Reliability of multi-site UK Biobank MRI brain phenotypes for the assessment of neuropsychiatric complications of SARS-CoV-2 infection: The COVID-CNS travelling heads study.

Funder: National Institute for Health Research (NIHR)INTRODUCTION: Magnetic resonance imaging (MRI) of the brain could be a key diagnostic and research tool for understanding the neuropsychiatric complications of COVID-19. For maximum impact, multi-modal MRI protocols will be needed to measure the effects of SARS-CoV-2 infection on the brain by diverse potentially pathogenic mechanisms, and with high reliability across multiple sites and scanner manufacturers. Here we describe the development of such a protocol, based upon the UK Biobank, and its validation with a travelling heads study. A multi-modal brain MRI protocol comprising sequences for T1-weighted MRI, T2-FLAIR, diffusion MRI (dMRI), resting-state functional MRI (fMRI), susceptibility-weighted imaging (swMRI), and arterial spin labelling (ASL), was defined in close approximation to prior UK Biobank (UKB) and C-MORE protocols for Siemens 3T systems. We iteratively defined a comparable set of sequences for General Electric (GE) 3T systems. To assess multi-site feasibility and between-site variability of this protocol, N = 8 healthy participants were each scanned at 4 UK sites: 3 using Siemens PRISMA scanners (Cambridge, Liverpool, Oxford) and 1 using a GE scanner (King's College London). Over 2,000 Imaging Derived Phenotypes (IDPs), measuring both data quality and regional image properties of interest, were automatically estimated by customised UKB image processing pipelines (S2 File). Components of variance and intra-class correlations (ICCs) were estimated for each IDP by linear mixed effects models and benchmarked by comparison to repeated measurements of the same IDPs from UKB participants. Intra-class correlations for many IDPs indicated good-to-excellent between-site reliability. Considering only data from the Siemens sites, between-site reliability generally matched the high levels of test-retest reliability of the same IDPs estimated in repeated, within-site, within-subject scans from UK Biobank. Inclusion of the GE site resulted in good-to-excellent reliability for many IDPs, although there were significant between-site differences in mean and scaling, and reduced ICCs, for some classes of IDP, especially T1 contrast and some dMRI-derived measures. We also identified high reliability of quantitative susceptibility mapping (QSM) IDPs derived from swMRI images, multi-network ICA-based IDPs from resting-state fMRI, and olfactory bulb structure IDPs from T1, T2-FLAIR and dMRI data. CONCLUSION: These results give confidence that large, multi-site MRI datasets can be collected reliably at different sites across the diverse range of MRI modalities and IDPs that could be mechanistically informative in COVID brain research. We discuss limitations of the study and strategies for further harmonisation of data collected from sites using scanners supplied by different manufacturers. These acquisition and analysis protocols are now in use for MRI assessments of post-COVID patients (N = 700) as part of the ongoing COVID-CNS study

The Alzheimer's Disease Prediction Of Longitudinal Evolution (TADPOLE) Challenge: Results after 1 Year Follow-up

We present the findings of "The Alzheimer's Disease Prediction Of Longitudinal Evolution" (TADPOLE) Challenge, which compared the performance of 92 algorithms from 33 international teams at predicting the future trajectory of 219 individuals at risk of Alzheimer's disease. Challenge participants were required to make a prediction, for each month of a 5-year future time period, of three key outcomes: clinical diagnosis, Alzheimer's Disease Assessment Scale Cognitive Subdomain (ADAS-Cog13), and total volume of the ventricles. No single submission was best at predicting all three outcomes. For clinical diagnosis and ventricle volume prediction, the best algorithms strongly outperform simple baselines in predictive ability. However, for ADAS-Cog13 no single submitted prediction method was significantly better than random guessing. Two ensemble methods based on taking the mean and median over all predictions, obtained top scores on almost all tasks. Better than average performance at diagnosis prediction was generally associated with the additional inclusion of features from cerebrospinal fluid (CSF) samples and diffusion tensor imaging (DTI). On the other hand, better performance at ventricle volume prediction was associated with inclusion of summary statistics, such as patient-specific biomarker trends. The submission system remains open via the website https://tadpole.grand-challenge.org, while code for submissions is being collated by TADPOLE SHARE: https://tadpole-share.github.io/. Our work suggests that current prediction algorithms are accurate for biomarkers related to clinical diagnosis and ventricle volume, opening up the possibility of cohort refinement in clinical trials for Alzheimer's disease

