Ludwig-Maximilians-Universität in Munich

Helical aromatic oligoamide foldamers bearing anionic side chains that mimic the overall shape and charge surface distribution of DNA were synthesized. Their interactions with chromosomal protein Sac7d, a non‐sequence‐selective DNA‐binder that kinks DNA, were investigated by Surface Plasmon Resonance (SPR), Isothermal Titration Calorimetry (ITC), Circular Dichroism spectroscopy (CD), melting curve analysis, Atomic Force Microscopy (AFM), and Nuclear Magnetic Resonance (NMR), as well as by single crystal X‐ray crystallography. The foldamers were shown to bind to Sac7d better than a DNA duplex of comparable length. The interaction is diastereoselective and takes place at the DNA binding site. Crystallography revealed that the DNA mimic foldamers have a binding mode of their own and that they can bind to Sac7d without being kinked.

Perfluorinated compounds (PFCs) are emerging environmental pollutants characterized by their extreme stability and resistance to degradation. Among them, tetrafluoromethane (CF4) is the simplest and most abundant PFC in the atmosphere. However, the highest C─F bond energy and its highly symmetrical structure make it particularly challenging to decompose. In this work, a yolk–shell Al2O3 micro‐reactor is developed to enhance the catalytic hydrolysis performance of CF4 by creating a local autothermic environment. Finite element simulations predict that the yolk–shell Al2O3 micro‐reactor captures the heat released during the catalytic hydrolysis of CF4, resulting in a local autothermic environment within the yolk–shell structure that is 50 °C higher than the set temperature. The effectiveness of this local autothermic environment is experimentally confirmed by in situ Raman spectroscopy. As a result, the obtained yolk–shell Al2O3 micro‐reactor achieves 100% CF4 conversion at a considerably low temperature of 580 °C for over 150 h, while hollow and solid Al2O3 structures required higher temperatures of 610 and 630 °C, respectively, to achieve the same conversion rate, demonstrating the potential of yolk–shell Al2O3 micro‐reactor to significantly reduce the energy requirements for PFCs degradation and contribute to more sustainable and effective environmental remediation strategies.

Many visualisations used in the climate communication field aim to present the scientific models of climate change to the public. However, relatively little research has been conducted on how such data are visually processed, particularly from a behavioural science perspective. This study examines trends in visual attention to climate change predictions in world maps using mobile eye-tracking while participants engage with the visualisations. Our primary aim is to assess engagement with the maps, as indicated by gaze metrics. Secondary analyses assess whether social context (as social viewing compared to solitary viewing) affects these trends, the relationship between projection types and visual attention, compare gaze metrics between scientific map and artwork viewing, and explore correlations between self-reported climate anxiety scores and attention patterns. We employed wearable, head-mounted eye-tracking to collect data in relatively naturalistic conditions, aiming to enhance ecological validity. In this research, participants engaged with ten world maps displaying near- and far-term climate projections across five data categories, adapted from the online interactive atlas provided by the International Panel on Climate Change (IPCC). To compare scientific information processing with aesthetic perception, participants also viewed two large-scale artworks. Responses to the Climate Change Anxiety Scale (CCAS) were also collected. Participants viewed the displays alone (single-viewing condition, N = 35) or together with a partner (paired-viewing condition, N = 12). Results revealed that the upper parts of the maps, particularly the continental Europe, received significant attention, suggesting a Euro-centric bias in viewing patterns. Spatial gaze patterns were similar between single and paired conditions, indicating that the visual attributes of the maps predominantly shaped attention locations. Although dwell times were comparable, the paired condition showed higher fixation counts, shorter average fixation durations, and longer scanpaths, suggesting a potentially dissociable viewing strategy and more exploratory viewing patterns influenced by social interaction. No substantial differences were observed in attention across projection timeframes or types, although individual variations were noted. Artwork viewing exhibited notably shorter average fixation durations compared to climate map viewing, potentially reflecting different visual engagement styles. Despite positive linear correlations among the four CCAS subscales, there was no apparent correlation between CCAS scores and main gaze metrics, indicating a lack of a direct relationship between self-reported anxiety and gaze behaviour. In summary, visual attention to climate change visualisations appears to be mainly influenced by the inherent visual attributes of the maps, but the social context may subtly influence visual attention. Additionally, the comparison with aesthetic viewing highlights relatively distinct attentional patterns in scientific versus aesthetic engagements.

RNA is an information‐carrying molecule that instructs protein synthesis, but it also functions as a catalyst in so‐called ribozymes. Here, we study this multifunctional character using a dynamic combinatorial library powered by chemical fuel. On the one hand, we demonstrate that RNA templates the oligomerization and inhibits deoligomerization. On the other hand, we show that RNA can be a structural element in the formation of hydrogels. Moreover, in its hydrogel, RNA degradation by nucleases is accelerated. Thus, templates have a role beyond blueprints, protectors, and selectors. Template‐oligomer interactions can create new (micro)environments that might affect evolutionary dynamics.

