ArticleScientific reports2017
Characterization of Large Copy Number Variation in Mexican Type 2 Diabetes subjects.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed, 12 citations in OpenAlex.
- Genetics of type 2 diabetes: Beyond single nucleotide variant studies.Molecular metabolism · 2026Review
- Computational strategies for copy number variation detection, disease association, and beyond.Genome biology · 2026Review
- PScnv: personalized self-normalizing CNV detection with a hierarchical multi-phase framework.Bioinformatics (Oxford, England) · 2026Article
- Dissecting causal relationships between immune cells, blood metabolites, and diabetic nephropathy.Diabetology & metabolic syndrome · 2025Article
- Copy Number Variants Are Ovarian Cancer Risk Alleles at Known and Novel Risk Loci.Journal of the National Cancer Institute · 2022Article
- 22q11.2 microdeletion and increased risk for type 2 diabetes.EClinicalMedicine · 2020Article
- Molecular Variants in Human Trace Amine-Associated Receptors and Their Implications in Mental and Metabolic Disorders.Cellular and molecular neurobiology · 2020Review
- Whole Genome Analyses of Chinese Population and De Novo Assembly of A Northern Han Genome.Genomics, proteomics & bioinformatics · 2019Article
- INDEX-db: The Indian Exome Reference Database (Phase I).Journal of computational biology : a journal of computational molecular cell biology · 2019Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 3 countries.
Funding
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).
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