Genome-wide association study and polygenic risk score analysis of esketamine treatment response

Association between polygenic risk scores combined with clinical characteristics and antidepressant efficacy

BACKGROUND

While millions of people suffer from major depressive disorder (MDD), research has shown that individual differences in antidepressant efficacy exist, potentially attributable to various factors. Polygenic risk scores (PRSs) carry clinical potential, but associations with treatment response are seldom reported. Here, we examined whether PRSs for MDD and schizophrenia (SCZ) are associated with antidepressant effectiveness and the influence of other factors.

METHODS

A total of 999 patients were included, and the PRSs for the MDD and SCZ were calculated. The main outcome was a change in the 17-item Hamilton Depression Rating Scale (HAMD17) scores from before to after 2-week treatment. The Mann-Whitney test, Spearman correlation analysis, multiple stepwise linear regression analysis, and interaction analysis were used for statistical analysis.

RESULTS

In the 912 subjects passing quality control, a difference in the HAM-D17 score reduction rate between the MDD phenotype PRS (MDD-PRS) high-risk and the low-risk groups was discovered (P = 0.009), and a correlation was found between the MDD-PRS and the HAM-D17 score reduction rate (r = -0.075, P = 0.024). Moreover, antidepressant efficacy was related to MDD-PRS (β = -4.086, P = 0.039), the Snaith-Hamilton Pleasure Scale-total score (β = -0.009, P = 0.005), and non-first episode (β = -0.039, P < 0.001). However, the result of the interaction analysis was nonsignificant.

LIMITATIONS

The main limitation was that only 1309 targeted genes were selected based on pathways known to be involved in MDD and/or antidepressant effects.

CONCLUSION

These findings suggest a difference in antidepressant efficacy between patients in different MDD-PRS groups. Moreover, the MDD-PRS combined with clinical characteristics partially explained inter-individual differences in antidepressant efficacy.

Pharmacogenomic scores in psychiatry: systematic review of current evidence

In the past two decades, significant progress has been made in the development of polygenic scores (PGSs). One specific application of PGSs is the development and potential use of pharmacogenomic- scores (PGx-scores) to identify patients who can benefit from a specific medication or are likely to experience side effects. This systematic review comprehensively evaluates published PGx-score studies in psychiatry and provides insights into their potential clinical use and avenues for future development. A systematic literature search was conducted across PubMed, EMBASE, and Web of Science databases until 22 August 2023. This review included fifty-three primary studies, of which the majority (69.8%) were conducted using samples of European ancestry. We found that over 90% of PGx-scores in psychiatry have been developed based on psychiatric and medical diagnoses or trait variants, rather than pharmacogenomic variants. Among these PGx-scores, the polygenic score for schizophrenia (PGSSCZ) has been most extensively studied in relation to its impact on treatment outcomes (32 publications). Twenty (62.5%) of these studies suggest that individuals with higher PGSSCZ have negative outcomes from psychotropic treatment - poorer treatment response, higher rates of treatment resistance, more antipsychotic-induced side effects, or more psychiatric hospitalizations, while the remaining studies did not find significant associations. Although PGx-scores alone accounted for at best 5.6% of the variance in treatment outcomes (in schizophrenia treatment resistance), together with clinical variables they explained up to 13.7% (in bipolar lithium response), suggesting that clinical translation might be achieved by including PGx-scores in multivariable models. In conclusion, our literature review found that there are still very few studies developing PGx-scores using pharmacogenomic variants. Research with larger and diverse populations is required to develop clinically relevant PGx-scores, using biology-informed and multi-phenotypic polygenic scoring approaches, as well as by integrating clinical variables with these scores to facilitate their translation to psychiatric practice.

Esketamine in depression: putative biomarkers from clinical research

The discovery of racemic (R, S)-ketamine as a rapid-acting antidepressant and the subsequent FDA approval of its (S)-enantiomer, esketamine, for treatment-resistant depression (TRD) are significant advances in the development of novel neuropsychiatric therapeutics. Esketamine is now recognized as a powerful tool for addressing persistent symptoms of TRD compared to traditional oral antidepressants. However, research on biomarkers associated with antidepressant response to esketamine has remained sparse and, to date, has been largely extrapolated from racemic ketamine studies. Genetic, proteomic, and metabolomic profiles suggest that inflammation and mitochondrial function may play a role in esketamine's antidepressant effects, though these preliminary results require verification. In addition, neuroimaging research has consistently implicated the prefrontal cortex, striatum, and anterior cingulate cortex in esketamine's effects. Esketamine also shows promise in perioperative settings for reducing depression and anxiety, and these effects appear to correlate with increased peripheral biomarkers such as brain-derived neurotrophic factor and serotonin. Further indications are likely to be identified with the continued repurposing of racemic ketamine, providing further opportunity for biomarker study and mechanistic understanding of therapeutic effects. Novel methodologies and well-designed biomarker-focused clinical research trials are needed to more clearly elucidate esketamine's therapeutic actions as well as biologically identify those most likely to benefit from this agent, allowing for the improved personalization of antidepressant treatment.

Esketamine: Less Drowsiness, More Analgesia

Racemic ketamine is a 1:1 mixture of 2 enantiomers that turn light in opposite direction: Dextrorotatory esketamine is approximately 4 times more affine for the N-methyl-D-aspartate (NMDA) receptor than levorotatory arketamine, which may explain why esketamine is about twice as potent as an analgesic and anesthetic as the racemate. Esketamine has attracted renewed interest in view of the opioid crisis, racemic ketamine's abuse, and esketamine's approval for expanded use. We evaluated the anesthesia literature concerning mental, cardiovascular, cerebral, and antinociceptive effects of esketamine published in English between 1980 and 2022. The review shows that esketamine and racemic ketamine are not "the same" at clinically equivalent analgesic and anesthetic dose: Psychomimetic effects seem to be essentially related to NMDA receptor blockade and esketamine is not devoid of unwanted mental impact. However, it probably involves less cholinergic inhibition. Cognitive disturbances during arousal, awakening, and recovery from the drug are less, and less pronounced with esketamine. The drug allows for an approximately 50% dose reduction in anesthesia and analgesia which goes along with a higher clearance and shorter recovery time as compared to racemic ketamine. In comparison of esketamine with placebo, esketamine shows cardiocirculatory stabilizing and neuroprotective effects which can be seen in anesthesia induction, cardiac surgery, and analgesia and sedation in brain injury. Evidence of esketamine's antinociceptive efficacy is inconsistent, although a recent meta-analysis reports improved pain relief after surgery in a study with short observation time. To better define esketamine's place, direct head-to-head comparison with the racemate at equi-analgesic/anesthetic dose is warranted.

Applying polygenic risk score methods to pharmacogenomics GWAS: challenges and opportunities

Polygenic risk scores (PRSs) have emerged as promising tools for the prediction of human diseases and complex traits in disease genome-wide association studies (GWAS). Applying PRSs to pharmacogenomics (PGx) studies has begun to show great potential for improving patient stratification and drug response prediction. However, there are unique challenges that arise when applying PRSs to PGx GWAS beyond those typically encountered in disease GWAS (e.g. Eurocentric or trans-ethnic bias). These challenges include: (i) the lack of knowledge about whether PGx or disease GWAS/variants should be used in the base cohort (BC); (ii) the small sample sizes in PGx GWAS with corresponding low power and (iii) the more complex PRS statistical modeling required for handling both prognostic and predictive effects simultaneously. To gain insights in this landscape about the general trends, challenges and possible solutions, we first conduct a systematic review of both PRS applications and PRS method development in PGx GWAS. To further address the challenges, we propose (i) a novel PRS application strategy by leveraging both PGx and disease GWAS summary statistics in the BC for PRS construction and (ii) a new Bayesian method (PRS-PGx-Bayesx) to reduce Eurocentric or cross-population PRS prediction bias. Extensive simulations are conducted to demonstrate their advantages over existing PRS methods applied in PGx GWAS. Our systematic review and methodology research work not only highlights current gaps and key considerations while applying PRS methods to PGx GWAS, but also provides possible solutions for better PGx PRS applications and future research.

Genetic Landscape of Major Depressive Disorder: Assessment of Potential Diagnostic and Antidepressant Response Markers

BACKGROUND

The clinical heterogeneity in major depressive disorder (MDD), variable treatment response, and conflicting findings limit the ability of genomics toward the discovery of evidence-based diagnosis and treatment regimen. This study attempts to curate all genetic association findings to evaluate potential variants for clinical translation.

