1
|
Zhao L, Zhang M, Li Q, Wang X, Lu J, Han Y, Cai Y. Storage time affects the level and diagnostic efficacy of plasma biomarkers for neurodegenerative diseases. Neural Regen Res 2025; 20:2373-2381. [PMID: 39359094 DOI: 10.4103/nrr.nrr-d-23-01983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 03/15/2024] [Indexed: 10/04/2024] Open
Abstract
JOURNAL/nrgr/04.03/01300535-202508000-00027/figure1/v/2024-09-30T120553Z/r/image-tiff Several promising plasma biomarker proteins, such as amyloid-β (Aβ), tau, neurofilament light chain, and glial fibrillary acidic protein, are widely used for the diagnosis of neurodegenerative diseases. However, little is known about the long-term stability of these biomarker proteins in plasma samples stored at -80°C. We aimed to explore how storage time would affect the diagnostic accuracy of these biomarkers using a large cohort. Plasma samples from 229 cognitively unimpaired individuals, encompassing healthy controls and those experiencing subjective cognitive decline, as well as 99 patients with cognitive impairment, comprising those with mild cognitive impairment and dementia, were acquired from the Sino Longitudinal Study on Cognitive Decline project. These samples were stored at -80°C for up to 6 years before being used in this study. Our results showed that plasma levels of Aβ42, Aβ40, neurofilament light chain, and glial fibrillary acidic protein were not significantly correlated with sample storage time. However, the level of total tau showed a negative correlation with sample storage time. Notably, in individuals without cognitive impairment, plasma levels of total protein and tau phosphorylated protein threonine 181 (p-tau181)also showed a negative correlation with sample storage time. This was not observed in individuals with cognitive impairment. Consequently, we speculate that the diagnostic accuracy of plasma p-tau181 and the p-tau181 to total tau ratio may be influenced by sample storage time. Therefore, caution is advised when using these plasma biomarkers for the identification of neurodegenerative diseases, such as Alzheimer's disease. Furthermore, in cohort studies, it is important to consider the impact of storage time on the overall results.
Collapse
Affiliation(s)
- Lifang Zhao
- Department of Clinical Biobank, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Geriatric Medical Research Center, Beijing, China
| | - Mingkai Zhang
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Qimeng Li
- Department of Clinical Biobank, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Geriatric Medical Research Center, Beijing, China
| | - Xuemin Wang
- Department of Clinical Biobank, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Geriatric Medical Research Center, Beijing, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Key Laboratory of Magnetic Resonance Imaging and Brain Informatics, Beijing, China
- Key Laboratory of Neurodegenerative diseases, Ministry of Education, Beijing, China
| | - Ying Han
- Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing, China
- School of Biomedical Engineering, Hainan University, Haikou, Hainan Province, China
- Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China
- National Clinical Research Center for Geriatric Diseases, Beijing, China
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, Gaoke Innovation Center, Shenzhen, Guangdong Province, China
| | - Yanning Cai
- Department of Clinical Biobank, Xuanwu Hospital, Capital Medical University, Beijing, China
- Beijing Geriatric Medical Research Center, Beijing, China
- Key Laboratory of Neurodegenerative diseases, Ministry of Education, Beijing, China
- Department of Neurobiology, Xuanwu Hospital, Capital Medical University, Beijing, China
| |
Collapse
|
2
|
Smith EE, Biessels GJ, Gao V, Gottesman RF, Liesz A, Parikh NS, Iadecola C. Systemic determinants of brain health in ageing. Nat Rev Neurol 2024; 20:647-659. [PMID: 39375564 DOI: 10.1038/s41582-024-01016-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/20/2024] [Indexed: 10/09/2024]
Abstract
Preservation of brain health is a worldwide priority. The traditional view is that the major threats to the ageing brain lie within the brain itself. Consequently, therapeutic approaches have focused on protecting the brain from these presumably intrinsic pathogenic processes. However, an increasing body of evidence has unveiled a previously under-recognized contribution of peripheral organs to brain dysfunction and damage. Thus, in addition to the well-known impact of diseases of the heart and endocrine glands on the brain, accumulating data suggest that dysfunction of other organs, such as gut, liver, kidney and lung, substantially affects the development and clinical manifestation of age-related brain pathologies. In this Review, a framework is provided to indicate how organ dysfunction can alter brain homeostasis and promote neurodegeneration, with a focus on dementia. We delineate the associations of subclinical dysfunction in specific organs with dementia risk and provide suggestions for public health promotion and clinical management.
Collapse
Affiliation(s)
- Eric E Smith
- Department of Clinical Neurosciences and Hotchkiss Brain Institute, University of Calgary, Calgary, Canada.
| | - Geert Jan Biessels
- Department of Neurology, UMC Utrecht Brain Center, University Medical Centre Utrecht, Utrecht, Netherlands
| | - Virginia Gao
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | | | - Arthur Liesz
- Institute for Stroke and Dementia Research, University Medical Center Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Neal S Parikh
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA
| | - Costantino Iadecola
- Feil Family Brain and Mind Research Institute, Weill Cornell Medicine, New York, NY, USA.
| |
Collapse
|
3
|
Wang WE, Asken BM, DeSimone JC, Levy SA, Barker W, Fiala JA, Velez-Uribe I, Curiel Cid RE, Rósselli M, Marsiske M, Adjouadi M, Loewenstein DA, Duara R, Smith GE, Armstrong MJ, Barnes LL, Vaillancourt DE, Coombes SA. Neuroimaging and biofluid biomarkers across race and ethnicity in older adults across the spectrum of cognition. Ageing Res Rev 2024; 101:102507. [PMID: 39306249 DOI: 10.1016/j.arr.2024.102507] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2024] [Accepted: 09/14/2024] [Indexed: 09/27/2024]
Abstract
Neuroimaging and biofluid biomarkers provide a proxy of pathological changes for Alzheimer's disease (AD) and are useful in improving diagnosis and assessing disease progression. However, it is not clear how race/ethnicity and different prevalence of AD risks impact biomarker levels. In this narrative review, we survey studies focusing on comparing biomarker differences between non-Hispanic White American(s) (NHW), African American(s) (AA), Hispanic/Latino American(s) (HLA), and Asian American(s) with normal cognition, mild cognitive impairment, and dementia. We found no strong evidence of racial and ethnic differences in imaging biomarkers after controlling for cognitive status and cardiovascular risks. For biofluid biomarkers, in AA, higher levels of plasma Aβ42/Aβ40, and lower levels of CSF total tau and p-tau 181, were observed after controlling for APOE status and comorbidities compared to NHW. Examining the impact of AD risks and comorbidities on biomarkers and their contributions to racial/ethnic differences in cognitive impairment are critical to interpreting biomarkers, understanding their generalizability, and eliminating racial/ethnic health disparities.
Collapse
Affiliation(s)
- Wei-En Wang
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
| | - Breton M Asken
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Jesse C DeSimone
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA
| | - Shellie-Anne Levy
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Warren Barker
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Wien Center for Alzheimer's Disease and Memory Disorders, Mt. Sinai Medical Center, Miami, FL, USA
| | - Jacob A Fiala
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Idaly Velez-Uribe
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Wien Center for Alzheimer's Disease and Memory Disorders, Mt. Sinai Medical Center, Miami, FL, USA
| | - Rosie E Curiel Cid
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Departments of Psychiatry and Behavioral Sciences and Neurology, Center for Cognitive Neuroscience and Aging, University of Miami, Miami, FL, USA
| | - Monica Rósselli
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Department of Psychology, Florida Atlantic University, Davie, FL, USA
| | - Michael Marsiske
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Malek Adjouadi
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Center for Advanced Technology and Education, Department of Electrical and Computer Engineering, Florida International University, Miami, FL, USA
| | - David A Loewenstein
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Departments of Psychiatry and Behavioral Sciences and Neurology, Center for Cognitive Neuroscience and Aging, University of Miami, Miami, FL, USA
| | - Ranjan Duara
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Wien Center for Alzheimer's Disease and Memory Disorders, Mt. Sinai Medical Center, Miami, FL, USA
| | - Glenn E Smith
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Department of Clinical and Health Psychology, University of Florida, Gainesville, FL, USA
| | - Melissa J Armstrong
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Department of Neurology, Fixel Institute for Neurological Disease, University of Florida, Gainesville, FL, USA
| | - Lisa L Barnes
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - David E Vaillancourt
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA; Department of Neurology, Fixel Institute for Neurological Disease, University of Florida, Gainesville, FL, USA
| | - Stephen A Coombes
- 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL, USA; Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, USA.
| |
Collapse
|
4
|
Quispialaya KM, Therriault J, Aliaga A, Tissot C, Servaes S, Rahmouni N, Karikari TK, Benedet AL, Ashton NJ, Macedo AC, Lussier FZ, Stevenson J, Wang YT, Arias JF, Hosseini A, Matsudaira T, Jean-Claude B, Gilfix BM, Zimmer ER, Soucy JP, Pascoal TA, Gauthier S, Zetterberg H, Blennow K, Rosa-Neto P. Plasma phosphorylated tau181 outperforms [ 18F] fluorodeoxyglucose positron emission tomography in the identification of early Alzheimer disease. Eur J Neurol 2024:e16255. [PMID: 39447157 DOI: 10.1111/ene.16255] [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: 10/20/2023] [Revised: 02/02/2024] [Accepted: 02/06/2024] [Indexed: 10/26/2024]
Abstract
BACKGROUND AND PURPOSE This study was undertaken to compare the performance of plasma p-tau181 with that of [18F]fluorodeoxyglucose (FDG) positron emission tomography (PET) in the identification of early biological Alzheimer disease (AD). METHODS We included 533 cognitively impaired participants from the Alzheimer's Disease Neuroimaging Initiative. Participants underwent PET scans, biofluid collection, and cognitive tests. Receiver operating characteristic analyses were used to determine the diagnostic accuracy of plasma p-tau181 and [18F]FDG-PET using clinical diagnosis and core AD biomarkers ([18F]florbetapir-PET and cerebrospinal fluid [CSF] p-tau181) as reference standards. Differences in the diagnostic accuracy between plasma p-tau181 and [18F]FDG-PET were determined by bootstrap-based tests. Correlations of [18F]FDG-PET and plasma p-tau181 with CSF p-tau181, amyloid β (Aβ) PET, and cognitive performance were evaluated to compare associations between measurements. RESULTS We observed that both plasma p-tau181 and [18F]FDG-PET identified individuals with positive AD biomarkers in CSF or on Aβ-PET. In the MCI group, plasma p-tau181 outperformed [18F]FDG-PET in identifying AD measured by CSF (p = 0.0007) and by Aβ-PET (p = 0.001). We also observed that both plasma p-tau181 and [18F]FDG-PET metabolism were associated with core AD biomarkers. However, [18F]FDG-PET uptake was more closely associated with cognitive outcomes (Montreal Cognitive Assessment, Mini-Mental State Examination, Clinical Dementia Rating Sum of Boxes, and logical memory delayed recall, p < 0.001) than plasma p-tau181. CONCLUSIONS Overall, although both plasma p-tau181 and [18F]FDG-PET were associated with core AD biomarkers, plasma p-tau181 outperformed [18F]FDG-PET in identifying individuals with early AD pathophysiology. Taken together, our study suggests that plasma p-tau181 may aid in detecting individuals with underlying early AD.
Collapse
Affiliation(s)
- Kely Monica Quispialaya
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute, Montreal, Quebec, Canada
- Department of Experimental Medicine, McGill University, Montreal, Quebec, Canada
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Antonio Aliaga
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Department of Experimental Medicine, McGill University, Montreal, Quebec, Canada
- Department of Pharmacology, Graduate Program in Biological Sciences: Biochemistry (PPGBioq) and Pharmacology and Therapeutics (PPGFT), Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Cécile Tissot
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Department of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Andrea L Benedet
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Wallenberg Centre for Molecular Medicine, University of Gothenburg, Gothenburg, Sweden
| | - Arthur C Macedo
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Firoza Z Lussier
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Department of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
| | - Yi-Ting Wang
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Jaime Fernandez Arias
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Ali Hosseini
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
| | - Takashi Matsudaira
- Department of Biofunctional Imaging, Hamamatsu University School of Medicine, Hamamatsu, Japan
- Department of Neurology, National Hospital Organization Shizuoka Institute of Epilepsy and Neurological Disorders, Urushiyama, Japan
| | - Bertrand Jean-Claude
- Department of Experimental Medicine, McGill University, Montreal, Quebec, Canada
| | - Brian M Gilfix
- Department of Specialized Medicine, McGill University, Montreal, Quebec, Canada
| | - Eduardo R Zimmer
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Department of Pharmacology, Graduate Program in Biological Sciences: Biochemistry (PPGBioq) and Pharmacology and Therapeutics (PPGFT), Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Department of Pharmacology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Brain Institute of Rio Grande do Sul, Pontifícia Universidade Católica do Rio Grande do Sul, Porto Alegre, Brazil
| | | | - Tharick A Pascoal
- Department of Neurology and Psychiatry, University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Serge Gauthier
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, University College London Institute of Neurology, London, UK
- UK Dementia Research Institute at University College London, London, UK
- Hong Kong Centre for Neurodegenerative Diseases, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill University Research Centre for Studies in Aging, Douglas Hospital, McGill University, Montreal, Quebec, Canada
- Montreal Neurological Institute, Montreal, Quebec, Canada
- Department of Experimental Medicine, McGill University, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, McGill University, Montreal, Quebec, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| |
Collapse
|
5
|
Lu Y, Pike JR, Chen J, Walker KA, Sullivan KJ, Thyagarajan B, Mielke MM, Lutsey PL, Knopman D, Gottesman RF, Sharrett AR, Coresh J, Mosley TH, Palta P. Changes in Alzheimer Disease Blood Biomarkers and Associations With Incident All-Cause Dementia. JAMA 2024; 332:1258-1269. [PMID: 39068543 PMCID: PMC11284635 DOI: 10.1001/jama.2024.6619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/16/2024] [Accepted: 03/29/2024] [Indexed: 07/30/2024]
Abstract
Importance Plasma biomarkers show promise for identifying Alzheimer disease (AD) neuropathology and neurodegeneration, but additional examination among diverse populations and throughout the life course is needed. Objective To assess temporal plasma biomarker changes and their association with all-cause dementia, overall and among subgroups of community-dwelling adults. Design, Setting, and Participants In 1525 participants from the US-based Atherosclerosis Risk in Communities (ARIC) study, plasma biomarkers were measured using stored specimens collected in midlife (1993-1995, mean age 58.3 years) and late life (2011-2013, mean age 76.0 years; followed up to 2016-2019, mean age 80.7 years). Midlife risk factors (hypertension, diabetes, lipids, coronary heart disease, cigarette use, and physical activity) were assessed for their associations with change in plasma biomarkers over time. The associations of biomarkers with incident all-cause dementia were evaluated in a subpopulation (n = 1339) who were dementia-free in 2011-2013 and had biomarker measurements in 1993-1995 and 2011-2013. Exposure Plasma biomarkers of amyloid-β 42 to amyloid-β 40 (Aβ42:Aβ40) ratio, phosphorylated tau at threonine 181 (p-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP) were measured using the Quanterix Simoa platform. Main Outcomes and Measures Incident all-cause dementia was ascertained from January 1, 2012, through December 31, 2019, from neuropsychological assessments, semiannual participant or informant contact, and medical record surveillance. Results Among 1525 participants (mean age, 58.3 [SD, 5.1] years), 914 participants (59.9%) were women, and 394 participants (25.8%) were Black. A total of 252 participants (16.5%) developed dementia. Decreasing Aβ42:Aβ40 ratio and increasing p-tau181, NfL, and GFAP were observed from midlife to late life, with more rapid biomarker changes among participants carrying the apolipoprotein E epsilon 4 (APOEε4) allele. Midlife hypertension was associated with a 0.15-SD faster NfL increase and a 0.08-SD faster GFAP increase per decade; estimates for midlife diabetes were a 0.11-SD faster for NfL and 0.15-SD faster for GFAP. Only AD-specific biomarkers in midlife demonstrated long-term associations with late-life dementia (hazard ratio per SD lower Aβ42:Aβ40 ratio, 1.11; 95% CI, 1.02-1.21; per SD higher p-tau181, 1.15; 95% CI, 1.06-1.25). All plasma biomarkers in late life had statistically significant associations with late-life dementia, with NfL demonstrating the largest association (1.92; 95% CI, 1.72-2.14). Conclusions and Relevance Plasma biomarkers of AD neuropathology, neuronal injury, and astrogliosis increase with age and are associated with known dementia risk factors. AD-specific biomarkers' association with dementia starts in midlife whereas late-life measures of AD, neuronal injury, and astrogliosis biomarkers are all associated with dementia.
Collapse
Affiliation(s)
- Yifei Lu
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill
| | - James Russell Pike
- Division of Epidemiology, Department of Population Health, New York University Grossman School of Medicine, New York
- Optimal Aging Institute, New York University Grossman School of Medicine, New York
| | - Jinyu Chen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Keenan A. Walker
- Laboratory of Behavioral Neuroscience, National Institute on Aging Intramural Research Program, Baltimore, Maryland
| | - Kevin J. Sullivan
- Department of Medicine, MIND Center, University of Mississippi Medical Center, Jackson
| | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis
| | - Michelle M. Mielke
- Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest University School of Medicine, Winston-Salem, North Carolina
| | - Pamela L. Lutsey
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis
| | - David Knopman
- Department of Neurology, Mayo Clinic, Rochester, Minnesota
| | - Rebecca F. Gottesman
- National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, Maryland
| | - A. Richey Sharrett
- Department of Medicine, MIND Center, University of Mississippi Medical Center, Jackson
| | - Josef Coresh
- Division of Epidemiology, Department of Population Health, New York University Grossman School of Medicine, New York
- Optimal Aging Institute, New York University Grossman School of Medicine, New York
| | - Thomas H. Mosley
- Department of Medicine, MIND Center, University of Mississippi Medical Center, Jackson
| | - Priya Palta
- Department of Neurology, University of North Carolina at Chapel Hill
| |
Collapse
|
6
|
Schindler SE, Petersen KK, Saef B, Tosun D, Shaw LM, Zetterberg H, Dage JL, Ferber K, Triana-Baltzer G, Du-Cuny L, Li Y, Coomaraswamy J, Baratta M, Mordashova Y, Saad ZS, Raunig DL, Ashton NJ, Meyers EA, Rubel CE, Rosenbaugh EG, Bannon AW, Potter WZ. Head-to-head comparison of leading blood tests for Alzheimer's disease pathology. Alzheimers Dement 2024. [PMID: 39394841 DOI: 10.1002/alz.14315] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2024] [Revised: 09/10/2024] [Accepted: 09/11/2024] [Indexed: 10/14/2024]
Abstract
INTRODUCTION Blood tests have the potential to improve the accuracy of Alzheimer's disease (AD) clinical diagnosis, which will enable greater access to AD-specific treatments. This study compared leading commercial blood tests for amyloid pathology and other AD-related outcomes. METHODS Plasma samples from the Alzheimer's Disease Neuroimaging Initiative were assayed with AD blood tests from C2N Diagnostics, Fujirebio Diagnostics, ALZPath, Janssen, Roche Diagnostics, and Quanterix. Outcomes measures were amyloid positron emission tomography (PET), tau PET, cortical thickness, and dementia severity. Logistic regression models assessed the classification accuracies of individual or combined plasma biomarkers for binarized outcomes, and Spearman correlations evaluated continuous relationships between individual plasma biomarkers and continuous outcomes. RESULTS Measures of plasma p-tau217, either individually or in combination with other plasma biomarkers, had the strongest relationships with all AD outcomes. DISCUSSION This study identified the plasma biomarker analytes and assays that most accurately classified amyloid pathology and other AD-related outcomes. HIGHLIGHTS Plasma p-tau217 measures most accurately classified amyloid and tau status. Plasma Aβ42/Aβ40 had relatively low accuracy in classification of amyloid status. Plasma p-tau217 measures had higher correlations with cortical thickness than NfL. Correlations of plasma biomarkers with dementia symptoms were relatively low.
Collapse
Affiliation(s)
- Suzanne E Schindler
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Kellen K Petersen
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Benjamin Saef
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California, USA
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute Fluid Biomarkers Laboratory, UK DRI at UCL, London, UK
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, Queen Square, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Jeffrey L Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Kyle Ferber
- Biogen, Biomarkers Group, Cambridge, Massachusetts, USA
| | - Gallen Triana-Baltzer
- Neuroscience Biomarkers, Johnson and Johnson Innovative Medicine, San Diego, California, USA
| | - Lei Du-Cuny
- AbbVie, Ludwigshafen am Rhein, Rheinland-Pfalz, Germany
| | - Yan Li
- Department of Neurology, Washington University in St. Louis, St. Louis, Missouri, USA
| | | | - Michael Baratta
- Takeda Pharmaceutical Company Ltd., Cambridge, Massachusetts, USA
| | | | - Ziad S Saad
- Neuroscience Biomarkers, Johnson and Johnson Innovative Medicine, San Diego, California, USA
| | - David L Raunig
- Takeda Pharmaceutical Company Ltd., Cambridge, Massachusetts, USA
| | - Nicholas J Ashton
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
- Banner Alzheimer's Institute, Phoenix, Arizona, USA
- Banner Sun Health Research Institute, Sun City, Arizona, USA
| | | | | | - Erin G Rosenbaugh
- The Foundation for the National Institutes of Health, North Bethesda, Maryland, USA
| | | | | |
Collapse
|
7
|
Hu Y, Cho M, Sachdev P, Dage J, Hendrix S, Hansson O, Bateman RJ, Hampel H. Fluid biomarkers in the context of amyloid-targeting disease-modifying treatments in Alzheimer's disease. MED 2024; 5:1206-1226. [PMID: 39255800 DOI: 10.1016/j.medj.2024.08.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2024] [Revised: 07/26/2024] [Accepted: 08/16/2024] [Indexed: 09/12/2024]
Abstract
Clinical management and therapeutics development for Alzheimer's disease (AD) have entered a new era, with recent approvals of monoclonal antibody therapies targeting the underlying pathophysiology of the disease and modifying its trajectory. Imaging and fluid biomarkers are becoming increasingly important in the clinical development of AD therapeutics. This review focuses on the evidence of fluid biomarkers from recent amyloid-β-targeting clinical trials, summarizing biomarker data across 12 trials. It further proposes a simple framework to put biomarker guidance in the context of amyloid-pathway-targeted disease modification, delineates factors that impact biomarker data in clinical trials, and highlights knowledge gaps and future directions. Increased knowledge and data on biomarkers in the context of disease progression and disease modification will help to better design future AD trials and guide the clinical management of patients on AD-modifying therapies, bringing us closer to the implementation of precision medicine in AD.
Collapse
Affiliation(s)
- Yan Hu
- Eisai Inc., Nutley, NJ, USA
| | | | | | - Jeffrey Dage
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA; Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Randall J Bateman
- Department of Neurology, Washington University of St. Louis, St. Louis, MO, USA; The Tracy Family SILQ Center, Washington University School of Medicine, Saint Louis, MO, USA
| | | |
Collapse
|
8
|
Lowe VJ, Mester CT, Lundt ES, Lee J, Ghatamaneni S, Algeciras-Schimnich A, Campbell MR, Graff-Radford J, Nguyen A, Min HK, Senjem ML, Machulda MM, Schwarz CG, Dickson DW, Murray ME, Kandimalla KK, Kantarci K, Boeve B, Vemuri P, Jones DT, Knopman D, Jack CR, Petersen RC, Mielke MM. Amyloid PET detects the deposition of brain Aβ earlier than CSF fluid biomarkers. Alzheimers Dement 2024. [PMID: 39392211 DOI: 10.1002/alz.14317] [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: 04/22/2024] [Revised: 09/09/2024] [Accepted: 09/13/2024] [Indexed: 10/12/2024]
Abstract
INTRODUCTION Understanding the relationship between amyloid beta (Aβ) positron emission tomography (PET) and Aβ cerebrospinal fluid (CSF) biomarkers will define their potential utility in Aβ treatment. Few population-based or neuropathologic comparisons have been reported. METHODS Participants 50+ years with Aβ PET and Aβ CSF biomarkers (phosphorylated tau [p-tau]181/Aβ42, n = 505, and Aβ42/40, n = 54) were included from the Mayo Clinic Study on Aging. From these participants, an autopsy subgroup was identified (n = 47). The relationships of Aβ PET and Aβ CSF biomarkers were assessed cross-sectionally in all participants and longitudinally in autopsy data. RESULTS Cross-sectionally, more participants were Aβ PET+ versus Aβ CSF- than Aβ PET- versus Aβ CSF+ with an incremental effect when using Aβ PET regions selected for early Aβ deposition. The sensitivity for the first detection of Thal phase ≥ 1 in longitudinal data was higher for Aβ PET (89%) than p-tau181/Aβ42 (64%). DISCUSSION Aβ PET can detect earlier cortical Aβ deposition than Aβ CSF biomarkers. Aβ PET+ versus Aβ CSF- findings are several-fold greater using regional Aβ PET analyses and in peri-threshold-standardized uptake value ratio participants. HIGHLIGHTS Amyloid beta (Aβ) positron emission tomography (PET) has greater sensitivity for Aβ deposition than Aβ cerebrospinal fluid (CSF) in early Aβ development. A population-based sample of participants (n = 505) with PET and CSF tests was used. Cortical regions showing early Aβ on Aβ PET were also used in these analyses. Neuropathology was used to validate detection of Aβ by Aβ PET and Aβ CSF biomarkers.
Collapse
Affiliation(s)
- Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Carly T Mester
- Departments of Radiology and Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Emily S Lundt
- Departments of Radiology and Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Jeyeon Lee
- Department of Biomedical Engineering, College of Medicine, Hanyang University, Seoul, Republic of Korea
| | | | | | - Michelle R Campbell
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Aivi Nguyen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, Minnesota, USA
| | - Hoon-Ki Min
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Matthew L Senjem
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
- Department of Information Technology, Mayo Clinic, Rochester, Minnesota, USA
| | - Mary M Machulda
- Department of Psychology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Dennis W Dickson
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Melissa E Murray
- Department of Neuroscience, Mayo Clinic, Jacksonville, Florida, USA
| | - Karunya K Kandimalla
- Department of Pharmaceutics and Brain Barriers Research Center, University of Minnesota, Minneapolis, Minnesota, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | - Bradley Boeve
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - David T Jones
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - David Knopman
- Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA
| | | | - Michelle M Mielke
- Department of Epidemiology and Prevention at Wake Forest University School of Medicine, Winston-Salem, North Carolina, USA
| |
Collapse
|
9
|
Chen W, Li J, Guo J, Li L, Wu H. Diagnosis and therapy of Alzheimer's disease: Light-driven heterogeneous redox processes. Adv Colloid Interface Sci 2024; 332:103253. [PMID: 39067260 DOI: 10.1016/j.cis.2024.103253] [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: 04/23/2024] [Revised: 07/15/2024] [Accepted: 07/19/2024] [Indexed: 07/30/2024]
Abstract
Light-driven heterogeneous processes are promising approaches for diagnosing and treating Alzheimer's disease (AD) by regulating its relevant biomolecules. The molecular understanding of the heterogeneous interface environment and its interaction with target biomolecules is important. This review critically appraises the advances in AD early diagnosis and therapy employing heterogeneous light-driven redox processes, encompassing photoelectrochemical (PEC) biosensing, photodynamic therapy, photothermal therapy, PEC therapy, and photoacoustic therapy. The design strategies for heterogeneous interfaces based on target biomolecules and applications are also compiled. Finally, the remaining challenges and future perspectives are discussed. The present review may promote the fundamental understanding of AD diagnosis and therapy and facilitate interdisciplinary studies at the junction of nanotechnology and bioscience.
Collapse
Affiliation(s)
- Wenting Chen
- Macau Institute of Materials Science and Engineering (MIMSE), Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa 999078, Macau
| | - Jiahui Li
- Macau Institute of Materials Science and Engineering (MIMSE), Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa 999078, Macau
| | - Jiaxin Guo
- School of Chemical Engineering and Technology, Xi'an Jiaotong University, Xi'an, China
| | - Liang Li
- Macau Institute of Materials Science and Engineering (MIMSE), Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa 999078, Macau
| | - Hao Wu
- Macau Institute of Materials Science and Engineering (MIMSE), Faculty of Innovation Engineering, Macau University of Science and Technology, Taipa 999078, Macau.
| |
Collapse
|
10
|
VandeVrede L, Rabinovici GD. Blood-Based Biomarkers for Alzheimer Disease-Ready for Primary Care? JAMA Neurol 2024; 81:1030-1031. [PMID: 39068546 DOI: 10.1001/jamaneurol.2024.2801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/30/2024]
Affiliation(s)
- Lawren VandeVrede
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
| | - Gil D Rabinovici
- Memory & Aging Center, Department of Neurology, University of California, San Francisco, San Francisco, California
- Department of Radiology & Biomedical Imaging, University of California, San Francisco, San Francisco, California
- Associate Editor, JAMA Neurology
| |
Collapse
|
11
|
Martino-Adami PV, Chatterjee M, Kleineidam L, Weyerer S, Bickel H, Wiese B, Riedel-Heller SG, Scherer M, Blennow K, Zetterberg H, Wagner M, Schneider A, Ramirez A. Prognostic value of Alzheimer's disease plasma biomarkers in the oldest-old: a prospective primary care-based study. THE LANCET REGIONAL HEALTH. EUROPE 2024; 45:101030. [PMID: 39253733 PMCID: PMC11381503 DOI: 10.1016/j.lanepe.2024.101030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/21/2024] [Revised: 07/26/2024] [Accepted: 07/30/2024] [Indexed: 09/11/2024]
Abstract
Background Blood-based biomarkers offer a promising, less invasive, and more cost-effective alternative for Alzheimer's disease screening compared to cerebrospinal fluid or imaging biomarkers. However, they have been extensively studied only in memory clinic-based cohorts. We aimed to validate them in a more heterogeneous, older patient population from primary care. Methods We measured plasma Aβ42/Aβ40, P-tau181, NfL, and GFAP in 1007 individuals without dementia, aged 79-94 years, from the longitudinal, primary care-based German AgeCoDe study. We assessed the association with cognitive decline, disease progression, and the capacity to predict future dementia of the Alzheimer's type (DAT). We also evaluated biomarker dynamics in 305 individuals with a follow-up sample (∼8 years later). Findings Higher levels of P-tau181 (HR = 1.32 [95% CI: 1.17-1.51]), NfL (HR = 1.19 [95% CI: 1.03-1.36]), and GFAP (HR = 1.36 [95% CI: 1.22-1.52]), and a lower Aβ42/Aβ40 ratio (HR = 0.80 [95% CI: 0.68-0.95]) were associated with an increased risk of progressing to clinically-diagnosed DAT. Additionally, higher levels of P-tau181 (β = -0.49 [95% CI: -0.71 to 0.26]), NfL (β = -0.29 [95% CI: -0.52 to 0.06]), and GFAP (β = -0.60 [95% CI: -0.83 to 0.38]) were linked to faster cognitive decline. A two-step DAT prediction strategy combining initial MMSE with biomarkers improved the identification of individuals in the prodromal stage for potential treatment eligibility. Biomarker levels changed over time, with increases in P-tau181 (β = 0.19 [95% CI: 0.14-0.25]), NfL (β = 2.88 [95% CI: 2.18-3.59]), and GFAP (β = 8.23 [95% CI: 6.71-9.75]). NfL (β = 2.47 [95% CI: 1.04-3.89]) and GFAP (β = 4.45 [95% CI: 1.38-7.51]) exhibited a faster increase in individuals progressing to DAT. Interpretation Evaluating plasma biomarkers, alongside brief cognitive assessments, might enhance the precision of risk assessment for DAT progression in primary care. Funding Alzheimer Forschung Initiative, Bundesministerium für Bildung und Forschung.
Collapse
Affiliation(s)
- Pamela V Martino-Adami
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
| | - Madhurima Chatterjee
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
| | - Luca Kleineidam
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn, Medical Faculty, Venusberg-Campus 1, 53127, Bonn, Germany
| | | | - Horst Bickel
- Department of Psychiatry, Technical University of Munich, Germany
| | - Birgitt Wiese
- Institute of General Practice, Hannover Medical School, Germany
| | - Steffi G Riedel-Heller
- Institute of Social Medicine, Occupational Health and Public Health, University of Leipzig, Germany
| | - Martin Scherer
- Department of Primary Medical Care, Center for Psychosocial Medicine, University Medical Center, Hamburg-Eppendorf, Germany
| | - 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
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, PR China
| | - 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 Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Michael Wagner
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn, Medical Faculty, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Anja Schneider
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn, Medical Faculty, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Alfredo Ramirez
- Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Kerpener Str. 62, 50937, Cologne, Germany
- German Center for Neurodegenerative Diseases (DZNE), Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Old Age Psychiatry and Cognitive Disorders, University Hospital Bonn, Medical Faculty, Venusberg-Campus 1, 53127, Bonn, Germany
- Department of Psychiatry and Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, 7703 Floyd Curl Drive, 78229, San Antonio, TX, USA
- Cologne Excellence Cluster on Cellular Stress Responses in Aging-associated Diseases (CECAD), University of Cologne, Joseph-Stelzmann-Straße 26, 50931, Cologne, Germany
| |
Collapse
|
12
|
Schöll M, Verberk IMW, Del Campo M, Delaby C, Therriault J, Chong JR, Palmqvist S, Alcolea D. Challenges in the practical implementation of blood biomarkers for Alzheimer's disease. THE LANCET. HEALTHY LONGEVITY 2024; 5:100630. [PMID: 39369727 DOI: 10.1016/j.lanhl.2024.07.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 06/23/2024] [Accepted: 07/29/2024] [Indexed: 10/08/2024] Open
Abstract
Blood biomarkers have emerged as accessible, cost-effective, and highly promising tools for advancing the diagnostics of Alzheimer's disease. However, transitioning from cerebrospinal fluid biomarkers to blood biomarkers-eg, to verify amyloid β pathology-requires careful consideration. This Series paper highlights the main challenges in the implementation of blood biomarkers for Alzheimer's disease in different possible contexts of use. Despite the robustness of measuring blood biomarker concentrations, the widespread adoption of blood biomarkers requires rigorous standardisation efforts to address inherent challenges in diverse contexts of use. The challenges include understanding the effect of pre-analytical and analytical conditions, potential confounding factors, and comorbidities that could influence outcomes of blood biomarkers and their use in diverse populations. Additionally, distinct scenarios present their own specific challenges. In memory clinics, the successful integration of blood biomarkers in diagnostic tests will require well-established diagnostic accuracy and comprehensive assessments of the effect of blood biomarkers on the diagnostic confidence and patient management of clinicians. In primary care settings, and even more when implemented in population-based screening programmes for which no experience with any biomarkers for Alzheimer's disease currently exists, the implementation of blood biomarkers will be challenged by the need for education of primary care clinical staff and clear guidelines. However, despite the challenges, blood biomarkers hold great promise for substantially enhancing the diagnostic accuracy and effectively streamlining referral processes, leading to earlier diagnosis and access to treatments. The ongoing efforts that are shaping the integration of blood biomarkers across diverse clinical settings pave the way towards precision medicine in Alzheimer's disease.
Collapse
Affiliation(s)
- Michael Schöll
- Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, Mölndal, Sweden; Department of Psychiatry and Neurochemistry, University of Gothenburg, Mölndal, Sweden; Dementia Research Centre, Queen Square Institute of Neurology, University College London, London, UK; Department of Clinical Physiology, Sahlgrenska University Hospital, Gothenburg, Sweden.
| | - Inge M W Verberk
- Neurochemistry Laboratory, Department of Laboratory Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Marta Del Campo
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall Foundation, Barcelona, Spain; Hospital del Mar Research Institute (IMIM), Barcelona, Spain; Departamento de Ciencias Farmacéuticas y de la Salud, Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
| | - Constance Delaby
- LBPC-PPC, University of Montpellier, CHU Montpellier, INM INSERM, Montpellier, France; Institut de Recerca Sant Pau (IR SANT PAU), Barcelona, Spain
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill Centre for Studies in Aging, McGill University, Montreal, QC, Canada; Montreal Neurological Institute, Department of Neurology and Neurosurgery, McGill University, Montreal, QC, Canada
| | - Joyce R Chong
- Department of Pharmacology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Memory, Aging and Cognition Centre, National University Health Systems, Singapore
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Clinical Sciences in Malmö, Lund University, Lund, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Daniel Alcolea
- Sant Pau Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain.
| |
Collapse
|
13
|
Wang N, Ma Y, Liang X, Fa W, Tian X, Liu C, Zhu M, Tian N, Liu K, Tang S, Song L, Cong L, Dai L, Xu H, Wang Y, Hou T, Du Y, Qiu C. Association of dementia with impaired kidney function and plasma biomarkers: A population-based study. Eur J Neurol 2024:e16488. [PMID: 39331367 DOI: 10.1111/ene.16488] [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: 05/07/2024] [Revised: 08/30/2024] [Accepted: 09/01/2024] [Indexed: 09/28/2024]
Abstract
BACKGROUND AND PURPOSE Emerging evidence has linked impaired kidney function with dementia in older adults, but the neuropathological pathways underlying their association remain poorly understood. We sought to examine the relationships of kidney function with dementia and plasma biomarkers in a Chinese rural population. METHODS This population-based study used data from the baseline examination of the Multimodal Interventions to Delay Dementia and Disability in rural China (MIND-China) cohort (March-September 2018; n = 5715). Kidney function was assessed using estimated glomerular filtration rate (eGFR) based on serum creatinine level. Dementia, Alzheimer's disease (AD) and vascular dementia (VaD) were diagnosed according to the international criteria. Plasma biomarkers were measured using the SIMOA platform in a subsample (n = 1446). Data were analyzed using logistic, general linear, and mediation models. RESULTS Of the 5715 participants, 306 were diagnosed with dementia, including 195 with AD and 100 with VaD. Impaired kidney function (eGFR <60 vs. ≥90 mL/min/1.73 m2) was associated with multivariable-adjusted odds ratios of 2.24 (95% confidence interval [CI] 1.44-3.46) for all-cause dementia, 1.85 (1.07-3.18) for AD, and 2.49 (1.16-5.22) for VaD. In the biomarker subsample, impaired kidney function was significantly associated with higher plasma amyloid-β (Aβ)40 (β-coefficient = 54.36, 95% CI 43.34-65.39), Aβ42 (β-coefficient = 3.14, 95% CI 2.42-3.86), neurofilament light chain (β-coefficient = 10.62, 95% CI 5.62-15.62), and total tau (β-coefficient = 0.68, 95% CI 0.44-0.91), and a lower Aβ42/Aβ40 ratio (β-coefficient = -4.11, 95% CI -8.08 to -0.14). The mediation analysis showed that plasma total tau significantly mediated 21.76% of the association between impaired kidney function and AD (p < 0.05). CONCLUSION Impaired kidney function is associated with dementia and plasma biomarkers among rural-dwelling older Chinese adults, and the association with AD is partly mediated by plasma biomarkers for neurodegeneration.
Collapse
Affiliation(s)
- Nan Wang
- Department of Neurology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People's Republic of China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, People's Republic of China
| | - Yixun Ma
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People's Republic of China
| | - Xiaoyan Liang
- Department of Neurology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People's Republic of China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, People's Republic of China
| | - Wenxin Fa
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People's Republic of China
| | - Xunyao Tian
- Department of Neurology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People's Republic of China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, People's Republic of China
| | - Cuicui Liu
- Department of Neurology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People's Republic of China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, People's Republic of China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People's Republic of China
| | - Min Zhu
- Department of Neurology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People's Republic of China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, People's Republic of China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People's Republic of China
| | - Na Tian
- Department of Neurology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People's Republic of China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People's Republic of China
| | - Keke Liu
- Shandong Academy of Clinical Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People's Republic of China
| | - Shi Tang
- Department of Neurology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People's Republic of China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, People's Republic of China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People's Republic of China
| | - Lin Song
- Department of Neurology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People's Republic of China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, People's Republic of China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People's Republic of China
| | - Lin Cong
- Department of Neurology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People's Republic of China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, People's Republic of China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People's Republic of China
| | - Lu Dai
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
| | - Hong Xu
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Yongxiang Wang
- Department of Neurology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People's Republic of China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, People's Republic of China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People's Republic of China
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
- Institute of Brain Science and Brain-Inspired Research, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China
| | - Tingting Hou
- Department of Neurology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People's Republic of China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, People's Republic of China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People's Republic of China
| | - Yifeng Du
- Department of Neurology, Shandong Provincial Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, People's Republic of China
- Shandong Provincial Clinical Research Center for Neurological Diseases, Jinan, Shandong, People's Republic of China
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People's Republic of China
- Institute of Brain Science and Brain-Inspired Research, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China
| | - Chengxuan Qiu
- Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, People's Republic of China
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet-Stockholm University, Stockholm, Sweden
- Institute of Brain Science and Brain-Inspired Research, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, Shandong, People's Republic of China
| |
Collapse
|
14
|
Kara F, Kantarci K. Understanding Proton Magnetic Resonance Spectroscopy Neurochemical Changes Using Alzheimer's Disease Biofluid, PET, Postmortem Pathology Biomarkers, and APOE Genotype. Int J Mol Sci 2024; 25:10064. [PMID: 39337551 PMCID: PMC11432594 DOI: 10.3390/ijms251810064] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2024] [Revised: 09/15/2024] [Accepted: 09/17/2024] [Indexed: 09/30/2024] Open
Abstract
In vivo proton (1H) magnetic resonance spectroscopy (MRS) is a powerful non-invasive method that can measure Alzheimer's disease (AD)-related neuropathological alterations at the molecular level. AD biomarkers include amyloid-beta (Aβ) plaques and hyperphosphorylated tau neurofibrillary tangles. These biomarkers can be detected via postmortem analysis but also in living individuals through positron emission tomography (PET) or biofluid biomarkers of Aβ and tau. This review offers an overview of biochemical abnormalities detected by 1H MRS within the biologically defined AD spectrum. It includes a summary of earlier studies that explored the association of 1H MRS metabolites with biofluid, PET, and postmortem AD biomarkers and examined how apolipoprotein e4 allele carrier status influences brain biochemistry. Studying these associations is crucial for understanding how AD pathology affects brain homeostasis throughout the AD continuum and may eventually facilitate the development of potential novel therapeutic approaches.
