Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

Public support for the implementation of personalised medicine policies (PMPs) within routine care is important owing to the high financial costs involved and the potential for redirection of resources from other services.

We aimed to determine the attributes of a PMP most likely to elicit public support for implementation. We also aimed to determine whether such support differed between a depression PMP and one for cystic fibrosis.

In a discrete-choice experiment, paired vignettes illustrating both the current model of care (CMoC) and a hypothetical PMP for either depression or cystic fibrosis were presented to a representative sample of the UK public (n = 2804). Each vignette integrated varying attributes, including anticipated therapeutic benefit over CMoC, and the annual cost to the taxpayer. Respondents were invited to express their preference for either the PMP or CMoC within each pair.

The financial cost was the most important attribute influencing public support for PMPs. Respondents favoured PMP implementation where it benefited a higher proportion of patients or was anticipated to be more effective than CMoC. A reduction in services for non-eligible patients reduced the likelihood of support for PMPs. Respondents were more willing to fund PMPs for cystic fibrosis than for depression.

Cost is a significant factor in the public's support for PMPs, but essential caveats, such as protection for services available to PMP-ineligible patients, may also apply. Further research should explore the factors contributing to condition-specific nuances in public support for PMPs.

Disaster impact databases are important resources for informing research, policy, and decision making. Therefore, understanding the underpinning methodology of data collection used by the databases, how they differ, and quality indicators of the data recorded is essential in ensuring that their use as reference points is valid.

The Australian Disaster Resilience Knowledge Hub (AIDRKH) is an open-source platform supported by government to inform disaster management practice. A comparative descriptive review of the Disaster Mapper (hosted at AIDRKH) and the international Emergency Events Database (EM-DAT) was undertaken to identify differences in how Australian disasters are captured and measured.

The results show substantial variation in identification and classification of disasters across hazard impacts and hazard types and a lack of data structure for the systematic reporting of contextual and impact variables.

These differences may have implications for reporting, academic analysis, and thus knowledge management informing disaster prevention and response policy or plans. Consistency in reporting methods based on international classification standards is recommended to improve the validity and usefulness of this Australian database.

A recent genome-wide association study (GWAS) identified 12 independent loci significantly associated with attention-deficit/hyperactivity disorder (ADHD). Polygenic risk scores (PRS), derived from the GWAS, can be used to assess genetic overlap between ADHD and other traits. Using ADHD samples from several international sites, we derived PRS for ADHD from the recent GWAS to test whether genetic variants that contribute to ADHD also influence two cognitive functions that show strong association with ADHD: attention regulation and response inhibition, captured by reaction time variability (RTV) and commission errors (CE).

The discovery GWAS included 19 099 ADHD cases and 34 194 control participants. The combined target sample included 845 people with ADHD (age: 8–40 years). RTV and CE were available from reaction time and response inhibition tasks. ADHD PRS were calculated from the GWAS using a leave-one-study-out approach. Regression analyses were run to investigate whether ADHD PRS were associated with CE and RTV. Results across sites were combined via random effect meta-analyses.

When combining the studies in meta-analyses, results were significant for RTV (R2 = 0.011, β = 0.088, p = 0.02) but not for CE (R2 = 0.011, β = 0.013, p = 0.732). No significant association was found between ADHD PRS and RTV or CE in any sample individually (p > 0.10).

We detected a significant association between PRS for ADHD and RTV (but not CE) in individuals with ADHD, suggesting that common genetic risk variants for ADHD influence attention regulation.

Implementation of genome-scale sequencing in clinical care has significant challenges: the technology is highly dimensional with many kinds of potential results, results interpretation and delivery require expertise and coordination across multiple medical specialties, clinical utility may be uncertain, and there may be broader familial or societal implications beyond the individual participant. Transdisciplinary consortia and collaborative team science are well poised to address these challenges. However, understanding the complex web of organizational, institutional, physical, environmental, technologic, and other political and societal factors that influence the effectiveness of consortia is understudied. We describe our experience working in the Clinical Sequencing Evidence-Generating Research (CSER) consortium, a multi-institutional translational genomics consortium.

A key aspect of the CSER consortium was the juxtaposition of site-specific measures with the need to identify consensus measures related to clinical utility and to create a core set of harmonized measures. During this harmonization process, we sought to minimize participant burden, accommodate project-specific choices, and use validated measures that allow data sharing.

