Alzheimer's Research & Therapy

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ISSN / EISSN : 1758-9193 / 1758-9193
Total articles ≅ 1,056
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, Philip Scheltens, Sangyun Kim, Sungmin Kang, Young Chul Youn, Seong Soo A. An, Jori Tomassen, Bart N. M. van Berckel, Pieter Jelle Visser, Wiesje M. van der Flier, et al.
Alzheimer's Research & Therapy, Volume 13, pp 1-10; doi:10.1186/s13195-021-00873-w

Objective We assessed the performance of plasma amyloid oligomerization tendency (OAβ) as a marker for abnormal amyloid status. Additionally, we examined long-term storage effects on plasma OAβ. Methods We included 399 subjects regardless of clinical diagnosis from the Amsterdam Dementia Cohort and European Medical Information Framework for AD project (age, 63.8 ± 6.6; 44% female). Amyloid status was determined by visual read on positron emission tomography (PET; nabnormal = 206). Plasma OAβ was measured using the multimer detection system (MDS). Long-term storage effects on MDS-OAβ were assessed using general linear models. Associations between plasma MDS-OAβ and Aβ-PET status were assessed using logistic regression and receiver operating characteristics analyses. Correlations between plasma MDS-OAβ and CSF biomarker levels were evaluated using Pearson correlation analyses. Results MDS-OAβ was higher in individuals with abnormal amyloid, and it identified abnormal Aβ-PET with an area under the curve (AUC) of 0.74 (95% CI, 0.67–0.81), especially in samples with a storage duration < 4 years. Combining APOEe4 and age with plasma MDS-OAβ revealed an AUC of 81% for abnormal amyloid PET status (95% CI, 74–87%). Plasma MDS-OAβ correlated negatively with MMSE (r = − 0.29, p < .01) and CSF Aβ42 (r = − 0.20, p < 0.05) and positively with CSF Tau (r = 0.20, p = 0.01). Conclusions Plasma MDS-OAβ combined with APOEe4 and age accurately identifies brain amyloidosis in a large Aβ-confirmed population. Using plasma MDS-OAβ as a screener reduced the costs and number of PET scans needed to screen for amyloidosis, which is relevant for clinical trials. Additionally, plasma MDS-OAβ levels appeared affected by long-term storage duration, which could be of interest for others measuring plasma Aβ biomarkers.
, Ahnjili Zhuparris, Ellen P. Hart, Robert-Jan Doll,
Alzheimer's Research & Therapy, Volume 13, pp 1-11; doi:10.1186/s13195-021-00874-9

Background In the current study, we aimed to develop an algorithm based on biomarkers obtained through non- or minimally invasive procedures to identify healthy elderly subjects who have an increased risk of abnormal cerebrospinal fluid (CSF) amyloid beta42 (Aβ) levels consistent with the presence of Alzheimer’s disease (AD) pathology. The use of the algorithm may help to identify subjects with preclinical AD who are eligible for potential participation in trials with disease modifying compounds being developed for AD. Due to this pre-selection, fewer lumbar punctures will be needed, decreasing overall burden for study subjects and costs. Methods Healthy elderly subjects (n = 200; age 65–70 (N = 100) and age > 70 (N = 100)) with an MMSE > 24 were recruited. An automated central nervous system test battery was used for cognitive profiling. CSF Aβ1-42 concentrations, plasma Aβ1-40, Aβ1-42, neurofilament light, and total Tau concentrations were measured. Aβ1-42/1-40 ratio was calculated for plasma. The neuroinflammation biomarker YKL-40 and APOE ε4 status were determined in plasma. Different mathematical models were evaluated on their sensitivity, specificity, and positive predictive value. A logistic regression algorithm described the data best. Data were analyzed using a 5-fold cross validation logistic regression classifier. Results Two hundred healthy elderly subjects were enrolled in this study. Data of 154 subjects were used for the per protocol analysis. The average age of the 154 subjects was 72.1 (65–86) years. Twenty-four (27.3%) were Aβ positive for AD (age 65–83). The results of the logistic regression classifier showed that predictive features for Aβ positivity/negativity in CSF consist of sex, 7 CNS tests, and 1 plasma-based assay. The model achieved a sensitivity of 70.82% (± 4.35) and a specificity of 89.25% (± 4.35) with respect to identifying abnormal CSF in healthy elderly subjects. The receiver operating characteristic curve showed an AUC of 65% (± 0.10). Conclusion This algorithm would allow for a 70% reduction of lumbar punctures needed to identify subjects with abnormal CSF Aβ levels consistent with AD. The use of this algorithm can be expected to lower overall subject burden and costs of identifying subjects with preclinical AD and therefore of total study costs. Trial registration identifier: ISRCTN79036545 (retrospectively registered).
M. Seibert, V. Mühlbauer, J. Holbrook, S. Voigt-Radloff, S. Brefka, D. Dallmeier, M. Denkinger, C. Schönfeldt-Lecuona, S. Klöppel,
Alzheimer's Research & Therapy, Volume 13; doi:10.1186/s13195-021-00867-8

