نتایج جستجو برای: quantitative study

تعداد نتایج: 4154513  

2012
Lenora W. M. Loo Iona Cheng Maarit Tiirikainen Annette Lum-Jones Ann Seifried Lucas M. Dunklee James M. Church Robert Gryfe Daniel J. Weisenberger Robert W. Haile Steven Gallinger David J. Duggan Stephen N. Thibodeau Graham Casey Loïc Le Marchand

Genome-wide association studies (GWAS) have identified 19 risk variants associated with colorectal cancer. As most of these risk variants reside outside the coding regions of genes, we conducted cis-expression quantitative trait loci (cis-eQTL) analyses to investigate possible regulatory functions on the expression of neighboring genes. Forty microsatellite stable and CpG island methylator phen...

2015
Martijn van de Bunt Jocelyn E. Manning Fox Xiaoqing Dai Amy Barrett Caleb Grey Lei Li Amanda J. Bennett Paul R. Johnson Raymond V. Rajotte Kyle J. Gaulton Emmanouil T. Dermitzakis Patrick E. MacDonald Mark I. McCarthy Anna L. Gloyn Barbara E. Stranger

The intersection of genome-wide association analyses with physiological and functional data indicates that variants regulating islet gene transcription influence type 2 diabetes (T2D) predisposition and glucose homeostasis. However, the specific genes through which these regulatory variants act remain poorly characterized. We generated expression quantitative trait locus (eQTL) data in 118 huma...

2012
Rajat M. Gupta Kiran Musunuru

Genome-wide association studies (GWAS) have identified genetic variants associated with numerous cardiovascular and metabolic diseases. Newly identified polymorphisms associated with myocardial infarction, dyslipidemia, hypertension, diabetes, and insulin resistance suggest novel mechanistic pathways that underlie these and other complex diseases. Working out the connections between the polymor...

2012
Brandon L. Pierce Muhammad G. Kibriya Lin Tong Farzana Jasmine Maria Argos Shantanu Roy Rachelle Paul-Brutus Ronald Rahaman Muhammad Rakibuz-Zaman Faruque Parvez Alauddin Ahmed Iftekhar Quasem Samar K. Hore Shafiul Alam Tariqul Islam Vesna Slavkovich Mary V. Gamble Md Yunus Mahfuzar Rahman John A. Baron Joseph H. Graziano Habibul Ahsan

Arsenic contamination of drinking water is a major public health issue in many countries, increasing risk for a wide array of diseases, including cancer. There is inter-individual variation in arsenic metabolism efficiency and susceptibility to arsenic toxicity; however, the basis of this variation is not well understood. Here, we have performed the first genome-wide association study (GWAS) of...

Journal: :Neurobiology of aging 2013
Filippo Martinelli-Boneschi Giacomo Giacalone Giuseppe Magnani Gloria Biella Elisabetta Coppi Roberto Santangelo Paola Brambilla Federica Esposito Sara Lupoli Francesca Clerici Luisa Benussi Roberta Ghidoni Daniela Galimberti Rosanna Squitti Annamaria Confaloni Giuseppe Bruno Sabrina Pichler Manuel Mayhaus Matthias Riemenschneider Claudio Mariani Giancarlo Comi Elio Scarpini Giuliano Binetti Gianluigi Forloni Massimo Franceschi Diego Albani

We conducted a genome-wide association study in a cohort of 176 Italian Alzheimer's disease (AD) patients with extreme phenotype of response to cholinesterase inhibitors. Patients were classified into responders in case of positive, stable, or ≤1 worsening of mini-mental state examination score and into nonresponders if >3 points worsening during a median follow-up of 0.85 years of treatment. F...

Journal: :Cancer research 2013
Xifeng Wu Liang Wang Yuanqing Ye Jeremiah A Aakre Xia Pu Gee-Chen Chang Pan-Chyr Yang Jack A Roth Randolph S Marks Scott M Lippman Joe Y Chang Charles Lu Claude Deschamps Wu-Chou Su Wen-Chang Wang Ming-Shyan Huang David W Chang Yan Li V Shane Pankratz John D Minna Waun Ki Hong Michelle A T Hildebrandt Chao Agnes Hsiung Ping Yang

To identify the genetic factors that influence overall survival in never smokers who have non-small cell lung carcinoma (NSCLC), we conducted a consistency meta-analysis study using genome-wide association approaches for overall survival in 327 never smoker patients with NSCLC from The University of Texas MD Anderson Cancer Center (Houston, TX) and 293 cases from the Mayo Clinic (Rochester, MN)...

2013
Guanglong Jiang Arindom Chakraborty Zhiping Wang Malaz Boustani Yunlong Liu Todd Skaar Lang Li

BACKGROUND The genome-wide association studies (GWAS) have been successful during the last few years. A key challenge is that the interpretation of the results is not straightforward, especially for transacting SNPs. Integration of transcriptome data into GWAS may provide clues elucidating the mechanisms by which a genetic variant leads to a disease. METHODS Here, we developed a novel mediati...

2014
Kyung-Won Hong Seok Won Jeong Myungguen Chung Seong Beom Cho

Most genome-wide association studies consider genes that are located closest to single nucleotide polymorphisms (SNPs) that are highly significant for those studies. However, the significance of the associations between SNPs and candidate genes has not been fully determined. An alternative approach that used SNPs in expression quantitative trait loci (eQTL) was reported previously for Crohn's d...

2016
Darren A. Cusanovich Minal Caliskan Christine Billstrand Katelyn Michelini Claudia Chavarria Sherryl De Leon Amy Mitrano Noah Lewellyn Jack A. Elias Geoffrey L. Chupp Roberto M. Lang Sanjiv J. Shah Jeanne M. Decara Yoav Gilad Carole Ober

Genome-wide association studies (GWASs) have become a standard tool for dissecting genetic contributions to disease risk. However, these studies typically require extraordinarily large sample sizes to be adequately powered. Strategies that incorporate functional information alongside genetic associations have proved successful in increasing GWAS power. Following this paradigm, we present the re...

2012
Dena G. Hernandez Mike A. Nalls Matthew Moore Sean Chong Allissa Dillman Daniah Trabzuni J. Raphael Gibbs Mina Ryten Sampath Arepalli Michael E. Weale Alan B. Zonderman Juan Troncoso Richard O'Brien Robert Walker Colin Smith Stefania Bandinelli Bryan J. Traynor John Hardy Andrew B. Singleton Mark R. Cookson

Genome-wide association studies have nominated many genetic variants for common human traits, including diseases, but in many cases the underlying biological reason for a trait association is unknown. Subsets of genetic polymorphisms show a statistical association with transcript expression levels, and have therefore been nominated as expression quantitative trait loci (eQTL). However, many tis...

نمودار تعداد نتایج جستجو در هر سال

با کلیک روی نمودار نتایج را به سال انتشار فیلتر کنید