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Ong SS, Peavey JJ, Hiatt KD, Whitlow CT, Sappington RM, Thompson AC, Lockhart SN, Chen H, Craft S, Rapp SR, Fitzpatrick AL, Heckbert SR, Luchsinger JA, Klein BEK, Meuer SM, Cotch MF, Wong TY, Hughes TM. Association of fractal dimension and other retinal vascular network parameters with cognitive performance and neuroimaging biomarkers: The Multi-Ethnic Study of Atherosclerosis (MESA). Alzheimers Dement 2024; 20:941-953. [PMID: 37828734 PMCID: PMC10916935 DOI: 10.1002/alz.13498] [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: 03/24/2023] [Revised: 08/16/2023] [Accepted: 09/09/2023] [Indexed: 10/14/2023]
Abstract
INTRODUCTION Retinal vascular network changes may reflect the integrity of the cerebral microcirculation, and may be associated with cognitive impairment. METHODS Associations of retinal vascular measures with cognitive function and MRI biomarkers were examined amongst Multi-Ethnic Study of Atherosclerosis (MESA) participants in North Carolina who had gradable retinal photographs at Exams 2 (2002 to 2004, n = 313) and 5 (2010 to 2012, n = 306), and detailed cognitive testing and MRI at Exam 6 (2016 to 2018). RESULTS After adjustment for covariates and multiple comparisons, greater arteriolar fractal dimension (FD) at Exam 2 was associated with less isotropic free water of gray matter regions (β = -0.0005, SE = 0.0024, p = 0.01) at Exam 6, while greater arteriolar FD at Exam 5 was associated with greater gray matter cortical volume (in mm3 , β = 5458, SE = 20.17, p = 0.04) at Exam 6. CONCLUSION Greater arteriolar FD, reflecting greater complexity of the branching pattern of the retinal arteries, is associated with MRI biomarkers indicative of less neuroinflammation and neurodegeneration.
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Affiliation(s)
- Sally S. Ong
- Department of OphthalmologyWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Jeremy J. Peavey
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Kevin D. Hiatt
- Department of RadiologyWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Christopher T. Whitlow
- Department of RadiologyWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Rebecca M. Sappington
- Department of OphthalmologyWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
- Department of BiochemistryWake Forest School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Atalie C. Thompson
- Department of OphthalmologyWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Samuel N. Lockhart
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Haiying Chen
- Department of Psychiatry and Behavioral MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Suzanne Craft
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Stephen R. Rapp
- Biostatistics and Data ScienceWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
| | - Annette L. Fitzpatrick
- Department of EpidemiologySchool of Public HealthUniversity of WashingtonSeattleWashingtonUSA
| | - Susan R. Heckbert
- Department of EpidemiologySchool of Public HealthUniversity of WashingtonSeattleWashingtonUSA
| | - José A. Luchsinger
- Departments of Medicine and EpidemiologyColumbia University Irving Medical CenterNew YorkNew YorkUSA
| | - Barbara E. K. Klein
- Department of Ophthalmology and Visual SciencesUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | - Stacy M Meuer
- Department of Ophthalmology and Visual SciencesUniversity of Wisconsin‐MadisonMadisonWisconsinUSA
| | | | - Tien Y. Wong
- Singapore Eye Research InstituteSingapore National Eye CenterOphthalmology and Visual Sciences Academic Clinical ProgramDuke‐NUS Medical SchoolSingapore
- Tsinghua MedicineTsinghua UniversityBeijingChina
| | - Timothy M. Hughes
- Department of Internal MedicineWake Forest University School of MedicineWinston‐SalemNorth CarolinaUSA
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Chaitanuwong P, Singhanetr P, Chainakul M, Arjkongharn N, Ruamviboonsuk P, Grzybowski A. Potential Ocular Biomarkers for Early Detection of Alzheimer's Disease and Their Roles in Artificial Intelligence Studies. Neurol Ther 2023; 12:1517-1532. [PMID: 37468682 PMCID: PMC10444735 DOI: 10.1007/s40120-023-00526-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Accepted: 07/03/2023] [Indexed: 07/21/2023] Open
Abstract
Alzheimer's disease (AD) is the leading cause of dementia worldwide. Early detection is believed to be essential to disease management because it enables physicians to initiate treatment in patients with early-stage AD (early AD), with the possibility of stopping the disease or slowing disease progression, preserving function and ultimately reducing disease burden. The purpose of this study was to review prior research on the use of eye biomarkers and artificial intelligence (AI) for detecting AD and early AD. The PubMed database was searched to identify studies for review. Ocular biomarkers in AD research and AI research on AD were reviewed and summarized. According to numerous studies, there is a high likelihood that ocular biomarkers can be used to detect early AD: tears, corneal nerves, retina, visual function and, in particular, eye movement tracking have been identified as ocular biomarkers with the potential to detect early AD. However, there is currently no ocular biomarker that can be used to definitely detect early AD. A few studies that used AI with ocular biomarkers to detect AD reported promising results, demonstrating that using AI with ocular biomarkers through multimodal imaging could improve the accuracy of identifying AD patients. This strategy may become a screening tool for detecting early AD in older patients prior to the onset of AD symptoms.
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Affiliation(s)
- Pareena Chaitanuwong
- Ophthalmology Department, Rajavithi Hospital, Ministry of Public Health, Bangkok, Thailand
- Department of Ophthalmology, Faculty of Medicine, Rangsit University, Bangkok, Thailand
| | - Panisa Singhanetr
- Mettapracharak Eye Institute, Mettapracharak (Wat Rai Khing) Hospital, Nakhon Pathom, Thailand
| | - Methaphon Chainakul
- Ophthalmology Department, Rajavithi Hospital, Ministry of Public Health, Bangkok, Thailand
- Department of Ophthalmology, Faculty of Medicine, Rangsit University, Bangkok, Thailand
| | - Niracha Arjkongharn
- Ophthalmology Department, Rajavithi Hospital, Ministry of Public Health, Bangkok, Thailand
- Department of Ophthalmology, Faculty of Medicine, Rangsit University, Bangkok, Thailand
| | - Paisan Ruamviboonsuk
- Ophthalmology Department, Rajavithi Hospital, Ministry of Public Health, Bangkok, Thailand
- Department of Ophthalmology, Faculty of Medicine, Rangsit University, Bangkok, Thailand
| | - Andrzej Grzybowski
- Institute of Research in Ophthalmology, Foundation for Ophthalmology Development, Mickiewicza 24/3B, 60-836, Poznan, Poland.
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Liao J, Wei Q, He Y, Liao Y, Xiong Z, Wang Q, Ding D, Huang X, Xiong Z, Wu Y. Retinopathy is associated with impaired cognition in patients undergoing peritoneal dialysis. Ren Fail 2023; 45:2258989. [PMID: 37732397 PMCID: PMC10515682 DOI: 10.1080/0886022x.2023.2258989] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 09/10/2023] [Indexed: 09/22/2023] Open
Abstract
Objective: Previous studies have shown a relationship between retinopathy and cognition including population with and without chronic kidney disease (CKD) but data regarding peritoneal dialysis (PD) are limited. This study aims to investigate the relationship between retinopathy and cognitive impairment in patients undergoing peritoneal dialysis (PD). Methods: In this observational study, we recruited a total of 107 participants undergoing PD, consisting of 48 men and 59 women, ages ranging from 21 to 78 years. The study followed a cross-sectional design. Retinal microvascular characteristics, such as geometric changes in retinal vascular including tortuosity, fractal dimension (FD), and calibers, were assessed. Retinopathy (such as retinal hemorrhage or microaneurysms) was evaluated using digitized photographs. The Modified Mini-Mental State Examination (3MS) was performed to assess global cognitive function. Results: The prevalence rates of retinal hemorrhage, microaneurysms, and retinopathy were 25%, 30%, and 43%, respectively. The mean arteriolar and venular calibers were 63.2 and 78.5 µm, respectively, and the corresponding mean tortuosity was 37.7 ± 3.6 and 37.2 ± 3.0 mm-1. The mean FD was 1.49. After adjusting for age, sex, education, mean arterial pressure, and Charlson index, a negative association was revealed between retinopathy and 3MS scores (regression coefficient: -3.71, 95% confidence interval: -7.09 to -0.33, p = 0.03). Conclusions: Retinopathy, a condition common in patients undergoing PD, was associated with global cognitive impairment. These findings highlight retinopathy, can serve as a valuable primary screening tool for assessing the risk of cognitive decline.
