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Niimi Y, Janelidze S, Sato K, Tomita N, Tsukamoto T, Kato T, Yoshiyama K, Kowa H, Iwata A, Ihara R, Suzuki K, Kasuga K, Ikeuchi T, Ishii K, Ito K, Nakamura A, Senda M, Day TA, Burnham SC, Iaccarino L, Pontecorvo MJ, Hansson O, Iwatsubo T. Combining plasma Aβ and p-tau217 improves detection of brain amyloid in non-demented elderly. Alzheimers Res Ther 2024; 16:115. [PMID: 38778353 PMCID: PMC11112892 DOI: 10.1186/s13195-024-01469-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: 03/12/2024] [Accepted: 04/29/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND Maximizing the efficiency to screen amyloid-positive individuals in asymptomatic and non-demented aged population using blood-based biomarkers is essential for future success of clinical trials in the early stage of Alzheimer's disease (AD). In this study, we elucidate the utility of combination of plasma amyloid-β (Aβ)-related biomarkers and tau phosphorylated at threonine 217 (p-tau217) to predict abnormal Aβ-positron emission tomography (PET) in the preclinical and prodromal AD. METHODS We designed the cross-sectional study including two ethnically distinct cohorts, the Japanese trial-ready cohort for preclinica and prodromal AD (J-TRC) and the Swedish BioFINDER study. J-TRC included 474 non-demented individuals (CDR 0: 331, CDR 0.5: 143). Participants underwent plasma Aβ and p-tau217 assessments, and Aβ-PET imaging. Findings in J-TRC were replicated in the BioFINDER cohort including 177 participants (cognitively unimpaired: 114, mild cognitive impairment: 63). In both cohorts, plasma Aβ(1-42) (Aβ42) and Aβ(1-40) (Aβ40) were measured using immunoprecipitation-MALDI TOF mass spectrometry (Shimadzu), and p-tau217 was measured with an immunoassay on the Meso Scale Discovery platform (Eli Lilly). RESULTS Aβ-PET was abnormal in 81 participants from J-TRC and 71 participants from BioFINDER. Plasma Aβ42/Aβ40 ratio and p-tau217 individually showed moderate to high accuracies when detecting abnormal Aβ-PET scans, which were improved by combining plasma biomarkers and by including age, sex and APOE genotype in the models. In J-TRC, the highest AUCs were observed for the models combining p-tau217/Aβ42 ratio, APOE, age, sex in the whole cohort (AUC = 0.936), combining p-tau217, Aβ42/Aβ40 ratio, APOE, age, sex in the CDR 0 group (AUC = 0.948), and combining p-tau217/Aβ42 ratio, APOE, age, sex in the CDR 0.5 group (AUC = 0.955), respectively. Each subgroup results were replicated in BioFINDER, where the highest AUCs were seen for models combining p-tau217, Aβ42/40 ratio, APOE, age, sex in cognitively unimpaired (AUC = 0.938), and p-tau217/Aβ42 ratio, APOE, age, sex in mild cognitive impairment (AUC = 0.914). CONCLUSIONS Combination of plasma Aβ-related biomarkers and p-tau217 exhibits high performance when predicting Aβ-PET positivity. Adding basic clinical information (i.e., age, sex, APOE ε genotype) improved the prediction in preclinical AD, but not in prodromal AD. Combination of Aβ-related biomarkers and p-tau217 could be highly useful for pre-screening of participants in clinical trials of preclinical and prodromal AD.
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Affiliation(s)
- Yoshiki Niimi
- Unit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Malmö, Sweden
| | - Kenichiro Sato
- Unit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan
- Department of Neuropathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Naoki Tomita
- Department of Aging Research and Geriatric Medicine, Institute of Development, Aging and Cancer, Tohoku University, Sendai, Japan
- Department of Geriatric Medicine and Neuroimaging, Tohoku University Hospital, Sendai, Japan
| | - Tadashi Tsukamoto
- Department of Neurology, National Center of Neurology and Psychiatry, Tokyo, Japan
| | - Takashi Kato
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Aichi, Japan
| | - Kenji Yoshiyama
- Department of Psychiatry, Osaka University Graduate School of Medicine, Osaka, Japan
| | - Hisatomo Kowa
- Graduate School of Health Sciences, Kobe University, Hyogo, Japan
| | - Atsushi Iwata
- Department of Neurology, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
| | - Ryoko Ihara
- Department of Neurology, Tokyo Metropolitan Institute for Geriatrics and Gerontology, Tokyo, Japan
| | - Kazushi Suzuki
- Division of Neurology, Internal Medicine, National Defense Medical College, Saitama, Japan
| | - Kensaku Kasuga
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Takeshi Ikeuchi
- Department of Molecular Genetics, Brain Research Institute, Niigata University, Niigata, Japan
| | - Kenji Ishii
- Integrated Research Initiative for Living Well With Dementia, Tokyo Metropolitan Institute for Geriatric and Gerontology, Tokyo, Japan
| | - Kengo Ito
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Aichi, Japan
| | - Akinori Nakamura
- Department of Clinical and Experimental Neuroimaging, National Center for Geriatrics and Gerontology, Aichi, Japan
| | - Michio Senda
- Department of Molecular Imaging Research, Kobe City Medical Center General Hospital, Hyogo, Japan
| | | | | | | | | | - Oskar Hansson
- Unit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan.
- Memory Clinic, Skåne University Hospital, Lund, Sweden.
| | - Takeshi Iwatsubo
- Unit for Early and Exploratory Clinical Development, The University of Tokyo Hospital, 7-3-1 Hongo, Bunkyo-Ku, Tokyo, 113-0033, Japan.
- Department of Neuropathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.
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Dark HE, An Y, Duggan MR, Joynes C, Davatzikos C, Erus G, Lewis A, Moghekar AR, Resnick SM, Walker KA. Alzheimer's and neurodegenerative disease biomarkers in blood predict brain atrophy and cognitive decline. Alzheimers Res Ther 2024; 16:94. [PMID: 38689358 PMCID: PMC11059745 DOI: 10.1186/s13195-024-01459-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2023] [Accepted: 04/16/2024] [Indexed: 05/02/2024]
Abstract
BACKGROUND Although blood-based biomarkers have been identified as cost-effective and scalable alternatives to PET and CSF markers of neurodegenerative disease, little is known about how these biomarkers predict future brain atrophy and cognitive decline in cognitively unimpaired individuals. Using data from the Baltimore Longitudinal Study of Aging (BLSA), we examined whether plasma biomarkers of Alzheimer's disease (AD) pathology (amyloid-β [Aβ42/40], phosphorylated tau [pTau-181]), astrogliosis (glial fibrillary acidic protein [GFAP]), and neuronal injury (neurofilament light chain [NfL]) were associated with longitudinal brain volume loss and cognitive decline. Additionally, we determined whether sex, APOEε4 status, and plasma amyloid-β status modified these associations. METHODS Plasma biomarkers were measured using Quanterix SIMOA assays. Regional brain volumes were measured by 3T MRI, and a battery of neuropsychological tests assessed five cognitive domains. Linear mixed effects models adjusted for demographic factors, kidney function, and intracranial volume (MRI analyses) were completed to relate baseline plasma biomarkers to baseline and longitudinal brain volume and cognitive performance. RESULTS Brain volume analyses included 622 participants (mean age ± SD: 70.9 ± 10.2) with an average of 3.3 MRI scans over 4.7 years. Cognitive performance analyses included 674 participants (mean age ± SD: 71.2 ± 10.0) with an average of 3.9 cognitive assessments over 5.7 years. Higher baseline pTau-181 was associated with steeper declines in total gray matter volume and steeper regional declines in several medial temporal regions, whereas higher baseline GFAP was associated with greater longitudinal increases in ventricular volume. Baseline Aβ42/40 and NfL levels were not associated with changes in brain volume. Lower baseline Aβ42/40 (higher Aβ burden) was associated with a faster decline in verbal memory and visuospatial performance, whereas higher baseline GFAP was associated with a faster decline in verbal fluency. Results were generally consistent across sex and APOEε4 status. However, the associations of higher pTau-181 with increasing ventricular volume and memory declines were significantly stronger among individuals with higher Aβ burden, as was the association of higher GFAP with memory decline. CONCLUSIONS Among cognitively unimpaired older adults, plasma biomarkers of AD pathology (pTau-181) and astrogliosis (GFAP), but not neuronal injury (NfL), serve as markers of future brain atrophy and cognitive decline.
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Affiliation(s)
- Heather E Dark
- Laboratory of Behavioral Neuroscience, National Institute On Aging, NIH BRC BG RM 04B311, 251 Bayview Blvd, Baltimore, MD, 21224, USA.
| | - Yang An
- Laboratory of Behavioral Neuroscience, National Institute On Aging, NIH BRC BG RM 04B311, 251 Bayview Blvd, Baltimore, MD, 21224, USA
| | - Michael R Duggan
- Laboratory of Behavioral Neuroscience, National Institute On Aging, NIH BRC BG RM 04B311, 251 Bayview Blvd, Baltimore, MD, 21224, USA
| | - Cassandra Joynes
- Laboratory of Behavioral Neuroscience, National Institute On Aging, NIH BRC BG RM 04B311, 251 Bayview Blvd, Baltimore, MD, 21224, USA
| | | | - Guray Erus
- Department of Radiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Alexandria Lewis
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Abhay R Moghekar
- Department of Neurology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Susan M Resnick
- Laboratory of Behavioral Neuroscience, National Institute On Aging, NIH BRC BG RM 04B311, 251 Bayview Blvd, Baltimore, MD, 21224, USA
| | - Keenan A Walker
- Laboratory of Behavioral Neuroscience, National Institute On Aging, NIH BRC BG RM 04B311, 251 Bayview Blvd, Baltimore, MD, 21224, USA.
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Jarek DJ, Mizerka H, Nuszkiewicz J, Szewczyk-Golec K. Evaluating p-tau217 and p-tau231 as Biomarkers for Early Diagnosis and Differentiation of Alzheimer's Disease: A Narrative Review. Biomedicines 2024; 12:786. [PMID: 38672142 PMCID: PMC11048667 DOI: 10.3390/biomedicines12040786] [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: 02/15/2024] [Revised: 03/26/2024] [Accepted: 03/30/2024] [Indexed: 04/28/2024] Open
Abstract
The escalating prevalence of Alzheimer's disease (AD) highlights the urgent need to develop reliable biomarkers for early diagnosis and intervention. AD is characterized by the pathological accumulation of amyloid-beta plaques and tau neurofibrillary tangles. Phosphorylated tau (p-tau) proteins, particularly p-tau217 and p-tau231, have been identified as promising biomarker candidates to differentiate the disease progression from preclinical stages. This narrative review is devoted to a critical evaluation of the diagnostic accuracy, sensitivity, and specificity of p-tau217 and p-tau231 levels in the detection of AD, measured in plasma, serum, and cerebrospinal fluid, compared to established biomarkers. Additionally, the efficacy of these markers in distinguishing AD from other neurodegenerative disorders is examined. The significant advances offered by p-tau217 and p-tau231 in AD diagnostics are highlighted, demonstrating their unique utility in early detection and differential diagnosis. This comprehensive analysis not only confirms the excellent diagnostic capabilities of these markers, but also deepens the understanding of the molecular dynamics of AD, contributing to the broader scientific discourse on neurodegenerative diseases. This review is aimed to provide key information for researchers and clinicians across disciplines, filling interdisciplinary gaps and highlighting the role of p-tau proteins in revolutionizing AD research and clinical practice.
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Affiliation(s)
- Dorian Julian Jarek
- Student Research Club of Medical Biology and Biochemistry, Department of Medical Biology and Biochemistry, Faculty of Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 85-092 Bydgoszcz, Poland;
| | - Hubert Mizerka
- Student Research Club of Medical Biology and Biochemistry, Department of Medical Biology and Biochemistry, Faculty of Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 85-092 Bydgoszcz, Poland;
| | - Jarosław Nuszkiewicz
- Department of Medical Biology and Biochemistry, Faculty of Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 85-092 Bydgoszcz, Poland;
| | - Karolina Szewczyk-Golec
- Department of Medical Biology and Biochemistry, Faculty of Medicine, Ludwik Rydygier Collegium Medicum in Bydgoszcz, Nicolaus Copernicus University in Toruń, 85-092 Bydgoszcz, Poland;
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Barthélemy NR, Salvadó G, Schindler SE, He Y, Janelidze S, Collij LE, Saef B, Henson RL, Chen CD, Gordon BA, Li Y, La Joie R, Benzinger TLS, Morris JC, Mattsson-Carlgren N, Palmqvist S, Ossenkoppele R, Rabinovici GD, Stomrud E, Bateman RJ, Hansson O. Highly accurate blood test for Alzheimer's disease is similar or superior to clinical cerebrospinal fluid tests. Nat Med 2024; 30:1085-1095. [PMID: 38382645 PMCID: PMC11031399 DOI: 10.1038/s41591-024-02869-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: 10/24/2023] [Accepted: 02/12/2024] [Indexed: 02/23/2024]
Abstract
With the emergence of Alzheimer's disease (AD) disease-modifying therapies, identifying patients who could benefit from these treatments becomes critical. In this study, we evaluated whether a precise blood test could perform as well as established cerebrospinal fluid (CSF) tests in detecting amyloid-β (Aβ) plaques and tau tangles. Plasma %p-tau217 (ratio of phosporylated-tau217 to non-phosphorylated tau) was analyzed by mass spectrometry in the Swedish BioFINDER-2 cohort (n = 1,422) and the US Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC) cohort (n = 337). Matched CSF samples were analyzed with clinically used and FDA-approved automated immunoassays for Aβ42/40 and p-tau181/Aβ42. The primary and secondary outcomes were detection of brain Aβ or tau pathology, respectively, using positron emission tomography (PET) imaging as the reference standard. Main analyses were focused on individuals with cognitive impairment (mild cognitive impairment and mild dementia), which is the target population for available disease-modifying treatments. Plasma %p-tau217 was clinically equivalent to FDA-approved CSF tests in classifying Aβ PET status, with an area under the curve (AUC) for both between 0.95 and 0.97. Plasma %p-tau217 was generally superior to CSF tests in classification of tau-PET with AUCs of 0.95-0.98. In cognitively impaired subcohorts (BioFINDER-2: n = 720; Knight ADRC: n = 50), plasma %p-tau217 had an accuracy, a positive predictive value and a negative predictive value of 89-90% for Aβ PET and 87-88% for tau PET status, which was clinically equivalent to CSF tests, further improving to 95% using a two-cutoffs approach. Blood plasma %p-tau217 demonstrated performance that was clinically equivalent or superior to clinically used FDA-approved CSF tests in the detection of AD pathology. Use of high-performance blood tests in clinical practice can improve access to accurate AD diagnosis and AD-specific treatments.
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Affiliation(s)
- Nicolas R Barthélemy
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Tracy Family Stable Isotope Labeling Quantitation (SILQ) Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University School of Medicine, St. Louis, MO, USA
| | - Yingxin He
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Tracy Family Stable Isotope Labeling Quantitation (SILQ) Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
| | - Lyduine E Collij
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
| | - Benjamin Saef
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Rachel L Henson
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
| | - Charles D Chen
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Brian A Gordon
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Yan Li
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- Division of Biostatistics, Washington University in St. Louis, St. Louis, MO, USA
| | - Renaud La Joie
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
| | - Tammie L S Benzinger
- Department of Radiology, 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 (Knight ADRC), Washington University School of Medicine, St. Louis, MO, USA
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden
- Amsterdam Neuroscience, Brain Imaging, Amsterdam, The Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, location VUmc, Amsterdam, The Netherlands
| | - Gil D Rabinovici
- Department of Neurology, Memory and Aging Center, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, USA
| | - Erik Stomrud
- 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 School of Medicine, St. Louis, MO, USA.
- Tracy Family Stable Isotope Labeling Quantitation (SILQ) Center, Washington University School of Medicine, St. Louis, MO, USA.
- Charles F. and Joanne Knight Alzheimer Disease Research Center (Knight ADRC), Washington University School of Medicine, St. Louis, MO, 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.
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Sarto J, Esteller-Gauxax D, Tort-Merino A, Guillén N, Pérez-Millan A, Falgàs N, Borrego-Écija S, Fernández-Villullas G, Bosch B, Juncà-Parella J, Antonell A, Naranjo L, Ruiz-García R, Augé JM, Sánchez-Valle R, Lladó A, Balasa M. Impact of demographics and comorbid conditions on plasma biomarkers concentrations and their diagnostic accuracy in a memory clinic cohort. J Neurol 2024; 271:1973-1984. [PMID: 38151575 DOI: 10.1007/s00415-023-12153-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2023] [Revised: 12/05/2023] [Accepted: 12/07/2023] [Indexed: 12/29/2023]
Abstract
Plasma biomarkers have emerged as promising tools for identifying amyloid beta (Aβ) pathology. Before implementation in routine clinical practice, confounding factors modifying their concentration beyond neurodegenerative diseases should be identified. We studied the association of a comprehensive list of demographics, comorbidities, medication and laboratory parameters with plasma p-tau181, glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) on a prospective memory clinic cohort and studied their impact on diagnostic accuracy for discriminating CSF/amyloid PET-defined Aβ status. Three hundred sixty patients (mean age 66.5 years, 55% females, 53% Aβ positive) were included. Sex, age and Aβ status-adjusted models showed that only estimated glomerular filtration rate (eGFR, standardized β -0.115 [-0.192 to -0.035], p = 0.005) was associated with p-tau181 levels, although with a much smaller effect than Aβ status (0.685 [0.607-0.763], p < 0.001). Age, sex, body mass index (BMI), Charlson comorbidity index (CCI) and eGFR significantly modified GFAP concentration. Age, blood volume (BV) and eGFR were associated with NfL levels. p-tau181 predicted Aβ status with 87% sensitivity and specificity with no relevant increase in diagnostic performance by adding any of the confounding factors. Using two cut-offs, plasma p-tau181 could have spared 62% of amyloid-PET/CSF testing. Excluding patients with chronic kidney disease did not change the proposed cut-offs nor the diagnostic performance. In conclusion, in a memory clinic cohort, age, sex, eGFR, BMI, BV and CCI slightly modified plasma p-tau181, GFAP and NfL concentrations but their impact on the diagnostic accuracy of plasma biomarkers for Aβ status discrimination was minimal.
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Affiliation(s)
- Jordi Sarto
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Diana Esteller-Gauxax
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Adrià Tort-Merino
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Núria Guillén
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Agnès Pérez-Millan
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Neus Falgàs
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Sergi Borrego-Écija
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Guadalupe Fernández-Villullas
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Beatriz Bosch
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Jordi Juncà-Parella
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Anna Antonell
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
| | - Laura Naranjo
- Immunology Service, Biomedical Diagnostic Center, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Raquel Ruiz-García
- Immunology Service, Biomedical Diagnostic Center, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Josep María Augé
- Biochemistry and Molecular Genetics Department, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Raquel Sánchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
- Department of Medicine, Faculty of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Albert Lladó
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain
- Department of Medicine, Faculty of Medicine and Health Sciences, Institute of Neurosciences, University of Barcelona, Barcelona, Spain
| | - Mircea Balasa
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic de Barcelona, Fundació de Recerca Clínic - Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Villaroel 170, 08036, Barcelona, Spain.
