How Real-World Data Can Facilitate the Development of Precision Medicine Treatment in Psychiatry.

Precision medicine has the ambition to improve treatment response and clinical outcomes through patient stratification and holds great potential for the treatment of mental disorders. However, several important factors are needed to transform current practice into a precision psychiatry framework. Most important are 1) the generation of accessible large real-world training and test data including genomic data integrated from multiple sources, 2) the development and validation of advanced analytical tools for stratification and prediction, and 3) the development of clinically useful management platforms for patient monitoring that can be integrated into health care systems in real-life settings. This narrative review summarizes strategies for obtaining the key elements-well-powered samples from large biobanks integrated with electronic health records and health registry data using novel artificial intelligence algorithms-to predict outcomes in severe mental disorders and translate these models into clinical management and treatment approaches. Key elements are massive mental health data and novel artificial intelligence algorithms. For the clinical translation of these strategies, we discuss a precision medicine platform for improved management of mental disorders. We use cases to illustrate how precision medicine interventions could be brought into psychiatry to improve the clinical outcomes of mental disorders.

Changes in patterns of age-related network connectivity are associated with risk for schizophrenia.

Alterations in fMRI-based brain functional network connectivity (FNC) are associated with schizophrenia (SCZ) and the genetic risk or subthreshold clinical symptoms preceding the onset of SCZ, which often occurs in early adulthood. Thus, age-sensitive FNC changes may be relevant to SCZ risk-related FNC. We used independent component analysis to estimate FNC from childhood to adulthood in 9,236 individuals. To capture individual brain features more accurately than single-session fMRI, we studied an average of three fMRI scans per individual. To identify potential familial risk-related FNC changes, we compared age-related FNC in first-degree relatives of SCZ patients mostly including unaffected siblings (SIB) with neurotypical controls (NC) at the same age stage. Then, we examined how polygenic risk scores for SCZ influenced risk-related FNC patterns. Finally, we investigated the same risk-related FNC patterns in adult SCZ patients (oSCZ) and young individuals with subclinical psychotic symptoms (PSY). Age-sensitive risk-related FNC patterns emerge during adolescence and early adulthood, but not before. Young SIB always followed older NC patterns, with decreased FNC in a cerebellar-occipitoparietal circuit and increased FNC in two prefrontal-sensorimotor circuits when compared to young NC. Two of these FNC alterations were also found in oSCZ, with one exhibiting reversed pattern. All were linked to polygenic risk for SCZ in unrelated individuals (R2 varied from 0.02 to 0.05). Young PSY showed FNC alterations in the same direction as SIB when compared to NC. These results suggest that age-related neurotypical FNC correlates with genetic risk for SCZ and is detectable with MRI in young participants.

Effect of anticholinergic burden on brain activity during Working Memory and real-world functioning in patients with schizophrenia.

Cognitive impairment has been associated with poor real-world functioning in patients with Schizophrenia. Previous studies have shown that pharmacological treatment with anticholinergic properties may contribute to cognitive impairment in Schizophrenia. We investigated the effect of the anticholinergic burden (ACB) on brain activity, cognition, and real-world functioning in Schizophrenia. We hypothesized that greater ACB would be associated with altered brain activity along with poorer cognitive performance and lower real-world functioning. A sample of 100 patients with a diagnosis of schizophrenia or schizoaffective disorder was recruited in the naturalistic multicenter study of the Italian Network for Research on Psychoses (NIRP) across 7 centres. For each participant, ACB was evaluated using the Anticholinergic Cognitive Burden scale. The association of ACB with brain function was assessed using BOLD fMRI during the N-Back Working Memory (WM) task in a nested cohort (N = 31). Real-world functioning was assessed using the Specific Level of Functioning (SLOF) scale. Patients with high ACB scores (≥3) showed lower brain activity in the WM frontoparietal network (TFCE corrected alpha <0.05) and poorer cognitive performance (p = 0.05) than patients with low ACB scores (<3). Both effects were unaffected by demographic characteristics, clinical severity, and antipsychotic dosage. Moreover, patients with high ACB showed poorer real-world functioning than patients with lower ACB (p = 0.03). Our results suggest that ACB in Schizophrenia is associated with impaired WM and abnormal underlying brain function along with reduced real-world functioning. Clinical practice should consider the potential adverse cognitive effects of ACB in the treatment decision-making process.

