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Lee CH, Holloman M, Salzer JL, Zhang J. Multi-parametric MRI can detect enhanced myelination in the Gli1 -/- mouse brain. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.11.20.567957. [PMID: 38045415 PMCID: PMC10690149 DOI: 10.1101/2023.11.20.567957] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/05/2023]
Abstract
This study investigated the potential of combining multiple MR parameters to enhance the characterization of myelin in the mouse brain. We collected ex vivo multi-parametric MR data at 7 Tesla from control and Gli1 -/- mice; the latter exhibit enhanced myelination at postnatal day 10 (P10) in the corpus callosum and cortex. The MR data included relaxivity, magnetization transfer, and diffusion measurements, each targeting distinct myelin properties. This analysis was followed by and compared to myelin basic protein (MBP) staining of the same samples. Although a majority of the MR parameters included in this study showed significant differences in the corpus callosum between the control and Gli1 -/- mice, only T 2 , T 1 /T 2, and radial diffusivity (RD) demonstrated a significant correlation with MBP values. Based on data from the corpus callosum, partial least square regression suggested that combining T 2 , T 1 /T 2 , and inhomogeneous magnetization transfer ratio could explain approximately 80% of the variance in the MBP values. Myelin predictions based on these three parameters yielded stronger correlations with the MBP values in the P10 mouse brain corpus callosum than any single MR parameter. In the motor cortex, combining T 2 , T 1 /T 2, and radial kurtosis could explain over 90% of the variance in the MBP values at P10. This study demonstrates the utility of multi-parametric MRI in improving the detection of myelin changes in the mouse brain.
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Bertran-Cobo C, Dumont E, Noordin NR, Lai MY, Stone W, Tetteh KK, Drakeley C, Krishna S, Lau YL, Wassmer SC. Plasmodium knowlesi infection is associated with elevated circulating biomarkers of brain injury and endothelial activation. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.25.24306382. [PMID: 38712121 PMCID: PMC11071568 DOI: 10.1101/2024.04.25.24306382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2024]
Abstract
Introduction Malaria remains a major public health concern with substantial morbidity and mortality worldwide. In Malaysia, the emergence of Plasmodium knowlesi has led to a surge in zoonotic malaria cases and deaths in recent years. Signs of cerebral involvement have been observed in a non-comatose, fatal case of severe knowlesi infection, but the potential impact of this malaria species on the brain remains underexplored. To address this gap, we investigated circulating levels of brain injury, inflammation, and vascular biomarkers in a cohort of knowlesi-infected patients and controls. Methods Archived plasma samples from 19 patients with confirmed symptomatic knowlesi infection and 19 healthy, age-matched controls from Peninsular Malaysia were analysed. A total of 52 plasma biomarkers of brain injury, inflammation, and vascular activation were measured using Luminex and SIMOA assays. Wilcoxon tests were used to examine group differences, and biomarker profiles were explored through hierarchical clustering heatmap analysis. Results Bonferroni-corrected analyses revealed significantly elevated brain injury biomarker levels in knowlesi-infected patients, including S100B (p<0.0001), Tau (p=0.0007), UCH-L1 (p<0.0001), αSyn (p<0.0001), Park7 (p=0.0006), NRGN (p=0.0022), and TDP-43 (p=0.005). Compared to controls, levels were lower in the infected group for BDNF (p<0.0001), CaBD (p<0.0001), CNTN1 (p<0.0001), NCAM-1 (p<0.0001), GFAP (p=0.0013), and KLK6 (p=0.0126). Hierarchical clustering revealed distinct group profiles for circulating levels of brain injury and vascular activation biomarkers. Conclusions Our findings highlight for the first time the impact of Plasmodium knowlesi infection on the brain, with distinct alterations in cerebral injury and endothelial activation biomarker profiles compared to healthy controls. Further studies are warranted to investigate the pathophysiology and clinical significance of these altered surrogate markers, through both neuroimaging and long-term neurocognitive assessments.
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Nicolas S, Dohm-Hansen S, Lavelle A, Bastiaanssen TFS, English JA, Cryan JF, Nolan YM. Exercise mitigates a gut microbiota-mediated reduction in adult hippocampal neurogenesis and associated behaviours in rats. Transl Psychiatry 2024; 14:195. [PMID: 38658547 PMCID: PMC11043361 DOI: 10.1038/s41398-024-02904-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/18/2023] [Revised: 04/03/2024] [Accepted: 04/08/2024] [Indexed: 04/26/2024] Open
Abstract
Lifestyle factors, especially exercise, impact the manifestation and progression of psychiatric and neurodegenerative disorders such as depression and Alzheimer's disease, mediated by changes in hippocampal neuroplasticity. The beneficial effects of exercise may be due to its promotion of adult hippocampal neurogenesis (AHN). Gut microbiota has also been showed to be altered in a variety of brain disorders, and disturbances of the microbiota have resulted in alterations in brain and behaviour. However, whether exercise can counteract the negative effects of altered gut microbiota on brain function remains under explored. To this end, chronic disruption of the gut microbiota was achieved using an antibiotic cocktail in rats that were sedentary or allowed voluntary access to running wheels. Sedentary rats with disrupted microbiota displayed impaired performance in hippocampal neurogenesis-dependent tasks: the modified spontaneous location recognition task and the novelty suppressed feeding test. Performance in the elevated plus maze was also impaired due to antibiotics treatment. These behaviours, and an antibiotics-induced reduction in AHN were attenuated by voluntary exercise. The effects were independent of changes in the hippocampal metabolome but were paralleled by caecal metabolomic changes. Taken together these data highlight the importance of the gut microbiota in AHN-dependent behaviours and demonstrate the power of lifestyle factors such as voluntary exercise to attenuate these changes.
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Affiliation(s)
- Sarah Nicolas
- Department of Anatomy and Neuroscience, University College Cork, Cork, Ireland
- APC Microbiome Ireland, University College Cork, Cork, Ireland
| | - Sebastian Dohm-Hansen
- Department of Anatomy and Neuroscience, University College Cork, Cork, Ireland
- APC Microbiome Ireland, University College Cork, Cork, Ireland
| | - Aonghus Lavelle
- Department of Anatomy and Neuroscience, University College Cork, Cork, Ireland
- APC Microbiome Ireland, University College Cork, Cork, Ireland
| | - Thomaz F S Bastiaanssen
- Department of Anatomy and Neuroscience, University College Cork, Cork, Ireland
- APC Microbiome Ireland, University College Cork, Cork, Ireland
| | - Jane A English
- Department of Anatomy and Neuroscience, University College Cork, Cork, Ireland
- INFANT Research Centre, Cork University Hospital, Wilton, Cork, Ireland
| | - John F Cryan
- Department of Anatomy and Neuroscience, University College Cork, Cork, Ireland
- APC Microbiome Ireland, University College Cork, Cork, Ireland
| | - Yvonne M Nolan
- Department of Anatomy and Neuroscience, University College Cork, Cork, Ireland.
- APC Microbiome Ireland, University College Cork, Cork, Ireland.
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Abdallah AE. Review on anti-alzheimer drug development: approaches, challenges and perspectives. RSC Adv 2024; 14:11057-11088. [PMID: 38586442 PMCID: PMC10995770 DOI: 10.1039/d3ra08333k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2023] [Accepted: 03/22/2024] [Indexed: 04/09/2024] Open
Abstract
Alzheimer is an irreversible progressive neurodegenerative disease that causes failure of cerebral neurons and disability of the affected person to practice normal daily life activities. There is no concrete evidence to identify the exact reason behind the disease, so several relevant hypotheses emerged, highlighting many possible therapeutic targets, such as acetylcholinesterase, cholinergic receptors, N-methyl d-aspartate receptors, phosphodiesterase, amyloid β protein, protein phosphatase 2A, glycogen synthase kinase-3 beta, β-secretase, γ-secretase, α-secretase, serotonergic receptors, glutaminyl cyclase, tumor necrosis factor-α, γ-aminobutyric acid receptors, and mitochondria. All of these targets have been involved in the design of new potential drugs. An extensive number of these drugs have been studied in clinical trials. However, only galantamine, donepezil, and rivastigmine (ChEIs), memantine (NMDA antagonist), and aducanumab and lecanemab (selective anti-Aβ monoclonal antibodies) have been approved for AD treatment. Many drugs failed in the clinical trials to such an extent that questions have been posed about the significance of some of the aforementioned targets. On the contrary, the data of other drugs were promising and shed light on the significance of their targets for the development of new potent anti-alzheimer drugs.
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Affiliation(s)
- Abdallah E Abdallah
- Pharmaceutical Medicinal Chemistry & Drug Design Department, Faculty of Pharmacy (Boys), Al-Azhar University 11884 Cairo Egypt
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5
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Reveley C, Ye FQ, Leopold DA. Diffusion kurtosis MRI tracks gray matter myelin content in the primate cerebral cortex. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.08.584058. [PMID: 38496676 PMCID: PMC10942417 DOI: 10.1101/2024.03.08.584058] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Diffusion magnetic resonance imaging (dMRI) has been widely employed to model the trajectory of myelinated fiber bundles in white matter. Increasingly, dMRI is also used to assess local tissue properties throughout the brain. In the cerebral cortex, myelin content is a critical indicator of the maturation, regional variation, and disease related degeneration of gray matter tissue. Gray matter myelination can be measured and mapped using several non-diffusion MRI strategies; however, first order diffusion statistics such as fractional anisotropy (FA) show only weak spatial correlation with cortical myelin content. Here we show that a simple higher order diffusion parameter, the mean diffusion kurtosis (MK), is strongly correlated with the laminar and regional variation of myelin in the primate cerebral cortex. We carried out ultra-high resolution, multi-shelled dMRI in ex vivo marmoset monkey brains and compared dMRI parameters from a number of higher order models (diffusion kurtosis, NODDI and MAP MRI) to the distribution of myelin obtained using histological staining, and via Magnetization Transfer Ratio MRI (MTR), a non-diffusion MRI method. In contrast to FA, MK closely matched the myelin content assessed by histology and by MTR in the same sample. The parameter maps from MAP-MRI and NODDI also showed good correspondence with cortical myelin content. The results demonstrate that dMRI can be used to assess the variation of local myelin content in the primate cortical cortex, which may be of great value for assessing tissue integrity and tracking disease in living human patients.
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Affiliation(s)
- Colin Reveley
- Wellcome Centre for Integrative Neuroimaging, Centre for fMRI of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Headington, Oxford, OX9 3DU, UK
| | - Frank Q Ye
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD
| | - David A Leopold
- Neurophysiology Imaging Facility, National Institute of Mental Health, National Institute of Neurological Disorders and Stroke, National Eye Institute, National Institutes of Health, Bethesda, MD
- Section on Cognitive Neurophysiology and Imaging, Laboratory of Neuropsychology, National Institute of Mental Health, National Institutes of Health, Bethesda, MD
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Morgado B, Klafki HW, Bauer C, Waniek K, Esselmann H, Wirths O, Hansen N, Lachmann I, Osterloh D, Schuchhardt J, Wiltfang J. Assessment of immunoprecipitation with subsequent immunoassays for the blood-based diagnosis of Alzheimer's disease. Eur Arch Psychiatry Clin Neurosci 2024:10.1007/s00406-023-01751-2. [PMID: 38316685 DOI: 10.1007/s00406-023-01751-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/10/2023] [Accepted: 12/18/2023] [Indexed: 02/07/2024]
Abstract
The Aβ42/40 ratio and the concentration of phosphorylated Tau181 in blood plasma represent attractive biomarkers for Alzheimer's disease. As a means for reducing potential matrix effects, which may interfere with plasma immunoassays, we have previously developed a pre-analytical sample workup by semi-automated immunoprecipitation. Here we test the compatibility of pre-analytical immunoprecipitations with automated Aβ1-40, Aβ1-42 and phosphorylated Tau181 immunoassays on the Lumipulse platform and compare the diagnostic performance of the respective immunoprecipitation immunoassay approaches with direct plasma measurements. 71 participants were dichotomized according to their Aβ42/40 ratios in cerebrospinal fluid into the diagnostic groups amyloid-positive (n = 32) and amyloid-negative (n = 39). The plasma Aβ1-42/1-40 ratio and phosphorylated Tau181 levels were determined on the Lumipulse G600II platform (Fujirebio) by direct measurements in EDTA-plasma or after Aβ- or Tau-immunoprecipitation, respectively. Pre-analytical immunoprecipitation of Aβ turned out to be compatible with the Lumipulse Aβ assays and resulted in a numerical, yet statistically not significant increase in the area under the ROC curve for plasma Aβ1-42/1-40. Additionally, we observed a significant increase in the standardised effect size (Cohen's D). Pre-analytical immunoprecipitation of Tau resulted in increased differences between the diagnostic groups in terms of median and mean phosphorylated Tau 181 levels. Furthermore, we observed a greater Cohen's d (p < 0.001) and a larger area under the ROC curve (p = 0.038) after Tau-IP. Our preliminary findings in a small, preselected sample indicate that pre-analytical immunoprecipitation may have the potential to improve the diagnostic performance of plasma biomarker immunoassays for Aβ1-42/1-40 and phosphorylated Tau181 to predict brain amyloid deposition.
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Affiliation(s)
- Barbara Morgado
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen (UMG), Georg-August University, Von-Siebold Strasse 5, 37075, Goettingen, Germany.
| | - Hans-Wolfgang Klafki
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen (UMG), Georg-August University, Von-Siebold Strasse 5, 37075, Goettingen, Germany
| | - Chris Bauer
- MicroDiscovery GmbH, Marienburger Strasse 1, 10405, Berlin, Germany
| | | | - Hermann Esselmann
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen (UMG), Georg-August University, Von-Siebold Strasse 5, 37075, Goettingen, Germany
| | - Oliver Wirths
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen (UMG), Georg-August University, Von-Siebold Strasse 5, 37075, Goettingen, Germany
| | - Niels Hansen
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen (UMG), Georg-August University, Von-Siebold Strasse 5, 37075, Goettingen, Germany
| | | | - Dirk Osterloh
- Roboscreen GmbH, Hohmannstrasse 7, 04129, Leipzig, Germany
| | | | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen (UMG), Georg-August University, Von-Siebold Strasse 5, 37075, Goettingen, Germany.
- German Center for Neurodegenerative Diseases (DZNE), 37075, Goettingen, Germany.
- Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, 3810-193, Aveiro, Portugal.
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Salwierz P, Thapa S, Taghdiri F, Vasilevskaya A, Anastassiadis C, Tang-Wai DF, Golas AC, Tartaglia MC. Investigating the association between a history of depression and biomarkers of Alzheimer's disease, cerebrovascular disease, and neurodegeneration in patients with dementia. GeroScience 2024; 46:783-793. [PMID: 38097855 PMCID: PMC10828163 DOI: 10.1007/s11357-023-01030-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Accepted: 11/29/2023] [Indexed: 01/31/2024] Open
Abstract
The association between depression and dementia, particularly Alzheimer's disease (AD) and cerebrovascular disease (CVD), remains an active area of research. This study aimed to investigate the relationship between a history of depression and biomarkers of AD and CVD in patients with dementia in a clinical setting. A total of 126 patients from the University Health Network (UHN) Memory Clinic with comprehensive clinical evaluations, including neuropsychological testing and medical examinations, were included. Lumbar puncture was performed to collect cerebrospinal fluid (CSF) for biomarker analysis, and brain magnetic resonance imaging (MRI) scans were obtained to assess white matter hyperintensity (WMH) burden. The presence of depression was determined through medical records. The study findings did not reveal significant differences between participants with and without a history of depression in terms of AD biomarkers, WMH burden, neurofilament light chain levels, cognitive scores, age of symptom onset, disease duration, or vascular risk scores. Logistic regression analysis did not indicate a meaningful predictive value of these variables for depression status. This clinical study contributes to our understanding regarding the association between depression and AD/CVD biomarkers in patients with cognitive impairment. Further research is needed to elucidate the complex relationship between depression and dementia and to explore the potential mechanisms linking depression, AD, and CVD.
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Affiliation(s)
- Patrick Salwierz
- Tanz Centre for Research in Neurodegenerative Diseases, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada.
| | - Simrika Thapa
- Tanz Centre for Research in Neurodegenerative Diseases, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Foad Taghdiri
- Tanz Centre for Research in Neurodegenerative Diseases, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Anna Vasilevskaya
- Tanz Centre for Research in Neurodegenerative Diseases, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - Chloe Anastassiadis
- Tanz Centre for Research in Neurodegenerative Diseases, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - David F Tang-Wai
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada
- Memory Clinic University Health Network, Krembil Brain Institute, Toronto, ON, Canada
| | - Angela C Golas
- Centre for Addiction and Mental Health, Toronto, ON, Canada
- Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
| | - M Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, Temerty Faculty of Medicine, University of Toronto, Toronto, ON, Canada
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada
- Memory Clinic University Health Network, Krembil Brain Institute, Toronto, ON, Canada
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8
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Tu MC, Huang SM, Hsu YH, Yang JJ, Lin CY, Kuo LW. Joint diffusional kurtosis magnetic resonance imaging analysis of white matter and the thalamus to identify subcortical ischemic vascular disease. Sci Rep 2024; 14:2570. [PMID: 38297073 PMCID: PMC10830492 DOI: 10.1038/s41598-024-52910-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Accepted: 01/25/2024] [Indexed: 02/02/2024] Open
Abstract
Identifying subcortical ischemic vascular disease (SIVD) in older adults is important but challenging. Growing evidence suggests that diffusional kurtosis imaging (DKI) can detect SIVD-relevant microstructural pathology, and a systematic assessment of the discriminant power of DKI metrics in various brain tissue microstructures is urgently needed. Therefore, the current study aimed to explore the value of DKI and diffusion tensor imaging (DTI) metrics in detecting early-stage SIVD by combining multiple diffusion metrics, analysis strategies, and clinical-radiological constraints. This prospective study compared DKI with diffusivity and macroscopic imaging evaluations across the aging spectrum including SIVD, Alzheimer's disease (AD), and cognitively normal (NC) groups. Using a white matter atlas and segregated thalamus analysis with considerations of the pre-identified macroscopic pathology, the most effective diffusion metrics were selected and then examined using multiple clinical-radiological constraints in a two-group or three-group paradigm. A total of 122 participants (mean age, 74.6 ± 7.38 years, 72 women) including 42 with SIVD, 50 with AD, and 30 NC were evaluated. Fractional anisotropy, mean kurtosis, and radial kurtosis were critical metrics in detecting early-stage SIVD. The optimal selection of diffusion metrics showed 84.4-100% correct classification of the results in a three-group paradigm, with an area under the curve of .909-.987 in a two-group paradigm related to SIVD detection (all P < .001). We therefore concluded that greatly resilient to the effect of pre-identified macroscopic pathology, the combination of DKI/DTI metrics showed preferable performance in identifying early-stage SIVD among adults across the aging spectrum.