Many patients with Alzheimer’s disease (AD) are physically frail or have substantial functional impairments. There is growing evidence that such patients are at higher risk for medication-induced adverse events. Furthermore, frailty seems to be more predictive of poor clinical outcomes than chronological age alone. To our knowledge, no systematic review of clinical trials examining drug therapy of AD or behavioural and psychological symptoms of dementia (BPSD) has specifically focused on the topic of physical frailty. Our objective was to evaluate the efficacy and safety of pharmacotherapy in AD patients with frailty or significant functional impairments. We performed a systematic literature search in MEDLINE, Embase and the Cochrane Central Register of Controlled Trials (CENTRAL) for randomized controlled trials (RCTs) of drug therapy of AD and BPSD in patients with significant functional impairments according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement and Cochrane research criteria. Significant functionally impaired patient populations were identified using the recommendations of the Medication and Quality of Life in frail older persons (MedQoL) Research Group. Screening, selection of studies, data extraction and risk of bias assessment were performed independently by two reviewers. Outcomes including functional status, cognitive function, changes in BPSD symptoms, clinical global impression and quality of life were analysed. For assessing harm, we assessed adverse events, drop-outs as a proxy for treatment tolerability and death. Results were analysed according to Cochrane standards and the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Of 45,045 search results, 38,447 abstracts and 187 full texts were screened, and finally, 10 RCTs were included in the systematic review. Selected articles evaluated pharmacotherapy with acetylcholinesterase-inhibitors (AChEI), anticonvulsants, antidepressants and antipsychotics. Studies of AChEIs suggested that patients with significant functional impairments had slight but significant improvements in cognition and that AChEIs were generally well tolerated. Studies of antidepressants did not show significant improvements in depressive symptoms. Antipsychotics and anticonvulsants showed small effects on some BPSD items but also higher rates of adverse events. However, due to the very small number of identified trials, the quality of evidence for all outcomes was low to very low. Overall, the small number of eligible studies demonstrates that significantly functional impaired older patients have not been adequately taken into consideration in most clinical trials investigating drug therapy of AD and BPSD. Due to lack of evidence, it is not possible to give specific recommendations for drug therapy of AD and BSPD in frail older patients or older patients with significant functional impairments. Therefore, clinical trials focussing on frail older adults are urgently required. A standardized approach to physical frailty in future clinical studies is highly desirable. The online version contains supplementary material available at 10.1186/s13195-021-00867-8.
, Maria Josefsson, Annelie Nordin Adolfsson, Mattias Landfors, Karolina Kauppi, Magnus Hultdin, Rolf Adolfsson, Sofie Degerman, Sara Pudas
Alzheimer's Research & Therapy, Volume 13; doi:10.1186/s13195-021-00871-y

