bluuebunny/crossref_metadata_2025 huggingface dataset:
Prediction of longitudinal clinical status changes in mild cognitive impairment by network structural covariance
Authors: Dang Mingxi , Yang Caishui , Xu Chang , Zhang Zhanjun
Published: December 2020

Background

Mild cognitive impairment (MCI) is the transitional zone between normal aging and Alzheimer’s dementia (AD), representing a group of subjects with higher risk of conversion to AD (Petersen, 2010). However, as accumulating evidence shows that there are a non‐negligible number of MCI subjects who revert to be cognitive normal (CN), additional measures are needed for better characterizations on the MCI groups (Petersen, 2014). Thus, the purpose of this study is to explore the structural covariance (SC) feature of subjects with different longitudinal clinical status changes.

Method

Participants were from the Beijing Aging Brain Rejuvenation Initiative (BABRI), with two clinical cognitive assessments and the baseline high‐resolution structural MRI data. And four groups were defined, the stable CN (sCN, n = 99), CN progressing to MCI (pCN, n = 23), stable MCI (sMCI, n = 29), and MCI reverting to CN (rMCI, n = 33), and the mean age and follow‐ups interval for CN and MCI subjects were 64.74 and 66.63, 2.46 and 1.45 years, respectively. And the seed‐based multivariate method (Alexander‐Bloch, 2013) was applied to identify the SC of default‐mode network (scDN), frontoparietal network (scFN) and hippocampal network (scHN), of which the covariance scores were calculated. To obtain the SC templates of three networks, 69 sCN were randomly selected, and the rest 30 sCN, with the other three groups, were included in establishing prediction model of clinical status changes based on network SC scores, by using the support vector machine method and leave‐one‐out cross‐validation. Moreover, baseline cognition was also added in the model.

Result

For classification between sCN and sMCI, the scHN score presented the highest accuracy (area under curve (AUC) = 0.89), and it was the scDN score showing the best performance in classifying sMCI and rMCI (AUC = 0.82), with the scFN score outperforming others in distinguishing pCN from sCN (AUC = 0.68). And when baseline cognition was also included, prediction accuracies of clinical changes were improved (AUC = 0.84 for sMCI vs. rMCI, AUC = 0.83 for sCN vs. pCN).

Conclusion

Taking together, our findings indicated the potential of network structural covariance in classifying MCI subjects with different risk of conversion.
Sex differences in risk factors for dementia in the UK Biobank: An analysis of more than half a million individuals
Authors: Gong Jessica , Harris Katie , Peters Sanne , Woodward Mark
Published: December 2020

Background

While some risk factors (RF) are known to be associated with dementia, understanding of sex differences in these risk factors is scant. This study investigated the sex differences in the strength of association across a range of RFs with dementia in the UK Biobank.

Methods

UK Biobank is a prospective population‐based cohort of 502,628 participants. We examined the sex differences in a number of RFs associated with incident dementia: blood pressure (BP), diabetes mellitus, smoking status, socioeconomic status (SES), stroke, cholesterol, and body anthropometries. Cox proportional hazard regression models were used to estimate the hazard ratios (HR) for dementia for each RF, with interaction terms between sex and each RF. The shape of the relationships between BP and the risk of dementia were further explored using restricted cubic splines.

Results

Over a median of 9.0 years follow‐up, 2,502 individuals (44.5% women) developed dementia. Diabetes, smoking, lower SES, prior stroke and all body anthropometries with the exception of body mass index (BMI) were associated with elevated risk of dementia in women and men. Higher systolic blood pressure (SBP) and diastolic blood pressure (DBP) were both associated with higher risk of dementia in women, but lower risk in men (women‐to‐men Ratio of Hazard Ratios (RHR), 1.14, 95% confidence intervals (CI) [1.05 – 1.24], for both SBP and DBP). Multiple‐adjusted splines unveiled differential relationships between SBP and the risk of dementia for men and women, indicating lower SBP increased the risk of dementia in men, but the effect attenuated for women; while higher SBP posed greater risk of dementia for women than men. Compared with high SES, women with low SES had a higher risk of dementia compared with men with low SES (RHR, 1.19 [1.01 to 1.41]).

Conclusion

The relationship between BP and the risk of dementia are manifested differently for men and women, which has important clinical implications when designing targeted interventions and setting BP goals to optimise treatment outcomes. Moreover, low SES conferred greater risk of dementia in women than men when compared to high SES, warrants further investigations in potential social and medical inequities between the sexes.
Using anxiety as a sex‐specific neuropsychiatric biomarker of Alzheimer’s disease
Authors: Hunsberger Holly C. , Lee Seonjoo , Cha Jiook , Denny Christine Ann
Published: December 2020

Background

Neuropsychiatric disturbances, such as depression and anxiety, are observed in 90% of Alzheimer’s disease (AD) patients and are frequent in those at risk for AD. However, until recently, much of the research narrowly targeted co‐morbid depression. Clinical reports have provided evidence that anxiety symptoms predict the conversion to AD, over and beyond the effects of depression, memory loss, and even atrophy. Similarly, epidemiological studies show that neurodegeneration and clinical symptoms occur more rapidly in females once diagnosed. Although most AD studies have been performed using male mice, females represent two‐thirds of the AD population and are more susceptible to depression and anxiety.