Collapse
Affiliation(s)
- Firat Kara
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| |
Collapse
|
15
|
Ankeny SE, Bacci JR, Decourt B, Sabbagh MN, Mielke MM. Navigating the Landscape of Plasma Biomarkers in Alzheimer's Disease: Focus on Past, Present, and Future Clinical Applications. Neurol Ther 2024:10.1007/s40120-024-00658-x. [PMID: 39244522 DOI: 10.1007/s40120-024-00658-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/02/2024] [Accepted: 08/20/2024] [Indexed: 09/09/2024] Open
Abstract
As the prevalence of Alzheimer's disease (AD) and its impact on healthcare systems increase, developing tools for accurate diagnosis and monitoring of disease progression is a priority. Recent technological advancements have allowed for the development of blood-based biomarkers (BBMs) to aid in the diagnosis of AD, but many questions remain regarding the clinical implementation of these BBMs. This review outlines the historical timeline of AD BBM development. It highlights key breakthroughs that have transformed the perspective of AD BBMs from theoretically ideal but unattainable markers, to clinically valid and reliable BBMs with potential for implementation in healthcare settings. Technological advancements like single-molecule detection and mass spectrometry methods have significantly improved assay sensitivity and accuracy. High-throughput, fully automated platforms have potential for clinical use. Despite these advancements, however, significant work is needed before AD BBMs can be implemented in widespread clinical practice. Cutpoints must be established, the influence of chronic conditions and medications on BBM levels must be better understood, and guidelines must be created for healthcare providers related to interpreting and communicating information obtained from AD BBMs. Additionally, the development of BBMs for synaptic dysfunction, inflammation, and cerebrovascular disease may provide better precision medicine approaches to treating AD and related dementia. Future research and collaboration between scientists and physicians are essential to addressing these challenges and further advancing AD BBMs, with the goal of integration in clinical practice.
Collapse
Affiliation(s)
- Sarrah E Ankeny
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Julia R Bacci
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Boris Decourt
- Department of Pharmacology and Neuroscience, School of Medicine, Texas Tech University Health Sciences Center, Lubbock, TX, USA
| | - Marwan N Sabbagh
- Alzheimer's and Memory Disorders Division, Barrow Neurological Institute, Phoenix, AZ, USA
| | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
| |
Collapse
|
16
|
Gebre RK, Graff-Radford J, Ramanan VK, Raghavan S, Hofrenning EI, Przybelski SA, Nguyen AT, Lesnick TG, Gunter JL, Algeciras-Schimnich A, Knopman DS, Machulda MM, Vassilaki M, Lowe VJ, Jack CR, Petersen RC, Vemuri P. Can integration of Alzheimer's plasma biomarkers with MRI, cardiovascular, genetics, and lifestyle measures improve cognition prediction? Brain Commun 2024; 6:fcae300. [PMID: 39291164 PMCID: PMC11406552 DOI: 10.1093/braincomms/fcae300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2024] [Revised: 07/13/2024] [Accepted: 09/03/2024] [Indexed: 09/19/2024] Open
Abstract
There is increasing interest in Alzheimer's disease related plasma biomarkers due to their accessibility and scalability. We hypothesized that integrating plasma biomarkers with other commonly used and available participant data (MRI, cardiovascular factors, lifestyle, genetics) using machine learning (ML) models can improve individual prediction of cognitive outcomes. Further, our goal was to evaluate the heterogeneity of these predictors across different age strata. This longitudinal study included 1185 participants from the Mayo Clinic Study of Aging who had complete plasma analyte work-up at baseline. We used the Quanterix Simoa immunoassay to measure neurofilament light, Aβ1-42 and Aβ1-40 (used as Aβ42/Aβ40 ratio), glial fibrillary acidic protein, and phosphorylated tau 181 (p-tau181). Participants' brain health was evaluated through gray and white matter structural MRIs. The study also considered cardiovascular factors (hyperlipidemia, hypertension, stroke, diabetes, chronic kidney disease), lifestyle factors (area deprivation index, body mass index, cognitive and physical activities), and genetic factors (APOE, single nucleotide polymorphisms, and polygenic risk scores). An ML model was developed to predict cognitive outcomes at baseline and decline (slope). Three models were created: a base model with groups of risk factors as predictors, an enhanced model included socio-demographics, and a final enhanced model by incorporating plasma and socio-demographics into the base models. Models were explained for three age strata: younger than 65 years, 65-80 years, and older than 80 years, and further divided based on amyloid positivity status. Regardless of amyloid status the plasma biomarkers showed comparable performance (R² = 0.15) to MRI (R² = 0.18) and cardiovascular measures (R² = 0.10) when predicting cognitive decline. Inclusion of cardiovascular or MRI measures with plasma in the presence of socio-demographic improved cognitive decline prediction (R² = 0.26 and 0.27). For amyloid positive individuals Aβ42/Aβ40, glial fibrillary acidic protein and p-tau181 were the top predictors of cognitive decline while Aβ42/Aβ40 was prominent for amyloid negative participants across all age groups. Socio-demographics explained a large portion of the variance in the amyloid negative individuals while the plasma biomarkers predominantly explained the variance in amyloid positive individuals (21% to 37% from the younger to the older age group). Plasma biomarkers performed similarly to MRI and cardiovascular measures when predicting cognitive outcomes and combining them with either measure resulted in better performance. Top predictors were heterogeneous between cross-sectional and longitudinal cognition models, across age groups, and amyloid status. Multimodal approaches will enhance the usefulness of plasma biomarkers through careful considerations of a study population's socio-demographics, brain and cardiovascular health.
Collapse
Affiliation(s)
- Robel K Gebre
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Vijay K Ramanan
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | - Scott A Przybelski
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Aivi T Nguyen
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, USA
| | - Timothy G Lesnick
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Mary M Machulda
- Department of Psychology, Mayo Clinic, Rochester, MN 55905, USA
| | - Maria Vassilaki
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | |
Collapse
|
17
|
Hunter TR, Santos LE, Tovar-Moll F, De Felice FG. Alzheimer's disease biomarkers and their current use in clinical research and practice. Mol Psychiatry 2024:10.1038/s41380-024-02709-z. [PMID: 39232196 DOI: 10.1038/s41380-024-02709-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: 11/24/2023] [Revised: 08/14/2024] [Accepted: 08/19/2024] [Indexed: 09/06/2024]
Abstract
While blood-based tests are readily available for various conditions, including cardiovascular diseases, type 2 diabetes, and common cancers, Alzheimer's disease (AD) and other neurodegenerative diseases lack an early blood-based screening test that can be used in primary care. Major efforts have been made towards the investigation of approaches that may lead to minimally invasive, cost-effective, and reliable tests capable of measuring brain pathological status. Here, we review past and current technologies developed to investigate biomarkers of AD, including novel blood-based approaches and the more established cerebrospinal fluid and neuroimaging biomarkers of disease. The utility of blood as a source of AD-related biomarkers in both clinical practice and interventional trials is discussed, supported by a comprehensive list of clinical trials for AD drugs and interventions that list biomarkers as primary or secondary endpoints. We highlight that identifying individuals in early preclinical AD using blood-based biomarkers will improve clinical trials and the optimization of therapeutic treatments as they become available. Lastly, we discuss challenges that remain in the field and address new approaches being developed, such as the examination of cargo packaged within extracellular vesicles of neuronal origin isolated from peripheral blood.
Collapse
Affiliation(s)
- Tai R Hunter
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada
| | - Luis E Santos
- D'Or Institute for Research and Education, Rio de Janeiro, RJ, Brazil.
| | | | - Fernanda G De Felice
- Department of Biomedical and Molecular Sciences, Queen's University, Kingston, ON, Canada.
- D'Or Institute for Research and Education, Rio de Janeiro, RJ, Brazil.
- Centre for Neuroscience Studies and Department of Psychiatry, Queen's University, Kingston, ON, Canada.
- Institute of Medical Biochemistry Leopoldo de Meis, Federal University of Rio de Janeiro, Rio de Janeiro, RJ, Brazil.
| |
Collapse
|
18
|
Brier MR, Schindler SE, Salter A, Perantie D, Shelley N, Judge B, Keefe S, Kirmess KM, Verghese PB, Yarasheski KE, Venkatesh V, Raji C, Gordon BA, Bateman RJ, Morris JC, Naismith RT, Holtzman DM, Benzinger TL, Cross AH. Unexpected Low Rate of Amyloid-β Pathology in Multiple Sclerosis Patients. Ann Neurol 2024; 96:453-459. [PMID: 38963256 PMCID: PMC11324391 DOI: 10.1002/ana.27027] [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: 04/08/2024] [Revised: 05/29/2024] [Accepted: 06/13/2024] [Indexed: 07/05/2024]
Abstract
The life expectancy of people with multiple sclerosis (MS) has increased, yet we have noted that development of a typical Alzheimer disease dementia syndrome is uncommon. We hypothesized that Alzheimer disease pathology is uncommon in MS patients. In 100 MS patients, the rate of amyloid-β plasma biomarker positivity was approximately half the rate in 300 non-MS controls matched on age, sex, apolipoprotein E proteotype, and cognitive status. Interestingly, most MS patients who did have amyloid-β pathology had features atypical for MS at diagnosis. These results support that MS is associated with reduced Alzheimer disease risk, and suggest new avenues of research. ANN NEUROL 2024;96:453-459.
Collapse
Affiliation(s)
- Matthew R. Brier
- Department of Neurology, Washington University in St. Louis
- Mallinckrodt Institute of Radiology, Washington University in St. Louis
| | | | - Amber Salter
- Department of Neurology, University of Texas Southwestern Medical Center
| | - Dana Perantie
- Department of Neurology, Washington University in St. Louis
| | - Nicole Shelley
- Department of Neurology, Washington University in St. Louis
| | - Bradley Judge
- Department of Neurology, Washington University in St. Louis
| | - Sarah Keefe
- Mallinckrodt Institute of Radiology, Washington University in St. Louis
| | | | | | | | | | - Cyrus Raji
- Mallinckrodt Institute of Radiology, Washington University in St. Louis
| | - Brian A. Gordon
- Mallinckrodt Institute of Radiology, Washington University in St. Louis
| | | | - John C. Morris
- Department of Neurology, Washington University in St. Louis
| | | | | | | | - Anne H. Cross
- Department of Neurology, Washington University in St. Louis
| |
Collapse
|
19
|
Mandelblatt J, Dage JL, Zhou X, Small BJ, Ahles TA, Ahn J, Artese A, Bethea TN, Breen EC, Carroll JE, Cohen HJ, Extermann M, Graham D, Claudine I, Jim HSL, McDonald BC, Nakamura ZM, Patel SK, Rebeck GW, Rentscher KE, Root JC, Russ KA, Tometich DB, Turner RS, Van Dyk K, Zhai W, Huang LW, Saykin AJ. Alzheimer disease-related biomarkers and cancer-related cognitive decline: the Thinking and Living with Cancer study. J Natl Cancer Inst 2024; 116:1495-1507. [PMID: 38788675 PMCID: PMC11378315 DOI: 10.1093/jnci/djae113] [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: 01/19/2024] [Revised: 04/22/2024] [Accepted: 05/15/2024] [Indexed: 05/26/2024] Open
Abstract
PURPOSE We evaluated whether plasma Alzheimer disease (AD)-related biomarkers were associated with cancer-related cognitive decline among older breast cancer survivors. METHODS We included survivors aged 60-90 years with primary stage 0-III breast cancers (n = 236) and frequency-matched noncancer control paricipant (n = 154) who passed a cognitive screen and had banked plasma specimens. Participants were assessed at baseline (presystemic therapy) and annually for up to 60 months. Cognition was measured using tests of attention, processing speed, and executive function and learning and memory; perceived cognition was measured by the Functional Assessment of Cancer Therapy-Cognitive Function v3 Perceived Cognitive Impairments. Baseline plasma neurofilament light, glial fibrillary acidic protein, β-amyloid 42 and 40 and phosphorylated tau 181 were assayed using single molecule arrays. Mixed models tested associations between cognition and baseline AD biomarkers, time, group (survivor vs control participant), and their 2- and 3-way interactions, controlling for age, race, Wide Range 4 Achievement Test Word Reading score, comorbidity, and body mass index; 2-sided P values of .05 were considered statistically significant. RESULTS There were no group differences in baseline AD-related biomarkers except survivors had higher baseline neurofilament light levels than control participants (P = .013). Survivors had lower adjusted longitudinal attention, processing speed, and executive function than control participants starting from baseline and continuing over time (P ≤ .002). However, baseline AD-related biomarker levels were not independently associated with adjusted cognition over time, except control participants had lower attention, processing speed, and executive function scores with higher glial fibrillary acidic protein levels (P = .008). CONCLUSION The results do not support a relationship between baseline AD-related biomarkers and cancer-related cognitive decline. Further investigation is warranted to confirm the findings, test effects of longitudinal changes in AD-related biomarkers, and examine other mechanisms and factors affecting cognition presystemic therapy.
Collapse
Affiliation(s)
- Jeanne Mandelblatt
- Georgetown Lombardi Institute for Cancer and Aging Research, Lombardi Comprehensive Cancer Center, Department of Oncology, Georgetown University, Washington, DC, USA
| | - Jeffrey L Dage
- Stark Neurosciences Research Institute, Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Xingtao Zhou
- Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University, Washington, DC, USA
| | - Brent J Small
- School of Aging Studies, University of South Florida, and Health Outcomes and Behavior Program, Moffitt Cancer Center, Tampa, FL, USA
| | - Tim A Ahles
- Department of Psychiatry and Behavioral Sciences, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Jaeil Ahn
- Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University, Washington, DC, USA
| | - Ashley Artese
- Department of Exercise Science and Health Promotion, Charles E. Schmidt College of Science, Florida Atlantic University, Boca Raton, FL, USA
| | - Traci N Bethea
- Lombardi Comprehensive Cancer Center, Department of Oncology, Georgetown University, Washington, DC, USA
| | - Elizabeth C Breen
- Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA
- Cousins Center for Psychoneuroimmunology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Judith E Carroll
- Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA
- Cousins Center for Psychoneuroimmunology, University of California, Los Angeles, Los Angeles, CA, USA
| | - Harvey J Cohen
- Department of Medicine, Center for the Study of Aging and Human Development, Duke University Medical Center, Durham, NC, USA
| | - Martine Extermann
- Senior Adult Oncology Program, Department of Oncology, Moffitt Cancer Center, University of South Florida, Tampa, FL, USA
| | - Deena Graham
- John Theurer Cancer Center, Hackensack University Medical Center, Hackensack, NJ, USA
| | - Isaacs Claudine
- Lombardi Comprehensive Cancer Center, Department of Oncology, Georgetown University, Washington, DC, USA
| | - Heather S L Jim
- Department of Health Outcomes and Behavior, Moffitt Cancer Center, Tampa, FL, USA
| | - Brenna C McDonald
- Department of Radiology and Imaging Sciences, Melvin and Bren Simon Comprehensive Cancer Center, and Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Zev M Nakamura
- Department of Psychiatry, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Sunita K Patel
- Department of Population Sciences and Department of Supportive Care Medicine, City of Hope Comprehensive Cancer Center, Duarte, CA, USA
| | - G William Rebeck
- Department of Neuroscience, Georgetown University, Washington, DC, USA
| | - Kelly E Rentscher
- Department of Psychiatry and Behavioral Medicine, Medical College of Wisconsin Cancer Center, Medical College of Wisconsin, Milwaukee, WI, USA
| | - James C Root
- Department of Psychiatry and Behavioral Sciences, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Kristen A Russ
- Department of Medical and Molecular Genetics and National Centralized Repository for Alzheimer’s and Related Dementias, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Danielle B Tometich
- Department of Health Outcomes and Behavior, Moffitt Cancer Center, Tampa, FL, USA
| | - R Scott Turner
- Department of Neurology, Georgetown University, Washington, DC, USA
| | - Kathleen Van Dyk
- Semel Institute for Neuroscience and Human Behavior, Department of Psychiatry and Biobehavioral Sciences, University of California, Los Angeles, Los Angeles, CA, USA
- Jonsson Comprehensive Cancer Center, University of California, Los Angeles, Los Angeles, CA, USA
| | - Wanting Zhai
- Department of Biostatistics, Bioinformatics, and Biomathematics, Georgetown University, Washington, DC, USA
| | - Li-Wen Huang
- Division of Hematology/Oncology, University of California San Francisco and San Francisco Veterans Affairs Medical Center, San Francisco, CA, USA
| | - Andrew J Saykin
- Department of Radiology and Imaging Sciences, Melvin and Bren Simon Comprehensive Cancer Center, and Indiana Alzheimer’s Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
| |
Collapse
|
20
|
Soleimani-Meigooni DN, Smith R, Provost K, Lesman-Segev OH, Allen IE, Chen MK, Cho H, Edwards L, Janelidze S, La Joie R, Mundada N, Ossenkoppele R, Stomrud E, Strandberg O, Strom A, Boxer AL, Dage JL, Gorno-Tempini ML, Kramer JH, Miller BL, Rojas JC, Rosen HJ, Lyoo CH, Hansson O, Rabinovici GD. Head-to-Head Comparison of Tau and Amyloid Positron Emission Tomography Visual Reads for Differential Diagnosis of Neurodegenerative Disorders: An International, Multicenter Study. Ann Neurol 2024; 96:476-487. [PMID: 38888212 PMCID: PMC11324380 DOI: 10.1002/ana.27008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2024] [Revised: 05/29/2024] [Accepted: 05/29/2024] [Indexed: 06/20/2024]
Abstract
OBJECTIVE We compared the accuracy of amyloid and [18F]Flortaucipir (FTP) tau positron emission tomography (PET) visual reads for distinguishing patients with mild cognitive impairment (MCI) or dementia with fluid biomarker support of Alzheimer's disease (AD). METHODS Participants with FTP-PET, amyloid-PET, and diagnosis of dementia-AD (n = 102), MCI-AD (n = 41), non-AD diseases (n = 76), and controls (n = 20) were included. AD status was determined independent of PET by cerebrospinal fluid or plasma biomarkers. The mean age was 66.9 years, and 44.8% were women. Three readers interpreted scans blindly and independently. Amyloid-PET was classified as positive/negative using tracer-specific criteria. FTP-PET was classified as positive with medial temporal lobe (MTL) binding as the minimum uptake indicating AD tau (tau-MTL+), positive with posterolateral temporal or extratemporal cortical binding in an AD-like pattern (tau-CTX+), or negative. The majority of scan interpretations were used to calculate diagnostic accuracy of visual reads in detecting MCI/dementia with fluid biomarker support for AD (MCI/dementia-AD). RESULTS Sensitivity of amyloid-PET for MCI/dementia-AD was 95.8% (95% confidence interval 91.1-98.4%), which was comparable to tau-CTX+ 92.3% (86.7-96.1%, p = 0.67) and tau-MTL+ 97.2% (93.0-99.2%, p = 0.27). Specificity of amyloid-PET for biomarker-negative healthy and disease controls was 84.4% (75.5-91.0%), which was like tau-CTX+ 88.5% (80.4-94.1%, p = 0.34), and trended toward being higher than tau-MTL+ 75.0% (65.1-83.3%, p = 0.08). Tau-CTX+ had higher specificity than tau-MTL+ (p = 0.0002), but sensitivity was lower (p = 0.02), driven by decreased sensitivity for MCI-AD (80.5% [65.1-91.2] vs. 95.1% [83.5-99.4], p = 0.03). INTERPRETATION Amyloid- and tau-PET visual reads have similar sensitivity/specificity for detecting AD in cognitively impaired patients. Visual tau-PET interpretations requiring cortical binding outside MTL increase specificity, but lower sensitivity for MCI-AD. ANN NEUROL 2024;96:476-487.
