
| | | | - William Jagust
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Susan M. Landau
- Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - John C. Morris
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA
| | - Ozioma Okonkwo
- Wisconsin Alzheimer's Disease Research Center and Department of MedicineUniversity of Wisconsin School of Medicine and Public HealthMadisonWisconsinUSA
| | - Richard J. Perrin
- Knight Alzheimer's Disease Research CenterWashington University School of MedicineSaint LouisMissouriUSA,Department of NeurologyWashington University School of MedicineSaint LouisMissouriUSA,Department of Pathology and ImmunologyWashington University School of MedicineSaint LouisMissouriUSA
| | | | | | - Andrew J. Saykin
- Department of Radiology and Imaging Sciences and Indiana Alzheimer's Disease Research CenterIndiana University School of MedicineIndianapolisIndianaUSA,Department of Medical and Molecular GeneticsIndiana University School of MedicineIndianapolisIndianaUSA
| | - Leslie M. Shaw
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Arthur W. Toga
- Laboratory of Neuroimaging, USC Stevens Institute of Neuroimaging and Informatics, Keck School of MedicineUniversity of Southern CaliforniaLos AngelesCaliforniaUSA
| | - Duygu Tosun
- Department of RadiologyUniversity of California, San FranciscoSan FranciscoCaliforniaUSA
| | - John Q. Trojanowski
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Research, School of MedicineUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
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Gonzales MM, Wang C, Short MI, Parent DM, Kautz T, MacCarthy D, Satizabal CL, González DA, Royall DR, Zare H, O'Bryant S, Maestre GE, Tracy RP, Seshadri S. Blood biomarkers for cognitive decline and clinical progression in a Mexican American cohort. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12298. [PMID: 35356487 PMCID: PMC8943903 DOI: 10.1002/dad2.12298] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 12/14/2021] [Accepted: 01/31/2022] [Indexed: 01/04/2023]
Abstract
Introduction: The clinical translation of biofluid markers for dementia requires validation in diverse cohorts. The study goal was to evaluate if blood biomarkers reflecting diverse pathophysiological processes predict disease progression in Mexican American adults. Methods: Mexican American adults (n = 745), 50 years of age and older, completed annual assessments over a mean of 4 years. Serum collected at baseline was assayed for total tau, neurofilament light (NFL), ubiquitin carboxyl-terminal hydrolase LI, glial fibrillary acidic protein (GFAP), soluble cluster of differentiation 14 (sCD14), and chitinase-3-like protein 1 (YKL-40). Results: Higher GFAP and NFL were associated with global cognitive decline. Only GFAP was associated with increased incident dementia risk (hazard ratio: 1.611 (95% confidence interval: 1.204-2.155)) and inclusion of additional biomarkers did not improve model fit. Discussion: Among a panel of six blood biomarkers previously associated with neurodegenerative disease, only GFAP predicted incident dementia in our cohort. The findings suggest that blood GFAP levels may aid dementia-risk prediction among Mexican American adults.
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Affiliation(s)
- Mitzi M. Gonzales
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science CenterSan AntonioTexasUSA
- Department of NeurologyUniversity of Texas Health Science CenterSan AntonioTexasUSA
| | - Chen‐Pin Wang
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science CenterSan AntonioTexasUSA
- Department of Population Health SciencesUniversity of Texas Health Science CenterSan AntonioTexasUSA
- Education & Clinical CenterSouth Texas Veterans Health Care System, Geriatric ResearchSan AntonioTexasUSA
| | - Meghan I. Short
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science CenterSan AntonioTexasUSA
- Broad Institute, Massachusetts Institute of TechnologyMassachusettsCambridgeUSA
| | - Danielle M. Parent
- Departments of Pathology & Laboratory Medicine, and BiochemistryLarner College of Medicine, University of VermontVermontBurlingtonUSA
| | - Tiffany Kautz
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science CenterSan AntonioTexasUSA
| | - Daniel MacCarthy
- Department of Population Health SciencesUniversity of Texas Health Science CenterSan AntonioTexasUSA
- Education & Clinical CenterSouth Texas Veterans Health Care System, Geriatric ResearchSan AntonioTexasUSA
| | - Claudia L. Satizabal
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science CenterSan AntonioTexasUSA
- Department of Population Health SciencesUniversity of Texas Health Science CenterSan AntonioTexasUSA
- Department of NeurologyBoston University School of MedicineMassachusettsBostonUSA
| | - David Andrés González
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science CenterSan AntonioTexasUSA
- Department of NeurologyUniversity of Texas Health Science CenterSan AntonioTexasUSA
| | - Donald R. Royall
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science CenterSan AntonioTexasUSA
| | - Habil Zare
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science CenterSan AntonioTexasUSA
- Department of Cell Systems and AnatomyUniversity of Texas Health Science CenterSan AntonioTexasUSA
| | - Sid O'Bryant
- Institute for Translational Research and Department of Pharmacology & NeuroscienceUniversity of North Texas Health Science CenterFort WorthTexasUSA
| | - Gladys E. Maestre
- Neurosciences Laboratory, Biological Research Institute and Research Institute of Cardiovascular Diseases, Faculty of MedicineUniversidad del ZuliaMaracaiboVenezuela
- Department of Biomedical SciencesDivision of NeurosciencesUniversity of Texas Rio Grande Valley School of MedicineBrownsvilleTexasUSA
| | - Russell P. Tracy
- Departments of Pathology & Laboratory Medicine, and BiochemistryLarner College of Medicine, University of VermontVermontBurlingtonUSA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science CenterSan AntonioTexasUSA
- Department of NeurologyUniversity of Texas Health Science CenterSan AntonioTexasUSA
