Association of Structural Forms of 17q21.31 with the Risk of Progressive Supranuclear Palsy and MAPT Sub-haplotypes.

Importance: The chromosome 17q21.31 region, containing a 900 Kb inversion that defines H1 and H2 haplotypes, represents the strongest genetic risk locus in progressive supranuclear palsy (PSP). In addition to H1 and H2, various structural forms of 17q21.31, characterized by the copy number of α, ß, and γ duplications, have been identified. However, the specific effect of each structural form on the risk of PSP has never been evaluated in a large cohort study. Objective: To assess the association of different structural forms of 17q.21.31, defined by the copy numbers of α, ß, and γ duplications, with the risk of PSP and MAPT sub-haplotypes. Design setting and participants: Utilizing whole genome sequencing data of 1,684 (1,386 autopsy confirmed) individuals with PSP and 2,392 control subjects, a case-control study was conducted to investigate the association of copy numbers of α, ß, and γ duplications and structural forms of 17q21.31 with the risk of PSP. All study subjects were selected from the Alzheimer's Disease Sequencing Project (ADSP) Umbrella NG00067.v7. Data were analyzed between March 2022 and November 2023. Main outcomes and measures: The main outcomes were the risk (odds ratios [ORs]) for PSP with 95% CIs. Risks for PSP were evaluated by logistic regression models. Results: The copy numbers of α and ß were associated with the risk of PSP only due to their correlation with H1 and H2, while the copy number of γ was independently associated with the increased risk of PSP. Each additional duplication of γ was associated with 1.10 (95% CI, 1.04-1.17; P = 0.0018) fold of increased risk of PSP when conditioning H1 and H2. For the H1 haplotype, addition γ duplications displayed a higher odds ratio for PSP: the odds ratio increases from 1.21 (95%CI 1.10-1.33, P = 5.47 × 10-5) for H1ß1γ1 to 1.29 (95%CI 1.16-1.43, P = 1.35 × 10-6) for H1ß1γ2, 1.45 (95%CI 1.27-1.65, P = 3.94 × 10-8) for H1ß1γ3, and 1.57 (95%CI 1.10-2.26, P = 1.35 × 10-2) for H1ß1γ4. Moreover, H1ß1γ3 is in linkage disequilibrium with H1c (R2 = 0.31), a widely recognized MAPT sub-haplotype associated with increased risk of PSP. The proportion of MAPT sub-haplotypes associated with increased risk of PSP (i.e., H1c, H1d, H1g, H1o, and H1h) increased from 34% in H1ß1γ1 to 77% in H1ß1γ4. Conclusions and relevance: This study revealed that the copy number of γ was associated with the risk of PSP independently from H1 and H2. The H1 haplotype with more γ duplications showed a higher odds ratio for PSP and were associated with MAPT sub-haplotypes with increased risk of PSP. These findings expand our understanding of how the complex structure at 17q21.31 affect the risk of PSP.

Structural Variation Detection and Association Analysis of Whole-Genome-Sequence Data from 16,905 Alzheimer's Diseases Sequencing Project Subjects.

Structural variations (SVs) are important contributors to the genetics of human diseases. However, their role in Alzheimer's disease (AD) remains largely unstudied due to challenges in accurately detecting SVs. We analyzed whole-genome sequencing data from the Alzheimer's Disease Sequencing Project (N = 16,905) and identified 400,234 (168,223 high-quality) SVs. Laboratory validation yielded a sensitivity of 82% (85% for high-quality). We found a significant burden of deletions and duplications in AD cases, particularly for singletons and homozygous events. On AD genes, we observed the ultra-rare SVs associated with the disease, including protein-altering SVs in ABCA7, APP, PLCG2, and SORL1. Twenty-one SVs are in linkage disequilibrium (LD) with known AD-risk variants, exemplified by a 5k deletion in complete LD with rs143080277 in NCK2. We also identified 16 SVs associated with AD and 13 SVs linked to AD-related pathological/cognitive endophenotypes. This study highlights the pivotal role of SVs in shaping our understanding of AD genetics.

