Conducting inclusive research in genetics for transgender, gender-diverse, and sex-diverse individuals: Case analyses and recommendations from a clinical genomics study.
Conducting inclusive research in genetics for transgender, gender-diverse, and sex-diverse individuals: Case analyses and recommendations from a clinical genomics study.
复制标题
对跨性别、性别多样化和性别多样化个体进行遗传学包容性研究：临床基因组学研究的案例分析和建议。
DOI：
10.1002/jgc4.1785
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发表时间：
2023
影响因子：
1.9
通讯作者：
Rosenbloom
中科院分区：
文献类型：
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作者：
Bland,HarrisT;Gilmore,MarianJ;Andujar,Justin;Martin,MakennaA;Celaya-Cobbs,Natasha;Edwards,Clasherrol;Gerhart,Meredith;Hooker,GillianW;Kraft,StephanieA;Marshall,DanaR;Orlando,LoriA;Paul,NatalieA;Pratap,Siddharth;Rosenbloom
一个人的表型性别（即，原发性、继发性和内分泌性特征的内源性表达）可以影响遗传评估的关键方面和由此产生的临床护理建议。在具有遗传学成分的研究中，收集表型性别、关于当前器官/组织库存和激素环境的信息以及性别认同至关重要。如果研究人员不仔细构建数据模型，跨性别，性别多样性和性别多样性（TGSD）的个人可能会被给予不适当的护理建议和/或遭受性别错误，造成医疗和心理社会伤害。对包容性护理体验的认可需求不应仅限于临床实践，而应扩展到研究环境，研究人员必须为TGSD参与者建立包容性体验。在这里，我们回顾了家族史和癌症风险研究（FOREST）中的三名TGSD参与者，以批判性地评估一项旨在识别遗传性癌症综合征风险患者的研究中的性别和性别相关调查措施和相关数据模型。此外，我们利用这些参与者对FOREST中与性别和性别认同相关的问题的回答，为FOREST数据模型提供所需的更改，并为包含TGSD的遗传学研究设计、数据模型和流程提出建议。
A person's phenotypic sex (i.e., endogenous expression of primary, secondary, and endocrinological sex characteristics) can impact crucial aspects of genetic assessment and resulting clinical care recommendations. In studies with genetics components, it is critical to collect phenotypic sex, information about current organ/tissue inventory and hormonal milieu, and gender identity. If researchers do not carefully construct data models, transgender, gender diverse, and sex diverse (TGSD) individuals may be given inappropriate care recommendations and/or be subjected to misgendering, inflicting medical and psychosocial harms. The recognized need for an inclusive care experience should not be limited to clinical practice but should extend to the research setting, where researchers must build an inclusive experience for TGSD participants. Here, we review three TGSD participants in the Family History and Cancer Risk Study (FOREST) to critically evaluate sex‐ and gender‐related survey measures and associated data models in a study seeking to identify patients at risk for hereditary cancer syndromes. Furthermore, we leverage these participants' responses to sex‐ and gender identity‐related questions in FOREST to inform needed changes to the FOREST data model and to make recommendations for TGSD‐inclusive genetics research design, data models, and processes.