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Younger DS. Neurogenetic motor disorders. HANDBOOK OF CLINICAL NEUROLOGY 2023; 195:183-250. [PMID: 37562870 DOI: 10.1016/b978-0-323-98818-6.00003-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/12/2023]
Abstract
Advances in the field of neurogenetics have practical applications in rapid diagnosis on blood and body fluids to extract DNA, obviating the need for invasive investigations. The ability to obtain a presymptomatic diagnosis through genetic screening and biomarkers can be a guide to life-saving disease-modifying therapy or enzyme replacement therapy to compensate for the deficient disease-causing enzyme. The benefits of a comprehensive neurogenetic evaluation extend to family members in whom identification of the causal gene defect ensures carrier detection and at-risk counseling for future generations. This chapter explores the many facets of the neurogenetic evaluation in adult and pediatric motor disorders as a primer for later chapters in this volume and a roadmap for the future applications of genetics in neurology.
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Affiliation(s)
- David S Younger
- Department of Clinical Medicine and Neuroscience, CUNY School of Medicine, New York, NY, United States; Department of Medicine, Section of Internal Medicine and Neurology, White Plains Hospital, White Plains, NY, United States.
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Csincsik L, Quinn N, Yong KXX, Crutch SJ, Peto T, Lengyel I. Retinal phenotyping of variants of Alzheimer's disease using ultra-widefield retinal images. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12232. [PMID: 34458553 PMCID: PMC8377778 DOI: 10.1002/dad2.12232] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/11/2021] [Revised: 06/25/2021] [Accepted: 07/01/2021] [Indexed: 11/19/2022]
Abstract
BACKGROUND Posterior cortical atrophy (PCA) is the most common atypical variant of Alzheimer's disease (AD). Changes associated with PCA in the brain affect the visual cortex, but little is known about retinal changes in PCA. In this study, we explored retinal phenotypic variations in typical AD (tAD) and PCA. METHODS Retinal phenotyping was carried out on ultra-widefield (UWF) images of 69 control, 24 tAD, and 25 PCA participants. RESULTS Individuals with tAD (odds ratio [OR] = 2.76 [confidence interval (CI):1.24 to 6.10], P = .012) and PCA (OR = 3.40 [CI:1.25 to 9.22], P = .016) were more likely phenotyped as hard drusen. tAD (OR = 0.34 [CI:0.12 to 0.92], P = .035) were less likely to have soft drusen compared to control. Almost 3-fold increase in reticular pseudodrusen formation in tAD (OR = 2.93 [CI:1.10 to 7.76], P = .030) compared to control was estimated. DISCUSSION Studying the peripheral retina may contribute to a better understanding of differences in retinal phenotypes of different AD variants.
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Affiliation(s)
- Lajos Csincsik
- Wellcome‐Wolfson Institute for Experimental MedicineQueen's University BelfastBelfastUK
| | - Nicola Quinn
- Centre for Public HealthQueen's University BelfastBelfastUK
| | - Keir X. X. Yong
- Dementia Research CentreUCL Queen Square Institute of NeurologyUniversity College LondonLondonUK
| | - Sebastian J. Crutch
- Dementia Research CentreUCL Queen Square Institute of NeurologyUniversity College LondonLondonUK
| | - Tunde Peto
- Centre for Public HealthQueen's University BelfastBelfastUK
| | - Imre Lengyel
- Wellcome‐Wolfson Institute for Experimental MedicineQueen's University BelfastBelfastUK
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3
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Banerjee G, Ambler G, Keshavan A, Paterson RW, Foiani MS, Toombs J, Heslegrave A, Dickson JC, Fraioli F, Groves AM, Lunn MP, Fox NC, Zetterberg H, Schott JM, Werring DJ. Cerebrospinal Fluid Biomarkers in Cerebral Amyloid Angiopathy. J Alzheimers Dis 2021; 74:1189-1201. [PMID: 32176643 PMCID: PMC7242825 DOI: 10.3233/jad-191254] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Background: There is limited data on cerebrospinal fluid (CSF) biomarkers in sporadic amyloid-β (Aβ) cerebral amyloid angiopathy (CAA). Objective: To determine the profile of biomarkers relevant to neurodegenerative disease in the CSF of patients with CAA. Methods: We performed a detailed comparison of CSF markers, comparing patients with CAA, Alzheimer’s disease (AD), and control (CS) participants, recruited from the Biomarkers and Outcomes in CAA (BOCAA) study, and a Specialist Cognitive Disorders Service. Results: We included 10 CAA, 20 AD, and 10 CS participants (mean age 68.6, 62.5, and 62.2 years, respectively). In unadjusted analyses, CAA patients had a distinctive CSF biomarker profile, with significantly lower (p < 0.01) median concentrations of Aβ38, Aβ40, Aβ42, sAβPPα, and sAβPPβ. CAA patients had higher levels of neurofilament light (NFL) than the CS group (p < 0.01), but there were no significant differences in CSF total tau, phospho-tau, soluble TREM2 (sTREM2), or neurogranin concentrations. AD patients had higher total tau, phospho-tau and neurogranin than CS and CAA groups. In age-adjusted analyses, differences for the CAA group remained for Aβ38, Aβ40, Aβ42, and sAβPPβ. Comparing CAA patients with amyloid-PET positive (n = 5) and negative (n = 5) scans, PET positive individuals had lower (p < 0.05) concentrations of CSF Aβ42, and higher total tau, phospho-tau, NFL, and neurogranin concentrations, consistent with an “AD-like” profile. Conclusion: CAA has a characteristic biomarker profile, suggestive of a global, rather than selective, accumulation of amyloid species; we also provide evidence of different phenotypes according to amyloid-PET positivity. Further replication and validation of these preliminary findings in larger cohorts is needed.