Structural Variation Detection and Association Analysis of Whole-Genome-Sequence Data from 16,905 Alzheimer's Diseases Sequencing Project Subjects.

Structural variations (SVs) are important contributors to the genetics of numerous human diseases. However, their role in Alzheimer's disease (AD) remains largely unstudied due to challenges in accurately detecting SVs. Here, we analyzed whole-genome sequencing data from the Alzheimer's Disease Sequencing Project (ADSP, N=16,905 subjects) and identified 400,234 (168,223 high-quality) SVs. We found a significant burden of deletions and duplications in AD cases (OR=1.05, P=0.03), particularly for singletons (OR=1.12, P=0.0002) and homozygous events (OR=1.10, P<0.0004). On AD genes, the ultra-rare SVs, including protein-altering SVs in ABCA7, APP, PLCG2, and SORL1, were associated with AD (SKAT-O P=0.004). Twenty-one SVs are in linkage disequilibrium (LD) with known AD-risk variants, e.g., a deletion (chr2:105731359-105736864) in complete LD (R2=0.99) with rs143080277 (chr2:105749599) in NCK2. We also identified 16 SVs associated with AD and 13 SVs associated with AD-related pathological/cognitive endophenotypes. Our findings demonstrate the broad impact of SVs on AD genetics.

Ambient temperature variability and hospital admissions for pneumonia: A nationwide study.

Few investigations have assessed the impact of short-term ambient temperature change on pneumonia risk. We aimed to study the relation of temperature variability (TV) with daily hospitalizations for pneumonia in China. We conducted a time-series study in 184 major cities by extracting daily hospital data between 2014 and 2017 from a medical insurance claims database of 0.28 billion beneficiaries. TV was calculated as standard deviation of daily minimum and maximum temperatures over exposure days. We estimated associations of pneumonia admissions with TV for each city using over-dispersed generalized linear models controlling for weather conditions and ambient air pollution, and pooled city-specific estimates using random effects meta-analyses. We also investigated exposure-response relationship curve and potential effect modifiers. We identified 4.2 million pneumonia hospitalizations during the study period. TV was positively related to daily pneumonia admissions. At the national-average level, each 1-°C increase in TV at 0-6 days' exposure corresponded to a 0.65 % (95 % CI: 0.34 %-0.96 %) increase in pneumonia admissions. An approximately linear exposure-response curve for the relation of TV with pneumonia admission was noted. The relations were more evident in cities with larger average age (P = 0.038). As the first study in China to assess the impact of temperature change on pneumonia on a national scale, our results indicated that acute TV exposure was related to higher admissions for pneumonia. Our findings should provide new insight into the health impacts associated with climate change.

Short-term exposure to ambient air pollution and risk of daily hospital admissions for anxiety in China: A multicity study.

The potential impact of short-term exposure to ambient air pollution on risk of anxiety remains uncertain. We performed a detailed evaluation based on data from national insurance databases in China. Daily hospital admissions for anxiety disorders were identified in 2013-2017 from the national insurance databases covering up to 261 million urban residents in 56 cities in China. A two-stage time-series study was conducted to evaluate the associations between short-term exposure to major ambient air pollutants, including fine particles, inhalable particles, nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone, and carbon monoxide, and risk of daily hospital admissions for anxiety. Significant associations between short-term exposures to ambient NO2 and SO2 and risk of daily hospital admissions for anxiety were found in the overall analysis. Per 10 µg/m3 increases in NO2 at lag0 and SO2 at lag6 were associated with significant increases of 1.37% (95% CI: 0.14%, 2.62%) and 1.53% (95% CI: 0.59%, 2.48%) in anxiety admissions, respectively. Stronger associations were found in the southern region and patients <65 years for SO2. Short-term exposure to ambient air pollution is associated with increased risk of anxiety admissions, which may provide important implications for promotion of mental health in the public.

