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| Status |
Public on Jun 04, 2015 |
| Title |
A Blood Transcriptional Diagnostic Assay for Septicemic Melioidosis |
| Organism |
Homo sapiens |
| Experiment type |
Expression profiling by array
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| Summary |
Melioidosis, caused by Gram negative bacteria Burkholderia pseudomallei, is a major type of community-acquired septicemia in Southeast Asia and Northern Australia with high mortality and morbidity rate. More accurate and rapid diagnosis is needed for improving the management of septicemic melioidosis. We previously identified 37-gene candidate signature to distinguish septicemic melioidosis from sepsis due to other pathogens. The aims of this current study were to independently validate our previous biomarker and consolidate gene selection from each of our microarray data set for establishing a targeted assay for the differential diagnosis of melioidosis. Blood samples were collected from patients who presented with severe inflammatory response syndromes from 3 provincial hospitals in Northeast of Thailand during September 2009 and November 2011. Only culture-confirmed sepsis were included in the study (n=166). We generated a new microarray dataset comprising of 29 patients with septicemic melioidosis and 54 patients with sepsis due to other pathogens. Validation of the 37-gene signature using this new dataset demonstrated the prediction accuracy of approximately 80% for detecting type of sepsis. In order to develop a nanoliter-scale high throughput PCR technology, we further identified additional gene signature from this new microarray dataset and by revisiting our published data. Altogether 85 genes including 6 housekeeping genes were selected. Using multi-steps iteration approach we could reduce the number of biomarkers to 12 genes while the performance is comparable to that of the full panel. The high performance (accuracy >70%) of this 12-gene signature could be validated in a second independent set of samples. The 12-gene panel identified by our study provides high performance for the differential diagnosis of septicemic melioidosis. This finding will be useful for improving the management of septicemic melioidosis in term of diagnosis, treatment and follow up.
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| Overall design |
Total RNA from whole blood obtained from patients with sepsis caused by B.pseudomallei (n=29) or other pathogens (n=54) and uninfected controls (28 healthy and 27 subjects with type 2 diabetes mellitus) were collected. In order to validate the published signature, microarray data were generated from these samples. This dataset was also used for an independent selection of signature for septicemic melioidosis. The same RNA samples were used for validation by a high throughput real-time PCR technique, Fluidigm.
Please note that the non_normalized.txt contains background-subtracted raw data.
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| Contributor(s) |
Khaenam P, Buddhisa S, Altman MC, Mason M, Whalen E, Susaengrat W, O’Brien K, Nguyen Q, Popov D, Gersuk V, Presnell S, Quinn C, Bancroft GJ, Lertmemongkolchai G, Chaussabel D |
| Citation(s) |
19903332 |
| Submission date |
Jun 03, 2015 |
| Last update date |
Apr 22, 2020 |
| Contact name |
Scott Presnell |
| E-mail(s) |
SPresnell@benaroyaresearch.org
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| Organization name |
Benaroya Research Institute
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| Street address |
1201 Ninth Avenue
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| City |
Seattle |
| State/province |
WA |
| ZIP/Postal code |
98101 |
| Country |
USA |
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| Platforms (1) |
| GPL10558 |
Illumina HumanHT-12 V4.0 expression beadchip |
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| Samples (138)
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| Relations |
| BioProject |
PRJNA285800 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSE69528_RAW.tar |
26.2 Mb |
(http)(custom) |
TAR |
| GSE69528_non_normalized.txt.gz |
41.2 Mb |
(ftp)(http) |
TXT |
| Processed data included within Sample table |
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