Associations between sleep duration trajectories and cognitive decline: A longitudinal cohort study in China.

OBJECT: The relationship between sleep duration trajectories and cognitive decline remains uncertain. This study aims to examine the connections between various patterns of sleep duration and cognitive function. METHODS: Group-based trajectory modeling (GBTM) was employed to identify longitudinal trajectories of sleep duration over four-year follow-up period, while considering age, sex and nap duration as adjustments. Logistic regression was utilized to analyze the association between sleep trajectories and cognition, with odds ratios (OR) and 95 % confidence intervals (CI) reported. Subgroup analyses based on various demographic characteristics were conducted to explore potential differences in sleep trajectories and cognitive decline across different population subgroups. RESULTS: A total of 5061 participants were followed for four years, and three sleep duration trajectories were identified: high increasing (n = 2101, 41.6 %), stable increasing (n = 2087, 40.7 %), and low decreasing (n = 873, 17.7 %). After adjustment for basic demographic information, health status, and baseline cognition, the high increasing trajectory was found to be associated with cognitive decline in terms of global cognition (OR:1.52,95 %CI:1.18-1.96), mental intactness (OR:1.36,95 %CI:1.07-1.73) and episodic memory (OR:1.33, 95 %CI:1.05-1.67), as compared to stable increasing trajectory. These associations were particularly prominent among the non-elderly population (≤65 years) and those without depressive symptoms. CONCLUSION: This study suggests that both high increasing and low decreasing sleep duration trajectories are linked to cognitive decline, as compared to the stable increasing trajectory. Long-term attention to changes in sleep duration facilitates early prevention of cognitive decline.

Development and external validation of a multimodal integrated feature neural network (MIFNN) for the diagnosis of malignancy in small pulmonary nodules (≤10 mm).

Objectives. Current lung cancer screening protocols primarily evaluate pulmonary nodules, yet often neglect the malignancy risk associated with small nodules (≤10 mm). This study endeavors to optimize the management of pulmonary nodules in this population by devising and externally validating a Multimodal Integrated Feature Neural Network (MIFNN). We hypothesize that the fusion of deep learning algorithms with morphological nodule features will significantly enhance diagnostic accuracy.Materials and Methods. Data were retrospectively collected from the Lung Nodule Analysis 2016 (LUNA16) dataset and four local centers in Beijing, China. The study includes patients with small pulmonary nodules (≤10 mm). We developed a neural network, termed MIFNN, that synergistically combines computed tomography (CT) images and morphological characteristics of pulmonary nodules. The network is designed to acquire clinically relevant deep learning features, thereby elevating the diagnostic accuracy of existing models. Importantly, the network's simple architecture and use of standard screening variables enable seamless integration into standard lung cancer screening protocols.Results. In summary, the study analyzed a total of 382 small pulmonary nodules (85 malignant) from the LUNA16 dataset and 101 small pulmonary nodules (33 malignant) obtained from four specialized centers in Beijing, China, for model training and external validation. Both internal and external validation metrics indicate that the MIFNN significantly surpasses extant state-of-the-art models, achieving an internal area under the curve (AUC) of 0.890 (95% CI: 0.848-0.932) and an external AUC of 0.843 (95% CI: 0.784-0.891).Conclusion. The MIFNN model significantly enhances the diagnostic accuracy of small pulmonary nodules, outperforming existing benchmarks by Zhanget alwith a 6.34% improvement for nodules less than 10 mm. Leveraging advanced integration techniques for imaging and clinical data, MIFNN increases the efficiency of lung cancer screenings and optimizes nodule management, potentially reducing false positives and unnecessary biopsies.Clinical relevance statement. The MIFNN enhances lung cancer screening efficiency and patient management for small pulmonary nodules, while seamlessly integrating into existing workflows due to its reliance on standard screening variables.

Remnant cholesterol traits and risk of stroke: A multivariable Mendelian randomization study.

