Genetic ancestry in lung-function predictions.
Genetic ancestry in lung-function predictions.
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DOI：
10.1056/nejmoa0907897
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发表时间：
2010-07-22
期刊：
影响因子：
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通讯作者：
Burchard EG
中科院分区：
文献类型：
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作者：
Kumar R;Seibold MA;Aldrich MC;Williams LK;Reiner AP;Colangelo L;Galanter J;Gignoux C;Hu D;Sen S;Choudhry S;Peterson EL;Rodriguez-Santana J;Rodriguez-Cintron W;Nalls MA;Leak TS;O'Meara E;Meibohm B;Kritchevsky SB;Li R;Harris TB;Nickerson DA;Fornage M;Enright P;Ziv E;Smith LJ;Liu K;Burchard EG
自我认定的种族或民族是用来确定正常参考标准预测肺功能。我们进行了一项研究，以确定遗传决定的非洲血统百分比是否与肺功能有关，以及使用它是否可以改善自认为是非裔美国人的肺功能预测。我们评估了年轻成人冠状动脉风险发展（CARDIA）研究中自认为非裔美国人的777名参与者的血统，并通过线性回归评估了肺功能与血统之间的关系。我们对两个独立的非裔美国人队列进行了类似的数据分析：813名健康、衰老和身体组成（HABC）研究参与者和579名心血管健康研究（CHS）参与者。我们比较了两种模型与肺功能测量的拟合：基于标准预测方程中使用的协变量的模型和包含祖先的模型。我们还在两个哮喘研究人群中评估了基于血统的模型对疾病严重程度分类的影响。在CARDIA队列中，非洲血统与1秒用力呼气量（FEV1）和用力肺活量呈负相关。这些关系也出现在HABC和CHS队列中。在预测肺功能时，基于血统的模型比标准模型更适合数据。基于血统的模型导致4%至5%的参与者对哮喘严重程度进行了重新分类（基于预测的FEV1的百分比）。目前的预测方程，仅依赖于自我认定的种族，可能会错误估计非裔美国人受试者的肺功能。将祖先纳入规范方程可以改善肺功能估计，更准确地分类疾病严重程度。（由美国国立卫生研究院和其他机构资助。）
Self-identified race or ethnic group is used to determine normal reference standards in the prediction of pulmonary function. We conducted a study to determine whether the genetically determined percentage of African ancestry is associated with lung function and whether its use could improve predictions of lung function among persons who identified themselves as African American. We assessed the ancestry of 777 participants self-identified as African American in the Coronary Artery Risk Development in Young Adults (CARDIA) study and evaluated the relation between pulmonary function and ancestry by means of linear regression. We performed similar analyses of data for two independent cohorts of subjects identifying themselves as African American: 813 participants in the Health, Aging, and Body Composition (HABC) study and 579 participants in the Cardiovascular Health Study (CHS). We compared the fit of two types of models to lung-function measurements: models based on the covariates used in standard prediction equations and models incorporating ancestry. We also evaluated the effect of the ancestry-based models on the classification of disease severity in two asthma-study populations. African ancestry was inversely related to forced expiratory volume in 1 second (FEV1) and forced vital capacity in the CARDIA cohort. These relations were also seen in the HABC and CHS cohorts. In predicting lung function, the ancestry-based model fit the data better than standard models. Ancestry-based models resulted in the reclassification of asthma severity (based on the percentage of the predicted FEV1) in 4 to 5% of participants. Current predictive equations, which rely on self-identified race alone, may misestimate lung function among subjects who identify themselves as African American. Incorporating ancestry into normative equations may improve lung-function estimates and more accurately categorize disease severity. (Funded by the National Institutes of Health and others.)