BackgroundAnticholinergic side effects of pharmacological treatment are a risk factor for cognitive decline in older people. Here, we aimed to assess the effect of anticholinergic burden of treatment on longitudinal rates of cognitive change and atrophy in functionally related brain regions in people from the Alzheimer’s disease (AD) spectrum.MethodsWe determined associations of anticholinergic burden of pharmacological treatment with rates of global cognition, episodic memory and executive function decline as well as basal forebrain and hippocampus atrophy in participants of the memory clinic based DELCODE cohort, spanning the range from cognitively normal through subjective cognitive decline, mild cognitive impairment and AD dementia. We had 794 cases with neuropsychological outcomes, and a subset of 703 cases with MRI outcomes. Effects were assessed using mixed effect models in a Bayesian framework using prior-insensitive cross-validated Bayes factors (CV-BF) and parameter estimates.ResultsWe found moderate evidence for an association of anticholinergic burden with baseline levels of cognitive impairment for the PACC5 as a global cognitive function score (CV-BF = 9.0) with more impairments with higher burden, but not with basal forebrain and hippocampus volumes, and weak evidence for an association of anticholinergic burden with longitudinal rates of change in the trail-making test B as an executive function score (CV-BF = 2.5), but not for other cognitive scores and not for brain volumes.ConclusionIn the presence of prodromal or manifest AD, in a memory clinic-based cohort anticholinergic burden had only a modest effect on cognitive decline and no effect on atrophy in brain regions that are related to the cholinergic system.

Individuals with Alzheimer's disease dementia show Alzheimer's disease pathology and a heterogeneous degeneration of the Substantia Nigra (SN) post-mortem. However, it is unclear how SN degeneration is related to cognitive dysfunction across the Alzheimer's disease dementia continuum. In this study, using data from the prospective DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE), we investigated whether in vivo SN MRI measures are lower in individuals with clinically defined Alzheimer's disease dementia than in healthy control subjects (HC) and if they are associated with hippocampal functional activity during the processing of novel visual stimuli and subsequent recognition memory. One hundred and sixty DELCODE participants (69 years ± 6 years, 88 men), including 79 HC, 70 individuals with subjective cognitive decline (SCD), 17 individuals with mild cognitive impairment (MCI) and 10 individuals with Alzheimer's disease dementia, completed a scene novelty and encoding task and a 3T SN-sensitive MRI scan, from which the two in vivo SN measures MRI contrast and volume were calculated and harmonized between scanner sites while preserving diagnostic group differences. For 71 individuals, CSF levels of phosphoTau, total tau and amyloid-beta 42/40 ratio (Aß42/40) were available. All individuals completed a neuropsychological task battery from which a global cognitive score was calculated. In separate models, we assessed the relationship between SN MRI markers and CSF levels of Alzheimer's disease, the global cognitive score, hippocampal novelty activation and recognition memory while accounting for age, sex, years of education and total intracranial volume (TIV). SN volume but not SN MRI contrast was lower in individuals with clinical Alzheimer's disease dementia [one-way analyses of covariance (ANCOVA); F(156,4) = 5.6665, P = 0.0010, n = 160]. SN MRI contrast and volume were not associated with Aß42/40, ptau and total tau CSF levels (all P > 0.1) or hippocampal novelty activation (all P > 0.1). Moreover, SN volume was positively associated with recognition memory (R 2 = 0.07, P < 0.001, n = 159), global cognition (R 2= 0.38, P < 0.0001, n = 160) and years of education (R 2 = 0.03, P = 0.036, n = 160). Our study emphasizes the potential of using in vivo SN MRI markers to study the impact of SN degeneration on general cognitive impairment and recognition memory in an Alzheimer's disease dementia cohort. Our results motivate future longitudinal studies to explore how SN volume and SN contrast change with disease progression, how these are differentially associated with cognitive decline, and how SN volume and SN contrast might be related to other dopamine-dependent cognitive functions and dysfunctions.

Alzheimer’s disease (AD) is characterised by the accumulation of β-amyloid (Aβ) and tau proteins, resulting in neurodegeneration and cognitive decline. Although Aβ and tau disrupt synaptic function, the association linking these molecular pathologies to network-level dysfunction and memory impairment remains poorly understood. Here, we investigated the effects of Aβ and tau pathology (CSF Aβ42/40 ratio and tau phosphorylated at position 181, p-tau-181, respectively) on effective connectivity related to memory encoding, which may provide a link between synaptic pathology and cognitive outcomes. Functional magnetic resonance imaging (fMRI) during visual memory encoding was acquired from 205 participants in the multicentric DZNE Longitudinal Cognitive Impairment and Dementia Study (DELCODE) across the AD spectrum. Effective connectivity was assessed using Dynamic Causal Modelling (DCM) of task-fMRI data, focusing on the parahippocampal place area (PPA), hippocampus (HC), and precuneus (PCU)—regions central to memory encoding. Disruptions in connectivity between temporal and parietal lobes were associated with both memory impairment and indices of AD pathology. Specifically, reduced positive effective connectivity from the PCU to the PPA and from the HC to the PCU were linked to higher p-tau-181 levels, with an amplification effect observed in the presence of amyloid accumulation for the latter connectivity. The disruption from the PCU to the PPA was found to be associated with decreased memory performance. Together, these findings indicate that temporo-parietal connectivity is associated with both AD molecular pathology and, for a subset of connections, with memory performance.

