Outdoor walking, genetic predisposition, and the risk of incident osteoporosis among older adults: A prospective large population-based cohort study.

This large-scale prospective study showed that a significant association between longer duration of daily outdoor walking and reduced osteoporosis risk was found among older adults, particularly among those with a low genetic predisposition to osteoporosis, which highlighted the importance of outdoor walking as a simple, cost-effective adjunct for preventing osteoporosis. PURPOSE: The available cross-sectional data and small-scale studies indicate that outdoor walking benefits bone metabolism. Nevertheless, there is a scarcity of comprehensive prospective research investigating the enduring correlation between outdoor walking and osteoporosis. This study aims to conduct a prospective analysis of the correlation between outdoor walking and osteoporosis while also examining potential variations influenced by genetic susceptibility to osteoporosis. METHODS: 24,700 older adults without osteoporosis at baseline were enrolled. These individuals were followed up until December 31, 2021, during which data on outdoor walking was gathered. The genetic risk score for osteoporosis was comprised of 14 single-nucleotide polymorphisms. RESULTS: 4,586 cases of osteoporosis were identified throughout a median follow-up period of 37.3 months. Those who walked outside for > 30 but ≤ 60 min per day had a hazard ratio (HR) of 0.83 (95% confidence interval (CI): 0.72-0.95) for incident osteoporosis, whereas those who walked outside for > 60 min per day had an HR of 0.60 (95% CI: 0.39-0.92). We found that osteoporosis risk exhibited a declining trend in individuals with low genetic risk. Individuals walking outside for > 60 min per day tended to have the lowest overall osteoporosis risk among those with high genetic risk. CONCLUSIONS: A significant negative correlation exists between an extended period of daily outdoor walking and osteoporosis incidence risk. This correlation is particularly pronounced among individuals with low genetic risk. The results above underscore the significance of outdoor walking as a simple and economical adjunct to public health programs to prevent osteoporosis.

Sex-specific associations between skeletal muscle mass and incident diabetes: A population-based cohort study.

AIMS: To investigate the sex-specific associations between predicted skeletal muscle mass index (pSMI) and incident type 2 diabetes in a retrospective longitudinal cohort of Chinese men and women. MATERIALS AND METHODS: We enrolled Chinese adults without diabetes at baseline from WATCH (West chinA adulT health CoHort), a large health check-up-based database. We calculated pSMI to estimate skeletal muscular mass, and measured blood glucose variables and assessed self-reported history to identify new-onset diabetes. The nonlinear association between pSMI and incident type 2 diabetes was modelled using the penalized spline method. The piecewise association was estimated using segmented linear splines in weighted Cox proportional hazards regression models. RESULTS: Of 47 885 adults (53.2% women) with a median age of 40 years, 1836 developed type 2 diabetes after a 5-year median follow-up. In women, higher pSMI was associated with a lower risk of incident type 2 diabetes (Pnonlinearity = 0.09, hazard ratio [HR] per standard deviation increment in pSMI: 0.79 [95% confidence interval {CI} 0.68, 0.91]). A nonlinear association of pSMI with incident type 2 diabetes was detected in men (Pnonlinearity < 0.001). In men with pSMI lower than 8.1, higher pSMI was associated with a lower risk of incident type 2 diabetes (HR 0.58 [95% CI 0.40, 0.84]), whereas pSMI was not significantly associated with incident diabetes in men with pSMI equal to or greater than 8.1 (HR 1.08 [95% CI 0.93, 1.25]). CONCLUSIONS: In females, a larger muscular mass is associated with a lower risk of type 2 diabetes. For males, this association is significant only among those with diminished muscle mass.

Structure-activity relationship study of a series of nucleoside derivatives bearing sulfonamide scaffold as potent and selective PRMT5 inhibitors.

Protein arginine methyltransferase 5 (PRMT5) is a promising target for the treatment of malignant tumors. The discovery of nucleoside-derived inhibitors against PRMT5 with novel scaffold has been challenging. Herein, we report our effort on the design and synthesis of nucleoside derivatives bearing sulfonamide scaffold as potent PRMT5 inhibitors. The representative compound 23n was identified as a potent and selective PRMT5 inhibitor with an IC50 value of 8 nM. Molecular docking study demonstrated the binding mode of compound 23n and illustrated its inhibitory activity to PRMT5. The Trimethyl Lock prodrug strategy was used to afford prodrug 36 with lower polarity which could rapidly release the active compound 23n after entering the tumor cells. Cell-based assays revealed that the prodrug 36 restrained the proliferation of Z-138 and MOLM-13 cells and suppressed methylation of PRMT5 substrate more potently than 23n. Additionally, both compound 23n and 36 exerted antiproliferative effects against Z-138 cells mainly by inducing apoptosis effectively rather than arresting cell cycle. Thus, compounds 23n and 36 represent a series of potent PRMT5 inhibitor with novel scaffold.

