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We aimed to investigate the association between polysocial risk score (PsRS), an estimator of individual-level exposure to cumulative social risks, and incident type 2 diabetes in the UK Biobank study.This study includes 319,832 participants who were free of diabetes, cardiovascular disease and cancer at baseline in the UK Biobank study. The PsRS was calculated by counting the 12 social determinants of health from three social risk domains (namely socioeconomic status, psychosocial factors, and neighbourhood and living environment) that had a statistically significant association with incident type 2 diabetes after Bonferroni correction. A healthy lifestyle score was calculated using information on smoking status, alcohol intake, physical activity, diet quality and sleep quality. A genetic risk score was calculated using 403 SNPs that showed significant genome-wide associations with type 2 diabetes in people of European descent. The Cox proportional hazards model was used to analyse the association between the PsRS and incident type 2 diabetes.During a median follow-up period of 8.7 years, 4427 participants were diagnosed with type 2 diabetes. After adjustment for major confounders, an intermediate PsRS (4-6) and high PsRS (≥7) was associated with higher risks of developing type 2 diabetes with the HRs being 1.38 (95% CI 1.26, 1.52) and 2.02 (95% CI 1.83, 2.22), respectively, compared with those with a low PsRS (≤3). In addition, an intermediate to high PsRS accounted for approximately 34% (95% CI 29, 39) of new-onset type 2 diabetes cases. A healthy lifestyle slightly, but significantly, mitigated PsRS-related risks of type 2 diabetes (pA higher PsRS was related to increased risks of type 2 diabetes. Adherence to a healthy lifestyle may attenuate elevated diabetes risks due to social vulnerability. Genetic susceptibility and disadvantaged social status may act synergistically, resulting in additional risks for type 2 diabetes.

The fat-to-muscle mass ratio (FMR), which integrates the antagonistic effects of fat and muscle mass, has been proposed as a useful indicator to assess disease risk independent of overall obesity. However, little is known about the association between FMR and dementia risk. We aimed to prospectively investigate the sex-specific associations between total and regional FMR and incident dementia.A total of 491 420 participants (223 581 men and 267 839 women; mean age 56.7 ± 8.2 and 56.3 ± 8.0 years old, respectively) free of dementia at baseline from the UK Biobank were included. Fat mass and muscle mass were measured using a bioelectrical impedance assessment device. Cox regression analyses were used to examine the associations of total and regional FMR with incident all-cause dementia, Alzheimer's disease (AD) and vascular dementia (VD). The shape of the associations of the continuous scale of FMR and incident dementia were examined using restricted cubic spline analysis.During a median 8.65 years of follow-up, we documented 2 225 incident all-cause dementia cases, including 836 AD and 468 VD cases. There was an L-shaped association between whole body FMR and all-cause dementia risk in both sexes after adjusting body mass index (BMI) and other covariates (P for non-linear0.001 in men and women), where all-cause dementia risk decreased steeply with increasing FMR and levelled off at around the medians (0.35 in men, 0.61 in women) with a hazard ratio (HR) of 0.78 (95% CI: 0.64, 0.96; P = 0.019) and 0.60 (0.47, 0.77;0.001) per 1 standard deviation (SD) increase in men and women, respectively. Compared with other body parts, FMR of the leg showed the strongest inverse associations [HR (95% CI; P) per 1 SD below the medians: 0.60 (0.48, 0.75;0.001); 0.61 (0.47, 0.79;0.001) in men and women, respectively]. Specifically, the inverse associations of whole body FMR on all-cause dementia risk were significant only among participants over the age of 60 (P for trend0.001). Multivariable adjusted Cox models showed inverse associations of whole body FMR with AD in men only (P for trend = 0.003), whereas no statistically significant decrease was detected in VD among men and women.Our analyses provide strong evidence for L-shaped associations of total and regional FMR with the development of dementia among participants aged 60 years or older independent of overall obesity.

