Sleeping more than 8 h: a silent factor contributing to decreased muscle mass in Chinese community-dwelling older adults.

BACKGROUND: Muscle mass loss is an age-related process that can be exacerbated by lifestyle, environmental and other factors, but can be mitigated by good sleep. The objective of this study was to investigate the correlation between varying time lags of sleep duration and the decline in muscle mass among individuals aged 60 years or older by using real-world health monitoring data obtained from wearable devices and smart home health monitoring devices. METHODS: This study included 86,037 observations from 2,869 participants in the Mobile Support System database. Missing data were supplemented by multiple imputation. The investigation utilized generalized estimating equations and restricted cubic spline curve to examine the relationship between sleep duration and low muscle mass. Various lag structures, including 0, 1, 2, 0-1, 0-2, and 1-2 months, were fitted, and the interaction effect of observation time with sleep duration was estimated for each lag structure. Additionally, subgroup analyses were conducted. The models were adjusted for various covariates, including gender, age, body mass index, footsteps, smoking status, drinking status, marital status, number of chronic diseases, number of medications, diabetes mellitus, hyperlipidemia, coronary artery disease, respiratory disease, and musculoskeletal disease and an interaction term between time and sleep duration. RESULTS: The results of the generalized estimating equation showed a significant correlation (p < 0.001) between sleep duration of 8 h or more and low muscle mass in older adults, using 6-7 h of sleep as a reference. This effect was seen over time and prolonged sleep accumulated over multiple months had a greater effect on muscle mass loss than a single month. The effect of long sleep duration on muscle mass loss was significantly greater in females than in males and greater in the over-75 than in the under-75 age group. Restricted cubic spline plots showed a non-linear relationship between sleep duration and low muscle mass (p < 0.001). CONCLUSIONS: This study found an association between sustained nighttime sleep of more than eight hours and decreased muscle mass in older adults, especially older women.

FTO genotype and body mass index reduction in childhood obesity interventions: A systematic review and meta-analysis.

Numerous guidelines have called for personalized interventions to address childhood obesity. The role of fat mass and obesity-associated gene (FTO) in the risk of childhood obesity has been summarized. However, it remains unclear whether FTO could influence individual responses to obesity interventions, especially in children. To address this, we systematically reviewed 12,255 records across 10 databases/registers and included 13 lifestyle-based obesity interventions (3980 children with overweight/obesity) reporting changes in body mass index (BMI) Z-score, BMI, waist circumference, waist-to-hip ratio, and body fat percentage after interventions. These obesity-related outcomes were first compared between children carrying different FTO genotypes (rs9939609 or its proxy) and then synthesized by random-effect meta-analysis models. The results from single-group interventions showed no evidence of associations between FTO risk allele and changes in obesity-related outcomes after interventions (e.g., BMI Z-score: -0.01; 95% CI: -0.04, 0.01). The results from controlled trials showed that associations between the FTO risk allele and changes in obesity-related outcomes did not differ by intervention/control group. To conclude, the FTO risk allele might play a minor role in the response to obesity interventions among children. Future studies might pay more attention to the accumulation effect of multiple genes in the intervention process among children.

[Association between insomnia and type 2 diabetes: A two-sample Mendelian rando-mization study].