Observational epidemiological studies have reported a relationship between remnant cholesterol and stroke. However, the results are inconclusive, and causality remains unclear due to confounding or reverse causality. Our objective in this study was to investigate the causal relevance of remnant cholesterol and the risk of stroke and its subtypes using the Mendelian randomization (MR) approach. Genome-wide association studies (GWASs) including 115,082 European individuals (UK Biobank) were used to identify instruments for remnant cholesterol, including intermediate-density lipoprotein (IDL) cholesterol and very-low-density lipoprotein (VLDL) cholesterol. Summary-level data for total stroke, intracerebral hemorrhage, subarachnoid hemorrhage, ischemic stroke (IS), and IS subtypes were obtained from GWAS meta-analyses conducted by the MEGASTROKE consortium. Univariable and multivariable MR analyses were performed. The GWAS identified multiple single-nucleotide polymorphisms after clumping for remnant cholesterol (n = 52), IDL cholesterol (n = 62), and VLDL cholesterol (n = 67). Assessed individually using MR, remnant cholesterol (weighted median: odds ratio [OR] 1.32 per 1-SD higher trait; 95% CI: 1.04-1.67; P = 0.024) had effect estimates consistent with a higher risk of LAS-IS, driven by IDL cholesterol (OR 1.32; 95% CI: 1.04-1.68; P = 0.022). In multivariable MR, IDL cholesterol (OR 1.46; 95% CI: 1.10-1.93; P = 0.009) retained a robust effect on LAS-IS after controlling for VLDL cholesterol and high-density lipoprotein cholesterol. The MR analysis did not indicate causal associations between remnant cholesterol and other stroke subtypes. This study suggests that remnant cholesterol is causally associated with the risk of LAS-IS driven by IDL cholesterol.

Temporal relationship between elevated serum uric acid levels and dyslipidemia: A 5-year cohort study using cross-lagged panel analysis.

BACKGROUND AND AIM: Previous studies have demonstrated an association between SUA and dyslipidemia. This study aims to explore the temporal relationship between SUA and dyslipidemia. METHODS AND RESULTS: Based on the Beijing Health Management Cohort conducted from 2013 to 2018, the data of a physical examination population was collected, including a total of 6630 study subjects. Cross-lagged panel analysis was employed to examine the temporal relationship between elevated SUA levels and dyslipidemia, indicated by either elevated TG or decreased HDL-C. The path coefficient and the 95 % CI from baseline TG to follow-up SUA were as follows: in the general population, men, women, and people with BMI ≥25 kg/m2were 0.027 (0.008-0.045), 0.024 (0.001-0.048), 0.032 (0.001-0.063) and 0.033 (0.006-0.059) (P < 0.05); however, the path coefficient from baseline SUA to follow-up TG and the 95 % CI were not statistically significant. Furthermore, the path coefficients and 95 % CIs between elevated SUA and decreased HDL-C were not statistically significant, both in the general population and in populations stratified by gender and BMI. CONCLUSIONS: We found a temporal relationship from elevated TG to elevated SUA in the general population and the populations stratified by gender and BMI (≥25 kg/m2). However, we did not observe a reverse relationship from elevated SUA to elevated TG. Additionally, we did not find a temporal relationship between decreased HDL-C and elevated SUA in both the general population and the stratified populations.

Association of Abnormal Lung Function and Its Subtypes With Arterial Stiffness: A Longitudinal Cohort Study.

BACKGROUND: Prior studies have reported the cross-sectional relationship between lung function and arterial stiffness, while the longitudinal association remains unclear to date. This study aimed to investigate whether abnormal lung function and its subtypes at baseline are associated with increased arterial stiffness using a cohort. METHODS AND RESULTS: This was a secondary analysis extracting 2461 participants from Beijing Health Management Cohort as baseline and annually followed for development of arterial stiffness. Abnormal lung function was defined by forced expiratory volume in 1s <80% of the predicted value, forced vital capacity of the predicted value, or forced expiratory volume in 1s/forced vital capacity ratio <70%. Increased arterial stiffness was determined by brachial-ankle pulse wave velocity ≥1400 cm/s. Cox proportional hazards model was used to calculate the hazard ratio and population attributable fraction. The mean age was 42.8±8.1 years, and 444 (18.0%) cases developed increased arterial stiffness during a median follow-up of 3.0 years. The adjusted hazard ratio (95% CI) of arterial stiffness was 1.47 (95% CI, 1.10-1.96) for abnormal lung function, with a population attributable fraction of 3.9% (95% CI, 0.8-7.1). Of subtypes, only obstructive ventilatory dysfunction was significantly associated with arterial stiffness (adjusted hazard ratio, 2.06 [95% CI, 1.27-3.36]), not restricted ventilatory dysfunction (adjusted hazard ratio, 0.95 [95% CI, 0.54-1.65]). Consistent results were observed on multiple sensitivity analyses. CONCLUSIONS: Our study indicated a longitudinal association of abnormal lung function with increased arterial stiffness using a large cohort, especially for the obstructive ventilatory dysfunction.

Machine Learning Model of ResNet50-Ensemble Voting for Malignant-Benign Small Pulmonary Nodule Classification on Computed Tomography Images.