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 for 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 two-sample MR analysis. A systematic review for 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 of neoplasms, diseases of the genitourinary system, and essential hypertension. Systematic review of 53 MR studies found evidence to support 16 out of the 66 outcomes. Conclusion 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.

Background: There is a growing interest in the linkage of cardiovascular health (CVH) with depression/anxiety but the evidence of the latest “Life’s Essential 8” is scarce. We aimed to evaluate prospective associations of “Life’s Essential 8” CVH score redefined in 2022 with risk of incident depression and anxiety. Methods: Based on the latest definition of CVH score (“Life’s Essential 8”), we calculated the total score (0-800 points) based on eight components (0-100 points/component) including diet, physical activity, smoking, sleep duration, body mass index, blood lipids, blood glucose, and blood pressure. Hospital records and mental health questionnaires were employed to yield the baseline prevalence and incidence of depression and anxiety. To address potential genetic confounding and gene-CVH interactions, we quantified genetic risk for both disorders using polygenic scores derived from genome-wide association studies. Results: Participants with a lower CVH score more often experienced depression, anxiety, and either disorder. During the follow-up, 17,554 incident events with symptoms of either disorder were recorded. Per 100-point decrease in CVH score was significantly associated with an increased risk of incident either disorder (Hazard ratio [HR]=1.149, 95% confidence interval [CI]:1.128-1.170), depression (HR=1.232, 95% CI:1.205-1.260), and anxiety (HR=1.045, 95% CI:1.018-1.072). Sleep duration was the key component related to the risk of depression/anxiety by providing much better estimates of the risks of depression/anxiety. A higher genetic risk could further significantly enhance the impact of worsened CVH on the incidences of either disorder and depression. Conclusions: Poor CVH is a risk factor for the incident late-life depression/anxiety symptoms of middle-aged and older adults and healthy behaviors especially sleep quality could be targeted for the risk assessment and intervention of depression/anxiety.

Theory predicts that biological processes of aging may contribute to poor mental health in late life. To test this hypothesis, we evaluated prospective associations between biological age and incident depression and anxiety in 424,299 UK Biobank participants. We measured biological age from clinical traits using the KDM-BA and PhenoAge algorithms. At baseline, participants who were biologically older more often experienced depression/anxiety. During a median of 8.7 years of follow-up, participants with older biological age were at increased risk of incident depression/anxiety (5.9% increase per standard deviation [SD] of KDM-BA acceleration, 95% confidence intervals [CI]: 3.3%–8.5%; 11.3% increase per SD of PhenoAge acceleration, 95% CI: 9.%–13.0%). Biological-aging-associated risk of depression/anxiety was independent of and additive to genetic risk measured by genome-wide-association-study-based polygenic scores. Advanced biological aging may represent a potential risk factor for incident depression/anxiety in midlife and older adults and a potential target for risk assessment and intervention.

Background The evidence is equivocal on the association between meat consumption and ischemic heart disease (IHD) risk. To what extent the variation of individuals' metabolic responses to the same diet may account for this association is not fully understood. We aim to identify metabolomic signatures characterizing consumption of unprocessed red meat and processed meat and whether such signatures are associated with IHD risk. Methods and Results We conducted a cohort study of 92 246 individuals (mean age, 56.1 years; 55.1% women) using the UK Biobank. During the median follow‐up of 8.74 years, 3059 incident IHD events were documented. Unprocessed red meat and processed meat consumption was assessed using a touchscreen dietary questionnaire. Plasma metabolome was profiled by high‐throughput nuclear magnetic resonance spectroscopy. Cox proportional hazards regression model was used to test the association of meat consumption with IHD. Genome‐wide association analysis and 1‐sample Mendelian randomization were performed for metabolomic signatures and causal association of signatures with IHD. Using elastic net regularized regressions, we constructed metabolomic signatures consisting of 157 and 142 metabolites for unprocessed red meat (Spearman correlation coefficient [ r ]=0.223) and processed meat ( r =0.329), respectively. These signatures showed positive associations with incident IHD (red meat related signature: hazard ratio [HR] per SD increment=1.11 [95% CI, 1.06–1.16], P P Conclusions We identify metabolomic signatures that reflect consumption of unprocessed red meat and processed meat, and these signatures are associated with an increased risk of IHD.

