Genome-wide analysis suggests the importance of vascular processes and neuroinflammation in late-life antidepressant response

Research hotspots and trends of post-stroke depression rehabilitation: a bibliometric analysis from 2003 to 2024

Background

Post-stroke depression (PSD) is a common complication of stroke and is associated with stroke prognosis. Rehabilitation plays an essential role in the comprehensive treatment of PSD. However, there are few bibliometric analyses of studies on PSD rehabilitation. This study aimed to comprehensively sort out the network of PSD rehabilitation through bibliometric analyses, analyze the research trends, focus on the hotspots related to PSD rehabilitation, and provide new research perspectives and guidance for future studies.

Methods

The Web of Science Core Collection (WoSCC) database was searched for studies about depression rehabilitation after a stroke. The search covered the period from January 1, 2003, to October 31, 2024. We analyzed countries, institutions, journals, authors and keywords using CiteSpace and VOSviewer software to create visualizations and perform a bibliometric analysis.

Results

A total of 2,227 papers were analyzed, with an increasing trend in the number of papers published each year. The United States had the highest number of published articles (458 publications), and Maastricht University and Utrecht University were the most published institutions (56 articles). Archives of Physical Medicine and Rehabilitation is the journal with the most cited publications (5,913 citations). Johanna M. A. is the most prolific author (24 publications).

Conclusion

Using bibliometric methods, relevant studies on PSD rehabilitation were reviewed. The hotspots of future research on PSD rehabilitation will center on the brain plasticity mechanism of PSD rehabilitation, PSD assessment, and new techniques of PSD rehabilitation. This article provides systematic information to support and guide future research in this area.

Polygenic Risk Score Analysis of Antidepressant Treatment Outcomes: A CAN-BIND-1 Study Report: Analyse des résultats du traitement antidépresseur à l'aide des scores de risque polygéniques : Rapport sur l'étude CAN-BIND-1

ObjectiveThe genetic architecture of antidepressant response is poorly understood. This study investigated whether polygenic risk scores (PRSs) for major psychiatric disorders and a personality trait (neuroticism) are associated with antidepressant treatment outcomes.MethodsWe analysed 148 participants with major depressive disorder (MDD) from the Canadian Biomarker Integration Network for Depression-1 (CAN-BIND-1) cohort. Participants initially received escitalopram (ESC) monotherapy for 8 weeks. Nonresponders at week 8 received augmentation with aripiprazole (ARI), while responders continued ESC until week 16. Primary outcomes were remission status and symptom improvement measured at weeks 8 and 16. At week 16, post-hoc stratified analyses were performed by treatment arm (ESC-only vs. ESC + ARI). Eleven PRSs derived from genome-wide association studies of psychiatric disorders (e.g., MDD and post-traumatic stress syndrome (PTSD)) and neuroticism, were analysed for associations with these outcomes using logistic and linear regression models.ResultsAt week 8, a higher PRS for PTSD was nominally associated with a lower probability of remission (odds ratio (OR) = 0.08 [0.014-0.42], empirical p-value = 0.017) and reduced symptom improvement (beta (standard error) = -29.15 (9.76), empirical p-value = 0.019). Similarly, a higher PRS for MDD was nominally associated with decreased remission probability (OR = 0.38 [0.18-0.78], empirical p-value = 0.044). However, none of the results survived multiple testing corrections. At week 16, the stratified analysis for the ESC-only group revealed that a higher PRS for MDD was associated with increased remission probability (empirical p-value = 0.034) and greater symptom improvement (empirical p-value = 0.02). In contrast, higher PRSs for schizophrenia (empirical p-value = 0.013) and attention-deficit hyperactivity disorder (empirical p-value = 0.032) were associated with lower symptom improvement. No significant associations were observed in the ESC + ARI group.ConclusionsThese findings suggest that PRSs may influence treatment outcomes, particularly in ESC monotherapy. Replication in larger studies is needed to validate these observations.

Cardiovascular Risk Predicts White Matter Hyperintensities, Brain Atrophy and Treatment Resistance in Major Depressive Disorder: Role of Genetic Liability

INTRODUCTION

Depressive disorders are a leading cause of global disease burden, particularly with the challenge of treatment-resistant depression (TRD). Research points to a complex bidirectional relationship between cardiovascular (CV) risk factors and TRD, with CV risk negatively impacting brain structure and potentially influencing antidepressant resistance. Moreover, the association between depression and the genetic vulnerability to cardiovascular disease suggests a shared pathophysiological process between the two. This study investigates the mediating role of brain structural alterations in the relationship between CV and cerebrovascular (CeV) risk and treatment resistance in depression.

