利用可公开获得的数据构建子宫肌瘤的多世系多基因风险评分,凸显了包容性遗传研究的必要性。

Jessica L G Winters, Jacqueline A Piekos, Jacklyn N Hellwege, Ozan Dikilitas, Iftikhar J Kullo, Daniel J Schaid, Todd L Edwards, Digna R Velez Edwards
{"title":"利用可公开获得的数据构建子宫肌瘤的多世系多基因风险评分,凸显了包容性遗传研究的必要性。","authors":"Jessica L G Winters, Jacqueline A Piekos, Jacklyn N Hellwege, Ozan Dikilitas, Iftikhar J Kullo, Daniel J Schaid, Todd L Edwards, Digna R Velez Edwards","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>Uterine leiomyomata, or fibroids, are common gynecological tumors causing pelvic and menstrual symptoms that can negatively affect quality of life and child-bearing desires. As fibroids grow, symptoms can intensify and lead to invasive treatments that are less likely to preserve fertility. Identifying individuals at highest risk for fibroids can aid in access to earlier diagnoses. Polygenic risk scores (PRS) quantify genetic risk to identify those at highest risk for disease. Utilizing the PRS software PRS-CSx and publicly available genome-wide association study (GWAS) summary statistics from FinnGen and Biobank Japan, we constructed a multi-ancestry (META) PRS for fibroids. We validated the META PRS in two cross-ancestry cohorts. In the cross-ancestry Electronic Medical Record and Genomics (eMERGE) Network cohort, the META PRS was significantly associated with fibroid status and exhibited 1.11 greater odds for fibroids per standard deviation increase in PRS (95% confidence interval [CI]: 1.05 - 1.17, p = 5.21x10-5). The META PRS was validated in two BioVU cohorts: one using ICD9/ICD10 codes and one requiring imaging confirmation of fibroid status. In the ICD cohort, a standard deviation increase in the META PRS increased the odds of fibroids by 1.23 (95% CI: 1.15 - 1.32, p = 9.68x10-9), while in the imaging cohort, the odds increased by 1.26 (95% CI: 1.18 - 1.35, p = 2.40x10-11). We subsequently constructed single ancestry PRS for FinnGen (European ancestry [EUR]) and Biobank Japan (East Asian ancestry [EAS]) using PRS-CS and discovered a nominally significant association in the eMERGE cohort within fibroids and EAS PRS but not EUR PRS (95% CI: 1.09 - 1.20, p = 1.64x10-7). These findings highlight the strong predictive power of multi-ancestry PRS over single ancestry PRS. This study underscores the necessity of diverse population inclusion in genetic research to ensure precision medicine benefits all individuals equitably.</p>","PeriodicalId":34954,"journal":{"name":"Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing","volume":"30 ","pages":"268-280"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11731894/pdf/","citationCount":"0","resultStr":"{\"title\":\"Constructing a multi-ancestry polygenic risk score for uterine fibroids using publicly available data highlights need for inclusive genetic research.\",\"authors\":\"Jessica L G Winters, Jacqueline A Piekos, Jacklyn N Hellwege, Ozan Dikilitas, Iftikhar J Kullo, Daniel J Schaid, Todd L Edwards, Digna R Velez Edwards\",\"doi\":\"\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Uterine leiomyomata, or fibroids, are common gynecological tumors causing pelvic and menstrual symptoms that can negatively affect quality of life and child-bearing desires. As fibroids grow, symptoms can intensify and lead to invasive treatments that are less likely to preserve fertility. Identifying individuals at highest risk for fibroids can aid in access to earlier diagnoses. Polygenic risk scores (PRS) quantify genetic risk to identify those at highest risk for disease. Utilizing the PRS software PRS-CSx and publicly available genome-wide association study (GWAS) summary statistics from FinnGen and Biobank Japan, we constructed a multi-ancestry (META) PRS for fibroids. We validated the META PRS in two cross-ancestry cohorts. In the cross-ancestry Electronic Medical Record and Genomics (eMERGE) Network cohort, the META PRS was significantly associated with fibroid status and exhibited 1.11 greater odds for fibroids per standard deviation increase in PRS (95% confidence interval [CI]: 1.05 - 1.17, p = 5.21x10-5). The META PRS was validated in two BioVU cohorts: one using ICD9/ICD10 codes and one requiring imaging confirmation of fibroid status. In the ICD cohort, a standard deviation increase in the META PRS increased the odds of fibroids by 1.23 (95% CI: 1.15 - 1.32, p = 9.68x10-9), while in the imaging cohort, the odds increased by 1.26 (95% CI: 1.18 - 1.35, p = 2.40x10-11). We subsequently constructed single ancestry PRS for FinnGen (European ancestry [EUR]) and Biobank Japan (East Asian ancestry [EAS]) using PRS-CS and discovered a nominally significant association in the eMERGE cohort within fibroids and EAS PRS but not EUR PRS (95% CI: 1.09 - 1.20, p = 1.64x10-7). These findings highlight the strong predictive power of multi-ancestry PRS over single ancestry PRS. This study underscores the necessity of diverse population inclusion in genetic research to ensure precision medicine benefits all individuals equitably.</p>\",\"PeriodicalId\":34954,\"journal\":{\"name\":\"Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing\",\"volume\":\"30 \",\"pages\":\"268-280\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11731894/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Computer Science\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 0