Method

To study how anatomical sex and anxiety impact AD progression, I used our activity‐dependent tagging system mice. These mice allow for brain‐wide indelible labeling of neurons activated during learning, which then can be compared with secondary neuronal ensembles activated during memory retrieval. The neurons activated at both time points represent a memory trace or engram. Here, we aimed to identify the neural ensembles linking anxiety and memory loss following AD progression by utilizing behavioral studies, calcium imaging and whole‐brain microscopy, in female and male mice.

Result

We found: 1) Female AD mice exhibited anxiety‐like behavior at an earlier age compared to controls and male mice, 2) AD female mice displayed memory deficits as early as 2 months of age, 3) Anxiety‐like behavior correlated with memory impairment only in AD female mice, and 4) Unlike their male counterparts, female AD mice showed a decline in memory traces in the CA3 of the hippocampus.

Conclusion

We now believe that anxiety could represent a neuropsychiatric predictor of AD and are currently working to translate these findings to humans using the Alzheimer’s disease neuroimaging initiative (ADNI) dataset. We have found that in humans, anxiety predicts transition to dementia and that anxiety has a sex‐specific effect on brain atrophy.
Depletion of the AD risk gene SORL1 selectively impairs neuronal endosomal traffic independent of amyloidogenic APP processing
Authors: Knupp Allison , Mishra Swati , Martinez Refugio A. , Braggin Jacquelyn E. , Small Scott A. , Jayadev Suman , Young Jessica E.
Published: December 2020

Background

The SORL1 gene encodes for the protein SorLA, a sorting receptor involved in retromer‐related endosomal traffic. Many SORL1 genetic variants increase Alzheimer’s disease (AD) risk, and rare loss‐of‐function truncation mutations have been found to be causal of AD. SORL1 is expressed in neurons and glia of the central nervous system and loss of SORL1 has been reported AD tissue.

Method

To model the causal loss‐of‐function mutations, we used CRISPR/Cas9 technology to deplete SORL1 in human induced pluripotent stem cells (hiPSCs) to test the hypothesis that loss of SORL1 contributes to AD pathogenesis by leading to endosome dysfunction.

Result

We report that loss of SORL1 in hiPSC‐derived neurons leads to early endosome enlargement, a cellular phenotype that is indicative of ‘traffic jams’ and is now considered a hallmark cytopathology AD. We validate defects in neuronal endosomal traffic by showing decreased localization of amyloid‐precursor protein (APP) in the trans‐Golgi network (TGN), and increased localization of APP in early endosomes, a site of APP cleavage by the b secretase BACE1. Microglia, immune cells of the CNS, which also play a role in the AD pathology also express SORL1. We therefore tested and found no effect of SORL1 depletion on endosome size or morphology in hiPSC‐derived microglia, suggesting a selective effect on neuronal endocytic trafficking. Finally, because BACE1 dependent APP fragments can cause endosome enlargement, we treated SORL1 deficient hiPSC‐derived neurons with BACE1 inhibitors and demonstrate that endosome enlargement occurs independent of amyloidogenic APP fragments.

Conclusion

Collectively, these findings clarify where and how SORL1 links to AD. Moreover, our data, together with recent findings, underscores how sporadic AD pathways that regulate endosomal trafficking, and autosomal‐dominant AD pathways that regulate APP cleavage, independently converge on AD’s defining cytopathology.
Different relationship of cross‐regional correlations of progression of local cortical thickness and local SUVR 18F‐flortaucipir PET values to strength of connectivity
Authors: Soucy Jean‐Paul , Mohammadi Fatameh , Boulier Thomas , Hortelan Valentine , Rosa‐Neto Pedro , Pascoal Tharick A. , Savard Melissa , Kang Min Su , Mathotaarachchi Sulantha , Therriault Joseph , Benali Habib
Published: December 2020

Background

We have demonstrated in vivo in humans that spatial progression of tau distribution and atrophy in Alzheimer’s is largely driven by connectivity (Soucy et al, HAI2020). Nevertheless, local tau accumulation and atrophy should not progress in parallel during disease evolution. Atrophy keeps worsening, while local tau density (SUVRs estimated with PET) initially increases but could then decline because of tissue loss. Therefore, despite the impact of connectivity on progression of both local atrophy and SUVRs, it likely will not remain the same for both over time. This is what we tested in this work.

Method

We studied 35 AD subjects from ADNI with 2 PET studies (18F‐florbetapir) at times Ta/Tb (mean elapsed time = 438 days, median = 454), and a T1 MRI at Ta. Eighteen subjects were non‐progressors (NP) and 17 were progressors (P) based on change between Ta/b hippocampal SUVRs values. This criterion was considered to represent how far advanced patients were in their disease. Moran I statistic was used to measure autocorrelations between connectivity and T1 MRI‐defined cortical thickness at Ta or tau PET SUVR values at both times Ta and Tb in NP and P subjects in regions separately analyzed based the “intensity” of their connectivity as defined by a standard connectivity map (Human Connectome Project). We defined 3 groups of regions from thresholds separating poorly connected from moderately connected (0.01) and moderately connected from highly connected ones (0.021).

Result

In both NPs and Ps, regions with high connectivity showed higher Z‐score (4.06) of the Moran I value for correlations between regions’ cortical thickness than those with low (2.64)/moderate (2.17) connectivity. For SUVR values however, in both NPs and Ps and at both time points, Z‐scores were always lower for the highly connected regions than for those with moderate/low connectivity.

