RESUMO
Lung function detection in mice is currently most accurately measured by invasive techniques, which are costly, labor intensive, and terminal. This limits their use for large-scale or longitudinal studies. Noninvasive assays are often used instead, but their accuracy for measuring lung function parameters such as resistance and elastance has been questioned in studies involving small numbers of mouse strains. Here we compared parameters detected by two different methods using 29 inbred mouse strains: enhanced pause (Penh), detected by unrestrained plethysmography, and central airway resistance and lung elastance, detected by a forced oscillation technique. We further tested whether the phenotypic variations were determined by the same genomic location in genome-wide association studies using a linear mixed model algorithm. Penh, resistance, and elastance were measured in nonexposed mice or mice exposed to saline and increasing doses of aerosolized methacholine. Because Penh differed from airway resistance in several strains and because the peak genetic associations found for Penh, resistance, or elastance were located at different genomic regions, we conclude that using Penh as an indicator for lung function changes in high-throughput genetic studies (i.e., genome-wide association studies or quantitative trait locus studies) measures something fundamentally different than airway resistance and lung elastance.
Assuntos
Resistência das Vias Respiratórias/fisiologia , Pletismografia/métodos , Resistência das Vias Respiratórias/efeitos dos fármacos , Algoritmos , Animais , Feminino , Estudo de Associação Genômica Ampla , Masculino , Cloreto de Metacolina/farmacologia , Camundongos , Locos de Características QuantitativasRESUMO
Airway hyper-responsiveness (AHR) is a critical phenotype of human asthma and animal models of asthma. Other studies have measured AHR in nine mouse strains, but only six strains have been used to identify genetic loci underlying AHR. Our goals were to increase the genetic diversity of available strains by surveying 27 additional strains, to apply haplotype association mapping to the 36-strain survey, and to identify new genetic determinants for AHR. We derived AHR from the increase in airway resistance in females subjected to increasing levels of methacholine concentrations. We used haplotype association mapping to identify associations between AHR and haplotypes on chromosomes 3, 5, 8, 12, 13, and 14. And we used bioinformatics techniques to narrow the identified region on chromosome 13, reducing the region to 29 candidate genes, with 11 of considerable interest. Our combined use of haplotype association mapping with bioinformatics tools is the first study of its kind for AHR on these 36 strains of mice. Our analyses have narrowed the possible QTL genes and will facilitate the discovery of novel genes that regulate AHR in mice.
Assuntos
Camundongos Endogâmicos/genética , Locos de Características Quantitativas , Hipersensibilidade Respiratória/genética , Animais , Mapeamento Cromossômico , Cromossomos , Feminino , Haplótipos , CamundongosRESUMO
Effective diabetes problem solving requires identification of risk factors for inadequate mealtime self-management. Ecological momentary assessment was used to enhance identification of factors hypothesized to impact self-management. Adolescents with type 1 diabetes participated in a feasibility trial for a mobile app called MyDay. Meals, mealtime insulin, self-monitored blood glucose, and psychosocial and contextual data were obtained for 30 days. Using 1472 assessments, mixed-effects between-subjects analyses showed that social context, location, and mealtime were associated with missed self-monitored blood glucose. Stress, energy, mood, and fatigue were associated with missed insulin. Within-subjects analyses indicated that all factors were associated with both self-management tasks. Intraclass correlations showed within-subjects accounted for the majority of variance. The ecological momentary assessment method provided specific targets for improving self-management problem solving, phenotyping, or integration within just-in-time adaptive interventions.