BACKGROUND: The early detection of benign and malignant lung tumors enabled patients to diagnose lesions and implement appropriate health measures earlier, dramatically improving lung cancer patients' quality of living. Machine learning methods performed admirably when recognizing small benign and malignant lung nodules. However, exploration and investigation are required to fully leverage the potential of machine learning in distinguishing between benign and malignant small lung nodules. OBJECTIVE: The aim of this study was to develop and evaluate the ResNet50-Ensemble Voting model for detecting the benign and malignant nature of small pulmonary nodules (<20 mm) based on CT images. METHODS: In this study, 834 CT imaging data from 396 patients with small pulmonary nodules were gathered and randomly assigned to the training and validation sets in an 8:2 ratio. ResNet50 and VGG16 algorithms were utilized to extract CT image features, followed by XGBoost, SVM, and Ensemble Voting techniques for classification, for a total of ten different classes of machine learning combinatorial classifiers. Indicators such as accuracy, sensitivity, and specificity were used to assess the models. The collected features are also shown to investigate the contrasts between them. RESULTS: The algorithm we presented, ResNet50-Ensemble Voting, performed best in the test set, with an accuracy of 0.943 (0.938, 0.948) and sensitivity and specificity of 0.964 and 0.911, respectively. VGG16-Ensemble Voting had an accuracy of 0.887 (0.880, 0.894), with a sensitivity and specificity of 0.952 and 0.784, respectively. CONCLUSION: Machine learning models that were implemented and integrated ResNet50-Ensemble Voting performed exceptionally well in identifying benign and malignant small pulmonary nodules (<20 mm) from various sites, which might help doctors in accurately diagnosing the nature of early-stage lung nodules in clinical practice.

Association between nonalcoholic fatty liver disease and type 2 diabetes: A bidirectional two-sample mendelian randomization study.

OBJECTIVE: The aim of this study was to explore the mutually causal relationship between NAFLD and type 2 diabetes. METHODS: Based on the data obtained from GWAS, this study employed bidirectional two-sample MR analysis to investigate the causal relationship between NAFLD and type 2 diabetes, and also examined the causal relationship between liver fat accumulation and type 2 diabetes as well as the relationship between NAFLD and FPG, IR. RESULTS: In MR analysis of NAFLD and type 2 diabetes, when NAFLD as an exposure and type 2 diabetes as a result, the OR (95 % CI) was 1.10890 (1.00135-1.22801); in the reverse analysis, the OR value was not statistically significant. In MR analysis of NAFLD, FPG and IR, there was no statistical significance in both directions. In MR analysis of liver fat accumulation and type 2 diabetes, when liver fat as an exposure and type 2 diabetes as a result, the OR (95 % CI) was 1.17516 (1.02054-1.35321); in the reverse analysis, the OR value (95 % CI) was 1.06283 (1.02879-1.09799). CONCLUSION: There is a unidirectional causal relationship between NAFLD and type 2 diabetes. Furthermore, a bidirectional causal relationship exists between liver fat accumulation and type 2 diabetes.

Intraindividual difference in estimated GFR by creatinine and cystatin C, cognitive trajectories and motoric cognitive risk syndrome.

BACKGROUND: Intraindividual differences between estimated glomerular filtration rate (eGFR) based on cystatin C (eGFRcys) and creatinine (eGFRcr) can convey important clinical information regarding the health status. However, the clinical implications of these differences (eGFRdiff) for risk of cognitive decline and motoric cognitive risk syndrome (MCR) remains unclear. We aimed to investigate the longitudinal associations of eGFRdiff with cognitive trajectories and incident MCR. METHODS: Based on the China Health and Retirement Longitudinal Study, we identified two study sub-cohorts: one for cognitive trajectory follow-up (6423 participants; years:2011-2018) and another for incident MCR follow-up (2477 participants; years:2011-2015). The eGFRdiff was defined as eGFRcys minus eGFRcr. Adjusted ordinal and binary logistics regression models were separately used to assess the associations of eGFRdiff with cognitive trajectories and incident MCR. We also performed discordance analyses for eGFRdiff vs eGFRcys, eGFRcr or eGFR based on both creatinine and cystatin C (eGFRcys-cr). RESULTS: In the first sub-cohort, four distinct 7-year cognitive trajectories were identified. Each 1-SD higher eGFRdiff (value for eGFRcys minus eGFRcr) was associated with a lower risk of poorer cognitive trajectories (OR: 0.909, 95% CI: 0.877-0.942). In the second sub-cohort, 121 participants developed incident MCR after a 4-year follow-up. Each 1-SD higher eGFRdiff (value for eGFRcys minus eGFRcr) was linked with a 25.3% (95%CI: 16.6%-33.2%) decreased risk for MCR. The above associations persisted in individuals with normal kidney function. Additionally, the risk for cognitive decline and incident MCR was more strongly associated with eGFRcys than eGFRcr and eGFRcys-cr. For the discordance analyses, 'discordantly high eGFRdiff/low eGFR' group, but not 'discordantly low eGFRdiff/high eGFR', exhibited a significantly lower risk of poorer cognitive trajectories and MCR compared to the concordant group. CONCLUSIONS: A large negative difference between eGFRcys and eGFRcr (eGFRcys lower than eGFRcr) was associated with higher risk of cognitive decline and incident MCR. The eGFRdiff could capture additional valuable risk information beyond eGFRcys, eGFRcr, and eGFRcys-cr.

