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Background: Independent contributions of enlarged perivascular spaces (ePVS) to cognition remain elusive due to their intertwining with white matter hyperintensities (WMH). We studied the unique and shared effects of ePVS and WMH on cognitive performance in 397 subjects along the Alzheimer's disease (AD) continuum. Methods: We quantified baseline volumes of WMH, basal ganglia (BG) and centrum semiovale (CSO) ePVS in participants of the multicentre DELCODE study (Controls = 81/Subjective Cognitive Decline = 151/Mild Cognitive Impairment = 79/AD = 45/AD relatives = 41) and regressed age, sex, pTau181, and image quality out of them. We established cognitive domain scores (memory, working memory, language, executive, visuospatial) based on a comprehensive cognitive test battery and confirmatory factor analysis, and assessed preclinical Alzheimer's cognitive composite (PACC5) scores. Using principle component (PC) analysis, we estimated unique and shared variances. We began by extracting the first PC (PC1)—a weighted average of ePVS and WMH volumes—which indicated overall cerebrovascular dysfunction (Figure 1). We then regressed PC1 out of ePVS and WMH volumes to estimate their unique variances, which should reflect glymphatic function and white matter (WM) damage, respectively. For each cognitive domain, we compared null linear regression models (years of education, age, sex, pTau181, and image quality) to those enriched with the shared (PC1) and unique variances of BG‐/CSO‐ePVS and WMH. Results: Overall cerebrovascular dysfunction—PC1—substantially affected all cognitive domains negatively. BG‐ePVS' unique variance—surrogate for glymphatic function—contributed to better memory (B = 0.19, 95%‐CI[0.02;0.36]), language (B = 0.25, 95%‐CI[0.09;0.42]) and PACC5 performance (B = 0.25, 95%‐CI[0.07;0.43]) beyond overall cerebrovascular dysfunction. However, WM damage—WMH unique variance—contributed more substantially and negatively to the same cognitive domains (memory: R²PC1 = 0.365

Background: Perivascular spaces in the brain can become enlarged (ePVS); their temporal dynamics remain under increasing debate. We studied automatic ePVS measurements obtained from 870 subjects along the AD continuum over the course of three years. Method: We measured centrum semiovale (CSO) and basal ganglia (BG) ePVS volumes computationally in the multicentre DZNE Longitudinal Cognitive Impairment and Dementia Study (DELCODE) (Table 1; 870 subjects; 51% female, mean age 70.85 (SD 6.16), up to 4 annual time points; 2487 sets of T1w and FLAIR). We segmented ePVS using a multiscale Hessian‐based filtering method leveraging T1w and FLAIR imaging and validated segmentation against clinical visual ratings. We studied local longitudinal changes via the sandwich estimator toolbox and linear mixed‐effect modelling and tested for effects of age, hypertension, clinical diagnosis, ApoE4 status, pTau181, and Aβ42/40 on ePVS trajectories. Result: BG‐ePVS and CSO‐ePVS became more voluminous over time (Table 2 and Figure 1A‐C; BG: B = 0.04 [95%‐CI 0.03‐0.05], p<0.001; CSO: B = 0.02 [95%‐CI 0.00‐0.04], p<0.031). The age of the patient at baseline determined the baseline volume of ePVS in the BG (B = 0.13 [95%‐CI 0.09‐0.17], p<0.001), but not in the CSO‐ePVS (p = 0.245). WMH can form around ePVS (Figure 1D) and their progression was correlated with PVS enlargement (BG: B = 0.05 [95%‐CI 0.04‐0.07], p<0.001; CSO: B = 0.19 [95%‐CI 0.15‐0.22], p<0.001). No other predictors contributed significantly to longitudinal ePVS changes. Conclusion: Ageing is a major contributor to the volumetric expansion of ePVS over time. WMH and ePVS growth are associated, suggesting shared underlying pathological mechanisms. [ABSTRACT FROM AUTHOR]

Background: Inflammation, vascular disease and Alzheimer's Disease (AD) appear to be closely linked. We recently showed that increased vascular risk relates to certain inflammatory profiles in CSF in the DELCODE cohort (Hayek et al, AAIC 2022). Moreover, we found cerebrovascular alterations in posterior‐midline regions including precuneus in subjects at risk for AD and with cognitive impairment relative to controls (Behrenbruch et al). Here, we examined the contributions of vascular risk and related inflammatory markers to alterations in resting‐state fMRI BOLD fluctuations that are sensitive to cerebrovascular reactivity (CVR)—a proposed marker of cerebrovascular dysfunction. Method: Leveraging resting‐state fMRI BOLD signal, we mapped voxel‐wise relative CVR (rCVR), using mean global signal as regressor, and the relative coefficient of variation (rCV). See Figure 1 for methodological details. We derived average rCV/rCVR from the precuneus as region of interest. Inflammation‐related CSF markers and AD markers (ptau181 and Aβ42/40) from CSF were available in 205 subjects with rCVR/rCV maps. A Principal component (PC) analysis on 16 inflammation‐related CSF markers previously revealed 4 PCs. PC2 and PC3 were related to higher vascular risk scores (covering hypertension, diabetes and abnormal fat metabolism based on medical reports). We used linear regression models to assess how inflammation PC scores and AD biomarkers related to precuneus rCVR or rCV (controlling for age, sex, site, education and mean framewise displacement). We also tested if rCVR/rCV was related to vascular risk or memory. Result: Lower precuneus rCVR was predicted by higher values of the inflammatory component PC2 (mainly driven by markers CRP, C1q and FactorB), with no additional effect of other PCs or AD markers. Lower precuneus rCV was predicted by higher values of the inflammatory component PC3 (mainly driven by IP10, MCP1, MIF, CRP, C4) and by higher ptau. Lower precuneus rCVR was also related to higher vascular risk. Lower rCVR and rCV related to worse memory. Figure 2 shows supplementary correlations of individual inflammation markers. Conclusion: Lower rCVR and rCV in the precuneus that are thought to reflect vascular dysfunction, relate to higher vascular‐risk related inflammatory markers beyond AD pathology. Their concurrent dynamics requires further investigation to understand their unique contributions to microvascular pathology. [ABSTRACT FROM AUTHOR]

Background: The current research consensus is that long Aβ(1‐42) peptides are neurotoxic pathological hallmarks of AD. Interestingly, short Aβ peptides, such as Aβ(1‐38), appear to be less neurotoxic and may counteract AD neuropathology. However, research on Aβ(1‐38) is scarce and their effect on AD pathophysiology in humans in vivo remains unclear. Here, we investigate whether higher relative concentrations of Aβ(1‐38) levels in the cerebrospinal fluid (CSF), compared to Aβ(1‐42) alone, with phospho Tau (pTau) or with both, protect against cognitive decline and risk of conversion to AD dementia. Method: Participants with subjective cognitive decline (n = 56), mild cognitive impairment (n = 60) and AD dementia (n = 61) from the DELCODE study with a likely pathological Aβ42/P‐tau ratio of > 9.68 at baseline were included. Cognitive performance was assessed annually for five years with the Mini‐Mental State Examination (MMSE) and the Preclinical Alzheimer Cognitive Composite (i.e., PACC5), which was derived from the Consortium to Establish a Registry for Alzheimer's Disease (CERAD). Conversion to AD dementia was assessed with the Clinical Dementia Rating (CDR) and NINCDS‐ARDA criteria. CSF was collected at baseline. Data was analysed using statistical model fitting procedures for linear mixed models, i.e., Likelihood Ratio (LR) testing. Additionally, we controlled for baseline diagnostic status and the relative effect of Aβ(1‐42) and pTau. Result: Higher Aβ(1‐38) baseline levels were associated with better follow‐up performance on the PACC5 in all three groups across the AD continuum (p <.001). For the MMSE, only the MCI group showed significantly better follow‐up performance (p =.003), and a trend was found in the other groups (SCD: p =.090, AD p =.099). Furthermore, higher Aβ(1‐38) baseline levels decreased risk of conversion to AD dementia within three years by 88% (p =.003) in the SCD and MCI groups. Conclusion: Across the AD spectrum, higher Aβ(1‐38) levels protect against cognitive decline and reduce the risk of conversion to AD dementia. This could inform individual risk prediction in memory clinic patients. [ABSTRACT FROM AUTHOR]

Background: Altered fluctuations in blood oxygen level dependent (BOLD) signal during resting‐state functional magnetic resonance imaging (rs‐fMRI) have been considered indicative of decreased cerebrovascular health. Previous studies reported changes in BOLD fluctuations associated with Alzheimer's dementia (AD) and white matter hyperintensities (WMH). However, to date, there has been no large‐scale study involving patients with AD, mild cognitive impairment (MCI), subjective cognitive decline (SCD), and control subjects (CON) that has explored local AD‐ and WMH‐related effects in BOLD fluctuations. Method: We calculated the voxel‐based coefficient of variation (CV: standard deviation divided by the mean) and the relative CV (rCV: CV divided by the mean CV of the whole‐brain) of the rs‐fMRI BOLD signal in the large multicentric DZNE DELCODE cohort. After spatial preprocessing, regression of movement parameters, movement spikes, and scanner drift, low‐pass filtering and exclusion of subjects with high motion, CV and rCV maps were obtained and compared with respect to (A) clinical diagnosis (AD: n = 79; MCI: n = 113; SCD: n = 314; CON: n = 192) and cerebrospinal fluid Aß42/40 (AD: n = 41; MCI: n = 64; SCD: n = 139; CON: n = 77); and (B) effects of vascular‐related lesions, here WMH. Result: The CV and rCV of the precuneus and middle cingulum indicated increasingly reduced BOLD fluctuation across the clinical groups towards AD. Interestingly, we observed increases in rCV in the basal ganglia and frontal white matter in AD compared with CON. Of note, lower CSF Aß42/40 (more pathological) was associated to reduced CV and rCV in the precuneus and with lower rCV in the right angular gyrus. Subjects with higher WMH volume showed widespread reductions of CV in white matter near the left angular gyrus and reduced rCV in large portions of white matter and subcortical gray matter. Conclusion: The AD spectrum exhibits altered BOLD fluctuations that are at least partially tied to actual amyloid differences. Larger WMH are associated with reduced BOLD signal fluctuations consistent with widespread white matter pathology ‐ beyond the effects of diagnosis. We argue that rCV is a useful complement to CV to detect these changes that might reflect cerebrovascular impairment. [ABSTRACT FROM AUTHOR]

