Should pharmacogenetics be incorporated in major depression treatment? Economic evaluation in high- and middle-income European countries

Dietary niacin intake in relation to depression among adults: a population-based study

BACKGROUND

Previous studies have shown that an antioxidant diet is a protective factor against depression. However, the association between niacin, an important antioxidant consumed from the diet, and depression has received little attention. Therefore, we explored the association between niacin intake and depression through a cross-sectional analysis of the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2016.

METHODS

Depression was measured using the Patient Health Questionnaire (PHQ-9, score ≥ 10). Niacin intake was assessed through 24-h dietary recall interviews. The relationship of niacin intake with depression among adults in US was assessed by using a weighted multiple logistic regression model with subgroup analysis. Non-linear associations were explored using restricted cubic spline models. And we used a two-piece-wise logistic regression model with smoothing to explore the threshold for association between them.

RESULTS

A total of 16,098 adults were included in this study. Compared with individuals with lowest niacin intake Q1 (≤ 15.96 mg/day), the adjusted OR values for dietary niacin intake and depression in Q2 (15.97-22.86 mg/day), Q3 (22.87-32.28 mg/day) and Q4 (≥ 32.29 mg/day), were 0.92 (95% CI: 0.70-1.20), 0.76 (95% CI: 0.56-0.99,) and 0.68 (95% CI: 0.48-0.98), respectively. The results were not modified by sex, by age and by BMI. Furthermore, the relationship between dietary niacin intake and depression exhibited a U-shaped curve (nonlinear, p < 0.001). And depression risk was lowest when dietary consumption of niacin was around 36 mg/day.

CONCLUSIONS

In present study, moderate niacin intake, but not high intake, was associated with lower odds of depression suggesting a U-shaped association.

A Promising Approach to Optimizing Sequential Treatment Decisions for Depression: Markov Decision Process

The most appropriate next step in depression treatment after the initial treatment fails is unclear. This study explores the suitability of the Markov decision process for optimizing sequential treatment decisions for depression. We conducted a formal comparison of a Markov decision process approach and mainstream state-transition models as used in health economic decision analysis to clarify differences in the model structure. We performed two reviews: the first to identify existing applications of the Markov decision process in the field of healthcare and the second to identify existing health economic models for depression. We then illustrated the application of a Markov decision process by reformulating an existing health economic model. This provided input for discussing the suitability of a Markov decision process for solving sequential treatment decisions in depression. The Markov decision process and state-transition models differed in terms of flexibility in modeling actions and rewards. In all, 23 applications of a Markov decision process within the context of somatic disease were included, 16 of which concerned sequential treatment decisions. Most existing health economic models relating to depression have a state-transition structure. The example application replicated the health economic model and enabled additional capacity to make dynamic comparisons of more interventions over time than was possible with traditional state-transition models. Markov decision processes have been successfully applied to address sequential treatment-decision problems, although the results have been published mostly in economics journals that are not related to healthcare. One advantage of a Markov decision process compared with state-transition models is that it allows extended action space: the possibility of making dynamic comparisons of different treatments over time. Within the context of depression, although existing state-transition models are too basic to evaluate sequential treatment decisions, the assumptions of a Markov decision process could be satisfied. The Markov decision process could therefore serve as a powerful model for optimizing sequential treatment in depression. This would require a sufficiently elaborate state-transition model at the cohort or patient level.

Economic evaluation in psychiatric pharmacogenomics: a systematic review

Nowadays, many relevant drug-gene associations have been discovered, but pharmacogenomics (PGx)-guided treatment needs to be cost-effective as well as clinically beneficial to be incorporated into standard health care. To address current challenges, this systematic review provides an update regarding previously published studies, which assessed the cost-effectiveness of PGx testing for the prescription of antidepressants and antipsychotics. From a total of 1159 studies initially identified by literature database querying, and after manual assessment and curation of all of them, a mere 18 studies met our inclusion criteria. Of the 18 studies evaluations, 16 studies (88.89%) drew conclusions in favor of PGx testing, of which 9 (50%) genome-guided interventions were cost-effective and 7 (38.9%) were less costly compared to standard treatment based on cost analysis. More precisely, supportive evidence exists for CYP2D6 and CYP2C19 drug-gene associations and for combinatorial PGx panels, but evidence is limited for many other drug-gene combinations. Amongst the limitations of the field are the unclear explanation of perspective and cost inputs, as well as the underreporting of study design elements, which can influence though the economic evaluation. Overall, the findings of this article demonstrate that although there is growing evidence on the cost-effectiveness of genome-guided interventions in psychiatric diseases, there is still a need for performing additional research on economic evaluations of PGx implementation with an emphasis on psychiatric disorders.