Abstract Background The brain age gap (BAG), the difference between neuroimaging-predicted and chronological age, captures inter-individual variation in brain aging. Although sensitive to Alzheimer’s disease (AD) pathology, its longitudinal patterns across the clinical AD continuum and prognostic relevance remain unclear. Methods 577 participants from the DELCODE cohort (>2,100 MRI scans) were analysed: healthy controls individuals (HC, N=202), and patients with subjective cognitive decline (SCD, N=248), mild cognitive impairment (N=93), and AD dementia (N=34). All underwent structural MRI, amyloid (Aβ 42/40 ) and phosphorylated tau181 assessment, and lifestyle-related dementia risk profiling (LIBRA). BAG was derived using brainageR. Associations with baseline cognition, cognitive decline, and clinical progression (up to eight years) were examined using mixed-effects and Cox models. Mediation analyses tested whether BAG accounted for LIBRA-cognition associations. Biomarker-related and clinical findings were replicated in ADNI (N=461). Findings BAG showed excellent short-term reliability, increased stepwise across the clinical spectrum and was elevated in amyloid-positive SCD, but not in asymptomatic amyloid-positive HC. Longitudinal BAG increases were strongest in amyloid- and tau-positive participants (Aβ+T+). Higher BAG was associated with poorer baseline cognition and predicted cognitive decline, with strongest effects in Aβ+T+. All main findings replicated in ADNI. BAG was associated with LIBRA only in biomarker-negative participants and partly mediated associations with cognitive outcomes in DELCODE. Interpretation BAG is a reliable non-invasive marker of structural brain health sensitive to AD pathology and to modifiable AD risk. Detectable divergence prior to objective cognitive impairment supports its relevance for early risk stratification and prevention-oriented research. Funding Helmholtz AI Cooperation Unit (ZT-I-PF-5-163).

Research on visual episodic memory impairment in Alzheimer's disease often focuses on memory processes rather than the specific content of image being remembered. We previously showed that patients with mild cognitive impairment (MCI), a transitional stage that may precede Alzheimer's disease, can memorize certain images well, indicating that episodic memory is not uniformly impaired. Conversely, other specific images could not be memorized by MCI patients and were instead diagnostic for distinguishing MCI from healthy older adults. In this study, we investigate whether poor memory for these diagnostic images relates to impaired neural processing in specific brain regions and Alzheimer's biomarker pathology. We assessed 64 healthy controls and 48 MCI participants from the DZNE Longitudinal Cognitive Impairment and Dementia Study. Participants performed a visual scene memory task during fMRI and provided CSF biomarker data for amyloid and tau. Diagnostic images demonstrated significantly larger behavior-biomarker correlations (total tau, phospho-tau, Aβ42/Aβ40, and Aβ42/phospho-tau) compared with nondiagnostic images. This suggests memory for these specific diagnostic images is more affected by Alzheimer's disease pathology. The fMRI data revealed an interaction effect between group membership (healthy control/MCI) and image diagnosticity (diagnostic/nondiagnostic). MCI participants exhibited higher activation in specific scene-processing regions (parahippocampal place area, retrosplenial cortex, and occipital place area) for diagnostic compared with nondiagnostic images. Healthy controls, however, showed no processing differences between diagnostic and nondiagnostic images. These findings suggest MCI individuals may engage in inefficiently heightened encoding activation for diagnostic images. Our results show that special "diagnostic" images exist that can reliably reveal underlying amyloid and tau pathology alongside altered neural activity in scene regions.

