Serum lipids in the GENECARD study of coronary artery disease identify quantitative trait loci and phenotypic subsets on chromosomes 3q and 5q

Gene by stress genome-wide interaction analysis and path analysis identify EBF1 as a cardiovascular and metabolic risk gene

We performed gene-environment interaction genome-wide association analysis (G × E GWAS) to identify SNPs whose effects on metabolic traits are modified by chronic psychosocial stress in the Multi-Ethnic Study of Atherosclerosis (MESA). In Whites, the G × E GWAS for hip circumference identified five SNPs within the Early B-cell Factor 1 (EBF1) gene, all of which were in strong linkage disequilibrium. The gene-by-stress interaction (SNP × STRESS) term P-values were genome-wide significant (Ps = 7.14E-09 to 2.33E-08, uncorrected; Ps = 1.99E-07 to 5.18E-07, corrected for genomic control). The SNP-only (without interaction) model P-values (Ps = 0.011-0.022) were not significant at the conventional genome-wide significance level. Further analysis of related phenotypes identified gene-by-stress interaction effects for waist circumference, body mass index (BMI), fasting glucose, type II diabetes status, and common carotid intimal-medial thickness (CCIMT), supporting a proposed model of gene-by-stress interaction that connects cardiovascular disease (CVD) risk factor endophenotypes such as central obesity and increased blood glucose or diabetes to CVD itself. Structural equation path analysis suggested that the path from chronic psychosocial stress to CCIMT via hip circumference and fasting glucose was larger (estimate = 0.26, P = 0.033, 95% CI = 0.02-0.49) in the EBF1 rs4704963 CT/CC genotypes group than the same path in the TT group (estimate = 0.004, P = 0.34, 95% CI = -0.004-0.012). We replicated the association of the EBF1 SNPs and hip circumference in the Framingham Offspring Cohort (gene-by-stress term P-values = 0.007-0.012) as well as identified similar path relationships. This observed and replicated interaction between psychosocial stress and variation in the EBF1 gene may provide a biological hypothesis for the complex relationship between psychosocial stress, central obesity, diabetes, and cardiovascular disease.

A study of the role of GATA2 gene polymorphism in coronary artery disease risk traits

The GATA2 is a multi-catalytic transcription factor believed to play an important role in regulating inflammatory processes, largely contributory to cardiovascular-related events. However, its role in coronary artery disease (CAD) risk traits remains poorly understood. In a preliminary study using Affymetrix 250K, we established a link on chromosome (chr) 3, which harbors the GATA2 gene, to early onset of CAD in two families with heterozygous familial hyperlipidemia (HFH), suggesting a role for the gene in metabolic-related CAD in the general population. We then sequenced the gene in the families and an additional 200 individuals in the general population, followed by an association study for 8 SNPs on CAD metabolic risk traits in a total of 4557 individuals (2386 CAD cases versus 2171 angiographed controls) by the Applied Biosystems real-time PCR system. The rs1573949_C [1.15(1.00-1.32); p=0.049] was associated with MI, rs7431368_AA [5.2(1.05-26.60); p=0.43] conferred risk for harboring low high density lipoprotein, and obesity was linked to rs10934857_AA [5.69(1.04-30.98); p=0.045] following Bonferroni corrections and multivariate adjustments for confounders. Furthermore, a haplotype CCCGGGTC (χ(2)=4.23; p=0.04) constructed from the eight studied SNPs and its 6-mer derivative CGGGTC (χ(2)=5.05; p=0.025) were associated with CAD. Obesity was associated with the 6-mer CATAAA (χ(2)=3.66; p=0.049), and hypercholesterolemia was linked to the 8-mer CCTGGACC (χ(2)=6.02; p=0.014), but most significantly so with its 5-mer derivative, CTGGA (χ(2)=6.75; p=0.009). On the other hand, high low density lipoprotein was linked to TGG (χ(2)=4.48; p=0.034). Our study points to an association of GATA2 at both SNP and haplotype levels with important metabolic risk traits for atherosclerosis.

