bluuebunny/crossref_metadata_2025 huggingface dataset:
Detection of Mild Cognitive Impairment Using Convergent Cross‐Mapping Based on Resting‐State EEG Signals among Community‐Dwelling African American Participants
Authors: Sun Boxin , Deng Jinxian , Li Tongtong , Kavcic Voyko , Giordani Bruno
Published: December 2023

Background

Accurate and early detection of mild cognitive impairment (MCI) is critical for interventions to promote cognitive resiliency. EEG‐based detection of MCI is attracting considerable attention from the research community due to its accessibility, affordability and increasing accuracy.

Method

Our research is based on resting‐state EEG (64‐channel, eye‐closed). The current dataset includes 90 consensus‐diagnosed, community‐dwelling African Americans (ages 60‐90 years, 51 normal cognition, NC; 39 Mild Cognitive Impairment, MCI) recruited through the Wayne State Institute of Gerontology Healthy Black Elders Center and the Michigan Alzheimer’s Disease Research Center, all with subjective cognitive complaints.

From an information‐theoretic perspective, causality measures the effective connectivity or directed information transfer from one brain region to another. Convergent cross‐mapping has attracted considerable attention recently since it was proven to be able to detect causal coupling in both deterministic and random settings. In this research, we propose to develop an EEG‐based MCI detection model by exploiting cross‐mapping causality analysis.

We first derived the current source density (CSD) from EEG signals and performed cross‐mapping based causality analysis between the CSD signals of all the possible pairs across the selected EEG regions of interest. We then conducted joint time‐frequency‐spatial analysis on the cross‐mapping causation and selected features which are likely to reflect the differences between NC and MCI. The selected features were then fed into a machine‐learning algorithm for discrimination of NC and MCI.

Result

By tuning the observing window size and the number of features used, we obtained a series of different configurations of the discrimination model between NC and MCI, each with its own estimation accuracy. The overall result is a combined output of the model under different configurations, which improve the reliability and sensitivity of the discrimination model. For the 90‐sample dataset we are working with, the leave‐one‐out cross‐validation accuracy of our model is 97.78%.

Conclusion

Our analysis indicates that, potentially, EEG‐based cross‐mapping causality analysis may serve as a promising assessment tool for early detection of people at risk of MCI and dementia, even when just relying on resting state EEG.

Funding: NSF‐2032709/Li; NIH‐1R21AG046637‐01A1/Kavcic and NIH‐1R01AG054484‐01A1/Kavcic; NIH‐ P30AG05376004/Paulson
Role of Onset of Diabetes on Development of Cognitive Impairment in Rats
Authors: Goura Venkatesh , Kallepalli Rajesh , Abraham Renny , Jayarajan Pradeep , Nirogi Ramakrishna
Published: December 2023

Background

The risk of cognitive impairment in diabetic patients is increasing in day to day life. One of the reasons for cognitive impairment in diabetic patients is hyperglycemic condition. Hyperglycemia leads to amyloid beta accumulation in brain, aggravates oxidative stress, neuro‐inflammation, and results in mitochondrial dysfunction, which impairs neuronal integrity, and eventually neurodegeneration. These are possible working mechanisms in diabetes‐related cognitive impairment. Further, literature says that, earlier the development of diabetes, greater the chances of developing cognitive impairment.

Method

Diabetes was induced using streptozotocin in juvenile (3‐6 weeks old), adult (8‐10 weeks old) and aged (30‐34 weeks old) rats. Blood glucose levels were monitored after 10 days of streptozotocin administration. Rats which showed cognitive impairment were treated with insulin or insulin + donepezil. Diabetic rats were evaluated for cognitive impairment in fear conditioning memory task at 3 and 6 weeks after the confirming diabetes.

Result

The total freezing time decreased in juvenile> adult > aged diabetic rats respectively, when compared with naïve rats. The cognitively impaired diabetic rats treated with insulin + donepezil showed improvement in the associative memory observed from increase in freezing behavior in fear conditioning task.

Conclusion

Diabetes in the early stages of life may have greater risk for developing cognitive impairment.
Associations of peripheral and neuronal insulin resistance with cognition and functional brain networks in older adults with obesity
Authors: McIntyre Clayton Connor , Lyday Robert , Macauley Shannon L , Deep Gagan , Su Yixin , Nicklas Barbara , Hugenschmidt Christina E
Published: December 2023

Background

Insulin resistance (IR) in peripheral tissue is a risk factor for Alzheimer’s disease. A proposed method for isolating neural‐enriched extracellular vesicles (nEVs) may allow measurement of neuronal IR in living humans. The hippocampus may be particularly sensitive to insulin signaling. We assessed associations of peripheral and neuronal IR with cognition and resting‐state functional brain networks in sedentary adults aged 65+ with obesity.

Methods

Analyses were performed on baseline data in a subset of participants (n = 75) from the INFINITE study who had MMSE ≥ 24 and had obesity but not type 2 diabetes. HOMA2‐IR quantified peripheral IR. The proposed insulin resistance index for nEVs (nEV‐IR) quantified neuronal IR. Executive function was measured by a composite score calculated from the digit symbol coding task, Trail Making Test parts A and B, Stroop task, phonemic fluency, and semantic fluency. Immediate learning was measured by the summed score of Auditory Verbal Learning Test (AVLT) trials 1‐5. Associations between cognition and HOMA2‐IR or nEV‐IR were evaluated using linear regression adjusted for age, sex, education, and BMI. Functional networks were created from resting‐state fMRI. Associations between brain network features in the hippocampus (global efficiency (Eglob), local efficiency (Eloc), first‐step connections, community structure) and HOMA2‐IR or nEV‐IR were evaluated using a novel regression framework for brain network distance metrics. Brain network regression models controlled for age, sex, education, and BMI.

Results

HOMA2‐IR and nEV‐IR were not correlated (p = .682). HOMA2‐IR was negatively associated with the executive function composite (β = ‐0.752, SE = 0.329, p = .026) but not AVLT trials 1‐5 (p = .185) or MMSE (p = .099). nEV‐IR was not associated with the executive function composite (p = .861), AVLT trials 1‐5 (p = .725), or MMSE (p = .262). HOMA2‐IR was positively associated with hippocampal Eloc (β = 0.0035, SE = 0.0014, p = .011) but not Eglob (p = .724). nEV‐IR was not associated with Eloc (p = .782) or Eglob (p = .752). Neither HOMA2‐IR nor nEV‐IR was associated with hippocampal connectivity (HOMA2‐IR: p = .419, nEV‐IR: p = .187) or community structure (HOMA2‐IR: p = .670, nEV‐IR: p = .404).

Conclusion

Measures of peripheral – but not neuronal – IR are associated with unfavorable cognitive outcomes and with higher local efficiency in the hippocampus. These findings add to ongoing debate over nEV‐IR as a neuronal IR assessment.
Level of blood Tau and p‐Tau : a non‐invasive approach for the diagnosis of Alzheimer’s Disease(AD)
Authors: Kumari Sakshi , Yadav Yudhishthir , Singh Abhinay Kumar , Kaur Priyajit , Chakrawarty Avinash , Dey Sharmistha
Published: December 2023

Background

Prominent expression of Tau and phosphorylated Tau in cerebrospinal fluid (CSF) is one of the well‐known hallmarks of the Alzheimer’s disease (AD). High levels of p‐Tau can easily differentiate AD from other neurodegenerative disease. However, the serum levels of these proteins in AD patients are not well explored. This study provides an alternative non‐invasive approach to diagnose the disease by evaluating the level of Tau and p‐Tau181 in serum samples.

Method

Blood samples were collected from 39 AD patients, 37 MCI patients and 37 elderly individuals as controls. Quantification of tau and pTau in serum samples was done with the help of a label free real time Surface Plasmon Resonance technology, and further validated by Western Blot. Statistical analysis, including Receiver Operating Characteristic (ROC), was done for further affirmation.

Result

The concentrations of serum Tau and p‐Tau181 were significantly higher (p<0.00001) in AD (Tau; 47.49±9.00ng/µL, p‐Tau181; 0.161±0.04 ng/µL) compared to MCI (Tau; 39.26±7.78 ng/µL, p‐Tau181; 0.135±0.02 ng/µL) and were further compared to elderly controls (Tau; 34.92±6.58 ng/µL, p‐Tau181; 0.122±0.01 ng/ µL). A significant (p<0.0001) downhill correlation was found between Tau as well as p‐Tau181 levels with HMSE and MoCA score.

Conclusion

This study for the first time reports the concentration of Tau and p‐Tau181 in serum of AD and MCI patients. The cut‐off values of Tau and p‐Tau181 of AD and MCI patients with sensitivity and specificity reveal that serum level of these proteins can be used as a predictive marker for AD and MCI.
The quality of visual entrainment correlates with forward traveling wave properties in human cortex
Authors: Lahijanian Mojtaba , Panjehpour Armin , Aghajan Hamid ,   Augmented Intelligence Research Lab (AIRLab)
Published: December 2023

Background

Flickering light stimulation has been shown to entrain the brain’s oscillatory activity at the input frequency and synchronize different cortical regions in that frequency (Herrmann et al., 2001; Lahijanian et al., 2021). Brain entrainment at gamma frequency has been proposed and shown promising results as a non‐pharmaceutical therapeutic approach for Alzheimer’s disease (Cimenser et al., 2021). Studying the effects of such stimulation on the brain’s neural activity can help explain the mechanisms that underlie the reported improvements. It is known that neural oscillations form traveling waves across the brain during various cognitive functions (Bhattacharya et al., 2022). In this study, we use different flickering light frequencies as entrainment input and investigate the spatiotemporal pattern of neural activity modulated by visual entrainment which appears as a traveling wave across the posterior‐frontal pathway.

Method

EEG data recorded from young healthy adults were analyzed during multi‐trial flickering light stimulation at 10, 15, 20, 22, and 30Hz frequencies. In order to analyze the quality of posterior‐frontal waves, the spatiotemporal phase pattern was measured over the head midline. The wave quality was defined as the consistency of the spatiotemporal phase pattern during consecutive time intervals, and the quality of entrainment was defined as the intensity of the power spectral density at the input frequency.

Result

During the resting state, different wave patterns traveling across the frontoparietal link are canceled out. However, visual stimulation invigorates the forward wave from the sensory (posterior – visual) region to the upstream area (frontal lobe) at the target frequency compared to the baseline. Meanwhile, in contrast to the forward wave, traveling wave in the backward direction does not show noticeable presence at the stimulation frequency. Furthermore, as the entrainment quality increases, the wave pattern consistency is improved for all stimulating frequencies (Figs. 1, 2).

Conclusion

The forward wave induced during non‐invasive visual stimulation represents long‐range activity along the posterior‐frontal pathway known to be activated during sensory processing and inference. The observed correlation between the wave’s quality and the quality of entrainment at the target frequency points to the mechanism underlying the therapeutic effects of gamma entrainment.
Alzheimer’s disease is associated with increased modularity and assortativity: Evidence from structural and metabolic connectivity
Authors: Khokhar Sunil Kumar , Kumar Manoj , Kumar S Sandeep , Manae Tejaswini , Thanissery Nithin , Ramakrishnan Subasree , Arshad Faheem , Nagaraj Chandana , Mangalore Sandhya , Alladi Survana , Gandhi Tapan K , Bharath Rose Dawn
Published: December 2023

Background

Alzheimer’s disease (AD) is a progressive disorder associated with cognitive dysfunction that alters brain connectivity and assessing these altered connectivity patterns has become a topic of increasing interest. In this study, we examine the structural and metabolic connectivity using cortical thickness and [18F] Flouro deoxyglucose (FDG)‐positron emission tomography (PET) to identify the network modification in patient with AD when compared to mild cognitive impairment (MCI). To examine our hypothesis; we quantified a relatively newer graph theory measures including assortativity and modularity. We aimed to unravel the multimodal network alterations using simultaneous MRI‐PET acquisitions.

Methods

Patients who underwent simultaneous FDG‐PET and MRI study on a 3T MRI were recruited for this exploratory study. After appropriate pre‐processing of structural‐MRI and PET‐metabolic data, graph measures were obtained using the BRAPH toolbox, and subsequently; global and nodal network measures were used to derive group‐level differences (corrected p<0.05). Regions that revealed significant differences were correlated with the cognitive scores (ACE‐III).

Results

83 demographically matched patients [MCI (n = 27), and AD (n = 56)] were analysed. There were no significant differences between the groups in the mean age (MCI 63.52 ±9.19 years and AD 63.73 ±9.60 years), gender (M: F) MCI 20:7 and AD 26:30, or the mean duration of disease (MCI 2.23±1.92 and AD 2.95 years) other than ACE scores (MCI‐87.30±5.53 and AD 46.02 ±20.61, p value <0.001) and the CDR (MCI‐very mild and AD‐Moderate and Severe). Patients with AD revealed significantly increased assortativity at the global level in both structural and metabolic connectivity analysis. In addition, metabolic connectivity revealed increased modularity and decreased participation coefficient in patients with AD. Cortical thickness and SUV abnormalities in several regions in bilateral parietotemporal lobes were proportional with the cognitive scores (ACE‐III).

Conclusion

Probable erroneous and homophilic network segregation paralleling the aging associated loss of whole brain integration was found proportional to the memory scores. Further studies in larger cohorts are required to ascertain the clinical relevance of these findings as an imaging biomarker.
Nowhere to run, nowhere to hide ‐ targeting the immune system in AD with multimodal plasma therapeutics
Authors: Lehallier Benoit , Feng Chunmiao , Nanasi Tibor , Gonzalo Ricardo , Minguet Carla , Ortiz Ana Maria , Bravo Isabel , Lohr Scott , Boada Mercè , Lopez Oscar L. , Páez Antonio , Cerezo Cesar , Costa Montserrat , Braithwaite Steven P
Published: December 2023

Background

Age‐related diseases, especially Alzheimer’s Disease (AD), have multifaceted nature because of the different factors and pathways contributing to these diseases. Multi‐modal plasma therapies have the potential to impact multiple pathways and modulate different mechanisms of diseases in a safe and versatile way. Here we discuss insights from deep plasma proteomics profiling in patients from the GRF6019 and AMBAR clinical trials in which multi‐modal plasma therapeutics were used and limited cognitive decline was observed.

Method

The GRF6019 phase 2 trials were based on the infusion of a complex plasma fraction while the AMBAR phase 2b/3 trial used plasma exchange and albumin replacement (PE‐Alb). Patients in these trials were mild‐to‐moderate AD and 1143 plasma samples were analyzed using the SomaScan platform. The trajectories of 7k proteins were analyzed using classic and new machine learning techniques.

Result

GRF6019 infusion resulted in an acute and broad impact on the plasma proteome but the detectable long‐term effects on molecular level were minimal. Pathways analysis of protein trajectories pointed out to the immune system, ECM remodeling but also brain specific biological processes linked to neurons and axon guidance, suggesting that various biological pathways were significantly modulated (q<0.05). PE‐Alb treatment also induced an acute effect on several hundreds of proteins (461 proteins with log2FC←1 & q<0.05) but some proteomics changes lasted for weeks after the end of the intensive period (25 proteins with q<0.05). A significant part of these changes (19% of acute and 56% of lasting response proteins) were related to immune and inflammatory‐related pathways. In addition, several individual proteins from the immune pathway were associated with improvement of CDR‐SB or ADCS‐CGIC at the end of the AMBAR trial suggesting that multiple parts of the immune system might need to be targeted to slow‐down AD progression.

Conclusion

AD has multifaceted nature and plasma therapeutics have proven safety, efficacy, and versatility. The proteomics results from these trials shed the light on the underlying mode of action of multi‐modal plasma‐derived therapies and demonstrate that they can modulate multiple pathways relevant to AD, with a strong effect on the immune and inflammatory responses which may contribute to slowing down AD progression.
Early changes of fecal short‐chain fatty acid levels in patients with mild cognitive impairments
Authors: Chen Shengdi
Published: December 2023

Background

Mild cognitive impairment (MCI) is with great risk for the conversion to Alzheimer’s disease (AD). The aim of present study wanted to explore whether fecal Short‐chain fatty acids (SCFAs) could be used as the biomarker for the identification of MCI patients and to examine the relationship between fecal SCFAs and amyloid‐β deposition in the brain.

Methods

A cohort of 32 MCI patients and 27 NC were recruited in our study. Fecal levels of SCFAs were measured using chromatography and mass spectrometry. Disease duration, ApoE genotype, body mass index, constipation, and diabetes were evaluated. To assess cognitive impairment, we used the Mini‐Mental Status Examination (MMSE). To assess brain atrophy, the degree of medial temporal atrophy (MTA score, Grade 0‐4) was measured by structural MRI. β‐amyloid positron emission tomography (PET) with 18F‐AV‐45 was performed in seven MCI patients to detect and quantify Aβ deposition in the brain.

Results

Compared with NC, MCI patients had significantly lower fecal levels of acetic acid, butyric acid, and caproic acid. Among fecal SCFAs, acetic acid performed the best in discriminating MCI from NC, achieved an AUC of 0.752 (p = 0.001, 95% CI: 0.628‐0.876), specificity of 66.7% and sensitivity of 75%. By combining fecal levels of acetic acid, butyric acid and caproic acid, the diagnostic specificity was significantly improved, reaching 88.9%. To better verify the diagnostic performance of SCFAs, we randomly assigned 80% of participants into training dataset and 20% into testing dataset. Only acetic acid showed significantly difference between these two groups in the training dataset. Based on the fecal levels of acetic acid, we achieved the ROC curve. Next, the ROC curve was evaluated in the independent test data and 66.7% (4 in 6) of MCI patients, and 80% (4 in 5) of NC could be identified correctly. Subgroup analysis showed that reduced fecal SCFAs in MCI group were negatively associated with Aβ deposition in cognition‐related brain regions.

Conclusion

Our findings suggest that gut metabolite SCFAs have the potential to serve as early diagnostic biomarkers for distinguishing patients with MCI from NC and could serve as potential targets for preventing AD.
Association of resting heart rate with cognitive decline and brain age in older adults: a large‐scale cohort study in the UK Biobank
Authors: Wang Jiao , Yang Wenzhe , Dove Abigail , Qi Xiuying , Xu Weili
Published: December 2023

Background

The relationship of resting heart rate (RHR), a common indicator of cardiovascular health, with cognitive decline is unclear. We aimed to investigate the association of RHR with cognitive trajectory and brain age assessed by brain Magnetic Resonance Imaging (MRI) in the UK Biobank.

Method

Within the UK Biobank 18,210 chronic brain disorders‐free participants aged 60+ were followed for up to 16 years. RHR was assessed by blood pressure monitor and categorized into <60, 60‐69 (reference), 70‐79, and ≥80 beats per minute (bpm). Cognitive function including global cognition, numeric memory, prospective memory, pairs matching, fluid intelligence, and reaction time was collected at baseline and each follow‐up wave. A subsample of 10,458 participants underwent brain MRI (T1‐weighted MRI, T2‐FLAIR, T2∗, diffusion‐MRI, task fMRI, and resting‐state fMRI) to detect brain age and brain predicted age difference (PAD) using Lasso regression. Data were analyzed using mixed‐effects model and linear regression model.

Result

Compared to reference group, RHR≥80 bpm was associated with faster decline in global cognition (β: ‐0.03, 95% confidence interval [CI]: ‐0.05, ‐0.01) and reaction time (β: ‐0.03, 95% CI: ‐0.07, ‐0.01). In the MRI data analysis, RHR≥80 bpm was associated with older brain age (β [95% CI]: 0.50 [0.25, 0.76]) and bigger brain PAD (β [95% CI]: 0.50 [0.26, 0.74]).

Conclusion

Higher RHR is associated with faster cognitive decline and older brain age. Monitoring and controlling elevated RHR could be a promising interventional target in preserving cognitive function.
Development of a framework capturing the interactions of people with dementia and their facilitators in virtual CST sessions: A proposal
Authors: Wong Winsy Wing Sze , Choy Jacky Chak Pui
Published: December 2023

Background

Telehealth has been gaining much attention, especially since the COVID‐19 pandemic. A virtual version of Cognitive Stimulation Therapy (CST), based on the conventional face‐to‐face CST (Spector et al., 2003), has been developed, with feasibility reported in Perkins et al. (2022). The present study proposes an analytic framework for capturing the verbal and nonverbal interactions of people with dementia (PwD) and their facilitators during virtual CST sessions delivered via tablet computers and video conferencing tool.

Method

Existing models/frameworks for capturing verbal and nonverbal interactions of PwD and their communication partners were identified and evaluated. Quantifiable parameters/features which are observable/applicable to virtual CST sessions were incorporated into the new framework.

Result

A newly proposed framework, primarily based on the conversation analysis (Perkins et al., 1998) of PwD and coding system of co‐verbal gestures of people with aphasia (Kong et al., 2015), has been developed. Issues specific to virtual delivery of CST have been considered and accommodated in the framework.

Conclusion

The proposed framework will help researchers investigate and quantify the verbal and nonverbal interactions during virtual CST. Its potential in enhancing treatment outcomes, in terms of training of facilitators, and investigations of the relation between the behaviors of PwD during sessions and treatment gains in different aspects, will be discussed.

References:

Kong, A. P. H., Law, S. P., Kwan, C. C. Y. et al. (2015). A coding system with independent annotations of gesture forms and functions during verbal communication: Development of a database of Speech and GEsture (DoSaGE). Journal of Nonverbal Behaviors, 39, 93‐111.

Perkins, L., Fisher, E., Felstead, C., Rooney, C., Wong, G. H., Dai, R., … & Spector, A. (2022). Delivering cognitive stimulation therapy (CST) virtually: Developing and field‐testing a new framework. Clinical Interventions in Aging, 17, 97.

