Lessons and Applications of Omics Research in Diabetes Epidemiology.

PURPOSE OF REVIEW: Recent advances in genomic technology and molecular techniques have greatly facilitated the identification of disease biomarkers, advanced understanding of pathogenesis of different common diseases, and heralded the dawn of precision medicine. Much of these advances in the area of diabetes have been made possible through deep phenotyping of epidemiological cohorts, and analysis of the different omics data in relation to detailed clinical information. In this review, we aim to provide an overview on how omics research could be incorporated into the design of current and future epidemiological studies. RECENT FINDINGS: We provide an up-to-date review of the current understanding in the area of genetic, epigenetic, proteomic and metabolomic markers for diabetes and related outcomes, including polygenic risk scores. We have drawn on key examples from the literature, as well as our own experience of conducting omics research using the Hong Kong Diabetes Register and Hong Kong Diabetes Biobank, as well as other cohorts, to illustrate the potential of omics research in diabetes. Recent studies highlight the opportunity, as well as potential benefit, to incorporate molecular profiling in the design and set-up of diabetes epidemiology studies, which can also advance understanding on the heterogeneity of diabetes. Learnings from these examples should facilitate other researchers to consider incorporating research on omics technologies into their work to advance the field and our understanding of diabetes and its related co-morbidities. Insights from these studies would be important for future development of precision medicine in diabetes.

Age- and sex-specific hospital bed-day rates in people with and without type 2 diabetes: A territory-wide population-based cohort study of 1.5 million people in Hong Kong.

BACKGROUND: Type 2 diabetes affects multiple systems. We aimed to compare age- and sex-specific rates of all-cause and cause-specific hospital bed-days between people with and without type 2 diabetes. METHODS AND FINDINGS: Data were provided by the Hong Kong Hospital Authority. We included 1,516,508 one-to-one matched people with incident type 2 diabetes (n = 758,254) and those without diabetes during the entire follow-up period (n = 758,254) between 2002 and 2018, followed until 2019. People with type 2 diabetes and controls were matched for age at index date (±2 years), sex, and index year (±2 years). We defined hospital bed-day rate as total inpatient bed-days divided by follow-up time. We constructed negative binominal regression models to estimate hospital bed-day rate ratios (RRs) by age at diabetes diagnosis and sex. All RRs were stratified by sex and adjusted for age and index year. During a median of 7.8 years of follow-up, 60.5% (n = 459,440) of people with type 2 diabetes and 56.5% (n = 428,296) of controls had a hospital admission for any cause, with a hospital bed-day rate of 3,359 bed-days and 2,350 bed-days per 1,000 person-years, respectively. All-cause hospital bed-day rate increased with increasing age in controls, but showed a J-shaped relationship with age in people with type 2 diabetes, with 38.4% of bed-days in those diagnosed <40 years caused by mental health disorders. Type 2 diabetes was associated with increased risks for a wide range of medical conditions, with an RR of 1.75 (95% CI [confidence interval] [1.73, 1.76]; p < 0.001) for all-cause hospital bed-days in men and 1.87 (95% CI [1.85, 1.89]; p < 0.001) in women. The RRs were greater in people with diabetes diagnosed at a younger than older age and varied by sex according to medical conditions. Sex differences were most notable for a higher RR for urinary tract infection and peptic ulcer, and a lower RR for chronic kidney disease and pancreatic disease in women than men. The main limitation of the study was that young people without diabetes in the database were unlikely to be representative of those in the Hong Kong general population with potential selection bias due to inclusion of individuals in need of medical care. CONCLUSIONS: In this study, we observed that type 2 diabetes was associated with increased risks of hospital bed-days for a wide range of medical conditions, with an excess burden of mental health disorders in people diagnosed at a young age. Age and sex differences should be considered in planning preventive and therapeutic strategies for type 2 diabetes. Effective control of risk factors with a focus on mental health disorders are urgently needed in young people with type 2 diabetes. Healthcare systems and policymakers should consider allocating adequate resources and developing strategies to meet the mental health needs of young people with type 2 diabetes, including integrating mental health services into diabetes care.

Evaluating the impact of glucokinase activation on risk of cardiovascular disease: a Mendelian randomisation analysis.

