Prognostic Value of a Multi-mRNA Signature for 1-Year All-Cause Death in Hospitalized Patients With Heart Failure With a Preserved Ejection Fraction.

BACKGROUND: Heart failure with preserved ejection fraction is a major global public health problem, while effective risk stratification tools are still lacking. We sought to construct a multi-mRNA signature to predict 1-year all-cause death. METHODS: We selected 30 patients with heart failure with preserved ejection fraction who died during 1-year follow-up and 30 who survived in the discovery set. One hundred seventy-one and 120 patients with heart failure with preserved ejection fraction were randomly selected as a test set and a validation set, respectively. We performed mRNA microarrays in all patients. RESULTS: We constructed a 5-mRNA signature for predicting 1-year all-cause death. The scores of the 5-mRNA signature were significantly associated with the 1-year risk of all-cause death in both the test set (hazard ratio, 2.72 [95% CI, 1.98-3.74]; P<0.001) and the validation set (hazard ratio, 3.95 [95% CI, 2.40-6.48]; P<0.001). Compared with a reference model, which included sex, ASCEND-HF (Acute Study of Clinical Effectiveness of Nesiritide in Decompensated Heart Failure) score, history of HF and NT-proBNP (N-terminal pro-B-type natriuretic peptide), the 5-mRNA signature had a better discrimination capability, with an increased area under the curve from 0.696 to 0.813 in the test set and from 0.712 to 0.848 in the validation set. A composite model integrating the 5-mRNA risk score and variables in the reference model demonstrated an excellent discrimination capability, with an area under the curve of 0.861 (95% CI, 0.784-0.939) in the test set and an area under the curve of 0.859 (95% CI, 0.755-0.963) in the validation set. The net reclassification improvement and integrated discrimination improvement indicated that the composite model significantly improved patient classification compared with the reference model in both sets (P<0.001). CONCLUSIONS: The 5-mRNA signature is a promising predictive tool for 1-year all-cause death and shows improved prognostic power over the established risk scores and NT-proBNP in patients with heart failure with preserved ejection fraction.

Association of high-density lipoprotein cholesterol with all-cause and cause-specific mortality in a Chinese population of 3.3 million adults: a prospective cohort study.

Background: High-density lipoprotein cholesterol (HDL-C) has been inversely associated with cardiovascular disease (CVD) risk, but recent evidence suggests that extremely high levels of HDL-C are paradoxically related to increased CVD incidence and mortality. This study aimed to comprehensively examine the associations of HDL-C with all-cause and cause-specific mortality in a Chinese population. Methods: The China Health Evaluation And risk Reduction through nationwide Teamwork (ChinaHEART) project included 3,397,547 participants aged 35-75 years with a median follow-up of 3.9 years. Baseline HDL-C levels were measured, and mortality data was ascertained from the National Mortality Surveillance System and Vital Registration of Chinese Center for Disease Control and Prevention. Findings: This study found U-shaped associations of HDL-C with all-cause, cardiovascular and cancer mortality. When compared with the groups with the lowest risk, the adjusted hazard ratios (95% CIs) for HDL-C <30 mg/dL was 1.23 (1.17-1.29), 1.33 (1.23-1.45) and 1.18 (1.09-1.28) for all-cause, CVD and cancer mortality, respectively. For HDL-C >90 mg/dL, the corresponding HR (95% CIs) was 1.10 (1.05-1.15), 1.09 (1.01-1.18) and 1.11 (1.03-1.19). Similar U-shaped patterns were also found in associations of HDL-C with ischemic heart disease, ischemic stroke, and liver cancer. About 3.25% of all-cause mortality could be attributed to abnormal levels of HDL-C. The major contributor to mortality was ischemic heart disease (16.06 deaths per 100,000 persons, 95% UI: 10.30-22.67) for HDL-C <40 mg/dL and esophageal cancer (2.29 deaths per 100,000 persons, 95% UI: 0.57-4.77) for HDL-C >70 mg/dL. Interpretation: Both low and high HDL-C were associated with increased mortality risk. We recommended 50-79 mg/dL as the optimal range of HDL-C among Chinese adults. Individuals with dyslipidemia might benefit from proper management of both low and high HDL-C. Funding: The CAMS Innovation Fund for Medical Science (2021-1-I2M-011), the National High Level Hospital Clinical Research Funding (2022-GSP-GG-4), the Ministry of Finance of China and National Health Commission of China, and the 111 Project from the Ministry of Education of China (B16005), the Program for Guangdong Introducing Innovative and Enterpreneurial Teams (2019ZT08Y481), Sanming Project of Medicine in Shenzhen (SZSM201811096), the Young Talent Program of the Academician Fund, Fuwai Hospital Chinese Academy of Medical Sciences, Shenzhen (YS-2022-006) and Guangdong Basic and Applied Basic Research Foundation (2023A1515010076 & 2021A1515220173).

