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Barsoum S, Latimer CS, Nolan AL, Barrett A, Chang K, Troncoso J, Keene CD, Benjamini D. Resiliency to Alzheimer's disease neuropathology can be distinguished from dementia using cortical astrogliosis imaging. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.06.592719. [PMID: 38766087 PMCID: PMC11100587 DOI: 10.1101/2024.05.06.592719] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Despite the presence of significant Alzheimer's disease (AD) pathology, characterized by amyloid β (Aβ) plaques and phosphorylated tau (pTau) tangles, some cognitively normal elderly individuals do not inevitably develop dementia. These findings give rise to the notion of cognitive 'resilience', suggesting maintained cognitive function despite the presence of AD neuropathology, highlighting the influence of factors beyond classical pathology. Cortical astroglial inflammation, a ubiquitous feature of symptomatic AD, shows a strong correlation with cognitive impairment severity, potentially contributing to the diversity of clinical presentations. However, noninvasively imaging neuroinflammation, particularly astrogliosis, using MRI remains a significant challenge. Here we sought to address this challenge and to leverage multidimensional (MD) MRI, a powerful approach that combines relaxation with diffusion MR contrasts, to map cortical astrogliosis in the human brain by accessing sub-voxel information. Our goal was to test whether MD-MRI can map astroglial pathology in the cerebral cortex, and if so, whether it can distinguish cognitive resiliency from dementia in the presence of hallmark AD neuropathological changes. We adopted a multimodal approach by integrating histological and MRI analyses using human postmortem brain samples. Ex vivo cerebral cortical tissue specimens derived from three groups comprised of non-demented individuals with significant AD pathology postmortem, individuals with both AD pathology and dementia, and non-demented individuals with minimal AD pathology postmortem as controls, underwent MRI at 7 T. We acquired and processed MD-MRI, diffusion tensor, and quantitative T 1 and T 2 MRI data, followed by histopathological processing on slices from the same tissue. By carefully co-registering MRI and microscopy data, we performed quantitative multimodal analyses, leveraging targeted immunostaining to assess MD-MRI sensitivity and specificity towards Aβ, pTau, and glial fibrillary acidic protein (GFAP), a marker for astrogliosis. Our findings reveal a distinct MD-MRI signature of cortical astrogliosis, enabling the creation of predictive maps for cognitive resilience amid AD neuropathological changes. Multiple linear regression linked histological values to MRI changes, revealing that the MD-MRI cortical astrogliosis biomarker was significantly associated with GFAP burden (standardized β=0.658, pFDR<0.0001), but not with Aβ (standardized β=0.009, p FDR =0.913) or pTau (standardized β=-0.196, p FDR =0.051). Conversely, none of the conventional MRI parameters showed significant associations with GFAP burden in the cortex. While the extent to which pathological glial activation contributes to neuronal damage and cognitive impairment in AD is uncertain, developing a noninvasive imaging method to see its affects holds promise from a mechanistic perspective and as a potential predictor of cognitive outcomes.
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Mantellatto Grigoli M, Pelegrini LNC, Whelan R, Cominetti MR. Present and Future of Blood-Based Biomarkers of Alzheimer's Disease: Beyond the Classics. Brain Res 2024; 1830:148812. [PMID: 38369085 DOI: 10.1016/j.brainres.2024.148812] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Revised: 11/13/2023] [Accepted: 02/13/2024] [Indexed: 02/20/2024]
Abstract
The field of blood-based biomarkers for Alzheimer's disease (AD) has advanced at an incredible pace, especially after the development of sensitive analytic platforms that can facilitate large-scale screening. Such screening will be important when more sophisticated diagnostic methods are scarce and expensive. Thus, blood-based biomarkers can potentially reduce diagnosis inequities among populations from different socioeconomic contexts. This large-scale screening can be performed so that older adults at risk of cognitive decline assessed using these methods can then undergo more complete assessments with classic biomarkers, increasing diagnosis efficiency and reducing costs to the health systems. Blood-based biomarkers can also aid in assessing the effect of new disease-modifying treatments. This paper reviews recent advances in the area, focusing on the following leading candidates for blood-based biomarkers: amyloid-beta (Aβ), phosphorylated tau isoforms (p-tau), neurofilament light (NfL), and glial fibrillary acidic (GFAP) proteins, as well as on new candidates, Neuron-Derived Exosomes contents (NDEs) and Transactive response DNA-binding protein-43 (TDP-43), based on data from longitudinal observational cohort studies. The underlying challenges of validating and incorporating these biomarkers into routine clinical practice and primary care settings are also discussed. Importantly, challenges related to the underrepresentation of ethnic minorities and socioeconomically disadvantaged persons must be considered. If these challenges are overcome, a new time of cost-effective blood-based biomarkers for AD could represent the future of clinical procedures in the field and, together with continued prevention strategies, the beginning of an era with a lower incidence of dementia worldwide.
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Affiliation(s)
| | | | - Robert Whelan
- Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland; School of Psychology, Trinity College Dublin, Dublin, Ireland
| | - Marcia R Cominetti
- Department of Gerontology, Federal University of São Carlos, Brazil; Global Brain Health Institute, Trinity College Dublin, Dublin, Ireland.