Identifying platforms to ensure swift communication between teams and management of materials and data were essential to our harmonization efforts. Funding agencies can help consortia by clarifying key study design elements across projects during the proposal preparation phase and by providing a framework for data sharing data across participating projects.

In summary, time and resources must be devoted to developing and implementing collaborative practices as preparatory work at the beginning of project timelines to improve the effectiveness of research consortia.

To evaluate the health status and quality of life of young patients who had cone reconstruction for Ebstein anomaly.

We reviewed all patients who had cone reconstruction from 2007 to 2016 at our institution. Prospective surveys were mailed to all eligible patients. Quality of life was assessed using the PedsQL 4.0 Generic Core Scales, including four domains: physical, emotional, social, and school functioning.

Of 116 eligible patients, 72 (62%) responded. About 96% reported their health as excellent or good, and 52% were symptom-free. Only 37% of patients were taking any medications, the most common of which was aspirin (30%). Only 19% had been hospitalised for cardiac reasons following cone reconstruction. The average self-reported quality of life was 85.3/100, whereas the average parent proxy-reported quality of life was 81.8/100. There was no difference by self or parent proxy-report in quality of life between cone reconstruction patients and healthy children; however, quality of life was significantly better compared with children with other chronic health conditions. By self-report and parent proxy-report, 15.1 and 16.7% of patients were deemed “at risk” for reduced quality of life, respectively. Socially, 63/64 (98%) patients over 5 years old were either full-time students or working full-time.

Children with Ebstein anomaly following cone reconstruction have excellent quality of life comparable with healthy peers and significantly better than other children with chronic health conditions. Families of children with Ebstein anomaly can expect excellent quality of life, long-term health status, and social functioning following cone reconstruction.

This study profiles climate change as an emerging disaster risk in Oceania. The rationale for undertaking this study was to investigate climate change and disaster risk in Oceania. The role of this analysis is to examine what evidence exists to support decision-making and profile the nature, type, and potential human and economic impact of climate change and disaster risk in Oceania.

To evaluate perceptions of climate change and disaster risk in the Oceania region.

Thirty individual interviews with participants from 9 different countries were conducted. All of the participants were engaged in disaster management in the Oceania region as researchers, practitioners in emergency management, disaster health care and policy managers, or academics. Data collection was conducted between April and November 2017. Thematic analysis was conducted using narrative inquiry to gather first-hand insights on their perceptions of current and emerging threats and propose improvements in risk management practice to capture, monitor, and control disaster risk.

Interviewees who viewed climate change as a risk or hazard described a breadth of impacts. Hazards identified included climate variability and climate-related disasters, climate issues in island areas and loss of land mass, trans-nation migration, and increased transportation risk due to rising sea levels. These emerging risks are reflective of both the geographical location of countries in Oceania, where land mass due to rising oceans has been previously reported and climate change-driven migration of island populations.

Climate change was perceived as a significant contemporary and future risk, and as an influencing factor on other risks in the Oceania region.

The rationale for undertaking this study was to investigate how characteristics of population health relate to and impact disaster risk, resilience, vulnerability, impact, and recovery. The multi-disciplinary environment that contextualizes disaster practice can influence determinants of health. Robust health determinants, or lack thereof, may influence the outcomes of disaster events affecting an individual or a community.

To investigate how the social determinants of health inform community perceptions of disaster risk.

Community perception of disaster risk in reference to the social determinants of health was assessed in this study. Individual interviews with participants from a community were conducted, all of whom were permanent community residents. Thematic analysis was conducted using narrative inquiry to gather firsthand insights on their perceptions of how characteristics of population health relate to and impact an individual’s disaster risk.

Analysis demonstrated commonality between interviewees in perceptions of the influence of the social determinants of health on individual disaster risk by determinant type. Interviewees sensed a strong correlation between low community connection and disaster risk vulnerability. Specific populations thought to have low community connection were perceived to be socially isolated, resulting in low knowledge or awareness of the surrounding disaster risks, or how to prepare and respond to disasters. In addition, they had reduced access to communication and support in time of need.

The importance of a strong social community connection was a feature of this research. Further research on how health determinants can enable disaster risk awareness and disaster risk communication is warranted.