Short-Term Ambient Particulate Air Pollution and Hospitalization Expenditures of Cause-Specific Cardiorespiratory Diseases in China: A Multicity Analysis.

BACKGROUND: Ambient air pollution is leading risk factor for health burden in China. Few studies in China have investigated the economic loss related to short-term exposure to ambient PM2.5, which could trigger acute onset of cardiorespiratory diseases within a few days. METHODS: Daily ambient air pollutants data are obtained for each city from the National Air Quality Monitoring System and daily hospitalization data are obtained from the urban employee-based basic medical insurance scheme database in 74 Chinese cities with an average coverage of 88.5 million urban employees during 2016-2017. A three-stage time-series analytic approach is used in this study to investigate the impact of short-term exposure to ambient fine particulate (PM2.5) air pollution on hospital admissions, expenses and hospital stays of three cause-specific cardiorespiratory diseases, including lower respiratory infections (LRI), coronary heart disease (CHD) and stroke in the included cities. FINDINGS: Based on the time-series analysis using daily hospitalization data, 28,560 LRI cases, 54,600 CHD cases, and 23,989 stroke cases are attributable to ambient PM2.5 in the 74 cities during the study period, and the related attributable expenses are 220 million CNY (US$ 32.9 million) for LRI, 458 million CNY (US$ 68.5 million) for CHD, and 410 million CNY (US$ 65.8 million) for stroke, respectively. These attributable numbers account for 1.45% to 2.05% of total hospital admissions and 1.10% to 1.51% of total expenses for the three diseases during 2016-2017, respectively. The attributable numbers for the three cause-specific cardiorespiratory diseases would increase to 362,007 hospital admission cases and 3.68 billion CNY expenses ($US550 million) in the entire urban employee population (299 million) in China during 2016-2017, and the related direct economic loss of absence from work would be 798 million CNY (US$ 119.3 million). INTERPRETATION: Our results support that short-term exposure to ambient PM2.5 pollution could lead to significant health and economic impacts in China. Reducing levels of ambient PM2.5 can avoid substantial health damage and expenditures, and generate appreciable economic benefits from decreasing absence from work. FUNDING: Natural Science Foundation of China (82073509, 71903010, 71903011), and the National Key Research and Development Program of China (2017YFC0211600, 2017YFC0211601).

Association Between Ambient Air Pollution and Daily Hospital Admissions for Depression in 75 Chinese Cities.

OBJECTIVE: Although the association between ambient air pollution and risk of depression has been investigated in several epidemiological studies, the evidence is still lacking for hospital admissions for depression, which indicates a more severe form of depressive episode. The authors used national morbidity data to investigate the association between short-term exposure to ambient air pollution and daily hospital admissions for depression. METHODS: Using data from the Chinese national medical insurance databases for urban populations, the authors conducted a two-stage time-series analysis to investigate the associations of short-term exposure to major ambient air pollutants-fine particles (PM2.5), inhalable particles (PM10), nitrogen dioxide (NO2), sulfur dioxide (SO2), ozone (O3), and carbon monoxide (CO)-and daily hospital admission risk for depression in 75 Chinese cities during the period 2013-2017. RESULTS: The authors identified 111,620 hospital admissions for depression in 75 cities. In the single-pollutant models, the effect estimates of all included air pollutants, with the exception of O3, were significant at several lags within 7 days. For example, 10 µg/m3 increases in PM2.5, PM10, and NO2 at lag01 were associated with increases of 0.52% (95% CI=0.03, 1.01), 0.41% (95% CI=0.05, 0.78), and 1.78% (95% CI=0.73, 2.83), respectively, in daily hospital admissions for depression. Subgroup, sensitivity, and two-pollutant model analyses highlighted the robustness of the effect estimates for NO2. CONCLUSIONS: The study results suggest that short-term exposure to ambient air pollution is associated with an increased risk of daily hospital admission for depression in the general urban population in China, which may have important implications for improving mental wellness among the public.

