Gray Matter Changes in Parkinson's and Alzheimer's Disease and Relation to Cognition

Region-specific Cerebral Metabolic Alterations in Parkinson's Disease Patients With/without Mild Cognitive Impairment

N-acetylaspartate (NAA), choline (Cho) and creatine (Cr) are brain metabolites involved in some key neuronal functions within the brain, such as cognitive function. The aim of this study was to investigate whether Parkinson's disease (PD) with different cognitive status induces regional brain metabolite differences. 38 diagnosed PD patients, including 18 PD patients with normal cognitive (PDN), 20 PD subjects with cognitive impairment (PDMCI) and 25 healthy controls (HC) participated in this study. All subjects underwent a single-voxel proton MR spectroscopy (1H-MRS) on a 3T scanner. 1H-MRS were obtained from bilateral PCC, left thalamus and PFC regions in all subjects, respectively. Region-specific cerebral metabolic alterations existed in PD patients with different cognitive status. PDMCI patients showed a significant reduction of NAA, Cho and tCr in the PCC and left thalamus, compared to healthy controls; whereas lower levels of NAA and Cho in thalamus were found in PDN patients. Moreover, Cho and tCr levels were positively correlated with MMSE scores. Both NAA and tCr in PCC levels were positively correlated with MMSE and MoCA scores. The combination of thalamic and PCC metabolites showed a 75.6% accuracy in distinguishing PDMCI patients from PDN patients. This study provides preliminary evidence that thalamic, PCC and PFC neurometabolic alterations occur in PD patients with cognition decline. Findings of this study indicate that NAA and tCr abnormalities in PCC and thalamus might be used as a biomarker to track cognitive decline in Parkinson's disease in clinical settings.

The longitudinal volumetric and shape changes of subcortical nuclei in Parkinson's disease

Brain structural changes in Parkinson's disease (PD) are progressive throughout the disease course. Changes in surface morphology with disease progression remain unclear. This study aimed to assess the volumetric and shape changes of the subcortical nuclei during disease progression and explore their association with clinical symptoms. Thirty-four patients and 32 healthy controls were enrolled. The global volume and shape of the subcortical nuclei were compared between patients and controls at baseline. The volume and shape changes of the subcortical nuclei were also explored between baseline and 2 years of follow-up. Association analysis was performed between the volume of subcortical structures and clinical symptoms. In patients with PD, there were significantly atrophied areas in the left pallidum and left putamen, while in healthy controls, the right putamen was dilated compared to baseline. The local morphology of the left pallidum was correlated with Mini Mental State Examination scores. The left putamen shape variation was negatively correlated with changes in Unified Parkinson's Disease Rating Scale PART III scores. Local morphological atrophy of the putamen and pallidum is an important pathophysiological change in the development of PD, and is associated with motor symptoms and cognitive status in patients with PD.

Morphometric similarity differences in drug-naive Parkinson's disease correlate with transcriptomic signatures

BACKGROUND

Differences in cortical morphology have been reported in individuals with Parkinson's disease (PD). However, the pathophysiological mechanism of transcriptomic vulnerability in local brain regions remains unclear.

OBJECTIVE

This study aimed to characterize the morphometric changes of brain regions in early drug-naive PD patients and uncover the brain-wide gene expression correlates.

METHODS

The morphometric similarity (MS) network analysis was used to quantify the interregional structural similarity from multiple magnetic resonance imaging anatomical indices measured in each brain region of 170 early drug-naive PD patients and 123 controls. Then, we applied partial least squares regression to determine the relationship between regional changes in MS and spatial transcriptional signatures from the Allen Human Brain Atlas dataset, and identified the specific genes related to MS differences in PD. We further investigated the biological processes by which the PD-related genes were enriched and the cellular characterization of these genes.

RESULTS

Our results showed that MS was mainly decreased in cingulate, frontal, and temporal cortical areas and increased in parietal and occipital cortical areas in early drug-naive PD patients. In addition, genes whose expression patterns were associated with regional MS changes in PD were involved in astrocytes, excitatory, and inhibitory neurons and were functionally enriched in neuron-specific biological processes related to trans-synaptic signaling and nervous system development.

CONCLUSIONS

These findings advance our understanding of the microscale genetic and cellular mechanisms driving macroscale morphological abnormalities in early drug-naive PD patients and provide potential targets for future therapeutic trials.

Imaging Biomarkers in Prodromal and Earliest Phases of Parkinson's Disease

Assessing imaging biomarker in the prodromal and early phases of Parkinson's disease (PD) is of great importance to ensure an early and safe diagnosis. In the last decades, imaging modalities advanced and are now able to assess many different aspects of neurodegeneration in PD. MRI sequences can measure iron content or neuromelanin. Apart from SPECT imaging with Ioflupane, more specific PET tracers to assess degeneration of the dopaminergic system are available. Furthermore, metabolic PET patterns can be used to anticipate a phenoconversion from prodromal PD to manifest PD. In this regard, it is worth mentioning that PET imaging of inflammation will gain significance. Molecular imaging of neurotransmitters like serotonin, noradrenaline and acetylcholine shed more light on non-motor symptoms. Outside of the brain, molecular imaging of the heart and gut is used to measure PD-related degeneration of the autonomous nervous system. Moreover, optical coherence tomography can noninvasively detect degeneration of retinal fibers as a potential biomarker in PD. In this review, we describe these state-of-the-art imaging modalities in early and prodromal PD and point out in how far these techniques can and will be used in the future to pave the way towards a biomarker-based staging of PD.

Diagnostic value of plasma SIRT1 levels and whole-brain gray matter volume in Parkinson's disease patients with cognitive impairment

OBJECTIVE

This study was designed to investigate the diagnostic value of plasma SIRT1 levels and whole-brain gray matter (GM) volume in Parkinson's disease (PD) patients with cognitive impairment.

METHODS

Automated enzymatic analysis was performed to measure plasma SIRT1 levels in 80 healthy controls and 77 PD patients. Motor symptoms and nonmotor symptoms in PD patients were assessed using the corresponding scales. A Siemens MAGNETOM Prisma 3 T MRI scanner was used to acquire images in 35 of 77 PD patients.

RESULTS

Plasma SIRT1 levels in PD patients were lower than those in healthy controls. Plasma SIRT1 levels were negatively correlated with the age, Unified Parkinson's Disease Rating Scale Part III (UPDRS-III) scores, anxiety, depression, excessive daytime sleepiness (EDS), quality of life, and especially cognitive impairment. Thus, it showed that plasma SIRT1 levels were relevant to visuospatial/executive function, memory, and language. Receiver-operating characteristic (ROC) analysis confirmed that plasma SIRT1 levels had good diagnostic accuracy for PD with anxiety and EDS. Furthermore, plasma SIRT1 levels had a significant positive correlation with GM volume in the whole brain, and ROC analysis confirmed that plasma SIRT1 levels and the total GM volume had good diagnostic accuracy for PD with cognitive impairment.

