Reproducibility of the peritoneal regression grading score for assessment of response to therapy in peritoneal metastasis.

The four-tiered peritoneal regression grading score (PRGS) assesses the response to chemotherapy in peritoneal metastasis (PM). The PRGS is used, for example, to assess the response to pressurised intraperitoneal aerosol chemotherapy (PIPAC). However, the reproducibility of the PRGS is currently unknown. We aimed to evaluate the inter- and intraobserver variability of the PRGS. Thirty-three patients who underwent at least three PIPAC treatments as part of the PIPAC-OPC1 or PIPAC-OPC2 clinical trials at Odense University Hospital, Denmark, were included. Prior to each therapy cycle, peritoneal quadrant biopsies were obtained and three haematoxylin and eosin (H&E)-stained step sections were scanned and uploaded to a pseudonymised web library. For determining interobserver variability, eight pathologists assessed the PRGS for each quadrant biopsy, and Krippendorff's alpha and intraclass correlation coefficients (ICCs) were calculated. For determining intraobserver variability, three pathologists repeated their own assessments and Cohen's kappa and ICCs were calculated. A total of 331 peritoneal biopsies were analysed. Interobserver variability for PRGS of each biopsy and for the mean and maximum PRGS per biopsy set was moderate to good/substantial. The intraobserver variability for PRGS of each biopsy and for the mean and maximum PRGS per biopsy set was good to excellent/almost perfect. Our data support the PRGS as a reproducible and useful tool to assess response to intraperitoneal chemotherapy in PM. Future studies should evaluate the prognostic and predictive role of the PRGS

Optimization of the Strength-Fracture Toughness Relation in Particulate-Reinforced Aluminum Composites via Control of the Matrix Microstructure

The article of record as published may be found at http://dx.doi.org/10.1007/s11661-998-0119-9The evolution of the microstructure and mechanical properties of a 17.5 vol. pct SiC particulatereinforced aluminum alloy 6092-matrix composite has been studied as a function of postfabrication processing and heat treatment. It is demonstrated that, by the control of particulate distribution, matrix grain, and substructure and of the matrix precipitate state, the strength-toughness combination in the composite can be optimized over a wide range of properties, without resorting to unstable, underaged (UA) matrix microstructures, which are usually deemed necessary to produce a higher fracture toughness than that displayed in the peak-aged condition. Further, it is demonstrated that, following an appropriate combination of thermomechanical processing and unconventional heat treatment, the composite may possess better stiffness, strength, and fracture toughness than a similar unreinforced alloy. In the high- and low-strength matrix microstructural conditions, the matrix grain and substructure were found to play a substantial role in determining fracture properties. However, in the intermediate- strength regime, properties appeared to be optimizable by the utilization of heat treatments only. These observations are rationalized on the basis of current understanding of the grain size dependence of fracture toughness and the detailed microstructural features resulting from thermomechanical treatments.United States Army Research OfficeArmy Research LabratoryUnited States Air Force Office of Scientific ResearchWright Materials LabratoryDWA Composite

Improving Genetic Prediction by Leveraging Genetic Correlations Among Human Diseases and Traits

Genomic prediction has the potential to contribute to precision medicine. However, to date, the utility of such predictors is limited due to low accuracy for most traits. Here theory and simulation study are used to demonstrate that widespread pleiotropy among phenotypes can be utilised to improve genomic risk prediction. We show how a genetic predictor can be created as a weighted index that combines published genome-wide association study (GWAS) summary statistics across many different traits. We apply this framework to predict risk of schizophrenia and bipolar disorder in the Psychiatric Genomics consortium data, finding substantial heterogeneity in prediction accuracy increases across cohorts. For six additional phenotypes in the UK Biobank data, we find increases in prediction accuracy ranging from 0.7 for height to 47 for type 2 diabetes, when using a multi-trait predictor that combines published summary statistics from multiple traits, as compared to a predictor based only on one trait. © 2018 The Author(s)

Genome-wide association study identifies 30 Loci Associated with Bipolar Disorder

