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Zarkali A, Hannaway N, McColgan P, Heslegrave AJ, Veleva E, Laban R, Zetterberg H, Lees AJ, Fox NC, Weil RS. Neuroimaging and plasma evidence of early white matter loss in Parkinson's disease with poor outcomes. Brain Commun 2024; 6:fcae130. [PMID: 38715714 PMCID: PMC11073930 DOI: 10.1093/braincomms/fcae130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2023] [Revised: 02/26/2024] [Accepted: 04/23/2024] [Indexed: 06/30/2024] Open
Abstract
Parkinson's disease is a common and debilitating neurodegenerative disorder, with over half of patients progressing to postural instability, dementia or death within 10 years of diagnosis. However, the onset and rate of progression to poor outcomes is highly variable, underpinned by heterogeneity in underlying pathological processes. Quantitative and sensitive measures predicting poor outcomes will be critical for targeted treatment, but most studies to date have been limited to a single modality or assessed patients with established cognitive impairment. Here, we used multimodal neuroimaging and plasma measures in 98 patients with Parkinson's disease and 28 age-matched controls followed up over 3 years. We examined: grey matter (cortical thickness and subcortical volume), white matter (fibre cross-section, a measure of macrostructure; and fibre density, a measure of microstructure) at whole-brain and tract level; structural and functional connectivity; and plasma levels of neurofilament light chain and phosphorylated tau 181. We evaluated relationships with subsequent poor outcomes, defined as development of mild cognitive impairment, dementia, frailty or death at any time during follow-up, in people with Parkinson's disease. We show that extensive white matter macrostructural changes are already evident at baseline assessment in people with Parkinson's disease who progress to poor outcomes (n = 31): with up to 19% reduction in fibre cross-section in multiple tracts, and a subnetwork of reduced structural connectivity strength, particularly involving connections between right frontoparietal and left frontal, right frontoparietal and left parietal and right temporo-occipital and left parietal modules. In contrast, grey matter volumes and functional connectivity were preserved in people with Parkinson's disease with poor outcomes. Neurofilament light chain, but not phosphorylated tau 181 levels were increased in people with Parkinson's disease with poor outcomes, and correlated with white matter loss. These findings suggest that imaging sensitive to white matter macrostructure and plasma neurofilament light chain may be useful early markers of poor outcomes in Parkinson's disease. As new targeted treatments for neurodegenerative disease are emerging, these measures show important potential to aid patient selection for treatment and improve stratification for clinical trials.
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Affiliation(s)
- Angeliki Zarkali
- Dementia Research Centre, Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Naomi Hannaway
- Dementia Research Centre, Institute of Neurology, University College London, London WC1N 3AR, UK
| | - Peter McColgan
- Huntington’s Disease Centre, Institute of Neurology, University College London, London WC1B 5EH, UK
| | - Amanda J Heslegrave
- UK DRI Fluid Biomarker Lab and Biomarker Factory, University College London, London WC1E 6BT, UK
| | - Elena Veleva
- UK DRI Fluid Biomarker Lab and Biomarker Factory, University College London, London WC1E 6BT, UK
| | - Rhiannon Laban
- UK DRI Fluid Biomarker Lab and Biomarker Factory, University College London, London WC1E 6BT, UK
| | - Henrik Zetterberg
- Dementia Research Centre, Institute of Neurology, University College London, London WC1N 3AR, UK
- UK DRI Fluid Biomarker Lab and Biomarker Factory, University College London, London WC1E 6BT, UK
| | - Andrew J Lees
- Reta Lila Weston Institute of Neurological Studies, University College London, London WC1N 1PJ, UK
| | - Nick C Fox
- Dementia Research Centre, Institute of Neurology, University College London, London WC1N 3AR, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals, London WC1N 3BG, UK
| | - Rimona S Weil
- Dementia Research Centre, Institute of Neurology, University College London, London WC1N 3AR, UK
- National Hospital for Neurology and Neurosurgery, University College London Hospitals, London WC1N 3BG, UK
- Movement Disorders Centre, University College London, London WC1N 3BG, UK
- The Wellcome Centre for Human Neuroimaging, Institute of Neurology, University College London, London WC1N 3AR, UK
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Zhou Y, Jing J, Zhang Z, Pan Y, Cai X, Zhu W, Li Z, Liu C, Liu H, Meng X, Cheng J, Wang Y, Li H, Wang S, Niu H, Wen W, Sachdev PS, Wei T, Liu T, Wang Y. Disrupted pattern of rich-club organization in structural brain network from prediabetes to diabetes: A population-based study. Hum Brain Mapp 2024; 45:e26598. [PMID: 38339955 PMCID: PMC10839741 DOI: 10.1002/hbm.26598] [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: 04/28/2023] [Revised: 12/22/2023] [Accepted: 01/04/2024] [Indexed: 02/12/2024] Open
Abstract
The network nature of the brain is gradually becoming a consensus in the neuroscience field. A set of highly connected regions in the brain network called "rich-club" are crucial high efficiency communication hubs in the brain. The abnormal rich-club organization can reflect underlying abnormal brain function and metabolism, which receives increasing attention. Diabetes is one of the risk factors for neurological diseases, and most individuals with prediabetes will develop overt diabetes within their lifetime. However, the gradual impact of hyperglycemia on brain structures, including rich-club organization, remains unclear. We hypothesized that the brain follows a special disrupted pattern of rich-club organization in prediabetes and diabetes. We used cross-sectional baseline data from the population-based PolyvasculaR Evaluation for Cognitive Impairment and vaScular Events (PRECISE) study, which included 2218 participants with a mean age of 61.3 ± 6.6 years and 54.1% females comprising 1205 prediabetes, 504 diabetes, and 509 normal control subjects. The rich-club organization and network properties of the structural networks derived from diffusion tensor imaging data were investigated using a graph theory approach. Linear mixed models were used to assess associations between rich-club organization disruptions and the subjects' glucose status. Based on the graphical analysis methods, we observed the disrupted pattern of rich-club organization was from peripheral regions mainly located in frontal areas to rich-club regions mainly located in subcortical areas from prediabetes to diabetes. The rich-club organization disruptions were associated with elevated glucose levels. These findings provided more details of the process by which hyperglycemia affects the brain, contributing to a better understanding of the potential neurological consequences. Furthermore, the disrupted pattern observed in rich-club organization may serve as a potential neuroimaging marker for early detection and monitoring of neurological disorders in individuals with prediabetes or diabetes.