Hypothesis of the neuroendocrine cortisol pathway gene role in the comorbidity of depression, type 2 diabetes, and metabolic syndrome

Depression, type 2 diabetes (T2D), and metabolic syndrome (MetS) are often comorbid. Depression per se increases the risk for T2D by 60%. This risk is not accounted for by the use of antidepressant therapy. Stress causes hyperactivation of the hypothalamic–pituitary–adrenal (HPA) axis, by triggering the hypothalamic corticotropin-releasing hormone (CRH) secretion, which stimulates the anterior pituitary to release the adrenocorticotropin hormone (ACTH), which causes the adrenal secretion of cortisol. Depression is associated with an increased level of cortisol, and CRH and ACTH at inappropriately “normal” levels, that is too high compared to their expected lower levels due to cortisol negative feedback. T2D and MetS are also associated with hypercortisolism. High levels of cortisol can impair mood as well as cause hyperglycemia and insulin resistance and other traits typical of T2D and MetS. We hypothesize that HPA axis hyperactivation may be due to variants in the genes of the CRH receptors (CRHR1, CRHR2), corticotropin receptors (or melanocortin receptors, MC1R-MC5R), glucocorticoid receptor (NR3C1), mineralocorticoid receptor (NR3C2), and of the FK506 binding protein 51 (FKBP5), and that these variants may be partially responsible for the clinical association of depression, T2D and MetS. In this review, we will focus on the correlation of stress, HPA axis hyperactivation, and the possible genetic role of the CRHR1, CRHR2, MCR1–5, NR3C1, and NR3C2 receptors and FKBP5 in the susceptibility to the comorbidity of depression, T2D, and MetS. New studies are needed to confirm the hypothesized role of these genes in the clinical association of depression, T2D, and MetS.

The genetic basis for survivorship in coronary artery disease

Survivorship is a trait characterized by endurance and virility in the face of hardship. It is largely considered a psychosocial attribute developed during fatal conditions, rather than a biological trait for robustness in the context of complex, age-dependent diseases like coronary artery disease (CAD). The purpose of this paper is to present the novel phenotype, survivorship in CAD as an observed survival advantage concurrent with clinically significant CAD. We present a model for characterizing survivorship in CAD and its relationships with overlapping time- and clinically-related phenotypes. We offer an optimal measurement interval for investigating survivorship in CAD. We hypothesize genetic contributions to this construct and review the literature for evidence of genetic contribution to overlapping phenotypes in support of our hypothesis. We also present preliminary evidence of genetic effects on survival in people with clinically significant CAD from a primary case-control study of symptomatic coronary disease. Identifying gene variants that confer improved survival in the context of clinically appreciable CAD may improve our understanding of cardioprotective mechanisms acting at the gene level and potentially impact patients clinically in the future. Further, characterizing other survival-variant genetic effects may improve signal-to-noise ratio in detecting gene associations for CAD.

Gene-smoking interactions in multiple Rho-GTPase pathway genes in an early-onset coronary artery disease cohort

We performed a gene-smoking interaction analysis using families from an early-onset coronary artery disease cohort (GENECARD). This analysis was focused on validating and expanding results from previous studies implicating single nucleotide polymorphisms (SNPs) on chromosome 3 in smoking-mediated coronary artery disease. We analyzed 430 SNPs on chromosome 3 and identified 16 SNPs that showed a gene-smoking interaction at P < 0.05 using association in the presence of linkage--ordered subset analysis, a method that uses permutations of the data to empirically estimate the strength of the association signal. Seven of the 16 SNPs were in the Rho-GTPase pathway indicating a 1.87-fold enrichment for this pathway. A meta-analysis of gene-smoking interactions in three independent studies revealed that rs9289231 in KALRN had a Fisher's combined P value of 0.0017 for the interaction with smoking. In a gene-based meta-analysis KALRN had a P value of 0.026. Finally, a pathway-based analysis of the association results using WebGestalt revealed several enriched pathways including the regulation of the actin cytoskeleton pathway as defined by the Kyoto Encyclopedia of Genes and Genomes.

Matrix metalloproteinase-9 genetic polymorphisms and the risk for advanced pelvic organ prolapse

OBJECTIVE

Matrix metalloproteinase-9 (MMP9) is a protease associated with degradation of collagen and elastin. Because increased MMP9 activity in vaginal tissue has been associated with pelvic organ prolapse (POP), we sought to comprehensively estimate MMP9 genetic variants and the risk for advanced prolapse.

