Metabolomics Biomarkers for Precision Psychiatry

Evidence from preclinical and clinical metabolomics studies on the antidepressant effects of ketamine and esketamine

The antidepressant effects of ketamine and esketamine are well-documented. Nonetheless, most of the underlying molecular mechanisms have to be uncovered yet. In the last decade, metabolomics has emerged as a useful means to investigate the metabolic phenotype associated with depression as well as changes induced by antidepressant treatments. This mini-review aims at summarizing the main findings from preclinical and clinical studies that used metabolomics to investigate the metabolic effects of subanesthetic, antidepressant doses of ketamine and esketamine and their relationship with clinical response. Both animal and human studies report alterations in several metabolic pathways - including the tricarboxylic acid cycle, glycolysis, the pentose phosphate pathway, lipid metabolism, amino acid metabolism, the kynurenine pathway, and the urea cycle - following the administration of ketamine or its enantiomers. Although more research is needed to clarify commonalities and differences in molecular mechanisms of action between the racemic compound and its enantiomers, these findings comprehensively support an influence of ketamine and esketamine on mitochondrial and cellular energy production, membrane homeostasis, neurotransmission, and signaling. Metabolomics may thus represent a promising strategy to clarify molecular mechanisms underlying treatment-resistant depression and related markers of clinical response to ketamine and esketamine. This body of preclinical and clinical evidence, if further substantiated, has the potential to guide clinicians towards personalized approaches, contributing to new paradigms in the clinical management of depression.

Present and future of metabolic and metabolomics studies focused on classical psychedelics in humans

Psychedelics are classical hallucinogen drugs that induce a marked altered state of consciousness. In recent years, there has been renewed attention to the possible use of classical psychedelics for the treatment of certain mental health disorders. However, further investigation to better understand their biological effects in humans, their mechanism of action, and their metabolism in humans is needed when considering the development of future novel therapeutic approaches. Both metabolic and metabolomics studies may help for these purposes. On one hand, metabolic studies aim to determine the main metabolites of the drug. On the other hand, the application of metabolomics in human psychedelics studies can help to further understand the biological processes underlying the psychedelic state and the mechanisms of action underlying their therapeutic potential. This review presents the state of the art of metabolic and metabolomic studies after lysergic acid diethylamide (LSD), mescaline, N,N-dimethyltryptamine (DMT) and β-carboline alkaloids (ayahuasca brew), 5-methoxy-DMT and psilocybin administrations in humans. We first describe the characteristics of the published research. Afterward, we reviewed the main results obtained by both metabolic and metabolomics (if available) studies in classical psychedelics and we found out that metabolic and metabolomics studies in psychedelics progress at two different speeds. Thus, whereas the main metabolites for classical psychedelics have been robustly established, the main metabolic alterations induced by psychedelics need to be explored. The integration of metabolomics and pharmacokinetics for investigating the molecular interaction between psychedelics and multiple targets may open new avenues in understanding the therapeutic role of psychedelics.

Metabolome subtyping reveals multi-omics characteristics and biological heterogeneity in major psychiatric disorders

Growing evidence suggests that major psychiatric disorders (MPDs) share common etiologies and pathological processes. However, the diagnosis is currently based on descriptive symptoms, which ignores the underlying pathogenesis and hinders the development of clinical treatments. This highlights the urgency of characterizing molecular biomarkers and establishing objective diagnoses of MPDs. Here, we collected untargeted metabolomics, proteomics and DNA methylation data of 327 patients with MPDs, 131 individuals with genetic high risk and 146 healthy controls to explore the multi-omics characteristics of MPDs. First, differential metabolites (DMs) were identified and we classified MPD patients into 3 subtypes based on DMs. The subtypes showed distinct metabolomics, proteomics and DNA methylation signatures. Specifically, one subtype showed dysregulation of complement and coagulation proteins, while the DNA methylation showed abnormalities in chemical synapses and autophagy. Integrative analysis in metabolic pathways identified the important roles of the citrate cycle, sphingolipid metabolism and amino acid metabolism. Finally, we constructed prediction models based on the metabolites and proteomics that successfully captured the risks of MPD patients. Our study established molecular subtypes of MPDs and elucidated their biological heterogeneity through a multi-omics investigation. These results facilitate the understanding of pathological mechanisms and promote the diagnosis and prevention of MPDs.