Introduction: This study aimed to analyze the impact of low‐value medications (Lvm), that is, medications unlikely to benefit patients but to cause harm, on patient‐centered outcomes over 24 months. Methods: This longitudinal analysis was based on baseline, 12 and 24 months follow‐up data of 352 patients with dementia. The impact of Lvm on health‐related quality of life (HRQoL), hospitalizations, and health care costs were assessed using multiple panel‐specific regression models. Results: Over 24 months, 182 patients (52%) received Lvm at least once and 56 (16%) continuously. Lvm significantly increased the risk of hospitalization by 49% (odds ratio, confidence interval [CI] 95% 1.06–2.09; p = 0.022), increased health care costs by €6810 (CI 95% −707€–14,27€; p = 0.076), and reduced patients' HRQoL (b = −1.55; CI 95% −2.76 to −0.35; p = 0.011). Discussion: More than every second patient received Lvm, negatively impacting patient‐reported HRQoL, hospitalizations, and costs. Innovative approaches are needed to encourage prescribers to avoid and replace Lvm in dementia care. Highlights: Over 24 months, more than every second patient received low‐value medications (Lvm).Lvm negatively impact physical, psychological, and financial outcomes.Appropriate measures are needed to change prescription behaviors. [ABSTRACT FROM AUTHOR]

Background: Engagement in complex leisure activities, such as playing a musical instrument, may help preserve cognitive and brain health in older age (e.g. Böttcher et al., 2022). In this study, we investigated the associations between leisure‐time musical activity and resting‐state functional connectivity (RSFC) in three higher‐order networks, the Default Mode. Fronto‐Parietal and Salience Networks, in older adults. Method: In total, 130 cognitively unimpaired older (aged 60 years and older) participants of the DZNE ‐ DELCODE (Jessen et al., 2018) were assessed. Two groups matched for their reserve proxies were identified (with musical activity during life: n = 65 and controls: n = 65) based on self‐reported musical instrument playing during life, as measured by the Lifetime of Experiences Questionnaire. The two groups were compared in global and local (seed‐to‐voxel) RSFC patterns using pre‐specified seeds of the three brain networks. A mediation analysis explored the interrelations between lifetime musical activity, RSFC, and cognitive composites (Wolfsgruber et al., 2020). Result: Older participants with musical activity showed higher local RSFC between the medial prefrontal cortex (Default Mode Network seed) and temporal regions, namely the bilateral temporal poles as well as the right inferior and middle temporal gyrus, compared to controls (see Figure 1). There were no group differences in global RSFC of the three networks and no mediation effects of musical activity‐related RSFC on global and domain‐specific cognition. Conclusion: We show that self‐reported lifetime musical activity relates to higher RSFC between frontal and temporal core regions of the Default Mode Network in older adults. The finding implies that playing a musical instrument during life may help preserve neural functioning in a key network that is vulnerable to aging and AD. References: Böttcher et al. Frontiers in Psychology 2022. Jessen et al. Alzheimer's Research & Therapy 2018. Wolfsgruber et al. Neurology 2020. [ABSTRACT FROM AUTHOR]

Background: Self‐ and informant‐reports of cognitive decline have been previously associated with a higher risk of cognitive decline in elderly. Yet, few studies assessed their longitudinal changes over time with regard to both incident mild cognitive impairment (iMCI) and Alzheimer's disease (AD) pathology. This study aims at describing these links to better understand which trajectories are indicative of higher AD‐risk. Method: We used data from 501 participants followed‐up annually (2.51±1.35 years) in the DELCODE project. All were cognitively unimpaired, and had an amyloid measurement available, at inclusion. Among them, 145 were amyloid‐positive, and 65 progressed to iMCI during the follow‐up period (31 iMCI‐Aß+). The SCD‐Interview was used to measure (i) the number of cognitive domains in which the participants or its relative perceived a decline (i.e., self‐ and informant‐SCD‐I), and (ii) the number of fulfilled SCD‐plus criteria. Linear mixed‐effect models were used to assess SCD trajectories over time, according to four groups defined by amyloid status and clinical progression (Stable‐Aß‐, Stable‐Aß+, iMCI‐Aß‐ and iMCI‐Aß+). Analyses were adjusted for age, sex and education; and their interaction with time. Results: Both self‐SCD‐I levels and SCD‐plus scores decreased significantly over time, without significant differences between groups (Figure 1A, 1B). Conversely, informant‐SCD‐I levels did not significantly change over time in the whole sample, although slopes significantly differed between groups. Compared to the Stable‐Aß‐ group, there was a greater increase over time of informant‐SCD‐I report only in iMCI‐Aß+ [est 0.16, SE 0.05, p<.001] (Figure 1C). The resulting discrepancy score (Self‐SCD‐I minus Informant‐SCD‐I) tended to decrease over time with significant differences between groups. Compared to the Stable‐Aß‐ group, the discrepancy score showed a faster decrease over time in iMCI‐Aß+ [est ‐0.21, SE 0.056 p<.001] (Figure 1D). Conclusion: Longitudinal patterns in subjective reports of cognitive decline might help identify preclinical AD subjects at higher risk of clinical progression. Specifically, an increase of informant‐reported cognitive decline over time may indicate objective cognitive decline in amyloid‐positive subjects. Conversely, the decrease of self‐reported cognitive decline over time, regardless of the group, may reflect generally reduced concerns after inclusion, or result from current limitations in longitudinal SCD assessment. [ABSTRACT FROM AUTHOR]

Background: Amyloidopathy, one pathological hallmark of Alzheimer's disease (AD), results from dysbalanced amyloid‐β production and clearance. Therefore, disruptions in brain clearance may have a pivotal role as pathogenic drivers. Transgenic mice models of AD may serve to develop and establish minimally invasive in vivo measurement methods to observe brain clearance longitudinally. Method: We used magnetic resonance imaging (MRI) with intravenously administered gadolinium‐based contrast agent (GBCA) on a 7T small animal ultrahighfield MRI scanner to determine brain clearance efficacy. Imaging sessions were performed longitudinally in n = 9 APPswe/PS1dE9 (tg) mice and n = 9 wild type (wt) littermates at 6, 9 and 12 months of age with a scan protocol consisting of a highly T2w Inv. Rec. RARE (FLAIR) sequence. For a subsample of n = 6 wt and n = 6 tg at 9 and 12 months we used an additional T1w RARE sequence for evaluation of parenchymal changes. Both protocols were carried out every 5‐6.5 minutes for a total of 180 minutes. We determined mean voxel values in manually delineated volumes of interest in ventricles (in T2w images) and brain parenchyma (T1w images) using PMOD software. Result: We created intensity‐time‐curves and measured slopes for signal increase and decrease, derived from fitting with a model consisting of an exponential convoluted with another exponential and used to normalize area under the curve (AUC) values (Figure 1A‐C). Repeated measurements ANOVA revealed no differences in normalized AUC values regarding age in both lateral (p = 0.568, F(2, 28) = 0.577), 3rd (p = 0.306, F(1.903, 26.64) = 1.232) and 4th ventricles (p = 0.181, F(1.345, 18.83) = 1.924) and also no differences regarding genotype in both lateral (p = 0.684, F(1,16) = 0.172), 3rd (p = 0.737, F(1,16) = 0.117) and 4th ventricle (p = 0.186, F(1,16) = 1.910). Measurements of parenchymal clearance capacity are still ongoing and first results will be presented at the conference. Conclusion: Our first results showed no measurable difference in the brain clearance efficacy. This could have two possible reasons. Either ventricular clearance measurements are not sensitive enough to measure AD related changes in brain clearance or the used pathogenetic model shows no changes in clearance efficacy. Our still ongoing analyses of parenchymal brain could help to elucidate further on this question. [ABSTRACT FROM AUTHOR]

Background: Structural MRI is frequently used to track Alzheimer's disease (AD) progression in clinic, research, and pharmacological trials. It has been shown that established MRI‐derived measures lack diagnostic sensitivity particularly in early stages of AD. Here, we investigate if the utility of structural MRI for tracking early AD progression can be increased when focusing on subregions of the medial temporal lobe (MTL) which are known to exhibit earliest AD‐related neuropathological change. Method: We used data from N = 143 participants enrolled in the DZNE Longitudinal Cognitive Impairment and Dementia Study (DELCODE). This included cognitively unimpaired participants who were either Aβ‐negative (CU Aβ‐; n = 67) or Aβ‐positive (CU Aβ+; n = 20), Aβ+ participants with subjective cognitive decline (SCD Aβ+; n = 38), and Aβ+ participants with MCI (MCI Aβ+; n = 18). Participants underwent annual assessments up to three years after baseline, including MRI (2.19 ± 0.86 follow‐ups) and a neuropsychological testing (2.18 ± 0.83 follow‐ups). Segmentations of MTL subregions were generated using a longiudinal, template‐based implementation of the Automated Segmentation of Hippocampal Subfields (ASHS; Yushkevich et al., 2015, Hum Brain Mapp.) algorithm (Figure 1). Linear mixed models were fitted to derive volumetric slopes and to test their relationship with longitudinal changes in Preclinical Alzheimer Cognitive Composite (PACC‐5) scores. Result: We observed significant volume losses across diagnostic groups with the MCI Aβ+ group exhibiting the fastest rates. Compared with the CU Aβ‐ group, there were accelerated volume losses in the subiculum and dentate gyrus in the SCD Aβ+ group and, additionally, in the entorhinal cortex and Brodmann areas 35 and 36 in the MCI Aβ+ group. There was also a trend towards faster volume losses in the entorhinal cortex in the CU Aβ+ group. Higher rates of MTL subregional volume losses, particularly in the cornu ammonis 1 subfield, were related to a faster decline on the PACC‐5 in the MCI Aβ+ group. This effect remained significant when controlling for baseline volumes. Conclusion: Our findings highlight the viability of subregional MTL morphometry for tracking earliest neurodegeneration and related cognitive decline due to AD. [ABSTRACT FROM AUTHOR]