CONCLUSIONS

This study showed that plasma SIRT1 levels were correlated with the nonmotor symptoms of anxiety, depression, EDS, and especially cognitive impairment as well as the total GM volume. Furthermore, the combination of plasma SIRT1 levels and the total GM volume had good diagnostic accuracy for PD with cognitive impairment.

Atrophy of hippocampal subfields relates to memory decline during the pathological progression of Alzheimer's disease

Background

It has been well documented that atrophy of hippocampus and hippocampal subfields is closely linked to cognitive decline in normal aging and patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). However, evidence is still sparce regarding the atrophy of hippocampus and hippocampal subfields in normal aging adults who later developed MCI or AD.

Objective

To examine whether atrophy of hippocampus and hippocampal subfields has occurred in normal aging before a diagnosis of MCI or AD.

Methods

We analyzed structural magnetic resonance imaging (MRI) data of cognitively normal (CN, n = 144), MCI (n = 90), and AD (n = 145) participants obtained from the Alzheimer's Disease Neuroimaging Initiative. The CN participants were categorized into early dementia converters (CN-C) and non-converters (CN-NC) based on their scores of clinical dementia rating after an average of 36.2 months (range: 6-105 months). We extracted the whole hippocampus and hippocampal subfields for each participant using FreeSurfer, and analyzed the differences in volumes of hippocampus and hippocampal subfields between groups. We then examined the associations between volume of hippocampal subfields and delayed recall scores in each group separately.

Results

Hippocampus and most of the hippocampal subfields demonstrated significant atrophy during the progression of AD. The CN-C and CN-NC groups differed in the left hippocampus-amygdala transition area (HATA). Furthermore, the volume of presubiculum was significantly correlated with delayed recall scores in the CN-NC and AD groups, but not in the CN-C and MCI groups.

Conclusion

Hippocampal subfield atrophy (i.e., left HATA) had occurred in cognitively normal elderly individuals before clinical symptoms were recognized. Significant associations of presubiculum with delayed recall scores in the CN-NC and AD groups highlight the essential role of the hippocampal subfields in both early dementia detection and AD progression.

Relationships of Residential Distance to Major Traffic Roads with Dementia Incidence and Brain Structure Measures: Mediation Role of Air Pollution

Background: Uncertainty exists regarding the operating pathways between near-roadway exposure and dementia incidence. We intend to examine relationships between proximity to major roadways with dementia incidence and brain MRI structure measures, and potential mediation roles of air and noise pollution. Methods: The cohort study was based on the UK Biobank. Baseline survey was conducted from 2006 to 2010, with linkage to electronic health records conducted for follow-up. Residential distance to major roadways was ascertained residential address postcode. A land use regression model was applied for estimating traffic-related air pollution at residence. Dementia incidence was ascertained using national administrative databases. Brain MRI measures were derived as image-derived phenotypes, including total brain, white matter, gray matter, and peripheral cortical gray matter. Results: We included 460,901 participants [mean (SD) age: 57.1 (8.1) years; men: 45.7%]. Compared with individuals living >1,000 m from major traffic roads, living ≤1,000 m was associated with a 13% to 14% higher dementia risk, accounting for 10% of dementia cases. Observed association between residential distance and dementia was substantially mediated by traffic-related air pollution, mainly nitrogen dioxide (proportion mediated: 63.6%; 95% CI, 27.0 to 89.2%) and PM2.5 (60.9%, 26.8 to 87.0%). The shorter residential distance was associated with smaller volumes of brain structures, which was also mediated by traffic-related air pollutants. No significant mediation role was observed of noise pollution. Conclusions: The shorter residential distance to major roads was associated with elevated dementia incidence and smaller brain structure volumes, which was mainly mediated by traffic-related air pollution.

Are Ischemic Stroke and Alzheimer's Disease Genetically Consecutive Pathologies?

Complex diseases that affect the functioning of the central nervous system pose a major problem for modern society. Among these, ischemic stroke (IS) holds a special place as one of the most common causes of disability and mortality worldwide. Furthermore, Alzheimer's disease (AD) ranks first among neurodegenerative diseases, drastically reducing brain activity and overall life quality and duration. Recent studies have shown that AD and IS share several common risk and pathogenic factors, such as an overlapping genomic architecture and molecular signature. In this review, we will summarize the genomics and RNA biology studies of IS and AD, discussing the interconnected nature of these pathologies. Additionally, we highlight specific genomic points and RNA molecules that can serve as potential tools in predicting the risks of diseases and developing effective therapies in the future.

Neurofilaments - Small proteins of physiological significance and predictive power for future neurodegeneration and cognitive decline across the life span

Neurofilaments (NFs) are not only important for axonal integrity and nerve conduction in large myelinated axons but they are also thought to be crucial for receptor and synaptic functioning. Therefore, NFs may play a critical role in cognitive functions, as cognitive processes are known to depend on synaptic integrity and are modulated by dopaminergic signaling. Here, we present a theory-driven interdisciplinary approach that NFs may link inflammation, neurodegeneration, and cognitive functions. We base our hypothesis on a wealth of evidence suggesting a causal link between inflammation and neurodegeneration and between these two and cognitive decline (see Fig. 1), also taking dopaminergic signaling into account. We conclude that NFs may not only serve as biomarkers for inflammatory, neurodegenerative, and cognitive processes but also represent a potential mechanical hinge between them, moreover, they may even have predictive power regarding future cognitive decline. In addition, we advocate the use of both NFs and MRI parameters, as their synthesis offers the opportunity to individualize medical treatment by providing a comprehensive view of underlying disease activity in neurological diseases. Since our society will become significantly older in the upcoming years and decades, maintaining cognitive functions and healthy aging will play an important role. Thanks to technological advances in recent decades, NFs could serve as a rapid, noninvasive, and relatively inexpensive early warning system to identify individuals at increased risk for cognitive decline and could facilitate the management of cognitive dysfunctions across the lifespan.

