Developed by Shray Alag, The Harker School
Sections: Correlations,
Clinical Trials, and HPO
Navigate: Clinical Trials and HPO
| Name (Synonyms) | Correlation | |
|---|---|---|
| drug1732 | GENETIC Wiki | 0.41 |
| drug5059 | mobile internet survey on self-test Wiki | 0.41 |
| drug2890 | Nutrition Wiki | 0.41 |
| Name (Synonyms) | Correlation | |
|---|---|---|
| D020022 | Genetic Predisposition to Disease NIH | 0.58 |
| D009164 | Mycobacterium Infections NIH | 0.20 |
| D003141 | Communicable Diseases NIH | 0.03 |
| Name (Synonyms) | Correlation |
|---|
Navigate: Correlations HPO
There are 6 clinical trials
This research aims to investigate how exposure to advertising for Electronic Nicotine Delivery Systems (commonly called e-cigarettes) may lead to combustible smoking initiation in adolescents.
Description: Scores are measured by recording the amount of time (reaction time) it takes to categorize smoking-related words with positive (e.g., cool) and negative (e.g., cancer) words. Faster reaction times when categorizing smoking-related words with positive words is evidence of higher positive smoking expectancies.
Measure: change in baseline in implicit positive smoking expectancies, measured by the implicit association test Time: baseline, within 5 minutes post interventionDescription: Eye-tracking will be used to measure the amount of time spent looking at static smoking cues in screen shots taken from e-cigarette advertisements. The amount time spent looking at a smoking cue is a measure how much attention was given to the smoking cue. The longer the looking time, the greater amount of attention.
Measure: Amount of time spent looking at static smoking cues in e-cigarette advertisements Time: approximately 30 minutes post interventionDescription: Scores are measured on a 7-item scale. Positive smoking expectancies will be assessed using the following questions that follow the lead-in, "Please tell me how you feel about the following statements." "I think I would enjoy smoking"; "I think smoking would give me something to do when I'm bored"; "I think smoking would help me deal with problems or stress"; "I think smoking would help me stay thin"; "I think smoking would help me to feel more comfortable at parties"; "I think smoking would be relaxing"; and "I think smoking would make me look older." Responses are yes/no. Responses are coded as "1" for yes and "0" for no. Responses are then summed for a maximum positive smoking expectancy score out of 7. Higher scores mean higher positive smoking expectancies.
Measure: 7-item explicit positive smoking expectancies scale Time: approximately 30 minutes post interventionDescription: This 11-item scale assess social normative beliefs about smoking related to 1) perceived disapproval from family/friends, 2) perceived popularity among successful/elite, and 3) perceived prevalence. Disapproval scale questions are answered using a 4-point Likert scale (1 = Strongly disagree; 4 = Strongly agree). A total disapproval score (ranging from 1 to 4) is calculated by averaging responses to each question. Higher values indicate a higher disapproval score. Popularity scale questions are answered using a 4-point Likert scale (1 = Strongly disagree; 4 = Strongly agree). A total popularity score (ranging from 1 to 4) is calculated by averaging responses to each question. Higher values indicate a higher popularity score. Prevalence scale questions are answered using a percent scale from 0 - 100% in 10% increments. A total prevalence scale (from 0 to 100) is calculated by averaging the responses to each question. Higher values indicate a higher prevalence score.
Measure: 11-item scale that measures social normative beliefs about smoking Time: approximately 30 minutes post interventionDescription: This 3-item instrument is used to predict which never smokers are likely to start smoking by measuring their curiosity to use tobacco products. Item responses are on a 4-point Likert scale (definitely yes, probably yes, probably not, definitely not). To classify a respondent as not susceptible to smoking, the respondent must indicate "definitely not" to all four items. Any other response to any item classifies a respondent as "susceptible."
Measure: A 3-item scale that measures adolescent smoking susceptibility Time: approximately 30 minutes post interventionDescription: Eye-tracking will be used to measure the total amount of time spent looking in realtime at smoking cues in TV commercials for e-cigarettes. The amount of time looking at smoking cues will be a measure of the amount of attention given to smoking cues. The longer the amount of time spent looking at smoking cues indicates that a greater amount of attention was given to the smoking cues.
