Summarizing polygenic risks for complex diseases in a clinical whole-genome report

Area of Science:

• Genomics
• Clinical Genetics
• Statistical Genetics

Background:

• Whole-genome sequencing is crucial for identifying disease-causing mutations and pharmacogenomic variants.
• Estimating genetic liability for complex diseases using risk alleles may offer future clinical benefits.

Purpose of the Study:

• To compare polygenic scoring methods for estimating genetic liability in complex diseases.
• To assess the clinical utility of summarizing complex trait risk variants for clinicians.

Main Methods:

• Utilized a case-control dataset from the MedSeq Project with independently discovered risk alleles.
• Estimated multiplicative polygenic risk scores for eight clinical traits using 161 published risk alleles.
• Normalized polygenic risk scores using the 1000 Genomes Project population median.

Main Results:

• The polygenic score approach successfully identified an overrepresentation of risk alleles in cases versus controls.
• Normalized polygenic risk scores and population rank provide context for interpreting multilocus disease risk models.
• Disease prevalence and heritability explained by common variants are key for contextualizing risk models.

Conclusions:

• The MedSeq Project demonstrates a method for summarizing complex trait risk variants from individual genomes for clinicians.
• Definitive clinical studies are necessary to establish reference data and clinical utility for polygenic risk scores.
• Further research is needed to validate and implement polygenic risk scores in clinical practice.