Accountability analysis of health benefits related to National Action Plan on Air Pollution Prevention and Control in China.

China is one of the largest producers and consumers of coal in the world. The National Action Plan on Air Pollution Prevention and Control in China (2013-2017) particularly aimed to reduce emissions from coal combustion. Here, we show whether the acute health effects of PM2.5 changed from 2013 to 2018 and factors that might account for any observed changes in the Beijing-Tianjin-Hebei (BTH) and the surrounding areas where there were major reductions in PM2.5 concentrations. We used a two-stage analysis strategy, with a quasi-Poisson regression model and a random effects meta-analysis, to assess the effects of PM2.5 on mortality in the 47 counties of BTH. We found that the mean daily PM2.5 levels and the SO42- component ratio dramatically decreased in the study period, which was likely related to the control of coal emissions. Subsequently, the acute effects of PM2.5 were significantly decreased for total and circulatory mortality. A 10 µg/m3 increase in PM2.5 concentrations was associated with a 0.16% (95% CI: 0.08, 0.24%) and 0.02% (95% CI: -0.09, 0.13%) increase in mortality from 2013 to 2015 and from 2016 to 2018, respectively. The changes in air pollution sources or PM2.5 components appeared to have played a core role in reducing the health effects. The air pollution control measures implemented recently targeting coal emissions taken in China may have resulted in significant health benefits.

Cancer risks among first-degree relatives of women with a genetic predisposition to breast cancer.

BACKGROUND: Associations between germline alterations in women and cancer risks among their relatives are largely unknown. METHODS: We used women from two Swedish cohorts (KARMA and pKARMA), including 28,362 women with genotyping data and 13,226 with sequencing data. Using Swedish Multi-Generation Register, we linked these women to 133,389 first-degree relatives. Associations between protein-truncating variants (PTVs) in 8 risk genes and breast cancer polygenic risk score (PRS) in index women and cancer risks among their relatives were modeled via Cox regression. RESULTS: Female relatives of index women who were PTV carriers in any of the 8 risk genes had an increased breast cancer risk compared to those of non-carriers (HR1.85, 95% CI: 1.52-2.27), with the strongest association found for PTVs in BRCA1/2. These relatives had a statistically higher risk of early-onset than late-onset breast cancer (P = .001). Elevated breast cancer risk was also observed in female relatives of index women with higher PRS (HR per SD: 1.28, 95% CI: 1.23-1.32). The estimated lifetime risk was 22.3% for female relatives of PTV carriers and 14.4% for those related to women in the top PRS quartile. Moreover, relatives of index women with PTV presence (HR: 1.30, 95% CI: 1.06-1.59) or higher PRS (HR per SD: 1.04, 95% CI: 1.01-1.07) were also at higher risk of non-breast-HBOC cancers, including prostate, ovarian, pancreatic cancer, and melanoma. CONCLUSIONS: Both PTVs of risk genes and higher PRS in index women are associated with an increased risk of breast and other HBOC-related cancers among relatives.

Investigation of Genetic Alterations Associated With Interval Breast Cancer.

Importance: Breast cancers (BCs) diagnosed between 2 screening examinations are called interval cancers (ICs), and they have worse clinicopathological characteristics and poorer prognosis than screen-detected cancers (SDCs). However, the association of rare germline genetic variants with IC have not been studied. Objective: To evaluate whether rare germline deleterious protein-truncating variants (PTVs) can be applied to discriminate between IC and SDC while considering mammographic density. Design, Setting, and Participants: This population-based genetic association study was based on women aged 40 to 76 years who were attending mammographic screening in Sweden. All women with a diagnosis of BC between January 2001 and January 2016 were included, together with age-matched controls. Patients with BC were followed up for survival until 2021. Statistical analysis was performed from September 2021 to December 2022. Exposure: Germline PTVs in 34 BC susceptibility genes as analyzed by targeted sequencing. Main Outcomes and Measures: Odds ratios (ORs) were used to compare IC with SDC using logistic regression. Hazard ratios were used to investigate BC-specific survival using Cox regression. Results: All 4121 patients with BC (IC, n = 1229; SDC, n = 2892) were female, with a mean (SD) age of 55.5 (7.1) years. There were 5631 age-matched controls. The PTVs of the ATM, BRCA1, BRCA2, CHEK2, and PALB2 genes were more common in patients with IC compared with SDC (OR, 1.48; 95% CI, 1.06-2.05). This association was primarily influenced by BRCA1/2 and PALB2 variants. A family history of BC together with PTVs of any of these genes synergistically increased the probability of receiving a diagnosis of IC rather than SDC (OR, 3.95; 95% CI, 1.97-7.92). Furthermore, 10-year BC-specific survival revealed that if a patient received a diagnosis of an IC, carriers of PTVs in any of these 5 genes had significantly worse survival compared with patients not carrying any of them (hazard ratio, 2.04; 95% CI, 1.06-3.92). All of these associations were further pronounced in a subset of patients with IC who had a low mammographic density at prior screening examination. Conclusions and Relevance: The results of this study may be helpful in future optimizations of screening programs that aim to lower mortality as well as the clinical treatment of patients with BC.