Perkins, L., Whitworth, A., & Lesser, R. (1998). Conversing in dementia: A conversation analytic approach. Journal of Neurolinguistics, 11, 33‐53.

Spector, A., Thorgrimsen, L., Woods, B., Royan, L., Davies, S., Butterworth, M., & Orrell, M. (2003). Efficacy of an evidence‐based cognitive stimulation therapy program for people with dementia. British Journal of Psychiatry, 183, 248‐254.
Relationships of Psychiatric Comorbidities with the Risk of Hospitalization for Motor Vehicle Crash Injury in Young‐Onset Dementia: A Nationwide Population‐Based Study in Taiwan
Authors: Liu Chih‐Ching
Published: December 2023

Background

Although the association between young‐onset dementia and hospitalization for motor vehicle crash injury (MVCI) has been shown, little is known about the relationship between the risk of MVCI and psychiatric comorbidities in young‐onset dementia. This study investigates the which psychiatric comorbidities in young‐onset dementia increases the risk of MVCI.

Method

In this retrospective population‐based cohort study, we identified 39,344 dementia aged 40‐64 years from the Taiwan National Health Insurance Research Database (NHIRD) entries between 2006 and 2012. MVCI‐related hospitalization was determined using linked data from the Police‐reported Traffic Accident Registry and the NHIRD between 2006 and 2015. We performed the Cox regression model to estimate the association of the risk of hospitalization for MVCI with young‐onset dementia comorbid with specific psychiatric disorders, including anxiety disorders, depressive disorders, bipolar disorders, alcohol‐related disorders, other substance‐related disorders, and insomnia.

Result

Of the 39,344 participants included in the study, all participants encountered 1,013 hospitalizations for MVCI in the 222,239.8 person‐years observed, representing incidence densities of hospitalization for MVCI of 45.58 (95% CI 42.77‐48.39) per 10,000 person‐years. The incidence densities of hospitalization for MVCI increased when young‐onset dementia comorbid with anxiety disorders (56.17 per 10,000 person‐years), depressive disorders (58.61 per 10,000 person‐years), bipolar disorders (83.55 per 10,000 person‐years), alcohol‐related disorders (85.64 per 10,000 person‐years), other substance‐related disorders (84.79 per 10,000 person‐years), and insomnia (59.80 per 10,000 person‐years). However, the risk of hospitalization for MVCI was only significantly increased when young‐onset dementia comorbid with bipolar disorders (HR, 1.60; 95% CI: 1.21‐2.13), alcohol‐related disorders (HR, 1.55; 95% CI: 1.27‐1.90) and insomnia (HR, 1.26; 95% CI: 1.07‐1.47).

Conclusion

Younger adults with dementia comorbid with specific psychiatric disorders rise the risk of hospitalization for MVCI, which suggests the reinforcement transport safety in those population is needed.
What attributes have been included in discrete choice experiments related to health technologies used in the early detection, diagnosis and treatment of neurodegenerative conditions? A systematic literature review
Authors: Kamran Ifrah , Ardle Ríona Mc , Ternent Laura , Slight Sarah
Published: December 2023

Introduction

Alzheimer’s disease (AD) and Parkinson’s disease (PD) are the most common neurodegenerative conditions. Information on the preferences of patients, health care professionals and the public on the early detection, diagnosis and treatment of these conditions is limited. Understanding preferences is essential to improve health‐related outcomes. Discrete choice experiments (DCEs) are a widely used method to elicit preferences. A previous systematic review identified the attributes that were included in DCEs related to health technologies, although none of the included studies related to neurodegenerative conditions.

Aims

To identify attributes and their respective levels used in the design of discrete choice experiments that examined preferences for early detection, diagnosis and treatment for AD and PD.

Method

Four large databases (Cinahl, Embase, Medline, Scopus, Web of science) were searched between January 2015 and October 2022. Search terms included grouped into sets relating to discrete choice and dementia. The search was limited to peer reviewed studies in English and related to the use of health technology (defined as the application of organised knowledge and skills in the form of devices, medicines, vaccines, procedures, and systems) in the early detection, diagnosis or treatment AD or PD. Studies included people diagnosed with AD or PD, members of the public or clinicians. This review was registered with PROSPERO (registration number: CRD42023365169), adhered to PRISMA guidelines and used a DCE quality assessment tool devised by Mandeville et al. (2014).

Results

A total of 196 studies were identified, eight of which were included. Two studies focused on AD and six studies on PD. The average number of attributes included in the DCEs was 4.5 (SD 0.57), the average number of levels per attribute was 3.4 (SD 0.80). The most common attributes used in DCEs were as follows: risk of side effects, cost, device type, oral medicines required, duration of ON time and increase in daily ON time (the period when medication for Parkinson’s is effective is ON time). There was no overlap in attributes within studies reporting on AD.

Conclusion

Preference researchers can incorporate the attributes identified into surveys in order to support the development of clinical decision‐making frameworks.
The Effect of Hippo Pathway Inhibitor Xmu‐mp‐1 on Cognitive Impairment in a Rat Model of Alzheimer’s Disease: Protection against Oxidative Stress, Tau Hyperphosphorylation, and Neurodegeneration
Authors: Sahu Manas Ranjan , Mondal Amal Chandra
Published: December 2023

Background

Alzheimer’s Disease (AD), the most common form of dementia, is a growing global health concern with unmet clinical therapeutics. AD can be attributed to amyloid beta aggregation and tau hyperphosphorylation‐induced oxidative stress and neurodegeneration in the brain. Previous studies have implicated a hyper‐activated Hippo signaling pathway with neuronal loss in neurodegenerative disorders, including AD. However, it is still unknown if suppressing the Hippo pathway can rescue neuronal death in AD.

Method

In this study, we investigated the cognitive impairment ameliorative effect of the novel Hippo signaling inhibitor, Xmu‐mp‐1, in a rat model of AD. Adult male Wistar rats were stereotaxically injected with a well‐known AD inducer Streptozotocin (STZ), to mimic AD‐like features. A pharmacological antagonist of Hippo signaling component MST1 called Xmu‐mp‐1 was administered intraperitoneally at a dose of 0.5mg/kg body weight for 14 days. Then the effect of Xmu‐mp‐1 on cognitive impairment was assessed using the Morris water maze test and novel object recognition test. Further, we did biochemical and histopathological studies to explore the effect of Xmu‐mp‐1 on several AD‐associated pathophysiological changes, including oxidative stress, tau hyperphosphorylation, and neurodegeneration.

Result

Xmu‐mp‐1 significantly improved the cognitive impairment of the AD rats in the Morris water maze test and the novel object recognition test (n = 7). Biochemical analysis of the brain hippocampal and cortical tissues revealed that Xmu‐mp‐1 also ameliorated the AD‐associated oxidative stress burden as the levels of anti‐oxidants (SOD, Catalase, GSH) significantly increased and the levels of oxidative stress biomarkers (protein carbonyl and lipid peroxidation) significantly reduced after Xmu‐mp‐1 treatment in the AD rats (n = 6). Moreover, the level of tau phosphorylation, a prime characteristic of AD, was also reduced following Xmu‐mp‐1 treatment (n = 3). Finally, neuronal death was also found to be rescued after Xmu‐mp‐1 treatment in AD rats (n = 3).

Conclusion

Xmu‐mp‐1 exhibits a neuroprotective role against AD as it improves the cognitive impairment induced by STZ. Further mechanistic investigations into the neuroprotective role of Xmu‐mp‐1 revealed that Xmu‐mp‐1 provides protection from oxidative stress, tau hyperphosphorylation, and aberrant neurodegeneration under an AD background. Future studies can explore the therapeutic potential of Hippo signaling inhibition against AD in more detail.
Estimating the potential for prevention of dementia in Germany
Authors: Blotenberg Iris , Hoffmann Wolfgang , Thyrian Jochen René
Published: December 2023

Background

As the German population ages, the number of people with dementia is predicted to rise considerably in the upcoming decades. In the absence of a disease‐modifying treatment, prevention is key to curb the growing numbers of dementia cases. In order to tailor prevention approaches to the German context, knowledge about the potential for prevention in Germany and the most prevalent modifiable risk factors is vital.

Method

We calculated population attributable fractions (PAF) for eleven potentially modifiable risk factors for dementia. Relative risks were taken from a recent review, prevalence estimates and weights were calculated using data from the German Ageing Survey. Weights were used to adjust for associations between risk factors, they were calculated using a principal component analysis based on tetrachoric correlations between risk factors. Potential impact fractions (PIF) were calculated to estimate the effect of a reduction in risk factor prevalence on the future number of dementia cases.

Result

More than a third of dementia cases in Germany are associated with eleven potentially modifiable risk factors. The largest number of cases are associated with hearing impairment and hypertension, among others. A significant reduction in risk factor prevalence could theoretically reduce the number of dementia cases in 2050 by more than 150.000.

Conclusion

The number of dementia cases in Germany is rising, but there is considerable potential for prevention. Further advancement of prevention approaches for healthy ageing and their implementation into routine care should be fostered.
Prediction of Global Cognition Trajectories with Medial Temporal Brain Stiffness in Aging and Alzheimer’s Disease
Authors: Pavuluri KowsalyaDevi , Huston John , Ehman Richard L. , Manduca Armando , Vemuri Prashanthi , Jack Clifford R. , Senjem Matthew L. , Murphy Matthew C.
Published: December 2023

Background

Cognitive decline with aging and neurodegeneration is caused by various neurobiological processes at molecular, cellular, and organ levels. Advanced imaging techniques that detect tissue microstructural alterations may predict cognitive decline earlier than atrophy measures. Tissue‐level mechanical properties are thought to primarily reflect the rigidity and tension of extracellular matrix‐cytoskeleton matrix (https://doi.org/10.1038/s41586‐019‐1516‐5) and can be measured noninvasively by Magnetic Resonance Elastography (MRE) (https://doi.org/10.1126/science.7569924). These properties are sensitive to pathophysiological processes that characterize neurological disease including dementias. This study examines the role of medial temporal lobe stiffness in predicting global cognitive decline in participants along the Alzheimer’s disease spectrum.

Method

Seventy‐five participants underwent MRE, MRI, amyloid PET imaging, and cognitive assessments with informed consent, and the study was approved by the Mayo Clinic IRB. MRE stiffness maps were calculated by neural network inversion, and medial temporal (MT) stiffness extracted (https://doi.org/10.1002/mrm.29226https://doi.org/10.1016/j.nicl.2023.103328). White matter hyperintensity (WMH) load, average cortical thickness of AD signature regions, PiB‐PET standardized uptake ratio (PiB‐SUVr), and global cognition z‐scores were each computed (https://doi.org/10.1016/j.neurobiolaging.2020.09.005). Linear mixed effect models were used to assess the effects of MT‐stiffness and its interaction with follow‐up time on global cognition. The additional effects of cortical thickness, WMH, and PiB‐SUVr, and their interactions with cognition follow‐up time were evaluated.

Result

Table 1 summarizes results from three mixed effect models. MT‐stiffness and its interaction with time were significant predictors in models 1 (MT‐stiffness only) and 2 (MT‐stiffness+cortical thickness). In model 3 (MT‐stiffness+cortical thickness+PiB‐ratio+WMH), MT‐stiffness alone did not reach significance (P= 0.058), but its interaction with time was a significant predictor. Fig.1 shows global cognition z‐scores with age. Figs. 2A,2B, and 2C show global cognition prediction trajectories. These results suggest that softer MT‐stiffness predicts faster cognitive decline. MT‐stiffness was a significant predictor of cognitive score even when controlling for other biomarkers such as cortical thickness, PiB‐SUVr, and WMH. These results indicate that stiffness measurements can add predictive value regarding cognitive decline in addition to atrophy and amyloidosis.

Conclusion

Brain mechanical alterations capture microstructural changes that may aid in understanding disease progression and provide information about future cognitive decline in elderly participants along the Alzheimer’s disease continuum.
Computerized serious game‐based cognitive training in subjective cognitive decline
Authors: Brill Esther , Krebs Christine R. , Brem Anna‐Katharine , Klöppel Stefan
Published: December 2023

Background

The neurodegenerative process in Alzheimer’s Disease (AD) commences long before the onset of clinically relevant symptoms. Subjective cognitive decline (SCD) has predictive value towards AD and lends itself as target for non‐pharmacological preventive interventions such as serious game‐based computerized cognitive training (CCT). CCT is effective in attenuating cognitive decline in older adults with mild cognitive impairment or dementia (Hill et al., 2017), however, results in SCD are heterogeneous and long‐term adherence to trainings at home remain a challenge. Additionally, this study aims at addressing shortcomings of previous CCT studies such as comparisons to passive but also active control conditions, matched e.g. for the social elements, crucial for adherence.

Method

In this ongoing bi‐centric, randomized controlled trial (RCT) with parallel groups, participants aged 60 ‐ 85 years with SCD are randomized to one of three study arms (Brill et al., 2022). We compare serious game‐based CCT against a passive wait list control condition and an active control condition (watching documentaries). CCT here focuses on episodic memory, semantic and spatial ability, each leading to one composite score. The protocol in both training conditions entails five weekly at‐home sessions for ten weeks (50 sessions) and weekly on‐site group meetings.

Result

Adherence among the current 135 participants was very high. The scores of cognitive function increased in both training groups over the ten weeks’ period, irrespective of the training condition. Baseline imaging data demonstrate strong activations of networks related to spatial ration and episodic memory. Analysis of longitudinal data is ongoing.

Conclusion

Our preliminary results indicate no specific advantage of CCT over an active control condition in improving cognitive performance. Modulating biological (AD biomarkers) but also psychological factors (e.g. motivation) require further analysis in our dataset. Social elements such as interactive groups meetings seem to be effective in ensuring adherence across training conditions.

Keywords:

Computerized cognitive training, serious games, subjective cognitive decline
Gamma‐band transcranial alternating current stimulation in amnestic mild cognitive impairment: A pilot study
Authors: Zanto Theodore P.
Published: December 2023

Background

Amnestic mild cognitive impairment (aMCI) is a pre‐dementia stage of Alzheimer’s disease (AD) associated with dysfunctional episodic memory and limited treatment options. Recent findings from animal models of AD show that 40 Hz (gamma) stimulation (e.g., through light, sound, magnetic, or electrical stimulation sources) can improve episodic memory and learning, can facilitate neurogenesis, and can also reduce biomarkers associated with AD pathology including beta‐amyloid (Aβ) and tau. Although preliminary studies regarding the efficacy of gamma stimulation in humans has been promising, evidence is limited, neuroplastic changes are unclear, and the feasibility of electrical‐based gamma stimulation is still under investigation. Here, we aimed to characterize feasibility and neuroplastic changes associated with possible improvements in episodic memory following electrical non‐invasive neurostimulation.

Method

13 individuals with aMCI received eight 60‐minute sessions of 40‐Hz (gamma) transcranial alternating current stimulation (tACS), in a single‐arm design. Primary outcomes assessed side‐effects and drop‐out as indicators of feasibility. Secondary outcomes included episodic memory, plasma‐based Aβ and tau. Exploratory measures included neurofilament light chain (NfL), glial fibrillary acidic protein (GFAP) and white matter fractional anisotropy. Additionally, neuroplastic changes were characterized by resting state functional connectivity (RSFC) within an episodic memory network and neuronal excitatory/inhibitory (Glx/GABA) balance via magnetic resonance spectroscopy.

Result

Results revealed that gamma tACS was feasible (minimal side effects and no drop‐outs due to tACS). Moreover, aMCI participants demonstrated improvement in multiple metrics of episodic memory, but no changes in Aβ, tau, NfL, or GFAP. Improvements in episodic memory were most pronounced in participants who had the highest modeled tACS‐induced electric fields and exhibited the greatest changes in RSFC – all within an episodic memory network. Increased RSFC was also associated with greater hippocampal excitability and higher baseline white matter integrity across numerous tracts.

