Limits...
Coexpression network analysis in abdominal and gluteal adipose tissue reveals regulatory genetic loci for metabolic syndrome and related phenotypes.

Min JL, Nicholson G, Halgrimsdottir I, Almstrup K, Petri A, Barrett A, Travers M, Rayner NW, Mägi R, Pettersson FH, Broxholme J, Neville MJ, Wills QF, Cheeseman J, GIANT ConsortiumMolPAGE ConsortiumAllen M, Holmes CC, Spector TD, Fleckner J, McCarthy MI, Karpe F, Lindgren CM, Zondervan KT - PLoS Genet. (2012)

Bottom Line: The strongest associated module, significantly enriched for immune response-related processes, contained 94/620 (15%) genes with inter-depot differences.In an independent cohort of 145/141 twins with ABD and WB longitudinal expression data, median variability in ABD due to familiality was greater for MetS-associated versus un-associated modules (ABD: 0.48 versus 0.18, P = 0.08; GLU: 0.54 versus 0.20, P = 7.8×10(-4)).Corresponding eSNPs were tested for association with MetS-related phenotypes in two GWAS of >100,000 individuals; rs10282458, affecting expression of RARRES2 (encoding chemerin), was associated with body mass index (BMI) (P = 6.0×10(-4)); and rs2395185, affecting inter-depot differences of HLA-DRB1 expression, was associated with high-density lipoprotein (P = 8.7×10(-4)) and BMI-adjusted waist-to-hip ratio (P = 2.4×10(-4)).

View Article: PubMed Central - PubMed

Affiliation: The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom. jlmin@well.ox.ac.uk

ABSTRACT
Metabolic Syndrome (MetS) is highly prevalent and has considerable public health impact, but its underlying genetic factors remain elusive. To identify gene networks involved in MetS, we conducted whole-genome expression and genotype profiling on abdominal (ABD) and gluteal (GLU) adipose tissue, and whole blood (WB), from 29 MetS cases and 44 controls. Co-expression network analysis for each tissue independently identified nine, six, and zero MetS-associated modules of coexpressed genes in ABD, GLU, and WB, respectively. Of 8,992 probesets expressed in ABD or GLU, 685 (7.6%) were expressed in ABD and 51 (0.6%) in GLU only. Differential eigengene network analysis of 8,256 shared probesets detected 22 shared modules with high preservation across adipose depots (D(ABD-GLU) = 0.89), seven of which were associated with MetS (FDR P<0.01). The strongest associated module, significantly enriched for immune response-related processes, contained 94/620 (15%) genes with inter-depot differences. In an independent cohort of 145/141 twins with ABD and WB longitudinal expression data, median variability in ABD due to familiality was greater for MetS-associated versus un-associated modules (ABD: 0.48 versus 0.18, P = 0.08; GLU: 0.54 versus 0.20, P = 7.8×10(-4)). Cis-eQTL analysis of probesets associated with MetS (FDR P<0.01) and/or inter-depot differences (FDR P<0.01) provided evidence for 32 eQTLs. Corresponding eSNPs were tested for association with MetS-related phenotypes in two GWAS of >100,000 individuals; rs10282458, affecting expression of RARRES2 (encoding chemerin), was associated with body mass index (BMI) (P = 6.0×10(-4)); and rs2395185, affecting inter-depot differences of HLA-DRB1 expression, was associated with high-density lipoprotein (P = 8.7×10(-4)) and BMI-adjusted waist-to-hip ratio (P = 2.4×10(-4)). Since many genes and their interactions influence complex traits such as MetS, integrated analysis of genotypes and coexpression networks across multiple tissues relevant to clinical traits is an efficient strategy to identify novel associations.