Leukocyte telomere length (LTL) has been shown to predict Alzheimer’s disease (AD), albeit inconsistently. Failing to account for the competing risks between AD, other dementia types, and mortality, can be an explanation for the inconsistent findings in previous time-to-event analyses. Furthermore, previous studies indicate that the association between LTL and AD is non-linear and may differ depending on apolipoprotein E (APOE) ε4 allele carriage, the strongest genetic AD predictor. We analyzed whether baseline LTL in interaction with APOE ε4 predicts AD, by following 1306 initially non-demented subjects for 25 years. Gender- and age-residualized LTL (rLTL) was categorized into tertiles of short, medium, and long rLTLs. Two complementary time-to-event models that account for competing risks were used; the Fine-Gray model to estimate the association between the rLTL tertiles and the cumulative incidence of AD, and the cause-specific hazard model to assess whether the cause-specific risk of AD differed between the rLTL groups. Vascular dementia and death were considered competing risk events. Models were adjusted for baseline lifestyle-related risk factors, gender, age, and non-proportional hazards. After follow-up, 149 were diagnosed with AD, 96 were diagnosed with vascular dementia, 465 died without dementia, and 596 remained healthy. Baseline rLTL and other covariates were assessed on average 8 years before AD onset (range 1–24). APOE ε4-carriers had significantly increased incidence of AD, as well as increased cause-specific AD risk. A significant rLTL-APOE interaction indicated that short rLTL at baseline was significantly associated with an increased incidence of AD among non-APOE ε4-carriers (subdistribution hazard ratio = 3.24, CI 1.404–7.462, P = 0.005), as well as borderline associated with increased cause-specific risk of AD (cause-specific hazard ratio = 1.67, CI 0.947–2.964, P = 0.07). Among APOE ε4-carriers, short or long rLTLs were not significantly associated with AD incidence, nor with the cause-specific risk of AD. Our findings from two complementary competing risk time-to-event models indicate that short rLTL may be a valuable predictor of the AD incidence in non-APOE ε4-carriers, on average 8 years before AD onset. More generally, the findings highlight the importance of accounting for competing risks, as well as the APOE status of participants in AD biomarker research. The online version contains supplementary material available at 10.1186/s13195-021-00871-y.
Philippe Desmarais, Andrew F. Gao, Krista Lanctôt, Ekaterina Rogaeva, Joel Ramirez, Nathan Herrmann, Donald T. Stuss, Sandra E. Black, Julia Keith,
Alzheimer's Research & Therapy, Volume 13; doi:10.1186/s13195-021-00869-6

We aimed to systematically describe the burden and distribution of white matter hyperintensities (WMH) and investigate correlations with neuropsychiatric symptoms in pathologically proven Alzheimer’s disease (AD) and frontotemporal lobar degeneration (FTLD). Autopsy-confirmed cases were identified from the Sunnybrook Dementia Study, including 15 cases of AD and 58 cases of FTLD (22 FTLD-TDP cases; 10 FTLD-Tau [Pick’s] cases; 11 FTLD-Tau Corticobasal Degeneration cases; and 15 FTLD-Tau Progressive Supranuclear Palsy cases). Healthy matched controls (n = 35) were included for comparison purposes. Data analyses included ANCOVA to compare the burden of WMH on antemortem brain MRI between groups, adjusted linear regression models to identify associations between WMH burden and neuropsychiatric symptoms, and image-guided pathology review of selected areas of WMH from each pathologic group. Burden and regional distribution of WMH differed significantly between neuropathological groups (F5,77 = 2.67, P’ = 0.029), with the FTLD-TDP group having the highest mean volume globally (8032 ± 8889 mm3) and in frontal regions (4897 ± 6163 mm3). The AD group had the highest mean volume in occipital regions (468 ± 420 mm3). Total score on the Neuropsychiatric Inventory correlated with bilateral frontal WMH volume (β = 0.330, P = 0.006), depression correlated with bilateral occipital WMH volume (β = 0.401, P < 0.001), and apathy correlated with bilateral frontal WMH volume (β = 0.311, P = 0.009), all corrected for the false discovery rate. Image-guided neuropathological assessment of selected cases with the highest burden of WMH in each pathologic group revealed presence of severe gliosis, myelin pallor, and axonal loss, but with no distinguishing features indicative of the underlying proteinopathy. These findings suggest that WMH are associated with neuropsychiatric manifestations in AD and FTLD and that WMH burden and regional distribution in neurodegenerative disorders differ according to the underlying neuropathological processes. The online version contains supplementary material available at 10.1186/s13195-021-00869-6.
Hannah D. Franklin, Lucy L. Russell, Georgia Peakman, Caroline V. Greaves, Martina Bocchetta, Jennifer Nicholas, Jackie Poos, Rhian S. Convery, David M. Cash, John van Swieten, et al.
Alzheimer's Research & Therapy, Volume 13, pp 1-12; doi:10.1186/s13195-021-00865-w

