Marek's Disease Virus VP22: Subcellular Localization and Characterization of Carboxyl Terminal Deletion Mutations

AbstractMarek's disease virus (MDV) is an alphaherpesvirus that causes T cell lymphoma and severe immunosuppression in chickens. The MDV UL49 gene, which encodes the tegument viral protein 22 (VP22), has been expressed as a green fluorescent protein (GFP) fusion protein in chicken embryonic fibroblasts to examine its subcellular localization. As with both human herpesvirus 1 and bovine herpesvirus 1VP22-GFP fusion proteins, the MDV VP22-GFP product binds to microtubules and heterochromatin. In addition, the MDV protein also binds to the centrosomes. During mitosis, VP22-GFP binds to sister chromatids, but dissociates from the centrosomes and the microtubules of the mitotic spindle. A series of VP22 carboxy terminal truncation mutants were constructed to define regions responsible for these binding properties. These mutants identified separable domains or motifs responsible for binding microtubules and heterochromatin

Biological mechanisms underlying inter‐individual variation in factor VIII clearance in haemophilia

Previous studies have highlighted marked inter‐individual variations in factor VIII (FVIII) clearance between patients with haemophilia (PWH). The half‐life of infused FVIII has been reported to vary from as little as 5.3 hours in some adult PWH, up to as long as 28.8 hours in other individuals. These differences in clearance kinetics have been consistently observed using a number of different plasma‐derived and recombinant FVIII products. Furthermore, recent studies have demonstrated that half‐life for extended half‐life (EHL‐) FVIII products also demonstrates significant inter‐patient variation. Since time spent with FVIII trough levels <1% has been shown to be associated with increased bleeding risk in PWH on prophylaxis therapy, this variability in FVIII clearance clearly has major clinical significance. Recent studies have provided significant novel insights into the cellular basis underlying FVIII clearance pathways. In addition, accumulating data have shown that endogenous plasma VWF levels, ABO blood group and age, all play important roles in regulating FVIII half‐life in PWH. Indeed, multiple regression analysis suggests that together these factors account for approximately 34% of the total inter‐individual variation in FVIII clearance observed between subjects with severe haemophilia A. In this review, we consider these and other putative modulators of FVIII half‐life, and discuss the biological mechanisms through which these factors impact upon FVIII clearance in vivo.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/156160/2/hae14078.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/156160/1/hae14078_am.pd

Exploring high mortality rates among people with multiple and complex needs: a qualitative study using peer research methods

Objective To explore the perceived reasons underlying high mortality rates among people with multiple and complex needs.Design Qualitative study using peer research.Setting North East of England.Participants Three focus group discussions were held involving (1) people with lived experience of multiple and complex needs (n=5); (2) front-line staff from health, social care and voluntary organisations that support multiple and complex needs groups (n=7); and (3) managers and commissioners of these organisations (n=9).Results Findings from this study provide valuable perspectives of people with multiple complex needs and those that provide them with support on what may be perceived factors underlying premature mortality. Mental ill health and substance misuse (often co-occurring dual diagnosis) were perceived as influencing premature mortality among multiple and complex needs groups. Perceptions of opportunities to identify people at risk included critical life events (eg, bereavement, relationship breakdown) and transitions (eg, release from prison, completion of drug treatment). Early prevention, particularly supporting young people experiencing adverse childhood experiences, was also highlighted as a priority.Conclusion High mortality in multiple and complex needs groups may be reduced by addressing dual diagnosis, providing more support at critical life events and investing in early prevention efforts. Future interventions could take into consideration the intricate nature of multiple and complex needs and improve service access and navigation

The effect of socioeconomic deprivation on the association between an extended measurement of unhealthy lifestyle factors and health outcomes: a prospective analysis of the UK Biobank cohort

Background: Combinations of lifestyle factors interact to increase mortality. Combinations of traditional factors such as smoking and alcohol are well described, but the additional effects of emerging factors such as television viewing time are not. The effect of socioeconomic deprivation on these extended lifestyle risks also remains unclear. We aimed to examine whether deprivation modifies the association between an extended score of lifestyle-related risk factors and health outcomes. Methods: Data for this prospective analysis were sourced from the UK Biobank, a prospective population-based cohort study. We assigned all participants an extended lifestyle score, with 1 point for each unhealthy lifestyle factor (incorporating sleep duration and high television viewing time, in addition to smoking, excessive alcohol, poor diet [low intake of oily fish or fruits and vegetables, and high intake of red meat or processed meats], and low physical activity), categorised as most healthy (score 0–2), moderately healthy (score 3–5), or least healthy (score 6–9). Cox proportional hazards models were used to examine the association between lifestyle score and health outcomes (all-cause mortality and cardiovascular disease mortality and incidence), and whether this association was modified by deprivation. All analyses were landmark analyses, in which participants were excluded if they had an event (death or cardiovascular disease event) within 2 years of recruitment. Participants with non-communicable diseases (except hypertension) and missing covariate data were excluded from analyses. Participants were also excluded if they reported implausible values for physical activity, sleep duration, and total screen time. All analyses were adjusted for age, sex, ethnicity, month of assessment, history of hypertension, systolic blood pressure, medication for hypercholesterolaemia or hypertension, and body-mass index categories. Findings: 328 594 participants aged 40–69 years were included in the study, with a mean follow-up period of 4·9 years (SD 0·83) after the landmark period for all-cause and cardiovascular disease mortality, and 4·1 years (0·81) for cardiovascular disease incidence. In the least deprived quintile, the adjusted hazard ratio (HR) in the least healthy lifestyle category, compared with the most healthy category, was 1·65 (95% CI 1·25–2·19) for all-cause mortality, 1·93 (1·16–3·20) for cardiovascular disease mortality, and 1·29 (1·10–1·52) for cardiovascular disease incidence. Equivalent HRs in the most deprived quintile were 2·47 (95% CI 2·04–3·00), 3·36 (2·36–4·76), and 1·41 (1·25–1·60), respectively. The HR for trend for one increment change towards least healthy in the least deprived quintile compared with that in the most deprived quintile was 1·25 (95% CI 1·12–1·39) versus 1·55 (1·40–1·70) for all-cause mortality, 1·30 (1·05–1·61) versus 1·83 (1·54–2·18) for cardiovascular disease mortality, and 1·10 (1·04–1·17) versus 1·16 (1·09–1·23) for cardiovascular disease incidence. A significant interaction was found between lifestyle and deprivation for all-cause and cardiovascular disease mortality (both pinteraction&lt;0·0001), but not for cardiovascular disease incidence (pinteraction=0·11). Interpretation: Wide combinations of lifestyle factors are associated with disproportionate harm in deprived populations. Social and fiscal policies that reduce poverty are needed alongside public health and individual-level interventions that address a wider range of lifestyle factors in areas of deprivation

Multimorbidity, polypharmacy, and COVID-19 infection within the UK Biobank cohort

