Measuring quality of life of people with predementia and dementia and their caregivers: a systematic review protocol

Introduction Dementia is the fastest growing major cause of disability globally and may have a profound impact on the health-related quality of life (HRQoL) of both the patient with dementia and those who care for them. This review aims to systematically identify and synthesise the measurements of HRQoL for people with, and their caregivers across the full spectrum of, dementia from its preceding stage of predementia to end of life. Methods and analysis A systematic literature review was conducted in Medical Literature Analysis and Retrieval System Online , ExcerptaMedicadataBASE, Cochrane Database of Systematic Reviews , Cochrane Central Register of Controlled Trials, Database of Abstracts of Reviews of Effect, National Health Service Economic Evaluation Database and PsycINFO between January 1990 and the end of April 2017. Two reviewers will independently assess each study for inclusion and disagreements will be resolved by a third reviewer. Data will be extracted using a predefined data extraction form following best practice. Study quality will be assessed with the Effective Public Health Practice Project quality assessment tool. HRQoL measurements will be presented separately for people with dementia and caregivers by instrument used and, when possible, HRQoL will be reported by disease type and stage of the disease. Descriptive statistics of the results will be provided. A narrative synthesis of studies will also be provided discussing differences in HRQoL measurements by instrument used to estimate it, type of dementia and disease severity. Ethics and dissemination This systematic literature review is exempt from ethics approval because the work is carried out on published documents. The findings of the review will be disseminated in a related peer-reviewed journal and presented at conferences. They will also contribute to the work developed in the Real World Outcomes across the Alzheimer’s disease spectrum for better care: multimodal data access platform (ROADMAP)

Working with bacteria and putting bacteria to work: The biopolitics of synthetic biology for energy in the United Kingdom

The UK government has made significant investment into so called ‘fourth-generation’ biofuel technologies. These biofuels are based on engineering the metabolic pathways of bacteria in order to create products compatible with existing infrastructure. Bacteria play an important role in what is promoted as a potentially new biological industrial revolution, which could address some of the negative environmental legacies of the last. This article presents results from ethnographic research with synthetic biologists who are challenged with balancing the curiosity-driven and intrinsically fulfilling scientific task of working with bacteria, alongside the policy-driven task of putting bacteria to work for extrinsic economic gains. In addition, the scientists also have to balance these demands with a new research governance framework, Responsible Research and Innovation, which envisions technoscientific innovation will be responsive to societal concerns and work in collaboration with stakeholders and members of the public. Major themes emerging from the ethnographic research revolve around stewardship, care, responsibility and agency. An overall conflict surfaces between individual agents assuming responsibility for ‘stewarding’ bacteria, against funding systems and structures imposing responsibility for economic growth. We discuss these findings against the theoretical backdrop of a new concept of ‘energopolitics’ and an anthropology of ethics and responsibility

Promoter-anchored chromatin interactions predicted from genetic analysis of epigenomic data

Promoter-anchored chromatin interactions (PAIs) play a pivotal role in transcriptional regulation. Current high-throughput technologies for detecting PAIs, such as promoter capture Hi-C, are not scalable to large cohorts. Here, we present an analytical approach that uses summary-level data from cohort-based DNA methylation (DNAm) quantitative trait locus (mQTL) studies to predict PAIs. Using mQTL data from human peripheral blood ([Formula: see text]), we predict 34,797 PAIs which show strong overlap with the chromatin contacts identified by previous experimental assays. The promoter-interacting DNAm sites are enriched in enhancers or near expression QTLs. Genes whose promoters are involved in PAIs are more actively expressed, and gene pairs with promoter-promoter interactions are enriched for co-expression. Integration of the predicted PAIs with GWAS data highlight interactions among 601 DNAm sites associated with 15 complex traits. This study demonstrates the use of mQTL data to predict PAIs and provides insights into the role of PAIs in complex trait variation

Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits

The identification of genes and regulatory elements underlying the associations discovered by GWAS is essential to understanding the aetiology of complex traits (including diseases). Here, we demonstrate an analytical paradigm of prioritizing genes and regulatory elements at GWAS loci for follow-up functional studies. We perform an integrative analysis that uses summary-level SNP data from multi-omics studies to detect DNA methylation (DNAm) sites associated with gene expression and phenotype through shared genetic effects (i.e., pleiotropy). We identify pleiotropic associations between 7858 DNAm sites and 2733 genes. These DNAm sites are enriched in enhancers and promoters, and >40% of them are mapped to distal genes. Further pleiotropic association analyses, which link both the methylome and transcriptome to 12 complex traits, identify 149 DNAm sites and 66 genes, indicating a plausible mechanism whereby the effect of a genetic variant on phenotype is mediated by genetic regulation of transcription through DNAm

Systematic literature review of methodologies and data sources of existing economic models across the full spectrum of Alzheimer’s disease and dementia from apparently healthy through disease progression to end of life care: a systematic review protocol

Introduction Dementia is one of the greatest health challenges the world will face in the coming decades, as it is one of the principal causes of disability and dependency among older people. Economic modelling is used widely across many health conditions to inform decisions on health and social care policy and practice. The aim of this literature review is to systematically identify, review and critically evaluate existing health economics models in dementia. We included the full spectrum of dementia, including Alzheimer’s disease (AD), from preclinical stages through to severe dementia and end of life. This review forms part of the Real world Outcomes across the Alzheimer’s Disease spectrum for better care: multimodal data Access Platform (ROADMAP) project. Methods and analysis Electronic searches were conducted in Medical Literature Analysis and Retrieval System Online, Excerpta Medica dataBASE, Economic Literature Database, NHS Economic Evaluation Database, Cochrane Central Register of Controlled Trials, Cost-Effectiveness Analysis Registry, Research Papers in Economics, Database of Abstracts of Reviews of Effectiveness, Science Citation Index, Turning Research Into Practice and Open Grey for studies published between January 2000 and the end of June 2017. Two reviewers will independently assess each study against predefined eligibility criteria. A third reviewer will resolve any disagreement. Data will be extracted using a predefined data extraction form following best practice. Study quality will be assessed using the Phillips checklist for decision analytic modelling. A narrative synthesis will be used. Ethics and dissemination The results will be made available in a scientific peer-reviewed journal paper, will be presented at relevant conferences and will also be made available through the ROADMAP project

A comparison of two workflows for regulome and transcriptome-based prioritization of genetic variants associated with myocardial mass

A typical task arising from main effect analyses in a Genome Wide Association Study (GWAS) is to identify single nucleotide polymorphisms (SNPs), in linkage disequilibrium with the observed signals, that are likely causal variants and the affected genes. The affected genes may not be those closest to associating SNPs. Functional genomics data from relevant tissues are believed to be helpful in selecting likely causal SNPs and interpreting implicated biological mechanisms, ultimately facilitating prevention and treatment in the case of a disease trait. These data are typically used post GWAS analyses to fine-map the statistically significant signals identified agnostically by testing all SNPs and applying a multiple testing correction. The number of tested SNPs is typically in the millions, so the multiple testing burden is high. Motivated by this, in this study we investigated an alternative workflow, which consists in utilizing the available functional genomics data as a first step to reduce the number of SNPs tested for association. We analyzed GWAS on electrocardiographic QRS duration using these two workflows. The alternative workflow identified more SNPs, including some residing in loci not discovered with the typical workflow. Moreover, the latter are corroborated by other reports on QRS duration. This indicates the potential value of incorporating functional genomics information at the onset in GWAS analyses