4 blood biomarkers may help improve T2D prediction in Chinese

Using a composite score of four blood biomarkers may be useful for predicting the risk of type 2 diabetes (T2D) in a Chinese population, suggests a nested case-control analysis of the Singapore Chinese Health Study (SCHS).    

The four biomarkers that were significantly associated with the risk of developing T2D were plasma triglyceride (TG)-to-HDL ratio, alanine transaminase (ALT), ferritin, and adiponectin. [Diabetes Metab J 2019;doi:10.4093/dmj.2019.0020]

For each quartile increment of the respective biomarker, T2D risk increased by 48 percent (odds ratio [OR], 1.48, 95 percent confidence interval [CI], 1.21–1.82) for TG-to-HDL ratio, by 30 percent (OR, 1.30, 95 percent CI, 1.08–1.57) for ALT, and by 24 percent for ferritin (OR, 1.24, 95 percent CI, 1.04–1.48). In contrast, each quartile increment of adiponectin was associated with a 28 percent reduction in T2D risk (OR, 0.72, 95 percent CI, 0.60–0.86).

“We have shown the utility of a composite score of four biomarkers as a predictor of T2D in a Chinese population, and our findings suggest that this score is a promising marker as a screening tool to identify at-risk individuals for targeted diet and lifestyle intervention,” said the researchers led by Dr Wang Yeli of Duke-NUS Medical School, Singapore.

Based on the strength of the associations, Wang and colleagues created a weighted biomarker score comprising the four biomarkers and tested the predictive performance using data of 485 T2D cases matched by age and sex to 485 controls nested within the prospective SCHS cohort (mean age 59.4 years, 56.3 percent female). All participants were free of T2D when blood samples were first collected at baseline. Blood sampling was performed again during follow-up interviews to identify participants who developed T2D.

The researchers found a positive association between the biomarker score and T2D risk: the higher the biomarker score, the more likely the participants were to develop T2D subsequently (p-trend <0.001). Compared with those with the lowest quartile score, participants in the highest quartile were 12 times more likely (OR, 12.0, 95 percent CI, 5.43–26.6) to develop T2D.

When the biomarker score was added to a base predictive model that included age, BMI, history of hypertension, smoking, and levels of random glucose and insulin, the predictive utility — as indicated by area under the curve (AUC) — improved significantly from 0.81 to 0.83 (p=0.002).

Furthermore, in another base model as above but included HbA1c in place of random glucose levels, adding the biomarker score again improved AUC from 0.85 to 0.86 (p=0.032).

“The biomarker score significantly improved the T2D prediction, and it correctly reassigned 32.0 percent cases to higher T2D risk and 15.5 percent controls to lower T2D risk. Collectively, our results suggested that joint analysis of multiple biomarkers may be a useful tool to predict T2D risk,” Wang and colleagues pointed out.

While these biomarkers have been shown to improve prediction of T2D risk over traditional clinical risk factors in Western populations, this is the first prospective study on a Chinese population, the researchers highlighted.

“Although the clinical usefulness of the biomarker score has been shown in the current study, whether the biomarker score is also cost-effectiveness is unclear yet,” said Wang and colleagues. “Among the four biomarkers, TG-to-HDL ratio and ALT are routinely tested in the clinical setting, while measurements for adiponectin and ferritin are less common and could be expensive.”

They suggested more studies be done to assess the cost-effectiveness of the biomarkers and to validate the current findings, which may be limited by one-time collection of blood samples and lack of information such as waist circumference and family history of T2D.