To explore the association between life’s essential 8 and epigenetic age based on twins population. This study included 1030 twins (515 pairs) for cross-sectional analysis and conducted cross-lagged analysis among 294 twins (147 pairs) who participated in both the baseline and follow-up surveys from the Chinese National Twin Registry. LE8 scores were obtained from measurements based on American Heart Association definitions. DNA methylation data were used to calculate epigenetic age metrics, including GrimAA, DamAA and DunedinPACE. Linear mixed-effect models were applied for cross-twin analyses and within-monozygotic-pair analyses. In the cross-sectional analysis, higher LE8 score was associated with slower epigenetic aging (DunedinPACE and DamAA) in both across-twin analyses and within-monozygotic-pair analyses. In stratified analyses, the association between LE8 score and epigenetic age appeared more significant in males and in individuals aged 50 years older. The cross-lagged analysis further revealed significant temporal associations between LE8, health factor, and DunedinPACE. Higher LE8 scores were associated with a deceleration in biological aging.

Introduction:Chronic kidney disease (CKD) is a growing public health concern, yet evidence on its incidence is limited in China. Methods:Using data from the China Kadoorie Biobank (CKB), which recruited 512,723 participants aged 30 to 79 years from 10 areas across China, we analyzed 5 major CKD subtypes: diabetic kidney disease (DKD), hypertensive nephropathy (HTN), glomerulonephritis (GN), chronic tubulointerstitial nephritis (CTIN), and obstructive nephropathy (ON). Total CKD included the aforementioned subtypes, CKD due to other reasons, or chronic kidney failure. Outcomes were ascertained through linkages to local death and disease registries and health insurance databases until December 31, 2018. Poisson regression model was used to assess secular trends and population variations. Results:Over a mean of 9.5 years of follow-up, 5662 total CKD cases were identified. The crude incidence rate (per 100,000 person-years) of total CKD was 119.7 (95% confidence interval: 116.6-122.8) between 2009 and 2018, with an annual increase of 8.9% (7.9%-10.0%) after adjusting for age, sex, and study area. The crude incidence rates were highest in GN, whereas biggest increases were observed in ON, DKD, and HTN. Total CKD incidence rate was similar between urban and rural areas; however, those of different subtypes varied: DKD or CTIN were higher in urban areas, and ON was significantly higher in rural areas. Males, older adults, and participants with hypertension or diabetes mellitus were at higher risks. Conclusion:Despite the underestimation of CKD incidence because of outcome ascertainment methods, the incidence of total CKD and its subtypes increased in the CKB population during 2009 to 2018. Measures should be taken against major driving factors, such as diabetes mellitus, hypertension, and kidney stones.

Gaps exist concerning the associations of PM2.5-10, gaseous pollutants, and composite pollutants with the acute exacerbation of chronic obstructive pulmonary disease (AECOPD). The interaction effects of lifestyle factors, indoor air pollution, and meteorological conditions with air pollutants have been underexplored. This time-stratified case-crossover study was nested within the China Kadoorie Biobank cohort study of middle-aged and elderly participants from five urban and five rural areas in China spanning from 2004 to 2018. 10,712 participants were included, each with a mean of 2.3 episodes of AECOPD hospitalizations during the observation period. A composite air pollution score was derived through principal component analysis. Short-term exposure to particulate matter and NO2 was positively associated with hospital admissions for AECOPD, with the largest temperature- and humidity-adjusted odds ratio (95% confidence interval) of 1.101 (1.073, 1.129) at a lag of 1 day for per 1 standard deviation increase in air pollution score. The effect of O3 appeared to be conflicting. The associations were further corroborated by the self-controlled case-series design. Unfavorable body shapes, cold season, and low humidity could exacerbate the influence of air pollution. These findings reinforce the evidence of links between air pollution and AECOPD and implicate the management of body weight and cold and dry circumstances.

