1
|
Estarellas M, Oxtoby NP, Schott JM, Alexander DC, Young AL. Multimodal subtypes identified in Alzheimer's Disease Neuroimaging Initiative participants by missing-data-enabled subtype and stage inference. Brain Commun 2024; 6:fcae219. [PMID: 39035417 PMCID: PMC11259979 DOI: 10.1093/braincomms/fcae219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 03/14/2024] [Accepted: 06/22/2024] [Indexed: 07/23/2024] Open
Abstract
Alzheimer's disease is a highly heterogeneous disease in which different biomarkers are dynamic over different windows of the decades-long pathophysiological processes, and potentially have distinct involvement in different subgroups. Subtype and Stage Inference is an unsupervised learning algorithm that disentangles the phenotypic heterogeneity and temporal progression of disease biomarkers, providing disease insight and quantitative estimates of individual subtype and stage. However, a key limitation of Subtype and Stage Inference is that it requires a complete set of biomarkers for each subject, reducing the number of datapoints available for model fitting and limiting applications of Subtype and Stage Inference to modalities that are widely collected, e.g. volumetric biomarkers derived from structural MRI. In this study, we adapted the Subtype and Stage Inference algorithm to handle missing data, enabling the application of Subtype and Stage Inference to multimodal data (magnetic resonance imaging, positron emission tomography, cerebrospinal fluid and cognitive tests) from 789 participants in the Alzheimer's Disease Neuroimaging Initiative. Missing-data Subtype and Stage Inference identified five subtypes having distinct progression patterns, which we describe by the earliest unique abnormality as 'Typical AD with Early Tau', 'Typical AD with Late Tau', 'Cortical', 'Cognitive' and 'Subcortical'. These new multimodal subtypes were differentially associated with age, years of education, Apolipoprotein E (APOE4) status, white matter hyperintensity burden and the rate of conversion from mild cognitive impairment to Alzheimer's disease, with the 'Cognitive' subtype showing the fastest clinical progression, and the 'Subcortical' subtype the slowest. Overall, we demonstrate that missing-data Subtype and Stage Inference reveals a finer landscape of Alzheimer's disease subtypes, each of which are associated with different risk factors. Missing-data Subtype and Stage Inference has broad utility, enabling the prediction of progression in a much wider set of individuals, rather than being restricted to those with complete data.
Collapse
Affiliation(s)
- Mar Estarellas
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- School of Biological and Behavioural Sciences, Queen Mary University of London, London, UK
| | - Neil P Oxtoby
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
| | - Alexandra L Young
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, UK
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| |
Collapse
|
2
|
Wuestefeld A, Binette AP, van Westen D, Strandberg O, Stomrud E, Mattsson-Carlgren N, Janelidze S, Smith R, Palmqvist S, Baumeister H, Berron D, Yushkevich PA, Hansson O, Spotorno N, Wisse LEM. Medial temporal lobe atrophy patterns in early- versus late-onset amnestic Alzheimer's disease. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.21.594976. [PMID: 38826333 PMCID: PMC11142072 DOI: 10.1101/2024.05.21.594976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Background The medial temporal lobe (MTL) is hypothesized to be relatively spared in early-onset Alzheimer's disease (EOAD). Yet, detailed examination of MTL subfield volumes and drivers of atrophy in amnestic EOAD is lacking. Methods BioFINDER-2 participants with memory impairment, abnormal amyloid-β status and tau-PET were included. Forty-one EOAD individuals aged ≤65 years and, as comparison, late-onset AD (LOAD, ≥70 years, n=154) and Aβ-negative cognitively unimpaired controls were included. MTL subregions and biomarkers of (co-)pathologies were measured. Results AD groups showed smaller MTL subregions compared to controls. Atrophy patterns were similar across AD groups, although LOAD showed thinner entorhinal cortices compared to EOAD. EOAD showed lower WMH compared to LOAD. No differences in MTL tau-PET or transactive response DNA binding protein 43-proxy positivity was found. Conclusions We found in vivo evidence for MTL atrophy in amnestic EOAD and overall similar levels to LOAD of MTL tau pathology and co-pathologies.
Collapse
Affiliation(s)
- Anika Wuestefeld
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
| | - Alexa Pichet Binette
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
| | - Danielle van Westen
- Department of Diagnostic Radiology, Clinical Sciences, Lund University, 22242 Lund, Sweden
- Image and Function, Skåne University Hospital, 22242 Lund Sweden
| | - Olof Strandberg
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
| | - Erik Stomrud
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
- Memory Clinic, Skåne University Hospital, 20502 Malmö, Sweden
| | - Niklas Mattsson-Carlgren
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
- Department of Neurology, Skåne University Hospital, 22242 Lund, Sweden
- Wallenberg Center for Molecular Medicine, Lund University, 22184 Lund, Sweden
| | - Shorena Janelidze
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
| | - Ruben Smith
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
- Memory Clinic, Skåne University Hospital, 20502 Malmö, Sweden
| | - Sebastian Palmqvist
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
- Memory Clinic, Skåne University Hospital, 20502 Malmö, Sweden
| | - Hannah Baumeister
- German Center for Neurodegenerative Diseases (DZNE), 39120 Magdeburg, Germany
| | - David Berron
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
- German Center for Neurodegenerative Diseases (DZNE), 39120 Magdeburg, Germany
| | - Paul A. Yushkevich
- Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, Philadelphia 19104, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
- Memory Clinic, Skåne University Hospital, 20502 Malmö, Sweden
| | - Nicola Spotorno
- Clinical Memory Research Unit, Department of Clinical Sciences Malmö, Lund University, 22242 Lund, Sweden
| | - Laura EM Wisse
- Department of Diagnostic Radiology, Clinical Sciences, Lund University, 22242 Lund, Sweden
| |
Collapse
|
3
|
Dubois B, von Arnim CAF, Burnie N, Bozeat S, Cummings J. Biomarkers in Alzheimer's disease: role in early and differential diagnosis and recognition of atypical variants. Alzheimers Res Ther 2023; 15:175. [PMID: 37833762 PMCID: PMC10571241 DOI: 10.1186/s13195-023-01314-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Accepted: 09/25/2023] [Indexed: 10/15/2023]
Abstract
BACKGROUND Development of in vivo biomarkers has shifted the diagnosis of Alzheimer's disease (AD) from the later dementia stages of disease towards the earlier stages and has introduced the potential for pre-symptomatic diagnosis. The International Working Group recommends that AD diagnosis is restricted in the clinical setting to people with specific AD phenotypes and supportive biomarker findings. MAIN BODY In this review, we discuss the phenotypic presentation and use of biomarkers for the early diagnosis of typical and atypical AD and describe how this can support clinical decision making, benefit patient communication, and improve the patient journey. Early diagnosis is essential to optimize the benefits of available and emerging treatments. As atypical presentations of AD often mimic other dementias, differential diagnosis can be challenging and can be facilitated using AD biomarkers. However, AD biomarkers alone are not sufficient to confidently diagnose AD or predict disease progression and should be supplementary to clinical assessment to help inform the diagnosis of AD. CONCLUSIONS Use of AD biomarkers with incorporation of atypical AD phenotypes into diagnostic criteria will allow earlier diagnosis of patients with atypical clinical presentations that otherwise would have been misdiagnosed and treated inappropriately. Early diagnosis is essential to guide informed discussion, appropriate care and support, and individualized treatment. It is hoped that disease-modifying treatments will impact the underlying AD pathology; thus, determining the patient's AD phenotype will be a critical factor in guiding the therapeutic approach and the assessment of the effects of interventions.
Collapse
Affiliation(s)
- Bruno Dubois
- Assistance Publique-Hôpitaux de Paris (AP-HP), Memory and Alzheimer's Disease Institute, Sorbonne University, Paris, France
- Brain Institute, Sorbonne University, Paris, France
| | | | - Nerida Burnie
- General Practice, South West London CCG, London, UK
- London Dementia Clinical Network, London, UK
| | | | - Jeffrey Cummings
- Chambers-Grundy Center for Transformative Neuroscience, Pam Quirk Brain Health and Biomarker Laboratory, Department of Brain Health, School of Integrated Health Sciences, University of Nevada Las Vegas, Las Vegas, NV, USA
| |
Collapse
|
4
|
Yong KXX, Graff-Radford J, Ahmed S, Chapleau M, Ossenkoppele R, Putcha D, Rabinovici GD, Suarez-Gonzalez A, Schott JM, Crutch S, Harding E. Diagnosis and Management of Posterior Cortical Atrophy. Curr Treat Options Neurol 2023; 25:23-43. [PMID: 36820004 PMCID: PMC9935654 DOI: 10.1007/s11940-022-00745-0] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 12/08/2022] [Indexed: 02/10/2023]
Abstract
Purpose of review The study aims to provide a summary of recent developments for diagnosing and managing posterior cortical atrophy (PCA). We present current efforts to improve PCA characterisation and recommendations regarding use of clinical, neuropsychological and biomarker methods in PCA diagnosis and management and highlight current knowledge gaps. Recent findings Recent multi-centre consensus recommendations provide PCA criteria with implications for different management strategies (e.g. targeting clinical features and/or disease). Studies emphasise the preponderance of primary or co-existing Alzheimer's disease (AD) pathology underpinning PCA. Evidence of approaches to manage PCA symptoms is largely derived from small studies. Summary PCA diagnosis is frequently delayed, and people are likely to receive misdiagnoses of ocular or psychological conditions. Current treatment of PCA is symptomatic - pharmacological and non-pharmacological - and the use of most treatment options is based on small studies or expert opinion. Recommendations for non-pharmacological approaches include interdisciplinary management tailored to the PCA clinical profile - visual-spatial - rather than memory-led, predominantly young onset - and psychosocial implications. Whilst emerging disease-modifying treatments have not been tested in PCA, an accurate and timely diagnosis of PCA and determining underlying pathology is of increasing importance in the advent of disease-modifying therapies for AD and other albeit rare causes of PCA.
Collapse
Affiliation(s)
- Keir X. X. Yong
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | | | - Samrah Ahmed
- Nuffield Department of Clinical Neuroscience, University of Oxford, Oxford, UK
- School of Psychology and Clinical Language Sciences, University of Reading, Reading, Berkshire UK
| | - Marianne Chapleau
- Memory and Aging Center, University of California San Francisco, San Francisco, CA USA
| | - Rik Ossenkoppele
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, Netherlands
- Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Deepti Putcha
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA USA
| | - Gil D. Rabinovici
- Department of Neurology, Radiology, and Biomedical Imaging, University of California San Francisco, San Francisco, CA USA
| | - Aida Suarez-Gonzalez
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | - Jonathan M. Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | - Sebastian Crutch
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| | - Emma Harding
- Dementia Research Centre, UCL Queen Square Institute of Neurology, Box 16, Queen Square, London, WC1N 3BG UK
| |
Collapse
|
5
|
Panikkar D, Vivek S, Crimmins E, Faul J, Langa KM, Thyagarajan B. Pre-Analytical Variables Influencing Stability of Blood-Based Biomarkers of Neuropathology. J Alzheimers Dis 2023; 95:735-748. [PMID: 37574735 DOI: 10.3233/jad-230384] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
BACKGROUND Sample collection and preanalytical protocols may significantly impact the results of large-scale epidemiological studies incorporating blood-based biomarkers of neuropathology. OBJECTIVE To evaluate the stability and assay variability of several blood-based biomarkers of neuropathology for common preanalytical conditions. METHODS We collected serum and plasma samples from 41 participants and evaluated the effect of processing delay of up to 72 h when stored at 4∘C, three freeze-thaw cycles, and a combination of 48-h processing delay when stored at 4∘C and three freeze-thaw cycles on biomarker stability. Using the Simoa assay (Quanterix Inc.), we measured amyloid-β 40 (Aβ40), amyloid-β 42 (Aβ42), neurofilament light (NfL), glial fibrillary acidic protein (GFAP), and phosphorylated tau 181 (p-tau-181). RESULTS We found that Aβ40 and Aβ42 levels significantly decreased after a 24-h processing delay in both plasma and serum samples, and a single freeze-thaw cycle (p < 0.0001). Nevertheless, serum Aβ42/40 ratio remained stable with a processing delay up to 48 h while plasma Aβ42/40 ratio showed only small but significant increase with a delay up to 72 h. Both plasma and serum GFAP and NfL levels were only modestly affected by processing delay and freeze-thaw cycles. Plasma p-tau-181 levels notably increased with a 24-, 48-, and 72-h processing delay, but remained stable in serum. Intra-individual variation over two weeks was minimal for all biomarkers and their levels were substantially lower in serum when compared with plasma. CONCLUSION These results suggest that standardizing preanalytical variables will allow robust measurements of biomarkers of neuropathology in population studies.
Collapse
Affiliation(s)
- Daniel Panikkar
- Department of Neuroscience, University of Minnesota, Minneapolis, MN, USA
| | - Sithara Vivek
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Eileen Crimmins
- Davis School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - Jessica Faul
- Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI, USA
| | - Kenneth M Langa
- Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI, USA
- Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Veterans Affairs Ann Arbor Center for Clinical Management Research, Ann Arbor, MI, USA
| | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| |
Collapse
|
6
|
Recognizing Atypical Presentations of Alzheimer's Disease: The Importance of CSF Biomarkers in Clinical Practice. Diagnostics (Basel) 2022; 12:diagnostics12123011. [PMID: 36553018 PMCID: PMC9776656 DOI: 10.3390/diagnostics12123011] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Revised: 11/24/2022] [Accepted: 11/25/2022] [Indexed: 12/05/2022] Open
Abstract
Besides the typical amnestic presentation, neuropathological studies indicate that Alzheimer's disease (AD) may present with atypical clinical pictures. The relative frequencies of typical and atypical or mixed presentations within the entire spectrum of AD remain unclear, while some mixed or atypical presentations may have not received adequate attention for them to be included in diagnostic criteria. We investigated the spectrum of clinical presentations in patients with the AD CSF biomarker profile (high tau and phospho-tau, low Aβ42 levels), hospitalized in a tertiary academic center. Among 98 patients with the CSF AD profile, 46% of patients had the typical presentation of "hippocampal" amnestic dementia. Additionally, 23.5% and 15.3% fulfilled the criteria of mixed or atypical presentations, respectively, as described in the IWG-2 criteria. The remaining 15.3% had unusual presentations, including non-logopenic (semantic and non-fluent agrammatic) primary progressive aphasia, corticobasal syndrome, and Richardson syndrome, or could be diagnosed with normal pressure hydrocephalus. Despite selection bias (academic center), atypical clinical presentations of AD may be more common than previously thought. CSF biomarkers seem to be a useful tool for antemortem identification of such patients, which is likely to affect therapeutic decisions. Some of the unusual presentations described above should be incorporated in diagnostic criteria.
Collapse
|
7
|
Sirkis DW, Bonham LW, Johnson TP, La Joie R, Yokoyama JS. Dissecting the clinical heterogeneity of early-onset Alzheimer's disease. Mol Psychiatry 2022; 27:2674-2688. [PMID: 35393555 PMCID: PMC9156414 DOI: 10.1038/s41380-022-01531-9] [Citation(s) in RCA: 43] [Impact Index Per Article: 21.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Revised: 03/07/2022] [Accepted: 03/16/2022] [Indexed: 12/14/2022]
Abstract
Early-onset Alzheimer's disease (EOAD) is a rare but particularly devastating form of AD. Though notable for its high degree of clinical heterogeneity, EOAD is defined by the same neuropathological hallmarks underlying the more common, late-onset form of AD. In this review, we describe the various clinical syndromes associated with EOAD, including the typical amnestic phenotype as well as atypical variants affecting visuospatial, language, executive, behavioral, and motor functions. We go on to highlight advances in fluid biomarker research and describe how molecular, structural, and functional neuroimaging can be used not only to improve EOAD diagnostic acumen but also enhance our understanding of fundamental pathobiological changes occurring years (and even decades) before the onset of symptoms. In addition, we discuss genetic variation underlying EOAD, including pathogenic variants responsible for the well-known mendelian forms of EOAD as well as variants that may increase risk for the much more common forms of EOAD that are either considered to be sporadic or lack a clear autosomal-dominant inheritance pattern. Intriguingly, specific pathogenic variants in PRNP and MAPT-genes which are more commonly associated with other neurodegenerative diseases-may provide unexpectedly important insights into the formation of AD tau pathology. Genetic analysis of the atypical clinical syndromes associated with EOAD will continue to be challenging given their rarity, but integration of fluid biomarker data, multimodal imaging, and various 'omics techniques and their application to the study of large, multicenter cohorts will enable future discoveries of fundamental mechanisms underlying the development of EOAD and its varied clinical presentations.
Collapse
Affiliation(s)
- Daniel W Sirkis
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Luke W Bonham
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Taylor P Johnson
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Renaud La Joie
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA
| | - Jennifer S Yokoyama
- Memory and Aging Center, Department of Neurology, Weill Institute for Neurosciences, University of California, San Francisco, San Francisco, CA, 94158, USA.
