Different inflammatory signatures based on CSF biomarkers relate to preserved or diminished brain structure and cognition.

Neuroinflammation is a hallmark of Alzheimer's disease (AD) and both positive and negative associations of individual inflammation-related markers with brain structure and cognitive function have been described. We aimed to identify inflammatory signatures of CSF immune-related markers that relate to changes of brain structure and cognition across the clinical spectrum ranging from normal aging to AD. A panel of 16 inflammatory markers, Aß42/40 and p-tau181 were measured in CSF at baseline in the DZNE DELCODE cohort (n = 295); a longitudinal observational study focusing on at-risk stages of AD. Volumetric maps of gray and white matter (GM/WM; n = 261) and white matter hyperintensities (WMHs, n = 249) were derived from baseline MRIs. Cognitive decline (n = 204) and the rate of change in GM volume was measured in subjects with at least 3 visits (n = 175). A principal component analysis on the CSF markers revealed four inflammatory components (PCs). Of these, the first component PC1 (highly loading on sTyro3, sAXL, sTREM2, YKL-40, and C1q) was associated with older age and higher p-tau levels, but with less pathological Aß when controlling for p-tau. PC2 (highly loading on CRP, IL-18, complement factor F/H and C4) was related to male gender, higher body mass index and greater vascular risk. PC1 levels, adjusted for AD markers, were related to higher GM and WM volumes, less WMHs, better baseline memory, and to slower atrophy rates in AD-related areas and less cognitive decline. In contrast, PC2 related to less GM and WM volumes and worse memory at baseline. Similar inflammatory signatures and associations were identified in the independent F.ACE cohort. Our data suggest that there are beneficial and detrimental signatures of inflammatory CSF biomarkers. While higher levels of TAM receptors (sTyro/sAXL) or sTREM2 might reflect a protective glia response to degeneration related to phagocytic clearance, other markers might rather reflect proinflammatory states that have detrimental impact on brain integrity.

Single-value brain activity scores reflect both severity and risk across the Alzheimer's continuum.

Single-value scores reflecting the deviation from (FADE score) or similarity with (SAME score) prototypical novelty-related and memory-related functional magnetic resonance imaging (fMRI) activation patterns in young adults have been proposed as imaging biomarkers of healthy neurocognitive aging. Here, we tested the utility of these scores as potential diagnostic and prognostic markers in Alzheimer's disease (AD) and risk states like mild cognitive impairment (MCI) or subjective cognitive decline (SCD). To this end, we analyzed subsequent memory fMRI data from individuals with SCD, MCI, and AD dementia as well as healthy controls (HC) and first-degree relatives of AD dementia patients (AD-rel) who participated in the multi-center DELCODE study (N = 468). Based on the individual participants' whole-brain fMRI novelty and subsequent memory responses, we calculated the FADE and SAME scores and assessed their association with AD risk stage, neuropsychological test scores, CSF amyloid positivity, and ApoE genotype. Memory-based FADE and SAME scores showed a considerably larger deviation from a reference sample of young adults in the MCI and AD dementia groups compared to HC, SCD and AD-rel. In addition, novelty-based scores significantly differed between the MCI and AD dementia groups. Across the entire sample, single-value scores correlated with neuropsychological test performance. The novelty-based SAME score further differed between Aß-positive and Aß-negative individuals in SCD and AD-rel, and between ApoE ε4 carriers and non-carriers in AD-rel. Hence, FADE and SAME scores are associated with both cognitive performance and individual risk factors for AD. Their potential utility as diagnostic and prognostic biomarkers warrants further exploration, particularly in individuals with SCD and healthy relatives of AD dementia patients.

A generalizable data-driven model of atrophy heterogeneity and progression in memory clinic settings.