OBJECTIVE: To explore the robust relationship between insomnia and type 2 diabetes mellitus by two-sample Mendelian randomization analysis to overcome confounding factors and reverse causality in observational studies. METHODS: We identified strong, independent single nucleotide polymorphisms (SNPs) of insomnia from the most up to date genome wide association studies (GWAS) within European ancestors and applied them as instrumental variable to GWAS of type 2 diabetes mellitus. After excluding SNPs that were significantly associated with smoking, physical activity, alcohol consumption, educational attainment, obesity, or type 2 diabetes mellitus, we assessed the impact of insomnia on type 2 diabetes mellitus using inverse variance weighting (IVW) method. Weighted median and MR-Egger regression analysis were also conducted to test the robustness of the association. We calculated the F statistic of the selected SNPs to test the applicability of instrumental variable and F statistic over than ten indicated that there was little possibility of bias of weak instrumental variables. We further examined the existence of pleiotropy by testing whether the intercept term in MR-Egger regression was significantly different from zero. In addition, the leave-one-out method was used for sensitivity analysis to verify the stability and reliability of the results. RESULTS: We selected 248 SNPs independently associated with insomnia at the genome-wide level (P<5×10-8) as a preliminary candidate set of instrumental variables. After clumping based on the reference panel from 1000 Genome Project and removing the potential pleiotropic SNPs, a total of 167 SNPs associated with insomnia were included as final instrumental variables. The F statistic of this study was 39. 74, which was in line with the relevance assumption of Mendelian randomization. IVW method showed insomnia was associated with higher risk of type 2 diabetes mellitus that po-pulation with insomnia were 1. 14 times more likely to develop type 2 diabetes mellitus than those without insomnia (95% CI: 1.09-1.21, P<0.001). The weighted median estimator (WME) method and MR-Egger regression showed similar causal effect of insomnia on type 2 diabetes mellitus. And MR-Egger regression also showed that the effect was less likely to be triggered by pleiotropy. Sensitivity analyses produced directionally similar estimates. CONCLUSION: Insomnia is a risk factor of type 2 diabetes mellitus, which has positively effects on type 2 diabetes mellitus. Our study provides further rationale for indivi-duals at risk for diabetes to keep healthy lifestyle.

Occupational noise and hypertension in Southern Chinese workers: a large occupational population-based study.

INTRODUCTION: An increasing number of original studies suggested that occupational noise exposure might be associated with the risk of hypertension, but the results remain inconsistent and inconclusive. In addition, the attributable fraction (AF) of occupational noise exposure has not been well quantified. We aimed to conduct a large-scale occupational population-based study to comprehensively investigate the relationship between occupational noise exposure and blood pressure and different hypertension subtypes and to estimate the AF for hypertension burden attributable to occupational noise exposure. METHODS: A total of 715,135 workers aged 18-60 years were included in this study based on the Key Occupational Diseases Surveillance Project of Guangdong in 2020. Multiple linear regression was performed to explore the relationships of occupational noise exposure status, the combination of occupational noise exposure and binaural high frequency threshold on average (BHFTA) with systolic and diastolic blood pressure (SBP, DBP). Multivariable logistic regression was used to examine the relationshipassociation between occupational noise exposure status, occupational noise exposure combined with BHFTA and hypertension. Furthermore, the attributable risk (AR) was calculated to estimate the hypertension burden attributed to occupational exposure to noise. RESULTS: The prevalence of hypertension among occupational noise-exposed participants was 13·7%. SBP and DBP were both significantly associated with the occupational noise exposure status and classification of occupational noise exposure combined with BHFTA in the crude and adjusted models (all P < 0·0001). Compared with workers without occupational noise exposure, the risk of hypertension was 50% greater among those exposed to occupational noise in the adjusted model (95% CI 1·42-1·58). For participants of occupational noise exposed with BHFTA normal, and occupational noise exposed with BHFTA elevated, the corresponding risks of hypertension were 48% (1·41-1·56) and 56% (1·46-1·63) greater than those of occupational noise non-exposed with BHFTA normal, respectively. A similar association was found in isolated systolic hypertension (ISH) and prehypertension. Subgroup analysis by sex and age showed that the positive associations between occupational noise exposure and hypertension remained statistically significant across all subgroups (all P < 0.001). Significant interactions between occupational noise status, classification of occupational noise exposure combined with BHFTA, and age in relation to hypertension risk were identified (all P for interaction < 0.001). The associations of occupational noise status, classification of occupational noise exposure combined with BHFTA and hypertension were most pronounced in the 18-29 age groups. The AR% of occupational noise exposure for hypertension was 28·05% in the final adjusted model. CONCLUSIONS: Occupational noise exposure was positively associated with blood pressure levels and the prevalence of hypertension, ISH, and prehypertension in a large occupational population-based study. A significantly increased risk of hypertension was found even in individuals with normal BHFTA exposed to occupational noise, with a further elevated risk observed in those with elevated BHFTA. Our findings provide epidemiological evidence for key groups associated with occupational noise exposure and hypertension, and more than one-fourth of hypertension cases would have been prevented by avoiding occupational noise exposure.

Detecting Gene-Gene Interaction among DNA Repair Genes in Chinese non-Syndromic Cleft lip with or Without Palate Trios.

OBJECTIVE: The objective of this study is to investigate the gene-gene interactions associated with NSCL/P among DNA repair genes. DESIGN: This study included 806 NSCL/P case-parent trios from China. Quality control process was conducted for genotyped single nucleotide polymorphisms (SNPs) located in six DNA repair genes (ATR, ERCC4, RFC1, TYMS, XRCC1 and XRCC3). We tested gene-gene interactions with Cordell's method using statistical package TRIO in R software. Bonferroni corrected significance level was set as P = 4.24 × 10-4. We also test the robustness of the interactions by permutation tests. SETTING: Not applicable. PATIENTS/PARTICIPANTS: A total of 806 NSCL/P case-parent trios (complete trios: 682, incomplete trios: 124) with Chinese ancestry. INTERVENTIONS: Not applicable. MAIN OUTCOME MEASURE(S): Not applicable. RESULTS: A total of 118 SNPs were extracted for the interaction tests. Fourteen pairs of significant interactions were identified after Bonferroni correction, which were confirmed in permutation tests. Twelve pairs were between ATR and ERCC4 or XRCC3. The most significant interaction occurred between rs2244500 in TYMS and rs3213403 in XRCC1(P = 8.16 × 10-15). CONCLUSIONS: The current study identified gene-gene interactions among DNA repair genes in 806 Chinese NSCL/P trios, providing additional evidence for the complicated genetic structure underlying NSCL/P. ATR, ERCC4, XRCC3, TYMS and RFC1 were suggested to be possible candidate genes for NSCL/P.

'Let's Talk About Children' family focused practice for children of parents with schizophrenia and bipolar disorder: protocol for a randomized controlled trial.

INTRODUCTION: 'Let's Talk About Children' is a brief family focused intervention developed to improve mental health outcomes of children of parents with mental illness (COPMI). This study aims to assess the efficacy of LTC in improving mental health of children of parents with schizophrenia or bipolar disorder in China. METHODS: The planned study is a multicentre parallel group randomized wait-list controlled trial. A total of 400 eligible families with children aged 8 to 18 years will be recruited, 200 each for families with parental schizophrenia or bipolar disorder. The intervention group will receive Let's Talk About Children delivered by a trained therapist, while the control group will receive treatment as usual. The primary outcomes are child mental health measured by the strengths and difficulties questionnaire and parent-child communication measured using the parent-adolescent communication scale. Parental mental health and family functioning are secondary outcomes. This study also plans to explore mediating factors for the effect of Let's Talk About Children on child mental health, as well as conduct a cost-effectiveness analysis on using Let's Talk About Children in China. CONCLUSION: The present study will provide evidence for the efficacy of Let's Talk About Children in families with parental schizophrenia and bipolar disorder in China. In addition, it will evaluate potential mechanisms of action and cost-effectiveness of Let's Talk About Children, providing a basis for future implementation. TRIAL REGISTRATION: ChiCTR2300073904.

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.'

Identifying Risk Factors for Aspiration in Patients Hospitalized with Community-Acquired Pneumonia.