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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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Dark HE, Duggan MR, Walker KA. Plasma biomarkers for Alzheimer's and related dementias: A review and outlook for clinical neuropsychology. Arch Clin Neuropsychol 2024; 39:313-324. [PMID: 38520383 DOI: 10.1093/arclin/acae019] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 02/05/2024] [Indexed: 03/25/2024] Open
Abstract
Recent technological advances have improved the sensitivity and specificity of blood-based biomarkers for Alzheimer's disease and related dementias. Accurate quantification of amyloid-ß peptide, phosphorylated tau (pTau) isoforms, as well as markers of neurodegeneration (neurofilament light chain [NfL]) and neuro-immune activation (glial fibrillary acidic protein [GFAP] and chitinase-3-like protein 1 [YKL-40]) in blood has allowed researchers to characterize neurobiological processes at scale in a cost-effective and minimally invasive manner. Although currently used primarily for research purposes, these blood-based biomarkers have the potential to be highly impactful in the clinical setting - aiding in diagnosis, predicting disease risk, and monitoring disease progression. Whereas plasma NfL has shown promise as a non-specific marker of neuronal injury, plasma pTau181, pTau217, pTau231, and GFAP have demonstrated desirable levels of sensitivity and specificity for identification of individuals with Alzheimer's disease pathology and Alzheimer's dementia. In this forward looking review, we (i) provide an overview of the most commonly used blood-based biomarkers for Alzheimer's disease and related dementias, (ii) discuss how comorbid medical conditions, demographic, and genetic factors can inform the interpretation of these biomarkers, (iii) describe ongoing efforts to move blood-based biomarkers into the clinic, and (iv) highlight the central role that clinical neuropsychologists may play in contextualizing and communicating blood-based biomarker results for patients.
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Affiliation(s)
- Heather E Dark
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
| | - Michael R Duggan
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
| | - Keenan A Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging, Intramural Research Program, Baltimore, MD, USA
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Lu Y, Pike JR, Hoogeveen R, Walker K, Raffield L, Selvin E, Avery C, Engel S, Mielke MM, Garcia T, Heiss G, Palta P. Nonalcoholic Fatty Liver Disease and Longitudinal Change in Imaging and Plasma Biomarkers of Alzheimer Disease and Vascular Pathology. Neurology 2024; 102:e209203. [PMID: 38471046 PMCID: PMC11033987 DOI: 10.1212/wnl.0000000000209203] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 01/23/2024] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Prospective measures of plasma and cerebral MRI biomarkers of Alzheimer disease (AD) and vascular neuropathology provide an opportunity to investigate possible mechanisms linking liver disease and dementia. We aimed to quantify the association of midlife nonalcoholic fatty liver disease (NAFLD) with change in plasma and brain MRI biomarkers of AD and vascular neuropathology. METHODS We included participants from the Atherosclerosis Risk in Communities Study with brain MRI measurements of white matter hyperintensity (WMH) volume and temporal-parietal lobe cortical thickness meta region of interest (ROI) at up to 2 different visits, in 2011-13 and 2016-19, and plasma biomarkers of β-amyloid (Aβ)42:40, phosphorylated tau at threonine 181, and neurofilament light (NfL) were measured up to 3 times in 1993-95, 2011-13, and 2016-19. NAFLD was categorized using the fatty liver index in 1990-92. Multivariate linear regression was performed for associations between midlife NAFLD and change in plasma and brain MRI biomarkers of AD and vascular neuropathology. The primary models adjusted for demographics, Apolipoprotein E, alcohol use, and kidney function. RESULTS Among 1,706 participants (mean age 56 years, 62% female, 28% Black), midlife NAFLD vs no NAFLD was associated with greater late-life WMH volume (difference per SD 0.19, 95% CI 0.06-0.31) and faster late-life WMH increase over 6 years (difference in annual change, SD 0.28, 95% CI 0.05-0.51), suggesting accumulating vascular pathology. Midlife NAFLD vs no NAFLD was also associated with AD biomarkers in midlife (lower Aβ42:40 [SD -0.21, 95% CI -0.39 to -0.04] measured in 1993-95) and late life (lower Aβ42:40 [SD -0.13, 95% CI -0.23 to -0.03] and lower temporal-parietal lobe cortical thickness meta ROI [SD -0.16, 95% CI -0.28 to -0.05] measured in 2011-13). Although midlife NfL was lower in individuals with vs without midlife NAFLD, those with NAFLD exhibited a faster rate of NfL increase that accelerated over time. DISCUSSION Midlife NAFLD shows associations with AD and accumulating vascular pathology, revealing potential pathways linking liver function to dementia. Plasma biomarkers of neuropathology and neuronal injury may serve as easily measurable and dynamic indicators for monitoring the impacts of impaired liver function on brain health.
