Identification and evaluation of biomarkers for Huntington’s disease

Huntington’s disease (HD) is a devastating, incurable inherited neurodegenerative disorder that commonly affects adults in mid-life. Despite encouraging results from in vitro and animal trials, disease-modifying therapeutic trials in HD are limited by a lack of tools to track disease progression. HD is clinically heterogeneous, and current clinical rating scales lack sensitivity and specificity, particularly over relatively short time periods. Improvements in the precision of objective measurement of disease progression in HD could lead to state markers (biomarkers) better able to predict onset, detect progression and measure the effects of therapeutic intervention. Biomarkers capable of detecting disease-related changes in premanifest gene carriers will be essential for clinical trials of treatments to delay onset. Imaging, clinical and cognitive assessment as well as laboratory markers have all been proposed as biomarkers, but few measures have been quantified over short time intervals or shown to be predictive of clinical change over longer periods. A robust panel of biomarkers from a number of modalities will be necessary to progress to interventional clinical trials of disease-modifying therapies in HD, using biomarkers to measure the success or failure of an intervention. Such cross-validation requires simultaneous multimodal biomarker evaluation within a suitable cohort of subjects studied longitudinally. This thesis describes a multi-modal approach to the discovery and evaluation of potential biomarkers for Huntington's disease in a large cohort of human volunteers. After reviewing the relevant features of Huntington's disease and current state of biomarker research in Huntington's disease, several approaches to, and outcomes from, biomarker discovery and evaluation are described, including proteomic profiling, targeted ELISA, multiplex inflammatory profiling and measurement of whole-brain atrophy by longitudinal magnetic resonance imaging. The thesis draws together these different approaches and summarises the contributions to both biomarker research and our understanding of the neurobiology of HD that the work has generated

Sitting Time and Waist Circumference Are Associated With Glycemia in U.K. South Asians: Data from 1,228 adults screened for the PODOSA trial

OBJECTIVE-To investigate the independent contributions of waist circumference, physical activity, and sedentary behavior on glycemia in South Asians living in Scotland. RESEARCH DESIGN AND METHODS-Participants were 1,228 (523 men and 705 women) adults of Indian or Pakistani origin screened for the Prevention of Type 2 Diabetes and Obesity in South Asians (PODOSA) trial. All undertook an oral glucose tolerance test, had physical activity and sitting time assessed by International Physical Activity Questionnaire, and had waist circumference measured. RESULTS-Mean +/- SD age and waist circumference were 49.8 +/- 10.1 years and 99.2 +/- 10.2 cm, respectively. One hundred ninety-one participants had impaired fasting glycemia or impaired glucose tolerance, and 97 had possible type 2 diabetes. In multivariate regression analysis, ay (0.012 mmol.L-1.year [95% CI 0.006-0.017]) and waist circumference (0.018 mmol.L-1.cm(-1) [0.012-0.024]) were significantly independently associated with fasting glucose concentration, and age (0.032 mmol.L-1.year(-1) [0.016-0.049]), waist (0.057 mmolL(-1).cm(-1) [0.040-0.074]), and sitting time (0.097 mmol.L-1.h(-1).day(-1) [0.036-0.158]) were significantly independently associated with 2-h glucose concentration. Vigorous activity time had a borderline significant association with 2-h glucose concentration (-0.819 mmol.L-1.h(-1).day-1 [-1.672 to 0.034]) in the multivariate model. CONCLUSIONS-These data highlight an important relationship between sitting time and 2-h glucose levels in U.K. South Asians, independent of physical activity and waist circumference. Although the data are cross-sectional and thus do not permit firm conclusions about causality to be drawn, the results suggest that further study investigating the effects of sitting time on glycemia and other aspects of metabolic risk in South Asian populations is warrante

JASP: Graphical Statistical Software for Common Statistical Designs

This paper introduces JASP, a free graphical software package for basic statistical procedures such as t tests, ANOVAs, linear regression models, and analyses of contingency tables. JASP is open-source and differentiates itself from existing open-source solutions in two ways. First, JASP provides several innovations in user interface design; specifically, results are provided immediately as the user makes changes to options, output is attractive, minimalist, and designed around the principle of progressive disclosure, and analyses can be peer reviewed without requiring a "syntax". Second, JASP provides some of the recent developments in Bayesian hypothesis testing and Bayesian parameter estimation. The ease with which these relatively complex Bayesian techniques are available in JASP encourages their broader adoption and furthers a more inclusive statistical reporting practice. The JASP analyses are implemented in R and a series of R packages

Association between SGLT2 inhibitor treatment and diabetic ketoacidosis and mortality in people with type 2 diabetes admitted to hospital with COVID-19

