Modelling survival : exposure pattern, species sensitivity and uncertainty

The General Unified Threshold model for Survival (GUTS) integrates previously published toxicokinetic-toxicodynamic models and estimates survival with explicitly defined assumptions. Importantly, GUTS accounts for time-variable exposure to the stressor. We performed three studies to test the ability of GUTS to predict survival of aquatic organisms across different pesticide exposure patterns, time scales and species. Firstly, using synthetic data, we identified experimental data requirements which allow for the estimation of all parameters of the GUTS proper model. Secondly, we assessed how well GUTS, calibrated with short-term survival data of Gammarus pulex exposed to four pesticides, can forecast effects of longer-term pulsed exposures. Thirdly, we tested the ability of GUTS to estimate 14-day median effect concentrations of malathion for a range of species and use these estimates to build species sensitivity distributions for different exposure patterns. We find that GUTS adequately predicts survival across exposure patterns that vary over time. When toxicity is assessed for time-variable concentrations species may differ in their responses depending on the exposure profile. This can result in different species sensitivity rankings and safe levels. The interplay of exposure pattern and species sensitivity deserves systematic investigation in order to better understand how organisms respond to stress, including humans

Variability in the Dynamics of Mortality and Immobility Responses of Freshwater Arthropods Exposed to Chlorpyrifos

The species sensitivity distribution (SSD) concept is an important probabilistic tool for environmental risk assessment (ERA) and accounts for differences in species sensitivity to different chemicals. The SSD model assumes that the sensitivity of the species included is randomly distributed. If this assumption is violated, indicator values, such as the 50% hazardous concentration, can potentially change dramatically. Fundamental research, however, has discovered and described specific mechanisms and factors influencing toxicity and sensitivity for several model species and chemical combinations. Further knowledge on how these mechanisms and factors relate to toxicologic standard end points would be beneficial for ERA. For instance, little is known about how the processes of toxicity relate to the dynamics of standard toxicity end points and how these may vary across species. In this article, we discuss the relevance of immobilization and mortality as end points for effects of the organophosphate insecticide chlorpyrifos on 14 freshwater arthropods in the context of ERA. For this, we compared the differences in response dynamics during 96 h of exposure with the two end points across species using dose response models and SSDs. The investigated freshwater arthropods vary less in their immobility than in their mortality response. However, differences in observed immobility and mortality were surprisingly large for some species even after 96 h of exposure. As expected immobility was consistently the more sensitive end point and less variable across the tested species and may therefore be considered as the relevant end point for population of SSDs and ERA, although an immobile animal may still potentially recover. This is even more relevant because an immobile animal is unlikely to survive for long periods under field conditions. This and other such considerations relevant to the decision-making process for a particular end point are discussed

Reduction of serum IGF-I levels in patients affected with Monoclonal Gammopathies of undetermined significance or Multiple Myeloma. Comparison with bFGF, VEGF and K-ras gene mutation

<p>Abstract</p> <p>Background</p> <p>Serum levels of IGF-I in patients affected with multiple myeloma (MM) have been scarcely studied. The present study is aimed to explore this point comparing 55 healthy subjects, 71 monoclonal gammopaties of uncertain significance (MGUS) and 77 overt MM patients. In the same subjects, basic FGF and VEGF, have been detected. All three mediators were analyzed in function of K-<it>ras </it>mutation and melphalan response. Concerning IGF-I, two representative monitoring examples have also been added.</p> <p>Methods</p> <p>Cytokine determinations were performed by commercially available ELISA kits, while K12-<it>ras </it>mutation was investigated on genomic DNA isolated from bone marrow cell specimens by RFLP-PCR assay.</p> <p>Results</p> <p>Significant reductions of IGF-I levels were observed in MGUS and MM as compared with healthy controls. In addition, MM subjects showed significantly decreased serum IGF-I levels than MGUS. Conversely, increasing levels were observed for bFGF and VEGF, molecules significantly correlated. A multivariate analysis corrected for age and gender confirmed the significant difference only for IGF-I values (P = 0.01). K12-<it>ras </it>mutation was significantly associated with malignancy, response to therapy and with significantly increased serum bFGF levels.</p> <p>Conclusion</p> <p>IGF-I reduction in the transition: Controls→MGUS→MM and changes observed over time suggest that IGF-I should be furtherly studied in future clinical trials as a possible monitoring marker for MM.</p

Maternal prepregnancy body mass index and offspring white matter microstructure: results from three birth cohorts

