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Biesbroek JM, Coenen M, DeCarli C, Fletcher EM, Maillard PM, Barkhof F, Barnes J, Benke T, Chen CPLH, Dal‐Bianco P, Dewenter A, Duering M, Enzinger C, Ewers M, Exalto LG, Franzmeier N, Hilal S, Hofer E, Koek HL, Maier AB, McCreary CR, Papma JM, Paterson RW, Pijnenburg YAL, Rubinski A, Schmidt R, Schott JM, Slattery CF, Smith EE, Sudre CH, Steketee RME, Teunissen CE, van den Berg E, van der Flier WM, Venketasubramanian N, Venkatraghavan V, Vernooij MW, Wolters FJ, Xin X, Kuijf HJ, Biessels GJ. Amyloid pathology and vascular risk are associated with distinct patterns of cerebral white matter hyperintensities: A multicenter study in 3132 memory clinic patients. Alzheimers Dement 2024; 20:2980-2989. [PMID: 38477469 PMCID: PMC11032573 DOI: 10.1002/alz.13765] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Revised: 01/30/2024] [Accepted: 01/31/2024] [Indexed: 03/14/2024]
Abstract
INTRODUCTION White matter hyperintensities (WMH) are associated with key dementia etiologies, in particular arteriolosclerosis and amyloid pathology. We aimed to identify WMH locations associated with vascular risk or cerebral amyloid-β1-42 (Aβ42)-positive status. METHODS Individual patient data (n = 3,132; mean age 71.5 ± 9 years; 49.3% female) from 11 memory clinic cohorts were harmonized. WMH volumes in 28 regions were related to a vascular risk compound score (VRCS) and Aß42 status (based on cerebrospinal fluid or amyloid positron emission tomography), correcting for age, sex, study site, and total WMH volume. RESULTS VRCS was associated with WMH in anterior/superior corona radiata (B = 0.034/0.038, p < 0.001), external capsule (B = 0.052, p < 0.001), and middle cerebellar peduncle (B = 0.067, p < 0.001), and Aß42-positive status with WMH in posterior thalamic radiation (B = 0.097, p < 0.001) and splenium (B = 0.103, p < 0.001). DISCUSSION Vascular risk factors and Aß42 pathology have distinct signature WMH patterns. This regional vulnerability may incite future studies into how arteriolosclerosis and Aß42 pathology affect the brain's white matter. HIGHLIGHTS Key dementia etiologies may be associated with specific patterns of white matter hyperintensities (WMH). We related WMH locations to vascular risk and cerebral Aβ42 status in 11 memory clinic cohorts. Aβ42 positive status was associated with posterior WMH in splenium and posterior thalamic radiation. Vascular risk was associated with anterior and infratentorial WMH. Amyloid pathology and vascular risk have distinct signature WMH patterns.
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Murakami T, Abe M, Tiksnadi A, Nemoto A, Futamura M, Yamakuni R, Kubo H, Kobayashi N, Ito H, Hanajima R, Hashimoto Y, Ugawa Y. Abnormal motor cortical plasticity as a useful neurophysiological biomarker for Alzheimer's disease pathology. Clin Neurophysiol 2024; 158:170-179. [PMID: 38219406 DOI: 10.1016/j.clinph.2023.12.131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2022] [Revised: 11/27/2023] [Accepted: 12/15/2023] [Indexed: 01/16/2024]
Abstract
OBJECTIVE Amyloid-beta (Aβ) and tau accumulations impair long-term potentiation (LTP) induction in animal hippocampi. We investigated relationships between motor-cortical plasticity and biomarkers for Alzheimer's disease (AD) diagnosis in subjects with cognitive decline. METHODS Twenty-six consecutive subjects who complained of memory problems participated in this study. We applied transcranial quadripuse stimulation with an interstimulus interval of 5 ms (QPS5) to induce LTP-like plasticity. Motor-evoked potentials were recorded from the right first-dorsal interosseous muscle before and after QPS5. Cognitive functions, Aβ42 and tau levels in the cerebrospinal fluid (CSF) were measured. Amyloid positron-emission tomography (PET) with11C-Pittsburg compound-B was also conducted. We studied correlations of QPS5-induced plasticity with cognitive functions or AD-related biomarkers. RESULTS QPS5-induced LTP-like plasticity positively correlated with cognitive scores. The degree of LTP-like plasticity negatively correlated with levels of CSF-tau, and the amount of amyloid-PET accumulation at the precuneus, and correlated with the CSF-Aβ42 level positively. In the amyloid-PET positive subjects, non-responder rate of QPS5 was higher than the CSF-tau positive rate. CONCLUSIONS Findings suggest that QPS5-induced LTP-like plasticity is a functional biomarker of AD. QPS5 could detect abnormality at earlier stages than CSF-tau in the amyloid-PET positive subjects. SIGNIFICANCE Assessing motor-cortical plasticity could be a useful neurophysiological biomarker for AD pathology.
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Affiliation(s)
- Takenobu Murakami
- Department of Neurology, Faculty of Medicine, Fukushima Medical University, Hikarigaoka 1, Fukushima 960-1295, Japan; Division of Neurology, Department of Brain and Neurosciences, Faculty of Medicine, Tottori University, Nishimachi 36-1, Yonago 683-8504, Japan.
| | - Mitsunari Abe
- Center for Neurological Disorders, Faculty of Medicine, Fukushima Medical University, Hikarigaoka 1, Fukushima 960-1295, Japan
| | - Amanda Tiksnadi
- Department of Neurology, Faculty of Medicine, Fukushima Medical University, Hikarigaoka 1, Fukushima 960-1295, Japan; Department of Neurology, Cipto Mangunkusumo Hospital, Faculty of Medicine, Universitas Indonesia, Salemba Raya No. 6, Jakarta 10430, Indonesia
| | - Ayaka Nemoto
- Advanced Clinical Research Center, Faculty of Medicine, Fukushima Medical University, Hikarigaoka 1, Fukushima 960-1295, Japan
| | - Miyako Futamura
- Rehabilitation Center, Faculty of Medicine, Fukushima Medical University, Hikarigaoka 1, Fukushima 960-1295, Japan
| | - Ryo Yamakuni
- Department of Radiology, Faculty of Medicine, Fukushima Medical University, Hikarigaoka 1, Fukushima 960-1295, Japan
| | - Hitoshi Kubo
- Advanced Clinical Research Center, Faculty of Medicine, Fukushima Medical University, Hikarigaoka 1, Fukushima 960-1295, Japan; Department of Radiological Sciences, Faculty of Medicine, Fukushima Medical University, Hikarigaoka 1, Fukushima 960-1295, Japan
| | - Naoto Kobayashi
- Azuma Street Clinic, Sakaemachi 1-28, Fukushima 960-8031, Japan
| | - Hiroshi Ito
- Advanced Clinical Research Center, Faculty of Medicine, Fukushima Medical University, Hikarigaoka 1, Fukushima 960-1295, Japan; Department of Radiology, Faculty of Medicine, Fukushima Medical University, Hikarigaoka 1, Fukushima 960-1295, Japan
| | - Ritsuko Hanajima
- Division of Neurology, Department of Brain and Neurosciences, Faculty of Medicine, Tottori University, Nishimachi 36-1, Yonago 683-8504, Japan
| | - Yasuhiro Hashimoto
- Department of Biochemistry, Faculty of Medicine, Fukushima Medical University, Hikarigaoka 1, Fukushima 960-1295, Japan
| | - Yoshikazu Ugawa
- Department of Neurology, Faculty of Medicine, Fukushima Medical University, Hikarigaoka 1, Fukushima 960-1295, Japan; Department of Human Neurophysiology, Faculty of Medicine, Fukushima Medical University, Hikarigaoka 1, Fukushima 960-1295, Japan
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Fernandes M, Maio S, Eusebi P, Placidi F, Izzi F, Spanetta M, De Masi C, Lupo C, Calvello C, Nuccetelli M, Bernardini S, Mercuri NB, Liguori C. Cerebrospinal-fluid biomarkers for predicting phenoconversion in patients with isolated rapid-eye movement sleep behavior disorder. Sleep 2024; 47:zsad198. [PMID: 37542734 DOI: 10.1093/sleep/zsad198] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 05/22/2023] [Indexed: 08/07/2023] Open
Abstract
STUDY OBJECTIVES Patients with isolated rapid-eye-movement sleep behavior disorder (iRBD) have an increased risk of developing neurodegenerative diseases. This study assessed cerebrospinal-fluid (CSF) biomarkers of neurodegeneration and blood-brain barrier (BBB) alteration in patients with iRBD compared to controls and ascertain whether these biomarkers may predict phenoconversion to alpha-synucleinopathies (Parkinson's Disease (PD), Dementia with Lewy bodies (DLB), Multiple System Atrophy (MSA)). METHODS Patients and controls underwent between 2012 and 2016 a neurological assessment, a lumbar puncture for CSF biomarker analysis (β-amyloid42 - Aβ42; total-tau, and phosphorylated tau), and BBB alteration (CSF/serum albumin ratio). All patients with iRBD were followed until 2021 and then classified into patients who converted to alpha-synucleinopathies (iRBD converters, cRBD) or not (iRBD non-converters, ncRBD). RESULTS Thirty-four patients with iRBD (mean age 67.12 ± 8.14) and 33 controls (mean age 64.97 ± 8.91) were included. At follow-up (7.63 ± 3.40 years), eight patients were ncRBD and 33 patients were cRBD: eleven converted to PD, 10 to DLB, and two to MSA. Patients with iRBD showed lower CSF Aβ42 levels and higher CSF/serum albumin ratio than controls. Cox regression analysis showed that the phenoconversion rate increases with higher motor impairment (hazard ratio [HR] = 1.23, p = 0.032). CSF Aβ42 levels predicted phenoconversion to DLB (HR = 0.67, p = 0.038) and BBB alteration predicted phenoconversion to PD (HR = 1.20, p = 0.038). DISCUSSION This study showed that low CSF Aβ42 levels and high BBB alteration may predict the phenoconversion to DLB and PD in patients with iRBD, respectively. These findings highlight the possibility to discriminate phenoconversion in iRBD patients through CSF biomarkers; however, further studies are needed.
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Affiliation(s)
- Mariana Fernandes
- Department of Systems Medicine, University of Rome 'Tor Vergata", Rome, Italy
| | - Silvia Maio
- Department of Systems Medicine, University of Rome 'Tor Vergata", Rome, Italy
- Sleep Medicine Centre, Neurology Unit, University Hospital "Tor Vergata", Rome, Italy
| | - Paolo Eusebi
- Department of Medicine, Neurology Clinic, University Hospital of Perugia, Italy
| | - Fabio Placidi
- Department of Systems Medicine, University of Rome 'Tor Vergata", Rome, Italy
- Sleep Medicine Centre, Neurology Unit, University Hospital "Tor Vergata", Rome, Italy
| | - Francesca Izzi
- Sleep Medicine Centre, Neurology Unit, University Hospital "Tor Vergata", Rome, Italy
| | - Matteo Spanetta
- Department of Systems Medicine, University of Rome 'Tor Vergata", Rome, Italy
| | - Claudia De Masi
- Sleep Medicine Centre, Neurology Unit, University Hospital "Tor Vergata", Rome, Italy
| | - Clementina Lupo
- Department of Systems Medicine, University of Rome 'Tor Vergata", Rome, Italy
| | - Carmen Calvello
- Department of Systems Medicine, University of Rome 'Tor Vergata", Rome, Italy
| | - Marzia Nuccetelli
- Department of Clinical Biochemistry and Molecular Biology, University of Rome "Tor Vergata", Rome, Italy
| | - Sergio Bernardini
- Department of Clinical Biochemistry and Molecular Biology, University of Rome "Tor Vergata", Rome, Italy
| | - Nicola Biagio Mercuri
- Department of Systems Medicine, University of Rome 'Tor Vergata", Rome, Italy
- Sleep Medicine Centre, Neurology Unit, University Hospital "Tor Vergata", Rome, Italy
| | - Claudio Liguori
- Department of Systems Medicine, University of Rome 'Tor Vergata", Rome, Italy
- Sleep Medicine Centre, Neurology Unit, University Hospital "Tor Vergata", Rome, Italy
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Tijms BM, Vromen EM, Mjaavatten O, Holstege H, Reus LM, van der Lee S, Wesenhagen KEJ, Lorenzini L, Vermunt L, Venkatraghavan V, Tesi N, Tomassen J, den Braber A, Goossens J, Vanmechelen E, Barkhof F, Pijnenburg YAL, van der Flier WM, Teunissen CE, Berven FS, Visser PJ. Cerebrospinal fluid proteomics in patients with Alzheimer's disease reveals five molecular subtypes with distinct genetic risk profiles. Nat Aging 2024; 4:33-47. [PMID: 38195725 PMCID: PMC10798889 DOI: 10.1038/s43587-023-00550-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 11/29/2023] [Indexed: 01/11/2024]
Abstract
Alzheimer's disease (AD) is heterogenous at the molecular level. Understanding this heterogeneity is critical for AD drug development. Here we define AD molecular subtypes using mass spectrometry proteomics in cerebrospinal fluid, based on 1,058 proteins, with different levels in individuals with AD (n = 419) compared to controls (n = 187). These AD subtypes had alterations in protein levels that were associated with distinct molecular processes: subtype 1 was characterized by proteins related to neuronal hyperplasticity; subtype 2 by innate immune activation; subtype 3 by RNA dysregulation; subtype 4 by choroid plexus dysfunction; and subtype 5 by blood-brain barrier impairment. Each subtype was related to specific AD genetic risk variants, for example, subtype 1 was enriched with TREM2 R47H. Subtypes also differed in clinical outcomes, survival times and anatomical patterns of brain atrophy. These results indicate molecular heterogeneity in AD and highlight the need for personalized medicine.
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Affiliation(s)
- Betty M Tijms
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands.
| | - Ellen M Vromen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Olav Mjaavatten
- Proteomics Unit at the University of Bergen, Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Henne Holstege
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Department of Clinical Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Lianne M Reus
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Sven van der Lee
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Kirsten E J Wesenhagen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Luigi Lorenzini
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neuroimaging, Amsterdam, the Netherlands
| | - Lisa Vermunt
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Neurochemistry Laboratory, Department of Laboratory Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Vikram Venkatraghavan
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Niccoló Tesi
- Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, Delft, the Netherlands
| | - Jori Tomassen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Anouk den Braber
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Department of Biological Psychology, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | | | | | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Yolande A L Pijnenburg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Epidemiology & Data Science, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Charlotte E Teunissen
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Neurochemistry Laboratory, Department of Laboratory Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
| | - Frode S Berven
- Proteomics Unit at the University of Bergen, Department of Biomedicine, University of Bergen, Bergen, Norway
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, the Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
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Castegnaro A, Ji Z, Rudzka K, Chan D, Burgess N. Overestimation in angular path integration precedes Alzheimer's dementia. Curr Biol 2023; 33:4650-4661.e7. [PMID: 37827151 PMCID: PMC10957396 DOI: 10.1016/j.cub.2023.09.047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 08/21/2023] [Accepted: 09/20/2023] [Indexed: 10/14/2023]
Abstract
Path integration (PI) is impaired early in Alzheimer's disease (AD) but reflects multiple sub-processes that may be differentially sensitive to AD. To characterize these sub-processes, we developed a novel generative linear-angular model of PI (GLAMPI) to fit the inbound paths of healthy elderly participants performing triangle completion, a popular PI task, in immersive virtual reality with real movement. The model fits seven parameters reflecting the encoding, calculation, and production errors associated with inaccuracies in PI. We compared these parameters across younger and older participants and patients with mild cognitive impairment (MCI), including those with (MCI+) and without (MCI-) cerebrospinal fluid biomarkers of AD neuropathology. MCI patients showed overestimation of the angular turn in the outbound path and more variable inbound distances and directions compared with healthy elderly. MCI+ were best distinguished from MCI- patients by overestimation of outbound turns and more variable inbound directions. Our results suggest that overestimation of turning underlies the PI errors seen in patients with early AD, indicating specific neural pathways and diagnostic behaviors for further research.
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Affiliation(s)
- Andrea Castegnaro
- UCL Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AZ, UK; UCL Queen Square Institute of Neurology, University College London, Queen Square, London WC1N 3BG, UK
| | - Zilong Ji
- UCL Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AZ, UK; Peking-Tsinghua Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Haidian District, Beijing 100871, China
| | - Katarzyna Rudzka
- UCL Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AZ, UK
| | - Dennis Chan
- UCL Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AZ, UK
| | - Neil Burgess
- UCL Institute of Cognitive Neuroscience, University College London, 17 Queen Square, London WC1N 3AZ, UK; UCL Queen Square Institute of Neurology, University College London, Queen Square, London WC1N 3BG, UK.
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Scheijbeler EP, de Haan W, Stam CJ, Twisk JWR, Gouw AA. Longitudinal resting-state EEG in amyloid-positive patients along the Alzheimer's disease continuum: considerations for clinical trials. Alzheimers Res Ther 2023; 15:182. [PMID: 37858173 PMCID: PMC10585755 DOI: 10.1186/s13195-023-01327-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 10/06/2023] [Indexed: 10/21/2023]
Abstract
BACKGROUND To enable successful inclusion of electroencephalography (EEG) outcome measures in Alzheimer's disease (AD) clinical trials, we retrospectively mapped the progression of resting-state EEG measures over time in amyloid-positive patients with mild cognitive impairment (MCI) or dementia due to AD. METHODS Resting-state 21-channel EEG was recorded in 148 amyloid-positive AD patients (MCI, n = 88; dementia due to AD, n = 60). Two or more EEG recordings were available for all subjects. We computed whole-brain and regional relative power (i.e., theta (4-8 Hz), alpha1 (8-10 Hz), alpha2 (10-13 Hz), beta (13-30 Hz)), peak frequency, signal variability (i.e., theta permutation entropy), and functional connectivity values (i.e., alpha and beta corrected amplitude envelope correlation, theta phase lag index, weighted symbolic mutual information, inverted joint permutation entropy). Whole-group linear mixed effects models were used to model the development of EEG measures over time. Group-wise analysis was performed to investigate potential differences in change trajectories between the MCI and dementia subgroups. Finally, we estimated the minimum sample size required to detect different treatment effects (i.e., 50% less deterioration, stabilization, or 50% improvement) on the development of EEG measures over time, in hypothetical clinical trials of 1- or 2-year duration. RESULTS Whole-group analysis revealed significant regional and global oscillatory slowing over time (i.e., increased relative theta power, decreased beta power), with strongest effects for temporal and parieto-occipital regions. Disease severity at baseline influenced the EEG measures' rates of change, with fastest deterioration reported in MCI patients. Only AD dementia patients displayed a significant decrease of the parieto-occipital peak frequency and theta signal variability over time. We estimate that 2-year trials, focusing on amyloid-positive MCI patients, require 36 subjects per arm (2 arms, 1:1 randomization, 80% power) to detect a stabilizing treatment effect on temporal relative theta power. CONCLUSIONS Resting-state EEG measures could facilitate early detection of treatment effects on neuronal function in AD patients. Their sensitivity depends on the region-of-interest and disease severity of the study population. Conventional spectral measures, particularly recorded from temporal regions, present sensitive AD treatment monitoring markers.
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Affiliation(s)
- Elliz P Scheijbeler
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands.
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands.
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands.
| | - Willem de Haan
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
| | - Cornelis J Stam
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
| | - Jos W R Twisk
- Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
| | - Alida A Gouw
- Clinical Neurophysiology and MEG Center, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, Netherlands
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, Netherlands
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Fernandes M, Chiaravalloti A, Nuccetelli M, Placidi F, Izzi F, Camedda R, Bernardini S, Sancesario G, Schillaci O, Mercuri NB, Liguori C. Sleep Dysregulation Is Associated with 18F-FDG PET and Cerebrospinal Fluid Biomarkers in Alzheimer's Disease. J Alzheimers Dis Rep 2023; 7:845-854. [PMID: 37662614 PMCID: PMC10473116 DOI: 10.3233/adr-220111] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Accepted: 07/11/2023] [Indexed: 09/05/2023] Open
Abstract
Background Sleep impairment has been commonly reported in Alzheimer's disease (AD) patients. The association between sleep dysregulation and AD biomarkers has been separately explored in mild cognitive impairment (MCI) and AD patients. Objective The present study investigated cerebrospinal-fluid (CSF) and 18F-fluoro-deoxy-glucose positron emission tomography (18F-FDG-PET) biomarkers in MCI and AD patients in order to explore their association with sleep parameters measured with polysomnography (PSG). Methods MCI and AD patients underwent PSG, 18F-FDG-PET, and CSF analysis for detecting and correlating these biomarkers with sleep architecture. Results Thirty-five patients were included in the study (9 MCI and 26 AD patients). 18F-FDG uptake in left Brodmann area 31 (owing to the posterior cingulate cortex) correlated negatively with REM sleep latency (p = 0.013) and positively with REM sleep (p = 0.033). 18F-FDG uptake in the hippocampus was negatively associated with sleep onset latency (p = 0.041). Higher CSF orexin levels were associated with higher sleep onset latency (p = 0.042), Non-REM stage 1 of sleep (p = 0.031), wake after sleep onset (p = 0.028), and lower sleep efficiency (p = 0.045). CSF levels of Aβ42 correlated negatively with the wake bouts index (p = 0.002). CSF total-tau and phosphorylated tau levels correlated positively with total sleep time (p = 0.045) and time in bed (p = 0.031), respectively. Conclusion Sleep impairment, namely sleep fragmentation, REM sleep dysregulation, and difficulty in initiating sleep correlates with AD biomarkers, suggesting an effect of sleep on the pathological processes in different AD stages. Targeting sleep for counteracting the AD pathological processes represents a timely need for clinicians and researchers.
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Affiliation(s)
- Mariana Fernandes
- Department of Systems Medicine, University of Rome “Tor Vergata”, Rome, Italy
| | - Agostino Chiaravalloti
- Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Rome, Italy
- IRCCS Neuromed, Pozzilli, Italy
| | - Marzia Nuccetelli
- Department of Clinical Biochemistry and Molecular Biology, University of Rome “Tor Vergata”, Rome, Italy
| | - Fabio Placidi
- Department of Systems Medicine, University of Rome “Tor Vergata”, Rome, Italy
- Sleep Medicine Centre, Neurology Unit, University Hospital of Rome “Tor Vergata”, Rome, Italy
| | - Francesca Izzi
- Sleep Medicine Centre, Neurology Unit, University Hospital of Rome “Tor Vergata”, Rome, Italy
| | - Riccardo Camedda
- Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Rome, Italy
| | - Sergio Bernardini
- Department of Clinical Biochemistry and Molecular Biology, University of Rome “Tor Vergata”, Rome, Italy
| | - Giuseppe Sancesario
- Sleep Medicine Centre, Neurology Unit, University Hospital of Rome “Tor Vergata”, Rome, Italy
| | - Orazio Schillaci
- Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Rome, Italy
| | - Nicola Biagio Mercuri
- Department of Systems Medicine, University of Rome “Tor Vergata”, Rome, Italy
- Sleep Medicine Centre, Neurology Unit, University Hospital of Rome “Tor Vergata”, Rome, Italy
| | - Claudio Liguori
- Department of Systems Medicine, University of Rome “Tor Vergata”, Rome, Italy
- Sleep Medicine Centre, Neurology Unit, University Hospital of Rome “Tor Vergata”, Rome, Italy
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Dimou E, Katsinelos T, Meisl G, Tuck BJ, Keeling S, Smith AE, Hidari E, Lam JYL, Burke M, Lövestam S, Ranasinghe RT, McEwan WA, Klenerman D. Super-resolution imaging unveils the self-replication of tau aggregates upon seeding. Cell Rep 2023; 42:112725. [PMID: 37393617 PMCID: PMC7614924 DOI: 10.1016/j.celrep.2023.112725] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2022] [Revised: 04/03/2023] [Accepted: 06/14/2023] [Indexed: 07/04/2023] Open
Abstract
Tau is a soluble protein interacting with tubulin to stabilize microtubules. However, under pathological conditions, it becomes hyperphosphorylated and aggregates, a process that can be induced by treating cells with exogenously added tau fibrils. Here, we employ single-molecule localization microscopy to resolve the aggregate species formed in early stages of seeded tau aggregation. We report that entry of sufficient tau assemblies into the cytosol induces the self-replication of small tau aggregates, with a doubling time of 5 h inside HEK cells and 1 day in murine primary neurons, which then grow into fibrils. Seeding occurs in the vicinity of the microtubule cytoskeleton, is accelerated by the proteasome, and results in release of small assemblies into the media. In the absence of seeding, cells still spontaneously form small aggregates at lower levels. Overall, our work provides a quantitative picture of the early stages of templated seeded tau aggregation in cells.
