bluuebunny/crossref_metadata_2025 huggingface dataset:
The brain‐immune ecosystem: Implications for immunotherapy in defeating neurodegenerative diseases
Authors: Schwartz Michal
Published: December 2023

Background

Since Medawar and Burnet’s studies some 70 years ago, it was widely accepted that the CNS cannot tolerate any immune activity under any circumstances. Over the past two decades, my team initiated a change in this dogma, by demonstrating that the brain requires support from innate and adaptive immune cells for its maintenance and repair. Deep understanding of these relationships by our team and by others has led us to propose that the immune cells that are hosted within the brain’s borders, together with neurons and non‐neuronal cells, form an ecosystem that enhances the resilience of the brain and its robustness in withstanding continuous and diverse perturbations. Accordingly, any dysfunction in this brain‐immune communication might impact brain activity.

Method

As aging is the major risk factor in dementia, including Alzheimer’s disease, we propose that dysfunction of any aspect of the brain‐immune ecosystem could affect disease onset and severity, but could be amenable to immune intervention. This model led us to propose that defeating such diseases could be accomplished by harnessing the immune system, which is either exhausted or insufficient

Result

We found that transiently blocking the inhibitory PD‐1/PD‐L1 immune checkpoint pathway, initiates an immune response in the periphery that leads to disease modification within the brain. This approach was found to be effective regardless of disease etiology, and is independent of microglial polymorphism. We found that the treatment improved cognitive performance and reduced multiple parameters that contribute to disease escalation, including neural loss, local inflammation, and phospho‐ and aggregated‐tau in tauopathy, and soluble oligomers of amyloid beta in amyloidosis. The effect was found to be dependent on bone marrow‐derived macrophages, and was also associated with homing of FoxP3 regulatory T cells. Brief intermittent treatment with an AD‐optimized antibody was found to provide long‐term effect.

Conclusion

Together, these studies show that targeting the immune system provides new avenues for understanding and treating neurodegenerative diseases.
CNS Immune Surveillance in Alzheimer’s Disease
Authors: Elyaman Wassim
Published: December 2023

Background

The etiology of Alzheimer’s disease (AD) is currently unknown, but several risk factors have been associated with AD including infectious agents. The central nervous system (CNS) is continuously monitored by immune cells, many of which circulate through the cerebrospinal fluid and the meninges. Meningeal immune cells respond to CNS‐intrinsic perturbations, such as neuroinflammation or neurodegeneration as well as to CNS‐extrinsic challenges, such as systemic infection. The goal of the study is to analyze the profile of meningeal immune cells and T cell clonality in AD in comparison with other neurodegenerative diseases.

Method

We used single‐cell RNA and T‐cell receptor (TCR) sequencing to characterize CD45+ immune cells from fresh leptomeninges from AD, Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS).

Result

We identified multiple myeloid and lymphoid clusters in all neurodegenerative samples including meningeal macrophages expressing CD14 and C1QA and the resident meningeal macrophage marker LYVE‐1. Lymphoid populations represented the majority of total cells and were composed of both CD8+ effector memory T‐cells and a mixed population of NK cells and NK‐like T‐cells. Ligand/receptor network analyses identified several significant intercellular interactions including osteopontin signaling between meningeal macrophages and both clonally expanded cytotoxic CD8 T and NK/NK‐like T‐cells. TCR sequence analysis revealed up to 500 unique TCR clonotypes in each sample, many of which were hyperexpanded with 25‐50% of the TCR repertoire being occupied by the top 20 clonotypes and some of which had high TCRa chain sequence homology to EBV‐specific TCRs.

Conclusion

We provide evidence for disrupted myeloid homeostasis and broad T‐cell clonal expansion in the leptomeninges of AD patients. Network analyses suggest that meningeal macrophages in neurodegeneration may promote long‐term clonally expanded T‐cell survival through osteopontin signaling. These data recapitulate findings across several animal studies and will be useful in developing immunomodulatory interventions to treat neurodegeneration.
Self‐harm in people with dementia – assessing risk factors, health profiles and healthcare pathways using big data
Authors: Reppermund Simone , Walker Adrian , Cvejic Rachael , Srasuebkul Preeyaporn , Wand Anne , Draper Brian , Trollor Julian N
Published: December 2023

Background

Dementia is often associated with poorer mental health and higher rates of self‐harm compared to older people without dementia. This study investigated risk factors for self‐harm in dementia and risk factors for developing dementia following self‐harm. A further aim was to elucidate the health profiles and healthcare pathways of individuals with dementia who self‐harm as a critical step to develop effective prevention strategies.

Method

Using linked health data from hospital admissions, emergency department presentations and ambulatory mental health visits, we established a population‐based cohort of individuals with dementia and self‐harm in New South Wales, Australia spanning 13 years. The project was guided by an advocate advisory group, including people with dementia and care‐partners who inform all stages of the project.

Result

The cohort included 154,811 people with dementia, of which 652 (0.4%) had a subsequent diagnosis of self‐harm. People with dementia who self‐harmed were younger at the time of their dementia diagnosis (median age 69.6 (IQR 52.7‐80.1) versus 83.5 (IQR 78.0‐88.1)) and had a lower proportion of females (39.4% versus 59.6%) compared to people with dementia without self‐harm. A diagnosis of self‐harm most often occured within 24 months after a dementia diagnosis. Men living with dementia, and people with complex psychiatric profiles had the greatest risk of self‐harm. People with dementia and self‐harm had more comorbidities compared to those without self‐harm. The most frequent comorbidities in people with dementia and self‐harm were drug/alcohol use (19.9%), depression (13.5%), anxiety (11.8%), and psychotic disorder (10.9%); these comorbidities were observed in 2.7%, 2.7%, 2.2% and 2.1% of people with dementia without self‐harm, respectively. People with dementia and self‐harm had more ambulatory mental health visits, ED presentations and involuntary admissions in the year before a dementia diagnosis compared to those without self‐harm.