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Affiliation(s)
- Jinlan Liao
- Department of Nephropathy, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
- Division of Nephrology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Qijie Wei
- Vistel AI Lab, Visionary Intelligence Ltd, Beijing, China
| | - Yingying He
- Division of Nephrology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Yumei Liao
- Division of Nephrology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Zibo Xiong
- Division of Nephrology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Qing Wang
- Division of Nephrology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Dayong Ding
- Vistel AI Lab, Visionary Intelligence Ltd, Beijing, China
| | - Xiaoyan Huang
- Division of Nephrology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
- Clinical Research Academy, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Zuying Xiong
- Division of Nephrology, Peking University Shenzhen Hospital, Shenzhen, Guangdong, China
| | - Yonggui Wu
- Department of Nephropathy, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China
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Shi XH, Dong L, Zhang RH, Zhou DJ, Ling SG, Shao L, Yan YN, Wang YX, Wei WB. Relationships between quantitative retinal microvascular characteristics and cognitive function based on automated artificial intelligence measurements. Front Cell Dev Biol 2023; 11:1174984. [PMID: 37416799 PMCID: PMC10322221 DOI: 10.3389/fcell.2023.1174984] [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: 02/27/2023] [Accepted: 06/09/2023] [Indexed: 07/08/2023] Open
Abstract
Introduction: The purpose of this study is to assess the relationship between retinal vascular characteristics and cognitive function using artificial intelligence techniques to obtain fully automated quantitative measurements of retinal vascular morphological parameters. Methods: A deep learning-based semantic segmentation network ResNet101-UNet was used to construct a vascular segmentation model for fully automated quantitative measurement of retinal vascular parameters on fundus photographs. Retinal photographs centered on the optic disc of 3107 participants (aged 50-93 years) from the Beijing Eye Study 2011, a population-based cross-sectional study, were analyzed. The main parameters included the retinal vascular branching angle, vascular fractal dimension, vascular diameter, vascular tortuosity, and vascular density. Cognitive function was assessed using the Mini-Mental State Examination (MMSE). Results: The results showed that the mean MMSE score was 26.34 ± 3.64 (median: 27; range: 2-30). Among the participants, 414 (13.3%) were classified as having cognitive impairment (MMSE score < 24), 296 (9.5%) were classified as mild cognitive impairment (MMSE: 19-23), 98 (3.2%) were classified as moderate cognitive impairment (MMSE: 10-18), and 20 (0.6%) were classified as severe cognitive impairment (MMSE < 10). Compared with the normal cognitive function group, the retinal venular average diameter was significantly larger (p = 0.013), and the retinal vascular fractal dimension and vascular density were significantly smaller (both p < 0.001) in the mild cognitive impairment group. The retinal arteriole-to-venular ratio (p = 0.003) and vascular fractal dimension (p = 0.033) were significantly decreased in the severe cognitive impairment group compared to the mild cognitive impairment group. In the multivariate analysis, better cognition (i.e., higher MMSE score) was significantly associated with higher retinal vascular fractal dimension (b = 0.134, p = 0.043) and higher retinal vascular density (b = 0.152, p = 0.023) after adjustment for age, best corrected visual acuity (BCVA) (logMAR) and education level. Discussion: In conclusion, our findings derived from an artificial intelligence-based fully automated retinal vascular parameter measurement method showed that several retinal vascular morphological parameters were correlated with cognitive impairment. The decrease in retinal vascular fractal dimension and decreased vascular density may serve as candidate biomarkers for early identification of cognitive impairment. The observed reduction in the retinal arteriole-to-venular ratio occurs in the late stages of cognitive impairment.
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Affiliation(s)
- Xu Han Shi
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Beijing Ophthalmology and Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Li Dong
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Beijing Ophthalmology and Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Rui Heng Zhang
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Beijing Ophthalmology and Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Deng Ji Zhou
- EVision Technology (Beijing) Co., Ltd., Beijing, China
| | | | - Lei Shao
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Beijing Ophthalmology and Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Yan Ni Yan
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Beijing Ophthalmology and Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
| | - Ya Xing Wang
- Beijing Ophthalmology and Visual Science Key Laboratory, Beijing Tongren Eye Center, Beijing Tongren Hospital, Beijing Institute of Ophthalmology, Capital Medical University, Beijing, China
| | - Wen Bin Wei
- Beijing Tongren Eye Center, Beijing Key Laboratory of Intraocular Tumor Diagnosis and Treatment, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Beijing Ophthalmology and Visual Sciences Key Lab, Beijing Tongren Hospital, Capital Medical University, Beijing, China
- Medical Artificial Intelligence Research and Verification Key Laboratory of the Ministry of Industry and Information Technology, Beijing Tongren Hospital, Capital Medical University, Beijing, China
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Costanzo E, Lengyel I, Parravano M, Biagini I, Veldsman M, Badhwar A, Betts M, Cherubini A, Llewellyn DJ, Lourida I, MacGillivray T, Rittman T, Tamburin S, Tai XY, Virgili G. Ocular Biomarkers for Alzheimer Disease Dementia: An Umbrella Review of Systematic Reviews and Meta-analyses. JAMA Ophthalmol 2023; 141:84-91. [PMID: 36394831 DOI: 10.1001/jamaophthalmol.2022.4845] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Importance Several ocular biomarkers have been proposed for the early detection of Alzheimer disease (AD) and mild cognitive impairment (MCI), particularly fundus photography, optical coherence tomography (OCT), and OCT angiography (OCTA). Objective To perform an umbrella review of systematic reviews to assess the diagnostic accuracy of ocular biomarkers for early diagnosis of Alzheimer disease. Data Sources MEDLINE, Embase, and PsycINFO were searched from January 2000 to November 2021. The references of included reviews were also searched. Study Selection Systematic reviews investigating the diagnostic accuracy of ocular biomarkers to detect AD and MCI, in secondary care or memory clinics, against established clinical criteria or clinical judgment. Data Extraction and Synthesis The Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline checklist was followed and the Risk Of Bias in Systematic reviews tool was used to assess review quality. Main Outcomes and Measures The prespecified outcome was the accuracy of ocular biomarkers for diagnosing AD and MCI. The area under the curve (AUC) was derived from standardized mean difference. Results From the 591 titles, 14 systematic reviews were included (median [range] number of studies in each review, 14 [5-126]). Only 4 reviews were at low risk of bias on all Risk of Bias in Systematic Reviews domains. The imaging-derived parameters with the most evidence for detecting AD compared with healthy controls were OCT peripapillary retinal nerve fiber layer thickness (38 studies including 1883 patients with AD and 2510 controls; AUC = 0.70; 95% CI, 0.53-0.79); OCTA foveal avascular zone (5 studies including 177 patients with AD and 371 controls; AUC = 0.73; 95% CI, 0.50-0.89); and saccadic eye movements prosaccade latency (30 studies including 651 patients with AD/MCI and 771 controls; AUC = 0.64; 95% CI, 0.58-0.69). Antisaccade error was investigated in fewer studies (12 studies including 424 patients with AD/MCI and 382 controls) and yielded the best accuracy (AUC = 0.79; 95% CI, 0.70-0.88). Conclusions and Relevance This umbrella review has highlighted limitations in design and reporting of the existing research on ocular biomarkers for diagnosing AD. Parameters with the best evidence showed poor to moderate diagnostic accuracy in cross-sectional studies. Future longitudinal studies should investigate whether changes in OCT and OCTA measurements over time can yield accurate predictions of AD onset.
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Affiliation(s)
| | - Imre Lengyel
- Wellcome-Wolfson Institute for Experimental Medicine, Queen's University Belfast, Belfast, United Kingdom
| | | | - Ilaria Biagini
- Department NEUROFARBA, University of Florence, Florence, Italy
| | - Michele Veldsman
- Department of Experimental Psychology, University of Oxford, Oxford, United Kingdom
| | - AmanPreet Badhwar
- Department of Pharmacology and Physiology, University of Montreal, Montreal, Québec, Canada.,Centre de recherche de l'Institut Universitaire de Geriatrie, Montreal, Québec, Canada
| | - Matthew Betts
- Institute of Cognitive Neurology and Dementia Research, Otto-von-Guericke University Magdeburg, Magdeburg, Germany.,German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany.,Center for Behavioral Brain Sciences, University of Magdeburg, Magdeburg, Germany
| | - Antonio Cherubini
- Geriatria, Accettazione geriatrica e Centro di ricerca per l'invecchiamento, IRCCS INRCA, Ancona, Italy
| | - David J Llewellyn
- College of Medicine and Health, University of Exeter, Exeter, United Kingdom
| | - Ilianna Lourida
- College of Medicine and Health, University of Exeter, Exeter, United Kingdom
| | - Tom MacGillivray
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Timothy Rittman
- Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Stefano Tamburin
- Department of Neurosciences, Biomedicine and Movement Sciences, University of Verona, Verona, Italy
| | - Xin You Tai
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Gianni Virgili
- Department NEUROFARBA, University of Florence, Florence, Italy.,Centre for Public Health, Queens University Belfast, Belfast, United Kingdom
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6
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Atagun MI, Sonugur G, Yusifova A, Celik I, Ugurlu N. Machine learning algorithms revealed distorted retinal vascular branching in individuals with bipolar disorder. J Affect Disord 2022; 315:35-41. [PMID: 35905794 DOI: 10.1016/j.jad.2022.07.060] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Revised: 07/18/2022] [Accepted: 07/22/2022] [Indexed: 11/28/2022]
Abstract
BACKGROUND Converging evidence designate vascular vulnerability in bipolar disorder. The predisposition progresses into distortion in time, thus detection of the vascular susceptibility may help reducing morbidity and mortality. It was aimed to assess retinal fundus vasculature in cardiovascular risk-free patients with bipolar disorder. METHODS Total of 68 individuals (38 patients with bipolar disorder, 30 healthy controls) were enrolled. In order to avoid from degenerative processes, participants were between 18 and 45 years of age, vascular risk factors were eliminated. Microscopic retinal fundus images were processed with machine learning algorithms (multilayer perceptron and support vector machine) and artificial neural network approaches. RESULTS In comparison to the healthy control group, the bipolar disorder group had lower number of breaking points (P < 0.001), lower number of curved vessel segments (P < 0.001). Total length of smooth vessels was longer (P = 0.040), and total length of curved vessel segments was significantly shorter (P < 0.001) than the control group. Vascular endothelial growth factor levels and gender were the confounders. There were significant correlations between vascular measures and serum lipid levels. LIMITATIONS Sample size was small and patients were on various medications. CONCLUSIONS These results indicate distortion in retinal vascular branching in bipolar disorder. Disrupted branching may reflect disturbed prosperity of retinal vascular plexus in patients with bipolar disorder. Alterations in the retinal vessels might be indicators of disruption in cerebral vascular system efficiency and thus neurovascular unit dysfunction in bipolar disorder.
