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Amudaria S, Jawhar SJ. MIMI-ONET: Multi-Modal image augmentation via Butterfly Optimized neural network for Huntington DiseaseDetection. Brain Res 2025; 1855:149530. [PMID: 40010625 DOI: 10.1016/j.brainres.2025.149530] [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: 12/23/2024] [Revised: 02/18/2025] [Accepted: 02/22/2025] [Indexed: 02/28/2025]
Abstract
Huntington's disease (HD) is a chronic neurodegenerative ailment that affects cognitive decline, motor impairment, and psychiatric symptoms. However, the existing HD detection methods are struggle with limited annotated datasets that restricts their generalization performance. This research work proposes a novel MIMI-ONET for primary detection of HD using augmented multi-modal brain MRI images. The two-dimensional stationary wavelet transform (2DSWT) decomposes the MRI images into different frequency wavelet sub-bands. These sub-bands are enhanced with Contract Stretching Adaptive Histogram Equalization (CSAHE) and Multi-scale Adaptive Retinex (MSAR) by reducing the irrelevant distortions. The proposed MIMI-ONET introduces a Hepta Generative Adversarial Network (Hepta-GAN) to generates different noise-free HD images based on hepta azimuth angles (45°, 90°, 135°, 180°, 225°, 270°, 315°). Hepta-GAN incorporates Affine Estimation Module (AEM) to extract the multi-scale features using dilated convolutional layers for efficient HD image generation. Moreover, Hepta-GAN is normalized with Butterfly Optimization (BO) algorithm for enhancing augmentation performance by balancing the parameters. Finally, the generated images are given to Deep neural network (DNN) for the classification of normal control (NC), Adult-Onset HD (AHD) and Juvenile HD (JHD) cases. The ability of the proposed MIMI-ONET is evaluated with precision, specificity, f1 score, recall, and accuracy, PSNR and MSE. From the experimental results, the proposed MIMI-ONET attains the accuracy of 98.85% and reaches PSNR value of 48.05 based on the gathered Image-HD dataset. The proposed MIMI-ONET increases the overall accuracy of 9.96%, 1.85%, 5.91%, 13.80% and 13.5% for 3DCNN, KNN, FCN, RNN and ML framework respectively.
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Affiliation(s)
- S Amudaria
- Department of Computer Science and Engineering, Arunachala College of Engineering for Women, Manavilai, Nagercoil, Tamil Nadu, India.
| | - S Joseph Jawhar
- Department of Electrical and Electronics Engineering, Arunachala College of Engineering for Women, Manavilai, Nagercoil, Tamil Nadu, India
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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] [Grants] [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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Carriello MA, Costa DFB, Alvim PHP, Pestana MC, Bicudo DDS, Gomes EMP, Coelho TA, Biava PJ, Berlitz VG, Bianchini AJ, Shiokawa A, Shiokawa N, Sato MT, Massuda R. Retinal layers and symptoms and inflammation in schizophrenia. Eur Arch Psychiatry Clin Neurosci 2024; 274:1115-1124. [PMID: 36928482 DOI: 10.1007/s00406-023-01583-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 02/26/2023] [Indexed: 03/18/2023]
Abstract
Schizophrenia is a neurodevelopmental disorder that affects brain structure and function. The retina, as well as the brain, consists of neuronal and glial cells packed in layers. Cortical volume and brain thickness are associated with inflammatory biomarkers, however, no study has been performed associating inflammatory biomarkers and retina in schizophrenia. our study aims to compare the retinal macular thickness and volume and peripapillary thickness in patients with schizophrenia and controls, and associate it to symptoms of schizophrenia, to interleukin-6 (IL-6) and C Reactive Protein (CRP) levels. Optical coherence tomography was performed to assess retinal layer thickness and volume, and CRP and IL-6 levels were measured in patients with schizophrenia and controls. Positive, negative, and general symptoms of schizophrenia were measured with the Positive and Negative Syndrome Scale (PANSS). A linear regression controlling for confounding factors was performed. 70 subjects were included, 35 patients, and 35 controls matched for sex and age. Patients with schizophrenia presented a significantly lower macular volume (p < 0.05) and thickness (< 0.05) than controls. PANSS positive, general and total scores were associated with retinal nerve fiber layer (RNFL) thickness (p < 0.05). There was no association between inflammatory markers (CRP and IL-6) levels and the retinal layer. A reduction in macular volume and thickness was found in patients with schizophrenia. The severity of schizophrenia symptoms was associated with RNFL thickness. CRP and IL-6 are not associated with retinal thickness/volume in schizophrenia or controls.
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Affiliation(s)
- Marcelo Alves Carriello
- Psychotic Disorders Research Program, Department of Psychiatry, Universidade Federal Do Paraná-UFPR, Curitiba, Brazil.
| | - Diogo F Bornancin Costa
- Psychotic Disorders Research Program, Department of Psychiatry, Universidade Federal Do Paraná-UFPR, Curitiba, Brazil
| | - Pedro Henrique Pereira Alvim
- Psychotic Disorders Research Program, Department of Psychiatry, Universidade Federal Do Paraná-UFPR, Curitiba, Brazil
| | - Mariana Camargo Pestana
- Psychotic Disorders Research Program, Department of Psychiatry, Universidade Federal Do Paraná-UFPR, Curitiba, Brazil
| | - Duana Dos Santos Bicudo
- Psychotic Disorders Research Program, Department of Psychiatry, Universidade Federal Do Paraná-UFPR, Curitiba, Brazil
| | - Eloisa Maria Pontarolo Gomes
- Psychotic Disorders Research Program, Department of Psychiatry, Universidade Federal Do Paraná-UFPR, Curitiba, Brazil
| | - Tamires Amelotti Coelho
- Psychotic Disorders Research Program, Department of Psychiatry, Universidade Federal Do Paraná-UFPR, Curitiba, Brazil
| | - Patrick Junior Biava
- Psychotic Disorders Research Program, Department of Psychiatry, Universidade Federal Do Paraná-UFPR, Curitiba, Brazil
| | - Vitória Gabriela Berlitz
- Psychotic Disorders Research Program, Department of Psychiatry, Universidade Federal Do Paraná-UFPR, Curitiba, Brazil
| | - Ana J Bianchini
- Psychotic Disorders Research Program, Department of Psychiatry, Universidade Federal Do Paraná-UFPR, Curitiba, Brazil
| | - Aline Shiokawa
- Retina and Vitreous Ophthalmology-Curitiba, Curitiba, Brazil
| | - Naoye Shiokawa
- Retina and Vitreous Ophthalmology-Curitiba, Curitiba, Brazil
| | - Mario Teruo Sato
- Retina and Vitreous Ophthalmology-Curitiba, Curitiba, Brazil
- Department of Ophthalmology, Universidade Federal Do Paraná-UFPR, Curitiba, Brazil
| | - Raffael Massuda
- Psychotic Disorders Research Program, Department of Psychiatry, Universidade Federal Do Paraná-UFPR, Curitiba, Brazil
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Patterson EJ, Bounds AD, Wagner SK, Kadri-Langford R, Taylor R, Daly D. Oculomics: A Crusade Against the Four Horsemen of Chronic Disease. Ophthalmol Ther 2024; 13:1427-1451. [PMID: 38630354 PMCID: PMC11109082 DOI: 10.1007/s40123-024-00942-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2024] [Accepted: 03/25/2024] [Indexed: 05/22/2024] Open
Abstract
Chronic, non-communicable diseases present a major barrier to living a long and healthy life. In many cases, early diagnosis can facilitate prevention, monitoring, and treatment efforts, improving patient outcomes. There is therefore a critical need to make screening techniques as accessible, unintimidating, and cost-effective as possible. The association between ocular biomarkers and systemic health and disease (oculomics) presents an attractive opportunity for detection of systemic diseases, as ophthalmic techniques are often relatively low-cost, fast, and non-invasive. In this review, we highlight the key associations between structural biomarkers in the eye and the four globally leading causes of morbidity and mortality: cardiovascular disease, cancer, neurodegenerative disease, and metabolic disease. We observe that neurodegenerative disease is a particularly promising target for oculomics, with biomarkers detected in multiple ocular structures. Cardiovascular disease biomarkers are present in the choroid, retinal vasculature, and retinal nerve fiber layer, and metabolic disease biomarkers are present in the eyelid, tear fluid, lens, and retinal vasculature. In contrast, only the tear fluid emerged as a promising ocular target for the detection of cancer. The retina is a rich source of oculomics data, the analysis of which has been enhanced by artificial intelligence-based tools. Although not all biomarkers are disease-specific, limiting their current diagnostic utility, future oculomics research will likely benefit from combining data from various structures to improve specificity, as well as active design, development, and optimization of instruments that target specific disease signatures, thus facilitating differential diagnoses.
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Affiliation(s)
| | | | - Siegfried K Wagner
- Moorfields Eye Hospital NHS Trust, 162 City Road, London, EC1V 2PD, UK
- UCL Institute of Ophthalmology, University College London, 11-43 Bath Street, London, EC1V 9EL, UK
| | | | - Robin Taylor
- Occuity, The Blade, Abbey Square, Reading, Berkshire, RG1 3BE, UK
| | - Dan Daly
- Occuity, The Blade, Abbey Square, Reading, Berkshire, RG1 3BE, UK
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Komatsu H, Onoguchi G, Silverstein SM, Jerotic S, Sakuma A, Kanahara N, Kakuto Y, Ono T, Yabana T, Nakazawa T, Tomita H. Retina as a potential biomarker in schizophrenia spectrum disorders: a systematic review and meta-analysis of optical coherence tomography and electroretinography. Mol Psychiatry 2024; 29:464-482. [PMID: 38081943 PMCID: PMC11116118 DOI: 10.1038/s41380-023-02340-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/24/2023] [Revised: 11/16/2023] [Accepted: 11/23/2023] [Indexed: 05/25/2024]
Abstract
INTRODUCTION Abnormal findings on optical coherence tomography (OCT) and electroretinography (ERG) have been reported in participants with schizophrenia spectrum disorders (SSDs). This study aims to reveal the pooled standard mean difference (SMD) in retinal parameters on OCT and ERG among participants with SSDs and healthy controls and their association with demographic characteristics, clinical symptoms, smoking, diabetes mellitus, and hypertension. METHODS Using PubMed, Scopus, Web of Science, and PSYNDEX, we searched the literature from inception to March 31, 2023, using specific search terms. This study was registered with PROSPERO (CRD4202235795) and conducted according to PRISMA 2020. RESULTS We included 65 studies in the systematic review and 44 in the meta-analysis. Participants with SSDs showed thinning of the peripapillary retinal nerve fiber layer (pRNFL), macular ganglion cell layer- inner plexiform cell layer, and retinal thickness in all other segments of the macula. A meta-analysis of studies that excluded SSD participants with diabetes and hypertension showed no change in results, except for pRNFL inferior and nasal thickness. Furthermore, a significant difference was found in the pooled SMD of pRNFL temporal thickness between the left and right eyes. Meta-regression analysis revealed an association between retinal thinning and duration of illness, positive and negative symptoms. In OCT angiography, no differences were found in the foveal avascular zone and superficial layer foveal vessel density between SSD participants and controls. In flash ERG, the meta-analysis showed reduced amplitude of both a- and b-waves under photopic and scotopic conditions in SSD participants. Furthermore, the latency of photopic a-wave was significantly shorter in SSD participants in comparison with HCs. DISCUSSION Considering the prior report of retinal thinning in unaffected first-degree relatives and the results of the meta-analysis, the findings suggest that retinal changes in SSDs have both trait and state aspects. Future longitudinal multimodal retinal imaging studies are needed to clarify the pathophysiological mechanisms of these changes and to clarify their utility in individual patient monitoring efforts.
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Affiliation(s)
- Hiroshi Komatsu
- Department of Psychiatry, Tohoku University Hospital, Sendai, Japan.
- Miyagi Psychiatric Center, Natori, Japan.
| | - Goh Onoguchi
- Department of Psychiatry, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Steven M Silverstein
- Department of Psychiatry, University of Rochester Medical Center, Rochester, NY, USA
| | - Stefan Jerotic
- Clinic for Psychiatry, University Clinical Centre of Serbia, Belgrade, Serbia
- Faculty of Medicine, University of Belgrade, Belgrade, Serbia
| | - Atsushi Sakuma
- Department of Psychiatry, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Nobuhisa Kanahara
- Department of Psychiatry, Chiba University Graduate School of Medicine, Chiba, Japan
- Division of Medical Treatment and Rehabilitation, Chiba University Center for Forensic Mental Health, Chiba, Japan
| | - Yoshihisa Kakuto
- Miyagi Psychiatric Center, Natori, Japan
- Department of Community Psychiatry, Tohoku University Graduate School of Medicine, Sendai, Japan
| | | | - Takeshi Yabana
- Department of Ophthalmology, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Toru Nakazawa
- Department of Ophthalmology, Tohoku University Graduate School of Medicine, Sendai, Japan
- Department of Ophthalmic Imaging and Information Analytics, Tohoku University Graduate School of Medicine, Sendai, Japan
- Department of Retinal Disease Control, Tohoku University Graduate School of Medicine, Sendai, Japan
- Department of Advanced Ophthalmic Medicine, Tohoku University Graduate School of Medicine, Sendai, Japan
| | - Hiroaki Tomita
- Department of Psychiatry, Tohoku University Hospital, Sendai, Japan
- Department of Psychiatry, Tohoku University Graduate School of Medicine, Sendai, Japan
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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: 1.0] [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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Janti SS, Tikka SK. Retinal microvasculature in schizophrenia: A meta-analysis with trial sequential analysis of studies assessing vessel density using Optical Coherence Tomography Angiography. Asian J Psychiatr 2023; 84:103570. [PMID: 37030089 DOI: 10.1016/j.ajp.2023.103570] [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: 02/23/2023] [Revised: 03/24/2023] [Accepted: 03/25/2023] [Indexed: 04/10/2023]
Abstract
We performed a series of random-effects meta-analyses on cross-sectional studies assessing vessel density (VD) using Optical Coherence Tomography Angiography (OCTA) in schizophrenia. Five studies with a total sample size of 410 (schizophrenia-192;healthy-218) were analysed. Supplementary Trial Sequential Analyses (TSA) was also performed. Meta-analyses revealed significantly lower VD in schizophrenia patients compared to healthy controls in the peripapillary region of the optic disc, including both superior hemisphere and inferior hemisphere. TSA validated these significant effects. We conclude that reduced VD at the peripapillary region of the optic disc as measured by OCTA may have the potential to be a schizophrenia biomarker.
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Affiliation(s)
- Siddharam S Janti
- Department of Ophthalmology, All India Institute of Medical Sciences, Bibinagar, Hyderabad, Telangana, India
| | - Sai Krishna Tikka
- Department of Psychiatry, All India Institute of Medical Sciences, Bibinagar, Hyderabad, Telangana, India.
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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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