Searching across-cohort relatives in 54,092 GWAS samples via encrypted genotype regression.

Explicitly sharing individual level data in genomics studies has many merits comparing to sharing summary statistics, including more strict QCs, common statistical analyses, relative identification and improved statistical power in GWAS, but it is hampered by privacy or ethical constraints. In this study, we developed encG-reg, a regression approach that can detect relatives of various degrees based on encrypted genomic data, which is immune of ethical constraints. The encryption properties of encG-reg are based on the random matrix theory by masking the original genotypic matrix without sacrificing precision of individual-level genotype data. We established a connection between the dimension of a random matrix, which masked genotype matrices, and the required precision of a study for encrypted genotype data. encG-reg has false positive and false negative rates equivalent to sharing original individual level data, and is computationally efficient when searching relatives. We split the UK Biobank into their respective centers, and then encrypted the genotype data. We observed that the relatives estimated using encG-reg was equivalently accurate with the estimation by KING, which is a widely used software but requires original genotype data. In a more complex application, we launched a finely devised multi-center collaboration across 5 research institutes in China, covering 9 cohorts of 54,092 GWAS samples. encG-reg again identified true relatives existing across the cohorts with even different ethnic backgrounds and genotypic qualities. Our study clearly demonstrates that encrypted genomic data can be used for data sharing without loss of information or data sharing barrier.

COLOCdb: a comprehensive resource for multi-model colocalization of complex traits.

Large-scale genome-wide association studies (GWAS) have provided profound insights into complex traits and diseases. Yet, deciphering the fine-scale molecular mechanisms of how genetic variants manifest to cause the phenotypes remains a daunting task. Here, we present COLOCdb (https://ngdc.cncb.ac.cn/colocdb), a comprehensive genetic colocalization database by integrating more than 3000 GWAS summary statistics and 13 types of xQTL to date. By employing two representative approaches for the colocalization analysis, COLOCdb deposits results from three key components: (i) GWAS-xQTL, pair-wise colocalization between GWAS loci and different types of xQTL, (ii) GWAS-GWAS, pair-wise colocalization between the trait-associated genetic loci from GWASs and (iii) xQTL-xQTL, pair-wise colocalization between the genetic loci associated with molecular phenotypes in xQTLs. These results together represent the most comprehensive colocalization analysis, which also greatly expands the list of shared variants with genetic pleiotropy. We expect that COLOCdb can serve as a unique and useful resource in advancing the discovery of new biological mechanisms and benefit future functional studies.

GPMeta: a GPU-accelerated method for ultrarapid pathogen identification from metagenomic sequences.

Metagenomic sequencing (mNGS) is a powerful diagnostic tool to detect causative pathogens in clinical microbiological testing owing to its unbiasedness and substantially reduced costs. Rapid and accurate classification of metagenomic sequences is a critical procedure for pathogen identification in dry-lab step of mNGS test. However, clinical practices of the testing technology are hampered by the challenge of classifying sequences within a clinically relevant timeframe. Here, we present GPMeta, a novel GPU-accelerated approach to ultrarapid pathogen identification from complex mNGS data, allowing users to bypass this limitation. Using mock microbial community datasets and public real metagenomic sequencing datasets from clinical samples, we show that GPMeta has not only higher accuracy but also significantly higher speed than existing state-of-the-art tools such as Bowtie2, Bwa, Kraken2 and Centrifuge. Furthermore, GPMeta offers GPMetaC clustering algorithm, a statistical model for clustering and rescoring ambiguous alignments to improve the discrimination of highly homologous sequences from microbial genomes with average nucleotide identity >95%. GPMetaC exhibits higher precision and recall rate than others. GPMeta underlines its key role in the development of the mNGS test in infectious diseases that require rapid turnaround times. Further study will discern how to best and easily integrate GPMeta into routine clinical practices. GPMeta is freely accessible to non-commercial users at https://github.com/Bgi-LUSH/GPMeta.

