ArticleBMC bioinformatics2017
Ultra-high dimensional variable selection with application to normative aging study: DNA methylation and metabolic syndrome.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
5 citing papers in PubMed, 9 citations in OpenAlex.
- High-dimensional randomization-based inference capitalizing on classical design and modern computing.Behaviormetrika · 2023Article
- ABCA1 and ABCG1 DNA methylation in epicardial adipose tissue of patients with coronary artery disease.BMC cardiovascular disorders · 2021Article
- Hypermethylation in Calca Promoter Inhibited ASC Osteogenic Differentiation in Rats with Type 2 Diabetic Mellitus.Stem cells international · 2020Article
- Integrated analysis of the gene expression profile and DNA methylation profile of obese patients with type 2 diabetes.Molecular medicine reports · 2018Article
- Epigenome-wide association study of metabolic syndrome in African-American adults.Clinical epigenetics · 2018Article
Corrections and comments
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Authors and funding
14 authors at 5 institutions in 3 countries.
Funding
Abstract
backgroundMetabolic syndrome has become a major public health challenge worldwide. The association between metabolic syndrome and DNA methylation is of great research interest.
resultsWe constructed a binomial model to investigate the association between a metabolic syndrome index and DNA methylation in the Normative Aging Study. We applied the Iterative Sure Independence Screening (ISIS) method with elastic net penalty to DNA methylation levels at 484,548 CpG markers from 659 human subjects, and demonstrated that the screening step in ISIS can significantly improve the performance of the elastic net.
conclusionThe proposed method identifies four CpGs which can be mapped to two biologically relevant and functional genes. Identification of significant CpG markers may potentially have practical implications for disease prevention and treatment.
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Registered trials
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.