Conclusion

The way connectivity influences correlations of atrophy across regions is indeed different from the way it affects correlations of tau deposition, likely for the reasons we hypothesized above to guide the progression of each parameter. Models of tau propagation across the brain will need to factor in ongoing atrophy but reversible accumulation of tau.
Tau immunotherapy rescues cognitive impairment by clearing extracellular tau
Authors: Iqbal Khalid , Dai Chunling , Hu Wen , Liu Fei
Published: December 2020

Background

Alzheimer’s disease (AD) is histopathologically characterized by loss of neuronal connectivity associated with extensive tau and Abeta pathologies. Tau immunization can inhibit the seeding and spread of tau pathology and reduce not only tau but also Abeta pathology and rescue cognitive impairment in transgenic tau overexpression mouse models of AD pathology. The specific objective of this study was to determine if tau immunization in wild type aged mice, which like AD patients do not overexpress either APP or tau, can rescue cognitive impairment.

Method

We investigated the effect of immunization with monoclonal antibody 77E9 against tau 184‐195 in 18month‐old male C57 BL/6 wild type (WT) mice, 15 microgram/200 microliter intravenous weekly injection for 6 weeks or once every four weeks injection for 24 weeks; mice injected with mouse IgG were used as controls.

Result

We found (1) that tau immunization did not significantly alter the level of brain tau as tested by Western blots developed with 77E9 or with rabbit polyclonal tau antibodies 92e or 134d to total tau, (2) that aged mice were impaired as compared with the young animals as determined by novel object recognition test and Morris water maze test, and showed dendritic and synaptic deficits and (3) that tau immunization rescued these deficits and cognitive impairment.

Conclusion

The therapeutic beneficial effect of immunization with tau antibody is probably through the restoration of neuronal connectivity due to clearance of primarily extracellular tau. Tau immunotherapy is thus likely to be effective only in those conditions where a reduction of extracellular tau will benefit.
Elucidating the pathogenic mechanisms of AD brain‐derived, tau‐containing extracellular vesicles: Highly transmissible and preferential propagation to GABAergic neurons
Authors: Ikezu Tsuneya , Ruan Zhi , Pathak Dhruba , Muraoka Satoshi , DeLeo Annina M. , Kayed Rakez , Gendelman Howard E. , Ikezu Seiko
Published: December 2020

Backgrounds

Tau‐containing extracellular vesicles (EVs) are transmissible and induce tau phosphorylation and conformational change in the recipient neurons. However, whether human brain‐derived EVs induce tau pathology has not yet been characterized in the mouse brain. Here, we assess the mechanisms of disease spread after intrahippocampal injection of human brain‐derived EVs into the aged mouse model.

Methods

EV‐enriched fractions were isolated from unfixed frozen human brain samples from AD, prodromal AD (pAD), control (CTRL) cases, and tau knockout (TKO) mouse brains. Isolated EVs containing 300 pg of human total tau were sterotaxically injected into the right outer molecular layer of the dentate gyrus of 18 months‐old C57BL/6 female mice. 4.5 months after the injection, hippocampal slices were prepared for whole‐cell patch clamp recordings of CA1 pyramidal neurons were undertakent. Hippocampi were analyzed with immunohistochemistry using phosphorylated‐tau (p‐tau) epitopes including AT8. EVs were examined for protein composition by protein mass‐spectroscopy, the neuronal uptake in vitro, and structural analysis by the atomic force microscopy (AFM).

Results

Semiquantitative brain‐wide immunohistochemistry of p‐tau revealed that inoculation of AD or pAD‐EVs induced tau propagation throughout the hippocampus, including the dentate gyrus, CA3 and CA1 subregions. AT8 was localized primarily in GAD67+ GABAergic neurons in pAD and AD EVs groups, accompanied with reduced amplitude of inhibitory postsynaptic currents and Excitatory‐Inhibitory ratio in amplitube of postsynaptic currents in CA1 pyramidal neurons in pAD EVs. AFM analysis showed higher density of tau oligomers in both AD and pAD EVs while only AD EVs showed significantly higher neuronal uptake compared to CTRL EVs. Finally, proteomic analysis showed that AD EVs are enriched in disease and glia‐related molecules compared to CTRL EVs, which may contribute to their enhanced neuronal uptake.

Conclusions

Intracranial injection of AD or pAD EVs induced p‐tau accumulation primarily in GABAergic neurons throughout the hippocampus, resulted in higher uptake by neurons, and tau oligomer conformation, indicating of their pathogenic potency as seeding factors. GABAergic neuronal dysfunction in the hippocampal neuronal circuitry reported in early AD brains could be attributed to specific EV mediated tau propagation in this cell type, a phenomenon meriting further investigation and validation.
Plasma extracellular vesicles of neuronal and astrocytic origins: Biomarker carriers and pathogenic effectors in Alzheimer’s disease
Authors: Kapogiannis Dimitrios , Eren Erden , Hunt Jack F.V. , Shardell Michelle , Vogt Nicholas M. , Johnson Sterling C. , Bendlin Barbara B. , Nogueras‐Ortiz Carlos , Delgado‐Peraza Francheska , Eitan Erez
Published: December 2020

Background

Circulating neuronal and astrocytic Extracellular Vesicles (NEVs, AEVs) provide biomarkers for Alzheimer’s disease (AD) (including total and p‐Tau in NEVs, complement in AEVs). In a large case‐control study leveraging Baltimore Longitudinal Study of Aging samples, Tau‐related NEV biomarkers predicted future AD diagnosis with high accuracy, sensitivity and specificity. To validate NEV Tau biomarkers for predicting cognitive decline in late middle‐age we leveraged Wisconsin Registry for Alzheimer’s prevention (WRAP) study samples. To examine convergent validity we used transgenic AD mice. Finally, we examined functional effects of circulating EVs.

Methods

We isolated NEVs and AEVs from plasma through immunocapture against L1CAM and GLAST respectively. Total and p‐Tau were measured in 292 serum samples from 146 cognitively unimpaired WRAP participants, divided into longitudinal cognitive decliner and non‐decliner groups. We also measured Tau biomarkers in circulating NEVs and brains of 28 mice (4 2xTg, 15 3xTg, 9 WT). To study functional effects of circulating EVs, we co‐cultured AEVs and NEVs (from 8 AD patients, 8 controls) with rat cortical and human iPSC‐derived neurons and performed cell viability and neurodegeneration assays.

Results

In WRAP, cognitive status was associated with NEV Tau biomarkers depending on age, with cognitively declining compared to stable individuals showing higher pTau231 (p < 0.01), total Tau (p <0.001) and pTau181 (p < 0.05) with older age. Combining longitudinal NEV biomarkers achieved up to 94% area‐under‐curve (AUC), 86.0% sensitivity and 86.7% specificity for predicting cognitive decline. In mice, total Tau and pTau181 levels in circulating NEVs showed strong correlations with levels in cortex and hippocampus (p < 0.001; Figure: Fraction1 acquired ante‐mortem, Fraction 2 acquired during euthanasia). Functionally, AEVs (and, less effectively, NEVs) of AD patients induced complement Membrane Attack Complex deposition, membrane disruption, neurodegeneration, and necroptosis on recipient neurons. Neurodegenerative effects were not produced by total circulating EVs from AD patients or AEVs/NEVs from controls and were suppressed by complement inhibitors.

Conclusions

NEV Tau biomarkers predict cognitive decline in late middle‐age humans. Tau in circulating NEVs reflect brain levels in mice. Functionally, AD patients’ circulating AEV/NEVs are neurotoxic. Inhibition of EV‐associated complement components may be therapeutically beneficial in AD.
Data‐driven approach reveals heterogeneity and region‐specific association of white matter hyperintensities with the APOE genotype
Authors: Habes Mohamad , Sotiras Aristeidis , Erus Guray , Toledo Jon B. , Janowitz Deborah , Wolk David A. , Shou Haochang , Bryan Nick , Doshi Jimit , Voelzke Henry , Schminke Ulf , Hoffmann Wolfgang , Resnick Susan M. , Grabe Hans J. , Davatzikos Christos
Published: December 2020

Background

We used a transparent machine learning algorithm to identify subtypes of white matter damage in aging and to characterize their clinical representations. White matter hyperintensities (WMH), a common finding on brain magnetic resonance imaging (MRI), are known to be associated with cognitive impairment and dementia. Previous studies have shown spatial heterogeneity of WMH appearance, but the contribution of Alzheimer disease (AD) dementia and related genetic risk factors to this heterogeneity remains unclear. We sought to investigate the heterogeneity of WMH, in the general population, leveraging state of the art pattern analysis methods and exploring whether the APOE genotype is contributing to this heterogeneity.

Method

A sample of N=1836 people was obtained from the Study of Health in Pomerania (SHIP), Germany, covering a wide age range (22–84 years, median age 52.2±13.16). WMH were automatically segmented on multi‐modal MRI scans and decomposed into four spatially distinctive components using Non‐Negative Matrix Factorization (NNMF), a machine‐learning based structural covariance method. Associations of these components with the APOE genotype (available for n=303) was investigated in subjects older than 60 years of age, using a multivariable linear regression model for each component, with WMH component loadings as the outcome variable and APOE genotype (encoded as shown in Table 1) as the independent variable. Age, sex and ship sub‐cohort were included as covariates. All reported P‐values were Bonferroni corrected for multiple comparisons.

Result

Data‐driven approach identified four WMH components, consistent with clinical categorization in deep and periventricular lesions, while further dividing periventricular WMH into posterior, frontal and dorsal components (Figure 1). APOE genotype was significantly associated with the dorsal periventricular WMH component (P=0.035, Bonferroni corrected), but not with the other three WMH components (Table 1).

Conclusion

We obtained a high consistency of data‐driven WMH components and established clinical categorizations. Our data demonstrated that the appearance of WMH follows heterogeneous regional distribution patterns. Additionally, the APOE genotype, the strongest genetic risk factor for sporadic AD, is specifically associated with one of the components indicating spatial specificity and a potential link to early MRI changes in the predementia phase.
Visualization of deep learning relevance maps for AD detection
Authors: Budding Celine , EitelAlbrecht FabianJan‐Philipp , Ritter Kerstin
Published: December 2020

Background

Deep learning methods, in particular convolutional neural networks (CNNs), have been very successfully applied to the diagnosis of AD and MCI based on structural MRI data. However, since the training of those models needs the adaptation of many parameters, they are often criticized for being a “black‐box”. Here, we compute heatmaps using layer‐wise relevance propagation (LRP) to (1) validate CNN models and (2) explain neural network decision in single patients. Furthermore, we investigated whether the resulting heatmaps help in identifying subgroups of AD and MCI.

