bluuebunny/crossref_metadata_2025 huggingface dataset:
APP‐dependent cell adhesion is regulated by GWAS genes
Authors: Chapuis Julien , NAJDEK Chloé , Coulon Audrey , Eysert Fanny , Grenier‐Boley Benjamin , Bellenguez Céline , Demiautte Florie , Amouyel Philippe , Dumont Julie , Kilinc Devrim , Lambert Jean‐Charles
Published: December 2023

Background

Thanks to Genome‐Wide Association Studies (GWAS), 75 susceptibility loci for Alzheimer’s disease (AD) have been identified (Bellenguez et al, Nat genetics. 2022). However, one of the greatest challenges resides in the understanding of the functional consequences of these genetic determinants. One of the main hypothesis would be that some of these genetic factors could be involved in APP metabolism and Aβ production. Indeed, even if numerous players of the APP metabolism have been characterized over the last 20 years, a large part of the is still unknown. Moreover, with more than 200 genes localized in the AD susceptibility loci, the classical approach, i.e., studying genes one by one, cannot be done in a timely manner. Therefore, we took advantage of Genome‐Wide siRNA screening using a High Content Screening (HCS) approach allowing a systematic functional assessment of human genes on APP metabolism.

Method

A HEK293 cell line stably over‐expressing a fluorescently‐tagged APP was transitory transfected in 384‐well plates with the human siGENOME siRNA library to silence every human gene. High content analysis was performed to automatically quantify (i) fluorescence intensities reflecting the intracellular accumulation of APP byproducts and (ii) cell‐cell interaction. Enrichment pathway analysis was performed to identify the pathways in which the modulators of APP are mainly involved.

Result

Expected GWAS‐defined genes were identified among the genes showing the stronger effects on APP metabolism (APP, ADAM10, SORL1). Moreover, we observed that a large portion of the GWAS‐defined genes are modulators of APP metabolism and are involved in cell adhesion signaling, including the genetic risk factors FERMT2 and Cass4. In our model, silencing of these genes was also able to modulate cell‐cell interaction, suggesting that APP‐dependent cell adhesion is regulated by GWAS‐defined genes.

Conclusion

Remarkably, many genetic risk factors of AD are involved in cell adhesion pathway, such as APP which has been shown to be involved in synaptic formation and plasticity. Since synaptic dysfunction and loss is one of the very early hallmarks of AD, our data suggest that beyond Aβ production, APP could impact AD process through an impairment of cell adhesion at the synaptic level.
Single domain antibodies as promising tools for the selective detection and neutralization of neurotoxic Aβ42 oligomers in the cerebrospinal fluid of Alzheimer’s disease patients
Authors: Napolitano Liliana , Bigi Alessandra , Vadukul Devkee , Aprile Francesco , Chiti Fabrizio , Cecchi Cristina , Cascella Roberta
Published: December 2023

Background

Extracellular amyloid β (Aβ) plaques and intracellular neurofibrillary tangles of the hyperphosphorylated tau protein are the main hallmarks of Alzheimer’s disease (AD). Small, soluble oligomers, rather than mature fibrils, are the major neurotoxic agents. The heterogeneous structures and the transient nature of these oligomers make their isolation and characterization very challenging. Single domain Abs (sdAbs), composed only of a variable domain of the heavy chain with high specificity and affinity, appear as promising tools for an early diagnosis and therapy for AD.

Methods

Performing an in vitro and in vivo screening of different sdAbs, we selected those targeting Aβ42 oligomers or fibrils with high specificity using dot‐blot, ELISA assay and the super resolution stimulated emission depletion (STED) microscopy. The potential of sdAbs was also investigated in preventing Aβ42 oligomer‐induced cytotoxicity in cultured neuronal cells. Then, the sdAbs were used to selectively detect Aβ42 species in the cerebrospinal fluid (CSF) of AD patients and control subjects and to neutralize their associated harmful effects following cell exposure to CSF samples.

Results

sdAbs can selectively detect Aβ42 oligomers or fibrils both in vitro and in cultured cells, preventing the neurotoxicity induced by small oligomers. Moreover, sdAbs can significantly identify Aβ42 oligomers in the CSF of AD patients counteracting their induced toxicity in our cell models.

Conclusions

All these data provide a solid foundation for the development of sdAbs‐based immunodiagnostic tools that can selectively detect toxic aggregates in human body fluids for an early differential diagnosis of protein deposition diseases, such as AD. Furthermore, our results contribute to the improvement of the current therapeutic approaches against AD.

The study was supported by Airalzh (AGYR 2020 to R.C.).
Speaker Identification in Dementia Households
Authors: Jouaiti Melanie , Vaidyanathan Ravi
Published: December 2023

Background

Speaker identification on datasets collected in the wild faces several challenges, including the scarcity of labelled data, noisy data and data where several people are talking. Previous works have focused on speaker identification using large amounts of labelled data or semi‐supervised approaches where a small amount of data is used a training set, but in this case, the datasets used only contain clean data and often the same sentences repeated several times by each participant.