The impact of ambient ozone pollution on pneumonia: A nationwide time-series analysis.

Few large multicity studies have assessed acute effect of tropospheric ozone pollution on pneumonia risk. We aimed to examine the relation between day-to-day changes in ozone concentrations and hospital admissions for pneumonia in China. We conducted a national time-series study in 184 major Chinese cities from 2014 to 2017. City-specific relation between ozone concentrations and pneumonia admissions was evaluated using an over-dispersed generalized additive model. Random-effects meta-analysis was conducted to pool the city-specific estimates. Two-pollutant models were fitted to test the robustness of the relations. We also investigated potential effect modifiers. Overall, we observed increased admissions for pneumonia associated with ozone exposure. The national-average estimates per 10-µg/m3 increase in ozone were 0.14% (95% CI: 0.03%-0.25%) at lag 0 day in the whole year, 0.30% (95% CI: 0.17%-0.43%) at lag 0 day in the warm season, and 0.20% (95% CI: 0.05%-0.34%) at lag 1 day in the cool season. Two-pollutant models indicated that the ozone effects were not confounded by PM2.5, SO2, NO2 or CO. The association between ozone and pneumonia was stronger in the elderly. Ozone levels and gross domestic product per capita reduced the effects of ozone, and smoking enhanced the effects of ozone. In conclusion, we estimated an increase in daily pneumonia admissions associated with ozone exposure in China. As the first national study in China to report acute effect of ozone on pneumonia hospitalizations, our findings are incredibly meaningful in terms of both ozone pollution related policy development and pneumonia prevention.

Multimorbidity of cardiometabolic diseases: prevalence and risk for mortality from one million Chinese adults in a longitudinal cohort study.

OBJECTIVES: The evolution of multimorbidity describes the continuum from a healthy status to the development of a single disease and further progression to multimorbidity with additional diseases. We investigated the evolution of cardiometabolic multimorbidity and risk for mortality in a Chinese population. DESIGN: Longitudinal cohort study using data from the CHinese Electronic health Records Research in Yinzhou (CHERRY) study, with 5.43 million person-years follow-up (median 5.16 years). PARTICIPANTS: Data for 1 038 704 adults (total 22 750 deaths) were analysed. EXPOSURE: Cardiometabolic multimorbidity was defined as ever being diagnosed with two or more of three diseases: hypertension, diabetes and cardiovascular disease (CVD). PRIMARY AND SECONDARY OUTCOME MEASURES: Age-adjusted and sex-adjusted HRs were calculated for all-cause mortality. RESULTS: The cardiometabolic disease status of 105 209 (10.1%) individuals changed during the follow-up. The prevalence of cardiometabolic multimorbidity increased from 2.41% (95% CI: 2.38% to 2.44%) to 5.94% (95% CI: 5.90% to 5.99%). Baseline multimorbidity status showed the HR (95% CI) was 1.37 (1.33 to 1.42) in those with one disease, 1.71 (1.64 to 1.79) in those with two diseases and 2.22 (2.00 to 2.46) in those with three diseases. The highest HRs were observed for CVD only (3.31, 95% CI: 3.05 to 3.59) or diabetes and CVD (3.12, 95% CI: 2.37 to 4.11). Those with hypertension only had the lowest HR (1.26, 95% CI: 1.22 to 1.30). Longitudinal data showed the HRs (95% CI) in patients with one, two and three diseases were 1.36 (1.32 to 1.41), 2.03 (1.96 to 2.10) and 2.16 (2.05 to 2.29), respectively. CONCLUSIONS: The prevalence of cardiometabolic multimorbidity in a general Chinese population increased more than doubled over 5 years, indicating rapid evolution of cardiometabolic multimorbidity. A history of CVD dominates the risk for mortality. A complementary strategy for primary and secondary prevention of cardiometabolic diseases is needed in China.

