MGMT methylation may benefit overall survival in patients with moderately vascularized glioblastomas

[EN] Objectives To assess the combined role of tumor vascularity, estimated from perfusion MRI, andMGMTmethylation status on overall survival (OS) in patients with glioblastoma. Methods A multicentric international dataset including 96 patients from NCT03439332 clinical study were used to study the prognostic relationships betweenMGMTand perfusion markers. Relative cerebral blood volume (rCBV) in the most vascularized tumor regions was automatically obtained from preoperative MRIs using ONCOhabitats online analysis service. Cox survival regression models and stratification strategies were conducted to define a subpopulation that is particularly favored byMGMTmethylation in terms of OS. Results rCBV distributions did not differ significantly (p > 0.05) in the methylated and the non-methylated subpopulations. In patients with moderately vascularized tumors (rCBV 10.73), however, there was no significant effect ofMGMTmethylation (HR = 1.72,p = 0.10, AUC = 0.56). Conclusions Our results indicate the existence of complementary prognostic information provided byMGMTmethylation and rCBV. Perfusion markers could identify a subpopulation of patients who will benefit the most fromMGMTmethylation. Not considering this information may lead to bias in the interpretation of clinical studies.Open Access funding provided by University of Oslo (incl Oslo University Hospital). This study has received funding from MTS4up project (National Plan for Scientific and Technical Research and Innovation 2013-2016, No. DPI2016-80054-R) (JMGG); H2020-SC12016-CNECT Project (No. 727560) (JMGG), H2020-SC1-BHC-20182020 (No. 825750) (JMGG), the European Research Council (ERC) under the European Union's Horizon 2020 (Grant Agreement No. 758657), the South-Eastern Norway Regional Health Authority Grants 2017073 and 2013069, the Research Council of Norway Grants 261984 (KEE). M.A.T was supported by Programa Estatal de Promocion del Talento y su Empleabilidad en I+D+i (DPI2016-80054-R). E.F.G was supported by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement (No. 844646).Fuster García, E.; Lorente Estellés, D.; Álvarez-Torres, MDM.; Juan-Albarracín, J.; Chelebian-Kocharyan, EA.; Rovira, A.; Auger Acosta, C.... (2021). MGMT methylation may benefit overall survival in patients with moderately vascularized glioblastomas. European Radiology. 31(3):1738-1747. https://doi.org/10.1007/s00330-020-07297-41738174731

Treatment of rats with a self-selected hyperlipidic diet, increases the lipid content of the main adipose tissue sites in a proportion similar to that of the lipids in the rest of organs and tissues

Adipose tissue (AT) is distributed as large differentiated masses, and smaller depots covering vessels, and organs, as well as interspersed within them. The differences between types and size of cells makes AT one of the most disperse and complex organs. Lipid storage is partly shared by other tissues such as muscle and liver. We intended to obtain an approximate estimation of the size of lipid reserves stored outside the main fat depots. Both male and female rats were made overweight by 4-weeks feeding of a cafeteria diet. Total lipid content was analyzed in brain, liver, gastrocnemius muscle, four white AT sites: subcutaneous, perigonadal, retroperitoneal and mesenteric, two brown AT sites (interscapular and perirenal) and in a pool of the rest of organs and tissues (after discarding gut contents). Organ lipid content was estimated and tabulated for each individual rat. Food intake was measured daily. There was a surprisingly high proportion of lipid not accounted for by the main macroscopic AT sites, even when brain, liver and BAT main sites were discounted. Muscle contained about 8% of body lipids, liver 1-1.4%, four white AT sites lipid 28-63% of body lipid, and the rest of the body (including muscle) 38-44%. There was a good correlation between AT lipid and body lipid, but lipid in"other organs" was highly correlated too with body lipid. Brain lipid was not. Irrespective of dietary intake, accumulation of body fat was uniform both for the main lipid storage and handling organs: large masses of AT (but also liver, muscle), as well as in the"rest" of tissues. These storage sites, in specialized (adipose) or not-specialized (liver, muscle) tissues reacted in parallel against a hyperlipidic diet challenge. We postulate that body lipid stores are handled and regulated coordinately, with a more centralized and overall mechanisms than usually assumed

Robust association between vascular habitats and patient prognosis in glioblastoma: an international retrospective multicenter study

This is the peer reviewed version of the following article: del Mar Álvarez-Torres, M., Juan-Albarracín, J., Fuster-Garcia, E., Bellvís-Bataller, F., Lorente, D., Reynés, G., Font de Mora, J., Aparici-Robles, F., Botella, C., Muñoz-Langa, J., Faubel, R., Asensio-Cuesta, S., García-Ferrando, G.A., Chelebian, E., Auger, C., Pineda, J., Rovira, A., Oleaga, L., Mollà-Olmos, E., Revert, A.J., Tshibanda, L., Crisi, G., Emblem, K.E., Martin, D., Due-Tønnessen, P., Meling, T.R., Filice, S., Sáez, C. and García-Gómez, J.M. (2020), Robust association between vascular habitats and patient prognosis in glioblastoma: An international multicenter study. J Magn Reson Imaging, 51: 1478-1486, which has been published in final form at https://doi.org/10.1002/jmri.26958. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.[EN] Background Glioblastoma (GBM) is the most aggressive primary brain tumor, characterized by a heterogeneous and abnormal vascularity. Subtypes of vascular habitats within the tumor and edema can be distinguished: high angiogenic tumor (HAT), low angiogenic tumor (LAT), infiltrated peripheral edema (IPE), and vasogenic peripheral edema (VPE). Purpose To validate the association between hemodynamic markers from vascular habitats and overall survival (OS) in glioblastoma patients, considering the intercenter variability of acquisition protocols. Study Type Multicenter retrospective study. Population In all, 184 glioblastoma patients from seven European centers participating in the NCT03439332 clinical study. Field Strength/Sequence 1.5T (for 54 patients) or 3.0T (for 130 patients). Pregadolinium and postgadolinium-based contrast agent-enhanced T-1-weighted MRI, T-2- and FLAIR T-2-weighted, and dynamic susceptibility contrast (DSC) T-2* perfusion. Assessment We analyzed preoperative MRIs to establish the association between the maximum relative cerebral blood volume (rCBV(max)) at each habitat with OS. Moreover, the stratification capabilities of the markers to divide patients into "vascular" groups were tested. The variability in the markers between individual centers was also assessed. Statistical Tests Uniparametric Cox regression; Kaplan-Meier test; Mann-Whitney test. Results The rCBV(max) derived from the HAT, LAT, and IPE habitats were significantly associated with patient OS (P < 0.05; hazard ratio [HR]: 1.05, 1.11, 1.28, respectively). Moreover, these markers can stratify patients into "moderate-" and "high-vascular" groups (P < 0.05). The Mann-Whitney test did not find significant differences among most of the centers in markers (HAT: P = 0.02-0.685; LAT: P = 0.010-0.769; IPE: P = 0.093-0.939; VPE: P = 0.016-1.000). Data Conclusion The rCBV(max) calculated in HAT, LAT, and IPE habitats have been validated as clinically relevant prognostic biomarkers for glioblastoma patients in the pretreatment stage. This study demonstrates the robustness of the hemodynamic tissue signature (HTS) habitats to assess the GBM vascular heterogeneity and their association with patient prognosis independently of intercenter variability. Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019.This work was partially supported by: MTS4up project (National Plan for Scientific and Technical Research and Innovation 2013-2016, No. DPI2016-80054-R) (to J.M.G.G.); H2020-SC1-2016-CNECT Project (No. 727560) (to J.M.G.G.) and H2020-SC1-BHC-2018-2020 (No. 825750) (to J.M.G.G.); M.A.T was supported by DPI2016-80054-R (Programa Estatal de Promocion del Talento y su Empleabilidad en I + D + i). The data acquisition and curation of the Oslo University Hospital was supported by: the European Research Council (ERC) under the European Union's Horizon 2020 (Grant Agreement No. 758657), the South-Eastern Norway Regional Health Authority Grants 2017073 and 2013069, and the Research Council of Norway Grants 261984 (to K.E.E.). We gratefully acknowledge the support of NVIDIA Corporation with the donation of the Titan V GPU used for this research. E.F.G. was supported by the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 844646. Figure 1 was designed by the Science Artist Elena Poritskaya.Álvarez-Torres, MDM.; Juan-Albarracín, J.; Fuster García, E.; Bellvís-Bataller, F.; Lorente, D.; Reynés, G.; Font De Mora, J.... (2020). Robust association between vascular habitats and patient prognosis in glioblastoma: an international retrospective multicenter study. Journal of Magnetic Resonance Imaging. 51(5):1478-1486. https://doi.org/10.1002/jmri.2695814781486515Louis, D. N., Perry, A., Reifenberger, G., von Deimling, A., Figarella-Branger, D., Cavenee, W. K., … Ellison, D. W. (2016). The 2016 World Health Organization Classification of Tumors of the Central Nervous System: a summary. Acta Neuropathologica, 131(6), 803-820. doi:10.1007/s00401-016-1545-1Gately, L., McLachlan, S., Dowling, A., & Philip, J. (2017). Life beyond a diagnosis of glioblastoma: a systematic review of the literature. Journal of Cancer Survivorship, 11(4), 447-452. doi:10.1007/s11764-017-0602-7Bae, S., Choi, Y. S., Ahn, S. S., Chang, J. H., Kang, S.-G., Kim, E. H., … Lee, S.-K. (2018). Radiomic MRI Phenotyping of Glioblastoma: Improving Survival Prediction. Radiology, 289(3), 797-806. doi:10.1148/radiol.2018180200Akbari, H., Macyszyn, L., Da, X., Wolf, R. L., Bilello, M., Verma, R., … Davatzikos, C. (2014). Pattern Analysis of Dynamic Susceptibility Contrast-enhanced MR Imaging Demonstrates Peritumoral Tissue Heterogeneity. Radiology, 273(2), 502-510. doi:10.1148/radiol.14132458Weis, S. M., & Cheresh, D. A. (2011). Tumor angiogenesis: molecular pathways and therapeutic targets. Nature Medicine, 17(11), 1359-1370. doi:10.1038/nm.2537De Palma, M., Biziato, D., & Petrova, T. V. (2017). Microenvironmental regulation of tumour angiogenesis. Nature Reviews Cancer, 17(8), 457-474. doi:10.1038/nrc.2017.51Jain, R., Poisson, L. M., Gutman, D., Scarpace, L., Hwang, S. N., Holder, C. A., … Flanders, A. (2014). Outcome Prediction in Patients with Glioblastoma by Using Imaging, Clinical, and Genomic Biomarkers: Focus on the Nonenhancing Component of the Tumor. Radiology, 272(2), 484-493. doi:10.1148/radiol.14131691Jensen, R. L., Mumert, M. L., Gillespie, D. L., Kinney, A. Y., Schabel, M. C., & Salzman, K. L. (2013). Preoperative dynamic contrast-enhanced MRI correlates with molecular markers of hypoxia and vascularity in specific areas of intratumoral microenvironment and is predictive of patient outcome. Neuro-Oncology, 16(2), 280-291. doi:10.1093/neuonc/not148Jena, A., Taneja, S., Gambhir, A., Mishra, A. K., D’souza, M. M., Verma, S. M., … Sogani, S. K. (2016). Glioma Recurrence Versus Radiation Necrosis. Clinical Nuclear Medicine, 41(5), e228-e236. doi:10.1097/rlu.0000000000001152Price, S. J., Young, A. M. H., Scotton, W. J., Ching, J., Mohsen, L. A., Boonzaier, N. R., … Larkin, T. J. (2015). Multimodal MRI can identify perfusion and metabolic changes in the invasive margin of glioblastomas. Journal of Magnetic Resonance Imaging, 43(2), 487-494. doi:10.1002/jmri.24996Chang, Y.