Search

Objectives Long-term sickness absence from employment has negative consequences for the economy and can lead to widened health inequalities. Sick notes (also called ‘fit notes’) are issued by general practitioners when a person cannot work for health reasons for more than 7 days. We quantified the sick note rate in people with evidence of COVID-19 in 2020, 2021 and 2022, as an indication of the burden for people recovering from COVID-19.Design Cohort study.Setting With National Health Service (NHS) England approval, we used routine clinical data (primary care, hospital and COVID-19 testing records) within the OpenSAFELY-TPP database.Participants People 18–64 years with a recorded positive test or diagnosis of COVID-19 in 2020 (n=365 421), 2021 (n=1 206 555) or 2022 (n=1 321 313); general population matched in age, sex and region in 2019 (n=3 140 326), 2020 (n=3 439 534), 2021 (n=4 571 469) and 2022 (n=4 818 870); people hospitalised with pneumonia in 2019 (n=29 673).Primary outcome measure Receipt of a sick note in primary care.Results Among people with a positive SARS-CoV-2 test or COVID-19 diagnosis, the sick note rate was 4.88 per 100 person-months (95% CI 4.83 to 4.93) in 2020, 2.66 (95% CI 2.64 to 2.67) in 2021 and 1.73 (95% CI 1.72 to 1.73) in 2022. Compared with the age, sex and region-matched general population, the adjusted HR for receipt of a sick note over the entire follow-up period (up to 10 months) was 4.07 (95% CI 4.02 to 4.12) in 2020 decreasing to 1.57 (95% CI 1.56 to 1.58) in 2022. The HR was highest in the first 30 days postdiagnosis in all years. Among people hospitalised with COVID-19, after adjustment, the sick note rate was lower than in people hospitalised with pneumonia.Conclusions Given the under-recording of postacute COVID-19-related symptoms, these findings contribute a valuable perspective on the long-term effects of COVID-19. Despite likely underestimation of the sick note rate, sick notes were issued more frequently to people with COVID-19 compared with those without, even in an era when most people are vaccinated. Most sick notes occurred in the first 30 days postdiagnosis, but the increased risk several months postdiagnosis may provide further evidence of the long-term impact.

Abstract Background Multimorbidity, smoking status, and pregnancy are identified as three risk factors associated with more severe outcomes following a SARS-CoV-2 infection, thus vaccination uptake is crucial for pregnant women living with multimorbidity and a history of smoking. This study aimed to examine the impact of multimorbidity, smoking status, and demographics (age, ethnic group, area of deprivation) on vaccine hesitancy among pregnant women in Wales using electronic health records (EHR) linkage. Methods This cohort study utilised routinely collected, individual-level, anonymised population-scale linked data within the Secure Anonymised Information Linkage (SAIL) Databank. Pregnant women were identified from 13th April 2021 to 31st December 2021. Survival analysis was employed to examine and compare the length of time to vaccination uptake in pregnancy by considering multimorbidity, smoking status, as well as depression, diabetes, asthma, and cardiovascular conditions independently. The study also assessed the variation in uptake by multimorbidity, smoking status, and demographics, both jointly and separately for the independent conditions, using hazard ratios (HR) derived from the Cox regression model. Results Within the population cohort, 8,203 (32.7%) received at least one dose of the COVID-19 vaccine during pregnancy, with 8,572 (34.1%) remaining unvaccinated throughout the follow-up period, and 8,336 (33.2%) receiving the vaccine postpartum. Women aged 30 years or older were more likely to have the vaccine in pregnancy. Those who had depression were slightly but significantly more likely to have the vaccine compared to those without depression (HR = 1.08, 95% CI 1.03 to 1.14, p = 0.002). Women living with multimorbidity were 1.12 times more likely to have the vaccine compared to those living without multimorbidity (HR = 1.12, 95% CI 1.04 to 1.19, p = 0.001). Vaccine uptakes were significantly lower among both current smokers and former smokers compared to never smokers (HR = 0.87, 95% CI 0.81 to 0.94, p

Introduction Considering the high prevalence of polypharmacy in pregnant women and the knowledge gap in the risk–benefit safety profile of their often-complex treatment plan, more research is needed to optimise prescribing. In this study, we aim to detect adverse and protective effect signals of exposure to individual and pairwise combinations of medications during pregnancy.Methods and analysis Using a range of real-world data sources from the UK, we aim to conduct a pharmacovigilance study to assess the safety of medications prescribed during the preconception period (3 months prior to conception) and first trimester of pregnancy. Women aged between 15 and 49 years with a record of pregnancy within the Clinical Practice Research Datalink (CPRD) Pregnancy Register, the Welsh Secure Anonymised Information Linkage (SAIL), the Scottish Morbidity Record (SMR) data sets and the Northern Ireland Maternity System (NIMATS) will be included. A series of case control studies will be conducted to estimate measures of disproportionality, detecting signals of association between a range of pregnancy outcomes and exposure to individual and combinations of medications. A multidisciplinary expert team will be invited to a signal detection workshop. By employing a structured framework, signals will be transparently assessed by each member of the team using a questionnaire appraising the signals on aspects of temporality, selection, time and measurement-related biases and confounding by underlying disease or comedications. Through group discussion, the expert team will reach consensus on each of the medication exposure–outcome signal, thereby excluding spurious signals, leaving signals suggestive of causal associations for further evaluation.Ethics and dissemination Ethical approval has been obtained from the Independent Scientific Advisory Committee, SAIL Information Governance Review Panel, University of St. Andrews Teaching and Research Ethics Committee and Office for Research Ethics Committees Northern Ireland (ORECNI) for access and use of CPRD, SAIL, SMR and NIMATS data, respectively.

The past four decades have seen a steady rise of references to ‘security’ by health academics, policy-makers and practitioners, particularly in relation to threats posed by infectious disease pandemics. Yet, despite an increasingly dominant health security discourse, the many different ways in which health and security issues and actors intersect have remained largely unassessed and unpacked in current critical global health scholarship. This paper discusses the emerging and growing health-security nexus in the wake of COVID-19 and the international focus on global health security. In recognising the contested and fluid concept of health security, this paper presents two contrasting approaches to health security: neocolonial health security and universal health security. Building from this analysis, we present a novel heuristic that delineates the multiple intersections and entanglements between health and security actors and agendas to broaden our conceptualisation of global health security configurations and practices and to highlight the potential for harmful unintended consequences, the erosion of global health norms and values, and the risk of health actors being co-opted by the security sector.

Abstract Background Vaccine hesitancy amongst pregnant women has been found to be a concern during past epidemics. This study aimed to (1) estimate COVID-19 vaccination rates among pregnant women in Wales and their association with age, ethnicity, and area of deprivation, using electronic health record (EHR) data linkage, and (2) explore pregnant women’s views on receiving the COVID-19 vaccine during pregnancy using data from a survey recruiting via social media (Facebook, Twitter), through midwives, and posters in hospitals (Born-In-Wales Cohort). Methods This was a mixed-methods study utilising routinely collected linked data from the Secure Anonymised Information Linkage (SAIL) Databank (Objective 1) and the Born-In-Wales Birth Cohort participants (Objective 2). Pregnant women were identified from 13th April 2021 to 31st December 2021. Survival analysis was utilised to examine and compare the length of time to vaccination uptake in pregnancy, and variation in uptake by; age, ethnic group, and deprivation area was examined using hazard ratios (HR) from Cox regression. Survey respondents were women who had a baby during the COVID-19 pandemic or were pregnant between 1st November 2021 and 24th March 2022 and participating in Born-In-Wales. Codebook thematic analysis was used to generate themes from an open-ended question on the survey. Results Population-level data linkage (objective 1): Within the population cohort, 8203 (32.7%) received at least one dose of the COVID-19 vaccine during pregnancy, 8572 (34.1%) remained unvaccinated throughout the follow-up period, and 8336 (33.2%) received the vaccine postpartum. Younger women (

Summary: Background: Exposure to domestic abuse can lead to long-term negative impacts on the victim's physical and psychological wellbeing. The 1998 Crime and Disorder Act requires agencies to collaborate on crime reduction strategies, including data sharing. Although data sharing is feasible for individuals, rarely are whole-agency data linked. This study aimed to examine the knowledge obtained by integrating information from police and health-care datasets through data linkage and analyse associated risk factor clusters. Methods: This retrospective cohort study analyses data from residents of South Wales who were victims of domestic abuse resulting in a Public Protection Notification (PPN) submission between Aug 12, 2015 and March 31, 2020. The study links these data with the victims’ health records, collated within the Secure Anonymised Information Linkage databank, to examine factors associated with the outcome of an Emergency Department attendance, emergency hospital admission, or death within 12 months of the PPN submission. To assess the time to outcome for domestic abuse victims after the index PPN submission, we used Kaplan-Meier survival analysis. We used multivariable Cox regression models to identify which factors contributed the highest risk of experiencing an outcome after the index PPN submission. Finally, we created decision trees to describe specific groups of individuals who are at risk of experiencing a domestic abuse incident and subsequent outcome. Findings: After excluding individuals with multiple PPN records, duplicates, and records with a poor matching score or missing fields, the resulting clean dataset consisted of 8709 domestic abuse victims, of whom 6257 (71·8%) were female. Within a year of a domestic abuse incident, 3650 (41·9%) individuals had an outcome. Factors associated with experiencing an outcome within 12 months of the PPN included younger victim age (hazard ratio 1·183 [95% CI 1·053–1·329], p=0·0048), further PPN submissions after the initial referral (1·383 [1·295–1·476]; p

Summary: Background: The COVID-19 pandemic disrupted healthcare and may have impacted ethnic inequalities in healthcare. We aimed to describe the impact of pandemic-related disruption on ethnic differences in clinical monitoring and hospital admissions for non-COVID conditions in England. Methods: In this population-based, observational cohort study we used primary care electronic health record data with linkage to hospital episode statistics data and mortality data within OpenSAFELY, a data analytics platform created, with approval of NHS England, to address urgent COVID-19 research questions. We included adults aged 18 years and over registered with a TPP practice between March 1, 2018, and April 30, 2022. We excluded those with missing age, sex, geographic region, or Index of Multiple Deprivation. We grouped ethnicity (exposure), into five categories: White, Asian, Black, Other, and Mixed. We used interrupted time-series regression to estimate ethnic differences in clinical monitoring frequency (blood pressure and Hba1c measurements, chronic obstructive pulmonary disease and asthma annual reviews) before and after March 23, 2020. We used multivariable Cox regression to quantify ethnic differences in hospitalisations related to diabetes, cardiovascular disease, respiratory disease, and mental health before and after March 23, 2020. Findings: Of 33,510,937 registered with a GP as of 1st January 2020, 19,064,019 were adults, alive and registered for at least 3 months, 3,010,751 met the exclusion criteria and 1,122,912 were missing ethnicity. This resulted in 14,930,356 adults with known ethnicity (92% of sample): 86.6% were White, 7.3% Asian, 2.6% Black, 1.4% Mixed ethnicity, and 2.2% Other ethnicities. Clinical monitoring did not return to pre-pandemic levels for any ethnic group. Ethnic differences were apparent pre-pandemic, except for diabetes monitoring, and remained unchanged, except for blood pressure monitoring in those with mental health conditions where differences narrowed during the pandemic. For those of Black ethnicity, there were seven additional admissions for diabetic ketoacidosis per month during the pandemic, and relative ethnic differences narrowed during the pandemic compared to the White ethnic group (Pre-pandemic hazard ratio (HR): 0.50, 95% confidence interval (CI) 0.41, 0.60, Pandemic HR: 0.75, 95% CI: 0.65, 0.87). There was increased admissions for heart failure during the pandemic for all ethnic groups, though highest in those of White ethnicity (heart failure risk difference: 5.4). Relatively, ethnic differences narrowed for heart failure admission in those of Asian (Pre-pandemic HR 1.56, 95% CI 1.49, 1.64, Pandemic HR 1.24, 95% CI 1.19, 1.29) and Black ethnicity (Pre-pandemic HR 1.41, 95% CI: 1.30, 1.53, Pandemic HR: 1.16, 95% CI 1.09, 1.25) compared with White ethnicity. For other outcomes the pandemic had minimal impact on ethnic differences. Interpretation: Our study suggests that ethnic differences in clinical monitoring and hospitalisations remained largely unchanged during the pandemic for most conditions. Key exceptions were hospitalisations for diabetic ketoacidosis and heart failure, which warrant further investigation to understand the causes. Funding: LSHTM COVID-19 Response Grant (DONAT15912).

