Left ventricular mass (LVM) is an important clinical phenotype, whose assessment
can predict adverse cardiovascular events and premature death in all genders,
races, and ages. Increase in LVM defines left ventricular hypertrophy (LVH) with
the thickening of the left ventricle of the heart. In community-based cohorts, the
presence of left ventricular hypertrophy (LVH) and increased LVM predict the
development of coronary heart disease, congestive heart failure, stroke, and
cardiovascular disease. Thus this trait serves not only as measures of cardiac
structure, but also as intermediate phenotype for clinical cardiovascular disease
outcome. Several studies have indicated that LVM is influenced by genetic factors.
Genome wide linkage and association studies in diverse population have been
performed to identify genes influencing LVM, but much of the heritability remains
unexplained, the identity of the underlying gene pathways and functional variants
remain unknown, and the promise of genetically based risk prediction remains
unfulfilled.
The aim of the study was to investigate the association of common genetic variants
with left ventricular mass using a genome wide approach in a large cohort of never
treated mild-to-moderate essential hypertensive subjects. From the linear analysis,
we selected 85 single nucleotide polymorphisms (SNPs), with a suggestive p-value
of association with LVM ( 64 10-5). In particular, some SNPs lying in genes
previously described as having a role in the pathogenesis of cardiac hypertrophy,
such as ROCK1, IGF1, CACNA1D, FGFR1, TRAF5, SOX5, and KSR2. Each of
them might play a putative role in determining the LVM phenotype as well as other
pathophysiological pathways directly or indirectly linked to cardiac pathophysiology.
To assess the risk alleles associated to the most interesting findings in relation to
the phenotype studied, we performed a case-control analysis by dividing our
sample in two subsets according to LVM values. Most of the SNPs associated with
LVM in linear regression presented a significant association, showing that the
carriers of the risk alleles have an odds ratio higher than 1 to have increased LVM,
i.e. to be cases respect to controls. Nevertheless as for most of the complex traits,
the observed odds ratios are modest (except for those biased by the absence of
homozygous risk genotypes), so their relevance for a clinical use is uncertain.
Thus, we defined a weighted genetic risk score using the effect size of the risk
allele (beta value of the linear regression analysis) to account for the strength of
the genetic association with each allele. The possibility to combine more variants in
a global genetic risk score could be interesting and could add relevance to the
results.
In conclusion, our GWAS allowed us to pinpoint genes whose role in heart function
and/or cardiac hypertrophy has been demonstrated in previously publications by
different authors. Moreover, we highlighted the usefulness of an aggregate
measure of risk of LVH to discriminate high-risk subjects. However, the results
must be interpreted within the context of some potential limitations and
perspectives. No SNPs reached a Bonferroni\u2019s significance level probably due to a
limited sample size. However, the phenotypic homogeneity of our cohort and the
absence of previous antihypertensive treatment are prerequisites for the
identification of true genetic effects. A replication in independent cohorts is needed
VII
to further confirm the findings; however an independent cohort with similar criteria
was not available for replication. Moreover, it often happens, as in our study, the
significant SNPs map in non-coding regions, making it difficult to explain their
causative role. These limitations should not reduce the relevance of the genes
identified and confirmed by previously published papers.
Future perspectives of this study should be the replication of the GWAS findings in
independent cohorts and the assessment in independent samples of the prediction
ability of wGRS to correctly classify true positives and true negatives according to
their genetic background
