Decisive gene strategy on osteoarthritis: a comprehensive whole-literature based approach for conclusive gene targets.

BACKGROUND: Previous meta-analyses only examined the association between single or several gene polymorphisms and osteoarthritis (OA), whereas no studies have concluded that there are existing all gene loci that associate with OA. OBJECTIVE: To assess whether a definite conclusion of the association between the gene loci and OA can be drawn. METHODS: Decisive gene strategy (DGS), a literature-based approach, was used to search PubMed, Embase, and Cochrane databases for all meta-analyses that associated gene polymorphisms and OA. Trial Sequential Analysis (TSA) examined the sufficiency of the cumulative sample size. Finally, we assessed the importance of gene loci in OA based on whether there were enough sample sizes and the heterogeneity of the literatures with I2 value. RESULTS: After excluding 179 irrelevant publications, 80 meta-analysis papers were recruited. Among Caucasians, SMAD3 rs12901499 (OR = 1.20, 95% CI: 1.12-1.29) was a risk factor with validation of sufficient sample sizes through TSA model. Among Asians, there were 3 gene loci risk factors with validation of sufficient sample sizes through TSA model: ESR1 rs2228480, SMAD3 rs12901499, and MMP-1 rs1799750 (OR = 1.35, 95% CI: 1.08-1.69; OR = 1.34, 95% CI: 1.07-1.69; OR = 1.43, 95% CI: 1.18-1.74, respectively). Besides, 3 gene loci, DVWA rs7639618, GDF5 rs143383, and VDR rs7975232 (OR = 0.78, 95% CI: 0.67-0.90; OR = 0.74, 95% CI: 0.67-0.81; OR = 0.56, 95% CI: 0.35-0.90, respectively) were identified as protective factors through TSA model. CONCLUSIONS: We used DGS to identify conclusive gene loci associated with OA. These findings provide implications of precision medicine in OA and may potentially advance genetic therapy.

A case-control study coupling with meta-analysis elaborates decisive association between IGF-1 rs35767 and osteoporosis in Asian postmenopausal females.

BACKGROUND: Osteoporosis (OP) is prevalent in postmenopausal women. Several studies investigated the association between IGF-1 polymorphisms and OP among postmenopausal females with conflicting outcomes. OBJECTIVE: To investigate whether the IGF-1 (rs35767, rs2288377, rs5742612) were associated with OP in postmenopausal females. METHODS: In case-control study, 95 OP cases and 222 healthy controls were recruited between March 2015 and July 2019. OP was diagnosed based on WHO criteria for diagnosis of OP as T score of bone mineral density (BMD) ≤-2.5; normal, as T score of BMD ≥-1. IGF-1 SNPs were genotyped by iPLEX Gold SNP genotyping. To be solid, related studies from PubMed, Embase, Cochrane, Web of science, and previous meta-analysis up until November 2020, along with our case-control study, were incorporated into a meta-analysis with criteria of significance using odds ratios (ORs) with corresponding 95% confidence intervals (CI) to evaluate risk factor of SNPs on OP. TSA was used to estimate the sample sizes required to achieve a conclusion. RESULTS: In dominant model of our case-control study, we found nonsignificant association of rs35767 [Adj-OR: 0.95 (95% CI: 0.56-1.60)], rs2288377 [Adj-OR: 1.15 (95% CI: 0.67-1.97)], and rs5742612 [Adj-OR: 1.07 (95% CI: 0.62-1.83)] with OP in postmenopausal females. However, integration of our case-control study and 3 published studies, rs35767 [OR: 1.24 (95% CI: 1.05-1.47)] showed a conclusively risk association with OP in postmenopausal females judged by TSA with 2267 Asians. CONCLUSIONS: This study demonstrates a crucial sample to conclude that IGF-1 rs35767 is significantly associated with OP in postmenopausal women.

Gender difference in appendicular muscle strength: determinant of the quality of life in the older Taiwanese.

