Analysis of genetic data opens up many opportunities for medical and scientific advances. The use of phenotypic information and polygenic risk scores to analyze genetic data is widespread. Most work on genetic privacy focuses on basic genetic data such as SNP values and specific genotypes. In this paper, we introduce a novel methodology to quantify and prevent privacy risks by focusing on polygenic scores and phenotypic information. Our methodology is based on the tool-supported privacy risk analysis method Privug. We demonstrate the use of Privug to assess privacy risks posed by disclosing a polygenic trait score for bitter taste receptors, encoded by TAS2R38 and TAS2R16, to a person's privacy in regards to their ethnicity. We provide an extensive privacy risks analysis of different programs for genetic data disclosure: taster phenotype, tasting polygenic score, and a polygenic score distorted with noise. Finally, we discuss the privacy/utility trade-offs of the polygenic score.

翻译：遗传数据分析为医学和科学进步提供了许多机会; 广泛使用小类信息和多源风险评分来分析遗传数据; 大多数关于遗传隐私权的工作侧重于基本遗传数据,如SNP值和具体的基因型; 本文介绍了一种新的方法,通过侧重于多源分数和小类信息来量化和预防隐私风险; 我们的方法以工具支持的隐私风险分析方法Privug为基础; 我们展示了利用Privug评估隐私风险的方法,通过披露由TAS2R38和TAS2R16编码的苦味受体多源特征评分来评估个人在族裔方面的隐私; 我们对不同的遗传数据披露方案进行了广泛的隐私风险分析:品尝型、调味多源分数和用噪音扭曲的多源分数; 最后,我们讨论了多源分数的隐私/效用权衡。