Long-Term Exposure to Low Concentrations of Ambient Benzene and Mortality in a National English Cohort.

Background: Benzene affects human health through environmental exposure in addition to occupational contact. However, few studies have examined the associations between long-term exposure to low concentrations of ambient benzene and mortality risks in nonoccupational settings.Methods: This prospective cohort study consists of 393,042 participants without stroke, myocardial infarction, or cancer at baseline from the UK Biobank. Annual average concentrations of benzene for each year during follow-up were measured using air dispersion models. The main outcomes were all-cause mortality and mortality from specific causes. Cox proportional-hazards models with time-varying exposure measurements were used to estimate the hazard ratios and 95% confidence intervals (CIs) for mortality risks. Restricted cubic spline models were used to estimate exposure-response relationships.Measurements and Main Results: With each interquartile range increase in the average annual concentration of benzene, the adjusted hazard ratios of mortality risk from all causes, cardiovascular disease, cancer, and respiratory disease were 1.26 (95% CI, 1.24-1.27), 1.24 (95% CI, 1.21-1.28), 1.27 (95% CI, 1.25-1.29), and 1.25 (95% CI, 1.20-1.30), respectively. The monotonically increasing exposure-response curves showed no threshold and plateau within the observed concentration range. Furthermore, the effect of benzene exposure on mortality persisted across different subgroups and was somewhat stronger in younger and White people (P for interaction < 0.05).Conclusions: Long-term exposure to low concentrations of ambient benzene significantly increases mortality risk in the general population. Ambient benzene represents a potential threat to public health, and further investigations are needed to support timely pollution regulation and health protection.

Long-term variations of urban-Rural disparities in infectious disease burden of over 8.44 million children, adolescents, and youth in China from 2013 to 2021: An observational study.

BACKGROUND: An accelerated epidemiological transition, spurred by economic development and urbanization, has led to a rapid transformation of the disease spectrum. However, this transition has resulted in a divergent change in the burden of infectious diseases between urban and rural areas. The objective of our study was to evaluate the long-term urban-rural disparities in infectious diseases among children, adolescents, and youths in China, while also examining the specific diseases driving these disparities. METHODS AND FINDINGS: This observational study examined data on 43 notifiable infectious diseases from 8,442,956 cases from individuals aged 4 to 24 years, with 4,487,043 cases in urban areas and 3,955,913 in rural areas. The data from 2013 to 2021 were obtained from China's Notifiable Infectious Disease Surveillance System. The 43 infectious diseases were categorized into 7 categories: vaccine-preventable, bacterial, gastrointestinal and enterovirus, sexually transmitted and bloodborne, vectorborne, zoonotic, and quarantinable diseases. The calculation of infectious disease incidence was stratified by urban and rural areas. We used the index of incidence rate ratio (IRR), calculated by dividing the urban incidence rate by the rural incidence rate for each disease category, to assess the urban-rural disparity. During the nine-year study period, most notifiable infectious diseases in both urban and rural areas exhibited either a decreased or stable pattern. However, a significant and progressively widening urban-rural disparity in notifiable infectious diseases was observed. Children, adolescents, and youths in urban areas experienced a higher average yearly incidence compared to their rural counterparts, with rates of 439 per 100,000 compared to 211 per 100,000, respectively (IRR: 2.078, 95% CI [2.075, 2.081]; p < 0.001). From 2013 to 2021, this disparity was primarily driven by higher incidences of pertussis (IRR: 1.782, 95% CI [1.705, 1.862]; p < 0.001) and seasonal influenza (IRR: 3.213, 95% CI [3.205, 3.220]; p < 0.001) among vaccine-preventable diseases, tuberculosis (IRR: 1.011, 95% CI [1.006, 1.015]; p < 0.001), and scarlet fever (IRR: 2.942, 95% CI [2.918, 2.966]; p < 0.001) among bacterial diseases, infectious diarrhea (IRR: 1.932, 95% CI [1.924, 1.939]; p < 0.001), and hand, foot, and mouth disease (IRR: 2.501, 95% CI [2.491, 2.510]; p < 0.001) among gastrointestinal and enterovirus diseases, dengue (IRR: 11.952, 95% CI [11.313, 12.628]; p < 0.001) among vectorborne diseases, and 4 sexually transmitted and bloodborne diseases (syphilis: IRR 1.743, 95% CI [1.731, 1.755], p < 0.001; gonorrhea: IRR 2.658, 95% CI [2.635, 2.682], p < 0.001; HIV/AIDS: IRR 2.269, 95% CI [2.239, 2.299], p < 0.001; hepatitis C: IRR 1.540, 95% CI [1.506, 1.575], p < 0.001), but was partially offset by lower incidences of most zoonotic and quarantinable diseases in urban areas (for example, brucellosis among zoonotic: IRR 0.516, 95% CI [0.498, 0.534], p < 0.001; hemorrhagic fever among quarantinable: IRR 0.930, 95% CI [0.881, 0.981], p = 0.008). Additionally, the overall urban-rural disparity was particularly pronounced in the middle (IRR: 1.704, 95% CI [1.699, 1.708]; p < 0.001) and northeastern regions (IRR: 1.713, 95% CI [1.700, 1.726]; p < 0.001) of China. A primary limitation of our study is that the incidence was calculated based on annual average population data without accounting for population mobility. CONCLUSIONS: A significant urban-rural disparity in notifiable infectious diseases among children, adolescents, and youths was evident from our study. The burden in urban areas exceeded that in rural areas by more than 2-fold, and this gap appears to be widening, particularly influenced by tuberculosis, scarlet fever, infectious diarrhea, and typhus. These findings underscore the urgent need for interventions to mitigate infectious diseases and address the growing urban-rural disparity.