Memory clinic patients are a heterogeneous population representing various aetiologies of pathological ageing. It is not known whether divergent spatiotemporal progression patterns of brain atrophy, as previously described in Alzheimer's disease patients, are prevalent and clinically meaningful in this group of older adults. To uncover distinct atrophy subtypes, we applied the Subtype and Stage Inference (SuStaIn) algorithm to baseline structural MRI data from 813 participants enrolled in the DELCODE cohort (mean ± standard deviation, age = 70.67 ± 6.07 years, 52% females). Participants were cognitively unimpaired (n = 285) or fulfilled diagnostic criteria for subjective cognitive decline (n = 342), mild cognitive impairment (n = 118) or dementia of the Alzheimer's type (n = 68). Atrophy subtypes were compared in baseline demographics, fluid Alzheimer's disease biomarker levels, the Preclinical Alzheimer Cognitive Composite (PACC-5) as well as episodic memory and executive functioning. PACC-5 trajectories over up to 240 weeks were examined. To test whether baseline atrophy subtype and stage predicted clinical trajectories before manifest cognitive impairment, we analysed PACC-5 trajectories and mild cognitive impairment conversion rates of cognitively unimpaired participants and those with subjective cognitive decline. Limbic-predominant and hippocampal-sparing atrophy subtypes were identified. Limbic-predominant atrophy initially affected the medial temporal lobes, followed by further temporal regions and, finally, the remaining cortical regions. At baseline, this subtype was related to older age, more pathological Alzheimer's disease biomarker levels, APOE ε4 carriership and an amnestic cognitive impairment. Hippocampal-sparing atrophy initially occurred outside the temporal lobe, with the medial temporal lobe spared up to advanced atrophy stages. This atrophy pattern also affected individuals with positive Alzheimer's disease biomarkers and was associated with more generalized cognitive impairment. Limbic-predominant atrophy, in all participants and in only unimpaired participants, was linked to more negative longitudinal PACC-5 slopes than observed in participants without or with hippocampal-sparing atrophy and increased the risk of mild cognitive impairment conversion. SuStaIn modelling was repeated in a sample from the Swedish BioFINDER-2 cohort. Highly similar atrophy progression patterns and associated cognitive profiles were identified. Cross-cohort model generalizability, at both the subject and the group level, was excellent, indicating reliable performance in previously unseen data. The proposed model is a promising tool for capturing heterogeneity among older adults at early at-risk states for Alzheimer's disease in applied settings. The implementation of atrophy subtype- and stage-specific end points might increase the statistical power of pharmacological trials targeting early Alzheimer's disease.

Psychological outcomes of dementia risk estimation in MCI patients: Results from the PreDADQoL project.

INTRODUCTION: Understanding the impact of biomarker-based dementia risk estimation in people with mild cognitive impairment (MCI) and their care partners is critical for patient care. METHODS: MCI patients and study partners were counseled on Alzheimer's disease (AD) biomarker and dementia risk was disclosed. Data on mood, quality of life (QoL), and satisfaction with life (SwL) were obtained 1 week and 3 months after disclosure. RESULTS: Seventy-six dyads were enrolled, and two-thirds of the patients opted for biomarker testing. None of the participants experienced clinically relevant depression or anxiety after disclosure. All dyads reported moderate to high QoL and SwL throughout the study. Patients reported more subthreshold depressive symptoms 1 week and lower QoL and SwL 3 months after disclosure. In patients, depression (odds ratio [OR]: 0.76) and anxiety (OR: 0.81) were significant predictors for the decision against biomarker testing. DISCUSSION: No major psychological harm is to be expected in MCI patients and care partners after dementia risk disclosure. TRIAL REGISTRATION: This study is registered in the German clinical trials register (Deutsches Register Klinischer Studien, DRKS): http://www.drks.de/DRKS00011155, DRKS registration number: DRKS00011155, date of registration: 18.08.2017. HIGHLIGHTS: Patients with mild cognitive impairment (MCI) and study partners were counseled on Alzheimer's disease (AD) biomarker-based dementia risk estimation. About two-thirds of patients opted for biomarker testing and received their dementia risk based on their AD biomarker status. Patients who decided in favor or against CSF biomarker testing differed in psychological features. We did not observe major psychological harm after the dementia risk disclosure. Coping strategies were associated with better subsequent mood and well-being in all participants.

Plasma amyloid beta X-42/X-40 ratio and cognitive decline in suspected early and preclinical Alzheimer's disease.