A comparative study of posterior cingulate metabolism in patients with mild cognitive impairment due to Parkinson's disease or Alzheimer's disease

Few comparative studies have assessed metabolic brain changes in cognitive impairment among neurodegenerative disorders, and the posterior cingulate cortex (PCC) is a metabolically active brain region with high involvement in multiple cognitive processes. Therefore, in this study, metabolic abnormalities of the PCC were compared in patients with mild cognitive impairment (MCI) due to Parkinson's disease (PD) or Alzheimer's disease (AD), as examined by proton magnetic resonance spectroscopy (1H-MRS). Thirty-eight patients with idiopathic PD, including 20 with mild cognitive impairment (PDMCI) and 18 with normal cognitive function (PDN), 18 patients with probable mild cognitive impairment (ADMCI), and 25 healthy elderly controls (HCs) were recruited and underwent PCC 1H-MRS scans. Compared with HCs, patients with PDMCI exhibited significantly reduced concentrations of N-acetyl aspartate (NAA), total NAA (tNAA), choline (Cho), glutathione (GSH), glutamate + glutamine (Glx) and total creatine (tCr), while ADMCI cases exhibited significantly elevated levels of myo-inositol (Ins) and Ins/tCr ratio, as well as reduced NAA/Ins ratio. No significant metabolic changes were detected in PDN subjects. Compared with ADMCI, reduced NAA, Ins and tCr concentrations were detected in PDMCI. Besides, ROC curve analysis revealed that tCr concentration could differentiate PDMCI from PDN with an AUC of 0.71, and NAA/Ins ratio could differentiate patients with MCI from controls with normal cognitive function with an AUC of 0.74. Patients with PDMCI and ADMCI exhibited distinct PCC metabolic 1H-MRS profiles. The findings suggested cognitively normal PD patients with low NAA and tCr in the PCC might be at risk of preclinical PDMCI, and Ins and/or NAA/MI ratio in the PCC should be reconsidered a possible biomarker of preclinical MCI in clinical practice. So, comparing PCC's 1H-MRS profiles of cognitive impairment among neurodegenerative illnesses may provide useful information for better defining the disease process and elucidate possible treatment mechanisms.

Correlation between cerebral hemodynamic functional near-infrared spectroscopy and positron emission tomography for assessing mild cognitive impairment and Alzheimer's disease: An exploratory study

This study was performed to investigate the usefulness of functional near-infrared spectroscopy (fNIRS) by conducting a comparative analysis of hemodynamic activation detected by fNIRS and positron emission tomography (PET) and magnetic resonance imaging (MRI) in patients with mild cognitive impairment (MCI) and Alzheimer's disease (AD). Participants were divided into four groups: the subjective memory impairment (SMI), amnestic MCI (aMCI), non-amnestic MCI (naMCI), and AD groups. We recorded the hemodynamic response during the semantic verbal fluency task (SVFT) using a commercial wireless continuous-wave NIRS system. The correlation between the parameters of the neuroimaging assessments among the groups was analyzed. Region of interest-based comparisons showed that the four groups had significantly different hemodynamic responses during SVFT in the bilateral dorsolateral prefrontal cortex (DLPFC). The linear mixed effect model result indicates that the mean ΔHbO2 from the bilateral DLPFC regions showed a significant positive correlation to the overall FDG-PET after controlling for age and group differences in the fNIRS signals. Amyloid PET signals tended to better differentiate the AD group from other groups, and fNIRS signals tended to better differentiate the SMI group from other groups. In addition, a comparison between the group pairs revealed a mirrored pattern between the hippocampal volume and hemodynamic response in the DLPFC. The hemodynamic response detected by fNIRS showed a significant correlation with metabolic and anatomical changes associated with disease progression. Therefore, fNIRS may be considered as a screening tool to predict the hemodynamic and metabolic statuses of the brain in patients with MCI and AD.

Assessment of complementary white matter microstructural changes and grey matter atrophy in a preclinical model of Alzheimer's disease

Alzheimer's disease (AD) has been associated with amyloid and tau pathology, as well as neurodegeneration. Beyond these hallmark features, white matter microstructural abnormalities have been observed using MRI. The objective of this study was to assess grey matter atrophy and white matter microstructural changes in a preclinical mouse model of AD (3xTg-AD) using voxel-based morphometry (VBM) and free-water (FW) diffusion tensor imaging (FW-DTI). Compared to controls, lower grey matter density was observed in the 3xTg-AD model, corresponding to the small clusters in the caudate-putamen, hypothalamus, and cortex. DTI-based fractional anisotropy (FA) was decreased in the 3xTg model, while the FW index was increased. Notably, the largest clusters for both FW-FA and FW index were in the fimbria, with other regions including the anterior commissure, corpus callosum, forebrain septum, and internal capsule. Additionally, the presence of amyloid and tau in the 3xTg model was confirmed with histopathology, with significantly higher levels observed across many regions of the brain. Taken together, these results are consistent with subtle neurodegenerative and white matter microstructural changes in the 3xTg-AD model that manifest as increased FW, decreased FW-FA, and decreased grey matter density.

The Latest Cellular and Molecular Mechanisms of COVID-19 on Non-Lung Organs

Understanding the transmission pathways of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will aid in developing effective therapies directed at the virus’s life cycle or its side effects. While severe respiratory distress is the most common symptom of a coronavirus 2019 (COVID-19) infection, the virus is also known to cause damage to almost every major organ and system in the body. However, it is not obvious whether pathological changes in extra-respiratory organs are caused by direct infection, indirect, or combination of these effects. In this narrative review, we first elaborate on the characteristics of SARS-CoV-2, followed by the mechanisms of this virus on various organs such as brain, eye, and olfactory nerve and different systems such as the endocrine and gastrointestinal systems.

Brain Gray Matter Volume Mediated the Correlation Between Plasma P-Tau and Cognitive Function of Early Alzheimer's Disease in China: A Cross-Sectional Observational Study

BACKGROUND

The primary manifestations of Alzheimer's disease (AD) include cognitive decline and brain gray matter volume (GMV) atrophy. Recent studies have found that plasma phosphorylated-tau (p-tau) concentrations perform better in diagnosing, differentiating, and monitoring the progression of AD. However, the correlation between plasma p-tau, GMV, and cognition remains unclear.

OBJECTIVE

To investigate whether GMV plays a mediating role in the association between plasma p-tau concentrations and cognition.

METHODS

In total, 99 participants (47 patients with AD and 52 cognitively unimpaired [CU] individuals) were included. All participants underwent neuropsychological assessments, laboratory examinations, and magnetic resonance imaging scans. Plasma p-tau217 and p-tau181 concentrations were measured using an enzyme-linked immunosorbent assay kit. Voxel-based morphometry was performed to assess participants' brain GMV. Partial correlation and mediation analyses were conducted in AD group.

RESULTS

Plasma p-tau concentrations were significantly higher in the AD group than in the CU group. Patients with AD had significant brain GMV atrophy in the right hippocampus, bilateral middle temporal gyrus, and right inferior temporal gyrus. In the AD group, there were significant correlations between plasma p-tau217 concentrations, GMV, and Mini-Mental State Examination (MMSE) scores. Brain GMV of the right hippocampus mediated the association between plasma p-tau217 concentrations and MMSE scores. A significant correlation between plasma p-tau181 and MMSE scores was not identified.