Use of Sex-Specific Body Mass Index to Optimize Low Correlation With Height and High Correlation With Fatness: A UK Biobank Study.

Body mass index (BMI; weight (kg)/height (m)2) is commonly used to measure general adiposity. However, evidence of its appropriateness for males and females remains inconsistent. We aimed to identify the most appropriate sex-specific power value that height should be raised to in the formula and the value that would make it achieve height independency and body fatness dependency. We randomly assigned UK Biobank participants recruited in the United Kingdom between 2006 and 2010 (n = 489,873; mean age = 56.5 years; 94.2% White) to training and testing sets (80%:20%). Using height raised to the power of -50.00 to 50.00, we identified the optimal power value that either minimized correlation with height or maximized correlation with body fat percentage, using age-adjusted correlations. The optimal power values for height were 1.77 for males and 1.39 for females. The new formulas resulted in 4.5% of females and 2.4% of males being reclassified into a different BMI category. The formulas did not show significant improvement (in terms of area under the receiver operating characteristic curve, sensitivity, and specificity) in identifying individuals with excessive body fat percentage or in predicting risk of all-cause mortality. Therefore, the conventional BMI formula is still valuable in research and disease screening for both sexes.

Global burden of early-onset osteoarthritis, 1990-2019: results from the Global Burden of Disease Study 2019.

OBJECTIVES: Early-onset osteoarthritis (OA) is an emerging health issue amidst the escalating prevalence of overweight and obesity. However, there are scant data on its disease, economic burden and attributable burden due to high body mass index (BMI). METHODS: Using data from the Global Burden of Diseases Study 2019, we examined the numbers of incident cases, prevalent cases, years lived with disability (YLDs) and corresponding age-standardised rates for early-onset OA (diagnosis before age 55) from 1990 to 2019. The case definition was symptomatic and radiographically confirmed OA in any joint. The average annual percentage changes (AAPCs) of the age-standardised rates were calculated to quantify changes. We estimated the economic burden of early-onset OA and attributable burden to high BMI. RESULTS: From 1990 to 2019, the global incident cases, prevalent cases and YLDs of early-onset OA were doubled. 52.31% of incident OA cases in 2019 were under 55 years. The age-standardised rates of incidence, prevalence and YLDs increased globally and for countries in all Sociodemographic Index (SDI) quintiles (all AAPCs>0, p<0.05), with the fastest increases in low-middle SDI countries. 98.04% of countries exhibited increasing trends in all age-standardised rates. Early-onset OA accounts for US$46.17 billion in healthcare expenditure and US$60.70 billion in productivity loss cost in 2019. The attributable proportion of high BMI for early-onset OA increased globally from 9.41% (1990) to 15.29% (2019). CONCLUSIONS: Early-onset OA is a developing global health problem, causing substantial economic costs in most countries. Targeted implementation of cost-effective policies and preventive intervention is required to address the growing health challenge.