Downregulation of mGluR1-mediated signaling underlying autistic-like core symptoms in Shank1 P1812L-knock-in mice

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by core symptoms that consist of social deficits and repetitive behaviors. Unfortunately, no effective medication is available thus far to target the core symptoms of ASD, since the pathogenesis remains largely unknown. To investigate the pathogenesis of the core symptoms in ASD, we constructed Shank1 P1812L-knock-in (KI) mice corresponding to a recurrent ASD-related mutation, SHANK1 P1806L, to achieve construct validity and face validity. Shank1 P1812L-KI heterozygous (HET) mice presented with social deficits and repetitive behaviors without the presence of confounding comorbidities. HET mice also exhibited downregulation of metabotropic glutamate receptor (mGluR1) and associated signals, along with structural abnormalities in the dendritic spines and postsynaptic densities. Combined with findings from Shank1 R882H-KI mice, our study confirms that mGluR1-mediated signaling dysfunction is a pivotal mechanism underlying the core symptoms of ASD. Interestingly, Shank1 P1812L-KI homozygous (HOM) mice manifested behavioral signs of impaired long-term memory rather than autistic-like core traits; thus, their phenotype was markedly different from that of Shank1 P1812L-KI HET mice. Correspondingly, at the molecular level, Shank1 P1812L-KI HOM displayed upregulation of AMPA receptor (GluA2)-related signals. The different patterns of protein changes in HOM and HET mice may explain the differences in behaviors. Our study emphasizes the universality of mGluR1-signaling hypofunction in the pathogenesis of the core symptoms in ASD, providing a potential target for therapeutic drugs. The precise correspondence between genotype and phenotype, as shown in HOM and HET mice, indicates the importance of reproducing disease-related genotypes in mouse models.

Metabolomics and Self-Reported Depression, Anxiety, and Phobic Symptoms in the VA Normative Aging Study

Traditional approaches to understanding metabolomics in mental illness have focused on investigating a single disorder or comparisons between diagnoses, but a growing body of evidence suggests substantial mechanistic overlap in mental disorders that could be reflected by the metabolome. In this study, we investigated associations between global plasma metabolites and abnormal scores on the depression, anxiety, and phobic anxiety subscales of the Brief Symptom Inventory (BSI) among 405 older males who participated in the Normative Aging Study (NAS). Our analysis revealed overlapping and distinct metabolites associated with each mental health dimension subscale and four metabolites belonging to xenobiotic, carbohydrate, and amino acid classes that were consistently associated across all three symptom dimension subscales. Furthermore, three of these four metabolites demonstrated a higher degree of alteration in men who reported poor scores in all three dimensions compared to men with poor scores in only one, suggesting the potential for shared underlying biology but a differing degree of perturbation when depression and anxiety symptoms co-occur. Our findings implicate pathways of interest relevant to the overlap of mental health conditions in aging veterans and could represent clinically translatable targets underlying poor mental health in this high-risk population.

Relationship between Urinary Metabolomic Profiles and Depressive Episode in Antarctica

Antarctic expeditions have a high risk of participant depression owing to long stays and isolated environments. By quantifying the stress state and changes in biomolecules over time before the onset of depressive symptoms, predictive markers of depression can be explored. Here, we evaluated the psychological changes in 30 participants in the Japanese Antarctic Research Expedition using the Patient Health Questionnaire-9 (PHQ-9). Urinary samples were collected every three months for a year, and comprehensive urinary metabolomic profiles were quantified using liquid chromatography time-of-flight mass spectrometry. Five participants showed major depressive episodes (PHQ-9 ≥ 10) at 12 months. The urinary metabolites between these participants and the 25 unaffected participants were compared at individual metabolite and pathway levels. The individual comparisons showed the most significant differences at 12 months in 14 metabolites, including ornithine and beta-alanine. Data from shorter stays showed less significant differences. In contrast, pathway and enrichment analyses showed the most significant difference at three months and a less significant difference at longer stays. These time transitions of urinary metabolites could help in the development of urinary biomarkers to detect subjects with depressive episodes at an early stage.

