Adipose Co-expression networks across Finns and Mexicans identify novel triglyceride-associated genes

Autor: Haas Blake E, Horvath Steve, Pietiläinen Kirsi H, Cantor Rita M, Nikkola Elina, Weissglas-Volkov Daphna, Rissanen Aila, Civelek Mete, Cruz-Bautista Ivette, Riba Laura, Kuusisto Johanna, Kaprio Jaakko, Tusie-Luna Teresa, Laakso Markku, Aguilar-Salinas Carlos A, Pajukanta Päivi
Jazyk: angličtina
Rok vydání: 2012
Předmět:
Zdroj: BMC Medical Genomics, Vol 5, Iss 1, p 61 (2012)
Druh dokumentu: article
ISSN: 1755-8794
DOI: 10.1186/1755-8794-5-61
Popis: Abstract Background High serum triglyceride (TG) levels is an established risk factor for coronary heart disease (CHD). Fat is stored in the form of TGs in human adipose tissue. We hypothesized that gene co-expression networks in human adipose tissue may be correlated with serum TG levels and help reveal novel genes involved in TG regulation. Methods Gene co-expression networks were constructed from two Finnish and one Mexican study sample using the blockwiseModules R function in Weighted Gene Co-expression Network Analysis (WGCNA). Overlap between TG-associated networks from each of the three study samples were calculated using a Fisher’s Exact test. Gene ontology was used to determine known pathways enriched in each TG-associated network. Results We measured gene expression in adipose samples from two Finnish and one Mexican study sample. In each study sample, we observed a gene co-expression network that was significantly associated with serum TG levels. The TG modules observed in Finns and Mexicans significantly overlapped and shared 34 genes. Seven of the 34 genes (ARHGAP30, CCR1, CXCL16, FERMT3, HCST, RNASET2, SELPG) were identified as the key hub genes of all three TG modules. Furthermore, two of the 34 genes (ARHGAP9, LST1) reside in previous TG GWAS regions, suggesting them as the regional candidates underlying the GWAS signals. Conclusions This study presents a novel adipose gene co-expression network with 34 genes significantly correlated with serum TG across populations.
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