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Affiliation(s)
- Eleni Dimou
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK; UK Dementia Research Institute at University of Cambridge, Department of Clinical Neurosciences, Hills Road, Cambridge CB2 0AH, UK.
| | - Taxiarchis Katsinelos
- UK Dementia Research Institute at University of Cambridge, Department of Clinical Neurosciences, Hills Road, Cambridge CB2 0AH, UK; MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, UK
| | - Georg Meisl
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK
| | - Benjamin J Tuck
- UK Dementia Research Institute at University of Cambridge, Department of Clinical Neurosciences, Hills Road, Cambridge CB2 0AH, UK
| | - Sophie Keeling
- UK Dementia Research Institute at University of Cambridge, Department of Clinical Neurosciences, Hills Road, Cambridge CB2 0AH, UK
| | - Annabel E Smith
- UK Dementia Research Institute at University of Cambridge, Department of Clinical Neurosciences, Hills Road, Cambridge CB2 0AH, UK
| | - Eric Hidari
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK; UK Dementia Research Institute at University of Cambridge, Department of Clinical Neurosciences, Hills Road, Cambridge CB2 0AH, UK
| | - Jeff Y L Lam
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK; UK Dementia Research Institute at University of Cambridge, Department of Clinical Neurosciences, Hills Road, Cambridge CB2 0AH, UK
| | - Melanie Burke
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK; UK Dementia Research Institute at University of Cambridge, Department of Clinical Neurosciences, Hills Road, Cambridge CB2 0AH, UK
| | - Sofia Lövestam
- MRC Laboratory of Molecular Biology, Francis Crick Avenue, Cambridge CB2 0QH, UK
| | - Rohan T Ranasinghe
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK; UK Dementia Research Institute at University of Cambridge, Department of Clinical Neurosciences, Hills Road, Cambridge CB2 0AH, UK
| | - William A McEwan
- UK Dementia Research Institute at University of Cambridge, Department of Clinical Neurosciences, Hills Road, Cambridge CB2 0AH, UK
| | - David Klenerman
- Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, UK; UK Dementia Research Institute at University of Cambridge, Department of Clinical Neurosciences, Hills Road, Cambridge CB2 0AH, UK.
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9
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Wang Y, Ye X, Song B, Yan Y, Ma W, Shi J. Features of event-related potentials during retrieval of episodic memory in patients with mild cognitive impairment due to Alzheimer's disease. Front Neurosci 2023; 17:1185228. [PMID: 37469837 PMCID: PMC10352679 DOI: 10.3389/fnins.2023.1185228] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 06/20/2023] [Indexed: 07/21/2023] Open
Abstract
Objective To provide a rigorous comparison between patients with mild cognitive impairment due to Alzheimer's disease (MCI-AD) and healthy elderly, as well as to assess the value of electroencephalography (EEG) in terms of early diagnosis, we conducted a neutral image recognition memory task involving individuals with positive biomarkers including β amyloid deposition, pathologic tau or neurodegeneration. Methods The task involving study and test blocks was designed to evaluate participants' recognition memory. Electroencephalogram was recorded synchronously to elicit event-related potentials in patients with MCI-AD and healthy control subjects. We further analyzed differences between groups or conditions in terms of behavioral performance, time domain, and time-frequency domain. Results The MCI-AD cohort showed a slower response time to old/new images and had low accuracy regarding behavioral performance. The amplitude of the late positive complex for the old/new effects was significantly suppressed in the MCI-AD cohort when compared with that in the HC cohort. The amplitude of the late old/new effects was correlated with the Auditory Verbal Learning Test recognition score in all participants. The time-frequency domain analysis revealed that correct recognition of old items elicited a decrease in beta power, mainly limited to the HC cohort. Moreover, the combination of behavioral (processing speed and accuracy) and electrophysiological (average amplitude and relative power of delta band) measures contributes to classifying patients with MCI-AD from healthy elderly people. Conclusion Changes of old/new effects, accuracy and response time are sensitive to the impairment of recognition memory in patients with MCI-AD and have moderate value in predicting the incipient stage of AD.
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10
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van Amerongen S, Kamps S, Kaijser KKM, Pijnenburg YAL, Scheltens P, Teunissen CE, Barkhof F, Ossenkoppele R, Rozemuller AJM, Stern RA, Hoozemans JJM, Vijverberg EGB. Severe CTE and TDP-43 pathology in a former professional soccer player with dementia: a clinicopathological case report and review of the literature. Acta Neuropathol Commun 2023; 11:77. [PMID: 37161501 PMCID: PMC10169296 DOI: 10.1186/s40478-023-01572-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Accepted: 04/20/2023] [Indexed: 05/11/2023] Open
Abstract
In the last decades, numerous post-mortem case series have documented chronic traumatic encephalopathy (CTE) in former contact-sport athletes, though reports of CTE pathology in former soccer players are scarce. This study presents a clinicopathological case of a former professional soccer player with young-onset dementia. The patient experienced early onset progressive cognitive decline and developed dementia in his mid-50 s, after playing soccer for 12 years at a professional level. While the clinical picture mimicked Alzheimer's disease, amyloid PET imaging did not provide evidence of elevated beta-amyloid plaque density. After he died in his mid-60 s, brain autopsy showed severe phosphorylated tau (p-tau) abnormalities fulfilling the neuropathological criteria for high-stage CTE, as well as astrocytic and oligodendroglial tau pathology in terms of tufted astrocytes, thorn-shaped astrocytes, and coiled bodies. Additionally, there were TAR DNA-binding protein 43 (TDP-43) positive cytoplasmic inclusions in the frontal lobe and hippocampus, and Amyloid Precursor Protein (APP) positivity in the axons of the white matter. A systematic review of the literature revealed only 13 other soccer players with postmortem diagnosis of CTE. Our report illustrates the complex clinicopathological correlation of CTE and the need for disease-specific biomarkers.
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Affiliation(s)
- Suzan van Amerongen
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands.
- Department of Neurology, Amsterdam UMC, location Vrije Universiteit Amsterdam, Alzheimer Center Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, the Netherlands.
- Department of Neurology, Boston University Alzheimer's Disease Research Center, Boston University CTE Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA.
| | - Suzie Kamps
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Department of Neurology, Amsterdam UMC, location Vrije Universiteit Amsterdam, Alzheimer Center Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, the Netherlands
| | - Kyra K M Kaijser
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Department of Pathology, Amsterdam UMC, location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Yolande A L Pijnenburg
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Department of Neurology, Amsterdam UMC, location Vrije Universiteit Amsterdam, Alzheimer Center Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, the Netherlands
| | - Philip Scheltens
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Department of Neurology, Amsterdam UMC, location Vrije Universiteit Amsterdam, Alzheimer Center Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, the Netherlands
- EQT Life Sciences, Amsterdam, the Netherlands
| | - Charlotte E Teunissen
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam UMC, Location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Frederik Barkhof
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Department of Radiology & Nuclear Medicine, Amsterdam UMC, Location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Rik Ossenkoppele
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Department of Neurology, Amsterdam UMC, location Vrije Universiteit Amsterdam, Alzheimer Center Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, the Netherlands
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Annemieke J M Rozemuller
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, the Netherlands
- Department of Pathology, Amsterdam UMC, location Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - Robert A Stern
- Department of Neurology, Boston University Alzheimer's Disease Research Center, Boston University CTE Center, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
- Departments of Neurosurgery, and Anatomy and Neurobiology, Boston University Chobanian and Avedisian School of Medicine, Boston, MA, USA
| | | | - Everard G B Vijverberg
- Department of Neurology, Amsterdam UMC, location Vrije Universiteit Amsterdam, Alzheimer Center Amsterdam, De Boelelaan 1117, 1081 HV, Amsterdam, the Netherlands
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11
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den Hoedt S, Dorst-Lagerwerf KY, de Vries HE, Rozemuller AJ, Scheltens P, Walter J, Sijbrands EJ, Martinez-Martinez P, Verhoeven AJ, Teunissen CE, Mulder MT. Sphingolipids in Cerebrospinal Fluid and Plasma Lipoproteins of APOE4 Homozygotes and Non-APOE4 Carriers with Mild Cognitive Impairment versus Subjective Cognitive Decline. J Alzheimers Dis Rep 2023; 7:339-354. [DOI: 10.3233/adr220072] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2022] [Accepted: 02/24/2023] [Indexed: 03/18/2023] Open
Abstract
Background: Alzheimer’s disease (AD) patients display alterations in cerebrospinal fluid (CSF) and plasma sphingolipids. The APOE4 genotype increases the risk of developing AD. Objective: To test the hypothesis that the APOE4 genotype affects common sphingolipids in CSF and in plasma of patients with early stages of AD. Methods: Patients homozygous for APOE4 and non-APOE4 carriers with mild cognitive impairment (MCI; n = 20 versus 20) were compared to patients with subjective cognitive decline (SCD; n = 18 versus 20). Sphingolipids in CSF and plasma lipoproteins were determined by liquid-chromatography-tandem mass spectrometry. Aβ42 levels in CSF were determined by immunoassay. Results: APOE4 homozygotes displayed lower levels of sphingomyelin (SM; p = 0.042), SM(d18:1/18:0) (p = 0.026), and Aβ 42 (p < 0.001) in CSF than non-APOE4 carriers. CSF-Aβ 42 correlated with Cer(d18:1/18:0), SM(d18:1/18:0), and SM(d18:1/18:1) levels in APOE4 homozygotes (r > 0.49; p < 0.032) and with Cer(d18:1/24:1) in non-APOE4 carriers (r = 0.50; p = 0.025). CSF-Aβ 42 correlated positively with Cer(d18:1/24:0) in MCI (p = 0.028), but negatively in SCD patients (p = 0.019). Levels of Cer(d18:1/22:0) and long-chain SMs were inversely correlated with Mini-Mental State Examination score among MCI patients, independent of APOE4 genotype (r< –0.47; p < 0.039). Nevertheless, age and sex are stronger determinants of individual sphingolipid levels in CSF than either the APOE genotype or the cognitive state. In HDL, ratios of Cer(d18:1/18:0) and Cer(d18:1/22:0) to cholesterol were higher in APOE4 homozygotes than in non-APOE4 carriers (p = 0.048 and 0.047, respectively). Conclusion: The APOE4 genotype affects sphingolipid profiles of CSF and plasma lipoproteins already at early stages of AD. ApoE4 may contribute to the early development of AD through modulation of sphingolipid metabolism.
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Affiliation(s)
- Sandra den Hoedt
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | | | - Helga E. de Vries
- Department of Molecular Cell Biology and Immunology, Amsterdam Neuroscience, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, The Netherlands
| | - Annemieke J.M. Rozemuller
- Department of Pathology, Amsterdam Neuroscience, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, The Netherlands
| | - Philip Scheltens
- Department of Clinical Chemistry, The Alzheimer Center Amsterdam, and Neurochemistry Laboratory, Amsterdam Neuroscience, Amsterdam University Medical Center, VrijeUniversiteit Amsterdam, The Netherlands
| | - Jochen Walter
- Department of Neurology, University of Bonn, Bonn, Germany
| | - Eric J.G. Sijbrands
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Pilar Martinez-Martinez
- Department of Neuroscience, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
| | - Adrie J.M. Verhoeven
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Charlotte E. Teunissen
- Department of Clinical Chemistry, The Alzheimer Center Amsterdam, and Neurochemistry Laboratory, Amsterdam Neuroscience, Amsterdam University Medical Center, VrijeUniversiteit Amsterdam, The Netherlands
| | - Monique T. Mulder
- Department of Internal Medicine, Erasmus University Medical Center, Rotterdam, The Netherlands
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12
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Zou Y, Yu S, Ma X, Ma C, Mao C, Mu D, Li L, Gao J, Qiu L. How far is the goal of applying β-amyloid in cerebrospinal fluid for clinical diagnosis of Alzheimer's disease with standardization of measurements? Clin Biochem 2023; 112:33-42. [PMID: 36473516 DOI: 10.1016/j.clinbiochem.2022.11.013] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2022] [Revised: 11/02/2022] [Accepted: 11/30/2022] [Indexed: 12/12/2022]
Abstract
Cerebrospinal fluid (CSF) β-amyloid (Aβ) is important for early diagnosis of Alzheimer's disease (AD). However, the cohort distributions and cut-off values have large variation across different analytical assays, kits, and laboratories. In this review, we summarize the cut-off values and diagnostic performance for CSF Aβ1-42 and Aβ1-42/Aβ1-40, and explore the important effect factors. Based on the Alzheimer's Association external quality control program (AAQC program), the peer group coefficient of variation of manual ELISA assays for CSF Aβ1-42 was unsatisfied (>20%). Fully automated platforms with better performance have recently been developed, but still not widely applied. In 2020, the certified reference material (CRM) for CSF Aβ1-42 was launched; however, the AAQC 2021-round results did not show effective improvements. Thus, further development and popularization of CRM for CSF Aβ1-42 and Aβ1-40 are urgently required. Standardizing the diagnostic procedures of AD and related status and the pre-analytical protocols of CSF samples, improving detection performance of analytical assays, and popularizing the application of fully automated platforms are also important for the establishment of uniform cut-off values. Moreover, each laboratory should verify the applicability of uniform cut-off values, and evaluate whether it is necessary to establish its own population- and assay-specific cut-off values.
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Affiliation(s)
- Yutong Zou
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China
| | - Songlin Yu
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China
| | - Xiaoli Ma
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China; Medical Science Research Center, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China
| | - Chaochao Ma
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China
| | - Chenhui Mao
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing 100730, China
| | - Danni Mu
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China
| | - Lei Li
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China
| | - Jing Gao
- Department of Neurology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing 100730, China.
| | - Ling Qiu
- Department of Laboratory Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing 100730, China; State Key Laboratory of Complex Severe and Rare Diseases, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing 100730, China.
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13
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Hazan J, Wing M, Liu KY, Reeves S, Howard R. Clinical utility of cerebrospinal fluid biomarkers in the evaluation of cognitive impairment: a systematic review and meta-analysis. J Neurol Neurosurg Psychiatry 2023; 94:113-120. [PMID: 36096664 DOI: 10.1136/jnnp-2022-329530] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 08/29/2022] [Indexed: 01/14/2023]
Abstract
BACKGROUND The analytical and clinical validity of cerebrospinal (CSF) biomarkers has been extensively researched in dementia. Further work is needed to assess the ability of these biomarkers to improve diagnosis, management and health outcomes in the clinical setting OBJECTIVES: To assess the added value and clinical utility of CSF biomarkers in the diagnostic assessment of cognitively impaired patients under evaluation for Alzheimer's disease (AD). METHODS Systematic literature searches of Medline, EMBASE, PsycINFO and Web of Science research databases were conducted on 17 December 2022. Data from relevant studies were extracted and independently screened for quality using a tool for bias. Clinical utility was measured by clinicians' changes in diagnosis, diagnostic confidence and patient management (when available), after their examination of patients' CSF biomarkers. Cost-effectiveness was assessed by consideration of additional cost per patient and quality-adjusted life years. RESULTS Searches identified 17 studies comprising 2090 patient participants and 593 clinicians. The meta-analysis revealed that clinicians' use of CSF biomarkers resulted in a pooled percentage change in diagnosis of 25% (95% CI 14 to 37), an increase in diagnostic confidence of 14% (95% CI 9 to 18) and a pooled proportion of patients whose management changed of 31% (95% CI 12 to 50). CSF biomarkers were deemed cost-effective, particularly in memory services, where pre-test AD prevalence is higher compared with a primary care setting. CONCLUSIONS CSF biomarkers can be a helpful additional diagnostic tool for clinicians assessing patients with cognitive impairment. In particular, CSF biomarkers consistently improved clinicians' confidence in diagnosing AD and influenced on diagnostic change and patient management. Further research is needed to study the clinical utility of blood-based biomarkers in the clinical setting.
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Affiliation(s)
- Jemma Hazan
- Division of Psychiatry, University College London, London, UK
| | - Michelle Wing
- Division of Psychiatry, University College London, London, UK
| | - Kathy Y Liu
- Division of Psychiatry, University College London, London, UK
| | - Suzanne Reeves
- Division of Psychiatry, University College London, London, UK
| | - Robert Howard
- Division of Psychiatry, University College London, London, UK
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14
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Arafah A, Khatoon S, Rasool I, Khan A, Rather MA, Abujabal KA, Faqih YAH, Rashid H, Rashid SM, Bilal Ahmad S, Alexiou A, Rehman MU. The Future of Precision Medicine in the Cure of Alzheimer's Disease. Biomedicines 2023; 11:biomedicines11020335. [PMID: 36830872 PMCID: PMC9953731 DOI: 10.3390/biomedicines11020335] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2022] [Revised: 01/18/2023] [Accepted: 01/18/2023] [Indexed: 01/26/2023] Open
Abstract
This decade has seen the beginning of ground-breaking conceptual shifts in the research of Alzheimer's disease (AD), which acknowledges risk elements and the evolving wide spectrum of complicated underlying pathophysiology among the range of diverse neurodegenerative diseases. Significant improvements in diagnosis, treatments, and mitigation of AD are likely to result from the development and application of a comprehensive approach to precision medicine (PM), as is the case with several other diseases. This strategy will probably be based on the achievements made in more sophisticated research areas, including cancer. PM will require the direct integration of neurology, neuroscience, and psychiatry into a paradigm of the healthcare field that turns away from the isolated method. PM is biomarker-guided treatment at a systems level that incorporates findings of the thorough pathophysiology of neurodegenerative disorders as well as methodological developments. Comprehensive examination and categorization of interrelated and convergent disease processes, an explanation of the genomic and epigenetic drivers, a description of the spatial and temporal paths of natural history, biological markers, and risk markers, as well as aspects about the regulation, and the ethical, governmental, and sociocultural repercussions of findings at a subclinical level all require clarification and realistic execution. Advances toward a comprehensive systems-based approach to PM may finally usher in a new era of scientific and technical achievement that will help to end the complications of AD.
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Affiliation(s)
- Azher Arafah
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia
- Correspondence: (A.A.); (A.K.); (M.U.R.)
| | - Saima Khatoon
- Department of Medical Elementology and Toxicology, School of Chemical and Life Sciences, Jamia Hamdard, New Delhi 110062, India
| | - Iyman Rasool
- Department of Pathology, Government Medical College (GMC-Srinagar), Karan Nagar, Srinagar 190010, India
| | - Andleeb Khan
- Department of Pharmacology and Toxicology, College of Pharmacy, Jazan University, Jazan 45142, Saudi Arabia
- Correspondence: (A.A.); (A.K.); (M.U.R.)
| | - Mashoque Ahmad Rather
- Department of Molecular Pharmacology & Physiology, Bryd Alzheimer’s Research Institute, Morsani College of Medicine, University of South Florida, Tampa, FL 33620, USA
| | | | | | - Hina Rashid
- Department of Pharmacology and Toxicology, College of Pharmacy, Jazan University, Jazan 45142, Saudi Arabia
| | - Shahzada Mudasir Rashid
- Division of Veterinary Biochemistry, Faculty of Veterinary Sciences and Animal Husbandry, Sher-e-Kashmir University of Agricultural Sciences and Technology (SKUAST-K), Srinagar 190006, India
| | - Sheikh Bilal Ahmad
- Division of Veterinary Biochemistry, Faculty of Veterinary Sciences and Animal Husbandry, Sher-e-Kashmir University of Agricultural Sciences and Technology (SKUAST-K), Srinagar 190006, India
| | - Athanasios Alexiou
- Novel Global Community Educational Foundation, Hebersham, NSW 2770, Australia
- AFNP Med, Haidingergasse 29, 1030 Vienna, Austria
| | - Muneeb U. Rehman
- Department of Clinical Pharmacy, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia
- Correspondence: (A.A.); (A.K.); (M.U.R.)
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15
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Elzayat EM, Shahien SA, El-Sherif AA, Hosney M. miRNAs and Stem Cells as Promising Diagnostic and Therapeutic Targets for Alzheimer's Disease. J Alzheimers Dis 2023; 94:S203-S225. [PMID: 37212107 PMCID: PMC10473110 DOI: 10.3233/jad-221298] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 03/30/2023] [Indexed: 05/23/2023]
Abstract
Alzheimer's disease (AD) is a cumulative progressive neurodegenerative disease characterized mainly by impairment in cognitive functions accompanied by memory loss, disturbance in behavior and personality, and difficulties in learning. Although the main causes of AD pathogenesis are not fully understood yet, amyloid-β peptides and tau proteins are supposed to be responsible for AD onset and pathogenesis. Various demographic, genetic, and environmental risk factors are involved in AD onset and pathogenesis such as age, gender, several genes, lipids, malnutrition, and poor diet. Significant changes were observed in microRNA (miRNA) levels between normal and AD cases giving hope for a diagnostic procedure for AD through a simple blood test. As yet, only two classes of AD therapeutic drugs are approved by FDA. They are classified as acetylcholinesterase inhibitors and N-methyl-D-aspartate antagonists (NMDA). Unfortunately, they can only treat the symptoms but cannot cure AD or stop its progression. New therapeutic approaches were developed for AD treatment including acitretin due to its ability to cross blood-brain barrier in the brain of rats and mice and induce the expression of ADAM 10 gene, the α-secretase of human amyloid-β protein precursor, stimulating the non-amyloidogenic pathway for amyloid-β protein precursor processing resulting in amyloid-β reduction. Also stem cells may have a crucial role in AD treatment as they can improve cognitive functions and memory in AD rats through regeneration of damaged neurons. This review spotlights on promising diagnostic techniques such as miRNAs and therapeutic approaches such as acitretin and/or stem cells keeping in consideration AD pathogenesis, stages, symptoms, and risk factors.
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Affiliation(s)
- Emad M. Elzayat
- Zoology Department, Faculty of Science, Cairo University, Giza, Egypt
| | - Sherif A. Shahien
- Biotechnology/Bimolecular Chemistry Program, Faculty of Science, Helwan University, Cairo, Egypt
| | - Ahmed A. El-Sherif
- Department of Chemistry, Faculty of Science, Cairo University, Giza, Egypt
| | - Mohamed Hosney
- Zoology Department, Faculty of Science, Cairo University, Giza, Egypt
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16
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Tarawneh R, Kasper RS, Sanford J, Phuah C, Hassenstab J, Cruchaga C. Vascular endothelial-cadherin as a marker of endothelial injury in preclinical Alzheimer disease. Ann Clin Transl Neurol 2022; 9:1926-1940. [PMID: 36342663 PMCID: PMC9735377 DOI: 10.1002/acn3.51685] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Revised: 10/02/2022] [Accepted: 10/10/2022] [Indexed: 11/09/2022] Open
Abstract
OBJECTIVE Endothelial dysfunction is an early and prevalent pathology in Alzheimer disease (AD). We here investigate the value of vascular endothelial-cadherin (VEC) as a cerebrospinal fluid (CSF) marker of endothelial injury in preclinical AD. METHODS Cognitively normal participants (Clinical Dementia Rating [CDR] 0) from the Knight Washington University-ADRC were included in this study (n = 700). Preclinical Alzheimer's Cognitive Composite (PACC) scores, CSF VEC, tau, p-tau181, Aβ42/Aβ40, neurofilament light-chain (NFL) levels, and magnetic resonance imaging (MRI) assessments of white matter injury (WMI) were obtained from all participants. A subset of participants underwent brain amyloid imaging using positron emission tomography (amyloid-PET) (n = 534). Linear regression examined associations of CSF VEC with PACC and individual cognitive scores in preclinical AD. Mediation analyses examined whether CSF VEC mediated effects of CSF amyloid and tau markers on cognition in preclinical AD. RESULTS CSF VEC levels significantly correlated with PACC and individual cognitive scores in participants with amyloid (A+T±N±; n = 558) or those with amyloid and tau pathologies (A+T+N±; n = 259), after adjusting for covariates. CSF VEC also correlated with CSF measures of amyloid, tau, and neurodegeneration and global amyloid burden on amyloid-PET scans in our cohort. Importantly, our findings suggest that CSF VEC mediates associations of CSF Aβ42/Aβ40, p-tau181, and global amyloid burden with cognitive outcomes in preclinical AD. INTERPRETATION Our results support the utility of CSF VEC as a marker of endothelial injury in AD and highlight the importance of endothelial injury as an early pathology that contributes to cognitive impairment in even the earliest preclinical stages.
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Affiliation(s)
- Rawan Tarawneh
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew MexicoUSA,Center for Memory and AgingUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Rachel S. Kasper
- Department of NeurologyUniversity of New MexicoAlbuquerqueNew MexicoUSA
| | - Jessie Sanford
- Department of PsychiatryWashington University in St LouisSt. LouisMissouriUSA,NeuroGenomics and Informatics CenterWashington University in St LouisMissouriUSA
| | - Chia‐Ling Phuah
- NeuroGenomics and Informatics CenterWashington University in St LouisMissouriUSA,Department of NeurologyWashington University in St LouisSt. LouisMissouriUSA
| | - Jason Hassenstab
- Department of PsychologyWashington University in St LouisSt. LouisMissouriUSA
| | - Carlos Cruchaga
- Department of PsychiatryWashington University in St LouisSt. LouisMissouriUSA,NeuroGenomics and Informatics CenterWashington University in St LouisMissouriUSA
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17
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White H, Webb R, McKnight I, Legg K, Lee C, Lee PH, Spicer OS, Shim JW. TRPV4 mRNA is elevated in the caudate nucleus with NPH but not in Alzheimer's disease. Front Genet 2022; 13:936151. [PMID: 36406122 PMCID: PMC9670164 DOI: 10.3389/fgene.2022.936151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2022] [Accepted: 10/17/2022] [Indexed: 01/04/2023] Open
Abstract
Symptoms of normal pressure hydrocephalus (NPH) and Alzheimer's disease (AD) are somewhat similar, and it is common to misdiagnose these two conditions. Although there are fluid markers detectable in humans with NPH and AD, determining which biomarker is optimal in representing genetic characteristics consistent throughout species is poorly understood. Here, we hypothesize that NPH can be differentiated from AD with mRNA biomarkers of unvaried proximity to telomeres. We examined human caudate nucleus tissue samples for the expression of transient receptor potential cation channel subfamily V member 4 (TRPV4) and amyloid precursor protein (APP). Using the genome data viewer, we analyzed the mutability of TRPV4 and other genes in mice, rats, and humans through matching nucleotides of six genes of interest and one house keeping gene with two factors associated with high mutation rate: 1) proximity to telomeres or 2) high adenine and thymine (A + T) content. We found that TRPV4 and microtubule associated protein tau (MAPT) mRNA were elevated in NPH. In AD, mRNA expression of TRPV4 was unaltered unlike APP and other genes. In mice, rats, and humans, the nucleotide size of TRPV4 did not vary, while in other genes, the sizes were inconsistent. Proximity to telomeres in TRPV4 was <50 Mb across species. Our analyses reveal that TRPV4 gene size and mutability are conserved across three species, suggesting that TRPV4 can be a potential link in the pathophysiology of chronic hydrocephalus in aged humans (>65 years) and laboratory rodents at comparable ages.
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Affiliation(s)
- Hunter White
- Department of Biomedical Engineering, Marshall University, Huntington, WV, United States
| | - Ryan Webb
- Department of Biomedical Engineering, Marshall University, Huntington, WV, United States
| | - Ian McKnight
- Department of Biomedical Engineering, Marshall University, Huntington, WV, United States
| | - Kaitlyn Legg
- Department of Biomedical Engineering, Marshall University, Huntington, WV, United States
| | - Chan Lee
- Department of Anesthesia, Indiana University Health Arnett Hospital, Lafayette, IN, United States
| | - Peter H.U. Lee
- Department of Cardiothoracic Surgery, Southcoast Health, Fall River, MA, United States,Department of Pathology and Laboratory Medicine, Brown University, Providence, RI, United States
| | - Olivia Smith Spicer
- National Institute of Mental Health, National Institute of Health, Bethesda, MD, United States
| | - Joon W. Shim
- Department of Biomedical Engineering, Marshall University, Huntington, WV, United States,*Correspondence: Joon W. Shim,
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18
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Fernandes M, Manfredi N, Aluisantonio L, Franchini F, Chiaravalloti A, Izzi F, Di Santo S, Schillaci O, Mercuri NB, Placidi F, Liguori C. Cognitive functioning, cerebrospinal fluid Alzheimer's disease biomarkers and cerebral glucose metabolism in late-onset epilepsy of unknown aetiology: A prospective study. Eur J Neurosci 2022; 56:5384-5396. [PMID: 35678770 DOI: 10.1111/ejn.15734] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 05/16/2022] [Accepted: 06/04/2022] [Indexed: 12/14/2022]
Abstract
Epilepsy is increasing, being more common in older adults, with more than 20% of late-onset cases with unknown aetiology (LOEU). Although epilepsy was associated with cognitive impairment, few studies evaluated the trajectories of cognitive decline in patients with LOEU. The present study aimed at assessing biomarkers of Alzheimer's disease (AD) in patients with LOEU and evaluating their cognitive performance for 12 months. For this study, 55 patients diagnosed with LOEU and 21 controls were included. Participants underwent cognitive evaluation and cerebrospinal fluid (CSF) biomarker analysis (ß-amyloid42 , tau proteins) before starting anti-seizure medication and then repeated the cognitive evaluation at the 12-month follow-up. A subgroup of LOEU patients and controls also performed 18 F-fluoro-2-deoxy-D-glucose positron emission tomography (18 F-FDG PET) before starting anti-seizure medication. At baseline, LOEU patients showed lower Mini-Mental State Examination (MMSE) score, worse cognitive performance in several domains, lower β-amyloid42 and higher tau proteins CSF levels than controls. Significantly reduced glucose consumption was observed in the right posterior cingulate cortex and left praecuneus areas in LOEU patients than controls, and this finding correlated with memory impairment. In the longitudinal analysis, a significant decrease in MMSE and an increase in verbal fluency scores were found in LOEU patients. These findings evidence that LOEU patients have a significant cognitive impairment, and alteration of cerebral glucose consumption and CSF AD biomarkers than controls. Moreover, they showed a progressive global cognitive decline at follow-up, although verbal fluency was preserved. Further studies are needed to better understand the pathophysiological aspects of LOEU and its association with AD.
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Affiliation(s)
- Mariana Fernandes
- Epilepsy Centre, Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | - Natalia Manfredi
- Epilepsy Centre, Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | - Lavinia Aluisantonio
- Epilepsy Centre, Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | | | - Agostino Chiaravalloti
- Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy.,IRCCS Neuromed, Pozzilli, Italy
| | - Francesca Izzi
- Epilepsy Centre, Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | | | - Orazio Schillaci
- Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy.,IRCCS Neuromed, Pozzilli, Italy
| | - Nicola Biagio Mercuri
- Epilepsy Centre, Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy.,IRCCS Fondazione Santa Lucia, Rome, Italy
| | - Fabio Placidi
- Epilepsy Centre, Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
| | - Claudio Liguori
- Epilepsy Centre, Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Rome, Italy
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19
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Holleman J, Adagunodo S, Kåreholt I, Hagman G, Aspö M, Udeh-Momoh CT, Solomon A, Kivipelto M, Sindi S. Cortisol, cognition and Alzheimer's disease biomarkers among memory clinic patients. BMJ Neurol Open 2022; 4:e000344. [PMID: 36277478 PMCID: PMC9582323 DOI: 10.1136/bmjno-2022-000344] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 10/05/2022] [Indexed: 11/03/2022] Open
Abstract
Objective This study aims to investigate the relationship between diurnal cortisol patterns, cognition and Alzheimer's disease (AD) biomarkers in memory clinic patients. Method Memory clinic patients were recruited from Karolinska University Hospital in Sweden (n=155). Diurnal cortisol patterns were assessed using five measures: awakening levels, cortisol awakening response, bedtime levels, the ratio of awakening to bedtime levels (AM/PM ratio) and total daily output. Cognition was measured in five domains: memory, working memory, processing speed, perceptual reasoning and overall cognition. AD biomarkers Aβ42, total tau and phosphorylated tau were assessed from cerebrospinal fluid (CSF). Cognition was measured at follow-up (average 32 months) in a subsample of participants (n=57). Results In assessing the associations between cortisol and cognition, higher awakening cortisol levels were associated with greater processing speed at baseline. No relationship was found between diurnal cortisol patterns and change in cognition over time or CSF AD biomarkers in the total sample. After stratification by CSF Aβ42 levels, higher awakening cortisol levels were associated with worse memory performance in amyloid-positive participants. In amyloid-negative participants, higher bedtime cortisol levels and a lower AM/PM ratio were associated with lower overall cognition, greater awakening cortisol levels were associated with better processing speed, and a higher AM/PM ratio was associated with better perceptual reasoning. Additionally, higher awakening cortisol levels were associated with lower CSF Aβ42 levels in amyloid-positive participants, while higher bedtime cortisol levels and a lower AM/PM ratio were associated with higher CSF total tau in amyloid-negative participants. Conclusions Our findings suggest that diurnal cortisol patterns are associated with cognitive function and provide new insights into the association between diurnal cortisol patterns and AD-related CSF biomarkers. Further research is needed to examine the complex relationship between cortisol, cognition and brain pathology.
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Affiliation(s)
- Jasper Holleman
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden
| | - Sofia Adagunodo
- Memory Clinic Zentralschweiz, Luzerner Psychiatrie, Pfaffnau-Sankt Urban, Switzerland
| | - Ingemar Kåreholt
- Institute of Gerontology, School of Health and Welfare, Aging Research Network – Jönköping (ARN-J), Jönköping University, Jonkoping, Sweden
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet and Stockholm University, Stockholm, Sweden
| | - Göran Hagman
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Malin Aspö
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
| | - Chinedu T Udeh-Momoh
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Faculty of Medicine, Imperial College London, London, UK
| | - Alina Solomon
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Faculty of Medicine, Imperial College London, London, UK
- Institute of Clinical Medicine, Neurology, University of Eastern Finland, Kuopio, Finland
| | - Miia Kivipelto
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden
- Theme Inflammation and Aging, Karolinska University Hospital, Stockholm, Sweden
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Faculty of Medicine, Imperial College London, London, UK
- Institute of Clinical Medicine, Neurology, University of Eastern Finland, Kuopio, Finland
- Institute of Public Health and Clinical Nutrition, University of Eastern Finland, Kuopio, Finland
| | - Shireen Sindi
- Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences, and Society, Karolinska Institutet, Stockholm, Sweden
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Faculty of Medicine, Imperial College London, London, UK
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20
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Dubbelman MA, Verrijp M, Terwee CB, Jutten RJ, Postema MC, Barkhof F, Berckel BNM, Gillissen F, Teeuwen V, Teunissen C, van de Flier WM, Scheltens P, Sikkes SAM. Determining the Minimal Important Change of Everyday Functioning in Dementia: Pursuing Clinical Meaningfulness. Neurology 2022; 99:e954-e964. [PMID: 35641309 PMCID: PMC9502738 DOI: 10.1212/wnl.0000000000200781] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2021] [Accepted: 04/11/2022] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Decline in everyday functioning is a key clinical change in Alzheimer disease and related disorders (ADRD). An important challenge remains the determination of what constitutes a clinically meaningful change in everyday functioning. We aimed to investigate this by establishing the minimal important change (MIC): the smallest amount of change that has a meaningful effect on patients' lives. We retrospectively investigated meaningful change in a memory clinic cohort. METHODS In the first, qualitative part of the study, community-recruited informal caregivers of patients with ADRD and memory clinic clinicians completed a survey in which they judged various situations representing changes in everyday functioning. Their judgments of meaningful change were used to determine thresholds for MIC, both for decline and improvement, on the Amsterdam Instrumental Activities of Daily Living (IADL) Questionnaire. In the second, quantitative part, we applied these values in an independent longitudinal cohort study of unselected memory clinic patients. RESULTS MIC thresholds were established at the average threshold of caregivers (N = 1,629; 62.4 ± 9.5 years; 77% female) and clinicians (N = 13): -2.2 points for clinically meaningful decline and +5.0 points for clinically meaningful improvement. Memory clinic patients (N = 230; 64.3 ± 7.7 years; 39% female; 60% dementia diagnosis) were followed for 1 year, 102 (45%) of whom showed a decline larger than the MIC, after a mean of 6.7 ± 3.5 months. Patients with a dementia diagnosis and more atrophy of the medial temporal lobe had larger odds (odds ratio [OR] = 3.4, 95% CI [1.5-7.8] and OR = 5.0, 95% CI [1.2-20.0], respectively) for passing the MIC threshold for decline than those with subjective cognitive complaints and no atrophy. DISCUSSION We were able to operationalize clinically meaningful decline in IADL by determining the MIC. The usefulness of the MIC was supported by our findings from the clinical sample that nearly half of a sample of unselected memory clinic patients showed a meaningful decline in less than a year. Disease stage and medial temporal atrophy were predictors of functional decline greater than the MIC. Our findings provide guidance in interpreting changes in IADL and may help evaluate treatment effects and monitor disease progression.
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Affiliation(s)
- Mark A Dubbelman
- From the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (M.A.D., M.V., M.C.P., F.G., V.T., W.M.F., P.S., S.A.M.S.); Department of Epidemiology and Data Science, Amsterdam UMC, The Netherlands (C.B.T., W.M.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (R.J.J.); Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (F.B., B.N.M.B.); Institutes of Neurology and Healthcare Engineering, University College London, United Kingdom (F.B.); Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands (C.T.); and Faculty of Behavioural and Movement Sciences (S.A.M.S.), Clinical Developmental Psychology & Clinical Neuropsychology, Vrije Universiteit Amsterdam, the Netherlands.
| | - Merike Verrijp
- From the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (M.A.D., M.V., M.C.P., F.G., V.T., W.M.F., P.S., S.A.M.S.); Department of Epidemiology and Data Science, Amsterdam UMC, The Netherlands (C.B.T., W.M.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (R.J.J.); Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (F.B., B.N.M.B.); Institutes of Neurology and Healthcare Engineering, University College London, United Kingdom (F.B.); Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands (C.T.); and Faculty of Behavioural and Movement Sciences (S.A.M.S.), Clinical Developmental Psychology & Clinical Neuropsychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Caroline B Terwee
- From the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (M.A.D., M.V., M.C.P., F.G., V.T., W.M.F., P.S., S.A.M.S.); Department of Epidemiology and Data Science, Amsterdam UMC, The Netherlands (C.B.T., W.M.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (R.J.J.); Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (F.B., B.N.M.B.); Institutes of Neurology and Healthcare Engineering, University College London, United Kingdom (F.B.); Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands (C.T.); and Faculty of Behavioural and Movement Sciences (S.A.M.S.), Clinical Developmental Psychology & Clinical Neuropsychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Roos J Jutten
- From the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (M.A.D., M.V., M.C.P., F.G., V.T., W.M.F., P.S., S.A.M.S.); Department of Epidemiology and Data Science, Amsterdam UMC, The Netherlands (C.B.T., W.M.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (R.J.J.); Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (F.B., B.N.M.B.); Institutes of Neurology and Healthcare Engineering, University College London, United Kingdom (F.B.); Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands (C.T.); and Faculty of Behavioural and Movement Sciences (S.A.M.S.), Clinical Developmental Psychology & Clinical Neuropsychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Merel C Postema
- From the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (M.A.D., M.V., M.C.P., F.G., V.T., W.M.F., P.S., S.A.M.S.); Department of Epidemiology and Data Science, Amsterdam UMC, The Netherlands (C.B.T., W.M.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (R.J.J.); Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (F.B., B.N.M.B.); Institutes of Neurology and Healthcare Engineering, University College London, United Kingdom (F.B.); Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands (C.T.); and Faculty of Behavioural and Movement Sciences (S.A.M.S.), Clinical Developmental Psychology & Clinical Neuropsychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Frederik Barkhof
- From the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (M.A.D., M.V., M.C.P., F.G., V.T., W.M.F., P.S., S.A.M.S.); Department of Epidemiology and Data Science, Amsterdam UMC, The Netherlands (C.B.T., W.M.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (R.J.J.); Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (F.B., B.N.M.B.); Institutes of Neurology and Healthcare Engineering, University College London, United Kingdom (F.B.); Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands (C.T.); and Faculty of Behavioural and Movement Sciences (S.A.M.S.), Clinical Developmental Psychology & Clinical Neuropsychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Bart N M Berckel
- From the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (M.A.D., M.V., M.C.P., F.G., V.T., W.M.F., P.S., S.A.M.S.); Department of Epidemiology and Data Science, Amsterdam UMC, The Netherlands (C.B.T., W.M.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (R.J.J.); Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (F.B., B.N.M.B.); Institutes of Neurology and Healthcare Engineering, University College London, United Kingdom (F.B.); Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands (C.T.); and Faculty of Behavioural and Movement Sciences (S.A.M.S.), Clinical Developmental Psychology & Clinical Neuropsychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Freek Gillissen
- From the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (M.A.D., M.V., M.C.P., F.G., V.T., W.M.F., P.S., S.A.M.S.); Department of Epidemiology and Data Science, Amsterdam UMC, The Netherlands (C.B.T., W.M.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (R.J.J.); Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (F.B., B.N.M.B.); Institutes of Neurology and Healthcare Engineering, University College London, United Kingdom (F.B.); Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands (C.T.); and Faculty of Behavioural and Movement Sciences (S.A.M.S.), Clinical Developmental Psychology & Clinical Neuropsychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Vivianne Teeuwen
- From the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (M.A.D., M.V., M.C.P., F.G., V.T., W.M.F., P.S., S.A.M.S.); Department of Epidemiology and Data Science, Amsterdam UMC, The Netherlands (C.B.T., W.M.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (R.J.J.); Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (F.B., B.N.M.B.); Institutes of Neurology and Healthcare Engineering, University College London, United Kingdom (F.B.); Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands (C.T.); and Faculty of Behavioural and Movement Sciences (S.A.M.S.), Clinical Developmental Psychology & Clinical Neuropsychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Charlotte Teunissen
- From the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (M.A.D., M.V., M.C.P., F.G., V.T., W.M.F., P.S., S.A.M.S.); Department of Epidemiology and Data Science, Amsterdam UMC, The Netherlands (C.B.T., W.M.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (R.J.J.); Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (F.B., B.N.M.B.); Institutes of Neurology and Healthcare Engineering, University College London, United Kingdom (F.B.); Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands (C.T.); and Faculty of Behavioural and Movement Sciences (S.A.M.S.), Clinical Developmental Psychology & Clinical Neuropsychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Wiesje M van de Flier
- From the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (M.A.D., M.V., M.C.P., F.G., V.T., W.M.F., P.S., S.A.M.S.); Department of Epidemiology and Data Science, Amsterdam UMC, The Netherlands (C.B.T., W.M.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (R.J.J.); Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (F.B., B.N.M.B.); Institutes of Neurology and Healthcare Engineering, University College London, United Kingdom (F.B.); Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands (C.T.); and Faculty of Behavioural and Movement Sciences (S.A.M.S.), Clinical Developmental Psychology & Clinical Neuropsychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Philip Scheltens
- From the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (M.A.D., M.V., M.C.P., F.G., V.T., W.M.F., P.S., S.A.M.S.); Department of Epidemiology and Data Science, Amsterdam UMC, The Netherlands (C.B.T., W.M.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (R.J.J.); Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (F.B., B.N.M.B.); Institutes of Neurology and Healthcare Engineering, University College London, United Kingdom (F.B.); Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands (C.T.); and Faculty of Behavioural and Movement Sciences (S.A.M.S.), Clinical Developmental Psychology & Clinical Neuropsychology, Vrije Universiteit Amsterdam, the Netherlands
| | - Sietske A M Sikkes
- From the Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (M.A.D., M.V., M.C.P., F.G., V.T., W.M.F., P.S., S.A.M.S.); Department of Epidemiology and Data Science, Amsterdam UMC, The Netherlands (C.B.T., W.M.F.); Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston (R.J.J.); Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands (F.B., B.N.M.B.); Institutes of Neurology and Healthcare Engineering, University College London, United Kingdom (F.B.); Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit Amsterdam, The Netherlands (C.T.); and Faculty of Behavioural and Movement Sciences (S.A.M.S.), Clinical Developmental Psychology & Clinical Neuropsychology, Vrije Universiteit Amsterdam, the Netherlands
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21
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Castegnaro A, Howett D, Li A, Harding E, Chan D, Burgess N, King J. Assessing mild cognitive impairment using object-location memory in immersive virtual environments. Hippocampus 2022; 32:660-678. [PMID: 35916343 PMCID: PMC9543035 DOI: 10.1002/hipo.23458] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 06/24/2022] [Accepted: 07/16/2022] [Indexed: 11/12/2022]
Abstract
Pathological changes in the medial temporal lobe (MTL) are found in the early stages of Alzheimer's disease (AD) and aging. The earliest pathological accumulation of tau colocalizes with the areas of the MTL involved in object processing as part of a wider anterolateral network. Here, we sought to assess the diagnostic potential of memory for object locations in iVR environments in individuals at high risk of AD dementia (amnestic mild cognitive impairment [aMCI] n = 23) as compared to age-related cognitive decline. Consistent with our primary hypothesis that early AD would be associated with impaired object location, aMCI patients exhibited impaired spatial feature binding. Compared to both older (n = 24) and younger (n = 53) controls, aMCI patients, recalled object locations with significantly less accuracy (p < .001), with a trend toward an impaired identification of the object's correct context (p = .05). Importantly, these findings were not explained by deficits in object recognition (p = .6). These deficits differentiated aMCI from controls with greater accuracy (AUC = 0.89) than the standard neuropsychological tests. Within the aMCI group, 16 had CSF biomarkers indicative of their likely AD status (MCI+ n = 9 vs. MCI- n = 7). MCI+ showed lower accuracy in the object-context association than MCI- (p = .03) suggesting a selective deficit in object-context binding postulated to be associated with anterior-temporal areas. MRI volumetric analysis across healthy older participants and aMCI revealed that test performance positively correlates with lateral entorhinal cortex volumes (p < .05) and hippocampus volumes (p < .01), consistent with their hypothesized role in binding contextual and spatial information with object identity. Our results indicate that tests relying on the anterolateral object processing stream, and in particular requiring successful binding of an object with spatial information, may aid detection of pre-dementia AD due to the underlying early spread of tau pathology.