Conclusion

The health profiles and healthcare pathways are significantly different for people with dementia who self‐harm versus those who do not. Poor mental health, dementia, and self‐harm are substantially intertwined in older adults. Post‐diagnostic counselling and support should be provided following a dementia diagnosis. This project will inform strategies for health services to better meet the needs of people with dementia who self‐harm.
TauFlowNet: Uncovering Spreading Pathways of Tau Aggregates by Neural Transport Equation
Authors: Wu Guorong , Dan Tingting
Published: December 2023

Background

Alzheimer’s disease (AD) is characterized by the propagation of tau aggregates throughout the brain in a prion‐like manner. Since current pathology imaging technologies only provide a spatial mapping of tau accumulation, computational modeling becomes indispensable in analyzing the spatial‐temporal propagation patterns of widespread tau aggregates.

Method

Current state‐of‐the‐art works focus on the change of focal patterns, lacking a system‐level understanding of the tau propagation mechanism that can explain and forecast the cascade of tau accumulation. To address this limitation, we conceptualize that the inter‐cellular spreading of tau pathology forms a dynamic system where each node (brain region) is ubiquitously wired with other nodes while interacting with the build‐up of pathological burdens. In this context, we formulate the biological process of tau spreading in a principled potential energy transport model (constrained by brain network topology), which allows us to develop an explainable neural network for uncovering the spatial‐temporal dynamics of tau propagation from the longitudinal tau‐PET scans. Specifically, we first translate the transport equation into a backbone of graph neural network (GNN), where the spreading flows are essentially driven by the potential energy of tau accumulation at each node.

Result

First, our physics‐informed deep model yields more accurate prediction of future tau aggregates. Second, we generate the population‐wise brain mapping of tau spreading through the brain. Sub‐cortex to cortex flows are the predominant patterns in the early stage of AD while the spreading patterns turn to cortex‐to‐cortex propagation as the disease progresses.

Conclusion

Our physics‐informed deep model outperforms existing state‐of‐the‐art methods in terms of prediction accuracy and model explainability. Since the region‐to‐region spreading flow provides rich information for understanding the tau propagation mechanism, our learning‐based method has great applicability in current AD studies.
Regulation of insulin entry into the brain
Authors: Rhea Elizabeth
Published: December 2023

Background

Central nervous system (CNS) insulin has repeatedly been shown to play a role in cognition. Little, if any, insulin is synthesized in the brain and therefore requires navigation of the blood‐brain barrier (BBB) to act. The BBB is a unique structure in the brain that regulates the entry of serum substrates and can act as both a barrier and signaling structure. We hypothesize the BBB is a critical structure involved in the regulation of CNS insulin signaling and CNS insulin availability. We have investigated the regulation of insulin BBB transport and interactions under various conditions including exercise, brain insulin resistance, and have begun to explore the mechanisms for insulin transport across the BBB.

Method

For exercise, male and female mice were habituated to locked voluntary running wheels. After habituation, wheels were unlocked in some cages (exercise) for 24 hours while remaining locked (sedentary) in the others. For brain insulin resistance, mice were treated with an intracerebroventricular delivery of the insulin receptor antagonist, S961. For mechanisms involved in insulin BBB transport and interactions, endocytosis inhibitors were used to differentiate between clathrin and caveolin endocytosis. Following manipulation, insulin BBB pharmacokinetics were assessed with the quantitative multiple‐time regression analysis using radioactively labeled insulin and albumin, a marker for vascular space. Mice were injected intravenously or perfused in situ with the radiolabeled substrates and at timepoints up to 10 min, blood and brains collected and radioactivity measured. 125I‐insulin entry and binding to the BBB was assessed.

Result

Exercise enhanced 125I‐insulin interactions at the BBB. Specifically, exercise increased insulin BBB transport by two‐fold in males and increased insulin binding at the BBB in females. Brain insulin resistance impaired 125I‐insulin transport across the BBB, particularly in females. Lastly, caveolin‐mediated endocytosis may be involved in hypothalamic 125I‐insulin BBB transport.

Conclusion

We have shown insulin BBB transport is highly regulated and can be impacted by exercise, brain insulin resistance, and may involve various endocytic pathways in a regional‐dependent manner. Continued investigation on the pathways involved in insulin BBB transport is warranted to aid in treating or preventing brain insulin resistance as occurs in Alzheimer’s disease.
Imaging the brain to assess brain insulin action
Authors: Kullmann Stephanie
Published: December 2023

Background

Ever since the brain was identified as an insulin‐sensitive organ, it was quickly appreciated that insulin action in the brain affects cognitive and metabolic processes [1]. Epidemiological evidence suggests a strong link between reduced peripheral insulin sensitivity and age‐related neurodegenerative processes, including Alzheimer’s disease (AD) [2].

Method

Characterization of brain insulin resistance in humans is challenging and relies on different neuroimaging methods in combination with insulin stimulation techniques. In my talk, I will focus on the administration of intranasal insulin, which has been established over the last decades to disentangle peripheral from brain insulin effects [1]. In combination with functional neuroimaging, I will show recent data on the quantification of brain insulin sensitivity non‐invasively in humans of different age and weight groups [3].

