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Prynn J, Alinaitwe R, Kimono B, Peto T, Ashton NJ, Steves CJ, Mugisha J, Prince M. Prevalence, aetiology, and service mapping of dementia in rural Uganda. Part of DEPEND Uganda (Dementia Epidemiology, unmet Need and co-Developing Solutions in Uganda).. Wellcome Open Res 2025; 9:544. [PMID: 39429626 PMCID: PMC11490832 DOI: 10.12688/wellcomeopenres.22944.1] [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] [Accepted: 01/23/2025] [Indexed: 10/22/2024] Open
Abstract
Background Dementia prevalence in low- and middle-income countries is increasing, yet epidemiological data from African populations remain scarce. Crucial risk factors differ in Africa from more intensively studied global areas, including a higher burden of cerebrovascular disease and HIV, but lower rates of other risk factors like physical inactivity.Understanding dementia aetiology in African settings has been limited by the expensive and invasive nature of biomarker testing. This study leverages developments in blood-based and retinal imaging biomarker technology to examine the drivers of dementia in older Ugandans.People with dementia have complex needs benefiting from multi-dimensional support. Understanding current services will allow identification of barriers and opportunities to strengthen support available to people with dementia and their families. Methods The study is nested within the General Population Cohort run by the Medical Research Council/Uganda Virus Research Institute & London School of Hygiene and Tropical Medicine Research Unit. All adults aged 60+ (around 1400) are undergoing brief cognitive screening.In Part 1, cohort participants are selected based on screening scores to undergo detailed cognitive assessment, using methods developed by the 10/66 Dementia Research Group. Part 2 is a case control study of people with and without dementia using antecedent data, questionnaires, physical assessment, retinal imaging, and Alzheimer's blood-based biomarkers. We will also compare disability, frailty, quality of life, and social engagement in people with and without dementia.Part 3 assesses current formal support structures for people with dementia through review of publicly available literature and expert interviews. Conclusions This is the first study in Africa using blood-based and retinal imaging biomarkers to examine pathological processes underlying dementia, and systematically map services available for people with dementia. This paves the way for effective policy strategies and further focused research regarding both dementia prevention and support for affected people and their families.
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Affiliation(s)
- Josephine Prynn
- School of Life Course and Population Sciences, King's College London Faculty of Life Sciences & Medicine, London, England, UK
- MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Central Region, Uganda
| | - Racheal Alinaitwe
- MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Central Region, Uganda
- Makerere University School of Health Sciences, Kampala, Central Region, Uganda
| | - Beatrice Kimono
- MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Central Region, Uganda
| | - Tunde Peto
- School of Medicine, Dentistry, and Biomedical Sciences, Queen's University Belfast, Belfast, Northern Ireland, UK
| | - Nicholas J Ashton
- Department of Psychiatry and Neurochemistry, University of Gothenburg, Gothenburg, Sweden
- Banner Health, Phoenix, Arizona, USA
- King's College London Institute of Psychiatry Psychology & Neuroscience, London, England, UK
| | - Claire J Steves
- School of Life Course and Population Sciences, King's College London Faculty of Life Sciences & Medicine, London, England, UK
| | - Joseph Mugisha
- MRC/UVRI and LSHTM Uganda Research Unit, Entebbe, Central Region, Uganda
| | - Martin Prince
- School of Life Course and Population Sciences, King's College London Faculty of Life Sciences & Medicine, London, England, UK
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2
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Cantone M, Pennisi M, Lanza G, Ferri R, Fisicaro F, Cappellani F, David E, Nicosia V, Cortese K, Pennisi G, Puglisi V, Bella R. Transcranial Doppler sonography follow-up study in mild vascular cognitive impairment. PLoS One 2025; 20:e0317888. [PMID: 39854302 PMCID: PMC11761083 DOI: 10.1371/journal.pone.0317888] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2024] [Accepted: 01/07/2025] [Indexed: 01/26/2025] Open
Abstract
BACKGROUND To date, few data to transcranial Doppler sonography (TCD) are available in patients with mild vascular cognitive impairment (VCI) at risk for vascular or mixed dementia. In a previous study in patients with mild VCI and cerebral small vessels disease, a hemodynamic pattern of cerebral hypoperfusion and enhanced vascular resistance were observed; however, longitudinal data are currently lacking. Here, we perform a clinical, psychopathological, and neurosonological follow-up of patients with VCI in order to monitor any progression and to identify TCD measures to detect it. METHODS From the original cohort of 161 patients, 127 with VCI (mean age 73.6 ± 7.1; 67 males) were re-evaluated after 5.0 ± 1.8 years. Namely, the Montreal Cognitive Assessment (MoCA), the 17-items Hamilton Depression Rating Scale (HDRS), and the Stroop Color-Word Interference Test (StroopT) were administered to screen for global cognitive status, to quantify depressive symptoms, and to explore executive functions, respectively. Mean blood flow velocity (MBFV), peak systolic blood flow velocity (PSV), end-diastolic blood flow velocity (EDV), pulsatility index (PI), and resistivity index (RI) were recorded from the middle cerebral artery, bilaterally. RESULTS At follow up, patients exhibited a significant worsening of both MoCA (21.7 ± 2.1 vs. 20.7 ± 2.0) and StroopT scores (57.4 ± 19.4 vs. 59.7 ± 18.6), whereas HDRS showed an improvement, although the mean raw score remained above the cut-off value for depression (10.3 ± 6.6 vs. 9.8 ± 6.3). MBFV, PSV, and EDV showed a significant increase in PSV and PI and a reduction in EDV. When focused to younger patients (<65 years), we confirmed the significant worsening of both MoCA and StroopT but not HDRS, as well as the significant changes in PI and RI. Finally, considering the differences (D) between baseline and follow-up, the following significant correlations emerged, although with a small-to-medium effect size for all of them: positive correlation between MBFV-D and MoCA-D and between RI-D and STROOP-D, and a negative significant correlation between RI-D and MoCA-D. CONCLUSIONS Notwithstanding some limitations, such as the lack of a control group and neuroimaging data at follow-up, TCD may contribute to the early detection, monitoring, and management of VCI patients at risk for dementia. Together with compatible clinical and cognitive features, the exploration of early TCD markers that possibly indicate a higher risk of progression might represent an intriguing research direction and a significant clinical perspective.
