1
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Tan CH, Tan JJX. Associations of cardiac function and arterial stiffness with cerebrovascular disease. Int J Cardiol 2024; 407:132037. [PMID: 38604451 DOI: 10.1016/j.ijcard.2024.132037] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/09/2024] [Revised: 04/05/2024] [Accepted: 04/08/2024] [Indexed: 04/13/2024]
Abstract
BACKGROUND White matter hyperintensities (WMHs) represent diffuse small vessel disease implicating the cardiac, systemic, and cerebral vasculatures. As the brain may be the end-organ of cumulative vascular disease, and higher education is protective of both cardiovascular and brain health, we aim to clarify their intertwining relationships. METHODS We evaluated participants (mean age = 64) from the UK Biobank with neuroimaging measures of WMHs, left ventricular ejection fraction (LVEF) quantified using cardiovascular MRI, and arterial stiffness index (ASI) quantified using finger photoplethysmography. We used multiple regression to evaluate the basic, independent, and interactive relationships of LVEF status (n = 27,512) and ASI (n = 33,584) with WMHs. Moderated mediation analysis was used to determine whether the relationship between LVEF status and WMH was mediated by ASI and moderated by education. RESULTS Abnormal LVEF (β = -0.082, p < 0.001) and higher ASI (β = 0.02, p < 0.001) were associated with greater WMHs separately and independently, but not interactively. Moderated mediation analyses revealed that the relationship between abnormal LVEF and WMH was mediated by ASI, for individuals with lower education (β = -0.004, p < 0.001). Abnormal LVEF was associated with lower cortical thickness in 16 predominantly frontotemporal and select parietal regions (FDR, q < 0.05). CONCLUSIONS Cardiovascular dysfunction is associated with regional cerebral atrophy and may precipitate cerebrovascular disease via stiffening of systemic vasculatures, particularly for individuals with lower education. Integrative approaches to study biophysiological vascular systems can elucidate the complex interplay between biological and social determinants of brain and cerebrovascular health.
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Affiliation(s)
- Chin Hong Tan
- Department of Psychology, Nanyang Technological University, Singapore, Singapore; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
| | - Jacinth J X Tan
- School of Social Sciences, Singapore Management University, Singapore, Singapore
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Huang WQ, Lin Q, Tzeng CM. Leukoaraiosis: Epidemiology, Imaging, Risk Factors, and Management of Age-Related Cerebral White Matter Hyperintensities. J Stroke 2024; 26:131-163. [PMID: 38836265 PMCID: PMC11164597 DOI: 10.5853/jos.2023.02719] [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: 08/18/2023] [Accepted: 01/15/2024] [Indexed: 06/06/2024] Open
Abstract
Leukoaraiosis (LA) manifests as cerebral white matter hyperintensities on T2-weighted magnetic resonance imaging scans and corresponds to white matter lesions or abnormalities in brain tissue. Clinically, it is generally detected in the early 40s and is highly prevalent globally in individuals aged >60 years. From the imaging perspective, LA can present as several heterogeneous forms, including punctate and patchy lesions in deep or subcortical white matter; lesions with periventricular caps, a pencil-thin lining, and smooth halo; as well as irregular lesions, which are not always benign. Given its potential of having deleterious effects on normal brain function and the resulting increase in public health burden, considerable effort has been focused on investigating the associations between various risk factors and LA risk, and developing its associated clinical interventions. However, study results have been inconsistent, most likely due to potential differences in study designs, neuroimaging methods, and sample sizes as well as the inherent neuroimaging heterogeneity and multi-factorial nature of LA. In this article, we provided an overview of LA and summarized the current knowledge regarding its epidemiology, neuroimaging classification, pathological characteristics, risk factors, and potential intervention strategies.
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Affiliation(s)
- Wen-Qing Huang
- Department of Central Laboratory, Shanghai Children's Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China
| | - Qing Lin
- Department of Neurology, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, China
- Xiamen Clinical Research Center for Neurological Diseases, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, China
- Fujian Provincial Clinical Research Center for Brain Diseases, The First Affiliated Hospital of Xiamen University, School of Medicine, Xiamen University, Xiamen, Fujian, China
- The Third Clinical College, Fujian Medical University, Fuzhou, Fujian, China
| | - Chi-Meng Tzeng
- Translational Medicine Research Center, School of Pharmaceutical Sciences, Xiamen University, Xiamen, Fujian, China
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Fu X, Wan XJ, Liu JY, Sun Q, Shen Y, Li J, Mao CJ, Ma QH, Wang F, Liu CF. Effects of sleep fragmentation on white matter pathology in a rat model of cerebral small vessel disease. Sleep 2024; 47:zsad225. [PMID: 37638817 DOI: 10.1093/sleep/zsad225] [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: 06/02/2023] [Revised: 08/10/2023] [Indexed: 08/29/2023] Open
Abstract
STUDY OBJECTIVES Mounting evidence indicated the correlation between sleep and cerebral small vessel disease (CSVD). However, little is known about the exact causality between poor sleep and white matter injury, a typical signature of CSVD, as well as the underlying mechanisms. METHODS Spontaneously hypertensive rats (SHR) and control Wistar Kyoto rats were subjected to sleep fragmentation (SF) for 16 weeks. The effects of chronic sleep disruption on the deep white matter and cognitive performance were observed. RESULTS SHR were validated as a rat model for CSVD. Fragmented sleep induced strain-dependent white matter abnormalities, characterized by reduced myelin integrity, impaired oligodendrocytes precursor cells (OPC) maturation and pro-inflammatory microglial polarization. Partially reversible phenotypes of OPC and microglia were observed in parallel following sleep recovery. CONCLUSIONS Long-term SF-induced pathological effects on the deep white matter in a rat model of CSVD. The pro-inflammatory microglial activation and the block of OPC maturation may be involved in the mechanisms linking sleep to white matter injury.
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Affiliation(s)
- Xiang Fu
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
- Jiangsu Key Laboratory of Neuropsychiatric Diseases and Institute of Neuroscience, Soochow University, Suzhou, China
| | - Xiao-Jie Wan
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
- Jiangsu Key Laboratory of Neuropsychiatric Diseases and Institute of Neuroscience, Soochow University, Suzhou, China
| | - Jun-Yi Liu
- Jiangsu Key Laboratory of Neuropsychiatric Diseases and Institute of Neuroscience, Soochow University, Suzhou, China
| | - Qian Sun
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Yun Shen
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Jie Li
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
| | - Cheng-Jie Mao
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
- Jiangsu Key Laboratory of Neuropsychiatric Diseases and Institute of Neuroscience, Soochow University, Suzhou, China
| | - Quan-Hong Ma
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
- Jiangsu Key Laboratory of Neuropsychiatric Diseases and Institute of Neuroscience, Soochow University, Suzhou, China
| | - Fen Wang
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
- Jiangsu Key Laboratory of Neuropsychiatric Diseases and Institute of Neuroscience, Soochow University, Suzhou, China
| | - Chun-Feng Liu
- Department of Neurology and Clinical Research Center of Neurological Disease, The Second Affiliated Hospital of Soochow University, Suzhou, China
- Jiangsu Key Laboratory of Neuropsychiatric Diseases and Institute of Neuroscience, Soochow University, Suzhou, China
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Clancy U, Cheng Y, Brara A, Doubal FN, Wardlaw JM. Occupational and domestic exposure associations with cerebral small vessel disease and vascular dementia: A systematic review and meta-analysis. Alzheimers Dement 2024; 20:3021-3033. [PMID: 38270898 PMCID: PMC11032565 DOI: 10.1002/alz.13647] [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: 09/13/2023] [Revised: 11/24/2023] [Accepted: 11/27/2023] [Indexed: 01/26/2024]
Abstract
INTRODUCTION The prevalence of cerebral smallvessel disease (SVD) and vascular dementia according to workplace or domestic exposure to hazardous substances is unclear. METHODS We included studies assessing occupational and domestic hazards/at-risk occupations and SVD features. We pooled prevalence estimates using random-effects models where possible, or presented a narrative synthesis. RESULTS We included 85 studies (n = 47,743, mean age = 44·5 years). 52/85 reported poolable estimates. SVD prevalence in populations exposed to carbon monoxide was 81%(95% CI = 60-93%; n = 1373; results unchanged in meta-regression), carbon disulfide73% (95% CI = 54-87%; n = 131), 1,2-dichloroethane 88% (95% CI = 4-100%, n = 40), toluene 82% (95% CI = 3-100%, n = 64), high altitude 49% (95% CI = 38-60%; n = 164),and diving 24% (95% CI = 5-67%, n = 172). We narratively reviewed vascular dementia studies and contact sport, lead, military, pesticide, and solvent exposures as estimates were too few/varied to pool. DISCUSSION SVD and vascular dementia may be associated with occupational/domestic exposure to hazardous substances. CRD42021297800.
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Affiliation(s)
- Una Clancy
- Centre for Clinical Brain Sciences and the UK Dementia Research InstituteChancellor's BuildingUniversity of EdinburghEdinburghUK
| | - Yajun Cheng
- Center of Cerebrovascular DiseasesDepartment of NeurologyWest China HospitalSichuan UniversityChengduSichuanChina
| | - Amrita Brara
- Centre for Clinical Brain Sciences and the UK Dementia Research InstituteChancellor's BuildingUniversity of EdinburghEdinburghUK
| | - Fergus N. Doubal
- Centre for Clinical Brain Sciences and the UK Dementia Research InstituteChancellor's BuildingUniversity of EdinburghEdinburghUK
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences and the UK Dementia Research InstituteChancellor's BuildingUniversity of EdinburghEdinburghUK
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Backhouse EV, Boardman JP, Wardlaw JM. Cerebral Small Vessel Disease: Early-Life Antecedents and Long-Term Implications for the Brain, Aging, Stroke, and Dementia. Hypertension 2024; 81:54-74. [PMID: 37732415 PMCID: PMC10734792 DOI: 10.1161/hypertensionaha.122.19940] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
Cerebral small vessel disease is common in older adults and increases the risk of stroke, cognitive impairment, and dementia. While often attributed to midlife vascular risk factors such as hypertension, factors from earlier in life may contribute to later small vessel disease risk. In this review, we summarize current evidence for early-life effects on small vessel disease, stroke and dementia focusing on prenatal nutrition, and cognitive ability, education, and socioeconomic status in childhood. We discuss possible reasons for these associations, including differences in brain resilience and reserve, access to cognitive, social, and economic resources, and health behaviors, and we consider the extent to which these associations are independent of vascular risk factors. Although early-life factors, particularly education, are major risk factors for Alzheimer disease, they are less established in small vessel disease or vascular cognitive impairment. We discuss current knowledge, gaps in knowledge, targets for future research, clinical practice, and policy change.
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Affiliation(s)
- Ellen V. Backhouse
- Centre for Clinical Brain Sciences (E.V.B., J.P.B., J.M.W.), University of Edinburgh, Scotland, United Kingdom
- MRC UK Dementia Research Institute (E.V.B., J.M.W.), University of Edinburgh, Scotland, United Kingdom
| | - James P. Boardman
- Centre for Clinical Brain Sciences (E.V.B., J.P.B., J.M.W.), University of Edinburgh, Scotland, United Kingdom
- MRC Centre for Reproductive Health (J.P.B.), University of Edinburgh, Scotland, United Kingdom
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences (E.V.B., J.P.B., J.M.W.), University of Edinburgh, Scotland, United Kingdom
- MRC UK Dementia Research Institute (E.V.B., J.M.W.), University of Edinburgh, Scotland, United Kingdom
- Edinburgh Imaging (J.M.W.), University of Edinburgh, Scotland, United Kingdom
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Schindler LS, Subramaniapillai S, Ambikairajah A, Barth C, Crestol A, Voldsbekk I, Beck D, Gurholt TP, Topiwala A, Suri S, Ebmeier KP, Andreassen OA, Draganski B, Westlye LT, de Lange AMG. Cardiometabolic health across menopausal years is linked to white matter hyperintensities up to a decade later. Front Glob Womens Health 2023; 4:1320640. [PMID: 38213741 PMCID: PMC10783171 DOI: 10.3389/fgwh.2023.1320640] [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: 10/12/2023] [Accepted: 12/06/2023] [Indexed: 01/13/2024] Open
Abstract
Introduction The menopause transition is associated with several cardiometabolic risk factors. Poor cardiometabolic health is further linked to microvascular brain lesions, which can be detected as white matter hyperintensities (WMHs) using T2-FLAIR magnetic resonance imaging (MRI) scans. Females show higher risk for WMHs post-menopause, but it remains unclear whether changes in cardiometabolic risk factors underlie menopause-related increase in brain pathology. Methods In this study, we assessed whether cross-sectional measures of cardiometabolic health, including body mass index (BMI) and waist-to-hip ratio (WHR), blood lipids, blood pressure, and long-term blood glucose (HbA1c), as well as longitudinal changes in BMI and WHR, differed according to menopausal status at baseline in 9,882 UK Biobank females (age range 40-70 years, n premenopausal = 3,529, n postmenopausal = 6,353). Furthermore, we examined whether these cardiometabolic factors were associated with WMH outcomes at the follow-up assessment, on average 8.78 years after baseline. Results Postmenopausal females showed higher levels of baseline blood lipids (HDL β = 0.14, p < 0.001, LDL β = 0.20, p < 0.001, triglycerides β = 0.12, p < 0.001) and HbA1c (β = 0.24, p < 0.001) compared to premenopausal women, beyond the effects of age. Over time, BMI increased more in the premenopausal compared to the postmenopausal group (β = -0.08, p < 0.001), while WHR increased to a similar extent in both groups (β = -0.03, p = 0.102). The change in WHR was however driven by increased waist circumference only in the premenopausal group. While the group level changes in BMI and WHR were in general small, these findings point to distinct anthropometric changes in pre- and postmenopausal females over time. Higher baseline measures of BMI, WHR, triglycerides, blood pressure, and HbA1c, as well as longitudinal increases in BMI and WHR, were associated with larger WMH volumes (β range = 0.03-0.13, p ≤ 0.002). HDL showed a significant inverse relationship with WMH volume (β = -0.27, p < 0.001). Discussion Our findings emphasise the importance of monitoring cardiometabolic risk factors in females from midlife through the menopause transition and into the postmenopausal phase, to ensure improved cerebrovascular outcomes in later years.
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Affiliation(s)
- Louise S. Schindler
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Sivaniya Subramaniapillai
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
| | - Ananthan Ambikairajah
- Discipline of Psychology, Faculty of Health, University of Canberra, Canberra, Australia
- National Centre for Epidemiology and Population Health, Australian National University, Canberra, Australia
| | - Claudia Barth
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Arielle Crestol
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Irene Voldsbekk
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Dani Beck
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatric Research, Diakonhjemmet Hospital, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Tiril P. Gurholt
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
| | - Anya Topiwala
- Nuffield Department Population Health, Big Data Institute, University of Oxford, Oxford, United Kingdom
| | - Sana Suri
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
- Wellcome Centre for Integrative Neuroimaging, University of Oxford, Oxford, United Kingdom
| | - Klaus P. Ebmeier
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
| | - Ole A. Andreassen
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Bogdan Draganski
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Lars T. Westlye
- Department of Psychology, University of Oslo, Oslo, Norway
- NORMENT, Division of Mental Health and Addiction, Oslo University Hospital & Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, Norway
| | - Ann-Marie G. de Lange
- LREN, Centre for Research in Neurosciences, Department of Clinical Neurosciences, Lausanne University Hospital (CHUV) and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, University of Oslo, Oslo, Norway
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom
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Backhouse EV, Bauermeister S, Wardlaw JM. Lifetime influences on imaging markers of adverse brain health and vascular disease. CEREBRAL CIRCULATION - COGNITION AND BEHAVIOR 2023; 6:100194. [PMID: 38292018 PMCID: PMC10827485 DOI: 10.1016/j.cccb.2023.100194] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/08/2023] [Revised: 11/13/2023] [Accepted: 12/11/2023] [Indexed: 02/01/2024]
Abstract
Cerebral small vessel disease (cSVD) is highly prevalent in the general population, increases with age and vascular risk factor exposure, and is a common cause of stroke and dementia. There is great variation in cSVD burden experienced in older age, and maintaining brain health across the life course requires looking beyond an individual's current clinical status and traditional vascular risk factors. Of particular importance are social determinants of health which can be more important than healthcare or lifestyle choices in influencing later life health outcomes, including brain health. In this paper we discuss the social determinants of cerebrovascular disease, focusing on the impact of socioeconomic status on markers of cSVD. We outline the potential mechanisms behind these associations, including early life exposures, health behaviours and brain reserve and maintenance, and we highlight the importance of public health interventions to address the key determinants and risk factors for cSVD from early life stages.