METHODS

We systematically reviewed all candidates and genome-wide association studies for both MDD susceptibility and antidepressant response, independently, using MEDLINE, particularly to identify replicated findings. These variants were evaluated for functional consequences using different in silico tools and further estimated their diagnostic predictability by calculating positive predictive values.

RESULTS

A total of 217 significantly associated studies comprising 1200 variants across 545 genes and 128 studies including 921 variants across 412 genes were included with MDD susceptibility and antidepressant response, respectively. Although the majority of associations were confirmed by a single study, we identified 31 and 18 replicated variants (in at least 2 studies) for MDD and antidepressant response. Functional annotation of these 31 variants predicted 20% coding variants as deleterious/damaging and 80.6% variants with regulatory effect. Similarly, the response-related 18 variants revealed 25% coding variant as damaging and 88.2% with substantial regulatory potential. Finally, we could calculate the diagnostic predictability of 19 and 5 variants whose positive predictive values ranges from 0.49 to 0.66 for MDD and 0.36 to 0.66 for response.

CONCLUSIONS

The replicated variants presented in our data are promising for disease diagnosis and improved response outcomes. Although these quantitative assessment measures are solely directive of available observational evidence, robust homogenous validation studies are required to strengthen these variants for molecular diagnostic application.

Migraine and treatment-resistant depression

Migraine and major depressive disorders (MDD) or treatment resistant depression (TRD) represent a significant global burden and are often comorbid, further complicating diagnosis and treatment. Epidemiological studies have demonstrated a bidirectional relationship between migraine and MDD/TRD, with patients suffering from one disorder exhibiting a heightened risk of developing the other. This association is believed to result from shared genetic factors, neurotransmitter dysregulation, inflammation, hormonal alteration, and other conditions comorbid with both disorders. Emerging evidence suggests that therapeutics targeting common pathways in both disorders may be beneficial for comorbid patients. Novel therapeutics for migraine or MDD/TRD, such as calcitonin gene-related peptide (CGRP)-targeting therapy, onabotulinumtoxinA, ketamine/esketamine, vagus nerve stimulation or transcranial magnetic stimulation, may be helpful in selected patients with comorbid migraine-MDD/TRD. Nevertheless, continued efforts are needed to improve early detection and intervention, to better understand the complex interplay between genetic, environmental, and psychosocial factors contributing to this comorbidity, to identify novel therapeutic targets, and ultimately, to alleviate the disease burden caused by this comorbidity.

Polygenic risk score association with multiple sclerosis susceptibility and phenotype in Europeans

Polygenic inheritance plays a pivotal role in driving multiple sclerosis susceptibility, an inflammatory demyelinating disease of the CNS. We developed polygenic risk scores (PRS) of multiple sclerosis and assessed associations with both disease status and severity in cohorts of European descent. The largest genome-wide association dataset for multiple sclerosis to date (n = 41 505) was leveraged to generate PRS scores, serving as an informative susceptibility marker, tested in two independent datasets, UK Biobank [area under the curve (AUC) = 0.73, 95% confidence interval (CI): 0.72-0.74, P = 6.41 × 10-146] and Kaiser Permanente in Northern California (KPNC, AUC = 0.8, 95% CI: 0.76-0.82, P = 1.5 × 10-53). Individuals within the top 10% of PRS were at higher than 5-fold increased risk in UK Biobank (95% CI: 4.7-6, P = 2.8 × 10-45) and 15-fold higher risk in KPNC (95% CI: 10.4-24, P = 3.7 × 10-11), relative to the median decile. The cumulative absolute risk of developing multiple sclerosis from age 20 onwards was significantly higher in genetically predisposed individuals according to PRS. Furthermore, inclusion of PRS in clinical risk models increased the risk discrimination by 13% to 26% over models based only on conventional risk factors in UK Biobank and KPNC, respectively. Stratifying disease risk by gene sets representative of curated cellular signalling cascades, nominated promising genetic candidate programmes for functional characterization. These pathways include inflammatory signalling mediation, response to viral infection, oxidative damage, RNA polymerase transcription, and epigenetic regulation of gene expression to be among significant contributors to multiple sclerosis susceptibility. This study also indicates that PRS is a useful measure for estimating susceptibility within related individuals in multicase families. We show a significant association of genetic predisposition with thalamic atrophy within 10 years of disease progression in the UCSF-EPIC cohort (P < 0.001), consistent with a partial overlap between the genetics of susceptibility and end-organ tissue injury. Mendelian randomization analysis suggested an effect of multiple sclerosis susceptibility on thalamic volume, which was further indicated to be through horizontal pleiotropy rather than a causal effect. In summary, this study indicates important, replicable associations of PRS with enhanced risk assessment and radiographic outcomes of tissue injury, potentially informing targeted screening and prevention strategies.

