SARS-CoV-2 is associated with changes in brain structure in UK Biobank

There is strong evidence of brain-related abnormalities in COVID-191,2,3,4,5,6,7,8,9,10,11,12,13. However, it remains unknown whether the impact of SARS-CoV-2 infection can be detected in milder cases, and whether this can reveal possible mechanisms contributing to brain pathology. Here we investigated brain changes in 785 participants of UK Biobank (aged 51–81 years) who were imaged twice using magnetic resonance imaging, including 401 cases who tested positive for infection with SARS-CoV-2 between their two scans—with 141 days on average separating their diagnosis and the second scan—as well as 384 controls. The availability of pre-infection imaging data reduces the likelihood of pre-existing risk factors being misinterpreted as disease effects. We identified significant longitudinal effects when comparing the two groups, including (1) a greater reduction in grey matter thickness and tissue contrast in the orbitofrontal cortex and parahippocampal gyrus; (2) greater changes in markers of tissue damage in regions that are functionally connected to the primary olfactory cortex; and (3) a greater reduction in global brain size in the SARS-CoV-2 cases. The participants who were infected with SARS-CoV-2 also showed on average a greater cognitive decline between the two time points. Importantly, these imaging and cognitive longitudinal effects were still observed after excluding the 15 patients who had been hospitalised. These mainly limbic brain imaging results may be the in vivo hallmarks of a degenerative spread of the disease through olfactory pathways, of neuroinflammatory events, or of the loss of sensory input due to anosmia. Whether this deleterious effect can be partially reversed, or whether these effects will persist in the long term, remains to be investigated with additional follow-up

Denoising Diffusion MRI: Considerations and implications for analysis

Development of diffusion MRI (dMRI) denoising approaches has experienced considerable growth over the last years. As noise can inherently reduce accuracy and precision in measurements, its effects have been well characterised both in terms of uncertainty increase in dMRI-derived features and in terms of biases caused by the noise floor, the smallest measurable signal given the noise level. However, gaps in our knowledge still exist in objectively characterising dMRI denoising approaches in terms of both of these effects and assessing their efficacy. In this work, we reconsider what a denoising method should and should not do and we accordingly define criteria to characterise the performance. We propose a comprehensive set of evaluations, including i) benefits in improving signal quality and reducing noise variance, ii) gains in reducing biases and the noise floor and improving, iii) preservation of spatial resolution, iv) agreement of denoised data against a gold standard, v) gains in downstream parameter estimation (precision and accuracy), vi) efficacy in enabling noise-prone applications, such as ultra-high-resolution imaging. We further provide newly acquired complex datasets (magnitude and phase) with multiple repeats that sample different SNR regimes to highlight performance differences under different scenarios. Without loss of generality, we subsequently apply a number of exemplar patch-based denoising algorithms to these datasets, including Non-Local Means, Marchenko-Pastur PCA (MPPCA) in the magnitude and complex domain and NORDIC, and compare them with respect to the above criteria and against a gold standard complex average of multiple repeats. We demonstrate that all tested denoising approaches reduce noise-related variance, but not always biases from the elevated noise floor. They all induce a spatial resolution penalty, but its extent can vary depending on the method and the implementation. Some denoising approaches agree with the gold standard more than others and we demonstrate challenges in even defining such a standard. Overall, we show that dMRI denoising performed in the complex domain is advantageous to magnitude domain denoising with respect to all the above criteria

The minimal preprocessing pipelines for the Human Connectome Project

The Human Connectome Project (HCP) faces the challenging task of bringing multiple magnetic resonance imaging (MRI) modalities together in a common automated preprocessing framework across a large cohort of subjects. The MRI data acquired by the HCP differ in many ways from data acquired on conventional 3 Tesla scanners and often require newly developed preprocessing methods. We describe the minimal preprocessing pipelines for structural, functional, and diffusion MRI that were developed by the HCP to accomplish many low level tasks, including spatial artifact/distortion removal, surface generation, cross-modal registration, and alignment to standard space. These pipelines are specially designed to capitalize on the high quality data offered by the HCP. The final standard space makes use of a recently introduced CIFTI file format and the associated grayordinate spatial coordinate system. This allows for combined cortical surface and subcortical volume analyses while reducing the storage and processing requirements for high spatial and temporal resolution data. Here, we provide the minimum image acquisition requirements for the HCP minimal preprocessing pipelines and additional advice for investigators interested in replicating the HCP's acquisition protocols or using these pipelines. Finally, we discuss some potential future improvements to the pipelines

Social connections predict brain structure in a multidimensional free-ranging primate society

Reproduction and survival in most primate species reflects management of both competitive and cooperative relationships. Here, we investigated the links between neuroanatomy and sociality in free-ranging rhesus macaques. In adults, the number of social partners predicted the volume of the mid–superior temporal sulcus and ventral-dysgranular insula, implicated in social decision-making and empathy, respectively. We found no link between brain structure and other key social variables such as social status or indirect connectedness in adults, nor between maternal social networks or status and dependent infant brain structure. Our findings demonstrate that the size of specific brain structures varies with the number of direct affiliative social connections and suggest that this relationship may arise during development. These results reinforce proposed links between social network size, biological success, and the expansion of specific brain circuits

Multimodal population brain imaging in the UK Biobank prospective epidemiological study

Medical imaging has enormous potential for early disease prediction, but is impeded by the difficulty and expense of acquiring data sets before symptom onset. UK Biobank aims to address this problem directly by acquiring high-quality, consistently acquired imaging data from 100,000 predominantly healthy participants, with health outcomes being tracked over the coming decades. The brain imaging includes structural, diffusion and functional modalities. Along with body and cardiac imaging, genetics, lifestyle measures, biological phenotyping and health records, this imaging is expected to enable discovery of imaging markers of a broad range of diseases at their earliest stages, as well as provide unique insight into disease mechanisms. We describe UK Biobank brain imaging and present results derived from the first 5,000 participants' data release. Although this covers just 5% of the ultimate cohort, it has already yielded a rich range of associations between brain imaging and other measures collected by UK Biobank

Characterization of the thermal and photoinduced reactions of photochromic spiropyrans in aqueous solution

Six water-soluble spiropyran derivatives have been characterized with respect to the thermal and photoinduced reactions over a broad pH-interval. A comprehensive kinetic model was formulated including the spiro- and the merocyanine isomers, the respective protonated forms, and the hydrolysis products. The experimental studies on the hydrolysis reaction mechanism were supplemented by calculations using quantum mechanical (QM) models employing density functional theory. The results show that (1) the substitution pattern dramatically influences the pKa-values of the protonated forms as well as the rates of the thermal isomerization reactions, (2) water is the nucleophile in the hydrolysis reaction around neutral pH, (3) the phenolate oxygen of the merocyanine form plays a key role in the hydrolysis reaction. Hence, the nonprotonated merocyanine isomer is susceptible to hydrolysis, whereas the corresponding protonated form is stable toward hydrolytic degradation

Asthmatics Exhibit Altered Oxylipin Profiles Compared to Healthy Individuals after Subway Air Exposure

Asthma is a chronic inflammatory lung disease that causes significant morbidity and mortality worldwide. Air pollutants such as particulate matter (PM) and oxidants are important factors in causing exacerbations in asthmatics, and the source and composition of pollutants greatly affects pathological implications.This randomized crossover study investigated responses of the respiratory system to Stockholm subway air in asthmatics and healthy individuals. Eicosanoids and other oxylipins were quantified in the distal lung to provide a measure of shifts in lipid mediators in association with exposure to subway air relative to ambient air.Sixty-four oxylipins representing the cyclooxygenase (COX), lipoxygenase (LOX) and cytochrome P450 (CYP) metabolic pathways were screened using liquid chromatography-tandem mass spectrometry (LC-MS/MS) of bronchoalveolar lavage (BAL)-fluid. Validations through immunocytochemistry staining of BAL-cells were performed for 15-LOX-1, COX-1, COX-2 and peroxisome proliferator-activated receptor gamma (PPARγ). Multivariate statistics were employed to interrogate acquired oxylipin and immunocytochemistry data in combination with patient clinical information.Asthmatics and healthy individuals exhibited divergent oxylipin profiles following exposure to ambient and subway air. Significant changes were observed in 8 metabolites of linoleic- and α-linolenic acid synthesized via the 15-LOX pathway, and of the COX product prostaglandin E(2) (PGE(2)). Oxylipin levels were increased in healthy individuals following exposure to subway air, whereas asthmatics evidenced decreases or no change.Several of the altered oxylipins have known or suspected bronchoprotective or anti-inflammatory effects, suggesting a possible reduced anti-inflammatory response in asthmatics following exposure to subway air. These observations may have ramifications for sensitive subpopulations in urban areas

