The novel coronavirus disease-2019 (COVID-19) has been spreading around the world rapidly and declared as a pandemic by WHO. Here, we compared the ABO blood group distribution in 2,173 patients with COVID-19 confirmed by SARS-CoV-2 test from three hospitals in Wuhan and Shenzhen, China with that in normal people from the corresponding regions. The results showed that blood group A was associated with a higher risk for acquiring COVID-19 compared with non-A blood groups, whereas blood group O was associated with a lower risk for the infection compared with non-O blood groups. This is the first observation of an association between the ABO blood type and COVID-19. It should be emphasized, however, that this is an early study with limitations. It would be premature to use this study to guide clinical practice at this time, but it should encourage further investigation of the relationship between the ABO blood group and the COVID-19 susceptibility.

Aims: To construct a polygenic risk score (PRS) for coronary artery disease (CAD) and comprehensively evaluate its potential in clinical utility for primary prevention in Chinese populations. Methods and results: Using meta-analytic approach and large genome-wide association results for CAD and CAD-related traits in East Asians, a PRS comprising 540 genetic variants was developed in a training set of 2800 patients with CAD and 2055 controls, and was further assessed for risk stratification for CAD integrating with the guideline-recommended clinical risk score in large prospective cohorts comprising 41 271 individuals. During a mean follow-up of 13.0 years, 1303 incident CAD cases were identified. Individuals with high PRS (the highest 20%) had about three-fold higher risk of CAD than the lowest 20% (hazard ratio 2.91, 95% confidence interval 2.43–3.49), with the lifetime risk of 15.9 and 5.8%, respectively. The addition of PRS to the clinical risk score yielded a modest yet significant improvement in C-statistic (1%) and net reclassification improvement (3.5%). We observed significant gradients in both 10-year and lifetime risk of CAD according to the PRS within each clinical risk strata. Particularly, when integrating high PRS, intermediate clinical risk individuals with uncertain clinical decision for intervention would reach the risk levels (10-year of 4.6 vs. 4.8%, lifetime of 17.9 vs. 16.6%) of high clinical risk individuals with intermediate (20–80%) PRS. Conclusion: The PRS could stratify individuals into different trajectories of CAD risk, and further refine risk stratification for CAD within each clinical risk strata, demonstrating a great potential to identify high-risk individuals for targeted intervention in clinical utility.

A meta-analysis of exome-wide association studies for blood lipid levels in East Asian populations identifies a novel coding variant. Exome array data from the Global Lipids Genetics Consortium were integrated and led to the discovery of novel and population-specific variants associated with cholesterol and triglycerides. Most genome-wide association studies have been of European individuals, even though most genetic variation in humans is seen only in non-European samples. To search for novel loci associated with blood lipid levels and clarify the mechanism of action at previously identified lipid loci, we used an exome array to examine protein-coding genetic variants in 47,532 East Asian individuals. We identified 255 variants at 41 loci that reached chip-wide significance, including 3 novel loci and 14 East Asian–specific coding variant associations. After a meta-analysis including >300,000 European samples, we identified an additional nine novel loci. Sixteen genes were identified by protein-altering variants in both East Asians and Europeans, and thus are likely to be functional genes. Our data demonstrate that most of the low-frequency or rare coding variants associated with lipids are population specific, and that examining genomic data across diverse ancestries may facilitate the identification of functional genes at associated loci.

The risk of incident hypertension associated with long-term exposure to fine particulate matter (PM _2.5 ) was still unclear by studies conducted in North America and Europe, and this relationship has rarely been quantified at higher ambient concentrations typically found in developing countries. We aimed to investigate the association between PM _2.5 and incident hypertension using the large-scale prospective cohorts in China. We included 59 456 participants without hypertension aged ≥18 years from the China-PAR (Prediction for Atherosclerotic Cardiovascular Disease Risk in China) project. Data on ambient PM _2.5 at participants’ residential address were obtained during 2004 to 2015 using a satellite-based spatial-temporal model. Hazard ratios and 95% CIs were calculated for incident hypertension using stratified Cox proportional hazards models with adjustment of potential confounders. The findings indicated that average PM _2.5 concentration from 2004 to 2015 at study participants’ address was 77.7 μg/m ³ . During the follow-up of 364 947 person-years, we identified 13 981 incident hypertension cases. Compared with the lowest quartile exposure of PM _2.5 , participants in the highest quartile had an increased risk of incident hypertension with a hazard ratio (95% CI) of 1.77 (1.56–2.00). Each 10 μg/m ³ increment of PM _2.5 concentration could increase 11% risk of hypertension (hazard ratio, 1.11; 95% CI, 1.05–1.17). This cohort study provided the first evidence from China that long-term exposure to PM _2.5 was independently associated with incident hypertension at relatively high ambient concentrations. Stringent strategies on PM _2.5 pollution control are warranted to improve the air quality and contribute to the reduction of disease burden of hypertension in China.

