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Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
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Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation

Published on: January 16, 2019

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Standardized Immunomonitoring: Separating the Signals from the Noise

Darragh Duffy1

  • 1Dendritic Cell Immunobiology Unit, Institut Pasteur, Paris, France; INSERM U1223, Paris, France.

Trends in Biotechnology
|October 23, 2018
PubMed

Insights

New protein assays and standardized immune stimulation methods can improve clinical immune response monitoring. These advances are key for adopting precision medicine strategies in healthcare.

Area of Science:

  • Clinical immunology
  • Biomarker discovery
  • Precision medicine

Background:

  • Classical immunoassays are standard for disease diagnosis and monitoring.
  • Advanced phenotyping technologies can broaden immune response monitoring.
  • Clinical translation of novel immune monitoring tools faces challenges.

Purpose of the Study:

  • To discuss strategies for advancing the clinical adoption of immune-based biomarkers.
  • To highlight methods for improving the reliability and utility of immune response monitoring in clinical settings.

Main Methods:

  • Focus on protein-based assays with digital readouts to minimize nonspecific signals.
  • Describe standardized immune stimulation approaches to reveal disease-specific signatures.
  • Emphasize integrating immune response phenotypes for clinical applications.

Main Results:

  • Digital readouts in protein assays reduce limitations of classical methods.
  • Standardized stimulation enhances detection of disease-specific immune responses.
  • Improved immune phenotyping is crucial for precision medicine.

Conclusions:

  • Protein-based digital assays and standardized immune stimulation are promising for clinical use.
  • These strategies can overcome current limitations in immune monitoring.
  • Integrating immune phenotypes is essential for advancing precision medicine.

Keywords:
biological noisebiomarkersfunctional immune responsesimmunomonitoringprecision medicineproteins

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