Association of mitochondrial DNA copy number with chronic kidney disease in older adults.

BACKGROUND: Mitochondrial dysfunction in kidney cells has been implicated in the pathogenesis of chronic kidney disease (CKD). Estimation of mitochondrial DNA copy number (mtDNA-CN) is considered a convenient method for representing mitochondrial function in large samples. However, no study has investigated the association between mtDNA-CN and CKD in older adults with the highest prevalence. The objective is to examine cross-sectional and prospective associations between mtDNA-CN values and CKD risk in older adults to determine whether mtDNA-CN represents a novel potential biomarker for the recognition of CKD risk. PATIENTS AND METHODS: In a Chinese community-based cohort of over 65-year-olds, we included 14,467 participants (52.6% females). CKD was defined by eGFR < 60 mL/min/1.73 m2 or ICD-10 codes (patients = 3831 (26.5%)). Participants had peripheral blood levels of mtDNA-CN calculated from probe intensities of the Axiom CAS Array. RESULTS: The risk of CKD prevalence decreased with mtDNA-CN per 1-SD increment, independent of established risk factors for older CKD (odds ratio [OR] per SD 0.90, 95% confidence interval [CI] 0.86, 0.93, P < 0.001), and has comparable strength of association with these established risk factors. Furthermore, the progression of kidney function was stratified according to the worsening of eGFR categories. The risk of kidney function progression to a more severe stage gradually decreased as the mtDNA-CN increased (P trend < 0.001). Non-CKD participants in the highest quartile of mtDNA-CN had a lower risk of developing CKD compared to the lowest quartile within 2 years of follow-up, reducing the risk of CKD by 36% (95% CI 0.42, 0.97; P = 0.037). CONCLUSIONS: Based on the analysis of the largest sample to date investigating the association between mtDNA-CN and CKD in older adults, higher levels of mtDNA-CN were found to be associated with a lower risk of CKD, suggesting that a reduced level of mtDNA-CN is a potential risk factor for CKD.

Design, synthesis and biological evaluation of (R)-5-methylpyrrolidin-2-ones as p300 bromodomain inhibitors with Anti-Tumor activities in multiple tumor lines.

p300/CBP bromodomain plays an important role in transcriptional regulation, and its overexpression is closely related to various diseases such as cancers. Two inhibitors of this target are currently in clinical trials but only CCS1477 (A1) have been published with the chemical structure. Herein, we modified the structure of CCS1477 based on the principle of bioisosterism and reasonable scaffold hopping, and discovered a series of new p300 bromodomain inhibitors with improved potency. More tumor cell lines sensitive to p300/CBP bromodomain inhibition were also identified. Among our new inhibitors, (R)-5-methylpyrrolidin-2-one derivitive B4 was the most potent one which showed comparable inhibitory activity against p300 (IC50 = 0.060 µM) as lead A1 (IC50 = 0.064 µM) at molecular level, and performed more potent proliferation inhibitory activities on various tumor cells than A1. Further we found that compound B4 had the high cell permeability and overcame the defect of the high efflux rate of A1, which could also explain the possible reason why B4 showed more potent inhibitory activities on sensitive tumor cells than lead A1. Western blotting analysis proved the target effects that B4 could suppress the expression of c-Myc and reduce H3K27 acetylation significantly. Liver microsomal metabolic stability assay and hERG channel inhibition evaluation illustrate compound B4 is metabolic stabilizable in human liver microsomes and has no hERG risk, which further demonstrate the good drug-likeness of B4. Therefore, compound B4 is a promising compound for further optimization and development.

Comparative transcriptome analysis of abnormal cap and healthy fruiting bodies of the edible mushroom Lentinula edodes.

