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Solé-Guardia G, Luijten M, Janssen E, Visch R, Geenen B, Küsters B, Claassen JAHR, Litjens G, de Leeuw FE, Wiesmann M, Kiliaan AJ. Deep learning-based segmentation in MRI-(immuno)histological examination of myelin and axonal damage in normal-appearing white matter and white matter hyperintensities. Brain Pathol 2024:e13301. [PMID: 39175459 DOI: 10.1111/bpa.13301] [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: 04/12/2024] [Accepted: 07/17/2024] [Indexed: 08/24/2024] Open
Abstract
The major vascular cause of dementia is cerebral small vessel disease (SVD). Its diagnosis relies on imaging hallmarks, such as white matter hyperintensities (WMH). WMH present a heterogenous pathology, including myelin and axonal loss. Yet, these might be only the "tip of the iceberg." Imaging modalities imply that microstructural alterations underlie still normal-appearing white matter (NAWM), preceding the conversion to WMH. Unfortunately, direct pathological characterization of these microstructural alterations affecting myelinated axonal fibers in WMH, and especially NAWM, is still missing. Given that there are no treatments to significantly reduce WMH progression, it is important to extend our knowledge on pathological processes that might already be occurring within NAWM. Staining of myelin with Luxol Fast Blue, while valuable, fails to assess subtle alterations in white matter microstructure. Therefore, we aimed to quantify myelin surrounding axonal fibers and axonal- and microstructural damage in detail by combining (immuno)histochemistry with polarized light imaging (PLI). To study the extent (of early) microstructural damage from periventricular NAWM to the center of WMH, we refined current analysis techniques by using deep learning to define smaller segments of white matter, capturing increasing fluid-attenuated inversion recovery signal. Integration of (immuno)histochemistry and PLI with post-mortem imaging of the brains of individuals with hypertension and normotensive controls enables voxel-wise assessment of the pathology throughout periventricular WMH and NAWM. Myelin loss, axonal integrity, and white matter microstructural damage are not limited to WMH but already occur within NAWM. Notably, we found that axonal damage is higher in individuals with hypertension, particularly in NAWM. These findings highlight the added value of advanced segmentation techniques to visualize subtle changes occurring already in NAWM preceding WMH. By using quantitative MRI and advanced diffusion MRI, future studies may elucidate these very early mechanisms leading to neurodegeneration, which ultimately contribute to the conversion of NAWM to WMH.
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Affiliation(s)
- Gemma Solé-Guardia
- Department of Medical Imaging, Anatomy, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, Nijmegen, The Netherlands
| | - Matthijs Luijten
- Department of Medical Imaging, Anatomy, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, Nijmegen, The Netherlands
| | - Esther Janssen
- Department of Medical Imaging, Anatomy, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, Nijmegen, The Netherlands
| | - Ruben Visch
- Department of Medical Imaging, Anatomy, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, Nijmegen, The Netherlands
| | - Bram Geenen
- Department of Medical Imaging, Anatomy, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, Nijmegen, The Netherlands
| | - Benno Küsters
- Department of Pathology, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jurgen A H R Claassen
- Department of Geriatrics, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Radboud Alzheimer Center, Nijmegen, The Netherlands
- Department of Cardiovascular Sciences, University of Leicester, Leicester, UK
| | - Geert Litjens
- Department of Pathology, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, The Netherlands
- Computational Pathology Group, Research Institute for Medical Innovation, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Frank-Erik de Leeuw
- Department of Neurology, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Nijmegen, The Netherlands
| | - Maximilian Wiesmann
- Department of Medical Imaging, Anatomy, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, Nijmegen, The Netherlands
| | - Amanda J Kiliaan
- Department of Medical Imaging, Anatomy, Research Institute for Medical Innovation, Radboud University Medical Center, Donders Institute for Brain, Cognition & Behavior, Center for Medical Neuroscience, Preclinical Imaging Center PRIME, Radboud Alzheimer Center, Nijmegen, The Netherlands
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Hemminghyth MS, Chwiszczuk LJ, Breitve MH, Gísladóttir B, Grøntvedt GR, Nakling A, Rongve A, Fladby T, Kirsebom BE. Cerebrospinal fluid neurofilament light chain mediates age-associated lower learning and memory in healthy adults. Neurobiol Aging 2024; 135:39-47. [PMID: 38159464 DOI: 10.1016/j.neurobiolaging.2023.12.005] [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: 05/25/2023] [Revised: 12/15/2023] [Accepted: 12/21/2023] [Indexed: 01/03/2024]
Abstract
Multiple cognitive domains, including learning, memory, and psychomotor speed, show significant reductions with age. Likewise, several cerebrospinal fluid (CSF) neurodegenerative biomarkers, including total tau (t-tau, a marker of neuronal body injury) and neurofilament light chain (NfL, a marker of axonal injury) show age-related increases in normal aging. In the current study, we aimed to investigate whether the age-effect within different cognitive domains was mediated by age-associated CSF markers for neurodegenerative changes. We fitted 10 mediation models using structural equation modeling to investigate this in a cohort of 137 healthy adults, aged 40-80 years, from the Norwegian Dementia Disease Initiation (DDI) study. Here, t-tau and NfL were defined as mediators between age and different cognitive tests. The models showed that NfL mediated the age-effect for CERAD learning and memory recall (learning: β = -0.395, p < 0.05; recall: β = -0.261, p < 0.01). No such effect was found in the other models. Our findings suggest that the age-related lower performance in verbal learning and memory may be linked to NfL-associated neurodegenerative changes in cognitively healthy adults.
