Transient elastohydrodynamic lubrication analysis of a novel metal-on-metal hip prosthesis with a non-spherical femoral bearing surface

Effective lubrication performance of metal-on-metal hip implants only requires optimum conformity within the main loaded area, while it is advantageous to increase the clearance in the equatorial region. Such a varying clearance can be achieved by using non-spherical bearing surfaces for either acetabular or femoral components. An elastohydrodynamic lubrication model of a novel metal-on-metal hip prosthesis using a non-spherical femoral bearing surface against a spherical cup was solved under loading and motion conditions specified by ISO standard. A full numerical methodology of considering the geometric variation in the rotating non-spherical head in elastohydrodynamic lubrication solution was presented, which is applicable to all non-spherical head designs. The lubrication performance of a hip prosthesis using a specific non-spherical femoral head, Alpharabola, was analysed and compared with those of spherical bearing surfaces and a non-spherical Alpharabola cup investigated in previous studies. The sensitivity of the lubrication performance to the anteversion angle of the Alpharabola head was also investigated. Results showed that the non-spherical head introduced a large squeeze-film action and also led to a large variation in clearance within the loaded area. With the same equatorial clearance, the lubrication performance of the metal-on-metal hip prosthesis using an Alpharabola head was better than that of the conventional spherical bearings but worse than that of the metal-on-metal hip prosthesis using an Alpharabola cup. The reduction in the lubrication performance caused by the initial anteversion angle of the non-spherical head was small, compared with the improvement resulted from the non-spherical geometry

The splice site variant rs11078928 may be associated with a genotype-dependent alteration in expression of GSDMB transcripts.

Published onlineJournal ArticleResearch Support, Non-U.S. Gov'tBACKGROUND: Many genetic variants have been associated with susceptibility to complex traits by genome wide association studies (GWAS), but for most, causal genes and mechanisms of action have yet to be elucidated. Using bioinformatics, we identified index and proxy variants associated with autoimmune disease susceptibility, with the potential to affect splicing of candidate genes. PCR and sequence analysis of whole blood RNA samples from population controls was then carried out for the 8 most promising variants to determine the effect of genetic variation on splicing of target genes. RESULTS: We identified 31 splice site SNPs with the potential to affect splicing, and prioritised 8 to determine the effect of genotype on candidate gene splicing. We identified that variants rs11078928 and rs2014886 were associated with altered splicing of the GSDMB and TSFM genes respectively. rs11078928, present in the asthma and autoimmune disease susceptibility locus on chromosome 17q12-21, was associated with the production of a novel Δ exon5-8 transcript of the GSDMB gene, and a separate decrease in the percentage of transcripts with inclusion of exon 6, whereas the multiple sclerosis susceptibility variant rs2014886, was associated with an alternative TFSM transcript encompassing a short cryptic exon within intron 2. CONCLUSIONS: Our findings demonstrate the utility of a bioinformatic approach in identification and prioritisation of genetic variants effecting splicing of their host genes, and suggest that rs11078928 and rs2014886 may affect the splicing of the GSDMB and TSFM genes respectively.Mendip Golf ClubNIHR Exeter Clinical Research Facilit

Red blood cell distribution width: Genetic evidence for aging pathways in 116,666 volunteers

This is the final version of the article. Available from Public Library of Science via the DOI in this record.INTRODUCTION: Variability in red blood cell volumes (distribution width, RDW) increases with age and is strongly predictive of mortality, incident coronary heart disease and cancer. We investigated inherited genetic variation associated with RDW in 116,666 UK Biobank human volunteers. RESULTS: A large proportion RDW is explained by genetic variants (29%), especially in the older group (60+ year olds, 33.8%, <50 year olds, 28.4%). RDW was associated with 194 independent genetic signals; 71 are known for conditions including autoimmune disease, certain cancers, BMI, Alzheimer's disease, longevity, age at menopause, bone density, myositis, Parkinson's disease, and age-related macular degeneration. Exclusion of anemic participants did not affect the overall findings. Pathways analysis showed enrichment for telomere maintenance, ribosomal RNA, and apoptosis. The majority of RDW-associated signals were intronic (119 of 194), including SNP rs6602909 located in an intron of oncogene GAS6, an eQTL in whole blood. CONCLUSIONS: Although increased RDW is predictive of cardiovascular outcomes, this was not explained by known CVD or related lipid genetic risks, and a RDW genetic score was not predictive of incident disease. The predictive value of RDW for a range of negative health outcomes may in part be due to variants influencing fundamental pathways of aging.This work was supported by an award to DM, TF, AM and LH by the UK Medical Research Council (grant number MR/M023095/1). SEJ is funded by the Medical Research Council (grant: MR/M005070/1). JT is funded by a Diabetes Research and Wellness Foundation Fellowship. RB is funded by the Wellcome Trust and Royal Society grant: 104150/Z/14/Z. MAT, MNW and AM are supported by the Wellcome Trust Institutional Strategic Support Award (WT097835MF). ARW, HY, and TF are supported by the European Research Council grant: 323195:GLUCOSEGENES-FP7-IDEAS-ERC. LF is supported by the Intramural Research Program of the National Institute on Aging, U.S. National Institutes of Health. Input from MD, CLK and GK was supported by the University of Connecticut Health Center. This research has been conducted using the UK Biobank Resource under Application Number 14631. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript

Whole-genome sequencing to understand the genetic architecture of common gene expression and biomarker phenotypes.

