African ancestry, lung function and the effect of genetics

Menezes, Ana Maria Baptista; Wehrmeister, Fernando César; Hartwig, Fernando Pires; Pérez‐Padilla, Rogelio; Gigante, Denise Petrucci; Barros, Fernando C.; Oliveira, Isabel; Ferreira, Gustavo Dias

doi:10.1183/09031936.00112114

Cited by 39 publications

(22 citation statements)

References 36 publications

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“…Global ancestry measures the proportion of the genome inherited from one or more parental populations within an admixed individual (30,31), and although they correlate highly with self-reported race/ethnicity, there is evidence that selfreported race is likely to leave a portion of the substructure within admixed populations, as race/ethnicity are sociopolitical constructs, the categories of which are fluid and subject to change along with societal and cultural trends (33,(35)(36)(37). Recent studies have shown that genetic ancestry was associated with pulmonary traits (asthma prevalence/severity, lung function) independent of self-reported race in African Americans and Puerto Ricans (23,32,33,38). Therefore, to avoid potential confounding, it is important to consider both self-identified race/ethnicity and genetic ancestry when constructing statistical models to assess the relationship between lung function and exposures of interest in admixed populations, such as the population of interest in the present study.…”

Section: Discussionmentioning

confidence: 99%

Air Pollution and Lung Function in Minority Youth with Asthma in the GALA II (Genes–Environments and Admixture in Latino Americans) and SAGE II (Study of African Americans, Asthma, Genes, and Environments) Studies

Neophytou

White²,

Oh³

et al. 2016

Am J Respir Crit Care Med

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Rationale: Adverse effects of exposures to ambient air pollution on lung function are well documented, but evidence in racial/ethnic minority children is lacking.Objectives: To assess the relationship between air pollution and lung function in minority children with asthma and possible modification by global genetic ancestry. Methods:The study population consisted of 1,449 Latino and 519 African American children with asthma from five different geographical regions in the mainland United States and Puerto Rico. We examined five pollutants (particulate matter <10 mm and <2.5 mm in diameter, ozone, nitrogen dioxide, and sulfur dioxide), derived from participant residential history and ambient air monitoring data, and assessed over several time windows. We fit generalized additive models for associations between pollutant exposures and lung function parameters and tested for interaction terms between exposures and genetic ancestry. Measurements and Main Results:A 5 mg/m 3 increase in average lifetime particulate matter less than or equal to 2.5 mm in diameter exposure was associated with a 7.7% decrease in FEV 1 (95% confidence interval = 211.8 to 23.5%) in the overall study population. Global genetic ancestry did not appear to significantly modify these associations, but percent African ancestry was a significant predictor of lung function.Conclusions: Early-life particulate exposures were associated with reduced lung function in Latino and African American children with asthma. This is the first study to report an association between exposure to particulates and reduced lung function in minority children in which racial/ethnic status was measured by ancestry-informative markers.

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Section: Discussionmentioning

confidence: 99%

Air Pollution and Lung Function in Minority Youth with Asthma in the GALA II (Genes–Environments and Admixture in Latino Americans) and SAGE II (Study of African Americans, Asthma, Genes, and Environments) Studies

Neophytou

White²,

Oh³

et al. 2016

Am J Respir Crit Care Med

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“…For example, data collected as part of a large population survey in Japan showed that changes in socioeconomic and general health conditions were associated with changes in body frame, such as a change in relative leg length, which has been associated with a secular trend in lung function in Japan [19]. In view of genetic determinants of pulmonary function [21][22][23], it is similarly a challenge to define normal lung function in mixed-ethnicity populations; possibly this played a role in the finding of an unsatisfactory fit of the GLI equations in a Tunisian population where Berbers have sub-Saharan ancestry [22]. Improving our understanding of how social and cultural changes affect both somatic and lung growth will make an important contribution to the literature.…”

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confidence: 99%

Do the Global Lung Function Initiative 2012 equations fit my population?

Quanjer

Stanojevic

2016

Eur Respir J

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Knowing whether a patient's lung function result is similar to what can be expected of a healthy individual is critical for the correct interpretation of pulmonary function test results. Since lung function changes with growth and ageing and differs according to sex and ethnicity, there are now >300 published reference equations available for spirometry alone. Consequently, individual pulmonary function laboratories are left with a challenging decision: which reference equation do I choose? While it is recommended that reference equations are population specific, there are obvious logistical challenges to collect normative data from a large and representative population such that the resulting range of normal values are not biased. Alternatively, laboratories can choose to use a published reference equation derived from a population similar to the one being tested. Several studies have shown that not all lung function reference equations produce the same results [1-3]. For instance, some equations are based on smaller samples of the population, while others are based on larger and representative population surveys. In some studies, spirometry curves are reviewed rigorously for quality control, while in others they are not. Some data are collected on antiquated equipment no longer available today, while others contain novel outcome measures. Furthermore, within each commercial spirometer, users have an overwhelming number of options: to use a single reference equation, or multiple reference equations combined into a single prediction set. The "stitching" of different equations results in artificial jumps in predicted values that could lead to erroneous interpretation of results and unnecessary intervention [2, 4, 5]. Most importantly, often the physicians interpreting results are unaware of which equations were used, and how the choice of equation might affect their interpretation [6-8]. Another common practice is to extrapolate reference equations beyond the age range of the intended age range, which has also been shown to bias interpretation of results [9].

