Informing Prevention and Intervention Policy Using Genetic Studies of Resistance.
- Authors
- Maher, Brion S; Latendresse, Shawn; Vanyukov, Michael M
- Year
- 2018
- Journal
- Prevention science : the official journal of the Society for Prevention Research
- PMID
- 27943075
- DOI
- 10.1007/s11121-016-0730-8
- PMCID
- PMC5466512
The common paradigm for conceptualizing the influence of genetic and environmental factors on a particular disease relies on the concept of risk. Consequently, the bulk of etiologic, including genetic, work focuses on "risk" factors. These factors are aggregated at the high end of the distribution of liability to disease, the latent variable underlying the distribution of probability and severity of a disorder. However, liability has a symmetric but distinct aspect to risk, resistance to disorder. Resistance factors, aggregated at the low end of the liability distribution and supporting health and recovery, appear to be more promising for effective prevention and intervention. Herein, we discuss existing work on resistance factors, highlighting those with known genetic influences. We examine the utility of incorporating resistance genetics in prevention and intervention trials and compare the statistical power of a series of ascertainment schemes to develop a general framework for examining resistance outcomes in genetically informative designs. We find that an approach that samples individuals discordant on measured liability, a low-risk design, is the most feasible design and yields power equivalent to or higher than commonly used designs for detecting resistance genetic and environmental effects.
Liability, Risk and Resistance
LLM interpretation
This diagram illustrates the concept of liability, risk, and resistance using a normal distribution curve. The x-axis represents "Liability" on a scale from 0 to 1, with a "Threshold" marking the boundary where individuals become "affected (cases)" (shaded blue). The area to the far left is labeled "highly resistant (target)" (shaded green), while the central area represents "unaffected (controls)."
Ascertainment Schemes for Resistance Studies
LLM interpretation
This figure consists of six diagrams (a-f) illustrating different ascertainment schemes for resistance studies: Case-Control, Random, Low Risk, High Risk, Low Environmental Risk, and Extreme Environmental Risk. Each panel pairs a pedigree chart—using symbols for unaffected (white), affected (black), and unknown (grey) individuals—with a corresponding distribution curve showing the selection criteria. Arrows indicate which individuals from the pedigrees are sampled to form the distribution shown above them.
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In this knowledge base
| Title | Year | PMID |
|---|---|---|
| Commentary for Special Issue of Prevention Science "Using Genetics in Prevention: Science Fiction or Science Fact?". | 2018 | 28735446 |
External
| Title | Authors | Journal | Year | Link |
|---|---|---|---|---|
| Personal Genetic Information about HIV: Research Participants' Views of Ethical, Social, and Behavioral Implications. | Boyce A et al. | — | 2019 | → |
| Commentary for Special Issue of Prevention Science "Using Genetics in Prevention: Science Fiction or Science Fact?" | Dick DM | — | 2018 | → |
| The Implications of Genetics for Prevention and Intervention Programming. | Musci RJ et al. | — | 2018 | → |