Unknown,Transcriptomics,Genomics,Proteomics

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Comparison of transcription profile of allogenic immune response generated in MLR and Humanzied mouse model

ABSTRACT: This experiment was carried out to demonstrate the efficacy of our novel humanized mouse model for identifying the best potential donor for the recipient. We performed a transcriptome analysis comparing the allogeneic immune response in MLR and the Hu-NSG-PBMC model. We identified several clinically relevant markers of graft rejection, such as GZMB, PRF1, and IL2, were significantly up regulated in one of the related donors only observed in the allogeneic response generated in the humanized mouse model.

ORGANISM(S): Mus musculus

SUBMITTER: Ashwin Ajith

PROVIDER: E-MTAB-10343 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Project description:Peripheral blood samples of patients with acute myocardial infarction were matched with those of control patients to identify possible differences in corresponding gene expression profiles. The controls were matched to cases based on gender, age, status of diabetes mellitus and smoking status. Six months cardiovascular survival status of the cases was used to identify two distinct subgroups among the cases. Linear models for microarray data (M-bM-^@M-^XlimmaM-bM-^@M-^Y) were employed to identify differential gene expression. Shrunken centroids technique helped in identifying the subsets of differentially expressed genes with predictive properties in independent samples. Predictive properties were evaluated using bootstrap sampling. Using the limma modeling with the log-fold change threshold of one (clinical significance) and StoreyM-bM-^@M-^Ys q-value approach (statistical significance), sixty transcripts were found to be both clinically and statistically differentially expressed among the cases not surviving the follow-up period relative to controls, while no such transcripts were observed among other surviving cases. The two subgroups of cases exhibited fourteen differentially expressed transcripts. Predictive modeling indicated sixteen out of sixty transcripts to best discriminate between the controls and cases who died during the follow-up period from cardiovascular causes, while for the surviving cases the already non-significant set of transcripts could not be further reduced. Eleven out of fourteen transcripts were found to best discriminate between the two groups of cases using shrunken centroids. The study identified genes, which were differentially expressed during the acute myocardial infarction, including those associated with short-term fatality of the cases. The genome-wide study used matched case-control design, with 97 samples of 90 patients in three disease groups. Matched control samples were used and several (7) technical replicates were performed.