Associations of dietary B vitamins intakes with depression in adults

Background: The impact of the dietary B vitamins intakes on the development of depression has been scarcely investigated. Thus, this study aimed to examine the associations of dietary B vitamins intakes with the risk of depression in American adults. Methods: The data we used in this study were from the National Health and Nutrition Examination Survey (NHANES) 2007-2014. We used the Logistic regression models to analyze the associations of the dietary intakes of B vitamins with the risk of depression. Results: 17,732 individuals (8,623 males and 9,109 females) were enrolled in the study and they were all 18 or older. Compared to the lowest quartile of dietary intake, the ORs (95%CIs) of the highest quartile were 0.64 (0.50-0.82), 0.78 (0.62-0.97), 0.60 (0.47-0.78), 0.65 (0.50-0.84), and 0.71 (0.54-0.95) for vitamin B1, vitamin B2, niacin, vitamin B6, and vitamin B12, respectively. Compared to the people whose dietary intakes below the RDA in the model 2, those with intake meeting the RDA of vitamin B1 (OR: 0.68; 95%CI: 0.56-0.84), niacin (OR: 0.65; 95%CI: 0.51-0.81), B6 (OR: 0.65; 95%CI: 0.52-0.81), or B12 (OR: 0.65; 95%CI: 0.48-0.88) had a lower risk of depression, severally. We also found a nonlinear negative association between dietary vitamin B1, vitamin B2, niacin, vitamin B6, and vitamin B12 intakes and the risk of depression in the dose-response analyses, severally. Conclusions: Our results suggested that dietary vitamin B1, vitamin B2, niacin, vitamin B6, and vitamin B12 intakes may be inversely associated with the risk of depression.

The burden of treatment-resistant depression: A systematic review of the economic and quality of life literature

BACKGROUND

Major depressive disorder (MDD) is a global public health concern. In particular, treatment-resistant depression (TRD) represents a key unmet need in the management of MDD. A systematic review of the epidemiological and economic literature on the burden associated with an increasing number of treatment steps due to TRD/non-response within an MDD episode was performed to quantify the burden of TRD.

METHODS

Studies were identified in the PubMed/Medline databases through April 27th, 2017. Articles were limited to full-length peer-reviewed journal publications with no date restrictions. Economic and patient health-related quality of life (HRQoL) data on non-response by the number of treatment steps were quantified and, where appropriate, compared across studies; otherwise, comparative data within studies were reported.

RESULTS

The 12 studies on economic burden found an association between increasing levels of TRD/non-response and elevations in direct and indirect costs. Likewise, the 19 studies studying HRQoL burden found that increasing levels of TRD/non-response correlated with reduced patient HRQoL and health status.

LIMITATIONS

TRD is defined inconsistently, which results in notable heterogeneity between published studies and poses methodological challenges for between-study comparisons. It is unknown if the increased economic and patient HRQoL burden are due to factors associated with TRD/non-response in addition to those due to depression persistence or severity.

CONCLUSIONS

A consistent trend was observed such that medical costs increased and patient HRQoL and health status decreased by increasing level of TRD/non-response within an MDD episode. These findings highlight the need for improved therapies for TRD to help reduce disease burden.

Pharmacogenetic testing among patients with mood and anxiety disorders is associated with decreased utilization and cost: A propensity-score matched study

BACKGROUND

Naturalistic and small randomized trials have suggested that pharmacogenetic testing may improve treatment outcomes in depression, but its cost-effectiveness is not known. There is growing enthusiasm for personalized medicine, relying on genetic variation as a contributor to heterogeneity of treatment effects. We sought to examine the relationship between a commercial pharmacogenetic test for psychotropic medications and 6-month cost of care and utilization in a large commercial health plan.

METHODS

We performed a propensity-score matched case-control analysis of longitudinal health claims data from a large US insurer. Individuals with a mood or anxiety disorder diagnosis (N = 817) who received genetic testing for pharmacokinetic and pharmacodynamic variation were matched to 2,745 individuals who did not receive such testing. Outcomes included number of outpatient visits, inpatient hospitalizations, emergency room visits, and prescriptions, as well as associated costs over 6 months.

RESULTS

On average, individuals who underwent testing experienced 40% fewer all-cause emergency room visits (mean difference 0.13 visits; P < 0.0001) and 58% fewer inpatient all-cause hospitalizations (mean difference 0.10 visits; P < 0.0001) than individuals in the control group. The two groups did not differ significantly in number of psychotropic medications prescribed or mood-disorder related hospitalizations. Overall 6-month costs were estimated to be $1,948 (SE 611) lower in the tested group.

CONCLUSIONS

Pharmacogenetic testing represents a promising strategy to reduce costs and utilization among patients with mood and anxiety disorders.

Model-Based Economic Evaluation of Treatments for Depression: A Systematic Literature Review

BACKGROUND

An increasing number of model-based studies that evaluate the cost effectiveness of treatments for depression are being published. These studies have different characteristics and use different simulation methods.

OBJECTIVE

We aimed to systematically review model-based studies evaluating the cost effectiveness of treatments for depression and examine which modelling technique is most appropriate for simulating the natural course of depression.

METHODS

The literature search was conducted in the databases PubMed, EMBASE and PsycInfo between 1 January 2002 and 1 October 2016. Studies were eligible if they used a health economic model with quality-adjusted life-years or disability-adjusted life-years as an outcome measure. Data related to various methodological characteristics were extracted from the included studies. The available modelling techniques were evaluated based on 11 predefined criteria.

RESULTS

This methodological review included 41 model-based studies, of which 21 used decision trees (DTs), 15 used cohort-based state-transition Markov models (CMMs), two used individual-based state-transition models (ISMs), and three used discrete-event simulation (DES) models. Just over half of the studies (54%) evaluated antidepressants compared with a control condition. The data sources, time horizons, cycle lengths, perspectives adopted and number of health states/events all varied widely between the included studies. DTs scored positively in four of the 11 criteria, CMMs in five, ISMs in six, and DES models in seven.

CONCLUSION

There were substantial methodological differences between the studies. Since the individual history of each patient is important for the prognosis of depression, DES and ISM simulation methods may be more appropriate than the others for a pragmatic representation of the course of depression. However, direct comparisons between the available modelling techniques are necessary to yield firm conclusions.

Cost-effectiveness of pharmacogenetic-guided treatment: are we there yet?

Pharmacogenetics (PGx) has the potential to personalize pharmaceutical treatments. Many relevant gene-drug associations have been discovered, but PGx-guided treatment needs to be cost-effective as well as clinically beneficial to be incorporated into standard health-care. We reviewed economic evaluations for PGx associations listed in the US Food and Drug Administration (FDA) Table of Pharmacogenomic Biomarkers in Drug Labeling. We determined the proportion of evaluations that found PGx-guided treatment to be cost-effective or dominant over the alternative strategies, and estimated the impact on this proportion of removing the cost of genetic testing. Of the 137 PGx associations in the FDA table, 44 economic evaluations, relating to 10 drugs, were identified. Of these evaluations, 57% drew conclusions in favour of PGx testing, of which 30% were cost-effective and 27% were dominant (cost-saving). If genetic information was freely available, 75% of economic evaluations would support PGx-guided treatment, of which 25% would be cost-effective and 50% would be dominant. Thus, PGx-guided treatment can be a cost-effective and even a cost-saving strategy. Having genetic information readily available in the clinical health record is a realistic future prospect, and would make more genetic tests economically worthwhile.

Rapid evidence review of the comparative effectiveness, harms, and cost-effectiveness of pharmacogenomics-guided antidepressant treatment versus usual care for major depressive disorder

OBJECTIVE

This study aims to conduct an evidence review of the effectiveness, harms, and cost-effectiveness of pharmacogenomics-guided antidepressant treatment for major depressive disorder.

METHODS

We searched MEDLINE®, the Cochrane Central Registry of Controlled Trials, and PsycINFO through February 2017. We used prespecified criteria to select studies, abstract data, and rate internal validity and strength of the evidence (PROSPERO number CRD42016036358).

