Identification of novel genes whose expression in adipose tissue affects body fat mass and distribution: an RNA-Seq and Mendelian Randomization study.
Stefan KonigorskiJürgen JankeGiannino PatoneManuela M BergmannChristoph LippertNorbert HübnerRudolf KaaksHeiner BoeingTobias PischonPublished in: European journal of human genetics : EJHG (2022)
Many studies have shown that abdominal adiposity is more strongly related to health risks than peripheral adiposity. However, the underlying pathways are still poorly understood. In this cross-sectional study using data from RNA-sequencing experiments and whole-body MRI scans of 200 participants in the EPIC-Potsdam cohort, our aim was to identify novel genes whose gene expression in subcutaneous adipose tissue has an effect on body fat mass (BFM) and body fat distribution (BFD). The analysis identified 625 genes associated with adiposity, of which 531 encode a known protein and 487 are novel candidate genes for obesity. Enrichment analyses indicated that BFM-associated genes were characterized by their higher than expected involvement in cellular, regulatory and immune system processes, and BFD-associated genes by their involvement in cellular, metabolic, and regulatory processes. Mendelian Randomization analyses suggested that the gene expression of 69 genes was causally related to BFM and BFD. Six genes were replicated in UK Biobank. In this study, we identified novel genes for BFM and BFD that are BFM- and BFD-specific, involved in different molecular processes, and whose up-/downregulated gene expression may causally contribute to obesity.
Keyphrases
- gene expression
- insulin resistance
- genome wide
- bioinformatics analysis
- adipose tissue
- genome wide identification
- rna seq
- dna methylation
- cross sectional
- metabolic syndrome
- single cell
- weight gain
- type diabetes
- transcription factor
- magnetic resonance imaging
- high fat diet
- computed tomography
- machine learning
- poor prognosis
- electronic health record
- deep learning
- high fat diet induced
- artificial intelligence