Fluoromethyl triflate (superfluoromethyl, SFM, FH2COSO2CF3) and fluoromethyl fluorosulfonate (magic fluoromethyl, MFM, FH2COSO2F) are two easily synthesized, highly effective and non‐ozone depleting fluoromethylation reagents. They are analogous to the well‐known and widely used methylation reagents H3COSO2CF3 and H3COSO2F. Both SFM and MFM have been fully characterized by multinuclear NMR spectroscopy (¹H, ¹³C, ¹⁷O, ¹⁹F, ³³S). Their structures have been determined in the solid state on in situ grown crystals by X‐ray diffraction and in the gas phase by electron diffraction. The fluoromethylation efficiency of SFM and MFM was shown by reactions with chalcogen nucleophiles of differing nucleophilicity. All fluoromethylated products were isolated as pure compounds and characterized by NMR and vibrational spectroscopy, as well as in some cases by single crystal X‐ray diffraction.

Hintergrund Die chronische spontane Urtikaria (CSU) beeinträchtigt die Lebensqualität der Patienten erheblich. Trotz Fortschritten bei Diagnose und Therapie ist die Behandlung immer noch unzureichend. Die Telemedizin bietet eine vielversprechende Lösung zur Verbesserung der Behandlung. Diese Pilotstudie bewertet die Akzeptanz und Nutzung eines digitalen Gesundheitskonzepts für die CSU, untersucht dessen Auswirkungen auf das Krankheitsmanagement und zeigt technische Herausforderungen auf. Patienten und Methodik In diese prospektive Pilotstudie wurden CSU-Patienten einer Universitätsklinik in Deutschland einbezogen. Über einen Zeitraum von 12 Monaten interagierten die Teilnehmer mit Ärzten über eine telemedizinische Plattform, welche die studienspezifische Intervention darstellte. Nach jeder dreimonatigen digitalen Visite wurden die Symptome und die Lebensqualität anhand von digitalen patientenberichteten Ergebnissen (ePROs) und Online-Fragebögen bewertet. Am Ende bewerteten Patienten und Ärzte die allgemeine Zufriedenheit, die Benutzerfreundlichkeit der Plattform und die technischen Herausforderungen. Ergebnisse 24 Patienten nahmen an der Studie teil. Die Mehrheit (92%) gab an, dass das digitale Konzept eine vielversprechende Alternative zu herkömmlichen Beratungsgesprächen sein könnte. Die Analyse von Beginn Ende der Studie ergab, dass die Krankheitskontrolle stabil blieb, während sich die Lebensqualität verbesserte. Alle Ärzte empfanden die digitale Anwendung als zuverlässig und zeitsparend. Schlussfolgerungen Diese Pilotstudie zeigt die Machbarkeit und hohe Akzeptanz eines digitalen Gesundheitskonzepts für das Management von CSU. Weitere Forschungen mit größeren Kohorten sind erforderlich, um eine breitere Anwendbarkeit zu ermitteln.

Numerous drugs (including disease‐modifying therapies, cognitive enhancers and neuropsychiatric treatments) are being developed for Alzheimer’s and related dementias (ADRD). Emerging neuroimaging modalities, and genetic and other biomarkers potentially enhance diagnostic and prognostic accuracy. These advances need to be assessed in real‐world studies (RWS). Currently, there are several national and two emerging international ADRD registries that differ in their data requirements. For instance, most existing registries do not routinely capture safety data. Outcome harmonisation would facilitate collaboration between international and national registries and, in turn, support interoperability, and enhance the statistical power and external validity of RWS. In response, the International Registry for Alzheimer’s Disease and other Dementias (InRAD) convened a Steering Committee of leaders and investigators from registries in Europe, Asia and Australia to define a harmonised minimum dataset (MDS) and extended dataset (EDS) that enables collaboration. A wider stakeholder group, including patient representatives, regulators, payors and industry, will validate the agreed MDS and EDS (Figure 1). The harmonised MDS and EDS will form the basis of data captured in InRAD, which can also form the foundation of collaboration in future RWS within and across registries (Figures 2 and 3). The harmonised MDS and EDS reflect the needs of two user levels. Firstly, the MDS and EDS should inform differential diagnosis and clinical decision making by presenting longitudinal data in a graphical dashboard summarising important outcomes at the point of care. The harmonised MDS will encompass demographics, functional and cognitive instruments, and rating scales. The harmonised EDS can answer specific questions and/or include additional functional and cognitive instruments to, for example, reflect local clinical practice and patient‐reported outcomes. Secondly, harmonised MDS and EDS facilitate collaboration between registries to, for example, benchmark, assess efficacy and important safety outcomes, and to inform health technology assessments. The harmonised data sets will be as lean as practical, undergo comprehensive beta‐testing by InRAD and the results shared with stakeholders. The presentation will explore the background to and need for data harmonisation across registries, the latest iteration of the harmonised MDS and EDS, and InRAD’s overall progress.

