ObjectiveWe systematically reviewed epidemiologic studies on ambient air pollution and congenital anomalies and conducted meta-analyses for a number of air pollutant–anomaly combinations.Data sources and extractionFrom bibliographic searches we extracted 10 original epidemiologic studies that examined the association between congenital anomaly risk and concentrations of air pollutants. Meta-analyses were conducted if at least four studies published risk estimates for the same pollutant and anomaly group. Summary risk estimates were calculated for a) risk at high versus low exposure level in each study and b) risk per unit increase in continuous pollutant concentration.Data synthesisEach individual study reported statistically significantly increased risks for some combinations of air pollutants and congenital anomalies, among many combinations tested. In meta-analyses, nitrogen dioxide (NO2) and sulfur dioxide (SO2) exposures were related to increases in risk of coarctation of the aorta [odds ratio (OR) per 10 ppb NO2 = 1.17; 95% confidence interval (CI), 1.00–1.36; OR per 1 ppb SO2 = 1.07; 95% CI, 1.01–1.13] and tetralogy of Fallot (OR per 10 ppb NO2 = 1.20; 95% CI, 1.02–1.42; OR per 1 ppb SO2 = 1.03; 95% CI, 1.01–1.05), and PM10 (particulate matter ≤ 10 μm) exposure was related to an increased risk of atrial septal defects (OR per 10 μg/m3 = 1.14; 95% CI, 1.01–1.28). Meta-analyses found no statistically significant increase in risk of other cardiac anomalies and oral clefts.ConclusionsWe found some evidence for an effect of ambient air pollutants on congenital cardiac anomaly risk. Improvements in the areas of exposure assessment, outcome harmonization, assessment of other congenital anomalies, and mechanistic knowledge are needed to advance this field.
Genetic discoveries of Alzheimer’s disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer’s disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer’s disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer’s disease.
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