METHODS

We assessed 165 inpatients with Major depressive disorder. Each patient's CV risk was assessed via the QRISK 3 calculator. For a subset of patients, CV and CeV disease polygenic risk scores (PRS) were obtained. All patients underwent a 3 T MRI scan, and white matter hyperintensities estimates and indicators of brain trophic state were obtained.

RESULTS

Both CV risk and CV disease PRSs are associated with treatment resistance status, white matter hyperintensities, and indicators of brain atrophy. Mediation analyses suggested that CV-induced brain alterations might underlie the relation between CV genetic and phenotypic risk and antidepressant treatment resistance.

CONCLUSION

These results underscore the need to explore cardiovascular risk management as part of treatment strategies for depression, pointing toward a shared pathophysiological process linking heart and brain health in treatment-resistant depression.

Polygenic score analyses on antidepressant response in late-life depression, results from the IRL-GRey study

Late-life depression (LLD) is often accompanied by medical comorbidities such as psychiatric disorders and cardiovascular diseases, posing challenges to antidepressant treatment. Recent studies highlighted significant associations between treatment-resistant depression (TRD) and polygenic risk score (PRS) for attention deficit hyperactivity disorder (ADHD) in adults as well as a negative association between antidepressant symptom improvement with both schizophrenia and bipolar. Here, we sought to validate these findings with symptom remission in LLD. We analyzed the Incomplete Response in Late Life Depression: Getting to Remission (IRL-GRey) sample consisting of adults aged 60+ with major depression (N = 342) treated with venlafaxine for 12 weeks. We constructed PRSs for ADHD, depression, schizophrenia, bipolar disorder, neuroticism, general intelligence, antidepressant symptom remission and antidepressant percentage symptom improvement using summary statistics from the Psychiatric Genomics Consortium and the GWAS Catalog. Logistic regression was used to test the association of PRSs with venlafaxine symptom remission and percentage symptom improvement, co-varying for the genomic principal components, age, sex and depressive symptoms severity at baseline. We found a nominal (i.e., p value ≤ 0.05) association between symptom remission and both PRS for ADHD and (OR = 1.36 [1.07, 1.73], p = 0.011) and PRS for bipolar disorder (OR = 0.75 [0.58, 0.97], p = 0.031), as well as between percentage symptom improvement and PRS for general intelligence (beta = 6.81 (SE = 3.122), p = 0.03). However, the ADHD association was in the opposite direction as expected, and both associations did not survive multiple testing corrections. Altogether, these findings suggest that previous findings regarding ADHD PRS and antidepressant response (measured with various outcomes) do not replicate in older adults.

Genetic determinants of antidepressant and antipsychotic drug response

Today, more than 90% of inpatients hospitalized with Major Depression or Schizophrenia are treated with psychotropic drugs. Since none of the treatment options is causal, response rates are modest and the course of recovery is very heterogeneous. Genetic studies on the etiology and pathogenesis of major psychiatric disorders over the past decades have been largely unsuccessful. Likewise, genetic studies to predict response to psychopharmacological treatment have also not been particularly successful. In this project we have recruited 902 inpatients with ICD-10 diagnoses of schizophrenic ("F2 patients") or depressive disorders ("F3 patients"). The study assessed today's acute inpatient treatment regimens with up to 8 repeated measurements regarding the time course of recovery and adverse side effects. The genotyping included 100 candidate genes with genotypic patterns computed from 549 Single Nucleotide Polymorphisms (SNPs). To predict response to psychopharmacological treatment, we relied on a multidimensional approach to analyzing genetic diversity in combination with multilayer Neural Nets (NNs). Central to this new method were the "gene vectors" that (1) assessed the multidimensional genotypic patterns observed with genes; and (2) evaluated the correlations between genes. By means of these methods, we searched for combinations of multidimensional genotypic patterns that were characteristic of treatment responders while being rare among non-responders. The chosen method of approach provided a powerful technique to detail the complex structures of SNP data that are not detectable by conventional association methods. Molecular-genetic NNs enabled correct classification of 100% "non-responders", along with 94.7% correctly classified "responders" among the F2 patients, and 82.6% correctly classified "responders" among the F3 patients. The F2 and F3 classifiers were not disjoint but showed an overlap of 29.6% and 35.7% between the diagnostic groups, thus indicating that clinical diagnoses may not constitute etiologic entities. Our results suggested that patients may have an unspecific physical-genetic disposition that enables, facilitates, impedes or prevents recovery from major psychiatric disorders by setting various thresholds for exogenous triggers that initiate improvement ("recovery disposition"). Even though this disposition is not causally linked to recovery, it can nonetheless be clinically used in the sense of a "surrogate". Indeed, clinicians are also interested in reliable tools that can "do the job", despite the fact that etiology and pathogenesis of the treated disorders remain unknown.