Background In Aotearoa/New Zealand, the first nation-wide coronavirus disease 2019 (COVID-19) lockdown occurred from March 23, 2020 to May 13, 2020, requiring most people to stay at home. Health services had to suddenly change how they delivered healthcare and some services were limited or postponed. This study investigated access to healthcare during this lockdown period, whether patients delayed seeking healthcare and reasons for these delays, focusing on the accessibility of primary care services. Methods Adults (aged 18 years or older) who had contact with primary care services were invited through social media and email lists to participate in an online survey (n = 1010) and 38 people were recruited for in-depth interviews. We thematically analysed qualitative data from the survey and interviews, reported alongside relevant descriptive survey results. Results More than half (55%) of survey respondents delayed seeking healthcare during lockdown. Factors at a national or health system-level that could influence delay were changing public service messages, an excessive focus on COVID-19 and urgent issues, and poor service integration. Influential factors at a primary care-level were communication and outreach, use of technology, gatekeeping, staff manner and the safety of the clinical practice environment. Factors that influenced patients’ individual decisions to seek healthcare were the ability to self-manage and self-triage, consciousness of perceived pressure on health services and fear of infection. Conclusion In future pandemic lockdowns or crises, appropriate access to primary care services can be improved by unambiguous national messages and better integration of services. Primary care practices should adopt rapid proactive outreach to patients, fostering a calm but safe clinical practice environment. More support for patients to self-manage and self-triage appropriately could benefit over-burdened health systems during lockdowns and as part of business as usual in less extraordinary times.

Ankylosing spondylitis is the second most common cause of inflammatory arthritis. However, a successful diagnosis can take a decade to confirm from symptom onset (via x-rays). The aim of this study was to use machine learning methods to develop a profile of the characteristics of people who are likely to be given a diagnosis of AS in future. The Secure Anonymised Information Linkage databank was used. Patients with ankylosing spondylitis were identified using their routine data and matched with controls who had no record of a diagnosis of ankylosing spondylitis or axial spondyloarthritis. Data was analysed separately for men and women. The model was developed using feature/variable selection and principal component analysis to develop decision trees. The decision tree with the highest average F value was selected and validated with a test dataset. The model for men indicated that lower back pain, uveitis, and NSAID use under age 20 is associated with AS development. The model for women showed an older age of symptom presentation compared to men with back pain and multiple pain relief medications. The models showed good prediction (positive predictive value 70%-80%) in test data but in the general population where prevalence is very low (0.09% of the population in this dataset) the positive predictive value would be very low (0.33%-0.25%). Machine learning can be used to help profile and understand the characteristics of people who will develop AS, and in test datasets with artificially high prevalence, will perform well. However, when applied to a general population with low prevalence rates, such as that in primary care, the positive predictive value for even the best model would be 1.4%. Multiple models may be needed to narrow down the population over time to improve the predictive value and therefore reduce the time to diagnosis of ankylosing spondylitis.

Objectives Examine if pre-COVID-19 pandemic (prior March 2020) health-related behaviours during primary school are associated with (1) being tested for SARS-CoV-2 and (2) testing positive between 1 March 2020 and 31 August 2021.Design Retrospective cohort study using an online cohort survey (January 2018 to February 2020) linked with routine PCR SARS-CoV-2 test results.Setting Children attending primary schools in Wales (2018–2020), UK, who were part of the Health and Attainment of Pupils in a Primary Education Network (HAPPEN)_school network.Participants Complete linked records of eligible participants were obtained for n=7062 individuals. 39.1% (n=2764) were tested (age 10.6±0.9; 48.9% girls) and 8.1% (n=569) tested positive for SARS-CoV-2 (age 10.6±1.0; 54.5% girls).Main outcome measures Logistic regression of health-related behaviours and demographics were used to determine the ORs of factors associated with (1) being tested for SARS-CoV-2 and (2) testing positive for SARS-CoV-2.Results Consuming sugary snacks (1–2 days/week OR=1.24, 95% CI 1.04 to 1.49; 5–6 days/week OR=1.31, 95% CI 1.07 to 1.61; reference 0 days), can swim 25 m (OR=1.21, 95% CI 1.06 to 1.39) and age (OR=1.25, 95% CI 1.16 to 1.35) were associated with an increased likelihood of being tested for SARS-CoV-2. Eating breakfast (OR=1.52, 95% CI 1.01 to 2.27), weekly physical activity ≥60 min (1–2 days OR=1.69, 95% CI 1.04 to 2.74; 3–4 days OR=1.76, 95% CI 1.10 to 2.82; reference 0 days), out-of-school club participation (OR=1.06, 95% CI 1.02 to 1.10), can ride a bike (OR=1.39, 95% CI 1.00 to 1.93), age (OR=1.16, 95% CI 1.05 to 1.28) and girls (OR=1.21, 95% CI 1.00 to 1.46) were associated with an increased likelihood of testing positive for SARS-CoV-2. Living in least deprived areas (quintile 4 OR=0.64, 95% CI 0.46 to 0.90; quintile 5 OR=0.64, 95% CI 0.46 to 0.89) compared with the most deprived (quintile 1) was associated with a decreased likelihood.Conclusions Associations may be related to parental health literacy and monitoring behaviours. Physically active behaviours may include coparticipation with others and exposure to SARS-CoV-2. A risk-versus-benefit approach must be considered in relation to promoting these health behaviours, given the importance of health-related behaviours such as childhood physical activity for development.

Abstract Background Health services internationally have been compelled to change their methods of service delivery in response to the global COVID-19 pandemic, to mitigate the spread of infection amongst health professionals and patients. In Aotearoa/New Zealand, widespread electronic delivery of prescriptions (e-prescribing) was enabled. The aim of the research was to explore patients’ experiences of how lockdown, changes to prescribing and the interface between general practices and community pharmacy affected access to prescription medications. Method The research employed a mixed-method approach. This included an online survey (n = 1,010) and in-depth interviews with a subset of survey respondents (n = 38) during the first COVID-19 lockdown (March–May 2020). Respondents were recruited through a snowballing approach, starting with social media and email list contacts of the research team. In keeping with the approach, descriptive statistics of survey data and thematic analysis of qualitative interview and open-ended questions in survey data were combined. Results For most respondents who received a prescription during lockdown, this was sent directly to the pharmacy. Most people picked up their medication from the pharmacy; home delivery of medication was rare (4%). Survey and interview respondents wanted e-prescribing to continue post-lockdown and described where things worked well and where they encountered delays in the process of acquiring prescription medication. Conclusions E-prescribing has the potential to improve access to prescription medication and is convenient for patients. The increase in e-prescribing during lockdown highlighted how the system could be improved, through better feedback about errors, more consistency across practices and pharmacies, more proactive communication with patients, and equitable prescribing costs.

