Bovine leukemia virus (BLV) is the causative agent of enzootic bovine leucosis. However, less than 5% of BLV-infected cattle will develop lymphoma, suggesting that, in addition to viral infection, host genetic polymorphisms might play a role in disease susceptibility. Bovine leukocyte antigen (BoLA)-DRB3 is a highly polymorphic gene associated with BLV proviral load (PVL) susceptibility. Due to the fact that PVL is positively associated with disease progression, it is believed that controlling PVL can prevent lymphoma development. Thus, many studies have focused on the relationship between PVL and BoLA-DRB3. Despite this, there is little information regarding the relationship between lymphoma and BoLA-DRB3. Furthermore, whether or not PVL-associated BoLA-DRB3 is linked to lymphoma-associated BoLA-DRB3 has not been clarified. Here, we investigated whether or not lymphoma-associated BoLA-DRB3 is correlated with PVL-associated BoLA-DRB3. We demonstrate that two BoLA-DRB3 alleles were specifically associated with lymphoma resistance (*010:01 and *011:01), but no lymphoma-specific susceptibility alleles were found; furthermore, two other alleles, *002:01 and *012:01, were associated with PVL resistance and susceptibility, respectively. In contrast, lymphoma and PVL shared two resistance-associated (DRB3*014:01:01 and *009:02) BoLA-DRB3 alleles. Interestingly, we found that PVL associated alleles, but not lymphoma associated alleles, are related with the anti-BLV gp51 antibody production level in cows. Overall, our study is the first to demonstrate that the BoLA-DRB3 polymorphism confers differential susceptibility to BLV-induced lymphoma and PVL.

The nicotine metabolite ratio (NMR; 3‐hydroxycotinine/cotinine) is an index of CYP2A6 activity. CYP2A6 is responsible for nicotine's metabolic inactivation and variation in the NMR/CYP2A6 is associated with several smoking behaviors. Our aim was to integrate established alleles and novel genome‐wide association studies (GWAS) signals to create a weighted genetic risk score (wGRS) for the CYP2A6 gene for European‐ancestry populations. The wGRS was compared with a previous CYP2A6 gene scoring approach designed for an alternative phenotype (C2/N2; cotinine‐d2/(nicotine‐d2 + cotinine‐d2)). CYP2A6 genotypes and the NMR were assessed in European‐ancestry participants. The wGRS training set included N = 933 smokers recruited to the Pharmacogenetics of Nicotine Addiction and Treatment clinical trial [NCT01314001]. The replication cohort included N = 196 smokers recruited to the Quit 2 Live clinical trial [NCT01836276]. Comparisons between the two CYP2A6 phenotypes and with fractional clearance were made in a laboratory‐based pharmacokinetic study (N = 92 participants). In both the training and replication sets, the wGRS, which included seven CYP2A6 variants, explained 33.8% (P < 0.001) of the variance in NMR, providing improved predictive power to the NMR phenotype when compared with other CYP2A6 gene scoring approaches. NMR and C2/N2 were strongly correlated to nicotine clearance (ρ = 0.70 and ρ = 0.79, respectively; P < 0.001), and to one another (ρ = 0.82; P < 0.001); however reduced function genotypes occurred in slow NMR but throughout C2/N2. The wGRS was able to predict smoking quantity and nicotine intake, to discriminate between NMR slow and normal metabolizers (AUC = 0.79; P < 0.001), and to replicate previous NMR‐stratified cessation outcomes showing unique treatment outcomes between metabolizer groups.

Sunitinib is a tyrosine kinase inhibitor and used as the first-line treatment for advanced renal cell carcinoma (RCC). Nevertheless, inter-individual variability of drug’s toxicity was often observed among patients who received sunitinib treatment. This study is to investigate the association of a functional germline variant on ABCG2 that affects the pharmacokinetics of sunitinib with sunitinib-induced toxicity of RCC patients in the Japanese population. A total of 219 RCC patients were recruited to this pharmacogenetic study. ABCG2 421C>A (Q141K) was genotyped by using PCR-Invader assay. The associations of both clinical and genetic variables were evaluated with logistic regression analysis and subsequently receiver operating characteristic (ROC) curve was plotted. About 43% (92/216) of RCC patients that received sunitinib treatment developed severe grade 3 or grade 4 thrombocytopenia according to the National Cancer Institute-Common Terminology Criteria for Adverse Events version 3.0, the most common sunitinib-induced adverse reaction in this study. In the univariate analysis, both age (P = 7.77x10-3, odds ratio (OR) = 1.04, 95%CI = 1.01–1.07) and ABCG2 421C>A (P = 1.87x10-2, OR = 1.71, 95%CI = 1.09–2.68) showed association with sunitinib-induced severe thrombocytopenia. Multivariate analysis indicated that the variant ABCG2 421C>A is suggestively associated with severe thrombocytopenia (P = 8.41x10-3, OR = 1.86, 95% CI = 1.17–2.94) after adjustment of age as a confounding factor. The area under curve (AUC) of the risk prediction model that utilized age and ABCG2 421C>A was 0.648 with sensitivity of 0.859 and specificity of 0.415. Severe thrombocytopenia is the most common adverse reaction of sunitinib treatment in Japanese RCC patients. ABCG2 421C>A could explain part of the inter-individual variability of sunitinib-induced severe thrombocytopenia.

The Nicotine Metabolite Ratio (NMR; 3‐hydroxycotinine/cotinine), a highly heritable index of nicotine metabolic inactivation by the CYP2A6 enzyme, is associated with numerous smoking behaviors and diseases, as well as unique cessation outcomes. However, the NMR cannot be measured in nonsmokers, former smokers, or intermittent smokers, for example, in evaluating tobacco‐related disease risk. Traditional pharmacogenetic groupings based on CYP2A6 * alleles capture a modest portion of NMR variation. We previously created a CYP2A6 weighted genetic risk score (wGRS) for European (EUR)‐ancestry populations by incorporating independent signals from genome‐wide association studies to capture a larger proportion of NMR variation. However, CYP2A6 genetic architecture is unique to ancestral populations. In this study, we developed and replicated an African‐ancestry (AFR) wGRS, which captured 30–35% of the variation in NMR. We demonstrated model robustness against known environmental sources of NMR variation. Furthermore, despite the vast diversity within AFR populations, we showed that the AFR wGRS was consistent between different US geographical regions and unaltered by fine AFR population substructure. The AFR and EUR wGRSs can distinguish slow from normal metabolizers in their respective populations, and were able to reflect unique smoking cessation pharmacotherapy outcomes previously observed for the NMR. Additionally, we evaluated the utility of a cross‐ancestry wGRS, and the capacity of EUR, AFR, and cross‐ancestry wGRSs to predict the NMR within stratified or admixed AFR‐EUR populations. Overall, our findings establish the clinical benefit of applying ancestry‐specific wGRSs, demonstrating superiority of the AFR wGRS in AFRs.

This is the first meta-analysis of NAT2 and the risk of ATDILI at the genotypic level. The result demonstrated that NAT2 ultra-slow acetylator genotypes will have the most effect on the increased risk of ATDILI.