Result

We could show that intranasal insulin can affect region‐specific activity and functional connectivity of the human brain. These diverse central insulin responses largely depend on its action in the hypothalamus, amygdala, hippocampus, striatum and parts of the insula and prefrontal cortex and influences a variety of metabolic and cognitive processes [3]. Specifically, I will show that disrupted brain insulin action can result in increased accumulation of visceral fat and altered reward learning in persons at high risk to develop T2D [4], but also in healthy individuals after overconsumption of high caloric foods (unpublished). Moreover, I will show that the effect of intranasal insulin in the hippocampus decreases with age in women but not men and that brain insulin responsivity is affected by the menstrual cycle (unpublished). Moreover, just recently, we could link enhanced brain insulin action in the mesocorticolimbic circuitry with improved cognitive and metabolic functions [5].

Conclusion

As brain insulin acts on striatal dopamine function and hippocampal plasticity, enhancing brain insulin action could lead to new treatment options in diabetes and aging‐associated diseases.

References

1. Hallschmid, M. J Neuroendocrinol, 2021. 33(4): p. e12934.

2. Frazier, H.N., et al. Exp Neurol, 2019. 313: p. 79‐87.

3. Kullmann, S., et al. Lancet Diabetes Endocrinol, 2020. 8(6): p. 524‐534.

4. Kullmann, S., et al. Nat Commun, 2020. 11(1): p. 1841.

5. Kullmann, S., et al. JCI Insight, 2022. 7(18).
Development of NLRP3 PET Radiotracers for Alzheimer’s disease
Authors: Xu Yiming , Xu Yulong , Biby Savannah , Wang Changning , Zhang Shijun ,   Medicinal Chemistry, VCU
Published: December 2023

Background

Novel PET tracers were designed and tested to target the NLRP3 inflammasome in the brain to develop biomarkers for neuroinflammation in AD.

Method

A novel chemical scaffold was rationally designed based on our previously developed NLRP3 inhibitors. One of the compounds, YM8, was radiolabeled with C‐11, and radiotracer was characterized in mouse models and non‐human primates (NHPs).

Result

The studies in wild type and nlrp3‐/‐ mouse brain tissues demonstrated that [11C]YM8 is a NLRP3 specific PET tracer with Bmax/Kd > 10, hinting to be a suitable CNS PET tracer. Studies in mice revealed rapid and high brain uptake of [11C]YM8. PET/MR studies of [11C]YM8 in NHPs demonstrated excellent brain uptake and radiometabolism stability as well as fast washout from blood.

Conclusion

A novel C‐11 labeled NRP3 PET radiotracer was developed and demonstrated to serve as a suitable CNS PET tracer to monitor inflammatory responses in the brain.
Nutrition in Alzheimer’s Disease: A Review of an Underappreciated Pathophysiological Mechanism
Authors: Jiang Jiwei , Shi Hanping , Li Wenyi , Xu Jun
Published: December 2023

Background

Pharmacy therapy of Alzheimer’s disease (AD) is one of the areas that are well funded, but where little progress has been made due to the complex pathogenesis. The gut‐microbiota‐brain axis has gained tremendous traction in the pathogenesis of AD through bidirectional communication with multiple neural, immune, and metabolic pathways, providing new insights into novel therapeutic strategies. Dietary nutrition is an important and profound environmental factor that influences the composition and function of the microbiota. The Nutrition for Dementia Prevention Working group recently found that dietary nutrition can affect the cognition of AD‐related dementia directly or indirectly through complex interactions of behavioral, genetic, systemic, and brain factors. This review aimed to emphasize the knowledge gaps to provide direction for future research and to establish optimal nutrition‐based intervention strategies for AD.

Method

This review discusses the associated evidence between malnutrition and the onset and development of AD for modifying the potentially reversible nutrition‐related risk factors of AD, describe the potential pathogenesis underlying the role of nutrition in the progression of AD and emphasize the current knowledge gaps for further research.

Result

The role and effects that nutrition and diet have on AD are more pervasive than previously believed. We identified and highlighted a novel vicious cycle comprising malnutrition, development of AD, and heavy caregiver burden (Figure 1). As pharmacological approaches demonstrate limited benefits for improving the symptoms of AD, early nutritional intervention for preventing or delaying the progression of AD are worth attempting. The mechanisms underlying the effect of nutrition on the development of AD remain uncertain, including genetics and epigenetics, AD‐specific biomarkers, metabolic pathways, the gut‐microbiota‐inflammation‐brain axis, and their complex interactions (Figure 2).

Conclusion

These potential nutrition‐related pathogenic pathways can be exploited as an important environmental factor and could be the focus of targeted AD interventions. Future research is needed to fill in the discussed gaps in knowledge, including prospective studies to identify nutritional biomarkers that can predict AD, multi‐omics studies to elucidate the exact mechanisms by which nutrition influences AD, and clinical trials to identify the best nutritional intervention strategies to prevent and improve cognitive and behavioral disturbances in the AD population.
Connected speech efficiency and lexical diversity are associated with PET amyloid and tau in a cognitively unimpaired sample
Authors: Hale Madeline R , Van Hulle Carol A. , Langhough Rebecca E , Basche Kristin E , Chin Nathaniel A. , Christian Bradley T. , Betthauser Tobey J , Hermann Bruce P , Johnson Sterling C. , Mueller Kimberly D
Published: December 2023

Background

Changes in connected speech (CS; language used in everyday conversations) have been documented throughout the Alzheimer’s disease (AD) spectrum, including the very early stages of disease. Our group identified four factors comprised of 10 measures of CS: fluency, semantic content, lexical diversity, and grammatical complexity. We demonstrated that fluency and semantic content were associated with subclinical cognitive decline (Mueller et al., 2018a). However, the relationship between these connected speech factors and AD biomarkers in preclinical AD is unknown.

Method

Cognitively unimpaired (CU) Wisconsin Registry for Alzheimer’s Prevention participants with positron emission tomography (PET) amyloid (A) and tau (T) were identified; 26 were A+/T+; an equal number matched 1:1 using nearest neighbor propensity score matching for age, sex, literacy, and race were selected from A‐/T‐ and A+/T‐ subsets (n = 78). A priori power calculation based on similar matched designs revealed >80% power to detect a medium effect size. We analyzed CS samples from a picture description task (Cookie Theft) at the neuropsychological visit closest to the most recent PET scans (median visit number = 6). Language measures were extracted from transcripts and transformed into standardized z‐scores that were used to create the factors (details in Mueller et al. (2018b)). ANOVA models investigated whether factor scores and two exploratory individual measures of CS efficiency (content information units per minute (CIU/Min) and semantic unit idea density (SUID)) differed across PET biomarker profiles (A‐/T‐ = reference group). Post‐hoc pairwise comparisons were then completed, and Cohen’s d characterized effect sizes.

Result

The mean(sd) years between CS sample and PET scan was 2.3(1.8) for amyloid and 2.1(1.7) for tau (Table 1). The lexical factor was associated with PET biomarker status, such that participants who were A+/T+ had lower lexical diversity than the A‐/T‐ group. Lower SUID was associated with both A+/T‐ and A+/T+ classification (Figure 1). Associations did not change when analyses were repeated without outliers. Effect sizes were highest for SUID (Table 2).

Conclusion

Of four previously derived language factors, lexical diversity was associated with PET biomarker status. However, a measure of connected speech efficiency (SUID) was also associated with biomarker status in this preclinical, CU sample. Replication in additional cohorts is needed.
APOE‐dependent and ‐independent polygenic pathways determining early Alzheimer’s Disease pathological changes in CSF and MRI
Authors: Lorenzini Luigi , Collij Lyduine E. , Tesi Niccoló , Ingala Silvia , Sudre Carole H , Wolz Robin , Haller Sven , Blennow Kaj , Frisoni Giovanni B , Payoux Pierre , Martinez‐Lage Pablo , Ewers Michael , Chetelat Gael , Ritchie Craig W , Gispert Juan Domingo , Mutsaerts Henk‐Jan , Altmann Andre , Tijms Betty M. , Wink Alle Meije , Visser Pieter Jelle , Barkhof Frederik
Published: December 2023

Background

Little is known about the genetic factors and downstream molecular pathways determining individual variability in fluid and imaging biomarkers associated with Alzheimer’s disease(AD). We studied polygenic risk scores (PRS) and pathway‐specific PRS in relationship with AD fluid and imaging biomarkers, in non‐demented individuals from the European Prevention of Alzheimer’s Dementia (EPAD) cohort.

Method

EPAD inclusion criteria were age>50 and Clinical Dementia Rating≤0.5 (n = 1886, Table 1). AD‐PRS was based on 85 previously identified loci, including and excluding APOE (PRSAPOE, PRSnoAPOE)[1]. Using gene‐variant and variant‐pathway mapping[2], six pathway‐specific PRSnoAPOE were identified:1) immune‐activation, 2) signal‐transduction, 3) inflammatory‐response, 4) migration, 5) amyloid‐production, and 6) clearance. Linear models were used to assess the relationship of all PRS with fluid AD biomarkers, including Aβ1‐42, p‐Tau181, and t‐tau; and several imaging biomarkers, including hippocampal volume, global and lobar white matter hyperintensities (WMH) volumes, fractional anisotropy (FA) in 14 regions of interest from diffusion tensor imaging, and 10 resting‐state network connectivity from functional MRI. Models were adjusted for age, sex, site, and multiple comparisons.

Result

Models’ coefficients are reported in Table 2. PRSAPOE was significantly associated with decreased Aβ1‐42, and increased p‐Tau181 and t‐Tau. PRSnoAPOE showed a weaker, but still significant, negative association with Aβ1‐42 levels, and a significant positive association with p‐Tau181 and t‐Tau. Aβ1‐42 was only significantly associated with the migration, amyloid, and clearance pathways, while all pathways were significantly positively associated with p‐Tau181 and t‐Tau.

Hippocampal volume was only significantly associated with PRSAPOE. Regarding WMH load, PRSAPOE showed a positive association with global, frontal periventricular, and parietal deep lobes. Furthermore, the clearance pathway was related to WMH load in all regions, most strongly in periventricular areas.

Only the migration pathway was related to increases in FA in the splenium, body, and genu of the corpus callosum. Only the PRSAPOE was related to reduced functional connectivity (FC) in the default mode, control, and visual networks.

Conclusion

We show that genetic risk beyond APOE facilitates the manifestation of AD related pathologies. Moreover, clearance and migration pathways were associated with neuroimaging measures of white matter integrity, while FC and hippocampal volume were associated with overall AD genetic risk.
Pathogenic α‐synuclein triggers focal tau pathology, developing to various brain areas in Parkinson disease
Authors: Hadi Fatemeh , Shahpasand Koorosh , Akrami Hassan , Totonchi Mehdi , Barzegar Abdolrazagh , Nabavi Seyed Massood
Published: December 2023

Background

Parkinson disease (PD) is the second most common neurodegenerative disorder, whose prevalence is 2∼3% in the population over 65. Recent studies have reported enhancing confirmation of tau pathology in PD, however, α‐synuclein accumulation is the significant pathological hallmark of PD. Despite extensive considerations, thus far, the actual spreading mechanism of neurodegeneration has remained elusive in a PD brain. This study aimed to further clarification the development of α‐synuclein and tau pathologies.

Method

We employed several PD models, containing cultured neurons treated with either 1‐methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP) or with recombinant α‐synuclein. Furthermore, we examined dopaminergic neurons of cytokine Interferon‐β knock‐out. Moreover, we tested rats administrated with 6‐hydroxydopamine, Rhesus monkeys injected with MPTP neurotoxin, and then human post‐mortem brains.

Result

We observed the α‐synuclein phosphorylation triggers tau pathogenicity. Moreover, we found more widespread phosphorylated tau than α‐synuclein with prion‐like nature in various brain areas. We optionally omitted P‐tau or P‐α‐synuclein from cytokine interferon‐β knock out with respective monoclonal antibodies. We observed that tau immunotherapy prevented neurodegeneration more than α‐synuclein exclusion.

Conclusion

Our observations show that the pathogenic tau could be one of the prominent causes of extensive neurodegeneration triggered by PD. Consequently, we could recommend an impressive therapeutic aims to fight the devastating disorder.
Predicting cognitive stage transition using plasma p‐tau181, the Centiloid scale, and other measures
Authors: Kwon Hyuk Sung , Park Hyun‐Hee , Lee Eun‐Hye , Hwang Min A , Baek Jeongmin , Lee Eunji , Ryu Yejin , Lee Sunju , Lee Yongkyung , Yoo Hyun‐Jung , Koh Seong‐Ho
Published: December 2023

Background

A combination of plasma phospho‐tau (p‐tau), amyloid beta (Aβ)‐PET, brain magnetic resonance imaging, cognitive function tests, and other biomarkers might predict future cognitive decline. This study aimed to investigate the efficacy of combining these biomarkers in predicting future cognitive stage transitions within 3 years.

Method

All participants were from the validation cohort of the Korean Brain Aging Study for the Early Diagnosis and Prediction of Alzheimer’s Disease (KBASE‐V) study. Among the participants in the KBASE‐V study, 49 mild cognitive impairment (MCI) and 113 cognitively unimpaired (CU) participants with Aβ‐PET and brain imaging data were analyzed. Main outcome was cognitive stage transitions within 3 years. The best combination model that predicts cognitive stage transition was considered by significant change of area under the curve (AUC) and Akaike information criterion value.

Result

Within 3 years, 19.1% of the participants showed a cognitive stage transition. Older age, increased plasma p‐tau, Aβ‐PET positivity, and decreased semantic fluency were independently associated with cognitive stage transitions. Plasma p‐tau181 (AUC = 0.673) and the Centiloid scale (AUC = 0.769) alone predicted cognitive stage transition well and correlated with each other significantly. Combining age, p‐tau181, the Centiloid scale, semantic fluency, and hippocampal volume produced better accuracy (AUC = 0.879). In MCI participants, the model combining age, p‐tau181, and the Centiloid scale demonstrated the highest predictive value (AUC = 0.963).

Conclusion

Plasma p‐tau181 and Centiloid scale, in combination with other biomarkers, might have high predictive value in predicting future cognitive stage transition in non‐dementia patients.
A retrospective cohort study of robotic‐assisted laparoscopic radical prostatectomy (RARP) to PONV scale effects on Alzheimer’s Disease‐Related Dementia patients’ sleep and vitality risks
Authors: Wu Jia‐Ping
Published: December 2023

Background

Prostate cancer is the most commonly safe with minimal morbidity and mortality rates of tumor cancer using microsurgical techniques. However, these rates have risen rapidly in the past two decades. This study aimed to determine comparing microsurgical prostatectomy techniques in National Comprehensive Cancer Network (NCCN) high‐risk and low‐risk robot‐assisted laparoscopic radical prostatectomy (RARP) and conventional laparoscopic radical prostatectomy (LRP) approach.

Methods

Retrospective case observation study of single team laparoscopic and robotic‐assisted laparoscopic radical prostatectomy for NCCN (n = 855,893) high‐risk and low‐risk prostate cancer from 2009 to 2020. 307 Alzheimer’s Disease and Alzheimer’s Disease‐related Dementias patients were divided into two groups, 120 patients low‐risk and 187 patients high‐risk, undergoing radical prostatectomy for prostate cancer using LRP and RARP. To determine univariate and adjusted odds and hazard ratios for BCR, post‐operative detective, and post‐salvage therapy disease between low‐risk and high‐risk groups in undetectable PSA patients.

Results

307 patients in the detectable NCCN group 120 patients for very high‐risk and 187 patients in high‐risk groups. Very high‐risk groups have significant differences compared with high‐risk groups by PSA density (p<0.001), BCR in undetectable PSA (p<0.001), PSA rate (p<0.004), and salvage therapy (p<0.001). Univariate hazard ratios for BCR and univariate odds ratios for post‐operative detective PSA, post‐salvage therapy disease, and time to BCR in very high‐risk groups have significant differences (p<0.001) compared with high risk.

Conclusions

RARP has better effects than conventional LRP available regarding lower incidence and risk factors. Very high‐risk prostate cancer is not good for radical prostatectomy and selected high‐risk group.
Bias in Acoustic‐ and Linguistic‐based Classifications of Alzheimer’s Disease
Authors: Parsapoor Mahboobeh , Dalmas Benjamin
Published: December 2023

Background

It is crucial to identify patients with Alzheimer’s disease (AD). To do so, various attempts have been made to develop AI and non‐AI assessments, among which some focus on developing acoustic‐ and linguistic‐based classifiers. They are based on the detection of impairments in their language and speech, which can manifest years before other cognitive impairments associated with AD appear. The fact is that most of the current vocal and language classifiers of AD have been trained using the Pitt corpus, which is an imbalanced class and gender dataset. These two characteristics could be enough to bias such classifiers making them untrustworthy and unsuitable for integration into AD care settings. This paper presents a novel method for collecting vocal data to reduce the impact of potential sources of bias on acoustic and linguistic classifiers for AD.

Method

We will use a data collection approach that collects voices from participants (i.e., patients with AD and healthy controls) with diversity in race, gender, educational, socioeconomic, and cultural backgrounds. Participants will be asked to perform diverse language tasks, including word association, verbal fluency, and grammaticality judgment tasks. Following such an approach can ensure we collect oral data that wouldn’t be affected by selection, recruitment, sociolinguistics, and gender biases.

Results

The main result of this study is the creation of a benchmark vocal dataset from diverse gender and racial groups and ensuring that the data is representative of the population with AD. We expect such data to be used for evaluating and validating and help AI developers to successfully develop fair acoustic and linguistic classifiers of AD. It, in its turn, can motivate healthcare professionals to employ these systems as assistants to identify patients with AD from their voices quickly.

Conclusion

The Pitt corpus is a biased data set. Thus, acoustic and linguistic classifiers trained upon it can not be considered trustworthy AI systems. The AI developers that aim to deploy vocal systems into Alzheimer’s disease care settings would need unbiased vocal data. This study proposed a method to collect such verbal data.
Plasma amyloid‐β, total tau, and neurofilament light chain across the Alzheimer clinical spectrum: a population‐based study
Authors: Dong Yi , Hou Tingting , Liu Rui , Li Yuanjing , Cong Lin , Tang Shi , Wang Yongxiang , Du Yifeng , Qiu Chengxuan
Published: December 2023

Background

Plasma biomarkers have emerged as a promising approach for defining mild cognitive impairment (MCI) and Alzheimer’s disease (AD). We aimed to characterize Alzheimer’s plasma biomarkers across the clinical continuum of AD, and to assess their ability to differentiate between MCI, AD, and normal cognition.

Method

This population‐based study engaged 1446 rural‐dwelling older adults (age≥60 years, 61.0% women) derived from Multimodal Interventions to Delay Dementia and Disability in Rural China study; of these, 902 were defined with normal cognition, 402 with MCI, and 142 with AD according to the international criteria. Plasma amyloid‐beta (Aβ), total‐tau (t‐tau), and neurofilament light chain (NfL) concentrations were analysed using Simoa platform. Data were analysed using the logistic and general linear models, and receiver operating characteristic (ROC) analysis.

Result

Plasma concentrations of Aβ40, Aβ42, t‐tau, and NfL were significantly increased with age (P<0.01). Women had higher plasma Aβ2 (age‐adjusted β = 0.62; 95%CI = 0.30‐0.94), Aβ42/Aβ40 ratio (0.19; 0.01‐0.36) and lower NfL concentrations (‐0.11; ‐0.16‐ ‐0.06). Plasma Aβ42 (age‐ and sex‐adjusted β = ‐0.73; ‐1.15‐ ‐0.31) and Aβ42/Aβ40 ratio (‐0.51; ‐0.74‐ ‐0.29) were lower in APOE ε4 carriers than that in non‐carriers. Plasma Aβ40 and Aβ42/Aβ40 ratio showed an increased and decreased trend, respectively, across AD clinical spectrum. Plasma t‐tau and t‐tau/Aβ42 ratio were higher in people with AD than those with MCI or normal cognition. Plasma NfL was increased across the AD clinical continuum and outperformed other Alzheimer’s biomarkers in differentiating AD from normal cognition (area under the ROC curve [AUC] = 0.75). However, all of these plasma biomarkers performed poorly to distinguish MCI from normal cognition (AUC<0.60). When adding plasma NfL to the basic model that included age, sex, education, and APOE genotype, the AUC was 0.87 for differentiating between AD and normal cognition, 0.79 between AD and MCI, and 0.64 between MCI and normal cognition.

Conclusion

Age, sex, and APOE genotype should be considered in clinical interpretation of Alzheimer’s plasma biomarkers. Plasma Aβ, t‐tau, and NfL concentrations differ across the cognitive continuum, but plasma NfL, which starts to elevate in the early stages of AD development, appears to be superior than plasma Aβ and t‐tau for defining cognitive continuum in old age.
Assessing motor cortex excitability and its relationship with brain atrophy in Ahlzeimer’s disease
Authors: Lawson Renee P , Zomorrodi Reza , Joseph Michael , Alhabbal Hiba , Asare Gifty , Blumberger Daniel M. , Daskalakis Zafiris J. , Fischer Corinne E. , Mulsant Benoit H. , Pollock Bruce G. , Rajji Tarek K. , Voineskos Aristotle N. , Kumar Sanjeev
Published: December 2023

Background

Cortical excitability detected using resting electroencephalography (EEG) or transcranial magnetic stimulation (TMS) combined with EEG has been proposed as a new neurophysiological marker of Alzheimer’s dementia (AD). However, the link between cortical excitability and structural changes in AD is not well understood. The objective of this study was to assess the relationship between cortical excitability and brain structure (cortical thickness) in the motor cortex of patients with AD and healthy older individuals.

Methods

63 participants (38 females) with AD (Mage = 74.5, SD = 8.0) and 48 healthy individuals (27 females) (Mage = 71.1, SD = 7.8) were included. hot spot’ over the left motor cortex was defined as the location that generated maximal motor‐evoked potentials in the abductor pollicis brevis muscle. Each participant’s resting motor threshold (rMT) was determined using the ‘hotspot’ by finding the lowest stimulus strength to evoke a motor‐evoked potential with a peak‐to‐peak amplitude of ≥50 µV in at least five of ten consecutive single pulse TMS trials. T1w MRI scans were pre‐processed using the anatomical pipeline in fMRIPrep v20.2.6. This pipeline includes recon‐all from Freesurfer v6.0.1, which estimates cortical thickness based on ROIs defined in the Desikan‐Killiany atlas.

Results

Participants with AD had lower motor cortex thickness than healthy individuals (t(93) = ‐4.398, p = <0.001). Participants with AD had lower rMT (indicative of higher excitability) than healthy individuals (t(109) = ‐2.265, p = 0.026). Within the total sample, rMT was correlated with motor cortex thickness (r = 0.216, df = 95, p = 0.036).

Conclusions

Consistent with previous literature, our study supports that AD is associated with decreased cortical thickness and higher motor cortex excitability. We also found that changes in cortical thickness positively correlated with rMT, suggesting that cortical hyperexcitability is influenced by cortical neurodegeneration. Future studies may wish to examine the association between cortical excitability and functional imaging measures to understand specific mechanisms.
Transformer Neural Networks, Information Biology, and Alzheimer’s Disease
Authors: Swan Melanie
Published: December 2023

Background

Alzheimer’s disease affects one in ten people older than 65 years, with the prevalence expected to triple by 2030, together with commensurate increases in cost. A comprehensive causal model of Alzheimer’s disease etiology is lacking despite more than three decades of study. Modern computational methods provide a new approach to multiscalar biosystems by modeling neuropathology in its native three‐dimensional character in topological biophysics and quantum computational models.

Method

This work describes how an emerging standard in machine learning, responsible for the AlphaFold (protein folding structure) and Gato generalist agent projects, transformer neural networks, may be applied to the study of Alzheimer’s disease per proven results in bot text chat, image recognition and creation, video generation, software programming, and autonomy in robotics and driving. The self‐attention and self‐learning mechanisms of transformer neural networks are discussed in application to multifaceted Alzheimer’s disease data sets involving neuroimaging scans, whole human genome data, and blood and CSF biomarker data.

Result

A machine learning‐based topological biophysics model of Alzheimer’s disease neuropathology hypothesis‐testing (misfolded proteins, gene expression, diabetes type‐3, and peptide immune system stimulation) is described.

Conclusion

There is an opportunity to apply state‐of‐the‐art transformer neural network machine learning techniques to the automated analysis of large accruing data stores of Alzheimer’s information (imaging, genomic, proteomic, and self‐reported data) towards the causal understanding of the neuropathology.
Efficacy of Sailuotong in vascular dementia: an exploratory analysis of possible disease modifying activity
Authors: Chen Christopher , Rahman Nabilah
Published: December 2023

Background

Multi‐component, multi‐target approaches may be needed for treatment of Vascular Dementia (VaD). SaiLuoTong (SLT) consists of active ingredients derived from Ginkgo Biloba, Panax Ginseng and Crocus Sativus. A phase II, randomized, controlled, double‐blind study (NCT01978730) demonstrated the symptomatic efficacy of SLT in VaD, however, the slowing of disease progression remains unexplored. This exploratory analysis is to compare the Vascular Dementia Assessment Scale‐cognitive subscale (VaDAS‐cog) between early‐ and delayed‐starters over a 52‐week period so as to assess the disease‐modification effect of SLT.

Method

Subjects with probable mild to moderate VaD were randomized to SLT 360 or 240 mg (early‐starters), or placebo (delayed‐starters). Whilst maintaining blinding, all early‐starters received SLT for 52 weeks and delayed‐starters switched to SLT 360 or 240 mg from placebo at week‐26. Using a modified intention‐to‐treat population of 325 subjects, comparison of change in VaDAS‐cog from baseline between early‐starters and delayed‐starters was performed using linear mixed‐effects models for repeated measurements, with fixed effect of intervention (early‐starters vs. delayed‐starters), time, time and intervention interaction, baseline VaDAS‐cog and randomization stratification factors. An unstructured variance‐covariance structure was employed.

Result

Early‐starters compared to delayed‐starters showed statistically significant improvement in adjusted mean change from baseline in VaDAS‐cog score at all timepoints: (Adjusted mean difference (AMD) [95% CI]: ‐1.53 [‐2.35, ‐0.71]; P<0.001) at week‐13, (AMD [95% CI]: ‐2.69 [‐3.69, ‐1.69]; P<0.001) at week‐26, (AMD [95% CI]: ‐2.15 [‐3.31, ‐0.98]; P<0.001) at week‐39 and (AMD [95% CI]: ‐1.94 [‐3.38, ‐0.51]; P = 0.008) at week‐52. The largest difference (early‐starters vs delayed‐starters) was observed at week‐26.

Conclusion

In this analysis, the effect of SLT was observed at week‐13 in early‐starters and sustained until week‐52. Delayed‐starters did not catch up with early‐starters on mean change in VaDAS‐cog from baseline at week‐52, suggesting not only a symptomatic effect of SLT but also a possible disease‐modifying effect.