Background:Although tobacco smoking is one of the established risk factors for liver cancer, results from epidemiological studies remain inconclusive on the relationship between second-hand smoke (SHS) and liver cancer, particularly among nonsmokers.Objectives:This study aimed to examine the association between SHS and liver cancer, and to assess its potential interaction with major risk factors such as hepatitis B virus (HBV) infection.Methods:A population-based case-control study was conducted in Jiangsu, China, from 2003 to 2010, including 2011 newly diagnosed primary liver cancer cases and 7933 population-based controls. Data on SHS exposure at home and in the workplace, along with other major liver cancer risk factors such as alcohol consumption, were collected through self-reported questionnaires. SHS exposure was assessed as a dichotomous variable, categorizing participants as either exposed or unexposed to SHS. HBV infection status was determined by testing serum samples for serum hepatitis B virus surface antigen. Multivariable unconditional logistic regression models were used to examine the association between SHS and risk of liver cancer. Besides stratified analyses, interactions on additive and multiplicative scales were further evaluated between SHS and other risk factors for liver cancer.Results:Exposure to SHS was associated with liver cancer, shown as adjusted odds ratios (ORs) of 1.84 (95% confidence interval [CI]: 1.56, 2.18) in the overall population and 2.11 (95% CI: 1.67, 2.65) among never smokers. Stratified analyses showed that the association between SHS and liver cancer was stronger among HBV-positive participants (OR: 2.09, 95% CI: 1.48, 2.93) compared with HBV-negative participants (OR: 1.87, 95% CI: 1.54, 2.27) (P = 0.02). Both super-additive and super-multiplicative interactions were observed between SHS and HBV infection, with relative excess risk due to interaction (RERI) of 12.56 (95% CI: 6.60, 18.53) and ratio of ORs of 1.55 (95% CI: 1.07, 2.23) in the total population, and RERI of 12.87 (95% CI: 4.93, 20.81) and ratio of ORs of 1.78 (95% CI: 1.06, 2.99) among never smokers.Conclusion:SHS is independently associated with liver cancer, and this association is further modified by HBV infection, leading to a substantially elevated risk, particularly among nonsmokers.

The risk profile of valvular heart disease (VHD) and its underlying mechanisms remain poorly understood. This study aimed to develop and validate a multi-omics-based risk prediction model, and to elucidate potential biological mechanisms. Using data from the UK Biobank, Cox proportional hazards and machine learning models (XGBoost and LightGBM) were evaluated for predicting VHD and its subtypes (aortic valve stenosis, AVS; aortic valve regurgitation, AVR; mitral valve regurgitation, MVR). Cox models based on key clinical factors showed the best predictive performance (C-index of 0.75-0.81), which was further enhanced by incorporating proteomic data (all C-index > 0.81) but not by genomic or metabolomic data. Notably, a simplified 10-year model comprising only four top proteins maintained favorable performance (C-index of 0.75-0.82). Cluster analysis identified blood pressure and lipid levels as leading modifiable risk factors for VHD onset. Functional enrichment analysis revealed that VHD is primarily associated with protease inhibition, AVS with fibrotic and matrix metabolic pathways, and MVR with immune-inflammatory activation. Mendelian randomization and Bayesian colocalization analyses suggested causal associations between CNTN5 and CD8A with risks of AVS and MVR, whilst IGFBP7 showed a reverse-direction association with AVS. These findings highlight promising avenues for early diagnostic biomarkers and potential precision-targeted therapies.

