Tackling dementia globally: the Global Dementia Prevention Program (GloDePP) collaboration

Investigating the Therapeutic Mechanisms of Total Saikosaponins in Alzheimer's Disease: A Metabolomic and Proteomic Approach

Alzheimer's disease (AD) is the leading cause of dementia among the elderly, yet effective treatments remain elusive. Total saikosaponins (TSS), the primary bioactive components in Bupleurum chinense, have shown promising therapeutic effects against AD in previous studies. Methods: To delve deeper into the mechanisms underlying the therapeutic role of TSS in AD, we investigated its neuroprotective effects and associated molecular mechanisms in APP/PS1 mice. Further, we employed metabolomic and proteomic analyses, with a focus on the potential protein-level changes induced by TSS, particularly those related to metabolite accumulation in the brain. Results: Our results showed that lysophosphatidylcholine, adenosine, and sphingomyelin in plasma might serve as potential biomarkers. Compared to the control group, AD mice exhibited significantly increased expression of proteins related to neuroinflammatory pathways, whereas proteins involved in cAMP signaling, cGMP-PKG signaling, and synaptic plasticity pathways were significantly downregulated. Notably, these signaling pathways were partially reversed in APP/PS1 mice following TSS administration. Behavioral tests demonstrated that TSS effectively improved the learning and memory functions of mice. Conclusions: Our findings suggest that TSS ameliorate cognitive decline through regulating neuroinflammatory pathways, cAMP and cGMP signaling, and synaptic plasticity pathways, providing insights into its therapeutic potential in AD.

The Effects of Virtual Reality-Based Reminiscence Therapies for Older Adults With Cognitive Impairment: Systematic Review

BACKGROUND

Reminiscence therapy (RT) is a commonly used nonpharmaceutical treatment for cognitive impairment. Artifacts or conversations are used in RT to recall individuals' memories and past experiences. Virtual reality (VR) has increasingly been used as an assistive technology during RT. However, the effects of VR-based RT (VR-RT) methods remain unclear, and insights into the related benefits and challenges are urgently needed.

OBJECTIVE

The study aims to systematically review the effects of VR-RTs for older adults with cognitive impairment.

METHODS

Seven databases (MEDLINE, Academic Search Premier, CINAHL, Web of Science, PubMed, the Cochrane Central Register of Controlled Trials, and ScienceDirect) were searched to identify relevant articles published from inception to August 10, 2023. Peer-reviewed publications that assessed the effect of VR-RTs (ie, using virtual clues to evoke participants' memories or past experiences) on cognitive-related outcomes were included. Two independent researchers conducted the literature search, review, and data extraction processes. A narrative synthesis approach was used to analyze the extracted data.

RESULTS

Of the 537 identified articles, 22 were ultimately included in the data analysis. The results revealed that VR-RTs could maintain cognitive status (4/4, 100%) and reduce anxiety (2/2, 100%) in older adults with cognitive impairment. Nevertheless, one study found a cognitive improvement after VR-RTs, whereas cognitive degradation was observed at a 3- to 6-month follow-up measure. Around 88% (7/8) of the included studies indicated that VR-RTs improved memory; however, the evidence regarding the beneficial effects of VR-RTs was limited in improving quality of life (1/4, 25%) and reducing apathy (0/2, 0%) and depression (1/3, 33%). The results indicated that VR-RTs are safe, engaging, acceptable, and satisfying for older adults with cognitive impairment. In VR scenarios, personalized stimulus materials related to the users' youth experiences were more effective for treating cognitive impairment than other stimulus materials.

CONCLUSIONS

The results of this systematic review demonstrate the potential benefits of VR-RT for older adults with cognitive impairment, especially in improving emotion and memory and maintaining cognitive status. VR-RT is also safe and enjoyable for older adults. However, due to the trial heterogeneity of included studies, we can only provide qualitative results instead of performing meta-analysis to quantify the effect size of VR-RTs. Thus, more randomized controlled trials are required to examine the designs and effects of VR-RTs for groups of older adults with specific needs.

A history of traumatic brain injury is associated with poorer cognition and imaging evidence of altered white matter tract integrity in UK Biobank (n = 50 376)

Traumatic brain injury (TBI) is a risk factor for neurodegenerative disease. We currently have no means to identify patients most at risk of neurodegenerative disease following injury and, resultantly, no means to target risk mitigation interventions. To address this, we explored the association between history of traumatic brain injury with cognitive performance and imaging measures of white matter integrity. From the UK Biobank imaging sub-study (n = 50 376), participants were identified with either self-reported (n = 177) or health record coded broad- (injury codes; n = 1096) or narrow-band (TBI specific codes; n = 274) TBI, or as controls with no such documented history (n = 49 280). Cognitive scores and imaging measures of corpus callosum white matter integrity were compared between injury participants (versus no injury), corrected for age, sex, socioeconomic status and medications. TBI was associated with poorer cognitive and imaging phenotypes. The strongest deleterious associations were for narrow-band injury (β difference 0.2-0.3; P < 0.01). All cognitive and imaging phenotypes were strongly inter-correlated (P < 0.001). This study provides insight into possible early biomarkers predating neurodegenerative disease following brain injury. Measures of cognition and white matter following injury may provide means to identify individuals most at risk of neurodegenerative disease, to which mitigation strategies might be targeted.

Barriers to Effective Memory Assessments for Alzheimer's Disease

Recently, Alzheimer's Disease International (ADI) stressed that around 75% of people living with dementia globally are still not receiving a diagnosis. In this commentary, I reflect on how efforts towards better cognitive assessments, particularly of memory, can be aligned and harmonized to contribute to such needs. I highlight some barriers that ongoing collaborations and trials are facing and their potential drivers. I suggest some strategies that can help overcome them and in so doing, integrate research agendas. We need to ignite the debate towards strategies that can help level the playfield to tackle Alzheimer's disease with true global solutions.

Patient and caregiver perspectives on a tool to increase recognition of undiagnosed dementia: a qualitative study

Background

Early detection of dementia may improve patient care and quality of life, yet up to half of people with dementia are undiagnosed. Electronic health record (EHR) data could be used to help identify individuals at risk of having undiagnosed dementia for outreach and assessment, but acceptability to people with dementia and caregivers is unknown.

Methods

We conducted five focus groups at Kaiser Permanente Washington (KPWA), an integrated healthcare system in Washington State, to explore people’s feelings about timing of dementia diagnosis, use of EHR-based tools to predict risk of undiagnosed dementia, and communication about risk. We recruited people enrolled in KPWA who had dementia or mild cognitive impairment, people enrolled in KPWA who had neither diagnosis, and caregivers (i.e., loved ones of people with dementia who assist with various tasks of daily life). People who were non-white or Hispanic were oversampled. Two team members analyzed transcripts using thematic coding.

Results

Forty people (63% women; 59% non-white or Hispanic) participated in the focus groups. Themes that arose included: perceived pros and cons of early dementia diagnosis; questions and concerns about a potential tool to assess risk of undiagnosed dementia; and preferences related to patient-provider conversations disclosing that a person was at high risk to have undiagnosed dementia. Participants supported early diagnosis, describing benefits such as time to adjust to the disease, plan, involve caregivers, and identify resources. They also acknowledged the possible psychosocial toll of receiving the diagnosis. Participants supported use of an EHR-based tool, but some people worried about accuracy and privacy. Participants emphasized that information about risk of undiagnosed dementia should be communicated thoughtfully by a trusted provider and that the conversation should include advice about prognosis, treatment options and other resources when a new dementia diagnosis was made.

Conclusion

People with dementia or mild cognitive impairment, people with neither diagnosis, and caregivers of people with dementia supported using EHR-based tools to help identify individuals at risk of having undiagnosed dementia. Such tools must be implemented carefully to address concerns and ensure that people living with dementia and their caregivers are adequately supported.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12877-021-02523-0.

Inter-Cohort Validation of SuStaIn Model for Alzheimer's Disease

Alzheimer’s disease (AD) is a neurodegenerative disorder which spans several years from preclinical manifestations to dementia. In recent years, interest in the application of machine learning (ML) algorithms to personalized medicine has grown considerably, and a major challenge that such models face is the transferability from the research settings to clinical practice. The objective of this work was to demonstrate the transferability of the Subtype and Stage Inference (SuStaIn) model from well-characterized research data set, employed as training set, to independent less-structured and heterogeneous test sets representative of the clinical setting. The training set was composed of MRI data of 1043 subjects from the Alzheimer’s disease Neuroimaging Initiative (ADNI), and the test set was composed of data from 767 subjects from OASIS, Pharma-Cog, and ViTA clinical datasets. Both sets included subjects covering the entire spectrum of AD, and for both sets volumes of relevant brain regions were derived from T1-3D MRI scans processed with Freesurfer v5.3 cross-sectional stream. In order to assess the predictive value of the model, subpopulations of subjects with stable mild cognitive impairment (MCI) and MCIs that progressed to AD dementia (pMCI) were identified in both sets. SuStaIn identified three disease subtypes, of which the most prevalent corresponded to the typical atrophy pattern of AD. The other SuStaIn subtypes exhibited similarities with the previously defined hippocampal sparing and limbic predominant atrophy patterns of AD. Subject subtyping proved to be consistent in time for all cohorts and the staging provided by the model was correlated with cognitive performance. Classification of subjects on the basis of a combination of SuStaIn subtype and stage, mini mental state examination and amyloid-β_1-42 cerebrospinal fluid concentration was proven to predict conversion from MCI to AD dementia on par with other novel statistical algorithms, with ROC curves that were not statistically different for the training and test sets and with area under curve respectively equal to 0.77 and 0.76. This study proves the transferability of a SuStaIn model for AD from research data to less-structured clinical cohorts, and indicates transferability to the clinical setting.