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Affiliation(s)
- Yifei Lu
- From the Departments of Epidemiology (Y.L., C.A., S.E., G.H.) and Biostatistics (T.G.), Gillings School of Global Public Health and Departments of Genetics (L.R.) and Neurology (P.P.), School of Medicine, University of North Carolina at Chapel Hill, NC; Department of Epidemiology (J.R.P., E.S.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Medicine (R.H.), Baylor College of Medicine, Houston, TX; Laboratory of Behavioral Neuroscience (K.W.), National Institute on Aging, Bethesda, MD; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - James R Pike
- From the Departments of Epidemiology (Y.L., C.A., S.E., G.H.) and Biostatistics (T.G.), Gillings School of Global Public Health and Departments of Genetics (L.R.) and Neurology (P.P.), School of Medicine, University of North Carolina at Chapel Hill, NC; Department of Epidemiology (J.R.P., E.S.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Medicine (R.H.), Baylor College of Medicine, Houston, TX; Laboratory of Behavioral Neuroscience (K.W.), National Institute on Aging, Bethesda, MD; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Ron Hoogeveen
- From the Departments of Epidemiology (Y.L., C.A., S.E., G.H.) and Biostatistics (T.G.), Gillings School of Global Public Health and Departments of Genetics (L.R.) and Neurology (P.P.), School of Medicine, University of North Carolina at Chapel Hill, NC; Department of Epidemiology (J.R.P., E.S.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Medicine (R.H.), Baylor College of Medicine, Houston, TX; Laboratory of Behavioral Neuroscience (K.W.), National Institute on Aging, Bethesda, MD; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Keenan Walker
- From the Departments of Epidemiology (Y.L., C.A., S.E., G.H.) and Biostatistics (T.G.), Gillings School of Global Public Health and Departments of Genetics (L.R.) and Neurology (P.P.), School of Medicine, University of North Carolina at Chapel Hill, NC; Department of Epidemiology (J.R.P., E.S.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Medicine (R.H.), Baylor College of Medicine, Houston, TX; Laboratory of Behavioral Neuroscience (K.W.), National Institute on Aging, Bethesda, MD; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Laura Raffield
- From the Departments of Epidemiology (Y.L., C.A., S.E., G.H.) and Biostatistics (T.G.), Gillings School of Global Public Health and Departments of Genetics (L.R.) and Neurology (P.P.), School of Medicine, University of North Carolina at Chapel Hill, NC; Department of Epidemiology (J.R.P., E.S.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Medicine (R.H.), Baylor College of Medicine, Houston, TX; Laboratory of Behavioral Neuroscience (K.W.), National Institute on Aging, Bethesda, MD; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Elizabeth Selvin
- From the Departments of Epidemiology (Y.L., C.A., S.E., G.H.) and Biostatistics (T.G.), Gillings School of Global Public Health and Departments of Genetics (L.R.) and Neurology (P.P.), School of Medicine, University of North Carolina at Chapel Hill, NC; Department of Epidemiology (J.R.P., E.S.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Medicine (R.H.), Baylor College of Medicine, Houston, TX; Laboratory of Behavioral Neuroscience (K.W.), National Institute on Aging, Bethesda, MD; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Christy Avery
- From the Departments of Epidemiology (Y.L., C.A., S.E., G.H.) and Biostatistics (T.G.), Gillings School of Global Public Health and Departments of Genetics (L.R.) and Neurology (P.P.), School of Medicine, University of North Carolina at Chapel Hill, NC; Department of Epidemiology (J.R.P., E.S.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Medicine (R.H.), Baylor College of Medicine, Houston, TX; Laboratory of Behavioral Neuroscience (K.W.), National Institute on Aging, Bethesda, MD; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Stephanie Engel
- From the Departments of Epidemiology (Y.L., C.A., S.E., G.H.) and Biostatistics (T.G.), Gillings School of Global Public Health and Departments of Genetics (L.R.) and Neurology (P.P.), School of Medicine, University of North Carolina at Chapel Hill, NC; Department of Epidemiology (J.R.P., E.S.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Medicine (R.H.), Baylor College of Medicine, Houston, TX; Laboratory of Behavioral Neuroscience (K.W.), National Institute on Aging, Bethesda, MD; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Michelle M Mielke
- From the Departments of Epidemiology (Y.L., C.A., S.E., G.H.) and Biostatistics (T.G.), Gillings School of Global Public Health and Departments of Genetics (L.R.) and Neurology (P.P.), School of Medicine, University of North Carolina at Chapel Hill, NC; Department of Epidemiology (J.R.P., E.S.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Medicine (R.H.), Baylor College of Medicine, Houston, TX; Laboratory of Behavioral Neuroscience (K.W.), National Institute on Aging, Bethesda, MD; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Tanya Garcia
- From the Departments of Epidemiology (Y.L., C.A., S.E., G.H.) and Biostatistics (T.G.), Gillings School of Global Public Health and Departments of Genetics (L.R.) and Neurology (P.P.), School of Medicine, University of North Carolina at Chapel Hill, NC; Department of Epidemiology (J.R.P., E.S.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Medicine (R.H.), Baylor College of Medicine, Houston, TX; Laboratory of Behavioral Neuroscience (K.W.), National Institute on Aging, Bethesda, MD; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Gerardo Heiss
- From the Departments of Epidemiology (Y.L., C.A., S.E., G.H.) and Biostatistics (T.G.), Gillings School of Global Public Health and Departments of Genetics (L.R.) and Neurology (P.P.), School of Medicine, University of North Carolina at Chapel Hill, NC; Department of Epidemiology (J.R.P., E.S.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Medicine (R.H.), Baylor College of Medicine, Houston, TX; Laboratory of Behavioral Neuroscience (K.W.), National Institute on Aging, Bethesda, MD; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
| | - Priya Palta
- From the Departments of Epidemiology (Y.L., C.A., S.E., G.H.) and Biostatistics (T.G.), Gillings School of Global Public Health and Departments of Genetics (L.R.) and Neurology (P.P.), School of Medicine, University of North Carolina at Chapel Hill, NC; Department of Epidemiology (J.R.P., E.S.), Johns Hopkins Bloomberg School of Public Health, Baltimore, MD; Department of Medicine (R.H.), Baylor College of Medicine, Houston, TX; Laboratory of Behavioral Neuroscience (K.W.), National Institute on Aging, Bethesda, MD; and Department of Epidemiology and Prevention (M.M.M.), Wake Forest University School of Medicine, Winston-Salem, NC
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Wang J, Huang Q, Chen X, You Z, He K, Guo Q, Huang Y, Yang Y, Lin Z, Guo T, Zhao J, Guan Y, Li B, Xie F. Tau pathology is associated with synaptic density and longitudinal synaptic loss in Alzheimer's disease. Mol Psychiatry 2024:10.1038/s41380-024-02501-z. [PMID: 38589563 DOI: 10.1038/s41380-024-02501-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/22/2023] [Revised: 02/23/2024] [Accepted: 02/27/2024] [Indexed: 04/10/2024]
Abstract
The associations of synaptic loss with amyloid-β (Aβ) and tau pathology measured by positron emission tomography (PET) and plasma analysis in Alzheimer's disease (AD) patients are unknown. Seventy-five participants, including 26 AD patients, 19 mild cognitive impairment (MCI) patients, and 30 normal controls (NCs), underwent [18F]SynVesT-1 PET/MR scans to assess synaptic density and [18F]florbetapir and [18F]MK6240 PET/CT scans to evaluate Aβ plaques and tau tangles. Among them, 19 AD patients, 12 MCI patients, and 29 NCs had plasma Aβ42/40 and p-tau181 levels measured by the Simoa platform. Twenty-three individuals, 6 AD patients, 4 MCI patients, and 13 NCs, underwent [18F]SynVesT-1 PET/MRI and [18F]MK6240 PET/CT scans during a one-year follow-up assessment. The associations of Aβ and tau pathology with cross-sectional and longitudinal synaptic loss were investigated using Pearson correlation analyses, generalized linear models and mediation analyses. AD patients exhibited lower synaptic density than NCs and MCI patients. In the whole cohort, global Aβ deposition was associated with synaptic loss in the medial (r = -0.431, p < 0.001) and lateral (r = -0.406, p < 0.001) temporal lobes. Synaptic density in almost all regions was related to the corresponding regional tau tangles independent of global Aβ deposition in the whole cohort and stratified groups. Synaptic density in the medial and lateral temporal lobes was correlated with plasma Aβ42/40 (r = 0.300, p = 0.020/r = 0.289, p = 0.025) and plasma p-tau 181 (r = -0.412, p = 0.001/r = -0.529, p < 0.001) levels in the whole cohort. Mediation analyses revealed that tau tangles mediated the relationship between Aβ plaques and synaptic density in the whole cohort. Baseline tau pathology was positively associated with longitudinal synaptic loss. This study suggested that tau burden is strongly linked to synaptic density independent of Aβ plaques, and also can predict longitudinal synaptic loss.
