A Bayesian General Linear Modeling Approach to Cortical Surface fMRI Data Analysis

Cortical surface functional magnetic resonance imaging (cs-fMRI) has recently grown in popularity versus traditional volumetric fMRI. In addition to offering better whole-brain visualization, dimension reduction, removal of extraneous tissue types, and improved alignment of cortical areas across subjects, it is also more compatible with common assumptions of Bayesian spatial models. However, as no spatial Bayesian model has been proposed for cs-fMRI data, most analyses continue to employ the classical general linear model (GLM), a “massive univariate” approach. Here, we propose a spatial Bayesian GLM for cs-fMRI, which employs a class of sophisticated spatial processes to model latent activation fields. We make several advances compared with existing spatial Bayesian models for volumetric fMRI. First, we use integrated nested Laplacian approximations, a highly accurate and efficient Bayesian computation technique, rather than variational Bayes. To identify regions of activation, we utilize an excursions set method based on the joint posterior distribution of the latent fields, rather than the marginal distribution at each location. Finally, we propose the first multi-subject spatial Bayesian modeling approach, which addresses a major gap in the existing literature. The methods are very computationally advantageous and are validated through simulation studies and two task fMRI studies from the Human Connectome Project. Supplementary materials for this article, including a standardized description of the materials available for reproducing the work, are available as an online supplement

Predictive response-relevant clustering of expression data provides insights into disease processes

This article describes and illustrates a novel method of microarray data analysis that couples model-based clustering and binary classification to form clusters of ;response-relevant' genes; that is, genes that are informative when discriminating between the different values of the response. Predictions are subsequently made using an appropriate statistical summary of each gene cluster, which we call the ;meta-covariate' representation of the cluster, in a probit regression model. We first illustrate this method by analysing a leukaemia expression dataset, before focusing closely on the meta-covariate analysis of a renal gene expression dataset in a rat model of salt-sensitive hypertension. We explore the biological insights provided by our analysis of these data. In particular, we identify a highly influential cluster of 13 genes-including three transcription factors (Arntl, Bhlhe41 and Npas2)-that is implicated as being protective against hypertension in response to increased dietary sodium. Functional and canonical pathway analysis of this cluster using Ingenuity Pathway Analysis implicated transcriptional activation and circadian rhythm signalling, respectively. Although we illustrate our method using only expression data, the method is applicable to any high-dimensional datasets

Farnesoid X Receptor and its ligands inhibit the function of platelets

Objective - While initially seemingly paradoxical due to the lack of nucleus, platelets possess a number of transcription factors that regulate their function through DNA-independent mechanisms. These include the Farnesoid X Receptor (FXR), a member of the superfamily of ligand-activated transcription factors that has been identified as a bile acid receptor. In this study, we show that FXR is present in human platelets and FXR ligands, GW4064 and 6-ECDCA, modulate platelet activation nongenomically. Approach and Results - FXR ligands inhibited the activation of platelets in response to stimulation of collagen or thrombin receptors, resulting in diminished intracellular calcium mobilization and secretion, fibrinogen binding and aggregation. Exposure to FXR ligands also reduced integrin alphaIIbbeta3 outside-in signaling and thereby reduced the ability of platelets to spread and to stimulate clot retraction. FXR function in platelets was found to be associated with the modulation of cGMP levels in platelets and associated downstream inhibitory signaling. Platelets from FXR-deficient mice were refractory to the actions of FXR agonists on platelet function and cyclic nucleotide signaling, firmly linking the non-genomic actions of these ligands to the FXR receptor. Conclusion – This study provides support for the ability of FXR ligands to modulate platelet activation. The athero-protective effects of GW4064, with its novel antiplatelet effects, indicate FXR as a potential target for prevention of athero-thrombotic disease

Which symptoms are linked to a delayed presentation among melanoma patients? A retrospective study

Background: The incidence of melanoma is rising. Early detection is associated with a more favourable outcome. The factors that influence the timing of a patient’s presentation for medical assessment are not fully understood. The aims of the study were to measure the nature and duration of melanoma symptoms in a group of patients diagnosed with melanoma within the preceding 18 months and to identify the symptoms and barriers associated with a delay in presentation. Methods: A questionnaire was distributed to a random sample of 200 of the 963 melanoma patients who had participated in the Cancer Patient Experience Survey 2010 and were known to be alive 1 year later. Data were collected on symptoms, duration of symptoms prior to presentation and the reasons for not attending a doctor sooner. Results: A total of 159 patients responded to the questionnaire; 74 (47%) were men; mean age was 62 (range 24–90) years. Of the 149 patients who reported a symptom, 40 (27%) had a delayed presentation (i.e. >3 months). A mole growing bigger was the most common symptom and reporting this symptom was significantly associated with a delayed presentation (odds ratio (OR) 2.04, 95% confidence interval (95% CI) 1.14–5.08). Patients aged ≥65 years were less likely to report a barrier to presentation and were less likely to delay than those under 40, although this was of borderline statistical significance (OR 0.28, 95% CI 0.08–1.00). Conclusions: This study highlights that an enlarging mole is a significant symptom influencing the timing of presentation. Increasing public awareness of the signs of melanoma and of the importance of early presentation is desirable. Health professionals should take advantage of the opportunity to educate patients on such symptoms and signs where feasible. Further exploration of the barriers to presentation in younger people should be considered