Collapse
Affiliation(s)
- David N Soleimani-Meigooni
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
| | - Ruben Smith
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Karine Provost
- Department of Nuclear Medicine, University of Montreal Hospital Center, Montréal, Canada
| | - Orit H Lesman-Segev
- Department of Diagnostic Imaging, Sheba Medical Center, Tel Hashomer, Ramat Gan, Israel
| | - Isabel Elaine Allen
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Miranda K Chen
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Hanna Cho
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Lauren Edwards
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
- Clinical Psychology, San Diego State University & University of California, San Diego, CA, USA
| | | | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Nidhi Mundada
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, the Netherlands
| | - Erik Stomrud
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Amelia Strom
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
- Health Sciences and Technology, Harvard & Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Adam L Boxer
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Jeffrey L Dage
- Stark Neuroscience Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Joel H Kramer
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Julio C Rojas
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Howard J Rosen
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
| | - Chul H Lyoo
- Department of Neurology, Gangnam Severance Hospital, Yonsei University College of Medicine, Seoul, South Korea
| | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Lund, Sweden
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
| |
Collapse
|
21
|
Figdore DJ, Griswold M, Bornhorst JA, Graff‐Radford J, Ramanan VK, Vemuri P, Lowe VJ, Knopman DS, Jack CR, Petersen RC, Algeciras‐Schimnich A. Optimizing cutpoints for clinical interpretation of brain amyloid status using plasma p-tau217 immunoassays. Alzheimers Dement 2024; 20:6506-6516. [PMID: 39030981 PMCID: PMC11497693 DOI: 10.1002/alz.14140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Revised: 06/21/2024] [Accepted: 06/25/2024] [Indexed: 07/22/2024]
Abstract
INTRODUCTION We aimed to evaluate clinical interpretation cutpoints for two plasma phosphorylated tau (p-tau)217 assays (ALZpath and Lumipulse) as predictors of amyloid status for implementation in clinical practice. METHODS Clinical performance of plasma p-tau217 against amyloid positron emission tomography status was evaluated in participants with mild cognitive impairment or mild dementia (n = 427). RESULTS Using a one-cutpoint approach (negative/positive), neither assay achieved ≥ 90% in both sensitivity and specificity. A two-cutpoint approach yielding 92% sensitivity and 96% specificity provided the desired balance of false positives and false negatives, while categorizing 20% and 39% of results as indeterminate for the Lumipulse and ALZpath assays, respectively. DISCUSSION This study provides a systematic framework for selection of assay-specific cutpoints for clinical use of plasma p-tau217 for determination of amyloid status. Our findings suggest that a two-cutpoint approach may have advantages in optimizing diagnostic accuracy while minimizing potential harm from false positive results. HIGHLIGHTS Phosphorylated tau (p-tau)217 cutpoints for detection of amyloid pathology were established. A two-cutpoint approach exhibited the best performance for clinical laboratory use. p-tau217 assays differed in the percentage of results categorized as intermediate.
Collapse
Affiliation(s)
- Daniel J. Figdore
- Department of Laboratory Medicine and PathologyMayo ClinicRochesterMinnesotaUSA
| | - Michael Griswold
- The MIND CenterUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | - Joshua A. Bornhorst
- Department of Laboratory Medicine and PathologyMayo ClinicRochesterMinnesotaUSA
| | | | | | | | - Val J. Lowe
- Department of RadiologyMayo ClinicRochesterMinnesotaUSA
| | | | | | | | | |
Collapse
|
22
|
Verberk IMW, Jutte J, Kingma MY, Vigneswaran S, Gouda MMTEE, van Engelen M, Alcolea D, Arranz J, Fortea J, Lleó A, Chevalier C, Marizzoni M, van de Giessen EM, Lemstra AW, Pijnenburg YAL, van der Flier WM, den Braber A, Wilson D, Schut MC, van Harten AC, Teunissen CE. Development of thresholds and a visualization tool for use of a blood test in routine clinical dementia practice. Alzheimers Dement 2024; 20:6115-6132. [PMID: 39096164 PMCID: PMC11497719 DOI: 10.1002/alz.14088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2024] [Revised: 05/28/2024] [Accepted: 05/31/2024] [Indexed: 08/05/2024]
Abstract
INTRODUCTION We developed a multimarker blood test result interpretation tool for the clinical dementia practice, including phosphorylated (P-)tau181, amyloid-beta (Abeta)42/40, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL). METHODS We measured the plasma biomarkers with Simoa (n = 1199), applied LASSO regression for biomarker selection and receiver operating characteristics (ROC) analyses to determine diagnostic accuracy. We validated our findings in two independent cohorts and constructed a visualization approach. RESULTS P-tau181, GFAP, and NfL were selected. This combination had area under the curve (AUC) = 83% to identify amyloid positivity in pre-dementia stages, AUC = 87%-89% to differentiate Alzheimer's or controls from frontotemporal dementia, AUC = 74%-76% to differentiate Alzheimer's or controls from dementia with Lewy bodies. Highly reproducible AUCs were obtained in independent cohorts. The resulting visualization tool includes UpSet plots to visualize the stand-alone biomarker results and density plots to visualize the biomarker results combined. DISCUSSION Our multimarker blood test interpretation tool is ready for testing in real-world clinical dementia settings. HIGHLIGHTS We developed a multimarker blood test interpretation tool for clinical dementia practice. Our interpretation tool includes plasma biomarkers P-tau, GFAP, and NfL. Our tool is particularly useful for Alzheimer's and frontotemporal dementia diagnosis.
Collapse
Affiliation(s)
- Inge M. W. Verberk
- Neurochemistry Laboratory, Department of Laboratory MedicineAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
| | - Jolien Jutte
- Neurochemistry Laboratory, Department of Laboratory MedicineAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
- Translational Artificial Intelligence Laboratory, Department of Laboratory MedicineAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public HealthAmsterdamThe Netherlands
| | - Maurice Y. Kingma
- Neurochemistry Laboratory, Department of Laboratory MedicineAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
- Translational Artificial Intelligence Laboratory, Department of Laboratory MedicineAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public HealthAmsterdamThe Netherlands
| | - Sinthujah Vigneswaran
- Neurochemistry Laboratory, Department of Laboratory MedicineAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
- Alzheimer Center, Department of NeurologyAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
| | - Mariam M. T. E. E. Gouda
- Neurochemistry Laboratory, Department of Laboratory MedicineAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
| | - Marie‐Paule van Engelen
- Alzheimer Center, Department of NeurologyAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
| | - Daniel Alcolea
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau – Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de BarcelonaBarcelonaSpain
| | - Javier Arranz
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau – Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de BarcelonaBarcelonaSpain
| | - Juan Fortea
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau – Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de BarcelonaBarcelonaSpain
| | - Alberto Lleó
- Sant Pau Memory Unit, Department of NeurologyHospital de la Santa Creu i Sant Pau – Biomedical Research Institute Sant Pau (IIB Sant Pau), Universitat Autònoma de BarcelonaBarcelonaSpain
| | - Claire Chevalier
- Memory Centre, Division of Geriatrics and RehabilitationUniversity Hospitals of Geneva and University of GenevaGenevaSwitzerland
| | - Moira Marizzoni
- Laboratory of Biological PsychiatryIRCCS Istituto Centro San Giovanni di Dio FatebenefratelliBresciaItaly
| | - Elsmarieke M. van de Giessen
- Department of Radiology and Nuclear MedicineAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
| | - Afina W. Lemstra
- Alzheimer Center, Department of NeurologyAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
| | - Yolande A. L. Pijnenburg
- Alzheimer Center, Department of NeurologyAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
| | - Wiesje M. van der Flier
- Alzheimer Center, Department of NeurologyAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
- Amsterdam Public Health, Methodology & Digital HealthAmsterdam UMC, Vrije Universiteit AmsterdamAmsterdamThe Netherlands
| | - Anouk den Braber
- Neurochemistry Laboratory, Department of Laboratory MedicineAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
- Alzheimer Center, Department of NeurologyAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
- Biological PsychologyVrije Universiteit AmsterdamAmsterdamThe Netherlands
| | | | - Martijn C. Schut
- Translational Artificial Intelligence Laboratory, Department of Laboratory MedicineAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam Public HealthAmsterdamThe Netherlands
| | - Argonde C. van Harten
- Neurochemistry Laboratory, Department of Laboratory MedicineAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
- Alzheimer Center, Department of NeurologyAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
| | - Charlotte E. Teunissen
- Neurochemistry Laboratory, Department of Laboratory MedicineAmsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam NeuroscienceAmsterdamThe Netherlands
| |
Collapse
|
23
|
Zhang J, Zhang Y, Wang J, Xia Y, Zhang J, Chen L. Recent advances in Alzheimer's disease: Mechanisms, clinical trials and new drug development strategies. Signal Transduct Target Ther 2024; 9:211. [PMID: 39174535 PMCID: PMC11344989 DOI: 10.1038/s41392-024-01911-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 03/18/2024] [Accepted: 07/02/2024] [Indexed: 08/24/2024] Open
Abstract
Alzheimer's disease (AD) stands as the predominant form of dementia, presenting significant and escalating global challenges. Its etiology is intricate and diverse, stemming from a combination of factors such as aging, genetics, and environment. Our current understanding of AD pathologies involves various hypotheses, such as the cholinergic, amyloid, tau protein, inflammatory, oxidative stress, metal ion, glutamate excitotoxicity, microbiota-gut-brain axis, and abnormal autophagy. Nonetheless, unraveling the interplay among these pathological aspects and pinpointing the primary initiators of AD require further elucidation and validation. In the past decades, most clinical drugs have been discontinued due to limited effectiveness or adverse effects. Presently, available drugs primarily offer symptomatic relief and often accompanied by undesirable side effects. However, recent approvals of aducanumab (1) and lecanemab (2) by the Food and Drug Administration (FDA) present the potential in disrease-modifying effects. Nevertheless, the long-term efficacy and safety of these drugs need further validation. Consequently, the quest for safer and more effective AD drugs persists as a formidable and pressing task. This review discusses the current understanding of AD pathogenesis, advances in diagnostic biomarkers, the latest updates of clinical trials, and emerging technologies for AD drug development. We highlight recent progress in the discovery of selective inhibitors, dual-target inhibitors, allosteric modulators, covalent inhibitors, proteolysis-targeting chimeras (PROTACs), and protein-protein interaction (PPI) modulators. Our goal is to provide insights into the prospective development and clinical application of novel AD drugs.
Collapse
Affiliation(s)
- Jifa Zhang
- Department of Neurology, Laboratory of Neuro-system and Multimorbidity and State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Yinglu Zhang
- Department of Neurology, Laboratory of Neuro-system and Multimorbidity and State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Jiaxing Wang
- Department of Pharmaceutical Sciences, College of Pharmacy, University of Tennessee Health Science Center, Memphis, 38163, TN, USA
| | - Yilin Xia
- Department of Neurology, Laboratory of Neuro-system and Multimorbidity and State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Jiaxian Zhang
- Department of Neurology, Laboratory of Neuro-system and Multimorbidity and State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China
| | - Lei Chen
- Department of Neurology, Laboratory of Neuro-system and Multimorbidity and State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, 610041, Sichuan, China.
| |
Collapse
|
24
|
Ashton NJ, Keshavan A, Brum WS, Andreasson U, Arslan B, Droescher M, Barghorn S, Vanbrabant J, Lambrechts C, Van Loo M, Stoops E, Iyengar S, Ji H, Xu X, Forrest-Hay A, Zhang B, Luo Y, Jeromin A, Vandijck M, Bastard NL, Kolb H, Triana-Baltzer G, Bali D, Janelidze S, Yang SY, Demos C, Romero D, Sigal G, Wohlstadter J, Malyavantham K, Khare M, Jethwa A, Stoeckl L, Gobom J, Kac PR, Gonzalez-Ortiz F, Montoliu-Gaya L, Hansson O, Rissman RA, Carillo MC, Shaw LM, Blennow K, Schott JM, Zetterberg H. The Alzheimer's Association Global Biomarker Standardization Consortium (GBSC) plasma phospho-tau Round Robin study. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.08.22.24312244. [PMID: 39228740 PMCID: PMC11370527 DOI: 10.1101/2024.08.22.24312244] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
BACKGROUND Phosphorylated tau (p-tau) is a specific blood biomarker for Alzheimer's disease (AD) pathology. Multiple p-tau biomarkers on several analytical platforms are poised for clinical use. The Alzheimer's Association Global Biomarker Standardisation Consortium plasma phospho-tau Round Robin study engaged assay developers in a blinded case-control study on plasma p-tau, aiming to learn which assays provide the largest fold-changes in AD compared to non-AD, have the strongest relationship between plasma and cerebrospinal fluid (CSF), and show the most consistent relationships between methods (commutability) in measuring both patient samples and candidate reference materials (CRM). METHODS Thirty-three different p-tau biomarker assays, built on eight different analytical platforms, were used to quantify paired plasma and CSF samples from 40 participants. AD biomarker status was categorised as "AD pathology" (n=25) and "non-AD pathology" (n=15) by CSF Aβ42/Aβ40 (US-FDA; CE-IVDR) and p-tau181 (CE-IVDR) methods. The commutability of four CRM, at three concentrations, was assessed across assays. FINDINGS Plasma p-tau217 consistently demonstrated higher fold-changes between AD and non-AD pathology groups, compared to other p-tau epitopes. Fujirebio LUMIPULSE G, UGOT IPMS, and Lilly MSD p-tau217 assays provided the highest median fold-changes. In CSF, p-tau217 assays also performed best, and exhibited substantially larger fold-changes than their plasma counterparts, despite similar diagnostic performance. P-tau217 showed the strongest correlations between plasma assays (rho=0.81 to 0.97). Plasma p-tau levels were weakly-to-moderately correlated with CSF p-tau, and correlations were non-significant within the AD group alone. The evaluated CRM were not commutable across assays. INTERPRETATION Plasma p-tau217 measures had larger fold-changes and discriminative accuracies for detecting AD pathology, and better agreement across platforms than other plasma p-tau variants. Plasma and CSF markers of p-tau, measured by immunoassays, are not substantially correlated, questioning the interchangeability of their continuous relationship. Further work is warranted to understand the pathophysiology underlying this dissociation, and to develop suitable reference materials facilitating cross-assay standardisation. FUNDING Alzheimer's Association (#ADSF-24-1284328-C).
Collapse
Affiliation(s)
- Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King's College London, Institute of Psychiatry, Psychology and Neuroscience Maurice Wohl 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
| | - Ashvini Keshavan
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Wagner S Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & 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
| | - Ulf Andreasson
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Burak Arslan
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Mathias Droescher
- AbbVie Deutschland GmbH & Co. KG, Neuroscience Research, Knollstrasse, 67061 Ludwigshafen, Germany
| | - Stefan Barghorn
- AbbVie Deutschland GmbH & Co. KG, Neuroscience Research, Knollstrasse, 67061 Ludwigshafen, Germany
| | | | | | - Maxime Van Loo
- ADx NeuroSciences N.V., Technologiepark 6, 9052 Ghent, Belgium
| | - Erik Stoops
- ADx NeuroSciences N.V., Technologiepark 6, 9052 Ghent, Belgium
| | | | - HaYeun Ji
- Alamar Biosciences, Inc., Fremont, CA, USA
| | - Xiaomei Xu
- Alamar Biosciences, Inc., Fremont, CA, USA
| | | | | | - Yuling Luo
- Alamar Biosciences, Inc., Fremont, CA, USA
| | | | | | | | | | - Gallen Triana-Baltzer
- Neuroscience Biomarkers, Janssen Research and Development, La Jolla, California, USA
| | - Divya Bali
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund 22184, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund 22184, Sweden
| | | | | | - Daniel Romero
- Meso Scale Diagnostics, LLC., Rockville, Maryland, USA
| | - George Sigal
- Meso Scale Diagnostics, LLC., Rockville, Maryland, USA
| | | | | | | | | | | | - Johan Gobom
- 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
| | - Przemysław R Kac
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Fernando Gonzalez-Ortiz
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Laia Montoliu-Gaya
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Lund 22184, Sweden
- Memory Clinic, Skåne University Hospital, Malmö 20502, Sweden
| | - Robert A Rissman
- Alzheimer's Therapeutic Research Institute, Keck School of Medicine of the University of Southern California, San Diego, CA 92121, USA
| | - Maria C Carillo
- Division of Medical & Scientific Relations, Alzheimer's Association, Chicago, Illinois, USA
| | - Leslie M Shaw
- Department of pathology & laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Memory Clinic, Skåne University Hospital, Malmö 20502, Sweden
- Paris Brain Institute, ICM, Pitié-Salpêtrière Hospital, Sorbonne University, Paris, France
- Neurodegenerative Disorder Research Center, Division of Life Sciences and Medicine, and Department of Neurology, Institute on Aging and Brain Disorders, University of Science and Technology of China and First Affiliated Hospital of USTC, Hefei, P.R. China
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
- UK Dementia Research Institute, University College London, London, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Memory Clinic, Skåne University Hospital, Malmö 20502, Sweden
- UK Dementia Research Institute, University College London, London, UK
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Science Park, Hong Kong, China
- School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin, USA
| |
Collapse
|
25
|
Bader I, Groot C, Tan HS, Milongo JMA, Haan JD, Verberk IMW, Yong K, Orellina J, Campbell S, Wilson D, van Harten AC, Kok PHB, van der Flier WM, Pijnenburg YAL, Barkhof F, van de Giessen E, Teunissen CE, Bouwman FH, Ossenkoppele R. Rationale and design of the BeyeOMARKER study: prospective evaluation of blood- and eye-based biomarkers for early detection of Alzheimer's disease pathology in the eye clinic. Alzheimers Res Ther 2024; 16:190. [PMID: 39169442 PMCID: PMC11340081 DOI: 10.1186/s13195-024-01545-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Accepted: 07/25/2024] [Indexed: 08/23/2024]
Abstract
BACKGROUND Alzheimer's disease (AD) is a common, complex and multifactorial disease that may require screening across multiple routes of referral to enable early detection and subsequent future implementation of tailored interventions. Blood- and eye-based biomarkers show promise as low-cost, scalable and patient-friendly tools for early AD detection given their ability to provide information on AD pathophysiological changes and manifestations in the retina, respectively. Eye clinics provide an intriguing real-world proof-of-concept setting to evaluate the performance of these potential AD screening tools given the intricate connections between the eye and brain, presumed enrichment for AD pathology in the aging population with eye disorders, and the potential for an accelerated diagnostic pathway for under-recognized patient groups. METHODS The BeyeOMARKER study is a prospective, observational, longitudinal cohort study aiming to include individuals visiting an eye-clinic. Inclusion criteria entail being ≥ 50 years old and having no prior dementia diagnosis. Excluded eye-conditions include traumatic insults, superficial inflammation, and conditions in surrounding structures of the eye that are not engaged in vision. The BeyeOMARKER cohort (n = 700) will undergo blood collection to assess plasma p-tau217 levels and a brief cognitive screening at the eye clinic. All participants will subsequently be invited for annual longitudinal follow-up including remotely administered cognitive screening and questionnaires. The BeyeOMARKER + cohort (n = 150), consisting of 100 plasma p-tau217 positive participants and 50 matched negative controls selected from the BeyeOMARKER cohort, will additionally undergo Aβ-PET and tau-PET, MRI, retinal imaging including hyperspectral imaging (primary), widefield imaging, optical coherence tomography (OCT) and OCT-Angiography (secondary), and cognitive and cortical vision assessments. RESULTS We aim to implement the current protocol between April 2024 until March 2027. Primary outcomes include the performance of plasma p-tau217 and hyperspectral retinal imaging to detect AD pathology (using Aβ- and tau-PET visual read as reference standard) and to detect cognitive decline. Initial follow-up is ~ 2 years but may be extended with additional funding. CONCLUSIONS We envision that the BeyeOMARKER study will demonstrate the feasibility of early AD detection based on blood- and eye-based biomarkers in alternative screening settings, and will improve our understanding of the eye-brain connection. TRIAL REGISTRATION The BeyeOMARKER study (Eudamed CIV ID: CIV-NL-23-09-044086; registration date: 19th of March 2024) is approved by the ethical review board of the Amsterdam UMC.
