scholarly journals Preclinical diagnosis of Alzheimer's disease: Prevention or prediction?

2010 ◽  
Vol 4 (4) ◽  
pp. 259-261 ◽  
Author(s):  
Ricardo Nitrini

Abstract The diagnosis of Alzheimer's disease (AD) for cases with dementia may be too late to allow effective treatment. Criteria for diagnosis of preclinical AD suggested by the Alzheimer's Association include the use of molecular and structural biomarkers. Preclinical diagnosis will enable testing of new drugs and forms of treatment toward achieving successful preventive treatment. But what are the advantages for the individual? To know that someone who is cognitively normal is probably going to develop AD's dementia when there is no effective preventive treatment is definitely not good news. A research method whereby volunteers are assigned to receive treatment or placebo without knowing whether they are in the control or at-risk arm of a trial would overcome this potential problem. If these new criteria are used wisely they may represent a relevant milestone in the search for a definitive treatment for AD.

2020 ◽  
Author(s):  
Jianfeng Wu ◽  
Qunxi Dong ◽  
Jie Gui ◽  
Jie Zhang ◽  
Yi Su ◽  
...  

ABSTRACTBiomarker assisted preclinical/early detection and intervention in Alzheimer’s disease (AD) may be the key to therapeutic breakthroughs. One of the presymptomatic hallmarks of AD is the accumulation of beta-amyloid (Aβ) plaques in the human brain. However, current methods to detect Aβ pathology are either invasive (lumbar puncture) or quite costly and not widely available (amyloid PET). Our prior studies show that MRI-based hippocampal multivariate morphometry statistics (MMS) are an effective neurodegenerative biomarker for preclinical AD. Here we attempt to use MRI-MMS to make inferences regarding brain amyloid burden at the individual subject level. As MMS data has a larger dimension than the sample size, we propose a sparse coding algorithm, Patch Analysis-based Surface Correntropy-induced Sparse coding and max-pooling (PASCS-MP), to generate a low-dimensional representation of hippocampal morphometry for each individual subject. Then we apply these individual representations and a binary random forest classifier to predict brain Aβ positivity for each person. We test our method in two independent cohorts, 841 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and 260 subjects from the Open Access Series of Imaging Studies (OASIS). Experimental results suggest that our proposed PASCS-MP method and MMS can discriminate Aβ positivity in people with mild cognitive impairment (MCI) (Accuracy (ACC)=0.89 (ADNI)) and in cognitively unimpaired (CU) individuals (ACC=0.79 (ADNI) and ACC=0.82 (OASIS)). These results compare favorably relative to measures derived from traditional algorithms, including hippocampal volume and surface area, shape measures based on spherical harmonics (SPHARM) and our prior Patch Analysis-based Surface Sparse-coding and Max-Pooling (PASS-MP) methods.


2021 ◽  
Vol 15 ◽  
Author(s):  
Jianfeng Wu ◽  
Qunxi Dong ◽  
Jie Gui ◽  
Jie Zhang ◽  
Yi Su ◽  
...  

Biomarker assisted preclinical/early detection and intervention in Alzheimer’s disease (AD) may be the key to therapeutic breakthroughs. One of the presymptomatic hallmarks of AD is the accumulation of beta-amyloid (Aβ) plaques in the human brain. However, current methods to detect Aβ pathology are either invasive (lumbar puncture) or quite costly and not widely available (amyloid PET). Our prior studies show that magnetic resonance imaging (MRI)-based hippocampal multivariate morphometry statistics (MMS) are an effective neurodegenerative biomarker for preclinical AD. Here we attempt to use MRI-MMS to make inferences regarding brain Aβ burden at the individual subject level. As MMS data has a larger dimension than the sample size, we propose a sparse coding algorithm, Patch Analysis-based Surface Correntropy-induced Sparse-coding and Max-Pooling (PASCS-MP), to generate a low-dimensional representation of hippocampal morphometry for each individual subject. Then we apply these individual representations and a binary random forest classifier to predict brain Aβ positivity for each person. We test our method in two independent cohorts, 841 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and 260 subjects from the Open Access Series of Imaging Studies (OASIS). Experimental results suggest that our proposed PASCS-MP method and MMS can discriminate Aβ positivity in people with mild cognitive impairment (MCI) [Accuracy (ACC) = 0.89 (ADNI)] and in cognitively unimpaired (CU) individuals [ACC = 0.79 (ADNI) and ACC = 0.81 (OASIS)]. These results compare favorably relative to measures derived from traditional algorithms, including hippocampal volume and surface area, shape measures based on spherical harmonics (SPHARM) and our prior Patch Analysis-based Surface Sparse-coding and Max-Pooling (PASS-MP) methods.


