Scientists have been trying to understand the molecular mechanisms of diseases to design preventive and therapeutic strategies for a long time. For some diseases, it has become evident that it is not ...enough to obtain a catalogue of the disease-related genes but to uncover how disruptions of molecular networks in the cell give rise to disease phenotypes. Moreover, with the unprecedented wealth of information available, even obtaining such catalogue is extremely difficult.
We developed a comprehensive gene-disease association database by integrating associations from several sources that cover different biomedical aspects of diseases. In particular, we focus on the current knowledge of human genetic diseases including mendelian, complex and environmental diseases. To assess the concept of modularity of human diseases, we performed a systematic study of the emergent properties of human gene-disease networks by means of network topology and functional annotation analysis. The results indicate a highly shared genetic origin of human diseases and show that for most diseases, including mendelian, complex and environmental diseases, functional modules exist. Moreover, a core set of biological pathways is found to be associated with most human diseases. We obtained similar results when studying clusters of diseases, suggesting that related diseases might arise due to dysfunction of common biological processes in the cell.
For the first time, we include mendelian, complex and environmental diseases in an integrated gene-disease association database and show that the concept of modularity applies for all of them. We furthermore provide a functional analysis of disease-related modules providing important new biological insights, which might not be discovered when considering each of the gene-disease association repositories independently. Hence, we present a suitable framework for the study of how genetic and environmental factors, such as drugs, contribute to diseases.
The gene-disease networks used in this study and part of the analysis are available at http://ibi.imim.es/DisGeNET/DisGeNETweb.html#Download.
Mental disorders have become a major concern in public health, and they are one of the main causes of the overall disease burden worldwide. Social media platforms allow us to observe the activities, ...thoughts, and feelings of people's daily lives, including those of patients suffering from mental disorders. There are studies that have analyzed the influence of mental disorders, including depression, in the behavior of social media users, but they have been usually focused on messages written in English.
The study aimed to identify the linguistic features of tweets in Spanish and the behavioral patterns of Twitter users who generate them, which could suggest signs of depression.
This study was developed in 2 steps. In the first step, the selection of users and the compilation of tweets were performed. A total of 3 datasets of tweets were created, a depressive users dataset (made up of the timeline of 90 users who explicitly mentioned that they suffer from depression), a depressive tweets dataset (a manual selection of tweets from the previous users, which included expressions indicative of depression), and a control dataset (made up of the timeline of 450 randomly selected users). In the second step, the comparison and analysis of the 3 datasets of tweets were carried out.
In comparison with the control dataset, the depressive users are less active in posting tweets, doing it more frequently between 23:00 and 6:00 (P<.001). The percentage of nouns used by the control dataset almost doubles that of the depressive users (P<.001). By contrast, the use of verbs is more common in the depressive users dataset (P<.001). The first-person singular pronoun was by far the most used in the depressive users dataset (80%), and the first- and the second-person plural pronouns were the least frequent (0.4% in both cases), this distribution being different from that of the control dataset (P<.001). Emotions related to sadness, anger, and disgust were more common in the depressive users and depressive tweets datasets, with significant differences when comparing these datasets with the control dataset (P<.001). As for negation words, they were detected in 34% and 46% of tweets in among depressive users and in depressive tweets, respectively, which are significantly different from the control dataset (P<.001). Negative polarity was more frequent in the depressive users (54%) and depressive tweets (65%) datasets than in the control dataset (43.5%; P<.001).
Twitter users who are potentially suffering from depression modify the general characteristics of their language and the way they interact on social media. On the basis of these changes, these users can be monitored and supported, thus introducing new opportunities for studying depression and providing additional health care services to people with this disorder.
Chronic thromboembolic pulmonary hypertension, a rare complication of acute pulmonary embolism, is characterized by fibrothrombotic obstructions of large pulmonary arteries combined with small-vessel ...arteriopathy. It can be cured by pulmonary endarterectomy, and can be clinically improved by medical therapy in inoperable patients. A European registry was set up in 27 centers to evaluate long-term outcome and outcome correlates in 2 distinct populations of operated and not-operated patients who have chronic thromboembolic pulmonary hypertension.
A total of 679 patients newly diagnosed with chronic thromboembolic pulmonary hypertension were prospectively included over a 24-month period. Estimated survival at 1, 2, and 3 years was 93% (95% confidence interval CI, 90-95), 91% (95% CI, 87-93), and 89% (95% CI, 86-92) in operated patients (n=404), and only 88% (95% CI, 83-91), 79% (95% CI, 74-83), and 70% (95% CI, 64-76) in not-operated patients (n=275). In both operated and not-operated patients, pulmonary arterial hypertension-targeted therapy did not affect survival estimates significantly. Mortality was associated with New York Heart Association functional class IV (hazard ratio HR, 4.16; 95% CI, 1.49-11.62; P=0.0065 and HR, 4.76; 95% CI, 1.76-12.88; P=0.0021), increased right atrial pressure (HR, 1.34; 95% CI, 0.95-1.90; P=0.0992 and HR, 1.50; 95% CI, 1.20-1.88; P=0.0004), and a history of cancer (HR, 3.02; 95% CI, 1.36-6.69; P=0.0065 and HR, 2.15; 95% CI, 1.18-3.94; P=0.0129) in operated and not-operated patients, respectively. Additional correlates of mortality were bridging therapy with pulmonary arterial hypertension-targeted drugs, postoperative pulmonary hypertension, surgical complications, and additional cardiac procedures in operated patients, and comorbidities such as coronary disease, left heart failure, and chronic obstructive pulmonary disease in not-operated patients.
The long-term prognosis of operated patients currently is excellent and better than the outcome of not-operated patients.
Abstract Plant virus infection involves the production of viral small RNAs (vsRNAs) with the potential to associate with distinct Argonaute (AGO)-containing silencing complexes and mediate diverse ...silencing effects on RNA and chromatin. We used multiplexed, high-throughput pyrosequencing to profile populations of vsRNAs from plants infected with viruses from different genera. Sense and antisense vsRNAs of 20 to 24 nucleotides (nts) spread throughout the entire viral genomes in an overlapping configuration; virtually all genomic nucleotide positions were represented in the data set. We present evidence to suggest that every genomic position could be a putative cleavage site for vsRNA formation, although viral genomes contain specific regions that serve as preferential sources of vsRNA production. Hotspots for vsRNAs of 21-, 22-, and 24-nt usually coincide in the same genomic regions, indicating similar target affinities among Dicer-like (DCL) enzymes. In the light of our results, the overall contribution of perfectly base paired double-stranded RNA and imperfectly base paired structures within single-stranded RNA to vsRNA formation is discussed. Our census of vsRNAs extends the current view of the distribution and composition of vsRNAs in virus-infected plants, and contributes to a better understanding of vsRNA biogenesis.
Due to the heterogeneity of existing European sources of observational healthcare data, data source-tailored choices are needed to execute multi-data source, multi-national epidemiological studies. ...This makes transparent documentation paramount. In this proof-of-concept study, a novel standard data derivation procedure was tested in a set of heterogeneous data sources. Identification of subjects with type 2 diabetes (T2DM) was the test case. We included three primary care data sources (PCDs), three record linkage of administrative and/or registry data sources (RLDs), one hospital and one biobank. Overall, data from 12 million subjects from six European countries were extracted. Based on a shared event definition, sixteeen standard algorithms (components) useful to identify T2DM cases were generated through a top-down/bottom-up iterative approach. Each component was based on one single data domain among diagnoses, drugs, diagnostic test utilization and laboratory results. Diagnoses-based components were subclassified considering the healthcare setting (primary, secondary, inpatient care). The Unified Medical Language System was used for semantic harmonization within data domains. Individual components were extracted and proportion of population identified was compared across data sources. Drug-based components performed similarly in RLDs and PCDs, unlike diagnoses-based components. Using components as building blocks, logical combinations with AND, OR, AND NOT were tested and local experts recommended their preferred data source-tailored combination. The population identified per data sources by resulting algorithms varied from 3.5% to 15.7%, however, age-specific results were fairly comparable. The impact of individual components was assessed: diagnoses-based components identified the majority of cases in PCDs (93-100%), while drug-based components were the main contributors in RLDs (81-100%). The proposed data derivation procedure allowed the generation of data source-tailored case-finding algorithms in a standardized fashion, facilitated transparent documentation of the process and benchmarking of data sources, and provided bases for interpretation of possible inter-data source inconsistency of findings in future studies.