Lentinula edodes, a commercially important mushroom, is cultivated worldwide. Artificially cultivated L. edodes often present with abnormal symptoms in the fruiting body, which affect their commercial value and reduce production efficiency. In this study, we carried out a comparative transcriptome analysis of normal fruiting body pileus (LeNP), normal margin in abnormal fruiting body pileus (LeAPNM), and abnormal margin in abnormal fruiting body pileus (LeAPAM). Metabolic pathways such as those involved in transmembrane transport, ribosome production, tryptophan metabolism, arginine and proline metabolism, and the metabolism of other amino acids were significantly enriched in LeAPAM. F-box, short-chain dehydrogenases/reductases, the major facilitator superfamily, and the FMN_red superfamily are related to malformation in L. edodes. Genes encoding heat shock proteins, G protein, and ß-1,3-glucanase in the GH5 family showed different expression patterns, suggesting that these genes are involved in the development of L. edodes fruiting bodies. In particular, CAZymes, which are involved in the development of cell walls in L. edodes, were highly expressed in LeAPAM. According to TEM observation, the cell wall of LeAPAM samples showed significant thickening compared to the other samples. These results suggested that cell wall anabolism in LeAPAM samples was more active than that in normal fruiting bodies, enhancing the environmental adaptability of the fungus. This study provides preliminary data for future research aimed at solving the phenomenon of abnormal fruiting bodies of L. edodes.

Novel Genetic Locus Influencing Retinal Venular Tortuosity Is Also Associated With Risk of Coronary Artery Disease.

OBJECTIVE: The retina may provide readily accessible imaging biomarkers of global cardiovascular health. Increasing evidence suggests variation in retinal vascular traits is highly heritable. This study aimed to identify the genetic determinants of retinal vascular traits. Approach and Results: We conducted a meta-analysis of genome-wide association studies for quantitative retinal vascular traits derived using semi-automatic image analysis of digital retinal photographs from the GoDARTS (Genetics of Diabetes Audit and Research in Tayside; N=1736) and ORCADES (Orkney Complex Disease Study; N=1358) cohorts. We identified a novel genome-wide significant locus at 19q13 (ACTN4/CAPN12) for retinal venular tortuosity (TortV), and one at 13q34 (COL4A2) for retinal arteriolar tortuosity (TortA); these 2 loci were subsequently confirmed in 3 independent cohorts (Ntotal=1413). In the combined analysis of discovery and replication cohorts, the lead single-nucleotide polymorphism in ACTN4/CAPN12 was rs1808382 (ßs.d.=-0.109; SE=0.015; P=2.39×10-13) and in COL4A2 was rs7991229 (ßs.d.=0.103; SE=0.015; P=4.66×10-12). Notably, the ACTN4/CAPN12 locus associated with TortV is also associated with coronary artery disease, heart rate, and atrial fibrillation. CONCLUSIONS: Genetic determinants of retinal vascular tortuosity are also linked to cardiovascular health. These findings provide a molecular pathophysiological foundation for the use of retinal vascular traits as biomarkers for cardiovascular diseases.

Rates of glycaemic deterioration in a real-world population with type 2 diabetes.

AIMS/HYPOTHESIS: There is considerable variability in how diabetes progresses after diagnosis. Progression modelling has largely focused on 'time to failure' methods, yet determining a 'coefficient of failure' has many advantages. We derived a rate of glycaemic deterioration in type 2 diabetes, using a large real-world cohort, and aimed to investigate the clinical, biochemical, pharmacological and immunological variables associated with fast and slow rates of glycaemic deterioration. METHODS: An observational cohort study was performed using the electronic medical records from participants in the Genetics of Diabetes Audit and Research in Tayside Study (GoDARTS). A model was derived based on an individual's observed HbA1c measures from the first eligible HbA1c after the diagnosis of diabetes through to the study end (defined as insulin initiation, death, leaving the area or end of follow-up). Each HbA1c measure was time-dependently adjusted for the effects of non-insulin glucose-lowering drugs, changes in BMI and corticosteroid use. GAD antibody (GADA) positivity was defined as GAD titres above the 97.5th centile of the population distribution. RESULTS: The mean (95% CI) glycaemic deterioration for type 2 diabetes and GADA-positive individuals was 1.4 (1.3, 1.4) and 2.8 (2.4, 3.3) mmol/mol HbA1c per year, respectively. A younger age of diagnosis, lower HDL-cholesterol concentration, higher BMI and earlier calendar year of diabetes diagnosis were independently associated with higher rates of glycaemic deterioration in individuals with type 2 diabetes. The rate of deterioration in those diagnosed at over 70 years of age was very low, with 66% having a rate of deterioration of less than 1.1 mmol/mol HbA1c per year, and only 1.5% progressing more rapidly than 4.4 mmol/mol HbA1c per year. CONCLUSIONS/INTERPRETATION: We have developed a novel approach for modelling the progression of diabetes in observational data across multiple drug combinations. This approach highlights how glycaemic deterioration in those diagnosed at over 70 years of age is minimal, supporting a stratified approach to diabetes management.