BACKGROUND:Evidence linking components of particulate matter with diameters ≤2.5 μm (PM2.5) to the incidence of cardiovascular disease (CVD) remains scarce and inconsistent. OBJECTIVES:The aim of this study was to investigate the associations of long-term exposure to PM2.5 components with incident CVD risk, considering both absolute concentrations and relative proportions. METHODS:This study included 487,037 participants from the China Kadoorie Biobank who were free of CVD or cancer at baseline. Three-year moving average concentrations of PM2.5 and its components (black carbon [BC], organic matter, chloride [Cl-], nitrate [NO3-], sulfate [SO42-], and ammonium [NH4+]) were geocoded to participants at 1 × 1 km resolution according to their community recruitment clinic locations. Time-varying Cox proportional hazards models were used to evaluate the associations between PM2.5 components and incident CVD risk. Substitution models were used to estimate the effects of reallocating PM2.5 component proportions while keeping total PM2.5 mass constant, thereby evaluating changes in CVD risk associated with shifts in component composition. RESULTS:Over a median 15.1-year follow-up, a total of 196,224 CVD cases, including 72,747 of ischemic heart disease, 74,594 of ischemic stroke, 17,553 of hemorrhagic stroke, and 54,306 of other cerebrovascular diseases, were documented. Long-term exposure to PM2.5 components was associated with increased risk for CVD and its major subtypes. For total CVD, the HRs per IQR increase were 1.15 (95% CI: 1.13-1.17) for BC, 1.17 (95% CI: 1.15-1.18) for organic matter, 1.28 (95% CI: 1.25-1.32) for Cl-, 1.29 (95% CI: 1.24-1.33) for NO3-, and 1.23 (95% CI: 1.20-1.25) for SO42-. Higher proportions of Cl-, SO42-, and BC were associated with an increased risk for ischemic stroke, and the aforementioned inorganic ions were also positively associated with ischemic heart disease. Substituting 1% of any other PM2.5 component with Cl- was associated with a 3% to 8% higher risk for total CVD, whereas substitutions with BC were associated with a 1% to 8% higher risk for ischemic stroke, and substitution with SO42- was associated with a 2% to 5% higher risk for ischemic heart disease. CONCLUSIONS:Long-term exposure to PM2.5 chemical components was positively associated with CVD risk. Critically, CVD risk was influence by compositional shifts, with a particularly hazardous profile characterized by higher proportions of Cl-, BC, or SO42-. These findings underscore the importance of implementing targeted, health-oriented control strategies that prioritize specific PM2.5 components.

BackgroundCardiovascular-kidney-metabolic (CKM) syndrome encompasses metabolic abnormalities, chronic kidney disease, and cardiovascular disease. The triglyceride–glucose (TyG) index reflects insulin resistance-related glucose–lipid imbalance, whereas serum uric acid (SUA) reflects purine metabolism and renal urate handling. However, their independent and joint associations with advanced CKM remain unclear.MethodsWe conducted a cross-sectional analysis of 8,939 adults from the Hakka Biobank baseline survey. Advanced CKM (stages 3–4) was defined according to the American Heart Association framework. Multivariable logistic regression examined associations of TyG and SUA with advanced CKM. Restricted cubic splines assessed nonlinearity, and joint associations used the same-dataset ROC-derived TyG threshold of 8.89 and sex-specific hyperuricemia (HUA) thresholds. Sensitivity and subgroup analyses assessed robustness and heterogeneity, while AUC and continuous net reclassification improvement (NRI) evaluated in-sample model performance.ResultsAmong 8,939 participants, 1,164 had advanced CKM. After adjustment, each 1-unit increase in TyG was associated with greater odds of advanced CKM (OR, 1.81; 95% CI, 1.64–2.01), as was each standard deviation increase in SUA (OR, 1.38; 95% CI, 1.28–1.48). TyG showed an approximately linear positive relationship, whereas SUA showed a J-shaped relationship (P for nonlinearity = 0.004), which was more evident in women. Participants with both high TyG and HUA had the greatest odds (OR, 3.01; 95% CI, 2.49–3.64). Results remained consistent across six sensitivity analyses involving medication adjustment, exclusions for renal impairment or metabolic medication use, and menopausal-status adjustment among women. Jointly adding TyG and SUA improved in-sample discrimination (AUC, 0.816 vs. 0.797; p < 0.001) and reclassification (NRI, 0.433; 95% CI, 0.372–0.496). The combined association was stronger in women (P for interaction = 0.028).ConclusionHigher TyG and SUA levels, particularly their co-occurrence, were associated with prevalent advanced CKM. These biomarkers may characterize distinct but overlapping metabolic profiles relevant to CKM assessment. Their potential value for community-based evaluation requires confirmation in prospective studies with external validation; no causal or treatment implications can be inferred from these cross-sectional findings.