Abstract
Motivation
The study of comorbidities is a major priority due to their impact on life expectancy, quality of life and healthcare cost. The availability of electronic health records (EHRs) ...for data mining offers the opportunity to discover disease associations and comorbidity patterns from the clinical history of patients gathered during routine medical care. This opens the need for analytical tools for detection of disease comorbidities, including the investigation of their underlying genetic basis.
Results
We present comoRbidity, an R package aimed at providing a systematic and comprehensive analysis of disease comorbidities from both the clinical and molecular perspectives. comoRbidity leverages from (i) user provided clinical data from EHR databases (the clinical comorbidity analysis) and (ii) genotype-phenotype information of the diseases under study (the molecular comorbidity analysis) for a comprehensive analysis of disease comorbidities. The clinical comorbidity analysis enables identifying significant disease comorbidities from clinical data, including sex and age stratification and temporal directionality analyses, while the molecular comorbidity analysis supports the generation of hypothesis on the underlying mechanisms of the disease comorbidities by exploring shared genes among disorders. The open-source comoRbidity package is a software tool aimed at expediting the integrative analysis of disease comorbidities by incorporating several analytical and visualization functions.
Availability and implementation
https://bitbucket.org/ibi_group/comorbidity
Supplementary information
Supplementary data are available at Bioinformatics online.
Chronic thromboembolic pulmonary hypertension (CTEPH) is often a sequel of venous thromboembolism with fatal natural history; however, many cases can be cured by pulmonary endarterectomy. The ...clinical characteristics and current management of patients enrolled in an international CTEPH registry was investigated.
The international registry included 679 newly diagnosed (≤6 months) consecutive patients with CTEPH, from February 2007 until January 2009. Diagnosis was confirmed by right heart catheterization, ventilation-perfusion lung scintigraphy, computerized tomography, and/or pulmonary angiography. At diagnosis, a median of 14.1 months had passed since first symptoms; 427 patients (62.9%) were considered operable, 247 (36.4%) nonoperable, and 5 (0.7%) had no operability data; 386 patients (56.8%, ranging from 12.0%- 60.9% across countries) underwent surgery. Operable patients did not differ from nonoperable patients relative to symptoms, New York Heart Association class, and hemodynamics. A history of acute pulmonary embolism was reported for 74.8% of patients (77.5% operable, 70.0% nonoperable). Associated conditions included thrombophilic disorder in 31.9% (37.1% operable, 23.5% nonoperable) and splenectomy in 3.4% of patients (1.9% operable, 5.7% nonoperable). At the time of CTEPH diagnosis, 37.7% of patients initiated at least 1 pulmonary arterial hypertension-targeted therapy (28.3% operable, 53.8% nonoperable). Pulmonary endarterectomy was performed with a 4.7% documented mortality rate.
Despite similarities in clinical presentation, operable and nonoperable CTEPH patients may have distinct associated medical conditions. Operability rates vary considerably across countries, and a substantial number of patients (operable and nonoperable) receive off-label pulmonary arterial hypertension-targeted treatments.
Thrombosis with thrombocytopenia syndrome (TTS) has been identified as a rare adverse event following some COVID-19 vaccines. Various guidelines have been issued on the treatment of TTS. We aimed to ...characterize the treatment of TTS and other thromboembolic events (venous thromboembolism (VTE), and arterial thromboembolism (ATE) after COVID-19 vaccination and compared to historical (pre-vaccination) data in Europe and the US.
We conducted an international network cohort study using 8 primary care, outpatient, and inpatient databases from France, Germany, Netherlands, Spain, The United Kingdom, and The United States. We investigated treatment pathways after the diagnosis of TTS, VTE, or ATE for a pre-vaccination (background) cohort (01/2017-11/2020), and a vaccinated cohort of people followed for 28 days after a dose of any COVID-19 vaccine recorded from 12/2020 onwards).