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Affiliation(s)
- Jie Wang
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Qi Huang
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Xing Chen
- Department of Nuclear Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 310000, China
| | - Zhiwen You
- Department of Nuclear Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 310000, China
| | - Kun He
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, 200040, China
| | - Qihao Guo
- Department of Gerontology, Shanghai Jiaotong University Affiliated Sixth People's Hospital, Shanghai, 200233, China
| | - Yiyun Huang
- PET Center, Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, Connecticut, CT, 06520-8048, USA
| | - Yang Yang
- Beijing United Imaging Research Institute of Intelligent Imaging, Beijing, 100089, China
| | - Zengping Lin
- Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, 201807, China
| | - Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Shenzhen, 518000, China
| | - Jun Zhao
- Department of Nuclear Medicine, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, 310000, China
| | - Yihui Guan
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, 200040, China.
| | - Binyin Li
- Department of Neurology and Institute of Neurology, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Fang Xie
- Department of Nuclear Medicine & PET Center, Huashan Hospital, Fudan University, Shanghai, 200040, China.
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7
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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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Sewell KR, Rainey-Smith SR, Pedrini S, Peiffer JJ, Sohrabi HR, Taddei K, Markovic SJ, Martins RN, Brown BM. The impact of exercise on blood-based biomarkers of Alzheimer's disease in cognitively unimpaired older adults. GeroScience 2024:10.1007/s11357-024-01130-2. [PMID: 38488949 DOI: 10.1007/s11357-024-01130-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2024] [Accepted: 03/08/2024] [Indexed: 03/17/2024] Open
Abstract
Physical activity is a promising preventative strategy for Alzheimer's disease: it is associated with lower dementia risk, better cognition, greater brain volume and lower brain beta-amyloid. Blood-based biomarkers have emerged as a low-cost, non-invasive strategy for detecting preclinical Alzheimer's disease, however, there is limited literature examining the effect of exercise (a structured form of physical activity) on blood-based biomarkers. The current study investigated the influence of a 6-month exercise intervention on levels of plasma beta-amyloid (Aβ42, Aβ40, Aβ42/40), phosphorylated tau (p-tau181), glial fibrillary acidic protein (GFAP) and neurofilament light (NfL) chain in cognitively unimpaired older adults, and as a secondary aim, whether blood-based biomarkers related to cognition. Ninety-nine community-dwelling older adults (69.1 ± 5.2) were allocated to an inactive control, or to moderate or high intensity exercise groups where they cycled twice weekly for six months. At baseline and six months (post-intervention), fasted blood was collected and analysed using single molecule array (SIMOA) assays, and cognition was assessed. Results demonstrated no change in levels of any plasma biomarker from pre- to post-intervention. At baseline, higher NfL was associated with poorer cognition (β = -0.33, SE = 0.13, adjusted p = .042). Exploratory analyses indicated higher cardiorespiratory fitness was associated with higher NfL and GFAP levels in apolipoprotein E (APOE) ε4 non-carriers compared to ε4 carriers (NfL, β = -0.43, SE = 0.19, p = .029; GFAP, β = -0.41, SE = 0.20, p = .044), though this association was mediated by body mass index (BMI). These results highlight the importance of considering BMI in analysis of blood-based biomarkers, especially when investigating differences between APOE ε4 carriers and non-carriers. Our results also indicate that longer follow-up periods may be required to observe exercise-induced change in blood-based biomarkers.
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Affiliation(s)
- Kelsey R Sewell
- Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Murdoch, WA, Australia.
