Fluid biomarkers - New biomarkers

10 important questions on Fluid biomarkers - New biomarkers

What are the 4 must-haves for new biomarkers?

  • Clinically relevant
  • Improve upon gold standard
  • Reproductive = als je het herhaald kun je hetzelfde meten
  • Generalizable = voor veel mensen

What are the 5 phases of biomarker development?

  1. Preclinical + explorative
  2. Clinical assay + validation (still in the lab)
  3. Longitudinal retrospective
  4. Prospective + real world
  5. Implementation

What does OLINK measure?

  • Epitopes (so the parts of the proteins that bind to the antibody) 
  • Quantifies the biomarkers DNA with PCR.
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What does mass spectrometry measure?

  • Peptides
  • Read out = mass-charge ratio (voorbeeld balletjes en fohn

What will be the output of phase 1?

  • Differential expression => how much of one specific protein
  • Classification => which proteins
  • You use this for a network/pathway analysis

Why is OLINK so good? But what must the situation be?

  • Good because it overcomes the translation gap => easier + scalabe assay
  • Good because it is a cleaner technology: you don't cut your proteins

But you need to know what kind of antibodies you are going to use => so you should already have an direction of thoughts --> however you can use 900 antibodies apparently.

So describe the CSF biomarker identification for Alzheimer (4)

  • Measure >900 proteins with OLINK in CSF
  • See which proteins are downregulated and which are upregulated (both can potentially be a target) left or right
  • Then you need to find a translatable classification panel
  • Validate findings to prevent false discoveries

Where do you need to think of when making translatable panels + validation? (4)

  • Prevent algorithm overfitting => means that the model can only predict correctly in the specific sample and not in other samples
  • Internal cross-validation
  • In independent datasets
  • Set it against controls + other diseases

Phase 3 +4. What happens here? What do you need for this? (4)

Clinical validation. You need:
  • Valid lab method
  • Cohort-independent validation. Relevant cohort => well balanced, no selection bias. Well-phenotyped volunteers
  • Gold standard to compare your measurements with
  • Enough samples to create sufficient statistical power

Determining the right cut point is important to get less false negative and less false positive. What is important for this?

  • Good cohort selection
  • That your test has a small fraction of bias + a cut point that is in line with the amount of bias.

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