Long-term exposure to the components of fine particulate matters and disability after stroke: Findings from the China National Stroke Screening Surveys.

BACKGROUND: Long-term exposure to ambient fine particulate matter (PM2.5) has been linked to an increased risk of stroke. However, the effect of long-term exposure to PM2.5 and its major components on the functional disability of stroke patients remains unclear. METHODS: Based on China National Stroke Screening Survey data obtained from 2013 to 2019, we conducted a national multicenter longitudinal study of the associations of long-term exposure to PM2.5 and its components with the risk of disability after stroke in China. Post-stroke disability was assessed using the modified Rankin scale (mRS), which ranges from 0 to 5, with higher scores indicating greater disability. Long-term exposure to PM2.5 and its five components [sulfate (SO42-), nitrate (NO3-), ammonium salt (NH4+), organic matter (OM), and black carbon (BC)] was determined based on average concentrations during the 3 years preceding mRS administration according to the geographic coordinates of residential communities, using state-of-the-art estimates from multiple sources. We used a fixed-effect model to evaluate the associations between mRS scores and PM2.5 exposure, with adjustment for multiple covariates. RESULTS: Every 10 µg/m3 increase in PM2.5 was associated with a 0.019 (95% confidence interval, 0.003, 0.036) increase in mRS score, but the effect was not significant after adjusting for all covariates [0.016 (95% CI, -0.003, 0.032)]. For PM2.5 components, each IQR (7.92 µg/m3) increment in OM exposure was associated significantly with 0.062 (95% CI, 0.013, 0.111) increment in the mRS score. A significant association was observed between SO42- exposure and the mRS score [0.057 (95% CI, 0.003, 0.112), per IQR: 6.28 µg/m3]. However, no significant association was found with BC, NO3-, or NH4+ exposure. Furthermore, the nonlinear curves were observed for the exposure-response relationship between PM2.5 exposure and the mRS score. CONCLUSION: Greater PM2.5 exposure increased the mRS score and was associated with post-stroke functional disability among stroke patients. However, different chemical components showed unequal neurotoxic effects, and long-term exposure to OM and SO42- may play a more important role. SYNOPSIS: This study reports fine particulate matter at higher concentrations damages the functional ability among specific stroke patients, and PM2.5 components have different neurotoxicities.

Drivers of Increasing Ozone during the Two Phases of Clean Air Actions in China 2013-2020.

In response to the severe air pollution issue, the Chinese government implemented two phases (Phase I, 2013-2017; Phase II, 2018-2020) of clean air actions since 2013, resulting in a significant decline in fine particles (PM2.5) during 2013-2020, while the warm-season (April-September) mean maximum daily 8 h average ozone (MDA8 O3) increased by 2.6 µg m-3 yr-1 in China during the same period. Here, we derived the drivers behind the rising O3 concentrations during the two phases of clean air actions by using a bottom-up emission inventory, a regional chemical transport model, and a multiple linear regression model. We found that both meteorological variations (3.6 µg m-3) and anthropogenic emissions (6.7 µg m-3) contributed to the growth of MDA8 O3 from 2013 to 2020, with the changes in anthropogenic emissions playing a more important role. The anthropogenic contributions to the O3 rise during 2017-2020 (1.2 µg m-3) were much lower than that in 2013-2017 (5.2 µg m-3). The lack of volatile organic compound (VOC) control and the decline in nitrogen oxides (NOx) emissions were responsible for the O3 increase in 2013-2017 due to VOC-limited regimes in most urban areas, while the synergistic control of VOC and NOx in Phase II initially worked to mitigate O3 pollution during 2018-2020, although its effectiveness was offset by the penalty of PM2.5 decline. Future mitigation efforts should pay more attention to the simultaneous control of VOC and NOx to improve O3 air quality.

