Global burden of disease study analysis of thyroid cancer burden across 204 countries and territories from 1990 to 2019.

Background: The purpose of this study is to assess the burden of thyroid cancer over the course of 30 years in 204 countries and territories. Methods: Data from the Global Burden of Disease (GBD) 2019 database was analyzed to extract information on prevalence, deaths, DALYs(disability-adjusted life-years), YLL(years of life los), YLD(years lived with disability), and their corresponding age-standardized rates at global, regional, and national levels. The primary focus of the study was to examine trends in thyroid cancer from 1990 to 2019, specifically looking at the Estimated Annual Percentage Change (EAPC) for ASPR, ASDR, and ASDR. Additionally, the study investigated the relationship between cancer burden and the Socio-Demographic Index (SDI). Results: Globally, there will be approximately 18.3 million thyroid cancer (TC) cases in 2019; China and the USA are projected to be the most significant with 310,327 and 220,711 cases (16.17 and 14.82 cases per 100,000 people, respectively).Over the period from 1990 to 2019, age-standardized prevalence rates exhibited a global rise, whereas deaths and DALYs saw a decrease(EAPC:1.63, -0.15- -0.14, respectively). Significantly, the age-standardized prevalence rate increased in 21 GBD regions, affecting 195 out of 204 countries or territories. Over the studied period, thyroid cancer cases, deaths, and DALYs were consistently higher among females than males. Furthermore, a higher Socio-demographic Index was associated with increased age-standardized prevalence rates.

Exercise may delay cognitive decline in Chinese older adults: a causal inference for ordered multi-categorical exposures with a Mendelian randomization approach.

The cognitive problems are prominent in the context of global aging, and the traditional Mendelian randomization method is not applicable to ordered multi-categorical exposures. Therefore, we aimed to address this issue through the development of a method and to investigate the causal inference of cognitive-related lifestyle factors. The study sample was derived from the Chinese Longitudinal Healthy Longevity Survey, which included 897 older adults aged 65 + . This study used genome-wide association analysis to screen genetic loci as instrumental variables and innovatively combined maximum likelihood estimation to infer causal associations between ordered multi-categorical exposures (diet, exercise, etc.) and continuous outcomes (cognitive level). The causal inference method for ordered multi-categorical exposures developed in this study was simple, easy to implement, and able to effectively and reliably discover the potential causal associations between variables. Through this method, we found a potential positive causal association between exercise status and cognitive level in Chinese older adults ( ß ^ = 1.883, 95%CI 0.182-3.512), in which there was no horizontal pleiotropy (p = 0.370). The study provided a causal inference method applicable to ordered multi-categorical exposures, that addressed the limitations of the traditional Mendelian randomization method.

Effects of genetically proxied lipid-lowering drugs on acute myocardial infarction: a drug-target mendelian randomization study.

OBJECTIVE: High low-density-lipoprotein (LDL) cholesterol has been associated with an increased risk of coronary artery diseases (CAD) including acute myocardial infarction (AMI). However, whether lipids lowering drug treatment is causally associated with decreased risk of AMI remains largely unknown. We used Mendelian randomization (MR) to evaluate the influence of genetic variation affecting the function of lipid-lowering drug targets on AMI. METHODS: Single-nucleotide polymorphisms (SNPs) associated with lipids as instruments were extracted from the Global Lipids Genetics Consortium (GLGC). The genome-wide association study (GWAS) data for AMI were obtained from UK Biobank. Two sample MR analysis was used to study the associations between high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides (TG) with AMI (n = 3,927). Genetic variants associated with LDL cholesterol at or near drug target gene were used to mimic drug effects on the AMI events in drug target MR. RESULTS: Genetically predicted higher LDL-C (per one SD increase in LDL-C of 38.67 mg/dL, OR 1.006, 95% CI 1.004-1.007) and TG (per one SD increase in TG of 90.72 mg/dL, 1.004, 1.002-1.006) was associated with increased risk of AMI, but decreased risk for higher HDL-C (per one SD increase in HDL-C of 15.51 mg/dL, 0.997, 0.995-0.999) in univariable MR. Association remained significant for LDL-C, but attenuated toward the null for HDL-C and TG in multivariable MR. Genetically proxied lower LDL-C with genetic variants at or near the PCSK9 region (drug target of evolocumab) and NPC1L1 (drug target of ezetimibe) were associated with decreased risk of AMI (0.997, 0.994-0.999 and 0.986, 0.975-0.998, respectively), whereas genetic variants at HMGCR region (drug target of statin) showed marginal association with AMI (0.995, 0.990-1.000). After excluding drug target-related SNPs, LDL-C related SNPs outside the drug target region remained a causal effect on AMI (0.994, 0.993-0.996). CONCLUSIONS: The findings suggest that genetically predicted LDL-C may play a predominant role in the development of AMI. The drug MR results imply that ezetimibe and evolocumab may decrease the risk of AMI due to their LDL-C lowering effect, and there are other non-drug related lipid lowering pathways that may be causally linked to AMI.