Bidirectional relationship between nonalcoholic fatty liver disease and serum creatinine-to-body weight ratio as a proxy for skeletal muscle mass index.

BACKGROUND AND AIM: Although an association between skeletal muscle mass index and nonalcoholic fatty liver disease (NAFLD) has previously been demonstrated, the causal direction remains unclear. Herein, we investigated the directional association between NAFLD and the serum creatinine-to-body weight ratio (sCr/bw), a surrogate marker of the muscle mass index, using longitudinal data. METHODS: We recruited 9662 participants in 2017 and performed follow-up over 4 years. We evaluated whether sCr/bw was related to NAFLD development (Analysis I) and whether NAFLD was associated with a low sCr/bw incidence (Analysis II) using logistic regression models. Furthermore, a random intercept cross-lagged panel model was applied to evaluate the bidirectional association between sCr/bw ratio and NAFLD (Analysis III). RESULTS: Analysis I demonstrated an association between sCr/bw and incident NAFLD (odds ratio [OR] = 0.160, 95% confidence interval [CI]:0.107-0.232). Analysis II indicated a relationship between NAFLD and subsequent low sCr/bw ratio (OR = 1.524, 95% CI: 1.258-1.846). Analysis III indicated that the standard regression coefficient from sCr/bw to subsequent hepatic steatosis (HS) was -0.053 for ßsCr/bw2017 â†’ HS2019 and -0.060 for ßsCr/bw2019 â†’ HS2021 and the coefficient from HS to subsequent sCr/bw was -0.093 for ßHS2017 â†’ sCr/bw2019 and -0.112 for ßHS2019 â†’ sCr/bw2021 (all P < 0.05). CONCLUSIONS: This study indicated mutual causality between sCr/bw and NAFLD. Considering that sCr/bw is a surrogate marker of muscle mass index, the findings emphasize that NAFLD and low muscle mass form a vicious cycle, which should be taken seriously in clinical practice.

Association of impaired sensitivity to thyroid hormones with hyperuricemia through obesity in the euthyroid population.

BACKGROUND: Impaired sensitivity to thyroid hormones is a newly proposed clinical entity associated with hyperuricemia in the subclinical hypothyroid population. However, it is unknown whether the association exists in the euthyroid population. This study aimed to explore the association of impaired sensitivity to thyroid hormones (assessed by the thyroid feedback quantile-based index [TFQI], parametric thyroid feedback quantile-based index [PTFQI], thyrotrophic thyroxine resistance index [TT4RI] and thyroid-stimulating hormone index [TSHI]) with hyperuricemia and quantify the mediating effect of body mass index BMI in the euthyroid population. METHODS: This cross-sectional study enrolled Chinese adults aged ≥ 20 years who participated in the Beijing Health Management Cohort (2008-2019). Adjusted logistic regression models were used to explore the association between indices of sensitivity to thyroid hormones and hyperuricemia. Odds ratios [OR] and absolute risk differences [ARD] were calculated. Mediation analyses were performed to estimate direct and indirect effects through BMI. RESULTS: Of 30,857 participants, 19,031 (61.7%) were male; the mean (SD) age was 47.3 (13.3) years; and 6,515 (21.1%) had hyperuricemia. After adjusting for confounders, individuals in the highest group of thyroid hormone sensitivity indices were associated with an increased prevalence of hyperuricemia compared with the lowest group (TFQI: OR = 1.18, 95% CI 1.04-1.35; PTFQI: OR = 1.20, 95% CI 1.05-1.36; TT4RI: OR = 1.17, 95% CI 1.08-1.27; TSHI: OR = 1.12, 95% CI 1.04-1.21). BMI significantly mediated 32.35%, 32.29%, 39.63%, and 37.68% of the associations of TFQI, PTFQI, TT4RI and TSHI with hyperuricemia, respectively. CONCLUSIONS: Our research revealed that BMI mediated the association between impaired sensitivity to thyroid hormones and hyperuricemia in the euthyroid population. These findings could provide useful evidence for understanding the interaction between impaired sensitivity to thyroid hormone and hyperuricemia in euthyroid individuals and suggest the clinical implications of weight control in terms of impaired thyroid hormones sensitivity.

Temporal and Bidirectional Association Between Blood Pressure Variability and Arterial Stiffness: Cross-Lagged Cohort Study.