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6
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Weber DM, Taylor SW, Lagier RJ, Kim JC, Goldman SM, Clarke NJ, Vaillancourt DE, Duara R, McFarland KN, Wang WE, Golde TE, Racke MK. Clinical utility of plasma Aβ42/40 ratio by LC-MS/MS in Alzheimer's disease assessment. Front Neurol 2024; 15:1364658. [PMID: 38595851 PMCID: PMC11003272 DOI: 10.3389/fneur.2024.1364658] [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: 01/02/2024] [Accepted: 03/08/2024] [Indexed: 04/11/2024] Open
Abstract
Introduction Plasma Aβ42/40 ratio can help predict amyloid PET status, but its clinical utility in Alzheimer's disease (AD) assessment is unclear. Methods Aβ42/40 ratio was measured by LC-MS/MS for 250 specimens with associated amyloid PET imaging, diagnosis, and demographic data, and for 6,192 consecutive clinical specimens submitted for Aβ42/40 testing. Results High diagnostic sensitivity and negative predictive value (NPV) for Aβ-PET positivity were observed, consistent with the clinical performance of other plasma LC-MS/MS assays, but with greater separation between Aβ42/40 values for individuals with positive vs. negative Aβ-PET results. Assuming a moderate prevalence of Aβ-PET positivity, a cutpoint was identified with 99% NPV, which could help predict that AD is likely not the cause of patients' cognitive impairment and help reduce PET evaluation by about 40%. Conclusion High-throughput plasma Aβ42/40 LC-MS/MS assays can help identify patients with low likelihood of AD pathology, which can reduce PET evaluations, allowing for cost savings.
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Affiliation(s)
- Darren M. Weber
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA, United States
| | - Steven W. Taylor
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA, United States
| | - Robert J. Lagier
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA, United States
| | - Jueun C. Kim
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA, United States
| | - Scott M. Goldman
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA, United States
| | - Nigel J. Clarke
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA, United States
| | - David E. Vaillancourt
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
| | - Ranjan Duara
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL, United States
| | - Karen N. McFarland
- Department of Neurology, Center for Translational Research in Neurodegenerative Disease, 1Florida Alzheimer’s Disease Research Center (ADRC), University of Florida, Gainesville, FL, United States
| | - Wei-en Wang
- Department of Applied Physiology and Kinesiology, University of Florida, Gainesville, FL, United States
| | - Todd E. Golde
- Department of Neurology, Center for Translational Research in Neurodegenerative Disease, 1Florida Alzheimer’s Disease Research Center (ADRC), University of Florida, Gainesville, FL, United States
- Department of Pharmacology and Chemical Biology, Department of Neurology, Emory Center for Neurodegenerative Disease, Emory University, Atlanta, GA, United States
| | - Michael K. Racke
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA, United States
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Chen Y, Zeng X, Lee J, Sehrawat A, Lafferty TK, Boslett JJ, Klunk WE, Pascoal TA, Villemagne VL, Cohen AD, Lopez O, Yates NA, Karikari TK. Effect of blood collection tube containing protease inhibitors on the pre-analytical stability of Alzheimer's disease plasma biomarkers. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.05.24303504. [PMID: 38496591 PMCID: PMC10942510 DOI: 10.1101/2024.03.05.24303504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
INTRODUCTION The reliability of plasma Alzheimer's disease (AD) biomarkers can be compromised by protease-induced degradation. This limits the feasibility of conducting plasma biomarker studies in environments that lack the capacity for immediate processing and appropriate storage of blood samples. We hypothesized that blood collection tube supplementation with protease inhibitors can improve the stability of plasma biomarkers at room temperatures (RT). This study conducted a comparative analysis of blood biomarker stability in traditional ethylenediaminetetraacetic acid (EDTA) tubes versus BD™ P100 collection tubes, the latter being coated with a protease inhibitor cocktail. The stability of six plasma AD biomarkers was evaluated over time under RT conditions. METHODS We evaluated three experimental approaches. In Approach 1, pooled plasma samples underwent storage at RT for up to 96 hours. In Approach 2, plasma samples isolated upfront from whole blood collected into EDTA or P100 tubes were stored at RT for 0h or 24h before biomarker measurements. In Approach 3, whole blood samples were collected into paired EDTA or P100 tubes, followed by storage at RT for 0h or 24h before isolating the plasma for analyses. Biomarkers were measured with Single Molecule Array (Simoa) and immunoprecipitation-mass spectrometry (IP-MS) assays. RESULTS Both the IP-MS and Simoa methods revealed that the use of P100 tubes significantly improved the stability of Aβ42 and Aβ40 across all approaches. Additionally, the Aβ42/Aβ40 ratio levels were significantly stabilized only in the IP-MS assay in Approach 3. No significant differences were observed in the levels of plasma p-tau181, GFAP, and NfL for samples collected using either tube type in any of the approaches. CONCLUSION Supplementation of blood collection tubes with protease inhibitors could reduce the protease-induced degradation of plasma Aβ42 and Aβ40, and the Aβ ratio for IP-MS assay. This has crucial implications for preanalytical procedures, particularly in resource-limited settings.
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Bali D, Hansson O, Janelidze S. Effects of certain pre-analytical factors on the performance of plasma phospho-tau217. Alzheimers Res Ther 2024; 16:31. [PMID: 38331843 PMCID: PMC10851521 DOI: 10.1186/s13195-024-01391-1] [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: 08/24/2023] [Accepted: 01/14/2024] [Indexed: 02/10/2024]
Abstract
INTRODUCTION Pre-analytical factors can cause substantial variability in the measurements of cerebrospinal fluid (CSF) and plasma biomarkers of Alzheimer's disease (AD). However, their effects on the performance of one of the most promising plasma AD biomarkers, phosphorylated tau (p-tau)217, are not known. METHODS We included 50 amyloid-β positive (Aβ+) and 50 Aβ- participants from the Swedish BioFINDER-1 study. Plasma and CSF p-tau217 were measured using an immunoassay developed by Lilly Research Laboratories. We examined the effect of four plasma handling conditions, i.e., (1) thawing at room temperature (RT) with no centrifugation, (2) thawing at RT followed by centrifugation, (3) thawing on ice with no centrifugation, and (4) thawing on ice followed by centrifugation. In addition, we also tested the effects of up to 3 freeze-thaw cycles on the associations of plasma p-tau217 with AD-related pathologies measured with CSF p-tau217 and CSF Aβ42/Aβ40. RESULTS In the whole cohort (combining Aβ+ and Aβ- participants), we found significant correlations between plasma p-tau217 and both CSF p-tau217 (Rrange, 0.614-0.717, p < 0.001) and CSF Aβ42/Aβ40 (Spearman Rrange, - 0.515 to - 0.652, p < 0.001) for each of the four tested conditions. Correlations between plasma and CSF p-tau217 were also significant for all conditions in the Aβ+ group (Rrange, 0.506-0.579, p < 0.001). However, in this Aβ+ subgroup, correlations with CSF Aβ42/Aβ40 were only significant for centrifuged samples (thawed at RT, R = - 0.394, p = 0.010; thawed on ice, R = - 0.406; p = 0.007). In Aβ- participants, correlations between plasma and CSF p-tau217 were again significant only for centrifuged samples (thawed at RT, R = 0.394, p = 0.007; thawed on ice, R = 0.334; p = 0.022), with no correlations seen between plasma p-tau217 and CSF Aβ42/Aβ40 for any of the conditions. While the accuracy of plasma p-tau217 to identify individuals with abnormal CSF Aβ42/Aβ40 or CSF p-tau217 status was high, the AUCs for samples thawed at RT and analyzed without centrifugation were numerically lower than the AUCs of other conditions (CSF Aβ42/Aβ40 = 0.845 vs 0.872-0.884; CSF p-tau217 = 0.866 vs 0.908-0.924, pdiff > 0.11). P-tau217 concentration was consistently higher in non-centrifuged samples than in centrifuged samples (p ≤ 0.021). There were no differences between samples freeze-thawed once, twice, or three times. CONCLUSION Centrifugation improved the performance of plasma p-tau217, but thawing temperatures and up to three freeze-thaw cycles did not have a significant impact. These results may inform the future development of standardized sample-handling protocols for AD biomarkers.
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Affiliation(s)
- Divya Bali
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Sölvegatan 19, BMC B11, 22184, Lund, Sweden.
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Sölvegatan 19, BMC B11, 22184, Lund, Sweden
- Memory Clinic, Skåne University Hospital, 20502, Malmö, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Sölvegatan 19, BMC B11, 22184, Lund, Sweden.
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Rissman RA, Langford O, Raman R, Donohue MC, Abdel‐Latif S, Meyer MR, Wente‐Roth T, Kirmess KM, Ngolab J, Winston CN, Jimenez‐Maggiora G, Rafii MS, Sachdev P, West T, Yarasheski KE, Braunstein JB, Irizarry M, Johnson KA, Aisen PS, Sperling RA. Plasma Aβ42/Aβ40 and phospho-tau217 concentration ratios increase the accuracy of amyloid PET classification in preclinical Alzheimer's disease. Alzheimers Dement 2024; 20:1214-1224. [PMID: 37932961 PMCID: PMC10916957 DOI: 10.1002/alz.13542] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/02/2023] [Revised: 09/15/2023] [Accepted: 09/28/2023] [Indexed: 11/08/2023]
Abstract
INTRODUCTION Incorporating blood-based Alzheimer's disease biomarkers such as tau and amyloid beta (Aβ) into screening algorithms may improve screening efficiency. METHODS Plasma Aβ, phosphorylated tau (p-tau)181, and p-tau217 concentration levels from AHEAD 3-45 study participants were measured using mass spectrometry. Tau concentration ratios for each proteoform were calculated to normalize for inter-individual differences. Receiver operating characteristic (ROC) curve analysis was performed for each biomarker against amyloid positivity, defined by > 20 Centiloids. Mixture of experts analysis assessed the value of including tau concentration ratios into the existing predictive algorithm for amyloid positron emission tomography status. RESULTS The area under the receiver operating curve (AUC) was 0.87 for Aβ42/Aβ40, 0.74 for phosphorylated variant p-tau181 ratio (p-tau181/np-tau181), and 0.92 for phosphorylated variant p-tau217 ratio (p-tau217/np-tau217). The Plasma Predicted Centiloid (PPC), a predictive model including p-tau217/np-tau217, Aβ42/Aβ40, age, and apolipoprotein E improved AUC to 0.95. DISCUSSION Including plasma p-tau217/np-tau217 along with Aβ42/Aβ40 in predictive algorithms may streamline screening preclinical individuals into anti-amyloid clinical trials. CLINICALTRIALS gov Identifier: NCT04468659 HIGHLIGHTS: The addition of plasma phosphorylated variant p-tau217 ratio (p-tau217/np-tau217) significantly improved plasma biomarker algorithms for identifying preclinical amyloid positron emission tomography positivity. Prediction performance at higher NAV Centiloid levels was improved with p-tau217/np-tau217. All models generated for this study are incorporated into the Plasma Predicted Centiloid (PPC) app for public use.
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Affiliation(s)
- Robert A. Rissman
- Department of NeurosciencesUniversity of California San DiegoLa JollaCaliforniaUSA
- Alzheimer's Therapeutic Research InstituteKeck School of Medicine of the University of Southern CaliforniaSan DiegoCaliforniaUSA
- VA San Diego Healthcare SystemSan DiegoCaliforniaUSA
| | - Oliver Langford
- Alzheimer's Therapeutic Research InstituteKeck School of Medicine of the University of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Rema Raman
- Alzheimer's Therapeutic Research InstituteKeck School of Medicine of the University of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Michael C. Donohue
- Alzheimer's Therapeutic Research InstituteKeck School of Medicine of the University of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Sara Abdel‐Latif
- Alzheimer's Therapeutic Research InstituteKeck School of Medicine of the University of Southern CaliforniaSan DiegoCaliforniaUSA
| | | | | | | | - Jennifer Ngolab
- Alzheimer's Therapeutic Research InstituteKeck School of Medicine of the University of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Charisse N. Winston
- Department of NeurosciencesUniversity of California San DiegoLa JollaCaliforniaUSA
- Alzheimer's Therapeutic Research InstituteKeck School of Medicine of the University of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Gustavo Jimenez‐Maggiora
- Alzheimer's Therapeutic Research InstituteKeck School of Medicine of the University of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Michael S. Rafii
- Alzheimer's Therapeutic Research InstituteKeck School of Medicine of the University of Southern CaliforniaSan DiegoCaliforniaUSA
| | | | - Tim West
- C2N DiagnosticsSt. LouisMissouriUSA
| | | | | | | | - Keith A. Johnson
- Brigham and Women's Hospital, Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
| | - Paul S. Aisen
- Alzheimer's Therapeutic Research InstituteKeck School of Medicine of the University of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Reisa A. Sperling
- Brigham and Women's Hospital, Massachusetts General HospitalHarvard Medical SchoolBostonMassachusettsUSA
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Muir RT, Ismail Z, Black SE, Smith EE. Comparative methods for quantifying plasma biomarkers in Alzheimer's disease: Implications for the next frontier in cerebral amyloid angiopathy diagnostics. Alzheimers Dement 2024; 20:1436-1458. [PMID: 37908054 PMCID: PMC10916950 DOI: 10.1002/alz.13510] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2023] [Revised: 08/09/2023] [Accepted: 08/13/2023] [Indexed: 11/02/2023]
Abstract
Plasma amyloid beta (Aβ) and tau are emerging as accessible biomarkers for Alzheimer's disease (AD). However, many assays exist with variable test performances, highlighting the need for a comparative assessment to identify the most valid assays for future use in AD and to apply to other settings in which the same biomarkers may be useful, namely, cerebral amyloid angiopathy (CAA). CAA is a progressive cerebrovascular disease characterized by deposition of Aβ40 and Aβ42 in cortical and leptomeningeal vessels. Novel immunotherapies for AD can induce amyloid-related imaging abnormalities resembling CAA-related inflammation. Few studies have evaluated plasma biomarkers in CAA. Identifying a CAA signature could facilitate diagnosis, prognosis, and a safer selection of patients with AD for emerging immunotherapies. This review evaluates studies that compare the diagnostic test performance of plasma biomarker techniques in AD and cerebrovascular and plasma biomarker profiles of CAA; it also discusses novel hypotheses and future avenues for plasma biomarker research in CAA.
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Affiliation(s)
- Ryan T. Muir
- Calgary Stroke ProgramDepartment of Clinical NeurosciencesUniversity of CalgaryCalgaryAlbertaCanada
- Department of Community Health SciencesUniversity of CalgaryCalgaryAlbertaCanada
- Hotchkiss Brain InstituteUniversity of CalgaryCalgaryAlbertaCanada
| | - Zahinoor Ismail
- Department of Community Health SciencesUniversity of CalgaryCalgaryAlbertaCanada
- Hotchkiss Brain InstituteUniversity of CalgaryCalgaryAlbertaCanada
- Department of PsychiatryUniversity of CalgaryCalgaryAlbertaCanada
| | - Sandra E. Black
- Division of NeurologyDepartment of MedicineSunnybrook Health Sciences CentreTorontoOntarioCanada
- LC Campbell Cognitive Neurology Research UnitDr Sandra Black Centre for Brain Resilience and Recovery, and Hurvitz Brain Sciences ProgramSunnybrook Research InstituteUniversity of TorontoTorontoOntarioCanada
| | - Eric E. Smith
- Calgary Stroke ProgramDepartment of Clinical NeurosciencesUniversity of CalgaryCalgaryAlbertaCanada
- Department of Community Health SciencesUniversity of CalgaryCalgaryAlbertaCanada
- Hotchkiss Brain InstituteUniversity of CalgaryCalgaryAlbertaCanada
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11
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Cheng YW, Lin YJ, Lin YS, Hong WP, Kuan YC, Wu KY, Hsu JL, Wang PN, Pai MC, Chen CS, Fuh JL, Hu CJ, Chiu MJ. Application of blood-based biomarkers of Alzheimer's disease in clinical practice: Recommendations from Taiwan Dementia Society. J Formos Med Assoc 2024:S0929-6646(24)00051-2. [PMID: 38296698 DOI: 10.1016/j.jfma.2024.01.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2023] [Revised: 11/29/2023] [Accepted: 01/14/2024] [Indexed: 02/02/2024] Open
Abstract
Blood-based biomarkers (BBM) are potentially powerful tools that assist in the biological diagnosis of Alzheimer's disease (AD) in vivo with minimal invasiveness, relatively low cost, and good accessibility. This review summarizes current evidence for using BBMs in AD, focusing on amyloid, tau, and biomarkers for neurodegeneration. Blood-based phosphorylated tau and the Aβ42/Aβ40 ratio showed consistent concordance with brain pathology measured by CSF or PET in the research setting. In addition, glial fibrillary acidic protein (GFAP) and neurofilament light chain (NfL) are neurodegenerative biomarkers that show the potential to assist in the differential diagnosis of AD. Other pathology-specific biomarkers, such as α-synuclein and TAR DNA-binding protein 43 (TDP-43), can potentially detect AD concurrent pathology. Based on current evidence, the working group from the Taiwan Dementia Society (TDS) achieved consensus recommendations on the appropriate use of BBMs for AD in clinical practice. BBMs may assist clinical diagnosis and prognosis in AD subjects with cognitive symptoms; however, the results should be interpreted by dementia specialists and combining biochemical, neuropsychological, and neuroimaging information. Further studies are needed to evaluate BBMs' real-world performance and potential impact on clinical decision-making.
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Affiliation(s)
- Yu-Wen Cheng
- Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan
| | - Yen-Ju Lin
- Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan
| | - Yung-Shuan Lin
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan; Institute of Brain Science, National Yang Ming Chiao Tung University, Taipei, Taiwan; Brain Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Wei-Pin Hong
- Department of Neurology, National Cheng Kung University Hospital, Tainan, Taiwan
| | - Yi-Chun Kuan
- Taipei Neuroscience Institute, Taipei Medical University, Taipei, Taiwan; Department of Neurology and Dementia Center, Taipei Medical University-Shuang Ho Hospital, New Taipei City, Taiwan; Department of Neurology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Kuan-Yi Wu
- Department of Psychiatry, Chang Gung Memorial Hospital and College of Medicine, Chang Gung University, Tao-Yuan, Taiwan
| | - Jung-Lung Hsu
- Department of Neurology, New Taipei Municipal TuCheng Hospital, Chang Gung Memorial Hospital and Chang Gung University, New Taipei City, Taiwan; Graduate Institute of Mind, Brain, & Consciousness, Taipei Medical University, Taipei, Taiwan; Brain & Consciousness Research Center, Shuang Ho Hospital, New Taipei City, Taiwan
| | - Pei-Ning Wang
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Ming-Chyi Pai
- Division of Behavioral Neurology, Department of Neurology, National Cheng Kung University Hospital, College of Medicine, National Cheng Kung University, Tainan, Taiwan; Alzheimer's Disease Research Center, National Cheng Kung University Hospital, Tainan, Taiwan; Institute of Gerontology, College of Medicine, National Cheng Kung University, Tainan, Taiwan
| | - Cheng-Sheng Chen
- Department of Psychiatry, Kaohsiung Medical University Hospital, Kaohsiung, Taiwan; Department of Psychiatry, College of Medicine, Kaohsiung Medical University, Kaohsiung, Taiwan
| | - Jong-Ling Fuh
- Department of Neurology, Neurological Institute, Taipei Veterans General Hospital, Taipei, Taiwan; School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Chaur-Jong Hu
- Taipei Neuroscience Institute, Taipei Medical University, Taipei, Taiwan; Department of Neurology and Dementia Center, Taipei Medical University-Shuang Ho Hospital, New Taipei City, Taiwan; Department of Neurology, School of Medicine, College of Medicine, Taipei Medical University, Taipei, Taiwan
| | - Ming-Jang Chiu
- Department of Neurology, National Taiwan University Hospital, Taipei, Taiwan.
