Longitudinal Effects of Embryonic Exposure to Cocaine on Morphology, Cardiovascular Physiology, and Behavior in Zebrafish

A sizeable portion of the societal drain from cocaine abuse results from the complications of in utero drug exposure. Because of challenges in using humans and mammalian model organisms as test subjects, much debate remains about the impact of in utero cocaine exposure. Zebrafish offer a number of advantages as a model in longitudinal toxicology studies and are quite sensitive physiologically and behaviorally to cocaine. In this study, we have used zebrafish to model the effects of embryonic pre-exposure to cocaine on development and on subsequent cardiovascular physiology and cocaine-induced conditioned place preference (CPP) in longitudinal adults. Larval fish showed a progressive decrease in telencephalic size with increased doses of cocaine. These treated larvae also showed a dose dependent response in heart rate that persisted 24 h after drug cessation. Embryonic cocaine exposure had little effect on overall health of longitudinal adults, but subtle changes in cardiovascular physiology were seen including decreased sensitivity to isoproterenol and increased sensitivity to cocaine. These longitudinal adult fish also showed an embryonic dose-dependent change in CPP behavior, suggesting an increased sensitivity. These studies clearly show that pre-exposure during embryonic development affects subsequent cocaine sensitivity in longitudinal adults

The bien r package: A tool to access the Botanical Information and Ecology Network (BIEN) database

There is an urgent need for largeâ scale botanical data to improve our understanding of community assembly, coexistence, biogeography, evolution, and many other fundamental biological processes. Understanding these processes is critical for predicting and handling humanâ biodiversity interactions and global change dynamics such as food and energy security, ecosystem services, climate change, and species invasions.The Botanical Information and Ecology Network (BIEN) database comprises an unprecedented wealth of cleaned and standardised botanical data, containing roughly 81 million occurrence records from c. 375,000 species, c. 915,000 trait observations across 28 traits from c. 93,000 species, and coâ occurrence records from 110,000 ecological plots globally, as well as 100,000 range maps and 100 replicated phylogenies (each containing 81,274 species) for New World species. Here, we describe an r package that provides easy access to these data.The bien r package allows users to access the multiple types of data in the BIEN database. Functions in this package query the BIEN database by turning user inputs into optimised PostgreSQL functions. Function names follow a convention designed to make it easy to understand what each function does. We have also developed a protocol for providing customised citations and herbarium acknowledgements for data downloaded through the bien r package.The development of the BIEN database represents a significant achievement in biological data integration, cleaning and standardization. Likewise, the bien r package represents an important tool for open science that makes the BIEN database freely and easily accessible to everyone.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142458/1/mee312861_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142458/2/mee312861.pd

Genetic subtypes of smoldering multiple myeloma are associated with distinct pathogenic phenotypes and clinical outcomes

Smoldering multiple myeloma (SMM) is a precursor condition of multiple myeloma (MM) with significant heterogeneity in disease progression. Existing clinical models of progression risk do not fully capture this heterogeneity. Here we integrate 42 genetic alterations from 214 SMM patients using unsupervised binary matrix factorization (BMF) clustering and identify six distinct genetic subtypes. These subtypes are differentially associated with established MM-related RNA signatures, oncogenic and immune transcriptional profiles, and evolving clinical biomarkers. Three genetic subtypes are associated with increased risk of progression to active MM in both the primary and validation cohorts, indicating they can be used to better predict high and low-risk patients within the currently used clinical risk stratification models

Plasma cells expression from smouldering myeloma to myeloma reveals the importance of the PRC2 complex, cell cycle progression, and the divergent evolutionary pathways within the different molecular subgroups

Sequencing studies have shed some light on the pathogenesis of progression from smouldering multiple myeloma (SMM) and symptomatic multiple myeloma (MM). Given the scarcity of smouldering samples, little data are available to determine which translational programmes are dysregulated and whether the mechanisms of progression are uniform across the main molecular subgroups. In this work, we investigated 223 SMM and 1348 MM samples from the University of Arkansas for Medical Sciences (UAMS) for which we had gene expression profiling (GEP). Patients were analysed by TC-7 subgroup for gene expression changes between SMM and MM. Among the commonly dysregulated genes in each subgroup, PHF19 and EZH2 highlight the importance of the PRC2.1 complex. We show that subgroup specific differences exist even at the SMM stage of disease with different biological features driving progression within each TC molecular subgroup. These data suggest that MMSET SMM has already transformed, but that the other precursor diseases are distinct clinical entities from their symptomatic counterpart

