Genomic Insights for Personalized Care: Motivating At-Risk Individuals Toward Evidence-Based Health Practices.
Tony ChenGiang PhamLouis FoxNina AdlerXiaoyu WangJingning ZhangJinyoung ByunYounghun HanGretchen R B SaundersDajiang LiuMichael J BrayAlex T RamseyJames McKayLaura BierutChristopher Ian AmosRayjean J HungXihong LinHaoyu ZhangLi-Shiun ChenPublished in: medRxiv : the preprint server for health sciences (2024)
Our PRS-based intervention model leverages large-scale genetic data for robust risk assessment across populations. This model will be evaluated in two cluster-randomized clinical trials aimed at motivating health behavior changes in high-risk patients of diverse ancestry. This pioneering approach integrates genomic insights into primary care, promising improved outcomes in cancer prevention and tobacco treatment.
Keyphrases
- healthcare
- primary care
- risk assessment
- public health
- end stage renal disease
- copy number
- human health
- mental health
- chronic kidney disease
- randomized controlled trial
- newly diagnosed
- ejection fraction
- health information
- prognostic factors
- genome wide
- machine learning
- dna methylation
- type diabetes
- clinical trial
- quality improvement
- adipose tissue
- patient reported outcomes
- social media
- genetic diversity
- artificial intelligence
- deep learning