Cysteine induces mitochondrial reductive stress in glioblastoma through hydrogen peroxide production.

Glucose and amino acid metabolism are critical for glioblastoma (GBM) growth, but little is known about the specific metabolic alterations in GBM that are targetable with FDA-approved compounds. To investigate tumor metabolism signatures unique to GBM, we interrogated The Cancer Genome Atlas for alterations in glucose and amino acid signatures in GBM relative to other human cancers and found that GBM exhibits the highest levels of cysteine and methionine pathway gene expression of 32 human cancers. Treatment of patient-derived GBM cells with the FDA-approved single cysteine compound N-acetylcysteine (NAC) reduced GBM cell growth and mitochondrial oxygen consumption, which was worsened by glucose starvation. Normal brain cells and other cancer cells showed no response to NAC. Mechanistic experiments revealed that cysteine compounds induce rapid mitochondrial H2O2 production and reductive stress in GBM cells, an effect blocked by oxidized glutathione, thioredoxin, and redox enzyme overexpression. From analysis of the clinical proteomic tumor analysis consortium (CPTAC) database, we found that GBM cells exhibit lower expression of mitochondrial redox enzymes than four other cancers whose proteomic data are available in CPTAC. Knockdown of mitochondrial thioredoxin-2 in lung cancer cells induced NAC susceptibility, indicating the importance of mitochondrial redox enzyme expression in mitigating reductive stress. Intraperitoneal treatment of mice bearing orthotopic GBM xenografts with a two-cysteine peptide induced H2O2 in brain tumors in vivo. These findings indicate that GBM is uniquely susceptible to NAC-driven reductive stress and could synergize with glucose-lowering treatments for GBM.

Cannabis reduction among adolescents as spillover from successful tobacco control.

BACKGROUND: National programs that reduce adolescent cannabis use warrant renewed attention in light of current discussions to reform cannabis legislation, including the possibility of legalization for recreational use. This study measures the size of a decrease in a country's prevalence of adolescent cannabis use that accompanies a decrease in its prevalence of adolescents who had ever smoked a cigarette. METHODS: Data are from the European School Survey Project on Alcohol and Other Drugs (ESPAD), which is a collaborative effort of more than 40 European countries to surveil adolescent substance use. This study uses data from the seven survey administrations in 1995, 1999, 2003, 2007, 2011, 2015, and 2019. The main analysis is a fixed-effect regression analysis of country-level, four-year changes in adolescent lifetime cannabis use prevalence on country-level, four-year changes in adolescent lifetime cigarette use prevalence. RESULTS: Decreases in the national prevalence of adolescents who had ever smoked a cigarette were accompanied by decreases half as large in national prevalence of adolescent lifetime cannabis use. CONCLUSION: For European countries considering the legalization of adult recreational cannabis use, tobacco control can offer a tool to help counter potential increases in cannabis use among adolescents.

Can drug policies modify cannabis use starting choice? Insights from criminalisation in Italy.

A key question in the ongoing drug policy debate is whether legalising cannabis leads to an increase in cannabis use. In Europe although no country has yet moved to legalisation, many have decriminalised personal possession. However, some jurisdictions are still discussing increased sanctions or have further strengthened penalties for the possession of illicit substances in order to deter widespread cannabis use. This is the case in Italy, where a law introduced in 2006 and repealed in 2014 de facto criminalised personal drug possession, and a potential increase in penalties is currently being debated as a policy option. Despite the intense public debate surrounding the legal status of cannabis, limited empirical research has been conducted in Europe to assess the population-level effects of drug policy reforms, mainly due to data availability constraints. In this study, we analyse the effect of criminalisation on the age of onset of cannabis use using an unique dataset that combines seven waves (2001-2017) of the nationally representative Italian Population Survey on Alcohol and other Drugs with relevant socio-economic data. The final dataset comprises 77,650 observations. Leveraging the rare opportunity to examine the effects of a policy that remained in force for a limited period, our empirical investigation employs a Complementary Log-Log model to analyse the starting rate, that is, the transition rate from non-use to use. To do so, we use self-reported data on the age of first cannabis use. Our results suggest that the implementation of stricter punishments has a significant effect in reducing the likelihood of early cannabis use initiation. The observed impact of criminalisation is limited in younger ages and diminished as adulthood approaches. This paper also discusses other considerations related to the social costs of criminalisation, which should also be taken into account in the ongoing policy debate.