| | - Stephanie R Rainey-Smith
- Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Murdoch, WA, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, WA, Australia
- School of Psychological Science, University of Western Australia, Crawley, WA, Australia
| | - Steve Pedrini
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, WA, Australia
| | - Jeremiah J Peiffer
- Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Murdoch, WA, Australia
| | - Hamid R Sohrabi
- Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Murdoch, WA, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, WA, Australia
- Department of Biomedical Sciences, Macquarie University, North Ryde, New South Wales, Australia
| | - Kevin Taddei
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, WA, Australia
| | - Shaun J Markovic
- Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Murdoch, WA, Australia
- Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, WA, Australia
| | - Ralph N Martins
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, WA, Australia
- Department of Biomedical Sciences, Macquarie University, North Ryde, New South Wales, Australia
| | - Belinda M Brown
- Centre for Healthy Ageing, Health Futures Institute, Murdoch University, Murdoch, WA, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
- Alzheimer's Research Australia, Ralph and Patricia Sarich Neuroscience Research Institute, Nedlands, WA, Australia
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De Meyer S, Blujdea ER, Schaeverbeke J, Reinartz M, Luckett ES, Adamczuk K, Van Laere K, Dupont P, Teunissen CE, Vandenberghe R, Poesen K. Longitudinal associations of serum biomarkers with early cognitive, amyloid and grey matter changes. Brain 2024; 147:936-948. [PMID: 37787146 DOI: 10.1093/brain/awad330] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Revised: 09/08/2023] [Accepted: 09/12/2023] [Indexed: 10/04/2023] Open
Abstract
Blood-based biomarkers have been extensively evaluated for their diagnostic potential in Alzheimer's disease. However, their relative prognostic and monitoring capabilities for cognitive decline, amyloid-β (Aβ) accumulation and grey matter loss in cognitively unimpaired elderly require further investigation over extended time periods. This prospective cohort study in cognitively unimpaired elderly [n = 185, mean age (range) = 69 (53-84) years, 48% female] examined the prognostic and monitoring capabilities of glial fibrillary acidic protein (GFAP), neurofilament light (NfL), Aβ1-42/Aβ1-40 and phosphorylated tau (pTau)181 through their quantification in serum. All participants underwent baseline Aβ-PET, MRI and blood sampling as well as 2-yearly cognitive testing. A subset additionally underwent Aβ-PET (n = 109), MRI (n = 106) and blood sampling (n = 110) during follow-up [median time interval (range) = 6.1 (1.3-11.0) years]. Matching plasma measurements were available for Aβ1-42/Aβ1-40 and pTau181 (both n = 140). Linear mixed-effects models showed that high serum GFAP and NfL predicted future cognitive decline in memory (βGFAP×Time = -0.021, PFDR = 0.007 and βNfL×Time = -0.031, PFDR = 0.002) and language (βGFAP×Time = -0.021, PFDR = 0.002 and βNfL×Time = -0.018, PFDR = 0.03) domains. Low serum Aβ1-42/Aβ1-40 equally but independently predicted memory decline (βAβ1-42/Aβ1-40×Time = -0.024, PFDR = 0.02). Whole-brain voxelwise analyses revealed that low Aβ1-42/Aβ1-40 predicted Aβ accumulation within the precuneus and frontal regions, high GFAP and NfL predicted grey matter loss within hippocampal regions and low Aβ1-42/Aβ1-40 predicted grey matter loss in lateral temporal regions. Serum GFAP, NfL and pTau181 increased over time, while Aβ1-42/Aβ1-40 decreased only in Aβ-PET-negative elderly. NfL increases associated with declining memory (βNfLchange×Time = -0.030, PFDR = 0.006) and language (βNfLchange×Time = -0.021, PFDR = 0.02) function and serum Aβ1-42/Aβ1-40 decreases associated with declining language function (βAβ1-42/Aβ1-40×Time = -0.020, PFDR = 0.04). GFAP increases associated with Aβ accumulation within the precuneus and NfL increases associated with grey matter loss. Baseline and longitudinal serum pTau181 only associated with Aβ accumulation in restricted occipital regions. In head-to-head comparisons, serum outperformed plasma Aβ1-42/Aβ1-40 (ΔAUC = 0.10, PDeLong, FDR = 0.04), while both plasma and serum pTau181 demonstrated poor performance to detect asymptomatic Aβ-PET positivity (AUC = 0.55 and 0.63, respectively). However, when measured with a more phospho-specific assay, plasma pTau181 detected Aβ-positivity with high performance (AUC = 0.82, PDeLong, FDR < 0.007). In conclusion, serum GFAP, NfL and Aβ1-42/Aβ1-40 are valuable prognostic and/or monitoring tools in asymptomatic stages providing complementary information in a time- and pathology-dependent manner.
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Affiliation(s)
- Steffi De Meyer
- Laboratory for Molecular Neurobiomarker Research, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
| | - Elena R Blujdea
- Neurochemistry Laboratory, Amsterdam UMC, 1081 HZ Amsterdam, The Netherlands
| | - Jolien Schaeverbeke
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
| | - Mariska Reinartz
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
| | - Emma S Luckett
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
| | - Katarzyna Adamczuk
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
| | - Koen Van Laere
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
- Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, 3000 Leuven, Belgium
- Division of Nuclear Medicine, UZ Leuven, 3000 Leuven, Belgium
| | - Patrick Dupont
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
| | | | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
- Department of Neurology, UZ Leuven, 3000 Leuven, Belgium
| | - Koen Poesen
- Laboratory for Molecular Neurobiomarker Research, Department of Neurosciences, KU Leuven, 3000 Leuven, Belgium
- Alzheimer Research Centre, Leuven Brain Institute (LBI), KU Leuven, 3000 Leuven, Belgium
- Department of Laboratory Medicine, UZ Leuven, 3000 Leuven, Belgium
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10
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Sanchez E, Wilkinson T, Coughlan G, Mirza S, Baril A, Ramirez J, Binns MA, Black SE, Borrie M, Dilliott AA, Dixon RA, Dowlatshahi D, Farhan S, Finger E, Fischer CE, Frank A, Freedman M, Goncalves RA, Grimes DA, Hassan A, Hegele RA, Kumar S, Lang AE, Marras C, McLaughlin PM, Orange JB, Pasternak SH, Pollock BG, Rajji TK, Roberts AC, Robinson JF, Rogaeva E, Sahlas DJ, Saposnik G, Strong MJ, Swartz RH, Tang‐Wai DF, Tartaglia MC, Troyer AK, Kvartsberg H, Zetterberg H, Munoz DP, Masellis M. Association of plasma biomarkers with cognition, cognitive decline, and daily function across and within neurodegenerative diseases: Results from the Ontario Neurodegenerative Disease Research Initiative. Alzheimers Dement 2024; 20:1753-1770. [PMID: 38105605 PMCID: PMC10984487 DOI: 10.1002/alz.13560] [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: 06/29/2023] [Revised: 10/02/2023] [Accepted: 10/29/2023] [Indexed: 12/19/2023]
Abstract
INTRODUCTION We investigated whether novel plasma biomarkers are associated with cognition, cognitive decline, and functional independence in activities of daily living across and within neurodegenerative diseases. METHODS Glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), phosphorylated tau (p-tau)181 and amyloid beta (Aβ)42/40 were measured using ultra-sensitive Simoa immunoassays in 44 healthy controls and 480 participants diagnosed with Alzheimer's disease/mild cognitive impairment (AD/MCI), Parkinson's disease (PD), frontotemporal dementia (FTD) spectrum disorders, or cerebrovascular disease (CVD). RESULTS GFAP, NfL, and/or p-tau181 were elevated among all diseases compared to controls, and were broadly associated with worse baseline cognitive performance, greater cognitive decline, and/or lower functional independence. While GFAP, NfL, and p-tau181 were highly predictive across diseases, p-tau181 was more specific to the AD/MCI cohort. Sparse associations were found in the FTD and CVD cohorts and for Aβ42/40 . DISCUSSION GFAP, NfL, and p-tau181 are valuable predictors of cognition and function across common neurodegenerative diseases, and may be useful in specialized clinics and clinical trials.
