Identification of serum metabolome signatures associated with retinal and renal complications of type 2 diabetes

Author:

Tomofuji YoshihikoORCID,Suzuki Ken,Kishikawa Toshihiro,Shojima Nobuhiro,Hosoe Jun,Inagaki Kyoko,Matsubayashi Sunao,Ishihara Hisamitsu,Watada Hirotaka,Ishigaki Yasushi,Yamanashi Yuji,Furukawa Yoichi,Morisaki Takayuki,Kamatani Yoichiro,Muto Kaori,Nagai Akiko,Obara Wataru,Yamaji Ken,Takahashi Kazuhisa,Asai Satoshi,Takahashi Yasuo,Suzuki Takao,Sinozaki Nobuaki,Yamaguchi Hiroki,Minami Shiro,Murayama Shigeo,Yoshimori Kozo,Nagayama Satoshi,Obata Daisuke,Higashiyama Masahiko,Masumoto Akihide,Koretsune Yukihiro,Inohara Hidenori,Murakami Yoshinori,Matsuda Koichi,Okada YukinoriORCID,Yamauchi Toshimasa,Kadowaki Takashi,

Abstract

Abstract 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.

Publisher

Springer Science and Business Media LLC

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