Potential Biomarkers for Predicting of Depression in Diabetes Mellitus

Abstract

Background To identify the potential biomarkers for predicting depression in diabetes mellitus using the support vector machine technique to analyze routine biochemical tests and vital signs between two groups: subjects with both diabetes mellitus and depression, and subjects with diabetes mellitus alone. Methods Electronic medical records upon admission and biochemical tests and vital signs of 135 patients with both diabetes mellitus and depression and 178 patients with diabetes mellitus alone were identi ed for this retrospective study. After the covariate regression analysis on age and sex, the two groups were classi ed by the recursive feature elimination-based support vector machine and the biomarkers were also identi ed by 10-fold cross validation. Speci cally, the training data, evaluation data, and testing data were split for ranking the parameters, determine the optimal parameters, and assess classi cation performance. Results The experimental results identi ed 12 predictive biomarkers with classi cation accuracy of 74%. The 12 biomarkers are hydroxybutyrate, magnesium, hydroxybutyrate dehydrogenase, creatine kinase, total protein, high-density lipoprotein cholesterol, cholesterol, absolute value of the lymphocyte, blood urea nitrogen, chlorine, platelet count, and glutamyltranspeptidase. Receiver operating characteristic curve analysis was also used with area under the curve being 0.79. Conclusions Some biochemical parameters may be potential biomarkers to predict depression among the subjects with diabetes mellitus. Background Diabetes mellitus is a chronic illness affecting about 347 million people worldwide in 2017, and this number is expected to increase more than half by 2035 [1, 2]. The disease will also lead to emotional distress other than physical symptoms and impose psychosocial impacts on life quality, which complicates its management. Depression and diabetes mellitus are common comorbid conditions [3]. A meta-analysis reported that patients with diabetes mellitus more than doubled the odds of developing depression [3]. Another study described that depression was highly prevalent, affecting approximately 26% of the patients with diabetes mellitus [4]. In addition, depression was found to be associated with a greater number of complications of diabetes mellitus [5]. Furthermore, depression itself is a disabling disease and imposes