Collapse
Affiliation(s)
- Ilse Bader
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, 1081 HV, The Netherlands.
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands.
- Department of Ophthalmology, Bergman Clinics, Amsterdam, 1101 BM, The Netherlands.
| | - Colin Groot
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, 1081 HV, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - H Stevie Tan
- Department of Ophthalmology, Bergman Clinics, Amsterdam, 1101 BM, The Netherlands
- Department of Ophthalmology, Amsterdam UMC, Amsterdam, 1081 HV, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands
- Amsterdam UMC Location VUmc, Amsterdam Reproduction and Development Research Institute, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands
| | - Jean-Marie A Milongo
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
- Department of Ophthalmology, Bergman Clinics, Amsterdam, 1101 BM, The Netherlands
| | - Jurre den Haan
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, 1081 HV, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - Inge M W Verberk
- Neurochemistry Laboratory, Laboratory Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, 1081 HV, The Netherlands
| | - Keir Yong
- Queen Square Institute of Neurology, Dementia Research Centre, London, WC1N 3BG, UK
| | | | | | | | - Argonde C van Harten
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, 1081 HV, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - Pauline H B Kok
- Department of Ophthalmology, Bergman Clinics, Amsterdam, 1101 BM, The Netherlands
| | - Wiesje M van der Flier
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, 1081 HV, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
- Epidemiology and Data Science, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, 1081 HV, The Netherlands
| | - Yolande A L Pijnenburg
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, 1081 HV, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - Frederik Barkhof
- Amsterdam Neuroscience, Brain Imaging, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands
- Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, 1081 HZ, The Netherlands
- UCL Queen Square Institute of Neurology and Centre for Medical Image Computing, University College, London, WC1N 3BG, UK
| | - Elsmarieke van de Giessen
- Amsterdam Neuroscience, Brain Imaging, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands
- Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - Charlotte E Teunissen
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, 1081 HV, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
- Neurochemistry Laboratory, Laboratory Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, 1081 HV, The Netherlands
| | - Femke H Bouwman
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, 1081 HV, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands
| | - Rik Ossenkoppele
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, 1081 HV, The Netherlands.
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, 1081 HZ, The Netherlands.
- Clinical Memory Research Unit, Lund University, Lund, Sweden.
| |
Collapse
|
26
|
Dyer AH, Dolphin H, O'Connor A, Morrison L, Sedgwick G, Young C, Killeen E, Gallagher C, McFeely A, Connolly E, Davey N, Claffey P, Doyle P, Lyons S, Gaffney C, Ennis R, McHale C, Joseph J, Knight G, Kelly E, O'Farrelly C, Fallon A, O'Dowd S, Bourke NM, Kennelly SP. Performance of plasma p-tau217 for the detection of amyloid-β positivity in a memory clinic cohort using an electrochemiluminescence immunoassay. Alzheimers Res Ther 2024; 16:186. [PMID: 39160628 PMCID: PMC11331802 DOI: 10.1186/s13195-024-01555-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2024] [Accepted: 08/11/2024] [Indexed: 08/21/2024]
Abstract
BACKGROUND Plasma p-tau217 has emerged as the most promising blood-based marker (BBM) for the detection of Alzheimer Disease (AD) pathology, yet few studies have evaluated plasma p-tau217 performance in memory clinic settings. We examined the performance of plasma p-tau217 for the detection of AD using a high-sensitivity immunoassay in individuals undergoing diagnostic lumbar puncture (LP). METHODS Paired plasma and cerebrospinal fluid (CSF) samples were analysed from the TIMC-BRAiN cohort. Amyloid (Aβ) and Tau (T) pathology were classified based on established cut-offs for CSF Aβ42 and CSF p-tau181 respectively. High-sensitivity electrochemiluminescence (ECL) immunoassays were performed on paired plasma/CSF samples for p-tau217, p-tau181, Glial Fibrillary Acidic Protein (GFAP), Neurofilament Light (NfL) and total tau (t-tau). Biomarker performance was evaluated using Receiver-Operating Curve (ROC) and Area-Under-the-Curve (AUC) analysis. RESULTS Of 108 participants (age: 69 ± 6.5 years; 54.6% female) with paired samples obtained at time of LP, 64.8% (n = 70/108) had Aβ pathology detected (35 with Mild Cognitive Impairment and 35 with mild dementia). Plasma p-tau217 was over three-fold higher in Aβ + (12.4 pg/mL; 7.3-19.2 pg/mL) vs. Aβ- participants (3.7 pg/mL; 2.8-4.1 pg/mL; Mann-Whitney U = 230, p < 0.001). Plasma p-tau217 exhibited excellent performance for the detection of Aβ pathology (AUC: 0.91; 95% Confidence Interval [95% CI]: 0.86-0.97)-greater than for T pathology (AUC: 0.83; 95% CI: 0.75-0.90; z = 1.75, p = 0.04). Plasma p-tau217 outperformed plasma p-tau181 for the detection of Aβ pathology (z = 3.24, p < 0.001). Of the other BBMs, only plasma GFAP significantly differed by Aβ status which significantly correlated with plasma p-tau217 in Aβ + (but not in Aβ-) individuals. Application of a two-point threshold at 95% and 97.5% sensitivities & specificities may have enabled avoidance of LP in 58-68% of cases. CONCLUSIONS Plasma p-tau217 measured using a high-sensitivity ECL immunoassay demonstrated excellent performance for detection of Aβ pathology in a real-world memory clinic cohort. Moving forward, clinical use of plasma p-tau217 to detect AD pathology may substantially reduce need for confirmatory diagnostic testing for AD pathology with diagnostic LP in specialist memory services.
Collapse
Affiliation(s)
- Adam H Dyer
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland.
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland.
| | - Helena Dolphin
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | | | - Laura Morrison
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Gavin Sedgwick
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Conor Young
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Emily Killeen
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Conal Gallagher
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Aoife McFeely
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Eimear Connolly
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Naomi Davey
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Paul Claffey
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Paddy Doyle
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Shane Lyons
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Christine Gaffney
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Ruth Ennis
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Cathy McHale
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Jasmine Joseph
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Graham Knight
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
| | - Emmet Kelly
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Cliona O'Farrelly
- School of Biochemistry and Immunology, Trinity Biomedical Sciences Institute, Trinity College Dublin, Dublin, Ireland
| | - Aoife Fallon
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Sean O'Dowd
- Department of Neurology, Tallaght University Hospital, Dublin, Ireland
| | - Nollaig M Bourke
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| | - Sean P Kennelly
- Department of Age-Related Healthcare, Tallaght University Hospital, Dublin, Ireland
- Discipline of Medical Gerontology, School of Medicine, Trinity Translational Medicine Institute, Trinity College Dublin, Dublin, Ireland
| |
Collapse
|
27
|
Lai R, Li B, Bishnoi R. P-tau217 as a Reliable Blood-Based Marker of Alzheimer's Disease. Biomedicines 2024; 12:1836. [PMID: 39200300 PMCID: PMC11351463 DOI: 10.3390/biomedicines12081836] [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: 07/17/2024] [Revised: 08/08/2024] [Accepted: 08/09/2024] [Indexed: 09/02/2024] Open
Abstract
Amyloid plaques and tau tangles are the hallmark pathologic features of Alzheimer's disease (AD). Traditionally, these changes are identified in vivo via cerebrospinal fluid (CSF) analysis or positron emission tomography (PET) scans. However, these methods are invasive, expensive, and resource-intensive. To address these limitations, there has been ongoing research over the past decade to identify blood-based markers for AD. Despite the challenges posed by their extremely low concentrations, recent advances in mass spectrometry and immunoassay techniques have made it feasible to detect these blood markers of amyloid and tau deposition. Phosphorylated tau (p-tau) has shown greater promise in reflecting amyloid pathology as evidenced by CSF and PET positivity. Various isoforms of p-tau, distinguished by their differential phosphorylation sites, have been recognized for their ability to identify amyloid-positive individuals. Notable examples include p-tau181, p-tau217, and p-tau235. Among these, p-tau217 has emerged as a superior and reliable marker of amyloid positivity and, thus, AD in terms of accuracy of diagnosis and ability for early prognosis. In this narrative review, we aim to elucidate the utility of p-tau217 as an AD marker, exploring its underlying basis, clinical diagnostic potential, and relevance in clinical care and trials.
Collapse
Affiliation(s)
- Roy Lai
- Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA (B.L.)
| | - Brenden Li
- Morsani College of Medicine, University of South Florida, Tampa, FL 33612, USA (B.L.)
| | - Ram Bishnoi
- Department of Psychiatry and Behavioral Neurosciences, University of South Florida, Tampa, FL 33613, USA
- USF Health Byrd Alzheimer’s Center and Research Institute, Tampa, FL 33613, USA
- USF Memory Disorder Clinic, Tampa, FL 33613, USA
| |
Collapse
|
28
|
Assfaw AD, Schindler SE, Morris JC. Advances in blood biomarkers for Alzheimer disease (AD): A review. Kaohsiung J Med Sci 2024; 40:692-698. [PMID: 38888066 DOI: 10.1002/kjm2.12870] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2024] [Accepted: 06/04/2024] [Indexed: 06/20/2024] Open
Abstract
Alzheimer disease (AD) and Alzheimer Disease and Related Dementias (AD/ADRD) are growing public health challenges globally affecting millions of older adults, necessitating concerted efforts to advance our understanding and management of these conditions. AD is a progressive neurodegenerative disorder characterized pathologically by amyloid plaques and tau neurofibrillary tangles that are the primary cause of dementia in older individuals. Early and accurate diagnosis of AD dementia is crucial for effective intervention and treatment but has proven challenging to accomplish. Although testing for AD brain pathology with cerebrospinal fluid (CSF) or positron emission tomography (PET) has been available for over 2 decades, most patients never underwent this testing because of inaccessibility, high out-of-pocket costs, perceived risks, and the lack of AD-specific treatments. However, in recent years, rapid progress has been made in developing blood biomarkers for AD/ADRD. Consequently, blood biomarkers have emerged as promising tools for non-invasive and cost-effective diagnosis, prognosis, and monitoring of AD progression. This review presents the evolving landscape of blood biomarkers in AD/ADRD and explores their potential applications in clinical practice for early detection, prognosis, and therapeutic interventions. It covers recent advances in blood biomarkers, including amyloid beta (Aβ) peptides, tau protein, neurofilament light chain (NfL), and glial fibrillary acidic protein (GFAP). It also discusses their diagnostic and prognostic utility while addressing associated challenges and limitations. Future research directions in this rapidly evolving field are also proposed.
Collapse
Affiliation(s)
- Araya Dimtsu Assfaw
- Department of Neurology, Knight Alzheimer Disease Research Center (Knight ADRC), Washington University School of Medicine, St. Louis, Missouri, USA
| | - Suzanne E Schindler
- Department of Neurology, Knight Alzheimer Disease Research Center (Knight ADRC), Washington University School of Medicine, St. Louis, Missouri, USA
| | - John C Morris
- Department of Neurology, Knight Alzheimer Disease Research Center (Knight ADRC), Washington University School of Medicine, St. Louis, Missouri, USA
| |
Collapse
|
29
|
Mielke MM, Fowler NR. Alzheimer disease blood biomarkers: considerations for population-level use. Nat Rev Neurol 2024; 20:495-504. [PMID: 38862788 PMCID: PMC11347965 DOI: 10.1038/s41582-024-00989-1] [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] [Accepted: 05/30/2024] [Indexed: 06/13/2024]
Abstract
In the past 5 years, we have witnessed the first approved Alzheimer disease (AD) disease-modifying therapy and the development of blood-based biomarkers (BBMs) to aid the diagnosis of AD. For many reasons, including accessibility, invasiveness and cost, BBMs are more acceptable and feasible for patients than a lumbar puncture (for cerebrospinal fluid collection) or neuroimaging. However, many questions remain regarding how best to utilize BBMs at the population level. In this Review, we outline the factors that warrant consideration for the widespread implementation and interpretation of AD BBMs. To set the scene, we review the current use of biomarkers, including BBMs, in AD. We go on to describe the characteristics of typical patients with cognitive impairment in primary care, who often differ from the patient populations used in AD BBM research studies. We also consider factors that might affect the interpretation of BBM tests, such as comorbidities, sex and race or ethnicity. We conclude by discussing broader issues such as ethics, patient and provider preference, incidental findings and dealing with indeterminate results and imperfect accuracy in implementing BBMs at the population level.
Collapse
Affiliation(s)
- Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA.
| | - Nicole R Fowler
- Department of Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana University Center for Aging Research, Indianapolis, IN, USA
- Regenstrief Institute, Inc., Indianapolis, IN, USA
| |
Collapse
|
30
|
Parvizi T, Wurm R, König T, Silvaieh S, Altmann P, Klotz S, Regelsberger G, Traub‐Weidinger T, Gelpi E, Stögmann E. Real-world performance of plasma p-tau181 in a heterogeneous memory clinic cohort. Ann Clin Transl Neurol 2024; 11:1988-1998. [PMID: 38965832 PMCID: PMC11330220 DOI: 10.1002/acn3.52116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 04/22/2024] [Accepted: 05/23/2024] [Indexed: 07/06/2024] Open
Abstract
OBJECTIVE In light of clinical trials and disease-modifying therapies, an early identification of patients at-risk of developing Alzheimer's disease (AD) is crucial. Blood-based biomarkers have shown promising results regarding the in vivo detection of the earliest neuropathological changes in AD. Herein, we investigated the ability of plasma p-tau181 to act as a prescreening marker for amyloid positivity in a heterogeneous memory clinic-based cohort. METHODS In this retrospective cross-sectional study, we included a total of 115 patients along the clinical AD continuum (mild cognitive impairment [MCI] due to AD, n = 62, probable AD dementia, n = 53). Based on their biomarker status, they were stratified into an amyloid-positive (Aβ+, n = 88) or amyloid-negative cohort (Aβ-, n = 27). Plasma and CSF p-tau181 concentrations were quantified using an ultrasensitive single-molecule array (SIMOA©). Furthermore, age- and sex-adjusted receiver operating characteristic (ROC) curves were calculated and the area under the curve (AUC) of each model was compared using DeLong's test for correlated AUC curves. RESULTS The median (interquartile range [IQR]) concentration of plasma p-tau181 was significantly higher in Aβ+ patients (3.6 pg/mL [2.5-4.6]), compared with Aβ- patients (1.7 pg/mL [1.2-1.9], p < 0.001). Regarding the distinction between Aβ+ and Aβ- patients and the prediction of amyloid positivity, a high diagnostic accuracy for plasma p-tau181 with an AUC of 0.89 (95% CI = 0.82-0.95) was calculated. Adding the risk factors, age and APOE4, to the model did not significantly improve its performance. INTERPRETATION Our findings demonstrate that plasma p-tau181 could be a noninvasive and feasible prescreening marker for amyloid positivity in a heterogeneous clinical AD cohort and therefore help in identifying those who would benefit from more invasive assessment of amyloid pathology.
Collapse
Affiliation(s)
- Tandis Parvizi
- Department of NeurologyMedical University of ViennaViennaAustria
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
| | - Raphael Wurm
- Department of NeurologyMedical University of ViennaViennaAustria
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
| | - Theresa König
- Department of NeurologyMedical University of ViennaViennaAustria
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
| | - Sara Silvaieh
- Department of NeurologyMedical University of ViennaViennaAustria
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
| | - Patrick Altmann
- Department of NeurologyMedical University of ViennaViennaAustria
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
| | - Sigrid Klotz
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
- Division of Neuropathology and Neurochemistry, Department of NeurologyMedical University of ViennaViennaAustria
| | - Guenther Regelsberger
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
- Division of Neuropathology and Neurochemistry, Department of NeurologyMedical University of ViennaViennaAustria
| | - Tatjana Traub‐Weidinger
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image‐Guided TherapyMedical University of ViennaViennaAustria
| | - Ellen Gelpi
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
- Division of Neuropathology and Neurochemistry, Department of NeurologyMedical University of ViennaViennaAustria
| | - Elisabeth Stögmann
- Department of NeurologyMedical University of ViennaViennaAustria
- Comprehensive Center for Clinical Neurosciences and Mental HealthMedical University of ViennaViennaAustria
| |
Collapse
|
31
|
Jack CR, Andrews JS, Beach TG, Buracchio T, Dunn B, Graf A, Hansson O, Ho C, Jagust W, McDade E, Molinuevo JL, Okonkwo OC, Pani L, Rafii MS, Scheltens P, Siemers E, Snyder HM, Sperling R, Teunissen CE, Carrillo MC. Revised criteria for diagnosis and staging of Alzheimer's disease: Alzheimer's Association Workgroup. Alzheimers Dement 2024; 20:5143-5169. [PMID: 38934362 PMCID: PMC11350039 DOI: 10.1002/alz.13859] [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: 02/07/2024] [Revised: 03/21/2024] [Accepted: 04/04/2024] [Indexed: 06/28/2024]
Abstract
The National Institute on Aging and the Alzheimer's Association convened three separate work groups in 2011 and single work groups in 2012 and 2018 to create recommendations for the diagnosis and characterization of Alzheimer's disease (AD). The present document updates the 2018 research framework in response to several recent developments. Defining diseases biologically, rather than based on syndromic presentation, has long been standard in many areas of medicine (e.g., oncology), and is becoming a unifying concept common to all neurodegenerative diseases, not just AD. The present document is consistent with this principle. Our intent is to present objective criteria for diagnosis and staging AD, incorporating recent advances in biomarkers, to serve as a bridge between research and clinical care. These criteria are not intended to provide step-by-step clinical practice guidelines for clinical workflow or specific treatment protocols, but rather serve as general principles to inform diagnosis and staging of AD that reflect current science. HIGHLIGHTS: We define Alzheimer's disease (AD) to be a biological process that begins with the appearance of AD neuropathologic change (ADNPC) while people are asymptomatic. Progression of the neuropathologic burden leads to the later appearance and progression of clinical symptoms. Early-changing Core 1 biomarkers (amyloid positron emission tomography [PET], approved cerebrospinal fluid biomarkers, and accurate plasma biomarkers [especially phosphorylated tau 217]) map onto either the amyloid beta or AD tauopathy pathway; however, these reflect the presence of ADNPC more generally (i.e., both neuritic plaques and tangles). An abnormal Core 1 biomarker result is sufficient to establish a diagnosis of AD and to inform clinical decision making throughout the disease continuum. Later-changing Core 2 biomarkers (biofluid and tau PET) can provide prognostic information, and when abnormal, will increase confidence that AD is contributing to symptoms. An integrated biological and clinical staging scheme is described that accommodates the fact that common copathologies, cognitive reserve, and resistance may modify relationships between clinical and biological AD stages.
