Human lymphoma mutations reveal CARD11 as the switch between self-antigen-induced B cell death or proliferation and autoantibody production

Self-tolerance and immunity are actively acquired in parallel through a poorly understood ability of antigen receptors to switch between signaling death or proliferation of antigenbinding lymphocytes in different contexts. It is not known whether this tolerance-immunity switch requires global rewiring of the signaling apparatus or if it can arise from a single molecular change. By introducing individual CARD11 mutations found in human lymphomas into antigen-activated mature B lymphocytes in mice, we find here that lymphoma-derived CARD11 mutations switch the effect of self-antigen from inducing B cell death into T cell- independent proliferation, Blimp1-mediated plasmablast differentiation, and autoantibody secretion. Our findings demonstrate that regulation of CARD11 signaling is a critical switch governing the decision between death and proliferation in antigen-stimulated mature B cells and that mutations in this switch represent a powerful initiator for aberrant B cell responses in vivo

Data linkage to national Australian health insurance data to investigate exposure to environmental hazards: the example of residential asbestos

Introduction The enrolment data for Medicare, the Australian universal health insurance provider, covers almost the entire population. Medicare data are commonly used for data linkage, usually to access national medical and pharmaceutical data. However, the enrolment data also enable the identification of geographical cohorts for studies analysing exposure to environmental hazards. Objectives and Approach One example of this was the ACT Asbestos Health Study examining the health risks associated with living in houses insulated with loose-fill asbestos in the Australian Capital Territory. The Medicare Enrolment File contains the personal details and addresses of all people enrolled since 1984, including all updates to these details. We linked these data to a register of ~1100 affected properties, with subsequent linkage to the national death index and the Australian Cancer Database. We estimated Standardized Incidence Ratios (SIR) for selected cancers in people living in these houses to obtain a measure of exposure to environmental risk within the population. Results After intensive cleaning and standardisation, nearly all (99.8%) of the affected addresses were linked. There were over one million people who had at least one ACT address between 1983 and 2013, and 2% of these had lived at an affected address and classified as exposed. The adjusted incidence of mesothelioma in exposed males was 2·5 times that of unexposed males (SIR 2·54, 95% CI 1·02–5·24), and there were some statistically significant results. The study population, number of deaths and cancers of interest were validated against the ACT census and registry figures. There were some limitations in coverage due to the period of available data, the frequency of address updates, and records with postal rather than residential addresses, but these were tested by sensitivity analyses. Conclusion/Implications The study demonstrates the power of data linkage to (a) obtain a measure of exposure to an environmental risk within a population, and (b) obtain outcomes for the resulting case and control cohorts. This method could be applied in other risk studies where exposure is based on geography

The ATHENA COVID-19 Study: Cohort profile and first findings for people diagnosed with COVID-19 in Queensland, 1 January to 31 December 2020

Background : To date, there are limited Australian data on characteristics of people diagnosed with COVID-19 and on how these characteristics relate to outcomes. The ATHENA COVID-19 Study was established to describe health outcomes and investigate predictors of outcomes for all people diagnosed with COVID-19 in Queensland by linking COVID-19 notification, hospital, general practice and death registry data. This paper reports on the establishment and first findings for the ATHENA COVID-19 Study. Methods : Part 1 of the ATHENA COVID-19 Study used Notifiable Conditions System data from 1 January 2020 to 31 December 2020, linked to: Emergency Department Collection data for the same period; Queensland Health Admitted Patient Data Collections (from 1 January 2010 to 30 January 2021); and Deaths Registrations data (from 1 January 2020 to 17 January 2021). Results : To 31 December 2020, a total of 1,254 people had been diagnosed with SARS-CoV-2 infection in Queensland: half were female (49.8%); two-thirds (67.7%) were aged 20–59 years; and there was an over-representation of people living in less-disadvantaged areas. More than half of people diagnosed (57.6%) presented to an emergency department (ED); 21.2% were admitted to hospital as an inpatient (median length of stay 11 days); 1.4% were admitted to an intensive care unit (82.4% of these required ventilation); and there were six deaths. Analysis of factors associated with these outcomes was limited due to small case numbers: people living in less-disadvantaged areas had a lower risk of being admitted to hospital (test for trend, p < 0.001), while those living in more remote areas were less likely than people living in major cities to present to an ED (test for trend: p=0.007), which may reflect differential health care access rather than health outcomes per se. Increasing age (test for trend, p < 0.001) and being a current/recent smoker (age-sex-adjusted relative risk: 1.61; 95% confidence interval: 1.00, 2.61) were associated with a higher risk of being admitted to hospital. Conclusion : Despite uncertainty in our estimates due to small numbers, our findings are consistent with what is known about COVID-19. Our findings reinforce the value of linking multiple data sources to enhance reporting of outcomes for people diagnosed with COVID-19 and provide a platform for longer term follow-up.This project was funded by Health Innovation, Investment and Research Office (HIIRO), Queensland Healt