Method

In this work, we propose a new approach to achieve fuzzy semi‐supervised clustering on Alexa data collected in households of people living with dementia (PLwD). In this context we wish to identify the carer and the PLwD, but also visitors. We extract x‐vectors from the audio data, apply PCA and use those as input features for our algorithm. The clusters are initialised with a small amount of data from each identified speaker (carer, PLwD). New data is added iteratively and membership scores are computed for each cluster. Membership is computed according to the Euclidian distance between the data point and each cluster. Centroids are updated every 30 iterations, only considering the points with high membership. Membership is also updated with the new centroids and considering the Mahalanolis distance.

Result

Our method performs comparatively to unsupervised learning and supervised learning in a two‐class problem (carer and PLwD), with 100% accuracy and 96% recall in identifying the PLwD with a training set of 5 files. When considering visitors as an unknown class, unsupervised learning fails. Our method performs similarly to supervised learning in identifying the carer and PLwD (97% accuracy and 80% recall), but is better at identifying visitors as unknown speakers than supervised learning (around 40% accuracy, and 4% respectively).

Conclusion

In this work, we propose a new method to perform speaker identification on data collected in the wild. We endeavour to address the shortcomings of supervised learning which tends to overfit and unsupervised learning which does not perform well with unknown classes.
Revealing hidden sensorimotor memories in mice with AD‐relevant pathology
Authors: Santi Andrea , Moore Sharlen , Lawlor Jennifer , Wang Aaron , Fogelson Kelly , Kuchibhotla Kishore
Published: December 2023

Background

Memories must be accessible for them to be useful. Alzheimer’s disease (AD) is a progressive form of dementia in which cognitive capacities slowly deteriorate due to underlying neurodegeneration. Interestingly, anecdotal observations have demonstrated that Alzheimer’s patients can exhibit cognitive fluctuations during all stages of the disease. In particular, it is thought that contextual factors are critical for unlocking these hidden memories. To date, however, exploration of the neural basis of cognitive fluctuations has been hampered due to the lack of a behavioral approach in mouse models to dissociate memories from contextual performance.

Method

Our previous work demonstrated that interleaving ‘reinforced’ trials with trials without reinforcement (‘probe’ trials) in an auditory go/no‐go discrimination task, allows us to distinguish between acquired sensorimotor memories and their contextual expression. Here, we used this approach, together with two‐photon calcium imaging on behaving AD‐relevant mice (APP/PS1+), to determine whether amyloid accumulation impacts underlying sensorimotor memories (measured using ‘probe’ trials) and/or contextual‐performance (measured using ‘reinforced’ trials) in an age dependent manner.

Result

Importantly, peripheral auditory function, measured using the threshold for detecting an auditory brainstem response, was similar between WT and APP/PS1+ mice. We found that while contextual‐performance is significantly impaired in young adult APP/PS1+ mice compared to age‐matched controls, these animals show only minor impairments in the underlying sensorimotor memories. However, middle aged APP/PS1+ mice show deficits in both domains. The impairment found in the young adults was accompanied by a reduction in stimulus selectivity and behavioral encoding in the auditory cortex of APP/PS1+ mice that that can be partially restored in probe trials. Ongoing analyses aim to identify whether this impairment is cortex‐wide or is concentrated near Aβ plaques. Finally, these effects were recapitulated by using a reinforcement learning model that accounts for changes in contextual signals. The main network model parameters affected between the control and the APP/PS1+ mice were those governing contextual scaling and behavioral inhibition.

Conclusion

These results suggest that Aβ deposition impacts circuits involved in contextual computations before those involved in acquiring knowledge and that neural circuit interventions, such as modulating inhibition, may hold promise to reveal hidden memories.
Functional Variants Identify Sex Specific Genes and Pathways in Alzheimer’s Disease
Authors: Lee Kwanghyuk Danny , Bourquard Thomas , Al‐Ramahi Ismael , Pham Minh , Shapiro Dillon , Lagiesetty Yashwanth , Soleimani Shirin , Mota Samantha , Wilhelm Kevin , Samieinasab Maryam , Kim Youngwon , Huh Eunna , Asmussen Jenn , Katsonis Panagiotis , Botas Juan , Lichtarge Olivier
Published: December 2023

Background

Alzheimer’s Disease (AD) incidence is almost double in women, suggesting sex‐specific risk genes for AD remain to be uncovered.

Method

To identify AD risk genes in smaller cohorts of only male or only female subjects we designed a machine learning case‐control study of genome variant differences that included a functional importance score as a feature. The method robustly finds genes in smaller cohorts, enabling us to analyze men and women separately.

Result

We found AD‐associated risk genes men‐only, women‐only, or combined subjects. These genes were consistent with a) prior AD GWAS; b) expression in AD patients brain regions; c) transcriptome analyses; d) and in vivo experiments in fly models of Amyloid beta and Tau neurodegeneration. Notably, the sex‐specific genes implicate pathways that are differentially altered in each sex – a stress response pathway unique to AD affected men and cell‐cycle/DNA quality control pathways unique to AD affected women.