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Affiliation(s)
- Ellen V Backhouse
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- MRC UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
| | - Sarah Bauermeister
- Department of Psychiatry, University of Oxford, Oxford OX3 7JX, UK
- MRC UK Dementia Research Institute, University of Oxford, Oxford OX3 7JX, UK
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor's Building, 49 Little France Crescent, Edinburgh EH16 4SB, UK
- MRC UK Dementia Research Institute, University of Edinburgh, Edinburgh, UK
- Edinburgh Imaging, University of Edinburgh, Edinburgh, UK
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Han S, Sun D, Jiang B, Sun H, Ru X, Jin A, Wang Y, Wang W. Prevalence and distribution of lacunar stroke in China: a cross-sectional study using self-reported survey data. BMJ Open 2022; 12:e063520. [PMID: 36585136 PMCID: PMC9809241 DOI: 10.1136/bmjopen-2022-063520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/31/2022] Open
Abstract
OBJECTIVES To report the prevalence and distribution of lacunar stroke in different regions of China, as well as the demographical characteristics of symptomatic and asymptomatic lacunar stroke. DESIGN Cross-sectional study. SETTING Data were derived from NESS-China Study that was conducted in 157 sites covering all 31 provinces, including 64 urban and 93 rural areas in mainland China between 1 September 2013 and 31 December 2013. Lacunar stroke was defined as being previously diagnosed according to the participants' medical history. Patients were further divided into symptomatic or asymptomatic groups, depending on whether they were initially diagnosed with neurological symptoms. PARTICIPANTS 458 833 participants aged ≥20 years were enrolled in this study. RESULTS A total of 7520 participants (1.63%) were diagnosed with lacunar stroke. The peak rate of diagnosis was between the ages of 70 and 79 years in both men and women. Geographically, the age-standardised and sex-standardised prevalence was highest in Northeast China (2495.3/100 000 persons) and lowest in Southeast China (599.7/100 000 persons), showing a geographical disparity. Over 90% of patients with lacunar stroke were diagnosed in secondary or tertiary hospitals. Patients with symptomatic lacunar stroke had significantly different demographic characteristics in age, sex and geographical regions compared with those who were asymptomatic. CONCLUSIONS In this study, the prevalence and distribution of lacunar stroke were reported at population level across China. Special attention and prevention should be given to the age, sex and geographical groups that are vulnerable to lacunar stroke.
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Affiliation(s)
- Shangrong Han
- Department of Neurology, Beijing Tiantan Hospital, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Dongling Sun
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Bin Jiang
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Haixin Sun
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Xiaojuan Ru
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
| | - Aoming Jin
- Department of Neurology, Beijing Tiantan Hospital, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Yilong Wang
- Department of Neurology, Beijing Tiantan Hospital, Beijing, China
- China National Clinical Research Center for Neurological Diseases, Beijing, China
| | - Wenzhi Wang
- Beijing Neurosurgical Institute, Capital Medical University, Beijing, China
- Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing, China
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Wan S, Dandu C, Han G, Guo Y, Ding Y, Song H, Meng R. Plasma inflammatory biomarkers in cerebral small vessel disease: A review. CNS Neurosci Ther 2022; 29:498-515. [PMID: 36478511 PMCID: PMC9873530 DOI: 10.1111/cns.14047] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 10/24/2022] [Accepted: 11/22/2022] [Indexed: 12/12/2022] Open
Abstract
Cerebral small vessel disease (CSVD) is a group of pathological processes affecting small arteries, arterioles, capillaries, and small veins of the brain. It is one of the most common subtypes of cerebrovascular diseases, especially highly prevalent in elderly populations, and is associated with stroke occurrence and recurrence, cognitive impairment, gait disorders, psychological disturbance, and dysuria. Its diagnosis mainly depends on MRI, characterized by recent small subcortical infarcts, lacunes, white matter hyperintensities (WMHs), enlarged perivascular spaces (EPVS), cerebral microbleeds (CMBs), and brain atrophy. While the pathophysiological processes of CSVD are not fully understood at present, inflammation is noticed as playing an important role. Herein, we aimed to review the relationship between plasma inflammatory biomarkers and the MRI features of CSVD, to provide background for further research.
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Affiliation(s)
- Shuling Wan
- Department of Neurology, National Center for Neurological Disorders, Xuanwu HospitalCapital Medical UniversityBeijingChina,Advanced Center of StrokeBeijing Institute for Brain DisordersBeijingChina
| | - Chaitu Dandu
- Department of NeurosurgeryWayne State University School of MedicineDetroitMichiganUSA
| | - Guangyu Han
- Department of Neurology, National Center for Neurological Disorders, Xuanwu HospitalCapital Medical UniversityBeijingChina,Advanced Center of StrokeBeijing Institute for Brain DisordersBeijingChina
| | - Yibing Guo
- Department of Neurology, National Center for Neurological Disorders, Xuanwu HospitalCapital Medical UniversityBeijingChina,Advanced Center of StrokeBeijing Institute for Brain DisordersBeijingChina
| | - Yuchuan Ding
- Department of NeurosurgeryWayne State University School of MedicineDetroitMichiganUSA
| | - Haiqing Song
- Department of Neurology, National Center for Neurological Disorders, Xuanwu HospitalCapital Medical UniversityBeijingChina,Advanced Center of StrokeBeijing Institute for Brain DisordersBeijingChina
| | - Ran Meng
- Department of Neurology, National Center for Neurological Disorders, Xuanwu HospitalCapital Medical UniversityBeijingChina,Advanced Center of StrokeBeijing Institute for Brain DisordersBeijingChina,Department of NeurosurgeryWayne State University School of MedicineDetroitMichiganUSA
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10
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Wagen AZ, Coath W, Keshavan A, James SN, Parker TD, Lane CA, Buchanan SM, Keuss SE, Storey M, Lu K, Macdougall A, Murray-Smith H, Freiberger T, Cash DM, Malone IB, Barnes J, Sudre CH, Wong A, Pavisic IM, Street R, Crutch SJ, Escott-Price V, Leonenko G, Zetterberg H, Wellington H, Heslegrave A, Barkhof F, Richards M, Fox NC, Cole JH, Schott JM. Life course, genetic, and neuropathological associations with brain age in the 1946 British Birth Cohort: a population-based study. THE LANCET. HEALTHY LONGEVITY 2022; 3:e607-e616. [PMID: 36102775 PMCID: PMC10499760 DOI: 10.1016/s2666-7568(22)00167-2] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2022] [Revised: 06/29/2022] [Accepted: 06/30/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND A neuroimaging-based biomarker termed the brain age is thought to reflect variability in the brain's ageing process and predict longevity. Using Insight 46, a unique narrow-age birth cohort, we aimed to examine potential drivers and correlates of brain age. METHODS Participants, born in a single week in 1946 in mainland Britain, have had 24 prospective waves of data collection to date, including MRI and amyloid PET imaging at approximately 70 years old. Using MRI data from a previously defined selection of this cohort, we derived brain-predicted age from an established machine-learning model (trained on 2001 healthy adults aged 18-90 years); subtracting this from chronological age (at time of assessment) gave the brain-predicted age difference (brain-PAD). We tested associations with data from early life, midlife, and late life, as well as rates of MRI-derived brain atrophy. FINDINGS Between May 28, 2015, and Jan 10, 2018, 502 individuals were assessed as part of Insight 46. We included 456 participants (225 female), with a mean chronological age of 70·7 years (SD 0·7; range 69·2 to 71·9). The mean brain-predicted age was 67·9 years (8·2, 46·3 to 94·3). Female sex was associated with a 5·4-year (95% CI 4·1 to 6·8) younger brain-PAD than male sex. An increase in brain-PAD was associated with increased cardiovascular risk at age 36 years (β=2·3 [95% CI 1·5 to 3·0]) and 69 years (β=2·6 [1·9 to 3·3]); increased cerebrovascular disease burden (1·9 [1·3 to 2·6]); lower cognitive performance (-1·3 [-2·4 to -0·2]); and increased serum neurofilament light concentration (1·2 [0·6 to 1·9]). Higher brain-PAD was associated with future hippocampal atrophy over the subsequent 2 years (0·003 mL/year [0·000 to 0·006] per 5-year increment in brain-PAD). Early-life factors did not relate to brain-PAD. Combining 12 metrics in a hierarchical partitioning model explained 33% of the variance in brain-PAD. INTERPRETATION Brain-PAD was associated with cardiovascular risk, and imaging and biochemical markers of neurodegeneration. These findings support brain-PAD as an integrative summary metric of brain health, reflecting multiple contributions to pathological brain ageing, and which might have prognostic utility. FUNDING Alzheimer's Research UK, Medical Research Council Dementia Platforms UK, Selfridges Group Foundation, Wolfson Foundation, Wellcome Trust, Brain Research UK, Alzheimer's Association.
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Affiliation(s)
- Aaron Z Wagen
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, UK; Neurodegeneration Biology Laboratory, The Francis Crick Institute, London, UK
| | - William Coath
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Ashvini Keshavan
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Sarah-Naomi James
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Thomas D Parker
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Department of Brain Sciences, Imperial College London, London, UK; UK Dementia Research Institute Centre for Care Research and Technology, Imperial College London, London, UK
| | - Christopher A Lane
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Sarah M Buchanan
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Sarah E Keuss
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Mathew Storey
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Kirsty Lu
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Amy Macdougall
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Department of Medical Statistics, London School of Hygiene & Tropical Medicine, London, UK
| | - Heidi Murray-Smith
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Tamar Freiberger
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - David M Cash
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK
| | - Ian B Malone
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Josephine Barnes
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Carole H Sudre
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK; Department of Computer Science, Centre for Medical Imaging Computing, University College London, London, UK; School of Biomedical Engineering and Imaging Sciences, King's College London, London, UK
| | - Andrew Wong
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Ivanna M Pavisic
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Rebecca Street
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | - Sebastian J Crutch
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK
| | | | - Ganna Leonenko
- Dementia Research Institute, Cardiff University, Cardiff, UK
| | - Henrik Zetterberg
- Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK; Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henrietta Wellington
- Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK; Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK
| | - Amanda Heslegrave
- Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK; Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK
| | - Frederik Barkhof
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Department of Neurodegenerative Disease, University College London Queen Square Institute of Neurology, London, UK; Department of Computer Science, Centre for Medical Imaging Computing, University College London, London, UK; Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centre, Vrije Universiteit, Amsterdam, Netherlands
| | - Marcus Richards
- Medical Research Council Unit for Lifelong Health and Ageing, University College London, London, UK
| | - Nick C Fox
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK
| | - James H Cole
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Department of Computer Science, Centre for Medical Imaging Computing, University College London, London, UK
| | - Jonathan M Schott
- Dementia Research Centre, University College London Queen Square Institute of Neurology, London, UK; Dementia Research Institute, University College London Queen Square Institute of Neurology, London, UK.
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11
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Quick S, Procter TV, Moss J, Seeker L, Walton M, Lawson A, Baker S, Beletski A, Garcia DJ, Mohammad M, Mungall W, Onishi A, Tobola Z, Stringer M, Jansen MA, Vallatos A, Giarratano Y, Bernabeu MO, Wardlaw JM, Williams A. Loss of the heterogeneous expression of flippase ATP11B leads to cerebral small vessel disease in a normotensive rat model. Acta Neuropathol 2022; 144:283-303. [PMID: 35635573 PMCID: PMC9288385 DOI: 10.1007/s00401-022-02441-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2022] [Revised: 05/18/2022] [Accepted: 05/18/2022] [Indexed: 01/20/2023]
Abstract
Cerebral small vessel disease (SVD) is the leading cause of vascular dementia, causes a quarter of strokes, and worsens stroke outcomes. The disease is characterised by patchy cerebral small vessel and white matter pathology, but the underlying mechanisms are poorly understood. This microvascular and tissue damage has been classically considered secondary to extrinsic factors, such as hypertension, but this fails to explain the patchy nature of the disease, the link to endothelial cell (EC) dysfunction even when hypertension is absent, and the increasing evidence of high heritability to SVD-related brain damage. We have previously shown the link between deletion of the phospholipase flippase Atp11b and EC dysfunction in an inbred hypertensive rat model with SVD-like pathology and a single nucleotide polymorphism (SNP) in ATP11B associated with human sporadic SVD. Here, we generated a novel normotensive transgenic rat model, where Atp11b is deleted, and show pathological, imaging and behavioural changes typical of those in human SVD, but that occur without hypertension. Atp11bKO rat brain and retinal small vessels show ECs with molecular and morphological changes of dysfunction, with myelin disruption in a patchy pattern around some but not all brain small vessels, similar to the human brain. We show that ATP11B/ATP11B is heterogeneously expressed in ECs in normal rat and human brain even in the same transverse section of the same blood vessel, suggesting variable effects of the loss of ATP11B on each vessel and an explanation for the patchy nature of the disease. This work highlights a link between inherent EC dysfunction and vulnerability to SVD white matter damage with a marked heterogeneity of ECs in vivo which modulates this response, occurring even in the absence of hypertension. These findings refocus our strategies for therapeutics away from antihypertensive (and vascular risk factor) control alone and towards ECs in the effort to provide alternative targets to prevent a major cause of stroke and dementia.
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Affiliation(s)
- Sophie Quick
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, EH16 4UU, UK
| | - Tessa V Procter
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, EH16 4UU, UK
| | - Jonathan Moss
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, EH16 4UU, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Luise Seeker
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, EH16 4UU, UK
| | - Marc Walton
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, EH16 4UU, UK
| | - Angus Lawson
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, EH16 4UU, UK
| | - Serena Baker
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, EH16 4UU, UK
| | - Anna Beletski
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, EH16 4UU, UK
| | - Daniela Jaime Garcia
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, EH16 4UU, UK
| | - Mehreen Mohammad
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, EH16 4SB, UK
| | - William Mungall
- Bioresearch and Veterinary Services, University of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Ami Onishi
- Bioresearch and Veterinary Services, University of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Zuzanna Tobola
- Centre for Clinical Brain Sciences, Edinburgh Imaging, Row Fogo Centre for Research into Ageing and the Brain, University of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Michael Stringer
- Centre for Clinical Brain Sciences, Edinburgh Imaging, Row Fogo Centre for Research into Ageing and the Brain, University of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Maurits A Jansen
- Centre for Cardiovascular Science, University of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Antoine Vallatos
- Centre for Clinical Brain Sciences, Edinburgh Imaging, Row Fogo Centre for Research into Ageing and the Brain, University of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Ylenia Giarratano
- College of Medicine and Veterinary Medicine, College of Science and Engineering, Bayes Centre, Usher Institute, University of Edinburgh, Edinburgh, EH16 4UX, UK
| | - Miguel O Bernabeu
- College of Medicine and Veterinary Medicine, College of Science and Engineering, Bayes Centre, Usher Institute, University of Edinburgh, Edinburgh, EH16 4UX, UK
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, Edinburgh Imaging, Row Fogo Centre for Research into Ageing and the Brain, University of Edinburgh, Edinburgh, EH16 4SB, UK
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Anna Williams
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, EH16 4UU, UK.
- UK Dementia Research Institute, University of Edinburgh, Edinburgh, EH16 4SB, UK.
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12
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Ibitoye RT, Castro P, Cooke J, Allum J, Arshad Q, Murdin L, Wardlaw J, Kaski D, Sharp DJ, Bronstein AM. A link between frontal white matter integrity and dizziness in cerebral small vessel disease. Neuroimage Clin 2022; 35:103098. [PMID: 35772195 PMCID: PMC9253455 DOI: 10.1016/j.nicl.2022.103098] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2022] [Revised: 05/30/2022] [Accepted: 06/21/2022] [Indexed: 11/18/2022]
Abstract
Idiopathic dizziness in older people is associated with more vascular risk. Idiopathic dizziness is also associated with impaired balance and cognition. These findings co-occur with more frontal markers of cerebral small vessel disease. Small vessel disease may contribute to dizziness through its effects on balance.
One in three older people (>60 years) complain of dizziness which often remains unexplained despite specialist assessment. We investigated if dizziness was associated with vascular injury to white matter tracts relevant to balance or vestibular self-motion perception in sporadic cerebral small vessel disease (age-related microangiopathy). We prospectively recruited 38 vestibular clinic patients with idiopathic (unexplained) dizziness and 36 age-matched asymptomatic controls who underwent clinical, cognitive, balance, gait and vestibular assessments, and structural and diffusion brain MRI. Patients had more vascular risk factors, worse balance, worse executive cognitive function, and worse ankle vibration thresholds in association with greater white matter hyperintensity in frontal deep white matter, and lower fractional anisotropy in the genu of the corpus callosum and the right inferior longitudinal fasciculus. A large bihemispheric white matter network had less structural connectivity in patients. Reflex and perceptual vestibular function was similar in patients and controls. Our results suggest cerebral small vessel disease is involved in the genesis of dizziness through its effect on balance.
