Polygenic scores in clinic: prediction requires calibration and context
A high percentile is not an absolute risk, and strong association does not establish that using a score improves care.
Find a starting point, a clinical perspective, or a closer look at the research.
12 articles
A high percentile is not an absolute risk, and strong association does not establish that using a score improves care.
Longer molecules can clarify structural variation and difficult regions, but analytical validation and study design still determine diagnostic value.
Cell atlases reveal biological heterogeneity, but meaningful disease comparisons require sound sampling, batch handling and independent replication.
Assay validation, disease mechanism and clinical calibration determine whether a laboratory observation can strengthen variant classification.
A screen identifies candidates under particular experimental conditions; orthogonal evidence is needed before treating a hit as a disease mechanism or therapeutic target.
A reproducible methylation pattern can support a diagnosis, but classifier coverage and validation determine how much it can resolve.
Association identifies a genomic neighborhood; causal variants, target genes and biological effects require additional evidence.
Reference databases are essential for variant interpretation, but absence, group labels and gene-level constraint each require careful qualification.
A plausible variant cannot compensate for an uncertain relationship between the gene and the proposed disorder.
FAIR principles and responsible governance can support discovery while preserving consent, privacy and accountability.
A one-time administration still requires long-term evidence about effectiveness, late adverse events and who remains represented in follow-up.
Small populations make endpoint selection more demanding, not less; connect measurement quality, natural history and patient relevance.