Genetically determined blood pressure, antihypertensive drug classes, and frailty: A Mendelian randomization study.

Observational studies have suggested that the use of antihypertensive drugs was associated with the risk of frailty; however, these findings may be biased by confounding and reverse causality. This study aimed to explore the effect of genetically predicted lifelong lowering blood pressure (BP) through different antihypertensive medications on frailty. One-sample Mendelian randomization (MR) and summary data-based MR (SMR) were applied. We utilized two kinds of genetic instruments to proxy the antihypertensive medications, including genetic variants within or nearby drugs target genes associated with systolic/diastolic BP, and expression level of the corresponding gene. Among 298,618 UK Biobank participants, one-sample MR analysis observed that genetically proxied BB use (relative risk ratios, 0.76; 95% CI, 0.65-0.90; p = 0.001) and CCB use (0.83; 0.72-0.95; p = 0.007), equivalent to a 10-mm Hg reduction in systolic BP, was significantly associated with lower risk of pre-frailty. In addition, although not statistically significant, the effect directions of systolic BP through ACEi variants (0.72; 0.39-1.33; p = 0.296) or thiazides variants (0.74; 0.53-1.03; p = 0.072) on pre-frailty were also protective. Similar results were obtained in analyses for diastolic BP. SMR of expression in artery showed that decreased expression level of KCNH2, a target gene of BBs, was associated with lower frailty index (beta -0.02, p = 2.87 × 10-4). This MR analysis found evidence that the use of BBs and CCBs was potentially associated with reduced frailty risk in the general population, and identified KCNH2 as a promising target for further clinical trials to prevent manifestations of frailty.

Unveiling gene regulatory networks during cellular state transitions without linkage across time points.

Time-stamped cross-sectional data, which lack linkage across time points, are commonly generated in single-cell transcriptional profiling. Many previous methods for inferring gene regulatory networks (GRNs) driving cell-state transitions relied on constructing single-cell temporal ordering. Introducing COSLIR (COvariance restricted Sparse LInear Regression), we presented a direct approach to reconstructing GRNs that govern cell-state transitions, utilizing only the first and second moments of samples between two consecutive time points. Simulations validated COSLIR's perfect accuracy in the oracle case and demonstrated its robust performance in real-world scenarios. When applied to single-cell RT-PCR and RNAseq datasets in developmental biology, COSLIR competed favorably with existing methods. Notably, its running time remained nearly independent of the number of cells. Therefore, COSLIR emerges as a promising addition to GRN reconstruction methods under cell-state transitions, bypassing the single-cell temporal ordering to enhance accuracy and efficiency in single-cell transcriptional profiling.

Elevated blood remnant cholesterol and triglycerides are causally related to the risks of cardiometabolic multimorbidity.

The connection between triglyceride-rich lipoproteins and cardiometabolic multimorbidity, characterized by the concurrence of at least two of type 2 diabetes, ischemic heart disease, and stroke, has not been definitively established. We aim to examine the prospective associations between serum remnant cholesterol, triglycerides, and the risks of progression from first cardiometabolic disease to multimorbidity via multistate modeling in the UK Biobank. We also evaluate the causality of these associations via Mendelian randomization using 13 biologically relevant SNPs as the genetic instruments. Here we show that elevated remnant cholesterol and triglycerides are significantly associated with gradually higher risks of cardiometabolic multimorbidity, particularly the progression of ischemic heart disease to the multimorbidity of ischemic heart disease and type 2 diabetes. These results advocate for effective management of remnant cholesterol and triglycerides as a potential strategy in mitigating the risks of cardiometabolic multimorbidity.

PCSK9 increases vulnerability of carotid plaque by promoting mitochondrial dysfunction and apoptosis of vascular smooth muscle cells.