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Affiliation(s)
- Min-Chien Tu
- Department of Neurology, Taichung Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Taichung, Taiwan
- Department of Neurology, School of Medicine, Tzu Chi University, Hualien, Taiwan
| | - Sheng-Min Huang
- Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan
| | - Yen-Hsuan Hsu
- Department of Psychology, National Chung Cheng University, Chiayi, Taiwan
- Center for Innovative Research on Aging Society (CIRAS), National Chung Cheng University, Chiayi, Taiwan
| | - Jir-Jei Yang
- Department of Radiology, Taichung Tzu Chi Hospital, Buddhist Tzu Chi Medical Foundation, Taichung, Taiwan
| | | | - Li-Wei Kuo
- Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan.
- Institute of Medical Device and Imaging, National Taiwan University College of Medicine, Taipei, Taiwan.
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Bai Y, Camargo CM, Glasauer SMK, Gifford R, Tian X, Longhini AP, Kosik KS. Single-cell mapping of lipid metabolites using an infrared probe in human-derived model systems. Nat Commun 2024; 15:350. [PMID: 38191490 PMCID: PMC10774263 DOI: 10.1038/s41467-023-44675-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 12/20/2023] [Indexed: 01/10/2024] Open
Abstract
Understanding metabolic heterogeneity is the key to uncovering the underlying mechanisms of metabolic-related diseases. Current metabolic imaging studies suffer from limitations including low resolution and specificity, and the model systems utilized often lack human relevance. Here, we present a single-cell metabolic imaging platform to enable direct imaging of lipid metabolism with high specificity in various human-derived 2D and 3D culture systems. Through the incorporation of an azide-tagged infrared probe, selective detection of newly synthesized lipids in cells and tissue became possible, while simultaneous fluorescence imaging enabled cell-type identification in complex tissues. In proof-of-concept experiments, newly synthesized lipids were directly visualized in human-relevant model systems among different cell types, mutation status, differentiation stages, and over time. We identified upregulated lipid metabolism in progranulin-knockdown human induced pluripotent stem cells and in their differentiated microglia cells. Furthermore, we observed that neurons in brain organoids exhibited a significantly lower lipid metabolism compared to astrocytes.
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Affiliation(s)
- Yeran Bai
- Neuroscience Research Institute, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA, USA.
- Photothermal Spectroscopy Corp., Santa Barbara, CA, USA.
| | - Carolina M Camargo
- Neuroscience Research Institute, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA, USA
| | - Stella M K Glasauer
- Neuroscience Research Institute, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA, USA
| | - Raymond Gifford
- Neuroscience Research Institute, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA, USA
| | - Xinran Tian
- Neuroscience Research Institute, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA, USA
| | - Andrew P Longhini
- Neuroscience Research Institute, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA, USA
| | - Kenneth S Kosik
- Neuroscience Research Institute, Department of Molecular, Cellular, and Developmental Biology, University of California, Santa Barbara, CA, USA.
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Scholz MP, Donders J. Cognitive complaints in older adults: relationships between self and informant report, objective test performance, and symptoms of depression. NEUROPSYCHOLOGY, DEVELOPMENT, AND COGNITION. SECTION B, AGING, NEUROPSYCHOLOGY AND COGNITION 2024; 31:263-278. [PMID: 36345862 DOI: 10.1080/13825585.2022.2144617] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 11/01/2022] [Indexed: 11/10/2022]
Abstract
This study explored the relationships between objective measures of cognitive functioning, self and informant reports of cognitive problems in daily life, and depression screening in older adults who had been referred because of reported or suspected cognitive changes. We used archival data from 100, predominantly White (97%), typically educated (M = 13.25 years), older adults (M = 70.38 years) who received an outpatient neuropsychological evaluation. We characterized the cognitive performance using the CVLT-II Total score. We characterized patient and collateral reports using the BRIEF-A MI index, a normed scale of cognitive problems in daily life. We also incorporated a depression screener (PHQ-9) into our analyses. Multiple linear regression analysis revealed that only the informant reported problems in daily life, using the BRIEF-A MI index, was a significant predictor of objective cognitive deficits, as defined by CVLT-II Total scores. Self BRIEF-A MI index scores were not significant predictors of CVLT-II Total performance after we accounted for depression using the patient's PHQ-9 score. Additionally, elevated depression widened the discrepancy between raters, with elevated depression associated with worsening sself-report scores compared to informant-reported scores. As informant-reported problems were the strongest predictor of cognitive deficits, we recommend routine collection of collateral informant reports in the neuropsychological evaluation of older adults referred for cognitive concerns. We also recommend incorporating self-ratings of daily life functioning and screening for depression to contextualize patient complaints and address their concerns, even in the absence of objective cognitive dysfunction.
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Affiliation(s)
- Michael P Scholz
- Psychology Department, Mary Free Bed Rehabilitation Hospital, Grand Rapids, MI, USA
| | - Jacobus Donders
- Psychology Department, Mary Free Bed Rehabilitation Hospital, Grand Rapids, MI, USA
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11
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Zhang W, Liao Y, Chang H. Categorical perception of lexical tones in Chinese people with post-stroke aphasia. CLINICAL LINGUISTICS & PHONETICS 2023; 37:1069-1090. [PMID: 36373592 DOI: 10.1080/02699206.2022.2138785] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Revised: 10/02/2022] [Accepted: 10/11/2022] [Indexed: 06/16/2023]
Abstract
This study used the categorical perception (CP) paradigm, a fine-grained perceptual method, to investigate the perceptual performance of lexical tones in Chinese people with post-stroke aphasia (PWA). Twenty patients with post-stroke aphasia (10 Broca's and 10 Wernicke's) and ten neurologically intact age-matched control participants were recruited to complete both identification and discrimination tasks of the Mandarin Tone 1-2 continuum. In addition, all participants completed tests on their auditory comprehension ability and working memory. The results showed that both Broca's and Wernicke's patients exhibited reduced sensitivity to within-category and between-category information but preserved CP of lexical tones. The degree of CP of lexical tones related to working memory in aphasic patients. Furthermore, lower-level acoustic processing underpinned higher-level phonological processing on the CP of lexical tones since both patient groups' unbalanced pitch processing ability extended to their CP of lexical tones. These findings are significant for researchers and clinicians in speech-language rehabilitation, clinical psychology, and cognitive communication.
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Affiliation(s)
- Wei Zhang
- School of Foreign Languages, Shanghai Jiao Tong University, Shanghai, China
- Oriental College of International Trade and Foreign Languages, Haikou University of Economics, Haikou, China
| | - Yi Liao
- International College for Chinese Studies, Nanjing Normal University, Nanjing, China
- School of Humanities and Communication, University of Sanya, Sanya, China
| | - Hui Chang
- School of Foreign Languages, Shanghai Jiao Tong University, Shanghai, China
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12
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Neumann A, Ohlei O, Küçükali F, Bos IJ, Timsina J, Vos S, Prokopenko D, Tijms BM, Andreasson U, Blennow K, Vandenberghe R, Scheltens P, Teunissen CE, Engelborghs S, Frisoni GB, Blin O, Richardson JC, Bordet R, Lleó A, Alcolea D, Popp J, Marsh TW, Gorijala P, Clark C, Peyratout G, Martinez-Lage P, Tainta M, Dobson RJB, Legido-Quigley C, Van Broeckhoven C, Tanzi RE, Ten Kate M, Lill CM, Barkhof F, Cruchaga C, Lovestone S, Streffer J, Zetterberg H, Visser PJ, Sleegers K, Bertram L. Multivariate GWAS of Alzheimer's disease CSF biomarker profiles implies GRIN2D in synaptic functioning. Genome Med 2023; 15:79. [PMID: 37794492 PMCID: PMC10548686 DOI: 10.1186/s13073-023-01233-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2023] [Accepted: 09/12/2023] [Indexed: 10/06/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) of Alzheimer's disease (AD) have identified several risk loci, but many remain unknown. Cerebrospinal fluid (CSF) biomarkers may aid in gene discovery and we previously demonstrated that six CSF biomarkers (β-amyloid, total/phosphorylated tau, NfL, YKL-40, and neurogranin) cluster into five principal components (PC), each representing statistically independent biological processes. Here, we aimed to (1) identify common genetic variants associated with these CSF profiles, (2) assess the role of associated variants in AD pathophysiology, and (3) explore potential sex differences. METHODS We performed GWAS for each of the five biomarker PCs in two multi-center studies (EMIF-AD and ADNI). In total, 973 participants (n = 205 controls, n = 546 mild cognitive impairment, n = 222 AD) were analyzed for 7,433,949 common SNPs and 19,511 protein-coding genes. Structural equation models tested whether biomarker PCs mediate genetic risk effects on AD, and stratified and interaction models probed for sex-specific effects. RESULTS Five loci showed genome-wide significant association with CSF profiles, two were novel (rs145791381 [inflammation] and GRIN2D [synaptic functioning]) and three were previously described (APOE, TMEM106B, and CHI3L1). Follow-up analyses of the two novel signals in independent datasets only supported the GRIN2D locus, which contains several functionally interesting candidate genes. Mediation tests indicated that variants in APOE are associated with AD status via processes related to amyloid and tau pathology, while markers in TMEM106B and CHI3L1 are associated with AD only via neuronal injury/inflammation. Additionally, seven loci showed sex-specific associations with AD biomarkers. CONCLUSIONS These results suggest that pathway and sex-specific analyses can improve our understanding of AD genetics and may contribute to precision medicine.
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Affiliation(s)
- Alexander Neumann
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Child and Adolescent Psychiatry/Psychology, Erasmus University Medical Center, Rotterdam, Netherlands
| | - Olena Ohlei
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, V50.2M, Lübeck, 23562, Germany
| | - Fahri Küçükali
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Isabelle J Bos
- Netherlands Institute for Health Services Research, Utrecht, Netherlands
| | - Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Stephanie Vos
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, Netherlands
| | - Dmitry Prokopenko
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Ulf Andreasson
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Neurology Service, University Hospital Leuven, Leuven, Belgium
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Charlotte E Teunissen
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, Netherlands
| | - Sebastiaan Engelborghs
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Department of Neurology and Memory Clinic, Universitair Ziekenhuis Brussel (UZ Brussel) and Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Giovanni B Frisoni
- Memory Center, Department of Rehabilitation and Geriatrics, Geneva University and University Hospitals, Geneva, Switzerland
| | - Oliver Blin
- Clinical Pharmacology & Pharmacovigilance Department, Marseille University Hospital, Marseille, France
| | | | - Régis Bordet
- Neuroscience & Cognition, CHU de Lille, University of Lille, Inserm, France
| | - Alberto Lleó
- Memory Unit, Neurology Department, Hospital de Sant Pau, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Daniel Alcolea
- Memory Unit, Neurology Department, Hospital de Sant Pau, Barcelona, Spain
- Centro de Investigación Biomédica en Red en Enfermedades Neurodegenerativas (CIBERNED), Madrid, Spain
| | - Julius Popp
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Zurich, Switzerland
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Thomas W Marsh
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- Division of Biology & Biomedical Sciences, Washington University in St. Louis, St Louis, MO, USA
| | - Priyanka Gorijala
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
| | - Christopher Clark
- Department of Psychiatry, Psychotherapy and Psychosomatics, University of Zürich, Zurich, Switzerland
| | - Gwendoline Peyratout
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Pablo Martinez-Lage
- Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
| | - Mikel Tainta
- Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
- Zumarraga Hospital, Osakidetza, Integrated Health Organization (OSI) Goierri-Urola Garia, Basque Country, Spain
| | - Richard J B Dobson
- Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience, King's College London, Boston, UK
- NIHR BioResource Centre Maudsley, NIHR Maudsley Biomedical Research Centre (BRC) at South London and Maudsley NHS Foundation Trust (SLaM) & Institute of Psychiatry, Psychology and Neuroscience (IoPPN), King's College London, London, UK
- Health Data Research UK London, University College London, London, UK
- Institute of Health Informatics, University College London, London, UK
- The National Institute for Health Research University College London Hospitals Biomedical Research Centre, University College London, London, UK
| | - Cristina Legido-Quigley
- Steno Diabetes Center, Copenhagen, Denmark
- Institute of Pharmaceutical Science, King's College London, London, UK
| | - Christine Van Broeckhoven
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Neurodegenerative Brain Diseases Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
| | - Rudolph E Tanzi
- Genetics and Aging Unit and McCance Center for Brain Health, Department of Neurology, Massachusetts General Hospital, Boston, MA, USA
| | - Mara Ten Kate
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, Netherlands
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, Netherlands
| | - Christina M Lill
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, V50.2M, Lübeck, 23562, Germany
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
- Ageing Epidemiology Research Unit, School of Public Health, Imperial College, London, UK
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit, Amsterdam, Netherlands
- Queen Square Institute of Neurology and Centre for Medical Image Computing, University College London, London, UK
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St Louis, MO, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St Louis, MO, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St Louis, MO, USA
| | - Simon Lovestone
- Janssen Medical Ltd, Wycombe, UK
- Department of Psychiatry, University of Oxford, Oxford, UK
| | - Johannes Streffer
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- AC Immune SA, Lausanne, Switzerland
- Janssen R&D, LLC, Beerse, Belgium
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute, University College London, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Pieter Jelle Visser
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, Netherlands
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, Netherlands
| | - Kristel Sleegers
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics (LIGA), University of Lübeck, Ratzeburger Allee 160, V50.2M, Lübeck, 23562, Germany.
- Centre for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway.
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13
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Tatsuo S, Watanabe K, Ide S, Tsushima F, Tatsuo S, Matsuzaka M, Murakami H, Ishida M, Iwane T, Daimon M, Yodono H, Nakaji S, Kakeda S. Association of prediabetes with reduced brain volume in a general elderly Japanese population. Eur Radiol 2023; 33:5378-5384. [PMID: 36892647 DOI: 10.1007/s00330-023-09509-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 12/30/2022] [Accepted: 02/05/2023] [Indexed: 03/10/2023]
Abstract
OBJECTIVES Diabetes frequently results in cognitive impairment, but it is less clear if brain health is adversely affected during the prediabetic stage. Our aim is to identify possible changes in brain volume as measured by magnetic resonance imaging (MRI) in a large elderly population stratified according to level of "dysglycemia." METHODS This is a cross-sectional study of 2144 participants (median age 69 years, 60.9% female) who underwent 3-T brain MRI. Participants were divided into 4 dysglycemia groups based on HbA1c levels (%): normal glucose metabolism (NGM) (< 5.7%), prediabetes (5.7 to < 6.5%), undiagnosed diabetes (6.5% or higher), and known diabetes (defined by self-report). RESULTS Of the 2144 participants, 982 had NGM, 845 prediabetes, 61 undiagnosed diabetes, and 256 known diabetes. After adjustment for age, sex, education, body weight, cognitive status, smoking, drinking, and disease history, total gray matter volume was significantly lower among participants with prediabetes (0.41% lower, standardized β = - 0.0021 [95% CI - 0.0039, - 0.00039], p = 0.016), undiagnosed diabetes (1.4% lower, standardized β = - 0.0069 [95% CI - 0.012, - 0.002], p = 0.005), and known diabetes (1.1% lower, standardized β = - 0.0055 [95% CI - 0.0081, - 0.0029], p < 0.001) compared to the NGM group. After adjustment, total white matter volume and hippocampal volume did not differ significantly between the NGM group and either the prediabetes group or the diabetes group. CONCLUSION Sustained hyperglycemia may have deleterious effects on gray matter integrity even prior to the onset of clinical diabetes. KEY POINTS • Sustained hyperglycemia has deleterious effects on gray matter integrity even prior to the onset of clinical diabetes.