Associations between Chinese visceral adiposity index and risks of all-cause and cause-specific mortality: A population-based cohort study.

AIM: To determine the associations between the Chinese visceral adiposity index (CVAI) and the risks of all-cause and cause-specific mortality. MATERIALS AND METHODS: A total of 3 916 214 Chinese adults were enrolled in a nationwide population cohort covering all 31 provinces of mainland China. The CVAI was calculated based on age, body mass index, waist circumference, and triglyceride and high-density lipoprotein cholesterol concentrations. We used a Cox proportional hazards regression model to determine the hazard ratios and 95% confidence intervals (CIs) for risk of mortality associated with different CVAI levels. RESULTS: The median follow-up duration was 3.8 years. A total of 86 158 deaths (34 867 cardiovascular disease [CVD] deaths, 29 884 cancer deaths, and 21 407 deaths due to other causes) were identified. In general, after adjusting for potential confounding factors, a U-shaped relationship between CVAI and all-cause mortality was observed by restricted cubic spline (RCS). Compared with participants in CVAI quartile 1, those in CVAI quartile 4 had a 23.0% (95% CI 20.0%-25.0%) lower risk of cancer death, but a 23.0% (95% CI 19.0-27.0) higher risk of CVD death. In subgroup analysis, a J-shaped and inverted U-shaped relationship for all-cause mortality and cancer mortality was observed in the group aged < 60 years. CONCLUSIONS: The CVAI, an accessible indicator reflecting visceral obesity among Chinese adults, has predictive value for all-cause, CVD, and cancer mortality risks. Moreover, the CVAI carries significance in the field of health economics and secondary prevention. In the future, it could be used for early screening purposes.

Associations of remnant cholesterol with cardiovascular and cancer mortality in a nationwide cohort.

The health significance of triglyceride-rich lipoproteins, also known as remnant cholesterol, has been increasingly recognized. However, evidence of their associations with cause-specific mortality in the general population was previously insufficient. To explore these associations and their heterogeneities across subgroups, a prospective cohort study was conducted including 3,403,414 community-based participants from ChinaHEART, an ongoing government-funded public health program throughout China, from November 2014 through December 2022. The study assessed mortality risk of all-cause mortality, cardiovascular disease (CVD) mortality (including mortality from ischemic heart diseases (IHD), ischemic stroke (IS), and hemorrhagic stroke (HS), separately), and cancer mortality (including lung cancer, stomach cancer, and liver cancer, separately). During the 4-year follow-up, 23,646 individuals died from CVD (including 8807 from IHD, 3067 from IS, and 5190 from HS), and 20,318 from cancer (including 6208 from lung cancer, 3013 from liver cancer, and 2174 from stomach cancer). Compared with individuals with remnant cholesterol <17.9 mg/dL, multivariable-adjusted mortality hazard ratios (HRs) for individuals with remnant cholesterol ≥27.7 mg/dL were 1.03 (1.00-1.05) for all-cause mortality, 1.17 (1.12-1.21) for CVD (1.19 (1.12-1.27) for IHD mortality, and 1.22 (1.09-1.36) for IS mortality), and 0.90 (0.87-0.94) for all-cancer mortality (0.94 (0.87-1.02) for lung cancer, 0.59 (0.53-0.66) for liver cancer, and 0.73 (0.64-0.83) for stomach cancer). In summary, this study revealed a correlation between increased remnant cholesterol levels and an elevated risk of cardiovascular disease mortality, as well as a reduced risk of mortality for certain types of cancer.

Influence of Socioeconomic Gender Inequality on Sex Disparities in Prevention and Outcome of Cardiovascular Disease: Data From a Nationwide Population Cohort in China.