Abstract Background Over recent years there have been several major terror attacks in cities across Europe. These attacks result in deaths, physical injuries, and pose long-term threats to mental health and wellbeing of large populations. Although psychologists have completed important work on mental health responses to disaster exposure including terrorist attacks, the mental health impacts of such attacks have been comparatively less examined in academic literature than the acute health response to physical injuries. This paper reflects on Southwark Council’s pioneering public mental health response to the June 2017 terror attack at London Bridge and Borough Market. It aims to explore perceptions of the mental health impact of the incident by those living and working in the borough. Methods A rapid qualitative evaluation informed by the logic underpinning Southwark Council’s response was conducted. Seven formative interviews were undertaken with individuals involved in the response planning and/or delivery, enabling the evaluation team to establish the response’s theoretical basis. Subsequently, nineteen semi-structured interviews with consenting Council employees, residents, business owners, and workers from the Borough were conducted to understand perceived mental health impacts of the attack and the success of the Council response. Thematic analysis of transcribed interviews was undertaken to evaluate the extent to which the response was implemented successfully. Results Participants reported feeling the attack had a wide-reaching negative impact on the mental health of residents, those working in the borough and visitors who witnessed the attack. Delivering the response was a challenge and response visibility within the community was limited. Participants suggested a comprehensive systematic approach to health needs assessment informed by knowledge and relationships of key Council workers and community stakeholders is imperative when responding to terrorist incidents. Improved communication and working relationships between statutory organisations and community stakeholders would ensure community groups are better supported. Prioritising mental health needs of terror attack responders to mitigate persisting negative impacts was highlighted. Conclusions This article highlights a potential public health approach and need for developing robust practical guidance in the aftermath of terror attacks. This approach has already influenced the response to the Christchurch mosque shooting in 2019.

Introduction Early alcohol use has significant association with poor health outcomes. Individual risk factors around early alcohol use have been identified, but a holistic, data-driven investigation into health and household environmental factors on early alcohol use is yet to be undertaken. Objectives This study aims to investigate the relationship between preceding health events, household exposures and early alcohol use during adolescence using a two-stage data-driven approach. Methods In stage one, a study population (N=1,072) were derived from the Millennium Cohort Study (MCS) Wales (born between 2000-2002). MCS data were first linked with electronic-health records. Factors associated with early (

Abstract Background During the first COVID-19 pandemic ‘lockdown’ in Aotearoa/New Zealand (March–May 2020, in which strict ‘stay at home’ measures were introduced), general practices were advised to use telephone and video consultations (telehealth) wherever possible instead of the usual in-person visits. This was a sudden change for most practices and patients. This research aimed to explore how patients accessed general practice during lockdown and evaluate their experiences with telehealth, to inform how telehealth could be most effectively used in the future. Methods Using a mixed-method approach, we undertook an online survey and in-depth interviews with adults (> 18 years) who had contact with practices during lockdown, recruited through social media and email lists. We present descriptive statistics from the survey data (n = 1010) and qualitative analysis of interview data (n = 38) and open-ended survey questions, using a framework of access to health care, from the patient’s perspective. Results In general, patients reported high satisfaction with telehealth in general practice during lockdown. Telehealth was convenient and allowed patients to safely access health care without having to weigh-up the fear of COVID-19 infection against the need to be seen. Telehealth worked best for routine and familiar health issues and when rapport was established between patients and clinicians. This was easier with a pre-existing clinical relationship, but not impossible without one. Telehealth was less suitable when a physical examination was needed, when the diagnosis was unknown or for patients who had a strong preference to be seen in-person. Conclusions Even in this disruptive lockdown period, that prompted an unexpected and rapid implementation of telehealth services in general practices, most patients had positive experiences with telehealth. In the future, patients want the choice of consultation type to match their needs, circumstances, and preferences. Technological issues and funding barriers may need to be addressed, and clear communication for both patients and clinicians is needed about key aspects of telehealth (e.g. cost, appropriateness, privacy). Maintaining telehealth as an option post-lockdown has the potential to increase timely and safe access to primary health care for many patients.

Objective To examine if mortality rates are lower in people with intellectual disability who have had a health check compared with those who have not had health checks.Setting General practice records of 26 954 people with an intellectual disability in Wales between 2005–2017, of which 7650 (28.4%) with a health check were matched 1:2 with those without a health check.Primary outcome measure Office of National Statistics mortality data; a Cox regression was utilised to examine time to death adjusted for comorbidities and gender.Results Patients who had a health check were stratified by those who (1) had a confirmed health check, that is, Read Code for a health check (n=7650 (28.4 %)) and (2) had no evidence of receiving a health check in their medical record. Patients with a health check were matched for age at time of health check with two people who did not have a health check. The health check was associated with improved survival for those with autism or Down’s Syndrome (HR 0.58 (95% CI 0.37 to 0.91) and HR 0.76 (95% CI 0.64 to 0.91), respectively). There was no evidence of improved survival for those diagnosed with diabetes or cancer. The people who had a health check were more likely to be older, have epilepsy and less likely to have autism or Down’s syndrome.Conclusions Health checks are likely to influence survival if started before a person is diagnosed with a chronic condition, especially for people with autism or Down’s syndrome.

Inequities in the provision of accessible primary health care contribute to poor health outcomes and health inequity. This study evaluated inequities in the prevalence and consequences of barriers that children face in seeing a general practitioner (GP) in Aotearoa New Zealand. We analysed data on 5,947 children from the Growing Up in New Zealand longitudinal study cohort on barriers to seeing a GP in the previous year, reported by mothers when their children were aged 24 months and 54 months (in 2011/12 and 2013/14 respectively); and maternal-reported hospitalisations in the year prior to age 54 months. We used logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CIs) for consequences of these barriers.Overall, 4.7% (n = 279) of children experienced barriers to seeing a GP in the year to 24 months and 5.5% (n = 325) in the year to 54 months. At each age, and for each specific barrier studied, barriers were more prevalent among Māori (the indigenous people of Aotearoa New Zealand), and among Pacific, compared to New Zealand European, children. Children facing barriers in the year to age 24 months were twice as likely to be hospitalised in the year to 54 months (OR 2.18, 95%CI: 1.38 to 3.44). When this relationship was analysed by ethnicity, the association was strongest for Māori (OR: 2.92, 95%CI: 1.60 to 5.30), less strong for Pacific (OR 2.01, 95%CI: 0.92 to 4.37) and not present for New Zealand European (OR 1.27, 95%CI 0.39 to 4.12) families.Barriers that children face to seeing a GP have social and cost implications for families and the health system. Changes to the health system, and future health policy, must align with the New Zealand government’s obligations under Te Tiriti o [The Treaty of] Waitangi, to ensure that health equity becomes a reality for Māori.