Collapse
Affiliation(s)
| | - J. Scott Andrews
- Global Evidence & OutcomesTakeda Pharmaceuticals Company LimitedCambridgeMassachusettsUSA
| | - Thomas G. Beach
- Civin Laboratory for NeuropathologyBanner Sun Health Research InstituteSun CityArizonaUSA
| | - Teresa Buracchio
- Office of NeuroscienceU.S. Food and Drug AdministrationSilver SpringMarylandUSA
| | - Billy Dunn
- The Michael J. Fox Foundation for Parkinson's ResearchNew YorkNew YorkUSA
| | - Ana Graf
- NovartisNeuroscience Global Drug DevelopmentBaselSwitzerland
| | - Oskar Hansson
- Department of Clinical Sciences Malmö, Faculty of MedicineLund UniversityLundSweden
- Memory ClinicSkåne University Hospital, MalmöLundSweden
| | - Carole Ho
- DevelopmentDenali TherapeuticsSouth San FranciscoCaliforniaUSA
| | - William Jagust
- School of Public Health and Helen Wills Neuroscience InstituteUniversity of California BerkeleyBerkeleyCaliforniaUSA
| | - Eric McDade
- Department of NeurologyWashington University St. Louis School of MedicineSt. LouisMissouriUSA
| | - Jose Luis Molinuevo
- Department of Global Clinical Development H. Lundbeck A/SExperimental MedicineCopenhagenDenmark
| | - Ozioma C. Okonkwo
- Department of Medicine, Division of Geriatrics and GerontologyUniversity of Wisconsin School of MedicineMadisonWisconsinUSA
| | - Luca Pani
- University of MiamiMiller School of MedicineMiamiFloridaUSA
| | - Michael S. Rafii
- Alzheimer's Therapeutic Research Institute (ATRI)Keck School of Medicine at the University of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Philip Scheltens
- Amsterdam University Medical Center (Emeritus)NeurologyAmsterdamthe Netherlands
| | - Eric Siemers
- Clinical ResearchAcumen PharmaceuticalsZionsvilleIndianaUSA
| | - Heather M. Snyder
- Medical & Scientific Relations DivisionAlzheimer's AssociationChicagoIllinoisUSA
| | - Reisa Sperling
- Department of Neurology, Brigham and Women's HospitalMassachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Charlotte E. Teunissen
- Department of Laboratory MedicineAmsterdam UMC, Neurochemistry LaboratoryAmsterdamthe Netherlands
| | - Maria C. Carrillo
- Medical & Scientific Relations DivisionAlzheimer's AssociationChicagoIllinoisUSA
| |
Collapse
|
32
|
Zhang Y, Bi K, Zhou L, Wang J, Huang L, Sun Y, Peng G, Wu W. Advances in Blood Biomarkers for Alzheimer's Disease: Ultra-Sensitive Detection Technologies and Impact on Clinical Diagnosis. Degener Neurol Neuromuscul Dis 2024; 14:85-102. [PMID: 39100640 PMCID: PMC11297492 DOI: 10.2147/dnnd.s471174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2024] [Accepted: 07/16/2024] [Indexed: 08/06/2024] Open
Abstract
Alzheimer's disease has escalated into a critical public health concern, marked by its neurodegenerative nature that progressively diminishes cognitive abilities. Recognized as a continuously advancing and presently incurable condition, AD underscores the necessity for early-stage diagnosis and interventions aimed at delaying the decline in mental function. Despite the proven efficacy of cerebrospinal fluid and positron emission tomography in diagnosing AD, their broader utility is constrained by significant costs and the invasive nature of these procedures. Consequently, the innovation of blood biomarkers such as Amyloid-beta, phosphorylated-tau, total-tau et al, distinguished by their high sensitivity, minimal invasiveness, accessibility, and cost-efficiency, emerges as a promising avenue for AD diagnosis. The advent of ultra-sensitive detection methodologies, including single-molecule enzyme-linked immunosorbent assay and immunoprecipitation-mass spectrometry, has revolutionized the detection of AD plasma biomarkers, supplanting previous low-sensitivity techniques. This rapid advancement in detection technology facilitates the more accurate quantification of pathological brain proteins and AD-associated biomarkers in the bloodstream. This manuscript meticulously reviews the landscape of current research on immunological markers for AD, anchored in the National Institute on Aging-Alzheimer's Association AT(N) research framework. It highlights a selection of forefront ultra-sensitive detection technologies now integral to assessing AD blood immunological markers. Additionally, this review examines the crucial pre-analytical processing steps for AD blood samples that significantly impact research outcomes and addresses the practical challenges faced during clinical testing. These discussions are crucial for enhancing our comprehension and refining the diagnostic precision of AD using blood-based biomarkers. The review aims to shed light on potential avenues for innovation and improvement in the techniques employed for detecting and investigating AD, thereby contributing to the broader field of neurodegenerative disease research.
Collapse
Affiliation(s)
- Yi Zhang
- Department of Laboratory Medicine, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
| | - Kefan Bi
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
| | - Linfu Zhou
- Department of Biochemistry, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
| | - Jie Wang
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
| | - Lingtong Huang
- Department of Critical Care Units, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
| | - Yan Sun
- Department of Neurology, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
| | - Guoping Peng
- Department of Neurology, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
| | - Wei Wu
- State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, National Medical Center for Infectious Diseases, Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, the First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, People’s Republic of China
| |
Collapse
|
33
|
Guo T, Li A, Sun P, He Z, Cai Y, Lan G, Liu L, Li J, Yang J, Zhu Y, Zhao R, Chen X, Shi D, Liu Z, Wang Q, Xu L, Zhou L, Ran P, Wang X, Sun K, Lu J, Han Y. Astrocyte reactivity is associated with tau tangle load and cortical thinning in Alzheimer's disease. Mol Neurodegener 2024; 19:58. [PMID: 39080744 PMCID: PMC11290175 DOI: 10.1186/s13024-024-00750-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Accepted: 07/25/2024] [Indexed: 08/02/2024] Open
Abstract
BACKGROUND It is not fully established whether plasma β-amyloid(Aβ)42/Aβ40 and phosphorylated Tau181 (p-Tau181) can effectively detect Alzheimer's disease (AD) pathophysiology in older Chinese adults and how these biomarkers correlate with astrocyte reactivity, Aβ plaque deposition, tau tangle aggregation, and neurodegeneration. METHODS We recruited 470 older adults and analyzed plasma Aβ42/Aβ40, p-Tau181, glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) using the Simoa platform. Among them, 301, 195, and 70 underwent magnetic resonance imaging, Aβ and tau positron emission tomography imaging. The plasma Aβ42/Aβ40 and p-Tau181 thresholds were defined as ≤0.0609 and ≥2.418 based on the receiver operating characteristic curve analysis using the Youden index by comparing Aβ-PET negative cognitively unimpaired individuals and Aβ-PET positive cognitively impaired patients. To evaluate the feasibility of using plasma Aβ42/Aβ40 (A) and p-Tau181 (T) to detect AD and understand how astrocyte reactivity affects this process, we compared plasma GFAP, Aβ plaque, tau tangle, plasma NfL, hippocampal volume, and temporal-metaROI cortical thickness between different plasma A/T profiles and explored their relations with each other using general linear models, including age, sex, APOE-ε4, and diagnosis as covariates. RESULTS Plasma A+/T + individuals showed the highest levels of astrocyte reactivity, Aβ plaque, tau tangle, and axonal degeneration, and the lowest hippocampal volume and temporal-metaROI cortical thickness. Lower plasma Aβ42/Aβ40 and higher plasma p-Tau181 were independently and synergistically correlated with higher plasma GFAP and Aβ plaque. Elevated plasma p-Tau181 and GFAP concentrations were directly and interactively associated with more tau tangle formation. Regarding neurodegeneration, higher plasma p-Tau181 and GFAP concentrations strongly correlated with more axonal degeneration, as measured by plasma NfL, and lower plasma Aβ42/Aβ40 and higher plasma p-Tau181 were related to greater hippocampal atrophy. Higher plasma GFAP levels were associated with thinner cortical thickness and significantly interacted with lower plasma Aβ42/Aβ40 and higher plasma p-Tau181 in predicting more temporal-metaROI cortical thinning. Voxel-wise imaging analysis confirmed these findings. DISCUSSION This study provides a valuable reference for using plasma biomarkers to detect AD in the Chinese community population and offers novel insights into how astrocyte reactivity contributes to AD progression, highlighting the importance of targeting reactive astrogliosis to prevent AD.
Collapse
Affiliation(s)
- Tengfei Guo
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China.
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, 518055, China.
| | - Anqi Li
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Pan Sun
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Zhengbo He
- 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
| | - Guoyu Lan
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Lin Liu
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Jieyin Li
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Jie Yang
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
- Department of Neurology, Xuanwu Hospital of Capital Medical University, #45 Changchun Street, Xicheng District, Beijing, 100053, China
| | - Yalin Zhu
- 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
| | - Xuhui Chen
- Department of Neurology, Peking University Shenzhen Hospital, Shenzhen, 518000, China
| | - Dai Shi
- Neurology Medicine Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518000, China
| | - Zhen Liu
- Institute of Biomedical Engineering, Shenzhen Bay Laboratory, No.5 Kelian Road, Shenzhen, 518132, China
| | - Qingyong Wang
- Department of Neurology, Shenzhen Guangming District People's Hospital, Shenzhen, 518107, China
| | - Linsen Xu
- Department of Medical Imaging, Shenzhen Guangming District People's Hospital, Shenzhen, 518106, China
| | - Liemin Zhou
- Neurology Medicine Center, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, 518000, China
| | - Pengcheng Ran
- Department of Nuclear Medicine, Guangdong Hospital of Traditional Chinese Medicine, Guangzhou, 510120, China
| | - Xinlu Wang
- Department of Nuclear Medicine, The First Affiliated Hospital, Guangzhou Medical University, Guangzhou, 510120, China
| | - Kun Sun
- Institute of Cancer Research, Shenzhen Bay Laboratory, Shenzhen, 518132, China
| | - Jie Lu
- Department of Neurology, Xuanwu Hospital of Capital Medical University, #45 Changchun Street, Xicheng District, Beijing, 100053, China.
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, #45 Changchun Street, Xicheng District, Beijing, 100053, China.
| | - 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, #45 Changchun Street, Xicheng District, Beijing, 100053, China.
- School of Biomedical Engineering, Hainan University, Haikou, 570228, China.
- Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, 100053, China.
- National Clinical Research Center for Geriatric Diseases, Beijing, 100053, China.
| |
Collapse
|
34
|
Krawczuk D, Kulczyńska-Przybik A, Mroczko B. Clinical Application of Blood Biomarkers in Neurodegenerative Diseases-Present and Future Perspectives. Int J Mol Sci 2024; 25:8132. [PMID: 39125699 PMCID: PMC11311320 DOI: 10.3390/ijms25158132] [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: 06/06/2024] [Revised: 07/19/2024] [Accepted: 07/22/2024] [Indexed: 08/12/2024] Open
Abstract
Neurodegenerative diseases are a group of complex diseases characterized by a progressive loss of neurons and degeneration in different areas of the nervous system. They share similar mechanisms, such as neuroinflammation, oxidative stress, and mitochondrial injury, resulting in neuronal loss. One of the biggest challenges in diagnosing neurodegenerative diseases is their heterogeneity. Clinical symptoms are usually present in the advanced stages of the disease, thus it is essential to find optimal biomarkers that would allow early diagnosis. Due to the development of ultrasensitive methods analyzing proteins in other fluids, such as blood, huge progress has been made in the field of biomarkers for neurodegenerative diseases. The application of protein biomarker measurement has significantly influenced not only diagnosis but also prognosis, differentiation, and the development of new therapies, as it enables the recognition of early stages of disease in individuals with preclinical stages or with mild symptoms. Additionally, the introduction of biochemical markers into routine clinical practice may improve diagnosis and allow for a stratification group of people with higher risk, as well as an extension of well-being since a treatment could be started early. In this review, we focus on blood biomarkers, which could be potentially useful in the daily medical practice of selected neurodegenerative diseases.
Collapse
Affiliation(s)
- Daria Krawczuk
- Department of Neurodegeneration Diagnostics, Medical University of Białystok, 15-089 Białystok, Poland; (D.K.); (A.K.-P.)
| | - Agnieszka Kulczyńska-Przybik
- Department of Neurodegeneration Diagnostics, Medical University of Białystok, 15-089 Białystok, Poland; (D.K.); (A.K.-P.)
| | - Barbara Mroczko
- Department of Neurodegeneration Diagnostics, Medical University of Białystok, 15-089 Białystok, Poland; (D.K.); (A.K.-P.)
- Department of Biochemical Diagnostics, Medical University of Białystok, 15-089 Białystok, Poland
| |
Collapse
|
35
|
Howe MD, Britton KJ, Joyce HE, Menard W, Emrani S, Kunicki ZJ, Faust MA, Dawson BC, Riddle MC, Huey ED, Janelidze S, Hansson O, Salloway SP. Clinical application of plasma P-tau217 to assess eligibility for amyloid-lowering immunotherapy in memory clinic patients with early Alzheimer's disease. Alzheimers Res Ther 2024; 16:154. [PMID: 38971815 PMCID: PMC11227160 DOI: 10.1186/s13195-024-01521-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2023] [Accepted: 06/26/2024] [Indexed: 07/08/2024]
Abstract
BACKGROUND With the approval of disease-modifying treatments (DMTs) for early Alzheimer's disease (AD), there is an increased need for efficient and non-invasive detection methods for cerebral amyloid-β (Aβ) pathology. Current methods, including positron emission tomography (PET) and cerebrospinal fluid (CSF) analysis, are costly and invasive methods that may limit access to new treatments. Plasma tau phosphorylated at threonine-217 (P-tau217) presents a promising alternative, yet optimal cutoffs for treatment eligibility with DMTs like aducanumab require further investigation. This study evaluates the efficacy of one- and two-cutoff strategies for determining DMT eligibility at the Butler Hospital Memory & Aging Program (MAP). METHODS In this retrospective, cross-sectional diagnostic cohort study, we first developed P-tau217 cutoffs using site-specific and BioFINDER-2 training data, which were then tested in potential DMT candidates from Butler MAP (total n = 150). ROC analysis was used to calculate the area under the curve (AUC) and accuracy of P-tau217 interpretation strategies, using Aβ-PET/CSF testing as the standard of truth. RESULTS Potential DMT candidates at Butler MAP (n = 50), primarily diagnosed with mild cognitive impairment (n = 29 [58%]) or mild dementia (21 [42%]), were predominantly Aβ-positive (38 [76%]), and half (25 [50%]) were subsequently treated with aducanumab. Elevated P-tau217 predicted cerebral Aβ positivity in potential DMT candidates (AUC = 0.97 [0.92-1]), with diagnostic accuracy ranging from 0.88 (0.76-0.95, p = 0.028) to 0.96 (0.86-1, p < .001). When using site-specific cutoffs, a subset of DMT candidates (10%) exhibited borderline P-tau217 (between 0.273 and 0.399 pg/mL) that would have potentially required confirmatory testing. CONCLUSIONS This study, which included participants treated with aducanumab, confirms the utility of one- and two-cutoff strategies for interpreting plasma P-tau217 in assessing DMT eligibility. Using P-tau217 could potentially replace more invasive diagnostic methods, and all aducanumab-treated participants would have been deemed eligible based on P-tau217. However, false positives remain a concern, particularly when applying externally derived cutoffs that exhibited lower specificity which could have led to inappropriate treatment of Aβ-negative participants. Future research should focus on prospective validation of P-tau217 cutoffs to enhance their generalizability and inform standardized treatment decision-making across diverse populations.
Collapse
Affiliation(s)
- Matthew D Howe
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA.
- Department of Psychiatry and Human Behavior, Brown University, Providence, RI, USA.
| | | | - Hannah E Joyce
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA
| | - William Menard
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA
| | - Sheina Emrani
- University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, USA
| | - Zachary J Kunicki
- Department of Psychiatry and Human Behavior, Brown University, Providence, RI, USA
| | - Melanie A Faust
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA
| | - Brittany C Dawson
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA
| | - Meghan C Riddle
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA
- Department of Psychiatry and Human Behavior, Brown University, Providence, RI, USA
| | - Edward D Huey
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA
- Department of Psychiatry and Human Behavior, Brown University, Providence, RI, USA
| | - Shorena Janelidze
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Stephen P Salloway
- Butler Hospital Memory & Aging Program, 345 Blackstone Boulevard, Providence, RI, 02906, USA
- Department of Psychiatry and Human Behavior, Brown University, Providence, RI, USA
| |
Collapse
|
36
|
Xiong C, Luo J, Wolk DA, Shaw LM, Roberson ED, Murchison CF, Henson RL, Benzinger TLS, Bui Q, Agboola F, Grant E, Gremminger EN, Moulder KL, Geldmacher DS, Clay OJ, Babulal G, Cruchaga C, Holtzman DM, Bateman RJ, Morris JC, Schindler SE. Baseline levels and longitudinal changes in plasma Aβ42/40 among Black and white individuals. Nat Commun 2024; 15:5539. [PMID: 38956096 PMCID: PMC11219932 DOI: 10.1038/s41467-024-49859-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Accepted: 06/21/2024] [Indexed: 07/04/2024] Open
Abstract
Blood-based biomarkers of Alzheimer disease (AD) may facilitate testing of historically under-represented groups. The Study of Race to Understand Alzheimer Biomarkers (SORTOUT-AB) is a multi-center longitudinal study to compare AD biomarkers in participants who identify their race as either Black or white. Plasma samples from 324 Black and 1,547 white participants underwent analysis with C2N Diagnostics' PrecivityAD test for Aβ42 and Aβ40. Compared to white individuals, Black individuals had higher average plasma Aβ42/40 levels at baseline, consistent with a lower average level of amyloid pathology. Interestingly, this difference resulted from lower average levels of plasma Aβ40 in Black participants. Despite the differences, Black and white individuals had similar longitudinal rates of change in Aβ42/40, consistent with a similar rate of amyloid accumulation. Our results agree with multiple recent studies demonstrating a lower prevalence of amyloid pathology in Black individuals, and additionally suggest that amyloid accumulates consistently across both groups.
Collapse
Affiliation(s)
- Chengjie Xiong
- Division of Biostatistics, Washington University, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Jingqin Luo
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO, USA
- Siteman Cancer Center Biostatistics and Qualitative Research Shared Resource, Washington University School of Medicine, St. Louis, MO, USA
| | - David A Wolk
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Leslie M Shaw
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Erik D Roberson
- Alzheimer's Disease Center, Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Charles F Murchison
- Alzheimer's Disease Center, Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Rachel L Henson
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L S Benzinger
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Mallinckrodt Institute of Radiology, Washington University, St. Louis, MO, USA
| | - Quoc Bui
- Division of Biostatistics, Washington University, St. Louis, MO, USA
| | - Folasade Agboola
- Division of Biostatistics, Washington University, St. Louis, MO, USA
| | - Elizabeth Grant
- Division of Biostatistics, Washington University, St. Louis, MO, USA
| | | | - Krista L Moulder
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - David S Geldmacher
- Alzheimer's Disease Center, Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Olivio J Clay
- Alzheimer's Disease Center, Department of Neurology, University of Alabama at Birmingham, Birmingham, AL, USA
- Department of Psychology, University of Alabama at Birmingham, Birmingham, AL, USA
| | - Ganesh Babulal
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Carlos Cruchaga
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA.
| |
Collapse
|
37
|
Asken BM, DeSimone JC, Wang W, McFarland KN, Arias F, Levy S, Fiala J, Velez‐Uribe I, Mayrand RP, Sawada LO, Freytes C, Adeyosoye M, Barker WW, Crocco EA, DeKosky ST, Adjouadi M, Rosselli M, Marsiske M, Armstrong MJ, Smith GE, Cid RC, Loewenstein DA, Vaillancourt DE, Duara R. Plasma p-tau217 concordance with amyloid PET among ethnically diverse older adults. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12617. [PMID: 39021585 PMCID: PMC11253830 DOI: 10.1002/dad2.12617] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 05/31/2024] [Accepted: 06/08/2024] [Indexed: 07/20/2024]
Abstract
INTRODUCTION Commercially available plasma p-tau217 biomarker tests are not well studied in ethnically diverse samples. METHODS We evaluated associations between ALZPath plasma p-tau217 and amyloid-beta positron emission tomography (Aβ-PET) in Hispanic/Latino (88% of Cuban or South American ancestry) and non-Hispanic/Latino older adults. One- and two-cutoff ranges were derived and evaluated to assess agreement with Aβ-PET. RESULTS A total of 239 participants underwent blood draw and Aβ-PET (age 70.8 ± 7.8, 55.2% female, education 15.6 ± 3.4 years, 48.9% Hispanic/Latino, 94.9% white). Plasma p-tau217 showed excellent discrimination of Aβ-PET positive and negative participants (visual read: AUC = 0.91 [0.87-0.95], p < 0.001; Centiloids quantification: AUC = 0.90 [0.86-0.94]). There was a greater percent agreement between low p-tau217 and negative Aβ-PET (95.8%) than high p-tau217 and positive Aβ-PET (86.3%). Analyses within ethnicity-specific subgroups suggested similar p-tau217 performance. DISCUSSION Plasma p-tau217 (ALZPath) relates to brain Aβ in Hispanic/Latino and non-Hispanic/Latino older adults. Independent validation and replication are necessary to establish reference ranges and inform appropriate contexts of use across ethno-racially diverse populations. HIGHLIGHTS Plasma p-tau217 (ALZPath) and Aβ-PET were measured in Hispanic/Latino and non-Hispanic/Latino older adults.Plasma p-tau217 accurately discriminated Aβ-PET positive and negative participants.Applying a two-cutoff "intermediate" plasma p-tau217 approach could reduce need for more invasive and costly testing.Plasma p-tau217 associations with Aβ-PET were strong within both Hispanic/Latino and non-Hispanic/Latino groups.