Background: Mnemonic discrimination of similar lures and targets is emerging as a promising marker of subtle memory decline in early Alzheimer's disease (AD) due to its reliance on regions most affected by AD pathology. Tau pathology initially targets medial temporal lobe (MTL) regions in an anterior‐temporal (AT) brain network, which is preferentially involved in object processing, before it can be found in the posterior‐medial (PM) network associated with scene processing. Tests of object and scene mnemonic discrimination may therefore serve as behavioural indicators of the functional integrity of AT and PM regions, respectively. We investigated behavioural and neural changes in mnemonic discrimination across the AD spectrum. Method: 201 DELCODE cohort participants underwent fMRI scanning during an object‐scene mnemonic discrimination task at four time points from baseline to three‐year follow‐up. At baseline, participants were split by diagnostic group (cognitively unimpaired = CU, subjective cognitive decline = SCD, mild cognitive impairment = MCI, dementia of the Alzheimer's type = DAT; Table 1). We identified brain regions showing lower activity to repeated targets but not similar lures, indicative of successful pattern separation of overlapping memory representations. Result: These findings present cross‐sectional baseline data. Behavioural data showed a main effect of group but no group by category (objects, scenes) interaction. CUs and SCDs outperformed patients across domains and CUs scored higher than SCDs only in scene discrimination. Amyloid positive and negative CUs and SCDs did not differ in performance. Successful mnemonic discrimination engaged hippocampus, parahippocampal cortex, precuneus, angular gyrus, and inferior frontal regions for both objects and scenes. Correct object discrimination was additionally associated with amygdala and transentorhinal cortical activity. Reduced brain activation in regions of the anterior‐temporal and posterior‐medial network during successful object and scene mnemonic discrimination, respectively, was found in patient groups (MCI+DAT) compared to cognitively normal (CU+SCD) older adults. Conclusion: Our findings lend further support to the utility of mnemonic discrimination as indicator of memory impairment in early AD. Object and scene tasks engage partially dissociable brain networks and individuals with cognitive impairment show reduced neural pattern separation effects. These findings lay the groundwork for future longitudinal analyses to track these changes based on clinical and biomarker status. [ABSTRACT FROM AUTHOR]

Background: Cerebrospinal fluid (CSF) biomarkers have immense diagnostic and prognostic potential for Alzheimer disease (AD). Currently, AD is still mostly diagnosed relatively late in the disease process, sometimes even years after the initial manifestation of cognitive symptoms. Disease‐modifying treatments should be most effective in the earliest stages, before amyloid plaques and neurodegeneration become prevalent. Thus, further identification of biomarkers is required that can detect AD in the predementia stage. This study aimed to assess the clinical utility of synaptic proteins neurogranin and beta‐secretase 1 (BACE1) in the diagnosis and prognosis of AD. Method: We enrolled 530 participants from DELCODE, a multicenter prospective cohort study, including healthy controls (HC), subjective cognitive decline (SCD) subjects, mild cognitive impairment (MCI) subjects, mild AD dementia and first‐degree relatives of AD patients. Based on amyloid and tau status, we divided the participants into four groups: A−T−; A−T+; A+T−; A+T+. Neurogranin and BACE1 levels across groups were assessed by ANCOVA after adjusted for age and sex. To test the correlation of the biomarkers to cognitive performance, we used linear mixed models to model baseline biomarker levels and 7 years longitudinal MMSE and PACC5 scores. Result: Regardless of amyloid status, CSF neurogranin and BACE1 levels were significantly higher in T+ group compared with T‐ (all p < 0.0001). Furthermore, for participants with negative tau status, neurogranin and BACE1 levels were lower in A+ group compared with A‐ (both p < 0.0001). After adjusting for covariates (Age, Sex, Education, APOEε4), linear mixed‐effect models indicated that higher neurogranin predicts faster decline in MMSE (β = ‐0.14, p < 0.01) and PACC5 (β = ‐0.03, p < 0.05) over 7 years. Conclusion: This study reveals that neurogranin and BACE1 could offer insight into identifying patients at early stages of AD and improve prediction of cognitive decline. [ABSTRACT FROM AUTHOR]

Background: Age is the strongest risk factor for dementia, including Alzheimer's disease (AD). However, across individuals of the same chronological age there is considerable heterogeneity in rates of cognitive decline. These differences have been attributed to individual differences in age‐related biological processes, including brain protein expression. To capture these differences, we developed a measure of protein brain age from cerebrospinal fluid (CSF)‐proteins, and validated its predictive utility. Methods: In older adults across the dementia continuum enrolled in DELCODE (training cohort; N = 488, 5‐year follow‐up) and patients with subjective cognitive decline and mild cognitive impairment (MCI) from the memory‐clinic based Fundació ACE (FACE) cohort (test cohort; N = 509, 3‐year follow‐up), 1063 CSF‐proteins were measured using OLINK‐technology. Proteins optimally predicting chronological age in A/T/N‐negative individuals without dementia from DELCODE (N = 196) were selected based on a LASSO‐regression and summarized into a BrainProteinAge‐score for all participants. A harmonized, age‐sensitive cognitive composite was created and the association between BrainProteinAge and cognitive decline assessed using structural equation modeling. Further, the predictive utility of ProteinBrainAge for incident all‐cause‐dementia was examined using time‐dependent ROC analysis in MCI patients from the test cohort. Results: 118 CSF‐proteins were selected and used to calculate BrainProteinAge. In the training (Est[SE] = 0.06[0.02],p<0.001) and test (Est[SE] = 0.04[0.02],p = 0.013) cohorts, BrainProteinAge predicted cognitive decline beyond demographic characteristics (chronological age, sex, education) and A/T/N profiles. ProteinBrainAge captured 40% of the processes linking chronological age and cognitive decline, and improved prediction to all‐cause dementia beyond demographic characteristics and A/T/N profiles in MCI‐patients (1‐year AUC: 0.78 versus 0.82, p(difference) = 0.006). Specifically, within the AD‐continuum, BrainProteinAge (HR[CI] = 1.056[1.004‐1.110]), compared to chronological age (HR[CI] = 1.022[0.990‐1.054]), has greater predictive utility. Whilst an 8.6‐year ProteinBrainAge difference corresponded to the same risk increase observed between A+/T+ and A+/T‐ MCI patients, a difference of 24.6‐years was required for chronological age. All results remained substantively unchanged when using an optimized BrainProteinAge based on 10 proteins most strongly linked to cognitive decline. Conclusions: A new measure of biological age improves individualized prediction of cognitive decline and conversion to dementia in memory clinic patients. This provides an opportunity for precision medicine and a better understanding of age‐related biological processes contributing to dementia. [ABSTRACT FROM AUTHOR]

Background: Language markers can serve screening and early detection in Alzheimer's disease (AD). Using artificial intelligence (AI) approaches enables automated assessment and analysis of speech biomarkes using chatbot technology. Reliable digital speech biomarkers require an easy‐to‐use chatbot which is adopted to the users' needs. Currently, chatbots often are unsuitable for people with cognitive impairment and rather frustrating for their users. Here, we implemented a user centred design approach to iteratively evaluate usability of a chatbot system for automated speech assessments for people with prodromal or preclinical dementia. Method: Within the study PROSPECT‐AD, participants (n = 53 by January 2023, 300 planned) are automatically called for six times every three months by our chatbot "Mili". Each call takes about 15 minutes and consists of three cognitive tasks (Wordlist, Semantic Verbal Fluency, Story Telling). We applied a six stage usability check to improve Mili iteratively (see Figure 1). For deeper insights, we conduct semi‐structured interviews (n = 20). During the interviews, we focus on affinity for technology, usability, and participants' attitude towards chatbots and artificial intelligence in medicine. Results: To date, Mili has completed 54 assessments (see Figure 2). Drop‐outs (11.3%) occcur around the first assessment. Reasons were e.g., lack of accessibility of participants, excessive demands through cognitive tasks or through Mili. Participants reported problems due to Mili's high speaking pace and hangs of Mili. Additionally, Mili struggled in automatically retrieving appointments and missed calling. All problems were quickly resolved. The speaking pace was reduced and the time‐out time extented by 2 seconds. Results of the system usability scale revealed a high user‐friendliness of the calls (see Table 1). Participants (n = 6) evaluated the calls as quick to learn and easy to use. Two participants wished for more technical support for the calls. Two participants felt uncomfortable in using Mili. Conclusion: Our results revealed a high usability and feasibility of the automated phone calls by Mili. Due to close colaboration, problems with Mili were solved qickly and further drop‐outs prevented. This underlines the benefit of close cooperation between participants, scientists, and IT specialists. Interviews are needed for further improvement of Mili and to understand uncertainty with Mili. [ABSTRACT FROM AUTHOR]