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Affiliation(s)
- Andrea Castegnaro
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - David Howett
- School of Psychological Science, University of Bristol, Bristol, UK
| | - Adrienne Li
- Department of Psychology, York University, Toronto, Ontario, Canada
| | - Elizabeth Harding
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Dennis Chan
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Neil Burgess
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - John King
- Department of Clinical, Educational and Health Psychology, University College London, London, UK
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22
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Park SA, Jang YJ, Kim MK, Lee SM, Moon SY. Promising Blood Biomarkers for Clinical Use in Alzheimer's Disease: A Focused Update. J Clin Neurol 2022; 18:401-409. [PMID: 35796265 PMCID: PMC9262460 DOI: 10.3988/jcn.2022.18.4.401] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 04/29/2022] [Accepted: 04/29/2022] [Indexed: 12/11/2022] Open
Abstract
Alzheimer’s disease (AD) is the most-common cause of neurodegenerative dementia, and it is characterized by abnormal amyloid and tau accumulation, which indicates neurodegeneration. AD has mostly been diagnosed clinically. However, ligand-specific positron emission tomography (PET) imaging, such as amyloid PET, and cerebrospinal fluid (CSF) biomarkers are needed to accurately diagnose AD, since they supplement the shortcomings of clinical diagnoses. Using biomarkers that represent the pathology of AD is essential (particularly when disease-modifying treatment is available) to identify the corresponding pathology of targeted therapy and for monitoring the treatment response. Although imaging and CSF biomarkers are useful, their widespread use is restricted by their high cost and the discomfort during the lumbar puncture, respectively. Recent advances in AD blood biomarkers shed light on their future use for clinical purposes. The amyloid β (Aβ)42/Aβ40 ratio and the concentrations of phosphorylated tau at threonine 181 and at threonine 217, and of neurofilament light in the blood were found to represent the pathology of Aβ, tau, and neurodegeneration in the brain when using automatic electrochemiluminescence technologies, single-molecule arrays, immunoprecipitation coupled with mass spectrometry, etc. These blood biomarkers are imminently expected to be incorporated into clinical practice to predict, diagnose, and determine the stage of AD. In this review we focus on advancements in the measurement technologies for blood biomarkers and the promising biomarkers that are approaching clinical application. We also discuss the current limitations, the needed further investigations, and the perspectives on their use.
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Affiliation(s)
- Sun Ah Park
- Lab for Neurodegenerative Dementia, Department of Anatomy, Ajou University School of Medicine, Suwon, Korea.,Department of Neurology, Ajou University School of Medicine, Suwon, Korea.,Neuroscience Graduate Program, Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea.
| | - Yu Jung Jang
- Lab for Neurodegenerative Dementia, Department of Anatomy, Ajou University School of Medicine, Suwon, Korea.,Neuroscience Graduate Program, Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea
| | - Min Kyoung Kim
- Lab for Neurodegenerative Dementia, Department of Anatomy, Ajou University School of Medicine, Suwon, Korea.,Neuroscience Graduate Program, Department of Biomedical Sciences, Ajou University Graduate School of Medicine, Suwon, Korea
| | - Sun Min Lee
- Department of Neurology, Ajou University School of Medicine, Suwon, Korea
| | - So Young Moon
- Department of Neurology, Ajou University School of Medicine, Suwon, Korea
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23
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Wang Q, Shi Y, Qi X, Qi L, Chen X, Shi J, Xie C, Zhang Z. Platelet-Derived Amyloid-β Protein Precursor as a Biomarker of Alzheimer's Disease. J Alzheimers Dis 2022; 88:589-599. [PMID: 35662121 DOI: 10.3233/jad-220122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Platelet proteins may be associated with Alzheimer's disease (AD) pathology. OBJECTIVE To investigate the relationship between platelet proteins and cerebrospinal fluid (CSF) biomarkers of AD and cognition in individuals with memory decline to identify effective screening methods for detecting the early stages of the disease. METHODS We classified 68 participants with subjective memory decline according to the ATN framework determined by CSF amyloid-β (A), CSF p-tau (T), and t-tau (N). All participants underwent Mini-Mental State Examination (MMSE) and platelet-related protein content testing. RESULTS Eighteen participants had normal AD biomarkers (NCs), 24 subjects had non-AD pathologic changes (non-AD), and 26 subjects fell within the Alzheimer's continuum (AD). The platelet amyloid-β protein precursor (AβPP) ratio in the AD group was significantly lower than in the non-AD and NCs groups, and positively correlated with MMSE scores and CSF amyloid-β42 level, which could affect MMSE scores through CSF amyloid-β42. Levels of platelet phosphorylated-tau 231 and ser396/404 phosphorylated tau were elevated in both AD and non-AD compared to NCs. Additionally, the receiver operating characteristic analysis demonstrated that the platelet AβPP ratio was a sensitive identifier for differentiating the AD from NCs (AUC = 0.846) and non-AD (AUC = 0.768). And ser396/404 phosphorylated tau could distinguish AD from NCs. CONCLUSION Our study was the first to find an association between platelet AβPP ratio and CSF biomarkers of AD, which contribute to the understanding of the peripheral changes in AD. These findings may help to discover potential feasible and effective screening tools for AD.
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Affiliation(s)
- Qing Wang
- Department of Neurology, The Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, China
| | - Yachen Shi
- Department of Neurology, The Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, China
| | - Xinyang Qi
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Lingyu Qi
- Department of Neurology, The Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, China
| | - Xiang Chen
- Department of Neurology, The Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, China
| | - Jingping Shi
- Department of Neurology, The Affiliated Brain Hospital of Nanjing Medical University, Nanjing, China
| | - Chunming Xie
- Department of Neurology, The Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, China.,The Key Laboratory of Developmental Genes and Human Disease, Southeast University, Nanjing, China
| | - Zhijun Zhang
- Department of Neurology, The Affiliated ZhongDa Hospital, School of Medicine, Institution of Neuropsychiatry, Southeast University, Nanjing, China.,The Key Laboratory of Developmental Genes and Human Disease, Southeast University, Nanjing, China.,The Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
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24
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Fernandes M, Mari L, Chiaravalloti A, Paoli B, Nuccetelli M, Izzi F, Giambrone MP, Camedda R, Bernardini S, Schillaci O, Mercuri NB, Placidi F, Liguori C. 18F-FDG PET, cognitive functioning, and CSF biomarkers in patients with obstructive sleep apnoea before and after continuous positive airway pressure treatment. J Neurol 2022; 269:5356-5367. [PMID: 35608659 PMCID: PMC9468130 DOI: 10.1007/s00415-022-11182-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 05/07/2022] [Accepted: 05/10/2022] [Indexed: 11/23/2022]
Abstract
Introduction Dysregulation of cerebral glucose consumption, alterations in cerebrospinal fluid (CSF) biomarkers, and cognitive impairment have been reported in patients with obstructive sleep apnoea (OSA). On these bases, OSA has been considered a risk factor for Alzheimer’s disease (AD). This study aimed to measure cognitive performance, CSF biomarkers, and cerebral glucose consumption in OSA patients and to evaluate the effects of continuous positive airway pressure (CPAP) treatment on these biomarkers over a 12-month period. Methods Thirty-four OSA patients and 34 controls underwent 18F-fluoro-2-deoxy-d-glucose positron emission tomography (18F-FDG PET), cognitive evaluation, and CSF analysis. A subgroup of 12 OSA patients treated with beneficial CPAP and performing the 12-month follow-up was included in the longitudinal analysis, and cognitive evaluation and 18F-FDG PET were repeated. Results Significantly reduced glucose consumption was observed in the bilateral praecuneus, posterior cingulate cortex, and frontal areas in OSA patients than controls. At baseline, OSA patients also showed lower β-amyloid42 and higher phosphorylated-tau CSF levels than controls. Increased total tau and phosphorylated tau levels correlated with a reduction in brain glucose consumption in a cluster of different brain areas. In the longitudinal analysis, OSA patients showed an improvement in cognition and a global increase in cerebral 18F-FDG uptake. Conclusions Cognitive impairment, reduced cerebral glucose consumption, and alterations in CSF biomarkers were observed in OSA patients, which may reinforce the hypothesis of AD neurodegenerative processes triggered by OSA. Notably, cognition and brain glucose consumption improved after beneficial CPAP treatment. Further studies are needed to evaluate the long-term effects of CPAP treatment on these AD biomarkers.
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Affiliation(s)
- Mariana Fernandes
- Department of Systems Medicine, Sleep Medicine Centre, University of Rome "Tor Vergata", Rome, Italy
| | - Luisa Mari
- Neurology Unit, University Hospital of Rome "Tor Vergata", Rome, Italy
| | - Agostino Chiaravalloti
- Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy.,IRCCS Neuromed, Pozzilli, Italy
| | - Barbara Paoli
- Department of Systems Medicine, Sleep Medicine Centre, University of Rome "Tor Vergata", Rome, Italy
| | - Marzia Nuccetelli
- Department of Clinical Biochemistry and Molecular Biology, University of Rome "Tor Vergata", Rome, Italy
| | - Francesca Izzi
- Neurology Unit, University Hospital of Rome "Tor Vergata", Rome, Italy
| | | | - Riccardo Camedda
- Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy
| | - Sergio Bernardini
- Department of Clinical Biochemistry and Molecular Biology, University of Rome "Tor Vergata", Rome, Italy
| | - Orazio Schillaci
- Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy.,IRCCS Neuromed, Pozzilli, Italy
| | - Nicola Biagio Mercuri
- Neurology Unit, University Hospital of Rome "Tor Vergata", Rome, Italy.,IRCSS Santa Lucia Foundation, Rome, Italy
| | - Fabio Placidi
- Department of Systems Medicine, Sleep Medicine Centre, University of Rome "Tor Vergata", Rome, Italy.,Neurology Unit, University Hospital of Rome "Tor Vergata", Rome, Italy
| | - Claudio Liguori
- Department of Systems Medicine, Sleep Medicine Centre, University of Rome "Tor Vergata", Rome, Italy. .,Neurology Unit, University Hospital of Rome "Tor Vergata", Rome, Italy.
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25
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Fernandes M, Chiaravalloti A, Manfredi N, Placidi F, Nuccetelli M, Izzi F, Camedda R, Bernardini S, Schillaci O, Mercuri NB, Liguori C. Nocturnal Hypoxia and Sleep Fragmentation May Drive Neurodegenerative Processes: The Compared Effects of Obstructive Sleep Apnea Syndrome and Periodic Limb Movement Disorder on Alzheimer’s Disease Biomarkers. J Alzheimers Dis 2022; 88:127-139. [DOI: 10.3233/jad-215734] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023]
Abstract
Background: Sleep disorders may cause dysregulation of cerebral glucose metabolism and synaptic functions, as well as alterations in cerebrospinal fluid (CSF) biomarker levels. Objective: This study aimed at measuring sleep, CSF Alzheimer’s disease (AD) biomarkers, and cerebral glucose consumption in patients with obstructive sleep apnea syndrome (OSAS) and patients with periodic limb movement disorder (PLMD), compared to controls. Methods: OSAS and PLMD patients underwent 18F-fluoro-2-deoxy-D-glucose positron emission tomography (18F-FDG PET), polysomnographic monitoring, and lumbar puncture to quantify CSF levels of amyloid-β42 (Aβ42), total tau, and phosphorylated tau. All patients were compared to controls, who were not affected by sleep or neurodegenerative disorders. Results: Twenty OSAS patients, 12 PLMD patients, and 15 controls were included. Sleep quality and sleep structure were altered in both OSAS and PLMD patients when compared to controls. OSAS and PLMD patients showed lower CSF Aβ42 levels than controls. OSAS patients showed a significant increase in glucose uptake in a wide cluster of temporal-frontal areas and cerebellum, as well as a reduced glucose consumption in temporal-parietal regions compared to controls. PLMD patients showed increased brain glucose consumption in the left parahippocampal gyrus and left caudate than controls. Conclusion: Sleep dysregulation and nocturnal hypoxia present in OSAS patients, more than sleep fragmentation in PLMD patients, were associated with the alteration in CSF and 18F-FDG PET AD biomarkers, namely reduction of CSF Aβ42 levels and cerebral glucose metabolism dysregulation mainly in temporal areas, thus highlighting the possible role of sleep disorders in driving neurodegenerative processes typical of AD pathology.
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Affiliation(s)
- Mariana Fernandes
- Department of Systems Medicine, Sleep Medicine Centre, University of Rome “Tor Vergata”, Rome, Italy
| | - Agostino Chiaravalloti
- Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Rome, Italy
- IRCCS Neuromed, Pozzilli, Italy
| | - Natalia Manfredi
- Department of Systems Medicine, Sleep Medicine Centre, University of Rome “Tor Vergata”, Rome, Italy
| | - Fabio Placidi
- Department of Systems Medicine, Sleep Medicine Centre, University of Rome “Tor Vergata”, Rome, Italy
- Neurology Unit, University Hospital of Rome “Tor Vergata”, Rome, Italy
| | - Marzia Nuccetelli
- Department of Clinical Biochemistry and Molecular Biology, University of Rome “Tor Vergata”, Rome, Italy
| | - Francesca Izzi
- Neurology Unit, University Hospital of Rome “Tor Vergata”, Rome, Italy
| | - Riccardo Camedda
- Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Rome, Italy
| | - Sergio Bernardini
- Department of Clinical Biochemistry and Molecular Biology, University of Rome “Tor Vergata”, Rome, Italy
| | - Orazio Schillaci
- Department of Biomedicine and Prevention, University of Rome “Tor Vergata”, Rome, Italy
- IRCCS Neuromed, Pozzilli, Italy
| | - Nicola Biagio Mercuri
- Neurology Unit, University Hospital of Rome “Tor Vergata”, Rome, Italy
- IRCSS Santa Lucia Foundation, Rome, Italy
| | - Claudio Liguori
- Department of Systems Medicine, Sleep Medicine Centre, University of Rome “Tor Vergata”, Rome, Italy
- Neurology Unit, University Hospital of Rome “Tor Vergata”, Rome, Italy
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26
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Florean I, Penolazzi B, Menichelli A, Pastore M, Cattaruzza T, Mazzon G, Manganotti P. Using the ATN system as a guide for the neuropsychological assessment of Alzheimer's disease. J Clin Exp Neuropsychol 2022; 43:926-943. [PMID: 35166171 DOI: 10.1080/13803395.2022.2036327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Abstract
INTRODUCTION Many studies have attempted to determine whether Alzheimer's disease (AD) in-vivo biomarkers can predict neuropsychological performance since pathophysiological changes precede cognitive changes by several years. Nonetheless, neuropsychological measures can also detect cognitive deterioration in cognitively normal individuals with AD-positive biomarkers. Recent studies have investigated whether cognitive measures can be used as a proxy for biomarkers. This is a crucial issue since biomarker analysis is expensive, invasive, and not yet widespread in clinical practice. However, these studies have so far considered only one or two classes of AD biomarkers. Here, we aim at preliminarily evaluating whether and which neuropsychological measures can discriminate individuals that have been classified according to the full scheme of biomarkers known as ATN system. This scheme groups biomarkers as a function of the three main AD-related pathologic processes they measure (i.e., β-amyloidosis, tauopathy, and neurodegeneration) to provide an unbiased and descriptive definition of the Alzheimer's continuum. METHOD Biomarkers and neuropsychological data from 78 patients (70.01 ± 9.15 years; 38 females) with suspected cognitive decline were extracted from a medical database. Participants' biomarker profiles were classified into the following ATN categories: normal AD biomarkers; Alzheimer's continuum; non-AD pathologic change. Data were analyzed using a Bayesian approach, to guarantee reliable result interpretation of data stemming from small samples. RESULTS The discrimination ability of each neuropsychological measure varied depending on the pairs of ATN categories compared. The best-discriminating predictor in the Alzheimer's continuum vs. normal biomarkers comparison was the figure naming ability. In contrast, in the Alzheimer's continuum vs. non-AD pathologic change comparison the best predictor was the wordlist forgetting rate. CONCLUSIONS Although the study was exploratory in nature, the proposed methodological approach may have the potential to identify the best neuropsychological measures for estimating AD neuropathological changes, leading to a more biologically informed use of neuropsychological assessment.
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Affiliation(s)
- Irene Florean
- Department of Life Sciences, University of Trieste, Trieste, Italy
| | | | - Alina Menichelli
- Rehabilitation Unit, Department of Medicine, Surgery and Health Sciences, Maggiore City Hospital Asugi, Trieste, Italy
| | - Massimiliano Pastore
- Department of Developmental and Social Psychology, University of Padua, Padua, Italy
| | - Tatiana Cattaruzza
- Clinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Cattinara University Hospital Asugi, University of Trieste, Trieste, Italy
| | - Giulia Mazzon
- Clinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Cattinara University Hospital Asugi, University of Trieste, Trieste, Italy
| | - Paolo Manganotti
- Clinical Unit of Neurology, Department of Medicine, Surgery and Health Sciences, Cattinara University Hospital Asugi, University of Trieste, Trieste, Italy
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27
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Pelkmans W, Vromen EM, Dicks E, Scheltens P, Teunissen CE, Barkhof F, van der Flier WM, Tijms BM. Grey matter network markers identify individuals with prodromal Alzheimer’s disease who will show rapid clinical decline. Brain Commun 2022; 4:fcac026. [PMID: 35310828 PMCID: PMC8924646 DOI: 10.1093/braincomms/fcac026] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2021] [Revised: 11/22/2021] [Accepted: 02/07/2022] [Indexed: 11/25/2022] Open
Abstract
Individuals with prodromal Alzheimer’s disease show considerable variability in rates of cognitive decline, which hampers the ability to detect potential treatment effects in clinical trials. Prognostic markers to select those individuals who will decline rapidly within a trial time frame are needed. Brain network measures based on grey matter covariance patterns have been associated with future cognitive decline in Alzheimer’s disease. In this longitudinal cohort study, we investigated whether cut-offs for grey matter networks could be derived to detect fast disease progression at an individual level. We further tested whether detection was improved by adding other biomarkers known to be associated with future cognitive decline [i.e. CSF tau phosphorylated at threonine 181 (p-tau181) levels and hippocampal volume]. We selected individuals with mild cognitive impairment and abnormal CSF amyloid β1–42 levels from the Amsterdam Dementia Cohort and the Alzheimer’s Disease Neuroimaging Initiative, when they had available baseline structural MRI and clinical follow-up. The outcome was progression to dementia within 2 years. We determined prognostic cut-offs for grey matter network properties (gamma, lambda and small-world coefficient) using time-dependent receiver operating characteristic analysis in the Amsterdam Dementia Cohort. We tested the generalization of cut-offs in the Alzheimer’s Disease Neuroimaging Initiative, using logistic regression analysis and classification statistics. We further tested whether combining these with CSF p-tau181 and hippocampal volume improved the detection of fast decliners. We observed that within 2 years, 24.6% (Amsterdam Dementia Cohort, n = 244) and 34.0% (Alzheimer’s Disease Neuroimaging Initiative, n = 247) of prodromal Alzheimer’s disease patients progressed to dementia. Using the grey matter network cut-offs for progression, we could detect fast progressors with 65% accuracy in the Alzheimer’s Disease Neuroimaging Initiative. Combining grey matter network measures with CSF p-tau and hippocampal volume resulted in the best model fit for classification of rapid decliners, increasing detecting accuracy to 72%. These data suggest that single-subject grey matter connectivity networks indicative of a more random network organization can contribute to identifying prodromal Alzheimer’s disease individuals who will show rapid disease progression. Moreover, we found that combined with p-tau and hippocampal volume this resulted in the highest accuracy. This could facilitate clinical trials by increasing chances to detect effects on clinical outcome measures.
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Affiliation(s)
- Wiesje Pelkmans
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Ellen M. Vromen
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Ellen Dicks
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Charlotte E. Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Frederik Barkhof
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, UCL, London, UK
| | - Wiesje M. van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Epidemiology & Biostatistics, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Betty M. Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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28
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Verhaar BJH, Hendriksen HMA, de Leeuw FA, Doorduijn AS, van Leeuwenstijn M, Teunissen CE, Barkhof F, Scheltens P, Kraaij R, van Duijn CM, Nieuwdorp M, Muller M, van der Flier WM. Gut Microbiota Composition Is Related to AD Pathology. Front Immunol 2022; 12:794519. [PMID: 35173707 PMCID: PMC8843078 DOI: 10.3389/fimmu.2021.794519] [Citation(s) in RCA: 57] [Impact Index Per Article: 28.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 12/31/2021] [Indexed: 12/26/2022] Open
Abstract
IntroductionSeveral studies have reported alterations in gut microbiota composition of Alzheimer’s disease (AD) patients. However, the observed differences are not consistent across studies. We aimed to investigate associations between gut microbiota composition and AD biomarkers using machine learning models in patients with AD dementia, mild cognitive impairment (MCI) and subjective cognitive decline (SCD).Materials and MethodsWe included 170 patients from the Amsterdam Dementia Cohort, comprising 33 with AD dementia (66 ± 8 years, 46%F, mini-mental state examination (MMSE) 21[19-24]), 21 with MCI (64 ± 8 years, 43%F, MMSE 27[25-29]) and 116 with SCD (62 ± 8 years, 44%F, MMSE 29[28-30]). Fecal samples were collected and gut microbiome composition was determined using 16S rRNA sequencing. Biomarkers of AD included cerebrospinal fluid (CSF) amyloid-beta 1-42 (amyloid) and phosphorylated tau (p-tau), and MRI visual scores (medial temporal atrophy, global cortical atrophy, white matter hyperintensities). Associations between gut microbiota composition and dichotomized AD biomarkers were assessed with machine learning classification models. The two models with the highest area under the curve (AUC) were selected for logistic regression, to assess associations between the 20 best predicting microbes and the outcome measures from these machine learning models while adjusting for age, sex, BMI, diabetes, medication use, and MMSE.ResultsThe machine learning prediction for amyloid and p-tau from microbiota composition performed best with AUCs of 0.64 and 0.63. Highest ranked microbes included several short chain fatty acid (SCFA)-producing species. Higher abundance of [Clostridium] leptum and lower abundance of [Eubacterium] ventriosum group spp., Lachnospiraceae spp., Marvinbryantia spp., Monoglobus spp., [Ruminococcus] torques group spp., Roseburia hominis, and Christensenellaceae R-7 spp., was associated with higher odds of amyloid positivity. We found associations between lower abundance of Lachnospiraceae spp., Lachnoclostridium spp., Roseburia hominis and Bilophila wadsworthia and higher odds of positive p-tau status.ConclusionsGut microbiota composition was associated with amyloid and p-tau status. We extend on recent studies that observed associations between SCFA levels and AD CSF biomarkers by showing that lower abundances of SCFA-producing microbes were associated with higher odds of positive amyloid and p-tau status.
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Affiliation(s)
- Barbara J. H. Verhaar
- Department of Internal Medicine - Geriatrics, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands
- Department of Internal and Vascular Medicine, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands
- Alzheimer Center, Department of Neurology, Amsterdam Neuroscience, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands
- *Correspondence: Barbara J. H. Verhaar,
| | - Heleen M. A. Hendriksen
- Alzheimer Center, Department of Neurology, Amsterdam Neuroscience, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands
| | - Francisca A. de Leeuw
- Alzheimer Center, Department of Neurology, Amsterdam Neuroscience, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands
| | - Astrid S. Doorduijn
- Alzheimer Center, Department of Neurology, Amsterdam Neuroscience, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands
| | - Mardou van Leeuwenstijn
- Alzheimer Center, Department of Neurology, Amsterdam Neuroscience, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands
| | - Charlotte E. Teunissen
- Department of Clinical Chemistry, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands
- University College London (UCL) Institutes of Neurology, Faculty of Brain Sciences, London, United Kingdom
| | - Philip Scheltens
- Alzheimer Center, Department of Neurology, Amsterdam Neuroscience, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands
| | - Robert Kraaij
- Department of Internal Medicine, Erasmus Medical Center (MC), Rotterdam, Netherlands
| | - Cornelia M. van Duijn
- Department of Epidemiology, Erasmus Medical Center (MC), Rotterdam, Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Max Nieuwdorp
- Department of Internal and Vascular Medicine, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands
| | - Majon Muller
- Department of Internal Medicine - Geriatrics, Amsterdam Cardiovascular Sciences, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands
| | - Wiesje M. van der Flier
- Alzheimer Center, Department of Neurology, Amsterdam Neuroscience, Amsterdam University Medical Center (UMC), Amsterdam, Netherlands
- Department of Epidemiology and Data Science, Amsterdam University Medical Center (UMC), Vrije Universiteit Amsterdam, Amsterdam, Netherlands
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29
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Kim Y, Kim J, Son M, Lee J, Yeo I, Choi KY, Kim H, Kim BC, Lee KH, Kim Y. Plasma protein biomarker model for screening Alzheimer disease using multiple reaction monitoring-mass spectrometry. Sci Rep 2022; 12:1282. [PMID: 35075217 PMCID: PMC8786819 DOI: 10.1038/s41598-022-05384-8] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 01/11/2022] [Indexed: 12/01/2022] Open
Abstract
Alzheimer disease (AD) is a leading cause of dementia that has gained prominence in our aging society. Yet, the complexity of diagnosing AD and measuring its invasiveness poses an obstacle. To this end, blood-based biomarkers could mitigate the inconveniences that impede an accurate diagnosis. We developed models to diagnose AD and measure the severity of neurocognitive impairment using blood protein biomarkers. Multiple reaction monitoring-mass spectrometry, a highly selective and sensitive approach for quantifying targeted proteins in samples, was used to analyze blood samples from 4 AD groups: cognitive normal control, asymptomatic AD, prodromal AD), and AD dementia. Multimarker models were developed using 10 protein biomarkers and apolipoprotein E genotypes for amyloid beta and 10 biomarkers with Korean Mini-Mental Status Examination (K-MMSE) score for predicting Alzheimer disease progression. The accuracies for the AD classification model and AD progression monitoring model were 84.9% (95% CI 82.8 to 87.0) and 79.1% (95% CI 77.8 to 80.5), respectively. The models were more accurate in diagnosing AD, compared with single APOE genotypes and the K-MMSE score. Our study demonstrates the possibility of predicting AD with high accuracy by blood biomarker analysis as an alternative method of screening for AD.