BACKGROUND: The loss of skeletal muscle mass by aging determines the health status and the quality of life (QoL). OBJECTIVE: To examine the relationships between appendicular muscle strength and the QoL of elderly adults in gender difference. METHODS: This was a cross-sectional study, in which 690 subjects who participated in older adults health examination in the health management center of Tri-Service General Hospital from 2018 to 2021. A structured questionnaire was used to collect basic demographic data. The 12-Item Short Form Survey (SF-12) was used to evaluate the QoL of subjects. Their grip strength and gait speed were measured, and Dual-energy X-ray absorptiometry was used to measure muscle mass and other body composition data. Multivariate regression analysis was used to examine the relationships between upper and lower limb muscle strength and the QoL of older adults. RESULTS: In men, legs muscle mass percentage (LegsMM%) (ß = 3.67; 95% CI: 0.64-6.69; p = 0.018) and gait speed (ß = 6.09; 95% CI: 3.88-8.30; p < 0.001) were positively associated with physical component summary (PCS) scores, and gait speed (ß = 4.63; 95% CI: 2.66-6.60; p < 0.001) was also related to an improvement mental component summary (MCS) scores. In women, arms muscle mass percentage (ArmsMM%) (ß = 6.50; 95% CI: 2.34-10.66; p = 0.002) and grip strength (ß = 10.54; 95% CI: 6.27-14.81; p < 0.001) had the greatest effect on improving PCS scores, whereas grip strength (ß = 7.58; 95% CI 4.00-11.17; p < 0.001) was also found to help improve MCS scores. CONCLUSIONS: Men should focus on lower limb training, whereas females should focus on upper limb training to effectively improve their QoL. Appropriate exercise interventions should be designed for different genders for the promotion of the healthy aging policy.

Differential gene expression orchestrated by transcription factors in osteoporosis: bioinformatics analysis of associated polymorphism elaborating functional relationships.

BACKGROUND: Identification of candidate SNPs from transcription factors (TFs) is a novel concept, while systematic large-scale studies on these SNPs are scarce. PURPOSE: This study aimed to identify the SNPs of six TF binding sites (TFBSs) and examine the association between candidate SNPs and osteoporosis. METHODS: We used the Taiwan BioBank database; University of California, Santa Cruz, reference genome; and a chromatin immunoprecipitation sequencing database to detect 14 SNPs at the potential binding sites of six TFs. Moreover, we performed a case-control study and genotyped 109 patients with osteoporosis (T-score ≤ -2.5 evaluated by dual-energy X-ray absorptiometry) and 262 healthy individuals (T-score ≥ -1) at Tri-Service General Hospital from 2015 to 2019. Furthermore, we used the expression quantitative trait loci (eQTL) from the Genotype-Tissue Expression database to identify downstream gene expression as a criterion for the function of candidate SNPs. RESULTS: Bioinformatic analysis identified 14 SNPs of TFBSs influencing osteoporosis. Of these SNPs, the rs130347 CC + TC genotype had 0.57 times higher risk than the TT genotype (OR = 0.57, p = 0.031). Validation of eQTL analysis revealed that rs130347 T allele influences mRNA expression of downstream A4GALT in whole blood (p = 0.0041) and skeletal tissues (p = 0.011). CONCLUSIONS: We successfully identified the unique osteoporosis locus rs130347 in the Taiwanese and functionally validated this finding. In the future, this strategy can be expanded to other diseases to identify susceptible loci and achieve personalized precision medicine.

Decisive gene strategy on osteoporosis: a comprehensive whole-literature-based approach for conclusive candidate gene targets.

PURPOSE: Previous meta-analyses only examined the association between single gene polymorphisms and osteoporosis; there is no compilation of all gene loci that correlate with osteoporosis in the literature. In this study, we develop a new literature-based approach, a decisive gene strategy (DGS), to examine the sufficiency of the cumulative sample size for each gene locus and to assess whether a definite conclusion of the association between the gene locus and osteoporosis can be drawn. METHODS: The DGS was used to search PubMed, Embase, and Cochrane databases for all meta-analyses that correlated gene polymorphisms with osteoporosis. Trial sequential analysis was employed to examine the sufficiency of the cumulative sample size. Finally, we assessed the importance of gene loci in osteoporosis based on whether there were enough sample sizes and the heterogeneity of the literature with the I2 value. RESULTS: After excluding 169 irrelevant publications, 39 meta-analysis papers were obtained. Among Caucasians, in 17 gene loci, there were eight gene loci (e.g., vitamin D Receptor ApaI rs7975232) with sufficient cumulative sample size to confirm that they were unrelated to the disease. Among Asians, in 15 gene loci, four gene loci that had sufficient sample sizes were risk factors: VDR FokI rs2228570 (odds ratio (OR) = 1.44, 95% confidence interval (CI) = 1.22-1.70), TGF ß1 rs1800470 (OR = 1.35, 95% CI = 1.10-1.65), IGF1 rs2288377 (OR = 1.44, 95% CI = 1.28-1.62), and IGF1 rs35767 (OR = 1.20, 95% CI = 1.06-1.36), respectively, whereas one gene locus, ESR2 RsaI rs1256049 (OR = 0.69, 95% CI = 0.59-0.81), was a protective factor. CONCLUSIONS: The DGS successfully identified five gene loci in osteoporosis that will apply to other diseases to find causal genes, which may contribute to further genetic therapy.