Background: Reproductive risk factors are associated with increased risk of cardiovascular disease (CVD) in women. However, the combined effects of the composite reproductive risk factors on CVD are unknown. This study was performed to construct a reproductive risk score (RRS) to measure reproductive status, examine the association between RRS and CVD, and explore the modification effect of healthy lifestyle on the association in women in the UK Biobank cohort. Methods: The RRS was constructed in 74 141 female participants with data about the items derived for the RRS in the UK Biobank. The RRS was derived from 17 baseline variables, all of which indicated women’s reproductive health status. We defined four categories of RRS status: low-risk group (score 0–1); low-intermediate group (score 2–3); high-intermediate group (score 4–5); and high-risk group (score 6–13). We also constructed a healthy lifestyle score (HLS) with five related factors, and categorized into unhealthy lifestyle group (score: 0–1), intermediate lifestyle group (score: 2–3) and healthy lifestyle group (score: 4–5). Findings: Each point increase in the RRS was associated with a 22% higher risk of CVD (adjusted hazard ratio (aHR): 1.22; 95% confidence interval (CI): 1.16 to 1.28), 23% higher risk of IHD (1.23; 1.17 to 1.31) and 19% higher risk of stroke (1.19; 1.07 to 1.32). The percentage population-attribution risks (PAR%) were 16% (95% CI: 8 to 24) for CVD, 15% (95% CI: 6 to 24) for IHD and 18% (95% CI: 1 to 33) for stroke. A healthy lifestyle significantly attenuated RRS associations with the incidence of CVD and IHD. The attributable proportions due to additive interaction ( P < 0.001) between RRS and HLS were 0.14 (95% CI: 0.07 to 0.22) for CVD and 0.15 (95% CI: 0.09 to 0.23) for IHD, respectively. Interpretation: High RRS was associated with increased risks of CVD, IHD and stroke in female participants in the UK Biobank. The early-stage identification of women with reproductive risk using synthesised indicators and appropriate healthy lifestyle interventions could be useful for the prevention of early CVD and the extension of healthy active life expectancy. Funding: This study was supported by grants from the National Key R&D Program of China (2020YFC2003401) and the High-performance Computing Platform of Peking University. The funders had no role in the study design, data collection, data analysis and interpretation, writing of the report or the decision to submit the article for publication.

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.

Objective: To construct a reproductive risk score (RRS) and an air pollution score (APS) and assess independent and joint associations between the two with incident COPD risk. Design: Population-based prospective cohort study. Setting: UK Biobank. Population: 78,218 female participants aged 40–69 years without baseline COPD recruited between 2006 to 2010. Methods: RRS was constructed by 17 women’s reproductive health-related items, and APS incorporating PM , PM , PM , NO , and NO was calculated to assess the joint exposure level. The associations of RRS and APS with COPD were examined by Cox proportional hazards regression. Main Outcome Measures: The outcome of the incident COPD was identified through the in-patient hospital register. Results: Higher RRS was associated with an increased risk of COPD (adjusted HR: 1.15, 95% CI: 1.12-1.19, P trend < 0.001). A dose-response manner can be observed between higher quintile APS and increased COPD risk (P trend < 0.001). The RERI of 0.030 (95% CI: 0.012-0.048) showed additive interaction between RRS and APS on COPD was significant. In the joint analysis, the combinations of both higher RRS and APS signified higher incident COPD risk. Conclusions: High RRS and high APS were associated with increased COPD risks in a dose-response pattern. Using comprehensive indicators to identify women’s reproductive risk factors, together with the control of air pollution, is effective for COPD prevention.