Parsing neurobiological heterogeneity of the clinical high-risk state for psychosis: A pseudo-continuous arterial spin labelling study.

Introduction: The impact of the clinical high-risk for psychosis (CHR-P) construct is dependent on accurately predicting outcomes. Individuals with brief limited intermittent psychotic symptoms (BLIPS) have higher risk of developing a first episode of psychosis (FEP) compared to individuals with attenuated psychotic symptoms (APS). Supplementing subgroup stratification with information from candidate biomarkers based on neurobiological parameters, such as resting-state, regional cerebral blood flow (rCBF), may help refine risk estimates. Based on previous evidence, we hypothesized that individuals with BLIPS would exhibit increased rCBF compared to APS in key regions linked to dopaminergic pathways. Methods: Data from four studies were combined using ComBat (to account for between-study differences) to analyse rCBF in 150 age- and sex-matched subjects (n = 30 healthy controls [HCs], n = 80 APS, n = 20 BLIPS and n = 20 FEP). Global gray matter (GM) rCBF was examined in addition to region-of-interest (ROI) analyses in bilateral/left/right frontal cortex, hippocampus and striatum. Group differences were assessed using general linear models: (i) alone; (ii) with global GM rCBF as a covariate; (iii) with global GM rCBF and smoking status as covariates. Significance was set at p < 0.05. Results: Whole-brain voxel-wise analyses and Bayesian ROI analyses were also conducted. No significant group differences were found in global [F(3,143) = 1,41, p = 0.24], bilateral frontal cortex [F(3,143) = 1.01, p = 0.39], hippocampus [F(3,143) = 0.63, p = 0.60] or striatum [F(3,143) = 0.52, p = 0.57] rCBF. Similar null findings were observed in lateralized ROIs (p > 0.05). All results were robust to addition of covariates (p > 0.05). No significant clusters were identified in whole-brain voxel-wise analyses (p > 0.05FWE). Weak-to-moderate evidence was found for an absence of rCBF differences between APS and BLIPS in Bayesian ROI analyses. Conclusion: On this evidence, APS and BLIPS are unlikely to be neurobiologically distinct. Due to this and the weak-to-moderate evidence for the null hypothesis, future research should investigate larger samples of APS and BLIPS through collaboration across large-scale international consortia.

Similarities and differences between multivariate patterns of cognitive and socio-cognitive deficits in schizophrenia, bipolar disorder and related risk.

Cognition and social cognition anomalies in patients with bipolar disorder (BD) and schizophrenia (SCZ) have been largely documented, but the degree of overlap between the two disorders remains unclear in this regard. We used machine learning to generate and combine two classifiers based on cognitive and socio-cognitive variables, thus delivering unimodal and multimodal signatures aimed at discriminating BD and SCZ from two independent groups of Healthy Controls (HC1 and HC2 respectively). Multimodal signatures discriminated well between patients and controls in both the HC1-BD and HC2-SCZ cohorts. Although specific disease-related deficits were characterized, the HC1 vs. BD signature successfully discriminated HC2 from SCZ, and vice-versa. Such combined signatures allowed to identify also individuals at First Episode of Psychosis (FEP), but not subjects at Clinical High Risk (CHR), which were classified neither as patients nor as HC. These findings suggest that both trans-diagnostic and disease-specific cognitive and socio-cognitive deficits characterize SCZ and BD. Anomalous patterns in these domains are also relevant to early stages of disease and offer novel insights for personalized rehabilitative programs.

The effects of acute Methylene Blue administration on cerebral blood flow and metabolism in humans and rats.