Abstract Background Potentially modifiable lifestyle and psychological factors may influence Alzheimer’s disease (AD)-related brain pathology and cognitive function, thereby influencing cognitive resilience in late life. Objective This cross-sectional study investigated associations and pathways between lifestyle and psychological factors related to cognitive reserve and psychological debt, AD-related biomarkers, and cognitive function, as well as potential differences in these associations between AD risk groups. Methods In total, 298 non-demented older adults (mean age = 69.5 years, 44% women) of the DELCODE study were included. Structural equation modeling was used to assess the associations between the constructs of cognitive reserve (education, occupational complexity, leisure activity participation) and psychological debt (depression and anxiety symptoms, neuroticism, sleep quality), manifest AD-related biomarkers (cerebrospinal fluid [CSF] amyloid-beta [Aβ] 42, splenial white matter hyperintensities [WMH], hippocampal volume), and latent cognitive function of increased AD risk (Preclinical Alzheimer’s Cognitive Composite [PACC]). In the structural equation model, biomarkers were transformed such that higher values indicated greater AD-related brain pathology and age was included as a covariate. Multigroup analyses assessed moderations by established AD risk modifiers, namely sex and apolipoprotein ε4 (APOE ε4) genotype. Results In the total sample, higher cognitive reserve was associated with better cognitive function (p = .005), independent of AD-related biomarkers. Higher cognitive reserve was associated with lower psychological debt (p = .035); however, neither construct showed a significant association with the AD-related biomarkers (p ≥ .177). AD-related biomarkers of CSF Aβ42 (p = .021), splenial WMH (p = .044), and hippocampal neurodegeneration (p = .007) were each independently associated with lower cognitive function. Most associations were comparable between AD risk groups stratified by sex and APOE ε4 genotype. The relationships between cognitive reserve and psychological debt, and between CSF Aβ42 and splenial WMH were stronger in APOE ε4 non-carriers than in carriers (all p ≤ .020). Conclusions Cognitive reserve emerges as a key resilience pathway, supporting late-life cognition independently of AD-related pathology, with largely consistent effects across AD risk groups. The role of psychological debt warrants longitudinal investigation, particularly in vulnerable older populations. Trial registration German Clinical Trials Register: DRKS00007966, Registered: 4 May 2015.

BACKGROUND AND OBJECTIVES:Behavioral and neuropsychiatric symptoms are common in frontotemporal dementia (FTD) and primary progressive aphasia (PPA). However, little is known about their patterns, time course, and association with brain atrophy. We, therefore, aimed to describe behavioral and neuropsychiatric phenotypes in patients with FTD and PPA, leveraging a hypothesis-free/data-driven approach. METHODS:We included participants diagnosed with behavioral variant FTD (bvFTD) or PPA according to Rascovsky and Gorno-Tempini criteria from the German Center for Neurodegenerative Diseases Clinical Registry Study of Neurodegenerative Diseases-FTD prospective multicenter observational cohort study. Symptoms were assessed using the Neuropsychiatric Inventory-Questionnaire. Principal component analysis (PCA) was used to delineate symptom groups. Subsequently, frequency and severity across diagnostic groups were examined. We applied linear mixed-effects models to describe the longitudinal evolution of symptoms. Associations with MRI-assessed atrophy were investigated using linear regression models. RESULTS:A total of 314 patients (42.4% female, mean age 65.52 [SD 9.0] years) with bvFTD or PPA were included. MRI was available for 134 of 314 individuals. PCA revealed 4 natural symptom groups, labeled active behavioral, passive behavioral, affective, and psychotic phenotypes. Symptom groups were observed at comparable frequencies across diagnostic groups. Time from symptom onset (0.130 [0.044-0.217], p < 0.003), sex (1.376 [0.666-2.087], p < 0.001), and the interaction between the nonfluent variant of PPA and sex (-1.940 [-3.242 to -0.638], p = 0.004) showed a significant effect on the active behavioral phenotype, with symptom severity increasing over time and being most pronounced in men with bvFTD. Patients with bvFTD exhibited more severe passive behavioral symptoms compared with any other diagnostic group. For the affective phenotype, a significant interaction between time and sex (0.063 [0.010-0.117], p = 0.021) indicated a progressive increase in symptom severity in men over time. Furthermore, we found robust neuroanatomical correlations of passive behavioral symptoms with subcortical and bilateral frontal and cingulate cortical atrophy. DISCUSSION:Our findings demonstrate that behavioral and neuropsychiatric symptoms are prevalent in both bvFTD and PPA. Their severity depends on the disease duration, phenotypic group, and sex. This detailed understanding of symptomatology is crucial for optimizing patient care, diagnostic evaluations, and the design of clinical trials. Limitations comprise the lack of neuropathologic validation and the limited availability of MRI data.