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Affiliation(s)
- Yeongshin Kim
- Interdisciplinary Program of Bioengineering, Seoul National University College of Engineering, Seoul, Republic of Korea
| | - Jaenyeon Kim
- Interdisciplinary Program of Bioengineering, Seoul National University College of Engineering, Seoul, Republic of Korea
| | - Minsoo Son
- Interdisciplinary Program of Bioengineering, Seoul National University College of Engineering, Seoul, Republic of Korea
| | - Jihyeon Lee
- Department of Biomedical Engineering, Seoul National University College of Medicine, 28 Yongon-Dong, Chongno-Ku, Seoul, 110-799, Republic of Korea
| | - Injoon Yeo
- Department of Biomedical Engineering, Seoul National University College of Medicine, 28 Yongon-Dong, Chongno-Ku, Seoul, 110-799, Republic of Korea
| | - Kyu Yeong Choi
- Gwangju Alzheimer's Disease and Related Dementia Cohort Research Center and Department of Biomedical Science, Chosun University, Gwangju, 61452, Republic of Korea
| | - Hoowon Kim
- Gwangju Alzheimer's Disease and Related Dementia Cohort Research Center and Department of Biomedical Science, Chosun University, Gwangju, 61452, Republic of Korea
- Department of Neurology, Chosun University Hospital, Gwangju, 61452, Republic of Korea
| | - Byeong C Kim
- Department of Neurology, Chonnam National University Medical School, Gwangju, 61469, Republic of Korea
| | - Kun Ho Lee
- Gwangju Alzheimer's Disease and Related Dementia Cohort Research Center and Department of Biomedical Science, Chosun University, Gwangju, 61452, Republic of Korea.
- Department of Biomedical Science, Chosun University, Gwangju, 61452, Republic of Korea.
- Aging Neuroscience Research Group, Korea Brain Research Institute, Daegu, 41062, Republic of Korea.
| | - Youngsoo Kim
- Interdisciplinary Program of Bioengineering, Seoul National University College of Engineering, Seoul, Republic of Korea.
- Department of Biomedical Engineering, Seoul National University College of Medicine, 28 Yongon-Dong, Chongno-Ku, Seoul, 110-799, Republic of Korea.
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30
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Vromen EM, del Campo Milán M, Scheltens P, Teunissen CE, Visser PJ, Tijms BM. CSF proteomic signature predicts progression to Alzheimer's disease dementia. A&D Transl Res & Clin Interv 2022; 8:e12240. [PMID: 35229020 PMCID: PMC8864445 DOI: 10.1002/trc2.12240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/02/2021] [Revised: 11/25/2021] [Accepted: 12/13/2021] [Indexed: 11/23/2022]
Abstract
Introduction Individuals in the Alzheimer's disease (AD) continuum with mild cognitive impairment (prodromal AD) are at increased risk to develop dementia. Still, underlying pathophysiological processes remain unclear. We studied whether cerebrospinal fluid (CSF) proteome changes are related to time to clinical progression in prodromal AD. Methods We measured 671 CSF proteins in 49 prodromal AD individuals (67±7 years old, 22 [45%] female) from the Amsterdam Dementia Cohort. Associations of protein levels with time to dementia onset were tested with Cox regression models, followed by biological pathway enrichment analysis. Results Eighteen (36%) individuals developed dementia during follow‐up. In total, 128 (98%) proteins were associated with a 1.4‐ to 17‐fold increased risk of progression to dementia (all P < .05). These proteins showed enrichment for immune system processes, signal transduction, neuronal death, and neurodevelopmental biology. Discussion CSF proteome changes related to rate of progression to dementia can be detected in prodromal AD, providing more insight into processes involved in early AD pathophysiology.
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Affiliation(s)
- Eleonora M. Vromen
- Alzheimer Center Amsterdam Amsterdam Neuroscience Amsterdam UMC Vrije Universiteit Amsterdam Amsterdam the Netherlands
| | - Marta del Campo Milán
- Neurochemistry Laboratory Department of Clinical Chemistry Amsterdam Neuroscience Amsterdam UMC Vrije Universiteit Amsterdam Amsterdam the Netherlands
- Departamento de Ciencias Farmacéuticas y de la Salud Facultad de Farmacia CEU Universities Urbanización Montepríncipe Universidad San Pablo‐CEU Alcorcón Spain
| | - Philip Scheltens
- Alzheimer Center Amsterdam Amsterdam Neuroscience Amsterdam UMC Vrije Universiteit Amsterdam Amsterdam the Netherlands
| | - Charlotte E. Teunissen
- Neurochemistry Laboratory Department of Clinical Chemistry Amsterdam Neuroscience Amsterdam UMC Vrije Universiteit Amsterdam Amsterdam the Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam Amsterdam Neuroscience Amsterdam UMC Vrije Universiteit Amsterdam Amsterdam the Netherlands
- Department of Psychiatry Maastricht University Maastricht the Netherlands
- Department of Neurobiology Care Sciences and Society Division of Neurogeriatrics Karolinska Institutet Stockholm Sweden
| | - Betty M. Tijms
- Alzheimer Center Amsterdam Amsterdam Neuroscience Amsterdam UMC Vrije Universiteit Amsterdam Amsterdam the Netherlands
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31
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Boomsma JMF, Exalto LG, Barkhof F, Leeuwis AE, Prins ND, Scheltens P, Teunissen CE, Weinstein HC, Biessels GJ, van der Flier WM, On-behalf-of-the-TRACE-VCI-study-group. Vascular Cognitive Impairment and cognitive decline; a longitudinal study comparing different types of vascular brain injury - The TRACE-VCI study. Cerebral Circulation - Cognition and Behavior 2022; 3:100141. [PMID: 36324410 PMCID: PMC9616348 DOI: 10.1016/j.cccb.2022.100141] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 03/05/2022] [Accepted: 03/24/2022] [Indexed: 11/24/2022]
Abstract
Memory clinic patients with vascular cognitive impairment show a diverse population. Cognitive decline over time was shown for all types of vascular brain injury. Little differences were found in cognitive trajectories depending on type of vascular brain injury.
Background Little is known about the trajectories of cognitive decline in relation to different types of vascular brain injury in patients presenting at a memory clinic with Vascular Cognitive Impairment (VCI). Methods We included 472 memory clinic patients (age 68 (±8.2) years, 44% female, MMSE 25.9 (±2.8), 210 (44.5%) dementia) from the prospective TRACE-VCI cohort study with possible VCI, defined as cognitive complaints and vascular brain injury on MRI and at least 1 follow-up cognitive assessment (follow-up time 2.5 (±1.4) years, n = 1172 assessments). Types of vascular brain injury considered lacune(s) (≥1; n = 108 patients (23%)), non-lacunar infarct(s) (≥1; n = 54 (11%)), white matter hyperintensities (WMH) (none/mild versus moderate/severe (n = 211 patients (45%)) and microbleed(s) (≥1; n = 202 patients (43%)). We assessed cognitive functioning at baseline and follow-up, including the Rey Auditory Verbal Learning Test (RAVLT), Trail Making Test (TMT) A and B, category naming task and MMSE. The association of different types of vascular brain injury with cognitive decline was evaluated with linear mixed models, including one type of vascular brain injury (dichotomized), time and vascular brain injury*time, adjusted for sex, age, dementia status (yes/no), education (Verhage scale) and medial temporal lobe atrophy (MTA) score (dichotomized as ≥ 1.5). Results Across the population, performance declined over time on all tests. Linear mixed models showed that lacune(s) were associated with worse baseline TMTA (Beta(SE)) (8.3 (3.8), p = .03) and TMTB (25.6 (10.3), p = .01), albeit with a slower rate of decline on MMSE, RAVLT and category naming. By contrast, patients with non-lacunar infarct(s) showed a steeper rate of decline on TMTB (29.6 (7.7), p = .00), mainly attributable to patients with dementia (62.9 (15.5), p = .00). Conclusion Although different types of vascular brain injury have different etiologies and different patterns, they show little differences in cognitive trajectories depending on type of vascular brain injury.
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32
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Jansen IE, van der Lee SJ, Gomez-Fonseca D, de Rojas I, Dalmasso MC, Grenier-Boley B, Zettergren A, Mishra A, Ali M, Andrade V, Bellenguez C, Kleineidam L, Küçükali F, Sung YJ, Tesí N, Vromen EM, Wightman DP, Alcolea D, Alegret M, Alvarez I, Amouyel P, Athanasiu L, Bahrami S, Bailly H, Belbin O, Bergh S, Bertram L, Biessels GJ, Blennow K, Blesa R, Boada M, Boland A, Buerger K, Carracedo Á, Cervera-Carles L, Chene G, Claassen JAHR, Debette S, Deleuze JF, de Deyn PP, Diehl-Schmid J, Djurovic S, Dols-Icardo O, Dufouil C, Duron E, Düzel E, Fladby T, Fortea J, Frölich L, García-González P, Garcia-Martinez M, Giegling I, Goldhardt O, Gobom J, Grimmer T, Haapasalo A, Hampel H, Hanon O, Hausner L, Heilmann-Heimbach S, Helisalmi S, Heneka MT, Hernández I, Herukka SK, Holstege H, Jarholm J, Kern S, Knapskog AB, Koivisto AM, Kornhuber J, Kuulasmaa T, Lage C, Laske C, Leinonen V, Lewczuk P, Lleó A, de Munain AL, Lopez-Garcia S, Maier W, Marquié M, Mol MO, Montrreal L, Moreno F, Moreno-Grau S, Nicolas G, Nöthen MM, Orellana A, Pålhaugen L, Papma JM, Pasquier F, Perneczky R, Peters O, Pijnenburg YAL, Popp J, Posthuma D, Pozueta A, Priller J, Puerta R, Quintela I, Ramakers I, Rodriguez-Rodriguez E, Rujescu D, Saltvedt I, Sanchez-Juan P, Scheltens P, Scherbaum N, Schmid M, Schneider A, Selbæk G, Selnes P, Shadrin A, Skoog I, Soininen H, Tárraga L, Teipel S, Tijms B, Tsolaki M, Van Broeckhoven C, Van Dongen J, van Swieten JC, Vandenberghe R, Vidal JS, Visser PJ, Vogelgsang J, Waern M, Wagner M, Wiltfang J, Wittens MMJ, Zetterberg H, Zulaica M, van Duijn CM, Bjerke M, Engelborghs S, Jessen F, Teunissen CE, Pastor P, Hiltunen M, Ingelsson M, Andreassen OA, Clarimón J, Sleegers K, Ruiz A, Ramirez A, Cruchaga C, Lambert JC, van der Flier W. Genome-wide meta-analysis for Alzheimer's disease cerebrospinal fluid biomarkers. Acta Neuropathol 2022; 144:821-842. [PMID: 36066633 PMCID: PMC9547780 DOI: 10.1007/s00401-022-02454-z] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 05/18/2022] [Accepted: 06/07/2022] [Indexed: 01/26/2023]
Abstract
Amyloid-beta 42 (Aβ42) and phosphorylated tau (pTau) levels in cerebrospinal fluid (CSF) reflect core features of the pathogenesis of Alzheimer's disease (AD) more directly than clinical diagnosis. Initiated by the European Alzheimer & Dementia Biobank (EADB), the largest collaborative effort on genetics underlying CSF biomarkers was established, including 31 cohorts with a total of 13,116 individuals (discovery n = 8074; replication n = 5042 individuals). Besides the APOE locus, novel associations with two other well-established AD risk loci were observed; CR1 was shown a locus for Aβ42 and BIN1 for pTau. GMNC and C16orf95 were further identified as loci for pTau, of which the latter is novel. Clustering methods exploring the influence of all known AD risk loci on the CSF protein levels, revealed 4 biological categories suggesting multiple Aβ42 and pTau related biological pathways involved in the etiology of AD. In functional follow-up analyses, GMNC and C16orf95 both associated with lateral ventricular volume, implying an overlap in genetic etiology for tau levels and brain ventricular volume.
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Affiliation(s)
- Iris E. Jansen
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands ,grid.484519.5Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, The Netherlands
| | - Sven J. van der Lee
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands ,grid.16872.3a0000 0004 0435 165XSection Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Duber Gomez-Fonseca
- grid.4367.60000 0001 2355 7002Department of Psychiatry, Washington University School of Medicine, St Louis, MO USA ,grid.4367.60000 0001 2355 7002NeuroGenomics and Informatics, 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
| | - Itziar de Rojas
- grid.410675.10000 0001 2325 3084Research Center and Memory Clinic, Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Maria Carolina Dalmasso
- grid.6190.e0000 0000 8580 3777Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany ,grid.502038.c0000 0004 4911 0518Neurosciences and Complex Systems Unit (ENyS), CONICET, Hospital El Cruce, National University A. Jauretche (UNAJ), Florencio Varela, Argentina
| | - Benjamin Grenier-Boley
- grid.503422.20000 0001 2242 6780Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167 - RID-AGE / Labex DISTALZ - Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, F-59000 Lille, France
| | - Anna Zettergren
- grid.8761.80000 0000 9919 9582Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
| | - Aniket Mishra
- grid.412041.20000 0001 2106 639XUniversity of Bordeaux, Inserm, Bordeaux Population Health Research Center, Team VINTAGE, UMR 1219, 33000 Bordeaux, France
| | - Muhammad Ali
- grid.4367.60000 0001 2355 7002Department of Psychiatry, Washington University School of Medicine, St Louis, MO USA ,grid.4367.60000 0001 2355 7002NeuroGenomics and Informatics, 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
| | - Victor Andrade
- grid.6190.e0000 0000 8580 3777Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany ,grid.15090.3d0000 0000 8786 803XDepartment of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Medical Faculty, Bonn, Germany
| | - Céline Bellenguez
- grid.503422.20000 0001 2242 6780Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167 - RID-AGE / Labex DISTALZ - Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, F-59000 Lille, France
| | - Luca Kleineidam
- grid.6190.e0000 0000 8580 3777Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany ,grid.15090.3d0000 0000 8786 803XDepartment of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Medical Faculty, Bonn, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Fahri Küçükali
- grid.511528.aComplex Genetics of Alzheimer’s Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Yun Ju Sung
- grid.4367.60000 0001 2355 7002Department of Psychiatry, Washington University School of Medicine, St Louis, MO USA ,grid.4367.60000 0001 2355 7002NeuroGenomics and Informatics, 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
| | - Niccolo Tesí
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands ,grid.16872.3a0000 0004 0435 165XSection Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Ellen M. Vromen
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Douglas P. Wightman
- grid.484519.5Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, The Netherlands
| | - Daniel Alcolea
- grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain ,grid.7080.f0000 0001 2296 0625Sant Pau Memory Unit, Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Montserrat Alegret
- grid.410675.10000 0001 2325 3084Research Center and Memory Clinic, Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Ignacio Alvarez
- grid.414875.b0000 0004 1794 4956Memory Disorders Unit, Department of Neurology, Hospital Universitari Mutua de Terrassa, Terrassa, Spain ,grid.414875.b0000 0004 1794 4956Fundació per a la Recerca Biomèdica i Social Mútua de Terrassa, Terrassa, Spain
| | - Philippe Amouyel
- grid.503422.20000 0001 2242 6780Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167 - RID-AGE / Labex DISTALZ - Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, F-59000 Lille, France
| | - Lavinia Athanasiu
- grid.5510.10000 0004 1936 8921NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health, Oslo, Norway
| | - Shahram Bahrami
- grid.5510.10000 0004 1936 8921NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health, Oslo, Norway
| | - Henri Bailly
- grid.508487.60000 0004 7885 7602Université Paris Cité, EA4468, Maladie d’Alzheimer, F-75013 Paris, France
| | - Olivia Belbin
- grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain ,grid.7080.f0000 0001 2296 0625Sant Pau Memory Unit, Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Sverre Bergh
- grid.412929.50000 0004 0627 386XThe Research-Centre for Age-Related Functional Decline and Disease, Innlandet Hospital Trust, Brumunddal, Norway ,grid.417292.b0000 0004 0627 3659Norwegian National Centre for Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway
| | - Lars Bertram
- grid.4562.50000 0001 0057 2672Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
| | - Geert Jan Biessels
- grid.7692.a0000000090126352Department of Neurology, UMC Utrecht Brain Center, Utrecht, The Netherlands
| | - Kaj Blennow
- 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
| | - Rafael Blesa
- grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain ,grid.7080.f0000 0001 2296 0625Sant Pau Memory Unit, Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Mercè Boada
- grid.410675.10000 0001 2325 3084Research Center and Memory Clinic, Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Anne Boland
- grid.418135.a0000 0004 0641 3404Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine, 91057 Evry, France
| | - Katharina Buerger
- grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany ,grid.5252.00000 0004 1936 973XInstitute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Ángel Carracedo
- grid.11794.3a0000000109410645Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII), Universidade de Santiago de Compostela, Santiago de Compostela, Spain ,grid.443929.10000 0004 4688 8850Fundación Pública Galega de Medicina Xenómica-CIBERER-IDIS, Santiago de Compostela, Spain
| | - Laura Cervera-Carles
- grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain ,grid.7080.f0000 0001 2296 0625Sant Pau Memory Unit, Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Geneviève Chene
- grid.412041.20000 0001 2106 639XUniversity of Bordeaux, Inserm, Bordeaux Population Health Research Center, Team VINTAGE, UMR 1219, 33000 Bordeaux, France ,grid.42399.350000 0004 0593 7118Department of Neurology, CHU de Bordeaux, 33000 Bordeaux, France
| | - Jurgen A. H. R. Claassen
- grid.10417.330000 0004 0444 9382Radboudumc Alzheimer Center, Department of Geriatrics, Radboud University Medical Center, Nijmegen, The Netherlands ,Donders Center for Medical Neuroscience, Nijmegen, The Netherlands
| | - Stephanie Debette
- grid.412041.20000 0001 2106 639XUniversity of Bordeaux, Inserm, Bordeaux Population Health Research Center, Team VINTAGE, UMR 1219, 33000 Bordeaux, France ,grid.42399.350000 0004 0593 7118Department of Neurology, CHU de Bordeaux, 33000 Bordeaux, France ,grid.189504.10000 0004 1936 7558Department of Neurology, Boston University School of Medicine, Boston, MA 2115 USA
| | - Jean-Francois Deleuze
- grid.418135.a0000 0004 0641 3404Université Paris-Saclay, CEA, Centre National de Recherche en Génomique Humaine, 91057 Evry, France
| | - Peter Paul de Deyn
- grid.4494.d0000 0000 9558 4598Department of Neurology and Alzheimer Center Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Janine Diehl-Schmid
- grid.15474.330000 0004 0477 2438Center for Cognitive Disorders, Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, Technical University of Munich, School of Medicine, Munich, Germany ,kbo-Inn-Salzach-Hospital, Wasserburg am Inn, Germany
| | - Srdjan Djurovic
- grid.55325.340000 0004 0389 8485Department of Medical Genetics, Oslo University Hospital, Oslo, Norway ,grid.7914.b0000 0004 1936 7443Department of Clinical Science, NORMENT Centre, University of Bergen, Bergen, Norway
| | - Oriol Dols-Icardo
- grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain ,grid.7080.f0000 0001 2296 0625Sant Pau Memory Unit, Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Carole Dufouil
- grid.412041.20000 0001 2106 639XUniversity of Bordeaux, Inserm, Bordeaux Population Health Research Center, Team VINTAGE, UMR 1219, 33000 Bordeaux, France ,grid.42399.350000 0004 0593 7118Pôle de Santé Publique Centre Hospitalier Universitaire (CHU) de Bordeaux, Bordeaux, France
| | | | - Emrah Düzel
- grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany ,grid.5807.a0000 0001 1018 4307Institute of Cognitive Neurology and Dementia Research (IKND), Otto-von-Guericke University, Magdeburg, Germany
| | | | - Tormod Fladby
- grid.5510.10000 0004 1936 8921Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.411279.80000 0000 9637 455XDepartment of Neurology, Akershus University Hospital, Lorenskog, Norway
| | - Juan Fortea
- grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain ,grid.7080.f0000 0001 2296 0625Sant Pau Memory Unit, Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Lutz Frölich
- grid.413757.30000 0004 0477 2235Department of Geriatric Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg, Germany
| | - Pablo García-González
- grid.410675.10000 0001 2325 3084Research Center and Memory Clinic, Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Maria Garcia-Martinez
- grid.418264.d0000 0004 1762 4012Cognitive Impairment Unit, Neurology Service, “Marqués de Valdecilla” University Hospital, Institute for Research “Marques de Valdecilla” (IDIVAL), University of Cantabria, Santander, Spain, and Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Ina Giegling
- grid.22937.3d0000 0000 9259 8492Division of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Oliver Goldhardt
- grid.15474.330000 0004 0477 2438Center for Cognitive Disorders, Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, Technical University of Munich, School of Medicine, Munich, Germany
| | - Johan Gobom
- grid.1649.a000000009445082XClinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Timo Grimmer
- grid.15474.330000 0004 0477 2438Center for Cognitive Disorders, Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar, Technical University of Munich, School of Medicine, Munich, Germany
| | - Annakaisa Haapasalo
- grid.9668.10000 0001 0726 2490A.I. Virtanen Institute for Molecular Sciences, University of Eastern Finland, Kuopio, Finland
| | - Harald Hampel
- grid.462844.80000 0001 2308 1657Alzheimer Precision Medicine (APM), Sorbonne University, AP-HP, Pitié-Salpêtrière Hospital, Paris, France ,grid.418767.b0000 0004 0599 8842Neurology Business Group, Eisai Inc, 100 Tice Blvd, Woodcliff Lake, NJ 07677 USA
| | - Olivier Hanon
- grid.508487.60000 0004 7885 7602Université Paris Cité, EA4468, Maladie d’Alzheimer, F-75013 Paris, France ,grid.413802.c0000 0001 0011 8533Service gériatrie, Centre Mémoire de Ressources et Recherches Ile de France-Broca, AP-HP, Hôpital Broca, F-75013 Paris, France
| | - Lucrezia Hausner
- grid.413757.30000 0004 0477 2235Department of Geriatric Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, Heidelberg, Germany
| | - Stefanie Heilmann-Heimbach
- grid.10388.320000 0001 2240 3300Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, 53127 Bonn, Germany
| | - Seppo Helisalmi
- grid.9668.10000 0001 0726 2490Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
| | - Michael T. Heneka
- grid.15090.3d0000 0000 8786 803XDepartment of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Medical Faculty, Bonn, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Isabel Hernández
- grid.410675.10000 0001 2325 3084Research Center and Memory Clinic, Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Sanna-Kaisa Herukka
- grid.9668.10000 0001 0726 2490Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Henne Holstege
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands ,grid.16872.3a0000 0004 0435 165XSection Genomics of Neurodegenerative Diseases and Aging, Human Genetics, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
| | - Jonas Jarholm
- grid.411279.80000 0000 9637 455XDepartment of Neurology, Akershus University Hospital, Lorenskog, Norway
| | - Silke Kern
- grid.8761.80000 0000 9919 9582Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden ,grid.1649.a000000009445082XRegion Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - Anne-Brita Knapskog
- grid.55325.340000 0004 0389 8485Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Anne M. Koivisto
- grid.9668.10000 0001 0726 2490Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland ,grid.410705.70000 0004 0628 207XDepartment of Neurology, Kuopio University Hospital, Kuopio, Finland ,grid.15485.3d0000 0000 9950 5666Department of Neurology, Helsinki University Hospital, Helsinki, Finland
| | - Johannes Kornhuber
- grid.411668.c0000 0000 9935 6525Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany
| | - Teemu Kuulasmaa
- grid.9668.10000 0001 0726 2490Bioinformatics Center, Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - Carmen Lage