Depression and anxiety are two mental disorders that are often comorbid. However, the associations of long-term air pollution exposure with depression and anxiety remain inconclusive.We conducted a cross-sectional and prospective study to examine the associations of ambient exposure to particulate matter (PM) with a diameter ofThis study included 398,241 participants from the UK Biobank, 128,456 of whom participated the 7-y online mental health survey. A total of 345,876 individuals were free of depression and anxiety at baseline; of those, 16,185 developed incident mental disorders during a median of 8.7 y of follow-up. Depression and anxiety were assessed using hospital admission records and mental health questionnaires. Associations of air pollution with prevalent and incident mental disorders were examined using logistic regression and Cox regression models, respectively.Elevated levels of the five air pollutants were associated with higher odds of mental disorders at baseline. Levels of four pollutants but notTo our knowledge, this research is one of the largest cohort studies that demonstrates an association between mental health disorders and exposure to long-term air pollution, which could be further enhanced by genetic predisposition. https://doi.org/10.1289/EHP10391.

Objective Lifestyle factors have been associated with colorectal cancer (CRC) risk. The majority of previous studies did not consider the complex nature of sleep pattern. We aimed to examine the relationship between sleep pattern and CRC events. Methods The study included 502,504 individuals in the UK Biobank. A healthy sleep score was created by combining chronotype, sleep duration, insomnia, snoring, and excessive daytime sleepiness. Healthy sleep factors were defined as sleep 7 to 8 h per day; never/rarely or sometimes insomnia symptoms; no snoring; no excessive daytime sleepiness. Healthy lifestyle scores were developed by combing physical activities, diet, drinking, smoking and obesity. Using Cox proportional hazards regression, we computed hazard ratios (HRs) to examine the associations of the sleep patterns, healthy lifestyle with incidence of CRC. Results The healthy sleep score was inversely associated with CRC events. The HRs for CRC were 0.884 (95% CI, 0.863–0.906) and 0.927 (95% CI, 0.899–0.956) for a 1-point increase in the healthy sleep score among males and females. When analyzing sleep components, sleeping 7 to 8 h/d, no frequent insomnia, no snoring, and no frequent daytime sleepiness were independently associated with 10%, 14%, 11%, and 14% lower risk of CRC. Healthy lifestyle scores were also inversely associated with the incidence of CRC across all models. Conclusions Sleep pattern and lifestyle were significantly correlated with the risk of CRC. The healthier the lifestyle and sleep pattern were, the lower the CRC risk was.

BackgroundCardiometabolic multimorbidity (CMM) with at least two cardiometabolic diseases (CMDs) including type II diabetes (T2D), ischemic heart disease (IHD), and stroke, is a global health problem with multiplicative mortality risk and deserves to be investigated as a top priority. Although air pollution is a leading modifiable environmental risk for individual CMD, its impacts on CMM progression were poorly understood.ObjectiveTo elucidate the impact of air pollution on CMM progression, individually and in the context of genetic preposition.DesignMulti-state modeling cohort study.SettingData were extracted from the UK Biobank.Participants415,855 eligible UK Biobank adults that were free of CMDs at baseline.MeasurementsAnnual concentrations of particulate matter (PM) with a diameter of ≤2.5 μm (PM2.5), 2.5-10 μm (PM2.5-10), and ≤10 μm (PM10), and nitrogen oxides (NOx and NO2) were estimated using Land Use Regression model.ResultsDuring a median follow-up of 8.93 years, 33,375 participants had a first CMD (FCMD), and 3,257 subsequently developed CMM. PM2.5, PM10, NO2, and NOx levels, as well as their combined exposure were associated with increased FCMD risks and even higher risks of CMM. Particularly, per a 5-μg/m3 increase in PM2.5, risks for FCMD and CMM increased by 27% (95% confidence interval: 20%-34%) and 41% (18%-68%), respectively. By FCMD types, participants with IHD had a higher risk of CMM than those with T2D or stroke. Eighty-five CMD-related genetic variants were associated with CMM trajectories in our study and associations of air pollution with FCMD and CMM risks could be aggravated progressively with increasing genetic risks.LimitationsOther major air pollutants including ozone and SO2 were not considered due to the data availability.ConclusionsAir pollution has profound adverse health impacts on the progression of CMM through multi-stage dynamics, especially for individuals with IHD and high genetic risk.

