Current Alzheimer Research - Volume 21, Issue 7, 2024

The COVID-19 pandemic has had multifaceted and enduring impacts on people with dementia and their caregivers; however, our understanding of the long-term outcomes remains limited. We aimed to explore the long-term effects of the COVID-19 pandemic on cognitive symptoms and vaccination rates in people living with dementia.

This study was conducted as a part of a longitudinal study design in two specialized hospitals in South India. In this study, patients with dementia and their caregivers assessed in earlier phases (‘period of lockdown with phased relaxations - phase-I’ and ‘cluster of cases transmission phase - phase-II’) were telephonically interviewed. We adopted a quantitative approach to understand disease progression during the three-year course of the pandemic. Changes in cognition and disease severity were measured using the Clinical Dementia Rating (CDR) scale. In brief, semi-structured interviews were carried out with caregivers of people with dementia to gain insights into vaccination rates. Data obtained from the current study (phase III) were compared against phase I data, which served as the baseline. Among the 72 participants contacted in the current phase, 59 (81·9%) could be reevaluated for dementia severity and vaccination status, whereas 13 (18·0%) had died. Among the 59 participants, 33 (55·9%) had severe dementia (CDR 3). This is in contrast to phases I and II, when 17·6% and 19·2% of the participants, respectively, were classified as CDR 3.

A significant difference in dementia severity between the two phases (phases I and III) was observed. In addition, we observed vaccination hesitancy among caregivers of patients with dementia. This study would provide valuable insights into the long-term impact of the COVID-19 pandemic on the cognitive outcomes and vaccination status of patients with dementia.

This overall longitudinal study has compared dementia severity between different phases throughout the pandemic, with implications for future studies to tailor home-based support and healthcare interventions in order to meet these evolving needs.

Alzheimer's Disease (AD) is the most common neurodegenerative disease, and timely and effective diagnosis is essential for the prevention and treatment of AD. Peripheral blood is readily available, inexpensive, and non-invasive, making it an ideal substrate for screening diagnostic biomarkers.

The Notch signaling pathway is closely related to AD, so genes related to the Notch signaling pathway may be candidate diagnostic biomarkers for AD. Here, we have performed an integrated analysis of peripheral blood cells transcriptomics from two AD cohorts (GSE63060: Ctrl = 104, MCI = 80, AD = 145; GSE63061: Ctrl = 134, MCI = 109, AD = 139) to reveal the expression levels of 16 Notch signals involving 100 genes.

The results have shown the changes in Notch signaling-related genes to be highly consistent in both AD cohorts. Bioinformatics analysis has found Differentially Expressed Genes (DEGs) related to Notch signaling to mainly play important roles in Alzheimer's disease, the Notch signaling pathway, and the C-type lectin receptor signaling pathway. Multiple machine learning analyses have revealed IKBKB, HDAC2, and PIK3R1 to exhibit good diagnostic value in both AD cohorts and that they may be ideal biomarkers for early diagnosis of AD.

This study has provided a comprehensive description of the molecular signatures of the Notch signaling pathway in AD peripheral blood and a potential diagnostic model for AD clinical screening.

Alzheimer's Disease (AD) is characterized by a progressive neurodegenerative process leading to cognitive decline and functional impairment. Endocrine factors, particularly sex hormones and their binding proteins, play a critical role in AD pathophysiology. Understanding the relationship between these factors and AD is essential for developing targeted interventions.

To investigate the potential links between sex hormone binding globulin (SHBG) levels, sex hormone profiles, inflammatory markers, and neurocognitive decline in patients with AD.

A retrospective case-control investigation was conducted with 110 AD patients who were admitted to our hospital from January 2021 to December 2023, and the patients were classified into either a mild neurocognitive impairment group (n=59) or a moderate to severe neurocognitive impairment group (n=51) according to their cognitive function. Correlation and regression analyses were conducted to examine relationships between variable factors.

The study revealed a significant neurocognitive decline in AD patients with lower Mini-Mental State Examination (MMSE) and higher AD Assessment Scale-Cognitive Subscale (ADAS-Cog) scores in the moderate to severe neurocognitive impairment group compared to the mild neurocognitive impairment group. Additionally, the moderate to severe neurocognitive impairment group significantly increased for SHBG, estradiol, progesterone inflammatory markers [C-reactive protein (CRP), interleukin-6 (IL-6), tumor necrosis factor α (TNF-α), interleukin-1β (IL-1β). It decreased for follicle-stimulating hormone (FSH) and luteinizing hormone (LH)]. Moreover, significant positive correlations were found between SHBG levels and ADAS-Cog scores, and significant negative correlations were found between SHBG levels and MMSE scores. FSH showed significant negative correlations with the MMSE score, while certain inflammatory markers demonstrated significant correlations with neurocognitive abilities. The correlation between sex hormones and inflammatory factors is weak. FSH, LH, SHBG, CRP, IL-6, TNF-α, and IL-1β are risk factors for neurocognitive impairment, while E2 and P are protective factors.

The study provides evidence of significant correlations between SHBG levels, sex hormone profiles, inflammatory markers, and neurocognitive decline in AD patients.

Alzheimer's Disease and Related Dementias (AD/ADRD) present significant caregiving challenges, with increasing burdens on informal caregivers. This study examines the potential of AI-driven Large Language Models (LLMs) in developing digital caregiving strategies for AD/ADRD. The objectives include analyzing existing caregiving education materials (CEMs) and mobile application descriptions (MADs) and aligning key caregiving tasks with digital functions across different stages of disease progression.

We analyzed 38 CEMs from the National Library of Medicine’s MedlinePlus, along with associated hyperlinked web resources, and 57 MADs focused on AD digital caregiving. Using ChatGPT 3.5, essential caregiving tasks were extracted and matched with digital functionalities suitable for each stage of AD progression, while also highlighting digital literacy requirements for caregivers.

The analysis categorizes AD caregiving into 4 stages-Pre-Clinical, Mild, Moderate, and Severe-identifying key tasks, such as behavior monitoring, daily assistance, direct supervision, and ensuring a safe environment. These tasks were supported by digital aids, including memory-enhancing apps, Global Positioning System (GPS) tracking, voice-controlled devices, and advanced GPS tracking for comprehensive care. Additionally, 6 essential digital literacy skills for AD/ADRD caregiving were identified: basic digital skills, communication, information management, safety and privacy, healthcare knowledge, and caregiver coordination, highlighting the need for tailored training.

The findings advocate for an LLM-driven strategy in designing digital caregiving interventions, particularly emphasizing a novel paradigm in AD/ADRD support, offering adaptive assistance that evolves with caregivers' needs, thereby enhancing their shared decision-making and patient care capabilities.

The association between physical activity (PA) and cognitive function remains controversial, and the impact of gender on this association remains underexplored. Therefore, this study aimed to investigate the association between PA and cognitive function and to explore whether this association was modified by gender among older adults.

In 2016, a cluster sampling method was used to select community-dwelling older adults aged 65 and above. PA was assessed using the International Physical Activity Questionnaire-Short Form and classified as low, middle, and high. Cognitive function was assessed using the revised Chinese version of the Wechsler Adult Intelligence Scale. The multiple linear regression model was used to explore the association between PA and cognitive function and to assess whether this association differs by gender.

A total of 676 participants with a mean age of 73.63 ± 6.39 were included. The multiple linear regression analysis showed that higher PA was significantly statistically associated with higher Full Intelligence Quotient (FIQ), Performance Intelligence Quotient (PIQ), and verbal Intelligence Quotient (VIQ) scores (P<0.05). Among the WAIS-RC subtests, higher PA was significantly statistically associated with higher scores of the similarity subtest, picture completion subtest, and picture arrangement subtest (P<0.05). In the gender subgroup analysis, higher PA was significantly statistically associated with higher FIQ and PIQ scores (P<0.05), but no significant association was found with VIQ scores (P>0.05) in the male group, while in the female group, there was no significant statistical association between higher PA and FIQ, PIQ, or VIQ scores (P>0.05).

Higher PA was significantly statistically associated with better cognitive function (P<0.05). In the male group, PA was significantly statistically associated with cognitive function, whereas no comparable association was found in the female group.