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12
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Colmant L, Boyer E, Gerard T, Sleegers K, Lhommel R, Ivanoiu A, Lefèvre P, Kienlen-Campard P, Hanseeuw B. Definition of a Threshold for the Plasma Aβ42/Aβ40 Ratio Measured by Single-Molecule Array to Predict the Amyloid Status of Individuals without Dementia. Int J Mol Sci 2024; 25:1173. [PMID: 38256246 PMCID: PMC10816992 DOI: 10.3390/ijms25021173] [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: 12/15/2023] [Revised: 01/15/2024] [Accepted: 01/16/2024] [Indexed: 01/24/2024] Open
Abstract
Alzheimer's disease (AD) is characterized by amyloid beta (Aβ) plaques and hyperphosphorylated tau in the brain. Aβ plaques precede cognitive impairments and can be detected through amyloid-positron emission tomography (PET) or in cerebrospinal fluid (CSF). Assessing the plasma Aβ42/Aβ40 ratio seems promising for non-invasive and cost-effective detection of brain Aβ accumulation. This approach involves some challenges, including the accuracy of blood-based biomarker measurements and the establishment of clear, standardized thresholds to categorize the risk of developing brain amyloid pathology. Plasma Aβ42/Aβ40 ratio was measured in 277 volunteers without dementia, 70 AD patients and 18 non-AD patients using single-molecule array. Patients (n = 88) and some volunteers (n = 66) were subject to evaluation of amyloid status by CSF Aβ quantification or PET analysis. Thresholds of plasma Aβ42/Aβ40 ratio were determined based on a Gaussian mixture model, a decision tree, and the Youden's index. The 0.0472 threshold, the one with the highest sensitivity, was retained for general population without dementia screening, and the 0.0450 threshold was retained for research and clinical trials recruitment, aiming to minimize the need for CSF or PET analyses to identify amyloid-positive individuals. These findings offer a promising step towards a cost-effective method for identifying individuals at risk of developing AD.
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Affiliation(s)
- Lise Colmant
- Institute of Neuroscience, UCLouvain, 1200 Brussels, Belgium; (L.C.); (E.B.); (T.G.); (P.L.); (P.K.-C.)
- Neurology Department, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium;
- Institute of Information and Communication Technologies, Electronics and Applied Mathematics, UCLouvain, 1348 Louvain-la-Neuve, Belgium
| | - Emilien Boyer
- Institute of Neuroscience, UCLouvain, 1200 Brussels, Belgium; (L.C.); (E.B.); (T.G.); (P.L.); (P.K.-C.)
- Neurology Department, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium;
| | - Thomas Gerard
- Institute of Neuroscience, UCLouvain, 1200 Brussels, Belgium; (L.C.); (E.B.); (T.G.); (P.L.); (P.K.-C.)
- Neurology Department, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium;
| | - Kristel Sleegers
- Complex Genetics of Alzheimer’s Disease Group, VIB-UAntwerp Center for Molecular Neurology, University of Antwerp, 2000 Antwerpen, Belgium;
| | - Renaud Lhommel
- Neurology Department, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium;
| | - Adrian Ivanoiu
- Institute of Neuroscience, UCLouvain, 1200 Brussels, Belgium; (L.C.); (E.B.); (T.G.); (P.L.); (P.K.-C.)
- Neurology Department, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium;
| | - Philippe Lefèvre
- Institute of Neuroscience, UCLouvain, 1200 Brussels, Belgium; (L.C.); (E.B.); (T.G.); (P.L.); (P.K.-C.)
- Institute of Information and Communication Technologies, Electronics and Applied Mathematics, UCLouvain, 1348 Louvain-la-Neuve, Belgium
| | - Pascal Kienlen-Campard
- Institute of Neuroscience, UCLouvain, 1200 Brussels, Belgium; (L.C.); (E.B.); (T.G.); (P.L.); (P.K.-C.)
| | - Bernard Hanseeuw
- Institute of Neuroscience, UCLouvain, 1200 Brussels, Belgium; (L.C.); (E.B.); (T.G.); (P.L.); (P.K.-C.)
- Neurology Department, Cliniques Universitaires Saint-Luc, 1200 Brussels, Belgium;
- WELBIO Department, WEL Research Institute, Avenue Pasteur, 6, 1300 Wavre, Belgium
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13
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Weber DM, Taylor SW, Lagier RJ, Kim JC, Goldman SM, Clarke NJ, Vaillancourt DE, Duara R, McFarland KN, Wang WE, Golde TE, Racke MK. Clinical utility of plasma Aβ42/40 ratio by LC-MS/MS in Alzheimer's disease assessment. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.12.12.23299878. [PMID: 38168329 PMCID: PMC10760303 DOI: 10.1101/2023.12.12.23299878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
INTRODUCTION Plasma Aβ42/40 ratio can be used to help predict amyloid PET status, but its clinical utility in Alzheimer's disease (AD) assessment is unclear. METHODS Aβ42/40 ratio was measured by LC-MS/MS in 250 specimens with associated amyloid PET imaging, diagnosis, and demographic data, and 6,192 consecutive clinical specimens submitted for Aβ42/40 testing. RESULTS High diagnostic sensitivity and negative predictive value (NPV) for Aβ-PET positivity were observed, consistent with the clinical performance of other plasma LC-MS/MS assays, but with greater separation between Aβ42/40 values for individuals with positive vs negative Aβ-PET results. Assuming a moderate prevalence of Aβ-PET positivity, a cutpoint was identified with 99% NPV, which could help predict that AD is likely not the cause of patients' cognitive impairment and help reduce PET evaluation by about 40%. DISCUSSION Using high-throughput plasma Aβ42/40 LC-MS/MS assays can help reduce PET evaluations in patients with low likelihood of AD pathology, allowing for cost savings.
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Affiliation(s)
- Darren M Weber
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA USA
| | - Steven W Taylor
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA USA
| | - Robert J Lagier
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA USA
| | - Jueun C Kim
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA USA
| | - Scott M Goldman
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA USA
| | - Nigel J Clarke
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA USA
| | - David E Vaillancourt
- Department of Applied Physiology and Kinesiology, Fixel Institute for Neurological Disorders, and 1Florida ADRC, University of Florida, Gainesville, FL USA
| | - Ranjan Duara
- Department of Applied Physiology and Kinesiology, Fixel Institute for Neurological Disorders, and 1Florida ADRC, University of Florida, Gainesville, FL USA
- Wien Center for Alzheimer's Disease and Memory Disorders, Mount Sinai Medical Center, Miami Beach, FL USA
| | - Karen N McFarland
- Department of Neurology, Center for Translational Research in Neurodegenerative Disease, 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL USA
| | - Wei-En Wang
- Department of Applied Physiology and Kinesiology, Fixel Institute for Neurological Disorders, and 1Florida ADRC, University of Florida, Gainesville, FL USA
| | - Todd E Golde
- Department of Neurology, Center for Translational Research in Neurodegenerative Disease, 1Florida Alzheimer's Disease Research Center (ADRC), University of Florida, Gainesville, FL USA
- Department of Pharmacology and Chemical Biology and Department of Neurology Center for Neurodegenerative Disease, Goizueta Institute Emory Brain Health, Emory University, School of Medicine. Atlanta, GA USA
| | - Michael K Racke
- Quest Diagnostics Nichols Institute, San Juan Capistrano, CA USA
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14
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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. RESEARCH SQUARE 2023:rs.3.rs-3725688. [PMID: 38168408 PMCID: PMC10760237 DOI: 10.21203/rs.3.rs-3725688/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: 01/05/2024]
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 potential of pTau217 to predict amyloidosis in CSF. 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 (x4.2) 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.
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Affiliation(s)
| | - Nuole Zhu
- IR SANT PAU, Hospital de la Santa Creu i Sant Pau
| | | | | | - Rosa Ferrer
- IR SANT PAU, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona
| | | | | | | | | | - Juan Fortea
- IR SANT PAU, Hospital de la Santa Creu i Sant Pau
| | - Alberto Lleó
- IR SANT PAU, Hospital de la Santa Creu i Sant Pau
| | - Mireia Tondo
- IR SANT PAU, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona
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Wang L, Chang M, Ma P, Chen H, Ma S, Chen N, Zhang X. Self-assembly of Au nanocubes for ultrasensitive detection of Alzheimer's disease biomarkers by SERS. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2023; 15:6385-6393. [PMID: 37968999 DOI: 10.1039/d3ay01667f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2023]
Abstract
Since presently Alzheimer's disease (AD) is incurable, early diagnosis of AD is crucial. Aβ 1-42 and tau-441 proteins are promising core biomarkers for early diagnosis and early therapeutic intervention in AD. Here we constructed a surface-enhanced Raman spectroscopy (SERS) biosensor for highly sensitive quantitative detection of Aβ 1-42 and tau proteins by preparing gold nanocube (AuNC) superlattices through evaporation self-assembly. The results showed that the method has a wide response range (0.1-10 000 ng mL-1 and 0.01-1000 ng mL-1, respectively) and high sensitivity. The detection limits of Aβ1-42 and tau protein were 0.0416 ng mL-1 and 0.0087 ng mL-1, respectively. In addition, the method was able to rapidly and simultaneously detect the two biomarkers in serum, which showed the feasibility of the method in complex biological environments. The detection of Aβ 1-42 and tau protein has great potential for the accurate prediction and early diagnosis of Alzheimer's disease.
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Affiliation(s)
- Luyao Wang
- Key Laboratory of Optical Technology and Instrument for Medicine, Ministry of Education, College of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Min Chang
- Key Laboratory of Optical Technology and Instrument for Medicine, Ministry of Education, College of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Pei Ma
- Key Laboratory of Optical Technology and Instrument for Medicine, Ministry of Education, College of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Hui Chen
- Key Laboratory of Optical Technology and Instrument for Medicine, Ministry of Education, College of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
| | - Shaojun Ma
- Department of Geriatrics, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Nan Chen
- School of Electrical Engineering, Nantong University, Nantong 226019, China
| | - Xuedian Zhang
- Key Laboratory of Optical Technology and Instrument for Medicine, Ministry of Education, College of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, Shanghai 200093, China
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16
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Kang JH, Korecka M, Lee EB, Cousins KAQ, Tropea TF, Chen-Plotkin AA, Irwin DJ, Wolk D, Brylska M, Wan Y, Shaw LM. Alzheimer Disease Biomarkers: Moving from CSF to Plasma for Reliable Detection of Amyloid and tau Pathology. Clin Chem 2023; 69:1247-1259. [PMID: 37725909 PMCID: PMC10895336 DOI: 10.1093/clinchem/hvad139] [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: 01/04/2023] [Accepted: 07/07/2023] [Indexed: 09/21/2023]
Abstract
BACKGROUND Development of validated biomarkers to detect early Alzheimer disease (AD) neuropathology is needed for therapeutic AD trials. Abnormal concentrations of "core" AD biomarkers, cerebrospinal fluid (CSF) amyloid beta1-42, total tau, and phosphorylated tau correlate well with neuroimaging biomarkers and autopsy findings. Nevertheless, given the limitations of established CSF and neuroimaging biomarkers, accelerated development of blood-based AD biomarkers is underway. CONTENT Here we describe the clinical significance of CSF and plasma AD biomarkers to detect disease pathology throughout the Alzheimer continuum and correlate with imaging biomarkers. Use of the AT(N) classification by CSF and imaging biomarkers provides a more objective biologically based diagnosis of AD than clinical diagnosis alone. Significant progress in measuring CSF AD biomarkers using extensively validated highly automated assay systems has facilitated their transition from research use only to approved in vitro diagnostics tests for clinical use. We summarize development of plasma AD biomarkers as screening tools for enrollment and monitoring participants in therapeutic trials and ultimately in clinical care. Finally, we discuss the challenges for AD biomarkers use in clinical trials and precision medicine, emphasizing the possible ethnocultural differences in the levels of AD biomarkers. SUMMARY CSF AD biomarker measurements using fully automated analytical platforms is possible. Building on this experience, validated blood-based biomarker tests are being implemented on highly automated immunoassay and mass spectrometry platforms. The progress made developing analytically and clinically validated plasma AD biomarkers within the AT(N) classification scheme can accelerate use of AD biomarkers in therapeutic trials and routine clinical practice.
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Affiliation(s)
- Ju Hee Kang
- Department of Pharmacology and Clinical Pharmacology, Research Center for Controlling Intercellular Communication, Inha University, Incheon, South Korea
| | - Magdalena Korecka
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Katheryn A Q Cousins
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Thomas F Tropea
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Alice A Chen-Plotkin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David J Irwin
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Magdalena Brylska
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Yang Wan
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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Imbimbo BP, Watling M, Imbimbo C, Nisticò R. Plasma ATN(I) classification and precision pharmacology in Alzheimer's disease. Alzheimers Dement 2023; 19:4729-4734. [PMID: 37079778 DOI: 10.1002/alz.13084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Revised: 03/15/2023] [Accepted: 03/15/2023] [Indexed: 04/22/2023]
Abstract
Evaluating potential therapies for Alzheimer's disease (AD) depends on use of biomarkers for appropriate subject selection and monitoring disease progression. Biomarkers that predict onset of clinical symptoms are particularly important for AD because they enable intervention before irreversible neurodegeneration occurs. The amyloid-β-tau-neurodegeneration (ATN) classification system is currently used as a biological staging model for AD and is based on three classes of biomarkers evaluating amyloid-β (Aβ), tau pathology and neurodegeneration or neuronal injury. Promising blood-based biomarkers for each of these categories have been identified (Aβ42/Aβ40 ratio, phosphorylated tau, neurofilament light chain), and this matrix is now being expanded toward an ATN(I) system, where "I" represents a neuroinflammatory biomarker. The plasma ATN(I) system, together with APOE genotyping, offers a basis for individualized evaluation and a move away from the classic "one size fits all" approach toward a biomarker-driven individualisation of therapy for patients with AD.
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Affiliation(s)
- Bruno P Imbimbo
- Department of Research & Development, Chiesi Farmaceutici, Parma, Italy
| | - Mark Watling
- Independent Scholar (formerly at TranScrip Ltd, Reading, UK), Ruthin, UK
| | - Camillo Imbimbo
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Robert Nisticò
- Department of Biology, School of Pharmacy, University of Tor Vergata, and European Brain Research Institute (EBRI), Rome, Italy
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Kwon HS, Lee E, Kim H, Park S, Park H, Jeong JH, Koh S, Choi SH, Lee J. Predicting amyloid PET positivity using plasma p-tau181 and other blood-based biomarkers. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12502. [PMID: 38026758 PMCID: PMC10654468 DOI: 10.1002/dad2.12502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Revised: 10/12/2023] [Accepted: 10/22/2023] [Indexed: 12/01/2023]
Abstract
Introduction This study aimed to determine the efficacy of combining plasma phosphorylated tau (p-tau)181, amyloid beta (Aβ)42/Aβ40, neurofilament light (NfL), and apolipoprotein E (APOE) genotypes for detecting positive amyloid positron emission tomography (PET), which is little known in the Asian population, in two independent cohorts. Methods Biomarkers were measured using a single-molecule array (Simoa) in a cohort study (Asan). All participants underwent amyloid PET. Significant changes in the area under the curve (AUC) and Akaike Information Criterion values were considered to determine the best model. The generalizability of this model was tested using another cohort (KBASE-V). Results In the Asan cohort, after adjusting for age and sex, p-tau181 (AUC = 0.854) or APOE ε4 status (AUC = 0.769) distinguished Aβ status with high accuracy. Combining them or adding NfL and Aβ42/40 improved model fitness. The best-fit model included the plasma p-tau181, APOE ε4, NfL and Aβ42/40. The models established from the Asan cohort were tested in the KBASE-V cohort. Additionally, in the KBASE-V cohort, these three biomarker models had similar AUC in cognitively unimpaired (AUC = 0.768) and mild cognitive impairment (MCI) (AUC = 0.997) participants. Conclusions Plasma p-tau181 showed a high performance in determining Aβ-PET positivity. Adding plasma NfL and APOE ε4 status improved the model fit without significant improvement in AUC.
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Affiliation(s)
- Hyuk Sung Kwon
- Department of NeurologyHanyang University Guri HospitalHanyang University College of MedicineGuriSouth Korea
| | - Eun‐Hye Lee
- Department of NeurologyHanyang University Guri HospitalHanyang University College of MedicineGuriSouth Korea
| | - Hyung‐Ji Kim
- Department of NeurologyUijeongbu Eulji Medical CenterEulji UniversityUijeongbuSouth Korea
| | - So‐Hee Park
- Department of NeurologyBobath Memorial HospitalSeongnamSouth Korea
| | - Hyun‐Hee Park
- Department of NeurologyHanyang University Guri HospitalHanyang University College of MedicineGuriSouth Korea
| | - Jee Hyang Jeong
- Department of NeurologyEwha Womans University School of MedicineSeoulSouth Korea
| | - Seong‐Ho Koh
- Department of NeurologyHanyang University Guri HospitalHanyang University College of MedicineGuriSouth Korea
- Department of Translational MedicineHanyang University Graduate School of Biomedical Science & EngineeringSeoulSouth Korea
| | - Seong Hye Choi
- Department of NeurologyInha University College of MedicineIncheonSouth Korea
| | - Jae‐Hong Lee
- Department of NeurologyUniversity of Ulsan College of MedicineAsan Medical CenterSeoulSouth Korea
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Kwon HS, Kim JY, Koh SH, Choi SH, Lee EH, Jeong JH, Jang JW, Park KW, Kim EJ, Hong JY, Yoon SJ, Yoon B, Park HH, Han MH. Predicting cognitive stage transition using p-tau181, Centiloid, and other measures. Alzheimers Dement 2023; 19:4641-4650. [PMID: 36988152 DOI: 10.1002/alz.13054] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 02/03/2023] [Accepted: 02/21/2023] [Indexed: 03/30/2023]
Abstract
BACKGROUND A combination of plasma phospho-tau (p-tau), amyloid beta (Aβ)-positron emission tomography (PET), brain magnetic resonance imaging, cognitive function tests, and other biomarkers might predict future cognitive decline. This study aimed to investigate the efficacy of combining these biomarkers in predicting future cognitive stage transitions within 3 years. METHODS Among the participants in the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer's Disease (KBASE-V) study, 49 mild cognitive impairment (MCI) and 113 cognitively unimpaired (CU) participants with Aβ-PET and brain imaging data were analyzed. RESULTS Older age, increased plasma p-tau181, Aβ-PET positivity, and decreased semantic fluency were independently associated with cognitive stage transitions. Combining age, p-tau181, the Centiloid scale, semantic fluency, and hippocampal volume produced high predictive value in predicting future cognitive stage transition (area under the curve = 0.879). CONCLUSIONS Plasma p-tau181 and Centiloid scale alone or in combination with other biomarkers, might predict future cognitive stage transition in non-dementia patients. HIGHLIGHTS -Plasma p-tau181 and Centiloid scale might predict future cognitive stage transition. -Combining them or adding other biomarkers increased the predictive value. -Factors that independently associated with cognitive stage transition were demonstrated.
