bluuebunny/crossref_metadata_2025 huggingface dataset:
Ex‐vivo microbleed detection in community‐based older adults using confidence‐aware learning
Authors: Nikseresht Grant , Evia Arnold M , Bennett David A. A , Schneider Julie A , Agam Gady , Arfanakis Konstantinos
Published: December 2023

Background

Cerebral microbleed (CMB) detection on MRI scans of autopsied brains of community‐based older adults is crucial for MR‐pathology studies of cerebral small vessel disease (SVD). However, training an ex‐vivo CMB detection model is difficult due to the low prevalence of CMBs in the brains of community‐based older adults, and the fact that CMB mimics greatly outnumber CMBs on ex‐vivo MRI. We demonstrate that confidence‐aware deep learning, a technique for enforcing correct ranking of examples during neural network training, significantly improves ex‐vivo CMB detection performance and enhances the interpretability of model predictions.

Method

CMBs from 286 participants from two longitudinal cohort studies of aging were included in this work. T2*‐weighted gradient echo scans of autopsied brains with a voxel size of 1×1×1 mm were used. Confidence‐aware learning was used to regularize deep learning model predictions such that they reflect the degree of confidence the detection model has in a prediction. Model confidence was estimated during training by correctness, the number of correct prediction events across epochs divided by the total number of epochs. The objective loss function was modified to include a correctness ranking loss (CRL) term that encourages correspondence between correctness and predicted probabilities. Models are trained with and without the CRL loss term to evaluate the impact of confidence‐aware learning on model performance. An end‐to‐end CMB detection framework that combines data synthesis, candidate selection, false positive reduction, and full scan evaluation was used as the backbone for this work.

Result

CMB detection models trained using correctness ranking loss achieved a significantly higher ensemble average precision (0.2915) compared with models trained without correctness ranking loss (0.2379). The CRL trained model achieved a 25% higher sensitivity at 0.5 false positives per subject and 12% higher sensitivity at 3 false positives per subject when compared to models trained without CRL.

Conclusion

This work demonstrates that training with confidence‐aware learning can improve the performance and interpretability of ex‐vivo CMB detection algorithms in community‐based cohorts. The use of a confidence‐aware CMB detection algorithm for assisted CMB annotation in ex‐vivo MRI will aid in future MR‐pathology studies into the relationships between CMBs and neuropathology.
Risk of neuropsychiatric symptoms among people who develop cognitive impairment with and without a history of post‐traumatic stress disorder
Authors: Gauthreaux Kathryn , Perales Jaime , Flatt Jason D. , Meyer Oanh L.
Published: December 2023

Background

Most research studying the link between PTSD and cognitive impairment focuses on PTSD as a risk factor for developing Alzheimer’s disease; however, few studies focus on the impact cognitive impairment has on neuropsychiatric symptoms among people with a history of PTSD. Symptoms associated with cognitive decline may increase or cause the relapse of recurrent intrusive memories, dreams, or flashbacks of traumatic events among individuals with a history of PTSD. Additionally, cognitive impairment may lead to a delayed onset, worsening, or recurrence of PTSD‐related neuropsychiatric symptoms among people with PTSD. We aimed to prospectively assess the change in neuropsychiatric symptoms among people who develop cognitive impairment and have a history of PTSD.

Method

Data were obtained from the National Alzheimer’s Coordinating Center (NACC). Eligibility criteria included participants who were cognitively unimpaired and had non‐missing assessment of PTSD at initial visit, and who had at least one follow‐up visit with cognitive impairment. Information from the Uniform Data Set (UDS) health history and clinical diagnosis forms at the initial visit was used to separate participants with a history of (PTSD+) and participants without a history of (PTSD‐). Demographics, clinical symptoms, and mean NPI‐Q severity scores at the first UDS visit vs first visit with a Clinical Dementia Rating global score (CDR‐GS) of 0.5 were compared between groups.

Result

The final analytic sample included 18 PTSD+ participants and 585 PTSD‐ participants. While both groups experienced significantly higher mean NPI‐Q severity scores between baseline and the first visit with CDR‐GS = 0.5, there was not a significant difference between the groups (p = 0.79). Additionally, both groups exhibited significantly increased rates of change in NPI‐Q severity scores, but this rate was not statistically different between the groups (p = 0.73).

Conclusion

In this sample, we found no differences in NPI‐Q scores. The small sample size of PTSD+ participants as well as the mild nature of participants’ cognitive impairment might account for these null findings, as it might be too mild to impact PTSD symptoms; as such, future research examining these symptoms in larger and more diverse samples is warranted.
The cytosolic antibody receptor TRIM21 is required for effective tau immunotherapy
Authors: Mukadam Aamir , Miller Lauren VC , Smith Annabel E , Keeling Sophie , Vaysburd Marina , Andersen Jan Terje , James Leo C , McEwan William A
Published: December 2023

Background

Using a variety of cell and animal model systems we demonstrate that the cytosolic antibody receptor and E3 ligase TRIM21 plays a critical role in antibody‐mediated protection against tau pathology

Method

Experiments with organotypic hippocampal slice cultures and in vivo studies in mouse models were conducted to study the role of TRIM21 in tau immunotherapy.

