Rethinking our public health genetics research paradigm

Abstract

Since the sequencing of the human genome, tremendous resources have been dedicated to understanding how genetic determinants may drive the production of disease. Despite some successes, the promise of genetics research in these areas remains largely unrealized. The focus on isolating individual (or clusters of) genes that may be associated with narrowly defined phenotypes in large part explains this discrepancy. In particular, efforts to identify genotypes associated with narrow phenotypes force the field to use study designs that capitalize on homogeneous samples to minimize the potential for competing influences or confounders, which imposes important limitations on understanding the role of genes in human health. We argue that a population health genetics that incorporates genetics into large, multiwave, multilevel cohorts has the best potential to clarify how genes, in combination and with the environment, jointly influence population health.

FIGURE 1—

Epigenetic modification as a mediator between genetic factors and outcomes and associated confounders. Note. t₁ = time 1; t₂ = time 2; t₃ = time 3. Support of epigenetic hypotheses requires measurement at three time points, and third variables that might confound relationships among loci, epigenetic modification, and outcomes should be measured at the second and third time points and adjusted for appropriately in analyses.

FIGURE 2—

Effect modification of the relationship between an environment (genetic factors) and an outcome and associated confounders by a locus of interest. Note. Third variables can predict all three factors, as can occur in selected study samples, and can challenge population-level inference regarding the role of genes as effect modifiers of relationships of interest.