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Affiliation(s)
- Mariagiovanna Cantone
- Neurology Unit, Policlinico University Hospital "G. Rodolico-San Marco", Catania, Italy
| | - Manuela Pennisi
- Department of Biomedical and Biotechnological Sciences, University of Catania, Catania, Italy
| | - Giuseppe Lanza
- Department of Surgery and Medical-Surgical Specialties, University of Catania, Catania, Italy
- Clinical Neurophysiology Research Unit, Oasi Research Institute-IRCCS, Troina, Italy
| | - Raffaele Ferri
- Clinical Neurophysiology Research Unit, Oasi Research Institute-IRCCS, Troina, Italy
| | - Francesco Fisicaro
- Department of Biomedical and Biotechnological Sciences, University of Catania, Catania, Italy
| | - Francesco Cappellani
- Ophthalmology Unit, Policlinico University Hospital "G. Rodolico-San Marco", Catania, Italy
| | - Emanuele David
- Department of Medical and Surgical Sciences and Advanced Technologies "G. F. Ingrassia", University of Catania, Catania, Italy
| | - Vito Nicosia
- Department of Medical and Surgical Sciences and Advanced Technologies "G. F. Ingrassia", University of Catania, Catania, Italy
| | - Klizia Cortese
- Department of Educational Sciences, University of Catania, Catania, Italy
| | - Giovanni Pennisi
- Department of Surgery and Medical-Surgical Specialties, University of Catania, Catania, Italy
| | - Valentina Puglisi
- Department of Neurology and Stroke Unit, ASST Cremona, Cremona, Italy
| | - Rita Bella
- Department of Medical and Surgical Sciences and Advanced Technologies "G. F. Ingrassia", University of Catania, Catania, Italy
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Zhao B, Li Y, Fan Z, Wu Z, Shu J, Yang X, Yang Y, Wang X, Li B, Wang X, Copana C, Yang Y, Lin J, Li Y, Stein JL, O'Brien JM, Li T, Zhu H. Eye-brain connections revealed by multimodal retinal and brain imaging genetics. Nat Commun 2024; 15:6064. [PMID: 39025851 PMCID: PMC11258354 DOI: 10.1038/s41467-024-50309-w] [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: 06/23/2023] [Accepted: 07/02/2024] [Indexed: 07/20/2024] Open
Abstract
The retina, an anatomical extension of the brain, forms physiological connections with the visual cortex of the brain. Although retinal structures offer a unique opportunity to assess brain disorders, their relationship to brain structure and function is not well understood. In this study, we conducted a systematic cross-organ genetic architecture analysis of eye-brain connections using retinal and brain imaging endophenotypes. We identified novel phenotypic and genetic links between retinal imaging biomarkers and brain structure and function measures from multimodal magnetic resonance imaging (MRI), with many associations involving the primary visual cortex and visual pathways. Retinal imaging biomarkers shared genetic influences with brain diseases and complex traits in 65 genomic regions, with 18 showing genetic overlap with brain MRI traits. Mendelian randomization suggests bidirectional genetic causal links between retinal structures and neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, our findings reveal the genetic basis for eye-brain connections, suggesting that retinal images can help uncover genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.
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Affiliation(s)
- Bingxin Zhao
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA.