Understanding treatment-resistant depression using "omics" techniques: A systematic review

BACKGROUND

Treatment-resistant depression (TRD) results in huge healthcare costs and poor patient clinical outcomes. Most studies have adopted a "candidate mechanism" approach to investigate TRD pathogenesis, however this is made more challenging due to the complex and heterogeneous nature of this condition. High-throughput "omics" technologies can provide a more holistic view and further insight into the underlying mechanisms involved in TRD development, expanding knowledge beyond already-identified mechanisms. This systematic review assessed the information from studies that examined TRD using hypothesis-free omics techniques.

METHODS

PubMed, MEDLINE, Embase, APA PsycInfo, Scopus and Web of Science databases were searched on July 2022. 37 human studies met the eligibility criteria, totalling 17,518 TRD patients, 571,402 healthy controls and 62,279 non-TRD depressed patients (including antidepressant responders and untreated MDD patients).

RESULTS

Significant findings were reported that implicate the role in TRD of various molecules, including polymorphisms, genes, mRNAs and microRNAs. The pathways most commonly reported by the identified studies were involved in immune system and inflammation, neuroplasticity, calcium signalling and neurotransmitters.

LIMITATIONS

Small sample sizes, variability in defining TRD, and heterogeneity in study design and methodology.

CONCLUSIONS

These findings provide insight into TRD pathophysiology, proposing future research directions for novel drug targets and potential biomarkers for clinical staging and response to antidepressants (citalopram/escitalopram in particular) and electroconvulsive therapy (ECT). Further validation is warranted in large prospective studies using standardised TRD criteria. A multi-omics and systems biology strategy with a collaborative effort will likely deliver robust findings for translation into the clinic.

Polygenic risk scores for predicting outcomes and treatment response in psychiatry: hope or hype?

Over the last years, the decreased costs and enhanced accessibility to large genome-wide association studies datasets have laid the foundations for the development of polygenic risk scores (PRSs). A PRS is calculated on the weighted sum of single nucleotide polymorphisms and measures the individual genetic predisposition to develop a certain phenotype. An increasing number of studies have attempted to utilize the PRSs for risk stratification and prognostic evaluation. The present narrative review aims to discuss the potential clinical utility of PRSs in predicting outcomes and treatment response in psychiatry. After summarizing the evidence on major mental disorders, we have discussed the advantages and limitations of currently available PRSs. Although PRSs represent stable trait features with a normal distribution in the general population and can be relatively easily calculated in terms of time and costs, their real-world applicability is reduced by several limitations, such as low predictive power and lack of population diversity. Even with the rapid expansion of the psychiatric genetic knowledge base, pure genetic prediction in clinical psychiatry appears to be out of reach in the near future. Therefore, combining genomic and exposomic vulnerabilities for mental disorders with a detailed clinical characterization is needed to personalize care.

Association Between Polygenic Risk Scores and Outcome of ECT

OBJECTIVE

Identifying biomarkers associated with response to electroconvulsive therapy (ECT) may aid clinical decisions. The authors examined whether greater polygenic liabilities for major depressive disorder, bipolar disorder, and schizophrenia are associated with improvement following ECT for a major depressive episode.

METHODS

Between 2013 and 2017, patients who had at least one treatment series recorded in the Swedish National Quality Register for ECT were invited to provide a blood sample for genotyping. The present study included 2,320 participants (median age, 51 years; 62.8% women) who had received an ECT series for a major depressive episode (77.1% unipolar depression), who had a registered treatment outcome, and whose polygenic risk scores (PRSs) could be calculated. Ordinal logistic regression was used to estimate the effect of PRS on Clinical Global Impressions improvement scale (CGI-I) score after each ECT series.

RESULTS

Greater PRS for major depressive disorder was significantly associated with less improvement on the CGI-I (odds ratio per standard deviation, 0.89, 95% CI=0.82, 0.96; R²=0.004), and greater PRS for bipolar disorder was associated with greater improvement on the CGI-I (odds ratio per standard deviation, 1.14, 95% CI=1.05, 1.23; R²=0.005) after ECT. PRS for schizophrenia was not associated with improvement. In an overlapping sample (N=1,207) with data on response and remission derived from the self-rated version of the Montgomery-Åsberg Depression Rating Scale, results were similar except that schizophrenia PRS was also associated with remission.