Using Newly Linked Data to Assess Equity of Out-Of-Pocket Healthcare Costs in Australia

Describing out-of-pocket (OOP) healthcare costs in relation to ability to pay requires multiple linked data sources not previously available. Current estimates of the progressivity of OOP healthcare costs in Australia are based on self-report surveys. Using newly linked Census to administrative income and medical claims data, we aimed to quantify, for the first time, the progressivity of OOP costs for government-subsidised out-of-hospital healthcare in Australia

Progressivity of out-of-pocket costs for Medicare-subsidised services and medicines in Australia.

Objectives In line with affordability and equity principles, Medicare—Australia’s universal public health insurance system—has measures to limit out-of-pocket costs (OOPC), especially among lower income households. We examined the distribution of OOPC for Medicare-subsidised out-of-hospital services and prescription medicines, for Census households, according to their ability to pay. Methods We used 2016 Australian Census data linked to Medicare claims to obtain OOPC for out-of-hospital services and medicines in each household in 2017-18. We derived household disposable income by combining income information from the Census linked to income tax and social security data. All data were available from the Multi-Agency Data Integration Project, enabled through a partnership of various government agencies. We quantified OOPC as a proportion of equivalised household disposable income and calculated Kakwani indices (K) to measure progressivity. We also used linked National Health Survey data to analyse costs separately by chronic conditions. Results We analysed 85% (n=6,830,365) of all Census private households. Overall, OOPC as a percentage of equivalised household disposable income decreased from 1.16% (out-of-hospital services) and 1.35% (prescription medicines) in the poorest decile to 0.63% and 0.34% in the richest decile, respectively. The regressive trend was less pronounced for out-of-hospital services (K = -0.06), with percentage OOPC relatively stable between the 2nd and 9th income deciles; while percentage OOPC decreased steeply with increasing income for medicines (K = -0.24).  (Chronic conditions results will be presented—embargoed at time of submission) Conclusion OOPC for out-of-hospital Medicare services were mildly regressive while those for prescription medicines were distinctly regressive. Actions to reduce inequity in OOPC for medicines, such as reducing the co-payments for low income households should be considered

Risk of cancer associated with residential exposure to asbestos insulation: a whole-population cohort study

Background The health risks associated with living in houses insulated with asbestos are unknown. Loose-fill asbestos was used to insulate some houses in the Australian Capital Territory (ACT). We compared the incidence of mesothelioma and other cancers in residents of the ACT who did and did not live in these houses. Methods Our cohort study included all ACT residents identified using Medicare enrolment data. These data were linked to addresses of affected residential properties in the ACT to ascertain exposure. We followed up residents by linking data to the Australian Cancer Database and National Death Index. Outcomes were diagnosis of mesothelioma and selected other cancers. Effects were estimated for males and females separately using standardised incidence ratios (SIRs), adjusting for age and calendar time of diagnosis. Findings Between Nov 1, 1983, and Dec 31, 2013, 1 035 578 ACT residents were identified from the Medicare database. Of these, 17 248 (2%) had lived in an affected property, including seven (2%) of 285 people diagnosed with mesothelioma. The adjusted incidence of mesothelioma in males who had lived at an affected property was 2·5 times that of unexposed males (SIR 2·54, 95% CI 1·02–5·24). No mesotheliomas were reported among females who had lived at an affected property. Among individuals who had lived at an affected property, there was an elevated incidence of colorectal cancer in women (SIR 1·73, 95% CI 1·29–2·26) and prostate cancer in men (1·29, 1·07–1·54); colorectal cancer was increased, although not significantly, in males (SIR 1·32, 95% CI 0·99–1·72), with no significant increase in the other cancers studied. Interpretation Residential asbestos insulation is likely to be unsafe. Our findings have important health, social, financial, and legal implications for governments and communities in which asbestos has been used to insulate houses.This work was funded by the ACT Government

Relative rates of cancers and deaths in Australian communities with PFAS exposure.

