Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub. 2020, 164(3):236-246 | DOI: 10.5507/bp.2020.028

Metabolomic analysis in ophthalmology

Neshe Nazifova-Tasinovaa, Mladena Radevab, Bistra Galunskaa, Christina Grupchevab
a Department of Biochemistry, Molecular medicine and Nutrigenomics, Faculty of Pharmacy, Medical University of Varna, 84 Tzar Osvoboditel street, 9000 Varna, Bulgaria
b Department of Ophthalmology and Visual Sciences, Faculty of Medicine, Medical University of Varna, 15 Doyran street, 9000 Varna, Bulgaria

Modern science takes into account phenotype complexity and establishes approaches to track changes on every possible level. Many "omics" studies have been developed over the last decade. Metabolomic analysis enables dynamic measurement of the metabolic response of a living system to a variety of stimuli or genetic modifications. Important targets of metabolomics is biomarker development and translation to the clinic for personalized diagnosis and a greater understanding of disease pathogenesis. The current review highlights the major aspects of metabolomic analysis and its applications for the identification of relevant predictive, diagnostic and prognostic biomarkers for some ocular diseases including dry eye, keratoconus, retinal diseases, macular degeneration, and glaucoma. To date, possible biomarker candidates for dry eye disease are lipid metabolites and androgens, for keratoconus cytokeratins, urea, citrate cycle, and oxidative stress metabolites. Palmitoylcarnitine, sphingolipids, vitamin D related metabolites, and steroid precursors may be used for distinguishing glaucoma patients from healthy controls. Dysregulation of amino acid and carnitine metabolism is critical in the development and progression of diabetic retinopathy. Further work is needed to discover and validate metabolic biomarkers as a powerful tool for understanding the molecular mechanisms of ocular diseases, to provide knowledge on their etiology and pathophysiology and opportunities for personalized clinical intervention at an early stage.

Keywords: metabolomics, biomarkers, metabolites, ocular diseases

Received: May 22, 2020; Revised: June 19, 2020; Accepted: June 24, 2020; Prepublished online: July 17, 2020; Published: September 17, 2020  Show citation

ACS AIP APA ASA Harvard Chicago Chicago Notes IEEE ISO690 MLA NLM Turabian Vancouver
Nazifova-Tasinova, N., Radeva, M., Galunska, B., & Grupcheva, C. (2020). Metabolomic analysis in ophthalmology. Biomedical papers, 164(3), 236-246. doi: 10.5507/bp.2020.028
Share...
Download citation
  • BibTeX (.bib)
  • Bookends (.ris)
  • EasyBib (.ris)
  • EndNote (.enw)
  • EndNote 8 (.xml)
  • ISI WoS (.isi)
  • Medlars (.medlars)
  • Mendeley (.ris)
  • MODS (.xml)
  • Papers (.ris)
  • RefWorks (.txt)
  • RefManager (.ris)
  • RIS (.ris)
  • MS Word (.xml)
  • Zotero (.ris)
    • Open full article

    References

    1. Nalbantoglu S. Metabolomics: Basic Principles and Strategies. Molecular Medicine, Sinem Nalbantoglu and Hakima Amri, IntechOpen [on the internet] 2019 Aug [cited 2019 Aug 7]; Available from: https://www.intechopen.com/books/molecular-medicine/metabolomics-basic-principles-and-strategies. doi: 10.5772/intechopen.88563 Go to original source...
    2. PubMed US National Library of Medicine National Institutes of Health. Available from: https://www.ncbi.nlm.nih.gov/pubmed
    3. METLIN. Available from: https://metlin.scripps.edu/landing_page.php?pgcontent=mainPage
    4. Lindon JC, Nicholson JK, Holmes E, editors. The Handbook of Metabolic Phenotyping. 1st ed. Amsterdam: Elsevier; 2019.
    5. Nicholson JK, Darzi AV, Holmes E, Lindon JC, editors. Metabolic Phenotyping in Personalized and Public Healthcare. 1st ed. New York: Academic Press; 2016.
