Identification of CCL20 as a prognostic predictor for severe fever with thrombocytopenia syndrome based on plasma proteomics.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS), a lethal tick-borne hemorrhagic fever, prompted our investigation into prognostic predictors and potential drug targets using plasma Olink Proteomics. METHODS: Employing the Olink assay, we analyzed 184 plasma proteins in 30 survivors and 8 non-survivors of SFTS. Validation was performed in a cohort of 154 SFTS patients using enzyme-linked immunosorbent assay. We utilized the Drug Gene Interaction database to identify protein-drug interactions. RESULTS: Non-survivors exhibited 110 differentially expressed proteins (DEPs) compared to survivors, with functional enrichment in the cell chemotaxis-related pathway. Thirteen DEPs, including C-C motif chemokine 20 (CCL20), calcitonin gene-related peptide alpha and Pleiotrophin, were associated with multiple organ dysfunction syndrome. CCL20 emerged as the top predictor of death, demonstrating an area under the curve of 1 (P = .0004) and 0.9033 (P < .0001) in the discovery and validation cohort, respectively. Patients with CCL20 levels exceeding 45.74 pg/mL exhibited a fatality rate of 45.65%, while no deaths occurred in those with lower CCL20 levels. Furthermore, we identified 202 FDA-approved drugs targeting 37 death-related plasma proteins. CONCLUSIONS: Distinct plasma proteomic profiles characterize SFTS patients with different outcomes, with CCL20 emerging as a novel, sensitive, accurate, and specific biomarker for predicting SFTS prognosis.

Susceptibility gene identification and risk evaluation model construction by transcriptome-wide association analysis for salt sensitivity of blood pressure.

BACKGROUND: Salt sensitivity of blood pressure (SSBP) is an intermediate phenotype of hypertension and is a predictor of long-term cardiovascular events and death. However, the genetic structures of SSBP are uncertain, and it is difficult to precisely diagnose SSBP in population. So, we aimed to identify genes related to susceptibility to the SSBP, construct a risk evaluation model, and explore the potential functions of these genes. METHODS AND RESULTS: A genome-wide association study of the systemic epidemiology of salt sensitivity (EpiSS) cohort was performed to obtain summary statistics for SSBP. Then, we conducted a transcriptome-wide association study (TWAS) of 12 tissues using FUSION software to predict the genes associated with SSBP and verified the genes with an mRNA microarray. The potential roles of the genes were explored. Risk evaluation models of SSBP were constructed based on the serial P value thresholds of polygenetic risk scores (PRSs), polygenic transcriptome risk scores (PTRSs) and their combinations of the identified genes and genetic variants from the TWAS. The TWAS revealed that 2605 genes were significantly associated with SSBP. Among these genes, 69 were differentially expressed according to the microarray analysis. The functional analysis showed that the genes identified in the TWAS were enriched in metabolic process pathways. The PRSs were correlated with PTRSs in the heart atrial appendage, adrenal gland, EBV-transformed lymphocytes, pituitary, artery coronary, artery tibial and whole blood. Multiple logistic regression models revealed that a PRS of P < 0.05 had the best predictive ability compared with other PRSs and PTRSs. The combinations of PRSs and PTRSs did not significantly increase the prediction accuracy of SSBP in the training and validation datasets. CONCLUSIONS: Several known and novel susceptibility genes for SSBP were identified via multitissue TWAS analysis. The risk evaluation model constructed with the PRS of susceptibility genes showed better diagnostic performance than the transcript levels, which could be applied to screen for SSBP high-risk individuals.

Impact of lipoprotein(a) level on cardiometabolic disease in the Chinese population: The CHCN-BTH Study.