Method

We included 2964 T1‐weighted MR scans of 732 participants (185 AD, 116 MCI‐converters, 211 MCI‐non converters and 210 Cognitive Normal [CN]) from the ADNI data base. The AD/CN cohort were split into a training/validation (80 %) and a test cohort (20 %) based on participant ID. A CNN model consisting of four 3D convolutional layers was then trained to separate patients with AD and CN. The model was tested on the AD/CN test set and applied to MCI‐converters / MCI‐non‐converters. Using LRP, we produced for each MRI scan a heatmap in the input space, indicating the relevance of each voxel for the final classification decision. The heatmaps were clustered using spectral relevance analysis.

Result

The CNN model resulted in a balanced accuracy of 85.12 % on the AD/CN test set and 67.37 % on the MCI‐converter / MCI‐non‐converter set. We additionally evaluated the CNN models with respect to different subgroups, including gender (88.11 % for females, 82.10 % for males) and age (92.57 % for 60‐73 years, 89.06 % for 74‐78 years, 74.17 % for 79‐90 years). Among regions with the highest LRP evidence for AD and MCI are hippocampus and parahippocampal gyrus. Spectral clustering revealed a higher variability within the AD and MCI subgroups than for CN.

Conclusion

In this study, we show the potential of a transparent deep learning framework in order to understand the underlying computing principles and their effect on clinical outcomes such as clinical diagnosis (AD vs. MCI vs. CN), gender and age. Future studies are necessary to address the robustness of heatmaps methods and their applicability in clinical routine.
Deep learning models for generating diagnostic explanations
Authors: Dyrba Martin , Pallath Arjun H. , Marzban Eman N. , Teipel Stefan J.
Published: December 2020

Background

Although machine learning approaches achieve high diagnostic accuracy when detecting Alzheimer’s disease (AD) based on MRI scans, they are rarely applied in clinical studies due to a lack of suitable methods for model comprehensibility and interpretability. Recent advances in convolutional neural networks (CNN) visualization algorithms and methods for generating textual explanations may fill this gap. Here, we will introduce these novel approaches, present first prototypical software using these techniques, and outline the potential of such tools for clinical studies.

Method

We implemented a CNN model trained on 662 T1‐weighted MRI scans obtained from ADNI. Various CNN visualization algorithms were compared, which generate relevance maps indicating the contribution of individual image areas for detecting AD. Further, we created an interactive web application to display them and interactively change visualization parameters. For evaluation, we compared relevance scores in the hippocampus region with hippocampal volume.

Result

The CNN model reached a cross‐validated area under the curve (AUC) of 0.93±0.06 for AD vs. controls and 0.74±0.09. The layer‐wise relevance propagation (LRP) algorithm was found to provide most informative and robust results (Fig. 1). The web app is shown in Fig. 2. Hippocampal volume and relevance scores of the hippocampus region‐of‐interest correlated with r= ‐0.79 (Fig. 3). Additionally, relevance maps highlighted various other image regions with local cortical and subcortical atrophy.

Conclusion

CNN relevance maps may support clinicians in their MRI examinations. CNN models for generating textual explanations may offer additional information, but are not yet available due to the vast amount of labeled training samples required for training.
Long‐term deprivation of ovarian hormones via ovariectomy alters functional connectivity, brain neurochemistry and white matter integrity in a mouse model of Alzheimer's disease
Authors: Kara Firat , Belloy Michael E , Voncken Rick , Sarwari Zahra , Yadav Garima , Anckaerts Cynthia , Langbeen An , Leysen Valérie , Shah Disha , Jacobs Jules , Hamaide Julie , Bols Peter , Van Audekerke Johan , Daans Jasmijn , Guglielmetti Caroline , Kantarci Kejal , Prevot Vincent , Rossner Steffen , Ponsaerts Peter , Van Der Linden Annemie , Verhoye Marleen
Published: December 2020

Background

The abrupt loss of ovarian hormones before menopause, induced by oophorectomy, has been associated with accelerated aging, multimorbidity, and Alzheimer’s disease (AD). We investigated the impact of prolonged loss of ovarian hormones on AD progression in a transgenic mouse model of amyloid pathology using in vivo diffusion tensor MRI, resting‐state functional MRI (rsfMRI) and spectroscopy (MRS).

Method

Female 3.5‐month‐old TG2576 (TG) (N=27) and wild‐type (WT) (N=27) mice were ovariectomized (TGOVX) or sham‐operated (TGSHAM). When they became 18‐month‐old, 1‐H MRS (ROIs: hypothalamus, hippocampus, and cerebral cortex), DTI and rsfMRI was performed. ROI based analysis was performed on rsfMRI and DTI (Fractional anisotropy (FA), axial diffusivity (AxD), mean diffusivity, and radial diffusivity). The brain samples were then evaluated by histology and ELISA to assess Aβ load and activated glial cells. The loss of ovarian hormones via OVX was validated with elevated plasma luteinizing hormone level: OVX>SHAM (p<0.05). Two‐way ANOVA and post‐hoc (Student’s‐t) tests were used for statistical analysis. P values were adjusted for multiple comparisons (FDR‐p).

