How are you doing? : emotions and personality in Facebook

User generated content on social media sites is a rich source of information about latent variables of their users. Proper mining of this content provides a shortcut to emotion and personality detection of users without filling out questionnaires. This in turn increases the application potential of personalized services that rely on the knowledge of such latent variables. In this paper we contribute to this emerging domain by studying the relation between emotions expressed in approximately 1 million Facebook (FB) status updates and the users' age, gender and personality. Additionally, we investigate the relations between emotion expression and the time when the status updates were posted. In particular, we find that female users are more emotional in their status posts than male users. In addition, we find a relation between age and sharing of emotions. Older FB users share their feelings more often than young users. In terms of seasons, people post about emotions less frequently in summer. On the other hand, December is a time when people are more likely to share their positive feelings with their friends. We also examine the relation between users' personality and their posts. We find that users who have an open personality express their emotions more frequently, while neurotic users are more reserved to share their feelings

Epigenetic profiling linked to multisystem inflammatory syndrome in children (MIS-C): A multicenter, retrospective study

BACKGROUND: Most children and adolescents infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain asymptomatic or develop a mild coronavirus disease 2019 (COVID-19) that usually does not require medical intervention. However, a small proportion of pediatric patients develop a severe clinical condition, multisystem inflammatory syndrome in children (MIS-C). The involvement of epigenetics in the control of the immune response and viral activity prompted us to carry out an epigenomic study to uncover target loci regulated by DNA methylation that could be altered upon the appearance of MIS-C. METHODS: Peripheral blood samples were recruited from 43 confirmed MIS-C patients. 69 non-COVID-19 pediatric samples and 15 COVID-19 pediatric samples without MIS-C were used as controls. The cases in the two groups were mixed and divided into discovery (MIS-C = 29 and non-MIS-C = 56) and validation (MIS-C = 14 and non-MIS-C = 28) cohorts, and balanced for age, gender and ethnic background. We interrogated 850,000 CpG sites of the human genome for DNA methylation variants. FINDINGS: The DNA methylation content of 33 CpG loci was linked with the presence of MIS-C. Of these sites, 18 (54.5%) were located in described genes. The top candidate gene was the immune T-cell mediator ZEB2; and others highly ranked candidates included the regulator of natural killer cell functional competence SH2D1B; VWA8, which contains a domain of the Von Willebrand factor A involved in the pediatric hemostasis disease; and human leukocyte antigen complex member HLA-DRB1; in addition to pro-inflammatory genes such as CUL2 and AIM2. The identified loci were used to construct a DNA methylation profile (EPIMISC) that was associated with MIS-C in both cohorts. The EPIMISC signature was also overrepresented in Kawasaki disease patients, a childhood pathology with a possible viral trigger, that shares many of the clinical features of MIS-C. INTERPRETATION: We have characterized DNA methylation loci that are associated with MIS-C diagnosis. The identified genes are likely contributors to the characteristic exaggerated host inflammatory response observed in these patients. The described epigenetic signature could also provide new targets for more specific therapies for the disorder.We thank the Health Department and the Centres de Recerca de Catalunya (CERCA) Programme of the Generalitat de Catalunya, the Josep Carreras Leukaemia Foundation, Fundació La Marató de TV3 and the Cellex Foundation for institutional support. We also wish to thank all the patients, family members and staff from all the units that participated in the studyPeer Reviewed"Article signat per 22 autors/es: Veronica Davalos, Carlos A. García-Prieto, Gerardo Ferrer, Sergio Aguilera-Albesa, Juan Valencia-Ramos, Agustí Rodríguez-Palmero, Montserrat Ruiz, Laura Planas-Serra, Iolanda Jordan, Iosune Alegría, Patricia Flores-Pérez, Verónica Cantarín, Victoria Fumadó, Maria Teresa Viadero, Carlos Rodrigo, Maria Méndez-Hernández, Eduardo López-Granados, Roger Colobran, Jacques G. Rivière, Pere Soler-Palacín, Aurora Pujol, Manel Esteller"Postprint (published version

Computational personality recognition in social media

A variety of approaches have been recently proposed to automatically infer users' personality from their user generated content in social media. Approaches differ in terms of the machine learning algorithms and the feature sets used, type of utilized footprint, and the social media environment used to collect the data. In this paper, we perform a comparative analysis of state-of-the-art computational personality recognition methods on a varied set of social media ground truth data from Facebook, Twitter and YouTube. We answer three questions: (1) Should personality prediction be treated as a multi-label prediction task (i.e., all personality traits of a given user are predicted at once), or should each trait be identified separately? (2) Which predictive features work well across different on-line environments? (3) What is the decay in accuracy when porting models trained in one social media environment to another

Epigenetic profiling linked to multisystem inflammatory syndrome in children (MIS-C): A multicenter, retrospective study