Prepregnancy maternal obesity is a global health problem and has been associated with offspring metabolic and mental ill-health. However, there is a knowledge gap in understanding potential neurobiological factors related to these associations. This study explored the relation between maternal prepregnancy body mass index (BMI) and offspring brain white matter microstructure at the age of 6, 10, and 26 years in three independent cohorts. Maternal BMI was associated with higher FA and lower MD in multiple brain tracts in offspring aged 10 and 26 years, but not at 6 years of age. Future studies should examine whether our observations can be replicated and explore the potential causal nature of the findings.This work was supported by the European Union’s Horizon 2020 research and innovation program [grant agreement no. 633595 DynaHEALTH] and no. 733206 LifeCycle], the Netherlands Organization for Health Research and Development [ZONMW Vici project 016.VICI.170.200]. The PREOBE cohort was funded by Spanish Ministry of Innovation and Science. Junta de Andalucía: Excellence Projects (P06-CTS-02341) and Spanish Ministry of Economy and Competitiveness (BFU2012-40254-C03-01). The first phase of the Generation R Study is made possible by financial support from the Erasmus Medical Centre, the Erasmus University, and the Netherlands Organization for Health Research and Development (ZonMW, grant ZonMW Geestkracht 10.000.1003). The Northern Finland Birth Cohort 1986 is funded by University of Oulu, University Hospital of Oulu, Academy of Finland (EGEA), Sigrid Juselius Foundation, European Commission (EURO-BLCS, Framework 5 award QLG1-CT-2000-01643), NIH/NIMH (5R01MH63706:02

Whole-Genome Sequencing Coupled to Imputation Discovers Genetic Signals for Anthropometric Traits

Deep sequence-based imputation can enhance the discovery power of genome-wide association studies by assessing previously unexplored variation across the common-and low-frequency spectra. We applied a hybrid whole-genome sequencing (WGS) and deep imputation approach to examine the broader allelic architecture of 12 anthropometric traits associated with height, body mass, and fat distribution in up to 267,616 individuals. We report 106 genome-wide significant signals that have not been previously identified, including 9 low-frequency variants pointing to functional candidates. Of the 106 signals, 6 are in genomic regions that have not been implicated with related traits before, 28 are independent signals at previously reported regions, and 72 represent previously reported signals for a different anthropometric trait. 71% of signals reside within genes and fine mapping resolves 23 signals to one or two likely causal variants. We confirm genetic overlap between human monogenic and polygenic anthropometric traits and find signal enrichment in cis expression QTLs in relevant tissues. Our results highlight the potential of WGS strategies to enhance biologically relevant discoveries across the frequency spectrum.Peer reviewe

Cuff inflation time significantly affects blood flow recorded with venous occlusion plethysmography

© 2019, The Author(s). Purpose: We tested whether the values of limb blood flow calculated with strain-gauge venous occlusion plethysmography (VOP) differ when venous occlusion is achieved by automated, or manual inflation, so providing rapid and slower inflation, respectively. Method: In 9 subjects (20–30 years), we calculated forearm blood flows (FBF) values at rest and following isometric handgrip at 70% maximum voluntary contraction (MVC) when rapid, or slower inflation was used. Result: Rapid and slower cuff inflation took 0.23 ± 0.01 (mean ± SEM) and 0.92 ± 0.02 s, respectively, reflecting the range reported in published studies. At rest, FBF calculated from the 1st cardiac cycle after rapid and slower inflation gave similar values: 10.5 ± 1.4 vs. 9.6 ± 1.3 ml dl − 1  min − 1 , respectively (P > 0.05). However, immediately post-contraction, FBF was ~ 40% lower with slower inflation: 54.6 ± 5.1 vs. 33.8 ± 4.2 ml dl − 1  min − 1 (P < 0.01). The latter value was similar to that calculated over the 3rd cardiac cycle following rapid inflation: 2nd cardiac cycle: 40.5 ± 4.5; 3rd cycle: 32.6 ± 4.5 ml dl − 1  min − 1 . Regression analyses of FBFs recorded at intervals post-contraction showed those calculated over the 1st, 2nd, or 3rd cardiac cycles with rapid inflation correlated well with those from the 1st cardiac cycle with manual inflation (r = 0.79, 0.82, 0.79; P < 0.01). However, only the slope for the 3rd cycle with rapid inflation vs. slower inflation was close to unity (2.07, 1.34, and 0.94, respectively). Conclusion: These findings confirm that the 1st cardiac cycle following venous occlusion should be used when calculating FBF using VOP and, but importantly, indicate that cuff inflation should be almost instantaneous; just ≥ 0.9 s leads to substantial underestimation, especially at high flows

Genome-wide associations for birth weight and correlations with adult disease

Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease1. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P < 5 × 10−8). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (Rg = −0.22, P = 5.5 × 10−13), T2D (Rg = −0.27, P = 1.1 × 10−6) and coronary artery disease (Rg = −0.30, P = 6.5 × 10−9). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P = 1.9 × 10−4). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated