Correlation between fat-to-muscle mass ratio and cognitive impairment in elderly patients with type 2 diabetes mellitus: a cross-sectional study.

BACKGROUND: Fat to muscle mass ratio (FMR), a novel index integrating fat and muscle composition, has garnered attention in age-related conditions such as type 2 diabetes mellitus (T2DM) and neurodegenerative diseases. Despite this research on the relationship between FMR and cognitive impairment (CI) in T2DM remains scarce. This study aimed to investigate the sex-specific association between FMR and CI in elderly T2DM patients. METHODS: A total of 768 elderly (> 60 years) T2DM in-patients (356 men and 412 women) were recruited from the Department of Endocrinology at Tianjin Nankai University affiliated hospital. Bioelectrical Impedance Analysis (BIA) was used to assess body composition, and Montreal Cognitive Assessment (MoCA) was used to evaluate cognitive performance. T2DM patients were categorized into normal cognitive function (NC) and cognitive impairment (CI) groups based on MoCA scores and stratified by sex. Binary logistic regression was employed to examine the association between FMR and CI. RESULTS: Among the participants, 42.7% of men and 56.3% of women experienced cognitive deterioration. Women with CI exhibited lower body mass index (BMI) and skeletal muscle mass index (SMI), while men with cognitive disorders showed lower SMI, FMR, and higher fat mass index (FMI). FMR was consistently unrelated to cognition in females, irrespective of adjustment made. However, in males, FMR was significantly associated with an increasing risk of cognitive dysfunction after adjusting for demographic and clinical variables (OR: 1.175, 95% CI: 1.045-1.320, p = 0.007). Furthermore, for each 0.1 increase in FMR, the incidence of CI rose by 31.1% after additional adjustment for BMI. In males, the prevalence of CI increased sequentially across FMR quartiles (p < 0.05). CONCLUSION: Elderly T2DM men with high FMR had unfavorable cognitive function. FMR is independently associated with an increased risk of CI in male T2DM patients regardless of BMI.

Effect of Sarcopenia on 10-Year Risk of Atherosclerotic Cardiovascular Disease in Patients with Type 2 Diabetes Mellitus.

Objective: To investigate the impact of sarcopenia on the 10-year risk of atherosclerotic cardiovascular disease (ASCVD) among individuals with type 2 diabetes mellitus (T2DM). Methods: This study included the clinical, laboratory, and body composition data of 1491 patients with T2DM who were admitted to the Department of Endocrinology and Metabolism at Tianjin Union Medical Center from July 2018 to July 2023. The China-PAR model was utilized to evaluate cardiovascular disease risk. Associations between ASCVD risk and various clinical parameters were analyzed, and the relationship between body composition parameters and ASCVD risk was assessed using logistic regression. Results: The analysis revealed that T2DM patients with sarcopenia had a higher 10-year ASCVD risk compared to those without sarcopenia, with reduced muscle mass independently predicting an increased risk of cardiovascular disease. This association was significant among female T2DM patients, while male T2DM patients with sarcopenia showed a marginally higher median ASCVD risk compared to their non-sarcopenic counterparts. ASCVD risk inversely correlated with body muscle parameters and positively correlated with fat content parameters. Specifically, height- and weight-adjusted fat mass (FM, FM%, FMI) were identified as risk factors for ASCVD. Conversely, muscle parameters adjusted for weight and fat (ASM%, SMM%, FFM%, ASM/FM, SMM/FM, FMM/FM) were protective against ASCVD risk. These findings highlight the critical role of sarcopenia in influencing cardiovascular disease risk among Chinese patients with T2DM, as predicted by the China-PAR model. Conclusion: This study highlights the importance of sarcopenia in T2DM patients, not only as an indicator of ASCVD risk, but possibly as an independent risk factor in this demographics.

Comparison of the RF-CL and CACS-CL models to estimate the pretest probability of obstructive coronary artery disease and predict prognosis in patients with stable chest pain and diabetes mellitus.

Background: The most appropriate tool for estimating the pretest probability (PTP) of obstructive coronary artery disease (CAD) in patients with diabetes mellitus (DM) and stable chest pain (SCP) remains unknown. Therefore, we aimed to validate and compare two recent models, namely, the risk factor-weighted clinical likelihood (RF-CL) model and coronary artery calcium score (CACS)-weighted clinical likelihood (CACS-CL) model, in these patient populations. Methods: A total of 1,245 symptomatic patients with DM, who underwent CACS and coronary computed tomographic angiography (CCTA) scan, were identified and followed up. PTP of obstructive CAD for each patient was estimated using the RF-CL model and CACS-CL model, respectively. Area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), and integrated discrimination improvement (IDI) were used to assess the performance of models. The associations of major adverse cardiovascular events (MACE) with risk groups were evaluated using Cox proportional hazards regression. Results: Compared with the RF-CL model, the CACS-CL model revealed a larger AUC (0.856 vs. 0.782, p = 0.0016), positive IDI (12%, p < 0.0001) and NRI (34%, p < 0.0001), stronger association to MACE (hazard ratio: 0.26 vs. 0.38) and less discrepancy between observed and predicted probabilities, resulting in a more effective risk assessment to optimize downstream clinical management. Conclusion: Among patients with DM and SCP, the incorporation of CACS into the CACS-CL model resulted in a more accurate estimation for PTP and prediction of MACE. Utilizing the CACS-CL model, instead of the RF-CL model, might have greater potential to avoid unnecessary and omissive cardiovascular imaging testing with minimal cost.

Metabolic-dysfunction associated steatotic liver disease-related diseases, cognition and dementia: A two-sample mendelian randomization study.

BACKGROUND: The results of current studies on metabolic-dysfunction associated steatotic liver disease (MASLD)-related diseases, cognition and dementia are inconsistent. This study aimed to elucidate the effects of MASLD-related diseases on cognition and dementia. METHODS: By using single-nucleotide polymorphisms (SNPs) associated with different traits of NAFLD (chronically elevated serum alanine aminotransferase levels [cALT], imaging-accessed and biopsy-proven NAFLD), metabolic dysfunction-associated steatohepatitis, and liver fibrosis and cirrhosis, we employed three methods of mendelian randomization (MR) analysis (inverse-variance weighted [IVW], weighted median, and MR-Egger) to determine the causal relationships between MASLD-related diseases and cognition and dementia. We used Cochran's Q test to examine the heterogeneity, and MR-PRESSO was used to identify outliers (NbDistribution = 10000). The horizontal pleiotropy was evaluated using the MR-Egger intercept test. A leave-one-out analysis was used to assess the impact of individual SNP on the overall MR results. We also repeated the MR analysis after excluding SNPs associated with confounding factors. RESULTS: The results of MR analysis suggested positive causal associations between MASLD confirmed by liver biopsy (p of IVW = 0.020, OR = 1.660, 95%CI = 1.082-2.546) and liver fibrosis and cirrhosis (p of IVW = 0.009, OR = 1.849, 95%CI = 1.169-2.922) with vascular dementia (VD). However, there was no evidence of a causal link between MASLD-related diseases and cognitive performance and other types of dementia (any dementia, Alzheimer's disease, dementia with lewy bodies, and frontotemporal dementia). Sensitivity tests supported the robustness of the results. CONCLUSIONS: This two-sample MR analysis suggests that genetically predicted MASLD and liver fibrosis and cirrhosis may increase the VD risk. Nonetheless, the causal effects of NAFLD-related diseases on VD need more in-depth research.

Risk factors for cognitive impairment in middle-aged type 2 diabetic patients: a cross-sectional study.

OBJECTIVE: The aim of this study was to investigate risk factors for cognitive impairment (CI) and explore the relationship between obesity and cognition in hospitalised middle-aged patients with type 2 diabetes (T2DM). METHODS: Subjects were divided into normal cognitive function (NCF) (n=320) and CI (n=204) groups based on the results of the Montreal Cognitive Assessment (MoCA) and Mini-Mental State Examination (MMSE). The risk factors for CI were determined by logistic regression analysis and generalised linear modelling. The associations between obesity parameters (body mass index (BMI) and waist circumference (WC)) and cognitive ability were studied with the use of linear regression analysis, piecewise regression modelling and interaction analysis. The receiver operating characteristic curve analysis was used to examine the diagnostic value of influencing factors for cc RESULTS: The prevalence of CI was 38.9% in hospitalised middle-aged T2DM patients (median age, 58 years). Age, WC, hypoglycaemic episode within past 3 months and cerebrovascular disease (CVD) were identified as independent risk factors for CI, while the independent protective factors were education, diabetic dietary pattern, overweight and obesity. BMI was a protective factor for the MoCA score within a certain range, whereas WC was a risk factor for the MMSE and MoCA scores. The area under the curve for the combination of BMI and WC was 0.754 (p<0.001). CONCLUSION: Age, education, diabetic dietary pattern, WC, overweight, obesity, hypoglycaemic episode in 3 months and CVD may be potential influencing factors for the occurrence of CI in hospitalised middle-aged population with T2DM. The combination of BMI and WC may represent a good predictor for early screening of CI in this population. Nevertheless, more relevant prospective studies are still needed.

Relationships Between Body Composition and Cognitive Impairment in Hospitalised Middle-Aged Type 2 Diabetic Patients.

Objective: The aim of this study was to elucidate the relationship between specific body composition and the risk of Cognitive Impairment (CI) in middle-aged Type 2 Diabetes Mellitus (T2DM) patients. Methods: This cross-sectional study included 504 hospitalized patients with T2DM from the Department of Endocrinology and Metabolism of the Tianjin Union Medical Center. Subjects were grouped by sex, and cognitive status was assessed using the Montreal Cognitive Assessment (MoCA). The relationship between body composition and cognitive ability was investigated with the use of linear regression analysis. The association between body composition and CI risk was determined by logistic regression analysis. Results: The prevalence of CI was 39.3% in middle-aged T2DM patients. After adjusting for age, education, marriage status, carotid atherosclerosis, cerebrovascular disease and hemoglobin, multiple linear regression analysis showed that lean mass index (LMI), body mass index (BMI) and appendicular skeletal muscle index (SMI) were significant predictors for the MoCA scores in men (p < 0.05). In addition, BMI (OR 0.913, 95% CI 0.840-0.992) and LMI (OR 0.820, 95% CI 0.682-0.916) were independent protective factors for CI in males. After adjusted for age, education, marriage status, dietary control of diabetes and cerebrovascular disease, visceral obesity (VO, OR 1.950, 95% CI 1.033-3.684) and abdominal obesity (AO, OR 2.537, 95% CI 1.191-5.403) were risk factors for CI in female patients. Conclusion: The results suggest that there may be different mechanisms underlying the relationship of body compositions and cognitive performance between middle-aged male and female patients with T2DM. In addition, our finding of potential determinants of cognitive impairment may facilitate the development of intervention programs for middle-aged type 2 diabetic patients. Nevertheless, more large prospective studies looking at cognition and changes in body composition over time are needed in the future to further support their association.

Association between Coronary Artery Disease Reporting and Data System-recommended Post-Coronary CT Angiography Management and Clinical Outcomes in Patients with Stable Chest Pain from a Chinese Registry.

Background Coronary Artery Disease Reporting and Data System (CAD-RADS) was developed to standardize and optimize disease management in patients after coronary CT angiography (CCTA), but the impact of CAD-RADS management recommendations on clinical outcomes remains unclear. Purpose To retrospectively assess the association between the appropriateness of post-CCTA management according to CAD-RADS version 2.0 and clinical outcomes. Materials and Methods From January 2016 to January 2018, consecutive participants with stable chest pain referred for CCTA were prospectively included in a Chinese registry and followed for 4 years. Retrospectively, CAD-RADS 2.0 classification and the appropriateness of post-CCTA management were determined. Propensity score matching (PSM) was used to adjust for confounding variables. Hazard ratios (HRs) for a major adverse cardiovascular event (MACE), relative risks for invasive coronary angiography (ICA), and the corresponding number needed to treat were estimated. Results Of the 14 232 included participants (mean age, 61 years ± 13 [SD]; 8852 male), 2330, 2756, and 2614 were retrospectively categorized in CAD-RADS 1, 2, and 3, respectively. Only 26% of participants with CAD-RADS 1-2 disease and 20% with CAD-RADS 3 received appropriate post-CCTA management. After PSM, appropriate post-CCTA management was associated with lower risk of MACEs (HR, 0.34; 95% CI: 0.22, 0.51; P < .001), corresponding to a number needed to treat of 21 in CAD-RADS 1-2 but not CAD-RADS 3 (HR, 0.86; 95% CI: 0.49, 1.85; P = .42). Appropriate post-CCTA management was associated with decreased use of ICA in CAD-RADS 1-2 (relative risk, 0.40; 95% CI: 0.29, 0.55; P < .001) and 3 (relative risk, 0.33; 95% CI: 0.28, 0.39; P < .001), resulting in a number needed to treat of 14 and 2, respectively. Conclusion In this retrospective secondary analysis, appropriate disease management after CCTA according to CAD-RADS 2.0 was associated with lower risk of MACEs and more prudent use of ICA. ClinicalTrials.gov registration no. NCT04691037 © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Leipsic and Tzimas in this issue.

Comparison of lipid accumulation product and visceral adiposity index with traditional obesity indices in early-onset type 2 diabetes prediction: a cross-sectional study.

BACKGROUND: The purpose of the study was to compare the efficacy of two novel obesity indices, lipid accumulation product (LAP) and visceral adiposity index (VAI), with traditional obesity indices in predicting early-onset type 2 diabetes (T2DM). METHODS: In this cross-sectional study, a total of 744 participants, including 605 patients newly diagnosed with T2DM and 139 non-diabetic control subjects, were enrolled from a tertiary care hospital in Tianjin, China. Participants with T2DM were divided into two groups based on their age at diagnosis, namely early-onset T2DM (age less than 40 years, n = 154) and late-onset T2DM (age 40 years or older, n = 451). The predictive power of each obesity index was evaluated using receiver operating characteristic (ROC) curve analysis. Furthermore, binary logistic regression analysis was conducted to examine the independent relationship between LAP and VAI with early-onset T2DM risk. The relationship between novel obesity indices and the age of T2DM onset was also evaluated through correlation and multiple linear regression analysis. RESULTS: In males, LAP had the highest predictive power for early-onset T2DM with an area under the ROC curve (AUC) of 0.742 (95% CI 0.684-0.799, P < 0.001). In females, VAI had the highest AUC for early-onset T2DM with a value of 0.748 (95% CI 0.657-0.839, P < 0.001), which was superior to traditional indices. Patients in the 4th quartile of LAP and VAI had 2.257 (95% CI 1.116-4.563, P = 0.023) and 4.705 (95% CI 2.132-10.384, P < 0.001) times higher risk of T2DM before age 40, compared to those in the 1st quartile, respectively. A tenfold increase in LAP was associated with a decrease in T2DM onset age of 12.862 years in males (ß = -12.862, P < 0.001) and 6.507 years in females (ß = -6.507, P = 0.013). A similar decrease in T2DM onset age was observed for each tenfold increase in VAI in both male (ß = -15.222, P < 0.001) and female (ß = -12.511, P < 0.001) participants. CONCLUSIONS: In young Chinese individuals, LAP and VAI are recommended over traditional obesity indices for improved prediction of early-onset T2DM risk.

