AI, Robotics, and Clinical Research for Innovative Dementia Interventions: A Japanese-German Collaboration

After a successful international workshop in Karlsruhe, Germany in June 2023, transformative initiative is underway involving major institutions: the RIKEN Cognitive Behavioral Assistive Technology (CB-AT) Team in Japan, the Deutsches Zentrum für Neurodegenerative Erkrankungen (DZNE) Rostock/Greifswald, Rostock, the Forschungszentrum Informatik (FZI) and the Karlsruhe Institute of Technology, Institute for Information Processing Technology as well as the Institute for Entrepreneurship, Technology Management and Innovation. The unique strengths of these institutions unite in an interdisciplinary collaboration focusing on novel dementia interventions. This consortium envisions the future of dementia care and the prevention of its progress – a model that brings together the strengths of AI, robotics, digital platforms, and clinical research, not just targeting patients but considering dyadic interventions that support both patients and caregivers. The KIT and FZI from Karlsruhe bring to the table expertise in software and AI engineering, and experience in research transfer. Particularly crucial is the role of the METIS platform, which supports multi-stage treatment processes for neurodegenerative diseases in an outpatient setting, integrating modern wearables and AI personalization of treatment strategies. RIKEN CB-AT complements this with robotics and system integration capabilities, including access to robots ready for integration into care regimens. The institute is renowned for its speech intervention strategies in dementia prevention, fostering the idea of using robots to aid caregivers and patients alike. Ultimately, the robots could serve as a base station, actively engaging with caregivers, assessing their stress levels, and providing mitigation strategies while simultaneously collecting crucial data. DZNE Rostock/Greifswald rounds out the partnership with a robust clinical background and access to well-defined clinical cohorts. Their research provides valuable insights into patient needs. Furthermore, their proficiency in qualitative research and dyadic interventions adds an essential layer of complexity to the project. In this alliance, a shared ethos of participatory approach, modern digital and wearable technology adoption, and individualized intervention strategies enable a unified research vision. The potential outcomes are manifold: they include technologies for outpatient measurements of intervention, prevention and care, robots aiding caregivers and patients, digitalization of care pathways, stress mitigation, and more. All partners strive to establish bi-lateral connections between existing technology and new integrations, enabling data insights from a variety of sources, including smartwatches, smartphones, robots, novel technology, and caregiver-patient interactions. These insights can be used for the personalization of intervention and care, medication, early detection of emergency situations, and strategies to empower patients and enhance the resilience of caregivers. Once addressed, the opportunity for transformative early prevention of dementia progression are immense. The expected outcomes span joint research projects, scientific publications, societal impact, and entrepreneurial initiatives. In conclusion, this collaborative venture aspires to make strides in dementia care and intervention through the integrative use of platform-based AI, robotics, and clinical research, fostering an enhanced care ecosystem that values patients and caregivers

Implementation and evaluation of participatory advisory boards in mental health research: a research protocol of the ‘PART-Beirat’ project

Background The use of participatory research approaches in the field of dementia and forensic mental health research has been on the rise. Advisory board structures, involving people with lived experience (PWLE), have frequently been used for guiding and leading research. Yet, there has been limited guidance on the establishment, retention and use of advisory boards in the field of dementia and forensic mental health research. Objective This project outlined in this research protocol will investigate the benefits and challenges of establishing three patient advisory boards, involving PWLE, practitioners and researchers with the purpose to guide research. Data will be used to develop guidelines for best practice in involving PWLE in dementia and forensic mental health research through advisory boards. Methods The research project will be divided into three phases: Phase I will involve two topic-specific systematic reviews on the use of participatory research with PWLE, followed by an initial study exploring PWLE’s, practitioners’ and researchers’ expectations on research involvement. Phase II will consist of the establishment of three advisory boards, one focusing on dementia, one on forensic mental health and one overarching coordinating advisory board, which will involve PWLE from both fields. Phase III, will consist of interviews and focus groups with advisory board members, exploring any challenges and benefits of involving PWLE and practitioners in advisory boards for guiding research. To capture the impact of involving PWLE in different research phases and tasks, interviews and focus groups will be conducted at four different points of time (0, 6, 12, 18 months). Reflexive thematic analysis will be used for the analysis of data. Discussion The project aims to explore the involvement of PWLE and practitioners in guiding research and aims to develop guidelines for best practice in establishing and using patient advisory boards in dementia and forensic mental health research and involving PWLE and practitioners in research

Robust automated detection of microstructural white matter degeneration in Alzheimer’s disease using machine learning classification of multicenter DTI data