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Affiliation(s)
- Soichiro Tatsuo
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Keita Watanabe
- Open Innovation Institute, Kyoto University, Kyoto, Japan
| | - Satoru Ide
- Department of Radiology, University of Occupational and Environmental Health, School of Medicine, Kitakyushu, Japan.
| | - Fumiyasu Tsushima
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Sayuri Tatsuo
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Masashi Matsuzaka
- Department of Medical Informatics and Clinical Research Support Center, Hirosaki University Hospital, Hirosaki, Japan
| | - Hiroshi Murakami
- Department of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Mizuri Ishida
- Hirosaki University COI Research Initiative Organization, Hirosaki University, Hirosaki, Japan
| | - Takuro Iwane
- Hirosaki University COI Research Initiative Organization, Hirosaki University, Hirosaki, Japan
| | - Makoto Daimon
- Department of Endocrinology and Metabolism, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
| | - Hiraku Yodono
- Department of Radiology, Narumi Hospital, Hirosaki, Japan
| | - Shigeyuki Nakaji
- Hirosaki University COI Research Initiative Organization, Hirosaki University, Hirosaki, Japan
| | - Shingo Kakeda
- Department of Radiology, Hirosaki University Graduate School of Medicine, Hirosaki, Japan
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14
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Pizarro-Galleguillos BM, Kunert L, Brüggemann N, Prasuhn J. Neuroinflammation and Mitochondrial Dysfunction in Parkinson's Disease: Connecting Neuroimaging with Pathophysiology. Antioxidants (Basel) 2023; 12:1411. [PMID: 37507950 PMCID: PMC10375976 DOI: 10.3390/antiox12071411] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Revised: 07/07/2023] [Accepted: 07/10/2023] [Indexed: 07/30/2023] Open
Abstract
There is a pressing need for disease-modifying therapies in patients suffering from neurodegenerative diseases, including Parkinson's disease (PD). However, these disorders face unique challenges in clinical trial designs to assess the neuroprotective properties of potential drug candidates. One of these challenges relates to the often unknown individual disease mechanisms that would, however, be relevant for targeted treatment strategies. Neuroinflammation and mitochondrial dysfunction are two proposed pathophysiological hallmarks and are considered to be highly interconnected in PD. Innovative neuroimaging methods can potentially help to gain deeper insights into one's predominant disease mechanisms, can facilitate patient stratification in clinical trials, and could potentially map treatment responses. This review aims to highlight the role of neuroinflammation and mitochondrial dysfunction in patients with PD (PwPD). We will specifically introduce different neuroimaging modalities, their respective technical hurdles and challenges, and their implementation into clinical practice. We will gather preliminary evidence for their potential use in PD research and discuss opportunities for future clinical trials.
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Affiliation(s)
- Benjamin Matís Pizarro-Galleguillos
- Facultad de Medicina, Universidad de Chile, Santiago 8380453, Chile
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, 23562 Lübeck, Germany
- Institute of Neurogenetics, University of Lübeck, 23562 Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, 23562 Lübeck, Germany
| | - Liesa Kunert
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, 23562 Lübeck, Germany
- Institute of Neurogenetics, University of Lübeck, 23562 Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, 23562 Lübeck, Germany
| | - Norbert Brüggemann
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, 23562 Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, 23562 Lübeck, Germany
| | - Jannik Prasuhn
- Department of Neurology, University Medical Center Schleswig-Holstein, Campus Lübeck, 23562 Lübeck, Germany
- Institute of Neurogenetics, University of Lübeck, 23562 Lübeck, Germany
- Center for Brain, Behavior, and Metabolism, University of Lübeck, 23562 Lübeck, Germany
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
- F.M. Kirby Research Center for Functional Brain Imaging, Kennedy Krieger Institute, Baltimore, MD 21287, USA
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15
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Thompson JL, Sheppard DP, Matchanova A, Morgan EE, Loft S, Woods SP. Subjective cognitive decline disrupts aspects of prospective memory in older adults with HIV disease. NEUROPSYCHOLOGY, DEVELOPMENT, AND COGNITION. SECTION B, AGING, NEUROPSYCHOLOGY AND COGNITION 2023; 30:582-600. [PMID: 35412440 PMCID: PMC9554043 DOI: 10.1080/13825585.2022.2065241] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Accepted: 04/07/2022] [Indexed: 05/10/2023]
Abstract
Subjective cognitive decline (SCD) is a risk factor for dementia that may occur at higher rates in people with HIV (PWH). Prospective memory (PM) is an aspect of cognition that may help us better understand how SCD impacts daily life. Paricipants were 62 PWH aged ≥ 50 years and 33 seronegative individuals. SCD was operationalized as normatively elevated cognitive symptoms on standardized questionnaires, but with normatively unimpaired performance-based cognition and no current affective disorders. PM was measured with the Comprehensive Assessment of Prospective Memory (CAPM), the Cambridge Test of Prospective Memory (CAMPROMPT), and an experimental computerized time-based PM task. A logistic regression revealed that older PWH had a three-fold increased likelihood for SCD. Among the PWH, SCD was associated with more frequent PM symptoms and poorer accuracy on the time-based scale of the CAMPROMPT. These findings suggest that SCD disrupts PM in older PWH.
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Affiliation(s)
| | - David P. Sheppard
- Mental Illness, Research, Education, and Clinical Care (MIRECC), Veterans Affairs Puget Sound Health Care System, Seattle, WA 98108, USA
| | | | - Erin E. Morgan
- Department of Psychiatry, University of California San Diego, San Diego, CA 92103, USA
| | - Shayne Loft
- School of Psychological Science, University of Western Australia, Perth, WA 6009, Australia
| | - Steven Paul Woods
- Department of Psychology, University of Houston, Houston, TX 77004, USA
- School of Psychological Science, University of Western Australia, Perth, WA 6009, Australia
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16
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de Geus MB, Leslie SN, Lam T, Wang W, Kivisakk P, Nairn AC, Arnold SE, Carlyle BC. Mass Spectrometry in Cerebrospinal Fluid Uncovers Association of Glycolysis Biomarkers with Alzheimer's Disease in a Large Clinical Sample. RESEARCH SQUARE 2023:rs.3.rs-3073597. [PMID: 37461556 PMCID: PMC10350182 DOI: 10.21203/rs.3.rs-3073597/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/24/2023]
Abstract
Background Alzheimer's disease (AD) is a complex heterogenous neurodegenerative disorder, characterized by multiple pathophysiologies, including disruptions in brain metabolism. Defining markers for patient stratification across these pathophysiologies is an important step towards personalized treatment of AD. Efficient brain glucose metabolism is essential to sustain neuronal activity, but hypometabolism is consistently observed in AD. The molecular changes underlying these observations remain unclear. Recent studies have indicated dysregulation of several glycolysis markers in AD cerebrospinal fluid and tissue. Methods In this study, unbiased mass spectrometry was used to perform a deep proteomic survey of cerebrospinal fluid (CSF) from a large-scale clinically complex cohort to uncover changes related to impaired glucose metabolism. Results Two glycolytic enzymes, Pyruvate kinase (PKM) and Aldolase A (ALDOA) were found to be specifically upregulated in AD CSF compared to other non-AD groups. Presence of full-length protein of these enzymes in CSF was confirmed through immunoblotting. Levels of tryptic peptides of these enzymes correlated significantly with CSF glucose and CSF lactate in matching CSF samples. Conclusions The results presented here indicate a general dysregulation of glucose metabolism in the brain in AD. We highlight two markers ALDOA and PKM that may act as potential functionally-relevant biomarkers of glucose metabolism dysregulation in AD.
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17
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Verdi S, Rutherford S, Fraza C, Tosun D, Altmann A, Raket LL, Schott JM, Marquand AF, Cole JH. Personalising Alzheimer's Disease progression using brain atrophy markers. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.15.23291418. [PMID: 37398392 PMCID: PMC10312850 DOI: 10.1101/2023.06.15.23291418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/04/2023]
Abstract
INTRODUCTION Neuroanatomical normative modelling can capture individual variability in Alzheimer's Disease (AD). We used neuroanatomical normative modelling to track individuals' disease progression in people with mild cognitive impairment (MCI) and patients with AD. METHODS Cortical thickness and subcortical volume neuroanatomical normative models were generated using healthy controls (n~58k). These models were used to calculate regional Z-scores in 4361 T1-weighted MRI time-series scans. Regions with Z-scores <-1.96 were classified as outliers and mapped on the brain, and also summarised by total outlier count (tOC). RESULTS Rate of change in tOC increased in AD and in people with MCI who converted to AD and correlated with multiple non-imaging markers. Moreover, a higher annual rate of change in tOC increased the risk of MCI progression to AD. Brain Z-score maps showed that the hippocampus had the highest rate of atrophy change. CONCLUSIONS Individual-level atrophy rates can be tracked by using regional outlier maps and tOC.
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Affiliation(s)
- Serena Verdi
- Centre for Medical Image Computing, University College London, London, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Saige Rutherford
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, 6525EN, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, 6525EN, the Netherlands
| | - Charlotte Fraza
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, 6525EN, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, 6525EN, the Netherlands
| | - Duygu Tosun
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Andre Altmann
- Centre for Medical Image Computing, University College London, London, UK
| | - Lars Lau Raket
- Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
| | - Andre F Marquand
- Donders Centre for Cognitive Neuroimaging, Donders Institute for Brain, Cognition and Behaviour, Radboud University, Nijmegen, 6525EN, the Netherlands
- Department of Cognitive Neuroscience, Radboud University Medical Centre, Nijmegen, 6525EN, the Netherlands
| | - James H Cole
- Centre for Medical Image Computing, University College London, London, UK
- Dementia Research Centre, UCL Queen Square Institute of Neurology, London, UK
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18
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Bernal J, Schreiber S, Menze I, Ostendorf A, Pfister M, Geisendörfer J, Nemali A, Maass A, Yakupov R, Peters O, Preis L, Schneider L, Herrera AL, Priller J, Spruth EJ, Altenstein S, Schneider A, Fliessbach K, Wiltfang J, Schott BH, Rostamzadeh A, Glanz W, Buerger K, Janowitz D, Ewers M, Perneczky R, Rauchmann BS, Teipel S, Kilimann I, Laske C, Munk MH, Spottke A, Roy N, Dobisch L, Dechent P, Scheffler K, Hetzer S, Wolfsgruber S, Kleineidam L, Schmid M, Berger M, Jessen F, Wirth M, Düzel E, Ziegler G. Arterial hypertension and β-amyloid accumulation have spatially overlapping effects on posterior white matter hyperintensity volume: a cross-sectional study. Alzheimers Res Ther 2023; 15:97. [PMID: 37226207 DOI: 10.1186/s13195-023-01243-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Accepted: 05/09/2023] [Indexed: 05/26/2023]
Abstract
BACKGROUND White matter hyperintensities (WMH) in subjects across the Alzheimer's disease (AD) spectrum with minimal vascular pathology suggests that amyloid pathology-not just arterial hypertension-impacts WMH, which in turn adversely influences cognition. Here we seek to determine the effect of both hypertension and Aβ positivity on WMH, and their impact on cognition. METHODS We analysed data from subjects with a low vascular profile and normal cognition (NC), subjective cognitive decline (SCD), and amnestic mild cognitive impairment (MCI) enrolled in the ongoing observational multicentre DZNE Longitudinal Cognitive Impairment and Dementia Study (n = 375, median age 70.0 [IQR 66.0, 74.4] years; 178 female; NC/SCD/MCI 127/162/86). All subjects underwent a rich neuropsychological assessment. We focused on baseline memory and executive function-derived from multiple neuropsychological tests using confirmatory factor analysis-, baseline preclinical Alzheimer's cognitive composite 5 (PACC5) scores, and changes in PACC5 scores over the course of three years (ΔPACC5). RESULTS Subjects with hypertension or Aβ positivity presented the largest WMH volumes (pFDR < 0.05), with spatial overlap in the frontal (hypertension: 0.42 ± 0.17; Aβ: 0.46 ± 0.18), occipital (hypertension: 0.50 ± 0.16; Aβ: 0.50 ± 0.16), parietal lobes (hypertension: 0.57 ± 0.18; Aβ: 0.56 ± 0.20), corona radiata (hypertension: 0.45 ± 0.17; Aβ: 0.40 ± 0.13), optic radiation (hypertension: 0.39 ± 0.18; Aβ: 0.74 ± 0.19), and splenium of the corpus callosum (hypertension: 0.36 ± 0.12; Aβ: 0.28 ± 0.12). Elevated global and regional WMH volumes coincided with worse cognitive performance at baseline and over 3 years (pFDR < 0.05). Aβ positivity was negatively associated with cognitive performance (direct effect-memory: - 0.33 ± 0.08, pFDR < 0.001; executive: - 0.21 ± 0.08, pFDR < 0.001; PACC5: - 0.29 ± 0.09, pFDR = 0.006; ΔPACC5: - 0.34 ± 0.04, pFDR < 0.05). Splenial WMH mediated the relationship between hypertension and cognitive performance (indirect-only effect-memory: - 0.05 ± 0.02, pFDR = 0.029; executive: - 0.04 ± 0.02, pFDR = 0.067; PACC5: - 0.05 ± 0.02, pFDR = 0.030; ΔPACC5: - 0.09 ± 0.03, pFDR = 0.043) and WMH in the optic radiation partially mediated that between Aβ positivity and memory (indirect effect-memory: - 0.05 ± 0.02, pFDR = 0.029). CONCLUSIONS Posterior white matter is susceptible to hypertension and Aβ accumulation. Posterior WMH mediate the association between these pathologies and cognitive dysfunction, making them a promising target to tackle the downstream damage related to the potentially interacting and potentiating effects of the two pathologies. TRIAL REGISTRATION German Clinical Trials Register (DRKS00007966, 04/05/2015).
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Affiliation(s)
- Jose Bernal
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany.
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany.
| | - Stefanie Schreiber
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
- Department of Neurology, Medical Faculty, University Hospital Magdeburg, Magdeburg, Germany
| | - Inga Menze
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Anna Ostendorf
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
| | - Malte Pfister
- Department of Neurology, Medical Faculty, University Hospital Magdeburg, Magdeburg, Germany
| | - Jonas Geisendörfer
- Department of Neurology, Medical Faculty, University Hospital Magdeburg, Magdeburg, Germany
| | - Aditya Nemali
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Anne Maass
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Renat Yakupov
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Oliver Peters
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Lukas Preis
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Luisa Schneider
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Ana Lucia Herrera
- Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität Zu Berlin-Institute of Psychiatry and Psychotherapy, Berlin, Germany
| | - Josef Priller
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
- School of Medicine, Department of Psychiatry and Psychotherapy, Technical University of Munich, Munich, Germany
- University of Edinburgh and UK DRI, Edinburgh, UK
| | - Eike Jakob Spruth
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Slawek Altenstein
- German Center for Neurodegenerative Diseases (DZNE), Berlin, Germany
- Department of Psychiatry and Psychotherapy, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Anja Schneider
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Klaus Fliessbach
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Jens Wiltfang
- German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, University of Goettingen, Goettingen, Germany
- Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Björn H Schott
- German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, University of Goettingen, Goettingen, Germany
| | - Ayda Rostamzadeh
- Department of Psychiatry, University of Cologne, Cologne, Germany
| | - Wenzel Glanz
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
| | - Katharina Buerger
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Daniel Janowitz
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Michael Ewers
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Institute for Stroke and Dementia Research (ISD), University Hospital, LMU Munich, Munich, Germany
| | - Robert Perneczky
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy) Munich, Munich, Germany
- Ageing Epidemiology Research Unit (AGE), School of Public Health, Imperial College London, London, UK
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Boris-Stephan Rauchmann
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Munich, Germany
| | - Stefan Teipel
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Ingo Kilimann
- German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany
- Department of Psychosomatic Medicine, Rostock University Medical Center, Rostock, Germany
| | - Christoph Laske
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Section for Dementia Research, Hertie Institute for Clinical Brain Research and Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Matthias H Munk
- German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Annika Spottke
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Nina Roy
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Laura Dobisch
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
| | - Peter Dechent
- MR-Research in Neurosciences, Department of Cognitive Neurology, Georg-August-University Goettingen, Göttingen, Germany
| | - Klaus Scheffler
- Department for Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Stefan Hetzer
- Berlin Center for Advanced Neuroimaging, Charité - Universitätsmedizin Berlin, Berlin, Germany
| | - Steffen Wolfsgruber
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Luca Kleineidam
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Clinic for Neurodegenerative Diseases and Geriatric Psychiatry, University of Bonn, Bonn, Germany
| | - Matthias Schmid
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Bonn, Germany
| | - Moritz Berger
- Institute for Medical Biometry, Informatics and Epidemiology, University Hospital Bonn, Bonn, Germany
| | - Frank Jessen
- German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Psychiatry, University of Cologne, Cologne, Germany
- Excellence Cluster On Cellular Stress Responses in Aging-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Miranka Wirth
- German Center for Neurodegenerative Diseases (DZNE), Tatzberg 41, Dresden, 01307, Germany.
| | - Emrah Düzel
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
- Institute of Cognitive Neuroscience, University College London, London, UK
| | - Gabriel Ziegler
- Institute of Cognitive Neurology and Dementia Research, Otto-Von-Guericke University Magdeburg, Magdeburg, Germany
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Leipziger Str. 44, 39120, Magdeburg, Germany
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19
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Timsina J, Ali M, Do A, Wang L, Sung YJ, Cruchaga C. Harmonization of CSF and imaging biomarkers for Alzheimer's disease biomarkers: need and practical applications for genetics studies and preclinical classification. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.24.542118. [PMID: 37292823 PMCID: PMC10245826 DOI: 10.1101/2023.05.24.542118] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
INTRODUCTION In Alzheimer's disease (AD) research, cerebrospinal fluid (CSF) Amyloid beta (Aβ), Tau and pTau are the most accepted and well validated biomarkers. Several methods and platforms exist to measure those biomarkers which leads to challenges in combining data across studies. Thus, there is a need to identify methods that harmonize and standardize these values. METHODS We used a Z-score based approach to harmonize CSF and amyloid imaging data from multiple cohorts and compared GWAS result using this method with currently accepted methods. We also used a generalized mixture modelling to calculate the threshold for biomarker-positivity. RESULTS Z-scores method performed as well as meta-analysis and did not lead to any spurious results. Cutoffs calculated with this approach were found to be very similar to those reported previously. DISCUSSION This approach can be applied to heterogeneous platforms and provides biomarker cut-offs consistent with the classical approaches without requiring any additional data.