- grid.418264.d0000 0004 1762 4012Cognitive Impairment Unit, Neurology Service, “Marqués de Valdecilla” University Hospital, Institute for Research “Marques de Valdecilla” (IDIVAL), University of Cantabria, Santander, Spain, and Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain ,grid.266102.10000 0001 2297 6811Atlantic Fellow at the Global Brain Health Institute (GBHI) -, University of California, San Francisco, USA
| | - Christoph Laske
- grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany ,grid.10392.390000 0001 2190 1447Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Ville Leinonen
- grid.9668.10000 0001 0726 2490Institute of Clinical Medicine, Neurosurgery, University of Eastern Finland, Kuopio, Finland ,grid.410705.70000 0004 0628 207XDepartment of Neurosurgery, Kuopio University Hospital, Kuopio, Finland
| | - Piotr Lewczuk
- grid.411668.c0000 0000 9935 6525Department of Psychiatry and Psychotherapy, Universitätsklinikum Erlangen, and Friedrich-Alexander Universität Erlangen-Nürnberg, Erlangen, Germany ,grid.48324.390000000122482838Department of Neurodegeneration Diagnostics, Medical University of Białystok, Białystok, Poland
| | - Alberto Lleó
- grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain ,grid.7080.f0000 0001 2296 0625Sant Pau Memory Unit, Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Adolfo López de Munain
- grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain ,grid.414651.30000 0000 9920 5292Hospital Universitario Donostia-OSAKIDETZA, Donostia, Spain ,grid.432380.eInstituto Biodonostia, San Sebastián, Spain ,grid.11480.3c0000000121671098University of The Basque Country, San Sebastian, Spain
| | - Sara Lopez-Garcia
- grid.418264.d0000 0004 1762 4012Cognitive Impairment Unit, Neurology Service, “Marqués de Valdecilla” University Hospital, Institute for Research “Marques de Valdecilla” (IDIVAL), University of Cantabria, Santander, Spain, and Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Wolfgang Maier
- grid.15090.3d0000 0000 8786 803XDepartment of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Medical Faculty, Bonn, Germany
| | - Marta Marquié
- grid.410675.10000 0001 2325 3084Research Center and Memory Clinic, Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Merel O. Mol
- grid.5645.2000000040459992XDepartment of Neurology and Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Laura Montrreal
- grid.410675.10000 0001 2325 3084Research Center and Memory Clinic, Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Fermin Moreno
- grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain ,grid.414651.30000 0000 9920 5292Hospital Universitario Donostia-OSAKIDETZA, Donostia, Spain ,grid.432380.eInstituto Biodonostia, San Sebastián, Spain
| | - Sonia Moreno-Grau
- grid.410675.10000 0001 2325 3084Research Center and Memory Clinic, Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Gael Nicolas
- grid.41724.340000 0001 2296 5231Department of Genetics and CNR-MAJ, Normandie Univ, UNIROUEN, Inserm U1245 and CHU Rouen, Rouen, France
| | - Markus M. Nöthen
- grid.10388.320000 0001 2240 3300Institute of Human Genetics, University of Bonn, School of Medicine and University Hospital Bonn, 53127 Bonn, Germany
| | - Adelina Orellana
- grid.410675.10000 0001 2325 3084Research Center and Memory Clinic, Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Lene Pålhaugen
- grid.5510.10000 0004 1936 8921Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.411279.80000 0000 9637 455XDepartment of Neurology, Akershus University Hospital, Lorenskog, Norway
| | - Janne M. Papma
- grid.5645.2000000040459992XDepartment of Neurology and Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Florence Pasquier
- grid.503422.20000 0001 2242 6780Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167 - RID-AGE / Labex DISTALZ - Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, F-59000 Lille, France
| | - Robert Perneczky
- grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany ,grid.5252.00000 0004 1936 973XDepartment of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany ,grid.452617.3Munich Cluster for Systems Neurology (SyNergy) Munich, Munich, Germany ,grid.7445.20000 0001 2113 8111Ageing Epidemiology Research Unit, School of Public Health, Imperial College London, London, UK
| | - Oliver Peters
- grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
| | - Yolande A. L. Pijnenburg
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Julius Popp
- grid.412004.30000 0004 0478 9977Department of Geriatric Psychiatry, University Hospital of Psychiatry Zürich and University of Zürich, Zurich, Switzerland ,grid.8515.90000 0001 0423 4662Old Age Psychiatry, Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Danielle Posthuma
- grid.484519.5Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU Amsterdam, Amsterdam, The Netherlands
| | - Ana Pozueta
- grid.418264.d0000 0004 1762 4012Cognitive Impairment Unit, Neurology Service, “Marqués de Valdecilla” University Hospital, Institute for Research “Marques de Valdecilla” (IDIVAL), University of Cantabria, Santander, Spain, and Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Josef Priller
- grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany ,grid.6363.00000 0001 2218 4662Department of Psychiatry and Psychotherapy, Charité, Charitéplatz 1, 10117 Berlin, Germany ,grid.6936.a0000000123222966Department of Psychiatry and Psychotherapy, Klinikum rechts der isar, Technical University Munich, 81675 Munich, Germany
| | - Raquel Puerta
- grid.410675.10000 0001 2325 3084Research Center and Memory Clinic, Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain
| | - Inés Quintela
- grid.11794.3a0000000109410645Grupo de Medicina Xenómica, Centro Nacional de Genotipado (CEGEN-PRB3-ISCIII), Universidade de Santiago de Compostela, Santiago de Compostela, Spain
| | - Inez Ramakers
- grid.412966.e0000 0004 0480 1382Department of Psychiatry and Neuropsychologie, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands
| | - Eloy Rodriguez-Rodriguez
- grid.418264.d0000 0004 1762 4012Cognitive Impairment Unit, Neurology Service, “Marqués de Valdecilla” University Hospital, Institute for Research “Marques de Valdecilla” (IDIVAL), University of Cantabria, Santander, Spain, and Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Dan Rujescu
- grid.22937.3d0000 0000 9259 8492Division of General Psychiatry, Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria
| | - Ingvild Saltvedt
- grid.5947.f0000 0001 1516 2393Department of Neuromedicine and Movement Science, Norwegian University of Science and Technology (NTNU), Trondheim, Norway ,grid.52522.320000 0004 0627 3560Department of Geriatrics, St Olav Hospital, University Hospital of Trondheim, Trondheim, Norway
| | - Pascual Sanchez-Juan
- grid.413448.e0000 0000 9314 1427Alzheimer’s Centre Reina Sofia-CIEN Foundation-ISCIII, 28031 Madrid, Spain
| | - Philip Scheltens
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Norbert Scherbaum
- grid.5718.b0000 0001 2187 5445Department of Psychiatry and Psychotherapy, Medical Faculty, LVR-Hospital Essen, University of Duisburg-Essen, Essen, Germany
| | - Matthias Schmid
- grid.15090.3d0000 0000 8786 803XInstitute of Medical Biometry, Informatics and Epidemiology, University Hospital of Bonn, Bonn, Germany
| | - Anja Schneider
- grid.15090.3d0000 0000 8786 803XDepartment of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Medical Faculty, Bonn, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Geir Selbæk
- grid.417292.b0000 0004 0627 3659Norwegian National Centre for Ageing and Health, Vestfold Hospital Trust, Tønsberg, Norway ,grid.5510.10000 0004 1936 8921Institute of Clinical Medicine, University of Oslo, Oslo, Norway ,grid.55325.340000 0004 0389 8485Department of Geriatric Medicine, Oslo University Hospital, Oslo, Norway
| | - Per Selnes
- grid.411279.80000 0000 9637 455XDepartment of Neurology, Akershus University Hospital, Lorenskog, Norway
| | - Alexey Shadrin
- grid.5510.10000 0004 1936 8921NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health, Oslo, Norway
| | - Ingmar Skoog
- grid.8761.80000 0000 9919 9582Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden ,grid.1649.a000000009445082XRegion Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - Hilkka Soininen
- grid.9668.10000 0001 0726 2490Department of Neurology, Institute of Clinical Medicine, University of Eastern Finland, Kuopio, Finland
| | - Lluís Tárraga
- grid.410675.10000 0001 2325 3084Research Center and Memory Clinic, Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Stefan Teipel
- grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany ,grid.413108.f0000 0000 9737 0454Department of Psychosomatic Medicine, Rostock University Medical Center, Gehlsheimer Str. 20, 18147 Rostock, Germany
| | | | - Betty Tijms
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Magda Tsolaki
- grid.4793.900000001094570051st Department of Neurology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Thessaloniki, Makedonia Greece
| | - Christine Van Broeckhoven
- grid.5284.b0000 0001 0790 3681Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium ,grid.511528.aNeurodegenerative Brain Diseases Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
| | - Jasper Van Dongen
- grid.511528.aComplex Genetics of Alzheimer’s Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - John C. van Swieten
- grid.5645.2000000040459992XDepartment of Neurology and Alzheimer Center Erasmus MC, Erasmus MC University Medical Center, Rotterdam, The Netherlands
| | - Rik Vandenberghe
- grid.410569.f0000 0004 0626 3338Neurology, University Hospitals Leuven, Leuven, Belgium ,grid.5596.f0000 0001 0668 7884Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, Leuven, Belgium
| | - Jean-Sébastien Vidal
- grid.508487.60000 0004 7885 7602Université Paris Cité, EA4468, Maladie d’Alzheimer, F-75013 Paris, France
| | - Pieter J. Visser
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands ,grid.5012.60000 0001 0481 6099Alzheimer Center Limburg, School for Mental Health and Neuroscience Maastricht University, Maastricht, The Netherlands ,grid.4714.60000 0004 1937 0626Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics Karolinska Institutet, Stockholm, Sweden
| | - Jonathan Vogelgsang
- grid.411984.10000 0001 0482 5331Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, Göttingen, Germany ,grid.38142.3c000000041936754XDepartment of Psychiatry, Harvard Medical School, McLean Hospital, Belmont, MA USA
| | - Margda Waern
- grid.8761.80000 0000 9919 9582Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden ,grid.1649.a000000009445082XRegion Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Psychosis Clinic, Gothenburg, Sweden
| | - Michael Wagner
- grid.15090.3d0000 0000 8786 803XDepartment of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Medical Faculty, Bonn, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Jens Wiltfang
- grid.411984.10000 0001 0482 5331Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, Göttingen, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Göttingen, Germany ,Medical Science Department, iBiMED, Aveiro, Portugal
| | - Mandy M. J. Wittens
- grid.5284.b0000 0001 0790 3681Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium ,grid.8767.e0000 0001 2290 8069Center for Neurosciences (C4N), Vrije Universiteit Brussel, Brussels, Belgium
| | - 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, London, UK ,grid.83440.3b0000000121901201UK Dementia Research Institute at UCL, London, UK ,grid.24515.370000 0004 1937 1450Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Miren Zulaica
- grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain ,grid.414651.30000 0000 9920 5292Hospital Universitario Donostia-OSAKIDETZA, Donostia, Spain ,grid.432380.eInstituto Biodonostia, San Sebastián, Spain
| | - Cornelia M. van Duijn
- grid.5645.2000000040459992XDepartment of Epidemiology, ErasmusMC, Rotterdam, The Netherlands ,grid.4991.50000 0004 1936 8948Nuffield Department of Population Health, Oxford University, Oxford, UK
| | - Maria Bjerke
- grid.5284.b0000 0001 0790 3681Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium ,grid.8767.e0000 0001 2290 8069Center for Neurosciences (C4N), Vrije Universiteit Brussel, Brussels, Belgium ,grid.411326.30000 0004 0626 3362Laboratory of Neurochemistry, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | - Sebastiaan Engelborghs
- grid.5284.b0000 0001 0790 3681Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium ,grid.8767.e0000 0001 2290 8069Center for Neurosciences (C4N), Vrije Universiteit Brussel, Brussels, Belgium ,grid.411326.30000 0004 0626 3362Laboratory of Neurochemistry, Universitair Ziekenhuis Brussel, Brussels, Belgium ,grid.411326.30000 0004 0626 3362Department of Neurology, Universitair Ziekenhuis Brussel, Brussels, Belgium
| | - Frank Jessen
- grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany ,grid.6190.e0000 0000 8580 3777Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany ,grid.6190.e0000 0000 8580 3777Cluster of Excellence Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Charlotte E. Teunissen
- grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands ,grid.484519.5Neurochemistry Lab, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Pau Pastor
- grid.411438.b0000 0004 1767 6330Unit of Neurodegenerative diseases, Department of Neurology, University Hospital Germans Trias i Pujol and The Germans Trias i Pujol Research Institute (IGTP) Badalona, Barcelona, Spain
| | - Mikko Hiltunen
- grid.9668.10000 0001 0726 2490Institute of Biomedicine, University of Eastern Finland, Kuopio, Finland
| | - Martin Ingelsson
- grid.8993.b0000 0004 1936 9457Department of Public Health and Caring Sciences, Molecular Geriatrics, Rudbeck Laboratory, Uppsala University, Uppsala, Sweden ,grid.231844.80000 0004 0474 0428Krembil Brain Institute, University Health Network, Toronto, Ontario Canada ,grid.17063.330000 0001 2157 2938Department of Medicine and Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, Canada
| | - Ole A. Andreassen
- grid.5510.10000 0004 1936 8921NORMENT Centre, Institute of Clinical Medicine, University of Oslo and Division of Mental Health, Oslo, Norway ,grid.55325.340000 0004 0389 8485Addiction, Oslo University Hospital, 0407 Oslo, Norway
| | - Jordi Clarimón
- grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain ,grid.7080.f0000 0001 2296 0625Sant Pau Memory Unit, Department of Neurology, Institut d’Investigacions Biomèdiques Sant Pau - Hospital de Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Kristel Sleegers
- grid.511528.aComplex Genetics of Alzheimer’s Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium ,grid.5284.b0000 0001 0790 3681Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Agustín Ruiz
- grid.410675.10000 0001 2325 3084Research Center and Memory Clinic, Ace Alzheimer Center Barcelona, Universitat Internacional de Catalunya, Barcelona, Spain ,grid.413448.e0000 0000 9314 1427CIBERNED, Network Center for Biomedical Research in Neurodegenerative Diseases, National Institute of Health Carlos III, Madrid, Spain
| | - Alfredo Ramirez
- grid.6190.e0000 0000 8580 3777Division of Neurogenetics and Molecular Psychiatry, Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital Cologne, University of Cologne, Cologne, Germany ,grid.15090.3d0000 0000 8786 803XDepartment of Neurodegenerative Diseases and Geriatric Psychiatry, University Hospital Bonn, Medical Faculty, Bonn, Germany ,grid.424247.30000 0004 0438 0426German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany ,grid.6190.e0000 0000 8580 3777Cluster of Excellence Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany ,Department of Psychiatry, Glenn Biggs Institute for Alzheimer’s and Neurodegenerative Diseases, San Antonio, TX USA
| | - Carlos Cruchaga
- grid.4367.60000 0001 2355 7002Department of Psychiatry, Washington University School of Medicine, St Louis, MO USA ,grid.4367.60000 0001 2355 7002NeuroGenomics and Informatics, 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
| | - Jean-Charles Lambert
- grid.503422.20000 0001 2242 6780Univ. Lille, Inserm, CHU Lille, Institut Pasteur de Lille, U1167 - RID-AGE / Labex DISTALZ - Facteurs de risque et déterminants moléculaires des maladies liées au vieillissement, F-59000 Lille, France
| | - Wiesje van der Flier
- grid.12380.380000 0004 1754 9227Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands ,grid.484519.5Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
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Wu X, Li R, Lai T, Tao G, Liu F, Li N. Universal Nanoparticle Counting Platform for Tetraplexed Biomarkers by Integrating Immunorecognition and Nucleic Acid Hybridization in One Assay. Anal Chem 2021; 93:16873-16879. [PMID: 34874148 DOI: 10.1021/acs.analchem.1c03858] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
The development of a simple and universal strategy for simultaneous quantification of proteins and nucleic acid biomarkers in one assay is valuable, particularly for disease diagnosis and pathogenesis studies. Herein, a universal and amplification-free quantum dot-doped nanoparticle counting platform was developed by integrating immunorecognition and nucleic acid hybridization in one assay. The assay can be performed at room temperature, which is friendly for routine analysis. Multiplexed biomarkers associated with Alzheimer's disease (AD) including proteins and nucleic acids were detected. For simultaneous detection of tetraplex biomarkers, the assay for amyloid β 1-42 (Aβ42), tau protein, miR-146a, and miR-138 presented limit of detection values of 250 pg/mL, 55.7 pg/mL, 52.5 pM, and 0.62 pM, respectively. By spiking all the above four biomarkers in one artificial cerebrospinal fluid sample, the recoveries were found to be 94.7-117.2%. Using tau protein as the model, four measurements in 88 days presented a coefficient of variance of 7.5%. The proposed platform for the multiplexed assay of proteins and nucleic acids presents the universality, reasonable sensitivity, and repeatability, which may open a new door for early diagnosis and pathogenesis research for AD and other diseases.
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Affiliation(s)
- Xi Wu
- Beijing National Laboratory for Molecular Sciences (BNLMS), Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Institute of Analytical Chemistry, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China.,Education Department of Heilongjiang Province, Harbin 150001, China
| | - Rongsheng Li
- Beijing National Laboratory for Molecular Sciences (BNLMS), Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Institute of Analytical Chemistry, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Tiancheng Lai
- Beijing National Laboratory for Molecular Sciences (BNLMS), Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Institute of Analytical Chemistry, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Guangyu Tao
- Beijing National Laboratory for Molecular Sciences (BNLMS), Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Institute of Analytical Chemistry, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Feng Liu
- Beijing National Laboratory for Molecular Sciences (BNLMS), Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Institute of Analytical Chemistry, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
| | - Na Li
- Beijing National Laboratory for Molecular Sciences (BNLMS), Key Laboratory of Bioorganic Chemistry and Molecular Engineering of Ministry of Education, Institute of Analytical Chemistry, College of Chemistry and Molecular Engineering, Peking University, Beijing 100871, China
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Liguori C, Stefani A, Fernandes M, Cerroni R, Mercuri NB, Pierantozzi M. Biomarkers of Cerebral Glucose Metabolism and Neurodegeneration in Parkinson's Disease: A Cerebrospinal Fluid-Based Study. J Parkinsons Dis 2021; 12:537-544. [PMID: 34864690 DOI: 10.3233/jpd-212936] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
BACKGROUND Several biomarkers have been evaluated in Parkinson's disease (PD); cerebrospinal fluid (CSF) levels of lactate may reflect cerebral metabolism function and CSF amyloid-β42 (Aβ42), total tau (t-tau) and phosphorylated tau (p-tau) concentrations may detect an underlying neurodegenerative process. OBJECTIVE CSF levels of lactate, Aβ42, t-tau, and p-tau were measured in patients with mild to moderate PD. CSF levels of dopamine (DA) and its metabolite 3,4-Dihydroxyphenylacetic acid (DOPAC) were also assessed, exploring their relations with the other CSF biomarkers. METHODS 101 drug-naive PD patients and 60 controls were included. Participants underwent clinical assessments and CSF biomarker analysis. Patients were divided into subgroups according to their Hoehn & Yahr stage (PD-1, PD-2, PD-3). RESULTS PD patients showed higher lactate levels (M = 1.91; p = 0.03) and lower Aβ42 (M = 595; p < 0.001) and DA levels (M = 0.32; p = 0.04) than controls (Mlactate = 1.72; MAβ42 = 837; MDA = 0.50), while no significant differences were found in t-tau, p-tau and DOPAC concentrations. Considering the subgroup analysis, PD-3 group had higher lactate (M = 2.12) and t-tau levels (M = 333) than both PD-1 (Mlactate = 1.75, p = 0.006; Mt - tau = 176, p = 0.008) and PD-2 groups (Mlactate = 1.91, p = 0.01; Mt - tau = 176, p = 0.03), as well as the controls (Mlactate = 1.72, p = 0.04; Mt - tau = 205, p = 0.04). PD-2 group showed higher lactate levels than PD-1 group (p = 0.04) and controls (p = 0.03). Finally, CSF lactate levels negatively correlated with DA (r = -0.42) and positively with t-tau CSF levels (r = 0.33). CONCLUSION This CSF-based study shows that lactate levels in PD correlated with both clinical disease progression and neurodegeneration biomarkers, such as tau proteins and DA. Further studies should explore the clinical potential of measuring CSF biomarkers for better understanding the role of brain energy metabolism in PD, for research and therapeutic options.
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Affiliation(s)
- Claudio Liguori
- Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Italy.,Sleep Medicine Centre, Department of Systems Medicine, University of Rome "Tor Vergata", Italy.,UOSD Parkinson's Disease Centre, Department of Systems Medicine, University of Rome "Tor Vergata", Italy
| | - Alessandro Stefani
- Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Italy.,UOSD Parkinson's Disease Centre, Department of Systems Medicine, University of Rome "Tor Vergata", Italy
| | - Mariana Fernandes
- Sleep Medicine Centre, Department of Systems Medicine, University of Rome "Tor Vergata", Italy
| | - Rocco Cerroni
- Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Italy.,UOSD Parkinson's Disease Centre, Department of Systems Medicine, University of Rome "Tor Vergata", Italy
| | - Nicola Biagio Mercuri
- Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Italy.,IRCCS Santa Lucia Foundation, Rome, Italy
| | - Mariangela Pierantozzi
- Neurology Unit, Department of Systems Medicine, University of Rome "Tor Vergata", Italy.,UOSD Parkinson's Disease Centre, Department of Systems Medicine, University of Rome "Tor Vergata", Italy
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van den Bosch KA, Verberk IMW, Ebenau JL, van der Lee SJ, Jansen IE, Prins ND, Scheltens P, Teunissen CE, Van der Flier WM. BDNF-Met polymorphism and amyloid-beta in relation to cognitive decline in cognitively normal elderly: the SCIENCe project. Neurobiol Aging 2021; 108:146-154. [PMID: 34601245 DOI: 10.1016/j.neurobiolaging.2021.08.018] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/07/2021] [Revised: 08/24/2021] [Accepted: 08/26/2021] [Indexed: 11/25/2022]
Abstract
Brain-derived neurotrophic factor (BNDF) plays a role in synapse integrity. We investigated in 398 cognitively normal adults (60±8years, 41% female, MMSE=28±1) the joint association of the Val66Met polymorphism of the BDNF gene (Met+/-) and plasma BDNF levels and abnormal cerebrospinal fluid (CSF) amyloid-beta status (A+/-) with cognitive decline and dementia risk. Age-, sex- and education-adjusted linear mixed models showed that compared to Met-A-, Met+A+ showed steeper decline on tests of global cognition, memory, language, attention and executive functioning, while Met-A+ showed steeper decline on a smaller number of tests. There were no associations between Met+A- and cognitive decline. Cox models showed that compared to Met-A-, Met+A+ participants were at increased risk of dementia (HR=8.8, 95%CI: 2.8-27.9), as were Met-A+ participants (HR=6.5, 95%CI: 2.2-19.5). Lower plasma BDNF was associated with an increased risk of progression to dementia in the A+ participants. Our results imply that Met-carriage on top of amyloid-beta pathology might increase rate of cognitive decline to dementia.
