Genomics and the future of psychopharmacology: MicroRNAs offer novel therapeutics
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MicroRNAs (miRNAs) are short, noncoding RNAs functioning as regulators of the transcription of protein-coding genes in eukaryotes. During the last two decades, studies on miRNAs indicate that they have potential as diagnostic and prognostic biomarkers for a wide range of cancers. Research interest in miRNAs has moved to embrace further medical disciplines, including neuropsychiatric disorders, comparing miRNA expression and mRNA targets between patient and control blood samples and postmortem brain tissues, as well as in animal models of neuropsychiatric disorders. This manuscript reviews recent findings on miRNAs implicated in the pathology of mood disorders, schizophrenia, and autism, as well as their diagnostic potential, and their potential as tentative targets for future therapeutics. The plausible contribution of X chromosome miRNAs to the larger prevalence of major depression among women is also evaluated.
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Los microARN (miARNs) son ARN cortos y no codificantes que funcionan como reguladores de la transcripción de genes que codifican proteínas en los eucariotes. Durante las últimas dos décadas, los estudios sobre miARNs señalan que tienen un potencial como biomarcadores diagnósticos y pronósticos para una amplia gama de cánceres. El interés de la investigación en los miARNs se ha extendido a otras disciplinas médicas, como los trastornos neuropsiquiátricos, donde se compara la expresión de los miARNs y los blancos de ARNm entre las muestras de sangre de pacientes y controles y los tejidos cerebrales postmortem, como también en modelos animales de trastornos neuropsiquiátricos. Este artículo revisa los hallazgos más recientes sobre los miARNs implicados en los trastornos del ánimo, la esquizofrenia y el autismo, así como su potencial en el diagnóstico y como blancos experimentales para futuras terapias. También se evalúa la eventual contribución de los miARNs del cromosoma X a la mayor prevalencia de depresión mayor entre las mujeres.

Les micro-ARN (miARN) sont de courts ARN non codants, fonctionnant comme des régulateurs de la transcription des gènes codant la protéine dans les cellules eucaryotes. D'après des études menées au cours des dix dernières années, les micro-ARN ont un potentiel en tant que biomarqueurs diagnostiques et pronostiques dans une large gamme de cancers. Les centres d'intérêt de la recherche sur les miARN se sont élargis à d'autres disciplines médicales, dont l'étude des maladies neuropsychiatriques, en comparant l'expression des miARN et des ARNm cibles dans des échantillons de sang de patients avec des échantillons de contrôle, dans des tissus cérébraux post-mortem, ainsi que dans des modèles animaux de maladies neuropsychiatriques. Cet article passe en revue les découvertes les plus récentes sur les miARN impliqués dans les pathologies des troubles de l'humeur, la schizophrénie et l'autisme ainsi que leur potentiel diagnostique et thérapeutique en tant que cibles expérimentales pour de futures thérapies. Il y sera également étudié la possible implication des miARN du chromosome X dans la prévalence plus grande de la dépression majeure chez les femmes.

Psychopharmacology for Borderline Personality Disorder.

Treating individuals with borderline personality disorder (BPD) is a complex and challenging process fraught with clinician stigma and bias. Clinically, polypharmacy is the most common approach, even though it is more likely to produce greater drug-drug adverse effects and interactions than effective improvement in symptoms. Currently, there are no approved medications specific for the treatment of BPD. The current article reviews the extant literature on psychopharmacology and provides treatment recommendations. [Journal of Psychosocial Nursing and Mental Health Services, 56(4), 8-11.].

Female psychopharmacology matters! Towards a sex-specific psychopharmacology.

There is increasing recognition that women have a higher prevalence of certain psychiatric illnesses, and a differential treatment response and course of illness compared to men. Additionally, clinicians deal with a number of disorders like premenstrual syndrome, premenstrual dysphoric disorder, and postpartum depression, which affect women specifically and for which treatment and biological pathways are still unclear. In this article we highlight recent research which suggests that different biological mechanisms may underlie sex differences in responsiveness to stress. Sex differences are evident at the receptor level; where the corticotropin-releasing factor receptor shows differential coupling to adaptor proteins in males and females. The neuropeptide oxytocin also shows sex-specific effects in a range of social behaviors. It may act as a biomarker in post-traumatic stress disorder where sex differences are evident. Studies in women using hormonal contraception show that some of these oxytocin-mediated effects are likely influenced by sex hormones. In female rats rapid changes in circulating progesterone levels are associated with exaggerated behavioral responses to mild stress and blunted responses to benzodiazepines that could be prevented by acute treatment with low-dose fluoxetine. Perceived barriers in research on women have hindered progress. The development of a sex-specific psychopharmacology as a basis for translating this type of research into clinical practice is vital to improve treatment outcomes for women.

Psychopharmacological treatment of 2195 in-patients with borderline personality disorder: A comparison with other psychiatric disorders.

Patients with borderline personality disorder (BPD) are usually prescribed a variety of psychotropic drugs; however, none is recommended in the guidelines nor has any been approved for this indication. As data on drug prescriptions for BPD are sparse, cross-sectional data from the European Drug Safety Project AMSP were used to analyse drug prescriptions of 2195 in-patients with BPD between 2001 and 2011, and the mean values, confidence intervals and regression analyses were calculated. 70% of all BPD patients were medicated with antipsychotics and/or antidepressants, 33% with anticonvulsants, 30% with benzodiazepines, and 4% with lithium; 90% received at least one, 80%≥2, and 54%≥3 psychotropic drugs concomitantly (mean: 2.8). Prescription rates for quetiapine, the single drug most often used in BPD (22%), increased significantly over time. In view of the high percentage of young females with BPD, 18-40 year-old female patients with BPD were compared with patients of the same age but with depression (unipolar and bipolar) and schizophrenia. Typical sedative antipsychotics and anticonvulsants were prescribed more often in BPD than in the other diagnostic groups, with the exception of bipolar depression; this was true for the single substances quetiapine, levomepromazine, chlorprothixene, carbamazepine, and valproate. A limitation of the study was the use of clinical data without verifying the diagnoses by structured interviews. Contrary to the guidelines, about 90% of in-patients with BPD received psychotropic drugs. Polypharmacy was common, and antipsychotics with sedative profiles such as quetiapine and mood-stabilizing anticonvulsants such as valproate appear to be preferred.

Practical clinical trials in psychopharmacology: a systematic review.

Practical clinical trials (PCTs) are randomized experiments under typical practice conditions with the aim of testing the "real-life" benefits and risks of therapeutic interventions. Influential PCTs have been conducted in cardiology, oncology, and internal medicine. Psychotropic medications are widely and increasingly used in medical practice. This review examines recent progress in conducting PCTs in psychopharmacology. The January 2000 to October 2014 MEDLINE, Scopus, and ClinicalTrials.gov databases were searched for peer-reviewed publications of PCTs with at least 100 subjects per treatment arm. Most PCTs in psychiatry evaluated mental health services or psychosocial interventions rather than specific pharmacotherapies. Of 157 PCTs in psychiatry, 30 (19%) were in psychopharmacology, with a median of 2 publications per year and no increase during the period of observation. Sample size ranged from 200 to 18,154; only 11 studies randomized 500 patients or more. Psychopharmacology PCTs were equally likely to be funded by industry as by public agencies. There were 10 PCTs of antidepressants, for a total of 4206 patients (in comparison with at least 46 PCTs of antihypertensive medications, for a total of 208,014 patients). Some psychopharmacology PCTs used suicidal behavior, treatment discontinuation, or mortality as primary outcome and produced effectiveness and safety data that have influenced both practice guidelines and regulatory decisions. Practical clinical trials can constitute an important source of information for clinicians, patients, regulators, and policy makers but have been relatively underused in psychopharmacology. Electronic medical records and integrated practice research networks offer promising platforms for a more efficient conduct of PCTs.

Psychopharmacology in cancer.

