Related Experiment Video
Updated: Jun 3, 2026
Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
Published on: May 6, 2022
Differential coexpression analysis of obesity-associated networks in human subcutaneous adipose tissue
A J Walley1, P Jacobson, M Falchi
1Department of Genomics of Common Disease, School of Public Health, Imperial College London, Hammersmith Hospital, London, UK.
Objective:
To use a unique obesity-discordant sib-pair study design to combine differential expression analysis, expression quantitative trait loci (eQTLs) mapping and a coexpression regulatory network approach in subcutaneous human adipose tissue to identify genes relevant to the obese state.
Study Design:
Genome-wide transcript expression in subcutaneous human adipose tissue was measured using Affymetrix U133 Plus 2.0 microarrays (Affymetrix, Santa Clara, CA, USA), and genome-wide genotyping data was obtained using an Applied Biosystems (Applied Biosystems; Life Technologies, Carlsbad, CA, USA) SNPlex linkage panel.
Subjects:
A total of 154 Swedish families ascertained through an obese proband (body mass index (BMI) >30 kg m(-2)) with a discordant sibling (BMI>10 kg m(-2) less than proband).
Results:
Approximately one-third of the transcripts were differentially expressed between lean and obese siblings. The cellular adhesion molecules (CAMs) KEGG grouping contained the largest number of differentially expressed genes under cis-acting genetic control. By using a novel approach to contrast CAMs coexpression networks between lean and obese siblings, a subset of differentially regulated genes was identified, with the previously GWAS obesity-associated neuronal growth regulator 1 (NEGR1) as a central hub. Independent analysis using mouse data demonstrated that this finding of NEGR1 is conserved across species.
Conclusion:
Our data suggest that in addition to its reported role in the brain, NEGR1 is also expressed in subcutaneous adipose tissue and acts as a central 'hub' in an obesity-related transcript network.