Initial results from sequencing studies suggest that there are relatively few low-frequency (&lt;5%) variants associated with large effects on common phenotypes. We performed low-pass whole-genome sequencing in 680 individuals from the InCHIANTI study to test two primary hypotheses: (i) that sequencing would detect single low-frequency-large effect variants that explained similar amounts of phenotypic variance as single common variants, and (ii) that some common variant associations could be explained by low-frequency variants. We tested two sets of disease-related common phenotypes for which we had statistical power to detect large numbers of common variant-common phenotype associations-11 132 cis-gene expression traits in 450 individuals and 93 circulating biomarkers in all 680 individuals. From a total of 11 657 229 high-quality variants of which 6 129 221 and 5 528 008 were common and low frequency (&lt;5%), respectively, low frequency-large effect associations comprised 7% of detectable cis-gene expression traits [89 of 1314 cis-eQTLs at P &lt; 1 × 10(-06) (false discovery rate ∼5%)] and one of eight biomarker associations at P &lt; 8 × 10(-10). Very few (30 of 1232; 2%) common variant associations were fully explained by low-frequency variants. Our data show that whole-genome sequencing can identify low-frequency variants undetected by genotyping based approaches when sample sizes are sufficiently large to detect substantial numbers of common variant associations, and that common variant associations are rarely explained by single low-frequency variants of large effect

Genetic Evidence for a Link Between Favorable Adiposity and Lower Risk of Type 2 Diabetes, Hypertension, and Heart Disease.

Recent genetic studies have identified some alleles that are associated with higher BMI but lower risk of type 2 diabetes, hypertension, and heart disease. These "favorable adiposity" alleles are collectively associated with lower insulin levels and higher subcutaneous-to-visceral adipose tissue ratio and may protect from disease through higher adipose storage capacity. We aimed to use data from 164,609 individuals from the UK Biobank and five other studies to replicate associations between a genetic score of 11 favorable adiposity variants and adiposity and risk of disease, to test for interactions between BMI and favorable adiposity genetics, and to test effects separately in men and women. In the UK Biobank, the 50% of individuals carrying the most favorable adiposity alleles had higher BMIs (0.120 kg/m(2) [95% CI 0.066, 0.174]; P = 1E-5) and higher body fat percentage (0.301% [0.230, 0.372]; P = 1E-16) compared with the 50% of individuals carrying the fewest alleles. For a given BMI, the 50% of individuals carrying the most favorable adiposity alleles were at lower risk of type 2 diabetes (odds ratio [OR] 0.837 [0.784, 0.894]; P = 1E-7), hypertension (OR 0.935 [0.911, 0.958]; P = 1E-7), and heart disease (OR 0.921 [0.872, 0.973]; P = 0.003) and had lower blood pressure (systolic -0.859 mmHg [-1.099, -0.618]; P = 3E-12 and diastolic -0.394 mmHg [-0.534, -0.254]; P = 4E-8). In women, these associations could be explained by the observation that the alleles associated with higher BMI but lower risk of disease were also associated with a favorable body fat distribution, with a lower waist-to-hip ratio (-0.004 cm [95% CI -0.005, -0.003] 50% vs. 50%; P = 3E-14), but in men, the favorable adiposity alleles were associated with higher waist circumference (0.454 cm [0.267, 0.641] 50% vs. 50%; P = 2E-6) and higher waist-to-hip ratio (0.0013 [0.0003, 0.0024] 50% vs. 50%; P = 0.01). Results were strengthened when a meta-analysis with five additional studies was conducted. There was no evidence of interaction between a genetic score consisting of known BMI variants and the favorable adiposity genetic score. In conclusion, different molecular mechanisms that lead to higher body fat percentage (with greater subcutaneous storage capacity) can have different impacts on cardiometabolic disease risk. Although higher BMI is associated with higher risk of diseases, better fat storage capacity could reduce the risk.This is the author accepted manuscript. The final version is available from the American Diabetes Association via http://dx.doi.org/10.2337/db15-167

BREADR: An R Package for the Bayesian Estimation of Genetic Relatedness from Low-coverage Genotype Data

Robust and reliable estimates of how individuals are biologically related to each other are a key source of information when reconstructing pedigrees. In combination with contextual data, reconstructed pedigrees can be used to infer possible kinship practices in prehistoric populations. However, standard methods to estimate biological relatedness from genome sequence data cannot be applied to low coverage sequence data, such as are common in ancient DNA (aDNA) studies. Critically, a statistically robust method for assessing and quantifying the confidence of a classification of a specific degree of relatedness for a pair of individuals, using low coverage genome data, is lacking.In this paper we present the R-package BREADR (Biological RElatedness from Ancient DNA in R), which leverages the so-called pairwise mismatch rate, calculated on optimally-filtered genome-wide pseudo-haploid sequence data, to estimate genetic relatedness up to the second degree, assuming an underlying binomial distribution. BREADR also returns a posterior probability for each degree of relatedness, from identical twins/same individual, first-degree, second-degree or “unrelated” pairs, allowing researchers to quantify and report the uncertainty, even for very low-coverage data. We show that this method accurately recovers degrees of relatedness forsequence data with coverage as low as 0.04X using simulated data (produced as in Popli etal.(Popli et al., 2023))

Human longevity is influenced by many genetic variants: evidence from 75,000 UK Biobank participants

This is the final version of the article. Available from the publisher via the DOI in this record.Variation in human lifespan is 20 to 30% heritable in twins but few genetic variants have been identified. We undertook a Genome Wide Association Study (GWAS) using age at death of parents of middle-aged UK Biobank participants of European decent (n=75,244 with father's and/or mother's data, excluding early deaths). Genetic risk scores for 19 phenotypes (n=777 proven variants) were also tested. In GWAS, a nicotine receptor locus(CHRNA3, previously associated with increased smoking and lung cancer) was associated with fathers' survival. Less common variants requiring further confirmation were also identified. Offspring of longer lived parents had more protective alleles for coronary artery disease, systolic blood pressure, body mass index, cholesterol and triglyceride levels, type-1 diabetes, inflammatory bowel disease and Alzheimer's disease. In candidate analyses, variants in the TOMM40/APOE locus were associated with longevity, but FOXO variants were not. Associations between extreme longevity (mother >=98 years, fathers >=95 years, n=1,339) and disease alleles were similar, with an additional association with HDL cholesterol (p=5.7x10-3). These results support a multiple protective factors model influencing lifespan and longevity (top 1% survival) in humans, with prominent roles for cardiovascular-related pathways. Several of these genetically influenced risks, including blood pressure and tobacco exposure, are potentially modifiable.This work was generously funded by an award to DM, TF, AM, LH and CB by the Medical Research Council MR/M023095/1. This research has been conducted using the UK Biobank Resource, under application 1417. The authors wish to thank the UK Biobank participants and coordinators for this unique dataset. S.E.J. is funded by the Medical Research Council (grant: MR/M005070/1). J.T. is funded by a Diabetes Research and Wellness Foundation Fellowship. R.B. is funded by the Wellcome Trust and Royal Society grant: 104150/Z/14/Z. M.A.T., M.N.W. and A.M. are supported by the Wellcome Trust Institutional Strategic Support Award (WT097835MF). R.M.F. is a Sir Henry Dale Fellow (Wellcome Trust and Royal Society grant: 104150/Z/14/Z). A.R.W. H.Y., and T.M.F. are supported by the European Research Council grant: 323195:GLUCOSEGENES-FP7-IDEAS-ERC. The funders had no influence on study design, data collection and analysis, decision to publish, or preparation of the manuscript. The Framingham Heart Study is supported by Contract No. N01-HC-25195 and HHSN268201500001I and its contract with Affymetrix, Inc for genotyping services (Contract No. N02-HL-6-4278). The phenotypegenotype association analyses were supported by National Institute of Aging R01AG29451. This work has made use of the resources provided by the University of Exeter Science Strategy and resulting Systems Biology initiative. Primarily these include high-performance computing facilities managed by Konrad Paszkiewicz of the College of Environmental and Life Sciences and Pete Leggett of the University of Exeter Academics services unit