Identification of genetic loci jointly influencing COVID-19 and coronary heart diseases.

BACKGROUND: Comorbidities of coronavirus disease 2019 (COVID-19)/coronary heart disease (CHD) pose great threats to disease outcomes, yet little is known about their shared pathology. The study aimed to examine whether comorbidities of COVID-19/CHD involved shared genetic pathology, as well as to clarify the shared genetic variants predisposing risks common to COVID-19 severity and CHD risks. METHODS: By leveraging publicly available summary statistics, we assessed the genetically determined causality between COVID-19 and CHD with bidirectional Mendelian randomization. To further quantify the causality contributed by shared genetic variants, we interrogated their genetic correlation with the linkage disequilibrium score regression method. Bayesian colocalization analysis coupled with conditional/conjunctional false discovery rate analysis was applied to decipher the shared causal single nucleotide polymorphisms (SNPs). FINDINGS: Briefly, we observed that the incident CHD risks post COVID-19 infection were partially determined by shared genetic variants. The shared genetic variants contributed to the causality at a proportion of 0.18 (95% CI 0.18-0.19) to 0.23 (95% CI 0.23-0.24). The SNP (rs10490770) located near LZTFL1 suggested direct causality (SNPs → COVID-19 → CHD), and SNPs in ABO (rs579459, rs495828), ILRUN(rs2744961), and CACFD1(rs4962153, rs3094379) may simultaneously influence COVID-19 severity and CHD risks. INTERPRETATION: Five SNPs located near LZTFL1 (rs10490770), ABO (rs579459, rs495828), ILRUN (rs2744961), and CACFD1 (rs4962153, rs3094379) may simultaneously influence their risks. The current study suggested that there may be shared mechanisms predisposing to both COVID-19 severity and CHD risks. Genetic predisposition to COVID-19 is a causal risk factor for CHD, supporting that reducing the COVID-19 infection risk or alleviating COVID-19 severity among those with specific genotypes might reduce their subsequent CHD adverse outcomes. Meanwhile, the shared genetic variants identified may be of clinical implications for identifying the target population who are more vulnerable to adverse CHD outcomes post COVID-19 and may also advance treatments of 'Long COVID-19.'

Photoprotective effects of Lithospermum erythrorhizon and Pueraria lobata extracts on UVB-induced photoaging: A study on skin barrier protection.

AIM: Lithospermum erythrorhizon and Pueraria lobata exhibit promising potential as cosmetic additives for mitigating skin barrier impairment induced by photoaging. Despite their potential, the precise mechanisms underlying their protective and ameliorative effects remain elusive. This study sought to assess the reparative properties of Lithospermum erythrorhizon and Pueraria lobata extracts (LP) on UVB-irradiated human skin keratinocytes (HaCaT cells) and explore the therapeutic potential of LP as a skin barrier protection agent. MATERIALS AND METHODS: Antioxidant activities were gauged through 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) (ABTS), and reactive oxygen species (ROS) assays. The expression levels of skin barrier-related markers, encompassing metalloproteinases (MMPs) and hyaluronidase (HYAL) were scrutinized using enzyme-linked immunosorbent assay (ELISA), reverse transcriptase (RT)-PCR, and Western blotting, with a particular focus on the involvement of the transforming growth factor (TGF)-ß/Smad and nuclear factor-κB (NF-κB) signaling pathways. RESULTS: The study revealed that LP effectively scavenges free radicals, diminishes ROS production in a dose-dependent manner, and significantly attenuates UVB-induced expression of MMP-1 and MMP-3 through modulation of the hyaluronan synthase (HAS)2/HYAL1 signaling axis in UVB-irradiated HaCaT cells. Additionally, LP demonstrated enhanced TGF-ß signaling activation, fostering procollagen type I synthesis, and concurrently exhibited mitogen-activated protein kinases (MAPK)/NF-κB signaling inactivation, thereby mitigating pro-inflammatory cytokine release and alleviating UVB-induced cellular damage. CONCLUSION: In conclusion, the observed protective effects of LP on skin cellular constituents highlight its substantial biological potential for shielding against UVB-induced skin photoaging, positioning it as a promising candidate for both pharmaceutical and cosmetic applications.