Rare and common variants associated with alcohol consumption identify a conserved molecular network

BACKGROUND

Genome-wide association studies (GWAS) have identified hundreds of common variants associated with alcohol consumption. In contrast, genetic studies of alcohol consumption that use rare variants are still in their early stages. No prior studies of alcohol consumption have examined whether common and rare variants implicate the same genes and molecular networks, leaving open the possibility that the two approaches might identify distinct biology.

METHODS

To address this knowledge gap, we used publicly available alcohol consumption GWAS summary statistics (GSCAN, N = 666,978) and whole exome sequencing data (Genebass, N = 393,099) to identify a set of common and rare variants for alcohol consumption. We used gene-based analysis to implicate genes from common and rare variant analyses, which we then propagated onto a shared molecular network using a network colocalization procedure.

RESULTS

Gene-based analysis of each dataset implicated 294 (common variants) and 35 (rare variants) genes, including ethanol metabolizing genes ADH1B and ADH1C, which were identified by both analyses, and ANKRD12, GIGYF1, KIF21B, and STK31, which were identified in only the rare variant analysis, but have been associated with other neuropsychiatric traits. Network colocalization revealed significant network overlap between the genes identified via common and rare variants. The shared network identified gene families that function in alcohol metabolism, including ADH, ALDH, CYP, and UGT. Seventy-one of the genes in the shared network were previously implicated in neuropsychiatric or substance use disorders but not alcohol-related behaviors (e.g. EXOC2, EPM2A, and CACNG4). Differential gene expression analysis showed enrichment in the liver and several brain regions.

CONCLUSIONS

Genes implicated by network colocalization identify shared biology relevant to alcohol consumption, which also underlie neuropsychiatric traits and substance use disorders that are comorbid with alcohol use, providing a more holistic understanding of two disparate sources of genetic information.

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.

Research status and global trends of late-life depression from 2004 to 2023: bibliometric analysis

Background

Global research hotspots and future research trends in the neurobiological mechanisms of late-life depression (LLD) as well as its diagnosis and treatment are not yet clear.

Objectives

This study profiled the current state of global research on LLD and predicted future research trends in the field.

Methods

Literature with the subject term LLD was retrieved from the Web of Science Core Collection, and CiteSpace software was used to perform econometric and co-occurrence analyses. The results were visualized using CiteSpace, VOSviewer, and other software packages.

Results

In total, 10,570 publications were included in the analysis. Publications on LLD have shown an increasing trend since 2004. The United States and the University of California had the highest number of publications, followed consecutively by China and England, making these countries and institutions the most influential in the field. Reynolds, Charles F. was the author with the most publications. The International Journal of Geriatric Psychiatry was the journal with the most articles and citations. According to the co-occurrence analysis and keyword/citation burst analysis, cognitive impairment, brain network dysfunction, vascular disease, and treatment of LLD were research hotspots.

Conclusion

Late-life depression has attracted increasing attention from researchers, with the number of publications increasing annually. However, many questions remain unaddressed in this field, such as the relationship between LLD and cognitive impairment and dementia, or the impact of vascular factors and brain network dysfunction on LLD. Additionally, the treatment of patients with LLD is currently a clinical challenge. The results of this study will help researchers find suitable research partners and journals, as well as predict future hotspots.

Bidirectional associations between mental disorders, antidepressants and cardiovascular disease

BACKGROUND

Mental disorders have a high comorbidity with cardiovascular disease (CVD), but the causality between them has not been fully appreciated.

OBJECTIVE

This study aimed to systematically explore the bidirectional causality between the two broad categories of diseases.

METHODS

We conducted Mendelian randomisation (MR) and multivariable MR (MVMR) analyses to evaluate potential causal links between 10 mental disorders, the use of antidepressants and 7 CVDs.

