Fibrosis Biomarkers: KL-6, SP-D, and ELF Score Guide

Fibrosis Biomarkers: A Practical Guide to Diagnosis, Prognosis, and Treatment Monitoring

Introduction: Why are Biomarkers Important?

Diagnosis of fibrosis has long relied on invasive "Tissue Biopsy." However, biopsy carries risks such as bleeding, infection, and sampling error (needle missing the lesion), and imposes a heavy burden on patients, creating a desperate need for the development of Non-invasive Biomarkers. Biomarkers are extremely important in clinical trials and drug discovery research because they can be used not only for diagnosis but also for assessing disease severity, predicting prognosis, and monitoring treatment effects. This article explains major organ-specific biomarkers and their clinical significance.

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1. Pulmonary Fibrosis Biomarkers

KL-6 (Krebs von den Lungen-6)

Characteristics and Origin

• High molecular weight glycoprotein, mainly produced by alveolar type II epithelial cells.
• Expression increases during lung epithelial injury/repair, leaking into serum.

Diagnostic Value

• Serum KL-6 is significantly higher in IPF patients compared to other ILDs and healthy individuals (Frontiers in Medicine).
• Meta-analyses show high sensitivity and specificity in IPF diagnosis.

Severity and Prognostic Assessment

• Correlation with Severity: High KL-6 is associated with more advanced ILD. It is about 700 U/ml higher in severe ILD patients than in mild cases.
• Prediction of Acute Exacerbation: KL-6 rises by about 545 U/ml during acute exacerbation.
• Mortality Risk: High KL-6 is associated with a 2.05-fold increased mortality risk (HR=2.05, 95% CI: 1.50–2.78).
• Cut-off Value: In systemic sclerosis-associated ILD, KL-6 > 1273 U/ml is a strong predictor of end-stage lung disease.

Limitations

• While lung specificity is high, it can also rise in other lung diseases (pneumonia, lung cancer).

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SP-D (Surfactant Protein-D)

Characteristics and Origin

• Protein of the Collectin family, produced by alveolar type II epithelial cells and Clara cells.
• A component of surfactant with immunomodulatory effects.

Diagnostic Value

• Serum SP-D is significantly higher in IPF patients than in healthy individuals.
• High SP-D in bronchoalveolar lavage (BAL) fluid correlates with the severity of lung injury.

Prognostic Assessment

• High SP-D strongly correlates with reduced survival rate in IPF patients (111% increase in mortality risk).
• Decrease in SP-D during anti-fibrotic treatment (Pirfenidone) may indicate therapeutic efficacy. For a broader perspective, see our overview of the IPF treatment landscape and the clinical positioning of approved therapies.

Combination of KL-6 and SP-D

• KL-6: Reflects fibrosis + inflammation.
• SP-D: Mainly reflects inflammation.
• The product of both (KL-6 × SP-D) correlates strongly with lung function, enabling more comprehensive evaluation.

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2. Liver Fibrosis Biomarkers

Hyaluronic Acid (HA)

Characteristics and Origin

• High molecular weight polysaccharide, produced by hepatic stellate cells and degraded by sinusoidal endothelial cells.
• Production increases or degradation decreases due to inflammation/fibrosis.

Diagnostic Performance

• Excellent for detecting advanced fibrosis/cirrhosis:
  • Chronic Hepatitis C (CHC): AUC 0.85–0.90 for cirrhosis diagnosis.
  • Alcoholic Liver Disease (ALD): AUC 0.93 for cirrhosis diagnosis.
  • Chronic Hepatitis B (CHB): Detects advanced fibrosis with 90.9% sensitivity and 98.1% specificity at a cut-off of 126.4 ng/ml.

Limitations

• Difficult to differentiate early fibrosis (F0-F2): Useful for differentiating F2/F3, but limited for F1/F2.
• Does not completely replace biopsy; combination with algorithmic models is recommended.

