Minimal improvement in coronary artery disease risk prediction in Chinese population using polygenic risk scores: evidence from the China Kadoorie Biobank / 中华医学杂志(英文版)

BACKGROUND@#Several studies have reported that polygenic risk scores (PRSs) can enhance risk prediction of coronary artery disease (CAD) in European populations. However, research on this topic is far from sufficient in non-European countries, including China. We aimed to evaluate the potential of PRS for predicting CAD for primary prevention in the Chinese population.@*METHODS@#Participants with genome-wide genotypic data from the China Kadoorie Biobank were divided into training ( n = 28,490) and testing sets ( n = 72,150). Ten previously developed PRSs were evaluated, and new ones were developed using clumping and thresholding or LDpred method. The PRS showing the strongest association with CAD in the training set was selected to further evaluate its effects on improving the traditional CAD risk-prediction model in the testing set. Genetic risk was computed by summing the product of the weights and allele dosages across genome-wide single-nucleotide polymorphisms. Prediction of the 10-year first CAD events was assessed using hazard ratios (HRs) and measures of model discrimination, calibration, and net reclassification improvement (NRI). Hard CAD (nonfatal I21-I23 and fatal I20-I25) and soft CAD (all fatal or nonfatal I20-I25) were analyzed separately.@*RESULTS@#In the testing set, 1214 hard and 7201 soft CAD cases were documented during a mean follow-up of 11.2 years. The HR per standard deviation of the optimal PRS was 1.26 (95% CI:1.19-1.33) for hard CAD. Based on a traditional CAD risk prediction model containing only non-laboratory-based information, the addition of PRS for hard CAD increased Harrell's C index by 0.001 (-0.001 to 0.003) in women and 0.003 (0.001 to 0.005) in men. Among the different high-risk thresholds ranging from 1% to 10%, the highest categorical NRI was 3.2% (95% CI: 0.4-6.0%) at a high-risk threshold of 10.0% in women. The association of the PRS with soft CAD was much weaker than with hard CAD, leading to minimal or no improvement in the soft CAD model.@*CONCLUSIONS@#In this Chinese population sample, the current PRSs minimally changed risk discrimination and offered little improvement in risk stratification for soft CAD. Therefore, this may not be suitable for promoting genetic screening in the general Chinese population to improve CAD risk prediction.

Heritability of tea drinking and its relationship with cigarette smoking in the Chinese male adult twins.

The aims of this study are to estimate the contributions of genetic factors to the variation of tea drinking and cigarette smoking, to examine the roles of genetic factors in their correlation and further to investigate underlying causation between them. We included 11 625 male twin pairs from the Chinese National Twin Registry (CNTR). Bivariate genetic modelling was fitted to explore the genetic influences on tea drinking, cigarette smoking and their correlation. Inference about Causation through Examination of FAmiliaL CONfounding (ICE FALCON) was further used to explore the causal relationship between them. We found that genetic factors explained 17% and 23% of the variation in tea drinking and cigarette smoking, respectively. A low phenotypic association between them was reported (rph = 0.21, 95% confidence interval [CI]: [0.19, 0.24]), which was partly attributed to common genetic factors (rA = 0.45, 95% CI [0.19, 1.00]). In the ICE FALCON analysis with current smoking as the exposure, tea drinking was associated with his own (ßself = 0.39, 95% CI [0.23, 0.55]) and his co-twin's smoking status (ßco-twin = 0.25, 95% CI [0.10, 0.41]). Their association attenuated with borderline significance conditioning on his own smoking status (p = 0.045), indicating a suggestive causal effect of smoking status on tea drinking. On the contrary, when we used tea drinking as the predictor, we found familial confounding between them only. In conclusion, both tea drinking and cigarette smoking were influenced by genetic factors, and their correlation was partly explained by common genetic factors. In addition, our finding suggests that familial confounders account for the relationship between tea drinking and cigarette smoking. And current smoking might have a causal effect on weekly tea drinking, but not vice versa.

Multimorbidity patterns and association with mortality in 0.5 million Chinese adults / 中华医学杂志(英文版)

BACKGROUND@#Few studies have assessed the relationship between multimorbidity patterns and mortality risk in the Chinese population. We aimed to identify multimorbidity patterns and examined the associations of multimorbidity patterns and the number of chronic diseases with the risk of mortality among Chinese middle-aged and older adults.@*METHODS@#We used data from the China Kadoorie Biobank and included 512,723 participants aged 30 to 79 years. Multimorbidity was defined as the presence of two or more of the 15 chronic diseases collected by self-report or physical examination at baseline. Multimorbidity patterns were identified using hierarchical cluster analysis. Cox regression was used to estimate the associations of multimorbidity patterns and the number of chronic diseases with all-cause and cause-specific mortality.@*RESULTS@#Overall, 15.8% of participants had multimorbidity. The prevalence of multimorbidity increased with age and was higher in urban than rural participants. Four multimorbidity patterns were identified, including cardiometabolic multimorbidity (diabetes, coronary heart disease, stroke, and hypertension), respiratory multimorbidity (tuberculosis, asthma, and chronic obstructive pulmonary disease), gastrointestinal and hepatorenal multimorbidity (gallstone disease, chronic kidney disease, cirrhosis, peptic ulcer, and cancer), and mental and arthritis multimorbidity (neurasthenia, psychiatric disorder, and rheumatoid arthritis). During a median of 10.8 years of follow-up, 49,371 deaths occurred. Compared with participants without multimorbidity, cardiometabolic multimorbidity (hazard ratios [HR] = 2.20, 95% confidence intervals [CI]: 2.14 - 2.26) and respiratory multimorbidity (HR = 2.13, 95% CI:1.97 - 2.31) demonstrated relatively higher risks of mortality, followed by gastrointestinal and hepatorenal multimorbidity (HR = 1.33, 95% CI:1.22 - 1.46). The mortality risk increased by 36% (HR = 1.36, 95% CI: 1.35 - 1.37) with every additional disease.@*CONCLUSION@#Cardiometabolic multimorbidity and respiratory multimorbidity posed the highest threat on mortality risk and deserved particular attention in Chinese adults.

A population-based seroprevalence survey of severe acute respiratory syndrome coronavirus 2 infection in Beijing, China

BACKGOUNDThe spread of Coronavirus Disease 2019 (COVID-19) had been controlled in China. The seroprevalence of COVID-19 in Beijing has not been evaluated. METHODSIn April, residents in Beijing were randomly enrolled. Blood samples were collected and antibodies to SARS- CoV-2 were tested by two colloidal gold kits. All colloidal gold positive serums were then tested by Micro- neutralization assay. RESULTSNone of 2,184 residents participated was tested positive by micro-neutralization assay. The seroprevalence of COVID-19 in Beijing was estimated < 0.17%. CONCLUSIONSThe seroprevalence of COVID-19 was low in April suggesting that community-wide spread was prevented in Beijing.