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

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

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

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

Relevance of Minor Neuropsychological Deficits in Patients With Subjective Cognitive Decline

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

Performance evaluation of automated white matter hyperintensity segmentation algorithms in a multicenter cohort on cognitive impairment and dementia

Background: White matter hyperintensities (WMH), a biomarker of small vessel disease, are often found in Alzheimer’s disease (AD) and their advanced detection and quantification can be beneficial for research and clinical applications. To investigate WMH in large-scale multicenter studies on cognitive impairment and AD, appropriate automated WMH segmentation algorithms are required. This study aimed to compare the performance of segmentation tools and provide information on their application in multicenter research. Methods: We used a pseudo-randomly selected dataset (n = 50) from the DZNE-multicenter observational Longitudinal Cognitive Impairment and Dementia Study (DELCODE) that included 3D fluid-attenuated inversion recovery (FLAIR) images from participants across the cognitive continuum. Performances of top-rated algorithms for automated WMH segmentation [Brain Intensity Abnormality Classification Algorithm (BIANCA), lesion segmentation toolbox (LST), lesion growth algorithm (LGA), LST lesion prediction algorithm (LPA), pgs, and sysu_media] were compared to manual reference segmentation (RS). Results: Across tools, segmentation performance was moderate for global WMH volume and number of detected lesions. After retraining on a DELCODE subset, the deep learning algorithm sysu_media showed the highest performances with an average Dice’s coefficient of 0.702 (±0.109 SD) for volume and a mean F1-score of 0.642 (±0.109 SD) for the number of lesions. The intra-class correlation was excellent for all algorithms (>0.9) but BIANCA (0.835). Performance improved with high WMH burden and varied across brain regions. Conclusion: To conclude, the deep learning algorithm, when retrained, performed well in the multicenter context. Nevertheless, the performance was close to traditional methods. We provide methodological recommendations for future studies using automated WMH segmentation to quantify and assess WMH along the continuum of cognitive impairment and AD dementia

Identification of genetic variants associated with Huntington's disease progression: a genome-wide association study

Background Huntington's disease is caused by a CAG repeat expansion in the huntingtin gene, HTT. Age at onset has been used as a quantitative phenotype in genetic analysis looking for Huntington's disease modifiers, but is hard to define and not always available. Therefore, we aimed to generate a novel measure of disease progression and to identify genetic markers associated with this progression measure. Methods We generated a progression score on the basis of principal component analysis of prospectively acquired longitudinal changes in motor, cognitive, and imaging measures in the 218 indivduals in the TRACK-HD cohort of Huntington's disease gene mutation carriers (data collected 2008–11). We generated a parallel progression score using data from 1773 previously genotyped participants from the European Huntington's Disease Network REGISTRY study of Huntington's disease mutation carriers (data collected 2003–13). We did a genome-wide association analyses in terms of progression for 216 TRACK-HD participants and 1773 REGISTRY participants, then a meta-analysis of these results was undertaken. Findings Longitudinal motor, cognitive, and imaging scores were correlated with each other in TRACK-HD participants, justifying use of a single, cross-domain measure of disease progression in both studies. The TRACK-HD and REGISTRY progression measures were correlated with each other (r=0·674), and with age at onset (TRACK-HD, r=0·315; REGISTRY, r=0·234). The meta-analysis of progression in TRACK-HD and REGISTRY gave a genome-wide significant signal (p=1·12 × 10−10) on chromosome 5 spanning three genes: MSH3, DHFR, and MTRNR2L2. The genes in this locus were associated with progression in TRACK-HD (MSH3 p=2·94 × 10−8 DHFR p=8·37 × 10−7 MTRNR2L2 p=2·15 × 10−9) and to a lesser extent in REGISTRY (MSH3 p=9·36 × 10−4 DHFR p=8·45 × 10−4 MTRNR2L2 p=1·20 × 10−3). The lead single nucleotide polymorphism (SNP) in TRACK-HD (rs557874766) was genome-wide significant in the meta-analysis (p=1·58 × 10−8), and encodes an aminoacid change (Pro67Ala) in MSH3. In TRACK-HD, each copy of the minor allele at this SNP was associated with a 0·4 units per year (95% CI 0·16–0·66) reduction in the rate of change of the Unified Huntington's Disease Rating Scale (UHDRS) Total Motor Score, and a reduction of 0·12 units per year (95% CI 0·06–0·18) in the rate of change of UHDRS Total Functional Capacity score. These associations remained significant after adjusting for age of onset. Interpretation The multidomain progression measure in TRACK-HD was associated with a functional variant that was genome-wide significant in our meta-analysis. The association in only 216 participants implies that the progression measure is a sensitive reflection of disease burden, that the effect size at this locus is large, or both. Knockout of Msh3 reduces somatic expansion in Huntington's disease mouse models, suggesting this mechanism as an area for future therapeutic investigation

