Associations Between Plasma Growth and Differentiation Factor-15 with Aging Phenotypes in Muscle, Adipose Tissue, and Bone.

Growth and differentiation factor 15 (GDF-15) is associated with muscle, fat, and bone metabolism; however, this association has not been well characterized. Plasma GDF-15, appendicular skeletal muscle mass (ASM), fat mass (FM), and bone mineral density (BMD) were measured in 146 postmenopausal women. GDF-15 levels were higher in subjects with low Body Mass Index (BMI)-adjusted ASM than in those without (median [interquartile range] 831.3 [635.4-1011.4] vs. 583.8 [455.8-771.1] pg/mL, p = 0.018). The GDF-15 level was inversely correlated with BMI-adjusted ASM (r = - 0.377, p < 0.001) and BMD at femur neck (FN-BMD; r = - 0.201, p = 0.015), and positively correlated with percent FM (pFM; r = 0.328, p < 0.001). After adjusting for confounders, the GDF-15 level was inversely associated with BMI-adjusted ASM (ß = -0.250, p = 0.006) and positively associated with pFM (ß = 0.272, p = 0.004), and tended to be inversely associated with FN-BMD (ß = - 0.176, p = 0.076). The area under the receiver-operating characteristic curve of GDF-15 level > 618.4 pg/mL for sarcopenia was 0.706 (95% confidence interval (CI) 0.625-0.779) with a sensitivity of 83.3% and a specificity of 54.5%. Using a GDF-15 level of 618.4 pg/mL as a cut-off, the GDF-15 level was associated with a significantly greater likelihood of sarcopenia (odds ratio [OR] 2.35; 95% CI 1.00-5.51; p = 0.049), obesity (OR 3.28; 95% CI 1.48-7.27; p = 0.001), osteopenic obesity (OR 3.10; 95% CI 1.31-7.30; p = 0.010), and sarcopenic or osteosarcopenic obesity (OR 4.84; 95% CI 0.88-26.69; p = 0.070). These findings support the potential of GDF-15 as a biomarker for age-related changes in muscle, fat, and bone.

Associations of Circulating Levels of Sphingosine 1-Phosphate with the Trabecular Bone Score and Bone Mineral Density in Postmenopausal Women.

Despite the potential roles of sphingosine 1-phosphate (S1P) as a biomarker of osteoporotic fracture (OF), independent of bone mineral density (BMD) and clinical risk factors (CRFs), its association with bone microarchitecture, a key determinant of bone quality, have not been studied yet. We here investigated the association of S1P with the trabecular bone score (TBS), an index of the bone microarchitecture. The plasma S1P concentrations, TBS, and BMD were measured in the 339 postmenopausal women. The S1P level was inversely correlated with the TBS (γ=-0.096, p=0.049) and BMD at the femur neck (FN-BMD: γ=-0.122, p=0.025) and tended to be inversely correlated the BMD at the total hip (TH-BMD: γ=-0.096, p=0.079), but not at the lumbar spine (LS-BMD). After adjusting for fracture risk assessment tool probabilities of major OF from CRFs, the S1P level was inversely associated with the TBS (ß=-0.096, p=0.049) and FN-BMD (ß=-0.118, p=0.025) and tended to be inversely associated with the TH-BMD (ß=-0.092, p=0.083). Compared with subjects in the lowest S1P tertile, those in the highest S1P tertile had a significantly lower TBS (p=0.032) and BMD at femur (p=0.004-0.036). These findings indicated that a high S1P level in postmenopausal women was inversely associated with the both bone mass and microarchitecture, reflecting the compromised bone strength.

High Circulating Sphingosine 1-Phosphate is a Risk Factor for Osteoporotic Fracture Independent of Fracture Risk Assessment Tool.