BACKGROUND: Proprotein convertase subtilisin/kexin type 9 (PCSK9) has been recognized as a novel lipid-lowing target. Recent clinical studies suggested the value of inhibiting PCSK9 in decreasing the vulnerability of coronary plaques. However, the evidence of PCSK9-regulated evolution of unstable carotid plaques is unclear, which has limited the use of PCSK9 inhibitor in carotid plaques. This study aimed to determine the effect and molecular mechanisms of PCSK9 on vulnerability of carotid plaques, to provide potential therapeutic targets for stabilizing carotid plaques. METHODS: The expression of PCSK9 in stable and unstable carotid plaques were examined in tissue and plasma. Human aortic vascular smooth muscle cells (VSMCs) and carotid VSMCs were employed to transfect lentivirus for overexpression and knockdown of PCSK9, respectively. Morphological and functional changes of mitochondria were observed by live-cell imaging. Cell apoptosis was evaluated by propidium iodide staining. RNA-sequencing and biological examinations were performed to explore and validate the underlying mechanisms. Truncated plasmids were employed to identify the functional domain of PCSK9 in regulation of VSMCs' mitochondrial morphology, function and apoptosis. RESULTS: Clinically, PCSK9 was closely related with vulnerability of human carotid plaques. Increased expression of PCSK9 in human VSMCs was accompanied by higher level of apoptosis. At subcellular level of VSMCs, the morphology of mitochondria was shifted toward the fission state, followed by mitochondrial dysfunction. Inhibition of p38 MAPK activation partially rescued the above morphological and behavioral changes caused by PCSK9. Furthermore, inhibiting of dynamin-related protein 1 (DRP1) attenuated PCSK9-related mitochondrial dysfunction and cell apoptosis. The 1-149aa domain of PCSK9 protein was essential to achieve functional regulation to VSMCs. CONCLUSION: Our findings demonstrated that PCSK9 induced morphology-related mitochondrial dysfunction and apoptosis of VSMCs, which may be related to increased vulnerability of carotid plaque.

Associations of healthy aging index and all-cause and cause-specific mortality: a prospective cohort study of UK Biobank participants.

The healthy aging index (HAI) has been recently developed as a surrogate measure of biological age. However, to what extent the HAI is associated with all-cause and cause-specific mortality and whether this association differs in younger and older adults remains unknown. We aimed to quantify the association between the HAI and mortality in a population of UK adults. In the prospective cohort study, data are obtained from the UK Biobank. Five HAI components (systolic blood pressure, reaction time, cystatin C, serum glucose, forced vital capacity) were scored 0 (healthiest), 1, and 2 (unhealthiest) according to sex-specific tertiles or clinically relevant cut-points and summed to construct the HAI (range 0-10). Cox proportional hazard regression models were used to estimate the associations of the HAI with the risk of all-cause and cause-specific mortality. 387,794 middle-aged and older participants were followed up for a median of 8.9 years (IQR 8.3-9.5). A total of 14,112 all-cause deaths were documented. After adjustments, each 1-point increase in the HAI was related to a higher risk of all-cause mortality (hazards ratio [HR], 1.17; 95%CI, 1.15-1.18). Such association was stronger among adults younger than 60 years (1.19, 1.17-1.21) than that among those 60 years and older (1.15, 1.14-1.17) (P interaction < 0.001). For each unit increment of the HAI, the multivariate-adjusted HRs for risk of death were 1.28 (1.25-1.31) for cardiovascular diseases, 1.09 (1.07-1.10) for cancer, 1.36 (1.29-1.44) for digestive disease, 1.42 (1.35-1.48) for respiratory disease, 1.42 (1.33-1.51) for infectious diseases, and 1.15 (1.09-1.21) for neurodegenerative disease, respectively. Our findings indicate that the HAI is positively associated with all-cause and cause-specific mortality independent of chronological age. Our results further underscore the importance of effective early-life interventions to slow aging and prevent premature death.

Identifying Potential Causal Effects of Telomere Length on Health Outcomes: A Phenome-Wide Investigation and Mendelian Randomization Study.