Background Positron emission tomography (PET) imaging with [¹⁸F]flortaucipir allows for in‐vivo visualization of aggregated tau in Alzheimer’s disease (AD). The FDA‐approved label for [¹⁸F]flortaucipir PET provides a standardized, clinically applicable definition of tau‐PET positivity by visual interpretation. Here, we studied the concordance between this clinically approved definition of tau PET positivity and a recently proposed universal scale—CenTauR—for the standardized quantification of abnormal tau aggregates. Method We included 1849 participants (cognitively unimpaired [CU] and impaired [CI, MCI or AD dementia]) from four cohorts (A4 study, ADNI, OASIS‐3, and HABS) with available [¹⁸F]flortaucipir PET (mean age: 72.2 y, 55% females). Three trained readers scored each [¹⁸F]flortaucipir PET scan as positive/negative using an FDA‐approved visual interpretation method. Visual reads were compared to [¹⁸F]flortaucipir PET quantification using the Universal CenTauRz scale. Specifically, we analysed concordance by 1) performing a receiver operating characteristic (ROC) curve analysis of continuous CenTauRz (CTRz) values discriminating between positive/negative visual reads; and 2) computing sensitivity and specificity when using a previously proposed cut‐point of 2 CTRz. Result Concordance between visual interpretation and continuous CTRz measures was limited (AUC = 0.82 for CU and AUC = 0.87 for CI, Figure 1). When using a previously proposed cut‐point of 2 CTRz, this quantitative approach yielded a sensitivity of 49% [95% CI, 42% to 57%] and a specificity of 95% [93% to 96%] in CU individuals and a sensitivity of 73% [95% CI, 66% to 79%] and a specificity of 94% [95% CI, 90% to 96%] in CI individuals. Visual‐positive, CenTauRz‐negative individuals were more frequently Aβ‐positive than visual‐negative, CenTauRz‐positive individuals (87% vs 48%, p<0.001). Conclusion Visual interpretation of [¹⁸F]flortaucipir PET images and quantification using the universal CenTauRz scale exhibited limited agreement, particularly among CU individuals. Tau‐PET positivity based on visual interpretation aligns better with the presence of Aβ‐pathology. Visual interpretation seems to be more sensitive to early tau aggregation compared to universal CenTauRz quantification. Future analyses will compare clinical outcomes associated to each definition of tau‐PET positivity.

Background Memory clinic patients typically present with Alzheimer’s disease (AD) and cerebral small vessel disease (SVD) to varying degrees. Therefore, it is crucial to determine the etiology of cognitive deficits for facilitating patient‐centered treatment in memory clinics. Plasma biomarkers (ptau217, Glial Fibrillary Acidic Protein [GFAP], Neurofilament light chain [NfL]) and fixel‐based advanced diffusion MRI markers (fiber density, fiber‐bundle cross‐section) show potential towards disentangling AD‐ and SVD‐related brain changes (Dewenter et al., Brain, 2023). However, their predictive power in understanding heterogeneous and SVD/AD‐specific cognitive deficits in memory clinic patients remains incomplete. We assessed i) how plasma‐based and fixel markers explain AD‐typical and SVD‐typical cognitive deficits and ii) their interrelation to uncover disease‐specific mechanisms. Method We included n = 76 in‐house memory clinic patients with Simoa‐based plasma ptau217, GFAP and NfL assessments, comprehensive neuropsychological testing (CERAD‐plus battery) and 3T MRI. Global white matter hyperintensity (WMH) volume and average skeletonized mean diffusivity (MD) were included as well‐established SVD markers. AD severity was probed through plasma ptau217 and cortical thickness of the pre‐established AD signature ROI. Advanced diffusion MRI was used to assess fiber density and fiber bundle cross‐section of key white matter tracts (Fig. 1A). Result Using linear regression, increased ptau217, reduced cortical thickness in AD signature ROI and fiber‐bundle cross‐section were highly associated with impaired episodic memory, i.e. a typical AD‐related symptom (Fig.1B, Fig.2A). In contrast, GFAP and NfL increases and reductions in MSMD and fiber density were associated with executive dysfunction, a typical sign of SVD‐related cognitive impairment (Fig.1B, Fig.2A). Additionally, fiber density was associated with GFAP and NfL levels, while fiber bundle‐cross section, a macroscopic marker of tract atrophy, was not associated with any of the plasma markers (Fig.2B). Conclusion Ptau217 displayed high sensitivity and specificity for AD‐typical memory impairment, whereas GFAP and NfL were associated with SVD‐typical processing speed and executive impairment. Additionally, fiber density, a pre‐established imaging marker for SVD, was associated with GFAP and NfL. This highlights the effectiveness of these markers in distinguishing and characterizing SVD and AD in memory clinic patients and emphasizes the importance of considering concomitant SVD in patients with elevated GFAP and NfL levels.