BACKGROUND:Abdominal adiposity may contribute to both general and cardiovascular ageing, yet the extent to which accelerated biological age (BA) at distinct molecular levels mediates these effects has not been fully elucidated. METHODS:Three BA measures were constructed using metabolomics (MetaboAge, n=4391), clinical biomarkers (Klemera-Doubal method BA; KDM-BA, n=12 369) and DNA methylation (DNAm PhenoAge, n=980) within the prospective China Kadoorie Biobank and their predictive accuracy for all-cause mortality were evaluated. We explored the potential causal effects of abdominal adiposity, measured by waist-to-hip ratio (WHR) and WHR adjusted for body mass index (WHRadjBMI), on BA acceleration using observational study and Mendelian randomisation. We further investigated the extent to which BA accelerations mediated the effects of abdominal adiposity on cardiovascular ageing (assessed by atherosclerotic cardiovascular disease (ASCVD) incidence and mortality) and general ageing (assessed by all-cause mortality and frailty index). RESULTS:Both MetaboAge and KDM-BA improved prediction for all-cause mortality beyond chronological age (area under the receiver operating characteristic curve (AUROC) difference: MetaboAge=0.040, KDM-BA=0.012, p<0.001). In observational analyses, abdominal adiposity was associated with accelerated ageing across all three BA clocks, with effect estimates ranging from 0.055 (95% CI 0.038 to 0.073) for the association between WHR and KDM-BA acceleration to 0.107 (0.044 to 0.170) for the association between WHRadjBMI and DNAm PhenoAge acceleration. These associations remained significant in Mendelian randomisation analyses. Mediation analyses revealed that acceleration of MetaboAge and KDM-BA partially explained the effects of abdominal adiposity on cardiovascular ageing (%mediated: 6.0%-25.3%), while all three BA clocks accelerations mediated associations with general ageing assessed by all-cause mortality (%mediated: 17.6%-60.6%), with MetaboAge contributing the largest proportion of mediation. Additionally, KDM-BA acceleration mediated the association between abdominal adiposity and frailty index. CONCLUSIONS:Abdominal adiposity is associated with ageing acceleration across multiple biological domains, especially via metabolic alterations captured by MetaboAge. Our findings demonstrated that targeting abdominal adiposity-related metabolic dysfunction may mitigate age-related conditions.

Aortic diseases are often clinically silent until advanced stages, and risk determinants beyond traditional cardiovascular factors remain incompletely characterised. Here, we investigate associations of 42 chronic conditions and multimorbidity with incident aortic disease in UK Biobank (UKB), with external validation in China Kadoorie Biobank (CKB). In UKB, 21 chronic conditions are associated with overall aortic disease after false discovery rate correction, including coronary heart disease, hypertension, atrial fibrillation, peripheral vascular disease, heart failure, and COPD; similar patterns are observed in CKB. Aortic atherosclerosis shows the broadest comorbidity profile, whereas dissection and aneurysm subtypes show narrower profiles. Higher multimorbidity burden is associated with higher incidence in both cohorts. In UKB, hypertension shows the largest estimated population-attributable fraction, with additional contributions from COPD and chronic kidney disease. Mendelian randomization supports selected associations, and machine-learning models show internal discriminatory performance. These findings support consideration of multimorbidity in aortic disease risk assessment. This study shows that multimorbidity and several chronic conditions, including cardiovascular, respiratory and kidney diseases, are associated with higher risk of aortic disease in two large cohorts.

Background Breastfeeding may be associated with lower future risk of maternal type 2 diabetes (T2D). However, existing evidence is inconsistent and derived largely from studies in high-income countries. We assess the association of breastfeeding and breastfeeding duration with incident T2D among Chinese women.Research design and methods The prospective China Kadoorie Biobank recruited 512 724 adults from 10 localities across China between 2004 and 2008. During 11.8 years’ follow-up, 12 011 cases of incident T2D were recorded among 283 855 female participants without prior diabetes. Cox regression was used to estimate adjusted HRs for incident T2D associated with ever breastfeeding, mean breastfeeding duration per child and lifetime breastfeeding duration.Results Overall, 98.6% of female participants were parous, among whom 97.2% reported ever breastfeeding, with mean lifetime breastfeeding duration and breastfeeding duration per child of 34.8 and 14.9 months, respectively. Among parous female participants, there was no clear association between ever breastfeeding and risk of incident T2D (adjusted HR 1.06 (95% CI 0.94 to 1.20)). A modest log-linear positive association was observed between lifetime breastfeeding duration and incident T2D among parous female participants who ever breastfed (1.01 (1.01 to 1.02) per 6 months longer breastfeeding), but this was attenuated after adjustment for parity (1.00 (0.99 to 1.01)). Mean breastfeeding duration per child was not associated with incident T2D (1.01 (0.99 to 1.02) per 6 months longer breastfeeding).Conclusions In this population with almost universal childbearing and breastfeeding, there was no apparent association of ever breastfeeding or of breastfeeding duration with incident T2D.

OBJECTIVE:Coronary artery disease (CAD) remains a leading cause of mortality worldwide, with substantial unmet therapeutic needs. This study aimed to identify and prioritize genetically supported therapeutic targets for CAD using Mendelian randomization (MR). METHODS:We implemented a two-sample MR framework to infer the causal effects of blood druggable cis-expression quantitative trait loci (cis-eQTLs) on CAD. To consolidate MR findings, we applied Steiger filtering, Bayesian colocalization, and multiple sensitivity analyses. Mediation and phenomewide MR analyses were employed to investigate potential mechanisms and on-target effects of prioritized druggable genes. RESULTS:We identified 66 causal druggable genes associated with CAD in European populations (false discovery rate < 0.001). Among these, ERP29 (odds ratio [OR] = 1.311; 95% confidence interval [CI]: 1.176-1.460), MCL1 (OR = 0.877; 95% CI: 0.840-0.915), TNXB (OR = 1.183; 95% CI: 1.102-1.269), DAGLB, FES, and TRPM4 colocalized with CAD (posterior probability for colocalization > 0.8). The associations for ERP29, MCL1, and TNXB were replicated in an East Asian cohort. Protein-protein interaction network analysis highlighted MAPK3 and TNF as prioritized druggable targets at the protein level. Mediation analysis indicated that body mass index, triglycerides, blood pressure, and atrial fibrillation partially mediate the association between MAPK3 and CAD. Phenome-wide MR analysis further suggested additional beneficial effects of targeting MAPK3 and TNF on diabetes mellitus, obesity, hypertension, unstable angina, myocardial infarction, angina pectoris, coronary atherosclerosis, ischemic heart disease, and disorders of lipoid metabolism. DISCUSSION:This druggable genome-wide MR study not only corroborated the targets of FDA-approved CAD medications (e.g., FGFR1, MAPK3, NEU1) but also uncovered several novel genes, such as ERP29, MCL1, TNXB, DAGLB, FES, and TRPM4, implicating mechanisms related to blood pressure, lipid metabolism, and additional beneficial effects on endocrine/cardiometabolic traits and circulatory system disorders. Further exploration is imperative to explore their feasibility and generalizability. CONCLUSION:We identified circulating ERP29, MCL1, TNXB, DAGLB, FES, TRPM4, MAPK3, and TNF as promising, genetically supported druggable targets for CAD treatment. Notably, MAPK3 and TNF demonstrated strong protein-level interactions and close associations with cardiometabolic disorders.

