Pharmacogenetics and schizophrenia

COMT and Neuregulin 1 Markers for Personalized Treatment of Schizophrenia Spectrum Disorders Treated with Risperidone Monotherapy

Pharmacogenetic markers are current targets for the personalized treatment of psychosis. Limited data exist on COMT and NRG1 polymorphisms in relation to risperidone treatment. This study focuses on the impact of COMT rs4680 and NRG1 (rs35753505, rs3924999) polymorphisms on risperidone treatment in schizophrenia spectrum disorders (SSDs). This study included 103 subjects with SSD treated with risperidone monotherapy. COMT rs4680, NRG1 rs35753505, and rs3924999 were analyzed by RT-PCR. Participants were evaluated via the Positive and Negative Syndrome Scale (PANSS) after six weeks. Socio-demographic and clinical characteristics were collected. COMT rs4680 genotypes significantly differed in PANSS N scores at admission: AG>AA genotypes (p = 0.03). After six weeks of risperidone, PANSS G improvement was AA>GG (p = 0.05). The PANSS total score was as follows: AA>AG (p = 0.04), AA>GG (p = 0.02). NRG1 rs35753504 genotypes significantly differed across educational levels, with CC>CT (p = 0.02), and regarding the number of episodes, TT>CC, CT>CC (p = 0.01). The PANSS total score after six weeks of treatment showed a better improvement for TT Collapse

Key Words

• COMT
• neuregulin 1
• risperidone monotherapy
• schizophrenia spectrum disorders

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MESH Headings

• Humans
• Neuregulin-1/genetics
• Catechol O-Methyltransferase/genetics
• Risperidone/therapeutic use
• Schizophrenia/drug therapy
• Schizophrenia/genetics
• Male
• Female
• Adult
• Polymorphism, Single Nucleotide
• Antipsychotic Agents/therapeutic use
• Middle Aged
• Precision Medicine/methods
• Genotype

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Affiliation(s)

Mariana Bondrescu Department of Neurosciences-Psychiatry, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania; (M.B.); (I.P.) Timis County Emergency Clinical Hospital “Pius Brinzeu”, Liviu Rebreanu 156, 300723 Timisoara, Romania; (V.N.); (D.V.M.); (A.E.G.) Doctoral School, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania
Liana Dehelean Department of Neurosciences-Psychiatry, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania; (M.B.); (I.P.) Timis County Emergency Clinical Hospital “Pius Brinzeu”, Liviu Rebreanu 156, 300723 Timisoara, Romania; (V.N.); (D.V.M.); (A.E.G.)
Simona Sorina Farcas Discipline of Medical Genetics, Department of Microscopic Morphology, Center of Genomic Medicine “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania; (S.S.F.); (N.I.A.)
Ion Papava Department of Neurosciences-Psychiatry, “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania; (M.B.); (I.P.) Timis County Emergency Clinical Hospital “Pius Brinzeu”, Liviu Rebreanu 156, 300723 Timisoara, Romania; (V.N.); (D.V.M.); (A.E.G.)
Vlad Nicoras Timis County Emergency Clinical Hospital “Pius Brinzeu”, Liviu Rebreanu 156, 300723 Timisoara, Romania; (V.N.); (D.V.M.); (A.E.G.)
Dana Violeta Mager Timis County Emergency Clinical Hospital “Pius Brinzeu”, Liviu Rebreanu 156, 300723 Timisoara, Romania; (V.N.); (D.V.M.); (A.E.G.)
Anca Eliza Grecescu Timis County Emergency Clinical Hospital “Pius Brinzeu”, Liviu Rebreanu 156, 300723 Timisoara, Romania; (V.N.); (D.V.M.); (A.E.G.)
Petre Adrian Podaru Faculty of Mathematics and Informatics, West University of Timisoara, Vasile Parvan 4, 300223 Timisoara, Romania;
Nicoleta Ioana Andreescu Discipline of Medical Genetics, Department of Microscopic Morphology, Center of Genomic Medicine “Victor Babes” University of Medicine and Pharmacy, Eftimie Murgu Square 2, 300041 Timisoara, Romania; (S.S.F.); (N.I.A.)