The PM2.5 concentration reduction improves survival rate of lung cancer in Beijing.

INTRODUCTION: Long-term exposure to ambient fine particulate matter (PM2.5) has been linked to increases in the incidence of lung cancer. However, more evidence is needed to conclude its effects on lung cancer survival. OBJECTIVES: The study aimed to explore the relationship between long-term PM2.5 exposure and lung cancer survival and evaluated the benefits of clean air actions in Beijing. METHODS: A whole-population cohort study was conducted on lung cancer patients diagnosed between 2001 and 2017. An atmospheric chemical transport model was used to estimate exposure under a counterfactual scenario without the policy and then quantified the effect of the policy. Cox regression models were used with the seasonality-adjusted PM2.5 as the main effect. RESULTS: A 10 µg/m3 increase in PM2.5 was estimated to be with a 6.5 % (95 % CI: 4.8 %, 8.2 %) increase in the mortality rates. The association was heterogeneous and modified by individual-level characteristics. The clean air actions were estimated to have prevented 3548 (95 % CI: 3280, 3825) premature deaths and to have prolonged survival time by 4.29 months (95 % CI: 0.01, 25.11). CONCLUSION: Our findings suggest that PM2.5 exposure lowers the survival rate for lung cancer. The clean air actions implemented in Beijing can protect lung cancer patients by increasing their survival time. SYNOPSIS: Long-term exposure to PM2.5 can lower lung patients' survival rates whereas the clean air actions in Beijing have prolonged these patients' survival time by reducing PM2.5 level.

Tracking Daily Concentrations of PM2.5 Chemical Composition in China since 2000.

PM2.5 chemical components play significant roles in the climate, air quality, and public health, and the roles vary due to their different physicochemical properties. Obtaining accurate and timely updated information on China's PM2.5 chemical composition is the basis for research and environmental management. Here, we developed a full-coverage near-real-time PM2.5 chemical composition data set at 10 km spatial resolution since 2000, combining the Weather Research and Forecasting-Community Multiscale Air Quality modeling system, ground observations, a machine learning algorithm, and multisource-fusion PM2.5 data. PM2.5 chemical components in our data set are in good agreement with the available observations (correlation coefficients range from 0.64 to 0.75 at a monthly scale from 2000 to 2020 and from 0.67 to 0.80 at a daily scale from 2013 to 2020; most normalized mean biases within ±20%). Our data set reveals the long-term trends in PM2.5 chemical composition in China, especially the rapid decreases after 2013 for sulfate, nitrate, ammonium, organic matter, and black carbon, at the rate of -9.0, -7.2, -8.1, -8.4, and -9.2% per year, respectively. The day-to-day variability is also well captured, including evolutions in spatial distribution and shares of PM2.5 components. As part of Tracking Air Pollution in China (http://tapdata.org.cn), this daily-updated data set provides large opportunities for health and climate research as well as policy-making in China.

Long-Term Exposure to Ozone Increases Neurological Disability after Stroke: Findings from a Nationwide Longitudinal Study in China.

Exposure to ozone (O3) is associated with stroke incidence and mortality. However, whether long-term exposure to O3 is associated with post-stroke neurological disability remains unknown. This study investigated the relationship based on the longitudinal analysis of China National Stroke Screening Survey (CNSSS), which included 65,778 records of stroke patients. All of the analyzed patients were followed-up at least twice. Stroke disability was assessed using the modified Rankin scale (mRS). Long-term exposure was assessed by the peak-season or annual mean of maximum 8-h O3 concentrations for 365 days before the mRS measurement. We used fixed-effect models to evaluate the associations between O3 and mRS score, with adjustment for multiple confounders, and found a 10 µg/m3 increase in peak-season O3 concentration was associated with a 0.0186 (95% confidence interval [CI] 0.0115-0.0256) increment in the mRS score. The association was robust in various subpopulations. For secondary outcomes, for each 10 µg/m3 increment in peak-season O3, the odds ratio of an increased mRS score (vs. unchanged or decreased mRS score) increased by 23% (95% CI 9-37%). A nonlinear analysis showed a sublinear association between O3 exposure and risk for post-stroke disability. A saturation effect was observed at an O3 concentration of more than ~120 µg/m3. Our study adds to evidence that long-term exposure to O3 increases the risk of neurological disability after stroke.