BACKGROUND:Patients with metabolic dysfunction-associated steatotic liver disease (MASLD) are at increased risk of both hepatic and extrahepatic adverse outcomes. However, the evidence regarding lean MASLD and its prognosis remains controversial. OBJECTIVE:To comprehensively investigate the long-term prognosis of lean patients with MASLD versus non-lean MASLD in Western and Asian populations. DESIGN:This prospective multicohort study included 153 192 patients with MASLD from UK Biobank (UKB), 29 700 from Kailuan cohort and 3329 from China Kadoorie Biobank (CKB). Lean MASLD was defined as body mass index (BMI)<23 kg/m² in Kailuan and CKB and <25 kg/m² in UKB. Primary endpoints were liver-related events (LREs), all-cause mortality, liver-related mortality (LRM), cardiovascular disease (CVD) mortality, CVD, hepatocellular carcinoma (HCC) and extrahepatic cancer. RESULTS:Overall, 181 191 non-lean and 5030 lean patients with MASLD were included. During a median of 14.2-year follow-up (median 14.1, 14.8 and 13.4 years in UKB, Kailuan and CKB), 2501 incident LREs, 22 482 all-cause deaths, 28 722 incident CVD cases, 326 HCC and 25 258 extrahepatic cancer cases were identified, with 375 LRM and 4511 CVD deaths. Pooled analysis of three cohorts showed lean MASLD had higher risks of LREs (HR=2.14; 95% CI 1.27 to 3.62), all-cause mortality (HR=1.26; 95% CI 1.14 to 1.39), LRM (HR=2.31; 95% CI 1.54 to 3.46) and CVD mortality (HR=1.22; 95% CI 1.05 to 1.41). By contrast, lean MASLD exhibited comparable HCC risk (HR=1.76; 95% CI 0.84 to 3.71) and extrahepatic cancer risk (HR=1.14; 95% CI 0.88 to 1.48), but reduced CVD risk (HR=0.89; 95% CI 0.83 to 0.95) versus non-lean MASLD. CONCLUSION:Lean patients with MASLD have worse liver outcomes and greater risk of all-cause mortality, but similar risk of HCC and extrahepatic cancer, and lower CVD risk.

Background and Objectives Little is known about whether frailty index (FI) and phenotypic age (PhenoAge), two independent indicators of biological age, may jointly or interactively predict death risk.Methods This prospective study was conducted using National Health and Nutrition Examination Survey (NHANES) data of four survey cycles (2003 to 2010) and mortality records until December 31, 2019. FI was calculated for each participant based on his/her responses to 34 questions, and PhenoAge was derived from algorithms using data of nine biomarkers and chronological age. We used Cox proportional hazards (PH) models and competing risk models to estimate the associations of FI, PhenoAge, and their interactions with all-cause mortality and cause-specific mortality. The C-statistic, continuous net reclassification index (NRI), and integrated discrimination improvement (IDI) were used to evaluate model performance.Results After an updated median follow-up of 11.8 years among 20, 089 adults, a total of 3778 deaths were documented. Each 1 standard deviation (SD) increment in FI and PhenoAgeAccel was associated with 47% (42%-51%) and 41% (38%-45%) higher risk of all-cause mortality, respectively. However, their multiplicative interaction on death risk was not found (P = 0.054). Compared with the reference group (robust-decelerated aging), the risk of all-cause mortality was the highest in the frail-accelerated aging group with a hazard ratio (HR) (95% confidence interval [CI]) of 5.32 (4.50-6.29). Notably, adding both FI and PhenoAgeAccel to the traditional model significantly enhanced predictive accuracy (C-index 0.882 vs. 0.866, NRI 46.18%, and IDI 4.10%).Conclusions Individual death risk could be better predicted by a joint inclusion of both FI and PhenoAge, indicating that targeting their components may reduce death risk and prolong health span.

