Dopamine genes and migraine

Migraine is a common chronic disorder with an etiology still mostly unknown. Several neurotransmitters such as dopamine and serotonin are considered to be involved in the pathogenesis of the disease and the study of their systems is crucial in the understanding of migraine. Dopaminergic receptors are variously represented in human CNS and periphery. The hypothesis that a hypersensitivity of the dopaminergic system may have a role in migraine is based on clinical and genetic data. Genetic data are represented by association studies using dopaminergic genes as candidate genes which show that the D2 receptor gene appears to be involved in the pathogenesis of migraine

High leptin levels are associated with migraine with aura.

Background Migraine is a prevalent disorder characterised by recurrent headache attacks preceded or accompanied by aura in a subgroup of patients. Migraine often occurs together with major depressive disorder (MDD). Alterations of adipokine levels have been reported both in migraine and in MDD. In this cross-sectional study, we aimed to assess the associations between serum leptin and adiponectin levels and migraine or migraine subtypes. Analyses were adjusted for a lifetime history of MDD in order to investigate the association between adipokines and migraine under consideration of depression status. Methods We included 3025 participants from the CoLaus/PsyCoLaus study. The impact of leptin and adiponectin levels on a diagnosis of migraine was analysed by binary regression analyses, adjusting for variables known to influence adipokine levels. Subgroup analyses were conducted based on the presence of aura. Results Crude leptin levels were significantly higher in subjects with migraine than controls (Mann-Whitney U = 515,102, p = 6 × 10-7). When performing adjusted analyses, leptin levels were found to be significantly higher in subjects with migraine (odds ratio = 1.22, p = 0.024) and migraine with aura (odds ratio = 1.34, p = 0.004). Conclusion High leptin levels might play a role in the pathogenesis of migraine and migraine with aura

Cost–utility analysis of pharmacogenetic testing based on CYP2C19 or CYP2D6 in major depressive disorder: assessing the drivers of different cost-effectiveness levels from an Italian societal perspective

Background and Objectives Major depressive disorder (MDD) is a common and severe psychiatric disorder that has enor- mous economical and societal costs. As pharmacogenetics is one of the key tools of precision psychiatry, we analyze the cost–utility of test screening of CYP2C19 and CYP2D6 for patients suffering from major depressive disorder (MDD) and try to understand the main drivers that influence the cost–utility. Methods We developed two pharmacoeconomic nonhomogeneous Markov models to test the cost–utility, from an Ital- ian societal perspective, of pharmacogenetic testing genetic to characterize the metabolizing profiles of cytochrome P450 (CYP) 2C19 and CYP2D6 in a hypothetical case study of patients suffering from major depressive disorder (MDD). The model considers different scenarios of adjustment of antidepressant treatment according to the patient’s metabolizing profile or treatment over a period of 18 weeks. The uncertainty of model parameters is tested through both a probabilistic sensitivity analysis and a one-way deterministic sensitivity analysis, and these results are used in a post-hoc analysis to understand the main drivers of three alternative cost-effectiveness levels (“poor,” “standard,” and “high”). These drivers are first evaluated from an exploratory multidimensional perspective and next from a predictive perspective as the probability that a patient belongs to a specific cost-effectiveness level is estimated on the basis of a restricted set of parameters used in the original pharmacoeconomic model. Results The models for CYP2C19 and CYP2D6 indicate that screening has an incremental cost-effectiveness ratio of 60,000€ and 47,000€ per quality-adjusted life year (QALY), respectively. The probabilistic sensitivity analysis shows that the treat- ments are cost-effective for a 75,000€ willingness to pay (WTP) threshold in 58% and 63% of the Monte Carlo replications, respectively. The post-hoc analysis highlights the factors that allow us to clearly discriminates poor cost-effectiveness from high cost-effectiveness scenarios and demonstrates that it is possible to predict with reasonable accuracy the cost-effectiveness of a genetic test and the associated therapeutic pattern. Conclusions Our findings suggest that screenings for both CYP2C19 and CYP2D6 enzymes for patients with MDD are cost-effective for a WTP threshold of 75,000€ per QALY, and provide relevant suggestions about the most important aspects to be further explored in clinical studies aimed at addressing the cost-effectiveness of genetic testing for patients diagnosed with MDD

Sex differences in shared genetic determinants between severe mental disorders and metabolic traits

High rates of metabolic risk factors contribute to premature mortality in patients with severe mental disorders, but the molecular underpinnings of this association are largely unknown. We performed the first analysis on shared genetic factors between severe mental disorders and metabolic traits considering the effect of sex. We applied an integrated analytical pipeline on the largest sex-stratified genome-wide association datasets available for bipolar disorder (BD), major depressive disorder (MDD), schizophrenia (SZ), and for body mass index (BMI) and waist-to-hip ratio (WHR) (all including participants of European origin). We observed extensive genetic overlap between all severe mental disorders and variants associated with BMI in women or men and identified several genetic loci shared between BD, or SZ and BMI in women (24 and 91, respectively) or men (13 and 208, respectively), with mixed directions of effect. A large part of the identified genetic variants showed sex differences in terms of location, genes modulated in adipose tissue and/or brain regions, and druggable targets. By providing a complete picture of disorder specific and cross-disorder shared genetic determinants, our results highlight potential sex differences in the genetic liability to metabolic comorbidities in patients with severe mental disorders

Novel integrative genomic tool for interrogating lithium response in bipolar disorder

We developed a novel integrative genomic tool called GRANITE (Genetic Regulatory Analysis of Networks Investigational Tool Environment) that can effectively analyze large complex data sets to generate interactive networks. GRANITE is an open-source tool and invaluable resource for a variety of genomic fields. Although our analysis is confined to static expression data, GRANITE has the capability of evaluating time-course data and generating interactive networks that may shed light on acute versus chronic treatment, as well as evaluating dose response and providing insight into mechanisms that underlie therapeutic versus sub-therapeutic doses or toxic doses. As a proof-of-concept study, we investigated lithium (Li) response in bipolar disorder (BD). BD is a severe mood disorder marked by cycles of mania and depression. Li is one of the most commonly prescribed and decidedly effective treatments for many patients (responders), although its mode of action is not yet fully understood, nor is it effective in every patient (non-responders). In an in vitro study, we compared vehicle versus chronic Li treatment in patient-derived lymphoblastoid cells (LCLs) (derived from either responders or non-responders) using both microRNA (miRNA) and messenger RNA gene expression profiling. We present both Li responder and non-responder network visualizations created by our GRANITE analysis in BD. We identified by network visualization that the Let-7 family is consistently downregulated by Li in both groups where this miRNA family has been implicated in neurodegeneration, cell survival and synaptic development. We discuss the potential of this analysis for investigating treatment response and even providing clinicians with a tool for predicting treatment response in their patients, as well as for providing the industry with a tool for identifying network nodes as targets for novel drug discovery

Exemplar scoring identifies genetically separable phenotypes of lithium responsive bipolar disorder

Predicting lithium response (LiR) in bipolar disorder (BD) may inform treatment planning, but phenotypic heterogeneity complicates discovery of genomic markers. We hypothesized that patients with "exemplary phenotypes"-those whose clinical features are reliably associated with LiR and non-response (LiNR)-are more genetically separable than those with less exemplary phenotypes. Using clinical data collected from people with BD (n = 1266 across 7 centers; 34.7% responders), we computed a "clinical exemplar score," which measures the degree to which a subject's clinical phenotype is reliably predictive of LiR/LiNR. For patients whose genotypes were available (n = 321), we evaluated whether a subgroup of responders/non-responders with the top 25% of clinical exemplar scores (the "best clinical exemplars") were more accurately classified based on genetic data, compared to a subgroup with the lowest 25% of clinical exemplar scores (the "poor clinical exemplars"). On average, the best clinical exemplars of LiR had a later illness onset, completely episodic clinical course, absence of rapid cycling and psychosis, and few psychiatric comorbidities. The best clinical exemplars of LiR and LiNR were genetically separable with an area under the receiver operating characteristic curve of 0.88 (IQR [0.83, 0.98]), compared to 0.66 [0.61, 0.80] (p = 0.0032) among poor clinical exemplars. Variants in the Alzheimer's amyloid-secretase pathway, along with G-protein-coupled receptor, muscarinic acetylcholine, and histamine H1R signaling pathways were informative predictors. This study must be replicated on larger samples and extended to predict response to other mood stabilizers