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Affiliation(s)
- Jigyasha Timsina
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Muhammad Ali
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Anh Do
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Lihua Wang
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Yun Ju Sung
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Carlos Cruchaga
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO 63110, USA
- NeuroGenomics and Informatics Center, Washington University School of Medicine, St. Louis, MO 63110, USA
- Hope Center for Neurological Disorders, Washington University School of Medicine, St. Louis, MO 63110, USA
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20
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Gogishvili D, Vromen EM, Koppes-den Hertog S, Lemstra AW, Pijnenburg YAL, Visser PJ, Tijms BM, Del Campo M, Abeln S, Teunissen CE, Vermunt L. Discovery of novel CSF biomarkers to predict progression in dementia using machine learning. Sci Rep 2023; 13:6531. [PMID: 37085545 PMCID: PMC10121677 DOI: 10.1038/s41598-023-33045-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 04/06/2023] [Indexed: 04/23/2023] Open
Abstract
Providing an accurate prognosis for individual dementia patients remains a challenge since they greatly differ in rates of cognitive decline. In this study, we used machine learning techniques with the aim to identify cerebrospinal fluid (CSF) biomarkers that predict the rate of cognitive decline within dementia patients. First, longitudinal mini-mental state examination scores (MMSE) of 210 dementia patients were used to create fast and slow progression groups. Second, we trained random forest classifiers on CSF proteomic profiles and obtained a well-performing prediction model for the progression group (ROC-AUC = 0.82). As a third step, Shapley values and Gini feature importance measures were used to interpret the model performance and identify top biomarker candidates for predicting the rate of cognitive decline. Finally, we explored the potential for each of the 20 top candidates in internal sensitivity analyses. TNFRSF4 and TGF [Formula: see text]-1 emerged as the top markers, being lower in fast-progressing patients compared to slow-progressing patients. Proteins of which a low concentration was associated with fast progression were enriched for cell signalling and immune response pathways. None of our top markers stood out as strong individual predictors of subsequent cognitive decline. This could be explained by small effect sizes per protein and biological heterogeneity among dementia patients. Taken together, this study presents a novel progression biomarker identification framework and protein leads for personalised prediction of cognitive decline in dementia.
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Affiliation(s)
- Dea Gogishvili
- Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands.
| | - Eleonora M Vromen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Sascha Koppes-den Hertog
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Afina W Lemstra
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Yolande A L Pijnenburg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Alzheimer Center Limburg, School for Mental Health and Neuroscience, Maastricht University, Maastricht, The Netherlands
- Department of Neurobiology, Care Sciences and Society, Division of Neurogeriatrics, Karolinska Institutet, Stockholm, Sweden
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Marta Del Campo
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Barcelonabeta Brain Research Center, Pasqual Maragall Foundation, Barcelona, Spain
- Departamento de Ciencias Farmacéuticas y de la Salud, Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Madrid, Spain
| | - Sanne Abeln
- Computer Science, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
- CWI, Amsterdam , The Netherlands
| | - Charlotte E Teunissen
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Lisa Vermunt
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC location VUmc, Amsterdam, The Netherlands
- Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
- Neurochemistry Laboratory, Department of Clinical Chemistry, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
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21
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Vasilevskaya A, Mushtaque A, Tsang MY, Alwazan B, Herridge M, Cheung AM, Tartaglia MC. Sex and age affect acute and persisting COVID-19 illness. Sci Rep 2023; 13:6029. [PMID: 37055492 PMCID: PMC10098246 DOI: 10.1038/s41598-023-33150-x] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 04/07/2023] [Indexed: 04/15/2023] Open
Abstract
Long COVID is associated with neurological and neuropsychiatric manifestations. We conducted an observational study on 97 patients with prior SARS-CoV-2 infection and persisting cognitive complaints that presented to the University Health Network Memory Clinic between October 2020 and December 2021. We assessed the main effects of sex, age, and their interaction on COVID-19 symptoms and outcomes. We also examined the relative contribution of demographics and acute COVID-19 presentation (assessed retrospectively) on persistent neurological symptoms and cognition. Among our cohort, males had higher hospitalization rates than females during the acute COVID-19 illness (18/35 (51%) vs. 15/62 (24%); P = .009). Abnormal scores on cognitive assessments post-COVID were associated with older age (AOR = 0.84; 95% CI 0.74-0.93) and brain fog during initial illness (AOR = 8.80; 95% CI 1.76-65.13). Female sex (ARR = 1.42; 95% CI 1.09-1.87) and acute shortness of breath (ARR = 1.41; 95% CI 1.09-1.84) were associated with a higher risk of experiencing more persistent short-term memory symptoms. Female sex was the only predictor associated with persistent executive dysfunction (ARR = 1.39; 95% CI 1.12-1.76) and neurological symptoms (ARR = 1.66; 95% CI 1.19-2.36). Sex differences were evident in presentations and cognitive outcomes in patients with long COVID.
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Affiliation(s)
- Anna Vasilevskaya
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Division of Neurology, Toronto Western Hospital, University Health Network, 399 Bathurst St. WW5-449, Toronto, ON, M5T 2S8, Canada
- Krembil Research Institute, University Health Network, Toronto, ON, Canada
| | - Asma Mushtaque
- Division of Neurology, Toronto Western Hospital, University Health Network, 399 Bathurst St. WW5-449, Toronto, ON, M5T 2S8, Canada
- Krembil Research Institute, University Health Network, Toronto, ON, Canada
| | - Michelle Y Tsang
- Division of Neurology, Toronto Western Hospital, University Health Network, 399 Bathurst St. WW5-449, Toronto, ON, M5T 2S8, Canada
- Krembil Research Institute, University Health Network, Toronto, ON, Canada
| | - Batoul Alwazan
- Division of Neurology, Toronto Western Hospital, University Health Network, 399 Bathurst St. WW5-449, Toronto, ON, M5T 2S8, Canada
- Krembil Research Institute, University Health Network, Toronto, ON, Canada
- Internal Medicine Board, Kuwait Institution for Medical Specialty (KIMS), Andalous, Kuwait
- Geriatric Medicine, McMaster University, Hamilton, ON, Canada
| | - Margaret Herridge
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Interdepartmental Division of Critical Care Medicine, University of Toronto, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Angela M Cheung
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Toronto General Hospital Research Institute, University Health Network, University of Toronto, Toronto, ON, Canada
| | - Maria Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Toronto, ON, Canada.
- Institute of Medical Science, University of Toronto, Toronto, ON, Canada.
- Division of Neurology, Toronto Western Hospital, University Health Network, 399 Bathurst St. WW5-449, Toronto, ON, M5T 2S8, Canada.
- Krembil Research Institute, University Health Network, Toronto, ON, Canada.
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22
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van 't Hooft JJ, Pelkmans W, Tomassen J, Smits C, Legdeur N, den Braber A, Barkhof F, van Berckel B, Yaqub M, Scheltens P, Pijnenburg YA, Visser PJ, Tijms BM. Distinct disease mechanisms may underlie cognitive decline related to hearing loss in different age groups. J Neurol Neurosurg Psychiatry 2023; 94:314-320. [PMID: 36639225 DOI: 10.1136/jnnp-2022-329726] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 11/21/2022] [Indexed: 01/15/2023]
Abstract
BACKGROUND Hearing loss in older adults is associated with increased dementia risk. Underlying mechanisms that connect hearing loss with dementia remain largely unclear. METHODS We studied the association of hearing loss and biomarkers for dementia risk in two age groups with normal cognition: 65 participants from the European Medical Information Framework (EMIF)-Alzheimer's disease (AD) 90+ study (oldest-old; mean age 92.7 years, 56.9% female) and 60 participants from the EMIF-AD PreclinAD study (younger-old; mean age 74.4, 43.3% female). Hearing function was tested by the 'digits-in-noise test' and cognition by repeated neuropsychological evaluation. Regressions and generalised estimating equations were used to test the association of hearing function and PET-derived amyloid burden, and linear mixed models were used to test the association of hearing function and cognitive decline. In the oldest-old group, mediation analyses were performed to study whether cognitive decline is mediated through regional brain atrophy. RESULTS In oldest-old individuals, hearing function was not associated with amyloid pathology (p=0.7), whereas in the younger-old individuals hearing loss was associated with higher amyloid burden (p=0.0034). In oldest-old individuals, poorer hearing was associated with a steeper decline in memory, global cognition and language, and in the younger-old with steeper decline in language only. The hippocampus and nucleus accumbens mediated the effects of hearing loss on memory and global cognition in the oldest-old individuals. CONCLUSIONS Hearing loss was associated with amyloid binding in younger-old individuals only, and with cognitive decline in both age groups. These results suggest that mechanisms linking hearing loss with risk for dementia depends on age.
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Affiliation(s)
- Jochum J van 't Hooft
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands .,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Wiesje Pelkmans
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Jori Tomassen
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Cas Smits
- Otolaryngology - Head and Neck Surgery, Ear and Hearing, Amsterdam Public Health Research Institute, Amsterdam UMC, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands
| | - Nienke Legdeur
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Anouk den Braber
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.,UCL Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Bart van Berckel
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Maqsood Yaqub
- Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Yolande Al Pijnenburg
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
| | - Pieter Jelle Visser
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands.,Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Alzheimer Center Limburg, Maastricht University, Maastricht, The Netherlands
| | - Betty M Tijms
- Alzheimer Center Amsterdam, Neurology, Vrije Universiteit Amsterdam, Amsterdam UMC Location VUmc, Amsterdam, The Netherlands.,Amsterdam Neuroscience, Neurodegeneration, Amsterdam, The Netherlands
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23
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Zhang H, Wang Z, Chan KH, Shea YF, Lee CY, Chiu PKC, Cao P, Mak HKF. The Use of Diffusion Kurtosis Imaging for the Differential Diagnosis of Alzheimer’s Disease Spectrum. Brain Sci 2023; 13:brainsci13040595. [PMID: 37190560 DOI: 10.3390/brainsci13040595] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2023] [Revised: 03/26/2023] [Accepted: 03/29/2023] [Indexed: 04/03/2023] Open
Abstract
Structural and diffusion kurtosis imaging (DKI) can be used to assess hippocampal macrostructural and microstructural alterations respectively, in Alzheimer’s disease (AD) spectrum, spanning from subjective cognitive decline (SCD) to mild cognitive impairment (MCI) and AD. In this study, we explored the diagnostic performance of structural imaging and DKI of the hippocampus in the AD spectrum. Eleven SCD, thirty-seven MCI, sixteen AD, and nineteen age- and sex-matched normal controls (NCs) were included. Bilateral hippocampal volume, mean diffusivity (MD), and mean kurtosis (MK) were obtained. We detected that in AD vs. NCs, the right hippocampal volume showed the most prominent AUC value (AUC = 0.977); in MCI vs. NCs, the right hippocampal MD was the most sensitive discriminator (AUC = 0.819); in SCD vs. NCs, the left hippocampal MK was the most sensitive biomarker (AUC = 0.775). These findings suggest that, in the predementia stage (SCD and MCI), hippocampal microstructural changes are predominant, and the best discriminators are microstructural measurements (left hippocampal MK for SCD and right hippocampal MD for MCI); while in the dementia stage (AD), hippocampal macrostructural alterations are superior, and the best indicator is the macrostructural index (right hippocampal volume).
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24
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Vasilkovska T, Adhikari M, Van Audekerke J, Salajeghe S, Pustina D, Cachope R, Tang H, Liu L, Munoz-Sanjuan I, Van der Linden A, Verhoye M. Resting-state fMRI reveals longitudinal alterations in brain network connectivity in the zQ175DN mouse model of Huntington's disease. Neurobiol Dis 2023; 181:106095. [PMID: 36963694 DOI: 10.1016/j.nbd.2023.106095] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 03/13/2023] [Accepted: 03/20/2023] [Indexed: 03/26/2023] Open
Abstract
Huntington's disease is an autosomal, dominantly inherited neurodegenerative disease caused by an expansion of the CAG repeats in exon 1 of the huntingtin gene. Neuronal degeneration and dysfunction that precedes regional atrophy result in the impairment of striatal and cortical circuits that affect the brain's large-scale network functionality. However, the evolution of these disease-driven, large-scale connectivity alterations is still poorly understood. Here we used resting-state fMRI to investigate functional connectivity changes in a mouse model of Huntington's disease in several relevant brain networks and how they are affected at different ages that follow a disease-like phenotypic progression. Towards this, we used the heterozygous (HET) form of the zQ175DN Huntington's disease mouse model that recapitulates aspects of human disease pathology. Seed- and Region-based analyses were performed at different ages, on 3-, 6-, 10-, and 12-month-old HET and age-matched wild-type mice. Our results demonstrate decreased connectivity starting at 6 months of age, most prominently in regions such as the retrosplenial and cingulate cortices, pertaining to the default mode-like network and auditory and visual cortices, part of the associative cortical network. At 12 months, we observe a shift towards decreased connectivity in regions such as the somatosensory cortices, pertaining to the lateral cortical network, and the caudate putamen, a constituent of the subcortical network. Moreover, we assessed the impact of distinct Huntington's Disease-like pathology of the zQ175DN HET mice on age-dependent connectivity between different brain regions and networks where we demonstrate that connectivity strength follows a nonlinear, inverted U-shape pattern, a well-known phenomenon of development and normal aging. Conversely, the neuropathologically driven alteration of connectivity, especially in the default mode and associative cortical networks, showed diminished age-dependent evolution of functional connectivity. These findings reveal that in this Huntington's disease model, altered connectivity starts with cortical network aberrations which precede striatal connectivity changes, that appear only at a later age. Taken together, these results suggest that the age-dependent cortical network dysfunction seen in rodents could represent a relevant pathological process in Huntington's disease progression.
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Affiliation(s)
- Tamara Vasilkovska
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium; μNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium.
| | - Mohit Adhikari
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium; μNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Johan Van Audekerke
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium; μNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Somaie Salajeghe
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium
| | | | | | - Haiying Tang
- CHDI Management/CHDI Foundation, Princeton, NJ, USA
| | - Longbin Liu
- CHDI Management/CHDI Foundation, Princeton, NJ, USA
| | | | - Annemie Van der Linden
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium; μNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Marleen Verhoye
- Bio-Imaging Lab, University of Antwerp, Universiteitsplein 1, 2610 Wilrijk, Antwerp, Belgium; μNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
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Economou A, Varlokosta S, Kontari P, Papageorgiou SG. The nonverbal BriefScreen: A cognitive screening method for patients with limited language and motor abilities. APPLIED NEUROPSYCHOLOGY. ADULT 2023; 30:186-193. [PMID: 33980090 DOI: 10.1080/23279095.2021.1920414] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
Dementia and significant cognitive decline are frequent sequelae of stroke, but are difficult to evaluate when aphasia and/or motor impairment are present. The linguistic and motor requirements of commonly employed screening tests render them problematic for use post-stroke. The present study examines the validity of the Nonverbal BriefScreen, a brief screening method with limited verbal and motor requirements, in groups of patients with known cognitive impairment using the MMSE as a gold standard. Participants were 137 healthy middle aged and older community dwellers, 21 patients with MCI/early dementia and 35 patients with different types of dementia. The sensitivity and specificity of the Nonverbal BriefScreen were calculated for various cutoff scores, with the MMSE as comparison. The Nonverbal BriefScreen was effective in discriminating between healthy controls and patients with dementia, as well as between healthy controls and all patients, with areas under the ROC curve similar to that of the MMSE. ROC analyses with a smaller sample of 35 age-matched healthy controls showed adequate discriminant ability to detect cognitive impairment. The Nonverbal BriefScreen was shown to be a valid method for screening for cognitive impairment that could be employed as a screening method for patients with limited language.
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Affiliation(s)
- Alexandra Economou
- Department of Psychology, School of Philosophy, National and Kapodistrian University of Athens, Athens, Greece
| | - Spyridoula Varlokosta
- Department of Linguistics, School of Philology, National and Kapodistrian University of Athens, Athens, Greece
| | - Panagiota Kontari
- School of Psychology, Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Sokratis G Papageorgiou
- Memory, Cognitive Disorders and Rare Dementias Outpatient Unit, 1st Department of Neurology, Eginition University Hospital, National and Kapodistrian University of Athens, Athens, Greece
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Intranasal delivery of full-length anti-Nogo-A antibody: A potential alternative route for therapeutic antibodies to central nervous system targets. Proc Natl Acad Sci U S A 2023; 120:e2200057120. [PMID: 36649432 PMCID: PMC9942809 DOI: 10.1073/pnas.2200057120] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Antibody delivery to the CNS remains a huge hurdle for the clinical application of antibodies targeting a CNS antigen. The blood-brain barrier and blood-CSF barrier restrict access of therapeutic antibodies to their CNS targets in a major way. The very high amounts of therapeutic antibodies that are administered systemically in recent clinical trials to reach CNS targets are barely viable cost-wise for broad, routine applications. Though global CNS delivery of antibodies can be achieved by intrathecal application, these procedures are invasive. A non-invasive method to bring antibodies into the CNS reliably and reproducibly remains an important unmet need in neurology. In the present study, we show that intranasal application of a mouse monoclonal antibody against the neurite growth-inhibiting and plasticity-restricting membrane protein Nogo-A leads to a rapid transfer of significant amounts of antibody to the brain and spinal cord in intact adult rats. Daily intranasal application for 2 wk of anti-Nogo-A antibody enhanced growth and compensatory sprouting of corticofugal projections and functional recovery in rats after large unilateral cortical strokes. These findings are a starting point for clinical translation for a less invasive route of application of therapeutic antibodies to CNS targets for many neurological indications.
