GA4GH: International policies and standards for data sharing across genomic research and healthcare.

The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits

The handbook for standardized field and laboratory measurements in terrestrial climate change experiments and observational studies (ClimEx)

1. Climate change is a world‐wide threat to biodiversity and ecosystem structure, functioning and services. To understand the underlying drivers and mechanisms, and to predict the consequences for nature and people, we urgently need better understanding of the direction and magnitude of climate change impacts across the soil–plant–atmosphere continuum. An increasing number of climate change studies are creating new opportunities for meaningful and high‐quality generalizations and improved process understanding. However, significant challenges exist related to data availability and/or compatibility across studies, compromising opportunities for data re‐use, synthesis and upscaling. Many of these challenges relate to a lack of an established ‘best practice’ for measuring key impacts and responses. This restrains our current understanding of complex processes and mechanisms in terrestrial ecosystems related to climate change. 2. To overcome these challenges, we collected best‐practice methods emerging from major ecological research networks and experiments, as synthesized by 115 experts from across a wide range of scientific disciplines. Our handbook contains guidance on the selection of response variables for different purposes, protocols for standardized measurements of 66 such response variables and advice on data management. Specifically, we recommend a minimum subset of variables that should be collected in all climate change studies to allow data re‐use and synthesis, and give guidance on additional variables critical for different types of synthesis and upscaling. The goal of this community effort is to facilitate awareness of the importance and broader application of standardized methods to promote data re‐use, availability, compatibility and transparency. We envision improved research practices that will increase returns on investments in individual research projects, facilitate second‐order research outputs and create opportunities for collaboration across scientific communities. Ultimately, this should significantly improve the quality and impact of the science, which is required to fulfil society's needs in a changing world

Stress, Health Behaviors, and Health Outcomes in Caregivers of Children with Autism Spectrum Disorder

Autism spectrum disorder (ASD) is a developmental disorder marked by communication limitations and behavioral features that vary broadly across individuals. The identification of ASD has increased by approximately 30% since 2008. As the identification of ASD continues to increase, similarly so does the number of caregivers of children with ASD, making this an important, and growing population. Since children with ASD may have a unique phenotypic profile of behaviors caregivers of children with ASD often face increased levels of stress, and experience higher levels of stress compared to other populations, including caregivers of children of other developmental disabilities. Chronic stress is a known risk factor for a wide range of chronic diseases, including cardiometabolic and mental health outcomes. Chronic stress may also influence health behaviors such as smoking, alcohol use and physical activity through coping mechanisms. The occurrence of chronic diseases and their risk factors in caregivers of children with ASD has not been well studied. There is a need to further investigate specific child behaviors as correlates of caregiver health and health behaviors. This project included two studies. The first study examined stress in caregivers of children with ASD and focused on specific child behaviors, within a locally-recruited sample of N=116 caregivers of children with ASD aged 3-17 years. Caregivers completed the Autism Behavior Inventory-Short as a measure of child behaviors, and the Parent Stress Scale as a measure of total parenting stress. We used linear regression to determine the association between specific child behaviors and caregiver stress. We hypothesized that caregivers of children with higher levels of behavioral difficulties (social-communication, mental health, repetitive behaviors) will report higher levels of self-reported stress, compared to caregivers of children with fewer behavioral difficulties. More behavioral difficulties in each domain was associated with higher levels of parental stress. For the second study, data on health behaviors and health outcomes from the National Health Interview Survey 2016-2017 cycles were used to compare caregivers of children with ASD to caregivers of typically developing children and children with other disabilities (N=10,162). For the child, information on child’s diagnosis was reported by the parent. For the parent, health risk behaviors and health outcomes were self-reported. We used logistic regression to determine effects and hypothesized that caregivers of children with ASD will report more adverse health behaviors (i.e., smoking, alcohol use, less physical activity) compared to caregivers of typically developing children and caregivers of children with other disabilities. We also hypothesized that caregivers of children with ASD will have more cardiometabolic outcomes (i.e., type 2 diabetes, obesity, hypertension, high cholesterol) and more mental health symptoms compared to caregivers of typically developing children and caregivers of children with other disabilities. Compared to typically developing caregivers, caregivers of children with ASD had higher odds of physical inactivity, smoking and tobacco use, and heavy drinking, though these relationships varied when compared to other disability groups. The effect estimates for these relationships also were of low magnitude and were relativity imprecise. Similar patterns of association were shown for health outcomes compared to caregivers of children with other disabilities. Overall, our findings suggest that it is the culmination of the child’s phenotype that results in increased caregiver stress, rather than individual, unique behaviors. This may support the idea that is the total experience of all behaviors that is important, including those not required for an ASD diagnosis, but that are commonly shared with other developmental disorders. Furthermore, caregivers of children with ASD had more adverse health behaviors and outcomes compared to caregivers of typically developing children, but not when compared to other disability groups, though these estimates had low magnitude and were relatively imprecise. Caregiver stress should be considered for potential interventions to improve their health. Future studies should seek to better understand why child behaviors influence caregiver stress and how caregiver stress may influence health risk behaviors and health outcomes