METHODS

This is a candidate gene association study of women with stage III-IV prolapse (case group, n=239) and women with stage 0-1 prolapse (control group, n=197). We attempted to oversample "extreme" phenotypes, including younger women with severe prolapse and older women without prolapse, in an attempt to concentrate the genetic effect. We used a linkage disequilibrium tagged approach to identify single nucleotide polymorphisms in MMP9 to evaluate in our study. To minimize potential confounding by race, our analysis focused on non-Hispanic white women. We performed multivariable logistic regression to estimate the association between MMP9 single nucleotide polymorphisms and case-control status, adjusting for age and vaginal parity.

RESULTS

Women with advanced prolapse were slightly younger (64.8 ± 10.3 compared with 69.0 ± 10.2 years, P<.001) and more likely to have had one or more vaginal deliveries (96.6% compared with 82.2%, P<.001) when compared with control participants. Eight single nucleotide polymorphisms were assessed, which represented 93% coverage of the MMP9 gene. Of these, two were associated with advanced prolapse: 1) rs3918253 (adjusted odds ratio [OR] 0.64, 95% confidence interval [CI] 0.41-1.0, P=.05); and 2) rs3918256 (adjusted OR 0.64, 95% CI 0.41-1.01, P=.05).

CONCLUSION

MMP9 is a biologically plausible candidate gene for POP given our results.

Characterizing the phenotype of advanced pelvic organ prolapse

OBJECTIVE

Genetic studies require a clearly defined phenotype to reach valid conclusions. Our aim was to characterize the phenotype of advanced prolapse by comparing women with stage III to IV prolapse with controls without prolapse.

METHODS

Based on the pelvic organ prolapse quantification examination, women with stage 0 to stage I prolapse (controls) and those with stage III to stage IV prolapse (cases) were prospectively recruited as part of a genetic epidemiologic study. Data regarding sociodemographics; medical, obstetric, and surgical history; family history; and body mass index were obtained by a questionnaire administered by a trained coordinator and abstracted from electronic medical records.

RESULTS

There were 275 case patients with advanced prolapse and 206 controls with stage 0 to stage I prolapse. Based on our recruitment strategy, the women were younger than the controls (64.7 ± 10.1 vs 68.6 ± 10.4 years; P<0.001); cases were also more likely to have had one or more vaginal deliveries (96.0% vs 82.0%; P<0.001). There were no differences in race, body mass index, and constipation. Regarding family history, cases were more likely to report that either their mother and/or sister(s) had prolapse (44.8% vs 16.9%, P<0.001). In a logistic regression model, vaginal parity (odds ratio, 4.05; 95% confidence interval, 1.67-9.85) and family history of prolapse (odds ratio, 3.74; 95% confidence interval, 2.16-6.46) remained significantly associated with advanced prolapse.

CONCLUSIONS

Vaginal parity and a family history of prolapse are more common in women with advanced prolapse compared to those without prolapse. These characteristics are important in phenotyping advanced prolapse, suggesting that these data should be collected in future genetic epidemiologic studies.

Comprehensive analysis of LAMC1 genetic variants in advanced pelvic organ prolapse

OBJECTIVE

We sought to comprehensively evaluate the association of laminin gamma-1 (LAMC1) and advance pelvic organ prolapse.

STUDY DESIGN

We conducted a candidate gene association of patients (n = 239) with stages III-IV prolapse and controls (n = 197) with stages 0-I prolapse. We used a linkage disequilibrium (LD)-tagged approach to identify single-nucleotide polymorphisms (SNPs) in LAMC1 and focused on non-Hispanic white women to minimize population stratification. Additive and dominant multivariable logistic regression models were used to test for association between individual SNPs and advanced prolapse.

RESULTS

Fourteen SNPs representing 99% coverage of LAMC1 were genotyped. There was no association between SNP rs10911193 and advanced prolapse (P = .34). However, there was a trend toward significance for SNPs rs1413390 (P = .11), rs20563 (P = .11), and rs20558 (P = .12).

CONCLUSION

Although we found that the previously reported LAMC1 SNP rs10911193 was not associated with nonfamilial prolapse, our results support further investigation of this candidate gene in the pathophysiology of prolapse.