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Spooner A, Mohammadi G, Sachdev PS, Brodaty H, Sowmya A. Ensemble feature selection with data-driven thresholding for Alzheimer's disease biomarker discovery. BMC Bioinformatics 2023; 24:9. [PMID: 36624372 PMCID: PMC9830744 DOI: 10.1186/s12859-022-05132-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Accepted: 12/30/2022] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND Feature selection is often used to identify the important features in a dataset but can produce unstable results when applied to high-dimensional data. The stability of feature selection can be improved with the use of feature selection ensembles, which aggregate the results of multiple base feature selectors. However, a threshold must be applied to the final aggregated feature set to separate the relevant features from the redundant ones. A fixed threshold, which is typically used, offers no guarantee that the final set of selected features contains only relevant features. This work examines a selection of data-driven thresholds to automatically identify the relevant features in an ensemble feature selector and evaluates their predictive accuracy and stability. Ensemble feature selection with data-driven thresholding is applied to two real-world studies of Alzheimer's disease. Alzheimer's disease is a progressive neurodegenerative disease with no known cure, that begins at least 2-3 decades before overt symptoms appear, presenting an opportunity for researchers to identify early biomarkers that might identify patients at risk of developing Alzheimer's disease. RESULTS The ensemble feature selectors, combined with data-driven thresholds, produced more stable results, on the whole, than the equivalent individual feature selectors, showing an improvement in stability of up to 34%. The most successful data-driven thresholds were the robust rank aggregation threshold and the threshold algorithm threshold from the field of information retrieval. The features identified by applying these methods to datasets from Alzheimer's disease studies reflect current findings in the AD literature. CONCLUSIONS Data-driven thresholds applied to ensemble feature selectors provide more stable, and therefore more reproducible, selections of features than individual feature selectors, without loss of performance. The use of a data-driven threshold eliminates the need to choose a fixed threshold a-priori and can select a more meaningful set of features. A reliable and compact set of features can produce more interpretable models by identifying the factors that are important in understanding a disease.
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Affiliation(s)
- Annette Spooner
- grid.1005.40000 0004 4902 0432School of Computer Science and Engineering, University of New South Wales, Sydney, Australia
| | - Gelareh Mohammadi
- grid.1005.40000 0004 4902 0432School of Computer Science and Engineering, University of New South Wales, Sydney, Australia
| | - Perminder S. Sachdev
- grid.1005.40000 0004 4902 0432Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Henry Brodaty
- grid.1005.40000 0004 4902 0432Centre for Healthy Brain Ageing (CHeBA), Discipline of Psychiatry & Mental Health, School of Clinical Medicine, University of New South Wales, Sydney, Australia
| | - Arcot Sowmya
- grid.1005.40000 0004 4902 0432School of Computer Science and Engineering, University of New South Wales, Sydney, Australia
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Subramanyam Rallabandi V, Seetharaman K. Classification of cognitively normal controls, mild cognitive impairment and Alzheimer’s disease using transfer learning approach. Biomed Signal Process Control 2023. [DOI: 10.1016/j.bspc.2022.104092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/15/2022]
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29
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Bonvicini G, Syvänen S, Andersson KG, Haaparanta-Solin M, López-Picón F, Sehlin D. ImmunoPET imaging of amyloid-beta in a rat model of Alzheimer's disease with a bispecific, brain-penetrating fusion protein. Transl Neurodegener 2022; 11:55. [PMID: 36567338 PMCID: PMC9791759 DOI: 10.1186/s40035-022-00324-y] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 11/03/2022] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Hijacking the transferrin receptor (TfR) is an effective strategy to transport amyloid-beta (Aβ) immuno-positron emission tomography (immunoPET) ligands across the blood-brain barrier (BBB). Such ligands are more sensitive and specific than small-molecule ligands at detecting Aβ pathology in mouse models of Alzheimer's disease (AD). This study aimed to determine if this strategy would be as sensitive in rats and to assess how TfR affinity affects BBB transport of bispecific immunoPET radioligands. METHODS Two affinity variants of the rat TfR antibody, OX26, were chemically conjugated to a F(ab')2 fragment of the anti-Aβ antibody, bapineuzumab (Bapi), to generate two bispecific fusion proteins: OX265-F(ab')2-Bapi and OX2676-F(ab')2-Bapi. Pharmacokinetic analyses were performed 4 h and 70 h post-injection of radioiodinated fusion proteins in wild-type (WT) rats. [124I]I-OX265-F(ab')2-Bapi was administered to TgF344-AD and WT rats for in vivo PET imaging. Ex vivo distribution of injected [124I]I-OX265-F(ab')2-Bapi and Aβ pathology were assessed. RESULTS More [125I]I-OX265-F(ab')2-Bapi was taken up into the brain 4 h post-administration than [124I]I-OX2676-F(ab')2-Bapi. [124I]I-OX265-F(ab')2-Bapi PET visualized Aβ pathology with significantly higher signals in the TgF344-AD rats than in the WT littermates without Aβ pathology. The PET signals significantly correlated with Aβ levels in AD animals. CONCLUSION Affinity to TfR affects how efficiently a TfR-targeting bispecific fusion protein will cross the BBB, such that the higher-affinity bispecific fusion protein crossed the BBB more efficiently. Furthermore, bispecific immunoPET imaging of brain Aβ pathology using TfR-mediated transport provides good imaging contrast between TgF344-AD and WT rats, suggesting that this immunoPET strategy has the potential to be translated to higher species.
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Affiliation(s)
- Gillian Bonvicini
- grid.8993.b0000 0004 1936 9457Department of Public Health and Caring Sciences, Uppsala University, 751 85 Uppsala, Sweden ,BioArctic AB, 112 51 Stockholm, Sweden
| | - Stina Syvänen
- grid.8993.b0000 0004 1936 9457Department of Public Health and Caring Sciences, Uppsala University, 751 85 Uppsala, Sweden
| | | | - Merja Haaparanta-Solin
- grid.1374.10000 0001 2097 1371Preclinical Imaging Laboratory, Turku PET Centre, University of Turku, 20520 Turku, Finland ,grid.1374.10000 0001 2097 1371MediCity Research Laboratory, University of Turku, 20520 Turku, Finland
| | - Francisco López-Picón
- grid.1374.10000 0001 2097 1371Preclinical Imaging Laboratory, Turku PET Centre, University of Turku, 20520 Turku, Finland ,grid.1374.10000 0001 2097 1371MediCity Research Laboratory, University of Turku, 20520 Turku, Finland
| | - Dag Sehlin
- grid.8993.b0000 0004 1936 9457Department of Public Health and Caring Sciences, Uppsala University, 751 85 Uppsala, Sweden
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Reemst K, Kracht L, Kotah JM, Rahimian R, van Irsen AAS, Congrains Sotomayor G, Verboon LN, Brouwer N, Simard S, Turecki G, Mechawar N, Kooistra SM, Eggen BJL, Korosi A. Early-life stress lastingly impacts microglial transcriptome and function under basal and immune-challenged conditions. Transl Psychiatry 2022; 12:507. [PMID: 36481769 PMCID: PMC9731997 DOI: 10.1038/s41398-022-02265-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 11/18/2022] [Accepted: 11/23/2022] [Indexed: 12/13/2022] Open
Abstract
Early-life stress (ELS) leads to increased vulnerability to psychiatric disorders including depression later in life. Neuroinflammatory processes have been implicated in ELS-induced negative health outcomes, but how ELS impacts microglia, the main tissue-resident macrophages of the central nervous system, is unknown. Here, we determined the effects of ELS-induced by limited bedding and nesting material during the first week of life (postnatal days [P]2-9) on microglial (i) morphology; (ii) hippocampal gene expression; and (iii) synaptosome phagocytic capacity in male pups (P9) and adult (P200) mice. The hippocampus of ELS-exposed adult mice displayed altered proportions of morphological subtypes of microglia, as well as microglial transcriptomic changes related to the tumor necrosis factor response and protein ubiquitination. ELS exposure leads to distinct gene expression profiles during microglial development from P9 to P200 and in response to an LPS challenge at P200. Functionally, synaptosomes from ELS-exposed mice were phagocytosed less by age-matched microglia. At P200, but not P9, ELS microglia showed reduced synaptosome phagocytic capacity when compared to control microglia. Lastly, we confirmed the ELS-induced increased expression of the phagocytosis-related gene GAS6 that we observed in mice, in the dentate gyrus of individuals with a history of child abuse using in situ hybridization. These findings reveal persistent effects of ELS on microglial function and suggest that altered microglial phagocytic capacity is a key contributor to ELS-induced phenotypes.
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Affiliation(s)
- Kitty Reemst
- grid.7177.60000000084992262Swammerdam Institute for Life Sciences, Center for Neuroscience, Brain Plasticity Group, University of Amsterdam, Amsterdam, Science Park 904, 1098 XH The Netherlands
| | - Laura Kracht
- grid.4494.d0000 0000 9558 4598Department of Biomedical Sciences of Cells & Systems, Section Molecular Neurobiology, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 1, 9713 AV Groningen, The Netherlands
| | - Janssen M. Kotah
- grid.7177.60000000084992262Swammerdam Institute for Life Sciences, Center for Neuroscience, Brain Plasticity Group, University of Amsterdam, Amsterdam, Science Park 904, 1098 XH The Netherlands
| | - Reza Rahimian
- grid.412078.80000 0001 2353 5268McGill Group for Suicide Studies, Douglas Hospital Research Center, Montreal, QC H4H 1R3 Canada ,grid.14709.3b0000 0004 1936 8649Department of Psychiatry, McGill University, Montreal, QC H3A 1A1 Canada
| | - Astrid A. S. van Irsen
- grid.7177.60000000084992262Swammerdam Institute for Life Sciences, Center for Neuroscience, Brain Plasticity Group, University of Amsterdam, Amsterdam, Science Park 904, 1098 XH The Netherlands
| | - Gonzalo Congrains Sotomayor
- grid.7177.60000000084992262Swammerdam Institute for Life Sciences, Center for Neuroscience, Brain Plasticity Group, University of Amsterdam, Amsterdam, Science Park 904, 1098 XH The Netherlands
| | - Laura N. Verboon
- grid.7177.60000000084992262Swammerdam Institute for Life Sciences, Center for Neuroscience, Brain Plasticity Group, University of Amsterdam, Amsterdam, Science Park 904, 1098 XH The Netherlands
| | - Nieske Brouwer
- grid.4494.d0000 0000 9558 4598Department of Biomedical Sciences of Cells & Systems, Section Molecular Neurobiology, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 1, 9713 AV Groningen, The Netherlands
| | - Sophie Simard
- grid.412078.80000 0001 2353 5268McGill Group for Suicide Studies, Douglas Hospital Research Center, Montreal, QC H4H 1R3 Canada ,grid.14709.3b0000 0004 1936 8649Department of Psychiatry, McGill University, Montreal, QC H3A 1A1 Canada
| | - Gustavo Turecki
- grid.412078.80000 0001 2353 5268McGill Group for Suicide Studies, Douglas Hospital Research Center, Montreal, QC H4H 1R3 Canada ,grid.14709.3b0000 0004 1936 8649Department of Psychiatry, McGill University, Montreal, QC H3A 1A1 Canada
| | - Naguib Mechawar
- grid.412078.80000 0001 2353 5268McGill Group for Suicide Studies, Douglas Hospital Research Center, Montreal, QC H4H 1R3 Canada ,grid.14709.3b0000 0004 1936 8649Department of Psychiatry, McGill University, Montreal, QC H3A 1A1 Canada
| | - Susanne M. Kooistra
- grid.4494.d0000 0000 9558 4598Department of Biomedical Sciences of Cells & Systems, Section Molecular Neurobiology, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 1, 9713 AV Groningen, The Netherlands
| | - Bart J. L. Eggen
- grid.4494.d0000 0000 9558 4598Department of Biomedical Sciences of Cells & Systems, Section Molecular Neurobiology, University of Groningen, University Medical Center Groningen, Antonius Deusinglaan 1, 9713 AV Groningen, The Netherlands
| | - Aniko Korosi
- Swammerdam Institute for Life Sciences, Center for Neuroscience, Brain Plasticity Group, University of Amsterdam, Amsterdam, Science Park 904, 1098 XH, The Netherlands.
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Falangola MF, Nie X, Voltin J, Ward R, Dhiman S, Nietert PJ, Jensen JH. Brain microstructure abnormalities in the 3xTg-AD mouse - A diffusion MRI and morphology correlation study. Magn Reson Imaging 2022; 94:48-55. [PMID: 36116712 PMCID: PMC9695071 DOI: 10.1016/j.mri.2022.09.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 08/26/2022] [Accepted: 09/13/2022] [Indexed: 10/14/2022]
Abstract
The widely studied triple transgenic (3xTg-AD) mouse provides a robust model of Alzheimer's disease (AD) with region dependent patterns of progressive amyloid-β (Aß) and tau pathology. Using diffusion MRI (dMRI), we investigated the sensitivity of dMRI measures in capturing AD pathology associated microstructure alterations in older 3xTg-AD mice, and the degree to which dMRI changes correlate with measurements of Aβ and tau pathology. 3xTg-AD and normal control (NC) mice, 15 to 21 months of age, were used in this study. In vivo dMRI data were acquired for the generation of diffusion tensor (DT) and diffusional kurtosis (DK) measures within the hippocampus and fimbria (Fi). For these same brain regions, Aβ and tau pathology were quantified by morphological analysis of Aß1-42 and AT8 immunoreactivity. Two-tailed, two-sample t-tests were performed to assess group differences in each brain region of interest (ROI), with the Benjamini-Hochberg false discovery rate (FDR) method being applied to adjust for multiple comparisons. Spearman correlation coefficients were calculated to investigate associations between diffusion and morphological measures. Our results revealed, depending on the brain region, DT and DK measures were able to detect group differences. In the dorsal hippocampus (HD), fractional anisotropy (FA) was significantly higher in the 3xTg-AD mice compared with NC mice. In the subiculum (SUB), FA, axial diffusivity (D||) and radial kurtosis (K┴) were significantly higher in 3xTg-AD mice compared with NC mice. Morphological quantification of Aß1-42 and AT8 immunoreactivity showed elevated Aß and tau in the Fi, ventral hippocampus (HV) and SUB of 3xTg-AD mice. The presence of Aβ and tau was significantly correlated with several DT and DK measures, particularly in the SUB, where an increase in tau correlated with an increase in mean kurtosis (MK) and K┴. This work demonstrates significant dMRI differences between older 3xTg-AD and NC mice in the hippocampus and Fi. Significant correlations were found between dMRI and morphological measures of Aβ and tau pathology. These results support the potential of dMRI-derived parameters as biomarkers of AD pathology. Since the imaging methods employed here are easily translatable to clinical MRI, our results are also relevant for human AD patients.
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Affiliation(s)
- Maria Fatima Falangola
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA; Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA.
| | - Xingju Nie
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA; Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA
| | - Joshua Voltin
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA; Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA
| | - Ralph Ward
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Siddhartha Dhiman
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA
| | - Paul J Nietert
- Department of Public Health Sciences, Medical University of South Carolina, Charleston, SC, USA
| | - Jens H Jensen
- Department of Neuroscience, Medical University of South Carolina, Charleston, SC, USA; Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA
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Kor DZL, Jbabdi S, Huszar IN, Mollink J, Tendler BC, Foxley S, Wang C, Scott C, Smart A, Ansorge O, Pallebage-Gamarallage M, Miller KL, Howard AFD. An automated pipeline for extracting histological stain area fraction for voxelwise quantitative MRI-histology comparisons. Neuroimage 2022; 264:119726. [PMID: 36368503 PMCID: PMC10933753 DOI: 10.1016/j.neuroimage.2022.119726] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2022] [Revised: 10/27/2022] [Accepted: 10/31/2022] [Indexed: 11/11/2022] Open
Abstract
The acquisition of MRI and histology in the same post-mortem tissue sample enables direct correlation between MRI and histologically-derived parameters. However, there still lacks a standardised automated pipeline to process histology data, with most studies relying on manual intervention. Here, we introduce an automated pipeline to extract a quantitative histological measure for staining density (stain area fraction, SAF) from multiple immunohistochemical (IHC) stains. The pipeline is designed to directly address key IHC artefacts related to tissue staining and slide digitisation. Here, the pipeline was applied to post-mortem human brain data from multiple subjects, relating MRI parameters (FA, MD, RD, AD, R2*, R1) to IHC slides stained for myelin, neurofilaments, microglia and activated microglia. Utilising high-quality MRI-histology co-registrations, we then performed whole-slide voxelwise comparisons (simple correlations, partial correlations and multiple regression analyses) between multimodal MRI- and IHC-derived parameters. The pipeline was found to be reproducible, robust to artefacts and generalisable across multiple IHC stains. Our partial correlation results suggest that some simple MRI-SAF correlations should be interpreted with caution, due to the co-localisation of other tissue features (e.g., myelin and neurofilaments). Further, we find activated microglia-a generic biomarker of inflammation-to consistently be the strongest predictor of high DTI FA and low RD, which may suggest sensitivity of diffusion MRI to aspects of neuroinflammation related to microglial activation, even after accounting for other microstructural changes (demyelination, axonal loss and general microglia infiltration). Together, these results show the utility of this approach in carefully curating IHC data and performing multimodal analyses to better understand microstructural relationships with MRI.