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“…Histórica y operacionalmente se ha utilizado la edad, altura y peso para determinar valores referenciales, sin embargo, en la actualidad se sabe que la longitud de los miembros inferiores en relación al tórax son diferentes en distintas poblaciones, por lo que la altura no representaría exactamente la participación del tórax en el funcionamiento del proceso de ventilación (Menezes et al, 2015).…”

Section: Introductionunclassified

Propuesta de Ecuaciones Predictivas de Capacidad Inspiratoria y Flujo Espiratorio Máximo Considerando Mediciones Torácicas: Un Estudio Piloto

Muñoz-Cofré

Sol

2018

Int. J. Morphol.

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MUÑOZ, C. R. & DEL SOL, M.Propuesta de ecuaciones predictivas de capacidad inspiratoria y flujo espiratorio máximo considerando mediciones torácicas: un estudio piloto. Int. J. Morphol., 36(1):333-337, 2018. RESUMEN:El objetivo del siguiente estudio fue determinar si las mediciones de tórax provocan modificaciones en las ecuaciones predictivas de capacidad inspiratoria (CI) y flujo espiratorio máximo (FEM). Se evaluaron 24 sujetos de sexo masculino entre 18 y 26 años, todos estudiantes sedentarios de la Universidad Católica del Maule, Chile. Se les realizó antropometría corporal básica (peso y talla corporal) y específica de tórax, diámetro antero-posterior (DAT) y transverso (DTT) de tórax y perímetro mesoesternal (PME). Posterior a esto, se evaluó la función ventilatoria a través de pletismografía corporal. Para estimar las ecuaciones de regresión lineal se utilizó el método de mínimos cuadrados relacionando la CI y FEM. La comparación entre el valor predicho establecido y nuestra propuesta fue comparado utilizando la prueba t de student o U de Mann-Whitney según correspondiera, considerándose un nivel de significancia estadística de p<0,05. Los resultados indican que para la propuesta de la ecuación de FEM se consideró el DTT y PME, logrando diferencias significativas con los valores de Knudson et al. Por tanto, se concluye que las mediciones de DTT a VR y PME a CPT influyeron en la ecuación predictiva de FEM en estudiantes sedentarios.PALABRAS CLAVES: Antropometría de tórax, función pulmonar, ecuaciones predictivas. INTRODUCCIÓNEn Chile, las enfermedades del sistema respiratorio constituyen el tercer grupo de causas de muerte, al mismo tiempo son la segunda causa de egreso hospitalario en sujetos mayores de 65 años (Olmos et al., 2015). Por tanto un diagnóstico oportuno, es vital para la disminución de estas cifras, así, una correcta valoración de la función pulmonar contribuiría a lograr este objetivo.En un gran número de laboratorios de función pulmonar locales se utilizan los valores referenciales de Knudson et al. al no contar con parámetros nacionales (Alvarez et al., 2004). En este contexto, Gutiérrez et al. (2014) definieron ecuaciones predictivas de función pulmonar en población chilena sana, en donde los valores derivados de estas fueron significativamente superiores a los de Knudson et al. Por tanto, los investigadores sugieren la obtención de valores de referencia a partir de sujetos sanos, con características antropométricas similares a la población blanco.Si bien existen numerosos factores que influyen en los valores de función pulmonar, se reconocen como los más importantes al sexo, edad, etnia y antropometría (Whittaker et al., 2005). Histórica y operacionalmente se ha utilizado la edad, altura y peso para determinar valores referenciales, sin embargo, en la actualidad se sabe que la longitud de los miembros inferiores en relación al tórax son diferentes en distintas poblaciones, por lo que la altura no representaría exactamente la participación del tórax en el funcionamiento del proceso de ve...

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African ancestry, lung function and the effect of genetics

Cited by 39 publications

References 36 publications

Air Pollution and Lung Function in Minority Youth with Asthma in the GALA II (Genes–Environments and Admixture in Latino Americans) and SAGE II (Study of African Americans, Asthma, Genes, and Environments) Studies

Air Pollution and Lung Function in Minority Youth with Asthma in the GALA II (Genes–Environments and Admixture in Latino Americans) and SAGE II (Study of African Americans, Asthma, Genes, and Environments) Studies

Do the Global Lung Function Initiative 2012 equations fit my population?

Propuesta de Ecuaciones Predictivas de Capacidad Inspiratoria y Flujo Espiratorio Máximo Considerando Mediciones Torácicas: Un Estudio Piloto

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