Multidimensional Connectomics and Treatment-Resistant Schizophrenia: Linking Phenotypic Circuits to Targeted Therapeutics

Effects of ulotaront on brain circuits of reward, working memory, and emotion processing in healthy volunteers with high or low schizotypy

Ulotaront, a trace amine-associated receptor 1 (TAAR1) and serotonin 5-HT1A receptor agonist without antagonist activity at dopamine D2 or the serotonin 5-HT2A receptors, has demonstrated efficacy in the treatment of schizophrenia. Here we report the phase 1 translational studies that profiled the effect of ulotaront on brain responses to reward, working memory, and resting state connectivity (RSC) in individuals with low or high schizotypy (LS or HS). Participants were randomized to placebo (n = 32), ulotaront (50 mg; n = 30), or the D2 receptor antagonist amisulpride (400 mg; n = 34) 2 h prior to functional magnetic resonance imaging (fMRI) of blood oxygen level-dependent (BOLD) responses to task performance. Ulotaront increased subjective drowsiness, but reaction times were impaired by less than 10% and did not correlate with BOLD responses. In the Monetary Incentive Delay task (reward processing), ulotaront significantly modulated striatal responses to incentive cues, induced medial orbitofrontal responses, and prevented insula activation seen in HS subjects. In the N-Back working memory task, ulotaront modulated BOLD signals in brain regions associated with cognitive impairment in schizophrenia. Ulotaront did not show antidepressant-like biases in an emotion processing task. HS had significantly reduced connectivity in default, salience, and executive networks compared to LS participants and both drugs reduced this difference. Although performance impairment may have weakened or contributed to the fMRI findings, the profile of ulotaront on BOLD activations elicited by reward, memory, and resting state is compatible with an indirect modulation of dopaminergic function as indicated by preclinical studies. This phase 1 study supported the subsequent clinical proof of concept trial in people with schizophrenia.Clinical trial registration: Registry# and URL: ClinicalTrials.gov NCT01972711, https://clinicaltrials.gov/ct2/show/NCT01972711.

Altered Patterns of Brain Glucose Metabolism Involve More Extensive and Discrete Cortical Areas in Treatment-resistant Schizophrenia Patients Compared to Responder Patients and Controls: Results From a Head-to-Head 2-[18F]-FDG-PET Study

BACKGROUND AND HYPOTHESIS

Treatment resistant schizophrenia (TRS) affects almost 30% of patients with schizophrenia and has been considered a different phenotype of the disease. In vivo characterization of brain metabolic patterns associated with treatment response could contribute to elucidate the neurobiological underpinnings of TRS. Here, we used 2-[18F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) to provide the first head-to-head comparative analysis of cerebral glucose metabolism in TRS patients compared to schizophrenia responder patients (nTRS), and controls. Additionally, we investigated, for the first time, the differences between clozapine responders (Clz-R) and non-responders (Clz-nR).

STUDY DESIGN

53 participants underwent FDG-PET studies (41 patients and 12 controls). Response to conventional antipsychotics and to clozapine was evaluated using a standardized prospective procedure based on PANSS score changes. Maps of relative brain glucose metabolism were processed for voxel-based analysis using Statistical Parametric Mapping software.

STUDY RESULTS

Restricted areas of significant bilateral relative hypometabolism in the superior frontal gyrus characterized TRS compared to nTRS. Moreover, reduced parietal and frontal metabolism was associated with high PANSS disorganization factor scores in TRS (P < .001 voxel level uncorrected, P < .05 cluster level FWE-corrected). Only TRS compared to controls showed significant bilateral prefrontal relative hypometabolism, more extensive in CLZ-nR than in CLZ-R (P < .05 voxel level FWE-corrected). Relative significant hypermetabolism was observed in the temporo-occipital regions in TRS compared to nTRS and controls.

CONCLUSIONS

These data indicate that, in TRS patients, altered metabolism involved discrete brain regions not found affected in nTRS, possibly indicating a more severe disrupted functional brain network associated with disorganization symptoms.

Dopamine Dynamics and Neurobiology of Non-Response to Antipsychotics, Relevance for Treatment Resistant Schizophrenia: A Systematic Review and Critical Appraisal

