Objective: To develop novel strategies to identify relevant molecular signatures for complex human diseases based on data of identical-by-decent profiles and genomic context.Methods: In the proposed strategies, we define four relevancy criteria for mapping SNP-phenotype relationships-point-wise IBD mean difference, averaged IBD difference for window, Z curve and averaged slope for window.Results: Application of these criteria and permutation test to 100 simulated replicates for two hypothetical American populations to extract the relevant SNPs for alcoholism based on sib-pair IBD profiles of pedigrees demonstrates that the proposed strategies have successfully identified most of the simulated true loci.Conclusion: The data mining practice implies that IBD statistic and genomic context could be used as the informatics for locating the underlying genes for complex human diseases. Compared with the classical Haseman-Elston sib-pair regression method, the proposed strategies are more efficient for large-scale genomic mining.

Objective: To extract the relevant SNPs for alcoholism using sib-pair IBD profiles of pedigrees.Methods: We used the ensemble decision approach, a supervised learning approach based on decision forests, to locate alcoholism relevant SNPs using genome-wide SNP data. Results: Application to a publicly available large dataset of 100 simulated replicates for three American populations (http://www.gaworkshop.org/) demonstrates that the proposed approach has successfully located all of the simulated true loci.Conclusion: The numerical results establish the proposed decision forest analysis to be a powerful and practical alternative for large-scale family-based association study.

OBJECTIVETo evaluate the association between the two single nucleotide polymorphisms located in catechol-O-methyltransferase (COMT) gene and type 2 diabetes mellitus (T2DM)in Han population in Guangdong province.

METHODSTwo tagSNPs (rs4646312 and rs4680) were picked out from COMT gene. Using the SNPscan(TM) Kit, SNP genotyping was then performed, in two cohorts, including 595 cases and 725 controls. Finally, Chi-square test, logistic regression model and other methods were employed for statistical analysis.

RESULTSThe frequencies of TT, CT and CC of rs4646312 appeared to be 304(51.1%), 234(39.3%)and 57 (8.6%) in cases, 323 (44.6%), 319 (44.0%) and 83(11.4%)in controls, respectively. The frequencies of GG,GA and AA of rs4680 were 311(52.4%), 236 (39.8%) and 46(7.8%)in cases, 417(57.7%), 265 (36.6%) and 41 (5.7%) in controls, respectively.

RESULTSshowed that SNP rs4646312 was significantly associated with T2DM both in allelic association analysis (P = 0.020,OR = 1.26, 95%CI:1.04-1.53)and in recessive model (P = 0.022, OR = 1.35, 95% CI:1.05-1.74)after adjustment for sex,BMI and TG. The association between rs4680 and T2DM was not significant, but BMI was remarkably different among the three genotypes of rs4680 after controlling for other factors.

CONCLUSIONSNP rs4646312 of COMT gene was associated with the increased risk of T2DM in Han population in Guangdong province. However, rs4680 was not significantly associated with T2DM.

Adult ; Aged ; Alleles ; Case-Control Studies ; Catechol O-Methyltransferase ; genetics ; Diabetes Mellitus, Type 2 ; etiology ; genetics ; Female ; Gene Frequency ; Genotype ; Humans ; Male ; Middle Aged ; Polymorphism, Single Nucleotide