BACKGROUND: Telomere length has been linked to various health outcomes. To comprehensively investigate the causal effects of telomere length throughout the human disease spectrum, we conducted a phenome-wide Mendelian randomization study (MR-PheWAS) and a systematic review of MR studies. METHODS: We conducted a PheWAS to screen for associations between telomere length and 1 035 phenotypes in the UK Biobank (n = 408 354). The exposure of interest was the genetic risk score (GRS) of telomere length. Observed associations passing multiple testing corrections were assessed for causality by 2-sample MR analysis. A systematic review of MR studies on telomere length was performed to harmonize the published evidence and complement our findings. RESULTS: Of the 1 035 phenotypes tested, PheWAS identified 29 and 78 associations of telomere length GRS at a Bonferroni- and false discovery rate-corrected threshold; 24 and 66 distinct health outcomes were causal in the following principal MR analysis. The replication MR using data from the FinnGen study provided evidence of causal effects of genetically instrumented telomere length on 28 out of 66 outcomes, including decreased risks of 5 diseases in respiratory diseases, digestive diseases, and myocardial infarction, and increased risks of 23 diseases, mainly comprised neoplasms, diseases of the genitourinary system, and essential hypertension. A systematic review of 53 MR studies found evidence to support 16 out of the 66 outcomes. CONCLUSIONS: This large-scale MR-PheWAS identified a wide range of health outcomes that were possibly affected by telomere length, and suggested that susceptibility to telomere length may vary across disease categories.

Polysocial and Polygenic Risk Scores and All-Cause Dementia, Alzheimer's Disease, and Vascular Dementia.

BACKGROUND: To establish a polysocial risk score (PsRS) incorporating various social factors for capturing the dementia risk and investigate the benefits of favorable social conditions across different genetic backgrounds. METHODS: This prospective cohort study comprised 345 439 participants initially free of dementia from the UK Biobank. A total of 10 social factors were summed to create a PsRS. A polygenic risk score (PRS) was constructed based on genome-wide significant variants. RESULTS: During a median follow-up of 12.5 years, we documented 4 595 incident all-cause dementia events including 2 067 Alzheimer's disease (AD) events and 1 028 vascular dementia (VD) events. Each additional PsRS was associated with a 19% increased risk of all-cause dementia (hazard ratio [HR], 1.19; 95% confidence interval [CI], 1.17 to 1.21), a 13% increased risk of AD (1.13; 1.10 to 1.16), and a 24% increased risk of VD (1.24; 1.19 to 1.29). 29% (24% to 33%) of dementia cases, 22% (14% to 29%) of AD cases, and 39% (28% to 48%) of VD cases were associated with a disadvantageous social environment. In addition, among participants at a high genetic risk, the low social risk was linked to a lower incidence rate of all-cause dementia, AD, and VD compared to those who had a high social risk, with reductions of 67.8%, 64.5%, and 84.2%, respectively. CONCLUSIONS: The PsRS could be effectively used in discriminating individuals at high risk of dementia. Around a quarter of dementia events could have a connection with a disadvantageous social environment, especially for those genetically susceptible to dementia.

Frequency of Adding Salt to Foods, Genetic Susceptibility, and Incident Type 2 Diabetes: A Prospective Cohort Study.

CONTEXT: Excessive salt consumption is known to increase the risk of hypertension and cardiovascular disease, but the association between salt intake and incident type 2 diabetes has not been extensively researched. OBJECTIVE: In this study, we aimed to investigate the relationships between the frequency of adding salt to foods and incident type 2 diabetes, as well as any potential interactions with genetic predisposition. METHODS: We included 368 137 eligible participants, aged 37 to 73 years, from the UK Biobank. The frequency of adding salt to foods was assessed via a food frequency questionnaire. RESULTS: During a median follow-up of 12.6 years, we documented 10 981 incident type 2 diabetes cases. After adjustment for major confounders, participants who sometimes, usually, and always added salt to foods had 7% (hazard ratio [HR]: 1.07; 95% CI, 1.03-1.12), 9% (HR: 1.09; 95% CI, 1.03-1.16), 28% (HR: 1.28; 95% CI, 1.19-1.38) higher risks of developing type 2 diabetes, respectively, than those that never/rarely added salt to foods (P for trend < .001). We found these associations to be consistent across stratified and sensitivity analyses. However, we did not observe any statistically significant multiplicative or additive interactions between the frequency of adding salt to foods and genetic predisposition regarding incident type 2 diabetes. CONCLUSION: Our findings suggest that consuming salt regularly, regardless of genetic susceptibility, may increase the risk of type 2 diabetes. Therefore, public health interventions aimed at reducing excessive salt consumption may help prevent the onset of type 2 diabetes.

Advances in methodologies of negative controls: a scoping review.