Background: Aspiration pneumonia (AP) is difficult to diagnose and has poor outcomes. This case-control study aimed to explore the risk factors and delineate the antibiotic usage for AP. Methods: Inpatients diagnosed with community-acquired pneumonia (CAP) from 2013 to 2017, enrolled in the urban employee basic medical insurance program in Beijing, were included and classified into the AP (N = 2,885) and non-AP (N = 53,825) groups. Risk factors were identified by logistic regression. Results: Older age (compared to 18-64 years, OR for 65-79 years: 4.3, 95% CI: 3.8-4.9; OR for >80 years: 6.3, 95% CI: 5.6-7.2), male (OR: 1.4, 95% CI: 1.3-1.5), cerebrovascular disease (OR: 3.1, 95% CI: 2.8-3.5), dementia (OR: 2.0, 95% CI: 1.8-2.1), vomiting (OR: 1.4, 95% CI: 1.2-1.7), Parkinson's disease (OR: 2.1, 95% CI: 1.8-2.4), and epilepsy (OR: 3.2, 95% CI: 2.8-3.7) were associated with an increased risk of AP. 92.8% of the AP patients received antibiotic therapy. Among them, patients treated with broad-spectrum antibiotics, antibiotics for injection, and combined antibiotics accounted for 93.3%, 97.9%, and 81.7%, respectively. Conclusions: Older age, male, and several comorbidities were independent risk factors for AP, and combined antibiotics treatments are common, which merits attention in accurate detection of AP in a high-risk population.

PDE3A and GSK3B as Atrial Fibrillation Susceptibility Genes in the Chinese Population via Bioinformatics and Genome-Wide Association Analysis.

BACKGROUND: Atrial fibrillation (AF) is the most common cardiac arrhythmia, with uncovered genetic etiology and pathogenesis. We aimed to screen out AF susceptibility genes with potential pathogenesis significance in the Chinese population. METHODS: Differentially expressed genes (DEGs) were screened by the Limma package in three GEO data sets of atrial tissue. AF-related genes were identified by combination of DEGs and public GWAS susceptibility genes. Potential drug target genes were selected using the DrugBank, STITCH and TCMSP databases. Pathway enrichment analyses of AF-related genes were performed using the databases GO and KEGG databases. The pathway gene network was visualized by Cytoscape software to identify gene-gene interactions and hub genes. GWAS analysis of 110 cases of AF and 1201 controls was carried out through a genome-wide efficient mixed model in the Fangshan population to verify the results of bioinformatic analysis. RESULTS: A total of 3173 DEGs were identified, 57 of which were found to be significantly associated with of AF in public GWAS results. A total of 75 AF-related genes were found to be potential therapeutic targets. Pathway enrichment analysis selected 79 significant pathways and classified them into 7 major pathway networks. A total of 35 hub genes were selected from the pathway networks. GWAS analysis identified 126 AF-associated loci. PDE3A and GSK3B were found to be overlapping genes between bioinformatic analysis and GWAS analysis. CONCLUSIONS: We screened out several pivotal genes and pathways involved in AF pathogenesis. Among them, PDE3A and GSK3B were significantly associated with the risk of AF in the Chinese population. Our study provided new insights into the mechanisms of action of AF.

KCNQ1 rs2237892 polymorphism modify the association between short-term ambient particulate matter exposure and fasting blood glucose: A family-based study.

BACKGROUND: The association between particulate matter and fasting blood glucose (FBG) has shown conflicting results. Genome-wide association studies have shown that KCNQ1 rs2237892 polymorphism is associated with the risk of diabetes. Whether KCNQ1 rs2237892 polymorphism might modify the association between particulate matter and FBG is still uncertain. METHODS: Data collected from a family-based cohort study in Northern China, were used to perform the analysis. A generalized additive Gaussian model was used to examine the short-term effects of air pollutants on FBG. We further conducted interaction analyses by including a cross-product term of air pollutants by rs2237892 within KCNQ1 gene. RESULTS: A total of 4418 participants were included in the study. In the single pollutant model, the FBG level increased 0.0031 mmol/L with per 10 µg/m3 elevation in fine particular matter (PM2.5) for lag 0 day. After additional adjustments for nitrogen dioxide (NO2) and sulfur dioxide (SO2), similar results were observed for lag 0-2 days. As for particulate matter with particle size below 10 µm (PM10), the significant association between the daily average concentration of the pollutant and FBG level was observed for lag 0-3 days. Additionally, rs2237892 in KCNQ1 gene modified the association between PM and FBG level. The higher risk of FBG levels associated with elevations in PM10 and PM2.5 were more evident as the number of risk allele C increased. Individuals with a CC genotype had the highest risk of elevation in FBG levels. CONCLUSION: Short-term exposures to PM2.5 and PM10 were associated with higher FBG levels. Additionally, rs2237892 in KCNQ1 gene might modify the association between the air pollutants and FBG levels.