Heavy metal contamination impacts the structure and co-occurrence patterns of bacterial communities in agricultural soils.

Heavy metal (HM) contamination caused by mining and smelting activities can be harmful to soil microbiota, which are highly sensitive to HM stress. Here, we explore the effects of HM contamination on the taxonomic composition, predicted function, and co-occurrence patterns of soil bacterial communities in two agricultural fields with contrasting levels of soil HMs (i.e., contaminated and uncontaminated natural areas). Our results indicate that HM contamination does not significantly influence soil bacterial α diversity but changes the bacterial community composition by enriching the phyla Gemmatimonadetes, Planctomycetes, and Parcubacteria and reducing the relative abundance of Actinobacteria. Our results further demonstrate that HM contamination can strengthen the complexity and modularity of the bacterial co-occurrence network but weaken positive interactions between keystone taxa, leading to the gradual disappearance of some taxa that originally played an important role in healthy soil, thereby possibly reducing the resistance of bacterial communities to HM toxicity. The predicted functions of bacterial communities are related to membrane transport, amino acid metabolism, energy metabolism, and carbohydrate metabolism. Among these, functions related to HM detoxification and antioxidation are enriched in uncontaminated soils, while HM contamination enriches functions related to metal resistance. This study demonstrated that microorganisms adapt to the stress of HM pollution by adjusting their composition and enhancing their network complexity and potential ecological functions.

Association between circulating 25-hydroxyvitamin D metabolites and periodontitis: Results from the NHANES 2009-2012 and Mendelian randomization study.

AIM: This study sought to investigate associations of 25-hydroxyvitamin D (25(OH)D) metabolites with periodontitis and to assess causality using Mendelian randomization (MR). MATERIALS AND METHODS: This study included 7246 participants of the National Health and Nutrition Examination Survey, 2009-2012. The association of periodontitis with 25(OH)D metabolites was assessed using multivariable logistic regression analysis. Two-sample MR for 25(OH)D, 25(OH)D3 , and C3-epi-25(OH)D3 with periodontitis (n = 17,353 cases/28,210 controls) was conducted. The principal analysis employed the inverse-variance-weighted (IVW) approach. We controlled for horizontal pleiotropy using five additional methods. RESULTS: Based on the observational study, each 1-point increase in standard deviation of 25(OH)D lowered the risk of periodontitis by 15% (OR = 0.85, 95% confidence interval [CI]: 0.78-0.93, p = .006) after multivariable adjustment. A similar relationship was observed between 25(OH)D3 and periodontitis (OR = 0.88, 95% CI: 0.80-0.97, p = .031). Furthermore, a potential non-linear association was found between periodontitis and both 25(OH)D and 25(OH)D3 . However, C3-epi-25(OH)D3 was not found to be associated with periodontitis risk. IVW-MR showed that periodontitis risk was not significantly associated with genetically increased levels of 25(OH)D (OR = 1.02, 95% CI: 0.90-1.16, p = .732), 25(OH)D3 (OR = 1.04, 95% CI: 0.93-1.17, p = .472), or C3-epi-25(OH)D3 (OR = 1.11, 95% CI: 0.87-1.41, p = .400). The pleiotropy-robust MR approaches yielded similar results after we had eliminated the variants with horizontal pleiotropy risk. CONCLUSIONS: Cross-sectional observational analysis identified significant relationships between periodontitis with 25(OH)D metabolites, while findings based on MR study did not support a causal role.

Ecological and health risk assessment of heavy metals in agricultural soils from northern China.

Soil pollution by heavy metals can cause continuing damage to ecosystems and the human body. In this study, we collected nine fresh topsoil samples and 18 maize samples (including nine leaf samples and nine corn samples) from agricultural soils in the Baiyin mining areas. The results showed that the order of heavy metal concentrations (mg/kg) in agricultural soils was as follows: Zn (377.40) > Pb (125.06) > Cu (75.06) > Ni (28.29) > Cd (5.46) > Hg (0.37). Cd, Cu, Zn, and Pb exceeded the Chinese risk limit for agricultural soil pollution. The average the pollution load index (4.39) was greater than 3, indicating a heavy contamination level. The element that contributed the most to contamination and high ecological risk in soil was Cd. Principal component analysis (PCA) and Pearson's correlation analysis indicated that the sources of Ni, Cd, Cu, and Zn in the soil were primarily mixed, involving both industrial and agricultural activities, whereas the sources of Hg and Pb included both industrial and transportation activities. Adults and children are not likely to experience non-carcinogenic impacts from the soil in this region. Nonetheless, it was important to be aware of the elevated cancer risk presented by Cd, Pb, and especially Ni. The exceedance rates of Cd and Pb in corn were 66.67% and 33.3%, respectively. The results of this research provide data to improve soil protection, human health monitoring, and crop management in the Baiyin district.

Genetic predisposition to coronary artery disease is predictive of recurrent events: a Chinese prospective cohort study.

Evidence of the effects of genetic risk score (GRS) on secondary prevention is scarce and mixed. We investigated whether coronary artery disease (CAD) susceptible loci can be used to predict the risk of major adverse cardiovascular events (MACEs) in a cohort with acute coronary syndromes (ACSs). A total of 1667 patients hospitalized with ACS were enrolled and prospectively followed for a median of 2 years. We constructed a weighted GRS comprising 79 CAD risk variants and investigated the association between GRS and MACE using a multivariable cox proportional hazard regression model. The incremental value of adding GRS into the prediction model was assessed by integrated discrimination improvement (IDI) and decision curve analysis (DCA). In the age- and sex-adjusted model, each increase in standard deviation in the GRS was associated with a 33% increased risk of MACE (hazard ratio: 1.33; 95% confidence interval: 1.10-1.61; P = 0.003), with this association not attenuating after further adjustment for traditional cardiovascular risk factors. The addition of GRS to a prediction model of seven clinical risk factors and EPICOR prognostic model slightly improved risk stratification for MACE as calculated by IDI (+1.7%, P = 0.006; +0.3%, P = 0.024, respectively). DCA demonstrated positive net benefits by adding GRS to other models. GRS was associated with MACE after multivariable adjustment in a cohort comprising Chinese ACS patients. Future studies are needed to validate our results and further evaluate the predictive value of GRS in secondary prevention.

Evidence for CAT gene being functionally involved in the susceptibility of COVID-19.

Novel coronary pneumonia (COVID-19) is a respiratory distress syndrome caused by a new type of coronavirus. Understanding the genetic basis of susceptibility and prognosis to COVID-19 is of great significance to disease prevention, molecular typing, prognosis, and treatment. However, so far, there have been only two genome-wide association studies (GWASs) on the susceptibility of COVID-19. Starting with these reported DNA variants, we found the genes regulated by these variants through cis-eQTL and cis-meQTL acting. We further did a series of bioinformatics analysis on these potential risk genes. The analysis shows that the genetic variants on EHF regulate the expression of its neighbor CAT gene via cis-eQTL. There was significant evidence that CAT and the SARS-CoV-2-related S protein binding protein ACE2 interact with each other. Intracellular localization results showed that CAT and ACE2 proteins both exists in the cell membrane and extracellular area and their interaction could have an impact on the cell invasion ability of S protein. In addition, the expression of these three genes showed a significant positive correlation in the lungs. Based on these results, we propose that CAT plays a crucial intermediary role in binding effectiveness of ACE2, thereby affecting the susceptibility to COVID-19.