INTRODUCTION: Blood-based biomarkers are a cost-effective and minimally invasive method for diagnosing the early and preclinical stages of amyloid positivity (AP). Our study aims to investigate our novel immunoprecipitation-immunoassay (IP-IA) as a test for predicting cognitive decline. METHODS: We measured levels of amyloid beta (Aß)X-40 and AßX-42 in immunoprecipitated eluates from the DELCODE cohort. Receiver-operating characteristic (ROC) curves, regression analyses, and Cox proportional hazard regression models were constructed to predict AP by Aß42/40 classification in cerebrospinal fluid (CSF) and conversion to mild cognitive impairment (MCI) or dementia. RESULTS: We detected a significant correlation between AßX-42/X-40 in plasma and CSF (r = 0.473). Mixed-modeling analysis revealed a substantial prediction of AßX-42/X-40 with an area under the curve (AUC) of 0.81 for AP (sensitivity: 0.79, specificity: 0.74, positive predictive value [PPV]: 0.71, negative predictive value [NPV]: 0.81). In addition, lower AßX-42/X-40 ratios were associated with negative PACC5 slopes, suggesting cognitive decline. DISCUSSION: Our results suggest that assessing the plasma AßX-42/X-40 ratio via our semiautomated IP-IA is a promising biomarker when examining patients with early or preclinical AD. HIGHLIGHTS: New plasma Aß42/Aß40 measurement using immunoprecipitation-immunoassay Plasma Aß42/Aß40 associated with longitudinal cognitive decline Promising biomarker to detect subjective cognitive decline at-risk for brain amyloid positivity.

Amyloid and SCD jointly predict cognitive decline across Chinese and German cohorts.

INTRODUCTION: Subjective cognitive decline (SCD) in amyloid-positive (Aß+) individuals was proposed as a clinical indicator of Stage 2 in the Alzheimer's disease (AD) continuum, but this requires further validation across cultures, measures, and recruitment strategies. METHODS: Eight hundred twenty-one participants from SILCODE and DELCODE cohorts, including normal controls (NC) and individuals with SCD recruited from the community or from memory clinics, underwent neuropsychological assessments over up to 6 years. Amyloid positivity was derived from positron emission tomography or plasma biomarkers. Global cognitive change was analyzed using linear mixed-effects models. RESULTS: In the combined and stratified cohorts, Aß+ participants with SCD showed steeper cognitive decline or diminished practice effects compared with NC or Aß- participants with SCD. These findings were confirmed using different operationalizations of SCD and amyloid positivity, and across different SCD recruitment settings. DISCUSSION: Aß+ individuals with SCD in German and Chinese populations showed greater global cognitive decline and could be targeted for interventional trials. HIGHLIGHTS: SCD in amyloid-positive (Aß+) participants predicts a steeper cognitive decline. This finding does not rely on specific SCD or amyloid operationalization. This finding is not specific to SCD patients recruited from memory clinics. This finding is valid in both German and Chinese populations. Aß+ older adults with SCD could be a target population for interventional trials.

Machine learning-based classification of Alzheimer's disease and its at-risk states using personality traits, anxiety, and depression.

BACKGROUND: Alzheimer's disease (AD) is often preceded by stages of cognitive impairment, namely subjective cognitive decline (SCD) and mild cognitive impairment (MCI). While cerebrospinal fluid (CSF) biomarkers are established predictors of AD, other non-invasive candidate predictors include personality traits, anxiety, and depression, among others. These predictors offer non-invasive assessment and exhibit changes during AD development and preclinical stages. METHODS: In a cross-sectional design, we comparatively evaluated the predictive value of personality traits (Big Five), geriatric anxiety and depression scores, resting-state functional magnetic resonance imaging activity of the default mode network, apoliprotein E (ApoE) genotype, and CSF biomarkers (tTau, pTau181, Aß42/40 ratio) in a multi-class support vector machine classification. Participants included 189 healthy controls (HC), 338 individuals with SCD, 132 with amnestic MCI, and 74 with mild AD from the multicenter DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE). RESULTS: Mean predictive accuracy across all participant groups was highest when utilizing a combination of personality, depression, and anxiety scores. HC were best predicted by a feature set comprised of depression and anxiety scores and participants with AD were best predicted by a feature set containing CSF biomarkers. Classification of participants with SCD or aMCI was near chance level for all assessed feature sets. CONCLUSION: Our results demonstrate predictive value of personality trait and state scores for AD. Importantly, CSF biomarkers, personality, depression, anxiety, and ApoE genotype show complementary value for classification of AD and its at-risk stages.

