Genetic ancestry in lung-function predictions

Rajesh Kumar, Max A. Seibold, Melinda C. Aldrich, L. Keoki Williams, Alex P. Reiner, Laura Colangelo, Joshua Galanter, Christopher Gignoux, Donglei Hu, Saunak Sen, Shweta Choudhry, Edward L. Peterson, Jose Rodriguez-Santana, William Rodriguez-Cintron, Michael A. Nalls, Tennille S. Leak, Ellen O'Meara, Bernd Meibohm, Stephen B. Kritchevsky, Rongling Li & 8 others Tamara B. Harris, Deborah A. Nickerson, Myriam Fornage, Paul Enright, Elad Ziv, Lewis J. Smith, Kiang Liu, Esteban González Burchard

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Abstract

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.)

Original languageEnglish (US)
Pages (from-to)321-330
Number of pages10
JournalNew England Journal of Medicine
Volume363
Issue number4
DOIs
StatePublished - Jul 22 2010

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Lung
African Americans
Health
Forced Expiratory Volume
Body Composition
Young Adult
Coronary Vessels
Asthma
Vital Capacity
National Institutes of Health (U.S.)
Ethnic Groups
Linear Models
Cohort Studies
Population

All Science Journal Classification (ASJC) codes

  • Medicine(all)

Cite this

Kumar, R., Seibold, M. A., Aldrich, M. C., Williams, L. K., Reiner, A. P., Colangelo, L., ... Burchard, E. G. (2010). Genetic ancestry in lung-function predictions. New England Journal of Medicine, 363(4), 321-330. https://doi.org/10.1056/NEJMoa0907897

Genetic ancestry in lung-function predictions. / Kumar, Rajesh; Seibold, Max A.; Aldrich, Melinda C.; Williams, L. Keoki; Reiner, Alex P.; Colangelo, Laura; Galanter, Joshua; Gignoux, Christopher; Hu, Donglei; Sen, Saunak; Choudhry, Shweta; Peterson, Edward L.; Rodriguez-Santana, Jose; Rodriguez-Cintron, William; Nalls, Michael A.; Leak, Tennille S.; O'Meara, Ellen; Meibohm, Bernd; Kritchevsky, Stephen B.; Li, Rongling; Harris, Tamara B.; Nickerson, Deborah A.; Fornage, Myriam; Enright, Paul; Ziv, Elad; Smith, Lewis J.; Liu, Kiang; Burchard, Esteban González.

In: New England Journal of Medicine, Vol. 363, No. 4, 22.07.2010, p. 321-330.

Research output: Contribution to journalArticle

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 2010, 'Genetic ancestry in lung-function predictions', New England Journal of Medicine, vol. 363, no. 4, pp. 321-330. https://doi.org/10.1056/NEJMoa0907897
Kumar R, Seibold MA, Aldrich MC, Williams LK, Reiner AP, Colangelo L et al. Genetic ancestry in lung-function predictions. New England Journal of Medicine. 2010 Jul 22;363(4):321-330. https://doi.org/10.1056/NEJMoa0907897
Kumar, Rajesh ; Seibold, Max A. ; Aldrich, Melinda C. ; Williams, L. Keoki ; Reiner, Alex P. ; Colangelo, Laura ; Galanter, Joshua ; Gignoux, Christopher ; Hu, Donglei ; Sen, Saunak ; Choudhry, Shweta ; Peterson, Edward L. ; Rodriguez-Santana, Jose ; Rodriguez-Cintron, William ; Nalls, Michael A. ; Leak, Tennille S. ; O'Meara, Ellen ; Meibohm, Bernd ; Kritchevsky, Stephen B. ; Li, Rongling ; Harris, Tamara B. ; Nickerson, Deborah A. ; Fornage, Myriam ; Enright, Paul ; Ziv, Elad ; Smith, Lewis J. ; Liu, Kiang ; Burchard, Esteban González. / Genetic ancestry in lung-function predictions. In: New England Journal of Medicine. 2010 ; Vol. 363, No. 4. pp. 321-330.
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abstract = "BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.)",
author = "Rajesh Kumar and Seibold, {Max A.} and Aldrich, {Melinda C.} and Williams, {L. Keoki} and Reiner, {Alex P.} and Laura Colangelo and Joshua Galanter and Christopher Gignoux and Donglei Hu and Saunak Sen and Shweta Choudhry and Peterson, {Edward L.} and Jose Rodriguez-Santana and William Rodriguez-Cintron and Nalls, {Michael A.} and Leak, {Tennille S.} and Ellen O'Meara and Bernd Meibohm and Kritchevsky, {Stephen B.} and Rongling Li and Harris, {Tamara B.} and Nickerson, {Deborah A.} and Myriam Fornage and Paul Enright and Elad Ziv and Smith, {Lewis J.} and Kiang Liu and Burchard, {Esteban Gonz{\'a}lez}",
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T1 - Genetic ancestry in lung-function predictions

AU - Kumar, Rajesh

AU - Seibold, Max A.

AU - Aldrich, Melinda C.

AU - Williams, L. Keoki

AU - Reiner, Alex P.

AU - Colangelo, Laura

AU - Galanter, Joshua

AU - Gignoux, Christopher

AU - Hu, Donglei

AU - Sen, Saunak

AU - Choudhry, Shweta

AU - Peterson, Edward L.

AU - Rodriguez-Santana, Jose

AU - Rodriguez-Cintron, William

AU - Nalls, Michael A.

AU - Leak, Tennille S.

AU - O'Meara, Ellen

AU - Meibohm, Bernd

AU - Kritchevsky, Stephen B.

AU - Li, Rongling

AU - Harris, Tamara B.

AU - Nickerson, Deborah A.

AU - Fornage, Myriam

AU - Enright, Paul

AU - Ziv, Elad

AU - Smith, Lewis J.

AU - Liu, Kiang

AU - Burchard, Esteban González

PY - 2010/7/22

Y1 - 2010/7/22

N2 - BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.)

AB - BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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.)

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DO - 10.1056/NEJMoa0907897

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