Comprehensive nutritional index for predicting overall survival in hepatocellular carcinoma patients after multiple transarterial chemoembolization.

BACKGROUND AND OBJECTIVES: Little is known about nutritional status in patients with hepatocellular carcinoma (HCC) after multiple rounds of transarterial chemoembolization (TACE). We established a comprehensive nutritional index (CNI) and evaluated its prognostic value for overall survival (OS) and time to progression (TTP). METHODS AND STUDY DESIGN: HCC patients (N=282) who underwent multiple TACE treatments were enrolled. CNI was established by principal component analysis based on body mass index, usual body weight percentage, hemoglobin, total lymphocyte count, and albumin; the cutoff value was determined by receiver operating characteristic curve and Youden index analysis. The correlation between CNI and treatment-related complications was analyzed with Spearman's method. The Kaplan-Meier method with log-rank test and Cox proportional hazards model were used to compare the prognostic values of CNI, prognostic nutritional index (PNI), and nutrition risk index (NRI) for OS and TTP. RESULTS: Nutritional status declined after repeated TACE (p<0.001). CNI (cutoff= 0.251) varied according to albumin-bilirubin grade, tumor size, and number of TACE treatments (p<0.001 or 0.025) and was negatively correlated with rate of serious complications (r=-0.185, p=0.002). Patients with low CNI had shorter OS (p=0.014) and TTP (p=0.007); high CNI predicted longer OS (hazard ratio [HR], 0.72; 95% confidence interval [CI]: 0.52-1.00, p=0.048) and TTP (HR, 0.69; 95% CI: 0.50-0.94, p=0.019). Post-treatment PNI and NRI were unrelated to prognosis (p>0.05). CONCLUSIONS: HCC patients have poor nutritional status after multiple TACE treatments, which predicts shorter OS and TTP. The prognostic performance of CNI is superior to those of PNI and NRI.

A nomogram model to predict death rate among non-small cell lung cancer (NSCLC) patients with surgery in surveillance, epidemiology, and end results (SEER) database.

BACKGROUND: This study aimed to establish a novel nomogram prognostic model to predict death probability for non-small cell lung cancer (NSCLC) patients who received surgery.. METHODS: We collected data from the Surveillance, Epidemiology, and End Results (SEER) database of the National Cancer Institute in the United States. A nomogram prognostic model was constructed to predict mortality of NSCLC patients who received surgery. RESULTS: A total of 44,880 NSCLC patients who received surgery from 2004 to 2014 were included in this study. Gender, ethnicity, tumor anatomic sites, histologic subtype, tumor differentiation, clinical stage, tumor size, tumor extent, lymph node stage, examined lymph node, positive lymph node, type of surgery showed significant associations with lung cancer related death rate (P < 0.001). Patients who received chemotherapy and radiotherapy had significant higher lung cancer related death rate but were associated with significant lower non-cancer related mortality (P<0.001). A nomogram model was established based on multivariate models of training data set. In the validation cohort, the unadjusted C-index was 0.73 (95% CI, 0.72-0.74), 0.71 (95% CI, 0.66-0.75) and 0.69 (95% CI, 0.68-0.70) for lung cancer related death, other cancer related death and non-cancer related death. CONCLUSIONS: A prognostic nomogram model was constructed to give information about the risk of death for NSCLC patients who received surgery.

Nomogram model for predicting cause-specific mortality in patients with stage I small-cell lung cancer: a competing risk analysis.