Plasma metabolomics profiling of 580 patients from an Early Detection Research Network prostate cancer cohort.

Prostate cancer is the second most common cancer in men and affects 1 in 9 men in the United States. Early screening for prostate cancer often involves monitoring levels of prostate-specific antigen (PSA) and performing digital rectal exams. However, a prostate biopsy is always required for definitive cancer diagnosis. The Early Detection Research Network (EDRN) is a consortium within the National Cancer Institute aimed at improving screening approaches and early detection of cancers. As part of this effort, the Weill Cornell EDRN Prostate Cancer has collected and biobanked specimens from men undergoing a prostate biopsy between 2008 and 2017. In this report, we describe blood metabolomics measurements for a subset of this population. The dataset includes detailed clinical and prospective records for 580 patients who underwent prostate biopsy, 287 of which were subsequentially diagnosed with prostate cancer, combined with profiling of 1,482 metabolites from plasma samples collected at the time of biopsy. We expect this dataset to provide a valuable resource for scientists investigating prostate cancer metabolism.

Non-prescribed pharmaceutical stimulants use among adolescents: A way to self-care or peer success?

BACKGROUND: the use of pharmaceutical stimulants without a medical prescription (PSWMP) among adolescents is considered an established public health issue. The present study aimed to investigate the potential links between different patterns of non-medical use of pharmaceutical stimulants, psycho-social factors, and other risky behaviours (e.g. psychoactive substance use). METHODS: For this purpose, data from a sample of 14,685 adolescents aged 15-19 participating in the ESPAD®Italia 2019 study were analysed by conducting descriptive analyses and multinomial logistic regressions. RESULTS: The findings highlight the key role of psycho-social factors and engagement in other risky behaviours in either reducing or promoting the risk of PSWMP use. Particularly, being satisfied with peer relationships and with oneself is significantly associated with lower use of PSWMP. Conversely, the consumption of other psychoactive substances (both legal and illegal) and engagement in other risky behaviours (e.g., gambling and cyberbullying) may increase this phenomenon. CONCLUSIONS: Considering their representativeness, the results of the present study could be used as groundwork for the development of effective and targeted prevention programs and interventions.

A multimodal atlas of tumour metabolism reveals the architecture of gene-metabolite covariation.

Tumour metabolism is controlled by coordinated changes in metabolite abundance and gene expression, but simultaneous quantification of metabolites and transcripts in primary tissue is rare. To overcome this limitation and to study gene-metabolite covariation in cancer, we assemble the Cancer Atlas of Metabolic Profiles of metabolomic and transcriptomic data from 988 tumour and control specimens spanning 11 cancer types in published and newly generated datasets. Meta-analysis of the Cancer Atlas of Metabolic Profiles reveals two classes of gene-metabolite covariation that transcend cancer types. The first corresponds to gene-metabolite pairs engaged in direct enzyme-substrate interactions, identifying putative genes controlling metabolite pool sizes. A second class of gene-metabolite covariation represents a small number of hub metabolites, including quinolinate and nicotinamide adenine dinucleotide, which correlate to many genes specifically expressed in immune cell populations. These results provide evidence that gene-metabolite covariation in cellularly heterogeneous tissue arises, in part, from both mechanistic interactions between genes and metabolites, and from remodelling of the bulk metabolome in specific immune microenvironments.

piTracer - Automatic reconstruction of molecular cascades for the identification of synergistic drug targets.