Alzheimer's disease (AD) is a major cause of dementia and cognitive decline. Here, we assessed how episodic memory (EM) network dysfunction, a hallmark of AD, is related to the longitudinal progression of AD biomarkers, neurodegeneration and cognition using data from the DZNE DELCODE study. This data set includes over 1000 longitudinal functional magnetic resonance imaging measurements of EM network function. We related activation and deactivation of EM to individual disease progression scores from a disease progression model. Voxel-wise analyses revealed widespread loss of deactivation and activation with disease progression. Trajectories for the loss of deactivation were nonlinear, associated with amyloid- and tau-positivity and visually preceded trajectories of cognitive decline. The relationship between deactivation and cognitive decline was partly independent of neurodegeneration. Our results provide evidence that synaptic dysfunction and neurodegeneration are independent drivers of cognitive decline, providing a rationale for targeting synaptic dysfunction along the AD cascade.

Brain maintenance - the preservation of brain structure or function relevant to cognitive performance - remains challenging to quantify. Here, we propose a domain-general brain maintenance index derived by jointly modelling the longitudinal co-evolution of ageing-related atrophy (via medial temporal lobe to ventricle ratio, MTLV-ratio), white matter hyperintensities (WMH), and global cognition assessed by the preclinical Alzheimer's cognitive composite (PACC5) using latent growth curve modelling. We demonstrate its utility in 543 cognitively unimpaired older adults from the DELCODE cohort, followed annually over four years. We show that changes in MTLV-ratio and WMH additively predict cognitive change. We further show that higher neuroticism, depressive symptoms, lower openness, and faster biological ageing are related to unfavourable domain-specific trajectories and poorer brain maintenance. Our findings highlight the combined relevance of WMH and ageing-related atrophy dynamics for brain maintenance. Maintaining cerebrovascular and mental health alongside cognitive engagement could promote brain maintenance, delay cognitive decline and dementia.

Subjective cognitive decline (SCD) refers to a self-perceived, persistent cognitive decline compared to previous levels in individuals with objectively unimpaired cognition. Studies have repeatedly shown associations of SCD characteristics with amyloid pathology and increased risk of future cognitive decline, especially in memory-clinic settings. The aim of this project is to model individual differences of cognitive decline in individuals with SCD. Latent Growth Curve Model (LGCM) analysis was applied to individuals with SCD from the DZNE Longitudinal Cognitive Impairment and Dementia (DELCODE) study. We chose a sample of n  = 203 participants who showed a decline on the Preclinical Alzheimer's Cognitive Composite (PACC5) score over five years. First, a two-factor linear growth model was fitted on the annualized PACC5 data. We then calculated and compared two models to which we added the following baseline predictors: 1) plasma Aß42/40, plasma ptau181, ApoE-4-carrier status and hippocampal volume (biological model), and 2) Geriatric Depression Scale (GDS), Geriatric Anxiety Inventory–Short Form (GAIS-SF) and Neuropsychiatric Inventory Questionnaire (NPI-Q) total scores (neuropsychiatric model). The LGCM of longitudinal PACC-5 scores yielded adequate model fit for a linear model ( X 2 (16)=67.5, p  < .001, CFI = 0.93, SMRM=0.07, AIC=1437.10). The baseline PACC score was -0.03 ( SE  = 0.05, p  = .533) and average cognition declined slightly over time by -0.13 ( SE  = 0.01, p  < .001). The biological model showed an improvement in fit, with an AIC of 742.30. Here, we observed a positive relationship between plasma Aß42/40 and the intercept ( B  = 7.60, SE  = 3.01, p  = .012) and a negative relationship between plasma ptau181 and the intercept ( B  = -0.22, SE  = 0.09, p  = .016). Plasma Aß42/40 was the only significant predictor of the PACC5 slope in this model ( B  = 1.35, SE  = 0.62, p  = .030). In comparison, the AIC value for the neuropsychiatric model was 1341.17, with the GDS total score being negatively related to the PACC5 slope ( B  = -0.03, SE  = 0.01, p  = .009). These results add to gaining a better understanding of SCD trajectories and specific predictors of cognitive decline, which is relevant to power future clinical trials in this population.

Subjective cognitive decline (SCD) is proposed as an indicator of transitional disease stage 2 in the Alzheimer’s disease (AD) continuum. However, molecular and particularly longitudinal fluid biomarker data for this stage are still limited. This study aimed to determine whether blood-based biomarkers in amyloid-positive individuals with SCD (A + SCD) support the notion of stage 2 as a distinct stage between stages 1 and 3 of AD and to identify those at high risk for clinical progression. In a prospective multicenter study (DELCODE) involving 457 participants across the AD continuum, we analyzed plasma phospho-tau 181 (p181) and neurofilament light chain (NfL) and assessed their association with longitudinal cognition, hippocampal atrophy, and AD clinical stage transition. The results showed that baseline plasma p181 levels were elevated and increased more rapidly in A + SCD individuals compared to amyloid-positive cognitively unimpaired (A + CU) individuals (stage 1). NfL levels rose across A + CU, A + SCD, and amyloid-positive mild cognitive impairment (A + MCI, stage 3). In A + SCD, but not in A + CU, higher p181 levels predicted cognitive decline (PACC5) and transition to MCI. In conclusion, plasma p181 provides molecular biomarker evidence supporting A + SCD as a pre-dementia AD stage (stage 2) distinct from A + CU (stage 1) and helps identify individuals at risk for cognitive decline early in the AD continuum.

OBJECTIVE:In cerebral small vessel disease (CSVD), compromised arterial supply to the deep gray matter contributes to cognitive decline. While CSVD frequently involves lenticulostriate arteries supplying the putamen, the functional consequences of altered putaminal vascular architecture remain unclear. We hypothesized that a less homogeneous arterial network in the putamen is associated with impaired perfusion and worse cognitive performance in CSVD. METHODS:We enrolled 16 CSVD patients with cerebral microbleeds and 21 age‑matched controls (mean age 71 years; 38 % female). High-resolution 7 T time‑of‑flight angiography was used to segment all visible intraputaminal vessels. For each voxel in the putamen, the distance to its nearest segmented vessel was computed to generate a vessel distance map; the mean vessel distance reflects the homogeneity of the arterial network. Putaminal perfusion was quantified via multi‑inversion time pulsed arterial spin labeling (ASL) at 3 T, and CSVD severity was scored on clinical 3 T MRI. All participants completed a comprehensive neuropsychological battery to derive a global cognition composite score. RESULTS:Linear regression revealed that higher CSVD MRI scores predicted larger mean vessel distance, reflecting a sparser arterial network, in both the right (B = 0.12, β = 0.42, p = 0.010) and left putamen (B = 0.13, β = 0.43, p = 0.014). Across all participants, increased vessel distance was also associated with prolonged arterial transit time in the right (B = 0.044, β = 0.50, p = 0.009) and left putamen (B = 0.042, β = 0.49, p = 0.009). Finally, in a multivariable linear regression adjusting for demographics, vascular risk factors, and CSVD severity, greater vessel distance in the right putamen was associated with lower global cognitive performance (B = -1.26, β = -0.34, p = 0.012). CONCLUSION:This study demonstrates the impact of an impaired arterial network in the putamen on blood supply and cognitive function across the continuum of CSVD.

Perivascular spaces (PVS) can become large enough to be visible in magnetic resonance imaging (MRI). The exact aetiology of PVS enlargement in humans remains, however, elusive and under continuous debate [1-5]. Here, we tracked PVS volumes longitudinally over three years in 525 individuals along AD syndromal cognitive stages, namely cognitively unimpaired (CU), mild cognitive impairment (MCI), and Alzheimer’s disease (AD), to pinpoint conditions related to PVS enlargement. We studied centrum semiovale (CSO) and basal ganglia (BG) PVS computationally over three to four annual visits in 525 DELCODE participants (CU/MCI/AD 417/72/36; 49.52% female, mean age 70.85 (SD 5.78)) [6]. We segmented PVS using a multimodal Hessian-based filtering method [7] leveraging T1w and FLAIR imaging, which we validated against clinical visual ratings. We used linear mixed-effect modelling to study temporal PVS volume changes. First, we tested whether PVS volumes increased over follow-ups in CU. Second, we explored whether longitudinal PVS enlargement was associated across ROIs, and predicted by individual white matter hyperintensities (WMH), Amyloid and Tau positivity status at baseline in the entire cohort. We adjusted all analyses by age, sex, years of education, and total intracranial volume. We observed PVS volume increase over follow-ups in healthy ageing with a significant individual difference of change (Figure 1; BG: B=0.06 [95%-CI 0.04-0.08], p<0.001; CSO: B=0.06 [95%-CI 0.04-0.09], p<0.001). PVS enlargement in BG was associated with that in CSO (ρ=0.17, p FDR <0.001). Participants with greater baseline WMH volumes tended to have faster BG-PVS enlargement (ρ=0.05, p FDR =0.06). Participants with both Amyloid and Tau positive tended to have faster CSO-PVS enlargement than those with neither (Figure 2; Χ²(2)=5.07, p=0.079, η²=0.014). Given our findings, ageing is a primary driver of PVS enlargement. Associations between PVS and WMH underline shared cerebrovascular mechanisms. Detrimental cycles driven by neurotoxic waste accumulation might also contribute to PVS enlargement. Further research is needed to disentangle pathological cascades, their concurrent dynamics, and their unique contribution to disease progression. References 10.1016/j.neurobiolaging.2022.01.006 10.18632/oncotarget.17724 10.1002/ana.26475 10.1161/STROKEAHA.117.017526 10.1016/j.clineuro.2019.05.002 10.1186/s13195-017-0314-2 10.1007/BFb0056195

Alzheimer’s disease (AD) is characterised by the accumulation of beta-amyloid (Aβ) and tau proteins, leading to neurodegeneration and cognitive decline. While Aβ and tau are known to disrupt synaptic function, the mechanisms linking these molecular pathologies to network-level dysfunction and memory impairment remain poorly understood. Here we investigated the effects of Aβ and tau pathology (CSF Aβ42/40 ratio and tau phosphorylated at position 181, p-tau-181, respectively) on effective connectivity (EC) related to memory encoding, which may constitute a link between synaptic pathology and cognitive outcomes. Functional magnetic resonance imaging (fMRI) during visual memory encoding was acquired from participants of the multicentric DZNE Longitudinal Cognitive Impairment and Dementia Study (DELCODE), including 203 cognitively normal older participants (CN) as well as individuals with subjective cognitive decline (SCD; N = 204), mild cognitive impairment (MCI; N = 65), and early dementia due to AD (DAT; N = 21). EC was assessed by applying Dynamic causal modelling (DCM) to the fMRI data, using brain regions previously implicated in memory-encoding: the parahippocampal place area (PPA), the hippocampus (HC) and the precuneus (PCU). Disruptions in forward connectivity from the PPA to the HC and PCU were associated with both memory impairment and indices of AD pathology. Specifically, reduced excitatory EC from the PPA to the HC was associated with higher p-tau-181 levels and correlated with poorer memory performance. Diminished inhibitory EC from the PPA to the PCU was driven by both tau and amyloid pathology and was likewise linked to memory decline. Our findings suggest that disrupted forward connectivity within the temporo-parietal memory network constitutes a candidate mechanism mediating the relationship between molecular pathology and cognitive dysfunction. ### Competing Interest Statement E.D. is one of co-founders of neotiv GmbH and conducted paid consultancy work for Eisai, Lilly, Biogen, Roche and RoxHealth (unrelated to this study). C.B. received honoraria as a commercial advisory board member for Lilly (April 2024); honoria for lectures from Boehringer Ingelheim (September 2024), Roche (June 2021), Lilly (March 2025) and Eisai (April 2024); and funding from the German Alzheimer Association (DAlzG; 2021-2023). * AB : beta-amyloid AD : Alzheimer’s disease CN : cognitively normal DAT : dementia of Alzheimer’s type DCM : Dynamic causal modelling DELCODE : DZNE - Longitudinal Cognitive Impairment and Dementia Study DZNE : German Centre for Neurodegenerative Diseases GAMs : Generalised additive models HC : hippocampus MCI : mild cognitive impairment PPA : parahippocampal place area PCU : precuneus p-tau : phosphorylated tau SCD : subjective cognitive decline Deutsche Forschungsgemeinschaft, 362321501/RTG 2413 'SynAGE', 374011584/3T Ganzkörper MR-Tomograf, CRC 1436, projects C01, B02, and A05 German Center for Neurodegenerative Diseases, https://ror.org/043j0f473, BN012

For over three decades, the concomitance of cortical neurodegeneration and white matter hyperintensities (WMH) has sparked discussion about their coupled temporal dynamics (Garnier-Crussard et al. 2023). Longitudinal evidence supporting this hypothesis remains nonetheless scarce (Ter Telgte et al. 2018). We integrated surface-based morphometry and bivariate latent change score modelling (BLCSM) to examine interrelationships between individual WMH and cortical thickness changes over a one-year period in cognitively unimpaired participants. We analysed baseline and 12-month follow-up data from cognitively unimpaired DELCODE participants (n=393; median age 70.31 [IQR 66.06-74.87] years; 52% females). We used T2w FLAIR and T1w MPRAGE data to segment WMH (LST; Schmidt and Wink 2019) and estimate cortical thicknesses (CAT12; Gaser et al., n.d.). Using BLCSM in a vertex-wise fashion, we tested whether baseline WMH volumes predicted cortical thinning rates and whether baseline cortical thickness predicted WMH volumes increases (Figure 1). Due to the posterior dominance of WMH in AD (Bernal et al. 2023), we focussed on parietal and occipital WMH. All models included age, sex, years of education, and total cardiovascular risk factors as covariates on baseline and change scores. We log-10 transformed WMH volumes and corrected WMH volumes and thicknesses measurements for TICV via residualisation. We finally tested for moderation effects of CSF-derived Aβ42/40 and pTau181 on cross-domain coupling. BLCSM generally provided good data fits (RMSEA≤0.05, CFI≥0.095, SRMR≤0.05) across all analyses. The mean thickness across precuneal and superiorparietal cortices at baseline predicted the progression of WMH better than any other cortical region (Figure 2B; β Thick→ΔWMH =-0.051, SE=0.011, Z=-4.535, p-value<0.001). This was especially evident with lower CSF-derived Aβ42/40 (β Thick*Aβ42/40→ΔWMH =0.176, SE=0.053, Z=3.309, p-value=0.001). WMH volume at baseline explained, in part, the level of thinning of parts of the fusiform cortex (Figure 2D; β WMH→ΔThick =-0.139, SE=0.028, Z=-5.030, p-value<0.001). This interrelationship was moderated by CSF-derived pTau181 (β WMH*pTau181→ΔThick =-0.144, SE=0.053, Z=-2.711, p-value=0.007). Cortical thinning and WMH progression may be mutually reinforcing processes that become reciprocally coupled prior to any detectable cognitive deficits. Hallmark AD proteins appear to moderate their interrelationships.

BACKGROUND:Subjective cognitive decline (SCD) refers to a self-perceived, persistent cognitive decline compared to previous levels in individuals with objectively unimpaired cognition. Studies have repeatedly shown associations of SCD characteristics with amyloid pathology and increased risk of future cognitive decline, especially in memory-clinic settings. The aim of this project is to model individual differences of cognitive decline in individuals with SCD. METHOD:Latent Growth Curve Model (LGCM) analysis was applied to individuals with SCD from the DZNE Longitudinal Cognitive Impairment and Dementia (DELCODE) study. We chose a sample of n = 203 participants who showed a decline on the Preclinical Alzheimer's Cognitive Composite (PACC5) score over five years. First, a two-factor linear growth model was fitted on the annualized PACC5 data. We then calculated and compared two models to which we added the following baseline predictors: 1) plasma Aß42/40, plasma ptau181, ApoE-4-carrier status and hippocampal volume (biological model), and 2) Geriatric Depression Scale (GDS), Geriatric Anxiety Inventory-Short Form (GAIS-SF) and Neuropsychiatric Inventory Questionnaire (NPI-Q) total scores (neuropsychiatric model). RESULT:The LGCM of longitudinal PACC-5 scores yielded adequate model fit for a linear model (X2(16)=67.5, p < .001, CFI = 0.93, SMRM=0.07, AIC=1437.10). The baseline PACC score was -0.03 (SE = 0.05, p = .533) and average cognition declined slightly over time by -0.13 (SE = 0.01, p < .001). The biological model showed an improvement in fit, with an AIC of 742.30. Here, we observed a positive relationship between plasma Aß42/40 and the intercept (B = 7.60, SE = 3.01, p = .012) and a negative relationship between plasma ptau181 and the intercept (B = -0.22, SE = 0.09, p = .016). Plasma Aß42/40 was the only significant predictor of the PACC5 slope in this model (B = 1.35, SE = 0.62, p = .030). In comparison, the AIC value for the neuropsychiatric model was 1341.17, with the GDS total score being negatively related to the PACC5 slope (B = -0.03, SE = 0.01, p = .009). CONCLUSION:These results add to gaining a better understanding of SCD trajectories and specific predictors of cognitive decline, which is relevant to power future clinical trials in this population.

INTRODUCTION:Structural magnetic resonance imaging (MRI) often lacks diagnostic, prognostic, and monitoring value in Alzheimer's disease (AD), particularly in early disease stages. To improve its utility, we aimed to identify optimal atrophy markers for different intended uses. METHODS:We included 363 older adults; cognitively unimpaired individuals who were negative or positive for amyloid beta (Aβ) and Aβ-positive patients with subjective cognitive decline, mild cognitive impairment, or dementia of the Alzheimer type. MRI and neuropsychological assessments were administered annually for up to 3 years. RESULTS:Accelerated atrophy of medial temporal lobe subregions was evident already during preclinical AD. Symptomatic disease stages most notably differed in their hippocampal and parietal atrophy signatures. Atrophy-cognition relationships varied by intended use and disease stage. DISCUSSION:With the appropriate marker, MRI can detect abnormal atrophy already during preclinical AD. To optimize performance, atrophy markers should be tailored to the targeted disease stage and intended use. HIGHLIGHTS:Subregional atrophy markers detect ongoing atrophy in preclinical Alzheimer's disease (AD). Subjective cognitive decline in preclinical AD links to manifest atrophy. Optimal atrophy markers differ by the disease stage and intended use.

Behavioral risk or protective factors related to “cognitive debt” and “cognitive reserve” may influence brain pathology and cognition and thereby contribute to resilience in aging. This cross-sectional study examined direct and indirect associations of cognitive debt (risk factor) and cognitive reserve (protective factor) with mixed brain pathologies and cognition in older adults. A sample of N = 298 non-demented older adults (mean age=70 years, 56% male) from the DELCODE study (DRKS00007966) were analyzed using structural equation modeling (SEM) and an a-priori path model. We assessed the association between cognitive debt and cognitive reserve (modelled as latent constructs) and global cognition (Preclinical Alzheimer Cognitive Composite 5 [PACC5] modelled as latent construct) through pathological pathways involving beta-amyloid (Aß) burden, hippocampal neurodegeneration, and white matter hyperintensities (WMH) in the corpus callosum splenium (CCs), while adjusting for age. A goodness-of-fit analysis ensured adequate model fit. Brain pathology was associated with lower PACC5 performance via direct pathways (for WMH in the CCs and hippocampal neurodegeneration) and indirect pathways (for Aß deposition via hippocampal neurodegeneration) (all p < .05). Cognitive debt and cognitive reserve were not significantly associated with brain pathology (all p > .05). Cognitive reserve, but not cognitive debt, was independently associated with better PACC5 performance ( p = .005). Cognitive debt and cognitive reserve were associated at trend level ( p = .068). Results are displayed in Figure 1. Brain pathologies were linked to lower cognitive performance. Cognitive reserve, but not cognitive debt, was independently associated with better cognitive performance (1). There were no significant associations of cognitive debt and cognitive reserve with brain pathologies. The findings suggest that cognitive reserve may influence resilience through mechanisms independent of brain pathology (2). Future longitudinal studies are needed to investigate these pathways and clarify causal relationships. References 1. Vemuri P, Weigand SD, Przybelski SA, Knopman DS, Smith GE, Trojanowski JQ, et al. Cognitive reserve and Alzheimer's disease biomarkers are independent determinants of cognition. Brain. 2011;134(Pt 5):1479-92. 2. Vemuri P, Lesnick TG, Przybelski SA, Knopman DS, Roberts RO, Lowe VJ, et al. Effect of lifestyle activities on Alzheimer disease biomarkers and cognition. Ann Neurol. 2012;72(5):730-8.

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. We estimated AD disease stages using a multivariate Gaussian Process (GP) DPM including CSF-Aβ42/40 ratio, CSF-p-tau 181 , 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. 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. 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.

Inadequate glymphatic clearance through perivascular spaces (PVS) is hypothesized to contribute to the formation of white matter hyperintensities (WMH). However, longitudinal evidence for such a mechanistic link in aging remains limited. Using multivariate modelling, we investigated the interrelationship between PVS and WMH over time to elucidate potential cascades of early cerebrovascular alterations and tested whether AD-biomarkers and inflammatory markers associated with vascular disease can explain individual variability in their occurrence and progression. We quantified PVS and WMH using T1w MPRAGE and T2w FLAIR imaging of 439 cognitively unimpaired participants from the DELCODE study (52.85% females; mean age = 69.88±5.72), who underwent annual scans over a four-year period and attended at least three visits ( n observations = 1790; mean number of visits = 4.08±0.79). We employed latent growth curve modelling to assess reciprocal connections between PVS and WMH, focusing on their initial volumes (latent intercepts) and their rates of change over four years (latent slopes). We used log10-transformed total PVS and WMH volumes, and controlled for age, sex, years of education, total cardiovascular risk score, and total intracranial volume. We then derived interindividual latent factor scores and tested their relation to CSF-derived AD-biomarkers (Aβ42/40, pTau181; available for n = 195; z-scored) and inflammatory markers (CRP, IL-6; available for n = 125; Box-Cox-transformed) via Spearman’s correlation (FDR-corrected). The model showed good model fit ( CFI = 0.997; RMSEA = 0.021; SRMR = 0.017; Fig. 1A ). WMH and PVS volumes increased over time ( intercept WMH-slope = 0.068, SE = 0.004, Z = 16.490, p< 0.001; intercept PVS-slope = 0.036, SE = 0.007, Z = 4.927, p< 0.001; Fig. 1B ). Participants with higher baseline PVS volumes not only had higher baseline WMH volumes ( covariance PVS-intercept&WMH-intercept = 0.120, SE = 0.040, Z = 2.936, p = 0.003; Fig. 1C ) but also tended to exhibit faster WMH volume increase over time ( covariance PVS-intercept&WMH-slope = 0.007, SE = 0.004, Z = 1.796, p = 0.072; Fig. 1C ). In this sample of cognitively unimpaired participants, biomarkers of AD and inflammation did neither relate to individual baseline differences nor progression rates ( Table 1 ). Our findings are consistent with the notion that PVS dysfunction might contribute to and precede WMH progression ( Fig. 1D ). However, the individual variability requires further investigation to elucidate mechanisms driving PVS dysfunction in the first place. Unraveling the interrelationships and further factors contributing to cerebrovascular alterations will be crucial to understand pathological cascades in aging that could inform targeted treatment strategies.