IntroductionSchool-based COVID-19 mitigation strategies have greatly impacted the primary school day (children aged 3-11) including: wearing face coverings, two metre distancing, no mixing of children, and no breakfast clubs or extra-curricular activities. This study examines these mitigation measures and association with COVID-19 infection, respiratory infection, and school staff wellbeing between October to December 2020 in Wales, UK.MethodsA school staff survey captured self-reported COVID-19 mitigation measures in the school, participant anxiety and depression, and open-text responses regarding experiences of teaching and implementing measures. These survey responses were linked to national-scale COVID-19 test results data to examine association of measures in the school and the likelihood of a positive (staff or pupil) COVID-19 case in the school (clustered by school, adjusted for school size and free school meals using logistic regression). Linkage was conducted through the SAIL (Secure Anonymised Information Linkage) Databank.ResultsResponses were obtained from 353 participants from 59 primary schools within 15 of 22 local authorities. Having more direct non-household contacts was associated with a higher likelihood of COVID-19 positive case in the school (1-5 contacts compared to none, OR 2.89 (1.01, 8.31)) and a trend to more self-reported cold symptoms. Staff face covering was not associated with a lower odds of school COVID-19 cases (mask vs. no covering OR 2.82 (1.11, 7.14)) and was associated with higher self-reported cold symptoms. School staff reported the impacts of wearing face coverings on teaching, including having to stand closer to pupils and raise their voices to be heard. 67.1% were not able to implement two metre social distancing from pupils. We did not find evidence that maintaining a two metre distance was associated with lower rates of COVID-19 in the school.ConclusionsImplementing, adhering to and evaluating COVID-19 mitigation guidelines is challenging in primary school settings. Our findings suggest that reducing non-household direct contacts lowers infection rates. There was no evidence that face coverings, two metre social distancing or stopping children mixing was associated with lower odds of COVID-19 or cold infection rates in the school. Primary school staff found teaching challenging during COVID-19 restrictions, especially for younger learners and those with additional learning needs.

The inclusion of machine-learning-derived models in systematic reviews of risk prediction models for colorectal cancer is rare. Whilst such reviews have highlighted methodological issues and limited performance of the models included, it is unclear why machine-learning-derived models are absent and whether such models suffer similar methodological problems. This scoping review aims to identify machine-learning models, assess their methodology, and compare their performance with that found in previous reviews. A literature search of four databases was performed for colorectal cancer prediction and prognosis model publications that included at least one machine-learning model. A total of 14 publications were identified for inclusion in the scoping review. Data was extracted using an adapted CHARM checklist against which the models were benchmarked. The review found similar methodological problems with machine-learning models to that observed in systematic reviews for non-machine-learning models, although model performance was better. The inclusion of machine-learning models in systematic reviews is required, as they offer improved performance despite similar methodological omissions; however, to achieve this the methodological issues that affect many prediction models need to be addressed.

Background Uveal melanoma (UM) is the most common intraocular malignancy in adults. In contrast to cutaneous melanoma (CM), there is no standard therapy, and the efficacy and safety of dual checkpoint blockade with nivolumab and ipilimumab is not well defined.Methods We conducted a retrospective analysis of patients with metastatic UM (mUM) who received treatment with ipilimumab plus nivolumab across 14 academic medical centers. Toxicity was graded using National Cancer Institute Common Terminology Criteria for Adverse Events V.5.0. Progression-free survival (PFS) and overall survival (OS) were calculated using Kaplan-Meier methodology.Results 89 eligible patients were identified. 45% had received prior therapy, which included liver directed therapy (29%), immunotherapy (21%), targeted therapy (10%) and radiation (16%). Patients received a median 3 cycles of ipilimumab plus nivolumab. The median follow-up time was 9.2 months. Overall response rate was 11.6%. One patient achieved complete response (1%), 9 patients had partial response (10%), 21 patients had stable disease (24%) and 55 patients had progressive disease (62%). Median OS from treatment initiation was 15 months and median PFS was 2.7 months. Overall, 82 (92%) of patients discontinued treatment, 34 due to toxicity and 27 due to progressive disease. Common immune-related adverse events were colitis/diarrhea (32%), fatigue (23%), rash (21%) and transaminitis (21%).Conclusions Dual checkpoint inhibition yielded higher response rates than previous reports of single-agent immunotherapy in patients with mUM, but the efficacy is lower than in metastatic CM. The median OS of 15 months suggests that the rate of clinical benefit may be larger than the modest response rate.

ObjectivesProton pump inhibitors (PPIs) are commonly prescribed for prevention and treatment of gastrointestinal conditions or for gastroprotection from other drugs. Research suggests they are linked to increased dementia risk. We use linked national health data to examine the association between PPI use and the development of incident dementia.Methods and findingsA population-based study using electronic health-data from the Secure Anonymised Information Linkage (SAIL) Databank, Wales (UK) from 1999 to 2015. Of data available on 3,765,744 individuals, a cohort who had ever been prescribed a PPI was developed (n = 183,968) for people aged 55 years and over and compared to non-PPI exposed individuals (131,110). Those with prior dementia, mild-cognitive-impairment or delirium codes were excluded. Confounding factors included comorbidities and/or drugs associated with them. Comorbidities might include head injury and some examples of medications include antidepressants, antiplatelets and anticoagulants. These commonly prescribed drugs were investigated as it was not feasible to explore all drugs in this study. The main outcome was a diagnosis of incident dementia. Cox proportional hazard regression modelling was used to calculate the Hazard ratio (HR) of developing dementia in PPI-exposed compared to unexposed individuals while controlling for potential confounders. The mean age of the PPI exposed individuals was 69.9 years and 39.8% male while the mean age of the unexposed individuals was 72.1 years and 41.1% male. The rate of PPI usage was 58.4% (183,968) and incident dementia rate was 11.8% (37,148/315,078). PPI use was associated with decreased dementia risk (HR: 0.67, 95% CI: 0.65 to 0.67, pConclusionsThis study, using large-scale, multi-centre health-data was unable to confirm an association between PPI use and increased dementia risk. Previously reported links may be associated with confounders of people using PPI's, such as increased risk of cardiovascular disease and/or depression and their associated medications which may be responsible for any increased risk of developing dementia.

