Race, genetic ancestry and response to antidepressant treatment for major depression

Development of a differential treatment selection model for depression on consolidated and transformed clinical trial datasets

Major depressive disorder (MDD) is the leading cause of disability worldwide, yet treatment selection still proceeds via "trial and error". Given the varied presentation of MDD and heterogeneity of treatment response, the use of machine learning to understand complex, non-linear relationships in data may be key for treatment personalization. Well-organized, structured data from clinical trials with standardized outcome measures is useful for training machine learning models; however, combining data across trials poses numerous challenges. There is also persistent concern that machine learning models can propagate harmful biases. We have created a methodology for organizing and preprocessing depression clinical trial data such that transformed variables harmonized across disparate datasets can be used as input for feature selection. Using Bayesian optimization, we identified an optimal multi-layer dense neural network that used data from 21 clinical and sociodemographic features as input in order to perform differential treatment benefit prediction. With this combined dataset of 5032 individuals and 6 drugs, we created a differential treatment benefit prediction model. Our model generalized well to the held-out test set and produced similar accuracy metrics in the test and validation set with an AUC of 0.7 when predicting binary remission. To address the potential for bias propagation, we used a bias testing performance metric to evaluate the model for harmful biases related to ethnicity, age, or sex. We present a full pipeline from data preprocessing to model validation that was employed to create the first differential treatment benefit prediction model for MDD containing 6 treatment options.

Efficacy and Safety of Antidiabetic Agents for Major Depressive Disorder and Bipolar Depression: A Meta-Analysis of Randomized, Double-Blind, Placebo-Controlled Trials

BACKGROUND

This meta-analysis aimed to determine the efficacy and safety of antidiabetic agents in the treatment of major depressive disorder and bipolar depression.

METHODS

Randomized controlled trials (RCTs) of antidiabetic agents in major depressive disorder or bipolar depression were searched in three electronic databases and three clinical trial registry websites from their inception up to October 2023. The differences in changes in the depression rating scale scores from baseline to endpoint or pre-defined sessions, response rate, remission rate, rate of side effects and dropout rate between antidiabetic agents and placebo were meta-analyzed.

RESULTS

Six RCTs involving 399 participants were included in the final meta-analysis, which did not find that antidiabetics outperformed the placebo in reducing depressive symptoms. The standardized mean difference (SMD) in the depression scores from baseline to endpoint was 0.25 (95% CI -0.1, 0.61). However, a subgroup analysis found a significant difference between antidiabetics and placebos in reducing depressive symptoms in Middle Eastern populations, with an SMD of 0.89 (95% CI 0.44, 1.34).

CONCLUSIONS

The current meta-analysis does not support the efficacy of antidiabetics being superior to the placebo in the treatment of unipolar and bipolar depression. However, a subgroup analysis indicates that patients from the Middle East may benefit from adding an antidiabetic medication to their ongoing medication(s) for their depression. Larger studies with good-quality study designs are warranted.

A Bibliometric and Visual Analysis of Single Nucleotide Polymorphism Studies in Depression

BACKGROUND

Genetic polymorphism has been proven to have an important association with depression, which can influence the risk of developing depression, the efficacy of medications, and adverse effects via metabolic and neurological pathways. Nonetheless, aspects of the association between single nucleotide polymorphisms and depression have not been systematically investigated by bibliometric analysis.

OBJECTIVE

The aim of this study was to analyze the current status and trends of single nucleotide polymorphism research on depression through bibliometric and visual analysis.

METHODS

The Web of Science Core Collection was used to retrieve 10,043 articles that were published between 1998 and 2021. CiteSpace (6.1 R4) was used to perform collaborative network analysis, co-citation analysis, co-occurrence analysis, and citation burst detection.

RESULTS

The most productive and co-cited journals were the Journal of Affective Disorders and Biological Psychiatry, respectively, and an analysis of the references showed that the most recent research focused on the largest thematic cluster, "5-HT", reflecting the important research base in this area. "CYP2D6" has been in the spotlight since its emergence in 2009 and has become a research hotspot since its outbreak in 2019. However, "BDNF ", "COMT ", "older adults", "loci", and "DNA methylation" are also the new frontier of research, and some of them are currently in the process of exploration.

CONCLUSION

These findings offer a useful perspective on existing research and potential future approaches in the study of the association between single nucleotide polymorphisms and depression, which may assist researchers in selecting appropriate collaborators or journals.

Influence of Admixture on Phenotypes

Individuals of European descent have historically been the focus of genetic studies and possess relatively homogenous genomes. As a result, analytical methods have been developed and optimized with such genomes in mind. African-descent and Latino individuals generally possess genomes of greater architectural complexity due to mosaic genomic ancestry, which can extensively and intricately impact phenotypic expression. As such, genetic analyses of admixed individuals require that genetic admixture be quantified to accurately model the impact of genetic variation on phenotypic expression. In this overview, we explore how fundamental genetic concepts such as linkage disequilibrium and differential allele frequency interact with genetic admixture to uniquely influence phenotypes in admixed individuals. © 2023 The Authors. Current Protocols published by Wiley Periodicals LLC.