Fine mapping of a linkage peak with integration of lipid traits identifies novel coronary artery disease genes on chromosome 5

Background

Coronary artery disease (CAD), and one of its intermediate risk factors, dyslipidemia, possess a demonstrable genetic component, although the genetic architecture is incompletely defined. We previously reported a linkage peak on chromosome 5q31-33 for early-onset CAD where the strength of evidence for linkage was increased in families with higher mean low density lipoprotein-cholesterol (LDL-C). Therefore, we sought to fine-map the peak using association mapping of LDL-C as an intermediate disease-related trait to further define the etiology of this linkage peak. The study populations consisted of 1908 individuals from the CATHGEN biorepository of patients undergoing cardiac catheterization; 254 families (N = 827 individuals) from the GENECARD familial study of early-onset CAD; and 162 aorta samples harvested from deceased donors. Linkage disequilibrium-tagged SNPs were selected with an average of one SNP per 20 kb for 126.6-160.2 MB (region of highest linkage) and less dense spacing (one SNP per 50 kb) for the flanking regions (117.7-126.6 and 160.2-167.5 MB) and genotyped on all samples using a custom Illumina array. Association analysis of each SNP with LDL-C was performed using multivariable linear regression (CATHGEN) and the quantitative trait transmission disequilibrium test (QTDT; GENECARD). SNPs associated with the intermediate quantitative trait, LDL-C, were then assessed for association with CAD (i.e., a qualitative phenotype) using linkage and association in the presence of linkage (APL; GENECARD) and logistic regression (CATHGEN and aortas).

Results

We identified four genes with SNPs that showed the strongest and most consistent associations with LDL-C and CAD: EBF1, PPP2R2B, SPOCK1, and PRELID2. The most significant results for association of SNPs with LDL-C were: EBF1, rs6865969, p = 0.01; PPP2R2B, rs2125443, p = 0.005; SPOCK1, rs17600115, p = 0.003; and PRELID2, rs10074645, p = 0.0002). The most significant results for CAD were EBF1, rs6865969, p = 0.007; PPP2R2B, rs7736604, p = 0.0003; SPOCK1, rs17170899, p = 0.004; and PRELID2, rs7713855, p = 0.003.

Conclusion

Using an intermediate disease-related quantitative trait of LDL-C we have identified four novel CAD genes, EBF1, PRELID2, SPOCK1, and PPP2R2B. These four genes should be further examined in future functional studies as candidate susceptibility loci for cardiovascular disease mediated through LDL-cholesterol pathways.

Ordered subset analysis for case-control studies

Genetic heterogeneity, which may manifest on a population level as different frequencies of a specific disease susceptibility allele in different subsets of patients, is a common problem for candidate gene and genome-wide association studies of complex human diseases. The ordered subset analysis (OSA) was originally developed as a method to reduce genetic heterogeneity in the context of family-based linkage studies. Here, we have extended a previously proposed method (OSACC) for applying the OSA methodology to case-control datasets. We have evaluated the type I error and power of different OSACC permutation tests with an extensive simulation study. Case-control datasets were generated under two different models by which continuous clinical or environmental covariates may influence the relationship between susceptibility genotypes and disease risk. Our results demonstrate that OSACC is more powerful under some disease models than the commonly used trend test and a previously proposed joint test of main genetic and gene-environment interaction effects. An additional unique benefit of OSACC is its ability to identify a more informative subset of cases that may be subjected to more detailed molecular analysis, such as DNA sequencing of selected genomic regions to detect functional variants in linkage disequilibrium with the associated polymorphism. The OSACC-identified covariate threshold may also improve the power of an additional dataset to replicate previously reported associations that may only be detectable in a fraction of the original and replication datasets. In summary, we have demonstrated that OSACC is a useful method for improving SNP association signals in genetically heterogeneous datasets.