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Affiliation(s)
- Yijun Zhou
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical EngineeringBeihang UniversityBeijingChina
| | - Jing Jing
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Zhe Zhang
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Yuesong Pan
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Xueli Cai
- Department of Neurology, Lishui HospitalZhejiang University School of MedicineLishuiZhejiangChina
| | - Wanlin Zhu
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Zixiao Li
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Chang Liu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical EngineeringBeihang UniversityBeijingChina
| | - Hao Liu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical EngineeringBeihang UniversityBeijingChina
| | - Xia Meng
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Jian Cheng
- School of Computer Science and Engineering, Beihang UniversityBeijingChina
| | - Yilong Wang
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Hao Li
- China National Clinical Research Center for Neurological DiseasesBeijingChina
| | - Suying Wang
- Cerebrovascular Research Lab, Lishui Hospital, Zhejiang University School of MedicineLishuiZhejiangChina
| | - Haijun Niu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical EngineeringBeihang UniversityBeijingChina
| | - Wei Wen
- Division of Psychiatry and Mental Health, Faculty of Medicine and Health, Centre for Healthy Brain Ageing (CHeBA)UNSWSydneyNew South WalesAustralia
- Neuropsychiatric Institute, Prince of Wales HospitalSydneyNew South WalesAustralia
| | - Perminder S. Sachdev
- Division of Psychiatry and Mental Health, Faculty of Medicine and Health, Centre for Healthy Brain Ageing (CHeBA)UNSWSydneyNew South WalesAustralia
- Neuropsychiatric Institute, Prince of Wales HospitalSydneyNew South WalesAustralia
| | - Tiemin Wei
- Department of Cardiology, Lishui HospitalZhejiang University School of MedicineZhejiangChina
| | - Tao Liu
- Beijing Advanced Innovation Center for Biomedical Engineering, School of Biological Science and Medical EngineeringBeihang UniversityBeijingChina
| | - Yongjun Wang
- Department of Neurology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
- China National Clinical Research Center for Neurological DiseasesBeijingChina
- Research Unit of Artificial Intelligence in Cerebrovascular DiseaseChinese Academy of Medical Sciences, 2019RU018BeijingChina
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Guan M, Xie Y, Li C, Zhang T, Ma C, Wang Z, Ma Z, Wang H, Fang P. Rich-club reorganization of white matter structural network in schizophrenia patients with auditory verbal hallucinations following 1 Hz rTMS treatment. Neuroimage Clin 2023; 40:103546. [PMID: 37988997 PMCID: PMC10701084 DOI: 10.1016/j.nicl.2023.103546] [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: 11/12/2023] [Revised: 11/17/2023] [Accepted: 11/17/2023] [Indexed: 11/23/2023]
Abstract
The human brain comprises a large-scale structural network of regions and interregional pathways, including a selectively defined set of highly central and interconnected hub regions, often referred to as the "rich club", which may play a pivotal role in the integrative processes of the brain. A quintessential symptom of schizophrenia, auditory verbal hallucinations (AVH) have shown a decrease in severity following low-frequency repetitive transcranial magnetic stimulation (rTMS). However, the underlying mechanism of rTMS in treating AVH remains elusive. This study investigated the effect of low-frequency rTMS on the rich-club organization within the brain in patients diagnosed with schizophrenia who experience AVH using diffusion tensor imaging data. Through by constructing structural connectivity networks, we identified several critical rich hub nodes, which constituted a rich-club subnetwork, predominantly located in the prefrontal cortices. Notably, our findings revealed enhanced connection strength and density within the rich-club subnetwork following rTMS treatment. Furthermore, we found that the decreased connectivity within the subnetwork components, including the rich-club subnetwork, was notably enhanced in patients following rTMS treatment. In particular, the increased connectivity strength of the right median superior frontal gyrus, which functions as a critical local bridge, with the right postcentral gyrus exhibited a significant correlation with improvements in both positive symptoms and AVH. These findings provide valuable insights into the role of rTMS in inducing reorganizational changes within the rich-club structural network in schizophrenia and shed light on potential mechanisms through which rTMS may alleviate AVH.
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Affiliation(s)
- Muzhen Guan
- Department of Mental Health, Xi'an Medical College, Xi'an, China.
| | - Yuanjun Xie
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China; Department of Radiology, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
| | - Chenxi Li
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Tian Zhang
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Chaozong Ma
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China
| | - Zhongheng Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Zhujing Ma
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China
| | - Huaning Wang
- Department of Psychiatry, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
| | - Peng Fang
- Military Medical Psychology School, Fourth Military Medical University, Xi'an, China.
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