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A PheWAS Model of Autism Spectrum Disorder
2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), 2021Children with Autism Spectrum Disorder (ASD) exhibit a wide diversity in type, number, and severity of social deficits as well as communicative and cognitive difficulties. It is a challenge to categorize the phenotypes of a particular ASD patient with their unique genetic variants.
John Matta +6 more
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A PheWAS approach in studying HLA-DRB1*1501 [PDF]
Genes and Immunity, 2013 HLA-DRB1 codes for a major histocompatibility complex class II cell surface receptor. Genetic variants in and around this gene have been linked to numerous autoimmune diseases. Most notably, an association between HLA-DRB1*1501 haplotype and multiple sclerosis (MS) has been defined.
Steven Schrodi
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A Fast and Accurate Algorithm to Test for Binary Phenotypes and Its Application to PheWAS [PDF]
American Journal of Human Genetics, 2017 Abstract The availability of electronic health record (EHR)-based phenotypes allows for genome-wide association analyses in thousands of traits, and has great potential to identify novel genetic variants associated with clinical phenotypes.
Rounak Dey +2 more
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High-throughput multimodal automated phenotyping (MAP) with application to PheWAS [PDF]
Journal of the American Medical Informatics Association: JAMIA, 2019 Abstract Objective Electronic health records (EHR) linked with biorepositories are a powerful platform for translational studies. A major bottleneck exists in the ability to phenotype patients accurately and efficiently.
Chuan Hong +2 more
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Connecting phenotype to genotype: PheWAS-inspired analysis of autism spectrum disorder
Frontiers in Human Neuroscience, 2022 Autism Spectrum Disorder (ASD) is extremely heterogeneous clinically and genetically. There is a pressing need for a better understanding of the heterogeneity of ASD based on scientifically rigorous approaches centered on systematic evaluation of the clinical and research utility of both phenotype and genotype markers.
Tayo Obafemi-Ajayi +2 more
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Systematic analysis of genes and diseases using PheWAS-Associated networks
Computers in Biology and Medicine, 2019Several scientific sources have reported different causes of various diseases. One of these factors is genetic variation. Natural selection, molecular evolution and susceptibility to external conditions are the main causes of genetic variations. Phenome-Wide Association Studies (PheWAS) can emphasize the associations of genetic variations and diseases.
Morteza Kouhsar +2 more
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Using Phecodes for Research with the Electronic Health Record: From PheWAS to PheRS
Annual Review of Biomedical Data Science, 2021Electronic health records (EHRs) are a rich source of data for researchers, but extracting meaningful information out of this highly complex data source is challenging. Phecodes represent one strategy for defining phenotypes for research using EHR data. They are a high-throughput phenotyping tool based on ICD (International Classification of Diseases)
Lisa Bastarache
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Trophic Status of Lake Phewa and Kulekhani Reservoir, Nepal
Asian Journal of Water, Environment and Pollution, 2021Eutrophication is one of the growing environmental concerns and is affecting and compromising freshwater bodies across the world making the trophic status assessment of water bodies crucial for their restoration and sustainable use. This paper describes the trophic status of Lake Phewa and Kulekhani Reservoir from Nepal.
Gurung, Smriti +7 more
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PheWAS analysis on large-scale biobank data with PheTK
BioinformaticsAbstract Summary With the rapid growth of genetic data linked to electronic health record (EHR) data in huge cohorts, large-scale phenome-wide association study (PheWAS) have become powerful discovery tools in biomedical research.
Chenjie Zeng +2 more
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A PheWAS Analysis of the Risks and Benefits of Growing Up on a Farm
Journal of AgromedicineGrowing up on a farm presents a health paradox, with increased risks of injuries but some purported benefits. This study estimated differences in the burden of medical comorbidities between youth who live versus do not live on farms. No a priori hypotheses were tested.A phenome-wide association study (PheWAS) was used in a cohort of youth in north ...
Bryan Weichelt +2 more
exaly +3 more sources