- Department of NeurologyBoston University School of MedicineMassachusettsBostonUSA
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46
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Ren R, Qi J, Lin S, Liu X, Yin P, Wang Z, Tang R, Wang J, Huang Q, Li J, Xie X, Hu Y, Cui S, Zhu Y, Yu X, Wang P, Zhu Y, Wang Y, Huang Y, Hu Y, Wang Y, Li C, Zhou M, Wang G. The China Alzheimer Report 2022. Gen Psychiatr 2022; 35:e100751. [PMID: 35372787 PMCID: PMC8919463 DOI: 10.1136/gpsych-2022-100751] [Citation(s) in RCA: 70] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 02/23/2022] [Indexed: 01/22/2023] Open
Abstract
China’s population has rapidly aged over the recent decades of social and economic development as neurodegenerative disorders have proliferated, especially Alzheimer’s disease (AD) and related dementias (ADRD). AD’s incidence rate, morbidity, and mortality have steadily increased to make it presently the fifth leading cause of death among urban and rural residents in China and magnify the resulting financial burdens on individuals, families and society. The ‘Healthy China Action’ plan of 2019–2030 promotes the transition from disease treatment to health maintenance for this expanding population with ADRD. This report describes related epidemiological trends, evaluates the economic burden of the disease, outlines current clinical diagnosis and treatment status and delineates existing available public health resources. More specifically, it examines the public health impact of ADRD, including prevalence, mortality, costs, usage of care, and the overall effect on caregivers and society. In addition, this special report presents technical guidance and supports for the prevention and treatment of AD, provides expertise to guide relevant governmental healthcare policy development and suggests an information platform for international exchange and cooperation.
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Affiliation(s)
- Rujing Ren
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jinlei Qi
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Shaohui Lin
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xinya Liu
- School of Public Health, Fudan University, Shanghai, China
- NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Peng Yin
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Zhihui Wang
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ran Tang
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jintao Wang
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Qiang Huang
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Jianping Li
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xinyi Xie
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yongbo Hu
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Shishuang Cui
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yuan Zhu
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Xiaoping Yu
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Pengfei Wang
- School of Public Health, Fudan University, Shanghai, China
- NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Yikang Zhu
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yiran Wang
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Yanyan Huang
- Department of Geriatrics, Huashan Hospital, Fudan University, Shanghai, China
| | - Yisong Hu
- National Survey Research Center, Renmin University of China, Beijing, China
| | - Ying Wang
- School of Public Health, Fudan University, Shanghai, China
- NHC Key Laboratory of Health Technology Assessment, Fudan University, Shanghai, China
| | - Chunbo Li
- Shanghai Key Laboratory of Psychotic Disorders, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Maigeng Zhou
- National Center for Chronic and Noncommunicable Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Gang Wang
- Department of Neurology and Institute of Neurology, Ruijin Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China
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Álvarez-Sánchez L, Peña-Bautista C, Baquero M, Cháfer-Pericás C. Novel Ultrasensitive Detection Technologies for the Identification of Early and Minimally Invasive Alzheimer's Disease Blood Biomarkers. J Alzheimers Dis 2022; 86:1337-1369. [PMID: 35213367 DOI: 10.3233/jad-215093] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
BACKGROUND Single molecule array (SIMOA) and other ultrasensitive detection technologies have allowed the determination of blood-based biomarkers of Alzheimer's disease (AD) for diagnosis and monitoring, thereby opening up a promising field of research. OBJECTIVE To review the published bibliography on plasma biomarkers in AD using new ultrasensitive techniques. METHODS A systematic review of the PubMed database was carried out to identify reports on the use of blood-based ultrasensitive technology to identify biomarkers for AD. RESULTS Based on this search, 86 works were included and classified according to the biomarker determined. First, plasma amyloid-β showed satisfactory accuracy as an AD biomarker in patients with a high risk of developing dementia. Second, plasma t-Tau displayed good sensitivity in detecting different neurodegenerative diseases. Third, plasma p-Tau was highly specific for AD. Fourth, plasma NfL was highly sensitive for distinguishing between patients with neurodegenerative diseases and healthy controls. In general, the simultaneous determination of several biomarkers facilitated greater accuracy in diagnosing AD (Aβ42/Aβ40, p-Tau181/217). CONCLUSION The recent development of ultrasensitive technology allows the determination of blood-based biomarkers with high sensitivity, thus facilitating the early detection of AD through the analysis of easily obtained biological samples. In short, as a result of this knowledge, pre-symptomatic and early AD diagnosis may be possible, and the recruitment process for future clinical trials could be more precise. However, further studies are necessary to standardize levels of blood-based biomarkers in the general population and thus achieve reproducible results among different laboratories.
