Dataset Information

Characterization of Large Copy Number Variation in Mexican Type 2 Diabetes subjects.

ABSTRACT: The effect of Copy Number Variants (CNVs) on Type 2 Diabetes (T2D) remains little explored. The present study characterized large rare CNVs in 686 T2D and 194 non-T2D subjects of Mexican ancestry genotyped using the Affymetrix Genome-Wide Human SNP array 5.0. Rare CNVs with???100?kb length were identified using a stringent strategy based on merging CNVs calls generated using Birdsuit, iPattern and PennCNV algorithms. We applied three different strategies to evaluate the distribution of CNVs in the T2D and non-T2D samples: 1) Burden analysis, 2) Identification of CNVs in loci previously associated to T2D, and 3) Identification of CNVs observed only in the T2D group. In the CNV burden analysis, the T2D group showed a higher proportion of CNVs, and also a higher proportion of CNVs overlapping at least one gene than the non T2D group. Five of the six loci previously associated with T2D had duplications or deletions in the T2D sample, but not the non-T2D sample. A gene-set analysis including genes with CNVs observed only in the T2D group highlighted gene-sets related with sensory perception (olfactory receptors, OR) and phenylpyruvate tautomerase/dopachrome isomerase activity (MIF and DDT genes).

SUBMITTER: de Jesus Ascencio-Montiel I

PROVIDER: S-EPMC5719030 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Characterization of Large Copy Number Variation in Mexican Type 2 Diabetes subjects.

de Jesús Ascencio-Montiel Iván I Pinto Dalila D Parra Esteban J EJ Valladares-Salgado Adán A Cruz Miguel M Scherer Stephen W SW

Scientific reports 20171206 1

The effect of Copy Number Variants (CNVs) on Type 2 Diabetes (T2D) remains little explored. The present study characterized large rare CNVs in 686 T2D and 194 non-T2D subjects of Mexican ancestry genotyped using the Affymetrix Genome-Wide Human SNP array 5.0. Rare CNVs with ≥ 100 kb length were identified using a stringent strategy based on merging CNVs calls generated using Birdsuit, iPattern and PennCNV algorithms. We applied three different strategies to evaluate the distribution of CNVs in t ...[more]

PMID: 29213072

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Project description:BackgroundChildhood obesity is a serious public health concern that confers a greater risk of developing important comorbidities such as MetS and T2DM. Recent studies evidence that gut microbiota may be a contributing factor; however, only few studies exist in school-age children. Understanding the potential role of gut microbiota in MetS and T2DM pathophysiology from early stages of life might contribute to innovative gut microbiome-based interventions that may improve public health. The main objective of the present study was to characterize and compare gut bacteria of T2DM and MetS children against control subjects and determine which microorganisms might be potentially related with cardiometabolic risk factors to propose gut microbial biomarkers that characterize these conditions for future development of pre-diagnostic tools.ResultsStool samples from 21 children with T2DM, 25 with MetS, and 20 controls (n = 66) were collected and processed to conduct 16S rDNA gene sequencing. α- and β-diversity were studied to detect microbial differences among studied groups. Spearman correlation was used to analyze possible associations between gut microbiota and cardiometabolic risk factors, and linear discriminant analyses (LDA) were conducted to determine potential gut bacterial biomarkers. T2DM and MetS showed significant changes in their gut microbiota at genus and family level. Read relative abundance of Faecalibacterium and Oscillospora was significantly higher in MetS and an increasing trend of Prevotella and Dorea was observed from the control group towards T2DM. Positive correlations were found between Prevotella, Dorea, Faecalibacterium, and Lactobacillus with hypertension, abdominal obesity, high glucose levels, and high triglyceride levels. LDA demonstrated the relevance of studying least abundant microbial communities to find specific microbial communities that were characteristic of each studied health condition.ConclusionsGut microbiota was different at family and genus taxonomic levels among controls, MetS, and T2DM study groups within children from 7 to 17 years old, and some communities seemed to be correlated with relevant subjects' metadata. LDA helped to find potential microbial biomarkers, providing new insights regarding pediatric gut microbiota and its possible use in the future development of gut microbiome-based predictive algorithms.

Dataset Information

Characterization of Large Copy Number Variation in Mexican Type 2 Diabetes subjects.

Publications

Characterization of Large Copy Number Variation in Mexican Type 2 Diabetes subjects.

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