The effects of antipsychotics on brain structure: what have we learnt from structural imaging of schizophrenia?

Prospective, randomized, multicenter clinical trial evaluating longitudinal changes in brain function and microstructure in first-episode schizophrenia patients treated with long-acting injectable paliperidone palmitate versus oral antipsychotics

Widespread anatomical alterations and abnormal functional connectivity have shown strong association with symptom severity in first-episode schizophrenia (FES) patients. Second-generation antipsychotic treatment might slow disease progression and possibly modify the cerebral plasticity in FES patients. However, whether a long-acting injectable antipsychotic (paliperidone palmitate [PP]), available in monthly and every-3-months formulations, is more effective than oral antipsychotics (OAP) in improving cerebral organization has been unclear. Therefore, in the current longitudinal study, we evaluated the differences in functional and microstructural changes of 68 FES patients in a randomized clinical trial of PP vs OAP. When compared to OAP treatment, PP treatment was more effective in decreasing abnormally high fronto-temporal and thalamo-temporal connectivity, as well as increasing fronto-sensorimotor and thalamo-insular connectivity. Consistent with previous studies, multiple white matter pathways showed larger changes in fractional anisotropy (FA) and mean diffusivity (MD) in response to PP compared with OAP treatment. These findings suggest that PP treatment might reduce regional abnormalities and improve cerebral connectivity networks compared with OAP treatment, and identified changes that may serve as reliable imaging biomarkers associated with medication treatment efficacy.

Neuroanatomical subtypes of schizophrenia and relationship with illness duration and deficit status

BACKGROUND

The heterogeneity of schizophrenia (SCZ) regarding psychopathology, illness trajectory and their inter-relationships with underlying neural substrates remain incompletely understood. In a bid to reduce illness heterogeneity using neural substrates, our study aimed to replicate the findings of an earlier study by Chand et al. (2020). We employed brain structural measures for subtyping SCZ patients, and evaluate each subtype's relationship with clinical features such as illness duration, psychotic psychopathology, and additionally deficit status.

METHODS

Overall, 240 subjects (160 SCZ patients, 80 healthy controls) were recruited for this study. The participants underwent brain structural magnetic resonance imaging scans and clinical rating using the Positive and Negative Syndrome Scale. Neuroanatomical subtypes of SCZ were identified using "Heterogeneity through discriminative analysis" (HYDRA), a clustering technique which accounted for relevant covariates and the inter-group normalized percentage changes in brain volume were also calculated.

RESULTS

As replicated, two neuroanatomical subtypes (SG-1 and SG-2) were found amongst our patients with SCZ. The subtype SG-1 was associated with enlargements in the third and lateral ventricles, volume increase in the basal ganglia (putamen, caudate, pallidum), longer illness duration, and deficit status. The subtype SG-2 was associated with reductions of cortical and subcortical structures (hippocampus, thalamus, basal ganglia).

CONCLUSIONS

These replicated findings have clinical implications in the early intervention, response monitoring, and prognostication of SCZ. Future studies may adopt a multi-modal neuroimaging approach to enhance insights into the neurobiological composition of relevant subtypes.

Pattern classification as decision support tool in antipsychotic treatment algorithms

Pattern classification aims to establish a new approach in personalized treatment. The scope is to tailor treatment on individual characteristics during all phases of care including prevention, diagnosis, treatment, and clinical outcome. In psychotic disorders, this need results from the fact that a third of patients with psychotic symptoms do not respond to antipsychotic treatment and are described as having treatment-resistant disorders. This, in addition to the high variability of treatment responses among patients, enhances the need of applying advanced classification algorithms to identify antipsychotic treatment patterns. This review comprehensively summarizes advancements and challenges of pattern classification in antipsychotic treatment response to date and aims to introduce clinicians and researchers to the challenges of including pattern classification into antipsychotic treatment decision algorithms.

Total gray matter volume is reduced in individuals with bipolar disorder currently treated with atypical antipsychotics

BACKGROUND/AIMS

Recent evidence indicates that the intake of atypical antipsychotics (AAP) is associated with gray matter abnormalities in patients with psychiatric disorders. We explored if patients with bipolar disorder (BD) who are medicated with AAP exhibit total gray matter volume (TGV) reduction compared to BD individuals not medicated with AAP and healthy controls (HC).

