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Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.
The Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia
(2019)
The impact of many unfavorable childhood traits or diseases, such as low birth weight and mental disorders, is not limited to childhood and adolescence, as they are also associated with poor outcomes in adulthood, such as cardiovascular disease. Insight into the genetic etiology of childhood and adolescent traits and disorders may therefore provide new perspectives, not only on how to improve wellbeing during childhood, but also how to prevent later adverse outcomes. To achieve the sample sizes required for genetic research, the Early Growth Genetics (EGG) and EArly Genetics and Lifecourse Epidemiology (EAGLE) consortia were established. The majority of the participating cohorts are longitudinal population-based samples, but other cohorts with data on early childhood phenotypes are also involved. Cohorts often have a broad focus and collect(ed) data on various somatic and psychiatric traits as well as environmental factors. Genetic variants have been successfully identified for multiple traits, for example, birth weight, atopic dermatitis, childhood BMI, allergic sensitization, and pubertal growth. Furthermore, the results have shown that genetic factors also partly underlie the association with adult traits. As sample sizes are still increasing, it is expected that future analyses will identify additional variants. This, in combination with the development of innovative statistical methods, will provide detailed insight on the mechanisms underlying the transition from childhood to adult disorders. Both consortia welcome new collaborations. Policies and contact details are available from the corresponding authors of this manuscript and/or the consortium websites.
Metabolic footprint and intestinal microbial changes in response to dietary proteins in a pig model
(2019)
Epidemiological studies revealed that dietary proteins can contribute to the modulation of the cardiovascular disease risk. Still, direct effects of dietary proteins on serum metabolites and other health-modulating factors have not been fully explored. Here, we compared the effects of dietary lupin protein with the effects of beef protein and casein on the serum metabolite profile, cardiovascular risk markers and the fecal microbiome. Pigs were fed diets containing 15% of the respective proteins for 4 weeks. A classification analysis of the serum metabolites revealed six biomarker sets of two metabolites each that discriminated between the intake of lupin protein, lean beef or casein. These biomarker sets included 1- and 3-methylhistidine, betaine, carnitine, homoarginine and methionine. The study revealed differences in the serum levels of the metabolites 1- and 3- methylhistidine, homoarginine, methionine and homocysteine, which are involved in the one-carbon cycle. However, these changes were not associated with differences in the methylation capacity or the histone methylation pattern. With the exception of serum homocysteine and homoarginine levels, other cardiovascular risk markers, such as the homeostatic model assessment index, trimethylamine-N-oxide and lipids, were not influenced by the dietary protein source. However, the composition of the fecal microorganisms was markedly changed by the dietary protein source. Lupin-protein-fed pigs exhibited more species from the phyla Bacteroidetes and Firmicutes than the other two groups. In conclusion, different dietary protein sources induce distinct serum metabolic fingerprints, have an impact on the cardiovascular risk and modulate the composition of the fecal microbiome. (C) 2019 Elsevier Inc. All rights reserved.
River ecosystems receive and process vast quantities of terrestrial organic carbon, the fate of which depends strongly on microbial activity. Variation in and controls of processing rates, however, are poorly characterized at the global scale. In response, we used a peer-sourced research network and a highly standardized carbon processing assay to conduct a global-scale field experiment in greater than 1000 river and riparian sites. We found that Earth’s biomes have distinct carbon processing signatures. Slow processing is evident across latitudes, whereas rapid rates are restricted to lower latitudes. Both the mean rate and variability decline with latitude, suggesting temperature constraints toward the poles and greater roles for other environmental drivers (e.g., nutrient loading) toward the equator. These results and data set the stage for unprecedented “next-generation biomonitoring” by establishing baselines to help quantify environmental impacts to the functioning of ecosystems at a global scale.
An understanding of the factors limiting the open-circuit voltage (V-oc) and related photon energy loss mechanisms is critical to increase the power conversion efficiency (PCE) of small-molecule organic solar cells (OSCs), especially those with near-infrared (NIR) absorbers. In this work, two NIR boron dipyrromethene (BODIPY) molecules are characterized for application in planar (PHJ) and bulk (BHJ) heterojunction OSCs. When two H atoms are substituted by F atoms on the peripheral phenyl rings of the molecules, the molecular aggregation type in the thin film changes from the H-type to J-type. For PHJ devices, the nonradiative voltage loss of 0.35 V in the J-aggregated BODIPY is lower than that of 0.49 V in the H-aggregated device. In BHJ devices with a nonradiative voltage loss of 0.35 V, a PCE of 5.5% is achieved with an external quantum efficiency (EQE) maximum of 68% at 700 nm.