Result

We demonstrate that tau:antibody complexes were internalised to the cytosol of neurons, enabling TRIM21 engagement and thereby protecting against seeded aggregation. Crucially, antibody‐mediated protection against tau pathology was lost in mice lacking TRIM21

Conclusion

The cytosolic compartment provides a site of immunotherapeutic protection, which can help in the design of antibody‐based therapies in neurodegenerative disease.
Effect of genetic clusters related to insulin resistance on neurological traits in diverse populations from the Trans‐Omics for Precision Medicine Program
Authors: Sarnowski Chloé , Zhang Yixin , Ammous Farah , Shade Lincoln MP , Jian Xueqiu , Dupuis Josée , Hivert Marie‐France , Florez Jose C , Seshadri Sudha , Morrison Alanna C ,   the TOPMed Neurocognitive and Diabetes working groups
Published: December 2023

Background

Insulin resistance (IR) is a major risk factor for Alzheimer’s disease (AD) and is primarily driven by obesity, another AD risk factor. The biological mechanism by which IR predisposes to AD is unknown. Genetic clustering analyses of type 2 diabetes (T2D) loci can help characterize which mechanism of impaired insulin action may be involved in AD and related traits.

Method

We constructed five genetic clusters related to IR (Obesity, Lipodystrophy, Liver/Lipid, ALP [alkaline phosphatase] negative, and Hyper‐Insulin Secretion) based on a recent clustering analysis of T2D loci (PMID: 36538063). We evaluated the association of each cluster with the Homeostatic Model Assessment for Insulin Resistance (HOMA‐IR) and neurological traits (AD, dementia, general cognitive function, and four brain MRI volumes) in >38k participants (36% men, mean age 55yrs (14.5)) of diverse race or ethnicity, from the Trans‐Omics for Precision Medicine (TOPMed) Program. We conducted pooled and race/ethnicity‐stratified association analyses (European‐50%, African‐American‐22.5%, and Hispanic/Latino‐21%). We used logistic or linear mixed‐effect models, adjusted for age, sex, study, and the first 11 genetic principal components. We accounted for relatedness and allowed for heterogeneous variances across studies.

Result

We confirmed the association of each IR genetic cluster with HOMA‐IR in the pooled analysis (2.6E‐66≤P≤2E‐4) and detected significant to suggestive associations in group‐stratified analyses (6.3E‐39≤P≤0.05), except for the Hyper‐Insulin Secretion cluster in African‐Americans (P = 0.30). The genetic clusters were not significantly associated with neurological outcomes after multiple testing adjustment (P = 0.05/Ngroups/Nclusters/Noutcomes = 0.05/4/5/7 = 3.6×10−4). We observed nominal associations (P<0.05) for two genetic clusters. The Lipodystrophy cluster was negatively associated with intracranial volume in the pooled analysis (beta = ‐0.51, P = 0.003) as well as in European (beta = ‐0.47, P = 0.02) and Hispanic/Latino (beta = ‐1.23, P = 0.01) participants. The Hyper‐Insulin Secretion cluster was negatively associated with hippocampal volume in Hispanic/Latino participants (beta = ‐0.005, P = 0.03), and positively associated with AD and dementia (OR = 1.02 [1.001‐1.038], P = 0.03) in European participants.

Conclusion

Our findings are consistent with the literature suggesting that IR may be associated with lower brain volumes and increased AD risk. Our analyses shed light on two biological mechanisms of impaired insulin action potentially involved in AD and related traits, with genetic associations that may differ by race or ethnicity.

Funding: R00AG066849
Levels of ADAM10 and BDNF in low‐educated healthy older adults and individuals with Alzheimer’s dementia
Authors: Pelegrini Lucas Nogueira de Carvalho , Pedroso Renata Valle , Grigoli Marina Mantellatto , Manzine Patricia Regina , Cominetti Marcia Regina
Published: December 2023

Background

Alzheimer’s Disease (AD) is the most common type of dementia among older adults (Prince et al., 2015). Research has focused on specific biomarkers for AD that could contribute to early diagnosis. Levels of ADAM10, for example, are altered in people with AD, and this protein has been studied as a potential blood‐based biomarker for this disease (Elsworthy et al., 2022). Brain‐derived neurotrophic factor (BDNF), in turn, is a protective factor involved, for example, in neurotransmitter modulation, as well as in neuronal plasticity and survival (Tarassova et al., 2020). Therefore, analyzing the possible relationship between these variables is relevant to expand the knowledge of AD biomarkers.

Aim

to verify whether there is a relationship between the levels of ADAM10 and BDNF among healthy older adults and individuals with AD with low educational attainment.

Methods

This is a cross‐sectional study in which community‐dwelling older adults with low educational levels (n = 85) were assigned to two groups: healthy older adults (n = 37) and participants with AD (n = 48). The interview was based on a sociodemographic questionnaire and cognitive assessment (Mini‐Mental State Examination‐MMSE and the Clock Drawing Test‐CDT). Participants had their blood collected, and SDS‐PAGE and Western Blotting techniques were used to measure plasma ADAM10 levels.

Results

Participants with AD were older (p<.001); had less educational attainment (p<.001); worse performance on MMSE (p<.001), and on its domains [Orientation (p<.001), attention, memory (p = .028), language(p<.001), and evocation(p<.001)]; as well as worse performance on CDT (p<.001). Also, compared to the healthy group, persons with AD had significantly higher levels of plasma ADAM10 (p = .04). No difference in BDNF levels was observed between the groups (p = .07). Correlation analyses revealed a significant correlation between ADAM10 and years of education (r = ‐.234; p = .04); MMSE total score (r = ‐.328; p = .003), and its orientation (r = ‐.224; p = .04), attention (r = ‐.278; p = .01), and evocation (r = ‐.332; p = .003) domains. BNDF was not correlated with any of the variables in this study.

Conclusion

This study showed that plasma ADAM10 levels in low‐educated older adults, but not BDNF, differ between healthy and AD participants. Our results reinforce the potential role of ADAM10 as a biomarker for AD.
Association of plasma Alzheimer’s and neurodegenerative disease biomarkers with brain volume loss and cognitive decline
Authors: Dark Heather E , Duggan Michael R , An Yang , Bilgel Murat , Joynes Cassie , Lewis Alexandria , Moghekar Abhay , Resnick Susan M. , Walker Keenan A.
Published: December 2023

Background

Although plasma Alzheimer’s disease (AD) and neurodegenerative disease biomarkers have been associated with reduced cognition and lower brain volume, few studies have examined whether plasma biomarkers measured in predominately cognitively unimpaired adults are associated with longitudinal brain volume loss and cognitive decline. Using data from the Baltimore Longitudinal Study of Aging (BLSA), we examined whether plasma biomarkers of AD pathology (Aβ42/40, phosphorylated tau [pTau‐181]), reactive astrogliosis (glial fibrillary acidic protein [GFAP]), and neuronal injury (neurofilament light chain [NfL]) were associated with longitudinal brain volume loss and cognitive decline.

Method

Plasma biomarkers (Aβ42/40, pTau‐181, GFAP, NfL) were measured using Quanterix SIMOA assays. Baseline visits were considered the earliest visits that had concurrent 3T MRI scans and plasma biomarker measurements, and the earliest visits that had concurrent cognitive assessments and plasma biomarker measurements. Composite Z scores were computed to reflect 5 cognitive domains (Figure 1). Linear mixed effects models adjusted for baseline age, sex, race, education, estimated glomerular filtration rate, and total intracranial volume (brain volume analyses), were used to examine the association of plasma biomarkers with baseline and longitudinal brain volume and cognition. False Discovery Rate correction was used to adjust for multiple comparisons.

Result

Brain volume analyses included 628 participants (mean age±SD: 71.0±10.2; Table 1) with an average of 3.3 MRI scans over 4.7 years. Cognition analyses included 686 participants (mean age±SD: 71.4±10.1) with an average of 3.9 cognitive assessments over 5.7 years. Although Aβ42/40 was unrelated to brain volume changes, higher pTau‐181 was associated with longitudinal declines in total gray matter volume and regional declines in medial temporal regions. Higher GFAP was associated with longitudinal increases in ventricular volume, whereas NfL was not associated with brain volume change (Table 2). Both lower Aβ42/40 and higher pTau‐181 were associated with a decline in verbal memory. Additionally, lower Aβ42/40 was associated with a decline in visuospatial performance. Further, higher GFAP was associated with a decline in verbal fluency (Figure 1).

Conclusion

Plasma biomarkers of AD pathology and astrogliosis may serve as markers of future brain atrophy and cognitive decline.
Risk factor of suicidal thoughts in caregivers of dementia patients: a systematic review and meta‐analysis
Authors: Chambergo‐Michilot Diego , Custodio Nilton , Montesinos Rosa , Lanata Serggio
Published: December 2023

Background

Dementia is a neurologic syndrome that affects several domains of daily life. However it does not exclusively affect the patient, but relatives, friends and caregivers, who are people constantly in contact with the patient. Deterioration of cognition and daily life activities may affect mental health of the caregiver. In this systematic review, we collected evidence regarding risk factors of suicidal thoughts among caregivers of patients with dementia.

Method

A search was carried out in PubMed, Scopus, and Web of Science up to January 2023. Observational studies that analyzed factors associated with suicidal thoughts in caregivers were selected and revised. Meta‐analyses were performed with R Studio.

Result

Four studies were selected for this systematic review. Only one study assessed caregivers of dementia and non‐dementia patients. Total sample size was 2224. Mean age was approximately 60 years. We did not find significant differences between caregivers with and without suicidal thoughts in age, educational level, religious status, being a woman, being spouse or caring one year or more. However, we found that CES tool score for depression was higher in those caregivers who reported suicidal thoughts (MD: 8.03, 95% CI: 6.26‐9.80).

Conclusion

Depression is a risk factor of suicidal thoughts, however more efforts should be done to assess non‐typical risk factors of suicidal thoughts among caregivers. We highly recommend increasing the sample size for future studies.
Functional neuroanatomic validity of a novel, smartphone‐based remote assessment of processing speed in early Alzheimer’s Disease
Authors: Taylor Kirsten I , Kurniawan Irma T , Wolfer Arnaud M , Lipsmeier Florian , Perumal Thanneer M
Published: December 2023

Background

The quantification of information processing speed (IPS) and its changes over time is a cornerstone of neuropsychological assessment for early Alzheimer’s disease (eAD). Additionally, clinical practice and drug development increasingly require tools enabling the remote assessment of cognition. We previously reported the feasibility, reliability and clinical validity of a novel, smartphone‐based IPS test remotely self‐administered to healthy controls (HC) and individuals with subjective cognitive decline (SCD) and eAD. The present study performed whole‐brain voxel‐based morphometry (VBM) analyses to determine whether smartphone‐based IPS performance indeed correlated with atrophy of brain regions known to support processing speed.