2020 ◽  
Vol 27 ◽  
Author(s):  
Reyaz Hassan Mir ◽  
Abdul Jalil Shah ◽  
Roohi Mohi-ud-din ◽  
Faheem Hyder Potoo ◽  
Mohd. Akbar Dar ◽  
...  

: Alzheimer's disease (AD) is a chronic neurodegenerative brain disorder characterized by memory impairment, dementia, oxidative stress in elderly people. Currently, only a few drugs are available in the market with various adverse effects. So to develop new drugs with protective action against the disease, research is turning to the identification of plant products as a remedy. Natural compounds with anti-inflammatory activity could be good candidates for developing effective therapeutic strategies. Phytochemicals including Curcumin, Resveratrol, Quercetin, Huperzine-A, Rosmarinic acid, genistein, obovatol, and Oxyresvertarol were reported molecules for the treatment of AD. Several alkaloids such as galantamine, oridonin, glaucocalyxin B, tetrandrine, berberine, anatabine have been shown anti-inflammatory effects in AD models in vitro as well as in-vivo. In conclusion, natural products from plants represent interesting candidates for the treatment of AD. This review highlights the potential of specific compounds from natural products along with their synthetic derivatives to counteract AD in the CNS.


2018 ◽  
Vol 16 (1) ◽  
pp. 49-55 ◽  
Author(s):  
J. Stenzel ◽  
C. Rühlmann ◽  
T. Lindner ◽  
S. Polei ◽  
S. Teipel ◽  
...  

Background: Positron-emission-tomography (PET) using 18F labeled florbetaben allows noninvasive in vivo-assessment of amyloid-beta (Aβ), a pathological hallmark of Alzheimer’s disease (AD). In preclinical research, [<sup>18</sup>F]-florbetaben-PET has already been used to test the amyloid-lowering potential of new drugs, both in humans and in transgenic models of cerebral amyloidosis. The aim of this study was to characterize the spatial pattern of cerebral uptake of [<sup>18</sup>F]-florbetaben in the APPswe/ PS1dE9 mouse model of AD in comparison to histologically determined number and size of cerebral Aβ plaques. Methods: Both, APPswe/PS1dE9 and wild type mice at an age of 12 months were investigated by smallanimal PET/CT after intravenous injection of [<sup>18</sup>F]-florbetaben. High-resolution magnetic resonance imaging data were used for quantification of the PET data by volume of interest analysis. The standardized uptake values (SUVs) of [<sup>18</sup>F]-florbetaben in vivo as well as post mortem cerebral Aβ plaque load in cortex, hippocampus and cerebellum were analyzed. Results: Visual inspection and SUVs revealed an increased cerebral uptake of [<sup>18</sup>F]-florbetaben in APPswe/ PS1dE9 mice compared with wild type mice especially in the cortex, the hippocampus and the cerebellum. However, SUV ratios (SUVRs) relative to cerebellum revealed only significant differences in the hippocampus between the APPswe/PS1dE9 and wild type mice but not in cortex; this differential effect may reflect the lower plaque area in the cortex than in the hippocampus as found in the histological analysis. Conclusion: The findings suggest that histopathological characteristics of Aβ plaque size and spatial distribution can be depicted in vivo using [<sup>18</sup>F]-florbetaben in the APPswe/PS1dE9 mouse model.


2020 ◽  
Vol 17 (5) ◽  
pp. 438-445
Author(s):  
Van Giau Vo ◽  
Jung-Min Pyun ◽  
Eva Bagyinszky ◽  
Seong S.A. An ◽  
Sang Y. Kim

