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Azathioprine is a thiopurine which has a narrow therapeutic index and marked hematological and hepatic toxicity. Thiopurine s-methyltransferase is an enzyme involved in the metabolism of thiopurines. Mutations in the gene that encodes the enzyme may augment the risk of adverse events. For that reason, pharmacogenetic determinations prior to the initiation of therapy can provide useful information for the future therapeutic strategy. Nevertheless, its utility in the local environment is not completely established. Forty-five subjects (13 men) who had been prescribed azathioprine were included. The presence of *2, *3A, *3B and *3C mutations were determined by PCR-RFLP, and the relationship between genotype and incidence of adverse events related to the drug was analyzed. Nine carried at least one non-functional allele, one of them with *3A/*3A genotype. Among the eighteen patients who initiated treatment with azathioprine, toxicity was detected in 3 cases: 2 mild events were observed in patients with normal genotype, and the only serious event (bone marrow suppression) occurred in the individual with homozygous mutant genotype. The only homozygous mutant patient developed the most severe of the registered events, in spite of being under treatment with low doses of azathioprine. This is the reason why enzymatic determination could be of utility, even though it does not replace clinical and biochemical follow-up in patients under thiopurine treatment.

Precision medicine aims to predict a patient's disease risk and best therapeutic options by using that individual's genetic sequencing data. The Critical Assessment of Genome Interpretation (CAGI) is a community experiment consisting of genotype–phenotype prediction challenges; participants build models, undergo assessment, and share key findings. For CAGI 4, three challenges involved using exome-sequencing data: Crohn's disease, bipolar disorder, and warfarin dosing. Previous CAGI challenges included prior versions of the Crohn's disease challenge. Here, we discuss the range of techniques used for phenotype prediction as well as the methods used for assessing predictive models. Additionally, we outline some of the difficulties associated with making predictions and evaluating them. The lessons learned from the exome challenges can be applied to both research and clinical efforts to improve phenotype prediction from genotype. In addition, these challenges serve as a vehicle for sharing clinical and research exome data in a secure manner with scientists who have a broad range of expertise, contributing to a collaborative effort to advance our understanding of genotype–phenotype relationships.

Background Major depressive disorder is a high-prevalence disease associated with a heavy burden on both personal well-being and socio-economical welfare, partly as a result of lacking tailored treatment options [1]. Common single nucleotide polymorphisms (SNPs) were estimated to account for 0.42 of the variance in antidepressant response [2], confirming the hypothesis that genetic polymorphisms may be used as effective markers to provide tailored antidepressant treatments. Candidate gene and genome-wide analyses can provide a complementary strategy, since the former can be applied to clarify the role of SNPs with high pre-test probability of association with the trait and the latter is useful to study the joint effects of a number of SNPs in a gene or a set of genes [3]. Aim We applied such a complementary strategy to the study of eight genes that are very strong candidates with previous evidence of pleiotropic effect across psychiatric traits. The genes of interest are involved in the regulation of neurotransmission (CACNA1C, CACNB2, ANK3), neural differentiation, synaptic plasticity, adhesion processes and structural organization (GRM7, TCF4, ITIH3, SYNE1) and glucocorticoid signaling (FKBP5). Methods Three samples with major depressive disorder (total n=671) were genotyped for 44 SNPs in strong candidate genes based on biological function and previous genome-wide association studies (CACNA1C, CACNB2, ANK3, GRM7, TCF4, ITIH3, SYNE1, FKBP5). Phenotypes were response/remission after 4 weeks of treatment and treatment-resistant depression (TRD: non response/non remission to at least two antidepressant treatments). Genome-wide data from STAR*D were used to replicate findings for response/remission (Level 1, n=1409) and TRD (Level 2, n=620). Pathways including the most promising candidate genes for involvement in TRD were investigated in STAR*D Level 2. Top pathway(s) were investigated using machine learning models. Results FKBP5 rs3800373, rs1360780 and rs9470080 showed replicated associations with response, remission or TRD. CACNA1C SNPs showed contradictory direction of association across samples. ANK3 rs1049862 AA genotype showed a replicated association with better outcome. In STAR*D the best pathway associated with TRD included CACNA1C (GO:0006942, permutated p=0.15). Neural networks and gradient boosted machine showed that independent SNPs in this pathway predicted TRD with a mean sensitivity of 0.83 and specificity of 0.56 after 10-fold cross validation repeated 100 times. Conclusions FKBP5 polymorphisms should be considered for inclusion in antidepressant pharmacogenetic tests. CACNA1C is a good candidate and GO:0006942 includes several genes coding for ion channels expressed in the central nervous system and other genes relevant for excitatory mechanisms. CACNB2 and ANK3 showed replicated associations with phenotypes and further investigations could help in clarifying their role. This study may pave the way to the identification of sets of genetic predictors in specific pathways able to predict the risk of TRD. It is reasonable to hypothesize a certain degree of variability in the genetic variants involved in TRD across different patients, but the involved pathways are expected to be more stable. Validated genetic markers of TRD could have a pivotal role in the implementation of targeted antidepressant treatments.

