Objective:To explore the relationship between obesity indicators and DNA methylation clocks acceleration,and to analyze their temporal sequence.Methods:Data were obtained from two sur-veys conducted in 2013 and 2017-2018 by the Chinese National Twin Registry.Peripheral blood DNA methylation data were measured using the Illumina Infinium Human Methylation 450K BeadChip and EPIC BeadChip.DNA methylation clocks/acceleration metrics(GrimAA,PCGrimAA and Dunedin-PACE)were calculated using the DNA methylation online tool(https://dnamage.genetics.ucla.edu/)or R code provided by researchers.Obesity indicators included weight,body mass index(BMI),waist circumference,waist-hip ratio,and waist-height ratio.A total of 1 070 twin individuals were included in the cross-sectional analysis,comprising 378 monozygotic(MZ)twin pairs and 155 dizygotic(DZ)twin pairs for within-pair analysis.Mixed-effects models were used to examine the associations between obesity indicators and DNA methylation clocks,as well as their acceleration measures.The longitudinal analysis included 314 twin individuals,comprising 95 MZ twin pairs and 62 DZ twin pairs for within-pair analy-sis.Cross-lagged panel models were applied to further explore the temporal relationships between obesity and DNA methylation clock indicators.All analyses were conducted both in the full twin sample and separately within MZ and DZ twin pairs.Results:In the cross-sectional analysis population,monozygotic twins accounted for 71.0％,males for 68.0％,and the mean chronological age was(49.9±12.1)years.In the longitudinal analysis population,monozygotic twins accounted for 60.5％,males for 60.8％,with a mean baseline chronological age of(50.4±10.2)years and a mean follow-up duration of(4.6±0.6)years.Except for the waist-to-hip ratio,which was significantly higher at follow-up com-pared with baseline,no statistically significant differences were observed in the means of other obesity in-dicators between baseline and follow-up.Correlation analysis revealed that weight,BMI,waist circumfe-rence,waist-hip ratio(WHR),and waist-height ratio(WHtR)were positively correlated with Dunedin-PACE in all the twins,with WHtR showing the strongest association(β=0.21,95％CI:0.11 to 0.31).Weight and BMI were negatively associated with GrimAA(β=-0.03,95％CI:-0.05 to-0.01;β=-0.07,95％CI:-0.12 to-0.02),while weight was negatively associated with PCGrim-AA(β=-0.02,95％CI:-0.03 to 0.00).However,within-twin-pair analyses showed no statistically significant correlations.Cross-lagged panel model analysis indicated that higher baseline weight might lead to increased GrimAA at follow-up,while elevated baseline weight,BMI,and waist circumference might increase PCGrimAA.Higher baseline WHR was associated with increased DunedinPACE at follow-up.Conclusion:Obesity indicators correlate with DNA methylation clock acceleration metrics.Baseline obesity may influence changes in certain DNA methylation clock indicators over time,suggesting that obesity could exert long-term health effects by accelerating DNA methylation aging.However,these associations may be confounded by shared genetic or environmental factors among the twins.

Objective:To describe the distribution characteristics of alcohol consumption in adult twins in the Chinese National Twin Registry (CNTR), and further explore the influence of genetic factors on alcohol consumption in adult twins.Methods:The subjects of the study were twins registered by CNTR in 11 project areas across China from 2010 to 2018. A total of 56 966 twins (28 483 pairs) aged 18 years and above who answered questions about drinking behavior were included, and the random effect model was used to describe the population and regional distribution characteristics of alcohol consumption. Intra-pair analysis was performed to calculate the concordance rate and heritability of their alcohol consumption.Results:The age of all subjects was (36.6±12.0) years, and current drinkers accounted for 16.6% (9 461/56 966) of all subjects. In men, those aged 50-59 years, those in northern China, those living in rural area, those with low education level and those with high BMI, the proportions of current drinkers were higher. After excluding 468 pairs of twins who had stopped alcohol use and 21 764 pairs of twins who had no drink or had small amount drink, an intra-pair analysis was conducted in 4 929 pairs of same-sex twins, and found that the concordance rate of alcohol consumption was 64.0% (2 059/3 215) in monozygotic twins, and 52.6% (902/1 714) in dizygotic twins, the difference was significant ( P<0.001), and the heritability of alcohol consumption was 24.1% (95% CI: 18.9%- 29.3%). The further stratified analysis found that in southern men, the heritability was highest in those aged 40-49 years (36.1%, 95% CI: 21.6%-50.7%), while in northern men, the heritability was highest in those aged 50-59 years (34.2%, 95% CI: 18.1%-50.3%). Conclusions:In adult twins in China, there were population and regional differences in the distribution of alcohol consumption behavior, and alcohol consumption was influenced by genetic factors, and gender, age and region had potential modifying effects.

This study aims to describe the population and regional distribution characteristics of smoking behavior among adult twins in the China Twin Registry (CNTR), as well as the concordance rates for smoking behavior in monozygotic and dizygotic twins, and estimate the heritability. The study population included adult twins in CNTR who had smoking questionnaire data. A random-effects regression model was used to describe the distribution of smoking behavior among different subgroups based on various characteristics. The concordance of smoking behavior between different zygosity groups was calculated, and heritability was estimated. A total of 28 444 twin pairs were included in this study, with an average age of (36.6±12.0) years. Among male twins, 41.2% were current smokers, while only 1.2% of females smoked. Higher smoking rates were observed among male smokers in the 50-59 age group ( z=23.0, P<0.001), northern regions ( z=2.9, P<0.01), rural areas ( z=-5.2, P<0.001), those who were divorced/widowed ( z=3.8, P<0.001), and first-born twins ( z=-4.3, P<0.001), while lower smoking rates were found in those with higher education ( z=-16.1, P<0.001) and unmarried individuals ( z=-16.0, P<0.001). The smoking concordance rate for male monozygotic twins was 69.6%, significantly higher than the 57.3% concordance rate for dizygotic twins ( χ 2=105.0, P<0.05). The heritability of smoking behavior in male twins was estimated at 28.9% (95% CI: 24.3%-33.4%). Stratified analyses showed differences in heritability across regions and age groups: the heritability in northern regions was 32.6% (95% CI: 27.3%-38.0%), higher than the 21.0% (95% CI: 12.4%-29.5%) observed in southern regions; the highest heritability of 35.1% (95% CI: 26.3%-43.9%) was found in the 18-29 age group, with heritability decreasing with age. In conclusion, the smoking rate and influencing factors in the twin population are similar to those in the general population, with unique characteristics, such as higher smoking rates in first-born twins. Genetic factors have a significant impact on smoking behavior.

This study aims to describe the population and regional distribution characteristics of smoking behavior among adult twins in the China Twin Registry (CNTR), as well as the concordance rates for smoking behavior in monozygotic and dizygotic twins, and estimate the heritability. The study population included adult twins in CNTR who had smoking questionnaire data. A random-effects regression model was used to describe the distribution of smoking behavior among different subgroups based on various characteristics. The concordance of smoking behavior between different zygosity groups was calculated, and heritability was estimated. A total of 28 444 twin pairs were included in this study, with an average age of (36.6±12.0) years. Among male twins, 41.2% were current smokers, while only 1.2% of females smoked. Higher smoking rates were observed among male smokers in the 50-59 age group ( z=23.0, P<0.001), northern regions ( z=2.9, P<0.01), rural areas ( z=-5.2, P<0.001), those who were divorced/widowed ( z=3.8, P<0.001), and first-born twins ( z=-4.3, P<0.001), while lower smoking rates were found in those with higher education ( z=-16.1, P<0.001) and unmarried individuals ( z=-16.0, P<0.001). The smoking concordance rate for male monozygotic twins was 69.6%, significantly higher than the 57.3% concordance rate for dizygotic twins ( χ 2=105.0, P<0.05). The heritability of smoking behavior in male twins was estimated at 28.9% (95% CI: 24.3%-33.4%). Stratified analyses showed differences in heritability across regions and age groups: the heritability in northern regions was 32.6% (95% CI: 27.3%-38.0%), higher than the 21.0% (95% CI: 12.4%-29.5%) observed in southern regions; the highest heritability of 35.1% (95% CI: 26.3%-43.9%) was found in the 18-29 age group, with heritability decreasing with age. In conclusion, the smoking rate and influencing factors in the twin population are similar to those in the general population, with unique characteristics, such as higher smoking rates in first-born twins. Genetic factors have a significant impact on smoking behavior.