Cancer cells frequently undergo metabolic reprogramming as a mechanism of resistance against chemotherapeutic drugs. Metabolomic profiling provides a direct readout of metabolic changes and can thus be used to identify these tumor escape mechanisms. Here, we introduce piTracer, a computational tool that uses multi-scale molecular networks to identify potential combination therapies from pre- and post-treatment metabolomics data. We first demonstrate piTracer’s core ability to reconstruct cellular cascades by inspecting well-characterized molecular pathways and previously studied associations between genetic variants and metabolite levels. We then apply a new gene ranking algorithm on differential metabolomic profiles from human breast cancer cells after glutaminase inhibition. Four of the automatically identified gene targets were experimentally tested by simultaneous inhibition of the respective targets and glutaminase. Of these combination treatments, two were be confirmed to induce synthetic lethality in the cell line. In summary, piTracer integrates the molecular monitoring of escape mechanisms into comprehensive pathway networks to accelerate drug target identification. The tool is open source and can be accessed at https://github.com/krumsieklab/pitracer .

Alcohol versus combined alcohol and energy drinks consumption: Risk behaviors and consumption patterns among European students.

INTRODUCTION: Recent research found that drinking alcohol mixed with energy drinks (AmED) could be riskier than drinking alcohol alone. Our aim was to compare rates of risk behaviors in consumers of AmED versus exclusive alcohol drinkers, matching them based on their drinking frequency. METHODS: Data about 16-year-old students who reported the number of occasions on which they had drunk AmED or alcohol only in the preceding 12 months (n = 32,848) were drawn from the 2019 ESPAD study. After matching for consumption frequency, the sample consisted of 22,370 students (11,185 AmED consumers and 11,185 exclusive alcohol drinkers). Key predictors comprised substance use, other individual risk behaviors, and family characteristics (parental regulation, monitoring, and caring). RESULTS: The multivariate analysis showed significantly higher odds of being AmED consumers compared to being exclusive alcohol drinkers in the majority of the investigated risk behaviors, including: daily tobacco smoking, illicit drug use, heavy episodic drinking, truancy at school, engaging in physical fights and serious arguments, having troubles with the police, and having unprotected sexual intercourse. Instead, lower odds were found for reporting high parents' educational level, medium and low family economic status, perceived possibility to freely talk about problems to family members, spending free time reading books or other hobbies. CONCLUSIONS: Our study shows that, given the same consumption frequency in the past year, AmED consumers typically reported higher associations with risk-taking behaviors compared to exclusive alcohol drinkers. These findings advance past research that failed to control for the frequency of AmED use versus exclusive alcohol consumption.

A Novel Methodological Approach to Measure Linear Trends in Health Inequalities: Proof of Concept With Adolescent Smoking in Europe.

We describe a new method for presenting and interpreting linear trends in health inequalities, and present a proof-of-concept analysis of inequalities in smoking among adolescents in Europe. We estimated the regression line of the assumed linear relationship between smoking prevalence in low- and high-socioeconomic status (SES) youth over time. Using simulation, we constructed a 95% confidence interval (CI) for the smoking prevalence in low-SES youth for when this would be 0% in high-SES youth, and we calculated the likelihood of eradicating smoking inequality (<5% for both low and high SES). This method was applied to data on adolescents aged 15-16 years (n = 250,326) from 23 European countries, derived from the 2003-2015 European Survey Project on Alcohol and Other Drugs. Smoking prevalence decreased more slowly among low- than among high-SES adolescents. The estimated smoking prevalence was 9.4% (95% CI: 6.1, 12.7) for boys and 5.4% (95% CI: 1.4, 9.2) for girls with low SES when 0% with high SES. The likelihood of eradicating smoking inequality was <1% for boys and 37% for girls. We conclude that this novel methodological approach to trends in health inequalities is feasible in practice. Applying it to trends in smoking inequalities among adolescents in Europe, we found that Europe is currently not on track to eradicate youth smoking across SES groups.

rox: A Statistical Model for Regression with Missing Values.

High-dimensional omics datasets frequently contain missing data points, which typically occur due to concentrations below the limit of detection (LOD) of the profiling platform. The presence of such missing values significantly limits downstream statistical analysis and result interpretation. Two common techniques to deal with this issue include the removal of samples with missing values and imputation approaches that substitute the missing measurements with reasonable estimates. Both approaches, however, suffer from various shortcomings and pitfalls. In this paper, we present "rox", a novel statistical model for the analysis of omics data with missing values without the need for imputation. The model directly incorporates missing values as "low" concentrations into the calculation. We show the superiority of rox over common approaches on simulated data and on six metabolomics datasets. Fully leveraging the information contained in LOD-based missing values, rox provides a powerful tool for the statistical analysis of omics data.

Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS.

BACKGROUND: Acute respiratory distress syndrome (ARDS), a life-threatening condition during critical illness, is a common complication of COVID-19. It can originate from various disease etiologies, including severe infections, major injury, or inhalation of irritants. ARDS poses substantial clinical challenges due to a lack of etiology-specific therapies, multisystem involvement, and heterogeneous, poor patient outcomes. A molecular comparison of ARDS groups holds the potential to reveal common and distinct mechanisms underlying ARDS pathogenesis. METHODS: We performed a comparative analysis of urine-based metabolomics and proteomics profiles from COVID-19 ARDS patients (n = 42) and bacterial sepsis-induced ARDS patients (n = 17). To this end, we used two different approaches, first we compared the molecular omics profiles between ARDS groups, and second, we correlated clinical manifestations within each group with the omics profiles. RESULTS: The comparison of the two ARDS etiologies identified 150 metabolites and 70 proteins that were differentially abundant between the two groups. Based on these findings, we interrogated the interplay of cell adhesion/extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis through a multi-omic network approach. Moreover, we identified a proteomic signature associated with mortality in COVID-19 ARDS patients, which contained several proteins that had previously been implicated in clinical manifestations frequently linked with ARDS pathogenesis. CONCLUSION: In summary, our results provide evidence for significant molecular differences in ARDS patients from different etiologies and a potential synergy of extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis. The proteomic mortality signature should be further investigated in future studies to develop prediction models for COVID-19 patient outcomes.

Multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS.

BACKGROUND: Acute respiratory distress syndrome (ARDS), a life-threatening condition characterized by hypoxemia and poor lung compliance, is associated with high mortality. ARDS induced by COVID-19 has similar clinical presentations and pathological manifestations as non-COVID-19 ARDS. However, COVID-19 ARDS is associated with a more protracted inflammatory respiratory failure compared to traditional ARDS. Therefore, a comprehensive molecular comparison of ARDS of different etiologies groups may pave the way for more specific clinical interventions. METHODS AND FINDINGS: In this study, we compared COVID-19 ARDS (n = 43) and bacterial sepsis-induced (non-COVID-19) ARDS (n = 24) using multi-omic plasma profiles covering 663 metabolites, 1,051 lipids, and 266 proteins. To address both between- and within- ARDS group variabilities we followed two approaches. First, we identified 706 molecules differently abundant between the two ARDS etiologies, revealing more than 40 biological processes differently regulated between the two groups. From these processes, we assembled a cascade of therapeutically relevant pathways downstream of sphingosine metabolism. The analysis suggests a possible overactivation of arginine metabolism involved in long-term sequelae of ARDS and highlights the potential of JAK inhibitors to improve outcomes in bacterial sepsis-induced ARDS. The second part of our study involved the comparison of the two ARDS groups with respect to clinical manifestations. Using a data-driven multi-omic network, we identified signatures of acute kidney injury (AKI) and thrombocytosis within each ARDS group. The AKI-associated network implicated mitochondrial dysregulation which might lead to post-ARDS renal-sequalae. The thrombocytosis-associated network hinted at a synergy between prothrombotic processes, namely IL-17, MAPK, TNF signaling pathways, and cell adhesion molecules. Thus, we speculate that combination therapy targeting two or more of these processes may ameliorate thrombocytosis-mediated hypercoagulation. CONCLUSION: We present a first comprehensive molecular characterization of differences between two ARDS etiologies-COVID-19 and bacterial sepsis. Further investigation into the identified pathways will lead to a better understanding of the pathophysiological processes, potentially enabling novel therapeutic interventions.

Multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS.

Background: Acute respiratory distress syndrome (ARDS), a life-threatening condition characterized by hypoxemia and poor lung compliance, is associated with high mortality. ARDS induced by COVID-19 has similar clinical presentations and pathological manifestations as non-COVID-19 ARDS. However, COVID-19 ARDS is associated with a more protracted inflammatory respiratory failure compared to traditional ARDS. Therefore, a comprehensive molecular comparison of ARDS of different etiologies groups may pave the way for more specific clinical interventions. Methods and Findings: In this study, we compared COVID-19 ARDS (n=43) and bacterial sepsis-induced (non-COVID-19) ARDS (n=24) using multi-omic plasma profiles covering 663 metabolites, 1,051 lipids, and 266 proteins. To address both between- and within-ARDS group variabilities we followed two approaches. First, we identified 706 molecules differently abundant between the two ARDS etiologies, revealing more than 40 biological processes differently regulated between the two groups. From these processes, we assembled a cascade of therapeutically relevant pathways downstream of sphingosine metabolism. The analysis suggests a possible overactivation of arginine metabolism involved in long-term sequelae of ARDS and highlights the potential of JAK inhibitors to improve outcomes in bacterial sepsis-induced ARDS. The second part of our study involved the comparison of the two ARDS groups with respect to clinical manifestations. Using a data-driven multi-omic network, we identified signatures of acute kidney injury (AKI) and thrombocytosis within each ARDS group. The AKI-associated network implicated mitochondrial dysregulation which might lead to post-ARDS renal-sequalae. The thrombocytosis-associated network hinted at a synergy between prothrombotic processes, namely IL-17, MAPK, TNF signaling pathways, and cell adhesion molecules. Thus, we speculate that combination therapy targeting two or more of these processes may ameliorate thrombocytosis-mediated hypercoagulation. Conclusion: We present a first comprehensive molecular characterization of differences between two ARDS etiologies - COVID-19 and bacterial sepsis. Further investigation into the identified pathways will lead to a better understanding of the pathophysiological processes, potentially enabling novel therapeutic interventions.

Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS.

Acute respiratory distress syndrome (ARDS), a life-threatening condition during critical illness, is a common complication of COVID-19. It can originate from various disease etiologies, including severe infections, major injury, or inhalation of irritants. ARDS poses substantial clinical challenges due to a lack of etiology-specific therapies, multisystem involvement, and heterogeneous, poor patient outcomes. A molecular comparison of ARDS groups holds the potential to reveal common and distinct mechanisms underlying ARDS pathogenesis. In this study, we performed a comparative analysis of urine-based metabolomics and proteomics profiles from COVID-19 ARDS patients (n = 42) and bacterial sepsis-induced ARDS patients (n = 17). The comparison of these ARDS etiologies identified 150 metabolites and 70 proteins that were differentially abundant between the two groups. Based on these findings, we interrogated the interplay of cell adhesion/extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis through a multi-omic network approach. Moreover, we identified a proteomic signature associated with mortality in COVID-19 ARDS patients, which contained several proteins that had previously been implicated in clinical manifestations frequently linked with ARDS pathogenesis. In summary, our results provide evidence for significant molecular differences in ARDS patients from different etiologies and a potential synergy of extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis. The proteomic mortality signature should be further investigated in future studies to develop prediction models for COVID-19 patient outcomes.

