Systemic and central nervous system neuroinflammatory signatures of neuropsychiatric symptoms and related cognitive decline in older people

BACKGROUND Neuroinflammation may contribute to psychiatric symptoms in older people, in particular in the context of Alzheimer's disease (AD). We sought to identify systemic and central nervous system (CNS) inflammatory alterations associated with neuropsychiatric symptoms (NPS); and to investigate their relationships with AD pathology and clinical disease progression. METHODS We quantified a panel of 38 neuroinflammation and vascular injury markers in paired serum and cerebrospinal fluid (CSF) samples in a cohort of cognitively normal and impaired older subjects. We performed neuropsychiatric and cognitive evaluations and measured CSF biomarkers of AD pathology. Multivariate analysis determined serum and CSF neuroinflammatory alterations associated with NPS, considering cognitive status, AD pathology, and cognitive decline at follow-up visits. RESULTS NPS were associated with distinct inflammatory profiles in serum, involving eotaxin-3, interleukin (IL)-6 and C-reactive protein (CRP); and in CSF, including soluble intracellular cell adhesion molecule-1 (sICAM-1), IL-8, 10-kDa interferon-γ-induced protein, and CRP. AD pathology interacted with CSF sICAM-1 in association with NPS. Presenting NPS was associated with subsequent cognitive decline which was mediated by CSF sICAM-1. CONCLUSIONS Distinct systemic and CNS inflammatory processes are involved in the pathophysiology of NPS in older people. Neuroinflammation may explain the link between NPS and more rapid clinical disease progression

Cerebrospinal Fluid Cortisol and Dehydroepiandrosterone Sulfate, Alzheimer's Disease Pathology, and Cognitive Decline

INTRODUCTION Elevated cortisol levels have been reported in Alzheimer's disease (AD) and may accelerate the development of brain pathology and cognitive decline. Dehydroepiandrosterone sulfate (DHEAS) has anti-glucocorticoid effects and it may be involved in the AD pathophysiology. OBJECTIVES To investigate associations of cerebrospinal fluid (CSF) cortisol and DHEAS levels with (1) cognitive performance at baseline; (2) CSF biomarkers of amyloid pathology (as assessed by CSF Aβ levels), neuronal injury (as assessed by CSF tau), and tau hyperphosphorylation (as assessed by CSF p-tau); (3) regional brain volumes; and (4) clinical disease progression. MATERIALS AND METHODS Individuals between 49 and 88 years (n = 145) with mild cognitive impairment or dementia or with normal cognition were included. Clinical scores, AD biomarkers, brain MRI volumetry along with CSF cortisol and DHEAS were obtained at baseline. Cognitive and functional performance was re-assessed at 18 and 36 months from baseline. We also assessed the following covariates: apolipoprotein E (APOE) genotype, BMI, and education. We used linear regression and mixed models to address associations of interest. RESULTS Higher CSF cortisol was associated with poorer global cognitive performance and higher disease severity at baseline. Cortisol and cortisol/DHEAS ratio were positively associated with tau and p-tau CSF levels, and negatively associated with the amygdala and insula volumes at baseline. Higher CSF cortisol predicted more pronounced cognitive decline and clinical disease progression over 36 months. Higher CSF DHEAS predicted more pronounced disease progression over 36 months. CONCLUSION Increased cortisol in the CNS is associated with tau pathology and neurodegeneration, and with decreased insula and amygdala volume. Both CSF cortisol and DHEAS levels predict faster clinical disease progression. These results have implications for the identification of patients at risk of rapid decline as well as for the development of interventions targeting both neurodegeneration and clinical manifestations of AD

Prospective head motion correction using FID-guided on-demand image navigators

PURPOSE: We suggest a motion correction concept that employs free-induction-decay (FID) navigator signals to continuously monitor motion and to guide the acquisition of image navigators for prospective motion correction following motion detection. METHODS: Motion causes out-of-range signal changes in FID time series that, and in this approach, initiate the acquisition of an image navigator. Co-registration of the image navigator to a reference provides rigid-body-motion parameters to facilitate prospective motion correction. Both FID and image navigator are integrated into a prototype magnetization-prepared rapid gradient-echo (MPRAGE) sequence. The performance of the method is investigated using image quality metrics and the consistency of brain volume measurements. RESULTS: Ten healthy subjects were scanned (a) while performing head movements (nodding, shaking, and moving in z-direction) and (b) to assess the co-registration performance. Mean absolute errors of 0.27 +/- 0.38 mm and 0.19 +/- 0.24 degrees for translation and rotation parameters were measured. Image quality was qualitatively improved after correction. Significant improvements were observed in automated image quality measures and for most quantitative brain volume computations after correction. CONCLUSION: The presented method provides high sensitivity to detect head motion while minimizing the time invested in acquiring navigator images. Limits of this implementation arise from temporal resolution to detect motion, false-positive alarms, and registration accuracy