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Affiliation(s)
- Karlijn A van den Bosch
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Inge M W Verberk
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; Neurochemistry Laboratory, Department of Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | - Jarith L Ebenau
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Sven J van der Lee
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; Department of Clinical Genetics, Amsterdam UMC, Amsterdam, The Netherlands
| | - Iris E Jansen
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, VU, Amsterdam, The Netherlands
| | - Niels D Prins
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; Brain Research Center, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; Neurochemistry Laboratory, Department of Clinical Chemistry, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Wiesje M Van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands; Department of Epidemiology and Data Science, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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Zhang M, Zhang S, Yu W, Li X, Ma N, Cui Y. Simultaneous Determination of D-amino Acids in Rat Urine by Highperformance Liquid Chromatography-tandem Mass Spectrometry Method: Application to Investigate the Clinical Value of D-amino Acids in the Early Diagnosis of Alzheimer’s Disease. CURR PHARM ANAL 2021. [DOI: 10.2174/1573412916999200717235048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Background:
D-amino acids are closely related to the development and progression of
Alzheimer's disease (AD) and are expected as the novel biomarkers for AD diagnosis.
Objective:The aim was to investigate the potential clinical value of D-amino acids for Alzheimer's
disease.
Methods:A simple and sensitive HPLC/MS-MS method was developed for the simultaneous determination
of D-alanine, D-glutamine, D-proline and D-serine in rat urine. The samples were firstly pretreated
by methanol, then derivatized by 7-chloro-4-nitrobenzoxadiazole with Fudosteine as internal
standard, enantioseparated on Sumichiral OA-2500S column, using a mobile phase composed of acetonitrile-
methanol (50:50, v/v) containing 0.5% formic acid, and detected with 4000 Qtrap MS/MS in
electrospray-ionization source by negative ion mode.
Results:The established method was successfully applied to determine the D-amino acid levels in rat
urine from 20 Alzheimer's disease rats and 20 age-matched normal controls. The mean levels of Damino
acids in the urine of Alzheimer's disease rats were all significantly lower than those in normal
controls. Based on the contents of D-amino acids, the distinction model between Alzheimer's disease
rats and normal controls was established by the Bayesian discriminant analysis.
Conclusion:
The relationship between Alzheimer's disease and D-amino acids revealed that D-amino
acids would be potential biomarkers for Alzheimer’s disease.
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Affiliation(s)
- Min Zhang
- School of Functional Food and Wine, Shenyang Pharmaceutical University, 103 Wenhua Road, Shenyang 110016,China
| | - Shuting Zhang
- School of Functional Food and Wine, Shenyang Pharmaceutical University, 103 Wenhua Road, Shenyang 110016,China
| | - Weichao Yu
- School of Pharmacy, Shenyang Pharmaceutical University, 103 Wenhua Road, Shenyang 110016,China
| | - Xiaoyan Li
- PAREXEL International Unit, 286 Qingnian Street, Shenyang 110004,China
| | - Ning Ma
- The Second Affiliated Hospital of Liaoning University of Traditional Chinese Medicine, 60 North Yellow River Street, Shenyang, 110034,China
| | - Yan Cui
- School of Pharmacy, Shenyang Pharmaceutical University, 103 Wenhua Road, Shenyang 110016,China
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Bommarito G, Van De Ville D, Frisoni GB, Garibotto V, Ribaldi F, Stampacchia S, Assal F, Allali G, Griffa A. Alzheimer's Disease Biomarkers in Idiopathic Normal Pressure Hydrocephalus: Linking Functional Connectivity and Clinical Outcome. J Alzheimers Dis 2021; 83:1717-1728. [PMID: 34459399 DOI: 10.3233/jad-210534] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
BACKGROUND Alzheimer's disease (AD) pathology impacts the response to treatment in patients with idiopathic normal pressure hydrocephalus (iNPH), possibly through changes in resting-state functional connectivity (rs-FC). OBJECTIVE To explore the relationship between cerebrospinal fluid biomarkers of AD and the default mode network (DMN)/hippocampal rs-FC in iNPH patients, based on their outcome after cerebrospinal fluid tap test (CSFTT), and in patients with AD. METHODS Twenty-six iNPH patients (mean age: 79.9±5.9 years; 12 females) underwent MRI and clinical assessment before and after CSFTT and were classified as responders (Resp) or not (NResp), based on the improvement at the timed up and go test and walking speed. Eleven AD patients (mean age: 70.91±5.2 years; 5 females), matched to iNPH for cognitive status, were also included. DMN and hippocampal rs-FC was related to amyloid-β42 and phosphorylated tau (pTau) levels. RESULTS Lower amyloid-β42 levels were associated with reduced inter- and intra-network rs-FC in NResp, and the interaction between amyloid-β42 and rs-FC was a predictor of outcome after CSFTT. The rs-FC between DMN and salience networks positively correlated to amyloid-β42 levels in both NResp and AD patients. The increase in the inter-network rs-FC after CSFTT was associated with higher pTau and lower amyloid-β42 levels in NResp, and to lower pTau levels in Resp. CONCLUSION Amyloid-β42 and pTau impact on rs-FC and its changes after CSFTT in iNPH patients. The interaction between AD biomarkers and rs-FC might explain the responder status in iNPH.
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Affiliation(s)
- Giulia Bommarito
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Dimitri Van De Ville
- Institute of Bioengineering, Center of Neuroprosthetics, Ecole Polytechnique Fédérale De Lausanne (EPFL), Lausanne, Switzerland.,Department of Radiology and Medical Informatics, Geneva University Hospitals and University of Geneva, Geneva, Switzerland
| | - Giovanni B Frisoni
- Memory Clinic, Department of Rehabilitation and Geriatrics, Geneva University and University Hospitals, Geneva, Switzerland
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals and NIMTlab, Geneva University, Geneva, Switzerland
| | - Federica Ribaldi
- Memory Clinic, Department of Rehabilitation and Geriatrics, Geneva University and University Hospitals, Geneva, Switzerland
| | - Sara Stampacchia
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals and NIMTlab, Geneva University, Geneva, Switzerland
| | - Frédéric Assal
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Gilles Allali
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Department of Neurology, Division of Cognitive & Motor Aging, Albert Einstein College of Medicine, Yeshiva University, Bronx, NY, USA
| | - Alessandra Griffa
- Department of Clinical Neurosciences, Division of Neurology, Geneva University Hospitals and Faculty of Medicine, University of Geneva, Geneva, Switzerland.,Institute of Bioengineering, Center of Neuroprosthetics, Ecole Polytechnique Fédérale De Lausanne (EPFL), Lausanne, Switzerland
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38
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Mommaerts K, Willemse EAJ, Marchese M, Larue C, van der Flier WM, Betsou F, Teunissen CE. A Cystatin C Cleavage ELISA Assay as a Quality Control Tool for Determining Sub-Optimal Storage Conditions of Cerebrospinal Fluid Samples in Alzheimer's Disease Research. J Alzheimers Dis 2021; 83:1367-1377. [PMID: 34420976 PMCID: PMC8673510 DOI: 10.3233/jad-210741] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Background: An N-terminal octapeptide cleavage of the cystatin C protein was discovered by mass spectrometry when cerebrospinal fluid (CSF) was stored at –20°C for 3 months, which did not occur when CSF was stored at –80°C. Objective: The aim was to develop an immunoassay as quality assessment tool to detect this –20°C cleavage of cystatin C in CSF and support Alzheimer’s disease research. Methods: A specific monoclonal antibody and a double indirect sandwich ELISA were developed: one assay quantifies the octapeptide uncleaved protein specifically and the other quantifies the total cystatin C present in the biological fluid (both cleaved and uncleaved forms). The ratio of these concentrations was calculated to assess the extent of cleavage of cystatin C. The novel ELISA was validated and applied in a short-term (up to 4 weeks) and mid-term (up to one year) stability study of CSF stored at 4°C, –20°C, –80°C, and liquid nitrogen. Impact of freeze-thaw cycles, adsorption, and protease inhibitors were tested. Results: The ratio of truncated protein was modified following –20°C storage and seemed to reach a plateau after 6 months. The ratio was impacted neither by freeze-thaw cycles nor adsorption. The –20°C specific cleavage was found to be protease related. Conclusion: Using this novel double indirect sandwich ELISA, absolute levels of the total and uncleaved cystatin C and the ratio of truncated cystatin C can be measured. This assay is an easily applicable tool which can be used to confirm that CSF biospecimen are fit-for-purpose for Alzheimer’s disease research.
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Affiliation(s)
- Kathleen Mommaerts
- Biospecimen Research Group, Integrated Biobank of Luxembourg, Luxembourg Institute of Health, Luxembourg.,Luxembourg Centre for Systems Biomedicine (LCSB), University of Luxembourg, Luxembourg
| | - Eline A J Willemse
- Department of Clinical Chemistry, Neurochemistry Laboratory, Amsterdam Neuroscience, Amsterdam University Medical Center, VU University, Amsterdam, the Netherlands
| | - Monica Marchese
- Translational Biomarker Group, Integrated Biobank of Luxembourg, Luxembourg Institute of Health, Luxembourg
| | - Catherine Larue
- Integrated Biobank of Luxembourg, Luxembourg Institute of Health, Luxembourg
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Amsterdam Neuroscience, Amsterdam University Medical Center, VU University, Amsterdam, the Netherlands.,Department of Epidemiology and Biostatistics, Amsterdam University Medical Center, VU Amsterdam, Amsterdam, the Netherlands
| | - Fay Betsou
- Integrated Biobank of Luxembourg, Luxembourg Institute of Health, Luxembourg
| | - Charlotte E Teunissen
- Department of Clinical Chemistry, Neurochemistry Laboratory, Amsterdam Neuroscience, Amsterdam University Medical Center, VU University, Amsterdam, the Netherlands
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Pinaya WHL, Scarpazza C, Garcia-Dias R, Vieira S, Baecker L, F da Costa P, Redolfi A, Frisoni GB, Pievani M, Calhoun VD, Sato JR, Mechelli A. Using normative modelling to detect disease progression in mild cognitive impairment and Alzheimer's disease in a cross-sectional multi-cohort study. Sci Rep 2021; 11:15746. [PMID: 34344910 PMCID: PMC8333350 DOI: 10.1038/s41598-021-95098-0] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2021] [Accepted: 06/22/2021] [Indexed: 02/04/2023] Open
Abstract
Normative modelling is an emerging method for quantifying how individuals deviate from the healthy populational pattern. Several machine learning models have been implemented to develop normative models to investigate brain disorders, including regression, support vector machines and Gaussian process models. With the advance of deep learning technology, the use of deep neural networks has also been proposed. In this study, we assessed normative models based on deep autoencoders using structural neuroimaging data from patients with Alzheimer's disease (n = 206) and mild cognitive impairment (n = 354). We first trained the autoencoder on an independent dataset (UK Biobank dataset) with 11,034 healthy controls. Then, we estimated how each patient deviated from this norm and established which brain regions were associated to this deviation. Finally, we compared the performance of our normative model against traditional classifiers. As expected, we found that patients exhibited deviations according to the severity of their clinical condition. The model identified medial temporal regions, including the hippocampus, and the ventricular system as critical regions for the calculation of the deviation score. Overall, the normative model had comparable cross-cohort generalizability to traditional classifiers. To promote open science, we are making all scripts and the trained models available to the wider research community.
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Affiliation(s)
- Walter H L Pinaya
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK.
- Center of Mathematics, Computing, and Cognition, Universidade Federal do ABC, Santo André, Brazil.
- Department of Biomedical Engineering, School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK.
| | - Cristina Scarpazza
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Department of General Psychology, University of Padua, Padua, Italy
| | - Rafael Garcia-Dias
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Sandra Vieira
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Lea Baecker
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Pedro F da Costa
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Centre for Brain and Cognitive Development, Birkbeck College, University of London, London, UK
| | - Alberto Redolfi
- Laboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Giovanni B Frisoni
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
- Memory Clinic and LANVIE Laboratory of Neuroimaging of Aging, University Hospitals and University of Geneva, Geneva, Switzerland
| | - Michela Pievani
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Vince D Calhoun
- Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State, Georgia Tech, Emory, USA
| | - João R Sato
- Center of Mathematics, Computing, and Cognition, Universidade Federal do ABC, Santo André, Brazil
| | - Andrea Mechelli
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
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40
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Jung NY, Kim ES, Kim HS, Jeon S, Lee MJ, Pak K, Lee JH, Lee YM, Lee K, Shin JH, Ko JK, Lee JM, Yoon JA, Hwang C, Choi KU, Lee EC, Seong JK, Huh GY, Kim DS, Kim EJ. Comparison of Diagnostic Performances Between Cerebrospinal Fluid Biomarkers and Amyloid PET in a Clinical Setting. J Alzheimers Dis 2021; 74:473-490. [PMID: 32039853 DOI: 10.3233/jad-191109] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
The diagnostic performances of cerebrospinal fluid (CSF) biomarkers and amyloid positron emission tomography (PET) were compared by examining the association and concordance or discordance between CSF Aβ1-42 and amyloid PET, after determining our own cut-off values for CSF Alzheimer's disease (AD) biomarkers. Furthermore, we evaluated the ability of CSF biomarkers and amyloid PET to predict clinical progression. CSF Aβ1-42, t-tau, and p-tau levels were analyzed in 203 individuals [27 normal controls, 38 mild cognitive impairment (MCI), 62 AD dementia, and 76 patients with other neurodegenerative diseases] consecutively recruited from two dementia clinics. We used both visual and standardized uptake value ratio (SUVR)-based amyloid PET assessments for analyses. The association of CSF biomarkers with amyloid PET SUVR, hippocampal atrophy, and cognitive function were investigated by linear regression analysis, and the risk of conversion from MCI to AD dementia was assessed using a Cox proportional hazards model. CSF p-tau/Aβ1-42 and t-tau/Aβ1-42 exhibited the best diagnostic accuracies among the CSF AD biomarkers examined. Correlations were observed between CSF biomarkers and global SUVR, hippocampal volume, and cognitive function. Overall concordance and discordance between CSF Aβ1-42 and amyloid PET was 77% and 23%, respectively. Baseline positive CSF Aβ1-42 for MCI demonstrated a 5.6-fold greater conversion risk than negative CSF Aβ1-42 . However, amyloid PET findings failed to exhibit significant prognostic value. Therefore, despite presence of a significant correlation between the CSF Aβ1-42 level and SUVR of amyloid PET, and a relevant concordance between CSF Aβ1-42 and amyloid PET, baseline CSF Aβ1-42 better predicted AD conversion.
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Affiliation(s)
- Na-Yeon Jung
- Department of Neurology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, Republic of Korea.,Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Eun Soo Kim
- Department of Anesthesia and Pain Medicine, Pusan National University Hospital, School of Medicine, Pusan National University, Busan, Republic of Korea
| | - Hyang-Sook Kim
- Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Sumin Jeon
- Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan, Republic of Korea
| | - Myung Jun Lee
- Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan, Republic of Korea
| | - Kyoungjune Pak
- Department of Nuclear Medicine, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea
| | - Jae-Hyeok Lee
- Department of Neurology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, Republic of Korea.,Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Young Min Lee
- Department of Psychiatry, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea
| | - Kangyoon Lee
- Department of Psychiatry, Pusan National University Hospital, Pusan National University School of Medicine, Busan, Republic of Korea
| | - Jin-Hong Shin
- Department of Neurology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, Republic of Korea.,Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, Republic of Korea
| | - Jun Kyeung Ko
- Department of Neurosurgery, Medical Research Institute, Pusan National University Hospital, Busan, Republic of Korea
| | - Jae Meen Lee
- Department of Neurosurgery, Medical Research Institute, Pusan National University Hospital, Busan, Republic of Korea
| | - Jin A Yoon
- Department of Rehabilitation Medicine, Pusan National University School of Medicine and Biomedical Research Institute, Pusan National University Hospital, Busan, Republic of Korea
| | - Chungsu Hwang
- Department of Pathology, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Kyung-Un Choi
- Department of Pathology, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Eun Chong Lee
- School of Biomedical Engineering, Korea University, Seoul, Republic of Korea
| | - Joon-Kyung Seong
- School of Biomedical Engineering, Korea University, Seoul, Republic of Korea
| | - Gi Yeong Huh
- Department of Forensic Medicine, Pusan National University School of Medicine, Yangsan, Republic of Korea
| | - Dae-Seong Kim
- Department of Neurology, Pusan National University Yangsan Hospital, Pusan National University School of Medicine, Yangsan, Republic of Korea.,Research Institute for Convergence of Biomedical Science and Technology, Pusan National University Yangsan Hospital, Yangsan, 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
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Thijssen EH, Verberk IMW, Vanbrabant J, Koelewijn A, Heijst H, Scheltens P, van der Flier W, Vanderstichele H, Stoops E, Teunissen CE. Highly specific and ultrasensitive plasma test detects Abeta(1-42) and Abeta(1-40) in Alzheimer's disease. Sci Rep 2021; 11:9736. [PMID: 33958661 DOI: 10.1038/s41598-021-89004-x] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 04/19/2021] [Indexed: 12/12/2022] Open
Abstract
Plasma biomarkers that reflect specific amyloid beta (Abeta) proteoforms provide an insight in the treatment effects of Alzheimer’s disease (AD) therapies. Our aim was to develop and validate ready-to-use Simoa ‘Amyblood’ assays that measure full length Abeta1-42 and Abeta1-40 and compare their performance with two commercial assays. Linearity, intra- and inter-assay %CV were compared between Amyblood, Quanterix Simoa triplex, and Euroimmun ELISA. Sensitivity and selectivity were assessed for Amyblood and the Quanterix triplex. Clinical performance was assessed in CSF biomarker confirmed AD (n = 43, 68 ± 6 years) and controls (n = 42, 62 ± 5 years). Prototype and Amyblood showed similar calibrator curves and differentiation (20 AD vs 20 controls, p < 0.001). Amyblood, Quanterix triplex, and ELISA showed similar linearity (96%-122%) and intra-assay %CVs (≤ 3.1%). A minor non-specific signal was measured with Amyblood of + 2.4 pg/mL Abeta1-42 when incubated with 60 pg/mL Abeta1-40. A substantial non-specific signal of + 24.7 pg/mL Abetax-42 was obtained when 40 pg/mL Abeta3-42 was measured with the Quanterix triplex. Selectivity for Abeta1-42 at physiological Abeta1-42 and Abeta1-40 concentrations was 125% for Amyblood and 163% for Quanterix. Amyblood and Quanterix ratios (p < 0.001) and ELISA Abeta1-42 concentration (p = 0.025) could differentiate AD from controls. We successfully developed and upscaled a prototype to the Amyblood assays with similar technical and clinical performance as the Quanterix triplex and ELISA, but better specificity and selectivity than the Quanterix triplex assay. These results suggest leverage of this specific assay for monitoring treatment response in trials.
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Stiffel M, Bergeron D, Mourabit Amari K, Poulin É, Roberge X, Meilleur-Durand S, Sellami L, Molin P, Nadeau Y, Fortin MP, Caron S, Poulin S, Verret L, Bouchard RW, Teunissen C, Laforce RJ. Use of Alzheimer's Disease Cerebrospinal Fluid Biomarkers in A Tertiary Care Memory Clinic. Can J Neurol Sci 2021;:1-7. [PMID: 33845924 DOI: 10.1017/cjn.2021.67] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
INTRODUCTION Alzheimer's disease (AD) cerebrospinal fluid (CSF) biomarkers are promising tools to help identify the underlying pathology of neurocognitive disorders. In this manuscript, we report our experience with AD CSF biomarkers in 262 consecutive patients in a tertiary care memory clinic. METHODS We retrospectively reviewed 262 consecutive patients who underwent lumbar puncture (LP) and CSF measurement of AD biomarkers (Aβ1-42, total tau or t-tau, and p-tau181). We studied the safety of the procedure and its impact on patient's diagnosis and management. RESULTS The LP allowed to identify underlying AD pathology in 72 of the 121 patients (59%) with early onset amnestic mild cognitive impairment (aMCI) with a high probability of progression to AD; to distinguish the behavioral/dysexecutive variant of AD from the behavioral variant of frontotemporal dementia (bvFTD) in 25 of the 45 patients (55%) with an atypical neurobehavioral profile; to identify AD as the underlying pathology in 15 of the 27 patients (55%) with atypical or unclassifiable primary progressive aphasia (PPA); and to distinguish AD from other disorders in 9 of the 29 patients (31%) with psychiatric differential diagnoses and 19 of the 40 patients (47%) with lesional differential diagnoses (normal pressure hydrocephalus, encephalitis, prion disease, etc.). No major complications occurred following the LP. INTERPRETATION Our results suggest that CSF analysis is a safe and effective diagnostic tool in select patients with neurocognitive disorders. We advocate for a wider use of this biomarker in tertiary care memory clinics in Canada.
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Mentis AFA, Dardiotis E, Chrousos GP. Apolipoprotein E4 and meningeal lymphatics in Alzheimer disease: a conceptual framework. Mol Psychiatry 2021; 26:1075-1097. [PMID: 32355332 PMCID: PMC7985019 DOI: 10.1038/s41380-020-0731-7] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/03/2019] [Revised: 04/01/2020] [Accepted: 04/09/2020] [Indexed: 12/11/2022]
Abstract
The potential existence and roles of the meningeal lymphatic system in normal and pathological brain function have been a long-standing enigma. Recent evidence suggests that meningeal lymphatic vessels are present in both the mouse and human brain; in mice, they seem to play a role in clearing toxic amyloid-beta peptides, which have been connected with Alzheimer disease (AD). Here, we review the evidence linking the meningeal lymphatic system with human AD. Novel findings suggest that the recently described meningeal lymphatic vessels could be linked to, and possibly drain, the efferent paravascular glial lymphatic (glymphatic) system carrying cerebrospinal fluid, after solute and immune cell exchange with brain interstitial fluid. In so doing, the glymphatic system could contribute to the export of toxic solutes and immune cells from the brain (an exported fluid we wish to describe as glymph, similarly to lymph) to the meningeal lymphatic system; the latter, by being connected with downstream anatomic regions, carries the glymph to the conventional cervical lymphatic vessels and nodes. Thus, abnormal function in the meningeal lymphatic system could, in theory, lead to the accumulation, in the brain, of amyloid-beta, cellular debris, and inflammatory mediators, as well as immune cells, resulting in damage of the brain parenchyma and, in turn, cognitive and other neurologic dysfunctions. In addition, we provide novel insights into APOE4-the leading genetic risk factor for AD-and its relation to the meningeal lymphatic system. In this regard, we have reanalyzed previously published RNA-Seq data to show that induced pluripotent stem cells (iPSCs) carrying the APOE4 allele (either as APOE4 knock-in or stemming from APOE4 patients) express lower levels of (a) genes associated with lymphatic markers, and (b) genes for which well-characterized missense mutations have been linked to peripheral lymphedema. Taking into account this evidence, we propose a new conceptual framework, according to which APOE4 could play a novel role in the premature shrinkage of meningeal lymphatic vessels (meningeal lymphosclerosis), leading to abnormal meningeal lymphatic functions (meningeal lymphedema), and, in turn, reduction in the clearance of amyloid-beta and other macromolecules and inflammatory mediators, as well as immune cells, from the brain, exacerbation of AD manifestations, and progression of the disease. Altogether, these findings and their potential interpretations may herald novel diagnostic tools and therapeutic approaches in patients with AD.
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Affiliation(s)
- Alexios-Fotios A Mentis
- Public Health Laboratories, Hellenic Pasteur Institute, Vas. Sofias Avenue 127, 115 21, Athens, Greece.
- Department of Microbiology, University of Thessaly, Panepistimiou 3, Viopolis, 41 500, Larissa, Greece.
| | - Efthimios Dardiotis
- Department of Neurology, University of Thessaly, Panepistimiou 3, Viopolis, 41 500, Larissa, Greece
| | - George P Chrousos
- University Research Institute of Maternal and Child Health and Precision Medicine, National and Kapodistrian University of Athens, Medical School, Aghia Sophia Children's Hospital, Livadias 8, 115 27, Athens, Greece
- UNESCO Chair on Adolescent Health Care, Athens, Greece
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Ye LQ, Gao PR, Zhang YB, Cheng HR, Tao QQ, Wu ZY, Li HL. Application of Cerebrospinal Fluid AT(N) Framework on the Diagnosis of AD and Related Cognitive Disorders in Chinese Han Population. Clin Interv Aging 2021; 16:311-323. [PMID: 33654388 PMCID: PMC7910151 DOI: 10.2147/cia.s294756] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Accepted: 01/21/2021] [Indexed: 11/23/2022] Open
Abstract
Background Studies concerning the impact of the AT(N) framework on diagnostic capability in the dementia population are lacking. We aimed to explore the diagnostic application of CSF AT(N) framework in clinical routines of Alzheimer's disease (AD) as well as differential diagnosis of other cognitive diseases in the Chinese Han population. Patients and Methods A total of 137 patients with cognitive disorders received CSF tests of Aβ42, t-tau and p-tau181. Their CSF biomarker results were categorized and interpreted by the AT(N) framework. Neurologists provided a diagnosis both pre- and post-CSF biomarker disclosure with corresponding diagnostic confidence. Results The total initial diagnosis included 79 patients with AD and 58 patients with non-AD (NAD). The results of CSF biomarkers led to a diagnostic change of 28% in the cohort. Approximately 81.5% (n=53) of 65 patients whose CSF biomarker showed an underlying AD pathology were finally diagnosed as AD, with an increase of 17.5% in diagnostic confidence. Thirty-seven CSF results indicating NAD pathologic changes contributed to an exclusion of AD in 56.8% (n=21) of the patients along with a modest increase of 9.8% in average confidence. Thirty-five patients with normal CSF biomarkers maintained the diagnosis of NAD in 68.6% (n=24) of the group, leading to a slight elevation of 7.6% in confidence. Conclusion We found that the presence of amyloid pathology (A+) is contributable to diagnosing AD and improving confidence. On occasion of negative amyloid pathology (A-), with or without tau pathology, gaining uncertainty of the primary AD diagnosis would diminish the corresponding confidence. To the best of our knowledge, this is the first study performed in the Chinese Han population with cognitive disorders that explores the clinical capability of CSF AT(N) framework in a quantitative way.
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Affiliation(s)
- Ling-Qi Ye
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, and Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, People's Republic of China.,Department of Rehabilitation Medicine and Rehabilitation & Sports Medicine Research Institute of Zhejiang Province, Zhejiang Provincial People's Hospital, People's Hospital of Hangzhou Medical College, Hangzhou, People's Republic of China
| | - Pei-Rong Gao
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, and Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Yan-Bin Zhang
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, and Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, People's Republic of China.,Department of Neurology and Institute of Neurology in First Affiliated Hospital, Fujian Medical University, Fuzhou, People's Republic of China
| | - Hong-Rong Cheng
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, and Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, People's Republic of China.,Department of Neurology in Fourth Affiliated Hospital, Zhejiang University School of Medicine, Yiwu, People's Republic of China
| | - Qing-Qing Tao
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, and Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Zhi-Ying Wu
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, and Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
| | - Hong-Lei Li
- Department of Neurology and Research Center of Neurology in Second Affiliated Hospital, and Key Laboratory of Medical Neurobiology of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, People's Republic of China
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Babapour Mofrad R, Fruijtier AD, Visser LNC, Hoogland N, van Dijk M, van Rossum F, Bouwman FH, Smets EMA, Teunissen CE, van der Flier WM. Lumbar puncture patient video increases knowledge and reduces uncertainty: An RCT. Alzheimers Dement (N Y) 2021; 7:e12127. [PMID: 33614895 PMCID: PMC7882513 DOI: 10.1002/trc2.12127] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/25/2020] [Revised: 11/13/2020] [Accepted: 11/25/2020] [Indexed: 11/16/2022]
Abstract
BACKGROUND Patients often perceive a lumbar puncture (LP) as an invasive procedure. We aimed to evaluate the impact of a 3-minute educational animation-video explaining the LP procedure, on patients' knowledge, uncertainty, anxiety, and post-LP complications. METHODS We included 203 newly referred memory clinic patients, who were randomly assigned to one of three conditions: (1) home viewing of the video, (2) clinic viewing of the video, or (3) control condition (care as usual). Participants completed questionnaires measuring knowledge as information recall, uncertainty, anxiety, and post-LP complications, the latter when patients underwent an LP procedure (n = 145). RESULTS Viewing the video increased information recall for both home (P < .001), and clinic viewers (P < .001) compared to controls. Levels of uncertainty decreased after viewing (Pfor interaction = .044), particularly for clinic viewers. Viewing the video or not did not affect anxiety and post-LP complications. DISCUSSION Preparing individuals for an LP by means of an educational video can help to increase knowledge about the procedure and reduce feelings of uncertainty.
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Affiliation(s)
- Rosha Babapour Mofrad
- Neurochemistry Laboratory and BiobankDepartment of Clinical Chemistry, Amsterdam NeuroscienceVU University Medical Center AmsterdamAmsterdam UMCAmsterdamthe Netherlands
- Department of Neurology, Alzheimer Center, Neuroscience Campus AmsterdamVU University Medical CenterAmsterdam UMCAmsterdamthe Netherlands
| | - Agnetha D. Fruijtier
- Department of Neurology, Alzheimer Center, Neuroscience Campus AmsterdamVU University Medical CenterAmsterdam UMCAmsterdamthe Netherlands
- Department of Medical Psychology, Amsterdam Public HealthUniversity of AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Leonie N. C. Visser
- Department of Neurology, Alzheimer Center, Neuroscience Campus AmsterdamVU University Medical CenterAmsterdam UMCAmsterdamthe Netherlands
- Department of Medical Psychology, Amsterdam Public HealthUniversity of AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Nina Hoogland
- Department of Neurology, Alzheimer Center, Neuroscience Campus AmsterdamVU University Medical CenterAmsterdam UMCAmsterdamthe Netherlands
| | - Maisa van Dijk
- Neuroscience Campus AmsterdamVU University Medical CenterAmsterdam UMCAmsterdamthe Netherlands
| | - Frederique van Rossum
- Neuroscience Campus AmsterdamVU University Medical CenterAmsterdam UMCAmsterdamthe Netherlands
| | - Femke H. Bouwman
- Department of Neurology, Alzheimer Center, Neuroscience Campus AmsterdamVU University Medical CenterAmsterdam UMCAmsterdamthe Netherlands
| | - Ellen M. A. Smets
- Department of Medical Psychology, Amsterdam Public HealthUniversity of AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Charlotte E. Teunissen
- Neurochemistry Laboratory and BiobankDepartment of Clinical Chemistry, Amsterdam NeuroscienceVU University Medical Center AmsterdamAmsterdam UMCAmsterdamthe Netherlands
| | - Wiesje M. van der Flier
- Department of Neurology, Alzheimer Center, Neuroscience Campus AmsterdamVU University Medical CenterAmsterdam UMCAmsterdamthe Netherlands
- Department of Epidemiology and BiostatisticsVU University Medical CenterAmsterdam UMCAmsterdamthe Netherlands
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van Hooren RWE, Verhey FRJ, Ramakers IHGB, Jansen WJ, Jacobs HIL. Elevated norepinephrine metabolism is linked to cortical thickness in the context of Alzheimer's disease pathology. Neurobiol Aging 2021; 102:17-22. [PMID: 33667876 DOI: 10.1016/j.neurobiolaging.2021.01.024] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 01/19/2021] [Accepted: 01/26/2021] [Indexed: 01/05/2023]
Abstract
Advanced Alzheimer's disease (AD) is characterized by higher noradrenaline metabolite levels that may be associated with AD pathology. The locus coeruleus (LC) is the main site for cerebral noradrenaline synthesis and LC volume loss occurs as early as Braak stage 1. This study investigates the association between noradrenergic turnover and brain morphology, and the modifying effect of AD pathology. The study sample included 77 memory clinic patients (37 cognitively unimpaired and 40 cognitively impaired (mild cognitive impairment or AD dementia)). Cortical thickness and volumetric analyses were performed using FreeSurfer. Cerebrospinal fluid was analyzed for noradrenergic metabolite 3-methoxy-4-hydroxyphenylethyleneglycol (MHPG), Aβ42 and phosphorylated tau. Higher MHPG was associated with lower cortical thickness and hippocampal volume at lower, but subthreshold, levels of Aβ42 and at higher p-tau levels. These associations remained significant after adding APOE-E4 or cognitive status as covariates. Our results suggest that greater MHPG together with worse AD pathology contributes to neurodegeneration, possibly before significant amyloidosis. The noradrenergic system may play an important role in early detection of AD-related processes.
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Moon S, Kim S, Mankhong S, Choi SH, Vandijck M, Kostanjevecki V, Jeong JH, Yoon SJ, Park KW, Kim EJ, Yoon B, Kim HJ, Jang JW, Hong JY, Park DH, Shaw LM, Kang JH. Alzheimer's cerebrospinal biomarkers from Lumipulse fully automated immunoassay: concordance with amyloid-beta PET and manual immunoassay in Koreans : CSF AD biomarkers measured by Lumipulse in Koreans. Alzheimers Res Ther 2021; 13:22. [PMID: 33436035 PMCID: PMC7802266 DOI: 10.1186/s13195-020-00767-3] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/26/2020] [Accepted: 12/29/2020] [Indexed: 12/14/2022]
Abstract
Background Alzheimer’s disease (AD) cerebrospinal fluid (CSF) biomarker cutoffs from immunoassays with low interlaboratory variability in diverse ethnic groups are necessary for their use in clinics and clinical trials. With lack of cutoffs from fully automated immunoassay platforms in diverse races, the aim of this study is to evaluate the clinical utility of CSF AD biomarkers from the Lumipulse fully automated immunoassay based on β-amyloid (Aβ) positron emission tomography (PET) status comparing with these from two manual immunoassays, in Koreans. Methods Among 331 Korean participants enrolled from a prospective, 3-year longitudinal observational study of the validation cohort of Korean Brain Aging Study for the Early Diagnosis and Prediction of AD, 139 (29 CN, 58 SCD, 29 MCI, and 23 AD) provided CSF and 271 underwent baseline amyloid PET (n = 128 with overlapping CSF and Aβ-PET, and 143 without CSFs). Three annual cognitive and neuropsychiatric function tests were conducted. Aβ42, Aβ40, total-tau, and phosphorylated-tau181 were measured by Lumipulse fully automated immunoassay and two manual immunoassays (INNO-BIA AlzBio3, INNOTEST). Clinical utility of CSF biomarker cutoffs, based on 128 participants with Aβ-PET, was evaluated. Results Cognitive and neuropsychological scores differed significantly among the groups, with descending performance among CN>SCD>MCI>AD. Biomarker levels among immunoassays were strongly intercorrelated. We determined the Aβ-PET status in a subgroup without CSF (n = 143), and then when we applied CSF biomarker cutoffs determined based on the Aβ-PET status, the CSF biomarkers (cutoffs of 642.1 pg/mL for Aβ42, 0.060 for Aβ42/Aβ40, 0.315 for t-tau/Aβ42, and 0.051 for p-tau/Aβ42, respectively) showed good agreement with Aβ-PET (overall AUC ranges of 0.840–0.898). Use of the Aβ-PET-based CSF cutoffs showed excellent diagnostic discrimination between AD and CN (Aβ42, Aβ42/Aβ40, t-tau/Aβ42, and p-tau/Aβ42) with overall AUC ranges of 0.876–0.952. During follow-up, participants with AD-like CSF signature determined by Aβ-PET-based cutoffs from Lumipulse showed rapid progression of cognitive decline in 139 subjects, after adjustment for potential confounders, compared with those with a normal CSF signature. Conclusion CSF AD biomarkers measured by different immunoassay platforms show strong intercorrelated agreement with Aβ-PET in Koreans. The Korean-specific Aβ-PET-based CSF biomarker cutoffs measured by the Lumipulse assay strongly predicts progression of cognitive decline. The clinical utility of CSF biomarkers from fully-automated immunoassay platforms should be evaluated in larger, more diverse cohorts.
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Affiliation(s)
- Sohee Moon
- Department of Pharmacology and Hypoxia-related Disease Research Center, College of Medicine, Inha University, Room 1015, 60th Anniversary Hall, 100, Inha-ro, Nam-gu, Incheon, 22212, South Korea
| | - Sujin Kim
- Department of Pharmacology and Hypoxia-related Disease Research Center, College of Medicine, Inha University, Room 1015, 60th Anniversary Hall, 100, Inha-ro, Nam-gu, Incheon, 22212, South Korea.,Department of Kinesiology, Inha University, Incheon, 22212, South Korea
| | - Sakulrat Mankhong
- Department of Pharmacology and Hypoxia-related Disease Research Center, College of Medicine, Inha University, Room 1015, 60th Anniversary Hall, 100, Inha-ro, Nam-gu, Incheon, 22212, South Korea.,Program in Biomedical Science and Engineering, Inha University, Incheon, 22212, South Korea
| | - Seong Hye Choi
- Department of Neurology, College of Medicine, Inha University, Incheon, 22332, South Korea
| | - Manu Vandijck
- Fujirebio-Europe N.V., Technologiepark 6, 9052, Ghent, Belgium
| | | | - Jee Hyang Jeong
- Department of Neurology, Ewha Womans University Mokdong Hospital, Ewha Womans University School of Medicine, Seoul, 07985, South Korea
| | - Soo Jin Yoon
- Department of Neurology, Eulji University Hospital, Eulji University School of Medicine, Daejeon, 35233, South Korea
| | - Kyung Won Park
- Department of Neurology, Dong-A Medical Center, Dong-A University College of Medicine, Busan, 49201, South Korea
| | - Eun-Joo Kim
- Department of Neurology, Pusan National University Hospital, Pusan National University School of Medicine and Medical Research Institute, Busan, 49241, South Korea
| | - Bora Yoon
- Department of Neurology, Konyang University College of Medicine, Daejeon, 35365, South Korea
| | - Hee Jin Kim
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, 06351, South Korea
| | - Jae-Won Jang
- Department of Neurology, Kangwon National University Hospital, Chuncheon, 24289, South Korea
| | - Jin Yong Hong
- Department of Neurology, Yonsei University Wonju College of Medicine, Wonju, 26426, South Korea
| | - Dong-Ho Park
- Department of Kinesiology, Inha University, Incheon, 22212, South Korea
| | - Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, 19104, PA, USA
| | - Ju-Hee Kang
- Department of Pharmacology and Hypoxia-related Disease Research Center, College of Medicine, Inha University, Room 1015, 60th Anniversary Hall, 100, Inha-ro, Nam-gu, Incheon, 22212, South Korea. .,Program in Biomedical Science and Engineering, Inha University, Incheon, 22212, South Korea.
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van Maurik IS, Rhodius-Meester HFM, Teunissen CE, Scheltens P, Barkhof F, Palmqvist S, Hansson O, van der Flier WM, Berkhof J. Biomarker testing in MCI patients-deciding who to test. Alzheimers Res Ther 2021; 13:14. [PMID: 33413634 PMCID: PMC7792312 DOI: 10.1186/s13195-020-00763-7] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 12/23/2020] [Indexed: 11/10/2022]
Abstract
BACKGROUND We aimed to derive an algorithm to define the optimal proportion of patients with mild cognitive impairment (MCI) in whom cerebrospinal fluid (CSF) testing is of added prognostic value. METHODS MCI patients were selected from the Amsterdam Dementia Cohort (n = 402). Three-year progression probabilities to dementia were predicted using previously published models with and without CSF data (amyloid-beta1-42 (Abeta), phosphorylated tau (p-tau)). We incrementally augmented the proportion of patients undergoing CSF, starting with the 10% patients with prognostic probabilities based on clinical data around the median (percentile 45-55), until all patients received CSF. The optimal proportion was defined as the proportion where the stepwise algorithm showed similar prognostic discrimination (Harrell's C) and accuracy (three-year Brier scores) compared to CSF testing of all patients. We used the BioFINDER study (n = 221) for validation. RESULTS The optimal proportion of MCI patients to receive CSF testing selected by the stepwise approach was 50%. CSF testing in only this proportion improved the performance of the model with clinical data only from Harrell's C = 0.60, Brier = 0.198 (Harrell's C = 0.61, Brier = 0.197 if the information on magnetic resonance imaging was available) to Harrell's C = 0.67 and Brier = 0.190, and performed similarly to a model in which all patients received CSF testing. Applying the stepwise approach in the BioFINDER study would again select half of the MCI patients and yielded robust results with respect to prognostic performance. INTERPRETATION CSF biomarker testing adds prognostic value in half of the MCI patients. As such, we achieve a CSF saving recommendation while simultaneously retaining optimal prognostic accuracy.
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Affiliation(s)
- Ingrid S van Maurik
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands. .,Department of Epidemiology and Data Sciences, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
| | - Hanneke F M Rhodius-Meester
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands.,Department of Internal Medicine, Geriatric Medicine Section, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Institutes of Neurology and Healthcare Engineering, University College London, London, England
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences, Malmö, Lund University, Lund, Sweden.,Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, VU University Medical Center, Vrije Universiteit Amsterdam, Amsterdam UMC, De Boelelaan 1118, 1081 HZ, Amsterdam, The Netherlands.,Department of Epidemiology and Data Sciences, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Johannes Berkhof
- Department of Epidemiology and Data Sciences, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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Duits FH, Wesenhagen KEJ, Ekblad L, Wolters E, Willemse EAJ, Scheltens P, van der Flier WM, Teunissen CE, Visser PJ, Tijms BM. Four subgroups based on tau levels in Alzheimer's disease observed in two independent cohorts. Alzheimers Res Ther 2021; 13:2. [PMID: 33397464 PMCID: PMC7780683 DOI: 10.1186/s13195-020-00713-3] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2020] [Accepted: 10/22/2020] [Indexed: 12/20/2022]
Abstract
BACKGROUND As Alzheimer's disease (AD) pathology presents decades before dementia manifests, unbiased biomarker cut-points may more closely reflect presence of pathology than clinically defined cut-points. Currently, unbiased cerebrospinal fluid (CSF) tau cut-points are lacking. METHODS We investigated CSF t-tau and p-tau cut-points across the clinical spectrum using Gaussian mixture modelling, in two independent cohorts (Amsterdam Dementia Cohort and ADNI). RESULTS Individuals with normal cognition (NC) (total n = 1111), mild cognitive impairment (MCI) (total n = 1213) and Alzheimer's disease dementia (AD) (total n = 1524) were included. In both cohorts, four CSF t- and p-tau distributions and three corresponding cut-points were identified. Increasingly high tau subgroups were characterized by steeper MMSE decline and higher progression risk to AD (cohort/platform-dependent HR, t-tau 1.9-21.3; p-tau 2.2-9.5). LIMITATIONS The number of subjects in some subgroups and subanalyses was small, especially in the highest tau subgroup and in tau PET analyses. CONCLUSIONS In two independent cohorts, t-tau and p-tau levels showed four subgroups. Increasingly high tau subgroups were associated with faster clinical decline, suggesting our approach may aid in more precise prognoses.
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Affiliation(s)
- Flora H Duits
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Kirsten E J Wesenhagen
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands.
| | - Laura Ekblad
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Turku PET Centre, University of Turku and Turku University Hospital, Turku, Finland
| | - Emma Wolters
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Department of Radiology & Nuclear Medicine, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Eline A J Willemse
- Department of Clinical Chemistry, Neurochemistry Laboratory, Amsterdam UMC, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Philip Scheltens
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
| | - Wiesje M van der Flier
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Department of Epidemiology and Biostatistics, Amsterdam UMC, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Department of Clinical Chemistry, Neurochemistry Laboratory, Amsterdam UMC, Amsterdam Neuroscience, Amsterdam, Netherlands
| | - Pieter Jelle Visser
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
- Alzheimer Center Limburg, Department of Psychiatry & Neuropsychology, School of Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden
| | - Betty M Tijms
- Department of Neurology, Alzheimer Center Amsterdam, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, the Netherlands
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Hansen EO, Dias NS, Burgos ICB, Costa MV, Carvalho AT, Teixeira AL, Barbosa IG, Santos LAV, Rosa DVF, Ribeiro AJF, Viana BM, Bicalho MAC. Millipore xMap® Luminex (HATMAG-68K): An Accurate and Cost-Effective Method for Evaluating Alzheimer's Biomarkers in Cerebrospinal Fluid. Front Psychiatry 2021; 12:716686. [PMID: 34531769 PMCID: PMC8438166 DOI: 10.3389/fpsyt.2021.716686] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Accepted: 07/21/2021] [Indexed: 11/13/2022] Open
Abstract
Background: Alzheimer's disease (AD) biomarkers are of great relevance in clinical research, especially after the AT(N) framework. They enable early diagnosis, disease staging and research with new promising drugs, monitoring therapeutic response. However, the high cost and low availability of the most well-known methods limits their use in low and medium-income countries. In this context, Millipore xMap® Luminex may be a cost-effective alternative. In our study, using INNOTEST® as reference, we assess the diagnostic accuracy of Millipore xMap® and propose a cutoff point for AD. Methods: We performed lumbar puncture of seven older individuals with clinically defined AD, 17 with amnestic mild cognitive impairment (aMCI) and 11 without objective cognitive impairment-control group (CG). Cerebrospinal fluid (CSF) biomarkers concentrations for aB42, p-Tau, and t-Tau were measured by INNOTEST® and Millipore xMap®, and then the techniques were compared to assess the diagnostic accuracy of the new test and to define a cutoff. Results: INNOTEST® and Millipore xMap® measurements showed all correlations >0.8 for the same biomarker, except for t-Tau that was 0.66. Millipore xMap® measurements showed a robust accuracy for all biomarkers, with AUC higher than 0.808 (t-Tau), and the best for Aβ42 (AUC = 0.952). The most accurate cutoffs were found at 1012.98 pg/ml (Aβ42), 64.54 pg/ml (p-tau), 3251.81 pg/ml (t-tau), 3.370 (t-Tau/Aβ42), and 0.059 (p-Tau/Aβ42). Conclusion: Given its good accuracy and cost-effectiveness, Milliplex xMap® tests seems a reliable and promising tool, especially for low and middle-income countries.
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Affiliation(s)
- Erika Oliveira Hansen
- Jenny de Andrade Faria Institute- Reference Center for the Elderly, Hospital das Clínicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Molecular Medicine Program, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Natalia Silva Dias
- Neuroscience Program, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Elderly Psychiatry and Psychology Extension Program (PROEPSI), Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Ivonne Carolina Bolaños Burgos
- Adult Health Sciences Applied Program, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Monica Vieira Costa
- Molecular Medicine Program, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | - Antonio Lucio Teixeira
- Department of Psychiatry and Behavioral Sciences, UT Health, Houston, TX, United States.,Instituto de Ensino e Pesquisa, Santa Casa de Belo Horizonte, Belo Horizonte, Brazil
| | - Izabela Guimarães Barbosa
- Neuroscience Program, Institute of Biological Sciences, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Elderly Psychiatry and Psychology Extension Program (PROEPSI), Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Department of Mental Health, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Lorena Aline Valu Santos
- National Institute of Science and Technology of Molecular Medicine (INCT-MM), Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Daniela Valadão Freitas Rosa
- National Institute of Science and Technology of Molecular Medicine (INCT-MM), Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | | | - Bernardo Mattos Viana
- Jenny de Andrade Faria Institute- Reference Center for the Elderly, Hospital das Clínicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Elderly Psychiatry and Psychology Extension Program (PROEPSI), Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Department of Mental Health, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
| | - Maria Aparecida Camargos Bicalho
- Jenny de Andrade Faria Institute- Reference Center for the Elderly, Hospital das Clínicas, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Molecular Medicine Program, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Elderly Psychiatry and Psychology Extension Program (PROEPSI), Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,National Institute of Science and Technology of Molecular Medicine (INCT-MM), Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil.,Department of Clinical Medicine, Faculdade de Medicina, Universidade Federal de Minas Gerais, Belo Horizonte, Brazil
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