نتایج جستجو برای: gwas

تعداد نتایج: 6259  

Journal: :Molecular & cellular proteomics : MCP 2013
Amitabh Sharma Natali Gulbahce Samuel J Pevzner Jörg Menche Claes Ladenvall Lasse Folkersen Per Eriksson Marju Orho-Melander Albert-László Barabási

Genome wide association studies (GWAS) identify susceptibility loci for complex traits, but do not identify particular genes of interest. Integration of functional and network information may help in overcoming this limitation and identifying new susceptibility loci. Using GWAS and comorbidity data, we present a network-based approach to predict candidate genes for lipid and lipoprotein traits....

2011
Naomi R. Wray Shaun M. Purcell Peter M. Visscher

Complex traits and diseases, such as body-mass index, height, diabetes, heart disease, and psychiatric disorders are undoubtedly caused by multiple genetic and environmental factors, although it has been a major challenge to identify specific genes. Recently, genome-wide association studies (GWAS) have resulted in the detection of many robustly associated single nucleotide polymorphism (SNP) va...

Journal: :Circulation Research 2020

Journal: :Circulation: Cardiovascular Genetics 2010

2012
Mattias Johansson Angus Roberts Dan Chen Yaoyong Li Manon Delahaye-Sourdeix Niraj Aswani Mark A. Greenwood Simone Benhamou Pagona Lagiou Ivana Holcátová Lorenzo Richiardi Kristina Kjaerheim Antonio Agudo Xavier Castellsagué Tatiana V. Macfarlane Luigi Barzan Cristina Canova Nalin S. Thakker David I. Conway Ariana Znaor Claire M. Healy Wolfgang Ahrens David Zaridze Neonilia Szeszenia-Dabrowska Jolanta Lissowska Eleonóra Fabiánová Ioan Nicolae Mates Vladimir Bencko Lenka Foretova Vladimir Janout Maria Paula Curado Sergio Koifman Ana Menezes Victor Wünsch-Filho Jose Eluf-Neto Paolo Boffetta Silvia Franceschi Rolando Herrero Leticia Fernandez Garrote Renato Talamini Stefania Boccia Pilar Galan Lars Vatten Peter Thomson Diana Zelenika Mark Lathrop Graham Byrnes Hamish Cunningham Paul Brennan Jon Wakefield James D. Mckay

BACKGROUND Genome-wide association studies (GWAS) require large sample sizes to obtain adequate statistical power, but it may be possible to increase the power by incorporating complementary data. In this study we investigated the feasibility of automatically retrieving information from the medical literature and leveraging this information in GWAS. METHODS We developed a method that searches...

2013
Blanca E. Himes Keith Sheppard Annerose Berndt Adriana S. Leme Rachel A. Myers Christopher R. Gignoux Albert M. Levin W. James Gauderman James J. Yang Rasika A. Mathias Isabelle Romieu Dara G. Torgerson Lindsey A. Roth Scott Huntsman Celeste Eng Barbara Klanderman John Ziniti Jody Senter-Sylvia Stanley J. Szefler Robert F. Lemanske Robert S. Zeiger Robert C. Strunk Fernando D. Martinez Homer Boushey Vernon M. Chinchilli Elliot Israel David Mauger Gerard H. Koppelman Dirkje S. Postma Maartje A. E. Nieuwenhuis Judith M. Vonk John J. Lima Charles G. Irvin Stephen P. Peters Michiaki Kubo Mayumi Tamari Yusuke Nakamura Augusto A. Litonjua Kelan G. Tantisira Benjamin A. Raby Eugene R. Bleecker Deborah A. Meyers Stephanie J. London Kathleen C. Barnes Frank D. Gilliland L. Keoki Williams Esteban G. Burchard Dan L. Nicolae Carole Ober Dawn L. DeMeo Edwin K. Silverman Beverly Paigen Gary Churchill Steve D. Shapiro Scott T. Weiss

Asthma is a common chronic respiratory disease characterized by airway hyperresponsiveness (AHR). The genetics of asthma have been widely studied in mouse and human, and homologous genomic regions have been associated with mouse AHR and human asthma-related phenotypes. Our goal was to identify asthma-related genes by integrating AHR associations in mouse with human genome-wide association study...

Journal: :The American Journal of Human Genetics 2012

Journal: :Rheumatology 2014

Journal: :Radiotherapy and Oncology 2018

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