The microbiome stabilizes circadian rhythms in the gut.

The gut microbiome is well known to impact host physiology and health. Given widespread control of physiology by circadian clocks, we asked how the microbiome interacts with circadian rhythms in the Drosophila gut. The microbiome did not cycle in flies fed ad libitum, and timed feeding (TF) drove limited cycling only in clockless per01 flies. However, TF and loss of the microbiome influenced the composition of the gut cycling transcriptome, independently and together. Moreover, both interventions increased the amplitude of rhythmic gene expression, with effects of TF at least partly due to changes in histone acetylation. Contrary to expectations, timed feeding rendered animals more sensitive to stress. Analysis of microbiome function in circadian physiology revealed that germ-free flies reset more rapidly with shifts in the light:dark cycle. We propose that the microbiome stabilizes cycling in the host gut to prevent rapid fluctuations with changing environmental conditions.

PIP2 depletion and altered endocytosis caused by expression of Alzheimer's disease-protective variant PLCγ2 R522.

Variants identified in genome-wide association studies have implicated immune pathways in the development of Alzheimer's disease (AD). Here, we investigated the mechanistic basis for protection from AD associated with PLCγ2 R522, a rare coding variant of the PLCG2 gene. We studied the variant's role in macrophages and microglia of newly generated PLCG2-R522-expressing human induced pluripotent cell lines (hiPSC) and knockin mice, which exhibit normal endogenous PLCG2 expression. In all models, cells expressing the R522 mutation show a consistent non-redundant hyperfunctionality in the context of normal expression of other PLC isoforms. This manifests as enhanced release of cellular calcium ion stores in response to physiologically relevant stimuli like Fc-receptor ligation or exposure to Aß oligomers. Expression of the PLCγ2-R522 variant resulted in increased stimulus-dependent PIP2 depletion and reduced basal PIP2 levels in vivo. Furthermore, it was associated with impaired phagocytosis and enhanced endocytosis. PLCγ2 acts downstream of other AD-related factors, such as TREM2 and CSF1R, and alterations in its activity directly impact cell function. The inherent druggability of enzymes such as PLCγ2 raises the prospect of PLCγ2 manipulation as a future therapeutic approach in AD.

Unbiased kidney-centric molecular categorization of chronic kidney disease as a step towards precision medicine.

Current classification of chronic kidney disease (CKD) into stages using indirect systemic measures (estimated glomerular filtration rate (eGFR) and albuminuria) is agnostic to the heterogeneity of underlying molecular processes in the kidney thereby limiting precision medicine approaches. To generate a novel CKD categorization that directly reflects within kidney disease drivers we analyzed publicly available transcriptomic data from kidney biopsy tissue. A Self-Organizing Maps unsupervised artificial neural network machine-learning algorithm was used to stratify a total of 369 patients with CKD and 46 living kidney donors as healthy controls. Unbiased stratification of the discovery cohort resulted in identification of four novel molecular categories of disease termed CKD-Blue, CKD-Gold, CKD-Olive, CKD-Plum that were replicated in independent CKD and diabetic kidney disease datasets and can be further tested on any external data at kidneyclass.org. Each molecular category spanned across CKD stages and histopathological diagnoses and represented transcriptional activation of distinct biological pathways. Disease progression rates were highly significantly different between the molecular categories. CKD-Gold displayed rapid progression, with significant eGFR-adjusted Cox regression hazard ratio of 5.6 [1.01-31.3] for kidney failure and hazard ratio of 4.7 [1.3-16.5] for composite of kidney failure or a 40% or more eGFR decline. Urine proteomics revealed distinct patterns between the molecular categories, and a 25-protein signature was identified to distinguish CKD-Gold from other molecular categories. Thus, patient stratification based on kidney tissue omics offers a gateway to non-invasive biomarker-driven categorization and the potential for future clinical implementation, as a key step towards precision medicine in CKD.

Golgi apparatus, endoplasmic reticulum and mitochondrial function implicated in Alzheimer's disease through polygenic risk and RNA sequencing.