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Affiliation(s)
- Murat Ilhan Atagun
- Department of Psychiatry, Canakkale Onsekiz Mart University Faculty of Medicine, Canakkale, Turkey.
| | - Guray Sonugur
- Mechatronics Engineering, Faculty of Technology, Afyon Kocatepe University, Afyonkarahisar, Turkey
| | | | - Ibrahim Celik
- Mechatronics Engineering, Faculty of Technology, Afyon Kocatepe University, Afyonkarahisar, Turkey
| | - Nagihan Ugurlu
- Department of Ophtalmology, Ankara Yildirim Beyazit University Faculty of Medicine, Ankara, Turkey
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Doney ASF, Nar A, Huang Y, Trucco E, MacGillivray T, Connelly P, Leese GP, McKay GJ. Retinal vascular measures from diabetes retinal screening photographs and risk of incident dementia in type 2 diabetes: A GoDARTS study. Front Digit Health 2022; 4:945276. [PMID: 36120710 PMCID: PMC9470757 DOI: 10.3389/fdgth.2022.945276] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 08/10/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectivePatients with diabetes have an increased risk of dementia. Improved prediction of dementia is an important goal in developing future prevention strategies. Diabetic retinopathy screening (DRS) photographs may be a convenient source of imaging biomarkers of brain health. We therefore investigated the association of retinal vascular measures (RVMs) from DRS photographs in patients with type 2 diabetes with dementia risk.Research Design and MethodsRVMs were obtained from 6,111 patients in the GoDARTS bioresource (635 incident cases) using VAMPIRE software. Their association, independent of Apo E4 genotype and clinical parameters, was determined for incident all cause dementia (ACD) and separately Alzheimer's disease (AD) and vascular dementia (VD). We used Cox’s proportional hazards with competing risk of death without dementia. The potential value of RVMs to increase the accuracy of risk prediction was evaluated.ResultsIncreased retinal arteriolar fractal dimension associated with increased risk of ACD (csHR 1.17; 1.08–1.26) and AD (HR 1.33; 1.16–1.52), whereas increased venular fractal dimension (FDV) was associated with reduced risk of AD (csHR 0.85; 0.74–0.96). Conversely, FDV was associated with increased risk of VD (csHR 1.22; 1.07–1.40). Wider arteriolar calibre was associated with a reduced risk of ACD (csHR 0.9; 0.83–0.98) and wider venular calibre was associated with a reduced risk of AD (csHR 0.87; 0.78–0.97). Accounting for competing risk did not substantially alter these findings. RVMs significantly increased the accuracy of prediction.ConclusionsConventional DRS photographs could enhance stratifying patients with diabetes at increased risk of dementia facilitating the development of future prevention strategies.
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Affiliation(s)
- Alexander S. F. Doney
- Population Health and Genomics, University of Dundee, Dundee, United Kingdom
- Correspondence: Alexander S.F. Doney
| | - Aditya Nar
- Population Health and Genomics, University of Dundee, Dundee, United Kingdom
| | - Yu Huang
- Population Health and Genomics, University of Dundee, Dundee, United Kingdom
| | - Emanuele Trucco
- VAMPIRE project, Computing, School of Science and Engineering, University of Dundee, Dundee, United Kingdom
| | - Tom MacGillivray
- VAMPIRE project, Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Peter Connelly
- NHS Tayside; NHS Research Scotland Neuroprogressive Disorders and Dementia Research Network, Ninewells Hospital Dundee; University of Dundee, Dundee, Scotland
| | - Graham P. Leese
- Population Health and Genomics, University of Dundee, Dundee, United Kingdom
| | - Gareth J. McKay
- Centre for Public Health, Queen’s University Belfast, Belfast, NIR, United Kingdom
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Tao W, Kwapong WR, Xie J, Wang Z, Guo X, Liu J, Ye C, Wu B, Zhao Y, Liu M. Retinal microvasculature and imaging markers of brain frailty in normal aging adults. Front Aging Neurosci 2022; 14:945964. [PMID: 36072485 PMCID: PMC9441884 DOI: 10.3389/fnagi.2022.945964] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Accepted: 07/22/2022] [Indexed: 11/13/2022] Open
Abstract
BackgroundThe retina and brain share a similar embryologic origin, blood barriers, and microvasculature features. Thus, retinal imaging has been of interest in the aging population to help in the early detection of brain disorders. Imaging evaluation of brain frailty, including brain atrophy and markers of cerebral small vessel disease (CSVD), could reflect brain health in normal aging, but is costly and time-consuming. In this study, we aimed to evaluate the retinal microvasculature and its association with radiological indicators of brain frailty in normal aging adults.MethodsSwept-source optical coherence tomography angiography (SS-OCTA) and 3T-MRI brain scanning were performed on normal aging adults (aged ≥ 50 years). Using a deep learning algorithm, microvascular tortuosity (VT) and fractal dimension parameter (Dbox) were used to evaluate the superficial vascular complex (SVC) and deep vascular complex (DVC) of the retina. MRI markers of brain frailty include brain volumetric measures and CSVD markers that were assessed.ResultsOf the 139 normal aging individuals included, the mean age was 59.43 ± 7.31 years, and 64.0% (n = 89) of the participants were females. After adjustment of age, sex, and vascular risk factors, Dbox in the DVC showed a significant association with the presence of lacunes (β = 0.58, p = 0.007), while VT in the SVC significantly correlated with the score of cerebral deep white matter hyperintensity (β = 0.31, p = 0.027). No correlations were found between brain volumes and retinal microvasculature changes (P > 0.05).ConclusionOur report suggests that imaging of the retinal microvasculature may give clues to brain frailty in the aging population.
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Affiliation(s)
- Wendan Tao
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | | | - Jianyang Xie
- Cixi Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
| | - Zetao Wang
- Department of Radiology, West China Hospital, Sichuan University, Chengdu, China
| | - Xiaonan Guo
- School of Information Science and Engineering, Yanshan University, Qinhuangdao, China
| | - Junfeng Liu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Chen Ye
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Bo Wu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
| | - Yitian Zhao
- The Affiliated People’s Hospital of Ningbo University, Ningbo, China
- Cixi Institute of Biomedical Engineering, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo, China
- Yitian Zhao,
| | - Ming Liu
- Department of Neurology, West China Hospital, Sichuan University, Chengdu, China
- *Correspondence: Ming Liu,
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Jin CY, Yu SW, Yin JT, Yuan XY, Wang XG. Corresponding risk factors between cognitive impairment and type 1 diabetes mellitus: a narrative review. Heliyon 2022; 8:e10073. [PMID: 35991978 PMCID: PMC9389196 DOI: 10.1016/j.heliyon.2022.e10073] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2022] [Revised: 04/24/2022] [Accepted: 07/20/2022] [Indexed: 11/30/2022] Open
Abstract
Type 1 diabetes mellitus (T1DM) is a type of diabetes caused by the destruction of pancreatic β cells and the absolute lack of insulin secretion. T1DM usually starts in adolescence or develops directly as a severe disease state of ketoacidosis. T1DM and its complications make many people suffer and have psychological problems, which make us have to pay more attention to the prevention and early control of T1DM. Cognitive impairment (CI) is one of the major complications of T1DM. It can further develop into Alzheimer's disease, which can seriously affect the quality of life of the elderly. Furthermore, the relationship between T1DM and CI is unclear. Hence, we conducted a narrative review of the existing literature through a PubMed search. We summarized some risk factors that may be associated with the cognitive changes in T1DM patients, including onset age and duration, education and gender, glycemic states, microvascular complications, glycemic control, neuropsychology and emotion, intestinal flora, dyslipidemia, sleep quality. We aimed to provide some content related to CI in T1DM, and hoped that it could play a role in early prediction and treatment to reduce the prevalence. Corresponding risk factors between cognitive impairment and type 1 diabetes mellitus. Duration and age; Education and gender and Glycemic states. Diabetic ketoacidosis; Microvascular complications and Glycemic control–HbA1c. Neuropsychology and emotion; Intestinal flora; Dyslipidemia and Sleep Quality.
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Affiliation(s)
- Chen-Yang Jin
- The First Affiliated Hospital of Dalian Medical University, Dalian Medical University, Dalian 116011, PR China
| | - Shi-Wen Yu
- The First Affiliated Hospital of Dalian Medical University, Dalian Medical University, Dalian 116011, PR China
| | - Jun-Ting Yin
- The Second Affiliated Hospital of Dalian Medical University, Dalian Medical University, Dalian 116027, PR China
| | - Xiao-Ying Yuan
- Department of Anatomy, College of Basic Medicine, Dalian Medical University, Dalian 116044, PR China
- Department of Surgery, The Affiliated Zhongshan Hospital of Dalian University, Dalian 116001, PR China
- Corresponding author.
| | - Xu-Gang Wang
- Department of Neurology, The Second Affiliated Hospital of Dalian Medical University, Dalian 116027, PR China
- Corresponding author.
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van der Heide FCT, van Sloten TT, Willekens N, Stehouwer CDA. Neurovascular coupling unit dysfunction and dementia: Retinal measurements as tools to move towards population-based evidence. Front Endocrinol (Lausanne) 2022; 13:1014287. [PMID: 36506058 PMCID: PMC9727310 DOI: 10.3389/fendo.2022.1014287] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Accepted: 10/31/2022] [Indexed: 11/24/2022] Open
Abstract
Dysfunction of the neurovascular coupling unit may be an important contributor to dementia. The neurovascular coupling unit comprises neuronal structures (e.g. astrocytes) and vascular structures (e.g. endothelial cells) that functionally interact both at the level of the arterioles as well as at the capillary level (blood-brain barrier) to regulate optimal metabolic conditions in the brain. However, it remains unclear how and to what extent dysfunction of the neurovascular coupling unit contributes to the early-stage pathobiology of dementia. Currently, limited data are available on the association between neurovascular coupling unit dysfunction, as quantified by cerebral imaging techniques, and cognitive performance. In particular, there is a lack of population-based human data (defined as studies with a sample size ~n>500). This is an important limitation because population-based studies, in comparison with smaller clinical studies, provide data which is better representative of the general population; are less susceptible to selection bias; and have a larger statistical power to detect small associations. To acquire population-based data, however, alternative imaging techniques than cerebral imaging techniques may be required. Disadvantages of cerebral imaging techniques, which limit use in population-based studies, are that these techniques are relatively expensive, time-consuming, and/or invasive. In this review, we propose that retinal imaging techniques can be used for population-based studies: on the one hand the retina and brain have many anatomical and physiological similarities; and on the other hand retinal imaging techniques are non-invasive, highly accurate, relatively inexpensive, and require relatively short measurement time. To provide support for this concept, we provide an overview on the human (population-based) evidence on the associations of retinal indices of neurodegeneration, microvascular dysfunction, and dysfunction of the neurovascular coupling unit with magnetic resonance imaging (MRI) features of structural brain abnormalities and cognitive performance.
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Affiliation(s)
- Frank C. T. van der Heide
- CARIM School for Cardiovascular Diseases, Maastricht University (UM), Maastricht, Netherlands
- Department of Internal Medicine, Maastricht University Medical Center+ (MUMC+), Maastricht, Netherlands
- Department of Psychiatry and Neuropsychology, MUMC+, Maastricht, Netherlands
- School of Mental Health and Neuroscience, MUMC+, Maastricht, Netherlands
- *Correspondence: Frank C. T. van der Heide,
| | - Thomas T. van Sloten
- CARIM School for Cardiovascular Diseases, Maastricht University (UM), Maastricht, Netherlands
- Department of Internal Medicine, Maastricht University Medical Center+ (MUMC+), Maastricht, Netherlands
| | - Nele Willekens
- CARIM School for Cardiovascular Diseases, Maastricht University (UM), Maastricht, Netherlands
- Department of Internal Medicine, Maastricht University Medical Center+ (MUMC+), Maastricht, Netherlands
| | - Coen D. A. Stehouwer
- CARIM School for Cardiovascular Diseases, Maastricht University (UM), Maastricht, Netherlands
- Department of Internal Medicine, Maastricht University Medical Center+ (MUMC+), Maastricht, Netherlands
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O'Neill RA, Maxwell AP, Paterson EN, Kee F, Young I, Hogg RE, Cruise S, Murphy S, McGuinness B, McKay GJ. Retinal microvascular parameters are not significantly associated with mild cognitive impairment in the Northern Ireland Cohort for the Longitudinal Study of Ageing. BMC Neurol 2021; 21:112. [PMID: 33706706 PMCID: PMC7948373 DOI: 10.1186/s12883-021-02137-4] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/23/2020] [Accepted: 03/03/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The retinal and cerebral microvasculature share similar embryological origins and physiological characteristics. Improved imaging technologies provide opportunistic non-invasive assessment of retinal microvascular parameters (RMPs) against cognitive outcomes. We evaluated baseline measures for associations between RMPs and mild cognitive impairment (MCI) from participants of the Northern Ireland Cohort for the Longitudinal Study of Ageing (NICOLA). METHODS RMPs (central retinal arteriolar / venular equivalents, arteriole to venular ratio, fractal dimension and tortuosity) were measured from optic disc centred fundus images and analysed using semi-automated software. Associations between RMPs and MCI were assessed by multivariable logistic regression with adjustment for potential confounders including age, sex, alcohol consumption, smoking status, educational attainment, physical activity, cardiovascular disease (CVD), hypertension, mean arterial blood pressure, triglycerides, diabetes, body mass index, and high density lipoprotein levels. P < 0.05 was considered statistically significant. RESULTS Data were available for 1431 participants, of which 156 (10.9%) were classified with MCI defined by a Montreal Cognitive Assessment (MoCA) score ≤ 26, with subjective cognitive decline, in the absence of depression or problems with activities of daily living. Participants had a mean age of 62.4 ± 8.5 yrs. and 52% were female. As expected, individuals with MCI had a lower MoCA score than those without (23.5 ± 2.6 versus 26.3 ± 2.7, respectively), were more likely to be female, have a lower level of educational attainment, be less physically active, more likely to have CVD, have higher levels of triglycerides and lower levels of high density lipoprotein. No significant associations between RMPs and MCI were detected in unadjusted, minimally adjusted or fully adjusted regression models or subsequent sensitivity analyses. CONCLUSION Previous studies have reported both increased retinal venular calibre and reduced fractal dimension in association with mild cognitive impairment. Our study failed to detect any associations between RMPs and those individuals at an early stage of cognitive loss in an older community-based cohort.
