A novel approach for equitable characterization of gender and its use in exposing subgroup discrepancies in polygenic score associations

一种公平描述性别的新方法及其在揭示多基因评分关联中亚组差异中的应用

• 批准号: 10710044
• 负责人: Jacob James Michaelson
• 金额: $ 54.87万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-09-26 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10710044
• 关键词: Address; Adult; Biomedical Research; Calibration; Categories; Communities; Complex; Data; Descriptor; Dimensions; Disease; Disparity; Dissociation; Equity; Ethics; Exclusion; Female; Gender; Gender Identity; Genetic; Genetic Research; Genetic Risk; Genomics; Genotype; Health; Heterogeneity; Hip region structure; Individual; Ions; Measures; Medical; Mental Health; Methods; Minority Groups; Modeling; Nature; Outcome; Patient Self-Report; Pattern; Persons; Psyche structure; Questionnaires; Research; Risk; Risk Assessment; Sampling; Scientist; Subgroup; Writing; autism spectrum disorder; cisgender; clinical risk; community partnership; experience; gender diversity; gender minority; gender minority group; insight; male; nonbinary; novel; novel strategies; personalized medicine; potassium cyanate; recruit; resilience; sex; suicidal risk; trait

ABSTRACT Polygenic scores — summaries of the genomic contribution to risk and resilience for biomedical traits — are an emerging and promising approach for clinical risk assessment and personalized medicine. Minoritized groups, such as gender minorities, do not currently benefit from insights gained via studies of polygenic scores because these groups have not been sufficiently included or characterized in this research. This disparity must be addressed both by inclusion during recruitment as well as consideration of the effects of heterogeneity during analysis. For example, our preliminary data show striking dissociations in suicide risk as influenced by polygenic scores. Notably, these opposing associations are apparent only when gender diversity status (i.e., cisgender; gender-diverse) is modeled, underscoring the imperative to parsing the heterogeneity of such associations by both sex and gender. These results suggest value in genomic research for gender minority groups to understand both innate risk and resilience. The promise of genomic research informed by designated sex, gender, and their interaction (i.e., gender diversity) depends on the ability to rigorously and equitably include and characterize individuals across the spectra of designated sex and gender. Currently, biomedical research relies on checklist or write-in gender identity descriptors, which do not capture the continuous and simultaneous nature of dimensional binary and nonbinary gender experiences and result in statistically underpowered analytics with far too few individuals within each gender self-descriptor category. This perpetuates the exclusion of gender and its intersection with designated sex in genetic research. We propose to close this gap by calibrating and genetically characterizing the Gender Self-Report (GSR), a novel and broadly disseminable method for obtaining multidimensional gender for genomic research and broader research applications. First, we will facilitate partnership between scientists and gender diverse community stakeholders, and reduce paternalistic tendencies in this ethically complex field of research, by building on our established community partnerships with a purposively recruited stakeholder panel (N=50) to provide a final version of the GSR itemset. Next, to advance the dimensional characterization of gender identity and gender diversity in a genomic research context, we will validate the stakeholder-refined GSR in a large sample (N=10,000) of genotyped neurotypical and neurodivergent adults, enriched across broad experiences of gender diversity. Finally, to demonstrate proof-of-principle for how designated sex, gender, and gender diversity contextualize patterns of association with polygenic scores, we will measure key health outcomes (both mental and physical), in a large, genetically informed sample enriched for neurodiversity (e.g., autism) and broad gender diversity. The proposed research will provide value to gender minority groups by seeking a better understanding of how polygenic scores apply specifically to them, and not just the cisgender proportional majority.

摘要 多基因评分--基因组对生物医学特征风险和弹性贡献的汇总--是一种 临床风险评估和个性化医疗的新兴和有前途的方法。小规模的团体， 例如性别少数群体，目前没有从多基因得分研究中获得的洞察力中受益 因为这些群体在这项研究中没有得到充分的纳入或表征。这一差距必须 应通过在征聘过程中纳入以及考虑到 分析过程中的异质性。例如，我们的初步数据显示，自杀风险与 受多基因得分的影响。值得注意的是，只有当性别多样性时，这些对立的联系才明显 身份(即，顺性；性别多样性)是模型化的，强调了分析 这种联系既有性别又有性别。这些结果表明性别在基因组研究中的价值。 少数群体了解天生的风险和韧性。基因组研究的前景由 指定的性别、性别及其互动(即性别多样性)取决于严格和 公平地包括和描述指定性别和性别范围内的个人。 目前，生物医学研究依赖于检查表或写入的性别身份描述符，这些描述符不包括 维度二元和非二元性别体验和结果的连续和同时的性质 统计上的分析能力不足，每个性别自我描述类别中的个人太少。 这使基因研究中的性别排除及其与指定性别的交集永久化。我们 建议通过对性别自我报告(GSR)进行校正和基因特征来缩小这一差距，这是一种新的 以及广泛传播的用于基因组研究和更广泛的获得多维性别的方法 研究应用。首先，我们将促进科学家和性别多元化社区之间的伙伴关系 利益相关者，并减少这个伦理复杂的研究领域中的家长式倾向，通过建立在我们的 与专门招募的利益相关者小组(N=50)建立社区合作伙伴关系，以提供最终的 GSR项目集的版本。接下来，推进性别认同和性别的维度表征 在基因组研究背景下，我们将在大样本中验证利益相关者改进的GSR (n=10,000)分型的神经典型和神经分化的成年人，丰富了 性别多样性。最后，演示如何指定性别、性别和性别的原则证明 多样性将关联模式与多基因得分联系起来，我们将衡量关键的健康状况 结果(精神和身体)，在大量的遗传信息样本中，丰富了神经多样性(例如， 自闭症)和广泛的性别多样性。拟议的研究将通过以下方式为性别少数群体提供价值 寻求更好地了解多基因评分如何特别适用于他们，而不仅仅是顺性 比例多数。