Phänotypisierung neurodegenerativer Erkrankungen am Beispiel der Alzheimer-Erkrankung

Hintergrund: In einer alternden Bevölkerung stellt die Alzheimer-Erkrankung als häufigste Demenzform eine zunehmende Herausforderung für unsere Gesellschaft dar. Die Erkenntnisse aus der Forschung der letzten Jahrzehnte haben zu einem zunehmend besseren Verständnis der Pathomechanismen und zu zuverlässigeren Diagnosestellungen geführt. Dennoch werden atypische Verläufe und prodromale Stadien oft nicht erkannt. Um diese sicherer identifizieren zu können, ist neben der Entwicklung von paraklinischen Biomarkern die Kenntnis der typischen Präsentation des Krankheitsbildes, seiner selteneren Manifestationsformen und das Wissen um prodromale Symptome von Bedeutung. Ziel dieser Arbeit war es, unterschiedliche Ansätze der Phänotypisierung der Alzheimer-Krankheit und ihrer Vorstufen zu untersuchen. Methodik: 1. Phänotypisierung über Data Mining: Es wurde mittels eines halbautomatisierten Data Mining-Verfahrens eine Liste mit Symptom-beschreibenden Begriffen erstellt, die in mit dem MeSH-Schlagwort „Alzheimer Disease“ annotierten Abstracts häufiger vorkamen als im Rest der PubMed-Datenbank. 2. Klinische Phänotypisierung über neuropsychologische Testverfahren: Es wurden neuropsychologische Daten von 168 Teilnehmern der longitudinalen Beobachtungsstudie DELCODE des Deutschen Zentrums für neurodegenerative Erkrankungen (DZNE) ausgewertet. Ergebnisse: 1. Nach der oben beschriebenen Methode konnte eine Liste mit 90 klinischen Beschreibungen der Alzheimer-Erkrankung erstellt werden, die neben typischen Symptomen der Alzheimer-Erkrankung auch seltene, z.T. nur kasuistisch beschriebene Symptome, beinhaltete. 2. Mittels neuropsychologischer Testverfahren ließen sich Patienten in einem leichtgradigen Stadium einer Alzheimer-Demenz von Gesunden sowie von Probanden in einem möglichen Prodromalstadium unterscheiden. Eine besonders gute Aussagekraft für die diagnostische Abgrenzung fand sich dabei für Verfahren, die das verbale und das figurale episodische Gedächtnis, die kognitive Flexibilität, die verbale Flüssigkeit und die psychomotorische Geschwindigkeit testen. Bei möglichen Vorstufen einer Alzheimer-Demenz erwiesen sich v.a. Tests des verzögerten Abrufs und des Wiedererkennens gelernter verbaler Informationen als zeitsensible Messinstrumente. Außerdem prädizierten sie am besten eine Konversion zur Alzheimer-Demenz im Folgejahr. Schlussfolgerung: 1. Mit Hilfe von Methoden des Data Mining ist es möglich, eine unvoreingenommene und umfangreiche Phänotypbeschreibung der Alzheimer Erkrankung vorzunehmen. 2. Spezielle neuropsychologische Testverfahren helfen, die Prodromalstadien einer Alzheimer-Erkrankung besser zu charakterisieren. Sie können zudem eine Konversion zur Alzheimer-Demenz anzeigen.Background: In an aging population, Alzheimer's disease, the most common form of dementia, represents an increasing challenge for our society. Research findings in recent decades have led to a better understanding of the pathomechanisms and to more reliable diagnoses. Nevertheless, atypical courses and prodromal stages are often not recognized. In order to be able to identify them more reliably, knowledge of the typical presentation of the disease pattern, its rarer manifestations and knowledge of prodromal symptoms is important in addition to the development of biomarkers. The aim of this study was to investigate different approaches to phenotyping Alzheimer's disease and its prodromal stages. Methods: 1. Phenotyping via data mining: A list of symptom-describing terms that occurred more frequently in abstracts annotated with the MeSH term "Alzheimer's disease" than in the rest of the PubMed database was compiled using a semi-automated data mining procedure. 2. clinical phenotyping using neuropsychological testing: Neuropsychological data of 168 participants of the longitudinal observational study DELCODE of the German Center for Neurodegenerative Diseases (DZNE) were analysed. Results: 1. 90 clinical descriptions of Alzheimer's disease could be compiled using the method described above, which included typical symptoms of Alzheimer's disease as well as rare symptoms, some of which were only described casuistically. 2. By means of neuropsychological testing procedures, patients in a mild stage of Alzheimer's dementia could be distinguished from healthy participants and participants with a possible prodromal stage. A particularly good diagnostic differentiation was found for procedures testing verbal and figural episodic memory, cognitive flexibility, verbal fluency and psychomotor speed. In prodromal stages of Alzheimer's dementia, tests of delayed recall and recognition of learned verbal information proved to be time-sensitive instruments. In addition, they best predicted a conversion to Alzheimer's dementia in the following year. Conclusion: 1. With the help of data mining methods it is possible to provide an unbiased and comprehensive phenotype description of Alzheimer's disease. 2. Neuropsychological test procedures can help to better characterize the prodromal stages of Alzheimer's disease. They can also indicate conversion to Alzheimer's dementia