- Applied Mathematics and Computational Science Graduate Group, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Center for AI and Data Science for Integrated Diagnostics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Penn Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Population Aging Research Center, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
| | - Yujue Li
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Zirui Fan
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Zhenyi Wu
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Juan Shu
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Xiaochen Yang
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Yilin Yang
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Xifeng Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Bingxuan Li
- Department of Computer Science, Purdue University, West Lafayette, IN, 47907, USA
| | - Xiyao Wang
- Department of Computer Science, Purdue University, West Lafayette, IN, 47907, USA
| | - Carlos Copana
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Yue Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Jinjie Lin
- Yale School of Management, Yale University, New Haven, CT, 06511, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Jason L Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Joan M O'Brien
- Scheie Eye Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Penn Medicine Center for Ophthalmic Genetics in Complex Diseases, Philadelphia, PA, 19104, USA
| | - Tengfei Li
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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Wang R, Wu X, Zhang Z, Cao L, Kwapong WR, Wang H, Tao W, Ye C, Liu J, Wu B. Retinal ganglion cell-inner plexiform layer, white matter hyperintensities, and their interaction with cognition in older adults. Front Aging Neurosci 2023; 15:1240815. [PMID: 38035269 PMCID: PMC10685347 DOI: 10.3389/fnagi.2023.1240815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 10/11/2023] [Indexed: 12/02/2023] Open
Abstract
Purpose We explored the interaction of optical coherence tomography (OCT) parameters and white matter hyperintensities with cognitive measures in our older adult cohort. Methods This observational study enrolled participants who underwent a comprehensive neuropsychological battery, structural 3-T brain magnetic resonance imaging (MRI), visual acuity examination, and OCT imaging. Cerebral small vessel disease (CSVD) markers were read on MR images; lacune, cerebral microbleeds (CMB), white matter hyperintensities (WMH), and enlarged perivascular spaces (EPVS), were defined according to the STRIVE standards. Retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (GCIPL) thicknesses (μm) were measured on the OCT tool. Results Older adults with cognitive impairment (CI) showed lower RNFL (p = 0.001), GCIPL (p = 0.009) thicknesses, and lower hippocampal volume (p = 0.004) when compared to non-cognitively impaired (NCI). RNFL (p = 0.006) and GCIPL thicknesses (p = 0.032) correlated with MoCA scores. GCIPL thickness (p = 0.037), total WMH (p = 0.003), PWMH (p = 0.041), and DWMH (p = 0.001) correlated with hippocampal volume in our older adults after adjusting for covariates. With hippocampal volume as the outcome, a significant interaction (p < 0.05) between GCIPL and PWMH and total WMH was observed in our older adults. Conclusion Both GCIPL thinning and higher WMH burden (especially PWMH) are associated with hippocampal volume and older adults with both pathologies are more susceptible to subclinical cognitive decline.
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Affiliation(s)
- Ruilin Wang
- Ophthalmology Department, West China Hospital, Sichuan University, Chengdu, China
| | - Xinmao Wu
- Neurology Department, West China Hospital, Sichuan University, Chengdu, China
| | - Zengyi Zhang
- Neurology Department, West China Hospital, Sichuan University, Chengdu, China
| | - Le Cao
- Ophthalmology Department, West China Hospital, Sichuan University, Chengdu, China
| | | | - Hang Wang
- Neurology Department, West China Hospital, Sichuan University, Chengdu, China
| | - Wendan Tao
- Neurology Department, West China Hospital, Sichuan University, Chengdu, China
| | - Chen Ye
- Neurology Department, West China Hospital, Sichuan University, Chengdu, China
| | - Junfeng Liu
- Neurology Department, West China Hospital, Sichuan University, Chengdu, China
| | - Bo Wu
- Neurology Department, West China Hospital, Sichuan University, Chengdu, China
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5
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Tomasoni M, Beyeler MJ, Vela SO, Mounier N, Porcu E, Corre T, Krefl D, Button AL, Abouzeid H, Lazaros K, Bochud M, Schlingemann R, Bergin C, Bergmann S. Genome-wide Association Studies of Retinal Vessel Tortuosity Identify Numerous Novel Loci Revealing Genes and Pathways Associated With Ocular and Cardiometabolic Diseases. OPHTHALMOLOGY SCIENCE 2023; 3:100288. [PMID: 37131961 PMCID: PMC10149284 DOI: 10.1016/j.xops.2023.100288] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 02/03/2023] [Accepted: 02/09/2023] [Indexed: 02/18/2023]
Abstract
Purpose To identify novel susceptibility loci for retinal vascular tortuosity, to better understand the molecular mechanisms modulating this trait, and reveal causal relationships with diseases and their risk factors. Design Genome-wide Association Studies (GWAS) of vascular tortuosity of retinal arteries and veins followed by replication meta-analysis and Mendelian randomization (MR). Participants We analyzed 116 639 fundus images of suitable quality from 63 662 participants from 3 cohorts, namely the UK Biobank (n = 62 751), the Swiss Kidney Project on Genes in Hypertension (n = 397), and OphtalmoLaus (n = 512). Methods Using a fully automated retina image processing pipeline to annotate vessels and a deep learning algorithm to determine the vessel type, we computed the median arterial, venous and combined vessel tortuosity measured by the distance factor (the length of a vessel segment over its chord length), as well as by 6 alternative measures that integrate over vessel curvature. We then performed the largest GWAS of these traits to date and assessed gene set enrichment using the novel high-precision statistical method PascalX. Main Outcome Measure We evaluated the genetic association of retinal tortuosity, measured by the distance factor. Results Higher retinal tortuosity was significantly associated with higher incidence of angina, myocardial infarction, stroke, deep vein thrombosis, and hypertension. We identified 175 significantly associated genetic loci in the UK Biobank; 173 of these were novel and 4 replicated in our second, much smaller, metacohort. We estimated heritability at ∼25% using linkage disequilibrium score regression. Vessel type specific GWAS revealed 116 loci for arteries and 63 for veins. Genes with significant association signals included COL4A2, ACTN4, LGALS4, LGALS7, LGALS7B, TNS1, MAP4K1, EIF3K, CAPN12, ECH1, and SYNPO2. These tortuosity genes were overexpressed in arteries and heart muscle and linked to pathways related to the structural properties of the vasculature. We demonstrated that retinal tortuosity loci served pleiotropic functions as cardiometabolic disease variants and risk factors. Concordantly, MR revealed causal effects between tortuosity, body mass index, and low-density lipoprotein. Conclusions Several alleles associated with retinal vessel tortuosity suggest a common genetic architecture of this trait with ocular diseases (glaucoma, myopia), cardiovascular diseases, and metabolic syndrome. Our results shed new light on the genetics of vascular diseases and their pathomechanisms and highlight how GWASs and heritability can be used to improve phenotype extraction from high-dimensional data, such as images. Financial Disclosures The author(s) have no proprietary or commercial interest in any materials discussed in this article.
