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Identification of serum metabolome signatures associated with retinal and renal complications of type 2 diabetes
BACKGROUND: Type 2 diabetes is a common disease around the world and its major complications are diabetic retinopathy (DR) and diabetic kidney disease (DKD). Persons with type 2 diabetes with complications, especially who have both DR and DKD, have poorer prognoses than those without complications....
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9829655/ https://www.ncbi.nlm.nih.gov/pubmed/36624208 http://dx.doi.org/10.1038/s43856-022-00231-3 |
Sumario: | BACKGROUND: Type 2 diabetes is a common disease around the world and its major complications are diabetic retinopathy (DR) and diabetic kidney disease (DKD). Persons with type 2 diabetes with complications, especially who have both DR and DKD, have poorer prognoses than those without complications. Therefore, prevention and early identification of the complications of type 2 diabetes are necessary to improve the prognosis of persons with type 2 diabetes. The aim of this study is to identify factors associated with the development of multiple complications of type 2 diabetes. METHODS: We profiled serum metabolites of persons with type 2 diabetes with both DR and DKD (N = 141) and without complications (N = 159) using a comprehensive non-targeted metabolomics approach with mass spectrometry. Based on the serum metabolite profiles, case–control comparisons and metabolite set enrichment analysis (MSEA) were performed. RESULTS: Here we show that five metabolites (cyclohexylamine, P = 4.5 × 10(−6); 1,2-distearoyl-glycero-3-phosphocholine, P = 7.3 × 10(−6); piperidine, P = 4.8 × 10(−4); N-acetylneuraminic acid, P = 5.1 × 10(−4); stearoyl ethanolamide, P = 6.8 × 10(−4)) are significantly increased in those with the complications. MSEA identifies fatty acid biosynthesis as the type 2 diabetes complications-associated biological pathway (P = 0.0020). CONCLUSIONS: Our metabolome analysis identifies the serum metabolite features of the persons with type 2 diabetes with multiple complications, which could potentially be used as biomarkers. |
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