Change in glomerular filtration rate over time in the Oxford Renal Cohort Study:observational study

Background: Decline in kidney function can result in adverse health outcomes. The Oxford Renal Cohort Study has detailed baseline assessments from 884 participants ≥60 years of age. Aim: To determine the proportion of participants with a decline in estimated glomerular filtration rate (eGFR), identify determinants of decline, and determine proportions with chronic kidney disease (CKD) remission. Design and setting: Observational cohort study in UK primary care. Method: Data were used from baseline and annual follow-up assessments to monitor change in kidney function. Rapid eGFR decline was defined as eGFR decrease &gt;5 ml/min/1.73 m2/year, improvement as eGFR increase &gt;5 ml/min/1.73 m2/year, and remission in those with CKD at baseline and eGFR &gt;60 ml/min/1.73 m2 during follow-up. Cox proportional hazard models were used to identify factors associated with eGFR decline. Results: There was a net decline in eGFR in the 884 participants over 5 years of follow-up. In 686 participants with &gt;2 eGFR tests with a median follow-up of 2.1 years, 164 (24%) evidenced rapid GFR decline, 185 (27%) experienced eGFR improvement, and 82 of 394 (21%) meeting CKD stage 1-4 at baseline experienced remission. In the multivariable analysis, smoking status, higher systolic blood pressure, and being known to have CKD at cohort entry were associated with rapid GFR decline. Those with CKD stage 3 at baseline were less likely to exhibit GFR decline compared with normal kidney function. Conclusion: This study established that 24% of people evidenced rapid GFR decline whereas 21% evidenced remission of CKD. People at risk of rapid GFR decline may benefit from closer monitoring and appropriate treatment to minimise risks of adverse outcomes, although only a small proportion meet the National Institute for Health and Care Excellence criteria for referral to secondary care.</p

Mouse podoplanin supports adhesion and aggregation of platelets under arterial shear: a novel mechanism of haemostasis

The Podoplanin-CLEC-2 axis is critical in mice for prevention of haemorrhage in the cerebral vasculature during mid-gestation. This raises the question as to how platelets are captured by podoplanin on neuroepithelial cells in a high shear environment. In this study, we demonstrate that mouse platelets form stable aggregates on mouse podoplanin at arterial shear through a CLEC-2 and Src kinase-dependent pathway. Adhesion and aggregation are also dependent on the platelet glycoprotein (GP) receptors, integrin αIIbβ3 and GPIb, and the feedback agonists ADP and thromboxane A2 (TxA2). CLEC-2 does not bind to von Willebrand factor (VWF) suggesting that the interaction with podoplanin is sufficient to both tether and activate platelets. Consistent with this, surface plasmon resonance measurements reveal that mouse CLEC-2 binds to mouse podoplanin with nanomolar affinity. The present findings demonstrate a novel pathway of haemostasis in which podoplanin supporting platelet capture and activation at arteriolar rates of shear

Falkland Island peatland development processes and the pervasive presence of fire

Acknowledgments RJP secured funding for this research from the Quaternary Research Association, University of York and the Russian Science Foundation (19-14-00102). We thank Paul Brickle and other members of the South Atlantic Environmental Research Institute for their help with logistics, David Large for valuable discussions about Falkland Islands peat and all landowners for access permission. This work is dedicated to Richard J. Payne who was tragically killed while climbing Peak 6477, a previously unclimbed subsidiary peak of Nanda Devi (Garhwal Himalayas) in May 2019. CRediT authorship contribution statement Dmitri Mauquoy: Conceptualization, Investigation, Writing - original draft, Writing - review & editing. Richard J. Payne: Conceptualization, Investigation. Kirill V. Babeshko: Investigation, Writing - original draft, Writing - review & editing. Rebecca Bartlett: Investigation, Writing - original draft, Writing - review & editing. Ian Boomer: Investigation. Hannah Bowey: Investigation. Chris D. Evans: Conceptualization, Writing - original draft, Writing - review & editing. Fin Ring-Hrubesh: Investigation. David Muirhead: Methodology, Investigation, Writing - original draft, Writing - review & editing. Matthew O’Callaghan: Investigation. Natalia Piotrowska: Investigation. Graham Rush: Investigation. Thomas Sloan: Investigation. Craig Smeaton: Methodology, Investigation, Writing - original draft. Andrey N. Tsyganov: Investigation, Writing - original draft, Writing - review & editing. Yuri A. Mazei: Investigation, Writing - original draft, Writing - review & editing.Peer reviewedPostprin

Quality of life in older adults with chronic kidney disease and transient changes in renal function: Findings from the Oxford Renal cohort