Background Analysis of neuroimaging data based on convolutional neural networks (CNNs) can improve detection of clinically relevant characteristics of patients with Alzheimer’s disease (AD). Previously, our group developed a CNN‐based approach for detecting AD via magnetic resonance imaging (MRI) scans and for identifying features that are relevant to the decision of the network. In the current study, we aimed to evaluate the potential utility of applying this approach to MRI scans to assist in the identification of individuals at high risk for amyloid positivity to aid in the selection of study samples and case finding for treatment. Method In the current analysis, we have trained a CNN to detect amyloid positivity using MRI scans from 1461 Alzheimer’s Disease Neuroimaging Initiative (ADNI) participants (498 cognitively normal participants, 103 participants with significant memory concern, 640 participants with mild cognitive impairment, and 220 participants with AD dementia). Amyloid positivity was assessed via amyloid PET scans obtained with [18F]florbetapir or [18F]florbetaben and quantified on a Centiloid scale. A threshold of 24.1 CL categorized 46% of participants as amyloid‐positive. The modeling approach was evaluated using 10‐fold cross‐validation, the number of epochs in training was set to 10. Result For each of 10 cross‐validation folds, we selected a model state corresponding to an epoch showing best performance in the validation partition. Balanced accuracy across these models ranged from 0.62 to 0.72 with an average of 0.68 (SD = 0.03). Conclusion We used a previously established approach to train CNNs for detecting amyloid positivity using MRI scans. Such models, particularly when tuned to have low rates of false negatives, have a potential to enhance identification of patients who would benefit from more in‐depth assessments, which could then inform antibody treatment. We are conducting ongoing work to improve and characterize the modeling approach, including evaluation of relevance maps which indicate importance of brain regions for detecting amyloid positivity. Future work will evaluate the role of amyloid positivity threshold selection. Planned analyses also include validation in independent data such as the German DZNE ‐ Longitudinal Cognitive Impairment and Dementia Study (DELCODE) dataset.

Background Lewy body pathology consisting of aggregated alpha‐Synuclein (a‐Syn) is the hallmark pathology in Parkinson’s disease, yet a‐Syn aggregates are also commonly observed post‐mortem as a co‐pathology in Alzheimer’s disease (AD) patients. Preclinical research has shown that a‐Syn can amplify Ab‐associated tau seeding and aggregation, hence a‐Syn co‐pathology may contribute to the Ab‐induced progression of tau pathology in AD. To address this, we combined a novel CSF‐based RT‐QuIC seed‐amplification assay to determine a‐Syn positivity, with PET‐neuroimaging in a large patient cohort ranging from cognitively normal to dementia, to determine whether a‐Syn co‐pathology accelerates Ab‐driven tau accumulation. Method In 261 Ab‐positive vs. 272 Ab‐negative subjects ranging from cognitively normal to dementia we employed amyloid‐PET, Flortaucipir tau‐PET and a CSF‐based a‐Syn RT‐QuIC assay for in vivo detection of abnormal a‐Syn aggregation. A subset of 136 Ab‐positive vs. 102 Ab‐negative subjects had longitudinal tau‐PET across ∼2.5years. Using linear regression, we tested whether a‐Syn positivity was linked to stronger Ab‐related tau aggregation (i.e. interaction a‐Syn x amyloid‐PET on tau‐PET). Result Prevalence of a‐Syn positivity rose across increasing clinical severity and was particularly pronounced in Ab+ (i.e. CN/MCI/Dementia=20/23/47%) vs. Ab‐ subjects (i.e. CN/MCI/Dementia=15/10/29%), suggesting that a‐Syn co‐pathology is more common in clinically advanced AD (chi‐squared‐test, p<0.001). When testing the interaction between a‐Syn and global amyloid‐PET, we found that a‐Syn positivity was associated with stronger Ab‐related tau deposition (Figure 1A, p<0.001), and faster Ab‐related tau accumulation rates (Figure 1B, p=0.010) in typical tau vulnerable brain regions (i.e. temporal meta ROI), adjusting for age and sex. Regional analyses confirmed that higher regional amyloid‐PET was associated with stronger temporal‐lobe tau deposition (Figure 2A) and faster tau accumulation in downstream regions (Figure 2B) in a‐Syn positive individuals. In addition, there was an independent effect of a‐Syn positivity on faster temporal lobe tau accumulation rates controlling for age, sex and global amyloid, suggesting that a‐Syn may also independently contribute to tau aggregation (Figure 3). Conclusion a‐Syn co‐pathology as detected by CSF seed‐amplification assays is more common at clinically advanced AD and related to faster Ab‐related tau aggregation. This suggests that a‐Syn co‐pathology may actively contribute to AD‐related tau accumulation and therefore contribute to dementia development.

