Skyler JS, Bakris GL, Bonifacio E, Darsow T, Eckel RH, Groop L, et al. Differentiation of diabetes by pathophysiology, natural history, and prognosis. Diabetes. 2017;66:241–55.
Google Scholar
Sun H, Saeedi P, Karuranga S, Pinkepank M, Ogurtsova K, Duncan BB, et al. IDF Diabetes Atlas: global, regional and country-level diabetes prevalence estimates for 2021 and projections for 2045. Diabetes Res Clin Pract. 2022;183:109119.
Google Scholar
Menke A, Casagrande S, Geiss L, Cowie CC. Prevalence of and trends in diabetes among adults in the United States, 1988–2012. JAMA. 2015;314:1021–9.
Google Scholar
Balkau B, Lange CL, Fezeu L, Tichet J, de Lauzon-Guillain B, Czernichow S, et al. Predicting Diabetes: clinical, biological, and genetic approaches. Diabetes Care. 2008;31:2056–61.
Google Scholar
Zhou X, Qiao Q, Ji L, Ning F, Yang W, Weng J, et al. Nonlaboratory-based risk assessment algorithm for undiagnosed type 2 diabetes developed on a nationwide diabetes survey. Diabetes Care. 2013;36:3944–52.
Google Scholar
Yu DY, Cringle SJ. Oxygen distribution and consumption within the retina in vascularised and avascular retinas and in animal models of retinal disease. Prog Retin Eye Res. 2001;20:175–208.
Google Scholar
Huru J, Leiviskä I, Saarela V, Liinamaa MJ. Prediabetes influences the structure of the macula: thinning of the macula in the Northern Finland birth cohort. Br J Ophthalmol. 2021;105:1731–7.
Google Scholar
De Clerck EEB, Schouten JSAG, Berendschot TTJM, Goezinne F, Dagnelie PC, Schaper NC, et al. Macular thinning in prediabetes or type 2 diabetes without diabetic retinopathy: the Maastricht study. Acta Ophthalmol. 2018;96:174–82.
Google Scholar
Şahin M, Şahin A, Kılınç F, Karaalp Ü, Yüksel H, Özkurt ZG, et al. Early detection of macular and peripapillary changes with spectralis optical coherence tomography in patients with prediabetes. Arch Physiol Biochem. 2018;124:75–79.
Google Scholar
Yang S, Zhu Z, Chen S, Yuan Y, He M, Wang W. Metabolic fingerprinting on retinal pigment epithelium thickness for individualized risk stratification of type 2 diabetes mellitus. Nat Commun. 2023;14:6573.
Google Scholar
Karaca C, Karaca Z. Beyond hyperglycemia, evidence for retinal neurodegeneration in metabolic syndrome. Investig Ophthalmol Vis Sci. 2018;59:1360–7.
Google Scholar
Énzsöly A, Szabó A, Kántor O, Dávid C, Szalay P, Szabó K, et al. Pathologic alterations of the outer retina in streptozotocin-induced diabetes. Investig Ophthalmol Vis Sci. 2014;55:3686–99.
Google Scholar
Hammoum I, Benlarbi M, Dellaa A, Szabó K, Dékány B, Csaba D, et al. Study of retinal neurodegeneration and maculopathy in diabetic Meriones shawi: a particular animal model with human-like macula. J Comp Neurol. 2017;525:2890–914.
Google Scholar
Verma A, Rani PK, Raman R, Pal SS, Laxmi G, Gupta M, et al. Is neuronal dysfunction an early sign of diabetic retinopathy? Microperimetry and spectral domain optical coherence tomography (SD-OCT) study in individuals with diabetes, but no diabetic retinopathy. Eye. 2009;23:1824–30.
Google Scholar
Zhu Z, Shi D, Liao H, Ha J, Shang X, Huang Y, et al. Visual impairment and risk of dementia: the UK Biobank study. Am J Ophthalmol. 2022;235:7–14.
Google Scholar
Ko F, Foster PJ, Strouthidis NG, Shweikh Y, Yang Q, Reisman CA, et al. Associations with retinal pigment epithelium thickness measures in a large cohort: results from the UK Biobank. Ophthalmology. 2017;124:105–17.
Google Scholar
Foster HME, Celis-Morales CA, Nicholl BI, Petermann-Rocha F, Pell JP, Gill JMR, et al. The effect of socioeconomic deprivation on the association between an extended measurement of unhealthy lifestyle factors and health outcomes: a prospective analysis of the UK Biobank cohort. Lancet Public Health. 2018;3:e576–e585.
Google Scholar
Obesity: preventing and managing the global epidemic. Report of a WHO consultation. World Health Organ Tech Rep Ser. 2000;894:i-xii, 1–253.
Bull FC, Al-Ansari SS, Biddle S, Borodulin K, Buman MP, Cardon G, et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour. Br J Sports Med. 2020;54:1451–62.
Google Scholar
Park S-Y, Freedman ND, Haiman CA, Le Marchand L, Wilkens LR, Setiawan VW. Association of coffee consumption with total and cause-specific mortality among nonwhite populations. Ann Intern Med. 2017;167:228–35.
Google Scholar
Harrell FE, Lee KL, Mark DB. Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors. Stat Med. 1996;15:361–87.
Google Scholar
Pencina MJ, D’Agostino RB, Steyerberg EW. Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers. Stat Med. 2011;30:11–21.
Google Scholar
Leening MJG, Vedder MM, Witteman JCM, Pencina MJ, Steyerberg EW. Net reclassification improvement: computation, interpretation, and controversies: a literature review and clinician’s guide. Ann Intern Med. 2014;160:122–31.
Google Scholar
Diehl t, mullins r, Kapopopogannis D. Insulin resistance in Alzheimer’s disease. Transl Res. 2017;183:26–4
Google Scholar
Takeda S, Sato N, Ikimura K, Nishino H, Rakugi H, Morishita R. Increased blood-brain barrier vulnerability to systemic inflammation in an Alzheimer’s disease mouse model. Neurobiol Aging. 2013;34:2064–70.
Google Scholar
Murphy MP. How mitochondria produce reactive oxygen species. Biochem J. 2009;417:1–13.
Google Scholar
Bhatti JS, Bhatti GK, Reddy PH. Mitochondrial dysfunction and oxidative stress in metabolic disorders—a step towards mitochondria based therapeutic strategies. Biochim Biophys Acta Mol Basis Dis. 2017;1863:1066–77.
Google Scholar
Reddy PH. Mitochondrial medicine for aging and neurodegenerative diseases. Neuromol. Med. 2008;10:291–315.
Google Scholar
Nieves-moreno M, Martínez-De-Casa JM, Morales-Fernández L, Sánchez-Frentean r, Sáenz-French F, García-Feijo J. Impacts of Age and Six on the Layer Thicksses Measured by Specral Domain optal. plus au. 2018;13:e0194169.
Google Scholar
Chua J, Tham YC, Tan B, Devarajan K, Schwarzhans F, Gan A, et al. Age-related changes of individual macular retinal layers among Asians. Sci Rep. 2019;9:20352.
Google Scholar
Trinh M, Khou V, Zangerl B, Kalloniatis M, Nivison-Smith L. Modelling normal age-related changes in individual retinal layers using location-specific OCT analysis. Sci Rep. 2021;11:558.
Google Scholar
