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:We aimed to exemplify early and late transcriptional response of M. galloprovincialis to live Vibrio cells. Hemolymph was collected at 3 and 48 hours after the injection of 10 to 7 cells Vibrio splendidus LGP32 into the posterior adductor muscle. Hemolymph samples were similarly collected from paired control mussels injected with PBS-NaCl. The purified RNAs were successfully amplified, labelled and competitively hybridized to the new mussel oligoarray Immunochip 1.0.
Project description:Genome-wide mRNA expression profiles of 31 primary gastric tumors from the UK patient cohort. Gastric cancer (GC) is the second leading cause of global cancer mortality, with individual gastric tumors displaying significant heterogeneity in their deregulation of various oncogenic pathways. We aim to identify major oncogenic pathways in GC that robustly impact patient survival and treatment response. We used an in silico strategy based on gene expression signatures and connectivity analytics to map patterns of oncogenic pathway activation in 25 unique GC cell lines, and in 301 primary gastric cancers from three independent patient cohorts. Of 11 oncogenic pathways previously implicated in GC, we identified three predominant pathways (proliferation/stem cell, NF-kB, and Wnt/b-catenin) deregulated in the majority (>70%) of gastric tumors. Using a variety of proliferative, Wnt, and NF-kB-related assays, we experimentally validated the pathway predictions in multiple GC cell lines showing similar pathway activation patterns in vitro. Patients stratified at the level of individual pathways did not exhibit consistent differences in clinical outcome. However, patients grouped by oncogenic pathway combinations demonstrated robust and significant survival differences (e.g., high proliferation/high NF-kB vs. low proliferation/low NF-kB), suggesting that tumor behavior in GC is likely influenced by the combined effects of multiple oncogenic pathways. Our results demonstrate that GCs can be successfully taxonomized by oncogenic pathway activity into biologically and clinically relevant subgroups. Keywords: gastric cancer, cell culture
Project description:Alzheimer case-control samples originate from the EU funded AddNeuroMed Cohort, which is a large cross-European AD biomarker study relying on human blood as the source of RNA.