Dissecting the genetic overlap between severe mental disorders and markers of cellular aging: Identification of pleiotropic genes and druggable targets.

Patients with severe mental disorders such as bipolar disorder (BD), schizophrenia (SCZ) and major depressive disorder (MDD) show a substantial reduction in life expectancy, increased incidence of comorbid medical conditions commonly observed with advanced age and alterations of aging hallmarks. While severe mental disorders are heritable, the extent to which genetic predisposition might contribute to accelerated cellular aging is not known. We used bivariate causal mixture models to quantify the trait-specific and shared architecture of mental disorders and 2 aging hallmarks (leukocyte telomere length [LTL] and mitochondrial DNA copy number), and the conjunctional false discovery rate method to detect shared genetic loci. We integrated gene expression data from brain regions from GTEx and used different tools to functionally annotate identified loci and investigate their druggability. Aging hallmarks showed low polygenicity compared with severe mental disorders. We observed a significant negative global genetic correlation between MDD and LTL (rg = -0.14, p = 6.5E-10), and no significant results for other severe mental disorders or for mtDNA-cn. However, conditional QQ plots and bivariate causal mixture models pointed to significant pleiotropy among all severe mental disorders and aging hallmarks. We identified genetic variants significantly shared between LTL and BD (n = 17), SCZ (n = 55) or MDD (n = 19), or mtDNA-cn and BD (n = 4), SCZ (n = 12) or MDD (n = 1), with mixed direction of effects. The exonic rs7909129 variant in the SORCS3 gene, encoding a member of the retromer complex involved in protein trafficking and intracellular/intercellular signaling, was associated with shorter LTL and increased predisposition to all severe mental disorders. Genetic variants underlying risk of SCZ or MDD and shorter LTL modulate expression of several druggable genes in different brain regions. Genistein, a phytoestrogen with anti-inflammatory and antioxidant effects, was an upstream regulator of 2 genes modulated by variants associated with risk of MDD and shorter LTL. While our results suggest that shared heritability might play a limited role in contributing to accelerated cellular aging in severe mental disorders, we identified shared genetic determinants and prioritized different druggable targets and compounds.

Symptomatic remission and recovery in major psychosis: Is there a role for BDNF? A secondary analysis of the LABSP cohort data.

Remission, relapse prevention, and clinical recovery are crucial areas of interest in schizophrenia (SCZ) research. Although SCZ is a chronic disorder with poor overall outcomes, years of research demonstrated that recovery is possible. There are considerable data linking brain-derived neurotrophic factor (BDNF) to SCZ, however, evidence on the role of BDNF in remission in SCZ is scarce. This secondary analysis of the Longitudinal Assessment of BDNF in Sardinian patients (LABSP) data aimed to investigate the relationship between serum BDNF levels and symptomatic remission, simultaneous clinical and functional remission, and recovery in patients with SCZ. A total of 105 patients with SCZ or schizoaffective disorder were recruited for a longitudinal assessment of BDNF levels over 24 months. Longitudinal data were analyzed using mixed-effects linear regression models. The study found significant associations between use of long acting injectables (χ2 = 7.075, df = 1, p = 0.008), baseline serum BDNF levels (U = 701, z = -2.543, p = 0.011), and "childhood" (U = 475, z = -2.124, p = 0.034) and "general" (U = 55, z = -2.014, p = 0.044) subscales of the Premorbid Adjustment Scale (PAS) with patients maintaining remission and recovery. The diagnosis of SCZ was significantly associated with lower BDNF levels for patients with simultaneous clinical and functional remission (Z = 2.035, p = 0.0419) and recovery (Z = 2.009, p = 0.0445) compared to those without. There were no significant associations between remission in the entire sample and longitudinal serum BDNF levels or genetic variants within the BDNF gene. These findings provide further insight into the complex relationship between BDNF and SCZ.

A Pilot Interaction Analysis of Gut Microbiota and Peripheral Markers of Aging in Severe Psychiatric Disorders: A Role for Lachnoclostridium?