Author Correction: Expanded encyclopaedias of DNA elements in the human and mouse genomes

Online Correction for: https://doi.org/10.1038/s41586-020-2493-4 | Erratum for https://bura.brunel.ac.uk/handle/2438/21299In the version of this article initially published, two members of the ENCODE Project Consortium were missing from the author list. Rizi Ai (Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla, CA, USA) and Shantao Li (Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT, USA) are now included in the author list. These errors have been corrected in the online version of the article : 'Expanded encyclopaedias of DNA elements in the human and mouse genomes'.https://www.nature.com/articles/s41586-021-04226-3https://www.nature.com/articles/s41586-021-04226-

Perspectives on ENCODE

Supplementary information is available for this paper at https://doi.org/10.1038/s41586-020- 2449-8.© 2020, The Author(s). The Encylopedia of DNA Elements (ENCODE) Project launched in 2003 with the long-term goal of developing a comprehensive map of functional elements in the human genome. These included genes, biochemical regions associated with gene regulation (for example, transcription factor binding sites, open chromatin, and histone marks) and transcript isoforms. The marks serve as sites for candidate cis-regulatory elements (cCREs) that may serve functional roles in regulating gene expression1. The project has been extended to model organisms, particularly the mouse. In the third phase of ENCODE, nearly a million and more than 300,000 cCRE annotations have been generated for human and mouse, respectively, and these have provided a valuable resource for the scientific community.NIH grants: U01HG007019, U01HG007033, U01HG007036, U01HG007037, U41HG006992, U41HG006993, U41HG006994, U41HG006995, U41HG006996, U41HG006997, U41HG006998, U41HG006999, U41HG007000, U41HG007001, U41HG007002, U41HG007003, U41HG007234, U54HG006991, U54HG006997, U54HG006998, U54HG007004, U54HG007005, U54HG007010 and UM1HG009442

