57 resultados para Mendelian Principles


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Mendelian cardiomyopathies and arrhythmias are characterized by an important genetic heterogeneity, rendering Sanger sequencing very laborious and expensive. As a proof of concept, we explored multiplex targeted high-throughput sequencing (HTS) as a fast and cost-efficient diagnostic method for individuals suffering from Mendelian cardiac disorders. We designed a DNA capture assay including all exons from 130 genes involved in cardiovascular Mendelian disorders and analysed simultaneously four samples by multiplexing. Two patients had familial hypertrophic cardiomyopathy (HCM) and two patients suffered from long QT syndrome (LQTS). In patient 1 with HCM, we identified two known pathogenic missense variants in the two most frequently mutated sarcomeric genes MYH7 and MYBPC. In patient 2 with HCM, a known acceptor splice site variant in MYBPC3 was found. In patient 3 with LQTS, two missense variants in the genes SCN5A and KCNQ were identified. Finally, in patient 4 with LQTS a known missense variant was found in MYBPC3, which is usually mutated in patients with cardiomyopathy. Our results showed that multiplex targeted HTS works as an efficient and cost-effective tool for molecular diagnosis of heterogeneous disorders in clinical practice and offers new insights in the pathogenesis of these complex diseases.

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Meta-analyses are considered as an important pillar of evidence-based medicine. The aim of this review is to describe the main principles of a meta-analysis and to use examples of head and neck oncology to demonstrate their clinical impact and methodological interest. The major role of individual patient data is outlined, as well as the superiority of individual patient data over meta-analyses based on published summary data. The major clinical breakthrough of head and neck meta-analyses are summarized, regarding concomitant chemotherapy, altered fractionated chemotherapy, new regimens of induction chemotherapy or the use of radioprotectants. Recent methodological developments are described, including network meta-analyses, the validation of surrogate markers. Lastly, the future of meta-analyses is discussed in the context of personalized medicine.

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OBJECTIVES: To investigate, using a Mendelian randomisation approach, whether heavier smoking is associated with a range of regional adiposity phenotypes, in particular those related to abdominal adiposity. DESIGN: Mendelian randomisation meta-analyses using a genetic variant (rs16969968/rs1051730 in the CHRNA5-CHRNA3-CHRNB4 gene region) as a proxy for smoking heaviness, of the associations of smoking heaviness with a range of adiposity phenotypes. PARTICIPANTS: 148 731 current, former and never-smokers of European ancestry aged ≥16 years from 29 studies in the consortium for Causal Analysis Research in Tobacco and Alcohol (CARTA). PRIMARY OUTCOME MEASURES: Waist and hip circumferences, and waist-hip ratio. RESULTS: The data included up to 66 809 never-smokers, 43 009 former smokers and 38 913 current daily cigarette smokers. Among current smokers, for each extra minor allele, the geometric mean was lower for waist circumference by -0.40% (95% CI -0.57% to -0.22%), with effects on hip circumference, waist-hip ratio and body mass index (BMI) being -0.31% (95% CI -0.42% to -0.19), -0.08% (-0.19% to 0.03%) and -0.74% (-0.96% to -0.51%), respectively. In contrast, among never-smokers, these effects were higher by 0.23% (0.09% to 0.36%), 0.17% (0.08% to 0.26%), 0.07% (-0.01% to 0.15%) and 0.35% (0.18% to 0.52%), respectively. When adjusting the three central adiposity measures for BMI, the effects among current smokers changed direction and were higher by 0.14% (0.05% to 0.22%) for waist circumference, 0.02% (-0.05% to 0.08%) for hip circumference and 0.10% (0.02% to 0.19%) for waist-hip ratio, for each extra minor allele. CONCLUSIONS: For a given BMI, a gene variant associated with increased cigarette consumption was associated with increased waist circumference. Smoking in an effort to control weight may lead to accumulation of central adiposity.

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BACKGROUND: Obesity has been shown to be associated with depression and it has been suggested that higher body mass index (BMI) increases the risk of depression and other common mental disorders. However, the causal relationship remains unclear and Mendelian randomisation, a form of instrumental variable analysis, has recently been employed to attempt to resolve this issue. AIMS: To investigate whether higher BMI increases the risk of major depression. METHOD: Two instrumental variable analyses were conducted to test the causal relationship between obesity and major depression in RADIANT, a large case-control study of major depression. We used a single nucleotide polymorphism (SNP) in FTO and a genetic risk score (GRS) based on 32 SNPs with well-established associations with BMI. RESULTS: Linear regression analysis, as expected, showed that individuals carrying more risk alleles of FTO or having higher score of GRS had a higher BMI. Probit regression suggested that higher BMI is associated with increased risk of major depression. However, our two instrumental variable analyses did not support a causal relationship between higher BMI and major depression (FTO genotype: coefficient -0.03, 95% CI -0.18 to 0.13, P = 0.73; GRS: coefficient -0.02, 95% CI -0.11 to 0.07, P = 0.62). CONCLUSIONS: Our instrumental variable analyses did not support a causal relationship between higher BMI and major depression. The positive associations of higher BMI with major depression in probit regression analyses might be explained by reverse causality and/or residual confounding.