Adverse childhood experiences in offspring living with parental mental illness: a controlled study from China.

BACKGROUND: Adverse childhood experiences (ACEs) affect children's development, and their harm to health is pervasive throughout the life course. AIMS: To identify ACEs and their risk factors in Chinese household with or without parental mental illness. METHODS: A controlled study was conducted among 181 young adults with parental mental illness (positive group) and 201 demographically matched individuals without parental mental illness (negative group). Univariate and multivariate analyses were performed to study the correlation between ACEs and their risk factors. RESULTS: The positive group suffered emotional abuse, domestic violence, bullying, and cumulative ACEs more frequently than the negative group. In the positive group, living in rural areas and having a low household economic status during childhood were identified as risk factors for cumulative ACEs, whereas a higher education level of the mother was a protective factor for cumulative ACEs in univariate analyses. Low household economic status remained an independent risk factor for cumulative ACEs in the positive group in multivariate analyses. CONCLUSIONS: Children living with parental mental illness are more vulnerable to ACEs, and our findings highlight the importance of socioeconomic factors in increasing the risk of ACEs. To alleviate the deleterious impact of parental mental illness on offspring, multidimensional supports are needed.

Synergism of cell adhesion regulatory genes and instant air pollutants on blood pressure elevation.

Accumulating evidence suggests that an instant exposure to particulate matter (PM) may elevate blood pressure (BP), where cell-adhesion regulatory genes may be involved in the interplay. However, few studies to date critically examined their interaction, and it remained unclear whether these genes modified the association. To assess the association between instant PM exposure and BP, and to examine whether single-nucleotide polymorphisms (SNPs) mapped in four cell adhesion regulatory genes modify the relationship, a cross-sectional study was performed, based on the baseline of an ongoing family-based cohort in Beijing, China. A total of 4418 persons from 2089 families in Northern China were included in the analysis. Four tagged SNPs in cell adhesion regulatory genes were selected among ZFHX3, CXCL12, RASGRP1 and MIR146A. A generalized additive model (GAM) with a Gaussian link was adopted to estimate the change in blood pressure after instant PM2.5 or PM10 exposure. A cross-product term of PM2.5/PM10 and genotype was incorporated into the GAM model to test for interaction. The study observed that an instant exposure to either PM2.5 or PM10 was found to be associated with elevated systolic blood pressure (SBP). On average, a 10 µg/m3 increase in instant exposure to PM2.5 and PM10 concentration corresponded to 0.140% (95% CI: 0.014%-0.265%, P = 0.029) and 0.173% (95% CI: 0.080%-0.266%, P < 0.001) higher SBP. However, diastolic blood pressure (DBP) was not elevated as the PM2.5 or PM10 concentration increased (P > 0.05). A synergetic interaction on SBP was observed between SNPs in four cell adhesion regulatory genes (rs2910164 in MIR146A, rs2297630 in CXCL12, rs7403531 in RASGRP1, and rs7193343 in ZFHX3) and instant PM2.5 exposure (Pfor interaction <0.05). Briefly, as carriers of risk alleles in each of these four genes increased, an enhanced association was found between instant PM2.5 exposure and SBP.

Disease patterns of coronary heart disease and type 2 diabetes harbored distinct and shared genetic architecture.