Latent Class Analysis of Barriers to Care Among Emergency Department Patients

Introduction: Emergency department (ED) patients experience a variety of barriers to care that can lead to unnecessary or repeated visits. By identifying the patterns of barriers experienced by subsets of the ED patient population, future researchers might effectively design interventions to circumvent these barriers and improve care. This study sought to identify classes of individuals with regard to perceived barriers to care. Methods: Over a 10-week period, two medical students distributed surveys to eligible patients ≥18 years who presented to the ED. After consent, patients provided demographics data and rated their perceived access to care on nine specific items (scored 1-5). We used latent class analysis (LCA), a parametric clustering method, to determine patient groups. Demographic characteristics were then compared across classes.Results: We enrolled a total of 637 patients. Results of the LCA indicated that a six-class solution fit best: 1) low barriers (60%); 2) “work responsibility” barriers (13%); 3) economic-related barriers (10%); 4) “appointment difficulty” barriers (8%); 5) “illness and care responsibilities” barriers (6%); and 6) diverse barriers (2%). Patients in the low-barriers class were the oldest across classes (p<.001). Individuals in the low-barriers class were also more likely to be White (p=.015) and have private insurance (p<.001) than those in the “appointment difficulty,” “illness and care responsibilities,” and diverse barriers classes. Conclusion: LCA suggests there are six distinct classes of patients with regard to perceived access to care. These classes may be used as a potential starting point in designing targeted interventions for ED patients to improve continuity of care

Latent Class Analysis of Barriers to Care Among Emergency Department Patients

Introduction: Emergency department (ED) patients experience a variety of barriers to care that can lead to unnecessary or repeated visits. By identifying the patterns of barriers experienced by subsets of the ED patient population, future researchers might effectively design interventions to circumvent these barriers and improve care. This study sought to identify classes of individuals with regard to perceived barriers to care. Methods: Over a 10-week period, two medical students distributed surveys to eligible patients ≥18 years who presented to the ED. After consent, patients provided demographics data and rated their perceived access to care on nine specific items (scored 1–5). We used latent class analysis (LCA), a parametric clustering method, to determine patient groups. Demographic characteristics were then compared across classes. Results: We enrolled a total of 637 patients. Results of the LCA indicated that a six-class solution fit best: 1) low barriers (60%); 2) “work responsibility” barriers (13%); 3) economic-related barriers (10%); 4) “appointment difficulty” barriers (8%); 5) “illness and care responsibilities” barriers (6%); and 6) diverse barriers (2%). Patients in the low-barriers class were the oldest across classes (p<.001). Individuals in the low-barriers class were also more likely to be White (p=.015) and have private insurance (p<.001) than those in the “appointment difficulty,” “illness and care responsibilities,” and diverse barriers classes. Conclusion: LCA suggests there are six distinct classes of patients with regard to perceived access to care. These classes may be used as a potential starting point in designing targeted interventions for ED patients to improve continuity of care

Effects of aspirin in combination with EPA and DHA on HDL-C cholesterol and ApoA1 exchange in individuals with type 2 diabetes mellitus

Background/synopsisLow-dose aspirin is an effective drug for the prevention of cardiovascular disease (CVD) events but individuals with diabetes mellitus can be subject to 'aspirin resistance'. Thus, aspirin's effect in these individuals is controversial. Higher blood levels of seafood-derived omega-3 polyunsaturated fatty acids (ω3) eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) also have beneficial effects in reducing risk of CVD events but few studies have examined the interaction of plasma EPA and DHA with aspirin ingestion.Objective/purposeOur study examined the combinatory effects of EPA, DHA, and aspirin ingestion on HDL-cholesterol (HDL-C) and apoA-I exchange (shown to be associated with CVD event risk).Methods30 adults with Type 2 diabetes mellitus ingested aspirin (81mg/day) for 7 consecutive days, EPA+DHA (2.6g/day) for 28 days, then both for 7 days. Plasma was collected at baseline and at 5 subsequent visits including 4h after each aspirin ingestion. Mixed model methods were used to determine HDL-C-concentrations and apoA-I exchange compared to the baseline visit values. LOWESS curves were used for non-linear analyses of outcomes to help discern change patterns, which was followed by piecewise linear functions for formal testing of curvilinear relationships.ResultsSignificant changes (p &lt; 0.05) compared to baseline in both HDL-C-concentrations and apoA-I exchange were present at different times. After 7 days of aspirin-only ingestion, apoA-I exchange was significantly modified by increasing levels of DHA concentration, with increased apoA-I exchange observed up until log(DHA) of 4.6 and decreased exchange thereafter (p = 0.03). These LOWESS curve effects were not observed for EPA or HDL-C (p &gt; 0.05). Aspirin's effects on apoA-I exchange were the greatest when EPA or DHA concentrations were moderate compared to high or low. Comparison of EPA, DHA, and EPA+DHA LOWESS curves, demonstrated that the majority of the effect is due to DHA.ConclusionOur results strongly suggest that plasma concentrations of EPA and DHA influence aspirin effects on lipid mediators of CVD event risk where their concentrations are most beneficial when moderate, not high or low. These effects on HDL-C cholesterol and apoA-I exchange are novel. Personalized dosing of DHA in those who take aspirin may be a beneficial option for patients with type 2 diabetes mellitus