Biomarker disclosure protocols in prodromal Alzheimer's disease clinical trials.

INTRODUCTION: The development of biomarkers for Alzheimer's disease (AD) has allowed researchers to increase sample homogeneity and test candidate treatments earlier in the disease. The integration of biomarker "screening" criteria should be met with a parallel implementation of standardized methods to disclose biomarker testing results to research participants; however, the extent to which protocolized disclosure occurs in trials is unknown. METHODS: We reviewed the literature to identify prodromal AD trials published in the past 10 years. From these, we quantified the frequency of biomarker disclosure reporting and the depth of descriptions provided. RESULTS: Of 30 published trials using positron emission tomography or cerebrospinal fluid-based amyloid positivity as an eligibility criterion, only one mentioned disclosure, with no details on methods. DISCUSSION: Possible reasons for and implications of this information gap are discussed. Recommendations are provided for trialists considering biomarker screening as part of intervention trials focused on prodromal AD. HIGHLIGHTS: Few prodromal Alzheimer's disease (AD) trial papers discuss biomarker disclosure. Disclosure has implications for participants, family members, and trial success. Disclosure must be consistently integrated and reported in prodromal AD trials. Best practice guidelines and training resources for disclosure are needed.

[Brain health services: individual dementia risk profiling at the Cologne Alzheimer Prevention Center]. / Brain Health Services: Erfassung des individuellen Demenzrisikos am Kölner Alzheimer Präventionszentrum.

BACKGROUND: According to current knowledge approximately 30-40% of all cases of dementia can be attributed to modifiable risk factors. As a result, dementia prevention and the concept of brain health are becoming increasingly relevant. RESEARCH QUESTION: The requirements for brain health services and their implementation are discussed and the Cologne Alzheimer Prevention Center (KAP) of the University Hospital Cologne is described as an example. MATERIAL AND METHODS: In addition to a report on international brain health initiatives, the main activities of the KAP are presented. A program for individual risk profiling and risk communication is provided, which was piloted in the KAP in the context of the "Individual risk profiling for Alzheimer's disease and dementia prevention (INSPIRATION)" study. The prevalence of risk factors in a cognitively healthy sample aged 50-86 years (n = 162) with interest in dementia prevention is presented. RESULTS: The most common risk factors were non-Mediterranean diet, obesity, subjective poor sleep quality and increased stress. Based on these results, preventive interventions can be developed that are adapted to the individual risk profile as a personalized medicine approach. DISCUSSION: Structures such as the KAP can provide individual risk factor assessment and personalized dementia prevention. The efficacy of this approach on dementia risk reduction needs to be evaluated.

Alzheimer's Disease Plasma Biomarkers Distinguish Clinical Diagnostic Groups in Memory Clinic Patients.

INTRODUCTION: Several recent research studies show high performance of blood biomarkers to identify Alzheimer's disease also in the pre-dementia mild cognitive impairment (MCI) stage, but data from the routine clinical care memory clinic setting are needed. METHODS: We examined plasma samples of 144 memory clinic patients, including dementia of Alzheimer type (DAT, n = 54), MCI (n = 57), and subjective cognitive decline (SCD, n = 33), who either presented as self-referrals or were referred by general practitioners or neurologists or psychiatrists. The plasma biomarkers, amyloid-beta42 (Aß42), amyloid-beta40 (Aß40), phospho-Tau181 (pTau181), total-tau (tTau), and neurofilament light (NFL), as well as different ratios, were measured using the ultrasensitive single molecule array (Simoa) immunoassay technology. Statistical analysis including Kruskal-Wallis test, linear regression, and receiver operating characteristics analyses was performed. RESULTS: Of the single markers, we observed statistically significant group effects of pTau181 (H(2) = 34.43, p < 0.001) and NFL (H(2) = 27.66, p < 0.001). All individual group comparisons of pTau181 were significant, while the contrast of SCD versus MCI for NFL was not significant. In addition, the ratios of Aß42/Aß40 (H(2) = 7.50, p = 0.02) and pTau181/Aß42 (H(2) = 25.26, p < 0.001) showed significant group effects with significant difference between all groups for pTau181/Aß42 and an SCD versus MCI difference for Aß42/Aß40. PTau181 showed the highest area under the curve of 0.85 for the discrimination of SCD and DAT with a sensitivity of 80% and a specificity of 79% at a cut-off of 12.2 pg/mL. Age influenced Aß42, Aß40, and NFL concentrations. CONCLUSION: Plasma pTau181 and NFL, as well as the ratios Aß42/Aß40 and pTau181/Aß42, are biomarkers, which can differentiate diagnostic groups in a memory clinic setting outside of research studies.

[Predictive Diagnosis of Alzheimer's Dementia]. / Prädiktive Diagnostik der Alzheimer-Demenz.

Expanding technologies of early disease detection allow to identify Alzheimer's disease (AD) long before symptom onset. Hence, patients are increasingly demanding for these diagnostic procedures. Biomarker-based early detection of AD is therefore increasingly important in the clinical work-up. This article gives an overview of predictive procedures in the field of Alzheimer's dementia.

[Early detection of Alzheimer's disease and dementia prediction in patients with mild cognitive impairment : Summary of current recommendations]. / Früherkennung der Alzheimer-Krankheit und Demenzprädiktion bei Patienten mit leichter kognitiver Störung : Zusammenfassung aktueller Empfehlungen.

Mild cognitive impairment (MCI) is characterized by cognitive deficits but essentially preserved competence in activities of daily living. It is a risk factor for the development of dementia and can reflect a prodromal predementia state of Alzheimer's disease (AD). The pathology of AD is defined by cerebral deposition of amyloid-beta-1-42 protein and aggregation of phosphorylated tau protein, which can be identified in vivo by biomarkers for these alterations. As a result of advances in the field of biomarker-based early detection of AD, it is possible to differentiate between MCI patients with and without a pathological AD condition and therefore, between patients with a low and those with a high risk for the development of dementia. At present there are no specific guideline recommendations in Germany for the diagnostic use of biomarkers in predementia detection of AD and for dementia risk assessment in patients with MCI. This article summarizes the current recommendations of a European expert consensus publication and a multidisciplinary working group of the Alzheimer's Association on the clinical application of cerebrospinal fluid (CSF) biomarkers for the diagnostics of AD in patients with MCI. If the clinical diagnostic criteria for MCI are fulfilled according to the medical history and neuropsychological testing, it is recommended to carry out further diagnostics (blood test, brain imaging) in order to more precisely define the differential diagnostic classification. Counseling on the potential benefits, limits and risks of biomarker testing for early AD detection and dementia risk prediction should always precede assessment of CSF biomarkers. Information about the individual risk of developing dementia has potential consequences for the psychological well-being and life planning; therefore, clinical follow-up visits are recommended.

Predictors of acute and persisting ischemic brain lesions in patients randomized to carotid stenting or endarterectomy.

BACKGROUND AND PURPOSE: We investigated predictors for acute and persisting periprocedural ischemic brain lesions among patients with symptomatic carotid stenosis randomized to stenting or endarterectomy in the International Carotid Stenting Study. METHODS: We assessed acute lesions on diffusion-weighted imaging 1 to 3 days after treatment in 124 stenting and 107 endarterectomy patients and lesions persisting on fluid-attenuated inversion recovery after 1 month in 86 and 75 patients, respectively. RESULTS: Stenting patients had more acute (relative risk, 8.8; 95% confidence interval, 4.4-17.5; P<0.001) and persisting lesions (relative risk, 4.2; 95% confidence interval, 1.6-11.1; P=0.005) than endarterectomy patients. Acute lesion count was associated with age (by trend), male sex, and stroke as the qualifying event in stenting; high systolic blood pressure in endarterectomy; and white matter disease in both groups. The rate of conversion from acute to persisting lesions was lower in the stenting group (relative risk, 0.4; 95% confidence interval, 0.2-0.8; P=0.007), and was only predicted by acute lesion volume. CONCLUSIONS: Stenting caused more acute and persisting ischemic brain lesions than endarterectomy. However, the rate of conversion from acute to persisting lesions was lower in the stenting group, most likely attributable to lower acute lesion volumes. Clinical Trial Registration -URL: www.isrctn.org. Unique identifier: ISRCTN25337470.

