Nonpar MANOVA via Independence Testing

The $k$-sample testing problem tests whether or not $k$ groups of data points are sampled from the same distribution. Multivariate analysis of variance (MANOVA) is currently the gold standard for $k$-sample testing but makes strong, often inappropriate, parametric assumptions. Moreover, independence testing and $k$-sample testing are tightly related, and there are many nonparametric multivariate independence tests with strong theoretical and empirical properties, including distance correlation (Dcorr) and Hilbert-Schmidt-Independence-Criterion (Hsic). We prove that universally consistent independence tests achieve universally consistent $k$-sample testing and that $k$-sample statistics like Energy and Maximum Mean Discrepancy (MMD) are exactly equivalent to Dcorr. Empirically evaluating these tests for $k$-sample scenarios demonstrates that these nonparametric independence tests typically outperform MANOVA, even for Gaussian distributed settings. Finally, we extend these non-parametric $k$-sample testing procedures to perform multiway and multilevel tests. Thus, we illustrate the existence of many theoretically motivated and empirically performant $k$-sample tests. A Python package with all independence and k-sample tests called hyppo is available from https://hyppo.neurodata.io/.Comment: 15 pages main + 4 pages appendix, 9 figure

Effects of long-term exposure to outdoor air pollution on COVID-19 incidence: A population-based cohort study accounting for SARS-CoV-2 exposure levels in the Netherlands

Several studies have linked air pollution to COVID-19 morbidity and severity. However, these studies do not account for exposure levels to SARS-CoV-2, nor for different sources of air pollution. We analyzed individual-level data for 8.3 million adults in the Netherlands to assess associations between long-term exposure to ambient air pollution and SARS-CoV-2 infection (i.e., positive test) and COVID-19 hospitalisation risks, accounting for spatiotemporal variation in SARS-CoV-2 exposure levels during the first two major epidemic waves (February 2020-February 2021). We estimated average annual concentrations of PM 10, PM 2.5 and NO 2 at residential addresses, overall and by PM source (road traffic, industry, livestock, other agricultural sources, foreign sources, other Dutch sources), at 1 × 1 km resolution, and weekly SARS-CoV-2 exposure at municipal level. Using generalized additive models, we performed interval-censored survival analyses to assess associations between individuals' average exposure to PM 10, PM 2.5 and NO 2 in the three years before the pandemic (2017-2019) and COVID-19-outcomes, adjusting for SARS-CoV-2 exposure, individual and area-specific confounders. In single-pollutant models, per interquartile (IQR) increase in exposure, PM 10 was associated with 7% increased infection risk and 16% increased hospitalisation risk, PM 2.5 with 8% increased infection risk and 18% increased hospitalisation risk, and NO 2 with 3% increased infection risk and 11% increased hospitalisation risk. Bi-pollutant models suggested that effects were mainly driven by PM. Associations for PM were confirmed when stratifying by urbanization degree, epidemic wave and testing policy. All emission sources of PM, except industry, showed adverse effects on both outcomes. Livestock showed the most detrimental effects per unit exposure, whereas road traffic affected severity (hospitalisation) more than infection risk. This study shows that long-term exposure to air pollution increases both SARS-CoV-2 infection and COVID-19 hospitalisation risks, even after controlling for SARS-CoV-2 exposure levels, and that PM may have differential effects on these COVID-19 outcomes depending on the emission source

Outdoor air pollution as a risk factor for testing positive for SARS-CoV-2: A nationwide test-negative case-control study in the Netherlands

Air pollution is a known risk factor for several diseases, but the extent to which it influences COVID-19 compared to other respiratory diseases remains unclear. We performed a test-negative case-control study among people with COVID-19-compatible symptoms who were tested for SARS-CoV-2 infection, to assess whether their long- and short-term exposure to ambient air pollution (AAP) was associated with testing positive (vs. negative) for SARS-CoV-2. We used individual-level data for all adult residents in the Netherlands who were tested for SARS-CoV-2 between June and November 2020, when only symptomatic people were tested, and modeled ambient concentrations of PM10, PM2.5, NO2 and O3 at geocoded residential addresses. In long-term exposure analysis, we selected individuals who did not change residential address in 2017–2019 (1.7 million tests) and considered the average concentrations of PM10, PM2.5 and NO2 in that period, and different sources of PM (industry, livestock, other agricultural activities, road traffic, other Dutch sources, foreign sources). In short-term exposure analysis, individuals not changing residential address in the two weeks before testing day (2.7 million tests) were included in the analyses, thus considering 1- and 2-week average concentrations of PM10, PM2.5, NO2 and O3 before testing day as exposure. Mixed-effects logistic regression analysis with adjustment for several confounders, including municipality and testing week to account for spatiotemporal variation in viral circulation, was used. Overall, there was no statistically significant effect of long-term exposure to the studied pollutants on the odds of testing positive vs. negative for SARS-CoV-2. However, significant positive associations of long-term exposure to PM10 and PM2.5 from specifically foreign and livestock sources, and to PM10 from other agricultural sources, were observed. Short-term exposure to PM10 (adjusting for NO2) and PM2.5 were also positively associated with increased odds of testing positive for SARS-CoV-2. While these exposures seemed to increase COVID-19 risk relative to other respiratory diseases, the underlying biological mechanisms remain unclear. This study reinforces the need to continue to strive for better air quality to support public health

Inflammatory biomarkers in Alzheimer's disease plasma

Introduction:Plasma biomarkers for Alzheimer’s disease (AD) diagnosis/stratification are a“Holy Grail” of AD research and intensively sought; however, there are no well-established plasmamarkers.Methods:A hypothesis-led plasma biomarker search was conducted in the context of internationalmulticenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL;259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed.Results:Ten analytes showed significant intergroup differences. Logistic regression identified five(FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APOε4 adjusted, optimally differentiated AD andCTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI(AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Twoanalytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71).Discussion:Plasma markers of inflammation and complement dysregulation support diagnosis andoutcome prediction in AD and MCI. Further replication is needed before clinical translatio

Mécanismes cognitifs et neuronaux sous-tendant la régulation de la douleur aiguë par la méditation de pleine conscience : une recherche utilisant des méthodes expérimentales et expérientielles

Pain is not a direct read-out of sensory input, rather it is shaped by cognitive-affective factors that can amplify or reduce pain experience. A key aggravating factor is pain catastrophizing, an exaggerated negative mental set. It has been proposed that mindfulness meditation involves the cultivation of a present-centered metacognitive stance, labeled cognitive defusion, that counteracts elaborative thought processes like pain catastrophizing, while retaining openness to sensory experience, thus inducing sensory-affective uncoupling of pain experience. This tentative hypothesis has not been explored so far, which was the aim of the present work. We additionally explored the hypothesis that the chronometry of the anterior insula is a sensitive marker of sensory-affective uncoupling of pain experience. We applied a multidimensional approach that was informed by the phenomenology of mindfulness practices and aimed to address clinically relevant questions by combining experiential and experimental methods in the context of a novel fMRI-scanner acute pain paradigm devised to amplify the cognitive-affective aspects of pain experience in trained novice and expert meditators. We found that a style of mindfulness meditation labeled Open Monitoring reduced pain unpleasantness but not pain intensity compared to attentional distraction in novice (state effect) and expert meditators (state and trait effects). Trait pain catastrophizing predicted this sensory-affective uncoupling (Study 1). In addition, cognitive defusion showed a specific inverse relation to pain catastrophizing (that was robust to controlling for variance shared with other common cognitive-emotional constructs), and both constructs specifically predicted pain unpleasantness as opposed to pain intensity, with cognitive defusion showing strongest associations. No experiential dimensions were identified that mediated this relationship (Study 2). Finally, predictions on the anterior insula as a neural marker of sensory-affective uncoupling of pain were only partly confirmed. During pain anticipation, experts exhibited lower anterior insula activation in a cluster that negatively predicted self-reported sensory-affective uncoupling but did not correlate with pain catastrophizing scores. However, we could not confirm broader predictions on anterior insula function during pain and could not identify neural markers of self-reported state effects. Instead, we observed pronounced group differences in several prefrontal clusters during the reception and anticipation of pain that could be linked to subjective pain experience, consistent with a larger literature (Study 3). These findings advance our understanding of the cognitive and neuronal mechanisms underlying mindfulness-based pain regulation and can be used to inform future contemplative neuroscientific investigations as well as treatment strategies for chronic painLa douleur ne reflète pas directement les stimulations de l'entrée sensorielle, mais est façonnée par plusieurs facteurs cognitifs-affectifs qui peuvent amplifier ou réduire l'expérience de la douleur. Un des principaux facteurs aggravants est la catastrophisation de la douleur, une disposition mentale négative qui exagère et amplifie la douleur. Il a été proposé que la méditation de pleine conscience implique la cultivation d'une posture métacognitive centrée sur le moment-présent, appelée défusion cognitive, qui contrecarre les processus de pensée élaboratifs comme la catastrophisation de la douleur, tout en conservant l'ouverture à l'expérience sensorielle. Cette postureré duirait le désagrément de la douleur en induirant un découplage sensori-affectif de l'expérience de la douleur. Cette hypothèse n'a pas été explorée explicitement jusqu'à présent, ce qui a étéle but du présent travail. Nous avons également exploré l'hypothèse selon laquelle la chronométrie de l'insula antérieure est un marqueur sensible du découplage sensori-affectif de l'expérience de la douleur pendant la méditation pleine conscience. Nous avons appliqué une approche multidisciplinaire qui était informée par la phénoménologie des pratiques de pleine conscience et visait à répondre aux questions cliniquement pertinentes. Cette approche combinait des méthodes expérientielles à des méthodes expérimentales dans le contexte d'un nouveau paradigme de douleur aiguë utilisant l’imagerie cérébrale fonctionnelle(IRMf). Ce paradigmea été conçu pour amplifier les aspects cognitifs-affectifs de l'expérience de la douleur,et a été utilisé chez des méditants novices et experts expérimentés. Nous avons constaté qu'un style de méditation de pleine conscience dit de Monitoring Ouvert réduisait le désagrément de la douleur mais pas l'intensité de la douleur par rapport à la distraction attentionnelle chez les novices (effet d'état) et les méditants experts (effets d'état et de trait). La catastrophisation de la douleur prédisait ce découplage sensori-affectif (étude 1). De plus, la défusion cognitive a montré une relation inverse spécifique par rapport aux mesures de catastrophisation de la douleur, et les deux constructions prédisaient spécifiquement le désagrément de la douleur par opposition à l'intensité de la douleur, la défusion cognitive montrant les associations les plus fortes. Aucune dimension expérientielle n'a été identifiée comme médiateur de cette relation (étude 2). Enfin, les prédictions sur l'insula antérieure en tant que marqueur neuronal du découplage sensoriel-affectif de la douleur n'ont été que partiellement confirmées. Consistent avec nos hypothèses, les experts ont montré au cours de l'anticipation de la douleur une activation de l'insula antérieure inférieure à celle des novices dans un cluster qui prédisait négativement le découplage sensoriel-affectif rapporté par les participants pendant la douleur. Cette activité n’était pas corrélée avec les scores de catastrophisation de la douleur. Néanmoins, nous n'avons pas pu confirmer des hypothèses plus larges sur la fonction de l'insula antérieure pendant la douleur et n'avons pas pu identifier les marqueurs neuronaux des effets d'état rapportés par les participants. Au lieu de cela, nous avons observé des différences de groupe prononcées dans plusieurs regions préfrontales lors de la réception et de l'anticipation de la douleur qui pourraient être liées à une expérience subjective de la douleur (étude 3). Une analyse future de la connectivité fonctionnelle entre l’insula et le reste du cerveau pourrait permettre de raffiner la compression de mécanismes neurophysiologiques en jeu pendant ces états. Ces résultats font progresser notre compréhension des mécanismes cognitifs et neuronaux qui sous-tendent la régulation de la douleur basée sur la méditation de pleine conscience et permettent de raffiner les stratégies psychothérapeutiques de traitement de la douleur chroniqu