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Affiliation(s)
- Hyuk Sung Kwon
- Department of Neurology, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Republic of Korea
| | - Ji Young Kim
- Department of Nuclear Medicine, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Republic of Korea
| | - Seong-Ho Koh
- Department of Neurology, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Republic of Korea
| | - Seong Hye Choi
- Department of Neurology, Inha University College of Medicine, Incheon, Republic of Korea
| | - Eun-Hye Lee
- Department of Neurology, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Republic of Korea
| | - Jee Hyang Jeong
- Department of Neurology, Ewha Womans University School of Medicine, Seoul, Republic of Korea
| | - Jae-Won Jang
- Department of Neurology, Kangwon National University School of Medicine, Chuncheon, Republic of Korea
| | - Kyung Won Park
- Department of Neurology, Dong-A Medical Center, Dong-A University College of Medicine, Busan, Republic of Korea
| | - Eun-Joo Kim
- Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan, Republic of Korea
| | - Jin Yong Hong
- Department of Neurology, Yonsei University Wonju College of Medicine, Wonju, Republic of Korea
| | - Soo Jin Yoon
- Department of Neurology, Eulji University Hospital, Eulji University School of Medicine, Daejeon, Republic of Korea
| | - Bora Yoon
- Department of Neurology, Konyang University College of Medicine, Daejeon, Republic of Korea
| | - Hyun-Hee Park
- Department of Neurology, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Republic of Korea
| | - Myung Hoon Han
- Department of Neurosurgery, Hanyang University Guri Hospital, Hanyang University College of Medicine, Guri, Republic of Korea
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Xiao Z, Wu W, Ma X, Wu J, Liang X, Zhou X, Cao Y, Zhao Q, Ding D. Plasma p-tau217, p-tau181, and NfL as early indicators of dementia risk in a community cohort: The Shanghai Aging Study. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12514. [PMID: 38145191 PMCID: PMC10740382 DOI: 10.1002/dad2.12514] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 11/13/2023] [Accepted: 11/19/2023] [Indexed: 12/26/2023]
Abstract
INTRODUCTION Blood biomarkers showed values for predicting future cognitive impairment. Evidence from the community-based cohort was limited only in high-income countries. METHODS This study included 1857 dementia-free community residents recruited in 2009-2011 and followed up in waves 2014-2016 and 2019-2023 in the Shanghai Aging Study. We intended to explore the relationships of baseline plasma ALZpath phosphorylated tau 217 (p-tau217), p-tau181, neurofilament light chain (NfL) with follow-up incident dementia, Alzheimer's disease (AD), and amyloidosis. RESULTS Higher concentrations of plasma p-tau217, p-tau181, and NfL were correlated to higher decline speed of Mini-Mental State Examination score, and higher risk of incident dementia and AD. The p-tau217 demonstrated a significant correlation with longitudinal neocortical amyloid-beta (Aβ) deposition (r = 0.57 [0.30, 0.76]) and a high accuracy differentiating Aβ+ from Aβ- at follow-ups (area under the receiver operating characteristic curve = 0.821 [0.703, 0.940]). DISCUSSION Plasma p-tau217 may be an early predictive marker of AD and Aβ pathology in older community-dwelling individuals.Highlights: Plasma p-tau217, p-tau181, and NfL were positively associated with long-term cognitive decline and risk of incident dementia.Plasma p-tau217 showed a better performance distinguishing Aβ+ individuals from Aβ- individuals at follow-ups.Plasma NfL may be a suitable predictor of general cognitive decline in older community-dwelling individuals.
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Affiliation(s)
- Zhenxu Xiao
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
| | - Wanqing Wu
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
| | - Xiaoxi Ma
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
| | - Jie Wu
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
| | - Xiaoniu Liang
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
| | - Xiaowen Zhou
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
| | - Yang Cao
- Clinical Epidemiology and BiostatisticsSchool of Medical SciencesFaculty of Medicine and HealthÖrebro UniversityÖrebroSweden
- Unit of Integrative EpidemiologyInstitute of Environmental MedicineKarolinska InstituteStockholmSweden
| | - Qianhua Zhao
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
- MOE Frontiers Center for Brain ScienceFudan UniversityShanghaiChina
| | - Ding Ding
- Institute of NeurologyHuashan HospitalFudan UniversityShanghaiChina
- National Clinical Research Center for Aging and MedicineHuashan HospitalFudan UniversityShanghaiChina
- National Center for Neurological DisordersHuashan HospitalFudan UniversityShanghaiChina
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21
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Johnson EL, Sullivan KJ, Schneider ALC, Simino J, Mosley TH, Kucharska-Newton A, Knopman DS, Gottesman RF. Association of Plasma Aβ 42/Aβ 40 Ratio and Late-Onset Epilepsy: Results From the Atherosclerosis Risk in Communities Study. Neurology 2023; 101:e1319-e1327. [PMID: 37541842 PMCID: PMC10558158 DOI: 10.1212/wnl.0000000000207635] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 05/30/2023] [Indexed: 08/06/2023] Open
Abstract
BACKGROUND AND OBJECTIVES The objective of this study was to determine the relationship between plasma β-amyloid (Aβ), specifically the ratio of 2 Aβ peptides (the Aβ42/Aβ40 ratio, which correlates with increased accumulation of Aβ in the CNS), and late-onset epilepsy (LOE). METHODS We used Medicare fee-for-service claims codes from 1991 to 2018 to identify cases of LOE among 1,424 Black and White men and women enrolled in the Atherosclerosis Risk in Communities (ARIC) study cohort. The Aβ42/Aβ40 ratio was calculated from plasma samples collected from ARIC participants in 1993-1995 (age 50-71 years) and 2011-2013 (age 67-90 years). We used survival analysis accounting for the competing risk of death to determine the relationship between late-life plasma Aβ42/Aβ40, and its change from midlife to late life, and the subsequent development of epilepsy. We adjusted for demographics, the apolipoprotein e4 genotype, and comorbidities, including stroke, dementia, and head injury. A low plasma ratio of 2 Aβ peptides, the Aβ42/Aβ40 ratio, correlates with low CSF Aβ42/Aβ40 and with increased accumulation of Aβ in the CNS. RESULTS Decrease in plasma Aβ42/Aβ40 ratio from midlife to late life, but not an isolated measurement of Aβ42/Aβ40, was associated with development of epilepsy in later life. For every 50% reduction in Aβ42/Aβ40, there was a 2-fold increase in risk of epilepsy (adjusted subhazard ratio 2.30, 95% CI 1.27-4.17). DISCUSSION A reduction in plasma Aβ42/Aβ40 is associated with an increased risk of subsequent epilepsy. Our observations provide a further validation of the link between Aβ, hyperexcitable states, and LOE.
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Affiliation(s)
- Emily L Johnson
- From the Department of Neurology (E.L.J.), Johns Hopkins School of Medicine, Baltimore, MD; Department of Medicine (K.J.S., T.H.M.), University of Mississippi Medical Center, Jackson; Departments of Neurology (A.L.C.S.) and Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Philadelphia; Department of Data Science and Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.S.), University of Mississippi Medical Center, Jackson, MD; Department of Epidemiology (A.K.-N.), University of North Carolina Chapel Hill; Department of Epidemiology (A.K.-N.), University of Kentucky Lexington; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and National Institute for Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), National Institutes of Health, Bethesda, MD.
| | - Kevin J Sullivan
- From the Department of Neurology (E.L.J.), Johns Hopkins School of Medicine, Baltimore, MD; Department of Medicine (K.J.S., T.H.M.), University of Mississippi Medical Center, Jackson; Departments of Neurology (A.L.C.S.) and Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Philadelphia; Department of Data Science and Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.S.), University of Mississippi Medical Center, Jackson, MD; Department of Epidemiology (A.K.-N.), University of North Carolina Chapel Hill; Department of Epidemiology (A.K.-N.), University of Kentucky Lexington; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and National Institute for Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), National Institutes of Health, Bethesda, MD
| | - Andrea Lauren Christman Schneider
- From the Department of Neurology (E.L.J.), Johns Hopkins School of Medicine, Baltimore, MD; Department of Medicine (K.J.S., T.H.M.), University of Mississippi Medical Center, Jackson; Departments of Neurology (A.L.C.S.) and Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Philadelphia; Department of Data Science and Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.S.), University of Mississippi Medical Center, Jackson, MD; Department of Epidemiology (A.K.-N.), University of North Carolina Chapel Hill; Department of Epidemiology (A.K.-N.), University of Kentucky Lexington; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and National Institute for Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), National Institutes of Health, Bethesda, MD
| | - Jeannette Simino
- From the Department of Neurology (E.L.J.), Johns Hopkins School of Medicine, Baltimore, MD; Department of Medicine (K.J.S., T.H.M.), University of Mississippi Medical Center, Jackson; Departments of Neurology (A.L.C.S.) and Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Philadelphia; Department of Data Science and Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.S.), University of Mississippi Medical Center, Jackson, MD; Department of Epidemiology (A.K.-N.), University of North Carolina Chapel Hill; Department of Epidemiology (A.K.-N.), University of Kentucky Lexington; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and National Institute for Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), National Institutes of Health, Bethesda, MD
| | - Tom H Mosley
- From the Department of Neurology (E.L.J.), Johns Hopkins School of Medicine, Baltimore, MD; Department of Medicine (K.J.S., T.H.M.), University of Mississippi Medical Center, Jackson; Departments of Neurology (A.L.C.S.) and Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Philadelphia; Department of Data Science and Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.S.), University of Mississippi Medical Center, Jackson, MD; Department of Epidemiology (A.K.-N.), University of North Carolina Chapel Hill; Department of Epidemiology (A.K.-N.), University of Kentucky Lexington; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and National Institute for Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), National Institutes of Health, Bethesda, MD
| | - Anna Kucharska-Newton
- From the Department of Neurology (E.L.J.), Johns Hopkins School of Medicine, Baltimore, MD; Department of Medicine (K.J.S., T.H.M.), University of Mississippi Medical Center, Jackson; Departments of Neurology (A.L.C.S.) and Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Philadelphia; Department of Data Science and Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.S.), University of Mississippi Medical Center, Jackson, MD; Department of Epidemiology (A.K.-N.), University of North Carolina Chapel Hill; Department of Epidemiology (A.K.-N.), University of Kentucky Lexington; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and National Institute for Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), National Institutes of Health, Bethesda, MD
| | - David S Knopman
- From the Department of Neurology (E.L.J.), Johns Hopkins School of Medicine, Baltimore, MD; Department of Medicine (K.J.S., T.H.M.), University of Mississippi Medical Center, Jackson; Departments of Neurology (A.L.C.S.) and Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Philadelphia; Department of Data Science and Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.S.), University of Mississippi Medical Center, Jackson, MD; Department of Epidemiology (A.K.-N.), University of North Carolina Chapel Hill; Department of Epidemiology (A.K.-N.), University of Kentucky Lexington; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and National Institute for Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), National Institutes of Health, Bethesda, MD
| | - Rebecca F Gottesman
- From the Department of Neurology (E.L.J.), Johns Hopkins School of Medicine, Baltimore, MD; Department of Medicine (K.J.S., T.H.M.), University of Mississippi Medical Center, Jackson; Departments of Neurology (A.L.C.S.) and Biostatistics, Epidemiology, and Informatics (A.L.C.S.), University of Pennsylvania Philadelphia; Department of Data Science and Memory Impairment and Neurodegenerative Dementia (MIND) Center (J.S.), University of Mississippi Medical Center, Jackson, MD; Department of Epidemiology (A.K.-N.), University of North Carolina Chapel Hill; Department of Epidemiology (A.K.-N.), University of Kentucky Lexington; Department of Neurology (D.S.K.), Mayo Clinic, Rochester, MN; and National Institute for Neurologic Disorders and Stroke Intramural Research Program (R.F.G.), National Institutes of Health, Bethesda, MD
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Hampel H, Hu Y, Cummings J, Mattke S, Iwatsubo T, Nakamura A, Vellas B, O'Bryant S, Shaw LM, Cho M, Batrla R, Vergallo A, Blennow K, Dage J, Schindler SE. Blood-based biomarkers for Alzheimer's disease: Current state and future use in a transformed global healthcare landscape. Neuron 2023; 111:2781-2799. [PMID: 37295421 PMCID: PMC10720399 DOI: 10.1016/j.neuron.2023.05.017] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2022] [Revised: 03/03/2023] [Accepted: 05/19/2023] [Indexed: 06/12/2023]
Abstract
Timely detection of the pathophysiological changes and cognitive impairment caused by Alzheimer's disease (AD) is increasingly pressing because of the advent of biomarker-guided targeted therapies that may be most effective when provided early in the disease. Currently, diagnosis and management of early AD are largely guided by clinical symptoms. FDA-approved neuroimaging and cerebrospinal fluid biomarkers can aid detection and diagnosis, but the clinical implementation of these testing modalities is limited because of availability, cost, and perceived invasiveness. Blood-based biomarkers (BBBMs) may enable earlier and faster diagnoses as well as aid in risk assessment, early detection, prognosis, and management. Herein, we review data on BBBMs that are closest to clinical implementation, particularly those based on measures of amyloid-β peptides and phosphorylated tau species. We discuss key parameters and considerations for the development and potential deployment of these BBBMs under different contexts of use and highlight challenges at the methodological, clinical, and regulatory levels.
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Affiliation(s)
- Harald Hampel
- Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA.
| | - Yan Hu
- Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA.
| | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Pam Quirk Brain Health and Biomarker Laboratory, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas (UNLV), Las Vegas, NV, USA
| | - Soeren Mattke
- Center for Improving Chronic Illness Care, University of Southern California, Los Angeles, CA, USA
| | - Takeshi Iwatsubo
- Department of Neuropathology, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan
| | - Akinori Nakamura
- Department of Biomarker Research, National Center for Geriatrics and Gerontology, Obu, Japan; Department of Cognition and Behavior Science, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Bruno Vellas
- University Paul Sabatier, Gérontopôle, Toulouse University Hospital, UMR INSERM 1285, Toulouse, France
| | - Sid O'Bryant
- Institute for Translational Research, Texas College of Osteopathic Medicine, Department of Family Medicine, University of North Texas Health Science Center, Fort Worth, TX, USA
| | - Leslie M Shaw
- Perelman School of Medicine, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Min Cho
- Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA
| | - Richard Batrla
- Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA
| | - Andrea Vergallo
- Alzheimer's Disease and Brain Health, Eisai Inc., Nutley, NJ, USA
| | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Jeffrey Dage
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Suzanne E Schindler
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
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23
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Taneva SG, Todinova S, Andreeva T. Morphometric and Nanomechanical Screening of Peripheral Blood Cells with Atomic Force Microscopy for Label-Free Assessment of Alzheimer's Disease, Parkinson's Disease, and Amyotrophic Lateral Sclerosis. Int J Mol Sci 2023; 24:14296. [PMID: 37762599 PMCID: PMC10531602 DOI: 10.3390/ijms241814296] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2023] [Revised: 09/09/2023] [Accepted: 09/16/2023] [Indexed: 09/29/2023] Open
Abstract
Neurodegenerative disorders (NDDs) are complex, multifactorial disorders with significant social and economic impact in today's society. NDDs are predicted to become the second-most common cause of death in the next few decades due to an increase in life expectancy but also to a lack of early diagnosis and mainly symptomatic treatment. Despite recent advances in diagnostic and therapeutic methods, there are yet no reliable biomarkers identifying the complex pathways contributing to these pathologies. The development of new approaches for early diagnosis and new therapies, together with the identification of non-invasive and more cost-effective diagnostic biomarkers, is one of the main trends in NDD biomedical research. Here we summarize data on peripheral biomarkers, biofluids (cerebrospinal fluid and blood plasma), and peripheral blood cells (platelets (PLTs) and red blood cells (RBCs)), reported so far for the three most common NDDs-Alzheimer's disease (AD), Parkinson's disease (PD), and amyotrophic lateral sclerosis (ALS). PLTs and RBCs, beyond their primary physiological functions, are increasingly recognized as valuable sources of biomarkers for NDDs. Special attention is given to the morphological and nanomechanical signatures of PLTs and RBCs as biophysical markers for the three pathologies. Modifications of the surface nanostructure and morphometric and nanomechanical signatures of PLTs and RBCs from patients with AD, PD, and ALS have been revealed by atomic force microscopy (AFM). AFM is currently experiencing rapid and widespread adoption in biomedicine and clinical medicine, in particular for early diagnostics of various medical conditions. AFM is a unique instrument without an analog, allowing the generation of three-dimensional cell images with extremely high spatial resolution at near-atomic scale, which are complemented by insights into the mechanical properties of cells and subcellular structures. Data demonstrate that AFM can distinguish between the three pathologies and the normal, healthy state. The specific PLT and RBC signatures can serve as biomarkers in combination with the currently used diagnostic tools. We highlight the strong correlation of the morphological and nanomechanical signatures between RBCs and PLTs in PD, ALS, and AD.
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Affiliation(s)
- Stefka G. Taneva
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, “Acad. G. Bontchev” Str. 21, 1113 Sofia, Bulgaria; (S.T.); (T.A.)
| | - Svetla Todinova
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, “Acad. G. Bontchev” Str. 21, 1113 Sofia, Bulgaria; (S.T.); (T.A.)
| | - Tonya Andreeva
- Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, “Acad. G. Bontchev” Str. 21, 1113 Sofia, Bulgaria; (S.T.); (T.A.)
- Faculty of Life Sciences, Reutlingen University, Alteburgstraße 150, D-72762 Reutlingen, Germany
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24
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Hällqvist J, Pinto RC, Heywood WE, Cordey J, Foulkes AJM, Slattery CF, Leckey CA, Murphy EC, Zetterberg H, Schott JM, Mills K, Paterson RW. A Multiplexed Urinary Biomarker Panel Has Potential for Alzheimer's Disease Diagnosis Using Targeted Proteomics and Machine Learning. Int J Mol Sci 2023; 24:13758. [PMID: 37762058 PMCID: PMC10531486 DOI: 10.3390/ijms241813758] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 08/24/2023] [Accepted: 08/28/2023] [Indexed: 09/29/2023] Open
Abstract
As disease-modifying therapies are now available for Alzheimer's disease (AD), accessible, accurate and affordable biomarkers to support diagnosis are urgently needed. We sought to develop a mass spectrometry-based urine test as a high-throughput screening tool for diagnosing AD. We collected urine from a discovery cohort (n = 11) of well-characterised individuals with AD (n = 6) and their asymptomatic, CSF biomarker-negative study partners (n = 5) and used untargeted proteomics for biomarker discovery. Protein biomarkers identified were taken forward to develop a high-throughput, multiplexed and targeted proteomic assay which was tested on an independent cohort (n = 21). The panel of proteins identified are known to be involved in AD pathogenesis. In comparing AD and controls, a panel of proteins including MIEN1, TNFB, VCAM1, REG1B and ABCA7 had a classification accuracy of 86%. These proteins have been previously implicated in AD pathogenesis. This suggests that urine-targeted mass spectrometry has potential utility as a diagnostic screening tool in AD.
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Affiliation(s)
- Jenny Hällqvist
- Translational Mass Spectrometry Research Group, Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; (J.H.); (K.M.)
| | - Rui C. Pinto
- Faculty of Medicine, School of Public Health, Imperial College London, London SW7 2BX, UK
| | - Wendy E. Heywood
- Translational Mass Spectrometry Research Group, Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; (J.H.); (K.M.)
| | - Jonjo Cordey
- Translational Mass Spectrometry Research Group, Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; (J.H.); (K.M.)
| | | | | | - Claire A. Leckey
- Translational Mass Spectrometry Research Group, Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; (J.H.); (K.M.)
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Eimear C. Murphy
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, S-431 80 Mölndal, Sweden
- UK Dementia Research Institute, UCL, London WC1E 6BT, UK
| | - Jonathan M. Schott
- National Hospital for Neurology and Neurosurgery, Queen Square London, London WC1N 3BG, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
| | - Kevin Mills
- Translational Mass Spectrometry Research Group, Genetics and Genomic Medicine, UCL Great Ormond Street Institute of Child Health, London WC1N 1EH, UK; (J.H.); (K.M.)
| | - Ross W. Paterson
- National Hospital for Neurology and Neurosurgery, Queen Square London, London WC1N 3BG, UK
- Darent Valley Hospital, Dartford DA2 8DA, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, S-431 80 Mölndal, Sweden
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25
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Brum WS, Cullen NC, Janelidze S, Ashton NJ, Zimmer ER, Therriault J, Benedet AL, Rahmouni N, Tissot C, Stevenson J, Servaes S, Triana-Baltzer G, Kolb HC, Palmqvist S, Stomrud E, Rosa-Neto P, Blennow K, Hansson O. A two-step workflow based on plasma p-tau217 to screen for amyloid β positivity with further confirmatory testing only in uncertain cases. NATURE AGING 2023; 3:1079-1090. [PMID: 37653254 PMCID: PMC10501903 DOI: 10.1038/s43587-023-00471-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Accepted: 07/18/2023] [Indexed: 09/02/2023]
Abstract
Cost-effective strategies for identifying amyloid-β (Aβ) positivity in patients with cognitive impairment are urgently needed with recent approvals of anti-Aβ immunotherapies for Alzheimer's disease (AD). Blood biomarkers can accurately detect AD pathology, but it is unclear whether their incorporation into a full diagnostic workflow can reduce the number of confirmatory cerebrospinal fluid (CSF) or positron emission tomography (PET) tests needed while accurately classifying patients. We evaluated a two-step workflow for determining Aβ-PET status in patients with mild cognitive impairment (MCI) from two independent memory clinic-based cohorts (n = 348). A blood-based model including plasma tau protein 217 (p-tau217), age and APOE ε4 status was developed in BioFINDER-1 (area under the curve (AUC) = 89.3%) and validated in BioFINDER-2 (AUC = 94.3%). In step 1, the blood-based model was used to stratify the patients into low, intermediate or high risk of Aβ-PET positivity. In step 2, we assumed referral only of intermediate-risk patients to CSF Aβ42/Aβ40 testing, whereas step 1 alone determined Aβ-status for low- and high-risk groups. Depending on whether lenient, moderate or stringent thresholds were used in step 1, the two-step workflow overall accuracy for detecting Aβ-PET status was 88.2%, 90.5% and 92.0%, respectively, while reducing the number of necessary CSF tests by 85.9%, 72.7% and 61.2%, respectively. In secondary analyses, an adapted version of the BioFINDER-1 model led to successful validation of the two-step workflow with a different plasma p-tau217 immunoassay in patients with cognitive impairment from the TRIAD cohort (n = 84). In conclusion, using a plasma p-tau217-based model for risk stratification of patients with MCI can substantially reduce the need for confirmatory testing while accurately classifying patients, offering a cost-effective strategy to detect AD in memory clinic settings.