Conclusion

This study highlights the potential of gamma tACS to improve episodic memory in an aMCI population by modulating functional connectivity and excitability within an episodic memory network.
Adaptive video games for the assessment and rehabilitation of dementia
Authors: Sander Florian , Manera Valeria , Krebs Christine R. , Touya Maylis , Fischer Elia Luca , Popa Traian , Guevara Andrea Brioschi Brioschi , Anguera Joaquin A , Gazzaley Adam , Klöppel Stefan , Allali Gilles , Demonet Jean‐François , Robert Philippe , Sokolov Arseny A
Published: December 2023

Background

Neurorehabilitation in dementia becomes an increasingly relevant topic and requires early detection of signs of domain‐specific cognitive decline. To this end, neuropsychological testing is usually performed in specialized centers, which can be difficult to reach for people living in rural regions for example. These centers also usually have long waiting‐lists, which can defer proper diagnosis for long periods of time. Today, increasing attention is devoted to developing rapid cognitive screening batteries that are easy to administer remotely, and have a game‐like interface to reduce test anxiety, capture attention and increase motivation. In terms of treatment, “serious videogames” share the same stimulating, motivating and adaptive qualities, and are surfacing and showing real promise as a viable treatment option (Sokolov et al., 2020).

Method

Regarding assessment: We conducted an observational multi‐centric study, evaluating the reliability of the mobile and adaptive serious videogame ACE‐X in detecting cognitive deficits in patients with subjective cognitive decline and mild neurocognitive disorders consulting specialized memory clinics in Bern and Lausanne in Switzerland, and Nice in France.

Regarding neurorehabilitation and serious games: We have tested a closed‐loop adaptive cognitive exergame in healthy older adults (Anguera et al., 2022), patients with stroke (NCT05169632) and multiple sclerosis (NCT03737825).

Results

Regarding assessment: The results indicate that ACE‐X can reveal deficits in working memory and multi‐tasking relevant for everyday life.

Regarding neurorehabilitation and serious games: The outcomes show sustained benefits in attention, working memory and everyday life. These findings pave the way for integrated, cognitive‐physical, closed‐loop adaptive training for the cognitive neurorehabilitation of people with dementia.

Conclusion

Detecting subclinical signs of cognitive decline in the aging population is crucial, as it allows to put in place early ‐ and thus more effective ‐ interventions. Closed‐loop adaptive assessment serious video games may be used to perform large‐scale screenings of elderly people at home, to identify those that may benefit from a referral to a medical practitioner. Subsequently, interventional serious video games may represent a promising tool for cognitive neurorehabilitation of cognitive decline due to neurodegeneration.
Fully Automated Lumipulse Plasma Amyloid and phosphorylated Tau assays for Progression to Alzheimer’s disease in Mild Cognitive Impairment patients
Authors: Silva‐Spínola Anuschka , Leitão Maria João , Santana Isabel , Nadal Alicia , Bastard Nathalie Le , Baldeiras Inês
Published: December 2023

Background

Lumipulse G automated immunoassays represent the most widely used method for the quantification of Alzheimer’s disease (AD) biomarkers in cerebrospinal fluid (CSF)1. Less invasive blood‐based markers confer a promising tool for AD diagnosis at prodromal stages (Mild Cognitive Impairment‐MCI)2. Highly sensitive assays for the quantification of amyloid‐beta (Aβ) and phosphorylated Tau‐181 (p‐Tau181) in blood are showing promising results3. In this study we evaluated the clinical performance of the available Lumipulse plasma markers for progression to AD.

Method

A group of 138 patients (22 neurological controls‐NC, 72 MCI and 44 AD) recruited at the Dementia Clinic of Centro Hospitalar Universitário de Coimbra (CHUC) was included. Data regarding baseline CSF levels of Ab42, Ab40, t‐Tau and p‐Tau181 was available, allowing for characterization into ATN categories4. Baseline Ab42, Ab40 and p‐Tau181 levels were determined in stored plasma samples using high‐throughput fully automated Lumipulse assays. Progression from MCI to AD dementia was assessed at follow‐up (mean 5.9±3.0 years; 36 converted ‐MCI‐AD/36 stable ‐MCI‐St).

Result

In the total cohort, correlations between CSF and plasma were moderate for p‐Tau 181 (r = 0.61, p<0.001), weak for Aβ42 (r = 0.28, p = 0.001) and non‐significant for Aβ40 (r = ‐0.05, p = 0.54). Plasma p‐Tau181 levels were significantly increased while Aβ42, Aβ42/Aβ40 and Aβ42/p‐Tau181 were significantly decreased (p<0.001) in patients classified as MCI‐AD and AD in relation both to NC and MCI‐St. Plasma p‐Tau181 showed a robust performance in differentiating NC+MCI‐St vs. MCI‐AD+AD (AUC = 0.89, 95%CI:0.83‐0.94), MCI‐St vs. MCI‐AD (AUC = 0.89, 95%CI:0.81‐0.96) and CSF A+ vs. A‐ (AUC = 0.84, 95%CI:0.77‐0.91). Plasma Aβ42/p‐Tau181 gave similar AUC results (AUCs = 0.88, 0.84 and 0.83) and showed no significant differences compared to p‐Tau181 alone (p = 0.34, 0.33 and 0.92). For MCI‐St vs. MCI‐AD, when maximizing for sensitivity (0.92, specificity 0.67), baseline plasma p‐Tau181 levels higher than 1.69 pg/mL predicted future AD dementia (HR = 11.5; 95%CI = 10.9‐12.1).

Conclusion

Our results show that the measurement of p‐Tau181 in peripheral blood has great potential as a non‐invasive prognostic screening tool for AD dementia in MCI patients.

1. Delaby C, et al. Alzheimer’s Dement. 2021; 2.Teunissen CE, et al. Lancet Neurol. 2022; 3.Palmqvist S, et al. Nat Med. 2021; 4.Jack CR, et al. Alzheimer’s Dement. 2018