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Hugo Villamil-ramírez – One of the best experts on this subject based on the ideXlab platform.

  • Latin Americans show wide-spread Converso Ancestry and the imprint of local Native Ancestry on physical appearance
    , 2018
    Co-Authors: Juan-camilo Chacón-duque, Kaustubh Adhikari, Macarena Fuentes-guajardo, Javier Mendoza-revilla, Victor Acuña-alonzo, Rodrigo Barquera, Mirsha Quinto-sánchez, Jorge Gómez-valdés, Paola Everardo Martínez, Hugo Villamil-ramírez

    Abstract:

    Historical records and genetic analyses indicate that Latin Americans trace their Ancestry mainly to the admixture of Native Americans, Europeans and Sub-Saharan Africans. Using novel haplotype-based methods here we infer the sub-populations involved in admixture for over 6,500 Latin Americans and evaluate the impact of sub-continental Ancestry on the physical appearance of these individuals. We find that pre-Columbian Native genetic structure is mirrored in Latin Americans and that sources of non-Native Ancestry, and admixture timings, match documented migratory flows. We also detect South/East Mediterranean Ancestry across Latin America, probably stemming from the clandestine colonial migration of Christian converts of non-European origin (Conversos). Furthermore, we find that Central Andean Ancestry impacts on variation of facial features in Latin Americans, particularly nose morphology, possibly relating to environmental adaptation during the evolution of Native Americans.

  • Latin Americans show wide-spread Converso Ancestry and imprint of local Native Ancestry on physical appearance
    Nature Communications, 2018
    Co-Authors: Juan-camilo Chacón-duque, Kaustubh Adhikari, Macarena Fuentes-guajardo, Javier Mendoza-revilla, Victor Acuña-alonzo, Rodrigo Barquera, Mirsha Quinto-sánchez, Jorge Gómez-valdés, Paola Everardo Martínez, Hugo Villamil-ramírez

    Abstract:

    Historical records and genetic analyses indicate that Latin Americans trace their Ancestry mainly to the intermixing (admixture) of Native Americans, Europeans and Sub-Saharan Africans. Using novel haplotype-based methods, here we infer sub-continental Ancestry in over 6,500 Latin Americans and evaluate the impact of regional Ancestry variation on physical appearance. We find that Native American Ancestry components in Latin Americans correspond geographically to the present-day genetic structure of Native groups, and that sources of non-Native Ancestry, and admixture timings, match documented migratory flows. We also detect South/East Mediterranean Ancestry across Latin America, probably stemming mostly from the clandestine colonial migration of Christian converts of non-European origin (Conversos). Furthermore, we find that Ancestry related to highland (Central Andean) versus lowland (Mapuche) Natives is associated with variation in facial features, particularly nose morphology, and detect significant differences in allele frequencies between these groups at loci previously associated with nose morphology in this sample.

Tilahun Abebe – One of the best experts on this subject based on the ideXlab platform.

  • Self-reported race/ethnicity in the age of genomic research: its potential impact on understanding health disparities
    Human Genomics, 2015
    Co-Authors: Tesfaye B Mersha, Tilahun Abebe

    Abstract:

    This review explores the limitations of self-reported race, ethnicity, and genetic Ancestry in biomedical research. Various terminologies are used to classify human differences in genomic research including race, ethnicity, and Ancestry. Although race and ethnicity are related, race refers to a person’s physical appearance, such as skin color and eye color. Ethnicity, on the other hand, refers to communality in cultural heritage, language, social practice, traditions, and geopolitical factors. Genetic Ancestry inferred using Ancestry informative markers (AIMs) is based on genetic/genomic data. Phenotype-based race/ethnicity information and data computed using AIMs often disagree. For example, self-reporting African Americans can have drastically different levels of African or European Ancestry. Genetic analysis of individual Ancestry shows that some self-identified African Americans have up to 99% of European Ancestry, whereas some self-identified European Americans have substantial admixture from African Ancestry. Similarly, African Ancestry in the Latino population varies between 3% in Mexican Americans to 16% in Puerto Ricans. The implication of this is that, in African American or Latino populations, self-reported Ancestry may not be as accurate as direct assessment of individual genomic information in predicting treatment outcomes. To better understand human genetic variation in the context of health disparities, we suggest using “Ancestry” (or biogeographical Ancestry) to describe actual genetic variation, “race” to describe health disparity in societies characterized by racial categories, and “ethnicity” to describe traditions, lifestyle, diet, and values. We also suggest using Ancestry informative markers for precise characterization of individuals’ biological Ancestry. Understanding the sources of human genetic variation and the causes of health disparities could lead to interventions that would improve the health of all individuals.