HLA-C*07:01 and HLA-DQB1*02:01 protect against white matter hyperintensities and deterioration of cognitive function: A population-based cohort study.

BACKGROUND: Neuroinflammation and aberrant immune regulation are increasingly implicated in the pathophysiology of white matter hyperintensities (WMH), an imaging marker of cerebrovascular pathologies and predictor of cognitive impairment. The role of human leukocyte antigen (HLA) genes, critical in immunoregulation and associated with susceptibility to neurodegenerative diseases, in WMH pathophysiology remains unexplored. METHODS: We performed association analyses between classical HLA alleles and WMH volume, derived from MRI scans of 38 302 participants in the UK Biobank. To identify independent functional alleles driving these associations, we conducted conditional forward stepwise regression and lasso regression. We further investigated whether these functional alleles showed consistent associations with WMH across subgroups characterized by varying levels of clinical determinants. Additionally, we validated the clinical relevance of the identified alleles by examining their association with cognitive function (n = 147 549) and dementia (n = 460 029) in a larger cohort. FINDINGS: Four HLA alleles (DQB1*02:01, DRB1*03:01, C*07:01, and B*08:01) showed an association with reduced WMH volume after Bonferroni correction for multiple comparisons. Among these alleles, DQB1*02:01 exhibited the most significant association (ß = -0.041, 95 % CI: -0.060 to -0.023, p = 1.04 × 10-5). Forward selection and lasso regression analyses indicated that DQB1*02:01 and C*07:01 primarily drove this association. The protective effect against WMH conferred by DQB1*02:01 and C*07:01 persisted in clinically relevant subgroups, with a stronger effect observed in older participants. Carrying DQB1*02:01 and C*07:01 was associated with higher cognitive function, but no association with dementia was found. INTERPRETATION: Our population-based findings support the involvement of immune-associated mechanisms, particularly both HLA class I and class II genes, in the pathogenesis of WMH and subsequent consequence of cognitive functions.

Association of Regular Opioid Use With Incident Dementia and Neuroimaging Markers of Brain Health in Chronic Pain Patients: Analysis of UK Biobank.

OBJECTIVES: We aimed to investigate the association of regular opioid use, compared with non-opioid analgesics, with incident dementia and neuroimaging outcomes among chronic pain patients. DESIGN: The primary design is a prospective cohort study. To triangulate evidence, we also conducted a nested case-control study analyzing opioid prescriptions and a cross-sectional study analyzing neuroimaging outcomes. SETTING AND PARTICIPANTS: Dementia-free UK Biobank participants with chronic pain and regular analgesic use. MEASUREMENTS: Chronic pain status and regular analgesic use were captured using self-reported questionnaires and verbal interviews. Opioid prescription data were obtained from primary care records. Dementia cases were ascertained using primary care, hospital, and death registry records. Propensity score-matched Cox proportional hazards analysis, conditional logistic regression, and linear regression were applied to the data in the prospective cohort, nested case-control, and cross-sectional studies, respectively. RESULTS: Prospective analyses revealed that regular opioid use, compared with non-opioid analgesics, was associated with an increased dementia risk over the 15-year follow-up (Hazard ratio [HR], 1.18 [95% confidence interval (CI): 1.08-1.30]; Absolute rate difference [ARD], 0.44 [95% CI: 0.19-0.71] per 1000 person-years; Wald χ2 = 3.65; df = 1; p <0.001). The nested case-control study suggested that a higher number of opioid prescriptions was associated with an increased risk of dementia (1 to 5 prescriptions: OR = 1.21, 95% CI: 1.07-1.37, Wald χ2 = 3.02, df = 1, p = 0.003; 6 to 20: OR = 1.27, 95% CI: 1.08-1.50, Wald χ2 = 2.93, df = 1, p = 0.003; more than 20: OR = 1.43, 95% CI: 1.23-1.67, Wald χ2 = 4.57, df = 1, p < 0.001). Finally, neuroimaging analyses revealed that regular opioid use was associated with lower total grey matter and hippocampal volumes, and higher white matter hyperintensities volumes. CONCLUSION: Regular opioid use in chronic pain patients was associated with an increased risk of dementia and poorer brain health when compared to non-opioid analgesic use. These findings imply a need for re-evaluation of opioid prescription practices for chronic pain patients and, if further evidence supports causality, provide insights into strategies to mitigate the burden of dementia.