OBJECTIVES: Negative controls are considered an important tool to mitigate biases in observational studies. The aim of this scoping review was to summarize current methodologies of negative controls (both negative control exposure [NCE] and negative control outcome [NCO]). STUDY DESIGN AND SETTING: We searched PubMed, Web of Science, Embase, and Cochrane Library (up to March 9, 2023) for articles on methodologies of negative controls. Two reviewers selected eligible studies and collected relevant data independently and in duplicate. We reported total numbers and percentages, and summarized methodologies narratively. RESULTS: A total of 37 relevant methodological articles were included in our review. These publications covered NCE (n = 11, 29.8%), NCO (n = 13, 35.1%), or both (n = 13, 35.1%), with most focused on bias detection (n = 14, 37.8%), bias correction (n = 16, 43.3%), and P value or confidence interval (CI) calibration (n = 5, 13.5%). For the two remaining articles (5.4%), one discussed bias detection and P value or CI calibration and the other covered all the three functions. For bias detection, the existence of an association between the NCE (NCO) and outcome (exposure) variables of interest simply indicates that results may suffer from confounding bias, selection bias and/or information bias. For bias correction, however, the algorithms of negative control methods need more stringent assumptions such as rank preservation, monotonicity, and linearity. CONCLUSION: Negative controls can be leveraged for bias detection, P value or CI calibration, and bias correction, among which bias correction has been the most studied methodologically. The current available methods need some stringent assumptions to detect or remove bias. More methodological research is needed to optimize the use of negative controls.

Leisure-Time Television Viewing and Computer Use, Family History, and Incidence of Dementia.

INTRODUCTION: Time spent on screen-based sedentary activities is significantly associated with dementia risk, however, whether the associations vary by family history (FHx) of dementia is currently unknown. We aimed to examine independent associations of two prevalent types of screen-based sedentary activities (television [TV] viewing and computer use) with dementia and assess the modifying effect of FHx. METHODS: We included 415,048 individuals free of dementia from the UK Biobank. Associations of TV viewing, computer use, and FHx with dementia risk were determined using Cox regression models. We estimated both multiplicative- and additive-scale interactions between TV viewing and computer use and FHx. RESULTS: During a median follow-up of 12.6 years, 5,549 participants developed dementia. After adjusting for potential confounding factors, we observed that moderate (2-3 h/day; hazard ratio [HR] 1.13, 95% confidence interval 0.03-1.23) and high (>3 h/day; 1.33, 1.21-1.46) TV viewing was associated with a higher dementia risk, compared with low (0-1 h/day) TV viewing. Using restricted cubic spline models, the relationship of TV viewing with dementia was nonlinear (relative to 0 h/day; p for nonlinear = 0.005). We found that >3 h/day of TV viewing was associated with a 42% (1.42, 1.18-1.71) higher dementia risk in participants with FHx while a 30% (1.30, 1.17-1.45) in those without FHx. For computer use, both low (0 h/day; 1.41, 1.33-1.50) and high (>2 h/day; 1.17, 1.05-1.29) computer use were associated with elevated dementia risk, compared with moderate (1-2 h/day) computer use. We observed a J-shaped relationship with dementia (relative to 2 h/day; p for nonlinear <0.001). Compared with 1-2 h/day of computer use, the HRs of dementia were 1.46 (1.29-1.65) and 1.10 (0.90-1.36) for 0 h/day and >2 h/day of computer use in participants with FHx, respectively, while the corresponding HRs were 1.40 (1.30-1.50) and 1.19 (1.06-1.33) in those without FHx. We observed a positive additive interaction (RERI 0.29, 0.06-0.53) between computer use and FHx, while little evidence of interaction between TV viewing and FHx. CONCLUSIONS: The time spent on TV viewing and computer use were independent risk factors for dementia, and the adverse effects of computer use and FHx were additive. Our findings point to new behavioral targets for intervention on preventing an early onset of dementia, especially for those with FHx.

New predictive models and indices for screening MAFLD in school-aged overweight/obese children.