- Department of Radiology and Biomedical Imaging, University of California, San Francisco, San Francisco, CA, 94158, USA.
| |
Collapse
|
8
|
Tsantzali I, Boufidou F, Sideri E, Mavromatos A, Papaioannou MG, Foska A, Tollos I, Paraskevas SG, Bonakis A, Voumvourakis KI, Tsivgoulis G, Kapaki E, Paraskevas GP. From Cerebrospinal Fluid Neurochemistry to Clinical Diagnosis of Alzheimer's Disease in the Era of Anti-Amyloid Treatments. Report of Four Patients. Biomedicines 2021; 9:biomedicines9101376. [PMID: 34680493 PMCID: PMC8533180 DOI: 10.3390/biomedicines9101376] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/31/2021] [Revised: 09/26/2021] [Accepted: 09/30/2021] [Indexed: 12/26/2022] Open
Abstract
Analysis of classical cerebrospinal fluid biomarkers, especially when incorporated in a classification/diagnostic system such as the AT(N), may offer a significant diagnostic tool allowing correct identification of Alzheimer’s disease during life. We describe four patients with more or less atypical or mixed clinical presentation, in which the classical cerebrospinal fluid biomarkers amyloid peptide with 42 and 40 amino acids (Aβ42 and Aβ40, respectively), phospho-tau (τP-181) and total tau (τΤ) were measured. Despite the unusual clinical presentation, the biomarker profile was compatible with Alzheimer’s disease in all four patients. The measurement of classical biomarkers in the cerebrospinal fluid may be a useful tool in identifying the biochemical fingerprints of Alzheimer’s disease, especially currently, due to the recent approval of the first disease-modifying treatment, allowing not only typical but also atypical cases to be enrolled in trials of such treatments.
Collapse
Affiliation(s)
- Ioanna Tsantzali
- 2nd Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, “Attikon” General University Hospital, 12462 Athens, Greece; (I.T.); (E.S.); (A.M.); (A.F.); (I.T.); (A.B.); (K.I.V.); (G.T.)
| | - Fotini Boufidou
- Neurochemistry and Biological Markers Unit, 1st Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, “Eginition” Hospital, 11528 Athens, Greece; (F.B.); (M.G.P.); (S.G.P.); (E.K.)
| | - Eleni Sideri
- 2nd Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, “Attikon” General University Hospital, 12462 Athens, Greece; (I.T.); (E.S.); (A.M.); (A.F.); (I.T.); (A.B.); (K.I.V.); (G.T.)
| | - Antonis Mavromatos
- 2nd Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, “Attikon” General University Hospital, 12462 Athens, Greece; (I.T.); (E.S.); (A.M.); (A.F.); (I.T.); (A.B.); (K.I.V.); (G.T.)
| | - Myrto G. Papaioannou
- Neurochemistry and Biological Markers Unit, 1st Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, “Eginition” Hospital, 11528 Athens, Greece; (F.B.); (M.G.P.); (S.G.P.); (E.K.)
| | - Aikaterini Foska
- 2nd Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, “Attikon” General University Hospital, 12462 Athens, Greece; (I.T.); (E.S.); (A.M.); (A.F.); (I.T.); (A.B.); (K.I.V.); (G.T.)
| | - Ioannis Tollos
- 2nd Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, “Attikon” General University Hospital, 12462 Athens, Greece; (I.T.); (E.S.); (A.M.); (A.F.); (I.T.); (A.B.); (K.I.V.); (G.T.)
| | - Sotirios G. Paraskevas
- Neurochemistry and Biological Markers Unit, 1st Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, “Eginition” Hospital, 11528 Athens, Greece; (F.B.); (M.G.P.); (S.G.P.); (E.K.)
| | - Anastasios Bonakis
- 2nd Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, “Attikon” General University Hospital, 12462 Athens, Greece; (I.T.); (E.S.); (A.M.); (A.F.); (I.T.); (A.B.); (K.I.V.); (G.T.)
| | - Konstantinos I. Voumvourakis
- 2nd Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, “Attikon” General University Hospital, 12462 Athens, Greece; (I.T.); (E.S.); (A.M.); (A.F.); (I.T.); (A.B.); (K.I.V.); (G.T.)
| | - Georgios Tsivgoulis
- 2nd Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, “Attikon” General University Hospital, 12462 Athens, Greece; (I.T.); (E.S.); (A.M.); (A.F.); (I.T.); (A.B.); (K.I.V.); (G.T.)
| | - Elisabeth Kapaki
- Neurochemistry and Biological Markers Unit, 1st Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, “Eginition” Hospital, 11528 Athens, Greece; (F.B.); (M.G.P.); (S.G.P.); (E.K.)
| | - George P. Paraskevas
- 2nd Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, “Attikon” General University Hospital, 12462 Athens, Greece; (I.T.); (E.S.); (A.M.); (A.F.); (I.T.); (A.B.); (K.I.V.); (G.T.)
- Neurochemistry and Biological Markers Unit, 1st Department of Neurology, School of Medicine, National and Kapodistrian University of Athens, “Eginition” Hospital, 11528 Athens, Greece; (F.B.); (M.G.P.); (S.G.P.); (E.K.)
- Correspondence: ; Tel.: +30-2105832466
| |
Collapse
|
9
|
Contador J, Pérez-Millán A, Tort-Merino A, Balasa M, Falgàs N, Olives J, Castellví M, Borrego-Écija S, Bosch B, Fernández-Villullas G, Ramos-Campoy O, Antonell A, Bargalló N, Sanchez-Valle R, Sala-Llonch R, Lladó A. Longitudinal brain atrophy and CSF biomarkers in early-onset Alzheimer's disease. NEUROIMAGE-CLINICAL 2021; 32:102804. [PMID: 34474317 PMCID: PMC8405839 DOI: 10.1016/j.nicl.2021.102804] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/19/2021] [Revised: 08/17/2021] [Accepted: 08/20/2021] [Indexed: 01/09/2023]
Abstract
There is evidence of longitudinal atrophy in posterior brain areas in early-onset Alzheimer's disease (EOAD; aged < 65 years), but no studies have been conducted in an EOAD cohort with fluid biomarkers characterization. We used 3T-MRI and Freesurfer 6.0 to investigate cortical and subcortical gray matter loss at two years in 12 EOAD patients (A + T + N + ) compared to 19 controls (A-T-N-) from the Hospital Clínic Barcelona cohort. We explored group differences in atrophy patterns and we correlated atrophy and baseline CSF-biomarkers levels in EOAD. We replicated the correlation analyses in 14 EOAD (A + T + N + ) and 55 late-onset AD (LOAD; aged ≥ 75 years; A + T + N + ) participants from the Alzheimer's disease Neuroimaging Initiative. We found that EOAD longitudinal atrophy spread with a posterior-to-anterior gradient and beyond hippocampus/amygdala. In EOAD, higher initial CSF NfL levels correlated with higher ventricular volumes at baseline. On the other hand, higher initial CSF Aβ42 levels (within pathological range) predicted higher rates of cortical loss in EOAD. In EOAD and LOAD subjects, higher CSF t-tau values at baseline predicted higher rates of subcortical atrophy. CSF p-tau did not show any significant correlation. In conclusion, posterior cortices, hippocampus and amygdala capture EOAD atrophy from early stages. CSF Aβ42 might predict cortical thinning and t-tau/NfL subcortical atrophy.
Collapse
Affiliation(s)
- José Contador
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain
| | - Agnès Pérez-Millán
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain
| | - Adrià Tort-Merino
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain
| | - Mircea Balasa
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain; Atlantic Fellow for Equity in Brain Health, Global Brain Heath Institute
| | - Neus Falgàs
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain; Atlantic Fellow for Equity in Brain Health, Global Brain Heath Institute; Department of Neurology, Memory & Aging Center, Weill Institute for Neurosciences, University of California, 675 Nelson Rising Lane, Suite 190, San Francisco, CA 94158, USA
| | - Jaume Olives
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain
| | - Magdalena Castellví
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain
| | - Sergi Borrego-Écija
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain
| | - Beatriz Bosch
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain
| | - Guadalupe Fernández-Villullas
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain
| | - Oscar Ramos-Campoy
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain
| | - Anna Antonell
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain
| | - Nuria Bargalló
- Image Diagnostic Centre, IDIBAPS, Hospital Clínic de Barcelona, Barcelona, Spain
| | - Raquel Sanchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas. CIBERNED, Spain
| | - Roser Sala-Llonch
- Institute of Neurosciences. Department of Biomedicine, Faculty of Medicine, University of Barcelona, Barcelona, 08036, Spain; Biomedical Imaging Group, Biomedical Research Networking Center in Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Barcelona, Spain
| | - Albert Lladó
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic of Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona 08036, Spain; Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas. CIBERNED, Spain.
| |
Collapse
|
10
|
Shea YF, Pan Y, Mak HKF, Bao Y, Lee SC, Chiu PKC, Chan HWF. A systematic review of atypical Alzheimer's disease including behavioural and psychological symptoms. Psychogeriatrics 2021; 21:396-406. [PMID: 33594793 DOI: 10.1111/psyg.12665] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 01/06/2021] [Accepted: 01/25/2021] [Indexed: 12/20/2022]
Abstract
Alzheimer's disease (AD) is the commonest cause of dementia, characterized by the clinical presentation of progressive anterograde episodic memory impairment. However, atypical presentation of patients is increasingly recognized. These atypical AD include logopenic aphasia, behavioural variant AD, posterior cortical atrophy, and corticobasal syndrome. These atypical AD are more common in patients with young onset AD before the age of 65 years old. Since medical needs (including the behavioural and psychological symptoms of dementia) of atypical AD patients could be different from typical AD patients, it is important for clinicians to be aware of these atypical forms of AD. In addition, disease modifying treatment may be available in the future. This review aims at providing an update on various important subtypes of atypical AD including behavioural and psychological symptoms.
Collapse
Affiliation(s)
- Yat-Fung Shea
- Department of Medicine, LKS Faculty of Medicine, University of Hong Kong, Queen Mary Hospital, Pok Fu Lam, Hong Kong
| | - Yining Pan
- School of Biomedical Sciences, LKS Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Henry Ka-Fung Mak
- Department of Diagnostic Radiology, LKS Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Yiwen Bao
- Department of Diagnostic Radiology, LKS Faculty of Medicine, The University of Hong Kong, Pok Fu Lam, Hong Kong
| | - Shui-Ching Lee
- Department of Medicine, LKS Faculty of Medicine, University of Hong Kong, Queen Mary Hospital, Pok Fu Lam, Hong Kong
| | - Patrick Ka-Chun Chiu
- Department of Medicine, LKS Faculty of Medicine, University of Hong Kong, Queen Mary Hospital, Pok Fu Lam, Hong Kong
| | - Hon-Wai Felix Chan
- Department of Medicine, LKS Faculty of Medicine, University of Hong Kong, Queen Mary Hospital, Pok Fu Lam, Hong Kong
| |
Collapse
|
11
|
Ikeda M, Kodaira S, Kasahara H, Takai E, Nagashima K, Fujita Y, Makioka K, Hirayanagi K, Furuta N, Furuta M, Sanada E, Kobayashi A, Harigaya Y, Nagamine S, Hattori N, Tashiro Y, Kishi K, Shimada H, Suto T, Tanaka H, Sakai Y, Yamazaki T, Tanaka Y, Aihara Y, Amari M, Yamaguchi H, Okamoto K, Takatama M, Ishii K, Higuchi T, Tsushima Y, Ikeda Y. Cerebral Microbleeds, Cerebrospinal Fluid, and Neuroimaging Markers in Clinical Subtypes of Alzheimer's Disease. Front Neurol 2021; 12:543866. [PMID: 33889121 PMCID: PMC8056016 DOI: 10.3389/fneur.2021.543866] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2020] [Accepted: 02/26/2021] [Indexed: 12/12/2022] Open
Abstract
Lobar cerebral microbleeds (CMBs) in Alzheimer's disease (AD) are associated with cerebral amyloid angiopathy (CAA) due to vascular amyloid beta (Aβ) deposits. However, the relationship between lobar CMBs and clinical subtypes of AD remains unknown. Here, we enrolled patients with early- and late-onset amnestic dominant AD, logopenic variant of primary progressive aphasia (lvPPA) and posterior cortical atrophy (PCA) who were compatible with the AD criteria. We then examined the levels of cerebrospinal fluid (CSF) biomarkers [Aβ1-42, Aβ1-40, Aβ1-38, phosphorylated tau 181 (P-Tau), total tau (T-Tau), neurofilament light chain (NFL), and chitinase 3-like 1 protein (YKL-40)], analyzed the number and localization of CMBs, and measured the cerebral blood flow (CBF) volume by 99mTc-ethyl cysteinate dimer single photon emission computerized tomography (99mTc ECD-SPECT), as well as the mean cortical standard uptake value ratio by 11C-labeled Pittsburgh Compound B-positron emission tomography (11C PiB-PET). Lobar CMBs in lvPPA were distributed in the temporal, frontal, and parietal lobes with the left side predominance, while the CBF volume in lvPPA significantly decreased in the left temporal area, where the number of lobar CMBs and the CBF volumes showed a significant inversely correlation. The CSF levels of NFL in lvPPA were significantly higher compared to the other AD subtypes and non-demented subjects. The numbers of lobar CMBs significantly increased the CSF levels of NFL in the total AD patients, additionally, among AD subtypes, the CSF levels of NFL in lvPPA predominantly were higher by increasing number of lobar CMBs. On the other hand, the CSF levels of Aβ1-38, Aβ1-40, Aβ1-42, P-Tau, and T-Tau were lower by increasing number of lobar CMBs in the total AD patients. These findings may suggest that aberrant brain hypoperfusion in lvPPA was derived from the brain atrophy due to neurodegeneration, and possibly may involve the aberrant microcirculation causing by lobar CMBs and cerebrovascular injuries, with the left side dominance, consequently leading to a clinical phenotype of logopenic variant.
Collapse
Affiliation(s)
- Masaki Ikeda
- Department of Neurology, Gunma University Graduate School of Medicine, Maebashi, Japan.,Department of Neurology, Geriatrics Research Institute and Hospital, Maebashi, Japan.,Division of Common Education (Neurology), Faculty of Health and Medical Care, Saitama Medical University, Hidaka, Japan
| | - Sayaka Kodaira
- Department of Diagnostic Radiology and Nuclear Medicine, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Hiroo Kasahara
- Department of Neurology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Eriko Takai
- Department of Neurology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Kazuaki Nagashima
- Department of Neurology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Yukio Fujita
- Department of Neurology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Kouki Makioka
- Department of Neurology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Kimitoshi Hirayanagi
- Department of Neurology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Natsumi Furuta
- Department of Neurology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Minori Furuta
- Department of Neurology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Etsuko Sanada
- Department of Neurology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Ayumi Kobayashi
- Department of Neurology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Yasuo Harigaya
- Department of Neurology, Maebashi Red Cross Hospital, Maebashi, Japan
| | - Shun Nagamine
- Department of Neurology, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Noriaki Hattori
- Department of Neuropsychiatry, Jomo Hospital, Maebashi, Japan
| | - Yuichi Tashiro
- Department of Neurology, Mito Medical Center, Mito, Japan
| | - Kazuhiro Kishi
- Department of Radiology, Gunma University Hospital, Maebashi, Japan
| | - Hirotaka Shimada
- Department of Radiology, Gunma University Hospital, Maebashi, Japan
| | - Takayuki Suto
- Department of Radiology, Gunma University Hospital, Maebashi, Japan
| | - Hisashi Tanaka
- Department of Neuropsychiatry, Tanaka Hospital, Yoshioka, Japan
| | - Yasujiro Sakai
- Department of Neurology, Geriatrics Research Institute and Hospital, Maebashi, Japan
| | - Tsuneo Yamazaki
- Department of Occupational Therapy, Gunma University Graduate School of Health Sciences, Maebashi, Japan
| | - Yukiko Tanaka
- Department of Geriatric Medicine, Uchida Hospital, Numata, Japan
| | - Yuko Aihara
- Department of Neurology, Shinozuka Hospital, Fujioka, Japan
| | - Masakuni Amari
- Department of Neurology, Geriatrics Research Institute and Hospital, Maebashi, Japan
| | - Haruyasu Yamaguchi
- Department of Neurology, Geriatrics Research Institute and Hospital, Maebashi, Japan.,Tokyo Center for Dementia Research and Practices, Tokyo, Japan
| | - Koichi Okamoto
- Department of Neurology, Geriatrics Research Institute and Hospital, Maebashi, Japan
| | - Masamitsu Takatama
- Department of Neurology, Geriatrics Research Institute and Hospital, Maebashi, Japan
| | - Kenji Ishii
- Team for Neuroimaging, Tokyo Metropolitan Institute of Gerontology, Tokyo, Japan
| | - Tetsuya Higuchi
- Department of Diagnostic Radiology and Nuclear Medicine, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Yoshito Tsushima
- Department of Diagnostic Radiology and Nuclear Medicine, Gunma University Graduate School of Medicine, Maebashi, Japan
| | - Yoshio Ikeda
- Department of Neurology, Gunma University Graduate School of Medicine, Maebashi, Japan
| |
Collapse
|
12
|
Groot C, Grothe MJ, Mukherjee S, Jelistratova I, Jansen I, van Loenhoud AC, Risacher SL, Saykin AJ, Mac Donald CL, Mez J, Trittschuh EH, Gryglewski G, Lanzenberger R, Pijnenburg YAL, Barkhof F, Scheltens P, van der Flier WM, Crane PK, Ossenkoppele R. Differential patterns of gray matter volumes and associated gene expression profiles in cognitively-defined Alzheimer's disease subgroups. Neuroimage Clin 2021; 30:102660. [PMID: 33895633 PMCID: PMC8186562 DOI: 10.1016/j.nicl.2021.102660] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Revised: 02/25/2021] [Accepted: 03/30/2021] [Indexed: 01/04/2023]
Abstract
The clinical presentation of Alzheimer's disease (AD) varies widely across individuals but the neurobiological mechanisms underlying this heterogeneity are largely unknown. Here, we compared regional gray matter (GM) volumes and associated gene expression profiles between cognitively-defined subgroups of amyloid-β positive individuals clinically diagnosed with AD dementia (age: 66 ± 7, 47% male, MMSE: 21 ± 5). All participants underwent neuropsychological assessment with tests covering memory, executive-functioning, language and visuospatial-functioning domains. Subgroup classification was achieved using a psychometric framework that assesses which cognitive domain shows substantial relative impairment compared to the intra-individual average across domains, which yielded the following subgroups in our sample; AD-Memory (n = 41), AD-Executive (n = 117), AD-Language (n = 33), AD-Visuospatial (n = 171). We performed voxel-wise contrasts of GM volumes derived from 3Tesla structural MRI between subgroups and controls (n = 127, age 58 ± 9, 42% male, MMSE 29 ± 1), and observed that differences in regional GM volumes compared to controls closely matched the respective cognitive profiles. Specifically, we detected lower medial temporal lobe GM volumes in AD-Memory, lower fronto-parietal GM volumes in AD-Executive, asymmetric GM volumes in the temporal lobe (left < right) in AD-Language, and lower GM volumes in posterior areas in AD-Visuospatial. In order to examine possible biological drivers of these differences in regional GM volumes, we correlated subgroup-specific regional GM volumes to brain-wide gene expression profiles based on a stereotactic characterization of the transcriptional architecture of the human brain as provided by the Allen human brain atlas. Gene-set enrichment analyses revealed that variations in regional expression of genes involved in processes like mitochondrial respiration and metabolism of proteins were associated with patterns of regional GM volume across multiple subgroups. Other gene expression vs GM volume-associations were only detected in particular subgroups, e.g., genes involved in the cell cycle for AD-Memory, specific sets of genes related to protein metabolism in AD-Language, and genes associated with modification of gene expression in AD-Visuospatial. We conclude that cognitively-defined AD subgroups show neurobiological differences, and distinct biological pathways may be involved in the emergence of these differences.