METHODS

In a cross-sectional design, 124 individuals with BD and 86 HC underwent 3T-MRI of the brain and clinical assessment as part of our BIPFAT-study. The TGV was estimated using Freesurfer. We used univariate covariance analysis (ANCOVA) to test for normalized TGV differences and controlled for covariates.

RESULTS

ANCOVA results indicated that 75 BD individuals taking AAP had significantly reduced normalized TGV as compared to 49 BD not taking AAP (F = 9.995, p = .002., Eta = 0.084) and 86 HC (F = 7.577, p = .007, Eta = 0.046).

LIMITATIONS

Our cross-sectional results are not suited to draw conclusions about causality. We have no clear information on treatment time and baseline volumes before drug treatment in the studied subjects. We cannot exclude that patients received different psychopharmacologic medications prior to the study point. We did not included dosages into the calculation. Many BD individuals received combinations of psychopharmacotherapy across drug classes. We did not have records displaying quantitative alcohol consumption and drug abuse in our sample.

CONCLUSIONS

Our data provide further evidence for the impact of AAP on brain structure in BD. Longitudinal studies are needed to investigate the causal directions of the proposed relationships.

Increased frontal gray matter volume in individuals with prodromal psychosis

Background

Brain anatomical deficits associated with cognitive dysfunction have been reported in patients with schizophrenia. However, it remains unknown whether such anatomical deficits exist in individuals with prodromal psychosis. The present study is designed to investigate anatomical deficits in prodromal individuals and their associations with clinical/cognitive features.

Methods

Seventy‐four prodromal individuals and seventy‐six healthy controls were scanned using structural magnetic resonance imaging. Support vector machines were applied to test whether anatomical deficits might be used to discriminate prodromal individuals from healthy controls.

Results

Prodromal individuals showed significantly increased gray matter volume (GMV) in the right inferior frontal gyrus (IFG) and right rectus gyrus relative to healthy controls. No correlations were observed between increased GMV and clinical/cognitive characteristics. The combination of increased GMV in the right rectus gyrus and right IFG showed a sensitivity of 74.32%, a specificity of 67.11%, and an accuracy of 70.67% in differentiating prodromal individuals from healthy controls.

Conclusion

Our results provide evidence of increased frontal GMV in prodromal individuals. A combination of GMV values in the two frontal brain areas may serve as potential markers to discriminate prodromal individuals from healthy controls. The results thus highlight the importance of the frontal regions in the pathophysiology of psychosis.

A Perspective of the Cross-Tissue Interplay of Genetics, Epigenetics, and Transcriptomics, and Their Relation to Brain Based Phenotypes in Schizophrenia

Genetic association studies of psychiatric disorders have provided unprecedented insight into disease risk profiles with high confidence. Yet, the next research challenge is how to translate this rich information into mechanisms of disease, and further help interventions and treatments. Given other comprehensive reviews elsewhere, here we want to discuss the research approaches that integrate information across various tissue types. Taking schizophrenia as an example, the tissues, cells, or organisms being investigated include postmortem brain tissues or neurons, peripheral blood and saliva, in vivo brain imaging, and in vitro cell lines, particularly human induced pluripotent stem cells (iPSC) and iPSC derived neurons. There is a wealth of information on the molecular signatures including genetics, epigenetics, and transcriptomics of various tissues, along with neuronal phenotypic measurements including neuronal morphometry and function, together with brain imaging and other techniques that provide data from various spatial temporal points of disease development. Through consistent or complementary processes across tissues, such as cross-tissue methylation quantitative trait loci (QTL) and expression QTL effects, systemic integration of such information holds the promise to put the pieces of puzzle together for a more complete view of schizophrenia disease pathogenesis.