Performance of atherosclerotic cardiovascular risk prediction models in a rural Northern Chinese population: Results from the Fangshan Cohort Study.

BACKGROUND: Performance of Pooled Cohort Equations (PCEs) for atherosclerotic cardiovascular disease (ASCVD) risks varied across populations. Whether the recently developed Prediction for ASCVD Risk in China (China-PAR) model could accurately predict cardiovascular risks in real practice remains unclear. METHODS: A population-based cohort study in rural Beijing in the "stroke belt" in North China was used to externally validate PCE and China-PAR models for 5-year ASCVD risk prediction. Expected 5-year prediction risk using China-PAR model was compared with PCE (white). The models were assessed for calibration, discrimination, and reclassification. RESULTS: Among 11,169 adults aged 40 to 79 years over a median 6.44 years of follow-up, 1,921 participants developed a first ASCVD event during total 70,951 person-years. China-PAR model fairly predicted ASCVD risk in men but overestimated by 29.4% risk in women (calibration χ2 = 81.4, P < .001). Underestimations were shown by PCE as 76.2% in men and 88.2% in women with poor calibration (both P < .001). However, discrimination was similar in both models: C-statistics in men were 0.685 (95% CI 0.660-0.710) for China-PAR and 0.675 (95% CI 0.649-0.701) for PCE; C-statistics in women were 0.711 (95% CI 0.694-0.728) for China-PAR and 0.714 (95% CI 0.697-0.731) for PCE. Moreover, China-PAR did not substantially improve accuracy of reclassification compared with PCE. CONCLUSIONS: China-PAR outperformed PCE in 5-year ASCVD risk prediction in this rural Northern Chinese population at average population risk level, fairly predicted risk in men, but overestimated risk in women; however, China-PAR did not meaningfully improve the accuracy of discrimination and reclassification at individual risk level.

Association between temperature variability and daily hospital admissions for cause-specific cardiovascular disease in urban China: A national time-series study.

BACKGROUND: Epidemiological studies have provided compelling evidence of associations between ambient temperature and cardiovascular disease. However, evidence of effects of daily temperature variability on cardiovascular disease is scarce and mixed. We aimed to examine short-term associations between temperature variability and hospital admissions for cause-specific cardiovascular disease in urban China. METHODS AND FINDINGS: We conducted a national time-series analysis in 184 cities in China between 2014 and 2017. Data on daily hospital admissions for ischemic heart disease, heart failure, heart rhythm disturbances, and ischemic stroke were obtained from the database of Urban Employee Basic Medical Insurance (UEBMI) including 0.28 billion enrollees. Temperature data were acquired from the China Meteorological Data Sharing Service Center. Temperature variability was calculated from the standard deviation (SD) of daily minimum and maximum temperatures over exposure days. City-specific associations between temperature variability and cardiovascular disease were examined with overdispersed Poisson models controlling for calendar time, day of the week, public holiday, and daily mean temperature and relative humidity. Random-effects meta-analyses were performed to obtain national and regional average associations. We also plotted exposure-response relationship curve using a natural cubic spline of temperature variability. There were 8.0 million hospital admissions for cardiovascular disease during the study period. At the national-average level, a 1-°C increase in temperature variability at 0-1 days (TV0-1) was associated with a 0.44% (0.32%-0.55%), 0.31% (0.20%-0.43%), 0.48% (0.01%-0.96%), 0.34% (0.01%-0.67%), and 0.82% (0.59%-1.05%) increase in hospital admissions for cardiovascular disease, ischemic heart disease, heart failure, heart rhythm disturbances, and ischemic stroke, respectively. The estimates decreased but remained significant when controlling for ambient fine particulate matter (PM2.5), NO2, and SO2 pollution. The main limitation of the present study was the unavailability of data on individual exposure to temperature variability. CONCLUSIONS: Our findings suggested that short-term temperature variability exposure could increase the risk of cardiovascular disease, which may provide new insights into the health effects of climate change.