Collapse
Affiliation(s)
- Colin Groot
- Department of Neurology & Alzheimer Center, Amsterdam University Medical Center - Location VU University Medical Center, Amsterdam, The Netherlands.
| | - Michel J Grothe
- Unidad de Trastornos del Movimiento, Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla, Hospital Universitario Virgen del Rocío/CSIC/Universidad de Sevilla, Seville, Spain; German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany.
| | | | | | - Iris Jansen
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, VU University, Amsterdam, The Netherlands.
| | - Anna Catharina van Loenhoud
- Department of Neurology & Alzheimer Center, Amsterdam University Medical Center - Location VU University Medical Center, Amsterdam, The Netherlands.
| | | | - Andrew J Saykin
- Indiana University School of Medicine, Indianapolis, IN, USA.
| | | | - Jesse Mez
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA; Alzheimer's Disease Center, Boston University School of Medicine, MA, USA.
| | - Emily H Trittschuh
- Psychiatry & Behavioral Science, University of Washington, Seattle, WA, USA; Veterans Affairs Puget Sound Health Care System, Geriatric Research, Education, & Clinical Center, Seattle, WA, USA.
| | - Gregor Gryglewski
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
| | - Rupert Lanzenberger
- Department of Psychiatry and Psychotherapy, Medical University of Vienna, Vienna, Austria.
| | - Yolande A L Pijnenburg
- Department of Neurology & Alzheimer Center, Amsterdam University Medical Center - Location VU University Medical Center, Amsterdam, The Netherlands.
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center - Location VU University Medical Center, Amsterdam, The Netherlands; University College London, Institutes of Neurology & Healthcare Engineering, London, United Kingdom.
| | - Philip Scheltens
- Department of Neurology & Alzheimer Center, Amsterdam University Medical Center - Location VU University Medical Center, Amsterdam, The Netherlands.
| | - Wiesje M van der Flier
- Department of Neurology & Alzheimer Center, Amsterdam University Medical Center - Location VU University Medical Center, Amsterdam, The Netherlands; Epidemiology and Biostatistics, Amsterdam University Medical Center - Location VU University Medical Center, Amsterdam, The Netherlands.
| | - Paul K Crane
- Department of Medicine, University of Washington, Seattle, WA, USA.
| | - Rik Ossenkoppele
- Department of Neurology & Alzheimer Center, Amsterdam University Medical Center - Location VU University Medical Center, Amsterdam, The Netherlands; Lund University, Clinical Memory Research Unit, Lund, Sweden.
| |
Collapse
|
13
|
Stefanovski L, Meier JM, Pai RK, Triebkorn P, Lett T, Martin L, Bülau K, Hofmann-Apitius M, Solodkin A, McIntosh AR, Ritter P. Bridging Scales in Alzheimer's Disease: Biological Framework for Brain Simulation With The Virtual Brain. Front Neuroinform 2021; 15:630172. [PMID: 33867964 PMCID: PMC8047422 DOI: 10.3389/fninf.2021.630172] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 03/08/2021] [Indexed: 12/18/2022] Open
Abstract
Despite the acceleration of knowledge and data accumulation in neuroscience over the last years, the highly prevalent neurodegenerative disease of AD remains a growing problem. Alzheimer's Disease (AD) is the most common cause of dementia and represents the most prevalent neurodegenerative disease. For AD, disease-modifying treatments are presently lacking, and the understanding of disease mechanisms continues to be incomplete. In the present review, we discuss candidate contributing factors leading to AD, and evaluate novel computational brain simulation methods to further disentangle their potential roles. We first present an overview of existing computational models for AD that aim to provide a mechanistic understanding of the disease. Next, we outline the potential to link molecular aspects of neurodegeneration in AD with large-scale brain network modeling using The Virtual Brain (www.thevirtualbrain.org), an open-source, multiscale, whole-brain simulation neuroinformatics platform. Finally, we discuss how this methodological approach may contribute to the understanding, improved diagnostics, and treatment optimization of AD.
Collapse
Affiliation(s)
- Leon Stefanovski
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
| | - Jil Mona Meier
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
| | - Roopa Kalsank Pai
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
| | - Paul Triebkorn
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
- Institut de Neurosciences des Systèmes, Aix Marseille Université, Marseille, France
| | - Tristram Lett
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
| | - Leon Martin
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
| | - Konstantin Bülau
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
| | - Martin Hofmann-Apitius
- Fraunhofer Institute for Algorithms and Scientific Computing SCAI, Sankt Augustin, Germany
| | - Ana Solodkin
- Behavioral and Brain Sciences, University of Texas at Dallas, Dallas, TX, United States
| | | | - Petra Ritter
- Berlin Institute of Health at Charité - Universitätsmedizin Berlin, Berlin, Germany
- Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Neurology with Experimental Neurology, Brain Simulation Section, Berlin, Germany
- Bernstein Center for Computational Neuroscience Berlin, Berlin, Germany
- Einstein Center for Neuroscience Berlin, Berlin, Germany
- Einstein Center Digital Future, Berlin, Germany
| |
Collapse
|
14
|
Graff-Radford J, Yong KXX, Apostolova LG, Bouwman FH, Carrillo M, Dickerson BC, Rabinovici GD, Schott JM, Jones DT, Murray ME. New insights into atypical Alzheimer's disease in the era of biomarkers. Lancet Neurol 2021; 20:222-234. [PMID: 33609479 PMCID: PMC8056394 DOI: 10.1016/s1474-4422(20)30440-3] [Citation(s) in RCA: 207] [Impact Index Per Article: 69.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Revised: 11/09/2020] [Accepted: 11/10/2020] [Indexed: 12/12/2022]
Abstract
Most patients with Alzheimer's disease present with amnestic problems; however, a substantial proportion, over-represented in young-onset cases, have atypical phenotypes including predominant visual, language, executive, behavioural, or motor dysfunction. In the past, these individuals often received a late diagnosis; however, availability of CSF and PET biomarkers of Alzheimer's disease pathologies and incorporation of atypical forms of Alzheimer's disease into new diagnostic criteria increasingly allows them to be more confidently diagnosed early in their illness. This early diagnosis in turn allows patients to be offered tailored information, appropriate care and support, and individualised treatment plans. These advances will provide improved access to clinical trials, which often exclude atypical phenotypes. Research into atypical Alzheimer's disease has revealed previously unrecognised neuropathological heterogeneity across the Alzheimer's disease spectrum. Neuroimaging, genetic, biomarker, and basic science studies are providing key insights into the factors that might drive selective vulnerability of differing brain networks, with potential mechanistic implications for understanding typical late-onset Alzheimer's disease.
Collapse
Affiliation(s)
| | - Keir X. X. Yong
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Liana G. Apostolova
- Department of Neurology, Indiana University School of Medicine, Indianapolis, Indiana, USA
| | - Femke H. Bouwman
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam University Medical Center
| | | | - Bradford C. Dickerson
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
| | - Gil D. Rabinovici
- Departments of Neurology, Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Jonathan M. Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - David T. Jones
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
| | | |
Collapse
|
15
|
Ruksenaite J, Volkmer A, Jiang J, Johnson JC, Marshall CR, Warren JD, Hardy CJ. Primary Progressive Aphasia: Toward a Pathophysiological Synthesis. Curr Neurol Neurosci Rep 2021; 21:7. [PMID: 33543347 PMCID: PMC7861583 DOI: 10.1007/s11910-021-01097-z] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/13/2021] [Indexed: 12/14/2022]
Abstract
PURPOSE OF REVIEW The term primary progressive aphasia (PPA) refers to a diverse group of dementias that present with prominent and early problems with speech and language. They present considerable challenges to clinicians and researchers. RECENT FINDINGS Here, we review critical issues around diagnosis of the three major PPA variants (semantic variant PPA, nonfluent/agrammatic variant PPA, logopenic variant PPA), as well as considering 'fragmentary' syndromes. We next consider issues around assessing disease stage, before discussing physiological phenotyping of proteinopathies across the PPA spectrum. We also review evidence for core central auditory impairments in PPA, outline critical challenges associated with treatment, discuss pathophysiological features of each major PPA variant, and conclude with thoughts on key challenges that remain to be addressed. New findings elucidating the pathophysiology of PPA represent a major step forward in our understanding of these diseases, with implications for diagnosis, care, management, and therapies.
Collapse
Affiliation(s)
- Justina Ruksenaite
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8 - 11 Queen Square, London, WC1N 3BG, UK
| | - Anna Volkmer
- Division of Psychology and Language Sciences, University College London, London, UK
| | - Jessica Jiang
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8 - 11 Queen Square, London, WC1N 3BG, UK
| | - Jeremy Cs Johnson
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8 - 11 Queen Square, London, WC1N 3BG, UK
| | - Charles R Marshall
- Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London, UK
| | - Jason D Warren
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8 - 11 Queen Square, London, WC1N 3BG, UK
| | - Chris Jd Hardy
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, 8 - 11 Queen Square, London, WC1N 3BG, UK.
| |
Collapse
|
16
|
Brisson M, Brodeur C, Létourneau‐Guillon L, Masellis M, Stoessl J, Tamm A, Zukotynski K, Ismail Z, Gauthier S, Rosa‐Neto P, Soucy J. CCCDTD5: Clinical role of neuroimaging and liquid biomarkers in patients with cognitive impairment. ALZHEIMER'S & DEMENTIA (NEW YORK, N. Y.) 2021; 6:e12098. [PMID: 33532543 PMCID: PMC7821956 DOI: 10.1002/trc2.12098] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/24/2020] [Accepted: 09/11/2020] [Indexed: 04/21/2023]
Abstract
Since 1989, four Canadian Consensus Conferences on the Diagnosis and Treatment of Dementia (CCCDTDs) have provided evidence-based dementia diagnostic and treatment guidelines for Canadian clinicians and researchers. We present the results from the Neuroimaging and Fluid Biomarkers Group of the 5th CCCDTD (CCCDTD5), which addressed topics chosen by the steering committee to reflect advances in the field and build on our previous guidelines. Recommendations on Imaging and Fluid Biomarker Use from this Conference cover a series of different fields. Prior structural imaging recommendations for both computerized tomography (CT) and magnetic resonance imaging (MRI) remain largely unchanged, but MRI is now more central to the evaluation than before, with suggested sequences described here. The use of visual rating scales for both atrophy and white matter anomalies is now included in our recommendations. Molecular imaging with [18F]-fluorodeoxyglucose ([18F]-FDG) Positron Emisson Tomography (PET) or [99mTc]-hexamethylpropyleneamine oxime/ethylene cysteinate dimer ([99mTc]-HMPAO/ECD) Single Photon Emission Tomography (SPECT), should now decidedly favor PET. The value of [18F]-FDG PET in the assessment of neurodegenerative conditions has been established with greater certainty since the previous conference, and it has now been recognized as a useful biomarker to establish the presence of neurodegeneration by a number of professional organizations around the world. Furthermore, the role of amyloid PET has been clarified and our recommendations follow those from other groups in multiple countries. SPECT with [123I]-ioflupane (DaTscanTM) is now included as a useful study in differentiating Alzheimer's disease (AD) from Lewy body disease. Finally, liquid biomarkers are in a rapid phase of development and, could lead to a revolution in the assessment AD and other neurodegenerative conditions at a reasonable cost. We hope these guidelines will be useful for clinicians, researchers, policy makers, and the lay public, to inform a current and evidence-based approach to the use of neuroimaging and liquid biomarkers in clinical dementia evaluation and management.
Collapse
Affiliation(s)
- Mélanie Brisson
- Centre hospitalier de l'université de QuébecQuebec CityCanada
| | | | | | | | - Jon Stoessl
- Vancouver Coastal Health, University of British‐ColumbiaVancouverCanada
| | | | | | - Zahinoor Ismail
- Department of Psychiatry, Hotchkiss Brain Institute and O'Brien Institute for Public HealthUniversity of CalgaryCalgaryCanada
| | | | - Pedro Rosa‐Neto
- McGill Center for Studies in AgingCanada
- McConnell Brain Imaging Centre, Montreal Neurological InstituteMontrealCanada
| | - Jean‐Paul Soucy
- Centre hospitalier de l'université de MontréalMontrealCanada
- McConnell Brain Imaging Centre, Montreal Neurological InstituteMontrealCanada
- PERFORM Center, Concordia UniversityMontrealCanada
| |
Collapse
|
17
|
Cousins KAQ, Irwin DJ, Wolk DA, Lee EB, Shaw LMJ, Trojanowski JQ, Da Re F, Gibbons GS, Grossman M, Phillips JS. ATN status in amnestic and non-amnestic Alzheimer's disease and frontotemporal lobar degeneration. Brain 2020; 143:2295-2311. [PMID: 32666090 DOI: 10.1093/brain/awaa165] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 02/27/2020] [Accepted: 03/27/2020] [Indexed: 12/13/2022] Open
Abstract
Under the ATN framework, CSF analytes provide evidence of the presence or absence of Alzheimer's disease pathological hallmarks: amyloid plaques (A), phosphorylated tau (T), and accompanying neurodegeneration (N). Still, differences in CSF levels across amnestic and non-amnestic variants or due to co-occurring pathologies might lead to misdiagnoses. We assess the diagnostic accuracy of CSF markers for amyloid, tau, and neurodegeneration in an autopsy cohort of 118 Alzheimer's disease patients (98 amnestic; 20 non-amnestic) and 64 frontotemporal lobar degeneration patients (five amnestic; 59 non-amnestic). We calculated between-group differences in CSF concentrations of amyloid-β1-42 peptide, tau protein phosphorylated at threonine 181, total tau, and the ratio of phosphorylated tau to amyloid-β1-42. Results show that non-amnestic Alzheimer's disease patients were less likely to be correctly classified under the ATN framework using independent, published biomarker cut-offs for positivity. Amyloid-β1-42 did not differ between amnestic and non-amnestic Alzheimer's disease, and receiver operating characteristic curve analyses indicated that amyloid-β1-42 was equally effective in discriminating both groups from frontotemporal lobar degeneration. However, CSF concentrations of phosphorylated tau, total tau, and the ratio of phosphorylated tau to amyloid-β1-42 were significantly lower in non-amnestic compared to amnestic Alzheimer's disease patients. Receiver operating characteristic curve analyses for these markers showed reduced area under the curve when discriminating non-amnestic Alzheimer's disease from frontotemporal lobar degeneration, compared to discrimination of amnestic Alzheimer's disease from frontotemporal lobar degeneration. In addition, the ATN framework was relatively insensitive to frontotemporal lobar degeneration, and these patients were likely to be classified as having normal biomarkers or biomarkers suggestive of primary Alzheimer's disease pathology. We conclude that amyloid-β1-42 maintains high sensitivity to A status, although with lower specificity, and this single biomarker provides better sensitivity to non-amnestic Alzheimer's disease than either the ATN framework or the phosphorylated-tau/amyloid-β1-42 ratio. In contrast, T and N status biomarkers differed between amnestic and non-amnestic Alzheimer's disease; standard cut-offs for phosphorylated tau and total tau may thus result in misclassifications for non-amnestic Alzheimer's disease patients. Consideration of clinical syndrome may help improve the accuracy of ATN designations for identifying true non-amnestic Alzheimer's disease.