Pain regulation during mindfulness meditation: phenomenological fingerprints in novice and expert practitioners

Background: The way people respond to pain is based on psychological mechanisms, beliefs and expectations. Mindfulness meditation (MM) has been shown to regulate pain and mental suffering through different mechanisms such as positive reappraisal, attentional and emotional regulation. Yet, subjective experience and meaning of pain in connection with MM are still largely unexplored. Methods: The present mixed-methods study combined an interpretative-phenomenological qualitative approach with an experimental thermal pain paradigm to explore and compare the meaning of experiencing pain in 32 novices who received short meditation training and 30 experts in meditation practice (more than 10, 000 hours in life). We collected the qualitative data during in-depth semi-structured interviews where we probed participants’ response strategies. During the pain task, we collected self-reports of intensity and unpleasantness, while after the task we collected self-reports of avoidance, openness, vividness and blissfulness. Results: Five phenomenological clusters (PhC) emerged from the interviews, including three which described pain as an unpleasant sensation calling for: 1) experiential avoidance-suppression, 2) volitional agency-distanciation, or 3) a positive cognitive reappraisal and flexibility. Two additional clusters (4-5), containing mostly expert meditators, thematized pain sensation as an opportunity to gain metacognitive insights about mental processes, and to deconstruct one’s suffering through these insights. PhC5 further integrates these insights with the recognition that suffering is part of the shared human experience and with the aspiration to relieve others from suffering. Each PhC was correlated to a unique profile of self-reports during the pain paradigm. Conclusion: These findings need to be replicated in patients with severe and chronic pain and practicing MM. They also warrant the integration of this mixed-method approach with brain imaging data to refine the experiential neuroscience of pain. Significance: We compared the meaning of experiencing and regulating pain in novices and expert meditators using qualitative interviews. We identified five phenomenological clusters describing relevant features implicated in pain response strategies and meditation. These clusters were organized along a pseudo-gradient, which captured meditation expertise and predicted self-reports related to a pain paradigm and psychometric scales associated with pain and its regulation. These findings advance our understanding of the metacognitive mechanisms and beliefs underlying mindfulness meditation and can inform pain treatment strategie

