GSE57065

Early and dynamic changes in gene expression in septic shock patients: a genome wide approach

Whole-study status Not suitable

Dataset does not meet the current suitability threshold.

Whole-study downloads — these do not apply your sample requirements.

Selected cohort requirements

Samples meeting selected requirements: 0 cases / 0 controls

View matching samples

Patient pairs verified in indexed sample metadata: 0

A case/control comparison meeting these requirements is not confirmed.

Counts describe samples, not independent patients. Pair verification uses explicit subject identifiers in indexed sample metadata. Zero verified pairs does not establish that the study is unpaired; reported matched-normal design alone is insufficient.

Summary

Background: As early and appropriate care of severe septic patients is associated with better outcome, understanding of very first events in the disease process is needed. Pan-genomic analyses offer an interesting opportunity to study global genomic response within the very first hours after sepsis. The objective of this study was to investigate the systemic genomic response in severe Intensive Care Unit (ICU) patients and determine whether patterns of gene expression could be associated with clinical severity evaluated by severity score. Methods: Twenty-eight ICU patients were enrolled at the onset of septic shock. Blood samples were collected within 30 minutes, 24 and 48 hours after shock and genomic response was evaluated using microarrays. The genome wide expression pattern of blood leukocytes was sequentially compared to healthy volunteers and after stratification based on SAPSII score to identify potential mechanisms of dysregulation. Results: Septic shock induces a global reprogramming of the whole leukocyte transcriptome affecting multiple functions and pathways (> 71% of the whole genome was modified). Most altered pathways were not significantly different between SAPSII-high and SAPSII-low groups of patients. However the magnitude and the duration of these alterations were different between these two groups. Importantly, we observed that the more severe patients did not exhibit the strongest modulation. This indicates that some regulation mechanisms leading to recovery seem to take place at early stage. Conclusion: In conclusion, both pro- and anti-inflammatory processes, measured at the transcriptomic level, are induced within the very first hours after septic shock. Interestingly, the more severe patients did not exhibit the strongest modulation. This highlights that, not only the responses mechanisms by themself but mainly their early and appropriate regulation, are crucial for patient recovery. This reinforces the idea that an immediate and tailored aggressive care of patients, aimed at restoring an appropriately regulated immune response, may have a beneficial impact on outcome.

Overall design

Twenty-eight ICU patients were enrolled at the onset of septic shock. Blood samples were collected within 30 minutes, 24 and 48 hours after septic shock and compared to twenty-five healthy volunteers

Source Evidence

4 sources
Source Contribution Status
GEO

Original dataset metadata, sample metadata, source links, and GEO data availability flags.

Sample records
107 GSM samples
Primary source
recount3

Planned trusted source for processed count availability.

No match found
Expression Atlas

Planned source for curated expression experiment links.

No match found
PubMed

Primary GEO citations and related PubMed articles that mention this dataset.

21 linked publications 21 DOIs

Primary publication

  1. Endogenous Retroviruses Transcriptional Modulation After Severe Infection, Trauma and Burn. Frontiers in immunology, 2018