Identification of TUL01101: A Novel Potent and Selective JAK1 Inhibitor for the Treatment of Rheumatoid Arthritis.

Janus kinase 1 (JAK1) is a potential target for the treatment of rheumatoid arthritis (RA). In this study, the introduction of a spiro ring with a difluoro-substituted cyclopropionamide resulted in the identification of TUL01101 (compound 36) based on a triazolo[1,5-a]pyridine core of filgotinib. It showed excellent potency on JAK1 with an IC50 value of 3 nM and exhibited more than 12-fold selectivity for JAK2 and TYK2. Whole blood assay also demonstrated the high activity and selectivity (37-fold for JAK2). At the same time, TUL01101 also demonstrated excellent metabolic stability and pharmacokinetics (PK) profiles were assayed in three species (mouse, rat, and dog). Moreover, it has been validated for effective activity in the treatment of RA both in collagen-induced arthritis (CIA) and adjuvant-induced arthritis (AIA) models, with low dose and low toxicity. Now, TUL01101 has progressed into phase I clinical trials.

KDM1A promotes thyroid cancer progression and maintains stemness through the Wnt/ß-catenin signaling pathway.

Background: Cancer stem cells (CSCs) are highly tumorigenic, chemotherapy-resistant, tumor growth-sustaining, and are implicated in tumor recurrence. Previous studies have shown that lysine-specific histone demethylase 1A (KDM1A) is highly expressed in several human malignancies and CSCs. However, the role of KDM1A in CSCs and the therapeutic potential of KDM1A inhibitors for the treatment of the advanced thyroid cancer are poorly understood. Methods: Firstly, KDM1A was identified as an important epigenetic modifier that maintained the stemness of thyroid cancer through a mini histone methylation modifier screen and confirmed in thyroid cancer tissues and cell lines. RNA sequence was performed to discover the downstream genes of KDM1A. The underlying mechanisms were further investigated by ChIP, IP and dual luciferase reporter assays, gain and loss of function assays. Results: Here we report that KDM1A regulates the stemness of thyroid cancer and promotes thyroid cancer progression via the Wnt/ß-catenin pathway. Mechanistically, KDM1A down-regulates two antagonists of the canonical Wnt pathway, APC2 and DKK1, by demethylating H3K4me1/2 of the APC2 promoter region and the nonhistone substrate HIF-1α, resulting in the inhibition of APC2 transcription and the activation of the HIF-1α/microRNA-146a/DKK1 axis. Importantly, we also demonstrate that GSK-LSD1, a highly selective inhibitor of KDM1A, significantly inhibits thyroid cancer progression and enhances the sensitivity of thyroid cancer to chemotherapy. Conclusions: KDM1A plays an important role in thyroid cancer progression and maintains stemness, our study provides a new strategy for the therapy of advanced thyroid cancer.

High-throughput and trace analysis of diazepam in plasma using DART-MS/MS and its pharmacokinetic application.

A high-throughput quantitative analytical method based on Direct Analysis in Real Time tandem mass spectrometry (DART-MS/MS) has been developed and validated for the determination of diazepam in rat plasma, whereby analyzing of each sample needs merely 25 µL plasma, simple solid phase extraction sample preparation and 15 s acquisition time. The multiple reaction monitoring (MRM) transitions at m/z 285.2 â†’ 193.1 and 316.0 â†’ 270.0 were selected for the monitoring of diazepam and its internal standard clonazepam respectively. A good linearity within the range of 10-2000 ng/mL, an intra- and inter-day precisions within <7.78% as to an accuracy ranging from 1.04% to 7.92% have been achieved. The method has been successfully applied to the pharmacokinetic study of diazepam in rats' plasma after a single intragastric administration at a dose of 10 mg/kg. The results indicate that this method fulfills the requirements of the bioanalysis in sensitivity and accuracy. It shows considerable promise for application of DART-MS to the quantitative investigation of other drugs.