BACKGROUND: Coronary heart disease (CHD) and type 2 diabetes (T2D) are two complex diseases with complex interrelationships. However, the genetic architecture of the two diseases is often studied independently by the individual single-nucleotide polymorphism (SNP) approach. Here, we presented a genotypic-phenotypic framework for deciphering the genetic architecture underlying the disease patterns of CHD and T2D. METHOD: A data-driven SNP-set approach was performed in a genome-wide association study consisting of subpopulations with different disease patterns of CHD and T2D (comorbidity, CHD without T2D, T2D without CHD and all none). We applied nonsmooth nonnegative matrix factorization (nsNMF) clustering to generate SNP sets interacting the information of SNP and subject. Relationships between SNP sets and phenotype sets harboring different disease patterns were then assessed, and we further co-clustered the SNP sets into a genetic network to topologically elucidate the genetic architecture composed of SNP sets. RESULTS: We identified 23 non-identical SNP sets with significant association with CHD or T2D (SNP-set based association test, P < 3.70 × [Formula: see text]). Among them, disease patterns involving CHD and T2D were related to distinct SNP sets (Hypergeometric test, P < 2.17 × [Formula: see text]). Accordingly, numerous genes (e.g., KLKs, GRM8, SHANK2) and pathways (e.g., fatty acid metabolism) were diversely implicated in different subtypes and related pathophysiological processes. Finally, we showed that the genetic architecture for disease patterns of CHD and T2D was composed of disjoint genetic networks (heterogeneity), with common genes contributing to it (pleiotropy). CONCLUSION: The SNP-set approach deciphered the complexity of both genotype and phenotype as well as their complex relationships. Different disease patterns of CHD and T2D share distinct genetic architectures, for which lipid metabolism related to fibrosis may be an atherogenic pathway that is specifically activated by diabetes. Our findings provide new insights for exploring new biological pathways.

Linear and nonlinear analyses of the association between low-density lipoprotein cholesterol and diabetes: The spurious U-curve in observational study.

Objective: Hyperlipidemia is traditionally considered a risk factor for diabetes. The effect of low-density lipoprotein cholesterol (LDL-C) is counterintuitive to diabetes. We sought to investigate the relationship between LDL-C and diabetes for better lipid management. Methods: We tested the shape of association between LDL-C and diabetes and created polygenic risk scores of LDL-C and generated linear Mendelian randomization (MR) estimates for the effect of LDL-C and diabetes. We evaluated for nonlinearity in the observational and genetic relationship between LDL-C and diabetes. Results: Traditional observational analysis suggested a complex non-linear association between LDL-C and diabetes while nonlinear MR analyses found no evidence for a non-linear association. Under the assumption of linear association, we found a consistently protective effect of LDL-C against diabetes among the females without lipid-lowering drugs use. The ORs were 0.84 (95% CI, 0.72-0.97, P=0.0168) in an observational analysis which was more prominent in MR analysis and suggested increasing the overall distribution of LDL-C in females led to an overall decrease in the risk of diabetes (P=0.0258). Conclusions: We verified the liner protective effect of LDL-C against diabetes among the females without lipid-lowering drug use. Non-linear associations between LDL-C against diabetes in observational analysis are not causal.

Identification of Novel Metabolic Subtypes Using Multi-Trait Limited Mixed Regression in the Chinese Population.

The aggregation and interaction of metabolic risk factors leads to highly heterogeneous pathogeneses, manifestations, and outcomes, hindering risk stratification and targeted management. To deconstruct the heterogeneity, we used baseline data from phase II of the Fangshan Family-Based Ischemic Stroke Study (FISSIC), and a total of 4632 participants were included. A total of 732 individuals who did not have any component of metabolic syndrome (MetS) were set as a reference group, while 3900 individuals with metabolic abnormalities were clustered into subtypes using multi-trait limited mixed regression (MFMR). Four metabolic subtypes were identified with the dominant characteristics of abdominal obesity, hypertension, hyperglycemia, and dyslipidemia. Multivariate logistic regression showed that the hyperglycemia-dominant subtype had the highest coronary heart disease (CHD) risk (OR: 6.440, 95% CI: 3.177-13.977) and that the dyslipidemia-dominant subtype had the highest stroke risk (OR: 2.450, 95% CI: 1.250-5.265). Exome-wide association studies (EWASs) identified eight SNPs related to the dyslipidemia-dominant subtype with genome-wide significance, which were located in the genes APOA5, BUD13, ZNF259, and WNT4. Functional analysis revealed an enrichment of top genes in metabolism-related biological pathways and expression in the heart, brain, arteries, and kidneys. Our findings provide directions for future attempts at risk stratification and evidence-based management in populations with metabolic abnormalities from a systematic perspective.