Background Most children and adolescents infected with the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain asymptomatic or develop a mild coronavirus disease 2019 (COVID-19) that usually does not require medical intervention. However, a small proportion of pediatric patients develop a severe clinical condition, multisystem inflammatory syndrome in children (MIS-C). The involvement of epigenetics in the control of the immune response and viral activity prompted us to carry out an epigenomic study to uncover target loci regulated by DNA methylation that could be altered upon the appearance of MIS-C. Methods Peripheral blood samples were recruited from 43 confirmed MIS-C patients. 69 non-COVID-19 pediatric samples and 15 COVID-19 pediatric samples without MIS-C were used as controls. The cases in the two groups were mixed and divided into discovery (MIS-C= 29 and non-MIS-C= 56) and validation (MIS-C= 14 and non-MIS C = 28) cohorts, and balanced for age, gender and ethnic background. We interrogated 850,000 CpG sites of the human genome for DNA methylation variants. Findings The DNA methylation content of 33 CpG loci was linked with the presence of MIS-C. Of these sites, 18 (54.5%) were located in described genes. The top candidate gene was the immune T-cell mediator ZEB2; and others highly ranked candidates included the regulator of natural killer cell functional competence SH2D1B; VWA8, which contains a domain of the Von Willebrand factor A involved in the pediatric hemostasis disease; and human leukocyte antigen complex member HLA-DRB1; in addition to pro-inflammatory genes such as CUL2 and AIM2. The identified loci were used to construct a DNA methylation profile (EPIMISC) that was associated with MIS-C in both cohorts. The EPIMISC signature was also overrepresented in Kawasaki disease patients, a childhood pathology with a possible viral trigger, that shares many of the clinical features of MIS-C. Interpretation We have characterized DNA methylation loci that are associated with MIS-C diagnosis. The identified genes are likely contributors to the characteristic exaggerated host inflammatory response observed in these patients. The described epigenetic signature could also provide new targets for more specific therapies for the disorder.Copyright (c) 2022 The Author(s). Published by Elsevier Ltd

Epigenetic prediction of response to anti-PD-1 treatment in non-small-cell lung cancer: a multicenter, retrospective analysis

Background: Anti-programmed death-1 (PD-1) treatment for advanced non-small-cell lung cancer (NSCLC) has improved the survival of patients. However, a substantial percentage of patients do not respond to this treatment. We examined the use of DNA methylation profiles to determine the efficacy of anti-PD-1 treatment in patients recruited with current stage IV NSCLC. Methods: In this multicentre study, we recruited adult patients from 15 hospitals in France, Spain, and Italy who had histologically proven stage IV NSCLC and had been exposed to PD-1 blockade during the course of the disease. The study structure comprised a discovery cohort to assess the correlation between epigenetic features and clinical benefit with PD-1 blockade and two validation cohorts to assess the validity of our assumptions. We first established an epigenomic profile based on a microarray DNA methylation signature (EPIMMUNE) in a discovery set of tumour samples from patients treated with nivolumab or pembrolizumab. The EPIMMUNE signature was validated in an independent set of patients. A derived DNA methylation marker was validated by a single-methylation assay in a validation cohort of patients. The main study outcomes were progression-free survival and overall survival. We used the Kaplan-Meier method to estimate progression-free and overall survival, and calculated the differences between the groups with the log-rank test. We constructed a multivariate Cox model to identify the variables independently associated with progression-free and overall survival. Findings: Between June 23, 2014, and May 18, 2017, we obtained samples from 142 patients: 34 in the discovery cohort, 47 in the EPIMMUNE validation cohort, and 61 in the derived methylation marker cohort (the T-cell differentiation factor forkhead box P1 [FOXP1]). The EPIMMUNE signature in patients with stage IV NSCLC treated with anti-PD-1 agents was associated with improved progression-free survival (hazard ratio [HR] 0·010, 95% CI 3·29 × 10 −4–0·0282; p=0·0067) and overall survival (0·080, 0·017–0·373; p=0·0012). The EPIMMUNE-positive signature was not associated with PD-L1 expression, the presence of CD8+ cells, or mutational load. EPIMMUNE-negative tumours were enriched in tumour-associated macrophages and neutrophils, cancer-associated fibroblasts, and senescent endothelial cells. The EPIMMUNE-positive signature was associated with improved progression-free survival in the EPIMMUNE validation cohort (0·330, 0·149–0·727; p=0·0064). The unmethylated status of FOXP1 was associated with improved progression-free survival (0·415, 0·209–0·802; p=0·0063) and overall survival (0·409, 0·220–0·780; p=0·0094) in the FOXP1 validation cohort. The EPIMMUNE signature and unmethylated FOXP1 were not associated with clinical benefit in lung tumours that did not receive immunotherapy. Interpretation: Our study shows that the epigenetic milieu of NSCLC tumours indicates which patients are most likely to benefit from nivolumab or pembrolizumab treatments. The methylation status of FOXP1 could be associated with validated predictive biomarkers such as PD-L1 staining and mutational load to better select patients who will experience clinical benefit with PD-1 blockade, and its predictive value should be evaluated in prospective studies