A Simple Algorithm Using Ventilator Parameters to Predict Successfully Rapid Weaning Program in Cardiac Intensive Care Unit Patients.

BACKGROUND: Ventilator weaning is one of the most significant challenges in the intensive care unit (ICU). Approximately 30% of patients fail to wean, resulting in prolonged use of ventilators and increased mortality. There are numerous high-performance prediction models available today, but they require a large number of parameters to predict and are thus impractical in clinical practice. OBJECTIVES: This study aims to create an artificial intelligence (AI) model for predicting weaning time and to identify the most simplified key predictors that will allow the model to achieve adequate accuracy with as few parameters as possible. METHODS: This is a retrospective study of to-be-weaned patients (n = 1439) hospitalized in the cardiac ICU of Cheng Hsin General Hospital's Department of Cardiac Surgery from November 2018 to August 2020. The patients were divided into two groups based on whether they could be weaned within 24 h (i.e., "patients weaned within 24 h" (n = 1042) and "patients not weaned within 24 h" (n = 397)). Twenty-eight variables were collected including demographic characteristics, arterial blood gas readings, and ventilation set parameters. We created a prediction model using logistic regression and compared it to other machine learning techniques such as decision tree, random forest, support vector machine (SVM), extreme gradient boosting, and artificial neural network. Forward, backward, and stepwise selection methods were used to identify significant variables, and the receiver operating characteristic curve was used to assess the accuracy of each AI model. RESULTS: The SVM [receiver operating characteristic curve (ROC-AUC) = 88%], logistic regression (ROC-AUC = 86%), and XGBoost (ROC-AUC = 85%) models outperformed the other five machine learning models in predicting weaning time. The accuracies in predicting patient weaning within 24 h using seven variables (i.e., expiratory minute ventilation, expiratory tidal volume, ventilation rate set, heart rate, peak pressure, pH, and age) were close to those using 28 variables. CONCLUSIONS: The model developed in this research successfully predicted the weaning success of ICU patients using a few and easily accessible parameters such as age. Therefore, it can be used in clinical practice to identify difficult-to-wean patients to improve their treatment.

The Effect of PPARγ rs1801282 Variant on Mortality Risk Among Asians With Chronic Kidney Disease: A Cohort Study and Meta-Analysis.

Background: Chronic kidney disease (CKD) is a public health issue, and an independent risk factor for cardiovascular disease. The peroxisome proliferator-activated receptor gamma (PPARG) plays an important role in the cardiovascular system. Previous studies have examined one important exon polymorphism, Pro12Ala, in PPARG with respect to mortality of CKD patients, but the results were inconsistent and current evidence is insufficient to support a strong conclusion. This study aimed to examine the correlation between Pro12Ala gene polymorphism and mortality among Asians with CKD by trial sequential analysis (TSA). Methods: The research was divided into observational research and meta-analysis. For the cohort study, 767 subjects from dialysis centers in Taipei were selected as samples, and tracked from December 2015 to February 2017. For the meta-analysis, relevant literature from "PubMed" and "Embase" databases (until December 2016), was searched and TSA was used to verify the results. In order to achieve the best evidence hierarchies, our retrospective cohort study was added to the meta-analysis and the TSA. Results: The combined sample size for Asian was 1,685 after adding our cohort study, and there was no significant correlation between PPARG Pro12Ala and mortality by the allele model (RR: 0.85, 95% CI: 0.39-1.83, I2 = 79.3%). Under the parameter setting with the RR value of 1.5, TSA estimation presented that the cumulative sample size entered into the futility area, and it confirmed the conclusion in this study. Conclusion: We found that PPARG Pro12Ala gene polymorphism was not related to mortality in CKD Asians patients, and validated our conclusion using TSA after adding our sample.

Novel and Efficient Quantitative Posterior-Circulation-Structure-Based Scale via Noncontrast CT to Predict Ischemic Stroke Prognosis: A Retrospective Study.