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Affiliation(s)
- Gargi Banerjee
- Stroke Research Centre, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology and the National Hospital for Neurology and Neurosurgery, London, UK
| | - Gareth Ambler
- Department of Statistical Science, University College London, Gower Street, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Ross W Paterson
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Martha S Foiani
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK.,UK Dementia Research Institute at UCL, London, UK
| | - Jamie Toombs
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK.,UK Dementia Research Institute at UCL, London, UK
| | - Amanda Heslegrave
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK.,UK Dementia Research Institute at UCL, London, UK
| | - John C Dickson
- Institute of Nuclear Medicine, UCL and University College Hospital, London, UK
| | - Francesco Fraioli
- Institute of Nuclear Medicine, UCL and University College Hospital, London, UK
| | - Ashley M Groves
- Institute of Nuclear Medicine, UCL and University College Hospital, London, UK
| | - Michael P Lunn
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK.,MRC Centre for Neuromuscular Disease, National Hospital for Neurology and Neurosurgery, London, UK
| | - Nick C Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK.,UK Dementia Research Institute at UCL, London, UK
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK.,UK Dementia Research Institute at UCL, London, UK.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden.,Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Salhgrenska Academy at the University of Gothenburg, Gothenburg, Sweden
| | - Jonathan M Schott
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - David J Werring
- Stroke Research Centre, Department of Brain Repair and Rehabilitation, UCL Queen Square Institute of Neurology and the National Hospital for Neurology and Neurosurgery, London, UK
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4
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Wang J, Yang C, Wang H, Li D, Li T, Sun Y, Zhao M, Ma J, Hua W, Yang Z. A New Rat Model of Chronic Cerebral Hypoperfusion Resulting in Early-Stage Vascular Cognitive Impairment. Front Aging Neurosci 2020; 12:86. [PMID: 32351379 PMCID: PMC7174718 DOI: 10.3389/fnagi.2020.00086] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Accepted: 03/12/2020] [Indexed: 12/12/2022] Open
Abstract
Objective Currently, most models of vascular cognitive impairment are established by occluding the carotid arteries uni- or bilaterally to reduce the cerebral blood flow mimicking chronic cerebral hypoxia. Due to the sudden blood flow interruption, a gradual narrowing of the carotid artery cannot be completely imitated. This paper aims to establish a bilateral carotid stenosis model with mild cognitive dysfunction and mild white matter changes to simulate patients with vascular predementia. Methods Aged Wistar rats (18 months old) underwent either bilateral common carotid artery stenosis (BCAS) or occlusion (BCAO) surgery or a sham operation (control group). The cerebral blood flow in the frontal cortex was measured using Doppler flowmetry. Thirty days after surgery, cognitive function impairments were determined with the Morris water maze; cerebral magnetic resonance imaging was performed to detect changes in fractional anisotropy to assess white matter injuries, and histological studies were performed. Results The aged rats in the BCAS group showed a more gradual cerebral blood flow reduction and a lower mortality rate (11%) compared to rats in the BCAO group. The water maze test revealed a more marginal impairment affecting spatial learning and memory in rats with BCAS than in rats with BCAO. Diffusion tensor imaging detected white matter injuries in the hippocampus and cerebral cortex of BCAS rats. Particularly, a small portion of nerve fibers of the lateral somatosensory cortex was significantly different between rats of the BCAO and BCAS groups. In the BCAS group, the microscopic structure of the hippocampal CA1 region changed slightly after 30 days and sustained a slight mitochondrial crista crack. Fluorescence staining indicated that the number of GFAP-positive cells was increased in rat brains of the BCAS group, and this phenomenon was even more pronounced in the BCAO group. The hnRNPA2/B1 and GABAAR-α1 expression levels were significantly decreased in the hippocampus of rats with BCAS compared to those of controls. Conclusion Severe bilateral carotid stenosis induced mild cognitive dysfunction and slight structural changes in the brains of aged rats. Thus, a chronic cerebral hypoperfusion model was successfully established.