The common polymorphic variant in the 5′ untranslated region of the excision repair cross-complementation group 5 (ERCC5) gene was described to generate an upstream open reading frame that regulates both the basal ERCC5 expression and its ability to be synthesized following DNA damage. This variant was reported to affect response to platinum therapy in a cohort of patients with pediatric ependymoma. The role of this variant was investigated in two cohorts of cancer patients, specifically in non-small-cell lung cancer (NSCLC) patients (N = 137) and in epithelial ovarian carcinoma (EOC) patients (N = 240), treated in first-line with platinum-based compounds. Differently from what reported for pediatric ependymoma, the analysis of the polymorphism in NSCLC patients cohort was not able to detect any difference among patients harboring different genotypes both in progression free survival (HR = 0.93; 95%CI 0.64–1.33; p-value = 0.678) and overall survival (HR = 0.90; 95%CI 0.62–1.33; p-value = 0.625). These data were corroborated in a EOC patients cohort, where similar progression free survival (HR = 0.91; 95% CI 0.67–1.24; p-value = 0.561) and overall survival (HR = 0.98; 95% CI 0.71–1.35; p-value = 0.912) were found for the different genotypes. These data, obtained in appropriately sized populations, indicate that the effect of this ERCC5 polymorphism is likely to be relevant only in specific tumors.

The aim of the study is the identification of genetic factors that influence the long-term response to interferon-β (IFNβ) (4-year follow-up). We performed a genome-wide association study in 337 IFNβ-treated Italian multiple sclerosis patients at the extreme of treatment response, and we meta-analyzed association effects, integrating results with pathway analysis, gene-expression profiling of IFNβ-stimulated peripheral blood mononuclear cells from 20 healthy controls (HC) and expression quantitative locus (eQTL) analyses. From meta-analysis, 43 markers were associated at P

Background: We investigated phosphodiesterase 7B (PDE7B), neuromedin B receptor (NMBR) and epilepsy progressive myoclonus type 2A (EPM2A) genes in schizophrenia (SCZ). To the best of our knowledge, these genes have been poorly investigated in studies of SCZ. Methods: Five hundred and seventy-three SCZ inpatients of Korean ethnicity and 560 healthy controls were genotyped for 2 PDE7B, 3 NMBR and 3 EPM2A polymorphisms. Differences in the allelic and genetic frequencies among healthy subjects and patients were calculated using the χ2 statistics. Repeated-measure ANOVA was used to test possible influences of single-nucleotide polymorphisms on treatment efficacy. In case of positive findings, clinical and demographic variables were added as covariates, in order to investigate possible stratification bias. Results: The rs2717 and rs6926279 within the NMBR gene and rs702304 and rs2235481 within the EPM2A gene were associated with SCZ liability. rs1415744 was also associated with Positive and Negative Symptom Scale negative clinical improvement. The results remained the same after inclusion of the covariates and were partially confirmed in the allelic and haplotype analyses. Conclusion: Our preliminary findings suggest a possible role of NMBR and EPM2A genes in SCZ susceptibility and, for the second one, also in antipsychotic pharmacogenetics. Nonetheless, further research is needed to confirm our findings.