Statistical issues and approaches in endophenotype research

This special topic comprises 9 papers which were presented at the Symposium. (Chinese Science Bulletin, 2011, v. 56 n. 32 Editorial. doi: 10.1007/s11434-011-4716-4)This journal issue entitled: SPECIAL TOPIC Endophenotype Strategies for the Study of Neuropsychiatric DisordersThe endophenotype concept was initially proposed to enhance the power of genetic studies of complex disorders. It is closely related to the genetic component in a liability-threshold model; a perfect endophenotype should have a correlation of 1 with the genetic component of the liability to disease. In reality, a putative endophenotype is unlikely to be a perfect representation of the genetic component of disease liability. The magnitude of the correlation between a putative endophenotype and the genetic component of disease liability can be estimated by fitting multivariate genetic models to twin data. A number of statistical methods have been developed for incorporating endophenotypes in genetic linkage and association analyses with the aim of improving statistical power. The most recent of such methods can handle multiple endophenotypes simultaneously for the greatest increase in power. In addition to increasing statistical power, endophenotype research plays an important role in helping to understand the mechanisms which connect the associated genetic variants with disease occurrence. Novel statistical approaches may be required for the analysis of the complex relationships between endophenotypes at different levels and how they converge to cause the occurrence of disease. © 2011 Science China Press and Springer-Verlag Berlin Heidelberg.published_or_final_versio

I feel it in my finger: Measurement device affects cardiac interoceptive accuracy

This is the final version. Available on open access from Elsevier via the DOI in this recordIn recent years, measures of cardiac interoceptive accuracy have been heavily scrutinised. The focus has been on potentially confounding physiological and psychological factors; little research has examined whether the device used to record objective heartbeats may influence cardiac interoceptive accuracy. The present studies assessed whether the device employed influences heartbeat counting (HCT) accuracy and the location from which heartbeats are perceived. In Study One, participants completed the HCT using a hard-clip finger pulse oximeter, electrocardiogram (ECG) and a smartphone application. In Study Two, an ECG, hard-clip and soft-clip oximeter were compared. Moderate-strong correlations were observed across devices, however, mean HCT accuracy and confidence varied as a function of device. Increased sensation in the finger when using a hard-clip pulse oximeter was related to increased accuracy relative to ECG. Results suggest that the device employed can influence HCT performance, and argue against comparing, or combining, scores obtained using different devices.Economic and Social Research Council (ESRC)Baily Thomas TrustFonds de Recherche Québec – Sant

MFV Reductions of MSSM Parameter Space

The 100+ free parameters of the minimal supersymmetric standard model (MSSM) make it computationally difficult to compare systematically with data, motivating the study of specific parameter reductions such as the cMSSM and pMSSM. Here we instead study the reductions of parameter space implied by using minimal flavour violation (MFV) to organise the R-parity conserving MSSM, with a view towards systematically building in constraints on flavour-violating physics. Within this framework the space of parameters is reduced by expanding soft supersymmetry-breaking terms in powers of the Cabibbo angle, leading to a 24-, 30- or 42-parameter framework (which we call MSSM-24, MSSM-30, and MSSM-42 respectively), depending on the order kept in the expansion. We provide a Bayesian global fit to data of the MSSM-30 parameter set to show that this is manageable with current tools. We compare the MFV reductions to the 19-parameter pMSSM choice and show that the pMSSM is not contained as a subset. The MSSM-30 analysis favours a relatively lighter TeV-scale pseudoscalar Higgs boson and $\tan \beta \sim 10$ with multi-TeV sparticles.Comment: 2nd version, minor comments and references added, accepted for publication in JHE

The dynamics of human body weight change

An imbalance between energy intake and energy expenditure will lead to a change in body weight (mass) and body composition (fat and lean masses). A quantitative understanding of the processes involved, which currently remains lacking, will be useful in determining the etiology and treatment of obesity and other conditions resulting from prolonged energy imbalance. Here, we show that the long-term dynamics of human weight change can be captured by a mathematical model of the macronutrient flux balances and all previous models are special cases of this model. We show that the generic dynamical behavior of body composition for a clamped diet can be divided into two classes. In the first class, the body composition and mass are determined uniquely. In the second class, the body composition can exist at an infinite number of possible states. Surprisingly, perturbations of dietary energy intake or energy expenditure can give identical responses in both model classes and existing data are insufficient to distinguish between these two possibilities. However, this distinction is important for the efficacy of clinical interventions that alter body composition and mass

