Quantitative founder-effect analysis of French Canadian families identifies specific loci contributing to metabolic phenotypes of hypertension

Genetic determinants of the metabolic syndrome

Complex interactions between inherited factors and the environment determine an individual's susceptibility to type 2 diabetes mellitus and related syndromes. Insulin resistance, obesity, hypertension, and hyperlipidemia frequently precede the development of frank diabetes and aggregate in families. Several genome-wide scans have recently been performed in families with this constellation of findings, called the "metabolic syndrome." These analyses strongly support an inherited component to the syndrome. In this review, we provide an overview of the evidence in support of an inherited contribution to the metabolic syndrome and the search for causative genomic regions. When multiple genome scans involving different patient cohorts implicate a common genomic region as susceptible to the metabolic syndrome, it is highly likely that causative genes reside in that area. Identification of these genes will dramatically improve our understanding of the mechanisms that underlie the metabolic syndrome, and could lead to novel treatment strategies. It is hoped that these therapies will also prevent the future development of type 2 diabetes mellitus and atherosclerotic complications, both common among individuals affected by the metabolic syndrome.

The genetic dissection of essential hypertension

QTL mapping in humans and rats has identified hundreds of blood-pressure-related phenotypes and genomic regions; the next daunting task is gene identification and validation. The development of novel rat model systems that mimic many elements of the human disease, coupled with advances in the genomic and informatic infrastructure for rats, promise to revolutionize the hunt for genes that determine susceptibility to hypertension. Furthermore, methods are evolving that should enable the identification of candidate genes in human populations. Together with the computational reconstruction of regulatory networks, these methods provide opportunities to significantly advance our understanding of the underlying aetiology of hypertension.

Genome-wide scan for premature hypertension supports linkage to chromosome 2 in a large Kyrgyz family

We report a genome-wide scan for susceptibility loci to hypertension in a single Kyrgyz family where 10 of the affected relatives developed hypertension before the age of 35 years, and some members have suffered stroke. The early onset of disease and the geographic isolation of the Kyrgyz population are both expected to select for an increased influence of genetic factors in hypertension. We genotyped 44 individuals from this Krygyz family with 374 microsatellite markers, covering a 10-centimorgan map. Nonparametric analysis suggests that affected status is linked to loci in the chromosome 2q23 to q37 genomic interval, whereas 2-point parametric analysis returned a logarithm of odds score of 2.67 for marker D2S2330 (2q24.3). Multipoint linkage analysis substantiated the evidence for a hypertension susceptibility allele in the chromosome 2q23 to q36 region. Fine mapping and haplotype analysis implicate that the genetic lesion resides between markers D2S2380 (166.5 cM) and D2S335 (175.9 cM). This finding supports other recent studies of early onset hypertension suggesting that the region 2q24.3 to q31.1 encompasses a novel locus for premature hypertension.

Novel double-congenic strain reveals effects of spontaneously hypertensive rat chromosome 2 on specific lipoprotein subfractions and adiposity

We have developed a new, double-congenic rat strain BN- Lx.SHR2, which carries two distinct segments of chromosome 2 introgressed from the spontaneously hypertensive rat strain (SHR) into the genetic background of congenic strain BN- Lx, which was previously shown to express variety of metabolic syndrome features. In 16-wk-old male rats of BN- Lx and BN- Lx.SHR2 strains, we compared their glucose tolerance and triacylglycerol and cholesterol concentrations in 20 lipoprotein subfractions and the lipoprotein particle sizes under conditions of feeding standard and high-sucrose diets. Introgression of two distinct SHR-derived chromosome 2 segments resulted in decreased adiposity together with aggravation of glucose intolerance in the double-congenic strain. The BN- Lx.SHR2 rats were more sensitive to sucrose-induced rise in triacylglycerolemia. Although the total cholesterol concentrations of the two strains were comparable after the standard diet and even lower in BN- Lx.SHR2 after sucrose feeding, detailed analysis revealed that under both dietary conditions, the double-congenic strain had significantly higher cholesterol concentrations in low-density lipoprotein fractions and lower high-density lipoprotein fractions. We established a new inbred model showing dyslipidemia and mild glucose intolerance without obesity, attributable to specific genomic regions. For the first time, the chromosome 2 segments of SHR origin are shown to influence other than blood pressure-related features of metabolic syndrome or to be involved in relevant nutrigenomic interactions.

Heritability of cardiovascular and personality traits in 6,148 Sardinians

In family studies, phenotypic similarities between relatives yield information on the overall contribution of genes to trait variation. Large samples are important for these family studies, especially when comparing heritability between subgroups such as young and old, or males and females. We recruited a cohort of 6,148 participants, aged 14–102 y, from four clustered towns in Sardinia. The cohort includes 34,469 relative pairs. To extract genetic information, we implemented software for variance components heritability analysis, designed to handle large pedigrees, analyze multiple traits simultaneously, and model heterogeneity. Here, we report heritability analyses for 98 quantitative traits, focusing on facets of personality and cardiovascular function. We also summarize results of bivariate analyses for all pairs of traits and of heterogeneity analyses for each trait. We found a significant genetic component for every trait. On average, genetic effects explained 40% of the variance for 38 blood tests, 51% for five anthropometric measures, 25% for 20 measures of cardiovascular function, and 19% for 35 personality traits. Four traits showed significant evidence for an X-linked component. Bivariate analyses suggested overlapping genetic determinants for many traits, including multiple personality facets and several traits related to the metabolic syndrome; but we found no evidence for shared genetic determinants that might underlie the reported association of some personality traits and cardiovascular risk factors. Models allowing for heterogeneity suggested that, in this cohort, the genetic variance was typically larger in females and in younger individuals, but interesting exceptions were observed. For example, narrow heritability of blood pressure was approximately 26% in individuals more than 42 y old, but only approximately 8% in younger individuals. Despite the heterogeneity in effect sizes, the same loci appear to contribute to variance in young and old, and in males and females. In summary, we find significant evidence for heritability of many medically important traits, including cardiovascular function and personality. Evidence for heterogeneity by age and sex suggests that models allowing for these differences will be important in mapping quantitative traits.

Genetic analysis of complex traits, which are influenced by many different variables, is difficult because different genes and environmental factors can affect each individual. To simplify analysis, the authors turned to Sardinia, one of the rare, relatively isolated populations. They recruited 6,148 participants, aged 14–102 y, from four neighboring towns. Their sample includes many related individuals, including, for example, approximately 5,000 pairs of brothers and sisters. The authors measured 98 traits in each individual, including different aspects of blood composition and several cardiovascular and personality measures.

Here, the authors evaluate the overall impact of genes and environment on each trait and show that genes can explain many of the differences and similarities between individuals. Genetic influences were typically larger in females and in younger individuals, but interesting exceptions were observed. For example, genetic factors accounted for approximately 26% of the variation in blood pressure for those more than 42 y old, but only for approximately 8% in younger individuals. Their analysis also showed that the same genetic factor could influence multiple traits, for example by affecting multiple features of personality or of cardiovascular function. DNA analyses of this cohort will eventually allow researchers to identify genes that affect each of the traits studied, including important risk factors for cardiovascular disease.

Trait components provide tools to dissect the genetic susceptibility of migraine

The commonly used "end diagnosis" phenotype that is adopted in linkage and association studies of complex traits is likely to represent an oversimplified model of the genetic background of a disease. This is also likely to be the case for common types of migraine, for which no convincingly associated genetic variants have been reported. In headache disorders, most genetic studies have used end diagnoses of the International Headache Society (IHS) classification as phenotypes. Here, we introduce an alternative strategy; we use trait components--individual clinical symptoms of migraine--to determine affection status in genomewide linkage analyses of migraine-affected families. We identified linkage between several traits and markers on chromosome 4q24 (highest LOD score under locus heterogeneity [HLOD] 4.52), a locus we previously reported to be linked to the end diagnosis migraine with aura. The pulsation trait identified a novel locus on 17p13 (HLOD 4.65). Additionally, a trait combination phenotype (IHS full criteria) revealed a locus on 18q12 (HLOD 3.29), and the age at onset trait revealed a locus on 4q28 (HLOD 2.99). Furthermore, suggestive or nearly suggestive evidence of linkage to four additional loci was observed with the traits phonophobia (10q22) and aggravation by physical exercise (12q21, 15q14, and Xp21), and, interestingly, these loci have been linked to migraine in previous studies. Our findings suggest that the use of symptom components of migraine instead of the end diagnosis provides a useful tool in stratifying the sample for genetic studies.

Genome-wide scan identified QTLs underlying femoral neck cross-sectional geometry that are novel studied risk factors of osteoporosis

A genome-wide screen was conducted using a large white sample to identify QTLs for FNCS geometry. We found significant linkage of FNCS parameters to 20q12 and Xq25, plus significant epistatic interactions and sex-specific QTLs influencing FNCS geometry variation.

INTRODUCTION

Bone geometry, a highly heritable trait, is a critical component of bone strength that significantly determines osteoporotic fracture risk. Specifically, femoral neck cross-sectional (FNCS) geometry is significantly associated with hip fracture risk as well as genetic factors. However, genetic research in this respect is still in its infancy.

MATERIALS AND METHODS

To identify the underlying genomic regions influencing FNCS variables, we performed a remarkably large-scale whole genome linkage scan involving 3998 individuals from 434 pedigrees for four FNCS geometry parameters, namely buckling ratio (BR), cross-sectional area (CSA), cortical thickness (CT), and section modulus (Z). The major statistical approach adopted is the variance component method implemented in SOLAR.

RESULTS

Significant linkage evidence (threshold LOD = 3.72 after correction for tests of multiple phenotypes) was found in the regions of 20q12 and Xq25 for CT (LOD = 4.28 and 3.90, respectively). We also identified eight suggestive linkage signals (threshold LOD = 2.31 after correction for multiple tests) for the respective geometry traits. The above findings were supported by principal component linkage analysis. Of them, 20q12 was of particular interest because it was linked to multiple FNCS geometry traits and significantly interacted with five other genomic loci to influence CSA variation. The effects of 20q12 on FNCS geometry were present in both male and female subgroups. Subgroup analysis also revealed the presence of sex-specific quantitative trait loci (QTLs) for FNCS traits in the regions such as 2p14, 3q26, 7q21 and 15q21.

CONCLUSIONS

Our findings laid a foundation for further replication and fine-mapping studies as well as for positional and functional candidate gene studies, aiming at eventually finding the causal genetic variants and hidden mechanisms concerning FNCS geometry variation and the associated hip fractures.

A loss of genome buffering capacity of Dahl salt-sensitive model to modulate blood pressure as a cause of hypertension

Essential hypertension is a complex trait influenced by multiple genes known as quantitative trait loci (QTLs) for blood pressure (BP). It is not clear, however, what roles these QTLs play in maintaining normotension. Insights gained toward the maintenance of normotension will shed light on how hypertension can result from a deficiency or malfunctioning of this maintenance. Currently, congenic strains were systematically constructed using Dahl salt-sensitive (DSS) and Lewis (LEW) rats not only to define QTLs (i.e. in DSS background), but also to ascertain effects of the same QTLs in preserving normotension (i.e. in LEW background), a first such study. Results showed that although LEW alleles for two QTLs on Chromosome (Chr) 18 lowered BP on the DSS background, their BP-increasing DSS alleles failed to influence BP in the LEW background. To further prove that the LEW background is resistant and the DSS background is susceptible to the effects of QTLs, BP-increasing alleles of a QTL on Chr 2 were introgressed into the DSS background, and its BP-decreasing alleles into the LEW background. Indeed, there was no BP-decreasing effect on the LEW background while demonstrating a BP-increasing effect on the DSS background. Thus, a genetic regulation of BP QTLs in the LEW genome inhibits BP changes by nullifying the effects of BP-altering QTLs. In comparison, the DSS genome must have lost the buffering capacity for stabilizing BP. The current work presents good evidence that a lack of regulation for functions of BP QTLs is a potential underlying cause of hypertension.