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Affiliation(s)
- Wagner S Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
| | - Nicholas C Cullen
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience, King's College London, London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia, South London and Maudsley NHS Foundation, London, UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Eduardo R Zimmer
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Department of Pharmacology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- Graduate Program in Biological Sciences: Pharmacology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
- McGill Centre for Studies in Aging, McGill University, Montreal, Québec, Canada
| | - Joseph Therriault
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Québec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Québec, Canada
| | - Andrea L Benedet
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Nesrine Rahmouni
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Québec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Québec, Canada
| | - Cécile Tissot
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Québec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Québec, Canada
| | - Jenna Stevenson
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Québec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Québec, Canada
| | - Stijn Servaes
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Québec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Québec, Canada
| | | | - Hartmuth C Kolb
- Neuroscience Biomarkers, Janssen Research & Development, La Jolla, CA, USA
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Pedro Rosa-Neto
- Translational Neuroimaging Laboratory, McGill Research Centre for Studies in Aging, Montreal, Québec, Canada
- Department of Neurology and Neurosurgery, Faculty of Medicine, McGill University, Montreal, Québec, Canada
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, Malmö, Sweden.
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26
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Wang J, Chen M, Masters CL, Wang YJ. Translating blood biomarkers into clinical practice for Alzheimer's disease: Challenges and perspectives. Alzheimers Dement 2023; 19:4226-4236. [PMID: 37218404 DOI: 10.1002/alz.13116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 03/23/2023] [Accepted: 04/04/2023] [Indexed: 05/24/2023]
Abstract
Early and accurate diagnosis of Alzheimer's disease (AD) in clinical practice is urgent with advances in AD treatment. Blood biomarker assays are preferential diagnostic tools for widespread clinical use with the advantages of being less invasive, cost effective, and easily accessible, and they have shown good performance in research cohorts. However, in community-based populations with maximum heterogeneity, great challenges are still faced in diagnosing AD based on blood biomarkers in terms of accuracy and robustness. Here, we analyze these challenges, including the confounding impact of systemic and biological factors, small changes in blood biomarkers, and difficulty in detecting early changes. Furthermore, we provide perspectives on several potential strategies to overcome these challenges for blood biomarkers to bridge the gap from research to clinical practice.
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Affiliation(s)
- Jun Wang
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, China
- Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China
| | - Ming Chen
- Department of Clinical Laboratory Medicine, Southwest Hospital, Third Military Medical University, Chongqing, China
| | - Colin L Masters
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - Yan-Jiang Wang
- Department of Neurology and Centre for Clinical Neuroscience, Daping Hospital, Third Military Medical University, Chongqing, China
- Chongqing Key Laboratory of Ageing and Brain Diseases, Chongqing, China
- State Key Laboratory of Trauma, Burns, and Combined Injury, Third Military Medical University, Chongqing, China
- Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
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27
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Ferretti G, Serafini S, Angiolillo A, Monterosso P, Di Costanzo A, Matrone C. Advances in peripheral blood biomarkers of patients with Alzheimer's disease: Moving closer to personalized therapies. Biomed Pharmacother 2023; 165:115094. [PMID: 37392653 DOI: 10.1016/j.biopha.2023.115094] [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: 04/16/2023] [Revised: 06/17/2023] [Accepted: 06/27/2023] [Indexed: 07/03/2023] Open
Abstract
Recently, measurable peripheral biomarkers in the plasma of patients with Alzheimer's disease (AD) have gained considerable clinical interest. Several studies have identified one or more blood signatures that may facilitate the development of novel diagnostic and therapeutic strategies. For instance, changes in peripheral amyloid β42 (Aβ42) levels have been largely investigated in patients with AD and correlated with the progression of the pathology, although with controversial results. In addition, tumor necrosis factor α (TNFα) has been identified as an inflammatory biomarker strongly associated with AD, and several studies have consistently suggested the pharmacological targeting of TNFα to reduce systemic inflammation and prevent neurotoxicity in AD. Moreover, alterations in plasma metabolite levels appear to predict the progression of systemic processes relevant to brain functions. In this study, we analyzed the changes in the levels of Aβ42, TNFα, and plasma metabolites in subjects with AD and compared the results with those in healthy elderly (HE) subjects. Differences in plasma metabolites of patients with AD were analyzed with respect to Aβ42, TNFα, and the Mini-Mental State Examination (MMSE) score, searching for plasma signatures that changed simultaneously. In addition, the phosphorylation levels of the Tyr682 residue of the amyloid precursor protein (APP), which we previously proposed as a biomarker of AD, were measured in five HE and five AD patients, in whom the levels of Aβ42, TNFα, and two plasma lipid metabolites increased simultaneously. Overall, this study highlights the potential of combining different plasma signatures to define specific clinical phenotypes of patient subgroups, thus paving the way for the stratification of patients with AD and development of personalized approaches.
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Affiliation(s)
- Gabriella Ferretti
- Unit of Pharmacology, Department of Neuroscience, Faculty of Medicine, University of Naples Federico II, Via Pansini, 5 80131 Naples, Italy
| | - Sara Serafini
- Unit of Pharmacology, Department of Neuroscience, Faculty of Medicine, University of Naples Federico II, Via Pansini, 5 80131 Naples, Italy
| | - Antonella Angiolillo
- Department of Medicine and Health Sciences, Center for Research and Training in Aging Medicine, University of Molise, 86100 Campobasso, Italy
| | - Paola Monterosso
- Unit of Pharmacology, Department of Neuroscience, Faculty of Medicine, University of Naples Federico II, Via Pansini, 5 80131 Naples, Italy
| | - Alfonso Di Costanzo
- Department of Medicine and Health Sciences, Center for Research and Training in Aging Medicine, University of Molise, 86100 Campobasso, Italy
| | - Carmela Matrone
- Unit of Pharmacology, Department of Neuroscience, Faculty of Medicine, University of Naples Federico II, Via Pansini, 5 80131 Naples, Italy.
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28
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Yu L, Boyle PA, Janelidze S, Petyuk VA, Wang T, Bennett DA, Hansson O, Schneider JA. Plasma p-tau181 and p-tau217 in discriminating PART, AD and other key neuropathologies in older adults. Acta Neuropathol 2023; 146:1-11. [PMID: 37031430 PMCID: PMC10261204 DOI: 10.1007/s00401-023-02570-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 03/29/2023] [Accepted: 03/30/2023] [Indexed: 04/10/2023]
Abstract
We examined whether plasma p-tau181 and p-tau217 are specific biomarkers of pathologically confirmed Alzheimer's disease (AD). In particular, we investigated the utility of plasma p-tau for differentiating AD from primary age-related tauopathy (PART), as well as AD with mixed pathologies. Data came from 269 older adults who participated in the Religious Orders Study or the Rush Memory and Aging Project. Blood samples were collected during annual clinical evaluations. Participants died and underwent brain autopsy. P-tau181 and p-tau217 were quantified in the plasma samples proximate to death (average interval before death: 1.4 years) using Lilly-developed MSD immunoassays. Uniform neuropathologic evaluations assessed AD, PART, and other common degenerative and cerebrovascular conditions. Plasma p-tau217 was more strongly correlated with brain β-amyloid and paired helical filament tau (PHFtau) tangles than p-tau181. Both p-tau markers were associated with greater odds of AD, but p-tau217 had higher accuracy (area under the ROC curve (AUC): 0.83) than p-tau181 (AUC: 0.76). Plasma p-tau markers were almost exclusively associated with AD pathologic indices with the exception of cerebral amyloid angiopathy. Compared to p-tau181, p-tau217 showed a higher AUC (0.82 versus 0.74) in differentiating AD from PART. For either p-tau, we did not observe a level difference between individuals with AD alone and those with mixed AD pathologies. In summary, plasma p-tau181and p-tau217 were specifically associated with AD pathological changes. Further, our data provide initial evidence that p-tau217 may be able to differentiate between AD and PART in individuals with comparable burdens of tau tangle pathology. These results demonstrate the specificity of p-tau217 for AD, supporting its use to identify patients suitable for anti-AD therapies including β-amyloid immunotherapies.
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Affiliation(s)
- Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison Street, Suite 1000, Chicago, IL, 60612, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Patricia A Boyle
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison Street, Suite 1000, Chicago, IL, 60612, USA
- Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden
| | | | - Tianhao Wang
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison Street, Suite 1000, Chicago, IL, 60612, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison Street, Suite 1000, Chicago, IL, 60612, USA
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden.
- Memory Clinic, Skåne University Hospital, SE-205 02, Malmö, Sweden.
| | - Julie A Schneider
- Rush Alzheimer's Disease Center, Rush University Medical Center, 1750 W Harrison Street, Suite 1000, Chicago, IL, 60612, USA.
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA.
- Department of Pathology, Rush University Medical Center, Chicago, IL, USA.
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29
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Chen W, Lin C, Su F, Fang Y, Liu G, Chen YC, Zhou X, Yao X, Ashford CB, Li F, Ashford JW, Fu Q, Pei Z. Early Diagnosis of Mild Cognitive Impairment due to Alzheimer's Disease Using a Composite of MemTrax and Blood Biomarkers. J Alzheimers Dis 2023:JAD230182. [PMID: 37355900 DOI: 10.3233/jad-230182] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/26/2023]
Abstract
BACKGROUND Accessible measurements for the early detection of mild cognitive impairment (MCI) due to Alzheimer's disease (AD) are urgently needed to address the increasing prevalence of AD. OBJECTIVE To determine the benefits of a composite MemTrax Memory Test and AD-related blood biomarker assessment for the early detection of MCI-AD in non-specialty clinics. METHODS The MemTrax Memory Test and Montreal Cognitive Assessment were administered to 99 healthy seniors with normal cognitive function and 101 patients with MCI-AD; clinical manifestation and peripheral blood samples were collected. We evaluated correlations between the MemTrax Memory Test and blood biomarkers using Spearman's rank correlation analyses and then built discrimination models using various machine learning approaches that combined the MemTrax Memory Test and blood biomarker results. The models' performances were assessed according to the areas under the receiver operating characteristic curve. RESULTS The MemTrax Memory Test and Montreal Cognitive Assessment areas under the curve for differentiating patients with MCI-AD from the healthy controls were similar. The MemTrax Memory Test strongly correlated with phosphorylated tau 181 and amyloid-β 42/40. The area under the curve for the best composite MemTrax Memory Test and blood biomarker model was 0.975 (95% confidence interval: 0.950-0.999). CONCLUSION Combining MemTrax Memory Test and blood biomarker results is a promising new technique for the early detection of MCI-AD.
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Affiliation(s)
- Weineng Chen
- Department of Neurology, The First Affiliated Hospital, Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases; National Key Clinical Department and Key Discipline of Neurology, Sun Yat-sen University, Guangzhou, China
| | - Cha Lin
- Neurobiology Research Center, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Fengjuan Su
- Department of Neurology, The First Affiliated Hospital, Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases; National Key Clinical Department and Key Discipline of Neurology, Sun Yat-sen University, Guangzhou, China
| | - Yingying Fang
- Department of Neurology, The First Affiliated Hospital, Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases; National Key Clinical Department and Key Discipline of Neurology, Sun Yat-sen University, Guangzhou, China
| | - Ganqiang Liu
- Neurobiology Research Center, School of Medicine, Shenzhen Campus of Sun Yat-sen University, Shenzhen, Guangdong, China
| | - Yu-Chian Chen
- The School of Intelligent Systems Engineering, Sun Yat-sen University, Shenzhen, China
| | - Xianbo Zhou
- Center for Alzheimer's Research, Washington Institute of Clinical Research, Vienna, VA, USA
- AstraNeura, Co., Ltd., Shanghai, China
| | - Xiaoli Yao
- Department of Neurology, The First Affiliated Hospital, Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases; National Key Clinical Department and Key Discipline of Neurology, Sun Yat-sen University, Guangzhou, China
| | | | - Feng Li
- Moore Threads Co., Ltd., Beijing, China
| | - J Wesson Ashford
- Department of Psychiatry & Behavioral Sciences, Stanford University, War Related Illness & Injury Study Center, VA Palo Alto Health Care System, Palo Alto, CA, USA
| | - Qingling Fu
- Otorhinolaryngology Hospital, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Zhong Pei
- Department of Neurology, The First Affiliated Hospital, Guangdong Provincial Key Laboratory of Diagnosis and Treatment of Major Neurological Diseases; National Key Clinical Department and Key Discipline of Neurology, Sun Yat-sen University, Guangzhou, China
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Telser J, Grossmann K, Wohlwend N, Risch L, Saely CH, Werner P. Phosphorylated tau in Alzheimer's disease. Adv Clin Chem 2023; 116:31-111. [PMID: 37852722 DOI: 10.1016/bs.acc.2023.05.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2023]
Abstract
There is a need for blood biomarkers to detect individuals at different Alzheimer's disease (AD) stages because obtaining cerebrospinal fluid-based biomarkers is invasive and costly. Plasma phosphorylated tau proteins (p-tau) have shown potential as such biomarkers. This systematic review was conducted according to the PRISMA guidelines and aimed to determine whether quantification of plasma tau phosphorylated at threonine 181 (p-tau181), threonine 217 (p-tau217) and threonine 231 (p-tau231) is informative in the diagnosis of AD. All p-tau isoforms increase as a function of Aβ-accumulation and discriminate healthy individuals from those at preclinical AD stages with high accuracy. P-tau231 increases earliest, followed by p-tau181 and p-tau217. In advanced stages, all p-tau isoforms are associated with the clinical classification of AD and increase with disease severity, with the greatest increase seen for p-tau217. This is also reflected by a better correlation of p-tau217 with Aβ scans, whereas both, p-tau217 and p-tau181 correlated equally with tau scans. However, at the very advanced stages, p-tau181 begins to plateau, which may mirror the trajectory of the Aβ pathology and indicate an association with a more intermediate risk of AD. Across the AD continuum, the incremental increase in all biomarkers is associated with structural changes in widespread brain regions and underlying cognitive decline. Furthermore, all isoforms differentiate AD from non-AD neurodegenerative disorders, making them specific for AD. Incorporating p-tau181, p-tau217 and p-tau231 in clinical use requires further studies to examine ideal cut-points and harmonize assays.
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Affiliation(s)
- Julia Telser
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Laboratory Dr. Risch, Vaduz, Liechtenstein
| | - Kirsten Grossmann
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Laboratory Dr. Risch, Vaduz, Liechtenstein
| | - Niklas Wohlwend
- Laboratory Dr. Risch, Vaduz, Liechtenstein; Department of Internal Medicine Spital Grabs, Spitalregion Rheintal Werdenberg Sarganserland, Grabs, Switzerland
| | - Lorenz Risch
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Laboratory Dr. Risch, Vaduz, Liechtenstein; University Institute of Clinical Chemistry, University Hospital and University of Bern, Inselspital, Bern, Switzerland
| | - Christoph H Saely
- Faculty of Medical Science, Private University in the Principality of Liechtenstein, Triesen, Liechtenstein; Vorarlberg Institute for Vascular Investigation and Treatment (VIVIT), Feldkirch, Austria
| | - Philipp Werner
- Department of Neurology, State Hospital of Rankweil, Academic Teaching Hospital, Rankweil, Austria.
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Aguillon D, Langella S, Chen Y, Sanchez J, Su Y, Vila-Castelar C, Vasquez D, Zetterberg H, Hansson O, Dage JL, Janelidze S, Chen K, Fox-Fuller JT, Aduen P, Martinez JE, Garcia G, Baena A, Guzman C, Johnson K, Sperling RA, Blennow K, Reiman EM, Lopera F, Quiroz YT. Plasma p-tau217 predicts in vivo brain pathology and cognition in autosomal dominant Alzheimer's disease. Alzheimers Dement 2023; 19:2585-2594. [PMID: 36571821 PMCID: PMC10271963 DOI: 10.1002/alz.12906] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2022] [Revised: 11/16/2022] [Accepted: 11/17/2022] [Indexed: 12/27/2022]
Abstract
INTRODUCTION Plasma-measured tau phosphorylated at threonine 217 (p-tau217) is a potential non-invasive biomarker of Alzheimer's disease (AD). We investigated whether plasma p-tau217 predicts subsequent cognition and positron emission tomography (PET) markers of pathology in autosomal dominant AD. METHODS We analyzed baseline levels of plasma p-tau217 and its associations with amyloid PET, tau PET, and word list delayed recall measured 7.61 years later in non-demented age- and education-matched presenilin-1 E280A carriers (n = 24) and non-carrier (n = 20) family members. RESULTS Carriers had higher plasma p-tau217 levels than non-carriers. Baseline plasma p-tau217 was associated with subsequent amyloid and tau PET pathology levels and cognitive function. DISCUSSION Our findings suggest that plasma p-tau217 predicts subsequent brain pathological burden and memory performance in presenilin-1 E280A carriers. These results provide support for plasma p-tau217 as a minimally invasive diagnostic and prognostic biomarker for AD, with potential utility in clinical practice and trials. HIGHLIGHTS Non-demented presenilin-1 E280A carriers have higher plasma tau phosphorylated at threonine 217 (p-tau217) than do age-matched non-carriers. Higher baseline p-tau217 is associated with greater future amyloid positron emission tomography (PET) pathology burden. Higher baseline p-tau217 is associated with greater future tau PET pathology burden. Higher baseline p-tau217 is associated with worse future memory performance.
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Affiliation(s)
- David Aguillon
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellin, Colombia
| | | | | | - Justin Sanchez
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Yi Su
- Banner Alzheimer’s Institute, Phoenix, AZ, USA
| | | | - Daniel Vasquez
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellin, Colombia
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Oskar Hansson
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, Sweden
| | - Jeffrey L. Dage
- Indiana University School of Medicine, Indianapolis, IN, USA
| | | | - Kewei Chen
- Banner Alzheimer’s Institute, Phoenix, AZ, USA
| | - Joshua T. Fox-Fuller
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychological and Brain Sciences, Boston University, Boston, USA
| | - Paula Aduen
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jairo E. Martinez
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Department of Psychological and Brain Sciences, Boston University, Boston, USA
| | - Gloria Garcia
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellin, Colombia
| | - Ana Baena
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellin, Colombia
| | - Claudia Guzman
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellin, Colombia
| | - Keith Johnson
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Reisa A. Sperling
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | | | - Francisco Lopera
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellin, Colombia
| | - Yakeel T. Quiroz
- Grupo de Neurociencias de Antioquia, Facultad de Medicina, Universidad de Antioquia, Medellin, Colombia
- Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
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Pan F, Huang Y, Cai X, Wang Y, Guan Y, Deng J, Yang D, Zhu J, Zhao Y, Xie F, Fang Z, Guo Q. Integrated algorithm combining plasma biomarkers and cognitive assessments accurately predicts brain β-amyloid pathology. COMMUNICATIONS MEDICINE 2023; 3:65. [PMID: 37165172 PMCID: PMC10172320 DOI: 10.1038/s43856-023-00295-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Accepted: 04/27/2023] [Indexed: 05/12/2023] Open
Abstract
BACKGROUND Accurate prediction of cerebral amyloidosis with easily available indicators is urgently needed for diagnosis and treatment of Alzheimer's disease (AD). METHODS We examined plasma Aβ42, Aβ40, T-tau, P-tau181, and NfL, with APOE genotypes, cognitive test scores and key demographics in a large Chinese cohort (N = 609, aged 40 to 84 years) covering full AD spectrum. Data-driven integrated computational models were developed to predict brain β-amyloid (Aβ) pathology. RESULTS Our computational models accurately predict brain Aβ positivity (area under the ROC curves (AUC) = 0.94). The results are validated in Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. Particularly, the models have the highest prediction power (AUC = 0.97) in mild cognitive impairment (MCI) participants. Three levels of models are designed with different accuracies and complexities. The model which only consists of plasma biomarkers can predict Aβ positivity in amnestic MCI (aMCI) patients with AUC = 0.89. Generally the models perform better in participants without comorbidities or family histories. CONCLUSIONS The innovative integrated models provide opportunity to assess Aβ pathology in a non-invasive and cost-effective way, which might facilitate AD-drug development, early screening, clinical diagnosis and prognosis evaluation.