Gene-obesogenic environment interactions in the UK Biobank study

This is the final version of the article. Available from the publisher via the DOI in this record.BACKGROUND: Previous studies have suggested that modern obesogenic environments accentuate the genetic risk of obesity. However, these studies have proven controversial as to which, if any, measures of the environment accentuate genetic susceptibility to high body mass index (BMI). METHODS: We used up to 120 000 adults from the UK Biobank study to test the hypothesis that high-risk obesogenic environments and behaviours accentuate genetic susceptibility to obesity. We used BMI as the outcome and a 69-variant genetic risk score (GRS) for obesity and 12 measures of the obesogenic environment as exposures. These measures included Townsend deprivation index (TDI) as a measure of socio-economic position, TV watching, a 'Westernized' diet and physical activity. We performed several negative control tests, including randomly selecting groups of different average BMIs, using a simulated environment and including sun-protection use as an environment. RESULTS: We found gene-environment interactions with TDI (Pinteraction = 3 × 10(-10)), self-reported TV watching (Pinteraction = 7 × 10(-5)) and self-reported physical activity (Pinteraction = 5 × 10(-6)). Within the group of 50% living in the most relatively deprived situations, carrying 10 additional BMI-raising alleles was associated with approximately 3.8 kg extra weight in someone 1.73 m tall. In contrast, within the group of 50% living in the least deprivation, carrying 10 additional BMI-raising alleles was associated with approximately 2.9 kg extra weight. The interactions were weaker, but present, with the negative controls, including sun-protection use, indicating that residual confounding is likely. CONCLUSIONS: Our findings suggest that the obesogenic environment accentuates the risk of obesity in genetically susceptible adults. Of the factors we tested, relative social deprivation best captures the aspects of the obesogenic environment responsible.J.T. is funded by a Diabetes Research and Wellness Foundation Fellowship. S.E.J. is funded by the Medical Research Council (grant: MR/M005070/1). M.A.T., M.N.W. and A.M. are supported by the Wellcome Trust Institutional Strategic Support Award (WT097835MF). A.R.W., H.Y. and T.M.F. are supported by the European Research Council grant: 323195:SZ-245 50371- GLUCOSEGENES-FP7-IDEAS-ERC. R.M.F. is a Sir Henry Dale Fellow (Wellcome Trust and Royal Society grant: 104150/Z/14/Z). R.B. is funded by the Wellcome Trust and Royal Society grant: 104150/Z/14/Z. R.M.A is supported by the Wellcome Trust Institutional Strategic Support Award (WT105618MA). Z.K. is funded by Swiss National Science Foundation (31003A-143914). The funders had no influence on study design, data collection and analysis, decision to publish or preparation of the manuscript. The data reported in this paper are available via application directly to the UK Biobank

Evolutionary quantitative genetics of juvenile body size in a population of feral horses reveals sexually antagonistic selection

This is the author accepted manuscript. The final version is available from Springer via the DOI in this record.Inter-individual variation in juvenile body size can have important consequences for individual fitness, population dynamics, and adaptive evolution. In wild vertebrate populations, larger juvenile size is usually expected to be selected for. However, understanding how such selection may translate into adaptive evolution requires an understanding of the genetic underpinnings of early development and the factors modulating selection. In this study, we characterised the genetic basis of and selection pressures acting upon juvenile body size in a large insular population of feral horses on Sable Island, Canada, to gain insights into the evolution of juvenile body size in wild vertebrate populations. We used pedigree-based quantitative genetic ‘animal models’ to quantify the sources of phenotypic variation in withers-knee length, and assessed the influence of maternal age, sex, and temporal (birth year) and spatial environmental heterogeneity in modulating overwinter survival selection. We found that withers-knee length is moderately heritable and that there was a significant positive genetic correlation between males and females. There was no indication of directional selection in a pooled-sex analysis, but we did find evidence for significant sexually antagonistic selection, with a tendency for smaller body size to be favoured in males and larger body size to be favoured in females. These results suggest that juvenile body size has the potential to evolve in this population, and that selection on juvenile size may play an important role in modulating sex-specific contributions to population dynamics. However, our results also suggest that there is unlikely to be evolutionary change in the mean body size of Sable Island foals.Natural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationRoyal SocietyUniversity of Exete

Novel Developmental Analyses Identify Longitudinal Patterns of Early Gut Microbiota that Affect Infant Growth

It is acknowledged that some obesity trajectories are set early in life, and that rapid weight gain in infancy is a risk factor for later development of obesity. Identifying modifiable factors associated with early rapid weight gain is a prerequisite for curtailing the growing worldwide obesity epidemic. Recently, much attention has been given to findings indicating that gut microbiota may play a role in obesity development. We aim at identifying how the development of early gut microbiota is associated with expected infant growth. We developed a novel procedure that allows for the identification of longitudinal gut microbiota patterns (corresponding to the gut ecosystem developing), which are associated with an outcome of interest, while appropriately controlling for the false discovery rate. Our method identified developmental pathways of Staphylococcus species and Escherichia coli that were associated with expected growth, and traditional methods indicated that the detection of Bacteroides species at day 30 was associated with growth. Our method should have wide future applicability for studying gut microbiota, and is particularly important for translational considerations, as it is critical to understand the timing of microbiome transitions prior to attempting to manipulate gut microbiota in early life