RESUMEN
OBJECTIVES: To explore the metabolic fingerprints of diabetic retinopathy (DR) in individuals with type 2 diabetes using a newly-developed laser desorption/ionization mass spectrometry (LDI-MS) platform assisted by ferric particles. METHODS: Metabolic fingerprinting was performed using a ferric particle-assisted LDI-MS platform. A nested population-based case-control study was performed on 216 DR cases and 216 control individuals with type 2 diabetes. RESULTS: DR cases and control individuals with type 2 diabetes were comparable for a list of clinical factors. The newly-developed LDI-MS platform allowed us to draw the blueprint of plasma metabolic fingerprints from participants with and without DR. The neural network afforded diagnostic performance with an average area under curve value of 0.928 for discovery cohort and 0.905 for validation cohort (95â¯% confidence interval: 0.902-0.954 and 0.845-0.965, respectively). Tandem MS and Fourier transform ion cyclotron resonance MS with ultrahigh resolution identified seven specific metabolites that were significantly associated with DR in fully adjusted models. Of these metabolites, dihydrobiopterin, phosphoserine, N-arachidonoylglycine, and 3-methylhistamine levels in plasma were first reported to show the associations. CONCLUSIONS: This work advances the design of metabolic analysis for DR and holds the potential to promise as an efficient tool for clinical management of DR.
Asunto(s)
Diabetes Mellitus Tipo 2 , Retinopatía Diabética , Humanos , Retinopatía Diabética/diagnóstico , Estudios de Casos y Controles , Espectrometría de Masas/métodos , Rayos Láser , Espectrometría de Masa por Láser de Matriz Asistida de Ionización Desorción/métodosRESUMEN
PURPOSE: To evaluate the association between spousal diabetes status and the prevalence of diabetic retinopathy in Chinese patients with type 2 diabetes. METHODS: A cross-sectional community-based study was performed in 1510 patients with type 2 diabetes in Shanghai, China. Non-mydriatic digital fundus photography was used to detect diabetic retinopathy. Spousal diabetes status was assessed using a standardised interview questionnaire. RESULTS: The prevalence of diabetic retinopathy was significantly lower in patients who had diabetic spouses, compared with those who did not (20.2% vs 29.1%, p ⩽ 0.01). The fully adjusted odds ratio for diabetic retinopathy in those had diabetic spouses was decreased by 36% (odds ratio = 0.64, 95% confidence interval = 0.42-1.00, p = 0.048). The negative correlation between spousal diabetes status and diabetic retinopathy was presented in patients with the duration of diabetes ⩾ 10 years, those with HbA1c ⩾ 7% and those not using lipid-lowering drugs (odds ratio = 0.31, 95% confidence interval = 0.13-0.74, p = 0.0082; odds ratio = 0.50, 95% confidence interval = 0.27-0.94, p = 0.031; odds ratio = 0.58, 95% confidence interval = 0.37-0.92, p = 0.021, respectively). CONCLUSION: We demonstrated that spousal diabetes was associated with a lower diabetic retinopathy prevalence in Chinese patients with type 2 diabetes.