Measure: Amount of time looking at dynamic smoking cues in e-cigarette advertisements Time: During the intervention, approximately 15 minutes post baselineDescription: Character Attributes will be collected using a scale that measures participants beliefs about character attributes using the lead in: "I think [Character Name] is: " using a 5-point Likert (1 = strongly disagree; 5 = strongly agree). There is a total of 6 attributes assessed: 1) smart (smart, intelligent, stupid), 2) successful (successful, achieves goals, gets what he/she wants), 3) attractive (physically attractive, ugly, good-looking), 4) funny (funny, humorous, makes me laugh), 5) respected (respected by others, receives approval, criticized by others), and 6) popular (has lots of friends, well liked, gets support from others). A total score (form 1 to 5) for each scale is calculated by averaging responses for each question within that scale. For each scale, a higher total score indicates higher beliefs about that attribute.
Measure: 18-item scale that measures character attributes of actors that appeared in the commercials Time: approximately 30 minutes post interventionDescription: This 5-item is scale is used to quantify how much a participant would like to be like an actor appearing in a commercial. Questions are rated on a 5-point Likert scale (1 = Strongly Disagree; 5 = Strongly agree). A total identification score (from 1 to 25) is calculated by summing the responses to each question. A higher total score indicates a higher level of wishful identification.
Measure: 5-item scale that measure how much participants wish to be like the actors appearing in the commercials. Time: approximately 30 minutes post interventionDescription: This 13-item scale measures risk perceptions associated with cigarette use. Questions are answered using a sliding percent scale from 0 - 100% in 10% increments. A risk perception scale is calculated (from 0 to 100) by averaging the responses to each question. Higher values indicate a higher risk perception.
Measure: 13-item scale to measure risk perception about cigarette use Time: approximately 30 minutes post interventionDescription: This 13-item scale measures risk perceptions associated with e-cigarette use. Questions are answered using a sliding percent scale from 0 - 100% in 10% increments. A risk perception scale is calculated (from 0 to 100) by averaging the responses to each question. Higher values indicate a higher risk perception.
Measure: 13-item scale to Measure risk perception about e-cigarette use Time: approximately 30 minutes post interventionThe "COVID-19 infection self-test and alert system" (hereinafter referred to as "COVID-19 self-test applet") jointly developed by Beijing Tsinghua Changgung Hospital, Institute for precision medicine, artificial intelligence of Tsinghua University was launched on February 1，2020. Residents , according to their actual healthy situation, after answering questions online, the system will conduct intelligent analysis, make disease risk assessment and give healthcare and medical guidance. Based on the Internet population survey, and referring to the diagnosis and screening standards of the National Health Commission of the People's Republic of China, investigators carried out the mobile applet of Internet survey and registry study for the Internet accessible identifiable population, so as to screen the suspected population and guide the medical treatment.
Description: after the end of this study, investigators calculate and sum up the total evaluated population and positively diagnosed population, then check the ROC of this system, finally to calculate the sensitivity and accuracy of this self-test and self-alert system
Measure: positive number diagnosed by national guideline in the evaluated population Time: 5 monthsDescription: after the end of this study, investigators calculate the proportion and distribution of evaluated people with normal and abnormal scores
Measure: distribution map of evaluated people Time: 5 monthDescription: after the end of this study, investigators sent the feedback inform to every evaluated people and collect and analysis the response to find out whether this applet can help them in the following surveillance or medical treatment. And how it works.
Measure: Effect of medical guidance by designated feedback questionnaire Time: 5 monthDescription: after the end of this study, investigators sent the designated mental scale including anxiety, and collect the response and draw the conclusion.
Measure: mental scale of relief the mental anxiety and avoid unnecessary outpatient Time: 5 monthBackground: There is a current worldwide outbreak of the novel coronavirus Covid-19 which originated from Wuhan in China and has now spread to 6 continents including 210 countries. There is still a lack of any report about severe acute respiratory syndromes (SARS-CoV-2) genetic polymorphisms which are associated with the susceptibility to infection. In addition, gene polymorphisms of MBL (mannose-binding lectin) associated with antigen presentation are related to the risk of SARS-CoV infection. Aim: To investigate the association of different genetic markers of different mechanisms of viral pathogenesis with the outcome of COVID-19. Methods: The study will include one hundred patients diagnosed as COVID-19. Biological blood samples will be taken for routine diagnostic analysis, routine molecular testing using Real-time polymerase chain reaction (PCR), Allelic discrimination and genotyping analysis. Outcome: Different genetic markers could play a role in the outcome and prognosis of COVID-19 viral infection.
Description: To assess genetic mutation via detection of genetic polymorphisms of ACE2 in patients and control to detect what alleles will be associated with the susceptibility to COVID-19 and what alleles will be associated with clearance or protection from infections. using allelic discrimination SSCP (i.e Real-time PCR and genetic sequencer).