Genetic susceptibility and lifestyle modify the association of long-term air pollution exposure on major depressive disorder: a prospective study in UK Biobank.

BACKGROUND: Evidence linking air pollution to major depressive disorder (MDD) remains sparse and results are heterogeneous. In addition, the evidence about the interaction and joint associations of genetic risk and lifestyle with air pollution on incident MDD risk remains unclear. We aimed to examine the association of various air pollutants with the risk of incident MDD and assessed whether genetic susceptibility and lifestyle influence the associations. METHODS: This population-based prospective cohort study analyzed data collected between March 2006 and October 2010 from 354,897 participants aged 37 to 73 years from the UK Biobank. Annual average concentrations of PM2.5, PM10, NO2, and NOx were estimated using a Land Use Regression model. A lifestyle score was determined based on a combination of smoking, alcohol drinking, physical activity, television viewing time, sleep duration, and diet. A polygenic risk score (PRS) was defined using 17 MDD-associated genetic loci. RESULTS: During a median follow-up of 9.7 years (3,427,084 person-years), 14,710 incident MDD events were ascertained. PM2.5 (HR: 1.16, 95% CI: 1.07-1.26; per 5 µg/m3) and NOx (HR: 1.02, 95% CI: 1.01-1.05; per 20 µg/m3) were associated with increased risk of MDD. There was a significant interaction between the genetic susceptibility and air pollution for MDD (P-interaction < 0.05). Compared with participants with low genetic risk and low air pollution, those with high genetic risk and high PM2.5 exposure had the highest risk of incident MDD (PM2.5: HR: 1.34, 95% CI: 1.23-1.46). We also observed an interaction between PM2.5 exposure and unhealthy lifestyle (P-interaction < 0.05). Participants with the least healthy lifestyle and high air pollution exposures had the highest MDD risk when compared to those with the most healthy lifestyle and low air pollution (PM2.5: HR: 2.22, 95% CI: 1.92-2.58; PM10: HR: 2.09, 95% CI: 1.78-2.45; NO2: HR: 2.11, 95% CI: 1.82-2.46; NOx: HR: 2.28, 95% CI: 1.97-2.64). CONCLUSIONS: Long-term exposure to air pollution is associated with MDD risk. Identifying individuals with high genetic risk and developing healthy lifestyle for reducing the harm of air pollution to public mental health.

Air pollutants, genetic susceptibility and risk of incident idiopathic pulmonary fibrosis.

BACKGROUND: Air pollutants are considered as non-negligible risk factors of idiopathic pulmonary fibrosis (IPF). However, the relationship between long-term air pollution and the incidence of IPF is unknown. Our objective was to explore the associations of air pollutants with IPF risk and further assess the modification effect of genetic susceptibility. METHODS: We used land-use regression model estimated concentrations of nitrogen dioxide (NO2), nitrogen oxides (NO x ) and particulate matter (fine particulate matter with diameter <2.5 µm (PM2.5) and particulate matter with diameter <10 µm (PM10)). The polygenic risk score (PRS) was constructed using 13 independent single nucleotide polymorphisms. Cox proportional hazard models were used to evaluate the associations of air pollutants with IPF risk and further investigate the modification effect of genetic susceptibility. Additionally, absolute risk was calculated. RESULTS: Among 433 738 participants from the UK Biobank, the incidence of IPF was 27.45 per 100 000 person-years during a median follow-up of 11.78 years. The adjusted hazard ratios of IPF for each interquartile range increase in NO2, NO x and PM2.5 were 1.11 (95% CI 1.03-1.19), 1.07 (95% CI 1.01-1.13) and 1.09 (95% CI 1.02-1.17), respectively. PM2.5 had the highest population attribution risk, followed by NO x and NO2. There were additive interactions between NO2, NO x and PM2.5 and genetic susceptibility. Participants with a high PRS and high air pollution had the highest risk of incident IPF compared with those with a low PRS and low air pollution (adjusted hazard ratio: NO2 3.94 (95% CI 2.77-5.60), NO x 3.08 (95% CI 2.21-4.27), PM2.5 3.65 (95% CI 2.60-5.13) and PM10 3.23 (95% CI 2.32-4.50)). CONCLUSION: Long-term exposures to air pollutants may elevate the risk of incident IPF. There are additive effects of air pollutants and genetic susceptibility on IPF risk.