Utility of pharmacogenetic testing to optimise antidepressant pharmacotherapy in youth: a narrative literature review

Pharmacogenetics (PGx) is the study and application of how interindividual differences in our genomes can influence drug responses. By evaluating individuals' genetic variability in genes related to drug metabolism, PGx testing has the capabilities to individualise primary care and build a safer drug prescription model than the current "one-size-fits-all" approach. In particular, the use of PGx testing in psychiatry has shown promising evidence in improving drug efficacy as well as reducing toxicity and adverse drug reactions. Despite randomised controlled trials demonstrating an evidence base for its use, there are still numerous barriers impeding its implementation. This review paper will discuss the management of mental health conditions with PGx-guided treatment with a strong focus on youth mental illness. PGx testing in clinical practice, the concerns for its implementation in youth psychiatry, and some of the barriers inhibiting its integration in clinical healthcare will also be discussed. Overall, this paper provides a comprehensive review of the current state of knowledge and application for PGx in psychiatry and summarises the capabilities of genetic information to personalising medicine for the treatment of mental ill-health in youth.

Exome-wide association study of treatment-resistant depression suggests novel treatment targets

Treatment-resistant depression (TRD) is a severe form of major depressive disorder (MDD) with substantial public health impact and poor treatment outcome. Treatment outcome in MDD is significantly heritable, but genome-wide association studies have failed to identify replicable common marker alleles, suggesting a potential role for uncommon variants. Here we investigated the hypothesis that uncommon, putatively functional genetic variants are associated with TRD. Whole-exome sequencing data was obtained from 182 TRD cases and 2021 psychiatrically healthy controls. After quality control, the remaining 149 TRD cases and 1976 controls were analyzed with tests designed to detect excess burdens of uncommon variants. At the gene level, 5 genes, ZNF248, PRKRA, PYHIN1, SLC7A8, and STK19 each carried exome-wide significant excess burdens of variants in TRD cases (q < 0.05). Analysis of 41 pre-selected gene sets suggested an excess of uncommon, functional variants among genes involved in lithium response. Among the genes identified in previous TRD studies, ZDHHC3 was also significant in this sample after multiple test correction. ZNF248 and STK19 are involved in transcriptional regulation, PHYIN1 and PRKRA are involved in immune response, SLC7A8 is associated with thyroid hormone transporter activity, and ZDHHC3 regulates synaptic clustering of GABA and glutamate receptors. These results implicate uncommon, functional alleles in TRD and suggest promising novel targets for future research.

Breast cancer pharmacogenetics: a systematic review

Breast cancer was declared the most prevalent type of cancer in 2020. Among other factors, treatment response can be affected by genetic polymorphisms - which is the focus of pharmacogenetics - and ethnicity is also a contributing factor in this context. Relevant genes in disease treatment pathways were selected to evaluate treatment response from the pharmacogenetic perspective; polymorphism frequencies and ethnic and continental representation across the available literature were also assessed through a systematic review. The identified associations and gaps have been described in this study with the purpose that, in the future, treatments can be personalized and thus be more effective, safer, and accessible to all.

Exercise improves depression through positive modulation of brain-derived neurotrophic factor (BDNF). A review based on 100 manuscripts over 20 years

The aim of this review was to explore the relevant neurobiology and the association between peripheral levels of brain-derived neurotrophic factor (BDNF) and acute and short to long-term exercise regimes, as well as its relation to depression and antidepressant treatment. A 20-year literature search was conducted. The screening process resulted in 100 manuscripts. Antidepressants as well as acute exercise, particularly high-intensity, elevates BDNF in healthy humans and clinical populations, as evidenced from aerobic and resistance-based studies. Although exercise is increasingly recognised in the management of depression, acute and short-term exercise studies have failed to establish a relationship between the severity of depression and changes in peripheral BDNF. The latter rapidly returns to baseline, possibly indicating a quick re-uptake by the brain, aiding its neuroplasticity functions. The timescale of administration needed for the antidepressants to stimulate biochemical changes is longer than similar increases with acute exercise.

Psychopharmacoepidemiology of antidepressant medications among homeless and unstably housed service users in the Veterans Affairs healthcare system

OBJECTIVE

This study conducted a pharmacoepidemiologic examination of antidepressant prescription patterns in homeless and unstably housed (HUH) populations.

METHODS

Data were analyzed on over 2.6 million veterans from the U.S. Department of Veterans Affairs (VA), the largest provider of healthcare for HUH veterans and a system that does not require healthcare insurance.

RESULTS

Multivariable analyses revealed that HUH veterans with depression and PTSD were less likely to receive an antidepressant Rx compared to their stably housed (SH) counterparts with these conditions (OR = 0.77, 99% CI = 0.74-0.79; and OR = 0.87, 99% CI = 0.84-0.90, respectively). Antidepressants were mostly prescribed in specialty mental health care settings, but HUH veterans were less likely to be prescribed antidepressants in primary care settings than SH veterans. In the total sample, the 40-49 age group, female sex, VA service-connected disability, outpatient mental health visits, and emergency department visits were positively associated with any antidepressant Rx. Nearly all psychiatric diagnoses were more associated with prescription of selective serotonin reuptake inhibitors/serotonin and norepinephrine reuptake inhibitors (SSRIs/SNRIs) than tricyclic antidepressants.

CONCLUSION

These findings highlight socioeconomic disparities in antidepressant Rx in a healthcare system that does not rely on insurance and suggest clinical challenges with antidepressant prescriptions in HUH populations.