Background Knowledge gaps remain in how gender-related socioeconomic inequality affects sex disparities in cardiovascular diseases (CVD) prevention and outcome. Methods and Results Based on a nationwide population cohort, we enrolled 3 737 036 residents aged 35 to 75 years (2014-2021). Age-standardized sex differences and the effect of gender-related socioeconomic inequality (Gender Inequality Index) on sex disparities were explored in 9 CVD prevention indicators. Compared with men, women had seemingly better primary prevention (aspirin usage: relative risk [RR], 1.24 [95% CI, 1.18-1.31] and statin usage: RR, 1.48 [95% CI, 1.39-1.57]); however, women's status became insignificant or even worse when adjusted for metabolic factors. In secondary prevention, the sex disparities in usage of aspirin (RR, 0.65 [95% CI, 0.63-0.68]) and statin (RR, 0.63 [95% CI, 0.61-0.66]) were explicitly larger than disparities in usage of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (RR, 0.88 [95% CI, 0.84-0.91]) or ß blockers (RR, 0.67 [95% CI, 0.63-0.71]). Nevertheless, women had better hypertension awareness (RR, 1.09 [95% CI, 1.09-1.10]), similar hypertension control (RR, 1.01 [95% CI, 1.00-1.02]), and lower CVD mortality (hazard ratio, 0.46 [95% CI, 0.45-0.47]). Heterogeneities of sex disparities existed across all subgroups. Significant correlations existed between regional Gender Inequality Index values and sex disparities in usage of angiotensin-converting enzyme inhibitors/angiotensin receptor blockers (Spearman correlation coefficient, r=-0.57, P=0.0013), hypertension control (r=-0.62, P=0.0007), and CVD mortality (r=0.45, P=0.014), which remained significant after adjusting for economic factors. Conclusions Notable sex disparities remain in CVD prevention and outcomes, with large subgroup heterogeneities. Gendered socioeconomic factors could reinforce such disparities. A sex-specific perspective factoring in socioeconomic disadvantages could facilitate more targeted prevention policy making.

Associations of long-term fine particulate matter exposure with all-cause and cause-specific mortality: results from the ChinaHEART project.

Background: The chronic effects of fine particulate matter (PM2.5) at high concentrations remains uncertain. We aimed to examine the relationship of long-term PM2.5 exposure with all-cause and the top three causes of death (cardiovascular disease [CVD], cancer, and respiratory disease), and to analyze their concentration-response functions over a wide range of concentrations. Methods: We enrolled community residents aged 35-75 years from 2014 to 2017 from all 31 provinces of the Chinese Mainland, and followed them up until 2021. We used a long-term estimation dataset for both PM2.5 and O3 concentrations with a high spatiotemporal resolution to assess the individual exposure, and used Cox proportional hazards models to estimate the associations between PM2.5 and mortalities. Findings: We included 1,910,923 participants, whose mean age was 55.6 ± 9.8 years and 59.4% were female. A 10 µg/m3 increment in PM2.5 exposure was associated with increased risk for all-cause death (hazard ratio 1.02 [95% confidence interval 1.012-1.028]), CVD death (1.024 [1.011-1.037]), cancer death (1.037 [1.023-1.052]), and respiratory disease death (1.083 [1.049-1.117]), respectively. Long-term PM2.5 exposure nonlinearly related with all-cause, CVD, and cancer mortalities, while linearly related with respiratory disease mortality. Interpretation: The overall effects of long-term PM2.5 exposure on mortality in the high concentration settings are weaker than previous reports from settings of PM2.5 concentrations < 35 µg/m³. The distinct concentration-response relationships of CVD, cancer, and respiratory disease mortalities could facilitate targeted public health efforts to prevent death caused by air pollution. Funding: The Chinese Academy of Medical Sciences Innovation Fund for Medical Science, the National High Level Hospital Clinical Research Funding, the Ministry of Finance of China and National Health Commission of China, the 111 Project from the Ministry of Education of China.

A novel scatterplot-based method to detect copy number variation (CNV).