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Metabolomics-based understanding of the olanzapine-induced weight gain in female first-episode drug-naïve patients with schizophrenia

Previous studies have demonstrated that patients with schizophrenia (SZ) have greater rate of metabolic disorder as compared with the control population, which likely be the consequence of use of atypical antipsychotics. Olanzapine is a widely used antipsychotic, which increases the weight of SZ patients. However, the underlying mechanism remains poorly understood. Here we report the metabolomics-based understanding of the weight gain induced by olanzapine. 57 first-episode drug-naïve patients (FEDN) were recruited, of whom 27 patients completed a 4-week clinical trial. We then profiled the metabolomes of their plasma with the LC-MS-based nontargeted metabolomics approach at the baseline and after olanzapine monotherapy for 4 weeks. We observed that the plasma of the olanzapine-treated patient had significantly higher lysophosphatidylcholine (LysoPC), lysophosphatidylethanolamine (LysoPE) and lower carnitine as compared with that of the baseline plasma samples. Moreover, regression analyses indicated that the change of LysoPC(14:0) level was an independent contributor to the olanzapine-induced weight gain. Our study suggests that the metabolomics-based approach may facilitate the identification of biomarkers associated with the metabolic disorder causing by antipsychotic in schizophrenia patients.

C677T Polymorphism in the MTHFR Gene Is Associated With Risperidone-Induced Weight Gain in Schizophrenia

OBJECTIVE

To explore the association of methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism with risperidone-induced weight gain.

METHODS

We analyzed the association between MTHFR C677T polymorphism and risperidone-induced weight gain in 356 schizophrenia patients. The patients were treated with risperidone for 8 weeks. The height and body weight of the patients were measured before and 8 weeks after risperidone treatment. Blood DNA was genotyped for MTHFR C677T polymorphisms.

RESULTS

We found a significant association between MTHFR C677T polymorphism and body mass index (BMI) change after 8-week risperidone treatment. The BMI of carriers with different genotypes of MTHFR gene increased over 2-8 weeks. After 8 weeks of risperidone treatment, BMI added value (kg/m²) of CC or CT genotype carriers was significantly higher than that of TT genotype carriers [CC (4.47 ± 1.09), CT (4.54 ± 1.27), TT (2.31 ± 0.75), F = 5.634, P = 0.001]. Based on whether the rate of weight gain from baseline at 8 weeks of treatment exceeded 7%, it was divided into a weight gain group (n = 61) and a non-weight gain group (n = 295). The C allele frequency was significantly different between the two groups (48.4% vs 32.4%, χ² = 11.342, P = 0.001).

CONCLUSION

MTHFR C677T polymorphism was associated with risperidone-induced weight gain in Chinese Han population.

Evaluation of research topic evolution in psychiatry using co-word analysis

With the rapid increase in the incidence of mental disorders and mental issues, psychiatry has become one of the fastest growing clinical medical disciplines. Development priorities and research foci in this field have evolved over different periods.All the articles in 10 psychiatric journals with the highest impact factors were selected from the Science Citation Index (SCI) in Web of Science from 2001 to 2015. The information visualization software Sci was used to conduct co-word and clustering analyses on these articles. The articles were divided into 3 periods: 2001 to 2005, 2006 to 2010, and 2011 to 2015. Each bibliographic record contained a title, author names, abstract, keywords, references, and other information.During the 3 periods between 2001 and 2015, child and adolescent psychiatry, major depression, schizophrenia, and prefrontal cortex were constant research foci. The brain and meta-analysis gradually became new research foci, although research on symptoms slowly decreased. Molecular genetics was also an area of interest.Using scientometrics technology to visualize research foci can provide us with new ideas and research methods. Co-word analysis for the preliminary exploration of research foci and developmental trends in psychiatry is helpful in finding developmental rules, choices of topics, and innovative research. Our study had some limitations. In the future, we should expand our research scope and use a variety of research methods to enrich our results.

Analysis on evolution and research focus in psychiatry field

BACKGROUND

With the dramatic rise in mental disorders and mental illnesses, psychiatry has become one of the fastest growing clinical medical disciplines. This has led to a rise in the number of scientific research papers being published in this field.