Collapse
Affiliation(s)
| | - David J Irwin
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, USA
| | - Leslie M J Shaw
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, USA
| | - Fulvio Da Re
- School of Medicine and Surgery, Milan Center for Neuroscience, University of Milano-Bicocca, Milan, Italy
| | - Garrett S Gibbons
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, USA
| | - Murray Grossman
- Department of Neurology, University of Pennsylvania, Philadelphia, USA
| | | |
Collapse
|
18
|
Charil A, Shcherbinin S, Southekal S, Devous MD, Mintun M, Murray ME, Miller BB, Schwarz AJ. Tau Subtypes of Alzheimer's Disease Determined in vivo Using Flortaucipir PET Imaging. J Alzheimers Dis 2020; 71:1037-1048. [PMID: 31476153 DOI: 10.3233/jad-190264] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
At autopsy, individuals with Alzheimer's disease (AD) exhibit heterogeneity in the distribution of neurofibrillary tangles in neocortical and hippocampal regions. Subtypes of AD, defined using an algorithm based on the relative number of tangle counts in these regions, have been proposed-hippocampal sparing (relative sparing of the hippocampus but high cortical load), limbic predominant (high hippocampal load but lower load in association cortices), and typical (balanced neurofibrillary tangles counts in the hippocampus and association cortices) AD-and shown to be associated with distinct antemortem clinical phenotypes. The ability to distinguish these AD subtypes from the more typical tau signature in vivo could have important implications for clinical research. Flortaucipir positron emission tomography (PET) images acquired from 45 amyloid-positive participants, defined clinically as mild cognitive impairment or AD, aged 50-92 years, 56% female, and estimated to be Braak V-VI based on their PET pattern of tau pathology, were studied. By translating the neuropathologic algorithm to flortaucipir PET scans, patterns of tau pathology consistent with autopsy findings, and with a similar prevalence, were identified in vivo. 6/45 (13%) participants were identified as hippocampal sparing and 6/45 (13%) as limbic predominant AD subtypes. Hippocampal sparing participants were significantly younger than those assigned to the other two subtypes. Worse performance on delayed recall was associated with increased hippocampal tau signal, and worse performance on the trail making test B-A was associated with lower values of the hippocampus to cortex ratio. Prospective studies can further validate the flortaucipir SUVR cut-points and the phenotype of the corresponding AD subtypes.
Collapse
Affiliation(s)
| | | | | | | | - Mark Mintun
- Eli Lilly and Company, Indianapolis, IN, USA.,Avid Radiopharmaceuticals, Philadelphia, PA, USA
| | | | | | - Adam J Schwarz
- Eli Lilly and Company, Indianapolis, IN, USA.,Department of Psychological and Brain Sciences, Indiana University, Bloomington, IN, USA.,Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, USA
| |
Collapse
|
19
|
Pillai JA, Bonner-Jackson A, Bekris LM, Safar J, Bena J, Leverenz JB. Highly Elevated Cerebrospinal Fluid Total Tau Level Reflects Higher Likelihood of Non-Amnestic Subtype of Alzheimer's Disease. J Alzheimers Dis 2020; 70:1051-1058. [PMID: 31306137 DOI: 10.3233/jad-190519] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
BACKGROUND Cerebrospinal fluid (CSF) levels of total tau (t-tau) protein are thought to reflect the intensity of the neuronal damage in neurodegeneration, including Alzheimer's disease (AD). The recent link of CSF t-tau to rapidly progressive AD raises the question among other AD clinical variants regarding CSF t-tau. We investigated the clinical phenotypes of AD patients with varying CSF t-tau levels. OBJECTIVE We tested the hypothesis that highly elevated CSF t-tau level would have a higher likelihood of presenting with atypical non-amnestic variants of AD. METHODS Retrospective comparative case study of 97 patients evaluated in a memory clinic with clinical presentation and CSF biomarkers consistent with AD. We compared the age, sex, education, APOEɛ4 status, Montreal Cognitive Assessment (MoCA) score, clinical phenotype, and MRI volumetric measures by CSF t-tau quartile at baseline. Multivariable logistic regression models were used to evaluate if CSF t-tau levels predict non-amnestic presentations controlling for covariates. RESULTS Non-amnestic AD had a higher median CSF t-tau level compared to amnestic-AD (p = 0.014). Each 50 pg/ml increase in CSF t-tau was associated with an increase in the odds of having a non-amnestic presentation (7.4%) and aphasia (10.6 %) as the initial presenting symptom even after taking into account; age, sex, education, APOEɛ4, MoCA, and CSF Aβ42. Logopenic AD had higher t-tau and p-tau levels compared to other variants. CONCLUSIONS Highly elevated CSF t-tau levels could indicate more cortical involvement presenting with early non-amnestic symptoms in atypical AD subtypes, particularly in the logopenic variant.
Collapse
Affiliation(s)
- Jagan A Pillai
- Lou Ruvo Center for Brain Health, Cleveland Clinic, Cleveland, OH, USA.,Department of Neurology, Cleveland Clinic, Cleveland, OH, USA
| | | | - Lynn M Bekris
- Department of Genomic Medicine Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Jiri Safar
- Department of Pathology, Cleveland, OH, USA.,Department of University Hospitals Cleveland Medical Center, Cleveland, OH, USA
| | - Jim Bena
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA
| | - James B Leverenz
- Lou Ruvo Center for Brain Health, Cleveland Clinic, Cleveland, OH, USA.,Department of Neurology, Cleveland Clinic, Cleveland, OH, USA
| |
Collapse
|
20
|
Deng Y, Zhang J, Sun X, Ma G, Luo G, Miao Z, Song L. miR-132 improves the cognitive function of rats with Alzheimer's disease by inhibiting the MAPK1 signal pathway. Exp Ther Med 2020; 20:159. [PMID: 33093897 PMCID: PMC7571341 DOI: 10.3892/etm.2020.9288] [Citation(s) in RCA: 43] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 05/28/2020] [Indexed: 12/11/2022] Open
Abstract
Alzheimer's disease (AD) is a common worldwide progressive neurodegenerative disease. The dysregulation of miRNA is crucial in neurodegenerative diseases and neuron apoptosis during AD and is closely associated with the MAPK pathway. By bioinformatic website, we found that there was target inhibiting relationship between microRNA (miR)-132 and MAPK1. Therefore, the current study speculated that miR-132 could improve the cognitive function of rats with AD by inhibiting MAPK1 expression. To verify our hypothesis, 10 normal rats and 60 rats with AD were selected and divided into model, Ad-miR-132 negative control (NC), Ad-miR-132, Ad-small interfering (si)MAPK1 NC, Ad-siMAPK1 and Ad-miR-132 + Ad-MAPK1 groups. Rats were evaluated for learning by performing morris water maze tests and pathological changes of the hippocampus were assessed via HE staining. Additionally, hippocampus cell apoptosis was determined using a TUNEL assay and levels of acetylcholinesterase (AChE), reactive oxygen species (ROS), malondialdehyde (MDA), superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) were evaluated in sera via ELISA. The mRNA and protein expression of miR-132, iNOS, MAPK1 and phosphorylated (p)-MAPK1 was determined in hippocampus tissues via reverse transcription-quantitative PCR and western blotting, respectively. Compared with normal mice, rats with AD had significantly decreased learning abilities, increased cell apoptosis rates, increased levels of AChE, iNOS, ROS, MDA, MAPK1 and p-MAPK1 and decreased levels of SOD, GSH-Px and miR-132. Upregulation of miR-132 group improved the above indictors and silencing MAKP1 worsened the condition of rats. miR-132 upregulation therefore reversed the negative effects caused by MAPK1 silencing in rats with AD. In conclusion, miR-132 inhibited hippocampal iNOS expression and oxidative stress by inhibiting MAPK1expression to improve the cognitive function of rats with AD.
Collapse
Affiliation(s)
- Yiming Deng
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, P.R. China.,China National Clinical Research Center for Neurological Diseases, Beijing 100070, P.R. China
| | - Jingyu Zhang
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, P.R. China.,China National Clinical Research Center for Neurological Diseases, Beijing 100070, P.R. China
| | - Xuan Sun
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, P.R. China.,China National Clinical Research Center for Neurological Diseases, Beijing 100070, P.R. China
| | - Gaoting Ma
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, P.R. China.,China National Clinical Research Center for Neurological Diseases, Beijing 100070, P.R. China
| | - Gang Luo
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, P.R. China.,China National Clinical Research Center for Neurological Diseases, Beijing 100070, P.R. China
| | - Zhongrong Miao
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, P.R. China.,China National Clinical Research Center for Neurological Diseases, Beijing 100070, P.R. China
| | - Ligang Song
- Department of Interventional Neuroradiology, Beijing Tiantan Hospital, Capital Medical University, Beijing 100070, P.R. China.,China National Clinical Research Center for Neurological Diseases, Beijing 100070, P.R. China
| |
Collapse
|
21
|
Falgàs N, Ruiz‐Peris M, Pérez‐Millan A, Sala‐Llonch R, Antonell A, Balasa M, Borrego‐Écija S, Ramos‐Campoy O, Augé JM, Castellví M, Tort‐Merino A, Olives J, Fernández‐Villullas G, Blennow K, Zetterberg H, Bargalló N, Lladó A, Sánchez‐Valle R. Contribution of CSF biomarkers to early-onset Alzheimer's disease and frontotemporal dementia neuroimaging signatures. Hum Brain Mapp 2020; 41:2004-2013. [PMID: 31944489 PMCID: PMC7267898 DOI: 10.1002/hbm.24925] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2019] [Revised: 12/11/2019] [Accepted: 01/04/2020] [Indexed: 12/19/2022] Open
Abstract
Prior studies have described distinct patterns of brain gray matter and white matter alterations in Alzheimer's disease (AD) and frontotemporal lobar degeneration (FTLD), as well as differences in their cerebrospinal fluid (CSF) biomarkers profiles. We aim to investigate the relationship between early-onset AD (EOAD) and FTLD structural alterations and CSF biomarker levels. We included 138 subjects (64 EOAD, 26 FTLD, and 48 controls), all of them with a 3T MRI brain scan and CSF biomarkers available (the 42 amino acid-long form of the amyloid-beta protein [Aβ42], total-tau protein [T-tau], neurofilament light chain [NfL], neurogranin [Ng], and 14-3-3 levels). We used FreeSurfer and FSL to obtain cortical thickness (CTh) and fraction anisotropy (FA) maps. We studied group differences in CTh and FA and described the "AD signature" and "FTLD signature." We tested multiple regression models to find which CSF-biomarkers better explained each disease neuroimaging signature. CTh and FA maps corresponding to the AD and FTLD signatures were in accordance with previous literature. Multiple regression analyses showed that the biomarkers that better explained CTh values within the AD signature were Aβ and 14-3-3; whereas NfL and 14-3-3 levels explained CTh values within the FTLD signature. Similarly, NfL levels explained FA values in the FTLD signature. Ng levels were not predictive in any of the models. Biochemical markers contribute differently to structural (CTh and FA) changes typical of AD and FTLD.
Collapse
Affiliation(s)
- Neus Falgàs
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hospital ClínicInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Fundació Clínic per a la Recerca Biomèdica, University of BarcelonaBarcelonaSpain
- Atlantic Fellow for Equity in Brain HealthGlobal Brain Health Institute, University of CaliforniaSan FranciscoCalifornia
| | - Mariona Ruiz‐Peris
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hospital ClínicInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Fundació Clínic per a la Recerca Biomèdica, University of BarcelonaBarcelonaSpain
- Department of BiomedicineUniversity of BarcelonaBarcelonaSpain
| | - Agnès Pérez‐Millan
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hospital ClínicInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Fundació Clínic per a la Recerca Biomèdica, University of BarcelonaBarcelonaSpain
- Department of BiomedicineUniversity of BarcelonaBarcelonaSpain
| | | | - Anna Antonell
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hospital ClínicInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Fundació Clínic per a la Recerca Biomèdica, University of BarcelonaBarcelonaSpain
| | - Mircea Balasa
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hospital ClínicInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Fundació Clínic per a la Recerca Biomèdica, University of BarcelonaBarcelonaSpain
- Senior Atlantic Fellow for Equity inBrain Health, Global Brain Health InstituteTrinity College DublinIreland
| | - Sergi Borrego‐Écija
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hospital ClínicInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Fundació Clínic per a la Recerca Biomèdica, University of BarcelonaBarcelonaSpain
| | - Oscar Ramos‐Campoy
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hospital ClínicInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Fundació Clínic per a la Recerca Biomèdica, University of BarcelonaBarcelonaSpain
| | - Josep Maria Augé
- Biochemistry and Molecular Genetics Department, Hospital Clínic de BarcelonaBarcelonaSpain
| | - Magdalena Castellví
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hospital ClínicInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Fundació Clínic per a la Recerca Biomèdica, University of BarcelonaBarcelonaSpain
| | - Adrià Tort‐Merino
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hospital ClínicInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Fundació Clínic per a la Recerca Biomèdica, University of BarcelonaBarcelonaSpain
| | - Jaume Olives
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hospital ClínicInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Fundació Clínic per a la Recerca Biomèdica, University of BarcelonaBarcelonaSpain
| | - Guadalupe Fernández‐Villullas
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hospital ClínicInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Fundació Clínic per a la Recerca Biomèdica, University of BarcelonaBarcelonaSpain
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute ofNeuroscience and Physiology, The Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute ofNeuroscience and Physiology, The Sahlgrenska Academy at the University of GothenburgMölndalSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Department of Neurodegenerative DiseaseUniversity College LondonLondonUK
- UK Dementia Research Institute at UCLLondonUK
| | - Núria Bargalló
- Radiology Service, Hospital ClínicMRI imaging platform. Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS)
| | - Albert Lladó
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hospital ClínicInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Fundació Clínic per a la Recerca Biomèdica, University of BarcelonaBarcelonaSpain
| | - Raquel Sánchez‐Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit, Hospital ClínicInstitut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Fundació Clínic per a la Recerca Biomèdica, University of BarcelonaBarcelonaSpain
| |
Collapse
|
22
|
Abstract
PURPOSE OF REVIEW Early-onset Alzheimer disease (AD) is defined as having an age of onset younger than 65 years. While early-onset AD is often overshadowed by the more common late-onset AD, recognition of the differences between early- and late-onset AD is important for clinicians. RECENT FINDINGS Early-onset AD comprises about 5% to 6% of cases of AD and includes a substantial percentage of phenotypic variants that differ from the usual amnestic presentation of typical AD. Characteristics of early-onset AD in comparison to late-onset AD include a larger genetic predisposition (familial mutations and summed polygenic risk), more aggressive course, more frequent delay in diagnosis, higher prevalence of traumatic brain injury, less memory impairment and greater involvement of other cognitive domains on presentation, and greater psychosocial difficulties. Neuroimaging features of early-onset AD in comparison to late-onset AD include greater frequency of hippocampal sparing and posterior neocortical atrophy, increased tau burden, and greater connectomic changes affecting frontoparietal networks rather than the default mode network. SUMMARY Early-onset AD differs substantially from late-onset AD, with different phenotypic presentations, greater genetic predisposition, and differences in neuropathologic burden and topography. Early-onset AD more often presents with nonamnestic phenotypic variants that spare the hippocampi and with greater tau burden in posterior neocortices. The early-onset AD phenotypic variants involve different neural networks than typical AD. The management of early-onset AD is similar to that of late-onset AD but with special emphasis on targeting specific cognitive areas and more age-appropriate psychosocial support and education.