Conclusion

A machine learning combined with an evolution‐based training feature for variant impact identified common as well as sex‐specific AD‐associated genes and mechanisms of potential value for pre‐symptomatic risk assessment and drug targeting.
Alzheimer’s Dementia and Care: Legal aspects of the use of technology
Authors: Schmitz‐Luhn Björn , Chandler Jennifer
Published: December 2023

Background

Modern technology promises many improvements for the lives of persons suffering from Alzheimer’s dementia and their caregivers. For example, technology can help with the assessment and measurement of symptoms, monitoring of disease progression, supporting decision‐making to alleviate symptoms and foster well‐being, facilitating training, physical activity and remote care.

For example, wearable, clothing, or ambient sensors can be used to closely monitor physiological functions and detect any falls or accidents, automatically alert physicians or caregivers, and warn about slightest changes in biological function. Wandering can be tracked, and assistive technology can help in case of disorientation. It can assist with cognitive training and physical activity. Above all, the algorithmic analysis of large sets of patient data can, e.g., point to potential indicators for disease risk or progress, allowing for the development or personalization of possible treatments, or for algorithmically assisted care decision‐making.

Method

In an international prospect of existing rules and regulations regarding the use of technology for AD care, challenges, divergencies and possible gaps have been identified, highlighting pitfalls and hindrances for medical care as technology evolves.

Result

In spite of major advantages brought about by technology, there are also challenges from legal and ethical perspectives. They include questions of liability for technology by developers and medical practitioners, of equity and access to assistive technology in statutory and private health care, of information and consent regarding the use of complex technology, as well as of privacy, autonomy and the internationally diverging levels of data protection regulation.

Conclusion

Given challenges and hindrances must be considered in order to protect the interests of the affected persons and to ensure the responsible use of technology to benefit patients and caregivers. We will present some of these, and point to solutions for health policy makers in order to both foster emerging technology and ensure its safe use for patients as well as regulatory reliability for medical practitioners.
Disambiguating the macro‐scale anatomy of dysexecutive and behavioral degenerative diseases of the mind
Authors: Corriveau‐Lecavalier Nick , Barnard Leland R , Botha Hugo , Radford Jonathan Graff , Ramanan Vijay K , Lee Jeyeon , Dicks Ellen , Boeve Brad F. , Machulda Mary M. , Dickson Dennis W. , Graff‐Radford Neill R , Knopman David S. , Lowe Val J. , Petersen Ronald C. , Jack Clifford R. , Jones David T.
Published: December 2023

Background

There is a longstanding ambiguity regarding the clinical diagnosis of dementia syndromes predominantly targeting executive functions versus behavior/personality. This is due to a lack of knowledge about the macro‐scale anatomy underlying these symptomatologies, a partial overlap in clinical features, and the fact that a single underlying pathology can give rise to both phenotypes and vice‐versa.

Method

We included data from patients with genetic, biomarker, and/or autopsy evidence for fronto‐temporal lobar degeneration (FTLD) diagnosed with behavioral variant fronto‐temporal dementia (bvFTD, n = 30) and patients with biomarker and/or autopsy evidence for Alzheimer’s disease (AD) pathology diagnosed with either an initial and predominant dysexecutive (dAD, n = 52), behavioral (bvAD, n = 7), or amnestic (aAD, n = 28) syndrome. We assessed group‐wise differences in clinical/cognitive features and 18Fluorodeoxyglucose‐positron emission tomography (FDG‐PET) patterns. This was followed by a spectral covariance decomposition between FDG‐PET images to yield latent patterns of relative metabolism (“eigenbrains”). These eigenbrains were subsequently linked to clinical/cognitive data and meta‐analytic topics reflecting a wide range of mental abilities. We used a linear discriminant analysis (LDA) to perform eigenbrain‐based diagnostic predictions.

Result

dAD and bvFTD patients were the youngest at symptom onset, followed by bvAD, then aAD. dAD patients had worse cognitive performance on nearly all cognitive domains compared to other groups. Hypometabolism was observed across associative cortices in dAD, temporo‐parietal areas in aAD, and fronto‐temporal areas in bvFTD and bvAD (Fig. 1). The spectral covariance decomposition yielded nine eigenbrains which explained 61% of the variance in patterns of FDG‐PET, and only the first three are presented (Fig. 2). These eigenbrains revealed that relative hypometabolism in association cortices, notably lateral parietal areas, associated with dysexecutive symptomatology and a lower likelihood of behavior/personality problems, whereas relative hypometabolism restricted to frontal and temporopolar areas showed opposite associations. The LDA yielded an accuracy of 82.1% in predicting diagnostic category (Fig. 3).

Conclusion

This study suggests distinct macro‐scale underpinnings underlying predominant dysexecutive versus behavioral symptomatology in degenerative dementia phenotypes. This has implication for the implementation of clinical and research criteria for these dementia syndromes and highlights the importance of data‐driven techniques to inform the classification of degenerative diseases.
Psychosocial and physiological effects of choir singing in people with dementia: A pilot study
Authors: Dawudi Milad , Schall Arthur , Tesky Valentina Antonia , Pantel Johannes
Published: December 2023

Background

Research suggests that music‐based interventions can improve emotional well‐being and quality of life in people with dementia. However, investigations are generally confined to specific music therapy settings. Complex music‐based interventions from day‐to‐day life, such as choir singing, have rarely been studied, not least because of the methodological challenges. Here we report on a pilot study examining the benefits of singing in persons with dementia that had joined a choir created especially for them.

Method

In preparation for a larger study on the impact of regular choir singing in dementia, we conducted a feasibility study to assess the expected effects on psychosocial and physiological outcomes. Emotional well‐being, depression, neuropsychiatric symptoms, physiological stress markers and quality of life were measured in the 19 choir members, all of whom had mild to moderate dementia (age: M = 76.95 [SD = 8.18]; f = 10 (52.6%); MMSE: M = 16.42 [SD = 5.79]) and were accompanied by their caregiving relatives. The weekly choir rehearsals took place over two months. Sessions were evaluated individually (situational measurements) and overall (pre/post‐tests).

Result

Our data suggested significant increases in emotional well‐being during the choir sessions (p < .05; Cohen’s dRM between 0.5 and 0.9), as well as significant reductions in cortisol levels in saliva as an indicator of stress (p < .05; dRM between ‐0.2 and ‐0.76). A pre‐post evaluation (paired sample t‐tests) showed noticeable, but not significant improvements in neuropsychiatric symptoms, depression, and quality of life. Caregivers’ observations confirmed the positive influence of choir singing on participants’ emotional and communication behavior.

Conclusion

The results of the pilot study reveal the therapeutic potential of choir‐based music interventions in persons with dementia and show that these effects can be demonstrated under real‐world conditions. A large‐scale randomized controlled study should further investigate the effects of choir singing in dementia.
Alzheimer’s Disease Patient Stratification Biomarkers and Cross‐disease Mechanisms
Authors: Taylor Krystyna , Malinowski Andy
Published: December 2023

Background

Alzheimer’s disease (AD) is characterised by a high degree of heterogeneity in the patient population. GWAS have identified several disease‐associated genes, but these findings have not translated into progress in the clinic. This likely reflects the limitations of GWAS in only identifying single variants, while the key to understanding and treating complex diseases that are influenced by multiple genetic loci is to find combinations of variants that distinguish patient subgroups.

Method

The PrecisionLife platform utilises a hypothesis‐free method for the detection of combinations of features that together are strongly associated with variations in disease risk, symptoms, progression rates and therapy response.

To explore the diversity within the AD population we analysed a genomic dataset from the UK Biobank, including 882 patients diagnosed with AD, compared against healthy controls. Subsequently, pathway enrichment analysis was performed to identify biological mechanisms underlying the AD patient subgroups that are shared with other CNS indications.

Result

Our analysis identified combinations of genetic variants which mapped to 113 genes that are significantly associated with AD pathology. These include known and novel genes. Clustering of these combinations, based upon the degree of patient overlap, revealed six distinct subgroups. Each patient subgroup reflected a specific biological function ‐ lipid metabolism, neuroinflammation, autophagy, serotonin signalling, metal ion homeostasis, and metabolic dysfunction.

PrecisionLife’s patient stratification approach enables understanding of shared genetic aetiologies and underlying dysregulated biological processes across multiple diseases where there is evidence of overlapping symptomology. We performed a pathway enrichment analysis, using the patient stratification results from the AD study, to find commonalities identified in other patient datasets, including FTD, schizophrenia and long COVID. We were able to identify multiple AD‐associated pathways that are significantly enriched in at least one additional disease. These included processes associated with neurotransmission, cell death signalling and lipoprotein metabolism.

Conclusion

The results demonstrate that combinatorial analysis can stratify heterogenous patient populations with complex pathologies to identify effective therapeutic strategies with accompanying biomarkers, improving the probability of success in AD drug development and opening an opportunity for identifying biological mechanisms and pathways relevant to treating multiple, related CNS diseases.
The diagnostic accuracy of cerebral amyloid angiopathy criteria between modified Boston criteria v1.5, Boston criteria v2.0, and simplified Edinburgh criteria – the first Thai cerebral amyloid angiopathy pathological confirmed cohort.
Authors: Pongpitakmetha Thanakit , Thanprasertsuk Sekh
Published: December 2023

Background

The gold standard of cerebral amyloid angiopathy (CAA) diagnosis are surgical pathology or postmortem examination, which are scarcely done in clinical practice. Thus, the current diagnostic criteria are mainly based on clinic‐radiological characteristics, including modified Boston criteria v1.5 [Linn J, et al. 2010] and Boston criteria v2.0 [Charidimou A, et al. 2022], which are magnetic resonance imaging (MRI)‐based, as well as simplified [Sembill JA, et al. 2022] and full [Rodrigues MA, et al. 2018] Edinburg criteria, which are computerized topography (CT)‐based. These criteria had been developed based on patients in western countries. Therefore, the application of these criteria in Asian population, especially in South‐East Asian, is limited. This study aimed to explore the clinico‐radiological characteristics and the accuracy of the current diagnostic criteria among Thai CAA patients.

Method

Congo Red staining brain histopathological specimens in King Chulalongkorn Memorial Hospital, Thailand during 2011‐2021 were reviewed. Patients’ characteristics were gathered from the best available data in electronic medical records. Each clinical event was analyzed separately. Radiological biomarkers in brain CT and MRI which had been done closet to the pathological confirmed date were systematically rated by trained investigators. Level of diagnosis was assessed based on the modified Boston criteria v1.5, Boston criteria v2.0, and simplified Edinburg criteria.