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Affiliation(s)
- Richard T Ibitoye
- Neuro-otology Unit, Imperial College London, London, UK; The Computational, Cognitive and Clinical Neuroimaging Laboratory (C3NL), Imperial College London, London, UK
| | | | - Josie Cooke
- Neuro-otology Unit, Imperial College London, London, UK
| | - John Allum
- Department of Otorhinolaryngology (ORL), University Hospital Basel, Basel, Switzerland
| | - Qadeer Arshad
- inAmind Laboratory, Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
| | - Louisa Murdin
- Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - Joanna Wardlaw
- Centre for Clinical Brain Sciences, UK Dementia Research Institute, The University of Edinburgh, UK
| | - Diego Kaski
- Neuro-otology Unit, Imperial College London, London, UK; Department of Clinical and Movement Neurosciences, University College London, London, UK
| | - David J Sharp
- The Computational, Cognitive and Clinical Neuroimaging Laboratory (C3NL), Imperial College London, London, UK
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13
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Del Brutto OH, Mera RM, Recalde BY, Rumbea DA, Del Brutto VJ. High Social Risk Influence Progression of White Matter Hyperintensities of Presumed Vascular Origin: A Prospective Study in Community-Dwelling Older Adults. Stroke 2022; 53:2577-2584. [PMID: 35506386 DOI: 10.1161/strokeaha.122.038561] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND Information on cerebrovascular consequences of high social risk, as determined by the social determinants of health, is limited. We sought to evaluate the impact of high social risk on the progression of white matter hyperintensities (WMHs) of presumed vascular origin. METHODS Following a longitudinal prospective study design, participants of the Atahualpa Project Cohort received baseline social risk determinations by means of social determinants of health components included in the Gijon's Social-Familial Evaluation Scale together with clinical interviews and brain magnetic resonance imagings. Those who also received follow-up brain magnetic resonance imaging at the end of the study were included. We used Poisson regression models adjusted for demographics, education levels and traditional cardiovascular risk factors to assess the incidence rate ratio of WMH progression according to the Gijon's Social-Familial Evaluation Scale score. RESULTS The study included 263 individuals aged ≥60 years (mean age, 65.7±6.2 years; 57% women). The Gijon's Social-Familial Evaluation Scale mean score was 8.9±2.2 points. Follow-up magnetic resonance imagings revealed WMH progression in 103 (39%) individuals after a mean follow-up of 6.5 years (SD±1.4 years). Poisson regression models showed increased WMH progression rate among individuals in the third tertile of the Gijon's Social-Familial Evaluation Scale score compared with those in the first tertile (incidence rate ratio, 1.65 [95% CI, 1.05-2.61]; P=0.032). Separate Poisson regression models using individual social determinants of health components showed that poor social relationships (incidence rate ratio, 1.39 [95% CI, 1.10-1.77]; P=0.006) and deficient support networks (incidence rate ratio, 1.79 [95% CI, 1.19-2.69]; P=0.005) were independently associated with WMH progression, whereas family situation, economic status, and housing did not. CONCLUSIONS Poor social relationships and deficient support networks were significantly associated with WMH progression in community-dwelling older adults living in a rural setting. Our findings may help planning cost-effective preventive policies to reduce progression of cerebral small vessel disease among vulnerable populations.
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Affiliation(s)
- Oscar H Del Brutto
- School of Medicine and Research Center, Universidad Espíritu Santo - Ecuador, Samborondón (O.H.D.B., B.Y.R., D.A.R.)
| | - Robertino M Mera
- Department of Biostatistics/Epidemiology, Freenome, Inc, South San Francisco, CA (R.M.M.)
| | - Bettsy Y Recalde
- School of Medicine and Research Center, Universidad Espíritu Santo - Ecuador, Samborondón (O.H.D.B., B.Y.R., D.A.R.)
| | - Denisse A Rumbea
- School of Medicine and Research Center, Universidad Espíritu Santo - Ecuador, Samborondón (O.H.D.B., B.Y.R., D.A.R.)
| | - Victor J Del Brutto
- Department of Neurology, University of Miami, Miller School of Medicine, FL (V.J.D.B.), USA
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14
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Wardlaw JM, Benveniste H, Williams A. Cerebral Vascular Dysfunctions Detected in Human Small Vessel Disease and Implications for Preclinical Studies. Annu Rev Physiol 2022; 84:409-434. [PMID: 34699267 DOI: 10.1146/annurev-physiol-060821-014521] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Cerebral small vessel disease (SVD) is highly prevalent and a common cause of ischemic and hemorrhagic stroke and dementia, yet the pathophysiology is poorly understood. Its clinical expression is highly varied, and prognostic implications are frequently overlooked in clinics; thus, treatment is currently confined to vascular risk factor management. Traditionally, SVD is considered the small vessel equivalent of large artery stroke (occlusion, rupture), but data emerging from human neuroimaging and genetic studies refute this, instead showing microvessel endothelial dysfunction impacting on cell-cell interactions and leading to brain damage. These dysfunctions reflect defects that appear to be inherited and secondary to environmental exposures, including vascular risk factors. Interrogation in preclinical models shows consistent and converging molecular and cellular interactions across the endothelial-glial-neural unit that increasingly explain the human macroscopic observations and identify common patterns of pathology despite different triggers. Importantly, these insights may offer new targets for therapeutic intervention focused on restoring endothelial-glial physiology.
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Affiliation(s)
- Joanna M Wardlaw
- Division of Neuroimaging Sciences, Centre for Clinical Brain Sciences; UK Dementia Research Institute; and Edinburgh Imaging, University of Edinburgh, Edinburgh, United Kingdom;
| | - Helene Benveniste
- Department of Anesthesiology, Yale School of Medicine, New Haven, Connecticut, USA
| | - Anna Williams
- Centre for Regenerative Medicine, Institute for Regeneration and Repair, University of Edinburgh, Edinburgh, United Kingdom
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15
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Clancy U, Makin SD, McHutchison CA, Cvoro V, Chappell FM, Hernández MDCV, Sakka E, Doubal F, Wardlaw JM. Impact of Small Vessel Disease Progression on Long-term Cognitive and Functional Changes After Stroke. Neurology 2022; 98:e1459-e1469. [PMID: 35131905 PMCID: PMC8992602 DOI: 10.1212/wnl.0000000000200005] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Accepted: 01/03/2022] [Indexed: 11/30/2022] Open
Abstract
Background and Objectives The severity of white matter hyperintensities (WMH) at presentation with stroke is associated with poststroke dementia and dependency. However, WMH can decrease or increase after stroke; prediction of cognitive decline is imprecise; and there are few data assessing longitudinal interrelationships among changing WMH, cognition, and function after stroke, despite the clinical importance. Methods We recruited patients within 3 months of a minor ischemic stroke, defined as NIH Stroke Scale (NIHSS) score <8 and not expected to result in a modified Rankin Scale (mRS) score >2. Participants repeated MRI at 1 year and cognitive and mRS assessments at 1 and 3 years. We ran longitudinal mixed-effects models assessing change in Addenbrooke’s Cognitive Examination–Revised (ACE-R) and mRS scores. For mRS score, we assessed longitudinal WMH volumes (cube root; percentage intracranial volume [ICV]), adjusting for age, NIHSS score, ACE-R, stroke subtype, and time to assessment. For ACE-R score, we additionally adjusted for ICV, mRS, premorbid IQ, and vascular risk factors. We then used a multivariate model to jointly assess changing cognition/mRS score, adjusted for prognostic variables, using all available data. Results We recruited 264 patients; mean age was 66.9 (SD 11.8) years; 41.7% were female; and median mRS score was 1 (interquartile range 1–2). One year after stroke, normalized WMH volumes were associated more strongly with 1-year ACE-R score (β = −0.259, 95% CI −0.407 to −0.111 more WMH per 1-point ACE-R decrease, p = 0.001) compared to subacute WMH volumes and ACE-R score (β = 0.105, 95% CI −0.265 to 0.054, p = 0.195). Three-year mRS score was associated with 3-year ACE-R score (β = −0.272, 95% CI −0.429 to −0.115, p = 0.001). Combined change in baseline-1-year jointly assessed ACE-R/mRS scores was associated with fluctuating WMH volumes (F = 9.3, p = 0.03). Discussion After stroke, fluctuating WMH mean that 1-year, but not baseline, WMH volumes are associated strongly with contemporaneous cognitive scores. Covarying longitudinal decline in cognition and independence after stroke, central to dementia diagnosis, is associated with increasing WMH volumes.
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Affiliation(s)
- Una Clancy
- Centre for Clinical Brain Sciences, Edinburgh Imaging and the UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Stephen Dj Makin
- Centre for Clinical Brain Sciences, Edinburgh Imaging and the UK Dementia Research Institute, University of Edinburgh, United Kingdom.,Centre For Rural Health, Institute of Applied Health Sciences, University of Aberdeen, United Kingdom
| | - Caroline A McHutchison
- Centre for Clinical Brain Sciences, Edinburgh Imaging and the UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Vera Cvoro
- Centre for Clinical Brain Sciences, Edinburgh Imaging and the UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Francesca M Chappell
- Centre for Clinical Brain Sciences, Edinburgh Imaging and the UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Maria Del C Valdés Hernández
- Centre for Clinical Brain Sciences, Edinburgh Imaging and the UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Eleni Sakka
- Centre for Clinical Brain Sciences, Edinburgh Imaging and the UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Fergus Doubal
- Centre for Clinical Brain Sciences, Edinburgh Imaging and the UK Dementia Research Institute, University of Edinburgh, United Kingdom
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, Edinburgh Imaging and the UK Dementia Research Institute, University of Edinburgh, United Kingdom
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16
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Abstract
As life expectancy grows, brain health is increasingly seen as central to what we mean by successful aging-and vascular brain health as central to overall brain health. Cerebrovascular pathologies are highly prevalent independent contributors to age-related cognitive impairment and at least partly modifiable with available treatments. The current Focused Update addresses vascular brain health from multiple angles, ranging from pathophysiologic mechanisms and neuroimaging features to epidemiologic risk factors, social determinants, and candidate treatments. Here we highlight some of the shared themes that cut across these distinct perspectives: 1) the lifetime course of vascular brain injury pathogenesis and progression; 2) the scientific and ethical imperative to extend vascular brain health research in non-White and non-affluent populations; 3) the need for improved tools to study the cerebral small vessels themselves; 4) the potential role for brain recovery mechanisms in determining vascular brain health and resilience; and 5) the cross-pathway mechanisms by which vascular and neurodegenerative processes may interact. The diverse perspectives featured in this Focused Update offer a sense of the multidisciplinary approaches and collaborations that will be required to launch our populations towards improved brain health and successful aging.
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Affiliation(s)
- Steven M Greenberg
- J. Philip Kistler Stroke Research Center, Massachusetts General Hospital, Harvard Medical School, Boston
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17
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Backhouse EV, Shenkin SD, McIntosh AM, Bastin ME, Whalley HC, Valdez Hernandez M, Muñoz Maniega S, Harris MA, Stolicyn A, Campbell A, Steele D, Waiter GD, Sandu AL, Waymont JMJ, Murray AD, Cox SR, de Rooij SR, Roseboom TJ, Wardlaw JM. Early life predictors of late life cerebral small vessel disease in four prospective cohort studies. Brain 2021; 144:3769-3778. [PMID: 34581779 PMCID: PMC8719837 DOI: 10.1093/brain/awab331] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2021] [Revised: 06/12/2021] [Accepted: 07/07/2021] [Indexed: 11/12/2022] Open
Abstract
Development of cerebral small vessel disease, a major cause of stroke and dementia, may be influenced by early life factors. It is unclear whether these relationships are independent of each other, of adult socio-economic status or of vascular risk factor exposures. We examined associations between factors from birth (ponderal index, birth weight), childhood (IQ, education, socio-economic status), adult small vessel disease, and brain volumes, using data from four prospective cohort studies: STratifying Resilience And Depression Longitudinally (STRADL) (n = 1080; mean age = 59 years); the Dutch Famine Birth Cohort (n = 118; mean age = 68 years); the Lothian Birth Cohort 1936 (LBC1936; n = 617; mean age = 73 years), and the Simpson's cohort (n = 110; mean age = 78 years). We analysed each small vessel disease feature individually and summed to give a total small vessel disease score (range 1-4) in each cohort separately, then in meta-analysis, adjusted for vascular risk factors and adult socio-economic status. Higher birth weight was associated with fewer lacunes [odds ratio (OR) per 100 g = 0.93, 95% confidence interval (CI) = 0.88 to 0.99], fewer infarcts (OR = 0.94, 95% CI = 0.89 to 0.99), and fewer perivascular spaces (OR = 0.95, 95% CI = 0.91 to 0.99). Higher childhood IQ was associated with lower white matter hyperintensity burden (OR per IQ point = 0.99, 95% CI 0.98 to 0.998), fewer infarcts (OR = 0.98, 95% CI = 0.97 to 0.998), fewer lacunes (OR = 0.98, 95% CI = 0.97 to 0.999), and lower total small vessel disease burden (OR = 0.98, 95% CI = 0.96 to 0.999). Low education was associated with more microbleeds (OR = 1.90, 95% CI = 1.33 to 2.72) and lower total brain volume (mean difference = -178.86 cm3, 95% CI = -325.07 to -32.66). Low childhood socio-economic status was associated with fewer lacunes (OR = 0.62, 95% CI = 0.40 to 0.95). Early life factors are associated with worse small vessel disease in later life, independent of each other, vascular risk factors and adult socio-economic status. Risk for small vessel disease may originate in early life and provide a mechanistic link between early life factors and risk of stroke and dementia. Policies investing in early child development may improve lifelong brain health and contribute to the prevention of dementia and stroke in older age.
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Affiliation(s)
- Ellen V Backhouse
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK
- MRC UK Dementia Research Institute at the University of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Susan D Shenkin
- Geriatric Medicine, Usher Institute, The University of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Andrew M McIntosh
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Institute of Neuroscience and Psychology, Glasgow G12 8QB, UK
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Heather C Whalley
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Maria Valdez Hernandez
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Institute of Neuroscience and Psychology, Glasgow G12 8QB, UK
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Susana Muñoz Maniega
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Institute of Neuroscience and Psychology, Glasgow G12 8QB, UK
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4TJ, UK
| | - Mathew A Harris
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Aleks Stolicyn
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Archie Campbell
- Division of Psychiatry, Royal Edinburgh Hospital, University of Edinburgh, Edinburgh, EH10 5HF, UK
| | - Douglas Steele
- Division of Imaging Sciences and Technology, Medical School, University of Dundee, Dundee, DD1 9SY, UK
| | - Gordon D Waiter
- Aberdeen Biomedical Imaging Centre, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Foresterhill, Aberdeen, AB25 2ZD, UK
| | - Anca-Larisa Sandu
- Aberdeen Biomedical Imaging Centre, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Foresterhill, Aberdeen, AB25 2ZD, UK
| | - Jennifer M J Waymont
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Institute of Neuroscience and Psychology, Glasgow G12 8QB, UK
- Aberdeen Biomedical Imaging Centre, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Foresterhill, Aberdeen, AB25 2ZD, UK
| | - Alison D Murray
- Aberdeen Biomedical Imaging Centre, School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Foresterhill, Aberdeen, AB25 2ZD, UK
| | - Simon R Cox
- Lothian Birth Cohorts Group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Susanne R de Rooij
- Department of Epidemiology and Data Science, Amsterdam University, Medical Centres, University of Amsterdam, The Netherlands
| | - Tessa J Roseboom
- Department of Epidemiology and Data Science, Amsterdam University, Medical Centres, University of Amsterdam, The Netherlands
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK
- MRC UK Dementia Research Institute at the University of Edinburgh, Edinburgh, EH16 4SB, UK
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Institute of Neuroscience and Psychology, Glasgow G12 8QB, UK
- Brain Research Imaging Centre, Division of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4TJ, UK
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18
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Jiménez-Sánchez L, Hamilton OKL, Clancy U, Backhouse EV, Stewart CR, Stringer MS, Doubal FN, Wardlaw JM. Sex Differences in Cerebral Small Vessel Disease: A Systematic Review and Meta-Analysis. Front Neurol 2021; 12:756887. [PMID: 34777227 PMCID: PMC8581736 DOI: 10.3389/fneur.2021.756887] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Accepted: 10/04/2021] [Indexed: 01/12/2023] Open
Abstract
Background: Cerebral small vessel disease (SVD) is a common cause of stroke, mild cognitive impairment, dementia and physical impairments. Differences in SVD incidence or severity between males and females are unknown. We assessed sex differences in SVD by assessing the male-to-female ratio (M:F) of recruited participants and incidence of SVD, risk factor presence, distribution, and severity of SVD features. Methods: We assessed four recent systematic reviews on SVD and performed a supplementary search of MEDLINE to identify studies reporting M:F ratio in covert, stroke, or cognitive SVD presentations (registered protocol: CRD42020193995). We meta-analyzed differences in sex ratios across time, countries, SVD severity and presentations, age and risk factors for SVD. Results: Amongst 123 relevant studies (n = 36,910 participants) including 53 community-based, 67 hospital-based and three mixed studies published between 1989 and 2020, more males were recruited in hospital-based than in community-based studies [M:F = 1.16 (0.70) vs. M:F = 0.79 (0.35), respectively; p < 0.001]. More males had moderate to severe SVD [M:F = 1.08 (0.81) vs. M:F = 0.82 (0.47) in healthy to mild SVD; p < 0.001], and stroke presentations where M:F was 1.67 (0.53). M:F did not differ for recent (2015-2020) vs. pre-2015 publications, by geographical region, or age. There were insufficient sex-stratified data to explore M:F and risk factors for SVD. Conclusions: Our results highlight differences in male-to-female ratios in SVD severity and amongst those presenting with stroke that have important clinical and translational implications. Future SVD research should report participant demographics, risk factors and outcomes separately for males and females. Systematic Review Registration: [PROSPERO], identifier [CRD42020193995].
