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In a recent study published in the journal Nature Aging, researchers assessed the added predictive value of integrating polygenic risk scores (PRSs) and gut microbiome scores with conventional risk factors for common diseases in a long-term cohort study.
Analysis: Integration of polygenic and gut metagenomic risk prediction for common diseases. Image Credit: remotevfx.com / Shutterstock.
Background
Multiomic technologies are transforming disease prediction by integrating genomic and microbiomic data, offering new insights into age-related conditions like heart disease, diabetes, and cancer. Previously, risk assessments relied mainly on demographic, lifestyle, and clinical metrics. Now, the integration of PRSs and gut microbiome analysis into risk models promises to improve predictive accuracy beyond traditional factors. PRSs provide a cost-effective genetic predisposition metric, while the gut microbiome adds a novel dimension to understanding disease risk. This emerging approach necessitates further research to refine its accuracy and ensure its effectiveness across various populations and healthcare systems.
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