Excessive predominance of pathological species in the gut microbiota could increase the production of inflammatory mediators at the gut level and, via modification of the gut-blood barrier, at the systemic level. This pro-inflammatory state could, in turn, increase biological aging that is generally proxied by telomere shortening. In this study, we present findings from a secondary interaction analysis of gut microbiota, aging, and inflammatory marker data from a cohort of patients with different diagnoses of severe mental disorders. We analyzed 15 controls, 35 patients with schizophrenia (SCZ), and 31 patients with major depressive disorder (MDD) recruited among those attending a community mental health center (50 males and 31 females, mean and median age 46.8 and 46.3 years, respectively). We performed 16S rRNA sequencing as well as measurement of telomere length via quantitative fluorescence in situ hybridization and high-sensitivity C-reactive protein. We applied statistical modeling with logistic regression to test for interaction between gut microbiota and these markers. Our results showed statistically significant interactions between telomere length and gut microbiota pointing to the genus Lachnostridium, which remained significantly associated with a reduced likelihood of MDD even after adjustment for a series of covariates. Although exploratory, these findings show that specific gut microbiota signatures overexpressing Lachnoclostridium and interacting with biological aging could modulate the liability for MDD.

Melatonin MT1 receptors as a target for the psychopharmacology of bipolar disorder: A translational study.

The treatment of bipolar disorder (BD) still remains a challenge. Melatonin (MLT), acting through its two receptors MT1 and MT2, plays a key role in regulating circadian rhythms which are dysfunctional in BD. Using a translational approach, we examined the implication and potential of MT1 receptors in the pathophysiology and psychopharmacology of BD. We employed a murine model of the manic phase of BD (Clock mutant (ClockΔ19) mice) to study the activation of MT1 receptors by UCM871, a selective partial agonist, in behavioral pharmacology tests and in-vivo electrophysiology. We then performed a high-resolution Nuclear Magnetic Resonance study on isolated membranes to characterize the molecular mechanism of interaction of UCM871. Finally, in a cohort of BD patients, we investigated the link between clinical measures of BD and genetic variants located in the MT1 receptor and CLOCK genes. We demonstrated that: 1) UCM871 can revert behavioral and electrophysiological abnormalities of ClockΔ19 mice; 2) UCM871 promotes the activation state of MT1 receptors; 3) there is a significant association between the number of severe manic episodes and MLT levels, depending on the genetic configuration of the MT1 rs2165666 variant. Overall, this work lends support to the potentiality of MT1 receptors as target for the treatment of BD.

Biological markers of sex-based differences in major depressive disorder and in antidepressant response.

Major depressive disorder (MDD) presents different clinical features in women and men, with women being more affected and responding differently to antidepressant treatment. Specific molecular mechanisms underlying these differences are not well studied and this narrative review aims at providing an overview of the neurobiological features underlying sex-differences in biological systems involved in MDD pathophysiology and response to antidepressant treatment, focusing on human studies. The majority of the reviewed studies were performed through candidate gene approaches, focusing on biological systems involved in MDD pathophysiology, including the stress response, inflammatory and immune, monoaminergic, neurotrophic, gamma-aminobutyric acid and glutamatergic, and oxytocin systems. The influence of the endocrine system and sex-specific hormone effects are also discussed. Genome, epigenome and transcriptome-wide approaches are less frequently performed and most of these studies do not focus on sex-specific alterations, revealing a paucity of omics studies directed to unravel sex-based differences in MDD. Few studies about sex-related differences in antidepressant treatment response have been conducted, mostly involving the inflammatory system, with less evidence on the monoaminergic system and sparse evidence in omics approaches. Our review covers the importance of accounting for sex-differences in research, optimizing patient stratification for a more precise diagnostic and individualized treatment for women and men.

RNA Biomarkers in Bipolar Disorder and Response to Mood Stabilizers.

Bipolar disorder (BD) is a severe chronic disorder that represents one of the main causes of disability among young people. To date, no reliable biomarkers are available to inform the diagnosis of BD or clinical response to pharmacological treatment. Studies focused on coding and noncoding transcripts may provide information complementary to genome-wide association studies, allowing to correlate the dynamic evolution of different types of RNAs based on specific cell types and developmental stage with disease development or clinical course. In this narrative review, we summarize findings from human studies that evaluated the potential utility of messenger RNAs and noncoding transcripts, such as microRNAs, circular RNAs and long noncoding RNAs, as peripheral markers of BD and/or response to lithium and other mood stabilizers. The majority of available studies investigated specific targets or pathways, with large heterogeneity in the included type of cells or biofluids. However, a growing number of studies are using hypothesis-free designs, with some studies also integrating data on coding and noncoding RNAs measured in the same participants. Finally, studies conducted in neurons derived from induced-pluripotent stem cells or in brain organoids provide promising preliminary findings supporting the power and utility of these cellular models to investigate the molecular determinants of BD and clinical response.

