Connorduus9463

© 2020 The Author(s).Genetic variation occurring within conserved functional protein domains warrants special attention when examining DNA variation in the context of disease causation. Here we introduce a resource, freely available at www.prot2hg.com, that addresses the question of whether a particular variant falls onto an annotated protein domain and directly translates chromosomal coordinates onto protein residues. The tool can perform a multiple-site query in a simple way, and the whole dataset is available for download as well as incorporated into our own accessible pipeline. To create this resource, National Center for Biotechnology Information protein data were retrieved using the Entrez Programming Utilities. After processing all human protein domains, residue positions were reverse translated and mapped to the reference genome hg19 and stored in a MySQL database. In total, 760 487 protein domains from 42 371 protein models were mapped to hg19 coordinates and made publicly available for search or download (www.prot2hg.com). In addition, this annotation was implemented into the genomics research platform GENESIS in order to query nearly 8000 exomes and genomes of families with rare Mendelian disorders (tgp-foundation.org). When applied to patient genetic data, we found that rare (1%) variants. Similarly, variants described as pathogenic or likely pathogenic in ClinVar were more likely to be annotated onto a domain. In addition, we tested a dataset consisting of 60 causal variants in a cohort of patients with epileptic encephalopathy and found that 71% of them (43 variants) were propagated onto protein domains. In summary, we developed a resource that annotates variants in the coding part of the genome onto conserved protein domains in order to increase variant prioritization efficiency. © The Author(s) 2020. Published by Oxford University Press.Falling sequencing costs and large initiatives are resulting in increasing amounts of data available for investigator use. However, there are informatics challenges in being able to access genomic data. Performance and storage are well-appreciated issues, but precision is critical for meaningful analysis and interpretation of genomic data. There is an inherent accuracy vs. performance trade-off with existing solutions. The most common approach (Variant-only Storage Model, VOSM) stores only variant data. Systems must therefore assume that everything not variant is reference, sacrificing precision and potentially accuracy. A more complete model (Full Storage Model, FSM) would store the state of every base (variant, reference and missing) in the genome thereby sacrificing performance. A compressed variation of the FSM can store the state of contiguous regions of the genome as blocks (Block Storage Model, BLSM), much like the file-based gVCF model. We propose a novel approach by which this state is encoded such that both performance and accuracy are maintained. The Negative Storage Model (NSM) can store and retrieve precise genomic state from different sequencing sources, including clinical and whole exome sequencing panels. Reduced storage requirements are achieved by storing only the variant and missing states and inferring the reference state. We evaluate the performance characteristics of FSM, BLSM and NSM and demonstrate dramatic improvements in storage and performance using the NSM approach. © The Author(s) 2020. Published by Oxford University Press.BACKGROUND AND OBJECTIVES Motivated by the high rates of health problems found among caregivers of persons with neurodegenerative disease, we examined associations between deficits in two aspects of care recipients' socioemotional functioning and their caregivers' health. RESEARCH DESIGN AND METHODS In 2 studies with independent samples (N = 171 and 73 dyads), caregivers reported on care recipients' emotion recognition and emotional reactivity. Caregiver health was assessed using both self-report measures (Studies 1 and 2) and autonomic nervous system indices (Study 2). RESULTS Lower emotion recognition in care recipients was linearly associated with worse self-reported health, faster resting heart rate, and greater physiological reactivity to an acoustic startle stimulus in caregivers. These effects held after accounting for a variety of risk factors for poor caregiver health, including care recipients' neuropsychiatric symptoms. Emotional reactivity showed a quadratic association with health, such that the lowest and highest levels of emotional reactivity in care recipients were associated with lower self-reported health in caregivers. DISCUSSION AND IMPLICATIONS Results shed light on the unique associations between two aspects of care recipients' emotional functioning and caregivers' health. Findings suggest potential ways to identify and help caregivers at heightened risk for adverse health outcomes. © The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail journals.permissions@oup.com.The Rapid Inquiry Facility 4.0 (RIF) is a new user-friendly and open-access tool, developed by the UK Small Area Health Statistics Unit (SAHSU), to facilitate environment public health tracking (EPHT) or surveillance (EPHS). The RIF is designed to help public health professionals and academics to rapidly perform exploratory investigations of health and environmental data at the small-area level (e.g. postcode or detailed census areas) in order to identify unusual signals, such as disease clusters and potential environmental hazards, whether localized (e.g. industrial site) or widespread (e.g. air and noise pollution). The RIF allows the use of advanced disease mapping methods, including Bayesian small-area smoothing and complex risk analysis functionalities, while accounting for confounders. PX-478 The RIF could be particularly useful to monitor spatio-temporal trends in mortality and morbidity associated with cardiovascular diseases, cancers, diabetes and chronic lung diseases, or to conduct local or national studies on air pollution, flooding, low-magnetic fields or nuclear power plants. © The Author(s) 2020. Published by Oxford University Press on behalf of the International Epidemiological Association.