Objective: Most methods to detect copy number variation (CNV) have high false positive rates, especially for small CNVs and in real-life samples from clinical studies. In this study, we explored a novel scatterplot-based method to detect CNVs in microarray samples. Methods: Illumina SNP microarray data from 13,254 individuals were analyzed with scatterplots and by PennCNV. The data were analyzed without the prior exclusion of low-quality samples. For CNV scatterplot visualization, the median signal intensity of all SNPs located within a CNV region was plotted against the median signal intensity of the flanking genomic region. Since CNV causes loss or gain of signal intensities, carriers of different CNV alleles pop up in clusters. Moreover, SNPs within a deletion are not heterozygous, whereas heterozygous SNPs within a duplication show typical 1:2 signal distribution between the alleles. Scatterplot-based CNV calls were compared with standard results of PennCNV analysis. All discordant calls as well as a random selection of 100 concordant calls were individually analyzed by visual inspection after noise-reduction. Results: An algorithm for the automated scatterplot visualization of CNVs was developed and used to analyze six known CNV regions. Use of scatterplots and PennCNV yielded 1019 concordant and 108 discordant CNV calls. All concordant calls were evaluated as true CNV-findings. Among the 108 discordant calls, 7 were false positive findings by the scatterplot method, 80 were PennCNV false positives, and 21 were true CNVs detected by the scatterplot method, but missed by PennCNV (i.e., false negative findings). Conclusion: CNV visualization by scatterplots allows for a reliable and rapid detection of CNVs in large studies. This novel method may thus be used both to confirm the results of genome-wide CNV detection software and to identify known CNVs in hitherto untyped samples.

A novel polygenic risk score improves prognostic prediction of heart failure with preserved ejection fraction in the Chinese Han population.

AIMS: Mortality risk assessment in patients with heart failure (HF) with preserved ejection fraction (HFpEF) presents a major challenge. We sought to construct a polygenic risk score (PRS) to accurately predict the mortality risk of HFpEF. METHODS AND RESULTS: We first carried out a microarray analysis of 50 HFpEF patients who died and 50 matched controls who survived during 1-year follow-up for candidate gene selection. The HF-PRS was developed using the independent common (MAF > 0.05) genetic variants that showed significant associations with 1-year all-cause death (P < 0.05) in 1442 HFpEF patients. Internal cross-validation and subgroup analyses were performed to evaluate the discrimination ability of the HF-PRS. In 209 genes identified by microarray analysis, 69 independent variants (r < 0.1) were selected to develop the HF-PRS model. This model yielded the best discrimination capability for 1-year all-cause mortality with an area under the curve (AUC) of 0.852 (95% CI 0.827-0.877), which outperformed the clinical risk score consisting of 10 significant traditional risk factors for 1-year all-cause mortality (AUC 0.696, 95% CI 0.658-0.734, P = 4 × 10-11), with net reclassification improvement (NRI) of 0.741 (95% CI 0.605-0.877; P < 0.001) and integrated discrimination improvement (IDI) of 0.181 (95% CI 0.145-0.218; P < 0.001). Individuals in the medium and the highest tertile of the HF-PRS had nearly a five-fold (HR = 5.3, 95% CI 2.4-11.9; P = 5.6 × 10-5) and 30-fold (HR = 29.8, 95% CI 14.0-63.5; P = 1.4 × 10-18) increased risk of mortality compared to those in the lowest tertile, respectively. The discrimination ability of the HF-PRS was excellent in cross validation and throughout the subgroups regardless of comorbidities, gender, and patients with or without a history of heart failure. CONCLUSION: The HF-PRS comprising 69 genetic variants provided an improvement of prognostic power over the contemporary risk scores and NT-proBNP in HFpEF patients.

We performed integrated analyses of mRNA transcriptional and genetic data to construct an HF-PRS comprised of 69 genetic variants in 1442 HFpEF patients from the China PEACE 5p-HF study. We found that the HF-PRS yielded a satisfactory discrimination capability with an AUC of 0.852, which outperformed the clinical risk score consisting of 10 significant traditional risk factors by 15.6% for 1-year all-cause mortality. The discrimination ability of the HF-PRS was excellent in cross validation and throughout the subgroups regardless of comorbidities, gender and patients with or without history of heart failure.

Deciphering complex antibiotic resistance patterns in Helicobacter pylori through whole genome sequencing and machine learning.

