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Genetics and Epigenetics

Admixture/fine-mapping in Brazilians reveals a West African associated potential regulatory variant (rs114066381) with a strong female-specific effect on body mass and fat mass indexes

International Journal of Obesity volume 45, pages 1017–1029 (2021)Cite this article

Subjects

Abstract

Background/objectives

Admixed populations are a resource to study the global genetic architecture of complex phenotypes, which is critical, considering that non-European populations are severely underrepresented in genomic studies. Here, we study the genetic architecture of BMI in children, young adults, and elderly individuals from the admixed population of Brazil.

Subjects/methods

Leveraging admixture in Brazilians, whose chromosomes are mosaics of fragments of Native American, European, and African origins, we used genome-wide data to perform admixture mapping/fine-mapping of body mass index (BMI) in three Brazilian population-based cohorts from Northeast (Salvador), Southeast (Bambuí), and South (Pelotas).

Results

We found significant associations with African-associated alleles in children from Salvador (PALD1 and ZMIZ1 genes), and in young adults from Pelotas (NOD2 and MTUS2 genes). More importantly, in Pelotas, rs114066381, mapped in a potential regulatory region, is significantly associated only in females (p = 2.76e−06). This variant is rare in Europeans but with frequencies of ~3% in West Africa and has a strong female-specific effect (95% CI: 2.32–5.65 kg/m2 per each A allele). We confirmed this sex-specific association and replicated its strong effect for an adjusted fat mass index in the same Pelotas cohort, and for BMI in another Brazilian cohort from São Paulo (Southeast Brazil). A meta-analysis confirmed the significant association. Remarkably, we observed that while the frequency of rs114066381-A allele ranges from 0.8 to 2.1% in the studied populations, it attains ~9% among women with morbid obesity from Pelotas, São Paulo, and Bambuí. The effect size of rs114066381 is at least five times higher than the FTO SNPs rs9939609 and rs1558902, already emblematic for their high effects.

Conclusions

We identified six candidate SNPs associated with BMI. rs114066381 stands out for its high effect that was replicated and its high frequency in women with morbid obesity. We demonstrate how admixed populations are a source of new relevant phenotype-associated genetic variants.

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Fig. 1: Admixture in the Brazilian cohorts, BMI distributions, and admixture mapping (AM) Manhattan plots with significant peaks.
Fig. 2: LocusZoom plot of the fine-mapping of consensus significant admixture mapping peak in young adults from Pelotas at 13q12.3 associated with European ancestry in females performed using both genotyped and imputed SNPs ±1 Mb from target region (lead windows).
Fig. 3: Body mass index (BMI) in females and males’ adults from Pelotas cohort, according to their genotypes in the SNP rs114066381.
Fig. 4: Forest plots from the meta-analysis synthesizing association results between rs114066381 and BMI from seven populations.

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Code availability

Used bioinformatics pipelines are available in the EPIGEN-Brazil Project Scientific Workflow (http://www.ldgh.com.br/scientificworkflow, [34]).

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Acknowledgements

For analyses, we used the Sagarana cluster (from Centro de Laboratórios Multiusuários do Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais). We thank Miguel Ortega for help in the use of Sagarana, Ms. Evelyn Tay at University of Ghana Medical School (Accra, Ghana) for managing the study, and Ms. Marcelle Bartholomeu and Ms. Àlex Teixeira for technical support. The EPIGEN-Brazil Initiative is funded by the Brazilian Ministry of Health (Department of Science and Technology from the Secretaria de Ciência, Tecnologia e Insumos Estratégicos) through Financiadora de Estudos e Projetos. The EPIGEN-Brazil investigators received funding from the Brazilian Ministry of Education (CAPES Agency), Brazilian National Research Council (CNPq), the Minas Gerais State Agency for Support of Research (FAPEMIG), Rede Mineira de Genômica Populacional e Medicina de Precisão (FAPEMIG-RED-00314-16), and TWAS-CNPq Full PhD fellow, and grant 2019/19998-8, São Paulo Research Foundation (FAPESP).

Author information

Author notes

  1. These authors contributed equally: Marilia O. Scliar, Hanaisa P. Sant Anna, Meddly L. Santolalla

Authors and Affiliations

  1. Departamento de Genética, Ecologia e Evolução, Instituto de Ciências Biológicas, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil

    Marilia O. Scliar, Hanaisa P. Sant’Anna, Meddly L. Santolalla, Thiago P. Leal, Nathalia M. Araújo, Isabela Alvim, Victor Borda, Wagner C. S. Magalhães, Mateus H. Gouveia, Ricardo Lyra, Moara Machado, Lucas Michelin, Maíra R. Rodrigues, Fernanda S. G. Kehdy, Camila Zolini, Marcelo R. Luizon, Francisco Lobo & Eduardo Tarazona-Santos

  2. Human Genome and Stem Cell Research Center, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, Brazil

    Marilia O. Scliar, Michel S. Naslavsky, Guilherme L. Yamamoto, Maria Rita Passos-Bueno & Mayana Zatz

  3. Melbourne Integrative Genomics, The University of Melbourne, Melbourne, VIC, Australia

    Hanaisa P. Sant’Anna & Isabela Alvim

  4. Emerge, Emerging Diseases and Climate Change Research Unit, School of Public Health and Administration, Universidad Peruana Cayetano Heredia, Lima, Peru

