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Blose BA, Silverstein SM, Stuart KV, Keane PA, Khawaja AP, Wagner SK. Association between polygenic risk for schizophrenia and retinal morphology: A cross-sectional analysis of the United Kingdom Biobank. Psychiatry Res 2024; 339:116106. [PMID: 39079374 DOI: 10.1016/j.psychres.2024.116106] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/22/2024] [Revised: 07/17/2024] [Accepted: 07/24/2024] [Indexed: 08/15/2024]
Abstract
We examined the relationship between genetic risk for schizophrenia (SZ), using polygenic risk scores (PRSs), and retinal morphological alterations. Retinal structural and vascular indices derived from optical coherence tomography (OCT) and color fundus photography (CFP) and PRSs for SZ were analyzed in N = 35,024 individuals from the prospective cohort study, United Kingdom Biobank (UKB). Results indicated that macular ganglion cell-inner plexiform layer (mGC-IPL) thickness was significantly inversely related to PRS for SZ, and this relationship was strongest within higher PRS quintiles and independent of potential confounders and age. PRS, however, was unrelated to retinal vascular characteristics, with the exception of venular tortuosity, and other retinal structural indices (macular retinal nerve fiber layer [mRNFL], inner nuclear layer [INL], cup-to-disc ratio [CDR]). Additionally, the association between greater PRS and reduced mGC-IPL thickness was only significant for participants in the 40-49 and 50-59 age groups, not those in the 60-69 age group. These findings suggest that mGC-IPL thinning is associated with a genetic predisposition to SZ and may reflect neurodevelopmental and/or neurodegenerative processes inherent to SZ. Retinal microvasculature alterations, however, may be secondary consequences of SZ and do not appear to be associated with a genetic predisposition to SZ.
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Affiliation(s)
- Brittany A Blose
- Department of Psychology, University of Rochester, Rochester, NY, United States; Department of Psychiatry, University of Rochester Medical Center, Rochester, New York, United States
| | - Steven M Silverstein
- Department of Psychiatry, University of Rochester Medical Center, Rochester, New York, United States; Department of Ophthalmology, University of Rochester Medical Center, Rochester, New York, United States; Department of Neuroscience, University of Rochester Medical Center, Rochester, New York, United States; Center for Visual Science, University of Rochester, Rochester, New York, United States.
| | - Kelsey V Stuart
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom; Institute of Ophthalmology, University College London, London, United Kingdom; Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Pearse A Keane
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom; Institute of Ophthalmology, University College London, London, United Kingdom; Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Anthony P Khawaja
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom; Institute of Ophthalmology, University College London, London, United Kingdom; Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Siegfried K Wagner
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom; Institute of Ophthalmology, University College London, London, United Kingdom; Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
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Zhang G, Qu Y, Zhang Y, Tang J, Wang C, Yin H, Yao X, Liang G, Shen T, Ren Q, Jia H, Sun X. Multimodal Eye Imaging, Retina Characteristics, and Psychological Assessment Dataset. Sci Data 2024; 11:836. [PMID: 39095400 PMCID: PMC11297319 DOI: 10.1038/s41597-024-03690-6] [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: 03/20/2024] [Accepted: 07/26/2024] [Indexed: 08/04/2024] Open
Abstract
The eyes provide insights into psychology, potentially offering a distinctive perspective for psychological health profiles. However, there exist a notable deficiency in datasets that simultaneously encompass eye features and psychological assessments. To address this gap, our study presents a dataset that included Fundus Photography, Psychological Assessment, Retina Characteristics, and Multimodal Imaging (FPRM). FPRM dataset comprise fundus images at different wavelengths (548 nm and 605 nm), image of oxygen saturation for the retina and 8 specific retinal vessels, videos of retinal blood flow and pupillary light reflex, along with 61 items of multimodal quantitative measurement from 384 participants. Additionally, it features psychological assessments across five dimensions (geriatric depression, generalized anxiety disorder, insomnia, activities of daily living, and deterioration), accompanied by fundus photographs and 6 items of retina characteristics from 1683 participants. FPRM dataset is the first to integrate multimodal ophthalmic data and psychological assessments, not only advancing the development of machine learning applications but also facilitating in-depth research into the relationship between eye health and psychological health profiles.
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Affiliation(s)
- Guanran Zhang
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai, China
- National Clinical Research Center for Eye Diseases, Shanghai, China
| | - Yanlin Qu
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai, China
- National Clinical Research Center for Eye Diseases, Shanghai, China
| | - Yanping Zhang
- Jinshan District Mental Health Center, Shanghai, China
| | - Jiayi Tang
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai, China
- National Clinical Research Center for Eye Diseases, Shanghai, China
| | - Chunyan Wang
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai, China
- National Clinical Research Center for Eye Diseases, Shanghai, China
| | - Haogui Yin
- Jinshan District Mental Health Center, Shanghai, China
| | - Xiaoping Yao
- Jinshan District Mental Health Center, Shanghai, China
| | - Gengshi Liang
- Community Health Service Center in Lvxiang Town, Shanghai, China
| | - Ting Shen
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai, China
- National Clinical Research Center for Eye Diseases, Shanghai, China
| | - Qiushi Ren
- Department of Biomedical Engineering and National Biomedical Imaging Center, College of Future Technology, Peking University, Beijing, China
- Institute of Biomedical Engineering, Peking University Shenzhen Graduate School, Shenzhen, China
| | - Huixun Jia
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai, China.
- National Clinical Research Center for Eye Diseases, Shanghai, China.
| | - Xiaodong Sun
- Department of Ophthalmology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai, China.
- National Clinical Research Center for Eye Diseases, Shanghai, China.
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Liu F, Chen X, Wang Q, Lin W, Li Y, Zhang R, Huang H, Jiang S, Niu Y, Liu W, Wang L, Zhang W, Zheng Y, Cao X, Wang Y, Wu J, Zhang L, Tang L, Zhou J, Chen P, Cai G, Dong Z. Correlation between retinal vascular geometric parameters and pathologically diagnosed type 2 diabetic nephropathy. Clin Kidney J 2024; 17:sfae204. [PMID: 39099565 PMCID: PMC11292218 DOI: 10.1093/ckj/sfae204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2024] [Indexed: 08/06/2024] Open
Abstract
Background Diabetic nephropathy (DN) and diabetic retinopathy (DR) are common microvascular complications of diabetes. The purpose of this study was to investigate the correlation between retinal vascular geometric parameters and pathologically diagnosed type 2 DN and to determine the capacity of retinal vascular geometric parameters in differentiating DN from non-diabetic renal disease (NDRD). Methods The study participants were adult patients with type 2 diabetes mellitus (T2DM) and chronic kidney disease who underwent a renal biopsy. Univariate and multivariable regression analyses were performed to evaluate associations between retinal vessel geometry parameters and pathologically diagnosed DN. Multivariate binary logistic regression analyses were performed to establish a differential diagnostic model for DN. Results In total, 403 patients were examined in this cross-sectional study, including 152 (37.7%) with DN, 157 (39.0%) with NDRD and 94 (23.3%) with DN combined with NDRD. After univariate logistic regression, total vessel fractal dimension, arteriolar fractal dimension and venular fractal dimension were all found to be associated with DN. In multivariate analyses adjusting for age, sex, blood pressure, diabetes, DR and other factors, smaller retinal vascular fractal dimensions were significantly associated with DN (P < .05). We developed a differential diagnostic model for DN combining traditional clinical indicators and retinal vascular geometric parameters. The area under the curve of the model established by multivariate logistic regression was 0.930. Conclusions Retinal vessel fractal dimension is of great significance for the rapid and non-invasive differentiation of DN. Incorporating retinal vessel fractal dimension into the diagnostic model for DN and NDRD can improve the diagnostic efficiency.
