Population differences in risk of disease are common, but the potential genetic basis for these differences is not well understood. A standard approach is to compare genetic risk across populations ...by testing for mean differences in polygenic scores, but existing studies that use this approach do not account for statistical noise in effect estimates (i.e., the GWAS betas) that arise due to the finite sample size of GWAS training data. Here, we show using Bayesian polygenic score methods that the level of uncertainty in estimates of genetic risk differences across populations is highly dependent on the GWAS training sample size, the polygenicity (number of causal variants), and genetic distance (FST) between the populations considered. We derive a Wald test for formally assessing the difference in genetic risk across populations, which we show to have calibrated type 1 error rates under a simplified assumption that all SNPs are independent, which we achieve in practise using linkage disequilibrium (LD) pruning. We further provide closed-form expressions for assessing the uncertainty in estimates of relative genetic risk across populations under the special case of an infinitesimal genetic architecture. We suggest that for many complex traits and diseases, particularly those with more polygenic architectures, current GWAS sample sizes are insufficient to detect moderate differences in genetic risk across populations, though more substantial differences in relative genetic risk (relative risk > 1.5) can be detected. We show that conventional approaches that do not account for sampling error from the training sample, such as using a simple t-test, have very high type 1 error rates. When applying our approach to prostate cancer, we demonstrate a higher genetic risk in African Ancestry men, with lower risk in men of European followed by East Asian ancestry.
The aim of this study was to assess the causal relationship between habitual walking pace and cardiovascular disease risk using a Mendelian randomisation approach. We performed both one- and ...two-sample Mendelian randomisation analyses in a sample of 340,000 European ancestry participants from UK Biobank, applying a range of sensitivity analyses to assess pleiotropy and reverse causality. We used a latent variable framework throughout to model walking pace as a continuous exposure, despite being measured in discrete categories, which provided more robust and interpretable causal effect estimates. Using one-sample Mendelian randomisation, we estimated that a 1 mph (i.e., 1.6 kph) increase in self-reported habitual walking pace corresponds to a 63% (hazard ratio (HR) = 0.37, 95% confidence interval (CI), 0.25-0.55, P = 2.0 × 10
) reduction in coronary artery disease risk. Using conditional analyses, we also estimated that the proportion of the total effect on coronary artery disease mediated through BMI was 45% (95% CI 16-70%). We further validated findings from UK Biobank using two-sample Mendelian randomisation with outcome data from the CARDIoGRAMplusC4D consortium. Our findings suggest that interventions that seek to encourage individuals to walk more briskly should lead to protective effects on cardiovascular disease risk.
The aim of this study was to determine the time course of architectural adaptations in the biceps femoris long head (BFLH) following high or low volume eccentric training. Twenty recreationally ...active males completed a two week standardized period of eccentric Nordic hamstring exercise (NHE) training, followed by four weeks of high (n = 10) or low volume (n = 10) training. Eccentric strength was assessed pre‐ and post intervention and following detraining. Architecture was assessed weekly during training and after two and four weeks of detraining. After six weeks of training, BFLH fascicles increased significantly in the high (23% ± 7%, P < .001, d = 2.87) and low volume (24% ± 4%, P < .001, d = 3.46) groups, but reversed following two weeks of detraining (high volume: −17% ± 5%, P < .001, d = −2.04; low volume: −15% ± 3%, P < .001, d = −2.56) after completing the intervention. Both groups increased eccentric strength after six weeks of training (high volume: 28% ± 20%, P = .009, d = 1.55; low volume: 34% ± 14%, P < .001, d = 2.09) and saw no change in strength following a four week period of detraining (high volume: −7% ± 7%, P = .97, d = −0.31; low volume: −2% ± 5%, P = .99, d = −0.20). Both low and high volume NHE training stimulate increases in BFLH fascicle length and eccentric knee flexor strength. Architectural adaptations reverted to baseline levels within two weeks after ceasing training, but eccentric strength was maintained for at least four weeks. These observations provide novel insight into the effects of training volume and detraining on BFLH architecture and may provide guidance for the implementation of NHE programs.
Recently, there has been a call for vertical jump testing via force-plate analysis to be included in the assessment of individuals rehabilitating from ACLR, and as part of return to play criteria. ......a paucity of information exists to guide clinicians on what tests to perform, what force-plate metrics to assess and how these may change over the time-course of rehabilitation. The aims of this systematic review were to: (1) synthesise all available literature reporting force-plate-derived performance variables during vertical jump testing in individuals with a history of ACLR.
Statistical parametric mapping was used to assess between-limb and between-group regional variation along the relative length of tissues. Previously injured limbs displayed significantly smaller ...muscle-to-aponeurosis volume ratios (P=0.040, Wilcoxon effect size (ES) =0.33) and larger BFlh aponeurosis volumes (P=0.023, ES= 0.36) than control limbs with no history of HSI. Discussion: Theoretically, a smaller BFlh muscle-to-aponeurosis volume ratio in limbs with a history of HSI might alter strains at or near the proximal musculotendinous junction during active lengthening (e.g., the injurious terminal swing phase of sprinting). ...to earlier work, which proposed aponeurosis size as a HSI risk factor, the absence of clear between-limb differences in the HSI cohort presents challenges in identifying aponeurosis volume as a direct risk factor for HSI.
