ArticlePeerJ2017
BMI prediction within a Korean population.
Article in PeerJ, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- Identifying BMI-associated genes via a genome-wide multi-omics integrative approach using summary data.Human molecular genetics · 2024Pooled it
- Article
- 3D genomic features across >50 diverse cell types reveal insights into the genomic architecture of childhood obesity.medRxiv : the preprint server for health sciences · 2024Article
- Influence of the Brain-Derived Neurotrophic Factor Gene Polymorphism on Weight Loss Following Intragastric Balloon Intervention: A Cross-Sectional Study.Diabetes, metabolic syndrome and obesity : targets and therapy · 2024Article
- Fine Mapping of theFrontiers in genetics · 2022Article
- Molecular modelling of novel ADCY3 variant predicts a molecular target for tackling obesity.International journal of molecular medicine · 2022Article
- Body mass index but not genetic risk is longitudinally associated with altered structural brain parameters.Scientific reports · 2021Article
- Genotype-expression interactions for BDNF across human brain regions.BMC genomics · 2021Article
- Prediction of cholesterol ratios within a Korean population.Royal Society open science · 2018Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBody Mass Index (BMI) is widely regarded as an important clinical trait for obesity and other diseases such as Type 2 diabetes, coronary heart disease, and osteoarthritis.
methodsThis study uses 6,011 samples of genotype data from ethnic Korean subjects. The data was retrieved from the Korea Association Resource. To identify the BMI-related markers within the Korean population, we collected genome-wide association study (GWAS) markers using a GWAS catalog and also obtained other markers from nearby regions. Of the total 6,011 samples, 5,410 subjects were used as part of a single nucleotide polymorphism (SNP) selection set in order to identify the overlapping BMI-associated SNPs within a 10-fold cross validation.
resultsWe selected nine SNPs ( DISCUSSION: The set of nine SNPs identified in this study may be useful for prospective predictions of BMI.
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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.