Ratai, Eva‐Maria

Introduction Neurological post-acute sequelae of COVID-19 (neuroPASC) are associated with persistent cognitive dysfunction and quality-of-life decline. We aimed to identify clinical, behavioral and sociodemographic factors associated with neuroPASC symptom burden two years after COVID-19 among individuals without prior neurological disease. Methods In this prospective, observational study, individuals with neuroPASC ( n = 102) and controls without symptomatic COVID-19 ( n = 74), all without prior neurological, psychiatric, or post-viral conditions, were enrolled between February 2022 and June 2024 across five academic sites. An unsupervised algorithm identified clusters with differing self-reported neurological symptom burden within the neuroPASC group. Functional differences between clusters were evaluated using quality-of-life, neurological and cognitive evaluations. Demographics, behavioral history, comorbidities, and blood biomarkers were compared across clusters and controls. Multivariable logistic regression assessed predictors of neuroPASC severity, including demographics, body-mass-index, Charlson Comorbidity Index, Framingham Risk Score, pre-existing endocrine/metabolic and/or gastrointestinal/hepatobiliary conditions, COVID-19 vaccination prior to infection, hospitalization during acute infection, and cumulative alcohol use. Results Two clusters emerged based on neurological symptom burden, labeled “high-burden” and “low-burden” neuroPASC, reflecting differences in the number and frequency of symptoms. Both clusters had deficits in quality-of-life and cognitive function compared to controls, with greater impairment in high-burden than low-burden neuroPASC. The clusters did not differ by sex, education, tobacco and cannabis use, blood pressure, body-mass-index, HbA1C, days since infection, hospitalization during COVID-19, pre-COVID vaccination rate, antibody-positivity, inflammation, and neurodegeneration biomarkers. The high-burden cluster was older and exhibited higher comorbidity burden and greater cumulative alcohol use compared with the low-burden cluster and controls. Pre-existing endocrine/metabolic and gastrointestinal/hepatobiliary conditions were more common in high-burden (63%) than in low-burden neuroPASC (35%). After adjusting for clinical and demographic factors, these pre-existing conditions remained the only independent predictor of severity, conferring a 3.5-fold increase in the odds of high-burden versus low-burden neuroPASC. Discussion Older age, higher comorbidity burden, greater cumulative alcohol use, and endocrine/metabolic and gastrointestinal conditions, rather than acute COVID-19 severity, were observed in the high-burden neuroPASC cluster. After multivariable adjustment, only pre-existing endocrine/metabolic and/or gastrointestinal/hepatobiliary conditions remained independently associated with high-burden neuroPASC, conferring a 3.5-fold increase in odds and highlighting the need for targeted post-infection monitoring in at-risk patients.

Abstract Age-related cognitive decline results from complex interactions between neuroendocrine and neurometabolic processes that undergo lifelong degredation, yet the mechanisms underlying these interactions remain poorly understood. This study examined the effects of diabetes and sex on functional brain networks across aging through analysis of two large cohorts (N=1,621 total) using both 3T and 7T functional MRI, complemented by spatial transcriptomic data from over 14,000 genes from six post-mortem brains. Four networks— cingulo-opercular, default mode, salience, and lateral somatomotor—exhibited significant functional decline in both individuals with diabetes and independently in males. Gene expression analysis of vulnerable networks revealed significant overexpression of insulin-dependent glucose transporters, dopaminergic and GABAergic synaptic genes, and VEGFA-VEGFR2 pathway components. These findings suggest functionally-specific circuit vulnerability to metabolic and hormonal dysregulation, potentially offering targets for early intervention before irreversible neurodegeneration occurs.

Understanding the key drivers of brain aging is essential for effective prevention and treatment of neurodegenerative diseases. Here, we integrate human brain and physiological data to investigate underlying mechanisms. Functional MRI analyses across four large datasets (totaling 19,300 participants) show that brain networks not only destabilize throughout the lifetime but do so along a nonlinear trajectory, with consistent temporal “landmarks” of brain aging starting in midlife (40s). Comparison of metabolic, vascular, and inflammatory biomarkers implicate dysregulated glucose homeostasis as the driver mechanism for these transitions. Correlation between the brain’s regionally heterogeneous patterns of aging and gene expression further supports these findings, selectively implicating GLUT4 (insulin-dependent glucose transporter) and APOE (lipid transport protein). Notably, MCT2 (a neuronal, but not glial, ketone transporter) emerges as a potential counteracting factor by facilitating neurons’ energy uptake independently of insulin. Consistent with these results, an interventional study of 101 participants shows that ketones exhibit robust effects in restabilizing brain networks, maximized from ages 40 to 60, suggesting a midlife “critical window” for early metabolic intervention.

