10 resultados para quantitative trait locus

em Deakin Research Online - Australia


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BACKGROUND: Left ventricular (LV) hypertrophy is a risk factor for cardiovascular death, but the genetic factors determining LV size and predisposition to hypertrophy are not well understood. We have previously linked the quantitative trait locus cardiac mass 22 (Cm22) on chromosome 2 with cardiac hypertrophy independent of blood pressure in the spontaneously hypertensive rat. From an original cross of spontaneously hypertensive rat with F344 rats, we derived a normotensive polygenic model of spontaneous cardiac hypertrophy, the hypertrophic heart rat (HHR) and its control strain, the normal heart rat (NHR).

METHODS AND RESULTS: To identify the genes and molecular mechanisms underlying spontaneous LV hypertrophy we sequenced the HHR genome with special focus on quantitative trait locus Cm22. For correlative analyses of function, we measured global RNA transcripts in LV of neonatal HHR and NHR and 198 neonatal rats of an HHR × NHR F2 crossbred population. Only one gene within locus Cm22 was differentially expressed in the parental generation: tripartite motif-containing 55 (Trim55), with mRNA downregulation in HHR (P < 0.05) and reduced protein expression. Trim55 mRNA levels were negatively correlated with LV mass in the F2 cross (r = -0.16, P = 0.025). In exon nine of Trim55 in HHR, we found one missense mutation that functionally alters protein structure. This mutation was strongly associated with Trim55 mRNA expression in F2 rats (F = 10.35, P < 0.0001). Similarly, in humans, we found reduced Trim55 expression in hearts of subjects with idiopathic dilated cardiomyopathy.

CONCLUSION: Our study suggests that the Trim55 gene, located in Cm22, is a novel candidate gene for polygenic LV hypertrophy independent of blood pressure.

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Aims/hypothesis Insulin hypersecretion may be an independent predictor of progression to type 2 diabetes. Identifying genes affecting insulin hypersecretion are important in understanding disease progression. We have previously shown that diabetes-susceptible DBA/2 mice congenitally display high insulin secretion. We studied this model to map and identify the gene(s) responsible for this trait.

Methods Intravenous glucose tolerance tests followed by a genome-wide scan were performed on 171 (C57BL/6 × DBA/2) × C57BL/6 backcross mice.

Results A quantitative trait locus, designated hyperinsulin production-1 (Hip1), was mapped with a logarithm of odds score of 7.7 to a region on chromosome 13. Production of congenic mice confirmed that Hip1 influenced the insulin hypersecretion trait. By studying appropriate recombinant inbred mouse strains, the Hip1 locus was further localised to a 2 Mb interval, which contained only nine genes. Expression analysis showed that the only gene differentially expressed in islets isolated from the parental strains was Nnt, which encodes the mitochondrial proton pump, nicotinamide nucleotide transhydrogenase (NNT). We also found in five mouse strains a positive correlation (r 2  = 0.90, p < 0.01) between NNT activity and first-phase insulin secretion, emphasising the importance of this enzyme in beta cell function. Furthermore, of these five strains, only those with high NNT activity are known to exhibit severe diabetes after becoming obese.

Conclusions/interpretation Insulin hypersecretion is associated with increased Nnt expression. We suggest that NNT must play an important role in beta cell function and that its effect on the high insulin secretory capacity of the DBA/2 mouse may predispose beta cells of these mice to failure.

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New treatments are currently required for the common metabolic diseases obesity and type 2 diabetes. The identification of physiological and  biochemical factors that underlie the metabolic disturbances observed in obesity and type 2 diabetes is a key step in developing better therapeutic outcomes. The discovery of new genes and pathways involved in the  pathogenesis of these diseases is critical to this process, however  identification of genes that contribute to the risk of developing these diseases represents a significant challenge as obesity and type 2 diabetes are complex diseases with many genetic and environmental causes. A number of diverse approaches have been used to discover and validate potential new targets for obesity and diabetes. To date, DNA-based approaches using candidate gene and genome-wide linkage analysis have had limited success in identifying genomic regions or genes involved in the development of these diseases. Recent advances in the ability to evaluate linkage analysis data from large family pedigrees using variance components based linkage analysis show great promise in robustly identifying genomic regions associated with the development of obesity and diabetes. RNA-based technologies such as cDNA microarrays have identified many genes differentially expressed in tissues of healthy and diseased subjects. Using a combined approach, we are endeavouring to focus attention on differentially expressed genes located in chromosomal regions previously linked with obesity and / or diabetes. Using this strategy, we have identified Beacon as a potential new target for obesity and diabetes.

