Improved prediction of fracture risk leveraging a genome-wide polygenic risk score.
Improved prediction of fracture risk leveraging a genome-wide polygenic risk score.
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利用全基因组多基因风险评分的破裂风险的预测改进。
DOI：
10.1186/s13073-021-00838-6
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发表时间：
2021-02-03
期刊：
影响因子：
12.3
通讯作者：
Richards JB
中科院分区：
文献类型：
--
作者：
Lu T;Forgetta V;Keller-Baruch J;Nethander M;Bennett D;Forest M;Bhatnagar S;Walters RG;Lin K;Chen Z;Li L;Karlsson M;Mellström D;Orwoll E;McCloskey EV;Kanis JA;Leslie WD;Clarke RJ;Ohlsson C;Greenwood CMT;Richards JB
准确地量化腰椎骨折的风险对于指导适当的临床干预是重要的。虽然骨骼测量，如足跟定量声速（SOS）和双能X射线骨密度吸收法能够预测骨质疏松性骨折的风险，但这些测量的实用性取决于设备和人力资源的可用性。使用来自341，449名英国白色血统个体的数据，我们先前开发了一种全基因组多基因风险评分（PRS），称为gSOS，捕获SOS总方差的25.0%。在这里，我们测试gSOS是否可以改善骨折风险预测。我们在五个全基因组基因分型队列中检查了gSOS的预测能力，包括90，172名欧洲血统的个体和25，034名亚洲血统的个体。我们计算了每个人的gSOS，并检验了gSOS与重大腰椎骨折和髋部骨折之间的相关性。我们测试了将gSOS添加到风险预测模型中是否比使用其他常用临床风险因素的模型增加了价值。在欧洲血统的人群中，gSOS标准差的降低与重大腰椎骨折事件的几率增加相关，四个队列的比值比范围为1.35至1.46。在亚洲人群中，它还与1.26倍（95%置信区间（CI）1.13-1.41）的重大腰椎骨折事件发生几率增加相关。我们证明gSOS更能预测重大腰椎骨折的发生（受试者工作特征曲线下面积（AUROC）= 0.734; 95% CI 0.727-0.740）和发生髋部骨折（AUROC = 0.798; 95%CI 0.791-0.805），而不是大多数传统的临床风险因素，包括既往骨折、使用皮质类固醇、类风湿性关节炎和吸烟。我们还表明，将gSOS添加到骨折风险评估工具（FRAX）中可以改进风险预测，其净重新分类指数范围为0.024至0.072。我们生成并验证了与骨折风险相关的SOS PRS。与许多临床风险因素相比，该评分与骨折风险的相关性更强，并提供了风险预测的改善。应探索gSOS作为一种工具，以改善风险分层，识别骨折高危人群。在线版本包含补充材料，可通过10.1186/s13073-021-00838-6获得。
Accurately quantifying the risk of osteoporotic fracture is important for directing appropriate clinical interventions. While skeletal measures such as heel quantitative speed of sound (SOS) and dual-energy X-ray absorptiometry bone mineral density are able to predict the risk of osteoporotic fracture, the utility of such measurements is subject to the availability of equipment and human resources. Using data from 341,449 individuals of white British ancestry, we previously developed a genome-wide polygenic risk score (PRS), called gSOS, that captured 25.0% of the total variance in SOS. Here, we test whether gSOS can improve fracture risk prediction. We examined the predictive power of gSOS in five genome-wide genotyped cohorts, including 90,172 individuals of European ancestry and 25,034 individuals of Asian ancestry. We calculated gSOS for each individual and tested for the association between gSOS and incident major osteoporotic fracture and hip fracture. We tested whether adding gSOS to the risk prediction models had added value over models using other commonly used clinical risk factors. A standard deviation decrease in gSOS was associated with an increased odds of incident major osteoporotic fracture in populations of European ancestry, with odds ratios ranging from 1.35 to 1.46 in four cohorts. It was also associated with a 1.26-fold (95% confidence interval (CI) 1.13–1.41) increased odds of incident major osteoporotic fracture in the Asian population. We demonstrated that gSOS was more predictive of incident major osteoporotic fracture (area under the receiver operating characteristic curve (AUROC) = 0.734; 95% CI 0.727–0.740) and incident hip fracture (AUROC = 0.798; 95% CI 0.791–0.805) than most traditional clinical risk factors, including prior fracture, use of corticosteroids, rheumatoid arthritis, and smoking. We also showed that adding gSOS to the Fracture Risk Assessment Tool (FRAX) could refine the risk prediction with a positive net reclassification index ranging from 0.024 to 0.072. We generated and validated a PRS for SOS which was associated with the risk of fracture. This score was more strongly associated with the risk of fracture than many clinical risk factors and provided an improvement in risk prediction. gSOS should be explored as a tool to improve risk stratification to identify individuals at high risk of fracture. The online version contains supplementary material available at 10.1186/s13073-021-00838-6.
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影响因子：
5
作者：
Fry A;Littlejohns TJ;Sudlow C;Doherty N;Adamska L;Sprosen T;Collins R;Allen NE
通讯作者：
Allen NE
影响因子：
4
作者：
Kanis, J. A.;McCloskey, E. V.;Oden, A.
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Oden, A.
影响因子：
64.8
作者：
Bycroft C;Freeman C;Petkova D;Band G;Elliott LT;Sharp K;Motyer A;Vukcevic D;Delaneau O;O'Connell J;Cortes A;Welsh S;Young A;Effingham M;McVean G;Leslie S;Allen N;Donnelly P;Marchini J
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Marchini J
影响因子：
6.2
作者：
Eriksson, Joel;Evans, Daniel S.;Ohlsson, Claes
通讯作者：
Ohlsson, Claes
影响因子：
120.7
作者：
CUMMINGS, SR;BLACK, DM;VOGT, TM
通讯作者：
VOGT, TM