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Using a total gene expression microarray, we detected 924 differentially expressed gene transcripts in lymphoblastoid cell lines (LCLs) between 19 male heroin-dependent individuals and 20 male control subjects, including 279 upregulated and 645 downregulated gene transcripts in heroin-dependent individuals. We verified the reduced expression of the neuron-specific enolase gene (ENO2) in heroin-dependent individuals using real-time quantitative polymerase chain reaction and Western blot analysis. We further compared the allele and genotype frequencies of three single nucleotide polymorphisms (SNPs, rs11064464, rs3213433 and rs10849541) of the ENO2 gene between 532 male heroin-dependent individuals and 369 male controls. No significant differences in the allele or genotype frequencies of these three SNPs were detected between these two Oxacillin groups. Nevertheless, we identified a haplotype (T-C-G) derived from these three SNPs significantly underrepresented in heroin-dependent individuals compared with the learn more control group (72.7% versus 75.9%, P?IPI-145 datasheet makes the treatment of heroin dependence a challenging task. Like the other substance use disorders, the development of heroin dependence results from the interactions between psychosocial factors and genetic predisposing factors (Vanyukov et?al. 2003). Previous studies have demonstrated that heroin dependence has a high estimated heritability, indicating that genetic factor plays an important role in its etiology (Goldman, Oroszi & Ducci 2005; Uhl et?al. 2008). Thus, identification of heroin dependence vulnerability genes can bring new insight into the pathogenesis of heroin dependence and help prevent its occurrence and relapse. Previous studies have revealed various genes associated with heroin dependence (Goldman et?al. 2005; Kreek et?al. 2005), indicating that heroin dependence is a complex polygenic disorder. However, more genes remain to be discovered. Microarray-based gene expression profiling analysis that allows simultaneous measurement of hundreds to thousands of gene transcripts has been successfully used for novel gene discovery in complex disorders (Schena et?al.