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Affiliation(s)
- Lorena Jiménez-Sánchez
- Translational Neuroscience PhD Programme, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Olivia K. L. Hamilton
- Translational Neuroscience PhD Programme, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Edinburgh Dementia Research Centre in the UK Dementia Research Institute, Edinburgh, United Kingdom
| | - Una Clancy
- Edinburgh Dementia Research Centre in the UK Dementia Research Institute, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Ellen V. Backhouse
- Edinburgh Dementia Research Centre in the UK Dementia Research Institute, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Catriona R. Stewart
- Edinburgh Dementia Research Centre in the UK Dementia Research Institute, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Michael S. Stringer
- Edinburgh Dementia Research Centre in the UK Dementia Research Institute, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Fergus N. Doubal
- Edinburgh Dementia Research Centre in the UK Dementia Research Institute, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Joanna M. Wardlaw
- Edinburgh Dementia Research Centre in the UK Dementia Research Institute, Edinburgh, United Kingdom
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Lothian Birth Cohorts, University of Edinburgh, Edinburgh, United Kingdom
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19
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Ibitoye RT, Castro P, Desowska A, Cooke J, Edwards AE, Guven O, Arshad Q, Murdin L, Kaski D, Bronstein AM. Small vessel disease disrupts EEG postural brain networks in 'unexplained dizziness in the elderly'. Clin Neurophysiol 2021; 132:2751-2762. [PMID: 34583117 PMCID: PMC8559782 DOI: 10.1016/j.clinph.2021.07.027] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2021] [Revised: 06/15/2021] [Accepted: 07/25/2021] [Indexed: 11/28/2022]
Abstract
Unexplained dizziness in the elderly may result from
cerebral small vessel disease. Dizzy elderly patients differed from controls in EEG
power when standing. EEG power when standing correlated with subjective
(perceived) instability.
Objective To examine the hypothesis that small vessel disease
disrupts postural networks in older adults with unexplained dizziness in the
elderly (UDE). Methods Simultaneous electroencephalography and postural sway
measurements were undertaken in upright, eyes closed standing, and sitting
postures (as baseline) in 19 younger adults, 33 older controls and 36 older
patients with UDE. Older adults underwent magnetic resonance imaging to
determine whole brain white matter hyperintensity volumes, a measure of small
vessel disease. Linear regression was used to estimate the effect of instability
on electroencephalographic power and connectivity. Results Ageing increased theta and alpha desynchronisation on
standing. In older controls, delta and gamma power increased, and theta and
alpha power reduced with instability. Dizzy older patients had higher white
matter hyperintensity volumes and more theta desynchronisation during periods of
instability. White matter hyperintensity volume and delta power during periods
of instability were correlated, positively in controls but negatively in dizzy
older patients. Delta power correlated with subjective dizziness and
instability. Conclusions Neural resource demands of postural control increase
with age, particularly in patients with UDE, driven by small vessel
disease. Significance EEG correlates of postural control saturate in older
adults with UDE, offering a neuro-physiological basis to this common
syndrome.
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Affiliation(s)
- R T Ibitoye
- Neuro-otology Unit, Imperial College London, London, UK; The Computational, Cognitive and Clinical Neuroimaging Laboratory (C3NL), Imperial College London, London, UK
| | - P Castro
- Neuro-otology Unit, Imperial College London, London, UK
| | - A Desowska
- The Computational, Cognitive and Clinical Neuroimaging Laboratory (C3NL), Imperial College London, London, UK
| | - J Cooke
- Neuro-otology Unit, Imperial College London, London, UK
| | - A E Edwards
- Neuro-otology Unit, Imperial College London, London, UK
| | - O Guven
- Neuro-otology Unit, Imperial College London, London, UK
| | - Q Arshad
- Neuro-otology Unit, Imperial College London, London, UK; inAmind Laboratory, Department of Neuroscience, Psychology and Behaviour, University of Leicester, Leicester, UK
| | - L Murdin
- Guy's and St Thomas' NHS Foundation Trust, London, UK
| | - D Kaski
- Neuro-otology Unit, Imperial College London, London, UK; Department of Clinical and Movement Neurosciences, University College London, London, UK
| | - A M Bronstein
- Neuro-otology Unit, Imperial College London, London, UK.
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20
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Hillary RF, Stevenson AJ, Cox SR, McCartney DL, Harris SE, Seeboth A, Higham J, Sproul D, Taylor AM, Redmond P, Corley J, Pattie A, Hernández MDCV, Muñoz-Maniega S, Bastin ME, Wardlaw JM, Horvath S, Ritchie CW, Spires-Jones TL, McIntosh AM, Evans KL, Deary IJ, Marioni RE. An epigenetic predictor of death captures multi-modal measures of brain health. Mol Psychiatry 2021; 26:3806-3816. [PMID: 31796892 PMCID: PMC8550950 DOI: 10.1038/s41380-019-0616-9] [Citation(s) in RCA: 66] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/30/2019] [Revised: 11/14/2019] [Accepted: 11/20/2019] [Indexed: 11/08/2022]
Abstract
Individuals of the same chronological age exhibit disparate rates of biological ageing. Consequently, a number of methodologies have been proposed to determine biological age and primarily exploit variation at the level of DNA methylation (DNAm). A novel epigenetic clock, termed 'DNAm GrimAge' has outperformed its predecessors in predicting the risk of mortality as well as many age-related morbidities. However, the association between DNAm GrimAge and cognitive or neuroimaging phenotypes remains unknown. We explore these associations in the Lothian Birth Cohort 1936 (n = 709, mean age 73 years). Higher DNAm GrimAge was strongly associated with all-cause mortality over the eighth decade (Hazard Ratio per standard deviation increase in GrimAge: 1.81, P < 2.0 × 10-16). Higher DNAm GrimAge was associated with lower age 11 IQ (β = -0.11), lower age 73 general cognitive ability (β = -0.18), decreased brain volume (β = -0.25) and increased brain white matter hyperintensities (β = 0.17). There was tentative evidence for a longitudinal association between DNAm GrimAge and cognitive decline from age 70 to 79. Sixty-nine of 137 health- and brain-related phenotypes tested were significantly associated with GrimAge. Adjusting all models for childhood intelligence attenuated to non-significance a small number of associations (12/69 associations; 6 of which were cognitive traits), but not the association with general cognitive ability (33.9% attenuation). Higher DNAm GrimAge associates with lower cognitive ability and brain vascular lesions in older age, independently of early-life cognitive ability. This epigenetic predictor of mortality associates with different measures of brain health and may aid in the prediction of age-related cognitive decline.
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Affiliation(s)
- Robert F Hillary
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Anna J Stevenson
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Simon R Cox
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Daniel L McCartney
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Anne Seeboth
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Jon Higham
- Medical Research Council Human Genetics Unit, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Duncan Sproul
- Medical Research Council Human Genetics Unit, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Edinburgh Cancer Research Centre, Medical Research Council Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
| | - Adele M Taylor
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Paul Redmond
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Janie Corley
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Alison Pattie
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Maria Del C Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Susana Muñoz-Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- UK Dementia Research Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
| | - Steve Horvath
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California, USA
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, California, USA
| | - Craig W Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Tara L Spires-Jones
- UK Dementia Research Institute, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Andrew M McIntosh
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Division of Psychiatry, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Kathryn L Evans
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK
- Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, UK.
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, UK.
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21
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Wardlaw JM. A Stroke Is a Stroke, With or Without a Visible Infarct. Neurology 2021; 97:515-516. [PMID: 34290129 DOI: 10.1212/wnl.0000000000012540] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Affiliation(s)
- Joanna M Wardlaw
- Centre for Clinical Brain Sciences, UK Dementia Research Institute, University of Edinburgh
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22
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Tsuchida A, Laurent A, Crivello F, Petit L, Joliot M, Pepe A, Beguedou N, Gueye MF, Verrecchia V, Nozais V, Zago L, Mellet E, Debette S, Tzourio C, Mazoyer B. The MRi-Share database: brain imaging in a cross-sectional cohort of 1870 university students. Brain Struct Funct 2021; 226:2057-2085. [PMID: 34283296 DOI: 10.1007/s00429-021-02334-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 06/11/2021] [Indexed: 01/04/2023]
Abstract
We report on MRi-Share, a multi-modal brain MRI database acquired in a unique sample of 1870 young healthy adults, aged 18-35 years, while undergoing university-level education. MRi-Share contains structural (T1 and FLAIR), diffusion (multispectral), susceptibility-weighted (SWI), and resting-state functional imaging modalities. Here, we described the contents of these different neuroimaging datasets and the processing pipelines used to derive brain phenotypes, as well as how quality control was assessed. In addition, we present preliminary results on associations of some of these brain image-derived phenotypes at the whole brain level with both age and sex, in the subsample of 1722 individuals aged less than 26 years. We demonstrate that the post-adolescence period is characterized by changes in both structural and microstructural brain phenotypes. Grey matter cortical thickness, surface area and volume were found to decrease with age, while white matter volume shows increase. Diffusivity, either radial or axial, was found to robustly decrease with age whereas fractional anisotropy only slightly increased. As for the neurite orientation dispersion and densities, both were found to increase with age. The isotropic volume fraction also showed a slight increase with age. These preliminary findings emphasize the complexity of changes in brain structure and function occurring in this critical period at the interface of late maturation and early ageing.
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Affiliation(s)
- Ami Tsuchida
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CEA, Bordeaux, France
| | - Alexandre Laurent
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CEA, Bordeaux, France
| | - Fabrice Crivello
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CEA, Bordeaux, France
| | - Laurent Petit
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CEA, Bordeaux, France
| | - Marc Joliot
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CEA, Bordeaux, France.,Ginesislab, Fealinx and Université de Bordeaux, Bordeaux, France
| | - Antonietta Pepe
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CEA, Bordeaux, France
| | - Naka Beguedou
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CEA, Bordeaux, France
| | - Marie-Fateye Gueye
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CEA, Bordeaux, France.,Ginesislab, Fealinx and Université de Bordeaux, Bordeaux, France
| | - Violaine Verrecchia
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CEA, Bordeaux, France.,Ginesislab, Fealinx and Université de Bordeaux, Bordeaux, France
| | - Victor Nozais
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CEA, Bordeaux, France.,Ginesislab, Fealinx and Université de Bordeaux, Bordeaux, France
| | - Laure Zago
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CEA, Bordeaux, France
| | - Emmanuel Mellet
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, Université de Bordeaux, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CNRS, Bordeaux, France.,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CEA, Bordeaux, France
| | - Stéphanie Debette
- Université de Bordeaux, INSERM, Bordeaux Population Health Research Center, U1219, CHU Bordeaux, Bordeaux, France.,Centre Hospitalier Universitaire Pellegrin, Bordeaux, France
| | - Christophe Tzourio
- Université de Bordeaux, INSERM, Bordeaux Population Health Research Center, U1219, CHU Bordeaux, Bordeaux, France.,Centre Hospitalier Universitaire Pellegrin, Bordeaux, France
| | - Bernard Mazoyer
- Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, Université de Bordeaux, Bordeaux, France. .,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CNRS, Bordeaux, France. .,Groupe d'Imagerie Neurofonctionnelle, Institut des Maladies Neurodégénératives, UMR5293, CEA, Bordeaux, France. .,Ginesislab, Fealinx and Université de Bordeaux, Bordeaux, France. .,Centre Hospitalier Universitaire Pellegrin, Bordeaux, France.
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23
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Cerebral small vessel disease burden and longitudinal cognitive decline from age 73 to 82: the Lothian Birth Cohort 1936. Transl Psychiatry 2021; 11:376. [PMID: 34226517 PMCID: PMC8257729 DOI: 10.1038/s41398-021-01495-4] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Revised: 06/14/2021] [Accepted: 06/22/2021] [Indexed: 12/15/2022] Open
Abstract
Slowed processing speed is considered a hallmark feature of cognitive decline in cerebral small vessel disease (SVD); however, it is unclear whether SVD's association with slowed processing might be due to its association with overall declining general cognitive ability. We quantified the total MRI-visible SVD burden of 540 members of the Lothian Birth Cohort 1936 (age: 72.6 ± 0.7 years; 47% female). Using latent growth curve modelling, we tested associations between total SVD burden at mean age 73 and changes in general cognitive ability, processing speed, verbal memory and visuospatial ability, measured at age 73, 76, 79 and 82. Covariates included age, sex, vascular risk and childhood cognitive ability. In the fully adjusted models, greater SVD burden was associated with greater declines in general cognitive ability (standardised β: -0.201; 95% CI: [-0.36, -0.04]; pFDR = 0.022) and processing speed (-0.222; [-0.40, -0.04]; pFDR = 0.022). SVD burden accounted for between 4 and 5% of variance in declines of general cognitive ability and processing speed. After accounting for the covariance between tests of processing speed and general cognitive ability, only SVD's association with greater decline in general cognitive ability remained significant, prior to FDR correction (-0.222; [-0.39, -0.06]; p = 0.008; pFDR = 0.085). Our findings do not support the notion that SVD has a specific association with declining processing speed, independent of decline in general cognitive ability (which captures the variance shared across domains of cognitive ability). The association between SVD burden and declining general cognitive ability supports the notion of SVD as a diffuse, whole-brain disease and suggests that trials monitoring SVD-related cognitive changes should consider domain-specific changes in the context of overall, general cognitive decline.
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24
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Grosu S, Lorbeer R, Hartmann F, Rospleszcz S, Bamberg F, Schlett CL, Galie F, Selder S, Auweter S, Heier M, Rathmann W, Mueller-Peltzer K, Ladwig KH, Peters A, Ertl-Wagner BB, Stoecklein S. White matter hyperintensity volume in pre-diabetes, diabetes and normoglycemia. BMJ Open Diabetes Res Care 2021; 9:9/1/e002050. [PMID: 34183320 PMCID: PMC8240582 DOI: 10.1136/bmjdrc-2020-002050] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2020] [Accepted: 06/01/2021] [Indexed: 02/07/2023] Open
Abstract
INTRODUCTION As white matter hyperintensities (WMHs) of the brain are associated with an increased risk of stroke, cognitive decline, and depression, elucidating the associated risk factors is important. In addition to age and hypertension, pre-diabetes and diabetes may play important roles in the development of WMHs. Previous studies have, however, shown conflicting results. We aimed to investigate the effect of diabetes status and quantitative markers of glucose metabolism on WMH volume in a population-based cohort without prior cardiovascular disease. RESEARCH DESIGN AND METHODS 400 participants underwent 3 T MRI. WMHs were manually segmented on 3D fluid-attenuated inversion recovery images. An oral glucose tolerance test (OGTT) was administered to all participants not previously diagnosed with diabetes to assess 2-hour serum glucose concentrations. Fasting glucose concentrations and glycated hemoglobin (HbA1c) levels were measured. Zero-inflated negative binomial regression analyses of WMH volume and measures of glycemic status were performed while controlling for cardiovascular risk factors and multiple testing. RESULTS The final study population comprised 388 participants (57% male; age 56.3±9.2 years; n=98 with pre-diabetes, n=51 with diabetes). Higher WMH volume was associated with pre-diabetes (p=0.001) and diabetes (p=0.026) compared with normoglycemic control participants after adjustment for cardiovascular risk factors. 2-hour serum glucose (p<0.001), but not fasting glucose (p=0.389) or HbA1c (p=0.050), showed a significant positive association with WMH volume after adjustment for cardiovascular risk factors. CONCLUSION Our results indicate that high 2-hour serum glucose concentration in OGTT, but not fasting glucose levels, may be an independent risk factor for the development of WMHs, with the potential to inform intensified prevention strategies in individuals at risk of WMH-associated morbidity.
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Affiliation(s)
- Sergio Grosu
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Roberto Lorbeer
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Felix Hartmann
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Susanne Rospleszcz
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
- Department of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Fabian Bamberg
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Christopher L Schlett
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Franziska Galie
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Sonja Selder
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Sigrid Auweter
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
| | - Margit Heier
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
- KORA Study Centre, University Hospital of Augsburg, Augsburg, Germany
| | - Wolfgang Rathmann
- Institute for Biometrics and Epidemiology, German Diabetes Center, Duesseldorf, Germany
- German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany
| | - Katharina Mueller-Peltzer
- Department of Diagnostic and Interventional Radiology, Medical Center-University of Freiburg, Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Karl-Heinz Ladwig
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
- Department of Psychosomatic Medicine and Psychotherapy, Hospital Rechts der Isar, Technical University Munich, Munich, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Munich-Neuherberg, Germany
- Department of Epidemiology, Institute for Medical Information Processing, Biometry and Epidemiology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Birgit B Ertl-Wagner
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
- Department of Radiology, The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada
| | - Sophia Stoecklein
- Department of Radiology, University Hospital, LMU Munich, Munich, Germany
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25
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Valdés Hernández MDC, Ballerini L, Glatz A, Muñoz Maniega S, Gow AJ, Bastin ME, Starr JM, Deary IJ, Wardlaw JM. Perivascular spaces in the centrum semiovale at the beginning of the 8th decade of life: effect on cognition and associations with mineral deposition. Brain Imaging Behav 2021; 14:1865-1875. [PMID: 31250262 PMCID: PMC7572330 DOI: 10.1007/s11682-019-00128-1] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022]
Abstract
Brain iron deposits (IDs) are indicative of microvessel dysfunction which may predispose to small vessel disease (SVD) brain damage and worsen cognition later in life. Visible perivascular spaces in the centrum semiovale (CSO-PVS) are SVD features linked with microvessel dysfunction. We examined possible associations of CSO-PVS volume and count with brain IDs and cognitive abilities in 700 community-dwelling individuals from the Lothian Birth Cohort 1936 who underwent detailed cognitive testing and multimodal brain MRI at mean age 72.7 years. Brain IDs were assessed automatically followed by manual editing. PVS were automatically assessed in the centrum semiovale and deep corona radiata supraventricular. General factors of overall cognitive function (g), processing speed (g-speed) and memory (g-memory) were used in the analyses. Median (IQR) volumes of IDs and CSO-PVS expressed as a percentage of intracranial volume were 0.0021 (0.011) and 0.22 (0.13)% respectively. Median count of CSO-PVS was 410 (IQR = 201). Total volumes of CSO-PVS and ID, adjusted for head size, were correlated (Spearman ρ = 0.13, p < 0.001). CSO-PVS volume, despite being correlated with all three cognitive measures, was only associated with g-memory (B = -114.5, SE = 48.35, p = 0.018) in general linear models, adjusting for age, sex, vascular risk factors, childhood intelligence and white matter hyperintensity volume. The interaction of CSO-PVS count with diabetes (B = -0.0019, SE = 0.00093, p = 0.041) and volume with age (B = 1.57, SE = 0.67, p = 0.019) were also associated with g-memory. Linear regression models did not replicate these associations. Therefore, it does not seem that CSO-PVS burden is directly associated with general cognitive ability in older age.
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Affiliation(s)
- Maria Del C Valdés Hernández
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, 49 Little France Crescent, Chancellor's Building, Edinburgh, EH16 4SB, UK. .,Dementia Research Institute, University of Edinburgh, 49 Little France Crescent, Chancellor's Building FU-427, Edinburgh, EH16 4SB, UK. .,Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK. .,Department of Psychology, School of Social Sciences, Heriot-Watt University, Edinburgh Campus, David Brewster Building (Room 2.63A), Edinburgh, EH14 4AS, UK.
| | - Lucia Ballerini
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, 49 Little France Crescent, Chancellor's Building, Edinburgh, EH16 4SB, UK.,Dementia Research Institute, University of Edinburgh, 49 Little France Crescent, Chancellor's Building FU-427, Edinburgh, EH16 4SB, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Andreas Glatz
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, 49 Little France Crescent, Chancellor's Building, Edinburgh, EH16 4SB, UK
| | - Susana Muñoz Maniega
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, 49 Little France Crescent, Chancellor's Building, Edinburgh, EH16 4SB, UK.,Dementia Research Institute, University of Edinburgh, 49 Little France Crescent, Chancellor's Building FU-427, Edinburgh, EH16 4SB, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Alan J Gow
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.,Department of Psychology, School of Social Sciences, Heriot-Watt University, Edinburgh Campus, David Brewster Building (Room 2.63A), Edinburgh, EH14 4AS, UK
| | - Mark E Bastin
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, 49 Little France Crescent, Chancellor's Building, Edinburgh, EH16 4SB, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - John M Starr
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.,Alzheimer Scotland Dementia Research Centre, Department of Psychology (Room G24), University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.,Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK
| | - Joanna M Wardlaw
- Department of Neuroimaging Sciences, Centre for Clinical Brain Sciences, University of Edinburgh, 49 Little France Crescent, Chancellor's Building, Edinburgh, EH16 4SB, UK.,Dementia Research Institute, University of Edinburgh, 49 Little France Crescent, Chancellor's Building FU-427, Edinburgh, EH16 4SB, UK.,Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, EH8 9JZ, UK.,Row Fogo Centre for Ageing and the Brain, University of Edinburgh, 49 Little France Crescent, Chancellor's Building, Edinburgh, EH16 4SB, UK
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26
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Deary IJ, Hill WD, Gale CR. Intelligence, health and death. Nat Hum Behav 2021; 5:416-430. [PMID: 33795857 DOI: 10.1038/s41562-021-01078-9] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/16/2019] [Accepted: 02/15/2021] [Indexed: 02/06/2023]
Abstract
The field of cognitive epidemiology studies the prospective associations between cognitive abilities and health outcomes. We review research in this field over the past decade and describe how our understanding of the association between intelligence and all-cause mortality has consolidated with the appearance of new, population-scale data. To try to understand the association better, we discuss how intelligence relates to specific causes of death, diseases/diagnoses and biomarkers of health through the adult life course. We examine the extent to which mortality and health associations with intelligence might be attributable to people's differences in education, other indicators of socioeconomic status, health literacy and adult environments and behaviours. Finally, we discuss whether genetic data provide new tools to understand parts of the intelligence-health associations. Social epidemiologists, differential psychologists and behavioural and statistical geneticists, among others, contribute to cognitive epidemiology; advances will occur by building on a common cross-disciplinary knowledge base.
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Affiliation(s)
- Ian J Deary
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK.
| | - W David Hill
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Catharine R Gale
- Lothian Birth Cohorts, Department of Psychology, University of Edinburgh, Edinburgh, UK.,MRC Lifecourse Epidemiology Unit, University of Southampton, Southampton General Hospital, Southampton, UK
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27
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Hamilton OKL, Backhouse EV, Janssen E, Jochems ACC, Maher C, Ritakari TE, Stevenson AJ, Xia L, Deary IJ, Wardlaw JM. Cognitive impairment in sporadic cerebral small vessel disease: A systematic review and meta-analysis. Alzheimers Dement 2021; 17:665-685. [PMID: 33185327 PMCID: PMC8593445 DOI: 10.1002/alz.12221] [Citation(s) in RCA: 89] [Impact Index Per Article: 29.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2020] [Revised: 02/08/2020] [Accepted: 05/10/2020] [Indexed: 01/09/2023]
Abstract
This paper is a proposal for an update on the characterization of cognitive impairments associated with sporadic cerebral small vessel disease (SVD). We pose a series of questions about the nature of SVD-related cognitive impairments and provide answers based on a comprehensive review and meta-analysis of published data from 69 studies. Although SVD is thought primarily to affect executive function and processing speed, we hypothesize that SVD affects all major domains of cognitive ability. We also identify low levels of education as a potentially modifiable risk factor for SVD-related cognitive impairment. Therefore, we propose the use of comprehensive cognitive assessments and the measurement of educational level both in clinics and research settings, and suggest several recommendations for future research.
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Affiliation(s)
- Olivia KL Hamilton
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - Ellen V Backhouse
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - Esther Janssen
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - Angela CC Jochems
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - Caragh Maher
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - Tuula E Ritakari
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
| | - Anna J Stevenson
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Centre for Genomic and Experimental Medicine, MRC Institute of Genetics and Molecular Medicine, University of Edinburgh, Western General Hospital Campus, Crewe Road, Edinburgh, UK, EH4 2XU
- Centre for Discovery Brain Sciences, University of Edinburgh, Hugh Robson Building, 15 George Square, Edinburgh, UK, EH8 9XD
| | - Lihua Xia
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - Ian J Deary
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
- Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Dementia Research Institute, University of Edinburgh, Chancellor’s Building, 49 Little France Crescent, Edinburgh, UK, EH16 4SB
- Lothian Birth Cohorts, University of Edinburgh, 7 George Square, Edinburgh, UK, EH8 9JZ
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28
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LncRNA-MIAT promotes neural cell autophagy and apoptosis in ischemic stroke by up-regulating REDD1. Brain Res 2021; 1763:147436. [PMID: 33745924 DOI: 10.1016/j.brainres.2021.147436] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2020] [Revised: 02/28/2021] [Accepted: 03/14/2021] [Indexed: 12/16/2022]
Abstract
BACKGROUND Ischemic stroke (IS) accounts for 80% of stroke incidence, which has an impact on the life quality of patients. Long non-coding RNA (LncRNA), a class of non-coding transcripts greater than 200 nucleotidesin length, has been extensively studied in cerebrovascular diseases. Myocardial infarction associated transcript (MIAT) is highly expressed in nervous system. Therefore this study aims to explore the role of LncRNA MIAT in IS and to clarify its underlying mechanism, providing therapeutic value for the treatment of IS. METHODS The neurological function of rats was evaluated by neurological deficit score. Triphenyltetrazolium chloride (TTC) staining was used to detect infarct area in brain tissues. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to examine the expression of MIAT. Western blotting was used to detect the expressions of REDD1, p-mTOR, autophagy-related proteins LC3 and p62, and apoptotic-related proteins Bax, cleaved-caspase3, Bcl-2. Flow cytometry was applied to examine neuronal cell apoptosis. RNA pull-down and RIP assay was used to verify the binding of MIAT and REDD1. The level of REDD1 ubiquitination was detected by ubiquitination and Co-immunoprecipitation (Co-IP) assay. RESULTS The expressions of MIAT and REDD1 were increased in IS rats and oxygen-glucose deprivation/reoxygenation (OGD/R)-induced PC12 cell injury. After interference with si-MIAT, the results of flow cytometry showed that the rate of apoptosis was reduced. Western blotting results showed that the expression of LC3II/LC3I, Bax, and cleaved-caspase3 was decreased, while the expression of p-mTOR, p62, and Bcl-2 was increased. RNA pull-down and RIP assay found the binding relationship between MIAT and REDD1, and interference with si-MIAT down-regulated the expression of REDD1. The level of REDD1 ubiquitination was increased and the expression of REDD1 was decreased after interference with si-MIAT in PC12 cells. Co-IP results showed that interference with si-MIAT enhanced the binding ability of CUL4A-DDB1 and REDD1. CONCLUSION Altogether, MIAT promotes autophagy and apoptosis of neural cells and aggravates IS by up-regulating the expression of REDD1.
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29
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Associated factors of white matter hyperintensity volume: a machine-learning approach. Sci Rep 2021; 11:2325. [PMID: 33504924 PMCID: PMC7840689 DOI: 10.1038/s41598-021-81883-4] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2020] [Accepted: 01/11/2021] [Indexed: 01/08/2023] Open
Abstract
To identify the most important parameters associated with cerebral white matter hyperintensities (WMH), in consideration of potential collinearity, we used a data-driven machine-learning approach. We analysed two independent cohorts (KORA and SHIP). WMH volumes were derived from cMRI-images (FLAIR). 90 (KORA) and 34 (SHIP) potential determinants of WMH including measures of diabetes, blood-pressure, medication-intake, sociodemographics, life-style factors, somatic/depressive-symptoms and sleep were collected. Elastic net regression was used to identify relevant predictor covariates associated with WMH volume. The ten most frequently selected variables in KORA were subsequently examined for robustness in SHIP. The final KORA sample consisted of 370 participants (58% male; age 55.7 ± 9.1 years), the SHIP sample comprised 854 participants (38% male; age 53.9 ± 9.3 years). The most often selected and highly replicable parameters associated with WMH volume were in descending order age, hypertension, components of the social environment (i.e. widowed, living alone) and prediabetes. A systematic machine-learning based analysis of two independent, population-based cohorts showed, that besides age and hypertension, prediabetes and components of the social environment might play important roles in the development of WMH. Our results enable personal risk assessment for the development of WMH and inform prevention strategies tailored to the individual patient.
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30
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Sargurupremraj M, Suzuki H, Jian X, Sarnowski C, Evans TE, Bis JC, Eiriksdottir G, Sakaue S, Terzikhan N, Habes M, Zhao W, Armstrong NJ, Hofer E, Yanek LR, Hagenaars SP, Kumar RB, van den Akker EB, McWhirter RE, Trompet S, Mishra A, Saba Y, Satizabal CL, Beaudet G, Petit L, Tsuchida A, Zago L, Schilling S, Sigurdsson S, Gottesman RF, Lewis CE, Aggarwal NT, Lopez OL, Smith JA, Valdés Hernández MC, van der Grond J, Wright MJ, Knol MJ, Dörr M, Thomson RJ, Bordes C, Le Grand Q, Duperron MG, Smith AV, Knopman DS, Schreiner PJ, Evans DA, Rotter JI, Beiser AS, Maniega SM, Beekman M, Trollor J, Stott DJ, Vernooij MW, Wittfeld K, Niessen WJ, Soumaré A, Boerwinkle E, Sidney S, Turner ST, Davies G, Thalamuthu A, Völker U, van Buchem MA, Bryan RN, Dupuis J, Bastin ME, Ames D, Teumer A, Amouyel P, Kwok JB, Bülow R, Deary IJ, Schofield PR, Brodaty H, Jiang J, Tabara Y, Setoh K, Miyamoto S, Yoshida K, Nagata M, Kamatani Y, Matsuda F, Psaty BM, Bennett DA, De Jager PL, Mosley TH, Sachdev PS, Schmidt R, Warren HR, Evangelou E, Trégouët DA, Ikram MA, Wen W, DeCarli C, Srikanth VK, Jukema JW, Slagboom EP, Kardia SLR, Okada Y, Mazoyer B, Wardlaw JM, Nyquist PA, Mather KA, Grabe HJ, Schmidt H, Van Duijn CM, Gudnason V, Longstreth WT, Launer LJ, Lathrop M, Seshadri S, Tzourio C, Adams HH, Matthews PM, Fornage M, Debette S. Cerebral small vessel disease genomics and its implications across the lifespan. Nat Commun 2020; 11:6285. [PMID: 33293549 PMCID: PMC7722866 DOI: 10.1038/s41467-020-19111-2] [Citation(s) in RCA: 83] [Impact Index Per Article: 20.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2020] [Accepted: 09/10/2020] [Indexed: 12/14/2022] Open
Abstract
White matter hyperintensities (WMH) are the most common brain-imaging feature of cerebral small vessel disease (SVD), hypertension being the main known risk factor. Here, we identify 27 genome-wide loci for WMH-volume in a cohort of 50,970 older individuals, accounting for modification/confounding by hypertension. Aggregated WMH risk variants were associated with altered white matter integrity (p = 2.5×10-7) in brain images from 1,738 young healthy adults, providing insight into the lifetime impact of SVD genetic risk. Mendelian randomization suggested causal association of increasing WMH-volume with stroke, Alzheimer-type dementia, and of increasing blood pressure (BP) with larger WMH-volume, notably also in persons without clinical hypertension. Transcriptome-wide colocalization analyses showed association of WMH-volume with expression of 39 genes, of which four encode known drug targets. Finally, we provide insight into BP-independent biological pathways underlying SVD and suggest potential for genetic stratification of high-risk individuals and for genetically-informed prioritization of drug targets for prevention trials.