PurposeAdvanced MRS protocols improve data quality and reproducibility relative to vendor‐provided protocols; however, they are challenging to incorporate into the clinical workflow and require local MRS expertise for successful implementation. Here, we developed an automated advanced MRS acquisition protocol at 3T to facilitate acquisition of high‐quality spectroscopic data without local MRS expertise.MethodsFirst, a B0 shimming protocol was selected for automation by comparing 3 widely used B0 algorithms (2 vendor protocols and FAST(EST)MAP). Next, voxel‐based B0 and B1 calibrations were incorporated into the consensus‐recommended semi‐LASER sequence and combined with an automated VOI prescription tool, a recently developed method for automated voxel prescription. The efficiency of collecting single‐voxel data from a clinical cohort (N = 40) with the automated protocol (calibration time and fraction of usable datasets) was compared with the nonautomated semi‐LASER protocol (N = 35) whereby all prescan calibrations were executed manually in the academic hospital setting with rotating MR technologists in the neuroradiology unit.ResultsA multi‐iteration FAST(EST)MAP protocol resulted in narrower water linewidths than vendor’s B0 shim protocols for data acquired from 6 brain locations (p < 1e‐5) and was selected for automation. The automated B0 and B1 calibrations resulted in a time saving of ~4.5 minutes per voxel relative to the same advanced protocol executed manually. All spectra acquired with the automated protocol were usable, whereas only 86% of those collected with the manual protocol were usable and spectral quality was more variable.ConclusionThe plug‐and‐play advanced MRS protocol allows automated acquisition of high‐quality MRS data with high success rate and consistency on a clinical 3T platform.

Abstract The semi‐adiabatic localization by adiabatic selective refocusing (sLASER) sequence provides single‐shot full intensity signal with clean localization and minimal chemical shift displacement error and was recommended by the international MRS Consensus Group as the preferred localization sequence at high‐ and ultra‐high fields. Across‐vendor standardization of the sLASER sequence at 3 tesla has been challenging due to the B 1 requirements of the adiabatic inversion pulses and maximum B 1 limitations on some platforms. The aims of this study were to design a short‐echo sLASER sequence that can be executed within a B 1 limit of 15 μT by taking advantage of gradient‐modulated RF pulses, to implement it on three major platforms and to evaluate the between‐vendor reproducibility of its perfomance with phantoms and in vivo. In addition, voxel‐based first and second order B 0 shimming and voxel‐based B 1 adjustments of RF pulses were implemented on all platforms. Amongst the gradient‐modulated pulses considered (GOIA, FOCI and BASSI), GOIA‐WURST was identified as the optimal refocusing pulse that provides good voxel selection within a maximum B 1 of 15 μT based on localization efficiency, contamination error and ripple artifacts of the inversion profile. An sLASER sequence (30 ms echo time) that incorporates VAPOR water suppression and 3D outer volume suppression was implemented with identical parameters (RF pulse type and duration, spoiler gradients and inter‐pulse delays) on GE, Philips and Siemens and generated identical spectra on the GE ‘Braino’ phantom between vendors. High‐quality spectra were consistently obtained in multiple regions (cerebellar white matter, hippocampus, pons, posterior cingulate cortex and putamen) in the human brain across vendors (5 subjects scanned per vendor per region; mean signal‐to‐noise ratio > 33; mean water linewidth between 6.5 Hz to 11.4 Hz). The harmonized sLASER protocol is expected to produce high reproducibility of MRS across sites thereby allowing large multi‐site studies with clinical cohorts.

Proton MRS (1H MRS) provides noninvasive, quantitative metabolite profiles of tissue and has been shown to aid the clinical management of several brain diseases. Although most modern clinical MR scanners support MRS capabilities, routine use is largely restricted to specialized centers with good access to MR research support. Widespread adoption has been slow for several reasons, and technical challenges toward obtaining reliable good‐quality results have been identified as a contributing factor. Considerable progress has been made by the research community to address many of these challenges, and in this paper a consensus is presented on deficiencies in widely available MRS methodology and validated improvements that are currently in routine use at several clinical research institutions. In particular, the localization error for the PRESS localization sequence was found to be unacceptably high at 3 T, and use of the semi‐adiabatic localization by adiabatic selective refocusing sequence is a recommended solution. Incorporation of simulated metabolite basis sets into analysis routines is recommended for reliably capturing the full spectral detail available from short TE acquisitions. In addition, the importance of achieving a highly homogenous static magnetic field (B0) in the acquisition region is emphasized, and the limitations of current methods and hardware are discussed. Most recommendations require only software improvements, greatly enhancing the capabilities of clinical MRS on existing hardware. Implementation of these recommendations should strengthen current clinical applications and advance progress toward developing and validating new MRS biomarkers for clinical use.