Background Although social cognitive dysfunction is a major feature of frontotemporal dementia (FTD), it has been poorly studied in familial forms. A key goal of studies is to detect early cognitive impairment using validated measures in large patient cohorts. Methods We used the Revised Self-Monitoring Scale (RSMS) as a measure of socioemotional sensitivity in 730 participants from the genetic FTD initiative (GENFI) observational study: 269 mutation-negative healthy controls, 193 C9orf72 expansion carriers, 193 GRN mutation carriers and 75 MAPT mutation carriers. All participants underwent the standardised GENFI clinical assessment including the ‘CDR® plus NACC FTLD’ scale and RSMS. The RSMS total score and its two subscores, socioemotional expressiveness (EX score) and modification of self-presentation (SP score) were measured. Volumetric T1-weighted magnetic resonance imaging was available from 377 mutation carriers for voxel-based morphometry (VBM) analysis. Results The RSMS was decreased in symptomatic mutation carriers in all genetic groups but at a prodromal stage only in the C9orf72 (for the total score and both subscores) and GRN (for the modification of self-presentation subscore) groups. RSMS score correlated with disease severity in all groups. The VBM analysis implicated an overlapping network of regions including the orbitofrontal cortex, insula, temporal pole, medial temporal lobe and striatum. Conclusions The RSMS indexes socioemotional impairment at an early stage of genetic FTD and may be a suitable outcome measure in forthcoming trials.
, , C. De Looze, D. Carey, S. Scarlett, Y. Stern, I. H. Robertson, R. A. Kenny,
Alzheimer's Research & Therapy, Volume 13, pp 1-18; doi:10.1186/s13195-021-00870-z

Background Cognitive reserve is most commonly measured using socio-behavioural proxy variables. These variables are easy to collect, have a straightforward interpretation, and are widely associated with reduced risk of dementia and cognitive decline in epidemiological studies. However, the specific proxies vary across studies and have rarely been assessed in complete models of cognitive reserve (i.e. alongside both a measure of cognitive outcome and a measure of brain structure). Complete models can test independent associations between proxies and cognitive function in addition to the moderation effect of proxies on the brain-cognition relationship. Consequently, there is insufficient empirical evidence guiding the choice of proxy measures of cognitive reserve and poor comparability across studies. Method In a cross-sectional study, we assessed the validity of 5 common proxies (education, occupational complexity, verbal intelligence, leisure activities, and exercise) and all possible combinations of these proxies in 2 separate community-dwelling older adult cohorts: The Irish Longitudinal Study on Ageing (TILDA; N = 313, mean age = 68.9 years, range = 54–88) and the Cognitive Reserve/Reference Ability Neural Network Study (CR/RANN; N = 234, mean age = 64.49 years, range = 50–80). Fifteen models were created with 3 brain structure variables (grey matter volume, hippocampal volume, and mean cortical thickness) and 5 cognitive variables (verbal fluency, processing speed, executive function, episodic memory, and global cognition). Results No moderation effects were observed. There were robust positive associations with cognitive function, independent of brain structure, for 2 individual proxies (verbal intelligence and education) and 16 composites (i.e. combinations of proxies). Verbal intelligence was statistically significant in all models. Education was significant only in models with executive function as the cognitive outcome variable. Three robust composites were observed in more than two-thirds of brain-cognition models: the composites of (1) occupational complexity and verbal intelligence, (2) education and verbal intelligence, and (3) education, occupational complexity, and verbal intelligence. However, no composite had larger average effects nor was more robust than verbal intelligence alone. Conclusion These results support the use of verbal intelligence as a proxy measure of CR in cross-sectional studies of cognitively healthy older adults.
Alzheimer's Research & Therapy, Volume 13, pp 1-30; doi:10.1186/s13195-021-00862-z

