Race- and Ethnicity-Based Spirometry Reference Equations: Are They Accurate for Genetically Admixed Children?

基于种族和民族的肺活量测定参考方程:它们对基因混杂的儿童准确吗?

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Abstract

BACKGROUND: Variation in genetic ancestry among genetically admixed racial and ethnic groups may influence the fit of guideline-recommended spirometry reference equations, which rely on self-identified race and ethnicity. RESEARCH QUESTION: What is the influence of genetic ancestry on the fit of race- and ethnicity-based spirometry reference equations in populations of genetically admixed children? STUDY DESIGN AND METHODS: Cross-sectional fit of guideline-recommended race- and ethnicity-based spirometry reference equations was evaluated in healthy control participants from case-control studies of asthma. Anthropometry, blood samples, and spirometric measurements were obtained for 599 genetically admixed children 8 to 21 years of age. Genetic ancestry was estimated using genome-wide genotype data. Equation fit, measured as a mean z score, was assessed in self-identified African American (n = 275) and Puerto Rican (n = 324) children as well as genetic ancestry-defined strata of each population. RESULTS: For African American children, African American-derived equations fit for predicting FEV(1) and FVC in those with an African ancestry more than the median (81.4%-100.0%), whereas composite equations for "other/mixed" populations fit for predicting FEV(1) and FVC in those with African ancestry at or less than the median (30.7%-81.3%). For Puerto Rican children with African ancestry at or less than the median (6.4%-21.3%), White-derived equations fit both FEV(1) and FVC, whereas for those with African ancestry more than the median (21.4%-87.5%), White-derived equations fit the FEV(1) and the composite equations fit the FVC. INTERPRETATION: Guideline-recommended spirometry reference equations yielded biased estimates of lung function in genetically admixed children with high variation of African ancestry. Spirometry could benefit from reference equations that incorporate genetic ancestry, either for more precise application of the current equations or the derivation and use of new equations.

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