Fully Automated MRI-based Analysis of the Locus Coeruleus in Aging and Alzheimer's Disease Dementia using ELSI-Net.

INTRODUCTION: The Locus Coeruleus (LC) is linked to the development and pathophysiology of neurodegenerative diseases such as Alzheimer's Disease (AD). Magnetic Resonance Imaging based LC features have shown potential to assess LC integrity in vivo. METHODS: We present a Deep Learning based LC segmentation and feature extraction method: ELSI-Net and apply it to healthy aging and AD dementia datasets. Agreement to expert raters and previously published LC atlases were assessed. We aimed to reproduce previously reported differences in LC integrity in aging and AD dementia and correlate extracted features to cerebrospinal fluid (CSF) biomarkers of AD pathology. RESULTS: ELSI-Net demonstrated high agreement to expert raters and published atlases. Previously reported group differences in LC integrity were detected and correlations to CSF biomarkers were found. DISCUSSION: Although we found excellent performance, further evaluations on more diverse datasets from clinical cohorts are required for a conclusive assessment of ELSI-Nets general applicability.

Association of Neurogranin and BACE1 With Clinical Cognitive Decline in Individuals With Subjective Cognitive Decline.

BACKGROUND AND OBJECTIVES: CSF biomarkers have immense diagnostic and prognostic potential for Alzheimer disease (AD). However, AD is still diagnosed relatively late in the disease process, sometimes even years after the initial manifestation of cognitive symptoms. Thus, further identification of biomarkers is required to detect related pathology in the preclinical stage and predict cognitive decline. Our study aimed to assess the association of neurogranin and ß-site amyloid precursor protein-cleaving enzyme 1 (BACE1) with cognitive decline in individuals with subjective cognitive decline (SCD). METHODS: We enrolled participants with available neurogranin and BACE1 measurements in CSF from the DELCODE (DZNE-Longitudinal Cognitive Impairment and Dementia, Germany) cohort. The longitudinal change of Preclinical Alzheimer's Cognitive Composite score was assessed as the primary outcome in participants with SCD and controls. The secondary outcome was defined as conversion of SCD to mild cognitive impairment (MCI) during follow-up. Levels of neurogranin, BACE1, and neurogranin/BACE1 ratio across groups were compared by analysis of covariance after adjustment for demographics. The linear mixed-effects model and Cox regression analysis were applied to evaluate their association with cognitive decline and progression of SCD to MCI, respectively. RESULTS: A total of 530 participants (mean age: 70.76 ± 6.01 years, 48.7% female) were analyzed in the study. The rate of cognitive decline was faster in individuals with SCD with higher neurogranin and neurogranin/BACE1 ratio (ß = -0.138, SE = 0.065, p = 0.037, and ß = -0.293, SE = 0.115, p = 0.013). Higher baseline neurogranin and neurogranin/BACE1 ratio were associated with an increased rate of conversion from SCD to MCI (hazard ratio [HR] 1.35 per SD, 95% CI 1.03-1.77, p = 0.028, and HR 1.53 per SD, 95% CI 1.13-2.07, p = 0.007). In addition, the impact of higher neurogranin levels on accelerating the rate of cognitive decline was more pronounced in the SCD group than in cognitively unimpaired controls (ß = -0.077, SE = 0.033, p = 0.020). DISCUSSION: Our findings suggest that CSF neurogranin and BACE1 begin to change in the preclinical stage of AD and they are associated with clinical progression in individuals with SCD.

Longitudinal evidence for a mutually reinforcing relationship between white matter hyperintensities and cortical thickness in cognitively unimpaired older adults.

