ReviewFrontiers in genetics2015
Mapping asthma-associated variants in admixed populations.
Review in Frontiers in genetics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
28 citing papers in PubMed, 43 citations in OpenAlex.
- Genome-wide association study of inhaled corticosteroid response in admixed children with asthma.Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology · 2019Trial
- FRAME: fast reference-based ancestry makeup estimation tool.Bioinformatics advances · 2026Article
- Machine learning models incorporating genotype and ancestry improve severe asthma risk prediction.Scientific reports · 2025Article
- Identifying the Genetic Ancestry of the Pediatric Obesity-Related Asthma Variant (rs6494395) at Rps27l.Pediatric pulmonology · 2025Article
- Asthma-Genomic Advances Toward Risk Prediction.Clinics in chest medicine · 2024Review
- Genome-wide admixture and association analysis identifies African ancestry-specific risk loci of eosinophilic esophagitis in African Americans.The Journal of allergy and clinical immunology · 2023Article
- Leveraging genetic ancestry to study severe asthma exacerbations in an admixed population.Thorax · 2023Article
- Including diverse and admixed populations in genetic epidemiology research.Genetic epidemiology · 2022Article
- Asthma and the Missing Heritability Problem: Necessity for Multiomics Approaches in Determining Accurate Risk Profiles.Frontiers in immunology · 2022Review
- Genome-wide association study of asthma, total IgE, and lung function in a cohort of Peruvian children.The Journal of allergy and clinical immunology · 2021Article
- Air, Land, and Sea: Gene-Environment Interaction in Chronic Disease.The American journal of medicine · 2021Review
- Genetic ancestry differences in pediatric asthma readmission are mediated by socioenvironmental factors.The Journal of allergy and clinical immunology · 2021Article
- Identification ofJournal of personalized medicine · 2021Article
- Genetics of Food Allergy.Immunology and allergy clinics of North America · 2021Review
- Genome-wide association study of asthma exacerbations despite inhaled corticosteroid use.The European respiratory journal · 2021Article
- Genetic ancestry plays a central role in population pharmacogenomics.Communications biology · 2021Article
- The impact of global and local Polynesian genetic ancestry on complex traits in Native Hawaiians.PLoS genetics · 2021Article
- MI-MAAP: marker informativeness for multi-ancestry admixed populations.BMC bioinformatics · 2020Article
- PAMAM: Power analysis in multiancestry admixture mapping.Genetic epidemiology · 2019Article
- Interactions between environmental pollutants and genetic susceptibility in asthma risk.Current opinion in immunology · 2019Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
Admixed populations arise when two or more previously isolated populations interbreed. Mapping asthma susceptibility loci in an admixed population using admixture mapping (AM) involves screening the genome of individuals of mixed ancestry for chromosomal regions that have a higher frequency of alleles from a parental population with higher asthma risk as compared with parental population with lower asthma risk. AM takes advantage of the admixture created in populations of mixed ancestry to identify genomic regions where an association exists between genetic ancestry and asthma (in contrast to between the genotype of the marker and asthma). The theory behind AM is that chromosomal segments of affected individuals contain a significantly higher-than-average proportion of alleles from the high-risk parental population and thus are more likely to harbor disease-associated loci. Criteria to evaluate the applicability of AM as a gene mapping approach include: (1) the prevalence of the disease differences in ancestral populations from which the admixed population was formed; (2) a measurable difference in disease-causing alleles between the parental populations; (3) reduced linkage disequilibrium (LD) between unlinked loci across chromosomes and strong LD between neighboring loci; (4) a set of markers with noticeable allele-frequency differences between parental populations that contributes to the admixed population (single nucleotide polymorphisms (SNPs) are the markers of choice because they are abundant, stable, relatively cheap to genotype, and informative with regard to the LD structure of chromosomal segments); and (5) there is an understanding of the extent of segmental chromosomal admixtures and their interactions with environmental factors. Although genome-wide association studies have contributed greatly to our understanding of the genetic components of asthma, the large and increasing degree of admixture in populations across the world create many challenges for further efforts to map disease-causing genes. This review, summarizes the historical context of admixed populations and AM, and considers current opportunities to use AM to map asthma genes. In addition, we provide an overview of the potential limitations and future directions of AM in biomedical research, including joint admixture and association mapping for asthma and asthma-related disorders.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.