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Affiliation(s)
- Jinxin Wang
- Department of Anesthesiology, The Third Central Clinical College of Tianjin Medical University, Tianjin Third Central Hospital, Nankai University Affinity the Third Central Hospital, Tianjin Institute of Hepatobiliary Disease, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
| | - Chenyi Yang
- Department of Anesthesiology, The Third Central Clinical College of Tianjin Medical University, Tianjin Third Central Hospital, Nankai University Affinity the Third Central Hospital, Tianjin Institute of Hepatobiliary Disease, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
| | - Haiyun Wang
- Department of Anesthesiology, The Third Central Clinical College of Tianjin Medical University, Tianjin Third Central Hospital, Nankai University Affinity the Third Central Hospital, Tianjin Institute of Hepatobiliary Disease, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China.,Medical College of Nankai University, Nankai University, Tianjin, China.,Tianjin Research Institute of Anesthesiology, Tianjin, China
| | - Dongxue Li
- Department of Anesthesiology, The Third Central Clinical College of Tianjin Medical University, Tianjin Third Central Hospital, Nankai University Affinity the Third Central Hospital, Tianjin Institute of Hepatobiliary Disease, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
| | - Tang Li
- Department of Anesthesiology, The Third Central Clinical College of Tianjin Medical University, Tianjin Third Central Hospital, Nankai University Affinity the Third Central Hospital, Tianjin Institute of Hepatobiliary Disease, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
| | - Yi Sun
- Department of Anesthesiology, The Third Central Clinical College of Tianjin Medical University, Tianjin Third Central Hospital, Nankai University Affinity the Third Central Hospital, Tianjin Institute of Hepatobiliary Disease, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
| | - Mingshu Zhao
- Department of Anesthesiology, The Third Central Clinical College of Tianjin Medical University, Tianjin Third Central Hospital, Nankai University Affinity the Third Central Hospital, Tianjin Institute of Hepatobiliary Disease, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
| | - Ji Ma
- Department of Anesthesiology, The Third Central Clinical College of Tianjin Medical University, Tianjin Third Central Hospital, Nankai University Affinity the Third Central Hospital, Tianjin Institute of Hepatobiliary Disease, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
| | - Wei Hua
- Department of Anesthesiology, The Third Central Clinical College of Tianjin Medical University, Tianjin Third Central Hospital, Nankai University Affinity the Third Central Hospital, Tianjin Institute of Hepatobiliary Disease, Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
| | - Zhuo Yang
- Medical College of Nankai University, Nankai University, Tianjin, China
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5
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den Haan J, Csinscik L, Parker T, Paterson RW, Slattery CF, Foulkes A, Bouwman FH, Verbraak FD, Scheltens P, Peto T, Lengyel I, Schott JM, Crutch SJ, Shakespeare TJ, Yong KXX. Retinal thickness as potential biomarker in posterior cortical atrophy and typical Alzheimer's disease. Alzheimers Res Ther 2019; 11:62. [PMID: 31319885 PMCID: PMC6639972 DOI: 10.1186/s13195-019-0516-x] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Accepted: 07/08/2019] [Indexed: 12/13/2022]
Abstract
BACKGROUND Retinal thickness can be measured non-invasively with optical coherence tomography (OCT) and may offer compelling potential as a biomarker for Alzheimer's disease (AD). Retinal thinning is hypothesized to be a result of retrograde atrophy and/or parallel neurodegenerative processes. Changes in the visual pathway are of particular interest in posterior cortical atrophy (PCA), the most common atypical AD phenotype predominantly affecting the parietal-occipital cortices. We therefore evaluated retinal thickness as non-invasive biomarker of neurodegeneration in well-characterized participants with posterior cortical atrophy (PCA) and typical Alzheimer's disease (tAD). METHODS Retinal thickness measures were acquired from 48 patient participants (N = 25 PCA; N = 23 tAD) fulfilling consensus diagnostic criteria and 70 age-matched controls. Participants were recruited between 2014 and 2016. All participants underwent optical coherence tomography (OCT) imaging, including measurement of peripapillary retinal nerve fiber layer (pRNFL) thickness and total macular thickness (mRT). Participants did not show evidence of any significant ophthalmological