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. 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. 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 Aβ42 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. 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 Aβ42 concentration. German Clinical Trials Register DRKS00007966 . Registered 4 May 2015.

Although human endogenous retroviruses (HERVs) represent a substantial proportion of the human genome and some HERVs, such as HERV-K(HML-2), are reported to be involved in neurological disorders, little is known about their biological function. We report that RNA from an HERV-K(HML-2) envelope gene region binds to and activates human Toll-like receptor (TLR) 8, as well as murine Tlr7, expressed in neurons and microglia, thereby causing neurodegeneration. HERV-K(HML-2) RNA introduced into the cerebrospinal fluid (CSF) of either C57BL/6 wild-type mice or APPPS1 mice, a mouse model for Alzheimer’s disease (AD), resulted in neurodegeneration and microglia accumulation. Tlr7-deficient mice were protected against neurodegenerative effects but were resensitized toward HERV-K(HML-2) RNA when neurons ectopically expressed murine Tlr7 or human TLR8. Transcriptome data sets of human AD brain samples revealed a distinct correlation of upregulated HERV-K(HML-2) and TLR8 RNA expression. HERV-K(HML-2) RNA was detectable more frequently in CSF from individuals with AD compared with controls. Our data establish HERV-K(HML-2) RNA as an endogenous ligand for species-specific TLRs 7/8 and imply a functional contribution of human endogenous retroviral transcripts to neurodegenerative processes, such as AD.

Subjective cognitive decline (SCD) has been proposed as a pre-MCI at-risk condition of Alzheimer’s disease (AD). Current research is focusing on a refined assessment of specific SCD features associated with increased risk for AD, as proposed in the SCD-plus criteria. We developed a structured interview (SCD-I) for the assessment of these features and tested their relationship with AD biomarkers. We analyzed data of 205 cognitively normal participants of the DELCODE study (mean age = 68.9 years; 52% female) with available CSF AD biomarkers (Aß-42, p-Tau181, Aß-42/Tau ratio, total Tau). For each of five cognitive domains (including memory, language, attention, planning, others), a study physician asked participants about the following SCD-plus features: the presence of subjective decline, associated worries, onset of SCD, feeling of worse performance than others of the same age group, and informant confirmation. We compared AD biomarkers of subjects endorsing each of these questions with those who did not, controlling for age. SCD was also quantified by two summary scores: the number of fulfilled SCD-plus features, and the number of domains with experienced decline. Covariate-adjusted linear regression analyses were used to test whether these SCD scores predicted abnormality in AD biomarkers. Lower Aß-42 levels were associated with a reported decline in memory and language abilities, and with the following SCD-plus features: onset of subjective decline within 5 years, confirmation of cognitive decline by an informant, and decline-related worries. Furthermore, both quantitative SCD scores were associated with lower Aß42 and lower Aß42/Tau ratio, but not with total Tau or p-Tau181. Findings support the usefulness of a criterion-based interview approach to assess and quantify SCD in the context of AD and validate the current SCD-plus features as predictors of AD pathology. While some features seem to be more closely associated with AD biomarkers than others, aggregated scores over several SCD-plus features or SCD domains may be the best predictors of AD pathology.

The progression of mild cognitive impairment (MCI) to Alzheimer’s disease (AD) dementia can be predicted by cognitive, neuroimaging, and cerebrospinal fluid (CSF) markers. Since most biomarkers reveal complementary information, a combination of biomarkers may increase the predictive power. We investigated which combination of the Mini-Mental State Examination (MMSE), Clinical Dementia Rating (CDR)-sum-of-boxes, the word list delayed free recall from the Consortium to Establish a Registry of Dementia (CERAD) test battery, hippocampal volume (HCV), amyloid-beta1–42 (Aβ42), amyloid-beta1–40 (Aβ40) levels, the ratio of Aβ42/Aβ40, phosphorylated tau, and total tau (t-Tau) levels in the CSF best predicted a short-term conversion from MCI to AD dementia. We used 115 complete datasets from MCI patients of the “Dementia Competence Network”, a German multicenter cohort study with annual follow-up up to 3 years. MCI was broadly defined to include amnestic and nonamnestic syndromes. Variables known to predict progression in MCI patients were selected a priori. Nine individual predictors were compared by receiver operating characteristic (ROC) curve analysis. ROC curves of the five best two-, three-, and four-parameter combinations were analyzed for significant superiority by a bootstrapping wrapper around a support vector machine with linear kernel. The incremental value of combinations was tested for statistical significance by comparing the specificities of the different classifiers at a given sensitivity of 85%. Out of 115 subjects, 28 (24.3%) with MCI progressed to AD dementia within a mean follow-up period of 25.5 months. At baseline, MCI-AD patients were no different from stable MCI in age and gender distribution, but had lower educational attainment. All single biomarkers were significantly different between the two groups at baseline. ROC curves of the individual predictors gave areas under the curve (AUC) between 0.66 and 0.77, and all single predictors were statistically superior to Aβ40. The AUC of the two-parameter combinations ranged from 0.77 to 0.81. The three-parameter combinations ranged from AUC 0.80–0.83, and the four-parameter combination from AUC 0.81–0.82. None of the predictor combinations was significantly superior to the two best single predictors (HCV and t-Tau). When maximizing the AUC differences by fixing sensitivity at 85%, the two- to four-parameter combinations were superior to HCV alone. A combination of two biomarkers of neurodegeneration (e.g., HCV and t-Tau) is not superior over the single parameters in identifying patients with MCI who are most likely to progress to AD dementia, although there is a gradual increase in the statistical measures across increasing biomarker combinations. This may have implications for clinical diagnosis and for selecting subjects for participation in clinical trials.

Alzheimer's disease (AD) may affect all cell types in the central nervous system. Astrocytes have rarely been investigated in the aged brain and the role of astrocytes in AD is poorly understood. In this study, we used acute brain slices from an amyl

Background: Early diagnosis of Alzheimer’s disease (AD) may be corroborated by imaging of beta-amyloid plaques using positron emission tomography (PET). Here, we performed an add-on questionnaire study to evaluate the relevance of florbetaben imaging (BAY 949172) in diagnosis and consecutive management of probable AD patients. Methods: AD patients with a clinical diagnosis in accordance with the NINCDS-ADRDA criteria or controls were imaged using florbetaben. Referring physicians were asked on a voluntary basis about their confidence in initial diagnosis, significance of PET imaging results, and their anticipated consequences for future patient care. Results: 121 questionnaires for probable AD patients and 80 questionnaires for controls were evaluated. In 18% of patients who had initially received the diagnosis of probable AD, PET scans were rated negative, whereas in controls 18% of scans were positive. An increase in confidence in the initial diagnosis was frequently reported (80%). Imaging results had a significant impact on the intended patient care, as judged by the referring physicians; this was most prominent in those patients with a contradicting scan and/or a low confidence in the initial diagnosis. Conclusion: Florbetaben amyloid imaging increases the overall confidence in diagnosis of AD and may frequently influence clinical decisions and patient management.