Background Cavum Septum Pellucidum [CSP] is commonly observed on neuroimaging in individuals exposed to repetitive head impacts [RHI] and in post‐mortem examination in Chronic Traumatic Encephalopathy [CTE]. A CSP is proposed as a potential biomarker for CTE, yet prevalence across neurodegenerative diseases and its clinical implications are largely unknown. We assessed CSP prevalence and clinical associations in RHI‐exposed individuals in comparison to veterans with a history of traumatic brain injury [TBI], individuals with a neurodegenerative disease (i.e. Alzheimer’s Disease [AD] or Frontotemporal dementia [FTD]) and Cognitively Unimpaired individuals [CU]. Method The group‐of‐interest, i.e., individuals exposed to RHI in contact sports or military service (n = 66), was compared against age‐ and sex‐matched ADNI‐DOD participants with TBI (n = 62) and non‐exposed participants of the Amsterdam Dementia Cohort (AD, n = 30; FTD, n = 25; CU, n = 25). Structural 3D brain MRI scans were visually rated on CSP grade (ranging 0‐4, Figure 1) according to established criteria by two independent raters without access to clinical information. A CSP scored at least grade 2 was considered abnormal. If scores between raters differed, scans were discussed to reach consensus. Inter‐rater reliability was assessed with Cohens’ weighted Kappa (κ). We investigated group differences in CSP grade as well as associations between CSP grade and neuropsychiatric symptoms (using the Neuropsychiatric Inventory [NPI]) and CTE probability (using the Traumatic Encephalopathy Syndrome [TES] criteria). Result Inter‐rater reliability was substantial (κ = 0.712). Prevalence of an abnormal CSP differed between groups (χ2 = 11.72, p = .020). An abnormal CSP was observed most often in the RHI group (43%), followed by TBI (31%, OR = 0.589, p = .158), and significantly less in AD (16%, OR = 0.255, p = .014), FTD (17%, OR = 0.267, p = .029), and SCD (14%, OR = 0.222, p = .012) compared to RHI (Figure 2). Across groups, CSP grade was not associated with severity of neuropsychiatric symptoms (F = 1.7, p = 0.151). An abnormal CSP was observed more in RHI‐exposed individuals with probable (57%) or possible (55%) CTE compared to suggestive of CTE (36%) or no TES (36%). Conclusion A CSP was more prevalent in RHI‐exposed individuals and veterans with TBI compared to patients with a neurodegenerative disease or CU individuals. Presence of a CSP on MRI may be indicative of head impact exposure, especially repetitive impacts.

Background Understanding modulators of Alzheimer's disease’s (AD) progression is crucial for determining optimal treatment windows and targets. Apolipoprotein E e4 (ApoE4), i.e. a key AD risk factor, is associated with earlier tau accumulation at lower Aß levels (Steward et al. 2023), yet, the mechanisms driving this connection remain unclear. Thus, we assessed whether ApoE4 accelerates initial Aß‐related tau secretion measurable in CSF or subsequent tau aggregation as determined via PET (Figure 1A). Method We combined cross‐sectional CSF measures of phosphorylated tau (p‐tau181) and Aß‐PET in 287 APOE genotyped non‐demented (cognitively normal [CN]; mildly cognitively impaired [MCI]) ADNI participants. P‐tau181 was adjusted to Aß40 to account for inter‐individual variability in CSF protein concentrations. Using linear regression, we investigated i) whether ApoE4 was related to accelerated Aß‐related p‐tau secretion (i.e., Aß‐PET by ApoE4 interaction on p‐tau181), ii) whether ApoE4 accelerated the p‐tau‐induced fibrillisation of tau (i.e. p‐tau181 by ApoE4 interaction on tau‐PET) and iii) whether regional effects of ApoE4 on p‐tau‐related tau fibrillisation were associated with ApoE4 mRNA expression levels. Result ApoE4 did not moderate the relationship between Aß‐PET and p‐tau181 (Figure 1B, p=0.76) but strengthened the effect of p‐tau181 on global Tau‐PET increase (Figure 1C, ß=0.7, p<0.001). At the regional level, this ApoE4 x p‐tau181 interaction on tau‐PET was correlated with regional APOE mRNA expression in CN (Figure 2B, r=0.5, pspin<0.001), but not in MCI (p=0.141), suggesting that ApoE4 drives earliest p‐tau‐induced tau aggregation. Supporting this further, we found that the regional effect of p‐tau181 on Tau‐PET was more strongly correlated with APOE mRNA expression in CN ApoE4 carriers (Figure 2C, r=0.54, pspin<0.001) than in CN non‐carriers (r=0.4, pspin=0.05). Lastly, we confirmed that the effect of Aß on tau aggregation is mediated by p‐tau increases (Figure 1D, ACME: B=0.28; p<0.001; ADE: B=0.206; p=0.008) which is strengthened in ApoE4 carriers (B=0.21, p=0.006). Conclusion ApoE4 promotes p‐tau‐induced tau aggregation, particularly in early disease stages and in regions that express high APOE. This suggests that ApoE4 can trigger earlier Aß‐related tau spreading most likely due to facilitated p‐tau induced tau aggregation. This suggests that preventing soluble p‐tau increases may attenuate tau aggregation and therefore dementia.