The Human Connectome Project's neuroimaging approach

Noninvasive human neuroimaging has yielded many discoveries about the brain. Numerous methodological advances have also occurred, though inertia has slowed their adoption. This paper presents an integrated approach to data acquisition, analysis and sharing that builds upon recent advances, particularly from the Human Connectome Project (HCP). The 'HCP-style' paradigm has seven core tenets: (i) collect multimodal imaging data from many subjects; (ii) acquire data at high spatial and temporal resolution; (iii) preprocess data to minimize distortions, blurring and temporal artifacts; (iv) represent data using the natural geometry of cortical and subcortical structures; (v) accurately align corresponding brain areas across subjects and studies; (vi) analyze data using neurobiologically accurate brain parcellations; and (vii) share published data via user-friendly databases. We illustrate the HCP-style paradigm using existing HCP data sets and provide guidance for future research. Widespread adoption of this paradigm should accelerate progress in understanding the brain in health and disease

<em>Enterococcus faecalis</em> Infection Causes Inflammation, Intracellular Oxphos-Independent ROS Production, and DNA Damage in Human Gastric Cancer Cells

Background: Achlorhydria caused by e.g. atrophic gastritis allows for bacterial overgrowth, which induces chronic inflammation and damage to the mucosal cells of infected individuals driving gastric malignancies and cancer. Enterococcus faecalis (E. faecalis) can colonize achlohydric stomachs and we therefore wanted to study the impact of E. faecalis infection on inflammatory response, reactive oxygen species (ROS) formation, mitochondrial respiration, and mitochondrial genetic stability in gastric mucosal cells. Methods: To separate the changes induced by bacteria from those of the inflammatory cells we established an in vitro E. faecalis infection model system using the gastric carcinoma cell line MKN74. Total ROS and superoxide was measured by fluorescence microscopy. Cellular oxygen consumption was characterized non-invasively using XF24 microplate based respirometry. Gene expression was examined by microarray, and response pathways were identified by Gene Set Analysis (GSA). Selected gene transcripts were verified by quantitative real-time polymerase chain reaction (qRT-PCR). Mitochondrial mutations were determined by sequencing. Results: Infection of MKN74 cells with E. faecalis induced intracellular ROS production through a pathway independent of oxidative phosphorylation (oxphos). Furthermore, E. faecalis infection induced mitochondrial DNA instability. Following infection, genes coding for inflammatory response proteins were transcriptionally up-regulated while DNA damage repair and cell cycle control genes were down-regulated. Cell growth slowed down when infected with viable E. faecalis and responded in a dose dependent manner to E. faecalis lysate. Conclusions: Infection by E. faecalis induced an oxphos-independent intracellular ROS response and damaged the mitochondrial genome in gastric cell culture. Finally the bacteria induced an NF-kappa B inflammatory response as well as impaired DNA damage response and cell cycle control gene expression

Heritability of fractional anisotropy in human white matter: a comparison of Human Connectome Project and ENIGMA-DTI data

The degree to which genetic factors influence brain connectivity is beginning to be understood. Large-scale efforts are underway to map the profile of genetic effects in various brain regions. The NIH-funded Human Connectome Project (HCP) is providing data valuable for analyzing the degree of genetic influence underlying brain connectivity revealed by state-of-the-art neuroimaging methods. We calculated the heritability of the fractional anisotropy (FA) measure derived from diffusion tensor imaging (DTI) reconstruction in 481 HCP subjects (194/287 M/F) consisting of 57/60 pairs of mono- and dizygotic twins, and 246 siblings. FA measurements were derived using (Enhancing NeuroImaging Genetics through Meta-Analysis) ENIGMA DTI protocols and heritability estimates were calculated using the SOLAR-Eclipse imaging genetic analysis package. We compared heritability estimates derived from HCP data to those publicly available through the ENIGMA-DTI consortium, which were pooled together from five-family based studies across the US, Europe, and Australia. FA measurements from the HCP cohort for eleven major white matter tracts were highly heritable (h2 = 0.53–0.90, p < 10− 5), and were significantly correlated with the joint-analytical estimates from the ENIGMA cohort on the tract and voxel-wise levels. The similarity in regional heritability suggests that the additive genetic contribution to white matter microstructure is consistent across populations and imaging acquisition parameters. It also suggests that the overarching genetic influence provides an opportunity to define a common genetic search space for future gene-discovery studies. Uniquely, the measurements of additive genetic contribution performed in this study can be repeated using online genetic analysis tools provided by the HCP ConnectomeDB web application