METHODS

We selected research papers in ten psychiatric journals that were published during 1983 to 2012. These ten journals were those with the top Impact Factor (IF) as indicated by the Science Citation Index Expanded (SCI-Expanded). We utilized information visualization software (CiteSpace) to conduct co-citation and Hierarchal clustering analysis to map knowledge domains to determine the evolution and the foci of research in this field.

RESULTS

In the evolution of the field of psychiatry, there were four stages identified. The result of hierarchal clustering analysis revealed that the research foci in the psychiatric field were primarily studies of child and adolescent psychiatry, diagnostic and classification criteria, brain imaging and molecular genetics.

CONCLUSION

The results provide information about the evolution and the foci of the research in the field of psychiatry. This information can help researchers determine the direction of the research in the field of psychiatry; Moreover, this research provides reasonable suggestions to guide research in psychiatry field and provide scientific evidence to aid in the effective prevention and treatment of mental disorders.

Visualization analysis of author collaborations in schizophrenia research

BACKGROUND

Schizophrenia is a serious mental illness that levies a heavy medical toll and cost burden throughout the world. Scientific collaborations are necessary for progress in psychiatric research. However, there have been few publications on scientific collaborations in schizophrenia. The aim of this study was to investigate the extent of author collaborations in schizophrenia research.

METHODS

This study used 58,107 records on schizophrenia from 2003 to 2012 which were downloaded from Science Citation Index Expanded (SCI Expanded) via Web of Science. CiteSpace III, an information visualization and analysis software, was used to make a visual analysis.

RESULTS

Collaborative author networks within the field of schizophrenia were determined using published documents. We found that external author collaboration networks were more scattered while potential author collaboration networks were more compact. Results from hierarchical clustering analysis showed that the main collaborative field was genetic research in schizophrenia.

CONCLUSION

Based on the results, authors belonging to different institutions and in different countries should be encouraged to collaborate in schizophrenia research. This will help researchers focus their studies on key issues, and allow each other to offer reasonable suggestions for making polices and providing scientific evidence to effectively diagnose, prevent, and cure schizophrenia.

Biomarkers in psychosis: an approach to early identification and individualized treatment

Numerous biomarkers for somatic disorders are used in routine medical practice. Yet, despite remarkable advances in mental health research, we are not able to identify biomarkers with established clinical utility for mental disorders such as schizophrenia. While identification and characterization of biomarkers are crucial first steps in this process, their predictive diagnostic and treatment utility need to be better developed for clinical practice. The heterogeneity of psychotic disorders etiologically, pathologically and symptomatically presents both a challenge and an opportunity for the use of biomarkers in clinical practice. Simply said, a single biomarker might not exist that necessitates the search for a biomarker profile. In this review we discuss research findings in light of such an approach. We summarize some examples of emerging biomarkers in early psychosis research and delineate how these can be applied to a clinical setting to inform treatment on an individual basis fostering a personalized treatment approach.

Pharmacogenetics: a reality or misplaced optimism?

The paper aims to review current evidence that supports the application of genetic information in the management and use of psychotropic medication. Although the importance of an individual's genetic makeup in the metabolism of drugs has been known for at least 50 years, it is only recently that such information is finding clinical application. A literature review of recent studies suggest that there are clear variations in the way people respond to psychotropic medication. These variations can be seen across racial and ethnic lines, and are genetically determined. The hope is that, in future we will be able to use genetic information to predict which patient will benefit from which drug and at what dose. In other fields of health care such as anticoagulant therapy, the application of pharmacogenetics is now established in routine clinical care. Several psychiatric pharmacogenetic tests are currently available, including tests for the determination of metabolic status, risk of agranulocytosis and metabolic syndrome, and selection of beneficial medications. Since nurses are the centrepiece of mental health care, these advances are likely to alter significantly future mental health nurse education and practice.