BACKGROUND: The causal relationship between blood pressure variability (BPV) and arterial stiffness remains debated. OBJECTIVE: This study aimed to explore the temporal and bidirectional associations between long-term BPV and arterial stiffness using a cohort design with multiple surveys. METHODS: Participants from the Beijing Health Management Cohort who underwent health examinations from visit 1 (2010-2011) to visit 5 (2018-2019) were enrolled in this study. Long-term BPV was defined as intraindividual variation using the coefficient of variation (CV) and SD. Arterial stiffness was measured by brachial-ankle pulse wave velocity (baPWV). The bidirectional relationship between BPV and arterial stiffness was explored using cross-lagged analysis and linear regression models, with records before and after visit 3 categorized as phase 1 and phase 2, respectively. RESULTS: Of the 1506 participants, who were a mean of 56.11 (SD 8.57) years old, 1148 (76.2%) were male. The cross-lagged analysis indicated that the standardized coefficients of BPV at phase 1 directing to the baPWV level at phase 2 were statistically significant but not vice-versa. The adjusted regression coefficients of the CV were 4.708 (95% CI 0.946-8.470) for systolic blood pressure, 3.119 (95% 0.166-6.073) for diastolic pressure, and 2.205 (95% CI 0.300-4.110) for pulse pressure. The coefficients of the SD were 4.208 (95% CI 0.177-8.239) for diastolic pressure and 4.247 (95% CI 0.448-8.046) for pulse pressure. The associations were predominant in the subgroup with hypertension, but we did not observe any significant association of baPWV level with subsequent BPV indices. CONCLUSIONS: The findings supported a temporal relationship between long-term BPV and arterial stiffness level, especially among people with hypertension.

Separate and Joint Associations of Remnant Cholesterol Accumulation and Variability With Carotid Atherosclerosis: A Prospective Cohort Study.

Background We aimed to examine separate and joint associations of remnant cholesterol (RC) accumulation and variability with the risk of carotid atherosclerosis (CAS) in the general population. Methods and Results A total of 6213 participants who underwent 3 sequential health examinations during 2010 to 2015 were enrolled and were followed up until December 31, 2021. Cumulative RC (cumRC) and RC variability among the 3 visits were the exposure of interest in our study. Adjusted Cox models were performed to calculate the hazard ratio (HR) and 95% CI. C-statistics, integrated discrimination improvement, and the net reclassification index were used to estimate the incremental predictive ability. During a median follow-up of 4.00 years, 2613 participants developed CAS. Higher cumRC (HR, 1.33 [95% CI, 1.17-1.52]) and greater RC variability (HR, 1.22 [95% CI, 1.08-1.39]) were significantly associated with elevated risk of CAS, independent of traditional cardiovascular risk factors and low-density lipoprotein cholesterol. Participants were divided into 4 groups according to the median of cumRC and RC variability to assess their joint associations. Compared with "low cumRC and low variability," "high cumRC and high variability" had the highest risk of CAS, followed by "high cumRC and low variability" and "low cumRC and high variability." Finally, joint assessment of RC accumulation and variability had the significantly highest incremental effect on the predictive value of CAS versus single-time-point measures of RC. Conclusions Excessive cumRC levels and greater RC variability were each independently associated with higher incidence of CAS, and their coexistence could further yield significantly higher risks.

Association Between Long-Term Exposure to Fine Particulate Matter Constituents and Progression of Cerebral Blood Flow Velocity in Beijing: Modifying Effect of Greenness.

Few studies have explored the effects of fine particulate matter (PM2.5) and its constituents on the progression of cerebral blood flow velocity (BFV) and the potential modifying role of greenness. In this study, we investigated the association of PM2.5 and its constituents, including sulfate (SO4 2-), nitrate (NO3 -), ammonium (NH4 +), organic matter (OM), and black carbon (BC), with the progression of BFV in the middle cerebral artery. Participants from the Beijing Health Management Cohort who underwent at least two transcranial Doppler sonography examinations during 2015-2020 were recruited. BFV change and BFV change rate were used to define the progression of cerebral BFV. Linear mixed effects models were employed to analyze the data, and the weighted quantile sum regression assessed the contribution of PM2.5 constituents. Additionally, greenness was examined as a modifier. Among the examined constituents, OM exhibited the strongest association with BFV progression. An interquartile range increase in PM2.5 and OM exposure concentrations was associated with a decrease of -16.519 cm/s (95% CI: -17.837, -15.201) and -15.403 cm/s (95% CI: -16.681, -14.126) in BFV change, and -10.369 cm/s/year (95% CI: -11.387, -9.352) and -9.615 cm/s/year (95% CI: -10.599, -8.632) in BFV change rate, respectively. Furthermore, stronger associations between PM2.5 and BFV progression were observed in individuals working in areas with lower greenness, those aged under 45 years, and females. In conclusion, reducing PM2.5 levels in the air, particularly the OM constituent, and enhancing greenness could potentially contribute to the protection of cerebrovascular health.