BACKGROUND:Substantial improvements in air quality have been recorded following the implementation of China's Clean Air Act (CCAA) in 2013. However, the association between CCAA implementation and individual-level cardiovascular disease (CVD) risk remains unclear. We aimed to examine the long-term association between CCAA implementation and individual-level predicted CVD risk. METHODS:In this prospective, quasi-experimental study, we used data from the China Kadoorie Biobank, a prospective cohort study that recruited participants from five urban and five rural areas across China between 2004 and 2008, with three resurveys conducted after the baseline survey (in 2008, 2013-14, and 2020-21). We included 34 862 individuals (mean age 51·3 years) who participated in at least one resurvey and had no history of CVD at baseline. Participants were classified into intervention (n=25 497) and control (n=9365) groups based on the local government's targets for particulate matter reduction. We estimated the 10-year risk of incident CVD morbidity or mortality using a validated risk prediction model. We used a difference-in-difference model to assess the long-term association between CCAA implementation and predicted risk, with adjustments made for regional confounders and individual-level characteristics, including demographics, lifestyle factors, medical history, and indoor air pollution exposure. The relationship between changes in long-term exposure to PM2·5, PM10, and O3 and predicted risk after CCAA implementation was analysed using a linear model. The estimated risk differences associated with air pollutant changes were estimated based on the magnitude of changes and their corresponding effect sizes. FINDINGS:After the CCAA was implemented, PM2·5 and PM10 concentrations declined in both groups, but O3 concentrations increased. The intervention group showed a 3·95% (95% CI 3·18-4·72%) lower increase in predicted risk than the control group, with larger estimated differences under stricter enforcement. Between 2013 and 2021, each 10 μg/m3 change in PM2·5 concentration was positively associated with a 1·80 (1·34-2·27) percentage point change in predicted CVD risk, whereas each 10 μg/m3 change in PM10 concentration was associated with a 1·24 (0·84-1·63) percentage point change and each 10 μg/m3 change in O3 concentration with a 0·58 (0·33-0·83) percentage point change. Overall, the observed changes in air pollutants during the study period were associated with an average 6·6 percentage point reduction in predicted CVD risk. INTERPRETATION:The CCAA and improved air quality were associated with a slower increase in predicted CVD risk, supporting the necessity for stricter, multipollutant air quality policies to maximise public health benefits. FUNDING:National Natural Science Foundation of China, Kadoorie Charitable Foundation, Noncommunicable Chronic Diseases-National Science and Technology Major Project, National Key R&D Program of China, Chinese Ministry of Science and Technology, and UK Wellcome Trust.

Circadian timing influences human physiology and disease risk, yet scalable measures of molecular circadian phase are lacking. Here we infer circadian phase from circulating blood biomarkers in UK Biobank. Among 3,228 plasma biomarkers, 58% exhibit significant diurnal variation, with harmonic modeling identifying acrophase clustering consistent with canonical circadian patterns and independent constant-routine datasets. Machine-learning models trained on plasma proteomics predict sampling time (R²≈0.68) and retain substantial accuracy with ∼60 proteins. We define a novel construct, circadian acceleration (CA), as deviation from the population-average phase; CA is temporally stable, associates with chronotype and shift work, and responds to environmental perturbation. CA is heritable (h² SNP ≈0.10) and genetically correlated with chronotype and accelerometry-derived sleep traits. These results establish plasma proteomics as a scalable approach for population-level molecular circadian phenotyping.

Accurate risk stratification of colorectal cancer (CRC) is essential for precise screening. Polygenic risk scores (PRS) hold promise for improving predictive efficacy in CRC. However, the real-world applicability of a risk-adapted CRC screening strategy based on the PRS remains underexplored. Therefore, we aimed to evaluate the optimized PRS in a large prospective cohort in China and assess its utility for risk-adapted CRC screening. We evaluated multiple PRS construction strategies using East Asian genome-wide association study data and well-established PRSs to select an optimal score, which was then assessed in 100,639 eligible participants from the China Kadoorie Biobank. The risk-adapted screening strategy assigns high-risk individuals to colonoscopy and low-risk individuals to fecal immunochemical testing (FIT), with FIT-positive cases referred for colonoscopy. We assessed the screening performance of the PRS, Asia–Pacific Colorectal Screening score, and their combination-based risk-adapted screening strategies against a standard FIT-based strategy among 2,821 participants in the TARGET-C CRC screening trial. The combined PRS (i.e., PRS121) demonstrated the best predictive performance (C-index = 0.602) for CRC. Individuals in the highest PRS quintile (top 20