    6. Noreldeen HAA, Liu X, Xu G. Metabolomics of lung cancer: Analytical platforms and their applications. J Sep Sci 2020;43(1):120-33. Go to original source... Go to PubMed...
    7. Vinaixa M, Schymanski EL, Neumann S, Navarro M, Sale R, Yanes Ó. Mass spectral databases for LC/MS- and GC/MS-based metabolomics: State of the field and future prospects. Trends Analyt Chem 2016;78,23-35. Go to original source...
    8. Chen W, Li S, Kulkarni AS, Huang L, Cao J, Qian K, Wan J. Single Cell Omics: From Assay Design to Biomedical Application. Biotechnol J [serial on the Internet]. 2019 Oct [cited 2019 Oct 21]; 15(1):[about 10 p.]. Available from: https://onlinelibrary.wiley.com/doi/epdf/10.1002/biot.201900262. Go to original source... Go to PubMed...
    9. Alonso A, Marsal S, Julià A. Analytical methods in untargeted metabolomics: state of the art in 2015. Front Bioeng Biotechnol [serial on the Internet]. 2015 Mar [cited 2015 Mar 5]; 3:[about 20 p. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4350445/ Go to original source...
    10. Gika H, Virgiliou C, Theodoridis G, Plumb RS, Wilson ID. Untargeted LC/MS-based metabolic phenotyping (metabonomics/metabolomics): The state of the art. J Chromatogr B Analyt Technol Biomed Life Sci 2019;1(1117):136-47. Go to original source... Go to PubMed...
    11. Schrimpe-Rutledge AC, Codreanu SG, Sherrod SD, McLean JA. Untargeted Metabolomics Strategies-Challenges and Emerging Directions. J Am Soc Mass Spectrom 2016;27(12):1897-05. Go to original source... Go to PubMed...
    12. Silva RA, Pereira TCS, Souza AR, Ribeiro PR. 1H NMR-based metabolite profiling for biomarker identification. Clin Chim Acta 2020;502:269-79. Go to original source... Go to PubMed...
    13. Emwas A-H, Roy R, McKay RT, Tenori L, Saccenti E, Gowda GAN, Raftery D, Alahmari F, Jaremko L, Jaremko M, Wishart DS. Spectroscopy for Metabolomics Research. Metabolites [serial on the internet]. 2019 Jun [cited 2019 Jun 27];9(7):[about 39 p.]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6680826/ Go to original source... Go to PubMed...
    14. Clendinen CS., Pasquel C, Ajredini R, Edison AS. 13C NMR Metabolomics: INADEQUATE Network Analysis. Anal Chem 2015;87(11):5698-5706. Go to original source... Go to PubMed...
    15. Alsaleh M, Barbera TA, Andrews RH, Sithithaworn P, Khuntikeo N, Loilome W, Yongvanit P, Cox IJ, Syms RRA, Holmes E, Taylor-Robinson SD. Mass Spectrometry: A Guide for the Clinician. J Clin Exp Hepatol 2019;9(5):597-06. Go to original source... Go to PubMed...
    16. Zhou J, Liu H, Liu Y, Liu J, Zhao X., Yin Y. Development and Evaluation of a Parallel eaction Monitoring Strategy for Large-Scale Targeted Metabolomics Quantification. Analytical Chemistry 2016;88(8):4478-86. Go to original source...
    17. Use of Metabolomics to Advance Research on Environmental Exposures and the Human Exposome. In: Workshop in Brief. National Academies of Sciences, Engineering, and Medicine, Division on Earth and Life Studies; Board on Life Sciences. Washington, DC, USA. The National Academies Press; 2016.
    18. Vernocchi P, Del Chierico F, Putignani L. Gut Microbiota Profiling: Metabolomics Based Approach to Unravel Compounds Affecting Human Health. Front Microbiol [serial on the Internet]. 2016 Jul [cited 2016 Jul 26];7:[about 21 p.]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4960240/ Go to original source...