New Paradigms of Old Psychedelics in Schizophrenia

Psychedelics such as lysergic acid diethylamide (LSD), psilocybin (magic mushrooms), and mescaline exhibit intense effects on the human brain and behaviour. In recent years, there has been a surge in studies investigating these drugs because clinical studies have shown that these once banned drugs are well tolerated and efficacious in medically supervised low doses called microdosing. Psychedelics have demonstrated efficacy in treating neuropsychiatric maladies such as difficult to treat anxiety, depression, mood disorders, obsessive compulsive disorders, suicidal ideation, posttraumatic stress disorder, and also in treating substance use disorders. The primary mode of action of psychedelics is activation of serotonin 5-HT_2A receptors affecting cognition and brain connectivity through the modulation of several downstream signalling pathways via complex molecular mechanisms. Some atypical antipsychotic drugs (APDs) primarily exhibit pharmacological actions through 5-HT_2A receptors, which are also the target of psychedelic drugs. Psychedelic drugs including the newer second generation along with the glutamatergic APDs are thought to mediate pharmacological actions through a common pathway, i.e., a complex serotonin-glutamate receptor interaction in cortical neurons of pyramidal origin. Furthermore, psychedelic drugs have been reported to act via a complex interplay between 5HT_2A, mGlu2/3, and NMDA receptors to mediate neurobehavioral and pharmacological actions. Findings from recent studies have suggested that serotoninergic and glutamatergic neurotransmissions are very closely connected in producing pharmacological responses to psychedelics and antipsychotic medication. Emerging hypotheses suggest that psychedelics work through brain resetting mechanisms. Hence, there is a need to dig deeply into psychedelic neurobiology to uncover how psychedelics could best be used as scientific tools to benefit psychiatric disorders including schizophrenia.

Neuroinflammation and Mitochondrial Dysfunction Link Social Stress to Depression

Major depressive disorder is a debilitating mental illness and a leading cause of global disease burden. While many etiological factors have been identified, social stress is a highly prevalent causative factor for the onset of depression. Unfortunately, rates of depression continue to increase around the world, and the recent COVID-19 pandemic has further exacerbated this mental health crisis. Though several therapeutic strategies are available, nearly 50% of patients who receive treatment never reach remission. The exact mechanisms by which social stress exposure promotes the development of depression are unclear, making it challenging to develop novel and more effective therapeutics. However, accumulating evidence points to a role for stress-induced neuroinflammation, particularly in treatment-resistant patients. Moreover, recent evidence has expanded the concept of the pathogenesis of depression to mitochondrial dysfunction, suggesting that the combined effects of social stress on mitochondria and inflammation may synergize to facilitate stress-related depression. In this chapter, we review evidence for neuroinflammation and mitochondrial dysfunction in the pathogenesis of social stress-induced depression and discuss these in the context of novel therapeutic targets for the treatment of depression.

Monitoring inflammation in psychiatry: Caveats and advice

Most researchers working in the field of immunopsychiatry would agree with the statement that "severe psychiatric disorders are associated with inflammation and more broadly with changes in immune variables". However, as many other fields in biology and medicine, immunopsychiatry suffers from a replication crisis characterized by lack of reproducibility. In this paper, we will comment on four types of immune variables which have been studied in psychiatric disorders: Acute Phase Proteins (AAPs), cytokines, lipid mediators of inflammation and immune cell parameters, and discuss the rationale for looking at them in blood. We will briefly describe the analytical methods that are currently used to measure the levels of these biomarkers and comment on overlooked analytical and statistical methodological issues that may explain some of the conflicting data reported in the literature. Lastly, we will briefly summarize what cross-sectional, longitudinal and mendelian randomization studies have brought to our understanding of schizophrenia (SZ).

