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. 2010 Feb;208(2):412-20.
doi: 10.1016/j.atherosclerosis.2009.11.035. Epub 2009 Dec 2.

Clear detection of ADIPOQ locus as the major gene for plasma adiponectin: results of genome-wide association analyses including 4659 European individuals

Iris M Heid  1 , Peter Henneman, Andrew Hicks, Stefan Coassin, Thomas Winkler, Yurii S Aulchenko, Christian Fuchsberger, Kijoung Song, Marie-France Hivert, Dawn M Waterworth, Nicholas J Timpson, J Brent Richards, John R B Perry, Toshiko Tanaka, Najaf Amin, Barbara Kollerits, Irene Pichler, Ben A Oostra, Barbara Thorand, Rune R Frants, Thomas Illig, Josée Dupuis, Beate Glaser, Tim Spector, Jack Guralnik, Josephine M Egan, Jose C Florez, David M Evans, Nicole Soranzo, Stefania Bandinelli, Olga D Carlson, Timothy M Frayling, Keith Burling, George Davey Smith, Vincent Mooser, Luigi Ferrucci, James B Meigs, Peter Vollenweider, Ko Willems van Dijk, Peter Pramstaller, Florian Kronenberg, Cornelia M van Duijn
Affiliations

Clear detection of ADIPOQ locus as the major gene for plasma adiponectin: results of genome-wide association analyses including 4659 European individuals

Iris M Heid et al. Atherosclerosis. 2010 Feb.

Abstract

Objective: Plasma adiponectin is strongly associated with various components of metabolic syndrome, type 2 diabetes and cardiovascular outcomes. Concentrations are highly heritable and differ between men and women. We therefore aimed to investigate the genetics of plasma adiponectin in men and women.

Methods: We combined genome-wide association scans of three population-based studies including 4659 persons. For the replication stage in 13795 subjects, we selected the 20 top signals of the combined analysis, as well as the 10 top signals with p-values less than 1.0 x 10(-4) for each the men- and the women-specific analyses. We further selected 73 SNPs that were consistently associated with metabolic syndrome parameters in previous genome-wide association studies to check for their association with plasma adiponectin.

Results: The ADIPOQ locus showed genome-wide significant p-values in the combined (p=4.3 x 10(-24)) as well as in both women- and men-specific analyses (p=8.7 x 10(-17) and p=2.5 x 10(-11), respectively). None of the other 39 top signal SNPs showed evidence for association in the replication analysis. None of 73 SNPs from metabolic syndrome loci exhibited association with plasma adiponectin (p>0.01).

Conclusions: We demonstrated the ADIPOQ gene as the only major gene for plasma adiponectin, which explains 6.7% of the phenotypic variance. We further found that neither this gene nor any of the metabolic syndrome loci explained the sex differences observed for plasma adiponectin. Larger studies are needed to identify more moderate genetic determinants of plasma adiponectin.

Keywords: adiponectin; cardiovascular disease; genome-wide association study; metabolic syndrome; polymorphism.

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Figures

Figure 1
Figure 1
Study design illustrating the genome-wide association (GWA) study approach and the candidate gene approach.
Figure 2
Figure 2
The analyses in panel A-C are provided for the combined sex analysis as well as the analysis stratified for women and men. A. Manhattan plots showing p-values of association of each SNPs in the meta-analysis with plasma adiponectin levels. SNPs are plotted on the X-axis to their position on each chromosome against association with plasma adiponectin on the Y-axis (shown as −log10 P-value). B. Regional Manhattan plots showing significance of association of all SNPs in the ADIPOQ region (3q27). SNPs are plotted on the X-axis to their position on chromosome 3 against association with plasma adiponectin on the Y-axis (shown as −log10 P-value). In each panel, the top-SNP rs17366568 is shown as red diamond. The SNPs surrounding this top-SNP are color-coded (see inset) to reflect their LD with the top-SNP using pair-wise r2 values from the KORA study. Estimated recombination rates from HapMap-CEU are plotted in blue to illustrate the local LD structure on a secondary Y-axis. Genes and their direction of transcription are provided below the plots using data from the UCSC genome browser. C. Quantile-quantile (QQ) plots of SNPs. Expected p-values are plotted on X-axis against the observed p-values plotted on the Y-axis.
Figure 3
Figure 3
Linkage disequilibrium (LD) plot of SNPs in the ADIPOQ region spanning 50kb (positions 188030-188080kb). The grey shading of the diamonds represent the pair-wise D′ and the numbers in the diamonds represent the pair-wise r2 between the two SNPs defined by the top left and the top right sides of the diamond. The figure clearly shows that the top-hit rs17366568 is located within an own LD block and shows virtually no correlations with any other SNP in the entire 50kb region. The columns on the right side of the Figure show i) whether a particular SNP is genotyped by the Affymetrix 500K chip (A) or the Illumina HumanHap300 chip (I); all other SNPs are imputed; ii) the z-scores and iii) the p-values for each SNP-adiponection association for the combined analysis of the cohorts ERF, KORA and MICROS; iv) SNPs that are correlated with an r2>0.60 are grouped in groups 1-9.
Figure 4
Figure 4
Predicted regulatory regions in the ADIPOQ downstream region and their affection by copy number variations. Panel A: Genomatix Software Suite: Position of the regulatory promoter regions predicted by PromoterInspector (red boxes) and their position relative the ADIPOQ gene region (green box). Panel B: UCSC Browser: Position of the predicted regulatory regions (red boxes) relative to known copy number variations in the ADIPOQ gene region (represented by bold blue lines). The numbers on the left side correspond to the accession number of the respective copy number variation in the Database of Genomic Variants.
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