Background: Degeneration of the Locus coeruleus (LC) is associated with Alzheimer's disease (AD) pathology and cognitive decline. Recent evidence from animal models indicates that this relationship may be mediated by neuroinflammation. Here we examined how LC MRI contrast is related to CSF biomarkers of neuroinflammation in humans. Method: The LC as well as the Substantia nigra (SN) were visualized and segmented using neuromelanin‐sensitive T1‐weighted FLASH‐MRI images acquired at 3T and MRI contrast values were calculated as previously described (Betts et al., 2019b). A cohort of 65 participants with MRI contrast and CSF data from the DZNE longitudinal cognitive impairment and dementia (DELCODE) study (20 HC, 22 SCD, 16 MCI, 7 AD dementia; 53.8% female) were included in the analyses. We performed correlational analyses to test for associations between LC and SN contrast with a panel of 4 Principal Components (PC) created from a Principial Component Analysis on 16 individual inflammation‐related CSF biomarkers (Fig. 1). Both bivariate and partial correlation analyses were performed between PCs and MRI contrast values using sex, age, site and CSF levels of AD pathology, namely Aß42/40‐ratio and phosphorylated tau, as covariates (see Fig. 2). Result: We found a significant positive association between LC MRI contrast and the inflammatory component PC4 including the proinflammatory complement factors C3 and C3b across the entire sample (r = 0.365, p = 0.003). Additional post‐hoc correlational analyses showed this association with LC MRI contrast was mainly due to a correlation with C3b (r = 0.349, p = 0.004). A significant positive association was still observed (r = 0.347, p = 0.008) in a subgroup of individuals comprising healthy older adults and individuals with a risk of AD dementia (HC, SCD and MCI) as shown in Fig. 2. In contrast, no significant associations between SN MRI contrast and any neurodegenerative or inflammatory measure were observed indicating effects were specific to the LC. Conclusion: The results demonstrate LC MRI contrast is associated with complement factors in CSF, in particular complement factor C3b in healthy older adults and individuals with a risk of AD dementia. Further analyses are required to determine if elevated complement factors may predict degeneration of the LC and subsequent cognitive decline. [ABSTRACT FROM AUTHOR]

Background: Self‐ and informant‐reports of cognitive decline have been previously associated with a higher risk of cognitive decline in elderly. Yet, few studies assessed their longitudinal changes over time with regard to both incident mild cognitive impairment (iMCI) and Alzheimer's disease (AD) pathology. This study aims at describing these links to better understand which trajectories are indicative of higher AD‐risk. Method: We used data from 501 participants followed‐up annually (2.51±1.35 years) in the DELCODE project. All were cognitively unimpaired, and had an amyloid measurement available, at inclusion. Among them, 145 were amyloid‐positive, and 65 progressed to iMCI during the follow‐up period (31 iMCI‐Aß+). The SCD‐Interview was used to measure (i) the number of cognitive domains in which the participants or its relative perceived a decline (i.e., self‐ and informant‐SCD‐I), and (ii) the number of fulfilled SCD‐plus criteria. Linear mixed‐effect models were used to assess SCD trajectories over time, according to four groups defined by amyloid status and clinical progression (Stable‐Aß‐, Stable‐Aß+, iMCI‐Aß‐ and iMCI‐Aß+). Analyses were adjusted for age, sex and education; and their interaction with time. Result: Both self‐SCD‐I levels and SCD‐plus scores decreased significantly over time, without significant differences between groups (Figure 1A, 1B). Conversely, informant‐SCD‐I levels did not significantly change over time in the whole sample, although slopes significantly differed between groups. Compared to the Stable‐Aß‐ group, there was a greater increase over time of informant‐SCD‐I report only in iMCI‐Aß+ [est 0.16, SE 0.05, p<.001] (Figure 1C). The resulting discrepancy score (Self‐SCD‐I minus Informant‐SCD‐I) tended to decrease over time with significant differences between groups. Compared to the Stable‐Aß‐ group, the discrepancy score showed a faster decrease over time in iMCI‐Aß+ [est ‐0.21, SE 0.056 p<.001] (Figure 1D). Conclusion: Longitudinal patterns in subjective reports of cognitive decline might help identify preclinical AD subjects at higher risk of clinical progression. Specifically, an increase of informant‐reported cognitive decline over time may indicate objective cognitive decline in amyloid‐positive subjects. Conversely, the decrease of self‐reported cognitive decline over time, regardless of the group, may reflect generally reduced concerns after inclusion, or result from current limitations in longitudinal SCD assessment. [ABSTRACT FROM AUTHOR]

Background: Inflammation, vascular disease and Alzheimer's Disease (AD) appear to be closely linked. We recently showed that increased vascular risk relates to certain inflammatory profiles in CSF in the DELCODE cohort (Hayek et al, AAIC 2022). Moreover, we found cerebrovascular alterations in posterior‐midline regions including precuneus in subjects at risk for AD and with cognitive impairment relative to controls (Behrenbruch et al). Here, we examined the contributions of vascular risk and related inflammatory markers to alterations in resting‐state fMRI BOLD fluctuations that are sensitive to cerebrovascular reactivity (CVR)—a proposed marker of cerebrovascular dysfunction. Method: Leveraging resting‐state fMRI BOLD signal, we mapped voxel‐wise relative CVR (rCVR), using mean global signal as regressor, and the relative coefficient of variation (rCV). See Figure 1 for methodological details. We derived average rCV/rCVR from the precuneus as region of interest. Inflammation‐related CSF markers and AD markers (ptau181 and Aß42/40) from CSF were available in 205 subjects with rCVR/rCV maps. A Principal component (PC) analysis on 16 inflammation‐related CSF markers previously revealed 4 PCs. PC2 and PC3 were related to higher vascular risk scores (covering hypertension, diabetes and abnormal fat metabolism based on medical reports). We used linear regression models to assess how inflammation PC scores and AD biomarkers related to precuneus rCVR or rCV (controlling for age, sex, site, education and mean framewise displacement). We also tested if rCVR/rCV was related to vascular risk or memory. Result: Lower precuneus rCVR was predicted by higher values of the inflammatory component PC2 (mainly driven by markers CRP, C1q and FactorB), with no additional effect of other PCs or AD markers. Lower precuneus rCV was predicted by higher values of the inflammatory component PC3 (mainly driven by IP10, MCP1, MIF, CRP, C4) and by higher ptau. Lower precuneus rCVR was also related to higher vascular risk. Lower rCVR and rCV related to worse memory. Figure 2 shows supplementary correlations of individual inflammation markers. Conclusion: Lower rCVR and rCV in the precuneus that are thought to reflect vascular dysfunction, relate to higher vascular‐risk related inflammatory markers beyond AD pathology. Their concurrent dynamics requires further investigation to understand their unique contributions to microvascular pathology. [ABSTRACT FROM AUTHOR]

Background: The quantitative analysis of biomarker proteins in the cerebrospinal fluid (CSF) substantiates the clinical diagnosis of Alzheimer´s disease (AD). A substantial problem in the early diagnosis of AD is that clinical symptoms as measured by neuropsychological tests appear only after massive cell loss has already occurred in the brain. However, when the disease manifests, abeta‐ and tau‐protein levels have already become static. In this study, we asked whether concentrations of the astrocyte‐derived proteins glial fibrillary acidic protein (GFAP) and S100 calcium‐binding protein B (S100B) in CSF might serve as markers of pathophysiological events and astrocyte reactivation in the course of AD. Although, there are some previously studies reporting high GFAP levels in cerebrospinal fluid of AD group, the CSF levels of GFAP and S100B in the early course of the AD have not been reported. Methods: We measured the levels of GFAP and S100B in the CSF of healthy control subjects (n = 90), first degree relatives of AD (parent or sibling, n = 46), subjective memory decline (SCD) (n = 211), mild cognitive impairment (MCI) (n = 114) and AD (n = 65) patients in a well‐structured cohort (DELCODE Cohort), which has a larger sample size than previous studies. Results: After comparing the CSF levels of GFAP in the study groups, we found that healthy controls had significantly lower GFAP levels than AD patients (p = 0.001, Figure 1) and the MCI patients (p = 0,004, Figure 1). It might prove to be a very important evidence of the role of astrogliosis in early stages. Furthermore, no significantly differences were found in levels of S100B, although S100B mean values show also gradual increasing from SCD to AD (Figure 2). As a note to the reader, we also found that there was low correlation between the levels of glial markers (GFAP und S100B) and markers of classical biomarkers (Aβ‐42, Ratio Aβ‐42/Aβ‐40, Total‐τ, Phospho‐τ‐181) of neurodegeneration in the disease course. Conclusion: This result may prove the role of early reactive astrocytes in early stages of disease. And this finding could lead to develop another treatment concepts targeting the early reactive astrocytes. [ABSTRACT FROM AUTHOR]