BackgroundQuality of life (QoL) is an important measure of disease burden and general health perception. The relationship between early chronic kidney disease (CKD) and QoL remains poorly understood. The Oxford Renal Study (OxRen) cohort comprises 1063 adults aged ≥60 years from UK primary care practices screened for early CKD, grouped according to existing or screen-detected CKD diagnoses, or biochemistry results indicative of reduced renal function (referred to as transient estimated glomerular filtration rate (eGFR) reduction).ObjectivesThis study aimed to compare QoL in participants known to have CKD at recruitment to those identified as having CKD through a screening programme.MethodsHealth profile data and multi-attribute utility scores were reported for two generic questionnaires: 5-level EuroQol-5 Dimension (EQ-5D-5L) and ICEpop CAPability measure for Adults (ICECAP-A). QoL was compared between patients with existing and screen-detected CKD; those with transient eGFR reduction served as the reference group in univariable and multivariable linear regression.ResultsMean and standard deviation utility scores were not significantly different between the subgroups for EQ-5D-5L (screen-detected:0.785±0.156, n = 480, transient:0.779±0.157, n = 261, existing CKD:0.763±0.171, n = 322, p = 0.216) or ICECAP-A (screen-detected:0.909±0.094, transient:0.904±0.110, existing CKD:0.894±0.115, p = 0.200). Age, smoking status, and number of comorbidities were identified as independent predictors of QoL in this cohort.ConclusionQoL of participants with existing CKD diagnoses was not significantly different from those with screen-detected CKD or transient eGFR reduction and was similar to UK mean scores for the same age, suggesting that patient burden of early CKD is minor. Moreover, CKD-related comorbidities contribute more significantly to disease burden in earlier stages of CKD than renal function per se. Larger prospective studies are required to define the relationship between QoL and CKD progression more precisely. These data also confirm the essentially asymptomatic nature of CKD, implying that routine screening or case finding are required to diagnose it

Marizomib for patients with newly diagnosed glioblastoma: a randomized phase 3 trial

Background: Standard treatment for patients with newly diagnosed glioblastoma includes surgery, radiotherapy (RT) and temozolomide (TMZ) chemotherapy (TMZ/RT→TMZ). The proteasome has long been considered a promising therapeutic target because of its role as a central biological hub in tumor cells. Marizomib is a novel pan-proteasome inhibitor that crosses the blood brain barrier. Methods: EORTC 1709/CCTG CE.8 was a multicenter, randomized, controlled, open label phase 3 superiority trial. Key eligibility criteria included newly diagnosed glioblastoma, age > 18 years and Karnofsky performance status > 70. Patients were randomized in a 1:1 ratio. The primary objective was to compare overall survival (OS) in patients receiving marizomib in addition to TMZ/RT→TMZ with patients receiving only standard treatment in the whole population, and in the subgroup of patients with MGMT promoter-unmethylated tumors. Results: The trial was opened at 82 institutions in Europe, Canada and the US. A total of 749 patients (99.9% of planned 750) were randomized. OS was not different between the standard and the marizomib arm (median 17 vs 16.5 months; HR=1.04; p=0.64). PFS was not statistically different either (median 6.0 vs. 6.3 months; HR=0.97; p=0.67). In patients with MGMT promoter-unmethylated tumors, OS was also not different between standard therapy and marizomib (median 14.5 vs 15.1 months, HR=1.13; p=0.27). More CTCAE grade 3/4 treatment-emergent adverse events were observed in the marizomib arm than in the standard arm. Conclusions: Adding marizomib to standard temozolomide-based radiochemotherapy resulted in more toxicity, but did not improve OS or PFS in patients with newly diagnosed glioblastoma

RHPS4 G-quadruplex ligand induces anti-proliferative effects in brain tumor cells

Background Telomeric 3’ overhangs can fold into a four-stranded DNA structure termed G-quadruplex (G4), a formation which inhibits telomerase. As telomerase activation is crucial for telomere maintenance in most cancer cells, several classes of G4 ligands have been designed to directly disrupt telomeric structure. Methods We exposed brain tumor cells to the G4 ligand 3,11-difluoro-6,8,13-trimethyl-8H-quino[4,3,2-kl]acridinium methosulfate (RHPS4) and investigated proliferation, cell cycle dynamics, telomere length, telomerase activity and activated c-Myc levels. Results Although all cell lines tested were sensitive to RHPS4, PFSK-1 central nervous system primitive neuroectodermal cells, DAOY medulloblastoma cells and U87 glioblastoma cells exhibited up to 30-fold increased sensitivity compared to KNS42 glioblastoma, C6 glioma and Res196 ependymoma cells. An increased proportion of S-phase cells were observed in medulloblastoma and high grade glioma cells whilst CNS PNET cells showed an increased proportion of G1-phase cells. RHPS4-induced phenotypes were concomitant with telomerase inhibition, manifested in a telomere length-independent manner and not associated with activated c-Myc levels. However, anti-proliferative effects were also observed in normal neural/endothelial cells in vitro and ex vivo. Conclusion This study warrants in vivo validation of RHPS4 and alternative G4 ligands as potential anti-cancer agents for brain tumors but highlights the consideration of dose-limiting tissue toxicities

