Literature DB >> 21318483

Identification of a combination of SNPs associated with Graves' disease using swarm intelligence.

Bin Wei1, QinKe Peng, QuanWei Zhang, ChenYao Li.   

Abstract

Graves' disease, the production of thyroid-stimulating hormone receptor-stimulating antibodies leading to hyperthyroidism, is one of the most common forms of human autoimmune disease. It is widely agreed that complex diseases are not controlled simply by an individual gene or DNA variation but by their combination. Single nucleotide polymorphisms (SNPs), which are the most common form of DNA variation, have great potential as a medical diagnostic tool. In this paper, the P-value is used as a SNP pre-selection criterion, and a wrapper algorithm with binary particle swarm optimization is used to find the rule for discriminating between affected and control subjects. We analyzed the association between combinations of SNPs and Graves' disease by investigating 108 SNPs in 384 cases and 652 controls. We evaluated our method by differentiating between cases and controls in a five-fold cross validation test, and it achieved a 72.9% prediction accuracy with a combination of 17 SNPs. The experimental results showed that SNPs, even those with a high P-value, have a greater effect on Graves' disease when acting in a combination.

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Year:  2011        PMID: 21318483     DOI: 10.1007/s11427-010-4117-y

Source DB:  PubMed          Journal:  Sci China Life Sci        ISSN: 1674-7305            Impact factor:   6.038


  2 in total

1.  A 20 year history of clinical and genetic study of thyroid autoimmunity in a Tunisian multigenerational family: Evidence for gene interaction.

Authors:  Noura Bougacha-Elleuch; Nadia Charfi; Najla Kharrat; Fatma Ayadi; Abdellatif Maalej; Ghazi Chabchoub; Ahmed Rebai; Maha Kammoun-Krichen; Salima Belguith-Maalej; Mohamed Abid; Mouna Mnif; Hammadi Ayadi
Journal:  Meta Gene       Date:  2013-12-29

2.  Detecting Susceptibility to Breast Cancer with SNP-SNP Interaction Using BPSOHS and Emotional Neural Networks.

Authors:  Xiao Wang; Qinke Peng; Yue Fan
Journal:  Biomed Res Int       Date:  2016-05-11       Impact factor: 3.411

  2 in total

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