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Affiliation(s)
- Muralidharan Sargurupremraj
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Hideaki Suzuki
- Tohoku Medical Megabank Organization, Tohoku University, 2-1, Seiryo, Aoba, Sendai, 980-8573, Japan
- Department of Cardiovascular Medicine, Tohoku University Hospital, 1-1, Seiryo, Aoba, Sendai, 980-8574, Japan
- Department of Brain Sciences, Imperial College London, London, W12 0NN, UK
| | - Xueqiu Jian
- University of Texas Health Science Center at Houston McGovern Medical School, Houston, TX, 77030, USA
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
| | - Chloé Sarnowski
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Tavia E Evans
- Department of Clinical Genetics, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
- Department of Radiology & Nuclear Medicine, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Joshua C Bis
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, 98101, USA
| | | | - Saori Sakaue
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan
- Department of Allergy and Rheumatology, Graduate School of Medicine, the University of Tokyo, Tokyo, 113-0033, Japan
| | - Natalie Terzikhan
- Department of Epidemiology, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Mohamad Habes
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Institute for Community Medicine, University Medicine Greifswald, 17475, Greifswald, Germany
| | - Wei Zhao
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109-2029, USA
| | - Nicola J Armstrong
- Mathematics and Statistics, Murdoch University, Murdoch, WA, 6150, Australia
| | - Edith Hofer
- Clinical Division of Neurogeriatrics, Department of Neurology, Medical University of Graz, 8036, Graz, Austria
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, 8036, Graz, Austria
| | - Lisa R Yanek
- GeneSTAR Research Program, Division of General Internal Medicine, Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21205, USA
| | - Saskia P Hagenaars
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Social Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, SE5 8AF, UK
| | - Rajan B Kumar
- Department of Public Health Sciences, University of California at Davis, Davis, CA, 95616, USA
| | - Erik B van den Akker
- Section of Molecular Epidemiology, Biomedical Sciences, Leiden university Medical Center, 2333 ZA, Leiden, The Netherlands
- Pattern Recognition & Bioinformatics, Delft University of Technology, Delft, NL, 2629 HS, USA
- Leiden Computational Biology Centre, Leiden University Medical Centre, 2333 ZA, Leiden, The Netherlands
| | - Rebekah E McWhirter
- Centre for Law and Genetics, Faculty of Law, University of Tasmania, Hobart, TAS, 7005, Australia
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
| | - Stella Trompet
- Department of Internal Medicine, section of gerontology and geriatrics, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
- Department of Cardiology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Aniket Mishra
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Yasaman Saba
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
- Gottfried Schatz Research Center, Department of Molecular Biology and Biochemistry, Medical University of Graz, 8010, Graz, Austria
| | - Claudia L Satizabal
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
- Boston University and the NHLBI's Framingham Heart Study, Boston, MA, 02215, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Gregory Beaudet
- University of Bordeaux, IMN, UMR 5293, 33000, Bordeaux, France
| | - Laurent Petit
- University of Bordeaux, IMN, UMR 5293, 33000, Bordeaux, France
| | - Ami Tsuchida
- University of Bordeaux, IMN, UMR 5293, 33000, Bordeaux, France
| | - Laure Zago
- University of Bordeaux, IMN, UMR 5293, 33000, Bordeaux, France
| | - Sabrina Schilling
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | | | | | - Cora E Lewis
- University of Alabama at Birmingham School of Medicine, Birmingham, AL, 35233, USA
| | - Neelum T Aggarwal
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Oscar L Lopez
- Departments of Neurology and Psychiatry, University of Pittsburgh, Pittsburgh, PA, 15213, USA
| | - Jennifer A Smith
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109-2029, USA
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Maria C Valdés Hernández
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK
- Row Fogo Centre for Ageing and The Brain, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Jeroen van der Grond
- Department of Radiology, Leiden University medical Center, 2333 ZA, Leiden, The Netherlands
| | - Margaret J Wright
- Queensland Brain Institute, The University of Queensland, St Lucia, QLD, 4072, Australia
- Centre for Advanced Imaging, The University of Queensland, St Lucia, QLD, 4072, Australia
| | - Maria J Knol
- Department of Epidemiology, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Marcus Dörr
- Department of Internal Medicine B, University Medicine Greifswald, 17475, Greifswald, Germany
- DZHK (German Center for Cardiovascular Research), partner site Greifswald, 17475, Greifswald, Germany
| | - Russell J Thomson
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
- Centre for Research in Mathematics and Data Science, Western Sydney University, Penrith, NSW, 2751, Australia
| | - Constance Bordes
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Quentin Le Grand
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Marie-Gabrielle Duperron
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | | | | | - Pamela J Schreiner
- University of Minnesota School of Public Health, Minneapolis, MN, 55455, USA
| | - Denis A Evans
- Department of Internal Medicine, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Alexa S Beiser
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
- Boston University and the NHLBI's Framingham Heart Study, Boston, MA, 02215, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Susana Muñoz Maniega
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK
| | - Marian Beekman
- Section of Molecular Epidemiology, Biomedical Sciences, Leiden university Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Julian Trollor
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, 2052, Australia
- Department of Developmental Disability Neuropsychiatry, School of Psychiatry, University of New South Wales, Sydney, NSW, 2052, Australia
| | - David J Stott
- Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, UK
| | - Meike W Vernooij
- Department of Radiology & Nuclear Medicine, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
- Department of Epidemiology, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Katharina Wittfeld
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, 17489, Greifswald, Germany
| | - Wiro J Niessen
- Department of Radiology & Nuclear Medicine, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
- Faculty of Applied Sciences, Delft University of Technology, Delft, NL, 2629 HS, USA
| | - Aicha Soumaré
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Eric Boerwinkle
- University of Texas Health Science Center at Houston School of Public Health, Houston, TX, 77030, USA
| | - Stephen Sidney
- Kaiser Permanente Division of Research, Oakland, CA, 94612, USA
| | - Stephen T Turner
- Division of Nephrology and Hypertension, Mayo Clinic, Rochester, MN, 55905, USA
| | - Gail Davies
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, 8036, Graz, Austria
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Anbupalam Thalamuthu
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Uwe Völker
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, 17475, Greifswald, Germany
| | - Mark A van Buchem
- Row Fogo Centre for Ageing and The Brain, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - R Nick Bryan
- The University of Texas at Austin Dell Medical School, Austin, TX, 78712, USA
| | - Josée Dupuis
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
- Department of Cardiology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Mark E Bastin
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, 8036, Graz, Austria
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, 48104, USA
| | - David Ames
- National Ageing Research Institute Royal Melbourne Hospital, Parkville, VIC, 3052, Australia
- Academic Unit for Psychiatry of Old Age, University of Melbourne, St George's Hospital, Kew, VIC, 3101, Australia
| | - Alexander Teumer
- Department of Epidemiology, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
- Department of Internal Medicine B, University Medicine Greifswald, 17475, Greifswald, Germany
| | - Philippe Amouyel
- Inserm U1167, 59000, Lille, France
- Department of Epidemiology and Public Health, Pasteur Institute of Lille, 59000, Lille, France
| | - John B Kwok
- Brain and Mind Centre - The University of Sydney, Camperdown, NSW, 2050, Australia
- School of Medical Sciences, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Robin Bülow
- Department of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, 17489, Greifswald, Germany
| | - Ian J Deary
- Institute for Medical Informatics, Statistics and Documentation, Medical University of Graz, 8036, Graz, Austria
- Department of Psychology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
| | - Peter R Schofield
- School of Medical Sciences, University of New South Wales, Sydney, NSW, 2052, Australia
- Neuroscience Research Australia, Randwick, NSW, 2031, Australia
| | - Henry Brodaty
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
- Dementia Centre for Research Collaboration, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Jiyang Jiang
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Yasuharu Tabara
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Kazuya Setoh
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Susumu Miyamoto
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Kazumichi Yoshida
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Manabu Nagata
- Department of Neurosurgery, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan
| | - Fumihiko Matsuda
- Center for Genomic Medicine, Kyoto University Graduate School of Medicine, Kyoto, 606-8501, Japan
| | - Bruce M Psaty
- Departments of Epidemiology, Medicine and Health Services, University of Washington, Seattle, WA, 98195, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, 98101, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, 60612, USA
| | - Philip L De Jager
- Center for Translational and Computational Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, NY, 10032, USA
- Program in Population and Medical Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Thomas H Mosley
- Memory Impairment and Neurodegenerative Dementia (MIND) Center, University of Mississippi Medical Center, Jackson, MS, 39216, USA
| | - Perminder S Sachdev
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute and Pediatrics at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
- Neuropsychiatric Institute, Prince of Wales Hospital, Sydney, NSW, 2031, Australia
| | - Reinhold Schmidt
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109-2029, USA
| | - Helen R Warren
- William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, E1 4NS, UK
- National Institute for Health Research Barts Cardiovascular Biomedical Research Unit, Queen Mary University of London, London, EC1M 6BQ, UK
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, SW7 2AZ, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, Ioannina, Mpizani, 455 00, Greece
| | - David-Alexandre Trégouët
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
| | - Mohammad A Ikram
- Department of Epidemiology, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Wei Wen
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, 2052, Australia
| | - Charles DeCarli
- Department of Neurology and Center for Neuroscience, University of California at Davis, Sacramento, CA, 95817, USA
| | - Velandai K Srikanth
- Menzies Institute for Medical Research, University of Tasmania, Hobart, TAS, 7000, Australia
- Peninsula Clinical School, Central Clinical School, Monash University, Melbourne, VIC, 3004, Australia
| | - J Wouter Jukema
- Department of Cardiology, Leiden University Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Eline P Slagboom
- Section of Molecular Epidemiology, Biomedical Sciences, Leiden university Medical Center, 2333 ZA, Leiden, The Netherlands
| | - Sharon L R Kardia
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, 48109-2029, USA
| | - Yukinori Okada
- Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871, Japan
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Tsurumi-ku, Yokohama City, Kanagawa, 230-0045, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, 565-0871, Osaka, Japan
| | - Bernard Mazoyer
- University of Bordeaux, IMN, UMR 5293, 33000, Bordeaux, France
| | - Joanna M Wardlaw
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, EH16 4SB, UK
- Row Fogo Centre for Ageing and The Brain, University of Edinburgh, Edinburgh, EH8 9JZ, UK
- MRC UK Dementia Research Institute at the University of Edinburgh, Edinburgh, EH8 9YL, UK
| | - Paul A Nyquist
- Department of Neurology, Johns Hopkins School of Medicine, Baltimone, MD, 21205, USA
- General Internal Medicine, Johns Hopkins School of Medicine, Baltimore, MD, 21205, USA
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, University of New South Wales, Sydney, NSW, 2052, Australia
- Neuroscience Research Australia, Randwick, NSW, 2031, Australia
| | - Hans J Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, 17475, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Rostock/Greifswald, 17475, Greifswald, Germany
| | - Helena Schmidt
- Gottfried Schatz Research Center, Department of Molecular Biology and Biochemistry, Medical University of Graz, 8010, Graz, Austria
| | - Cornelia M Van Duijn
- Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Vilmundur Gudnason
- Icelandic Heart Association, IS-201, Kópavogur, Iceland
- University of Iceland, Faculty of Medicine, 101, Reykjavík, Iceland
| | - William T Longstreth
- Departments of Neurology and Epidemiology, University of Washington, Seattle, WA, 98104-2420, USA
| | - Lenore J Launer
- Laboratory of Epidemiology, Demography, and Biometry, National Institute of Aging, The National Institutes of Health, Bethesda, MD, 20892, USA
- Intramural Research Program/National Institute on Aging/National Institutes of Health, Bethesda, MD, 20892, USA
| | - Mark Lathrop
- University of McGill Genome Center, Montreal, QC, H3A 0G1, Canada
| | - Sudha Seshadri
- Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center, San Antonio, TX, 78229, USA
- Boston University and the NHLBI's Framingham Heart Study, Boston, MA, 02215, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Christophe Tzourio
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France
- CHU de Bordeaux, Pole de santé publique, Service d'information médicale, 33000, Bordeaux, France
| | - Hieab H Adams
- Department of Clinical Genetics, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
- Department of Radiology & Nuclear Medicine, Erasmus MC, 3015 GE, Rotterdam, The Netherlands
| | - Paul M Matthews
- Department of Brain Sciences, Imperial College London, London, W12 0NN, UK
- UK Dementia Research Institute, London, WC1E 6BT, UK
- Data Science Institute, Imperial College London, London, SW7 2AZ, UK
| | - Myriam Fornage
- University of Texas Health Science Center at Houston McGovern Medical School, Houston, TX, 77030, USA.
| | - Stéphanie Debette
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000, Bordeaux, France.
- Department of Neurology, Boston University School of Medicine, Boston, MA, 02118, USA.
- Department of Neurology, CHU de Bordeaux, 33000, Bordeaux, France.
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Bahrani AA, Kong W, Shang Y, Huang C, Smith CD, Powell DK, Jiang Y, Rayapati AO, Jicha GA, Yu G. Diffuse optical assessment of cerebral-autoregulation in older adults stratified by cerebrovascular risk. JOURNAL OF BIOPHOTONICS 2020; 13:e202000073. [PMID: 32533642 PMCID: PMC8824485 DOI: 10.1002/jbio.202000073] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 05/06/2020] [Accepted: 06/09/2020] [Indexed: 05/04/2023]
Abstract
Diagnosis of cerebrovascular disease (CVD) at early stages is essential for preventing sequential complications. CVD is often associated with abnormal cerebral microvasculature, which may impact cerebral-autoregulation (CA). A novel hybrid near-infrared diffuse optical instrument and a finger plethysmograph were used to simultaneously detect low-frequency oscillations (LFOs) of cerebral blood flow (CBF), oxy-hemoglobin concentration ([HbO2 ]), deoxy-hemoglobin concentration ([Hb]) and mean arterial pressure (MAP) in older adults before, during and after 70° head-up-tilting (HUT). The participants with valid data were divided based on Framingham risk score (FRS, 1-30 points) into low-risk (FRS ≤15, n = 13) and high-risk (FRS >15, n = 11) groups for developing CVD. The LFO gains were determined by transfer function analyses with MAP as the input, and CBF, [HbO2 ] and [Hb] as the outputs (CA ∝ 1/Gain). At resting-baseline, LFO gains in the high-risk group were relatively lower compared to the low-risk group. The lower baseline gains in the high-risk group may attribute to compensatory mechanisms to maintain stronger steady-state CAs. However, HUT resulted in smaller gain reductions in the high-risk group compared to the low-risk group, suggesting weaker dynamic CAs. LFO gains are potentially valuable biomarkers for early detection of CVD based on associations with CAs.
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Affiliation(s)
- Ahmed A. Bahrani
- Department of Biomedical Engineering, University of Kentucky, Lexington, Kentucky
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky
- Biomedical Engineering Department, Al-Khwarizmi College of Engineering, University of Baghdad, Baghdad, Iraq
| | - Weikai Kong
- Department of Biomedical Engineering, University of Kentucky, Lexington, Kentucky
| | - Yu Shang
- Shanxi Provincial Key Laboratory for Biomedical Imaging and Big Data, North University of China, Shanxi, China
| | - Chong Huang
- Department of Biomedical Engineering, University of Kentucky, Lexington, Kentucky
| | - Charles D. Smith
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky
- Magnetic Resonance Imaging and Spectroscopy Center (MRISC), University of Kentucky, Lexington, Kentucky
- Department of Neurology, University of Kentucky, Lexington, Kentucky
| | - David K. Powell
- Magnetic Resonance Imaging and Spectroscopy Center (MRISC), University of Kentucky, Lexington, Kentucky
- Neuroscience Department, University of Kentucky, Lexington, Kentucky
| | - Yang Jiang
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky
- Magnetic Resonance Imaging and Spectroscopy Center (MRISC), University of Kentucky, Lexington, Kentucky
- Department of Behavioral Science, University of Kentucky, Lexington, Kentucky
| | - Abner O. Rayapati
- Department of Psychiatry, University of Kentucky, Lexington, Kentucky
| | - Gregory A. Jicha
- Sanders-Brown Center on Aging, University of Kentucky, Lexington, Kentucky
- Magnetic Resonance Imaging and Spectroscopy Center (MRISC), University of Kentucky, Lexington, Kentucky
- Department of Neurology, University of Kentucky, Lexington, Kentucky
| | - Guoqiang Yu
- Department of Biomedical Engineering, University of Kentucky, Lexington, Kentucky
- Correspondence: Guoqiang Yu, Department of Biomedical Engineering, University of Kentucky, Lexington, KY 40506,
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32
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Zarnani K, Smith SM, Alfaro-Almagro F, Fagerlund B, Lauritzen M, Rostrup E, Nichols TE. Discovering correlates of age-related decline in a healthy late-midlife male birth cohort. Aging (Albany NY) 2020; 12:16709-16743. [PMID: 32913141 PMCID: PMC7521526 DOI: 10.18632/aging.103345] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Accepted: 05/01/2020] [Indexed: 01/24/2023]
Abstract
Studies exploring age-related brain and cognitive change have identified substantial heterogeneity among individuals, but the underlying reasons for the differential trajectories remain largely unknown. We investigated cross-sectional and longitudinal associations between brain-imaging phenotypes (IDPs) and cognitive ability, and how these relations may be modified by common risk and protective factors. Participants were recruited from the 1953 Danish Male Birth Cohort (N=123), a longitudinal study of cognitive and brain ageing. Childhood IQ and socio-demographic factors are available for these participants who have been assessed regularly on multiple IDPs and behavioural factors in midlife. Using Pearson correlations and canonical correlation analysis (CCA), we explored the relation between 454 IDPs and 114 behavioural variables. CCA identified a single mode of population covariation coupling cross-subject longitudinal changes in brain structure to changes in cognitive performance and to a range of age-related covariates (r=0.92, Pcorrected < 0.001). Specifically, this CCA-mode indicated that; decreases in IQ and speed assessed tasks, higher rates of familial myocardial infarct, less physical activity, and poorer mental health are associated with larger decreases in whole brain grey matter and white matter. We found no evidence supporting the role of baseline scores as predictors of impending brain and behavioural change in late-midlife.
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Affiliation(s)
- Kiyana Zarnani
- Functional Imaging Unit, Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Glostrup, Denmark
- Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark
- Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Stephen M. Smith
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Fidel Alfaro-Almagro
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Birgitte Fagerlund
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Center Glostrup, Denmark
- Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Martin Lauritzen
- Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark
- Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Neurophysiology, Rigshospitalet-Glostrup, Denmark
| | - Egill Rostrup
- Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Center Glostrup, Denmark
| | - Thomas E. Nichols
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
- Oxford Big Data Institute, Li Ka Shing, Centre For Health Information and Discovery, Nuffield Department of Population Health, University of Oxford, UK
- Department of Statistics, University of Warwick, Coventry, UK
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33
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Zaborenko CJ, Ferraro KF, Williams-Farrelly MM. Childhood Misfortune and Late-Life Stroke Incidence, 2004-2014. THE GERONTOLOGIST 2020; 60:1060-1070. [PMID: 32267501 DOI: 10.1093/geront/gnaa007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/24/2019] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND AND OBJECTIVES Although most strokes occur in later life, recent studies reveal that negative exposures decades earlier are associated with stroke risk. The purpose of this study was to examine whether accumulated and/or specific domains of early misfortune are related to stroke incidence in later life. RESEARCH DESIGN AND METHODS A decade of longitudinal data from stroke-free participants 50 years or older in the Health and Retirement Study were analyzed (N = 12,473). Incident stroke was defined as either self-reported first incident stroke or death due to stroke between 2004 and 2014. RESULTS Analyses revealed that accumulated misfortune was associated with increased stroke risk, but the relationship was moderated by wealth. Examining specific domains of childhood misfortune revealed that stroke incidence was greater for persons with behavioral/psychological risks, but that this relationship also was moderated by higher wealth for those with only one behavioral/psychological risk. DISCUSSION AND IMPLICATIONS Accumulated childhood misfortune and adolescent depression heighten the risk of stroke in later life, but the influence is remediable through adult wealth. Reducing poverty in later life may decrease stroke incidence for persons exposed to negative childhood exposures.