Depression, anxiety, delirium, and other psychiatric symptoms are highly prevalent in the cancer setting, and pharmacological intervention is an important component in the overall psychosocial care of the patient. Psychopharmacology is also used as a primary or adjuvant treatment for the management of cancer-related symptoms stemming from the disease itself and/or its treatment, including sleep disturbance, loss of appetite, neuropathic pain, nausea, fatigue, and hot flashes. Psychiatrists, oncologists, and palliative care physicians working as members of a multidisciplinary team have the opportunity to target multiple symptoms that negatively affect a patient's quality of life with the strategic use of psychotropic medications when deemed appropriate. This article aims to review the indications for use of antidepressants, psychostimulants, anxiolytics, antipsychotics, and mood stabilizers in oncology. An updated review of the relevant literature is discussed and referenced in each section.

Evaluation of the individual safe correction of antipsychotic agent polypharmacy in Japanese patients with chronic schizophrenia: validation of safe corrections for antipsychotic polypharmacy and the high-dose method.

BACKGROUND: Polypharmacy for schizophrenia treatment is not justified by the available clinical evidence. We evaluated a treatment reduction approach that reduces the dose and number of antipsychotic medications simultaneously prescribed to patients. METHODS: In a randomized open study of the Safe Correction of Antipsychotic Polypharmacy and High-Dose Prescriptions program funded by the Japanese Ministry of Health, Labour, and Welfare, we evaluated a drug reduction method consisting of a dose reduction intervention performed on 163 patients with schizophrenia for twelve or 24 weeks. One antipsychotic medication was removed each week from each patient's treatment regimen by reducing the dose by 0 to 50 chlorpromazine equivalents. Data on health-related indices of quality of life, clinical symptoms, and risk of side effects were analyzed using a two-way repeated-measures mixed linear model. RESULTS: Despite a 23% reduction in antipsychotic dose, no differences in outcomes were observed between the dose reduction and observation groups (effect size = 0.001 - 0.085, P = .24-.97), despite high statistical power (1-ß = 0.48-0.97). The findings are limited by the nonuniformity of the participants' treatment history, duration, and dose reduction amount. Dose reduction protocol patients exhibited no difference in psychotic symptoms or adverse events compared with the observation group. CONCLUSIONS: Importantly, the low dropout rate in our study (6.9% of participants withdrew because of patient factors and 23.8% for all secondary reasons) indicates that our "slowly" method is well tolerated. We hope that this approach will result in therapeutic improvements.

Psychosocial issues in evidence-based guidelines on inflammatory bowel diseases: a review.

AIM: To study statements and recommendations on psychosocial issues as presented in international evidence-based guidelines on the management of inflammatory bowel diseases (IBD). METHODS: MEDLINE, guidelines International Network, National Guideline Clearing House and National Institute for Health and Care Excellence were searched from January 2006 to June 30, 2013 for evidence-based guidelines on the management of IBD. RESULTS: The search yielded 364 hits. Thirteen guidelines were included in the review, of which three were prepared in Asia, eight in Europe and two in the United States. Eleven guidelines made statements and recommendations on psychosocial issues. The guidelines were concordant in that mental health disorders and stress do not contribute to the aetiology of IBD, but that they can influence its course. It was recommended that IBD-patients should be screened for psychological distress. If indicated, psychotherapy and/or psychopharmacological therapy should be recommended. IBD-centres should collaborate with mental health care specialists. Tobacco smoking patients with Crohn's disease should be advised to quit. CONCLUSION: Patients and mental health specialists should be able to participate in future guideline groups to contribute to establishing recommendations on psychosocial issues in IBD. Future guidelines should acknowledge the presence of psychosocial problems in IBD-patients and encourage screening for psychological distress.

Time-varying processes involved in smoking lapse in a randomized trial of smoking cessation therapies.

INTRODUCTION: Researchers have increasingly begun to gather ecological momentary assessment (EMA) data on smoking, but new statistical methods are necessary to fully unlock information from such data. In this paper, we use a new technique, the logistic time-varying effect model (logistic TVEM), to examine the odds of smoking in the 2 weeks after a quit attempt. METHODS: Data are from a subsample of participants from a randomized, placebo-controlled trial of smoking cessation pharmacotherapies who achieved initial abstinence (N = 1,106, 58% female). Participants completed up to 4 EMA assessments per day during the 2 weeks after their quit day. Predictors include baseline nicotine dependence, EMA measures of craving and negative affect, and whether an individual was assigned to a placebo, monotherapy, or combination therapy condition. Time-varying effects of these predictors were estimated using logistic TVEM. RESULTS: Cravings were a significant predictor of smoking throughout the entire 2 weeks postquit, whereas the effect of baseline dependence became nonsignificant by the second week, and the effect of negative affect increased over time. Individuals in the monotherapy and combination therapy conditions had decreased odds of smoking compared with placebo in the first week postquit, but these differences were nonsignificant in the second week. CONCLUSIONS: Findings suggest that pharmacotherapies are more effective compared with placebo earlier in a quit attempt, when the effect of baseline nicotine dependence on smoking is stronger, whereas the effect of craving and negative affect increased over time. Future cessation therapies may be more successful by providing additional support in the second week after quit attempt.

The promise of intensive longitudinal data capture for behavioral health research.

Advances in technology and the associated cultural norms, especially the advent of the smartphone, offer an unprecedented opportunity to collect data on relevant health behaviors and experiences unobtrusively at a greater frequency and in greater volumes than ever before. This special issue will acquaint the readership of Nicotine and Tobacco Research with the potential for intensive longitudinal data and will illustrate some innovative analytic techniques for addressing research questions associated with this type of complex data. This introductory article will provide a brief history of the analytic techniques for intensive longitudinal data and will point to some resources that support and enable the use of these techniques.

Smoking antecedents: separating between- and within-person effects of tobacco dependence in a multiwave ecological momentary assessment investigation of adolescent smoking.

INTRODUCTION: Ecological momentary assessment (EMA) investigations have shown that the antecedents of smoking vary with individual differences in tobacco dependence. This has been interpreted as indicating that the transition to dependence is characterized by an erosion of external stimulus control over smoking. Rigorously testing this requires collecting multiple waves of EMA data, which permits separation of the influence of between- and within-person tobacco dependence variation in multilevel models. METHODS: Adolescents (n = 313, 9th or 10th grade at baseline) participated in up to 4 waves of week-long EMA assessment over the course of 2 years as part of a larger longitudinal, observational study. At each wave, participants recorded contextual features and subjective states in response to prompted diary assessments and when smoking. They completed a youth-specific form of the Nicotine Dependence Syndrome Scale at each wave. RESULTS: In cross-sectional multilevel analyses, smoking was less contingent on alcohol/drug use and was more common at home and in the morning for adolescents with higher levels of dependence. Multiwave analyses demonstrated that these effects were largely attributable to between-person variation in dependence, although parameter estimates for intraindividual dependence × antecedent effects tended to be in the predicted direction. DISCUSSION: Findings provided partial support for the contention that the antecedents of smoking shift as an individual progresses to higher levels of dependence. Distinctive choices concerning smoking settings also appear to reflect between-person differences in propensity to dependence. More generally, the findings illustrate the value of using multilevel modeling and repeated EMA assessments to investigate the correlates of tobacco dependence at different levels of analysis.

Conceptualizing analyses of ecological momentary assessment data.

Ecological momentary assessment (EMA) methods, which involve collection of real-time data in subjects' real-world environments, are particularly well suited to studying tobacco use. Analyzing EMA datasets can be challenging, as the datasets include a large and varied number of observations per subject and are relatively unstructured. This paper suggests that time is typically a key organizing principle in EMA data and that conceptualizing the data as a timeline of events, behaviors, and experiences can help define analytic approaches. EMA datasets lend themselves to answering a diverse array of research questions, and the research question must drive how data are arranged for analysis, and the kinds of statistical models that are applied. This is illustrated this with brief examples of diverse analyses applied to answer different questions from an EMA study of tobacco use and relapse.

Integrative biological analysis for neuropsychopharmacology.

Although advances in psychotherapy have been made in recent years, drug discovery for brain diseases such as schizophrenia and mood disorders has stagnated. The need for new biomarkers and validated therapeutic targets in the field of neuropsychopharmacology is widely unmet. The brain is the most complex part of human anatomy from the standpoint of number and types of cells, their interconnections, and circuitry. To better meet patient needs, improved methods to approach brain studies by understanding functional networks that interact with the genome are being developed. The integrated biological approaches--proteomics, transcriptomics, metabolomics, and glycomics--have a strong record in several areas of biomedicine, including neurochemistry and neuro-oncology. Published applications of an integrated approach to projects of neurological, psychiatric, and pharmacological natures are still few but show promise to provide deep biological knowledge derived from cells, animal models, and clinical materials. Future studies that yield insights based on integrated analyses promise to deliver new therapeutic targets and biomarkers for personalized medicine.

Advancing cessation research by integrating EMA and geospatial methodologies: associations between tobacco retail outlets and real-time smoking urges during a quit attempt.

INTRODUCTION: Residential tobacco retail outlet (TRO) density and proximity have been associated with smoking behaviors. More research is needed to understand the mechanisms underlying these relations and their potential relevance outside of the residential setting. This study integrates ecological momentary assessment (EMA) and geo-location tracking to explore real-time associations between exposure to TROs and smoking urges among 47 economically disadvantaged smokers in a cessation trial (59.6% female; 36.2% White). METHODS: EMA data were collected for 1 week postquit via smartphone, which recorded smoking urge strength ≤ 4 random times daily along with real-time participant location data. For each assessment, the participants' proximity to the closest TRO and the density of TROs surrounding the participant were calculated. Linear mixed model regressions examined associations between TRO variables and smoking urges and whether relations varied based on participants' distance from their home. Covariates included sociodemographics, prequit tobacco dependence, treatment group, and daily smoking status. RESULTS: Main effects were nonsignificant; however, the interaction between TRO proximity and distance from home was considered significant (p = .056). Specifically, closer proximity to TROs was associated with stronger smoking urges ≤ 1 mile of home (p = .001) but not >1 mile from home (p = .307). Significant associations were attributable to assessments completed at participants' home addresses. All density analyses were nonsignificant. CONCLUSIONS: Technological challenges encountered in this study resulted in a significant amount of missing data, highlighting the preliminary nature of these findings and limiting the inferences that can be drawn. However, results suggest that closer residential proximity to tobacco outlets may trigger stronger urges to smoke among economically disadvantaged smokers trying to quit, perhaps due to enhanced cigarette availability and accessibility. Therefore, limiting tobacco sales in close proximity to residential areas may complement existing tobacco control efforts and facilitate cessation.

A dynamical systems approach to understanding self-regulation in smoking cessation behavior change.

INTRODUCTION: Self-regulation, a key component of the addiction process, has been challenging to model precisely in smoking cessation settings, largely due to the limitations of traditional methodological approaches in measuring behavior over time. However, increased availability of intensive longitudinal data (ILD) measured through ecological momentary assessment facilitates the novel use of an engineering modeling approach to better understand self-regulation. METHODS: Dynamical systems modeling is a mature engineering methodology that can represent smoking cessation as a self-regulation process. This article shows how a dynamical systems approach effectively captures the reciprocal relationship between day-to-day changes in craving and smoking. Models are estimated using ILD from a smoking cessation randomized clinical trial. RESULTS: A system of low-order differential equations is presented that models cessation as a self-regulatory process. It explains 87.32% and 89.16% of the variance observed in craving and smoking levels, respectively, for an active treatment group and 62.25% and 84.12% of the variance in a control group. The models quantify the initial increase and subsequent gradual decrease in craving occurring postquit as well as the dramatic quit-induced smoking reduction and postquit smoking resumption observed in both groups. Comparing the estimated parameters for the group models suggests that active treatment facilitates craving reduction and slows postquit smoking resumption. CONCLUSIONS: This article illustrates that dynamical systems modeling can effectively leverage ILD in order to understand self-regulation within smoking cessation. Such models quantify group-level dynamic responses in smoking cessation and can inform the development of more effective interventions in the future.

Compliance with an EMA monitoring protocol and its relationship with participant and smoking characteristics.

INTRODUCTION: Arguably, the greatest advantage of ecological momentary assessment (EMA) studies is that data are collected repeatedly in real-time and real-world situations, which reduces recall and situational biases and thus improves the accuracy and validity of the data collected. However, the validity of EMA data is contingent upon compliance rates. If participant characteristics are related to missing data, analyses should control for these factors, or they should be targeted in EMA training sessions. This study evaluates the impact of demographic and smoking-related participant characteristics on compliance to an EMA smoking study protocol. METHODS: Prequit-day data were taken from the control arm of an ongoing randomized controlled trial of a smoking-cessation program. After training, 119 participants were asked to carry a mobile device with them at all times for ~6 days and to log every cigarette they smoked in addition to completing randomly scheduled assessments. Different types of compliance were assessed: the percentage of completed random prompts (signal-contingent compliance), the percentage of logged cigarettes per day compared to a timeline follow-back measure, and the correlation between logged cigarettes and a carbon monoxide assessment 2 hr later (both event-contingent compliance). RESULTS: Overall compliance rates were 78.48% for event-contingent and 72.17% for signal-contingent compliance. None of the demographic or smoking-related participant characteristics predicted signal-contingent compliance; however, female participants showed higher event-contingent compliance than male participants, and Caucasian participants showed higher event-contingent compliance than non-Caucasian participants. CONCLUSIONS: Compliance did not depend on smoking-related characteristics. EMA is a valid method for assessing smoking behavior in real-time and real-world settings.

Modeling mood variation and covariation among adolescent smokers: application of a bivariate location-scale mixed-effects model.

INTRODUCTION: Ecological momentary assessments (EMAs) are useful for understanding both between- and within-subject dynamic changes in smoking and mood. Modeling 2 moods (positive affect [PA] and negative affect [NA], PA and NA) simultaneously will better enable researchers to explore the association between mood variables and what influences them at both the momentary and subject level. METHODS: The EMA component of a natural history study of adolescent smoking was analyzed with a bivariate location-scale mixed-effects model. The proposed model separately estimates the between- and within-subject variances and jointly models the 2 mood constructs. A total of 461 adolescents completed the baseline EMA wave, which resulted in 14,105 random prompts. Smoking level, represented by the number of smoking events on EMA, entered the model as 2 predictors: one that compared nonsmokers during the EMA week to 1-cigarette smokers, and the second one that estimated the effect of smoking level on mood among smokers. RESULTS: Results suggest that nonsmokers had more consistent positive and negative moods compared to 1-cigarette smokers. Among those who smoked, both moods were more consistent at higher smoking levels. The effects of smoking level were greater for NA than for PA. The within-subject association between mood constructs was negative and strongest among 1-cigarette smokers; the within-subject association between positive and negative moods was negatively associated with smoking. CONCLUSIONS: Mood variation and association between mood constructs varied across smoking levels. The most infrequent smokers were characterized with more inconsistent moods, whereas mood was more consistent for subjects with higher smoking levels.

Advancing the understanding of craving during smoking cessation attempts: a demonstration of the time-varying effect model.

INTRODUCTION: Advancing the understanding of smoking cessation requires a complex and nuanced understanding of behavior change. To this end, ecological momentary assessments (EMA) are now being collected extensively. The time-varying effect model (TVEM) is a statistical technique ideally suited to model processes that unfold as behavior and nicotine dependence change. Coefficients are expressed dynamically over time and are represented as smooth functions of time. METHODS: The TVEM approach is demonstrated using data from a smoking-cessation trial. Time-varying effects of baseline nicotine dependence (a time-invariant covariate) and negative affect (a time-varying covariate) on urge to smoke during a quit attempt were estimated for monotherapy, combination therapy, and placebo groups. SAS syntax for conducting TVEM is provided so that readers can adapt it for their research. RESULTS: During the first 2 days after quitting, the association between negative affect and craving was significantly stronger among individuals in the placebo group, suggesting an early positive impact of treatment. For the monotherapy and combination therapy groups, during the second week of the quit attempt, baseline dependence was less strongly related to craving compared with the placebo group, indicating a different positive impact of treatments later in the quit attempt. CONCLUSIONS: The results reveal information about the underlying dynamics that unfold during a quit attempt and how monotherapy and combination therapy impact those processes. This suggests possible mechanisms to target in an intervention and indicates timepoints that hold the greatest promise for effective treatment. TVEM is a straightforward approach to examining time-varying processes embedded in EMA.