这篇研究文章探讨了基于电子健康记录（EHR）的表型风险评分（PheRS）与多基因评分（PGS）在预测疾病发病风险方面的可推广性和准确性。研究人员利用芬兰（FinnGen）、英国（UKB）和爱沙尼亚（EstB）三个生物样本库的超过八十万个体数据，构建并比较了预测 13 种常见疾病发病风险的模型。关键发现表明，PheRS 模型在不同医疗系统之间具有良好的通用性，并且与 PGS 捕获了大致独立的信息，将两者结合使用可以提高疾病风险预测的准确性。文章讨论了 EHR 数据作为预测工具的优势和挑战，特别是其与遗传数据相结合以改善疾病早期干预的潜力。References: Detrois K E, Hartonen T, Teder-Laving M, et al. Cross-biobank generalizability and accuracy of electronic health record-based predictors compared to polygenic scores[J]. Nature Genetics, 2025: 1-10.
No persons identified in this episode.
This episode hasn't been transcribed yet
Help us prioritize this episode for transcription by upvoting it.
Popular episodes get transcribed faster
Other recent transcribed episodes
Transcribed and ready to explore now
Trump $82 Million Bond Spree, Brazil Tariffs 'Too High,' More
16 Nov 2025
Bloomberg News Now
Ex-Fed Gov Resigned After Rules Violations, Trump Buys $82 Mil of Bonds, More
16 Nov 2025
Bloomberg News Now
THIS TRUMP INTERVIEW WAS INSANE!
16 Nov 2025
HasanAbi
Epstein Emails and Trump's Alleged Involvement
15 Nov 2025
Conspiracy Theories Exploring The Unseen
New Epstein Emails Directly Implicate Trump - H3 Show #211
15 Nov 2025
H3 Podcast
Trump Humiliates Himself on FOX as They Call Him Out
15 Nov 2025
IHIP News