Probing the Association between Cognition, Suicidal Behavior and Tryptophan Metabolism in a Sample of Individuals Living with Bipolar Disorder: A Secondary Analysis.

Background and Objectives: Alterations in hot cognition and in the tryptophan metabolism through serotonin (5-HT) and kynurenine (KYN) pathways have been associated with an increased risk of suicidal behavior. Here, we aim at probing the association between Stroop test performances and tryptophan pathway components in a sample of individuals with bipolar disorder (BD). Materials and Methods: We explored the association between the Emotion Inhibition Subtask (EIS) performances of the Brief Assessment of Cognition for Affective Disorders (BAC-A) and plasmatic levels of 5-hydroxytriptophan (5-HTP), 5-HT, KYN, 3-hydroxykynurenine (3-HK), quinolinic acid (QA), and kynurenic acid (KYNA) among subjects reporting lifetime suicide ideation (LSI) vs. non-LSI and subjects reporting lifetime suicide attempts (LSA) vs. non-LSA. Results: In a sample of 45 subjects with BD, we found a statistically significant different performance for LSA vs. non-LSA in the color naming (CN) and neutral words (NW) EIS subtasks. There was a significant association between CN performances and plasma 5-HTP levels among LSI and LSA subjects but not among non-LSI or non-LSA. Conclusions: In our sample, patients with LSA and LSI presented lower performances on some EIS subtasks compared to non-LSA and non-LSI. Moreover, we found an inverse correlation between plasma 5-HTP concentration and some EIS performances in LSA and LSI but not among non-LSA or non-LSI. This may represent an interesting avenue for future studies probing this complex association.

A genome-wide association study of antidepressant-induced mania.

Antidepressant-induced mania (AIM) is a side effect of antidepressant treatment that is characterized by mania or hypomania after the start of medication. It is likely polygenic, but its genetic component remains largely unexplored. We aim to conduct the first genome-wide association study of AIM in 814 bipolar disorder patients of European ancestry. We report no significant findings from our single-marker or gene-based analyses. Our polygenic risk score analyses also did not yield significant results with bipolar disorder, antidepressant response, or lithium response. Our suggestive findings on the hypothalamic-pituitary-adrenal axis and the opioid system in AIM require independent replications.

Pharmacokinetic Markers of Clinical Outcomes in Severe Mental Illness: A Systematic Review.

The term severe mental illness (SMI) encompasses those psychiatric disorders exerting the highest clinical burden and socio-economic impact on the affected individuals and their communities. Pharmacogenomic (PGx) approaches hold great promise in personalizing treatment selection and clinical outcomes, possibly reducing the burden of SMI. Here, we sought to review the literature in the field, focusing on PGx testing and particularly on pharmacokinetic markers. We performed a systematic review on PUBMED/Medline, Web of Science, and Scopus. The last search was performed on the 17 September 2022, and further augmented with a comprehensive pearl-growing strategy. In total, 1979 records were screened, and after duplicate removal, 587 unique records were screened by at least 2 independent reviewers. Ultimately, forty-two articles were included in the qualitative analysis, eleven randomized controlled trials and thirty-one nonrandomized studies. The observed lack of standardization in PGx tests, population selection, and tested outcomes limit the overall interpretation of the available evidence. A growing body of evidence suggests that PGx testing might be cost-effective in specific settings and may modestly improve clinical outcomes. More efforts need to be directed toward improving PGx standardization, knowledge for all stakeholders, and clinical practice guidelines for screening recommendations.

Multi-omics data integration methods and their applications in psychiatric disorders.