BACKGROUND: The five-year cumulative incidence rate in patients diagnosed with stage I small-cell lung cancer (SCLC) who were instructed to undergo surgery was from 40 to 60%.The death competition influence the accuracy of the classical survival analyses. The aim of the study is to investigate the mortality of stage I small-cell lung cancer (SCLC) patients in the presence of competing risks according to a proportional hazards model, and to establish a competing risk nomogram to predict probabilities of both cause-specific death and death resulting from other causes. METHODS: The study subjects were patients diagnosed with stage I SCLC according to ICD-O-3. First, the cumulative incidence functions (CIFs) of cause-specific death, as well as of death resulting from other causes, were calculated. Then, a proportional hazards model for the sub-distribution of competing risks and a monogram were constructed to evaluate the probability of mortality in stage I SCLC patients. RESULTS: 1811 patients were included in this study. The five-year probabilities of death due to specific causes and other causes were 61.5 and 13.6%, respectively. Tumor size, extent of tumor, surgery, and radiotherapy were identified as the predictors of death resulting from specific causes in stage I SCLC. The results showed that surgery could effectively reduce the cancer-specific death, and the one-year cumulative incidence dropped from 34.5 to 11.2%. Like surgery, chemotherapy and radiotherapy improved the one-year survival rate. CONCLUSIONS: We constructed a predictive model for stage I SCLC using the data from the SEER database. The proportional sub-distribution models of competing risks revealed the predictors of death resulting from both specific causes and other causes. The competing risk nomogram that we built to predict the prognosis showed good reliability and could provide beneficial and individualized predictive information for stage I SCLC patients.

Integration of genome-wide association study and expression quantitative trait loci data identifies AIM2 as a risk gene of periodontitis.

AIM: To identify risk variants associated with gene expression in peripheral blood and to identify genes whose expression change may contribute to the susceptibility to periodontitis. MATERIAL AND METHODS: We systematically integrated the genetic associations from a recent large-scale periodontitis GWAS and blood expression quantitative trait loci (eQTL) data using Sherlock, a Bayesian statistical framework. We then validated the potential causal genes in independent gene expression data sets. Gene co-expression analysis was used to explore the functional relationship for the identified causal genes. RESULTS: Sherlock analysis identified 10 genes (rs7403881 for MT1L, rs12459542 for SIGLEC5, rs12459542 for SIGLEC14, rs6680386 for S100A12, rs10489524 for TRIM33, rs11962642 for HIST1H3E, rs2814770 for AIM2, rs7593959 for FASTKD2, rs10416904 for PKN1, and rs10508204 for WDR37) whose expression may influence periodontitis. Among these genes, AIM2 was consistent significantly upregulated in periodontium of periodontitis patients across four data sets. The cis-eQTL (rs2814770, ~16 kb upstream of AIM2) showed significant association with AIM2 (p = 6.63 × 10-6 ) and suggestive association with periodontitis (p = 7.52 × 10-4 ). We also validated the significant association between rs2814770 and AIM2 expression in independent expression data set. Pathway analysis revealed that genes co-expressed with AIM2 were significantly enriched in immune- and inflammation-related pathways. CONCLUSION: Our findings implicate that AIM2 is a susceptibility gene, expression of which in gingiva may influence periodontitis risk. Further functional investigation of AIM2 may provide new insight for periodontitis pathogenesis.

Analyzing Functional Pathways and constructing gene-gene network for Narcolepsy based on candidate genes.

Aims: To investigate the interactions among narcolepsy-associated genes and reveal the pathways these genes involved through bioinformatics analyses. Methods: The study was performed with the following steps: 1) Selected the previously discovered narcolepsy risk genes through literature review, 2) pathway enrichment analysis, and construction of gene-gene and protein-protein interaction (PPI) networks for narcolepsy. Results: 1) GO analysis revealed the positive regulation of interferon-gamma production as the most enriched terms in biological process, and C-C chemokine receptor activity as the most enriched term in molecular function, 2) KEGG pathway enrichment analysis revealed selective enrichment of genes in cytokine-cytokine receptor interaction signaling pathways, and 3) five hub genes were identified (IFNAR1, IL10RB, DNMT1, TNFSF4 and NFATC2). Conclusion: The bioinformatics results provide new insights into the molecular pathogenesis of narcolepsy and the identification of potential therapeutic targets for narcolepsy treatment.