Interaction between variants in the CYP2C9 and POR genes and the risk of sulfonylurea-induced hypoglycaemia: A GoDARTS Study.

Data on the association of CYP2C9 genetic polymorphisms with sulfonylurea (SU)-induced hypoglycaemia (SH) are inconsistent. Recent studies showed that variants in the P450 oxidoreductase (POR) gene could affect CYP2C9 activity. In this study, we explored the effects of POR*28 and combined CYP2C9*2 and CYP2C9*3 genotypes on SH and the efficacy of SU treatment in type 2 diabetes. A total of 1770 patients were included in the analysis of SU efficacy, assessed as the combined outcome of the HbA1c reduction and the prescribed SU daily dose. Sixty-nine patients with severe SH were compared with 311 control patients. The number of CYP2C9 deficient alleles was associated with nearly three-fold higher odds of hypoglycaemia (OR, 2.81; 95% CI, 1.30-6.09; P = .009) and better response to SU treatment (ß, -0.218; SE, 0.074; P = .003) only in patients carrying the POR*1/*1 genotype. Our results indicate that interaction between CYP2C9 and POR genes may be an important determinant of efficacy and severe adverse effects of SU treatment.

Evidence-based prioritisation and enrichment of genes interacting with metformin in type 2 diabetes.

AIMS/HYPOTHESIS: There is an extensive body of literature suggesting the involvement of multiple loci in regulating the action of metformin; most findings lack replication, without which distinguishing true-positive from false-positive findings is difficult. To address this, we undertook evidence-based, multiple data integration to determine the validity of published evidence. METHODS: We (1) built a database of published data on gene-metformin interactions using an automated text-mining approach (n = 5963 publications), (2) generated evidence scores for each reported locus, (3) from which a rank-ordered gene set was generated, and (4) determined the extent to which this gene set was enriched for glycaemic response through replication analyses in a well-powered independent genome-wide association study (GWAS) dataset from the Genetics of Diabetes and Audit Research Tayside Study (GoDARTS). RESULTS: From the literature search, seven genes were identified that are related to the clinical outcomes of metformin. Fifteen genes were linked with either metformin pharmacokinetics or pharmacodynamics, and the expression profiles of a further 51 genes were found to be responsive to metformin. Gene-set enrichment analysis consisting of the three sets and two more composite sets derived from the above three showed no significant enrichment in four of the gene sets. However, we detected significant enrichment of genes in the least prioritised category (a gene set in which their expression is affected by metformin) with glycaemic response to metformin (p = 0.03). This gene set includes novel candidate genes such as SLC2A4 (p = 3.24 × 10-04) and G6PC (p = 4.77 × 10-04). CONCLUSIONS/INTERPRETATION: We have described a semi-automated text-mining and evidence-scoring algorithm that facilitates the organisation and extraction of useful information about gene-drug interactions. We further validated the output of this algorithm in a drug-response GWAS dataset, providing novel candidate loci for gene-metformin interactions.

Acute kidney injury, plasma lactate concentrations and lactic acidosis in metformin users: A GoDarts study.

AIMS: Metformin is renally excreted and has been associated with the development of lactic acidosis. Although current advice is to omit metformin during illnesses that may increase the risk of acute kidney injury (AKI), the evidence supporting this is lacking. We investigated the relationship between AKI, lactate concentrations and the risk of lactic acidosis in those exposed to metformin. MATERIALS AND METHODS: We undertook a population-based case-control study of lactic acidosis in 1746 participants with Type 2 diabetes and 846 individuals without diabetes with clinically measured lactates with and without AKI between 1994 and 2014. AKI was stratified by severity according to "Kidney Disease: Improving Global Outcomes" guidelines. Mixed-effects logistic and linear regression were used to analyse lactic acidosis risk and lactate concentrations, respectively. RESULTS: Eighty-two cases of lactic acidosis were identified. In Type 2 diabetes, those treated with metformin had a greater incidence of lactic acidosis [45.7 per 100 000 patient years; 95% confidence interval (CI) 35.9-58.3] compared to those not exposed to this drug (11.8 per 100 000 patient years; 95% CI 4.9-28.5). Lactate concentrations were 0.34 mmol/L higher in the metformin-exposed cohort (P < .001). The risk of lactic acidosis was higher in metformin users [odds ratio (OR) 2.3; P = .002] and increased with AKI severity (stage 1: OR 3.0, P = .002; stage 2: OR 9.4, P < .001; stage 3: OR 16.1, P < .001). CONCLUSIONS: A clear association was found between metformin, lactate accumulation and the development of lactic acidosis. This relationship is strongest in those with AKI. These results provide robust evidence to support current recommendations to omit metformin in any illness that may precipitate AKI.