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Affiliation(s)
- Mattia Tomasoni
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Jules-Gonin Eye Hospital, Lausanne, Switzerland
| | - Michael Johannes Beyeler
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Sofia Ortin Vela
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Ninon Mounier
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Eleonora Porcu
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
- Center for Integrative Genomics, University of Lausanne, Lausanne, Switzerland
| | - Tanguy Corre
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Daniel Krefl
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Alexander Luke Button
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Hana Abouzeid
- Division of Ophthalmology, Geneva University Hospitals, Geneva, Switzerland
- Clinical Eye Research Center Memorial Adolphe de Rothschild, Geneva, Switzerland
| | | | - Murielle Bochud
- Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland
| | - Reinier Schlingemann
- Jules-Gonin Eye Hospital, Lausanne, Switzerland
- Department of Ophthalmology, Amsterdam University Medical Centres, Amsterdam, The Netherlands
| | | | - Sven Bergmann
- Department of Computational Biology, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
- Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
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6
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Owens CD, Bonin Pinto C, Mukli P, Szarvas Z, Peterfi A, Detwiler S, Olay L, Olson AL, Li G, Galvan V, Kirkpatrick AC, Balasubramanian P, Tarantini S, Csiszar A, Ungvari Z, Prodan CI, Yabluchanskiy A. Vascular mechanisms leading to progression of mild cognitive impairment to dementia after COVID-19: Protocol and methodology of a prospective longitudinal observational study. PLoS One 2023; 18:e0289508. [PMID: 37535668 PMCID: PMC10399897 DOI: 10.1371/journal.pone.0289508] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2023] [Accepted: 07/19/2023] [Indexed: 08/05/2023] Open
Abstract
INTRODUCTION Mild cognitive impairment (MCI) is a prodromal stage to dementia, affecting up to 20% of the aging population worldwide. Patients with MCI have an annual conversion rate to dementia of 15-20%. Thus, conditions that increase the conversion from MCI to dementia are of the utmost public health concern. The COVID-19 pandemic poses a significant impact on our aging population with cognitive decline as one of the leading complications following recovery from acute infection. Recent findings suggest that COVID-19 increases the conversion rate from MCI to dementia in older adults. Hence, we aim to uncover a mechanism for COVID-19 induced cognitive impairment and progression to dementia to pave the way for future therapeutic targets that may mitigate COVID-19 induced cognitive decline. METHODOLOGY A prospective longitudinal study is conducted at the University of Oklahoma Health Sciences Center. Patients are screened in the Department of Neurology and must have a formal diagnosis of MCI, and MRI imaging prior to study enrollment. Patients who meet the inclusion criteria are enrolled and followed-up at 18-months after their first visit. Visit one and 18-month follow-up will include an integrated and cohesive battery of vascular and cognitive measurements, including peripheral endothelial function (flow-mediated dilation, laser speckle contrast imaging), retinal and cerebrovascular hemodynamics (dynamic vessel retinal analysis, functional near-infrared spectroscopy), and fluid and crystalized intelligence (NIH-Toolbox, n-back). Multiple logistic regression will be used for primary longitudinal data analysis to determine whether COVID-19 related impairment in neurovascular coupling and increases in white matter hyperintensity burden contribute to progression to dementia.
