Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
Review
. 2015 Sep 29:6:292.
doi: 10.3389/fgene.2015.00292. eCollection 2015.

Mapping asthma-associated variants in admixed populations

Tesfaye B Mersha  1
Affiliations
Review

Mapping asthma-associated variants in admixed populations

Tesfaye B Mersha. Front Genet. .

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.

Keywords: admixed population; admixture mapping (AM); ancestry-informative markers (AIMs); asthma; genetic ancestry; genome-wide association study (GWAS); next-generation sequencing (NGS); socio-environmental risk factors.

PubMed Disclaimer

Figures

Figure 1
Figure 1
Childhood asthma prevalence by state-by-state in the United States. Asthma prevalence rates are generally higher in the Northeast region. This could attribute to the population composition. For example, the Puerto Rican population, in which asthma prevalence is highest, tends to be concentrated in the Northeast region of the country. Source: CDC/NCHS, National Health Interview Survey, annual average for the period 2001–2005.
Figure 2
Figure 2
Asthma prevalence rates by race/ethnicity among the U.S. children. Race is considered as risk factor for asthma. But, how much is due to environmental exposures, genetic, and asthma morbidity factors required further studies.
Figure 3
Figure 3
Schematic presentations of the mosaic chromosomal structures of admixed population derived from two founders. The chromosomes of the two founders are combined and after several generations of random mating produce present day admixed individual. Admixed population can be studied using case-control and case-only admixture mapping study design to map mutation as indicated by red star.
Figure 4
Figure 4
Asthma GWAS catalog variants grouped by ancestry: Asthma related variants identified through genome-wide association studies (GWAS) NHGRI catalog of published GWAS was searched. PhenoGram was used to plot and visualize GWA catalog association results for potentially pleiotropic SNPs among across ancestry (Wolfe et al., 2013). An Ideogram of all 22 chromosomes is plotted, along with the X and Y chromosomes. Lines are plotted on the chromosomes corresponding to the base-pair location of each asthma-related SNP, and the line connects to colored shape representing the phenotype(s) associated with that SNP.
Figure 5
Figure 5
Strategies to prioritize ancestry-specific risk loci via admixture mapping and ancestry-shared risk loci via GWAS for follow-up genotyping and analysis.
Figure 6
Figure 6
Studies considering the relationship between degrees of African ancestry proportion and asthma and asthma-related outcomes.
Figure 7
Figure 7
Impact of ancestry with both genetic and non-genetic risk factors in causing asthma and asthma-related risks.
See this image and copyright information in PMC