FINDINGS

We discovered that major depressive disorder (MDD), attention-deficit/hyperactivity disorder (ADHD) and insomnia exhibit connections with elevated risks of two or more CVDs. Moreover, the use of antidepressants is linked to heightened risks of each CVD. Each distinct CVD is correlated with a greater probability of taking antidepressants. Our MVMR analysis demonstrated that the use of antidepressants is correlated with the elevation of respective risks across all cardiovascular conditions. This includes arrhythmias (OR: 1.28), atrial fibrillation (OR: 1.44), coronary artery disease (OR: 1.16), hypertension (OR: 1.16), heart failure (OR: 1.16), stroke (OR: 1.44) and entire CVD group (OR: 1.35). However, MDD itself was not linked to a heightened risk of any CVD.

CONCLUSIONS

The findings of our study indicate that MDD, insomnia and ADHD may increase the risk of CVD. Our findings highlight the utilisation of antidepressants as an independent risk factor for CVD, thus explaining the influence of MDD on CVD through the mediating effects of antidepressants.

CLINICAL IMPLICATIONS

When treating patients with antidepressants, it is necessary to take into consideration the potential beneficial and detrimental effects of antidepressants.

Rare and Common Variants Associated with Alcohol Consumption Identify a Conserved Molecular Network

Genome-wide association studies (GWAS) have identified hundreds of common variants associated with alcohol consumption. In contrast, rare variants have only begun to be studied for their role in alcohol consumption. No studies have examined whether common and rare variants implicate the same genes and molecular networks. To address this knowledge gap, we used publicly available alcohol consumption GWAS summary statistics (GSCAN, N=666,978) and whole exome sequencing data (Genebass, N=393,099) to identify a set of common and rare variants for alcohol consumption. Gene-based analysis of each dataset have implicated 294 (common variants) and 35 (rare variants) genes, including ethanol metabolizing genes ADH1B and ADH1C, which were identified by both analyses, and ANKRD12, GIGYF1, KIF21B, and STK31, which were identified only by rare variant analysis, but have been associated with related psychiatric traits. We then used a network colocalization procedure to propagate the common and rare gene sets onto a shared molecular network, revealing significant overlap. The shared network identified gene families that function in alcohol metabolism, including ADH, ALDH, CYP, and UGT. 74 of the genes in the network were previously implicated in comorbid psychiatric or substance use disorders, but had not previously been identified for alcohol-related behaviors, including EXOC2, EPM2A, CACNB3, and CACNG4. Differential gene expression analysis showed enrichment in the liver and several brain regions supporting the role of network genes in alcohol consumption. Thus, genes implicated by common and rare variants identify shared functions relevant to alcohol consumption, which also underlie psychiatric traits and substance use disorders that are comorbid with alcohol use.

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.

Exploratory genome-wide analyses of cortical inhibition, facilitation, and plasticity in late-life depression

Late-life depression (LLD) is a heterogenous mood disorder influenced by genetic factors. Cortical physiological processes such as cortical inhibition, facilitation, and plasticity may be markers of illness that are more strongly associated with genetic factors than the clinical phenotype. Thus, exploring the relationship between genetic factors and these physiological processes may help to characterize the biological mechanisms underlying LLD and improve diagnosis and treatment selection. Transcranial magnetic stimulation (TMS) combined with electromyography was used to measure short interval intracortical inhibition (SICI), cortical silent period (CSP), intracortical facilitation (ICF), and paired associative stimulation (PAS) in 79 participants with LLD. We used exploratory genome-wide association and gene-based analyses to assess for genetic correlations of these TMS measures. MARK4 (which encodes microtubule affinity-regulating kinase 4) and PPP1R37 (which encodes protein phosphatase 1 regulatory subunit 37) showed genome-wide significant association with SICI. EGFLAM (which encodes EGF-like fibronectin type III and laminin G domain) showed genome-wide significant association with CSP. No genes met genome-wide significant association with ICF or PAS. We observed genetic influences on cortical inhibition in older adults with LLD. Replication with larger sample sizes, exploration of clinical phenotype subgroups, and functional analysis of relevant genotypes is warranted to better characterize genetic influences on cortical physiology in LLD. This work is needed to determine whether cortical inhibition may serve as a biomarker to improve diagnostic precision and guide treatment selection in LLD.