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Affiliation(s)
- Fang Liu
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
- First Clinical Medical College, Guangdong Pharmaceutical University, Guangzhou, China
| | - Xiaoniao Chen
- Senior Department of Ophthalmology, Third Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Qian Wang
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Wenwen Lin
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
- First Clinical Medical College, Guangdong Pharmaceutical University, Guangzhou, China
| | - Ying Li
- Senior Department of Ophthalmology, Third Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Ruimin Zhang
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
- College of Basic Medical Sciences, Chengdu University of Traditional Chinese Medicine, Chengdu, China
| | - Hui Huang
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
- First Clinical Medical College, Guangdong Pharmaceutical University, Guangzhou, China
| | - Shuangshuang Jiang
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Yue Niu
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Weicen Liu
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Liqiang Wang
- Senior Department of Ophthalmology, Third Medical Center, Chinese PLA General Hospital, Beijing, China
| | - Weiguang Zhang
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Ying Zheng
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Xueying Cao
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Yong Wang
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Jie Wu
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Li Zhang
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Li Tang
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Jianhui Zhou
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Pu Chen
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Guangyan Cai
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
| | - Zheyi Dong
- Department of Nephrology, First Medical Center of Chinese PLA General Hospital, State Key Laboratory of Kidney Diseases, National Clinical Research Center for Kidney Diseases, Beijing Key Laboratory of Kidney Diseases Research, Beijing, China
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Hall PA, Burhan AM, MacKillop JC, Duarte D. Next-generation cognitive assessment: Combining functional brain imaging, system perturbations and novel equipment interfaces. Brain Res Bull 2023; 204:110797. [PMID: 37875208 DOI: 10.1016/j.brainresbull.2023.110797] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2023] [Revised: 10/14/2023] [Accepted: 10/19/2023] [Indexed: 10/26/2023]
Abstract
Conventional cognitive assessment is widely used in clinical and research settings, in educational institutions, and in the corporate world for personnel selection. Such approaches involve having a client, a patient, or a research participant complete a series of standardized cognitive tasks in order to challenge specific and global cognitive abilities, and then quantify performance for the desired end purpose. The latter may include a diagnostic confirmation of a disease, description of a state or ability, or matching cognitive characteristics to a particular occupational role requirement. Metrics derived from cognitive assessments are putatively informative about important features of the brain and its function. For this reason, the research sector also makes use of cognitive assessments, most frequently as a stimulus for cognitive activity from which to extract functional neuroimaging data. Such "task-related activations" form the core of the most widely used neuroimaging technologies, such as fMRI. Much of what we know about the brain has been drawn from the interleaving of cognitive assessments of various types with functional brain imaging technologies. Despite innovation in neuroimaging (i.e., quantifying the neural response), relatively little innovation has occurred on task presentation and volitional response measurement; yet these together comprise the core of cognitive performance. Moreover, even when cognitive assessment is interleaved with functional neuroimaging, this is most often undertaken in the research domain, rather than the primary applications of cognitive assessment in diagnosis and monitoring, education and personnel selection. There are new ways in which brain imaging-and even more importantly, brain modulation-technologies can be combined with automation and artificial intelligence to deliver next-generation cognitive assessment methods. In this review paper, we describe some prototypes for how this can be done and identify important areas for progress (technological and otherwise) to enable it to happen. We will argue that the future of cognitive assessment will include semi- and fully-automated assessments involving neuroimaging, standardized perturbations via neuromodulation technologies, and artificial intelligence. Furthermore, the fact that cognitive assessments take place in a social/interpersonal context-normally between the patient and clinician-makes the human-machine interface consequential, and this will also be discussed.
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Affiliation(s)
- Peter A Hall
- School of Public Health Sciences, Faculty of Health, University of Waterloo, Waterloo, Ontario, Canada; Centre for Bioengineering and Biotechnology, University of Waterloo, Waterloo, Ontario, Canada.
| | - Amer M Burhan
- Ontario Shores Centre for Mental Health Sciences, Whitby, Ontario, Canada; Department of Psychiatry, Temerty Faculty of Medicine, University of Toronto, Toronto, Ontario, Canada
| | - James C MacKillop
- Department of Psychiatry and Behavioural Neurosciences, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada
| | - Dante Duarte
- Department of Psychiatry and Behavioural Neurosciences, Faculty of Health Sciences, McMaster University, Hamilton, Ontario, Canada; Seniors Mental Health Program, St. Joseph's Healthcare, Hamilton, Ontario, Canada
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Constable PA, Lim JKH, Thompson DA. Retinal electrophysiology in central nervous system disorders. A review of human and mouse studies. Front Neurosci 2023; 17:1215097. [PMID: 37600004 PMCID: PMC10433210 DOI: 10.3389/fnins.2023.1215097] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2023] [Accepted: 07/17/2023] [Indexed: 08/22/2023] Open
Abstract
The retina and brain share similar neurochemistry and neurodevelopmental origins, with the retina, often viewed as a "window to the brain." With retinal measures of structure and function becoming easier to obtain in clinical populations there is a growing interest in using retinal findings as potential biomarkers for disorders affecting the central nervous system. Functional retinal biomarkers, such as the electroretinogram, show promise in neurological disorders, despite having limitations imposed by the existence of overlapping genetic markers, clinical traits or the effects of medications that may reduce their specificity in some conditions. This narrative review summarizes the principal functional retinal findings in central nervous system disorders and related mouse models and provides a background to the main excitatory and inhibitory retinal neurotransmitters that have been implicated to explain the visual electrophysiological findings. These changes in retinal neurochemistry may contribute to our understanding of these conditions based on the findings of retinal electrophysiological tests such as the flash, pattern, multifocal electroretinograms, and electro-oculogram. It is likely that future applications of signal analysis and machine learning algorithms will offer new insights into the pathophysiology, classification, and progression of these clinical disorders including autism, attention deficit/hyperactivity disorder, bipolar disorder, schizophrenia, depression, Parkinson's, and Alzheimer's disease. New clinical applications of visual electrophysiology to this field may lead to earlier, more accurate diagnoses and better targeted therapeutic interventions benefiting individual patients and clinicians managing these individuals and their families.
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Affiliation(s)
- Paul A. Constable
- College of Nursing and Health Sciences, Caring Futures Institute, Flinders University, Adelaide, SA, Australia
| | - Jeremiah K. H. Lim
- Discipline of Optometry, School of Allied Health, University of Western Australia, Perth, WA, Australia
| | - Dorothy A. Thompson
- The Tony Kriss Visual Electrophysiology Unit, Clinical and Academic Department of Ophthalmology, Great Ormond Street Hospital for Children NHS Trust, London, United Kingdom
- UCL Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
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Wagner SK, Cortina-Borja M, Silverstein SM, Zhou Y, Romero-Bascones D, Struyven RR, Trucco E, Mookiah MRK, MacGillivray T, Hogg S, Liu T, Williamson DJ, Pontikos N, Patel PJ, Balaskas K, Alexander DC, Stuart KV, Khawaja AP, Denniston AK, Rahi JS, Petzold A, Keane PA. Association Between Retinal Features From Multimodal Imaging and Schizophrenia. JAMA Psychiatry 2023; 80:478-487. [PMID: 36947045 PMCID: PMC10034669 DOI: 10.1001/jamapsychiatry.2023.0171] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Accepted: 01/23/2023] [Indexed: 03/23/2023]
Abstract
Importance The potential association of schizophrenia with distinct retinal changes is of clinical interest but has been challenging to investigate because of a lack of sufficiently large and detailed cohorts. Objective To investigate the association between retinal biomarkers from multimodal imaging (oculomics) and schizophrenia in a large real-world population. Design, Setting, and Participants This cross-sectional analysis used data from a retrospective cohort of 154 830 patients 40 years and older from the AlzEye study, which linked ophthalmic data with hospital admission data across England. Patients attended Moorfields Eye Hospital, a secondary care ophthalmic hospital with a principal central site, 4 district hubs, and 5 satellite clinics in and around London, United Kingdom, and had retinal imaging during the study period (January 2008 and April 2018). Data were analyzed from January 2022 to July 2022. Main Outcomes and Measures Retinovascular and optic nerve indices were computed from color fundus photography. Macular retinal nerve fiber layer (RNFL) and ganglion cell-inner plexiform layer (mGC-IPL) thicknesses were extracted from optical coherence tomography. Linear mixed-effects models were used to examine the association between schizophrenia and retinal biomarkers. Results A total of 485 individuals (747 eyes) with schizophrenia (mean [SD] age, 64.9 years [12.2]; 258 [53.2%] female) and 100 931 individuals (165 400 eyes) without schizophrenia (mean age, 65.9 years [13.7]; 53 253 [52.8%] female) were included after images underwent quality control and potentially confounding conditions were excluded. Individuals with schizophrenia were more likely to have hypertension (407 [83.9%] vs 49 971 [48.0%]) and diabetes (364 [75.1%] vs 28 762 [27.6%]). The schizophrenia group had thinner mGC-IPL (-4.05 μm, 95% CI, -5.40 to -2.69; P = 5.4 × 10-9), which persisted when investigating only patients without diabetes (-3.99 μm; 95% CI, -6.67 to -1.30; P = .004) or just those 55 years and younger (-2.90 μm; 95% CI, -5.55 to -0.24; P = .03). On adjusted analysis, retinal fractal dimension among vascular variables was reduced in individuals with schizophrenia (-0.14 units; 95% CI, -0.22 to -0.05; P = .001), although this was not present when excluding patients with diabetes. Conclusions and Relevance In this study, patients with schizophrenia had measurable differences in neural and vascular integrity of the retina. Differences in retinal vasculature were mostly secondary to the higher prevalence of diabetes and hypertension in patients with schizophrenia. The role of retinal features as adjunct outcomes in patients with schizophrenia warrants further investigation.
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Affiliation(s)
- Siegfried K. Wagner
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Mario Cortina-Borja
- Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
| | - Steven M. Silverstein
- Department of Psychiatry, University of Rochester Medical Center, Rochester, New York
- Department of Ophthalmology, University of Rochester Medical Center, Rochester, New York
- Department of Neuroscience, University of Rochester Medical Center, Rochester, New York
- Center for Visual Science, University of Rochester, Rochester, New York
| | - Yukun Zhou
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - David Romero-Bascones
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
- Biomedical Engineering Department, Faculty of Engineering (MU-ENG), Mondragon Unibertsitatea, Mondragón, Spain
| | - Robbert R. Struyven
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - Emanuele Trucco
- VAMPIRE Project, School of Science and Engineering, University of Dundee, Dundee, United Kingdom
| | - Muthu R. K. Mookiah
- VAMPIRE Project, 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
| | - Stephen Hogg
- VAMPIRE Project, School of Science and Engineering, University of Dundee, Dundee, United Kingdom
| | - Timing Liu
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Dominic J. Williamson
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - Nikolas Pontikos
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Praveen J. Patel
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Konstantinos Balaskas
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Daniel C. Alexander
- Centre for Medical Image Computing, Department of Computer Science, University College London, London, United Kingdom
| | - Kelsey V. Stuart
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Anthony P. Khawaja
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
| | - Alastair K. Denniston
- University of Birmingham, Birmingham, United Kingdom
- University Hospitals Birmingham NHS Foundation Trust, Birmingham, United Kingdom
- NIHR Birmingham Biomedical Research Centre, University of Birmingham, Birmingham, United Kingdom
| | - Jugnoo S. Rahi
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Great Ormond Street Institute of Child Health, University College London, London, United Kingdom
- Great Ormond Street Hospital NHS Foundation Trust, London, United Kingdom
- Ulverscroft Vision Research Group, University College London, London, United Kingdom
- NIHR Biomedical Research Centre at UCL Great Ormond Street Institute of Child Health and Great Ormond Street Hospital, London, United Kingdom
| | - Axel Petzold
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
- Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Pearse A. Keane
- NIHR Moorfields Biomedical Research Centre, London, United Kingdom
- Institute of Ophthalmology, University College London, London, United Kingdom
- Moorfields Eye Hospital NHS Foundation Trust, London, United Kingdom
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Choroidal structural analysis in ultra-high risk and first-episode psychosis. Eur Neuropsychopharmacol 2023; 70:72-80. [PMID: 36931136 DOI: 10.1016/j.euroneuro.2023.02.016] [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: 01/03/2023] [Revised: 02/02/2023] [Accepted: 02/22/2023] [Indexed: 03/19/2023]
Abstract
Both structural and functional alterations in the retina and the choroid of the eye, as parts of the central nervous system, have been shown in psychotic disorders, especially in schizophrenia. In addition, genetic and imaging studies indicate vascular and angiogenesis anomalies in the psychosis spectrum disorders. In this ocular imaging study, choroidal structure and vascularity were investigated using enhanced depth imaging (EDI) optical coherence tomography (OCT) in first-episode psychosis (FEP), ultra-high risk for psychosis (UHR-P), and age- and gender- matched healthy controls (HCs). There were no significant differences between groups in central choroidal thickness, stromal choroidal area (SCA), luminal choroidal area (LCA) and total subfoveal choroidal area. The LCA/SCA ratio (p<0.001) and the choroidal vascularity index (CVI) (p<0.001) were significantly different between FEP, UHR-P and HCs. CVI and LCA/SCA ratio were significantly higher in patients with FEP compared to help-seeking youth at UHR-P. CVI and LCA/SCA ratio were not different between UHR-P and HCs. However, CVI was higher in UHR-P compared to HCs after excluding the outliers for the sensitivity analysis (p = 0.002). Current findings suggest that choroidal thickness is normal, but there are abnormalities in choroidal microvasculature in prodromal and first-episode psychosis. Further longitudinal studies are needed to investigate oculomics, especially CVI, as a promising biomarker for the prediction of conversion to psychosis in individuals at clinical high-risk.
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Mio M, Grigorian A, Zou Y, Dimick MK, Selkirk B, Kertes P, McCrindle BW, Swardfager W, Hahn MK, Black SE, MacIntosh BJ, Goldstein BI. Neurovascular correlates of retinal microvascular caliber in adolescent bipolar disorder. J Affect Disord 2023; 320:81-90. [PMID: 36162693 DOI: 10.1016/j.jad.2022.09.082] [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: 12/14/2021] [Revised: 08/26/2022] [Accepted: 09/20/2022] [Indexed: 02/02/2023]
Abstract
BACKGROUND The connection between vascular and brain metrics is well-studied in older adults, but neglected in youth and in psychiatric populations at increased cardiovascular risk. We therefore examined the association of retinal vascular caliber with cerebral blood flow (CBF) in adolescents with and without bipolar disorder (BD). METHODS Ninety-four adolescents (n = 48 BD, n = 46 controls) completed retinal fundus imaging, yielding estimates of arteriolar and venular diameter. Arterial spin labelling MRI was performed to measure CBF. We tested for associations between retinal vascular caliber and CBF in regions of interest; anterior cingulate cortex (ACC), middle frontal gyrus, and hippocampus in BD and controls separately. Complementary voxel-wise analyses were also performed. RESULTS In the BD group, higher arteriovenous ratio (AVR) was associated with greater ACC CBF (β = 0.34, puncorrected = 0.02), after controlling for age, sex, and BMI, however this finding did not survive correction for multiple comparisons. The control group did not show any associations (β = 0.13, puncorrected = 0.40). Voxel-wise analyses within the BD group detected a significant positive association between AVR and regional CBF in two distinct clusters: i) left hippocampus (p < 0.0001); ii) right middle temporal gyrus (p = 0.04). LIMITATIONS Limited sample size; young, medically healthy sample limits signal detection; cross-sectional design. CONCLUSION This study reveals that higher AVR is associated with higher regional CBF in adolescents with BD. Present findings advance understanding of potential neurofunctional mechanisms linking retinal vascular caliber with psychiatric diagnoses. This proof-of-concept study was designed to generate initial insights to guide future studies focusing on the vascular-brain connection in youth and in psychiatry.
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Affiliation(s)
- Megan Mio
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, Canada; Department of Pharmacology and Toxicology, University of Toronto, Toronto, Canada.
| | - Anahit Grigorian
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, Canada
| | - Yi Zou
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, Canada; Department of Pharmacology and Toxicology, University of Toronto, Toronto, Canada
| | - Mikaela K Dimick
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, Canada; Department of Pharmacology and Toxicology, University of Toronto, Toronto, Canada
| | - Beth Selkirk
- John and Liz Tory Eye Centre, Department of Ophthalmology and Vision Sciences, Sunnybrook Health Sciences Centre, Canada
| | - Peter Kertes
- John and Liz Tory Eye Centre, Department of Ophthalmology and Vision Sciences, Sunnybrook Health Sciences Centre, Canada; University of Toronto, Ophthalmology and Vision Sciences, Toronto, Canada
| | - Brian W McCrindle
- Labatt Family Heart Centre, Hospital for Sick Children, Toronto, Canada; Department of Pediatrics, Faculty of Medicine, University of Toronto, Toronto, Canada
| | - Walter Swardfager
- Department of Pharmacology and Toxicology, University of Toronto, Toronto, Canada; Hurvitz Brain Sciences Research Program, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Margaret K Hahn
- Schizophrenia Department, Centre for Addiction and Mental Health, Toronto, Canada; Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Sandra E Black
- Hurvitz Brain Sciences Research Program, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Bradley J MacIntosh
- Hurvitz Brain Sciences Research Program, Sunnybrook Health Sciences Centre, Toronto, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Benjamin I Goldstein
- Centre for Youth Bipolar Disorder, Centre for Addiction and Mental Health, Toronto, Canada; Department of Pharmacology and Toxicology, University of Toronto, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada
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9
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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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10
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Abstract
Schizophrenia is increasingly recognized as a systemic disease, characterized by dysregulation in multiple physiological systems (eg, neural, cardiovascular, endocrine). Many of these changes are observed as early as the first psychotic episode, and in people at high risk for the disorder. Expanding the search for biomarkers of schizophrenia beyond genes, blood, and brain may allow for inexpensive, noninvasive, and objective markers of diagnosis, phenotype, treatment response, and prognosis. Several anatomic and physiologic aspects of the eye have shown promise as biomarkers of brain health in a range of neurological disorders, and of heart, kidney, endocrine, and other impairments in other medical conditions. In schizophrenia, thinning and volume loss in retinal neural layers have been observed, and are associated with illness progression, brain volume loss, and cognitive impairment. Retinal microvascular changes have also been observed. Abnormal pupil responses and corneal nerve disintegration are related to aspects of brain function and structure in schizophrenia. In addition, studying the eye can inform about emerging cardiovascular, neuroinflammatory, and metabolic diseases in people with early psychosis, and about the causes of several of the visual changes observed in the disorder. Application of the methods of oculomics, or eye-based biomarkers of non-ophthalmological pathology, to the treatment and study of schizophrenia has the potential to provide tools for patient monitoring and data-driven prediction, as well as for clarifying pathophysiology and course of illness. Given their demonstrated utility in neuropsychiatry, we recommend greater adoption of these tools for schizophrenia research and patient care.
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Affiliation(s)
- Steven M Silverstein
- Department of Psychiatry, University of Rochester Medical Center, Rochester, NY, USA
- Department of Ophthalmology, University of Rochester Medical Center, Rochester, NY, USA
- Department of Neuroscience, University of Rochester Medical Center, Rochester, NY, USA
- Center for Visual Science, University of Rochester, Rochester, NY, USA
| | - Joy J Choi
- Department of Psychiatry, University of Rochester Medical Center, Rochester, NY, USA
| | - Kyle M Green
- Department of Ophthalmology, University of Rochester Medical Center, Rochester, NY, USA
| | | | - Rajeev S Ramchandran
- Department of Ophthalmology, University of Rochester Medical Center, Rochester, NY, USA
- Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA
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11
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Association between retinal vascular measures and brain white matter lesions in schizophrenia. Asian J Psychiatr 2022; 70:103042. [PMID: 35219980 DOI: 10.1016/j.ajp.2022.103042] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2021] [Revised: 01/28/2022] [Accepted: 02/17/2022] [Indexed: 11/22/2022]
Abstract
OBJECTIVE Recent studies have examined retinal vascular abnormalities in schizophrenia as retinal vascular imaging is a non-invasive proxy to cerebral microvasculature. However, relation between retinal vascular abnormalities and brain structure is not well examined in schizophrenia. Hence in this study, for the first time, we examined the relationship between retinal vascular measures and brain white matter lesions in schizophrenia. We examined brain white matter lesions as they are considered a predictive marker for future adverse cerebrovascular event. METHODS We acquired retinal vascular images of both eyes using a non-mydriatic camera and calculated retinal vascular diameter, tortuosity, trajectory and fractal dimension using validated methods. All patients underwent Magnetic Resonance Imaging of bran and we computed white matter hypo-intensities using Freesurfer software. We performed a linear regression analysis to examine the relationship between white matter hypo-intensities and retinal vascular measures controlling for age, sex, fasting blood sugar, creatinine, whole-brain volume, and antipsychotic dose. RESULTS The regression model was significant in Schizophrenia patients (R=0.983;R2 =0.966;-F=10.849;p = 0.008) but not in healthy volunteers (R=0.828;R2 =0.686;F=0.182; p = 0.963). Among the retinal vascular measures, arterial tortuosity (β = 0.963;p-0.002), tortuosity (β = -1.002;p = 0.001) and fractal dimension (β = -0.688;p = 0.014) were significant predictors of white matter lesions. DISCUSSION The current study's findings support the conclusion that retinal vascular fractal dimension and tortuosity are associated with changes in cerebral white matter and may be considered proxy markers for cerebral microvasculature in schizophrenia. Considering the relationship between white matter lesions and stroke, these observations could have important clinical implications to screen schizophrenia patients for risk of adverse cerebrovascular event.
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12
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Hsu TW, Bai YM, Tsai SJ, Chen TJ, Liang CS, Chen MH. Risk of retinal disease in patients with bipolar disorder: A nationwide cohort study. Psychiatry Clin Neurosci 2022; 76:106-113. [PMID: 34994991 DOI: 10.1111/pcn.13326] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2021] [Revised: 12/06/2021] [Accepted: 12/21/2021] [Indexed: 12/13/2022]
Abstract
AIMS Patients with brain diseases have been associated with several retinal abnormalities. This study aimed to assess the risk of retinal diseases in patients with bipolar disorder (BD). METHODS This nationwide cohort of 73,271 patients with BD was enrolled between 2001 and 2009. To identify newly diagnosed retinal diseases, the patients were followed to the end of 2011. The control group included 293,084 patients, matched for demographic characteristics and medical and ophthalmological comorbidities. The Kaplan-Meier method was used to estimate incidence rates of retinal diseases. Cox regression was applied to calculate the hazard ratios (HRs) with 95% confidence intervals (CIs) after adjusting for confounders. RESULTS Patients with BD had higher incidence rates of any retinal disease than the controls (1.27% vs 0.48%, P < 0.001), and retinal diseases were diagnosed at a young age (54.23 years [±12.68 years] vs 57.01 years [±13.12 years], P < 0.001). After adjusting for demographic characteristics, physical and ophthalmological comorbidities, and medications, the HR was 3.24 (95% CI, 2.18-4.82) for retinal detachment, 2.35 (95% CI, 1.83-3.03) for primary retinopathy, 2.26 (95% CI, 1.91-2.68) for diabetes retinopathy, 2.39 (95% CI, 1.49-3.82) for hypertensive retinopathy, and 3.46 (95% CI, 2.45-4.89) for retinal vascular complications in patients with BD vs controls. The cumulative daily dose of bipolar medications was not associated with the incidence of any retinal disease. CONCLUSION Patients with BD were associated with a higher risk of retinal detachment, primary retinopathy, diabetes retinopathy, hypertensive retinopathy, and retinal vascular complications than the controls. Further studies are needed to examine the mechanisms mediating these retinal diseases in patients with BD.
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Affiliation(s)
- Tien-Wei Hsu
- Department of Psychiatry, Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan
| | - Ya-Mei Bai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Psychiatry, School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
| | - Shih-Jen Tsai
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Psychiatry, School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
| | - Tzeng-Ji Chen
- Department of Psychiatry, Beitou Branch, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan.,Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan
| | - Chih-Sung Liang
- Department of Family Medicine, Taipei Veterans General Hospital, Taipei, Taiwan.,Institute of Hospital and Health Care Administration, National Yang-Ming University, Taipei, Taiwan
| | - Mu-Hong Chen
- Department of Psychiatry, Taipei Veterans General Hospital, Taipei, Taiwan.,Department of Psychiatry, School of Medicine, College of Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.,Institute of Brain Science, National Yang-Ming University, Taipei, Taiwan
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13
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Appaji A, Harish V, Korann V, Devi P, Jacob A, Padmanabha A, Kumar V, Varambally S, Venkatasubramanian G, Rao SV, Suma HN, Webers CAB, Berendschot TTJM, Rao NP. Deep learning model using retinal vascular images for classifying schizophrenia. Schizophr Res 2022; 241:238-243. [PMID: 35176722 DOI: 10.1016/j.schres.2022.01.058] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Revised: 01/25/2022] [Accepted: 01/29/2022] [Indexed: 12/13/2022]
Abstract
Contemporary psychiatric diagnosis still relies on the subjective symptom report of the patient during a clinical interview by a psychiatrist. Given the significant variability in personal reporting and differences in the skill set of psychiatrists, it is desirable to have objective diagnostic markers that could help clinicians differentiate patients from healthy individuals. A few recent studies have reported retinal vascular abnormalities in patients with schizophrenia (SCZ) using retinal fundus images. The goal of this study was to use a trained convolution neural network (CNN) deep learning algorithm to detect SCZ using retinal fundus images. A total of 327 subjects [139 patients with Schizophrenia (SCZ) and 188 Healthy volunteers (HV)] were recruited, and retinal images were acquired using a fundus camera. The images were preprocessed and fed to a convolution neural network for the classification. The model performance was evaluated using the area under the receiver operating characteristic curve (AUC). The CNN achieved an accuracy of 95% for classifying SCZ and HV with an AUC of 0.98. Findings from the current study suggest the potential utility of deep learning to classify patients with SCZ and assist clinicians in clinical settings. Future studies need to examine the utility of the deep learning model with retinal vascular images as biomarkers in schizophrenia with larger sample sizes.
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Affiliation(s)
- Abhishek Appaji
- Department of Medical Electronics Engineering, B.M.S. College of Engineering, Bangalore, India
| | - Vaishak Harish
- Department of Medical Electronics Engineering, B.M.S. College of Engineering, Bangalore, India
| | - Vittal Korann
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Priyanka Devi
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Arpitha Jacob
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Anantha Padmanabha
- Department of Medical Electronics Engineering, B.M.S. College of Engineering, Bangalore, India
| | - Vijay Kumar
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | | | | | - Shyam Vasudeva Rao
- University Eye Clinic Maastricht, Maastricht University, Maastricht, the Netherlands
| | - H N Suma
- Department of Medical Electronics Engineering, B.M.S. College of Engineering, Bangalore, India
| | - Caroll A B Webers
- University Eye Clinic Maastricht, Maastricht University, Maastricht, the Netherlands
| | - Tos T J M Berendschot
- University Eye Clinic Maastricht, Maastricht University, Maastricht, the Netherlands
| | - Naren P Rao
- National Institute of Mental Health and Neurosciences, Bangalore, India.
