83 research outputs found

    Phenotype forecasting with SNPs data through gene-based Bayesian networks

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    <p>Abstract</p> <p>Background</p> <p>Bayesian networks are powerful instruments to learn genetic models from association studies data. They are able to derive the existing correlation between genetic markers and phenotypic traits and, at the same time, to find the relationships between the markers themselves. However, learning Bayesian networks is often non-trivial due to the high number of variables to be taken into account in the model with respect to the instances of the dataset. Therefore, it becomes very interesting to use an abstraction of the variable space that suitably reduces its dimensionality without losing information. In this paper we present a new strategy to achieve this goal by mapping the SNPs related to the same gene to one meta-variable. In order to assign states to the meta-variables we employ an approach based on classification trees.</p> <p>Results</p> <p>We applied our approach to data coming from a genome-wide scan on 288 individuals affected by arterial hypertension and 271 nonagenarians without history of hypertension. After pre-processing, we focused on a subset of 24 SNPs. We compared the performance of the proposed approach with the Bayesian network learned with SNPs as variables and with the network learned with haplotypes as meta-variables. The results were obtained by running a hold-out experiment five times. The mean accuracy of the new method was 64.28%, while the mean accuracy of the SNPs network was 58.99% and the mean accuracy of the haplotype network was 54.57%.</p> <p>Conclusion</p> <p>The new approach presented in this paper is able to derive a gene-based predictive model based on SNPs data. Such model is more parsimonious than the one based on single SNPs, while preserving the capability of highlighting predictive SNPs configurations. The prediction performance of this approach was consistently superior to the SNP-based and the haplotype-based one in all the test sets of the evaluation procedure. The method can be then considered as an alternative way to analyze the data coming from association studies.</p

    Phenotype forecasting with SNPs data through gene-based Bayesian networks

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Bayesian networks are powerful instruments to learn genetic models from association studies data. They are able to derive the existing correlation between genetic markers and phenotypic traits and, at the same time, to find the relationships between the markers themselves. However, learning Bayesian networks is often non-trivial due to the high number of variables to be taken into account in the model with respect to the instances of the dataset. Therefore, it becomes very interesting to use an abstraction of the variable space that suitably reduces its dimensionality without losing information. In this paper we present a new strategy to achieve this goal by mapping the SNPs related to the same gene to one meta-variable. In order to assign states to the meta-variables we employ an approach based on classification trees.</p> <p>Results</p> <p>We applied our approach to data coming from a genome-wide scan on 288 individuals affected by arterial hypertension and 271 nonagenarians without history of hypertension. After pre-processing, we focused on a subset of 24 SNPs. We compared the performance of the proposed approach with the Bayesian network learned with SNPs as variables and with the network learned with haplotypes as meta-variables. The results were obtained by running a hold-out experiment five times. The mean accuracy of the new method was 64.28%, while the mean accuracy of the SNPs network was 58.99% and the mean accuracy of the haplotype network was 54.57%.</p> <p>Conclusion</p> <p>The new approach presented in this paper is able to derive a gene-based predictive model based on SNPs data. Such model is more parsimonious than the one based on single SNPs, while preserving the capability of highlighting predictive SNPs configurations. The prediction performance of this approach was consistently superior to the SNP-based and the haplotype-based one in all the test sets of the evaluation procedure. The method can be then considered as an alternative way to analyze the data coming from association studies.</p

    The genetics of exceptional longevity identifies new druggable targets forvascular protection and repair

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    Therapeutic angiogenesis is a relatively new medical strategy in the field of cardiovascular diseases. The underpinning concept is that angiogenic growth factors or proangiogenic cells could be exploited therapeutically in cardiovascular patients to enhance native revascularization responses to an ischemic insult, thereby accelerating tissue healing. The initial enthusiasm generated by preclinical studies has been tempered by the modest success of clinical trials assessing therapeutic angiogenesis. Similarly, proangiogenic cell therapy has so far not maintained the original promises. Intriguingly, the current trend is to consider regeneration as a prerogative of the youngest organism. Consequentially, the embryonic and foetal models are attracting much attention for clinical translation into corrective modalities in the adulthood. Scientists seem to undervalue the lesson from Mother Nature, e.g. all humans are born young but very few achieve the goal of an exceptional healthy longevity. Either natural experimentation is driven by a supreme intelligence or stochastic phenomena, one has to accept the evidence that healthy longevity is the fruit of an evolutionary process lasting million years. It is therefore extremely likely that results of this natural experimentation are more reliable and translatable than the intensive, but very short human investigation on mechanisms governing repair and regeneration. With this preamble in mind, here we propose to shift the focus from the very beginning to the very end of human life and thus capture the secret of prolonged health span to improve well-being in the adulthood

    Ankyrin-B Syndrome: Enhanced Cardiac Function Balanced by Risk of Cardiac Death and Premature Senescence