Effects of residential greenness and genetic predisposition on hemoglobin A1c and type 2 diabetes: Gene-environment interaction analysis from a nationwide study.

BACKGROUND: Current evidence on the relations of residential greenness with glucose homeostasis and type 2 diabetes (T2D) remained largely uncertain. Most importantly, no prior studies have investigated whether genetic predisposition modifies the above associations. METHODS: We leveraged data from the UK Biobank prospective cohort study, with participants enrolled between 2006 and 2010. Residential greenness was assessed by using the Normalized Difference Vegetation Index, and the weighting T2D-specific genetic risk score (GRS) was constructed based on previously published genome-wide association studies. Linear regression models and logistic regression models were used to investigate associations of residential greenness with glycated hemoglobin (HbA1c) and T2D prevalence, respectively. Interaction models explored whether genetic predisposition modifies greenness-HbA1c/T2D associations. RESULTS: Among 315,146 individuals (mean [SD] age, 56.59 [8.09] years), each one-unit increase in residential greenness was associated with reduction in HbA1c (ß: -0.87, 95% CI: -1.16 to -0.58) and a 12% decrease in odds of T2D (OR: 0.88, 95% CI: 0.79 to 0.98), respectively. Additionally, interaction analyses further demonstrated that residential greenness and genetic risk had cumulative effects on HbA1c and T2D. Compared with individuals who were exposed to low greenness and had high GRS, participants with low GRS and high greenness had a significant decline in HbA1c (ß: -2.96, 95% CI: -3.10 to -2.82, P for interaction = 0.04) and T2D (OR: 0.47, 95% CI: 0.45 to 0.50, P for interaction = 0.09). CONCLUSIONS: We add novel evidence that residential greenness has protective effects on glucose metabolism and T2D, and those beneficial effects can be amplified by low genetic risk. Our findings may facilitate the improvement of the living environment and the development of prevention strategies by considering genetic susceptibility to T2D.

Temperature variability and common diseases of the elderly in China: a national cross-sectional study.

BACKGROUND: In the context of climate change, it has been well observed that short-term temperature variability (TV) could increase the overall and cause-specific mortality and morbidity. However, the association between long-term TV and a broader spectrum of diseases is not yet well understood, especially in the elderly. METHODS: Our study used data from the fourth Urban and Rural Elderly Population (UREP) study. Long-term TV was calculated from the standard deviation (SD) of daily minimum and maximum temperatures within the study periods (2010-2014, 2011-2014, 2012-2014, 2013-2014, and 2014). Ten self-reported diseases and conditions were collected by questionnaire, including cataract, hypertension, diabetes, cardio-cerebrovascular diseases, stomach diseases, arthritis, chronic lung disease, asthma, cancer, and reproductive diseases. The province-stratified logistic regression model was used to quantify the association between long-term TV and the prevalence of each disease. RESULTS: A total of 184,047 participants were included in our study. In general, there were significant associations between TV and the prevalence of most diseases at the national level. Cardio-cerebrovascular disease (OR: 1.16, 95% CI: 1.13, 1.20) generated the highest estimates, followed by stomach diseases (OR: 1.15, 95% CI: 1.10, 1.19), asthma (OR: 1.14, 95% CI: 1.06, 1.22), chronic lung diseases (OR: 1.08, 95% CI: 1.03, 1.13), arthritis (OR: 1.08, 95% CI: 1.05, 1.11), and cataract (OR: 1.06, 95% CI: 1.02, 1.10). Moreover, the associations varied by geographical regions and across subgroups stratified by sex, household income, physical activity, and education. CONCLUSIONS: Our study showed that long-term exposure to TV was associated with the prevalence of main diseases in the elderly. More attention should be paid to the elderly and targeted strategies should be implemented, such as an early warning system.