Motor dysfunction within the schizophrenia-spectrum: A dimensional step towards an underappreciated domain

At the beginning of the 20th century, genuine motor abnormalities (GMA) were considered to be intricately linked to schizophrenia. Subsequently, however, GMA have been increasingly regarded as unspecific transdiagnostic phenomena or related to side effects of antipsychotic treatment. Despite possible medication confounds, within the schizophrenia spectrum GMA have been categorized into three broad categories, i.e. neurological soft signs, abnormal involuntary movements and catatonia. Schizophrenia patients show a substantial overlap across a broad range of distinct motor signs and symptoms suggesting a prominent involvement of the motor system in disease pathophysiology. There have been several attempts to increase reliability and validity in diagnosing schizophrenia based on behavior and neurobiology, yet relatively little attention has been paid to the motor domain in the past. Nevertheless, accumulating neuroscientific evidence suggests the possibility of a motor endophenotype in schizophrenia, and that GMA could represent a specific dimension within the schizophrenia-spectrum. Here, we review current neuroimaging research on GMA in schizophrenia with an emphasis on distinct and common mechanisms of brain dysfunction. Based on a dimensional approach we show that multimodal neuroimaging combined with fine-grained clinical examination can result in a comprehensive characterization of structural and functional brain changes that are presumed to underlie core GMA in schizophrenia. We discuss the possibility of a distinct motor domain, together with its implications for future research. Investigating GMA by means of multimodal neuroimaging can essentially contribute at identifying novel and biologically reliable phenotypes in psychiatry.

Neuroinflammation and white matter pathology in schizophrenia: systematic review

BACKGROUND

Neuroinflammation and white matter pathology have each been independently associated with schizophrenia, and experimental studies have revealed mechanisms by which the two can interact in vitro, but whether these abnormalities simultaneously co-occur in people with schizophrenia remains unclear.

METHOD

We searched MEDLINE, EMBASE, PsycINFO and Web of Science from inception through 12 January 2014 for studies reporting human data on the relationship between microglial or astroglial activation, or cytokines and white matter pathology in schizophrenia.

RESULTS

Fifteen studies totaling 792 subjects (350 with schizophrenia, 346 controls, 49 with bipolar disorder, 37 with major depressive disorder and 10 with Alzheimer's disease) met all eligibility criteria. Five neuropathological and two neuroimaging studies collectively yielded consistent evidence of an association between schizophrenia and microglial activation, particularly in white rather than gray matter regions. Ultrastructural analysis revealed activated microglia near dystrophic and apoptotic oligodendroglia, demyelinating and dysmyelinating axons and swollen and vacuolated astroglia in subjects with schizophrenia but not controls. Two neuroimaging studies found an association between carrier status for a functional single nucleotide polymorphism in the interleukin-1β gene and abnormal white as well as gray matter volumes in schizophrenia but not controls. A neuropathological study found that orbitofrontal white matter neuronal density was increased in schizophrenia cases exhibiting high transcription levels of pro-inflammatory cytokines relative to those exhibiting low transcription levels and to controls. Schizophrenia was associated with decreased astroglial density specifically in subgenual cingulate white matter and anterior corpus callosum, but not other gray or white matter areas. Astrogliosis was consistently absent. Data on astroglial gene expression, mRNA expression and protein concentration were inconsistent.

CONCLUSION

Neuroinflammation is associated with white matter pathology in people with schizophrenia, and may contribute to structural and functional disconnectivity, even at the first episode of psychosis.

Neuroanatomical markers of genetic liability to psychosis and first episode psychosis: a voxelwise meta-analytical comparison

OBJECTIVES

To address at a meta-analytical level the neuroanatomical markers of genetic liability to psychosis and a of first episode of psychosis.

METHODS

Fifteen voxel-based morphometry (VBM) studies of antipsychotic-naive subjects at genetic high-risk (HR) for psychosis or with a first-episode psychosis (FEP) were included in a Signed Differential Mapping (SDM) meta-analysis. Publication bias was assessed with funnel plots and Egger's intercept. Heterogeneity was assessed with Q statistics and I (2) index.

