Bayesian inference for group-level cortical surface image-on-scalar-regression with Gaussian process priors

In regression-based analyses of group-level neuroimage data researchers typically fit a series of marginal general linear models to image outcomes at each spatially-referenced pixel. Spatial regularization of effects of interest is usually induced indirectly by applying spatial smoothing to the data during preprocessing. While this procedure often works well, resulting inference can be poorly calibrated. Spatial modeling of effects of interest leads to more powerful analyses, however the number of locations in a typical neuroimage can preclude standard computation with explicitly spatial models. Here we contribute a Bayesian spatial regression model for group-level neuroimaging analyses. We induce regularization of spatially varying regression coefficient functions through Gaussian process priors. When combined with a simple nonstationary model for the error process, our prior hierarchy can lead to more data-adaptive smoothing than standard methods. We achieve computational tractability through Vecchia approximation of our prior which, critically, can be constructed for a wide class of spatial correlation functions and results in prior models that retain full spatial rank. We outline several ways to work with our model in practice and compare performance against standard vertex-wise analyses. Finally we illustrate our method in an analysis of cortical surface fMRI task contrast data from a large cohort of children enrolled in the Adolescent Brain Cognitive Development study

Bayesian Inference for Brain Activity from Functional Magnetic Resonance Imaging Collected at Two Spatial Resolutions

Neuroradiologists and neurosurgeons increasingly opt to use functional magnetic resonance imaging (fMRI) to map functionally relevant brain regions for noninvasive presurgical planning and intraoperative neuronavigation. This application requires a high degree of spatial accuracy, but the fMRI signal-to-noise ratio (SNR) decreases as spatial resolution increases. In practice, fMRI scans can be collected at multiple spatial resolutions, and it is of interest to make more accurate inference on brain activity by combining data with different resolutions. To this end, we develop a new Bayesian model to leverage both better anatomical precision in high resolution fMRI and higher SNR in standard resolution fMRI. We assign a Gaussian process prior to the mean intensity function and develop an efficient, scalable posterior computation algorithm to integrate both sources of data. We draw posterior samples using an algorithm analogous to Riemann manifold Hamiltonian Monte Carlo in an expanded parameter space. We illustrate our method in analysis of presurgical fMRI data, and show in simulation that it infers the mean intensity more accurately than alternatives that use either the high or standard resolution fMRI data alone.Comment: 37 pages, 12 figure

Prescription drug monitoring program data tracking of opioid addiction treatment outcomes in integrated dual diagnosis care involving injectable naltrexone

BACKGROUND AND OBJECTIVES: Fourfold increases in opioid prescribing and dispensations over 2 decades in the U.S. has paralleled increases in opioid addictions and overdoses, requiring new preventative, diagnostic, and treatment strategies. This study examines Prescription Drug Monitoring Program (PDMP) tracking as a novel measure of opioid addiction treatment outcomes in a university-affiliated integrated mental health-addiction treatment clinic. METHODS: Repeated measure parametrics examined PDMP and urine drug screening (UDS) data before and after first injection for all patients (N = 68) who received at least one long-acting naltrexone injection (380 mg/IM) according to diagnostic groupings of having either (i) alcohol (control); (ii) opioid; or (iii) combined alcohol and opioid use disorders. RESULTS: There were no group differences post-injection in treatment days, injections delivered, or treatment service encounters. UDS and PDMP measures of opioid exposures were greater in opioid compared to alcohol-only patients. Post-first injection, UDS's positive for opioids declined (p < .05) along with PDMP measures of opioid prescriptions (p < .001), doses (p < .01), types (p < .001), numbers of dispensing prescribers (p < .001) and pharmacies (p < .001). Opioid patients without alcohol disorders showed the best outcomes with 50% to 80% reductions in PDMP-measures of opioids, down to levels of alcohol-only patients. CONCLUSIONS: This study shows PDMP utility for measuring opioid addiction treatment outcomes, supporting the routine use of PDMPs in clinical and research settings. SCIENTIFIC SIGNIFICANCE: These findings demonstrate that opioid addiction in patients with complex addictions and mental illnesses comorbidities can show effective treatment responses as measured by PDMP tracking of decreases in opioid prescriptions to those patients. (Am J Addict 2016;25:557-564)

The Prognostic and Predictive Value of Melanoma-related MicroRNAs Using Tissue and Serum: A MicroRNA Expression Analysis

