Biomarker Discovery
Genetic analysis enables the identification of biomarkers that are not merely associated with disease but causally related — making them far more likely to function as predictive or surrogate endpoints in clinical trials.
We combine MR, polygenic scores, and omics integration to discover and validate biomarkers with actionable clinical utility.
- Causal biomarker identification using bidirectional MR
- Polygenic score construction and clinical stratification analysis
- Multi-omic biomarker panels integrating genomics, proteomics, and metabolomics
- Surrogate endpoint validation using genetic approaches
- Biomarker-disease causal inference for trial design support
Biomarker Validation Pipeline
01.
Candidate Identification
Screen omics datasets for heritable traits with strong GWAS instruments
02.
Causal Validation
Bidirectional MR to establish direction of causality between biomarker and outcome
03.
Polygenic Score Construction
Build and validate polygenic scores for patient stratification in prospective cohorts
04.
Clinical Utility Assessment
Evaluate biomarker performance as risk predictor, diagnostic marker, or trial endpoint
