Psychosis of Alzheimer's disease: Neuropsychological and neuroimaging longitudinal study

The Associations Between Neuropsychiatric Symptoms and Cognition in People with Dementia: A Systematic Review and Meta-Analysis

Most people with dementia experience neuropsychiatric symptoms (NPS), including anxiety, depression or disinhibition. There is growing interest in the relationship between NPS and cognitive impairment, but data is still limited. This study aimed to investigate the specific associations between NPS and cognition in people with dementia. MEDLINE, EMBASE and PsycINFO were searched for published, peer-reviewed studies of associations between at least one NPS and one cognitive ability in people with dementia. The quality of the studies was assessed with the NIH National Heart, Lung and Blood Institute's quality assessment tools. A meta-analysis was conducted using Robumeta package for R. Ninety studies were included. We found significant associations between NPS, global cognition and cognitive domains, e.g. apathy was associated with global cognitive and memory impairment; dysphoria was associated with worse attention; delusions with executive dysfunction. Increased NPS in people with dementia are associated with worse cognitive performance. There were few studies looking at associations between some neuropsychiatric clusters and cognitive abilities, and there was little research on causal relationships. Our review was limited by the inclusion of studies that reported associations in specific formats, and most included people with a diagnosis of Alzheimer's disease (AD). However, given the large number of studies, this is unlikely to have biased results. More research is needed that includes diverse people with different dementia syndromes. Registration: PROSPERO 2020 CRD42020165565.

Integrating Clinical Neuropsychology and Psychotic Spectrum Disorders: A Systematic Analysis of Cognitive Dynamics, Interventions, and Underlying Mechanisms

Background and Objectives: The study aims to provide a comprehensive neuropsychological analysis of psychotic spectrum disorders, including schizophrenia, bipolar disorder, and depression. It focuses on the critical aspects of cognitive impairments, diagnostic tools, intervention efficacy, and the roles of genetic and environmental factors in these disorders. The paper emphasizes the diagnostic significance of neuropsychological tests in identifying cognitive deficiencies and their predictive value in the early management of psychosis. Materials and Methods: The study involved a systematic literature review following the PRISMA guidelines. The search was conducted in significant databases like Scopus, PsycINFO, PubMed, and Web of Science using keywords relevant to clinical neuropsychology and psychotic spectrum disorders. The inclusion criteria required articles to be in English, published between 2018 and 2023, and pertinent to clinical neuropsychology's application in these disorders. A total of 153 articles were identified, with 44 ultimately included for detailed analysis based on relevance and publication status after screening. Results: The review highlights several key findings, including the diagnostic and prognostic significance of mismatch negativity, neuroprogressive trajectories, cortical thinning in familial high-risk individuals, and distinct illness trajectories within psychosis subgroups. The studies evaluated underline the role of neuropsychological tests in diagnosing psychiatric disorders and emphasize early detection and the effectiveness of intervention strategies based on cognitive and neurobiological markers. Conclusions: The systematic review underscores the importance of investigating the neuropsychological components of psychotic spectrum disorders. It identifies significant cognitive impairments in attention, memory, and executive function, correlating with structural and functional brain abnormalities. The paper stresses the need for precise diagnoses and personalized treatment modalities, highlighting the complex interplay between genetic, environmental, and psychosocial factors. It calls for a deeper understanding of these neuropsychological processes to enhance diagnostic accuracy and therapeutic outcomes.

Characteristics of very late-onset schizophrenia-like psychosis classified with the biomarkers for Alzheimer's disease: a retrospective cross-sectional study

OBJECTIVES

We aimed to investigate the association between very late-onset schizophrenia-like psychosis (VLOSLP), a schizophrenia spectrum disorder with an onset of ≥60 years, and Alzheimer's disease (AD) using biomarkers.

DESIGN

Retrospective cross-sectional study.

SETTING

Neuropsychology clinic of Osaka University Hospital in Japan.

PARTICIPANTS

Thirty-three participants were classified into three groups: eight AD biomarker-negative VLOSLP (VLOSLP-AD), nine AD biomarker-positive VLOSLP (VLOSLP+AD), and sixteen amnestic mild cognitive impairment due to AD without psychosis (aMCI-P+AD) participants.

MEASUREMENTS

Phosphorylated tau levels in the cerebrospinal fluid and 18F-Florbetapir positron emission tomography results were used as AD biomarkers. Several scales (e.g. the Mini-Mental State Examination (MMSE), Wechsler Memory Scale-Revised (WMS-R) Logical Memory (LM) I and II, and Neuropsychiatric Inventory (NPI)-plus) were conducted to assess clinical characteristics.

RESULTS

Those in both VLOSLP-AD and +AD groups scored higher than those in aMCI-P+AD in WMS-R LM I. On the other hand, VLOSLP+AD participants scored in between the other two groups in the WMS-R LM II, with only VLOSLP-AD participants scoring significantly higher than aMCI-P+AD participants. There were no significant differences in sex distribution and MMSE scores among the three groups or in the subtype of psychotic symptoms between VLOSLP-AD and +AD participants. Four VLOSLP-AD and five VLOSLP+AD participants harbored partition delusions. Delusion of theft was shown in two VLOSLP-AD patients and five VLOSLP+AD patients.

CONCLUSION

Some VLOSLP patients had AD pathology. Clinical characteristics were different between AD biomarker-positive and AD biomarker-negative VLOSLP, which may be helpful for detecting AD pathology in VLOSLP patients.

Neural networks underlying visual illusions: An activation likelihood estimation meta-analysis

Visual illusions have long been used to study visual perception and contextual integration. Neuroimaging studies employ illusions to identify the brain regions involved in visual perception and how they interact. We conducted an Activation Likelihood Estimation (ALE) meta-analysis and meta-analytic connectivity modeling on fMRI studies using static and motion illusions to reveal the neural signatures of illusory processing and to investigate the degree to which different areas are commonly recruited in perceptual inference. The resulting networks encompass ventral and dorsal regions, including the inferior and middle occipital cortices bilaterally in both types of illusions. The static and motion illusion networks selectively included the right posterior parietal cortex and the ventral premotor cortex respectively. Overall, these results describe a network of areas crucially involved in perceptual inference relying on feed-back and feed-forward interactions between areas of the ventral and dorsal visual pathways. The same network is proposed to be involved in hallucinogenic symptoms characteristic of schizophrenia and other disorders, with crucial implications in the use of illusions as biomarkers.

Accelerated atrophy in dopaminergic targets and medial temporo-parietal regions precedes the onset of delusions in patients with Alzheimer's disease

People with Alzheimer's disease (AD) and delusions have worse quality of life and prognosis. However, early markers of delusions have not been identified yet. The present study investigated whether there are any detectable differences in grey matter (GM) volume and cognitive changes in the year before symptom onset between patients with AD who did and did not develop delusions. Two matched samples of AD patients, 63 who did (PT-D) and 63 who did not develop delusions (PT-ND) over 1 year, were identified from the Alzheimer's Disease Neuroimaging Initiative database. The Neuropsychiatric Inventory (NPI) was used to assess the presence of delusions. Sixty-three additional matched healthy controls (HC) were selected. Repeated-measures ANCOVA models were used to investigate group-by-time effects on the volume of selected GM regions of interest and on cognitive performance. No neurocognitive differences were observed between patient groups prior to symptom onset. Greater episodic memory decline and GM loss in bilateral caudate nuclei, medio-temporal and midline cingulo-parietal regions were found in the PT-D compared with the PT-ND group. A pattern of faster GM loss in brain areas typically affected by AD and in cortical and subcortical targets of dopaminergic pathways, paralleled by worsening of episodic memory and behavioural symptoms, may explain the emergence of delusions in patients with AD.

Cortical complexity alterations in the medial temporal lobe are associated with Alzheimer's disease psychosis

Psychosis is frequent in Alzheimer's disease (AD) and it is associated with a worse disease course. AD psychosis may represent a distinct AD phenotype, though its specific neurobiological underpinnings have yet to be identified. This study investigated neural underpinnings of AD psychosis using surface-based-morphometry.Data from 32 AD patients, 17 with psychosis (AD-P) and 15 without were analyzed. Average cortical complexity (fractal dimension, FD) was estimated for each theoretically motivated ROI and patient. First, we compared regional FD in AD-P and AD patients. Then we calculated the correlation coefficients between FD and the severity of misidentification and paranoid psychotic symptoms. AD-P showed decreased FD in ventral-visual-stream compared to AD, suggesting that perceptual processes might be pivotal in psychosis. A negative correlation was found between misidentification severity and FD in the entorhinal cortex suggesting that misidentification may be specifically associated with alterations in regions involved in high-level perceptual and contextualization processes.

Depression symptoms moderate the relationship between gray matter volumes and cognitive function in patients with mild cognitive impairment

Previous studies have demonstrated that decreased gray matter volume (GMV) correlates with cognitive function in elderly patients with mild cognitive impairment (MCI). However, it is unclear whether those correlations are present in MCI patients with depressive symptoms (MCID). This study investigated the association among depressive symptoms, GMV and cognitive function. We included 210 participants, namely, 70 elderly MCID patients, 70 MCI patients without depressive symptoms (MCIND) and 70 healthy controls (HCs). Voxel-based morphometry (VBM) was used to investigate the structural disruptions among the patients in the three groups, and correlation analysis was performed between the GMV of regions showing group differences and cognitive function. Moderation analyses were conducted to verify the conditional effect of depressive symptoms on the relationship between structural changes and cognitive function. We found decreased GMV in the bilateral fusiform gyrus, inferior temporal gyrus, parahippocampal gyrus, and hippocampus in the MCIND group compared to the HC group. Moreover, we identified decreased GMV in the bilateral fusiform gyrus in the elderly MCID patients compared with the elderly MCIND patients, which provides further insights into the neural mechanisms of depressive symptoms in patients with MCID. Most importantly, the severity of depressive symptoms moderated the positive correlation between the GMV of abnormal brain regions and cognitive function. Furthermore, this study is the first report of the moderating effect of depressive symptoms on the GMV of abnormal brain areas and cognitive function in patients with MCID, indicating the significance of clinical intervention in elderly MCI patients with depressive symptoms.

