Spirometry Accuracy for Genetically Admixed Children

A need exists for personalized, genetic ancestry-informed respiratory equations for predicting an individual’s lung function.

Guideline-recommended spirometry reference equations, which rely on self-identified race and ethnicity, may be influenced by variations in genetic ancestry among genetically admixed racial and ethnic groups. Equations that determine normative lung functions have been categorized by self-reported race and ethnicity per the Global Lung Function Initiative (GLI) as well as the NHANES III, explains Jonathan Witonsky, MD.

“The applicability of race- and ethnically-based spirometry equations has come into question with regard to children who are genetically admixed,” Dr. Witonsky says. “Specifically, the guideline-recommended lung function reference equations predict individuals’ forced expiratory volume in 1 second (FEV₁) and forced vital capacity (FVC) after adjusting for their race or ethnicity (Figure),” Dr. Witonsky says. “However, we found that these race/ethnicity-based equations are frequently inaccurate when used for individuals of mixed ancestry and, therefore, may contribute to biased medical care and perpetuate health disparities.”

African Ancestry Median Used for Classification

For a study published in CHEST Journal, Dr. Witonsky and colleagues evaluated a cross-sectional fit of guideline-recommended race- and ethnically-based spirometry reference equations. They identified 599 healthy controls (aged 8-21) from case-control studies of asthma who were genetically admixed. Genome-wide, genotype data were used to estimate the participants’ genetic ancestry. Based on parent or grandparent self-identification, 326 of the participants were Puerto Rican and 280 were African American.

The African ancestry median was used to classify the African American (median 81.3%; range, 30.7%-100%) and Puerto Rican (median, 21.3% range, 6.4%-87.5%) populations into two groups. The first group consisted of participants with more than the median and the second group was made up of participants at or less than the median.

When classifying African American children using the African genetic ancestry median, only the GLI composite equations were appropriate for predicting FEV₁ and FVC with mean z scores of –0.25 (95% CI, –0.42 to –0.09) for FEV₁ (5.8% < the lower limit of normal [LLN]) and –0.08 (95% CI, –0.25 to 0.10) for FVC (5.8% < the LLN) for African American children classified at or less than the median.

GLI Composite Equations Had Least Misclassification for both FEV₁ & FVC

Although the NHANES III equations derived from African Americans were fitting for FEV₁ predictions (0.24; 95% CI, 0.08- 0.39), the equations did not statistically fit for predicting FVC (0.41; 95% CI, 0.26-0.56) in African American children classified at or less than the median.

The NHANES III equations derived from African American individuals were appropriate for predicting FEV₁ (0.11; 95% CI, –0.04 to 0.26) and FVC (0.27; 95% CI, 0.10-0.43) for African American children with African ancestry at more than the median.

GLI equations derived from African American individuals were appropriate for predicting FEV₁ (0.29; 95% CI, 0.13-0.44), but underestimated with statistical significance FVC (0.43; 95% CI, 0.26-0.60) in African American children with African ancestry at more than the median. The GLI composite equations resulted in the least misclassification for both FEV₁ and FVC in all subpopulations.

For Puerto Rican children, GLI equations derived from White individuals were appropriate with mean z scores of –0.06 (95% CI, –0.19 to 0.06) for predicting FEV₁ (6.8% < the LLN) and –0.33 (95% CI, –0.46 to –0.21) for predicting FVC (11.1% < the LLN).

For Puerto Rican children with African ancestry at or less than the median as well as at more than the median, the GLI and NHANES III equations derived from White individuals fit for predicting FEV₁. The White-derived equations fit for predicting only FVC among Puerto Rican children with African ancestry at or less than the median.

The GLI composite equation was appropriate for predicting FVC in the subpopulation of Puerto Rican children with African ancestry at more than the median. Among those with African ancestry at or less than the median, the GLI composite equations underestimated FEV₁ predictions. In Puerto Rican children with African ancestry at or less than the median, both GLI and NHANES III equations derived from White individuals were appropriate for predicting FEV₁ and FVC.

“Genetic ancestry, the architecture of genome variation between populations or individuals, can explain a portion of lung function variation between and within groups even after accounting for the influence of social and environmental factors,” Dr. Witonsky notes. “Until genetic ancestry-based equations are widely available, racially and ethnically diverse individuals are likely best served if their spirometric measurements are evaluated using multiple equations, with each result taken in the context of clinical symptoms.”