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首页> 外文期刊>PLoS Medicine >Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study
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Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study

机译:多基因风险分数的发展,以改善裂缝风险的筛查:遗传风险预测研究

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Background Since screening programs identify only a small proportion of the population as eligible for an intervention, genomic prediction of heritable risk factors could decrease the number needing to be screened by removing individuals at low genetic risk. We therefore tested whether a polygenic risk score for heel quantitative ultrasound speed of sound (SOS)—a heritable risk factor for osteoporotic fracture—can identify low-risk individuals who can safely be excluded from a fracture risk screening program. Methods and findings A polygenic risk score for SOS was trained and selected in 2 separate subsets of UK Biobank (comprising 341,449 and 5,335 individuals). The top-performing prediction model was termed “gSOS”, and its utility in fracture risk screening was tested in 5 validation cohorts using the National Osteoporosis Guideline Group clinical guidelines (N = 10,522 eligible participants). All individuals were genome-wide genotyped and had measured fracture risk factors. Across the 5 cohorts, the average age ranged from 57 to 75 years, and 54% of studied individuals were women. The main outcomes were the sensitivity and specificity to correctly identify individuals requiring treatment with and without genetic prescreening. The reference standard was a bone mineral density (BMD)–based Fracture Risk Assessment Tool (FRAX) score. The secondary outcomes were the proportions of the screened population requiring clinical-risk-factor-based FRAX (CRF-FRAX) screening and BMD-based FRAX (BMD-FRAX) screening. gSOS was strongly correlated with measured SOS (r2 = 23.2%, 95% CI 22.7% to 23.7%). Without genetic prescreening, guideline recommendations achieved a sensitivity and specificity for correct treatment assignment of 99.6% and 97.1%, respectively, in the validation cohorts. However, 81% of the population required CRF-FRAX tests, and 37% required BMD-FRAX tests to achieve this accuracy. Using gSOS in prescreening and limiting further assessment to those with a low gSOS resulted in small changes to the sensitivity and specificity (93.4% and 98.5%, respectively), but the proportions of individuals requiring CRF-FRAX tests and BMD-FRAX tests were reduced by 37% and 41%, respectively. Study limitations include a reliance on cohorts of predominantly European ethnicity and use of a proxy of fracture risk. Conclusions Our results suggest that the use of a polygenic risk score in fracture risk screening could decrease the number of individuals requiring screening tests, including BMD measurement, while maintaining a high sensitivity and specificity to identify individuals who should be recommended an intervention.
机译:背景技术由于筛选计划仅识别少量的人口,因为符合涉及干预的条件,可遗传危险因素的基因组预测可以降低​​在低遗传风险下除去个体需要筛选的数量。因此,我们测试了对骨质疏松骨折的脚后跟定量超声速度的多基因风险评分是否 - 骨质疏松骨折的可遗传性危险因素 - 可以识别可以安全地排除在骨折风险筛查计划中的低风险个体。方法和结果在英国Biobank的2个单独的子集中培训和选择SOS的多基因风险评分(包含341,449和5,335人)。最佳的预测模型被称为“GSOS”,其在5次验证队列中使用国家骨质疏松症准则组临床指南测试其在裂缝风险筛选中的实用性(N = 10,522个符合条件的参与者)。所有个体都是基因组宽的基因分型,并测量了骨折危险因素。在5个队列中,平均年龄范围为57至75岁,54%的学习是女性。主要结果是敏感性和特异性,正确识别需要在没有遗传预筛选的情况下进行治疗的个体。参考标准是骨矿物密度(BMD)基础的骨折风险评估工具(FRAX)得分。二次结果是需要临床风险因子的粉迹(CRF-FRAX)筛选和基于BMD的粉体(BMD-FRAX)筛选的比例。 GSO与测量的SOS强烈相关(R2 = 23.2%,95%CI 22.7%至23.7%)。如果没有遗传预算,指南建议在验证队列中分别达到99.6%和97.1%的正确治疗分配的敏感性和特异性。然而,81%的人口需要CRF-FRAX测试,37%所需的BMD-FRAX测试以实现这种准确性。使用GSO在预先生中并限制对具有低GSO的人的进一步评估导致敏感性和特异性的较小变化(分别为93.4%和98.5%),但需要CRF-FRAX测试和BMD-FRAX测试的个体的比例降低了分别为37%和41%。研究限制包括依赖主要欧洲种族的群体和使用裂缝风险的代理。结论我们的研究结果表明,使用骨折风险筛查中的多基因风险评分可降低需要筛查测试的个体数量,包括BMD测量,同时保持高灵敏度和特异性,以确定应建议干预的个人。

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