BACKGROUND: Glucokinase activators (GKAs) are an emerging class of glucose lowering drugs that activate the glucose-sensing enzyme glucokinase (GK). Pending formal cardiovascular outcome trials, we applied two-sample Mendelian randomisation (MR) to investigate the impact of GK activation on risk of cardiovascular diseases. METHODS: We used independent genetic variants in or around the glucokinase gene meanwhile associated with HbA1c at genome-wide significance (P < 5 × 10-8) in the Meta-Analyses of Glucose and Insulin-related traits Consortium study (N = 146,806; European ancestry) as instrumental variables (IVs) to mimic the effects of GK activation. We assessed the association between genetically proxied GK activation and the risk of coronary artery disease (CAD; 122,733 cases and 424,528 controls), peripheral arterial disease (PAD; 7098 cases and 206,541 controls), stroke (40,585 cases and 406,111 controls) and heart failure (HF; 47,309 cases and 930,014 controls), using genome-wide association study summary statistics of these outcomes in Europeans. We compared the effect estimates of genetically proxied GK activation with estimates of genetically proxied lower HbA1c on the same outcomes. We repeated our MR analyses in East Asians as validation. RESULTS: Genetically proxied GK activation was associated with reduced risk of CAD (OR 0.38 per 1% lower HbA1c, 95% CI 0.29-0.51, P = 8.77 × 10-11) and HF (OR 0.54 per 1% lower HbA1c, 95% CI 0.41-0.73, P = 3.55 × 10-5). The genetically proxied protective effects of GKA on CAD and HF exceeded those due to non-targeted HbA1c lowering. There was no causal relationship between genetically proxied GK activation and risk of PAD or stroke. The estimates in sensitivity analyses and in East Asians were generally consistent. CONCLUSIONS: GKAs may protect against CAD and HF which needs confirmation by long-term clinical trials.

Risk stratification of ST-segment elevation myocardial infarction (STEMI) patients using machine learning based on lipid profiles.

BACKGROUND: Numerous studies have revealed the relationship between lipid expression and increased cardiovascular risk in ST-segment elevation myocardial infarction (STEMI) patients. Nevertheless, few investigations have focused on the risk stratification of STEMI patients using machine learning algorithms. METHODS: A total of 1355 STEMI patients who underwent percutaneous coronary intervention were enrolled in this study during 2015-2018. Unsupervised machine learning (consensus clustering) was applied to the present cohort to classify patients into different lipid expression phenogroups, without the guidance of clinical outcomes. Kaplan-Meier curves were implemented to show prognosis during a 904-day median follow-up (interquartile range: 587-1316). In the adjusted Cox model, the association of cluster membership with all adverse events including all-cause mortality, all-cause rehospitalization, and cardiac rehospitalization was evaluated. RESULTS: All patients were classified into three phenogroups, 1, 2, and 3. Patients in phenogroup 1 with the highest Lp(a) and the lowest HDL-C and apoA1 were recognized as the statin-modified cardiovascular risk group. Patients in phenogroup 2 had the highest HDL-C and apoA1 and the lowest TG, TC, LDL-C and apoB. Conversely, patients in phenogroup 3 had the highest TG, TC, LDL-C and apoB and the lowest Lp(a). Additionally, phenogroup 1 had the worst prognosis. Furthermore, a multivariate Cox analysis revealed that patients in phenogroup 1 were at significantly higher risk for all adverse outcomes. CONCLUSION: Machine learning-based cluster analysis indicated that STEMI patients with increased concentrations of Lp(a) and decreased concentrations of HDL-C and apoA1 are likely to have adverse clinical outcomes due to statin-modified cardiovascular risks. TRIAL REGISTRATION: ChiCTR1900028516 ( http://www.chictr.org.cn/index.aspx ).

Comparison of desmopressin, alarm, desmopressin plus alarm, and desmopressin plus anticholinergic agents in the management of paediatric monosymptomatic nocturnal enuresis: a network meta-analysis.

OBJECTIVE: To assess the efficacy of desmopressin, alarm, desmopressin plus alarm, and desmopressin plus anticholinergic agent (AA) therapy in the management of paediatric monosymptomatic nocturnal enuresis (MNE) using a network meta-analysis. MATERIALS AND METHODS: We searched the electronic databases PubMed, Cochrane Library, EMBASE and Web of Science from inception to 1 March 2018. Randomized controlled trials (RCTs) that compared desmopressin, alarm, desmopressin plus alarm, and desmopressin plus AAs were identified. The network meta-analysis was conducted with software R 3.3.2 and STATA 14.0. RESULTS: Eighteen RCTs with a total of 1 649 participants were included. The meta-analysis results showed that complete response (CR) and success rates with desmopressin plus AAs were higher than with desmopressin or alarm monotherapy. Success rates for desmopressin plus alarm therapy were higher than for alarm monotherapy. No obvious difference was observed between desmopressin plus AAs and desmopressin plus alarm therapy with regard to CR rate and success rate. The relapse rate with alarm monotherapy was much lower than with desmopressin monotherapy. Adverse events seemed to be infrequently and tolerable for all treatments. The ranking probability results were as follows: desmopressin plus AA ranked first for the outcomes of CR and success, desmopressin plus alarm therapy ranked first for mean number of wet nights per week, and alarm therapy had the lowest relapse rate. CONCLUSIONS: The network meta-analysis showed that desmopressin had similar efficacy to alarm therapy but a higher relapse rate. Desmopressin plus AA therapy was associated with better efficacy than and a similar relapse rate to desmopressin monotherapy. Desmopressin plus alarm therapy was similar to both desmopressin and alarm monotherapy in efficacy. All treatments, including desmopressin plus AAwere associated with tolerable adverse events; however, additional high-quality studies are needed for further evaluation of these treatments.

Comparison of different prognostic models for predicting cancer-specific survival in bladder transitional cell carcinoma.

OBJECTIVE: To construct the newly valuable nomogram which can compare the predictive performance with American Joint Committee on Cancer (AJCC) staging system in bladder transitional cell carcinoma (BTCC). METHODS: BTCC patients were screened (2004-2015) from the SEER database. The nomogram incorporating lymph node ratio was constructed to evaluate individualized cancer-specific survival. RESULTS: The C-index of the nomogram for predicting cancer-specific survival was 0.743 (95% CI: 0.720-0.766), which was higher than C-index of the AJCC staging system. CONCLUSION: Lymph node ratio can be a reliable prognostic indicator for BTCC. The proposed nomogram showed more satisfactory predictive accuracy and wider applicability than current AJCC staging system in individualized prediction of BTCC patients.

The efficacy and safety comparison of surgical treatments for stress urinary incontinence: A network meta-analysis.

AIMS: Stress urinary incontinence (SUI) is a common problem worldwide. Mainstream surgical procedures include tension-free vaginal tape (TVT), transobturator tape (TOT), tension-free vaginal tape-obturator (TVT-O), tension-free vaginal tape SECUR (TVT-S), and adjustable single-incision sling (Ajust). The aim of this study was to compare the efficacy and safety of these surgical procedures and assess which surgery is most optimal for SUI by adopting a network meta-analysis (NMA). METHODS: Electronic databases including PubMed, Cochrance Library, and Embase database were researched systematically, until March 21, 2017. The randomized controlled trials (RCTs) that compared the efficacy and safety of TVT, TOT, TVT-O, TVT-S, and Ajust were identified. The studies were included in the analysis when met the predefined inclusion criteria. After demographic and outcome data extraction, a network meta-analysis was conducted with software R 3.3.2 and STATA 14.0. Objective cure rate, subjective cure rate, postoperative complication rate, bladder perforation, tape erosion, urinary retention, and postoperative pain were considered as outcomes, and the outcomes were displayed as odds ratios (ORs) and 95% credible intervals (CrI). The consistency of direct and indirect evidence was assessed by node splitting. The ranks based on probabilities of intervention for the different endpoints were performed. RESULTS: Fourty-five RCTs with 7295 participants were analyzed. The NMA results revealed that, TVT, TOT, and Ajust had a higher objective cure rate than TVT-O and TVT-S (TVT-O: OR = 0.76, 95%CI [0.61, 0.94]; TVT-S: OR = 0.41, 95%CI [0.28, 0.60]). TVT, TOT, and TVT-O had a superior subjective cure rate than TVT-S and Ajust (Ajust: OR = 0.45, 95%CI [0.20, 0.91]; TVT-S: OR = 0.29, 95%CI [0.15, 0.56]). With TVT as the reference, TVT-S had a statistically lower postoperative complication rate (TVT-S: OR = 0.39, 95%CI [0.16, 0.89]). TVT-O, TVT-S, and TOT had a significantly lower bladder perforation rate (TOT: OR = 0.076, 95%CI [0.0060, 0.37]; TVT-O: OR = 4.1e-17, 95%CI [6.1e-48, 0.0032]; TVT-S: OR = 3.8e-17, 95%CI [1.8e-48, 0.0052]). There were no obvious differences between the five treatments for tape erosion. TVT-O exhibited a less postoperative retention (TVT-O: OR = 0.35, 95%CI [0.16, 0.74]). Probabilities of ranking results indicated that TOT was the treatment with best ranking in efficacy and a relatively high safety. CONCLUSIONS: Our study recommend TOT as the optimal regimen for SUI with high efficacy and moderate safety when compared with TVT, TVT-O, TVT-S, and Ajust interventions. However, with the limitation of our study, additional high-quality studies are needed to further evaluate the outcomes.

Construction and Comprehensive Analysis for Dysregulated Long Non-Coding RNA (lncRNA)-Associated Competing Endogenous RNA (ceRNA) Network in Gastric Cancer.