Clinical Need and Rationale for Multi-Target Drugs in Psychiatry

High attrition in attempts to discover new pharmacological agents for the treatment of psychiatric disorders has triggered a decline in R&D investment in important disease categories such as schizophrenia and mood disorders. Poor knowledge about disease molecular pathology and molecular target validation coupled with notable costly failures involving clinical trials with highly novel and selective single target agents (STAs) have contributed to the development of this trend. One positive development arising from the current situation is the renewed interest in investigating approaches involving multi-target agents (MTAs), which have historically shown a strong track record of success and utility in the treatment of psychiatric disorders. However, it is clear that the traditional serendipity-dependent drug discovery approach for multi-target agents is suboptimal and has to evolve towards a new model of rationally designed and tailored MTAs. It is of course highly challenging to optimise compounds across several therapeutic targets whilst minimising potential broad receptor promiscuity as well as other properties to generate high quality drug candidates. Nevertheless, recent developments in medicinal chemistry approaches and pharmacological evaluation suggest that feasibility for tailored MTAs is not unrealistic. Appropriately designed MTAs, such as hybrids of validated and unprecedented novel molecular targets, offer a multi-functional pharmacology with the potential for multi-symptomatic efficacy and multi-indicational use. If successful this will help to address the compelling unmet medical need and the treatment requirements of schizophrenia and mood disorder patients as well as easing the burden of carers and the societal costs arising from these devastating illnesses.

Validation of candidate genes associated with cardiovascular risk factors in psychiatric patients

The purpose of this study was to identify genetic variants predictive of cardiovascular risk factors in a psychiatric population treated with second generation antipsychotics (SGA). 924 patients undergoing treatment for severe mental illness at four US hospitals were genotyped at 1.2 million single nucleotide polymorphisms. Patients were assessed for fasting serum lipid (low density lipoprotein cholesterol [LDLc], high density lipoprotein cholesterol [HDLc], and triglycerides) and obesity phenotypes (body mass index, BMI). Thirteen candidate genes from previous studies of the same phenotypes in non-psychiatric populations were tested for association. We confirmed 8 of the 13 candidate genes at the 95% confidence level. An increased genetic effect size was observed for triglycerides in the psychiatric population compared to that in the cardiovascular population.

Biomarkers in development of psychotropic drugs

Biomarkers have been receiving increasing attention, especially in the field of psychiatry. In contrast to the availability of potent therapeutic tools including pharmacotherapy, psychotherapy, and biological therapies, unmet needs remain in terms of onset of action, stability of response, and further improvement of the clinical course. Biomarkers are objectively measured characteristics which serve as indicators of the causes of illnesses, their clinical course, and modification by treatment. There exist a variety of markers: laboratory markers which comprise the determination of genetic and epigenetic markers, neurotransmitters, hormones, cytokines, neuropeptides, enzymes, and others as single measures; electrophysiological markers which usually comprise electroencephalography (EEG) measures, and in particular sleep EEG and evoked potentials, magnetic encephalography, electrocardiogram, facial electromyography, skin conductance, and others; brain imaging techniques such as cranial computed tomography, magnetic resonance imaging, functional MRl, magnetic resonance spectroscopy, positron emission tomography, and single photon emission computed tomography; and behavioral approaches such as cue exposure and challenge tests which can be used to induce especially emotional processes in anxiety and depression. Examples for each of these domains are provided in this review. With a view to developing more individually tailored therapeutic strategies, the characterization of patients and the courses of different types of treatment will become even more important in the future.

General overview: biomarkers in neuroscience research

Biomarkers are in demand for disease diagnosis, treatment response monitoring, and development of novel therapeutics. Biomarker discovery in neuroscience is challenging due to absence of robust molecular correlates and the interpatient heterogeneity that characterizes neuropsychiatric disorders. Because of the complexity of these disorders, a panel of biomarkers derived from different platforms will be required to precisely reflect disease-related alterations. Animal models of psychiatric phenotypes as well as -omics and imaging methodologies are important tools for biomarker discovery. However, the limitations of current research concerning sample handling and collection, candidate biomarker validation, and a lack of interdisciplinary approaches need to be addressed. Ultimately, the coordinated effort of relevant stakeholders including researchers, physicians, and funding organizations together with standardization initiatives will be vital to overcome the present challenges and to advance personalized health care using sensitive and specific biomarkers.