Informed baseline subtraction of proteomic mass spectrometry data aided by a novel sliding window algorithm

Proteomic matrix-assisted laser desorption/ionisation (MALDI) linear time-of-flight (TOF) mass spectrometry (MS) may be used to produce protein profiles from biological samples with the aim of discovering biomarkers for disease. However, the raw protein profiles suffer from several sources of bias or systematic variation which need to be removed via pre-processing before meaningful downstream analysis of the data can be undertaken. Baseline subtraction, an early pre-processing step that removes the non-peptide signal from the spectra, is complicated by the following: (i) each spectrum has, on average, wider peaks for peptides with higher mass-to-charge ratios (m/z), and (ii) the time-consuming and error-prone trial-and-error process for optimising the baseline subtraction input arguments. With reference to the aforementioned complications, we present an automated pipeline that includes (i) a novel `continuous' line segment algorithm that efficiently operates over data with a transformed m/z-axis to remove the relationship between peptide mass and peak width, and (ii) an input-free algorithm to estimate peak widths on the transformed m/z scale. The automated baseline subtraction method was deployed on six publicly available proteomic MS datasets using six different m/z-axis transformations. Optimality of the automated baseline subtraction pipeline was assessed quantitatively using the mean absolute scaled error (MASE) when compared to a gold-standard baseline subtracted signal. Near-optimal baseline subtraction was achieved using the automated pipeline. The advantages of the proposed pipeline include informed and data specific input arguments for baseline subtraction methods, the avoidance of time-intensive and subjective piecewise baseline subtraction, and the ability to automate baseline subtraction completely. Moreover, individual steps can be adopted as stand-alone routines.Comment: 50 pages, 19 figure

Bayesian Multilevel Compositional Data Analysis: Introduction, Evaluation, and Application

Multilevel compositional data commonly occur in various fields, particularly in intensive, longitudinal studies using ecological momentary assessments. Examples include data repeatedly measured over time that are non-negative and sum to a constant value, such as sleep-wake movement behaviours in a 24-hour day. This article presents a novel methodology for analysing multilevel compositional data using a Bayesian inference approach. This method can be used to investigate how reallocation of time between sleep-wake movement behaviours may be associated with other phenomena (e.g., emotions, cognitions) at a daily level. We explain the theoretical details of the data and the models, and outline the steps necessary to implement this method. We introduce the R package multilevelcoda to facilitate the application of this method and illustrate using a real data example. An extensive parameter recovery simulation study verified the robust performance of the method. Across all simulation conditions investigated in the simulation study, the model had minimal convergence issues (convergence rate > 99%) and achieved excellent quality of parameter estimates and inference, with an average bias of 0.00 (range -0.09, 0.05) and coverage of 0.95 (range 0.93, 0.97). We conclude the article with recommendations on the use of the Bayesian compositional multilevel modelling approach, and hope to promote wider application of this method to answer robust questions using the increasingly available data from intensive, longitudinal studies

Adiposity and the isotemporal substitution of physical activity, sedentary time and sleep among school-aged children : a compositional data analysis approach

Background: Daily activity data are by nature compositional data. Accordingly, they occupy a specific geometry with unique properties that is different to standard Euclidean geometry. This study aimed to estimate the difference in adiposity associated with isotemporal reallocation between daily activity behaviours, and to compare the findings from compositional isotemporal subsitution to those obtained from traditional isotemporal substitution. Methods: We estimated the differences in adiposity (body fat%) associated with reallocating fixed durations of time (isotemporal substitution) between accelerometer-measured daily activity behaviours (sleep, sedentary time and light and moderate-to-vigorous physical activity (MVPA)) among 1728 children aged 9-11 years from Australia, Canada, Finland and the UK (International Study of Childhood Obesity, Lifestyle and the Environment, 2011-2013).We generated estimates from compositional isotemporal substitution models and traditional non-compositional isotemporal substitution models. Results: Both compositional and traditional models estimated a positive (unfavourable) difference in body fat% when time was reallocated from MVPA to any other behaviour. Unlike traditional models, compositional models found the differences in estimated adiposity (1) were not necessarily symmetrical when an activity was being displaced, or displacing another (2) were not linearly related to the durations of time reallocated, and (3) varied depending on the starting composition. Conclusion: The compositional isotemporal model caters for the constrained and therefore relative nature of activity behaviour data and enables all daily behaviours to be included in a single statistical model. The traditional model treats data as real variables, thus the constrained nature of time is not accounted for, nor reflected in the findings. Findings from compositional isotemporal substitution support the importance of MVPA to children's health, and suggest that while interventions to increase MVPA may be of benefit, attention should be directed towards strategies to avoid decline in MVPA levels, particularly among already inactive children. Future applications of the compositional model can extend from pair-wise reallocations to other configurations of time-reallocation, for example, increasing MVPA at the expense of multiple other behaviours.Peer reviewe

