1
|
Mendez K, Lains I, Kelly RS, Gil J, Silva R, Miller J, Vavvas DG, Kim I, Miller J, Liang L, Lasky-Su JA, Husain D. Metabolomic-derived endotypes of age-related macular degeneration (AMD): a step towards identification of disease subgroups. Sci Rep 2024; 14:12145. [PMID: 38802406 PMCID: PMC11130126 DOI: 10.1038/s41598-024-59045-z] [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: 12/29/2023] [Accepted: 04/05/2024] [Indexed: 05/29/2024] Open
Abstract
Age-related macular degeneration (AMD) is a leading cause of blindness worldwide, with a complex pathophysiology and phenotypic diversity. Here, we apply Similarity Network Fusion (SNF) to cluster AMD patients into putative metabolomics-derived endotypes. Using a discovery cohort of 163 AMD patients from Boston, US, and a validation cohort of 214 patients from Coimbra, Portugal, we identified four distinct metabolomics-derived endotypes with varying retinal structural and functional characteristics, confirmed across both cohorts. Patients clustered into Endotype 1 exhibited a milder form of AMD and were characterized by low levels of amino acids in specific metabolic pathways. Meanwhile, patients clustered into both Endotype 3 and 4 were associated with more severe AMD and exhibited low levels of fatty acid metabolites and elevated levels of sphingomyelins and fatty acid metabolites, respectively. These preliminary findings indicate that metabolomics-derived endotyping may offer a refined strategy for categorizing AMD patients based on their specific pathophysiological underpinnings, rather than relying solely on traditional observational clinical indicators.
Collapse
Affiliation(s)
- Kevin Mendez
- Retina Service, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles Street, Boston, MA, 02114, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Centre for Integrative Metabolomics & Computational Biology, School of Science, Edith Cowan University, Perth, WA, Australia
| | - Ines Lains
- Retina Service, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles Street, Boston, MA, 02114, USA
| | - Rachel S Kelly
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - João Gil
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Rufino Silva
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal
- Department of Ophthalmology, Coimbra Hospital and University Center, Coimbra, Portugal
- Association for Innovation and Biomedical Research in Light and Image (AIBILI), Coimbra, Portugal
| | - John Miller
- Retina Service, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles Street, Boston, MA, 02114, USA
| | - Demetrios G Vavvas
- Retina Service, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles Street, Boston, MA, 02114, USA
| | - Ivana Kim
- Retina Service, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles Street, Boston, MA, 02114, USA
| | - Joan Miller
- Retina Service, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles Street, Boston, MA, 02114, USA
| | - Liming Liang
- Program in Genetic Epidemiology and Statistical Genetics, Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jessica A Lasky-Su
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Deeba Husain
- Retina Service, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles Street, Boston, MA, 02114, USA.
| |
Collapse
|
2
|
Zhang X, Xia M, Wu Y, Zhang F. Branched-Chain Amino Acids Metabolism and Their Roles in Retinopathy: From Relevance to Mechanism. Nutrients 2023; 15:2161. [PMID: 37432261 DOI: 10.3390/nu15092161] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2023] [Revised: 04/20/2023] [Accepted: 04/27/2023] [Indexed: 07/12/2023] Open
Abstract
Retinopathy is one of the leading causes of irreversible blindness and vision loss worldwide. Imbalanced nutrients play important roles in the pathogenesis and pathophysiology of retinal diseases. Branched-Chain Amino Acids (BCAAs), as essential amino acids, perform a variety of biological functions, including protein synthesis, glucose metabolism, lipid metabolism, inflammation, and oxidative stress in metabolic tissues of diabetes and aging-related diseases. Recently, it has been shown that BCAAs are highly related to neuroprotection, oxidative stress, inflammatory and glutamate toxicity in the retina of retinopathy. Therefore, this review summarizes the alterations of BCAA levels in retinopathy, especially diabetic retinopathy and aging-related macular disease, and the genetics, functions, and mechanisms of BCAAs in the retina as well as other metabolic tissues for reference. All of these efforts aim to provide fundamental knowledge of BCAAs for further discoveries and research on retina health based on the sensing and signaling of essential amino acids.
Collapse
Affiliation(s)
- Xiaonan Zhang
- National Clinical Research Center for Eye Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
- Liaoning Provence Key Laboratory of Genome Engineered Animal Models, National Center of Genetically Engineered Animal Models for International Research, Institute for Genome Engineered Animal Models of Human Diseases, Dalian Medical University, Dalian 116000, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
| | - Mengxue Xia
- National Clinical Research Center for Eye Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
| | - Yingjie Wu
- Liaoning Provence Key Laboratory of Genome Engineered Animal Models, National Center of Genetically Engineered Animal Models for International Research, Institute for Genome Engineered Animal Models of Human Diseases, Dalian Medical University, Dalian 116000, China
- Shandong Provincial Hospital, School of Laboratory Animal & Shandong Laboratory Animal Center, Science and Technology Innovation Center, Shandong First Medical University & Shandong Academy of Medical Sciences, Jinan 250021, China
- Department of Molecular Pathobiology, New York University College of Dentistry, New York, NY 10010, USA
| | - Fang Zhang
- National Clinical Research Center for Eye Diseases, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
- Shanghai Key Laboratory of Ocular Fundus Diseases, Shanghai 200080, China
| |
Collapse
|
3
|
Amino Acids Metabolism in Retinopathy: From Clinical and Basic Research Perspective. Metabolites 2022; 12:metabo12121244. [PMID: 36557282 PMCID: PMC9781488 DOI: 10.3390/metabo12121244] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 11/22/2022] [Accepted: 12/06/2022] [Indexed: 12/14/2022] Open
Abstract
Retinopathy, including age-related macular degeneration (AMD), diabetic retinopathy (DR), and retinopathy of prematurity (ROP), are the leading cause of blindness among seniors, working-age populations, and children. However, the pathophysiology of retinopathy remains unclear. Accumulating studies demonstrate that amino acid metabolism is associated with retinopathy. This study discusses the characterization of amino acids in DR, AMD, and ROP by metabolomics from clinical and basic research perspectives. The features of amino acids in retinopathy were summarized using a comparative approach based on existing high-throughput metabolomics studies from PubMed. Besides taking up a large proportion, amino acids appear in both human and animal, intraocular and peripheral samples. Among them, some metabolites differ significantly in all three types of retinopathy, including glutamine, glutamate, alanine, and others. Studies on the mechanisms behind retinal cell death caused by glutamate accumulation are on the verge of making some progress. To develop potential therapeutics, it is imperative to understand amino acid-induced retinal functional alterations and the underlying mechanisms. This review delineates the significance of amino acid metabolism in retinopathy and provides possible direction to discover therapeutic targets for retinopathy.
Collapse
|
4
|
Pucchio A, Krance SH, Pur DR, Miranda RN, Felfeli T. Artificial Intelligence Analysis of Biofluid Markers in Age-Related Macular Degeneration: A Systematic Review. Clin Ophthalmol 2022; 16:2463-2476. [PMID: 35968055 PMCID: PMC9369085 DOI: 10.2147/opth.s377262] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Accepted: 07/26/2022] [Indexed: 11/23/2022] Open
Abstract
This systematic review explores the use of artificial intelligence (AI) in the analysis of biofluid markers in age-related macular degeneration (AMD). We detail the accuracy and validity of AI in diagnostic and prognostic models and biofluid markers that provide insight into AMD pathogenesis and progression. This review was conducted in accordance with the Preferred Reporting Items for a Systematic Review and Meta-analysis guidelines. A comprehensive search was conducted across 5 electronic databases including Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, EMBASE, Medline, and Web of Science from inception to July 14, 2021. Studies pertaining to biofluid marker analysis using AI or bioinformatics in AMD were included. Identified studies were assessed for risk of bias and critically appraised using the Joanna Briggs Institute Critical Appraisal tools. A total of 10,264 articles were retrieved from all databases and 37 studies met the inclusion criteria, including 15 cross-sectional studies, 15 prospective cohort studies, five retrospective cohort studies, one randomized controlled trial, and one case–control study. The majority of studies had a general focus on AMD (58%), while neovascular AMD (nAMD) was the focus in 11 studies (30%), and geographic atrophy (GA) was highlighted by three studies. Fifteen studies examined disease characteristics, 15 studied risk factors, and seven guided treatment decisions. Altered lipid metabolism (HDL-cholesterol, total serum triglycerides), inflammation (c-reactive protein), oxidative stress, and protein digestion were implicated in AMD development and progression. AI tools were able to both accurately differentiate controls and AMD patients with accuracies as high as 87% and predict responsiveness to anti-VEGF therapy in nAMD patients. Use of AI models such as discriminant analysis could inform prognostic and diagnostic decision-making in a clinical setting. The identified pathways provide opportunity for future studies of AMD development and could be valuable in the advancement of novel treatments.