Background Rapid population ageing has raised the proportion of older former smokers considerably, but a comprehensive assessment tool of former smoking-related health risks is absent. Objective We utilised the large-scale data of UK Biobank and ESTHER study to build a former smoking score (FSS) for older former smokers using three major former smoking traits: pack-years, smoking duration and time since smoking cessation. Design UK Biobank and ESTHER study are two cohorts of older adults with 502,528 and 9,940 participants from the UK and Germany, respectively. Methods Smoking history and covariates were retrieved from the self-administrated questionnaires and mortality and morbidity data were obtained through regular linkages to hospital records. Results We constructed the FSS based on the 94,446 former smokers of UK Biobank by retrieving the averaged effect estimates of each trait with a 100-time random sampling. This score was robustly associated with higher risks of mortality and incidence of major smoking-related diseases, outperforming each trait. In the validation panel of 2,683 former smokers from ESTHER study, the FSS was highly predictive of mortality and morbidities. Particularly, compared with the 1st quartile of the FSS group, the 4th quartile group had 114.1, 104.5 and 158.9% higher risks of all-cause, CVD and cancer mortality, respectively, and 41.9, 31.9, 52.4 and 831.3% higher risks of incident CVD, type 2 diabetes, any cancers and lung cancer, respectively. Conclusions Our study demonstrates the large potential of refined risk assessment of former smokers by more comprehensive consideration of the major traits of former smoking.

ObjectiveTo explore the correlation between the ideal cardiovascular health metrics (ICVHMs) and the incidence of colorectal cancer (CRC) among people aged 50 years or older.DesignProspective cohort study.SettingThe UK Biobank, a prospective cohort of middle-aged participants recruited between 2006 and 2010.ParticipantsThe study included 342 226 participants from the UK Biobank aged 50 years or older without prevalent cancer.ExposureThe ICVHMs consist of four behavioural factors (abstinence from smoking, ideal body mass index (BMI), physical activity at goal and consumption of healthy diet) and three cardiometabolic factors (untreated total cholesterol Main outcomesThe outcome was ascertained by linkage to cancer and death registries using the International Classification of Diseases, Tenth codes C18–C20.ResultsDuring a median follow-up time of 8.72 years, 3060 CRC cases were identified. Compared with the reference (participants with ICVHMs ≤2), the multivariable-adjusted HRs for subgroups with 3, 4, 5 and ≥6 ICVHM factors were 0.98 (95% CI 0.85 to 1.12), 0.90 (95% CI 0.77 to 1.02), 0.85 (95% CI 0.71 to 0.98) and 0.69 (95% CI 0.48 to 0.90), respectively. Among the seven ICVHM factors, lower BMI, healthier diet and ideal fasting plasma glucose were significantly associated with lower risk of CRC (HR: 0.86, 95% CI 0.78 to 0.95; HR: 0.92, 95% CI 0.84 to 0.99; HR: 0.90, 95% CI 0.80 to 0.99).ConclusionsAdherence to the ICVHMs was associated with a lower risk of CRC among people aged 50 years or older. Among the seven ICVHM factors, BMI, diet and fasting plasma glucose played a more critical role in the prevention of CRC. These findings imply that adherence to ICVHMs should be encouraged to reduce the burden of cardiovascular disease as well as CRC.