conditions. Subgroup analyses were performed in participants with available MRI and CSF measures, providing evidence of neurodegeneration and underlying AD pathology respectively. RESULTS There was no evidence of overall between-group differences in pRNFL thickness (mean PCA 98.7 ± 12.2; tAD 99.9 ± 8.7; controls 99.6 ± 10.0 μm, one-way analysis of variance (ANOVA) p = 0.92) or total mRT (mean PCA 266.9 ± 16.3; tAD 267.8 ± 13.6; controls 269.3 ± 13.6 μm, one-way ANOVA p = 0.75). Similarly, subgroup analysis with MRI biomarkers (PCA = 18, tAD = 17, controls = 31) showing neurodegeneration, and CSF biomarkers (PCA = 18, tAD = 14, controls = 13) supporting underlying AD pathology did not provide evidence of overall between-group differences in pRNFL or mRT measures (all p > 0.3). CONCLUSIONS Retinal thickness did not discriminate tAD and PCA from controls or from one another despite unequivocal differences on standard clinical, neuro-imaging and CSF measures. Findings from this well-characterized sample, including cases with PCA, do not support the hypothesis that retinal neurodegeneration, measured using conventional OCT, is a useful biomarker for AD or PCA.
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Affiliation(s)
- Jurre den Haan
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Mailbox 7057, 1007 MB Amsterdam, The Netherlands
| | - Lajos Csinscik
- Centre for Experimental Medicine, Queen’s University, Belfast, UK
- Institute of Ophthalmology UCL, London, UK
| | - Tom Parker
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Ross W. Paterson
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | | | - Alexander Foulkes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Femke H. Bouwman
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Mailbox 7057, 1007 MB Amsterdam, The Netherlands
| | - Frank D. Verbraak
- Department of Ophthalmology, Amsterdam UMC, Vrije Universiteit, Amsterdam, The Netherlands
| | - Philip Scheltens
- Department of Neurology, Amsterdam Neuroscience, Alzheimer Center Amsterdam, Amsterdam UMC, Vrije Universiteit Amsterdam, Mailbox 7057, 1007 MB Amsterdam, The Netherlands
| | - Tunde Peto
- Centre for Experimental Medicine, Queen’s University, Belfast, UK
- NIHR Biomedical Research Centre, Moorfields Eye Hospital NHS Foundation Trust and UCL, London, UK
| | - Imre Lengyel
- Centre for Experimental Medicine, Queen’s University, Belfast, UK
- Institute of Ophthalmology UCL, London, UK
| | - Jonathan M. Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Sebastian J. Crutch
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | | | - Keir X. X. Yong
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
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He M, Baker SL, Shah VD, Lockhart SN, Jagust WJ. Scan-Time Corrections for 80-100-min Standardizetd Uptake Volume Ratios to Measure the 18F-AV-1451 Tracer for Tau Imaging. IEEE TRANSACTIONS ON MEDICAL IMAGING 2019; 38:697-709. [PMID: 30235119 PMCID: PMC6475617 DOI: 10.1109/tmi.2018.2870441] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/01/2023]
Abstract
The 18F-AV-1451 PET tracer binds to tau, an Alzheimer's disease biomarker. The standardized uptake value ratio (SUVR) 80-100 min window is widely used to quantify tau binding, although 18F-AV-1451 continues increasing relative to a reference region in regions with tau deposition. Left uncorrected, acquisition time inaccuracies can lead to errors from -4% to 6% in 20-min SUVR measurements in subjects with Alzheimer's disease. In 40 subjects with scans from 75-115 min following 18F-AV-1451 injection, we created 20-min reconstructions (4×5 min) of start-times ranging from 75-85 min, as proxies of offset scans and calculated the mean in regions of interest (ROIs). We developed a segmented least squares (SLS) method to obtain error-minimizing weighting coefficients for 18F-AV-1451 ROIs that best predict SUVR 80-100 from weighted means of SUVRs from offset start-times. We compared residual errors of our SLS method to those in: 1) uncorrected offset 20-min-SUVRs; 2) the mean of five-min frames within the 80-100 window; and 3) a least-squares interpolation method. We evaluated errors induced by start-time offset on SUVRs for each method. TheSLS, which corrected using least-squares coefficients of 5-min components, consistently reduced errors across all offset starttimes. Effect size analysis for simulated clinical longitudinal 18F-AV-1451 drug trials showed that uncorrected 20-min offset SUVRs would require up to 20% more participants to detect treatment effects compared with using SLS. Correction of SUVR scan-time errors by SLS minimizes errors compared with other correction methods and may be extended to other scanners and tracers.
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7
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Chen Z, Mengel D, Keshavan A, Rissman RA, Billinton A, Perkinton M, Percival-Alwyn J, Schultz A, Properzi M, Johnson K, Selkoe DJ, Sperling RA, Patel P, Zetterberg H, Galasko D, Schott JM, Walsh DM. Learnings about the complexity of extracellular tau aid development of a blood-based screen for Alzheimer's disease. Alzheimers Dement 2019; 15:487-496. [PMID: 30419228 PMCID: PMC6476313 DOI: 10.1016/j.jalz.2018.09.010] [Citation(s) in RCA: 83] [Impact Index Per Article: 16.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2018] [Revised: 09/16/2018] [Accepted: 09/30/2018] [Indexed: 10/27/2022]
Abstract
INTRODUCTION The tau protein plays a central role in Alzheimer's disease (AD), and there is huge interest in measuring tau in blood and cerebrospinal fluid (CSF). METHODS We developed a set of immunoassays to measure tau in specimens from humans diagnosed based on current best clinical and CSF biomarker criteria. RESULTS In CSF, mid-region- and N-terminal-detected tau predominated and rose in disease. In plasma, an N-terminal assay (NT1) detected elevated levels of tau in AD and AD-mild cognitive impairment (MCI). Plasma NT1 measurements separated controls from AD-MCI (area under the curve [AUC] = 0.88) and AD (AUC = 0.96) in a discovery cohort and in a Validation Cohort (with AUCs = 0.79 and 0.75, respectively). DISCUSSION The forms of tau in CSF and plasma are distinct, but in each specimen type, the levels of certain fragments are increased in AD. Measurement of plasma NT1 tau should be aggressively pursued as a potential blood-based screening test for AD/AD-MCI.
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Affiliation(s)
- Zhicheng Chen
- Laboratory for Neurodegenerative Research, Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - David Mengel
- Laboratory for Neurodegenerative Research, Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Ashvini Keshavan
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, England
| | - Robert A Rissman
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA; VA San Diego Healthcare System, La Jolla, CA, USA
| | - Andrew Billinton
- AstraZeneca Neuroscience Innovative Medicines, MedImmune Ltd, Cambridge, England
| | - Michael Perkinton
- AstraZeneca Neuroscience Innovative Medicines, MedImmune Ltd, Cambridge, England
| | | | - Aaron Schultz
- Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Michael Properzi
- Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Keith Johnson
- Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, USA
| | - Dennis J Selkoe
- Laboratory for Neurodegenerative Research, Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Reisa A Sperling
- Laboratory for Neurodegenerative Research, Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, England; UK Dementia Research Institute at UCL, London, England; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Douglas Galasko
- Department of Neurosciences, University of California San Diego, La Jolla, CA, USA
| | - Jonathan M Schott
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, England
| | - Dominic M Walsh
- Laboratory for Neurodegenerative Research, Ann Romney Center for Neurologic Diseases, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, England.