    Meddly L. Santolalla & Robert H. Gilman

  5. Departamento de Estatística, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil

    Thiago P. Leal

  6. Instituto de Pesquisas René Rachou, Fundação Oswaldo Cruz, Belo Horizonte, MG, Brazil

    Nathalia M. Araújo, Mateus H. Gouveia, Sérgio V. Peixoto & Maria Fernanda Lima-Costa

  7. Laboratório de Bioinformática, LABINFO, Laboratório Nacional de Computação Científica (LNCC), Petrópolis, RJ, Brazil

    Victor Borda

  8. Núcleo de Ensino e Pesquisa, Instituto Mário Penna, Belo Horizonte, MG, Brazil

    Wagner C. S. Magalhães

  9. Center for Research on Genomics and Global Health, National Human Genome Research Institute, Bethesda, MD, USA

    Mateus H. Gouveia

  10. Departamento de Genética e Biologia Evolutiva, Instituto de Biociências, Universidade de São Paulo, São Paulo, SP, Brazil

    Maíra R. Rodrigues

  11. Programa de Pós-graduação em Genética e Biologia Molecular, Laboratório de Genética Humana e Médica, Instituto de Ciências Biológicas, Universidade Federal do Pará—Campus Guamá, Belém, PA, Brazil

    Gilderlanio S. Araújo

  12. Laboratório de Hanseníase, Instituto Oswaldo Cruz, Fundação Oswaldo Cruz, Rio de Janeiro, RJ, Brazil

    Fernanda S. G. Kehdy

  13. Beagle, Belo Horizonte, MG, Brazil

    Camila Zolini

  14. Mosaico Translational Genomics Initiative, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil

    Camila Zolini & Eduardo Tarazona-Santos

  15. Departamento de Gestão em Saúde, Escola de Enfermagem, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brasil

    Sérgio V. Peixoto

  16. Department of Clinical Genetics, Children’s Hospital, Medical School, Universidade de São Paulo, São Paulo, SP, Brazil

    Guilherme L. Yamamoto

  17. Department of Epidemiology, Public Health School, Universidade de São Paulo, São Paulo, SP, Brazil

    Yeda A. O. Duarte

  18. School of Nursing, Universidade de São Paulo, São Paulo, SP, Brazil

    Yeda A. O. Duarte

  19. Departments of Biology and Genetics, University of Pennsylvania, Philadelphia, PA, USA

    Matthew E. B. Hansen & Sarah A. Tishkoff

  20. SAMRC/Wits Developmental Pathways for Health Research Unit, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

    Shane A. Norris

  21. Department of International Health, Johns Hopkins School of Public Health, Baltimore, MD, USA

    Robert H. Gilman

  22. Instituto Nacional de Salud, Lima, Peru

    Heinner Guio

  23. Stanford Cancer Institute, Stanford University, Stanford, CA, USA

    Ann W. Hsing

  24. Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA

    Sam M. Mbulaiteye

  25. University of Ghana Medical School, Accra, Ghana

    James Mensah & Edward Yeboah

  26. Cancer Biology Division, Ponce Research Institute, Ponce Health Sciences University, Ponce, Puerto Rico

    Julie Dutil

  27. Cancer Genomics Research Laboratory, Leidos Biomedical Research, Frederick National Laboratory for Cancer Research, Frederick, MD, USA

    Meredith Yeager

  28. Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

    Ananyo Choudhury & Michele Ramsay

  29. Division of Human Genetics, National Health Laboratory Service and School of Pathology, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa

    Michele Ramsay

  30. Institute of Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA

    Timothy D. O´Connor

  31. Program in Personalized and Genomic Medicine, University of Maryland School of Medicine, Baltimore, MD, USA

    Timothy D. O´Connor

  32. Department of Medicine, University of Maryland School of Medicine, Baltimore, MD, USA

    Timothy D. O´Connor

  33. Instituto do Coração, Universidade de São Paulo, São Paulo, SP, Brazil

    Alexandre C. Pereira

  34. Instituto de Saúde Coletiva, Universidade Federal da Bahia, Salvador, BA, Brazil

    Mauricio L. Barreto

  35. Center for Data and Knowledge Integration for Health, Institute Gonçalo Muniz, Fundação Oswaldo Cruz, Salvador, BA, Brazil

    Mauricio L. Barreto

  36. Programa de Pós-Graduação em Epidemiologia, Universidade Federal de Pelotas, Pelotas, RS, Brazil

    Bernardo L. Horta

  37. Universidad Peruana Cayetano Heredia, Lima, Peru

    Eduardo Tarazona-Santos

  38. Instituto de Estudos Avançados Transdisciplinares, Universidade Federal de Minas Gerais, Belo Horizonte, MG, Brazil

    Eduardo Tarazona-Santos

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  1. Marilia O. Scliar
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Correspondence to Eduardo Tarazona-Santos.

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Scliar, M.O., Sant’Anna, H.P., Santolalla, M.L. et al. Admixture/fine-mapping in Brazilians reveals a West African associated potential regulatory variant (rs114066381) with a strong female-specific effect on body mass and fat mass indexes. Int J Obes 45, 1017–1029 (2021). https://doi.org/10.1038/s41366-021-00761-1

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