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Affiliation(s)
- Cameron D. Owens
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Neurosurgery, Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
| | - Camila Bonin Pinto
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Neurosurgery, Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
| | - Peter Mukli
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Neurosurgery, Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Doctoral School of Basic and Translational Medicine/Departments of Public Health, International Training Program in Geroscience, Translational Medicine and Physiology, Semmelweis University, Budapest, Hungary
| | - Zsofia Szarvas
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Neurosurgery, Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Doctoral School of Basic and Translational Medicine/Departments of Public Health, International Training Program in Geroscience, Translational Medicine and Physiology, Semmelweis University, Budapest, Hungary
| | - Anna Peterfi
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Neurosurgery, Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Doctoral School of Basic and Translational Medicine/Departments of Public Health, International Training Program in Geroscience, Translational Medicine and Physiology, Semmelweis University, Budapest, Hungary
| | - Sam Detwiler
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Neurosurgery, Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
| | - Lauren Olay
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Neurosurgery, Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
| | - Ann L. Olson
- Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
| | - Guangpu Li
- Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
| | - Veronica Galvan
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Biochemistry and Molecular Biology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Veterans Affairs Medical Center, Oklahoma City, OK, United States of America
| | - Angelia C. Kirkpatrick
- Veterans Affairs Medical Center, Oklahoma City, OK, United States of America
- Department of Medicine, Cardiovascular Section, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
| | - Priya Balasubramanian
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Neurosurgery, Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Medicine, Cardiovascular Section, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
| | - Stefano Tarantini
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Neurosurgery, Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Doctoral School of Basic and Translational Medicine/Departments of Public Health, International Training Program in Geroscience, Translational Medicine and Physiology, Semmelweis University, Budapest, Hungary
- The Peggy and Charles Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
| | - Anna Csiszar
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Neurosurgery, Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Doctoral School of Basic and Translational Medicine/Departments of Public Health, International Training Program in Geroscience, Translational Medicine and Physiology, Semmelweis University, Budapest, Hungary
| | - Zoltan Ungvari
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Neurosurgery, Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Doctoral School of Basic and Translational Medicine/Departments of Public Health, International Training Program in Geroscience, Translational Medicine and Physiology, Semmelweis University, Budapest, Hungary
- Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
| | - Calin I. Prodan
- Veterans Affairs Medical Center, Oklahoma City, OK, United States of America
- Department of Neurology, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
| | - Andriy Yabluchanskiy
- Oklahoma Center for Geroscience and Healthy Brain Aging, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Neurosurgery, Vascular Cognitive Impairment, Neurodegeneration and Healthy Brain Aging Program, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- The Peggy and Charles Stephenson Cancer Center, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
- Department of Health Promotion Sciences, College of Public Health, University of Oklahoma Health Sciences Center, Oklahoma City, OK, United States of America
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7
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Zhao B, Li Y, Fan Z, Wu Z, Shu J, Yang X, Yang Y, Wang X, Li B, Wang X, Copana C, Yang Y, Lin J, Li Y, Stein JL, O'Brien JM, Li T, Zhu H. Eye-brain connections revealed by multimodal retinal and brain imaging genetics in the UK Biobank. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.16.23286035. [PMID: 36824893 PMCID: PMC9949187 DOI: 10.1101/2023.02.16.23286035] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
As an anatomical extension of the brain, the retina of the eye is synaptically connected to the visual cortex, establishing physiological connections between the eye and the brain. Despite the unique opportunity retinal structures offer for assessing brain disorders, less is known about their relationship to brain structure and function. Here we present a systematic cross-organ genetic architecture analysis of eye-brain connections using retina and brain imaging endophenotypes. Novel phenotypic and genetic links were identified between retinal imaging biomarkers and brain structure and function measures derived from multimodal magnetic resonance imaging (MRI), many of which were involved in the visual pathways, including the primary visual cortex. In 65 genomic regions, retinal imaging biomarkers shared genetic influences with brain diseases and complex traits, 18 showing more genetic overlaps with brain MRI traits. Mendelian randomization suggests that retinal structures have bidirectional genetic causal links with neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, cross-organ imaging genetics reveals a genetic basis for eye-brain connections, suggesting that the retinal images can elucidate genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.
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Affiliation(s)
- Bingxin Zhao
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Yujue Li
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Zirui Fan
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Zhenyi Wu
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Juan Shu
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Xiaochen Yang
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Yilin Yang
- Department of Computer and Information Science and Electrical and Systems Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Xifeng Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Bingxuan Li
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
| | - Xiyao Wang
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
| | - Carlos Copana
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Yue Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jinjie Lin
- Yale School of Management, Yale University, New Haven, CT 06511, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jason L. Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Joan M. O'Brien
- Scheie Eye Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Penn Medicine Center for Ophthalmic Genetics in Complex Diseases, PA, 19104, USA
| | - Tengfei Li
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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8
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Abdelhak A, Solomon I, Montes SC, Saias A, Cordano C, Asken B, Fonseca C, Oertel FC, Arfanakis K, Staffaroni AM, Kramer JH, Geschwind M, Miller BL, Elahi FM, Green AJ. Retinal arteriolar parameters as a surrogate marker of intracranial vascular pathology. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2022; 14:e12338. [PMID: 35814617 PMCID: PMC9257197 DOI: 10.1002/dad2.12338] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Revised: 05/15/2022] [Accepted: 05/17/2022] [Indexed: 11/10/2022]
Abstract
Introduction Development of novel diagnostic tools is a top research priority in vascular dementia. A major obstacle is the lack of a simple, non-invasive method to visualize cerebral arteriolar walls in vivo. Retinal arterioles offer a window into the cerebral circulation. Methods Intensity-based retinal arteriolar visualization in optical coherence tomography (I-bRAVO) was applied to evaluate mean wall thickness (MWT) and wall-to-lumen ratio (WLR) in 250 subjects with sporadic and genetic cerebral small vessel disease (CSVD), non-vascular neurodegenerative diseases (NVND), and healthy controls (HC) in association with imaging and cognitive markers. Results MWT and WLR were higher in CSVD, associated with severity of vascular white matter lesions, and correlated with magnetic resonance imaging-based intracranial arteriolosclerosis score. WLR correlated with gray and white matter volume and differentiated asymptomatic sporadic CSVD from HC (area under the curve = 0.82). Discussion I-bRAVO is a rapid, non-invasive tool. MWT and WLR were associated with imaging markers of CSVD and could contribute to early identification of sporadic CSVD.