RESULTS

We included two randomized trials (RCT), five controlled cohort studies, and six modeling studies of mostly women in their mid-40s with few comorbidities. CNSDose (ABCB1, ABCC1, CYP2C19, CYP2D6, UGT1A1) is the only pharmacogenomics test that significantly improved remission (one additional remitting patient in 12 weeks per three genotyped, 95% CI 1.7 to 3.5) and reduced intolerability in an RCT. ABCB1 genotyping leads to one additional remitting patient in 5 weeks per three genotyped (95% CI 3 to 20), but tolerability was not reported. In an RCT, GeneSight (CYP2D6, CYPC19, CYP1A2, SLC6A4, HTR2A) did not statistically significantly improve remission, and evidence is inconclusive about its tolerability. Evidence is generally low strength because RCTs were few and underpowered. Cost-effectiveness is unclear due to lack of directly observed cost-effectiveness outcomes. We found no studies that evaluated whether pharmacogenomics shortens time to optimal treatment, whether improvements were due to switches to genetically congruent medication, or whether effectiveness varies based on test and patient characteristics.

CONCLUSIONS

Certain pharmacogenomics tools show promise of improving short-term remission rates in women in their mid-40s with few comorbidities. But, important evidence limitations preclude recommending their widespread use and indicate a need for further research.

A Systematic Review of Economic Evaluations of Pharmacogenetic Testing for Prevention of Adverse Drug Reactions

BACKGROUND

Pharmacogenetics offers the potential to improve health outcomes by identifying individuals who are at greater risk of harm from certain medicines. Routine adoption of pharmacogenetic tests requires evidence of their cost effectiveness.

OBJECTIVE

The present review aims to systematically review published economic evaluations of pharmacogenetic tests that aim to prevent or reduce the incidence of ADRs.

METHODS

We conducted a systematic literature review of economic evaluations of pharmacogenetic tests aimed to reduce the incidence of adverse drug reactions. Literature was searched using Embase, MEDLINE and the NHS Economic Evaluation Database with search terms relating to pharmacogenetic testing, adverse drug reactions, economic evaluations and pharmaceuticals. Titles were screened independently by two reviewers. Articles deemed to meet the inclusion criteria were screened independently on abstract, and full texts reviewed.

RESULTS

We identified 852 articles, of which 47 met the inclusion criteria. There was evidence supporting the cost effectiveness of testing for HLA-B*57:01 (prior to abacavir), HLA-B*15:02 and HLA-A*31:01 (prior to carbamazepine), HLA-B*58:01 (prior to allopurinol) and CYP2C19 (prior to clopidogrel treatment). Economic evidence was inconclusive with respect to TPMT (prior to 6-mercaptoputine, azathioprine and cisplatin therapy), CYP2C9 and VKORC1 (to inform genotype-guided dosing of coumarin derivatives), MTHFR (prior to methotrexate treatment) and factor V Leiden testing (prior to oral contraception). Testing for A1555G is not cost effective before prescribing aminoglycosides.

CONCLUSIONS

Our systematic review identified robust evidence of the cost effectiveness of genotyping prior to treatment with a number of common drugs. However, further analyses and (or) availability of robust clinical evidence is necessary to make recommendations for others.

Examining perceptions of the usefulness and usability of a mobile-based system for pharmacogenomics clinical decision support: a mixed methods study