Treatment resistant schizophrenia (TRS) is characterized by a lack of, or suboptimal response to, antipsychotic agents. The biological underpinnings of this clinical condition are still scarcely understood. Since all antipsychotics block dopamine D2 receptors (D2R), dopamine-related mechanisms should be considered the main candidates in the neurobiology of antipsychotic non-response, although other neurotransmitter systems play a role. The aims of this review are: (i) to recapitulate and critically appraise the relevant literature on dopamine-related mechanisms of TRS; (ii) to discuss the methodological limitations of the studies so far conducted and delineate a theoretical framework on dopamine mechanisms of TRS; and (iii) to highlight future perspectives of research and unmet needs. Dopamine-related neurobiological mechanisms of TRS may be multiple and putatively subdivided into three biological points: (1) D2R-related, including increased D2R levels; increased density of D2Rs in the high-affinity state; aberrant D2R dimer or heteromer formation; imbalance between D2R short and long variants; extrastriatal D2Rs; (2) presynaptic dopamine, including low or normal dopamine synthesis and/or release compared to responder patients; and (3) exaggerated postsynaptic D2R-mediated neurotransmission. Future points to be addressed are: (i) a more neurobiologically-oriented phenotypic categorization of TRS; (ii) implementation of neurobiological studies by directly comparing treatment resistant vs. treatment responder patients; (iii) development of a reliable animal model of non-response to antipsychotics.

Artificial intelligence and machine-learning approaches in structure and ligand-based discovery of drugs affecting central nervous system

CNS disorders are indications with a very high unmet medical needs, relatively smaller number of available drugs, and a subpar satisfaction level among patients and caregiver. Discovery of CNS drugs is extremely expensive affair with its own unique challenges leading to extremely high attrition rates and low efficiency. With explosion of data in information age, there is hardly any aspect of life that has not been touched by data driven technologies such as artificial intelligence (AI) and machine learning (ML). Drug discovery is no exception, emergence of big data via genomic, proteomic, biological, and chemical technologies has driven pharmaceutical giants to collaborate with AI oriented companies to revolutionise drug discovery, with the goal of increasing the efficiency of the process. In recent years many examples of innovative applications of AI and ML techniques in CNS drug discovery has been reported. Research on therapeutics for diseases such as schizophrenia, Alzheimer's and Parkinsonism has been provided with a new direction and thrust from these developments. AI and ML has been applied to both ligand-based and structure-based drug discovery and design of CNS therapeutics. In this review, we have summarised the general aspects of AI and ML from the perspective of drug discovery followed by a comprehensive coverage of the recent developments in the applications of AI/ML techniques in CNS drug discovery.

Alterations in the volume of thalamic nuclei in patients with schizophrenia and persistent auditory hallucinations

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Analysis of structural MRI images using a probabilistic atlas for segmentation of several nuclei of the thalamus.

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Comparison of chronic patients with schizophrenia, with and without auditory hallucinations and matched healthy controls.

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Volumetric reductions in patients with AH vs controls: Medial geniculate nucleus, anterior pulvinar nucleus and lateral and medial mediodorsal nuclei.

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In patients without AH we found reductions in the volume of the pulvinar and mediodorsal nuclei, but not in the medial geniculate nucleus.

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Found also some significant correlations between the volume of these nuclei and the total score of the PSYRATS scale.

The thalamus is a subcortical structure formed by different nuclei that relay information to the neocortex. Several reports have already described alterations of this structure in patients of schizophrenia that experience auditory hallucinations. However, to date no study has addressed whether the volumes of specific thalamic nuclei are altered in chronic patients experiencing persistent auditory hallucinations. We have processed structural MRI images using Freesurfer, and have segmented them into 25 nuclei using the probabilistic atlas developed by Iglesias and collaborators (Iglesias et al., 2018). To homogenize the sample, we have matched patients of schizophrenia, with and without persistent auditory hallucinations, with control subjects, considering sex, age and their estimated intracranial volume. This rendered a group number of 41 patients experiencing persistent auditory hallucinations, 35 patients without auditory hallucinations, and 55 healthy controls. In addition, we have also correlated the volume of the altered thalamic nuclei with the total score of the PSYRATS, a clinical scale used to evaluate the positive symptoms of this disorder. We have found alterations in the volume of 8 thalamic nuclei in both cohorts of patients with schizophrenia: The medial and lateral geniculate nuclei, the anterior, inferior, and lateral pulvinar nuclei, the lateral complex and the lateral and medial mediodorsal nuclei. We have also found some significant correlations between the volume of these nuclei in patients experiencing auditory hallucinations, and the total score of the PSYRATS scale. Altogether our results indicate that volumetric alterations of thalamic nuclei involved in audition may be related to persistent auditory hallucinations in chronic schizophrenia patients, whereas alterations in nuclei related to association cortices are evident in all patients. Future studies should explore whether the structural alterations are cause or consequence of these positive symptoms and whether they are already present in first episodes of psychosis.

Precision Psychiatry: Machine learning as a tool to find new pharmacological targets

There is an increasing amount of data arising from neurobehavioral sciences and medical records that cannot be adequately analyzed by traditional research methods. New drugs develop at a slow rate and seem unsatisfactory for the majority of neurobehavioral disorders. Machine learning (ML) techniques, instead, can incorporate psychopathological, computational, cognitive, and neurobiological underpinning knowledge leading to a refinement of detection, diagnosis, prognosis, treatment, research, and support. Machine and deep learning methods are currently used to accelerate the process of discovering new pharmacological targets and drugs.