Methylene Blue (MB) is a brain-penetrating drug with putative neuroprotective, antioxidant and metabolic enhancing effects. In vitro studies suggest that MB enhances mitochondrial complexes activity. However, no study has directly assessed the metabolic effects of MB in the human brain. We used in vivo neuroimaging to measure the effect of MB on cerebral blood flow (CBF) and brain metabolism in humans and in rats. Two doses of MB (0.5 and 1 mg/kg in humans; 2 and 4 mg/kg in rats; iv) induced reductions in global cerebral blood flow (CBF) in humans (F(1.74, 12.17)5.82, p = 0.02) and rats (F(1,5)26.04, p = 0.0038). Human cerebral metabolic rate of oxygen (CMRO2) was also significantly reduced (F(1.26, 8.84)8.01, p = 0.016), as was the rat cerebral metabolic rate of glucose (CMRglu) (t = 2.6(16) p = 0.018). This was contrary to our hypothesis that MB will increase CBF and energy metrics. Nevertheless, our results were reproducible across species and dose dependent. One possible explanation is that the concentrations used, although clinically relevant, reflect MB's hormetic effects, i.e., higher concentrations produce inhibitory rather than augmentation effects on metabolism. Additionally, here we used healthy volunteers and healthy rats with normal cerebral metabolism where MB's ability to enhance cerebral metabolism might be limited.

Brain glucose metabolism in schizophrenia: a systematic review and meta-analysis of 18FDG-PET studies in schizophrenia.

BACKGROUND: Impaired brain metabolism may be central to schizophrenia pathophysiology, but the magnitude and consistency of metabolic dysfunction is unknown. METHODS: We searched MEDLINE, PsychINFO and EMBASE between 01/01/1980 and 13/05/2021 for studies comparing regional brain glucose metabolism using 18FDG-PET, in schizophrenia/first-episode psychosis v. controls. Effect sizes (Hedges g) were pooled using a random-effects model. Primary measures were regional absolute and relative CMRGlu in frontal, temporal, parietal and occipital lobes, basal ganglia and thalamus. RESULTS: Thirty-six studies (1335 subjects) were included. Frontal absolute glucose metabolism (Hedge's g = -0.74 ± 0.54, p = 0.01; I2 = 67%) and metabolism relative to whole brain (g = -0.44 ± 0.34, p = 0.01; I2 = 55%) were lower in schizophrenia v. controls with moderate heterogeneity. Absolute frontal metabolism was lower in chronic (g = -1.18 ± 0.73) v. first-episode patients (g = -0.09 ± 0.88) and controls. Medicated patients showed frontal hypometabolism relative to controls (-1.04 ± 0.26) while metabolism in drug-free patients did not differ significantly from controls. There were no differences in parietal, temporal or occipital lobe or thalamic metabolism in schizophrenia v. controls. Excluding outliers, absolute basal ganglia metabolism was lower in schizophrenia v. controls (-0.25 ± 0.24, p = 0.049; I2 = 5%). Studies identified reporting voxel-based morphometry measures of absolute 18FDG uptake (eight studies) were also analysed using signed differential mapping analysis, finding lower 18FDG uptake in the left anterior cingulate gyrus (Z = -4.143; p = 0.007) and the left inferior orbital frontal gyrus (Z = -4.239; p = 0.02) in schizophrenia. CONCLUSIONS: We report evidence for hypometabolism with large effect sizes in the frontal cortex in schizophrenia without consistent evidence for alterations in other brain regions. Our findings support the hypothesis of hypofrontality in schizophrenia.

Reduced cortical cerebral blood flow in antipsychotic-free first-episode psychosis and relationship to treatment response.