Integrative metabolomic and proteomic signatures define clinical outcomes in severe COVID-19.

The coronavirus disease-19 (COVID-19) pandemic has ravaged global healthcare with previously unseen levels of morbidity and mortality. In this study, we performed large-scale integrative multi-omics analyses of serum obtained from COVID-19 patients with the goal of uncovering novel pathogenic complexities of this disease and identifying molecular signatures that predict clinical outcomes. We assembled a network of protein-metabolite interactions through targeted metabolomic and proteomic profiling in 330 COVID-19 patients compared to 97 non-COVID, hospitalized controls. Our network identified distinct protein-metabolite cross talk related to immune modulation, energy and nucleotide metabolism, vascular homeostasis, and collagen catabolism. Additionally, our data linked multiple proteins and metabolites to clinical indices associated with long-term mortality and morbidity. Finally, we developed a novel composite outcome measure for COVID-19 disease severity based on metabolomics data. The model predicts severe disease with a concordance index of around 0.69, and shows high predictive power of 0.83-0.93 in two independent datasets.

Mitonuclear genotype remodels the metabolic and microenvironmental landscape of Hürthle cell carcinoma.

Hürthle cell carcinomas (HCCs) display two exceptional genotypes: near-homoplasmic mutation of mitochondrial DNA (mtDNA) and genome-wide loss of heterozygosity (gLOH). To understand the phenotypic consequences of these genetic alterations, we analyzed genomic, metabolomic, and immunophenotypic data of HCC and other thyroid cancers. Both mtDNA mutations and profound depletion of citrate pools are common in HCC and other thyroid malignancies, suggesting that thyroid cancers are broadly equipped to survive tricarboxylic acid cycle impairment, whereas metabolites in the reduced form of NADH-dependent lysine degradation pathway were elevated exclusively in HCC. The presence of gLOH was not associated with metabolic phenotypes but rather with reduced immune infiltration, indicating that gLOH confers a selective advantage partially through immunosuppression. Unsupervised multimodal clustering revealed four clusters of HCC with distinct clinical, metabolomic, and microenvironmental phenotypes but overlapping genotypes. These findings chart the metabolic and microenvironmental landscape of HCC and shed light on the interaction between genotype, metabolism, and the microenvironment in cancer.

The Prostate Cancer Androgen Receptor Cistrome in African American Men Associates with Upregulation of Lipid Metabolism and Immune Response.

African-American (AA) men are more likely to be diagnosed with and die from prostate cancer than European American (EA) men. Despite the central role of the androgen receptor (AR) transcription factor in prostate cancer, little is known about the contribution of epigenetics to observed racial disparities. We performed AR chromatin immunoprecipitation sequencing on primary prostate tumors from AA and EA men, finding that sites with greater AR binding intensity in AA relative to EA prostate cancer are enriched for lipid metabolism and immune response genes. Integration with transcriptomic and metabolomic data demonstrated coinciding upregulation of lipid metabolism gene expression and increased lipid levels in AA prostate cancer. In a metastatic prostate cancer cohort, upregulated lipid metabolism associated with poor prognosis. These findings offer the first insights into ancestry-specific differences in the prostate cancer AR cistrome. The data suggest a model whereby increased androgen signaling may contribute to higher levels of lipid metabolism, immune response, and cytokine signaling in AA prostate tumors. Given the association of upregulated lipogenesis with prostate cancer progression, our study provides a plausible biological explanation for the higher incidence and aggressiveness of prostate cancer observed in AA men. SIGNIFICANCE: With immunotherapies and inhibitors of metabolic enzymes in clinical development, the altered lipid metabolism and immune response in African-American men provides potential therapeutic opportunities to attenuate racial disparities in prostate cancer.

E-cigarette use and conventional cigarette smoking among European students: findings from the 2019 ESPAD survey.