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Affiliation(s)
- Callie J Zaborenko
- Department of Sociology, Purdue University, West Lafayette, Indiana.,Center on Aging and the Life Course, Purdue University, West Lafayette, Indiana
| | - Kenneth F Ferraro
- Department of Sociology, Purdue University, West Lafayette, Indiana.,Center on Aging and the Life Course, Purdue University, West Lafayette, Indiana
| | - Monica M Williams-Farrelly
- Department of Sociology, Purdue University, West Lafayette, Indiana.,Center on Aging and the Life Course, Purdue University, West Lafayette, Indiana
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34
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Clancy U, Garcia DJ, Stringer MS, Thrippleton MJ, Valdés-Hernández MC, Wiseman S, Hamilton OK, Chappell FM, Brown R, Blair GW, Hewins W, Sleight E, Ballerini L, Bastin ME, Maniega SM, MacGillivray T, Hetherington K, Hamid C, Arteaga C, Morgan AG, Manning C, Backhouse E, Hamilton I, Job D, Marshall I, Doubal FN, Wardlaw JM. Rationale and design of a longitudinal study of cerebral small vessel diseases, clinical and imaging outcomes in patients presenting with mild ischaemic stroke: Mild Stroke Study 3. Eur Stroke J 2020; 6:81-88. [PMID: 33817338 PMCID: PMC7995323 DOI: 10.1177/2396987320929617] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2020] [Accepted: 04/14/2020] [Indexed: 12/21/2022] Open
Abstract
Background Cerebral small vessel disease is a major cause of dementia and stroke, visible on brain magnetic resonance imaging. Recent data suggest that small vessel disease lesions may be dynamic, damage extends into normal-appearing brain and microvascular dysfunctions include abnormal blood–brain barrier leakage, vasoreactivity and pulsatility, but much remains unknown regarding underlying pathophysiology, symptoms, clinical features and risk factors of small vessel disease. Patients and Methods: The Mild Stroke Study 3 is a prospective observational cohort study to identify risk factors for and clinical implications of small vessel disease progression and regression among up to 300 adults with non-disabling stroke. We perform detailed serial clinical, cognitive, lifestyle, physiological, retinal and brain magnetic resonance imaging assessments over one year; we assess cerebrovascular reactivity, blood flow, pulsatility and blood–brain barrier leakage on magnetic resonance imaging at baseline; we follow up to four years by post and phone. The study is registered ISRCTN 12113543. Summary Factors which influence direction and rate of change of small vessel disease lesions are poorly understood. We investigate the role of small vessel dysfunction using advanced serial neuroimaging in a deeply phenotyped cohort to increase understanding of the natural history of small vessel disease, identify those at highest risk of early disease progression or regression and uncover novel targets for small vessel disease prevention and therapy.
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Affiliation(s)
- Una Clancy
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Michael S Stringer
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | | | - Stewart Wiseman
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Olivia Kl Hamilton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Rosalind Brown
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Gordon W Blair
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Will Hewins
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Emilie Sleight
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Lucia Ballerini
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Mark E Bastin
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Tom MacGillivray
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Charlene Hamid
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Carmen Arteaga
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Alasdair G Morgan
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Cameron Manning
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Ellen Backhouse
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Iona Hamilton
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Dominic Job
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Ian Marshall
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Fergus N Doubal
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
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Abstract
Covert brain infarcts (CBIs) are five times more prevalent than symptomatic brain infarcts. CBIs are associated with cognitive impairment and therefore may be a target for preventing cognitive decline and dementia. This review focuses on strategies for preventing CBI-related cognitive impairment, either by preventing incident or recurrent CBI or by enhancing cognitive reserve. CBIs begin to become prevalent during midlife and are highly prevalent in later life. The distribution of vascular pathologies of CBI differs from those that cause symptomatic stroke; therefore, preventive treatments may need to differ as well. Only a few randomized clinical trials have provided data on CBI prevention, without conclusive results. Limited data suggest that higher early-life education, hypothesized to enhance cognitive reserve, can protect the brain from effects of CBI.
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Becker CE, Quinn TJ, Williams A. Association Between Endothelial Cell Stabilizing Medication and Small Vessel Disease Stroke: A Case-Control Study. Front Neurol 2019; 10:1029. [PMID: 31608006 PMCID: PMC6773869 DOI: 10.3389/fneur.2019.01029] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2019] [Accepted: 09/10/2019] [Indexed: 11/23/2022] Open
Abstract
Increasing evidence suggests a role for endothelial cell (EC) dysfunction in pathogenesis of cerebral small vessel disease. Commonly used medications including certain antihypertensives and statins have EC-stabilizing effects. We used individual patient data from completed acute stroke trials to assess whether prior exposure to EC-stabilizing medications was associated with lacunar stroke, using lacunar stroke as a clinical proxy for cerebral small vessel disease. Across 12,002 patients with relevant data, 2,855 (24%) had a lacunar stroke presentation. Univariable analyses suggested potential confounding from vascular diseases treated with EC-stabilizing medications. Initial multivariable logistic regression gave conflicting results when describing the independent association of exposure to EC-stabilizing medication and lacunar stroke in the complete population (O.R. 0.87, 95% C.I.: 0.77– 0.98) and limited to those taking any antihypertensive (O.R. 1.51, 95% C.I.: 1.21–1.88). Re-running the analyses including statins in the EC-stabilizing category suggested a beneficial effect of EC-stabilizing medication exposure on lacunar stroke incidence (O.R. 0.83, 95% C.I.: 0.73–0.93). These results align with recent pre-clinical data and would support interventional trials of EC-stabilizing medication for preventing cerebral small vessel disease. Our results also suggest that analyses of EC-stabilizing interventions need to adjust for potential endothelial effects of other co-prescribed medication.
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Affiliation(s)
- Charlotte Elisabeth Becker
- Centre for Regenerative Medicine, UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom.,School of Medicine and Health Sciences, University of Oldenburg, Oldenburg, Germany
| | - Terence J Quinn
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, United Kingdom
| | - Anna Williams
- Centre for Regenerative Medicine, UK Dementia Research Institute, University of Edinburgh, Edinburgh, United Kingdom
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Zarnani K, Nichols TE, Alfaro-Almagro F, Fagerlund B, Lauritzen M, Rostrup E, Smith SM. Discovering markers of healthy aging: a prospective study in a Danish male birth cohort. Aging (Albany NY) 2019; 11:5943-5974. [PMID: 31480020 PMCID: PMC6738442 DOI: 10.18632/aging.102151] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2019] [Accepted: 07/31/2019] [Indexed: 01/23/2023]
Abstract
There is a pressing need to identify markers of cognitive and neural decline in healthy late-midlife participants. We explored the relationship between cross-sectional structural brain-imaging derived phenotypes (IDPs) and cognitive ability, demographic, health and lifestyle factors (non-IDPs). Participants were recruited from the 1953 Danish Male Birth Cohort (N=193). Applying an extreme group design, members were selected in 2 groups based on cognitive change between IQ at age ~20y (IQ-20) and age ~57y (IQ-57). Subjects showing the highest (n=95) and lowest (n=98) change were selected (at age ~57) for assessments on multiple IDPs and non-IDPs. We investigated the relationship between 453 IDPs and 70 non-IDPs through pairwise correlation and multivariate canonical correlation analysis (CCA) models. Significant pairwise associations included positive associations between IQ-20 and gray-matter volume of the temporal pole. CCA identified a richer pattern - a single "positive-negative" mode of population co-variation coupling individual cross-subject variations in IDPs to an extensive range of non-IDP measures (r = 0.75, Pcorrected < 0.01). Specifically, this mode linked higher cognitive performance, positive early-life social factors, and mental health to a larger brain volume of several brain structures, overall volume, and microstructural properties of some white matter tracts. Interestingly, both statistical models identified IQ-20 and gray-matter volume of the temporal pole as important contributors to the inter-individual variation observed. The converging patterns provide novel insight into the importance of early adulthood intelligence as a significant marker of late-midlife neural decline and motivates additional study.
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Affiliation(s)
- Kiyana Zarnani
- Functional Imaging Unit, Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital Rigshospitalet, Glostrup, Denmark.,Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark.,Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark.,Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Thomas E Nichols
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.,Oxford Big Data Institute, Li Ka Shing, Centre For Health Information and Discovery, Nuffield Department of Population Health University of Oxford, Oxford, UK.,Department of Statistics, University of Warwick, Coventry, UK
| | - Fidel Alfaro-Almagro
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Birgitte Fagerlund
- Center for Neuropsychiatric Schizophrenia Research, Mental Health Center, Glostrup, Denmark.,Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Martin Lauritzen
- Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark.,Department of Neuroscience, University of Copenhagen, Copenhagen, Denmark.,Department of Clinical Medicine, Glostrup, Denmark
| | - Egill Rostrup
- Center for Healthy Aging, University of Copenhagen, Copenhagen, Denmark.,Center for Neuropsychiatric Schizophrenia Research, Mental Health Center, Glostrup, Denmark.,Department of Psychology, University of Copenhagen, Copenhagen, Denmark
| | - Stephen M Smith
- Wellcome Centre for Integrative Neuroimaging, Oxford Centre for Functional Magnetic Resonance Imaging of the Brain (FMRIB), Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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Wardlaw JM, Smith C, Dichgans M. Small vessel disease: mechanisms and clinical implications. Lancet Neurol 2019; 18:684-696. [DOI: 10.1016/s1474-4422(19)30079-1] [Citation(s) in RCA: 500] [Impact Index Per Article: 100.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2018] [Revised: 02/01/2019] [Accepted: 02/07/2019] [Indexed: 02/06/2023]
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Deary IJ, Harris SE, Hill WD. What genome-wide association studies reveal about the association between intelligence and physical health, illness, and mortality. Curr Opin Psychol 2019; 27:6-12. [PMID: 30071465 PMCID: PMC6624475 DOI: 10.1016/j.copsyc.2018.07.005] [Citation(s) in RCA: 34] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2018] [Accepted: 07/17/2018] [Indexed: 01/02/2023]
Abstract
The associations between higher intelligence test scores from early life and later good health, fewer illnesses, and longer life are recent discoveries. Researchers are mapping the extent of these associations and trying to understanding them. Part of the intelligence-health association has genetic origins. Recent advances in molecular genetic technology and statistical analyses have revealed that: intelligence and many health outcomes are highly polygenic; and that modest but widespread genetic correlations exist between intelligence and health, illness and mortality. Causal accounts of intelligence-health associations are still poorly understood. The contribution of education and socio-economic status - both of which are partly genetic in origin - to the intelligence-health associations are being explored.
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Affiliation(s)
- Ian J Deary
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, United Kingdom.
| | - Sarah E Harris
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, United Kingdom; Medical Genetics Section, Centre for Genomic & Experimental Medicine, MRC Institute of Genetics & Molecular Medicine, University of Edinburgh, Western General Hospital, Edinburgh EH4 2XU, United Kingdom
| | - W David Hill
- Centre for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, 7 George Square, Edinburgh EH8 9JZ, United Kingdom
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Eroğlu SE, Aksel G, Yönak H, Satıcı MO. Diagnostic and prognostic values of cerebral oxygen saturations measured by INVOS™ in patients with ischemic and hemorrhagic cerebrovascular disease. Turk J Emerg Med 2019; 19:64-67. [PMID: 31073543 PMCID: PMC6497985 DOI: 10.1016/j.tjem.2019.01.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2018] [Revised: 01/09/2019] [Accepted: 01/09/2019] [Indexed: 11/20/2022] Open
Abstract
Objectives In this study it was aimed to investigate whether measurement of potential changes of cerebral oxygenation saturations due to ischemic or hemorrhagic cerebrovascular diseases have an early diagnostic and prognostic value. Methods Adult patients (≥18 years old) having acute ischemic or hemorrhagic stroke were included in the study. Patients under 18-year-old, those with incomplete data or suspicious diagnosis were excluded. The cerebral oxygen saturations of the patients were compared with the healthy subjects. Patients were also grouped according to their clinical outcomes; good clinical status (group 1) and poor clinical status (group 2). These groups were compared according to the patients’ cerebral oxygen saturations. Results The mean oxygen saturation of the patients and healthy people were similar (59.48% ± 10.6 versus 58.44% ± 9.6). There was no difference between patients and healthy population according to cerebral oxygen saturations. Furthermore, mean oxygen levels were also similar between the hemisphere without lesion and with lesion in the patients group (59.8% ± 11.8 versus 59.2% ± 10.4). When the patients were grouped according to their clinical status, there were 30 patients in group 1 and 15 in group 2. The cerebral oxygen saturations of the hemisphere with lesion were similar between these groups and no statistical difference was observed (59.2% ± 9.3 versus 59.1% ± 12.6, p = 0.9). There was also no statistical difference between the groups when delta oxygen levels of the affected and unaffected hemispheres of the groups were calculated (0.9% ± 6.1 versus 0.13% ± 8.4, p = 0.7). Conclusion Results of this study revealed that there was no difference in cerebral oxygen saturations measured by near-infrared cerebral oximetry system between the patients with cerebrovascular disease and healthy population. Furthermore, our results did not support that the cerebral oxygen saturations may be used for determining the prognosis of the patients with cerebrovascular disease.
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Affiliation(s)
- Serkan Emre Eroğlu
- University of Health Sciences, Umraniye Training and Research Hospital, Emergency Medicine Clinic, Istanbul, Turkey
| | - Gökhan Aksel
- University of Health Sciences, Umraniye Training and Research Hospital, Emergency Medicine Clinic, Istanbul, Turkey
| | - Hayrullah Yönak
- University of Health Sciences, Umraniye Training and Research Hospital, Emergency Medicine Clinic, Istanbul, Turkey
| | - Merve Osoydan Satıcı
- University of Health Sciences, Umraniye Training and Research Hospital, Emergency Medicine Clinic, Istanbul, Turkey
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Abdulle LE, Hao JL, Pant OP, Liu XF, Zhou DD, Gao Y, Suwal A, Lu CW. MALAT1 as a Diagnostic and Therapeutic Target in Diabetes-Related Complications: A Promising Long-Noncoding RNA. Int J Med Sci 2019; 16:548-555. [PMID: 31171906 PMCID: PMC6535662 DOI: 10.7150/ijms.30097] [Citation(s) in RCA: 74] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/20/2018] [Accepted: 02/08/2019] [Indexed: 02/06/2023] Open
Abstract
Diabetes mellitus is a global issue with increasing incidence rate worldwide. In an uncontrolled case, it can advance to various organ-related complications leading to an increase in morbidity and mortality. Long non-coding RNA (lncRNA) Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) appears to be a fairly novel lncRNA that is relevant to diabetes and its role in diabetic-related diseases initiation and progression have long been a subject of attention to many scholars. The expression of MALAT1 is elevated in different diabetic-related diseases. In this review, we demonstrate the various functions of MALAT1 in the different diabetes-related complications including ischemic reperfusion injury, retinopathy, cataract, atherosclerosis, cardiomyopathy, non-alcoholic steatohepatitis, gastroparesis, kidney disease, and gestational diabetes. The emerging evidence showed that the role of MALAT1 in diabetic-related complications is both pro-inflammatory and apoptosis in different cell types. These results concluded that MALAT1 is a potential diagnostic and future targeted therapy for diabetes-associated complications.
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Affiliation(s)
| | | | | | | | | | - Ying Gao
- Department of Endocrinology, The First Hospital of Jilin University, No. 71 of Xinmin St. Changchun, Jilin Province, 130021, China
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Altermatt A, Gaetano L, Magon S, Bauer L, Feurer R, Gnahn H, Hartmann J, Seifert CL, Poppert H, Wuerfel J, Radue EW, Kappos L, Sprenger T. Clinical associations of T2-weighted lesion load and lesion location in small vessel disease: Insights from a large prospective cohort study. Neuroimage 2019; 189:727-733. [DOI: 10.1016/j.neuroimage.2019.01.052] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2018] [Revised: 01/14/2019] [Accepted: 01/19/2019] [Indexed: 11/28/2022] Open
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Debette S, Strbian D, Wardlaw JM, van der Worp HB, Rinkel GJE, Caso V, Dichgans M. Fourth European stroke science workshop. Eur Stroke J 2018; 3:206-219. [PMID: 31009021 PMCID: PMC6453207 DOI: 10.1177/2396987318774443] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2018] [Accepted: 03/23/2018] [Indexed: 12/15/2022] Open
Abstract
Lake Eibsee, Garmisch-Partenkirchen, 16 to 18 November, 2017: The European Stroke Organisation convened >120 stroke experts from 21 countries to discuss latest results and hot topics in clinical, translational and basic stroke research. Since its inception in 2011, the European Stroke Science Workshop has become a cornerstone of European Stroke Organisation's academic activities and a major highlight for researchers in the field. Participants include stroke researchers at all career stages and with different backgrounds, who convene for plenary lectures and discussions. The workshop was organised in seven scientific sessions focusing on the following topics: (1) acute stroke treatment and endovascular therapy; (2) small vessel disease; (3) opportunities for stroke research in the omics era; (4) vascular cognitive impairment; (5) intracerebral and subarachnoid haemorrhage; (6) alternative treatment concepts and (7) neural circuits, recovery and rehabilitation. All sessions started with a keynote lecture providing an overview on current developments, followed by focused talks on a timely topic with the most recent findings, including unpublished data. In the following, we summarise the key contents of the meeting. The program is provided in the online only Data Supplement. The workshop started with a key note lecture on how to improve the efficiency of clinical trial endpoints in stroke, which was delivered by Craig Anderson (Sydney, Australia) and set the scene for the following discussions.
