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Two-stage designs to identify the effects of SNP combinations on complex diseases
Kang, Guolian2; Yue, Weihua1; Zhang, Jifeng2; Huebner, Marianne3; Zhang, Handi1; Ruan, Yan1; Lu, Tianlan1; Ling, Yansu1; Zuo, Yijun3; Zhang, Dai1
2008-08-01
Source PublicationJOURNAL OF HUMAN GENETICS
ISSN1434-5161
Volume53Issue:8Pages:739-746
AbstractThe genetic basis of complex diseases is expected to be highly heterogeneous, with many disease genes, where each gene by itself has only a small effect. Based on the nonlinear contributions of disease genes across the genome to complex diseases, we introduce the concept of single nucleotide polymorphism (SNP) synergistic blocks. A two-stage approach is applied to detect the genetic association of synergistic blocks with a disease. In the first stage, synergistic blocks associated with a complex disease are identified by clustering SNP patterns and choosing blocks within a cluster that minimize a diversity criterion. In the second stage, a logistic regression model is given for a synergistic block. Using simulated case-control data, we demonstrate that our method has reasonable power to identify gene-gene interactions. To further evaluate the performance of our method, we apply our method to 17 loci of four candidate genes for paranoid schizophrenia in a Chinese population. Five synergistic blocks are found to be associated with schizophrenia, three of which are negatively associated (odds ratio, OR < 0.3, P < 0.05), while the others are positively associated (OR > 2.0, P < 0.05). The mathematical models of these five synergistic blocks are presented. The results suggest that there may be interactive effects for schizophrenia among variants of the genes neuregulin 1 (NRG1, 8p22-p11), G72 (13q34), the regulator of G-protein signaling-4 (RGS4, 1q21-q22) and frizzled 3 (FZD3, 8p21). Using synergistic blocks, we can reduce the dimensionality in a multi-locus association analysis, and evaluate the sizes of interactive effects among multiple disease genes on complex phenotypes.
KeywordSNP pattern synergistic block association study
DOI10.1007/s10038-008-0307-x
Language英语
WOS Research AreaGenetics & Heredity
WOS SubjectGenetics & Heredity
WOS IDWOS:000258112900008
PublisherNATURE PUBLISHING GROUP
Citation statistics
Document Type期刊论文
Identifierhttp://ir.amss.ac.cn/handle/2S8OKBNM/5719
Collection系统科学研究所
Corresponding AuthorZhang, Dai
Affiliation1.Peking Univ, Inst Mental Hlth, Key Lab Mental Hlth, Minist Hlth, Beijing 100083, Peoples R China
2.Chinese Acad Sci, Acad Math & Syst Sci, Inst Syst Sci, Key Lab Syst & Control, Beijing 100080, Peoples R China
3.Michigan State Univ, Dept Stat & Probabil, E Lansing, MI 48824 USA
Recommended Citation
GB/T 7714
Kang, Guolian,Yue, Weihua,Zhang, Jifeng,et al. Two-stage designs to identify the effects of SNP combinations on complex diseases[J]. JOURNAL OF HUMAN GENETICS,2008,53(8):739-746.
APA Kang, Guolian.,Yue, Weihua.,Zhang, Jifeng.,Huebner, Marianne.,Zhang, Handi.,...&Zhang, Dai.(2008).Two-stage designs to identify the effects of SNP combinations on complex diseases.JOURNAL OF HUMAN GENETICS,53(8),739-746.
MLA Kang, Guolian,et al."Two-stage designs to identify the effects of SNP combinations on complex diseases".JOURNAL OF HUMAN GENETICS 53.8(2008):739-746.
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