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11
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Cogswell PM, Lundt ES, Therneau TM, Wiste HJ, Graff‐Radford J, Algeciras‐Schimnich A, Lowe VJ, Mielke MM, Schwarz CG, Senjem ML, Gunter JL, Knopman DS, Vemuri P, Petersen RC, Jack Jr CR. Modeling the temporal evolution of plasma p-tau in relation to amyloid beta and tau PET. Alzheimers Dement 2024; 20:1225-1238. [PMID: 37963289 PMCID: PMC10916944 DOI: 10.1002/alz.13539] [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: 07/21/2023] [Revised: 10/02/2023] [Accepted: 10/11/2023] [Indexed: 11/16/2023]
Abstract
INTRODUCTION The timing of plasma biomarker changes is not well understood. The goal of this study was to evaluate the temporal co-evolution of plasma and positron emission tomography (PET) Alzheimer's disease (AD) biomarkers. METHODS We included 1408 Mayo Clinic Study of Aging and Alzheimer's Disease Research Center participants. An accelerated failure time (AFT) model was fit with amyloid beta (Aβ) PET, tau PET, plasma p-tau217, p-tau181, and glial fibrillary acidic protein (GFAP) as endpoints. RESULTS Individual timing of plasma p-tau progression was strongly associated with Aβ PET and GFAP progression. In the population, GFAP became abnormal first, then Aβ PET, plasma p-tau, and tau PET temporal meta-regions of interest when applying cut points based on young, cognitively unimpaired participants. DISCUSSION Plasma p-tau is a stronger indicator of a temporally linked response to elevated brain Aβ than of tau pathology. While Aβ deposition and a rise in GFAP are upstream events associated with tau phosphorylation, the temporal link between p-tau and Aβ PET was the strongest. HIGHLIGHTS Plasma p-tau progression was more strongly associated with Aβ than tau PET. Progression on plasma p-tau was associated with Aβ PET and GFAP progression. P-tau181 and p-tau217 become abnormal after Aβ PET and before tau PET. GFAP became abnormal first, before plasma p-tau and Aβ PET.
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Affiliation(s)
| | - Emily S. Lundt
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | - Terry M. Therneau
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | - Heather J. Wiste
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
| | | | | | - Val J. Lowe
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
| | - Michelle M. Mielke
- Department of Epidemiology and PreventionWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | | | - Matthew L. Senjem
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
- Department of Information TechnologyMayo ClinicRochesterMinnesotaUSA
| | | | | | | | - Ronald C. Petersen
- Department of Quantitative Health SciencesMayo ClinicRochesterMinnesotaUSA
- Department of NeurologyMayo ClinicRochesterMinnesotaUSA
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12
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Varma VR, An Y, Kac PR, Bilgel M, Moghekar A, Loeffler T, Amschl D, Troncoso J, Blennow K, Zetterberg H, Ashton NJ, Resnick SM, Thambisetty M. Longitudinal progression of blood biomarkers reveals a key role of astrocyte reactivity in preclinical Alzheimer's disease. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.25.24301779. [PMID: 38343809 PMCID: PMC10854357 DOI: 10.1101/2024.01.25.24301779] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/26/2024]
Abstract
Defining the progression of blood biomarkers of Alzheimer's disease (AD) is essential for targeting treatments in patients most likely to benefit from early intervention. We delineated the temporal ordering of blood biomarkers a decade prior to the onset of AD symptoms in participants in the Baltimore Longitudinal Study of Aging. We show that increased astrocyte reactivity, assessed by elevated glial fibrillary acidic protein (GFAP) levels is an early event in the progression of blood biomarker changes in preclinical AD. In AD-converters who are initially cognitively unimpaired (N=158, 377 serial plasma samples), higher plasma GFAP levels are observed as early as 10-years prior to the onset of cognitive impairment due to incident AD compared to individuals who remain cognitively unimpaired (CU, N=160, 379 serial plasma samples). Plasma GFAP levels in AD-converters remain elevated 5-years prior to and coincident with the onset of cognitive impairment due to AD. In participants with neuropathologically confirmed AD, plasma GFAP levels are elevated relative to cognitively normal individuals and intermediate in those who remain cognitively unimpaired despite significant AD pathology (asymptomatic AD). Higher plasma GFAP levels at death are associated with greater severity of both neuritic plaques and neurofibrillary tangles. In the 5XFAD transgenic model of AD, we observed greater GFAP levels in the cortex and hippocampus of transgenic mice relative to wild-type prior to the development of cognitive impairment. Reactive astrocytosis, an established biological response to neuronal injury, may be an early initiator of AD pathogenesis and a promising therapeutic target.