Integrating multiple traits for improving polygenic risk prediction in disease and pharmacogenomics GWAS

Polygenic risk score (PRS) has been recently developed for predicting complex traits and drug responses. It remains unknown whether multi-trait PRS (mtPRS) methods, by integrating information from multiple genetically correlated traits, can improve prediction accuracy and power for PRS analysis compared with single-trait PRS (stPRS) methods. In this paper, we first review commonly used mtPRS methods and find that they do not directly model the underlying genetic correlations among traits, which has been shown to be useful in guiding multi-trait association analysis in the literature. To overcome this limitation, we propose a mtPRS-PCA method to combine PRSs from multiple traits with weights obtained from performing principal component analysis (PCA) on the genetic correlation matrix. To accommodate various genetic architectures covering different effect directions, signal sparseness and across-trait correlation structures, we further propose an omnibus mtPRS method (mtPRS-O) by combining P values from mtPRS-PCA, mtPRS-ML (mtPRS based on machine learning) and stPRSs using Cauchy Combination Test. Our extensive simulation studies show that mtPRS-PCA outperforms other mtPRS methods in both disease and pharmacogenomics (PGx) genome-wide association studies (GWAS) contexts when traits are similarly correlated, with dense signal effects and in similar effect directions, and mtPRS-O is consistently superior to most other methods due to its robustness under various genetic architectures. We further apply mtPRS-PCA, mtPRS-O and other methods to PGx GWAS data from a randomized clinical trial in the cardiovascular domain and demonstrate performance improvement of mtPRS-PCA in both prediction accuracy and patient stratification as well as the robustness of mtPRS-O in PRS association test.

Phosphodiesterase inhibitors in psychiatric disorders

RATIONALE

Challenges in drug development for psychiatric disorders have left much room for the introduction of novel treatments with better therapeutic efficacies and indices. As a result, intense research has focused on identifying new targets for developing such pharmacotherapies. One of these targets may be the phosphodiesterase (PDE) class of enzymes, which play important roles in intracellular signaling. Due to their critical roles in cellular pathways, these enzymes affect diverse neurobiological functions from learning and memory formation to neuroinflammation.

OBJECTIVES

In this paper, we reviewed studies on the use of PDE inhibitors (PDEIs) in preclinical models and clinical trials of psychiatric disorders including depression, anxiety, schizophrenia, post-traumatic stress disorder (PTSD), bipolar disorder (BP), sexual dysfunction, and feeding disorders.

RESULTS

PDEIs are able to improve symptoms of psychiatric disorders in preclinical models through activating the cAMP-PKA-CREB and cGMP-PKG pathways, attenuating neuroinflammation and oxidative stress, and stimulating neural plasticity. The most promising therapeutic candidates to emerge from these preclinical studies are PDE2 and PDE4 inhibitors for depression and anxiety and PDE1 and PDE10 inhibitors for schizophrenia. Furthermore, PDE3 and 4 inhibitors have shown promising results in clinical trials in patients with depression and schizophrenia.

CONCLUSIONS

Larger and better designed clinical studies of PDEIs in schizophrenia, depression, and anxiety are warranted to facilitate their translation into the clinic. Regarding the other conditions discussed in this review (most notably PTSD and BP), better characterization of the effects of PDEIs in preclinical models is required before clinical studies.

Genomic Investigation of Remission and Relapse of Psychotic Depression Treated with Sertraline plus Olanzapine: The STOP-PD II Study

INTRODUCTION

Little is known regarding genetic factors associated with treatment outcome of psychotic depression. We explored genomic associations of remission and relapse of psychotic depression treated with pharmacotherapy.

METHODS

Genomic analyses were performed in 171 men and women aged 18-85 years with an episode of psychotic depression who participated in the Study of the Pharmacotherapy of Psychotic Depression II (STOP-PD II). Participants were treated with open-label sertraline plus olanzapine for up to 12 weeks; those who achieved remission or near-remission and maintained it following 8 weeks of stabilization were eligible to participate in a 36-week randomized controlled trial that compared sertraline plus olanzapine with sertraline plus placebo in preventing relapse.

RESULTS

There were no genome-wide significant associations with either remission or relapse. However, at a suggestive threshold, SNP rs1026501 (31 kb from SYNPO2) in the whole sample and rs6844137 (within the intronic region of SYNPO2) in the European ancestry subsample were associated with a decreased likelihood of remission. In polygenic risk analyses, participants who had greater improvement after antidepressant treatments showed a higher likelihood of reaching remission. Those who achieved remission and had a higher polygenic risk for Alzheimer's disease had a significantly decreased likelihood of relapse.