To study mental illness and health, in the past researchers have often broken down their complexity into individual subsystems (e.g., genomics, transcriptomics, proteomics, clinical data) and explored the components independently. Technological advancements and decreasing costs of high throughput sequencing has led to an unprecedented increase in data generation. Furthermore, over the years it has become increasingly clear that these subsystems do not act in isolation but instead interact with each other to drive mental illness and health. Consequently, individual subsystems are now analysed jointly to promote a holistic understanding of the underlying biological complexity of health and disease. Complementing the increasing data availability, current research is geared towards developing novel methods that can efficiently combine the information rich multi-omics data to discover biologically meaningful biomarkers for diagnosis, treatment, and prognosis. However, clinical translation of the research is still challenging. In this review, we summarise conventional and state-of-the-art statistical and machine learning approaches for discovery of biomarker, diagnosis, as well as outcome and treatment response prediction through integrating multi-omics and clinical data. In addition, we describe the role of biological model systems and in silico multi-omics model designs in clinical translation of psychiatric research from bench to bedside. Finally, we discuss the current challenges and explore the application of multi-omics integration in future psychiatric research. The review provides a structured overview and latest updates in the field of multi-omics in psychiatry.

An integrated precision medicine approach in major depressive disorder: a study protocol to create a new algorithm for the prediction of treatment response.

Major depressive disorder (MDD) is the most common psychiatric disease worldwide with a huge socio-economic impact. Pharmacotherapy represents the most common option among the first-line treatment choice; however, only about one third of patients respond to the first trial and about 30% are classified as treatment-resistant depression (TRD). TRD is associated with specific clinical features and genetic/gene expression signatures. To date, single sets of markers have shown limited power in response prediction. Here we describe the methodology of the PROMPT project that aims at the development of a precision medicine algorithm that would help early detection of non-responder patients, who might be more prone to later develop TRD. To address this, the project will be organized in 2 phases. Phase 1 will involve 300 patients with MDD already recruited, comprising 150 TRD and 150 responders, considered as extremes phenotypes of response. A deep clinical stratification will be performed for all patients; moreover, a genomic, transcriptomic and miRNomic profiling will be conducted. The data generated will be exploited to develop an innovative algorithm integrating clinical, omics and sex-related data, in order to predict treatment response and TRD development. In phase 2, a new naturalistic cohort of 300 MDD patients will be recruited to assess, under real-world conditions, the capability of the algorithm to correctly predict the treatment outcomes. Moreover, in this phase we will investigate shared decision making (SDM) in the context of pharmacogenetic testing and evaluate various needs and perspectives of different stakeholders toward the use of predictive tools for MDD treatment to foster active participation and patients' empowerment. This project represents a proof-of-concept study. The obtained results will provide information about the feasibility and usefulness of the proposed approach, with the perspective of designing future clinical trials in which algorithms could be tested as a predictive tool to drive decision making by clinicians, enabling a better prevention and management of MDD resistance.

Converging Evidence Points to BDNF as Biomarker of Depressive Symptoms in Schizophrenia-Spectrum Disorders.

Brain-derived neurotrophic factor (BDNF) is a key modulator of neuroplasticity and has an important role in determining the susceptibility to severe psychiatric disorder with a significant neurodevelopmental component such as major psychoses. Indeed, a potential association between BDNF serum levels and schizophrenia (SCZ) and schizoaffective disorder (SAD) has been tested in diverse studies and a considerable amount of them found reduced BDNF levels in these disorders. Here, we aimed at testing the association of BDNF serum levels with several demographic, clinical, and psychometric measures in 105 patients with SCZ and SAD, assessing the moderating effect of genetic variants within the BDNF gene. We also verified whether peripheral BDNF levels differed between patients with SCZ and SAD. Our findings revealed that BDNF serum levels are significantly lower in patients affected by SCZ and SAD presenting more severe depressive symptomatology. This finding awaits replication in future independent studies and points to BDNF as a possible prognostic indicator in major psychoses.

Investigation of Genetic Variants Associated with Tryptophan Metabolite Levels via Serotonin and Kynurenine Pathways in Patients with Bipolar Disorder.

The kynurenine pathway (KP) may play a role in the pathophysiology of bipolar disorder (BD). We conducted a genome-wide association study (GWAS) to identify genetic variants associated with the plasma levels of the metabolites of tryptophan (TRP) via the serotonin (5-HT) and kynurenine (KYN) pathways in 44 patients with BD and 45 healthy controls. We assessed whether variants that were differentially associated with metabolite levels based on the diagnostic status improved the prediction accuracy of BD using penalized regression approaches. We identified several genetic variants that were significantly associated with metabolites (5-HT, 5-hydroxytryptophan (5-HTP), TRP, and quinolinic acid (QA) or metabolite ratios (5-HTP/TRP and KYN/TRP) and for which the diagnostic status exerted a significant effect. The inclusion of genetic variants led to increased accuracy in the prediction of the BD diagnostic status. Specifically, we obtained an accuracy of 0.77 using Least Absolute Shrinkage and Selection Operator (LASSO) regression. The predictors retained as informative in this model included body mass index (BMI), the levels of TRP, QA, and 5-HT, the 5-HTP/TRP ratio, and genetic variants associated with the levels of QA (rs6827515, rs715692, rs425094, rs4645874, and rs77048355) and TRP (rs292212) or the 5-HTP/TRP ratio (rs7902231). In conclusion, our study identified statistically significant associations between metabolites of TRP via the 5-HT and KYN pathways and genetic variants at the genome-wide level. The discriminative performance of penalized regression models incorporating clinical, genetic, and metabolic predictors warrants a follow-up analysis of this panel of determinants.

