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"Lee, Phil"
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A genome-wide cross-trait analysis from UK Biobank highlights the shared genetic architecture of asthma and allergic diseases
Clinical and epidemiological data suggest that asthma and allergic diseases are associated and may share a common genetic etiology. We analyzed genome-wide SNP data for asthma and allergic diseases in 33,593 cases and 76,768 controls of European ancestry from UK Biobank. Two publicly available independent genome-wide association studies were used for replication. We have found a strong genome-wide genetic correlation between asthma and allergic diseases (
r
g
= 0.75,
P
= 6.84 × 10
−62
). Cross-trait analysis identified 38 genome-wide significant loci, including 7 novel shared loci. Computational analysis showed that shared genetic loci are enriched in immune/inflammatory systems and tissues with epithelium cells. Our work identifies common genetic architectures shared between asthma and allergy and will help to advance understanding of the molecular mechanisms underlying co-morbid asthma and allergic diseases.
Genome-wide cross-trait analysis shows a strong genetic correlation between asthma and allergic diseases. Shared susceptibility loci are enriched for genes involved in immune and inflammatory responses and genes expressed in epithelial tissues.
Journal Article
Bruges and Ghent
Discover these picture-perfect Belgian cities with the most incisive and entertaining travel guide on the market. You can take this handy, pocket-sized book out with you anywhere, any time. Whether you plan to admire medieval Flemish art and modern masterpieces, explore on foot, by bike or canal boat, or simply track down the best beer and ......
Book
Pleiotropy in complex traits: challenges and strategies
Key Points
Genome-wide association studies have identified many novel loci for hundreds of traits. Interestingly, numerous genetic loci have been associated with multiple seemingly distinct traits. These cross-phenotype (CP) associations highlight the relevance of pleiotropy in human disease.
There is substantial evidence for CP associations in contemporary gene-mapping studies.
Different types of pleiotropy (biological, mediated and spurious pleiotropy) can underlie a CP association.
Various analytical approaches have been devised for detecting CP associations, especially methods that are based on summary statistics as opposed to individual-level data. Different methods have relative advantages and disadvantages and are distinguished by their underlying algorithms and by the types of phenotype data that they handle.
Study design considerations are crucial for minimizing the identification of spurious CP associations.
CP associations can highlight shared biological pathways and, when associated with different diseases, have clinical implications for diagnosis, counselling and treatment.
Modern genomic studies are revealing widespread associations between single genetic variants and multiple distinct traits, including diseases. This Review discusses the biological underpinnings of such pleiotropy and the available bioinformatic tools for the detection and characterization of these effects, as well as the implications for understanding human disease.
Genome-wide association studies have identified many variants that each affects multiple traits, particularly across autoimmune diseases, cancers and neuropsychiatric disorders, suggesting that pleiotropic effects on human complex traits may be widespread. However, systematic detection of such effects is challenging and requires new methodologies and frameworks for interpreting cross-phenotype results. In this Review, we discuss the evidence for pleiotropy in contemporary genetic mapping studies, new and established analytical approaches to identifying pleiotropic effects, sources of spurious cross-phenotype effects and study design considerations. We also outline the molecular and clinical implications of such findings and discuss future directions of research.
Journal Article
Principles and methods of in-silico prioritization of non-coding regulatory variants
Over a decade of genome-wide association, studies have made great strides toward the detection of genes and genetic mechanisms underlying complex traits. However, the majority of associated loci reside in non-coding regions that are functionally uncharacterized in general. Now, the availability of large-scale tissue and cell type-specific transcriptome and epigenome data enables us to elucidate how non-coding genetic variants can affect gene expressions and are associated with phenotypic changes. Here, we provide an overview of this emerging field in human genomics, summarizing available data resources and state-of-the-art analytic methods to facilitate in-silico prioritization of non-coding regulatory mutations. We also highlight the limitations of current approaches and discuss the direction of much-needed future research.
Journal Article
The rough guide to Norway
A budget guide to traveling in Norway that discusses the history of the country, transportation, money, and other topics; and provides information on accommodations, dining, nightlife, and major attractions.