Related publications

  1. Identification and mechanistic analysis of shared biomarkers and pathogenesis in acute pancreatitis and sepsis based on differential gene expression and protein interaction networks. Functional & integrative genomics, 2025
  2. PPARγ agonist alleviates sepsis-related liver injury by modulating M1/M2 macrophage polarization via the PPARγ/IκBα/NF-κB pathway. Life sciences, 2025
  3. Integrated multiomics and Mendelian randomization identify CHIT1 as a novel sepsis biomarker and therapeutic target. Scientific reports, 2025
  4. Candidate target genes in sepsis diagnosis and therapy: identifying hub genes with a spotlight on KLRB1. BMC infectious diseases, 2025
  5. Integrating single-cell transcriptomics and epigenetics in a multi-omics MR framework identifies PARK7 as a causal gene in streptococcal septicemia. Epigenetics & chromatin, 2026
  6. Identification of immune-related mitochondrial metabolic disorder genes in septic shock using bioinformatics and machine learning. Hereditas, 2024
  7. PPI-based screening of hub genes related to sepsis migration/pyroptosis and immune infiltration analysis. PloS one, 2025
  8. Identification of Potential Therapeutic Targets for Sepsis Using Mendelian Randomization and Integrated eQTL/pQTL Analysis. International journal of general medicine, 2025
  9. Cuproptosis-Related Biomarkers and Characterization of Immune Infiltration in Sepsis. Journal of inflammation research, 2024
  10. Deciphering the role of pyroptosis-related genes and natural killer T cells in sepsis pathogenesis: a comprehensive bioinformatics and Mendelian randomization analysis. Journal of physiology and pharmacology : an official journal of the Polish Physiological Society, 2025
  11. Systematic analysis of programmed cell death-related genes in sepsis reveals immune heterogeneity and enables patient stratification. Frontiers in cell and developmental biology, 2026
  12. Integrated bioinformatics analysis of molecular signatures and therapeutic targets in early sepsis. Frontiers in cellular and infection microbiology, 2026
  13. Identification of m5C-Related gene diagnostic biomarkers for sepsis: a machine learning study. Frontiers in genetics, 2024
  14. Development and validation of a machine-learning-based model for identification of genes associated with sepsis-associated acute kidney injury. Frontiers in genetics, 2025
  15. IL7R, GZMA and CD8A serve as potential molecular biomarkers for sepsis based on bioinformatics analysis. Frontiers in immunology, 2024
  16. The significance of long chain non-coding RNA signature genes in the diagnosis and management of sepsis patients, and the development of a prediction model. Frontiers in immunology, 2024
  17. Identification of FTO as a key m6A demethylase linking immune dysregulation to sepsis pathogenesis. Frontiers in immunology, 2026
  18. Integration of Transcriptomic and Single-Cell Data to Uncover Senescence- and Ferroptosis-Associated Biomarkers in Sepsis. Biomedicines, 2025
  19. [Exploration of key ferroptosis-related genes as therapeutic targets for sepsis based on bioinformatics and the depiction of their immune profiles characterization]. Zhonghua wei zhong bing ji jiu yi xue, 2024
  20. Bioinformatics analysis identifies IL-23A and JAK2 as regulatory factors in sepsis immune response via the JAK/STAT3 pathway. Journal of infection in developing countries, 2026
Available

Metadata Quality Components

Analysis Readiness

Not ready
33% DE readiness

Contrast completeness

0/25 pts

No usable case/control contrast was detected.

Minimum group size

0/20 pts

Minimum group size cannot be evaluated until a complete contrast exists.

Processed data availability

20/20 pts

Processed data is marked available in the GEO index.

Sample decision clarity

3/15 pts

Unassigned or review-needed samples remain before analysis.

Blocking warnings

0/10 pts

Critical warnings must be resolved before downstream analysis.

Metadata normalization

10/10 pts

Metadata quality is high enough to support downstream handoff.

Blockers

  • No complete case/control contrast is available.
  • 107 samples are still unassigned.
  • Critical dataset warnings must be resolved.

Next Steps

  • Resolve unassigned or review-needed samples in the grouping table.
  • Resolve critical warnings before downstream analysis.

Analysis Preparation Checklist

3/6 ready

Group labels reviewed

Blocked

No complete case/control grouping exists yet.

Review the sample grouping table and assign both case and control groups.

Minimum sample count met

Blocked

At least one group has fewer than 2 samples.

Choose a larger dataset or merge only scientifically valid groups.

Processed counts available

Ready

Processed data availability is marked true in the GEO index.

Verify that downloaded processed files contain usable count or expression identifiers.

Ambiguous samples handled

Needs review

0 review-needed samples and 107 unassigned samples remain.

Resolve ambiguous and unassigned samples before finalizing the contrast.

Exclusion decisions recorded

Ready

No hard-excluded samples were detected by the current rules.

Record any manual exclusions in the downstream analysis notes.

Source traceability preserved

Ready

The dataset and sample accessions can be traced back to GEO.

Keep GEO accessions with exported metadata.

Bioinformatician Review

Bioinformatician review required

Ask a bioinformatician to review grouping, count availability, exclusions, and design before DE.

Analysis readiness has blockers that must be resolved before DE.

Analysis preparation checklist contains blocked items.

No complete case/control or treatment/control contrast is available.

At least one comparison group has fewer than two samples.

One or more samples are unassigned and need manual grouping decisions.

Critical dataset warnings are present.

Assay context may require expert handling before DESeq2-style analysis.

Study design is model-system or unclear and should be reviewed before analysis.

Why This Is Ranked Here

Tumor vs normal
Not suitable Dataset does not meet the current suitability threshold.

Applied Review Decisions

No active review decisions affect this ranking.