Show MeSH

Related in: MedlinePlus

Scatterplot between MM (x-axis) and gene significance (y-axis) for MetS and the six MetS components in the ABD brown module.Gene significance was defined as −log10 pvalue of the probeset-clinical trait association for each gene in the brown module. Gene expression probesets marked in red showed evidence for a cis eQTL, and their eSNPs were examined for association with BMI, HDL and TG (Table 4).
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC3285582&req=5

pgen-1002505-g003: Scatterplot between MM (x-axis) and gene significance (y-axis) for MetS and the six MetS components in the ABD brown module.Gene significance was defined as −log10 pvalue of the probeset-clinical trait association for each gene in the brown module. Gene expression probesets marked in red showed evidence for a cis eQTL, and their eSNPs were examined for association with BMI, HDL and TG (Table 4).

Mentions: To investigate to what extent gene expression probesets identified in the single-gene analyses as associated with MetS were included in the MetS-associated modules, and signified hubgenes, the correlation between MM and gene significance (direct association between gene expression probeset and MetS from single-gene analyses) was calculated for each gene expression probeset (see Methods and [33]). For 862/893 (97%) and 238/335 (71%) of the MetS-associated probesets in ABD (p<0.01, MM>0.36) and GLU (p<0.01, MM>0.41), a significant association with a MetS-associated module eigengene was found (147 probesets were overlapping). For the ABD brown (Pearson ρ>0.41, p<10−36) and the GLU darkgreen modules (Pearson ρ>0.57, p<10−9) most significantly associated with MetS (Table 2), the correlations between gene significance for MetS and the individual MetS components and MM were highly significant (Figure 3, Figure S3). These results imply substantial concordance in results between the two approaches and support the increased power of the network-based approach by reducing the number of tests significantly. A further advantage of the network approach is the identification of distinct functional modules within single-tissue networks that associated with MetS. Genes that fall into these modules were more highly connected than with genes in other modules (Figure S2) and their relevance can be inferred based on the correlation with the eigengene. The MetS-associated modules were enriched for immune response and oxidative phosphorylation pathways consistent with studies showing that adipose tissue secretes factors that regulate energy homeostasis and the immune response and the activation of inflammatory signalling pathways that emerges in the presence of obesity, insulin resistance and T2D [11], [36].


Coexpression network analysis in abdominal and gluteal adipose tissue reveals regulatory genetic loci for metabolic syndrome and related phenotypes.

Min JL, Nicholson G, Halgrimsdottir I, Almstrup K, Petri A, Barrett A, Travers M, Rayner NW, Mägi R, Pettersson FH, Broxholme J, Neville MJ, Wills QF, Cheeseman J, GIANT ConsortiumMolPAGE ConsortiumAllen M, Holmes CC, Spector TD, Fleckner J, McCarthy MI, Karpe F, Lindgren CM, Zondervan KT - PLoS Genet. (2012)

Scatterplot between MM (x-axis) and gene significance (y-axis) for MetS and the six MetS components in the ABD brown module.Gene significance was defined as −log10 pvalue of the probeset-clinical trait association for each gene in the brown module. Gene expression probesets marked in red showed evidence for a cis eQTL, and their eSNPs were examined for association with BMI, HDL and TG (Table 4).
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3285582&req=5

pgen-1002505-g003: Scatterplot between MM (x-axis) and gene significance (y-axis) for MetS and the six MetS components in the ABD brown module.Gene significance was defined as −log10 pvalue of the probeset-clinical trait association for each gene in the brown module. Gene expression probesets marked in red showed evidence for a cis eQTL, and their eSNPs were examined for association with BMI, HDL and TG (Table 4).
Mentions: To investigate to what extent gene expression probesets identified in the single-gene analyses as associated with MetS were included in the MetS-associated modules, and signified hubgenes, the correlation between MM and gene significance (direct association between gene expression probeset and MetS from single-gene analyses) was calculated for each gene expression probeset (see Methods and [33]). For 862/893 (97%) and 238/335 (71%) of the MetS-associated probesets in ABD (p<0.01, MM>0.36) and GLU (p<0.01, MM>0.41), a significant association with a MetS-associated module eigengene was found (147 probesets were overlapping). For the ABD brown (Pearson ρ>0.41, p<10−36) and the GLU darkgreen modules (Pearson ρ>0.57, p<10−9) most significantly associated with MetS (Table 2), the correlations between gene significance for MetS and the individual MetS components and MM were highly significant (Figure 3, Figure S3). These results imply substantial concordance in results between the two approaches and support the increased power of the network-based approach by reducing the number of tests significantly. A further advantage of the network approach is the identification of distinct functional modules within single-tissue networks that associated with MetS. Genes that fall into these modules were more highly connected than with genes in other modules (Figure S2) and their relevance can be inferred based on the correlation with the eigengene. The MetS-associated modules were enriched for immune response and oxidative phosphorylation pathways consistent with studies showing that adipose tissue secretes factors that regulate energy homeostasis and the immune response and the activation of inflammatory signalling pathways that emerges in the presence of obesity, insulin resistance and T2D [11], [36].