   Objective  To determine the association between prescription of SGLT2 inhibitors and diabetic ketoacidosis (DKA) incidence or mortality in people with type 2 diabetes hospitalized with COVID-19.  Research Design and Methods  This was a retrospective cohort study based on secondary analysis of data from a large nationwide audit from a network of 40 centres in United Kingdom with data collection up to December 2020 that was originally designed to describe risk factors associated with adverse outcomes among people with diabetes who were admitted to hospital with COVID-19.. The primary outcome for this analysis was DKA on or during hospital admission. The secondary outcome was mortality. Crude, age-sex adjusted and multivariable logistic regression models, were used to generate odds ratios and 95% confidence intervals for people prescribed SGLT2 inhibitor compared to those not prescribed SGLT2 inhibitor.   Results  The original national audit included 3067 people with type 2 diabetes who were admitted to hospital with COVID-19, of whom 230 (7.5%) were prescribed SGLT2 inhibitors prior to hospital admission. Mean (SD) age of the overall cohort was 72 years, 62.3% were men and 34.9% were prescribed insulin. Overall, 2.8% of the total population had DKA and 35.6% people died. The adjusted odds of DKA were not significantly different between those prescribed SGLT2 inhibitors and those not (OR 0.56, 0.16-1.97). The adjusted odds of mortality associated with SGLT2 inhibitors were similar in the total study population (OR 1.13, 0.78-1.63 ), in the sub-group prescribed insulin (OR 1.02, 0.59-1.77), and in the sub-group that developed DKA (OR 0.21, 0.01-8.76).  Conclusions We demonstrate a low risk of DKA and high mortality rate in people with type 2 diabetes admitted to hospital with COVID-19 and limited power but no evidence of increased risk of DKA or in-hospital mortality associated with prescription of SGLT2 inhibitors. </p

Application of non-HDL cholesterol for population-based cardiovascular risk stratification: results from the Multinational Cardiovascular Risk Consortium.

BACKGROUND: The relevance of blood lipid concentrations to long-term incidence of cardiovascular disease and the relevance of lipid-lowering therapy for cardiovascular disease outcomes is unclear. We investigated the cardiovascular disease risk associated with the full spectrum of bloodstream non-HDL cholesterol concentrations. We also created an easy-to-use tool to estimate the long-term probabilities for a cardiovascular disease event associated with non-HDL cholesterol and modelled its risk reduction by lipid-lowering treatment. METHODS: In this risk-evaluation and risk-modelling study, we used Multinational Cardiovascular Risk Consortium data from 19 countries across Europe, Australia, and North America. Individuals without prevalent cardiovascular disease at baseline and with robust available data on cardiovascular disease outcomes were included. The primary composite endpoint of atherosclerotic cardiovascular disease was defined as the occurrence of the coronary heart disease event or ischaemic stroke. Sex-specific multivariable analyses were computed using non-HDL cholesterol categories according to the European guideline thresholds, adjusted for age, sex, cohort, and classical modifiable cardiovascular risk factors. In a derivation and validation design, we created a tool to estimate the probabilities of a cardiovascular disease event by the age of 75 years, dependent on age, sex, and risk factors, and the associated modelled risk reduction, assuming a 50% reduction of non-HDL cholesterol. FINDINGS: Of the 524 444 individuals in the 44 cohorts in the Consortium database, we identified 398 846 individuals belonging to 38 cohorts (184 055 [48·7%] women; median age 51·0 years [IQR 40·7-59·7]). 199 415 individuals were included in the derivation cohort (91 786 [48·4%] women) and 199 431 (92 269 [49·1%] women) in the validation cohort. During a maximum follow-up of 43·6 years (median 13·5 years, IQR 7·0-20·1), 54 542 cardiovascular endpoints occurred. Incidence curve analyses showed progressively higher 30-year cardiovascular disease event-rates for increasing non-HDL cholesterol categories (from 7·7% for non-HDL cholesterol <2·6 mmol/L to 33·7% for ≥5·7 mmol/L in women and from 12·8% to 43·6% in men; p<0·0001). Multivariable adjusted Cox models with non-HDL cholesterol lower than 2·6 mmol/L as reference showed an increase in the association between non-HDL cholesterol concentration and cardiovascular disease for both sexes (from hazard ratio 1·1, 95% CI 1·0-1·3 for non-HDL cholesterol 2·6 to <3·7 mmol/L to 1·9, 1·6-2·2 for ≥5·7 mmol/L in women and from 1·1, 1·0-1·3 to 2·3, 2·0-2·5 in men). The derived tool allowed the estimation of cardiovascular disease event probabilities specific for non-HDL cholesterol with high comparability between the derivation and validation cohorts as reflected by smooth calibration curves analyses and a root mean square error lower than 1% for the estimated probabilities of cardiovascular disease. A 50% reduction of non-HDL cholesterol concentrations was associated with reduced risk of a cardiovascular disease event by the age of 75 years, and this risk reduction was greater the earlier cholesterol concentrations were reduced. INTERPRETATION: Non-HDL cholesterol concentrations in blood are strongly associated with long-term risk of atherosclerotic cardiovascular disease. We provide a simple tool for individual long-term risk assessment and the potential benefit of early lipid-lowering intervention. These data could be useful for physician-patient communication about primary prevention strategies. FUNDING: EU Framework Programme, UK Medical Research Council, and German Centre for Cardiovascular Research