Influence of Aging Processes on the Biology and Outcome of Multiple Myeloma

Introduction While Multiple myeloma (MM) is a disease of the elderly diagnosed at a median age of 69 years with nearly a third being above the age 75, little is known about the impact of aging processes on either disease biology or clinical outcomes. Treatment decisions are complicated, and it is important to take account three interacting variables: tumor genetics, comorbidities and the efficacy and toxicity of the treatment selected. While frailty scores help stratify elderly MM patients by functional status, quantitative measures of aging could provide biological markers to enhance clinical staging systems, standardize decision making, and guide treatment choices in the elderly MM population. In this work, we characterized the genetics of older MM patients compared to younger patients, and determined the associations of age with clonal hematopoiesis and telomere length (TL), both of which have been shown to be impacted by aging. Methods Using the MMRF CoMMpass IA15 data, we analyzed 972 NDMM patients with whole genome long insert sequencing with matching whole exomes. Using paired samples, we determined mutations (Mutect2 and Strelka), copy number (Control-FREEC v. 11.4), translocations (Manta v. 1.4.0), complex rearrangements (ChainFinder and ShatterSeek), as previously described and TL using Telomerecat. Looking at the germline data, we quantified Clonal Hematopoiesis of Indeterminate Potential (CHIP) and quantified TL using the same approach. Results The overall survival of patients aged over sixty-five is significantly worse than patients younger than this age (HR 1.7 (CI 95% 1.3-2.3), p<0.0001). Using a Bayesian approach, we show that, that del(16p) and del(6q) were more frequent in older patients (Corr=0.10, BF=1.1 and Corr=0.13, BF=11). Similarly, mutational signatures did not substantially differ between age groups with the exception of the proportion of APOBEC (SBS2 and 5) which was higher in the group over age > 80 (χ2=11, p=0.02). We determined both simple and complex structural variants and found that the prevalence of chromothripsis increased with age (χ2=10.8, p=0.001). To determine whether this may be related to chromosomal instability occurring as a consequence of aging we examined the extent of telomere attrition. A significant negative correlation was identified between TL and age (F=9.5, p=0.002) but there were no correlations with complex rearrangements. We did, however, find that TL was significantly shorter in the TP53 (χ2=9, p=0.002) and ATM (χ2=7.2, p=0.007) mutated groups suggesting TL shortening may be associated with DNA instability. To further determine the association of short TL in malignant plasmacells with adverse outcomes we ranked patients based on TL quartile and determined the impact on outcome for the shortest TL. We show that 14%, 29%, 24%, 29%, and 21% of the >50, 50-60, 60-70-70-80, and >80 year old patients were within this short TL group. There was a significant correlation with adverse overall-survival both in the younger and older patients, Figure 1A. To understand and quantify the impact of aging of the normal hematopoietic system on outcomes in MM we quantified CHIP and TL on the germline samples. CHIP was seen in 156 patients (16%) and DNMT3A, ASXL1, and TET2 were the more frequent mutations. Patients with CHIP were significantly older (χ2=3.9, p=0.005), as it was seen in 22% of the over 80. The only signatures identified using a fitting approach for these CHIP mutations were the two age related mutational signatures (SBS1 and SBS5). Interestingly, patients with CHIP did not have significantly adverse clinical outcome. To understand the impact of genetics and markers of aging in the older population we performed a multivariate analysis on the subset of patients over age 65 (n=375). Like others, we found that the well described prognostic genetic risk factors (del(17p), TP53 mutations, t(4;14), t(14;16), and amp1q) did not appear to contribute to the independent assessment of risk when taking into account age, ISS, and performance status (ECOG≥2). We show that in this population of older myeloma that short TL was, however, an independent marker for negative outcome, Figure 1B. Conclusion: We highlight the importance of TL, a composite factor that takes into account both DNA instability, copy number losses, and aging as a potential novel biological marker to assess outcome and aid personalized treatment decisions in older patients with MM. Disclosures Bauer: Synthekine: Current Employment. Braunstein:Janssen: Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Amgen: Membership on an entity's Board of Directors or advisory committees; TG Therapeutics: Membership on an entity's Board of Directors or advisory committees; AstraZeneca: Membership on an entity's Board of Directors or advisory committees; Verastem: Membership on an entity's Board of Directors or advisory committees; Epizyme: Membership on an entity's Board of Directors or advisory committees; Morphosys: Membership on an entity's Board of Directors or advisory committees. Landgren:Amgen: Consultancy, Honoraria, Research Funding; Takeda: Other: Independent Data Monitoring Committees for clinical trials, Research Funding; Janssen: Consultancy, Honoraria, Other: Independent Data Monitoring Committees for clinical trials, Research Funding; Janssen: Consultancy, Honoraria, Other: Independent Data Monitoring Committees for clinical trials, Research Funding; Seattle Genetics: Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Glenmark: Consultancy, Honoraria, Research Funding; Takeda: Other: Independent Data Monitoring Committees for clinical trials, Research Funding; Binding Site: Consultancy, Honoraria; Cellectis: Consultancy, Honoraria; BMS: Consultancy, Honoraria; Karyopharma: Research Funding; BMS: Consultancy, Honoraria; Binding Site: Consultancy, Honoraria; Karyopharma: Research Funding; Merck: Other; Glenmark: Consultancy, Honoraria, Research Funding; Adaptive: Consultancy, Honoraria; Seattle Genetics: Research Funding; Pfizer: Consultancy, Honoraria; Juno: Consultancy, Honoraria; Juno: Consultancy, Honoraria; Cellectis: Consultancy, Honoraria; Pfizer: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Merck: Other. Davies:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotech: Honoraria; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene/BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Morgan:Karyopharm: Consultancy, Honoraria; GSK: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; Roche: Consultancy, Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria; Bristol-Myers Squibb: Consultancy, Honoraria; Janssen: Research Funding

Chromothripsis as a pathogenic driver of multiple myeloma

Analysis of the genetic basis for multiple myeloma (MM) has informed many of our current concepts of the biology that underlies disease initiation and progression. Studying these events in further detail is predicted to deliver important insights into its pathogenesis, prognosis and treatment. Information from whole genome sequencing of structural variation is revealing the role of these events as drivers of MM. In particular, we discuss how the insights we have gained from studying chromothripsis suggest that it can be used to provide information on disease initiation and that, as a consequence, it can be used for the clinical classification of myeloma precursor diseases allowing for early intervention and prognostic determination. For newly diagnosed MM, the integration of information on the presence of chromothripsis has the potential to significantly enhance current risk prediction strategies and to better characterize patients with high-risk disease biology. In this article we summarize the genetic basis for MM and the role played by chromothripsis as a critical pathogenic factor active at early disease phases. [Display omitted