Insights from genome-wide association studies of drug response.

Early genome-wide association studies (GWAS) using relatively small samples have identified both rare and common genetic variants with large impact on severe adverse drug reactions, dosing, and efficacy. Here we outline the challenges and recent successes of the GWAS approach in disease genetics and the ways in which these can be applied to pharmacogenomics for biological discovery, determination of heritability, and personalized treatment. We highlight that the genetic architecture of drug efficacy reflects a complex trait yet that of adverse drug reactions more closely mirrors the architecture of Mendelian diseases and how this difference affects future study design. Given that multiple layers of biological data are increasingly available on large samples from biorepositories linked to electronic medical records, GWAS will remain a key component of the systems biology approach to uncovering small to moderate genetic determinants of drug response; these discoveries should move us closer to a personalized approach to health care.

Characterization of erm(B)-Carrying Integrative and Conjugative Elements Transferred from Streptococcus anginosus to Other Streptococci and Enterococci.

Integrative and conjugative elements (ICEs) are important vectors of lateral gene transfer and contribute to the evolution of bacterial pathogens. However, studies on the transfer among species and the physiological consequences of ICEs are rare. The objective of this study was to investigate the cross-species transferability of newly identified erm(B)-carried ICE in Streptococcus anginosus San95 and its physiological consequences after transfer. The erm(B)-carried ICE, characterized by a triple serine integrase module, integrated into hsdM genes, thus designated ICESan95_hsdM. Analysis of ICESan95_hsdM revealed 32 additional ICESan95-like ICEs in the available NCBI genome (n = 24) and sequence of clinical isolates (n = 8). Polymerase chain reaction (PCR) was used to evaluate the 467 clinical isolates, of which 84 were positive for core genes (integrase, relaxase, and T4SS genes) of ICESan95_hsdM. Cross-species transfer experiments demonstrated that ICESan95_hsdM could transfer from S. anginosus to different streptococcal and enterococcal recipients. Growth and competitive culture assays showed acquisition of ICESan95_hsdM incurred no fitness cost. Our work discovered a group of ICEs in Streptococci and Enterococci. For the first time, we demonstrated the broad cross-species transferability to different species or genera of ICEs with no fitness cost that enables commensal S. anginosus to deliver antimicrobial resistance genes to other streptococci and enterococci.

Correlation Between Blood Urea Nitrogen and Short- and Long-Term Glycemic Variability in Elderly Patients with Type 2 Diabetes Mellitus Who Were hospitalized:A Retrospective Study.

Objective: Type 2 diabetes mellitus (T2DM) is a metabolic disease characterized by insulin resistance and progressively impaired insulin secretion resulting in dynamic fluctuations in glucose levels.High blood urea nitrogen (BUN) levels have been linked to decreased insulin sensitivity, suppressed insulin synthesis and increased risk of incident diabetes mellitus in humans as well as insulin use in patients with T2DM.This study characterize the association between BUN levels and short-term and long-term glycemic variability(GV) in the elderly patients with T2DM who were hospitalized. Methods: A total of 927 elderly patients with T2DM were included in the study. The short-term GV was quantified using parameters such as standard deviation (SD), coefficient of variation (CV), time in range (TIR), and mean amplitude of glycemic excursions (MAGE), based on multi-point fingertip blood glucose monitoring. The long-term GV was quantified using parameters such as SD, CV, variation independent of the mean (VIM), and average successive variability (ARV), based on fasting blood glucose(FPG). The relationship between BUN levels and short-term and long-term GV in elderly T2DM who were hospitalized was explored using methods such as Spearman correlation coefficient, linear regression analysis, logistic regression analysis, and interaction tests. Results: In elderly patients with T2DM were hospitalized, there is a significant correlation between BUN levels and both short-term and long-term GV. BUN is negatively correlated with the GV parameter TIR (r=-0.12, P=0.000), and positively correlated with SD (r=0.12, P=0.000), CV (r=0.07, P=0.026), MAGE (r=0.11, P=0.001), FPG-SD (r=0.08, P=0.013), and FPG-CV (r=0.08, P=0.014).Furthermore, the association remains consistent across different age, gender, BMI, and haemoglobin A1c (HbA1c) subgroups (P interaction > 0.05). Conclusion: In elderly patients with T2DM were hospitalized, BUN levels were positively associated with GV.Therefore, monitoring BUN levels were beneficial in assessing the degree of GV.

