Migraine is the most disabling and expensive chronic disorders, the etiology of which is still not fully known. The neuronal systems, (glutammatergic, dopaminergic, serotoninergic and GABA-ergic) whose functionality is partly attributable to genetically determined factors, has been suggested to play an important role. The treatment of acute attacks and the prophylactic management of chronic forms include the use of different category of drugs, and it is demonstrated that not each subject has the same clinical answer to them. The reason of this is to be searched in different functional capacity and quantity of phase I enzymes (such as different isoforms of CYP P450), phase II enzymes (such as UDP-glucuronosyltransferases), receptors (such as OPRM1 for opioids) and transporters (such as ABCB1) involved in the metabolic destiny of each drug, all of these dictated by DNA and RNA variations. The general picture is further exacerbated by the need for polytherapies, often also to treat comorbidities, which may interfere with the pharmacological action of anti-migraine drugs. Personalized medicine has the objective of setting the optimal therapies in the light of the functional biochemical asset and of the comorbidities of the individual patient, in order to obtain the best clinical response. Novel therapeutic perspectives in migraine includes biotechnological drugs directed against molecules (such as CGRP and its receptor) that cause vasodilatation at the peripheral level of the meningeal blood vessels and reflex stimulation of the parasympathetic system. Drug-drug interactions and the possible competitive metabolic destiny should be studied by the application of pharmacogenomics in large scale. Drug-drug interactions and their possible competitive metabolic destiny should be studied by the application of pharmacogenomics in large scale.

Background: Oftentimes, persistent post traumatic headache (PPTH) and migraine are phenotypically similar and the only clinical feature that differentiate them is the presence of a mild or moderate traumatic brain injury (mTBI). The aim of this study is to describe the differences in brain area and in biochemical cascade after concussion and to define the efficacy and safety of treatments in use. Methods: Sources were chosen in according to the International Classification of Headache Disorder (ICHD) criteria. Results: The articles demonstrated a significant difference between PPTH and migraine regarding static functional connectivity (sFC) and dynamic functional connectivity (dFC) in brain structure that could be used for exploring the pathophysiological mechanisms in PPTH. Many studies described a cascade of neuro-metabolic changes that occur after traumatic brain injury. These variations are associated to the mechanism occurring when developing a PPTH. Conclusions: The state of art of this important topic show how although the mechanisms underlying the development of the two different diseases are different, the treatment of common migraine is efficacious in patients that have developed a post traumatic form.

Multiple Chemical Sensitivity (MCS) is a chronic and/or recurrent condition with somatic, cognitive, and affective symptoms following a contact with chemical agents whose concentrations do not correlate with toxicity in the general population. Its prevalence is not well defined; it mainly affects women between 40 and 50 years, without variations in ethnicity, education and economic status. We aimed to assess the core symptoms of this illness in a sample of Italian patients. Two physicians investigated different symptoms with a checklist compilation in 129 patients with MCS (117 women). We conducted a categorical Principal Component Analysis (CATPCA) with Varimax rotation on the checklist dataset. A typical triad was documented: hyperosmia, asthenia, and dyspnoea were the most common symptoms. Patients also frequently showed cough and headache. The CATPCA showed seven main factors: 1, neurocognitive symptoms; 2, physical (objective) symptoms; 3, gastrointestinal symptoms; 4, dermatological symptoms; 5, anxiety-depressive symptoms; 6, respiratory symptoms; 7, hyperosmia and asthenia. Patients showed higher mean prevalence of factors 7 (89.9%), 6 (71.7%), and 1 (62.13%). In conclusion, MCS patients frequently manifest hyperosmia, asthenia, and dyspnoea, which are often concomitant with other respiratory and neurocognitive symptoms. Considering the clinical association that is often made with anxiety, more studies are necessary on the psychosomatic aspects of this syndrome. Further analytical epidemiological studies are needed to support the formulation of aetiological hypotheses of MCS.

Patients affected by mental disorders smoke more than the general population. The reasons behind this habit are genetic, environmental, etc. This study aims to investigate the correlations between some polymorphisms and the smoking habits and nicotine dependence in patients with psychiatric disorders. We recruited 88 patients with treatment-resistant mental disorders, including 35 with major depressive disorder, 43 with bipolar spectrum disorder, and 10 with schizophrenia spectrum disorder. We carried out a clinical and psychometric assessment on current smoking habits, years of smoking, number of daily cigarettes, and level of nicotine addiction. The patients performed a peripheral blood sample for DNA analyses of different polymorphisms. We searched for correlations between the measures of nicotine addiction and analysed genotypes. The expression of the T allele of the DRD2 rs1800497 and DRD3 rs6280 polymorphisms significantly correlated with a lower level of nicotine dependence and lower use of cigarettes. We did not find significant correlations between nicotine dependence and OPRM1 rs1799971, COMT rs4680 and rs4633 polymorphisms, CYP2A6 rs1801272 and rs28399433, or 5-HTTLPR genotype. Concluding, DRD2 rs1800497 and DRD3 rs6280 polymorphisms are involved in nicotine dependence and cigarette smoking habits in patients with treatment-resistant mental disorders

Drug–drug interactions (DDIs) can affect both treatment efficacy and toxicity. We used Drug-PIN^® (Personalized Interactions Network) software in colorectal cancer (CRC) patients to evaluate drug–drug–gene interactions (DDGIs), defined as the combination of DDIs and individual genetic polymorphisms. Inclusion criteria were: (i) stage II-IV CRC; (ii) ECOG PS (Performance status sec. Eastern coperative oncology group) ≤2; (iii) ≥5 concomitant drugs; and (iv) adequate renal, hepatic, and bone marrow function. The Drug-PIN^® system analyzes interactions between active and/or pro-drug forms by integrating biochemical, demographic, and genomic data from 110 SNPs. We selected DDI, DrugPin1, and DrugPin2 scores, resulting from concomitant medication interactions, concomitant medications, and SNP profiles, and DrugPin1 added to chemotherapy drugs, respectively. Thirty-four patients, taking a median of seven concomitant medications, were included. The median DrugPin1 and DrugPin2 scores were 42.6 and 77.7, respectively. In 13 patients, the DrugPin2 score was two-fold higher than the DrugPin1 score, with 7 (54%) of these patients experiencing severe toxicity that required hospitalization. On chi-squared testing for any toxicity, a doubled DrugPin2 score (p = 0.001) was significantly related to G3–G4 toxicity. Drug-PIN^® software may prevent severe adverse events, decrease hospitalizations, and improve survival in cancer patients.

Treatment-resistant depression (TRD) reduces affected patients’ quality of life and leads to important social health care costs. Pharmacogenomics-guided treatment (PGT) may be effective in the cure of TRD. The main aim of this study was to evaluate the clinical changes after PGT in patients with TRD (two or more recent failed psychopharmacological trials) affected by bipolar disorder (BD) or major depressive disorder (MDD) compared to a control group with treatment as usual (TAU). We based the PGT on assessing different gene polymorphisms involved in the pharmacodynamics and pharmacokinetics of drugs. We analyzed, with a repeated-measure ANOVA, the changes between the baseline and a 6 month follow-up of the efficacy index assessed through the Clinical Global Impression (CGI) scale, and depressive symptoms through the Hamilton Depression Rating Scale (HDRS). The PGT sample included 53 patients (26 BD and 27 MDD), and the TAU group included 52 patients (31 BD and 21 MDD). We found a significant within-subject effect of treatment time on symptoms and efficacy index for the whole sample, with significant improvements in the efficacy index (F = 8.544; partial η² = 0.077, p < 0.004) and clinical global impression of severity of illness (F = 6.818; partial η² = 0.062, p < 0.01) in the PGT vs. the TAU group. We also found a significantly better follow-up response (χ² = 5.479; p = 0.019) and remission (χ² = 10.351; p = 0.001) rates in the PGT vs. the TAU group. PGT may be an important option for the long-term treatment of patients with TRD affected by mood disorders, providing information that can better define drug treatment strategies and increase therapeutic improvement.