Result

The multimodel imaging data showed that there was a significant increase in taurine and total creatine (markers for inflammation and energy metabolism) in the hypothalamus, decrease in FA and AxD (markers for white matter integrity) in the white matter regions, and decrease in the functional connectivity between the prefrontal cortex and the hippocampus and dorsal and ventral hippocampus regions (a neural marker of network activity and integrity) (FDR‐p <0.05 (Figure 1)) in TGOVX mice compared to TGSHAM mice (post‐hoc t‐test). rsFMRI showed a significant increase in rsfMRI connectivity in WTOVX mice compared to WTSHAM mice. Complementary histological (and ELISA) analysis revealed no differences in Aβ load (plaque and soluble) and activated glial cells between the TG groups.

Conclusion

The MRI results suggest that inflammatory response was elevated, energy metabolism was disrupted and white matter and network integrity decreased after prolonged ovarian hormone loss. These MRI results support other data from human and animal studies suggesting that abrupt hormonal changes associated with premenopausal removal of ovaries may increase the risk factors of AD, and accelerate the disease progression by causing abnormalities in brain structure, function and metabolism.
PS1 FAD mutants inactivate ephrinB1 and BDNF‐dependent neuroprotection against excitotoxicity by affecting neuroprotective complexes of NMDA receptor
Authors: Rahim Md A.
Published: December 2020

Background

Excitotoxicity is thought to play a key role in brain neurodegeneration and stroke. Here, we show that neuroprotection against excitotoxicity by trophic factors ephrinB1 (efnB1) and BDNF (called here Factors) involves de novo formation of “survival complexes” which are Factor‐stimulated complexes of NMDA receptor (NMDAR) with Factor receptor (FR) and PS1.

Method

Primary cortical neuronal cultures from wild type or from PS1 hemizygous (PS1+/‐) or homozygous (PS1‐/‐) knockout (KO) mouse embryos were used to examine the role of PS1 on NMDAR‐FR complex formation. We also used two independently constructed PS1 FAD mutant knock‐in (KI) mice, one expressing human FAD mutant allele PS1 M146V and the other expressing FAD allele I213T, to test the effects of PS1 FAD mutants on Factors‐dependent neuroprotection, NMDAR complexes with FR and PS1, and NMDAR EPSCs. In addition, postmortem human brains carrying PS1 FAD mutants were used to test the relevance of our study in human disease mechanism.

Result

Absence of PS1 reduces the formation of survival complexes and abolishes neuroprotection. EphB2‐ and NMDAR‐derived peptides designed to disrupt formation of survival complexes also decrease the Factor‐stimulated neuroprotection. Strikingly, the neuroprotective effect of Factors and the levels of de novo Factor‐stimulated survival complexes decrease dramatically in neurons expressing PS1 Familial Alzheimer disease (FAD) mutants. Mouse neurons and brains expressing PS1 FAD mutants contain increased amounts of constitutive PS1‐NMDAR complexes. Additional evidence indicate that constitutive PS1‐NMDAR complexes formed in PS1 FAD mutant‐expressing neurons may differ from those formed in WT neurons and that neurons of PS1 FAD mutant‐expressing brains are more vulnerable to cerebral ischemia than neurons of WT brains. Furthermore, NMDAR‐mediated EPSCs at CA1 synapses are altered by PS1 FAD mutants. Importantly, high levels of PS1‐NMDAR complexes were also found in postmortem brains of AD patients expressing PS1 FAD mutants.

Conclusion

Together, our data identify a novel PS1‐dependent neuroprotective mechanism against excitotoxicity and indicate a pathway by which PS1 FAD mutants may decrease Factor‐depended neuroprotection against toxic insults. These findings have implications for the pathogenic effects of FAD mutants and therapeutic strategies.
Brain‐age predicts subsequent dementia in memory clinic patients
Authors: Biondo Francesca , Jewell Amelia , Pritchard Megan , Mueller Christoph , Steves Claire J , Cole James
Published: December 2020

Background

The lack of disease‐modifying therapies in the current dementia epidemic emphasises the importance of targeting earlier disease stages. Cognitive measures alone do not confer sufficient sensitivity and specificity for this, motivating research into neuroimaging biomarkers that might detect more subtle early changes. One promising measure, so‐called ‘brain age’, has previously been associated with neurological and psychiatric disorders, and predictive of future health outcomes. This includes the development of dementia in observational research cohorts (Gaser et al., 2013; Wang et al., 2019). Here we present results from a community sample of people referred to memory clinics (the Brain Ageing and Risk of Cognitive Decline [BARCODE] project), determining whether baseline brain‐age in people with subject or mild cognitive impairment predicted subsequent dementia diagnosis.

Method

We used T1‐weighted MRI n=318 memory clinic patients with subjective or mild cognitive impairment (192 female and mean [SD] age of 76.3 [0.5] years). Using in‐house software (https://github.com/james‐cole/brainageR) we calculated brain‐predicted age difference (brain‐PAD) for each patients. We determined which participants went on to develop dementia via linkage to electronic health records. Logistic regression analysis tested whether brain‐PAD at time of scan predicted a subsequent dementia diagnosis, controlling for age and sex.

Result

Out of 318 participants, n=248 subsequently received a dementia diagnosis. Logistic regression (McFadden’s R
2=0.19) indicated that brain‐PAD scores at time of scan were significantly higher in patients who subsequently received a dementia diagnosis, B(SE)=0.04(0.02), p<0.05, OR 1.04 (95%CI 1.00‐1.08).

