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Zhao B, Li Y, Fan Z, Wu Z, Shu J, Yang X, Yang Y, Wang X, Li B, Wang X, Copana C, Yang Y, Lin J, Li Y, Stein JL, O'Brien JM, Li T, Zhu H. Eye-brain connections revealed by multimodal retinal and brain imaging genetics. Nat Commun 2024; 15:6064. [PMID: 39025851 PMCID: PMC11258354 DOI: 10.1038/s41467-024-50309-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 07/02/2024] [Indexed: 07/20/2024] Open
Abstract
The retina, an anatomical extension of the brain, forms physiological connections with the visual cortex of the brain. Although retinal structures offer a unique opportunity to assess brain disorders, their relationship to brain structure and function is not well understood. In this study, we conducted a systematic cross-organ genetic architecture analysis of eye-brain connections using retinal and brain imaging endophenotypes. We identified novel phenotypic and genetic links between retinal imaging biomarkers and brain structure and function measures from multimodal magnetic resonance imaging (MRI), with many associations involving the primary visual cortex and visual pathways. Retinal imaging biomarkers shared genetic influences with brain diseases and complex traits in 65 genomic regions, with 18 showing genetic overlap with brain MRI traits. Mendelian randomization suggests bidirectional genetic causal links between retinal structures and neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, our findings reveal the genetic basis for eye-brain connections, suggesting that retinal images can help uncover genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.
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Affiliation(s)
- Bingxin Zhao
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA.
- Applied Mathematics and Computational Science Graduate Group, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Center for AI and Data Science for Integrated Diagnostics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Penn Institute for Biomedical Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Population Aging Research Center, University of Pennsylvania, Philadelphia, PA, 19104, USA.
- Institute for Translational Medicine and Therapeutics, University of Pennsylvania, Philadelphia, PA, 19104, USA.
| | - Yujue Li
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Zirui Fan
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Zhenyi Wu
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Juan Shu
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Xiaochen Yang
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Yilin Yang
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - Xifeng Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Bingxuan Li
- Department of Computer Science, Purdue University, West Lafayette, IN, 47907, USA
| | - Xiyao Wang
- Department of Computer Science, Purdue University, West Lafayette, IN, 47907, USA
| | - Carlos Copana
- Department of Statistics, Purdue University, West Lafayette, IN, 47907, USA
| | - Yue Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Jinjie Lin
- Yale School of Management, Yale University, New Haven, CT, 06511, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Jason L Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Joan M O'Brien
- Scheie Eye Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Penn Medicine Center for Ophthalmic Genetics in Complex Diseases, Philadelphia, PA, 19104, USA
| | - Tengfei Li
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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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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Williams LM, Carpenter WT, Carretta C, Papanastasiou E, Vaidyanathan U. Precision psychiatry and Research Domain Criteria: Implications for clinical trials and future practice. CNS Spectr 2024; 29:26-39. [PMID: 37675453 DOI: 10.1017/s1092852923002420] [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] [Indexed: 09/08/2023]
Abstract
Psychiatric disorders are associated with significant social and economic burdens, many of which are related to issues with current diagnosis and treatments. The coronavirus (COVID-19) pandemic is estimated to have increased the prevalence and burden of major depressive and anxiety disorders, indicating an urgent need to strengthen mental health systems globally. To date, current approaches adopted in drug discovery and development for psychiatric disorders have been relatively unsuccessful. Precision psychiatry aims to tailor healthcare more closely to the needs of individual patients and, when informed by neuroscience, can offer the opportunity to improve the accuracy of disease classification, treatment decisions, and prevention efforts. In this review, we highlight the growing global interest in precision psychiatry and the potential for the National Institute of Health-devised Research Domain Criteria (RDoC) to facilitate the implementation of transdiagnostic and improved treatment approaches. The need for current psychiatric nosology to evolve with recent scientific advancements and increase awareness in emerging investigators/clinicians of the value of this approach is essential. Finally, we examine current challenges and future opportunities of adopting the RDoC-associated translational and transdiagnostic approaches in clinical studies, acknowledging that the strength of RDoC is that they form a dynamic framework of guiding principles that is intended to evolve continuously with scientific developments into the future. A collaborative approach that recruits expertise from multiple disciplines, while also considering the patient perspective, is needed to pave the way for precision psychiatry that can improve the prognosis and quality of life of psychiatric patients.
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Affiliation(s)
- Leanne M Williams
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
- Sierra-Pacific Mental Illness Research, Education, and Clinical Center (MIRECC), Veterans Affairs Palo Alto Health Care System, Palo Alto, CA, USA
| | - William T Carpenter
- Department of Psychiatry, University of Maryland School of Medicine, Baltimore, MD, USA
| | | | - Evangelos Papanastasiou
- Boehringer Ingelheim Pharma GmbH & Co, Ingelheim am Rhein, Rhineland-Palatinate, Germany
- HMNC Holding GmbH, Wilhelm-Wagenfeld-Strasse 20, 80807Munich, Bavaria, Germany
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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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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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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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Shoham N, Lewis G, Hayes JF, Silverstein SM, Cooper C. Association between visual impairment and psychosis: A longitudinal study and nested case-control study of adults. Schizophr Res 2023; 254:81-89. [PMID: 36805651 DOI: 10.1016/j.schres.2023.02.017] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Revised: 01/08/2023] [Accepted: 02/09/2023] [Indexed: 02/20/2023]
Abstract
BACKGROUND Theories propose that visual impairment might increase the risk of psychosis, and vice versa. We aimed to investigate the relationship between visual impairment and psychosis in the UK Biobank cohort. STUDY DESIGN In a nested case control study of ~116,000 adults, we tested whether a Schizophrenia Spectrum Disorder (SSD) diagnosis as exposure was associated with visual impairment. We also tested longitudinally whether poorer visual acuity, and thinner retinal structures on Optical Coherence Tomography (OCT) scans in 2009 were associated with psychotic experiences in 2016. We adjusted for age, sex, depression and anxiety symptoms; and socioeconomic variables and vascular risk factors where appropriate. We compared complete case with multiple imputation models, designed to reduce bias potentially introduced by missing data. RESULTS People with visual impairment had greater odds of SSD than controls in multiply imputed data (Adjusted Odds Ratio [AOR] 1.42, 95 % Confidence Interval [CI] 1.05-1.93, p = 0.021). We also found evidence that poorer visual acuity was associated with psychotic experiences during follow-up (AOR per 0.1 point worse visual acuity score 1.06, 95 % CI 1.01-1.11, p = 0.020; and 1.04, 95 % CI 1.00-1.08, p = 0.037 in right and left eye respectively). In complete case data (15 % of this cohort) we found no clear association, although confidence intervals included the multiple imputation effect estimates. OCT measures were not associated with psychotic experiences. CONCLUSIONS Our findings highlight the importance of eye care for people with psychotic illnesses. We could not conclude whether visual impairment is a likely causal risk factor for psychosis.
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Affiliation(s)
- Natalie Shoham
- University College London Division of Psychiatry, 6th Floor Maple House, 149 Tottenham Court Road, London W1T 7NF, UK; Camden and Islington NHS Foundation Trust, St Pancras Hospital, 4 St Pancras Way, London NW1 0PE, UK.
| | - Gemma Lewis
- University College London Division of Psychiatry, 6th Floor Maple House, 149 Tottenham Court Road, London W1T 7NF, UK
| | - Joseph F Hayes
- University College London Division of Psychiatry, 6th Floor Maple House, 149 Tottenham Court Road, London W1T 7NF, UK; Camden and Islington NHS Foundation Trust, St Pancras Hospital, 4 St Pancras Way, London NW1 0PE, UK
| | - Steven M Silverstein
- University of Rochester Medical Center, Department of Psychiatry, 300 Crittenden Boulevard, Rochester, NY 14642, USA; Center for Visual Science, University of Rochester, 601 Elmwood Ave, Rochester, NY 14642, USA
| | - Claudia Cooper
- University College London Division of Psychiatry, 6th Floor Maple House, 149 Tottenham Court Road, London W1T 7NF, UK; Centre for Psychiatry and Mental Health, Wolfson Institute of Population Health, Queen Mary University London, London E1 2AD, UK; East London NHS Foundation Trust, UK
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Zhao B, Li Y, Fan Z, Wu Z, Shu J, Yang X, Yang Y, Wang X, Li B, Wang X, Copana C, Yang Y, Lin J, Li Y, Stein JL, O'Brien JM, Li T, Zhu H. Eye-brain connections revealed by multimodal retinal and brain imaging genetics in the UK Biobank. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.02.16.23286035. [PMID: 36824893 PMCID: PMC9949187 DOI: 10.1101/2023.02.16.23286035] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/19/2023]
Abstract
As an anatomical extension of the brain, the retina of the eye is synaptically connected to the visual cortex, establishing physiological connections between the eye and the brain. Despite the unique opportunity retinal structures offer for assessing brain disorders, less is known about their relationship to brain structure and function. Here we present a systematic cross-organ genetic architecture analysis of eye-brain connections using retina and brain imaging endophenotypes. Novel phenotypic and genetic links were identified between retinal imaging biomarkers and brain structure and function measures derived from multimodal magnetic resonance imaging (MRI), many of which were involved in the visual pathways, including the primary visual cortex. In 65 genomic regions, retinal imaging biomarkers shared genetic influences with brain diseases and complex traits, 18 showing more genetic overlaps with brain MRI traits. Mendelian randomization suggests that retinal structures have bidirectional genetic causal links with neurological and neuropsychiatric disorders, such as Alzheimer's disease. Overall, cross-organ imaging genetics reveals a genetic basis for eye-brain connections, suggesting that the retinal images can elucidate genetic risk factors for brain disorders and disease-related changes in intracranial structure and function.