Association between ambient fine particulate pollution and hospital admissions for cause specific cardiovascular disease: time series study in 184 major Chinese cities.

OBJECTIVE: To estimate the risks of daily hospital admissions for cause specific major cardiovascular diseases associated with short term exposure to ambient fine particulate matter (aerodynamic diameter ≤2.5 µm; PM2.5) pollution in China. DESIGN: National time series study. SETTING: 184 major cities in China. POPULATION: 8 834 533 hospital admissions for cardiovascular causes in 184 Chinese cities recorded by the national database of Urban Employee Basic Medical Insurance from 1 January 2014 to 31 December 2017. MAIN OUTCOME MEASURES: Daily counts of city specific hospital admissions for primary diagnoses of ischaemic heart disease, heart failure, heart rhythm disturbances, ischaemic stroke, and haemorrhagic stroke among different demographic groups were used to estimate the associations between PM2.5 and morbidity. An overdispersed generalised additive model was used to estimate city specific associations between PM2.5 and cardiovascular admissions, and random effects meta-analysis used to combine the city specific estimates. RESULTS: Over the study period, a mean of 47 hospital admissions per day (standard deviation 74) occurred for cardiovascular disease, 26 (53) for ischaemic heart disease, one (five) for heart failure, two (four) for heart rhythm disturbances, 14 (28) for ischaemic stroke, and two (four) for haemorrhagic stroke. At the national average level, an increase of 10 µg/m3 in PM2.5 was associated with a 0.26% (95% confidence interval 0.17% to 0.35%) increase in hospital admissions on the same day for cardiovascular disease, 0.31% (0.22% to 0.40%) for ischaemic heart disease, 0.27% (0.04% to 0.51%) for heart failure, 0.29% (0.12% to 0.46%) for heart rhythm disturbances, and 0.29% (0.18% to 0.40%) for ischaemic stroke, but not with haemorrhagic stroke (-0.02% (-0.23% to 0.19%)). The national average association of PM2.5 with cardiovascular disease was slightly non-linear, with a sharp slope at PM2.5 levels below 50 µg/m3, a moderate slope at 50-250 µg/m3, and a plateau at concentrations higher than 250 µg/m3. Compared with days with PM2.5 up to 15 µg/m3, days with PM2.5 of 15-25, 25-35, 35-75, and 75 µg/m3 or more were significantly associated with increases in cardiovascular admissions of 1.1% (0 to 2.2%), 1.9% (0.6% to 3.2%), 2.6% (1.3% to 3.9%), and 3.8% (2.1% to 5.5%), respectively.According to projections, achieving the Chinese grade 2 (35 µg/m3), Chinese grade 1 (15 µg/m3), and World Health Organization (10 µg/m3) regulatory limits for annual mean PM2.5 concentrations would reduce the annual number of admissions for cardiovascular disease in China. Assuming causality, which should be done with caution, this reduction would translate into an estimated 36 448 (95% confidence interval 24 441 to 48 471), 85 270 (57 129 to 113 494), and 97 516 (65 320 to 129 820), respectively. CONCLUSIONS: These data suggest that in China, short term exposure to PM2.5 is associated with increased hospital admissions for all major cardiovascular diseases except for haemorrhagic stroke, even for exposure levels not exceeding the current regulatory limits.

Ambient particulate matter pollution and adult hospital admissions for pneumonia in urban China: A national time series analysis for 2014 through 2017.