This paper is dedicated to the memory of Psychiatric Genomics Consortium (PGC) founding member and Bipolar disorder working group co-chair Pamela Sklar. We thank the participants who donated their time, experiences and DNA to this research, and to the clinical and scientific teams that worked with them. We are deeply indebted to the investigators who comprise the PGC. The views expressed are those of the authors and not necessarily those of any funding or regulatory body. Analyses were carried out on the NL Genetic Cluster Computer (http://www.geneticcluster.org ) hosted by SURFsara, and the Mount Sinai high performance computing cluster (http://hpc.mssm.edu).Bipolar disorder is a highly heritable psychiatric disorder. We performed a genome-wide association study including 20,352 cases and 31,358 controls of European descent, with follow-up analysis of 822 variants with P<1x10-4 in an additional 9,412 cases and 137,760 controls. Eight of the 19 variants that were genome-wide significant (GWS, p < 5x10-8) in the discovery GWAS were not GWS in the combined analysis, consistent with small effect sizes and limited power but also with genetic heterogeneity. In the combined analysis 30 loci were GWS including 20 novel loci. The significant loci contain genes encoding ion channels, neurotransmitter transporters and synaptic components. Pathway analysis revealed nine significantly enriched gene-sets including regulation of insulin secretion and endocannabinoid signaling. BDI is strongly genetically correlated with schizophrenia, driven by psychosis, whereas BDII is more strongly correlated with major depressive disorder. These findings address key clinical questions and provide potential new biological mechanisms for BD.This work was funded in part by the Brain and Behavior Research Foundation, Stanley Medical Research Institute, University of Michigan, Pritzker Neuropsychiatric Disorders Research Fund L.L.C., Marriot Foundation and the Mayo Clinic Center for Individualized Medicine, the NIMH Intramural Research Program; Canadian Institutes of Health Research; the UK Maudsley NHS Foundation Trust, NIHR, NRS, MRC, Wellcome Trust; European Research Council; German Ministry for Education and Research, German Research Foundation IZKF of Münster, Deutsche Forschungsgemeinschaft, ImmunoSensation, the Dr. Lisa-Oehler Foundation, University of Bonn; the Swiss National Science Foundation; French Foundation FondaMental and ANR; Spanish Ministerio de Economía, CIBERSAM, Industria y Competitividad, European Regional Development Fund (ERDF), Generalitat de Catalunya, EU Horizon 2020 Research and Innovation Programme; BBMRI-NL; South-East Norway Regional Health Authority and Mrs. Throne-Holst; Swedish Research Council, Stockholm County Council, Söderström Foundation; Lundbeck Foundation, Aarhus University; Australia NHMRC, NSW Ministry of Health, Janette M O'Neil and Betty C Lynch

Age at first birth in women is genetically associated with increased risk of schizophrenia

Prof. Paunio on PGC:n jäsenPrevious studies have shown an increased risk for mental health problems in children born to both younger and older parents compared to children of average-aged parents. We previously used a novel design to reveal a latent mechanism of genetic association between schizophrenia and age at first birth in women (AFB). Here, we use independent data from the UK Biobank (N = 38,892) to replicate the finding of an association between predicted genetic risk of schizophrenia and AFB in women, and to estimate the genetic correlation between schizophrenia and AFB in women stratified into younger and older groups. We find evidence for an association between predicted genetic risk of schizophrenia and AFB in women (P-value = 1.12E-05), and we show genetic heterogeneity between younger and older AFB groups (P-value = 3.45E-03). The genetic correlation between schizophrenia and AFB in the younger AFB group is -0.16 (SE = 0.04) while that between schizophrenia and AFB in the older AFB group is 0.14 (SE = 0.08). Our results suggest that early, and perhaps also late, age at first birth in women is associated with increased genetic risk for schizophrenia in the UK Biobank sample. These findings contribute new insights into factors contributing to the complex bio-social risk architecture underpinning the association between parental age and offspring mental health.Peer reviewe

Integrated analysis of environmental and genetic influences on cord blood DNA methylation in new-borns

Epigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. Here we examine the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs) in 4 independent cohorts (overall n = 2365). We use Akaike’s information criterion to test which factors best explain variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E), genotypes in cis (G), or their additive (G + E) or interaction (GxE) effects. Genetic and environmental factors in combination best explain DNAm at the majority of VMRs. The CpGs best explained by either G, G + E or GxE are functionally distinct. The enrichment of genetic variants from GxE models in GWAS for complex disorders supports their importance for disease risk

Assessment of the quality of patient-orientated internet information on surgery for ulcerative colitis

Aim The study examines the quality of websites that provide information on ulcerative colitis, including treatment options and surgery. Method Two search engines (Google and Yahoo) and the search terms \u201csurgery for ulcerative colitis\u201d were used. The first 50 sites of each were assessed. Sites were evaluated for content and scored using the DISCERN instrument, which evaluates the quality of health information on treatment choices. Results One hundred sites were examined, of which 14 were duplicates. Of the remainder 58 provided patient orientated information for adults, and one site provided information for surgery in children. The other 27 sites included six scientific articles, three blogs, three links, six resources for clinicians, five fora, two video links and two dead links. Of the 58 websites that provided patient information for adults, only 26 (44.8%) had been updated within the last two years. Only 13/58 (22.4%) were affiliated to hospitals and clinics. Most sites (38/58, 65.5%) were associated with private companies with commercial interests. Although most websites contained information on symptoms and treatment options of ulcerative colitis, 37 (63.8%) did not describe any of the risks of surgery. Overall, only seven (12.1%) were identified as being \u201cgood\u201d or \u201cexcellent\u201d using the DISCERN criteria. Conclusion The quality of patient information on surgery for ulcerative colitis is highly variable. There is potential for internet provision of valuable information and clinicians should guide patients to access high quality websites