COVID-19 Prognosis in Association with Antidepressant Use

INTRODUCTION

Various subtypes of severe acute respiratory syndrome coronavirus 2 and variations among immune systems in different ethnicities need to be considered to understand the outcomes of coronavirus disease 2019 (COVID-19). This study aimed to provide evidence for the association between the use of antidepressants and the severity of COVID-19.

METHODS

We used the National Health Information Data-COVID database. Patients with one or more prescriptions of any antidepressant were selected as the exposure group. Detailed analyses were performed to determine the type of medication associated with the prognosis.

RESULTS

The use of selective serotonin reuptake inhibitors (SSRIs) was associated with a lower risk of severe outcomes of COVID-19, whereas the use of tricyclic antidepressants (TCAs) increased the risk of poor prognosis of COVID-19. Detailed analyses showed that escitalopram was significantly associated with better clinical outcomes, and nortriptyline was linked to more severe COVID-19 outcomes.

CONCLUSION

This study revealed an association between antidepressants and COVID-19 prognosis. SSRIs were significantly associated with a lower risk of severe outcomes, whereas TCAs were related to the poor prognosis of COVID-19.

Transdiagnostic and functional predictors of depression severity and trajectory in the Penn state psychiatry clinical assessment and rating evaluation system (PCARES) registry

BACKGROUND

Timely, accurate diagnosis and subsequent identification of risk factors for depression that is difficult-to-treat can aid in decreasing the burden of depressive illness and reducing probability of future disability. We aimed to identify sociodemographic, clinical, and functional factors that predict depression severity over one year in a real-world, naturalistic, transdiagnostic clinical sample. A subset sample with moderate depression was examined to determine the magnitude of improvement.

METHODS

The Penn State Psychiatry Clinical Assessment and Rating System (PCARES) Registry houses data from systematically-structured patient-reported outcomes and clinical data from an Electronic Medical Record (EMR) gathered during routine clinical care of patients seeking mental health care at a mid-Atlantic clinic. Self-report symptom and functional measures were obtained, and sociodemographic features and clinical diagnoses were extracted from the EMR from 1,766 patients between 2/6/2016 to 9/30/2019. The Patient Health Questionnaire 9 (PHQ-9) depression scale was obtained at each visit. Using a discrete mixture clustering model, the study population was divided into five longitudinal trajectory groups, termed depression severity groups, based on intra-individual PHQ-9 score trajectories over one year. Multinomial logistic regression models were estimated to evaluate associations between characteristics and the likelihood of depression severity group membership. To determine the magnitude of improvement, predictors of the slope of the PHQ-9 trajectory were examined for patients with moderate depression.

RESULTS

The strongest predictors of high depression severity over one year were poor functioning, high transdiagnostic DSM-5 Level 1 crosscutting symptom score, diagnosis of Post-Traumatic Stress Disorder (PTSD), public/self-pay insurance, female gender, and non-White race. Among the subset of patients with moderate depression, strong predictors of improvement were commercial insurance and exposure to trauma; the strongest predictors of worsening were high functional impairment, high transdiagnostic Level 1 symptom score, diagnosis of PTSD, diagnosis of bipolar disorder, and marital status of single or formerly married; depression-specific symptom measures were not predictive.

LIMITATIONS

Limitations include inferring education and income status from zip code level-data, the non-random missingness of data, and the use of diagnoses collected from the electronic medical record.

CONCLUSION

Functional impairment, transdiagnostic measures of symptom burden, and insurance status are strong predictors of depression severity and poor outcome.

Sociodemographic Differences in Pain Medication Usage and Healthcare Provider Utilization Among Adults With Chronic Low Back Pain

Chronic low back pain (cLBP) is the most common reason for individual suffering and health care utilization in adults. Ample evidence suggests sociodemographic variables and socioeconomic status (SES) influence pain. However, a framework informing associations on race, SES, and the utilization of pharmacologic therapies and provider type are limited—particularly in cLBP. Thus, this study examined the extent to which sociodemographic (i.e., age, race, and gender) and socioeconomic factors (i.e., national area deprivation index, NADI) influence pain treatment (i.e., NSAIDs, opioids, antidepressants, and non-NSAIDs) and provider utilization for cLBP (i.e., no provider care, primary care, or tertiary care). Eligible participants with cLBP completed a series of questionnaires. Of the 174 participants, 58% were women, 59% were non-Hispanic Black (NHB), and the mean age was 46.10 (SD 13.58). Based on NADI distributions by race, NHB participants lived in more socioeconomically disadvantaged neighborhoods (p &lt; 0.001) than non-Hispanic White (NHW) adults. Results suggested that the use of one or more pharmacologic therapies was associated with race (p = 0.021). Specifically, NHW adults were two times more likely to take one or more pharmacologic therapies than NHBs (p = 0.009). NHWs were also more likely to use NSAIDs (p = 0.041) and antidepressants (p &lt; 0.001) than NHBs. Furthermore, provider utilization was significantly associated with gender (p = 0.037) and age (p = 0.018); which suggests older women were more likely to use primary or tertiary care. Findings from this study expand on the existing literature as it relates to associations between disparities in access to healthcare providers and access to medications. Future research should seek to understand differences in age and utilization of primary or tertiary care providers and continue to examine the influence of sociodemographic and SES factors to cLBP and compare with other types of chronic pain.

The increasing challenge of the possible impact of ethnicity on psychopharmacology

Ethnic differences may significantly influence the outcome of psychopharmacological treatment, in terms of prescription, adherence, clinical response, emergence of side effects, as well as pharmacokinetics and pharmacodynamics. The purpose of this review was to explore the available literature in order to provide general suggestions to help clinicians in choosing the best therapeutic option for patients, taking into account ethnicity. Although findings are sometimes controversial, the overall published studies suggest that ethnicities other than Caucasians tend to show a lower response to antidepressants and a reduced compliance. Africans tend to be more prescribed with antipsychotics, probably due to cultural stereotypes, except with clozapine, probably for their chronic benign neutropenia. Asians usually require less antipsychotic dosages than Caucasians. The differential response and side effect profile of antidepressants and antipsychotics have been related to individual intrinsic factors, to genetic make-up, but also to cultural and contextual variables. Interestingly, albeit limited data suggest ethnic-related genetic heterogeneity at the level of the serotonin transporters, the cytochromes and some neuroreceptors. Taken together, no conclusive findings are available about the role and impact of ethnicity in psychopharmacology. One of the main problems is that the majority of the studies in psychopharmacology have been conducted on Caucasians, so that there is an urgent need to have data in other populations. Furthermore, in the era of precision medicine, the role of ethnicity may be also supported by genetic analysis.

Intrinsic reward circuit connectivity profiles underlying symptom and quality of life outcomes following antidepressant medication: a report from the iSPOT-D trial

There is a critical need to better understand the neural basis of antidepressant medication (ADM) response with respect to both symptom alleviation and quality of life (QoL) in major depressive disorder (MDD). Reward neurocircuitry has been implicated in QoL, the neural basis of MDD, and the mechanisms of ADM response. Yet, we do not know whether change in reward neurocircuitry as a function of ADM is associated with change in symptoms and QoL. To address this gap in knowledge, we analyzed data from 128 patients with MDD who participated in the iSPOT-D trial and were assessed with functional neuroimaging pre- and post-ADM treatment (randomized to sertraline, venlafaxine-XR, or escitalopram). 58 matched healthy controls were scanned at the same time points. We quantified functional connectivity (FC) of reward neurocircuitry using nucleus accumbens (NAc) seed regions of interest, and then characterized how changes in FC relate to symptom response (primary outcome) and QoL response (secondary outcome). Symptom responders showed an increase in NAc-dorsal anterior cingulate cortex (ACC) FC relative to non-responders (p < 0.001) which was associated with improvement in physical QoL (p < 0.0003), and a decrease in NAc-inferior parietal lobule FC relative to controls (p < 0.001). QoL response was characterized by increases in FC between NAc-ventral ACC for environmental, NAc-thalamus for physical, and NAc-paracingulate gyrus for social domains (p < 0.001). Symptom responders to sertraline were distinguished by a decrease in NAc-insula FC (p < 0.001) and to venlafaxine-XR by an increase in NAc-inferior temporal gyrus FC (p < 0.005). Findings suggest that change in reward neurocircuitry may underlie differential ADM response profiles with respect to symptoms and QoL in depression.

Smoking Cessation Pharmacotherapy Based on Genetically-Informed Biomarkers: What is the Evidence?

INTRODUCTION

Pharmacogenomic studies have used genetic variants to identify smokers likely to respond to pharmacological treatments for smoking cessation.

METHODS

We performed a systematic review and meta-analysis of primary and secondary analyses of trials of smoking cessation pharmacotherapies. Eligible were trials with data on a priori selected single nucleotide polymorphisms, replicated non-single nucleotide polymorphisms, and/or the nicotine metabolite ratio. We estimated the genotype × treatment interaction as the ratio of risk ratios (RRR) for treatment effects across genotype groups.

RESULTS

We identified 18 trials (N = 9017 participants), including 40 active (bupropion, nicotine replacement therapy [NRT], varenicline, or combination therapies) versus placebo comparisons and 16 active versus active comparisons. There was statistical evidence of heterogeneity across rs16969968 genotypes in CHRNA5 with regard to both 6-month abstinence and end-of-treatment abstinence in non-Hispanic black smokers and end-of-treatment abstinence in non-Hispanic white smokers. There was also heterogeneity across rs1051730 genotypes in CHRNA3 with regard to end-of-treatment abstinence in non-Hispanic white smokers. There was no clear statistical evidence for other genotype-by-treatment combinations. Compared with placebo, NRT was more effective among non-Hispanic black smokers with rs16969968-GG with regard to both 6-month abstinence (RRR for GG vs. GA or AA, 3.51; 95% confidence interval [CI] = 1.19 to 10.30) and end-of-treatment abstinence (RRR for GG vs. GA or AA, 5.84; 95% CI = 1.89 to 18.10). Among non-Hispanic white smokers, NRT effectiveness relative to placebo was comparable across rs1051730 and rs169969960 genotypes.

CONCLUSIONS

We did not identify widespread differential effects of smoking cessation pharmacotherapies based on genotype. The quality of the evidence is generally moderate.

IMPLICATIONS

Although we identified some evidence of genotype × treatment interactions, the vast majority of analyses did not provide evidence of differential treatment response by genotype. Where we find some evidence, these results should be considered preliminary and interpreted with caution because of the small number of contributing trials per genotype comparison, the wide confidence intervals, and the moderate quality of evidence. Prospective trials and individual-patient data meta-analyses accounting for heterogeneity of treatment effects through modeling are needed to assess the clinical utility of genetically informed biomarkers to guide pharmacotherapy choice for smoking cessation.

