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Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Rare genetic variants and treatment response: sample size and analysis issues
1Department of Epidemiology and Biostatistics, Institute for Human Genetics, University of California, San Francisco, CA 94143, U.S.A. jwitte@ucsf.edu
Statistics in Medicine
|June 28, 2012
Summary
Genetic information can optimize clinical trials by identifying nonresponders, reducing sample size. New methods efficiently analyze rare genetic variants to understand treatment response, improving trial design and genomic insights.
Area of Science:
- Pharmacogenomics
- Clinical Trial Design
- Genomic Analysis
Background:
- Genetic variants influence individual responses to medical treatments.
- Genome-wide association studies reveal genetic associations with treatment response.
- Advancements in sequencing technology provide extensive genetic data, including rare variants.
Purpose of the Study:
- To explore the utility of genetic information in improving clinical trial design and analysis.
- To investigate methods for analyzing rare genetic variants in relation to treatment response.
- To develop an effective approach for aggregating and analyzing sparse rare variant data.
Main Methods:
- Utilizing genome-wide association study findings to highlight genetic associations.
- Evaluating the impact of rare variants on treatment response.
- Developing and applying an empirical approach for aggregating and analyzing rare variants.
Main Results:
- Genetic associations with treatment response are typically larger than those for common diseases.
- Analyzing rare variants individually requires very large sample sizes.
- Combining rare variants reduces sample size requirements but necessitates assumptions about variant effects.
Conclusions:
- Incorporating genetic data, including rare variants, can enhance clinical trial efficiency and power.
- A novel empirical approach effectively analyzes aggregated rare variants, minimizing assumptions.
- These analyses offer a pathway to a deeper understanding of the genomic underpinnings of treatment response.
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