Polygenic risk scores (PRS) have been widely adopted as a tool for measuring common variant liability and they have been shown to predict lifetime risk of Alzheimer's disease (AD) development. However, the relationship between PRS and AD pathogenesis is largely unknown. To this end, we performed a differential gene-expression and associated disrupted biological pathway analyses of AD PRS vs. case/controls in human brain-derived cohort sample (cerebellum/temporal cortex; MayoRNAseq). The results highlighted already implicated mechanisms: immune and stress response, lipids, fatty acids and cholesterol metabolisms, endosome and cellular/neuronal death, being disrupted biological pathways in both case/controls and PRS, as well as previously less well characterised processes such as cellular structures, mitochondrial respiration and secretion. Despite heterogeneity in terms of differentially expressed genes in case/controls vs. PRS, there was a consensus of commonly disrupted biological mechanisms. Glia and microglia-related terms were also significantly disrupted, albeit not being the top disrupted Gene Ontology terms. GWAS implicated genes were significantly and in their majority, up-regulated in response to different PRS among the temporal cortex samples, suggesting potential common regulatory mechanisms. Tissue specificity in terms of disrupted biological pathways in temporal cortex vs. cerebellum was observed in relation to PRS, but limited tissue specificity when the datasets were analysed as case/controls. The largely common biological mechanisms between a case/control classification and in association with PRS suggests that PRS stratification can be used for studies where suitable case/control samples are not available or the selection of individuals with high and low PRS in clinical trials.

Plasma biomarkers and genetics in the diagnosis and prediction of Alzheimer's disease.

Plasma biomarkers for Alzheimer's disease-related pathologies have undergone rapid developments during the past few years, and there are now well-validated blood tests for amyloid and tau pathology, as well as neurodegeneration and astrocytic activation. To define Alzheimer's disease with biomarkers rather than clinical assessment, we assessed prediction of research-diagnosed disease status using these biomarkers and tested genetic variants associated with the biomarkers that may reflect more accurately the risk of biochemically defined Alzheimer's disease instead of the risk of dementia. In a cohort of Alzheimer's disease cases [n = 1439, mean age 68 years (standard deviation = 8.2)] and screened controls [n = 508, mean age 82 years (standard deviation = 6.8)], we measured plasma concentrations of the 40 and 42 amino acid-long amyloid-ß (Aß) fragments (Aß40 and Aß42, respectively), tau phosphorylated at amino acid 181 (P-tau181), neurofilament light (NfL) and glial fibrillary acidic protein (GFAP) using state-of-the-art Single molecule array (Simoa) technology. We tested the relationships between the biomarkers and Alzheimer's disease genetic risk, age at onset and disease duration. We also conducted a genome-wide association study for association of disease risk genes with these biomarkers. The prediction accuracy of Alzheimer's disease clinical diagnosis by the combination of all biomarkers, APOE and polygenic risk score reached area under receiver operating characteristic curve (AUC) = 0.81, with the most significant contributors being ε4, Aß40 or Aß42, GFAP and NfL. All biomarkers were significantly associated with age in cases and controls (P < 4.3 × 10-5). Concentrations of the Aß-related biomarkers in plasma were significantly lower in cases compared with controls, whereas other biomarker levels were significantly higher in cases. In the case-control genome-wide analyses, APOE-ε4 was associated with all biomarkers (P = 0.011-4.78 × 10-8), except NfL. No novel genome-wide significant single nucleotide polymorphisms were found in the case-control design; however, in a case-only analysis, we found two independent genome-wide significant associations between the Aß42/Aß40 ratio and WWOX and COPG2 genes. Disease prediction modelling by the combination of all biomarkers indicates that the variance attributed to P-tau181 is mostly captured by APOE-ε4, whereas Aß40, Aß42, GFAP and NfL biomarkers explain additional variation over and above APOE. We identified novel plausible genome wide-significant genes associated with Aß42/Aß40 ratio in a sample which is 50 times smaller than current genome-wide association studies in Alzheimer's disease.

Alzheimer's disease-associated P460L variant of EphA1 dysregulates receptor activity and blood-brain barrier function.

INTRODUCTION: Genome-wide association studies link susceptibility to late-onset Alzheimer's disease (LOAD) with EphA1. Sequencing identified a non-synonymous substitution P460L as a LOAD risk variant. Other Ephs regulate vascular permeability and immune cell recruitment. We hypothesized that P460L dysregulates EphA1 receptor activity and impacts neuroinflammation. METHODS: EphA1/P460L receptor activity was assayed in isogenic Human Embryonic Kidney (HEK) cells. Soluble EphA1/P460L (sEphA1/sP460L) reverse signaling in brain endothelial cells was assessed by T-cell recruitment and barrier function assays. RESULTS: EphA1 and P460L were expressed in HEK cells, but membrane and soluble P460L were significantly reduced. Ligand engagement induced Y781 phosphorylation of EphA1 but not P460L. sEphA1 primed brain endothelial cells for increased T-cell recruitment; however, sP460L was less effective. sEphA1 decreased the integrity of the brain endothelial barrier, while sP460L had no effect. DISCUSSION: These findings suggest that P460L alters EphA1-dependent forward and reverse signaling, which may impact blood-brain barrier function in LOAD. HIGHLIGHTS: EphA1-dependent reverse signaling controls recruitment of T cells by brain endothelial cells. EphA1-dependent reverse signaling remodels brain endothelial cell contacts. LOAD-associated P460L variant of EphA1 shows reduced membrane expression and reduced ligand responses. LOAD-associated P460L variant of EphA1 fails to reverse signal to brain endothelial cells.

Exploring the Use of Digital Interventions by People with Severe Mental Illness to Support Their Physical Health: A Mixed Methods Study.

People with severe mental illness (SMI) are more likely to experience physical health conditions than the general population. Little is known about the experience of people with SMI using digital health interventions (DHIs) to support their physical health. We explored how people with SMI use DHIs to support their physical health, the acceptability, factors affecting use, and impact on physical health. This was a three-stage mixed methods study (1) online survey of people with SMI; (2) interviews with a subsample of participants from Stage 1; (3) stakeholder workshops. Participants were generally satisfied with the DHIs they used. The most popular DHIs were targeted at diet, exercise, and weight management. Factors that encouraged use included simplicity and data-linkage. Concerns included costs, data security, and reliability of information. Positive impacts included accountability and tangible physical health benefits. Mental health impacted engagement with DHIs. DHIs were seen as a useful tool to monitor physical health but could not replace contact with clinical services. DHIs were considered useful and acceptable by people with SMI and may be used as an extension of clinical care. The specific needs and priorities of people with SMI should be considered both in developing and recommending interventions.

Alzheimer's disease-associated complement gene variants influence plasma complement protein levels.

BACKGROUND: Alzheimer's disease (AD) has been associated with immune dysregulation in biomarker and genome-wide association studies (GWAS). GWAS hits include the genes encoding complement regulators clusterin (CLU) and complement receptor 1 (CR1), recognised as key players in AD pathology, and complement proteins have been proposed as biomarkers. MAIN BODY: To address whether changes in plasma complement protein levels in AD relate to AD-associated complement gene variants we first measured relevant plasma complement proteins (clusterin, C1q, C1s, CR1, factor H) in a large cohort comprising early onset AD (EOAD; n = 912), late onset AD (LOAD; n = 492) and control (n = 504) donors. Clusterin and C1q were significantly increased (p < 0.001) and sCR1 and factor H reduced (p < 0.01) in AD plasma versus controls. ROC analyses were performed to assess utility of the measured complement biomarkers, alone or in combination with amyloid beta, in predicting AD. C1q was the most predictive single complement biomarker (AUC 0.655 LOAD, 0.601 EOAD); combining C1q with other complement or neurodegeneration makers through stepAIC-informed models improved predictive values slightly. Effects of GWS SNPs (rs6656401, rs6691117 in CR1; rs11136000, rs9331888 in CLU; rs3919533 in C1S) on protein concentrations were assessed by comparing protein levels in carriers of the minor vs major allele. To identify new associations between SNPs and changes in plasma protein levels, we performed a GWAS combining genotyping data in the cohort with complement protein levels as endophenotype. SNPs in CR1 (rs6656401), C1S (rs3919533) and CFH (rs6664877) reached significance and influenced plasma levels of the corresponding protein, whereas SNPs in CLU did not influence clusterin levels. CONCLUSION: Complement dysregulation is evident in AD and may contribute to pathology. AD-associated SNPs in CR1, C1S and CFH impact plasma levels of the encoded proteins, suggesting a mechanism for impact on disease risk.

Evaluating an under-mattress sleep monitor compared to a peripheral arterial tonometry home sleep apnea test device in the diagnosis of obstructive sleep apnea.

STUDY OBJECTIVES: To evaluate whether or not the apnea-hypopnea index (AHI) from a peripheral arterial tonometry (PAT) home sleep apnea test (HSAT) is equivalent to the AHI provided by the mean of one, three, or seven nights from the Withings Sleep Analyzer (WSA) under-mattress device. METHODS: We prospectively enrolled patients with suspected OSA in whom a PAT-HSAT was ordered. Eligible patients used the WSA for seven to nine nights. PAT data were scored using the device's intrinsic machine learning algorithms to arrive at the AHI using both 3% and 4% desaturation criteria for hypopnea estimations (PAT3%-AHI and PAT4%-AHI, respectively). These were then compared with the WSA-estimated AHI (WSA-AHI). RESULTS: Of 61 patients enrolled, 35 completed the study with valid PAT and WSA data. Of the 35 completers 16 (46%) had at least moderately severe OSA (PAT3%-AHI ≥ 15). The seven-night mean WSA-AHI was 2.13 (95%CI = - 0.88, 5.14) less than the PAT3%-AHI, but 5.64 (95%CI = 2.54, 8.73) greater than the PAT4%-AHI. The accuracy and area under the receiver operating curve (AUC) using the PAT3%-AHI ≥ 15 were 77% and 0.87 and for PAT4%-AHI ≥ 15 were 77% and 0.85, respectively. The one-, three-, or seven-night WSA-AHI were not equivalent to either the 3% or 4% PAT-AHI (equivalency threshold of ± 2.5 using the two one-sided t-test method). CONCLUSIONS: The WSA derives estimates of the AHI unobtrusively over many nights, which may prove to be a valuable clinical tool. However, the WSA-AHI over- or underestimates the PAT-AHI in clinical use, and the appropriate use of the WSA in clinical practice will require further evaluation. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04778748.

The Early-Onset Alzheimer's Disease Whole-Genome Sequencing Project: Study design and methodology.

INTRODUCTION: Sequencing efforts to identify genetic variants and pathways underlying Alzheimer's disease (AD) have largely focused on late-onset AD although early-onset AD (EOAD), accounting for ∼10% of cases, is largely unexplained by known mutations, resulting in a lack of understanding of its molecular etiology. METHODS: Whole-genome sequencing and harmonization of clinical, neuropathological, and biomarker data of over 5000 EOAD cases of diverse ancestries. RESULTS: A publicly available genomics resource for EOAD with extensive harmonized phenotypes. Primary analysis will (1) identify novel EOAD risk loci and druggable targets; (2) assess local-ancestry effects; (3) create EOAD prediction models; and (4) assess genetic overlap with cardiovascular and other traits. DISCUSSION: This novel resource complements over 50,000 control and late-onset AD samples generated through the Alzheimer's Disease Sequencing Project (ADSP). The harmonized EOAD/ADSP joint call will be available through upcoming ADSP data releases and will allow for additional analyses across the full onset range. HIGHLIGHTS: Sequencing efforts to identify genetic variants and pathways underlying Alzheimer's disease (AD) have largely focused on late-onset AD although early-onset AD (EOAD), accounting for ∼10% of cases, is largely unexplained by known mutations. This results in a significant lack of understanding of the molecular etiology of this devastating form of the disease. The Early-Onset Alzheimer's Disease Whole-genome Sequencing Project is a collaborative initiative to generate a large-scale genomics resource for early-onset Alzheimer's disease with extensive harmonized phenotype data. Primary analyses are designed to (1) identify novel EOAD risk and protective loci and druggable targets; (2) assess local-ancestry effects; (3) create EOAD prediction models; and (4) assess genetic overlap with cardiovascular and other traits. The harmonized genomic and phenotypic data from this initiative will be available through NIAGADS.