CONCLUSIONS

Improvement after ECT is associated with polygenic liability for major depressive disorder and bipolar disorder, providing evidence of a genetic component for ECT clinical response. These liabilities may be considered along with clinical predictors in future prediction models of ECT outcomes.

Effects of GRIN2B, GRIA1, and BDNF Polymorphisms on the Therapeutic Action of Ketamine and Esketamine in Treatment-Resistant Depression Patients: Secondary Analysis From a Randomized Clinical Trial

OBJECTIVE

This study aimed to evaluate the effect of genetic variants in glutamate ionotropic receptor N-methyl-d-aspartate type subunit 2B (GRIN2B), glutamate ionotropic receptor α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid type subunit 1 (GRIA1), and brain-derived neurotrophic factor (BDNF) genes on therapeutic response, remission, and total Montgomery-Åsberg Depression Rating Scale scores after treatment with ketamine or esketamine in treatment-resistant depression (TRD) patients.

METHODS

Participants (N = 60) are from a double-blind, randomized, noninferiority clinical trial comparing single-dose intravenous ketamine (0.5 mg/kg) to esketamine (0.25 mg/kg) for TRD. Montgomery-Åsberg Depression Rating Scale was applied at baseline, 24 hours, 72 hours, and 7 days postinfusion to assess depressive symptoms. Blood samples were collected to evaluate single nucleotide polymorphisms rs1805502 (GRIN2B), rs1994862 (GRIA1), and rs6265 (BDNF).

RESULTS

There was no association between rs1805502, rs1994862, or rs6265 polymorphisms and antidepressant response (P = 0.909, P = 0.776, and P = 0.482, respectively), remission P = 0.790, P = 0.086, and P = 0.669), or Montgomery-Åsberg Depression Rating Scale scores at each time point (P = 0.907, P = 0.552, and P = 0.778).

CONCLUSIONS

We found no association between the studied single nucleotide polymorphisms (rs6265, rs1805502, and rs1994862) and ketamine's therapeutic action in TRD patients. Further studies with larger samples are needed to clarify the utility of these genes of interest as predictors for antidepressant treatment.

A polygenic-informed approach to a predictive EEG signature empowers antidepressant treatment prediction: A proof-of-concept study

The treatment of major depressive disorder (MDD) is hampered by low chances of treatment response in each treatment step, which is partly due to a lack of firmly established outcome-predictive biomarkers. Here, we hypothesize that polygenic-informed EEG signatures may help predict antidepressant treatment response. Using a polygenic-informed electroencephalography (EEG) data-driven, data-reduction approach, we identify a brain network in a large cohort (N=1,123), and discover it is sex-specifically (male patients, N=617) associated with polygenic risk score (PRS) of antidepressant response. Subsequently, we demonstrate in three independent datasets the utility of the network in predicting response to antidepressant medication (male, N=232) as well as repetitive transcranial magnetic stimulation (rTMS) and concurrent psychotherapy (male, N=95). This network significantly improves a treatment response prediction model with age and baseline severity data (area under the curve, AUC=0.623 for medicaton; AUC=0.719 for rTMS). A predictive model for MDD patients, aimed at increasing the likelihood of being a responder to antidepressants or rTMS and concurrent psychotherapy based on only this network, yields a positive predictive value (PPV) of 69% for medication and 77% for rTMS. Finally, blinded out-of-sample validation of the network as predictor for psychotherapy response in another independent dataset (male, N=50) results in a within-subsample response rate of 50% (improvement of 56%). Overall, the findings provide a first proof-of-concept of a combined genetic and neurophysiological approach in the search for clinically-relevant biomarkers in psychiatric disorders, and should encourage researchers to incorporate genetic information, such as PRS, in their search for clinically relevant neuroimaging biomarkers.

The Potential of Polygenic Risk Scores to Predict Antidepressant Treatment Response in Major Depression: A Systematic Review

BACKGROUND

Understanding the genetic underpinnings of antidepressant treatment response in unipolar major depressive disorder (MDD) can be useful in identifying patients at risk for poor treatment response or treatment resistant depression. A polygenic risk score (PRS) is a useful tool to explore genetic liability of a complex trait such as antidepressant treatment response. Here, we review studies that use PRSs to examine genetic overlap between any trait and antidepressant treatment response in unipolar MDD.