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Affiliation(s)
- Daniel Z L Kor
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom.
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Istvan N Huszar
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Jeroen Mollink
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Sean Foxley
- Department of Radiology, University of Chicago, Chicago, IL, United States of America
| | - Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Connor Scott
- Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Adele Smart
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom; Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Olaf Ansorge
- Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Menuka Pallebage-Gamarallage
- Academic Unit of Neuropathology, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
| | - Amy F D Howard
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Headington, Oxford OX3 9DU, , United Kingdom
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Maharjan S, Tsai AP, Lin PB, Ingraham C, Jewett MR, Landreth GE, Oblak AL, Wang N. Age-dependent microstructure alterations in 5xFAD mice by high-resolution diffusion tensor imaging. Front Neurosci 2022; 16:964654. [PMID: 36061588 PMCID: PMC9428354 DOI: 10.3389/fnins.2022.964654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Accepted: 07/18/2022] [Indexed: 11/23/2022] Open
Abstract
Purpose To evaluate the age-dependent microstructure changes in 5xFAD mice using high-resolution diffusion tensor imaging (DTI). Methods The 5xFAD mice at 4, 7.5, and 12 months and the wild-type controls at 4 months were scanned at 9.4T using a 3D echo-planar imaging (EPI) pulse sequence with the isotropic spatial resolution of 100 μm. The b-value was 3000 s/mm2 for all the diffusion MRI scans. The samples were also acquired with a gradient echo pulse sequence at 50 μm isotropic resolution. The microstructure changes were quantified with DTI metrics, including fractional anisotropy (FA) and mean diffusivity (MD). The conventional histology was performed to validate with MRI findings. Results The FA values (p = 0.028) showed significant differences in the cortex between wild-type (WT) and 5xFAD mice at 4 months, while hippocampus, anterior commissure, corpus callosum, and fornix showed no significant differences for either FA and MD. FA values of 5xFAD mice gradually decreased in cortex (0.140 ± 0.007 at 4 months, 0.132 ± 0.008 at 7.5 months, 0.126 ± 0.013 at 12 months) and fornix (0.140 ± 0.007 at 4 months, 0.132 ± 0.008 at 7.5 months, 0.126 ± 0.013 at 12 months) with aging. Both FA (p = 0.029) and MD (p = 0.037) demonstrated significant differences in corpus callosum between 4 and 12 months age old. FA and MD were not significantly different in the hippocampus or anterior commissure. The age-dependent microstructure alterations were better captured by FA when compared to MD. Conclusion FA showed higher sensitivity to monitor amyloid deposition in 5xFAD mice. DTI may be utilized as a sensitive biomarker to monitor beta-amyloid progression for preclinical studies.
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Affiliation(s)
- Surendra Maharjan
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
| | - Andy P. Tsai
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Peter B. Lin
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Cynthia Ingraham
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Megan R. Jewett
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
| | - Gary E. Landreth
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
- Department of Anatomy, Cell Biology and Physiology, Indiana University, Indianapolis, IN, United States
| | - Adrian L. Oblak
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
| | - Nian Wang
- Department of Radiology and Imaging Sciences, Indiana University, Indianapolis, IN, United States
- Stark Neurosciences Research Institute, Indiana University, Indianapolis, IN, United States
- *Correspondence: Nian Wang,
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Dual PET-fMRI reveals a link between neuroinflammation, amyloid binding and compensatory task-related brain activity in Alzheimer's disease. Commun Biol 2022; 5:804. [PMID: 35948611 PMCID: PMC9365841 DOI: 10.1038/s42003-022-03761-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Accepted: 07/22/2022] [Indexed: 11/17/2022] Open
Abstract
The interplay among neuropathological mechanisms underlying Alzheimer’s disease (AD), as neuroinflammation and amyloid-beta (Aβ), as well their impact on neuronal function remains elusive. A major gap in knowledge is the functional impact of neuroinflammation. The posterior cingulate cortex (PCC), as the most prominent site of amyloid pathology in AD, is a pivotal region to investigate the concomitant presence of pathophysiological mechanisms such as microglia activation, indexing neuroinflammation, and changes in task related activity. Here we used a dual PET approach to simultaneously study Aβ load and neuroinflammation (TSPO uptake marker), using 11C-PiB and 11C-PK11195 radiotracers, respectively and fMRI to study task related neural activation in an AD sample (n = 19) and matched controls (n = 19). Here we show significantly increased Aβ deposition, neuroinflammation and brain activity related to a visual object working memory task in this key region. Microglia activation was associated with increased brain activity specifically in patients, independently of amyloid binding, raising the possibility that abnormal brain activity might be restored in clinical trials aimed at reducing microglia activation. Multimodal PET-fMRI imaging of Alzheimer’s disease patients and healthy controls suggests that microglia activation in the posterior cingulate cortex is associated with increased brain activity in Alzheimer’s disease, and independent of amyloid accumulation.
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Sharf T, van der Molen T, Glasauer SMK, Guzman E, Buccino AP, Luna G, Cheng Z, Audouard M, Ranasinghe KG, Kudo K, Nagarajan SS, Tovar KR, Petzold LR, Hierlemann A, Hansma PK, Kosik KS. Functional neuronal circuitry and oscillatory dynamics in human brain organoids. Nat Commun 2022; 13:4403. [PMID: 35906223 PMCID: PMC9338020 DOI: 10.1038/s41467-022-32115-4] [Citation(s) in RCA: 52] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 07/18/2022] [Indexed: 12/30/2022] Open
Abstract
Human brain organoids replicate much of the cellular diversity and developmental anatomy of the human brain. However, the physiology of neuronal circuits within organoids remains under-explored. With high-density CMOS microelectrode arrays and shank electrodes, we captured spontaneous extracellular activity from brain organoids derived from human induced pluripotent stem cells. We inferred functional connectivity from spike timing, revealing a large number of weak connections within a skeleton of significantly fewer strong connections. A benzodiazepine increased the uniformity of firing patterns and decreased the relative fraction of weakly connected edges. Our analysis of the local field potential demonstrate that brain organoids contain neuronal assemblies of sufficient size and functional connectivity to co-activate and generate field potentials from their collective transmembrane currents that phase-lock to spiking activity. These results point to the potential of brain organoids for the study of neuropsychiatric diseases, drug action, and the effects of external stimuli upon neuronal networks.
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Affiliation(s)
- Tal Sharf
- Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA, 93106, USA. .,Department of Molecular, Cellular and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA, 93106, USA. .,Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, 95064, USA.
| | - Tjitse van der Molen
- Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA, 93106, USA.,Department of Molecular, Cellular and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Stella M K Glasauer
- Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA, 93106, USA.,Department of Molecular, Cellular and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Elmer Guzman
- Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA, 93106, USA.,Department of Molecular, Cellular and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Alessio P Buccino
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Gabriel Luna
- Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA, 93106, USA.,Department of Molecular, Cellular and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Zhuowei Cheng
- Department of Computer Science, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Morgane Audouard
- Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA, 93106, USA.,Department of Molecular, Cellular and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Kamalini G Ranasinghe
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Kiwamu Kudo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Srikantan S Nagarajan
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Kenneth R Tovar
- Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Linda R Petzold
- Department of Computer Science, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Andreas Hierlemann
- Department of Biosystems Science and Engineering, ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Paul K Hansma
- Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA, 93106, USA.,Department of Physics, University of California Santa Barbara, Santa Barbara, CA, 93106, USA
| | - Kenneth S Kosik
- Neuroscience Research Institute, University of California Santa Barbara, Santa Barbara, CA, 93106, USA. .,Department of Molecular, Cellular and Developmental Biology, University of California Santa Barbara, Santa Barbara, CA, 93106, USA.
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Faldu KG, Shah JS. Alzheimer's disease: a scoping review of biomarker research and development for effective disease diagnosis. Expert Rev Mol Diagn 2022; 22:681-703. [PMID: 35855631 DOI: 10.1080/14737159.2022.2104639] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022]
Abstract
INTRODUCTION Alzheimer's disease (AD) is regarded as the foremost reason for neurodegeneration that prominently affects the geriatric population. Characterized by extracellular accumulation of amyloid-beta (Aβ), intracellular aggregation of hyperphosphorylated tau (p-tau), and neuronal degeneration that causes impairment of memory and cognition. Amyloid/tau/neurodegeneration (ATN) classification is utilized for research purposes and involves amyloid, tau, and neuronal injury staging through MRI, PET scanning, and CSF protein concentration estimations. CSF sampling is invasive, and MRI and PET scanning requires sophisticated radiological facilities which limit its widespread diagnostic use. ATN classification lacks effectiveness in preclinical AD. AREAS COVERED This publication intends to collate and review the existing biomarker profile and the current research and development of a new arsenal of biomarkers for AD pathology from different biological samples, microRNA (miRNA), proteomics, metabolomics, artificial intelligence, and machine learning for AD screening, diagnosis, prognosis, and monitoring of AD treatments. EXPERT OPINION It is an accepted observation that AD-related pathological changes occur over a long period of time before the first symptoms are observed providing ample opportunity for detection of biological alterations in various biological samples that can aid in early diagnosis and modify treatment outcomes.
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Affiliation(s)
- Khushboo Govind Faldu
- Department of Pharmacology, Institute of Pharmacy, Nirma University, Ahmedabad, Gujarat, India
| | - Jigna Samir Shah
- Department of Pharmacology, Institute of Pharmacy, Nirma University, Ahmedabad, Gujarat, India
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37
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Wilson KM, Katona E, Glaria I, Carcolé M, Swift IJ, Sogorb-Esteve A, Heller C, Bouzigues A, Heslegrave AJ, Keshavan A, Knowles K, Patil S, Mohapatra S, Liu Y, Goyal J, Sanchez-Valle R, Laforce RJ, Synofzik M, Rowe JB, Finger E, Vandenberghe R, Butler CR, Gerhard A, Van Swieten JC, Seelaar H, Borroni B, Galimberti D, de Mendonça A, Masellis M, Tartaglia MC, Otto M, Graff C, Ducharme S, Schott JM, Malaspina A, Zetterberg H, Boyanapalli R, Rohrer JD, Isaacs AM. Development of a sensitive trial-ready poly(GP) CSF biomarker assay for C9orf72-associated frontotemporal dementia and amyotrophic lateral sclerosis. J Neurol Neurosurg Psychiatry 2022; 93:761-771. [PMID: 35379698 PMCID: PMC9279742 DOI: 10.1136/jnnp-2021-328710] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/21/2021] [Accepted: 03/04/2022] [Indexed: 01/15/2023]
Abstract
OBJECTIVE A GGGGCC repeat expansion in the C9orf72 gene is the most common cause of genetic frontotemporal dementia (FTD) and amyotrophic lateral sclerosis (ALS). As potential therapies targeting the repeat expansion are now entering clinical trials, sensitive biomarker assays of target engagement are urgently required. Our objective was to develop such an assay. METHODS We used the single molecule array (Simoa) platform to develop an immunoassay for measuring poly(GP) dipeptide repeat proteins (DPRs) generated by the C9orf72 repeat expansion in cerebrospinal fluid (CSF) of people with C9orf72-associated FTD/ALS. RESULTS AND CONCLUSIONS We show the assay to be highly sensitive and robust, passing extensive qualification criteria including low intraplate and interplate variability, a high precision and accuracy in measuring both calibrators and samples, dilutional parallelism, tolerance to sample and standard freeze-thaw and no haemoglobin interference. We used this assay to measure poly(GP) in CSF samples collected through the Genetic FTD Initiative (N=40 C9orf72 and 15 controls). We found it had 100% specificity and 100% sensitivity and a large window for detecting target engagement, as the C9orf72 CSF sample with the lowest poly(GP) signal had eightfold higher signal than controls and on average values from C9orf72 samples were 38-fold higher than controls, which all fell below the lower limit of quantification of the assay. These data indicate that a Simoa-based poly(GP) DPR assay is suitable for use in clinical trials to determine target engagement of therapeutics aimed at reducing C9orf72 repeat-containing transcripts.
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Affiliation(s)
- Katherine M Wilson
- UK Dementia Research Institute at UCL, UCL Queen Square Institute of Neurology, London, UK
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Eszter Katona
- UK Dementia Research Institute at UCL, UCL Queen Square Institute of Neurology, London, UK
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Idoia Glaria
- UK Dementia Research Institute at UCL, UCL Queen Square Institute of Neurology, London, UK
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Mireia Carcolé
- UK Dementia Research Institute at UCL, UCL Queen Square Institute of Neurology, London, UK
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Imogen J Swift
- UK Dementia Research Institute at UCL, UCL Queen Square Institute of Neurology, London, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Aitana Sogorb-Esteve
- UK Dementia Research Institute at UCL, UCL Queen Square Institute of Neurology, London, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Carolin Heller
- UK Dementia Research Institute at UCL, UCL Queen Square Institute of Neurology, London, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Arabella Bouzigues
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Amanda J Heslegrave
- UK Dementia Research Institute at UCL, UCL Queen Square Institute of Neurology, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Kathryn Knowles
- UK Dementia Research Institute at UCL, UCL Queen Square Institute of Neurology, London, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | | | | | - Yuanjing Liu
- Wave Life Sciences, Cambridge, Massachusetts, USA
| | - Jaya Goyal
- Wave Life Sciences, Cambridge, Massachusetts, USA
| | - Raquel Sanchez-Valle
- Alzheimer's Disease and Other Cognitive Disorders Unit, Neurology Service, Hospital Clínic, Institut d'Investigacións Biomèdiques August Pi I Sunyer, University of Barcelona, Barcelona, Spain
| | - Robert Jr Laforce
- Clinique Interdisciplinaire de Mémoire, Département des Sciences Neurologiques, CHU de Québec, and Faculté de Médecine, Université Laval, Quebec City, Quebec, Canada
| | - Matthis Synofzik
- Department of Neurodegenerative Diseases, Hertie-Institute for Clinical Brain Research and Center of Neurology, University of Tübingen, Tübingen, Germany
- Center for Neurodegenerative Diseases, (DZNE), Tübingen, Germany
| | - James B Rowe
- Department of Clinical Neurosciences and Cambridge University Hospitals NHS Trust and Medical Research Council Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, UK
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, University of Western Ontario, University of Western Ontario, London, Ontario, Canada
| | - Rik Vandenberghe
- Leuven Brain Institute, KU Leuven, Leuven, Belgium
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
- Neurology Service, University Hospitals, Leuven, Belgium
| | - Christopher R Butler
- Nuffield Department of Clinical Neurosciences, Medical Sciences Division, University of Oxford, Oxford, UK
- Department of Brain Sciences, Imperial College London, London, UK
| | - Alexander Gerhard
- Division of Neuroscience and Experimental Psychology, Wolfson Molecular Imaging Centre, The University of Manchester, Manchester, UK
- Departments of Geriatric Medicine and Nuclear Medicine, University of Duisburg- Essen, University of Duisburg- Essen, Essen, Germany
| | | | - Harro Seelaar
- Department of Neurology, Erasmus Medical Centre, Rotterdam, Netherlands
| | - Barbara Borroni
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Daniela Galimberti
- Fondazione IRCCS Ca' Granda, Ospedale Maggiore Policlinico, Milan, Italy
- Centro Dino Ferrari, University of Milan, Milan, Italy
| | | | - Mario Masellis
- Sunnybrook Health Sciences Centre, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - M Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Disease, University of Toronto, Toronto, Ontario, Canada
- Canadian Sports Concussion Project, Toronto, Ontario, Canada
| | - Markus Otto
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Caroline Graff
- Center for Alzheimer Research, Division of Neurogeriatrics, Department of Neurobiology, Care Sciences and Society, Bioclinicum, Karolinska Institutet, Solna, Sweden
- Unit for Hereditary Dementias, Theme Aging, Karolinska University Hospital, Solna, Sweden
| | - Simon Ducharme
- McConnell Brain Imaging Centre, Montreal Neurological Institute, McGill University, Montreal, Québec, Canada
- Department of Psychiatry, Douglas Mental Health University Institute, McGill University, Montreal, Quebec, Canada
| | - Jonathan M Schott
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Andrea Malaspina
- Barts and The London School of Medicine and Dentistry Blizard Institute, London, UK
- UCL Queen Square Motor Neuron Disease Centre, Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, UCL, London, UK
| | - Henrik Zetterberg
- UK Dementia Research Institute at UCL, UCL Queen Square Institute of Neurology, London, UK
- Department of Psychiatry and Neurochemistry, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
| | | | - Jonathan D Rohrer
- UK Dementia Research Institute at UCL, UCL Queen Square Institute of Neurology, London, UK
- Dementia Research Centre, Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
| | - Adrian M Isaacs
- UK Dementia Research Institute at UCL, UCL Queen Square Institute of Neurology, London, UK
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, London, UK
- UCL Queen Square Motor Neuron Disease Centre, Department of Neuromuscular Diseases, UCL Queen Square Institute of Neurology, UCL, London, UK
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Taha HT, Chad JA, Chen JJ. DKI enhances the sensitivity and interpretability of age-related DTI patterns in the white matter of UK biobank participants. Neurobiol Aging 2022; 115:39-49. [PMID: 35468551 DOI: 10.1016/j.neurobiolaging.2022.03.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2021] [Revised: 03/09/2022] [Accepted: 03/12/2022] [Indexed: 12/25/2022]
Abstract
Studies of healthy brain aging traditionally report diffusivity patterns associated with white matter degeneration using diffusion tensor imaging (DTI), which assumes that diffusion measured at typical b-values (approximately 1000 s/mm2) is Gaussian. Diffusion kurtosis imaging (DKI) is an extension of DTI that measures non-Gaussian diffusion (kurtosis) to better capture microenvironmental processes by incorporating additional data at a higher b-value. In this study, using diffusion data (b-values of 1000 and 2000 s/mm2) from 700 UK Biobank participants aged 46-80, we investigate (1) the extent of novel information gained from adding diffusional kurtosis to diffusivity observations in aging, and (2) how conventional DTI metrics in aging compare with diffusivity metrics derived from DKI, which are corrected for kurtosis. We establish a pattern of lower kurtosis alongside higher diffusivity among older adults, with kurtosis generally being more sensitive to age than diffusivity. We also find discrepancies between diffusivity metrics derived from DTI and DKI, emphasizing the importance of accounting for non-Gaussian diffusion when interpreting age-related diffusivity patterns.