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Affiliation(s)
- V R Varma
- Clinical and Translational Neuroscience Section, Laboratory of Behavioral Neuroscience, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, Maryland, United States of America
| | - Y An
- Brain Aging and Behavior Section, Laboratory of Behavioral Neuroscience, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, MD, USA
| | - P R Kac
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - M Bilgel
- Brain Aging and Behavior Section, Laboratory of Behavioral Neuroscience, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, MD, USA
| | - A Moghekar
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD 21224, USA
| | - T Loeffler
- Scantox Neuro GmbH, Parkring 12, 8074, Grambach, Austria
| | - D Amschl
- Scantox Neuro GmbH, Parkring 12, 8074, Grambach, Austria
| | - J Troncoso
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - K Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - H Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - N J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King's College London, Institute of Psychiatry, Psychology and Neuroscience Maurice Wohl 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
| | - S M Resnick
- Brain Aging and Behavior Section, Laboratory of Behavioral Neuroscience, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, MD, USA
| | - M Thambisetty
- Clinical and Translational Neuroscience Section, Laboratory of Behavioral Neuroscience, National Institute on Aging (NIA), National Institutes of Health (NIH), Baltimore, Maryland, United States of America
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13
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Snytnikova O, Telegina D, Savina E, Tsentalovich Y, Kolosova N. Quantitative Metabolomic Analysis of the Rat Hippocampus: Effects of Age and of the Development of Alzheimer's Disease-Like Pathology. J Alzheimers Dis 2024; 99:S327-S344. [PMID: 37980669 DOI: 10.3233/jad-230706] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2023]
Abstract
Background Alzheimer's disease (AD) is the most common type of dementia in the elderly. Incomplete knowledge about the pathogenesis of this disease determines the absence of medications for the treatment of AD today. Animal models can provide the necessary knowledge to understand the mechanisms of biochemical processes occurring in the body in health and disease. Objective To identify the most promising metabolomic predictors and biomarkers reflecting metabolic disorders in the development of AD signs. Methods High resolution 1H NMR spectroscopy was used for quantitative metabolomic profiling of the hippocampus of OXYS rats, an animal model of sporadic AD, which demonstrates key characteristics of this disease. Animals were examined during several key periods: 20 days group corresponds to the "preclinical" period preceding the development of AD signs, during their manifestation (3 months), and active progression (18 months). Wistar rats of the same age were used as control. Results Ranges of variation and mean concentrations were established for 59 brain metabolites. The main metabolic patterns during aging, which are involved in energy metabolism pathways and metabolic shifts of neurotransmitters, have been established. Of particular note is the significant increase of scyllo-inositol and decrease of hypotaurine in the hippocampus of OXYS rats as compared to Wistars for all studied age groups. Conclusions We suggest that the accumulation of scyllo-inositol and the reduction of hypotaurine in the brain, even at an early age, can be considered as predictors and potential biomarkers of the development of AD signs in OXYS rats and, probably, in humans.
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Affiliation(s)
- Olga Snytnikova
- International Tomography Center, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Darya Telegina
- The Federal Research Center Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Ekaterina Savina
- International Tomography Center, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Yuri Tsentalovich
- International Tomography Center, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
| | - Nataliya Kolosova
- The Federal Research Center Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, Novosibirsk, Russia
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14
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Xiao Z, Wu W, Ma X, Wu J, Liang X, Zhou X, Cao Y, Zhao Q, Ding D. Plasma p-tau217, p-tau181, and NfL as early indicators of dementia risk in a community cohort: The Shanghai Aging Study. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12514. [PMID: 38145191 PMCID: PMC10740382 DOI: 10.1002/dad2.12514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 11/13/2023] [Accepted: 11/19/2023] [Indexed: 12/26/2023]
Abstract
INTRODUCTION Blood biomarkers showed values for predicting future cognitive impairment. Evidence from the community-based cohort was limited only in high-income countries. METHODS This study included 1857 dementia-free community residents recruited in 2009-2011 and followed up in waves 2014-2016 and 2019-2023 in the Shanghai Aging Study. We intended to explore the relationships of baseline plasma ALZpath phosphorylated tau 217 (p-tau217), p-tau181, neurofilament light chain (NfL) with follow-up incident dementia, Alzheimer's disease (AD), and amyloidosis. RESULTS Higher concentrations of plasma p-tau217, p-tau181, and NfL were correlated to higher decline speed of Mini-Mental State Examination score, and higher risk of incident dementia and AD. The p-tau217 demonstrated a significant correlation with longitudinal neocortical amyloid-beta (Aβ) deposition (r = 0.57 [0.30, 0.76]) and a high accuracy differentiating Aβ+ from Aβ- at follow-ups (area under the receiver operating characteristic curve = 0.821 [0.703, 0.940]). DISCUSSION Plasma p-tau217 may be an early predictive marker of AD and Aβ pathology in older community-dwelling individuals.Highlights: Plasma p-tau217, p-tau181, and NfL were positively associated with long-term cognitive decline and risk of incident dementia.Plasma p-tau217 showed a better performance distinguishing Aβ+ individuals from Aβ- individuals at follow-ups.Plasma NfL may be a suitable predictor of general cognitive decline in older community-dwelling individuals.