摘要

子宫良性肌瘤或子宫肌瘤是常见的妇科肿瘤,会引起盆腔和月经症状,对生活质量和生育愿望造成负面影响。随着子宫肌瘤的生长,症状可能会加剧,并导致不太可能保留生育能力的侵入性治疗。识别子宫肌瘤的高危人群有助于尽早确诊。多基因风险评分(PRS)对遗传风险进行量化,以确定患病风险最高的人群。利用 PRS 软件 PRS-CSx,以及从 FinnGen 和 Biobank Japan 公开获得的全基因组关联研究(GWAS)汇总统计数据,我们构建了子宫肌瘤的多家系(META)PRS。我们在两个跨种属队列中验证了 META PRS。在跨种属电子病历和基因组学(eMERGE)网络队列中,META PRS 与子宫肌瘤状态显著相关,PRS 每增加一个标准差,子宫肌瘤发生几率增加 1.11(95% 置信区间 [CI]:1.05 - 1.17,p = 5.21x10-5)。META PRS 在 BioVU 的两个队列中进行了验证:一个队列使用 ICD9/ICD10 编码,另一个队列需要通过成像确认子宫肌瘤状态。在 ICD 队列中,META PRS 每增加一个标准差,子宫肌瘤的几率就增加 1.23(95% CI:1.15 - 1.32,p = 9.68x10-9),而在影像队列中,几率增加 1.26(95% CI:1.18 - 1.35,p = 2.40x10-11)。随后,我们使用 PRS-CS 为 FinnGen(欧洲血统 [EUR])和 Biobank Japan(东亚血统 [EAS])构建了单一血统 PRS,发现在 eMERGE 队列中,子宫肌瘤与 EAS PRS 名义上有显著关联,但与 EUR PRS 没有关联(95% CI:1.09 - 1.20,p = 1.64x10-7)。这些发现凸显了多血统 PRS 比单一血统 PRS 更强的预测能力。这项研究强调了将不同人群纳入基因研究的必要性,以确保精准医学公平地惠及所有人。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Constructing a multi-ancestry polygenic risk score for uterine fibroids using publicly available data highlights need for inclusive genetic research.

Uterine leiomyomata, or fibroids, are common gynecological tumors causing pelvic and menstrual symptoms that can negatively affect quality of life and child-bearing desires. As fibroids grow, symptoms can intensify and lead to invasive treatments that are less likely to preserve fertility. Identifying individuals at highest risk for fibroids can aid in access to earlier diagnoses. Polygenic risk scores (PRS) quantify genetic risk to identify those at highest risk for disease. Utilizing the PRS software PRS-CSx and publicly available genome-wide association study (GWAS) summary statistics from FinnGen and Biobank Japan, we constructed a multi-ancestry (META) PRS for fibroids. We validated the META PRS in two cross-ancestry cohorts. In the cross-ancestry Electronic Medical Record and Genomics (eMERGE) Network cohort, the META PRS was significantly associated with fibroid status and exhibited 1.11 greater odds for fibroids per standard deviation increase in PRS (95% confidence interval [CI]: 1.05 - 1.17, p = 5.21x10-5). The META PRS was validated in two BioVU cohorts: one using ICD9/ICD10 codes and one requiring imaging confirmation of fibroid status. In the ICD cohort, a standard deviation increase in the META PRS increased the odds of fibroids by 1.23 (95% CI: 1.15 - 1.32, p = 9.68x10-9), while in the imaging cohort, the odds increased by 1.26 (95% CI: 1.18 - 1.35, p = 2.40x10-11). We subsequently constructed single ancestry PRS for FinnGen (European ancestry [EUR]) and Biobank Japan (East Asian ancestry [EAS]) using PRS-CS and discovered a nominally significant association in the eMERGE cohort within fibroids and EAS PRS but not EUR PRS (95% CI: 1.09 - 1.20, p = 1.64x10-7). These findings highlight the strong predictive power of multi-ancestry PRS over single ancestry PRS. This study underscores the necessity of diverse population inclusion in genetic research to ensure precision medicine benefits all individuals equitably.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
4.50
自引率
0.00%
发文量
0
期刊最新文献
Session Introduction: AI and Machine Learning in Clinical Medicine: Generative and Interactive Systems at the Human-Machine Interface. Session Introduction: Overcoming health disparities in precision medicine: Intersectional approaches in precision medicine. Session Introduction: Precision Medicine: Multi-modal and multi-scale methods to promote mechanistic understanding of disease. Social risk factors and cardiovascular risk in obstructive sleep apnea: a systematic assessment of clinical predictors in community health centers. A Visual Analytics Framework for Assessing Interactive AI for Clinical Decision Support.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1