Genome-wide association identifies the first risk loci for psychosis in Alzheimer disease.

Psychotic symptoms, defined as the occurrence of delusions or hallucinations, are frequent in Alzheimer disease (AD with psychosis, AD + P). AD + P affects ~50% of individuals with AD, identifies a subgroup with poor outcomes, and is associated with a greater degree of cognitive impairment and depressive symptoms, compared to subjects without psychosis (AD - P). Although the estimated heritability of AD + P is 61%, genetic sources of risk are unknown. We report a genome-wide meta-analysis of 12,317 AD subjects, 5445 AD + P. Results showed common genetic variation accounted for a significant portion of heritability. Two loci, one in ENPP6 (rs9994623, O.R. (95%CI) 1.16 (1.10, 1.22), p = 1.26 × 10-8) and one spanning the 3'-UTR of an alternatively spliced transcript of SUMF1 (rs201109606, O.R. 0.65 (0.56-0.76), p = 3.24 × 10-8), had genome-wide significant associations with AD + P. Gene-based analysis identified a significant association with APOE, due to the APOE risk haplotype ε4. AD + P demonstrated negative genetic correlations with cognitive and educational attainment and positive genetic correlation with depressive symptoms. We previously observed a negative genetic correlation with schizophrenia; instead, we now found a stronger negative correlation with the related phenotype of bipolar disorder. Analysis of polygenic risk scores supported this genetic correlation and documented a positive genetic correlation with risk variation for AD, beyond the effect of ε4. We also document a small set of SNPs likely to affect risk for AD + P and AD or schizophrenia. These findings provide the first unbiased identification of the association of psychosis in AD with common genetic variation and provide insights into its genetic architecture.

Targeting inflammation for the treatment of Diabetic Kidney Disease: a five-compartment mechanistic model.

Diabetic kidney disease (DKD) is the leading cause of kidney failure worldwide. Mortality and morbidity associated with DKD are increasing with the global prevalence of type 2 diabetes. Chronic, sub-clinical, non-resolving inflammation contributes to the pathophysiology of renal and cardiovascular disease associated with diabetes. Inflammatory biomarkers correlate with poor renal outcomes and mortality in patients with DKD. Targeting chronic inflammation may therefore offer a route to novel therapeutics for DKD. However, the DKD patient population is highly heterogeneous, with varying etiology, presentation and disease progression. This heterogeneity is a challenge for clinical trials of novel anti-inflammatory therapies. Here, we present a conceptual model of how chronic inflammation affects kidney function in five compartments: immune cell recruitment and activation; filtration; resorption and secretion; extracellular matrix regulation; and perfusion. We believe that the rigorous alignment of pathophysiological insights, appropriate animal models and pathology-specific biomarkers may facilitate a mechanism-based shift from recruiting 'all comers' with DKD to stratification of patients based on the principal compartments of inflammatory disease activity.

An implementation framework and a feasibility evaluation of a clinical decision support system for diabetes management in secondary mental healthcare using CogStack.

