Project description:All subjects were recruited at Centennial Women?s Hospital and the Perinatal Research Center in Nashville, TN beginning in 2003. Pregnant women were enrolled during their first clinical visit after obtaining informed consent as described previously. Demographic and clinical data specific to the fetus was collected from clinical records. Gestational age of the neonate was determined by maternal reporting of the last menstrual period and corroboration by ultrasound dating. Accurate knowledge of gestational age (GA) is essential for proper monitoring and care of neonates. However, accurate GA measures are often not available. DNA methylation has previously been shown to associate with GA, and has been used to accurately predict chronological age in adults. In the current study, we examine whether DNA methylation in cord blood can be used to predict gestational age at birth. Results: We found that GA can be accurately predicted from DNA methylation of neonatal cord blood and blood spot samples (DNAm GA), using 148 CpG sites selected through elastic net regression in six training datasets (N=207). We evaluated predictive accuracy in six testing datasets (N=1,202), and found that the accuracy of DNAm GA meets or exceeds accuracy of gestational age estimates based on established methods. We also found an increased DNAm GA, relative to clinical GA, was associated with increased birthweight percentile (p=.00057), adjusting for GA, sex, and ancestry, suggesting that DNAm GA could represent developmental age more accurately than clinical estimates of GA. Conclusions: Further development of this predictor could provide a method of accurate neonatal estimation of GA for use in resource-limited populations, or in cases where GA cannot be estimated clinically. When clinical estimates are available, the predictor can be used to test hypotheses related to developmental age and other early life circumstances, and may provide increased accuracy beyond clinical estimates.
Project description:All subjects were recruited at Centennial Women?s Hospital and the Perinatal Research Center in Nashville, TN beginning in 2003. Pregnant women were enrolled during their first clinical visit after obtaining informed consent as described previously. Demographic and clinical data specific to the fetus was collected from clinical records. Gestational age of the neonate was determined by maternal reporting of the last menstrual period and corroboration by ultrasound dating. Accurate knowledge of gestational age (GA) is essential for proper monitoring and care of neonates. However, accurate GA measures are often not available. DNA methylation has previously been shown to associate with GA, and has been used to accurately predict chronological age in adults. In the current study, we examine whether DNA methylation in cord blood can be used to predict gestational age at birth. Results: We found that GA can be accurately predicted from DNA methylation of neonatal cord blood and blood spot samples (DNAm GA), using 148 CpG sites selected through elastic net regression in six training datasets (N=207). We evaluated predictive accuracy in six testing datasets (N=1,202), and found that the accuracy of DNAm GA meets or exceeds accuracy of gestational age estimates based on established methods. We also found an increased DNAm GA, relative to clinical GA, was associated with increased birthweight percentile (p=.00057), adjusting for GA, sex, and ancestry, suggesting that DNAm GA could represent developmental age more accurately than clinical estimates of GA. Conclusions: Further development of this predictor could provide a method of accurate neonatal estimation of GA for use in resource-limited populations, or in cases where GA cannot be estimated clinically. When clinical estimates are available, the predictor can be used to test hypotheses related to developmental age and other early life circumstances, and may provide increased accuracy beyond clinical estimates. 36 Umbilical cord blood samples were collected in EDTA tubes soon after placental delivery. Blood samples were centrifuged at 3,000 RPM to separate plasma, and buffy coats were aliquoted and stored at -80oC. DNA was extracted using the DNeasy Kit (Qiagen). DNA methylation was interrogated for each sample using the HumanMethylation450 BeadChip (Illumina).
Project description:BackgroundDespite experimental evidence that lactational exposure to persistent organic pollutants (POPs) can impact health, results from epidemiologic studies are inconclusive. Inconsistency across studies may reflect the inability of current methods to estimate children's blood levels during specific periods of susceptibility.ObjectivesWe developed a toxicokinetic model to simulate blood POP levels in children from two longitudinal birth cohorts and aimed to validate it against blood levels measured at 6, 16, and 45 months of age.MethodsThe model consisted of a maternal and a child lipid compartment connected through placental diffusion and breastfeeding. Simulations were carried out based on individual physiologic parameters; duration of breastfeeding; and levels of POPs measured in maternal blood at delivery, cord blood, or breast milk. Model validity was assessed through regression analyses of simulated against measured blood levels.ResultsSimulated levels explained between 10% and 83% of measured blood levels depending on the cohort, the compound, the sample used to simulate children's blood levels, and child's age when blood levels were measured. Model accuracy was highest for estimated blood POP levels at 6 months based on maternal or cord blood levels. However, loss in model precision between the 6th and the 45th month was small for most compounds.ConclusionsOur validated toxicokinetic model can be used to estimate children's blood POP levels in early to mid-childhood. Estimates can be used in epidemiologic studies to evaluate the impact of exposure during hypothesized postnatal periods of susceptibility on health.
Project description:The licensing of talimogene laherparepvec (T-Vec) represented a landmark moment for oncolytic virotherapy, since it provided unequivocal evidence for the long-touted potential of genetically modified replicating viruses as anti-cancer agents. Whilst T-Vec is promising as a locally delivered virotherapy, especially in combination with immune-checkpoint inhibitors, the quest continues for a virus capable of specific tumour cell killing via systemic administration. One candidate is oncolytic adenovirus (Ad); it’s double stranded DNA genome is easily manipulated and a wide range of strategies and technologies have been employed to empower the vector with improved pharmacokinetics and tumour targeting ability. As well characterised clinical and experimental agents, we have detailed knowledge of adenoviruses’ mechanisms of pathogenicity, supported by detailed virological studies and in vivo interactions. In this review we highlight the strides made in the engineering of bespoke adenoviral vectors to specifically infect, replicate within, and destroy tumour cells. We discuss how mutations in genes regulating adenoviral replication after cell entry can be used to restrict replication to the tumour, and summarise how detailed knowledge of viral capsid interactions enable rational modification to eliminate native tropisms, and simultaneously promote active uptake by cancerous tissues. We argue that these designer-viruses, exploiting the viruses natural mechanisms and regulated at every level of replication, represent the ideal platforms for local overexpression of therapeutic transgenes such as immunomodulatory agents. Where T-Vec has paved the way, Ad-based vectors now follow. The era of designer oncolytic virotherapies looks decidedly as though it will soon become a reality.
Project description:The GluD1 and GluD2 receptors form the GluD ionotropic glutamate receptor (iGluR) subfamily. Without known endogenous ligands, they have long been referred to as 'orphan' and remained enigmatic functionally. Recent progress has, however, radically changed this view. Both GluD receptors are expressed in wider brain regions than originally thought. Human genetic studies and analyses of knockout mice have revealed their involvement in multiple neurodevelopmental and psychiatric disorders. The discovery of endogenous ligands, together with structural investigations, has opened the way towards a mechanistic understanding of GluD signaling at central nervous system synapses. These studies have also prompted the hypothesis that all iGluRs, and potentially other neurotransmitter receptors, rely on the cooperative binding of extracellular small-molecule and protein ligands for physiological signaling.
Project description:Overactive phosphoinositide 3-kinase (PI3K) in cancer and immune dysregulation has spurred extensive efforts to develop therapeutic PI3K inhibitors. Although progress has been hampered by issues such as poor drug tolerance and drug resistance, several PI3K inhibitors have now received regulatory approval - the PI3Kα isoform-selective inhibitor alpelisib for the treatment of breast cancer and inhibitors mainly aimed at the leukocyte-enriched PI3Kδ in B cell malignancies. In addition to targeting cancer cell-intrinsic PI3K activity, emerging evidence highlights the potential of PI3K inhibitors in cancer immunotherapy. This Review summarizes key discoveries that aid the clinical translation of PI3Kα and PI3Kδ inhibitors, highlighting lessons learnt and future opportunities.
Project description:Insights into genetic origin of diseases and related traits could substantially impact strategies for improving human health. The results of genome-wide association studies (GWAS) are often positioned as discoveries of unconditional risk alleles of complex health traits. We re-analyzed the associations of single nucleotide polymorphisms (SNPs) associated with total cholesterol (TC) in a large-scale GWAS meta-analysis. We focused on three generations of genotyped participants of the Framingham Heart Study (FHS). We show that the effects of all ten directly-genotyped SNPs were clustered in different FHS generations and/or birth cohorts in a sex-specific or sex-unspecific manner. The sample size and procedure-therapeutic issues play, at most, a minor role in this clustering. An important result was clustering of significant associations with the strongest effects in the youngest, or 3rd Generation, cohort. These results imply that an assumption of unconditional connections of these SNPs with TC is generally implausible and that a demographic perspective can substantially improve GWAS efficiency. The analyses of genetic effects in age-matched samples suggest a role of environmental and age-related mechanisms in the associations of different SNPs with TC. Analysis of the literature supports systemic roles for genes for these SNPs beyond those related to lipid metabolism. Our analyses reveal strong antagonistic effects of rs2479409 (the PCSK9 gene) that cautions strategies aimed at targeting this gene in the next generation of lipid drugs. Our results suggest that standard GWAS strategies need to be advanced in order to appropriately address the problem of genetic susceptibility to complex traits that is imperative for translation to health care.
Project description:We assess the progress in biomolecular modeling and simulation, focusing on structure prediction and dynamics, by presenting the field’s history, metrics for its rise in popularity, early expressed expectations, and current significant applications. The increases in computational power combined with improvements in algorithms and force fields have led to considerable success, especially in protein folding, specificity of ligand/biomolecule interactions, and interpretation of complex experimental phenomena (e.g. NMR relaxation, protein-folding kinetics and multiple conformational states) through the generation of structural hypotheses and pathway mechanisms. Although far from a general automated tool, structure prediction is notable for proteins and RNA that preceded the experiment, especially by knowledge-based approaches. Thus, despite early unrealistic expectations and the realization that computer technology alone will not quickly bridge the gap between experimental and theoretical time frames, ongoing improvements to enhance the accuracy and scope of modeling and simulation are propelling the field onto a productive trajectory to become full partner with experiment and a field on its own right.
Project description:Since the first high-resolution structure of the nucleosome was reported in 1997, the available information on chromatin structure has increased very rapidly. Here, we review insights derived from cutting-edge biophysical and structural approaches applied to the study of nucleosome dynamics and nucleosome-binding factors, with a focus on the experimental advances driving the research. In addition, we highlight emerging challenges in nucleosome structural biology.