Poor outcome of revised resurfacing hip arthroplasty: 397 cases from the Australian Joint Replacement Registry

BACKGROUND AND PURPOSE: Recent years have seen a rapid increase in the use of resurfacing hip arthroplasty despite the lack of literature on the long-term outcome. In particular, there is little evidence regarding the outcome of revisions of primary resurfacing. The purpose of this analysis was to examine the survivorship of primary resurfacing hip arthroplasties that have been revised. PATIENTS AND METHODS: Over 12,000 primary resurfacing hip arthroplasties were recorded by the Australian Orthopaedic Association National Joint Replacement Registry between September 1, 1999 and December 31, 2008. During this time, 397 revisions for reasons other than infection were reported for these primary resurfacings and classified as acetabular, femoral, or both acetabular and femoral revisions. The survivorship of the different types of revisions was estimated using the Kaplan-Meier method and compared using proportional hazard models. Additionally, the outcome of a femoral-only revision was compared to that of primary conventional total hip arthroplasty. RESULTS: Acetabular-only revision had a high risk of re-revision compared to femoral-only and both acetabular and femoral revision (5-year cumulative per cent revision of 20%, 7%, and 5% respectively). Femoral-only revision had a risk of re-revision similar to that of revision of both the acetabular and femoral components. Femoral-only revision had over twice the risk of revision of primary conventional total hip arthroplasty. INTERPRETATION: Revision of a primary resurfacing arthroplasty is associated with a major risk of re-revision. The best outcome is achieved when either the femoral-only or both the acetabular and femoral components are revised. Technically straightforward femoral-only revisions generally have a worse outcome than a primary conventional total hip arthroplasty

Human development index, children's health-related quality of life and movement behaviors:a compositional data analysis

PURPOSE: Health-related quality of life has been related to physical activity, sedentary behavior, and sleep among children from developed nations. These relationships have rarely been assessed in developing nations, nor have behaviors been considered in their true context, as mutually exclusive and exhaustive parts of the movement behavior composition. This study aimed to explore whether children's health-related quality of life is related to their movement behavior composition and if the relationship differs according to human development index.METHODS: Children aged 9-11 years (n = 5855), from the 12-nation cross-sectional observational International Study of Childhood Obesity, Lifestyle and the Environment 2011-2013, self-reported their health-related quality of life (KIDSCREEN-10). Daily movement behaviors were from 24-h, 7-day accelerometry. Isometric log-ratio mixed-effect linear models were used to calculate estimates for difference in health-related quality of life for the reallocation of time between daily movement behaviors.RESULTS: Children from countries of higher human development index reported stronger positive relationships between health-related quality of life and moderate-to-vigorous physical activity, relative to the remaining behaviors (r = 0.75, p = 0.005) than those from lower human development index countries. In the very high human development index strata alone, health-related quality of life was significantly related to the movement behavior composition (p = 0.005), with moderate-to-vigorous physical activity (relative to remaining behaviors) being positively associated with health-related quality of life.CONCLUSIONS: The relationship between children's health-related quality of life and their movement behaviors is moderated by their country's human development index. This should be considered when 24-h movement behavior guidelines are developed for children around the world.</p

Human development index, children's health-related quality of life and movement behaviors:a compositional data analysis

