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.

抽象的 多基因评分——基因组对生物医学特征风险和恢复力的贡献的总结——是 临床风险评估和个性化医疗的新兴和有前途的方法， 例如性别少数群体，目前无法从通过多基因分数研究获得的见解中受益 因为这些群体尚未被充分纳入或表征于本研究中。 可以通过在招聘过程中纳入并考虑其影响来解决 例如，我们的初步数据显示自杀风险存在显着的分离。 值得注意的是，这些相反的关联仅在性别多样性时才明显。 地位（即顺性别；性别多样化）被建模，强调了解析性别异质性的必要性 这些结果表明性别基因组研究的价值。 少数群体了解先天风险和恢复力的基因组研究的前景。 指定的性别、性别及其相互作用（即性别多样性）取决于严格和 公平地包括和描述指定性别范围内的个人。 目前，生物医学研究依赖于清单或写入性别身份描述符，这些描述符不捕获 维度二元和非二元性别体验的连续性和同时性并导致 统计分析的力度不够，每个性别自我描述类别中的个体都太少。 这使得基因研究中性别及其与指定性别的交叉永久化。 建议通过校准性别自我报告（GSR）并对其进行基因表征来缩小这一差距，这是一种新颖的方法 以及为基因组研究和更广泛的领域获得多维性别的广泛传播的方法 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，并通过建立在我们的基础上，减少这个道德复杂的研究领域的家长式倾向 与有意招募的利益相关者小组（N = 50）建立社区合作伙伴关系，以提供最终结果 接下来，推进性别认同和性别的维度表征。 为了保证基因组研究背景下的多样性，我们将在大样本中验证利益相关者改进的 GSR (N=10,000) 基因型神经典型和神经分化的成年人，丰富了广泛的经验 最后，展示如何指定性别、性别和性别的原理验证。 背景多样性与多基因分数的关联模式，我们将测量关键的健康状况 结果（精神和身体），在一个大的、遗传信息丰富的神经多样性样本中（例如， 自闭症）和广泛的性别多样性，拟议的研究将为性别少数群体提供价值。 寻求更好地了解多基因分数如何专门应用于他们，而不仅仅是顺性别 比例多数。