Two-part mixed-effects location scale models.

Longitudinal time use data afford the opportunity to study within- and between-individual differences, but can present challenges in data analysis. Often the response set includes a large number of zeros representing those who did not engage in the target behavior. Coupled with this is a continuous measure of time use for those who did engage. The latter is strictly positive and skewed to the right if relatively few individuals engage in the behavior to a greater extent. Data analysis is further complicated for repeated measures, because within-individual responses are typically correlated, and some respondents may have missing data. This combination of zeros and positive responses is characteristic of a type of semicontinuous data in which the response is equal to a discrete value and is otherwise continuous. Two-part models have been successfully applied to cross-sectional time use data when the research goals distinguish between a respondent's likelihood to engage in a behavior and the time spent conditional on any time being spent, as these models allow different covariates to relate to each distinct aspect of a behavior. Two-part mixed-effects models extend two-part models for analysis of longitudinal semicontinuous data to simultaneously address longitudinal decisions to engage in a behavior and time spent conditional on any time spent. Heterogeneity between and within individuals can be studied in unique ways. This paper presents applications of these models to daily diary data to study individual differences in time spent relaxing or engaged in leisure activities for an adult sample.

Genetic predisposition to type 2 diabetes is associated with severity of coronary artery disease in patients with acute coronary syndromes.

BACKGROUND: Accumulating evidence has shown that type 2 diabetes (T2D) and coronary artery disease (CAD) may stem from a 'common soil'. The aim of our study was to examine the association between genetic predisposition to T2D and the risk of severe CAD among patients with acute coronary syndromes (ACS) undergoing angiography. METHODS: The current case-control study included 1414 ACS patients with at least one major epicardial vessel stenosis > 50% enrolled in the ACS Genetic Study. The severity of CAD was quantified by the number of coronary arteries involved. Genetic risk score (GRS) was calculated using 41 common variants that robustly associated with increased risk of T2D in East Asians. Logistic regression models were used to estimate the association between GRS and the severity of CAD. RESULTS: In the age-, sex- and BMI-adjusted model, each additional risk allele was associated with a 6% increased risk of multi-vessel disease (OR = 1.06, 95% CI 1.02-1.09). The OR was 1.43 (95% CI 1.08-1.89) for the risk of severe CAD when comparing the extreme tertiles of T2D-GRS. The association was not reduced after further adjustment for conventional cardiovascular risk factors. Additional adjustment for T2D status in our regression model attenuated the association by approximately one quarter. In subgroup analysis, the strengths of the associations between GRS and the severity of CAD were broadly similar in terms of baseline demographic information and disease characteristics. CONCLUSIONS: Our data indicated that genetic predisposition to T2D is associated with elevated risk of severe CAD. This association revealed a possible causal relationship and is partially mediated through diabetic status.

Chinese version of narcolepsy severity scale: a validation study.

BACKGROUND: The narcolepsy severity scale (NSS) was developed to measure the severity and consequences of symptoms in patients with narcolepsy. The scale has been validated in France, though no other studies have further validated this instrument. The current study aimed to present psychometric properties and describe the score distribution of the Chinese-NSS. METHODS: One hundred twenty-two patients with narcolepsy (41 females and 81 males; mean age 26.14 ± 15.40 years) participated in the study. All patients completed the Chinese-NSS. Cronbach's α, item-total score correlations, exploratory factor analysis (EFA), and correlations between NSS total scores and clinical or sleep parameters were then calculated. RESULTS: EFA yielded a three-factor model. Internal consistency was acceptable (Cronbach'sα = 0.799). The NSS total score had significant correlations with the Epworth sleepiness score (0.447), pediatric daytime sleepiness scale (0.318), the insomnia severity index (0.592), Beck depression inventory (0.593), EurQol five dimensions-utility (0.457), EurQol five dimensions -VAS (- 0.323), the sleep disturbance scale for children (0.440), the children depression inventory (0.553), and the pediatric quality of life inventory (0.555) total scores, demonstrating acceptable convergence as predicted. CONCLUSIONS: The current study is the first validation study of the narcolepsy severity scale in an Asian population. The findings validated the Chinese-narcolepsy severity scale in a Chinese population with acceptable psychometric properties. There are minor differences between our results and those of the original study due to cultural differences.