Exploring the association between brain-derived neurotrophic factor levels and longitudinal psychopathological and cognitive changes in Sardinian psychotic patients.

BACKGROUND AND HYPOTHESIS: Schizophrenia spectrum disorders are among the most debilitating mental disorders and has complex pathophysiological underpinnings. There is growing evidence that brain-derived neurotrophic factor (BDNF) can play a role in its pathogenesis. The present study investigated the longitudinal variation of serum BDNF levels in a 24-month observational prospective cohort study of Sardinian psychotic patients and its relationship with psychopathological and cognitive changes. Furthermore, we examined whether genetic variation within the BDNF gene could moderate these relationships. STUDY DESIGN: Every 6 months, 105 patients were assessed for their BDNF serum levels, as well as for a series of psychopathological, cognitive, and social measures. We performed a targeted analysis of four tag single nucleotide polymorphisms within the BDNF gene that were selected and analyzed using polymerase chain reaction. Longitudinal data were analyzed using mixed-effects linear regression models. STUDY RESULTS: We observed a declining longitudinal trajectory of BDNF levels in psychotic patients in general, and in relation to the severity of depressive and negative symptoms. BDNF serum levels also declined in patients scoring lower in cognitive measures such as attention and speed of information processing and verbal fluency. The rs7934165 polymorphism moderated the significant association between verbal fluency and BDNF levels. CONCLUSIONS: These findings in patients from real-world settings suggest a plausible role of peripheral BDNF levels as a marker of illness burden in schizophrenia spectrum disorders.

Analysis on in vitro effect of lithium on telomere length in lymphoblastoid cell lines from bipolar disorder patients with different clinical response to long-term lithium treatment.

BACKGROUND: It has been suggested that bipolar disorder (BD) is associated with clinical and biological features of accelerated aging. In our previous studies, we showed that long-term lithium treatment was correlated with longer leukocyte telomere length (LTL) in BD patients. A recent study explored the role of TL in BD using patients-derived lymphoblastoid cell lines (LCLs), showing that baseline TL was shorter in BD compared to controls and that lithium in vitro increased TL but only in BD. Here, we used the same cell system (LCLs) to explore if a 7-day treatment protocol with lithium chloride (LiCl) 1 mM was able to highlight differences in TL between BD patients clinically responders (Li-R; n = 15) or non-responders (Li-NR; n = 15) to lithium, and if BD differed from non-psychiatric controls (HC; n = 15). RESULTS: There was no difference in TL between BD patients and HC. Moreover, LiCl did not influence TL in the overall sample, and there was no difference between diagnostic or clinical response groups. Likewise, LiCl did not affect TL in neural precursor cells from healthy donors. CONCLUSIONS: Our findings suggest that a 7-day lithium treatment protocol and the use of LCLs might not represent a suitable approach to deepen our understanding on the role of altered telomere dynamics in BD as previously suggested by studies in vivo.

Cost-Utility Analysis of Pharmacogenetic Testing Based on CYP2C19 or CYP2D6 in Major Depressive Disorder: Assessing the Drivers of Different Cost-Effectiveness Levels from an Italian Societal Perspective.