Conclusion

Structural brain ageing is detectable in older adults with memory impairments. Critically, memory clinic patients with older‐looking brains are more likely to receive a subsequent dementia diagnosis. This illustrates the value of using brain age as a sensitive biomarker that has the potential to be used early‐on in memory clinics to detect patients at high‐risk of developing dementia.
Developing breath volatiles fingerprinting for Alzheimer's and Parkinson's diseases
Authors: Bayer Charlene W
Published: December 2020

Background

We tested the feasibility that an AD‐breath volatiles (BVOC) fingerprint will be useable to predict, track disease progression in combination with more traditional modalities, and therapeutic interventions responsiveness for AD resulting in an inexpensive, non‐invasive point‐of‐care tool. Additionally, we also hypothesized that the AD BVOC fingerprint will be functional for early differentiation of AD from other neurodegenerative diseases.

Method

Alveolar breath was collected by breathing into a sampling device and mass spectrometric analysis. Discriminatory statistical modeling was applied to the identified BVOCs, classifying MCI versus controls and identifying BVOCs with greatest discriminatory impact. Differentiation between AD and PD was examined by mixing our MCI and previously collected PD data.

Result

MCI from controls were classified with 97.8% accuracy with an ROC Curve AUC of 0.998. PD or MCI samples were differentiated with 92.5% correctly controls versus MCI or PD and 100% as either MCI or PD. Investigation of probable mechanistic BVOC formation pathways in MCI/AD resulted in two primary pathways: neuroinflammation and e stress and dysregulated glucose metabolism with differences between inflammatory BVOCs in AD versus PD.

Conclusion

We demonstrated feasibility of MCI/AD BVOC fingerprinting for early stage identification of disease via a 97.8% correct classification and the ability to differentiate between AD and PD as example of two neurodegenerative diseases. We showed the probable dysregulated glucose metabolism and inflammatory pathways via BVOCs.
Increases in plasma neurotensin levels and brain neurotensin receptors were associated with brain pathology in obese, insulin‐resistant rats
Authors: Saiyasit Napatsorn , Chunchai Titikorn , Apaijai Nattayaporn , Pratchayasakul Wasana , Sripetchwandee Jirapas , Chattipakorn Nipon , Chattipakorn Siriporn C.
Published: December 2020

Background

Our previous studies reported that long‐term high‐fat diet (HFD) consumption caused not only obese‐insulin resistance, and peripheral oxidative stress, but also brain pathologies, including increased brain oxidative stress, neuronal death, and dendritic spine loss. Neurotensin (NT) is an endogenous tridecapeptide, in which has been expressed in peripheral and central nervous system. Alterations of NT levels have been associated with several neuropathological conditions such as Alzheimer's disease, and obesity associated eating disorders. However, the association between the level of plasma NT, brain NT receptor (NTR), and peripheral/brain pathologies under HFD‐induced obese‐insulin resistance is still unclear. The present study hypothesizes that an increase in peripheral/brain NT are associated with the peripheral/brain pathologies in time‐dependent manner of HFD consumption.

Methods

Male Wistar rats were received either a normal diet (ND) or HFD for 12 and 40 weeks (n=4‐6 per diet/each time point). At the end of each time point, plasma NT levels and metabolic parameters were determined. Brains were collected to measure the levels of hippocampal reactive oxygen species (ROS), the dendritic spine densities, the levels of brain NT, the expression of NTR, and apoptotic‐related proteins after being sacrificed.

Results

An increase in plasma NT level and gut NTR1 expression (Figure 1A‐B), the metabolic disturbances, peripheral oxidative stress, as indicated by increasing the level of serum malondialdehyde, and systemic inflammation as indicated by increasing the level of serum lipopolysaccharide of 12‐ and 40‐week HFD‐fed rats were observed, when compared to ND‐fed rats at the same time point. Additionally, increased hippocampal ROS production, and decreased dendritic spine density (Figure 1C) were found in 12‐ and 40‐week HFD‐fed rats. However, the expression of brain NTR1 (Figure 1D) and brain apoptotic‐related proteins were significantly increased in only 40‐week HFD‐fed rats.

Conclusion

These findings suggest that the alterations of peripheral NT level and brain NTR are associated with peripheral/brain pathologies after chronic HFD consumption. Therefore, an increase in plasma NT level would be one of the early biomarker prior to the development of brain pathologies in obese condition.
Development of a method of low‐intensity transcranial magnetic stimulation based on the resonance of neurotransmitters
Authors: Novikov Vadim V , Bobkova Natalia V , Fesenko Evgeny E
Published: December 2020

Background

In this work the effect of the weak combined magnetic fields (MFs) was studied in vivo in heritable animal model of AD: well characterized mice transgenic for mutant APPswe and mutant presenilin 1 (PS1dE9) that cause early onset familial Alzheimer’s disease (AD).

Method

Transgenic mice (Tg) and control C3H mice were exposed to the same MF at age of 8 months. Mice were also exposed by MF in two groups at the same time (Tg+MF and C3H+MF). Setups for generating a magnetic field inside the head were equipped with portable inductors that were mounted on the body. A direct current was supplied to generate a constant component of MFs with induction of 42 mcT. An alternating current signal produced by a programmable sinusoidal current generator was fed to create a variable component of MFs with induction of the amplitude of 80 nT. The current signal was the sum of frequencies in the range 4.0 ‐ 5.0 Hz. These frequencies correspond to the cyclotron frequencies of glutamic and aspartic acids as well as acetylcholine. After exposure to the MFs, the mice were trained in a Morris water maze for 18 days (four trials per day). Spatial memory was tested on the following day after completion of training with the hidden platform removed. During the test period (60 s), occupancy time spent in each sector was recorded.