BACKGROUND: The emergence of promising compounds to lower lipoprotein(a) [Lp(a)] has increased the need for a precise characterisation and comparability assessment of Lp(a)-associated cardiometabolic disease risk. This study aimed to evaluate the distribution of Lp(a) levels in a Chinese population and characterise the association with cardiometabolic diseases. METHODS: We assessed data from individuals from the Cohort Study on Chronic Diseases of the General Community Population in the Beijing-Tianjin-Hebei Region project. All Lp(a) measurements were performed in the same hospital. The cardiometabolic diseases considered were coronary heart disease (CHD), stroke, hypertension and type 2 diabetes (T2DM). RESULTS: A total of 25343 individuals were included in the study. The median level of Lp(a) was 11.9 mg/dl (IQR 5.9 to 23.7 mg/dl), and higher Lp(a) levels showed a significant concentration-dependent association with CHD risk. Individuals with Lp(a) levels lower than the 25th percentile were at increased risk of hypertension (OR: 1.15, 95% CI: 1.06-1.25) and T2DM (OR: 1.15, 95% CI: 1.03-1.28); however, Lp(a) levels were not significantly associated with stroke. The addition of Lp(a) levels to the prognostic model led to a marginal but significant C-index, integrated discrimination improvement and net reclassification improvement. CONCLUSIONS: In this large sample size study, we observed that elevated Lp(a) levels were significantly associated with CHD. Furthermore, we found that the lowest Lp(a) levels were also significantly associated with hypertension and T2DM. These results provide evidence for differential approaches to higher levels of Lp(a) in individuals with different cardiometabolic diseases.

Construction of genetic classification model for coronary atherosclerosis heart disease using three machine learning methods.

BACKGROUND: Although the diagnostic method for coronary atherosclerosis heart disease (CAD) is constantly innovated, CAD in the early stage is still missed diagnosis for the absence of any symptoms. The gene expression levels varied during disease development; therefore, a classifier based on gene expression might contribute to CAD diagnosis. This study aimed to construct genetic classification models for CAD using gene expression data, which may provide new insight into the understanding of its pathogenesis. METHODS: All statistical analysis was completed by R 3.4.4 software. Three raw gene expression datasets (GSE12288, GSE7638 and GSE66360) related to CAD were downloaded from the Gene Expression Omnibus database and included for analysis. Limma package was performed to identify differentially expressed genes (DEGs) between CAD samples and healthy controls. The WGCNA package was conducted to recognize CAD-related gene modules and hub genes, followed by recursive feature elimination analysis to select the optimal features genes (OFGs). The genetic classification models were established using support vector machine (SVM), random forest (RF) and logistic regression (LR), respectively. Further validation and receiver operating characteristic (ROC) curve analysis were conducted to evaluate the classification performance. RESULTS: In total, 374 DEGs, eight gene modules, 33 hub genes and 12 OFGs (HTR4, KISS1, CA12, CAMK2B, KLK2, DDC, CNGB1, DERL1, BCL6, LILRA2, HCK, MTF2) were identified. ROC curve analysis showed that the accuracy of SVM, RF and LR were 75.58%, 63.57% and 63.95% in validation; with area under the curve of 0.813 (95% confidence interval, 95% CI 0.761-0.866, P < 0.0001), 0.727 (95% CI 0.665-0.788, P < 0.0001) and 0.783 (95% CI 0.725-0.841, P < 0.0001), respectively. CONCLUSIONS: In conclusion, this study found 12 gene signatures involved in the pathogenic mechanism of CAD. Among the CAD classifiers constructed by three machine learning methods, the SVM model has the best performance.

Identification of biomarkers associated with metabolic cardiovascular disease using mRNA-SNP-miRNA regulatory network analysis.

BACKGROUND: CVD is the leading cause of death in T2DM patients. However, few biomarkers have been identified to detect and diagnose CVD in the early stage of T2DM. The aim of our study was to identify the important mRNAs, micro (mi)RNAs and SNPs (single nucleotide polymorphisms) that are associated with metabolic cardiovascular disease. MATERIALS AND METHODS: Expression profiles and GWAS data were obtained from Gene Expression Omnibus (GEO) database. MiRNA-sequencing was conducted by Illumina HiSeq 2000 platform in T2DM patients and T2DM with CVD patients. EQTL analysis and gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted. MRNA-miRNA co-expression network and mRNA-SNP-miRNA interaction network were established and visualized by Cytoscape 3.7.2. RESULTS: In our study, we identified 56 genes and 16 miRNAs that were significantly differentially expressed. KEGG analyses results indicated that B cell receptor signaling pathway and hematopoietic cell lineage were included in the biological functions of differentially expressed genes. MRNA-miRNA co-expression network and mRNA-SNP-miRNA interaction network illustrated that let-7i-5p, RASGRP3, KRT1 and CEP41 may be potential biomarkers for the early detection and diagnosis of CVD in T2DM patients. CONCLUSION: Our results suggested that downregulated let-7i-5p, and upregulated RASGRP3, KRT1 and CEP41 may play crucial roles in molecular mechanisms underlying the initiation and development of CVD in T2DM patients.