CONCLUSION

Our analyses provide preliminary insights into the genetic architecture of remission and relapse in a well-characterized group of patients with psychotic depression.

Endo-Lysosomal and Autophagy Pathway and Ubiquitin-Proteasome System in Mood Disorders: A Review Article

Mood disorders are disabling conditions that cause significant functional impairment. Due to the clinical heterogeneity and complex nature of these disorders, diagnostic and treatment strategies face challenges. The etiology of mood disorders is multifactorial, involving genetic and environmental aspects that are associated with specific biological pathways including inflammation, oxidative stress, and neuroprotection. Alterations in these pathways may reduce the cell's ability to recover from stress conditions occurring during mood episodes. The endo-lysosomal and autophagy pathway (ELAP) and the ubiquitin-proteasome system (UPS) play critical roles in protein homeostasis, impacting neuroplasticity and neurodevelopment. Thus, emerging evidence has suggested a role for these pathways in mental disorders. In the case of neurodegenerative diseases (NDDs), a deeper understanding in the role of ELAP and UPS has been critical to discover new treatment targets. Since it is suggested that NDDs and mood disorders share clinical symptomatology and risk factors, it has been hypothesized that there might be common underlying molecular pathways. Here, we review the importance of the ELAP and UPS for the central nervous system and for mood disorders. Finally, we discuss potential translational strategies for the diagnosis and treatment of major depressive disorder and bipolar disorder associated with these pathways.

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.

Identification of Endocannabinoid Predictors of Treatment Outcomes in Major Depressive Disorder: A Secondary Analysis of the First Canadian Biomarker Integration Network in Depression (CAN-BIND 1) Study

INTRODUCTION

An increasing number of studies are examining the link between the endocannabinoidome and major depressive disorder (MDD). We conducted an exploratory analysis of this system to identify potential markers of treatment outcomes.

METHODS

The dataset of the Canadian Biomarker Integration Network in Depression-1 study, consisting of 180 patients with MDD treated for eight weeks with escitalopram followed by eight weeks with escitalopram alone or augmented with aripiprazole was analyzed. Association between response Montgomery-Asberg Depression Rating Scale (MADRS; score reduction≥50%) or remission (MADRS score≤10) at weeks 8 and 16 and single nucleotide polymorphisms (SNPs), methylation, and mRNA levels of 33 endocannabinoid markers were examined. A standard genome-wide association studies protocol was used for identifying SNPs, and logistic regression was used to assess methylation and mRNA levels.

RESULTS

Lower methylation of CpG islands of the diacylglycerol lipase alpha gene (DAGLA) was associated with non-remission at week 16 (DAGLA; OR=0.337, p<0.003, q=0.050). Methylation of DAGLA was correlated with improvement in Clinical Global Impression (p=0.026), Quick Inventory of Depressive Symptomatology (p=0.010), and Snaith-Hamilton Pleasure scales (p=0.028). We did not find any association between SNPs or mRNA levels and treatment outcomes.

DISCUSSION

Methylation of DAGLA is a promising candidate as a marker of treatment outcomes for MDD and needs to be explored further.

The pharmacogenomics of selective serotonin reuptake inhibitors

Antidepressant medications are frequently used as the first line of treatment for depression. However, their effectiveness is highly variable and influenced by genetic factors. Recently, pharmacogenetic studies, including candidate-gene, genome-wide association studies or polygenic risk scores, have attempted to uncover the genetic architecture of antidepressant response. Genetic variants in at least 27 genes are linked to antidepressant treatment response in both coding and non-coding genomic regions, but evidence is largely inconclusive due to the high polygenicity of the trait and limited cohort sizes in published studies. Future studies should increase the number and diversity of participants to yield sufficient statistical power to characterize the genetic underpinnings and biological mechanisms of treatment response, improve results generalizability and reduce racial health-related inequities.