The effect of ambient particle matters on hospital admissions for cardiac arrhythmia: a multi-city case-crossover study in China.

BACKGROUND: The relationship between particle matters (PMs) and cardiac arrhythmia has been investigated in numerous studies. However, evidence from developing countries is limited. The aim of this study was to evaluate the association between ambient PMs and hospital admissions for cardiac arrhythmia in China and to examine the potential effect modifiers. METHODS: A time-stratified case-crossover analysis was conducted in 26 large Chinese cities. In total, we identified 175,265 hospital admissions for cardiac arrhythmia between January 2014 and December 2015 from electronic hospitalization summary reports. Conditional logistic regression was performed to estimate the percentage changes in cardiac arrhythmia admissions in relation to interquartile range increases in air pollutants. Age, gender and prespecified comorbid health conditions including hypertension, diabetes, congestive heart failure and hyperlipidemia were stratified to evaluate susceptibility factors. RESULTS: PMs levels were positively associated with the number of hospital admissions for cardiac arrhythmia. Both PM2.5 and PM10 had the strongest impact on lag 2 days. An interquartile range increase in PM2.5 (47.5 µg/m3) and PM10 (76.9 µg/m3) concentrations on lag 2 days was associated with increments of 2.09% (95%CI, 1.58-2.60%) and 2.33% (95%CI, 1.68-2.97%) in hospital admission for cardiac arrhythmia, respectively. Evidence of effect modification by age and comorbid diabetes was observed. The elderly (> 65 years) and patients with comorbid diabetes were more likely to be hospitalized for cardiac arrhythmia following exposure to high levels of PMs. CONCLUSIONS: This study found an increased risk of arrhythmia admissions associated with PM2.5 and PM10 levels among 26 Chinese cities. The associations of PMs with arrhythmia admissions were stronger in aged population and people with diabetes.

Survival difference between EGFR Del19 and L858R mutant advanced non-small cell lung cancer patients receiving gefitinib: a propensity score matching analysis.

OBJECTIVE: Although superior clinical benefits of epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) in the treatment of advanced non-small-cell lung cancer (NSCLC) had been reported, the survival difference between exon 19 deletion (Del19) and exon 21 Leu858Arg substitution (L858R) remains controversial. The purpose of this study is to investigate the differences in progression-free survival (PFS) and overall survival (OS) between different EGFR mutant subtypes among advanced NSCLC patients receiving gefitinib. METHODS: There were 204 advanced NSCLC patients with EGFR mutations treated with gefitinib were enrolled in this retrospective cohort study. Patients were divided into the EGFR Del19 group and the L858R mutated group according to their mutant subtype. Propensity score matching (PSM) was conducted by using a nearest-neighbor algorithm (1:1) to adjust for demographical and clinical covariates. Survival curves were constructed with the Kaplan-Meier method and compared by using the log-rank test. RESULTS: The PFS in Del19 group was similar to that in the L858R group [before PSM 8.6 vs. 7.2 months, P=0.072; after PSM 7.3 vs. 7.2 months, P=0.155]. No differences were detected in OS between the L858R and the Del19 group (before PSM 17.8 vs. 13.1 months, P=0.253; after PSM 16.9 vs. 13.1 months, P=0.339). The Del19 group was significantly younger compared with the L858R mutation group in age (P=0.015). CONCLUSIONS: No significant difference was found in the PFS or OS between the Del19 and L858R mutant NSCLC patients receiving gefitinib. The age gap might contribute to the survival differences between Del19 and L858R groups. PSM is of important value to the elimination of potential bias.