ArticleEuropean journal of human genetics : EJHG2014
Controversial association results for INSIG2 on body mass index may be explained by interactions with age and with MC4R.
Article in European journal of human genetics : EJHG, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed.
- Article
- A comprehensive review of genetic causes of obesity.World journal of pediatrics : WJP · 2024Review
- Impact of Genetic Variations and Epigenetic Mechanisms on the Risk of Obesity.International journal of molecular sciences · 2020Review
- Tumour biology of obesity-related cancers: understanding the molecular concept for better diagnosis and treatment.Tumour biology : the journal of the International Society for Oncodevelopmental Biology and Medicine · 2016Review
- Practical Experience of the Application of a Weighted Burden Test to Whole Exome Sequence Data for Obesity and Schizophrenia.Annals of human genetics · 2016Article
- Polymorphism of the FTO Gene Influences Body Weight in Children with Type 1 Diabetes without Severe Obesity.International journal of endocrinology · 2014Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
Among the single-nucleotide polymorphisms (SNPs) previously reported to be associated with body mass index (BMI) and obesity, we focus on a common risk variant rs7566605 upstream of the insulin-induced gene 2 (INSIG2) gene and a rare protective variant rs2229616 on the melanocortin-4 receptor (MC4R) gene. INSIG2 is involved in adipogenesis and MC4R effects hormonal appetite control in response to the amount of adipose tissue. The influence of rs2229616 (MC4R) on BMI and obesity has been confirmed repeatedly and insight into the underlying mechanism provided. However, a main effect of rs7566605 (INSIG2) is under debate because of inconsistent replications of association. Interaction of rs7566605 with age may offer an explanation. SNP-age and SNP-SNP interaction models were tested on independent individuals from three population-based longitudinal cohorts, restricting the analysis to an observed age of 25-74 years. KORA S3/F3, KORA S4/F4 (Augsburg, Germany, 1994-2005, 1999-2008), and Framingham-Offspring data (Framingham, USA, 1971-2001) were analysed, with a total sample size of N=6926 in the joint analysis. The effect of interaction between rs7566605 and age on BMI and obesity status is significant and consistent across studies. This new evidence for rs7566605 (INSIG2) complements previous research. In addition, the interaction effect of rs7566605 with the MC4R variant rs2229616 on BMI was observed. This effect size was three times larger than that in a previously reported single-locus main effect of rs2229616. This leads to the conclusion that SNP-age or SNP-SNP interactions can mask genetic effects for complex diseases if left unaccounted for.
Indexed as
Identifiers
What OpenQuestion holds
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.