Result

The MFs improved the memory in Tg animals. The results of the factor analysis demonstrate that factors of the sector preference became statistically significant for Tg groups after MFs exposure.

Conclusion

Thus, the data suggest that MFs can be applied for preventive purposes in a group of risk of AD.
Understanding trisomy 21–associated alterations in APP/Amyloid‐β biology using mouse models
Authors: Wiseman Frances K.
Published: December 2020

Background

People who have Down syndrome (DS) are at significantly increased risk of developing Alzheimer’s disease (AD). An additional copy of the chromosome 21 encoded gene, APP, in the absence of DS causes the early development of AD, and triplication of APP is likely to have a key role in early AD development in people who have DS. We have previously shown in a mouse model that an additional copy of genes on chromosome 21 other than APP, exacerbates Aβ accumulation and worsens APP‐transgene associated mortality; suggesting gene(s) on chromosome 21 in addition to APP modulate AD development in people who have DS.

Methods

We crossed mouse models of DS (Dp2Tyb, Dp3Tyb, Dp10Yey and Dp17Yey) that have segmental duplications of subregions of chromosome 21 with a conventional mouse model of amyloid deposition (J20 APP transgenic), to determine which groups of genes on chromosome 21 are sufficient to alter APP/Aβ biology.

Results

We determined that a causal gene(s) for altered Aβ aggregation lies between Mir802 and Zbtb21 (within the ‘Dp3Tyb’ mouse duplication). We also found that a dosage sensitive gene(s) that enhances APP transgene‐associated mortality is located between Mis18a and Runx1 (within the ‘Dp2Tyb’ mouse duplication) and that dosage‐sensitive genes that protect against APP transgene‐associated mortality are located between Mir802 and Zbtb21 (Dp3Tyb duplication), Prmt2 and Pdxk (Dp10Yey duplication) and also between Abcg1 and Rrp1b (Dp17Yey duplication). We go on to show that the rescue of mortality by the Dp10Yey duplication occurs independently of changes to the frequency or duration of APP transgene‐associated seizures. These data show an extra copy of multiple chromosome 21 gene orthologous modulate multiple AD‐related phenotypes in mouse models. Similar mechanisms may also occur in people who have DS when they develop AD‐dementia and may contribute the AD‐clinical differences that occur in this patient population.

Conclusions

These data suggest that Alzheimer’s disease in people who have Down syndrome is modulated by the additional copy of chromosome 21 genes other than APP. We now aim to identify these genes, to provide further novel mechanistic insight into the development of Alzheimer’s disease in people who have Down syndrome.
Illness perceptions and affective symptoms: Predictors of self‐management behaviors in mild cognitive impairment
Authors: Kim Hyejin , Sereika Susan M , Bender Catherine , Albert Steven , Lingler Jennifer
Published: December 2020

Background

Although a recent guideline on mild cognitive impairment (MCI) recommends non‐pharmacological interventions (i.e., self‐management behaviors such as exercise and cognitive training) for the management of MCI, predictors of such behaviors have not been identified in this population. We explored predictors of four categories of self‐management behaviors (i.e., physical activity, cognitive‐enhancing medication, mental activity, and vitamin/herbal supplements) in persons with MCI (PwMCI).

Methods

Using a cross‐sectional design, we conducted a secondary analysis pooling two existing datasets. We examined the predictive role of perceptual factors (i.e., individuals’ perceived understanding of MCI and its cause), affective symptoms (i.e., anxiety and depression), and clinical/sociodemographic factors. We also measured the total number of (range: 0‐4), and performance of each (‘yes’ or ‘no’) of the four categories of self‐management behaviors. We performed hierarchical linear (for the total number of self‐management behaviors) and binary logistic (for each self‐management behavior) regression analyses, controlling for age, sex, years of education, and the number of comorbid conditions as potential covariates.

Results

Participants (N=137) were on average 71.5 years old with 16.1 years of education. Most were Caucasian (92.0%) and diagnosed with amnestic MCI (82.5%). Although we did not find any main effects of predictors, some interactions were significant through further model expansion. Better performance of self‐management behaviors was associated with 1) lower levels of perceived understanding of MCI in men (b= ‐0.090, =.037), and 2) lower levels of anxiety symptoms in Caucasian participants (b= ‐0.206, p=.049). In hierarchical logistic regression analyses, higher levels of perceived understanding of MCI were associated with the better performance of physical (OR=0.942, 95%CI=[0.898, 0.980]) and mental (OR=0.959, 95% CI=[0.922,0.998]) activities among participants with lower levels of education. Among participants with more years of education, higher levels of perceived understanding of MCI were associated with better adherence to cognitive‐enhancing medication (OR=1.043, 95% CI=[1.002, 1.085]), and more anxiety symptoms were associated with better performance of mental activity (OR=1.048, 95% CI=[1.003,1.095]).

Conclusion

Our findings suggest that perceived understanding of MCI, levels of anxiety, and demographic factors should be considered together when evaluating the performance of self‐management behaviors to prevent or delay further cognitive changes among PwMCI.