Previous studies have shown certain exposure factors (such as lifestyle and metabolism) are associated with colorectal cancer (CRC) events. However, the application of the exposome theoretical frame and the extent to which the exposome domain can modulate the risk of CRC remain unknown. Our study aimed to construct valid exposome measurements and examine the relationship between exposome counts and the risk of CRC. This study included 273,342 individuals in the UK Biobank. We used exploratory factor analysis to identify a valid construct of exposome factors. We then summed the exposome counts within each domain. Cox proportional hazard models were used to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) of CRC risk related to the exposome factors and counts. During an 8.69 year median follow-up, 8642 CRC cases were identified. Seven domains were extracted from 18 variables, including air pollution, noise pollution, ecosystem, lifestyle, tobacco and alcohol use, social economics, and social support. The Cox model results showed that the ecosystem was positively related to the reduced CRC risk (HR=0.97; 95% CI: 0.949–0.991). Similar results were also found among the domains of healthy lifestyles (HR=0. 873; 95% CI: 0.854–0.893), and no tobacco and alcohol use (HR=0.880; 95% CI: 0.862–0.899). The disadvantageous social economic (HR=1.068; 95% CI: 1.046–1.090) and insufficient social support domains (HR=1.067; 95% CI: 1.042–1.094) were associated with an increased risk of CRC. Similar risk trends were also observed across the exposome count groups with CRC incidence. Our findings suggest that certain exposure domains are related to the incidence of CRC. Ecosystem, lifestyle, and social factors can be incorporated into prediction models to identify individuals at high risk of CRC.

Sleep has been associated with aging and relevant health outcomes, but the causal relationship remains inconclusive. In this study, we investigated the associations of sleep behaviors with biological ages (BAs) among 363,886 middle and elderly adults from UK Biobank. Sleep index (0 [worst]-6 [best]) of each participant was retrieved from the following six sleep behaviors: snoring, chronotype, daytime sleepiness, sleep duration, insomnia, and difficulties in getting up. Two BAs, the KDM-biological age and PhenoAge, were estimated by corresponding algorithms based on clinical traits, and their residual discrepancies with chronological age were defined as the age accelerations (AAs). We first observed negative associations between the sleep index and the two AAs, and demonstrated that the change of AAs could be the consequence of sleep quality using Mendelian randomization with genetic risk scores of sleep index and BAs. Particularly, a one-unit increase in sleep index was associated with 0.104- and 0.119-year decreases in KDM-biological AA and PhenoAge acceleration, respectively. Air pollution is another key driver of aging. We further observed significant independent and joint effects of sleep and air pollution (PM

Previous studies have suggested a close but inconsistent relationship between essential nutrients and the risk of amyotrophic lateral sclerosis (ALS), and whether this association is causal remains unknown. We aimed to investigate the potential causal relation between essential nutrients (essential amino acids, essential fatty acids, essential minerals, and essential vitamins) and the risk of ALS using Mendelian randomization (MR) analysis. Large-scale European-based genome-wide association studies’ (GWASs) summary data related to ALS (assembling 27,205 ALS patients and 110,881 controls) and essential nutrient concentrations were separately obtained. MR analysis was performed using the inverse variance–weighted (IVW) method, and sensitivity analysis was conducted by the weighted median method, simple median method, MR–Egger method and MR–PRESSO method. We found a causal association between genetically predicted linoleic acid (LA) and the risk of ALS (OR: 1.066; 95% CI: 1.011–1.125; p = 0.019). An inverse association with ALS risk was noted for vitamin D (OR: 0.899; 95% CI: 0.819–0.987; p = 0.025) and for vitamin E (OR: 0.461; 95% CI: 0.340–0.626; p = 6.25 × 10−7). The sensitivity analyses illustrated similar trends. No causal effect was observed between essential amino acids and minerals on ALS. Our study profiled the effects of diet-derived circulating nutrients on the risk of ALS and demonstrated that vitamin D and vitamin E are protective against the risk of ALS, and LA is a suggested risk factor for ALS.

Aims The coronavirus disease 2019 (COVID‐19) has spread rapidly around the globe, causing significant morbidity and mortality. This study aims to describe electrocardiographic (ECG) characteristics of COVID‐19 patients and to identify ECG parameters that are associated with cardiac involvement. Methods and results The study included patients who were hospitalized with COVID‐19 diagnosis and had cardiac biomarker assessments and simultaneous 12‐lead surface ECGs. Sixty‐three hospitalized patients (median 53 [inter‐quartile range, 43–65] years, 76.2% male) were enrolled, including patients with (n = 23) and without (n = 40) cardiac injury. Patients with cardiac injury were older, had more pre‐existing co‐morbidities, and had higher mortality than those without cardiac injury. They also had prolonged QTc intervals and more T wave changes. Logistic regression model identified that the number of abnormal T waves (odds ratio (OR), 2.36 [95% confidence interval (CI), 1.38–4.04], P = 0.002) and QTc interval (OR, 1.31 [95% CI, 1.03–1.66], P = 0.027) were independent indicators for cardiac injury. The combination model of these two parameters along with age could well discriminate cardiac injury (area the under curve 0.881, P