Bottom Line: The strongest associated module, significantly enriched for immune response-related processes, contained 94/620 (15%) genes with inter-depot differences.In an independent cohort of 145/141 twins with ABD and WB longitudinal expression data, median variability in ABD due to familiality was greater for MetS-associated versus un-associated modules (ABD: 0.48 versus 0.18, P = 0.08; GLU: 0.54 versus 0.20, P = 7.8×10(-4)).Corresponding eSNPs were tested for association with MetS-related phenotypes in two GWAS of >100,000 individuals; rs10282458, affecting expression of RARRES2 (encoding chemerin), was associated with body mass index (BMI) (P = 6.0×10(-4)); and rs2395185, affecting inter-depot differences of HLA-DRB1 expression, was associated with high-density lipoprotein (P = 8.7×10(-4)) and BMI-adjusted waist-to-hip ratio (P = 2.4×10(-4)).

View Article: PubMed Central - PubMed

Affiliation: The Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom. jlmin@well.ox.ac.uk

ABSTRACT
Metabolic Syndrome (MetS) is highly prevalent and has considerable public health impact, but its underlying genetic factors remain elusive. To identify gene networks involved in MetS, we conducted whole-genome expression and genotype profiling on abdominal (ABD) and gluteal (GLU) adipose tissue, and whole blood (WB), from 29 MetS cases and 44 controls. Co-expression network analysis for each tissue independently identified nine, six, and zero MetS-associated modules of coexpressed genes in ABD, GLU, and WB, respectively. Of 8,992 probesets expressed in ABD or GLU, 685 (7.6%) were expressed in ABD and 51 (0.6%) in GLU only. Differential eigengene network analysis of 8,256 shared probesets detected 22 shared modules with high preservation across adipose depots (D(ABD-GLU) = 0.89), seven of which were associated with MetS (FDR P<0.01). The strongest associated module, significantly enriched for immune response-related processes, contained 94/620 (15%) genes with inter-depot differences. In an independent cohort of 145/141 twins with ABD and WB longitudinal expression data, median variability in ABD due to familiality was greater for MetS-associated versus un-associated modules (ABD: 0.48 versus 0.18, P = 0.08; GLU: 0.54 versus 0.20, P = 7.8×10(-4)). Cis-eQTL analysis of probesets associated with MetS (FDR P<0.01) and/or inter-depot differences (FDR P<0.01) provided evidence for 32 eQTLs. Corresponding eSNPs were tested for association with MetS-related phenotypes in two GWAS of >100,000 individuals; rs10282458, affecting expression of RARRES2 (encoding chemerin), was associated with body mass index (BMI) (P = 6.0×10(-4)); and rs2395185, affecting inter-depot differences of HLA-DRB1 expression, was associated with high-density lipoprotein (P = 8.7×10(-4)) and BMI-adjusted waist-to-hip ratio (P = 2.4×10(-4)). Since many genes and their interactions influence complex traits such as MetS, integrated analysis of genotypes and coexpression networks across multiple tissues relevant to clinical traits is an efficient strategy to identify novel associations.

Show MeSH
Related in: MedlinePlus