Currently, most predictions of metabolic-associated fatty liver disease (MAFLD) in school-aged children utilize indicators that usually predict nonalcoholic fatty liver disease (NAFLD). The present study aimed to develop new predictive models and predictors for children with MAFLD, which could enhance the feasibility of MAFLD screening programs in the future. A total of 331 school-aged overweight/obese children were recruited from six primary schools in Ningbo city, China. Hepatic steatosis and fibrosis were detected with controlled attenuation parameter (CAP) and liver stiffness measurement (LSM), respectively. Machine learning methods were adapted to build a set of variables to predict MAFLD in children. Then, the area under the curve (AUC) of multiple models and indices was compared to predict pediatric MAFLD. Compared with non-MAFLD children, children with MAFLD had more obvious metabolic disturbances, as they had higher anthropometric indicators, alanine aminotransferase, fasting plasma glucose, and inflammation indicators (white blood cell count, hemoglobin, neutrophil count) (all P < 0.05). The optimal variables for all subjects selected by random forest (RF) were alanine aminotransferase, uric acid, insulin, and BMI. The logistic regression (LR) model performed best, with AUC values of 0.758 for males and 0.642 for females in predicting MAFLD. LnAI-BMI, LnAI, and LnAL-WHtR were approving indices for predicting pediatric MAFLD in all participants, boys and girls individually. CONCLUSIONS: This study developed LR models and sex-specific indices for predicting MAFLD in overweight/obese children that may be useful for widespread screening and identification of children at high risk of MAFLD for early treatment. WHAT IS KNOWN: • Most of the indicators predicting pediatric MAFLD are derived from the predictive indicators for NAFLD, but the diagnostic criteria for MAFLD and NAFLD are not exactly the same. • The accuracy of predictors based on routine physical examination and blood biochemical indicators to diagnose MAFLD is limited. WHAT IS NEW: • This study developed indicators based on routine examination parameters that have approving performance for MAFLD, with AUC values exceeding 0.70.

Proteome-Wide Mendelian Randomization Analysis Identified Potential Drug Targets for Atrial Fibrillation.

Background Finding effective and safe therapeutic drugs for atrial fibrillation (AF) is an important concern for clinicians. Proteome-wide Mendelian randomization analysis provides new ideas for finding potential drug targets. Methods and Results Using a proteome-wide Mendelian randomization approach, we assessed the genetic predictive causality between thousands of proteins and AF risk and found that genetically predicted plasma levels of phosphomevalonate kinase, tumor necrosis factor ligand superfamily member 12, sulfhydryl oxidase 2, interleukin-6 receptor subunit alpha, and low-affinity immunoglobulin gamma Fc region receptor II-b might decrease AF risk, while genetically predicted plasma levels of beta-mannosidase, collagen alpha-1(XV) chain, ANXA4 (annexin A4), COF2 (cofilin-2), and RAB1A (Ras-related protein Rab-1A) might increase AF risk (P<3.4×10-5). By using different Mendelian randomization methods and instrumental variable selection thresholds, we performed sensitivity analyses in 30 scenarios to test the robustness of positive findings. Replication analyses were also performed in independent samples to further avoid false-positive findings. Drugs targeting tumor necrosis factor ligand superfamily member 12, interleukin-6 receptor subunit alpha, low-affinity immunoglobulin gamma Fc region receptor II-b, and annexin A4 are approved or in development. The results of the phenome-wide Mendelian randomization analysis showed that changing the plasma levels of phosphomevalonate kinase, cofilin-2, annexin A4, Ras-related protein Rab-1A, sulfhydryl oxidase 2, and collagen alpha-1(XV) chain did not increase the risk of other diseases while decreasing the risk of AF. Conclusions We found a significant causal association between genetically predicted levels of 10 plasma proteins and AF risk. Four of these proteins have drugs targeting them that are approved or in development, and our results suggest the potential for these drugs to treat AF or cause AF. Sulfhydryl oxidase 2, low-affinity immunoglobulin gamma Fc region receptor II-b, and beta-mannosidase have not been suggested by previous laboratory or epidemiological studies to be associated with AF and may reveal new pathophysiological pathways as well as therapeutic targets for AF.

Blood phytosterols in relation to cardiovascular diseases and mediating effects of blood lipids and hematological traits: a Mendelian randomization analysis.