Diabetes caused substantial economic and health burden worldwide. However, the associations between air pollution and diabetes incidence were rarely reported in the developing countries, especially in China with relatively high PM2.5 concentrations. A cohort-based study was conducted to assess the diabetes incidence associated with long-term exposure to ambient PM2.5. We collected individual health data and risk factors from the project of Prediction for Atherosclerotic Cardiovascular Disease Risk in China (China-PAR Project) from 15 provinces over China. Diabetes was defined as fasting glucose levels ≥7.0 mmol/L at the follow-ups and/or the use of insulin or oral hypoglycemic agents and/or diagnosed medical history of diabetes during 2004 to 2015. Individual-level PM2.5 exposures were estimated from satellite-based PM2.5 concentrations (10 km spatial resolution) during the study period. Cox proportional hazards models with random intercepts of each cohort and region were employed to estimate the diabetes incidence attributable to PM2.5, after the adjustment for age, gender, body mass index, smoking status, education, work-related physical activity level, hypertension, urbanicity, county-level averaged years of education, and long-term levels of temperature and relative humidity. A total of 88,397 subjects were analyzed with 580,928 person-years of follow-up after 2004, among which 6439 new cases of diabetes were observed. The mean age of the subjects was 51.7 years at baseline. For an increase of 10 μg/m3 in long-term PM2.5 exposure, the multivariable-adjusted percent increase in the diabetes incidence was estimated to be 15.66% (95% confidence interval: 6.42%, 25.70%). The adverse effects of PM2.5 were larger among females, rural subjects, non-smokers, normotensives, subjects younger than 65 years and subjects with body mass index <25 kg/m2. Our findings provided evidence for the association of long-term exposure to PM2.5 with diabetes incidence in China. A sustained improvement of air quality will benefit the reduction for diabetes epidemic in China.

Rationale: Limited cohort studies have evaluated chronic effects of high fine particulate matter (PM_2.5) exposure on lung cancer. Objectives: To investigate the response pattern of lung cancer associated with high PM_2.5 exposure. Methods: A Chinese cohort of 118,551 participants was followed up from 1992 to 2015. By incorporating with PM_2.5 exposure at 1 km spatial resolution during 2000-2015 generated using the satellite-based model, we estimated the association between lung cancer and time-weighted average PM_2.5 concentration using Cox proportional hazard models. Measurements and Main Results: 844 incident lung cancer cases were identified during 915,053 person-years of follow-up. Among them, 701 lung cancer deaths occurred later. The exposure-response curves for lung cancer associated with PM_2.5 exposure were non-linear, with steeper slopes at the higher concentration. Adjusted for age, sex, geographical region, urbanization, education level, smoking status, alcohol consumption, work-related physical activity and body mass index, participants exposed to the 2^nd-5^th quintiles of PM_2.5 had higher risk for lung cancer incidence than the 1^st quintile, with hazard ratios of 1.44 (95% confidence interval [CI]: 1.10-1.88), 1.49 (95% CI: 1.12-1.99), 2.08 (95% CI: 1.42-3.04) and 2.45 (95% CI: 1.83-3.29), respectively. The corresponding hazard ratios for lung cancer mortality were 1.83 (95% CI: 1.33-2.50), 1.80 (95% CI: 1.29-2.53), 2.50 (95% CI: 1.62-3.86) and 2.95 (95% CI: 2.09-4.17), respectively. Conclusions: We provides strong evidence that high PM_2.5 exposure leads to elevated risk of lung cancer incidence and mortality, highlighting that remarkable public health benefits could be obtained from improvement of air quality in highly polluted regions.