High IGKC-Expressing Intratumoral Plasma Cells Predict Response to Immune Checkpoint Blockade.

Resistance to Immune Checkpoint Blockade (ICB) constitutes the current limiting factor for the optimal implementation of this novel therapy, which otherwise demonstrates durable responses with acceptable toxicity scores. This limitation is exacerbated by a lack of robust biomarkers. In this study, we have dissected the basal TME composition at the gene expression and cellular levels that predict response to Nivolumab and prognosis. BCR, TCR and HLA profiling were employed for further characterization of the molecular variables associated with response. The findings were validated using a single-cell RNA-seq data of metastatic melanoma patients treated with ICB, and by multispectral immunofluorescence. Finally, machine learning was employed to construct a prediction algorithm that was validated across eight metastatic melanoma cohorts treated with ICB. Using this strategy, we have unmasked a major role played by basal intratumoral Plasma cells expressing high levels of IGKC in efficacy. IGKC, differentially expressed in good responders, was also identified within the Top response-related BCR clonotypes, together with IGK variants. These results were validated at gene, cellular and protein levels; CD138+ Plasma-like and Plasma cells were more abundant in good responders and correlated with the same RNA-seq-defined fraction. Finally, we generated a 15-gene prediction model that outperformed the current reference score in eight ICB-treated metastatic melanoma cohorts. The evidenced major contribution of basal intratumoral IGKC and Plasma cells in good response and outcome in ICB in metastatic melanoma is a groundbreaking finding in the field beyond the role of T lymphocytes.

CFTR reduces the proliferation of lung adenocarcinoma and is a strong predictor of survival in both smokers and non-smokers.

BACKGROUND: One of the main hurdles of oncological therapy is the development of drug resistance. The ABC transporter gene family contributes majorly to cancer chemoresistance. However, effects of somatic expression of most ABC transporters on cancer outcomes remain largely unclear. METHODS: We systematically analyzed expression signatures of all 48 human ABC transporters in samples from 8562 patients across 14 different cancer types. The association between CFTR (ABCC7) expression and outcomes was analyzed experimentally using knock-downs and pharmacological CFTR stimulation. RESULTS: Across 720 analyzed clinical associations with patient outcomes, 363 were nominally significant of which 29 remained significant after stringent Bonferroni correction. Among those were various previously known associations, as well as a multitude of novel factors that correlated with poor prognosis or predicted improved outcomes. The association between low CFTR levels and reduced survival in lung adenocarcinoma was confirmed in two independent cohorts of 246 patients with a history of smoking (logrank P = 0.0021, hazard ratio [HR], 0.49) and 143 never-smokers (logrank P = 0.0023, HR 0.31). Further in vitro experiments using naturally CFTR expressing lung adenocarcinoma cells showed that treatment with CFTR potentiators significantly reduced proliferation at therapeutically relevant concentrations. CONCLUSIONS: These results suggest that CFTR acts as a pharmacologically activatable tumor suppressor and constitutes a promising target for adjuvant therapy in lung adenocarcinoma.

New WHO global air quality guidelines help prevent premature deaths in China.

The World Health Organization has issued new air quality guidelines (AQG). Based on 2020 data, achieving the new AQG for PM2.5 could prevent an additional 285,000 chronic deaths and 13,000 acute deaths, across China, compared with the previous AQG. The new AQG can better protect health but cannot be achieved without coordinated air-pollution-control and climate-mitigation efforts.

Evaluating the spatiotemporal ozone characteristics with high-resolution predictions in mainland China, 2013-2019.