METHODS

A systematic search of literature was conducted in PubMed, Embase, and PsycINFO. Our search included studies examining associations between PRSs of psychiatric as well as non-psychiatric traits and antidepressant treatment response in patients with unipolar MDD. A quality assessment of the included studies was performed.

RESULTS

In total, eleven articles were included which contained PRSs for 30 traits. Studies varied in sample size and endpoints used for antidepressant treatment response. Overall, PRSs for attention-deficit hyperactivity disorder, the personality trait openness, coronary artery disease, obesity, and stroke have been associated with antidepressant treatment response in patients with unipolar MDD.

LIMITATIONS

The endpoints used by included studies differed significantly, therefore it was not possible to perform a meta-analysis.

CONCLUSIONS

Associations between a PRS and antidepressant treatment response have been reported for a number of traits in patients with unipolar MDD. PRSs could be informative to predict antidepressant treatment response in this population, given advances in the field. Most importantly, there is a need for larger study cohorts and the use of standardized outcome measures.

Mechanisms of ketamine and its metabolites as antidepressants

Treating major depression is a medical need that remains unmet by monoaminergic therapeutic strategies that commonly fail to achieve symptom remission. A breakthrough in the treatment of depression was the discovery that the anesthetic (R,S)-ketamine (ketamine), when administered at sub-anesthetic doses, elicits rapid (sometimes within hours) antidepressant effects in humans that are otherwise resistant to monoaminergic-acting therapies. While this finding was revolutionary and led to the FDA approval of (S)-ketamine (esketamine) for use in adults with treatment-resistant depression and suicidal ideation, the mechanisms underlying how ketamine or esketamine elicit their effects are still under active investigation. An emerging view is that metabolism of ketamine may be a crucial step in its mechanism of action, as several metabolites of ketamine have neuroactive effects of their own and may be leveraged as therapeutics. For example, (2R,6R)-hydroxynorketamine (HNK), is readily observed in humans following ketamine treatment and has shown therapeutic potential in preclinical tests of antidepressant efficacy and synaptic potentiation while being devoid of the negative adverse effects of ketamine, including its dissociative properties and abuse potential. We discuss preclinical and clinical studies pertaining to how ketamine and its metabolites produce antidepressant effects. Specifically, we explore effects on glutamate neurotransmission through N-methyl D-aspartate receptors (NMDARs) and α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptors (AMPARs), synaptic structural changes via brain derived neurotrophic factor (BDNF) signaling, interactions with opioid receptors, and the enhancement of serotonin, norepinephrine, and dopamine signaling. Strategic targeting of these mechanisms may result in novel rapid-acting antidepressants with fewer undesirable side effects compared to ketamine.

A meta-analysis of polygenic risk scores for mood disorders, neuroticism, and schizophrenia in antidepressant response

About two-thirds of patients with major depressive disorder (MDD) fail to achieve symptom remission after the initial antidepressant treatment. Despite a role of genetic factors was proven, the specific underpinnings are not fully understood yet. Polygenic risk scores (PRSs), which summarise the additive effect of multiple risk variants across the genome, might provide insights into the underlying genetics. This study aims to investigate the possible association of PRSs for bipolar disorder, MDD, neuroticism, and schizophrenia (SCZ) with antidepressant non-response or non-remission in patients with MDD. PRSs were calculated at eight genome-wide P-thresholds based on publicly available summary statistics of the largest genome-wide association studies. Logistic regressions were performed between PRSs and non-response or non-remission in six European clinical samples, adjusting for age, sex, baseline symptom severity, recruitment sites, and population stratification. Results were meta-analysed across samples, including up to 3,637 individuals. Bonferroni correction was applied. In the meta-analysis, no result was significant after Bonferroni correction. The top result was found for MDD-PRS and non-remission (p = 0.004), with patients in the highest vs. lowest PRS quintile being more likely not to achieve remission (OR=1.5, 95% CI=1.11-1.98, p = 0.007). Nominal associations were also found between MDD-PRS and non-response (p = 0.013), as well as between SCZ-PRS and non-remission (p = 0.035). Although PRSs are still not able to predict non-response or non-remission, our results are in line with previous works; methodological improvements in PRSs calculation may improve their predictive performance and have a meaningful role in precision psychiatry.