Collapse
Affiliation(s)
- Aidan Pucchio
- School of Medicine, Queen’s University, Kingston, ON, Canada
| | - Saffire H Krance
- Schulich School of Medicine & Dentistry, Western University, London, ON, Canada
| | - Daiana R Pur
- Schulich School of Medicine & Dentistry, Western University, London, ON, Canada
| | - Rafael N Miranda
- Toronto Health Economics and Technology Assessment Collaborative, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
| | - Tina Felfeli
- Toronto Health Economics and Technology Assessment Collaborative, Toronto, ON, Canada
- Institute of Health Policy, Management and Evaluation, University of Toronto, Toronto, ON, Canada
- Department of Ophthalmology and Vision Sciences, University of Toronto, Toronto, ON, Canada
- Correspondence: Tina Felfeli, Department of Ophthalmology and Vision Sciences, University of Toronto, 340 College Street, Suite 400, Toronto, ON, M5T 3A9, Canada, Fax +416-978-4590, Email
| |
Collapse
|
5
|
Plasma Metabolomic Profiles Associated with Three-Year Progression of Age-Related Macular Degeneration. Metabolites 2022; 12:metabo12010032. [PMID: 35050154 PMCID: PMC8780121 DOI: 10.3390/metabo12010032] [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: 11/13/2021] [Revised: 12/22/2021] [Accepted: 12/24/2021] [Indexed: 12/04/2022] Open
Abstract
Plasma metabolomic profiles have been shown to be associated with age-related macular degeneration (AMD) and its severity stages. However, all studies performed to date have been cross-sectional and have not assessed progression of AMD. This prospective, longitudinal, pilot study analyzes, for the first time, the association between plasma metabolomic profiles and progression of AMD over a 3-year period. At baseline and 3 years later, subjects with AMD (n = 108 eyes) and controls (n = 45 eyes) were imaged with color fundus photos for AMD staging and tested for retinal function with dark adaptation (DA). Fasting plasma samples were also collected for metabolomic profiling. AMD progression was considered present if AMD stage at 3 years was more advanced than at baseline (n = 26 eyes, 17%). Results showed that, of the metabolites measured at baseline, eight were associated with 3-year AMD progression (p < 0.01) and 19 (p < 0.01) with changes in DA. Additionally, changes in the levels (i.e., between 3 years and baseline) of 6 and 17 metabolites demonstrated significant associations (p < 0.01) with AMD progression and DA, respectively. In conclusion, plasma metabolomic profiles are associated with clinical and functional progression of AMD at 3 years. These findings contribute to our understanding of mechanisms of AMD progression and the identification of potential therapeutics for this blinding disease.
Collapse
|
6
|
Li X, Cai S, He Z, Reilly J, Zeng Z, Strang N, Shu X. Metabolomics in Retinal Diseases: An Update. BIOLOGY 2021; 10:944. [PMID: 34681043 PMCID: PMC8533136 DOI: 10.3390/biology10100944] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Revised: 09/16/2021] [Accepted: 09/18/2021] [Indexed: 12/17/2022]
Abstract
Retinal diseases are a leading cause of visual loss and blindness, affecting a significant proportion of the population worldwide and having a detrimental impact on quality of life, with consequent economic burden. The retina is highly metabolically active, and a number of retinal diseases are associated with metabolic dysfunction. To better understand the pathogenesis underlying such retinopathies, new technology has been developed to elucidate the mechanism behind retinal diseases. Metabolomics is a relatively new "omics" technology, which has developed subsequent to genomics, transcriptomics, and proteomics. This new technology can provide qualitative and quantitative information about low-molecular-weight metabolites (M.W. < 1500 Da) in a given biological system, which shed light on the physiological or pathological state of a cell or tissue sample at a particular time point. In this article we provide an extensive review of the application of metabolomics to retinal diseases, with focus on age-related macular degeneration (AMD), diabetic retinopathy (DR), retinopathy of prematurity (ROP), glaucoma, and retinitis pigmentosa (RP).
Collapse
Affiliation(s)
- Xing Li
- School of Basic Medical Sciences, Shaoyang University, Shaoyang 422000, China; (X.L.); (Z.H.)
| | - Shichang Cai
- Department of Human Anatomy, School of Medicine, Hunan University of Medicine, Huaihua 418000, China;
| | - Zhiming He
- School of Basic Medical Sciences, Shaoyang University, Shaoyang 422000, China; (X.L.); (Z.H.)
| | - James Reilly
- Department of Biological and Biomedical Sciences, Glasgow Caledonian University, Glasgow G4 0BA, UK;
| | - Zhihong Zeng
- College of Biological and Environmental Engineering, Changsha University, Changsha 410022, China;
| | - Niall Strang
- Department of Vision Science, Glasgow Caledonian University, Glasgow G4 0BA, UK;
| | - Xinhua Shu
- School of Basic Medical Sciences, Shaoyang University, Shaoyang 422000, China; (X.L.); (Z.H.)
- Department of Biological and Biomedical Sciences, Glasgow Caledonian University, Glasgow G4 0BA, UK;
- Department of Vision Science, Glasgow Caledonian University, Glasgow G4 0BA, UK;
| |
Collapse
|