BACKGROUND: Short-term clinical trials have shown the cholesterol-lowering potentials of phytosterols, but their impacts on cardiovascular disease (CVD) remain controversial. This study used the Mendelian randomization (MR) to investigate the relationships between genetic predisposition to blood sitosterol concentration and 11 CVD endpoints, along with the potential mediating effects of blood lipids and hematological traits. METHODS: Random-effect inverse-variance weighted method was used as the main analysis of MR. Genetic instruments of sitosterol (seven SNPs, F = 253, and R2 = 15.4 %) were derived from an Icelandic cohort. Summary-level data of the 11 CVDs were obtained from UK Biobank, FinnGen, and publicly available genome-wide association study results. RESULTS: Genetically predicted one unit increment in log-transformed blood total sitosterol was significantly associated with a higher risk of coronary atherosclerosis (OR: 1.52; 95 % CI: 1.41, 1.65; n = 667,551), myocardial infarction (OR: 1.40; 95 % CI: 1.25, 1.56; n = 596,436), all coronary heart disease (OR: 1.33; 95 % CI: 1.22, 1.46; n = 766,053), intracerebral hemorrhage (OR: 1.68; 95 % CI: 1.24, 2.27; n = 659,181), heart failure (OR: 1.16; 95 % CI: 1.08, 1.25; n = 1,195,531), and aortic aneurysm (OR: 1.74; 95 % CI: 1.42, 2.13; n = 665,714). Suggestive associations were observed for an increased risk of ischemic stroke (OR: 1.06; 95 % CI: 1.01, 1.12; n = 2,021,995) and peripheral artery disease (OR: 1.20; 95 % CI: 1.05, 1.37; n = 660,791). Notably, blood non-high-density lipoprotein cholesterol (nonHDL-C) and apolipoprotein B mediated about 38-47 %, 46-60 %, and 43-58 % of the associations between sitosterol and coronary atherosclerosis, myocardial infarction, and coronary heart disease, respectively. However, the associations between sitosterol and CVDs were less likely to depend on hematological traits. CONCLUSION: The study suggests that genetic predisposition to higher blood total sitosterol is linked to a greater risk of major CVDs. Moreover, blood nonHDL-C and apolipoprotein B might mediate a significant proportion of the associations between sitosterol and coronary diseases.

Hypothesis Testing for Progressive Kernel Estimation and VCM Framework.

Identifying an appropriate radius for unbiased kernel estimation is crucial for the efficiency of radiance estimation. However, determining both the radius and unbiasedness still faces big challenges. In this paper, we first propose a statistical model of photon samples and associated contributions for progressive kernel estimation, under which the kernel estimation is unbiased if the null hypothesis of this statistical model stands. Then, we present a method to decide whether to reject the null hypothesis about the statistical population (i.e., photon samples) by the F-test in the Analysis of Variance. Hereby, we implement a progressive photon mapping (PPM) algorithm, wherein the kernel radius is determined by this hypothesis test for unbiased radiance estimation. Secondly, we propose VCM+, a reinforcement of Vertex Connection and Merging (VCM), and derive its theoretically unbiased formulation. VCM+ combines hypothesis testing-based PPM with bidirectional path tracing (BDPT) via multiple importance sampling (MIS), wherein our kernel radius can leverage the contributions from PPM and BDPT. We test our new algorithms, improved PPM and VCM+, on diverse scenarios with different lighting settings. The experimental results demonstrate that our method can alleviate light leaks and visual blur artifacts of prior radiance estimate algorithms. We also evaluate the asymptotic performance of our approach and observe an overall improvement over the baseline in all testing scenarios.

Depression and risk of gastrointestinal disorders: a comprehensive two-sample Mendelian randomization study of European ancestry.

BACKGROUND: Major depressive disorder (MDD) is clinically documented to co-occur with multiple gastrointestinal disorders (GID), but the potential causal relationship between them remains unclear. We aimed to evaluate the potential causal relationship of MDD with 4 GID [gastroesophageal reflux disease (GERD), irritable bowel syndrome (IBS), peptic ulcer disease (PUD), and non-alcoholic fatty liver disease (NAFLD)] using a two-sample Mendelian randomization (MR) design. METHODS: We obtained genome-wide association data for MDD from a meta-analysis (N = 480 359), and for GID from the UK Biobank (N ranges: 332 601-486 601) and FinnGen (N ranges: 187 028-218 792) among individuals of European ancestry. Our primary method was inverse-variance weighted (IVW) MR, with a series of sensitivity analyses to test the hypothesis of MR. Individual study estimates were pooled using fixed-effect meta-analysis. RESULTS: Meta-analyses IVW MR found evidence that genetically predicted MDD may increase the risk of GERD, IBS, PUD and NAFLD. Additionally, reverse MR found evidence of genetically predicted GERD or IBS may increase the risk of MDD. CONCLUSIONS: Genetically predicted MDD may increase the risk of GERD, IBS, PUD and NAFLD. Genetically predicted GERD or IBS may increase the risk of MDD. The findings may help elucidate the mechanisms underlying the co-morbidity of MDD and GID. Focusing on GID symptoms in patients with MDD and emotional problems in patients with GID is important for the clinical management.