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Affiliation(s)
- Ahmed Abdelhak
- Weill Institute for NeurosciencesDepartment of NeurologyUniversity of California at San Francisco (UCSF)San FranciscoCaliforniaUSA
| | - Isaac Solomon
- San Diego School of MedicineUniversity of California, San DiegoLa JollaCaliforniaUSA
| | - Shivany Condor Montes
- Weill Institute for NeurosciencesDepartment of NeurologyUniversity of California at San Francisco (UCSF)San FranciscoCaliforniaUSA
| | - Alexandra Saias
- Weill Institute for NeurosciencesDepartment of NeurologyUniversity of California at San Francisco (UCSF)San FranciscoCaliforniaUSA
| | - Christian Cordano
- Weill Institute for NeurosciencesDepartment of NeurologyUniversity of California at San Francisco (UCSF)San FranciscoCaliforniaUSA
| | - Breton Asken
- Weill Institute for NeurosciencesDepartment of NeurologyUniversity of California at San Francisco (UCSF)San FranciscoCaliforniaUSA
| | - Corrina Fonseca
- Weill Institute for NeurosciencesDepartment of NeurologyUniversity of California at San Francisco (UCSF)San FranciscoCaliforniaUSA
| | - Frederike Cosima Oertel
- Weill Institute for NeurosciencesDepartment of NeurologyUniversity of California at San Francisco (UCSF)San FranciscoCaliforniaUSA
| | - Konstantinos Arfanakis
- Department of Biomedical EngineeringIllinois Institute of TechnologyChicagoIllinoisUSA
- Rush Alzheimer's Disease CenterRush University Medical CenterChicagoIllinoisUSA
| | - Adam M. Staffaroni
- Weill Institute for NeurosciencesDepartment of NeurologyUniversity of California at San Francisco (UCSF)San FranciscoCaliforniaUSA
| | - Joel H. Kramer
- Weill Institute for NeurosciencesDepartment of NeurologyUniversity of California at San Francisco (UCSF)San FranciscoCaliforniaUSA
| | - Michael Geschwind
- Weill Institute for NeurosciencesDepartment of NeurologyUniversity of California at San Francisco (UCSF)San FranciscoCaliforniaUSA
| | - Bruce L. Miller
- Weill Institute for NeurosciencesDepartment of NeurologyUniversity of California at San Francisco (UCSF)San FranciscoCaliforniaUSA
| | - Fanny M. Elahi
- Weill Institute for NeurosciencesDepartment of NeurologyUniversity of California at San Francisco (UCSF)San FranciscoCaliforniaUSA
- San Francisco Veterans Affairs Health Care System
| | - Ari J. Green
- Weill Institute for NeurosciencesDepartment of NeurologyUniversity of California at San Francisco (UCSF)San FranciscoCaliforniaUSA
- Department of OphthalmologyUniversity of California at San Francisco (UCSF)San FranciscoCaliforniaUSA
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9
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Czepita M, Fabijańska A. Image processing pipeline for the detection of blood flow through retinal vessels with subpixel accuracy in fundus images. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 208:106240. [PMID: 34198018 DOI: 10.1016/j.cmpb.2021.106240] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/06/2021] [Accepted: 06/14/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND AND OBJECTIVE Blood flow detection through the retinal vessels is an essential step in diagnosing several eye diseases. It manifests itself as changes in vessel diameter in consecutive phases of blood flow. Previous studies focused mainly on determining retinal vessel diameter by the manual demarcation of vessel edges, which is time-consuming. As a result, only a few selected vessels were considered, which is not reliable. Such measurements are also prone to human errors and operator subjectivity, which additionally decreases their reliability. For these reasons, this paper proposes an automated pipeline to analyze the blood flow through retinal vessels. METHODS Convolutional neural networks were used for optic disc and vessel detection and full width at half maximum analysis used for vessel width assessment at the subpixel level. Measurements of the diameter were performed for five phases of the blood flow to all vessels at a particular distance derived from the optic disc size. We tested the approach on fundus images of five patients, with both eyes examined in each participant. The threshold for the detections of blood flow was when the retinal diameter vessel measurements were above the camera's resolution as compared among all 5 phases of blood flow. RESULTS A total of 205 large caliber blood vessels were analyzed with blood flow detected in 18 retinal blood vessels. Conclusions Average vessel diameters derived from manual and automatic measurements differed on average by 4.96%. Average relative errors for single vessel measurements along the vessels range from 4.21 to 11.85%, with a global average at the level of 8%. Therefore, the measurements can be considered as accurate and in a high agreement between the expert and algorithm.
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Affiliation(s)
- Maciej Czepita
- Private Eye Practice, Starkiewicza Str. 5/2, Szczecin 70-112, Poland.
| | - Anna Fabijańska
- Lodz University of Technology, Institute of Applied Computer Science, Stefanowskiego Str. 18/22, Lodz 90-924, Poland.