Training novice practitioners to reliably report their meditation experience using shared phenomenological dimensions

International audienceEmpirical descriptions of the phenomenology of meditation states rely on practitioners' ability to provide accurate information on their experience. We present a meditation training protocol that was designed to equip naive participants with a theoretical background and experiential knowledge that would enable them to share their experience. Subsequently, novices carried on with daily practice during several weeks before participating in experiments. Using a neurophenomenological experiment designed to explore two different meditation states (focused attention and open monitoring), we found that self-reported phenomenological ratings (i) were sensitive to meditation states, (ii) reflected meditation dose and fatigue effects, and (iii) correlated with behavioral measures (variability of response time). Each of these effects was better predicted by features of participants' daily practice than by desirable responding. Our results provide evidence that novice practitioners can reliably report their experience along phenomenological dimensions and warrant the future investigation of this training protocol with a longitudinal design

Cortisol stress reactivity across psychiatric disorders: A systematic review and meta-analysis

The hypothalamus-pituitary-adrenal (HPA) axis and its end product cortisol are essential for an adequate response to stress. Considering the role of stress as a risk factor for psychiatric disorders, it is not surprising that cortisol stress reactivity has frequently been investigated in patients versus healthy individuals. However, the large heterogeneity in measures of the cortisol stress response has hampered a systematic evaluation of the evidence. We here report of a systematic literature review and meta-analysis on cortisol reactivity to psychosocial stress across psychiatric disorders. Original data from authors were obtained to construct standardized cortisol outcomes (the areas under the curve with respect to increase (AUCi) and ground (AUCg)) and to examine the influence of sex and symptomatic state on cortisol stress reactivity. Fourteen studies on major depressive disorder (MDD) (n = 1129), 9 on anxiety disorders (n = 732, including social anxiety disorder (SAD), posttraumatic stress disorder, panic disorder and mixed samples of anxiety disorders) and 4 on schizophrenia (n = 180) were included that used the Trier Social Stress Test or an equivalent psychosocial stress task. Sex-dependent changes in stress reactivity were apparent in MDD and anxiety disorders. Specifically, women with current MDD or an anxiety disorder exhibited a blunted cortisol stress response, whereas men with current MDD or SAD showed an increased cortisol response to psychosocial stress. In individuals with remitted MDD, altered cortisol stress reactivity was less pronounced in women and absent in men. For schizophrenia, cortisol stress reactivity was blunted in both men and women, but the number of studies was limited and showed evidence for publication bias. These findings illustrate that sharing individual data to disentangle the effects of sex, symptom levels and other factors is essential for further understanding of the alterations in cortisol stress reactivity across psychiatric disorders. (C) 2016 Elsevier Ltd. All rights reserved

Effects of long-term exposure to outdoor air pollution on COVID-19 incidence: A population-based cohort study accounting for SARS-CoV-2 exposure levels in the Netherlands.

Several studies have linked air pollution to COVID-19 morbidity and severity. However, these studies do not account for exposure levels to SARS-CoV-2, nor for different sources of air pollution. We analyzed individual-level data for 8.3 million adults in the Netherlands to assess associations between long-term exposure to ambient air pollution and SARS-CoV-2 infection (i.e., positive test) and COVID-19 hospitalisation risks, accounting for spatiotemporal variation in SARS-CoV-2 exposure levels during the first two major epidemic waves (February 2020-February 2021). We estimated average annual concentrations of PM10, PM2.5 and NO2 at residential addresses, overall and by PM source (road traffic, industry, livestock, other agricultural sources, foreign sources, other Dutch sources), at 1 × 1 km resolution, and weekly SARS-CoV-2 exposure at municipal level. Using generalized additive models, we performed interval-censored survival analyses to assess associations between individuals' average exposure to PM10, PM2.5 and NO2 in the three years before the pandemic (2017-2019) and COVID-19-outcomes, adjusting for SARS-CoV-2 exposure, individual and area-specific confounders. In single-pollutant models, per interquartile (IQR) increase in exposure, PM10 was associated with 7% increased infection risk and 16% increased hospitalisation risk, PM2.5 with 8% increased infection risk and 18% increased hospitalisation risk, and NO2 with 3% increased infection risk and 11% increased hospitalisation risk. Bi-pollutant models suggested that effects were mainly driven by PM. Associations for PM were confirmed when stratifying by urbanization degree, epidemic wave and testing policy. All emission sources of PM, except industry, showed adverse effects on both outcomes. Livestock showed the most detrimental effects per unit exposure, whereas road traffic affected severity (hospitalisation) more than infection risk. This study shows that long-term exposure to air pollution increases both SARS-CoV-2 infection and COVID-19 hospitalisation risks, even after controlling for SARS-CoV-2 exposure levels, and that PM may have differential effects on these COVID-19 outcomes depending on the emission source