    19. van der Hooft JJ, Wandy J, Young F, Padmanabhan S, Gerasimidis K, Burgess KEV, Barrett MP, Rogers S. Unsupervised Discovery and Comparison of Structural Families Across Multiple Samples in Untargeted Metabolomics. Anal Chem 2017;89(14):7569-77. Go to original source...
    20. Heinemann J. Cluster Analysis of Untargeted Metabolomic. Experiments. Methods Mol Biol 2017;1859:275-85. Go to original source... Go to PubMed...
    21. Blasco H, B³aszczynski, Billau JC H, Nadal-Desbarats L, Pradat PF, Devos D, Moreau C, Andres CR, Emond P, Corcia P, S³owiñski R. Comparative analysis of targeted metabolomics: Dominance-based rough set approach versus orthogonal partial least square-discriminant analysis. J Biomedi Informa 2015;53:291-9. Go to original source... Go to PubMed...
    22. Everett JR, Holmes E, Veselkov KA, Lindon JC, Nicholson JK. A Unified Conceptual Framework for Metabolic Phenotyping in Diagnosis and Prognosis. Trends Pharmacol Sci 2019;40(10):763-73. Go to original source... Go to PubMed...
    23. Burgess LG, Uppal K, Walker DI Roberson RM, Tran V, Parks MB, Wade EA, May AT, Umfress AC, Jarrell KL, Stanley BOC, Kuchtey J, Kuchtey RW, Jones DP, Brantley MA Jr. Metabolome wide association study of primary open angle glaucoma. Invest Ophthalmol Vis Sci 2015;56:5020-8. Go to original source... Go to PubMed...
    24. Sidek S, Ramli N, Rahmat K, Ramli NM, Abdulrahman F, Kuo TL. In vivo proton magnetic resonance spectroscopy (1H-MRS) evaluation of the metabolite concentration of optic radiation in primary open angle glaucoma. Eur Radiol 2016;26:4404-12. Go to original source... Go to PubMed...
    25. Laíns I, Chung W, Kelly RS Gil J, Marques M, Barreto P, Murta JN, Kim IK, Vavvas DG, Miller JB, Silva R, Lasky-Su J, Liang L, Miller JW, Husain D. Human Plasma Metabolomics in Age-Related Macular Degeneration: Meta-Analysis of Two Cohorts. Metabolites 2019;9(7):127. doi: 10.3390/metabo9070127 Go to original source... Go to PubMed...
    26. Laíns I, Duarte D, Barros AS Martins, AS, Gil J, Miller JB, Marques M, Mesquita T, Kim IK, Cachulo ML, Vavvas D, Carreira IM, Murta JN, Silva R, Miller JW, Husain D, Gil AM. Human plasma metabolomics in age-related macular degeneration (AMD) using nuclear magnetic resonance spectroscopy. PLoS One [serial on the Internet] 2017 May [cited 2017 May 18]; 12(5):[about 18 p.]. Available from: https://europepmc.org/backend/ptpmcrender.fcgi?accid=PMC5436712&blobtype=pdf Go to original source... Go to PubMed...
    27. Huiyi J, Bijun Z, Xia L, Jing J, Haidong Z. Metabolic characterization of diabetic retinopathy: An 1H-NMR-based metabolomic approach using human aqueous humor. J Pharm Biomed Anal 2019;174:414-21. Go to original source... Go to PubMed...
    28. Karamichos D, Zieske JD, Sejersen H, Sarker-Nag A, Asara JM, Hjortdal J. Tear metabolite changes in keratoconus. Exp Eye Res 2015;132:1-8. Go to original source... Go to PubMed...
    29. Yu M, Wu Z, Zhang Z, Huang X, Zhang Q. Metabolomic Analysis of Human Vitreous in Rhegmatogenous Retinal Detachment Associated With Choroidal Detachment. Invest Ophthalmol Vis Sci 2015;56(9):5706-13. Go to original source... Go to PubMed...
    30. Wang H, Zhai R, Sun Q, Wu Y, Wang Z, Fang J, Kong X. Metabolomic Profile of Posner-Schlossman Syndrome: A Gas Chromatography Time-of-Flight Mass Spectrometry-Based Approach Using Aqueous Humor. Front Pharmacol [serial on the Internet]. 2019 Nov [cited 2019 Nov 7]; 10:[about 11 p.]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6855217/ Go to original source...
    31. Galbis-Estrada C, Pinazo-Duran MD, Martinez-Castillo S, Morales JM, Monleon D, Zanon-Moreno V. A metabolomic approach to dry eye disorders: the role of oral supplements with antioxidants and omega 3 fatty acids. Mol Vis 2015;21:555-67.
    32. Munoz-Hernandez AM, Galbis-Estrada C, Santos-Bueso E, Cuiña-Sardiña R, Díaz-Valle D, Gegúndez-Fernández JA, Pinazo-Durán MD, Benítez-del-Castillo JM. Human tear metabolome. Arch Soc Esp Oftalmol 2016;91:157-9. Go to original source...
    33. Barbas-Bernardos C, Armitage EG, Garcia A, Mérida S, Navea A, Bosch-Morell F, Barbas C. Looking into aqueous humor through metabolomics spectacles - exploring its metabolic characteristics in relation to myopia. J Pharm Biomed Anal 2016;127:18-25. Go to original source... Go to PubMed...
    34. Ji Y, Rao J, Rong X, Lou S, Zheng Z, Lu Y. Metabolic characterization of human aqueous humor in relation to high myopia. Exp Eye Res 2017;159:147-55. Go to original source... Go to PubMed...
    35. Patnaik S, Jalali S, Joshi MB, Satyamoorthy K, Kaur I. Metabolomics Applicable to Retinal Vascular Diseases. Methods Mol Biol 2019;1996:325-31. Go to original source... Go to PubMed...
    36. Priyadarsini S, McKay TB, Sarker-Nag A, Allegood J, Chalfant C, Ma J-X, Karamichos D. Complete metabolome and lipidome analysis reveals novel biomarkers in the human diabetic corneal stroma. Exp. Eye Res 2016;153:90-100. Go to original source... Go to PubMed...
    37. Chen L, Li J, Guo T, Ghosh S, Ghosh S, Koh SK, Tian D, Zhang L, Jia D, Beuerman RW, Aebersold R, Chan ECY, Zhou L. Global metabonomic and proteomic analysis of human conjunctival epithelial cells (IOBA-NHC) in response to hyperosmotic stress. J Proteome Res 2015;14:3982-95. Go to original source... Go to PubMed...
    38. Tsentalovich YP, Verkhovod TD, Yanshole VV, Kiryutin AS, Yanshole LV, Fursova AZ, Stepakov DA, Novoselov VP, Sagdeev RZ. Metabolomic composition of normal aged and cataractous human lenses. Exp. Eye Res 2015;134:15-23. Go to original source... Go to PubMed...
    39. Craig JP, Nichols KK, Nichols JJ, Caffery B, Dua HS, Joo CK, Liu Z, Nelson JD, Nichols JJ, Tsubota K, Stapleton F. FOS DEWS II Definition and Classification Report. Ocular Surface 2017;15(3):276-83. Go to original source... Go to PubMed...
    40. Kanellopoulos, AJ, Asimellis G. In pursuit of objective dry eye screening clinical techniques. Eye Vis (Lond) [serial on the Internet]. 2016 Jan [cited 2016 Jan 18];3:[ about 7 p.]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4716631/ Go to original source...
    41. Aggarwal S, Galor A. What's new in dry eye disease diagnosis? Current advances and challenges. F1000Res [serial on the Internet]. 2018 Dec [cited 2018 Jun 19];7:[about 7 p.]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6305205/ Go to original source...
    42. Zhang X, Jeyalatha VM, Yangluowa Q, Qu Y, He X, Ou S, Bu J, Jia C, Wang J, Wu H, Liu Z, Li W. Dry eye management: Targeting the ocular surface microenvironment. Int J Mol Sci [serial on the Internet]. 2017 Jun [cited 2017 Jun 29];18(7):[about 28 p.]. 1398. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5535891/ Go to original source... Go to PubMed...
    43. Yazdani M, Benedikte K, Elgstøen P, Rootwelt H, Shahdadfar A, Utheim ØA, Utheim TP. Tear Metabolomics in Dry Eye Disease: A Review. Int J Mol Sci [serial on the Internet]. 2019 Aug [cited 2019 Aug 1]; 20(15):[about 18 p.]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6695908/ Go to original source... Go to PubMed...
    44. Chen X, Rao J, Zheng Z, Yu Y, Lou S, Liu L, He Q, Wu L, Sun X. Integrated Tear Proteome and Metabolome Reveal Panels of Inflammatory-Related Molecules via Key Regulatory Pathways in Dry Eye Syndrome. J. Proteome Res 2019;18(5):2321-30. Go to original source... Go to PubMed...
    45. Vehof J, Hysi PG, Hammond. CJ. A Metabolome-Wide Study of Dry Eye Disease Reveals Serum Androgens as Biomarkers. Ophthalmology 2017;124(4):505-11. Go to original source... Go to PubMed...
    46. Millodot M, Ortenberg I, Lahav-Yacouel K, Behrman S. Effect of ageing on keratoconic corneas. J Optom 2016;9(2),72-7. Go to original source... Go to PubMed...
    47. Soiberman U, Foster JW, Jun AS, Chakravarti S.Pathophysiology of Keratoconus: What Do We Know Today. Open Ophthalmol J 2017;11:252-61. Go to original source... Go to PubMed...
    48. Tan SZ, Begley P, Mullard G, Hollywood KA, Bishop PN. Introduction to metabolomics and its applications in ophthalmology. Eye 2016;30:773-83. Go to original source... Go to PubMed...
    49. Nishtala K, Pahuja N, Shetty R, Rudy MM, Nuijts A, Ghosh A. Tear biomarkers for keratoconus. Eye Vis (Lond) [serial on the Internet]. 2016 Aug [cited 2016 Aug 4]; 3:[about 7 p.]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4973115/ Go to original source...
    50. Shetty R, Ghosh A, Lim RR, Subramani M, Mihir K, Reshma AR, Ranganath A, Nagaraj S, Nuijts RMM, Beuerman R, Shetty R, Das D, Chaurasia SS, Sinha-Roy A, Ghosh A. Elevated Expression of Matrix Metalloproteinase-9 and Inflammatory Cytokines in Keratoconus Patients Is Inhibited by Cyclosporine A. Invest Ophthalmol Vis Sci 2015;56(2):738-50. Go to original source... Go to PubMed...
    51. You J, Hodge C, Wen L, McAvoy JW, Madigan MC, Sutton G. Tear levels of SFRP1 are significantly reduced in keratoconus patients. Molecular Vision 2013;19:509-15. Go to PubMed...
    52. Liao L, Zhu X-H. Advances in the treatment of rhegmatogenous retinal detachment. Int J Ophthalmol 2019;12:660-7.
    53. Yu M, Wu Z, Zhang Z, Huang X, Zhang Q. Metabolomic analysis of human vitreous in rhegmatogenous retinal detachment associated with choroidal detachment. Invest Ophthalmol Vis Sci 2015;56:5706-13. Go to original source... Go to PubMed...
    54. Laínsa I, Gantnerc M, Murinelloc S, Lasky-Su JA, Miller JW, Friedlander M5, Husain D. Metabolomics in the study of retinal health and disease. Prog Retin Eye Res 2019;69:57-79. Go to original source... Go to PubMed...
    55. Kwon OW, Song JH, Roh MI. Retinal detachment and proliferative vitreoretinopathy. Dev Ophthalmol 2015;55:154-62. Go to original source... Go to PubMed...