Kalirin: a novel genetic risk factor for ischemic stroke

Cerebrovascular and cardiovascular diseases are the leading causes of death and disability worldwide. They are complex disorders resulting from the interplay of genetic and environmental factors, and may share several susceptibility genes. Several recent studies have implicated variants of the Kalirin (KALRN) gene with susceptibility to cardiovascular and metabolic phenotypes, but no studies have yet been performed in stroke patients. KALRN is involved, among others, in the inhibition of inducible nitric oxide synthase, in the regulation of ischemic signal transduction, and in neuronal morphogenesis, plasticity, and stability. The goal of the present study was to determine whether SNPs in the KALRN region on 3q13, which includes the Ropporin gene (ROPN1), predispose to ischemic stroke (IS) in a cohort of Portuguese patients and controls. We genotyped 34 tagging SNPs in the KALRN and ROPN1 chromosomal region on 565 IS patients and 517 unrelated controls, and performed genotype imputation for 405 markers on chromosome 3. We tested the single-marker association of these SNPs with IS. One SNP (rs4499545) in the ROPN1-KALRN intergenic region and two SNPs in KALRN (rs17286604 and rs11712619) showed significant (P < 0.05) allelic and genotypic (unadjusted and adjusted for hypertension, diabetes, and ever smoking) association with IS risk. Thirty-two imputed SNPs also showed an association at P < 0.05, and actual genotyping of three of these polymorphisms (rs7620580, rs6438833, and rs11712039) validated their association. Furthermore, rs11712039 was associated with IS (0.001 < P < 0.01) in a recent well-powered genomewide association study (Ikram et al. 2009). These studies suggest that variants in the KALRN gene region constitute risk factors for stroke and that KALRN may represent a common risk factor for vascular diseases.

High heritability of metabolomic profiles in families burdened with premature cardiovascular disease

Integration of genetic and metabolic profiling holds promise for providing insight into human disease. Coronary artery disease (CAD) is strongly heritable, but the heritability of metabolomic profiles has not been evaluated in humans. We performed quantitative mass spectrometry-based metabolic profiling in 117 individuals within eight multiplex families from the GENECARD study of premature CAD. Heritabilities were calculated using variance components. We found high heritabilities for amino acids (arginine, ornithine, alanine, proline, leucine/isoleucine, valine, glutamate/glutamine, phenylalanine and glycine; h(2)=0.33-0.80, P=0.005-1.9 x 10(-16)), free fatty acids (arachidonic, palmitic, linoleic; h(2)=0.48-0.59, P=0.002-0.00005) and acylcarnitines (h(2)=0.23-0.79, P=0.05-0.0000002). Principal components analysis was used to identify metabolite clusters. Reflecting individual metabolites, several components were heritable, including components comprised of ketones, beta-hydroxybutyrate and C2-acylcarnitine (h(2)=0.61); short- and medium-chain acylcarnitines (h(2)=0.39); amino acids (h(2)=0.44); long-chain acylcarnitines (h(2)=0.39) and branched-chain amino acids (h(2)=0.27). We report a novel finding of high heritabilities of metabolites in premature CAD, establishing a possible genetic basis for these profiles. These results have implications for understanding CAD pathophysiology and genetics.

Ordered-subset analysis (OSA) for family-based association mapping of complex traits

Association analysis provides a powerful tool for complex disease gene mapping. However, in the presence of genetic heterogeneity, the power for association analysis can be low since only a fraction of the collected families may carry a specific disease susceptibility allele. Ordered-subset analysis (OSA) is a linkage test that can be powerful in the presence of genetic heterogeneity. OSA uses trait-related covariates to identify a subset of families that provide the most evidence for linkage. A similar strategy applied to genetic association analysis would likely result in increased power to detect association. Association in the presence of linkage (APL) is a family-based association test (FBAT) for nuclear families with multiple affected siblings that properly infers missing parental genotypes when linkage is present. We propose here APL-OSA, which applies the OSA method to the APL statistic to identify a subset of families that provide the most evidence for association. A permutation procedure is used to approximate the distribution of the APL-OSA statistic under the null hypothesis that there is no relationship between the family-specific covariate and the family-specific evidence for allelic association. We performed a comprehensive simulation study to verify that APL-OSA has the correct type I error rate under the null hypothesis. This simulation study also showed that APL-OSA can increase power relative to other commonly used association tests (APL, FBAT and FBAT with covariate adjustment) in the presence of genetic heterogeneity. Finally, we applied APL-OSA to a family study of age-related macular degeneration, where cigarette smoking was used as a covariate.

Inflammation and metabolic disorders

PURPOSE OF REVIEW

Poor nutrition, overweight and obesity have increasingly become a public health concern as they affect many metabolic disorders, including heart disease, diabetes, digestive system disorders, and renal failure. Study of the effects of life style including healthy nutrition will help further elucidate the mechanisms involved in the adverse effects of poor nutrition.