Acute treatment of migraine. Breaking the paradigm of monotherapy

BACKGROUND: Migraine is a highly prevalent disorder. The disability provoked by its attacks results in suffering as well as considerable economic and social losses. The objective of migraine acute treatment is to restore the patient to normal function as quickly and consistently as possible. There are numerous drugs available for this purpose and despite recent advances in the understanding of the mechanisms and different biological systems involved in migraine attacks, with the development of specific 5-HT agonists known as triptans, current options for acute migraine still stand below the ideal. DISCUSSION: Monotherapeutic approaches are the rule but up to one third of all patients discontinue their medications due to lack of efficacy, headache recurrence, cost and/or side effects. In addition, a rationale has been suggested for the development of polytherapeutic approaches, simultaneously aiming at some of the biological systems involved. This paper reviews the fundamentals for this changing approach as well as the evidence of its better efficacy. CONCLUSION: As a conclusion, most of the patients with a past history of not responding (no pain-free at 2 hours and/or no sustained pain-free at 24 hours) in at least 5 previous attacks should undergo a combination therapy suiting to their individual profile, which must include analgesics or non-steroidal anti-inflammatory agents plus a triptan or a gastro kinetic drug. The three-drug regimen may also be considered. In addition, changing the right moment to take it and the choice for formulations other than oral has also to be determined individually and clearly posted to the patient

Correction: A european spectrum of pharmacogenomic biomarkers: Implications for clinical pharmacogenomics (PLoS ONE (2016) 11:9 (e0162866) DOI: 10.1371/journal.pone.0162866)

The thirty-Third author's name is spelled incorrectly. The correct name is: Jadranka Sertić

Combining schizophrenia and depression polygenic risk scores improves the genetic prediction of lithium response in bipolar disorder patients

Lithium is the gold standard therapy for Bipolar Disorder (BD) but its effectiveness differs widely between individuals. The molecular mechanisms underlying treatment response heterogeneity are not well understood, and personalized treatment in BD remains elusive. Genetic analyses of the lithium treatment response phenotype may generate novel molecular insights into lithium's therapeutic mechanisms and lead to testable hypotheses to improve BD management and outcomes. We used fixed effect meta-analysis techniques to develop meta-analytic polygenic risk scores (MET-PRS) from combinations of highly correlated psychiatric traits, namely schizophrenia (SCZ), major depression (MD) and bipolar disorder (BD). We compared the effects of cross-disorder MET-PRS and single genetic trait PRS on lithium response. For the PRS analyses, we included clinical data on lithium treatment response and genetic information for n = 2283 BD cases from the International Consortium on Lithium Genetics (ConLi+Gen; www.ConLiGen.org). Higher SCZ and MD PRSs were associated with poorer lithium treatment response whereas BD-PRS had no association with treatment outcome. The combined MET2-PRS comprising of SCZ and MD variants (MET2-PRS) and a model using SCZ and MD-PRS sequentially improved response prediction, compared to single-disorder PRS or to a combined score using all three traits (MET3-PRS). Patients in the highest decile for MET2-PRS loading had 2.5 times higher odds of being classified as poor responders than patients with the lowest decile MET2-PRS scores. An exploratory functional pathway analysis of top MET2-PRS variants was conducted. Findings may inform the development of future testing strategies for personalized lithium prescribing in BD

HLA-DRB1 and HLA-DQB1 genetic diversity modulates response to lithium in bipolar affective disorders

Bipolar afective disorder (BD) is a severe psychiatric illness, for which lithium (Li) is the gold standard for acute and maintenance therapies. The therapeutic response to Li in BD is heterogeneous and reliable biomarkers allowing patients stratifcation are still needed. A GWAS performed by the International Consortium on Lithium Genetics (ConLiGen) has recently identifed genetic markers associated with treatment responses to Li in the human leukocyte antigens (HLA) region. To better understand the molecular mechanisms underlying this association, we have genetically imputed the classical alleles of the HLA region in the European patients of the ConLiGen cohort. We found our best signal for amino-acid variants belonging to the HLA-DRB1*11:01 classical allele, associated with a better response to Li (p < 1 × ­10−3; FDR< 0.09 in the recessive model). Alanine or Leucine at position 74 of the HLA-DRB1 heavy chain was associated with a good response while Arginine or Glutamic acid with a poor response. As these variants have been implicated in common infammatory/autoimmune processes, our fndings strongly suggest that HLA-mediated low infammatory background may contribute to the efcient response to Li in BD patients, while an infammatory status overriding Li anti-infammatory properties would favor a weak response