Background Blood circulating microRNAs that are specific for Alzheimer’s disease (AD) can be identified from differentially expressed microRNAs (DEmiRNAs). However, non-reproducible and inconsistent reports of DEmiRNAs hinder biomarker development. The most reliable DEmiRNAs can be identified by meta-analysis. To enrich the pool of DEmiRNAs for potential AD biomarkers, we used a machine learning method called adaptive boosting for miRNA disease association (ABMDA) to identify eligible candidates that share similar characteristics with the DEmiRNAs identified from meta-analysis. This study aimed to identify blood circulating DEmiRNAs as potential AD biomarkers by augmenting meta-analysis with the ABMDA ensemble learning method. Methods Studies on DEmiRNAs and their dysregulation states were corroborated with one another by meta-analysis based on a random-effects model. DEmiRNAs identified by meta-analysis were collected as positive examples of miRNA–AD pairs for ABMDA ensemble learning. ABMDA identified similar DEmiRNAs according to a set of predefined criteria. The biological significance of all resulting DEmiRNAs was determined by their target genes according to pathway enrichment analyses. The target genes common to both meta-analysis- and ABMDA-identified DEmiRNAs were collected to construct a network to investigate their biological functions. Results A systematic database search found 7841 studies for an extensive meta-analysis, covering 54 independent comparisons of 47 differential miRNA expression studies, and identified 18 reliable DEmiRNAs. ABMDA ensemble learning was conducted based on the meta-analysis results and the Human MicroRNA Disease Database, which identified 10 additional AD-related DEmiRNAs. These 28 DEmiRNAs and their dysregulated pathways were related to neuroinflammation. The dysregulated pathway related to neuronal cell cycle re-entry (CCR) was the only statistically significant pathway of the ABMDA-identified DEmiRNAs. In the biological network constructed from 1865 common target genes of the identified DEmiRNAs, the multiple core ubiquitin-proteasome system, that is involved in neuroinflammation and CCR, was highly connected. Conclusion This study identified 28 DEmiRNAs as potential AD biomarkers in blood, by meta-analysis and ABMDA ensemble learning in tandem. The DEmiRNAs identified by meta-analysis and ABMDA were significantly related to neuroinflammation, and the ABMDA-identified DEmiRNAs were related to neuronal CCR.
Maria Mensch, Jade Dunot, Sandy M. Yishan, Samuel S. Harris, Aline Blistein, Alban Avdiu, Paula A. Pousinha, Camilla Giudici, Marc Aurel Busche, Peter Jedlicka, et al.
Alzheimer's Research & Therapy, Volume 13, pp 1-13; doi:10.1186/s13195-021-00860-1

Background Amyloid precursor protein (APP) processing is central to Alzheimer’s disease (AD) etiology. As early cognitive alterations in AD are strongly correlated to abnormal information processing due to increasing synaptic impairment, it is crucial to characterize how peptides generated through APP cleavage modulate synapse function. We previously described a novel APP processing pathway producing η-secretase-derived peptides (Aη) and revealed that Aη–α, the longest form of Aη produced by η-secretase and α-secretase cleavage, impaired hippocampal long-term potentiation (LTP) ex vivo and neuronal activity in vivo. Methods With the intention of going beyond this initial observation, we performed a comprehensive analysis to further characterize the effects of both Aη-α and the shorter Aη-β peptide on hippocampus function using ex vivo field electrophysiology, in vivo multiphoton calcium imaging, and in vivo electrophysiology. Results We demonstrate that both synthetic peptides acutely impair LTP at low nanomolar concentrations ex vivo and reveal the N-terminus to be a primary site of activity. We further show that Aη-β, like Aη–α, inhibits neuronal activity in vivo and provide confirmation of LTP impairment by Aη–α in vivo. Conclusions These results provide novel insights into the functional role of the recently discovered η-secretase-derived products and suggest that Aη peptides represent important, pathophysiologically relevant, modulators of hippocampal network activity, with profound implications for APP-targeting therapeutic strategies in AD.
, Bradley F. Boeve, Melissa J. Armstrong, Doug R. Galasko, James E. Galvin, David J. Irwin, James B. Leverenz, Karen Marder, Victor Abler, Kevin Biglan, et al.
Alzheimer's Research & Therapy, Volume 13, pp 1-4; doi:10.1186/s13195-021-00868-7

In 2019, the Lewy Body Dementia Association formed an Industry Advisory Council to bring together a collaborative group of stakeholders with the goal of accelerating clinical research into Lewy body dementia treatments. At the second annual meeting of the Industry Advisory Council, held virtually on June 18, 2020, the key members presented ongoing and planned efforts toward the council’s goals. The meeting also featured a discussion about the effects of the COVID-19 pandemic on Lewy body dementia clinical research, lessons learned from that experience, and how those lessons can be applied to the design and conduct of future clinical trials. This report provides a brief summary of the meeting proceedings with a focus on efforts to improve and adapt future Lewy body dementia clinical research.
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