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Affiliation(s)
| | - Carmen Peña-Bautista
- Alzheimer Disease Research Group, Health Research Institute La Fe, Valencia, Spain
| | - Miguel Baquero
- Division of Neurology, University and Polytechnic Hospital La Fe, Valencia, Spain
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48
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Leuzy A, Mattsson‐Carlgren N, Palmqvist S, Janelidze S, Dage JL, Hansson O. Blood-based biomarkers for Alzheimer's disease. EMBO Mol Med 2022; 14:e14408. [PMID: 34859598 PMCID: PMC8749476 DOI: 10.15252/emmm.202114408] [Citation(s) in RCA: 129] [Impact Index Per Article: 64.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2021] [Revised: 11/02/2021] [Accepted: 11/05/2021] [Indexed: 12/01/2022] Open
Abstract
Neurodegenerative disorders such as Alzheimer's disease (AD) represent a mounting public health challenge. As these diseases are difficult to diagnose clinically, biomarkers of underlying pathophysiology are playing an ever-increasing role in research, clinical trials, and in the clinical work-up of patients. Though cerebrospinal fluid (CSF) and positron emission tomography (PET)-based measures are available, their use is not widespread due to limitations, including high costs and perceived invasiveness. As a result of rapid advances in the development of ultra-sensitive assays, the levels of pathological brain- and AD-related proteins can now be measured in blood, with recent work showing promising results. Plasma P-tau appears to be the best candidate marker during symptomatic AD (i.e., prodromal AD and AD dementia) and preclinical AD when combined with Aβ42/Aβ40. Though not AD-specific, blood NfL appears promising for the detection of neurodegeneration and could potentially be used to detect the effects of disease-modifying therapies. This review provides an overview of the progress achieved thus far using AD blood-based biomarkers, highlighting key areas of application and unmet challenges.
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Affiliation(s)
- Antoine Leuzy
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityMalmöSweden
| | - Niklas Mattsson‐Carlgren
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityMalmöSweden
- Department of NeurologySkåne University HospitalLundSweden
- Wallenberg Centre for Molecular MedicineLund UniversityLundSweden
| | - Sebastian Palmqvist
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityMalmöSweden
- Memory ClinicSkåne University HospitalLundSweden
| | - Shorena Janelidze
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityMalmöSweden
| | - Jeffrey L Dage
- Stark Neuroscience Research InstituteIndiana University School of MedicineIndianapolisINUSA
| | - Oskar Hansson
- Clinical Memory Research UnitDepartment of Clinical SciencesLund UniversityMalmöSweden
- Memory ClinicSkåne University HospitalLundSweden
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Frisoni GB, Altomare D, Thal DR, Ribaldi F, van der Kant R, Ossenkoppele R, Blennow K, Cummings J, van Duijn C, Nilsson PM, Dietrich PY, Scheltens P, Dubois B. The probabilistic model of Alzheimer disease: the amyloid hypothesis revised. Nat Rev Neurosci 2022; 23:53-66. [PMID: 34815562 PMCID: PMC8840505 DOI: 10.1038/s41583-021-00533-w] [Citation(s) in RCA: 185] [Impact Index Per Article: 92.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/04/2021] [Indexed: 01/03/2023]
Abstract
The current conceptualization of Alzheimer disease (AD) is driven by the amyloid hypothesis, in which a deterministic chain of events leads from amyloid deposition and then tau deposition to neurodegeneration and progressive cognitive impairment. This model fits autosomal dominant AD but is less applicable to sporadic AD. Owing to emerging information regarding the complex biology of AD and the challenges of developing amyloid-targeting drugs, the amyloid hypothesis needs to be reconsidered. Here we propose a probabilistic model of AD in which three variants of AD (autosomal dominant AD, APOE ε4-related sporadic AD and APOE ε4-unrelated sporadic AD) feature decreasing penetrance and decreasing weight of the amyloid pathophysiological cascade, and increasing weight of stochastic factors (environmental exposures and lower-risk genes). Together, these variants account for a large share of the neuropathological and clinical variability observed in people with AD. The implementation of this model in research might lead to a better understanding of disease pathophysiology, a revision of the current clinical taxonomy and accelerated development of strategies to prevent and treat AD.
