An epigenome-wide association study of child appetitive traits and DNA methylation

The etiology of childhood appetitive traits is poorly understood. Early-life epigenetic processes may be involved in the developmental programming of appetite regulation in childhood. One such process is DNA methylation (DNAm), whereby a methyl group is added to a specific part of DNA, where a cytosine base is next to a guanine base, a CpG site. We meta-analyzed epigenome-wide association studies (EWASs) of cord blood DNAm and early-childhood appetitive traits. Data were from two independent cohorts: the Generation R Study (n = 1,086, Rotterdam, the Netherlands) and the Healthy Start study (n = 236, Colorado, USA). DNAm at autosomal methylation sites in cord blood was measured using the Illumina Infinium HumanMethylation450 BeadChip. Parents reported on their child's food responsiveness, emotional undereating, satiety responsiveness and food fussiness using the Children's Eating Behaviour Questionnaire at age 4–5 years. Multiple regression models were used to examine the association of DNAm (predictor) at the individual site- and regional-level (using DMRff) with each appetitive trait (outcome), adjusting for covariates. Bonferroni-correction was applied to adjust for multiple testing. There were no associations of DNAm and any appetitive trait when examining individual CpG-sites. However, when examining multiple CpGs jointly in so-called differentially methylated regions, we identified 45 associations of DNAm with food responsiveness, 7 associations of DNAm with emotional undereating, 13 associations of DNAm with satiety responsiveness, and 9 associations of DNAm with food fussiness. This study shows that DNAm in the newborn may partially explain variation in appetitive traits expressed in early childhood and provides preliminary support for early programming of child appetitive traits through DNAm. Investigating differential DNAm associated with appetitive traits could be an important first step in identifying biological pathways underlying the development of these behaviors.</p

Real-Time Ligand Binding of Fluorescent VEGF-A Isoforms that Discriminate between VEGFR2 and NRP1 in Living Cells

© 2018 The Author(s) Fluorescent VEGF-A isoforms have been evaluated for their ability to discriminate between VEGFR2 and NRP1 in real-time ligand binding studies in live cells using BRET. To enable this, we synthesized single-site (N-terminal cysteine) labeled versions of VEGF165a, VEGF165b, and VEGF121a. These were used in combination with N-terminal NanoLuc-tagged VEGFR2 or NRP1 to evaluate the selectivity of VEGF isoforms for these two membrane proteins. All fluorescent VEGF-A isoforms displayed high affinity for VEGFR2. Only VEGF165a-TMR bound to NanoLuc-NRP1 with a similar high affinity (4.4 nM). Competition NRP1 binding experiments yielded a rank order of potency of VEGF165a > VEGF189a > VEGF145a. VEGF165b, VEGF-Ax, VEGF121a, and VEGF111a were unable to bind to NRP1. There were marked differences in the kinetic binding profiles of VEGF165a-TMR for NRP1 and VEGFR2. These data emphasize the importance of the kinetic aspects of ligand binding to VEGFR2 and its co-receptors in the dynamics of VEGF signaling. Peach et al. have used fluorescent VEGF-A isoforms to demonstrate that they can discriminate between VEGFR2 and its co-receptor NRP1 in real-time ligand binding studies in live cells. This precision chemical biology approach showed that fluorescent VEGF165a binds more rapidly to NRP1 than VEGFR2

Real-time analysis of the binding of fluorescent VEGF₁₆₅a to VEGFR2 in living cells: Effect of receptor tyrosine kinase inhibitors and fate of internalized agonist-receptor complexes

Vascular endothelial growth factor (VEGF) is an important mediator of angiogenesis. Here we have used a novel stoichiometric protein-labeling method to generate a fluorescent variant of VEGF (VEGF₁₆₅a-TMR) labeled on a single cysteine within each protomer of the antiparallel VEGF homodimer. VEGF₁₆₅a-TMR has then been used in conjunction with full length VEGFR2, tagged with the bioluminescent protein NanoLuc, to undertake a real time quantitative evaluation of VEGFR2 binding characteristics in living cells using bioluminescence resonance energy transfer (BRET). This provided quantitative information on VEGF-VEGFR2 interactions. At longer incubation times, VEGFR2 is internalized by VEGF₁₆₅a-TMR into intracellular endosomes. This internalization can be prevented by the receptor tyrosine kinase inhibitors (RTKIs) cediranib, sorafenib, pazopanib or vandetanib. In the absence of RTKIs, the BRET signal is decreased over time as a consequence of the dissociation of agonist from the receptor in intracellular endosomes and recycling of VEGFR2 back to the plasma membrane

Real-time ligand binding of fluorescent VEGF-A isoforms that discriminate between VEGFR2 and NRP1 in living cells

Fluorescent VEGF-A isoforms have been evaluated for their ability to discriminate between VEGFR2 and NRP1 in real-time ligand binding studies in live cells using BRET. To enable this, single-site (N-terminal cysteine) labelled versions of VEGF165a, VEGF165b and VEGF121a were synthesised. These were used in combination with N-terminal NanoLuc-tagged VEGFR2 or NRP1 to evaluate the selectivity of VEGF isoforms for these two membrane proteins. All fluorescent VEGF-A isoforms displayed high affinity for VEGFR2. Only VEGF165a-TMR bound to NanoLuc- NRP1 with a similar high affinity (4.4nM). Competition NRP1 binding experiments yielded a rank order of potency of VEGF165a > VEGF189a > VEGF145a. VEGF165b, VEGF-Ax, VEGF121a and VEGF111a were unable to bind to NRP1. There were marked differences in the kinetic binding profiles of VEGF165a-TMR for NRP1 and VEGFR2. These data emphasise the importance of the kinetic aspects of ligand binding to VEGFR2 and its co-receptors in the dynamics of VEGF signalling

Maternal Mediterranean diet in pregnancy and newborn DNA methylation:a meta-analysis in the PACE Consortium

Data de publicació electrònica: 02-03-2022Higher adherence to the Mediterranean diet during pregnancy is related to a lower risk of preterm birth and to better offspring cardiometabolic health. DNA methylation may be an underlying biological mechanism. We evaluated whether maternal adherence to the Mediterranean diet was associated with offspring cord blood DNA methylation.We meta-analysed epigenome-wide association studies (EWAS) of maternal adherence to the Mediterranean diet during pregnancy and offspring cord blood DNA methylation in 2802 mother-child pairs from five cohorts. We calculated the relative Mediterranean diet (rMED) score with range 0-18 and an adjusted rMED excluding alcohol (rMEDp, range 0-16). DNA methylation was measured using Illumina 450K arrays. We used robust linear regression modelling adjusted for child sex, maternal education, age, smoking, body mass index, energy intake, batch, and cell types. We performed several functional analyses and examined the persistence of differential DNA methylation into childhood (4.5-7.8 y).rMEDp was associated with cord blood DNA methylation at cg23757341 (0.064% increase in DNA methylation per 1-point increase in the rMEDp score, SE = 0.011, P = 2.41 × 10-8). This cytosine-phosphate-guanine (CpG) site maps to WNT5B, associated with adipogenesis and glycaemic phenotypes. We did not identify associations with childhood gene expression, nor did we find enriched biological pathways. The association did not persist into childhood.In this meta-analysis, maternal adherence to the Mediterranean diet (excluding alcohol) during pregnancy was associated with cord blood DNA methylation level at cg23757341. Potential mediation of DNA methylation in associations with offspring health requires further study.This work was supported by the Foundation for the National Institutes of Health [R01 HD034568, UH3 OD023286, R01 NR013945, R01 HL111108]; Joint Programming Initiative A healthy diet for a healthy life [529051023, MR/S036520/1, 529051022, MR/S036520/1, MR/S036520/1]; National Institute of Environmental Health Sciences [R00ES025817]; National institute of diabetes and digestive and kidney diseases [R01DK076648]; National Institutes of Health Office of the Director [UH3OD023248]; Horizon 2020 research and innovation [874739, 733206, 848158, 824989]; Medical Research Council [MR/S009310/1]

MiR-133b Targets Antiapoptotic Genes and Enhances Death Receptor-Induced Apoptosis

Despite the importance of microRNAs (miRs) for regulation of the delicate balance between cell proliferation and death, evidence for their specific involvement during death receptor (DR)-mediated apoptosis is scarce. Transfection with miR-133b rendered resistant HeLa cells sensitive to tumor necrosis factor-alpha (TNFα)-induced cell death. Similarly, miR-133b caused exacerbated proapoptotic responses to TNF-related apoptosis-inducing ligand (TRAIL) or an activating antibody to Fas/CD95. Comprehensive analysis, encompassing global RNA or protein expression profiling performed by microarray experiments and pulsed stable isotope labeling with amino acids in cell culture (pSILAC), led to the discovery of the antiapoptotic protein Fas apoptosis inhibitory molecule (FAIM) as immediate miR-133b target. Moreover, miR-133b impaired the expression of the detoxifying protein glutathione-S-transferase pi (GSTP1). Expression of miR-133b in tumor specimens of prostate cancer patients was significantly downregulated in 75% of the cases, when compared with matched healthy tissue. Furthermore, introduction of synthetic miR-133b into an ex-vivo model of prostate cancer resulted in impaired proliferation and cellular metabolic activity. PC3 cells were also sensitized to apoptotic stimuli after transfection with miR-133b similar to HeLa cells. These data reveal the ability of a single miR to influence major apoptosis pathways, suggesting an essential role for this molecule during cellular transformation, tumorigenesis and tissue homeostasis

Measuring progress and projecting attainment on the basis of past trends of the health-related Sustainable Development Goals in 188 countries: an analysis from the Global Burden of Disease Study 2016

The UN’s Sustainable Development Goals (SDGs) are grounded in the global ambition of “leaving no one behind”. Understanding today’s gains and gaps for the health-related SDGs is essential for decision makers as they aim to improve the health of populations. As part of the Global Burden of Diseases, Injuries, and Risk Factors Study 2016 (GBD 2016), we measured 37 of the 50 health-related SDG indicators over the period 1990–2016 for 188 countries, and then on the basis of these past trends, we projected indicators to 2030

Identification of <i>dom</i> modifiers among 30 loci encoding chromatin proteins.

<p>Table 1 shows the Bloomington stock number, gene name and modifier effect on <i>C96-domR</i> wing phenotype as Enhancer (E), Suppressor (S), No Effect (NE), or could not be determined (-) for the 30 tested loci. The 23 strains listed as modifiers showed highly significant wing nicking differences from controls (P< 0.001, chi square test). Ratio represents the % nicked wings observed in experimental divided by the control <i>w</i>^<i>1118</i> (% E/C) in crosses to <i>C96-domR</i> run simultaneously. N = # of wings scored. At least 500 <i>w</i>^<i>1118</i> control cross wings were scored for each assay. <i>C96-Gal4</i> column shows results of control crosses to the 30 strains to determine LOF effects. Nine strains showed such effects (+).</p><p>*The <i>TRIP1</i> cross to <i>C96-Gal4</i> was 100% lethal, but a small number of offspring eclosed from the <i>C96-domR</i> cross.</p><p>Identification of <i>dom</i> modifiers among 30 loci encoding chromatin proteins.</p

Genetic interactions of 30 chromatin protein encoding loci with <i>domino</i>.

<p>Wing mounts were prepared from the following Bloomington (BL) strains after crosses to <i>C96-domR</i>. Wings shown in panels C-F2 derived from crosses to TRiP strains. A. Wild Type wing BL3605 <i>w</i>^<i>1118</i>, B. Control wing <i>C96-domR/w</i>^<i>1118</i>, C. BL33981 <i>PCAF</i>, D. BL33962 <i>HP1c</i>, <i>E</i>. BL26234 <i>CC8</i>, <i>F</i>. BL31921 <i>JIGR1</i>, <i>G</i>. BL42514 <i>CC25</i>, <i>H</i>. BL31922 <i>CC20 I</i>. BL27085 <i>ERR</i>, <i>J</i>. BL33394 <i>RPS9</i>, <i>K</i>. BL32888 <i>CC24</i>, <i>L</i>. BL33361 <i>CC4</i>, <i>M</i>. BL33734 <i>CC7</i>, <i>N</i>. BL42491 <i>CC9</i>, <i>O</i>. BL26772 <i>CC15</i>, <i>P</i>. BL40853 <i>MAF-S</i>, <i>Q</i>. BL33974 <i>RYBP</i>, <i>R</i>. BL25993 <i>CC28</i>, <i>S</i>. BL29360 <i>CC32</i>, <i>T</i>. BL34580 <i>NUP50</i>, <i>U</i>. BL34069 <i>CAF1</i>, <i>V</i>. BL33043 <i>PCNA</i>, <i>W</i>. BL55250 <i>ASF1</i>, <i>X</i>. BL55314 <i>TOP1</i>, <i>Y</i>. BL33725 <i>RPD3</i>, <i>Z</i>. BL33666 <i>HEL25E</i>, <i>A2</i>. BL41937 <i>CC31</i>, <i>B2</i>. BL53697 <i>SIR2</i>, <i>C2</i>. BL34978 <i>TRIP1</i>, <i>D2</i>. BL26231 <i>CC34</i>, <i>E2</i>. BL31940 <i>CC30</i>, F2. BL31960 <i>DSP1</i></p