A novel study design for investigating relapse prevention in major depressive disorder: Preliminary data from the open-label period of a phase 4 vortioxetine study

BACKGROUND

Traditional randomized withdrawal studies have assessed the efficacy of antidepressants for reducing relapse and recurrence of major depressive episodes (MDEs) but have not compared dose reduction, increase, or maintenance within the same study.

METHODS

Here we present the development, implementation, and preliminary data from the open-label period of an ongoing phase 4, non-traditional, randomized withdrawal study. Designed to evaluate the efficacy of vortioxetine across its approved dose range for relapse prevention, the study enrolled adult patients with recurrent major depressive disorder (MDD), Montgomery-Åsberg Depression Rating Scale (MADRS) ≥ 26, and history of ≥2 MDEs. After a 16-week, open-label, fixed-dose (vortioxetine 10 mg once daily) period, patients meeting response criteria (≥50% reduction in MADRS total score, Weeks 8-16) and remission criteria (MADRS total score ≤12, Weeks 14 and 16) were randomized to vortioxetine 5, 10, or 20 mg, or placebo in a 32-week double-blind treatment period.

RESULTS

Of 1106 patients enrolled, 510 completed the open-label period (mean age: 45.7 years; mean MADRS = 5.0; predominantly female, white, and never smokers) and were eligible for randomization in the ongoing double-blind period.

LIMITATIONS

Study is ongoing; only data from the open-label period are available for evaluation.

CONCLUSIONS

Preliminary analysis suggests that patient baseline characteristics were not a factor in response to and stabilization with vortioxetine during the open-label period. The lack of flexibility in dosing, however, may have reduced the number of patients qualifying for randomization. This study design may provide useful information for optimizing the long-term efficacy and tolerability of vortioxetine treatment for MDD.

A review of clinical pharmacogenetics Studies in African populations

Effective interventions and treatments for complex diseases have been implemented globally, however, coverage in Africa has been comparatively lower due to lack of capacity, clinical applicability and knowledge on the genetic contribution to disease and treatment. Currently, there is a scarcity of genetic data on African populations, which have enormous genetic diversity. Pharmacogenomics studies have the potential to revolutionise treatment of diseases, therefore, African populations are likely to benefit from these approaches to identify likely responders, reduce adverse side effects and optimise drug dosing. This review discusses clinical pharmacogenetics studies conducted in African populations, focusing on studies that examined drug response in complex diseases relevant to healthcare. Several pharmacogenetics associations have emerged from African studies, as have gaps in knowledge.

Personalized Psychiatry and Depression: The Role of Sociodemographic and Clinical Variables

Despite several pharmacological options, the clinical outcomes of major depressive disorder (MDD) are often unsatisfactory. Personalized psychiatry attempts to tailor therapeutic interventions according to each patient's unique profile and characteristics. This approach can be a crucial strategy in improving pharmacological outcomes in MDD and overcoming trial-and-error treatment choices. In this narrative review, we evaluate whether sociodemographic (i.e., gender, age, race/ethnicity, and socioeconomic status) and clinical [i.e., body mass index (BMI), severity of depressive symptoms, and symptom profiles] variables that are easily assessable in clinical practice may help clinicians to optimize the selection of antidepressant treatment for each patient with MDD at the early stages of the disorder. We found that several variables were associated with poorer outcomes for all antidepressants. However, only preliminary associations were found between some clinical variables (i.e., BMI, anhedonia, and MDD with melancholic/atypical features) and possible benefits with some specific antidepressants. Finally, in clinical practice, the assessment of sociodemographic and clinical variables considered in our review can be valuable for early identification of depressed individuals at high risk for poor responses to antidepressants, but there are not enough data on which to ground any reliable selection of specific antidepressant class or compounds. Recent advances in computational resources, such as machine learning techniques, which are able to integrate multiple potential predictors, such as individual/ clinical variables, biomarkers, and genetic factors, may offer future reliable tools to guide personalized antidepressant choice for each patient with MDD.

Translating GWAS findings into therapies for depression and anxiety disorders: gene-set analyses reveal enrichment of psychiatric drug classes and implications for drug repositioning

BACKGROUND

Depression and anxiety disorders (AD) are the first and sixth leading causes of disability worldwide. Despite their high prevalence and significant disability resulted, there are limited advances in new drug development. Recently, genome-wide association studies (GWAS) have greatly advanced our understanding of the genetic basis underlying psychiatric disorders.

METHODS

Here we employed gene-set analyses of GWAS summary statistics for drug repositioning. We explored five related GWAS datasets, including two on major depressive disorder (MDD2018 and MDD-CONVERGE, with the latter focusing on severe melancholic depression), one on AD, and two on depressive symptoms and neuroticism in the population. We extracted gene-sets associated with each drug from DSigDB and examined their association with each GWAS phenotype. We also performed repositioning analyses on meta-analyzed GWAS data, integrating evidence from all related phenotypes.

RESULTS

Importantly, we showed that the repositioning hits are generally enriched for known psychiatric medications or those considered in clinical trials. Enrichment was seen for antidepressants and anxiolytics but also for antipsychotics. We also revealed new candidates or drug classes for repositioning, some of which were supported by experimental or clinical studies. For example, the top repositioning hit using meta-analyzed p values was fendiline, which was shown to produce antidepressant-like effects in mouse models by inhibition of acid sphingomyelinase.