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Affiliation(s)
- R A O'Neill
- Centre for Public Health, Queens University Belfast, Belfast, Northern Ireland
| | - A P Maxwell
- Centre for Public Health, Queens University Belfast, Belfast, Northern Ireland
| | - E N Paterson
- Centre for Public Health, Queens University Belfast, Belfast, Northern Ireland
| | - F Kee
- Centre for Public Health, Queens University Belfast, Belfast, Northern Ireland
| | - I Young
- Centre for Public Health, Queens University Belfast, Belfast, Northern Ireland
| | - R E Hogg
- Centre for Public Health, Queens University Belfast, Belfast, Northern Ireland
| | - S Cruise
- Centre for Public Health, Queens University Belfast, Belfast, Northern Ireland
| | - S Murphy
- Centre for Public Health, Queens University Belfast, Belfast, Northern Ireland
| | - B McGuinness
- Centre for Public Health, Queens University Belfast, Belfast, Northern Ireland
| | - G J McKay
- Centre for Public Health, Queens University Belfast, Belfast, Northern Ireland.
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12
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Provost EB, Nawrot TS, Int Panis L, Standaert A, Saenen ND, De Boever P. Denser Retinal Microvascular Network Is Inversely Associated With Behavioral Outcomes and Sustained Attention in Children. Front Neurol 2021; 12:547033. [PMID: 33584528 PMCID: PMC7880124 DOI: 10.3389/fneur.2021.547033] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2020] [Accepted: 01/08/2021] [Indexed: 11/25/2022] Open
Abstract
Changes in geometry of the retinal microvascular network, including vessel width, vessel density, and tortuosity, have been associated with neurological disorders in adults. We investigated metrics of the retinal microvasculature in association with behavior and cognition in 8- to 12-year-old children. Digital fundus images of 190 children (48.2% girls, mean age 9.9 years) were used to calculate retinal vessel diameters, fractal dimension, lacunarity, and tortuosity. Parents filled out a Strengths and Difficulties Questionnaire (SDQ) for behavioral screening. Cognitive performance testing included a computerized version of the Stroop test (selective attention), the Continuous Performance (sustained attention), the Digit-Symbol (visual scanning and information-processing speed) and the Pattern Comparison (visuospatial analytic ability) tests from the Neurobehavioral Evaluation System (NES3) battery. Retinal vessel geometry was significantly associated with the SDQ problem score, which increased with 1.1 points (95% CI: 0.3 to 1.9 points) per interquartile (IQR) increment in retinal fractal dimension, and decreased 1.4 points (95% CI: −2.4 to −0.4 points) or decreased 1.0 points (95% CI: −2.1 to 0.1 points) per IQR increment in retinal vascular lacunarity or tortuosity, respectively. Sensitivity analyses showed that results were driven by the hyperactivity/inattention and conduct problem scales of the SDQ. Correspondingly, mean reaction time on the Continuous Performance test increased by 11 ms (95% CI: 4.4 to 17.6 ms) with an IQR increase in fractal dimension. The results indicate that a denser retinal microvascular network, exemplified by a higher fractal dimension and lower lacunarity, are inversely associated with behavioral outcomes and sustained attention in children.
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Affiliation(s)
- Eline B Provost
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium.,Health Unit, Flemish Institute for Technological Research (VITO), Mol, Belgium
| | - Tim S Nawrot
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium.,Department of Public Health and Primary Care, Leuven University, Leuven, Belgium
| | - Luc Int Panis
- Health Unit, Flemish Institute for Technological Research (VITO), Mol, Belgium.,School for Mobility, Hasselt University, Diepenbeek, Belgium
| | - Arnout Standaert
- Health Unit, Flemish Institute for Technological Research (VITO), Mol, Belgium
| | - Nelly D Saenen
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium
| | - Patrick De Boever
- Centre for Environmental Sciences, Hasselt University, Diepenbeek, Belgium.,Health Unit, Flemish Institute for Technological Research (VITO), Mol, Belgium.,Department of Biology, University of Antwerp, Antwerp, Belgium
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