Collapse
|
23
|
Illán-Gala I, Pegueroles J, Montal V, Alcolea D, Vilaplana E, Bejanin A, Borrego-Écija S, Sampedro F, Subirana A, Sánchez-Saudinós MB, Rojas-García R, Vanderstichele H, Blesa R, Clarimón J, Antonell A, Lladó A, Sánchez-Valle R, Fortea J, Lleó A. APP-derived peptides reflect neurodegeneration in frontotemporal dementia. Ann Clin Transl Neurol 2019; 6:2518-2530. [PMID: 31789459 PMCID: PMC6917306 DOI: 10.1002/acn3.50948] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2019] [Accepted: 10/25/2019] [Indexed: 12/12/2022] Open
Abstract
Objective We aimed to investigate the relationship between cerebrospinal fluid levels (CSF) of amyloid precursor protein (APP)‐derived peptides related to the amyloidogenic pathway, cortical thickness, neuropsychological performance, and cortical gene expression profiles in frontotemporal lobar degeneration (FTLD)‐related syndromes, Alzheimer’s disease (AD), and healthy controls. Methods We included 214 participants with CSF available recruited at two centers: 93 with FTLD‐related syndromes, 57 patients with AD, and 64 healthy controls. CSF levels of amyloid β (Aβ)1‐42, Aβ1‐40, Aβ1‐38, and soluble β fragment of APP (sAPPβ) were centrally analyzed. We compared CSF levels of APP‐derived peptides between groups and, we studied the correlation between CSF biomarkers, cortical thickness, and domain‐specific cognitive composites in each group. Then, we explored the relationship between cortical thickness, CSF levels of APP‐derived peptides, and regional gene expression profile using a brain‐wide regional gene expression data in combination with gene set enrichment analysis. Results The CSF levels of Aβ1‐40, Aβ1‐38, and sAPPβ were lower in the FTLD‐related syndromes group than in the AD and healthy controls group. CSF levels of all APP‐derived peptides showed a positive correlation with cortical thickness and the executive cognitive composite in the FTLD‐related syndromes group but not in the healthy control or AD groups. In the cortical regions where we observed a significant association between cortical thickness and CSF levels of APP‐derived peptides, we found a reduced expression of genes related to synaptic function. Interpretation APP‐derived peptides in CSF may reflect FTLD‐related neurodegeneration. This observation has important implications as Aβ1‐42 levels are considered an indirect biomarker of cerebral amyloidosis.
Collapse
Affiliation(s)
- Ignacio Illán-Gala
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Jordi Pegueroles
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Victor Montal
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Daniel Alcolea
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Eduard Vilaplana
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Alexandre Bejanin
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Sergi Borrego-Écija
- Alzheimer's Disease and Other Cognitive Disorders, Neurology Department, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d'Investigacions Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
| | - Frederic Sampedro
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain
| | - Andrea Subirana
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - María-Belén Sánchez-Saudinós
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Ricard Rojas-García
- Neuromuscular Diseases Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain
| | | | - Rafael Blesa
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Jordi Clarimón
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| | - Anna Antonell
- Alzheimer's Disease and Other Cognitive Disorders, Neurology Department, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d'Investigacions Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
| | - Albert Lladó
- Alzheimer's Disease and Other Cognitive Disorders, Neurology Department, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d'Investigacions Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
| | - Raquel Sánchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders, Neurology Department, Hospital Clínic, Fundació Clínic per a la Recerca Biomèdica, Institut d'Investigacions Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
| | - Juan Fortea
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain.,Barcelona Down Medical Center, Fundació Catalana de Síndrome de Down, Barcelona, Spain
| | - Alberto Lleó
- Memory Unit, Department of Neurology, Hospital de la Santa Creu i Sant Pau, Biomedical Research Institute Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas, CIBERNED, Madrid, Spain
| |
Collapse
|
24
|
Alzheimer's disease clinical variants show distinct regional patterns of neurofibrillary tangle accumulation. Acta Neuropathol 2019; 138:597-612. [PMID: 31250152 DOI: 10.1007/s00401-019-02036-6] [Citation(s) in RCA: 64] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2019] [Revised: 06/16/2019] [Accepted: 06/16/2019] [Indexed: 10/26/2022]
Abstract
The clinical spectrum of Alzheimer's disease (AD) extends well beyond the classic amnestic-predominant syndrome. The previous studies have suggested differential neurofibrillary tangle (NFT) burden between amnestic and logopenic primary progressive aphasia presentations of AD. In this study, we explored the regional distribution of NFT pathology and its relationship to AD presentation across five different clinical syndromes. We assessed NFT density throughout six selected neocortical and hippocampal regions using thioflavin-S fluorescent microscopy in a well-characterized clinicopathological cohort of pure AD cases enriched for atypical clinical presentations. Subjects underwent apolipoprotein E genotyping and neuropsychological testing. Main cognitive domains (executive, visuospatial, language, and memory function) were assessed using an established composite z score. Our results showed that NFT regional burden aligns with the clinical presentation and region-specific cognitive scores. Cortical, but not hippocampal, NFT burden was higher among atypical clinical variants relative to the amnestic syndrome. In analyses of specific clinical variants, logopenic primary progressive aphasia showed higher NFT density in the superior temporal gyrus (p = 0.0091), and corticobasal syndrome showed higher NFT density in the primary motor cortex (p = 0.0205) relative to the amnestic syndrome. Higher NFT burden in the angular gyrus and CA1 sector of the hippocampus were independently associated with worsening visuospatial dysfunction. In addition, unbiased hierarchical clustering based on regional NFT densities identified three groups characterized by a low overall NFT burden, high overall burden, and cortical-predominant burden, respectively, which were found to differ in sex ratio, age, disease duration, and clinical presentation. In comparison, the typical, hippocampal sparing, and limbic-predominant subtypes derived from a previously proposed algorithm did not reproduce the same degree of clinical relevance in this sample. Overall, our results suggest domain-specific functional consequences of regional NFT accumulation. Mapping these consequences presents an opportunity to increase understanding of the neuropathological framework underlying atypical clinical manifestations.
Collapse
|
25
|
Scheltens NME, Tijms BM, Heymans MW, Rabinovici GD, Cohn-Sheehy BI, Miller BL, Kramer JH, Wolfsgruber S, Wagner M, Kornhuber J, Peters O, Scheltens P, van der Flier WM. Prominent Non-Memory Deficits in Alzheimer's Disease Are Associated with Faster Disease Progression. J Alzheimers Dis 2019; 65:1029-1039. [PMID: 30103316 DOI: 10.3233/jad-171088] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023]
Abstract
BACKGROUND Alzheimer's disease (AD) is a heterogeneous disorder. OBJECTIVE To investigate whether cognitive AD subtypes are associated with different rates of disease progression. METHODS We included 1,066 probable AD patients from the Amsterdam Dementia Cohort (n = 290), Alzheimer's Disease Neuroimaging Initiative (n = 268), Dementia Competence Network (n = 226), and University of California, San Francisco (n = 282) with available follow-up data. Patients were previously clustered into two subtypes based on their neuropsychological test results: one with most prominent memory impairment (n = 663) and one with most prominent non-memory impairment (n = 403). We examined associations between cognitive subtype and disease progression, as measured with repeated Mini-Mental State Examination (MMSE) and Clinical Dementia Rating scale sum of boxes (CDR sob), using linear mixed models. Furthermore, we investigated mortality risk associated with subtypes using Cox proportional hazard analyses. RESULTS Patients were 71±9 years old; 541 (51%) were female. At baseline, pooled non-memory patients had worse MMSE scores (23.1±0.1) and slightly worse CDR sob (4.4±0.1) than memory patients (MMSE 24.0±0.1; p < 0.001; CDR sob 4.1±0.1; p < 0.001). During follow-up, pooled non-memory patients showed steeper annual decline in MMSE (-2.8±0.1) and steeper annual increase in CDR sob (1.8±0.1) than memory patients (MMSE - 1.9±0.1; pinteraction<0.001; CDR sob 1.3±0.1; pinteraction<0.001). Furthermore, the non-memory subtype was associated with an increased risk of mortality compared with the memory subtype at trend level (HR = 1.36, CI = 1.00-1.85, p = 0.05). CONCLUSIONS AD patients with most prominently non-memory impairment show faster disease progression and higher risk of mortality than patients with most prominently memory impairment.
Collapse
Affiliation(s)
- Nienke M E Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, 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
| | - Martijn W Heymans
- Department of Epidemiology and Biostatistics, Amsterdam Neuroscience, Amsterdam UMC, Amsterdam, The Netherlands
| | - Gil D Rabinovici
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Brendan I Cohn-Sheehy
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Joel H Kramer
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Steffen Wolfsgruber
- Department of Psychiatry, University of Bonn, Bonn, Germany, and German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Michael Wagner
- Department of Psychiatry, University of Bonn, Bonn, Germany, and German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Johannes Kornhuber
- Department of Psychiatry, Friedrich-Alexander-University Erlangen, Erlangen, Germany
| | - Oliver Peters
- Department of Psychiatry, Charité Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | | |
Collapse
|
26
|
Firth NC, Primativo S, Marinescu RV, Shakespeare TJ, Suarez-Gonzalez A, Lehmann M, Carton A, Ocal D, Pavisic I, Paterson RW, Slattery CF, Foulkes AJM, Ridha BH, Gil-Néciga E, Oxtoby NP, Young AL, Modat M, Cardoso MJ, Ourselin S, Ryan NS, Miller BL, Rabinovici GD, Warrington EK, Rossor MN, Fox NC, Warren JD, Alexander DC, Schott JM, Yong KXX, Crutch SJ. Longitudinal neuroanatomical and cognitive progression of posterior cortical atrophy. Brain 2019; 142:2082-2095. [PMID: 31219516 PMCID: PMC6598737 DOI: 10.1093/brain/awz136] [Citation(s) in RCA: 49] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2018] [Revised: 02/28/2019] [Accepted: 03/24/2019] [Indexed: 01/27/2023] Open
Abstract
Posterior cortical atrophy is a clinico-radiological syndrome characterized by progressive decline in visual processing and atrophy of posterior brain regions. With the majority of cases attributable to Alzheimer's disease and recent evidence for genetic risk factors specifically related to posterior cortical atrophy, the syndrome can provide important insights into selective vulnerability and phenotypic diversity. The present study describes the first major longitudinal investigation of posterior cortical atrophy disease progression. Three hundred and sixty-one individuals (117 posterior cortical atrophy, 106 typical Alzheimer's disease, 138 controls) fulfilling consensus criteria for posterior cortical atrophy-pure and typical Alzheimer's disease were recruited from three centres in the UK, Spain and USA. Participants underwent up to six annual assessments involving MRI scans and neuropsychological testing. We constructed longitudinal trajectories of regional brain volumes within posterior cortical atrophy and typical Alzheimer's disease using differential equation models. We compared and contrasted the order in which regional brain volumes become abnormal within posterior cortical atrophy and typical Alzheimer's disease using event-based models. We also examined trajectories of cognitive decline and the order in which different cognitive tests show abnormality using the same models. Temporally aligned trajectories for eight regions of interest revealed distinct (P < 0.002) patterns of progression in posterior cortical atrophy and typical Alzheimer's disease. Patients with posterior cortical atrophy showed early occipital and parietal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion leading to tissue loss of comparable extent later. Hippocampal, entorhinal and frontal regions underwent a lower rate of change and never approached the extent of posterior cortical involvement. Patients with typical Alzheimer's disease showed early hippocampal atrophy, with subsequent higher rates of temporal atrophy and ventricular expansion. Cognitive models showed tests sensitive to visuospatial dysfunction declined earlier in posterior cortical atrophy than typical Alzheimer's disease whilst tests sensitive to working memory impairment declined earlier in typical Alzheimer's disease than posterior cortical atrophy. These findings indicate that posterior cortical atrophy and typical Alzheimer's disease have distinct sites of onset and different profiles of spatial and temporal progression. The ordering of disease events both motivates investigation of biological factors underpinning phenotypic heterogeneity, and informs the selection of measures for clinical trials in posterior cortical atrophy.
Collapse
Affiliation(s)
- Nicholas C Firth
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
- Centre for Medical Image Computing, Department of Computer Science, University College London, Gower Street, London, UK
| | - Silvia Primativo
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
- Department of Human Science, LUMSA University, Via della Traspontina, 21, Rome, Italy
| | - Razvan-Valentin Marinescu
- Centre for Medical Image Computing, Department of Computer Science, University College London, Gower Street, London, UK
| | - Timothy J Shakespeare
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Aida Suarez-Gonzalez
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
- Department of Neurology, University Hospital Virgen del Rocio, Seville, Spain
| | - Manja Lehmann
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
- Memory and Aging Center, University of California San Francisco, San Francisco, California, USA
| | - Amelia Carton
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Dilek Ocal
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Ivanna Pavisic
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Ross W Paterson
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Catherine F Slattery
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Alexander J M Foulkes
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Basil H Ridha
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Eulogio Gil-Néciga
- Department of Neurology, University Hospital Virgen del Rocio, Seville, Spain
| | - Neil P Oxtoby
- Centre for Medical Image Computing, Department of Computer Science, University College London, Gower Street, London, UK
| | - Alexandra L Young
- Centre for Medical Image Computing, Department of Computer Science, University College London, Gower Street, London, UK
| | - Marc Modat
- School of Biomedical Engineering and Imaging Sciences, King's College London, UK
| | - M Jorge Cardoso
- School of Biomedical Engineering and Imaging Sciences, King's College London, UK
| | - Sebastien Ourselin
- School of Biomedical Engineering and Imaging Sciences, King's College London, UK
| | - Natalie S Ryan
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Bruce L Miller
- Memory and Aging Center, University of California San Francisco, San Francisco, California, USA
| | - Gil D Rabinovici
- Memory and Aging Center, University of California San Francisco, San Francisco, California, USA
| | - Elizabeth K Warrington
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Martin N Rossor
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Nick C Fox
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Jason D Warren
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Daniel C Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London, Gower Street, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Keir X X Yong
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| | - Sebastian J Crutch
- Dementia Research Centre, Institute of Neurology, University College London, 8–11 Queen Square, London, UK
| |
Collapse
|
27
|
Herrera-Espejo S, Santos-Zorrozua B, Álvarez-González P, Lopez-Lopez E, Garcia-Orad Á. A Systematic Review of MicroRNA Expression as Biomarker of Late-Onset Alzheimer's Disease. Mol Neurobiol 2019; 56:8376-8391. [PMID: 31240600 DOI: 10.1007/s12035-019-01676-9] [Citation(s) in RCA: 54] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 06/09/2019] [Indexed: 12/11/2022]
Abstract
Late-onset Alzheimer's disease (LOAD) is a high-occurrence neurological disorder but the difficulty in identifying precise and early biomarkers has complicated the understanding of the disease and the development of new treatments. In this sense, important knowledge is emerging regarding novel molecular and biological candidates with diagnostic potential, including microRNAs (miRNAs), which have a key role in gene repression. The aim of this systematic review was to define the role of miRNAs' expression as biomarkers for LOAD both in brain tissues, which could help understand the biology of the disease, and circulating tissues, which could serve as non-invasive markers of the pathology. A systematic search was performed in Web of Science and PubMed using the keywords ((Alzheimer or Alzheimer's) and (microRNA or microRNAs or miRNA or miRNAs or miR)) until August 2018 to retrieve all articles that presented independent original data evaluating the impact of miRNA expression on the development of LOAD in human population. A total of 90 studies investigating the role of miRNAs' expression in the development of LOAD were identified. While other widely studied miRNAs such as hsa-miR-146a presented contradictory results among studies, deregulation in brain tissue of seven miRNAs, hsa-miR-16-5p, hsa-miR-34a-5p, hsa-miR-107, hsa-miR-125-5p, hsa-miR-132-3p, hsa-miR-181-3p, and hsa-miR-212-3p, was consistently identified in LOAD patients. Their role in the disease could be mediated through the regulation of key pathways, such as axon guidance, longevity, insulin, and MAPK signaling pathway. However, regarding their role as non-invasive biomarkers of LOAD in fluids, although the limited results available are promising, further studies are required.
Collapse
Affiliation(s)
- Soraya Herrera-Espejo
- Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Medicine and Nursing, University of The Basque Country (UPV/EHU), Barrio Sarriena s/n, 48940, Leioa, Spain
| | - Borja Santos-Zorrozua
- Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Medicine and Nursing, University of The Basque Country (UPV/EHU), Barrio Sarriena s/n, 48940, Leioa, Spain
| | - Paula Álvarez-González
- Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Medicine and Nursing, University of The Basque Country (UPV/EHU), Barrio Sarriena s/n, 48940, Leioa, Spain
| | - Elixabet Lopez-Lopez
- Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Medicine and Nursing, University of The Basque Country (UPV/EHU), Barrio Sarriena s/n, 48940, Leioa, Spain.
- BioCruces Bizkaia Health Research Institute, Barakaldo, Spain.
| | - África Garcia-Orad
- Department of Genetics, Physical Anthropology and Animal Physiology, Faculty of Medicine and Nursing, University of The Basque Country (UPV/EHU), Barrio Sarriena s/n, 48940, Leioa, Spain
- BioCruces Bizkaia Health Research Institute, Barakaldo, Spain
| |
Collapse
|
28
|
Cummings J. The National Institute on Aging-Alzheimer's Association Framework on Alzheimer's disease: Application to clinical trials. Alzheimers Dement 2019; 15:172-178. [PMID: 29936146 PMCID: PMC6417790 DOI: 10.1016/j.jalz.2018.05.006] [Citation(s) in RCA: 81] [Impact Index Per Article: 16.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2018] [Revised: 04/27/2018] [Accepted: 05/03/2018] [Indexed: 02/01/2023]
Abstract
INTRODUCTION The National Institute on Aging-Alzheimer's Association Research Framework on Alzheimer's disease (AD) represents an important advance in the biological characterization of the AD spectrum. METHODS The National Institute on Aging-Alzheimer's Association Framework is considered as it applies to clinical trials. RESULTS Using the combination of amyloid (A), tau (T), and neurodegeneration (N) biomarkers, the Framework provides a means of defining the state of patients with regard to Alzheimer pathologic change. The Framework is relevant to clinical trials of disease-modifying agents, allowing participants to be characterized biologically at baseline. The ATN Framework can also inform trial outcomes. The preclinical phase of the disease after amyloid deposition is defined by A+T-N-, and the transition to prodromal disease and dementia is characterized by the addition of T and N. Most symptomatic patients in clinical trials are in the class of A+T+N- and A+T+N+. DISCUSSION The National Institute on Aging-Alzheimer's Association Framework on AD represents progress in providing biomarker profiles of participants in the AD spectrum that can be used to help design clinical trials.