CONCLUSION

Taken together, our findings suggest that human genomic data such as GWAS are useful in guiding drug discoveries for depression and AD.

A Review of Mental Health and Mental Health Care Disparities Research: 2011-2014

Racial/ethnic minorities in the United States are more likely than Whites to have severe and persistent mental disorders and less likely to access mental health care. This comprehensive review evaluates studies of mental health and mental health care disparities funded by the National Institute of Mental Health (NIMH) to provide a benchmark for the 2015 NIMH revised strategic plan. A total of 615 articles were categorized into five pathways underlying mental health care and three pathways underlying mental health disparities. Identified studies demonstrate that socioeconomic mechanisms and demographic moderators of disparities in mental health status and treatment are well described, as are treatment options that support diverse patient needs. In contrast, there is a need for studies that focus on community- and policy-level predictors of mental health care disparities, link discrimination- and trauma-induced neurobiological pathways to disparities in mental illness, assess the cost effectiveness of disparities reduction programs, and scale up culturally adapted interventions.

Race reporting and disparities in clinical trials on Alzheimer's disease: A systematic review

INTRODUCTION

Race is an important health determinant and should adequately be considered in research and drug development protocols targeting Alzheimer's disease (AD).

METHODS

A systematic review of available randomized controlled trials (RCTs) on the currently marketed treatments for AD was conducted with the aim of 1) documenting the reporting of race, and 2) exploring the impact of race on the efficacy and safety/tolerability of the considered medications.

RESULTS

Overall, 59.2% of the 49 retained RCTs reported information concerning the race of participants. Only a striking minority of enrolled patients was constituted of blacks and Hispanics. None on the retained studies reported results on the efficacy and safety/tolerability of the tested treatment separately for racial groups nor performed sensitivity analyses accounting for the race of participants.

DISCUSSION

Race has insufficiently been reported in previous interventional studies on AD. Its potential association with the effectiveness and safety/tolerability of the tested medications has completely been neglected.

Effects of Depression and Antidepressant Use on Cognitive Deficits and Functional Cognition Following Severe Traumatic Brain Injury

OBJECTIVE

To use a Rehabilomics framework to evaluate relations hips between post-traumatic brain injury (TBI) depression (PTD) and potential associated factors, including antidepressant use, on cognitive recovery following severe TBI.

PARTICIPANTS

Severe TBI survivors (n = 154), recruited from a level 1 trauma center.

DESIGN

Prospective cohort study with assessments at 6 and 12 months postinjury.

MAIN MEASURES

Patient Health Questionnaire-9 (PTD symptoms); cognitive composite score from a neuropsychological assessment battery (cognitive impairment); and Functional Independence Measure-Cognition (FIM-Cog, self-reported functional cognition).

RESULTS

Individuals with and without PTD did not differ with respect to cognitive impairment. However, antidepressant use, regardless of PTD status, was associated with cognitive impairment. Individuals with PTD reported lower FIM-Cog scores at both time points compared with those without PTD. In a post hoc longitudinal analysis, individuals with late-onset PTD had worse cognitive impairment.

CONCLUSION

These results suggest that antidepressant use impairs cognition among individuals without PTD. Also, PTD did not directly affect cognitive impairment but may affect functional cognitive limitations through self-evaluation and apathy/motivation factors.

Pharmacotherapy for smoking cessation: effects by subgroup defined by genetically informed biomarkers

BACKGROUND

Smoking cessation therapies are not effective for all smokers, and researchers are interested in identifying those subgroups of individuals (e.g. based on genotype) who respond best to specific treatments.

OBJECTIVES

To assess whether quit rates vary by genetically informed biomarkers within pharmacotherapy treatment arms and as compared with placebo. To assess the effects of pharmacotherapies for smoking cessation in subgroups of smokers defined by genotype for identified genome-wide significant polymorphisms.

SEARCH METHODS

We searched the Cochrane Tobacco Addiction Group specialised register, clinical trial registries, and genetics databases for trials of pharmacotherapies for smoking cessation from inception until 16 August 2016.

SELECTION CRITERIA

We included randomised controlled trials (RCTs) that recruited adult smokers and reported pharmacogenomic analyses from trials of smoking cessation pharmacotherapies versus controls. Eligible trials included those with data on a priori genome-wide significant (P < 5 × 10-8) single-nucleotide polymorphisms (SNPs), replicated non-SNPs, and/or the nicotine metabolite ratio (NMR), hereafter collectively described as biomarkers.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures expected by Cochrane. The primary outcome was smoking abstinence at six months after treatment. The secondary outcome was abstinence at end of treatment (EOT). We conducted two types of meta-analyses- one in which we assessed smoking cessation of active treatment versus placebo within genotype groups, and another in which we compared smoking cessation across genotype groups within treatment arms. We carried out analyses separately in non-Hispanic whites (NHWs) and non-Hispanic blacks (NHBs). We assessed heterogeneity between genotype groups using T², I², and Cochrane Q statistics.