    56. Ciprian D. The Pathogeny of Proliferative Vitreoretinopathy. Rom J Ophthalmol 2015;59(2):88-92.
    57. Chen SC, Sheu SJ. Recent advances in managing and understanding uveitis. F1000 Research F1000Res [serial on the Internet]. 2017 Mar [cited 2017 Mar 16];6:[about 9 p.]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5357029/ Go to original source...
    58. Kanski J Bowling B. Kanski's Clinical Ophthalmology. A Systematic Approach. New York: Elsevier; 2016.
    59. Jonas JB, Aung T, Bourne RR, Bron AM, Ritch R, Panda-Jonas S. Glaucoma. Lancet 2017;390(10108):2183-93. Go to original source... Go to PubMed...
    60. Barbosa-Breda J, Himmelreich U, Ghesquière B, Rocha-Sousa A, Stalmans I. Clinical Metabolomics and Glaucoma. Ophthalmic Res 2018;59;1-6. Go to original source... Go to PubMed...
    61. Pan C, Ke C Chen Q, Tao Y, Zha X, Zhang YP, Zhong H. Differential metabolic markers associated with primary open-angle glaucoma and cataract in human aqueous humor. BMC Ophthalmol [serial on the Internet]. 2020 May [cited 2020 May 6]; 20: [about 8 p.]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7203853/pdf/12886_2020_Article_1452.pdf Go to original source...
    62. Leruez S, Marill A, Bresson T, de Saint Martin G, Buisset A, Muller J, Tessier L, Gadras C, Verny C, Gohier P, Amati-Bonneau P, Lenaers G, Bonneau D, Simard G, Milea D, Procaccio V, Reynier P, de la Barca JMC. A Metabolomics Profiling of Glaucoma Points to Mitochondrial Dysfunction, Senescence, and Polyamines Deficiency. Invest Ophthalmol Vis Sci 2018;59(11):4355-61. Go to original source... Go to PubMed...
    63. Nzoughet JK, Guehlouz K, Leruez S, Gohier P, Bocca C, Muller J, Blanchet O, Bonneau D, Simard G, Milea D, Procaccio V, Lenaers G, de la Barca JMC, Reynier P. A Data Mining Metabolomics Exploration of Glaucoma. Metabolites [serial on the Internet] 2020 Jan [cited 2020 Jan 28];10(2):[about 14 p.]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7074047/ Go to original source... Go to PubMed...
    64. Buisset A, Gohier P, Leruez S, Muller J, Amati-Bonneau P, Lenaers G, Bonneau D, Simard G, Procaccio V, Annweiler C, Milea D, Reynier P, de la Barca JMC. Metabolomic Profiling of Aqueous Humor in Glaucoma Points to Taurine and Spermine Deficiency: Findings from the Eye-D Study. J Proteome Res 2019;18(3):1307-15. Go to original source... Go to PubMed...
    65. Chen X, Chen Y, Wang L, Sun X. Metabolomics of the aqueous humor in patients with primary congenital glaucoma. Mol Vis 2019;25:489-01.
    66. Rong S, Li Y, Guan Y, Zhu L, Zhou Q, Gao M, Pan H, Zou L, Chang D. Long-chain unsaturated fatty acids as possible important metabolites for primary angle-closure glaucoma based on targeted metabolomic analysis. Biomed Chromatogr [serial on the Internet] 2017 Feb [cited Feb 18]; 31(9):[about 20 p.]. Available from: https://onlinelibrary.wiley.com/doi/epdf/10.1002/bmc.3963 Go to original source... Go to PubMed...
    67. Mitchell P, Liew G, Gopinath B, Wong TY. Age-related macular degeneration. Lancet 2018;392(10153):1147-59. Go to original source... Go to PubMed...
    68. Armstrong RA, Mousavi M. Overview of Risk Factors for Age-Related Macular Degeneration (AMD). J Stem Cells 2015;10(3):171-91.