Contact with Counter-Stereotypical Women Predicts Less Sexism, Less Rape Myth Acceptance, Less Intention to Rape (in Men) and Less Projected Enjoyment of Rape (in Women)

Intergroup contact—(positive) interactions with people from different social groups—is a widely researched and strongly supported prejudice-reducing mechanism shown to reduce prejudice against a wide variety of outgroups. However, no known previous research has investigated whether intergroup contact can also reduce sexism against women. Sexism has an array of negative outcomes. One of the most detrimental and violent ones is rape, which is both justified and downplayed by rape myth acceptance. We hypothesised that more frequent, higher quality contact with counter-stereotypical women would predict lower levels of sexism and thus less rape myth acceptance (in men) and less sexualised projected responses to rape (in women). Two studies using online surveys with community samples supported these hypotheses. In Study 1, 170 male participants who experienced more positive contact with counter-stereotypical women reported less intention to rape. Similarly, in Study 2, 280 female participants who experienced more positive contact with counter-stereotypical women reported less projected sexual arousal at the thought of being raped. Thus, the present research is the first known to show that contact could be a potential tool to combat sexism, rape myth acceptance, intentions to rape in men, and sexualisation of rape by women

A Bayesian Marked Hierarchical Spatial Point Process Model with Covariates for Lesion Data

Poster submitted to the 2016 Organization for Human Brain Mapping (OHBM) in Geneva, 26-30 June

Genetic deletion of monoacylglycerol lipase leads to impaired cannabinoid receptor CB1 R signaling and anxiety-like behavior.

Endocannabinoids (eCB) are key regulators of excitatory/inhibitory neurotransmission at cannabinoid-1-receptor (CB1R)-expressing axon terminals. The most abundant eCB in the brain, that is 2-arachidonoylglycerol (2-AG), is hydrolyzed by the enzyme monoacylglycerol lipase (MAGL), whose chronic inhibition in the brain was reported to cause CB1R desensitization. We employed the MAGL knock-out mice (MAGL-/-), a genetic model of congenital and sustained elevation of 2-AG levels in the brain, to provide morphological and biochemical evidence for \u3b2-arrestin2-mediated CB1R desensitization in brain regions involved in the control of emotional states, that is, the prefrontal cortex (PFC), amygdala, hippocampus and cerebellar cortex. We found a widespread CB1R/\u3b2-arrestin2 co-expression in the mPFC, amygdala and hippocampus accompanied by impairment of ERK signaling and elevation of vesicular glutamate transporter (VGluT1) at CB1R-positive excitatory terminals in the mPFC, or vesicular GABA transporter (VGAT) at CB1R-positive inhibitory terminals in the amygdala and hippocampus. The impairment of CB1R signaling in MAGL-/- mice was also accompanied by enhanced excitatory drive in the BLA-mPFC circuit, with subsequent elevation of glutamate release to the mPFC and anxiety-like behavior, as assessed by the marble burying test. Collectively, these data provide evidence for a \u3b2-arrestin2-mediated desensitization of CB1R in MAGL-/- mice, with impact on the synaptic plasticity of brain circuits involved in emotional functions. This article is protected by copyright. All rights reserved

Alcohol consumption and telomere length: Mendelian randomization clarifies alcohol’s effects

Alcohol’s impact on telomere length, a proposed marker of biological aging, is unclear. We performed the largest observational study to date (in n = 245,354 UK Biobank participants) and compared findings with Mendelian randomization (MR) estimates. Two-sample MR used data from 472,174 participants in a recent genome-wide association study (GWAS) of telomere length. Genetic variants were selected on the basis of associations with alcohol consumption (n = 941,280) and alcohol use disorder (AUD) (n = 57,564 cases). Non-linear MR employed UK Biobank individual data. MR analyses suggested a causal relationship between alcohol traits, more strongly for AUD, and telomere length. Higher genetically-predicted AUD (inverse variance-weighted (IVW) β = −0.06, 95% confidence interval (CI): −0.10 to −0.02, p = 0.001) was associated with shorter telomere length. There was a weaker association with genetically-predicted alcoholic drinks weekly (IVW β = −0.07, CI: −0.14 to −0.01, p = 0.03). Results were consistent across methods and independent from smoking. Non-linear analyses indicated a potential threshold relationship between alcohol and telomere length. Our findings indicate that alcohol consumption may shorten telomere length. There are implications for age-related diseases