Generalization of a Deep Learning Model for Continuous Glucose Monitoring-Based Hypoglycemia Prediction: Algorithm Development and Validation Study.

Background: Predicting hypoglycemia while maintaining a low false alarm rate is a challenge for the wide adoption of continuous glucose monitoring (CGM) devices in diabetes management. One small study suggested that a deep learning model based on the long short-term memory (LSTM) network had better performance in hypoglycemia prediction than traditional machine learning algorithms in European patients with type 1 diabetes. However, given that many well-recognized deep learning models perform poorly outside the training setting, it remains unclear whether the LSTM model could be generalized to different populations or patients with other diabetes subtypes. Objective: The aim of this study was to validate LSTM hypoglycemia prediction models in more diverse populations and across a wide spectrum of patients with different subtypes of diabetes. Methods: We assembled two large data sets of patients with type 1 and type 2 diabetes. The primary data set including CGM data from 192 Chinese patients with diabetes was used to develop the LSTM, support vector machine (SVM), and random forest (RF) models for hypoglycemia prediction with a prediction horizon of 30 minutes. Hypoglycemia was categorized into mild (glucose=54-70 mg/dL) and severe (glucose<54 mg/dL) levels. The validation data set of 427 patients of European-American ancestry in the United States was used to validate the models and examine their generalizations. The predictive performance of the models was evaluated according to the sensitivity, specificity, and area under the receiver operating characteristic curve (AUC). Results: For the difficult-to-predict mild hypoglycemia events, the LSTM model consistently achieved AUC values greater than 97% in the primary data set, with a less than 3% AUC reduction in the validation data set, indicating that the model was robust and generalizable across populations. AUC values above 93% were also achieved when the LSTM model was applied to both type 1 and type 2 diabetes in the validation data set, further strengthening the generalizability of the model. Under different satisfactory levels of sensitivity for mild and severe hypoglycemia prediction, the LSTM model achieved higher specificity than the SVM and RF models, thereby reducing false alarms. Conclusions: Our results demonstrate that the LSTM model is robust for hypoglycemia prediction and is generalizable across populations or diabetes subtypes. Given its additional advantage of false-alarm reduction, the LSTM model is a strong candidate to be widely implemented in future CGM devices for hypoglycemia prediction.

MODY Probability Calculator Is Suitable for MODY Screening in China: A Population-based Study.

Context: Selecting appropriate individuals for genetic testing is essential due to the optimal treatment for maturity-onset diabetes of the young (MODY). However, how to effectively screen for MODY in China remains unclear. Objective: To validate the performance of current screening strategies in selecting patients with MODY based on a nationwide type 2 diabetes cohort. Methods: A panel of 14 MODY genes was analyzed from 1911 type 2 diabetes patients who were ages 15 to 35 years. Variants were evaluated according to the American College of Medical Genetics and Genomics guidelines. Based on this cohort, we simulated the 2 most frequently used screening strategies, including the traditional MODY criteria and the MODY probability calculator (MPC), to assess their ability to select patients with MODY. Results: From a total of 1911 participants, 42 participants harbored pathogenic/likely pathogenic variants. The performance of the traditional criteria was sensitivity: 19.0%, specificity: 72.9%, positive predictive value (PPV): 1.6%, and missing rate: 81.0%. The optimal cut-off for MPC was 40.7%. Based on this cut-off value, the performance was sensitivity: 54.8%, specificity: 81.0%, PPV: 6.1%, and missing rate: 45.2%. Moreover, hemoglobin A1c, insulin treatment, and family history of diabetes have poor discrimination between MODY and young-onset type 2 diabetes. Conclusion: The MPC is better than traditional criteria in terms of both sensitivity and PPV. To ensure more MODY patients benefit from optimal treatment, we therefore suggest that routine genetic testing be performed on all type 2 diabetes patients who are between the ages of 15 and35 years and have MPC probability value over 40.7%.