Introduction: Helicobacter pylori (H.pylori, Hp) affects billions of people worldwide. However, the emerging resistance of Hp to antibiotics challenges the effectiveness of current treatments. Investigating the genotype-phenotype connection for Hp using next-generation sequencing could enhance our understanding of this resistance. Methods: In this study, we analyzed 52 Hp strains collected from various hospitals. The susceptibility of these strains to five antibiotics was assessed using the agar dilution assay. Whole-genome sequencing was then performed to screen the antimicrobial resistance (AMR) genotypes of these Hp strains. To model the relationship between drug resistance and genotype, we employed univariate statistical tests, unsupervised machine learning, and supervised machine learning techniques, including the development of support vector machine models. Results: Our models for predicting Amoxicillin resistance demonstrated 66% sensitivity and 100% specificity, while those for Clarithromycin resistance showed 100% sensitivity and 100% specificity. These results outperformed the known resistance sites for Amoxicillin (A1834G) and Clarithromycin (A2147), which had sensitivities of 22.2% and 87%, and specificities of 100% and 96%, respectively. Discussion: Our study demonstrates that predictive modeling using supervised learning algorithms with feature selection can yield diagnostic models with higher predictive power compared to models relying on single single-nucleotide polymorphism (SNP) sites. This approach significantly contributes to enhancing the precision and effectiveness of antibiotic treatment strategies for Hp infections. The application of whole-genome sequencing for Hp presents a promising pathway for advancing personalized medicine in this context.

BNIP3 Upregulation Characterizes Cancer Cell Subpopulation With Increased Fitness and Proliferation.

BNIP3 is a BH3-only protein with both pro-apoptotic and pro-survival roles depending on the cellular context. It remains unclear how BNIP3 RNA level dictates cell fate decisions of cancer cells. Here, we undertook a quantitative analysis of BNIP3 expression and functions in single-cell datasets of various epithelial malignancies. Our results demonstrated that BNIP3 upregulation characterizes cancer cell subpopulations with increased fitness and proliferation. We further validated the upregulation of BNIP3 in liver cancer 3D organoid cultures compared with 2D culture. Taken together, the combination of in silico perturbations using public single-cell datasets and experimental cancer modeling using organoids ushered in a new approach to address cancer heterogeneity.

Obesity Prevalence and Risks Among Chinese Adults: Findings From the China PEACE Million Persons Project, 2014-2018.

BACKGROUND: China has seen a burgeoning epidemic of obesity in recent decades, but few studies reported nationally on obesity across socio-demographic subgroups. We sought to assess the prevalence and socio-demographic associations of obesity nationwide. METHODS: We assessed the prevalence of overall obesity (body mass index ≥28 kg/m2) and abdominal obesity (waist circumference ≥85/90 cm for women/men) among 2.7 million community-dwelling adults aged 35 to 75 years in the China PEACE Million Persons Project from 2014 to 2018 and quantified the socio-demographic associations of obesity using multivariable mixed models. RESULTS: Age-standardized rates of overall and abdominal obesity were 14.4% (95% CI, 14.3%-14.4%) and 32.7% (32.6%-32.8%) in women and 16.0% (15.9%-16.1%) and 36.6% (36.5%-36.8%) in men. Obesity varied considerably across socio-demographic subgroups. Older women were at higher risk for obesity (eg, adjusted relative risk [95% CI] of women aged 65-75 versus 35-44 years: 1.29 [1.27-1.31] for overall obesity, 1.76 [1.74-1.77] for abdominal obesity) while older men were not. Higher education was associated with lower risk in women (eg, adjusted relative risk [95% CI] of those with college or university education versus below primary school: 0.47 [0.46-0.48] for overall obesity, 0.61 [0.60-0.62] for abdominal obesity) but higher risk in men (1.07 [1.05-1.10], 1.17 [1.16-1.19]). CONCLUSIONS: In China, over 1 in 7 individuals meet criteria for overall obesity, and 1 in 3 for abdominal obesity. Wide variation exists across socio-demographic subgroups. The associations of age and education with obesity are significant and differ by sex. Understanding obesity in contemporary China has broad domestic policy implications and provides a valuable international reference.

Genome-wide analysis of DNA methylation and risk of cardiovascular disease in a Chinese population.

