Birth outcomes in relation to neighborhood food access and individual food insecurity during pregnancy in the Environmental Influences on Child Health Outcomes (ECHO)-wide cohort study

BackgroundLimited access to healthy foods, resulting from residence in neighborhoods with low-food access or from household food insecurity, is a public health concern. Contributions of these measures during pregnancy to birth outcomes remain understudied.ObjectivesWe examined associations between neighborhood food access and individual food insecurity during pregnancy with birth outcomes.MethodsWe used data from 53 cohorts participating in the nationwide Environmental Influences on Child Health Outcomes-Wide Cohort Study. Participant inclusion required a geocoded residential address or response to a food insecurity question during pregnancy and information on birth outcomes. Exposures include low-income-low-food-access (LILA, where the nearest supermarket is >0.5 miles for urban or >10 miles for rural areas) or low-income-low-vehicle-access (LILV, where few households have a vehicle and >0.5 miles from the nearest supermarket) neighborhoods and individual food insecurity. Mixed-effects models estimated associations with birth outcomes, adjusting for socioeconomic and pregnancy characteristics.ResultsAmong 22,206 pregnant participants (mean age 30.4 y) with neighborhood food access data, 24.1% resided in LILA neighborhoods and 13.6% in LILV neighborhoods. Of 1630 pregnant participants with individual-level food insecurity data (mean age 29.7 y), 8.0% experienced food insecurity. Residence in LILA (compared with non-LILA) neighborhoods was associated with lower birth weight [β -44.3 g; 95% confidence interval (CI): -62.9, -25.6], lower birth weight-for-gestational-age z-score (-0.09 SD units; -0.12, -0.05), higher odds of small-for-gestational-age [odds ratio (OR) 1.15; 95% CI: 1.00, 1.33], and lower odds of large-for-gestational-age (0.85; 95% CI: 0.77, 0.94). Similar findings were observed for residence in LILV neighborhoods. No associations of individual food insecurity with birth outcomes were observed.ConclusionsResidence in LILA or LILV neighborhoods during pregnancy is associated with adverse birth outcomes. These findings highlight the need for future studies examining whether investing in neighborhood resources to improve food access during pregnancy would promote equitable birth outcomes

An integrative approach for building personalized gene regulatory networks for precision medicine

Only a small fraction of patients respond to the drug prescribed to treat their disease, which means that most are at risk of unnecessary exposure to side effects through ineffective drugs. This inter-individual variation in drug response is driven by differences in gene interactions caused by each patient's genetic background, environmental exposures, and the proportions of specific cell types involved in disease. These gene interactions can now be captured by building gene regulatory networks, by taking advantage of RNA velocity (the time derivative of the gene expression state), the ability to study hundreds of thousands of cells simultaneously, and the falling price of single-cell sequencing. Here, we propose an integrative approach that leverages these recent advances in single-cell data with the sensitivity of bulk data to enable the reconstruction of personalized, cell-type- and context-specific gene regulatory networks. We expect this approach will allow the prioritization of key driver genes for specific diseases and will provide knowledge that opens new avenues towards improved personalized healthcare

Monitoring influenza A viruses in wild waterfowl

Monitor antigenic and genomic properties of IAVs active in natural reservoir hosts sampled in the Mississippi and Atlantic Migratory Bird Flyway

Genetic effects on gene expression across human tissues.

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease