Using risk-based sampling to enrich cohorts for endpoints, genes, and exposures

Area of Science:

• Epidemiology
• Genetics
• Public Health

Background:

• Complex diseases often have genetic and environmental etiologic factors.
• Identifying these factors requires well-designed prospective studies.
• First-degree relatives of affected individuals represent a high-risk group.

Purpose of the Study:

• To evaluate the utility of risk-based cohorts for studying complex diseases.
• To provide power calculations for designing such studies.
• To quantify the benefits for detecting genetic and environmental risk factors.

Main Methods:

• The study design focuses on recruiting first-degree relatives of individuals with a specific complex disease.
• Power calculations were performed to assess the statistical efficiency of this design.
• The Sister Study, a nationwide breast cancer cohort, serves as an example.

Main Results:

• Risk-based cohorts significantly increase the rate of newly incident case accrual.
• This design enhances the detection of both known and unknown risk factors.
• The primary advantage stems from accelerated case accrual, not solely increased allele prevalence.

Conclusions:

• Recruiting first-degree relatives is an effective strategy for building high-yield prospective study cohorts.
• This approach optimizes the identification of etiologic factors for complex diseases.
• The design is particularly powerful for detecting genetic variants and gene-environment interactions.