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Background:The catechol-O-methyltransferase (COMT) enzyme plays a crucial role in dopamine degradation, and the COMT Val158Met polymorphism (rs4680) is associated with significant differences in enzymatic activity and consequently dopamine concentrations in the prefrontal cortex. Multiple studies have analyzed the COMT Val158Met variant in relation to antipsychotic response. Here, we conducted a meta-analysis examining the relationship between COMT Val158Met and antipsychotic response.Methods:Searches using PubMed, Web of Science, and PsycInfo databases (03/01/2015) yielded 23 studies investigating COMT Val158Met variation and antipsychotic response in schizophrenia and schizo-affective disorder. Responders/nonresponders were defined using each study’s original criteria. If no binary response definition was used, authors were asked to define response according to at least 30% Positive and Negative Syndrome Scale score reduction (or equivalent in other scales). Analysis was conducted under a fixed-effects model.Results:Ten studies met inclusion criteria for the meta-analysis. Five additional antipsychotic-treated samples were analyzed for Val158Met and response and included in the meta-analysis (ntotal=1416). Met/Met individuals were significantly more likely to respond than Val-carriers (P=.039, ORMet/Met=1.37, 95% CI: 1.02–1.85). Met/Met patients also experienced significantly greater improvement in positive symptoms relative to Val-carriers (P=.030, SMD=0.24, 95% CI: 0.024–0.46). Posthoc analyses on patients treated with atypical antipsychotics (n=1207) showed that Met/Met patients were significantly more likely to respond relative to Val-carriers (P=.0098, ORMet/Met=1.54, 95% CI: 1.11–2.14), while no difference was observed for typical-antipsychotic-treated patients (n=155) (P=.65).Conclusions:Our findings suggest that the COMT Val158Met polymorphism is associated with response to antipsychotics in schizophrenia and schizo-affective disorder patients. This effect may be more pronounced for atypical antipsychotics.

BackgroundRadiomic features calculated from routine medical images show great potential for personalized medicine in cancer. Patients with systemic sclerosis (SSc), a rare, multi-organ autoimmune disorder, have a similarly poor prognosis due to interstitial lung disease (ILD).ObjectivesTo explore computed tomography (CT)-based high-dimensional image analysis (radiomics) for disease characterisation, risk stratification, and relaying information on lung pathophysiology in SSc-ILD.MethodsWe investigated two independent, prospectively followed SSc-ILD cohorts (Zurich, derivation cohort, n=90; Oslo, validation cohort, n=66). For every subject, we defined 1′355 robust radiomic features from standard-of-care CT images. We performed unsupervised clustering to identify and characterize imaging-based patient clusters. A clinically applicable prognostic quantitative radiomic risk score (qRISSc) for progression-free survival was derived from radiomic profiles using supervised analysis. The biological basis of qRISSc was assessed in a cross-species approach by correlation with lung proteomics, histological and gene expression data derived from mice with bleomycin-induced lung fibrosis.ResultsRadiomic profiling identified two clinically and prognostically distinct SSc-ILD patient clusters. To evaluate the clinical applicability, we derived and externally validated a binary, quantitative radiomic risk score composed of 26 features, qRISSc, that accurately predicted progression-free survival and significantly improved upon clinical risk stratification parameters in multivariable Cox regression analyses in the pooled cohorts. A high qRISSc score, which identifies patients at risk for progression, was reverse translatable from human to experimental ILD and correlated with fibrotic pathway activation.ConclusionsRadiomics-based risk stratification using routine CT images provides complementary phenotypic, clinical and prognostic information significantly impacting clinical decision-making in SSc-ILD.

NET rs2242446/T-182C may serve as a biomarker to predict the likelihood of remission with venlafaxine in older adults with major depression. These findings may help to optimize antidepressant outcomes in older adults.

Genetic variations in clock-related genes were hypothesized to be involved to in the susceptibility of mood disorders MD (both unipolar (UPD) and bipolar (BPD) disorders). In our work we investigated role of gene variants form four core period proteins: CLOCK, ARNTL, TIM and PER3. The total sample comprised from 744 mood disorders inpatients (UPD = 229, BPD = 515) and 635 healthy voluntary controls. The 42 SNPs from four genes of interest were genotyped. We used single polymorphisms, haplotypes, SNPs interactions and prediction analysis using classical statistical and machine learning methods. We observed association between two polymorphisms of CLOCK (rs1801260 and rs11932595) with BPDII and two polymorphisms of TIM (rs2291739, rs11171856) with UPD. We also detected ARNTL haplotype variant (rs1160996C/rs11022779G/rs1122780T) to be associated with increased risk of MD, BPD (both types). We established significant epistatic interaction between PER3 (rs2172563) and ARNTL (rs4146388 and rs7107287) in case of BPD. Additionally relation between PER3 (rs2172563) and CLOCK (rs1268271 and rs3805148) appeared in case of UPD. Classification and Regression Trees (C and RT) showed significant predictive value for 10 polymorphisms in all analyzed genes. However we failed to obtain model with sufficient predictive power. During analyses of sleep disturbances sample, we found carriers of homozygote variants (ARNTL: rs11022778 TT, rs1562438 TT, rs1982350 AA and PER3: rs836755 CC) showing more frequent falling asleep difficulties when compare to other genotypes carriers. Our study suggested a putative role of the CLOCK, TIM, ARNTL and PER3 and polymorphisms in MD susceptibility. In our analyses we showed association of specific gene variants with particular types of MD. We also confirmed necessity of performing separate analyzes for BPD and UPD patients. Comprehensive statistical approach is required even with individual symptoms analyses.

Our finding provides evidence for rs2514218 association with antipsychotic response, but further replication is required before firm conclusions can be drawn.

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