Ruiz-Serra Victoria, Buslón Nataly, Philippe Olivier R, Saby Diego, Morales María, Pontes Camila, Andirkó Alejandro Muñoz, Holliday Gemma L, Jené Aina, Moldes Mauricio, Rambla Jordi, Valencia Alfonso, Rementeria María José, Cortés Atia, Cirillo Davide
Life Sciences, Barcelona Supercomputing Center (BSC), 08034 Barcelona, Spain.
European Commission, Joint Research Centre (JRC), 2440 Geel, Belgium.
iScience. 2024 Sep 23;27(10):110831. doi: 10.1016/j.isci.2024.110831. eCollection 2024 Oct 18.
Precision medicine aims at tailoring treatments to individual patient's characteristics. In this regard, recognizing the significance of sex and gender becomes indispensable for meeting the distinct healthcare needs of diverse populations. To this end, continuing a trend of improving data quality observed since 2014, the European Genome-phenome Archive (EGA) established a policy in 2018 that mandates data providers to declare the sex of donor samples, aiming to enhance data accuracy and prevent imbalance in sex classification. We analyzed sex classification imbalance in human data from EGA and the U.S. counterpart, the database of genotypes and phenotypes (dbGaP). Our findings show a significant decrease in samples classified as unknown in EGA, potentially promoting better sex reporting during data collection. Based on our findings, we raise awareness of sample imbalance problems and provide a list of recommendations for enhancing biomedical research practices.
精准医学旨在根据个体患者的特征量身定制治疗方案。在这方面，认识到性别和性别的重要性对于满足不同人群独特的医疗保健需求变得不可或缺。为此，欧洲基因组-表型档案库（EGA）延续自2014年以来不断提高数据质量的趋势，于2018年制定了一项政策，要求数据提供者声明供体样本的性别，旨在提高数据准确性并防止性别分类失衡。我们分析了来自EGA和美国同类数据库基因型和 phenotypes（dbGaP）的人类数据中的性别分类失衡情况。我们的研究结果表明，EGA中分类为未知的样本数量显著减少，这可能促进数据收集过程中更好的性别报告。基于我们的研究结果，我们提高了对样本失衡问题的认识，并提供了一系列加强生物医学研究实践的建议清单。