Result

Eight patients had pathological‐confirmed CAA and 11 clinical events from these patients were reviewed. The clinico‐radiological characteristics are shown in Table 1. Comparisons of the level of diagnosis between the criteria are shown in Table 2 and the diagnostic accuracy of the criteria using the Boston criteria v1.5 and v2.0 as reference standards are summarized in Table 3. The Boston criteria v2.0 revealed the better sensitivity compared with v1.5 (probable CAA, 63.6% vs 54.4%), likely due to an inclusion of non‐hemorrhagic biomarkers; whereas the simplified Edinburgh criteria showed lower sensitivity compared with Boston criteria. The AUC of probable CAA in Boston criteria v1.5 using v2.0 as a reference standard was 0.93 (95%CI[0.76‐1.00], sensitivity 85.7%, and specificity 100%).

Conclusion

We performed the application of most recent current diagnostic criteria in CAA Thai population. The larger and well‐designed confirmatory study in Asian cohort is needed.
Dysfunctional mitochondria during accelerated senescence and their impact on Alzheimer’s disease neuropathology
Authors: Caballol Nuria Suelves , Saleki Shirine , Palomares Debora , Ibrahim Tasha , Kienlen‐Campard Pascal
Published: December 2023

Background

Although aging is the leading risk factor for Alzheimer’s disease (AD), the exact mechanisms through which aging becomes pathogenic and triggers neurodegeneration have not yet been identified. Recent evidence suggests that AD is tightly correlated with the appearance of senescent cells and that mitochondrial dysfunction is a pathological feature occurring during senescence and AD. Additionally, studies have suggested that mitochondrial dysfunction and altered mitophagy might lead to Aβ accumulation. Our goal was to explore if a reduced removal of dysfunctional mitochondria during aging is a key contributor to amyloid pathology and neurodegeneration in AD.

Method

Since telomere shortening is a known trigger of cellular senescence, a telomerase‐deficient mouse model was used: Terc−/−. The brain proteome of Terc−/− mice was evaluated to validate classical and novel markers of senescence and investigate the alteration of key cellular pathways. Primary cultures and brain tissue from Terc−/− mice were evaluated for mitochondrial function/content and mitophagy alterations. Then, we explored the relationship between amyloid pathology and mitochondrial dysfunction by crossing the Terc−/− mice with an AD‐related amyloid mouse model (5xFAD) and exploring mitophagy alterations and amyloid‐β (Aβ) accumulation in disease‐vulnerable regions.

Result

Proteomic analysis revealed changes in proteins related to autophagy and mitochondrial functions during accelerated senescence. The mitophagy modulator BCL2/adenovirus E1B 19 kDa protein‐interacting protein 3 (BNIP3) was found downregulated in Terc−/− mice. We evidenced the presence of mitochondrial dysfunction and accumulation in senescent neurons. Additionally, we observed that senescence induces intraneuronal Aβ accumulation in specific brain regions (e.g., the subiculum) of an AD mouse model and we suggest that mitochondrial dysfunction and altered mitophagy might lead to Aβ accumulation.

Conclusion

Our results indicate that dysfunctional mitochondria accumulate during pathological aging due to a mitophagy impairment, which might contribute to AD neuropathology.
Cardiac remodeling, amyloidosis, neurotrophic signaling and innervation impairment in the Tg2576 model of Alzheimer’s disease
Authors: Elia Andrea , Parodi‐Rullan Rebecca M , Vazquez‐Torres Rafael , Carey Ashley M , Fossati Silvia
Published: December 2023

Background

In Alzheimer’s disease (AD), the characteristic cerebral amyloid β (Aβ) accumulation and tau pathology, are accompanied by a gradual loss of the two main neuromodulators, NGF and BDNF. This AD‐mediated derangement of the brain’s neuro‐signaling pathways may extend to the periphery and, along with potential peripheral amyloid deposition, induce peripheral nervous system impairment, thus affecting other organs, including the heart. However, whether and how AD pathology affects cardiac physiology, neurotrophins, innervation, and heart amyloidosis is still undefined.

Method

Here, we describe for the first‐time that cardiac remodeling and neuro‐signaling dysregulation are present in the hearts of Tg2576 mice, a widely used model of AD and cerebral amyloidosis.

Results

Echocardiographic analysis showed significant deterioration of left ventricle function, as demonstrated by a decline of both ejection fraction and fraction shortening in 12‐month‐old Tg2576 mice compared to age‐matched WT littermates. The transgenic mice hearts presented an increase in interstitial fibrosis, with an accumulation of amyloid aggregates, including Aβ, associated with severe cardiac nervous system dysfunction. Tg2576 mice exhibited a depletion in cardiac nerve fiber density, both adrenergic (stained with tyrosine hydroxylase‐ TH) and regenerating nerve terminals (labeled with GAP‐43) compared to the WT mice. This myocardial denervation was accompanied by a decline in NGF and BDNF protein expression as well as GAP‐43 expression in both the brain and heart of Tg2576 mice. Likewise, both human neuroblastoma cells (SH‐SY5Y) and human cardiomyocytes (AC16) challenged with human Aβ‐40 or Aβ‐42 oligomers showed significant downregulation of both BDNF and GAP‐43 activity.

Conclusion

Overall, this study highlights the deleterious impact of cerebral amyloidosis on the cardiac nervous system and heart physiology, providing potential therapeutic targets, such as neurotrophic factors, to prevent or limit the AD‐mediated degenerative mechanisms on the cardiovascular system.
BrainFM ‐ Tuning into the Modifiable Risk Factors of Dementia
Authors: Kaczmarska Magda , Yasoda‐Mohan Anusha
Published: December 2023

Background

Despite increasing research focus on 12 modifiable risk factors (MRF) reducing dementia risk by 40% across the life course, translation from bench to the broader society is limited thereby rampaging fear and stigmatisation. Furthermore, an Irish study showed that dementia awareness in Ireland was lower in younger than older people. Therefore, identifying methods that support community education about MRF in an accessible and engaging manner are paramount. To this end, BrainFM, is an educational tool that combines multisensory didactic learning with embodied co‐creative experience to deliver content around the brain and brain health. The current project describes one particular session around MRF delivered to an intergenerational population during Brain Awareness Week at the Creative Brain Week Conference (CBW) at the Global Brain Health Institute (GBHI), Trinity College Dublin in March 2022.

Methods

Four days of events highlighting the neuroscience behind three MRFs (hearing loss, social isolation and physical health) were co‐facilitated by Magda Kaczmarska, dancer and senior Atlantic Fellow and Dr. Anusha Yasoda‐Mohan, neuroscientist and current Atlantic Fellow for Equity in Brain Health at GBHI (Photo1). While Dr. Yasoda‐Mohan explained the didactic content, Ms. Kaczmarska facilitated creative dance and movement activities tailored to reinforce the content (Photo2). These sessions were delivered both online and in‐person to (i) multidisciplinary, international attendees of CBW; (ii) people living with dementia and care partners; (iii) first grade class at St. Paul’s primary school, Navan, Ireland and (iv) general public of the Dublin Docklands community (Photo3).

Results

The program was attended by 60 participants. Participant testimonials indicated heightened awareness and interest in proactive brain health and a feeling of community with fellow participants. Prominent clinical professionals engaging in co‐creative experience with artists and peers commented on how their understanding of an embodied connection was growing and influencing how they perceived other events of the week. Therefore, fostering interdisciplinary understanding supports innovation and solidarity around brain health in the community.

Conclusion

BrainFM was key in not only increasing mindfulness about the MRF and social connection but was also an advocate for the alliance between the arts and sciences as a powerful tool for expanding brain health literacy.
MIND diet consumption pattern in a cohort of cognitively healthy Mexican older adults. LatAm FINGERS Mexico
Authors: Salinas‐Contreras Rosa Maria , Martínez‐Galindo Joyce Graciela , Vigil‐Martinez Ana , Casildo‐Vasquez Tomas , Galindo Isabel Cristina , Sosa‐Ortiz Ana Luisa ,   LatAm FINGERS
Published: December 2023

Background

MIND diet is a hybrid diet designed from Mediterranean and DASH which emphasizes natural, plant‐based foods, promoting increased consumption of foods have been shown a positive impact on brain health and cognitive performance. Thus, understanding the food consumption habits is important.

Method

We analyzed elders cognitively healthy who were administered POINTER food habits questionnaire that evaluates the intake of 10 recommended foods and 5 limited foods from the MIND diet at basal evaluation. MIND score is 1 if the participant consumes the recommended portions, 0.5 if the intake is moderate, and zero if the intake is less than or equal to the recommendations. It was considered a good intake of MIND diet if the total score was ≥8 points. Descriptive analyses of both sociodemographic variables and food intake were performed.

Result

Analyzed 66 older adults between 60 and 77 years of age (mean 70 SD 5.14), 70% are women, with a mean of 9.9 years schooling (SD 3.9). 72% of the subjects evaluated did not meet the recommended MIND food intake (score ≤ 8). Among the recommended foods, the subjects ingested little or no olive oil, green leafy vegetables, red fruits, fish, and other vegetables, but they ingested large amounts of foods that should be limited, such as fried foods, pastries and sweets, cheese, fats, and margarines (table 1).

Conclusion

The recommended foods that the participants do not ingest in adequate quantities are those of high cost in our country (olive oil, red fruits, and fish), but the sample have a high intake of fast food and processed foods, some ones that should limit. Our sample consume adequately foods that are easily accessible and common in our country (legumes, poultry, red meat). It is necessary to make adaptations of the MIND diet according to access and regional characteristics, this could facilitate its adherence.
Statistical analysis to identify MRI markers for Alzheimer’s Disease: why moving towards AI?
Authors: Ruyter Swann , FIRAT Hüseyin , Racoceanu Daniel
Published: December 2023

Background

Alzheimer’s disease (AD) is characterized by progressive neurodegeneration of some brain structures and cognitive function decline. To evaluate the anatomical changes, structural Magnetic Resonance Imaging (sMRI) is a non‐invasive examination and allows the quantification of brain atrophy. Some of the affected structures could be common with other dementia types such as frontotemporal dementia (FTD) and dementia with Lewy bodies (DLB). The objective of this work is to identify specific affected structures in patients with AD to healthy individuals, and to patients suffering from FTD and DLB. This is a part of a larger effort to develop methods to better diagnose AD and to find specific markers of this dementia type.