Background: It is now well recognised that the risk of severe COVID-19 increases with some long-term conditions (LTCs). However, prior research primarily focuses on individual LTCs and there is a lack of data on the influence of multimorbidity (≥2 LTCs) on the risk of COVID-19. Given the high prevalence of multimorbidity, more detailed understanding of the associations with multimorbidity and COVID-19 would improve risk stratification and help protect those most vulnerable to severe COVID-19. Here we examine the relationships between multimorbidity, polypharmacy (a proxy of multimorbidity), and COVID-19; and how these differ by sociodemographic, lifestyle, and physiological prognostic factors. Methods and findings: We studied data from UK Biobank (428,199 participants; aged 37–73; recruited 2006–2010) on self-reported LTCs, medications, sociodemographic, lifestyle, and physiological measures which were linked to COVID-19 test data. Poisson regression models examined risk of COVID-19 by multimorbidity/polypharmacy and effect modification by COVID-19 prognostic factors (age/sex/ethnicity/socioeconomic status/smoking/physical activity/BMI/systolic blood pressure/renal function). 4,498 (1.05%) participants were tested; 1,324 (0.31%) tested positive for COVID-19. Compared with no LTCs, relative risk (RR) of COVID-19 in those with 1 LTC was no higher (RR 1.12 (CI 0.96–1.30)), whereas those with ≥2 LTCs had 48% higher risk; RR 1.48 (1.28–1.71). Compared with no cardiometabolic LTCs, having 1 and ≥2 cardiometabolic LTCs had a higher risk of COVID-19; RR 1.28 (1.12–1.46) and 1.77 (1.46–2.15), respectively. Polypharmacy was associated with a dose response higher risk of COVID-19. All prognostic factors were associated with a higher risk of COVID-19 infection in multimorbidity; being non-white, most socioeconomically deprived, BMI ≥40 kg/m2, and reduced renal function were associated with the highest risk of COVID-19 infection: RR 2.81 (2.09–3.78); 2.79 (2.00–3.90); 2.66 (1.88–3.76); 2.13 (1.46–3.12), respectively. No multiplicative interaction between multimorbidity and prognostic factors was identified. Important limitations include the low proportion of UK Biobank participants with COVID-19 test data (1.05%) and UK Biobank participants being more affluent, healthier and less ethnically diverse than the general population. Conclusions: Increasing multimorbidity, especially cardiometabolic multimorbidity, and polypharmacy are associated with a higher risk of developing COVID-19. Those with multimorbidity and additional factors, such as non-white ethnicity, are at heightened risk of COVID-19

Is older age associated with COVID-19 mortality in the absence of other risk factors? General population cohort study of 470,034 participants

Introduction: Older people have been reported to be at higher risk of COVID-19 mortality. This study explored the factors mediating this association and whether older age was associated with increased mortality risk in the absence of other risk factors. Methods: In UK Biobank, a population cohort study, baseline data were linked to COVID-19 deaths. Poisson regression was used to study the association between current age and COVID-19 mortality. Results: Among eligible participants, 438 (0.09%) died of COVID-19. Current age was associated exponentially with COVID-19 mortality. Overall, participants aged ≥75 years were at 13-fold (95% CI 9.13–17.85) mortality risk compared with those &lt;65 years. Low forced expiratory volume in 1 second, high systolic blood pressure, low handgrip strength, and multiple long-term conditions were significant mediators, and collectively explained 39.3% of their excess risk. The associations between these risk factors and COVID-19 mortality were stronger among older participants. Participants aged ≥75 without additional risk factors were at 4-fold risk (95% CI 1.57–9.96, P = 0.004) compared with all participants aged &lt;65 years. Conclusions: Higher COVID-19 mortality among older adults was partially explained by other risk factors. ‘Healthy’ older adults were at much lower risk. Nonetheless, older age was an independent risk factor for COVID-19 mortality

Outcomes among confirmed cases and a matched comparison group in the Long-COVID in Scotland Study

With increasing numbers infected by SARS-CoV-2, understanding long-COVID is essential to inform health and social care support. A Scottish population cohort of 33,281 laboratory-confirmed SARS-CoV-2 infections and 62,957 never-infected individuals were followed-up via 6, 12 and 18-month questionnaires and linkage to hospitalization and death records. Of the 31,486 symptomatic infections,1,856 (6%) had not recovered and 13,350 (42%) only partially. No recovery was associated with hospitalized infection, age, female sex, deprivation, respiratory disease, depression and multimorbidity. Previous symptomatic infection was associated with poorer quality of life, impairment across all daily activities and 24 persistent symptoms including breathlessness (OR 3.43, 95% CI 3.29–3.58), palpitations (OR 2.51, OR 2.36–2.66), chest pain (OR 2.09, 95% CI 1.96–2.23), and confusion (OR 2.92, 95% CI 2.78–3.07). Asymptomatic infection was not associated with adverse outcomes. Vaccination was associated with reduced risk of seven symptoms. Here we describe the nature of long-COVID and the factors associated with it