Background Differences in task‐fMRI activation have recently been found to be related to neuropathological hallmarks of AD. However, the evolution of fMRI‐based activation throughout AD disease progression and its relationship with other biomarkers remains elusive. Applying a disease progression model (DPM) to a multicentric cohort with up to four annual task‐fMRI visits, we hope to provide a deeper insight into these relationships. Method We estimated AD disease stages using a multivariate Gaussian Process (GP) DPM including CSF‐Aß42/40 ratio, CSF‐p‐tau181, hippocampal and entorhinal volume, ADAS13‐Cog sum and PACC5 scores. Disease stages from 493 participants with longitudinal task‐fMRI measurements from DELCODE (165 healthy controls (CN), 214 participants with SCD, 82 with MCI, 32 with suspected AD) were obtained. We derived subsequent memory and novelty contrasts from a visual memory encoding task using general linear modeling (GLM). Contrasts from all available follow‐ups were then submitted to voxel‐based group‐level GLM analyses. Activations from resulting disease‐stage‐related clusters were (1) used to estimate cluster‐level trajectory curves over disease stages using smoothing splines and (2) submitted to linear‐mixed effects models to test longitudinal changes over follow‐ups. Result Our DPM‐derived disease stages were associated with clinical groups, fMRI performance and white matter lesions (Figure 1C‐F). Generally, in both contrasts, activation increases were observed in task‐negative clusters while activation decreases were observed in task‐positive clusters (Figure 2C‐F). We did not find indications for inverted u‐shaped associations between disease stage and activation in whole brain voxel‐wise cross‐sectional analyses. However, smoothing splines revealed non‐linear monotonically increasing biomarker abnormality for task‐negative areas, showing earliest changes towards the beginning of disease progression. After a plateau, fMRI activation increases in abnormality conjointly with volume changes. For task‐positive areas, we observed linear relationships with disease stages (Figure 3). Activation changes over follow‐ups were not associated with disease stages. Conclusion Biomarker abnormality timing in our DPM reflected hypothetical AD progression. Changes in task‐fMRI activation and deactivation were both associated with progression towards AD. Smoothing spline fits indicated abnormality changes in task‐fMRI activation to begin in the earliest phases of the disease. Findings can be discussed as differential pathophysiological processes such as complex reorganization and neural noise.

Background Neuroimaging studies have revealed age and sex‐specific differences in Alzheimer’s disease (AD) trajectories. However, how age and sex modulate tau spreading remains unclear. Thus, we investigated how age and sex modulate the amyloid‐beta (Aß)‐induced accumulation and spreading of tau pathology from local epicenters across connected brain regions. Method We included 313 ADNI participants (female/male, n=167/146), i.e. 110 cognitively normal (CN) Aß‐negative, and 203 Aß‐positive subjects across the AD spectrum (i.e. CN/MCI/Dementia, n=98/70/35) with baseline amyloid‐PET and longitudinal Flortaucipir tau‐PET. Annual tau‐PET change rates for 200 cortical regions of the Schaefer atlas were calculated. Sex‐specific resting‐state fMRI‐connectivity templates across the 200 Schaefer regions were determined in independent Aß‐negative controls (female/male, n=118/82) to determine the connectivity of tau epicenters to the rest of the brain. Using linear regression, we investigated interactions between age, sex and Aß on tau accumulation and spread, controlling for APOE4‐status and diagnosis. Result Higher Aß (i.e. centiloid) predicted faster tau accumulation, where this association was pronounced in younger individuals (i.e. age x centiloid interaction, b=‐3.64, p<0.001, Figure 1A). This age x centiloid interaction was stronger in men (b=‐4.82, p<0.001, Figure 1B) vs. women (b=‐1.67, p=0.029, Figure 1C), suggesting that younger age promotes Aß‐related tau accumulation predominantly in men. Bootstrapping analysis further confirmed this effect (Figure 1D). In Aß+, epicenters with highest baseline tau‐PET showed a similar temporal‐lobe distribution in men and women (Figure 2A&B), yet epicenter connectivity to the rest of the brain was stronger in men vs. women (Figure 2C). Stronger connectivity of tau epicenters to the rest of the brain was linked to faster tau accumulation especially in younger Aß+ subjects (i.e. interaction age x epicenter connectivity, b= 4.41, p<0.001, Figure 3A). However, this effect was clearly driven by men (b=6.13, p<0.001, Figure 3B) and not observed when tested in women only (b=1.55, p=0.252, Figure 3C). Conclusion Aß drives faster tau accumulation and this effect is particularly strong at younger age and even further pronounced in men, whose tau epicenters are more densely interconnected with the rest of the brain. Together, age and sex have clear modulating effects on tau spreading, and heterogeneous AD trajectories may be partly arisen due to sex‐specific differences in brain network architecture.

Background The myelin sheath around axons is of fundamental importance for signal transduction. Myelin is reduced in white matter hyperintensities (WMH), which occur in both small vessel disease (SVD) and Alzheimer’s disease (AD), giving rise to the question to what extent myelin is reduced in these diseases. Here, we employed an advanced MRI based method to assess myelin independently from a major confounding factor, i.e. iron‐related signal, in monogenic small vessel disease (i.e. CADASIL) and in mild cognitive impairment (MCI) & AD dementia. Methods We included 62 CADASIL subjects, 11 with MCI or AD dementia, and 22 elderly controls (HC). Using 3D‐T2‐star‐weighted multi‐echo gradient‐echo MRI, we performed susceptibility source separation of diamagnetic (|χ‐negative|, e.g. myelin) and paramagnetic (χ‐positive, e.g. iron) sources (Shin et al., 2021). Mean diffusivity (MD) was calculated from diffusion tensor imaging. We extracted |χ‐negative| and MD values within WMH, normal appearing white matter (NAWM), and two ROIs including the left anterior thalamic radiation and forceps minor (genu) of the corpus callosum, i.e. two strategic tracts for processing speed. Subject‐level difference‐scores between CADASIL or MCI/dementia patients and group‐averaged HC were derived as abnormality scores. Voxel‐based WMH frequencies were mapped for each group. Group differences in |χ‐negative| and MD values were tested using linear regressions, controlled for χ‐positive scores, age, sex, and education. Results Voxel‐wise proportions of WMH are mapped for each group in Figure 1. For CADASIL, |χ‐negative| values were decreased, and MD values increased in each ROI compared to the HC group, with intermediate values for the MCI/dementia group (Figure 2 A&B). Worse |χ‐negative| and MD alterations were observed in WMH compared to NAWM (Figure 2 C‐F) in each disease group. Lower |χ‐negative| values were associated with higher MD in WMH (r = ‐0.57, Figure 3) and NAWM (r = ‐0.56). Conclusion |χ‐negative| values showed a marked decrease in WMH of CADASIL patients, suggesting myelin loss in SVD, with less pronounced myelin reduction present in MCI/AD. |χ‐negative| values were only moderately associated with MD, suggesting that each provides complimentary information. Our results encourage future studies to test the cognitive consequences of myelin loss in SVD and MCI.

Background In Alzheimer’s disease (AD), cortical tau aggregation is a strong predictor of cortical brain atrophy as shown by MRI and PET studies, particularly driving the degeneration of neuronal somata in the grey matter. However, tau’s physiological role is to stabilize microtubules within axons in the brain’s white matter (WM) pathways. Therefore, tau’s white‐to‐grey‐matter translocation and aggregation in neurofibrillary tangles close to neuronal somata may induce WM degeneration through destabilization of axonal microtubule integrity. To address this, we determined whether cortical tau predicted faster atrophy of connected WM tracts in AD. Method We included from ADNI cohort 37 amyloid‐PET negative (Aß‐) cognitively normal (CN) participants and 88 amyloid‐PET positive (Aß+) participants across the AD‐spectrum (i.e. CN/MCI/Dementia = 50/28/10), with baseline amyloid‐PET, longitudinal tau‐PET and longitudinal structural MRI data. For replication, we included baseline amyloid‐PET, tau‐PET and MRI data of 321 CN‐Aß+ subjects from the A4 cohort. T1‐weighed MRIs were segmented into grey and white matter and non‐linearly normalized to MNI space using CAT12. The cortical Brainnetome Atlas and a diffusion imaging‐based tractography atlas were applied tau‐PET and MRI data to i) determine cortical tau‐PET accumulation rates within Brainnetome ROIs, and ii) assess WM volume changes within fiber tracts connected to each cortical ROI. Statistical regression‐models were adjusted for age, sex, WM hyperintensity volume, global amyloid, intracranial volume, and APOE4‐status. Result In ADNI, higher baseline temporo‐parietal tau‐PET predicted faster volume reductions in connected WM tracts (Figure 1A), especially pronounced in Aß+ subjects (Figure 1B). Similarly, faster tau accumulation was strongly linked to widespread WM volume reductions in connected fiber tracts (Figure 2A; Figure 2B), particularly exacerbated in Aß+ APOE4 carriers (Figure 3A) compared to non‐carriers (Figure 3B). These results suggest that tau accumulation and WM degeneration are parallel processes in AD, modulated by APOE4. In the A4 validation sample of preclinical AD patients, we detected congruent associations between inferio‐temporal tau‐PET increase and reduced WM volume in connected fiber tracts (Figure 4). Conclusion Cortical tau aggregation is associated with progressive WM atrophy in connected fiber tracts throughout the brain, suggesting that tau accumulation triggers axonal degeneration, which may induce neuronal disconnection and dysfunction and thereby contributing to AD progression.