Sheldon-Hall syndrome

Sheldon-Hall syndrome (SHS) is a rare multiple congenital contracture syndrome characterized by contractures of the distal joints of the limbs, triangular face, downslanting palpebral fissures, small mouth, and high arched palate. Epidemiological data for the prevalence of SHS are not available, but less than 100 cases have been reported in the literature. Other common clinical features of SHS include prominent nasolabial folds, high arched palate, attached earlobes, mild cervical webbing, short stature, severe camptodactyly, ulnar deviation, and vertical talus and/or talipes equinovarus. Typically, the contractures are most severe at birth and non-progressive. SHS is inherited in an autosomal dominant pattern but about half the cases are sporadic. Mutations in either MYH3, TNNI2, or TNNT3 have been found in about 50% of cases. These genes encode proteins of the contractile apparatus of fast twitch skeletal muscle fibers. The diagnosis of SHS is based on clinical criteria. Mutation analysis is useful to distinguish SHS from arthrogryposis syndromes with similar features (e.g. distal arthrogryposis 1 and Freeman-Sheldon syndrome). Prenatal diagnosis by ultrasonography is feasible at 18–24 weeks of gestation. If the family history is positive and the mutation is known in the family, prenatal molecular genetic diagnosis is possible. There is no specific therapy for SHS. However, patients benefit from early intervention with occupational and physical therapy, serial casting, and/or surgery. Life expectancy and cognitive abilities are normal

The impact of the ATLAS zero-lepton, jets and missing momentum search on a CMSSM fit

Recent ATLAS data significantly extend the exclusion limits for supersymmetric particles. We examine the impact of such data on global fits of the constrained minimal supersymmetric standard model (CMSSM) to indirect and cosmological data. We calculate the likelihood map of the ATLAS search, taking into account systematic errors on the signal and on the background. We validate our calculation against the ATLAS determinaton of 95% confidence level exclusion contours. A previous CMSSM global fit is then re-weighted by the likelihood map, which takes a bite at the high probability density region of the global fit, pushing scalar and gaugino masses up.Comment: 16 pages, 7 figures. v2 has bigger figures and fixed typos. v3 has clarified explanation of our handling of signal systematic

Background risk of breast cancer and the association between physical activity and mammographic density

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Reliability of Eye Tracking and Pupillometry Measures in Individuals with Fragile X Syndrome

Recent insight into the underlying molecular and cellular mechanisms of fragile X syndrome (FXS) has led to the proposal and development of new pharmaceutical treatment strategies, and the initiation of clinical trials aimed at correcting core symptoms of the developmental disorder. Consequently, there is an urgent and critical need for outcome measures that are valid for quantifying specific symptoms of FXS and that are consistent across time. We used eye tracking to evaluate test–retest reliability of gaze and pupillometry measures in individuals with FXS and we demonstrate that these measures are viable options for assessing treatment-specific outcomes related to a core behavioral feature of the disorder

Predictive modeling of die filling of the pharmaceutical granules using the flexible neural tree

In this work, a computational intelligence (CI) technique named flexible neural tree (FNT) was developed to predict die filling performance of pharmaceutical granules and to identify significant die filling process variables. FNT resembles feedforward neural network, which creates a tree-like structure by using genetic programming. To improve accuracy, FNT parameters were optimized by using differential evolution algorithm. The performance of the FNT-based CI model was evaluated and compared with other CI techniques: multilayer perceptron, Gaussian process regression, and reduced error pruning tree. The accuracy of the CI model was evaluated experimentally using die filling as a case study. The die filling experiments were performed using a model shoe system and three different grades of microcrystalline cellulose (MCC) powders (MCC PH 101, MCC PH 102, and MCC DG). The feed powders were roll-compacted and milled into granules. The granules were then sieved into samples of various size classes. The mass of granules deposited into the die at different shoe speeds was measured. From these experiments, a dataset consisting true density, mean diameter (d50), granule size, and shoe speed as the inputs and the deposited mass as the output was generated. Cross-validation (CV) methods such as 10FCV and 5x2FCV were applied to develop and to validate the predictive models. It was found that the FNT-based CI model (for both CV methods) performed much better than other CI models. Additionally, it was observed that process variables such as the granule size and the shoe speed had a higher impact on the predictability than that of the powder property such as d50. Furthermore, validation of model prediction with experimental data showed that the die filling behavior of coarse granules could be better predicted than that of fine granules