Association of long-term exposure to ambient particulate pollution with stage 1 hypertension defined by the 2017 ACC/AHA Hypertension Guideline and cardiovascular disease: The CHCN-BTH cohort study.

BACKGROUND: Evidence regarding the effects of ambient air pollution on new stage 1 hypertension defined by the 2017 ACC/AHA Hypertension Guideline remains sparse. OBJECTIVES: To investigate the association of long-term exposure to ambient PM2.5 with stage 1 hypertension and to explore the mediating and modifying effects of PM2.5 on cardiovascular disease (CVD). METHODS: A total of 32,135 participants aged 18-80 years were recruited in 2017. The three-year (2014-2016) average PM2.5 concentrations were assessed by a spatial statistical model. Blood pressure (BP) was divided into four categories according to the 2017 ACC/AHA Hypertension Guideline: normal BP (SBP<120 mmHg and DBP<80 mmHg), elevated BP (SBP 120-129 mmHg and DBP<80 mmHg), stage 1 hypertension (SBP 130-139 mmHg or DBP 80-89 mmHg), and stage 2 hypertension (SBP≥140 mmHg or DBP≥90 mmHg or taking antihypertensive medications). The associations of PM2.5 with BP categories were estimated by two-level generalized linear mixed models. Analyses stratified by age, mediation and interaction analyses of PM2.5 and stage 1 hypertension with CVD were performed. RESULTS: We detected a positive significant association between long-term exposure to PM2.5 and stage 1 hypertension. Compared to normal BP, the OR was 1.05 (95% CI: 1.02, 1.08) per 10 µg/m3 increase in PM2.5. The association was stronger than that of elevated BP but weaker than that of stage 2 hypertension. Stage 1 hypertension only partially mediated the association between PM2.5 and CVD, and the mediation proportions ranged from 1.55% to 11.00%. However, it modified the association between PM2.5 and CVD, which was greater in participants with stage 1 hypertension (OR: 1.66; 95% CI: 1.43, 1.93) than in participants with normal BP (OR: 1.32; 95% CI: 1.11, 1.57), with Pinteraction<0.001. In the analysis stratified by age, the above associations were age-specific, and significant associations were only observed in the young and middle-aged (<60 years) groups. CONCLUSIONS: Long-term exposure to ambient PM2.5 was significantly associated with stage 1 hypertension. This earlier stage of hypertension may be a trigger BP range for adverse effects of air pollution in the development of hypertension and CVD, especially in young and middle-aged individuals.

Association study of fasting blood glucose and salt sensitivity of blood pressure in community population: The EpiSS study.

BACKGROUND AND AIMS: To evaluate the association between fasting blood glucose (FBG) and salt sensitivity of blood pressure (SSBP). METHODS AND RESULTS: This study is based on the baseline survey of systemic epidemiology of salt sensitivity study. Subjects were classified into salt sensitive (SS) and salt resistant groups according to blood pressure (BP) changes during the modified Sullivan's acute oral saline load and diuresis shrinkage test. Multivariate logistic and linear regression were used to evaluate associations between FBG with SS or BP changes. A total of 2051 participants were included in the analyses with 581 (28.33%) for SS. Multiple analysis showed that for every interquartile range increase in FBG, the OR (95%CI) for SS was 1.140 (1.069, 1.215), ß (95%CI) for mean arterial pressure change (ΔMAP1), systolic and diastolic BP changes during saline load were 0.421 (0.221, 0.622), 0.589 (0.263, 0.914) and 0.340 (0.149, 0.531), respectively. Compared to the lowest FBG quartile (Q1), the OR (95%CI) for SS in Q3 and Q4 were 1.342 (1.014, 1.776) and 1.577 (1.194, 2.084), respectively. Compared to subjects with normal FBG, the ß (95%CI) for ΔMAP1 was 0.973 (0.055, 1.891) in subjects with impaired FBG, and was 1.449 (0.602, 2.296) in patients with diabetes mellitus. Stratified analyses showed significant and stronger associations between FBG with SSBP in youngers, females, hypertensives, non-diabetics, non-current smokers and non-current drinkers. CONCLUSION: Our findings suggest FBG is an independent, dose-dependent associated factor for SSBP, and prevention of SS focusing on controlling FBG elevation in the early stage is important.

Association of Lipoprotein (a) variants with risk of cardiovascular disease: a Mendelian randomization study.