Metabolomics and cardiovascular imaging: a combined approach for cardiovascular ageing

The purpose of this review is to explore how metabolomics can help uncover new biomarkers and mechanisms for cardiovascular ageing. Cardiovascular ageing refers to cardiovascular structural and functional alterations that occur with chronological ageing and that can lead to the development of cardiovascular disease. These alterations, which were previously only detectable on tissue histology or corroborated on blood samples, are now detectable with modern imaging techniques. Despite the emergence of powerful new imaging tools, clinical investigation into cardiovascular ageing is challenging because ageing is a life course phenomenon involving known and unknown risk factors that play out in a dynamic fashion. Metabolomic profiling measures large numbers of metabolites with diverse chemical properties. Metabolomics has the potential to capture changes in biochemistry brought about by pathophysiologic processes as well as by normal ageing. When combined with non-invasive cardiovascular imaging tools, metabolomics can be used to understand pathological consequences of cardiovascular ageing. This review will summarize previous metabolomics and imaging studies in cardiovascular ageing. These methods may be a clinically relevant and novel approach to identify mechanisms of cardiovascular ageing and formulate or personalize treatment strategies.

Precision Psychiatry: Biomarker-Guided Tailored Therapy for Effective Treatment and Prevention in Major Depression

Depression contributes greatly to global disability and is a leading cause of suicide. It has multiple etiologies and therefore response to treatment can vary significantly. By applying the concepts of personalized medicine, precision psychiatry attempts to optimize psychiatric patient care by better predicting which individuals will develop an illness, by giving a more accurate biologically based diagnosis, and by utilizing more effective treatments based on an individual's biological characteristics (biomarkers). In this chapter, we discuss the basic principles underlying the role of biomarkers in psychiatric pathology and then explore multiple biomarkers that are specific to depression. These include endophenotypes, gene variants/polymorphisms, epigenetic factors such as methylation, biochemical measures, circadian rhythm dysregulation, and neuroimaging findings. We also examine the role of early childhood trauma in the development of, and treatment response to, depression. In addition, we review how new developments in technology may play a greater role in the determination of new biomarkers for depression.

Biomarkers, Inflammation, and Bipolar Disorder: Association Between the Improvement of Bipolar Disorder Severity and the Improvement in C-Reactive Protein Levels After 7 Days of Inpatient Treatment

Introduction: Compared to the general population, people with severe mental illness (SMI) have a poorer health status and a higher mortality rate, with a 10-20-year reduction in life expectancy. Excess mortality and morbidity in SMI have been explained by intertwined components. Inflammatory processes could increase the morbidity and mortality risk in patients with bipolar disorder (BD) because of a bidirectional interaction between BD and conditions related to inflammation. This pilot study aimed to evaluate the relationship between C-Reactive-Protein (CRP) and bipolar disorder severity. Methods: A retrospective observational study was conducted on 61 hospitalized patients with bipolar disorder. CRP was measured at admission to inpatient treatment (T0) and after seven days from the admission (T1). Clinical Global Impression for Depression, Mania and Overall Bipolar Illness were recorded at T0 and T1. Comparisons among the recorded CRP values were determined through the paired t-test. Correlations between CRP and CGI scores were determined through Spearman's correlation coefficient at T0 and T1. Results: A statistically significant decrease in CRP values was observed after 7 days of hospitalization (p < 0.001) and positive significant correlations emerged between CRP and CGI scores at T0 and T1. Conclusion: Patients admitted to the inpatient unit reported a statistically significant decrease of CRP values during the first 7 days of treatment. Although the direction of the relationship between BP severity and inflammation status continues to remain unclear, this study showed a relationship between the improvement of bipolar disease symptoms and the improvement of the inflammatory marker CRP.