MAIN RESULTS

Analyses included 18 trials including 9017 participants, of whom 6924 were NHW and 2093 NHB participants. Data were available for the following biomarkers: nine SNPs (rs1051730 (CHRNA3); rs16969968, rs588765, and rs2036527 (CHRNA5); rs3733829 and rs7937 (in EGLN2, near CYP2A6); rs1329650 and rs1028936 (LOC100188947); and rs215605 (PDE1C)), two variable number tandem repeats (VNTRs; DRD4 and SLC6A4), and the NMR. Included data produced a total of 40 active versus placebo comparisons, 16 active versus active comparisons, and 64 between-genotype comparisons within treatment arms.For those meta-analyses showing statistically significant heterogeneity between genotype groups, we found the quality of evidence (GRADE) to be generally moderate. We downgraded quality most often because of imprecision or risk of bias due to potential selection bias in genotyping trial participants. Comparisons of relative treatment effects by genotypeFor six-month abstinence, we found statistically significant heterogeneity between genotypes (rs16969968) for nicotine replacement therapy (NRT) versus placebo at six months for NHB participants (P = 0.03; n = 2 trials), but not for other biomarkers or treatment comparisons. Six-month abstinence was increased in the active NRT group as compared to placebo among participants with a GG genotype (risk ratio (RR) 1.47, 95% confidence interval (CI) 1.07 to 2.03), but not in the combined group of participants with a GA or AA genotype (RR 0.43, 95% CI 0.15 to 1.26; ratio of risk ratios (RRR) GG vs GA or AA of 3.51, 95% CI 1.19 to 10.3). Comparisons of treatment effects between genotype groups within pharmacotherapy randomisation armsFor those receiving active NRT, treatment was more effective in achieving six-month abstinence among individuals with a slow NMR than among those with a normal NMR among NHW and NHB combined participants (normal NMR vs slow NMR: RR 0.54, 95% CI 0.37 to 0.78; n = 2 trials). We found no such differences in treatment effects between genotypes at six months for any of the other biomarkers among individuals who received pharmacotherapy or placebo.

AUTHORS' CONCLUSIONS

We did not identify widespread differential treatment effects of pharmacotherapy based on genotype. Some genotype groups within certain ethnic groups may benefit more from NRT or may benefit less from the combination of bupropion with NRT. The reader should interpret these results with caution because none of the statistically significant meta-analyses included more than two trials per genotype comparison, many confidence intervals were wide, and the quality of this evidence (GRADE) was generally moderate. Although we found evidence of superior NRT efficacy for NMR slow versus normal metabolisers, because of the lack of heterogeneity between NMR groups, we cannot conclude that NRT is more effective for slow metabolisers. Access to additional data from multiple trials is needed, particularly for comparisons of different pharmacotherapies.

African-American representation in family and twin studies of mood and anxiety disorders: A systematic review

PURPOSE

Mood and anxiety disorders are common and disabling psychiatric disorders with known heritable risk factors. But the extent to which their heritability and familial risks can be generalized across ethnic/racial groups is still largely unknown, but remains of considerable scientific and clinical interest. The main objective in this review was to evaluate African-American (AA) representation in family and twin studies of major mood and anxiety disorders.

METHOD

We conducted key word-driven computerized searches in MEDLINE and PsycINFO and manual searches from reference lists of selected articles. Search parameters included family or twin studies, mood or anxiety disorders, and familial aggregation or heritability. US-based studies published from 1980 to 2015 were included.

RESULTS

The final selection yielded 209 studies, of which 88 did not report race/ethnicity or only reported Caucasian/white race. Of the remaining 121 studies, 66% did not include AAs, 24% included 1-10% AA, 8% included greater than 10% AA and 2 studies were exclusively AA. These trends were similar across study type, disorder and time periods spanning 35 years.

LIMITATIONS

Small samples, including the large number of studies without race/ethnicity reports, limited detailed analyses of change across time by disorder and study type. Adoption studies were not included in this review.

CONCLUSIONS

Underrepresentation of AAs in family and twin studies of affective disorders is substantial and can limit generalizability of established heritability and familial risk estimates across clinical and research settings. Additional twin and family studies focusing on AAs can be of benefit in closing this gap.

Antidepressant Use in the Elderly Is Associated With an Increased Risk of Dementia

A retrospective cohort study was conducted including 3688 patients age 60 years or older without dementia enrolled in a depression screening study in primary care clinics. Information on antidepressant use and incident dementia during follow-up was retrieved from electronic medical records. The Cox proportional hazard models were used to compare the risk for incident dementia among 5 participant groups: selective serotonin re-uptake inhibitors (SSRI) only, non-SSRI only (non-SSRI), mixed group of SSRI and non-SSRI, not on antidepressants but depressed, and not on antidepressants and not depressed. SSRI and non-SSRI users had significantly higher dementia risk than the nondepressed nonusers (hazard ratio [HR]=1.83, P=0.0025 for SSRI users and HR=1.50, P=0.004 for non-SSRI users). In addition, SSRIs users had significantly higher dementia risk than non-users with severe depression (HR=2.26, P=0.0005). Future research is needed to confirm our results in other populations and to explore potential mechanism underlying the observed association.

Genetic ancestry as an effect modifier of naltrexone in smoking cessation among African Americans: an analysis of a randomized controlled trial

OBJECTIVES

To determine whether there were differential quit rates between African Americans (AA) and European Americans with the experimental treatment naltrexone, and examine the role of genetic ancestry on these outcomes among AAs.

METHODS

Data from a previous randomized trial of 315 smokers to naltrexone versus placebo were reanalyzed using West African (WA) genetic ancestry to define subpopulations. Logistic regression models were used to estimate treatment effects on early and end of treatment quit rates, by race and WA ancestry.