Collapse
Affiliation(s)
- Jeffrey Cummings
- Cleveland Clinic Lou Ruvo Center for Brain Health, Las Vegas, NV, USA.
| |
Collapse
|
29
|
fMRI data processing in MRTOOL: to what extent does anatomical registration affect the reliability of functional results? Brain Imaging Behav 2018; 13:1538-1553. [PMID: 30467743 DOI: 10.1007/s11682-018-9986-x] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Spatial registration is an essential step in the analysis of fMRI data because it enables between-subject analyses of brain activity, measured either during task performance or in the resting state. In this study, we investigated how anatomical registration with MRTOOL affects the reliability of task-related fMRI activity. We used as a benchmark the results from two other spatial registration methods implemented in SPM12: the Unified Segmentation algorithm and the DARTEL toolbox. Structural alignment accuracy and the impact on functional activation maps were assessed with high-resolution T1-weighted images and a set of task-related functional volumes acquired in 10 healthy volunteers. Our findings confirmed that anatomical registration is a crucial step in fMRI data processing, contributing significantly to the total inter-subject variance of the activation maps. MRTOOL and DARTEL provided greater registration accuracy than Unified Segmentation. Although DARTEL had superior gray matter and white matter tissue alignment than MRTOOL, there were no significant differences between DARTEL and MRTOOL in test-retest reliability. Likewise, we found only limited differences in BOLD activation morphology between MRTOOL and DARTEL. The test-retest reliability of task-related responses was comparable between MRTOOL and DARTEL, and both proved superior to Unified Segmentation. We conclude that MRTOOL, which is suitable for single-subject processing of structural and functional MR images, is a valid alternative to other SPM12-based approaches that are intended for group analysis. MRTOOL now includes a normalization module for fMRI data and is freely available to the scientific community.
Collapse
|
30
|
Steinacker P, Barschke P, Otto M. Biomarkers for diseases with TDP-43 pathology. Mol Cell Neurosci 2018; 97:43-59. [PMID: 30399416 DOI: 10.1016/j.mcn.2018.10.003] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Revised: 10/26/2018] [Accepted: 10/29/2018] [Indexed: 01/01/2023] Open
Abstract
The discovery that aggregated transactive response DNA-binding protein 43 kDa (TDP-43) is the major component of pathological ubiquitinated inclusions in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) caused seminal progress in the unveiling of the genetic bases and molecular characteristics of these now so-called TDP-43 proteinopathies. Substantial increase in the knowledge of clinic-pathological coherencies, especially for FTLD variants, could be made in the last decade, but also revealed a considerable complexity of TDP-43 pathology and often a poor correlation of clinical and molecular disease characteristics. To date, an underlying TDP-43 pathology can be predicted only for patients with mutations in the genes C9orf72 and GRN, but is dependent on neuropathological verification in patients without family history, which represent the majority of cases. As etiology-specific therapies for neurodegenerative proteinopathies are emerging, methods to forecast TDP-43 pathology at patients' lifetime are highly required. Here, we review the current status of research pursued to identify specific indicators to predict or exclude TDP-43 pathology in the ALS-FTLD spectrum disorders and findings on candidates for prognosis and monitoring of disease progression in TDP-43 proteinopathies with a focus on TDP-43 with its pathological forms, neurochemical and imaging biomarkers.
Collapse
Affiliation(s)
| | - Peggy Barschke
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Markus Otto
- Department of Neurology, University of Ulm, Ulm, Germany.
| |
Collapse
|
31
|
Shaw LM, Arias J, Blennow K, Galasko D, Molinuevo JL, Salloway S, Schindler S, Carrillo MC, Hendrix JA, Ross A, Illes J, Ramus C, Fifer S. Appropriate use criteria for lumbar puncture and cerebrospinal fluid testing in the diagnosis of Alzheimer's disease. Alzheimers Dement 2018; 14:1505-1521. [PMID: 30316776 PMCID: PMC10013957 DOI: 10.1016/j.jalz.2018.07.220] [Citation(s) in RCA: 147] [Impact Index Per Article: 24.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2018] [Revised: 07/17/2018] [Accepted: 07/31/2018] [Indexed: 01/08/2023]
Abstract
INTRODUCTION The Alzheimer's Association convened a multidisciplinary workgroup to develop appropriate use criteria to guide the safe and optimal use of the lumbar puncture procedure and cerebrospinal fluid (CSF) testing for Alzheimer's disease pathology detection in the diagnostic process. METHODS The workgroup, experienced in the ethical use of lumbar puncture and CSF analysis, developed key research questions to guide the systematic review of the evidence and developed clinical indications commonly encountered in clinical practice based on key patient groups in whom the use of lumbar puncture and CSF may be considered as part of the diagnostic process. Based on their expertise and interpretation of the evidence from systematic review, members rated each indication as appropriate or inappropriate. RESULTS The workgroup finalized 14 indications, rating 6 appropriate and 8 inappropriate. DISCUSSION In anticipation of the emergence of more reliable CSF analysis platforms, the manuscript offers important guidance to health-care practitioners and suggestions for implementation and future research.
Collapse
Affiliation(s)
- Leslie M Shaw
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, PA, USA
| | - Jalayne Arias
- Department of Neurology, University of California, San Francisco, CA, USA
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, University of Gothenberg, Molndal, Sweden
| | - Douglas Galasko
- Department of Neuroscience, University of California, San Diego, CA, USA
| | | | - Stephen Salloway
- Butler Hospital Memory and Aging Program, The Warren Alpert Medical School of Brown University, Brown University, Providence, RI, USA
| | | | | | | | - April Ross
- Alzheimer's Association, Chicago, IL, USA
| | | | | | | |
Collapse
|
32
|
|
33
|
Mattsson N, Groot C, Jansen WJ, Landau SM, Villemagne VL, Engelborghs S, Mintun MM, Lleo A, Molinuevo JL, Jagust WJ, Frisoni GB, Ivanoiu A, Chételat G, Resende de Oliveira C, Rodrigue KM, Kornhuber J, Wallin A, Klimkowicz-Mrowiec A, Kandimalla R, Popp J, Aalten PP, Aarsland D, Alcolea D, Almdahl IS, Baldeiras I, van Buchem MA, Cavedo E, Chen K, Cohen AD, Förster S, Fortea J, Frederiksen KS, Freund-Levi Y, Gill KD, Gkatzima O, Grimmer T, Hampel H, Herukka SK, Johannsen P, van Laere K, de Leon MJ, Maier W, Marcusson J, Meulenbroek O, Møllergård HM, Morris JC, Mroczko B, Nordlund A, Prabhakar S, Peters O, Rami L, Rodríguez-Rodríguez E, Roe CM, Rüther E, Santana I, Schröder J, Seo SW, Soininen H, Spiru L, Stomrud E, Struyfs H, Teunissen CE, Verhey FRJ, Vos SJB, van Waalwijk van Doorn LJC, Waldemar G, Wallin ÅK, Wiltfang J, Vandenberghe R, Brooks DJ, Fladby T, Rowe CC, Drzezga A, Verbeek MM, Sarazin M, Wolk DA, Fleisher AS, Klunk WE, Na DL, Sánchez-Juan P, Lee DY, Nordberg A, Tsolaki M, Camus V, Rinne JO, Fagan AM, Zetterberg H, Blennow K, Rabinovici GD, Hansson O, van Berckel BNM, van der Flier WM, Scheltens P, Visser PJ, Ossenkoppele R. Prevalence of the apolipoprotein E ε4 allele in amyloid β positive subjects across the spectrum of Alzheimer's disease. Alzheimers Dement 2018; 14:913-924. [PMID: 29601787 DOI: 10.1016/j.jalz.2018.02.009] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2017] [Revised: 12/28/2017] [Accepted: 02/07/2018] [Indexed: 12/25/2022]
Abstract
INTRODUCTION Apolipoprotein E (APOE) ε4 is the major genetic risk factor for Alzheimer's disease (AD), but its prevalence is unclear because earlier studies did not require biomarker evidence of amyloid β (Aβ) pathology. METHODS We included 3451 Aβ+ subjects (853 AD-type dementia, 1810 mild cognitive impairment, and 788 cognitively normal). Generalized estimating equation models were used to assess APOE ε4 prevalence in relation to age, sex, education, and geographical location. RESULTS The APOE ε4 prevalence was 66% in AD-type dementia, 64% in mild cognitive impairment, and 51% in cognitively normal, and it decreased with advancing age in Aβ+ cognitively normal and Aβ+ mild cognitive impairment (P < .05) but not in Aβ+ AD dementia (P = .66). The prevalence was highest in Northern Europe but did not vary by sex or education. DISCUSSION The APOE ε4 prevalence in AD was higher than that in previous studies, which did not require presence of Aβ pathology. Furthermore, our results highlight disease heterogeneity related to age and geographical location.
Collapse
Affiliation(s)
- Niklas Mattsson
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden.
| | - Colin Groot
- Department of Neurology and Alzheimer Center, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Willemijn J Jansen
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Victor L Villemagne
- Department of Nuclear Medicine and Centre for PET, Austin Health, Melbourne, Australia
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
| | | | - Alberto Lleo
- Neurology Department, Hospital de Sant Pau, Barcelona, Spain
| | - José Luis Molinuevo
- Alzheimer's Disease and Other Cognitive Disorders Unit, IDIBAPS, Clinic University Hospital, Barcelona, Spain
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California, Berkeley, CA, USA
| | - Giovanni B Frisoni
- Memory Clinic and LANVIE- Laboratory of Neuroimaging of Aging, University Hospitals, and University of Geneva, Geneva, Switzerland; Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Adrian Ivanoiu
- Memory Clinic and Neurochemistry Laboratory, Saint Luc University Hospital, Institute of Neuroscience, Université catholique de Louvain, Brussels, Belgium
| | - Gaël Chételat
- Inserm, Inserm UMR-S U1237, Université de Caen-Normandie, GIP Cyceron, Caen, France
| | - Catarina Resende de Oliveira
- Center for Neuroscience and Cell Biology, Faculty of Medicine, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Karen M Rodrigue
- Center for Vital Longevity, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, USA
| | - Johannes Kornhuber
- Department of Psychiatry and Psychotherapy, Friedrich-Alexander University of Erlangen- Nuremberg, Erlangen, Germany
| | - Anders Wallin
- Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
| | | | - Ramesh Kandimalla
- Department of Biochemistry, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Julius Popp
- Department of Psychiatry, Service of Old Age Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Pauline P Aalten
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands
| | - Dag Aarsland
- Center for Age-Related Medicine, Stavanger University Hospital, Stavanger, Norway
| | - Daniel Alcolea
- Neurology Department, Hospital de Sant Pau, Barcelona, Spain
| | - Ina S Almdahl
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Inês Baldeiras
- Center for Neuroscience and Cell Biology, Faculty of Medicine, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Mark A van Buchem
- Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands
| | - Enrica Cavedo
- Laboratory of Alzheimer's Neuroimaging and Epidemiology, IRCCS Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy; AXA Research Fund & UPMC Chair, Sorbonne Universités, Université Pierre et Marie Curie (UPMC) Paris 06, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Hôpital Pitié-Salpêtrière, Paris, France
| | - Kewei Chen
- Banner Alzheimer's Institute, Phoenix, AZ, USA
| | - Ann D Cohen
- University of Pittsburgh School of Medicine, Department of Psychiatry, Pittsburgh, PA, USA
| | - Stefan Förster
- Department of Nuclear Medicine, Technische Universitaet München, Munich, Germany
| | - Juan Fortea
- Neurology Department, Hospital de Sant Pau, Barcelona, Spain
| | - Kristian S Frederiksen
- Danish Dementia Research Center, Department of Neurology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Yvonne Freund-Levi
- Department of Geriatrics, Karolinska University Hospital Huddinge, Section of Clinical Geriatrics, Institution of NVS, Karolinska Institutet, Stockholm, Sweden
| | - Kiran Dip Gill
- Department of Biochemistry, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Olymbia Gkatzima
- Third Department of Neurology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Timo Grimmer
- Department of Psychiatry and Psychotherapy, Klinikum rechts der Isar der Technischen Universitaet München, Munich, Germany
| | - Harald Hampel
- AXA Research Fund & UPMC Chair, Sorbonne Universités, Université Pierre et Marie Curie (UPMC) Paris 06, Inserm, CNRS, Institut du Cerveau et de la Moelle Épinière (ICM), Département de Neurologie, Institut de la Mémoire et de la Maladie d'Alzheimer (IM2A), Hôpital Pitié-Salpêtrière, Paris, France; Department of Psychiatry, Alzheimer Memorial Center and Geriatric Psychiatry Branch, Ludwig-Maximilian University, Munich, Germany
| | - Sanna-Kaisa Herukka
- Department of Neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Peter Johannsen
- Memory Clinic, Danish Dementia Research Center, Rigshospitalet, Copenhagen, Denmark
| | - Koen van Laere
- Department of Imaging and Pathology, Catholic University Leuven, Leuven, Belgium
| | - Mony J de Leon
- School of Medicine, Center for Brain Health, New York University, New York, NY, USA
| | - Wolfgang Maier
- Department of Psychiatry and Psychotherapy, University of Bonn, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Jan Marcusson
- Geriatric Medicine, Department of Clinical and Experimental Medicine, University of Linköping, Linköping, Sweden
| | - Olga Meulenbroek
- Department of Geriatric Medicine, Radboud Alzheimer Center, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Hanne M Møllergård
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - John C Morris
- Knight Alzheimer's Disease Research Center, Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Barbara Mroczko
- Department of Neurodegeneration Diagnostics, Leading National Research Centre in Białystok (KNOW), Medical University of Białystok, Białystok, Poland
| | - Arto Nordlund
- Institute of Neuroscience and Physiology, Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
| | - Sudesh Prabhakar
- Department of Neurology, Postgraduate Institute of Medical Education and Research (PGIMER), Chandigarh, India
| | - Oliver Peters
- Department of Psychiatry and Psychotherapy, Charité Berlin, German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
| | - Lorena Rami
- Alzheimer's Disease and Other Cognitive Disorders Unit, IDIBAPS, Clinic University Hospital, Barcelona, Spain
| | - Eloy Rodríguez-Rodríguez
- Neurology Service, Universitary Hospital Marqués de Valdecilla, CIBERNED, IDIVAL, Santander, Spain
| | - Catherine M Roe
- Knight Alzheimer's Disease Research Center, Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Eckart Rüther
- Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August University, Göttingen, Germany
| | - Isabel Santana
- Center for Neuroscience and Cell Biology, Faculty of Medicine, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Johannes Schröder
- Sektion Gerontopsychiatrie, Universität Heidelberg, Heidelberg, Germany
| | - Sang W Seo
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Hilkka Soininen
- Department of Neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | - Luiza Spiru
- Department of Geriatrics-Gerontology-Gerontopsychiatry, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
| | - Erik Stomrud
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Hanne Struyfs
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
| | - Charlotte E Teunissen
- Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, the Netherlands
| | - Frans R J Verhey
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands
| | - Stephanie J B Vos
- Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands
| | - Linda J C van Waalwijk van Doorn
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Laboratory Medicine, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Gunhild Waldemar
- Danish Dementia Research Center, Department of Neurology, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Åsa K Wallin
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August University, Göttingen, Germany; Department of Psychiatry and Psychotherapy, University Medical Center, Georg-August University, Göttingen, Germany
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology and Alzheimer Research Centre KU Leuven, Catholic University Leuven, Leuven, Belgium
| | - David J Brooks
- Division of Neuroscience, Medical Research Council Clinical Sciences Centre, Imperial College London, London, UK
| | - Tormod Fladby
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway
| | - Christopher C Rowe
- Department of Nuclear Medicine and Centre for PET, Austin Health, Melbourne, Australia
| | - Alexander Drzezga
- Department of Nuclear Medicine, University of Cologne, Cologne, Germany
| | - Marcel M Verbeek
- Department of Neurology, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Radboud University Medical Center, Nijmegen, the Netherlands; Department of Laboratory Medicine, Donders Institute for Brain, Cognition and Behaviour, Radboud Alzheimer Center, Radboud University Medical Center, Nijmegen, the Netherlands
| | - Marie Sarazin
- Neurologie de la Mémoire et du Langage, Centre Hospitalier Sainte-Anne, Université Paris Descartes, Sorbonne Paris Cité, Paris, France
| | - David A Wolk
- Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Adam S Fleisher
- Banner Alzheimer's Institute, Phoenix, AZ, USA; Eli Lilly, Indianapolis, IN, USA; Department of Neurosciences, University of California, San Diego, CA, USA
| | - William E Klunk
- University of Pittsburgh School of Medicine, Department of Psychiatry, Pittsburgh, PA, USA
| | - Duk L Na
- Department of Neurology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea
| | - Pascual Sánchez-Juan
- Neurology Service, Universitary Hospital Marqués de Valdecilla, CIBERNED, IDIVAL, Santander, Spain
| | - Dong Young Lee
- Department of Neuropsychiatry, Seoul National University, College of Medicine, Seoul, South Korea
| | - Agneta Nordberg
- Department NVS, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet and Geriatric Medicine, Karolinska University Hospital, Stockholm, Sweden
| | - Magda Tsolaki
- Third Department of Neurology, Aristotle University of Thessaloniki, Thessaloniki, Greece
| | - Vincent Camus
- CHRU de Tours, CIC INSERM 1415, INSERM U930, Université François Rabelais de Tours, Tours, France
| | - Juha O Rinne
- Turku PET Centre and Division of Clinical Neurosciences Turku, University of Turku and Turku University Hospital, Turku, Finland
| | - Anne M Fagan
- Knight Alzheimer's Disease Research Center, Department of Neurology, Washington University School of Medicine, St Louis, MO, USA
| | - Henrik Zetterberg
- Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, UK; UK Dementia Research Institute, London, UK; Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden; Sweden and Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden; Sweden and Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Gil D Rabinovici
- Department of Neurology, Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Oskar Hansson
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden
| | - Bart N M van Berckel
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Wiesje M van der Flier
- Department of Neurology and Alzheimer Center, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands; Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, the Netherlands
| | - Philip Scheltens
- Department of Neurology and Alzheimer Center, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands
| | - Pieter Jelle Visser
- Department of Neurology and Alzheimer Center, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands; Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, the Netherlands
| | - Rik Ossenkoppele
- Clinical Memory Research Unit, Clinical Sciences Malmö, Lund University, Lund, Sweden; Department of Neurology and Alzheimer Center, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands; Department of Radiology and Nuclear Medicine, VU University Medical Center, Neuroscience Campus Amsterdam, Amsterdam, the Netherlands.