BACKGROUND AND OBJECTIVES: Major depressive disorder (MDD) is a common and severe psychiatric disorder that has enormous economical and societal costs. As pharmacogenetics is one of the key tools of precision psychiatry, we analyze the cost-utility of test screening of CYP2C19 and CYP2D6 for patients suffering from major depressive disorder (MDD) and try to understand the main drivers that influence the cost-utility. METHODS: We developed two pharmacoeconomic nonhomogeneous Markov models to test the cost-utility, from an Italian societal perspective, of pharmacogenetic testing genetic to characterize the metabolizing profiles of cytochrome P450 (CYP) 2C19 and CYP2D6 in a hypothetical case study of patients suffering from major depressive disorder (MDD). The model considers different scenarios of adjustment of antidepressant treatment according to the patient's metabolizing profile or treatment over a period of 18 weeks. The uncertainty of model parameters is tested through both a probabilistic sensitivity analysis and a one-way deterministic sensitivity analysis, and these results are used in a post-hoc analysis to understand the main drivers of three alternative cost-effectiveness levels ("poor," "standard," and "high"). These drivers are first evaluated from an exploratory multidimensional perspective and next from a predictive perspective as the probability that a patient belongs to a specific cost-effectiveness level is estimated on the basis of a restricted set of parameters used in the original pharmacoeconomic model. RESULTS: The models for CYP2C19 and CYP2D6 indicate that screening has an incremental cost-effectiveness ratio of 60,000€ and 47,000€ per quality-adjusted life year (QALY), respectively. The probabilistic sensitivity analysis shows that the treatments are cost-effective for a 75,000€ willingness to pay (WTP) threshold in 58% and 63% of the Monte Carlo replications, respectively. The post-hoc analysis highlights the factors that allow us to clearly discriminates poor cost-effectiveness from high cost-effectiveness scenarios and demonstrates that it is possible to predict with reasonable accuracy the cost-effectiveness of a genetic test and the associated therapeutic pattern. CONCLUSIONS: Our findings suggest that screenings for both CYP2C19 and CYP2D6 enzymes for patients with MDD are cost-effective for a WTP threshold of 75,000€ per QALY, and provide relevant suggestions about the most important aspects to be further explored in clinical studies aimed at addressing the cost-effectiveness of genetic testing for patients diagnosed with MDD.

Ethical considerations for precision psychiatry: A roadmap for research and clinical practice.

Precision psychiatry is an emerging field with transformative opportunities for mental health. However, the use of clinical prediction models carries unprecedented ethical challenges, which must be addressed before accessing the potential benefits of precision psychiatry. This critical review covers multidisciplinary areas, including psychiatry, ethics, statistics and machine-learning, healthcare and academia, as well as input from people with lived experience of mental disorders, their family, and carers. We aimed to identify core ethical considerations for precision psychiatry and mitigate concerns by designing a roadmap for research and clinical practice. We identified priorities: learning from somatic medicine; identifying precision psychiatry use cases; enhancing transparency and generalizability; fostering implementation; promoting mental health literacy; communicating risk estimates; data protection and privacy; and fostering the equitable distribution of mental health care. We hope this blueprint will advance research and practice and enable people with mental health problems to benefit from precision psychiatry.

Is Poor Lithium Response in Individuals with Bipolar Disorder Associated with Increased Degradation of Tryptophan along the Kynurenine Pathway? Results of an Exploratory Study.

Bipolar disorder is associated with an inflammation-triggered elevated catabolism of tryptophan to the kynurenine pathway, which impacts psychiatric symptoms and outcomes. The data indicate that lithium exerts anti-inflammatory effects by inhibiting indoleamine-2,3-dioxygenase (IDO)-1 activity. This exploratory study aimed to investigate the tryptophan catabolism in individuals with bipolar disorder (n = 48) compared to healthy controls (n = 48), and the associations with the response to mood stabilizers such as lithium, valproate, or lamotrigine rated with the Retrospective Assessment of the Lithium Response Phenotype Scale (or the Alda scale). The results demonstrate an association of a poorer response to lithium with higher levels of kynurenine, kynurenine/tryptophan ratio as a proxy for IDO-1 activity, as well as quinolinic acid, which, overall, indicates a pro-inflammatory state with a higher degradation of tryptophan towards the neurotoxic branch. The treatment response to valproate and lamotrigine was not associated with the levels of the tryptophan metabolites. These findings support the anti-inflammatory properties of lithium. Furthermore, since quinolinic acid has neurotoxic features via the glutamatergic pathway, they also strengthen the assumption that the clinical drug response might be associated with biochemical processes. The relationship between the lithium response and the measurements of the tryptophan to the kynurenine pathway is of clinical relevance and may potentially bring advantages towards a personalized medicine approach to bipolar disorder that allows for the selection of the most effective mood-stabilizing drug.