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14
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Bannai D, Adhan I, Katz R, Kim LA, Keshavan M, Miller JB, Lizano P. Quantifying Retinal Microvascular Morphology in Schizophrenia Using Swept-Source Optical Coherence Tomography Angiography. Schizophr Bull 2022; 48:80-89. [PMID: 34554256 PMCID: PMC8781445 DOI: 10.1093/schbul/sbab111] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Retinovascular changes are reported on fundus imaging in schizophrenia (SZ). This is the first study to use swept-source optical coherence tomography angiography (OCT-A) to comprehensively examine retinal microvascular changes in SZ. METHODS This study included 30 patients with SZ/schizoaffective disorder (8 early and 15 chronic) and 22 healthy controls (HCs). All assessments were performed at Beth Israel Deaconess Medical Center and Massachusetts Eye and Ear. All participants underwent swept-source OCT-A of right (oculus dextrus [OD]) and left (oculus sinister [OS]) eye, clinical, and cognitive assessments. Macular OCT-A images (6 × 6 mm) were collected with the DRI Topcon Triton for superficial, deep, and choriocapillaris vascular regions. Microvasculature was quantified using vessel density (VD), skeletonized vessel density (SVD), fractal dimension (FD), and vessel diameter index (VDI). RESULTS Twenty-one HCs and 26 SZ subjects were included. Compared to HCs, SZ patients demonstrated higher overall OD superficial SVD, OD choriocapillaris VD, and OD choriocapillaris SVD, which were primarily observed in the central, central and outer superior, and central and outer inferior/superior, respectively. Early-course SZ subjects had significantly higher OD superficial VD, OD choriocapillaris SVD, and OD choriocapillaris FD compared to matched HCs. Higher bilateral (OU) superficial VD correlated with lower Positive and Negative Syndrome Scale (PANSS) positive scores, and higher OU deep VDI was associated with higher PANSS negative scores. CONCLUSIONS AND RELEVANCE These results suggest the presence of microvascular dysfunction associated with early-stage SZ. Clinical associations with microvascular alterations further implicate this hypothesis, with higher measures being associated with worse symptom severity and functioning in early stages and with lower symptom severity and better functioning in later stages.
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Affiliation(s)
- Deepthi Bannai
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Iniya Adhan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Raviv Katz
- Harvard Retinal Imaging Lab, Massachusetts Eye and Ear, Boston, MA, USA
| | - Leo A Kim
- Retina Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
| | - Matcheri Keshavan
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
| | - John B Miller
- Harvard Retinal Imaging Lab, Massachusetts Eye and Ear, Boston, MA, USA
- Retina Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA
| | - Paulo Lizano
- Department of Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Department of Psychiatry, Harvard Medical School, Boston, MA, USA
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15
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Silverstein SM, Lai A, Green KM, Crosta C, Fradkin SI, Ramchandran RS. Retinal Microvasculature in Schizophrenia. Eye Brain 2021; 13:205-217. [PMID: 34335068 PMCID: PMC8318708 DOI: 10.2147/eb.s317186] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2021] [Accepted: 06/15/2021] [Indexed: 01/01/2023] Open
Abstract
PURPOSE Schizophrenia is associated with alterations in neural structure and function of the retina that are similar to changes seen in the retina and brain in multiple neurodegenerative disorders. Preliminary evidence suggests that retinal microvasculature may also be compromised in schizophrenia. The goal of this study was to determine, using optical coherence tomography angiography (OCTA), whether 1) schizophrenia is associated with alterations in retinal microvasculature density; and 2) microvasculature reductions are associated with retinal neural layer thinning and performance on a measure of verbal IQ. PATIENTS AND METHODS Twenty-eight outpatients with schizophrenia or schizoaffective disorder and 37 psychiatrically healthy control subjects completed OCT and OCTA exams, and the Wechsler Test of Adult Reading. RESULTS Schizophrenia patients were characterized by retinal microvasculature density reductions, and enlarged foveal avascular zones, in both eyes. These microvascular abnormalities were generally associated with thinning of retinal neural (macular and peripapillary nerve fiber layer) tissue (but the data were stronger for the left than the right eye) and lower scores on a proxy measure of verbal IQ. First- and later-episode patients did not differ significantly on OCTA findings. CONCLUSION The retinal microvasculature impairments seen in schizophrenia appear to be a biomarker of overall brain health, as is the case for multiple neurological conditions. Additional research is needed, however, to clarify contributions of social disadvantage and medical comorbidities to the findings.
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Affiliation(s)
- Steven M Silverstein
- Department of Psychiatry, University of Rochester Medical Center, Rochester, NY, USA
- Department of Neuroscience, University of Rochester Medical Center, Rochester, NY, USA
- Department of Ophthalmology, University of Rochester Medical Center, Rochester, NY, USA
- Center for Visual Science, University of Rochester, Rochester, NY, USA
| | - Adriann Lai
- Department of Psychiatry, University of Rochester Medical Center, Rochester, NY, USA
| | - Kyle M Green
- Department of Ophthalmology, University of Rochester Medical Center, Rochester, NY, USA
| | - Christen Crosta
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ, USA
| | | | - Rajeev S Ramchandran
- Department of Ophthalmology, University of Rochester Medical Center, Rochester, NY, USA
- Department of Public Health Sciences, University of Rochester Medical Center, Rochester, NY, USA
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16
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Korann V, Appaji A, Jacob A, Devi P, Nagendra B, Chako DM, Padmanabha A, Thonse U, Bharath RD, Kumar V, Varambally S, Venkatasubramanian G, Rao SV, Webers CAB, Berendschot TTJM, Rao NP. Association between retinal vascular caliber and brain structure in schizophrenia. Asian J Psychiatr 2021; 61:102707. [PMID: 34052670 DOI: 10.1016/j.ajp.2021.102707] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/24/2020] [Revised: 05/11/2021] [Accepted: 05/21/2021] [Indexed: 02/07/2023]
Abstract
OBJECTIVE Several lines of research in the last decade have indicated the potential utility of retina as a window to the brain. Emerging evidence suggests abnormalities in retinal vascular caliber in schizophrenia. However, the relationship between retinal vascular measures and brain structure has not been examined in schizophrenia to date. Hence, we examined the relationship between retinal vasculature measured using fundus photography and brain structure measured using magnetic resonance imaging. METHOD We recruited 17 healthy volunteers and 20 patients with schizophrenia. Using a non-mydriatic camera, we captured the images for left and right eyes separately and retinal vascular calibers were calculated using a semi-automated software package. Whole-brain anatomical T1 MPRAGE images were acquired using a 3-Tesla MRI scanner. Whole-brain and regional volume and cortical thickness were calculated using the Freesurfer software package. We used FreeSurfer's QDEC interface to compute vertex-by-vertex for analysis of the volume and cortical thickness. The relation between brain volume, cortical thickness, and retinal vascular caliber was examined using partial correlation and regression analysis. RESULTS There was a significant negative correlation between average CRVE and global cortical mean thickness in schizophrenia but not in healthy. In schizophrenia patients, there was a significant negative correlation between average CRVE and cortical thickness in frontal regions - left rostral middle frontal, left superior frontal, and right caudal middle frontal gyri and posterior brain regions - left lateral occipital gyrus and left posterior cingulate cortex. DISCUSSION The findings of the study suggest potential utility of retinal venular diameter as a proxy marker to abnormal neurodevelopment in schizophrenia.
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Affiliation(s)
- Vittal Korann
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Abhishek Appaji
- Department of Medical Electronics, BMS College of Engineering, Bangalore, India
| | - Arpitha Jacob
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Priyanka Devi
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Bhargavi Nagendra
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Dona Maria Chako
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Ananth Padmanabha
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Umesh Thonse
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Rose Dawn Bharath
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | - Vijay Kumar
- National Institute of Mental Health and Neurosciences, Bangalore, India
| | | | | | - Shyam Vasudeva Rao
- Department of Medical Electronics, BMS College of Engineering, Bangalore, India
| | - Carroll A B Webers
- University Eye Clinic Maastricht, Maastricht University, Maastricht, the Netherlands
| | - Tos T J M Berendschot
- University Eye Clinic Maastricht, Maastricht University, Maastricht, the Netherlands
| | - Naren P Rao
- National Institute of Mental Health and Neurosciences, Bangalore, India.
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17
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DOU PENG, ZHANG YANG, ZHENG RUI, YE YU, MAO JIANBO, LIU LEI, WU MING, SUN MINGZHAI. RETINAL IMAGING AND ANALYSIS USING MACHINE LEARNING WITH INFORMATION FUSION OF THE FUNCTIONAL AND STRUCTURAL FEATURES BASED ON A DUAL-MODAL FUNDUS CAMERA. J MECH MED BIOL 2021. [DOI: 10.1142/s0219519421500305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Retinal diseases and systemic diseases, such as diabetic retinopathy (DR) and Alzheimer’s disease, may manifest themselves in the retina, changing the retinal oxygen saturation ([Formula: see text]) level or the retinal vascular structures. Recent studies explored the correlation of diseases with either retina vascular structures or [Formula: see text] level, but not both due to the lack of proper instrument or methodology. In this study, we applied a dual-modal fundus camera and developed a deep learning-based analysis method to simultaneously acquire and quantify the [Formula: see text] and vascular structures. Deep learning was used to automatically locate the optic discs and segment arterioles and venules of the blood vessels. We then sought to apply machine learning methods, such as random forest (RF) and support vector machine (SVM), to fuse the [Formula: see text] level and retinal vessel parameters as different features to discriminate against the disease from the healthy controls. We showed that the fusion of the functional (oxygen saturation) and structural (vascular parameters) features offers better performance to classify diseased and healthy subjects. For example, we gained a 13.8% and 2.0% increase in the accuracy with fusion using the RF and SVM to classify the nonproliferative DR and the healthy controls.
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Affiliation(s)
- PENG DOU
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, P. R. China
| | - YANG ZHANG
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, P. R. China
| | - RUI ZHENG
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, P. R. China
| | - YU YE
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, P. R. China
| | - JIANBO MAO
- Eye Hospital of Wenzhou Medical University, Wenzhou Medical University, Wenzhou, P. R. China
| | - LEI LIU
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, P. R. China
| | - MING WU
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui 230001, P. R. China
| | - MINGZHAI SUN
- Department of Precision Machinery and Precision Instrumentation, University of Science and Technology of China, Hefei 230026, P. R. China
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18
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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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19
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Liu CH, Kang EYC, Lin YH, Wu WC, Liu ZH, Kuo CF, Lai CC, Hwang YS. Association of ocular diseases with schizophrenia, bipolar disorder, and major depressive disorder: a retrospective case-control, population-based study. BMC Psychiatry 2020; 20:486. [PMID: 33008365 PMCID: PMC7532110 DOI: 10.1186/s12888-020-02881-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/22/2020] [Accepted: 09/19/2020] [Indexed: 01/17/2023] Open
Abstract
BACKGROUND Psychiatric disorders and ocular neurovascular diseases may share a similar pathophysiological route of vascular structures or neurological changes. The aim of this study is to investigate the association between ocular neurovascular diseases and the risk of major psychiatric disorders. METHODS This was a retrospective case-control, population-based study including patients aged ≥20 and were diagnosed between 1997 and 2013. Ocular neurovascular diseases diagnosed between 1997 and 2006 and newly diagnosed psychiatric disorders including bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia between 2007 and 2013 were registered. Patients were propensity-score matched with control groups without psychiatric disorders in each cohort based on selected covariates. RESULTS A total of one million sampled patients in the database were categorized based on their diagnoses; 2243 (37.4% men) were categorized into the BD group, 10,110 (35.2% men) into the MDD group, and 1623 (43.1% men) into the schizophrenia group. In the BD group, all glaucoma (OR 1.49, [1.18-1.89]), open-angle glaucoma (OR 2.08, [1.34-3.24]), and closed-angle glaucoma (OR 2.12, [1.36-3.33]) showed statistical significance of risk. In the MDD group, age-related macular degeneration (OR 1.33, [1.13-1.57]), all glaucoma (OR 1.24, [1.11-1.37]), open-angle glaucoma (OR 1.47, [1.21-1.80]), and dry eye syndrome (OR 1.22, [1.13-1.31]) were associated with a significantly higher risk. In the schizophrenia group, only all glaucoma (OR 1.47, [1.02-2.11]), glaucoma suspect (OR 1.88, [1.01-3.49]), and open-angle glaucoma (OR 2.19, [1.13-4.26]) showed statistical significance. CONCLUSIONS In this population-based study, ocular neurovascular diseases, especially glaucoma, were associated with increased risks of BD, MDD, and schizophrenia.
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Affiliation(s)
- Chun-Hao Liu
- Department of Psychiatry, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan ,Department of Psychiatry, New Taipei Municipal Tu-Cheng Hospital, New Taipei, Taiwan ,grid.145695.aCollege of Medicine, Chang Gung University, Taoyuan, Taiwan ,grid.260567.00000 0000 8964 3950Department of Sinophone Literatures, National Dong Hwa University, Hualien, Taiwan
| | - Eugene Yu-Chuan Kang
- grid.145695.aCollege of Medicine, Chang Gung University, Taoyuan, Taiwan ,Department of Ophthalmology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan
| | - Yu-Hsiang Lin
- grid.145695.aCollege of Medicine, Chang Gung University, Taoyuan, Taiwan ,Department of Urology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan ,grid.145695.aGraduate Institute of Clinical Medical Sciences, College of Medicine, Chang Gung University, Taoyuan, Taiwan
| | - Wei-Chi Wu
- grid.145695.aCollege of Medicine, Chang Gung University, Taoyuan, Taiwan ,Department of Ophthalmology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan
| | - Zhuo-Hao Liu
- grid.145695.aCollege of Medicine, Chang Gung University, Taoyuan, Taiwan ,Department of Neurosurgery, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan
| | - Chang-Fu Kuo
- grid.145695.aCollege of Medicine, Chang Gung University, Taoyuan, Taiwan ,Department of Rheumatology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan
| | - Chi-Chun Lai
- grid.145695.aCollege of Medicine, Chang Gung University, Taoyuan, Taiwan ,Department of Ophthalmology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan
| | - Yih-Shiou Hwang
- College of Medicine, Chang Gung University, Taoyuan, Taiwan. .,Department of Ophthalmology, Chang Gung Memorial Hospital, Linkou Medical Center, Taoyuan, Taiwan.