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Affiliation(s)
- Mathilde Suhr Hemminghyth
- Department of Research and Innovation, Research Group for Age-Related Medicine, Helse Fonna, Haugesund Hospital, Haugesund, Norway; Department of Neuropsychology, Helse Fonna, Haugesund Hospital, Haugesund, Norway; Department of Clinical Medicine (K1), University of Bergen, Bergen, Norway.
| | - Luiza Jadwiga Chwiszczuk
- Department of Research and Innovation, Research Group for Age-Related Medicine, Helse Fonna, Haugesund Hospital, Haugesund, Norway; Department of Age-related Medicine, Helse Fonna, Haugesund Hospital, Haugesund, Norway
| | - Monica Haraldseid Breitve
- Department of Research and Innovation, Research Group for Age-Related Medicine, Helse Fonna, Haugesund Hospital, Haugesund, Norway; Department of Neuropsychology, Helse Fonna, Haugesund Hospital, Haugesund, Norway; Department of Age-related Medicine, Helse Fonna, Haugesund Hospital, Haugesund, Norway
| | - Berglind Gísladóttir
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway; Clinical Molecular Biology (EpiGen), Medical Division, Akershus University Hospital and University of Oslo, Norway
| | - Gøril Rolfseng Grøntvedt
- Department of Neuromedicine and Movement Science, Faculty of Medicine and Health Sciences, Norwegian University of Science and Technology, Trondheim, Norway; Department of Neurology and Clinical Neurophysiology, University Hospital of Trondheim, Trondheim, Norway
| | - Arne Nakling
- Department of Clinical Medicine (K1), University of Bergen, Bergen, Norway
| | - Arvid Rongve
- Department of Research and Innovation, Research Group for Age-Related Medicine, Helse Fonna, Haugesund Hospital, Haugesund, Norway; Department of Clinical Medicine (K1), University of Bergen, Bergen, Norway; Department of Age-related Medicine, Helse Fonna, Haugesund Hospital, Haugesund, Norway
| | - Tormod Fladby
- Department of Neurology, Akershus University Hospital, Lørenskog, Norway; Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Bjørn-Eivind Kirsebom
- Department of Neurology, University Hospital of North Norway, Tromsø, Norway; Department of Psychology, Faculty of Health Sciences, UiT The Arctic University of Norway, Tromsø, Norway
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Li J, Yang M, Wei R, Cao Y, Fan X, Zhang S. The Predictive Ability of Blood Neurofilament Light Chain in Predicting Cognitive Decline in the Alzheimer's Disease Continuum: A Systematic Review and Meta-Analysis. J Alzheimers Dis 2024; 97:1589-1620. [PMID: 38306045 DOI: 10.3233/jad-231080] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2024]
Abstract
Background Alzheimer's disease (AD) is a neurodegenerative disease with insidious onset. Identifying candidate predictors to forecast AD dementia risk before disease onset is crucial for early diagnosis and treatment. Objective We aimed to assess the predictive ability of blood neurofilament light (NfL) chain in anticipating cognitive decline in the AD continuum. Methods We systematically searched PubMed, Web of Science, and Embase from inception until April 7, 2023. Longitudinal observational studies examining the association between baseline blood NfL and cognitive decline or clinical disease conversion were included based on inclusion/exclusion criteria. The final effect size was represented by adjusted hazard ratios (HR) or standardized beta (s.β) coefficients with a 95% confidence interval (CI). Results A total of 2,862 articles were identified, and 26 studies were included in this meta-analysis. The results indicated that baseline blood NfL could predict cognitive decline, with MMSE [s.β= -0.17, 95% CI (-0.26, -0.07)]; PACC [s.β= -0.09, 95% CI (-0.16, -0.03)]; ADAS-cog [s.β= 0.21, 95% CI (0.13, 0.29)]; CDR-SOB [s.β= 0.27, 95% CI (0.03, 0.50)]; Global cognitive composite [s.β= -0.05, 95% CI (-0.08, -0.01)]; Memory subdomain [s.β= -0.06, 95% CI (-0.09, -0.03)]; Language subdomain [s.β= -0.07, 95% CI (-0.10, -0.05)]; Executive function subdomain [s.β= -0.02, 95% CI (-0.03, -0.01)]; Visuospatial subdomain [s.β= -0.06, 95% CI (-0.08, -0.04)]. Additionally, baseline blood NfL could predict disease progression (conversion from CU/SCD/MCI to MCI/AD) in the AD continuum [Adjust HR = 1.32, 95% CI (1.12, 1.56)]. Conclusions Baseline blood NfL demonstrated predictive capabilities for global cognition and its memory, language, executive function, visuospatial subdomains decline in the AD continuum. Moreover, it exhibited the potential to predict disease progression in non-AD dementia participants.