Long non-coding RNA (lncRNA) is a kind of non-coding RNA with transcripts more than 200 bp in length. LncRNA can interact with the miRNA as a competing endogenous RNA (ceRNA) to regulate the expression of target genes, which play a significant role in the initiation and progression of tumors. In this study, we explored the functional roles and regulatory mechanisms of lncRNAs as ceRNAs in gastric cancer, and their potential implications for prognosis. The lncRNAs, miRNAs, and mRNAs expression profiles of 375 gastric cancer tissues and 32 non-tumor gastric tissues were downloaded from The Cancer Genome Atlas (TCGA) database. Differential expression of RNAs was identified using the DESeq package. Survival analysis was estimated based on Kaplan-Meier curve analysis. KEGG pathway analysis was performed using KOBAS 3.0. The dysregulated lncRNA-associated ceRNA network was constructed in gastric cancer based on bioinformatics generated from miRcode and miRTarBase. A total of 237 differentially expressed lncRNAs and 198 miRNAs between gastric cancer and matched normal tissues were screened in our study with thresholds of |log2FC| >2 and adjusted P value <0.01. Eleven discriminatively expressed lncRNAs may be correlated with tumorigenesis of gastric cancer. Seven out of 11 dysregulated lncRNA were found to be significantly associated with overall survival in gastric cancer (P value <0.05). The newly identified ceRNA network includes 11 gastric cancer-specific lncRNAs, 9 miRNAs, and 41 mRNAs. Collectively, our study will contribute to improving the understanding of the lncRNA-associated ceRNA network regulatory mechanisms in the pathogenesis of gastric cancer and provide and identify novel lncRNAs as candidate prognostic biomarkers or potential therapeutic targets.

The long non-coding RNA MALAT1 is increased in renal ischemia-reperfusion injury and inhibits hypoxia-induced inflammation.

BACKGROUND: To investigate the expression of long non-coding RNA metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) in renal ischemia-reperfusion injury and explore its role in acute kidney injury. METHODS: 18 mice were randomly divided into a sham operation group (Sham) and an ischemia-reperfusion group (IR) in which animals were sacrificed at 6 h or 12 h after surgery. The kidneys were harvested to measure the expression of MALAT1 mRNA. HK2 cells were treated with cobalt chloride (CoCl2) to mimic hypoxia or transfected with siRNA to knockdown MALAT1 before CoCl2 treatment. After that, MALAT1 was analyzed by RT-PCR (reverse transcription-polymerase chain reaction). HIF-1ɑ (hypoxia-inducible factor-1 alpha) and NF-κB (nuclear factor-kappa B) was measured by Western blot. The concentrations of IL-6 (interleukin-6) and TNF-ɑ (tumor necrosis factor-alpha) in the media were detected by ELISA (enzyme-linked immunosorbent assay). RESULTS: The expression of MALAT1 in the IR (6 h/12 h) group was significantly higher than that in the sham group. In HK2 cells, MALAT1 was significantly increased at 1 h, 3 h, and 6 h after CoCl2 treatment but had reduced to the basal level at 12 h and 24 h. Knockdown of MALAT1 by siRNA significantly up-regulated the expression of HIF-1ɑ and NF-κB proteins in CoCl2-treated HK2 cells. In addition, the concentrations of IL-6 and TNF-ɑ were increased by MALAT1 siRNA transfection in CoCl2-treated HK2 cells. CONCLUSION: The expression of MALAT1 is increased in renal ischemia-reperfusion injury. It is likely that MALAT1 inhibits the hypoxia-induced inflammatory response through the NF-κB pathway.

Precision prognostics for cardiovascular disease in Type 2 diabetes: a systematic review and meta-analysis.

BACKGROUND: Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with Type 2 diabetes (T2D). METHODS: We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. RESULTS: Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. CONCLUSIONS: Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

People living with type 2 diabetes (T2D) are more likely to develop problems with their heart or blood circulation, known as cardiovascular disease (CVD), than people who do not have T2D. However, it can be difficult to predict which people with T2D are most likely to develop CVD. This is because current approaches, such as blood tests, do not identify all people with T2D who are at an increased risk of CVD. In this study we reviewed published papers that investigated the differences between people with T2D who experienced CVD compared to those who did not. We found some indicators that could potentially be used to determine which people with T2D are most likely to develop CVD. More studies are needed to determine how useful these are. However, they could potentially be used to enable clinicians to provide targeted advice and treatment to those people with T2D at most risk of developing CVD.

DNA methylation markers for kidney function and progression of diabetic kidney disease.

