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. 2024 May;67(5):837-849.
doi: 10.1007/s00125-024-06108-5. Epub 2024 Feb 27.

Circulating metabolomic markers linking diabetic kidney disease and incident cardiovascular disease in type 2 diabetes: analyses from the Hong Kong Diabetes Biobank

Qiao Jin  1 , Eric S H Lau  1   2 , Andrea O Luk  1   2   3 , Claudia H T Tam  1   2   3   4 , Risa Ozaki  1   2 , Cadmon K P Lim  1   2   3   4 , Hongjiang Wu  1   2 , Elaine Y K Chow  1   2   3 , Alice P S Kong  1   2   3 , Heung Man Lee  1 , Baoqi Fan  1   2   3   4 , Alex C W Ng  1 , Guozhi Jiang  5 , Ka Fai Lee  6 , Shing Chung Siu  7 , Grace Hui  7 , Chiu Chi Tsang  8 , Kam Piu Lau  9 , Jenny Y Leung  10 , Man-Wo Tsang  11 , Elaine Y N Cheung  11 , Grace Kam  11 , Ip Tim Lau  12 , June K Li  13 , Vincent T F Yeung  14 , Emmy Lau  15 , Stanley Lo  15 , Samuel Fung  16 , Yuk Lun Cheng  17 , Chun Chung Chow  1 , Weichuan Yu  18 , Stephen K W Tsui  19 , Brian Tomlinson  1   20 , Yu Huang  19   21 , Hui-Yao Lan  1   3 , Cheuk Chun Szeto  1   3 , Wing Yee So  1   2   3 , Alicia J Jenkins  1   22   23 , Erik Fung  1   3   19 , Mirthe Muilwijk  24   25 , Marieke T Blom  25   26 , Leen M 't Hart  24   25   27   28 , Juliana C N Chan  1   2   3   4 , Ronald C W Ma  29   30   31   32 ; Hong Kong Diabetes Biobank Study Group
Affiliations

Circulating metabolomic markers linking diabetic kidney disease and incident cardiovascular disease in type 2 diabetes: analyses from the Hong Kong Diabetes Biobank

Qiao Jin et al. Diabetologia. 2024 May.

Abstract

Aims/hypothesis: The aim of this study was to describe the metabolome in diabetic kidney disease (DKD) and its association with incident CVD in type 2 diabetes, and identify prognostic biomarkers.

Methods: From a prospective cohort of individuals with type 2 diabetes, baseline sera (N=1991) were quantified for 170 metabolites using NMR spectroscopy with median 5.2 years of follow-up. Associations of chronic kidney disease (CKD, eGFR<60 ml/min per 1.73 m2) or severely increased albuminuria with each metabolite were examined using linear regression, adjusted for confounders and multiplicity. Associations between DKD (CKD or severely increased albuminuria)-related metabolites and incident CVD were examined using Cox regressions. Metabolomic biomarkers were identified and assessed for CVD prediction and replicated in two independent cohorts.

Results: At false discovery rate (FDR)<0.05, 156 metabolites were associated with DKD (151 for CKD and 128 for severely increased albuminuria), including apolipoprotein B-containing lipoproteins, HDL, fatty acids, phenylalanine, tyrosine, albumin and glycoprotein acetyls. Over 5.2 years of follow-up, 75 metabolites were associated with incident CVD at FDR<0.05. A model comprising age, sex and three metabolites (albumin, triglycerides in large HDL and phospholipids in small LDL) performed comparably to conventional risk factors (C statistic 0.765 vs 0.762, p=0.893) and adding the three metabolites further improved CVD prediction (C statistic from 0.762 to 0.797, p=0.014) and improved discrimination and reclassification. The 3-metabolite score was validated in independent Chinese and Dutch cohorts.

Conclusions/interpretation: Altered metabolomic signatures in DKD are associated with incident CVD and improve CVD risk stratification.

Keywords: Cardiovascular disease; Diabetic kidney disease; Metabolomics; NMR spectroscopy; Prognostic biomarker; Risk stratification; Severely increased albuminuria; Type 2 diabetes.

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Figures

Fig. 1
Fig. 1
Metabolites associated with CKD (a) or severely increased albuminuria (b). Estimated by linear regression adjusted for age, male sex, ever smoking, diabetes duration, SBP, BMI, HbA1c, oral glucose-lowering drugs, insulin, antihypertensive drugs, lipid-lowering drugs, RAS blockers, statins, diabetic retinopathy and severely increased albuminuria (for the association with severely increased albuminuria, CKD was included instead). Metabolites were loge-transformed and scaled to SD. The top 20 most significant metabolites were named
Fig. 2
Fig. 2
Associations between DKD-related metabolites and incident CVD. Estimated by Cox regression adjusted for age, male sex, ever smoking, diabetes duration, SBP, BMI, HbA1c, oral glucose-lowering drugs, insulin, antihypertensive drugs, lipid-lowering drugs, RAS blockers, statins and diabetic retinopathy. Metabolites were loge-transformed and scaled to SD. *p<0.05; **p<0.01
See this image and copyright information in PMC

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