Behavioral and molecular effects of the antipsychotic drug blonanserin in the chronic mild stress model

Psychiatric disorders represent a critical challenge to our society, given their high global prevalence, complex symptomatology, elusive etiology and the variable effectiveness of pharmacological therapies. Recently, there has been a shift in investigating and redefining these diseases by integrating behavioral observations and multilevel neurobiological measures. Accordingly, endophenotype-oriented studies are needed to develop new therapeutic strategies, with the idea of targeting shared symptoms instead of one defined disease. With these premises, here we investigated the therapeutic properties of chronic treatment with the second-generation antipsychotic blonanserin in counteracting the alterations caused by 7 weeks of Chronic Mild Stress (CMS) in the rat. CMS is a well-established preclinical model able to induce depressive and anxiety-like alterations, which are shared by different psychiatric disorders. Our results demonstrated that the antipsychotic treatment normalizes the CMS-induced emotionality deficits, an effect that may be due to its ability in modulating, within the prefrontal cortex, redox mechanisms, a molecular dysfunction associated with several psychiatric disorders. These evidences provide new insights into the therapeutic properties and potential use of blonanserin as well as in its mechanisms of action and provide further support for the role of oxidative stress in the pathophysiology of psychiatric disorders.

Die "Präzisionspsychiatrie" muss Teil der "personalisierten Psychiatrie" werden

'Precision medicine' is defined as 'an emerging approach for treatment and prevention that takes into account each person's variability in genes, environment, and lifestyle'. Sometimes the term 'personalized medicine' is also used, either as a synonym or in a broader sense. In psychiatry, the term 'personalized' applies to different levels of health-care provision, such as the service organization and the choice of treatment plans based on the characterization of the individual patient. This approach is already feasible but, currently, it is often hampered by the shortage of human and financial resources. Recently, the terminology of 'precision medicine' has been extended to psychiatry: the term 'precision psychiatry' refers to the full exploitation of recent scientific and technological advances to achieve a close match between individual biosignature and prevention / treatment strategies. This article provides an overview of recent advances in neuroimaging, multi-omics and computational neuroscience, which have contributed to foster our understanding of the neurobiology of major mental disorders, and led to the implementation of a precision medicine-oriented approach in psychiatry.We argue that, while 'precision psychiatry' represents an important step to further advance the effectiveness of the 'personalized psychiatry', the distinction between the two terms is important to avoid dangerous neglect of the current potential of personalized care in psychiatry and to underscore the need for disseminating good existing practices aimed at organizing mental health services and providing care according to person's psychopathological characteristics, illness trajectory, needs, environment and preferences.In conclusion, 'precision psychiatry' will contribute to advance 'personalized psychiatry', but for the time being keeping the distinction between the two terms will contribute to fully exploit the current potential of personalized care.

Biomarkers in Psychiatry: Concept, Definition, Types and Relevance to the Clinical Reality

During the last years, an extraordinary effort has been made to identify biomarkers as potential tools for improving prevention, diagnosis, drug response and drug development in psychiatric disorders. Contrary to other diseases, mental illnesses are classified by diagnostic categories with a broad variety list of symptoms. Consequently, patients diagnosed from the same psychiatric illness present a great heterogeneity in their clinical presentation. This fact together with the incomplete knowledge of the neurochemical alterations underlying mental disorders, contribute to the limited efficacy of current pharmacological options. In this respect, the identification of biomarkers in psychiatry is becoming essential to facilitate diagnosis through the developing of markers that allow to stratify groups within the syndrome, which in turn may lead to more focused treatment options. In order to shed light on this issue, this review summarizes the concept and types of biomarkers including an operational definition for therapeutic development. Besides, the advances in this field were summarized and sorted into five categories, which include genetics, transcriptomics, proteomics, metabolomics, and epigenetics. While promising results were achieved, there is a lack of biomarker investigations especially related to treatment response to psychiatric conditions. This review includes a final conclusion remarking the future challenges required to reach the goal of developing valid, reliable and broadly-usable biomarkers for psychiatric disorders and their treatment. The identification of factors predicting treatment response will reduce trial-and-error switches of medications facilitating the discovery of new effective treatments, being a crucial step towards the establishment of greater personalized medicine.