(1) Background: Posterior circulation ischemic stroke has high mortality and disability rates and requires an early prediction prognosis to provide the basis for an interventional approach. Current quantitative measures are only able to accurately assess the prognosis of patients using magnetic resonance imaging (MRI). However, it is difficult to obtain MRI images in critically urgent cases. Therefore, the development of a noncontrast CT-based rapid-assist tool is needed to enhance the value of the clinical application. (2) Objective: This study aimed to develop an auxiliary-annotating noncontrast CT-efficient tool, which is based on a deep learning model, to provide a quantitative scale and the prognosis of posterior circulation ischemic stroke patients. (3) Methods: A total of 31 patients with posterior circulation ischemic stroke, diagnosed in the stroke registry at the Tri-Service General Hospital from November 2019 to July 2020, were included in the study, with a total of 578 CT images collected from noncontrast CT and MRI that were ≤ 3 days apart. A 5-fold cross validation was used to develop an image segmentation model to identify nine posterior circulation structures, and intersection over union (IoU) was used to assess the ability of the model to identify each structure. A quantitative score was integrated to assess the importance of the proportion of ischemic lesions in each posterior circulation structure, and the ROC curve was compared with the semiquantitative score for prognostic power. The prognoses of the patients were defined into two groups of 18 patients. An mRS score of 0-2 at discharge was defined as a good prognosis, while an mRS score of 3-6 was deemed to be a poor prognosis. (4) Results: The performance of the image segmentation model for identifying the nine posterior circulation structures in noncontrast CT images was evaluated. The IoU of the left cerebellum was 0.78, the IoU of the right cerebellum was 0.79, the IoU of the left occipital lobe was 0.74, the IoU of the right occipital lobe was 0.68, the IoU of the left thalamus was 0.73, the IoU of the right thalamus was 0.75, the IoU of the medulla oblongata was 0.82, and the IoU of the midbrain was 0.83. The prognostic AUC of posterior circulation patients predicted using a quantitative integrated score was 0.74, which was significantly higher than that of the pc-ASPECTS (AUC = 0.63, p = 0.035), with a sensitivity of 0.67 and a specificity of 0.72. (5) Conclusions: In this study, a deep learning model was used to develop a noncontrast CT-based quantitative integrated score tool, which is an effective tool for clinicians to assess the prognosis of posterior circulation ischemic stroke.

Prognostic Analysis of Patients with Acute Myocardial Infarction Undergoing Implantation of Different Stents for the First Time.

For patients with acute myocardial infarction scheduled to undergo percutaneous coronary stent implantation, in most cases a drug-eluting stent is recommended as the first choice for treatment. However, there is a lack of research on the effectiveness of bare-metal stents and drug-eluting stents on patients with different types of myocardial infarction. Our objective was to explore the effects of bare-metal stents and drug-eluting stents on patients with different types of myocardial infarction in terms of major cardiovascular incidents. This retrospective cohort study included 934 patients with myocardial infarction undergoing coronary artery stent implantation for the first time at the cardiac catheter room of the Tri-Service General Hospital in the Neihu District between 2014 and 2018. Patients' information, including demographic data, laboratory data, cardiac echocardiography results, and angiocardiography results, was collected by reviewing medical records. Cox proportional hazards regression was used to adjust the potential confounding factors, and the adjusted data were then used to compare the correlation between different types of stents and major cardiovascular incidents in patients with ST-elevation myocardial infarction and non-ST-elevation myocardial infarction. After the confounding factors were adjusted, in patients with ST-elevation myocardial infarction receiving a drug-eluting stent compared with those receiving a bare-metal stent, it was found that the mortality risk was lower in terms of all causes of death (Adj-HR = 0.26, 95% CI = 0.14-0.48, p < 0.001) and cardiogenic death (Adj-HR = 0.20, 95% CI = 0.08-0.55, p = 0.002), the risk of non-fatal myocardial infarction was lower (Adj-HR = 0.17, 95% CI = 0.04-0.73, p = 0.017), and there was no difference in the risk of revascularization at the lesion site (Adj-HR = 0.59, 95% CI = 0.24-1.43, p = 0.243). It terms of the findings in patients with non-ST-elevation myocardial infarction, those receiving a drug-eluting stent had a lower risk of revascularization at the lesion site (Adj-HR = 0.48, 95% CI = 0.24-0.97, p = 0.04); however, there was no difference in the mortality risk in terms of all causes of death (Adj-HR = 0.71, 95% CI = 0.37-1.35, p = 0.296) or cardiogenic death (Adj-HR = 0.59, 95% CI = 0.18-1.90, p = 0.379),or in the risk of non-fatal myocardial infarction (Adj-HR = 0.27, 95% CI = 0.06-1.25, p = 0.093). Compared with bare-metal stents, drug-eluting stents provide better protection against death to receivers with ST-elevation myocardial infarction; however, this protection is decreased in receivers with non-ST-elevation myocardial infarction. It is recommended that for patients with non-ST-elevation myocardial infarction who are indicated to receive a drug-eluting stent, the clinical effectiveness of the treatment must be considered.