Deep-Learning Model of ResNet Combined with CBAM for Malignant-Benign Pulmonary Nodules Classification on Computed Tomography Images.

Background and Objectives: Lung cancer remains a leading cause of cancer mortality worldwide. Accurately classifying benign pulmonary nodules and malignant ones is crucial for early diagnosis and improved patient outcomes. The purpose of this study is to explore the deep-learning model of ResNet combined with a convolutional block attention module (CBAM) for the differentiation between benign and malignant lung cancer, based on computed tomography (CT) images, morphological features, and clinical information. Methods and materials: In this study, 8241 CT slices containing pulmonary nodules were retrospectively included. A random sample comprising 20% (n = 1647) of the images was used as the test set, and the remaining data were used as the training set. ResNet combined CBAM (ResNet-CBAM) was used to establish classifiers on the basis of images, morphological features, and clinical information. Nonsubsampled dual-tree complex contourlet transform (NSDTCT) combined with SVM classifier (NSDTCT-SVM) was used as a comparative model. Results: The AUC and the accuracy of the CBAM-ResNet model were 0.940 and 0.867, respectively, in test set when there were only images as inputs. By combining the morphological features and clinical information, CBAM-ResNet shows better performance (AUC: 0.957, accuracy: 0.898). In comparison, a radiomic analysis using NSDTCT-SVM achieved AUC and accuracy values of 0.807 and 0.779, respectively. Conclusions: Our findings demonstrate that deep-learning models, combined with additional information, can enhance the classification performance of pulmonary nodules. This model can assist clinicians in accurately diagnosing pulmonary nodules in clinical practice.

Associations of time-weighted individual exposure to ambient particulate matter with carotid atherosclerosis in Beijing, China.

BACKGROUND: Time-location information (time spent on commuting, indoors and outdoors around residential and work places and physical activity) and infiltrated outdoor pollution was less considered estimating individual exposure to ambient air pollution. Studies investigating the association between individual exposure to particulate matter (PM) with aerodynamic diameter < 10 µm (PM10) and < 2.5 µm (PM2.5) and carotid atherosclerosis presented inconsistent results. Moreover, combined effect of pollutants on carotid atherosclerosis was not fully explored. We aimed to investigate the association between long-term individual time-weighted average exposure to PM2.5 and PM10 and the risk of carotid atherosclerosis, and further explore the overall effect of co-exposure to pollutants on carotid atherosclerosis. METHODS: The study population included 3069 participants derived from the Beijing Health Management Cohort (BHMC) study. Daily concentration of ambient air pollutants was estimated by land-use regression model at both residential and work addresses, and one- and two-year time-weighted average individual exposure was calculated by further considering personal activity pattern and infiltration of ambient air pollution indoors. We explored the association of PM2.5 and PM10 with carotid atherosclerosis and pooled the overall effect of co-exposure to ambient air pollutants by quantile g-computation. RESULTS: A significant association between time-weighted average exposure to PM2.5 and PM10 and carotid atherosclerosis was observed. Per interquartile range increase in two-year exposure to PM2.5 (Hazard ratio (HR): 1.322, 95% confidence interval (CI): 1.219-1.434) and PM10 (HR:1.213, 95% CI: 1.116-1.319) showed the strongest association with carotid atherosclerosis, respectively. Individuals in higher quartiles of pollutants were at higher risk for carotid atherosclerosis compared with those in the lowest quartile group. Concentration response functions documented the nearly linear and nonlinear relationship and interpreted the upward trends of the risk for carotid atherosclerosis with increasing level of pollutant concentrations. Moreover, effect estimates for the mixture of pollutants and carotid atherosclerosis were larger than any of the individual pollutants (HR (95% CI) was 1.510 (1.338-1.704) and 1.613 (1.428-1.822) per quartile increase for one-year and two-year time-weighted average exposure, respectively). CONCLUSIONS: Individual time-weighted average exposure to PM2.5 and PM10 was associated with carotid atherosclerosis. Co-exposure to ambient air pollution was also positively associated with carotid atherosclerosis.

Combined Evaluation of Arterial Stiffness and Blood Pressure Promotes Risk Stratification of Peripheral Arterial Disease.