Book
Automated segmentation of ultra-widefield fluorescein angiography of diabetic retinopathy using deep learning
Background/AimsRetinal capillary non-perfusion (NP) and neovascularisation (NV) are two of the most important angiographic changes in diabetic retinopathy (DR). This study investigated the feasibility of using deep learning (DL) models to automatically segment NP and NV on ultra-widefield fluorescein angiography (UWFA) images from patients with DR.MethodsRetrospective cross-sectional chart review study. In total, 951 UWFA images were collected from patients with severe non-proliferative DR (NPDR) or proliferative DR (PDR). Each image was segmented and labelled for NP, NV, disc, background and outside areas. Using the labelled images, DL models were trained and validated (80%) using convolutional neural networks (CNNs) for automated segmentation and tested (20%) on test sets. Accuracy of each model and each label were assessed.ResultsThe best accuracy from CNN models for each label was 0.8208, 0.8338, 0.9801, 0.9253 and 0.9766 for NP, NV, disc, background and outside areas, respectively. The best Intersection over Union for each label was 0.6806, 0.5675, 0.7107, 0.8551 and 0.924 and mean mean boundary F1 score (BF score) was 0.6702, 0.8742, 0.9092, 0.8103 and 0.9006, respectively.ConclusionsDL models can detect NV and NP as well as disc and outer margins on UWFA with good performance. This automated segmentation of important UWFA features will aid physicians in DR clinics and in overcoming grader subjectivity.
Journal Article
The rough guide to Mallorca & Menorca
\"TRAVEL & HOLIDAY GUIDES. The Rough Guide to Mallorca & Menorca - now in full colour throughout - gets behind the sun, sex, booze and high-rise hotels cliches to reveal the surprising delights of these Balearic islands. Away from the handful of mega-resorts, discover the bustle of Mallorca's capital, Palma, the craggy mountains and medieval monasteries of the north coast, and the charming towns of the central plain. Menorca, lying to the east, boasts an interior of rollingfields and wooded ravines in between its capital Mao, and the beautifully preserved town of Ciutadella, while a chain of conservation areas protect the pristine coves and beaches that are Menorca's real treasures. Stunning photos, potential itineraries, day hike routes, colour-coded maps and trustworthy hotel and restaurant reviews, not to mention all the practical information you need, will help you enjoy the very best of both these islands. Make the most of your holiday with The Rough Guide to Mallorca & Menorca.\"--Provided by publisher.
Book
Low-dose pioglitazone can ameliorate learning and memory impairment in a mouse model of dementia by increasing LRP1 expression in the hippocampus
Amyloid-β (Aβ) accumulation in the brain is a pathological feature of Alzheimer’s disease (AD) and enhancing Aβ clearance is a potential therapeutic strategy. Pioglitazone is a peroxisome proliferator-activated receptor-γ (PPAR-γ) agonist and is widely used to treat type 2 diabetes. We previously reported that low-dose pioglitazone increased the expression of low-density lipoprotein receptor-related protein 1 (LRP1), which upregulates the clearance of Aβ, using human brain microvascular endothelial cells. We investigated whether low-dose pioglitazone can rescue the pathological phenotype and memory impairment in senescence-accelerated mouse prone-8 (SAMP8) mice by increasing LRP1 levels. SAMP8 mice were treated with vehicle or pioglitazone in dosages of 2 or 5 mg/kg/day for 7 weeks. In the water maze test, 2 mg/kg/day of pioglitazone significantly attenuated the increased escape latency in SAMP8 mice (
p
= 0.026), while 5 mg/kg/day of treatment did not. Compared with vehicle treatment, the hippocampi of SAMP8 mice with 2 mg/kg/day of pioglitazone exhibited fewer Aβ deposits and reduced Aβ
1–40
levels, along with elevated LRP1 expression (
p
= 0.005). Collectively, our results proposed that a new therapeutic application of the PPAR-γ agonist for AD treatment should be considered at a lower dose than the conventional dose used to treat diabetes.
Journal Article