BACKGROUND: Improvements to the primary prevention of physical health illnesses like diabetes in the general population have not been mirrored to the same extent in people with serious mental illness (SMI). This work evaluates the technical feasibility of implementing an electronic clinical decision support system (eCDSS) for supporting the management of dysglycaemia and diabetes in patients with serious mental illness in a secondary mental healthcare setting. METHODS: A stepwise approach was taken as an overarching and guiding framework for this work. Participatory methods were employed to design and deploy a monitoring and alerting eCDSS. The eCDSS was evaluated for its technical feasibility. The initial part of the feasibility evaluation was conducted in an outpatient community mental health team. Thereafter, the evaluation of the eCDSS progressed to a more in-depth in silico validation. RESULTS: A digital health intervention that enables monitoring and alerting of at-risk patients based on an approved diabetes management guideline was developed. The eCDSS generated alerts according to expected standards and in line with clinical guideline recommendations. CONCLUSIONS: It is feasible to design and deploy a functional monitoring and alerting eCDSS in secondary mental healthcare. Further work is required in order to fully evaluate the integration of the eCDSS into routine clinical workflows. By describing and sharing the steps that were and will be taken from concept to clinical testing, useful insights could be provided to teams that are interested in building similar digital health interventions.

Implementation of Telemental Health Services Before COVID-19: Rapid Umbrella Review of Systematic Reviews.

BACKGROUND: Telemental health care has been rapidly adopted for maintaining services during the COVID-19 pandemic, and a substantial interest is now being devoted in its future role. Service planning and policy making for recovery from the pandemic and beyond should draw on both COVID-19 experiences and the substantial research evidence accumulated before this pandemic. OBJECTIVE: We aim to conduct an umbrella review of systematic reviews available on the literature and evidence-based guidance on telemental health, including both qualitative and quantitative literature. METHODS: Three databases were searched between January 2010 and August 2020 for systematic reviews meeting the predefined criteria. The retrieved reviews were independently screened, and those meeting the inclusion criteria were synthesized and assessed for risk of bias. Narrative synthesis was used to report these findings. RESULTS: In total, 19 systematic reviews met the inclusion criteria. A total of 15 reviews examined clinical effectiveness, 8 reported on the aspects of telemental health implementation, 10 reported on acceptability to service users and clinicians, 2 reported on cost-effectiveness, and 1 reported on guidance. Most reviews were assessed to be of low quality. The findings suggested that video-based communication could be as effective and acceptable as face-to-face formats, at least in the short term. Evidence on the extent of digital exclusion and how it can be overcome and that on some significant contexts, such as children and young people's services and inpatient settings, was found to be lacking. CONCLUSIONS: This umbrella review suggests that telemental health has the potential to be an effective and acceptable form of service delivery. However, we found limited evidence on the impact of its large-scale implementation across catchment areas. Combining previous evidence and COVID-19 experiences may allow realistic planning for the future implementation of telemental health.

Implementation, Adoption, and Perceptions of Telemental Health During the COVID-19 Pandemic: Systematic Review.

BACKGROUND: Early in 2020, mental health services had to rapidly shift from face-to-face models of care to delivering the majority of treatments remotely (by video or phone call or occasionally messaging) due to the COVID-19 pandemic. This resulted in several challenges for staff and patients, but also in benefits such as convenience or increased access for people with impaired mobility or in rural areas. There is a need to understand the extent and impacts of telemental health implementation, and barriers and facilitators to its effective and acceptable use. This is relevant both to future emergency adoption of telemental health and to debates on its future use in routine mental health care. OBJECTIVE: To investigate the adoption and impacts of telemental health approaches during the COVID-19 pandemic, and facilitators and barriers to optimal implementation. METHODS: Four databases (PubMed, PsycINFO, CINAHL, and Web of Science) were searched for primary research relating to remote working, mental health care, and the COVID-19 pandemic. Preprint servers were also searched. Results of studies were synthesized using framework synthesis. RESULTS: A total of 77 papers met our inclusion criteria. In most studies, the majority of contacts could be transferred to a remote form during the pandemic, and good acceptability to service users and clinicians tended to be reported, at least where the alternative to remote contacts was interrupting care. However, a range of impediments to dealing optimal care by this means were also identified. CONCLUSIONS: Implementation of telemental health allowed some continuing support to the majority of service users during the COVID-19 pandemic and has value in an emergency situation. However, not all service users can be reached by this means, and better evidence is now needed on long-term impacts on therapeutic relationships and quality of care, and on impacts on groups at risk of digital exclusion and how to mitigate these. TRIAL REGISTRATION: PROSPERO International prospective register of systematic reviews CRD42021211025; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021211025.

Socio-demographic, behavioural and health-related characteristics associated with active commuting in a regional Australian state: Evidence from the 2016 Tasmanian Population Health Survey.

ISSUE ADDRESSED: Physical activity is lower and rates of preventable common diseases are higher in regional/rural than urban Australia. Active commuting (walking/bicycling to get from one place to another) may benefit health through increased physical activity, but most evidence of its correlates come from urban studies. This study aimed to investigate associations between active commuting, socio-demographic characteristics, behaviours, total physical activity and health in a regional/rural Australian state. METHODS: This study used data from the 2016 Tasmanian Population Health Survey, a representative cross-sectional self-report survey of 6,300 adults in Tasmania, Australia. Logistic regression modelling investigated associations between socio-demographic, behavioural and health characteristics and past week active commuting frequency. RESULTS: In multivariable models, being younger, having tertiary qualifications, living in a socio-economically advantaged area, being physically active, having a healthy body mass index and good/excellent self-rated health were associated with engaging in more active commuting. Inner regional dwellers were no more likely than outer regional dwellers to actively commute after covariate adjustment. CONCLUSION: Strategies to promote active commuting in regional/rural areas might consider targeting older adults, those less educated, those living in socio-economically disadvantaged areas, those less physically active, those with poorer health and those with higher body mass index. Research could further investigate why these groups appear to be less active for commuting purposes. SO WHAT?: Increasing physical activity and active commuting may help to reduce rates of preventable common diseases in regional/remote areas.

Genetic risk for alzheimer disease is distinct from genetic risk for amyloid deposition.

OBJECTIVE: Alzheimer disease (AD) is the most common form of dementia and is responsible for a huge and growing health care burden in the developed and developing world. The polygenic risk score (PRS) approach has shown 75 to 84% prediction accuracy of identifying individuals with AD risk. METHODS: In this study, we tested the prediction accuracy of AD, mild cognitive impairment (MCI), and amyloid deposition risks with PRS, including and excluding APOE genotypes in a large publicly available dataset with extensive phenotypic data, the Alzheimer's Disease Neuroimaging Initiative cohort. Among MCI individuals with amyloid-positive status, we examined PRS prediction accuracy in those who converted to AD. In addition, we divided polygenic risk score by biological pathways and tested them independently for distinguishing between AD, MCI, and amyloid deposition. RESULTS: We found that AD and MCI are predicted by both APOE genotype and PRS (area under the curve [AUC] = 0.82% and 68%, respectively). Amyloid deposition is predicted by APOE only (AUC = 79%). Further progression to AD of individuals with MCI and amyloid-positive status is predicted by PRS over and above APOE (AUC = 67%). In pathway-specific PRS analyses, the protein-lipid complex has the strongest association with AD and amyloid deposition even when genes in the APOE region were removed (p = 0.0055 and p = 0.0079, respectively). INTERPRETATION: The results showed different pattern of APOE contribution in PRS risk predictions of AD/MCI and amyloid deposition. Our study suggests that APOE mostly contributes to amyloid accumulation and the PRS affects risk of further conversion to AD. ANN NEUROL 2019;86:427-435.

Barriers and facilitators of clinician and researcher collaborations: a qualitative study.

