Sepsis Biomarkers: Advancements and Clinical Applications—A Narrative Review
Abstract
:1. Introduction
2. What Is an Ideal Sepsis Biomarker?
3. Methods
3.1. Inclusion and Exclusion Criteria
3.2. Search Strategies
3.3. Study Selection
3.4. Data Collection
4. Biomarkers for Sepsis Diagnosis
4.1. Commonly Used Diagnostic Biomarkers
4.1.1. C-Reactive Protein (CRP)
4.1.2. Procalcitonin (PCT)
4.1.3. Interleukin-6 (IL-6)
4.1.4. High-Mobility Group Box 1 (HMGB1)
4.1.5. Pancreatic Stone Protein (PSP)
4.1.6. Presepsin
4.1.7. Cluster of Differentiation 64 (CD64)
4.1.8. Soluble Triggering Receptor Expressed on Myeloid Cells-1 (sTREM-1)
4.2. Novel Diagnostic Biomarkers
4.2.1. Circular RNAs (circRNAs)
4.2.2. HOXA Distal Transcript Antisense RNA (HOTTIP)
4.2.3. microRNA-486-5p
5. Biomarkers for Sepsis Prognosis
5.1. Commonly Used Prognostic Biomarkers
5.1.1. Pentraxin-3 (PTX-3)
5.1.2. Adrenomedullin (ADM)
5.1.3. Endothelial Cell-Specific Molecule-1 (ESM-1)
5.1.4. Plasminogen Activator Inhibitor-1 (PAI-1)
5.1.5. S100 Calcium-Binding Protein B (S100B)
5.1.6. N-Terminal-Pro Hormone BNP (NT-proBNP)
5.1.7. Non-Coding RNAs
5.1.8. Others
5.2. Novel Prognostic Biomarkers
5.2.1. Prokineticin 2
5.2.2. Protein C (PC)
Biomarker | Source | Biological Function | Clinical Applications | Testing Methods | Strengths | Limitations | Refs. |
---|---|---|---|---|---|---|---|
Commonly used prognostic biomarkers | |||||||
PTX-3 | Various cells (macrophages, dendritic cells) | Acute inflammatory response |
|
|
|
| [47,91,92,93,94,95] |
ADM | Vascular smooth muscle and endothelial cells | Vasodilation, reduced endothelial permeability |
|
|
|
| [19,96,97,98,99,100] |
ESM-1 | Endothelial cells | Regulation of angiogenesis and inflammation |
|
|
|
| [102,103,104,105] |
PAI-1 | Various cells (endothelial cells, platelets, and adipocytes, etc.) | Inhibition of fibrinolysis |
|
|
|
| [106,107,108,109,110] |
S100B | Glial cells | Reflects blood–brain barrier disruption and brain injury |
|
|
|
| [111,112,113,114,115] |
NT-proBNP | Cardiac ventricular myocytes | Response to cardiac pressure changes |
|
|
|
| [116,117,118,119] |
lncRNAs CASC2 | Various tissues | Regulation of gene expression, cell proliferation, differentiation, apoptosis |
|
|
|
| [120,121,122] |
miRNAs | Various cells | Post-transcriptional regulation of gene expression |
|
|
|
| [84,90] |
sPD-L1 | Immune cells and tumor cells | Immune suppression |
|
|
|
| [124,125] |
Novel prognostic biomarkers | |||||||
Prokineticin 2 | Various tissues (CNS, gastrointestinal tract, and immune cells). | Regulation of multiple biological processes |
|
|
|
| [131] |
PC | Liver | Anticoagulant, regulates coagulation cascade |
|
|
|
| [20,132,133,134,135] |
6. Biomarkers for Sepsis-Associated Acute Kidney Injury (Sepsis-AKI)
6.1. Inflammatory Biomarkers
6.2. Microcirculatory Disturbance Biomarkers
7. Multi-Biomarker Approach
8. Conclusions
Author Contributions
Funding
Conflicts of Interest
References
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---|---|---|---|
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| [11] |
2 | Biomarkers of sepsis: time for a reappraisal (2020) |
| [15] |
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| [16] |
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| [17] |
5 | Current evidence and limitation of biomarkers for detecting sepsis and systemic infection (2020) |
| [18] |
6 | An update on sepsis biomarkers (2020) |
| [19] |
7 | Biomarkers for sepsis: more than just fever and leukocytosis—a narrative review (2022) |
| [20] |
Biomarker | Source | Response Time | Diagnostic Accuracy | Clinical Significance | Testing Methods | Strengths | Limitations | Refs. |
---|---|---|---|---|---|---|---|---|
Commonly used diagnostic biomarkers | ||||||||
CRP | Liver | Rises within 4–6 h after infection |
|
|
|
|
| [15,22,25,26,27,28,29,30,31,32,33,34] |
PCT | Thyroid C cells | Rises within 2–4 h after infection |
|
|
|
|
| [17,27,35,36,37,38,39,40,41,42,43,44,45] |
IL-6 | Immune and non-immune cells | Peaks within 2 h after infection |
|
|
|
|
| [18,46,47,48] |
HMGB1 | Immune cells (macrophages, monocytes, and neutrophils) | Increases within 4–8 h after infection |
|
|
|
|
| [49,50,51,52,53,54,55,56] |
PSP | Pancreatic acinar cells | Response time is not well-defined, but it rises rapidly after infection |
|
|
|
|
| [57,58,59,60,61,62,63] |
Presepsin | Macrophages and monocyte cells | Rises within 2 h after infection |
|
|
|
|
| [64,65,66,67] |
CD64 | Immune cells (especially neutrophils, monocytes/macrophages) | Upregulated within 6–8 h after infection |
|
|
|
|
| [68,69,70,71,72] |
sTREM-1 | Myeloid cells | Elevates within 2–4 h after infection |
|
|
|
|
| [73,74] |
Novel diagnostic biomarkers | ||||||||
circRNAs | Various tissues and cells, especially cancer cells and neural cells | Response time varies depending on the particular circRNA |
|
|
|
|
| [75,76,77,78,79] |
HOTTIP | Embryonic stem cells and various cancer cells | Response time is not well-defined |
|
|
|
|
| [81,82,83] |
microRNA-486-5p | Various tissues, particularly in skeletal muscles, lung tissues, and various cancer cells | Response time is not well-defined, but changes within several hours after infection |
|
|
|
|
| [84,85,86,87,88,89,90] |
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He, R.-R.; Yue, G.-L.; Dong, M.-L.; Wang, J.-Q.; Cheng, C. Sepsis Biomarkers: Advancements and Clinical Applications—A Narrative Review. Int. J. Mol. Sci. 2024, 25, 9010. https://doi.org/10.3390/ijms25169010
He R-R, Yue G-L, Dong M-L, Wang J-Q, Cheng C. Sepsis Biomarkers: Advancements and Clinical Applications—A Narrative Review. International Journal of Molecular Sciences. 2024; 25(16):9010. https://doi.org/10.3390/ijms25169010
Chicago/Turabian StyleHe, Rong-Rong, Guo-Li Yue, Mei-Ling Dong, Jia-Qi Wang, and Chen Cheng. 2024. "Sepsis Biomarkers: Advancements and Clinical Applications—A Narrative Review" International Journal of Molecular Sciences 25, no. 16: 9010. https://doi.org/10.3390/ijms25169010
APA StyleHe, R.-R., Yue, G.-L., Dong, M.-L., Wang, J.-Q., & Cheng, C. (2024). Sepsis Biomarkers: Advancements and Clinical Applications—A Narrative Review. International Journal of Molecular Sciences, 25(16), 9010. https://doi.org/10.3390/ijms25169010