THE RELATIONSHIP OF ANTHROPOMETRY AND BODY COMPOSITION WITH RUNNING ECONOMY

The aim of this study was to investigate the relationships of anthropometry and body composition with running economy within a large heterogeneous cohort of runners. Locomotory energy cost was determined in ninety-four healthy male and female endurance runners across a range of performance standards. Various anthropometric and body composition measurements were taken manually and via DXA scans. The relationships between anthropometry and running economy were assessed using independent Pearson’s correlation and stepwise multiple linear regression. Three parameters, normalised neck and calf perimeters and normalised whole body bone mass explained 30% of the variance in locomotory energy cost. Low locomotory energy cost was related solely to parameters indicating relative slenderness of the body

Combined exercise and visual gaze training improves stepping accuracy in people with diabetic peripheral neuropathy

Publisher's version (útgefin grein)Introduction: Patients with diabetes and diabetic peripheral neuropathy (DPN) place their feet with less accuracy whilst walking, which may contribute to the increased falls-risk. This study examines the effects of a multi-faceted intervention on stepping accuracy, in patients with diabetes and DPN. Methods: Forty participants began the study, of which 29 completed both the pre and post-intervention tests, 8 patients with DPN, 11 patients with diabetes but no neuropathy (D) and 10 healthy controls (C). Accuracy of stepping was measured pre- and post-intervention as participants walked along an irregularly arranged stepping walkway. Participants attended a one-hour session, once a week, for sixteen weeks, involving high-load resistance exercise and visual-motor training. Results: Patients who took part in the intervention improved stepping accuracy (DPN: +45%; D: +36%) (p < 0.05). The diabetic non-intervention (D-NI) group did not display any significant differences in stepping accuracy pre- to post- the intervention period (−7%). Discussion: The improved stepping accuracy observed in patients with diabetes and DPN as a result of this novel intervention, may contribute towards reducing falls-risk. This multi-faceted intervention presents promise for improving the general mobility and safety of patients during walking and could be considered for inclusion as part of clinical treatment programmes.This work was supported by a Clinical Research Grant from the European Foundation for the Study of Diabetes (EFSD).Peer Reviewe

Contributory Factors to Unsteadiness During Walking Up and Down Stairs in Patients With Diabetic Peripheral Neuropathy

OBJECTIVE Although patients with diabetic peripheral neuropathy (DPN) are more likely to fall than age-matched controls, the underlying causative factors are not yet fully understood. This study examines the effects of diabetes and neuropathy on strength generation and muscle activation patterns during walking up and down stairs, with implications for fall risk. RESEARCH DESIGN AND METHODS Sixty-three participants (21 patients with DPN, 21 diabetic controls, and 21 healthy controls) were examined while walking up and down a custom-built staircase. The speed of strength generation at the ankle and knee and muscle activation patterns of the ankle and knee extensor muscles were analyzed. RESULTS Patients with neuropathy displayed significantly slower ankle and knee strength generation than healthy controls during stair ascent and descent (P < 0.05). During ascent, the ankle and knee extensor muscles were activated significantly later by patients with neuropathy and took longer to reach peak activation (P < 0.05). During descent, neuropathic patients activated the ankle extensors significantly earlier, and the ankle and knee extensors took significantly longer to reach peak activation (P < 0.05). CONCLUSIONS Patients with DPN are slower at generating strength at the ankle and knee than control participants during walking up and down stairs. These changes, which are likely caused by altered activations of the extensor muscles, increase the likelihood of instability and may be important contributory factors for the increased risk of falling. Resistance exercise training may be a potential clinical intervention for improving these aspects and thereby potentially reducing fall risk

An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge

There is tremendous potential for genome sequencing to improve clinical diagnosis and care once it becomes routinely accessible, but this will require formalizing research methods into clinical best practices in the areas of sequence data generation, analysis, interpretation and reporting. The CLARITY Challenge was designed to spur convergence in methods for diagnosing genetic disease starting from clinical case history and genome sequencing data. DNA samples were obtained from three families with heritable genetic disorders and genomic sequence data were donated by sequencing platform vendors. The challenge was to analyze and interpret these data with the goals of identifying disease-causing variants and reporting the findings in a clinically useful format. Participating contestant groups were solicited broadly, and an independent panel of judges evaluated their performance. RESULTS: A total of 30 international groups were engaged. The entries reveal a general convergence of practices on most elements of the analysis and interpretation process. However, even given this commonality of approach, only two groups identified the consensus candidate variants in all disease cases, demonstrating a need for consistent fine-tuning of the generally accepted methods. There was greater diversity of the final clinical report content and in the patient consenting process, demonstrating that these areas require additional exploration and standardization. CONCLUSIONS: The CLARITY Challenge provides a comprehensive assessment of current practices for using genome sequencing to diagnose and report genetic diseases. There is remarkable convergence in bioinformatic techniques, but medical interpretation and reporting are areas that require further development by many groups

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of diseas

Genetic effects on gene expression across human tissues

Characterization of the molecular function of the human genome and its variation across individuals is essential for identifying the cellular mechanisms that underlie human genetic traits and diseases. The Genotype-Tissue Expression (GTEx) project aims to characterize variation in gene expression levels across individuals and diverse tissues of the human body, many of which are not easily accessible. Here we describe genetic effects on gene expression levels across 44 human tissues. We find that local genetic variation affects gene expression levels for the majority of genes, and we further identify inter-chromosomal genetic effects for 93 genes and 112 loci. On the basis of the identified genetic effects, we characterize patterns of tissue specificity, compare local and distal effects, and evaluate the functional properties of the genetic effects. We also demonstrate that multi-tissue, multi-individual data can be used to identify genes and pathways affected by human disease-associated variation, enabling a mechanistic interpretation of gene regulation and the genetic basis of disease

An analytical framework for whole-genome sequence association studies and its implications for autism spectrum disorder

Genomic association studies of common or rare protein-coding variation have established robust statistical approaches to account for multiple testing. Here we present a comparable framework to evaluate rare and de novo noncoding single-nucleotide variants, insertion/deletions, and all classes of structural variation from whole-genome sequencing (WGS). Integrating genomic annotations at the level of nucleotides, genes, and regulatory regions, we define 51,801 annotation categories. Analyses of 519 autism spectrum disorder families did not identify association with any categories after correction for 4,123 effective tests. Without appropriate correction, biologically plausible associations are observed in both cases and controls. Despite excluding previously identified gene-disrupting mutations, coding regions still exhibited the strongest associations. Thus, in autism, the contribution of de novo noncoding variation is probably modest in comparison to that of de novo coding variants. Robust results from future WGS studies will require large cohorts and comprehensive analytical strategies that consider the substantial multiple-testing burden

A systematic survey of loss-of-function variants in human protein-coding genes

Genome-sequencing studies indicate that all humans carry many genetic variants predicted to cause loss of function (LoF) of protein-coding genes, suggesting unexpected redundancy in the human genome. Here we apply stringent filters to 2951 putative LoF variants obtained from 185 human genomes to determine their true prevalence and properties. We estimate that human genomes typically contain ~100 genuine LoF variants with ~20 genes completely inactivated. We identify rare and likely deleterious LoF alleles, including 26 known and 21 predicted severe disease-causing variants, as well as common LoF variants in nonessential genes. We describe functional and evolutionary differences between LoF-tolerant and recessive disease genes and a method for using these differences to prioritize candidate genes found in clinical sequencing studies