Evaluating ozone levels at high resolutions and accuracy is crucial for understanding the spatiotemporal characteristics of ozone distribution and assessing ozone exposure levels in epidemiological studies. The national models with high spatiotemporal resolutions to predict ground ozone concentrations are limited in China so far. In this study, we aimed to develop a random forest model by combining ground ozone measurements from fixed stations, ozone simulations from the Community Multiscale Air Quality (CMAQ) modeling system, meteorological parameters, population density, road length, and elevation to predict ground maximum daily 8-h average (MDA8) ozone concentrations at a daily level and 1 km × 1 km spatial resolution. The model cross-validation R2 and root mean squared error (RMSE) were 0.80 and 20.93 µg/m3 at daily level in 2013-2019, respectively. CMAQ ozone simulations and near-surface temperature played vital roles in predicting ozone concentrations among all predictors. The population-weighted median concentrations of predicted MDA8 ozone were 89.34 µg/m3 in mainland China in 2013, and reached 100.96 µg/m3 in 2019. However, the long-term temporal variations among regions were heterogeneous. Central and Eastern China, as well as the Southeast Coastal Area, suffered higher ozone pollution and higher increased rates of ozone concentrations from 2013 to 2019. The seasonal pattern of ozone pollution varied spatially. The peak-season ozone pollution with the highest 6-month ozone concentrations occurred in different months among regions, with more than half domain in April-September. The predictions showed that not only the annual mean concentrations but also the percentages of grid-days with MDA8 ozone concentrations higher than 100/160 µg/m3 have been increasing in the past few years in China; meanwhile, majority areas in mainland China suffered peak-season ozone concentrations higher than the air quality guidelines launched by the World Health Organization in September 2021. The proposed model and ozone predictions with high spatiotemporal resolution and full coverage could provide health studies with flexible choices to evaluate ozone exposure levels at multiple spatiotemporal scales in the future.

Simultaneous removal of NOX and SO2 from flue gas in an integrated FGD-CABR system by sulfur cycling-mediated Fe(II)EDTA regeneration.

Chemical absorption-biological reduction (CABR) process is an attractive method for NOX removal and Fe(II)EDTA regeneration is important to sustain high NOX removal. In this study a sustainable and eco-friendly sulfur cycling-mediated Fe(II)EDTA regeneration method was incorporated in the integrated biological flue gas desulfurization (FGD)-CABR system. Here, we investigated the NOX and SO2 removal efficiency of the system under three different flue gas flows (100 mL/min, 500 mL/min, and 1000 mL/min) and evaluated the feasibility of chemical Fe(III)EDTA reduction by sulfide in series of batch tests. Our results showed that complete SO2 removal was achieved at all the tested scenarios with sulfide, thiosulfate and S0 accumulation in the solution. Meanwhile, the total removal efficiency of NOX achieved ∼100% in the system, of which 3.2%-23.3% was removed in spray scrubber and 76.7%-96.5% in EGSB reactor along with no N2O emission. The optimal pH and S2-/Fe(III)EDTA for Fe(II)EDTA regeneration and S0 recovery was 8.0 and 1:2. The microbial community analysis results showed that the cooperation of heterotrophic denitrifier (Saprospiraceae_uncultured and Dechloromonas) and iron-reducing bacteria (Klebsiella and Petrimonas) in EGSB reactor and sulfide-oxidizing, nitrate-reducing bacteria (Azoarcus and Pseudarcobacter) in spray scrubber contributed to the efficient removal of NOX in flue gas.

Tracking PM2.5 and O3 Pollution and the Related Health Burden in China 2013-2020.

Based on the exposure data sets from the Tracking Air Pollution in China (TAP, http://tapdata.org.cn/), we characterized the spatiotemporal variations in PM2.5 and O3 exposures and quantified the long- and short-term exposure related premature deaths during 2013-2020 with respect to the two-stage clean air actions (2013-2017 and 2018-2020). We find a 48% decrease in national PM2.5 exposure during 2013-2020, although the decrease rate has slowed after 2017. At the same time, O3 pollution worsened, with the average April-September O3 exposure increased by 17%. The improved air quality led to 308 thousand and 16 thousand avoided long- and short-term exposure related deaths, respectively, in 2020 compared to the 2013 level, which was majorly attributed to the reduction in ambient PM2.5 concentration. It is also noticed that with smaller PM2.5 reduction, the avoided long-term exposure associated deaths in 2017-2020 (13%) was greater than that in 2013-2017 (9%), because the exposure-response curve is nonlinear. As a result of the efforts in reducing PM2.5-polluted days with the daily average PM2.5 higher than 75 µg/m3 and the considerable increase in O3-polluted days with the daily maximum 8 h average O3 higher than 160 µg/m3, deaths attributable to the short-term O3 exposure were greater than those due to PM2.5 exposure since 2018. Future air quality improvement strategies for the coordinated control of PM2.5 and O3 are urgently needed.

Tracking Air Pollution in China: Near Real-Time PM2.5 Retrievals from Multisource Data Fusion.

