Introduction: Type 1 diabetes (T1D) increases risk for cardiovascular disease (CVD) at least 2-4 fold, with only half the excess risk explained by known risk factors. We sought to identify novel proteomic, lipidomic, and metabolomic biomarkers of CVD in T1D.

Methods: We first built a predictive model of coronary artery calcium progression (CACp) using LASSO regression of clinical variables measured at baseline in 365 participants with T1D in the Coronary Artery Calcification in Type 1 Diabetes (CACTI) study. The selected model was refit to a subgroup of 102 participants with complete clinical information and measured omics markers (targeted and untargeted metabolomics, global proteomics, glycated proteomics, and lipidomics) . Omics biomarkers were identified for inclusion in the final model by retaining the top markers that predicted CACp by moderated t-tests and sPLS-DA models.

Results: The table shows variables retained in the clinical model (AUC=0.91) and in the model with biomarkers added (AUC=0.94) . Higher age, urine albumin:creatinine, and insulin dose predicted CACp in both models. Longer duration of T1D predicted CACp in the clinical model. In the model with D-Glucosamine/D-galactosamine and glycated fibrinogen peptides, D-Glucosamine/D-Galactosamine predicted CACp.

Conclusion: Novel metabolites improved prediction of CACp in people with T1D.


L.Pyle: None. T.B.Vigers: None. R.K.Johnson: None. Q.Zhang: None. J.K.Snell-bergeon: Stock/Shareholder; GlaxoSmithKline plc.


American Heart Association (17CSA33570025) , NIH (P30-DK116073)

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