Background In Alzheimer’s disease, Aß triggers tau spreading which drives neurodegeneration and cognitive decline. However, the mechanistic link between Aß and tau remains unclear, which hinders therapeutic efforts to attenuate Aß‐related tau accumulation. Preclinical research could show that tau spreads across connected neurons in an activity‐dependent manner, and Aß was shown to trigger neuronal hyperactivity and hyperconnectivity. Therefore, we hypothesized that Aß induces neuronal hyperactivity and hyperconnectivity, thereby promoting tau spreading from initial epicenters across connected brain regions. Methods From ADNI, we included 140 Aß‐positive subjects across the AD spectrum plus 69 Aß‐negative controls, all with baseline amyloid‐PET, 3T resting‐state fMRI and longitudinal Flortaucipir tau‐PET data. For validation, we included cross‐sectional tau‐PET, amyloid‐PET and resting‐state fMRI data of 345 preclinical AD patients from A4. PET and fMRI data were parceled into 200 cortical ROIs, ROI‐wise longitudinal tau‐PET change rates were computed using linear mixed models. Resting‐state fMRI connectivity was computed across the 200 ROIs. Subject‐specific tau epicenters were defined as 5% of ROIs with highest baseline tau‐PET. Further, we included post‐mortem brain tissue from 5 AD patients vs. 4 controls stained for Aß and c‐Fos, i.e. a marker of ante‐mortem neuronal activity. Results In the AD spectrum cohort, we confirmed that Aß induces hyperconnectivity of temporal lobe tau epicenters (Fig.1) to posterior brain regions that are highly vulnerable to tau accumulation in AD (Fig.2A‐C). This was fully replicated in the validation cohort of preclinical AD patients with low cortical tau‐PET, suggesting that the emergence of Aß‐related hyperconnectivity precedes neocortical tau spreading (Fig.2D). Supporting that Aß‐associated fMRI‐based hyperconnectivity may mirror neuronal hyperactivity, we found that neurons in AD post‐mortem tissue expressed higher levels of c‐Fos compared to controls, i.e. a Calcium‐sensitive marker of ante‐mortem neuronal activity (Fig.3). Lastly, using longitudinal tau‐PET, we confirmed that Aß‐related connectivity increases of the tau epicenters to posterior brain regions mediated the effect of Aß on tau accumulation and triggered faster tau spreading (Fig.4). Conclusions Our translational results suggest that Aß promotes tau spreading via increasing neuronal activity and connectivity. Therefore, Aß‐associated neuronal hyperexcitability may be a promising target for attenuating tau spreading in AD.

Background Coronary heart disease (CHD) is a well‐known risk factor for cognitive impairment and dementia, and blood biomarkers of neurodegenerative diseases may be utilised to identify people at higher risk of cognitive decline. Here, we aimed to investigate prospective associations between these biomarkers and mild neurocognitive disorder (MiND) after a follow‐up of ten years in patients with stable CHD, and potential effect modification by hypercholesterolemia and ApoE genotype. Method Biomarkers of neurodegenerative diseases (glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), and phosphorylated tau181 (p‐tau181)) were measured in baseline blood serum samples using the Single‐Molecule Array (Simoa) Technology (Quanterix, USA) in a subset (n = 363) of a cohort of patients with stable CHD. MiND was defined as scores ≤ 21.8 on the Cognitive Telephone Screening Instrument (COGTEL). Hypercholesterolemia was categorised into none (normal total cholesterol (TC) levels without statin use), normal TC levels with statin use, or increased TC levels independent of statin use. We evaluated prospective associations of biomarkers of neurodegenerative disease with MiND using multivariable logistic regression models, adjusted for age, sex, study centre, hearing impairment, and comorbidities. We additionally checked for biomarker×ApoE genotype and biomarker×hypercholesterolemia interactions. Result At follow‐up, 55 (15.2%) patients had developed MiND. Higher levels of NfL were associated with increased risks of developing MiND (OR (95%‐CI) per SD increase: 1.44 (1.01‐2.04)). Associations of p‐tau181 with MiND were depending on hypercholesterolemia, but not on ApoE genotype. Higher levels of p‐tau181 were associated with lower odds of developing MiND in patients without hypercholesterolemia (OR (95%‐CI) per SD increase: 0.09 (0.01‐0.39)) and higher odds of developing MiND in patients with increased TC levels (OR (95%‐CI) per SD increase: 7.83 (1.72‐103.20)), but not in patients with normal TC levels using statins. Levels of GFAP were not associated with MiND. Conclusion Preliminary analyses suggest that NfL and p‐tau181 predict MiND after ten years in patients with stable CHD, and that the association of p‐tau181 with MiND was modified by hypercholesterolemia. This might imply that a deterioration in cognitive performance in this population might be halted through early management of hypercholesterolemia, however, more research is warranted.