Common variants of the beta and gamma subunits of the epithelial sodium channel and their relation to plasma renin and aldosterone levels in essential hypertension

BACKGROUND: Rare mutations of the epithelial sodium channel (ENaC) result in the monogenic hypertension form of Liddle's syndrome. We decided to screen for common variants in the ENaC βand γ subunits in patients with essential hypertension and to relate their occurrence to the activity of circulating renin-angiotensin-aldosterone system. METHODS: Initially, DNA samples from 27 patients with low renin/low aldosterone hypertension were examined. The DNA variants were subsequently screened for in 347 patients with treatment-resistant hypertension, 175 male subjects with documented long-lasting normotension and 301 healthy Plasma renin and aldosterone levels were measured under baseline conditions and during postural and captopril challenge tests. RESULTS: Two commonly occurring βENaC variants (G589S and a novel intronic i12-17CT substitution) and one novel γENaC variant (V546I) were detected. One of these variants occurred in a heterozygous form in 32 patients, a prevalence (9.2%) significantly higher than that in normotensive males (2.9%, p = 0.007) and blood donors (3.0%, p = 0.001). βENaC i12-17CT was significantly more prevalent in the hypertension group than in the two control groups combined (4.6% vs. 1.1%, p = 0.001). When expressed in Xenopus oocytes, neither of the two ENaC amino acid-changing variants showed a significant difference in activity compared with ENaC wild-type. No direct evidence for a mRNA splicing defect could be obtained for the βENaC intronic variant. The ratio of daily urinary potassium excretion to upright and mean (of supine and upright values) plasma renin activity was higher in variant allele carriers than in non-carriers (p = 0.034 and p = 0.048). CONCLUSIONS: At least 9% of Finnish patients with hypertension admitted to a specialized center carry genetic variants of β and γENaC, a three times higher prevalence than in the normotensive individuals or in random healthy controls. Patients with the variant alleles showed an increased urinary potassium excretion rate in relation to their renin levels

Prevention of fall incidents in patients with a high risk of falling: design of a randomised controlled trial with an economic evaluation of the effect of multidisciplinary transmural care

Background. Annually, about 30% of the persons of 65 years and older falls at least once and 15% falls at least twice. Falls often result in serious injuries, such as fractures. Therefore, the prevention of accidental falls is necessary. The aim is to describe the design of a study that evaluates the efficacy and cost-effectiveness of a multidisciplinary assessment and treatment of multiple fall risk factors in independently living older persons with a high risk of falling. Methods/Design. The study is designed as a randomised controlled trial (RCT) with an economic evaluation. Independently living persons of 65 years and older who recently experienced a fall are interviewed in their homes and screened for risk of recurrent falling using a validated fall risk profile. Persons at low risk of recurrent falling are excluded from the RCT. Persons who have a high risk of recurrent falling are blindly randomised into an intervention (n = 100) or usual care (n = 100) group. The intervention consists of a multidisciplinary assessment and treatment of multifactorial fall risk factors. The transmural multidisciplinary appraoch entails close cooperation between geriatrician, primary care phys

A discharge summary adapted to the frail elderly to ensure transfer of relevant information from the hospital to community settings: a model

<p>Abstract</p> <p>Background</p> <p>Elderly patients admitted to Geriatric Assessment Units (GAU) typically have complex health problems that require multi-professional care. Considering the scope of human and technological resources solicited during hospitalization, as well as the many risks and discomforts incurred by the patient, it is important to ensure the communication of pertinent information for quality follow-up care in the community setting. Conventional discharge summaries do not adequately incorporate the elements specific to an aging clientele.</p> <p>Objective</p> <p>To develop a discharge summary adapted to the frail elderly patient (D-SAFE) in order to communicate relevant information from hospital to community services.</p> <p>Methods</p> <p>The items to be included in the D-SAFE have been determined by means of a modified Delphi method through consultation with clinical experts from GAUs (11 physicians and 5 pharmacists) and the community (10 physicians and 5 pharmacists). The consensus analysis and the level of agreement among the experts were reached using a modified version of the RAND^®/University of California at Los Angeles appropriateness method.</p> <p>Results</p> <p>A consensus was reached after two rounds of consultation for all the items evaluated, where none was judged «inappropriate». Among the items proposed, four were judged to be « uncertain » and were eliminated from the final D-SAFE, which was divided into two sections: the medical discharge summary (22 main items) and the discharge prescription (14 main items).</p> <p>Conclusions</p> <p>The D-SAFE was developed as a more comprehensive tool specifically designed for GAU inpatients. Additional research to validate its acceptability and practical impact on the continuity of care is needed before it can be recommended for use on a broader scale.</p