Objective:To explore the relationship between obesity indicators and DNA methylation clocks acceleration,and to analyze their temporal sequence.Methods:Data were obtained from two sur-veys conducted in 2013 and 2017-2018 by the Chinese National Twin Registry.Peripheral blood DNA methylation data were measured using the Illumina Infinium Human Methylation 450K BeadChip and EPIC BeadChip.DNA methylation clocks/acceleration metrics(GrimAA,PCGrimAA and Dunedin-PACE)were calculated using the DNA methylation online tool(https://dnamage.genetics.ucla.edu/)or R code provided by researchers.Obesity indicators included weight,body mass index(BMI),waist circumference,waist-hip ratio,and waist-height ratio.A total of 1 070 twin individuals were included in the cross-sectional analysis,comprising 378 monozygotic(MZ)twin pairs and 155 dizygotic(DZ)twin pairs for within-pair analysis.Mixed-effects models were used to examine the associations between obesity indicators and DNA methylation clocks,as well as their acceleration measures.The longitudinal analysis included 314 twin individuals,comprising 95 MZ twin pairs and 62 DZ twin pairs for within-pair analy-sis.Cross-lagged panel models were applied to further explore the temporal relationships between obesity and DNA methylation clock indicators.All analyses were conducted both in the full twin sample and separately within MZ and DZ twin pairs.Results:In the cross-sectional analysis population,monozygotic twins accounted for 71.0％,males for 68.0％,and the mean chronological age was(49.9±12.1)years.In the longitudinal analysis population,monozygotic twins accounted for 60.5％,males for 60.8％,with a mean baseline chronological age of(50.4±10.2)years and a mean follow-up duration of(4.6±0.6)years.Except for the waist-to-hip ratio,which was significantly higher at follow-up com-pared with baseline,no statistically significant differences were observed in the means of other obesity in-dicators between baseline and follow-up.Correlation analysis revealed that weight,BMI,waist circumfe-rence,waist-hip ratio(WHR),and waist-height ratio(WHtR)were positively correlated with Dunedin-PACE in all the twins,with WHtR showing the strongest association(β=0.21,95％CI:0.11 to 0.31).Weight and BMI were negatively associated with GrimAA(β=-0.03,95％CI:-0.05 to-0.01;β=-0.07,95％CI:-0.12 to-0.02),while weight was negatively associated with PCGrim-AA(β=-0.02,95％CI:-0.03 to 0.00).However,within-twin-pair analyses showed no statistically significant correlations.Cross-lagged panel model analysis indicated that higher baseline weight might lead to increased GrimAA at follow-up,while elevated baseline weight,BMI,and waist circumference might increase PCGrimAA.Higher baseline WHR was associated with increased DunedinPACE at follow-up.Conclusion:Obesity indicators correlate with DNA methylation clock acceleration metrics.Baseline obesity may influence changes in certain DNA methylation clock indicators over time,suggesting that obesity could exert long-term health effects by accelerating DNA methylation aging.However,these associations may be confounded by shared genetic or environmental factors among the twins.

Objective:To describe the distribution characteristics of alcohol consumption in adult twins in the Chinese National Twin Registry (CNTR), and further explore the influence of genetic factors on alcohol consumption in adult twins.Methods:The subjects of the study were twins registered by CNTR in 11 project areas across China from 2010 to 2018. A total of 56 966 twins (28 483 pairs) aged 18 years and above who answered questions about drinking behavior were included, and the random effect model was used to describe the population and regional distribution characteristics of alcohol consumption. Intra-pair analysis was performed to calculate the concordance rate and heritability of their alcohol consumption.Results:The age of all subjects was (36.6±12.0) years, and current drinkers accounted for 16.6% (9 461/56 966) of all subjects. In men, those aged 50-59 years, those in northern China, those living in rural area, those with low education level and those with high BMI, the proportions of current drinkers were higher. After excluding 468 pairs of twins who had stopped alcohol use and 21 764 pairs of twins who had no drink or had small amount drink, an intra-pair analysis was conducted in 4 929 pairs of same-sex twins, and found that the concordance rate of alcohol consumption was 64.0% (2 059/3 215) in monozygotic twins, and 52.6% (902/1 714) in dizygotic twins, the difference was significant ( P<0.001), and the heritability of alcohol consumption was 24.1% (95% CI: 18.9%- 29.3%). The further stratified analysis found that in southern men, the heritability was highest in those aged 40-49 years (36.1%, 95% CI: 21.6%-50.7%), while in northern men, the heritability was highest in those aged 50-59 years (34.2%, 95% CI: 18.1%-50.3%). Conclusions:In adult twins in China, there were population and regional differences in the distribution of alcohol consumption behavior, and alcohol consumption was influenced by genetic factors, and gender, age and region had potential modifying effects.