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Affiliation(s)
- Giovanni B. Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland.,Memory Clinic, Geneva University Hospitals, Geneva, Switzerland.,
| | - Daniele Altomare
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland.,Memory Clinic, Geneva University Hospitals, Geneva, Switzerland
| | - Dietmar Rudolf Thal
- Laboratory for Neuropathology, Department of Imaging and Pathology, and Leuven Brain Institute, University of Leuven, Leuven, Belgium.,Department of Pathology, University Hospital Leuven, Leuven, Belgium
| | - Federica Ribaldi
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland.,Memory Clinic, Geneva University Hospitals, Geneva, Switzerland.,Laboratory of Alzheimer’s Neuroimaging and Epidemiology (LANE), IRCCS Centro S. Giovanni di Dio Fatebenefratelli, Brescia, Italy.,Department of Molecular and Translational Medicine, University of Brescia, Brescia, Italy
| | - Rik van der Kant
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands.,Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands.,Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Kaj Blennow
- Cinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Department of Brain Health, School of Integrated Health Sciences; University of Nevada, Las Vegas, Las Vegas, NV, USA
| | - Cornelia van Duijn
- Department of Epidemiology, Erasmus University Medical Center, Rotterdam, Netherlands.,Clinical Trial Service Unit and Epidemiological Studies Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Peter M. Nilsson
- Department of Clinical Sciences, Lund University, Skåne University Hospital, Malmö, Sweden
| | | | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands.,Life Science Partners, Amsterdam, Netherlands
| | - Bruno Dubois
- Institut de la Mémoire et de la Maladie d’Alzheimer, IM2A, Groupe Hospitalier Pitié-Salpêtrière, Sorbonne Université, Paris, France.,Institut du Cerveau et de la Moelle Épinière, UMR-S975, INSERM, Paris, France
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50
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Ma LZ, Hu H, Wang ZT, Ou YN, Dong Q, Tan L, Yu JT. P-tau and neurodegeneration mediate the effect of β-amyloid on cognition in non-demented elders. Alzheimers Res Ther 2021; 13:200. [PMID: 34911582 PMCID: PMC8675473 DOI: 10.1186/s13195-021-00943-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2021] [Accepted: 12/05/2021] [Indexed: 04/12/2023]
Abstract
BACKGROUND There are many pathological changes in the brains of Alzheimer's disease (AD) patients. For many years, the mainstream view on the pathogenesis of AD believes that β-amyloid (Aβ) usually acts independently in addition to triggering functions. However, the evidence now accumulating indicates another case that these pathological types have synergies. The objective of this study was to investigate whether effects of Aβ pathology on cognition were mediated by AD pathologies, including tau-related pathology (p-tau), neurodegeneration (t-tau, MRI measurements), axonal injury (NFL), synaptic dysfunction (neurogranin), and neuroinflammation (sTREM2, YKL-40). METHODS Three hundred seventy normal controls (CN) and 623 MCI patients from the ADNI (Alzheimer's Disease Neuroimaging Initiative) database were recruited in this research. Linear mixed-effects models were used to evaluate the associations of baseline Aβ with cognitive decline and biomarkers of several pathophysiological pathways. Causal mediation analyses with 10,000 bootstrapped iterations were conducted to explore the mediation effects of AD pathologies on cognition. RESULTS Tau-related pathology, neurodegeneration, neuroinflammation are correlated with the concentration of Aβ, even in CN participants. The results show that age, gender, and APOE ε4 carrier status have a moderating influence on some of these relationships. There is a stronger association of Aβ with biomarkers and cognitive changes in the elderly and females. In CN group, Aβ pathology is directly related to poor cognition and has no mediating effect (p < 0.05). In mild cognitive impairment, tau-related pathology (26.15% of total effect) and neurodegeneration (14.8% to 47.0% of total effect) mediate the impact of Aβ on cognition. CONCLUSIONS In conclusion, early Aβ accumulation has an independent effect on cognitive decline in CN and a tau, neurodegeneration-dependent effect in the subsequent cognitive decline in MCI patients.
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Affiliation(s)
- Ling-Zhi Ma
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China
| | - Hao Hu
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China
| | - Zuo-Teng Wang
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China
| | - Ya-Nan Ou
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China
| | - Qiang Dong
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12th Wulumuqi Zhong Road, Shanghai, 200040, China
| | - Lan Tan
- Department of Neurology, Qingdao Municipal Hospital, Qingdao University, Qingdao, 266071, China.
| | - Jin-Tai Yu
- Department of Neurology and Institute of Neurology, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, 12th Wulumuqi Zhong Road, Shanghai, 200040, China.
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