The enigma of vascular depression in old age: a critical update

Depression is common in older individuals and is associated with high disability and increased mortality, yet the factors predicting late-life depression (LLD) are poorly understood. The relationship between of depressive disorder, age- and disease-related processes have generated pathogenic hypotheses and provided new treatment options. LLD syndrome is often related to a variety of vascular mechanisms, in particular hypertension, cerebral small vessel disease, white matter lesions, subcortical vascular impairment, and other processes (e.g., inflammation, neuroimmune regulatory dysmechanisms, neurodegenerative changes, amyloid accumulation) that may represent etiological factors by affecting frontolimbic and other neuronal networks predisposing to depression. The "vascular depression" hypothesis suggests that cerebrovascular disease (CVD) and vascular risk factors may predispose, induce or perpetuate geriatric depressive disorders. It is based on the presence of various cerebrovascular risk factors in many patients with LLD, its co-morbidity with cerebrovascular lesions, and the frequent development of depression after stroke. Other findings related to vascular depression are atrophy of the medial temporal cortex or generalized cortical atrophy that are usually associated with cognitive impairment. Other pathogenetic hypotheses of LLD, such as metabolic or inflammatory ones, are briefly discussed. Treatment planning should consider there may be a modest response to antidepressants, but several evidence-based and novel treatment options for LLD exist, such as electroconvulsive therapy, transcranial magnetic stimulation, neurobiology-based psychotherapy, as well as antihypertension and antiinflammatory drugs. However, their effectiveness needs further investigation, and new methodologies for prevention and treatment of depression in older individuals should be developed.

Association of Molecular Senescence Markers in Late-Life Depression With Clinical Characteristics and Treatment Outcome

IMPORTANCE

Many older adults with depression do not experience remission with antidepressant treatment, and markers of cellular senescence in late-life depression (LLD) are associated with greater severity of depression, greater executive dysfunction, and higher medical illness burden. Since these clinical characteristics are associated with remission in LLD, molecular and cellular senescence abnormalities could be a possible biological mechanism underlying poor treatment response in this population.

OBJECTIVE

To examine whether the senescence-associated secretory phenotype (SASP) index was associated with the likelihood of remission from a depressive episode in older adults.

DESIGN, SETTING, AND PARTICIPANTS

A nonrandomized, open-label clinical trial was conducted between August 2009 and August 2014 in Pittsburgh, Pennsylvania; St Louis, Missouri; and Toronto, Ontario, Canada, with older adults in a current major depressive episode according to the Diagnostic and Statistical Manual of Mental Disorders (Fourth Edition, Text Revision) diagnostic criteria. Data from biomarker analyses were reported according to the clinical trial archived plasma samples run in March 2021. Data were analyzed from June to November 2021.

EXPOSURE

Venlafaxine extended release (dose ranging from 37.5 mg to 300 mg daily) for up to 12 weeks.

MAIN OUTCOMES AND MEASURES

The association between a composite biomarker-based index (SASP index) and treatment remission in older adults with major depression was measured using clinical data and blood samples.

RESULTS

There were 416 participants with a mean (SD) age of 60.02 (7.13) years; 64% (265 participants) were self-reported female, and the mean (SD) Montgomery-Asberg Depression Rating Scale score was 26.6 (5.7). Higher SASP index scores were independently associated with higher rates of nonremission, with an increase of 1 unit in the SASP index score increasing the odds of nonremission by 19% (adjusted odds ratio, 1.19; 95% CI, 1.05-1.35; P = .006). In contrast, no individual SASP factors were associated with remission in LLD.

CONCLUSIONS AND RELEVANCE

Using clinical data and blood samples from a nonrandomized clinical trial, the results of this study suggest that molecular and cellular senescence, as measured with the SASP index, is associated with worse treatment outcomes in LLD. Combining this index score reflecting interrelated biological processes with other molecular, clinical, and neuroimaging markers may be useful in evaluating antidepressant treatment outcomes. These findings inform a path forward for geroscience-guided interventions targeting senescence to improve remission rates in LLD.

TRIAL REGISTRATION

ClinicalTrials.gov Identifier: NCT00892047.

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.

Vascular and blood-brain barrier-related changes underlie stress responses and resilience in female mice and depression in human tissue

Prevalence, symptoms, and treatment of depression suggest that major depressive disorders (MDD) present sex differences. Social stress-induced neurovascular pathology is associated with depressive symptoms in male mice; however, this association is unclear in females. Here, we report that chronic social and subchronic variable stress promotes blood-brain barrier (BBB) alterations in mood-related brain regions of female mice. Targeted disruption of the BBB in the female prefrontal cortex (PFC) induces anxiety- and depression-like behaviours. By comparing the endothelium cell-specific transcriptomic profiling of the mouse male and female PFC, we identify several pathways and genes involved in maladaptive stress responses and resilience to stress. Furthermore, we confirm that the BBB in the PFC of stressed female mice is leaky. Then, we identify circulating vascular biomarkers of chronic stress, such as soluble E-selectin. Similar changes in circulating soluble E-selectin, BBB gene expression and morphology can be found in blood serum and postmortem brain samples from women diagnosed with MDD. Altogether, we propose that BBB dysfunction plays an important role in modulating stress responses in female mice and possibly MDD.

