Spatio-temporal Associations Between GOES Aerosol Optical Depth Retrievals and Ground-Level PM2.5

We assess the strength of association between aerosol optical depth (AOD) retrievals from the GOES Aerosol/Smoke Product (GASP) and ground-level fine particulate matter (PM2.5) to assess AOD as a proxy for PM2.5 in the United States. GASP AOD is retrieved from a geostationary platform and therefore provides dense temporal coverage with half-hourly observations every day, in contrast to once per day snapshots from polar-orbiting satellites. However, GASP AOD is based on a less-sophisticated instrument and retrieval algorithm. We find that correlations between GASP AOD and PM2.5 over time at fixed locations are reasonably high, except in the winter and in the western U.S. Correlations over space at fixed times are lower. Simple averaging over time actually reduces correlations over space dramatically, but statistical calibration allows averaging over time that produces strong correlations. These results and the data density of GASP AOD highlight its potential to help improve exposure estimates for epidemiological analyses. On average 40% of days in a month have a GASP AOD retrieval compared to 14% for MODIS and 4% for MISR. Furthermore, GASP AOD has been retrieved since November 1994, providing the possibility of a long-term record that pre-dates the availability of most PM2.5 monitoring data and other satellite instruments

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets

The trans-ancestral genomic architecture of glycemic traits

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 x 10(-8)), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution. A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.Peer reviewe

Comparison of smoking-related DNA methylation between newborns from prenatal exposure and adults from personal smoking.

Aim: Cigarette smoking influences DNA methylation genome wide, in newborns from pregnancy exposure and in adults from personal smoking. Whether a unique methylation signature exists for in utero exposure in newborns is unknown. Materials & methods: We separately meta-analyzed newborn blood DNA methylation (assessed using Illumina450k Beadchip), in relation to sustained maternal smoking during pregnancy (9 cohorts, 5648 newborns, 897 exposed) and adult blood methylation and personal smoking (16 cohorts, 15907 participants, 2433 current smokers). Results & conclusion: Comparing meta-analyses, we identified numerous signatures specific to newborns along with many shared between newborns and adults. Unique smoking-associated genes in newborns were enriched in xenobiotic metabolism pathways. Our findings may provide insights into specific health impacts of prenatal exposure on offspring

Gene by Environment Interaction and Ambient Air Pollution

Epidemiologic studies have clearly shown that air pollution is associated with a range of respiratory effects. Recent research has identified oxidative stress as a major biologic pathway underlying the toxic effect of air pollutants. Genetic susceptibility is likely to play a role in response to air pollution. Genes involved in oxidative stress and inflammatory pathways are logical candidates for the study of the interaction with air pollutants. In this article we use the example of asthma, a genetically complex disease, to address the issue of gene by environment interaction with air pollution. The majority of studies have focused on the genes GSTM1, GSTP1, NQO1, and TNF, but the inconsistency of the results prevents the drawing of firm conclusions. The limited sample size of most studies to date make them underpowered for the study of gene by gene interactions. Large consortia of studies with repeated measurements of environmental exposures and clear phenotypic assessments may help determine special environmental triggers and the window of susceptibility in the development of atopy and asthma. The role of gene by gene interactions and epigenetic mechanisms needs to be considered along with gene by environment interactions

Maternal Characteristics Determine Stunting in Children of Less than Five Years of Age Results from a National Probabilistic Survey

Background Maternal nutrition and some variables are the main determining factors of birthweight and delayed intrauterine growth of children. Objective To explore the association between the mothers’ biological and sociodemographic characteristics, and the anthropometry status in children under five years of age. Design The population consisted of a sub-sample of 1,047 mother-and-child selected pairs from the probabilistic National Nutrition Survey, carried out in Mexico. Mother-and-child pairs included mothers aged 12 to 49 years, with children under five years of age. Data on sociodemographic characteristics, obstetric history, 24-hour recall dietary intake, and the women and children's anthropometry were collected. The association between maternal characteristics and children's anthropometry status was assessed using multiple logistic regression models. Result Nearly 16.7% of the children 2y). The height/age of the children was severely affected by maternal height and birth order. In addition, the interaction between socioeconomic level and maternal schooling had a marginal effect (p = 0.09) in the ≤2y group. On the other hand, whether the family received social services and the interaction between maternal height and a dichotomy urbanism variable were significant (p = 0.05) and (p 2y group. Conclusion Some biological and socioeconomic characteristics among mothers have a negative effect on their children's attained size, especially in the period between 2 and 5 years of age