Purpose: Health-related quality of life has been related to physical activity, sedentary behavior, and sleep among children from developed nations. These relationships have rarely been assessed in developing nations, nor have behaviors been considered in their true context, as mutually exclusive and exhaustive parts of the movement behavior composition. This study aimed to explore whether children's health-related quality of life is related to their movement behavior composition and if the relationship differs according to human development index. Methods: Children aged 9-11 years (n = 5855), from the 12-nation cross-sectional observational International Study of Childhood Obesity, Lifestyle and the Environment 2011-2013, self-reported their health-related quality of life (KIDSCREEN-10). Daily movement behaviors were from 24-h, 7-day accelerometry. Isometric log-ratio mixed-effect linear models were used to calculate estimates for difference in health-related quality of life for the reallocation of time between daily movement behaviors. Results: Children from countries of higher human development index reported stronger positive relationships between health-related quality of life and moderate-to-vigorous physical activity, relative to the remaining behaviors (r = 0.75, p = 0.005) than those from lower human development index countries. In the very high human development index strata alone, health-related quality of life was significantly related to the movement behavior composition (p = 0.005), with moderate-to-vigorous physical activity (relative to remaining behaviors) being positively associated with health-related quality of life. Conclusions: The relationship between children's health-related quality of life and their movement behaviors is moderated by their country's human development index. This should be considered when 24-h movement behavior guidelines are developed for children around the world.Dorothea Dumuid, Carol Maher, Lucy K. Lewis, Tyman E. Stanford, Josep Antoni Martín Fernández, Julie Ratcliffe, Peter T. Katzmarzyk, Tiago V. Barreira, Jean-Philippe Chaput, Mikael Fogelholm, Gang Hu, José Maia, Olga L. Sarmiento, Martyn Standage, Mark S. Tremblay, Catrine Tudor-Locke, Timothy Old

Compositional data analysis for physical activity, sedentary time and sleep research

The health effects of daily activity behaviours (physical activity, sedentary time and sleep) are widely studied. While previous research has largely examined activity behaviours in isolation, recent studies have adjusted for multiple behaviours. However, the inclusion of all activity behaviours in traditional multivariate analyses has not been possible due to the perfect multicollinearity of 24-h time budget data. The ensuing lack of adjustment for known effects on the outcome undermines the validity of study findings. We describe a statistical approach that enables the inclusion of all daily activity behaviours, based on the principles of compositional data analysis. Using data from the International Study of Childhood Obesity, Lifestyle and the Environment, we demonstrate the application of compositional multiple linear regression to estimate adiposity from children’s daily activity behaviours expressed as isometric log-ratio coordinates. We present a novel method for predicting change in a continuous outcome based on relative changes within a composition, and for calculating associated confidence intervals to allow for statistical inference. The compositional data analysis presented overcomes the lack of adjustment that has plagued traditional statistical methods in the field, and provides robust and reliable insights into the health effects of daily activity behaviour

Cross-sectional analysis of association between socioeconomic status and utilization of primary total hip joint replacements 2006-7 : Australian orthopaedic association national joint replacement registry

Background The utilization of total hip replacement (THR) surgery is rapidly increasing, however few data examine whether these procedures are associated with socioeconomic status (SES) within Australia. This study examined primary THR across SES for both genders for the Barwon Statistical Division (BSD) of Victoria, Australia.Methods Using the Australian Orthopaedic Association National Joint Replacement Registry data for 2006&ndash;7, primary THR with a diagnosis of osteoarthritis (OA) among residents of the BSD was ascertained. The Index of Relative Socioeconomic Disadvantage was used to measure SES; determined by matching residential addresses with Australian Bureau of Statistics census data. The data were categorised into quintiles; quintile 1 indicating the most disadvantaged. Age- and sex-specific rates of primary THR per 1,000 person years were reported for 10-year age bands using the total population at risk.Results Females accounted for 46.9% of the 642 primary THR performed during 2006&ndash;7. THR utilization per 1,000 person years was 1.9 for males and 1.5 for females. The highest utilization of primary THR was observed in those aged 70&ndash;79&thinsp;years (males 6.1, and females 5.4 per 1,000 person years). Overall, the U-shaped pattern of THR across SES gave the appearance of bimodality for both males and females, whereby rates were greater for both the most disadvantaged and least disadvantaged groups.Conclusions Further work on a larger scale is required to determine whether relationships between SES and THR utilization for the diagnosis of OA is attributable to lifestyle factors related to SES, or alternatively reflects geographic and health system biases. Identifying contributing factors associated with SES may enhance resource planning and enable more effective and focussed preventive strategies for hip OA. <br /