Background: The noradrenergic (NA) system comprises several cortical and subcortical brain areas with differential densities of NA transporters and receptors. A decline in the NA system, together with additional risk factors such as ApoE4‐status, gender, age, vascular changes and years of education may contribute to the development of Alzheimer's disease (AD). The aim of this study was to examine whether brain areas known to be rich in NA receptors and transporters are particularly vulnerable to degeneration in preclinical AD. Method: We examined interindividual differences in volumes of specific brain areas grouped into high and low NA density regions (NA‐high/NA‐low) for healthy controls (HC) and AD relatives (n = 122), individuals with subjective cognitive decline (SCD) (n = 152) and mild cognitive impairment (MCI) (n = 78). Structural equation modeling (SEM) was used to simultaneously examine associations between NA‐high and NA‐low regions across clinical groups. We investigated whether brain volumes in NA‐high and NA‐low areas were differentially related to known AD risk factors (ApoE4 status, CSF amyloid‐ß (Aß) 42/40 and phosphorylated tau (pTau)), and whether these links differed in HC, SCD and MCI. Result: Estimating a two‐factor model with NA‐high and NA‐low revealed a better model fit than estimating one general factor. ApoE4‐carriers were associated with a lower ratio of Aß42/40 (‐0.472***) and a higher level of pTau (0.263***). In the whole sample, a low ratio of Aß42/40 was associated with lower brain volume in NA‐high (0.157***), but not NA‐low areas. pTau showed no significant association to NA‐high or NA‐low areas. The group analysis revealed an increasing association between ApoE4, pTau and Aß42/40 in HC, SCD and MCI. An association between Aß42/40 and NA‐high areas was observed in all groups, whilst for an additional positive association to NA‐low in HC (0.125*), but negative association in SCD (‐0.184*). Finally, the negative association between pTau and Aß42/40 is true for SCD and MCI, but not for HC. Conclusion: SEM can be used to separate brain regions into NA‐high and NA‐low areas. Higher risk status Aß42/40 is linked to lower brain volume in high NA density areas, suggesting a particular vulnerability of brain areas likely more affected by NA decline in AD. [ABSTRACT FROM AUTHOR]

Introduction: Standardized cognitive assessment would enhance diagnostic reliability across memory clinics. An expert consensus adapted the Uniform Dataset (UDS)‐3 for European centers, the clinician's UDS (cUDS). This study assessed its implementation acceptability and feasibility. Methods: We developed a survey investigating barriers, facilitators, and willingness to implement the cUDS. With a mixed‐methods design, we analyzed data from academic memory clinics. Results: Seventy‐eight percent of responding clinicians were experienced neuropsychologists/psychologists and 22% were medical specialists coming from 18 European countries. Sixty‐five percent clinicians were willing to implement cUDS. General barriers related to implementation (43%) and clinical‐methodological domains (21%). Favorable clinicians reported finances (15%) and digitalization (9%) as facilitating, but unavailability of local norms (23%) as hindering. Unfavorable clinicians reported logistical (23%) and time issues (18%). Discussion: Despite challenges, data showed moderate clinicians' acceptability and requirements to improve feasibility. Nonetheless, these results come from academic clinicians. The next steps will require feasibility evaluation in non‐academic contexts. [ABSTRACT FROM AUTHOR]

The neuromodulatory subcortical system (NSS) nuclei are critical hubs for survival, hedonic tone, and homeostasis. Tau‐associated NSS degeneration occurs early in Alzheimer's disease (AD) pathogenesis, long before the emergence of pathognomonic memory dysfunction and cortical lesions. Accumulating evidence supports the role of NSS dysfunction and degeneration in the behavioral and neuropsychiatric manifestations featured early in AD. Experimental studies even suggest that AD‐associated NSS degeneration drives brain neuroinflammatory status and contributes to disease progression, including the exacerbation of cortical lesions. Given the important pathophysiologic and etiologic roles that involve the NSS in early AD stages, there is an urgent need to expand our understanding of the mechanisms underlying NSS vulnerability and more precisely detail the clinical progression of NSS changes in AD. Here, the NSS Professional Interest Area of the International Society to Advance Alzheimer's Research and Treatment highlights knowledge gaps about NSS within AD and provides recommendations for priorities specific to clinical research, biomarker development, modeling, and intervention. Highlights: Neuromodulatory nuclei degenerate in early Alzheimer's disease pathological stages.Alzheimer's pathophysiology is exacerbated by neuromodulatory nuclei degeneration.Neuromodulatory nuclei degeneration drives neuropsychiatric symptoms in dementia.Biomarkers of neuromodulatory integrity would be value‐creating for dementia care.Neuromodulatory nuclei present strategic prospects for disease‐modifying therapies. [ABSTRACT FROM AUTHOR]

Introduction: Limbic age‐related TDP‐43 encephalopathy neuropathologic change (LATE‐NC) is common in advanced age and can underlie a clinical presentation mimicking Alzheimer's disease (AD). We studied whether an autopsy‐derived fluorodeoxyglucose positron emission tomography (FDG‐PET) signature of LATE‐NC provides clinical utility for differential diagnosis of amnestic dementia patients. Methods: Ante mortem FDG‐PET patterns from autopsy‐confirmed LATE‐NC (N = 7) and AD (N = 23) patients were used to stratify an independent cohort of clinically diagnosed AD dementia patients (N = 242) based on individual FDG‐PET profiles. Results: Autopsy‐confirmed LATE‐NC and AD groups showed markedly distinct temporo‐limbic and temporo‐parietal FDG‐PET patterns, respectively. Clinically diagnosed AD dementia patients showing a LATE‐NC–like FDG‐PET pattern (N = 25, 10%) were significantly older, showed less abnormal AD biomarker levels, lower APOE ε4, and higher TMEM106B risk allele load. Clinically, they exhibited a more memory‐predominant profile and a generally slower disease course. Discussion: An autopsy‐derived temporo‐limbic FDG‐PET signature identifies older amnestic patients whose clinical, genetic, and molecular biomarker features are consistent with underlying LATE‐NC. [ABSTRACT FROM AUTHOR]

Background: WMH in the corpus callosum (CC), as previously related to AD pathology(1) and lower cognition in AD patients(2), are suggested to play an important role in AD. The Aim of this study was to substantiate the associations between WMH location, biomarkers of AD pathophysiology, and cognitive performance in the DELCODE study. Method: 429 participants were included (HC: 126, SCD: 165, MCI: 87, AD: 51). WMH volumes were segmented from FLAIR images. WMH volumes were adjusted for total intracranial volume and log‐transformed. Beta‐Amyloid and total Tau (Aß42 and tTau, measured in CSF) and neurodegeneration (ND, measured by hippocampal volume) were log‐transformed and used as surrogate markers for AD pathophysiology. Cognitive performance was assessed by a global cognitive composite. Path modelling, adjusted for age, sex and education, was performed to estimate direct and indirect associations between regional WMH volumes (in the CC splenium, body, genu and the frontal lobe as possible control region), AD biomarkers and cognition. Results: The correlation matrix (Figure 1) showed the highest correlation of Aß42 and tTau with WMH volume the splenium CC. Greater WMH volume in the splenium CC was directly associated with lower global cognition (Figure 2a, ß = ‐0.10, p = 0.01) and indirectly through Aß42 (ß = ‐0.10, p = 0.001) and ND (Figure 2b, ß = ‐0.05, p = 0.001). The same indirect association was statistically significant regarding tTau (ß = ‐0.03, p < 0.001). Model outcomes were similar for the body and genu of the CC. For frontal WMH volume, the direct association with global cognition was not statistically significant (ß = ‐0.002, p = 0.96), only through indirect associations with Aß42 (ß = ‐0.05, p = 0.003) and ND (ß = ‐0.02, p = 0.05). Conclusion: WMH in the CC are associated with lower cognitive performance through direct and indirect associations with Aß42 and neurodegeneration. Similar associations were seen for frontal WMH. However, a direct association between frontal WMH volume and cognition was not noticed, when considering AD biomarkers. Our study substantiates the clinical relevance and impact of WMH in the CC, in particular the splenium, in AD. 1)Gaubert et al.,2021 2)Garnier‐Crussard et al.,2021 [ABSTRACT FROM AUTHOR]

Background: Cognitive reserve (CR) is a concept that addresses the differences in trajectories of cognitive decline while facing neurodegenerative changes in the brain. Common proxies of CR include demographic or socio‐behavioral measures such as sex and educational/occupational attainment. Recent studies have quantified CR using a residual approach, a direct and cross‐sectional measurement of the discrepancy between estimated cognition and neurodegenerative burden. The associations between these two approaches remain largely unclear. Methods: Data of 801 participants from the German DELCODE study was used, including 215 healthy controls and 586 individuals with increased risk of AD dementia (61 subjective cognitive decline, 150 mild cognitive impairment and 75 aged 80 years and older with a first‐degree relative with AD). To differentiate similar clusters in tested lifestyle factors, we conducted a dimension reduction method using principal component analysis and consequently derived 8 component factor scores. A residualized memory CR score (CRMEM) was calculated as residuals from a multilinear regression model. Functional connectivity was analyzed using resting‐state fMRI data. Results: Partial correlation analyses revealed significant positive correlations between CRMEM and component factors 1 (retirement and living), 3 (educational attainment) and 4 (social network and occupational attainment) in the entire cohort and at risk for AD dementia individuals. Higher CRMEM was associated with higher functional connectivity between the hippocampus and regions related to the default‐mode network. Factor scores 3 and 4 were associated with increased rostral hippocampus‐right angular gyrus functional connectivity. A mediation analysis showed a significant indirect effect of factor 3 on the relationship between CRMEM and rostral hippocampus‐right angular gyrus functional connectivity. Conclusion: CR‐favorable socio‐behavioral factors are correlated with higher CRMEM in healthy aging and AD‐risk groups. Educational attainment might present a rather specific proxy of CR for individuals at AD‐risk. In contrast, mid‐life (occupational attainment) and late‐life factors (retirement years, social network and living status) predict CR both in AD‐risk and healthy aging groups. However, only in the AD‐risk group, hippocampal functional connectivity was higher in individuals with higher CRMEM, mediated in favor of higher educational and female sex, suggesting a close relationship to neural reserve. [ABSTRACT FROM AUTHOR]

Preliminary estimates suggest that current global health‐care systems lack the resource capacity to provide persons with dementia timely access to diagnosis, treatment, and care. There is an increasing need to improve timely identification of individuals who will likely progress to Alzheimer's disease (AD) dementia particularly among under‐represented, underserved, and vulnerable populations. The rapidly evolving area of bioinformatics of health system data and the emergence of fluid‐based biomarkers for pre‐symptomatic AD may provide an innovative strategic option for health system planners. A think‐tank style meeting entitled "The Campaign to Prevent Alzheimer's Disease Work Group on Community‐Based Detection and Assessment of Cognitive Decline" developed recommendations to guide future sustainability activities, public policy campaigns, and implementation pilots. The group identified and explored different pathways of community‐based detection using electronic health records, from different international health‐care systems, to detect and surveil individuals with early possible cognitive impairment. [ABSTRACT FROM AUTHOR]

The increasing global prevalence of dementia demands concrete actions that are aimed strategically at optimizing processes that drive clinical innovation. The first step in this direction requires outlining hurdles in the transition from research to practice. The different parties needed to support translational processes have communication mismatches; methodological gaps hamper evidence‐based decision‐making; and data are insufficient to provide reliable estimates of long‐term health benefits and costs in decisional models. Pilot projects are tackling some of these gaps, but appropriate methods often still need to be devised or adapted to the dementia field. A consistent implementation perspective along the whole translational continuum, explicitly defined and shared among the relevant stakeholders, should overcome the "research‐versus‐adoption" dichotomy, and tackle the implementation cliff early on. Concrete next steps may consist of providing tools that support the effective participation of heterogeneous stakeholders and agreeing on a definition of clinical significance that facilitates the selection of proper outcome measures. [ABSTRACT FROM AUTHOR]

This perspective is a companion to a recent editorial on the use of Bayesian analysis in clinical research. We aim to introduce and highlight the relevance and advantages that Bayesian inference offers to clinical trials using the data on the amyloid antibody aducanumab presented at a Food and Drug Administration hearing in November 2020 as an applied example. We apply Bayesian analysis of model plausibility and effect sizes based on simulated data of the two phase 3 trials of aducanumab in prodromal and mild dementia stages of Alzheimer's disease (AD). Bayesian analysis can quantify evidence in favor of, or against, the presence of an effect (i.e., provide evidence of absence), as well as assess the strength of the effect. This is in contrast to the binary conclusions provided by frequentist tests. [ABSTRACT FROM AUTHOR]

Speech comprehension in noisy environments depends on central auditory functions, which are vulnerable in Alzheimer's disease (AD). Binaural processing exploits two ear sounds to optimally process degraded sound information; its characteristics are poorly understood in AD. We studied behavioral and electrophysiological alterations in binaural processing among 121 participants (AD = 27; amnestic mild cognitive impairment [aMCI] = 33; subjective cognitive decline [SCD] = 30; cognitively normal [CN] = 31). We observed impairment of binaural processing in AD and aMCI, and detected a U‐shaped curve change in phase synchrony (declining from CN to SCD and to aMCI, but increasing from aMCI to AD). This improvement in phase synchrony accompanying more severe cognitive stages could reflect neural adaptation for binaural processing. Moreover, increased phase synchrony is associated with worse memory during the stages when neural adaptation apparently occurs. These findings support a hypothesis that neural adaptation for binaural processing deficit may exacerbate cognitive impairment, which could help identify biomarkers and therapeutic targets in AD. [ABSTRACT FROM AUTHOR]

Background: While neuroinflammation is reckoned as a pathological hallmark of AD, research on suitable biomarkers is still ongoing. Here, we report on findings from the DZNE DELCODE, Fundacío ACE and other cohorts demonstrating distinct inflammatory biomarker profiles in CSF and serum. Intriguingly, within these profiles, soluble TAM receptor markers are elevated in neurodegeneration but still relate to protection of cognition and brain structure. Method: We investigated a panel of 20 experimental biomarkers utilizing customized immunoassays in CSF and serum samples of DELCODE and other cohorts with a total of >1000 subjects, including healthy controls, subjective cognitive decline, mild cognitive impairment, AD relatives and AD patients. Data were analyzed in relation to clinical and biomarker‐based staging as well as cognitive and structural imaging composite scores, adjusted for covariates such as age. Result: Various inflammatory markers, when measured in CSF, were found to correlate to tau isoforms and other neurodegeneration markers and to be elevated in pre‐dementia stage subjects with already pathological tau levels. Among these, soluble TAM receptors sAXL and sTyro3 were related to preserved cognition and brain structure. In serum, inflammatory markers displayed different interrelations, with individual proteins in serum showing no or modest correlation to their CSF counterparts or other AD biomarkers. Noteworthy, serum soluble AXL increased only in AD subjects and related to decreased structure and function. Conclusion: Neurodegeneration in AD is accompanied by a pattern of elevated inflammatory CSF biomarkers. These proteins likely represent cellular responses to neuronal damage and are evident already at pre‐dementia stages of disease. Within this response, upregulation of TAM receptors in the brain could serve to regulate neuroinflammation and promote cellular survival, with receptor turnover resulting in elevated CSF levels. Noteworthy, blood signatures of the same biomarkers, though not without significance, show different patterns of relations towards disease features, likely reflecting distinct peripheral cellular origins and biological functions of the respective proteins. These findings point towards TAM signalling as potential target for future therapeutic intervention, especially in subjects with pre‐dementia neurodegeneration phenotypes. As such, CSF soluble TAM levels might provide promising readout biomarkers. [ABSTRACT FROM AUTHOR]

Background: Neuroinflammation is a hallmark of Alzheimer ́s disease (AD) and other neurodegenerative disorders and is likely to be triggered throughout different stages of the disease. Microglia and Astrocytes are the main resident glia that mediate neuroinflammation through production of cytokines, chemokines and other neuroinflammatory biomarkers. Inflammatory processes have been implicated in the pathogenesis of cerebrovascular disease and white matter (WM) injury. However, imaging studies on the contribution of inflammation on WM structure in the aging and AD are rare. Method: Here, we aim to examine the relationship between inflammatory markers and WM hyperintensities (WMH) in the spectrum from normal aging towards AD. To do that, we used baseline data from the DZNE DELCODE study that is enriched in subjects at risk for development of AD and examined a panel of 16 inflammatory biomarkers from CSF of 249 subjects who also underwent FLAIR imaging. Participants included cognitively unimpaired (CU) individuals (healthy controls, AD relatives, and SCD) and cognitively impaired patients (CI) with MCI or AD dementia. WMH lesion volumes were automatically segmented from FLAIR images. Principal component analysis on the CSF markers generated one main composite factor (CP1) that included mainly TREM2, YKL40, AXL, Tyro3 and C1q (see Figure). Age, sex, vascular risk factors, Abeta ratio and ptau181 were used as covariates. Result: Linear regression models showed that higher values of this inflammatory composite factor was related to lower global WMH (p<0.01) and better memory performance (p<0.01) in the whole sample. These effects were also significant when including whole brain GM volume as additional covariate. Mediation model showed that global WMH partially mediated the effect of neuroinflammation on memory performance. Conclusion: These results suggest that some neuroinflammatory markers (e.g. sTyro3 and sAXL) might have a protective effect on WM structure, thus being beneficial for memory function as suggested by a recent study (Brosseron, Maass, Kleineidam et al, 2022), in which sTyro3 and sAXL were related to higher GM volume. Follow‐up analyses will aim to distinguish the effect of neuroinflammation in different clinical groups. Longitudinal studies are ultimately needed to determine whether the observed effect is "protective" or related to "brain reserve". [ABSTRACT FROM AUTHOR]

Background: The NIA‐AA proposed ATN (Amyloid/Tau/Neurodegeneration) as a classification system for AD pathology. The Amyloid Cascade Hypothesis (ACH) implies a sequence across ATN groups that patients might undergo during transition from healthy towards AD: A‐T‐N‐→A+T‐N‐→A+T+N‐→A+T+N+. Here we assess the evidence for monotonic brain volume decline for this particular (Amyloid‐conversion first, Tau‐conversion second, N‐conversion last; therefore ‘ATN’) and alternative progressions (ANT, TAN, TNA, NAT, NTA) using Voxel‐based Morphometry (VBM) of brain anatomy in a large MRI sample. Method: We used the DELCODE cohort of 437 subjects (49% female) which underwent lumbar puncture, MRI scanning and neuropsychological assessment. ATN classification was performed using (A+/‐) CSF‐Abeta42over40, (T+/‐) CSF‐phospho‐Tau, and (N+/‐) adjusted hippocampal volume. We compared voxel‐based model evidence for monotonic decline of gray matter volume across various sequences over ATN groups accounting for age, sex, education, TIV and WMH. The evidence of each progression was assessed using the Bayesian Information Criterion on voxel‐ and ROI‐level. First, face validity of the ACH transition trajectory A‐T‐N‐→A+T‐N‐→A+T+N‐→A+T+N+ for VBM was compared against 23 biologically less plausible (permuted) sequences among AD‐continuum ATN groups. Then we evaluated the evidence for 6 brain volume progressions from A‐T‐N‐ towards A+T+N+ (ATN, ANT, TAN, TNA, NAT, NTA) including also non‐AD continuum ATN groups. Result: The ACH‐based progression A‐T‐N‐→A+T‐N‐→A+T+N‐→A+T+N+ is in line with cognitive decline and clinical diagnosis (Figure 1&2). It also has highest evidence in 9% of the gray matter voxels (especially MTL; Figure 3&4). Many (especially cortical) regions were compatible with alternative non‐monotonic volume progressions (‘AP 1’: 16%, ‘AP 2’: 14%; see Figure 3) over ACH progression sequence, compatible with early amyloid‐related tissue expansion or sampling effects due to brain‐reserve (Figure 5). Volume decline in 65% of voxels was more compatible with ATN/ANT progression (A flips first) when compared to alternative sequences (TAN, TNA, NAT, NTA). Conclusion: Early Amyloid status conversion (before Tau and Neurodegeneration) is compatible with brain volume loss observed during AD progression. The ATN classification and the ACH are compatible with monotonic progress of MTL atrophy. [ABSTRACT FROM AUTHOR]