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Affiliation(s)
- S Debette
- Inserm Centre Bordeaux Population Health (U1219), University of Bordeaux, Bordeaux, France
- Department of Neurology, Bordeaux University Hospital, Bordeaux, France
| | - D Strbian
- Department of Neurology, Helsinki University Central Hospital, Helsinki, Finland
| | - JM Wardlaw
- Centre for Clinical Brain Sciences, and UK Dementia Research Institute at the University of Edinburgh, University of Edinburgh, Edinburgh, UK
| | - HB van der Worp
- Department of Neurology and neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands
| | - GJE Rinkel
- Department of Neurology and neurosurgery, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands
| | - V Caso
- Stroke Unit and Division of Cardiovascular Medicine, University of Perugia, Perugia, Italy
| | - M Dichgans
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
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Brown R, Benveniste H, Black SE, Charpak S, Dichgans M, Joutel A, Nedergaard M, Smith KJ, Zlokovic BV, Wardlaw JM. Understanding the role of the perivascular space in cerebral small vessel disease. Cardiovasc Res 2018; 114:1462-1473. [PMID: 29726891 PMCID: PMC6455920 DOI: 10.1093/cvr/cvy113] [Citation(s) in RCA: 199] [Impact Index Per Article: 33.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/05/2018] [Revised: 04/18/2018] [Accepted: 05/02/2018] [Indexed: 12/17/2022] Open
Abstract
Small vessel diseases (SVDs) are a group of disorders that result from pathological alteration of the small blood vessels in the brain, including the small arteries, capillaries and veins. Of the 35-36 million people that are estimated to suffer from dementia worldwide, up to 65% have an SVD component. Furthermore, SVD causes 20-25% of strokes, worsens outcome after stroke and is a leading cause of disability, cognitive impairment and poor mobility. Yet the underlying cause(s) of SVD are not fully understood. Magnetic resonance imaging has confirmed enlarged perivascular spaces (PVS) as a hallmark feature of SVD. In healthy tissue, these spaces are proposed to form part of a complex brain fluid drainage system which supports interstitial fluid exchange and may also facilitate clearance of waste products from the brain. The pathophysiological signature of PVS and what this infers about their function and interaction with cerebral microcirculation, plus subsequent downstream effects on lesion development in the brain has not been established. Here we discuss the potential of enlarged PVS to be a unique biomarker for SVD and related brain disorders with a vascular component. We propose that widening of PVS suggests presence of peri-vascular cell debris and other waste products that form part of a vicious cycle involving impaired cerebrovascular reactivity, blood-brain barrier dysfunction, perivascular inflammation and ultimately impaired clearance of waste proteins from the interstitial fluid space, leading to accumulation of toxins, hypoxia, and tissue damage. Here, we outline current knowledge, questions and hypotheses regarding understanding the brain fluid dynamics underpinning dementia and stroke through the common denominator of SVD.
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Affiliation(s)
- Rosalind Brown
- Centre for Clinical Brain Sciences, The University of Edinburgh, Chancellor's Building, Edinburgh, UK
| | - Helene Benveniste
- Department of Anesthesiology, Yale School of Medicine, New Haven, USA
| | - Sandra E Black
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
- Hurvitz Brain Sciences Program, Sunnybrook Health Sciences Center, University of Toronto, Toronto, Canada
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, Canada
| | - Serge Charpak
- INSERM U1128, Laboratory of Neurophysiology and New Microscopies, Université Paris Descartes, Paris, France
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
- German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany
- Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Anne Joutel
- Genetics and Pathogenesis of Cerebrovascular Diseases, INSERM, Université Paris Diderot-Paris 7, Paris, France
- DHU NeuroVasc, Sorbonne Paris Cité, Paris, France
| | - Maiken Nedergaard
- Section for Translational Neuroscience, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen 2200, Denmark
- Division of Glia Disease and Therapeutics, Center for Translational Neuromedicine, University of Rochester Medical School, Rochester, USA
| | - Kenneth J Smith
- Department of Neuroinflammation, UCL Institute of Neurology, London, UK
| | - Berislav V Zlokovic
- Zilkha Neurogenetic Institute, Keck School of Medicine, University of Southern California, Los Angeles, USA
- Department of Physiology and Neuroscience, Keck School of Medicine, University of Southern California, Los Angeles, USA
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, Chancellor's Building, Edinburgh, UK
- UK Dementia Research Institute at The University of Edinburgh, Chancellor's Building, Edinburgh, UK
- Row Fogo Centre for Research into Ageing and the Brain, The University of Edinburgh, Chancellor's Building, Edinburgh, UK
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Backhouse EV, McHutchison CA, Cvoro V, Shenkin SD, Wardlaw JM. Cognitive ability, education and socioeconomic status in childhood and risk of post-stroke depression in later life: A systematic review and meta-analysis. PLoS One 2018; 13:e0200525. [PMID: 30011299 PMCID: PMC6047794 DOI: 10.1371/journal.pone.0200525] [Citation(s) in RCA: 31] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2018] [Accepted: 06/28/2018] [Indexed: 11/18/2022] Open
Abstract
BACKGROUND Depression after stroke is common and is associated with poorer recovery. Risk factors such as gender, age and stroke severity are established, but it is unclear whether factors from earlier in life might also contribute. METHODS We searched MEDLINE, PsycINFO, EMBASE and meta-analysed all available evidence on childhood (premorbid) IQ, socioeconomic status (SES), education and stroke in adulthood. We included all studies reporting data on >50 patients, calculating overall odds ratios (OR), mean difference, correlation, 95% confidence intervals (CI) and 95% predictive intervals (PI) using random effects methods. We quality assessed all studies, performed sensitivity analyses, assessed heterogeneity and publication bias. RESULTS We identified 33 studies including 2,664 participants with post-stroke depression and 5,460 without (314 participants not classified). Low education (< = 8 years) was associated with post-stroke depression in studies which defined depression as score of mild and above on a depression rating scale (OR 1.47 95% CI 1.10-1.97, p<0.01) but not in studies where depression was defined as severe depressive symptoms or a clinical diagnosis of major depression (OR 1.04 95% CI 0.90-1.31, p = 0.60). Low education was not associated with an increased risk for post-stroke depression in studies that adjusted for age and sex (OR 0.86 95% CI 0.50-1.48 p = 0.58). Those with post-stroke depression had fewer years of education than those without post-stroke depression (MD 0.68 95% CI 0.05-1.31 p = 0.04). Few studies adjusted for vascular risk factors or stroke severity. Heterogeneity between studies was moderate and was partly explained by severity of depression. In the one study identified premorbid IQ did not differ between those with post-stroke depression (mean IQ 10.1.8 SD 9.8) vs those without (mean IQ 104 SD 10.1). There were no studies that examined childhood socioeconomic status and risk of post-stroke depression. CONCLUSIONS Having less education is associated with an increased risk of post-stroke depressive symptoms but with large confidence intervals and heterogeneity. Future studies should explore the relationship between early and late life risk factors to improve risk identification and to target prevention and treatment strategies.
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Affiliation(s)
- Ellen V. Backhouse
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Caroline A. McHutchison
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
| | - Vera Cvoro
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Scotland, United Kingdom
| | - Susan D. Shenkin
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Scotland, United Kingdom
- Geriatric Medicine, Department of Clinical and Surgical Sciences, The University of Edinburgh, Edinburgh, United Kingdom
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
- Centre for Cognitive Ageing and Cognitive Epidemiology, University of Edinburgh, Edinburgh, United Kingdom
- Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE), Scotland, United Kingdom
- UK Dementia Research Institute at The University of Edinburgh, Edinburgh Medical School, Edinburgh, United Kingdom
- * E-mail:
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Rajani RM, Quick S, Ruigrok SR, Graham D, Harris SE, Verhaaren BFJ, Fornage M, Seshadri S, Atanur SS, Dominiczak AF, Smith C, Wardlaw JM, Williams A. Reversal of endothelial dysfunction reduces white matter vulnerability in cerebral small vessel disease in rats. Sci Transl Med 2018; 10:10/448/eaam9507. [DOI: 10.1126/scitranslmed.aam9507] [Citation(s) in RCA: 86] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2017] [Revised: 01/31/2018] [Accepted: 06/08/2018] [Indexed: 12/23/2022]
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47
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Wardlaw JM. William M. Feinberg Award for Excellence in Clinical Stroke: Small Vessel Disease; a Big Problem, But Fixable. Stroke 2018; 49:1770-1775. [PMID: 29895535 DOI: 10.1161/strokeaha.118.021184] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2018] [Revised: 05/01/2018] [Accepted: 05/15/2018] [Indexed: 11/16/2022]
Affiliation(s)
- Joanna M Wardlaw
- From the Division of Neuroimaging Science, Centre for Clinical Brain Science, Edinburgh Imaging and UK Dementia Research Institute at the University of Edinburgh.
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48
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Jorgensen DR, Shaaban CE, Wiley CA, Gianaros PJ, Mettenburg J, Rosano C. A population neuroscience approach to the study of cerebral small vessel disease in midlife and late life: an invited review. Am J Physiol Heart Circ Physiol 2018; 314:H1117-H1136. [PMID: 29393657 PMCID: PMC6032084 DOI: 10.1152/ajpheart.00535.2017] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/01/2017] [Revised: 01/09/2018] [Accepted: 01/22/2018] [Indexed: 12/28/2022]
Abstract
Aging in later life engenders numerous changes to the cerebral microvasculature. Such changes can remain clinically silent but are associated with greater risk for negative health outcomes over time. Knowledge is limited about the pathogenesis, prevention, and treatment of potentially detrimental changes in the cerebral microvasculature that occur with advancing age. In this review, we summarize literature on aging of the cerebral microvasculature, and we propose a conceptual framework to fill existing research gaps and advance future work on this heterogeneous phenomenon. We propose that the major gaps in this area are attributable to an incomplete characterization of cerebrovascular pathology, the populations being studied, and the temporality of exposure to risk factors. Specifically, currently available measures of age-related cerebral microvasculature changes are indirect, primarily related to parenchymal damage rather than direct quantification of small vessel damage, limiting the understanding of cerebral small vessel disease (cSVD) itself. Moreover, studies seldom account for variability in the health-related conditions or interactions with risk factors, which are likely determinants of cSVD pathogenesis. Finally, study designs are predominantly cross-sectional and/or have relied on single time point measures, leaving no clear evidence of time trajectories of risk factors or of change in cerebral microvasculature. We argue that more resources should be invested in 1) developing methodological approaches and basic science models to better understand the pathogenic and etiological nature of age-related brain microvascular diseases and 2) implementing state-of-the-science population study designs that account for the temporal evolution of cerebral microvascular changes in diverse populations across the lifespan.
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Affiliation(s)
- Dana R Jorgensen
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh , Pittsburgh, Pennsylvania
| | - C Elizabeth Shaaban
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh , Pittsburgh, Pennsylvania
| | - Clayton A Wiley
- Department of Pathology, University of Pittsburgh , Pittsburgh, Pennsylvania
| | - Peter J Gianaros
- Departments of Psychology and Psychiatry, University of Pittsburgh , Pittsburgh, Pennsylvania
| | - Joseph Mettenburg
- Department of Radiology, University of Pittsburgh, University of Pittsburgh , Pittsburgh, Pennsylvania
| | - Caterina Rosano
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh , Pittsburgh, Pennsylvania
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49
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LncRNA MALAT1 promotes high glucose-induced inflammatory response of microglial cells via provoking MyD88/IRAK1/TRAF6 signaling. Sci Rep 2018; 8:8346. [PMID: 29844328 PMCID: PMC5974243 DOI: 10.1038/s41598-018-26421-5] [Citation(s) in RCA: 32] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2017] [Accepted: 05/08/2018] [Indexed: 11/09/2022] Open
Abstract
Although a large number of studies have confirmed from multiple levels that diabetes mellitus (DM) promotes cerebral ischemic reperfusion (I/R) injury, but the precise mechanism is still unclear. A cerebral I/R injury model in diabetic rats was established. The neurological deficit scores and brain edema were monitored at 24 and 72 hours after injury. The peri-infarct cortical tissues of rats were isolated for molecular biology detection. The rat primary microglia and microglia line HAPI were cultured to establish the cell model of DM-I/R by high glucose (HG) and hypoxia-reoxygenation (H/R). The endogenous expression of MALAT1 and MyD88 was regulated by the transfection with pcDNA-MALAT1, si-MALAT1 and si-MyD88, respectively. The cerebral I/R injury model in diabetic rats had more severe neuronal injury as shown by the significantly higher neurological deficit scores and an obvious increasing brain edema at 24 and 72 hours after injury. Moreover, the microglia were activated and induced a large number of inflammatory cytokines TNF-α, IL-1β and IL-6 in the peri-infarct cortical tissues during cerebral I/R injury associated with DM. The expression of MALAT1, MyD88, IRAK1 and TRAF6 protein were significantly up-regulated by DM-I/R in vitro and in vivo. Furthermore, the HG-H/R-induced MALAT1 promoted the inflammatory response in microglia via MyD88/IRAK1/TRAF6 signaling. Our results suggested that MALAT1 mediated the exacerbation of cerebral I/R injury induced by DM through triggering the inflammatory response in microglia via MyD88 signaling.
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50
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Horsburgh K, Wardlaw JM, van Agtmael T, Allan SM, Ashford MLJ, Bath PM, Brown R, Berwick J, Cader MZ, Carare RO, Davis JB, Duncombe J, Farr TD, Fowler JH, Goense J, Granata A, Hall CN, Hainsworth AH, Harvey A, Hawkes CA, Joutel A, Kalaria RN, Kehoe PG, Lawrence CB, Lockhart A, Love S, Macleod MR, Macrae IM, Markus HS, McCabe C, McColl BW, Meakin PJ, Miller A, Nedergaard M, O'Sullivan M, Quinn TJ, Rajani R, Saksida LM, Smith C, Smith KJ, Touyz RM, Trueman RC, Wang T, Williams A, Williams SCR, Work LM. Small vessels, dementia and chronic diseases - molecular mechanisms and pathophysiology. Clin Sci (Lond) 2018; 132:851-868. [PMID: 29712883 PMCID: PMC6700732 DOI: 10.1042/cs20171620] [Citation(s) in RCA: 38] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2017] [Revised: 02/08/2018] [Accepted: 02/21/2018] [Indexed: 12/14/2022]
Abstract
Cerebral small vessel disease (SVD) is a major contributor to stroke, cognitive impairment and dementia with limited therapeutic interventions. There is a critical need to provide mechanistic insight and improve translation between pre-clinical research and the clinic. A 2-day workshop was held which brought together experts from several disciplines in cerebrovascular disease, dementia and cardiovascular biology, to highlight current advances in these fields, explore synergies and scope for development. These proceedings provide a summary of key talks at the workshop with a particular focus on animal models of cerebral vascular disease and dementia, mechanisms and approaches to improve translation. The outcomes of discussion groups on related themes to identify the gaps in knowledge and requirements to advance knowledge are summarized.
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Affiliation(s)
- Karen Horsburgh
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, U.K.
| | - Joanna M Wardlaw
- Centre for Clinical Brain Sciences, UK Dementia Research Institute, University of Edinburgh, Edinburgh, U.K
| | - Tom van Agtmael
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, U.K
| | - Stuart M Allan
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester, U.K
| | | | - Philip M Bath
- Stroke Trials Unit, Division of Clinical Neuroscience, University of Nottingham, Nottingham, U.K
| | - Rosalind Brown
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, U.K
| | - Jason Berwick
- Department of Psychology, University of Sheffield, Sheffield, U.K
| | - M Zameel Cader
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Roxana O Carare
- Faculty of Medicine, University of Southampton, Southampton, U.K
| | - John B Davis
- Alzheimer's Research UK Oxford Drug Discovery Institute, University of Oxford, Oxford, U.K
| | - Jessica Duncombe
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, U.K
| | - Tracy D Farr
- School of Life Sciences, Nottingham University, Nottingham, U.K
| | - Jill H Fowler
- Centre for Discovery Brain Sciences, University of Edinburgh, Edinburgh, U.K
| | - Jozien Goense
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, U.K
| | - Alessandra Granata
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, U.K
| | | | - Atticus H Hainsworth
- Molecular and Clinical Sciences Research Institute, St Georges University of London, London, U.K
| | - Adam Harvey
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, U.K
| | - Cheryl A Hawkes
- Faculty of Science, Technology, Engineering & Mathematics, Open University, Milton Keynes, U.K
| | - Anne Joutel
- Genetics and Pathogenesis of Cerebrovascular Diseases, INSERM, Université Paris Diderot-Paris 7, Paris, France
| | - Rajesh N Kalaria
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, U.K
| | | | - Catherine B Lawrence
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester, U.K
| | | | - Seth Love
- Clinical Neurosciences, University of Bristol, Bristol, U.K
| | - Malcolm R Macleod
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, U.K
| | - I Mhairi Macrae
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, U.K
| | - Hugh S Markus
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, U.K
| | - Chris McCabe
- Institute of Neuroscience and Psychology, University of Glasgow, Glasgow, U.K
| | - Barry W McColl
- The Roslin Institute & R(D)SVS, UK Dementia Research Institute, University of Edinburgh, Edinburgh, U.K
| | - Paul J Meakin
- Division of Molecular & Clinical Medicine, School of Medicine, University of Dundee, Dundee, U.K
| | - Alyson Miller
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, U.K
| | - Maiken Nedergaard
- University of Rochester Medical Center, Rochester, NY, USA and University of Copenhagen's Center of Basic and Translational Neuroscience, Copenhagen, Denmark
| | - Michael O'Sullivan
- Mater Centre for Neuroscience and Queensland Brain Institute, Brisbane, Australia
| | - Terry J Quinn
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, U.K
| | - Rikesh Rajani
- Genetics and Pathogenesis of Cerebrovascular Diseases, INSERM, Université Paris Diderot-Paris 7, Paris, France
| | - Lisa M Saksida
- Robarts Research Institute, Western University, London, Ontario, Canada
| | - Colin Smith
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, U.K
| | - Kenneth J Smith
- Department of Neuroinflammation, UCL Institute of Neurology, London, U.K
| | - Rhian M Touyz
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, U.K
| | | | - Tao Wang
- Faculty of Biology, Medicine and Health, University of Manchester, Manchester, U.K
| | - Anna Williams
- MRC Centre for Regenerative Medicine, University of Edinburgh, Edinburgh, U.K
| | | | - Lorraine M Work
- Institute of Cardiovascular and Medical Sciences, University of Glasgow, Glasgow, U.K
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