The stressed synapse 2.0: pathophysiological mechanisms in stress-related neuropsychiatric disorders

Stress is a primary risk factor for several neuropsychiatric disorders. Evidence from preclinical models and clinical studies of depression have revealed an array of structural and functional maladaptive changes, whereby adverse environmental factors shape the brain. These changes, observed from the molecular and transcriptional levels through to large-scale brain networks, to the behaviours reveal a complex matrix of interrelated pathophysiological processes that differ between sexes, providing insight into the potential underpinnings of the sex bias of neuropsychiatric disorders. Although many preclinical studies use chronic stress protocols, long-term changes are also induced by acute exposure to traumatic stress, opening a path to identify determinants of resilient versus susceptible responses to both acute and chronic stress. Epigenetic regulation of gene expression has emerged as a key player underlying the persistent impact of stress on the brain. Indeed, histone modification, DNA methylation and microRNAs are closely involved in many aspects of the stress response and reveal the glutamate system as a key player. The success of ketamine has stimulated a whole line of research and development on drugs directly or indirectly targeting glutamate function. However, the challenge of translating the emerging understanding of stress pathophysiology into effective clinical treatments remains a major challenge.

Polygenic risk scores: An overview from bench to bedside for personalised medicine

Since the first polygenic risk score (PRS) in 2007, research in this area has progressed significantly. The increasing number of SNPs that have been identified by large scale GWAS analyses has fuelled the development of a myriad of PRSs for a wide variety of diseases and, more recently, to PRSs that potentially identify differential response to specific drugs. PRSs constitute a composite genomic biomarker and potential applications for PRSs in clinical practice encompass risk prediction and disease screening, early diagnosis, prognostication, and drug stratification to improve efficacy or reduce adverse drug reactions. Nevertheless, to our knowledge, no PRSs have yet been adopted into routine clinical practice. Beyond the technical considerations of PRS development, the major challenges that face PRSs include demonstrating clinical utility and circumnavigating the implementation of novel genomic technologies at scale into stretched healthcare systems. In this review, we discuss progress in developing disease susceptibility PRSs across multiple medical specialties, development of pharmacogenomic PRSs, and future directions for the field.

Molecular Mechanisms Associated with Antidepressant Treatment on Major Depression

Major depressive disorder (MDD) is a complex and multifactorial psychiatric disorder that causes serious health, social, and economic concerns worldwide. The main treatment of the symptoms is through antidepressant (AD) drugs. However, not all patients respond properly to these drugs. Omic sciences are widely used to analyze not only biomarkers for the AD response but also their molecular mechanism. In this review, we aimed to focus on omics data to better understand the molecular mechanisms involving AD effects on MDD. We consistently found, from preclinical to clinical data, that glutamatergic transmission, immune/inflammatory processes, energy metabolism, oxidative stress, and lipid metabolism were associated with traditional and potential new ADs. Despite efforts of studies investigating biomarkers of response to ADs, which could contribute to personalized treatment, there is no biomarker panel available for clinical application. From clinical genomic studies, we found that the main findings contribute to the development of pharmacogenomic tests for AD efficacy for each patient. Several studies pointed at DRD2, PXDNL, CACNA1E, and CACNA2D1 genes as potential targets for MDD treatment and the efficacy and rapid-antidepressant effect of ketamine. Finally, more in-depth studies of the molecular targets pointed here are needed to determine the clinical relevance and provide further evidence for precision MDD treatment.

The role of pharmacogenetics in the treatment of anxiety disorders and the future potential for targeted therapeutics

INTRODUCTION

Anxiety disorders (AD) are among the most common mental disorders worldwide. Pharmacotherapy, including benzodiazepines, selective serotonin reuptake inhibitors, serotonin-norepinephrine reuptake inhibitors, and tricyclic antidepressants is currently based on 'trial-and-error,' and is effective in a subset of patients or produces partial response only. Recent research proposes that treatment response and tolerability of the drugs are associated with genetic factors.

AREAS COVERED

In the present review, we provide information on pharmacogenetics (PGx) in AD, including pharmacokinetic and pharmacodynamic genes. Moreover, we discuss the future potential of PGx for personalized treatment.