CONCLUSION

The findings indicate that p-tau217 is a promising biomarker for central processes affecting brain GMV and cognitive function. This may provide potential targets for future intervention and treatment of tau-targeting therapies in the early stages of AD.

Radiomic and clinical nomogram for cognitive impairment prediction in Wilson's disease

Objective

To investigate potential biomarkers for the early detection of cognitive impairment in patients with Wilson's disease (WD), we developed a computer-assisted radiomics model to distinguish between WD and WD cognitive impairment.

Methods

Overall, 136 T1-weighted MR images were retrieved from the First Affiliated Hospital of Anhui University of Chinese Medicine, including 77 from patients with WD and 59 from patients with WD cognitive impairment. The images were divided into training and test groups at a ratio of 70:30. The radiomic features of each T1-weighted image were extracted using 3D Slicer software. R software was used to establish clinical and radiomic models based on clinical characteristics and radiomic features, respectively. The receiver operating characteristic profiles of the three models were evaluated to assess their diagnostic accuracy and reliability in distinguishing between WD and WD cognitive impairment. We combined relevant neuropsychological test scores of prospective memory to construct an integrated predictive model and visual nomogram to effectively assess the risk of cognitive decline in patients with WD.

Results

The area under the curve values for distinguishing WD and WD cognitive impairment for the clinical, radiomic, and integrated models were 0.863, 0.922, and 0.935 respectively, indicative of excellent performance. The nomogram based on the integrated model successfully differentiated between WD and WD cognitive impairment.

Conclusion

The nomogram developed in the current study may assist clinicians in the early identification of cognitive impairment in patients with WD. Early intervention following such identification may help improve long-term prognosis and quality of life of these patients.

Plasma p-tau181 associated with structural changes in mild cognitive impairment

Alzheimer's disease (AD) is a progressive neurodegenerative disease associated with dementia and is a serious concern for the health of individuals and government health care systems worldwide. Gray matter atrophy and white matter damage are major contributors to cognitive deficits in AD patients, as demonstrated by magnetic resonance imaging (MRI). Many of these brain changes associated with AD begin to occur about 15 years before the onset of initial clinical symptoms. Therefore, it is critical to find biomarkers reflective of these brain changes associated with AD to identify this disease and monitor its prognosis and development. The increased plasma level of hyperphosphorylated tau 181 (p-tau181) has been recently considered a novel biomarker for the diagnosis of AD, preclinical AD, and mild cognitive impairment (MCI). In the current study, we examined the association of cerebrospinal fluid (CSF) and plasma levels of p-tau181 with structural brain changes in cortical thickness, cortical volume, surface area, and subcortical volume in MCI patients. In this cross-sectional study, we included the information of 461 MCI patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. The results of voxel-wise partial correlation analyses showed a significant negative correlation between the increased levels of plasma p-tau181, CSF total tau, and CSF p-tau181 with structural changes in widespread brain regions. These results provide evidence for the use of plasma p-tau181 as a diagnostic marker for structural changes in the brain associated with the early stages of AD and neurodegeneration.

A Stacking Framework for Multi-Classification of Alzheimer’s Disease Using Neuroimaging and Clinical Features

Background: Alzheimer’s disease (AD) is a severe health problem. Challenges still remain in early diagnosis. Objective: The objective of this study was to build a Stacking framework for multi-classification of AD by a combination of neuroimaging and clinical features to improve the performance. Methods: The data we used were from the Alzheimer’s Disease Neuroimaging Initiative database with a total of 493 subjects, including 125 normal control (NC), 121 early mild cognitive impairment, 109 late mild cognitive impairment (LMCI), and 138 AD. We selected structural magnetic resonance imaging (sMRI) features by voting strategy. The imaging features, demographic information, Mini-Mental State Examination, and Alzheimer’s Disease Assessment Scale-Cognitive Subscale were combined together as classification features. We proposed a two-layer Stacking ensemble framework to classify four types of people. The first layer represented support vector machine, random forests, adaptive boosting, and gradient boosting decision tree; the second layer was a logistic regression classifier. Additionally, we analyzed performance of only sMRI feature and combined features and compared the proposed model with four base classifiers. Results: The Stacking model combined with sMRI and non-imaging features outshined four base classifiers with an average accuracy of 86.96% . Compared with using sMRI data alone, sMRI combined with non-imaging features significantly improved diagnostic accuracy, especially in NC versus LMCI and LMCI versus AD by 14.08% . Conclusion: The Stacking framework we used can improve performance in diagnosis of AD using combined features.

Test-retest reliability of multi-parametric maps (MPM) of brain microstructure

Multiparameter mapping (MPM) is a quantitative MRI protocol that is promising for studying microstructural brain changes in vivo with high specificity. Reliability values are an important prior knowledge for efficient study design and facilitating replicable findings in development, aging and neuroplasticity research. To explore longitudinal reliability of MPM we acquired the protocol in 31 healthy young subjects twice over a rescan interval of 4 weeks. We assessed the within-subject coefficient of variation (WCV), the between-subject coefficient of variation (BCV), and the intraclass correlation coefficient (ICC). Using these metrics, we investigated the reliability of (semi-) quantitative magnetization transfer saturation (MT_sat), proton density (PD), transversal relaxation (R2*) and longitudinal relaxation (R1). To increase relevance for explorative studies in development and training-induced plasticity, we assess reliability both on local voxel- as well as ROI-level. Finally, we disentangle contributions and interplay of within- and between-subject variability to ICC and assess the optimal degree of spatial smoothing applied to the data. We reveal evidence that voxelwise ICC reliability of MPMs is moderate to good with median values in cortex (subcortical GM): MT: 0.789 (0.447) PD: 0.553 (0.264) R1: 0.555 (0.369) R2*: 0.624 (0.477). The Gaussian smoothing kernel of 2 to 4 mm FWHM resulted in optimal reproducibility. We discuss these findings in the context of longitudinal intervention studies and the application to research designs in neuroimaging field.

Gardenia jasminoides J. Ellis extract alleviated white matter damage through promoting the differentiation of oligodendrocyte precursor cells via suppressing neuroinflammation

Increasing evidence has highlighted the role of white matter damage in the pathology of Alzheimer's disease (AD). Previous research has shown that a mixture of crocin analogues (GJ-4), Gardenia jasminoides J. Ellis extract, improved cognition in several AD mouse models, but the mechanism remains unclear. The aim of the present study was to investigate the effects and underlying mechanisms of GJ-4 on white matter damage. Proteomic analysis and western blotting results suggested that the level of myelin-related proteins, including myelin basic protein (MBP), myelin associated glycoprotein (MAG) and myelin associated oligodendrocyte basic protein (MOBP), was significantly decreased in the brain of PrP-hAβPPswe/PS1ΔE9 (APP/PS1) transgenic mice, and GJ-4 treatment increased the expressions of these proteins. This result revealed that GJ-4 could ameliorate myelin injury, suggesting that this might be a possible mechanism of GJ-4 on cognition. To validate the effects of GJ-4 on myelin, a metabolite of GJ-4, crocetin, which can pass through the blood-brain barrier, was applied in in vitro experiments. A mechanistic study revealed that crocetin significantly promoted the differentiation of primary cultured oligodendrocyte precursor cells to oligodendrocytes through up-regulation of nuclear Ki67 and transcription factor 2 (Olig2). Oligodendrocytes, the myelin-forming cells, have been reported to be lifelong partners of neurons. Therefore, to investigate the effects of crocetin on myelin and neurons, lysophosphatidylcholine (LPC)-treated primary mixed midbrain neuronal/glial culture was used. Immunofluorescence results indicated that crocetin treatment protected neurons and suppressed microglial activation against LPC-induced injury. To further discern the effects of GJ-4 on white matter injury and neuroinflammation, an LPC-induced mouse model was developed. GJ-4 administration increased oligodendrocyte proliferation, differentiation, and myelin repair. The mechanistic study indicated that GJ-4 improved white matter injury through the regulation of neuroinflammatory dysfunction. These data indicated that GJ-4 effectively repaired white matter damage in the LPC-treated mice. Thus, the present study supported GJ-4 as a potential therapeutic agent for AD and white matter related diseases.

The reduction of hippocampal volume in Parkinson's disease

The volume of the hippocampus decreases more slowly than the volume of the cortex during normal aging. We explored changes in the hippocampus-to-cortex volume (HV:CTV) ratio with increasing age in non-demented Parkinson's disease (PD) patients as compared to healthy controls (HC). We also evaluated the association between the HV:CTV ratio and cognitive outcomes. Altogether 130 participants without dementia aged 51-88 years were consecutively enrolled, including 54 PD patients (mean age 67, standard deviation (SD) 8 years) and 76 HC (mean age 69, SD 7 years). All participants underwent structural magnetic resonance examination and psychological evaluation. Hippocampal and cortex volumes were determined from T1 and FLAIR scans using FreeSurfer software, and the HV:CTV ratio was calculated. Regression lines for age-dependence of the HV:CTV ratio for PD and HC groups were calculated. We further assessed the association between the HV:CTV ratio and cognitive tests examining hippocampus-related cognitive functions. PD patients and age-matched HC showed a significant difference in age-dependence of HV:CTV ratio (p value = 0.012), with a decreasing slope in PD and increasing slope in HC. In the PD group, a significant correlation (R = 0.561, p = 0.024) was observed between the HV:CTV ratio and the Digit Symbol-Coding test. The reduction of HV:CTV ratio is accelerated in pathological aging due to PD pathology. The HV:CTV ratio was associated with impaired processing speed, i.e., the cognitive function that is linked to subcortical alterations of both associated basal ganglia circuitry and the hippocampus.

Biomedical Perspectives of Acute and Chronic Neurological and Neuropsychiatric Sequelae of COVID-19

The incidence of infections from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiologic agent for coronavirus disease 2019 (COVID-19), has dramatically escalated following the initial outbreak in China, in late 2019, resulting in a global pandemic with millions of deaths. Although the majority of infected patients survive, and the rapid advent and deployment of vaccines have afforded increased immunity against SARS-CoV-2, long-term sequelae of SARS-CoV-2 infection have become increasingly recognized. These include, but are not limited to, chronic pulmonary disease, cardiovascular disorders, and proinflammatory-associated neurological dysfunction that may lead to psychological and neurocognitive impairment. A major component of cognitive dysfunction is operationally categorized as "brain fog" which comprises difficulty concentrating, forgetfulness, confusion, depression, and fatigue. Multiple parameters associated with long-term neuropsychiatric sequelae of SARS-CoV-2 infection have been detailed in clinical studies. Empirically elucidated mechanisms associated with the neuropsychiatric manifestations of COVID-19 are by nature complex, but broad-based working models have focused on mitochondrial dysregulation, leading to systemic reductions of metabolic activity and cellular bioenergetics within the CNS structures. Multiple factors underlying the expression of brain fog may facilitate future pathogenic insults, leading to repetitive cycles of viral and bacterial propagation. Interestingly, diverse neurocognitive sequelae associated with COVID-19 are not dissimilar from those observed in other historical pandemics, thereby providing a broad and integrative perspective on potential common mechanisms of CNS dysfunction subsequent to viral infection. Poor mental health status may be reciprocally linked to compromised immune processes and enhanced susceptibility to infection by diverse pathogens. By extrapolation, we contend that COVID-19 may potentiate the severity of neurological/neurocognitive deficits in patients afflicted by well-studied neurodegenerative disorders, such as Alzheimer's disease and Parkinson's disease. Accordingly, the prevention, diagnosis, and management of sustained neuropsychiatric manifestations of COVID-19 are pivotal health care directives and provide a compelling rationale for careful monitoring of infected patients, as early mitigation efforts may reduce short- and long-term complications.

The Neuropsychological Correlates of Brain Perfusion and Gray Matter Volume in Alzheimer's Disease

BACKGROUND

Neuropsychological tests, structural neuroimaging, and functional neuroimaging are employed as diagnostic and monitoring biomarkers of patients with Alzheimer's disease (AD)Objective:We aimed to elucidate the similarities and differences in neuropsychological tests and neuroimaging with the use of the Mini-Mental State Examination (MMSE), Alzheimer's Disease Assessment Scale cognitive subscale (ADAS-cog), structural magnetic resonance image (MRI), and perfusion single photon emission computed tomography (SPECT), and parametric image analyses to understand its role in AD.

METHODS

Clinically-diagnosed AD patients (n = 155) were scanned with three-dimensional T1-weighted MRI and N-isopropyl-p-[123I] iodoamphetamine SPECT. Statistical parametric mapping 12 was used for preprocessing images, statistical analyses, and voxel-based morphometry for gray matter volume analyses. Group comparison (AD versus healthy controls), multiple regression analyses with MMSE, ADAS-cog total score, and ADAS-cog subscores as variables, were performed.