Potential of Non-Coding RNA as Biomarkers for Progressive Supranuclear Palsy.

Objective markers for the neurodegenerative disorder progressive supranuclear palsy (PSP) are needed to provide a timely diagnosis with greater certainty. Non-coding RNA (ncRNA), including microRNA, piwi-interacting RNA, and transfer RNA, are good candidate markers in other neurodegenerative diseases, but have not been investigated in PSP. Therefore, as proof of principle, we sought to identify whether they were dysregulated in matched serum and cerebrospinal fluid (CSF) samples of patients with PSP. Small RNA-seq was undertaken on serum and CSF samples from healthy controls (n = 20) and patients with PSP (n = 31) in two cohorts, with reverse transcription-quantitative PCR (RT-qPCR) to confirm their dysregulation. Using RT-qPCR, we found in serum significant down-regulation in hsa-miR-92a-3p, hsa-miR-626, hsa-piR-31068, and tRNA-ValCAC. In CSF, both hsa-let-7a-5p and hsa-piR-31068 showed significant up-regulation, consistent with their changes observed in the RNA-seq results. Interestingly, we saw no correlation in the expression of hsa-piR-31068 within our matched serum and CSF samples, suggesting there is no common dysregulatory mechanism between the two biofluids. While these changes were in a small cohort of samples, we have provided novel evidence that ncRNA in biofluids could be possible diagnostic biomarkers for PSP and further work will help to expand this potential

Design and first baseline data of the DZNE multicenter observational study on predementia Alzheimer's disease (DELCODE)

Background: Deep phenotyping and longitudinal assessment of predementia at-risk states of Alzheimer's disease (AD) are required to define populations and outcomes for dementia prevention trials. Subjective cognitive decline (SCD) is a pre-mild cognitive impairment (pre-MCI) at-risk state of dementia, which emerges as a highly promising target for AD prevention. Methods: The German Center for Neurodegenerative Diseases (DZNE) is conducting the multicenter DZNE-Longitudinal Cognitive Impairment and Dementia Study (DELCODE), which focuses on the characterization of SCD in patients recruited from memory clinics. In addition, individuals with amnestic MCI, mild Alzheimer's dementia patients, first-degree relatives of patients with Alzheimer's dementia, and cognitively unimpaired control subjects are studied. The total number of subjects to be enrolled is 1000. Participants receive extensive clinical and neuropsychological assessments, magnetic resonance imaging, positron emission tomography, and biomaterial collection is perfomed. In this publication, we report cognitive and clinical data as well as apolipoprotein E (APOE) genotype and cerebrospinal fluid (CSF) biomarker results of the first 394 baseline data sets. Results: In comparison with the control group, patients with SCD showed slightly poorer performance on cognitive and functional measures (Alzheimer's Disease Assessment Scale-cognitive part, Clinical Dementia Rating, Functional Activities Questionnaire), with all mean scores in a range which would be considered unimpaired. APOE4 genotype was enriched in the SCD group in comparison to what would be expected in the population and the frequency was significantly higher in comparison to the control group. CSF A beta 42 was lower in the SCD group in comparison to the control group at a statistical trend with age as a covariate. There were no group differences in Tau or pTau concentrations between the SCD and the control groups. The differences in all measures between the MCI group and the AD group were as expected. Conclusions: The initial baseline data for DELCODE support the approach of using SCD in patients recruited through memory clinics as an enrichment strategy for late-stage preclinical AD. This is indicated by slightly lower performance in a range of measures in SCD in comparison to the control subjects as well as by enriched APOE4 frequency and lower CSF A beta 42 concentration