BACKGROUND: There is a well-documented empirical relationship between lipoprotein (a) [Lp(a)] and cardiovascular disease (CVD); however, causal evidence, especially from the Chinese population, is lacking. Therefore, this study aims to estimate the causal association between variants in genes affecting Lp(a) concentrations and CVD in people of Han Chinese ethnicity. METHODS: Two-sample Mendelian randomization analysis was used to assess the causal effect of Lp(a) concentrations on the risk of CVD. Summary statistics for Lp(a) variants were obtained from 1256 individuals in the Cohort Study on Chronic Disease of Communities Natural Population in Beijing, Tianjin and Hebei. Data on associations between single-nucleotide polymorphisms (SNPs) and CVD were obtained from recently published genome-wide association studies. RESULTS: Thirteen SNPs associated with Lp(a) levels in the Han Chinese population were used as instrumental variables. Genetically elevated Lp(a) was inversely associated with the risk of atrial fibrillation [odds ratio (OR), 0.94; 95% confidence interval (95%CI), 0.901-0.987; P = 0.012)], the risk of arrhythmia (OR, 0.96; 95%CI, 0.941-0.990; P = 0.005), the left ventricular mass index (OR, 0.97; 95%CI, 0.949-1.000; P = 0.048), and the left ventricular internal dimension in diastole (OR, 0.97; 95%CI, 0.950-0.997; P = 0.028) according to the inverse-variance weighted method. No significant association was observed for congestive heart failure (OR, 0.99; 95% CI, 0.950-1.038; P = 0.766), ischemic stroke (OR, 1.01; 95%CI, 0.981-1.046; P = 0.422), and left ventricular internal dimension in systole (OR, 0.98; 95%CI, 0.960-1.009; P = 0.214). CONCLUSIONS: This study provided evidence that genetically elevated Lp(a) was inversely associated with atrial fibrillation, arrhythmia, the left ventricular mass index and the left ventricular internal dimension in diastole, but not with congestive heart failure, ischemic stroke, and the left ventricular internal dimension in systole in the Han Chinese population. Further research is needed to identify the mechanism underlying these results and determine whether genetically elevated Lp(a) increases the risk of coronary heart disease or other CVD subtypes.

Construction of a ceRNA coregulatory network and screening of hub biomarkers for salt-sensitive hypertension.

Salt-sensitive hypertension (SSH) is an independent risk factor for cardiovascular disease. The regulation of long non-coding RNAs, mRNAs and competing endogenous RNAs (ceRNAs) in the pathogenesis of SSH is uncertain. An RNA microarray was performed to discover SSH-associated differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs), and 296 DElncRNAs and 44 DEmRNAs were identified, and 247 DElncRNAs and 44 DEmRNAs among these RNAs were included in the coexpression network. The coregulatory network included 23 ceRNA loops, and six hub RNAs (lnc-ILK-8:1, lnc-OTX1-7:1, lnc-RCAN1-6:1, GIMAP8, SUV420H1 and PIGV) were identified for further population validation. The ceRNA correlations among lnc-OTX1-7:1, hsa-miR-361-5p and GIMAP8 were confirmed in SSH and SRH patients. A larger-sample validation confirmed that GIMAP8, SUV420H1 and PIGV were differentially expressed between the SSH and SRH groups. In addition, SUV420H1 was included in the SSH screening model, and the area under the curve of the model was 0.720 (95% CI: 0.624-0.816). Our study explored the transcriptome profiles of SSH and constructed a ceRNA network to help elucidate the mechanism of SSH. In addition, SUV420H1 was identified as a hub element that participates in SSH transcriptional regulation and as a potential biomarker for the early diagnosis of SSH.

Associations between ambient air pollution and mortality from all causes, pneumonia, and congenital heart diseases among children aged under 5 years in Beijing, China: A population-based time series study.