Air pollution has altered the Earth's radiation balance, disturbed the ecosystem, and increased human morbidity and mortality. Accordingly, a full-coverage high-resolution air pollutant data set with timely updates and historical long-term records is essential to support both research and environmental management. Here, for the first time, we develop a near real-time air pollutant database known as Tracking Air Pollution in China (TAP, http://tapdata.org.cn/) that combines information from multiple data sources, including ground observations, satellite aerosol optical depth (AOD), operational chemical transport model simulations, and other ancillary data such as meteorological fields, land use data, population, and elevation. Daily full-coverage PM2.5 data at a spatial resolution of 10 km is our first near real-time product. The TAP PM2.5 is estimated based on a two-stage machine learning model coupled with the synthetic minority oversampling technique and a tree-based gap-filling method. Our model has an averaged out-of-bag cross-validation R2 of 0.83 for different years, which is comparable to those of other studies, but improves its performance at high pollution levels and fills the gaps in missing AOD on daily scale. The full coverage and near real-time updates of the daily PM2.5 data allow us to track the day-to-day variations in PM2.5 concentrations over China in a timely manner. The long-term records of PM2.5 data since 2000 will also support policy assessments and health impact studies. The TAP PM2.5 data are publicly available through our website for sharing with the research and policy communities.

Benefits of active commuting on cardiovascular health modified by ambient fine particulate matter in China: A prospective cohort study.

BACKGROUND: Active commuting as a contributor to daily physical activity is beneficial for cardiovascular health, but leads to more chances of exposure to ambient air pollution. This study aimed to investigate associations between active commuting to work with cardiovascular disease (CVD), mortality and life expectancy among general Chinese adults, and to further evaluate the modification effect of fine particulate matter (PM2.5) exposure on these associations. METHODS: We included 76,176 Chinese adults without CVD from three large cohorts of the Prediction for Atherosclerotic Cardiovascular Disease Risk in China project. Information about commuting mode and physical activity were collected by unified questionnaire. Satellite-based PM2.5 concentrations at 1-km spatial resolution was used for estimating PM2.5 exposure of participants. Hazard ratios (HRs) and 95% confidence intervals (CIs) for CVD incidence, mortality and all-cause mortality were estimated using Cox proportional hazards regression models. Multiplicative interaction term of commuting mode and PM2.5 level was tested to investigate potential effect modification. RESULTS: During 448,499 person-years of follow-up, 2230 CVD events and 2777 all-cause deaths were recorded. Compared with the non-active commuters, the multivariable-adjusted HRs (95% CIs) of CVD incidence and all-cause mortality were 0.95(0.85-1.05) and 0.79(0.72-0.87) for walking commuters, respectively. Corresponding HRs (95% CIs) for cycling commuters were 0.71(0.62-0.82) and 0.67(0.59-0.76). Active commuters over 45 years old were estimated to have more CVD-free years and life expectancy than non-active commuters under lower PM2.5 concentration. However, these beneficial effects of active commuting were alleviated or counteracted by long-term exposure to high PM2.5 concentration. Significant multiplicative interaction of commuting mode and PM2.5 level was showed in all-cause mortality, with the lowest risk observed in cycling participants exposed to lower level of PM2.5. CONCLUSIONS: Active commuting was associated with lower risk of CVD, all-cause mortality, and longer life expectancy among Chinese adults under ambient settings with lower PM2.5 level. It will be valuable to encourage active commuting among adults and develop stringent strategies on ambient PM2.5 pollution control for prevention of CVD and prolongation of life expectancy.

The prevalence, genetic complexity and population-specific founder effects of human autosomal recessive disorders.

Autosomal recessive (AR) disorders pose a significant burden for public health. However, despite their clinical importance, epidemiology and molecular genetics of many AR diseases remain poorly characterized. Here, we analyzed the genetic variability of 508 genes associated with AR disorders based on sequencing data from 141,456 individuals across seven ethnogeographic groups by integrating variants with documented pathogenicity from ClinVar, with stringent functionality predictions for variants with unknown pathogenicity. We first validated our model using 85 diseases for which population-specific prevalence data were available and found that our estimates strongly correlated with the respective clinically observed disease frequencies (r = 0.68; p < 0.0001). We found striking differences in population-specific disease prevalence with 101 AR diseases (27%) being limited to specific populations, while an additional 305 diseases (68%) differed more than tenfold across major ethnogeographic groups. Furthermore, by analyzing genetic AR disease complexity, we confirm founder effects for cystic fibrosis and Stargardt disease, and provide strong evidences for >25 additional population-specific founder mutations. The presented analyses reveal the molecular genetics of AR diseases with unprecedented resolution and provide insights into epidemiology, complexity, and population-specific founder effects. These data can serve as a powerful resource for clinical geneticists to inform population-adjusted genetic screening programs, particularly in otherwise understudied ethnogeographic groups.