Background: Previous studies have reported the separate association of arterial stiffness (AS) and blood pressure with peripheral arterial disease (PAD). Objectives: The aim of this study was to investigate the risk stratification capacity of AS on incident PAD beyond blood pressure status. Methods: A total of 8,960 participants from Beijing Health Management Cohort were enrolled at the first health visit between 2008 and 2018 and then followed until the incidence of PAD or 2019. Elevated AS was defined as brachial-ankle pulse-wave velocity (baPWV) >1,400 cm/s, including moderate stiffness (1,400 ≤ baPWV <1,800 cm/s) and severe stiffness (baPWV ≥1,800 cm/s). PAD was defined as ankle-brachial index <0.9. A frailty Cox model was used to calculate the HR, integrated discrimination improvement, and net reclassification improvement. Results: During follow-up, 225 participants (2.5%) developed PAD. After adjusting for confounding factors, the highest risk for PAD was observed in the group with elevated AS and blood pressure (HR: 2.253; 95% CI: 1.472-3.448). Among participants with ideal blood pressure and those with well-controlled hypertension, PAD risk was still significant for severe AS. The results remained consistent in multiple sensitivity analyses. In addition, baPWV significantly improved the predictive capacity for PAD risk beyond systolic and diastolic blood pressures (integrated discrimination improvement 0.020 and 0.190, net reclassification improvement 0.037 and 0.303). Conclusions: This study suggests the clinical importance of combined evaluation and control of AS and blood pressure for the risk stratification and prevention of PAD.

Identification and validation of IgG N-glycosylation biomarkers of esophageal carcinoma.

Introduction: Altered Immunoglobulin G (IgG) N-glycosylation is associated with aging, inflammation, and diseases status, while its effect on esophageal squamous cell carcinoma (ESCC) remains unknown. As far as we know, this is the first study to explore and validate the association of IgG N-glycosylation and the carcinogenesis progression of ESCC, providing innovative biomarkers for the predictive identification and targeted prevention of ESCC. Methods: In total, 496 individuals of ESCC (n=114), precancerosis (n=187) and controls (n=195) from the discovery population (n=348) and validation population (n=148) were recruited in the study. IgG N-glycosylation profile was analyzed and an ESCC-related glycan score was composed by a stepwise ordinal logistic model in the discovery population. The receiver operating characteristic (ROC) curve with the bootstrapping procedure was used to assess the performance of the glycan score. Results: In the discovery population, the adjusted OR of GP20 (digalactosylated monosialylated biantennary with core and antennary fucose), IGP33 (the ratio of all fucosylated monosyalilated and disialylated structures), IGP44 (the proportion of high mannose glycan structures in total neutral IgG glycans), IGP58 (the percentage of all fucosylated structures in total neutral IgG glycans), IGP75 (the incidence of bisecting GlcNAc in all fucosylated digalactosylated structures in total neutral IgG glycans), and the glycan score are 4.03 (95% CI: 3.03-5.36, P<0.001), 0.69 (95% CI: 0.55-0.87, P<0.001), 0.56 (95% CI: 0.45-0.69, P<0.001), 0.52 (95% CI: 0.41-0.65, P<0.001), 7.17 (95% CI: 4.77-10.79, P<0.001), and 2.86 (95% CI: 2.33-3.53, P<0.001), respectively. Individuals in the highest tertile of the glycan score own an increased risk (OR: 11.41), compared with those in the lowest. The average multi-class AUC are 0.822 (95% CI: 0.786-0.849). Findings are verified in the validation population, with an average AUC of 0.807 (95% CI: 0.758-0.864). Discussion: Our study demonstrated that IgG N-glycans and the proposed glycan score appear to be promising predictive markers for ESCC, contributing to the early prevention of esophageal cancer. From the perspective of biological mechanism, IgG fucosylation and mannosylation might involve in the carcinogenesis progression of ESCC, and provide potential therapeutic targets for personalized interventions of cancer progression.

Short-Term Effects of Carbon Monoxide on Morbidity of Chronic Obstructive Pulmonary Disease With Comorbidities in Beijing.