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    Here we report the unexpected finding that specific human ANK2 variants represent a new example of balanced human variants. The prevalence of certain ANK2 (encodes ankyrin-B) variants range from 2 percent of European individuals to 8 percent in individuals from West Africa. Ankyrin-B variants associated with severe human arrhythmia phenotypes (eg E1425G, V1516D, R1788W) were rare in the general population. Variants associated with less severe clinical and in vitro phenotypes were unexpectedly common. Studies with the ankyrin-B+/− mouse reveal both benefits of enhanced cardiac contractility, as well as costs in earlier senescence and reduced lifespan. Together these findings suggest a constellation of traits that we term “ankyrin-B syndrome”, which may contribute to both aging-related disorders and enhanced cardiac function

    Unexpectedly Low Mutation Rates in Beta-Myosin Heavy Chain and Cardiac Myosin Binding Protein Genes in Italian Patients With Hypertrophic Cardiomyopathy

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    Hypertrophic cardiomyopathy (HCM) is the most common genetic cardiac disease. Fourteen sarcomeric and sarcomere-related genes have been implicated in HCM etiology, those encoding β-myosin heavy chain (MYH7) and cardiac myosin binding protein C (MYBPC3) reported as the most frequently mutated: in fact, these account for around 50% of all cases related to sarcomeric gene mutations, which are collectively responsible for approximately 70% of all HCM cases. Here, we used denaturing high-performance liquid chromatography followed by bidirectional sequencing to screen the coding regions of MYH7 and MYBPC3 in a cohort (n = 125) of Italian patients presenting with HCM. We found 6 MHY7 mutations in 9/125 patients and 18 MYBPC3 mutations in 19/125 patients. Of the three novel MYH7 mutations found, two were missense, and one was a silent mutation; of the eight novel MYBPC3 mutations, one was a substitution, three were stop codons, and four were missense mutations. Thus, our cohort of Italian HCM patients did not harbor the high frequency of mutations usually found in MYH7 and MYBPC3. This finding, coupled to the clinical diversity of our cohort, emphasizes the complexity of HCM and the need for more inclusive investigative approaches in order to fully understand the pathogenesis of this disease. J. Cell. Physiol. 226: 2894–2900, 2011. © 2011 Wiley-Liss, Inc

    Distinct DNA methylomes of newborns and centenarians

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    Human aging cannot be fully understood in terms of the constrained genetic setting. Epigenetic drift is an alternative means of explaining age-associated alterations. To address this issue, we performed whole-genome bisulfite sequencing (WGBS) of newborn and centenarian genomes. The centenarian DNA had a lower DNA methylation content and a reduced correlation in the methylation status of neighboring cytosine--phosphate--guanine (CpGs) throughout the genome in comparison with the more homogeneously methylated newborn DNA. The more hypomethylated CpGs observed in the centenarian DNA compared with the neonate covered all genomic compartments, such as promoters, exonic, intronic, and intergenic regions. For regulatory regions, the most hypomethylated sequences in the centenarian DNA were present mainly at CpG-poor promoters and in tissue-specific genes, whereas a greater level of DNA methylation was observed in CpG island promoters. We extended the study to a larger cohort of newborn and nonagenarian samples using a 450,000 CpG-site DNA methylation microarray that reinforced the observation of more hypomethylated DNA sequences in the advanced age group. WGBS and 450,000 analyses of middle-age individuals demonstrated DNA methylomes in the crossroad between the newborn and the nonagenarian/centenarian groups. Our study constitutes a unique DNA methylation analysis of the extreme points of human life at a single-nucleotide resolution level

    The longevity-associated BPIFB4 gene supports cardiac function and vascularization in ageing cardiomyopathy

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    Aims The ageing heart naturally incurs a progressive decline in function and perfusion that available treatments cannot halt. However, some exceptional individuals maintain good health until the very late stage of their life due to favourable gene–environment interaction. We have previously shown that carriers of a longevity-associated variant (LAV) of the BPIFB4 gene enjoy prolonged health spans and lesser cardiovascular complications. Moreover, supplementation of LAV-BPIFB4 via an adeno-associated viral vector improves cardiovascular performance in limb ischaemia, atherosclerosis, and diabetes models. Here, we asked whether the LAV-BPIFB4 gene could address the unmet therapeutic need to delay the heart’s spontaneous ageing. Methods and results Immunohistological studies showed a remarkable reduction in vessel coverage by pericytes in failing hearts explanted from elderly patients. This defect was attenuated in patients carrying the homozygous LAV-BPIFB4 genotype. Moreover, pericytes isolated from older hearts showed low levels of BPIFB4, depressed pro-angiogenic activity, and loss of ribosome biogenesis. LAV-BPIFB4 supplementation restored pericyte function and pericyte-endothelial cell interactions through a mechanism involving the nucleolar protein nucleolin. Conversely, BPIFB4 silencing in normal pericytes mimed the heart failure pericytes. Finally, gene therapy with LAV-BPIFB4 prevented cardiac deterioration in middle-aged mice and rescued cardiac function and myocardial perfusion in older mice by improving microvasculature density and pericyte coverage. Conclusions We report the success of the LAV-BPIFB4 gene/protein in improving homeostatic processes in the heart’s ageing. These findings open to using LAV-BPIFB4 to reverse the decline of heart performance in older people
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