Risk of depression, suicide and psychosis with hydroxychloroquine treatment for rheumatoid arthritis: a multinational network cohort study.

OBJECTIVES: Concern has been raised in the rheumatology community regarding recent regulatory warnings that HCQ used in the coronavirus disease 2019 pandemic could cause acute psychiatric events. We aimed to study whether there is risk of incident depression, suicidal ideation or psychosis associated with HCQ as used for RA. METHODS: We performed a new-user cohort study using claims and electronic medical records from 10 sources and 3 countries (Germany, UK and USA). RA patients ≥18 years of age and initiating HCQ were compared with those initiating SSZ (active comparator) and followed up in the short (30 days) and long term (on treatment). Study outcomes included depression, suicide/suicidal ideation and hospitalization for psychosis. Propensity score stratification and calibration using negative control outcomes were used to address confounding. Cox models were fitted to estimate database-specific calibrated hazard ratios (HRs), with estimates pooled where I2 <40%. RESULTS: A total of 918 144 and 290 383 users of HCQ and SSZ, respectively, were included. No consistent risk of psychiatric events was observed with short-term HCQ (compared with SSZ) use, with meta-analytic HRs of 0.96 (95% CI 0.79, 1.16) for depression, 0.94 (95% CI 0.49, 1.77) for suicide/suicidal ideation and 1.03 (95% CI 0.66, 1.60) for psychosis. No consistent long-term risk was seen, with meta-analytic HRs of 0.94 (95% CI 0.71, 1.26) for depression, 0.77 (95% CI 0.56, 1.07) for suicide/suicidal ideation and 0.99 (95% CI 0.72, 1.35) for psychosis. CONCLUSION: HCQ as used to treat RA does not appear to increase the risk of depression, suicide/suicidal ideation or psychosis compared with SSZ. No effects were seen in the short or long term. Use at a higher dose or for different indications needs further investigation. TRIAL REGISTRATION: Registered with EU PAS (reference no. EUPAS34497; http://www.encepp.eu/encepp/viewResource.htm? id=34498). The full study protocol and analysis source code can be found at https://github.com/ohdsi-studies/Covid19EstimationHydroxychloroquine2.

Association of Tramadol vs Codeine Prescription Dispensation With Mortality and Other Adverse Clinical Outcomes.

Importance: Although tramadol is increasingly used to manage chronic noncancer pain, few safety studies have compared it with other opioids. Objective: To assess the associations of tramadol, compared with codeine, with mortality and other adverse clinical outcomes as used in outpatient settings. Design, Setting, and Participants: Retrospective, population-based, propensity score-matched cohort study using a primary care database with routinely collected medical records and pharmacy dispensations covering more than 80% of the population of Catalonia, Spain (≈6 million people). Patients 18 years or older with 1 or more year of available data and dispensation of tramadol or codeine (2007-2017) were included and followed up to December 31, 2017. Exposures: New prescription dispensation of tramadol or codeine (no dispensation in the previous year). Main Outcomes and Measures: Outcomes studied were all-cause mortality, cardiovascular events, fractures, constipation, delirium, falls, opioid abuse/dependence, and sleep disorders within 1 year after the first dispensation. Absolute rate differences (ARDs) and hazard ratios (HRs) with 95% confidence intervals were calculated using cause-specific Cox models. Results: Of the 1 093 064 patients with a tramadol or codeine dispensation during the study period (326 921 for tramadol, 762 492 for codeine, 3651 for both drugs concomitantly), a total of 368 960 patients (184 480 propensity score-matched pairs) were included after study exclusions and propensity score matching (mean age, 53.1 [SD, 16.1] years; 57.3% women). Compared with codeine, tramadol dispensation was significantly associated with a higher risk of all-cause mortality (incidence, 13.00 vs 5.61 per 1000 person-years; HR, 2.31 [95% CI, 2.08-2.56]; ARD, 7.37 [95% CI, 6.09-8.78] per 1000 person-years), cardiovascular events (incidence, 10.03 vs 8.67 per 1000 person-years; HR, 1.15 [95% CI, 1.05-1.27]; ARD, 1.36 [95% CI, 0.45-2.36] per 1000 person-years), and fractures (incidence, 12.26 vs 8.13 per 1000 person-years; HR, 1.50 [95% CI, 1.37-1.65]; ARD, 4.10 [95% CI, 3.02-5.29] per 1000 person-years). No significant difference was observed for the risk of falls, delirium, constipation, opioid abuse/dependence, or sleep disorders. Conclusions and Relevance: In this population-based cohort study, a new prescription dispensation of tramadol, compared with codeine, was significantly associated with a higher risk of subsequent all-cause mortality, cardiovascular events, and fractures, but there was no significant difference in the risk of constipation, delirium, falls, opioid abuse/dependence, or sleep disorders. The findings should be interpreted cautiously, given the potential for residual confounding.

