Project description:Sub-optimal fetal development is associated with an increased risk of developing cardiovascular disease, type 2 diabetes (T2D) and adiposity later in life. However, definitions of intrauterine growth restriction (IUGR) and small for gestational age (SGA) are based on simple statistical approaches that may misclassify infants with a normal developmental profile and vice versa. We used an unbiased global profiling approach to identify gene expression patterns in umbilical cord tissue from 38 infants and identified a set of 466 genes which separated the subjects into 2 distinct groups – one biased towards lower birth weight and one biased towards normal birth weight. The data suggest that approximately 30% of children of normal size have a molecular profile more typical of impaired fetal development and who may be on a programmed trajectory. Differences in expression between the two groups encompassed 384 upregulated and 82 downregulated genes. Molecular profiling at birth may have utility in identifying markers that potentially reflect antenatal developmental and may be predictive of future phenotypic development after birth. Importantly, it may provide an alternative to the current classification of infants using birth weights.
Project description:Sub-optimal fetal development is associated with an increased risk of developing cardiovascular disease, type 2 diabetes (T2D) and adiposity later in life. However, definitions of intrauterine growth restriction (IUGR) and small for gestational age (SGA) are based on simple statistical approaches that may misclassify infants with a normal developmental profile and vice versa. We used an unbiased global profiling approach to identify gene expression patterns in umbilical cord tissue from 38 infants and identified a set of 466 genes which separated the subjects into 2 distinct groups – one biased towards lower birth weight and one biased towards normal birth weight. The data suggest that approximately 30% of children of normal size have a molecular profile more typical of impaired fetal development and who may be on a programmed trajectory. Differences in expression between the two groups encompassed 384 upregulated and 82 downregulated genes. Molecular profiling at birth may have utility in identifying markers that potentially reflect antenatal developmental and may be predictive of future phenotypic development after birth. Importantly, it may provide an alternative to the current classification of infants using birth weights. RNA from umbilical cord tissue from full term neonates was extracted and hybridized. Separation into 2 distinct groups, independent of birth weight, but based solely on gene expression levels was analysed by Genespring. After appropriate statistical analysis, one group was keenly associated with a higher birth weight (22 samples) while the other was associated with a lower birth-weight (18 samples). Technical replicates were included for all 40 samples.
Project description:Peripheral T-cell lymphoma (PTCL) is a clinically aggressive disease, with a poor response to therapy and a low overall survival rate of around 30% after 5 years. We have analyzed a series of 105 cases with a diagnosis of PTCL using a customized NanoString platform that includes 208 genes associated with T-cell differentiation, oncogenes and tumor suppressor genes, deregulated pathways and stromal cell subpopulations. A comparative analysis of the various histological types of PTCL (angioimmunoblastic T-cell lymphoma, AITL; PTCL-with T follicular helper phenotype, PTCL-TFH; PTCL-not otherwise signified, PTCL-NOS) showed that specific sets of genes were associated with each of the diagnoses. These included TFH markers, cytotoxic markers and genes whose expression was a surrogate for specific cellular subpopulations, including follicular dendritic cells, mast cells and genes belonging to precise survival (NF-κB) and other pathways. Furthermore, the mutational profile was analyzed using a custom panel that targeted 62 genes in 76 cases distributed in AITL, PTCL-TFH and PTCL-NOS. The main differences between the three nodal PTCL classes involved the RHOAG17V mutations (p<0.0001), which were approximately twice as frequent in AITL (34.09%) as in PTCL-TFH (16.66%) cases, but were not detected in PTCL-NOS. A multivariate analysis identified gene sets that allowed the series of cases to be stratified into different risk groups. This study supports and validates the current division of PTCL into these three categories, identifies sets of markers that can be used for a more precise diagnosis, and recognizes the expression of B-cell genes as an IPI-independent prognostic factor for AITL.