RESULTS

The AD group showed bilateral hippocampal volume reduction and hypoperfusion in the bilateral temporo-parietal lobe and posterior midline structures. Worse MMSE and ADAS-cog total score were associated with bilateral temporo-parietal volume loss and hypoperfusion. MMSE, but not ADAS-cog, was associated with the posterior midline structures. The ADAS-cog subscores were associated with the temporal volume, while perfusion analyses were linked to the left temporo-parietal region with the language function and right analogous region with the constructional praxis subscore.

CONCLUSION

MMSE and ADAS-cog are associated with temporo-parietal regions, both in volume and perfusion. The MMSE score is associated with posterior midline structures and linked to an abnormal diagnostic AD pattern. Perfusion image analyses better represents the cognitive function in AD patients.

Connecting Mind-Body Therapy-Mediated Effects to Pathological Features of Alzheimer's Disease

Alzheimer's disease (AD) is a complex, multifactorial neurodegenerative disorder that represents a major and increasing global health challenge. In most cases, the first clinical symptoms of AD are preceded by neuropathological changes in the brain that develop years to decades before their onset. Therefore, research in the last years has focused on this preclinical stage of AD trying to discover intervention strategies that might, if implemented effectively, delay or prevent disease progression. Among those strategies, mind-body therapies such as yoga and meditation have gained increasing interest as complementary alternative interventions. Several studies have reported a positive impact of yoga and meditation on brain health in both healthy older adults and dementia patients. However, the underlying neurobiological mechanisms contributing to these effects are currently not known in detail. More specifically, it is not known whether yogic interventions, directly or indirectly, can modulate risk factors or pathological mechanisms involved in the development of dementia. In this article, we first review the literature on the effects of yogic practices on outcomes such as cognitive functioning and neuropsychiatric symptoms in patients with mild cognitive impairment and dementia. Then, we analyze how yogic interventions affect different risk factors as well as aspects of AD pathophysiology based on observations of studies in healthy individuals or subjects with other conditions than dementia. Finally, we integrate this evidence and propose possible mechanisms that might explain the positive effects of yogic interventions in cognitively impaired individuals.

Cognition effectiveness of continuous positive airway pressure treatment in obstructive sleep apnea syndrome patients with cognitive impairment: a meta-analysis

Obstructive sleep apnea (OSA) is a common respiratory disorder characterized by recurrent pharyngeal collapses during sleep leading to intermittent hypoxia and sleep disruption. Cognitive challenges and high risks of cognitive impairment, including Alzheimer's disease (AD), are closely associated with OSA. Currently, continuous positive airway pressure (CPAP) is widely used in the treatment of OSA. However, whether CPAP benefits cognitive functions in patients with OSA remains elusive. Here, we identified published studies through a systematic review of PubMed, Cochrane Library, Embase, Wanfang Data, CBM, and CNKI from January 1, 1970, to July 1, 2020. 288 patients from 7 articles (one was excluded in the meta-analysis for it was a follow-up study) were included in the present study. It revealed that cognitive functions of OSA patients with mild cognitive impairment (MCI) or AD were mildly but significantly improved after CPAP treatment (SMD 0.49, 95% CI 0.11-0.86), especially long-term CPAP treatment (SMD 0.56, 95% CI 0.10-1.02, p = 0.02), as measured by Mini-Mental State Examination (MMSE) (SMD 0.49, 95%CI 0.11-0.86). However, no significant cognition benefits were detected by the Montreal Cognitive Assessment (SMD 0.43, 95% CI 0.85-1.72). In terms of heterogeneity, cognitive improvements by CPAP were detectable on OSA patients either at a younger age or over longer periods of CPAP treatment. Therefore, our findings highlight the partial efficiency of CPAP treatment in cognition improvement of OSA patients with MCI or AD.

Brain age and Alzheimer's-like atrophy are domain-specific predictors of cognitive impairment in Parkinson's disease

Recently, it was shown that patients with Parkinson's disease (PD) who exhibit an "Alzheimer's disease (AD)-like" pattern of brain atrophy are at greater risk for future cognitive decline. This study aimed to investigate whether this association is domain-specific and whether atrophy associated with brain aging also relates to cognitive impairment in PD. SPARE-AD, an MRI index capturing AD-like atrophy, and atrophy-based estimates of brain age were computed from longitudinal structural imaging data of 178 PD patients and 84 healthy subjects from the LANDSCAPE cohort. All patients underwent an extensive neuropsychological test battery. Patients diagnosed with mild cognitive impairment or dementia were found to have higher SPARE-AD scores as compared to patients with normal cognition and healthy controls. All patient groups showed increased brain age. SPARE-AD predicted impairment in memory, language and executive functions, whereas advanced brain age was associated with deficits in attention and working memory. Data suggest that SPARE-AD and brain age are differentially related to domain-specific cognitive decline in PD. The underlying pathomechanisms remain to be determined.

Diffusion kurtosis imaging detects the time-dependent progress of pathological changes in the oral rotenone mouse model of Parkinson's disease

Clinical diagnosis of Parkinson's disease (PD) occurs typically when a substantial proportion of dopaminergic neurons in the substantia nigra (SN) already died, and the first motor symptoms appear. Therefore, tools enabling the early diagnosis of PD are essential to identify early-stage PD patients in which neuroprotective treatments could have a significant impact. Here, we test the utility and sensitivity of the diffusion kurtosis imaging (DKI) in detecting progressive microstructural changes in several brain regions of mice exposed to chronic intragastric administration of rotenone, a mouse model that mimics the spatiotemporal progression of PD-like pathology from the ENS to the SN as described by Braak's staging. Our results show that DKI, especially kurtosis, can detect the progression of pathology-associated changes throughout the CNS. Increases in mean kurtosis were first observed in the dorsal motor nucleus of the vagus (DMV) after 2 months of exposure to rotenone and before the loss of dopaminergic neurons in the SN occurred. Remarkably, we also show that limited exposure to rotenone for 2 months is enough to trigger the progression of the disease in the absence of the environmental toxin, thus suggesting that once the first pathological changes in one region appear, they can self-perpetuate and progress within the CNS. Overall, our results show that DKI can be a useful radiological marker for the early detection and monitoring of PD pathology progression in patients with the potential to improve the clinical diagnosis and the development of neuroprotective treatments.

