Dataset Information

Genome-wide linkage analysis of pulmonary function in families of children with asthma in Costa Rica.

ABSTRACT:

Background

Although asthma is highly prevalent among certain Hispanic subgroups, genetic determinants of asthma and asthma-related traits have not been conclusively identified in Hispanic populations. A study was undertaken to identify genomic regions containing susceptibility loci for pulmonary function and bronchodilator responsiveness (BDR) in Costa Ricans.

Methods

Eight extended pedigrees were ascertained through schoolchildren with asthma in the Central Valley of Costa Rica. Short tandem repeat (STR) markers were genotyped throughout the genome at an average spacing of 8.2 cM. Multipoint variance component linkage analyses of forced expiratory volume in 1 second (FEV(1)) and FEV(1)/ forced vital capacity (FVC; both pre-bronchodilator and post-bronchodilator) and BDR were performed in these eight families (pre-bronchodilator spirometry, n = 640; post-bronchodilator spirometry and BDR, n = 624). Nine additional STR markers were genotyped on chromosome 7. Secondary analyses were repeated after stratification by cigarette smoking.

Results

Among all subjects, the highest logarithm of the odds of linkage (LOD) score for FEV(1) (post-bronchodilator) was found on chromosome 7q34-35 (LOD = 2.45, including the additional markers). The highest LOD scores for FEV(1)/FVC (pre-bronchodilator) and BDR were found on chromosomes 2q (LOD = 1.53) and 9p (LOD = 1.53), respectively. Among former and current smokers there was near-significant evidence of linkage to FEV(1)/FVC (post-bronchodilator) on chromosome 5p (LOD = 3.27) and suggestive evidence of linkage to FEV(1) on chromosomes 3q (pre-bronchodilator, LOD = 2.74) and 4q (post-bronchodilator, LOD = 2.66).

Conclusions

In eight families of children with asthma in Costa Rica, there is suggestive evidence of linkage to FEV(1) on chromosome 7q34-35. In these families, FEV(1)/FVC may be influenced by an interaction between cigarette smoking and a locus (loci) on chromosome 5p.

SUBMITTER: Hersh CP

PROVIDER: S-EPMC2117166 | biostudies-literature | 2007 Mar

REPOSITORIES: biostudies-literature

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Publications

Genome-wide linkage analysis of pulmonary function in families of children with asthma in Costa Rica.

Hersh Craig P CP Soto-Quirós Manuel E ME Avila Lydiana L Lake Stephen L SL Liang Catherine C Fournier Eduardo E Spesny Mitzi M Sylvia Jody S JS Lazarus Ross R Hudson Thomas T Verner Andrei A Klanderman Barbara J BJ Freimer Nelson B NB Silverman Edwin K EK Celedón Juan C JC

Thorax 20061110 3

<h4>Background</h4>Although asthma is highly prevalent among certain Hispanic subgroups, genetic determinants of asthma and asthma-related traits have not been conclusively identified in Hispanic populations. A study was undertaken to identify genomic regions containing susceptibility loci for pulmonary function and bronchodilator responsiveness (BDR) in Costa Ricans.<h4>Methods</h4>Eight extended pedigrees were ascertained through schoolchildren with asthma in the Central Valley of Costa Rica. ...[more]

PMID: 17099076

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Project description:Rationale: MicroRNAs have emerged as crucial post-transcriptional and network regulators in inflammatory diseases, including asthma. We hypothesized that peripheral blood miRNA would be associated with airflow obstruction in children with asthma, and that some of these effects would also be observable in adults with COPD. Methods: We analyzed small RNA-Seq data from 365 peripheral blood samples from the Genetics of Asthma in Costa Rica Study (GACRS). GACRS comprised children from the Central Valley of Costa Rica age 6-14 years with physician-diagnosed asthma and ≥2 respiratory symptoms or asthma attacks in the prior year. FEV1/FVC percent-predicted was dichotomized at 100%, splitting the cohort into those with and without evidence of airflow obstruction and used as our primary outcome. Differentially expressed (DE) miRs were identified using the DESeq2 package in R with a 10% FDR and adjustment for age, gender, and inhaled corticosteroid (ICS) use. We attempted to replicate the top airflow obstruction-associated microRNAs from the GACRS study in the COPDGene study, in which blood microRNA data were available in 439 current and former smoking adults with and without airflow obstruction (defined as raw FEV1/FVC < 0.7). Results: After QC, we had 361 samples and 649 miRs for DE analysis. Of the 361 samples, 220 and 141 were from subjects without and with airflow obstruction, respectively. We found 1 upregulated (let-7e-5p p=0.0004) and 2 downregulated (miR-342-3p p=0.0002; miR-671-5p p=0.0001) miRs in subjects with airflow obstruction compared to those without airflow obstruction. These three miRNAs were then tested for association with airflow obstruction in the COPDGene study, in which let-7e-5p was upregulated (p = 0.064) and miR-342-3p (p =0.085) was downregulated in participants with FEV1/FVC < 0.7 (n=196) compared to those with FEV1/FVC > 0.7 (n=243). Differentially expressed miR’s target genes were enriched for PI3K-Akt, Hippo, WNT, MAPK, and focal adhesion signaling pathways. We also separately considered the targets of only the two miRNAs that were also associated with FEV1/FVC in the adult current and former smokers, where PI3K-Akt, MAPK and Hippo signaling pathways were among the top five most enriched pathways. Conclusion: Three DE miRs were linked to airflow obstruction in children with asthma. Two miRs were associated with FEV1/FVC in current and former smoking adults. These miRs were involved in asthma and COPD-related pathways: PI3K-Akt, Hippo, MAPK, and focal adhesion signaling pathways. Together these findings provide important evidence that these two disorders may share genetic regulatory systems that contribute to airflow obstruction.

Dataset Information

Genome-wide linkage analysis of pulmonary function in families of children with asthma in Costa Rica.

Background

Methods

Results

Conclusions

Publications

Genome-wide linkage analysis of pulmonary function in families of children with asthma in Costa Rica.

Similar Datasets

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