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Mapping asthma-associated variants in admixed populations

Overview of attention for article published in Frontiers in Genetics, September 2015
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  • Above-average Attention Score compared to outputs of the same age (56th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

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Title
Mapping asthma-associated variants in admixed populations
Published in
Frontiers in Genetics, September 2015
DOI 10.3389/fgene.2015.00292
Pubmed ID
Authors

Tesfaye B. Mersha

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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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 3%
Unknown 62 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 20%
Student > Ph. D. Student 12 19%
Student > Bachelor 8 13%
Student > Master 7 11%
Student > Doctoral Student 3 5%
Other 6 9%
Unknown 15 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 28%
Biochemistry, Genetics and Molecular Biology 11 17%
Medicine and Dentistry 10 16%
Pharmacology, Toxicology and Pharmaceutical Science 2 3%
Computer Science 2 3%
Other 5 8%
Unknown 16 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 17 March 2016.
All research outputs
#7,655,010
of 23,305,591 outputs
Outputs from Frontiers in Genetics
#2,525
of 12,321 outputs
Outputs of similar age
#93,798
of 275,498 outputs
Outputs of similar age from Frontiers in Genetics
#22
of 60 outputs
Altmetric has tracked 23,305,591 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 12,321 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done well, scoring higher than 78% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 275,498 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.