BACKGROUND: The poor translation of research findings into routine clinical practice is common in all areas of healthcare. Having a better understanding of how researchers and clinicians experience engagement in and with research, their working relationships and expectations of each other, may be one way to help to facilitate collaborative partnerships and therefore increase successful translation of research into clinical practice. AIMS: To explore the views of clinical and research staff about their experiences of working together during research projects and identify the facilitators and barriers. METHODS: We conducted four focus groups with 18 participants - clinicians, researchers and those with a dual clinical-research role, recruited from one mental health Trust and one university. Data was analysed using thematic analysis. RESULTS: Eight themes were identified under the headings of two research questions 1) Barriers and facilitators of either engaging in or with research from the perspective of clinical staff, with themes of understanding the benefits of the research; perceived knowledge and personal qualities of researchers; lack of time and organisational support to be involved in and implement research; and lack of feedback about progress and outcome of research. 2) Barriers and facilitators for engaging with clinicians when conducting research, from the perspective of researchers, with themes of understanding what clinicians need to know and how they need to feel to engage with research; demonstrating an understanding of the clinician's world; navigating through the clinical world; and demands of the researcher role. CONCLUSION: There was agreement between clinicians and researchers about the barriers and facilitators for engaging clinicians in research. Both groups identified that it was the researcher's responsibility to form and maintain good working relationships. Better support for researchers in their role calls for training in communication skills and bespoke training to understand the local context in which research is taking place.

The changing role of Australian primary schools in providing breakfast to students: A qualitative study.

ISSUE ADDRESSED: In recent years, state governments throughout Australia have provided significant funding to support the expansion of school breakfast programs (SBPs), in response to concerns about children arriving at school hungry. This study investigated how schools have responded to the growing expectation that they provide breakfast for students. METHODS: This qualitative study draws on case studies of five Australian primary schools that operate SBPs. Interviews or focus groups were conducted with 78 children, parents, staff, volunteers and funders and data underwent thematic analysis. RESULTS: Three key themes were identified: Adjusting to the changing role of schools, SBPs reflecting the school's culture, Schools as an alternative or additional site for breakfast. Some staff and parents expressed unease about SBPs shifting responsibility for breakfast provision from parents to schools but were committed to supporting vulnerable students as part of the broader school culture. SBPs were found to provide an alternative or additional site for breakfast consumption for many children not experiencing food insecurity. CONCLUSION: The expectation that schools provide breakfast has created some challenges and tensions that have not been fully resolved. The adoption of an inclusive approach, undertaken to ensure students were not stigmatised for attendance, had resulted in concerns about the resources used by the programs as well as over-consumption of breakfast by some students. SO WHAT?: Increasingly, Australian schools are providing breakfast for students. Concerns about shifting responsibility and over-consumption could be addressed if schools were given more advice on program management by government and non-government funding bodies.

POLARIS: Polygenic LD-adjusted risk score approach for set-based analysis of GWAS data.

Polygenic risk scores (PRSs) are a method to summarize the additive trait variance captured by a set of SNPs, and can increase the power of set-based analyses by leveraging public genome-wide association study (GWAS) datasets. PRS aims to assess the genetic liability to some phenotype on the basis of polygenic risk for the same or different phenotype estimated from independent data. We propose the application of PRSs as a set-based method with an additional component of adjustment for linkage disequilibrium (LD), with potential extension of the PRS approach to analyze biologically meaningful SNP sets. We call this method POLARIS: POlygenic Ld-Adjusted RIsk Score. POLARIS identifies the LD structure of SNPs using spectral decomposition of the SNP correlation matrix and replaces the individuals' SNP allele counts with LD-adjusted dosages. Using a raw genotype dataset together with SNP effect sizes from a second independent dataset, POLARIS can be used for set-based analysis. MAGMA is an alternative set-based approach employing principal component analysis to account for LD between markers in a raw genotype dataset. We used simulations, both with simple constructed and real LD-structure, to compare the power of these methods. POLARIS shows more power than MAGMA applied to the raw genotype dataset only, but less or comparable power to combined analysis of both datasets. POLARIS has the advantages that it produces a risk score per person per set using all available SNPs, and aims to increase power by leveraging the effect sizes from the discovery set in a self-contained test of association in the test dataset.