Background Evidence is limited regarding the association of healthy lifestyle including sleep pattern with the risk of complicated type 2 diabetes mellitus (T2DM) among patients with hypertension. We aimed to investigate the associations of an overall healthy lifestyle including a healthy sleep pattern with subsequent development of T2DM among participants with hypertension compared to normotension, and to estimate how much of that risk could be prevented. Methods This study examined six lifestyle factors with T2DM cases among hypertension (227,966) and normotension (203,005) and their interaction in the UK Biobank. Low-risk lifestyle factors were defined as standard body mass index (BMI), drinking alcohol in moderation, nonsmoking, engaging in moderate- to vigorous-intensity physical activity, eating a high-quality diet, and maintaining a healthy sleep pattern. Results There were 12,403 incident T2DM cases during an average of 8.63 years of follow-up. Compared to those with 0 low-risk lifestyle factors, HRs for those with 5–6 were 0.14 (95% CI 0.10 to 0.19) for hypertensive participants, 0.13 (95% CI 0.08 to 0.19) for normotensive participants, respectively (ptrend Conclusions Adherence to a healthy lifestyle pattern including a healthy sleep pattern is associated with lower risk of T2DM in hypertensives, and this benefit is even further in normotensives.

BackgroundSleep has been associated with aging and relevant health outcomes, but their causal relationship remains inconclusive.MethodsIn this study, we investigated the associations of sleep behaviors with biological ages (BAs) among 363,886 middle and elderly-aged adults from UK Biobank. Sleep index (0 [worst]-6 [best]) of each participant was retrieved from six sleep behaviors: snoring, chronotype, daytime sleepiness, sleep duration, insomnia, and difficulties in getting up. Two BAs, the KDM-biological age and PhenoAge, were estimated by corresponding algorithms based on clinical traits, and their discrepancies with chronological age were defined as the age accelerations (AAs).ResultsWe first observed negative associations between the sleep index and the two AAs, and demonstrated that the change of AAs could be the consequence of sleep quality using Mendelian randomization with genetic risk scores of sleep index and BAs. Particularly, one unit increase in sleep index was associated with 0.105- and 0.125-year decreases in KDM-biological age acceleration and PhenoAge acceleration, respectively. Furthermore, we observed significant independent and joint effects of sleep and air pollution (i.e. PM2.5 and NO2), another key driver of aging, on BAs. Sleep quality also showed modifying effect on the associations of elevated PM2.5 and NO2 levels with accelerated aging. For instance, an interquartile range increase in PM2.5 level was associated with 0.011-, 0.047-, and 0.078-year increase in PhenoAge acceleration among people with high (5-6), medium (3-4), and low (0-2) sleep index, respectively.ConclusionsOur findings elucidate that better sleep quality could lessen accelerated biological aging resulting from exogenous exposures including air pollution.FundingPeking University Start-up Grant (BMU2021YJ044)

