13 biomarkers predict CVD risk in T2DM

An international team of experts has identified 13 promising biomarkers to predict cardiovascular disease (CVD) risk in patients with type 2 diabetes mellitus (T2DM), of which N-terminal pro-brain natriuretic peptide (NT-proBNP) has shown the highest predictive utility with highest strength of evidence.

T2DM patients have a 1.5- to 2-fold increased risk of developing CVD vs those without T2DM. Although early identification of at-risk populations may facilitate early intervention, it remains challenging for clinicians to predict which patients are most likely to develop CVD. [Nat Med 2024;doi:10.1038/s43856-023-00429-z]

Twenty-three experts from 11 countries, led by researchers from the Chinese University of Hong Kong (CUHK), Johns Hopkins University and Lund University, conducted a systematic review and meta-analysis to identify promising biomarkers that could enhance CVD risk prediction in T2DM. “We wanted to look beyond traditional prognostic factors such as hypertension and smoking,” said coauthor Professor Maria Gomez of the Lund University Diabetes Centre, Malmö, Sweden.

The researchers screened 9,380 observational studies published between 1990 and 2021 on PubMed, Embase, and from other sources. A total of 218 studies involving 195 biomarkers were analyzed. “Our study represents the largest and most ambitious overview of the state of knowledge on CVD risk prediction in T2DM to date,” remarked coauthor Dr Nestoras Mathioudakis of the School of Medicine, Johns Hopkins University, Maryland, US.

Of 195 evaluated biomarkers, only 13 were significantly associated with CVD risk in T2DM patients. NT-proBNP, troponin-T (TnT), triglyceride-glucose (TyG) index, and risk score for coronary heart disease were found to be the most promising biomarkers with high predictive utility.

Of note, NT-proBNP was found to have the highest predictive utility with the highest strength of evidence. A study included in the current review showed that each standard deviation increase in NT-proBNP level was associated with a 64 percent increased risk of CVD development (hazard ratio, 1.64; 95 percent confidence interval, 1.53─1.75; p<0.05).

“Our findings suggest that NT-proBNP, beyond its established role in diagnosis and management of heart failure, might also be used as a biomarker to predict CVD risk in T2DM patients,” pointed out the researchers.

Other identified biomarkers demonstrated varying levels of predictive utility. Coronary CT angiography, single-photon emission CT, and pulse wave velocity showed moderate predictive utility, while C-reactive protein, coronary artery calcium score, galectin-3, troponin-1, carotid plaque, and growth differentiation factor-15 had low predictive utility.

Beyond individual prognostic biomarkers, the researchers also identified studies that evaluated CVD risk prediction models, including the UK Prospective Diabetes Study (UKPDS) risk engine and Framingham risk equation. “However, they do not perform well in contemporary studies of T2DM,” commented the researchers. “This suggests difficulties in applying certain risk models to current healthcare settings.”

“Our study highlights the potential for incorporating emerging biomarkers into clinical risk prediction and the potential for precision medicine in T2DM management,” said coauthor Professor Ronald Ma of the Division of Endocrinology and Diabetes, CUHK. “More rigorous studies to test these biomarkers are needed. If their predictive values are validated, we may be able to change the standard of care.”