Rapid Epidemiological Analysis of Comorbidities and Treatments as risk factors for COVID-19 in Scotland (REACT-SCOT): a population-based case-control study

Background The objectives of this study were to identify risk factors for severe coronavirus disease 2019 (COVID-19) and to lay the basis for risk stratification based on demographic data and health records. Methods and findings The design was a matched case-control study. Severe COVID-19 was defined as either a positive nucleic acid test for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in the national database followed by entry to a critical care unit or death within 28 days or a death certificate with COVID-19 as underlying cause. Up to 10 controls per case matched for sex, age, and primary care practice were selected from the national population register. For this analysis—based on ascertainment of positive test results up to 6 June 2020, entry to critical care up to 14 June 2020, and deaths registered up to 14 June 2020—there were 36,948 controls and 4,272 cases, of which 1,894 (44%) were care home residents. All diagnostic codes from the past 5 years of hospitalisation records and all drug codes from prescriptions dispensed during the past 240 days were extracted. Rate ratios for severe COVID-19 were estimated by conditional logistic regression. In a logistic regression using the age-sex distribution of the national population, the odds ratios for severe disease were 2.87 for a 10-year increase in age and 1.63 for male sex. In the case-control analysis, the strongest risk factor was residence in a care home, with rate ratio 21.4 (95% CI 19.1–23.9, p = 8 × 10−644). Univariate rate ratios for conditions listed by public health agencies as conferring high risk were 2.75 (95% CI 1.96–3.88, p = 6 × 10−9) for type 1 diabetes, 1.60 (95% CI 1.48–1.74, p = 8 × 10−30) for type 2 diabetes, 1.49 (95% CI 1.37–1.61, p = 3 × 10−21) for ischemic heart disease, 2.23 (95% CI 2.08–2.39, p = 4 × 10−109) for other heart disease, 1.96 (95% CI 1.83–2.10, p = 2 × 10−78) for chronic lower respiratory tract disease, 4.06 (95% CI 3.15–5.23, p = 3 × 10−27) for chronic kidney disease, 5.4 (95% CI 4.9–5.8, p = 1 × 10−354) for neurological disease, 3.61 (95% CI 2.60–5.00, p = 2 × 10−14) for chronic liver disease, and 2.66 (95% CI 1.86–3.79, p = 7 × 10−8) for immune deficiency or suppression. Seventy-eight percent of cases and 52% of controls had at least one listed condition (51% of cases and 11% of controls under age 40). Severe disease was associated with encashment of at least one prescription in the past 9 months and with at least one hospital admission in the past 5 years (rate ratios 3.10 [95% CI 2.59–3.71] and 2.75 [95% CI 2.53–2.99], respectively) even after adjusting for the listed conditions. In those without listed conditions, significant associations with severe disease were seen across many hospital diagnoses and drug categories. Age and sex provided 2.58 bits of information for discrimination. A model based on demographic variables, listed conditions, hospital diagnoses, and prescriptions provided an additional 1.07 bits (C-statistic 0.804). A limitation of this study is that records from primary care were not available. Conclusions We have shown that, along with older age and male sex, severe COVID-19 is strongly associated with past medical history across all age groups. Many comorbidities beyond the risk conditions designated by public health agencies contribute to this. A risk classifier that uses all the information available in health records, rather than only a limited set of conditions, will more accurately discriminate between low-risk and high-risk individuals who may require shielding until the epidemic is over

Relation of severe COVID-19 to polypharmacy and prescribing of psychotropic drugs: the REACT-SCOT case-control study