Objectives The use of firefighting foam containing per- and polyfluoroalkyl substances (PFAS) has resulted in environmental contamination in three Australian communities. We examined whether people who had lived in these communities had higher rates of selected cancers and causes of deaths than those who had lived in comparison areas without known contamination. Approach The three exposure areas of interest were in Katherine (NT), Oakey (Qld) and Williamtown (NSW). We identified those who ever lived in exposure areas by linking street addresses in these areas to addresses collected in Medicare (1983-2019)—a consumer directory for Australia’s universal healthcare system. We also identified a sample of those who had lived in selected comparison areas. Exposed and comparison populations were then linked to Australia’s national cancer and death registries. We estimated standardised incidence ratios (SIRs) for 23 cancers, four causes of death and three control outcomes, adjusting for sex, age and calendar time of diagnosis. Results We observed higher rates of prostate cancer (SIR = 1·76, 95% confidence interval (CI) 1·36–2·24) in Katherine; laryngeal cancer (SIR = 2·71, 95% CI 1·30–4·98), kidney cancer (SIR = 1·82, 95% CI 1·04–2·96) and coronary heart disease (CHD) mortality (SIR = 1·81, 95% CI 1·46–2·33) in Oakey; and lung cancer (SIR = 1·83, 95% CI 1·39–2·38) and CHD mortality (SIR = 1·22, 95% CI 1·01–1·47) in Williamtown. We also saw elevated SIRs for control outcomes—outcomes not known or thought to be associated with PFAS exposure. SIRs for all other outcomes and overall cancer were similar across exposure and comparison areas. Conclusion There was limited evidence to support an association between PFAS exposure and risk of cancer. There was modest evidence of an association with CHD mortality, which merits further study given the links between PFAS and elevated blood lipids

Inequalities in life expectancy in Australia according to education level: a whole-of-population record linkage study

Background: Life expectancy in Australia is amongst the highest globally, but national estimates mask within-country inequalities. To monitor socioeconomic inequalities in health, many high-income countries routinely report life expectancy by education level. However in Australia, education-related gaps in life expectancy are not routinely reported because, until recently, the data required to produce these estimates have not been available. Using newly linked, whole-of-population data, we estimated education-related inequalities in adult life expectancy in Australia. Methods: Using data from 2016 Australian Census linked to 2016-17 Death Registrations, we estimated age-sex-education-specific mortality rates and used standard life table methodology to calculate life expectancy. For men and women separately, we estimated absolute (in years) and relative (ratios) differences in life expectancy at ages 25, 45, 65 and 85 years according to education level (measured in five categories, from university qualification [highest] to no formal qualifications [lowest]). Results: Data came from 14,565,910 Australian residents aged 25 years and older. At each age, those with lower levels of education had lower life expectancies. For men, the gap (highest vs. lowest level of education) was 9.1 (95 %CI: 8.8, 9.4) years at age 25, 7.3 (7.1, 7.5) years at age 45, 4.9 (4.7, 5.1) years at age 65 and 1.9 (1.8, 2.1) years at age 85. For women, the gap was 5.5 (5.1, 5.9) years at age 25, 4.7 (4.4, 5.0) years at age 45, 3.3 (3.1, 3.5) years at 65 and 1.6 (1.4, 1.8) years at age 85. Relative differences (comparing highest education level with each of the other levels) were larger for men than women and increased with age, but overall, revealed a 10–25 % reduction in life expectancy for those with the lowest compared to the highest education level. Conclusions: Education-related inequalities in life expectancy from age 25 years in Australia are substantial, particularly for men. Those with the lowest education level have a life expectancy equivalent to the national average 15–20 years ago. These vast gaps indicate large potential for further gains in life expectancy at the national level and continuing opportunities to improve health equity.This work was supported by the National Health and Medical Research Council of Australia Partnership Project Grant (grant number: 1134707), in conjunction with the Australian Bureau of Statistics, the Australian Institute of Health and Welfare and the National Heart Foundation of Australia. EB is supported by a Principal Research Fellowship from the National Health and Medical Research Council of Australia (ref: 1136128)

Protection from EAE in DOCK8 mutant mice occurs despite increased Th17 cell frequencies in the periphery.

peer reviewedMutation of Dedicator of cytokinesis 8 (DOCK8) has previously been reported to provide resistance to the Th17 cell dependent EAE in mice. Contrary to expectation, we observed an elevation of Th17 cells in two different DOCK8 mutant mouse strains in the steady state. This was specific for Th17 cells with no change in Th1 or Th2 cell populations. In vitro Th cell differentiation assays revealed that the elevated Th17 cell population was not due to a T cell intrinsic differentiation bias. Challenging these mutant mice in the EAE model, we confirmed a resistance to this autoimmune disease with Th17 cells remaining elevated systemically while cellular infiltration in the CNS was reduced. Infiltrating T cells lost the bias toward Th17 cells indicating a relative reduction of Th17 cells in the CNS and a Th17 cell specific migration disadvantage. Adoptive transfers of Th1 and Th17 cells in EAE-affected mice further supported the Th17 cell-specific migration defect, however, DOCK8-deficient Th17 cells expressed normal Th17 cell-specific CCR6 levels and migrated toward chemokine gradients in transwell assays. This study shows that resistance to EAE in DOCK8 mutant mice is achieved despite a systemic Th17 bias