BACKGROUND: The effects of ambient particulate matter (PM) pollution on pneumonia in adults are inconclusive, and few scientific data on a national scale have been generated in low- or middle-income countries, despite their much higher PM concentrations. We aimed to examine the association between PM levels and hospital admissions for pneumonia in Chinese adults. METHODS AND FINDINGS: A nationwide time series study was conducted in China between 2014 and 2017. Information on daily hospital admissions for pneumonia for 2014-2017 was collected from the database of Urban Employee Basic Medical Insurance (UEBMI), which covers 282.93 million adults. Associations of PM concentrations and hospital admissions for pneumonia were estimated for each city using a quasi-Poisson regression model controlling for time trend, temperature, relative humidity, day of the week, and public holiday and then pooled by random-effects meta-analysis. Meta-regression models were used to investigate potential effect modifiers, including cities' annual-average air pollutants concentrations, temperature, relative humidity, gross domestic product (GDP) per capita, and coverage rates by the UEBMI. More than 4.2 million pneumonia admissions were identified in 184 Chinese cities during the study period. Short-term elevations in PM concentrations were associated with increased pneumonia admissions. At the national level, a 10-µg/m3 increase in 3-day moving average (lag 0-2) concentrations of PM2.5 (PM ≤2.5 µm in aerodynamic diameter) and PM10 (PM ≤10 µm in aerodynamic diameter) was associated with 0.31% (95% confidence interval [CI] 0.15%-0.46%, P < 0.001) and 0.19% (0.11%-0.30%, P < 0.001) increases in hospital admissions for pneumonia, respectively. The effects of PM10 were stronger in cities with higher temperatures (percentage increase, 0.031%; 95% CI 0.003%-0.058%; P = 0.026) and relative humidity (percentage increase, 0.011%; 95% CI 0%-0.022%; P = 0.045), as well as in the elderly (percentage increase, 0.10% [95% CI 0.02%-0.19%] for people aged 18-64 years versus 0.32% [95% CI 0.22%-0.39%] for people aged ≥75 years; P < 0.001). The main limitation of the present study was the unavailability of data on individual exposure to PM pollution. CONCLUSIONS: Our findings suggest that there are significant short-term associations between ambient PM levels and increased hospital admissions for pneumonia in Chinese adults. These findings support the rationale that further limiting PM concentrations in China may be an effective strategy to reduce pneumonia-related hospital admissions.

Using big data to improve cardiovascular care and outcomes in China: a protocol for the CHinese Electronic health Records Research in Yinzhou (CHERRY) Study.

INTRODUCTION: Data based on electronic health records (EHRs) are rich with individual-level longitudinal measurement information and are becoming an increasingly common data source for clinical risk prediction worldwide. However, few EHR-based cohort studies are available in China. Harnessing EHRs for research requires a full understanding of data linkages, management, and data quality in large data sets, which presents unique analytical opportunities and challenges. The purpose of this study is to provide a framework to establish a uniquely integrated EHR database in China for scientific research. METHODS AND ANALYSIS: The CHinese Electronic health Records Research in Yinzhou (CHERRY) Study will extract individual participant data within the regional health information system of an eastern coastal area of China to establish a longitudinal population-based ambispective cohort study for cardiovascular care and outcomes research. A total of 1 053 565 Chinese adults aged over 18 years were registered in the health information system in 2009, and there were 23 394 deaths from 1 January 2009 to 31 December 2015. The study will include information from multiple epidemiological surveys; EHRs for chronic disease management; and health administrative, clinical, laboratory, drug and electronic medical record (EMR) databases. Follow-up of fatal and non-fatal clinical events is achieved through records linkage to the regional system of disease surveillance, chronic disease management and EMRs (based on diagnostic codes from the International Classification of Diseases, tenth revision). The CHERRY Study will provide a unique platform and serve as a valuable big data resource for cardiovascular risk prediction and population management, for primary and secondary prevention of cardiovascular events in China. ETHICS AND DISSEMINATION: The CHERRY Study was approved by the Peking University Institutional Review Board (IRB00001052-16011) in April 2016. Results of the study will be disseminated through published journal articles, conferences and seminar presentations, and on the study website (http://www.cherry-study.org).