    69. Fritsche LG, Igl W, Bailey JN, Grassmann F, Sengupta S, Bragg-Gresham JL, Burdon KP Hebbring SJ, Wen C, Gorski M, Kim IK, Cho D, Zack D, Souied E, Scholl HPN, Bala E, Lee KEHunter, DJ, Sardell RJ, Mitchell P, Merriam JE, Cipriani V, Hoffman JD, Schick T, Lechanteur YTE, Guymer RH, Johnson MP, Jiang Y, Stanton CM, Buitendijk GHS, Zhan X, Kwong AM, Boleda A, Brooks M, Gieser L, Ratnapriya R, Branham KE, Foerster JR, Heckenlively JR, Othman MI, Vote BJ, Liang HH, Souzeau E, McAllister IL, Isaacs T, Hall J, Lake S, Mackey DA, Constable IJ, Craig JE, Kitchner TE, Yang Z, Su Z, Luo H, Chen D, Ouyang H, Flagg K, Lin D, Mao G, Ferreyra H, Stark K, von Strachwitz CN, Wolf A, Brandl C, Rudolph G, Olden M, Morrison MA, Morgan DJ, Schu M Ahn J, Silvestri G, Tsironi EE, Park KH, Farrer LA, Orlin A, Brucker A, Li M, Curcio C, Mohand-Saïd S, Sahel J-A, Audo I, Benchaboune M, Cree AJ, Rennie CA, Goverdhan SV, Grunin M, Hagbi-Levi S, Campochiaro P, Katsanis N, Holz FG, Blond F, Blanché H, Deleuze JF,. Igo RP, Jr., Truitt B, Peachey NS, Meuer SM, Myers CE, Moore EL, Klein R, Hauser MA, Postel EA, Courtenay MD, Schwartz SG, Kovach JL, Scott WK, Liew G,. Tfan AG, Gopinath B, Merriam JC, Smith RT, Khan JC, Shahid H, Moore AT, McGrath JA, Laux R, Brantley MA, Jr., Agarwal A, Ersoy L, Caramoy A, Langmann T, Saksens NTM, de Jong EK, Hoyng CB, Cain MS, Richardson AJ, Martin TM, Blangero J, Weeks DE, Dhillon B, van Duijn CM, Doheny KF, Romm J, Klaver CC, Hayward, C, Gorin MB, Klein ML, Baird PN, den Hollander AI Fauser S, Yates JRW, Allikmets R, Wang JJ, Schaumberg DA, Klein BEK, Hagstrom SA, Chowers I, Lotery AJ, Léveillard T, Zhang K, Brilliant MH, Hewitt AW, Swaroop A, Chew EY, Pericak-Vance MA, DeAngelis M, Stambolian D, Haines JL, Iyengar SK, Weber BHF, Abecasis GR, Heid IM. A large genome-wide association study of age-related macular degeneration highlights contributions of rare and common variants. Nat Genet 2016;48(2):134-43. Go to original source... Go to PubMed...
    70. Laíns I, Kelly RS, Miller JB, Silva R, Vavvas DG, Kim IK, Murta JN, Lasky-Su J, Miller JW, Husain D. Human Plasma Metabolomics Study across All Stages of Age-Related Macular Degeneration Identifies Potential Lipid Biomarkers. Ophthalmology 2018;125(2):245-54. Go to original source... Go to PubMed...
    71. Laíns I, Duarte D, Barros AS, Martins AS, Carneiro TJ, Gil JQ, Miller JB, Marques M, Mesquita TS, Barreto P, Kim IK da Luz Cachulo M, Vavvas DG, Carreira IM, Murta JN, Silva R, Miller JW, Husain D, Gil AM. Urine Nuclear Magnetic Resonance (NMR) Metabolomics in Age-Related Macular Degeneration. J Proteome Res 2019;18(3):1278-88. Go to original source... Go to PubMed...
