Synchronous nonmonotonic changes in functional connectivity and white matter integrity in a rat model of sporadic Alzheimer's disease

Microstructural alterations in the locus coeruleus-entorhinal cortex pathway in Alzheimer's disease and frontotemporal dementia

INTRODUCTION

We investigated in vivo the microstructural integrity of the pathway connecting the locus coeruleus to the transentorhinal cortex (LC-TEC) in patients with Alzheimer's disease (AD) and frontotemporal dementia (FTD).

METHODS

Diffusion-weighted MRI scans were collected for 21 AD, 20 behavioral variants of FTD (bvFTD), and 20 controls. Fractional anisotropy (FA), mean, axial, and radial diffusivities (MD, AxD, RD) were computed in the LC-TEC pathway using a normative atlas. Atrophy was assessed using cortical thickness and correlated with microstructural measures.

RESULTS

We found (i) higher RD in AD than controls; (ii) higher MD, RD, and AxD, and lower FA in bvFTD than controls and AD; and (iii) a negative association between LC-TEC MD, RD, and AxD, and entorhinal cortex (EC) thickness in bvFTD (all p < 0.050).

DISCUSSION

LC-TEC microstructural alterations are more pronounced in bvFTD than AD, possibly reflecting neurodegeneration secondary to EC atrophy.

Highlights

Microstructural integrity of LC-TEC pathway is understudied in AD and bvFTD.LC-TEC microstructural alterations are present in both AD and bvFTD.Greater LC-TEC microstructural alterations in bvFTD than AD.LC-TEC microstructural alterations in bvFTD are associated to EC neurodegeneration.

Subject classification and cross-time prediction based on functional connectivity and white matter microstructure features in a rat model of Alzheimer's using machine learning

BACKGROUND

The pathological process of Alzheimer's disease (AD) typically takes decades from onset to clinical symptoms. Early brain changes in AD include MRI-measurable features such as altered functional connectivity (FC) and white matter degeneration. The ability of these features to discriminate between subjects without a diagnosis, or their prognostic value, is however not established.

METHODS

The main trigger mechanism of AD is still debated, although impaired brain glucose metabolism is taking an increasingly central role. Here, we used a rat model of sporadic AD, based on impaired brain glucose metabolism induced by an intracerebroventricular injection of streptozotocin (STZ). We characterized alterations in FC and white matter microstructure longitudinally using functional and diffusion MRI. Those MRI-derived measures were used to classify STZ from control rats using machine learning, and the importance of each individual measure was quantified using explainable artificial intelligence methods.

RESULTS

Overall, combining all the FC and white matter metrics in an ensemble way was the best strategy to discriminate STZ rats, with a consistent accuracy over 0.85. However, the best accuracy early on was achieved using white matter microstructure features, and later on using FC. This suggests that consistent damage in white matter in the STZ group might precede FC. For cross-timepoint prediction, microstructure features also had the highest performance while, in contrast, that of FC was reduced by its dynamic pattern which shifted from early hyperconnectivity to late hypoconnectivity.

CONCLUSIONS

Our study highlights the MRI-derived measures that best discriminate STZ vs control rats early in the course of the disease, with potential translation to humans.

Impact of transcranial direct current stimulation on white matter microstructure integrity in mild cognitive impairment patients according to effect modifiers as risk factors for Alzheimer's disease

Background

Little research exists on how individual risk factors for Alzheimer's disease (AD) affect the intermediate phenotype after transcranial direct current stimulation (tDCS), despite the importance of precision medicine-based therapeutic approaches.

Objective

To determine how an application of sequential tDCS (2 mA/day, left dorsolateral prefrontal cortex, 10 sessions) affects changes in white matter (WM) microstructure integrity in 63 mild cognitive impairment (MCI) patients with effect modifiers such as Aβ deposition, APOE ε4 carrier status, BDNF Val66Met polymorphism status, and sex.

Methods

We examined individual effect modifier-by-tDCS interactions and multiple effect modifiers-by-tDCS interactions for diffusion metrics. We also evaluated the association between baseline Aβ deposition and changes in WM microstructure integrity following tDCS.

Results

We found that APOE ε4 carrier status and sex had a significant interaction with tDCS, resulting in increased fractional anisotropy (FA) in the right uncinate fasciculus (UF) after stimulation. Additionally, we observed multiple effect modifiers-by-tDCS interactions on WM integrity of the right UF, leading to a more pronounced increase in FA values in APOE ε4 carriers and females with Val66 homozygotes. Finally, baseline Aβ deposition was positively associated with a difference in FA of the left cingulum in the hippocampal area, which showed a positive association with the changes in the score for delayed memory.

Conclusion

Our study shows the differential impact of individual AD risk factors on changes in the early intermediate phenotype after sequential tDCS in MCI patients. This research emphasizes the importance of precision medicine approaches in tDCS for the prodromal stages of AD.

The sodium glucose co-transporter 2 inhibitor ertugliflozin for Alzheimer's disease: Inhibition of brain insulin signaling disruption-induced tau hyperphosphorylation

An antidiabetic agent sodium glucose co-transporter 2 (SGLT2) inhibitor ertugliflozin has been revealed to bind to catalytic anionic site of acetylcholinesterase (AChE), which is considered to be associated with the cognitive decline in neurodegenerative diseases, such as Alzheimer's disease (AD). The aim of the present study was thus to probe the effect of ertugliflozin on AD. Intracerebroventricular injection of streptozotocin (STZ/i.c.v) (3 mg/kg) was done bilaterally in male Wistar rats at 7-8 weeks of age. Two treatment doses (5 mg/kg and 10 mg/kg) of ertugliflozin were given intragastrically to STZ/i.c.v-induced rats for 20 days daily for behavioral assessment. Biochemical estimations of cholinergic activity, neuronal apoptosis, mitochondrial function and synaptic plasticity were performed. Behavioral results with ertugliflozin treatment revealed attenuation of cognitive deficit. Ertugliflozin also inhibited hippocampal AChE activity, downregulated pro-apoptotic marker expression, as well as mitigated mitochondrial dysfunction and synaptic damage in STZ/i.c.v rats. Importantly, we found that the hyperphosphorylation of tau in the hippocampus of STZ/i.c.v rats was decreased after oral administration of ertugliflozin, which was accompanied by decreased Phospho.IRS-1_Ser307/Total.IRS-1 ratio and increased Phospho.Akt_Ser473/Total.Akt and Phospho.GSK3β_Ser9/Total.GSK3β ratios. Our results indicated that treatment with ertugliflozin reversed AD pathology, which may be associated with inhibition of insulin signaling disruption-induced tau hyperphosphorylation.

Parameter estimation for WMTI-Watson model of white matter using encoder-decoder recurrent neural network

PURPOSE

Biophysical modeling of the diffusion MRI (dMRI) signal provides estimates of specific microstructural tissue properties. Although non-linear least squares (NLLS) is the most widespread fitting method, it suffers from local minima and high computational cost. Deep learning approaches are steadily replacing NLLS, but come with the limitation that the model needs to be retrained for each acquisition protocol and noise level. In this study, a novel fitting approach was proposed based on the encoder-decoder recurrent neural network (RNN) to accelerate model estimation with good generalization to various datasets.

METHODS

The white matter tract integrity (WMTI)-Watson model as an implementation of the Standard Model of diffusion in white matter derives its parameters indirectly from the diffusion and kurtosis tensors (DKI). The RNN-based solver, which estimates the WMTI-Watson model from DKI, is therefore more readily translatable to various data, irrespective of acquisition protocols as long as the DKI was pre-computed from the signal. An embedding approach was also used to render the model insensitive to potential differences in distributions between training data and experimental data. The analytical solution, NLLS, RNN-, and a multilayer perceptron (MLP)-based methods were evaluated on synthetic and in vivo datasets of rat and human brain.

RESULTS

The proposed RNN solver showed highly reduced computation time over the analytical solution and NLLS, with similar accuracy but improved robustness, and superior generalizability over MLP.

CONCLUSION

The RNN estimator can be easily applied to various datasets without retraining, which shows great potential for a widespread use.

The impact of vasomotion on analysis of rodent fMRI data

Introduction

Small animal fMRI is an essential part of translational research in the cognitive neurosciences. Due to small dimensions and animal physiology preclinical fMRI is prone to artifacts that may lead to misinterpretation of the data. To reach unbiased translational conclusions, it is, therefore, crucial to identify potential sources of experimental noise and to develop correction methods for contributions that cannot be avoided such as physiological noise. Aim of this study was to assess origin and prevalence of hemodynamic oscillations (HDO) in preclinical fMRI in rat, as well as their impact on data analysis.

Methods

Following the development of algorithms for HDO detection and suppression, HDO prevalence in fMRI measurements was investigated for different anesthetic regimens, comprising isoflurane and medetomidine, and for both gradient echo and spin echo fMRI sequences. In addition to assessing the effect of vasodilation on HDO, it was studied if HDO have a direct neuronal correlate using local field potential (LFP) recordings. Finally, the impact of HDO on analysis of fMRI data was assessed, studying both the impact on calculation of activation maps as well as the impact on brain network analysis. Overall, 303 fMRI measurements and 32 LFP recordings were performed in 71 rats.