BACKGROUND: Systemic studies of association of genome-wide DNA methylated sites with cardiovascular disease (CVD) in prospective cohorts are lacking. Our aim was to identify DNA methylation sites associated with the risk of CVD and further investigate their potential predictive value in CVD development for high-risk subjects. METHODS: We performed an epigenome-wide association study (EWAS) to identify CpGs related to CVD development in a Chinese population.We adopted a nested case-control design based on data from China PEACE Million Persons Project. A total of 83 cases who developed CVD events during follow-up and 83 controls who were matched with cases by age, sex, BMI, ethnicity, medications treatment and behavior risk factors were included in the discovery stage. Genome-wide DNA methylation from whole blood was detected using Infinium Human Methylation EPIC Beadchip (850 K). For significant CpGs [FDR(false discovery rate) < 0.005], we further validated in an independent cohort including 38 cases and 38 controls. RESULTS: In discovery set, we identified 8 significant CpGs (FDR < 0.005) associated with the risk of CVD after adjustment for cell components, demographic and cardiac risk factors and the first 5 principal components. Two of these identified CpGs (cg06901278 and cg09306458 in UACA) were replicated in another independent set (p < 0.05). Enrichment analysis in 787 individual genes from 1036 CpGs in discovery set revealed a significant enrichment for anatomical structure homeostasis as well as regulation of vesicle-mediated transport. Receiver operating characteristic (ROC) analysis showed that the model combined 8 CVD-related CpGs with baseline characteristics showed much better predictive effect for CVD occurrence compared with the model with baseline characteristics only [AUC (area under the curve) = 0.967, 95% CI (0.942 - 0.991); AUC = 0.621, 95% CI (0.536 - 0.706); p = 9.716E-15]. CONCLUSIONS: Our study identified the novel CpGs associated with CVD development and revealed their additional predictive power in the risk of CVD for high-risk subjects.

The copy number variation and stroke (CaNVAS) risk and outcome study.

BACKGROUND AND PURPOSE: The role of copy number variation (CNV) variation in stroke susceptibility and outcome has yet to be explored. The Copy Number Variation and Stroke (CaNVAS) Risk and Outcome study addresses this knowledge gap. METHODS: Over 24,500 well-phenotyped IS cases, including IS subtypes, and over 43,500 controls have been identified, all with readily available genotyping on GWAS and exome arrays, with case measures of stroke outcome. To evaluate CNV-associated stroke risk and stroke outcome it is planned to: 1) perform Risk Discovery using several analytic approaches to identify CNVs that are associated with the risk of IS and its subtypes, across the age-, sex- and ethnicity-spectrums; 2) perform Risk Replication and Extension to determine whether the identified stroke-associated CNVs replicate in other ethnically diverse datasets and use biomarker data (e.g. methylation, proteomic, RNA, miRNA, etc.) to evaluate how the identified CNVs exert their effects on stroke risk, and lastly; 3) perform outcome-based Replication and Extension analyses of recent findings demonstrating an inverse relationship between CNV burden and stroke outcome at 3 months (mRS), and then determine the key CNV drivers responsible for these associations using existing biomarker data. RESULTS: The results of an initial CNV evaluation of 50 samples from each participating dataset are presented demonstrating that the existing GWAS and exome chip data are excellent for the planned CNV analyses. Further, some samples will require additional considerations for analysis, however such samples can readily be identified, as demonstrated by a sample demonstrating clonal mosaicism. CONCLUSION: The CaNVAS study will cost-effectively leverage the numerous advantages of using existing case-control data sets, exploring the relationships between CNV and IS and its subtypes, and outcome at 3 months, in both men and women, in those of African and European-Caucasian descent, this, across the entire adult-age spectrum.

Association between use of Qingfei Paidu Tang and mortality in hospitalized patients with COVID-19: A national retrospective registry study.