Sleep Patterns, Plasma Metabolome, and Risk of Incident Type 2 Diabetes Mellitus.

CONTEXT: A healthy sleep pattern has been related to a lower risk of type 2 diabetes mellitus (T2DM). OBJECTIVE: We aimed to identify the metabolomic signature for the healthy sleep pattern and assess its potential causality with T2DM. METHODS: This study included 78 659 participants with complete phenotypic data (sleep information and metabolomic measurements) from the UK Biobank study. Elastic net regularized regression was applied to calculate a metabolomic signature reflecting overall sleep patterns. We also performed genome-wide association analysis of the metabolomic signature and one-sample mendelian randomization (MR) with T2DM risk. RESULTS: During a median of 8.8 years of follow-up, we documented 1489 incident T2DM cases. Compared with individuals who had an unhealthy sleep pattern, those with a healthy sleep pattern had a 49% lower risk of T2DM (multivariable-adjusted hazard ratio [HR], 0.51; 95% CI, 0.40-0.63). We further constructed a metabolomic signature using elastic net regularized regressions that comprised 153 metabolites, and robustly correlated with sleep pattern (r = 0.19; P = 3×10-325). In multivariable Cox regressions, the metabolomic signature showed a statistically significant inverse association with T2DM risk (HR per SD increment in the signature, 0.56; 95% CI, 0.52-0.60). Additionally, MR analyses indicated a significant causal relation between the genetically predicted metabolomic signature and incident T2DM (P for trend < .001). CONCLUSION: In this large prospective study, we identified a metabolomic signature for the healthy sleep pattern, and such a signature showed a potential causality with T2DM risk independent of traditional risk factors.

Associations of Modified Healthy Aging Index With Major Adverse Cardiac Events, Major Coronary Events, and Ischemic Heart Disease.

Background The Healthy Aging Index (HAI) has been regarded as useful in capturing the health status of multiple organ systems. However, to what extent the HAI is associated with major cardiovascular events remains largely unknown. The authors constructed a modified HAI (mHAI) to quantify the association of physiological aging with major vascular events and explored how the effects of a healthy lifestyle can modify this association. Methods and Results The participants with either missing values of any individual mHAI component or major illnesses such as heart attack, angina and stroke, and self-reported cancer at baseline were excluded. The mHAI components include systolic blood pressure, reaction time, forced vital capacity, serum cystatin c, and serum glucose. The authors used Cox proportional hazard models to quantify the association of mHAI with major adverse cardiac events, major coronary events, and ischemic heart disease. Cumulative incidence at 5 and 10 years was estimated, and joint analyses were stratified by age group and 4 mHAI categories. The mHAI was significantly correlated with major cardiovascular events, which is a better reflection of the aging level of the body than chronological age. An mHAI was calculated in 338 044 participants aged 38 to 73 years in the UK Biobank. Each point increase in the mHAI was associated with a 44% higher risk of major adverse cardiac events (adjusted hazard ratio [aHR], 1.44 [95% CI, 1.40-1.49]), 44% higher risk of major coronary events (aHR, 1.44 [95% CI, 1.40-1.48]), and 36% higher risk of ischemic heart disease (aHR, 1.36 [95% CI, 1.33-1.39]). The percentage of population-attribution risk was 51% (95% CI, 47-55) for major adverse cardiac events, 49% (95% CI, 45-53) for major coronary events, and 47% (95% CI, 44-50) for ischemic heart disease, which means that a substantial portion of these events could be prevented. Systolic blood pressure was the factor most significantly associated with major adverse cardiac events (aHR, 1.94 [95% CI, 1.82-2.08]; percentage of population-attribution risk, 36%), major coronary events (aHR, 2.01 [95% CI, 1.85-2.17]; percentage of population-attribution risk, 38%), and ischemic heart disease (aHR, 1.80 [95% CI, 1.71-1.89]; percentage of population-attribution risk, 32%). A healthy lifestyle significantly attenuated mHAI associations with incidence of vascular events. Conclusions Our findings indicate that higher mHAI is associated with increased major vascular events. A healthy lifestyle may attenuate these associations.