BACKGROUND: Altered cerebral blood flow (CBF) has been found in people at risk for psychosis, with first-episode psychosis (FEP) and with chronic schizophrenia (SCZ). Studies using arterial spin labelling (ASL) have shown reduction of cortical CBF and increased subcortical CBF in SCZ. Previous studies have investigated CBF using ASL in FEP, reporting increased CBF in striatum and reduced CBF in frontal cortex. However, as these people were taking antipsychotics, it is unclear whether these changes are related to the disorder or antipsychotic treatment and how they relate to treatment response. METHODS: We examined CBF in FEP free from antipsychotic medication (N = 21), compared to healthy controls (N = 22). Both absolute and relative-to-global CBF were assessed. We also investigated the association between baseline CBF and treatment response in a partially nested follow-up study (N = 14). RESULTS: There was significantly lower absolute CBF in frontal cortex (Cohen's d = 0.84, p = 0.009) and no differences in striatum or hippocampus. Whole brain voxel-wise analysis revealed widespread cortical reductions in absolute CBF in large cortical clusters that encompassed occipital, parietal and frontal cortices (Threshold-Free Cluster Enhancement (TFCE)-corrected <0.05). No differences were found in relative-to-global CBF in the selected region of interests and in voxel-wise analysis. Relative-to-global frontal CBF was correlated with percentage change in total Positive and Negative Syndrome Scale after antipsychotic treatment (r = 0.67, p = 0.008). CONCLUSIONS: These results show lower cortical absolute perfusion in FEP prior to starting antipsychotic treatment and suggest relative-to-global frontal CBF as assessed with magnetic resonance imaging could potentially serve as a biomarker for antipsychotic response.

Integration of human whole-brain transcriptome and neuroimaging data: Practical considerations of current available methods.

The Allen Human Brain Atlas (AHBA) is the first example of human brain transcriptomic mappings and detailed anatomical annotations which, for the first time, has allowed the integration of human brain transcriptomics with neuroimaging. This has been made possible because the AHBA offered an original dataset that contains mRNA expression measures for >20,000 genes covering the whole brain and, critically, in a standard stereotaxic space. In recent years many different methods have been used to integrate this data set with brain imaging data, although this endeavour has lacked harmony in terms of the workflow of data processing and subsequent analyses. In this work we discuss five main issues that experience has highlighted as in need of thorough consideration when integrating the AHBA with neuroimaging. These concerns are corroborated by comparing the performance of three different publicly available methods in correlating the same measures of serotonin receptors density with the correspondent AHBA mRNA maps. In this representative case, we were able to show how these methods can lead to discrepant results, suggesting that processing options are not neutral. We believe that the field should take into serious consideration these issues as they could undermine reproducibility and, in the end, the intrinsic value of the AHBA. We also advise on possible strategies to overcome these discrepancies. Finally, we encourage authors towards practices that will improve reproducibility such as transparency in reporting, algorithm and data sharing, collaboration.

Brain scans from 21,297 individuals reveal the genetic architecture of hippocampal subfield volumes.

The hippocampus is a heterogeneous structure, comprising histologically distinguishable subfields. These subfields are differentially involved in memory consolidation, spatial navigation and pattern separation, complex functions often impaired in individuals with brain disorders characterized by reduced hippocampal volume, including Alzheimer's disease (AD) and schizophrenia. Given the structural and functional heterogeneity of the hippocampal formation, we sought to characterize the subfields' genetic architecture. T1-weighted brain scans (n = 21,297, 16 cohorts) were processed with the hippocampal subfields algorithm in FreeSurfer v6.0. We ran a genome-wide association analysis on each subfield, co-varying for whole hippocampal volume. We further calculated the single-nucleotide polymorphism (SNP)-based heritability of 12 subfields, as well as their genetic correlation with each other, with other structural brain features and with AD and schizophrenia. All outcome measures were corrected for age, sex and intracranial volume. We found 15 unique genome-wide significant loci across six subfields, of which eight had not been previously linked to the hippocampus. Top SNPs were mapped to genes associated with neuronal differentiation, locomotor behaviour, schizophrenia and AD. The volumes of all the subfields were estimated to be heritable (h2 from 0.14 to 0.27, all p < 1 × 10-16) and clustered together based on their genetic correlations compared with other structural brain features. There was also evidence of genetic overlap of subicular subfield volumes with schizophrenia. We conclude that hippocampal subfields have partly distinct genetic determinants associated with specific biological processes and traits. Taking into account this specificity may increase our understanding of hippocampal neurobiology and associated pathologies.