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Affiliation(s)
- Fengfeng Pan
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yanlu Huang
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Xiao Cai
- Department of Data & Analytics, WuXi Diagnostics Innovation Research Institute, Shanghai, China
| | - Ying Wang
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China
| | - Yihui Guan
- PET Center, Huashan Hospital, Fudan University, Shanghai, China
| | - Jiale Deng
- Department of Data & Analytics, WuXi Diagnostics Innovation Research Institute, Shanghai, China
| | - Dake Yang
- Department of Data & Analytics, WuXi Diagnostics Innovation Research Institute, Shanghai, China
| | - Jinhang Zhu
- Department of Data & Analytics, WuXi Diagnostics Innovation Research Institute, Shanghai, China
| | - Yike Zhao
- Department of Data & Analytics, WuXi Diagnostics Innovation Research Institute, Shanghai, China
| | - Fang Xie
- PET Center, Huashan Hospital, Fudan University, Shanghai, China.
| | - Zhuo Fang
- Department of Data & Analytics, WuXi Diagnostics Innovation Research Institute, Shanghai, China.
| | - Qihao Guo
- Department of Gerontology, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai, China.
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Jack CR, Wiste HJ, Algeciras-Schimnich A, Figdore DJ, Schwarz CG, Lowe VJ, Ramanan VK, Vemuri P, Mielke MM, Knopman DS, Graff-Radford J, Boeve BF, Kantarci K, Cogswell PM, Senjem ML, Gunter JL, Therneau TM, Petersen RC. Predicting amyloid PET and tau PET stages with plasma biomarkers. Brain 2023; 146:2029-2044. [PMID: 36789483 PMCID: PMC10151195 DOI: 10.1093/brain/awad042] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 12/20/2022] [Accepted: 01/21/2023] [Indexed: 02/16/2023] Open
Abstract
Staging the severity of Alzheimer's disease pathology using biomarkers is useful for therapeutic trials and clinical prognosis. Disease staging with amyloid and tau PET has face validity; however, this would be more practical with plasma biomarkers. Our objectives were, first, to examine approaches for staging amyloid and tau PET and, second, to examine prediction of amyloid and tau PET stages using plasma biomarkers. Participants (n = 1136) were enrolled in either the Mayo Clinic Study of Aging or the Alzheimer's Disease Research Center; had a concurrent amyloid PET, tau PET and blood draw; and met clinical criteria for cognitively unimpaired (n = 864), mild cognitive impairment (n = 148) or Alzheimer's clinical syndrome with dementia (n = 124). The latter two groups were combined into a cognitively impaired group (n = 272). We used multinomial regression models to estimate discrimination [concordance (C) statistics] among three amyloid PET stages (low, intermediate, high), four tau PET stages (Braak 0, 1-2, 3-4, 5-6) and a combined amyloid and tau PET stage (none/low versus intermediate/high severity) using plasma biomarkers as predictors separately within unimpaired and impaired individuals. Plasma analytes, p-tau181, Aβ1-42 and Aβ1-40 (analysed as the Aβ42/Aβ40 ratio), glial fibrillary acidic protein and neurofilament light chain were measured on the HD-X Simoa Quanterix platform. Plasma p-tau217 was also measured in a subset (n = 355) of cognitively unimpaired participants using the Lilly Meso Scale Discovery assay. Models with all Quanterix plasma analytes along with risk factors (age, sex and APOE) most often provided the best discrimination among amyloid PET stages (C = 0.78-0.82). Models with p-tau181 provided similar discrimination of tau PET stages to models with all four plasma analytes (C = 0.72-0.85 versus C = 0.73-0.86). Discriminating a PET proxy of intermediate/high from none/low Alzheimer's disease neuropathological change with all four Quanterix plasma analytes was excellent but not better than p-tau181 only (C = 0.88 versus 0.87 for unimpaired and C = 0.91 versus 0.90 for impaired). Lilly p-tau217 outperformed the Quanterix p-tau181 assay for discriminating high versus intermediate amyloid (C = 0.85 versus 0.74) but did not improve over a model with all Quanterix plasma analytes and risk factors (C = 0.85 versus 0.83). Plasma analytes along with risk factors can discriminate between amyloid and tau PET stages and between a PET surrogate for intermediate/high versus none/low neuropathological change with accuracy in the acceptable to excellent range. Combinations of plasma analytes are better than single analytes for many staging predictions with the exception that Quanterix p-tau181 alone usually performed equivalently to combinations of Quanterix analytes for tau PET discrimination.
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Affiliation(s)
- Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Heather J Wiste
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Dan J Figdore
- Department of Laboratory Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Val J Lowe
- Department of Nuclear Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | - Vijay K Ramanan
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Michelle M Mielke
- Department of Epidemiology and Prevention, Wake Forest University School of Medicine, Winston-Salem, NC 27101, USA
| | - David S Knopman
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Bradley F Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Kejal Kantarci
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | - Terry M Therneau
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN 55905, USA
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Hansson O, Blennow K, Zetterberg H, Dage J. Blood biomarkers for Alzheimer's disease in clinical practice and trials. NATURE AGING 2023; 3:506-519. [PMID: 37202517 PMCID: PMC10979350 DOI: 10.1038/s43587-023-00403-3] [Citation(s) in RCA: 33] [Impact Index Per Article: 33.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 03/21/2023] [Indexed: 05/20/2023]
Abstract
Blood-based biomarkers hold great promise to revolutionize the diagnostic and prognostic work-up of Alzheimer's disease (AD) in clinical practice. This is very timely, considering the recent development of anti-amyloid-β (Aβ) immunotherapies. Several assays for measuring phosphorylated tau (p-tau) in plasma exhibit high diagnostic accuracy in distinguishing AD from all other neurodegenerative diseases in patients with cognitive impairment. Prognostic models based on plasma p-tau levels can also predict future development of AD dementia in patients with mild cognitive complaints. The use of such high-performing plasma p-tau assays in the clinical practice of specialist memory clinics would reduce the need for more costly investigations involving cerebrospinal fluid samples or positron emission tomography. Indeed, blood-based biomarkers already facilitate identification of individuals with pre-symptomatic AD in the context of clinical trials. Longitudinal measurements of such biomarkers will also improve the detection of relevant disease-modifying effects of new drugs or lifestyle interventions.
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Affiliation(s)
- Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Faculty of Medicine, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, Lund, Sweden.
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for 27 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, WI, USA
| | - Jeffrey Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, IN, USA
- Indiana Alzheimer's Disease Research Center, Indiana University School of Medicine, Indianapolis, IN, USA
- Stark Neurosciences Research Institute, Indiana University School of Medicine, Indianapolis, IN, USA
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Binette AP, Janelidze S, Cullen N, Dage JL, Bateman RJ, Zetterberg H, Blennow K, Stomrud E, Mattsson-Carlgren N, Hansson O. Confounding factors of Alzheimer's disease plasma biomarkers and their impact on clinical performance. Alzheimers Dement 2023; 19:1403-1414. [PMID: 36152307 PMCID: PMC10499000 DOI: 10.1002/alz.12787] [Citation(s) in RCA: 46] [Impact Index Per Article: 46.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 07/27/2022] [Accepted: 07/31/2022] [Indexed: 11/10/2022]
Abstract
INTRODUCTION Plasma biomarkers will likely revolutionize the diagnostic work-up of Alzheimer's disease (AD) globally. Before widespread use, we need to determine if confounding factors affect the levels of these biomarkers, and their clinical utility. METHODS Participants with plasma and CSF biomarkers, creatinine, body mass index (BMI), and medical history data were included (BioFINDER-1: n = 748, BioFINDER-2: n = 421). We measured beta-amyloid (Aβ42, Aβ40), phosphorylated tau (p-tau217, p-tau181), neurofilament light (NfL), and glial fibrillary acidic protein (GFAP). RESULTS In both cohorts, creatinine and BMI were the main factors associated with NfL, GFAP, and to a lesser extent with p-tau. However, adjustment for BMI and creatinine had only minor effects in models predicting either the corresponding levels in CSF or subsequent development of dementia. DISCUSSION Creatinine and BMI are related to certain plasma biomarkers levels, but they do not have clinically relevant confounding effects for the vast majority of individuals. HIGHLIGHTS Creatinine and body mass index (BMI) are related to certain plasma biomarker levels. Adjusting for creatinine and BMI has minor influence on plasma-cerebrospinal fluid (CSF) associations. Adjusting for creatinine and BMI has minor influence on prediction of dementia using plasma biomarkers.
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Affiliation(s)
- Alexa Pichet Binette
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Nicholas Cullen
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Jeffrey L. Dage
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Randall J. Bateman
- Department of Neurology, Washington University School of Medicine, St Louis, Missouri
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Palmqvist S, Stomrud E, Cullen N, Janelidze S, Manuilova E, Jethwa A, Bittner T, Eichenlaub U, Suridjan I, Kollmorgen G, Riepe M, von Arnim CA, Tumani H, Hager K, Heidenreich F, Mattsson-Carlgren N, Zetterberg H, Blennow K, Hansson O. An accurate fully automated panel of plasma biomarkers for Alzheimer's disease. Alzheimers Dement 2023; 19:1204-1215. [PMID: 35950735 PMCID: PMC9918613 DOI: 10.1002/alz.12751] [Citation(s) in RCA: 47] [Impact Index Per Article: 47.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2022] [Revised: 05/27/2022] [Accepted: 06/10/2022] [Indexed: 12/23/2022]
Abstract
INTRODUCTION There is a great need for fully automated plasma assays that can measure amyloid beta (Aβ) pathology and predict future Alzheimer's disease (AD) dementia. METHODS Two cohorts (n = 920) were examined: Panel A+ (n = 32 cognitively unimpaired [CU], n = 106 mild cognitive impairment [MCI], and n = 89 AD) and BioFINDER-1 (n = 461 CU, n = 232 MCI). Plasma Aβ42/Aβ40, phosphorylated tau (p-tau)181, two p-tau217 variants, ApoE4 protein, neurofilament light, and GFAP were measured using Elecsys prototype immunoassays. RESULTS The best biomarker for discriminating Aβ-positive versus Aβ-negative participants was Aβ42/Aβ40 (are under the curve [AUC] 0.83-0.87). Combining Aβ42/Aβ40, p-tau181, and ApoE4 improved the AUCs significantly (0.90 to 0.93; P< 0.01). Adding additional biomarkers had marginal effects (ΔAUC ≤0.01). In BioFINDER, p-tau181, p-tau217, and ApoE4 predicted AD dementia within 6 years in CU (AUC 0.88) and p-tau181, p-tau217, and Aβ42/Aβ40 in MCI (AUC 0.87). DISCUSSION The high accuracies for Aβ pathology and future AD dementia using fully automated instruments are promising for implementing plasma biomarkers in clinical trials and clinical routine.
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Affiliation(s)
- Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Nicholas Cullen
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
| | | | | | | | | | | | | | - Matthias Riepe
- Division of Geriatric Psychiatry, Ulm University, Germany
| | - Christine A.F. von Arnim
- Division of Geriatrics, University Medical Center Göttingen, Georg-August-University, Goettingen, Germany
| | | | - Klaus Hager
- Institute for General Medicine and Palliative Medicine, Hannover Medical School, Germany
| | - Fedor Heidenreich
- Dept. of Neurology and Clinical Neurophysiology, Diakovere Krankenhaus Henriettenstift, Hannover, Germany
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
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Allué JA, Pascual‐Lucas M, Sarasa L, Castillo S, Sarasa M, Sáez ME, Abdel‐Latif S, Rissman RA, Terencio J. Clinical utility of an antibody-free LC-MS method to detect brain amyloid deposition in cognitively unimpaired individuals from the screening visit of the A4 Study. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2023; 15:e12451. [PMID: 37274930 PMCID: PMC10236000 DOI: 10.1002/dad2.12451] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 05/08/2023] [Accepted: 05/08/2023] [Indexed: 06/07/2023]
Abstract
INTRODUCTION This study explored the ability of plasma amyloid beta (Aβ)42/Aβ40 to identify brain amyloid deposition in cognitively unimpaired (CU) individuals. METHODS Plasma Aβ was quantified with an antibody-free high-performance liquid chromatography tandem mass spectrometry method from Araclon Biotech (ABtest-MS) in a subset of 731 CU individuals from the screening visit of the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study, to assess associations of Aβ42/Aβ40 with Aβ positron emission tomography (PET). RESULTS A model including Aβ42/Aβ40, age, apolipoprotein E ε4, and recruitment site identified Aβ PET status with an area under the curve of 0.88 and an overall accuracy of 81%. A plasma-based pre-screening step could save up to 42% of the total number of Aβ PET scans. DISCUSSION ABtest-MS accurately identified brain amyloid deposition in a population of CU individuals, supporting its implementation in AD secondary prevention trials to reduce recruitment time and costs. Although a certain degree of heterogeneity is inherent to large and multicentric trials, ABtest-MS could be more robust to pre-analytical bias compared to other immunoprecipitation mass spectrometry methods. HIGHLIGHTS Plasma amyloid beta (Aβ)42/Aβ40 accurately identified brain Aβ deposition in cognitively unimpaired individuals from the Anti-Amyloid Treatment in Asymptomatic Alzheimer's (A4) Study.The inclusion of the recruitment site in the predictive models has a non-negligible effect.A plasma biomarker-based model could reduce recruitment costs in Alzheimer's disease secondary prevention trials.Antibody-free liquid chromatography mass spectrometry methods may be more robust to pre-analytical variability than other platforms.
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Affiliation(s)
| | | | | | | | | | | | - Sara Abdel‐Latif
- Alzheimer's Therapeutic Research Institute, Keck School of MedicineUniversity of Southern CaliforniaSan DiegoCaliforniaUSA
| | - Robert A. Rissman
- Alzheimer's Therapeutic Research Institute, Keck School of MedicineUniversity of Southern CaliforniaSan DiegoCaliforniaUSA
- Department of NeurosciencesUniversity of CaliforniaSan Diego, La JollaCaliforniaUSA
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38
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Thanapornsangsuth P, Booncharoen K, Luechaipanit W, Supharatpariyakorn T, Sarutikriangkri Y, Tangnimitchok S, Likitjaroen Y, Sukprakun C, Tepmongkol S, Hemachudha T. Prospective evaluation of plasma phosphorylated tau in a real-life memory clinic in Thailand. Alzheimers Dement 2023. [PMID: 36924432 DOI: 10.1002/alz.13022] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Revised: 02/02/2023] [Accepted: 02/03/2023] [Indexed: 03/18/2023]
Abstract
INTRODUCTION Despite the substantial accuracy of plasma p-tau in diagnosing Alzheimer's disease (AD) in research cohorts, data on real-life memory clinic patients are lacking. METHODS Memory clinic patients at their early symptomatic stages were prospectively enrolled to undergo routine clinical assessment, plasma p-tau181 quantification (Simoa), amyloid and tau-positron emission tomography (PET). The diagnostic performance of plasma p-tau181, neurocognitive specialists, and regional tau-PET were compared head-to-head using amyloid-PET as the reference standard. RESULTS Plasma p-tau181 has the area under the curve (AUC), sensitivity, specificity, and accuracy of 0.84 (95% confidence interval [CI] 0.73-0.94), 0.80 (95% CI 0.64-0.90), 0.75 (95% CI 0.51-0.90), and 0.78 (95% CI 0.65-0.88) for detecting amyloid-PET positivity in early symptomatic patients, respectively. The AUC of clinical diagnosis and tau-PET were 0.70 (95% CI 0.56-0.85) and 0.88 (95% CI 0.79-0.97), respectively. DISCUSSION Plasma p-tau181 also performed well in real-life memory clinic settings and its role in clinical practice is supported.
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Affiliation(s)
- Poosanu Thanapornsangsuth
- Thai Red Cross Emerging Infectious Diseases Health Science Centre, World Health Organization Collaborating Centre for Research and Training on Viral Zoonoses, King Chulalongkorn Memorial Hospital The Thai Red Cross Society, Bangkok, Thailand.,Division of Neurology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.,Memory Clinic, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand
| | - Kittithatch Booncharoen
- Division of Neurology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.,Memory Clinic, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand.,Neurocognitive Unit, Division of Neurology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Watayuth Luechaipanit
- Thai Red Cross Emerging Infectious Diseases Health Science Centre, World Health Organization Collaborating Centre for Research and Training on Viral Zoonoses, King Chulalongkorn Memorial Hospital The Thai Red Cross Society, Bangkok, Thailand
| | - Thirawat Supharatpariyakorn
- Thai Red Cross Emerging Infectious Diseases Health Science Centre, World Health Organization Collaborating Centre for Research and Training on Viral Zoonoses, King Chulalongkorn Memorial Hospital The Thai Red Cross Society, Bangkok, Thailand
| | - Yuthachai Sarutikriangkri
- Memory Clinic, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand.,Neurocognitive Unit, Division of Neurology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Suchart Tangnimitchok
- Chulalongkorn Comprehensive Epilepsy Center of Excellence, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand
| | - Yuttachai Likitjaroen
- Division of Neurology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.,Memory Clinic, King Chulalongkorn Memorial Hospital, The Thai Red Cross Society, Bangkok, Thailand.,Neurocognitive Unit, Division of Neurology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Chanan Sukprakun
- Division of Nuclear Medicine, Department of Radiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Supatporn Tepmongkol
- Division of Nuclear Medicine, Department of Radiology, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Thiravat Hemachudha
- Thai Red Cross Emerging Infectious Diseases Health Science Centre, World Health Organization Collaborating Centre for Research and Training on Viral Zoonoses, King Chulalongkorn Memorial Hospital The Thai Red Cross Society, Bangkok, Thailand.,Division of Neurology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
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39
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Salvadó G, Ossenkoppele R, Ashton NJ, Beach TG, Serrano GE, Reiman EM, Zetterberg H, Mattsson-Carlgren N, Janelidze S, Blennow K, Hansson O. Specific associations between plasma biomarkers and postmortem amyloid plaque and tau tangle loads. EMBO Mol Med 2023; 15:e17123. [PMID: 36912178 PMCID: PMC10165361 DOI: 10.15252/emmm.202217123] [Citation(s) in RCA: 43] [Impact Index Per Article: 43.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 02/21/2023] [Accepted: 02/21/2023] [Indexed: 03/14/2023] Open
Abstract
Several promising plasma biomarkers for Alzheimer's disease have been recently developed, but their neuropathological correlates have not yet been fully determined. To investigate and compare independent associations between multiple plasma biomarkers (p-tau181, p-tau217, p-tau231, Aβ42/40, GFAP, and NfL) and neuropathologic measures of amyloid and tau, we included 105 participants from the Arizona Study of Aging and Neurodegenerative Disorders (AZSAND) with antemortem plasma samples and a postmortem neuropathological exam, 48 of whom had longitudinal p-tau217 and p-tau181. When simultaneously including plaque and tangle loads, the Aβ42/40 ratio and p-tau231 were only associated with plaques (ρAβ42/40 [95%CI] = -0.53[-0.65, -0.35], ρp-tau231 [95%CI] = 0.28[0.10, 0.43]), GFAP was only associated with tangles (ρGFAP [95%CI] = 0.39[0.17, 0.57]), and p-tau217 and p-tau181 were associated with both plaques (ρp-tau217 [95%CI] = 0.40[0.21, 0.56], ρp-tau181 [95%CI] = 0.36[0.15, 0.50]) and tangles (ρp-tau217 [95%CI] = 0.52[0.34, 0.66]; ρp-tau181 [95%CI] = 0.36[0.17, 0.52]). A model combining p-tau217 and the Aβ42/40 ratio showed the highest accuracy for predicting the presence of Alzheimer's disease neuropathological change (ADNC, AUC[95%CI] = 0.89[0.82, 0.96]) and plaque load (R2 = 0.55), while p-tau217 alone was optimal for predicting tangle load (R2 = 0.45). Our results suggest that high-performing assays of plasma p-tau217 and Aβ42/40 might be an optimal combination to assess Alzheimer's-related pathology in vivo.
