Effects of pharmacological treatments on neuroimaging findings in first episode affective psychosis: A review of longitudinal studies

The Risk for Schizophrenia-Bipolar Spectrum: Does the Apple Fall Close to the Tree? A Narrative Review

Schizophrenia (SCZ) and bipolar disorder (BD) are severe psychiatric disorders that share clinical features and several risk genes. Important information about their genetic underpinnings arises from intermediate phenotypes (IPs), quantifiable biological traits that are more prevalent in unaffected relatives (RELs) of patients compared to the general population and co-segregate with the disorders. Within IPs, neuropsychological functions and neuroimaging measures have the potential to provide useful insight into the pathophysiology of SCZ and BD. In this context, the present narrative review provides a comprehensive overview of the available evidence on deficits in neuropsychological functions and neuroimaging alterations in unaffected relatives of SCZ (SCZ-RELs) and BD (BD-RELs). Overall, deficits in cognitive functions including intelligence, memory, attention, executive functions, and social cognition could be considered IPs for SCZ. Although the picture for cognitive alterations in BD-RELs is less defined, BD-RELs seem to present worse performances compared to controls in executive functioning, including adaptable thinking, planning, self-monitoring, self-control, and working memory. Among neuroimaging markers, SCZ-RELs appear to be characterized by structural and functional alterations in the cortico-striatal-thalamic network, while BD risk seems to be associated with abnormalities in the prefrontal, temporal, thalamic, and limbic regions. In conclusion, SCZ-RELs and BD-RELs present a pattern of cognitive and neuroimaging alterations that lie between patients and healthy individuals. Similar abnormalities in SCZ-RELs and BD-RELs may be the phenotypic expression of the shared genetic mechanisms underlying both disorders, while the specificities in neuropsychological and neuroimaging profiles may be associated with the differential symptom expression in the two disorders.

A review of multi-modal magnetic resonance imaging studies on perimenopausal brain: a hint towards neural heterogeneity

The population ageing process worldwide is leading to an increasing number of women in the perimenopausal phase. Many of the perimenopausal symptoms, such as headache, depression, insomnia, and cognitive decline, are neurological in nature. Therefore, the study of the perimenopausal brain is of great importance. In addition, relevant studies can also provide an imaging basis for multiple therapies to treat perimenopausal symptoms. Because of its non-invasive nature, magnetic resonance imaging (MRI) has now been widely applied to the study of perimenopausal brains, revealing alterations in the brain associated with symptoms during the menopause transition. In this review, we collected papers and works of literature on the perimenopausal brain using MRI techniques in the Web of Science database. We firstly described the general principles and analysis methods of different MRI modalities briefly and then reviewed the structural, functional, perfusion, and metabolic compounds changes in the brain of perimenopausal women respectively, and described the latest advances in probing the perimenopausal brain using MRI, resulting in summary diagrams and figures. Based on the summary of existing works of the literature, this review further provided a perspective on multi-modal MRI studies in the perimenopausal brain, suggesting that population-based, multi-center, and longitudinal studies will be beneficial to the comprehensive understanding of changes in the perimenopausal brain. In addition, we found a hint towards neural heterogeneity in the perimenopausal brain, which should be addressed by future MRI studies to provide more help for the precise diagnosis and personalized treatment of perimenopausal symptoms. KEY POINTS: • Perimenopause is not only a physiological transition but also a period of neurological transition. • Multi-modal MRI studies have revealed that perimenopause is accompanied by alterations in the brain, which is implicated in many perimenopausal symptoms. • The diversity in the multi-modal MRI findings may give a hint to neural heterogeneity in the perimenopausal brain.

Mania-related effects on structural brain changes in bipolar disorder - a narrative review of the evidence

Cross-sectional neuroimaging studies show that bipolar disorder is associated with structural brain abnormalities, predominantly observed in prefrontal and temporal cortex, cingulate gyrus, and subcortical regions. However, longitudinal studies are needed to elucidate whether these abnormalities presage disease onset or are consequences of disease processes, and to identify potential contributing factors. Here, we narratively review and summarize longitudinal structural magnetic resonance imaging studies that relate imaging outcomes to manic episodes. First, we conclude that longitudinal brain imaging studies suggest an association of bipolar disorder with aberrant brain changes, including both deviant decreases and increases in morphometric measures. Second, we conclude that manic episodes have been related to accelerated cortical volume and thickness decreases, with the most consistent findings occurring in prefrontal brain areas. Importantly, evidence also suggests that in contrast to healthy controls, who in general show age-related cortical decline, brain metrics remain stable or increase during euthymic periods in bipolar disorder patients, potentially reflecting structural recovering mechanisms. The findings stress the importance of preventing manic episodes. We further propose a model of prefrontal cortical trajectories in relation to the occurrence of manic episodes. Finally, we discuss potential mechanisms at play, remaining limitations, and future directions.