The Fluorescence Detector of the Pierre Auger Observatory

The Pierre Auger Observatory is a hybrid detector for ultra-high energy cosmic rays. It combines a surface array to measure secondary particles at ground level together with a fluorescence detector to measure the development of air showers in the atmosphere above the array. The fluorescence detector comprises 24 large telescopes specialized for measuring the nitrogen fluorescence caused by charged particles of cosmic ray air showers. In this paper we describe the components of the fluorescence detector including its optical system, the design of the camera, the electronics, and the systems for relative and absolute calibration. We also discuss the operation and the monitoring of the detector. Finally, we evaluate the detector performance and precision of shower reconstructions.Comment: 53 pages. Submitted to Nuclear Instruments and Methods in Physics Research Section

Update on the correlation of the highest energy cosmic rays with nearby extragalactic matter

Data collected by the Pierre Auger Observatory through 31 August 2007 showed evidence for anisotropy in the arrival directions of cosmic rays above the Greisen-Zatsepin-Kuz'min energy threshold, \nobreak{$6\times 10^{19}$eV}. The anisotropy was measured by the fraction of arrival directions that are less than $3.1^\circ$ from the position of an active galactic nucleus within 75 Mpc (using the V\'eron-Cetty and V\'eron $12^{\rm th}$ catalog). An updated measurement of this fraction is reported here using the arrival directions of cosmic rays recorded above the same energy threshold through 31 December 2009. The number of arrival directions has increased from 27 to 69, allowing a more precise measurement. The correlating fraction is $(38^{+7}_{-6})$, compared with $21$ expected for isotropic cosmic rays. This is down from the early estimate of $(69^{+11}_{-13})$. The enlarged set of arrival directions is examined also in relation to other populations of nearby extragalactic objects: galaxies in the 2 Microns All Sky Survey and active galactic nuclei detected in hard X-rays by the Swift Burst Alert Telescope. A celestial region around the position of the radiogalaxy Cen A has the largest excess of arrival directions relative to isotropic expectations. The 2-point autocorrelation function is shown for the enlarged set of arrival directions and compared to the isotropic expectation.Comment: Accepted for publication in Astroparticle Physics on 31 August 201

Advanced functionality for radio analysis in the Offline software framework of the Pierre Auger Observatory

The advent of the Auger Engineering Radio Array (AERA) necessitates the development of a powerful framework for the analysis of radio measurements of cosmic ray air showers. As AERA performs "radio-hybrid" measurements of air shower radio emission in coincidence with the surface particle detectors and fluorescence telescopes of the Pierre Auger Observatory, the radio analysis functionality had to be incorporated in the existing hybrid analysis solutions for fluoresence and surface detector data. This goal has been achieved in a natural way by extending the existing Auger Offline software framework with radio functionality. In this article, we lay out the design, highlights and features of the radio extension implemented in the Auger Offline framework. Its functionality has achieved a high degree of sophistication and offers advanced features such as vectorial reconstruction of the electric field, advanced signal processing algorithms, a transparent and efficient handling of FFTs, a very detailed simulation of detector effects, and the read-in of multiple data formats including data from various radio simulation codes. The source code of this radio functionality can be made available to interested parties on request.Comment: accepted for publication in NIM A, 13 pages, minor corrections to author list and references in v

Search for First Harmonic Modulation in the Right Ascension Distribution of Cosmic Rays Detected at the Pierre Auger Observatory

We present the results of searches for dipolar-type anisotropies in different energy ranges above $2.5\times 10^{17}$ eV with the surface detector array of the Pierre Auger Observatory, reporting on both the phase and the amplitude measurements of the first harmonic modulation in the right-ascension distribution. Upper limits on the amplitudes are obtained, which provide the most stringent bounds at present, being below 2% at 99% $C.L.$ for EeV energies. We also compare our results to those of previous experiments as well as with some theoretical expectations.Comment: 28 pages, 11 figure