Inter-Cohort Validation of SuStaIn Model for Alzheimer's Disease

Alzheimer’s disease (AD) is a neurodegenerative disorder which spans several years from preclinical manifestations to dementia. In recent years, interest in the application of machine learning (ML) algorithms to personalized medicine has grown considerably, and a major challenge that such models face is the transferability from the research settings to clinical practice. The objective of this work was to demonstrate the transferability of the Subtype and Stage Inference (SuStaIn) model from well-characterized research data set, employed as training set, to independent less-structured and heterogeneous test sets representative of the clinical setting. The training set was composed of MRI data of 1043 subjects from the Alzheimer’s disease Neuroimaging Initiative (ADNI), and the test set was composed of data from 767 subjects from OASIS, Pharma-Cog, and ViTA clinical datasets. Both sets included subjects covering the entire spectrum of AD, and for both sets volumes of relevant brain regions were derived from T1-3D MRI scans processed with Freesurfer v5.3 cross-sectional stream. In order to assess the predictive value of the model, subpopulations of subjects with stable mild cognitive impairment (MCI) and MCIs that progressed to AD dementia (pMCI) were identified in both sets. SuStaIn identified three disease subtypes, of which the most prevalent corresponded to the typical atrophy pattern of AD. The other SuStaIn subtypes exhibited similarities with the previously defined hippocampal sparing and limbic predominant atrophy patterns of AD. Subject subtyping proved to be consistent in time for all cohorts and the staging provided by the model was correlated with cognitive performance. Classification of subjects on the basis of a combination of SuStaIn subtype and stage, mini mental state examination and amyloid-β_1-42 cerebrospinal fluid concentration was proven to predict conversion from MCI to AD dementia on par with other novel statistical algorithms, with ROC curves that were not statistically different for the training and test sets and with area under curve respectively equal to 0.77 and 0.76. This study proves the transferability of a SuStaIn model for AD from research data to less-structured clinical cohorts, and indicates transferability to the clinical setting.

Promotion time cure rate model with a neural network estimated nonparametric component

Promotion time cure rate models (PCM) are often used to model the survival data with a cure fraction. Medical images or biomarkers derived from medical images can be the key predictors in survival models. However, incorporating images in the PCM is challenging using traditional nonparametric methods such as splines. We propose to use neural network to model the nonparametric or unstructured predictors' effect in the PCM context. Expectation-maximization algorithm with neural network for the M-step is used for parameter estimation. Asymptotic properties of the proposed estimates are derived. Simulation studies show good performance in terms of both prediction and estimation. We finally apply our methods to analyze the brain images from open access series of imaging studies data.

Effects of perinatal HIV-infection on the cortical thickness and subcortical gray matter volumes in young adulthood

ABSTRACT

Brain atrophy has been observed in perinatally HIV-infected patients (PHIV) despite initiation on combined antiretroviral treatment (cART), but neuroimaging studies are limited. We aimed to evaluate cortical thickness (CT) and subcortical gray matter (GM) volumes of PHIV youths with stable immunovirological situation and with a normal daily performance.A prospective cross-sectional study was conducted. A total of 25 PHIV patients on cART and 25 HIV-negative (HIV-) controls matched by age, sex, level of education, and socioeconomic status underwent a magnetic resonance imaging scan. CAT12 toolbox was used to extract CT values from T1w images using parcellations from Desikan-Killiany atlas (DK40). To measure regional brain volumes, native segmented images were parceled in regions of interest according to the Neuromorphometrics Atlas. Neuropsychological assessment and psychopathological symptoms were documented.Fifty participants were included (60% females, median age 20 years [interquartile range, IQR 19-23], 64% Whites). No differences regarding neuropsychological tests or psychopathological symptoms were found between groups (all P > .05). All participants presented an average performance in the Fluid Intelligence (FI) test (PHIV mean: -0.12, HIV- mean: 0.24), When comparing CT, PHIV-infected patients showed thinner cortices compared with their peers in fusiform gyrus (P = .000, P = .009), lateral-orbitofrontal gyrus (P = .006, P = .0024), and right parsobitalis gyrus (P = .047). Regarding subcortical GM volumes, PHIV patients showed lower right amygdala (P = .014) and left putamen (P = .016) volumes when compared with HIV- controls. Within the PHIV group, higher CD4 count was associated with higher volumes in right putamen (B = 0.00000038, P = .045). Moreover, increased age at cART initiation and lower nadir CD4 count was associated with larger volumes in left accumbens (B = 0.0000046, P = .033; B = -0.00000008, P = .045, respectively).PHIV patients showed thinner cortices of areas in temporal, orbito-frontal and occipital lobes and lower volumes of subcortical GM volumes when compared with the HIV- control group, suggesting cortical and subcortical brain alterations in otherwise neuroasymptomatic patients. Nevertheless, larger and longitudinal studies are required to determine the impact of HIV on brain structure in PHIV patients and to further identify risk and protective factors that could be implicated.

Neurological Complications of COVID-19: Underlying Mechanisms and Management

COVID-19 is a severe respiratory disease caused by the newly identified human coronavirus (HCoV) Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2). The virus was discovered in December 2019, and in March 2020, the disease was declared a global pandemic by the World Health Organization (WHO) due to a high number of cases. Although SARS-CoV-2 primarily affects the respiratory system, several studies have reported neurological complications in COVID-19 patients. Headache, dizziness, loss of taste and smell, encephalitis, encephalopathy, and cerebrovascular diseases are the most common neurological complications that are associated with COVID-19. In addition, seizures, neuromuscular junctions' disorders, and Guillain-Barré syndrome were reported as complications of COVID-19, as well as neurodegenerative and demyelinating disorders. However, the management of these conditions remains a challenge. In this review, we discuss the prevalence, pathogenesis, and mechanisms of these neurological sequelae that are secondary to SARS-CoV-2 infection. We aim to update neurologists and healthcare workers on the possible neurological complications associated with COVID-19 and the management of these disease conditions.

Motor Thalamic Deep Brain Stimulation Alters Cortical Activity and Shows Therapeutic Utility for Treatment of Parkinson's Disease Symptoms in a Rat Model

Deep brain stimulation (DBS) in Parkinson's disease (PD) alters neuronal function and network communication to improve motor symptoms. The subthalamic nucleus (STN) is the most common DBS target for PD, but some patients experience adverse effects on memory and cognition. Previously, we reported that DBS of the ventral anterior (VA) and ventrolateral (VL) nuclei of the thalamus and at the interface between the two (VA|VL), collectively VA-VL, relieved forelimb akinesia in the hemiparkinsonian 6-hydroxydopamine (6-OHDA) rat model. To determine the mechanism(s) underlying VA-VL DBS efficacy, we examined how motor cortical neurons respond to VA-VL DBS using single-unit recording electrodes in anesthetized 6-OHDA lesioned rats. VA-VL DBS increased spike frequencies of primary (M1) and secondary (M2) motor cortical pyramidal cells and M2, but not M1, interneurons. To explore the translational merits of VA-VL DBS, we compared the therapeutic window, rate of stimulation-induced dyskinesia onset, and effects on memory between VA-VL and STN DBS. VA-VL and STN DBS had comparable therapeutic windows, induced dyskinesia at similar rates in hemiparkinsonian rats, and adversely affected performance in the novel object recognition (NOR) test in cognitively normal and mildly impaired sham animals. Interestingly, a subset of sham rats with VA-VL implants showed severe cognitive deficits with DBS off. VA-VL DBS improved NOR test performance in these animals. We conclude that VA-VL DBS may exert its therapeutic effects by increasing pyramidal cell activity in the motor cortex and interneuron activity in the M2, with plausible potential to improve memory in PD.