The overall 5-year survival for melanoma is 91%. However, if distant metastasis occurs (stage IV), cure rates are = 82%) when = 4 miRNAs were expressed. Moreover, the 'MELmiR-7' panel characterised overall survival of melanoma patients better than both serum LDH and S100B (delta log likelihood=11, p < 0.001). This panel was found to be superior to currently used serological markers for melanoma progression, recurrence, and survival; and would be ideally suited to monitor tumour progression in patients diagnosed with early metastatic disease (stages IIIa-c/IV M1a-b) to detect relapse following surgical or adjuvant treatment. (C) 2015 The Authors. Published by Elsevier B. V

Middle and Late Pleistocene environmental history of the Marsworth area, south-central England

To elucidate the Middle and Late Pleistocene environmental history of south-central England, we report the stratigraphy, sedimentology, palaeoecology and geochronology of some deposits near the foot of the Chiltern Hills scarp at Marsworth, Buckinghamshire. The Marsworth site is important because its sedimentary sequences contain a rich record of warm stages and cold stages, and it lies close to the Anglian glacial limit. Critical to its history are the origin and age of a brown pebbly silty clay (diamicton) previously interpreted as weathered till. The deposits described infill a river channel incised into chalk bedrock. They comprise clayey, silty and gravelly sediments, many containing locally derived chalk and some with molluscan, ostracod and vertebrate remains. Most of the deposits are readily attributed to periglacial and fluvial processes, and some are dated by optically stimulated luminescence to Marine Isotope Stage (MIS) 6. Although our sedimentological data do not discriminate between a glacial or periglacial interpretation of the diamicton, amino-acid dating of three molluscan taxa from beneath it indicates that it is younger than MIS 9 and older than MIS 5e. This makes a glacial interpretation unlikely, and we interpret the diamicton as a periglacial slope deposit. The Pleistocene history reconstructed for Marsworth identifies four key elements: (1) Anglian glaciation during MIS 12 closely approached Marsworth, introducing far-travelled pebbles such as Rhaxella chert and possibly some fine sand minerals into the area. (2) Interglacial environments inferred from fluvial sediments during MIS 7 varied from fully interglacial conditions during sub-stages 7e and 7c, cool temperate conditions during sub-stage 7b or 7a, temperate conditions similar to those today in central England towards the end of the interglacial, and cool temperate conditions during sub-stage 7a. (3) Periglacial activity during MIS 6 involved thermal contraction cracking, permafrost development, fracturing of chalk bedrock, fluvial activity, slopewash, mass movement and deposition of loess and coversand. (4) Fully interglacial conditions during sub-stage 5e led to renewed fluvial activity, soil formation and acidic weathering

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Whole Genome Expression Array Profiling Highlights Differences in Mucosal Defense Genes in Barrett's Esophagus and Esophageal Adenocarcinoma

Esophageal adenocarcinoma (EAC) has become a major concern in Western countries due to rapid rises in incidence coupled with very poor survival rates. One of the key risk factors for the development of this cancer is the presence of Barrett's esophagus (BE), which is believed to form in response to repeated gastro-esophageal reflux. In this study we performed comparative, genome-wide expression profiling (using Illumina whole-genome Beadarrays) on total RNA extracted from esophageal biopsy tissues from individuals with EAC, BE (in the absence of EAC) and those with normal squamous epithelium. We combined these data with publically accessible raw data from three similar studies to investigate key gene and ontology differences between these three tissue states. The results support the deduction that BE is a tissue with enhanced glycoprotein synthesis machinery (DPP4, ATP2A3, AGR2) designed to provide strong mucosal defenses aimed at resisting gastro-esophageal reflux. EAC exhibits the enhanced extracellular matrix remodeling (collagens, IGFBP7, PLAU) effects expected in an aggressive form of cancer, as well as evidence of reduced expression of genes associated with mucosal (MUC6, CA2, TFF1) and xenobiotic (AKR1C2, AKR1B10) defenses. When our results are compared to previous whole-genome expression profiling studies keratin, mucin, annexin and trefoil factor gene groups are the most frequently represented differentially expressed gene families. Eleven genes identified here are also represented in at least 3 other profiling studies. We used these genes to discriminate between squamous epithelium, BE and EAC within the two largest cohorts using a support vector machine leave one out cross validation (LOOCV) analysis. While this method was satisfactory for discriminating squamous epithelium and BE, it demonstrates the need for more detailed investigations into profiling changes between BE and EAC

The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions

Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention

The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions

Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention

Fine-Scale Mapping of the 4q24 Locus Identifies Two Independent Loci Associated with Breast Cancer Risk

Background: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. Methods: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. Results: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10−4; OR, 1.04; 95% confidence interval (CI), 1.02–1.07] and rs77928427 (P = 1.86 × 10−4; OR, 1.04; 95% CI, 1.02–1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r2 ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor–binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. Conclusion: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. Impact: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk