Evidence map›Paper›PMID 27350247›Full record

ArticleBMC genetics2016

Cardio-metabolic parameters are associated with genetic admixture estimates in a pediatric population from Colombia.

Angélica M Muñoz, Claudia M Velásquez, Gabriel Bedoya

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Article in BMC genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Angélica M MuñozResearch Group on Food and Human Nutrition, Universidad de Antioquia (UdeA), Calle 70 No. 52-21, Medellín, Colombia. angelicamariamc@yahoo.com.
Claudia M VelásquezResearch Group on Food and Human Nutrition, Universidad de Antioquia (UdeA), Calle 70 No. 52-21, Medellín, Colombia.
Gabriel BedoyaResearch Group on Molecular Genetic (GENMOL), Universidad de Antioquia (UdeA), Calle 70 No. 52-21, Medellín, Colombia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThere are different genetic patterns for cardio-metabolic parameters among different populations. Additionally, it has been found that ancestral genetic components (the proportion of Amerindian, European and African) in admixed Latin American populations influence an individual's susceptibility to cardio-metabolic disorders. The aim of this study was to evaluate the effect of ancestral genetic composition on a series of cardio-metabolic risk factors in a young admixed population from Colombia.

resultsIn a sample of 853 Colombian youth, 10 to 18 years old, the mean European contribution was 66.6 % (range: 41-82 %), the mean African contribution was 14 % (range: 4-48 %), and the mean Amerindian contribution was 19.4 % (range: 10-35 %) using a panel of 40 autosomal ancestry-informative markers (AIMs). We assessed the degree of association between ancestral African, Amerindian and European genetic components and measures of body mass index, waist circumference, fasting glucose, fasting insulin, insulin resistance, triglycerides, high-density lipoprotein, and systolic and diastolic blood pressure. Two of the nine measures assessed presented a nominal significant association with ancestral components after adjusting for confounding variables: triglyceride levels were associated with the Amerindian component (OR = 1.06, 98.3 % CI = 1.01-1.11, P = 0.002) and systolic blood pressure was associated with the European component (OR = 0.93, 98.3 % CI = 0.87 to 0.99, P = 0.008) and the African component (OR = 1.07, CI = 1.01-1.14 P = 0.008), although it was not significant following a global Bonferroni correction. Additionally, insulin levels and insulin resistance showed associations with the African component.

conclusionsOur findings support the idea that an Amerindian ancestral component may act as a risk factor for high triglyceride levels. In addition, an African ancestral component confers a risk for high systolic blood pressure, and a European ancestry serves as a protective factor for this condition in a young admixed population from Colombia. However, these results should be confirmed in a larger population.

Indexed as

AdolescentBlood PressureBody Mass IndexCardiovascular DiseasesChildColombiaEnvironmentFemaleGenetic Predisposition to DiseaseHumansInsulinMaleMyocardiumPhenotypeTriglyceridesWaist CircumferenceInsulinTriglyceridesAdmixed populationAncestryCardio-metabolic parametersYouth

Identifiers

PMID27350247
PMCPMC4924275

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.