-C. C., Ackerstaff, E., Tschudi, Y., Jimenez, B., Foltz, W., Fisher, C., … Stoyanova, R. (2017). Delineation of Tumor Habitats based on Dynamic Contrast Enhanced MRI. Scientific Reports, 7(1). doi:10.1038/s41598-017-09932-5Cui, Y., Tha, K. K., Terasaka, S., Yamaguchi, S., Wang, J., Kudo, K., … Li, R. (2016). Prognostic Imaging Biomarkers in Glioblastoma: Development and Independent Validation on the Basis of Multiregion and Quantitative Analysis of MR Images. Radiology, 278(2), 546-553. doi:10.1148/radiol.2015150358Juan-Albarracín, J., Fuster-Garcia, E., Pérez-Girbés, A., Aparici-Robles, F., Alberich-Bayarri, Á., Revert-Ventura, A., … García-Gómez, J. M. (2018). Glioblastoma: Vascular Habitats Detected at Preoperative Dynamic Susceptibility-weighted Contrast-enhanced Perfusion MR Imaging Predict Survival. Radiology, 287(3), 944-954. doi:10.1148/radiol.2017170845Fuster-Garcia, E., Juan-Albarracín, J., García-Ferrando, G. A., Martí-Bonmatí, L., Aparici-Robles, F., & García-Gómez, J. M. (2018). Improving the estimation of prognosis for glioblastoma patients by MR based hemodynamic tissue signatures. NMR in Biomedicine, 31(12), e4006. doi:10.1002/nbm.4006Abramson, R. G., Burton, K. R., Yu, J.-P. J., Scalzetti, E. M., Yankeelov, T. E., Rosenkrantz, A. B., … Subramaniam, R. M. (2015). Methods and Challenges in Quantitative Imaging Biomarker Development. Academic Radiology, 22(1), 25-32. doi:10.1016/j.acra.2014.09.001Stupp, R., Mason, W. P., van den Bent, M. J., Weller, M., Fisher, B., Taphoorn, M. J. B., … Mirimanoff, R. O. (2005). Radiotherapy plus Concomitant and Adjuvant Temozolomide for Glioblastoma. New England Journal of Medicine, 352(10), 987-996. doi:10.1056/nejmoa043330Wetzel, S. G., Cha, S., Johnson, G., Lee, P., Law, M., Kasow, D. L., … Xue, X. (2002). Relative Cerebral Blood Volume Measurements in Intracranial Mass Lesions: Interobserver and Intraobserver Reproducibility Study. Radiology, 224(3), 797-803. doi:10.1148/radiol.2243011014Schnack, H. G., van Haren, N. E. M., Hulshoff Pol, H. E., Picchioni, M., Weisbrod, M., Sauer, H., … Kahn, R. S. (2004). Reliability of brain volumes from multicenter MRI acquisition: A calibration study. Human Brain Mapping, 22(4), 312-320. doi:10.1002/hbm.20040De Guio, F., Jouvent, E., Biessels, G. J., Black, S. E., Brayne, C., Chen, C., … Chabriat, H. (2016). Reproducibility and variability of quantitative magnetic resonance imaging markers in cerebral small vessel disease. Journal of Cerebral Blood Flow & Metabolism, 36(8), 1319-1337. doi:10.1177/0271678x16647396Hirai, T., Murakami, R., Nakamura, H., Kitajima, M., Fukuoka, H., Sasao, A., … Yamashita, Y. (2008). Prognostic Value of Perfusion MR Imaging of High-Grade Astrocytomas: Long-Term Follow-Up Study. American Journal of Neuroradiology, 29(8), 1505-1510. doi:10.3174/ajnr.a1121Sawlani, R. N., Raizer, J., Horowitz, S. W., Shin, W., Grimm, S. A., Chandler, J. P., … Carroll, T. J. (2010). Glioblastoma: A Method for Predicting Response to Antiangiogenic Chemotherapy by Using MR Perfusion Imaging—Pilot Study. Radiology, 255(2), 622-628. doi:10.1148/radiol.10091341Hambardzumyan, D., & Bergers, G. (2015). Glioblastoma: Defining Tumor Niches. Trends in Cancer, 1(4), 252-265. doi:10.1016/j.trecan.2015.10.009Artzi, M., Bokstein, F., Blumenthal, D. T., Aizenstein, O., Liberman, G., Corn, B. W., & Ben Bashat, D. (2014). Differentiation between vasogenic-edema versus tumor-infiltrative area in patients with glioblastoma during bevacizumab therapy: A longitudinal MRI study. European Journal of Radiology, 83(7), 1250-1256. doi:10.1016/j.ejrad.2014.03.02