Robust association of the LPA locus with low-density lipoprotein cholesterol lowering response to statin treatment in a meta-analysis of 30 467 individuals from both randomized control trials and observational studies and association with coronary artery disease outcome during statin treatment.

OBJECTIVES: The LPA single-nucleotide polymorphism rs10455872 has been associated with low-density lipoprotein cholesterol (LDLc) lowering response to statins in several randomized control trials (RCTs) and is a known coronary artery disease (CAD) marker. However, it is unclear what residual risk of CAD this marker may have during statin treatment. METHODS: Using electronic medical records linked to the GoDARTS genotyped population, we identified over 8000 patients on statins in Tayside, Scotland. RESULTS: We replicated the findings of the RCTs, with the G allele of rs10455872 being associated with a 0.10 mmol/l per allele poorer reduction in LDLc in response to statin treatment, and conducted a meta-analysis with previously published RCTs (P = 1.46 × 10, n = 30 467). We showed an association between rs10455872 and CAD in statin-treated individuals and have replicated this finding in the Utrecht Cardiovascular Pharmacogenetics study (combined odds ratio 1.41, 95% confidence interval 1.17-1.68, P = 4.5 × 10, n = 8822) suggesting that statin treatment does not abrogate this well-established genetic risk for CAD. Furthermore, in a Cox proportional hazards model with LDLc measured time dependently, we demonstrated that the relationship between CAD and rs10455872 was independent of LDLc during statin treatment. CONCLUSION: Individuals with the G allele of rs10455872, which represents approximately one in seven patients, have a higher risk of CAD than the majority of the population even after treatment with statins; and therefore represent a vulnerable group requiring an alternative medication in addition to statin treatment.

Correlation Between Glycemic Variability and Diabetic Complications: A Narrative Review.

Diabetes mellitus is a metabolic disorder with a complex etiology in which glycemic dynamics are disturbed and the body is unable to maintain the process of glucose homeostasis through the pancreas. Persistent symptoms of high blood glucose or low blood glucose may lead to diabetic complications, such as neuropathy, nephropathy, retinopathy, and cardiovascular diseases. Glycemic variability which can represent the presence of excessive glycemic excursions is an indicator for evaluating glucose homoeostasis. Limiting glycemic variability has gradually become an emerging therapeutic target in improve diabetes metabolism and prevent associated complications. This article reviews the progress of research on the various quantifiable parameters of glycemic variability and their relationships with vascular lesions and mechanisms.

Continuous Glucose Monitoring Time Series Data Analysis: A Time Series Analysis Package for Continuous Glucose Monitoring Data.

The R package Continuous Glucose Monitoring Time Series Data Analysis (CGMTSA) was developed to facilitate investigations that examine the continuous glucose monitoring (CGM) data as a time series. Accordingly, novel time series functions were introduced to (1) enable more accurate missing data imputation and outlier identification; (2) calculate recommended CGM metrics as well as key time series parameters; (3) plot interactive and three-dimensional graphs that allow direct visualizations of temporal CGM data and time series model optimization. The software was designed to accommodate all popular CGM devices and support all common data processing steps. The program is available for Linux, Windows, and Mac at GitHub.

Regulating the electronic structure through charge redistribution in dense single-atom catalysts for enhanced alkene epoxidation.

Inter-site interaction in densely populated single-atom catalysts has been demonstrated to have a crucial role in regulating the electronic structure of metal atoms, and consequently their catalytic performances. We herein report a general and facile strategy for the synthesis of several densely populated single-atom catalysts. Taking cobalt as an example, we further produce a series of Co single-atom catalysts with varying loadings to investigate the influence of density on regulating the electronic structure and catalytic performance in alkene epoxidation with O2. Interestingly, the turnover frequency and mass-specific activity are significantly enhanced by 10 times and 30 times with increasing Co loading from 5.4 wt% to 21.2 wt% in trans-stilbene epoxidation, respectively. Further theoretical studies reveal that the electronic structure of densely populated Co atoms is altered through charge redistribution, resulting in less Bader charger and higher d-band center, which are demonstrated to be more beneficial for the activation of O2 and trans-stilbene. The present study demonstrates a new finding about the site interaction in densely populated single-atom catalysts, shedding insight on how density affects the electronic structure and catalytic performance for alkene epoxidation.