Results

In total, 62% of the fMRI measurements showed HDO with a frequency of (0.20 ± 0.02) Hz. This frequent occurrence indicated that HDO cannot be generally neglected in fMRI experiments. Using the developed algorithms, HDO were detected with a specificity of 95%, and removed efficiently from the signal time courses. HDO occurred brain-wide under vasoconstrictive conditions in both small and large blood vessels. Vasodilation immediately interrupted HDO, which, however, returned within 1 h under vasoconstrictive conditions. No direct neuronal correlate of HDO was observed in LFP recordings. HDO significantly impacted analysis of fMRI data, leading to altered cluster sizes and F-values for activated voxels, as well as altered brain networks, when comparing data with and without HDO.

Discussion

We therefore conclude that HDO are caused by vasomotion under certain anesthetic conditions and should be corrected during fMRI data analysis to avoid bias.

Multivalent Gd-DOTA Decorated Oligopeptide as Sensitive MRI Molecular Probes for In Vivo Imaging of Brain Connectivity

One of the most important goals of brain imaging is to define the anatomical connections within the brain. In addition to revealing normal circuitry, studies of neural connections and neuronal transport can show rewiring and degeneration following brain injury and diseases. In this work, a highly sensitive magnetic resonance imaging (MRI)-visible neural tracer that can be used to visualize brain connectivity in vivo is developed. It is based on an oligopeptide with gadolinium chelates appended to the peptide backbone. This peptide construct is a sensitive MRI contrast agent that was conjugated to the classical neurotracer, Cholera-toxin Subunit-B. Injection of this probe enabled it to be used to trace neural connections in vivo. This complements other MRI tracing techniques such as diffusion tensor imaging and manganese-enhanced MRI for neural tracing.

Imaging in experimental models of diabetes

Translational medicine, experimental medicine and experimental animal models, in particular mice and rats, represent a multidisciplinary field that has made it possible to achieve, in the last decades, important scientific progress. In this review, we have summarized the most frequently used imaging animal models, such as ultrasound (US), micro-CT, MRI and the optical imaging methods, and their main implications in diagnostic and therapeutic fields, with a particular focus on diabetes mellitus, a multifactorial disease extremely widespread among the general population.

Shenzhiling oral solution promotes myelin repair through PI3K/Akt-mTOR pathway in STZ-induced SAD mice

Most forms of Alzheimer's disease are sporadic. A model of sporadic Alzheimer's disease induced with bilateral intraventricular injection of streptozotocin leads to insulin resistance in the brain accompanied by memory decline, synaptic dysfunction, amyloid plaque deposition, oxidative stress, and neuronal apoptosis, all of which mimic the pathologies associated with sporadic Alzheimer's disease. Myelin injury is an essential component of Alzheimer's disease, playing a key role in early cognitive impairment. Our previously research found that sporadic Alzheimer's disease model showed myelin injury and that Shenzheling oral solution improved mild-to-moderate Alzheimer's disease; therefore, the protective effect of Shenzheling oral solution on myelin injury in early cognitive impairment is worth attention. In this study, the Morris water maze test results showed impairments in the learning and memory functions of mice in the model group, whereas the learning and memory function significantly improved after drug intervention. Immunohistochemistry showed increased β-amyloid plaques in the model group and decreased amounts in the drug group. Moreover, results of electron microscopy, western blot, and polymerase chain reaction showed that Shenzhiling oral solution improved early cognitive impairment and repaired myelin sheath damage; the potential mechanism of these effects may relate to the PI3K/Akt-mTOR signaling pathway. These findings support the application and promotion of Shenzhiling oral solution to treat sporadic Alzheimer's disease.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s13205-021-02900-x.

PIRACY: An Optimized Pipeline for Functional Connectivity Analysis in the Rat Brain

Resting state functional MRI (rs-fMRI) is a widespread and powerful tool for investigating functional connectivity (FC) and brain disorders. However, FC analysis can be seriously affected by random and structured noise from non-neural sources, such as physiology. Thus, it is essential to first reduce thermal noise and then correctly identify and remove non-neural artifacts from rs-fMRI signals through optimized data processing methods. However, existing tools that correct for these effects have been developed for human brain and are not readily transposable to rat data. Therefore, the aim of the present study was to establish a data processing pipeline that can robustly remove random and structured noise from rat rs-fMRI data. It includes a novel denoising approach based on the Marchenko-Pastur Principal Component Analysis (MP-PCA) method, FMRIB's ICA-based Xnoiseifier (FIX) for automatic artifact classification and cleaning, and global signal regression (GSR). Our results show that: (I) MP-PCA denoising substantially improves the temporal signal-to-noise ratio, (II) the pre-trained FIX classifier achieves a high accuracy in artifact classification, and (III) both independent component analysis (ICA) cleaning and GSR are essential steps in correcting for possible artifacts and minimizing the within-group variability in control animals while maintaining typical connectivity patterns. Reduced within-group variability also facilitates the exploration of potential between-group FC changes, as illustrated here in a rat model of sporadic Alzheimer's disease.