Method

31 HC, 31 SCDn (amyloid‐PET negative), 31 SCDp (amyloid‐PET positive) and 30 eAD individuals participated in a Alzheimer’s Digital Assessment Suite (AD‐DAS) Proof‐of‐Concept study (https://www.isrctn.com/ISRCTN17035495). Participants performed 9 IPS assessments (90s digit‐symbol matching) over 28 days on provisioned smartphones. Each response sequence and digit‐symbol pairing was novel and matched for difficulty within/across sessions.

High‐resolution anatomic, T1‐weighted MRI were submitted to whole‐brain VBM analyses (Computational Anatomy Toolbox, SPM12/Matlab 2021) testing whether performance (number correct) correlated with gray matter signal intensities (covariates: age, gender, years of education, study site, total intracranial volume). The statistical parametric map was thresholded at p<0.001 uncorrected (voxel‐level) and family‐wise error corrected p<0.05 (cluster‐level). Peak voxel MNI coordinates and t‐values, cluster‐level p‐values are reported.

Result

Poor smartphone‐based IPS performance correlated with atrophy in five regions centered in: (1) right insula (57, ‐14, 15; t = 5.83; p<0.0001), (2) right lingual gyrus (14, ‐64, ‐8; t = 5.21; p = 0.006), (3) left hippocampus (‐36, ‐24, ‐16; t = 4.83; p = 0.021), (4) left precuneus (‐10, ‐57, 26; t = 4.73; p = 0.017), (5) right fusiform gyrus (27, ‐38, ‐15; t = 4.69; p = 0.043), replicating previous functional MRI findings with IPS (lingual gyrus, precuneus) and known neuroanatomical correlates of working memory (insula, hippocampus).

Conclusion

These findings support the functional neuroanatomic validity of a novel smartphone‐based IPS task and thus remote, clinically meaningful characterization of preclinical/early AD individuals’ IPS impairments in clinical monitoring and drug trials.
Circular RNAs Associated with Idiopathic Parkinson’s Disease: Case/Control Study Results on PPMI Dataset
Authors: Sun Yichen , Beric Aleksandra , Chen Hsiang‐Han , Eteleeb Abdallah M , Cruchaga Carlos , Ibanez Laura
Published: December 2023

Background

PD is the second most common neurodegenerative disease after AD, for which biomarkers do not exist. We aimed identify circular RNAs associated with Parkinson’s Disease (PD) in a longitudinal dataset and test their potential as Bioamrkers.

Method

We included 2507 European ancestry blood samples from PPMI participants, with transcriptomic data available and distributed across five time‐points. We aligned reads to the reference genome (GRCh38) using STAR in chimeric alignment mode. Annotation and quantification of circRNAs were performed using DCC, followed by a cross‐sectional differential expression analyses for each visit using DESeq2. Significance was assessed and corrected by FDR at the last visit, with nominal p‐value for the remaining visits. We used Circular RNA Interactome web tool to predict microRNA (miRNA) target sites within significantly dysregulated circRNAs. Subsequently, we performed pathway analyses using DIANA tools.

Result

Two circRNAs were significantly dysregulated in PD across all visits: circRHBDD1 (p = 3.34´10−4, Log2FC = ‐0.13) and circDHRSX (p = 1.03´10−3, Log2FC = 0.4). We identified twenty miRNAs that putatively interact with circRHBDD1. Pathway analyses showed that fourteen of them are involved in the Hippo signaling pathway, fifteen in oxytocin signaling pathway, and sixteen in the ErbB1 signaling pathway. We also identified one hundred and twenty‐eight miRNAs interacting with circDHRSX that are also part of the Hippo signaling pathway.

Conclusion

We identified circRHBDD1 and circDHRSX to be dysregulated in PD across time. Both of them are enriched in binding sites for miRNAs that target the Hippo and ErbB1 signaling pathways. ErbB1 has already been associated with PD in brain studies, whereas the Hippo pathway is associated to neuronal cell death. We are conducting additional analyses in independent datasets and using mixed models to replicate the results and obtain the best predictive models.
RNA‐targeted therapy for Tau‐driven neuronal malfunction: preclinical screening
Authors: Silva Joana , Campos‐Marques Carlos , Godinho Bruno , Watts Jonathan , Sousa Nuno , Sotiropoulos Ioannis
Published: December 2023

Background

Tau protein is the most well‐known and studied microtubule‐associated protein, mainly due to its aberrant hyperphosphorylation and accumulation that is observed in Alzheimer’s disease (AD) and other Tauopathies. Accumulating evidence from different research teams, including ours, supports the involvement of Tau and its malfunction in brain pathologies with diverse etiologies such as epilepsy, stress‐driven depression, and more recently persistent pain, pointing towards a broader role of aberrant Tau accumulation in neuronal malfunction and brain pathology. Antisense oligonucleotides (ASOs) are small synthetic strings of nucleotides that regulate the RNA levels of the protein of interest while they have been proven to be safe for both animal and human use. As Tau reduction appears a promising therapeutic intervention against Tau‐driven neuronal malfunction, the current studies aim to design and monitor the efficiency of novel Tau‐ASOs.

Methods

We have designed 50 novel ASOs against total Tau or selectively 4R‐Tau while their efficiency was tested in differential N2a and SHSY‐5Y cell lines expressing WT and mutated human P301L‐Tau followed by hippocampal primary neuronal cultures of WT and P301L‐Tg mice.

Results

Based on the above in vitro assays, we have identified a set of novel and highly efficient ASOs for reducing Tau or modulating 4R/3R isoform ratio as assessed by different types of molecular and cellular, neurostructural, and synaptic analysis.

Conclusion

Altogether, these data provide solid evidence of the in vitro evidence of novel ASOs targeting total Tau or modulation of 4R/3R isoform ration to be beneficial against Tau‐related neuronal malfunction in neuronal pathologies, supporting this as an innovative RNA‐based therapeutic approach.
Longitudinal Coupling Between Depressive and Cognitive Symptoms in Ageing and Dementia: A Multi‐Cohort Analysis
Authors: Hamilton Calum Alexander
Published: December 2023

Background

Depression and cognition have a complex bidirectional relationship in adulthood and later life. This association is likely heterogeneous, differing between individuals. Further complicating this association is the possible influence of unseen neuropathological changes: any associations between depression and cognitive symptoms may differ in normal and pathological ageing.

We therefore aimed to examine the longitudinal coupling between depressive and cognitive symptoms in later life across multiple ageing cohorts drawing from population settings, memory services, and from a national dementia brain bank.

Method

Repeated data on cognitive performance and self‐ or informant‐reported depressive symptoms were drawn from multiple cohorts: three population ageing studies, CFAS (n = 17,807), Whitehall II (n = 8249) and ELSA (n = 17,980); MEMENTO (n = 2306), a clinical cohort of people with subjective/mild cognitive impairment (S/MCI); BDR (n = 584), a clinico‐pathological cohort with autopsy‐confirmed dementia‐related neurological disease.

Intercept and growth parameters for depressive and cognitive symptoms, and correlations between these, were estimated with bivariate latent growth models.

Result

The relationships between depressive and cognitive symptoms differed substantially between cohorts across the ageing continuum. In early ageing and S/MCI, worse cognitive performance was associated with worsening depression over time (r = 0.12, p = 0.022), whereas in clinical dementia groups and those with autopsy‐confirmed neurological disease, worse cognitive performance was associated with improving depression over time (r = ‐0.30, p = 0.008 and r = ‐0.49, p = 0.023, respectively).

Conclusion

Age‐related associations between cognitive and depressive symptoms may differ between specific ageing populations. When attempting to understand the relationship between depressive and cognitive trajectories, researchers should consider the position of the given sample along this healthy‐pathological ageing continuum.
Exploring the relationship between MRI changes and cognitive/neuropsychiatric complaints in a cohort of long COVID‐19 patients: A cross‐sectional and longitudinal study
Authors: Pérez‐Millan Agnès , Guillén Núria , Falgàs Neus , Botí María Ángeles , Tort‐Merino Adrià , Lledó‐Ibáñez Gema María , Ruiz‐García Raquel , Naranjo Laura , Rami Lorena , Balasa Mircea , Lladó Albert , Sala‐Llonch Roser , Sanchez‐Valle Raquel
Published: December 2023

Background

Post‐acute Covid‐19 syndrome (PACS) frequently refers to cognitive complaints. It is not yet clear whether there is an association between cognitive symptoms with brain changes or neuropsychiatric symptoms. Our aims are 1) to study cross‐sectional and longitudinal MRI brain measures in a cohort of PACS and 2) their association with cognitive performance and mood disturbances.

Method

We performed a prospective single‐center study with 3T‐T1w MRI of 49 PACS patients at a cross‐sectional level. These participants had confirmed SARS‐CoV2 infection, ≥ 8 weeks after symptoms onset and cognitive complaints. All participants completed a comprehensive neuropsychological battery (NPS) and questionnaires assessing depression, anxiety, and subjective cognitive complaints (SCD). We obtained global MRI measures (e.g; gray and white matter volumes and mean cortical thickness) with FreeSurfer. We measured correlations of global MRI measures with SCD, memory and executive function outcomes, anxiety, and depression. All analyses were corrected for multiple comparisons. 44 PACS subjects had a 6‐month follow‐up MRI: in these, we performed longitudinal analyses with Generalized Linear Mixed‐Effects Models to study changes between visits in global MRI measures.

Result

Demographics are shown in Table 1. We did not find any correlation between clinical outcomes (SCD, anxiety, depression) and MRI findings. Visual memory (Rey figure’s recall) and cognitive interference inhibition and processing speed ((Stroop’s color‐word condition) were positively correlated with global gray and white matter volume measures (Figure 1). We did not identify changes in global MRI measures at 6 months in PACS participants.

Conclusion

In PACS, worse visual memory and executive function, but not other clinical outcomes, were associated with lower global structural MRI indexes. We did not observe global longitudinal changes in MRI.
The impact of self‐reported retrospective early adversity on later life biopsychosocial outcomes
Authors: Kuenzi Morgane
Published: December 2023

Background

Early adversity has been associated with several biopsychosocial outcomes later in life. Early adversity and its long‐lasting consequences may affect directly or indirectly cognitive aging and increase the risk of developing dementia in older age. Therefore, investigating the biopsychosocial outcomes associated with early adverse experiences is essential to be able to promote good development across the life course (i.e., resilience) and healthy (cognitive) aging.

Method

The goal of this study is to investigate the effect of early adversity (i.e., trauma and deprivation) on various biopsychosocial outcomes (i.e., physical and mental health, lifestyle, and cognition) in two UK cohorts (UK Biobank, N = 500,000; the English Longitudinal Study of Ageing (ELSA), N = 20,000). In both cohorts, adversities are self‐reported retrospectively, and only those adversities assessed in both cohorts were selected.