Pathomechanisms of Vascular Depression in Older Adults

Depression in older individuals is a common complex mood disorder with high comorbidity of both psychiatric and physical diseases, associated with high disability, cognitive decline, and increased mortality The factors predicting the risk of late-life depression (LLD) are incompletely understood. The reciprocal relationship of depressive disorder and age- and disease-related processes has generated pathogenic hypotheses and provided various treatment options. The heterogeneity of depression complicates research into the underlying pathogenic cascade, and factors involved in LLD considerably differ from those involved in early life depression. Evidence suggests that a variety of vascular mechanisms, in particular cerebral small vessel disease, generalized microvascular, and endothelial dysfunction, as well as metabolic risk factors, including diabetes, and inflammation that may induce subcortical white and gray matter lesions by compromising fronto-limbic and other important neuronal networks, may contribute to the development of LLD. The "vascular depression" hypothesis postulates that cerebrovascular disease or vascular risk factors can predispose, precipitate, and perpetuate geriatric depression syndromes, based on their comorbidity with cerebrovascular lesions and the frequent development of depression after stroke. Vascular burden is associated with cognitive deficits and a specific form of LLD, vascular depression, which is marked by decreased white matter integrity, executive dysfunction, functional disability, and poorer response to antidepressive therapy than major depressive disorder without vascular risk factors. Other pathogenic factors of LLD, such as neurodegeneration or neuroimmune regulatory dysmechanisms, are briefly discussed. Treatment planning should consider a modest response of LLD to antidepressants, while vascular and metabolic factors may provide promising targets for its successful prevention and treatment. However, their effectiveness needs further investigation, and intervention studies are needed to assess which interventions are appropriate and effective in clinical practice.

A systematic review and analysis of the use of polygenic scores in pharmacogenomics

Polygenic scores (PGS) have emerged as promising tools for complex trait risk prediction. The application of these scores to pharmacogenomics provides new opportunities to improve the prediction of treatment outcomes. To gain insight into this area of research, we conducted a systematic review and accompanying analysis. This review uncovered 51 papers examining the use of PGS for drug-related outcomes, with the majority of these papers focusing on the treatment of psychiatric disorders (n=30). Due to difficulties in collecting large cohorts of uniformly treated patients, the majority of pharmacogenomic PGS were derived from large-scale genome-wide association studies of disease phenotypes that were related to the pharmacogenomic phenotypes under investigation (e.g. schizophrenia-derived PGS for antipsychotic response prediction). Examination of the research participants included in these studies revealed that the majority of cohort participants were of European descent (78.4%). These biases were also reflected in research affiliations, which were heavily weighted towards institutions located in Europe and North America, with no first or last authors originating from institutions in Africa or South Asia. There was also substantial variability in the methods used to develop PGS, with between 3 and 6.6 million variants included in the PGS. Finally, we observed significant inconsistencies in the reporting of PGS analyses and results, particularly in terms of risk model development and application, coupled with a lack of data transparency and availability, with only three pharmacogenomics PGS deposited on the PGS Catalog. These findings highlight current gaps and key areas for future pharmacogenomic PGS research.

Major Depressive Disorder in Older Patients as an Inflammatory Disorder: Implications for the Pharmacological Management of Geriatric Depression

Depression is a common and highly disabling condition in older adults. It is a heterogenous disorder and there is emerging evidence of a link between inflammation and depression in older patients, with a possible inflammatory subtype of depression. Persistent low-level inflammation, from several sources including psychological distress and chronic disease, can disrupt monoaminergic and glutaminergic systems to create dysfunctional brain networks. Despite the evidence for the role of inflammation in depression, there is insufficient evidence to recommend use of any putative anti-inflammatory agent in the treatment of depression in older adults at this stage. Further characterisation of markers of inflammation and stratification of participants with elevated rates of inflammatory markers in treatment trials is needed.