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Affiliation(s)
- Bingxin Zhao
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Yujue Li
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Zirui Fan
- Department of Statistics and Data Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Zhenyi Wu
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Juan Shu
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Xiaochen Yang
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Yilin Yang
- Department of Computer and Information Science and Electrical and Systems Engineering, School of Engineering & Applied Science, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Xifeng Wang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Bingxuan Li
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
| | - Xiyao Wang
- Department of Computer Science, Purdue University, West Lafayette, IN 47907, USA
| | - Carlos Copana
- Department of Statistics, Purdue University, West Lafayette, IN 47907, USA
| | - Yue Yang
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jinjie Lin
- Yale School of Management, Yale University, New Haven, CT 06511, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Jason L. Stein
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- UNC Neuroscience Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Joan M. O'Brien
- Scheie Eye Institute, University of Pennsylvania, Philadelphia, PA, 19104, USA
- Penn Medicine Center for Ophthalmic Genetics in Complex Diseases, PA, 19104, USA
| | - Tengfei Li
- Department of Radiology, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Biomedical Research Imaging Center, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
| | - Hongtu Zhu
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Computer Science, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- Department of Statistics and Operations Research, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
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Năstase MG, Vlaicu I, Trifu SC, Trifu SC. Genetic polymorphism and neuroanatomical changes in schizophrenia. ROMANIAN JOURNAL OF MORPHOLOGY AND EMBRYOLOGY = REVUE ROUMAINE DE MORPHOLOGIE ET EMBRYOLOGIE 2022; 63:307-322. [PMID: 36374137 PMCID: PMC9801677 DOI: 10.47162/rjme.63.2.03] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
The article is a review of the latest meta-analyses regarding the genetic spectrum in schizophrenia, discussing the risks given by the disrupted-in-schizophrenia 1 (DISC1), catechol-O-methyltransferase (COMT), monoamine oxidases-A∕B (MAO-A∕B), glutamic acid decarboxylase 67 (GAD67) and neuregulin 1 (NRG1) genes, and dysbindin-1 protein. The DISC1 polymorphism significantly increases the risk of schizophrenia, as well injuries from the prefrontal cortex that affect connectivity. NRG1 is one of the most important proteins involved. Its polymorphism is associated with the reduction of areas in the corpus callosum, right uncinate, inferior lateral fronto-occipital fascicle, right external capsule, fornix, right optic tract, gyrus. NRG1 and the ErbB4 receptor (tyrosine kinase receptor) are closely related to the N-methyl-D-aspartate receptor (NMDAR) (glutamate receptor). COMT is located on chromosome 22 and together with interleukin-10 (IL-10) have an anti-inflammatory and immunosuppressive function that influences the dopaminergic system. MAO gene methylation has been associated with mental disorders. MAO-A is a risk gene in the onset of schizophrenia, more precisely a certain type of single-nucleotide polymorphism (SNP), at the gene level, is associated with schizophrenia. In schizophrenia, we find deficits of the γ-aminobutyric acid (GABA)ergic neurotransmitter, the dysfunctions being found predominantly at the level of the substantia nigra. In schizophrenia, missing an allele at GAD67, caused by a SNP, has been correlated with decreases in parvalbumin (PV), somatostatin receptor (SSR), and GAD ribonucleic acid (RNA). Resulting in the inability to mature PV and SSR neurons, which has been associated with hyperactivity.
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Affiliation(s)
- Mihai Gabriel Năstase
- Department of Neurosciences, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania;
| | - Ilinca Vlaicu
- Department of Psychiatry, Hospital for Psychiatry, Săpunari, Călăraşi County, Romania
| | - Simona Corina Trifu
- Department of Neurosciences, Carol Davila University of Medicine and Pharmacy, Bucharest, Romania
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