The challenge for genetic epidemiologists: how to analyze large numbers of SNPs in relation to complex diseases

Genetic epidemiologists have taken the challenge to identify genetic polymorphisms involved in the development of diseases. Many have collected data on large numbers of genetic markers but are not familiar with available methods to assess their association with complex diseases. Statistical methods have been developed for analyzing the relation between large numbers of genetic and environmental predictors to disease or disease-related variables in genetic association studies. In this commentary we discuss logistic regression analysis, neural networks, including the parameter decreasing method (PDM) and genetic programming optimized neural networks (GPNN) and several non-parametric methods, which include the set association approach, combinatorial partitioning method (CPM), restricted partitioning method (RPM), multifactor dimensionality reduction (MDR) method and the random forests approach. The relative strengths and weaknesses of these methods are highlighted. Logistic regression and neural networks can handle only a limited number of predictor variables, depending on the number of observations in the dataset. Therefore, they are less useful than the non-parametric methods to approach association studies with large numbers of predictor variables. GPNN on the other hand may be a useful approach to select and model important predictors, but its performance to select the important effects in the presence of large numbers of predictors needs to be examined. Both the set association approach and random forests approach are able to handle a large number of predictors and are useful in reducing these predictors to a subset of predictors with an important contribution to disease. The combinatorial methods give more insight in combination patterns for sets of genetic and/or environmental predictor variables that may be related to the outcome variable. As the non-parametric methods have different strengths and weaknesses we conclude that to approach genetic association studies using the case-control design, the application of a combination of several methods, including the set association approach, MDR and the random forests approach, will likely be a useful strategy to find the important genes and interaction patterns involved in complex diseases

Tamoxifen metabolism predicts drug concentrations and outcome in premenopausal patients with early breast cancer

Tamoxifen is the standard-of-care treatment for estrogen receptor-positive premenopausal breast cancer. We examined tamoxifen metabolism via blood metabolite concentrations and germline variations of CYP3A5, CYP2C9, CYP2C19 and CYP2D6 in 587 premenopausal patients (Asians, Middle Eastern Arabs, Caucasian-UK; median age 39 years) and clinical outcome in 306 patients. N-desmethyltamoxifen (DM-Tam)/(Z)-endoxifen and CYP2D6 phenotype significantly correlated across ethnicities (R2: 53%, P&lt;10?77). CYP2C19 and CYP2C9 correlated with norendoxifen and (Z)-4-hydroxytamoxifen concentrations, respectively (P&lt;0.001). DM-Tam was influenced by body mass index (P&lt;0.001). Improved distant relapse-free survival (DRFS) was associated with decreasing DM-Tam/(Z)-endoxifen (P=0.036) and increasing CYP2D6 activity score (hazard ratio (HR)=0.62; 95% confidence interval (CI), 0.43–0.91; P=0.013). Low (&lt;14?nM) compared with high (&gt;35?nM) endoxifen concentrations were associated with shorter DRFS (univariate P=0.03; multivariate HR=1.94; 95% CI, 1.04–4.14; P=0.064). Our data indicate that endoxifen formation in premenopausal women depends on CYP2D6 irrespective of ethnicity. Low endoxifen concentration/formation and decreased CYP2D6 activity predict shorter DRFS

Interaction effects on common measures of sensitivity:Choice of measure, type I error, and power

Here we use simulation to assess previously unaddressed problems in the assessment of statistical interactions in detection and recognition tasks. The proportion of hits and false-alarms made by an observer on such tasks is affected by both their sensitivity and bias, and numerous measures have been developed to separate out these two factors. Each of these measures makes different assumptions regarding the underlying process and different predictions as to how false-alarm and hit rates should covary. Previous simulations have shown that choice of an inappropriate measure can lead to inflated type I error rates, or reduced power, for main effects, provided there are differences in response bias between the conditions being compared. Interaction effects pose a particular problem in this context. We show that spurious interaction effects in analysis of variance can be produced, or true interactions missed, even in the absence of variation in bias. Additional simulations show that variation in bias complicates patterns of type I error and power further. This under-appreciated fact has the potential to greatly distort the assessment of interactions in detection and recognition experiments. We discuss steps researchers can take to mitigate their chances of making an error

Definitions and methods of measuring and reporting on injurious falls in randomised controlled fall prevention trials: a systematic review

<p>Abstract</p> <p>Background</p> <p>The standardisation of the assessment methodology and case definition represents a major precondition for the comparison of study results and the conduction of meta-analyses. International guidelines provide recommendations for the standardisation of falls methodology; however, injurious falls have not been targeted. The aim of the present article was to review systematically the range of case definitions and methods used to measure and report on injurious falls in randomised controlled trials (RCTs) on fall prevention.</p> <p>Methods</p> <p>An electronic literature search of selected comprehensive databases was performed to identify injurious falls definitions in published trials. Inclusion criteria were: RCTs on falls prevention published in English, study population ≥ 65 years, definition of injurious falls as a study endpoint by using the terms "injuries" and "falls".</p> <p>Results</p> <p>The search yielded 2089 articles, 2048 were excluded according to defined inclusion criteria. Forty-one articles were included. The systematic analysis of the methodology applied in RCTs disclosed substantial variations in the definition and methods used to measure and document injurious falls. The limited standardisation hampered comparability of study results. Our results also highlight that studies which used a similar, standardised definition of injurious falls showed comparable outcomes.</p> <p>Conclusions</p> <p>No standard for defining, measuring, and documenting injurious falls could be identified among published RCTs. A standardised injurious falls definition enhances the comparability of study results as demonstrated by a subgroup of RCTs used a similar definition. Recommendations for standardising the methodology are given in the present review.</p

Meta-analysis of exome array data identifies six novel genetic loci for lung function

Background: Over 90 regions of the genome have been associated with lung function to date, many of which have also been implicated in chronic obstructive pulmonary disease. Methods: We carried out meta-analyses of exome array data and three lung function measures: forced expiratory volume in one second (FEV1), forced vital capacity (FVC) and the ratio of FEV1 to FVC (FEV1/FVC). These analyses by the SpiroMeta and CHARGE consortia included 60,749 individuals of European ancestry from 23 studies, and 7,721 individuals of African Ancestry from 5 studies in the discovery stage, with follow-up in up to 111,556 independent individuals. Results: We identified significant (P<2·8x10-7) associations with six SNPs: a nonsynonymous variant in RPAP1, which is predicted to be damaging, three intronic SNPs (SEC24C, CASC17 and UQCC1) and two intergenic SNPs near to LY86 and FGF10. Expression quantitative trait loci analyses found evidence for regulation of gene expression at three signals and implicated several genes, including TYRO3 and PLAU. Conclusions: Further interrogation of these loci could provide greater understanding of the determinants of lung function and pulmonary disease

Comparative Linkage Meta-Analysis Reveals Regionally-Distinct, Disparate Genetic Architectures: Application to Bipolar Disorder and Schizophrenia

New high-throughput, population-based methods and next-generation sequencing capabilities hold great promise in the quest for common and rare variant discovery and in the search for ”missing heritability.” However, the optimal analytic strategies for approaching such data are still actively debated, representing the latest rate-limiting step in genetic progress. Since it is likely a majority of common variants of modest effect have been identified through the application of tagSNP-based microarray platforms (i.e., GWAS), alternative approaches robust to detection of low-frequency (1–5% MAF) and rare (<1%) variants are of great importance. Of direct relevance, we have available an accumulated wealth of linkage data collected through traditional genetic methods over several decades, the full value of which has not been exhausted. To that end, we compare results from two different linkage meta-analysis methods—GSMA and MSP—applied to the same set of 13 bipolar disorder and 16 schizophrenia GWLS datasets. Interestingly, we find that the two methods implicate distinct, largely non-overlapping, genomic regions. Furthermore, based on the statistical methods themselves and our contextualization of these results within the larger genetic literatures, our findings suggest, for each disorder, distinct genetic architectures may reside within disparate genomic regions. Thus, comparative linkage meta-analysis (CLMA) may be used to optimize low-frequency and rare variant discovery in the modern genomic era