OBJECTIVE

The present work reviews current evidence regarding the contribution of machine learning to the discovery of new drug targets.

METHODS

Scientific articles from PubMed, SCOPUS, EMBASE, and Web of Science Core Collection published until May 2021 were included in this review.

RESULTS

The most significant areas of research are schizophrenia, depression and anxiety, Alzheimer´s disease, and substance use disorders. ML techniques have pinpointed target gene candidates and pathways, new molecular substances, and several biomarkers regarding psychiatric disorders. Drug repositioning studies using ML have identified multiple drug candidates as promising therapeutic agents.

CONCLUSION

Next-generation ML techniques and subsequent deep learning may power new findings regarding the discovery of new pharmacological agents by bridging the gap between biological data and chemical drug information.

Clozapine: Why Is It So Uniquely Effective in the Treatment of a Range of Neuropsychiatric Disorders?

Clozapine is superior to other antipsychotics as a therapy for treatment-resistant schizophrenia and schizoaffective disorder with increased risk of suicidal behavior. This drug has also been used in the off-label treatment of bipolar disorder, major depressive disorder (MDD), and Parkinson's disease (PD). Although usually reserved for severe and treatment-refractory cases, it is interesting that electroconvulsive therapy (ECT) has also been used in the treatment of these psychiatric disorders, suggesting some common or related mechanisms. A literature review on the applications of clozapine and electroconvulsive therapy (ECT) to the disorders mentioned above was undertaken, and this narrative review was prepared. Although both treatments have multiple actions, evidence to date suggests that the ability to elicit epileptiform activity and alter EEG activity, to increase neuroplasticity and elevate brain levels of neurotrophic factors, to affect imbalances in the relationship between glutamate and γ-aminobutyric acid (GABA), and to reduce inflammation through effects on neuron-glia interactions are common underlying mechanisms of these two treatments. This evidence may explain why clozapine is effective in a range of neuropsychiatric disorders. Future increased investigations into epigenetic and connectomic changes produced by clozapine and ECT should provide valuable information about these two treatments and the disorders they are used to treat.

Changes in nitric oxide, zinc and metallothionein levels in limbic regions at pre-pubertal and post-pubertal ages presented in an animal model of schizophrenia

Recent data suggest that rats with neonatal ventral hippocampal lesion (NVHL) show changes related to inflammatory processes and oxidative stress at the prefrontal cortex (PFC) level at post-pubertal age. The NVHL model is considered an animal model in schizophrenia. Here we analyzed the levels of nitrite, zinc, and metallothionein (MT) in cortical and subcortical regions of NVHL rats at pre-pubertal and post-pubertal ages. Nitric oxide (NO) levels were evaluated through measurement of nitrite levels. The locomotor activity was also evaluated in a novel environment. Animals with NVHL showed an increase in locomotor activity only at post-pubertal age. Furthermore, at pre-pubertal age, NVHL rats showed an increase in NO levels in ventral and dorsal hippocampus, thalamus, Caudate-putamen (CPu) and brainstem, in zinc levels in ventral and dorsal hippocampus, and CPu, and the MT level also in the ventral hippocampus and occipital cortex. In addition, at pre-pubertal age, a reduction in MT levels was also found in the PFC, parietal and temporal cortices, the CPu and the cerebellum. However, after puberty, NVHL caused an increase in NO levels in the PFC, and also zinc levels in the PFC and occipital and parietal cortices, with a reduction in MT levels in the thalamus and NAcc. Our results show the changes of these three molecules over time, among lesion (PD7), pre-pubertal and post-pubertal ages. This suggests changes at pre-pubertal age directly related to the site of the lesion, while at post-pubertal age, our data highlight changes in the PFC, a region mainly involved in schizophrenia.

Hippocampal Hyperactivity as a Druggable Circuit-Level Origin of Aberrant Salience in Schizophrenia

