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Genome-wide association (GWA) studies based on haplo type have emerged as a new and powerful approach to identify the genetic variants involved in human complex diseases. A challenging problem after a GWA study based on haplotype is to select high-risk disease-related regions from the results that contain false association between genotype and phenotype. Haplotype similarity difference in a particular region between affected and unaffected individuals can be considered a sound evidence for susceptibility loci in the region. In our study, we developed a new statistic to measure the haplotype similarity difference between the cases and controls around disease susceptibility regions, and then we selected and prioritized high-risk disease-related blocks after a GWA study based on haplotype. Our results show that the novel method combining evolutionary information to select high-risk disease-related regions after GWA studies based on haplotype can locate the disease-related regions precisely and improve the efficiency of a genome wide haplotype-based association study.