Effect of Sex and Prior Exposure to a Cafeteria Diet on the Distribution of Sex Hormones between Plasma and Blood Cells

It is generally assumed that steroid hormones are carried in the blood free and/or bound to plasma proteins. We investigated whether blood cells were also able to bind/carry sex-related hormones: estrone, estradiol, DHEA and testosterone. Wistar male and female rats were fed a cafeteria diet for 30 days, which induced overweight. The rats were fed the standard rat diet for 15 additional days to minimize the immediate effects of excess ingested energy. Controls were always kept on standard diet. After the rats were killed, their blood was used for 1) measuring plasma hormone levels, 2) determining the binding of labeled hormones to washed red blood cells (RBC), 3) incubating whole blood with labeled hormones and determining the distribution of label between plasma and packed cells, discounting the trapped plasma volume, 4) determining free plasma hormone using labeled hormones, both through membrane ultrafiltration and dextran-charcoal removal. The results were computed individually for each rat. Cells retained up to 32% estrone, and down to 10% of testosterone, with marked differences due to sex and diet (the latter only for estrogens, not for DHEA and testosterone). Sex and diet also affected the concentrations of all hormones, with no significant diet effects for estradiol and DHEA, but with considerable interaction between both factors. Binding to RBC was non-specific for all hormones. Estrogen distribution in plasma compartments was affected by sex and diet. In conclusion: a) there is a large non-specific RBC-carried compartment for estrone, estradiol, DHEA and testosterone deeply affected by sex; b) Prior exposure to a cafeteria (hyperlipidic) diet induced hormone distribution changes, affected by sex, which hint at sex-related structural differences in RBC membranes; c) We postulate that the RBC compartment may contribute to maintain free (i.e., fully active) sex hormone levels in a way similar to plasma proteins non-specific binding

Effect of Sex and Prior Exposure to a Cafeteria Diet on the Distribution of Sex Hormones between Plasma and Blood Cells

It is generally assumed that steroid hormones are carried in the blood free and/or bound to plasma proteins. We investigated whether blood cells were also able to bind/carry sex-related hormones: estrone, estradiol, DHEA and testosterone. Wistar male and female rats were fed a cafeteria diet for 30 days, which induced overweight. The rats were fed the standard rat diet for 15 additional days to minimize the immediate effects of excess ingested energy. Controls were always kept on standard diet. After the rats were killed, their blood was used for 1) measuring plasma hormone levels, 2) determining the binding of labeled hormones to washed red blood cells (RBC), 3) incubating whole blood with labeled hormones and determining the distribution of label between plasma and packed cells, discounting the trapped plasma volume, 4) determining free plasma hormone using labeled hormones, both through membrane ultrafiltration and dextran-charcoal removal. The results were computed individually for each rat. Cells retained up to 32% estrone, and down to 10% of testosterone, with marked differences due to sex and diet (the latter only for estrogens, not for DHEA and testosterone). Sex and diet also affected the concentrations of all hormones, with no significant diet effects for estradiol and DHEA, but with considerable interaction between both factors. Binding to RBC was non-specific for all hormones. Estrogen distribution in plasma compartments was affected by sex and diet. In conclusion: a) there is a large non-specific RBC-carried compartment for estrone, estradiol, DHEA and testosterone deeply affected by sex; b) Prior exposure to a cafeteria (hyperlipidic) diet induced hormone distribution changes, affected by sex, which hint at sex-related structural differences in RBC membranes; c) We postulate that the RBC compartment may contribute to maintain free (i.e., fully active) sex hormone levels in a way similar to plasma proteins non-specific binding

Effectiveness of an mHealth intervention combining a smartphone app and smart band on body composition in an overweight and obese population: Randomized controlled trial (EVIDENT 3 study)

Background: Mobile health (mHealth) is currently among the supporting elements that may contribute to an improvement in health markers by helping people adopt healthier lifestyles. mHealth interventions have been widely reported to achieve greater weight loss than other approaches, but their effect on body composition remains unclear. Objective: This study aimed to assess the short-term (3 months) effectiveness of a mobile app and a smart band for losing weight and changing body composition in sedentary Spanish adults who are overweight or obese. Methods: A randomized controlled, multicenter clinical trial was conducted involving the participation of 440 subjects from primary care centers, with 231 subjects in the intervention group (IG; counselling with smartphone app and smart band) and 209 in the control group (CG; counselling only). Both groups were counselled about healthy diet and physical activity. For the 3-month intervention period, the IG was trained to use a smartphone app that involved self-monitoring and tailored feedback, as well as a smart band that recorded daily physical activity (Mi Band 2, Xiaomi). Body composition was measured using the InBody 230 bioimpedance device (InBody Co., Ltd), and physical activity was measured using the International Physical Activity Questionnaire. Results: The mHealth intervention produced a greater loss of body weight (–1.97 kg, 95% CI –2.39 to –1.54) relative to standard counselling at 3 months (–1.13 kg, 95% CI –1.56 to –0.69). Comparing groups, the IG achieved a weight loss of 0.84 kg more than the CG at 3 months. The IG showed a decrease in body fat mass (BFM; –1.84 kg, 95% CI –2.48 to –1.20), percentage of body fat (PBF; –1.22%, 95% CI –1.82% to 0.62%), and BMI (–0.77 kg/m2, 95% CI –0.96 to 0.57). No significant changes were observed in any of these parameters in men; among women, there was a significant decrease in BMI in the IG compared with the CG. When subjects were grouped according to baseline BMI, the overweight group experienced a change in BFM of –1.18 kg (95% CI –2.30 to –0.06) and BMI of –0.47 kg/m2 (95% CI –0.80 to –0.13), whereas the obese group only experienced a change in BMI of –0.53 kg/m2 (95% CI –0.86 to –0.19). When the data were analyzed according to physical activity, the moderate-vigorous physical activity group showed significant changes in BFM of –1.03 kg (95% CI –1.74 to –0.33), PBF of –0.76% (95% CI –1.32% to –0.20%), and BMI of –0.5 kg/m2 (95% CI –0.83 to –0.19). Conclusions: The results from this multicenter, randomized controlled clinical trial study show that compared with standard counselling alone, adding a self-reported app and a smart band obtained beneficial results in terms of weight loss and a reduction in BFM and PBF in female subjects with a BMI less than 30 kg/m2 and a moderate-vigorous physical activity level. Nevertheless, further studies are needed to ensure that this profile benefits more than others from this intervention and to investigate modifications of this intervention to achieve a global effect

A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

The evolution of the ventilatory ratio is a prognostic factor in mechanically ventilated COVID-19 ARDS patients

Background: Mortality due to COVID-19 is high, especially in patients requiring mechanical ventilation. The purpose of the study is to investigate associations between mortality and variables measured during the first three days of mechanical ventilation in patients with COVID-19 intubated at ICU admission. Methods: Multicenter, observational, cohort study includes consecutive patients with COVID-19 admitted to 44 Spanish ICUs between February 25 and July 31, 2020, who required intubation at ICU admission and mechanical ventilation for more than three days. We collected demographic and clinical data prior to admission; information about clinical evolution at days 1 and 3 of mechanical ventilation; and outcomes. Results: Of the 2,095 patients with COVID-19 admitted to the ICU, 1,118 (53.3%) were intubated at day 1 and remained under mechanical ventilation at day three. From days 1 to 3, PaO2/FiO2 increased from 115.6 [80.0-171.2] to 180.0 [135.4-227.9] mmHg and the ventilatory ratio from 1.73 [1.33-2.25] to 1.96 [1.61-2.40]. In-hospital mortality was 38.7%. A higher increase between ICU admission and day 3 in the ventilatory ratio (OR 1.04 [CI 1.01-1.07], p = 0.030) and creatinine levels (OR 1.05 [CI 1.01-1.09], p = 0.005) and a lower increase in platelet counts (OR 0.96 [CI 0.93-1.00], p = 0.037) were independently associated with a higher risk of death. No association between mortality and the PaO2/FiO2 variation was observed (OR 0.99 [CI 0.95 to 1.02], p = 0.47). Conclusions: Higher ventilatory ratio and its increase at day 3 is associated with mortality in patients with COVID-19 receiving mechanical ventilation at ICU admission. No association was found in the PaO2/FiO2 variation

Variant PRC1 Complex-Dependent H2A Ubiquitylation Drives PRC2 Recruitment and Polycomb Domain Formation

Chromatin modifying activities inherent to polycomb repressive complexes PRC1 and PRC2 play an essential role in gene regulation, cellular differentiation, and development. However, the mechanisms by which these complexes recognize their target sites and function together to form repressive chromatin domains remain poorly understood. Recruitment of PRC1 to target sites has been proposed to occur through a hierarchical process, dependent on prior nucleation of PRC2 and placement of H3K27me3. Here, using a de novo targeting assay in mouse embryonic stem cells we unexpectedly discover that PRC1-dependent H2AK119ub1 leads to recruitment of PRC2 and H3K27me3 to effectively initiate a polycomb domain. This activity is restricted to variant PRC1 complexes, and genetic ablation experiments reveal that targeting of the variant PCGF1/PRC1 complex by KDM2B to CpG islands is required for normal polycomb domain formation and mouse development. These observations provide a surprising PRC1-dependent logic for PRC2 occupancy at target sites in vivo.This study was funded by the Wellcome Trust (WT0834922 and WT081385), CRUK (C28585/A10839), NIHR, EMBO, Lister Institute of Preventative Medicine, RIKEN, MEXT, and JST CRES

Clonal chromosomal mosaicism and loss of chromosome Y in elderly men increase vulnerability for SARS-CoV-2

The pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2, COVID-19) had an estimated overall case fatality ratio of 1.38% (pre-vaccination), being 53% higher in males and increasing exponentially with age. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, we found 133 cases (1.42%) with detectable clonal mosaicism for chromosome alterations (mCA) and 226 males (5.08%) with acquired loss of chromosome Y (LOY). Individuals with clonal mosaic events (mCA and/or LOY) showed a 54% increase in the risk of COVID-19 lethality. LOY is associated with transcriptomic biomarkers of immune dysfunction, pro-coagulation activity and cardiovascular risk. Interferon-induced genes involved in the initial immune response to SARS-CoV-2 are also down-regulated in LOY. Thus, mCA and LOY underlie at least part of the sex-biased severity and mortality of COVID-19 in aging patients. Given its potential therapeutic and prognostic relevance, evaluation of clonal mosaicism should be implemented as biomarker of COVID-19 severity in elderly people. Among 9578 individuals diagnosed with COVID-19 in the SCOURGE study, individuals with clonal mosaic events (clonal mosaicism for chromosome alterations and/or loss of chromosome Y) showed an increased risk of COVID-19 lethality