Fidgetin as a potential prognostic biomarker for hepatocellular carcinoma.

Background: Fidgetin (FIGN), a conserved ATP-dependent enzyme, is regarded as a hepatocellular carcinoma (HCC) risk gene, but the prognostic implication of FIGN in HCC remains obscure. In this study, we investigate the expression of FIGN in HCC and to evaluate its prognostic value. Methods: A total of 216 patients with HCC who experienced hepatectomy were recruited in this study. The expression of FIGN in HCC samples was evaluated by quantitative real-time PCR, immunohistochemistry and immunoblotting analysis. And Cox regression model was used to evaluate the prognostic value of all covariates. Results: Of the 216 HCC patients, 67 (31.0%) had tumors with high FIGN expression and 149 (69.0%) had tumors with low FIGN expression. FIGN expression was positively correlated with TNM stage (P = 0.039), tumor with incomplete capsule (P = 0.036), microvascular invasion (P = 0.023), and portal vein tumor thrombus (P = 0.003). High expression of FIGN indicated shorter overall survival (OS) (hazard ratio: 4.569, P = 0.036) and disease-free survival (DFS) (hazard ratio: 6.487, P = 0.001). Conclusion: Our results indicate that high Fidgetin expression is associated with tumor progression and suggest a worse prognosis in HCC. Fidgetin might serve as a potential target for therapy.

Addressing Noise and Skewness in Interpretable Health-Condition Assessment by Learning Model Confidence.

Assessing the health condition has a wide range of applications in healthcare, military, aerospace, and industrial fields. Nevertheless, traditional feature-engineered techniques involve manual feature extraction, which are too cumbersome to adapt to the changes caused by the development of sensor network technology. Recently, deep-learning-based methods have achieved initial success in health-condition assessment research, but insufficient considerations for problems such as class skewness, noisy segments, and result interpretability make it difficult to apply them to real-world applications. In this paper, we propose a K-margin-based Interpretable Learning approach for health-condition assessment. In detail, a skewness-aware RCR-Net model is employed to handle problems of class skewness. Furthermore, we present a diagnosis model based on K-margin to automatically handle noisy segments by naturally exploiting expected consistency among the segments associated with each record. Additionally, a knowledge-directed interpretation method is presented to learn domain knowledge-level features automatically without the help of human experts which can be used as an interpretable decision-making basis. Finally, through experimental validation in the field of both medical and aerospace, the proposed method has a better generality and high efficiency with 0.7974 and 0.8005 F1 scores, which outperform all state-of-the-art deep learning methods for health-condition assessment task by 3.30% and 2.99%, respectively.

Long-term risk of psychiatric disorder and psychotropic prescription after SARS-CoV-2 infection among UK general population.