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Affiliation(s)
- Hiba T Taha
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Institute of Medical Science, University of Toronto, Toronto, Ontario, Canada
| | - Jordan A Chad
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - J Jean Chen
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada; Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario, Canada.
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Investigating the use of plasma pTau181 in retired contact sports athletes. J Neurol 2022; 269:5582-5595. [PMID: 35751688 DOI: 10.1007/s00415-022-11223-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 05/26/2022] [Accepted: 06/09/2022] [Indexed: 10/17/2022]
Abstract
BACKGROUND Considering the wide range of outcomes following sport-related concussions, biomarkers are needed to detect underlying pathological changes. The objective was to analyze the use of plasma phosphorylated tau 181 (pTau181) as a non-invasive measure of underlying brain changes in a cohort of retired contact sports athletes at risk of neurodegeneration. METHODS Fifty-four retired contact sport athletes and 27 healthy controls whose blood plasma was analyzed for pTau181 were included. A portion (N = 21) of retired athletes had a 2-years follow-up visit. All participants had completed a neuropsychological battery and MRI imaging. RESULTS Plasma pTau181 was significantly higher in retired athletes compared to healthy controls (8.94 ± 5.08 pg/mL vs. 6.00 ± 2.53 pg/mL, respectively; 95% BCa CI 1.38-4.62; p = 0.02); and was significantly associated with fornix fractional anisotropy values only in the athletes group (β = - 0.002; 95% BCa CI - 0.003 to - 0.001; p = 0.002). When the retired athletes cohort was divided into high vs. normal pTau181 groups, the corpus callosum (CC) volume and white-matter integrity was significantly lower in high pTau181 compared to older healthy controls (CC volume: 1.57 ± 0.19 vs. 2.02 ± 0.32, p = 0.002; CC medial diffusivity: 0.96 ± 0.04 × 10-3 mm2/s vs. 0.90 ± 0.03 × 10-3 mm2/s, p = 0.003; CC axial diffusivity: 1.49 ± 0.04 × 10-3 mm2/s vs. 1.41 ± 0.02 × 10-3 mm2/s, p < 0.001, respectively). CONCLUSIONS Although high plasma pTau181 levels were associated with abnormalities in CC and fornix, baseline pTau181 did not predict longitudinal changes in regional brain volumes or white-matter integrity in the athletes. pTau181 may be useful for identifying those with brain abnormalities related to repeated concussion but not for predicting progression.
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40
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Asmuje NF, Mat S, Myint PK, Tan MP. Blood Pressure Variability and Cognitive Function: a Scoping Review. Curr Hypertens Rep 2022; 24:375-383. [PMID: 35731334 DOI: 10.1007/s11906-022-01200-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/16/2022] [Indexed: 11/03/2022]
Abstract
PURPOSE OF REVIEW To conduct a scoping review of articles which have evaluated BPV and cognitive function. Articles with keywords, titles or abstracts containing the terms 'cognitive' OR 'cognition' OR 'dementia' AND 'blood pressure variability' were identified from CINAHL, Medline, PMC and Web of Science. RECENT FINDINGS Methods of acquisition and analysis of BPV and cognitive measurements and their relationship were extracted from selected articles. Of 656 studies identified, 53 articles were selected. Twenty-five evaluated long-term (LTBPV), nine mid-term (MTBPV), 12 short-term (STBPV) and nine very short-term BPV (VSTBPV) with conflicting findings on the relationship between BPV and cognition. Variations existed in devices, period and procedure for acquisition. The studies also utilized a wide range of methods of BPV calculation. Thirteen cognitive assessment tools were used to measure global cognition or domain functions which were influenced by the population of interest. The interpretation of available studies was hence limited by heterogeneity. There is an urgent need for standardization of BPV assessments to streamline research on BPV and cognition. Future studies should also establish whether BPV could be a potential modifiable risk factor for cognitive decline, as well as a marker for treatment response.
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Affiliation(s)
- Nur Fazidah Asmuje
- Kolej Genius Insan, Universiti Sains Islam Malaysia, Negeri Sembilan, Malaysia. .,Ageing and Age-Associated Disorders Research Group, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia.
| | - Sumaiyah Mat
- Physiotherapy Programme and Center of Healthy Ageing and Wellness, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Bangi, Malaysia
| | - Phyo Kyaw Myint
- Ageing Clinical & Experimental Research (ACER) Team, Institute of Applied Health Sciences, University of Aberdeen, Aberdeen, UK.,Department of Medicine for the Elderly, NHS Grampian, Aberdeen Royal Infirmary, Aberdeen, UK
| | - Maw Pin Tan
- Ageing and Age-Associated Disorders Research Group, Department of Medicine, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia. .,Centre for Innovations in Medical Engineering, University of Malaya, Kuala Lumpur, Malaysia. .,Department of Medical Sciences, Faculty of Healthcare and Medical Sciences, Sunway University, Bandar Sunway, Malaysia.
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Hackett K, Sabat SR, Giovannetti T. A person-centered framework for designing music-based therapeutic studies in dementia: current barriers and a path forward. Aging Ment Health 2022; 26:940-949. [PMID: 34139133 PMCID: PMC8678363 DOI: 10.1080/13607863.2021.1931029] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
Abstract
Objectives: Music-based interventions have received growing attention to improve quality of life for people diagnosed with dementia. Results of randomized controlled trials and meta-analytic reviews to date, however, reveal a lack of conclusive evidence for or against the effectiveness of such interventions. Herein, we critically review the basic assumptions and methodological issues ingrained in the cultures of research and care as they relate to evaluating music-based treatments for people with dementia, and propose a shift in the methodology by which music interventions are empirically evaluated.Method: We begin by reviewing existing barriers to achieving clarity on the effectiveness of music interventions, and we highlight methodological and sociocultural constraints that have limited our ability to reach concrete conclusions in research studies to-date. We then consider several key factors that have demonstrated relevance in matching people to specific music-based interventions. Based on these key factors, we developed a person-centered framework integrating elements from precision-medicine methodology to guide intervention studies.Results: Our organizing framework systematically integrates the following factors to inform the design of intervention studies: 1) person-centered goals and desired outcomes; 2) differences among individuals in clinical, cognitive, and historical attributes; and 3) the context of intervention and access to resources.Conclusion: Integration of the proposed framework into empirical investigations of music interventions for people living with dementia will inform precise and tailored interventions that will bring clarity to this growing body of research. Another aim of this framework is to foster a more humane, person-centered approach to our culture of care.
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Affiliation(s)
| | - Steven R. Sabat
- Department of Psychology, Georgetown University, Washington, DC, USA
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Cai Y, Liu J, Wang B, Sun M, Yang H. Microglia in the Neuroinflammatory Pathogenesis of Alzheimer's Disease and Related Therapeutic Targets. Front Immunol 2022; 13:856376. [PMID: 35558075 PMCID: PMC9086828 DOI: 10.3389/fimmu.2022.856376] [Citation(s) in RCA: 34] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 03/30/2022] [Indexed: 11/13/2022] Open
Abstract
Alzheimer's disease (AD) is the most prevalent neurodegenerative disease worldwide, characterized by progressive neuron degeneration or loss due to excessive accumulation of β-amyloid (Aβ) peptides, formation of neurofibrillary tangles (NFTs), and hyperphosphorylated tau. The treatment of AD has been only partially successful as the majority of the pharmacotherapies on the market may alleviate some of the symptoms. In the occurrence of AD, increasing attention has been paid to neurodegeneration, while the resident glial cells, like microglia are also observed. Microglia, a kind of crucial glial cells associated with the innate immune response, functions as double-edge sword role in CNS. They exert a beneficial or detrimental influence on the adjacent neurons through secretion of both pro-inflammatory cytokines as well as neurotrophic factors. In addition, their endocytosis of debris and toxic protein like Aβ and tau ensures homeostasis of the neuronal microenvironment. In this review, we will systematically summarize recent research regarding the roles of microglia in AD pathology and latest microglia-associated therapeutic targets mainly including pro-inflammatory genes, anti-inflammatory genes and phagocytosis at length, some of which are contradictory and controversial and warrant to further be investigated.
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Affiliation(s)
| | | | | | - Miao Sun
- Institute for Fetology, The First Affiliated Hospital of Soochow University, Suzhou, China
| | - Hao Yang
- Institute for Fetology, The First Affiliated Hospital of Soochow University, Suzhou, China
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Kornaropoulos EN, Winzeck S, Rumetshofer T, Wikstrom A, Knutsson L, Correia MM, Sundgren PC, Nilsson M. Sensitivity of Diffusion MRI to White Matter Pathology: Influence of Diffusion Protocol, Magnetic Field Strength, and Processing Pipeline in Systemic Lupus Erythematosus. Front Neurol 2022; 13:837385. [PMID: 35557624 PMCID: PMC9087851 DOI: 10.3389/fneur.2022.837385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 03/16/2022] [Indexed: 11/13/2022] Open
Abstract
There are many ways to acquire and process diffusion MRI (dMRI) data for group studies, but it is unknown which maximizes the sensitivity to white matter (WM) pathology. Inspired by this question, we analyzed data acquired for diffusion tensor imaging (DTI) and diffusion kurtosis imaging (DKI) at 3T (3T-DTI and 3T-DKI) and DTI at 7T in patients with systemic lupus erythematosus (SLE) and healthy controls (HC). Parameter estimates in 72 WM tracts were obtained using TractSeg. The impact on the sensitivity to WM pathology was evaluated for the diffusion protocol, the magnetic field strength, and the processing pipeline. Sensitivity was quantified in terms of Cohen's d for group comparison. Results showed that the choice of diffusion protocol had the largest impact on the effect size. The effect size in fractional anisotropy (FA) across all WM tracts was 0.26 higher when derived by DTI than by DKI and 0.20 higher in 3T compared with 7T. The difference due to the diffusion protocol was larger than the difference due to magnetic field strength for the majority of diffusion parameters. In contrast, the difference between including or excluding different processing steps was near negligible, except for the correction of distortions from eddy currents and motion which had a clearly positive impact. For example, effect sizes increased on average by 0.07 by including motion and eddy correction for FA derived from 3T-DTI. Effect sizes were slightly reduced by the incorporation of denoising and Gibbs-ringing removal (on average by 0.011 and 0.005, respectively). Smoothing prior to diffusion model fitting generally reduced effect sizes. In summary, 3T-DTI in combination with eddy current and motion correction yielded the highest sensitivity to WM pathology in patients with SLE. However, our results also indicated that the 3T-DKI and 7T-DTI protocols used here may be adjusted to increase effect sizes.
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Affiliation(s)
- Evgenios N. Kornaropoulos
- Clinical Sciences, Diagnostic Radiology, Lund University, Lund, Sweden
- Division of Anaesthesia, University of Cambridge, Cambridge, United Kingdom
| | - Stefan Winzeck
- Division of Anaesthesia, University of Cambridge, Cambridge, United Kingdom
- BioMedIA Group, Department of Computing, Imperial College London, London, United Kingdom
| | | | - Anna Wikstrom
- Clinical Sciences, Diagnostic Radiology, Lund University, Lund, Sweden
| | - Linda Knutsson
- Department of Medical Radiation Physics, Lund University, Lund, Sweden
- Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University, School of Medicine, Baltimore, MD, United States
- F.M. Kirby Research Center, Kennedy Krieger Institute, Baltimore, MD, United States
| | - Marta M. Correia
- MRC Cognition and Brain Sciences Unit, University of Cambridge, Cambridge, United Kingdom
| | - Pia C. Sundgren
- Clinical Sciences, Diagnostic Radiology, Lund University, Lund, Sweden
- Lund University BioImaging Center, Lund University, Lund, Sweden
- Department of Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
| | - Markus Nilsson
- Clinical Sciences, Diagnostic Radiology, Lund University, Lund, Sweden
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Neumann A, Küçükali F, Bos I, Vos SJB, Engelborghs S, De Pooter T, Joris G, De Rijk P, De Roeck E, Tsolaki M, Verhey F, Martinez-Lage P, Tainta M, Frisoni G, Blin O, Richardson J, Bordet R, Scheltens P, Popp J, Peyratout G, Johannsen P, Frölich L, Vandenberghe R, Freund-Levi Y, Streffer J, Lovestone S, Legido-Quigley C, Ten Kate M, Barkhof F, Strazisar M, Zetterberg H, Bertram L, Visser PJ, van Broeckhoven C, Sleegers K. Rare variants in IFFO1, DTNB, NLRC3 and SLC22A10 associate with Alzheimer's disease CSF profile of neuronal injury and inflammation. Mol Psychiatry 2022; 27:1990-1999. [PMID: 35173266 PMCID: PMC9126805 DOI: 10.1038/s41380-022-01437-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/12/2021] [Revised: 11/04/2021] [Accepted: 01/05/2022] [Indexed: 11/30/2022]
Abstract
Alzheimer's disease (AD) biomarkers represent several neurodegenerative processes, such as synaptic dysfunction, neuronal inflammation and injury, as well as amyloid pathology. We performed an exome-wide rare variant analysis of six AD biomarkers (β-amyloid, total/phosphorylated tau, NfL, YKL-40, and Neurogranin) to discover genes associated with these markers. Genetic and biomarker information was available for 480 participants from two studies: EMIF-AD and ADNI. We applied a principal component (PC) analysis to derive biomarkers combinations, which represent statistically independent biological processes. We then tested whether rare variants in 9576 protein-coding genes associate with these PCs using a Meta-SKAT test. We also tested whether the PCs are intermediary to gene effects on AD symptoms with a SMUT test. One PC loaded on NfL and YKL-40, indicators of neuronal injury and inflammation. Four genes were associated with this PC: IFFO1, DTNB, NLRC3, and SLC22A10. Mediation tests suggest, that these genes also affect dementia symptoms via inflammation/injury. We also observed an association between a PC loading on Neurogranin, a marker for synaptic functioning, with GABBR2 and CASZ1, but no mediation effects. The results suggest that rare variants in IFFO1, DTNB, NLRC3, and SLC22A10 heighten susceptibility to neuronal injury and inflammation, potentially by altering cytoskeleton structure and immune activity disinhibition, resulting in an elevated dementia risk. GABBR2 and CASZ1 were associated with synaptic functioning, but mediation analyses suggest that the effect of these two genes on synaptic functioning is not consequential for AD development.
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Affiliation(s)
- Alexander Neumann
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium.