Background. Pharmacogenomic testing has the potential to improve the safety and efficacy of pharmacotherapy, but clinical application of pharmacogenetic knowledge has remained uncommon. Clinical Decision Support (CDS) systems could help overcome some of the barriers to clinical implementation. The aim of this study was to evaluate the perception and usability of a web- and mobile-enabled CDS system for pharmacogenetics-guided drug therapy–the Medication Safety Code (MSC) system–among potential users (i.e., physicians and pharmacists). Furthermore, this study sought to collect data on the practicability and comprehensibility of potential layouts of a proposed personalized pocket card that is intended to not only contain the machine-readable data for use with the MSC system but also human-readable data on the patient’s pharmacogenomic profile. Methods. We deployed an emergent mixed methods design encompassing (1) qualitative interviews with pharmacists and pharmacy students, (2) a survey among pharmacogenomics experts that included both qualitative and quantitative elements and (3) a quantitative survey among physicians and pharmacists. The interviews followed a semi-structured guide including a hypothetical patient scenario that had to be solved by using the MSC system. The survey among pharmacogenomics experts focused on what information should be printed on the card and how this information should be arranged. Furthermore, the MSC system was evaluated based on two hypothetical patient scenarios and four follow-up questions on the perceived usability. The second survey assessed physicians’ and pharmacists’ attitude towards the MSC system. Results. In total, 101 physicians, pharmacists and PGx experts coming from various relevant fields evaluated the MSC system. Overall, the reaction to the MSC system was positive across all investigated parameters and among all user groups. The majority of participants were able to solve the patient scenarios based on the recommendations displayed on the MSC interface. A frequent request among participants was to provide specific listings of alternative drugs and concrete dosage instructions. Negligence of other patient-specific factors for choosing the right treatment such as renal function and co-medication was a common concern related to the MSC system, while data privacy and cost-benefit considerations emerged as the participants’ major concerns regarding pharmacogenetic testing in general. The results of the card layout evaluation indicate that a gene-centered and tabulated presentation of the patient’s pharmacogenomic profile is helpful and well-accepted. Conclusions. We found that the MSC system was well-received among the physicians and pharmacists included in this study. A personalized pocket card that lists a patient’s metabolizer status along with critically affected drugs can alert physicians and pharmacists to the availability of essential therapy modifications.

Economic Evaluations of Pharmacogenetic and Pharmacogenomic Screening Tests: A Systematic Review. Second Update of the Literature

Objective

Due to extended application of pharmacogenetic and pharmacogenomic screening (PGx) tests it is important to assess whether they provide good value for money. This review provides an update of the literature.

Methods

A literature search was performed in PubMed and papers published between August 2010 and September 2014, investigating the cost-effectiveness of PGx screening tests, were included. Papers from 2000 until July 2010 were included via two previous systematic reviews. Studies’ overall quality was assessed with the Quality of Health Economic Studies (QHES) instrument.

Results

We found 38 studies, which combined with the previous 42 studies resulted in a total of 80 included studies. An average QHES score of 76 was found. Since 2010, more studies were funded by pharmaceutical companies. Most recent studies performed cost-utility analysis, univariate and probabilistic sensitivity analyses, and discussed limitations of their economic evaluations. Most studies indicated favorable cost-effectiveness. Majority of evaluations did not provide information regarding the intrinsic value of the PGx test. There were considerable differences in the costs for PGx testing. Reporting of the direction and magnitude of bias on the cost-effectiveness estimates as well as motivation for the chosen economic model and perspective were frequently missing.

Conclusions

Application of PGx tests was mostly found to be a cost-effective or cost-saving strategy. We found that only the minority of recent pharmacoeconomic evaluations assessed the intrinsic value of the PGx tests. There was an increase in the number of studies and in the reporting of quality associated characteristics. To improve future evaluations, scenario analysis including a broad range of PGx tests costs and equal costs of comparator drugs to assess the intrinsic value of the PGx tests, are recommended. In addition, robust clinical evidence regarding PGx tests’ efficacy remains of utmost importance.

Is personalized medicine achievable in obstetrics?

Personalized medicine seeks to identify the right dose of the right drug for the right patient at the right time. Typically, individualization of therapy is based on the pharmacogenomic makeup of the individual and environmental factors that alter drug disposition and response. In addition to these factors, during pregnancy, a woman's body undergoes many changes that can impact the therapeutic efficacy of medications. Yet, there is minimal research regarding personalized medicine in obstetrics. Adoption of pharmacogenetic testing into the obstetrical care is dependent on evidence of analytical validity, clinical validity, and clinical utility. Here, we briefly present information regarding the potential utility of personalized medicine for treating the obstetric patient for pain with narcotics, hypertension, and preterm labor, and discuss the impediments of bringing personalized medicine to the obstetrical clinic.

Benefit of slow titration of paroxetine to treat depression in the elderly

OBJECTIVE

Paroxetine is commonly used to treat depression in the elderly; however, titration issues have been raised. Rapid titration may lead to increased anxiety and early dropout. The aim of this cost-utility analysis was to compare the potential benefit of standard (10 mg the first day) versus slow titration (2.5 mg gradually increased).

METHODS

Clinical analysis was based on a naturalistic trial integrated with a decision-analytic model representing second treatments for those who initially did not respond and for dropout cases. Treatment setting was a public outpatient center for mental disorders in Italy. Service use data were estimated from best practice guidelines, whereas costs (Euros; 2012) were retrieved from Italian official sources.

RESULTS

Slow titration approach produced 0.031 more quality-adjusted life years (remission rate: 57% vs 44% in standard titration group) at an incremental cost of €5.53 (generic paroxetine) and €54.54 (brand paroxetine syrup). Incremental cost-effectiveness ratio (ICER) values were €159 and €1768, respectively, in favor of slow titration approach. Cost-effectiveness threshold, defined as ICER < 1 GDP per capita according to World Health Organization criteria, is about €25 000 in Italy.

CONCLUSIONS

Our results are consistent with a superiority of slow titration of paroxetine in older depressed patients. However, these findings, in part based on simulated data, need to be replicated in clinical trials.

Understanding the pharmacogenetics of selective serotonin reuptake inhibitors

INTRODUCTION

The genetic background of antidepressant response represents a unique opportunity to identify biological markers of treatment outcome. Encouraging results alternating with inconsistent findings made antidepressant pharmacogenetics a stimulating but often discouraging field that requires careful discussion about cumulative evidence and methodological issues.

AREAS COVERED

The present review discusses both known and less replicated genes that have been implicated in selective serotonin reuptake inhibitors (SSRIs) efficacy and side effects. Candidate genes studies and genome-wide association studies (GWAS) were collected through MEDLINE database search (articles published till January 2014). Further, GWAS signals localized in promising genetic regions according to candidate gene studies are reported in order to assess the general comparability of results obtained through these two types of pharmacogenetic studies. Finally, a pathway enrichment approach is applied to the top genes (those harboring SNPs with p < 0.0001) outlined by previous GWAS in order to identify possible molecular mechanisms involved in SSRI effect.

EXPERT OPINION

In order to improve the understanding of SSRI pharmacogenetics, the present review discusses the proposal of moving from the analysis of individual polymorphisms to genes and molecular pathways, and from the separation across different methodological approaches to their combination. Efforts in this direction are justified by the recent evidence of a favorable cost-utility of gene-guided antidepressant treatment.

Antidepressant pharmacogenetics

PURPOSE OF REVIEW

This article reviews recent literature published over the period March 2012-August 2013 on antidepressant pharmacogenetics, with a focus on clinical translation and methodological challenges.

RECENT FINDINGS

Recently, various polymorphisms associated with differential antidepressant efficacy, tolerability, and safety have emerged in association studies, but mixed findings, limited effect sizes, and poor control of confounders have prevented findings translating to practice. Although promising steps have been made, empirically robust clinically translatable pharmacogenetic tests are not yet established. The complex neurobiology of major depressive disorder (MDD) together with the evolving understanding of genetic processes present research challenges for clinical translation.

SUMMARY

Early reports of clinical utility are published. The current evidence base for antidepressant pharmacogenetics is, however, not yet empirically robust enough to inform routine prescribing guidelines. Over the coming years, genetically guided versus unguided trials will help determine if antidepressant pharmacogenetics merits more widespread application.

Challenging sequential approach to treatment resistant depression: cost-utility analysis based on the Sequenced Treatment Alternatives to Relieve Depression (STAR(⁎)D) trial

In major depression, when a first antidepressant does not cause remission of symptoms (60%-75%), there are several options for continuing treatment in the next step. This study is a cost-utility analysis (CUA) of different second-line approaches. In a simulated trial outpatients with MDD were treated with citalopram for 13 weeks (level 1), then based on two alternative algorithms implemented from the Sequenced Treatment Alternatives to Relieve Depression (STAR(*)D) study. Algorithm A: citalopram was continued until study endpoint (week 26). Algorithm B: patients who remitted during level 1 continued citalopram. Those who did not remit could opt for switching to another antidepressant (venlafaxine; sertraline) (b1) or adding bupropion to citalopram treatment (augmentation; b2). Algorithm B increased remission rate by 10.6% over Algorithm A (number needed to treat: 9.9; sensitivity range: 9.1-12.5). As a comparison, differences between active antidepressants and placebo are associated with NNT values of 6 to 8. In CUA Algorithm B was dominant with an ICER of $11,813 (sensitivity range=$1783 - $21,784), which is <1GDP per capita cost-effectiveness threshold (USA=$47,193). Among Algorithm B options, switching (b1) dominated Algorithm A with a smaller number of responders than augmentation approach (b2) (NNT 11 vs. 7.7), whereas ICER values were similar (b1: $14,738; b2: $15,458). However we cannot exclude a bias in selecting second treatment. This cost-utility analysis shows (in line with current guidelines) a benefit in modifying antidepressant treatment if response to first-line agent does not occur within 3 months, but not a clear-cut evidence in terms of NNT.