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P < 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Toward Reliable MR-Based Brain Structure Morphometry:Importance of Rigorous Quality Control

Dementing neurodegenerative disorders have more and more prominent public health implications with the most frequent cause being the currently non reversible Alzheimer's Disease (AD). However, over the past 15 years, an abundant literature has demonstrated the particular value of structural MRI from which brain morphological changes can be detected using automated volumetry and morphometry. These techniques offer promise to diagnose AD in early potentially-reversible stages as regional atrophy is currently "the" structural hallmark. Nevertheless, an essential question arises: to what extent are these quantitative measures dependent upon image quality? MRI quality can be mainly affected by machine-specific or patient-related artifacts, with motion being the most significant source of degradations. As we are currently not aware of any technique that reliably captures and corrects patient motion particularly for long high-resolution anatomical scans, rigorous quality assessment is hence of great importance to reliably derive qualitative or quantitative diagnostic information and consists in the first challenge addressed in this thesis. We developed a fully-automated method to classify the image quality based on a single MR image. Quality measures are derived by analyzing the air background of magnitude image and are capable of detecting image degradation from several sources, including bulk motion, residual magnetization from incomplete spoiling, blurring and ghosting. The method has been validated on 1670 multi-slice 2D, 3D T1- T2- PD- weighted 1.5T and 3T head scans acquired on Siemens and GE scanners operating with various software and hardware combinations. Results are compared against qualitative grades assigned by the Alzheimer's Disease Neuroimaging Initiative (ADNI) quality control center (taken as the reference standard). The derived quality indices are independent of the MR system used and agree with the reference standard with sensitivity and specificity higher than 90 %. With acceptable computational performance (less than 10 seconds), we incorporated our algorithm in the Siemens scanner software for routine clinical use. As for many other domains, quality criterion does not exhibit all-or-none properties (i.e., a unique quality cutoff value cannot discriminate high- versus low-quality scans) but is modulated by two main aspects addressed in this thesis: acquisition parameters (what kind of image?) and application (what for?). On the one hand, depending on acquisition parameters, more or less strong signal in the object is generated inducing more or less visible artifacts. Therefore, our quality criterion has to be adjusted accordingly. On the other hand, it appears quite natural that different quality criteria are required for algorithms segmenting global gray matter contrary to small brain structure such as hippocampus. Hence comes the second challenge addressed in this thesis: developing models that allow customizing quality criterion according to the acquisition parameters and the required performance of a target application. Taking up the first part of such challenge, we investigated certain acquisition parameters effects (i.e., echo time, bandwidth, signal suppression, field strength) and proposed an exploratory model with reasonable predictive performance (86.6 % sensitivity 92 % specificity). In order to customize quality cutoff levels according to the required performance of a target application, we developed a framework based on motion simulations. The idea is to progressively and realistically corrupt an image with motion and analyze the influence of such degradations (i.e., measured by means of our quality assessment technique) on the accuracy of a brain morphometry algorithm. To be faithful to the challenging research context of early diagnosis of AD, we targeted the automated morphometry of gray matter (GM) tissue (i.e., important imaging-based marker of pathological atrophy). Our framework reveals that 2 % error on the global volume of GM can be induced by a 1 mm patient motion halfway through the acquisition (critical low-frequency sampling of rectilinear k-space). However, this small movement is reliably caught by our quality index whose variation can be further characterized as an exponential function of the error. This model thus allows determining whether an image is of sufficient quality to warrant further quantitative analysis. In conclusion, this thesis underscores the importance of a rigorous quality assessment of MR images to support high-quality outputs of quantitative morphometry tools, ultimately increasing probability for higher diagnostic accuracy. Overall, we envision that such quality assessment could greatly improve clinical workflow through its ability to rule-out the need for a repeat scan while the patient is still in the magnet bore. Just as importantly, it would be an important step forward for incorporating morphometry analysis into regular brain-imaging protocols and thus, further exploit the clinical potential of MRI

Interrelation between cardiac and brain small-vessel disease: a pilot quantitative PET and MRI study

Abstract Background Small-vessel disease (SVD) plays a crucial role in cardiac and brain ischemia, but little is known about potential interrelation between both. We retrospectively evaluated 370 patients, aiming at assessing the interrelation between cardiac and brain SVD by using quantitative 82Rb cardiac PET/CT and brain MRI. Results In our population of 370 patients, 176 had normal myocardial perfusion, 38 had pure cardiac SVD and 156 had obstructive coronary artery disease. All underwent both a cardiac 82Rb PET/CT and a brain 1.5T or 3T MRI. Left-ventricle myocardial blood flow (LV-MBF) and flow reserve (LV-MFR) were recorded from 82Rb PET/CT, while Fazekas score, white matter lesion (WMab) volume, deep gray matter lesion (GMab) volume, and brain morphometry (for z-score calculation) using the MorphoBox research application were derived from MRI. Groups were compared with Kruskal–Wallis test, and the potential interrelation between heart and brain SVD markers was assessed using Pearson’s correlation coefficient. Patients with cardiac SVD had lower stress LV-MBF and MFR (P  0.45). In patients with cardiac SVD only, higher rest LV-MBF was associated with a lower left-putamen (rho = − 0.62, P = 0.033), right-thalamus (rho = 0.64, P = 0.026), and right-pallidum (rho = 0.60, P = 0.039) z-scores and with a higher GMab volume. Lower stress LV-MBF was associated with lower left-caudate z-score (rho = 0.69, P = 0.014), while lower LV-MFR was associated with lower left (rho = 0.75, P = 0.005)- and right (rho = 0.59, P = 0.045)-putamen z-scores, as well as higher right-thalamus GMab volume (rho = − 0.72, P = 0.009). Conclusion Significant interrelations between cardiac and cerebral SVD markers were found, especially regarding deep gray matter alterations, which supports the hypothesis of SVD as a systemic disease

Normative volumes and relaxation times at 3T during brain development.

While research has unveiled and quantified brain markers of abnormal neurodevelopment, clinicians still work with qualitative metrics for MRI brain investigation. The purpose of the current article is to bridge the knowledge gap between case-control cohort studies and individual patient care. Here, we provide a unique dataset of seventy-three 3-to-17 years-old healthy subjects acquired with a 6-minute MRI protocol encompassing T1 and T2 relaxation quantitative sequence that can be readily implemented in the clinical setting; MP2RAGE for T1 mapping and the prototype sequence GRAPPATINI for T2 mapping. White matter and grey matter volumes were automatically quantified. We further provide normative developmental curves based on these two imaging sequences; T1, T2 and volume normative ranges with respect to age were computed, for each ROI of a pediatric brain atlas. This open-source dataset provides normative values allowing to position individual patients acquired with the same protocol on the brain maturation curve and as such provides potentially useful quantitative biomarkers facilitating precise and personalized care

An Atypical Case of Head Tremor and Extensive White Matter in an Adult Female Caused by 3-Hydroxy-3-methylglutaryl-CoA Lyase Deficiency

3-Hydroxy-3-methylglutaryl-CoA (HMG-CoA) Lyase deficiency (HMGLD) (OMIM 246450) is an autosomal recessive genetic disorder caused by homozygous or compound heterozygous variants in the HMGCL gene located on 1p36.11. Clinically, this disorder is characterized by a life-threatening metabolic intoxication with a presentation including severe hypoglycemia without ketosis, metabolic acidosis, hyper-ammoniemia, hepatomegaly and a coma. HMGLD clinical onset is within the first few months of life after a symptomatic free period. In nonacute periods, the treatment is based on a protein- and fat-restricted diet. L-carnitine supplementation is recommended. A late onset presentation has been described in very few cases, and only two adult cases have been reported. The present work aims to describe an incidental discovery of an HMGLD case in a 54-year-old patient and reports a comprehensive review of clinical and biological features in adult patients to raise awareness about the late-onset presentation of this disease