Epigenetic markers are potential biomarkers for diabetes and related complications. Using a prospective cohort from the Hong Kong Diabetes Register, we perform two independent epigenome-wide association studies to identify methylation markers associated with baseline estimated glomerular filtration rate (eGFR) and subsequent decline in kidney function (eGFR slope), respectively, in 1,271 type 2 diabetes subjects. Here we show 40 (30 previously unidentified) and eight (all previously unidentified) CpG sites individually reach epigenome-wide significance for baseline eGFR and eGFR slope, respectively. We also develop a multisite analysis method, which selects 64 and 37 CpG sites for baseline eGFR and eGFR slope, respectively. These models are validated in an independent cohort of Native Americans with type 2 diabetes. Our identified CpG sites are near genes enriched for functional roles in kidney diseases, and some show association with renal damage. This study highlights the potential of methylation markers in risk stratification of kidney disease among type 2 diabetes individuals.

Precision Prognostics for Cardiovascular Disease in Type 2 Diabetes: A Systematic Review and Meta-analysis.

Background Precision medicine has the potential to improve cardiovascular disease (CVD) risk prediction in individuals with type 2 diabetes (T2D). Methods We conducted a systematic review and meta-analysis of longitudinal studies to identify potentially novel prognostic factors that may improve CVD risk prediction in T2D. Out of 9380 studies identified, 416 studies met inclusion criteria. Outcomes were reported for 321 biomarker studies, 48 genetic marker studies, and 47 risk score/model studies. Results Out of all evaluated biomarkers, only 13 showed improvement in prediction performance. Results of pooled meta-analyses, non-pooled analyses, and assessments of improvement in prediction performance and risk of bias, yielded the highest predictive utility for N-terminal pro b-type natriuretic peptide (NT-proBNP) (high-evidence), troponin-T (TnT) (moderate-evidence), triglyceride-glucose (TyG) index (moderate-evidence), Genetic Risk Score for Coronary Heart Disease (GRS-CHD) (moderate-evidence); moderate predictive utility for coronary computed tomography angiography (low-evidence), single-photon emission computed tomography (low-evidence), pulse wave velocity (moderate-evidence); and low predictive utility for C-reactive protein (moderate-evidence), coronary artery calcium score (low-evidence), galectin-3 (low-evidence), troponin-I (low-evidence), carotid plaque (low-evidence), and growth differentiation factor-15 (low-evidence). Risk scores showed modest discrimination, with lower performance in populations different from the original development cohort. Conclusions Despite high interest in this topic, very few studies conducted rigorous analyses to demonstrate incremental predictive utility beyond established CVD risk factors for T2D. The most promising markers identified were NT-proBNP, TnT, TyG and GRS-CHD, with the highest strength of evidence for NT-proBNP. Further research is needed to determine their clinical utility in risk stratification and management of CVD in T2D.

Human Serum Metabolites as Potential Mediators from Type 2 Diabetes and Obesity to COVID-19 Severity and Susceptibility: Evidence from Mendelian Randomization Study.

Obesity, type 2 diabetes (T2D), and severe coronavirus disease 2019 (COVID-19) are closely associated. The aim of this study was to elucidate the casual and mediating relationships of human serum metabolites on the pathways from obesity/T2D to COVID-19 using Mendelian randomization (MR) techniques. We performed two-sample MR to study the causal effects of 309 metabolites on COVID-19 severity and susceptibility, based on summary statistics from genome-wide association studies (GWAS) of metabolites (n = 7824), COVID-19 phenotypes (n = 2,586,691), and obesity (n = 322,154)/T2D traits (n = 898,130). We conducted two-sample network MR analysis to determine the mediating metabolites on the causal path from obesity/T2D to COVID-19 phenotypes. We used multivariable MR analysis (MVMR) to discover causal metabolites independent of body mass index (BMI). Our MR analysis yielded four causal metabolites that increased the risk of severe COVID-19, including 2-stearoylglycerophosphocholine (OR 2.15; 95% CI 1.48-3.11), decanoylcarnitine (OR 1.32; 95% CI 1.17-1.50), thymol sulfate (OR 1.20; 95% CI 1.10-1.30), and bradykinin-des-arg(9) (OR 1.09; 95% CI 1.05-1.13). One significant mediator, gamma-glutamyltyrosine, lay on the causal path from T2D/obesity to severe COVID-19, with 16.67% (0.64%, 32.70%) and 6.32% (1.76%, 10.87%) increased risk, respectively, per one-standard deviation increment of genetically predicted T2D and BMI. Our comprehensive MR analyses identified credible causative metabolites, mediators of T2D and obesity, and obesity-independent causative metabolites for severe COVID-19. These biomarkers provide a novel basis for mechanistic studies for risk assessment, prognostication, and therapeutic purposes in COVID-19.