BACKGROUND: Qingfei Paidu Tang (QPT), a formula of traditional Chinese medicine, which was suggested to be able to ease symptoms in patients with Coronavirus Disease 2019 (COVID-19), has been recommended by clinical guidelines and widely used to treat COVID-19 in China. However, whether it decreases mortality remains unknown. PURPOSE: We aimed to explore the association between QPT use and in-hospital mortality among patients hospitalized for COVID-19. STUDY DESIGN: A retrospective study based on a real-world database was conducted. METHODS: We identified patients consecutively hospitalized with COVID-19 in 15 hospitals from a national retrospective registry in China, from January through May 2020. Data on patients' characteristics, treatments, and outcomes were extracted from the electronic medical records. The association of QPT use with COVID-19 related mortality was evaluated using Cox proportional hazards models based on propensity score analysis. RESULTS: Of the 8939 patients included, 28.7% received QPT. The COVID-19 related mortality was 1.2% (95% confidence interval [CI] 0.8% to 1.7%) among the patients receiving QPT and 4.8% (95% CI 4.3% to 5.3%) among those not receiving QPT. After adjustment for patient characteristics and concomitant treatments, QPT use was associated with a relative reduction of 50% in-hospital COVID-19 related mortality (hazard ratio, 0.50; 95% CI, 0.37 to 0.66 p < 0.001). This association was consistent across subgroups by sex and age. Meanwhile, the incidences of acute liver injury (8.9% [95% CI, 7.8% to 10.1%] vs. 9.9% [95% CI, 9.2% to 10.7%]; odds ratio, 0.96 [95% CI, 0.81% to 1.14%], p = 0.658) and acute kidney injury (1.6% [95% CI, 1.2% to 2.2%] vs. 3.0% [95% CI, 2.6% to 3.5%]; odds ratio, 0.85 [95% CI, 0.62 to 1.17], p = 0.318) were comparable between patients receiving QPT and those not receiving QPT. The major study limitations included that the study was an observational study based on real-world data rather than a randomized control trial, and the quality of data could be affected by the accuracy and completeness of medical records. CONCLUSIONS: QPT was associated with a substantially lower risk of in-hospital mortality, without extra risk of acute liver injury or acute kidney injury among patients hospitalized with COVID-19.

Patient Stratification of Clear Cell Renal Cell Carcinoma Using the Global Transcription Factor Activity Landscape Derived From RNA-Seq Data.

Clear cell renal cell carcinoma represents the most common type of kidney cancer. Precision medicine approach to ccRCC requires an accurate stratification of patients that can predict prognosis and guide therapeutic decision. Transcription factors are implicated in the initiation and progression of human carcinogenesis. However, no comprehensive analysis of transcription factor activity has been proposed so far to realize patient stratification. Here we propose a novel approach to determine the subtypes of ccRCC patients based on global transcription factor activity landscape. Using the TCGA cohort dataset, we identified different subtypes that have distinct up-regulated biomarkers and altered biological pathways. More important, this subtype information can be used to predict the overall survival of ccRCC patients. Our results suggest that transcription factor activity can be harnessed to perform patient stratification.

Cardiovascular risk factors in China: a nationwide population-based cohort study.

BACKGROUND: It is estimated that 4 million deaths are due to cardiovascular diseases each year in China. Comprehensive understanding about modifiable risk factors and how the risk differs across regions is needed to inform public health policies. We aimed to examine the geographical profile of cardiovascular disease risk across China. METHODS: In this study, we analysed data from a nationwide, population-based screening project, which covered 152 rural counties and 100 urban districts from 31 provinces in China. Between Sept 1, 2015, and Nov 30, 2019, standardised measurements were taken from participants aged 35-75 years who had lived in the region for at least 6 of the preceding 12 months to collect information on blood pressure, blood lipids, blood glucose, physical activity, tobacco smoking, alcohol use, overweight or obesity, and intake frequencies of fruits, vegetables, whole grains, legumes, and red meat. Individuals with a high risk of cardiovascular disease were identified according to medical history and WHO risk prediction charts. FINDINGS: 983 476 individuals were included in this study. Among the participants included, 10·3% (95% CI 10·2-10·3) had a high cardiovascular disease risk after standardising age and sex, with a range of 3·1-24·9% across counties or districts. Among the seven regions in mainland China, the prevalence of high risk of cardiovascular disease was relatively high in northeast China (12·6% [12·4-12·8]) and north China (11·4% [11·3-11·6]), whereas it was low in south China (8·0% [7·8-8·2]). The geographical profiles of the 12 major cardiovascular disease risk factors were different. We found that the regions with high cardiovascular disease risk were facing challenges such as obesity and high blood pressure (north China) and consumption of unhealthy non-staple food (low intake of fruits and vegetables or high intake of red meat; northeast China). By contrast, south China-the region with the lowest cardiovascular disease risk-had the highest prevalence of unhealthy staple food (low intake of whole grains and beans), abnormal metabolism (glucose and lipid), and low physical activity in the country. INTERPRETATION: Risk for cardiovascular diseases varies geographically, and the major contributing risk factors are different across regions in China. Hence, geographically targeted interventions are needed to mitigate the risk and reduce the burden in such a vast country. FUNDING: Ministry of Science and Technology, Ministry of Finance, and National Health Commission of China.