References: Jia J, Wei C, Chen S, et al. Efficacy and safety of the compound Chinese medicine SaiLuoTong in vascular dementia: A randomized clinical trial. Alzheimers Dement (N Y). 2018;4:108‐117. Published 2018 Mar 22. https://doi.org/10.1016/j.trci.2018.02.004
Age‐related relative comorbidity burden of mild cognitive impairment: A US database study
Authors: Li Gang , Toschi Nicola , Batrla Richard , Boccato Tommaso , Cho Min , Ferrante Matteo , Frech Feride H , Galvin James E , Henley David , Mattke Soeren , DeSanti Susan , Hampel Harald
Published: December 2023

Background

As novel therapies emerge, timely detection and diagnosis of early Alzheimer’s disease (AD) become increasingly relevant. While primary care would be the most suitable setting for early detection, diagnosis rates of mild cognitive impairment (MCI) are low and systematic screening of asymptomatic individuals is currently not recommended. We investigated whether a predictive algorithm based on established AD risk factors can help to identify individuals at elevated risk of having undiagnosed MCI, in particular in younger age cohorts.

Method

Our retrospective study used MarketScan insurance claims data to identify individuals aged ≥50 years with MCI (but without dementia) and assemble controls without MCI/dementia diagnoses matched on age, sex, and geographic region. Medical conditions previously identified as AD risk factors in the literature were considered MCI risk factors if their prevalence in MCI individuals was statistically significantly higher than in controls. Logistic regression and extreme gradient boosting (XGBoost; a machine learning method) were applied to discriminate MCI from control individuals based on area under the curve (AUC). Analyses were conducted for the overall cohort and by age group (50‐64, 65‐79, and ≥80 years).

Result

Twenty‐five medical conditions had statistically higher frequency in the MCI cohort (n = 5,185) compared to controls (n = 15,555). The top MCI risk factors (with odds ratio for the 50‐64, 65‐79, and ≥80 years subgroups, respectively) were: depression (4.4, 3.1, 1.9); stroke/transient ischemic attack, TIA (6.4, 3.0, 2.1); obstructive sleep apnea, OSA (3.6, 2.5, 1.7); hyperlipidemia (1.7, 1.5, 1.4); and hypertension (1.6, 1.5, 1.5) (all p‐values <0.0001). The logistic regression models for identifying MCI individuals reached AUCs of 0.75, 0.69, and 0.66, for the 3 age groups, respectively. The XGBoost approach reached AUC = 0.94 (training set) and AUC = 0.78 (test set). Each approach was most accurate when discriminating MCI for the youngest age group.

Conclusion

Our two modeling approaches were able to predict MCI with acceptable accuracy. The predictions were more accurate in the 50‐64 age group than in the older groups, suggesting that the use of prediction models for triage in primary care will play a greater role in younger age groups.
Baseline cerebrovascular reactivity predicts longitudinal enlarged perivascular space burden in the basal ganglia among cognitively normal older adults
Authors: Libecap Timothy Justin , Bauer Christopher E. , Zachariou Valentinos , Pappas Colleen , Raslau Flavius D , Liu Peiying , Lu Hanzhang , Gold Brian T.
Published: December 2023

Background

Increasing evidence suggests that enlarged perivascular spaces (ePVS) on magnetic resonance images (MRIs) are associated with cognitive dysfunction in aging. However, the etiology of ePVS remains unknown. Here we tested the possibility that cerebrovascular dysfunction, as assessed by an MRI measure of cerebrovascular reactivity (CVR), may contribute to ePVS development.

Method

79 cognitively normal, older adults (46 women, age range 60‐84) were recruited to undergo baseline MRI scanning and follow‐up scanning approximately 2.5 years later. Of the 79 participants scanned at baseline, 50 returned for follow‐up. Participants were scanned on a 3T Siemens Prisma scanner with a 64‐channel head coil. All scanning methods were identical across time points and included collection of T1‐weighted, T2‐weighted FLAIR, and quantitative susceptibility mapping (QSM) images. Cerebrovascular dysfunction was assessed using CVR, a measure of the ability of cerebrovasculature to dilate in response to vasoactive stimuli. Participants underwent blocked administration of breathing either room air or hypercapnic gas, while blood‐oxygen‐level‐dependent (BOLD) functional magnetic resonance imaging (fMRI) was performed. CVR values were computed for baseline scans in specific regions by dividing change in BOLD signal by change in end‐tidal CO2. Baseline and follow‐up ePVS counts were performed by a single rater who was blinded to participant demographics. ePVS were individually and manually counted using STRIVE criteria in a representative, axial slice of the basal ganglia (BGePVS) and centrum semiovale (CSePVS).

Result

BGePVS and CSePVS significantly increased during the follow‐up period. Mixed effects models indicated that baseline basal ganglia CVR values significantly predicted increased BGePVS counts after controlling for age, sex, education, and time point (p = <0.001). Furthermore, this effect was present bilaterally: Baseline CVR in the left hemisphere predicted increased BGePVS in the left hemisphere (p = <0.001) and baseline CVR in the right hemisphere predicted increased BGePVS in the right hemisphere (p = <0.001). Conversely, there was no longitudinal relationship between baseline CVR and increased CSePVS (p = 0.449).

Conclusion

These results demonstrate that low baseline CVR is a risk factor for later development of ePVS. Localization of these findings to the basal ganglia suggests that it is particularly vulnerable to cerebrovascular dysfunction.