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Affiliation(s)
- Jianhong Li
- Fujian Key Laboratory of Aptamers Technology, 900TH hospital of Joint Logistics Support Force, People's Liberation Army (PLA), Fuzhou, Fujian, China
| | - Minguang Yang
- National-Local Joint Engineering Research Center of Rehabilitation Medicine Technology, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
| | - Renli Wei
- The Institute of Rehabilitation Industry, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
| | - Yue Cao
- Fujian Key Laboratory of Aptamers Technology, 900TH hospital of Joint Logistics Support Force, People's Liberation Army (PLA), Fuzhou, Fujian, China
| | - Xu Fan
- The Institute of Rehabilitation Industry, Fujian University of Traditional Chinese Medicine, Fuzhou, Fujian, China
| | - Shenghang Zhang
- Fujian Key Laboratory of Aptamers Technology, 900TH hospital of Joint Logistics Support Force, People's Liberation Army (PLA), Fuzhou, Fujian, China
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Gao Y, Su D, Xue Z, Ji L, Wang S. Association Between Serum Neurofilament Light Chain and Cognitive Performance Among Older Adults in the United States: A Cross-Sectional Study. Neurol Ther 2023; 12:2147-2160. [PMID: 37845473 PMCID: PMC10630257 DOI: 10.1007/s40120-023-00555-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Accepted: 09/29/2023] [Indexed: 10/18/2023] Open
Abstract
INTRODUCTION Serum neurofilament light chain (sNfL) is an emerging biomarker of neuronal damage in several neurological disorders. Its association with cognitive function in the general US population aged 60 years and above is unknown. The aim of this study was to investigate the correlation between sNfL and cognitive function in the general US population aged 60 and above. METHODS The data were obtained from the 2013-2014 National Health and Nutrition Examination Survey (NHANES), which include 506 individuals aged 60 or older who met our search criteria. In our study, sNfL levels were divided into two groups based on dichotomization (19.0 pg/mL). After adjusting for multiple covariates, it was found that the high sNfL group (≥ 19.0 pg/mL) had lower cognitive performance than the low sNfL group (< 19.0 pg/mL). This relationship was also stable in subgroup analysis. CONCLUSION In this sample of an American elderly population, higher sNfL levels are correlated with lower cognitive performance. Our findings suggest that sNfL may become a potential screening tool for early prediction and confirmation of cognitive damage.
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Affiliation(s)
- Yuanyuan Gao
- Affiliated Hospital Six of Nantong University, Yancheng Third People's Hospital, No. 75 Juchang Road, Yancheng, 224000, Jiangsu, China
- Yancheng Third People's Hospital, Yancheng, 224000, Jiangsu, China
| | - Dan Su
- Affiliated Hospital Six of Nantong University, Yancheng Third People's Hospital, No. 75 Juchang Road, Yancheng, 224000, Jiangsu, China
- Yancheng Third People's Hospital, Yancheng, 224000, Jiangsu, China
| | - Zhouya Xue
- The First People's Hospital of Yancheng, Yancheng, 224000, Jiangsu, China
| | - Lin Ji
- Affiliated Hospital Six of Nantong University, Yancheng Third People's Hospital, No. 75 Juchang Road, Yancheng, 224000, Jiangsu, China
- Yancheng Third People's Hospital, Yancheng, 224000, Jiangsu, China
| | - Shu Wang
- Affiliated Hospital Six of Nantong University, Yancheng Third People's Hospital, No. 75 Juchang Road, Yancheng, 224000, Jiangsu, China.
- Yancheng Third People's Hospital, Yancheng, 224000, Jiangsu, China.
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