Objective To analyze Professor Zhang Binghou's medication experience in the treatment of diabetic kidney disease using data mining methods;To screen the core medicinal pairs and medicinal groups.Methods Prescriptions of diabetic kidney disease of Professor Zhang Binghou from the outpatient department of Beijing Hospital of Traditional Chinese Medicine Affiliated to Capital Medical University were selected from January 2014 to December 2021.TCM Inheritance Platform System 2.5,SPSS Modeler 18 and SPSS Statistics 21 software were used for association rules,clustering analysis and factor analysis to summarize the medication frequency,properties and tastes and meridians,and medicinal pairs and combinations.Results A total of 161 prescriptions were included,involving 188 kinds of Chinese materia medica,with a total frequency of 2 220 time.The kinds of Chinese materia medica with higher frequency were Rehmannize Radix et Praeparata,Testudinis Carapax et Plastrum,Astragali Radix,Rehmannine Radix,etc.The main properties were cold and warm,the main tastes were sweet and bitter,and the main meridians were kidney,liver and spleen meridians.A total of 14 drug pair association rules were obtained,with 27 commonly used drug combinations.Clustering analysis extracted 10 combinations based on the spectrum,and factor analysis extracted 14 common factors.Conclusion Professor Zhang Binghou's treatment for diabetic kidney disease takes nourishing the true yin and clearing away damp-heat as the main treatment method,and at the same time,it pays attention to tonifying kidney,consolidating essence,nourishing yin and containing yang,promoting blood circulation and removing blood stasis,etc.,which embodies Professor Zhang Binghou's unique academic thought of treating diabetic kidney disease.

Objective:To investigate the independent and combined effects of maternal smoking during pregnancy and offspring genetic susceptibility on overall cancer mortality.Methods:Based on the United Kingdom Biobank ( n=419 228) data, the Cox proportional hazard regression model was used to estimate the effect of maternal smoking during pregnancy on offspring overall cancer (including 16 cancers in men and 18 in women) mortality and its combined effect and interaction with offspring genetic factors. Results:Maternal smoking during pregnancy was significantly associated with a 13% increased risk of overall cancer mortality in men [hazard ratio( HR)=1.13, 95% CI: 1.06-1.20] and 19% increased risk in women ( HR=1.19, 95% CI: 1.11-1.27). Participants with high genetic risk had the highest overall cancer mortality than those with low genetic risk (men: HR=1.42, 95% CI: 1.30-1.55; women: HR=1.38, 95% CI: 1.25-1.52). Compared with participants without maternal smoking during pregnancy and low genetic risk, those with maternal smoking during pregnancy and high genetic risk were associated with a 56% increased risk of overall cancer mortality in men ( HR=1.56, 95% CI: 1.37-1.77) and 59% in women ( HR=1.59, 95% CI: 1.39-1.83). Conclusion:Maternal smoking during pregnancy may increase offspring overall cancer mortality and more severe harm in individuals with high genetic risk.

Objective:To investigate the impact of air pollution on dynamic changes in lung function and further explore the association between genetic factors and lung function and its changes.Methods:Research data were from 14 506 participants in the United Kingdom Biobank with two complete baseline and follow-up lung function tests. Particulate matter [including particulate matter with aerodynamic diameter ≤2.5 μm and ≤10 μm (PM 2.5 and PM 10)], nitrogen dioxide (NO 2), and nitrogen oxides (NO x) concentrations were estimated using land-use regression models. Annual changes in lung function were calculated based on baseline and follow-up lung function tests. Polygenic risk scores (PRS) of lung function [forced expiratory volume in the first second (FEV 1), forced vital capacity (FVC), and the ratio of FEV 1 to FVC (FEV 1/FVC)] were constructed by genetic variations. The association between air pollution concentrations and lung function changes was analyzed by multiple linear regression models, and the impact of genetic factors on lung function and its changes was also assessed. Results:PM 2.5, PM 10, NO 2, and NO x showed a negative correlation with FVC changes [PM 2.5: -6.66 (95% CI: -9.92- -3.40) ml/year; PM 10: -0.40 (95% CI: -0.77- -0.03) ml/year; NO 2: -1.84 (95% CI: -2.60- -1.07) ml/year; NO x: -1.37 (95% CI: -2.27- -0.46) ml/year]. Additionally, PM 2.5, PM 10and NO 2 were also negatively correlated with changes in FEV 1 [PM 2.5: -3.19 (95% CI: -5.79- -0.59) ml/year; PM 10: -3.00 (95% CI: -5.92- -0.08) ml/year; NO 2: -0.95 (95% CI: -1.56- -0.34) ml/year]. PRS of lung function were positively correlated with baseline lung function (FVC, FEV 1, and FEV 1/FVC) and lung function changes (all β>0, all P<0.001). In different PRS stratification analyses, the effect of air pollution on lung function changes remained significant, and there was no apparent heterogeneity. Conclusions:PRS of lung function are significantly associated with baseline and lung function changes. Long-term exposure to air pollution accelerates the decline of lung function indicators such as FVC and FEV 1. The effects of air pollution are consistent in individuals with different genetic risk scores.