Psychosis as a Treatment Target in Dementia: A Roadmap for Designing Interventions

Psychotic phenomena are among the most severe and disruptive symptoms of dementias and appear in 30% to 50% of patients. They are associated with a worse evolution and great suffering to patients and caregivers. Their current treatments obtain limited results and are not free of adverse effects, which are sometimes serious. It is therefore crucial to develop new treatments that can improve this situation. We review available data that could enlighten the future design of clinical trials with psychosis in dementia as main target. Along with an explanation of its prevalence in the common diseases that cause dementia, we present proposals aimed at improving the definition of symptoms and what should be included and excluded in clinical trials. A review of the available information regarding the neurobiological basis of symptoms, in terms of pathology, neuroimaging, and genomics, is provided as a guide towards new therapeutic targets. The correct evaluation of symptoms is transcendental in any therapeutic trial and these aspects are extensively addressed. Finally, a critical overview of existing pharmacological and non-pharmacological treatments is made, revealing the unmet needs, in terms of efficacy and safety. Our work emphasizes the need for better definition and measurement of psychotic symptoms in dementias in order to highlight their differences with symptoms that appear in non-dementing diseases such as schizophrenia. Advances in neurobiology should illuminate the development of new, more effective and safer molecules for which this review can serve as a roadmap in the design of future clinical trials.

Psychosis

PURPOSE OF REVIEW

Psychosis can manifest in primary psychotic disorders, neurologic diseases, and medical conditions. This article reviews the definition of psychotic symptoms and the evaluation and management of psychosis in primary psychiatric and neurologic disorders frequently seen in neurologic practice.

RECENT FINDINGS

Emerging evidence supports significant connections between psychosis and structural and functional brain changes in both primary psychotic and neurologic disorders. In addition to antidopaminergic activity, the mechanism of new-generation antipsychotics shifts to act on serotonin receptors, which potentially contributes to their benefits in the treatment of negative symptoms of psychosis and a lesser frequency of extrapyramidal side effects compared with typical antipsychotics. This is also helpful in the treatment of psychosis in patients who have neurodegenerative diseases and are vulnerable to developing extrapyramidal side effects from typical antipsychotics.

SUMMARY

Even with significant overlap, management of psychosis in primary psychotic disorders differs from the approach of psychosis in neurologic diseases. This article helps clinicians learn how to practically evaluate psychosis from both psychiatric and neurologic perspectives.

Integration of Imaging Genomics Data for the Study of Alzheimer's Disease Using Joint-Connectivity-Based Sparse Nonnegative Matrix Factorization

Imaging genetics reveals the connection between microscopic genetics and macroscopic imaging, enabling the identification of disease biomarkers. In this work, we make full use of prior knowledge that has significant reference value for investigating the correlation between the brain and genetics to explore more biologically substantial biomarkers. In this paper, we propose joint-connectivity-based sparse nonnegative matrix factorization (JCB-SNMF). The algorithm simultaneously projects structural magnetic resonance imaging (sMRI), single-nucleotide polymorphism sites (SNPs), and gene expression data onto a common feature space, where heterogeneous variables with large coefficients in the same projection direction form a common module. In addition, the connectivity information for each region of the brain and genetic data are added as prior knowledge to identify regions of interest (ROIs), SNPs, and gene-related risks related to Alzheimer's disease (AD) patients. GraphNet regularization increases the anti-noise performance of the algorithm and the biological interpretability of the results. The simulation results show that compared with other NMF-based algorithms (JNMF, JSNMNMF), JCB-SNMF has better anti-noise performance and can identify and predict biomarkers closely related to AD from significant modules. By constructing a protein-protein interaction (PPI) network, we identified SF3B1, RPS20, and RBM14 as potential biomarkers of AD. We also found some significant SNP-ROI and gene-ROI pairs. Among them, two SNPs rs4472239 and rs11918049 and three genes KLHL8, ZC3H11A, and OSGEPL1 may have effects on the gray matter volume of multiple brain regions. This model provides a new way to further integrate multimodal impact genetic data to identify complex disease association patterns.

Older Adults Diagnosed With Schizophrenia in Long-term Care Facilities: Life Course Theory for Holistic Nursing Research and Practice

Older adults diagnosed with schizophrenia (OADWS) often enter long-term care facilities with unique challenges related to trauma and stress experienced throughout their life course. Health care workers often report that when they work with this population, they feel unprepared due to limited training. In this article, life course theory is presented as a lens for holistic nursing research and as a way for nurses to adapt interventions already used with cognitively impaired older adults (e.g., those diagnosed with Alzheimer's disease) for OADWS in long-term care. It is hoped that these ideas will facilitate discussion of ways to inform training for holistic long-term care of OADWS. Holistic principles of nursing addressed with life course theory as a lens include the following: (a) accounting for strengths and challenges; (b) honoring experiences, values, and health beliefs; (c) viewing interrelationships with the environment; and (d) nurturing of peace, wholeness, and healing.