RESULTS

The database comprised 458 HR and 206 antipsychotic-naïve FEP subjects, matched with controls. Gray matter (GM) reductions as compared to controls, were observed in the left parahippocampal gyrus and in the bilateral anterior cingulate gyrus in the HR group, and in the right superior temporal gyrus, in the left insula and in the left cerebellum in the FEP group. Further GM decreases were observed in the FEP group as compared to the HR group in the left anterior cingulate, in the right precuneus, in the left cerebellum and in the right superior temporal gyrus. Limitations. The cross-sectional nature of the included studies prevented the comparison of high risk subjects who later did or did not develop a psychotic episode. Other caveats are based on the methodological heterogeneity across individual imaging studies.

CONCLUSIONS

GM reductions in the anterior cingulate are markers of genetic liability to psychosis while reductions in the superior temporal gyrus and cerebellum can be interpreted as markers of a first onset of the illness.

Striatal presynaptic dopamine in schizophrenia, part II: meta-analysis of [(18)F/(11)C]-DOPA PET studies

BACKGROUND

Alterations in striatal dopamine neurotransmission are central to the emergence of psychotic symptoms and to the mechanism of action of antipsychotics. Although the functional integrity of the presynaptic system can be assessed by measuring striatal dopamine synthesis capacity (DSC), no quantitative meta-analysis is available.

METHODS

Eleven striatal (caudate and putamen) [(11)C/(18)F]-DOPA positron emission tomography studies comparing 113 patients with schizophrenia and 131 healthy controls were included in a quantitative meta-analysis of DSC. Demographic, clinical, and methodological variables were extracted from each study or obtained from the authors and tested as covariates. Hedges' g was used as a measure of effect size in Comprehensive Meta-Analysis. Publication bias was assessed with funnel plots and Egger's intercept. Heterogeneity was addressed with the Q statistic and I(2) index.

RESULTS

Patients and controls were well matched in sociodemographic variables (P > .05). Quantitative evaluation of publication bias was nonsignificant (P = .276). Heterogeneity across study was modest in magnitude and statistically nonsignificant (Q = 19.19; P = .078; I (2) = 39.17). Patients with schizophrenia showed increased striatal DSC as compared with controls (Hedges' g = 0.867, CI 95% from 0.594 to 1.140, Z = 6.222, P < .001). The DSC schizophrenia/control ratio showed a relatively homogenous elevation of around 14% in schizophrenic patients as compared with controls. DSC elevation was regionally confirmed in both caudate and putamen. Controlling for potential confounders such as age, illness duration, gender, psychotic symptoms, and exposure to antipsychotics had no impact on the results. Sensitivity analysis confirmed robustness of meta-analytic findings.

CONCLUSIONS

The present meta-analysis showed consistently increased striatal DSC in schizophrenia, with a 14% elevation in patients as compared with healthy controls.

Effect of chronic antipsychotic treatment on brain structure: a serial magnetic resonance imaging study with ex vivo and postmortem confirmation

BACKGROUND

There is increasing evidence that antipsychotic (APD) may affect brain structure directly. To examine this, we developed a rodent model that uses clinically relevant doses and serial magnetic resonance imaging (MRI), followed by postmortem histopathological analysis to study the effects of APD on brain structures.

METHODS

Antipsychotic , haloperidol, and olanzapine were continuously administered to rats via osmotic minipumps to maintain clinic-like steady state levels for 8 weeks. Longitudinal in vivo MRI scanning (T₂-weighted) was carried out at baseline, 4 weeks, and 8 weeks, after which animals were perfused and their brains preserved for ex vivo MRI scanning. Region of interest analyses were performed on magnetic resonance images (both in vivo as well as ex vivo) along with postmortem stereology using the Cavalieri estimator probe.

RESULTS

Chronic (8 weeks) exposure to both haloperidol and olanzapine resulted in significant decreases in whole-brain volume (6% to 8%) compared with vehicle-treated control subjects, driven mainly by a decrease in frontal cerebral cortex volume (8% to 12%). Hippocampal, corpus striatum, lateral ventricles, and corpus callosum volumes were not significantly different from control subjects, suggesting a differential effect of APD on the cortex. These results were corroborated by ex vivo MRI scans and decreased cortical volume was confirmed postmortem by stereology.

CONCLUSIONS

This is the first systematic whole-brain MRI study of the effects of APD, which highlights significant effects on the cortex. Although caution needs to be exerted when extrapolating results from animals to patients, the approach provides a tractable method for linking in vivo MRI findings to their histopathological origins.

Long-term antipsychotic treatment and brain volumes: a longitudinal study of first-episode schizophrenia

CONTEXT

Progressive brain volume changes in schizophrenia are thought to be due principally to the disease. However, recent animal studies indicate that antipsychotics, the mainstay of treatment for schizophrenia patients, may also contribute to brain tissue volume decrement. Because antipsychotics are prescribed for long periods for schizophrenia patients and have increasingly widespread use in other psychiatric disorders, it is imperative to determine their long-term effects on the human brain.

OBJECTIVE

To evaluate relative contributions of 4 potential predictors (illness duration, antipsychotic treatment, illness severity, and substance abuse) of brain volume change.

DESIGN

Predictors of brain volume changes were assessed prospectively based on multiple informants.

SETTING

Data from the Iowa Longitudinal Study.

PATIENTS

Two hundred eleven patients with schizophrenia who underwent repeated neuroimaging beginning soon after illness onset, yielding a total of 674 high-resolution magnetic resonance scans. On average, each patient had 3 scans (≥2 and as many as 5) over 7.2 years (up to 14 years).

MAIN OUTCOME MEASURE

Brain volumes.

RESULTS

During longitudinal follow-up, antipsychotic treatment reflected national prescribing practices in 1991 through 2009. Longer follow-up correlated with smaller brain tissue volumes and larger cerebrospinal fluid volumes. Greater intensity of antipsychotic treatment was associated with indicators of generalized and specific brain tissue reduction after controlling for effects of the other 3 predictors. More antipsychotic treatment was associated with smaller gray matter volumes. Progressive decrement in white matter volume was most evident among patients who received more antipsychotic treatment. Illness severity had relatively modest correlations with tissue volume reduction, and alcohol/illicit drug misuse had no significant associations when effects of the other variables were adjusted.

CONCLUSIONS

Viewed together with data from animal studies, our study suggests that antipsychotics have a subtle but measurable influence on brain tissue loss over time, suggesting the importance of careful risk-benefit review of dosage and duration of treatment as well as their off-label use.

Use of neuroanatomical pattern regression to predict the structural brain dynamics of vulnerability and transition to psychosis

BACKGROUND

The at-risk mental state for psychosis (ARMS) has been associated with abnormal structural brain dynamics underlying disease transition or non-transition. To date, it is unknown whether these dynamic brain changes can be predicted at the single-subject level prior to disease transition using MRI-based machine-learning techniques.

METHODS

First, deformation-based morphometry and partial-least-squares (PLS) was used to investigate patterns of volumetric changes over time in 25 ARMS individuals versus 28 healthy controls (HC) (1) irrespective of the clinical outcome and (2) according to illness transition or non-transition. Then, the baseline MRI data were employed to predict the expression of these volumetric changes at the individual level using support-vector regression (SVR).

RESULTS

PLS revealed a pattern of pronounced morphometric changes in ARMS versus HC that affected predominantly the right prefrontal, as well as the perisylvian, parietal and periventricular structures (p<0.011), and that was more pronounced in the converters versus the non-converters (p<0.010). The SVR analysis facilitated a reliable prediction of these longitudinal brain changes in individual out-of training cases (HC vs ARMS: r=0.83, p<0.001; HC vs converters vs non-converters: r=0.83, p<0.001) by relying on baseline patterns that involved ventricular enlargements, as well as prefrontal, perisylvian, limbic, parietal and subcortical volume reductions.

CONCLUSIONS

Abnormal brain changes over time may underlie an elevated vulnerability for psychosis and may be most pronounced in subsequent converters to psychosis. Pattern regression techniques may facilitate an accurate prediction of these structural brain dynamics, potentially allowing for an early recognition of individuals at risk of developing psychosis-associated neuroanatomical changes over time.