Value of genetic and epigenetic testing as biomarkers of response to antidepressant treatment

Major depressive disorder (MDD) is one of the most prevalent and disabling psychiatric disorders worldwide and therefore an important public health priority. The selection process of antidepressant treatment is primarily guided by trial and error, and the outcomes with current antidepressant strategies are disappointing. The biological background of the disease is heterogeneous with presumably multiple biological systems involved. With the aim to individualize antidepressant treatment, multiple candidate gene and a few genome-wide association studies have been performed, but so far with very limited success. To address the dynamic changes of depressive symptoms and their response to treatment, recent studies focus on epigenetic mechanisms, as these are modulated by environmental stimuli and adaptive to different stages of the disorder. In the present paper, after a brief summary of the most important results from pharmacogenetic studies in MDD, we comment on the current and potential future value of genetic testing as a biomarker of response to antidepressant treatment. The new and exciting field of epigenetic mechanisms in antidepressant drug treatment will be presented in the second part of this review.

Pharmacogenetics of antidepressant drugs: an update after almost 20 years of research

Major depressive disorder (MDD) is an emergent cause of personal and socio-economic burden, both for the high prevalence of the disorder and the unsatisfying response rate of the available antidepressant treatments. No reliable predictor of treatment efficacy and tolerance in the single patient is available, thus drug choice is based on a trial and error principle with poor clinical efficiency. Among modulators of treatment outcome, genetic polymorphisms are thought to explain a significant share of the inter-individual variability. The present review collected the main pharmacogenetic findings primarily about antidepressant response and secondly about antidepressant induced side effects, and discussed the main strengths and limits of both candidate and genome-wide association studies and the most promising methodological opportunities and challenges of the field. Despite clinical applications of antidepressant pharmacogenetics are not available yet, previous findings suggest that genotyping may be applied in the clinical practice. In order to reach this objective, further rigorous pharmacogenetic studies (adequate sample size, study of better defined clinical subtypes of MDD, adequate covering of the genetic variability), their combination with the results obtained through complementary methodologies (e.g., pathway analysis, epigenetics, transcriptomics, and proteomics), and finally cost-effectiveness trials are required.

Translational research in nicotine dependence

Nicotine addiction accounts for 4.9 million deaths each year. Furthermore, although smoking represents a significant health burden in the United States, at present there are only three FDA-approved pharmacotherapies currently on the market: (1) nicotine replacement therapy, (2) bupropion, and (3) varenicline. Despite this obvious gap in the market, the complexity of nicotine addiction in addition to the increasing cost of drug development makes targeted drug development prohibitive. Furthermore, using combinations of mouse and human studies, additional treatments could be developed from off-the-shelf, currently approved medication lists. This article reviews translational studies targeting manipulations of the cholinergic system as a viable therapeutic target for nicotine addiction.