Method

The ADDIA clinical study (EU‐H2020 project led by Firalis company) enrolled 800 participants and was designed to obtain high‐quality samples for the discovery of novel biomarkers for early and differential diagnosis of AD. The sMRI of 623 participants with the above‐mentioned pathologies and healthy individuals were analyzed and the volume of different areas measured with the software FreeSurfer. Statistics were performed to define significant differences in brain volumes between groups.

Result

One hundred and twelve brain areas were analyzed for volume by study participant. Compared with a healthy population, the atrophy of structures observed in AD patients almost completely overlaps with the one observed in DLB and FTD patients. When the DLB and FTD groups are compared to a healthy population, one brain area is specific in DLB patients and fifty‐eight in FTD patients. However, on these fifty‐eight affected brain areas, forty‐seven overlap with the mild AD patient group.

Conclusion

The measurement from imaging modality is not enough precise to report biomarkers as affected areas specific to the type of dementia. However, a promising framework lies in the application of machine and deep learning algorithms on a set of modalities: imaging, clinical and omics. These new tools allow for a finer understanding of data and a personalized approach to diagnosis. In preparation for this multimodal integration framework, the above categories of algorithms will be applied on MRI images. This will permit to discriminate AD from other dementia types at the individual level.
Identification of mild cognitive impairment with digital biomarkers in individuals presenting with cognitive complaints
Authors: Iulita M. Florencia , Ferrari Alberto , Harms Robbert , Quevenco Frances‐Catherine , Sánchez‐Benavides Gonzalo , Minguillón Carolina , Balasa Mircea , Bügler Maximilian , Santuccione Antonella , Tarnanas Ioannis
Published: December 2023

Background

One of the major challenges in Alzheimer’s disease (AD) is the identification of individuals at the earliest stages, who might benefit from disease‐modifying therapies. People presenting with clinical syndromes such as subjective cognitive decline (SCD), or mild cognitive impairment (MCI) harboring AD pathology are at high risk of cognitive worsening over time. Digital biomarkers could enable early, accurate and accessible diagnoses, and thus, streamline the patient journey to specialized care.

Methods

We included 102 participants from the β‐AARC cohort, established at the Barcelonaβeta Brain Research Center (BBRC), consisting of individuals seeking medical advice on their cognitive performance, mostly in primary care settings. Participants were classified as SCD (n = 94; age 66.4 [6.2] years; MMSE score 28.5 [1.3]) or MCI (n = 8; age 70.1 [4.6] years; MMSE score 26.3 [2.8]) after objective cognitive testing (Table 1). All had core CSF biomarkers (Aβ42/40, ptau‐181, t‐tau) determined with the Lumipulse automated platform (Fujirebio). Participants completed a digital cognitive assessment with Altoida’s research medical device. The device evaluates cognitive and functional impairment based on motoric and augmented reality tasks that simulate activities of daily living. These tasks evaluate multi‐modal features, including micro‐movements, micro‐errors, speed, reaction times, or navigation trajectories, which are used to train specific machine‐learning models, termed Digital Neuro Signature (DNS). The DNS‐MCI algorithm identifies cognitively normal individuals from those presenting with cognitive impairment. We compared DNS‐MCI scores across study groups and explored correlations with core AD biomarkers.

Result

DNS‐MCI scores were significantly lower in individuals presenting with MCI compared with SCD (p<0.05; Figure 1A). Participants who were Aβ+ based on the Aβ42/40 ratio (cut‐off ≤0.062) showed significantly lower DNS‐MCI scores compared with those who were Aβ‐ (p<0.001 for the whole sample; and p<0.05 for the SCD subsample (Figure 1B)). DNS‐MCI scores showed significant modest correlations with Aβ42/40, ptau‐181/Aβ42, ptau‐181 and t‐tau biomarkers (Figure 2).

Conclusion

Digital biomarkers identified differences in cognitive performance between MCI/SCD and Aβ+/Aβ‐ participants in a cohort with cognitive complaints seeking medical advice. DNS‐MCI scores correlated with core CSF AD biomarkers.

This work has received support from the Alzheimer’s Drug Discovery Foundation (grant #GDADB‐201906‐2018897) to Ioannis Tarnanas.
Federated BrainAge estimation from MRI: a proof of concept
Authors: Mateus Pedro , Yu Jing , Garst Swier J.F. , Harms Alexander G.J. , Cats Davy , Delgado Inigo Bermejo , Roshchupkin Gennady V. , Reinders Marcel JT , Slagboom Eline , Mei Haillang , Bron Esther E
Published: December 2023

Background

The gap between chronological and biological brain‐age, represented by MRI features, associates with dementia risk (Wang et. al., He et. al.). Age‐scores are predicted, however, using deep learning models, which require large amounts of MRI data. This poses a challenge, as patient brain MRI data is highly privacy‐sensitive and legal barriers often impede the sharing or transferring of data. Federated learning provides a potential solution by enabling training a global model on distributed data, allowing biobanks to keep data local while creating a shared model. In this study, we assess whether a federated set‐up is feasible for brain‐age estimation.