Loss of ten-eleven translocation 1 (TET1) expression as a diagnostic and prognostic biomarker of endometrial carcinoma.

Endometrial carcinoma (EC) is the most common gynecological cancer. However, there is currently no routinely used biomarker for differential diagnosis of malignant and premalignant endometrial lesions. Ten-eleven translocation (TET) proteins, especially TET1, were found to play a significant role in DNA demethylation, via conversion of 5-methylcytosine (5-mC) to 5-hydroxymethylcytosine (5-hmC). TET1, 5-mC, and 5-hmC expression profiles in endometrial carcinogenesis are currently unclear. We conducted a hospital-based retrospective review of the immunohistochemical expression of TET1, 5-mC, and 5-hmC in 181 endometrial samples. A "high" TET1 and 5-hmC expression score was observed in all cases of normal endometrium (100.0% and 100.0%, respectively) and in most samples of endometrial hyperplasia without atypia (90.9% and 78.8%, respectively) and atypical hyperplasia (90.6% and 93.8%, respectively), but a "high" score was found in only less than half of the EC samples (48.8% and 46.5%, respectively). The TET1 and 5-hmC expression scores were significantly higher in normal endometrium and premalignant endometrial lesions than in ECs (p < 0.001). A "high" 5-mC expression score was observed more frequently for ECs (81.4%) than for normal endometrium (40.0%), endometrial hyperplasia without atypia (51.5%), and atypical hyperplasia (53.1%) (p < 0.001). We also found that TET1 mRNA expression was lower in ECs compared to normal tissues (p = 0.0037). TET1 immunohistochemistry (IHC) scores were highly proportional to the TET1 mRNA levels and we summarize that the TET1 IHC scoring can be used for biomarker determinations. Most importantly, a higher TET1 score in EC cases was associated with a good overall survival (OS) rate, with a hazard ratio (HR) of 0.31 for death (95% confidence interval: 0.11-0.84). Our findings suggest that TET1, 5-mC, and 5-hmC expression is a potential histopathology biomarker for the differential diagnosis of malignant and premalignant endometrial lesions. TET1 is also a potential prognostic marker for EC.

Association between nitric oxide synthase T-786C genetic polymorphism and chronic kidney disease: Meta-analysis incorporating trial sequential analysis.

BACKGROUND: Several meta-analyses of the relationship between endothelial nitric oxide synthase (eNOS) T-786C gene polymorphism and chronic kidney disease (CKD) have been published. However, the results of these studies were inconsistent, and it is undetermined whether sample sizes are sufficient to reach a definite conclusion. OBJECTIVE: To elucidate the relationship between T-786C and CKD by combining previous studies with our case-control sample and incorporate trial sequential analysis (TSA) to verify whether the sample size is adequate to draw a definite conclusion. METHODS: PubMed and Embase databases were searched for relevant articles on eNOS T-786C and CKD before February 28, 2021. TSA was also incorporated to ascertain a conclusion. A total of 558 hemodialysis cases in the case-control study was recruited from nine dialysis centers in the northern area of Taiwan in 2020. Additionally, 640 healthy subjects of the control group, with estimated glomerular filtration rate (eGFR) ≥ 60 mL/min/1.73 m2, were selected from participants of the annual elderly health examination program at the Tri-Service General Hospital. The functional analysis was based on eQTL data from GTExPortal. RESULTS: After screening with eligibility criteria, 15 papers were included and eventually combined in a meta-analysis. The result of the TSA showed that the sample size for Caucasians was adequate to ascertain the correlation between eNOS T-786C and CKD but was insufficient for Asians. Therefore, we added our case-control samples (n = 1198), though not associated with CKD (odds ratio [OR] = 1.01, 95% confidence interval [CI] = 0.69-1.46), into a meta-analysis, which supported that eNOS T-786C was significantly associated with CKD in Asians (OR = 1.39, 95% CI = 1.04-1.85) by using an adequate cumulative sample size (n = 4572) analyzed by TSA. Data of eQTL from GTEx showed that T-786C with the C minor allele exhibited relatively lower eNOS mRNA expression in whole blood, indicating the hazardous role of eNOS T-786C in CKD. CONCLUSIONS: eNOS T-786C genetic polymorphism was of conclusive significance in the association with CKD among Asians in our meta-analysis. Our case-control samples play a decisive role in changing conclusions from indefinite to definite.