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Affiliation(s)
- Gemma Salvadó
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.,Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, King's College London, London, UK.,NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley, NHS Foundation, London, UK
| | | | | | - Eric M Reiman
- Banner Alzheimer's Institute, Arizona State University and University of Arizona, Phoenix, AZ, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK.,UK Dementia Research Institute at UCL, London, UK.,Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.,Department of Neurology, Skåne University Hospital, Lund, Sweden.,Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
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40
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Advances in sample preparation and HPLC-MS/MS methods for determining amyloid-β peptide in biological samples: a review. Anal Bioanal Chem 2023:10.1007/s00216-023-04631-9. [PMID: 36877264 DOI: 10.1007/s00216-023-04631-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/28/2023] [Accepted: 02/23/2023] [Indexed: 03/07/2023]
Abstract
Alzheimer's disease (AD), a neurological disorder, is a major public health concern and the most common form of dementia. Its typical symptoms include memory loss, confusion, changes in personality, and cognitive impairment, which result in patients gradually losing independence. Over the last decades, some studies have focused on searching for effective biomarkers as early diagnostic indicators of AD. Amyloid-β (Aβ) peptides have been consolidated as reliable AD biomarkers and have been incorporated into modern diagnostic research criteria. However, quantitative analysis of Aβ peptides in biological samples remains a challenge because both the sample and the physical-chemical properties of these peptides are complex. During clinical routine, Aβ peptides are measured in the cerebrospinal fluid by immunoassays, but the availability of a specific antibody is critical-in some cases, an antibody may not exist, or its specificity may be inadequate, leading to low sensitivity and false results. HPLC-MS/MS has been reported as a sensitive and selective method for determining different fragments of Aβ peptides in biological samples simultaneously. Developments in sample preparation techniques (preconcentration platforms) such as immunoprecipitation, 96-well plate SPME, online SPME, and fiber-in-tube SPME have enabled not only effective enrichment of Aβ peptides present at trace levels in biological samples, but also efficient exclusion of interferents from the sample matrix (sample cleanup). This high extraction efficiency has provided MS platforms with higher sensitivity. Recently, methods affording LLOQ values as low as 5 pg mL-1 have been reported. Such low LLOQ values are adequate for quantifying Aβ peptides in complex matrixes including cerebrospinal fluid (CSF) and plasma samples. This review summarizes the advances in mass spectrometry (MS)-based methods for quantifying Aβ peptides and covers the period 1992-2022. Important considerations regarding the development of the HPLC-MS/MS method such as the sample preparation step, optimization of the HPLC-MS/MS parameters, and matrix effects are described. Clinical applications, difficulties related to analysis of plasma samples, and future trends of these MS/MS-based methods are also discussed.
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The association of subjective sleep characteristics and plasma biomarkers of Alzheimer's disease pathology in older cognitively unimpaired adults with higher amyloid-β burden. J Neurol 2023; 270:3008-3021. [PMID: 36806992 DOI: 10.1007/s00415-023-11626-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 02/10/2023] [Accepted: 02/12/2023] [Indexed: 02/23/2023]
Abstract
We aimed to investigate the association of subjective sleep characteristics and plasma Alzheimer's disease (AD) biomarkers in older cognitively unimpaired adults with higher amyloid-β (Aβ) burden. Unimpaired cognition was determined by education-adjusted performance for the Mini-Mental State Examination and exclusion of dementia and mild cognitive impairment via standardized neuropsychological tests. We used Pittsburgh Sleep Quality Index (PSQI) to assess subjective sleep quality. The participants also underwent examination of plasma AD biomarkers and 18F-florbetapir PET scan. Correlation and multiple linear regression analyses were used to investigate the association between subjective sleep characteristics and AD biomarkers. A total of 335 participants were included and 114 were Aβ-PET positive. Multivariable regression analysis showed sleep duration > 8 h and sleep disturbance were associated with Aβ deposition in total participants. Two multiple linear regression models were applied and the results revealed in participants with Aβ-PET (+), falling asleep at ≥ 22:00 to ≤ 23:00 was associated with higher levels of Aβ42 and Aβ42/40. Other associations with higher Aβ42/40 and standard uptake value ratio contained sleep efficiency value, sleep efficiency ≥ 75%, no/mild daytime dysfunction and PSQI score ≤ 5. Higher p-Tau-181 level was associated with sleep latency > 30 min in Aβ-PET (+) group and moderate/severe sleep disturbance in Aβ-PET (-) group. Our data suggests sleep duration ≤ 8 h and no/mild sleep disturbance may be related to less Aβ burden. In participants with Aβ deposition, falling asleep at 22:00 to 23:00, higher sleep efficiency (at least ≥ 75%), no/mild daytime dysfunction, sleep latency ≤ 30 min, and good sleep quality may help improve AD pathology.
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42
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Assessment of Plasma and Cerebrospinal Fluid Biomarkers in Different Stages of Alzheimer's Disease and Frontotemporal Dementia. Int J Mol Sci 2023; 24:ijms24021226. [PMID: 36674742 PMCID: PMC9864037 DOI: 10.3390/ijms24021226] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 12/23/2022] [Accepted: 01/05/2023] [Indexed: 01/11/2023] Open
Abstract
Alzheimer's disease (AD) is the primary type of dementia, followed by frontotemporal lobar degeneration (FTLD). They share some clinical characteristics, mainly at the early stages. So, the identification of early, specific, and minimally invasive biomarkers is required. In this study, some plasma biomarkers (Amyloid β42, p-Tau181, t-Tau, neurofilament light (NfL), TAR DNA-binding protein 43 (TDP-43)) were determined by single molecule array technology (SIMOA®) in control subjects (n = 22), mild cognitive impairment due to AD (MCI-AD, n = 33), mild dementia due to AD (n = 12), and FTLD (n = 11) patients. The correlations between plasma and cerebrospinal fluid (CSF) levels and the accuracy of plasma biomarkers for AD early diagnosis and discriminating from FTLD were analyzed. As result, plasma p-Tau181 and NfL levels correlated with the corresponding CSF levels. Additionally, plasma p-Tau181 showed good accuracy for distinguishing between the controls and AD, as well as discriminating between AD and FTLD. Moreover, plasma NfL could discriminate dementia-AD vs. controls, FTLD vs. controls, and MCI-AD vs. dementia-AD. Therefore, the determination of these biomarkers in plasma is potentially helpful in AD spectrum diagnosis, but also discriminating from FTLD. In addition, the accessibility of these potential early and specific biomarkers may be useful for AD screening protocols in the future.
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Pascual-Lucas M, Allué JA, Sarasa L, Fandos N, Castillo S, Terencio J, Sarasa M, Tartari JP, Sanabria Á, Tárraga L, Ruíz A, Marquié M, Seo SW, Jang H, Boada M. Clinical performance of an antibody-free assay for plasma Aβ42/Aβ40 to detect early alterations of Alzheimer's disease in individuals with subjective cognitive decline. Alzheimers Res Ther 2023; 15:2. [PMID: 36604729 PMCID: PMC9814201 DOI: 10.1186/s13195-022-01143-z] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 12/14/2022] [Indexed: 01/07/2023]
Abstract
BACKGROUND Accessible and cost-effective diagnostic tools are urgently needed to accurately quantify blood biomarkers to support early diagnosis of Alzheimer's disease (AD). In this study, we investigated the ability of plasma amyloid-beta (Aβ)42/Aβ40 ratio measured by an antibody-free mass-spectrometric (MS) method, ABtest-MS, to detect early pathological changes of AD. METHODS This cohort study included data from the baseline and 2-year follow-up visits from the Fundació ACE Healthy Brain Initiative (FACEHBI) study. Plasma Aβ42/Aβ40 was measured with ABtest-MS and compared to 18F-Florbetaben PET as the reference standard (cutoff for early amyloid deposition of 13.5 centiloids). Cross-validation was performed in an independent DPUK-Korean cohort. Additionally, associations of plasma Aβ42/Aβ40 with episodic memory performance and brain atrophy were assessed. RESULTS The FACEHBI cohort at baseline included 200 healthy individuals with subjective cognitive decline (SCD), of which 36 (18%) were Aβ-PET positive. Plasma Aβ42/Aβ40 levels were significantly lower in Aβ-PET positive individuals (median [interquartile range, IQR], 0.215 [0.203-0.236]) versus Aβ-PET negative subjects (median [IQR], 0.261 [0.244-0.279]) (P < .001). Plasma Aβ42/Aβ40 was significantly correlated with Aβ-PET levels (rho = -0.390; P < .001) and identified Aβ-PET status with an area under the receiver operating characteristic curve (AUC) of 0.87 (95% confidence interval [CI], 0.80-0.93). A cutoff for the Aβ42/Aβ40 ratio of 0.241 (maximum Youden index) yielded a sensitivity of 86.1% and a specificity of 80.5%. These findings were cross-validated in an independent DPUK-Korean cohort (AUC 0.86 [95% CI 0.77-0.95]). Lower plasma Aβ42/Aβ40 ratio was associated with worse episodic memory performance and increased brain atrophy. Plasma Aβ42/Aβ40 at baseline predicted clinical conversion to mild cognitive impairment and longitudinal changes in amyloid deposition and brain atrophy at 2-year follow-up. CONCLUSIONS This study suggests that plasma Aβ42/Aβ40, as determined by this MS-based assay, has potential value as an accurate and cost-effective tool to identify individuals in the earliest stages of AD, supporting its implementation in clinical trials, preventative strategies and clinical practice.
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Affiliation(s)
| | | | | | | | | | | | | | - Juan Pablo Tartari
- grid.410675.10000 0001 2325 3084Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain
| | - Ángela Sanabria
- grid.410675.10000 0001 2325 3084Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain ,grid.418264.d0000 0004 1762 4012CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Lluís Tárraga
- grid.410675.10000 0001 2325 3084Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain ,grid.418264.d0000 0004 1762 4012CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Agustín Ruíz
- grid.410675.10000 0001 2325 3084Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain ,grid.418264.d0000 0004 1762 4012CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Marta Marquié
- grid.410675.10000 0001 2325 3084Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain ,grid.418264.d0000 0004 1762 4012CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Sang Won Seo
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Hyemin Jang
- grid.264381.a0000 0001 2181 989XDepartment of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Mercè Boada
- grid.410675.10000 0001 2325 3084Ace Alzheimer Center Barcelona - Universitat Internacional de Catalunya, Barcelona, Spain ,grid.418264.d0000 0004 1762 4012CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
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Brand AL, Lawler PE, Bollinger JG, Li Y, Schindler SE, Li M, Lopez S, Ovod V, Nakamura A, Shaw LM, Zetterberg H, Hansson O, Bateman RJ. The performance of plasma amyloid beta measurements in identifying amyloid plaques in Alzheimer's disease: a literature review. Alzheimers Res Ther 2022; 14:195. [PMID: 36575454 PMCID: PMC9793600 DOI: 10.1186/s13195-022-01117-1] [Citation(s) in RCA: 32] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2022] [Accepted: 11/06/2022] [Indexed: 12/28/2022]
Abstract
The extracellular buildup of amyloid beta (Aβ) plaques in the brain is a hallmark of Alzheimer's disease (AD). Detection of Aβ pathology is essential for AD diagnosis and for identifying and recruiting research participants for clinical trials evaluating disease-modifying therapies. Currently, AD diagnoses are usually made by clinical assessments, although detection of AD pathology with positron emission tomography (PET) scans or cerebrospinal fluid (CSF) analysis can be used by specialty clinics. These measures of Aβ aggregation, e.g. plaques, protofibrils, and oligomers, are medically invasive and often only available at specialized medical centers or not covered by medical insurance, and PET scans are costly. Therefore, a major goal in recent years has been to identify blood-based biomarkers that can accurately detect AD pathology with cost-effective, minimally invasive procedures.To assess the performance of plasma Aβ assays in predicting amyloid burden in the central nervous system (CNS), this review compares twenty-one different manuscripts that used measurements of 42 and 40 amino acid-long Aβ (Aβ42 and Aβ40) in plasma to predict CNS amyloid status. Methodologies that quantitate Aβ42 and 40 peptides in blood via immunoassay or immunoprecipitation-mass spectrometry (IP-MS) were considered, and their ability to distinguish participants with amyloidosis compared to amyloid PET and CSF Aβ measures as reference standards was evaluated. Recent studies indicate that some IP-MS assays perform well in accurately and precisely measuring Aβ and detecting brain amyloid aggregates.
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Affiliation(s)
- Abby L. Brand
- grid.4367.60000 0001 2355 7002Department of Neurology, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO USA
| | - Paige E. Lawler
- grid.4367.60000 0001 2355 7002Department of Neurology, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO USA
| | - James G. Bollinger
- grid.4367.60000 0001 2355 7002Department of Neurology, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO USA
| | - Yan Li
- grid.4367.60000 0001 2355 7002Department of Neurology, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO USA
| | - Suzanne E. Schindler
- grid.4367.60000 0001 2355 7002Department of Neurology, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO USA
| | - Melody Li
- grid.4367.60000 0001 2355 7002Department of Neurology, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO USA
| | - Samir Lopez
- grid.4367.60000 0001 2355 7002Department of Neurology, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO USA
| | - Vitaliy Ovod
- grid.4367.60000 0001 2355 7002Department of Neurology, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO USA
| | - Akinori Nakamura
- grid.419257.c0000 0004 1791 9005Department of Biomarker Research, National Center for Geriatrics and Gerontology, Obu, Japan ,grid.27476.300000 0001 0943 978XDepartment of Cognition and Behavior Science, Nagoya University Graduate School of Medicine, Nagoya, Japan
| | - Leslie M. Shaw
- grid.25879.310000 0004 1936 8972Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA USA
| | - Henrik Zetterberg
- grid.8761.80000 0000 9919 9582Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden ,grid.1649.a000000009445082XClinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden ,grid.83440.3b0000000121901201Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK ,grid.83440.3b0000000121901201UK Dementia Research Institute at UCL, London, UK ,grid.24515.370000 0004 1937 1450Hong Kong Center for Neurodegenerative Diseases, Clear Water Bay, Hong Kong, China
| | - Oskar Hansson
- grid.4514.40000 0001 0930 2361Clinical Memory Research Unit, Department of Clinical Sciences, Lund University, Malmö, Sweden ,grid.411843.b0000 0004 0623 9987Memory Clinic, Skåne University Hospital, Lund, Sweden
| | - Randall J. Bateman
- grid.4367.60000 0001 2355 7002Department of Neurology, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002The Tracy Family SILQ Center, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002Knight Alzheimer’s Disease Research Center, Washington University School of Medicine, St. Louis, MO USA ,grid.4367.60000 0001 2355 7002Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO USA
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Hansson O, Edelmayer RM, Boxer AL, Carrillo MC, Mielke MM, Rabinovici GD, Salloway S, Sperling R, Zetterberg H, Teunissen CE. The Alzheimer's Association appropriate use recommendations for blood biomarkers in Alzheimer's disease. Alzheimers Dement 2022; 18:2669-2686. [PMID: 35908251 PMCID: PMC10087669 DOI: 10.1002/alz.12756] [Citation(s) in RCA: 146] [Impact Index Per Article: 73.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Revised: 06/28/2022] [Accepted: 07/08/2022] [Indexed: 01/31/2023]
Abstract
Blood-based markers (BBMs) have recently shown promise to revolutionize the diagnostic and prognostic work-up of Alzheimer's disease (AD), as well as to improve the design of interventional trials. Here we discuss in detail further research needed to be performed before widespread use of BBMs. We already now recommend use of BBMs as (pre-)screeners to identify individuals likely to have AD pathological changes for inclusion in trials evaluating disease-modifying therapies, provided the AD status is confirmed with positron emission tomography (PET) or cerebrospinal fluid (CSF) testing. We also encourage studying longitudinal BBM changes in ongoing as well as future interventional trials. However, BBMs should not yet be used as primary endpoints in pivotal trials. Further, we recommend to cautiously start using BBMs in specialized memory clinics as part of the diagnostic work-up of patients with cognitive symptoms and the results should be confirmed whenever possible with CSF or PET. Additional data are needed before use of BBMs as stand-alone diagnostic AD markers, or before considering use in primary care.
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Affiliation(s)
- Oskar Hansson
- ClinicalMemory Research UnitDepartment of Clinical Sciences MalmöLund UniversityMalmöSweden
- Memory ClinicSkåne University HospitalMalmöSweden
| | | | - Adam L. Boxer
- Department of NeurologyUniversity of California San FranciscoMemory and Aging CenterSan FranciscoCaliforniaUSA
| | | | - Michelle M. Mielke
- Department of Epidemiology and PreventionWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Gil D. Rabinovici
- Department of NeurologyUniversity of California San FranciscoMemory and Aging CenterSan FranciscoCaliforniaUSA
| | - Stephen Salloway
- Departments of Neurology and PsychiatryAlpert Medical School of Brown UniversityProvidenceRhode IslandUSA
| | - Reisa Sperling
- Centerfor Alzheimer Research and TreatmentBrigham and Women's Hospital, Massachusetts General Hospital, Harvard Medical SchoolBostonMassachusettsUSA
| | - Henrik Zetterberg
- Department of Psychiatry and NeurochemistryInstitute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative DiseaseUCL Institute of NeurologyQueen SquareLondonUK
- UK Dementia Research Institute at UCLLondonUK
- Hong Kong Center for Neurodegenerative DiseasesClear Water BayHong KongPeople's Republic of China
| | - Charlotte E. Teunissen
- NeurochemistryLaboratoryDepartment of Clinical ChemistryAmsterdam University Medical CentersVrije UniversiteitAmsterdam NeuroscienceAmsterdamthe Netherlands
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Ashton NJ, Janelidze S, Mattsson-Carlgren N, Binette AP, Strandberg O, Brum WS, Karikari TK, González-Ortiz F, Di Molfetta G, Meda FJ, Jonaitis EM, Koscik RL, Cody K, Betthauser TJ, Li Y, Vanmechelen E, Palmqvist S, Stomrud E, Bateman RJ, Zetterberg H, Johnson SC, Blennow K, Hansson O. Differential roles of Aβ42/40, p-tau231 and p-tau217 for Alzheimer's trial selection and disease monitoring. Nat Med 2022; 28:2555-2562. [PMID: 36456833 PMCID: PMC9800279 DOI: 10.1038/s41591-022-02074-w] [Citation(s) in RCA: 100] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2022] [Accepted: 10/03/2022] [Indexed: 12/03/2022]
Abstract
Blood biomarkers indicative of Alzheimer's disease (AD) pathology are altered in both preclinical and symptomatic stages of the disease. Distinctive biomarkers may be optimal for the identification of AD pathology or monitoring of disease progression. Blood biomarkers that correlate with changes in cognition and atrophy during the course of the disease could be used in clinical trials to identify successful interventions and thereby accelerate the development of efficient therapies. When disease-modifying treatments become approved for use, efficient blood-based biomarkers might also inform on treatment implementation and management in clinical practice. In the BioFINDER-1 cohort, plasma phosphorylated (p)-tau231 and amyloid-β42/40 ratio were more changed at lower thresholds of amyloid pathology. Longitudinally, however, only p-tau217 demonstrated marked amyloid-dependent changes over 4-6 years in both preclinical and symptomatic stages of the disease, with no such changes observed in p-tau231, p-tau181, amyloid-β42/40, glial acidic fibrillary protein or neurofilament light. Only longitudinal increases of p-tau217 were also associated with clinical deterioration and brain atrophy in preclinical AD. The selective longitudinal increase of p-tau217 and its associations with cognitive decline and atrophy was confirmed in an independent cohort (Wisconsin Registry for Alzheimer's Prevention). These findings support the differential association of plasma biomarkers with disease development and strongly highlight p-tau217 as a surrogate marker of disease progression in preclinical and prodromal AD, with impact for the development of new disease-modifying treatments.
