17 research outputs found
Functional polymorphisms in the P2X7 receptor gene are associated with stress fracture injury
Context: Military recruits and elite athletes are susceptible to stress fracture injuries. Genetic predisposition has been postulated to have a role in their development. The P2X7 receptor (P2X7R) gene, a key regulator of bone remodelling, is a genetic candidate that may contribute to stress fracture predisposition.
Objective: To evaluate the putative contribution of P2X7R to stress fracture injury in two separate cohorts, military personnel and elite athletes.
Methods: In 210 Israeli Defence Forces (IDF) military conscripts, stress fracture injury was diagnosed (n=43) based on symptoms and a positive bone scan. In a separate cohort of 518 elite athletes, self-reported medical imaging scan-certified stress fracture injuries were recorded (n=125). Non-stress fracture controls were identified from these cohorts who had a normal bone scan or no history or symptoms of stress fracture injury. Study participants were genotyped for functional SNPs within the P2X7R gene using proprietary fluorescence-based competitive allele-specific PCR assay. Pearson Chi-square (χ2) tests, corrected for multiple comparisons, were used to assess associations in genotype frequencies.
Results: The variant allele of P2X7R SNP rs3751143 (Glu496Ala- loss of function) was associated with stress fracture injury, while the variant allele of rs1718119 (Ala348Thr- gain of function) was associated with a reduced occurrence of stress fracture injury in military conscripts (P<0.05). The association of the variant allele of rs3751143 with stress fractures was replicated in elite athletes (P<0.05), whereas the variant allele of rs1718119 was also associated with reduced multiple stress fracture cases in elite athletes (P<0.05).
Conclusions: The association between independent P2X7R polymorphisms with stress fracture prevalence supports the role of a genetic predisposition in the development of stress fracture injury
Key questions for modelling COVID-19 exit strategies
Combinations of intense non-pharmaceutical interventions ('lockdowns') were
introduced in countries worldwide to reduce SARS-CoV-2 transmission. Many
governments have begun to implement lockdown exit strategies that allow
restrictions to be relaxed while attempting to control the risk of a surge in
cases. Mathematical modelling has played a central role in guiding
interventions, but the challenge of designing optimal exit strategies in the
face of ongoing transmission is unprecedented. Here, we report discussions from
the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May
2020). A diverse community of modellers who are providing evidence to
governments worldwide were asked to identify the main questions that, if
answered, will allow for more accurate predictions of the effects of different
exit strategies. Based on these questions, we propose a roadmap to facilitate
the development of reliable models to guide exit strategies. The roadmap
requires a global collaborative effort from the scientific community and
policy-makers, and is made up of three parts: i) improve estimation of key
epidemiological parameters; ii) understand sources of heterogeneity in
populations; iii) focus on requirements for data collection, particularly in
Low-to-Middle-Income countries. This will provide important information for
planning exit strategies that balance socio-economic benefits with public
health
Key questions for modelling COVID-19 exit strategies
Combinations of intense non-pharmaceutical interventions (lockdowns) were introduced worldwide to reduce SARS-CoV-2 transmission. Many governments have begun to implement exit strategies that relax restrictions while attempting to control the risk of a surge in cases. Mathematical modelling has played a central role in guiding interventions, but the challenge of designing optimal exit strategies in the face of ongoing transmission is unprecedented. Here, we report discussions from the Isaac Newton Institute 'Models for an exit strategy' workshop (11-15 May 2020). A diverse community of modellers who are providing evidence to governments worldwide were asked to identify the main questions that, if answered, would allow for more accurate predictions of the effects of different exit strategies. Based on these questions, we propose a roadmap to facilitate the development of reliable models to guide exit strategies. This roadmap requires a global collaborative effort from the scientific community and policymakers, and has three parts: (i) improve estimation of key epidemiological parameters; (ii) understand sources of heterogeneity in populations; and (iii) focus on requirements for data collection, particularly in low-to-middle-income countries. This will provide important information for planning exit strategies that balance socio-economic benefits with public health.</p