Genetic predisposition to adverse events in Chinese children aged 3-24 months after diphtheria, tetanus, acellular pertussis and haemophilus influenzae type b combined vaccination.

BACKGROUND: Post-vaccination safety is a major public health concern. The genetic predisposition on immune response has not been clearly identified. Clarifying whether individual genetic predisposition plays a role on adverse events (AEs) is critical for the prevention of AEs. METHODS: From July 2019 to June 2020, we performed a case-control study among children aged 3-24 months in seven Chinese provinces. Each child received a combination vaccination against diphtheria, tetanus, acellular pertussis, and Haemophilus influenzae type b (DTaP-Hib). Through daily telephone follow-up, we collected AEs within seven days. Oral swab samples were collected to investigate the effects of single nucleotide polymorphisms (SNPs) on the risk of AEs. RESULTS: 304 participants were included in the study. In univariate analysis, we discovered three protective SNPs (rs452204, OR = 0.67, P = 0.0352; rs9282763 and rs839, OR = 0.64, P = 0.0256) and one risk SNP (rs9610, OR = 2.20, P = 0.0397). In multivariate analysis, the effects of rs452204 and rs839 were found to be stable. The interaction between rs452204 and rs9610 was observed (OR = 7.25, 95% CI: 1.44-36.58, P = 0.0165). CONCLUSION: Genetic predisposition was associated with the risk of AEs after DTaP-Hib vaccination, emphasizing the potential application in the prevention of AEs.

Identifying novel genetic loci associated with polycystic ovary syndrome based on its shared genetic architecture with type 2 diabetes.

Genome-wide association studies (GWAS) have identified several common variants associated with polycystic ovary syndrome (PCOS). However, the etiology behind PCOS remains incomplete. Available evidence suggests a potential genetic correlation between PCOS and type 2 diabetes (T2D). The publicly available data may provide an opportunity to enhance the understanding of the PCOS etiology. Here, we quantified the polygenic overlap between PCOS and T2D using summary statistics of PCOS and T2D and then identified the novel genetic variants associated with PCOS behind this phenotypic association. A bivariate causal mixture model (MiXeR model) found a moderate genetic overlap between PCOS and T2D (Dice coefficient = 44.1% and after adjusting for body mass index, 32.1%). The conditional/conjunctional false discovery rate method identified 11 potential risk variants of PCOS conditional on associations with T2D, 9 of which were novel and 6 of which were jointly associated with two phenotypes. The functional annotation of these genetic variants supports a significant role for genes involved in lipid metabolism, immune response, and the insulin signaling pathway. An expression quantitative trait locus functionality analysis successfully repeated that 5 loci were significantly associated with the expression of candidate genes in many tissues, including the whole blood, subcutaneous adipose, adrenal gland, and cerebellum. We found that SCN2A gene is co-localized with PCOS in subcutaneous adipose using GWAS-eQTL co-localization analyses. A total of 11 candidate genes were differentially expressed in multiple tissues of the PCOS samples. These findings provide a new understanding of the shared genetic architecture between PCOS and T2D and the underlying molecular genetic mechanism of PCOS.

Quality Evaluation and Reporting Specification for Real-World Studies of Traditional Chinese Medicine.

In recent years, the real-world studies (RWS) have attracted extensive attention, and the real-world evidence (RWE) has been accepted to support the drug development in China and abroad. However, there is still a lack of standards for the evaluation of the quality of RWE. It is necessary to formulate a quality evaluation and reporting specification for RWE especially in traditional Chinese medicine (TCM). To this end, under the guidance of China Association of Chinese Medicine, the Quality Evaluation and Reporting Specification for Real-World Evidence of Traditional Chinese Medicine (QUERST) Group, including 24 experts (clinical epidemiologists, clinicians, pharmacologists, ethical reviewer and statisticians), was established to develop the specification. This specification contains the listing of classification of RWS design and RWE, the general principles and methods of RWE quality evaluation (26 tools or scales), 25 types of bias in RWS, the special considerations in evaluating the quality of RWE of TCM, and the 19 reporting standards of RWE. This specification aims to propose the quality evaluation principles and key points of RWE, and provide guidance for the proper use of RWE in the development of TCM new drugs.