Method

We set up a federated learning framework across three biobanks (Fig. 2) to train a BrainAge model (Wang et. al). Data of healthy individuals from the ADNI dataset was randomly split across the three biobanks (N = 221, 219, 217). MRI images were pre‐processed into gray matter density maps (Good et. al.). The model was iteratively trained using federated averaging (McMahan et. al.) on data at two biobanks (70/30 training/validation split), and tested at the remaining biobank. We trained the model for ten rounds, and optimized for the number of epochs, learning rate, and learning decay hyperparameters. These results were compared to a centrally trained model, where the training samples were pooled together. Additionally, we applied the trained model to individuals with Mild Cognitive Impairment and Alzheimer’s Disease and performed a survival analysis. We assessed performance using Mean Absolute Error (MAE).

Result

Federated learning (MAE = 4.02) achieves similar test performance as central learning (MAE = 3.94) (Table 1). The model yielded an MAE of 4.89 for MCI and 5.45 for AD patients; this increase may be explained by their neurodegeneration. We also see a statistically different survival curve for developing AD in individuals with a brain‐age‐gap (Fig. 1), displaying an ‘older’ profile for their chronological age. This might indicate higher risk of developing AD, in line with previous results (Wang et. al.).

Conclusion

Results show federated learning has the potential to address the challenge of data accessibility for machine learning in complex and data hungry research, including dementia.
Determination of genetic, serological and cognitive markers in a cohort of elderly people in Panama
Authors: Britton Gabrielle B , Villarreal Alcibiades E , Oviedo Diana C , Carreira Maria B , Rangel Giselle
Published: December 2023

Background

The Panamanian Aging‐Focused Research Initiative (PARI) aims to study age‐associated neurodegenerative diseases in older people in Panama, such as determining genetic and serological biomarkers identified as risk factors for mild cognitive impairment (MCI) and Alzheimer’s disease (AD). Apoliprotein E (ApoE) is involved in lipoprotein metabolism and is the main carrier of cholesterol to the brain. The objective is to present the main findings on the allelic distribution of ApoE and its association with markers of inflammation and cognition in a cohort of elderly people in Panama

Method

PARI has enrolled more than 800 participants and has two recruitment waves. Informed consent was applied to all the participants, demographic data was collected, about their medical history and functional status, neuropsychological evaluations were carried out and blood samples were taken to determine the allelic frequency of the protein Apoliprotein E gene by means of PCR and various serological biomarkers. The clinical wave was made up of individuals ≥ 65 years of age who attended the CSS complex’s outpatient geriatrics, while the community wave consisted of individuals ≥ 60 years of age recruited in Panama City.

Result

The clinical wave presents greater age and cases of depression, and less education, body mass index and global cognition compared to the community wave. The presence of the ApoE2 isoform in both waves combined was 9.5%, while for ApoE 4 it was 27.4%. In the clinical wave, ApoE4 turned out to be a significant predictor with an Odds ratio of 5 (95% CI 2.11 – 12.52) for MCI. For both waves, global cognitive impairment is greater in people who have at least 1 copy of ApoE4, as well as worse ApoE 4‐associated cognitive function in female participants compared to male participants. Differences in the average levels of I‐309, IL‐18 and pancreatic polypeptide (PPY) between the groups with or without the presence of ApoE4 are significant when analyzing the cohort as a whole.

Conclusion

We conclude that the determination of the ApoE allele frequency, specifically the identification of ApoE4, can be considered viable as a genetic biomarker to be applied to the evaluations of cognitive impairment.
Creating a measure of community level dementia‐friendliness in faith communities
Authors: Moore Miranda , Gunn Grayson , Chester Mia , Chan Kiera , Epps Fayron , Bender Alexis Anne
Published: December 2023

Background

As the prevalence of dementia rises, modifying built and social environments of persons living with dementia (PLWD) becomes increasingly essential. Although there is a call to rigorously evaluate dementia‐friendly community initiatives, no known comprehensive evaluation tools exist to assess small communities such as churches and community centers. Therefore, we developed a person‐centered Dementia‐Friendly Community Assessment tool.

Methods

This tool consists of new and validated scales to assess the level of dementia‐friendliness among churches enrolled in a dementia‐friendly congregation program based in African American communities. An initial draft of the theory‐informed survey instrument was given to stakeholder groups (church leaders, care partners, PLWD, and the Alter advisory board) with the goal of gathering feedback on domains included in the tool, as well as general wording and appropriateness. After focus group recordings were transcribed, the team made revisions and administered the survey to 10 stakeholders (church leaders, care partners, PLWD, and lay congregants) to gather feedback on the digital version of the survey, proposed changes to the tool, and thoughts on implementation aids and barriers.

Results

Overall, the tool was well received by participants, with most participants indicating the tool’s resulting scores would be useful for their community. Additionally, the tool’s content prompted many to share personal experiences of living with dementia or caregiving for PLWD, indicating that future use of this tool may provide a starting point to address stigma.

Conclusion

Next steps include piloting the survey with broad church membership, and our aim is to enable programs to quantify their dementia‐friendly community initiatives.