Background: Presenilin 1 (PSEN1) was suggested as the most common causative gene of early onset Alzheimer’s Disease (AD). Methods: Patient who presented progressive memory decline in her 40s was enrolled in this study. A broad battery of neuropsychological tests and neuroimaging was applied to make the diagnosis. Genetic tests were performed in the patient to evaluate possible mutations using whole exome sequencing. The pathogenic nature of missense mutation and its 3D protein structure prediction were performed by in silico prediction programs. Results: A pathogenic mutation in PSEN1 (NM_000021.3: c.1027T>C p.Ala285Val), which was found in a Korean EOAD patient. Magnetic resonance imaging scan showed mild left temporal lobe atrophy. Hypometabolism appeared through 18F-fludeoxyglucose Positron Emission Tomography (FDG-PET) scanning in bilateral temporal and parietal lobe, and 18F-Florbetaben-PET (FBB-PET) showed increased amyloid deposition in bilateral frontal, parietal, temporal lobe and hence presumed preclinical AD. Protein modeling showed that the p.Ala285Val is located in the random coil region and could result in extra stress in this region, resulting in the replacement of an alanine residue with a valine. This prediction was confirmed previous in vitro studies that the p.Trp165Cys resulted in an elevated Aβ42/Aβ40 ratio in both COS-1 and HEK293 cell lines compared that of wild-type control. Conclusion: Together, the clinical characteristics and the effect of the mutation would facilitate our understanding of PSEN1 in AD pathogenesis for the disease diagnosis and treatment. Future in vivo study is needed to evaluate the role of PSEN1 p.Ala285Val mutation in AD progression.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Hao Hu ◽  
Lan Tan ◽  
Yan-Lin Bi ◽  
Wei Xu ◽  
Lin Tan ◽  
...  

AbstractThe bridging integrator 1 (BIN1) gene is the second most important susceptibility gene for late-onset Alzheimer’s disease (LOAD) after apolipoprotein E (APOE) gene. To explore whether the BIN1 methylation in peripheral blood changed in the early stage of LOAD, we included 814 participants (484 cognitively normal participants [CN] and 330 participants with subjective cognitive decline [SCD]) from the Chinese Alzheimer’s Biomarker and LifestylE (CABLE) database. Then we tested associations of methylation of BIN1 promoter in peripheral blood with the susceptibility for preclinical AD or early changes of cerebrospinal fluid (CSF) AD-related biomarkers. Results showed that SCD participants with significant AD biological characteristics had lower methylation levels of BIN1 promoter, even after correcting for covariates. Hypomethylation of BIN1 promoter were associated with decreased CSF Aβ42 (p = 0.0008), as well as increased p-tau/Aβ42 (p = 0.0001) and t-tau/Aβ42 (p < 0.0001) in total participants. Subgroup analysis showed that the above associations only remained in the SCD subgroup. In addition, hypomethylation of BIN1 promoter was also accompanied by increased CSF p-tau (p = 0.0028) and t-tau (p = 0.0130) in the SCD subgroup, which was independent of CSF Aβ42. Finally, above associations were still significant after correcting single nucleotide polymorphic sites (SNPs) and interaction of APOE ɛ4 status. Our study is the first to find a robust association between hypomethylation of BIN1 promoter in peripheral blood and preclinical AD. This provides new evidence for the involvement of BIN1 in AD, and may contribute to the discovery of new therapeutic targets for AD.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Soo Hyun Cho ◽  
Sookyoung Woo ◽  
Changsoo Kim ◽  
Hee Jin Kim ◽  
Hyemin Jang ◽  
...  

AbstractTo characterize the course of Alzheimer’s disease (AD) over a longer time interval, we aimed to construct a disease course model for the entire span of the disease using two separate cohorts ranging from preclinical AD to AD dementia. We modelled the progression course of 436 patients with AD continuum and investigated the effects of apolipoprotein E ε4 (APOE ε4) and sex on disease progression. To develop a model of progression from preclinical AD to AD dementia, we estimated Alzheimer’s Disease Assessment Scale-Cognitive Subscale 13 (ADAS-cog 13) scores. When calculated as the median of ADAS-cog 13 scores for each cohort, the estimated time from preclinical AD to MCI due to AD was 7.8 years and preclinical AD to AD dementia was 15.2 years. ADAS-cog 13 scores deteriorated most rapidly in women APOE ε4 carriers and most slowly in men APOE ε4 non-carriers (p < 0.001). Our results suggest that disease progression modelling from preclinical AD to AD dementia may help clinicians to estimate where patients are in the disease course and provide information on variation in the disease course by sex and APOE ε4 status.


2021 ◽  
Vol 79 (1) ◽  
pp. 225-235
Author(s):  
Maya Arvidsson Rådestig ◽  
Johan Skoog ◽  
Henrik Zetterberg ◽  
Jürgen Kern ◽  
Anna Zettergren ◽  
...  

Background: We have previously shown that older adults with preclinical Alzheimer’s disease (AD) pathology in cerebrospinal fluid (CSF) had slightly worse performance in Mini-Mental State Examination (MMSE) than participants without preclinical AD pathology. Objective: We therefore aimed to compare performance on neurocognitive tests in a population-based sample of 70-year-olds with and without CSF AD pathology. Methods: The sample was derived from the population-based Gothenburg H70 Birth Cohort Studies in Sweden. Participants (n = 316, 70 years old) underwent comprehensive cognitive examinations, and CSF Aβ-42, Aβ-40, T-tau, and P-tau concentrations were measured. Participants were classified according to the ATN system, and according to their Clinical Dementia Rating (CDR) score. Cognitive performance was examined in the CSF amyloid, tau, and neurodegeneration (ATN) categories. Results: Among participants with CDR 0 (n = 259), those with amyloid (A+) and/or tau pathology (T+, N+) showed similar performance on most cognitive tests compared to participants with A-T-N-. Participants with A-T-N+ performed worse in memory (Supra span (p = 0.003), object Delayed (p = 0.042) and Immediate recall (p = 0.033)). Among participants with CDR 0.5 (n = 57), those with amyloid pathology (A+) scored worse in category fluency (p = 0.003). Conclusion: Cognitively normal participants with amyloid and/or tau pathology performed similarly to those without any biomarker evidence of preclinical AD in most cognitive domains, with the exception of slightly poorer memory performance in A-T-N+. Our study suggests that preclinical AD biomarkers are altered before cognitive decline.


2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Yaojing Chen ◽  
Mingxi Dang ◽  
Zhanjun Zhang

AbstractNeuropsychiatric symptoms (NPSs) are common in patients with Alzheimer’s disease (AD) and are associated with accelerated cognitive impairment and earlier deaths. This review aims to explore the neural pathogenesis of NPSs in AD and its association with the progression of AD. We first provide a literature overview on the onset times of NPSs. Different NPSs occur in different disease stages of AD, but most symptoms appear in the preclinical AD or mild cognitive impairment stage and develop progressively. Next, we describe symptom-general and -specific patterns of brain lesions. Generally, the anterior cingulate cortex is a commonly damaged region across all symptoms, and the prefrontal cortex, especially the orbitofrontal cortex, is also a critical region associated with most NPSs. In contrast, the anterior cingulate-subcortical circuit is specifically related to apathy in AD, the frontal-limbic circuit is related to depression, and the amygdala circuit is related to anxiety. Finally, we elucidate the associations between the NPSs and AD by combining the onset time with the neural basis of NPSs.


2019 ◽  
Vol 216 (1) ◽  
pp. 43-48 ◽  
Author(s):  
Audun Osland Vik-Mo ◽  
Lasse Melvaer Giil ◽  
Miguel Germán Borda ◽  
Clive Ballard ◽  
Dag Aarsland

IntroductionUnderstanding the natural course of neuropsychiatric symptoms (NPS) in dementia is important for planning patient care and trial design, but few studies have described the long-term course of NPS in individuals.MethodPrimary inclusion of 223 patients with suspected mild dementia from general practice were followed by annual assessment, including the Neuropsychiatric Inventory (NPI), for up to 12 years. Total and item NPI scores were classified as stable, relapsing, single episodic or not present based on 4.96 (s.d. 2.3) observations (98% completeness of longitudinal data) for 113 patients with Alzheimer's disease and 84 patients with LBD (68 dementia with Lewy bodies and 16 Parkinson's disease dementia).ResultsWe found that 80% had stable NPI total ≥1, 50% had stable modest NPI total ≥12 and 25% had stable NPI total ≥24 scores. Very severe NPS (≥48) were mostly single episodes, but 8% of patients with Alzheimer's disease had stable severe NPS. Patients with Alzheimer's disease and the highest 20% NPI total scores had a more stable or relapsing course of four key symptoms: aberrant motor behaviour, aggression/agitation, delusions and irritability (odds ratio 55, P < 0.001). This was not seen in LBD. Finally, 57% of patients with Alzheimer's disease and 84% of patients with LBD had reoccurring psychotic symptoms.ConclusionsWe observed a highly individual course of NPS, with most presenting as a single episode or relapsing; a stable course was less common, especially in LBD. These findings demonstrate the importance of an individualised approach (i.e. personalised medicine) in dementia care.


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