Prefrontal cortex activities during verbal fluency and emotional words tasks in major depressive, adjustment, and bipolar disorders with depressive states

BACKGROUND

It can be difficult to differentiate psychiatric disorders from depressive states, with little knowledge on how to differentiate them. This study aimed to evaluate changes in brain activity during cognitive and emotional tasks in patients with depressive state to help with differential diagnoses.

METHODS

Sixty-two patients with depressive states [17 with adjustment disorder (AD), 27 with major depressive disorder (MDD), and 18 with bipolar disorder (BD)] and 34 healthy controls (HC) were recruited. We used a verbal fluency task (VFT) and emotional word tasks with happy and threat words. Functional near-infrared spectroscopy measured the relative change in oxygenated hemoglobin in the frontotemporal areas.

RESULTS

During the VFT, patients with AD or MDD showed significantly reduced activation in the bilateral frontotemporal region (all p < 0.01), whereas patients with BD demonstrated significantly reduced activation in the right frontotemporal areas compared to HC (p < 0.01). During the emotional words task with happy words, patients with MDD showed significantly increased activity in the frontopolar area compared to HC (p = 0.023). Binary logistic regression analysis showed that MDD or BD was significantly associated with brain activity during the happy word task. In distinguishing MDD or BD from HC, the happy words task performed equally well, with an area under the curve of 0.70.

LIMITATIONS

All study patients were taking psychotropic drugs.

CONCLUSIONS

Brain activation in response to a combination of cognitive or emotional stimuli could assist in distinguishing patients with depressive states from healthy controls.

The effect of first- and second-generation antipsychotics on brain morphology in schizophrenia: A systematic review of longitudinal magnetic resonance studies with a randomized allocation to treatment arms

Schizophrenia manifests as loss of brain volume in specific areas in a progressive nature and an important question concerns whether long-term treatment with medications contributes to this. The aim of the current PRISMA systematic review was to search for prospective studies involving randomization to treatment. PROSPERO ID: CRD42020197874. The MEDLINE/PUBMED was searched and it returned 2638 articles; 3 were fulfilling the inclusion criteria. A fourth was published later; they included 359 subjects, of whom 86 were healthy controls, while the rest were first-episode patients, with 91 under olanzapine, 93 under haloperidol, 48 under risperidone, 5 under paliperidone, 6 under ziprasidone, and 30 under placebo. Probably one-third of patients were suffering from a psychotic disorder other than schizophrenia. The consideration of their results suggested that there is no significant difference between these medications concerning their effects on brain structure and also in comparison to healthy subjects. There does not seem to be any strong support to the opinion that medications that treat psychosis cause loss of brain volume in patients with schizophrenia. On the contrary, the data might imply the possible presence of a protective effect for D2, 5-HT2, and NE alpha-2 antagonists (previously called SGAs). However, the literature is limited and focused research in large study samples is essential to clarify the issue, since important numerical differences do exist. The possibility of the results and their heterogeneity to be artifacts secondary to a modification of magnetic resonance imaging (MRI) signal by antipsychotics should not be easily rejected until relevant data are available.

Inferring the Individual Psychopathologic Deficits with Structural Connectivity in a Longitudinal Cohort of Schizophrenia

The prediction of schizophrenia-related psychopathologic deficits is exceedingly important in the fields of psychiatry and clinical practice. However, objective association of the brain structure alterations to the illness clinical symptoms is challenging. Although, schizophrenia has been characterized as a brain dysconnectivity syndrome, evidence accounting for neuroanatomical network alterations remain scarce. Moreover, the absence of generalized connectome biomarkers for the assessment of illness progression further perplexes the prediction of long-term symptom severity. In this paper, a combination of individualized prediction models with quantitative graph theoretical analysis was adopted, providing a comprehensive appreciation of the extent to which the brain network properties are affected over time in schizophrenia. Specifically, Connectome-based Prediction Models were employed on Structural Connectivity (SC) features, efficiently capturing individual network-related differences, while identifying the anatomical connectivity disturbances contributing to the prediction of psychopathological deficits. Our results demonstrated distinctions among widespread cortical circuits responsible for different domains of symptoms, indicating the complex neural mechanisms underlying schizophrenia. Furthermore, the generated models were able to significantly predict changes of symptoms using SC features at follow-up, while the preserved SC features suggested an association with improved positive and overall symptoms. Moreover, cross-sectional significant deficits were observed in network efficiency and a progressive aberration of global integration in patients compared to healthy controls, representing a group-consensus pathological map, while supporting the dysconnectivity hypothesis.