A High Serum Cortisol/DHEA-S Ratio Is a Risk Factor for Sarcopenia in Elderly Diabetic Patients

Ikumi Yanagita; Yuya Fujihara; Yuichi Kitajima; Misuzu Tajima; Masanao Honda; Tomoko Kawajiri; Terumi Eda; Kazue Yonemura; Noriko Yamaguchi; Hideko Asakawa; Yukiko Nei; Yumi Kayashima; Mihoko Yoshimoto; Mayumi Harada; Yuhei Araki; Shoji Yoshimoto; Eiji Aida; Toshihiko Yanase; Hajime Nawata; Kazuo Muta

Disclosures

J Endo Soc. 2019;3(4):801-813. 

In This Article

Results

Among the 108 elderly patients with T2DM with CFS stages 1 to 7, 38 had sarcopenia (13 males, 25 females), whereas 70 did not have sarcopenia (34 males, 36 females). Among the 108 patients, 7 were hospitalized, whereas the other 101 were outpatients. Among the seven hospitalized patients, six were categorized as having severe sarcopenia, whereas one was nonsarcopenic. Accordingly, the incidence of sarcopenia was 35.2%.

Table 1 shows the characteristics of elderly patients with T2DM stratified by the presence or absence of sarcopenia. Compared with patients without sarcopenia, patients with sarcopenia were significantly older and had a significantly lower bodyweight, BMI, DBP, red blood cell count, Hb concentration, and ALT concentration (P = 0.016 for ALT; P < 0.001 for the other variables). There were no differences between the groups with and without sarcopenia regarding sex, duration of T2DM, systolic blood pressure, serum concentrations of aspartate aminotransferase, creatinine, uric acid, triglycerides, LDL-C, HDL-C, and calcium, estimated glomerular filtration rate, and HbA1c concentration.

Compared with patients without sarcopenia, those with sarcopenia had a significantly lower serum DHEA-S concentration (P < 0.001) and a significantly higher serum cortisol concentration (P = 0.005). This resulted in a significantly higher cortisol/DHEA-S ratio in patients with sarcopenia than in those without sarcopenia (P = 0.004).

The ABI was significantly lower in patients with sarcopenia than in those without sarcopenia (P = 0.027). There were no significant differences between the groups with and without sarcopenia in the MMSE score, an arteriosclerotic marker (brachial-ankle pulse wave velocity), and an osteoporosis marker (vertebral young adult mean). However, the MMSE score tended to be lower in patients with sarcopenia than in those without sarcopenia (P = 0.072).

Regarding the diagnostic markers of sarcopenia, walking speed, grip strength, and the skeletal mass index were all significantly lower in patients with sarcopenia than in those without sarcopenia (all P < 0.001). In other physical ability tests, patients with sarcopenia had a significantly shorter ratio of two steps/height (P < 0.001) and a significantly longer standing time from a chair (P = 0.024) than did those without sarcopenia. These findings support the relative decrease in physical ability of patients with vs without sarcopenia.

The prevalence of frailty in accordance with the CFS criteria was significantly higher in patients with sarcopenia than in those without sarcopenia (P = 0.048). There was no difference between the groups with and without sarcopenia in the frequency of administration of antihypertensive or antidyslipidemia drugs. There were also no significant differences between the two groups in the type and number of T2DM medications.

Table 2 summarizes the results of single regression analysis or multivariate analysis by binary logistic regression analysis performed to clarify the risk factors for sarcopenia in elderly patients with T2DM. In single regression analysis without adjustment, all assessed variables showed significance for detecting sarcopenia, including age ≥75 years, BMI ≥25 kg/m2, DBP <70 mm Hg, red blood cell count <420 × 104/mL, Hb concentration <13 g/dL, cortisol/DHEA-S ratio ≥0.2 (all P < 0.001), ALT <22 IU/L (P = 0.05), DHEA-S concentration <73 μg/dL (P = 0.003), ABI <1.0 (P = 0.009), and presence of frailty (P = 0.039) (Table 2). Variables with P < 0.05 were then selected for use in the multiple binary regression model. Among the three variables of DHEA-S concentration, cortisol concentration, and the cortisol/DHEA-S ratio, the most significant variable (cortisol/DHEA-S ratio) was chosen as the explanatory variable based on the collinear characteristics between two variables. Multiple binary regression analysis revealed that DBP <70 mm Hg (P = 0.023), Hb concentration <13 g/dL (P = 0.040), cortisol/DHEA-S ratio ≥0.2 (P = 0.005), and ABI <1.0 (P = 0.015) remained significant independent risk factors for sarcopenia (Table 2). Importantly, the presence of frailty was not an independent risk factor for sarcopenia.

Table 3 summarizes the results of ROC analysis of various variables for the detection of sarcopenia. When the AUC was provided by ROC analysis based on single regression analysis, the AUC of the cortisol/DHEA-S ratio was the highest (0.769), followed by that of Hb concentration (0.734), DBP (0.711), and DHEA-S concentration (0.709) (Table 3).

The patients were divided into four groups in accordance with the severity of sarcopenia: no sarcopenia (n = 54), presarcopenia (n = 16), sarcopenia (n = 18), and severe sarcopenia (n = 20). With an increase in the severity of sarcopenia, there were significant increases in age (P < 0.001), cortisol concentration (P = 0.004), and the cortisol/DHEA-S ratio (P < 0.001), whereas there were significant decreases in BMI (P < 0.001), DHEA-S concentration (P < 0.001), DBP (P = 0.001), Hb concentration (P< 0.001), and MMSE score (P = 0.009). Frailty was most common in the severe sarcopenia group, and the incidence of frailty significantly increased with the severity of sarcopenia (P = 0.032). The ABI did not show a significant trend of change in accordance with the severity of sarcopenia (Figure 1).

Figure 1.

Important variables for sarcopenia stratified by the severity of sarcopenia. The graphs are plotted as mean ± SD. P values were determined by the Jonckheere–Terpstra test for increased or decreased tendency of continuous variables. Differences in percentages of frailty were investigated by the χ 2 test. *P < 0.05, **P < 0.01, ***P < 0.001 vs nonsarcopenia as determined by a multiple comparison method (Fisher least significant difference test) after ANOVA.

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