RESULTS

Among European Americans (n=136), naltrexone significantly increased quit rates at 4 weeks (62 vs. 43%, P=0.03) with directional, but not statistically significant effects at 12 weeks (30 vs. 18%, P=0.12). In contrast, among the AAs (n=95), quit rates did not differ between naltrexone and placebo groups at either interval (4 weeks: 43 vs. 32%, P=0.27; 12 weeks: 22 vs. 18%, P=0.60). A median split was conducted in AAs for WA ancestry. Among AAs with low WA ancestry, quit rates were significantly higher with naltrexone compared with placebo (60 vs. 27%, P=0.03). There was no advantage in quit rates with naltrexone for the high WA ancestry group.

CONCLUSION

Naltrexone efficacy for smoking cessation varies across AA individuals with different levels of WA ancestry. These results suggest that genetic background may partially explain racial differences in drug response.

Genome-wide association studies in pharmacogenomics of antidepressants

Major depressive disorder (MDD) is one of the most common psychiatric disorders worldwide. Doctors must prescribe antidepressants based on educated guesses due to the fact that it is unmanageable to predict the effectiveness of any particular antidepressant in an individual patient. With the recent advent of scientific research, the genome-wide association study (GWAS) is extensively employed to analyze hundreds of thousands of single nucleotide polymorphisms by high-throughput genotyping technologies. In addition to the candidate-gene approach, the GWAS approach has recently been utilized to investigate the determinants of antidepressant response to therapy. In this study, we reviewed GWAS studies, their limitations and future directions with respect to the pharmacogenomics of antidepressants in MDD.

Prediction of treatment outcomes in psychiatry--where do we stand ?

Psychiatric treatment relies on a solid armamentarium of pharmacologic and nonpharmacologic treatment modalities that perform reasonably well for many patients but leave others in a state of chronic disability or troubled by problematic side effects. Treatment planning in psychiatry remains an art that depends on considerable trial and error. Thus, there is an urgent need for better tools that will provide a means for matching individual patients with the most effective treatments while minimizing the risk of adverse events. This review will consider the current state of the science in predicting treatment outcomes in psychiatry. Genetic and other biomarkers will be considered alongside clinical diagnostic, and family history data. Problems inherent in prediction medicine will also be discussed, along with recent developments that support the hope that psychiatry can do a better job in quickly identifying the best treatments for each patient.

Racial differences in adherence and response to combined treatment for full and subthreshold post-traumatic stress disorder and alcohol use disorders: A secondary analysis

We conducted a secondary data analysis to examine whether there were racial differences in adherence and treatment outcomes for participants with co-occurring full and subthreshold post-traumatic stress disorder (PTSD) and alcohol/substance use disorders (A/SUD) who were treated with Seeking Safety (a cognitive-behavioral therapy) and sertraline or Seeking Safety and placebo as part of a clinical trial. Bivarate analyses examined the association between race and adherence, and generalized estimating equations assessed whether race moderated the effect of combination treatment on PTSD and alcohol use outcomes. Except for education, there were no statistically significant racial differences in baseline demographic and psychiatric characteristics. African Americans and Caucasians were equally adherent in number of psychotherapy and medication sessions attended and medication compliance. After controlling for baseline demographics and psychiatric symptoms, however, a race by treatment condition interaction emerged suggesting that African Americans who received the Seeking Safety and sertraline treatment had significantly lower PTSD symptom severity posttreatment and at six months follow-up compared to their counterparts who received Seeking Safety and placebo. No differential effect of treatment condition was found for Caucasians. Moreover, results indicated that a diagnosis of major depressive disorder negatively impacted PTSD symptom recovery for African American participants but not for Caucasians. In conclusion, no differences emerged between African Americans and Caucasians in adherence to combination treatments for PTSD and A/SUD. Findings also suggest assessment and treatment of MDD among African Americans may improve treatment outcomes. More research is needed to determine whether the differential response to Seeking Safety and sertraline among African Americans compared to Caucasians can be replicated.

Pharmacogenetics and analgesic effects of antidepressants in chronic pain management

Antidepressants are widely administered to chronic pain patients, but there is large interindividual variability in their efficacy and adverse effect rates that may be attributed to genetic factors. Studies have attempted to determine the impact of genetic polymorphisms in enzymes and transporters that are involved in antidepressant pharmacokinetics, for example, cytochrome P450 and P-gp. The impacts of genetic polymorphisms in the targets of antidepressants, such as the serotonin receptor or transporter, the noradrenaline transporter and the COMT and monoamine oxydase enzymes, have also been described. This manuscript discusses the current knowledge of the influence of genetic factors on the plasma concentrations, efficacy and adverse effects of the major antidepressants used in pain management.

Prediction of treatment outcomes in psychiatry--where do we stand ?

Psychiatric treatment relies on a solid armamentarium of pharmacologic and nonpharmacologic treatment modalities that perform reasonably well for many patients but leave others in a state of chronic disability or troubled by problematic side effects. Treatment planning in psychiatry remains an art that depends on considerable trial and error. Thus, there is an urgent need for better tools that will provide a means for matching individual patients with the most effective treatments while minimizing the risk of adverse events. This review will consider the current state of the science in predicting treatment outcomes in psychiatry. Genetic and other biomarkers will be considered alongside clinical diagnostic, and family history data. Problems inherent in prediction medicine will also be discussed, along with recent developments that support the hope that psychiatry can do a better job in quickly identifying the best treatments for each patient.