Author Correction: Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma.

The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article. Furthermore, in the original HTML version of this Article, the order of authors within the author list was incorrect. The PRACTICAL consortium was incorrectly listed after Richard S. Houlston and should have been listed after Nora Pashayan. This error has been corrected in the HTML version of the Article; the PDF version was correct at the time of publication.

Genetic Imbalance Is Associated With Functional Outcome After Ischemic Stroke.

Background and Purpose- We sought to explore the effect of genetic imbalance on functional outcome after ischemic stroke (IS). Methods- Copy number variation was identified in high-density single-nucleotide polymorphism microarray data of IS patients from the CADISP (Cervical Artery Dissection and Ischemic Stroke Patients) and SiGN (Stroke Genetics Network)/GISCOME (Genetics of Ischaemic Stroke Functional Outcome) networks. Genetic imbalance, defined as total number of protein-coding genes affected by copy number variations in an individual, was compared between patients with favorable (modified Rankin Scale score of 0-2) and unfavorable (modified Rankin Scale score of ≥3) outcome after 3 months. Subgroup analyses were confined to patients with imbalance affecting ohnologs-a class of dose-sensitive genes, or to those with imbalance not affecting ohnologs. The association of imbalance with outcome was analyzed by logistic regression analysis, adjusted for age, sex, stroke subtype, stroke severity, and ancestry. Results- The study sample comprised 816 CADISP patients (age 44.2±10.3 years) and 2498 SiGN/GISCOME patients (age 67.7±14.2 years). Outcome was unfavorable in 122 CADISP and 889 SiGN/GISCOME patients. Multivariate logistic regression analysis revealed that increased genetic imbalance was associated with less favorable outcome in both samples (CADISP: P=0.0007; odds ratio=0.89; 95% CI, 0.82-0.95 and SiGN/GISCOME: P=0.0036; odds ratio=0.94; 95% CI, 0.91-0.98). The association was independent of age, sex, stroke severity on admission, stroke subtype, and ancestry. On subgroup analysis, imbalance affecting ohnologs was associated with outcome (CADISP: odds ratio=0.88; 95% CI, 0.80-0.95 and SiGN/GISCOME: odds ratio=0.93; 95% CI, 0.89-0.98) whereas imbalance without ohnologs lacked such an association. Conclusions- Increased genetic imbalance was associated with poorer functional outcome after IS in both study populations. Subgroup analysis revealed that this association was driven by presence of ohnologs in the respective copy number variations, suggesting a causal role of the deleterious effects of genetic imbalance.

Tumor­released lncRNA H19 promotes gefitinib resistance via packaging into exosomes in non­small cell lung cancer.

Currently, resistance to tyrosine kinase inhibitors, such as gefitinib, has become one major obstacle for improving the clinical outcome of patients with metastatic and advanced­stage non­small cell lung cancer (NSCLC). While cell behavior can be modulated by long non­coding RNAs (lncRNAs), the contributions of lncRNAs within extracellular vesicles (exosomes) are largely unknown. To this end, the involvement and regulatory functions of lncRNA H19 wrapped by exosomes during formation of gefitinib resistance in human NSCLC were investigated. Gefitinib­resistant cell lines were built by continuously grafting HCC827 and HCC4006 cells into gefitinib­contained culture medium. RT­qPCR assays indicated that H19 was increased in gefitinib­resistant cells when compared to sensitive parent cells. Functional experiments revealed that silencing of H19 potently promoted gefitinib­induced cell cytotoxicity. H19 was secreted by packaging into exosomes and this packaging process was specifically mediated by hnRNPA2B1. H19 wrapped in exosomes could be transferred to non­resistant cells, thus inducing gefitinib resistance. Moreover, treatment­sensitive cells with exosomes highly­expressing H19 induced gefitinib resistance, while knockdown of H19 abrogated this effect. In conclusion, H19 promoted gefitinib resistance of NSCLC cells by packaging into exosomes. Therefore, exosomal H19 may be a promising therapeutic target for EGFR+ NSCLC patients.