Background: Macronutrient intake varies substantially between individuals, and there is evidence that this variation is partly accounted for by genetic variants.Objective: The objective of the study was to identify common genetic variants that are associated with macronutrient intake.Design: We performed 2-stage genome-wide association (GWA) meta-analysis of macronutrient intake in populations of European descent. Macronutrients were assessed by using food-frequency questionnaires and analyzed as percentages of total energy consumption from total fat, protein, and carbohydrate. From the discovery GWA (n = 38,360), 35 independent loci associated with macronutrient intake at P < 5 × 10−6 were identified and taken forward to replication in 3 additional cohorts (n = 33,533) from the DietGen Consortium. For one locus, fat mass obesity-associated protein (FTO), cohorts with Illumina MetaboChip genotype data (n = 7724) provided additional replication data.Results: A variant in the chromosome 19 locus (rs838145) was associated with higher carbohydrate (β ± SE: 0.25 ± 0.04%; P = 1.68 × 10−8) and lower fat (β ± SE: −0.21 ± 0.04%; P = 1.57 × 10−9) consumption. A candidate gene in this region, fibroblast growth factor 21 (FGF21), encodes a fibroblast growth factor involved in glucose and lipid metabolism. The variants in this locus were associated with circulating FGF21 protein concentrations (P < 0.05) but not mRNA concentrations in blood or brain. The body mass index (BMI)–increasing allele of the FTO variant (rs1421085) was associated with higher protein intake (β ± SE: 0.10 ± 0.02%; P = 9.96 × 10−10), independent of BMI (after adjustment for BMI, β ± SE: 0.08 ± 0.02%; P = 3.15 × 10−7).Conclusion: Our results indicate that variants in genes involved in nutrient metabolism and obesity are associated with macronutrient consumption in humans. Trials related to this study were registered at clinicaltrials.gov as NCT00005131 (Atherosclerosis Risk in Communities), NCT00005133 (Cardiovascular Health Study), NCT00005136 (Family Heart Study), NCT00005121 (Framingham Heart Study), NCT00083369 (Genetic and Environmental Determinants of Triglycerides), NCT01331512 (InCHIANTI Study), and NCT00005487 (Multi-Ethnic Study of Atherosclerosis).

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Objective-Angiogenesis and lymphangiogenesis are complex phenomena that involve the interplay of several growth factors and receptors. Recently, we have demonstrated that in Keratin-14 (K14) promoter-driven Vegf-A transgenic (Tg) mice, not only angiogenesis but also lymphangiogenesis is stimulated. However, the mechanism by which VEGFR1 is involved in lymphangiogenesis remains unclear. Methods and Results-To examine how important the tyrosine kinase (TK) of VEGFR1 is in lymphangiogenesis in K14Vegf-A Tg mice, we crossed the K14 Vegf-A Tg mice with Vegfr1-tk-deficient mice to generate double mutant K14 Vegf-A Tg Vegfr1 tk Ϫ/Ϫ mice. K14 Vegf-A Tg Vegfr1 tk Ϫ/Ϫ mice exhibit a remarkable decrease in lymphangiogensis as well as angiogenesis in subcutaneous tissues. To address the mechanism underlying the decrease in lymphangiogensis, we investigated the recruitment of monocyte-macrophage-lineage cells into the skin. The recruitment of VEGFR1-expressing macrophages driven by VEGF-A was reduced in K14 Vegf-A Tg Vegfr1 tk Ϫ/Ϫ mice. Vegf-A Tg mice that received Vegfr1-tk-deficient bone marrow showed a reduction of macrophage recruitment, lymphangiogenesis and angiogenesis compared with those in K14 Vegf-A Tg mice. Conclusions-VEGFR1

The assembly of individual endothelial cells into multicellular tubes is a complex morphogenetic event in vascular development. Extracellular matrix cues and cell-cell junctional communication are fundamental to tube formation. Together they determine the shape of endothelial cells and the tubular structures that they ultimately form. Little is known regarding how mechanical signals are transmitted between cells to control cell shape changes during morphogenesis. Here we provide evidence that the scaffold protein amotL2 is needed for aortic vessel lumen expansion. Using gene inactivation strategies in zebrafish, mouse and endothelial cell culture systems, we show that amotL2 associates to the VE-cadherin adhesion complex where it couples adherens junctions to contractile actin fibres. Inactivation of amotL2 dissociates VE-cadherin from cytoskeletal tensile forces that affect endothelial cell shape. We propose that the VE-cadherin/amotL2 complex is responsible for transmitting mechanical force between endothelial cells for the coordination of cellular morphogenesis consistent with aortic lumen expansion and function.

Nested case-control (NCC) design is used frequently in epidemiological studies as a cost-effective subcohort sampling strategy to conduct biomarker research. Sampling strategy, on the other hoand, creates challenges for data analysis because of outcome-dependent missingness in biomarker measurements. In this paper, we propose inverse probability weighted (IPW) methods for making inference about the prognostic accuracy of a novel biomarker for predicting future events with data from NCC studies. The consistency and asymptotic normality of these estimators are derived using the empirical process theory and convergence theorems for sequences of weakly dependent random variables. Simulation and analysis using Framingham Offspring Study data suggest that the proposed methods perform well in finite samples.

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ENCODE 3 (2012-2017) expanded production and added new types of assays 8 (Fig. 1, Extended Data Fig. 1), which revealed landscapes of RNA binding and the 3D organization of chromatin via methods such as chromatin interaction analysis by paired-end tagging (ChIA-PET) and Hi-C chromosome conformation capture. Phases 2 and 3 delivered 9,239 experiments (7,495 in human and 1,744 in mouse) in more than 500 cell types and tissues, including mapping of transcribed regions and transcript isoforms, regions of transcripts recognized by RNA-binding proteins, transcription factor binding regions, and regions that harbour specific histone modifications, open chromatin, and 3D chromatin interactions. The results of all of these experiments are available at the ENCODE portal (http://www.encodeproject.org). These efforts, combined with those of related projects and many other laboratories, have produced a greatly enhanced view of the human genome (Fig. 2), identifying 20,225 protein-coding and 37,595 noncoding genes