Background: The Locus Coeruleus (LC) may play an important role in the pathogenesis of Alzheimer's disease (AD). Neuromelanin‐sensitive Magnetic Resonance Imaging (MRI) permits the visualization of the LC in vivo. Previously, we proposed an automatic, deep learning‐based approach to segmenting the LC in a cohort of 82 healthy young and older adults (82 HC; Dünnwald et al. 2021). Here, we applied the same automatic segmentation method to baseline data from the DZNE Longitudinal Cognitive Impairment and Dementia (DELCODE) study comprising 42 healthy elderly adults (HEA), 18 participants with subjective cognitive decline (SCD), 25 participants with mild cognitive impairment (MCI) and 11 participants with AD. Method: The LC was visualized using 3T T1‐weighted Fast Low Angle Shot (FLASH) MRI acquired at 0.75mm isotropic resolution. Prior to processing, the data was sinc‐interpolated to a resolution of 0.375mm³. The automated segmentation pipeline comprises two consecutive Convolutional Neural Networks (CNNs), which perform LC centerpoint regression and segmentation (see Fig. 1). The networks were trained only on the 82 HC dataset using a cross‐validation scheme. We applied the networks to the unseen DELCODE data and assessed their performance with respect to manually delineated masks from two trained raters using Dice similarity coefficient (DSC) and intraclass correlation coefficient (ICC) of contrast ratios (CRs). Result: In HEA, the networks showed similar agreement (DSC, ICC) compared to that observed between two independent raters. Using DSC, automated segmentation of SCD, MCI and AD groups showed less agreement than in the HEA group with 66.67%, 64.86%, 59.77% and 67.06% on average respectively (see Fig. 2). However, good reliability between automated and manually delineated masks for all groups using LC MRI contrast was observed (see Tab. 1) indicating that CRs may be relatively robust wrt. mask differences (see Fig. 3 and 4 for qualitative comparisons). Conclusion: The results demonstrate good reliability between manual and automatically generated LC segmentations with respect to LC MRI contrast using networks trained on healthy older adults. Additional fine‐tuning of the networks to account for the variance in AD should be explored as a means to further improve reliability. [ABSTRACT FROM AUTHOR]

Background: Although deep learning approaches achieve high diagnostic accuracy for detecting Alzheimer's disease (AD) based on MRI scans, they are rarely applied in clinical research due to a lack of suitable methods for model comprehensibility and interpretability. Recent advances in convolutional neural networks (CNN) visualization algorithms may help to overcome these problems. Method: We implemented a CNN model structure, trained it on 662 T1‐weighted MRI scans obtained from ADNI in a twentyfold cross‐validation procedure, and validated it on 1655 cases from three independent samples. Various CNN visualization algorithms were compared, which generated relevance maps indicating the contribution of individual image areas for detecting AD. We developed an interactive web application to display the 3D relevance maps and interactively change various visualization parameters. We assessed the clinical utility of relevance maps by comparing hippocampus relevance scores with hippocampus volume. Result: Across the three independent validation datasets (Fig. 1), group separation showed high accuracy for AD dementia versus controls (AUC≥0.92) and moderate accuracy for amnestic mild cognitive impairment (MCI) versus controls (AUC≥0.73). Relevance maps obtained from Layer‐wise Relevance Propagation (LRP) provided a high spatial resolution and strongest focus (Fig. 2 & Fig. 3). LRP maps indicated that hippocampal atrophy was the most informative factor for AD detection (Fig. 4), with additional contributions from atrophy in other cortical and subcortical regions. Relevance scores within the hippocampus were highly correlated with hippocampal volumes (median: r=‐0.81, Fig. 5). The relevance maps of individual patients revealed additional clusters in the frontal and occipital lobe, which may be an indicator of model overfitting or potential bias of the training sample. When comparing the twenty cross‐validation models, stronger focus of the models on irrelevant areas was associated with lower accuracy to detect MCI. Conclusion: The relevance maps highlighted atrophy in regions that we had hypothesized a priori, which strengthens the overall comprehensibility and validity of the CNN models. [ABSTRACT FROM AUTHOR]

Background: The substantia nigra (SN) is susceptible to neurodegeneration in Alzheimer's disease. Automatic segmentation of the SN using MRI permits in vivo morphological assessment of the SN in cohort studies. Here we evaluate the multi‐brain segmentation (MB, Brudfors, 2020) to learn a probabilistic tissue prior of the SN using neuromelanin‐sensitive MRI while systematically studying effects of (A) SN tissue contrast; and (B) volumetric differences between healthy subjects and memory patients. Method: We studied 50 3T single‐site T1w FLASH MRI from cognitively healthy older adults from the DZNEDELCODE cohort and a second ageing cohort in Magdeburg and 25 multi‐site diagnosed memory patients (MCI or AD). We quantified local SN signal contrast and image noise as a quality metric (obtained from CAT/SPM toolbox). We learnt tissue priors for each 10, 20, 30 and 50 older adults with the highest SN tissue contrast. For each tissue prior, we obtained model‐based SN tissue segments and calculated (integrated) SN volume. We compared SN volume between tissue prior segmentations and correlated it to age and quality. We coregistered all patients to the N = 50 tissue prior and compared volumetric differences between healthy adults and patients using voxel‐based morphometry (VBM). Result: The template‐space N = 50 SN prior (in red) was visually larger than all other priors (Fig 1A). Patients visually had a lower SN volume than healthy from N = 50 (Fig 1B). The N = 50 native space SN tissue prior volume was significantly higher than all other tissue prior volumes (p>0.01, Fig 2A). SN volume correlated with quality for N = 50 (p = 0.02, Fig 2B). The N = 50 sample SN contrast (Fig 2C) did not differ between patients and healthy adults. Patients had a decreased volume in a cluster overlapping with the SN (N = 268, pFDR corrected = 0.02 (Fig 2D). Conclusion: Here we demonstrate that model‐based learning of a probabilistic SN tissue prior using intensity‐based generative approach to segmentation is feasable in a heterogenous cohort. Additionally, using this prior, we showed that while there is no difference of the SN contrast, there is a significant decrease in SN volume consistent with previous analyses (Krohn et al 2022). [ABSTRACT FROM AUTHOR]

Background: Age‐related cognitive decline increases the need for cognitive interventions to maintain cognitive function. Cognitive training is considered an effective non‐pharmacological intervention. Transfer of training gains to untrained tasks is a key indicator for the effectiveness of cognitive training. However, the underlying brain mechanisms need to be further investigated. We implemented a cognitive training study to assess functional connectivity determinants of transfer of training gains. Method: A sample of 181 healthy older adults (mean age: 68 years) underwent a 4‐week cognitive training across three sites. The control group consisted of 54 older adults. To evaluate transfer and training effects, participants underwent a neuropsychological assessment before and after the training. A second follow‐up assessment was applied 12 weeks after the training. The training group was divided in subjects who had and who did not have successful transfer, which was defined as higher improvement in cognitive tasks than the control group. We used composite scores representing working memory, memory and executive functions to assess transfer and training effects. Baseline resting‐state functional magnetic resonance imaging was used to investigate the functional connectivity of brain networks associated with cognitive functions. We extracted brain resting state networks using the Independent Component Analysis (ICA) approach. Result: We observed successful transfer of cognitive training gains in most of the participants. Our results demonstrated spatially restricted effects (p<.01 uncorrected) for the association of transfer of gains with the resting‐state connectivity of brain networks, such as the Default Mode Network and Central Executive Network. Conclusion: Transfer of training gains in aging is possible. A strong association between transfer of gains and resting‐state functional connectivity was not identified. [ABSTRACT FROM AUTHOR]

Background: Participatory research refer to the process of actively involving people with lived experience of a condition into the research process to improve its relevance, quality, and impact. Evidence indicates that engaging patients in research increases recruitment rates and supports researchers in obtaining funding, developing study protocols, and selecting appropriate outcome measures. The challenge is to establish a sustainable structure to include patient groups which are underrepresented yet, such as patients with neurodegenerative diseases. Objective: To develop, implement, and evaluate a patient advisory board (the "PART‐Beirat") facilitating involvement in research at the Rostock University Medical Center. As part of the project, we examine the prior knowledge and attitudes toward participatory research. Method: The project consists of three phases over three years and is supported by the Robert Bosch Stiftung. The first phase involves establishing the PART‐project's organizational structure, developing key documents and procedures, collecting knowledge (e. g. systematic reviews, survey) and raising awareness. In the second phase, we will connect people with lived experience with researchers to establish topic‐specific (neurodegenerative diseases) PART‐advisory boards. In the third phase, we will increase the number of projects within the PART‐Beirat, monitor their progress and share best practices across the research landscape. In phase one, we conduct a standardized survey on the current knowledge on participatory research among older adults. The questionnaire is based on a previous study conducted at the University of Zurich in 2020. Result: The survey covers participants' prior knowledge and attitude towards participatory research, willingness to engage as well as time they would want to invest into participatory research. Data collection of the survey will begin in January 2023. Descriptive results of the survey will be presented. Conclusion: At present, we are underway to develop the organizational structure of the patient advisory board to involve hard‐to‐reach patients and caregivers (PART project). The results of the survey will help us to identify the current level of knowledge on participatory research as well as attitudes towards and willingness to contribute to participatory research. This will provide us with a baseline which we hope to improve in the next three years with the establishment of the PART‐Beirat. [ABSTRACT FROM AUTHOR]

Background: It is well established that socioeconomic disadvantages such as low income are associated with a higher risk for poor cognitive health in old age. Under the concept of social deprivation, researchers have recently started exploring a broader concept of social embedding including, for instance, unemployment and asset ownership. However, little known of other characteristics of social deprivation and to what extent they are associated with cognitive health. Method: Participants of the multicenter DZNE Cognitive Impairment and Dementia Study (DELCODE) were asked to complete a questionnaire on four characteristics of social deprivation, (1) Conditions of the living environment, (2) Regional accessibility, (3) Neighborhood support, (4) Family social support. A total of N = 296, 48.3% male, M = 70.8 (SD = 5.8) years old, n = 97 cognitive healthy, n = 161 subjective cognitive decline (SCD), n = 38 mild cognitive impairment (MCI)) returned the questionnaire. Using confirmatory factor analysis, we excluded questions with non‐significant loadings and with coefficients <0.5. The latent scores were saved and a sum score was calculated. The scores were categorized into tertiles (high, medium, low). Result: Results from logistic regression (adjusted for age, gender, education, family status, depression, diabetes, hypertension, hypercholesterol, cerebrovascular diseases, heart disease, and body mass index) indicated that those with low (compared to high) social deprivation had a significantly reduced risk for SCD (OR = 0.38, p = 0.006) and MCI (OR = 0.25, p = 0.018). Of the individual factor scores, only Neighborhood support was significantly associated with SCD (OR = 0.48, p = 0.030) and MCI (OR = 0.32, p = 0.049). Conclusion: Our findings suggest that social deprivation and, in particularly, neighborhood support such as visits, helping out, and receiving/giving advice can play an important role in cognitive health in old age. Accordingly, individuals with a high risk for age‐related cognitive impairment might benefit from being embedded in a supportive neighborhood. [ABSTRACT FROM AUTHOR]

Background: Persons living with dementia (PwD) are commonly affected by low‐value medications (Lvm), i.e., medications unlikely to benefit patients but to cause harm. Lvm in PwD have been associated with negative physical, psychological, and financial outcomes. However, longitudinal effects have not yet been evaluated. Therefore, we aimed to analyze the impact of Lvm on patient‐centered outcomes among PwD over 24 months. Method: This longitudinal analysis was based on 352 community‐dwelling PwD. Data were assessed at baseline and after 12 and 24 months. Medications that were explicitly not recommended were used to identify Lvm dichotomously (yes/no) and cumulatively (once, over one or two years). The 12‐Item Short‐Form Health Survey assessed patients' health‐related quality of life (HRQoL). Hospitalizations were assessed retrospectively for 12 months. Health care costs were monetarized by standardized unit costs. Multiple panel‐specific regression models were applied to analyze the impact of Lvm on HRQoL, hospitalizations and costs. Result: Over 24 months, 182 PwD (52%) received Lvm at least once and 56 (16%) continuously. The Lvm prevalence decreased from 36% (CI95% 30.8% – 40.8%) at baseline to 29% (CI95% 24.2% – 33.7%) two years later. Treating PwD with Lvm significantly increased the risk of hospitalization by 58% (CI95% 1.14 OR – 2.19 OR; p = 0.006), increased health care costs by €5,359 (CI95% ‐790€ – 11,508€; p = 0.088), and reduced patients' HRQoL (b = ‐1.81; CI95% ‐3.00 – ‐0.63; p = 0.003). HRQoL declined more strongly the longer that Lvm was received, whereas hospitalizations and health care costs were substantially affected by short‐term Lvm use, indicated by an increased hospitalization risk due to receiving Lvm over one year of 178% (CI95% 1.32 OR – 5.86 OR; p = 0.007) and costs for receiving Lvm once of €8,939 (CI95% €‐590€ – €18,469; p = 0.066). Conclusion: More than every second PwD received Lvm once, up to 12 months or continuously over 24 months, negatively impacting patient‐reported HRQoL, hospitalizations, and costs. While continuous Lvm intake decreased patients' HRQoL, receiving Lvm in the short term was relevant regarding further increases in hospitalizations and costs. Innovative approaches are needed to encourage prescribers to avoid and replace Lvm in dementia care. [ABSTRACT FROM AUTHOR]

Background: Almost two‐thirds of people with dementia (PwD) living at home receive care from a family or other informal caregiver. Evidence shows that family caregivers experience increased physical, psychological, emotional, and social stress which, in the long term, results in adverse health outcomes. The development of effective healthcare and support management for family caregivers is vital. Therefore, our aim was to examine and compare the perceptions of participants who received a digitally supported care management programme with those who received usual care. Method: This study was embedded within a multi‐centre, cluster randomized controlled trial (GAIN study) examining the effectiveness of a care management programme for family caregivers of people with dementia. The trial is registered at ClinicalTrials.gov (NCT04037501). Data collected through semi‐structured interviews with participants of the GAIN trial were audio recorded, transcribed and analysed using framework analysis. We developed two semi‐structured interview schedules, each tailored to the content of the group (control or intervention). Result: We interviewed 36 dementia caregivers (30 women, six men) of whom 20 were in the intervention and 16 in the control group. The mean age was 68 years (SD 11,28, range 50‐82). The majority was the caregiver for their spouse, six were the caregiver for their parent and one was the caregiver for their aunt. The lengths of interviews varied between 15‐82 minutes with most interviews being 35 minutes long. Six themes were identified: (1) Health and well‐being before participating in GAIN (2) Use of services and support (3) Perceived health changes (4) Additional services discussed & received in the intervention group (5) Impact of study nurse support and (6) Possible improvements. Each theme had further sub‐themes and categories, which will be presented. Conclusion: Overall, participants in the care management programme reported benefits and additional services they used as a result of being in the intervention group (e.g., rehabilitation, home adaptations, care services) compared to the control group. Having someone professional by their side was reported to be helpful and motivating. Participants of both groups also reported that they preferred house visits rather than telephone contacts. The results can be used to further improve the care management programme. [ABSTRACT FROM AUTHOR]

Background: Almost two‐thirds of people with dementia (PwD) living at home receive care from informal caregivers. The caregiver's work load can be comparable or above a full‐time employment. Evidence shows that family caregivers have a higher risk for psychiatric and non‐psychiatric diseases compared to non‐caregivers. A dyadic approach on disease management can help to reduce the burden of care and increase the quality of life (QoL) of caregivers and PwD. Methods: The cluster randomized controlled trial "Gesund Angehörige Pflegen" (GAIN; ClinicalTrials.gov Identifier NCT04037501) conducted in general practitioner (GP) practices and memory clinics in Northern Germany aimed to evaluate the effectiveness of a 6‐months digitally supported care management program delivered by specifically qualified study nurses to reduce unmet needs of informal caregivers of PwD. Primary outcomes were the number of self‐reported unmet needs, regarding the caregiver and the PwD, assessed with a modified version of the Camberwell Assessment of Need for the Elderly (CANE) and the health‐related quality of life with the EQ‐5D‐5L questionnaire. A generalized linear mixed effects model was used with intercept as random effect. Results: The recruitment for the GAIN trial (October 2020 to January 2022) yielded n = 192 participants (mean age: 65 years, women 75%). The number of identified unmet needs was on average 8.66 (range 1 – 30). Analyses of the primary endpoints revealed a statistically significantly higher reduction of unmet needs of caregivers in the intervention group compared to the control group. Evaluation of the EQ‐5D‐5L showed no significant difference between groups. Conclusion: The GAIN care management program was able to lower the number of unmet needs for informal dementia caregivers. Health related quality of life showed a major ceiling effect (high scoring at baseline), which might explain the lack of an effect. The study shows the benefit of a computerized self‐assessment system in primary care and should be further developed as an entry point to the existing health care system. [ABSTRACT FROM AUTHOR]

Background: The clinical relevance and longitudinal impact of minor neuropsychological deficits (MND) in cognitively normal memory clinic patients with subjective cognitive decline (SCD) is still unclear. To address this, we set out to investigate whether MND in SCD patients are related to Alzheimer´s disease (AD) pathology and future cognitive decline. In addition, we wanted to assess whether SCD patients have an increased risk of neuropathology and cognitive decline even in the absence of MND. Method: We included 233 cognitively normal, healthy control participants (HC) without subjective cognitive concerns and 439 memory clinic SCD patients with available baseline CSF and/or longitudinal cognitive data from the observational DZNE Longitudinal Cognitive Impairment and Dementia (DELCODE) study. Participants, who scored at least 0.5SD below the mean on a composite measure calculated from the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) neuropsychological assessment battery, were classified as having MND. We compared the resulting participant groups regarding their baseline CSF Aβ42/40, p‐tau181, t‐tau and Aβ42/p‐tau181 levels, longitudinal preclinical Alzheimer´s cognitive composite (PACC5) trajectories and risk of progression to incident mild cognitive impairment (MCI). Result: Compared to SCD patients without MND (n = 384), SCD patients with MND (n = 55, 12.5% of SCD sample) showed significantly elevated CSF AD biomarker levels, accelerated PACC5 decline and a higher risk of progression to incident MCI. Baseline MND 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 to incident MCI within 3 years. SCD patients without MND showed increased PACC5 decline and a higher risk of incident MCI compared to HC participants without MND (n = 215), but did not differ from HC participants in their CSF biomarker levels. Conclusion: MND are a risk factor for AD pathology and cognitive decline in memory clinic patients with SCD. The assessment of MND could thus provide useful information for AD risk stratification and enrichment in SCD samples. Importantly, SCD patients still have an increased risk for cognitive decline in the absence of MND. [ABSTRACT FROM AUTHOR]