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium.
| | - Fahri Küçükali
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Isabelle Bos
- Netherlands Institute for Health Services Research, Utrecht, the Netherlands
| | - Stephanie J B Vos
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
| | - Sebastiaan Engelborghs
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Department of Neurology and Memory Clinic, Universitair Ziekenhuis Brussel (UZ Brussel) and Center for Neurosciences (C4N), Vrije Universiteit Brussel (VUB), Brussels, Belgium
| | - Tim De Pooter
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Neuromics Support Facility, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
| | - Geert Joris
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Neuromics Support Facility, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
| | - Peter De Rijk
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Neuromics Support Facility, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
| | - Ellen De Roeck
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Middelheim and Hoge Beuken, Antwerp, Belgium
| | - Magda Tsolaki
- 1st Department of Neurology, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Makedonia, Thessaloniki, Greece
| | - Frans Verhey
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
- Department of Psychiatry and Neuropsychology, Maastricht University, Maastricht, the Netherlands
- School for Mental Health and Neuroscience, Maastricht University, Maastricht, the Netherlands
| | - Pablo Martinez-Lage
- Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
| | - Mikel Tainta
- Center for Research and Advanced Therapies, CITA-Alzheimer Foundation, San Sebastian, Spain
| | - Giovanni Frisoni
- Department of Psychiatry, Faculty of Medicine, Geneva University Hospitals, Geneva, Switzerland
- RCCS Instituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Oliver Blin
- Clinical Pharmacology & Pharmacovigilance Department, Marseille University Hospital, Marseille, France
| | - Jill Richardson
- Neurosciences Therapeutic Area, GlaxoSmithKline R&D, Stevanage, UK
| | - Régis Bordet
- Neuroscience & Cognition, CHU de Lille, University of Lille, Inserm, France
| | - Philip Scheltens
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, the Netherlands
| | - Julius Popp
- Department of Geriatric Psychiatry, University Hospital of Psychiatry Zürich, Zürich, Switzerland
- Old Age Psychiatry, Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Gwendoline Peyratout
- Department of Psychiatry, University Hospital of Lausanne, Lausanne, Switzerland
| | - Peter Johannsen
- Clinical Drug Development, Novo Nordisk, Copenhagen, Denmark
| | - Lutz Frölich
- Department of Geriatric Psychiatry, Central Institute of Mental Health, Medical Faculty Mannheim, University of Heidelberg, Mannheim, Germany
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Yvonne Freund-Levi
- Center for Alzheimer Research, Division of Clinical Geriatrics, Department of Neurobiology, Care Sciences and Society Karolinska Institute Stockholm Sweden, Stockholm, Sweden
- School of Medical Sciences Örebro, University Örebro, Örebro, Sweden
| | - Johannes Streffer
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
| | - Simon Lovestone
- Department of Psychiatry, University of Oxford, Oxford, UK
- Janssen Medical Ltd, High Wycombe, UK
| | - Cristina Legido-Quigley
- Steno Diabetes Center, Copenhagen, Denmark
- Institute of Pharmaceutical Sciences, King's College London, London, UK
| | - Mara Ten Kate
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, the Netherlands
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, the Netherlands
- Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - Mojca Strazisar
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Neuromics Support Facility, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Department of Molecular Neuroscience, UCL Institute of Neurology, London, UK
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- UK Dementia Research Institute, University College London, London, UK
- Hong Kong Center for Neurodegenerative Diseases, Hong Kong, China
| | - Lars Bertram
- Lübeck Interdisciplinary Platform for Genome Analytics, University of Lübeck, Lübeck, Germany
- Centre for Lifespan Changes in Brain and Cognition, University of Oslo, Oslo, Norway
| | - Pieter Jelle Visser
- Alzheimer Centrum Limburg, Maastricht University, Maastricht, the Netherlands
- Alzheimer Center and Department of Neurology, VU University Medical Center, Amsterdam, the Netherlands
| | - Christine van Broeckhoven
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- Neurodegenerative Brain Diseases Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
| | - Kristel Sleegers
- Complex Genetics of Alzheimer's Disease Group, VIB Center for Molecular Neurology, VIB, Antwerp, Belgium
- Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
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Shobeiri P, Kalantari A, Teixeira AL, Rezaei N. Shedding light on biological sex differences and microbiota-gut-brain axis: a comprehensive review of its roles in neuropsychiatric disorders. Biol Sex Differ 2022; 13:12. [PMID: 35337376 PMCID: PMC8949832 DOI: 10.1186/s13293-022-00422-6] [Citation(s) in RCA: 37] [Impact Index Per Article: 18.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Accepted: 03/14/2022] [Indexed: 12/15/2022] Open
Abstract
Women and men are suggested to have differences in vulnerability to neuropsychiatric disorders, including major depressive disorder (MDD), generalized anxiety disorder (GAD), schizophrenia, eating disorders, including anorexia nervosa, and bulimia nervosa, neurodevelopmental disorders, such as autism spectrum disorder (ASD), and neurodegenerative disorders including Alzheimer’s disease, Parkinson’s disease. Genetic factors and sex hormones are apparently the main mediators of these differences. Recent evidence uncovers that reciprocal interactions between sex-related features (e.g., sex hormones and sex differences in the brain) and gut microbiota could play a role in the development of neuropsychiatric disorders via influencing the gut–brain axis. It is increasingly evident that sex–microbiota–brain interactions take part in the occurrence of neurologic and psychiatric disorders. Accordingly, integrating the existing evidence might help to enlighten the fundamental roles of these interactions in the pathogenesis of neuropsychiatric disorders. In addition, an increased understanding of the biological sex differences on the microbiota–brain may lead to advances in the treatment of neuropsychiatric disorders and increase the potential for precision medicine. This review discusses the effects of sex differences on the brain and gut microbiota and the putative underlying mechanisms of action. Additionally, we discuss the consequences of interactions between sex differences and gut microbiota on the emergence of particular neuropsychiatric disorders. The human microbiome is a unique set of organisms affecting health via the gut–brain axis. Neuropsychiatric disorders, eating disorders, neurodevelopmental disorders, and neurodegenerative disorders are regulated by the microbiota–gut–brain axis in a sex-specific manner. Understanding the role of the microbiota–gut–brain axis and its sex differences in various diseases can lead to better therapeutic methods.
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Affiliation(s)
- Parnian Shobeiri
- School of Medicine, Tehran University of Medical Sciences (TUMS), Children's Medical Center Hospital, Dr. Qarib St., Keshavarz Blvd, 14194, Tehran, Iran.,Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran.,Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.,Research Center for Immunodeficiencies, Pediatrics Center of Excellence, Children's Medical Center, Tehran University of Medical Sciences, Dr. Gharib St, Keshavarz Blvd, Tehran, Iran
| | - Amirali Kalantari
- School of Medicine, Tehran University of Medical Sciences (TUMS), Children's Medical Center Hospital, Dr. Qarib St., Keshavarz Blvd, 14194, Tehran, Iran.,Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran
| | - Antônio L Teixeira
- Neuropsychiatry Program, Department of Psychiatry and Behavioral Sciences, McGovern Medical School, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Nima Rezaei
- Network of Immunity in Infection, Malignancy and Autoimmunity (NIIMA), Universal Scientific Education and Research Network (USERN), Tehran, Iran. .,Research Center for Immunodeficiencies, Pediatrics Center of Excellence, Children's Medical Center, Tehran University of Medical Sciences, Dr. Gharib St, Keshavarz Blvd, Tehran, Iran. .,Department of Immunology, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
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46
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Christinaki E, Kulenovic H, Hadoux X, Baldassini N, Van Eijgen J, De Groef L, Stalmans I, van Wijngaarden P. Retinal imaging biomarkers of neurodegenerative diseases. Clin Exp Optom 2022; 105:194-204. [PMID: 34751086 DOI: 10.1080/08164622.2021.1984179] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
The timely detection of neurodegenerative diseases is central to improving clinical care as well as enabling the development and deployment of disease-modifying therapies. Retinal imaging is emerging as a method to detect features of a number of neurodegenerative diseases, given the anatomical and functional similarities between the retina and the brain. This review provides an overview of the current status of retinal imaging biomarkers of neurodegenerative diseases including Alzheimer's disease, Parkinson's disease, Lewy body dementia, frontotemporal dementia, Huntington's disease and multiple sclerosis. Whilst research findings are promising, efforts to harmonise study designs and imaging methods will be important in translating these findings into clinical care. Doing so may mean that eye care providers will play important roles in the detection of a variety of neurodegenerative diseases in future.
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Affiliation(s)
- Eirini Christinaki
- Research Group Ophthalmology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Hana Kulenovic
- Research Group Ophthalmology, Department of Neurosciences, KU Leuven, Leuven, Belgium
| | - Xavier Hadoux
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia
| | - Nicole Baldassini
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia
| | - Jan Van Eijgen
- Research Group Ophthalmology, Department of Neurosciences, KU Leuven, Leuven, Belgium.,Department of Ophthalmology, University Hospitals Leuven, Leuven, Belgium
| | - Lies De Groef
- Neural Circuit Development and Regeneration Research Group, Department of Biology, University of Leuven (KU Leuven), Leuven, Belgium.,Leuven Brain Institute, Leuven, Belgium
| | - Ingeborg Stalmans
- Research Group Ophthalmology, Department of Neurosciences, KU Leuven, Leuven, Belgium.,Department of Ophthalmology, University Hospitals Leuven, Leuven, Belgium.,Neural Circuit Development and Regeneration Research Group, Department of Biology, University of Leuven (KU Leuven), Leuven, Belgium
| | - Peter van Wijngaarden
- Centre for Eye Research Australia, Royal Victorian Eye and Ear Hospital, East Melbourne, Australia.,Ophthalmology, Department of Surgery, University of Melbourne, Parkville, Australia
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Omolaoye TS, Hachim MY, du Plessis SS. Using publicly available transcriptomic data to identify mechanistic and diagnostic biomarkers in azoospermia and overall male infertility. Sci Rep 2022; 12:2584. [PMID: 35173218 PMCID: PMC8850557 DOI: 10.1038/s41598-022-06476-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2021] [Accepted: 01/28/2022] [Indexed: 12/23/2022] Open
Abstract
Azoospermia, which is the absence of spermatozoa in an ejaculate occurring due to defects in sperm production, or the obstruction of the reproductive tract, affects about 1% of all men and is prevalent in up to 10–15% of infertile males. Conventional semen analysis remains the gold standard for diagnosing and treating male infertility; however, advances in molecular biology and bioinformatics now highlight the insufficiency thereof. Hence, the need to widen the scope of investigating the aetiology of male infertility stands pertinent. The current study aimed to identify common differentially expressed genes (DEGs) that might serve as potential biomarkers for non-obstructive azoospermia (NOA) and overall male infertility. DEGs across different datasets of transcriptomic profiling of testis from human patients with different causes of infertility/ impaired spermatogenesis and/or azoospermia were explored using the gene expression omnibus (GEO) database. Following the search using the GEOquery, 30 datasets were available, with 5 meeting the inclusion criteria. The DEGs for datasets were identified using limma R packages through the GEO2R tool. The annotated genes of the probes in each dataset were intersected with DEGs from all other datasets. Enriched Ontology Clustering for the identified genes was performed using Metascape to explore the possible connection or interaction between the genes. Twenty-five DEGs were shared between most of the datasets, which might indicate their role in the pathogenesis of male infertility. Of the 25 DEGs, eight genes (THEG, SPATA20, ROPN1L, GSTF1, TSSK1B, CABS1, ADAD1, RIMBP3) are either involved in the overall spermatogenic processes or at specific phases of spermatogenesis. We hypothesize that alteration in the expression of these genes leads to impaired spermatogenesis and, ultimately, male infertility. Thus, these genes can be used as potential biomarkers for the early detection of NOA.
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Affiliation(s)
- Temidayo S Omolaoye
- Department of Basic Sciences, College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE
| | - Mahmood Yaseen Hachim
- Department of Basic Sciences, College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE.
| | - Stefan S du Plessis
- Department of Basic Sciences, College of Medicine, Mohammed Bin Rashid University of Medicine and Health Sciences, Dubai, UAE.,Division of Medical Physiology, Faculty of Medicine and Health Sciences, Stellenbosch University, Tygerberg, South Africa
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Lukkarinen H, Jeppsson A, Wikkelsö C, Blennow K, Zetterberg H, Constantinescu R, Remes AM, Herukka SK, Hiltunen M, Rauramaa T, Nägga K, Leinonen V, Tullberg M. Cerebrospinal fluid biomarkers that reflect clinical symptoms in idiopathic normal pressure hydrocephalus patients. Fluids Barriers CNS 2022; 19:11. [PMID: 35123528 PMCID: PMC8817565 DOI: 10.1186/s12987-022-00309-z] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2021] [Accepted: 01/20/2022] [Indexed: 02/07/2023] Open
Abstract
Background The relationship between cerebrospinal fluid (CSF) biomarkers and the clinical features of idiopathic normal pressure hydrocephalus (iNPH) has been inconclusive. We aimed to evaluate CSF biomarkers reflecting Alzheimer’s disease (AD)-related amyloid β (Aβ) aggregation, tau pathology, neuroinflammation and axonal degeneration in relation to the clinical features of pre- and post-shunt surgery in iNPH patients. Methods Mini Mental State Examination (MMSE) scores and gait velocity were evaluated pre- and postoperatively in cohorts of 65 Finnish (FIN) and 82 Swedish (SWE) iNPH patients. Lumbar CSF samples were obtained prior to shunt surgery and analysed for soluble amyloid precursor protein alpha (sAPPα) and beta (sAPPβ); amyloid-β isoforms of 42, 40 and 38 (Aβ42, Aβ40, Aβ38); total tau (T-tau); phosphorylated tau (P-tau181); neurofilament light (NfL) and monocyte chemoattractant protein 1 (MCP1). Results Preoperative patient characteristics showed no significant differences between patients in the FIN and SWE cohorts. Patients in both cohorts had significantly improved gait velocity after shunt surgery (p < 0.0001). Low CSF T-tau and absence of apolipoprotein E ε4 predicted over 20% gait improvement postoperatively (p = 0.043 and p = 0.008). Preoperative CSF T-tau, P-tau181 and NfL correlated negatively with MMSE scores both pre- (p < 0.01) and post-surgery (p < 0.01). Furthermore, T-tau, NfL and Aβ42 correlated with MMSE outcomes (p < 0.05). Low preoperative CSF P-tau181 (p = 0.001) and T-tau with NfL (p < 0.001 and p = 0.049) best predicted pre- and postoperative MMSE scores greater than or equal to 26. Conclusions CSF biomarkers of neurodegeneration appeared to correlate with pre- and postoperative cognition, providing a window into neuropathological processes. In addition, preoperative CSF neurodegeneration biomarkers may have potential in the prediction of gait and cognitive outcomes after shunt surgery.
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Vogt NM, Hunt JFV, Adluru N, Ma Y, Van Hulle CA, Dean DC, Kecskemeti SR, Chin NA, Carlsson CM, Asthana S, Johnson SC, Kollmorgen G, Batrla R, Wild N, Buck K, Zetterberg H, Alexander AL, Blennow K, Bendlin BB. Interaction of amyloid and tau on cortical microstructure in cognitively unimpaired adults. Alzheimers Dement 2022; 18:65-76. [PMID: 33984184 PMCID: PMC8589921 DOI: 10.1002/alz.12364] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 03/31/2021] [Accepted: 04/12/2021] [Indexed: 01/03/2023]
Abstract
INTRODUCTION Neurite orientation dispersion and density imaging (NODDI), a multi-compartment diffusion-weighted imaging (DWI) model, may be useful for detecting early cortical microstructural alterations in Alzheimer's disease prior to cognitive impairment. METHODS Using neuroimaging (NODDI and T1-weighted magnetic resonance imaging [MRI]) and cerebrospinal fluid (CSF) biomarker data (measured using Elecsys® CSF immunoassays) from 219 cognitively unimpaired participants, we tested the main and interactive effects of CSF amyloid beta (Aβ)42 /Aβ40 and phosphorylated tau (p-tau) on cortical NODDI metrics and cortical thickness, controlling for age, sex, and apolipoprotein E ε4. RESULTS We observed a significant CSF Aβ42 /Aβ40 × p-tau interaction on cortical neurite density index (NDI), but not orientation dispersion index or cortical thickness. The directionality of these interactive effects indicated: (1) among individuals with lower CSF p-tau, greater amyloid burden was associated with higher cortical NDI; and (2) individuals with greater amyloid and p-tau burden had lower cortical NDI, consistent with cortical neurodegenerative changes. DISCUSSION NDI is a particularly sensitive marker for early cortical changes that occur prior to gross atrophy or development of cognitive impairment.
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Affiliation(s)
- Nicholas M. Vogt
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Jack F. V. Hunt
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Nagesh Adluru
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Yue Ma
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Carol A. Van Hulle
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Douglas C. Dean
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Pediatrics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Steven R. Kecskemeti
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
| | - Nathaniel A. Chin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Cynthia M. Carlsson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Sanjay Asthana
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | - Sterling C. Johnson
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
- Geriatric Research Education and Clinical Center, William S. Middleton Memorial Veterans Hospital, Madison, WI, USA
| | | | - Richard Batrla
- Roche Diagnostics International AG, Rotkreuz, Switzerland
| | | | | | - Henrik Zetterberg
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at University College London, London, UK
| | - Andrew L. Alexander
- Waisman Laboratory for Brain Imaging and Behavior, Waisman Center, University of Wisconsin-Madison, Madison, WI, USA
- Department of Medical Physics, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
| | - Kaj Blennow
- Institute of Neuroscience and Physiology, Department of Psychiatry and Neurochemistry, The Sahlgrenska Academy at the University of Gothenburg, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Barbara B. Bendlin
- Wisconsin Alzheimer’s Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA
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50
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Ni R. Magnetic Resonance Imaging in Animal Models of Alzheimer's Disease Amyloidosis. Int J Mol Sci 2021; 22:12768. [PMID: 34884573 PMCID: PMC8657987 DOI: 10.3390/ijms222312768] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 11/18/2021] [Accepted: 11/23/2021] [Indexed: 02/07/2023] Open
Abstract
Amyloid-beta (Aβ) plays an important role in the pathogenesis of Alzheimer's disease. Aberrant Aβ accumulation induces neuroinflammation, cerebrovascular alterations, and synaptic deficits, leading to cognitive impairment. Animal models recapitulating the Aβ pathology, such as transgenic, knock-in mouse and rat models, have facilitated the understanding of disease mechanisms and the development of therapeutics targeting Aβ. There is a rapid advance in high-field MRI in small animals. Versatile high-field magnetic resonance imaging (MRI) sequences, such as diffusion tensor imaging, arterial spin labeling, resting-state functional MRI, anatomical MRI, and MR spectroscopy, as well as contrast agents, have been developed for preclinical imaging in animal models. These tools have enabled high-resolution in vivo structural, functional, and molecular readouts with a whole-brain field of view. MRI has been used to visualize non-invasively the Aβ deposits, synaptic deficits, regional brain atrophy, impairment in white matter integrity, functional connectivity, and cerebrovascular and glymphatic system in animal models of Alzheimer's disease amyloidosis. Many of the readouts are translational toward clinical MRI applications in patients with Alzheimer's disease. In this review, we summarize the recent advances in MRI for visualizing the pathophysiology in amyloidosis animal models. We discuss the outstanding challenges in brain imaging using MRI in small animals and propose future outlook in visualizing Aβ-related alterations in the brains of animal models.
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Affiliation(s)
- Ruiqing Ni
- Institute for Biomedical Engineering, ETH Zurich & University of Zurich, 8093 Zurich, Switzerland;
- Institute for Regenerative Medicine, University of Zurich, 8952 Zurich, Switzerland
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