Background: The objective of this study was to investigate the relation of severe COVID-19 to prior drug prescribing. Methods: Severe cases were defined by entry to critical care or fatal outcome. For this matched case-control study (REACT-SCOT), all 4251 cases of severe COVID-19 in Scotland since the start of the epidemic were matched for age, sex and primary care practice to 36,738 controls from the population register. Records were linked to hospital discharges since June 2015 and dispensed prescriptions issued in primary care during the last 240 days. Results: Severe COVID-19 was strongly associated with the number of non-cardiovascular drug classes dispensed. This association was strongest in those not resident in a care home, in whom the rate ratio (95% CI) associated with dispensing of 12 or more drug classes versus none was 10.8 (8.8, 13.3), and in those without any of the conditions designated as conferring increased risk of COVID-19. Of 17 drug classes postulated at the start of the epidemic to be “ "medications compromising COVID", all were associated with increased risk of severe COVID-19 and these associations were present in those without any of the designated risk conditions. The fraction of cases in the population attributable to exposure to these drug classes was 38%. The largest effect was for antipsychotic agents: rate ratio 4.18 (3.42, 5.11). Other drug classes with large effects included proton pump inhibitors (rate ratio 2.20 (1.72, 2.83) for = 2 defined daily doses/day), opioids (3.66 (2.68, 5.01) for = 50 mg morphine equivalent/day) and gabapentinoids. These associations persisted after adjusting for covariates and were stronger with recent than with non-recent exposure. Conclusions: Severe COVID-19 is associated with polypharmacy and with drugs that cause sedation, respiratory depression, or dyskinesia; have anticholinergic effects; or affect the gastrointestinal system. These associations are not easily explained by co-morbidity. Measures to reduce the burden of mortality and morbidity from COVID-19 should include reinforcing existing guidance on reducing overprescribing of these drug classes and limiting inappropriate polypharmacy. Registration: ENCEPP number EUPAS3555

A water cycle for the Anthropocene

International audienceHumor us for a minute and do an online image search of the water cycle. How many diagrams do you have to scroll through before seeing any sign of humans? What about water pollution or climate change—two of the main drivers of the global water crisis? In a recent analysis of more than 450 water cycle diagrams, we found that 85% showed no human interaction with the water cycle and 98% omitted any sign of climate change or waterpollution (Abbott et al., 2019). Additionally, 92% of diagrams depicted verdant, temperate ecosystems with abundant freshwater and 95% showed only a single river basin. It did not matter if the diagrams came from textbooks, scientific articles, or the internet, nor if they were old or new; most showed an undisturbed water cycle, free from human interference. These depictions contrast starkly with the state of the water cycle in the Anthropocene, when land conversion, human water use, and climate change affect nearly every water pool and flux (Wurtsbaugh et al., 2017; Falkenmark et al., 2019; Wine and Davison, 2019). The dimensions and scale of human interference with water are manifest in failing fossil aquifersin the world’s great agricultural regions (Famiglietti, 2014), accelerating ice discharge from the Arctic (Box et al., 2018), and instability in atmospheric rivers that support continental rainfall (Paul et al., 2016).We believe that incorrect water cycle diagrams are a symptom of a much deeper and widespread problem about how humanity relates to water on Earth. Society does not understand how the water cycle works nor how humans fit into it (Attari, 2014; Linton, 2014; Abbott et al., 2019). In response to this crisis of understanding, we call on researchers, educators, journalists, lawyers, and policy makers to change how we conceptualize and present the global water cycle. Specifically, we must teach where water comes from, what determines its availability, and how many individuals and ecosystems are in crisis because of water mismanagement, climate change, and land conversion. Because the drivers of the global water crisis are truly global, ensuring adequate water for humans and ecosystems will require coordinated efforts that extend beyond geopolitical borders and outlast the tenure of individual administrations (Keys et al., 2017; Adler, 2019). This level of coordination and holistic thinking requires widespread understanding of the water cycle and the global water crisis. Making the causes and consequences of the water crisis visible in our diagrams is atractable and important step towards the goal of a sustainable relationship with water that includes ecosystems and society

Human domination of the global water cycle absent from depictions and perceptions

International audienceHuman water use, climate change and land conversion have created a water crisis for billions of individuals and many ecosystems worldwide. Global water stocks and fluxes are estimated empirically and with computer models, but this information is conveyed to policymakers and researchers through water cycle diagrams. Here we compiled a synthesis of the global water cycle, which we compared with 464 water cycle diagrams from around the world. Although human freshwater appropriation now equals half of global river discharge, only 15% of the water cycle diagrams depicted human interaction with water. Only 2% of the diagrams showed climate change or water pollution—two of the central causes of the global water crisis—which effectively conveys a false sense of water security. A single catchment was depicted in 95% of the diagrams, which precludes the representation of teleconnections such as ocean–land interactions and continental moisture recycling. These inaccuracies correspond with specific dimensions of water mismanagement, which suggest that flaws in water diagrams reflect and reinforce the misunderstanding of global hydrology by policymakers, researchers and the public. Correct depictions of the water cycle will not solve the global water crisis, but reconceiving this symbol is an important step towards equitable water governance, sustainable development and planetary thinking in the Anthropocene

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci.

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis