Validating the genomic signature of pediatric septic shock Pussy king erotik video
Effective targeted therapy for sepsis requires an understanding of the heterogeneity in the individual host response to infection.
We investigated this heterogeneity by defining interindividual variation in the transcriptome of patients with sepsis and related this to outcome and genetic diversity.
In the United States, sepsis is one of the top ten leading causes of mortality .
Although adjusted in-hospital mortality has decreased gradually (2-3% per year) according to a recent report [1, 5], sepsis associated mortality remained high, from 50/100,000 to 75/100,000 [1, 6].
We report that analytical variance caused by sample processing was acceptably small.
Blood leukocyte gene expression in the same individual over a 24-h period was remarkably constant.
We mapped genomic determinants of variation in gene transcription between patients as expression quantitative trait loci (e QTL).
We discovered that following admission to intensive care, transcriptomic analysis of peripheral blood leucocytes defines two distinct sepsis response signatures (SRS1 and SRS2).
A better understanding of the blood systems response to sepsis should expedite the identification of biomarkers for early diagnosis and therapeutic interventions. We analyzed microarray studies whose data is available from the GEO repository and which were performed on the whole blood of septic patients and normal controls. We identified 6 cohorts consisting of 450 individuals (sepsis = 323, control = 127) providing genome-wide messenger RNA (m RNA) expression data.
In contrast, pathways related to “Ribosome”, “Spliceosome” and “Cell adhesion molecules” were found to be downregulated, along with known pathways for immune dysfunction.
Overall, our study revealed distinct m RNA activation profiles and protein-protein interaction networks in blood of human sepsis. Our findings suggest that aberrant m RNA expression in the lysosome and cytoskeleton pathways may play a pivotal role in the molecular pathobiology of human sepsis.
These data are then integrated into a homology framework (relations of homology between organs and between genes), facilitating the comparison of gene expression patterns, between and within species, as well as the study of their evolution.
To date, we have manually curated 15 988 Affymetrix chips from 1285 experiments, retrieved from Gene Expression Omnibus (GEO) (2) and Array Express (3).