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10
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Wang H, Hu H, Gregori G, Zhang J, Jiang H, Wang J. The Effect of Software Versions on the Measurement of Retinal Vascular Densities Using Optical Coherence Tomography Angiography. Curr Eye Res 2020; 46:341-349. [PMID: 32767906 DOI: 10.1080/02713683.2020.1801756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
Abstract
BACKGROUND The goal of the study was to determine the effect of different software versions on the measurement of retinal vessel densities using optical coherence tomography angiography (OCTA) in normal subjects. METHODS Thirty-two eyes of eighteen healthy subjects were imaged using two OCTA devices: the Optovue RTVue and the Zeiss Cirrus. The macular 3 × 3 mm scan protocol was used. The images acquired using the Optovue OCTA device were exported using two different software versions in the system and compared to the images acquired through the Zeiss OCTA. In addition, the Optovue OCTA images were exported after manual adjustment of the segmentation boundaries according to the intraretinal layer definition. The densities of the superficial vascular plexus (SVP) and deep vascular plexus (DVP) were measured using fractal analysis by box-counting (Dbox). RESULTS Both the vessel densities of the SVP and DVP acquired using the Optovue OCTA device were significantly different when compared to those from the Zeiss OCTA device (all, P <.05). No significant difference was found between the vessel densities of the SVP exported using both the new and old versions of Optovue (P >.05). However, the DVP exported using the new Optovue software version was significantly different compared to those exported using the old version (P <.05). The vessel densities of the SVP and DVP were related among the Optovue OCTA software versions and manual adjustment method (r ranged from 0.55 to 0.77; all P <.05). CONCLUSION This is the first study to determine that different software versions with various intraretinal layer segmentation methods affect the vessel density measurements of the SVP and DVP.
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Affiliation(s)
- Huijuan Wang
- Department of Ophthalmology, Eye Hospital, China Academy of Chinese Medical Sciences , Beijing, China.,Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine , Miami, FL, USA
| | - Huiling Hu
- Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine , Miami, FL, USA.,Department of Ophthalmology, Shenzhen Key Laboratory of Ophthalmology, Shenzhen Eye Hospital, Jinan University , Shenzhen, China
| | - Giovanni Gregori
- Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine , Miami, FL, USA
| | - Juan Zhang
- Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine , Miami, FL, USA.,Department of Biomedical Engineering, School of Ophthalmology & Optometry, School of Biomedical Engineering, Wenzhou Medical University , Wenzhou, China
| | - Hong Jiang
- Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine , Miami, FL, USA
| | - Jianhua Wang
- Department of Ophthalmology, Bascom Palmer Eye Institute, University of Miami Miller School of Medicine , Miami, FL, USA
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11
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Zlokovic BV, Gottesman RF, Bernstein KE, Seshadri S, McKee A, Snyder H, Greenberg SM, Yaffe K, Schaffer CB, Yuan C, Hughes TM, Daemen MJ, Williamson JD, González HM, Schneider J, Wellington CL, Katusic ZS, Stoeckel L, Koenig JI, Corriveau RA, Fine L, Galis ZS, Reis J, Wright JD, Chen J. Vascular contributions to cognitive impairment and dementia (VCID): A report from the 2018 National Heart, Lung, and Blood Institute and National Institute of Neurological Disorders and Stroke Workshop. Alzheimers Dement 2020; 16:1714-1733. [PMID: 33030307 DOI: 10.1002/alz.12157] [Citation(s) in RCA: 138] [Impact Index Per Article: 27.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Revised: 06/30/2020] [Accepted: 06/30/2020] [Indexed: 12/14/2022]
Abstract
Vascular contributions to cognitive impairment and dementia (VCID) are characterized by the aging neurovascular unit being confronted with and failing to cope with biological insults due to systemic and cerebral vascular disease, proteinopathy including Alzheimer's biology, metabolic disease, or immune response, resulting in cognitive decline. This report summarizes the discussion and recommendations from a working group convened by the National Heart, Lung, and Blood Institute and the National Institute of Neurological Disorders and Stroke to evaluate the state of the field in VCID research, identify research priorities, and foster collaborations. As discussed in this report, advances in understanding the biological mechanisms of VCID across the wide spectrum of pathologies, chronic systemic comorbidities, and other risk factors may lead to potential prevention and new treatment strategies to decrease the burden of dementia. Better understanding of the social determinants of health that affect risks for both vascular disease and VCID could provide insight into strategies to reduce racial and ethnic disparities in VCID.
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Affiliation(s)
| | | | | | - Sudha Seshadri
- University of Texas Health Science Center, San Antonio and Boston University, San Antonio, Texas, USA
| | - Ann McKee
- VA Boston Healthcare System and Boston University, Boston, Massachusetts, USA
| | | | - Steven M Greenberg
- Massachusetts General Hospital and Harvard Medical School, Boston, Massachusetts, USA
| | - Kristine Yaffe
- University of California, San Francisco, San Francisco, California, USA
| | | | - Chun Yuan
- University of Washington, Seattle, Washington, USA
| | - Timothy M Hughes
- Wake Forest School of Medicine, Winston-Salem, North Carolina, USA
| | - Mat J Daemen
- Amsterdam UMC, University of Amsterdam, Amsterdam, the Netherlands
| | | | | | | | | | | | - Luke Stoeckel
- National Institute on Aging, Bethesda, Maryland, USA
| | - James I Koenig
- National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA
| | - Roderick A Corriveau
- National Institute of Neurological Disorders and Stroke, Bethesda, Maryland, USA
| | - Lawrence Fine
- National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA
| | - Zorina S Galis
- National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA
| | - Jared Reis
- National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA
| | | | - Jue Chen
- National Heart, Lung, and Blood Institute, Bethesda, Maryland, USA
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12
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Dumitrascu OM, Lyden PD, Torbati T, Sheyn J, Sherzai A, Sherzai D, Sherman DS, Rosenberry R, Cheng S, Johnson KO, Czeszynski AD, Verdooner S, Frautschy S, Black KL, Koronyo Y, Koronyo‐Hamaoui M. Sectoral segmentation of retinal amyloid imaging in subjects with cognitive decline. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2020; 12:e12109. [PMID: 33015311 PMCID: PMC7521595 DOI: 10.1002/dad2.12109] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 08/21/2020] [Accepted: 08/26/2020] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Despite advances in imaging retinal amyloidosis, a quantitative and topographical investigation of retinal amyloid beta burden in patients with cognitive decline has never been reported. METHODS We used the specific amyloid-binding fluorophore curcumin and laser ophthalmoscopy to assess retinal amyloid imaging (RAI) in 34 patients with cognitive decline. We automatically quantified retinal amyloid count (RAC) and area in the superotemporal retinal sub-regions and performed correlation analyses with cognitive and brain volumetric parameters. RESULTS RAC significantly and inversely correlated with hippocampal volume (HV; r = -0.39, P = .04). The proximal mid-periphery (PMP) RAC and RA areas were significantly greater in patients with Montreal Cognitive Assessment (MOCA) score < 26 (P = .01; Cohen d = 0.83 and 0.81, respectively). PMP showed significantly more RAC and area in subjects with amnestic mild cognitive impairment (MCI) and Alzheimer's disease (AD) compared to cognitively normal (P = .04; Cohen d = 0.83). CONCLUSION Quantitative RAI is a feasible technique and PMP RAC may predict HV. Future larger studies should determine RAI's potential as a biomarker of early AD.
