139 research outputs found
KELVIN: A Software Package for Rigorous Measurement of Statistical Evidence in Human Genetics
This paper describes the software package KELVIN, which supports the PPL (posterior probability of linkage) framework for the measurement of statistical evidence in human (or more generally, diploid) genetic studies. In terms of scope, KELVIN supports two-point (trait-marker or marker-marker) and multipoint linkage analysis, based on either sex-averaged or sex-specific genetic maps, with an option to allow for imprinting; trait-marker linkage disequilibrium (LD), or association analysis, in case-control data, trio data, and/or multiplex family data, with options for joint linkage and trait-marker LD or conditional LD given linkage; dichotomous trait, quantitative trait and quantitative trait threshold models; and certain types of gene-gene interactions and covariate effects. Features and data (pedigree) structures can be freely mixed and matched within analyses. The statistical framework is specifically tailored to accumulate evidence in a mathematically rigorous way across multiple data sets or data subsets while allowing for multiple sources of heterogeneity, and KELVIN itself utilizes sophisticated software engineering to provide a powerful and robust platform for studying the genetics of complex disorders
Aging Alters Functionally Human Dermal Papillary Fibroblasts but Not Reticular Fibroblasts: A New View of Skin Morphogenesis and Aging
Understanding the contribution of the dermis in skin aging is a key question, since this tissue is particularly important for skin integrity, and because its properties can affect the epidermis. Characteristics of matched pairs of dermal papillary and reticular fibroblasts (Fp and Fr) were investigated throughout aging, comparing morphology, secretion of cytokines, MMPs/TIMPs, growth potential, and interaction with epidermal keratinocytes. We observed that Fp populations were characterized by a higher proportion of small cells with low granularity and a higher growth potential than Fr populations. However, these differences became less marked with increasing age of donors. Aging was also associated with changes in the secretion activity of both Fp and Fr. Using a reconstructed skin model, we evidenced that Fp and Fr cells do not possess equivalent capacities to sustain keratinopoiesis. Comparing Fp and Fr from young donors, we noticed that dermal equivalents containing Fp were more potent to promote epidermal morphogenesis than those containing Fr. These data emphasize the complexity of dermal fibroblast biology and document the specific functional properties of Fp and Fr. Our results suggest a new model of skin aging in which marked alterations of Fp may affect the histological characteristics of skin
Novel method for combined linkage and genome-wide association analysis finds evidence of distinct genetic architecture for two subtypes of autism
The Autism Genome Project has assembled two large datasets originally designed for linkage analysis and genome-wide association analysis, respectively: 1,069 multiplex families genotyped on the Affymetrix 10 K platform, and 1,129 autism trios genotyped on the Illumina 1 M platform. We set out to exploit this unique pair of resources by analyzing the combined data with a novel statistical method, based on the PPL statistical framework, simultaneously searching for linkage and association to loci involved in autism spectrum disorders (ASD). Our analysis also allowed for potential differences in genetic architecture for ASD in the presence or absence of lower IQ, an important clinical indicator of ASD subtypes. We found strong evidence of multiple linked loci; however, association evidence implicating specific genes was low even under the linkage peaks. Distinct loci were found in the lower IQ families, and these families showed stronger and more numerous linkage peaks, while the normal IQ group yielded the strongest association evidence. It appears that presence/absence of lower IQ (LIQ) demarcates more genetically homogeneous subgroups of ASD patients, with not just different sets of loci acting in the two groups, but possibly distinct genetic architecture between them, such that the LIQ group involves more major gene effects (amenable to linkage mapping), while the normal IQ group potentially involves more common alleles with lower penetrances. The possibility of distinct genetic architecture across subtypes of ASD has implications for further research and perhaps for research approaches to other complex disorders as well
Adaptation of HIV-1 Depends on the Host-Cell Environment
Many viruses have the ability to rapidly develop resistance against antiviral drugs and escape from the host immune system. To which extent the host environment affects this adaptive potential of viruses is largely unknown. Here we show that for HIV-1, the host-cell environment is key to the adaptive potential of the virus. We performed a large-scale selection experiment with two HIV-1 strains in two different T-cell lines (MT4 and C8166). Over 110 days of culture, both virus strains adapted rapidly to the MT4 T-cell line. In contrast, when cultured on the C8166 T-cell line, the same strains did not show any increase in fitness. By sequence analyses and infections with viruses expressing either yellow or cyan fluorescent protein, we were able to show that the absence of adaptation was linked to a lower recombination rate in the C8166 T-cell line. Our findings suggest that if we can manipulate the host-cellular factors that mediate viral evolution, we may be able to significantly retard viral adaptability
Genetic linkage analysis in the age of whole-genome sequencing
For many years, linkage analysis was the primary tool used for the genetic mapping of Mendelian and complex traits with familial aggregation. Linkage analysis was largely supplanted by the wide adoption of genome-wide association studies (GWASs). However, with the recent increased use of whole-genome sequencing (WGS), linkage analysis is again emerging as an important and powerful analysis method for the identification of genes involved in disease aetiology, often in conjunction with WGS filtering approaches. Here, we review the principles of linkage analysis and provide practical guidelines for carrying out linkage studies using WGS data
Importance of patient bed pathways and length of stay differences in predicting COVID-19 hospital bed occupancy in England.