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PIIINP (Procollagen Type III N-terminal Peptide)

Characteristics and Origin

• Precursor peptide of Type III Collagen, a direct marker of ECM synthesis. Tissue collagen content is commonly quantified in parallel using the hydroxyproline assay, a well-established surrogate for total collagen.
• Increases in serum during enhanced collagen synthesis/degradation.

Diagnostic Performance

• NPV 0.95, PPV 1.00 (at specific cut-off values) for diagnosis of advanced fibrosis.
• Elevated in NAFLD and chronic liver diseases in general.

Limitations

• Low liver specificity (also produced in bone, cartilage, etc.), limiting accuracy when used alone (Sensitivity 78%, Specificity 81%).

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ELF Score (Enhanced Liver Fibrosis Score)

Composition

• Composite score of HA + PIIINP + TIMP-1 (Tissue Inhibitor of Metalloproteinase-1).
• Evaluates both ECM production and degradation.

Diagnostic Performance

• Superior to other non-invasive scores like APRI or FIB-4 in detecting advanced fibrosis.
• Promising as a strategy to reduce liver biopsies.

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3. Other Organ-Specific Biomarkers

Renal Fibrosis

• Serum Creatinine, eGFR: Reflect renal function decline but are not direct indicators of fibrosis.
• Urinary Biomarkers: TGF-β1, MCP-1, KIM-1 (Kidney Injury Molecule-1) are under research. Trials targeting CKD and renal fibrosis increasingly incorporate these urinary markers as exploratory endpoints.

Myocardial Fibrosis

• Galectin-3: Prognostic marker for myocardial fibrosis and heart failure.
• ST2 (Suppression of Tumorigenicity 2): Marker of myocardial remodeling.

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4. Imaging Biomarkers

Elastography (FibroScan)

• Liver Stiffness Measurement: Quantifies liver stiffness using ultrasound. Correlates with fibrosis progression.
• Advantages: Non-invasive, real-time assessment.
• Limitations: Reduced accuracy in obesity or ascites.

CT/MRI

• Evaluates morphological changes (liver surface irregularity, splenomegaly, etc.).
• Quantitative evaluation is limited and requires expert interpretation.

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5. Challenges and Prospects in Biomarker Development

Current Limitations

1. Insufficient Accuracy for Early Fibrosis: Many biomarkers are accurate for advanced stages (F3-F4) but limited for early stages (F0-F2).
2. Difficulty in Assessing Treatment Efficacy: Lack of dynamic biomarkers capable of detecting "Regression" of fibrosis.
3. Lack of Organ Specificity: Markers produced in multiple organs, like PIIINP, have low specificity.

Next-Generation Biomarkers

• Omics Technologies: "Fingerprint" analysis using proteomics, metabolomics, and transcriptomics.
• ECM Turnover Markers: Individually measuring synthesis (formation) and degradation to assess balance.
• Circulating miRNA: Potential for blood microRNAs to show fibrosis-specific profiles.

Utilization in Clinical Trials

• Movement to incorporate serum biomarker changes into "Go/No-Go decisions" in Phase II trials.
• Increasing number of trials using biomarker changes as secondary endpoints in addition to FVC and tissue biopsy.

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Conclusion

Fibrosis biomarkers are important tools that reduce invasive biopsies and enable more frequent monitoring. However, single markers have limitations, and combinations of multiple markers or integration with imaging diagnosis are recommended. Our fibrosis models allow for simultaneous measurement of these serum biomarkers in addition to tissue evaluation, enabling multilateral evaluation of candidate drug efficacy and enhancing clinical predictability.

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References

1. Bonella F, et al. Serum KL-6 and SP-D in interstitial lung diseases. Front Med (Lausanne). 2021;8:745704.
2. Calvaruso V, et al. Hyaluronic acid for non-invasive diagnosis of liver fibrosis. World J Hepatol. 2015;7(22):2484-2491.
3. Guha IN, et al. Noninvasive markers of fibrosis in nonalcoholic fatty liver disease: validating the ELF test. Hepatology. 2008;47(2):455-460.