The development of current neuroleptics was largely aiming to decrease excessive dopaminergic signaling in the striatum. However, the notion that abnormal dopamine creates psychotic symptoms by causing an aberrant assignment of salience that drives maladaptive learning chronically during disease development suggests a therapeutic value of early interventions that correct salience-related neural processing. The mesolimbic dopaminergic output is modulated by several interconnected brain-wide circuits centrally involving the hippocampus and key relays like the ventral and associative striatum, ventral pallidum, amygdala, bed nucleus of the stria terminalis, nucleus reuniens, lateral and medial septum, prefrontal and cingulate cortex, among others. Unraveling the causal relationships between these circuits using modern neuroscience techniques holds promise for identifying novel cellular—and ultimately molecular—treatment targets for reducing transition to psychosis and symptoms of schizophrenia. Imaging studies in humans have implicated a hyperactivity of the hippocampus as a robust and early endophenotype in schizophrenia. Experiments in rodents, in turn, suggested that the activity of its output region—the ventral subiculum—may modulate dopamine release from ventral tegmental area (VTA) neurons in the ventral striatum. Even though these observations suggested a novel circuit-level target for anti-psychotic action, no therapy has yet been developed along this rationale. Recently evaluated treatment strategies—at least in part—target excess glutamatergic activity, e.g. N-acetyl-cysteine (NAC), levetiracetam, and mGluR2/3 modulators. We here review the evidence for the central implication of the hippocampus-VTA axis in schizophrenia-related pathology, discuss its symptom-related implications with a particular focus on aberrant assignment of salience, and evaluate some of its short-comings and prospects for drug discovery.

D-amino acids in foods

With the only exception of glycine, all amino acids exist in two specular structures which are mirror images of each other, called D-(dextro) and L-(levo) enantiomers. During evolution, L-amino acids were preferred for protein synthesis and main metabolism; however, the D-amino acids (D-AAs) acquired different and specific functions in different organisms (from playing a structural role in the peptidoglycan of the bacterial cell wall to modulating neurotransmission in mammalian brain). With the advent of sophisticated and sensitive analytical techniques, it was established during the past few decades that many foods contain considerable amounts of D-AAs: we consume more than 100 mg of D-AAs every day. D-AAs are present in a variety of foodstuffs, where they fulfill a relevant role in producing differences in taste and flavor and in their antimicrobial and antiaging properties from the corresponding L-enantiomers. In this review, we report on the derivation of D-AAs in foods, mainly originating from the starting materials, fermentation processes, racemization during food processing, or contamination. We then focus on leading-edge methods to identify and quantify D-AAs in foods. Finally, current knowledge concerning the effect of D-AAs on the nutritional state and human health is summarized, highlighting some positive and negative effects. Notwithstanding recent progress in D-AA research, the relationships between presence and nutritional value of D-AAs in foods represent a main scientific issue with interesting economic impact in the near future.

Could Dietary Glutamate Play a Role in Psychiatric Distress?

Glutamate is an amino acid that functions as an excitatory neurotransmitter. It has also been associated with somatic and psychiatric distress and is implicated in the pathophysiology of psychiatric disorders such as schizophrenia. Ingestion of dietary glutamate, such as monosodium glutamate (MSG), has been mechanistically linked with greater distress among patients with chronic pain conditions, though findings have been equivocal. Preliminary research suggests that an MSG-restricted diet confers beneficial effects on somatic symptoms and well-being for some individuals with chronic pain conditions. In addition to associations with somatic distress, glutamate has been associated with the onset and progression of psychiatric symptoms. Thus, the role of dietary glutamate in psychiatric distress represents an underdeveloped and potentially important area for future research aimed at clarifying pathophysiological mechanisms and identifying targets for dietary intervention in psychiatric illnesses.

Can N-Methyl-D-Aspartate Receptor Hypofunction in Schizophrenia Be Localized to an Individual Cell Type?

Hypofunction of N-methyl-D-aspartate glutamate receptors (NMDARs), whether caused by endogenous factors like auto-antibodies or mutations, or by pharmacological or genetic manipulations, produces a wide variety of deficits which overlap with-but do not precisely match-the symptom spectrum of schizophrenia. In order to understand how NMDAR hypofunction leads to different components of the syndrome, it is necessary to take into account which neuronal subtypes are particularly affected by it in terms of detrimental functional alterations. We provide a comprehensive overview detailing findings in rodent models with cell type-specific knockout of NMDARs. Regarding inhibitory cortical cells, an emerging model suggests that NMDAR hypofunction in parvalbumin (PV) positive interneurons is a potential risk factor for this disease. PV interneurons display a selective vulnerability resulting from a combination of genetic, cellular, and environmental factors that produce pathological multi-level positive feedback loops. Central to this are two antioxidant mechanisms-NMDAR activity and perineuronal nets-which are themselves impaired by oxidative stress, amplifying disinhibition. However, NMDAR hypofunction in excitatory pyramidal cells also produces a range of schizophrenia-related deficits, in particular maladaptive learning and memory recall. Furthermore, NMDAR blockade in the thalamus disturbs thalamocortical communication, and NMDAR ablation in dopaminergic neurons may provoke over-generalization in associative learning, which could relate to the positive symptom domain. Therefore, NMDAR hypofunction can produce schizophrenia-related effects through an action on various different circuits and cell types.