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The BEACON gene was initially identified using the differential display polymerase chain reaction on hypothalamic mRNA samples collected from lean and obese Psammomys obesus, a polygenic animal model of obesity. Hypothalamic BEACON gene expression was positively correlated with percentage of body fat, and intracerebroventricular infusion of the Beacon protein resulted in a dose-dependent increase in food intake and body weight. The human homolog of BEACON, UBL5, is located on chromosome 19p in a region previously linked to quantitative traits related to obesity. Our previous studies showed a statistically significant association between UBL5 sequence variation and several obesity- and diabetes-related quantitative physiological measures in Asian Indian and Micronesian cohorts. Here we undertake a replication study in a Mexican American cohort where the original linkage signal was first detected. We exhaustively resequenced the complete gene plus the putative promoter region for genetic variation in 55 individuals and identified five single nucleotide polymorphisms (SNPs), one of which was novel. These SNPs were genotyped in a Mexican American cohort of 900 individuals from 40 families. Using a quantitative trait linkage disequilibrium test, we found significant associations between UBL5 genetic variants and waist-to-hip ratio (p = 0.027), and the circulating concentrations of insulin (p = 0.018) and total cholesterol (p = 0.023) in fasted individuals. These data are consistent with our earlier published studies and further support a functional role for the UBL5 gene in influencing physiological traits that underpin the development of metabolic syndrome.

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Chronic inflammation has a pathological role in many common diseases and is influenced by both genetic and environmental factors. Here we assess the role of genetic variation in selenoprotein S (SEPS1, also called SELS or SELENOS), a gene involved in stress response in the endoplasmic reticulum and inflammation control. After resequencing SEPS1, we genotyped 13 SNPs in 522 individuals from 92 families. As inflammation biomarkers, we measured plasma levels of IL-6, IL-1b and TNF-a. Bayesian quantitative trait nucleotide analysis identified associations between SEPS1 polymorphisms and all three proinflammatory
cytokines. One promoter variant, 105G-A, showed strong evidence for an association with each cytokine (multivariate P = 0.0000002). Functional analysis of this polymorphism showed that the A variant significantly impaired SEPS1 expression after exposure to endoplasmic reticulum stress agents (P = 0.00006). Furthermore, suppression of SEPS1 by short interfering RNA in macrophage cells increased the release of IL-6 and TNF-a. To investigate further the significance of the observed associations, we genotyped 105G-A in 419 Mexican American individuals from 23 families for replication. This analysis confirmed a significant
association with both TNF-a (P = 0.0049) and IL-1b (P = 0.0101). These results provide a direct mechanistic link between SEPS1 and the production of inflammatory cytokines and suggest that SEPS1 has a role in mediating inflammation.

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The physiological adaptation to the erect posture involves integrated neural and cardiovascular responses that might be determined by genetic factors. We examined the familial- and individual-specific components of variance for postural changes in systolic and diastolic blood pressure in 767 volunteer nuclear adult families from the Victorian Family Heart Study. In 274 adult sibling pairs, we made a genome-wide scan using 400 markers for quantitative trait loci linked with the postural changes in systolic and diastolic pressures. Overall, systolic pressure did not change on standing, but there was considerable variation in this phenotype (SD=8.1 mm Hg). Familial analyses revealed that 25% of the variance of change in systolic pressure was attributable to genetic factors. In contrast, diastolic pressure increased by 6.3 mm Hg (SD=7.0 mm Hg) on standing and there was no evidence of contributory genetic factors. Multipoint quantitative genome linkage mapping suggested evidence (Z=3.2) of linkage of the postural change in systolic pressure to chromosome 12 but found no genome-wide evidence of linkage for the change in diastolic pressure. These findings suggest that genetic factors determine whether systolic pressure decreases or increases when one stands, possibly as the result of unidentified alleles on chromosome 12. The genetics of postural changes in systolic blood pressure might reflect the general buffering function of the baroreflex; thereby, the predisposition to sudden decreases or increases in systolic pressure might cause postural hypotension or vessel wall disruption, respectively.