Neural substrates of psychosis revealed by altered dependencies between brain activity and white-matter architecture in individuals with 22q11 deletion syndrome

Longitudinal Analysis of Brain Function-Structure Dependencies in 22q11.2 Deletion Syndrome and Psychotic Symptoms

BACKGROUND

Compared with conventional unimodal analysis, understanding how brain function and structure relate to one another opens a new biologically relevant assessment of neural mechanisms. However, how function-structure dependencies (FSDs) evolve throughout typical and abnormal neurodevelopment remains elusive. The 22q11.2 deletion syndrome (22q11.2DS) offers an important opportunity to study the development of FSDs and their specific association with the pathophysiology of psychosis.

METHODS

Previously, we used graph signal processing to combine brain activity and structural connectivity measures in adults, quantifying FSD. Here, we combined FSD with longitudinal multivariate partial least squares correlation to evaluate FSD alterations across groups and among patients with and without mild to moderate positive psychotic symptoms. We assessed 391 longitudinally repeated resting-state functional and diffusion-weighted magnetic resonance images from 194 healthy control participants and 197 deletion carriers (ages 7-34 years, data collected over a span of 12 years).

RESULTS

Compared with control participants, patients with 22q11.2DS showed a persistent developmental offset from childhood, with regions of hyper- and hypocoupling across the brain. Additionally, a second deviating developmental pattern showed an exacerbation during adolescence, presenting hypocoupling in the frontal and cingulate cortices and hypercoupling in temporal regions for patients with 22q11.2DS. Interestingly, the observed aggravation during adolescence was strongly driven by the group with positive psychotic symptoms.

CONCLUSIONS

These results confirm a central role of altered FSD maturation in the emergence of psychotic symptoms in 22q11.2DS during adolescence. The FSD deviations precede the onset of psychotic episodes and thus offer a potential early indication for behavioral interventions in individuals at risk.

Structure-function coupling reveals the brain hierarchical structure dysfunction in Alzheimer's disease: A multicenter study

BACKGROUND

Alzheimer's disease (AD) is a neurodegenerative condition characterized by cognitive decline. To date, the specific dysfunction in the brain's hierarchical structure in AD remains unclear.

METHODS

We introduced the structural decoupling index (SDI), based on a multi-site data set comprising functional and diffusion-weighted magnetic resonance imaging data from 793 subjects, to assess their brain hierarchy.

RESULTS

Compared to normal controls (NCs), individuals with AD exhibited increased SDI within the posterior superior temporal sulcus, insular gyrus, precuneus, hippocampus, amygdala, postcentral gyrus, and cingulate gyrus; meanwhile, the patients with AD demonstrated decreased SDI in the frontal lobe. The SDI in those regions also showed a significant correlation with cognitive ability. Moreover, the SDI was a robust AD neuroimaging biomarker capable of accurately distinguishing diagnostic status (area under the curve [AUC] = 0.86).

DISCUSSION

Our findings revealed the dysfunction of the brain's hierarchical structure in AD. Furthermore, the SDI could serve as a promising neuroimaging biomarker for AD.

HIGHLIGHTS

This study utilized multi-center, multi-modal data from East Asian populations. We found an increased spatial gradient of the structure decoupling index (SDI) from sensory-motor to higher-order cognitive regions. Changes in SDI are associated with energy metabolism and mitochondria. SDI can identify Alzheimer's disease (AD) and further uncover the disease mechanisms of AD.

The effectiveness and tolerability of pharmacotherapy for psychosis in 22q11.2 Deletion Syndrome: A systematic review

OBJECTIVE

The 22q11.2 Deletion Syndrome (22q11.2DS) is the most common microdeletion in humans with over 180 phenotypic expressions. Approximately 30-40% of affected individuals will develop psychosis and 25% meet the criteria for schizophrenia. Despite this, pharmacotherapy for managing psychosis in 22q11.2DS is poorly understood and 22q11.2DS psychosis is frequently labelled as treatment resistant. The objectives of this paper are to evaluate the effectiveness and tolerability of pharmacotherapy for 22q11.2DS psychosis and evaluate the evidence for treatment resistance.

METHOD

A systematic search was performed using CINAHL, The Cochrane Library (Cochrane Database of Systematic Reviews; Cochrane Central Register of Controlled Trials and Cochrane Clinical Answers), EMBASE, PsycINFO, PubMed, Scopus and Web of Science Core Collection from inception to December 2022. It yielded 39 case reports, 6 case series and 1 retrospective study which met the inclusion criteria.

RESULTS

Based on the current literature, individuals with 22q11.2DS psychosis experience a greater rate of medical co-morbidities such as cardiac arrhythmias, seizures and movement disorders, which complicate pharmacotherapy. Poor tolerability rather than poor clinical response motivates the switching of antipsychotics, which may explain the labelling of treatment resistance in the literature.

CONCLUSION

There are insufficient data to recommend a single antipsychotic for 22q11.2DS psychosis. Nonetheless, with proactive management of co-morbidities, antipsychotic medication in 22q11.2DS psychosis is an effective treatment commonly resulting in improvement in quality of life.

Decomposing cortical activity through neuronal tracing connectome-eigenmodes in marmosets

Deciphering the complex relationship between neuroanatomical connections and functional activity in primate brains remains a daunting task, especially regarding the influence of monosynaptic connectivity on cortical activity. Here, we investigate the anatomical-functional relationship and decompose the neuronal-tracing connectome of marmoset brains into a series of eigenmodes using graph signal processing. These cellular connectome eigenmodes effectively constrain the cortical activity derived from resting-state functional MRI, and uncover a patterned cellular-functional decoupling. This pattern reveals a spatial gradient from coupled dorsal-posterior to decoupled ventral-anterior cortices, and recapitulates micro-structural profiles and macro-scale hierarchical cortical organization. Notably, these marmoset-derived eigenmodes may facilitate the inference of spontaneous cortical activity and functional connectivity of homologous areas in humans, highlighting the potential generalizing of the connectomic constraints across species. Collectively, our findings illuminate how neuronal-tracing connectome eigenmodes constrain cortical activity and improve our understanding of the brain's anatomical-functional relationship.