The significance of routine biochemical markers in patients with major depressive disorder

The aim of our study is to examine the levels of routine biochemical markers in patients with major depressive disorder (MDD), and combine multiple biochemical parameters to assess the discriminative power for patients with MDD. We used the Hamilton Depression (HAMD) score to evaluate the severity of depressive symptoms in 228 patients with MDD. The phase of depression severity was between moderate and severe in MDD patients. There were significant differences between MDD patients and healthy controls in alanine transaminase (ALT), urea nitrogen (UN), lactate dehydrogenase (LDH), uric acid (UA), total protein (TP), total bile acid (TBA), creatinine (Cr), total bilirubin (Tbil), direct bilirubin (Dbil) and indirect bilirubin (Ibil), high density lipoprotein-cholesterol (HDL-C), fasting blood-glucose (FBG) and fructosamine (SF). Multivariate analysis showed that UN, FBG, HDL-C, SF, TP, Cr and Tbil remained independently association with MDD. Further, a logit equation was established to identify patients with MDD. The composite markers exhibited an area under the curve of 0.810 with cut-off values of 0.410. Our results suggest the associations between UN, FBG, HDL-C, TP, Cr, Tbil, SF and MDD, use of these routine biochemical markers in combination may contribute to improve the complete management for patients with MDD.

A total of 251 healthy subjects with healthy diet at least one month were selected as controls, and all healthy individuals were no history of head trauma history, psychiatric disorder, neurological disorder in this study. The study was performed in accordance with the Declaration of Helsinki, and approved by the Ethics Committee of the Affiliated Hospital of Youjiang Medical University for Nationalities, and informed consent was obtained from all individuals.
Statistical analysis. Statistical analyses were performed with the statistical package SPSS version 16.0. All continuous variables were expressed as mean (±standard deviation), and categorical variables were expressed as percentage. A significant calculation for sample size was performed by Quanto software. The normality of data was tested with Kolmogorov-Smirnov test. The differences between continuous variables were compared by student t test or Mann-Whitney U test as appropriate. Demographic data were compared by Chi-square test. We used stepwise logistic regression analysis to identify underlying biochemical parameters associated with depressive disorder. Hosmer-Lemeshow test was also used to examine an identified effectiveness of model. An identified performance of the combinations of biochemical markers was analyzed by receiver operating characteristic (ROC) curve. P < 0.05 was considered statistically significant.
Cumulative results for biochemical tests were obtained from patients with MDD and controls. The laboratory characteristics were outlined in Table 2. Several significant differences were observed between the two groups, lower values of ALT, UN, LDH, UA, TP, TBA, Cr, Tbil, Dbil, Ibil were found to be statistical significance in patients with MDD compared with controls. In contrast, the levels of HDL-C, fasting blood-glucose (FBG) and SF were higher in patient with MDD than controls. The other laboratory markers had not significant differences between the two groups.
Statistically significant variables in univariate analysis were considered into stepwise logistic regression analysis, the results of logistic regression analysis showed that UN, FBG, HDL-C, SF, TP, Cr and Tbil remained independently association with MDD (Table 3). Regression coefficients of these biochemical markers were used to calculate a logit equation for the assessment of patients with MDD as follows: The logarithm of This calculated model was evaluated by using Hosmer-Lemeshow test (P = 0.325, Chi-square = 9.212). To evaluate the performance of combined biomarkers for patients with MDD, the sensitivity, specificity and area under the curve (AUC) of these markers in combination were calculated, respectively ( Table 4). The composite markers exhibited an AUC of 0.810 (95% CI: 0.796-0.846, P < 0.001) with the sensitivity of 0.806 and specificity of 0.636, and a cut-off values was defined with 0.410, indicating a more better effectiveness in identifying patients with MDD than all single markers.