BACKGROUND: Previous studies have mainly focused on the associations between particulate matters and infant mortality. However, evidence regarding the associations between gaseous pollutants and mortality among children aged <5 years remains sparse. OBJECTIVES: The aim of this study was to investigate the associations between ambient air pollution and death among children aged <5 years in Beijing, China, and explore the impact of age, gender and specific causes of death on these associations. METHODS: Concentrations of ambient air pollution and the number of deaths among children aged <5 years in Beijing from January 2014 to September 2016 were extracted from authoritative electronic databases. The associations were estimated for a single-month lag from the current month up to the previous 5 months (lag0-lag5) and moving averages of the current and previous months (lag01-lag05) using generalized additive Poisson regression (adjusted for time trends, season, meteorological variables and holidays). Subgroup analyses related to age, gender and specific diseases were performed. Two-pollutant models were used to evaluate the possible role of single pollutants. RESULTS: Sulfur dioxide (SO2), nitrogen dioxide (NO2) and carbon monoxide (CO) demonstrated the strongest associations with death among children aged <5 years at lag0, and the estimates decreased or even turned negative with the increasing lag periods. For an interquartile range increase in SO2, NO2 and CO at lag0, the odds ratios (OR) were 1.332 (95% CI 1.152-1.539), 1.383 (95% CI 1.113-1.718) and 1.273 (95% CI 1.028-1.575). However, CO lost significance after adjusting for SO2 and NO2, and PM2.5 gained significance (OR 1.548, 95% CI 1.061-2.258) after adjusting for PM10. The ORs for SO2 and NO2 remained the most stable across all two-pollutant models. The associations for children aged 1-5 years were stronger than those reported for infants at lag0 but lower at the other lag months. The pollutant associations were stronger for congenital heart disease-related death than overall and pneumonia-related death. We did not find significant differences in terms of gender. CONCLUSION: Exposure to air pollution may increase the incidence of death among children aged <5 years. SO2 and NO2 may be the most stable pollutants reflecting associations between air pollution and death, deserving further attention. Children with congenital heart diseases are more susceptible to air pollution. Therefore, it is urgent to implement the clean air targets established by WHO and reduce the exposure of children to air pollution.

Increased cTnI Predicts Early Death in Patients with Severe Fever with Thrombocytopenia: A Multicenter Study in North China.

Background: Myocardial injury is common in severe fever with thrombocytopenia syndrome (SFTS) patients. Currently, research on the prognostic value of cardiac troponin I (cTnI) for predicting the mortality of SFTS patients, especially death within 7 days is limited. Methods: Between May 2011 and October 2022, clinical and laboratory data on admission of consecutive SFTS cases were collected from six medical centres in China. The clinical endpoint was in-hospital all-cause death within seven days. Risk factors of myocardial injury and death were analysed using multivariable regression models. Prognostic models were established using Cox regression and performance of indicators was evaluated in terms of calibration, discrimination. Results: A total of 1379 laboratory-confirmed patients were enrolled, in which 686 subjects were included for analysis. The median age was 66 years, with 48.1% of male. Eighty-seven patients died within seven days and 396 patients diagnosed with myocardial injury during hospitalization. Non-survivors had significant higher levels of cardiac indices than survivors, including cTnI, aspartic transaminase (AST) and lactate dehydrogenase (LDH). Elevated levels of cTnI (HR = 1.058, 95% CI:1.032-1.085), AST (HR = 1.191, 95% CI:1.150-1.234) and LDH (HR = 1.019, 95% CI:1.009-1.029) predicted risk of early in-hospital mortality. cTnI model performed best, with area under curve of 0.850 (0.774-0.926) and concordance index of 0.842, respectively. Statistical differences were found between high and low levels of cTnI for mortality (P<0.001) using 0.35 ng/mL as the optimal cut-off. Conclusion: The risk of early in-hospital death can be predicted by cTnI. Clinical doctors should remind vigilant concerning the elevation of cardiac enzyme as soon as possible.

Activated partial thromboplastin time predicts mortality in patients with severe fever with thrombocytopenia syndrome: A multicenter study in north China.

Background: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease with high lethality. This study aimed to determine whether prolonged activated partial thromboplastin time (APTT) predicted SFTS mortality. Methods: SFTS patients were enrolled from 6 hospitals in the north China. Subjects were divided into training cohort and 5 externally validation cohorts. The least absolute shrinkage and selection operator Cox regression model was performed to screen potential prognostic factors. Risk factors were analyzed using multivariable regression models. Prognostic models were established by Cox regression and random survival forest (RSF) methods, and evaluated regarding discrimination, validity and clinical benefit. Time-dependent receiver operating characteristic (ROC) curve was used to evaluate the predictive effectiveness of variables. Results: 1332 SFTS cases were included, in which 211 patients died. Six potential prognostic factors were screened, and pulse, breath, APTT and aspartic transaminase (AST) were independently associated with mortality in both training cohort (Yantai, N = 791) and external validation cohort (N = 541). APTT was steadily correlated with the fatality (HR: 1.039-1.144; all P < 0.01) in each five sub-validation cohorts (Dandong, Dalian, Tai'an, Qingdao and Beijing). RSF model with variables of APTT, AST, pulse and breath had considerable prognostic effectiveness, which APTT showed the highest prognostic ability with the area under the curve of 0.848 and 0.787 for 7-day and 14-day survival, respectively. Survival differences were found between high and low levels of APTT for mortality using 50s as the optimal cut-off. Conclusions: SFTS patients have prolonged APTT, which is an independent risk factor for fatality. APTT≥50s was recommended as a biomarker to remind physicians to monitor and treat patients more aggressively to improve clinical prognosis.