Genetic correlation between amyotrophic lateral sclerosis and schizophrenia

A. Palotie on työryhmän Schizophrenia Working Grp Psychiat jäsen.We have previously shown higher-than-expected rates of schizophrenia in relatives of patients with amyotrophic lateral sclerosis (ALS), suggesting an aetiological relationship between the diseases. Here, we investigate the genetic relationship between ALS and schizophrenia using genome-wide association study data from over 100,000 unique individuals. Using linkage disequilibrium score regression, we estimate the genetic correlation between ALS and schizophrenia to be 14.3% (7.05-21.6; P = 1 x 10(-4)) with schizophrenia polygenic risk scores explaining up to 0.12% of the variance in ALS (P = 8.4 x 10(-7)). A modest increase in comorbidity of ALS and schizophrenia is expected given these findings (odds ratio 1.08-1.26) but this would require very large studies to observe epidemiologically. We identify five potential novel ALS-associated loci using conditional false discovery rate analysis. It is likely that shared neurobiological mechanisms between these two disorders will engender novel hypotheses in future preclinical and clinical studies.Peer reviewe

Interaction Testing and Polygenic Risk Scoring to Estimate the Association of Common Genetic Variants with Treatment Resistance in Schizophrenia

Importance: About 20% to 30% of people with schizophrenia have psychotic symptoms that do not respond adequately to first-line antipsychotic treatment. This clinical presentation, chronic and highly disabling, is known as treatment-resistant schizophrenia (TRS). The causes of treatment resistance and their relationships with causes underlying schizophrenia are largely unknown. Adequately powered genetic studies of TRS are scarce because of the difficulty in collecting data from well-characterized TRS cohorts. Objective: To examine the genetic architecture of TRS through the reassessment of genetic data from schizophrenia studies and its validation in carefully ascertained clinical samples. Design, Setting, and Participants: Two case-control genome-wide association studies (GWASs) of schizophrenia were performed in which the case samples were defined as individuals with TRS (n = 10501) and individuals with non-TRS (n = 20325). The differences in effect sizes for allelic associations were then determined between both studies, the reasoning being such differences reflect treatment resistance instead of schizophrenia. Genotype data were retrieved from the CLOZUK and Psychiatric Genomics Consortium (PGC) schizophrenia studies. The output was validated using polygenic risk score (PRS) profiling of 2 independent schizophrenia cohorts with TRS and non-TRS: a prevalence sample with 817 individuals (Cardiff Cognition in Schizophrenia [CardiffCOGS]) and an incidence sample with 563 individuals (Genetics Workstream of the Schizophrenia Treatment Resistance and Therapeutic Advances [STRATA-G]). Main Outcomes and Measures: GWAS of treatment resistance in schizophrenia. The results of the GWAS were compared with complex polygenic traits through a genetic correlation approach and were used for PRS analysis on the independent validation cohorts using the same TRS definition. Results: The study included a total of 85490 participants (48635 [56.9%] male) in its GWAS stage and 1380 participants (859 [62.2%] male) in its PRS validation stage. Treatment resistance in schizophrenia emerged as a polygenic trait with detectable heritability (1% to 4%), and several traits related to intelligence and cognition were found to be genetically correlated with it (genetic correlation, 0.41-0.69). PRS analysis in the CardiffCOGS prevalence sample showed a positive association between TRS and a history of taking clozapine (r2 = 2.03%; P =.001), which was replicated in the STRATA-G incidence sample (r2 = 1.09%; P =.04). Conclusions and Relevance: In this GWAS, common genetic variants were differentially associated with TRS, and these associations may have been obscured through the amalgamation of large GWAS samples in previous studies of broadly defined schizophrenia. Findings of this study suggest the validity of meta-analytic approaches for studies on patient outcomes, including treatment resistance

Estimation of Genetic Correlation via Linkage Disequilibrium Score Regression and Genomic Restricted Maximum Likelihood

J. Lönnqvist on työryhmän Psychiat Genomics Consortium jäsen.Genetic correlation is a key population parameter that describes the shared genetic architecture of complex traits and diseases. It can be estimated by current state-of-art methods, i.e., linkage disequilibrium score regression (LDSC) and genomic restricted maximum likelihood (GREML). The massively reduced computing burden of LDSC compared to GREML makes it an attractive tool, although the accuracy (i.e., magnitude of standard errors) of LDSC estimates has not been thoroughly studied. In simulation, we show that the accuracy of GREML is generally higher than that of LDSC. When there is genetic heterogeneity between the actual sample and reference data from which LD scores are estimated, the accuracy of LDSC decreases further. In real data analyses estimating the genetic correlation between schizophrenia (SCZ) and body mass index, we show that GREML estimates based on similar to 150,000 individuals give a higher accuracy than LDSC estimates based on similar to 400,000 individuals (from combinedmeta-data). A GREML genomic partitioning analysis reveals that the genetic correlation between SCZ and height is significantly negative for regulatory regions, which whole genome or LDSC approach has less power to detect. We conclude that LDSC estimates should be carefully interpreted as there can be uncertainty about homogeneity among combined meta-datasets. We suggest that any interesting findings from massive LDSC analysis for a large number of complex traits should be followed up, where possible, with more detailed analyses with GREML methods, even if sample sizes are lesser.Peer reviewe