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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.
The standard approach to the analysis of genome-wide association studies (GWAS) is based on testing each position in the genome individually for statistical significance of its association with the phenotype under investigation. To improve the analysis of GWAS, we propose a combination of machine learning and statistical testing that takes correlation structures within the set of SNPs under investigation in a mathematically well-controlled manner into account. The novel two-step algorithm, COMBI, first trains a support vector machine to determine a subset of candidate SNPs and then performs hypothesis tests for these SNPs together with an adequate threshold correction. Applying COMBI to data from a WTCCC study (2007) and measuring performance as replication by independent GWAS published within the 2008-2015 period, we show that our method outperforms ordinary raw p-value thresholding as well as other state-of-the-art methods. COMBI presents higher power and precision than the examined alternatives while yielding fewer false (i.e. non-replicated) and more true (i.e. replicated) discoveries when its results are validated on later GWAS studies. More than 80% of the discoveries made by COMBI upon WTCCC data have been validated by independent studies. Implementations of the COMBI method are available as a part of the GWASpi toolbox 2.0.
ATP production requires the establishment of an electrochemical proton gradient across the inner mitochondrial membrane. Mitochondrial uncouplers dissipate this proton gradient and disrupt numerous cellular processes, including vesicular trafficking, mainly through energy depletion. Here we show that Endosidin9 (ES9), a novel mitochondrial uncoupler, is a potent inhibitor of clathrin-mediated endocytosis (CME) in different systems and that ES9 induces inhibition of CME not because of its effect on cellular ATP, but rather due to its protonophore activity that leads to cytoplasm acidification. We show that the known tyrosine kinase inhibitor tyrphostinA23, which is routinely used to block CME, displays similar properties, thus questioning its use as a specific inhibitor of cargo recognition by the AP-2 adaptor complex via tyrosine motif-based endocytosis signals. Furthermore, we show that cytoplasm acidification dramatically affects the dynamics and recruitment of clathrin and associated adaptors, and leads to reduction of phosphatidylinositol 4,5-biphosphate from the plasma membrane.
Competing hypotheses suggest that Himalayan topography is sustained and the plate convergence is accommodated either solely along the basal decollement, the Main Himalayan thrust (MHT), or more broadly, across multiple thrust faults. In the past, structural, geomorphic, and geodetic data of the Nepalese Himalaya have been used to constrain the geometry of the MHT and its shallow frontal thrust fault, known as Main Frontal thrust (MFT). The MHT flattens at depth and connects to a hinterland mid-crustal, steeper thrust ramp, located similar to 100 km north of the deformation front. There, the present-day convergence across the Himalaya is mostly accommodated by slip along the MFT. Despite a general agreement that in Nepal most of the shortening is accommodated along the MHT, some researchers have suggested the occurrence of persistent out-of-sequence shortening on interior faults near the Main Central thrust (MCT). Along the northwest Himalaya, in contrast, some of these characteristics of central Nepal are missing, suggesting along-strike variation of wedge deformation and MHT fault geometry. Here we present new field observations and seven zircon (U-Th)/He (ZHe) cooling ages combined with existing low-temperature data sets. In agreement with our previous findings, we suggest that the transect of cooling age patterns across the frontal Dhauladhar Range reveals that the Main Boundary thrust (MBT) is a primary fault, which has uplifted and sustained this spectacular mountain front since at least the late Miocene. Our results suggest that the MBT forms an similar to 40-km-long fault ramp before it soles into the MHT, and motion along it has exhumed rocks from depth of similar to 8-10 km. New three-dimensional thermokinematic modeling (using Pecube finite-element code) reveals that the observed ZHe and apatite fission track cooling ages can only be explained by sustained mean MBT slip rates between similar to 2.6 and 3.5 mm a(-1) since at least 8 Ma, which corresponds to a horizontal shortening rate of similar to 1.7-2.4 mm a(-1). We propose that the MBT is active today, despite a lack of definitive field or seismogenic evidence, and continues to accommodate crustal shorting by out-of-sequence faulting. Assuming that present-day geodetic shorting rates (similar to 14 +/- 2 mm a(-1)) across the northwest Himalaya have been sustained over geologic time scales, this implies that the MBT accommodated similar to 15% of the total Himalayan convergence since its onset. Furthermore, our modeling results imply that the MHT is missing a hinterland mid-crustal ramp further north.
Coastal flood damage and adaptation costs under 21st century sea-level rise are assessed on a global scale taking into account a wide range of uncertainties in continental topography data, population data, protection strategies, socioeconomic development and sea-level rise. Uncertainty in global mean and regional sea level was derived from four different climate models from the Coupled Model Intercomparison Project Phase 5, each combined with three land-ice scenarios based on the published range of contributions from ice sheets and glaciers. Without adaptation, 0.2-4.6% of global population is expected to be flooded annually in 2100 under 25-123 cm of global mean sea-level rise, with expected annual losses of 0.3-9.3% of global gross domestic product. Damages of this magnitude are very unlikely to be tolerated by society and adaptation will be widespread. The global costs of protecting the coast with dikes are significant with annual investment and maintenance costs of US$ 12-71 billion in 2100, but much smaller than the global cost of avoided damages even without accounting for indirect costs of damage to regional production supply. Flood damages by the end of this century are much more sensitive to the applied protection strategy than to variations in climate and socioeconomic scenarios as well as in physical data sources (topography and climate model). Our results emphasize the central role of long-term coastal adaptation strategies. These should also take into account that protecting large parts of the developed coast increases the risk of catastrophic consequences in the case of defense failure.