Association of Serum Metabolites and Salt Sensitivity of Blood Pressure in Chinese Population: The EpiSS Study.

BACKGROUND: To identify novel metabolites associated with salt sensitivity of blood pressure (SSBP) in Chinese Han population. METHODS: A case-control study was conducted with 25 salt sensitive (SS) and 26 salt resistant (SR) participants, which was selected from the Systems Epidemiology Study on Salt Sensitivity of Blood Pressure (EpiSS) study. The modified Sullivan's acute oral saline load and diuresis shrinkage test (MSAOSL-DST) was conducted to identify SS. Untargeted, ultra-high performance liquid chromatograph-high resolution mass spectrometer (UPLC-HRMS) was conducted and orthogonal partial least squares-discriminate analysis (OPLS-DA) and multivariable logistic regression model were used to screen the metabolites related to SS, mixed linear regressions models were used to examined the association of SSBP with metabolites during saline load period and diuresis shrinkage period. Receiver operating characteristic (ROC) curve analysis was performed. The area under the curve's (AUC) sensitivity and specificity were calculated to identified metabolites biomarkers for SS. RESULTS: There were 39 differentially expressed metabolites (DE-metabolites) between SS and SR. Thirty-five and four of DE-metabolites were inversely or positively associated with SS, respectively. Four biochemical pathways demonstrated significant enrichment for identified metabolites. In single-metabolite analyses, L-Glutamine displayed the best diagnostic performance (AUC = 0.88, 95% CI: 0.78-0.97). In multi-metabolites analyses, L-Glutamine + Cholesterol ester 22:5n6 combination showed the best diagnostic performance (AUC = 0.96, 95% CI: 0.91-1.00). Adjusted for traditional risk factors, L-Glutamine and Cholesterol ester 22:5n6 explained an additional 38.3% of SS susceptibility. CONCLUSIONS: This study provide potential evidence for clarifying the mechanism of SS and provide novel biological insights into salt sensitive hypertension.

Associations between depressive, anxiety, stress symptoms and elevated blood pressure: Findings from the CHCN-BTH cohort study and a two-sample Mendelian randomization analysis.

BACKGROUND: We aimed to determine whether depressive, anxiety, stress symptoms were associated with the risk of elevated blood pressure by performing longitudinal cohort and Mendelian Randomization (MR) analyses. METHODS: We used data from the Cohort Study on Chronic Disease of Community Natural Population in the Beijing-Tianjin-Hebei region (CHCN-BTH) from 2017 to 2021. The Depression-Anxiety-Stress Scale was used to evaluate the depressive, anxiety, stress symptoms. The longitudinal associations between depressive, anxiety, stress symptoms and elevated blood pressure were estimated using Cox proportional regression models. Two-sample MR analysis was performed using the Inverse-variance weighted (IVW), weighted median, and MR-Egger to explore the causal relationships between depressive, anxiety, stress symptoms and elevated blood pressure. RESULTS: In total, 5624 participants were included. The risk of SBP ≥ 140 mmHg or DBP ≥ 90 mmHg was significantly higher in participants with baseline anxiety symptoms (HR = 1.48, 95 % CI: 1.03 to 2.12, P = 0.033; HR = 1.56, 95 % CI: 1.05 to 2.32, P = 0.028), especially in men and individuals with higher educational levels, independent of baseline depression and anxiety at the two-year follow-up. The two-sample MR analysis showed positive associations between depressive, anxiety, stress symptoms and elevated blood pressure. LIMITATION: Self-reported mental health symptoms, relatively shorter follow-up duration and the European-derived genome-wide association study data for MR analysis. CONCLUSIONS: Anxiety symptoms were positively associated with elevated blood pressures in the longitudinal analysis independent of depression, stress, and other confounders. The results were verified in MR analysis, providing evidence for causal effects of anxiety symptoms on the risk of elevated blood pressure.