Diffusion tensor imaging (DTI) based assessment of white matter fiber tract integrity can support the diagnosis of Alzheimer’s disease (AD). The use of DTI as a biomarker, however, depends on its applicability in a multicenter setting accounting for effects of different MRI scanners. We applied multivariate machine learning (ML) to a large multicenter sample from the recently created framework of the European DTI study on Dementia (EDSD). We hypothesized that ML approaches may amend effects of multicenter acquisition. We included a sample of 137 patients with clinically probable AD (MMSE 20.6±5.3) and 143 healthy elderly controls, scanned in nine different scanners. For diagnostic classification we used the DTI indices fractional anisotropy (FA) and mean diffusivity (MD) and, for comparison, gray matter and white matter density maps from anatomical MRI. Data were classified using a Support Vector Machine (SVM) and a Naïve Bayes (NB) classifier. We used two cross-validation approaches, (i) test and training samples randomly drawn from the entire data set (pooled cross-validation) and (ii) data from each scanner as test set, and the data from the remaining scanners as training set (scanner-specific cross-validation). In the pooled cross-validation, SVM achieved an accuracy of 80% for FA and 83% for MD. Accuracies for NB were significantly lower, ranging between 68% and 75%. Removing variance components arising from scanners using principal component analysis did not significantly change the classification results for both classifiers. For the scanner-specific cross-validation, the classification accuracy was reduced for both SVM and NB. After mean correction, classification accuracy reached a level comparable to the results obtained from the pooled cross-validation. Our findings support the notion that machine learning classification allows robust classification of DTI data sets arising from multiple scanners, even if a new data set comes from a scanner that was not part of the training sample

Cognitive Trajectories in Preclinical and Prodromal Alzheimer's Disease Related to Amyloid Status and Brain Atrophy:A Bayesian Approach

Background: Cognitive decline is a key outcome of clinical studies in Alzheimer’s disease (AD). Objective: To determine effects of global amyloid load as well as hippocampus and basal forebrain volumes on longitudinal rates and practice effects from repeated testing of domain specific cognitive change in the AD spectrum, considering non-linear effects and heterogeneity across cohorts. Methods: We included 1,514 cases from three cohorts, ADNI, AIBL, and DELCODE, spanning the range from cognitively normal people to people with subjective cognitive decline and mild cognitive impairment (MCI). We used generalized Bayesian mixed effects analysis of linear and polynomial models of amyloid and volume effects in time. Robustness of effects across cohorts was determined using Bayesian random effects meta-analysis. Results: We found a consistent effect of amyloid and hippocampus volume, but not of basal forebrain volume, on rates of memory change across the three cohorts in the meta-analysis. Effects for amyloid and volumetric markers on executive function were more heterogeneous. We found practice effects in memory and executive performance in amyloid negative cognitively normal controls and MCI cases, but only to a smaller degree in amyloid positive controls and not at all in amyloid positive MCI cases. Conclusions: We found heterogeneity between cohorts, particularly in effects on executive functions. Initial increases in cognitive performance in amyloid negative, but not in amyloid positive MCI cases and controls may reflect practice effects from repeated testing that are lost with higher levels of cerebral amyloid

Harmonizing neuropsychological assessment for mild neurocognitive disorders in Europe

INTRODUCTION Harmonized neuropsychological assessment for neurocognitive disorders, an international priority for valid and reliable diagnostic procedures, has been achieved only in specific countries or research contexts. METHODS To harmonize the assessment of mild cognitive impairment in Europe, a workshop (Geneva, May 2018) convened stakeholders, methodologists, academic, and non-academic clinicians and experts from European, US, and Australian harmonization initiatives. RESULTS With formal presentations and thematic working-groups we defined a standard battery consistent with the U.S. Uniform DataSet, version 3, and homogeneous methodology to obtain consistent normative data across tests and languages. Adaptations consist of including two tests specific to typical Alzheimer's disease and behavioral variant frontotemporal dementia. The methodology for harmonized normative data includes consensus definition of cognitively normal controls, classification of confounding factors (age, sex, and education), and calculation of minimum sample sizes. DISCUSSION This expert consensus allows harmonizing the diagnosis of neurocognitive disorders across European countries and possibly beyond

Relevance of Minor Neuropsychological Deficits in Patients With Subjective Cognitive Decline

