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?
- Preclinical + explorative
- Clinical assay + validation (still in the lab)
- Longitudinal retrospective
- Prospective + real world
- 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)
- 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.
The question on the page originate from the summary of the following study material:
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