The association between oral and gut microbiota in male patients with alcohol dependence.

Introduction: The relationship between oral and gut microbiota in alcohol dependence (AD) is not well understood, particularly the effects of oral microbiota on the intestinal microbiota. The current study aimed to explore the association between oral and gut microbiota in AD to clarify whether oral microbiota could ectopically colonize into the gut. Methods: 16S rRNA sequence libraries were used to compare oral and gut microbial profiles in persons with AD and healthy controls (HC). Source Tracker and NetShift were used to identify bacteria responsible for ectopic colonization and indicate the driver function of ectopic colonization bacteria. Results: The α-diversity of oral microbiota and intestinal microbiota was significantly decreased in persons with AD (all p < 0.05). Principal coordinate analysis indicated greater similarity between oral and gut microbiota in persons with AD than that in HC, and oral-gut overlaps in microbiota were found for 9 genera in persons with AD relative to only 3 genera in HC. The contribution ratio of oral microbiota to intestinal microbiota composition in AD is 5.26% based on Source Tracker，and the AD with ectopic colonization showed the daily maximum standard drinks, red blood cell counts, hemoglobin content, and PACS scores decreasing (all p < 0.05). Discussion: Results highlight the connection between oral-gut microbiota in AD and suggest novel potential mechanistic possibilities.

Integrated analysis of the lncRNA-associated competing endogenous RNA network in salt sensitivity of blood pressure.

Accumulating evidence showed that competing endogenous RNA (ceRNA) mechanism plays a pivotal role in salt sensitivity of blood pressure (SSBP). We constructed a ceRNA network based on SSBP-related differently expressed lncRNAs (2), mRNAs (73) and miRNAs (18). Bioinformatic analyses were utilized to analyze network and found network genes participate in biological pathways related to SSBP pathogenesis such as regulation of nitric oxide biosynthetic process (GO:0045,428) and cellular response to cytokine stimulus (GO:0071,345). Fourteen candidate ceRNA pathways were selected from network to perform qRT-PCR validation and found nine RNAs (KCNQ1OT1, SLC8A1-AS1, IL1B, BCL2L11, KCNJ15, CX3CR1, KLF2, hsa-miR-362-5p and hsa-miR-423-5p) differently expressed between salt-sensitive (SS) and salt-resistant (SR) groups (P < 0.05). Four ceRNA pathways were further validated by luciferase reporter assay and found KCNQ1OT1→hsa-miR-362-5p/hsa-miR-423-5p→IL1B pathways may influence the pathogenic mechanism of SS. Our findings suggested the ceRNA pathway and network may affect SS occurrence mainly through endothelial dysfunction and inflammatory activation.

Disrupted diurnal oscillations of the gut microbiota in patients with alcohol dependence.

Background: Patients with alcohol dependence (AD) can exhibit gut dysbacteria. Dysbacteria may co-occur with disruptions of circadian rhythmicity of the gut flora, which can aggravate AD. Herein, this study aimed to investigate diurnal oscillations of the gut microbiota in AD patients. Methods: Thirty-two patients with AD, based on the Diagnostic and Statistical Manual of Mental Disorders, 4th edition, and 20 healthy subjects were enrolled in this study. Demographic and clinical data were collected by self-report questionnaires. Fecal samples at 7:00 AM, 11:00 AM, 3:00 PM, and 7:00 PM were collected from each subject. 16S rDNA sequencing was conducted. Wilcoxon and Kruskal-Wallis tests were performed to characterize alterations and oscillations of the gut microbiota. Results: We found that ß-diversity of the gut microbiota in AD patients oscillated diurnally compared with healthy subjects (p = 0.01). Additionally, 0.66% of operational taxonomic units oscillated diurnally in AD patients versus 1.68% in healthy subjects. At different taxonomic levels, bacterial abundance oscillated diurnally in both groups, such as Pseudomonas and Prevotella pallens (all p < 0.05). ß-diversity of the gut microbiota in AD patients with high daily alcohol consumption, high-level cravings, short AD durations, and mild withdrawal symptoms oscillated diurnally compared with other AD patients (all p < 0.05). Conclusion: The gut microbiota in AD patients exhibits disruptions of diurnal oscillation, which may provide novel insights into mechanisms of AD and the development of therapeutic strategies.

