METABOLIC SYNDROME AND THE AGING RETINA: A SYSTEMATIC REVIEW
DOI:
https://doi.org/10.53555/nnmhs.v9i4.1642Keywords:
Aging, Metabolic syndrome, Retina, Retinopathy, VisualAbstract
As we get older, we experience a progressive loss of visual function in our eyes. Changes in the structures of the ocular tissues, specifically the cornea, lens, retina, retinal pigment epithelium (RPE), choroid, and optic nerve, are the root cause of age-related macular degeneration, which leads to a loss of vision. Aging is linked to a wide variety of eye conditions, including Fuch's dystrophy, dry eye syndrome, cataracts, presbyopia, age-related macular degeneration (AMD), diabetic retinopathy, and glaucoma, amongst others. Vision can be impaired as a result of these conditions in between 4 and 20 percent of people over the age of 65. The term "metabolic syndrome" (MetS) refers to a cluster of cardiometabolic components, some of which include abdominal obesity, hypertension, elevated glucose levels, and dyslipidemia. These components are highly predictive of type 2 diabetes mellitus and cardiovascular diseases (CVD), which eventually cause morbidity and mortality. The retinal age difference has proven itself as an innovative and reliable screening technique for metabolic syndrome and inflammation. When compared to earlier screening methods that were based on blood tests or anthropometric measurements, the retinal age gap is calculated using a deep learning model that automatically integrates all of the information from fundus images. This reduces the likelihood of making an error during manual assessment and eliminates the requirement for invasive testing. We discovered that there was a strong association between MetS and age gaps in the retina, as well as inflammation.
References
Gambato C, Longhin E, Catania AG, Lazzarini D, Parrozzani R, Midena E. Aging and corneal layers: an in vivo corneal confocal microscopy study. Graefe’s Arch Clin Exp Ophthalmol. 2015;253:267–75.
Gipson IK. Age-related changes and diseases of the ocular surface and cornea. Invest Ophthalmol Vis Sci. 2013;54(14):ORSF48–53.
Nadal-Nicolás FM, Vidal-Sanz M, Agudo-Barriuso M. The aging rat retina: from function to anatomy. Neurobiol Aging. 2018;61:146–68.
Salvi SM, Akhtar S, Currie Z. Ageing changes in the eye. Postgrad Med J. 2006 Sep;82(971):581–7.
Chader GJ, Taylor A. Preface: The aging eye: normal changes, age-related diseases, and sight-saving approaches. Invest Ophthalmol Vis Sci. 2013 Dec;54(14):ORSF1-4.
Rochlani Y, Pothineni NV, Kovelamudi S, Mehta JL. Metabolic syndrome: pathophysiology, management, and modulation by natural compounds. Ther Adv Cardiovasc Dis. 2017 Aug;11(8):215.
Herningtyas EH, Ng TS. Prevalence and distribution of metabolic syndrome and its components among provinces and ethnic groups in Indonesia. BMC Public Health. 2019 Apr;19(1):1–12.
Mahajan A, Jaiswal A, Tabassum R, Podder A, Ghosh S, Madhu S V, et al. Elevated levels of C-reactive protein as a risk factor for metabolic syndrome in Indians. Atherosclerosis. 2012;220(1):275–81.
Romero-Saldaña M, Fuentes-Jiménez FJ, Vaquero-Abellán M, Álvarez-Fernández C, Molina-Recio G, López-Miranda J. New non-invasive method for early detection of metabolic syndrome in the working population. Eur J Cardiovasc Nurs. 2016 Dec;15(7):549–58.
Meng W, Zhang C, Zhang Q, Song X, Lin H, Zhang D, et al. Association between leukocyte and metabolic syndrome in urban Han Chinese: a longitudinal cohort study. PLoS One. 2012;7(11):e49875.
Lee MJ, Jung CH, Kang YM, Hwang JY, Jang JE, Leem J, et al. Serum bilirubin as a predictor of incident metabolic syndrome: a 4-year retrospective longitudinal study of 6205 initially healthy Korean men. Diabetes Metab. 2014;40(4):305–9.
Romero-Saldaña M, Tauler P, Vaquero-Abellán M, López-González A-A, Fuentes-Jiménez F-J, Aguiló A, et al. Validation of a non-invasive method for the early detection of metabolic syndrome: a diagnostic accuracy test in a working population. BMJ Open. 2018;8(10):e020476.
Zhu Z, Liu D, Chen R, Hu W, Liao H, Kiburg K, et al. The Association of Retinal age gap with metabolic syndrome and inflammation. J Diabetes. 2023 Mar;15(3):237–45.
Zarei R, Anvari P, Eslami Y, Fakhraie G, Mohammadi M, Jamali A, et al. Retinal nerve fibre layer thickness is reduced in metabolic syndrome. Diabet Med. 2017;34(8):1061–6.
Wang SB, Mitchell P, Plant AJH, Phan K, Liew G, Thiagalingam A, et al. Metabolic syndrome and retinal microvascular calibre in a high cardiovascular disease risk cohort. Br J Ophthalmol. 2016;100(8):1041–6.
Ghaem Maralani H, Tai BC, Wong TY, Tai ES, Li J, Wang JJ, et al. Metabolic syndrome and risk of age-related macular degeneration. Retina. 2015 Mar;35(3):459–66.
Mbata O, El-Magd NFA, El-Remessy AB. Obesity, metabolic syndrome and diabetic retinopathy: Beyond hyperglycemia. World J Diabetes. 2017;8(7):317.
Catharina AS, Modolo R, Ritter AMV, et al. Metabolic Syndrome-Related Features in Controlled and Resistant Hypertensive Subjects. Arq Bras Cardiol. 2018;110(6):312–7.
Lopes de Faria JM, Russ H, Costa VP. Retinal nerve fibre layer loss in patients with type 1 diabetes mellitus without retinopathy. Vol. 86, The British journal of ophthalmology. England; 2002. p. 725–8.
Qiu F, Ma X, Shin Y-H, Chen J, Chen Q, Zhou K, et al. Pathogenic role of human C-reactive protein in diabetic retinopathy. Clin Sci. 2020;134(13):1613–29.
Shen J, Bi Y-L, Das UN. Potential role of polyunsaturated fatty acids in diabetic retinopathy. Arch Med Sci. 2014 Dec;10(6):1167–74.
Ouchi N, Parker JL, Lugus JJ, Walsh K. Adipokines in inflammation and metabolic disease. Nat Rev Immunol. 2011 Feb;11(2):85–97.
Au SCL, Tang S-M, Rong S-S, Chen L-J, Yam JCS. Association between hyperglycemia and retinopathy of prematurity: a systemic review and meta-analysis. Sci Rep. 2015 Mar;5:9091.
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