Result

The preliminary results showed that in both cohorts early adverse experiences have a significant detrimental effect on all the biopsychosocial outcomes investigated (i.e., physical and mental health, lifestyle, and cognition), Ps <.01.

Conclusion

In line with the literature, early adverse experiences have long‐lasting detrimental effects on a variety of biopsychosocial outcomes. The results found will be replicated on longitudinal data, to gain more information about the associations found and their underlying mechanisms. The aim of this study is to identify target factors on which to base interventions to promote resilience and healthy (cognitive) aging.
Interrelationships between depression, diabetes, and dementia in the prospective PREVENT cohort
Authors: Reid Graham
Published: December 2023

Background

Mood disorders, metabolic diseases, and cognitive impairment are significant challenges facing public health. These three conditions are increasing in epidemiological prevalence and comorbidities amongst the three are common. For example, research has shown that diabetes is associated with a twofold risk for both depression and all‐cause dementia. Depression has also been associated with greater cognitive impairment and the additive effect of comorbid diabetes accelerates cognitive decline. Depression and diabetes seem to be most highly associated with cognitive impairment in middle‐aged adults, but the interrelationships between these three non‐communicable disorders have not been well characterised in this period of life.

Method

As such, the aim of the current study was to investigate the relationships between depression, cognitive abilities, and insulin resistance in 665 middle‐aged adults from the prospective cohort, PREVENT. We assessed the interrelationships in older middle‐aged adults (50‐60 years old) and younger middle‐aged adults (40‐49 years old) using structural equation modelling.

Result

Our analyses showed that executive dysfunction could be predicted from insulin resistance in older but not younger middle‐aged adults. We also showed that depression could be predicted from insulin resistance in both younger and older adults in their midlife. And finally, we showed that deficits in visuospatial memory could be predicted from depression in older but not younger middle‐aged adults.

Conclusion

Going beyond the existing bivariate associations in the literature and focusing on middle‐aged adults where comorbidities are most likely to occur, we have captured the complexity of the relationships between these three non‐communicable diseases. Together, we demonstrate the interrelations between mood disorder, metabolic disease, and cognitive impairment, emphasising the need for combined interventions for adults in the middle period of their life.
Feasibility of longitudinal automated cognitive assessment in the stroke pathway
Authors: Blackburn Daniel J , Bell Simon M , Harkness Kirsty , O'Malley Ronan , Chapman Larissa , Lunn India , Mirheidari Bahman , Christensen Heidi
Published: December 2023

Background

Stroke, post‐stroke dementia and post‐stroke cognitive impairment prevalence is rising significantly, placing an increasing burden on healthcare systems. Standardised pen and paper tools for cognitive assessment require clinical time. There is increasing research into the use of automated cognitive assessment. CognoSpeak (https://cognospeak.github.io/website/) is a fully automated cognitive assessment tool based in language an interaction. A virtual clinician asking questions and listening to responses using automatic speech recognition and Machine Learning algorithms.

Methods

Patients who passed the eligibility criteria of having recent acute stroke/TIA, and do not have pre‐existing dementia, severe aphasia, deafness, or too medically unwell were approached to consent to speak to CognoSpeak. Participants completed the CognoSpeak assessment on the ward or at home via a web‐version, as well as MOCA and GAD and PHQ9.

Results

Recruitment started December 2020 and we approached 950 people and recruited 114 participants, with 20 having 6 months follow‐up and 5 12 months follow‐up. The mean age was 61.77 (SD 15.07). Most participants were recruited from Sheffield 71 (68%).The majority had ischemic stroke (67%) & mild stroke according to the NHISS (63%). The most common risk factor was hypertension (19%), and the majority of participants had no symptoms of disability before their stroke (22%). GAD and PHQ9 scores were collected.

Conclusion

It is feasible to complete automated cognitive assessment with the stroke population. There remains barriers in utilising technology within this acute and especially longitudinal cognitive assessment in stroke survivors, where rates of anxiety in hospital and at follow‐up appointments may reflect rapid discharge and changes in the stroke pathway during the initial covid pandemic.
Novel small molecules therapeutics for FTD/ALS reduce TDP43 related pathology
Authors: Mathur Vidhu , van Hummel Annika , Sabale Miheer , Ke Yazi D. , Liu Xikun , Bowers Michael T , Burke Kevin , Kokes Marcela , Shao Eric Q , Schwarz Jacon , Planey Katie
Published: December 2023

Background

TDP43 aggregation and mis‐localization is a hallmark of sporadic Amyotrophic Lateral Sclerosis (ALS) and TDP‐related Frontotemporal dementia (FTD‐TDP). Hyperphosphorylated and ubiquitinated cytosolic TDP43 aggregates have been identified in post‐mortem tissue from disease patients. However, no therapies targeting TDP43 are in the clinic.

Method

Using our novel machine learning platform, we identified compounds that can disaggregate toxic oligomers of amyloid like proteins including TDP43.

Result

We show that a TDP43 peptide can spontaneously form trimers, tetramers, hexamers and octamers in vitro using high resolution ion‐mobility mass spectrometry. Two of our compounds reduce these presumed toxic oligomers and restore physiologically relevant monomers and dimers. Furthermore, our compounds dose‐dependently reduce cytoplasmic aggregates in a cellular TDP43 aggregation model. These compounds show low plasma and brain homogenate binding, high metabolic stability, are orally bioavailable and are highly blood‐brain barrier permeable. Finally, our compounds were tested in a doxycycline‐repressible iTDP43A315T mouse model of ALS. Daily oral dosing of the compounds for approximately two months did not cause any toxicity in the mice at two doses. Both drugs were detectable at high concentrations in the brains of the mice at the end of the experiment. Importantly, drug treatments showed improvement in a motor behavior test and alleviated a disinhibition phenotype in an elevated plus maze test in the diseased mice. Further analysis of target engagement and other downstream efficacy markers is ongoing.

