title: Comparative analysis of the human hepatic and adipose tissue transcriptomes during LPS-induced inflammation leads to the identification of differential biological pathways and candidate biomarkers.
abstract: BACKGROUND
  Insulin resistance (IR) is accompanied by chronic low grade systemic inflammation, obesity, and deregulation of total body energy homeostasis. We induced inflammation in adipose and liver tissues in vitro in order to mimic inflammation in vivo with the aim to identify tissue-specific processes implicated in IR and to find biomarkers indicative for tissue-specific IR.
  
  
  METHODS
  Human adipose and liver tissues were cultured in the absence or presence of LPS and DNA Microarray Technology was applied for their transcriptome analysis. Gene Ontology (GO), gene functional analysis, and prediction of genes encoding for secretome were performed using publicly available bioinformatics tools (DAVID, STRING, SecretomeP). The transcriptome data were validated by proteomics analysis of the inflamed adipose tissue secretome.
  
  
  RESULTS
  LPS treatment significantly affected 667 and 483 genes in adipose and liver tissues respectively. The GO analysis revealed that during inflammation adipose tissue, compared to liver tissue, had more significantly upregulated genes, GO terms, and functional clusters related to inflammation and angiogenesis. The secretome prediction led to identification of 399 and 236 genes in adipose and liver tissue respectively. The secretomes of both tissues shared 66 genes and the remaining genes were the differential candidate biomarkers indicative for inflamed adipose or liver tissue. The transcriptome data of the inflamed adipose tissue secretome showed excellent correlation with the proteomics data.
  
  
  CONCLUSIONS
  The higher number of altered proinflammatory genes, GO processes, and genes encoding for secretome during inflammation in adipose tissue compared to liver tissue, suggests that adipose tissue is the major organ contributing to the development of systemic inflammation observed in IR. The identified tissue-specific functional clusters and biomarkers might be used in a strategy for the development of tissue-targeted treatment of insulin resistance in patients.
authors: Centre for Medical Biomics, University Medical Centre Groningen (UMCG), University of Groningen, Antonius Deusinglaan 1, 9713 AV Groningen, The Netherlands. ewa.szalowska@wur.nl
authors: Ewa
authors: E
authors: Szalowska
authors: Martijn
authors: M
authors: Dijkstra
authors: Marieke G L
authors: MG
authors: Elferink
authors: Desiree
authors: D
authors: Weening
authors: Marcel
authors: M
authors: de Vries
authors: Marcel
authors: M
authors: Bruinenberg
authors: Annemieke
authors: A
authors: Hoek
authors: Han
authors: H
authors: Roelofsen
authors: Geny M M
authors: GM
authors: Groothuis
authors: Roel J
authors: RJ
authors: Vonk
mesh_terms: D000273:Adipose Tissue / Q000378:metabolism*; D000293:Adolescent; D000328:Adult; D015415:Biomarkers / Q000378:metabolism*; D002478:Cells, Cultured; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D007249:Inflammation / Q000139:chemically induced* / Q000209:etiology / Q000235:genetics* / Q000378:metabolism; D007333:Insulin Resistance / Q000235:genetics; D008070:Lipopolysaccharides; D008099:Liver / Q000378:metabolism*; D008297:Male; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D040901:Proteomics; D015398:Signal Transduction / Q000235:genetics; D059467:Transcriptome
chemical_list: D015415:Biomarkers; D008070:Lipopolysaccharides