  • self reported race ethnicity in the age of genomic research its potential impact on understanding health disparities
    Human Genomics, 2015
    Co-Authors: Tesfaye B Mersha, Tilahun Abebe

    Abstract:

    This review explores the limitations of self-reported race, ethnicity, and genetic Ancestry in biomedical research. Various terminologies are used to classify human differences in genomic research including race, ethnicity, and Ancestry. Although race and ethnicity are related, race refers to a person’s physical appearance, such as skin color and eye color. Ethnicity, on the other hand, refers to communality in cultural heritage, language, social practice, traditions, and geopolitical factors. Genetic Ancestry inferred using Ancestry informative markers (AIMs) is based on genetic/genomic data. Phenotype-based race/ethnicity information and data computed using AIMs often disagree. For example, self-reporting African Americans can have drastically different levels of African or European Ancestry. Genetic analysis of individual Ancestry shows that some self-identified African Americans have up to 99% of European Ancestry, whereas some self-identified European Americans have substantial admixture from African Ancestry. Similarly, African Ancestry in the Latino population varies between 3% in Mexican Americans to 16% in Puerto Ricans. The implication of this is that, in African American or Latino populations, self-reported Ancestry may not be as accurate as direct assessment of individual genomic information in predicting treatment outcomes. To better understand human genetic variation in the context of health disparities, we suggest using “Ancestry” (or biogeographical Ancestry) to describe actual genetic variation, “race” to describe health disparity in societies characterized by racial categories, and “ethnicity” to describe traditions, lifestyle, diet, and values. We also suggest using Ancestry informative markers for precise characterization of individuals’ biological Ancestry. Understanding the sources of human genetic variation and the causes of health disparities could lead to interventions that would improve the health of all individuals.

Kenneth K Kidd – One of the best experts on this subject based on the ideXlab platform.

  • Analyses of a set of 128 Ancestry informative single-nucleotide polymorphisms in a global set of 119 population samples
    Investigative Genetics, 2011
    Co-Authors: Judith R Kidd, Françoise R Friedlaender, William C Speed, Andrew J Pakstis, Francisco M De La Vega, Kenneth K Kidd

    Abstract:

    Background Using DNA to determine an individual’s Ancestry from among human populations is generally interesting and useful for many purposes, including admixture mapping, controlling for population structure in disease or trait association studies and forensic Ancestry inference. However, to estimate Ancestry, including possible admixture within an individual, as well as heterogeneity within a group of individuals, allele frequencies are necessary for what are believed to be the contributing populations. For this purpose, panels of Ancestry informative markers (AIMs) have been developed. Results We are presenting our work on one such panel, composed of 128 Ancestry informative single-nucleotide polymorphisms (AISNPs) already proposed in the literature. Compared to previous studies of these AISNPs, we have studied three times the number of individuals (4,871) in three times as many population samples (119). We have validated this panel for many Ancestry assignment and admixture studies, especially those that were the rationale for the original selection of the 128 SNPs: African Americans and Mexican Americans. At the same time, the limitations of the panel for distinguishing Ancestry and quantifying admixture among Eurasian populations are noted. Conclusion We demonstrate the simultaneous importance of the specific set of population samples and their relative sample sizes in the use of the structure program to determine which groups cluster together and consequently influence the ability of a marker panel to infer Ancestry. We demonstrate the strengths and weaknesses of this particular panel of AISNPs in a global context.

  • analyses of a set of 128 Ancestry informative single nucleotide polymorphisms in a global set of 119 population samples
    Investigative Genetics, 2011
    Co-Authors: Judith R Kidd, Françoise R Friedlaender, William C Speed, Andrew J Pakstis, Francisco M De La Vega, Kenneth K Kidd

    Abstract:

    Using DNA to determine an individual’s Ancestry from among human populations is generally interesting and useful for many purposes, including admixture mapping, controlling for population structure in disease or trait association studies and forensic Ancestry inference. However, to estimate Ancestry, including possible admixture within an individual, as well as heterogeneity within a group of individuals, allele frequencies are necessary for what are believed to be the contributing populations. For this purpose, panels of Ancestry informative markers (AIMs) have been developed. We are presenting our work on one such panel, composed of 128 Ancestry informative single-nucleotide polymorphisms (AISNPs) already proposed in the literature. Compared to previous studies of these AISNPs, we have studied three times the number of individuals (4,871) in three times as many population samples (119). We have validated this panel for many Ancestry assignment and admixture studies, especially those that were the rationale for the original selection of the 128 SNPs: African Americans and Mexican Americans. At the same time, the limitations of the panel for distinguishing Ancestry and quantifying admixture among Eurasian populations are noted. We demonstrate the simultaneous importance of the specific set of population samples and their relative sample sizes in the use of the structure program to determine which groups cluster together and consequently influence the ability of a marker panel to infer Ancestry. We demonstrate the strengths and weaknesses of this particular panel of AISNPs in a global context.