Cross-Sectional Association of Blood Selenium with Glycemic Biomarkers among U.S. Adults with Normoglycemia in the National Health and Nutrition Examination Survey 2013-2016.

Selenium (Se) remains to have an inconsistent relationship with glycemic biomarkers and the risk of developing type 2 diabetes (T2D). Few studies have investigated the relationship between blood Se and glycemic biomarkers among people with normoglycemia. We conducted a cross-sectional analysis using the U.S. National Health and Nutrition Examination Survey 2013-2016. Multivariable linear regression models were developed to examine the associations of blood Se with glycemic biomarkers, namely, fasting plasma glucose (FPG), hemoglobin A1c (HbA1c), insulin, and the oral glucose tolerance test (OGTT). Blood Se was treated as continuous (per log-10 increment) and categorical exposure (in quartiles) in separate regression models. We assessed the dose-response relationships by restricted cubic spline analysis. After excluding the participants with T2D or incomplete data, 2706 participants were analyzed. The highest quartile of blood Se was associated with increased FPG [adjusted ß = 0.12, 95% Confidence Intervals (CI) = 0.04, 0.20], OGTT (adjusted ß = 0.29, 95% CI = 0.02, 0.56), HbA1c (adjusted ß = 0.04, 95% CI = 0.00, 0.07), and insulin (adjusted ß = 2.50, 95% CI = 1.05, 3.95) compared with the lowest quartile. Positive associations were also observed between every log-10 increment of blood Se level and glycemic biomarkers, except for OGTT. A positive linear dose-response relationship existed between blood Se and FPG (Poverall = 0.003, Pnonlinear = 0.073) and insulin (Poverall = 0.004, Pnonlinear =0.060). BMI, age, and smoking status modified the associations of the highest quartile of Se (compared with the lowest quartile) with glycemic biomarkers. Overall, positive associations of blood Se with glycemic biomarkers were observed among U.S. adults with normoglycemia. These findings implied that people with normoglycemia need to be aware of the level of Se and other mineral intakes from diet and supplements. Further research is required to identify the mechanisms of excess Se in the progression of diabetes.

Causal effects of genetically determined metabolites on cancers included lung, breast, ovarian cancer, and glioma: a Mendelian randomization study.

Background: Previous studies have shown that metabolites play important roles in phenotypic regulation, but the causal link between metabolites and tumors has not been examined adequately. Herein, we investigate the causality between metabolites and various cancers through a Mendelian randomization (MR) study. Methods: We carried out a two-sample MR analysis based on genetic instrumental variables as proxies for 486 selected human serum metabolites to evaluate the causal effects of genetically determined metabotypes (GDMs) on cancers. Summary data from various cancer types obtained from large consortia. Inverse variance weighted (IVW), MR-Egger and weighted-median methods were implemented to infer the causal effects, moreover, we particularly explored the presentence of horizontal pleiotropy through MR-Egger regression and MR-PRESSO Global test. Metabolic pathways analysis and subgroup analyses were further explored using available data. Statistical analyses were all performed in R. Results: In MR analysis, 202 significant causative relationship features were identified. 7-alpha-hydroxy-3-oxo-4-cholestenoate (ORIVW =1.45; 95% CI: 1.06-1.97; PIVW =0.018), gamma-glutamylisoleucine (ORIVW =1.40; 95% CI: 1.16-1.69; PIVW =0.0004), 1-oleoylglycerophosphocholine (ORIVW =1.22; 95% CI: 1.1-1.35; PIVW =0.0001), gamma-glutamylleucine (ORIVW =4.74; 95% CI: 1.18-18.93; PIVW =0.027) were the most dangerous metabolites for lung cancer, ovarian cancer, breast cancer, and glioma, respectively; while pseudouridine (ORIVW =0.50; 95% CI: 0.30-0.83; PIVW =0.007), 2-methylbutyroylcarnitine (ORIVW =0.77; 95% CI: 0.68-0.86; PIVW =2.9×10-6), 2-methylbutyroylcarnitine (ORIVW =0.77; 95% CI: 0.70-0.85; PIVW =3.4×10-7), glycylvaline (ORIVW =0.13; 95% CI: 0.02-0.75; PIVW =0.021) were associated with lower risk of lung cancer, ovarian cancer, breast cancer, and glioma, respectively. Interestingly, 2-methylbutyroylcarnitine was also associated with decreased risk of lung cancer (ORIVW =0.59; 0.50-0.70; P IVW =1.98×10-9) expect ovarian cancer and breast cancer. In subgroup analysis, 2-methylbutyroylcarnitine was associated with decreased risk of estrogen receptor (ER) positive breast cancer (ORIVW =0.72; 0.64-0.80; PIVW =3.55×10-9), lung adenocarcinoma (LAC) (ORIVW =0.60; 0.48-0.70; PIVW =1.14×10-5). Metabolic pathways analysis identified 4 significant pathways. Conclusions: Our study integrated metabolomics and genomics to explore the risk factors involved in the development of cancers. It is worth exploring whether metabolites with causality can be used as biomarkers to distinguish patients at high risk of cancer in clinical practice. More detailed studies are needed to clarify the mechanistic pathways.