Imaging Techniques in Alzheimer's Disease: A Review of Applications in Early Diagnosis and Longitudinal Monitoring

BACKGROUND

Alzheimer's disease (AD) is a progressive neurodegenerative disorder affecting many individuals worldwide with no effective treatment to date. AD is characterized by the formation of senile plaques and neurofibrillary tangles, followed by neurodegeneration, which leads to cognitive decline and eventually death.

INTRODUCTION

In AD, pathological changes occur many years before disease onset. Since disease-modifying therapies may be the most beneficial in the early stages of AD, biomarkers for the early diagnosis and longitudinal monitoring of disease progression are essential. Multiple imaging techniques with associated biomarkers are used to identify and monitor AD.

AIM

In this review, we discuss the contemporary early diagnosis and longitudinal monitoring of AD with imaging techniques regarding their diagnostic utility, benefits and limitations. Additionally, novel techniques, applications and biomarkers for AD research are assessed.

FINDINGS

Reduced hippocampal volume is a biomarker for neurodegeneration, but atrophy is not an AD-specific measure. Hypometabolism in temporoparietal regions is seen as a biomarker for AD. However, glucose uptake reflects astrocyte function rather than neuronal function. Amyloid-β (Aβ) is the earliest hallmark of AD and can be measured with positron emission tomography (PET), but Aβ accumulation stagnates as disease progresses. Therefore, Aβ may not be a suitable biomarker for monitoring disease progression. The measurement of tau accumulation with PET radiotracers exhibited promising results in both early diagnosis and longitudinal monitoring, but large-scale validation of these radiotracers is required. The implementation of new processing techniques, applications of other imaging techniques and novel biomarkers can contribute to understanding AD and finding a cure.

CONCLUSIONS

Several biomarkers are proposed for the early diagnosis and longitudinal monitoring of AD with imaging techniques, but all these biomarkers have their limitations regarding specificity, reliability and sensitivity. Future perspectives. Future research should focus on expanding the employment of imaging techniques and identifying novel biomarkers that reflect AD pathology in the earliest stages.

Articulatory network reorganization in Parkinson's disease as assessed by multimodal MRI and acoustic measures

INTRODUCTION

Hypokinetic dysarthria (HD) is common in Parkinson's disease (PD). Our objective was to evaluate articulatory networks and their reorganization due to PD pathology in individuals without overt speech impairment using a multimodal MRI protocol and acoustic analysis of speech.

METHODS

A total of 34 PD patients with no subjective HD complaints and 25 age-matched healthy controls (HC) underwent speech task recordings, structural MRI, and reading task-induced and resting-state fMRI. Grey matter probability maps, task-induced activations, and resting-state functional connectivity within the regions engaged in speech production (ROIs) were assessed and compared between groups. Correlation with acoustic parameters was also performed.

RESULTS

PD patients as compared Tto HC displayed temporal decreases in speech loudness which were related to BOLD signal increases in the right-sided regions of the dorsal language pathway/articulatory network. Among those regions, activation of the right anterior cingulate was increased in PD as compared to HC. We also found bilateral posterior superior temporal gyrus (STG) GM loss in PD as compared to HC that was strongly associated with diadochokinetic (DDK) irregularity in the PD group. Task-induced activations of the left STG were increased in PD as compared to HC and were related to the DDK rate control.

CONCLUSIONS

The results provide insight into the neural correlates of speech production control and distinct articulatory network reorganization in PD apparent already in patients without subjective speech impairment.

Morphological Abnormalities in the Basal Ganglia of Dystonia Patients

OBJECTIVE

The pathophysiology of dystonia is poorly understood. As opposed to secondary forms of dystonia, primary dystonia has long been believed to lack any neuroanatomical substrate. During trajectory planning for DBS, however, conspicuous T2-hyperinstensive signal alterations (SA) were registered within the target region, even in young patients, where ischemia is rare.

METHODS

Fifty MRIs of primary dystonia patients scheduled for DBS were analyzed. Total basal ganglia (BG) volumes, as well as proportionate SA volumes, were measured and compared to 50 age-matched control patients.

RESULTS

There was a 10-fold preponderance of percentaged SA within the globus pallidus (GP) in dystonia patients. The greatest disparity was in young patients <25 years. Also, total BG volume differences were observed with larger GP and markedly smaller putamen and caudate in the dystonia group.

CONCLUSIONS

BG morphology in primary dystonia differed from a control population. Volume reductions of the putamen and caudate may reflect functional degeneration, while volume increases of the GP may indicate overactivity. T2-hyperintensive SA in the GP of young primary dystonia patients, where microvascular lesions are highly unlikely, are striking. Their pathogenic role remains unclear.

Long-Term Respiratory and Neurological Sequelae of COVID-19

Since the initial reports of coronavirus disease 2019 (COVID-19) in China in late 2019, infections from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have spread rapidly, resulting in a global pandemic that has caused millions of deaths. Initially, the large number of infected people required the direction of global healthcare resources to provide supportive care for the acutely ill population in an attempt to reduce mortality. While clinical trials for safe and effective antiviral agents are ongoing, and vaccine development programs are being accelerated, long-term sequelae of SARS-CoV-2 infection have become increasingly recognized and concerning. Although the upper and lower respiratory tracts are the main sites of entry of SARS-CoV-2 into the body, resulting in COVID-19 pneumonia as the most common presentation, acute lung damage may be followed by pulmonary fibrosis and chronic impairment of lung function, with impaired quality of life. Also, increasing reports have shown that SARS-CoV-2 infection involves the central nervous system (CNS) and the peripheral nervous system (PNS) and directly or indirectly damages neurons, leading to long-term neurological sequelae. This review aims to provide an update on the mechanisms involved in the development of the long-term sequelae of SARS-CoV-2 infection in the 3 main areas of lung injury, neuronal injury, and neurodegenerative diseases, including Alzheimer disease, Parkinson disease, and multiple sclerosis, and highlights the need for patient monitoring following the acute stage of infection with SARS-CoV-2 to provide a rationale for the prevention, diagnosis, and management of these potential long-term sequelae.