Conclusion

All together, these in vitro cell‐based and preliminary in vivo mouse model data show that the Acelot machine learning platform can identify small molecules that have therapeutic potential for ALS, FTD and other amyloid‐associated diseases.
iPSC‐derived cortical neurons of sporadic Alzheimer’s disease patients reflect their clinical vulnerability
Authors: Bertherat Féodora , Ng Bryan , Bengoa‐Vergniory Nora , Carlyle Becky C. , Wade‐Martins Richard
Published: December 2023

Background

iPSC‐derived cortical neurons from sporadic Alzheimer’s Disease (AD) patients were used to compare cellulare phenotypes in response to AB or tau insults with clinical data of the individual patients.

Method

We generated14 iPSC lines from sAD patients from the Deep and Frequent Phenotyping study, which has collected a battery of clinical data from early‐stage sAD patients. Phenotypes such as neurite loss, axonal branching or cytotoxicity were measured in iPSC‐derived cortical neurons following Amyloid Beta oligomer treatment.

Result

Individual AD patient lines exhibit significantly different levels of neurite loss and decreased axonal branching due to Amyloid Beta. This differences is significantly correlated with clinical vulnerability of the individual patients.

Conclusion

Differences in disease vulnerability in patients observed in clinic is reflected in patient iPSC lines when treated with Amyloid Beta.
Efficacy of the murine version of E2814 in a validated AD brain seed‐injection model in hTau mice
Authors: Talma Sonia , Gartlon Jane , Takahashi Eri , Horie Kanta , Wildsmith Kristin R , Staddon James , De Silva Rohan , Roberts Malcolm
Published: December 2023

Background

As Alzheimer’s disease progresses, pathological tau spreads through the brain via synaptically connected pathways. Tau proteins containing the microtubule binding region (MTBR) may be essential to form extracellular ‘seeds’ that initiate and propagate pathology. To simulate this process preclinically, we have further characterised an AD brain‐derived seed‐injection in vivo model using hTau mice that overexpress all six isoforms of human wild‐type tau (Andorfer et al., 2003). In further follow up studies, mice were treated with the 7G6‐IgG2a antibody, which is the murine counterpart of E2814, an anti‐tau antibody currently in clinical trials that recognises the MTBR (Roberts et al., 2020).

Method

In a validation study, insoluble fraction or whole homogenate from human AD brain (‘seed’) was directly injected into the left hippocampus of 6‐month‐old hTau mice or their tau null littermates. At different times after seed injection, the generation of insoluble tau was quantified in selected brain regions (hippocampus and cortex) by western blotting following tissue fractionation with detergents.

In a subsequent therapeutic intervention study, animals were treated peripherally with a control mouse IgG2a antibody or 7G6‐IgG2a at different doses (3, 10, and 40 mg/kg). Levels of insoluble tau in the hippocampus and cortex were quantified as described above. Terminal CSF was also collected to measure target engagement of antibody. Additionally, immunohistochemistry using the AT8 antibody that detects pathological forms of phospho‐tau proteins was performed on brains from a limited number of animals receiving the highest dose of control IgG2a or 7G6‐IgG2a.

Result

AD brain insoluble fraction was superior to homogenate when used as a seed in the hTau mouse.

Peripheral treatment of seeded hTau mice with the 7G6‐IgG2a antibody (40 mg/kg) resulted in a significant reduction of insoluble tau in multiple brain regions. Antibody target engagement also increased in the CSF from treated animals in a dose‐dependent manner.

Conclusion

AD seed‐injection in hTau mice has been further validated and can be used in therapeutic intervention studies. The murine version of E2814, 7G6‐IgG2a, reduced pathological tau seeding and spreading in this model. The nonclinical data obtained here further supports E2814 being tested in clinical trials.
Small RNAs, short but mighty: the unknown players in AD pathobiology
Authors: Beric Aleksandra , Baldrich Patricia , Cruchaga Carlos , Ibanez Laura
Published: December 2023

Background

MicroRNAs (miRNAs) are known to be involved in Alzheimer’s disease (AD), but little is known about the other classes of small RNAs (sRNAs). We performed the first high throughput, unbiased study of sRNAs in AD brains aiming to build regulatory networks involved in AD pathogenesis.

Method

Sampling included 244 parietal brain samples from the Knight‐ADRC, 93% of which were AD cases, 90% male, and with a mean age of 83. After RNA extraction with a Maxwell RSC instrument, we generated sRNA libraries using the RealSeq®‐AC sRNA kit version 2. Libraries were aligned to the reference genome and known small RNAs using Bowtie2. After stringent quality control we performed differential expression analyses using DESeq2, adjusting by age, sex, post‐mortem interval and methodological variables. Finally, we integrated the sRNA data with RNA‐seq data from the same samples to identify correlations with known AD genes.