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Affiliation(s)
- Zhenxu Xiao
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
| | - Wanqing Wu
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
| | - Xiaoxi Ma
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
| | - Jie Wu
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
| | - Xiaoniu Liang
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
| | - Xiaowen Zhou
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
| | - Yang Cao
- Clinical Epidemiology and BiostatisticsSchool of Medical SciencesFaculty of Medicine and HealthÖrebro UniversityÖrebroSweden
- Unit of Integrative EpidemiologyInstitute of Environmental MedicineKarolinska InstituteStockholmSweden
| | - Qianhua Zhao
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
- MOE Frontiers Center for Brain ScienceFudan UniversityShanghaiChina
| | - Ding Ding
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
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Curiel Cid RE, Ortega A, Crocco EA, Hincapie D, McFarland KN, Duara R, Vaillancourt D, DeKosky ST, Smith G, Sfakianaki E, Rosselli M, Barker WW, Adjouadi M, Barreto Y, Feito Y, Loewenstein DA. Semantic intrusion errors are associated with plasma Ptau-181 among persons with amnestic mild cognitive impairment who are amyloid positive. Front Neurol 2023; 14:1179205. [PMID: 37602238 PMCID: PMC10436611 DOI: 10.3389/fneur.2023.1179205] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Accepted: 07/06/2023] [Indexed: 08/22/2023] Open
Abstract
Introduction Semantic intrusion errors (SI) have distinguished between those with amnestic Mild Cognitive Impairment (aMCI) who are amyloid positive (A+) versus negative (A-) on positron emission tomography (PET). Method This study examines the association between SI and plasma - based biomarkers. One hundred and twenty-eight participants received SiMoA derived measures of plasma pTau-181, ratio of two amyloid-β peptide fragments (Aβ42/Aβ40), Neurofilament Light protein (NfL), Glial Fibrillary Acidic Protein (GFAP), ApoE genotyping, and amyloid PET imaging. Results The aMCI A+ (n = 42) group had a higher percentage of ApoE ɛ4 carriers, and greater levels of pTau-181 and SI, than Cognitively Unimpaired (CU) A- participants (n = 25). CU controls did not differ from aMCI A- (n = 61) on plasma biomarkers or ApoE genotype. Logistic regression indicated that ApoE ɛ4 positivity, pTau-181, and SI were independent differentiating predictors (Correct classification = 82.0%; Sensitivity = 71.4%; Specificity = 90.2%) in identifying A+ from A- aMCI cases. Discussion A combination of plasma biomarkers, ApoE positivity and SI had high specificity in identifying A+ from A- aMCI cases.
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Affiliation(s)
- Rosie E. Curiel Cid
- Center for Cognitive Neuroscience and Aging, Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Alexandra Ortega
- Center for Cognitive Neuroscience and Aging, Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Elizabeth A. Crocco
- Center for Cognitive Neuroscience and Aging, Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Diana Hincapie
- Center for Cognitive Neuroscience and Aging, Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Karen N. McFarland
- Department of Neurology and the Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, United States
| | - Ranjan Duara
- Department of Neurology and the Center for Translational Research in Neurodegenerative Disease, University of Florida, Gainesville, FL, United States
| | - David Vaillancourt
- Department of Applied Physiology and Kinesiology, Gainesville, FL, United States
| | - Steven T. DeKosky
- Department of Neurology and McKnight Brain Institute, University of Florida, Gainesville, FL, United States
| | - Glenn Smith
- Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, United States
| | - Efrosyni Sfakianaki
- Center for Cognitive Neuroscience and Aging, Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Monica Rosselli
- Department of Psychology, Florida Atlantic University, Boca Raton, FL, United States
| | - Warren W. Barker
- Wien Center for Alzheimer’s Disease and Memory Disorders, Mount Sinai Medical Center, Miami, FL, United States
| | - Malek Adjouadi
- Center for Advanced Technology and Education, Florida International University, Miami, FL, United States
| | - Yarlenis Barreto
- Center for Cognitive Neuroscience and Aging, Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, United States
| | - Yuleidys Feito
- Center for Cognitive Neuroscience and Aging, Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, United States
| | - David A. Loewenstein
- Center for Cognitive Neuroscience and Aging, Department of Psychiatry and Behavioral Sciences, University of Miami Miller School of Medicine, Miami, FL, United States
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Kodosaki E, Zetterberg H, Heslegrave A. Validating blood tests as a possible routine diagnostic assay of Alzheimer's disease. Expert Rev Mol Diagn 2023; 23:1153-1165. [PMID: 38018372 DOI: 10.1080/14737159.2023.2289553] [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: 09/11/2023] [Accepted: 11/21/2023] [Indexed: 11/30/2023]
Abstract
INTRODUCTION In recent years, exciting developments in disease modifying treatments for Alzheimer's disease (AD) have made accurate and timely diagnosis of this disease a priority. Blood biomarkers (BBMs) for amyloid pathology using improved immunoassay and mass spectrometry techniques have been an area of intense research for the last 10 years and are coming to the fore, as a real prospect to be used in the clinical diagnostics of the disease. AREAS COVERED The following review will update and discuss blood biomarkers that will be most useful in diagnosing AD and the context necessary for their implementation. EXPERT OPINION It is clear we now have BBMs, and technology to measure them, that are capable of detecting amyloid pathology in AD. The challenge is to validate them across platforms and populations to incorporate them into clinical practice. It is important that implementation comes with education, we need to give clinicians the tools for appropriate use and interpretation. It is feasible that BBMs will be used to screen populations, initially for clinical trial entry but also therapeutic intervention in the foreseeable future. We now need to focus BBM research on other pathologies to ensure we accelerate the development of therapeutics for all neurodegenerative diseases.
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Affiliation(s)
- Eleftheria Kodosaki
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- Dementia Research Institute at UCL, London, UK
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- Dementia Research Institute at UCL, London, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Wisconsin Alzheimer's Disease Research Centre, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology,Dementia Research Institute at UCL, London, UK
- Hong Kong Centre for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Amanda Heslegrave
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- Dementia Research Institute at UCL, London, UK
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