Polymorphisms and Gene-Gene Interaction in AGER/IL6 Pathway Might Be Associated with Diabetic Ischemic Heart Disease.

Background: Although the genetic susceptibility to diabetes and ischemic heart disease (IHD) has been well demonstrated, studies aimed at exploring gene variations associated with diabetic IHD are still limited; Methods: Our study included 204 IHD cases who had been diagnosed with diabetes before the diagnosis of IHD and 882 healthy controls. Logistic regression was used to find the association of candidate SNPs and polygenic risk score (PRS) with diabetic IHD. The diagnostic accuracy was represented with AUC. Generalized multifactor dimensionality reduction (GMDR) was used to illustrate gene-gene interactions; Results: For IL6R rs4845625, the CT and TT genotypes were associated with a lower risk of diabetic IHD than the CC genotype (OR = 0.619, p = 0.033; OR = 0.542, p = 0.025, respectively). Haplotypes in the AGER gene (rs184003-rs1035798-rs2070600-rs1800624) and IL6R gene (rs7529229-rs4845625-rs4129267-rs7514452-rs4072391) were both significantly associated with diabetic IHD. PRS was associated with the disease (OR = 1.100, p = 0.005) after adjusting for covariates, and the AUC were 0.763 (p < 0.001). The GMDR analysis suggested that rs184003 and rs4845625 were the best interaction model after permutation testing (p = 0.001) with a cross-validation consistency of 10/10; Conclusions: SNPs and haplotypes in the AGER and IL6R genes and the interaction of rs184003 and rs4845625 were significantly associated with diabetic IHD.

SNPs in lncRNA KCNQ1OT1 Modulate Its Expression and Confer Susceptibility to Salt Sensitivity of Blood Pressure in a Chinese Han Population.

Long noncoding RNA (lncRNA) plays an important role in cardiovascular diseases, but the involvement of lncRNA in salt sensitivity of blood pressure (SSBP) is not well-known. We aimed to explore the association of sixteen single-nucleotide polymorphisms (SNPs) in five lncRNA genes (KCNQOT1, lnc-AGAP1-8:1, lnc-IGSF3-1:1, etc.) with their expression and susceptibility to SSBP. A two-stage association study was conducted among 2057 individuals. Quantified expression of the lncRNA was detected using real-time PCR. Genotyping was accomplished using the MassARRAY System. The expression quantitative tra2it loci test and the generalized linear model were utilized to explore the function of SNPs. One-sample Mendelian randomization was used to study the causal relationship between KCNQOT1 and SSBP. Significant effects were observed in KCNQ1OT1 expressions on the SSBP phenotype (p < 0.05). Rs10832417 and rs3782064 in KCNQ1OT1 may influence the secondary structure, miRNA binding, and expression of KCNQ1OT1. Rs10832417 and rs3782064 in KCNQ1OT1 were identified to be associated with one SSBP phenotype after multiple testing corrections and may be mediated by KCNQ1OT1. One-sample Mendelian randomization analyses showed a causal association between KCNQ1OT1 and SSBP. Our findings suggest that rs10832417 and rs3782064 might be associated with a lower risk of SSBP through influencing the KCNQ1OT1 secondary structure and miRNA binding, resulting in changes in KCNQ1OT1 expression.

Higher Potassium Intake and Lower Sodium Intake May Help in Reducing CVD Risk by Lowering Salt Sensitivity of Blood Pressure in the Han Chinese Population.

Sodium (Na) reduction with a parallel supplemental potassium (K) intake can prevent cardiovascular diseases (CVDs). The relationship of the urinary Na/K ratio and salt sensitivity of blood pressure (SSBP) with CVDs is not clearly explained. We assumed that the SSBP mediates the relationship between the Na/K ratio and CVDs. In total, 2055 subjects who had 24 h urine collected and SSBP determined were included in this study. CVD risk was estimated using the China-PAR equation. MediationMultivariate logistic regression was used to explore the associations between the Na/K ratio or SSBP with CVD risk. Mediation analysis using a logistic regression model was performed. Both the urinary Na/K ratio and SSBP were related to the estimated CVD risk (p < 0.05). The mediation analysis found that SSBP mediated approximately 12% of the association between Na/K ratio and CVD risk. Our findings indicate that higher K intake and lower Na intake may help in preventing CVD risk by reducing SSBP risk in individuals with normotension or stage-one hypertension.