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Affiliation(s)
- Oana M. Dumitrascu
- Department of NeurologyCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | - Patrick D. Lyden
- Department of NeurologyCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | - Tania Torbati
- Department of NeurosurgeryCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | - Julia Sheyn
- Department of NeurosurgeryCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | - Ayesha Sherzai
- Department of NeurologyLoma Linda UniversityLoma LindaCaliforniaUSA
| | - Dean Sherzai
- Department of NeurologyLoma Linda UniversityLoma LindaCaliforniaUSA
| | - Dale S. Sherman
- Department of NeuropsychologyCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | - Ryan Rosenberry
- Department of CardiologyCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | - Susan Cheng
- Department of CardiologyCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | | | | | | | - Sally Frautschy
- Department of NeurologyUniversity of California Los AngelesLos AngelesCaliforniaUSA
| | - Keith L. Black
- Department of NeurosurgeryCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | - Yosef Koronyo
- Department of NeurosurgeryCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
| | - Maya Koronyo‐Hamaoui
- Department of NeurosurgeryCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
- Biomedical SciencesCedars‐Sinai Medical CenterLos AngelesCaliforniaUSA
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13
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McGrory S, Ballerini L, Okely JA, Ritchie SJ, Doubal FN, Doney ASF, Dhillon B, Starr JM, MacGillivray TJ, Trucco E, Wardlaw JM, Deary IJ. Retinal microvascular features and cognitive change in the Lothian-Birth Cohort 1936. ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2019; 11:500-509. [PMID: 31338413 PMCID: PMC6625967 DOI: 10.1016/j.dadm.2019.04.012] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Introduction We test whether measures of the retinal vasculature are associated with cognitive functioning and cognitive change. Methods Retinal images from a narrow-age cohort were analyzed using Vessel Assessment and Measurement Platform for Images of the Retina, producing a comprehensive range of quantitative measurements of the retinal vasculature, at mean age 72.5 years (SD = 0.7). Cognitive ability and change were measured using a battery of multiple measures of memory, visuospatial, processing speed, and crystallized cognitive abilities at mean ages 73, 76, and 79 years. We applied multivariate growth curve models to test the association between retinal vascular measurements with cognitive abilities and their changes. Results Almost all associations were nonsignificant. In our most parsimonious model, venular asymmetry factor was associated with speed at age 73. Discussion Our null findings suggest that the quantitative retinal parameters applied in this study are not significantly associated with cognitive functioning or cognitive change.
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Affiliation(s)
- Sarah McGrory
- VAMPIRE project, Center for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK.,Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Lucia Ballerini
- VAMPIRE project, Center for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
| | - Judith A Okely
- Department of Psychology, University of Edinburgh, Edinburgh, UK.,Center for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Stuart J Ritchie
- Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
| | - Fergus N Doubal
- VAMPIRE project, Center for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
| | - Alex S F Doney
- Division of Cardiovascular and Diabetes Medicine, Medical Research Institute, Ninewells Hospital and Medical School, Dundee, UK
| | - Baljean Dhillon
- VAMPIRE project, Center for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
| | - John M Starr
- Center for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK.,Alzheimer Scotland Dementia Research Centre, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Thomas J MacGillivray
- VAMPIRE project, Center for Clinical Brain Sciences, Edinburgh Medical School, University of Edinburgh, Edinburgh, UK
| | - Emanuele Trucco
- VAMPIRE Project, Computing, School of Science and Engineering, University of Dundee, Dundee, UK
| | - Joanna M Wardlaw
- Center for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK.,Scottish Imaging Network, A Platform for Scientific Excellence (SINAPSE) Collaboration, Edinburgh, UK.,UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
| | - Ian J Deary
- Department of Psychology, University of Edinburgh, Edinburgh, UK.,Center for Cognitive Ageing and Cognitive Epidemiology, Department of Psychology, University of Edinburgh, Edinburgh, UK
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