The long-term trend of PM2.5-related mortality in China: The effects of source data selection.

Quantification of PM2.5 exposure and associated mortality is critical to inform policy making. Previous studies estimated varying PM2.5-related mortality in China due to the usage of different source data, but rarely justify the data selection. To quantify the sensitivity of mortality assessment to source data, we first constructed state-of-the-art PM2.5 predictions during 2000-2018 at a 1-km resolution with an ensemble machine learning model that filled missing data explicitly. We also calibrated and fused various gridded population data with a geostatistical method. Then we assessed the PM2.5-related mortality with various PM2.5 predictions, population distributions, exposure-response functions, and baseline mortalities. We found that in addition to the well documented uncertainties in the exposure-response functions, missingness in PM2.5 prediction, PM2.5 prediction error, and prediction error in population distribution resulted to a 40.5%, 25.2% and 15.9% lower mortality assessment compared to the mortality assessed with the best-performed source data, respectively. With the best-performed source data, we estimated a total of approximately 25 million PM2.5-related mortality during 2001-2017 in China. From 2001 to 2017, The PM2.5 variations, growth and aging of population, decrease in baseline mortality led to a 7.8% increase, a 42.0% increase and a 24.6% decrease in PM2.5-related mortality, separately. We showed that with the strict clean air policies implemented in 2013, the population-weighted PM2.5 concentration decreased remarkably at an annual rate of 4.5 µg/m3, leading to a decrease of 179 thousand PM2.5-related deaths nationwide during 2013-2017. The mortality decrease due to PM2.5 reduction was offset by the population growth and aging population.

Impact of variants in ATP-binding cassette transporters on breast cancer treatment.

There has been substantial interest in the impact of ATP-binding cassette (ABC) transporter variability on breast cancer drug resistance. Here, we provide a systematic review of ABC variants in breast cancer therapy. Notably, most studies used small heterogeneous cohorts and their identified associations lack statistical stringency, replication and mechanistic support. We conclude that commonly studied ABC polymorphisms are not suitable to accurately predict therapy response or toxicity in breast cancer patients and cannot guide treatment decisions. However, recent research shows that ABC transporters harbor a plethora of rare variants with individually small effect sizes, and we argue that a shift in strategy from target variant interrogation to comprehensive profiling might hold promise to drastically improve the predictive power of outcome models.

Estimating Spatiotemporal Variation in Ambient Ozone Exposure during 2013-2017 Using a Data-Fusion Model.

Since 2013, clean-air actions in China have reduced ambient concentrations of PM2.5. However, recent studies suggest that ground surface O3 concentrations increased over the same period. To understand the shift in air pollutants and to comprehensively evaluate their impacts on health, a spatiotemporal model for O3 is required for exposure assessment. This study presents a data-fusion algorithm for O3 estimation that combines in situ observations, satellite remote sensing measurements, and model results from the community multiscale air quality model. Performance of the algorithm for O3 estimation was evaluated by five-fold cross-validation. The estimates are highly correlated with the in situ observations of the maximum daily 8 h averaged O3 (R2 = 0.70). The mean modeling error (measured using the root-mean-squared error) is 26 µg/m3, which accounts for 29% of the mean level. We also found that satellite O3 played a key role to improve model performance, particularly during warm months. The estimates were further used to illustrate spatiotemporal variation in O3 during 2013-2017 for the whole country. In contrast to the reduced trend of PM2.5, we found that the population-weighted O3 mean increased from 86 µg/m3 in 2013 to 95 µg/m3 in 2017, with a rate of 2.07 (95% CI: 1.65, 2.48) µg/m3 per year at the national level. This increased trend in O3 suggests that it is becoming an important contributor to the burden of diseases attributable to air pollutants in China. The developed method and the results generated from this study can be used to support future health-related studies in China.