The association between CO and chronic obstructive pulmonary disease (COPD) has been widely reported; however, the association among patients with type 2 diabetes mellitus (T2DM) or hypertension has remained largely unknown in China. Over-dispersed generalized additive model was adopted to quantity the associations between CO and COPD with T2DM or hypertension. Based on principal diagnosis, COPD cases were identified according to the International Classification of Diseases (J44), and a history of T2DM and hypertension was coded as E12 and I10-15, O10-15, P29, respectively. A total of 459,258 COPD cases were recorded from 2014 to 2019. Each interquartile range uptick in CO at lag 03 corresponded to 0.21% (95%CI: 0.08%-0.34%), 0.39% (95%CI: 0.13%-0.65%), 0.29% (95%CI: 0.13%-0.45%) and 0.27% (95%CI: 0.12%-0.43%) increment in admissions for COPD, COPD with T2DM, COPD with hypertension and COPD with both T2DM and hypertension, respectively. The effects of CO on COPD with T2DM (Z = 0.77, P = 0.444), COPD with hypertension (Z = 0.19, P = 0.234) and COPD with T2DM and hypertension (Z = 0.61, P = 0.543) were insignificantly higher than that on COPD. Stratification analysis showed that females were more vulnerable than males except for T2DM group (COPD: Z = 3.49, P < 0.001; COPD with T2DM: Z = 0.176, P = 0.079; COPD with hypertension: Z = 2.48, P = 0.013; COPD with both T2DM and hypertension: Z = 2.44, P = 0.014); No statistically significant difference could be found between age groups (COPD: Z = 1.63, P = 0.104; COPD with T2DM: Z = 0.23, P = 0.821; COPD with hypertension: Z = 0.53, P = 0.595; COPD with both T2DM and hypertension: Z = 0.71, P = 0.476); Higher effects appeared in cold seasons than warm seasons on COPD (Z = 0.320, P < 0.001). This study demonstrated an increased risk of COPD with comorbidities related to CO exposure in Beijing. We further provided important information on lag patterns, susceptible subgroups, and sensitive seasons, as well as the characteristics of the exposure-response curves.

Distinct hyperuricemia trajectories are associated with different risks of incident diabetes: A prospective cohort study.

BACKGROUND AND AIM: Conflicting results suggest a link between serum uric acid and diabetes and previous studies ignored the effect of continuous exposure of serum uric acid on diabetes risk. This study aims to characterize hyperuricemia trajectories in middle-aged adults and to examine its potential impact on diabetes risk, considering the role of obesity, dyslipidemia, and hypertension. METHODS AND RESULTS: The cohort included 9192 participants who were free of diabetes before 2013. The hyperuricemia trajectories during 2009-2013 were identified by latent class growth models. Incident diabetes during 2014-2018 was used as the outcome. Modified Poisson regression models were used to assess the association of trajectories with diabetes. Furthermore, marginal structural models were used to estimate the mediating effects of the relationship between hyperuricemia trajectories and diabetes. We identified three discrete hyperuricemia trajectories: high-increasing (n = 5794), moderate-stable (n = 2049), and low-stable (n = 1349). During 5 years of follow-up, we documented 379 incident diabetes cases. Compared with the low-stable pattern, the high-increasing pattern had a higher risk of developing diabetes (RR, 1.42; 95% CI: 1.09-1.84). In addition, the percentages of total effect between the high-increasing hyperuricemia pattern and diabetes mediated by obesity, dyslipidemia, and hypertension were 24.41%, 18.26%, and 6.29%. However, the moderate-stable pattern was not associated with an increased risk of diabetes. CONCLUSIONS: These results indicate that the high-increasing hyperuricemia trajectory is significantly associated with an increased risk of diabetes. Furthermore, obesity, dyslipidemia, and hypertension play mediating roles in the relationship between the high-increasing hyperuricemia pattern and increased diabetes risk.

Longitudinal association of remnant cholesterol with joint arteriosclerosis and atherosclerosis progression beyond LDL cholesterol.

BACKGROUND: Arteriosclerosis and atherosclerosis are closely related with cardiovascular disease (CVD) risk. Remnant cholesterol (RC) could predict CVD. However, its effect on joint arteriosclerosis and atherosclerosis progression remains unclear. This study aims to evaluate the association of RC with joint arteriosclerosis and atherosclerosis progression trajectories in the general population. METHODS: This study collected data across five biennial surveys of the Beijing Health Management Cohort from 2010 to 2019. Multi-trajectory model was used to determine the joint arteriosclerosis and atherosclerosis progression patterns by brachial-ankle pulse wave velocity (baPWV) and ankle brachial index (ABI). We also performed discordance analyses for RC vs. low density lipoprotein cholesterol (LDL-C) using ordinal logistics model. RESULTS: A total of 3186 participants were included, with three clusters following distinct arteriosclerosis and atherosclerosis progression patterns identified using a multi-trajectory model. In the multivariable-adjusted ordinal logistics analyses, RC was significantly associated with baPWV and ABI progression (OR: 1.20; 95% CI: 1.13-1.28, per 10 mg/dL). For the discordance analyses, the discordant low RC group was associated with decreased risk compared to the concordant group (OR: 0.73; 95% CI: 0.60-0.89). People with a high RC level were at an increased risk of joint arteriosclerosis and atherosclerosis progression, even with optimal LDL-C. CONCLUSIONS: RC is independently associated with joint arteriosclerosis and atherosclerosis progression beyond LDL-C. RC could be an earlier risk factor than LDL-C of arteriosclerosis and atherosclerosis in the general population.