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BACKGROUND: Smoking is an important cardiovascular disease risk factor, but the mechanisms linking smoking to blood pressure are poorly understood. METHODS AND RESULTS: Data on 141 317 participants (62 666 never, 40 669 former, 37 982 current smokers) from 23 population-based studies were included in observational and Mendelian randomization meta-analyses of the associations of smoking status and smoking heaviness with systolic and diastolic blood pressure, hypertension, and resting heart rate. For the Mendelian randomization analyses, a genetic variant rs16969968/rs1051730 was used as a proxy for smoking heaviness in current smokers. In observational analyses, current as compared with never smoking was associated with lower systolic blood pressure and diastolic blood pressure and lower hypertension risk, but with higher resting heart rate. In observational analyses among current smokers, 1 cigarette/day higher level of smoking heaviness was associated with higher (0.21 bpm; 95% confidence interval 0.19; 0.24) resting heart rate and slightly higher diastolic blood pressure (0.05 mm Hg; 95% confidence interval 0.02; 0.08) and systolic blood pressure (0.08 mm Hg; 95% confidence interval 0.03; 0.13). However, in Mendelian randomization analyses among current smokers, although each smoking increasing allele of rs16969968/rs1051730 was associated with higher resting heart rate (0.36 bpm/allele; 95% confidence interval 0.18; 0.54), there was no strong association with diastolic blood pressure, systolic blood pressure, or hypertension. This would suggest a 7 bpm higher heart rate in those who smoke 20 cigarettes/day. CONCLUSIONS: This Mendelian randomization meta-analysis supports a causal association of smoking heaviness with higher level of resting heart rate, but not with blood pressure. These findings suggest that part of the cardiovascular risk of smoking may operate through increasing resting heart rate.

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In recent years, technological advances have allowed manufacturers to implement dual-energy computed tomography (DECT) on clinical scanners. With its unique ability to differentiate basis materials by their atomic number, DECT has opened new perspectives in imaging. DECT has been used successfully in musculoskeletal imaging with applications ranging from detection, characterization, and quantification of crystal and iron deposits; to simulation of noncalcium (improving the visualization of bone marrow lesions) or noniodine images. Furthermore, the data acquired with DECT can be postprocessed to generate monoenergetic images of varying kiloelectron volts, providing new methods for image contrast optimization as well as metal artifact reduction. The first part of this article reviews the basic principles and technical aspects of DECT including radiation dose considerations. The second part focuses on applications of DECT to musculoskeletal imaging including gout and other crystal-induced arthropathies, virtual noncalcium images for the study of bone marrow lesions, the study of collagenous structures, applications in computed tomography arthrography, as well as the detection of hemosiderin and metal particles.

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In recent years, technological advances have allowed manufacturers to implement dual-energy computed tomography (DECT) on clinical scanners. With its unique ability to differentiate basis materials by their atomic number, DECT has opened new perspectives in imaging. DECT has been successfully used in musculoskeletal imaging with applications ranging from detection, characterization, and quantification of crystal and iron deposits, to simulation of noncalcium (improving the visualization of bone marrow lesions) or noniodine images. Furthermore, the data acquired with DECT can be postprocessed to generate monoenergetic images of varying kiloelectron volts, providing new methods for image contrast optimization as well as metal artifact reduction. The first part of this article reviews the basic principles and technical aspects of DECT including radiation dose considerations. The second part focuses on applications of DECT to musculoskeletal imaging including gout and other crystal-induced arthropathies, virtual noncalcium images for the study of bone marrow lesions, the study of collagenous structures, applications in computed tomography arthrography, as well as the detection of hemosiderin and metal particles.

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In geriatrics, driving cessation is addressed within the biopsychosocial model. This has broadened the scope of practitioners, not only in terms of assessing fitness to drive, but also by helping to maintain social engagements and provide support for transport transition. Causes can be addressed at different levels by adapting medication, improving physical health, modifying behaviour, adapting lifestyle, or bringing changes to the environment. This transdisciplinary approach requires an understanding of how different disciplines are linked to each other. This article reviews the philosophical principles of causality between fields and provides a framework for understanding causality within the biopsychosocial model. Understanding interlevel constraints should help practitioners overcome their differences, and favor transversal approaches to driving cessation.