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20
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M T, Annamalai A. Telepsychiatry and the Role of Artificial Intelligence in Mental Health in Post-COVID-19 India: A Scoping Review on Opportunities. Indian J Psychol Med 2020; 42:428-434. [PMID: 33414589 PMCID: PMC7750848 DOI: 10.1177/0253717620952160] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 08/01/2020] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND COVID-19 has a profound impact on people with existing mental disorders, augmenting the prevailing inequalities in mental health. METHODS In order to understand the status of telepsychiatry in India and the role of artificial intelligence (AI) in mental health and its potential applications, a scoping review was done between March 2020 and May 2020. The literature review revealed 253 papers, which were used to derive the primary framework for analysis. The information was then reviewed for ideas and concepts, which were integrated with evidence from gray literature and categorized under broader themes based on the insights derived. Finally, a thematic framework was developed for discussion to tailor scientific information for decision-makers' needs. RESULTS Review findings are summarized under the following headings: changing patterns of health-seeking behavior, origin and evolution of telepsychiatry, possible applications of telepsychiatry and AI, technological features, and AI models in mental health. CONCLUSIONS Though there are several potential opportunities, the time is not yet ripe for telepsychiatry and AI to be adopted fully in the field of mental health care. But it is time that we develop indigenous proprietary technology and test and validate it. With many solutions offered by telepsychiatry and AI, psychiatrists must choose an appropriate tool based on their requirements, availability of resources, and feasibility of deployment. Harmony between conventional care and technology-based care must be reached gradually.
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Affiliation(s)
- Thenral M
- Shri Sathya Sai Medical College and
Research Institute, Kanchipuram, Tamil Nadu, India
| | - Arunkumar Annamalai
- National Institute of Epidemiology,
Indian Council of Medical Research, Chennai, Tamil Nadu, India
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21
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Goldstein BI, Baune BT, Bond DJ, Chen P, Eyler L, Fagiolini A, Gomes F, Hajek T, Hatch J, McElroy SL, McIntyre RS, Prieto M, Sylvia LG, Tsai S, Kcomt A, Fiedorowicz JG. Call to action regarding the vascular-bipolar link: A report from the Vascular Task Force of the International Society for Bipolar Disorders. Bipolar Disord 2020; 22:440-460. [PMID: 32356562 PMCID: PMC7522687 DOI: 10.1111/bdi.12921] [Citation(s) in RCA: 59] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
OBJECTIVES The association of bipolar disorder with early and excessive cardiovascular disease was identified over a century ago. Nonetheless, the vascular-bipolar link remains underrecognized, particularly with regard to how this link can contribute to our understanding of pathogenesis and treatment. METHODS An international group of experts completed a selective review of the literature, distilling core themes, identifying limitations and gaps in the literature, and highlighting future directions to bridge these gaps. RESULTS The association between bipolar disorder and vascular disease is large in magnitude, consistent across studies, and independent of confounding variables where assessed. The vascular-bipolar link is multifactorial and is difficult to study given the latency between the onset of bipolar disorder, often in adolescence or early adulthood, and subsequent vascular disease, which usually occurs decades later. As a result, studies have often focused on risk factors for vascular disease or intermediate phenotypes, such as structural and functional vascular imaging measures. There is interest in identifying the most relevant mediators of this relationship, including lifestyle (eg, smoking, diet, exercise), medications, and systemic biological mediators (eg, inflammation). Nonetheless, there is a paucity of treatment studies that deliberately engage these mediators, and thus far no treatment studies have focused on engaging vascular imaging targets. CONCLUSIONS Further research focused on the vascular-bipolar link holds promise for gleaning insights regarding the underlying causes of bipolar disorder, identifying novel treatment approaches, and mitigating disparities in cardiovascular outcomes for people with bipolar disorder.
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Affiliation(s)
- Benjamin I. Goldstein
- Centre for Youth Bipolar DisorderSunnybrook Health Sciences CentreTorontoONCanada,Departments of Psychiatry & PharmacologyFaculty of MedicineUniversity of TorontoTorontoONCanada
| | - Bernhard T. Baune
- Department of Psychiatry and PsychotherapyUniversity of MünsterMünsterGermany,Department of PsychiatryMelbourne Medical SchoolThe University of MelbourneMelbourneVICAustralia,The Florey Institute of Neuroscience and Mental HealthThe University of MelbourneParkvilleVICAustralia
| | - David J. Bond
- Department of Psychiatry and Behavioral ScienceUniversity of Minnesota Medical SchoolMinneapolisMNUSA
| | - Pao‐Huan Chen
- Department of PsychiatryTaipei Medical University HospitalTaipeiTaiwan,Department of PsychiatrySchool of MedicineCollege of MedicineTaipei Medical UniversityTaipeiTaiwan
| | - Lisa Eyler
- Department of PsychiatryUniversity of California San DiegoSan DiegoCAUSA
| | | | - Fabiano Gomes
- Department of PsychiatryQueen’s University School of MedicineKingstonONCanada
| | - Tomas Hajek
- Department of PsychiatryDalhousie UniversityHalifaxNSCanada,National Institute of Mental HealthKlecanyCzech Republic
| | - Jessica Hatch
- Centre for Youth Bipolar DisorderSunnybrook Health Sciences CentreTorontoONCanada,Departments of Psychiatry & PharmacologyFaculty of MedicineUniversity of TorontoTorontoONCanada
| | - Susan L. McElroy
- Department of Psychiatry and Behavioral NeuroscienceUniversity of Cincinnati College of MedicineCincinnatiOHUSA,Lindner Center of HOPEMasonOHUSA
| | - Roger S. McIntyre
- Departments of Psychiatry & PharmacologyFaculty of MedicineUniversity of TorontoTorontoONCanada,Mood Disorders Psychopharmacology UnitUniversity Health NetworkTorontoONCanada
| | - Miguel Prieto
- Department of PsychiatryFaculty of MedicineUniversidad de los AndesSantiagoChile,Mental Health ServiceClínica Universidad de los AndesSantiagoChile,Department of Psychiatry and PsychologyMayo Clinic College of Medicine and ScienceRochesterMNUSA
| | - Louisa G. Sylvia
- Department of PsychiatryMassachusetts General HospitalBostonMAUSA,Department of PsychiatryHarvard Medical SchoolCambridgeMAUSA
| | - Shang‐Ying Tsai
- Department of PsychiatryTaipei Medical University HospitalTaipeiTaiwan,Department of PsychiatrySchool of MedicineCollege of MedicineTaipei Medical UniversityTaipeiTaiwan
| | - Andrew Kcomt
- Hope+Me—Mood Disorders Association of OntarioTorontoONCanada
| | - Jess G. Fiedorowicz
- Departments of Psychiatry, Internal Medicine, & EpidemiologyCarver College of MedicineUniversity of IowaIowa CityIAUSA
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