Shortened Leukocyte Telomere Length Is Associated With Glycemic Progression in Type 2 Diabetes: A Prospective and Mendelian Randomization Analysis.

OBJECTIVE: Several studies support associations between relative leukocyte telomere length (rLTL), a biomarker of biological aging and type 2 diabetes. This study investigates the relationship between rLTL and the risk of glycemic progression in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS: In this cohort study, consecutive Chinese patients with type 2 diabetes (N = 5,506) from the Hong Kong Diabetes Register with stored baseline DNA and available follow-up data were studied. rLTL was measured using quantitative PCR. Glycemic progression was defined as the new need for exogenous insulin. RESULTS: The mean (SD) age of the 5,349 subjects was 57.0 (13.3) years, and mean (SD) follow-up was 8.8 (5.4) years. Baseline rLTL was significantly shorter in the 1,803 subjects who progressed to insulin requirement compared with the remaining subjects (4.43 ± 1.16 vs. 4.69 ± 1.20). Shorter rLTL was associated with a higher risk of glycemic progression (hazard ratio [95% CI] for each unit decrease [to ∼0.2 kilobases]: 1.10 [1.06-1.14]), which remained significant after adjusting for confounders. Baseline rLTL was independently associated with glycemic exposure during follow-up (ß = -0.05 [-0.06 to -0.04]). Each 1-kilobase decrease in absolute LTL was on average associated with a 1.69-fold higher risk of diabetes progression (95% CI 1.35-2.11). Two-sample Mendelian randomization analysis showed per 1-unit genetically decreased rLTL was associated with a 1.38-fold higher risk of diabetes progression (95% CI 1.12-1.70). CONCLUSIONS: Shorter rLTL was significantly associated with an increased risk of glycemic progression in individuals with type 2 diabetes, independent of established risk factors. Telomere length may be a useful biomarker for glycemic progression in people with type 2 diabetes.

Comparison of DJ stented, external stented and stent-less procedures for pediatric pyeloplasty: A network meta-analysis.

OBJECTIVE: To assess the efficacy and safety of double J (DJ) stented, external stented and stent-less procedures in pediatric pyeloplasty by adopting a network meta-analysis (NMA). MATERIAL AND METHODS: Electronic databases including PubMed, Cochrane Library, Web of science and Embase database were retrieved. The trials that compared double J (DJ) stented, external stented or stent-less procedures in pediatric pyeloplasty were identified. A network meta-analysis was conducted with the software of STATA 14.0. Probability-based ranking results were performed to identify the best treatment, and publication bias was analyzed by funnel plots. RESULTS: 15 studies with 1731 participants were enrolled in the analysis, including 4 randomized controlled trials (RCT) and 11 retrospective studies. The NMA results revealed that no significant differences were detected in the outcomes of operative time, operative success, hospital stay, improvement of renal functions, overall complications and redo pyeloplasty. DJ stented and external stented procedures were associated with more postoperative pain than that of stent-less procedures [DJ stented: OR = 4.47, 95%CI(1.05,19.08); external stented: OR = 5.83, 95%CI(0.09,1.43)]. DJ stented procedure had a lower rate of urine leakage than those of external stented procedure [OR = 0.18, 95%CI (0.04, 0.76)] and stent-less procedure [OR = 0.07, 95%CI=(0.01, 0.34)]. No significant difference was observed in other types of complications such as urinary tract infection (UTI), stent migration, recurrent ureteropelvic junction obstruction (UPJO) and fever. The probabilities of ranking results indicated that the DJ stented procedure was the best treatment in the outcomes of hospital stay, operative success, improvement of renal functions, and the complication of urine leakage. Stent-less procedure showed its advantages in the outcomes of operative time, flank pain and UTI. External stented procedure had the lowest rate of overall complications and redo pyeloplasty. CONCLUSIONS: There were no obvious differences in operative time, operative success, hospital stay, improvement of renal functions, overall complications between external stented, DJ stented and stent-less procedures for pediatric pyeloplasty. When considering the ranking results, the DJ stented procedure seemed to be more beneficial for pediatric pyeloplasty than the other methods. However, with the limitation of our study, additional high-quality studies are needed for further evaluation.