Despite evidence indicating increased risk of psychiatric issues among COVID-19 survivors, questions persist about long-term mental health outcomes and the protective effect of vaccination. Using UK Biobank data, three cohorts were constructed: SARS-CoV-2 infection (n = 26,101), contemporary control with no evidence of infection (n = 380,337) and historical control predating the pandemic (n = 390,621). Compared with contemporary controls, infected participants had higher subsequent risks of incident mental health at 1 year (hazard ratio (HR): 1.54, 95% CI 1.42-1.67; P = 1.70 × 10-24; difference in incidence rate: 27.36, 95% CI 21.16-34.10 per 1,000 person-years), including psychotic, mood, anxiety, alcohol use and sleep disorders, and prescriptions for antipsychotics, antidepressants, benzodiazepines, mood stabilizers and opioids. Risks were higher for hospitalized individuals (2.17, 1.70-2.78; P = 5.80 × 10-10) than those not hospitalized (1.41, 1.30-1.53; P = 1.46 × 10-16), and were reduced in fully vaccinated people (0.97, 0.80-1.19; P = 0.799) compared with non-vaccinated or partially vaccinated individuals (1.64, 1.49-1.79; P = 4.95 × 10-26). Breakthrough infections showed similar risk of psychiatric diagnosis (0.91, 0.78-1.07; P = 0.278) but increased prescription risk (1.42, 1.00-2.02; P = 0.053) compared with uninfected controls. Early identification and treatment of psychiatric disorders in COVID-19 survivors, especially those severely affected or unvaccinated, should be a priority in the management of long COVID. With the accumulation of breakthrough infections in the post-pandemic era, the findings highlight the need for continued optimization of strategies to foster resilience and prevent escalation of subclinical mental health symptoms to severe disorders.

Observational methods for COVID-19 vaccine effectiveness research: an empirical evaluation and target trial emulation.

BACKGROUND: There are scarce data on best practices to control for confounding in observational studies assessing vaccine effectiveness to prevent COVID-19. We compared the performance of three well-established methods [overlap weighting, inverse probability treatment weighting and propensity score (PS) matching] to minimize confounding when comparing vaccinated and unvaccinated people. Subsequently, we conducted a target trial emulation to study the ability of these methods to replicate COVID-19 vaccine trials. METHODS: We included all individuals aged ≥75 from primary care records from the UK [Clinical Practice Research Datalink (CPRD) AURUM], who were not infected with or vaccinated against SARS-CoV-2 as of 4 January 2021. Vaccination status was then defined based on first COVID-19 vaccine dose exposure between 4 January 2021 and 28 January 2021. Lasso regression was used to calculate PS. Location, age, prior observation time, regional vaccination rates, testing effort and COVID-19 incidence rates at index date were forced into the PS. Following PS weighting and matching, the three methods were compared for remaining covariate imbalance and residual confounding. Last, a target trial emulation comparing COVID-19 at 3 and 12 weeks after first vaccine dose vs unvaccinated was conducted. RESULTS: Vaccinated and unvaccinated cohorts comprised 583 813 and 332 315 individuals for weighting, respectively, and 459 000 individuals in the matched cohorts. Overlap weighting performed best in terms of minimizing confounding and systematic error. Overlap weighting successfully replicated estimates from clinical trials for vaccine effectiveness for ChAdOx1 (57%) and BNT162b2 (75%) at 12 weeks. CONCLUSION: Overlap weighting performed best in our setting. Our results based on overlap weighting replicate previous pivotal trials for the two first COVID-19 vaccines approved in Europe.

Early-life exposure to tobacco, genetic susceptibility, and accelerated biological aging in adulthood.

Early-life tobacco exposure serves as a non-negligible risk factor for aging-related diseases. To understand the underlying mechanisms, we explored the associations of early-life tobacco exposure with accelerated biological aging and further assessed the joint effects of tobacco exposure and genetic susceptibility. Compared with those without in utero exposure, participants with in utero tobacco exposure had an increase in Klemera-Doubal biological age (KDM-BA) and PhenoAge acceleration of 0.26 and 0.49 years, respectively, but a decrease in telomere length of 5.34% among 276,259 participants. We also found significant dose-response associations between the age of smoking initiation and accelerated biological aging. Furthermore, the joint effects revealed that high-polygenic risk score participants with in utero exposure and smoking initiation in childhood had the highest accelerated biological aging. There were interactions between early-life tobacco exposure and age, sex, deprivation, and diet on KDM-BA and PhenoAge acceleration. These findings highlight the importance of reducing early-life tobacco exposure to improve healthy aging.