Normalizing the Abnormal: Do Antipsychotic Drugs Push the Cortex Into an Unsustainable Metabolic Envelope?

The use of antipsychotic medication to manage psychosis, principally in those with a diagnosis of schizophrenia or bipolar disorder, is well established. Antipsychotics are effective in normalizing positive symptoms of psychosis in the short term (delusions, hallucinations and disordered thought). Their long-term use is, however, associated with side effects, including several types of movement (extrapyramidal syndrome, dyskinesia, akathisia), metabolic and cardiac disorders. Furthermore, higher lifetime antipsychotic dose-years may be associated with poorer cognitive performance and blunted affect, although the mechanisms driving the latter associations are not well understood. In this article, we propose a novel model of the long-term effects of antipsychotic administration focusing on the changes in brain metabolic homeostasis induced by the medication. We propose here that the brain metabolic normalization, that occurs in parallel to the normalization of psychotic symptoms following antipsychotic treatment, may not ultimately be sustainable by the cerebral tissue of some patients; these patients may be characterized by already reduced oxidative metabolic capacity and this may push the brain into an unsustainable metabolic envelope resulting in tissue remodeling. To support this perspective, we will review the existing data on the brain metabolic trajectories of patients with a diagnosis of schizophrenia as indexed using available neuroimaging tools before and after use of medication. We will also consider data from pre-clinical studies to provide mechanistic support for our model.

Topological gene expression networks recapitulate brain anatomy and function.

Understanding how gene expression translates to and affects human behavior is one of the ultimate goals of neuroscience. In this paper, we present a pipeline based on Mapper, a topological simplification tool, to analyze gene co-expression data. We first validate the method by reproducing key results from the literature on the Allen Human Brain Atlas and the correlations between resting-state fMRI and gene co-expression maps. We then analyze a dopamine-related gene set and find that co-expression networks produced by Mapper return a structure that matches the well-known anatomy of the dopaminergic pathway. Our results suggest that network based descriptions can be a powerful tool to explore the relationships between genetic pathways and their association with brain function and its perturbation due to illness and/or pharmacological challenges.

Receptor-Enriched Analysis of functional connectivity by targets (REACT): A novel, multimodal analytical approach informed by PET to study the pharmacodynamic response of the brain under MDMA.

One of the main limitations of pharmacological fMRI is its inability to provide a molecular insight into the main effect of compounds, leaving an open question about the relationship between drug effects and haemodynamic response. The aim of this study is to investigate the acute effects of 3,4-methylenedioxymethamphetamine (MDMA) on functional connectivity (FC) using a novel multimodal method (Receptor-Enriched Analysis of functional Connectivity by Targets - REACT). This approach enriches the resting state (rs-)fMRI analysis with the molecular information about the distribution density of serotonin receptors in the brain, given the serotonergic action of MDMA. Twenty healthy subjects participated in this double-blind, placebo-controlled, crossover study. A high-resolution in vivo atlas of four serotonin receptors (5-HT1A, 5-HT1B, 5-HT2A, and 5-HT4) and its transporter (5-HTT) was used as a template in a two-step multivariate regression analysis to estimate the spatial maps reflecting the whole-brain connectivity behaviour related to each target under placebo and MDMA. Results showed that the networks exhibiting significant changes after MDMA administration are the ones informed by the 5-HTT and 5-HT1A distribution density maps, which are the main targets of this compound. Changes in the 5-HT1A-enriched functional maps were also associated with the pharmacokinetic levels of MDMA and MDMA-induced FC changes in the 5-HT2A-enriched maps correlated with the spiritual experience subscale of the Altered States of Consciousness Questionnaire. By enriching the rs-fMRI analysis with molecular data of voxel-wise distribution of the serotonin receptors across the brain, we showed that MDMA effects on FC can be understood through the distribution of its main targets. This result supports the ability of this method to characterise the specificity of the functional response of the brain to MDMA binding to serotonergic receptors, paving the way to the definition of a new fingerprint in the characterization of new compounds and potentially to a further understanding to the response to treatment.

Genetic Variation of a DRD2 Co-expression Network is Associated with Changes in Prefrontal Function After D2 Receptors Stimulation.

Dopamine D2 receptors (D2Rs) contribute to the inverted U-shaped relationship between dopamine signaling and prefrontal function. Genetic networks from post-mortem human brain revealed 84 partner genes co-expressed with DRD2. Moreover, eight functional single nucleotide polymorphisms combined into a polygenic co-expression index (PCI) predicted co-expression of this DRD2 network and were associated with prefrontal function in humans. Here, we investigated the non-linear association of the PCI with behavioral and Working Memory (WM) related brain response to pharmacological D2Rs stimulation. Fifty healthy volunteers took part in a double-blind, placebo-controlled, functional MRI (fMRI) study with bromocriptine and performed the N-Back task. The PCI by drug interaction was significant on both WM behavioral scores (P = 0.046) and related prefrontal activity (all corrected P < 0.05) using a polynomial PCI model. Non-linear responses under placebo were reversed by bromocriptine administration. fMRI results on placebo were replicated in an independent sample of 50 participants who did not receive drug administration (P = 0.034). These results match earlier evidence in non-human primates and confirm the physiological relevance of this DRD2 co-expression network. Results show that in healthy subjects, different alleles evaluated as an ensemble are associated with non-linear prefrontal responses. Therefore, brain response to a dopaminergic drug may depend on a complex system of allelic patterns associated with DRD2 co-expression.

Increased cerebral blood flow after single dose of antipsychotics in healthy volunteers depends on dopamine D2 receptor density profiles.

As a result of neuro-vascular coupling, the functional effects of antipsychotics in human brain have been investigated in both healthy and clinical populations using haemodynamic markers such as regional Cerebral Blood Flow (rCBF). However, the relationship between observed haemodynamic effects and the pharmacological action of these drugs has not been fully established. Here, we analysed Arterial Spin Labelling (ASL) rCBF data from a placebo-controlled study in healthy volunteers, who received a single dose of three different D2 receptor (D2R) antagonists and tested the association of the main effects of the drugs on rCBF against normative population maps of D2R protein density and gene-expression data. In particular, we correlated CBF changes after antipsychotic administration with non-displaceable binding potential (BPND) template maps of the high affinity D2-antagonist Positron Emission Tomography (PET) ligand [18F]Fallypride and with brain post-mortem microarray mRNA expression data for the DRD2 gene from the Allen Human Brain Atlas (ABA). For all antipsychotics, rCBF changes were directly proportional to brain D2R densities and DRD2 mRNA expression measures, although PET BPND spatial profiles explained more variance as compared with mRNA profiles (PET R2 range = 0.20-0.60, mRNA PET R2 range 0.04-0.20, pairwise-comparisons all pcorrected<0.05). In addition, the spatial coupling between ΔCBF and D2R profiles varied between the different antipsychotics tested, possibly reflecting differential affinities. Overall, these results indicate that the functional effects of antipsychotics as measured with rCBF are tightly correlated with the distribution of their target receptors in striatal and extra-striatal regions. Our results further demonstrate the link between neurotransmitter targets and haemodynamic changes reinforcing rCBF as a robust in-vivo marker of drug effects. This work is important in bridging the gap between pharmacokinetic and pharmacodynamics of novel and existing compounds.

Familial Risk and a Genome-Wide Supported DRD2 Variant for Schizophrenia Predict Lateral Prefrontal-Amygdala Effective Connectivity During Emotion Processing.

The brain functional mechanisms translating genetic risk into emotional symptoms in schizophrenia (SCZ) may include abnormal functional integration between areas key for emotion processing, such as the amygdala and the lateral prefrontal cortex (LPFC). Indeed, investigation of these mechanisms is also complicated by emotion processing comprising different subcomponents and by disease-associated state variables. Here, our aim was to investigate the relationship between risk for SCZ and effective connectivity between the amygdala and the LPFC during different subcomponents of emotion processing. Thus, we first characterized with dynamic causal modeling (DCM) physiological patterns of LPFC-amygdala effective connectivity in healthy controls (HC) during implicit and explicit emotion processing. Then, we compared DCM patterns in a subsample of HC, in patients with SCZ and in healthy siblings of patients (SIB), matched for demographics. Finally, we investigated in HC association of LPFC-amygdala effective connectivity with a genome-wide supported variant increasing genetic risk for SCZ and possibly relevant to emotion processing (DRD2 rs2514218). In HC, we found that a "bottom-up" amygdala-to-LPFC pattern during implicit processing and a "top-down" LPFC-to-amygdala pattern during explicit processing were the most likely directional models of effective connectivity. Differently, implicit emotion processing in SIB, SCZ, and HC homozygous for the SCZ risk rs2514218 C allele was associated with decreased probability for the "bottom-up" as well as with increased probability for the "top-down" model. These findings suggest that task-specific anomaly in the directional flow of information or disconnection between the amygdala and the LPFC is a good candidate endophenotype of SCZ.

Variation in Dopamine D2 and Serotonin 5-HT2A Receptor Genes is Associated with Working Memory Processing and Response to Treatment with Antipsychotics.

Dopamine D2 and serotonin 5-HT2A receptors contribute to modulate prefrontal cortical physiology and response to treatment with antipsychotics in schizophrenia. Similarly, functional variation in the genes encoding these receptors is also associated with these phenotypes. In particular, the DRD2 rs1076560 T allele predicts a lower ratio of expression of D2 short/long isoforms, suboptimal working memory processing, and better response to antipsychotic treatment compared with the G allele. Furthermore, the HTR2A T allele is associated with lower 5-HT2A expression, impaired working memory processing, and poorer response to antipsychotics compared with the C allele. Here, we investigated in healthy subjects whether these functional polymorphisms have a combined effect on prefrontal cortical physiology and related cognitive behavior linked to schizophrenia as well as on response to treatment with second-generation antipsychotics in patients with schizophrenia. In a total sample of 620 healthy subjects, we found that subjects with the rs1076560 T and rs6314 T alleles have greater fMRI prefrontal activity during working memory. Similar results were obtained within the attentional domain. Also, the concomitant presence of the rs1076560 T/rs6314 T alleles also predicted lower behavioral accuracy during working memory. Moreover, we found that rs1076560 T carrier/rs6314 CC individuals had better responses to antipsychotic treatment in two independent samples of patients with schizophrenia (n=63 and n=54, respectively), consistent with the previously reported separate effects of these genotypes. These results indicate that DRD2 and HTR2A genetic variants together modulate physiological prefrontal efficiency during working memory and also modulate the response to antipsychotics. Therefore, these results suggest that further exploration is needed to better understand the clinical consequences of these genotype-phenotype relationships.

The role of the thalamus in schizophrenia from a neuroimaging perspective.

The thalamus is a crucial node for brain physiology and part of functional and structural pathways relevant for schizophrenia. Relatively few imaging studies on schizophrenia have focused on this brain region, yet extant evidence supports the association between this brain disorder and thalamic anomalies. Nevertheless, the mechanisms underlying this association remain largely conjectural. Here, we review imaging literature on the relationship between the thalamus and schizophrenia, focusing on critical challenges for future studies, in particular: (i) the anatomical and functional organization of the thalamus in separate nuclei, which are also differently connected with the cortex; (ii) state-dependent variables, which do not allow firm conclusions on the relevance of thalamic correlates as core phenotypes of schizophrenia and (iii) genetic variation, which affects thalamic physiology and may lead to variability of structural and functional patterns. Current evidence from the studies reviewed does not appear conclusive, although the relevance of thalamo-prefrontal interactions clearly emerges. Results from imaging genetics are beginning to cast insight on possible mechanisms of the involvement of the thalamus in schizophrenia.