Similar articles

  • Genome-wide Association Identifies Novel Etiological Insights Associated with Parkinson's Disease in African and African Admixed Populations.
    Rizig M, Bandres-Ciga S, Makarious MB, Ojo O, Crea PW, Abiodun O, Levine KS, Abubakar S, Achoru C, Vitale D, Adeniji O, Agabi O, Koretsky MJ, Agulanna U, Hall DA, Akinyemi R, Xie T, Ali M, Shamim EA, Ani-Osheku I, Padmanaban M, Arigbodi O, Standaert DG, Bello A, Dean M, Erameh C, Elsayed I, Farombi T, Okunoye O, Fawale M, Billingsley KJ, Imarhiagbe F, Jerez PA, Iwuozo E, Baker B, Komolafe M, Malik L, Nwani P, Daida K, Nwazor E, Miano-Burkhardt A, Nyandaiti Y, Fang ZH, Obiabo Y, Kluss JH, Odeniyi O, Hernandez D, Odiase F, Tayebi N, Ojini F, Sidranksy E, Onwuegbuzie G, D'Souza AM, Osaigbovo G, Berhe B, Osemwegie N, Reed X, Oshinaike O, Leonard H, Otubogun F, Alvarado CX, Oyakhire S, Ozomma S, Samuel S, Taiwo F, Wahab K, Zubair Y, Iwaki H, Kim JJ, Morris HR, Hardy J, Nalls M, Heilbron K, Norcliffe-Kaufmann L; Disease Research Network, International Parkinson’s Disease Genomics Consortium - Africa (IPDGC Africa), Black and African American Connections to Parkinson’s Disease (BLAAC PD) Study Group, the 23andMe Research Team; Blauwendraat C, Houlden H, Singleton A, Okubadejo N. Rizig M, et al. medRxiv [Preprint]. 2023 May 7:2023.05.05.23289529. doi: 10.1101/2023.05.05.23289529. medRxiv. 2023. Update in: Lancet Neurol. 2023 Nov;22(11):1015-1025. doi: 10.1016/S1474-4422(23)00283-1 PMID: 37398408 Free PMC article. Updated. Preprint.
  • Enhanced statistical tests for GWAS in admixed populations: assessment using African Americans from CARe and a Breast Cancer Consortium.
    Pasaniuc B, Zaitlen N, Lettre G, Chen GK, Tandon A, Kao WH, Ruczinski I, Fornage M, Siscovick DS, Zhu X, Larkin E, Lange LA, Cupples LA, Yang Q, Akylbekova EL, Musani SK, Divers J, Mychaleckyj J, Li M, Papanicolaou GJ, Millikan RC, Ambrosone CB, John EM, Bernstein L, Zheng W, Hu JJ, Ziegler RG, Nyante SJ, Bandera EV, Ingles SA, Press MF, Chanock SJ, Deming SL, Rodriguez-Gil JL, Palmer CD, Buxbaum S, Ekunwe L, Hirschhorn JN, Henderson BE, Myers S, Haiman CA, Reich D, Patterson N, Wilson JG, Price AL. Pasaniuc B, et al. PLoS Genet. 2011 Apr;7(4):e1001371. doi: 10.1371/journal.pgen.1001371. Epub 2011 Apr 21. PLoS Genet. 2011. PMID: 21541012 Free PMC article.
  • MI-MAAP: marker informativeness for multi-ancestry admixed populations.
    Chen S, Ghandikota S, Gautam Y, Mersha TB. Chen S, et al. BMC Bioinformatics. 2020 Apr 3;21(1):131. doi: 10.1186/s12859-020-3462-5. BMC Bioinformatics. 2020. PMID: 32245404 Free PMC article.
  • Genetic Ancestry Inference and Its Application for the Genetic Mapping of Human Diseases.
    Suarez-Pajes E, Díaz-de Usera A, Marcelino-Rodríguez I, Guillen-Guio B, Flores C. Suarez-Pajes E, et al. Int J Mol Sci. 2021 Jun 28;22(13):6962. doi: 10.3390/ijms22136962. Int J Mol Sci. 2021. PMID: 34203440 Free PMC article. Review.
  • Admixture mapping as a gene discovery approach for complex human traits and diseases.
    Nievergelt CM, Schork NJ. Nievergelt CM, et al. Curr Hypertens Rep. 2005 Feb;7(1):31-7. doi: 10.1007/s11906-005-0052-x. Curr Hypertens Rep. 2005. PMID: 15683584 Review.
See all similar articles

Cited by

See all "Cited by" articles

References

    1. Akinbami L. J., Moorman J. E., Bailey C., Zahran H. S., King M., Johnson C. A., et al. (2012). Trends in asthma prevalence, health care use, and mortality in the United States, 2001-2010. NCHS Data Brief 94, 1–8. Available online at: http://www.cdc.gov/nchs/data/databriefs/db94.htm - PubMed
    1. Akinbami L. J., Moorman J. E., Garbe P. L., Sondik E. J. (2009). Status of childhood asthma in the United States, 1980–2007. Pediatrics 123(Suppl. 3), S131–S145. 10.1542/peds.2008-2233c - DOI - PubMed
    1. Akinbami L. J., Moorman J. E., Liu X. (2011). Asthma prevalence, health care use, and mortality: United States, 2005-2009. Natl. Health Stat. Report 32, 1–14. Available online at: http://www.cdc.gov/nchs/data/nhsr/nhsr032.pdf - PubMed
    1. Akinbami L. J., Moorman J. E., Simon A. E., Schoendorf K. C. (2014). Trends in racial disparities for asthma outcomes among children 0 to 17 years, 2001–2010. J. Allergy Clin. Immunol. 134, 547–553.e545. 10.1016/j.jaci.2014.05.037 - DOI - PMC - PubMed
    1. Alexander D. H., Lange K. (2011). Enhancements to the ADMIXTURE algorithm for individual ancestry estimation. BMC Bioinformatics 12:246. 10.1186/1471-2105-12-246 - DOI - PMC - PubMed