• Asian Pacific Journal of Cancer Prevention
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• v.17 no.2
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• pp.647-653
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• 2016

Background: Breast cancer is the most common type of cancer affecting Malaysian women. Recent statistics revealed that the cumulative probability of breast cancer and related deaths in Malaysia is higher than in most of the countries of Southeast Asia. Single nucleotide polymorphisms (SNPs) in CYP2E1 (rs6413432 and rs3813867), STK15 (rs2273535 and rs1047972) and XRCC1 (rs1799782 and rs25487) have been associated with breast cancer risk in a meta-analysis but any link in Southeast Asia, including Malaysia, remained to be determined. Hence, we investigated the relationship between these SNPs and breast cancer risk among Malaysian women in the present case-control study. Materials and Methods: Genomic DNA was isolated from peripheral blood of 71 breast cancer patients and 260 healthy controls and subjected to polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) analysis. Results: Our study showed that the c1/c2 genotype or subjects with at least one c2 allele in CYP2E1 rs3813867 SNP had significantly increased almost 1.8-fold higher breast cancer risk in Malaysian women overall. In addition, the variant Phe allele in STK15 rs2273535 SNP appeared to protect against breast cancer in Malaysian Chinese. No significance association was found between XRCC1 SNPs and breast cancer risk in the population. Conclusions: This study provides additional knowledge on CYP2E1, STK15 and XRCC1 SNP impact of risk of breast cancer, particularly in the Malaysian population. From our findings, we also recommend Malaysian women to perform breast cancer screening before 50 years of age.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.16
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• pp.6709-6714
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• 2014

The rs2273535 polymorphism in the AURKA gene had proven to be associated with breast carcinoma susceptibility. Nevertheless, the results of different studies remain contradictory. A meta-analysis covering 28, 789 subjects from eleven different studies was here carried out in order to investigate the association in detail. The random effects model was used to analyze the pooled odds ratios (ORs) and their corresponding 95% confidence intervals (95% CIs). A significant relationship between the rs2273535 polymorphism and breast tumors was found in an allelic genetic model (OR: 1.076, 95% CI: 1.004-1.153, p=0.040, $P_{heterogeneity}$=0.002). No significant association was detected in a homozygote model (OR: 1.186, 95% CI: 0.990-1.423, P=0.065, $P_{heterogeneity}$=0.002), a heterozygote model (OR: 1.016, 95% CI: 0.959-1.076, p=0.064, $P_{heterogeneity}$=0.000), a dominant genetic model (OR: 1.147, 95% CI: 0.992-1.325, p=0.217, $P_{heterogeneity}$=0.294) and a recessive genetic model (OR: 1.093, 95% CI: 0.878-1.361, p=0.425, $P_{heterogeneity}$=0.707). A significant relationship between the rs2273535 polymorphism in the AURKA gene and breast tumor in Asian group was found in an allelic genetic model (OR: 1.124, 95% CI: 1.003-1.29, p=0.044, $P_{heterogeneity}$=0.034), a homozygote model (OR: 1.229, 95% CI: 1.038-1.455, p=0.016, $P_{heterogeneity}$=0.266) and a recessive genetic model (OR: 1.227, 95% CI: 1.001-1.504, p=0.049, $P_{heterogeneity}$=0.006). A significant association was thus observed between the rs2273535 polymorphism in the AURKA gene and breast cancer risk. Individuals with the rs2273535 polymorphism in the AURKA gene have a higher risk of breast cancer in Asian populations, but not in Caucasians.

• Asian-Australasian Journal of Animal Sciences
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• v.29 no.1
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• pp.36-42
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• 2016

Milk-related traits (milk yield, fat and protein) have been crucial to selection of Holstein. It is essential to find the current selection trends of Holstein. Despite this, uncovering the current trends of selection have been ignored in previous studies. We suggest a new formula to detect the current selection trends based on single nucleotide polymorphisms (SNP). This suggestion is based on the best linear unbiased prediction (BLUP) and the Fisher's fundamental theorem of natural selection both of which are trait-dependent. Fisher's theorem links the additive genetic variance to the selection coefficient. For Holstein milk production traits, we estimated the additive genetic variance using SNP effect from BLUP and selection coefficients based on genetic variance to search highly selective SNPs. Through these processes, we identified significantly selective SNPs. The number of genes containing highly selective SNPs with p-value <0.01 (nearly top 1% SNPs) in all traits and p-value <0.001 (nearly top 0.1%) in any traits was 14. They are phosphodiesterase 4B (PDE4B), serine/threonine kinase 40 (STK40), collagen, type XI, alpha 1 (COL11A1), ephrin-A1 (EFNA1), netrin 4 (NTN4), neuron specific gene family member 1 (NSG1), estrogen receptor 1 (ESR1), neurexin 3 (NRXN3), spectrin, beta, non-erythrocytic 1 (SPTBN1), ADP-ribosylation factor interacting protein 1 (ARFIP1), mutL homolog 1 (MLH1), transmembrane channel-like 7 (TMC7), carboxypeptidase X, member 2 (CPXM2) and ADAM metallopeptidase domain 12 (ADAM12). These genes may be important for future artificial selection trends. Also, we found that the SNP effect predicted from BLUP was the key factor to determine the expected current selection coefficient of SNP. Under Hardy-Weinberg equilibrium of SNP markers in current generation, the selection coefficient is equivalent to $2^*SNP$ effect.