Circulating sphingosine 1-phosphate (S1P) levels may be a biomarker for osteoporotic fracture (OF). This study assessed whether the addition of S1P levels to the fracture risk assessment tool (FRAX) could improve predictability of OF risk. Plasma S1P concentrations and FRAX variables were measured in 81 subjects with and 341 subjects without OF. S1P levels were higher in subjects with than those without OF (3.11 ± 0.13 µmol/L vs. 2.65 ± 0.61 µmol/L, P = 0.001). Higher S1P levels were associated with a higher likelihood of OF (odds ratio [OR] = 1.33, 95% confidence interval [CI] = 1.05-1.68), even after adjusting for FRAX probabilities. Compared with the lowest S1P tertile, subjects in the middle (OR = 3.37, 95% CI = 1.58-7.22) and highest (OR = 3.65, 95% CI = 1.66-8.03) S1P tertiles had higher rates of OF after adjustment. The addition of S1P levels to FRAX probabilities improved the area under the receiver-operating characteristics curve (AUC) for OF, from 0.708 to 0.769 (P = 0.013), as well as enhancing category-free net reclassification improvement (NRI = 0.504, 95% CI = 0.271-0.737, P < 0.001) and integrated discrimination improvement (IDI = 0.044, 95% CI = 0.022-0.065, P < 0.001). Adding S1P levels to FRAX probabilities especially in 222 subjects with osteopenia having a FRAX probability of 3.66-20.0% markedly improved the AUC for OF from 0.630 to 0.741 (P = 0.012), as well as significantly enhancing category-free NRI (0.571, 95% CI = 0.221-0.922, P = 0.001) and IDI (0.060, 95% CI = 0.023-0.097, P = 0.002). S1P is a consistent and significant risk factor of OF independent of FRAX, especially in subjects with osteopenia and low FRAX probability.

A Two-Step Approach to Overcoming Data Imbalance in the Development of an Electrocardiography Data Quality Assessment Algorithm: A Real-World Data Challenge.

Continuously acquired biosignals from patient monitors contain significant amounts of unusable data. During the development of a decision support system based on continuously acquired biosignals, we developed machine and deep learning algorithms to automatically classify the quality of ECG data. A total of 31,127 twenty-s ECG segments of 250 Hz were used as the training/validation dataset. Data quality was categorized into three classes: acceptable, unacceptable, and uncertain. In the training/validation dataset, 29,606 segments (95%) were in the acceptable class. Two one-step, three-class approaches and two two-step binary sequential approaches were developed using random forest (RF) and two-dimensional convolutional neural network (2D CNN) classifiers. Four approaches were tested on 9779 test samples from another hospital. On the test dataset, the two-step 2D CNN approach showed the best overall accuracy (0.85), and the one-step, three-class 2D CNN approach showed the worst overall accuracy (0.54). The most important parameter, precision in the acceptable class, was greater than 0.9 for all approaches, but recall in the acceptable class was better for the two-step approaches: one-step (0.77) vs. two-step RF (0.89) and one-step (0.51) vs. two-step 2D CNN (0.94) (p < 0.001 for both comparisons). For the ECG quality classification, where substantial data imbalance exists, the 2-step approaches showed more robust performance than the one-step approach. This algorithm can be used as a preprocessing step in artificial intelligence research using continuously acquired biosignals.

Effects of Primary Aldosteronism and Different Therapeutic Modalities on Glucose Metabolism.

Despite findings that aldosterone impairs glucose metabolism, studies concerning the effect of primary aldosteronism (PA) and its treatment on glucose metabolism are controversial. We aimed to determine glucose metabolism in PA and the effect of the treatment modality. We compared glucose metabolism between PA patients (N = 286) and age-, sex-, and body mass index-matched controls (N = 816), and the changes in glucose metabolism depending on the treatment modality (adrenalectomy vs. spironolactone treatment). Hyperglycemia including diabetes mellitus (DM; 19.6% vs. 13.1%, p = 0.011) was more frequent in PA patients. Hyperglycemia was also more frequent in PA patients without subclinical hypercortisolism (SH: p < 0.001) and in those regardless of hypokalemia (p < 0.001-0.001). PA patients and PA patients without SH had higher DM risk (odds ratio (OR); 95% confidence interval (CI): 1.63; 1.11-2.39 and 1.65; 1.08-2.51, respectively) after adjusting confounders. In PA patients, there was significant decrease in the DM prevalence (21.3% to 16.7%, p = 0.004) and fasting plasma glucose (p = 0.006) after adrenalectomy. However, there was no significant change in them after spironolactone treatment. Adrenalectomy was associated with more improved glucose status than spironolactone treatment (OR; 95% CI: 2.07; 1.10-3.90). Glucose metabolism was impaired in PA, regardless of hypokalemia and SH status, and was improved by adrenalectomy, but not spironolactone treatment.