Derived Classifications

  • Assay differs from search intent Microarray Search intent expects bulk RNA-seq. Assay came from Normalization rules.
  • Disease context Sepsis, septic shock Disease context came from Normalization rules.
  • Likely case group No case group detected 0 samples
  • Likely control group No control group detected 0 samples

Intent Interpretation

  • Downgrade or exclusion reason Comparison: Unclear study design. Specimen: Biofluid. Comparison suitability: 0%. Derived from current-intent ranking reasons.

Ranking Facts

Supporting evidence

  • Interpreted disease metadata: Sepsis, Septic shock.
  • Processed data is available for downstream review.
  • External evidence: PubMed links 21 publications; 21 DOIs available: PMID 30671061, PMID 38681070, PMID 39540021, PMID 39586719, PMID 39609718.
  • Publication context: Endogenous Retroviruses Transcriptional Modulation After Severe Infection, Trauma and Burn.. Frontiers in immunology, 2018. PMID 30671061. DOI 10.3389/fimmu.2018.03091.
  • Publication context: Cuproptosis-Related Biomarkers and Characterization of Immune Infiltration in Sepsis.. Journal of inflammation research, 2024. PMID 38681070. DOI 10.2147/JIR.S452980.
  • Publication context: Identification of m5C-Related gene diagnostic biomarkers for sepsis: a machine learning study.. Frontiers in genetics, 2024. PMID 39540021. DOI 10.3389/fgene.2024.1444003.
  • Publication context: 18 additional linked PubMed publications are available.

Cautions

  • Comparison: Unclear study design. Specimen: Biofluid. Comparison suitability: 0%.
  • Downgraded for tissue search because it is a biofluid cohort.
  • Downgraded for tissue search because study design or specimen source is unclear.
  • Downgraded assay: microarray cohorts are separated from the RNA-seq intent.
  • Blood, plasma, or serum cohort downgraded because this ranking targets tissue tumor-vs-normal comparisons.
  • Unclear study design downgraded for patient tissue tumor-vs-normal search intent.
  • Missing or unclear metadata. Unclear study design downgraded for patient tissue tumor-vs-normal search intent.
  • Microarray expression context downgraded below primary bulk RNA-seq for the default tissue ranking.
  • Missing or unclear metadata. Group clarity - Case and control groups are not clear from sample metadata.
  • Overall score capped because comparison suitability is weak for the selected search intent.
  • Overall score capped because microarray cohorts should be compared separately from RNA-seq cohorts.
  • Missing or unclear metadata. Comparison - Unclear study design. Specimen - Biofluid. Comparison suitability: 0%.
  • Missing or unclear metadata. Downgraded for tissue search because study design or specimen source is unclear.
  • Comparison suitability score is below the Phase 1 recommended threshold.