Background: Predicting bed occupancy for hospitalised patients with COVID-19 requires understanding of length of stay (LoS) in particular bed types. LoS can vary depending on the patient’s “bed pathway” - the sequence of transfers of individual patients between bed types during a hospital stay. In this study, we characterise these pathways, and their impact on predicted hospital bed occupancy. Methods: We obtained data from University College Hospital (UCH) and the ISARIC4C COVID-19 Clinical Information Network (CO-CIN) on hospitalised patients with COVID-19 who required care in general ward or critical care (CC) beds to determine possible bed pathways and LoS. We developed a discrete-time model to examine the implications of using either bed pathways or only average LoS by bed type to forecast bed occupancy. We compared model-predicted bed occupancy to publicly available bed occupancy data on COVID-19 in England between March and August 2020. Results: In both the UCH and CO-CIN datasets, 82% of hospitalised patients with COVID-19 only received care in general ward beds. We identified four other bed pathways, present in both datasets: “Ward, CC, Ward”, “Ward, CC”, “CC” and “CC, Ward”. Mean LoS varied by bed type, pathway, and dataset, between 1.78 and 13.53 days. For UCH, we found that using bed pathways improved the accuracy of bed occupancy predictions, while only using an average LoS for each bed type underestimated true bed occupancy. However, using the CO-CIN LoS dataset we were not able to replicate past data on bed occupancy in England, suggesting regional LoS heterogeneities. Conclusions: We identified five bed pathways, with substantial variation in LoS by bed type, pathway, and geography. This might be caused by local differences in patient characteristics, clinical care strategies, or resource availability, and suggests that national LoS averages may not be appropriate for local forecasts of bed occupancy for COVID-19. Trial registration: The ISARIC WHO CCP-UK study ISRCTN66726260 was retrospectively registered on 21/04/2020 and designated an Urgent Public Health Research Study by NIHR.</p
Ser mentor em medicina: uma visão arquetípica das motivações e transformações na jornada
Pest risk assessment of Eotetranychus lewisi for the EU territory
Based on the pest categorisation prepared by EFSA, E. lewisi has the potential to be both a quarantine pest, as it fulfils all ISPM 11 criteria, and a Non-Regulated Quarantine Pest, as it fulfils all ISPM 21 criteria. However, it is noted that information on the potential impact is very limited. At the same time, the organism is currently regulated only for plants of Citrus L., Fortunella Swingle, Poncirus Raf. and their hybrids. However, the affected host range is broader than what is currently covered. There are major hosts such as plants of Euphorbia, Rubus, Fragaria, Prunus, Vitis, etc. which are not regulated for this specific organism. In the European Union (EU), it has been found, for example, also on plants of Corokia cotoneaster in 1999. The pathways of spreading are numerous.
The Working Group recommends to keep this organism as Union Quarantine Pest. To support further decisions on risk reduction options, the PRA process has to continue. In particular, EFSA is asked to focus further work on the probability of entry of the pest (identification of the pathways), its establishment, as well as further spread after its establishment in the EU. It is important to explore as well the reasons for its absence in the EU. Additional information as regards the degree of impact would be also relevant even though the Working Group above acknowledges the absence of data in this respect
Characterising within-hospital SARS-CoV-2 transmission events using epidemiological and viral genomic data across two pandemic waves
Hospital outbreaks of COVID19 result in considerable mortality and disruption to healthcare services and yet little is known about transmission within this setting. We characterise within hospital transmission by combining viral genomic and epidemiological data using Bayesian modelling amongst 2181 patients and healthcare workers from a large UK NHS Trust. Transmission events were compared between Wave 1 (1st March to 25th July 2020) and Wave 2 (30th November 2020 to 24th January 2021). We show that staff-to-staff transmissions reduced from 31.6% to 12.9% of all infections. Patient-to-patient transmissions increased from 27.1% to 52.1%. 40%-50% of hospital-onset patient cases resulted in onward transmission compared to 4% of community-acquired cases. Control measures introduced during the pandemic likely reduced transmissions between healthcare workers but were insufficient to prevent increasing numbers of patient-to-patient transmissions. As hospital-acquired cases drive most onward transmission, earlier identification of nosocomial cases will be required to break hospital transmission chains
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