BACKGROUND: For over three decades, the concomitance of cortical neurodegeneration and white matter hyperintensities (WMH) has sparked discussions about their coupled temporal dynamics. Longitudinal studies supporting this hypothesis nonetheless remain scarce. METHODS: We applied global and regional bivariate latent growth curve modelling to determine the extent to which WMH and cortical thickness were interrelated over a four-year period. For this purpose, we leveraged longitudinal MRI data from 451 cognitively unimpaired participants (DELCODE; median age 69.71 [IQR 65.51, 75.50] years; 52.32% female). Participants underwent MRI sessions annually over a four-year period (1815 sessions in total, with roughly four MRI sessions per participant). We adjusted all models for demographics and cardiovascular risk. RESULTS: Our findings were three-fold. First, larger WMH volumes were linked to lower cortical thickness (σ = -0.165, SE = 0.047, Z = -3.515, P < 0.001). Second, individuals with higher WMH volumes experienced more rapid cortical thinning (σ = -0.226, SE = 0.093, Z = -2.443, P = 0.007), particularly in temporal, cingulate, and insular regions. Similarly, those with lower initial cortical thickness had faster WMH progression (σ = -0.141, SE = 0.060, Z = -2.336, P = 0.009), with this effect being most pronounced in temporal, cingulate, and insular cortices. Third, faster WMH progression was associated with accelerated cortical thinning (σ = -0.239, SE = 0.139, Z = -1.710, P = 0.044), particularly in frontal, occipital, and insular cortical regions. CONCLUSIONS: Our study suggests that cortical thinning and WMH progression could be mutually reinforcing rather than parallel, unrelated processes, which become entangled before cognitive deficits are detectable. TRIAL REGISTRATION: German Clinical Trials Register (DRKS00007966, 04/05/2015).

Symptomatic Clusters Related to Amyloid Positivity in Cognitively Unimpaired Individuals.

Background: The NIA-AA Research Framework on Alzheimer's disease (AD) proposes a transitional stage (stage 2) characterized by subtle cognitive decline, subjective cognitive decline (SCD) and mild neurobehavioral symptoms (NPS). Objective: To identify participant clusters based on stage 2 features and assess their association with amyloid positivity in cognitively unimpaired individuals. Methods: We included baseline data of N = 338 cognitively unimpaired participants from the DELCODE cohort with data on cerebrospinal fluid biomarkers for AD. Classification into the AD continuum (i.e., amyloid positivity, A+) was based on Aß42/40 status. Neuropsychological test data were used to assess subtle objective cognitive dysfunction (OBJ), the subjective cognitive decline interview (SCD-I) was used to detect SCD, and the Neuropsychiatric Inventory Questionnaire (NPI-Q) was used to assess NPS. A two-step cluster analysis was carried out and differences in AD biomarkers between clusters were analyzed. Results: We identified three distinct participant clusters based on presented symptoms. The highest rate of A+ participants (47.6%) was found in a cluster characterized by both OBJ and SCD. A cluster of participants that presented with SCD and NPS (A+:26.6%) and a cluster of participants with overall few symptoms (A+:19.7%) showed amyloid positivity in a range that was not higher than the expected A+ rate for the age group. Across the full sample, participants with a combination of SCD and OBJ in the memory domain showed a lower Aß42/ptau181 ratio compared to those with neither SCD nor OBJ. Conclusions: The cluster characterized by participants with OBJ and concomitant SCD was enriched for amyloid pathology.

Fornix fractional anisotropy mediates the association between Mediterranean diet adherence and memory four years later in older adults without dementia.

Here, we investigated whether fractional anisotropy (FA) of hippocampus-relevant white-matter tracts mediates the association between baseline Mediterranean diet adherence (MeDiAd) and verbal episodic memory over four years. Participants were healthy older adults with and without subjective cognitive decline and patients with amnestic mild cognitive impairment from the DELCODE cohort study (n = 376; age: 71.47 ± 6.09 years; 48.7 % female). MeDiAd and diffusion data were obtained at baseline. Verbal episodic memory was assessed at baseline and four yearly follow-ups. The associations between baseline MeDiAd and white matter, and verbal episodic memory's mean and rate of change over four years were tested with latent growth curve modeling. Baseline MeDiAd was associated with verbal episodic memory four years later (95 % confidence interval, CI [0.01, 0.32]) but not with its rate of change over this period. Baseline Fornix FA mediated - and, thus, explained - that association (95 % CI [0.002, 0.09]). Fornix FA may be an appropriate response biomarker of Mediterranean diet interventions on verbal memory in older adults.

Short communication: Lifetime musical activity and resting-state functional connectivity in cognitive networks.