Dataset Warnings

Normalized Fields

219 fields

Sample Group Preview

showing 50 of 107 preview rows
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Study totals: Case 0 | Control 0 | Unassigned 107 | Excluded 0 | Ambiguous 0 showing 50 of 107 preview rows
Group Role Accession Title Source / characteristics Reason
Unassigned Unassigned GSM1373914 Blood_P001_H00 Patient 001, H0 Age: 43; Gender: FEMALE; Sapsii: SAPSII-High; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373915 Blood_P001_H24 Patient 001, H24 Age: 43; Gender: FEMALE; Sapsii: SAPSII-High; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373916 Blood_P001_H48 Patient 001, H48 Age: 43; Gender: FEMALE; Sapsii: SAPSII-High; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373917 Blood_P002_H00 Patient 002, H0 Age: 34; Gender: FEMALE; Sapsii: SAPSII-Low; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373918 Blood_P002_H24 Patient 002, H24 Age: 34; Gender: FEMALE; Sapsii: SAPSII-Low; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373919 Blood_P002_H48 Patient 002, H48 Age: 34; Gender: FEMALE; Sapsii: SAPSII-Low; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373920 Blood_P003_H00 Patient 003, H0 Age: 69; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373921 Blood_P003_H24 Patient 003, H24 Age: 69; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373922 Blood_P003_H48 Patient 003, H48 Age: 69; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373923 Blood_P004_H00 Patient 004, H0 Age: 41; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373924 Blood_P004_H24 Patient 004, H24 Age: 41; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373925 Blood_P004_H48 Patient 004, H48 Age: 41; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373926 Blood_P005_H00 Patient 005, H0 Age: 79; Gender: MALE; Sapsii: SAPSII-High; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373927 Blood_P005_H24 Patient 005, H24 Age: 79; Gender: MALE; Sapsii: SAPSII-High; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373928 Blood_P005_H48 Patient 005, H48 Age: 79; Gender: MALE; Sapsii: SAPSII-High; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373929 Blood_P006_H00 Patient 006, H0 Age: 29; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373930 Blood_P006_H24 Patient 006, H24 Age: 29; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373931 Blood_P006_H48 Patient 006, H48 Age: 29; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373932 Blood_P007_H00 Patient 007, H0 Age: 76; Gender: FEMALE; Sapsii: SAPSII-Low; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373933 Blood_P007_H24 Patient 007, H24 Age: 76; Gender: FEMALE; Sapsii: SAPSII-Low; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373934 Blood_P007_H48 Patient 007, H48 Age: 76; Gender: FEMALE; Sapsii: SAPSII-Low; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373935 Blood_P008_H00 Patient 008, H0 Age: 84; Gender: FEMALE; Sapsii: SAPSII-High; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373936 Blood_P008_H24 Patient 008, H24 Age: 84; Gender: FEMALE; Sapsii: SAPSII-High; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373937 Blood_P008_H48 Patient 008, H48 Age: 84; Gender: FEMALE; Sapsii: SAPSII-High; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373938 Blood_P009_H00 Patient 009, H0 Age: 58; Gender: FEMALE; Sapsii: SAPSII-Low; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373939 Blood_P009_H24 Patient 009, H24 Age: 58; Gender: FEMALE; Sapsii: SAPSII-Low; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373940 Blood_P009_H48 Patient 009, H48 Age: 58; Gender: FEMALE; Sapsii: SAPSII-Low; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373941 Blood_P010_H00 Patient 010, H0 Age: 83; Gender: FEMALE; Sapsii: SAPSII-High; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373942 Blood_P010_H24 Patient 010, H24 Age: 83; Gender: FEMALE; Sapsii: SAPSII-High; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373943 Blood_P010_H48 Patient 010, H48 Age: 83; Gender: FEMALE; Sapsii: SAPSII-High; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373944 Blood_P011_H00 Patient 011, H0 Age: 79; Gender: MALE; Sapsii: SAPSII-High; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373945 Blood_P011_H24 Patient 011, H24 Age: 79; Gender: MALE; Sapsii: SAPSII-High; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373946 Blood_P011_H48 Patient 011, H48 Age: 79; Gender: MALE; Sapsii: SAPSII-High; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373947 Blood_P013_H00 Patient 013, H0 Age: 59; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373948 Blood_P013_H24 Patient 013, H24 Age: 59; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373949 Blood_P013_H48 Patient 013, H48 Age: 59; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373950 Blood_P014_H00 Patient 014, H0 Age: 76; Gender: MALE; Sapsii: SAPSII-High; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373951 Blood_P014_H24 Patient 014, H24 Age: 76; Gender: MALE; Sapsii: SAPSII-High; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373952 Blood_P014_H48 Patient 014, H48 Age: 76; Gender: MALE; Sapsii: SAPSII-High; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373953 Blood_P015_H00 Patient 015, H0 Age: 56; Gender: MALE; Sapsii: SAPSII-High; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373954 Blood_P015_H24 Patient 015, H24 Age: 56; Gender: MALE; Sapsii: SAPSII-High; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373955 Blood_P015_H48 Patient 015, H48 Age: 56; Gender: MALE; Sapsii: SAPSII-High; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373956 Blood_P017_H00 Patient 017, H0 Age: 56; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373957 Blood_P017_H24 Patient 017, H24 Age: 56; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373958 Blood_P017_H48 Patient 017, H48 Age: 56; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373959 Blood_P018_H00 Patient 018, H0 Age: 64; Gender: MALE; Sapsii: SAPSII-High; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373960 Blood_P018_H24 Patient 018, H24 Age: 64; Gender: MALE; Sapsii: SAPSII-High; Collection time: 24 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373961 Blood_P018_H48 Patient 018, H48 Age: 64; Gender: MALE; Sapsii: SAPSII-High; Collection time: 48 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373962 Blood_P019_H00 Patient 019, H0 Age: 68; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 0 hr No explicit case or control marker detected.
Unassigned Unassigned GSM1373963 Blood_P019_H24 Patient 019, H24 Age: 68; Gender: MALE; Sapsii: SAPSII-Low; Collection time: 24 hr No explicit case or control marker detected.
57 additional unassigned samples are hidden from this preview.

Use as Discovery Cohort

External Validation Finder

Carry Siftome's disease, organism, specimen, assay, data type, and accession into a validation project. Uncertain fields remain Unknown.