Collapse
|
38
|
Blankenship AE, Yoksh L, Kueck PJ, Mahnken JD, Morris JK, Gupta A. Changes in Alzheimer's disease blood biomarkers in kidney failure before and after kidney transplant. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2024; 16:e12614. [PMID: 38966621 PMCID: PMC11220407 DOI: 10.1002/dad2.12614] [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: 02/28/2024] [Revised: 05/22/2024] [Accepted: 06/01/2024] [Indexed: 07/06/2024]
Abstract
INTRODUCTION Alzheimer's disease (AD) blood biomarkers show promise for clinical diagnosis but their reliability in chronic kidney disease (CKD) is debated. This study investigates the impact of kidney transplant (KT) on AD biomarkers in CKD. METHODS We assessed AD biomarkers in 46 CKD patients pre-KT, at 12 weeks and 12 months post-KT, with baseline measures from 13 non-CKD controls. Using linear mixed models, we examined associations with participant groups, estimated glomerular filtration rate (eGFR) and cognition. RESULTS CKD patients showed elevated levels of neurofilament light (117 ± 72 vs. 11 ± 5 pg/mL), phosphorylated tau 181 (75 ± 42 vs. 13 ± 8 pg/mL), glial fibrillary acidic protein (193 ± 127 vs. 94 ± 39 pg/mL), amyloid β 42 (17 ± 5 vs. 5 ± 1 pg/mL), and amyloid β 40 (259 ± 96 vs. 72 ± 17 pg/mL) compared to controls. Post-KT, biomarker levels approached normal with improved eGFR, paralleled by enhanced cognitive function. DISCUSSION AD blood biomarker elevations in CKD are reversible with improved kidney function through KT. Highlights AD biomarker levels are extremely high in severe CKD.AD biomarker levels are higher in patients with kidney failure on dialysis when compared to CKD patients not on dialysis.These elevations in AD biomarker levels in kidney failure are reversable and decrease dramatically after kidney transplantation.The change in biomarker levels after transplantation align with changes in kidney function.The change in biomarker levels after transplantation align with changes in cognitive function.
Collapse
Affiliation(s)
- Anneka E. Blankenship
- University of Kansas Alzheimer's Disease Research Center, University of Kansas Medical CenterFairwayKansasUSA
- Department of NeurologyUniversity of Kansas Medical CenterKansas CityKansasUSA
| | - Lauren Yoksh
- Department of Biostatistics & Data ScienceUniversity of Kansas Medical CenterKansas CityKansasUSA
| | - Paul J. Kueck
- University of Kansas Alzheimer's Disease Research Center, University of Kansas Medical CenterFairwayKansasUSA
- Department of NeurologyUniversity of Kansas Medical CenterKansas CityKansasUSA
| | - Jonathan D. Mahnken
- University of Kansas Alzheimer's Disease Research Center, University of Kansas Medical CenterFairwayKansasUSA
- Department of Biostatistics & Data ScienceUniversity of Kansas Medical CenterKansas CityKansasUSA
- Frontiers Clinical & Translational Science Institute, University of Kansas Medical CenterFairwayKansasUSA
| | - Jill K. Morris
- University of Kansas Alzheimer's Disease Research Center, University of Kansas Medical CenterFairwayKansasUSA
- Department of NeurologyUniversity of Kansas Medical CenterKansas CityKansasUSA
| | - Aditi Gupta
- University of Kansas Alzheimer's Disease Research Center, University of Kansas Medical CenterFairwayKansasUSA
- Department of NeurologyUniversity of Kansas Medical CenterKansas CityKansasUSA
- Frontiers Clinical & Translational Science Institute, University of Kansas Medical CenterFairwayKansasUSA
- Division of Nephrology and HypertensionDepartment of Internal MedicineUniversity of Kansas Medical CenterKansas CityKansasUSA
| |
Collapse
|
39
|
Schindler SE, Galasko D, Pereira AC, Rabinovici GD, Salloway S, Suárez-Calvet M, Khachaturian AS, Mielke MM, Udeh-Momoh C, Weiss J, Batrla R, Bozeat S, Dwyer JR, Holzapfel D, Jones DR, Murray JF, Partrick KA, Scholler E, Vradenburg G, Young D, Algeciras-Schimnich A, Aubrecht J, Braunstein JB, Hendrix J, Hu YH, Mattke S, Monane M, Reilly D, Somers E, Teunissen CE, Shobin E, Vanderstichele H, Weiner MW, Wilson D, Hansson O. Acceptable performance of blood biomarker tests of amyloid pathology - recommendations from the Global CEO Initiative on Alzheimer's Disease. Nat Rev Neurol 2024; 20:426-439. [PMID: 38866966 DOI: 10.1038/s41582-024-00977-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/16/2024] [Indexed: 06/14/2024]
Abstract
Anti-amyloid treatments for early symptomatic Alzheimer disease have recently become clinically available in some countries, which has greatly increased the need for biomarker confirmation of amyloid pathology. Blood biomarker (BBM) tests for amyloid pathology are more acceptable, accessible and scalable than amyloid PET or cerebrospinal fluid (CSF) tests, but have highly variable levels of performance. The Global CEO Initiative on Alzheimer's Disease convened a BBM Workgroup to consider the minimum acceptable performance of BBM tests for clinical use. Amyloid PET status was identified as the reference standard. For use as a triaging test before subsequent confirmatory tests such as amyloid PET or CSF tests, the BBM Workgroup recommends that a BBM test has a sensitivity of ≥90% with a specificity of ≥85% in primary care and ≥75-85% in secondary care depending on the availability of follow-up testing. For use as a confirmatory test without follow-up tests, a BBM test should have performance equivalent to that of CSF tests - a sensitivity and specificity of ~90%. Importantly, the predictive values of all biomarker tests vary according to the pre-test probability of amyloid pathology and must be interpreted in the complete clinical context. Use of BBM tests that meet these performance standards could enable more people to receive an accurate and timely Alzheimer disease diagnosis and potentially benefit from new treatments.
Collapse
Affiliation(s)
- Suzanne E Schindler
- Department of Neurology, Knight Alzheimer's Disease Research Center, Washington University School of Medicine, St Louis, MO, USA.
| | - Douglas Galasko
- Department of Neurosciences, University of California, San Diego, La Jolla, CA, USA
| | - Ana C Pereira
- Department of Neurology, Icahn School of Medicine, Mount Sinai, New York, NY, USA
| | - Gil D Rabinovici
- Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, Weill Institute for Neurosciences, University of California, San Francisco, CA, USA
| | - Stephen Salloway
- Department of Neurology, Alpert Medical School, Brown University, Providence, RI, USA
| | - Marc Suárez-Calvet
- Barcelonaβeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
| | | | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Chi Udeh-Momoh
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC, USA
| | - Joan Weiss
- US Department of Health and Human Services, Health Resources and Services Administration, Bureau of Health Workforce, Rockville, MD, USA
| | | | | | - John R Dwyer
- Global Alzheimer's Platform Foundation, Washington, DC, USA
| | - Drew Holzapfel
- The Global CEO Initiative on Alzheimer's Disease, Philadelphia, PA, USA
| | | | | | | | - Emily Scholler
- The Global CEO Initiative on Alzheimer's Disease, Philadelphia, PA, USA
| | - George Vradenburg
- Davos Alzheimer's Collaborative, Philadelphia, PA, USA
- UsAgainstAlzheimer's, Washington, DC, USA
| | | | | | | | | | | | | | - Soeren Mattke
- The USC Brain Health Observatory, University of Southern California, Los Angeles, CA, USA
| | | | | | | | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam University Medical Centers, Vrije Universitiet, Amsterdam, The Netherlands
| | | | | | - Michael W Weiner
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, CA, USA
- Department of Psychiatry, University of California, San Francisco, CA, USA
- Department of Neurology, University of California, San Francisco, CA, USA
| | | | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, Malmö, Sweden.
| |
Collapse
|
40
|
Arranz J, Zhu N, Rubio-Guerra S, Rodríguez-Baz Í, Ferrer R, Carmona-Iragui M, Barroeta I, Illán-Gala I, Santos-Santos M, Fortea J, Lleó A, Tondo M, Alcolea D. Diagnostic performance of plasma pTau 217, pTau 181, Aβ 1-42 and Aβ 1-40 in the LUMIPULSE automated platform for the detection of Alzheimer disease. Alzheimers Res Ther 2024; 16:139. [PMID: 38926773 PMCID: PMC11200993 DOI: 10.1186/s13195-024-01513-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/08/2023] [Accepted: 06/20/2024] [Indexed: 06/28/2024]
Abstract
BACKGROUND Recently developed blood markers for Alzheimer's disease (AD) detection have high accuracy but usually require ultra-sensitive analytic tools not commonly available in clinical laboratories, and their performance in clinical practice is unknown. METHODS We analyzed plasma samples from 290 consecutive participants that underwent lumbar puncture in routine clinical practice in a specialized memory clinic (66 cognitively unimpaired, 130 participants with mild cognitive impairment, and 94 with dementia). Participants were classified as amyloid positive (A +) or negative (A-) according to CSF Aβ1-42/Aβ1-40 ratio. Plasma pTau217, pTau181, Aβ1-42 and Aβ1-40 were measured in the fully-automated LUMIPULSE platform. We used linear regression to compare plasma biomarkers concentrations between A + and A- groups, evaluated Spearman's correlation between plasma and CSF and performed ROC analyses to assess their diagnostic accuracy to detect brain amyloidosis as determined by CSF Aβ1-42/Aβ1-40 ratio. We analyzed the concordance of pTau217 with CSF amyloidosis. RESULTS Plasma pTau217 and pTau181 concentration were higher in A + than A- while the plasma Aβ1-42/Aβ1-40 ratio was lower in A + compared to A-. pTau181 and the Aβ1-42/Aβ1-40 ratio showed moderate correlation between plasma and CSF (Rho = 0.66 and 0.69, respectively). The areas under the ROC curve to discriminate A + from A- participants were 0.94 (95% CI 0.92-0.97) for pTau217, and 0.88 (95% CI 0.84-0.92) for both pTau181 and Aβ1-42/Aβ1-40. Chronic kidney disease (CKD) was related to increased plasma biomarker concentrations, but ratios were less affected. Plasma pTau217 had the highest fold change (× 3.2) and showed high predictive capability in discriminating A + from A-, having 4-7% misclassification rate. The global accuracy of plasma pTau217 using a two-threshold approach was robust in symptomatic groups, exceeding 90%. CONCLUSION The evaluation of blood biomarkers on an automated platform exhibited high diagnostic accuracy for AD pathophysiology, and pTau217 showed excellent diagnostic accuracy to identify participants with AD in a consecutive sample representing the routine clinical practice in a specialized memory unit.
Collapse
Affiliation(s)
- Javier Arranz
- Sant Pau Memory Unit, Department of Neurology, IR SANT PAU, Hospital de La Santa Creu I Sant Pau, C/Sant Quintí 89, 08041, Barcelona, Spain
- Department of Neurology, Unidad Alzheimer-Down, IR SANT PAU, Hospital de La Santa Creu I Sant Pau; Barcelona Down Medical Center, Fundació Catalana Síndrome de Down, Barcelona, Spain
- Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Nuole Zhu
- Sant Pau Memory Unit, Department of Neurology, IR SANT PAU, Hospital de La Santa Creu I Sant Pau, C/Sant Quintí 89, 08041, Barcelona, Spain
- Universitat Autònoma de Barcelona, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Sara Rubio-Guerra
- Sant Pau Memory Unit, Department of Neurology, IR SANT PAU, Hospital de La Santa Creu I Sant Pau, C/Sant Quintí 89, 08041, Barcelona, Spain
- Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Íñigo Rodríguez-Baz
- Sant Pau Memory Unit, Department of Neurology, IR SANT PAU, Hospital de La Santa Creu I Sant Pau, C/Sant Quintí 89, 08041, Barcelona, Spain
- Department of Neurology, Unidad Alzheimer-Down, IR SANT PAU, Hospital de La Santa Creu I Sant Pau; Barcelona Down Medical Center, Fundació Catalana Síndrome de Down, Barcelona, Spain
| | - Rosa Ferrer
- Servei de Bioquímica I Biologia Molecular, IR SANT PAU, Hospital de La Santa Creu I Sant Pau, Universitat Autònoma de Barcelona, C/Sant Quintí 89, 08041, Barcelona, Spain
| | - María Carmona-Iragui
- Sant Pau Memory Unit, Department of Neurology, IR SANT PAU, Hospital de La Santa Creu I Sant Pau, C/Sant Quintí 89, 08041, Barcelona, Spain
- Department of Neurology, Unidad Alzheimer-Down, IR SANT PAU, Hospital de La Santa Creu I Sant Pau; Barcelona Down Medical Center, Fundació Catalana Síndrome de Down, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Isabel Barroeta
- Sant Pau Memory Unit, Department of Neurology, IR SANT PAU, Hospital de La Santa Creu I Sant Pau, C/Sant Quintí 89, 08041, Barcelona, Spain
- Department of Neurology, Unidad Alzheimer-Down, IR SANT PAU, Hospital de La Santa Creu I Sant Pau; Barcelona Down Medical Center, Fundació Catalana Síndrome de Down, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Ignacio Illán-Gala
- Sant Pau Memory Unit, Department of Neurology, IR SANT PAU, Hospital de La Santa Creu I Sant Pau, C/Sant Quintí 89, 08041, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Miguel Santos-Santos
- Sant Pau Memory Unit, Department of Neurology, IR SANT PAU, Hospital de La Santa Creu I Sant Pau, C/Sant Quintí 89, 08041, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Juan Fortea
- Sant Pau Memory Unit, Department of Neurology, IR SANT PAU, Hospital de La Santa Creu I Sant Pau, C/Sant Quintí 89, 08041, Barcelona, Spain
- Department of Neurology, Unidad Alzheimer-Down, IR SANT PAU, Hospital de La Santa Creu I Sant Pau; Barcelona Down Medical Center, Fundació Catalana Síndrome de Down, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Alberto Lleó
- Sant Pau Memory Unit, Department of Neurology, IR SANT PAU, Hospital de La Santa Creu I Sant Pau, C/Sant Quintí 89, 08041, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Mireia Tondo
- Servei de Bioquímica I Biologia Molecular, IR SANT PAU, Hospital de La Santa Creu I Sant Pau, Universitat Autònoma de Barcelona, C/Sant Quintí 89, 08041, Barcelona, Spain.
- Centro de Investigación Biomédica en Red en Diabetes y Enfermedades Metabólicas, CIBERDEM, Madrid, Spain.
| | - Daniel Alcolea
- Sant Pau Memory Unit, Department of Neurology, IR SANT PAU, Hospital de La Santa Creu I Sant Pau, C/Sant Quintí 89, 08041, Barcelona, Spain.
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain.
| |
Collapse
|
41
|
Ossenkoppele R, Salvadó G, Janelidze S, Binette AP, Bali D, Karlsson L, Palmqvist S, Mattsson-Carlgren N, Stomrud E, Therriault J, Rahmouni N, Rosa-Neto P, Coomans EM, van de Giessen E, van der Flier WM, Teunissen CE, Jonaitis EM, Johnson SC, Villeneuve S, Benzinger TL, Schindler SE, Bateman RJ, Doecke JD, Doré V, Feizpour A, Masters CL, Rowe C, Wiste HJ, Petersen RC, Jack CR, Hansson O. Prediction of future cognitive decline among cognitively unimpaired individuals using measures of soluble phosphorylated tau or tau tangle pathology. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.06.12.24308824. [PMID: 38947004 PMCID: PMC11213114 DOI: 10.1101/2024.06.12.24308824] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/02/2024]
Abstract
Plasma p-tau217 and Tau-PET are strong prognostic biomarkers in Alzheimer's disease (AD), but their relative performance in predicting future cognitive decline among cognitively unimpaired (CU) individuals is unclear. In this head-to-head comparison study including 9 cohorts and 1534 individuals, we found that plasma p-tau217 and medial temporal lobe Tau-PET signal showed similar associations with cognitive decline on a global cognitive composite test (R2 PET=0.32 vs R2 PLASMA=0.32, pdifference=0.812) and with progression to mild cognitive impairment (Hazard ratio[HR]PET=1.56[1.43-1.70] vs HRPLASMA=1.63[1.50-1.77], pdifference=0.627). Combined plasma and PET models were superior to the single biomarker models (R2=0.36, p<0.01). Furthermore, sequential selection using plasma p-tau217 and then Tau-PET reduced the number of participants required for a clinical trial by 94%, compared to a 75% reduction when using plasma p-tau217 alone. We conclude that plasma p-tau217 and Tau-PET showed similar performance for predicting future cognitive decline in CU individuals, and their sequential use (i.e., plasma p-tau217 followed by Tau-PET in a subset with high plasma p-tau217) is useful for screening in clinical trials in preclinical AD.
Collapse
Affiliation(s)
- Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Divya Bali
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Linda Karlsson
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, 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, Montreal, Quebec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Quebec, Canada
| | - Emma M. Coomans
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Elsmarieke van de Giessen
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Radiology & Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Wiesje M. van der Flier
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Charlotte E. Teunissen
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Neurochemistry Laboratory, Department of Laboratory Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Erin M. Jonaitis
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison
| | - Sterling C. Johnson
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin-Madison, Madison
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin-Madison, Madison
| | | | - Sylvia Villeneuve
- Douglas Mental Health University Institute, Centre for Studies on the Prevention of Alzheimer's Disease (StoP-AD), Montreal, Quebec, Canada
- Department of Psychiatry, McGill University, Montreal, Quebec, Canada
| | - Tammie L.S. Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington, Washington University School of Medicine, St. Louis, MO, USA
| | - Suzanne E. Schindler
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
| | - Randall J. Bateman
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, United States
- The Tracy Family SILQ Center, Washington University School of Medicine, St Louis, MO, United States
| | - James D. Doecke
- Australian eHealth Research Centre, CSIRO, Melbourne, Victoria, Australia
| | - Vincent Doré
- Australian eHealth Research Centre, CSIRO, Melbourne, Victoria, Australia
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia
| | - Azadeh Feizpour
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Colin L. Masters
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Christopher Rowe
- Department of Molecular Imaging & Therapy, Austin Health, Heidelberg, Victoria, Australia
- The Florey Institute of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Heather J. Wiste
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | | | | | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences in Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| |
Collapse
|
42
|
Antonioni A, Raho EM, Di Lorenzo F. Is blood pTau a reliable indicator of the CSF status? A narrative review. Neurol Sci 2024; 45:2471-2487. [PMID: 38129590 DOI: 10.1007/s10072-023-07258-x] [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: 10/03/2023] [Accepted: 12/03/2023] [Indexed: 12/23/2023]
Abstract
BACKGROUND The identification of biomarkers for the early diagnosis of Alzheimer's disease (AD) is a crucial goal of the current research. Blood biomarkers are less invasive, easier to obtain and achievable by a cheaper means than those on cerebrospinal fluid (CSF) and significantly more economic than functional neuroimaging investigations; thus, a great interest is focused on blood isoforms of the phosphorylated Tau protein (pTau), indicators of ongoing tau pathology (i.e. neurofibrillary tangles, NFTs, an AD neuropathological hallmark) in the central nervous system (CNS). However, current data often highlight discordant results about the ability of blood pTau to predict CSF status. OBJECTIVE We aim to synthesise the studies that compared pTau levels on CSF and blood to assess their correlation in AD continuum. METHODS We performed a narrative literature review using, first, MEDLINE (via PubMed) by means of MeSH terms, and then, we expanded the reults by means of Scopus and Web of Sciences to be as inclusive as possible. Finally, we added work following an expert opinion. Only papers presenting original data on pTau values on both blood and CSF were included. RESULTS The 33 included studies show an extreme heterogeneity in terms of pTau isoform (pTau181, 217 and 231), laboratory methods, diagnostic criteria and choice of comparison groups. Most studies evaluated plasma pTau181, while data on other isoforms and serum are scarcer. DISCUSSION Most papers identify a correlation between CSF and blood measurements. Furthermore, even when not specified, it is often possible to show an increase in blood pTau values as AD-related damage progresses in the AD continuum and higher values in AD than in other neurodegenerative diseases. Notably, plasma pTau231 seems the first biomarker to look for in the earliest and pre-clinical stages, quickly followed by pTau217 and, finally, by pTau181. CONCLUSIONS Our results encourage the use of blood pTau for the early identification of patients with AD continuum.