    72. Luo D, Deng T, Yuan W, Deng H, Jin M. Plasma metabolomic study in Chinese patients with wet age-related macular degeneration. BMC Ophthalmol [serial on the Internet]. 2017 Sep [cited 2017 Sep 6];17(1):[about 9 p.]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5585971/ Go to original source... Go to PubMed...
    73. Liu K, Fang J, Jin J. Serum Metabolomics Reveals Personalized Metabolic Patterns for Macular Neovascular Disease Patient Stratification. J Proteome Res 2020;19(2):699-07. Go to original source... Go to PubMed...
    74. Brown CN, Green BD, Thompson RB, den Hollander AI, Lengyel I, and on behalf of the EYE-RISK consortium. Metabolomics and Age-Related Macular Degeneration. Metabolites 2019;9(4):1-36. Go to original source...
    75. Wang J, Westenskow PD, Fang M, Friedlander M, Siuzdak G. Quantitative metabolomics of photoreceptor degeneration and the effects of stem cell-derived retinal pigment epithelium transplantation. Philos Trans A Math Phys Eng Sci [serial on the Internet]. 2016 Oct [cited 2016 Oct 28]; 374(2079):[about 15 p.]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5031641/ Go to original source... Go to PubMed...
    76. Kersten E, Paun CC, Schellevis RL, Hoyng CB, Delcourt C, Lengyel I, Peto T, Ueffing M, Klaver CCW, Dammeier S, I den Hollander A, de Jong EK. Systemic and ocular fluid compounds as potential biomarkers in age-related macular degeneration. Surv Ophthalmol 2018;63:9-39. Go to original source... Go to PubMed...
    77. Wong TY, Cheung CM, Larsen M, Sharma S, Simó R. Diabetic retinopathy. Nat Rev Dis Primers. [serial on the Internet] 2016 Mar [cited 2016 Mar 17]; 2:[about 12 p.]. Available from: https://www.nature.com/articles/nrdp201612 Go to original source...
    78. Wang W, Lo ACY. Diabetic Retinopathy: Pathophysiology and Treatments. Int J Mol Sci [serial on the Internet]. 2018 Jun [cited 2018 Jun 20];19(6):[about 14 p.]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6032159/ Go to original source... Go to PubMed...
    79. Chen L, Cheng CY, Choi H, Ikram MK, Sabanayagam C, Tan GSW, Tian D, Zhang L, Venkatesan G, Tai ES, Wang JJ, Mitchell P, Cheung CMG, Beuerman RW, Zhou L, Chan ECY, Wong TY. Plasma Metabonomic Profiling of Diabetic Retinopathy. Diabetes 2016;65(4):1099-108. Go to original source... Go to PubMed...
    80. Paris LP, Johnson CH, Aguilar E, Usui Y, Cho K Hoang LT, Feitelberg D, Benton HP, Westenskow PD, Kurihara T, Trombley J, Tsubota K, Ueda S, Wakabayashi Y, Patti GJ, Ivanisevic J, Siuzdak G, Friedlander M. Global metabolomics reveals metabolic dysregulation in ischemic retinopathy. Metabolomics [serial on the Internet]. 2015 Nov [cited 2015 Nov 18];12:[about 10 p.]. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4651979/ Go to original source...
    81. Liew G, Lei Z, Tan G, Joachim N, Ho I, Wong TY, Mitchell P, Gopinath B, Crossett B. Metabolomics of Diabetic Retinopathy. Curr Diab Rep [serial on the Internet]. 2017 Sep [cited 2017 Sep 23];17(11):[about 15 p.]. 102. Available from: https://pubmed.ncbi.nlm.nih.gov/28940103/ Go to original source... Go to PubMed...
    82. Jin H, Zhu B, Liu X, Jin J, Zou H. Metabolic characterization of diabetic retinopathy: An 1H-NMR-based metabolomic approach using human aqueous humor. J Pharm Biomed Anal 2019;174:414-21. Go to original source... Go to PubMed...

    This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits use, distribution, and reproduction in any medium, provided the original publication is properly cited. No use, distribution or reproduction is permitted which does not comply with these terms.


    Return to the content