Concepts de base
Using HFS improves genetic association studies by enhancing biological interpretation and polygenic prediction of complex traits.
Résumé
The content introduces a new framework for genetic association studies using the Haplotype Function Score (HFS). It replaces genotypes with functional genomic activity scores, leading to improved insights into complex traits. The study identified causal associations, enriched pathway-trait associations, and enhanced cross-ancestry polygenic prediction. Key highlights include:
- Introduction of the HFS framework for genetic association studies.
- Identification of independent HFS-trait associations and causal loci.
- Enrichment analysis revealing pathway-trait associations and tissue-trait associations.
- Fine-mapping based on HFS showing increased causal signals compared to SNP-based methods.
- Biological interpretation based on HFS fine-mapping results.
- Highlighted genes for complex traits through enhanced fine-mapping and biological enrichment.
- Improved polygenic prediction accuracy using HFS-based PRS.
Stats
Applying the HFS framework led to 3,619 independent HFS-trait associations with a significance of p<5×10−8.
Fine-mapping revealed 2,699 causal associations, with a median increase of 63 causal findings per trait compared to SNP-based analysis.
The genomic control inflation factor (λGC) for the HFS association test varied between 0.99 for asthma and 1.50 for height.
Citations
"We concluded that HFS is a promising strategy for understanding the genetic basis of human complex traits."