Great variability was observed in the proportion of people treated (with any recommended therapy) across databases, both before and after vaccination. Most patients with TTS received heparins, platelet aggregation inhibitors, or direct Xa inhibitors. The majority of VTE patients (before and after vaccination) were first treated with heparins in inpatient settings and direct Xa inhibitors in outpatient settings. In ATE patients, treatments were also similar before and after vaccinations, with platelet aggregation inhibitors prescribed most frequently. Inpatient and claims data also showed substantial heparin use.
TTS, VTE, and ATE after COVID-19 vaccination were treated similarly to background events. Heparin use post-vaccine TTS suggests most events were not identified as vaccine-induced thrombosis with thrombocytopenia by the treating clinicians.
Increased tetrahydrobiopterin (BH4) generated in injured sensory neurons contributes to increased pain sensitivity and its persistence. GTP cyclohydrolase 1 (GCH1) is the rate-limiting enzyme in the ...de novo BH4 synthetic pathway, and human single-nucleotide polymorphism studies, together with mouse genetic modeling, have demonstrated that decreased GCH1 leads to both reduced BH4 and pain. However, little is known about the regulation of
expression upon nerve injury and whether this could be modulated as an analgesic therapeutic intervention. We performed a phenotypic screen using about 1000 bioactive compounds, many of which are target-annotated FDA-approved drugs, for their effect on regulating
expression in rodent injured dorsal root ganglion neurons. From this approach, we uncovered relevant pathways that regulate
expression in sensory neurons. We report that EGFR/KRAS signaling triggers increased
expression and contributes to neuropathic pain; conversely, inhibiting EGFR suppressed GCH1 and BH4 and exerted analgesic effects, suggesting a molecular link between EGFR/KRAS and pain perception. We also show that GCH1/BH4 acts downstream of KRAS to drive lung cancer, identifying a potentially druggable pathway. Our screen shows that pharmacologic modulation of GCH1 expression and BH4 could be used to develop pharmacological treatments to alleviate pain and identified a critical role for EGFR-regulated GCH1/BH4 expression in neuropathic pain and cancer in rodents.
Introduction
Individual case reports are the main asset in pharmacovigilance signal management. Signal validation is the first stage after signal detection and aims to determine if there is ...sufficient evidence to justify further assessment. Throughout signal management, a prioritization of signals is continually made. Routinely collected health data can provide relevant contextual information but are primarily used at a later stage in pharmacoepidemiological studies to assess communicated signals.
Objective
The aim of this study was to examine the feasibility and utility of analysing routine health data from a multinational distributed network to support signal validation and prioritization and to reflect on key user requirements for these analyses to become an integral part of this process.
Methods
Statistical signal detection was performed in VigiBase, the WHO global database of individual case safety reports, targeting generic manufacturer drugs and 16 prespecified adverse events. During a 5-day study-a-thon, signal validation and prioritization were performed using information from VigiBase, regulatory documents and the scientific literature alongside descriptive analyses of routine health data from 10 partners of the European Health Data and Evidence Network (EHDEN). Databases included in the study were from the UK, Spain, Norway, the Netherlands and Serbia, capturing records from primary care and/or hospitals.
Results
Ninety-five statistical signals were subjected to signal validation, of which eight were considered for descriptive analyses in the routine health data. Design, execution and interpretation of results from these analyses took up to a few hours for each signal (of which 15–60 minutes were for execution) and informed decisions for five out of eight signals. The impact of insights from the routine health data varied and included possible alternative explanations, potential public health and clinical impact and feasibility of follow-up pharmacoepidemiological studies. Three signals were selected for signal assessment, two of these decisions were supported by insights from the routine health data. Standardization of analytical code, availability of adverse event phenotypes including bridges between different source vocabularies, and governance around the access and use of routine health data were identified as important aspects for future development.
Conclusions
Analyses of routine health data from a distributed network to support signal validation and prioritization are feasible in the given time limits and can inform decision making. The cost–benefit of integrating these analyses at this stage of signal management requires further research.
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