Result

We identified four miRNAs and fifty‐six Piwi‐interacting RNAs (piRNAs) and one snoRNA that are significantly dysregulated in AD brains. We observed no significantly dysregulated tRNAs, suggesting that translational machinery was intact. We found significant positive correlation between miR‐6126 and miR‐3614‐3p, miR‐6126 and two piRNAs, as well as relationships among several piRNAs. Further, we identified dysregulated sRNAs that significantly correlate with AD genes such as APP, PSEN1, and PSEN2. For example, piR‐3746502 negatively correlates to over ten AD‐genes but associates with MS4A4A and TREM2 in the opposite direction of other AD genes, consistent with biological knowledge.

Conclusion

Our findings emphasize the importance of non‐coding RNAs in the pathobiology of AD. We showed that sRNAs beyond miRNAs contribute to AD and that large‐scale studies of sRNAs in brain are crucial to understand the regulation of the pathways involved in AD pathogenesis. Here, we described that several sRNAs involved in the regulation of known AD genes, with associations in the expected direction.
Assessment of RMTs for Discriminating Stages of Alzheimer’s Disease
Authors: Lentzen Manuel , Vairavan Srinivasan , Curcic Jelena , Atreya Alankar , Hinds Chris , Muurling Marijn , Conde Pauline , Grammatikopoulou Margarita , Lazarou Ioulietta , Nikolopoulos Spiros , Coello Neva , de Boer Casper , Aarsland Dag , Brem Anna‐Katharine , Fröhlich Holger ,   RADAR‐AD
Published: December 2023

Background

RADAR‐AD is a European project in the context of the Innovative Medicine Initiative (IMI) focusing on the earlier identification of patients at risk for developing Alzheimer’s Disease (AD) via a panel of remote monitoring technologies (RMTs), including smartphone apps and wearable devices.

Method

We examined the ability of 6 RMTs (Altoida, Axivity, Banking app, Fitbit, Physilog, and Mezurio) to distinguish between healthy controls (HC) and disease stages of preclinical (PreAD), prodromal (ProAD), and mild to moderate Alzheimer’s disease (MildAD) based on 175 patients (interim analysis). We trained three machine learning classifiers (Logistic Regression, Random Forest, and XGBoost) in a pairwise setting (HC vs. PreAD, HC vs. ProAD, HC vs. MildAD, PreAD vs. ProAD, and ProAD vs. MildAD). Since the interim dataset is still limited, we performed repeated, stratified nested cross‐validation to get a robust performance estimate. Each classifier was trained with the features of the different devices and a set of baseline variables. The latter include a patient’s gender, age, years of education, and body mass index (BMI) when physical conditions might play a role (Axivitiy, Fitbit, Physilog). In addition, we checked whether specific patterns of the study groups allowed discrimination of the different study groups based on the baseline variables alone. Therefore, we trained one Logistic Regression model with these variables and compared the performance of the other three models with this baseline. The models trained with the baseline and questionnaire‐based data served as the reference value in our benchmark that represents how well the discrimination of the different groups works with clinical tests.

Result

Our preliminary data show that RMTs can identify patients already in a prodromal disease stage (AUC ∼69%, Figure 1). Furthermore, the pairwise combination of data from a banking app and an app monitoring functional cognitive abilities via an augmented reality game slightly increased our model’s discriminative ability (Altoida ‐ Banking, Figure 2). The overall best performance was achieved when combining RMTs with the Amsterdam I‐ADL questionnaire.

Conclusion

Our results demonstrate the potential of RMTs and the Amsterdam I‐ADL questionnaire for identifying patients in prodromal stage in primary care settings.
Implementation of a 3‐Dimensional Embodied Conversational Agent to Support Neurologists in Conducting Cognitive Assessment in Alzheimer Patients
Authors: Sherimon Vinu , Sherimon P.C. , Nair Rahul V.
Published: December 2023

Background

Alzheimer’s disease is a universal medical and public health challenge. A timely identification of this ailment can enhance both the standard of care and the patient’s quality of life. Alzheimer’s diagnosis includes a critical component called cognitive assessment. These examinations have been carried out by neurologists, manually and digitally since the development of clinical neurological tests. But it’s obvious that integrating AI technologies into such assessments has many advantages. This research paper describes the implementation of a 3‐Dimensional Embodied Conversational Agent to support Neurologists in conducting cognitive assessments in Alzheimer patients.

Method

Twenty‐two questions are included in the assessment. The assessment checks different mental abilities of patients such as time orientation, place orientation, ability to recall things, concentration skills, language skills, ability to follow written and oral instructions, visual interpretation skills, etc. A score is given for each correct answer. A normal score must be higher than 24. A score of 24 or less is typically seen as abnormal and indicative of possible cognitive impairment further subject to detailed analysis of a neurologist as the result may occasionally be impacted by certain physical impairments, language or speech barriers, education level, or cultural differences.

The 3D agent was created using software such as Blender, iclone7, Adobe Photoshop, JavaScript, and MIT App Inventor. Text‐to‐speech synthesis algorithms were used to convert the questions to speech. The answers given by the user will be recognized using Natural Language Processing (NLP) algorithms. Correspondingly, a score will be awarded. TinyDB is used for local storage and CloudDB for web storage.

Result

The 3D agent receives the speech input, analyzes the input, and provides a vocal response. As per the total score, it will suggest suitable recommendations vocally. Also, an assessment report with the AI impression is generated.

Conclusion

The implementation of a 3‐D Embodied Conversational Agent to support Neurologists in conducting cognitive assessment is portrayed in this research. Instead of trying to replace clinicians, Artificial Intelligence aims to help them and make their tasks simpler.