BACKGROUND AND AIMS: Representative data on e-cigarette use among European adolescents are scant. This study reports current vaping and tobacco smoking individual and country-specific correlates among European students. DESIGN: Cross-sectional survey: 2019 European School Survey Project on Alcohol and Other Drugs (ESPAD) collecting data on risk behaviours on a representative sample of 16-year-old students. SETTING: A total of 35 European countries, 25-30 with Tobacco Control Scale (TCS) and TCS components PARTICIPANTS: A total of 99 648 students (49.1% males) turning 16 years in the survey year. MEASUREMENTS: Data on current cigarette and e-cigarette use were gathered through a self-administered questionnaire which also collected socio-demographics and individual and family characteristics. ESPAD data were integrated with country-level data on TCS and selected TCS parameters to assess their association with the prevalence of current cigarette and e-cigarette use. FINDINGS: Of the 99 648 participating students, 12.4% were current e-cigarette users, from 5.5% in Serbia to 41.4% in Monaco; 19.3% current smokers, from 5.1% in Iceland to 32.4% in Italy. Compared with non-users, current e-cigarette users less frequently came from an average well-off family [odds ratio (OR) = 0.85, 95% confidence interval (CI) = 0.80-0.90] and lived in countries with higher cigarette prices (OR = 0.71, 95% CI = 0.50-0.99), restrictive measures on tobacco advertising and promotion (OR = 0.79, 95% CI = 0.63-0.99) and intermediate implementation of tobacco control measures (OR = 0.57, 95% CI = 0.38-0.85). Current vapers were more frequently life ever smokers (OR = 7.31, 95% CI = 6.47-8.25), were early smokers (OR = 4.35, 95% CI = 3.66-5.17), males (OR = 1.61, 95% CI = 1.55-1.67), from non-traditional families (OR = 1.43, 95% CI = 1.34-1.53), with relatively low parental education (OR = 1.15, 95% CI = 1.10-1.20). Compared with non-smokers, current smokers had similar family characteristics to vapers, and were less likely to live in countries with higher cigarette prices (OR = 0.70, 95% CI = 0.49-0.99) and higher spending on public anti-tobacco media campaigns (OR = 0.23, 95% CI = 0.10-0.50). CONCLUSIONS: E-cigarette use among European adolescents is associated with weaker tobacco control measures, particularly on tobacco price, advertising and promotion. Besides preventing tobacco smoking, the adoption of governmental tobacco control policies in European countries also seems to contribute to the prevention of vaping among adolescents.

Angiopoietin 2 Is Associated with Vascular Necroptosis Induction in Coronavirus Disease 2019 Acute Respiratory Distress Syndrome.

Vascular injury is a well-established, disease-modifying factor in acute respiratory distress syndrome (ARDS) pathogenesis. Recently, coronavirus disease 2019 (COVID-19)-induced injury to the vascular compartment has been linked to complement activation, microvascular thrombosis, and dysregulated immune responses. This study sought to assess whether aberrant vascular activation in this prothrombotic context was associated with the induction of necroptotic vascular cell death. To achieve this, proteomic analysis was performed on blood samples from COVID-19 subjects at distinct time points during ARDS pathogenesis (hospitalized at risk, N = 59; ARDS, N = 31; and recovery, N = 12). Assessment of circulating vascular markers in the at-risk cohort revealed a signature of low vascular protein abundance that tracked with low platelet levels and increased mortality. This signature was replicated in the ARDS cohort and correlated with increased plasma angiopoietin 2 levels. COVID-19 ARDS lung autopsy immunostaining confirmed a link between vascular injury (angiopoietin 2) and platelet-rich microthrombi (CD61) and induction of necrotic cell death [phosphorylated mixed lineage kinase domain-like (pMLKL)]. Among recovery subjects, the vascular signature identified patients with poor functional outcomes. Taken together, this vascular injury signature was associated with low platelet levels and increased mortality and can be used to identify ARDS patients most likely to benefit from vascular targeted therapies.