| |
Collapse
|
34
|
Malpas CB, Saling MM, Velakoulis D, Desmond P, Hicks RJ, Zetterberg H, Blennow K, O’Brien TJ. Cerebrospinal Fluid Biomarkers are Differentially Related to Structural and Functional Changes in Dementia of the Alzheimer’s Type. J Alzheimers Dis 2018; 62:417-427. [DOI: 10.3233/jad-170250] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Charles B. Malpas
- Department of Medicine, Royal Melbourne Hospital, VIC, Australia
- Melbourne School of Psychological Sciences, The University of Melbourne, VIC, Australia
- Developmental Imaging, Murdoch Children’s Research Institute, Melbourne, VIC, Australia
| | - Michael M. Saling
- Melbourne School of Psychological Sciences, The University of Melbourne, VIC, Australia
| | | | - Patricia Desmond
- Department of Radiology, University of Melbourne, VIC, Australia
| | - Rodney J. Hicks
- Department of Radiology, University of Melbourne, VIC, Australia
- Centre for Molecular Imaging, Peter MacCallum Cancer Centre, Melbourne, VIC, Australia
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Molecular Neuroscience, UCL Institute of Neurology, Queen Square, London, UK
- UK Dementia Research Institute at UCL, London, UK
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Terence J. O’Brien
- Department of Medicine, Royal Melbourne Hospital, VIC, Australia
- Departments of Neuroscience and Neurology, The Central Clinical School and The Alfred Hospital, Monash University, Melbourne, VIC, Australia
| |
Collapse
|
35
|
Wellington H, Paterson RW, Suárez‐González A, Poole T, Frost C, Sjöbom U, Slattery CF, Magdalinou NK, Lehmann M, Portelius E, Fox NC, Blennow K, Zetterberg H, Schott JM. CSF neurogranin or tau distinguish typical and atypical Alzheimer disease. Ann Clin Transl Neurol 2018; 5:162-171. [PMID: 29468177 PMCID: PMC5817822 DOI: 10.1002/acn3.518] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Revised: 11/15/2017] [Accepted: 11/24/2017] [Indexed: 12/13/2022] Open
Abstract
Objective To assess whether high levels of cerebrospinal fluid neurogranin are found in atypical as well as typical Alzheimer's disease. Methods Immunoassays were used to measure cerebrospinal fluid neurogranin in 114 participants including healthy controls (n = 27), biomarker-proven amnestic Alzheimer's disease (n = 68), and the atypical visual variant of Alzheimer's (n = 19) according to international criteria. CSF total-tau, Aβ42, and neurofilament light concentrations were investigated using commercially available assays. All affected individuals had T1-weighted volumetric MR images available for analysis of whole and regional brain volumes. Associations between neurogranin, brain volumes, total-tau, Aβ42, and neurofilament light were assessed. Results Median cerebrospinal fluid neurogranin concentrations were higher in typical and atypical Alzheimer's compared to controls (P < 0.001 and P = 0.005). Both neurogranin and total-tau concentrations, but not neurofilament light and Aβ42, were higher in typical Alzheimer's compared to atypical patients (P = 0.004 and P = 0.03). There were significant differences in the left hippocampus and right and left superior parietal lobules in atypical patients, which were larger (P = 0.03) and smaller (P = 0.001 and P < 0.001), respectively, compared to typical patients. We found no evidence of associations between neurogranin and brain volumes but a strong association with total-tau (P < 0.001) and a weaker association with neurofilament light (P = 0.005). Interpretation These results show significant differences in neurogranin and total-tau between typical and atypical patients, which may relate to factors other than disease topography. The differential relationships between neurogranin, total-tau and neurofilament light in the Alzheimer's variants, provide evidence for mechanistically distinct and coupled markers of neurodegeneration.
Collapse
Affiliation(s)
| | - Ross W. Paterson
- Dementia Research CentreInstitute of Neurology, Queen Square, UCLLondonUK
| | | | - Teresa Poole
- Dementia Research CentreInstitute of Neurology, Queen Square, UCLLondonUK
- Faculty of Epidemiology and Population HealthDepartment of Medical StatisticsLondon School of Hygiene and Tropical MedicineLondonUK
| | - Chris Frost
- Dementia Research CentreInstitute of Neurology, Queen Square, UCLLondonUK
- Faculty of Epidemiology and Population HealthDepartment of Medical StatisticsLondon School of Hygiene and Tropical MedicineLondonUK
| | - Ulrika Sjöbom
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | | | | | - Manja Lehmann
- Dementia Research CentreInstitute of Neurology, Queen Square, UCLLondonUK
| | - Eric Portelius
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Institute of Neuroscience and PhysiologyDepartment of Psychiatry and NeurochemistryThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
| | - Nick C. Fox
- Dementia Research CentreInstitute of Neurology, Queen Square, UCLLondonUK
- UK Dementia Research Institute at UCLLondonUK
| | - Kaj Blennow
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Institute of Neuroscience and PhysiologyDepartment of Psychiatry and NeurochemistryThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
| | - Henrik Zetterberg
- Department of Molecular NeuroscienceInstitute of Neurology, UCLLondonUK
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
- Institute of Neuroscience and PhysiologyDepartment of Psychiatry and NeurochemistryThe Sahlgrenska Academy at the University of GothenburgMölndalSweden
- UK Dementia Research Institute at UCLLondonUK
| | - Jonathan M. Schott
- Dementia Research CentreInstitute of Neurology, Queen Square, UCLLondonUK
| |
Collapse
|
36
|
Caminiti SP, Ballarini T, Sala A, Cerami C, Presotto L, Santangelo R, Fallanca F, Vanoli EG, Gianolli L, Iannaccone S, Magnani G, Perani D. FDG-PET and CSF biomarker accuracy in prediction of conversion to different dementias in a large multicentre MCI cohort. Neuroimage Clin 2018; 18:167-177. [PMID: 29387532 PMCID: PMC5790816 DOI: 10.1016/j.nicl.2018.01.019] [Citation(s) in RCA: 91] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Revised: 11/15/2017] [Accepted: 01/18/2018] [Indexed: 01/29/2023]
Abstract
Background/aims In this multicentre study in clinical settings, we assessed the accuracy of optimized procedures for FDG-PET brain metabolism and CSF classifications in predicting or excluding the conversion to Alzheimer's disease (AD) dementia and non-AD dementias. Methods We included 80 MCI subjects with neurological and neuropsychological assessments, FDG-PET scan and CSF measures at entry, all with clinical follow-up. FDG-PET data were analysed with a validated voxel-based SPM method. Resulting single-subject SPM maps were classified by five imaging experts according to the disease-specific patterns, as "typical-AD", "atypical-AD" (i.e. posterior cortical atrophy, asymmetric logopenic AD variant, frontal-AD variant), "non-AD" (i.e. behavioural variant FTD, corticobasal degeneration, semantic variant FTD; dementia with Lewy bodies) or "negative" patterns. To perform the statistical analyses, the individual patterns were grouped either as "AD dementia vs. non-AD dementia (all diseases)" or as "FTD vs. non-FTD (all diseases)". Aβ42, total and phosphorylated Tau CSF-levels were classified dichotomously, and using the Erlangen Score algorithm. Multivariate logistic models tested the prognostic accuracy of FDG-PET-SPM and CSF dichotomous classifications. Accuracy of Erlangen score and Erlangen Score aided by FDG-PET SPM classification was evaluated. Results The multivariate logistic model identified FDG-PET "AD" SPM classification (Expβ = 19.35, 95% C.I. 4.8-77.8, p < 0.001) and CSF Aβ42 (Expβ = 6.5, 95% C.I. 1.64-25.43, p < 0.05) as the best predictors of conversion from MCI to AD dementia. The "FTD" SPM pattern significantly predicted conversion to FTD dementias at follow-up (Expβ = 14, 95% C.I. 3.1-63, p < 0.001). Overall, FDG-PET-SPM classification was the most accurate biomarker, able to correctly differentiate either the MCI subjects who converted to AD or FTD dementias, and those who remained stable or reverted to normal cognition (Expβ = 17.9, 95% C.I. 4.55-70.46, p < 0.001). Conclusions Our results support the relevant role of FDG-PET-SPM classification in predicting progression to different dementia conditions in prodromal MCI phase, and in the exclusion of progression, outperforming CSF biomarkers.
Collapse
Key Words
- AD, Alzheimer's disease
- AUC, area under curve
- Alzheimer's disease dementia
- CBD, corticobasal degeneration
- CDR, Clinical Dementia Rating
- CSF, cerebrospinal fluid
- Clinical setting
- DLB, dementia with Lewy bodies
- EANM, European Association of Nuclear Medicine
- Erlangen Score
- FDG, fluorodeoxyglucose
- FTD, frontotemporal dementia
- Frontotemporal dementia
- LR+, positive likelihood ratio
- LR-, negative likelihood ratio
- MCI, mild cognitive impairment
- PET, positron emission tomography
- PSP, progressive supranuclear palsy
- Prognosis
- aMCI, single-domain amnestic mild cognitive impairment
- bvFTD, behavioral variant of frontotemporal dementia
- md aMCI, multi-domain amnestic mild cognitive impairment
- md naMCI, multi-domain non-amnestic mild cognitive impairment
- naMCI, single-domain non-amnestic mild cognitive impairment
- p-tau, phosphorylated tau
- t-tau, total tau
Collapse
Affiliation(s)
- Silvia Paola Caminiti
- Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Tommaso Ballarini
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Arianna Sala
- Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Chiara Cerami
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Clinical Neuroscience Department, San Raffaele Turro Hospital, Milan, Italy
| | - Luca Presotto
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Roberto Santangelo
- Department of Neurology and INSPE, San Raffaele Scientific Institute, Milan, Italy
| | | | | | - Luigi Gianolli
- Nuclear Medicine Unit, IRCCS San Raffaele Hospital, Milan, Italy
| | - Sandro Iannaccone
- Clinical Neuroscience Department, San Raffaele Turro Hospital, Milan, Italy
| | - Giuseppe Magnani
- Department of Neurology and INSPE, San Raffaele Scientific Institute, Milan, Italy
| | - Daniela Perani
- Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Nuclear Medicine Unit, IRCCS San Raffaele Hospital, Milan, Italy.
| |
Collapse
|
37
|
Taipa R, Sousa AL, Melo Pires M, Sousa N. Does the Interplay Between Aging and Neuroinflammation Modulate Alzheimer's Disease Clinical Phenotypes? A Clinico-Pathological Perspective. J Alzheimers Dis 2018; 53:403-17. [PMID: 27176075 DOI: 10.3233/jad-160121] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
Alzheimer's disease (AD) is a chronic neurodegenerative disorder and is the most common cause of dementia worldwide. Cumulative data suggests that neuroinflammation plays a prominent and early role in AD, and there is compelling data from different research groups of age-associated dysregulation of the neuroimmune system. From the clinical point of view, despite clinical resemblance and neuropathological findings, there are important differences between the group of patients with sporadic early-onset (<65 years old) and late-onset AD (>65 years old). Thus, it seems important to understand the age-dependent relationship between neuroinflammation and the underlying biology of AD in order to identify potential explanations for clinical heterogeneity, interpret biomarkers, and promote the best treatment to different clinical AD phenotypes. The study of the delicate balance between pro-inflammatory or anti-inflammatory sides of immune players in the different ages of onset of AD would be important to understand treatment efficacy in clinical trials and eventually, not only direct treatment to early disease stages, but also the possibility of establishing different treatment approaches depending on the age of the patient. In this review, we would like to summarize what is currently known about the interplay between "normal" age associated inflammatory changes and AD pathological mechanisms, and also the potential differences between early-onset and late-onset AD taking into account the age-related neuroimmune background at disease onset.
Collapse
Affiliation(s)
- Ricardo Taipa
- Neuropathology Unit, Department of Neuroscience, Hospital Santo António - Centro Hospitalar do Porto, Porto, Portugal.,Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Braga, Portugal.,ICVS/3B's Associate Lab, PT Government Associated Lab, Braga/Guimarães, Portugal
| | - Ana Luísa Sousa
- Department of Neurology, Hospital Santo António - Centro Hospitalar do Porto, Porto, Portugal
| | - Manuel Melo Pires
- Neuropathology Unit, Department of Neuroscience, Hospital Santo António - Centro Hospitalar do Porto, Porto, Portugal
| | - Nuno Sousa
- Life and Health Sciences Research Institute (ICVS), School of Health Sciences, University of Minho, Braga, Portugal.,ICVS/3B's Associate Lab, PT Government Associated Lab, Braga/Guimarães, Portugal
| |
Collapse
|
38
|
|
39
|
Scheltens NME, Tijms BM, Koene T, Barkhof F, Teunissen CE, Wolfsgruber S, Wagner M, Kornhuber J, Peters O, Cohn-Sheehy BI, Rabinovici GD, Miller BL, Kramer JH, Scheltens P, van der Flier WM. Cognitive subtypes of probable Alzheimer's disease robustly identified in four cohorts. Alzheimers Dement 2017; 13:1226-1236. [PMID: 28427934 PMCID: PMC5857387 DOI: 10.1016/j.jalz.2017.03.002] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2016] [Revised: 03/09/2017] [Accepted: 03/09/2017] [Indexed: 01/25/2023]
Abstract
INTRODUCTION Patients with Alzheimer's disease (AD) show heterogeneity in profile of cognitive impairment. We aimed to identify cognitive subtypes in four large AD cohorts using a data-driven clustering approach. METHODS We included probable AD dementia patients from the Amsterdam Dementia Cohort (n = 496), Alzheimer's Disease Neuroimaging Initiative (n = 376), German Dementia Competence Network (n = 521), and University of California, San Francisco (n = 589). Neuropsychological data were clustered using nonnegative matrix factorization. We explored clinical and neurobiological characteristics of identified clusters. RESULTS In each cohort, a two-clusters solution best fitted the data (cophenetic correlation >0.9): one cluster was memory-impaired and the other relatively memory spared. Pooled analyses showed that the memory-spared clusters (29%-52% of patients) were younger, more often apolipoprotein E (APOE) ɛ4 negative, and had more severe posterior atrophy compared with the memory-impaired clusters (all P < .05). CONCLUSIONS We could identify two robust cognitive clusters in four independent large cohorts with distinct clinical characteristics.
Collapse
Affiliation(s)
- Nienke M. E. Scheltens
- Department of Neurology, Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands
| | - Betty M. Tijms
- Department of Neurology, Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands
| | - Teddy Koene
- Department of Medical Psychology, VU University Medical Center, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands
- Institute of Neurology, University College London, London, UK
- Institute of Healthcare Engineering, University College London, London, UK
| | - Charlotte E. Teunissen
- Neurochemistry Laboratory and Biobank, Department of Clinical Chemistry, Amsterdam Neuroscience, VU University Medical Centre, Amsterdam, The Netherlands
| | - Steffen Wolfsgruber
- Department of Psychiatry, University of Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Michael Wagner
- Department of Psychiatry, University of Bonn, Bonn, Germany
- German Center for Neurodegenerative Diseases, Bonn, Germany
| | - Johannes Kornhuber
- Department of Psychiatry, Friedrich-Alexander-University Erlangen, Erlangen, Germany
| | - Oliver Peters
- Department of Psychiatry, Charité Berlin, Campus Benjamin Franklin, Berlin, Germany
| | - Brendan I. Cohn-Sheehy
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Gil D. Rabinovici
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Bruce L. Miller
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Joel H. Kramer
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, USA
| | - Philip Scheltens
- Department of Neurology, Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands
| | - Wiesje M. van der Flier
- Department of Neurology, Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands
- Department of Epidemiology and Biostatistics, VU University Medical Center, Amsterdam, The Netherlands
| | | | | |
Collapse
|
40
|
LaPoint MR, Chhatwal JP, Sepulcre J, Johnson KA, Sperling RA, Schultz AP. The association between tau PET and retrospective cortical thinning in clinically normal elderly. Neuroimage 2017; 157:612-622. [PMID: 28545932 PMCID: PMC5772972 DOI: 10.1016/j.neuroimage.2017.05.049] [Citation(s) in RCA: 68] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2017] [Revised: 05/12/2017] [Accepted: 05/21/2017] [Indexed: 10/19/2022] Open
Abstract
Tau pathology has been associated with neuronal loss at autopsy, but the temporal evolution of tau pathology and atrophy remains unclear. Here, we investigate the association between cross-sectional AV-1451-PET as a marker of tau pathology and cortical thickness cross-sectionally. We also investigated retrospective rates of cortical thinning over the three years preceding the AV-1451 scan in a clinically normal cohort of 103 older adults from the Harvard Aging Brain Study. Tau measurements were Geometric Transfer Matrix partial volume corrected standardized uptake value ratios (SUVRs) with a cerebellar gray reference region. Thirty-four FreeSurfer-defined cortical regions of interest (ROIs) were used for both thickness and AV-1451 in each hemisphere, with seven additional volumetric ROIs. We examined "local" relationships between AV-1451 and cortical thickness in the same ROI, as well as inferior temporal AV-1451 and all thickness ROIs. All models included baseline age and sex, both interacting with time in retrospective longitudinal models, as covariates. Cross-sectional models controlled for the number of days between the two scans. Cross-sectional local comparisons revealed significant associations between elevated AV-1451 and thinner cortical ROIs predominantly in temporal regions, while analyses associating inferior temporal AV-1451 with all cortical ROIs showed a widespread pattern of significant relationships, which was strongest in temporal and parietal cortices. In our retrospective longitudinal analyses, we saw significant relationships in temporal and parietal regions. Significant local relationships were seen in right superior temporal, middle temporal, temporal pole, and fusiform, as well as the left cuneus and banks of the left superior temporal sulcus. Significant relationships between inferior temporal AV-1451 and faster thinning were observed in right temporal regions (middle temporal and fusiform) and bilateral parahippocampal cortices. We observed significant negative relationships between local and inferior temporal AV-1451 signal and both cross-sectional cortical thickness and rates of thinning in lateral and medial temporal regions. This is an important early step toward elucidating the relationship between tau pathology and retrospective longitudinal atrophy in aging and preclinical AD.
Collapse
Affiliation(s)
- Molly R LaPoint
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, 149/10.008 13th Street, Charlestown, MA 02129, USA
| | - Jasmeer P Chhatwal
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, 149/10.008 13th Street, Charlestown, MA 02129, USA
| | - Jorge Sepulcre
- Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02115, USA
| | - Keith A Johnson
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, 149/10.008 13th Street, Charlestown, MA 02129, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, 220 Longwood Ave, Boston, MA 02115, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02115, USA.
| | - Reisa A Sperling
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, 149/10.008 13th Street, Charlestown, MA 02129, USA; Center for Alzheimer Research and Treatment, Department of Neurology, Brigham and Women's Hospital, Harvard Medical School, 220 Longwood Ave, Boston, MA 02115, USA; Department of Radiology, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02115, USA
| | - Aaron P Schultz
- Department of Neurology, Massachusetts General Hospital, Harvard Medical School, and the Martinos Center for Biomedical Imaging, 149/10.008 13th Street, Charlestown, MA 02129, USA
| |
Collapse
|
41
|
Abstract
Early-onset Alzheimer disease (EOAD), with onset in individuals younger than 65 years, although overshadowed by the more common late-onset AD (LOAD), differs significantly from LOAD. EOAD comprises approximately 5% of AD and is associated with delays in diagnosis, aggressive course, and age-related psychosocial needs. One source of confusion is that a substantial percentage of EOAD are phenotypic variants that differ from the usual memory-disordered presentation of typical AD. The management of EOAD is similar to that for LOAD, but special emphasis should be placed on targeting the specific cognitive areas involved and more age-appropriate psychosocial support and education.
Collapse
Affiliation(s)
- Mario F Mendez
- Behavioral Neurology Program, David Geffen School of Medicine at UCLA, 300 Westwood Plaza, Suite B-200, Box 956975, Los Angeles, CA 90095, USA; Neurobehavior Unit, VA Greater Los Angeles Healthcare System, 11301 Wilshire Boulevard, Building 206, Los Angeles, CA 90073, USA.
| |
Collapse
|
42
|
Granadillo E, Paholpak P, Mendez MF, Teng E. Visual Ratings of Medial Temporal Lobe Atrophy Correlate with CSF Tau Indices in Clinical Variants of Early-Onset Alzheimer Disease. Dement Geriatr Cogn Disord 2017; 44:45-54. [PMID: 28675901 PMCID: PMC5575973 DOI: 10.1159/000477718] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 05/22/2017] [Indexed: 01/18/2023] Open
Abstract
BACKGROUND/AIMS Prior studies of late-onset Alzheimer disease (AD) have reported that cerebrospinal fluid (CSF) tau levels correlate with hippocampal/medial temporal lobe atrophy. These findings suggest that CSF tau indices in AD may reflect tau-related neurodegeneration in the medial temporal lobe. However, it remains uncertain whether elevated CSF tau levels in the clinically heterogeneous subtypes of early-onset AD (EOAD; amnestic, posterior cortical atrophy [PCA], and logopenic progressive aphasia [LPA]) are attributable to similar underlying mechanisms. METHODS We identified 41 EOAD patients (18 amnestic, 14 with LPA, and 9 with PCA) with CSF and brain MRI data. Semiquantitative ratings were used to assess medial temporal lobe atrophy and PCA, which were compared to CSF biomarker indices. RESULTS Lower CSF tau levels were seen in PCA relative to amnestic EOAD and LPA, but similar ratings for medial temporal lobe atrophy and PCA were seen across the groups. After adjustments for demographics and cognitive performance, both total (p = 0.004) and hyperphosphorylated (p = 0.026) tau levels correlated with medial temporal lobe atrophy across this EOAD cohort. CONCLUSIONS These results replicate prior findings in late-onset AD and support the hypothesis that CSF tau levels primarily reflect tau-related neurodegenerative changes in the hippocampus/medial temporal lobe across the clinical subtypes of EOAD.
Collapse
Affiliation(s)
- Elias Granadillo
- Department of Neurology, David Geffen School of Medicine at
UCLA,Veterans Affairs Greater Los Angeles Healthcare System
| | - Pongsatorn Paholpak
- Department of Neurology, David Geffen School of Medicine at
UCLA,Veterans Affairs Greater Los Angeles Healthcare System,Department of Psychiatry, Faculty of Medicine, Khon Kaen
University
| | - Mario F. Mendez
- Department of Neurology, David Geffen School of Medicine at
UCLA,Department of Psychiatry and Behavioral Sciences, David Geffen
School of Medicine at UCLA,Veterans Affairs Greater Los Angeles Healthcare System
| | - Edmond Teng
- Department of Neurology, David Geffen School of Medicine at
UCLA,Veterans Affairs Greater Los Angeles Healthcare System
| |
Collapse
|
43
|
Mattsson N, Schott JM, Hardy J, Turner MR, Zetterberg H. Selective vulnerability in neurodegeneration: insights from clinical variants of Alzheimer's disease. J Neurol Neurosurg Psychiatry 2016; 87:1000-4. [PMID: 26746185 DOI: 10.1136/jnnp-2015-311321] [Citation(s) in RCA: 51] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/08/2015] [Accepted: 12/05/2015] [Indexed: 11/04/2022]
Abstract
Selective vulnerability in the nervous system refers to the fact that subpopulations of neurons in different brain systems may be more or less prone to abnormal function or death in response to specific types of pathological states or injury. The concept has been used extensively as a potential way of explaining differences in degeneration patterns and the clinical presentation of different neurodegenerative diseases. Yet the increasing complexity of molecular histopathology at the cellular level in neurodegenerative disorders frequently appears at odds with phenotyping based on clinically-directed, macroscopic regional brain involvement. While cross-disease comparisons can provide insights into the differential vulnerability of networks and neuronal populations, we focus here on what is known about selective vulnerability-related factors that might explain the differential phenotypic expressions of the same disease-in this case, typical and atypical forms of Alzheimer's disease. Whereas considerable progress has been made in this area, much is yet to be elucidated; further studies comparing different phenotypic variants aimed at identifying both vulnerability and resilience factors may provide valuable insights into disease pathogenesis, and suggest novel targets for therapy.
Collapse
Affiliation(s)
- Niklas Mattsson
- Clinical Memory Research Unit, Faculty of Medicine, Lund University, Lund, Sweden
| | | | - John Hardy
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | - Martin R Turner
- Nuffield Department of Clinical Neurosciences, Oxford University, Oxford, UK
| | - Henrik Zetterberg
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK Clinical Neurochemistry Laboratory, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Mölndal, Sweden
| |
Collapse
|
44
|
Clinical and neuroimaging differences between posterior cortical atrophy and typical amnestic Alzheimer's disease patients at an early disease stage. Sci Rep 2016; 6:29372. [PMID: 27377199 PMCID: PMC4932506 DOI: 10.1038/srep29372] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2015] [Accepted: 06/16/2016] [Indexed: 11/09/2022] Open
Abstract
To identify clinical and neuroimaging characteristics between posterior cortical atrophy (PCA) and typical amnestic Alzheimer's disease (tAD) patients at an early disease stage, 16 PCA and 13 age-matched tAD patients were enrolled. Compared with tAD patients, PCA patients showed higher mean recognition and recall test scores, and lower mean calculation, spatial attention, shape discrimination, and writing test scores. Mean right hippocampal volume was larger in PCA patients compared with tAD patients, while cortical gray matter (GM) volume of bilateral parietal and occipital lobes was smaller in PCA patients. Further, when compared with tAD patients, significant hypometabolism was observed in bilateral parietal and occipital lobes, particularly the right occipitotemporal junction in PCA patients. Additionally, there were significant positive correlations in recognition and recall scores with hippocampal volumes. In PCA patients, calculation and visuospatial ability scores are positively associated with GM volume of parietal and occipital lobes. And only spatial attention and shape discrimination scores are positively associated with regional glucose metabolism of parietal and occipital lobes. Therefore, PCA patients display better recognition and recall scores, which are associated with larger hippocampal volumes and poorer performance in visual spatial tasks because of marked GM atrophy and hypometabolism of parietal and occipital lobes.
Collapse
|
45
|
Tellechea P, Pujol N, Esteve-Belloch P, Echeveste B, García-Eulate MR, Arbizu J, Riverol M. Early- and late-onset Alzheimer disease: Are they the same entity? Neurologia 2015; 33:244-253. [PMID: 26546285 DOI: 10.1016/j.nrl.2015.08.002] [Citation(s) in RCA: 41] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2015] [Revised: 08/06/2015] [Accepted: 08/14/2015] [Indexed: 11/29/2022] Open
Abstract
Early-onset Alzheimer disease (EOAD), which presents in patients younger than 65 years, has frequently been described as having different features from those of late-onset Alzheimer disease (LOAD). This review analyses the most recent studies comparing the clinical presentation and neuropsychological, neuropathological, genetic, and neuroimaging findings of both types in order to determine whether EOAD and LOAD are different entities or distinct forms of the same entity. We observed consistent differences between clinical findings in EOAD and in LOAD. Fundamentally, the onset of EOAD is more likely to be marked by atypical symptoms, and cognitive assessments point to poorer executive and visuospatial functioning and praxis with less marked memory impairment. Alzheimer-type features will be more dense and widespread in neuropathology studies, with structural and functional neuroimaging showing greater and more diffuse atrophy extending to neocortical areas (especially the precuneus). In conclusion, available evidence suggests that EOAD and LOAD are 2 different forms of a single entity. LOAD is likely to be influenced by ageing-related processes.
Collapse
Affiliation(s)
- P Tellechea
- Departamento de Neurología, Clínica Universidad de Navarra, Pamplona, Navarra, España
| | - N Pujol
- Departamento de Neurología, Clínica Universidad de Navarra, Pamplona, Navarra, España
| | - P Esteve-Belloch
- Departamento de Neurología, Clínica Universidad de Navarra, Pamplona, Navarra, España
| | - B Echeveste
- Departamento de Neurología, Clínica Universidad de Navarra, Pamplona, Navarra, España
| | - M R García-Eulate
- Departamento de Radiología, Clínica Universidad de Navarra, Pamplona, Navarra, España
| | - J Arbizu
- Departamento de Medicina Nuclear, Clínica Universidad de Navarra, Pamplona, Navarra, España
| | - M Riverol
- Departamento de Neurología, Clínica Universidad de Navarra, Pamplona, Navarra, España.
| |
Collapse
|
46
|
Paterson RW, Toombs J, Slattery CF, Nicholas JM, Andreasson U, Magdalinou NK, Blennow K, Warren JD, Mummery CJ, Rossor MN, Lunn MP, Crutch SJ, Fox NC, Zetterberg H, Schott JM. Dissecting IWG-2 typical and atypical Alzheimer's disease: insights from cerebrospinal fluid analysis. J Neurol 2015; 262:2722-30. [PMID: 26410752 DOI: 10.1007/s00415-015-7904-3] [Citation(s) in RCA: 36] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2015] [Revised: 09/10/2015] [Accepted: 09/11/2015] [Indexed: 10/23/2022]
Abstract
Pathobiological factors underlying phenotypic diversity in Alzheimer's disease (AD) are incompletely understood. We used an extended cerebrospinal fluid (CSF) panel to explore differences between "typical" with "atypical" AD and between amnestic, posterior cortical atrophy, logopenic aphasia and frontal variants. We included 97 subjects fulfilling International Working Group-2 research criteria for AD of whom 61 had "typical" AD and 36 "atypical" syndromes, and 30 controls. CSF biomarkers included total tau (T-tau), phosphorylated tau (P-tau), amyloid β1-42, amyloid βX-38/40/42, YKL-40, neurofilament light (NFL), and amyloid precursor proteins α and β. The typical and atypical groups were matched for age, sex, severity and rate of cognitive decline and had similar biomarker profiles, with the exception of NFL which was higher in the atypical group (p = 0.03). Sub-classifying the atypical group into its constituent clinical syndromes, posterior cortical atrophy was associated with the lowest T-tau [604.4 (436.8-675.8) pg/mL], P-tau (79.8 ± 21.8 pg/L), T-tau/Aβ1-42 ratio [2.3 (1.4-2.6)], AβX-40/X-42 ratio (22.1 ± 5.8) and rate of cognitive decline [1.9 (0.75-4.25) MMSE points/year]. Conversely, the frontal variant group had the highest levels of T-tau [1185.4 (591.7-1329.3) pg/mL], P-tau (116.4 ± 45.4 pg/L), T-tau/Aβ1-42 ratio [5.2 (3.3-6.9)] and AβX-40/X-42 ratio (27.9 ± 7.5), and rate of cognitive decline. Whilst on a group level IWG-2 "typical" and "atypical" AD share similar CSF profiles, which are very different from controls, atypical AD is a heterogeneous entity with evidence for subtle differences in amyloid processing and neurodegeneration between different clinical syndromes. These findings also have practical implications for the interpretation of clinical CSF biomarker results.
Collapse
Affiliation(s)
- Ross W Paterson
- Dementia Research Centre, UCL Institute of Neurology, London, UK.
| | - Jamie Toombs
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
| | | | - Jennifer M Nicholas
- Department of Medical Statistics, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, UK
| | - Ulf Andreasson
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | | | - Kaj Blennow
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Jason D Warren
- Dementia Research Centre, UCL Institute of Neurology, London, UK
| | - Cath J Mummery
- Dementia Research Centre, UCL Institute of Neurology, London, UK
| | - Martin N Rossor
- Dementia Research Centre, UCL Institute of Neurology, London, UK
| | - Michael P Lunn
- Department of Clinical Neuroimmunology, National Hospital for Neurology and Neurosurgery, London, UK
| | | | - Nick C Fox
- Dementia Research Centre, UCL Institute of Neurology, London, UK
| | - Henrik Zetterberg
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK.,Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Jonathan M Schott
- Dementia Research Centre, UCL Institute of Neurology, London, UK. .,Box 16 National Hospital for Neurology and Neurosurgery, Queen Square, London, WC1N 3BG, UK.
| |
Collapse
|