Weighted gene co­expression network analysis for identifying hub genes in association with prognosis in Wilms tumor.

Wilms tumor (WT) is the most common type of renal malignancy in children. Survival rates are low and high­risk WT generally still carries a poor prognosis. To better elucidate the pathogenesis and tumorigenic pathways of high­risk WT, the present study presents an integrated analysis of RNA expression profiles of high­risk WT to identify predictive molecular biomarkers, for the improvement of therapeutic decision­making. mRNA sequence data from high­risk WT and adjacent normal samples were downloaded from The Cancer Genome Atlas to screen for differentially expressed genes (DEGs) using R software. From 132 Wilms tumor samples and six normal samples, 2,089 downregulated and 941 upregulated DEGs were identified. In order to identify hub DEGs that regulate target genes, weighted gene co­expression network analysis (WGCNA) was used to identify 11 free­scale gene co­expressed clusters. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were annotated using KEGG Orthology Based Annotation System annotation of different module genes. The Search Tool for the Retrieval of Interacting Genes was used to construct a protein­protein interaction network for the identified DEGs, and the hub genes of WGCNA modules were identified using the Cytohubb plugin with Cytoscape software. Survival analysis was subsequently performed to highlight hub genes with a clinical signature. The present results suggest that epidermal growth factor, cyclin dependent kinase 1, endothelin receptor type A, nerve growth factor receptor, opa­interacting protein 5, NDC80 kinetochore complex component and cell division cycle associated 8 are essential to high­risk WT pathogenesis, and they are closely associated with clinical prognosis.

Investigation of miRNA- and lncRNA-mediated competing endogenous RNA network in cholangiocarcinoma.

Cholangiocarcinoma (CCA) is a biliary malignancy which is prone to lymphatic metastasis and has a high mortality rate. This disease lacks effective therapeutic targets and prognostic molecular biomarkers. The aim of the current study was to investigate differentially expressed genes and elucidate their association with CCA and the underlying mechanisms of action. mRNAs, long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) obtained from 36 CCA samples and nine normal samples from The Cancer Genome Atlas were integrated. Subsequently, 1,095 differentially expressed (DE) mRNAs and 75 DE miRNAs were identified using a threshold of |log2 fold change|>2 and an adjusted P<0.01. Weighted gene co-expression network analysis was used to identify the DEmRNAs that could be key target genes in CCA. A total of 12 hub DEmRNAs were identified as targetable genes. Furthermore, the hub DEmRNAs-DElncRNAs pairs were identified using the miRTarBase and miRcode databases. Cytoscape software was used to construct and visualize the protein-protein interactions and the competing endogenous RNA network. Survival time analysis and correlation analysis were used to further evaluate the hub genes. The results obtained in the current study suggested that spalt like transcription factor 3 and OPCML intronic transcript 1 may serve an important role in the development and progression of CCA.

Prognostic nomograms based on log odds of positive lymph nodes for patients with renal cell carcinoma: A retrospective cohort study.

OBJECTIVES: The aim of the current study is to build prognostic nomograms for patients with renal cell carcinoma (RCC) and compare the predictive performance with the American Joint Committee on Cancer (AJCC) staging system. METHODS: A total of 9453 patients were identified (2005-2015) from the Surveillance Epidemiology and End Results (SEER) database. Propensity-score matching (PSM) was conducted to reduce selective bias. The matched cohort was further divided equally into the development and the validation cohort. Nomograms based on log odds of positive lymph nodes (LODDS) were formulated to predict individualized cancer-specific survival (CSS) and overall survival (OS) for RCC. Then, the performance of nomograms was internally and externally validated via the concordance index (C-index) and calibration plots. Decision curve analysis (DCA) was used to compare the clinical practicable between nomograms and AJCC staging system. RESULTS: LODDS was identified as an independent prognostic indicator for CSS and OS using univariate and multivariate Cox regression analyses. Two nomograms incorporating LODDS were formulated. The C-indices of the nomograms for predicting CSS and OS were 0.7561 (95% CI, 0.7356-0.7766) and 0.7140 (95% CI, 0.6936-0.7343) in the development cohort, which was higher than C-index of the AJCC staging system. The results were reproducible in the validation cohort. Moreover, internal and external calibration plots showed that the nomograms-predicted was consistent with the actual observation. Additionally, DCA demonstrated that the nomograms were superior to the AJCC staging system with obtaining more clinical net benefit. CONCLUSIONS: LODDS could be considered as a reliable prognostic factor for patients with RCC. Two nomograms were able to more accurately and applicable than the AJCC staging system for predicting CSS and OS.