Personalized medicine in major depressive disorder -- opportunities and pitfalls

The sequencing of the human genome in the early days of this millennium was greeted with great fanfare as this accomplishment was expected to revolutionize medicine and result in individualized treatments based on the genetic make-up of the patient. The ultimate promise of personalized medicine would be fulfilled with the identification of disease biomarkers that would be widely available for use in diagnosis and treatment. Progress, however, has been slow in providing disease biomarkers or approved diagnostic tests. This is true for major depressive disorder (MDD), despite its prevalence in the general population and the widespread acceptance of its biological basis. Studies using strategies like genome-wide association and candidate gene analyses have identified a number of possible biomarkers of MDD, including serum levels of neurotrophic factors, inflammatory cytokines and HPA axis hormones, but none have proven sufficiently powerful for clinical use. The lack of biologically based tests available for use in identifying patients with MDD is a significant impediment to personalized and more effective treatment, because it means diagnosis continues to be driven by subjective symptoms. While genetic studies of MDD have not yet led to diagnostic and treatment biomarkers, progress in determining the role of the genome in drug metabolism heralds the first effort in personalized prescribing for the antidepressants. The FDA suggested and approved genotyping tests for common variants of drug metabolism genes, such as the cytochrome p450s. By using these tests a physician can select an appropriate antidepressant for a given patient, as differences in clearance, half-life, and peak blood concentrations are controlled by genetic variability in drug metabolism. Personalization in drug choice can be achieved because these tests: (1) identify responders and non-responders; (2) provide alerts to possible adverse drug events; and (3) help optimize dose. Improved ways of diagnosing and prescribing effective treatments for MDD are needed, as the available methods are inadequate and symptom based. In the foreseeable future, further interrogation of the genome may serve as the basis for development of new personalized medicine strategies for diagnosis and treatment of MDD.

Epigenetic Modulation of Mood Disorders

BACKGROUND

Mood disorders are expressed in many heterogeneous forms, varying from anxiety to severe major clinical depression. The disorders are expressed in individual variety through manifestations governed by co-morbidities, symptom frequency, severity, and duration, and the effects of genes on phenotypes. The underlying etiologies of mood disorders consist of complex interactive operations of genetic and environmental factors. The notion of endophenotypes, which encompasses the markers of several underlying liabilities to the disorders, may facilitate efforts to detect and define, through staging, the genetic risks inherent to the extreme complexity of disease state.

AIMS

This review evaluates the role of genetic biomarkers in assisting clinical diagnosis, identification of risk factors, and treatment of mood disorders.

METHODS

Through a systematic assessment of studies investigating the epigenetic basis for mood disorders, the present review examines the interaction of genes and environment underlying the pathophysiology of these disorders.

RESULTS

The majority of research findings suggest that the notion of endophenotypes, which encompasses the markers of several underlying liabilities to the disorders, may facilitate efforts to detect and define, through staging, the genetic risks inherent to the extreme complexity of the disease states. Several strategies under development and refinement show the propensity for derivation of essential elements in the etiopathogenesis of the disorders affecting drug-efficacy, drug metabolism, and drug adverse effects, e.g., with regard to selective serotonin reuptake inhibitors. These include: transporter gene expression and genes encoding receptor systems, hypothalamic-pituitary-adrenal axis factors, neurotrophic factors, and inflammatory factors affecting neuroimmune function. Nevertheless, procedural considerations of pharmacogenetics presume the parallel investment of policies and regulations to withstand eventual attempts at misuse, thereby ensuring patient integrity.

CONCLUSIONS

Identification of genetic biomarkers facilitates choice of treatment, prediction of response, and prognosis of outcome over a wide spectrum of symptoms associated with affective states, thereby optimizing clinical practice procedures. Epigenetic regulation of primary brain signaling, e.g., serotonin and hypothalamic-pituitary-adrenal function, and factors governing their metabolism are necessary considerations. The participation of neurotrophic factors remains indispensable for neurogenesis, survival, and functional maintenance of brain systems.

Opioid genetics in the context of opioid switching

PURPOSE OF REVIEW

On a population level, there is no difference in terms of efficacy or side-effects between any of the strong opioids. On an individual level, however, there is marked variation in response to opioids. This review presents some of the recent advances in opioid pharmacogenetic studies.

RECENT FINDINGS

A growing number of genes have been studied in a number of different patient populations. Most data have come from candidate-gene studies. There have been two genome-wide association studies in pain and opioid response. The clinical and genetic complexity of response to opioids has limited the clinical applicability of the genetic results. Currently, interindividual variation in opioid response is managed clinically through a process known as opioid switching. The evidence supporting the efficacy of opioid switching is poor, mainly because randomized controlled trials in this area are lacking.

SUMMARY

Adequately powered studies to allow identification of genetic variants with small effect size and exploration of gene-gene interaction are needed. Integration of genetic analysis in clinical studies with carefully defined outcome measures will increase the likelihood of identifying clinical and genetic factors which can be used to predict opioid response.