Literature DB >> 22994212

A highly sensitive and specific genetic marker to diagnose aspirin-exacerbated respiratory disease using a genome-wide association study.

Seung-Woo Shin1, JongSook Park, Yoon-Jeong Kim, Soo-taek Uh, Byoung Whui Choi, Mi-kyeong Kim, Inseon S Choi, Byung-Lae Park, HyoungDoo Shin, Choon-Sik Park.   

Abstract

The aim of the present study was to develop a diagnostic set of single-nucleotide polymorphisms (SNPs) for discriminating aspirin-exacerbated respiratory disease (AERD) from aspirin-tolerant asthma (ATA) using the genome-wide association study (GWAS) data; the GWAS data were filtered according to p-values and odds ratios (ORs) using PLINK software, and the 10 candidate SNPs most closely associated with AERD were selected, based on 100 AERD and 100 ATA subjects. Using multiple logistic regression and receiver-operating characteristic (ROC) curve analysis, eight SNPs were chosen as the best model for distinguishing between AERD and ATA. The relative risk for AERD in each subject was calculated based on the relative risk of each of the eight SNPs. Ten of the original 109,365 SNPs highly associated (filtered with p<0.001 and ORs) with the risk for AERD were selected. A combination model of the eight SNPs among the 10 SNPs showed the highest area under the ROC curve of 0.9. The overall relative risk for AERD based on the eight SNPs was significantly different between the AERD and ATA groups (p=2.802E-21), and the sensitivity and specificity were 78% and 88%, respectively. The candidate set of eight SNPs may be useful in predicting the risk for AERD.

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Year:  2012        PMID: 22994212     DOI: 10.1089/dna.2012.1688

Source DB:  PubMed          Journal:  DNA Cell Biol        ISSN: 1044-5498            Impact factor:   3.311


  9 in total

1.  Development of a genetic marker set to diagnose aspirin-exacerbated respiratory disease in a genome-wide association study.

Authors:  H S Chang; S W Shin; T H Lee; D J Bae; J S Park; Y H Kim; S T Uh; B W Choi; M K Kim; I S Choi; B L Park; H D Shin; C S Park
Journal:  Pharmacogenomics J       Date:  2015-02-24       Impact factor: 3.550

Review 2.  Aspirin exacerbated respiratory disease (AERD): molecular and cellular diagnostic & prognostic approaches.

Authors:  Habib Hybar; Najmaldin Saki; Mohsen Maleknia; Mana Moghaddasi; Armin Bordbar; Maliheh Naghavi
Journal:  Mol Biol Rep       Date:  2021-02-24       Impact factor: 2.316

Review 3.  Genetic and Epigenetic Components of Aspirin-Exacerbated Respiratory Disease.

Authors:  Amber Dahlin; Scott T Weiss
Journal:  Immunol Allergy Clin North Am       Date:  2016-11       Impact factor: 3.479

4.  Genome-wide association study identifies TNFSF15 associated with childhood asthma.

Authors:  Kyung Won Kim; Dong Yun Kim; Dankyu Yoon; Ka-Kyung Kim; Haerin Jang; Nathan Schoettler; Eun Gyul Kim; Mi Na Kim; Jung Yeon Hong; Jeom-Kyu Lee; Sangwoo Kim; Carole Ober; Heon Yung Gee; Myung Hyun Sohn
Journal:  Allergy       Date:  2021-06-14       Impact factor: 13.146

5.  Exonic variants associated with development of aspirin exacerbated respiratory diseases.

Authors:  Seung-Woo Shin; Byung Lae Park; HunSoo Chang; Jong Sook Park; Da-Jeong Bae; Hyun-Ji Song; Inseon S Choi; Mi-Kyeong Kim; Hea-Sim Park; Lyoung Hyo Kim; Suhg Namgoong; Ji On Kim; Hyoung Doo Shin; Choon-Sik Park
Journal:  PLoS One       Date:  2014-11-05       Impact factor: 3.240

6.  Computational methods using genome-wide association studies to predict radiotherapy complications and to identify correlative molecular processes.

Authors:  Jung Hun Oh; Sarah Kerns; Harry Ostrer; Simon N Powell; Barry Rosenstein; Joseph O Deasy
Journal:  Sci Rep       Date:  2017-02-24       Impact factor: 4.379

7.  Integrative information theoretic network analysis for genome-wide association study of aspirin exacerbated respiratory disease in Korean population.

Authors:  Sehee Wang; Hyun-Hwan Jeong; Dokyoon Kim; Kyubum Wee; Hae-Sim Park; Seung-Hyun Kim; Kyung-Ah Sohn
Journal:  BMC Med Genomics       Date:  2017-05-24       Impact factor: 3.063

8.  Machine learning on genome-wide association studies to predict the risk of radiation-associated contralateral breast cancer in the WECARE Study.

Authors:  Sangkyu Lee; Xiaolin Liang; Meghan Woods; Anne S Reiner; Patrick Concannon; Leslie Bernstein; Charles F Lynch; John D Boice; Joseph O Deasy; Jonine L Bernstein; Jung Hun Oh
Journal:  PLoS One       Date:  2020-02-27       Impact factor: 3.240

9.  Genome-Wide Association Study of Korean Asthmatics: A Comparison With UK Asthmatics.

Authors:  Jin An; Ah Ra Do; Hae Yeon Kang; Woo Jin Kim; Sanghun Lee; Ji Hyang Lee; Woo Jung Song; Hyouk Soo Kwon; You Sook Cho; Hee Bom Moon; Sile Hu; Ian M Adcock; Kian Fan Chung; Sungho Won; Tae Bum Kim
Journal:  Allergy Asthma Immunol Res       Date:  2021-07       Impact factor: 5.764

  9 in total

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