ArticleObesity (Silver Spring, Md.)2013
QTL-based association analyses reveal novel genes influencing pleiotropy of metabolic syndrome (MetS).
Article in Obesity (Silver Spring, Md.), 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it, 19 citations in OpenAlex.
- Epigenome-wide meta-analysis of BMI in nine cohorts: Examining the utility of epigenetically predicted BMI.American journal of human genetics · 2023Pooled it
- Evidence of a novel gene locusPhysiological genomics · 2025Article
- Multipartite network analysis to identify environmental and genetic associations of metabolic syndrome in the Korean population.Scientific reports · 2024Article
- A Novel GenebioRxiv : the preprint server for biology · 2024Article
- Systemic Blood Proteome Patterns Reflect Disease Phenotypes in Neovascular Age-Related Macular Degeneration.International journal of molecular sciences · 2023Article
- Genomic characterization of the world's longest selection experiment in mouse reveals the complexity of polygenic traits.BMC biology · 2022Article
- Innate-Immunity Genes in Obesity.Journal of personalized medicine · 2021Review
- Tumor Necrosis Receptor Superfamily Interact with Fusion and Fission of Mitochondria of Adipose Tissue in Obese Patients without Type 2 Diabetes.Biomedicines · 2021Article
- Association study between a polymorphic poly-T repeat sequence in the promoter of the somatostatin gene and metabolic syndrome.BMC medical genetics · 2018Article
- A GWA study reveals genetic loci for body conformation traits in Chinese Laiwu pigs and its implications for human BMI.Mammalian genome : official journal of the International Mammalian Genome Society · 2016Article
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Corrections and comments
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Authors and funding
14 authors at 2 institutions in 2 countries.
Funding
Abstract
objectiveMetabolic Syndrome (MetS) is a phenotype cluster predisposing to type 2 diabetes and cardiovascular disease. We conducted a study to elucidate the genetic basis underlying linkage signals for multiple representative traits of MetS that we had previously identified at two significant QTLs on chromosomes 3q27 and 17p12. DESIGN AND
methodsWe performed QTL-specific genomic and transcriptomic analyses in 1,137 individuals from 85 extended families that contributed to the original linkage. We tested in SOLAR association of MetS phenotypes with QTL-specific haplotype-tagging SNPs as well as transcriptional profiles of peripheral blood mononuclear cells (PBMCs).
resultsSNPs significantly associated with MetS phenotypes under the prior hypothesis of linkage mapped to seven genes at 3q27 and seven at 17p12. Prioritization based on biologic relevance, SNP association, and expression analyses identified two genes: insulin-like growth factor 2 mRNA-binding protein 2 (IGF2BP2) at 3q27 and tumor necrosis factor receptor 13B (TNFRSF13B) at 17p12. Prioritized genes could influence cell-cell adhesion and adipocyte differentiation, insulin/glucose responsiveness, cytokine effectiveness, plasma lipid levels, and lipoprotein densities.
conclusionsUsing an approach combining genomic, transcriptomic, and bioinformatic data we identified novel candidate genes for MetS.
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