Contribution of genetic ancestry and polygenic risk score in meeting vitamin B12 needs in healthy Brazilian children and adolescents

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Abstract

Polymorphisms in genes related to the metabolism of vitamin B12 haven’t been examined in a Brazilian population. To (a) determine the correlation between the local genetic ancestry components and vitamin B12 levels using ninety B12-related genes; (b) determine associations between these genes and their SNPs with vitamin B12 levels; (c) determine a polygenic risk score (PRS) using significant variants. This cross-sectional study included 168 children and adolescents, aged 9–13 years old. Total cobalamin was measured in plasma. Genotyping arrays and whole exome data were combined to yield ~ 7000 SNPs in 90 genes related to vitamin B12. The Efficient Local Ancestry Inference was used to estimate local ancestry for African (AFR), Native American, and European (EUR). The association between the genotypes and vitamin B12 levels were determined with generalized estimating equation. Vitamin B12 levels were driven by positive (EUR) and negative (AFR, AMR) correlations with genetic ancestry. A set of 36 variants were used to create a PRS that explained 42% of vitamin level variation. Vitamin B12 levels are influenced by genetic ancestry and a PRS explained almost 50% of the variation in plasma cobalamin in Brazilian children and adolescents.

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Most cited references 79

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Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

Yoav Benjamini, Yosef Hochberg (1995)

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STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

Damian Szklarczyk, Annika L Gable, David Lyon … (2018)

Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.

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The variant call format and VCFtools

Petr Danecek, Adam Auton, Gonçalo R Abecasis … (2011)

Summary: The variant call format (VCF) is a generic format for storing DNA polymorphism data such as SNPs, insertions, deletions and structural variants, together with rich annotations. VCF is usually stored in a compressed manner and can be indexed for fast data retrieval of variants from a range of positions on the reference genome. The format was developed for the 1000 Genomes Project, and has also been adopted by other projects such as UK10K, dbSNP and the NHLBI Exome Project. VCFtools is a software suite that implements various utilities for processing VCF files, including validation, merging, comparing and also provides a general Perl API. Availability: http://vcftools.sourceforge.net Contact: rd@sanger.ac.uk

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Author and article information

Contributors

Jacqueline Pontes Monteiro: jacque160165@gmail.com

Journal

Journal ID (nlm-ta): Sci Rep

Journal ID (iso-abbrev): Sci Rep

Title: Scientific Reports

Publisher: Nature Publishing Group UK (London )

ISSN (Electronic): 2045-2322

Publication date (Electronic): 7 June 2021

Publication date PMC-release: 7 June 2021

Publication date Collection: 2021

Volume: 11

Electronic Location Identifier: 11992

Affiliations

[1 ]GRID grid.11899.38, ISNI 0000 0004 1937 0722, Department of Clinical Analyses, Toxicology and Food Sciences, School of Pharmaceutics Sciences, , University of São Paulo, ; Ribeirão Preto, Brazil

[2 ]GRID grid.11899.38, ISNI 0000 0004 1937 0722, Department of Pediatrics and Department of Health Sciences, Ribeirão Preto Medical School, Nutrition and Metabolism Section, , University of São Paulo, ; Avenida Bandeirantes, 3900, Bairro Monte Alegre, Ribeirão Preto, SP 14040-900 Brazil

[3 ]GRID grid.12380.38, ISNI 0000 0004 1754 9227, Department of Chemistry and Pharmaceutical Sciences, Amsterdam Institute for Molecular and Life Sciences, , Vrije Universiteite Amsterdam, ; Amsterdam, The Netherlands

[4 ]GRID grid.419905.0, ISNI 0000 0001 0066 4948, Nestlé Research, Société Des Produits Nestlé SA, ; EPFL Innovation Park, H, 1015 Lausanne, Switzerland

[5 ]GRID grid.11899.38, ISNI 0000 0004 1937 0722, Center for Medical Genomics, Ribeirão Preto Medical School Hospital, , University of São Paulo, ; Ribeirão Preto, Brazil

[6 ]GRID grid.11899.38, ISNI 0000 0004 1937 0722, Department of Genetics, Ribeirão Preto Medical School, , University of São Paulo, ; Ribeirão Preto, Brazil

[7 ]Vydiant, Folsom, CA USA

[8 ]GRID grid.8591.5, ISNI 0000 0001 2322 4988, Present Address: Sophia Genetics, , Campus Biotech, ; 1202 Geneva, Switzerland

Article

Publisher ID: 91530

DOI: 10.1038/s41598-021-91530-7

PMC ID: 8184816

PubMed ID: 34099811

SO-VID: 73263e87-5ff2-4ae8-a596-834a2dbe29a1

License:

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

History

Date received : 30 November 2020

Date accepted : 25 May 2021

Funding

Funded by: Nestlé Research Lausanne Switzerland

Award ID: RDHS 000054

Award Recipient : Sofia Moco Ornella Cominetti Sylviane Métairon Solenn Pruvost Aline Charpagne Jerome Carayol Patrick Descombes Jim Kaput Jacqueline Pontes Monteiro

Funded by: Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Award ID: Process 2012/20421-8

Award Recipient : Jacqueline Pontes Monteiro

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ScienceOpen disciplines: Uncategorized

Keywords: computational biology and bioinformatics,genetics,systems biology,medical research,molecular medicine,risk factors

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ScienceOpen disciplines: Uncategorized

Keywords: computational biology and bioinformatics, genetics, systems biology, medical research, molecular medicine, risk factors

Contribution of genetic ancestry and polygenic risk score in meeting vitamin B12 needs in healthy Brazilian children and adolescents

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Most cited references 79

Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

The variant call format and VCFtools

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