Cellulases have a broad range of different industrial applications, ranging from food and beverages to pulp and paper and the biofuels area. Here a metagenomics based strategy was used to identify the cellulolytic enzyme CelRH5 from the rhizosphere. CelRH5 is a novel monospecific endo-β-1,4-glucanase belonging to the glycosyl hydrolase family 5 (GH5). Structural based modeling analysis indicated that CelRH5 is related to endo-β-1,4-glucanases derived from thermophilic microorganisms such as Thermotoga maritima, Fervidobacterium nodosum, and Ruminiclostridium thermocellum sharing 30-40% amino acid sequence identity. The molecular weight of the enzyme was determined as 40.5 kDa. Biochemical analyses revealed that the enzyme displayed good activity with soluble forms of cellulose as a substrate such as ostazin brilliant red hydroxyethyl cellulose (OBR-HEC), carboxymethylcellulose (CMC), hydroxyethyl cellulose (HEC), and insoluble azurine cross-linked hydroxyethylcellulose (AZCL-HEC). The enzyme shows highest enzymatic activity at pH 6.5 with high pH tolerance, remaining stable in the pH range 4.5–8.5. Highest activity was observed at 40°C, but CelRH5 is psychrotolerant being active and stable at temperatures below 30°C. The presence of the final products of cellulose hydrolysis (glucose and cellobiose) or metal ions such as Na+, K+, Li+, and Mg2+, as well as ethylenediaminetetraacetic acid (EDTA), urea, dithiothreitol (DTT), dimethyl sulfoxide (DMSO), 2-mercaptoethanol (2-ME) or glycerol, did not have a marked effect on CelRH5 activity. However, the enzyme is quite sensitive to the presence of 10 mM ions Zn2+, Ni2+, Co2+, Fe3+ and reagents such as 1 M guanidine HCl, 0.1% sodium dodecyl sulfate (SDS) and 20% ethanol. Given that it is psychrotolerant and retains activity in the presence of final cellulose degradation products, metal ions and various reagents, which are common in many technological processes; CelRH5 may be potential suitability for a variety of different biotechnological applications.

Introduction Excessive alcohol consumption has adverse effects on health but there is a recognised need for longitudinal analysis of population data to improve our understanding of the patterns of alcohol use, harms to consumers and those in their immediate environment. This paper describes the protocol for the project “Electronic Longitudinal Alcohol Study in Communities” (ELAStiC) that aims to leverage the value of a broad set of cross-linked cohorts, e-cohorts, surveys and data linkage facilities to construct an alcohol-specific analytical platform in the United Kingdom. Aims and objectives ELAStiC aims to address four aims: (a) the effect on children’s’ health and educational achievement of living in household in which one or more adults experience alcohol-related harm; (b) the longitudinal relationship between alcohol consumption, physical and mental health in adults in a Welsh county (Caerphilly); (c) the patterns of Welsh alcohol-related hospital admissions across 16 years; (d) the socioeconomic patterns in alcohol-related hospital admission in adults in Wales, considering individual alcohol consumption and other factors. Methods Datasets containing routinely collected electronic healthcare records including data from hospital admissions, general practice, cohorts specific to children as well as data from project specific observational studies. In addition, socioeconomic descriptors and mortality data were linked to these datasets. Conclusion The data used represent either Welsh population or county level. This level of representativeness could offer robust confidence for future analyses. In excess of 10 years of longitudinal data will help to understand alcohol-related disease and health trajectories across the lifespan.

ABSTRACT Objectives 1) To develop a fully data-driven framework for automatically identifying patients with a condition from routine electronic primary care records; 2) to identify informative codes (risk factors) of arthropathy conditions in primary care records that can accurately predict a diagnosis of the conditions in secondary care records. Approach This study linked routine primary and secondary care records in Wales, UK held in the SAIL (Secured Anonymised Information Linkage) databank, in which the secondary care records were used as golden standard. As such, we proposed to use machine learning techniques to extract patient information and identify cohorts with a condition from the large and high-dimensional linked dataset using the following phases: data preparation, performed in the machine learning context fashion; pre-selection of initial features, ranking and selecting features into a meaningful subset by using feature selection methods; and identification algorithm development which incorporates mechanisms of tackling the imbalanced nature of the data. This data-driven framework was then validated on an independent dataset, and compared with existing algorithm which had been developed using expert clinician knowledge for arthropathy conditions. Results Rheumatoid arthritis (RA) and ankylosing spondylitis (AS) were used to demonstrate the feasibility of this framework. Linking primary care records with the secondary care rheumatology clinical system, we collected 9,657 patients with 1,484 RA patients and 204 AS patients. The proposed framework identified various compact subsets of informative features (risk factors) from 43,100 potential Read codes. Applying to an independent test data, this framework achieved the classification accuracy and positive predictive values (PPVs) of 86.19% and 88.46% respectively for RA and 99.23 % and 97.75% respectively for AS, which are comparable with the performance of clinical knowledge-based method - the accuracy of 85.85%, the PPV of 85.28% for RA and the accuracy of 97.86% , the PPV of 95.65% for AS. Conclusion The proposed data-driven framework provides a rapid and cost-effective way of reliably identifying patients with a medical condition from primary care data. It performed as well as the clinically derived algorithm. This framework does not intend to substitute clinical expertise, instead it provides an decision support tool for clinicians during their decision process, in particular selection of patients for clinical trials.

ABSTRACT Objectives The Welsh Health Survey (WHS) has been carried out annually since 2003. Approximately 15000 adults and 3000 children are interviewed each year on a wide range of health related questions. From 2013, adult participants were asked to consent to their data being linked and incorporated into the SAIL databank, allowing linkage to the SAIL datasets. Here we focus on linkage to primary care, General Practitioner (GP), data. This provides a unique opportunity to compare some clinical concepts which are represented in both datasets. The questionnaires in the WHS are taken at a set moment in time and are standardised for everyone questioned, and are more complete. In comparison the GP data collects responses over the patients’ interactions with the GP, but the information may have been elicited in different ways and data are much more likely to be missing. Approach We have chosen a small number of variables scored in both datasets for comparison. BMI and its core variables height and weight are the principal numeric variables found in both datasets. Smoking behaviour is coded for 96% of people in the GP data, alcohol consumption for 79% and exercise for 62%. In contrast, in the WHS data, coding is for 99% (smoking), 99% (alcohol) and 97% (exercise). Results The 2013 WHS had 4362 participants linked to the SAIL databank, and 7332 from the 2014 WHS. Of these, 95 % had either an exact match or a probabilistic match of 0.9 or above, with 6869 people (63 %) of the combined WHS dataset having linked GP data. Of those with GP data, 5997 (87%) have weights in the GP data at any date. But only 2429 (35%) have weights within 1 year before and 1 year after the questionnaire date. Of the 2429, 135 have no weight in the WHS data. Conclusions For those using WHS data, the data can be enhanced with a temporal dimension, while the GP data user can augment missing values from the WHS. Both the GP and WHS can gain confirmation from each other. This allows the non-randomness of missingness in the GP dataset to be assessed.

Explaining global variation in geographic and taxonomic diversity gradients represents a central focus of macroecology and macroevolution. Ultimately, these diversity gradients have been generated over deep timescales as a consequence of historical variation in rates of dispersal, diversification, and the capacity of different geographic areas to preserve taxa through time. Here, I assess the relationships among these processes, to elucidate the causes of geographic and taxonomic variation in species richness among the most speciose order of birds: the Passeriformes (c. 6,500 species). To achieve this, I comparatively analyze phylogenetic, distributional and eco-morphological trait data collated at broad taxonomic and spatial scales. The results of my analyses strongly support the prevalence of historical dispersal events across large geographic scales, in addition to spatiotemporal variation in diversification rates. These findings reflect that some lineages and some geographic regions (notably tropical mountain regions and island archipelagoes) generate and maintain a much larger amount of species diversity than others. In addition, the evolution of particular life-history and eco-morphological traits, specifically pair breeding systems, and higher wing aspect-ratios, increased rates of range expansion and diversification. In summary, geographic variation in historical diversification combined with differences in the capacity of lineages to colonize new areas, determines spatial and taxonomic differences in passerine species richness.

ABSTRACT Objective To examine the impact of mindfulness-based stress reduction (MBSR) for people with ankylosing spondylitis (AS). Methods 193 People with AS were invited to take part in an MBSR 8 week course. The data linkage component of this study examined number of visits to the general practitioner before and after the course in participants and non-participants of the course (500 people taking part in a cohort study but not invited to the course). Results Of 193 people invited, 43 (22%) consented and took part in the course, GP records were available for 41 (95%) of MBSR participants and 457 (91%) of the 500 comparison group. There was a mean of 7.6 (median 3) visits to the GP in the 12 month period before the course for those undertaking MBSR and 4.6 (median 0) visits in the 12 month period after the course. This compared with 5.5 (median 0) visits (12 months before a random date) and 4.1 (median 0) visits (12 months after a random date) in the comparison group. Using Wilcoxon rank-sum (Mann-Whitney) test showed a significant reduction in GP visits in the MBSR group after the course compared to the comparison group. Conclusions Those who chose to attend an MBSR course had a higher number of visits to the GP before attending the course, than the comparison group. However, after attending the stress reduction course the number of visits to the GP reduced to levels equivalent to the comparison group. This study suggests that mindfulness based stress reduction could be effective in reducing the number of visits to the GP for people with arthritis who regularly see their GP. The findings from this study suggest a full RCT and cost effectiveness analysis is warranted.

ABSTRACT Objectives To examine the characteristics of children who are prescribed antipsychotic medication. Approach A cohort study using routine data from general practitioner and hospital records linked with education records. All children in Wales between the years 1999 to 2014 were included in the analysis, demographic characteristics and outcomes of children were stratified by intellectual disability/autism (identified using education records and GP records) and antipsychotic use. All data were linked and held in the Secure Anonymised Information Linkage (SAIL) Databank in Wales Results Of children with intellectual disability 2.4 % (360/14428) have been prescribed an antipsychotic and 75 % of these have a diagnosis of autism. This compares with 0.19% (1126/602320) of children without intellectual disability who are prescribed an antipsychotic. Children, predominantly boys (78.1% (281/360) of those with intellectual disability prescribed an antipsychotic were boys compared to 67.12% (9442/14068) of those not prescribed antipsychotics), with aggression codes (17.5% of those on an antipsychotic had aggression codes compared to 1.36% of those without antipsychotic) were more likely to be prescribed antipsychotics. Those with intellectual disabilities were prescribed antipsychotics at a younger age (58 % of those with intellectual disability started the drug before the age of 14 compared to 29 % of those without intellectual disability) but were less likely to be from a deprived area compared to those prescribed antipsychotics but without intellectual disability/autism (22.5 % and 28.4 %, were in the lowest fifth of deprivation, intellectual disability and non- intellectual disability, respectively). Antipsychotic use was associated with more visits to the GP for epilepsy, diabetes and injury (post drug compared to prior to drug) and higher deaths in childhood (compared to those not give antipsychotics). Conclusions The linkage of the education records allowed intellectual disability to be used as an explanatory factor in analysis looking at drug prescriptions. The majority of children prescribed antipsychotics do not have psychotic or mental disorder diagnosis codes but have a diagnosis of behavioural problems, attend special schools and have intellectual difficulties. In the group with intellectual disability/autism there is evidence that the use of antipsychotics may be associated with more visits to the GP for epilepsy, diabetes, injury (post drug compared to prior to drug) and is associated with more deaths in childhood. These findings support concerns that antipsychotics may be over used for managing predominately behavioural problems.

Metabolomics and genomics are two complementary platforms for analyzing an organism as they provide information on the phenotype and genotype, respectively. These two techniques were applied in the dereplication and identification of bioactive compounds from a Streptomyces sp. (SM8) isolated from the sponge Haliclona simulans from Irish waters. Streptomyces strain SM8 extracts showed antibacterial and antifungal activity. NMR analysis of the active fractions proved that hydroxylated saturated fatty acids were the major components present in the antibacterial fractions. Antimycin compounds were initially putatively identified in the antifungal fractions using LC-Orbitrap. Their presence was later confirmed by comparison to a standard. Genomic analysis of Streptomyces sp. SM8 revealed the presence of multiple secondary metabolism gene clusters, including a gene cluster for the biosynthesis of the antifungal antimycin family of compounds. The antimycin gene cluster of Streptomyces sp. SM8 was inactivated by disruption of the antimycin biosynthesis gene antC. Extracts from this mutant strain showed loss of antimycin production and significantly less antifungal activity than the wild-type strain. Three butenolides, 4,10-dihydroxy-10-methyl-dodec-2-en-1,4-olide (1), 4,11-dihydroxy-10-methyl-dodec-2-en-1,4-olide (2), and 4-hydroxy-10-methyl-11-oxo-dodec-2-en-1,4-olide (3) that had previously been reported from marine Streptomyces species were also isolated from SM8. Comparison of the extracts of Streptomyces strain SM8 and its host sponge, H. simulans, using LC-Orbitrap revealed the presence of metabolites common to both extracts, providing direct evidence linking sponge metabolites to a specific microbial symbiont.

The marine sponge Haliclona simulans collected from the Irish Sea yielded two new steroids: 24-vinyl-cholest-9-ene-3β,24-diol and 20-methyl-pregn-6-en-3β-ol,5a,8a-epidioxy, along with the widely distributed 24-methylenecholesterol. One of the steroids possesses an unusually short hydrocarbon side chain. The structures were elucidated using nuclear magnetic resonance spectroscopy and confirmed using electron impact- and high resolution electrospray-mass spectrometry. All three steroids possess antitrypanosomal and anti-mycobacterial activity. All the steroids were found to possess low cytotoxicity against Hs27 which was above their detected antitrypanosomal potent concentrations.

OBJECTIVES:1) To use data-driven method to examine clinical codes (risk factors) of a medical condition in primary care electronic health records (EHRs) that can accurately predict a diagnosis of the condition in secondary care EHRs. 2) To develop and validate a disease phenotyping algorithm for rheumatoid arthritis using primary care EHRs. METHODS:This study linked routine primary and secondary care EHRs in Wales, UK. A machine learning based scheme was used to identify patients with rheumatoid arthritis from primary care EHRs via the following steps: i) selection of variables by comparing relative frequencies of Read codes in the primary care dataset associated with disease case compared to non-disease control (disease/non-disease based on the secondary care diagnosis); ii) reduction of predictors/associated variables using a Random Forest method, iii) induction of decision rules from decision tree model. The proposed method was then extensively validated on an independent dataset, and compared for performance with two existing deterministic algorithms for RA which had been developed using expert clinical knowledge. RESULTS:Primary care EHRs were available for 2,238,360 patients over the age of 16 and of these 20,667 were also linked in the secondary care rheumatology clinical system. In the linked dataset, 900 predictors (out of a total of 43,100 variables) in the primary care record were discovered more frequently in those with versus those without RA. These variables were reduced to 37 groups of related clinical codes, which were used to develop a decision tree model. The final algorithm identified 8 predictors related to diagnostic codes for RA, medication codes, such as those for disease modifying anti-rheumatic drugs, and absence of alternative diagnoses such as psoriatic arthritis. The proposed data-driven method performed as well as the expert clinical knowledge based methods. CONCLUSION:Data-driven scheme, such as ensemble machine learning methods, has the potential of identifying the most informative predictors in a cost-effective and rapid way to accurately and reliably classify rheumatoid arthritis or other complex medical conditions in primary care EHRs.

The marine environment is extremely diverse, with huge variations in pressure and temperature. Nevertheless, life, especially microbial life, thrives throughout the marine biosphere and microbes have adapted to all the divergent environments present. Large scale DNA sequence based approaches have recently been used to investigate the marine environment and these studies have revealed that the oceans harbor unprecedented microbial diversity. Novel gene families with representatives only within such metagenomic datasets represent a large proportion of the ocean metagenome. The presence of so many new gene families from these uncultured and highly diverse microbial populations represents a challenge for the understanding of and exploitation of the biology and biochemistry of the ocean environment. The application of new metagenomic and single cell genomics tools offers new ways to explore the complete metabolic diversity of the marine biome.

The genus Streptomyces produces secondary metabolic compounds that are rich in biological activity. Many of these compounds are genetically encoded by large secondary metabolism biosynthetic gene clusters (smBGCs) such as polyketide synthases (PKS) and non-ribosomal peptide synthetases (NRPS) which are modular and can be highly repetitive. Due to the repeats, these gene clusters can be difficult to resolve using short read next generation datasets and are often quite poorly predicted using standard approaches. We have sequenced the genomes of 13 Streptomyces spp. strains isolated from shallow water and deep-sea sponges that display antimicrobial activities against a number of clinically relevant bacterial and yeast species. Draft genomes have been assembled and smBGCs have been identified using the antiSMASH (antibiotics and Secondary Metabolite Analysis Shell) web platform. We have compared the smBGCs amongst strains in the search for novel sequences conferring the potential to produce novel bioactive secondary metabolites. The strains in this study recruit to four distinct clades within the genus Streptomyces. The marine strains host abundant smBGCs which encode polyketides, NRPS, siderophores, bacteriocins and lantipeptides. The deep-sea strains appear to be enriched with gene clusters encoding NRPS. Marine adaptations are evident in the sponge-derived strains which are enriched for genes involved in the biosynthesis and transport of compatible solutes and for heat-shock proteins. Streptomyces spp. from marine environments are a promising source of novel bioactive secondary metabolites as the abundance and diversity of smBGCs show high degrees of novelty. Sponge derived Streptomyces spp. isolates appear to display genomic adaptations to marine living when compared to terrestrial strains.

The microbiota of four individual deep water sponges, Lissodendoryx diversichela, Poecillastra compressa, Inflatella pellicula, and Stelletta normani, together with surrounding seawater were analysed by pyrosequencing of a region of the 16S rRNA gene common to Bacteria and Archaea. Due to sampling constraints at depths below 700 m duplicate samples were not collected. The microbial communities of L. diversichela, P. compressa and I. pellicula were typical of low microbial abundance (LMA) sponges while S. normani had a community more typical of high microbial abundance (HMA) sponges. Analysis of the deep sea sponge microbiota revealed that the three LMA-like sponges shared a set of abundant OTUs that were distinct from those associated with sponges from shallow waters. Comparison of the pyrosequencing data with that from shallow water sponges revealed that the microbial communities of all sponges analysed have similar archaeal populations but that the bacterial populations of the deep sea sponges were distinct. Further analysis of the common and abundant OTUs from the three LMA-like sponges placed them within the groups of ammonia oxidising Archaea (Thaumarchaeota) and sulphur oxidising γ-Proteobacteria (Chromatiales). Reads from these two groups made up over 70% of all 16S rRNA genes detected from the three LMA-like sponge samples, providing evidence of a putative common microbial assemblage associated with deep sea LMA sponges.

Microbes associated with marine sponges play significant roles in host physiology. Remarkable levels of microbial diversity have been observed in sponges worldwide through both culture-dependent and culture-independent studies. Most studies have focused on the structure of the bacterial communities in sponges and have involved sponges sampled from shallow waters. Here, we used pyrosequencing of 16S rRNA genes to compare the bacterial and archaeal communities associated with two individuals of the marine sponge Inflatella pellicula from the deep-sea, sampled from a depth of 2,900 m, a depth which far exceeds any previous sequence-based report of sponge-associated microbial communities. Sponge-microbial communities were also compared to the microbial community in the surrounding seawater. Sponge-associated microbial communities were dominated by archaeal sequencing reads with a single archaeal OTU, comprising ~60% and ~72% of sequences, being observed from Inflatella pellicula. Archaeal sequencing reads were less abundant in seawater (~11% of sequences). Sponge-associated microbial communities were less diverse and less even than any other sponge-microbial community investigated to date with just 210 and 273 OTUs (97% sequence identity) identified in sponges, with 4 and 6 dominant OTUs comprising ~88% and ~89% of sequences, respectively. Members of the candidate phyla, SAR406, NC10 and ZB3 are reported here from sponges for the first time, increasing the number of bacterial phyla or candidate divisions associated with sponges to 43. A minor cohort from both sponge samples (~0.2% and ~0.3% of sequences) were not classified to phylum level. A single OTU, common to both sponge individuals, dominates these unclassified reads and shares sequence homology with a sponge associated clone which itself has no known close relative and may represent a novel taxon.