Evidence Bytes

Clinical relevance

Alterations in EV concentration, surface markers, and molecular cargo have been studied in Malignancies, Cardiovascular diseases, Neurodegenerative disorders, Renal diseases, Inflammatory conditions

Analytical considerations in laboratory evaluation

Pre-analytical variables significantly influence EV measurements, including Specimen type and collection method, Choice of collection tube, Centrifugation protocols, Storage conditions, Freeze–thaw cycles

EV isolation and enrichment techniques include:

• • • Differential centrifugation

    • Ultracentrifugation

    • Size-exclusion chromatography

    • Affinity-based capture methods

Characterization methods include:

• • • Nanoparticle tracking analysis (NTA)

    • Electron microscopy

    • Flow cytometry

    • Immunoassays

    • Mass spectrometry

EV-associated nucleic acids are analyzed using:

• • • RT-qPCR

    • Digital PCR

    • Next-generation sequencing (NGS)

Clinical application

EV-based liquid biopsy is a key emerging application.

Tumor-derived EVs may enable:

• • • Minimally invasive disease detection

    • Molecular classification of tumors

    • Monitoring of treatment response

    • Assessment of molecular residual disease

Current limitations

EV biomarkers are not yet established as routine clinical diagnostics.

Major challenges include

• • • Biological heterogeneity of EV populations

    • Contamination with lipoproteins and protein aggregates

    • Lack of standardized isolation protocols

    • Absence of universally accepted reference materials

    • Difficulties in analytical normalization

Conclusion

Translation of EV research into clinical assays requires:

• • • Standardization of methodologies

    • Robust analytical validation

    • Demonstration of clinical utility in well-designed studies

References

Welsh JA, et al. MISEV2023: An updated guide to EV research and applications. Journal of Extracellular Vesicles. 2024;13:e12416. 

Greening DW, Xu R, Rai A, et al. Clinical relevance of extracellular vesicles in cancer—therapeutic and diagnostic potential. Nature Reviews Clinical Oncology. 2025;22:924–952.

ARTICLE REVIEW 1

Paquette M, Thanassoulis G, Sherman MH, Blank DW, Baass A. Poor performance of LDL-cholesterol equations versus beta quantification in a very large cohort of patients with dyslipidemia. Clin Chem. 2026;72(7):801-813. doi:10.1093/clinchem/hvag038.  

1. The study evaluated the accuracy of the Modified Sampson equation and five previously published LDL-cholesterol (LDL-C) equations against the β-quantification (BQ) reference method.

2. The objective was to identify which equation most accurately estimates LDL-C across a broad spectrum of lipid disorders to improve clinical decision-making.

3. A large retrospective dataset comprising 32,533 LDL-C measurements from 13,746 patients attending a lipid clinic was analyzed.

4. The cohort included patients with various dyslipidemias, including familial hypercholesterolemia, familial chylomicronemia syndrome, and dysbetalipoproteinemia.

5. The reference LDL-C values were obtained using the NIH-standardized β-quantification method after overnight fasting.

6. Despite the availability of newer LDL-C equations, the Friedewald equation remains appropriate for routine clinical use when TG <400 mg/dL. However, when TG >400 mg/dL, no calculation formula is sufficiently accurate, and direct or reference LDL-C measurement is recommended. In this study, the Friedewald equation performed comparably to the newer LDL-C equations for triglycerides <400 mg/dL, while all equations performed poorly when triglycerides exceeded 400 mg/dL. 

7. For years, newer equations such as Martin–Hopkins and Sampson have been promoted as more accurate, especially in patients with low LDL-C or higher triglycerides. This study challenges that assumption by showing that, in a very large cohort using β-quantification as the reference, these newer equations did not provide a meaningful advantage over Friedewald.  

Martin SS, Blaha MJ, Elshazly MB, Toth PP, Kwiterovich PO, Blumenthal RS, et al. Comparison of a novel method vs the Friedewald equation for estimating low-density lipoprotein cholesterol levels from the standard lipid profile. JAMA. 2013;310(19):2061-2068.  

Sampson M, Ling C, Sun Q, Harb R, Ashmaig M, Warnick R, et al. A new equation for calculation of low-density lipoprotein cholesterol in patients with normolipidemia and/or hypertriglyceridemia. JAMA Cardiol. 2020;5(5):540-548. 

Martin SS, et al. Extensive evidence supports the Martin–Hopkins equation as the LDL-C calculation of choice. Clin Chem. 2024;70(2):392-395.