Intro:
Although up to 60% of left ventricular mass (LVM) can be accounted for by extra-cardiac factors, the cause of remaining variance is uncharacterised.
Hypothesis:
Cardiac gene expression is under genetic control and these genetic effects account, at least in part, for the uncharacterised component of LVM.
Method:
We combined genetic linkage analysis with genome-wide expression profiling in a recombinant inbred (RI) rat strain panel to map the genetic determinants of cardiac gene expression, taking into account naturally occurring variation in blood pressure. Cardiac gene expression in 29 RI strains was quantified with 128 Affymetrix 230 2.0 microarrays, and linkage analysis of gene expression was performed with correction for multiple testing. Candidate genes for LVM were defined as gene colocalised with regions of the rat genome previously associated with LVM. Candidate genes identified in the rat were prioritised by assessing whether their human orthologues were dynamically regulated in heart biopsies from patients with cardiac hypertrophy undergoing surgery for aortic stenosis (
n
=20) as compared to controls (
n
=7), as determined with Affymetrix U133 microarrays.
Results:
We showed that genetic regulation of cardiac transcription is predominant when compared to extra-cardiac effects. This enabled us to determine the major control points of cardiac gene expression in the rat (
n
=3,744, genome-wide
P
<0.05). A subset of 50 genes that mapped to themselves and colocalised with regions of the rat genome known to regulate LVM were identified. One of these 50 rat genes was mimecan or osteoglycin precursor (
Ogn
), whose orthologue showed the highest correlation with LVM out of the 22,284 probesets used in the human microarray analysis (
r
=0.62,
P
=0.0008). We went on to refine the rat QTL associated with
Ogn
(peak LOD 4), and identified sequence variations that might be causative. We then showed that cardiac protein levels of OGN are increased in both rat and human hypertrophy.
Conc:
Combined linkage and expression studies provide a new and powerful systems approach to dissecting the pathophysiology of genetically complex traits. These data implicate
Ogn
as a primary genetic driver and biomarker of cardiac hypertrophy and warrant further functional testing.
The sumLINK statistic for genetic linkage analysis in the presence of heterogeneity