Introduction Chronic kidney disease (CKD) is a growing public health concern, yet evidence on its incidence is limited in China. Methods Using data from the China Kadoorie Biobank (CKB), which recruited 512,723 participants aged 30-79 from 10 areas across China, we analyzed five major CKD subtypes: diabetic kidney disease (DKD), hypertensive nephropathy (HTN), glomerulonephritis (GN), chronic tubulointerstitial nephritis (CTIN), and obstructive nephropathy (ON). Total CKD included the aforementioned subtypes, CKD due to other reasons, or chronic kidney failure. Outcomes were ascertained through linkages to local death and disease registries and health insurance databases until December 31, 2018. Poisson regression model was used to assess secular trends and population variations. Results Over a mean 9.5-year follow-up, 5,662 total CKD cases were identified. The crude incidence rate (per 100,000 person-years) of total CKD was 119.7 (95% CI, 116.6-122.8) between 2009-2018, with an annual increase of 8.9% (7.9%-10.0%) after adjusting for age, sex, and study area. The crude incidence rates were highest in GN, while biggest increases were observed in ON, DKD, and HTN. Total CKD incidence rate was similar between urban and rural areas, but those of different subtypes varied: DKD/CTIN were higher in urban areas, and ON was significantly higher in rural areas. Males, older adults, and participants with hypertension or diabetes were at higher risks. Conclusion Despite the underestimation of CKD incidence due to outcome ascertainment methods, the incidence of total CKD and its subtypes increased in the CKB population during 2009-2018. Measures should be taken against major driven factors, such as diabetes, hypertension, and kidney stones.

Understanding the genetic regulation of circulating protein levels can provide new insights into disease mechanisms. Here, we present the largest proteogenomic study to date (n = 78,664 participants across 38 studies), identifying >24,000 protein quantitative trait loci (QTLs) associated with 1,116 proteins, acting near to (n = 5,040) or distant (n = 19,698) from the cognate gene. Using machine learning-guided effector gene assignment, we provide genetic evidence for pathways, cell types, and tissues that modulate circulating protein levels, highlighting N-linked glycosylation as an important regulatory pathway. We demonstrate that genetic instruments of protein production/function (“cis”) versus modulation (“trans”) reveal distinct phenotypic insights. We identify proteins as candidates for drug targets and engagement (e.g., plasma furin and cardiovascular diseases) by comparing cis-based genetic evidence with protein-disease associations. Systematic triangulation of trans-protein QTLs (pQTLs) with genetic and protein associations across many diseases highlights potential drug repurposing opportunities, e.g., tyrosine kinase 2 (TYK2) inhibitors for rheumatoid arthritis. Our multi-cohort meta-analyses generate proteogenomic insights into disease mechanisms and new treatment opportunities.

Background Hip fractures are a significant health issue for ageing populations, with high mortality and severe long-term effects, placing a substantial burden on healthcare systems worldwide, including in China. Although a multidisciplinary co-management model is regarded as best practice for hip fracture management, it typically involves shared care between orthopaedic teams and perioperative medical specialists such as geriatrics or internal medicine, working closely with nursing and rehabilitation staff. Its success depends on well-established medical and human resources, making implementation challenging in many settings. This study investigates the current management practices for hip fractures in county-level hospitals in China to inform development of targeted quality improvement interventions aimed at improving care. Methods This qualitative study was conducted in three sequential steps. In the first step, focus group interviews were conducted with multidisciplinary healthcare providers and hospital administrators from ten county-level hospitals across China. Guided by national clinical guidelines, these interviews aimed to identify barriers and facilitators influencing the quality of hip fracture management in older adults. The second step employed patient journey mapping to systematically analyze the treatment and management processes for hip fractures within these hospitals. In the third step, two rounds of clinician- and manager-led, evidence-informed co-design workshops were held, bringing together clinical staff including orthopaedics, internist and general practitioners, public health professionals and health management professionals to collaboratively identify areas to be intervened and develop specific interventions. Findings A total of ten focus group discussions were conducted, one in each province, involving 137 participants. These discussions identified ten key barriers and ten facilitators influencing the quality of hip fracture care. The patient journey mapping documented the treatment process for hip fractures in older adults across ten county-level hospitals, highlighting issues such as surgical delays and inadequate multidisciplinary collaboration. The co-design workshops led to the development of three interventions: (1) optimization of in-hospital management processes, (2) empowerment of surgeons and physicians, and (3) enhancement of awareness among patients and their families. Interpretation This study provides a comprehensive understanding of the challenges related to the management of hip fracture in resource-constrained county-level hospitals in China. The proposed interventions are expected to improve care quality and outcomes for patients with hip fractures in resource-constrained settings. Future efforts will focus on conducting randomized controlled trials to evaluate the effectiveness of these interventions. Funding This study was supported by the Beijing Hospitals Authority Clinical Medicine Development of Special Funding Support (code: ZLRK202310).