Level D· Scientific groundwork from lab and animal studiesAnimal StudyEurope PMCOpen access

An integrative systems genetics approach reveals potential causal genes and pathways related to obesity

Kogelman LJ., Zhernakova DV., Westra HJ., Cirera S., Fredholm M., Franke L.

Animal Study on Hip, published in Genome Med (2015) — summary generated from the PubMed abstract.

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Level D· Scientific groundwork from lab and animal studiesEvidence level of this study

Evidence from laboratory and animal studies provides groundwork for understanding mechanisms and potential before human studies continue.

  • Level A · Stronger Clinical Evidence
  • Level B · Emerging clinical evidence with positive signals
  • Level C · Early human research exploring benefits
  • Level D · Scientific groundwork from lab and animal studies
  • Emerging · Emerging topic under active research
Read the A–D evidence level guide

This page is generated from the PubMed record. The Thai description is an automated summary of bibliographic fields and the abstract, not a full translation, and is not medical advice.

Study type
Animal Study
Journal
Genome Med (2015)
Reported sample size
—
Source database
Europe PMC
PMID
26482556
PMCID
PMC4617184
DOI
10.1186/s13073-015-0229-0
Citations
32

Abstract (original English)

Background Obesity is a multi-factorial health problem in which genetic factors play an important role. Limited results have been obtained in single-gene studies using either genomic or transcriptomic data. RNA sequencing technology has shown its potential in gaining accurate knowledge about the transcriptome, and may reveal novel genes affecting complex diseases. Integration of genomic and transcriptomic variation (expression quantitative trait loci [eQTL] mapping) has identified causal variants that affect complex diseases. We integrated transcriptomic data from adipose tissue and genomic data from a porcine model to investigate the mechanisms involved in obesity using a systems genetics approach. Methods Using a selective gene expression profiling approach, we selected 36 animals based on a previously created genomic Obesity Index for RNA sequencing of subcutaneous adipose tissue. Differential expression analysis was performed using the Obesity Index as a continuous variable in a linear model. eQTL mapping was then performed to integrate 60 K porcine SNP chip data with the RNA sequencing data. Results were restricted based on genome-wide significant single nucleotide polymorphisms, detected differentially expressed genes, and previously detected co-expressed gene modules. Further data integration was performed by detecting co-expression patterns among eQTLs and integration w

What this study does not prove

  • • This study does not prove SVF is an approved treatment or a replacement for standard care.
  • • This is preclinical work; animal or laboratory results cannot be applied to humans.

Evidence level

Evidence from laboratory and animal studies provides groundwork for understanding mechanisms and potential before human studies continue.

How we grade evidence
Adipose TissueAnimalsSwineObesityGenetic Predisposition to DiseaseGene Expression ProfilingSequence Analysis, RNAGenomicsPolymorphism, Single NucleotideQuantitative Trait Loci

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