EXPERT OPINION

In psychiatry, PGx testing is still in its infancy, especially in the treatment of AD. As of today, implementation in clinical routine is recommended only for CYP2D6 and CYP2C19, mainly in terms of safety of treatment and potentially of treatment outcome in general. However, the evidence for PGx testing addressing pharmacodynamics for specific AD is limited to date. Nevertheless, PGx may develop into a valuable and promising tool to improve therapy in AD, but there is a need for more research to fully exploit its possibilities. Future perspectives include research into single genes, polygenic risk scores, and pharmacoepigenetics to provide targeted therapy.

Ready for a "breakthrough" with ketamine? A look at recent pharmacological insights!

PURPOSE OF REVIEW

To update pharmacological insights on ketamine integrating information from different disciplines for developing steps to "breakthrough" approaches in clinical challenges.

RECENT FINDINGS

Pharmacokinetic/pharmacodynamic (PK/PD) models have incorporated recirculation, ketamine metabolites, drug-drug interaction, and covariates such as age. Ketamine-induced relief from treatment-resistant depression has been explained by "disinhibition" of gamma-aminobutyric acid-ergic interneurons and synaptogenic mechanisms requiring neurotrophic signals. Neuroimaging/electroencephalographic investigations have shown an increase in gamma spectral power in healthy volunteers and patients with depression, but also opposite changes in functional network connectivity after subanesthetic ketamine. Volunteer data may not be transferable to clinical conditions. Altered states of consciousness induced by subanesthetic ketamine have been described by disruption of resisting-state functional networks and frontoparietal connectivity with preservation of multisensory and sensor-motor networks. This has been interpreted as a "disconnected consciousness".

SUMMARY

More precise PK/PD models may improve the ketamine use regimen. The findings from research on depression are an important discovery because ketamine's impact on neuronal plasticity and synaptogenesis in human brain disease has directly been documented. Psychic adverse effects with subanesthetic ketamine are related to a "disconnected consciousness". Overall, progress has been made, but the "breakthrough" still has to come.

Synthesizing the Evidence for Ketamine and Esketamine in Treatment-Resistant Depression: An International Expert Opinion on the Available Evidence and Implementation

Replicated international studies have underscored the human and societal costs associated with major depressive disorder. Despite the proven efficacy of monoamine-based antidepressants in major depression, the majority of treated individuals fail to achieve full syndromal and functional recovery with the index and subsequent pharmacological treatments. Ketamine and esketamine represent pharmacologically novel treatment avenues for adults with treatment-resistant depression. In addition to providing hope to affected persons, these agents represent the first non-monoaminergic agents with proven rapid-onset efficacy in major depressive disorder. Nevertheless, concerns remain about the safety and tolerability of ketamine and esketamine in mood disorders. Moreover, there is uncertainty about the appropriate position of these agents in treatment algorithms, their comparative effectiveness, and the appropriate setting, infrastructure, and personnel required for their competent and safe implementation. In this article, an international group of mood disorder experts provides a synthesis of the literature with respect to the efficacy, safety, and tolerability of ketamine and esketamine in adults with treatment-resistant depression. The authors also provide guidance for the implementation of these agents in clinical practice, with particular attention to practice parameters at point of care. Areas of consensus and future research vistas are discussed.

Treatment response to low-dose ketamine infusion for treatment-resistant depression: A gene-based genome-wide association study

BACKGROUNDS

Evidence suggested the crucial roles of brain-derived neurotrophic factor (BDNF) and glutamate system functioning in the antidepressant mechanisms of low-dose ketamine infusion in treatment-resistant depression (TRD).

METHODS

65 patients with TRD were genotyped for 684,616 single nucleotide polymorphisms (SNPs). Twelve ketamine-related genes were selected for the gene-based genome-wide association study on the antidepressant effect of ketamine infusion and the resulting serum ketamine and norketamine levels.

RESULTS

Specific SNPs and whole genes involved in BDNF-TrkB signaling (i.e., rs2049048 in BDNF and rs10217777 in NTRK2) and the glutamatergic and GABAergic systems (i.e., rs16966731 in GRIN2A) were associated with the rapid (within 240 min) and persistent (up to 2 weeks) antidepressant effect of low-dose ketamine infusion and with serum ketamine and norketamine levels.

DISCUSSION

Our findings confirmed the predictive roles of BDNF-TrkB signaling and glutamatergic and GABAergic systems in the underlying mechanisms of low-dose ketamine infusion for TRD treatment.