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8
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Slattery CF, Agustus JL, Paterson RW, McCallion O, Foulkes AJM, Macpherson K, Carton AM, Harding E, Golden HL, Jaisin K, Mummery CJ, Schott JM, Warren JD. The functional neuroanatomy of musical memory in Alzheimer's disease. Cortex 2019; 115:357-370. [PMID: 30846199 PMCID: PMC6525150 DOI: 10.1016/j.cortex.2019.02.003] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2018] [Revised: 12/06/2018] [Accepted: 02/01/2019] [Indexed: 12/20/2022]
Abstract
Background Memory for music has attracted much recent interest in Alzheimer's disease but the underlying brain mechanisms have not been defined in patients directly. Here we addressed this issue in an Alzheimer's disease cohort using activation fMRI of two core musical memory systems. Methods We studied 34 patients with younger onset Alzheimer's disease led either by episodic memory decline (typical Alzheimer's disease) or by visuospatial impairment (posterior cortical atrophy) in relation to 19 age-matched healthy individuals. We designed a novel fMRI paradigm based on passive listening to melodies that were either previously familiar or unfamiliar (musical semantic memory) and either presented singly or repeated (incidental musical episodic memory). Results Both syndromic groups showed significant functional neuroanatomical alterations relative to the healthy control group. For musical semantic memory, disease-associated activation group differences were localised to right inferior frontal cortex (reduced activation in the group with memory-led Alzheimer's disease); while for incidental musical episodic memory, disease-associated activation group differences were localised to precuneus and posterior cingulate cortex (abnormally enhanced activation in the syndromic groups). In post-scan behavioural testing, both patient groups had a deficit of musical episodic memory relative to healthy controls whereas musical semantic memory was unimpaired. Conclusions Our findings define functional neuroanatomical substrates for the differential involvement of musical semantic and incidental episodic memory in major phenotypes of Alzheimer's disease. The complex dynamic profile of brain activation group differences observed suggests that musical memory may be an informative probe of neural network function in Alzheimer's disease. These findings may guide the development of future musical interventions in dementia.
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Affiliation(s)
- Catherine F Slattery
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
| | - Jennifer L Agustus
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
| | - Ross W Paterson
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
| | - Oliver McCallion
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
| | - Alexander J M Foulkes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
| | - Kirsty Macpherson
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
| | - Amelia M Carton
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
| | - Emma Harding
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
| | - Hannah L Golden
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
| | - Kankamol Jaisin
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
| | - Catherine J Mummery
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
| | - Jason D Warren
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom.
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9
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Parker TD, Slattery CF, Yong KXX, Nicholas JM, Paterson RW, Foulkes AJM, Malone IB, Thomas DL, Cash DM, Crutch SJ, Fox NC, Schott JM. Differences in hippocampal subfield volume are seen in phenotypic variants of early onset Alzheimer's disease. Neuroimage Clin 2018; 21:101632. [PMID: 30558867 PMCID: PMC6411912 DOI: 10.1016/j.nicl.2018.101632] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2018] [Revised: 12/05/2018] [Accepted: 12/08/2018] [Indexed: 11/02/2022]
Abstract
The most common presentation of early onset Alzheimer's disease (EOAD - defined as symptom onset <65 years) is with progressive episodic memory impairment - amnestic or typical Alzheimer's disease (tAD). However, EOAD is notable for its phenotypic heterogeneity, with posterior cortical atrophy (PCA) - characterised by prominent higher-order visual processing deficits and relative sparing of episodic memory - the second most common canonical phenotype. The hippocampus, which comprises a number of interconnected anatomically and functionally distinct subfields, is centrally involved in Alzheimer's disease and is a crucial mediator of episodic memory. The extent to which volumes of individual hippocampal subfields differ between different phenotypes in EOAD is unclear. The aim of this analysis was to investigate the hypothesis that patients with a PCA phenotype will exhibit differences in specific hippocampal subfield volumes compared to tAD. We studied 63 participants with volumetric T1-weighted MRI performed on the same 3T scanner: 39 EOAD patients [27 with tAD and 12 with PCA] and 24 age-matched controls. Volumetric estimates of the following hippocampal subfields for each participant were obtained using Freesurfer version 6.0: CA1, CA2/3, CA4, presubiculum, subiculum, hippocampal tail, parasubiculum, the molecular and granule cell layers of the dentate gryus (GCMLDG), the molecular layer, and the hippocampal amygdala transition area (HATA). Linear regression analyses comparing mean hippocampal subfield volumes between groups, adjusting for age, sex and head size, were performed. Using a Bonferonni-corrected p-value of p < 0.0025, compared to controls, tAD was associated with atrophy in all hippocampal regions, except the parasubiculum. In PCA patients compared to controls, the strongest evidence for volume loss was in the left presubiclum, right subiculum, right GCMLDG, right molecular layer and the right HATA. Compared to PCA, patients with tAD had strong evidence for smaller volumes in left CA1 and left hippocampal tail. In conclusion, these data provide evidence that hippocampal subfield volumes differ in different phenotypes of EOAD.
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Affiliation(s)
- Thomas D Parker
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, UCL, London, UK.
| | - Catherine F Slattery
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, UCL, London, UK
| | - Keir X X Yong
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, UCL, London, UK
| | - Jennifer M Nicholas
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, UCL, London, UK; Department of Medical Statistics, London School of Hygiene and Tropical Medicine, London, UK
| | - Ross W Paterson
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, UCL, London, UK
| | - Alexander J M Foulkes
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, UCL, London, UK
| | - Ian B Malone
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, UCL, London, UK
| | - David L Thomas
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK; Leonard Wolfson Experimental Neurology Centre, UCL Institute of Neurology, London, UK
| | - David M Cash
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, UCL, London, UK
| | - Sebastian J Crutch
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, UCL, London, UK
| | - Nick C Fox
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, UCL, London, UK
| | - Jonathan M Schott
- Department of Neurodegenerative Disease, Queen Square Institute of Neurology, UCL, London, UK
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10
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Zetterberg H, Rohrer JD, Schott JM. Cerebrospinal fluid in the dementias. HANDBOOK OF CLINICAL NEUROLOGY 2018; 146:85-97. [DOI: 10.1016/b978-0-12-804279-3.00006-x] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
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11
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Álvarez I, Aguilar M, González JM, Ysamat M, Lorenzo-Bosquet C, Alonso A, Tartari JP, Romero S, Diez-Fairen M, Carcel M, Pujalte F, Pastor P. Clinic-Based Validation of Cerebrospinal Fluid Biomarkers with Florbetapir PET for Diagnosis of Dementia. J Alzheimers Dis 2017; 61:135-143. [DOI: 10.3233/jad-170753] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Affiliation(s)
- Ignacio Álvarez
- Fundació Docència i Recerca Mútua de Terrassa, Terrassa, Barcelona, Spain
- Department of Neurology, Memory Disorders Unit, Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain
| | - Miquel Aguilar
- Fundació Docència i Recerca Mútua de Terrassa, Terrassa, Barcelona, Spain
- Department of Neurology, Memory Disorders Unit, Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain
| | - Jose Manuel González
- Centre de Tecnologia Diagnòstica, Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain
| | - Montse Ysamat
- Centre de Tecnologia Diagnòstica, Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain
| | | | - Alvaro Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, USA
| | - Juan Pablo Tartari
- Fundació Docència i Recerca Mútua de Terrassa, Terrassa, Barcelona, Spain
- Department of Neurology, Memory Disorders Unit, Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain
| | - Silvia Romero
- Fundació Docència i Recerca Mútua de Terrassa, Terrassa, Barcelona, Spain
- Department of Neurology, Memory Disorders Unit, Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain
| | - Monica Diez-Fairen
- Fundació Docència i Recerca Mútua de Terrassa, Terrassa, Barcelona, Spain
- Department of Neurology, Memory Disorders Unit, Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain
| | - Maria Carcel
- Fundació Docència i Recerca Mútua de Terrassa, Terrassa, Barcelona, Spain
- Department of Neurology, Memory Disorders Unit, Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain
| | - Francisco Pujalte
- Immunology Area, Parc Logístic de Salut, Catlab, Viladecavalls, Barcelona, Spain
| | - Pau Pastor
- Fundació Docència i Recerca Mútua de Terrassa, Terrassa, Barcelona, Spain
- Department of Neurology, Memory Disorders Unit, Hospital Universitari Mutua de Terrassa, Terrassa, Barcelona, Spain
- CIBERNED, Instituto de Salud Carlos III, Madrid, Spain
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12
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Bertens D, Tijms BM, Scheltens P, Teunissen CE, Visser PJ. Unbiased estimates of cerebrospinal fluid β-amyloid 1-42 cutoffs in a large memory clinic population. ALZHEIMERS RESEARCH & THERAPY 2017; 9:8. [PMID: 28193256 PMCID: PMC5307885 DOI: 10.1186/s13195-016-0233-7] [Citation(s) in RCA: 53] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/17/2016] [Accepted: 12/28/2016] [Indexed: 12/19/2022]
Abstract
Background We sought to define a cutoff for β-amyloid 1–42 in cerebrospinal fluid (CSF), a key marker for Alzheimer’s disease (AD), with data-driven Gaussian mixture modeling in a memory clinic population. Methods We performed a combined cross-sectional and prospective cohort study. We selected 2462 subjects with subjective cognitive decline, mild cognitive impairment, AD-type dementia, and dementia other than AD from the Amsterdam Dementia Cohort. We defined CSF β-amyloid 1–42 cutoffs by data-driven Gaussian mixture modeling in the total population and in subgroups based on clinical diagnosis, age, and apolipoprotein E (APOE) genotype. We investigated whether abnormal β-amyloid 1–42 as defined by the data-driven cutoff could better predict progression to AD-type dementia than abnormal β-amyloid 1–42 defined by a clinical diagnosis-based cutoff using Cox proportional hazards regression. Results In the total group of patients, we found a cutoff for abnormal CSF β-amyloid 1–42 of 680 pg/ml (95% CI 660–705 pg/ml). Similar cutoffs were found within diagnostic and APOE genotype subgroups. The cutoff was higher in elderly subjects than in younger subjects. The data-driven cutoff was higher than our clinical diagnosis-based cutoff and had a better predictive accuracy for progression to AD-type dementia in nondemented subjects (HR 7.6 versus 5.2, p < 0.01). Conclusions Mixture modeling is a robust method to determine cutoffs for CSF β-amyloid 1–42. It might better capture biological changes that are related to AD than cutoffs based on clinical diagnosis. Electronic supplementary material The online version of this article (doi:10.1186/s13195-016-0233-7) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Daniela Bertens
- Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.,Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, De Boelelaan 1118, 1081, HZ, Amsterdam, The Netherlands
| | - Betty M Tijms
- Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.,Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, De Boelelaan 1118, 1081, HZ, Amsterdam, The Netherlands
| | - Philip Scheltens
- Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands.,Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, De Boelelaan 1118, 1081, HZ, Amsterdam, The Netherlands
| | - Charlotte E Teunissen
- Department of Clinical Chemistry, Neurochemistry Lab and Biobank, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Department of Neurology, Neuroscience Campus Amsterdam, VU University Medical Center, Amsterdam, The Netherlands. .,Alzheimer Center, Neuroscience Campus Amsterdam, VU University Medical Center, De Boelelaan 1118, 1081, HZ, Amsterdam, The Netherlands. .,Alzheimer Center, School for Mental Health and Neuroscience (MHeNS), University Medical Centre Maastricht, Maastricht, The Netherlands.
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13
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Weston PS, Paterson RW, Dickson J, Barnes A, Bomanji JB, Kayani I, Lunn MP, Mummery CJ, Warren JD, Rossor MN, Fox NC, Zetterberg H, Schott JM. Diagnosing Dementia in the Clinical Setting: Can Amyloid PET Provide Additional Value Over Cerebrospinal Fluid? J Alzheimers Dis 2016; 54:1297-1302. [PMID: 27567830 PMCID: PMC5181662 DOI: 10.3233/jad-160302] [Citation(s) in RCA: 20] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/15/2016] [Indexed: 11/28/2022]
Abstract
Cerebrospinal fluid (CSF) measures of amyloid and tau are the first-line Alzheimer's disease biomarkers in many clinical centers. We assessed if and when the addition of amyloid PET following CSF measurements provides added diagnostic value. Twenty patients from a cognitive clinic, who had undergone detailed assessment including CSF measures, went on to have amyloid PET. The treating neurologist's working diagnosis, and degree of diagnostic certainty, was assessed both before and after the PET. Amyloid PET changed the diagnosis in 7/20 cases. Amyloid PET can provide added diagnostic value, particularly in young-onset, atypical dementias, where CSF results are borderline and diagnostic uncertainty remains.
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Affiliation(s)
- Philip S.J. Weston
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Ross W. Paterson
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - John Dickson
- Institute of Nuclear Medicine, University College London Hospitals, London, UK
| | - Anna Barnes
- Institute of Nuclear Medicine, University College London Hospitals, London, UK
| | - Jamshed B. Bomanji
- Institute of Nuclear Medicine, University College London Hospitals, London, UK
| | - Irfan Kayani
- Institute of Nuclear Medicine, University College London Hospitals, London, UK
| | - Michael P. Lunn
- Department of Molecular Neuroscience, UCL Institute of Neurology, University College London, UK
| | - Catherine J. Mummery
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Jason D. Warren
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Martin N. Rossor
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Nick C. Fox
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
| | - Henrik Zetterberg
- Department of Molecular Neuroscience, UCL Institute of Neurology, University College London, UK
- Clinical Neurochemistry Laboratory, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | - Jonathan M. Schott
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
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