The total number of cumulative cases and deaths from the COVID-19 pandemic caused by SARS-CoV-2 is still increasing worldwide. Although many countries have actively implemented vaccination strategies to curb the epidemic, there is no specific efficient therapeutic drug for this virus to effectively reduce deaths. Therefore, the underappreciated macromolecular compounds have become the spotlight of research. Furthermore, the medicinal compounds in plants that provide myriad possibilities to treat human diseases have become of utmost importance. Experience indicates that Traditional Chinese medicine effectively treats SARS and has been used for treating patients with COVID-19 in China. As one of the world’s oldest herbal remedies, licorice is used for treating patients with all stages of COVID-19. Glycyrrhizic acid (GA), the main active compound in licorice, has been proven effective in killing the SARS virus. Meanwhile, as a natural plant molecule, GA can also directly target important protein structures of the SARS-CoV-2 virus and inhibit the replication of SARS-CoV-2. In this review, we summarized the immune synergy of GA and its potential role in treating COVID-19 complications. Besides, we reviewed its anti-inflammatory effects on the immune system and its positive effects in cooperation with various drugs to fight against COVID-19 and its comorbidities. The purpose of this review is to elucidate and suggest that GA can be used as a potential drug during COVID-19 treatment.

Background: Observational studies have shown that modifiable risk factors are associated with aortic valve stenosis (AVS). However, the causality behind these associations remains largely unknown. Objectives: To explore the associations of modifiable risk factors, including metabolic factors, biochemical measures, education, and lifestyles with AVS and their potential causal associations. Methods: We enrolled 361,930 British white people with genetic data in the UK biobank. Cox proportional risk regression models were used to estimate the hazard ratios between 28 modifiable risk factors and AVS. We used genetic instruments for modifiable risk factors to determine the potential causal relationships using a one-sample Mendelian randomization (MR) approach. Results: A total of 1602 participants developed AVS during an 8.4-year follow-up. Observational analyses showed higher adiposity, blood pressure, heart rate, low-density lipoprotein, urate, C-reactive protein, creatinine, albumin, and glycated hemoglobin, but lower serum vitamin D, and education, unhealthy lifestyle, and poor sleep quality were related to a higher risk of AVS after adjusting for the Bonferroni correction (p < 0.0013). Genetically predicted 1-SD higher levels of body mass index [HR: 1.09, 95% CI: 1.03 to 1.16], body fat percentage (1.17, 1.03 to 1.33), triglyceride (TG) [1.08, 1.00 to 1.16], low-density lipoprotein (LDL) (1.15, 1.08 to 1.21) and serum total cholesterol (TC) (1.13, 1.02 to 1.25) were associated with a higher risk of AVS, respectively. Genetically determined per category higher insomnia (1.32, 1.13 to 1.55) was also associated with AVS. The abovementioned genetic associations with the incident AVS showed an increasing relationship pattern. Conclusions: This study provides strong evidence for the potential causal roles of cardiometabolic factors in developing AVS, highlighting that an idea of metabolic status through a healthy lifestyle may help prevent AVS.

Cardiac injury is a common complication of the coronavirus disease 2019 (COVID-19), and is associated with adverse clinical outcomes. In this study, we aimed to reveal the association of cardiac injury with coagulation dysfunction. We enrolled 181 consecutive patients who were hospitalized with COVID-19, and studied the clinical characteristics and outcome of these patients. Cardiac biomarkers high-sensitivity troponin I (hs-cTnI), myohemoglobin and creatine kinase-myocardial band (CK-MB) were assessed in all patients. The clinical outcomes were defined as hospital discharge or death. The median age of the study cohort was 55 (IQR, 46–65) years, and 102 (56.4%) were males. Forty-two of the 181 patients (23.2%) had cardiac injury. Old age, high leukocyte count, and high levels of aspartate transaminase (AST), D-dimer and serum ferritin were significantly associated with cardiac injury. Multivariate regression analysis revealed old age and elevated D-dimer levels as being strong risk predictors of in-hospital mortality. Interleukin 6 (IL6) levels were comparable in patients with or without cardiac injury. Serial observations of coagulation parameters demonstrated highly synchronous alterations of D-dimer along with progression to cardiac injury. Cardiac injury is a common complication of COVID-19 and is an independent risk factor for in-hospital mortality. Old age, high leukocyte count, and high levels of AST, D-dimer and serum ferritin are significantly associated with cardiac injury, whereas IL6 are not. Therefore, the pathogenesis of cardiac injury in COVID-19 may be primarily due to coagulation dysfunction along with microvascular injury.