Nonalcoholic fatty liver disease and cardiovascular diseases: A Mendelian randomization study.

BACKGROUND: Evidence suggests that nonalcoholic fatty liver disease (NAFLD) is associated with cardiovascular diseases (CVDs). However, the results are inconsistent, and the causality remains to be established. OBJECTIVE: We aimed to investigate the potential causal relationship between NAFLD and CVDs, including arterial stiffness, coronary artery disease, heart failure, stroke, ischemic stroke and its subtypes using two-sample Mendelian randomization (MR). METHODS: Genetic instruments were used as proxies for NAFLD. Publicly available summary-level data were obtained from the UK Biobank, the CARDIoGRAMplusC4D Consortium, the MEGASTROKE Consortium, and other consortia. Six complementary MR methods were performed, including inverse variance weighted method (IVW), MR-Egger, weighted median, weighted mode, MR-PRESSO, and MR-RAPS. RESULTS: NAFLD was significantly associated with arterial stiffness (ß = 0.04 [95%CI, 0.02-0.06], P = 5.53E-04). Moreover, the results remained consistent and robust in the sensitivity analysis. As for heart failure, the IVW method suggested that NAFLD was significantly associated with heart failure (OR = 1.08, 95%CI: 1.02-1.14, P = 0.005) in the absence of pleiotropy. However, there were no significant associations of NAFLD with coronary artery disease, stroke, ischemic stroke, or any ischemic stroke subtype. CONCLUSION: The MR study supported the causal effect of NAFLD on arterial stiffness. However, the study did not provide enough evidence suggesting the causal associations of NAFLD with heart failure, coronary artery disease, and any stroke subtypes.

Integrative Identification of Genetic Loci Jointly Influencing Diabetes-Related Traits and Sleep Traits of Insomnia, Sleep Duration, and Chronotypes.

Accumulating evidence suggests a relationship between type 2 diabetes mellitus and sleep problems. A comprehensive study is needed to decipher whether shared polygenic risk variants exist between diabetic traits and sleep traits. METHODS: We integrated summary statistics from different genome-wide association studies and investigated overlap in single-nucleotide polymorphisms (SNPs) associated with diabetes-related traits (type 2 diabetes, fasting glucose, fasting insulin, and glycated hemoglobin) and sleep traits (insomnia symptoms, sleep duration, and chronotype) using a conditional/conjunctional false discovery rate approach. Pleiotropic genes were further evaluated for differential expression analysis, and we assessed their expression pattern effects on type 2 diabetes by Mendelian randomization (MR) analysis. RESULTS: We observed extensive polygenic pleiotropy between diabetic traits and sleep traits. Fifty-eight independent genetic loci jointly influenced the risk of type 2 diabetes and the sleep traits of insomnia, sleep duration, and chronotype. The strongest shared locus between type 2 diabetes and sleep straits was FTO (lead SNP rs8047587). Type 2 diabetes (z score, 16.19; P = 6.29 × 10-59) and two sleep traits, sleep duration (z score, -6.66; P = 2.66 × 10-11) and chronotype (z score, 7.42; P = 1.19 × 10-13), were shared. Two of the pleiotropic genes, ENSA and PMPCA, were validated to be differentially expressed in type 2 diabetes, and PMPCA showed a slight protective effect on type 2 diabetes in MR analysis. CONCLUSIONS: Our study provided evidence for the polygenic overlap between diabetic traits and sleep traits, of which the expression of PMPCA may play a crucial role and provide support of the hazardous effect of being an "evening" person on diabetes risk.