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Affiliation(s)
- Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- King's College London, Institute of Psychiatry, Psychology and Neuroscience, Maurice Wohl Institute Clinical Neuroscience Institute, London, UK
- NIHR Biomedical Research Centre for Mental Health and Biomedical Research Unit for Dementia at South London and Maudsley NHS Foundation, London, UK
- Centre for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Shorena Janelidze
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Department of Neurology, Skåne University Hospital, Lund University, Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, Lund, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | - Wagner S Brum
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | - Thomas K Karikari
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Department of Psychiatry, University of Pittsburgh, Pittsburgh, PA, USA
| | - Fernándo González-Ortiz
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Guglielmo Di Molfetta
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Francisco J Meda
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Erin M Jonaitis
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Rebecca Langhough Koscik
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Karly Cody
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Tobey J Betthauser
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Yan Li
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
| | | | - Sebastian Palmqvist
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
- Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Randall J Bateman
- Department of Neurology, Washington University School of Medicine, St. Louis, MO, USA
- SILQ Center, Washington University School of Medicine, St. Louis, MO, USA
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Sterling C Johnson
- Wisconsin Alzheimer's Institute, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
- Wisconsin Alzheimer's Disease Research Center, School of Medicine and Public Health, University of Wisconsin, Madison, WI, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
- ADx NeuroSciences, Technologiepark 94, Ghent, Belgium.
| | - Oskar Hansson
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden.
- Memory Clinic, Skåne University Hospital, Malmö, Sweden.
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Abstract
Alzheimer's disease (AD) characterization has progressed from being indexed using clinical symptomatology followed by neuropathological examination at autopsy to in vivo signatures using cerebrospinal fluid (CSF) biomarkers and positron emission tomography. The core AD biomarkers reflect amyloid-β plaques (A), tau pathology (T) and neurodegeneration (N), following the ATN schedule, and are now being introduced into clinical routine practice. This is an important development, as disease-modifying treatments are now emerging. Further, there are now reproducible data on CSF biomarkers which reflect synaptic pathology, neuroinflammation and common co-pathologies. In addition, the development of ultrasensitive techniques has enabled the core CSF biomarkers of AD pathophysiology to be translated to blood (e.g., phosphorylated tau, amyloid-β and neurofilament light). In this chapter, we review where we stand with both core and novel CSF biomarkers, as well as the explosion of data on blood biomarkers. Also, we discuss potential applications in research aiming to better understand the disease, as well as possible use in routine clinical practice and therapeutic trials.
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Affiliation(s)
- Joel Simrén
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden.
| | - Anders Elmgren
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Gothenburg, Sweden; Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, United Kingdom; UK Dementia Research Institute, University College London, London, United Kingdom; Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
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Gonzales MM, Wiedner C, Wang C, Liu Q, Bis JC, Li Z, Himali JJ, Ghosh S, Thomas EA, Parent DM, Kautz TF, Pase MP, Aparicio HJ, Djoussé L, Mukamal KJ, Psaty BM, Longstreth WT, Mosley TH, Gudnason V, Mbangdadji D, Lopez OL, Yaffe K, Sidney S, Bryan RN, Nasrallah IM, DeCarli CS, Beiser AS, Launer LJ, Fornage M, Tracy RP, Seshadri S, Satizabal CL. A population-based meta-analysis of circulating GFAP for cognition and dementia risk. Ann Clin Transl Neurol 2022; 9:1574-1585. [PMID: 36056631 PMCID: PMC9539381 DOI: 10.1002/acn3.51652] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2022] [Accepted: 08/10/2022] [Indexed: 11/26/2022] Open
Abstract
OBJECTIVE Expression of glial fibrillary acidic protein (GFAP), a marker of reactive astrocytosis, colocalizes with neuropathology in the brain. Blood levels of GFAP have been associated with cognitive decline and dementia status. However, further examinations at a population-based level are necessary to broaden generalizability to community settings. METHODS Circulating GFAP levels were assayed using a Simoa HD-1 analyzer in 4338 adults without prevalent dementia from four longitudinal community-based cohort studies. The associations between GFAP levels with general cognition, total brain volume, and hippocampal volume were evaluated with separate linear regression models in each cohort with adjustment for age, sex, education, race, diabetes, systolic blood pressure, antihypertensive medication, body mass index, apolipoprotein E ε4 status, site, and time between GFAP blood draw and the outcome. Associations with incident all-cause and Alzheimer's disease dementia were evaluated with adjusted Cox proportional hazard models. Meta-analysis was performed on the estimates derived from each cohort using random-effects models. RESULTS Meta-analyses indicated that higher circulating GFAP associated with lower general cognition (ß = -0.09, [95% confidence interval [CI]: -0.15 to -0.03], p = 0.005), but not with total brain or hippocampal volume (p > 0.05). However, each standard deviation unit increase in log-transformed GFAP levels was significantly associated with a 2.5-fold higher risk of incident all-cause dementia (Hazard Ratio [HR]: 2.47 (95% CI: 1.52-4.01)) and Alzheimer's disease dementia (HR: 2.54 [95% CI: 1.42-4.53]) over up to 15-years of follow-up. INTERPRETATION Results support the potential role of circulating GFAP levels for aiding dementia risk prediction and improving clinical trial stratification in community settings.
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Affiliation(s)
- Mitzi M. Gonzales
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
- Department of NeurologyUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
| | - Crystal Wiedner
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
| | - Chen‐Pin Wang
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
- Department of Population Health SciencesUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
- South Texas Veterans Health Care System, Geriatric ResearchEducation & Clinical CenterSan AntonioTexasUSA
| | - Qianqian Liu
- Department of Population Health SciencesUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
| | - Joshua C. Bis
- Cardiovascular Health Research UnitUniversity of WashingtonSeattleWashingtonUSA
| | - Zhiguang Li
- Laboratory of Epidemiology and Population Sciences, Intramural Research ProgramNational Institute on AgingBethesdaMarylandUSA
| | - Jayandra J. Himali
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
- Department of Population Health SciencesUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- Department of BiostatisticsBoston University School of MedicineBostonMassachusettsUSA
| | - Saptaparni Ghosh
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
| | - Emy A. Thomas
- Brown Foundation of Molecular Medicine, McGovern Medical SchoolUniversity of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Danielle M. Parent
- Department of Pathology and Laboratory Medicine, and Biochemistry, Larner College of MedicineUniversity of VermontBurlingtonVermontUSA
| | - Tiffany F. Kautz
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
| | - Matthew P. Pase
- The Framingham Heart StudyFraminghamMassachusettsUSA
- School of Psychological Sciences, Turner Institute for Brain and Mental HealthMonash UniversityClaytonVictoriaAustralia
- Harvard T.H. Chan School of Public HealthBostonMassachusettsUSA
| | - Hugo J. Aparicio
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
| | - Luc Djoussé
- Department of MedicineBrigham and Women's HospitalBostonMassachusettsUSA
- Boston Veterans Affairs Healthcare SystemBostonMassachusettsUSA
| | - Kenneth J. Mukamal
- Department of MedicineBeth Israel Deaconess Medical CenterBostonMassachusettsUSA
| | - Bruce M. Psaty
- Cardiovascular Health Research UnitUniversity of WashingtonSeattleWashingtonUSA
- Department of EpidemiologyUniversity of WashingtonSeattleWashingtonUSA
- Department of MedicineUniversity of WashingtonSeattleWashingtonUSA
- Department of Health Systems and Population HealthUniversity of WashingtonSeattleWashingtonUSA
| | - William T. Longstreth
- Department of EpidemiologyUniversity of WashingtonSeattleWashingtonUSA
- Department of NeurologyUniversity of WashingtonSeattleWashingtonUSA
| | - Thomas H. Mosley
- The MIND CenterUniversity of Mississippi Medical CenterJacksonMississippiUSA
| | - Vilmundur Gudnason
- Icelandic Heart Association Research InstituteKópavogurIceland
- Department of CardiologyUniversity of IcelandReykjavikIceland
| | - Djass Mbangdadji
- Laboratory of Epidemiology and Population Sciences, Intramural Research ProgramNational Institute on AgingBethesdaMarylandUSA
| | - Oscar L. Lopez
- Department of NeurologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Kristine Yaffe
- Department of PsychiatryUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of NeurologyUniversity of CaliforniaSan FranciscoCaliforniaUSA
- Department of Epidemiology and BiostatisticsUniversity of CaliforniaSan FranciscoCaliforniaUSA
- San Francisco VA Medical CenterSan FranciscoCaliforniaUSA
| | - Stephen Sidney
- Kaiser Permanente Medical Center ProgramOaklandCaliforniaUSA
| | - R. Nick Bryan
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | - Ilya M. Nasrallah
- Department of RadiologyUniversity of PennsylvaniaPhiladelphiaPennsylvaniaUSA
| | | | - Alexa S. Beiser
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
- Department of BiostatisticsBoston University School of MedicineBostonMassachusettsUSA
| | - Lenore J. Launer
- Laboratory of Epidemiology and Population Sciences, Intramural Research ProgramNational Institute on AgingBethesdaMarylandUSA
| | - Myriam Fornage
- Brown Foundation of Molecular Medicine, McGovern Medical SchoolUniversity of Texas Health Science Center at HoustonHoustonTexasUSA
| | - Russell P. Tracy
- Department of Pathology and Laboratory Medicine, and Biochemistry, Larner College of MedicineUniversity of VermontBurlingtonVermontUSA
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
- Department of NeurologyUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
- Department of NeurologyBoston University School of MedicineBostonMassachusettsUSA
| | - Claudia L. Satizabal
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative DiseasesUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
- Department of Population Health SciencesUniversity of Texas Health Science Center at San AntonioSan AntonioTexasUSA
- The Framingham Heart StudyFraminghamMassachusettsUSA
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49
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Kumar A, Janelidze S, Stomrud E, Palmqvist S, Hansson O, Mattsson-Carlgren N. β-Amyloid-Dependent and -Independent Genetic Pathways Regulating CSF Tau Biomarkers in Alzheimer Disease. Neurology 2022; 99:e476-e487. [PMID: 35641311 PMCID: PMC9421595 DOI: 10.1212/wnl.0000000000200605] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Accepted: 03/11/2022] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Abnormal metabolism of β-amyloid (Aβ) and soluble phosphorylated tau (P-tau), as well as neurodegeneration, are key components of Alzheimer disease (AD), but it is unclear how these different processes are related to genetic risk factors for AD. METHODS In the Swedish BioFINDER study, we tested associations between a priori defined polygenic risk scores (PRSs) for AD (excluding single-nucleotide polymorphism [SNP] within the APOE region in the main analysis) and biomarkers in CSF (total tau [T-tau] and P-tau181; Aβ1-38, Aβ1-40, Aβ1-42, and Aβ1-42/1-40; and neurofilament light [NfL]) in cognitively unimpaired (CU) individuals (n = 751), and in patients with mild cognitive impairment (MCI) (n = 212) and AD dementia (n = 150). Results were validated in the Alzheimer's Disease Neuroimaging Initiative data set with 777 individuals (AD = 119, MCI = 442, and CU = 216). RESULTS PRSs with SNPs significant at p < 5e-03 (∼1,742 variants) were associated with higher CSF P-tau181 (β = 0.13, p = 5.6e-05) and T-tau (β = 0.12, p = 4.3e-04). The associations between PRS and tau measures were partly attenuated but remained significant after adjusting for Aβ status. Aβ pathology mediated 37% of the effect of this PRS on tau levels. Aβ-dependent and Aβ-independent subsets of the PRS were identified and characterized. There were also associations between PRSs and CSF Aβ biomarkers with nominal significance, but not when corrected for multiple comparisons. There were no associations between PRSs and CSF NfL. DISCUSSION Genetic pathways implicated in causing AD are related to altered levels of soluble tau through both Aβ-dependent and Aβ-independent mechanisms, which may have relevance for anti-tau drug development.
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Affiliation(s)
- Atul Kumar
- From the Clinical Memory Research Unit (A.K., S.J., E.S., S.P., O.H., N.M.-C.), Department of Clinical Sciences, Lund University, Malmö; Memory Clinic (E.S., S.P., O.H.), Skåne University Hospital, Malmö; Department of Neurology (N.M.-C.), Skåne University Hospital, Lund; and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University, Sweden.
| | - Shorena Janelidze
- From the Clinical Memory Research Unit (A.K., S.J., E.S., S.P., O.H., N.M.-C.), Department of Clinical Sciences, Lund University, Malmö; Memory Clinic (E.S., S.P., O.H.), Skåne University Hospital, Malmö; Department of Neurology (N.M.-C.), Skåne University Hospital, Lund; and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University, Sweden
| | - Erik Stomrud
- From the Clinical Memory Research Unit (A.K., S.J., E.S., S.P., O.H., N.M.-C.), Department of Clinical Sciences, Lund University, Malmö; Memory Clinic (E.S., S.P., O.H.), Skåne University Hospital, Malmö; Department of Neurology (N.M.-C.), Skåne University Hospital, Lund; and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University, Sweden
| | - Sebastian Palmqvist
- From the Clinical Memory Research Unit (A.K., S.J., E.S., S.P., O.H., N.M.-C.), Department of Clinical Sciences, Lund University, Malmö; Memory Clinic (E.S., S.P., O.H.), Skåne University Hospital, Malmö; Department of Neurology (N.M.-C.), Skåne University Hospital, Lund; and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University, Sweden
| | - Oskar Hansson
- From the Clinical Memory Research Unit (A.K., S.J., E.S., S.P., O.H., N.M.-C.), Department of Clinical Sciences, Lund University, Malmö; Memory Clinic (E.S., S.P., O.H.), Skåne University Hospital, Malmö; Department of Neurology (N.M.-C.), Skåne University Hospital, Lund; and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University, Sweden
| | - Niklas Mattsson-Carlgren
- From the Clinical Memory Research Unit (A.K., S.J., E.S., S.P., O.H., N.M.-C.), Department of Clinical Sciences, Lund University, Malmö; Memory Clinic (E.S., S.P., O.H.), Skåne University Hospital, Malmö; Department of Neurology (N.M.-C.), Skåne University Hospital, Lund; and Wallenberg Centre for Molecular Medicine (N.M.-C.), Lund University, Sweden
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50
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Botella Lucena P, Vanherle S, Lodder C, Gutiérrez de Ravé M, Stancu IC, Lambrichts I, Vangheluwe R, Bruffaerts R, Dewachter I. Blood-based Aβ42 increases in the earliest pre-pathological stage before decreasing with progressive amyloid pathology in preclinical models and human subjects: opening new avenues for prevention. Acta Neuropathol 2022; 144:489-508. [PMID: 35796870 PMCID: PMC9381631 DOI: 10.1007/s00401-022-02458-9] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Revised: 06/21/2022] [Accepted: 06/21/2022] [Indexed: 11/27/2022]
Abstract
Blood-based (BB) biomarkers for Aβ and tau can indicate pathological processes in the brain, in the early pathological, even pre-symptomatic stages in Alzheimer’s disease. However, the relation between BB biomarkers and AD-related processes in the brain in the earliest pre-pathology stage before amyloid pathology develops, and their relation with total brain concentrations of Aβ and tau, is poorly understood. This stage presents a critical window for the earliest prevention of AD. Preclinical models with well-defined temporal progression to robust amyloid and tau pathology provide a unique opportunity to study this relation and were used here to study the link between BB biomarkers with AD-related processes in pre- and pathological stages. We performed a cross-sectional study at different ages assessing the link between BB concentrations and AD-related processes in the brain. This was complemented with a longitudinal analysis and with analysis of age-related changes in a small cohort of human subjects. We found that BB-tau concentrations increased in serum, correlating with progressive development of tau pathology and with increasing tau aggregates and p-tau concentrations in brain in TauP301S mice (PS19) developing tauopathy. BB-Aβ42 concentrations in serum decreased between 4.5 and 9 months of age, correlating with the progressive development of robust amyloid pathology in APP/PS1 (5xFAD) mice, in line with previous findings. Most importantly, BB-Aβ42 concentrations significantly increased between 1.5 and 4.5 months, i.e., in the earliest pre-pathological stage, before robust amyloid pathology develops in the brain, indicating biphasic BB-Aβ42 dynamics. Furthermore, increasing BB-Aβ42 in the pre-pathological phase, strongly correlated with increasing Aβ42 concentrations in brain. Our subsequent longitudinal analysis of BB-Aβ42 in 5xFAD mice, confirmed biphasic BB-Aβ42, with an initial increase, before decreasing with progressive robust pathology. Furthermore, in human samples, BB-Aβ42 concentrations were significantly higher in old (> 60 years) compared to young (< 50 years) subjects, as well as to age-matched AD patients, further supporting age-dependent increase of Aβ42 concentrations in the earliest pre-pathological phase, before amyloid pathology. Also BB-Aβ40 concentrations were found to increase in the earliest pre-pathological phase both in preclinical models and human subjects, while subsequent significantly decreasing concentrations in the pathological phase were characteristic for BB-Aβ42. Together our data indicate that BB biomarkers reflect pathological processes in brain of preclinical models with amyloid and tau pathology, both in the pathological and pre-pathological phase. Our data indicate a biphasic pattern of BB-Aβ42 in preclinical models and a human cohort. And most importantly, we here show that BB-Aβ increased and correlated with increasing concentrations of Aβ in the brain, in the earliest pre-pathological stage in a preclinical model. Our data thereby identify a novel critical window for prevention, using BB-Aβ as marker for accumulating Aβ in the brain, in the earliest pre-pathological stage, opening new avenues for personalized early preventive strategies against AD, even before amyloid pathology develops.
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Affiliation(s)
- Pablo Botella Lucena
- Biomedical Research Institute, BIOMED, Hasselt University, 3590, Diepenbeek, Belgium
| | - Sarah Vanherle
- Biomedical Research Institute, BIOMED, Hasselt University, 3590, Diepenbeek, Belgium
| | - Chritica Lodder
- Biomedical Research Institute, BIOMED, Hasselt University, 3590, Diepenbeek, Belgium
| | | | - Ilie-Cosmin Stancu
- Biomedical Research Institute, BIOMED, Hasselt University, 3590, Diepenbeek, Belgium
| | - Ivo Lambrichts
- Biomedical Research Institute, BIOMED, Hasselt University, 3590, Diepenbeek, Belgium
| | - Riet Vangheluwe
- Neurology Department, ZOL Genk General Hospital, Genk, Belgium
| | - Rose Bruffaerts
- Biomedical Research Institute, BIOMED, Hasselt University, 3590, Diepenbeek, Belgium.,Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute (LBI), KU, 3000, Leuven, Belgium.,Department of Neurology, University Hospitals, 3000, Leuven, Belgium.,Computational Neurology, Experimental Neurobiology Unit, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Ilse Dewachter
- Biomedical Research Institute, BIOMED, Hasselt University, 3590, Diepenbeek, Belgium.
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