peer reviewed[en] BACKGROUND AND OBJECTIVES: To determine the relevance of minor neuropsychological deficits (MNPD) in patients with subjective cognitive decline (SCD) with regard to CSF levels of Alzheimer disease (AD) biomarkers, cognitive decline, and clinical progression to mild cognitive impairment (MCI). METHODS: This study included patients with clinical SCD and SCD-free, healthy control (HC) participants with available baseline CSF and/or longitudinal cognitive data from the observational DZNE Longitudinal Cognitive Impairment and Dementia study. We defined MNPD as a performance of at least 0.5SD below the mean on a demographically adjusted total score derived from the Consortium to Establish a Registry for Alzheimer's Disease neuropsychological assessment battery. We compared SCD patients with MNPD and those without MNPD with regard to CSF amyloid-β (Aβ)42/Aβ40, phosphorylated tau (p-tau181), total tau and Aβ42/p-tau181 levels, longitudinal cognitive composite trajectories, and risk of clinical progression to incident MCI (follow-up M ± SD: 40.6 ± 23.7 months). In addition, we explored group differences between SCD and HC in those without MNPD. RESULTS: In our sample (N = 672, mean age: 70.7 ± 5.9 years, 50% female), SCD patients with MNPD (n = 55, 12.5% of SCD group) showed significantly more abnormal CSF biomarker levels, increased cognitive decline, and a higher risk of progression to incident MCI (HR: 4.07, 95% CI 2.46-6.74) compared with SCD patients without MNPD (n = 384). MNPD had a positive predictive value of 57.0% (95% CI 38.5-75.4) and a negative predictive value of 86.0% (95% CI 81.9-90.1) for the progression of SCD to MCI within 3 years. SCD patients without MNPD showed increased cognitive decline and a higher risk of incident MCI compared with HC participants without MNPD (n = 215; HR: 4.09, 95% CI 2.07-8.09), while AD biomarker levels did not differ significantly between these groups. DISCUSSION: Our results suggest that MNPD are a risk factor for AD-related clinical progression in cognitively normal patients seeking medical counseling because of SCD. As such, the assessment of MNPD could be useful for individual clinical prediction and for AD risk stratification in clinical trials. However, SCD remains a risk factor for future cognitive decline even in the absence of MNPD

Association of latent factors of neuroinflammation with Alzheimer's disease pathology and longitudinal cognitive decline

INTRODUCTION: We investigated the association of inflammatory mechanisms with markers of Alzheimer's disease (AD) pathology and rates of cognitive decline in the AD spectrum.METHODS: We studied 296 cases from the Deutsches Zentrum für Neurodegenerative Erkrankungen Longitudinal Cognitive Impairment and Dementia Study (DELCODE) cohort, and an extension cohort of 276 cases of the Alzheimer's Disease Neuroimaging Initiative study. Using Bayesian confirmatory factor analysis, we constructed latent factors for synaptic integrity, microglia, cerebrovascular endothelial function, cytokine/chemokine, and complement components of the inflammatory response using a set of inflammatory markers in cerebrospinal fluid.RESULTS: We found strong evidence for an association of synaptic integrity, microglia response, and cerebrovascular endothelial function with a latent factor of AD pathology and with rates of cognitive decline. We found evidence against an association of complement and cytokine/chemokine factors with AD pathology and rates of cognitive decline.DISCUSSION: Latent factors provided access to directly unobservable components of the neuroinflammatory response and their association with AD pathology and cognitive decline.</p

Amyloid pathology but not APOE ε4 status is permissive for tau-related hippocampal dysfunction

We investigated whether the impact of tau-pathology on memory performance and on hippocampal/medial temporal memory function in non-demented individuals depends on the presence of amyloid pathology, irrespective of diagnostic clinical stage. We conducted a cross-sectional analysis of the observational, multicentric DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE). Two hundred and thirty-five participants completed task functional MRI and provided CSF (92 cognitively unimpaired, 100 experiencing subjective cognitive decline and 43 with mild cognitive impairment). Presence (A+) and absence (A-) of amyloid pathology was defined by CSF amyloid-β42 (Aβ42) levels. Free recall performance in the Free and Cued Selective Reminding Test, scene recognition memory accuracy and hippocampal/medial temporal functional MRI novelty responses to scene images were related to CSF total-tau and phospho-tau levels separately for A+ and A- individuals. We found that total-tau and phospho-tau levels were negatively associated with memory performance in both tasks and with novelty responses in the hippocampus and amygdala, in interaction with Aβ42 levels. Subgroup analyses showed that these relationships were only present in A+ and remained stable when very high levels of tau (>700 pg/ml) and phospho-tau (>100 pg/ml) were excluded. These relationships were significant with diagnosis, age, education, sex, assessment site and Aβ42 levels as covariates. They also remained significant after propensity score based matching of phospho-tau levels across A+ and A- groups. After classifying this matched sample for phospho-tau pathology (T-/T+), individuals with A+/T+ were significantly more memory-impaired than A-/T+ despite the fact that both groups had the same amount of phospho-tau pathology. ApoE status (presence of the E4 allele), a known genetic risk factor for Alzheimer's disease, did not mediate the relationship between tau pathology and hippocampal function and memory performance. Thus, our data show that the presence of amyloid pathology is associated with a linear relationship between tau pathology, hippocampal dysfunction and memory impairment, although the actual severity of amyloid pathology is uncorrelated. Our data therefore indicate that the presence of amyloid pathology provides a permissive state for tau-related hippocampal dysfunction and hippocampus-dependent recognition and recall impairment. This raises the possibility that in the predementia stage of Alzheimer's disease, removing the negative impact of amyloid pathology could improve memory and hippocampal function even if the amount of tau-pathology in CSF is not changed, whereas reducing increased CSF tau-pathology in amyloid-negative individuals may not proportionally improve memory function