Discussion
To this day, there are few objective and available laboratory markers to estimate completely pathological conditions in patients with MDD, and single laboratory marker is often the lack of well sensitivity and specificity. Clinical biochemical tests are routine hospital examinations in clinical practice. This investigation found that UN, FBG, HDL-C, SF, TP, Cr and Tbil were independently associated with MDD in logistic regression analysis. Further, our study revealed that use of these markers in combination could provide useful and objective information in the assessment for patients with MDD.
Oxidative stress derives from increased production of reactive oxygen species, which leads to cell damage by biological reactions such as lipid peroxidation, enzyme inactivation and DNA modification 17 . Previous studies have demonstrated that oxidative stress related enzymes are associated with the pathogenic process of patients with depression, and anti-oxidative enzymes activity is increased in patients suffering from depressive disorder 18,19 . Emerging evidence has suggested that several inflammatory cytokines such as interleukin-1 (IL-1) beta, IL-6 and TNF are implicated with oxidative stress in patients with MDD 20,21 . Interesting, oxidative stress process has also been observed in the frontal cortex of patients with recurrent depressive disorder 22 . Moreover, the xanthine oxidase activity is increased in the thalamus and the putamen of patients with depression, which tends to induce oxidative stress by an increased production of reactive oxygen species 23 . These reports provide an important fact that oxidative stress may be a major contributor in the pathogenesis of MDD. There is no literature available with respect to serum bilirubin levels in patients with MDD, serum bilirubin levels in patients MDD were found to be decreased, and lower Tbil concentrations were associated with MDD in the present study. Bilirubin, the end product of heme catabolism, is an efficient and powerful antioxidant, the role of bilirubin in regarding with oxidation resistance, anti-inflammation and immunosuppression has been demonstrated in various diseases 24 . Indeed, lower serum levels of bilirubin have been reported in patients with migraine, carbon monoxide-poisoned and pulmonary embolism [25][26][27][28] , and serum bilirubin may provide a protective action in patients with cardiovascular disease and rheumatic disease 29,30 . In these studies, bilirubin as an endogenous antioxidant may be destroyed by excessive oxidative stress. Thus, the presence of oxidative stress may result in overconsumption of serum bilirubin, which is associated with lower bilirubin in patients with MDD. Higher levels of HDL-C have been reported in patients with depression 31 . In agreement with this finding, increased levels of HDL-C were demonstrated to be associated with MDD patients in our study. In addition, we observed lower concentrations of UN and TP in patients compared to healthy controls, the findings are consistent with recently reports on MDD patients 32 . Serum Cr concentrations were decreased in MDD patients compared with controls, the results may attribute to poor appetite and nutrition in patients with MDD, because accompanied anorexia has a high prevalent in patients with MDD 33,34 . Of note, increased levels of FBG and SF were found to be associated with MDD in our study. Oxidative stress is a crucial player in the establishment of insulin resistance and diabetes mellitus 35 . In fact, oxidative stress has been regarded as an underlying mediator of insulin resistance, and there is an inversely relation between oxidative stress and insulin action 36,37 . Studies have shown that oxidative stress can decrease insulin sensitivity by GLUT-4 deficiency 38 . Furthermore, major insulin secretion has been found to be dependent on the regulation of intracellular and extracellular reactive oxygen species to a certain extent 39 . It has recently been shown that oxidative stress may increase induction of HO-1 expression, leading to insulin resistance and insufficient insulin 35 . Obviously, enhanced oxidative stress may result in insulin resistance and influence on insulin secretion in patients with depressive disorder. Nevertheless, elevated FBG and SF have been positively correlated with insulin resistance and insufficient insulin response in diabetic and non-diabetic patients 40 , which are associated with increase in serum FBG and SF concentrations in patients with MDD.
Our study provides an insight on the role of combination markers of UN, FBG, HDL-C, SF, TP, Cr and Tbil in patients with MDD. Specific and sensitive laboratory indexes have been limited in the diagnosis of depressive disorder. In clinical practice, the diagnosis of MDD main depends on physician's clinical experiences, clinical symptoms and patient's self-assessments. In the current study, these biochemical parameters are objective and available, the composite information from these routine biochemical markers may improve the diagnostic effectiveness of depressive disorder.
We are aware that this study has several limitations. First, our study only included Chinese Han nationality in this cross-sectional design. Second, the differences of dietary habit might have effect on biochemical parameters in different regions and groups, which limit the extrapolation effect of our results. Third, the diagnostic power had to be improved for the logarithm of odds, because other clinical information was not obtained as variables in multivariate analysis. Taken together, our results suggest the associations between UN, FBG, HDL-C, SF, TP, Cr, Tbil and MDD, use of these biochemical markers in combination may contribute to improve the complete management for patients with MDD. However, our results are needed to be further established with multicenter and larger-scale study.  Table 4. Estimated performances of all single markers and combined markers by ROC curve.