Collapse
Affiliation(s)
- Annibale Antonioni
- Unit of Clinical Neurology, Neurosciences and Rehabilitation Department, University of Ferrara, 44121, Ferrara, Italy
- Doctoral Program in Translational Neurosciences and Neurotechnologies, University of Ferrara, 44121, Ferrara, Italy
| | - Emanuela Maria Raho
- Unit of Clinical Neurology, Neurosciences and Rehabilitation Department, University of Ferrara, 44121, Ferrara, Italy
| | - Francesco Di Lorenzo
- Non Invasive Brain Stimulation Unit, Istituto Di Ricovero E Cura a Carattere Scientifico Santa Lucia, 00179, Rome, Italy.
| |
Collapse
|
43
|
Howe MD, Britton KJ, Joyce HE, Menard W, Emrani S, Kunicki ZJ, Faust MA, Dawson BC, Riddle MC, Huey ED, Janelidze S, Hansson O, Salloway SP. Clinical application of plasma P-tau217 to assess eligibility for amyloid-lowering immunotherapy in memory clinic patients with early Alzheimer's disease. RESEARCH SQUARE 2024:rs.3.rs-3755419. [PMID: 38853872 PMCID: PMC11160917 DOI: 10.21203/rs.3.rs-3755419/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: 06/11/2024]
Abstract
Background With the approval of disease-modifying treatments (DMTs) for early Alzheimer's disease (AD), there is an increased need for efficient and non-invasive detection methods for cerebral amyloid-β (Aβ) pathology. Current methods, including positron emission tomography (PET) and cerebrospinal fluid (CSF) analysis, are costly and invasive methods that may limit access to new treatments. Plasma tau phosphorylated at threonine-217 (P-tau217) presents a promising alternative, yet optimal cutoffs for treatment eligibility with DMTs like aducanumab require further investigation. This study evaluates the efficacy of one- and two-cutoff strategies for determining DMT eligibility at the Butler Hospital Memory & Aging Program (MAP). Methods In this retrospective, cross-sectional diagnostic cohort study, we first developed P-tau217 cutoffs using site-specific training data and BioFINDER-2, which were then tested in potential DMT candidates from Butler MAP (total n = 150). ROC analysis was used to calculate the area under the curve (AUC) and accuracy of P-tau217 interpretation strategies, using Aβ-PET/CSF testing as the standard of truth. Results Potential DMT candidates at Butler MAP (n = 50), primarily diagnosed with mild cognitive impairment (n = 29 [58%]) or mild dementia (21 [42%]), were predominantly Aβ-positive (38 [76%]), and half (25 [50%]) were subsequently treated with aducanumab. Elevated P-tau217 predicted cerebral Aβ positivity in potential DMT candidates (AUC = 0.97 [0.92-1]), with diagnostic accuracy ranging from 0.88 (0.76-0.95, p = 0.028) to 0.96 (0.86-1, p < .001). When using site-specific cutoffs, a subset of DMT candidates (10%) exhibited borderline P-tau217 (between 0.273 and 0.399 pg/mL) that would have potentially required from confirmatory testing. Conclusions This study, which included participants treated with aducanumab, confirms the utility of one- and two-cutoff strategies for interpreting plasma P-tau217 in assessing DMT eligibility. Using P-tau217 could potentially replace more invasive diagnostic methods, and all aducanumab-treated participants would have been deemed eligible based on P-tau217. However, false positives remain a concern, particularly when applying externally derived cutoffs that exhibited lower specificity which could have led to inappropriate treatment of Aβ-negative participants. Future research should focus on prospective validation of P-tau217 cutoffs to enhance their generalizability and inform standardized treatment decision-making across diverse populations.
Collapse
|
44
|
Mendes AJ, Ribaldi F, Lathuiliere A, Ashton NJ, Zetterberg H, Abramowicz M, Scheffler M, Assal F, Garibotto V, Blennow K, Frisoni GB. Comparison of plasma and neuroimaging biomarkers to predict cognitive decline in non-demented memory clinic patients. Alzheimers Res Ther 2024; 16:110. [PMID: 38755703 PMCID: PMC11097559 DOI: 10.1186/s13195-024-01478-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Accepted: 05/07/2024] [Indexed: 05/18/2024]
Abstract
BACKGROUND Plasma biomarkers of Alzheimer's disease (AD) pathology, neurodegeneration, and neuroinflammation are ideally suited for secondary prevention programs in self-sufficient persons at-risk of dementia. Plasma biomarkers have been shown to be highly correlated with traditional imaging biomarkers. However, their comparative predictive value versus traditional AD biomarkers is still unclear in cognitively unimpaired (CU) subjects and with mild cognitive impairment (MCI). METHODS Plasma (Aβ42/40, p-tau181, p-tau231, NfL, and GFAP) and neuroimaging (hippocampal volume, centiloid of amyloid-PET, and tau-SUVR of tau-PET) biomarkers were assessed at baseline in 218 non-demented subjects (CU = 140; MCI = 78) from the Geneva Memory Center. Global cognition (MMSE) was evaluated at baseline and at follow-ups up to 5.7 years. We used linear mixed-effects models and Cox proportional-hazards regression to assess the association between biomarkers and cognitive decline. Lastly, sample size calculations using the linear mixed-effects models were performed on subjects positive for amyloid-PET combined with tau-PET and plasma biomarker positivity. RESULTS Cognitive decline was significantly predicted in MCI by baseline plasma NfL (β=-0.55), GFAP (β=-0.36), hippocampal volume (β = 0.44), centiloid (β=-0.38), and tau-SUVR (β=-0.66) (all p < 0.05). Subgroup analysis with amyloid-positive MCI participants also showed that only NfL and GFAP were the only significant predictors of cognitive decline among plasma biomarkers. Overall, NfL and tau-SUVR showed the highest prognostic values (hazard ratios of 7.3 and 5.9). Lastly, we demonstrated that adding NfL to the inclusion criteria could reduce the sample sizes of future AD clinical trials by up to one-fourth in subjects with amyloid-PET positivity or by half in subjects with amyloid-PET and tau-PET positivity. CONCLUSIONS Plasma NfL and GFAP predict cognitive decline in a similar manner to traditional imaging techniques in amyloid-positive MCI patients. Hence, even though they are non-specific biomarkers of AD, both can be implemented in memory clinic workups as important prognostic biomarkers. Likewise, future clinical trials might employ plasma biomarkers as additional inclusion criteria to stratify patients at higher risk of cognitive decline to reduce sample sizes and enhance effectiveness.
Collapse
Affiliation(s)
- Augusto J Mendes
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland.
- Geneva Memory Center, Department of Rehabilitation and Geriatrics,, Geneva University Hospitals, Geneva, Switzerland.
| | - Federica Ribaldi
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics,, Geneva University Hospitals, Geneva, Switzerland
| | - Aurelien Lathuiliere
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics,, Geneva University Hospitals, Geneva, Switzerland
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Clinical Neuroscience Institute, London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
- Wisconsin Alzheimer?s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Marc Abramowicz
- Genetic Medicine, Diagnostics Dept, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Max Scheffler
- Division of Radiology, Geneva University Hospitals, Geneva, Switzerland
| | - Frédéric Assal
- Division of Neurology, Department of Clinical Neurosciences, Faculty of Medicine, Geneva University Hospitals, University of Geneva, Geneva, Switzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Faculty of Medicine, Geneva University Neurocenter, University of Geneva, Geneva, Switzerland
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
- CIBM Center for Biomedical Imaging, Geneva, Switzerland
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE), University of Geneva, Geneva, Switzerland
- Geneva Memory Center, Department of Rehabilitation and Geriatrics,, Geneva University Hospitals, Geneva, Switzerland
| |
Collapse
|
45
|
Zeng X, Chen Y, Sehrawat A, Lee J, Lafferty TK, Kofler J, Berman SB, Sweet RA, Tudorascu DL, Klunk WE, Ikonomovic MD, Pfister A, Zetterberg H, Snitz BE, Cohen AD, Villemagne VL, Pascoal TA, Kamboh ML, Lopez OI, Blennow K, Karikari TK. Alzheimer blood biomarkers: practical guidelines for study design, sample collection, processing, biobanking, measurement and result reporting. Mol Neurodegener 2024; 19:40. [PMID: 38750570 PMCID: PMC11095038 DOI: 10.1186/s13024-024-00711-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2023] [Accepted: 02/13/2024] [Indexed: 05/19/2024] Open
Abstract
Alzheimer's disease (AD), the most common form of dementia, remains challenging to understand and treat despite decades of research and clinical investigation. This might be partly due to a lack of widely available and cost-effective modalities for diagnosis and prognosis. Recently, the blood-based AD biomarker field has seen significant progress driven by technological advances, mainly improved analytical sensitivity and precision of the assays and measurement platforms. Several blood-based biomarkers have shown high potential for accurately detecting AD pathophysiology. As a result, there has been considerable interest in applying these biomarkers for diagnosis and prognosis, as surrogate metrics to investigate the impact of various covariates on AD pathophysiology and to accelerate AD therapeutic trials and monitor treatment effects. However, the lack of standardization of how blood samples and collected, processed, stored analyzed and reported can affect the reproducibility of these biomarker measurements, potentially hindering progress toward their widespread use in clinical and research settings. To help address these issues, we provide fundamental guidelines developed according to recent research findings on the impact of sample handling on blood biomarker measurements. These guidelines cover important considerations including study design, blood collection, blood processing, biobanking, biomarker measurement, and result reporting. Furthermore, the proposed guidelines include best practices for appropriate blood handling procedures for genetic and ribonucleic acid analyses. While we focus on the key blood-based AD biomarkers for the AT(N) criteria (e.g., amyloid-beta [Aβ]40, Aβ42, Aβ42/40 ratio, total-tau, phosphorylated-tau, neurofilament light chain, brain-derived tau and glial fibrillary acidic protein), we anticipate that these guidelines will generally be applicable to other types of blood biomarkers. We also anticipate that these guidelines will assist investigators in planning and executing biomarker research, enabling harmonization of sample handling to improve comparability across studies.
Collapse
Affiliation(s)
- Xuemei Zeng
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Yijun Chen
- Department of Chemistry, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Anuradha Sehrawat
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Jihui Lee
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Tara K Lafferty
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Julia Kofler
- Department of Pathology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Sarah B Berman
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Robert A Sweet
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Dana L Tudorascu
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - William E Klunk
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Milos D Ikonomovic
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
- Geriatric Research Education and Clinical Center, VA Pittsburgh HS, Pittsburgh, PA, USA
| | - Anna Pfister
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
- Department of Medicine, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, USA
| | - Beth E Snitz
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Anne D Cohen
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Victor L Villemagne
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
| | - Tharick A Pascoal
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - M. llyas Kamboh
- Department of Human Genetics, School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Oscar I Lopez
- Department of Neurology, School of Medicine, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Thomas K Karikari
- Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA.
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Mölndal, Sweden.
| |
Collapse
|
46
|
Pilotto A, Quaresima V, Trasciatti C, Tolassi C, Bertoli D, Mordenti C, Galli A, Rizzardi A, Caratozzolo S, Zancanaro A, Contador J, Hansson O, Palmqvist S, Santis GD, Zetterberg H, Blennow K, Brugnoni D, Suárez-Calvet M, Ashton NJ, Padovani A. Plasma p-tau217 in Alzheimer's disease: Lumipulse and ALZpath SIMOA head-to-head comparison. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.02.24306780. [PMID: 38746261 PMCID: PMC11092737 DOI: 10.1101/2024.05.02.24306780] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/16/2024]
Abstract
Background Plasma phosphorylated-tau217 (p-tau217) has been shown to be one of the most accurate diagnostic markers for Alzheimer's disease (AD). No studies have compared the clinical performance of p-tau217 as assessed by the fully automated Lumipulse and SIMOA ALZpath p-tau217. Aim To evaluate the diagnostic accuracy of Lumipulse and SIMOA plasma p-tau217 assays for AD. Methods The study included 392 participants, 162 with AD, 70 with other neurodegenerative diseases (NDD) with CSF biomarkers and 160 healthy controls. Plasma p-tau217 levels were measured using the Lumipulse and ALZpath SIMOA assays. The ability of p-tau217 assessed by both techniques to discriminate AD from NDD and controls was investigated using ROC analyses. Results Both techniques showed high internal consistency of p-tau217 with similar correlation with CSF p-tau181 levels. In head-to-head comparison, Lumipulse and SIMOA showed similar diagnostic accuracy for differentiating AD from NDD (area under the curve [AUC] 0.952, 95%CI 0.927-0.978 vs 0.955, 95%CI 0.928-0.982, respectively) and HC (AUC 0.938, 95%CI 0.910-0.966 and 0.937, 95% CI0.907-0.967 for both assays). Conclusions This study demonstrated the high precision and diagnostic accuracy of p-tau217 for the clinical diagnosis of Alzheimer's disease using either fully automated or semi-automated techniques.
Collapse
|
47
|
Salvadó G, Horie K, Barthélemy NR, Vogel JW, Pichet Binette A, Chen CD, Aschenbrenner AJ, Gordon BA, Benzinger TLS, Holtzman DM, Morris JC, Palmqvist S, Stomrud E, Janelidze S, Ossenkoppele R, Schindler SE, Bateman RJ, Hansson O. Disease staging of Alzheimer's disease using a CSF-based biomarker model. NATURE AGING 2024; 4:694-708. [PMID: 38514824 PMCID: PMC11108782 DOI: 10.1038/s43587-024-00599-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/03/2023] [Accepted: 02/20/2024] [Indexed: 03/23/2024]
Abstract
Biological staging of individuals with Alzheimer's disease (AD) may improve diagnostic and prognostic workup of dementia in clinical practice and the design of clinical trials. In this study, we used the Subtype and Stage Inference (SuStaIn) algorithm to establish a robust biological staging model for AD using cerebrospinal fluid (CSF) biomarkers. Our analysis involved 426 participants from BioFINDER-2 and was validated in 222 participants from the Knight Alzheimer Disease Research Center cohort. SuStaIn identified a singular biomarker sequence and revealed that five CSF biomarkers effectively constituted a reliable staging model (ordered: Aβ42/40, pT217/T217, pT205/T205, MTBR-tau243 and non-phosphorylated mid-region tau). The CSF stages (0-5) demonstrated a correlation with increased abnormalities in other AD-related biomarkers, such as Aβ-PET and tau-PET, and aligned with longitudinal biomarker changes reflective of AD progression. Higher CSF stages at baseline were associated with an elevated hazard ratio of clinical decline. This study highlights a common molecular pathway underlying AD pathophysiology across all patients, suggesting that a single CSF collection can accurately indicate the presence of AD pathologies and characterize the stage of disease progression. The proposed staging model has implications for enhancing diagnostic and prognostic assessments in both clinical practice and the design of clinical trials.
Collapse
Affiliation(s)
- Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.
| | - Kanta Horie
- Tracy Family Stable Isotope Labeling Quantitation (SILQ) Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Eisai, Inc., Nutley, NJ, USA
| | - Nicolas R Barthélemy
- Tracy Family Stable Isotope Labeling Quantitation (SILQ) Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Jacob W Vogel
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Department of Clinical Science, Malmö, SciLifeLab, Lund University, Lund, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Charles D Chen
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Andrew J Aschenbrenner
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Brian A Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Tammie L S Benzinger
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - David M Holtzman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - John C Morris
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Randall J Bateman
- Tracy Family Stable Isotope Labeling Quantitation (SILQ) Center, Washington University School of Medicine, St. Louis, MO, USA
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, Malmö, Sweden.
| |
Collapse
|
48
|
Meyer MR, Kirmess KM, Eastwood S, Wente‐Roth TL, Irvin F, Holubasch MS, Venkatesh V, Fogelman I, Monane M, Hanna L, Rabinovici GD, Siegel BA, Whitmer RA, Apgar C, Bateman RJ, Holtzman DM, Irizarry M, Verbel D, Sachdev P, Ito S, Contois J, Yarasheski KE, Braunstein JB, Verghese PB, West T. Clinical validation of the PrecivityAD2 blood test: A mass spectrometry-based test with algorithm combining %p-tau217 and Aβ42/40 ratio to identify presence of brain amyloid. Alzheimers Dement 2024; 20:3179-3192. [PMID: 38491912 PMCID: PMC11095426 DOI: 10.1002/alz.13764] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 01/25/2024] [Accepted: 01/31/2024] [Indexed: 03/18/2024]
Abstract
BACKGROUND With the availability of disease-modifying therapies for Alzheimer's disease (AD), it is important for clinicians to have tests to aid in AD diagnosis, especially when the presence of amyloid pathology is a criterion for receiving treatment. METHODS High-throughput, mass spectrometry-based assays were used to measure %p-tau217 and amyloid beta (Aβ)42/40 ratio in blood samples from 583 individuals with suspected AD (53% positron emission tomography [PET] positive by Centiloid > 25). An algorithm (PrecivityAD2 test) was developed using these plasma biomarkers to identify brain amyloidosis by PET. RESULTS The area under the receiver operating characteristic curve (AUC-ROC) for %p-tau217 (0.94) was statistically significantly higher than that for p-tau217 concentration (0.91). The AUC-ROC for the PrecivityAD2 test output, the Amyloid Probability Score 2, was 0.94, yielding 88% agreement with amyloid PET. Diagnostic performance of the APS2 was similar by ethnicity, sex, age, and apoE4 status. DISCUSSION The PrecivityAD2 blood test showed strong clinical validity, with excellent agreement with brain amyloidosis by PET.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | | | - Lucy Hanna
- Center for Statistical SciencesBrown University School of Public HealthProvidenceRhode IslandUSA
| | | | | | | | - Charles Apgar
- American College of RadiologyPhiladelphiaPennsylvaniaUSA
| | | | | | | | | | | | | | | | | | | | | | - Tim West
- C2N DiagnosticsSt. LouisMissouriUSA
| |
Collapse
|
49
|
Oosthoek M, Vermunt L, de Wilde A, Bongers B, Antwi-Berko D, Scheltens P, van Bokhoven P, Vijverberg EGB, Teunissen CE. Utilization of fluid-based biomarkers as endpoints in disease-modifying clinical trials for Alzheimer's disease: a systematic review. Alzheimers Res Ther 2024; 16:93. [PMID: 38678292 PMCID: PMC11055304 DOI: 10.1186/s13195-024-01456-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2023] [Accepted: 04/12/2024] [Indexed: 04/29/2024]
Abstract
BACKGROUND Clinical trials in Alzheimer's disease (AD) had high failure rates for several reasons, including the lack of biological endpoints. Fluid-based biomarkers may present a solution to measure biologically relevant endpoints. It is currently unclear to what extent fluid-based biomarkers are applied to support drug development. METHODS We systematically reviewed 272 trials (clinicaltrials.gov) with disease-modifying therapies starting between 01-01-2017 and 01-01-2024 and identified which CSF and/or blood-based biomarker endpoints were used per purpose and trial type. RESULTS We found that 44% (N = 121) of the trials employed fluid-based biomarker endpoints among which the CSF ATN biomarkers (Aβ (42/40), p/tTau) were used most frequently. In blood, inflammatory cytokines, NFL, and pTau were most frequently employed. Blood- and CSF-based biomarkers were used approximately equally. Target engagement biomarkers were used in 26% (N = 72) of the trials, mainly in drugs targeting inflammation and amyloid. Lack of target engagement markers is most prominent in synaptic plasticity/neuroprotection, neurotransmitter receptor, vasculature, epigenetic regulators, proteostasis and, gut-brain axis targeting drugs. Positive biomarker results did not always translate to cognitive effects, most commonly the small significant reductions in CSF tau isoforms that were seen following anti-Tau treatments. On the other hand, the positive anti-amyloid trials results on cognitive function were supported by clear effect in most fluid markers. CONCLUSIONS As the field moves towards primary prevention, we expect an increase in the use of fluid-based biomarkers to determine disease modification. Use of blood-based biomarkers will rapidly increase, but CSF markers remain important to determine brain-specific treatment effects. With improving techniques, new biomarkers can be found to diversify the possibilities in measuring treatment effects and target engagement. It remains important to interpret biomarker results in the context of the trial and be aware of the performance of the biomarker. Diversifying biomarkers could aid in the development of surrogacy biomarkers for different drug targets.
Collapse
Affiliation(s)
- Marlies Oosthoek
- Department of Laboratory Medicine, Neurochemistry Laboratory, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands.
| | - Lisa Vermunt
- Department of Laboratory Medicine, Neurochemistry Laboratory, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Arno de Wilde
- EQT Life Sciences, Johannes Vermeersplein 9, 1071 DV, Amsterdam, The Netherlands
| | - Bram Bongers
- Department of Laboratory Medicine, Neurochemistry Laboratory, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Daniel Antwi-Berko
- Department of Laboratory Medicine, Neurochemistry Laboratory, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Philip Scheltens
- EQT Life Sciences, Johannes Vermeersplein 9, 1071 DV, Amsterdam, The Netherlands
- Alzheimer Center, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | | | - Everard G B Vijverberg
- Alzheimer Center, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Department of Laboratory Medicine, Neurochemistry Laboratory, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1117, 1081 HV, Amsterdam, The Netherlands
| |
Collapse
|
50
|
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 PMCID: PMC11484593 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.
Collapse
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
| |
Collapse
|