RECENT FINDINGS

Unhealthy life style including poor nutrition can result in imbalance in our oxidation/redox systems. Lipids can undergo oxidative modification by lipoxygenases, cyclooxygenases, myeloperoxidase, and other enzymes. Oxidized phospholipids can induce inflammatory molecules in the liver and other organs. This can contribute to inflammation, leading to coronary heart disease, stroke, renal failure, inflammatory bowl disease, metabolic syndrome, bone and joint disorders, and even certain types of cancer.

SUMMARY

Our antioxidant and antiinflammatory defense mechanisms contribute to a balance between the stimulators and the inhibitors of inflammation. Beyond a point, however, these systems might be overwhelmed and eventually fail. High-density lipoprotein is a potent inhibitor of the formation of toxic oxidized lipids. High-density lipoprotein is also an effective system for stimulating the genes whose products are active in the removal, inactivation, and elimination of toxic lipids. Supporting the high-density lipoprotein function should help maintain the balance in these systems. It is hoped that the present report would elucidate some of the ongoing work toward this goal.

Neural phenotypes of common and rare genetic variants

Neuroimaging methods offer a powerful way to bridge the gaps between genes, neurobiology and behavior. Such investigations may be further empowered by complementary strategies involving chromosomal abnormalities associated with particular neurobehavioral phenotypes, which can help to localize causative genes and better understand the genetics of complex traits in the general population. Here we review the evidence from studies using these convergent approaches to investigate genetic influences on brain structure: (1) studies of common genetic variations associated with particular neuroanatomic phenotypes, and (2) studies of possible 'genetic subtypes' of neuropsychiatric disorders with very high penetrance, with a focus on neuroimaging studies using novel computational brain mapping algorithms. Finally, we discuss the contribution of behavioral neurogenetics research to our understanding of the genetic basis of neuropsychiatric disorders in the broader population.

In utero environmental tobacco smoke exposure alters gene expression in lungs of adult BALB/c mice

BACKGROUND

In utero environmental tobacco smoke (ETS) exposure exacerbates initial lung responses of adult mice to ovalbumin (OVA), a common allergen in rodent models of allergic asthma.

OBJECTIVE

We tested the hypothesis that in utero ETS exposure alters expression of genes (including asthma-related and inflammatory genes) in the lungs of adult mice and that this differential expression is reflected in differential respiratory and immune responses to nontobacco allergens.

METHODS

Using Affymetrix Mouse Genome 430 2.0 arrays, we examined gene expression changes in lungs of BALB/c mice exposed to ETS in utero, OVA, or saline aerosol at weeks 7-8, and OVA sensitization and challenge at weeks 11-15. Data sets were filtered by transcript p-value (< or = 0.05), false discovery rate (< or = 0.05), and fold change (> or = 1.5). Differential expression of selected genes was confirmed by polymerase chain reaction (PCR).

RESULTS

Genes differentially expressed as a result of in utero ETS exposure are involved in regulation of biological processes (immune response, cell proliferation, apoptosis, cell metabolism) through altered cytoskeleton, adhesion, transcription, and enzyme molecules. A number of genes prominent in lung inflammation were differentially expressed on PCR but did not pass selection criteria for microarray, including arginase (Arg1), chitinases (Chia, Chi3l3, Chi3l4), eotaxins (Ccl11, Ccl24), small proline-rich protein 2a (Sprr2a), and cytokines (Il4, Il6, Il10, Il13, Tnfa) .

CONCLUSION

The differential lung gene expression reported here is consistent with previously reported functional changes in lungs of mice exposed in utero to ETS and as adults to the nontobacco allergen OVA.

Interpreting analyses of continuous covariates in affected sibling pair linkage studies

Datasets collected for linkage analyses of complex human diseases often include a number of clinical or environmental covariates. In this study, we evaluated the performance of three linkage analysis methods when the relationship between continuous covariates and disease risk or linkage heterogeneity was modeled in three different ways: (1) The covariate distribution is determined by a quantitative trait locus (QTL), which contributes indirectly to the disease risk; (2) the covariate is not genetically determined, but influences the disease risk through statistical interaction with a disease susceptibility locus; (3) the covariate distribution differs in families linked or unlinked to a particular disease susceptibility locus. We analyzed simulated datasets with a regression-based QTL analysis, a nonparametric analysis of the binary affection status, and the ordered subset analysis (OSA). We found that a significant OSA result may be due to a gene that influences variability in the population distribution of a continuous disease risk factor. Conversely, a regression-based QTL analysis may detect the presence of gene-environment (GxE) interaction in a sample of primarily affected individuals. The contribution of unaffected siblings and the size of baseline lod scores may help distinguish between QTL and GxE models. As illustrated by a linkage study of multiplex families with age-related macular degeneration, our findings assist in the interpretation of analysis results in real datasets. They suggest that the side-by-side evaluation of OSA and QTL results may provide important information about the relationship of measured covariates with either disease risk or linkage heterogeneity.

Peakwide mapping on chromosome 3q13 identifies the kalirin gene as a novel candidate gene for coronary artery disease

A susceptibility locus for coronary artery disease (CAD) has been mapped to chromosome 3q13-21 in a linkage study of early-onset CAD. We completed an association-mapping study across the 1-LOD-unit-down supporting interval, using two independent white case-control data sets (CATHGEN, initial and validation) to evaluate association under the peak. Single-nucleotide polymorphisms (SNPs) evenly spaced at 100-kb intervals were screened in the initial data set (N=468). Promising SNPs (P<.1) were then examined in the validation data set (N=514). Significant findings (P<.05) in the combined initial and validation data sets were further evaluated in multiple independent data sets, including a family-based data set (N=2,954), an African American case-control data set (N=190), and an additional white control data set (N=255). The association between genotype and aortic atherosclerosis was examined in 145 human aortas. The peakwide survey found evidence of association in SNPs from multiple genes. The strongest associations were found in three SNPs from the kalirin (KALRN) gene, especially in patients with early-onset CAD (P=.00001-00028 in the combined CATHGEN data sets). In-depth investigation of the gene found that an intronic SNP, rs9289231, was associated with early-onset CAD in all white data sets examined (P<.05). In the joint analysis of all white early-onset CAD cases (N=332) and controls (N=546), rs9289231 was highly significant (P=.00008), with an odds-ratio estimate of 2.1. Furthermore, the risk allele of this SNP was associated with atherosclerosis burden (P=.03) in 145 human aortas. KALRN is a protein with many functions, including the inhibition of inducible nitric oxide synthase and guanine-exchange-factor activity. KALRN and two other associated genes identified in this study (CDGAP and MYLK) belong to the Rho GTPase-signaling pathway. Our data suggest the importance of the KALRN gene and the Rho GTPase-signaling pathway in the pathogenesis of CAD.

GATA2 is associated with familial early-onset coronary artery disease

The transcription factor GATA2 plays an essential role in the establishment and maintenance of adult hematopoiesis. It is expressed in hematopoietic stem cells, as well as the cells that make up the aortic vasculature, namely aortic endothelial cells and smooth muscle cells. We have shown that GATA2 expression is predictive of location within the thoracic aorta; location is suggested to be a surrogate for disease susceptibility. The GATA2 gene maps beneath the Chromosome 3q linkage peak from our family-based sample set (GENECARD) study of early-onset coronary artery disease. Given these observations, we investigated the relationship of several known and novel polymorphisms within GATA2 to coronary artery disease. We identified five single nucleotide polymorphisms that were significantly associated with early-onset coronary artery disease in GENECARD. These results were validated by identifying significant association of two of these single nucleotide polymorphisms in an independent case-control sample set that was phenotypically similar to the GENECARD families. These observations identify GATA2 as a novel susceptibility gene for coronary artery disease and suggest that the study of this transcription factor and its downstream targets may uncover a regulatory network important for coronary artery disease inheritance.

Coronary artery disease (CAD) is the most common form of heart disease in the Western world and is one of the leading causes of death in the United States. CAD is inherited and is a complex genetic disease because it results from changes to multiple genes acting in concert with one another and the environment. The authors locate CAD susceptibility genes by convergence of techniques and identify variation within a gene of interest in an early-onset CAD population. If a specific variant is found more often in affected individuals or families than in controls, this can suggest that this gene variant is associated with disease. The authors have identified a gene, GATA2, which is located in a genomic region suspected to contain genes for CAD and displays expression patterns predictive of location of disease within human donor aortas. They have identified several GATA2 variants that segregate with CAD in a family-based early-onset CAD population and have further validated two of these associations in a separate young case-control sample affected with CAD. These data imply that the transcription factor GATA2 may play a role in CAD susceptibility and suggest that the study of GATA2 targets may uncover a set of GATA2-regulated genes important to CAD inheritance.