BACKGROUND: Participation in multimodal leisure activities, such as playing a musical instrument, may be protective against brain aging and dementia in older adults (OA). Potential neuroprotective correlates underlying musical activity remain unclear. OBJECTIVE: This cross-sectional study investigated the association between lifetime musical activity and resting-state functional connectivity (RSFC) in three higher-order brain networks: the Default Mode, Fronto-Parietal, and Salience networks. METHODS: We assessed 130 cognitively unimpaired participants (≥ 60 years) from the baseline cohort of the DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE) study. Lifetime musical activity was operationalized by the self-reported participation in musical instrument playing across early, middle, and late life stages using the Lifetime of Experiences Questionnaire (LEQ). Participants who reported musical activity during all life stages (n = 65) were compared to controls who were matched on demographic and reserve characteristics (including education, intelligence, socioeconomic status, self-reported physical activity, age, and sex) and never played a musical instrument (n = 65) in local (seed-to-voxel) and global (within-network and between-network) RSFC patterns using pre-specified network seeds. RESULTS: Older participants with lifetime musical activity showed significantly higher local RSFC between the medial prefrontal cortex (Default Mode Network seed) and temporal as well as frontal regions, namely the right temporal pole and the right precentral gyrus extending into the superior frontal gyrus, compared to matched controls. There were no significant group differences in global RSFC within or between the three networks. CONCLUSION: We show that playing a musical instrument during life relates to higher RSFC of the medial prefrontal cortex with distant brain regions involved in higher-order cognitive and motor processes. Preserved or enhanced functional connectivity could potentially contribute to better brain health and resilience in OA with a history in musical activity. TRIAL REGISTRATION: German Clinical Trials Register (DRKS00007966, 04/05/2015).

Machine Learning-Based Perivascular Space Volumetry in Alzheimer Disease.

OBJECTIVES: Impaired perivascular clearance has been suggested as a contributing factor to the pathogenesis of Alzheimer disease (AD). However, it remains unresolved when the anatomy of the perivascular space (PVS) is altered during AD progression. Therefore, this study investigates the association between PVS volume and AD progression in cognitively unimpaired (CU) individuals, both with and without subjective cognitive decline (SCD), and in those clinically diagnosed with mild cognitive impairment (MCI) or mild AD. MATERIALS AND METHODS: A convolutional neural network was trained using manually corrected, filter-based segmentations (n = 1000) to automatically segment the PVS in the centrum semiovale from interpolated, coronal T2-weighted magnetic resonance imaging scans (n = 894). These scans were sourced from the national German Center for Neurodegenerative Diseases Longitudinal Cognitive Impairment and Dementia Study. Convolutional neural network-based segmentations and those performed by a human rater were compared in terms of segmentation volume, identified PVS clusters, as well as Dice score. The comparison revealed good segmentation quality (Pearson correlation coefficient r = 0.70 with P < 0.0001 for PVS volume, detection rate in cluster analysis = 84.3%, and Dice score = 59.0%). Subsequent multivariate linear regression analysis, adjusted for participants' age, was performed to correlate PVS volume with clinical diagnoses, disease progression, cerebrospinal fluid biomarkers, lifestyle factors, and cognitive function. Cognitive function was assessed using the Mini-Mental State Examination, the Comprehensive Neuropsychological Test Battery, and the Cognitive Subscale of the 13-Item Alzheimer's Disease Assessment Scale. RESULTS: Multivariate analysis, adjusted for age, revealed that participants with AD and MCI, but not those with SCD, had significantly higher PVS volumes compared with CU participants without SCD ( P = 0.001 for each group). Furthermore, CU participants who developed incident MCI within 4.5 years after the baseline assessment showed significantly higher PVS volumes at baseline compared with those who did not progress to MCI ( P = 0.03). Cognitive function was negatively correlated with PVS volume across all participant groups ( P ≤ 0.005 for each). No significant correlation was found between PVS volume and any of the following parameters: cerebrospinal fluid biomarkers, sleep quality, body mass index, nicotine consumption, or alcohol abuse. CONCLUSIONS: The very early changes of PVS volume may suggest that alterations in PVS function are involved in the pathophysiology of AD. Overall, the volumetric assessment of centrum semiovale PVS represents a very early imaging biomarker for AD.