Measure: for the patients Time: 2 yearsThe primary objective of this study is to establish differences in susceptibility to SARS CoV-2 infection among health care workers (HCW) highly exposed to patients with COVID-19 diagnosis. To ascertain this issue, we evaluated: - Changes in receptor polymorphism (ACE2 and CD26 receptor study. - SARS-CoV-2 CD4/CD8 T cell response (CTL) - Different KIR phenotypes
Description: ACE2 analysis
Measure: Susceptibility to SARS CoV-2 infection according to ACE2 receptor Time: 1 monthDescription: Activation of CD4-CD8 by viral peptides
Measure: Cellular immune response to SARS CoV-2 infection Time: 1 monthDescription: Analysis of KIR in NK cells
Measure: Susceptibility to infections according to KIR phenoytpes Time: 2 monthsDescription: Survey
Measure: Characteristics of exposure in time and intensity of HCW with SARS CoV-2 infection Time: 1 monthDescription: Activation of CD4-CD8 by viral peptides
Measure: Cellular immune response in HCW with positive IgG against SARS CoV-2 Time: 1 monthA novel coronavirus was identified in late 2019 in Wuhan, China On 11 February, The International Committee on Taxonomy of Viruses (ICTV) announced that the official classification of the new coronavirus (2019-nCoV) is called severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The World Health Organization (WHO) announced on the same day that the official name of the disease caused by the virus is Corona Virus Disease-19 (COVID-19). WHO has declared the infection a Pandemic on March 11, 2020. Based on previous studies on SARS in 2003 and SARS-MERS 2013 there was a genetic polymorphism associated with the susceptibility and severity of the disease. Interleukin-12 (IL-12) is a cytokine secreted by activated phagocytes and dendritic cells. It plays a pivotal role in promoting Th1-type immune responses and cell-mediated immunity. IL-12 triggers many biological functions: it stimulates the proliferation of activated T- and NK-cells, enhances T- and NK-cell-mediated cytolytic activity, and induces the production of IFN-γ by both T-and NK-cells. The interferon-γ production induced by IL-12 forms a major link between innate and adaptive immunity. A recent study revealed that interferon-mediated immunopathological events are associated with atypical innate and adaptive immune responses in SARS patients. Also, TNF-α is a key mediator of the inflammatory response and is critical for host defense against a wide variety of pathogenic microbes. However, the over-expression of this cytokine may lead to badness in disease recovery. The dual role of TNF, acting as an agent of both innate immunity and inflammatory pathology, poses a considerable challenge for gene regulation.
Description: genetic polymorphism
Measure: Measure level of polymorphisms of interleukin (IL)-12 receptor B1 (IL-12RB1) and TNF- α alpha on COVID-19 related severe acute respiratory syndrome (SARS-CoV-2). Time: day 1The main objective of this part of the project is to identify the germline genetic factors which discriminate the benign and severe forms of SARS-CoV2 (CoVID-19) infection in the context of the ongoing SARS-CoV2 (HCOVID-19) epidemic. The scientific arguments of the project are described in APPENDIX. We hypothesize that pathogenic variants in genes coding for crucial factors involved in the HOST PATHOGEN interaction could explain the susceptibility of some patients to severe disease, even in the absence of comorbidities. The challenge is to identify those of the genetic factors who may be related respiratory distress and potentially further death. Based on our previous experience in sarcoidosis, a multifactorial disease predisposing to opportunistic infections, we will focus particularly the regulation of apoptosis and autophagy, immune response to viral infection, and endoplasmic reticulum stress response (ER STRESS) which is closely linked to apoptosis. Genetic defects in such pathways may decrease the clearance of viral particles and induces the progressive invasion by SARS-CoV2 and destruction of lung parenchyma. Our strategy will be similar to that described in our previous studies on sarcoidosis, recently published. We will combine a comparative genotype analysis by WHOLE EXOME SEQUENCING (WES) of benign and severe forms of SARS-CoV2 infection through clinical subgroups defined by the infectious diseases experts and a bioinformatics analysis of the functional networks identified by the panel of genes sharing pathogenic variants and discriminating the severe forms of the diseases. WES data will be carefully analyzed and related to all the intracellular physiological process and also the functional pathways involved in host-pathogen interaction: viral targets on the cell surface and downstream signaling, viral genomic RNA replication and translation, production and release of new viral particles. Finally, our main objectives are the definition of a gene panel more specifically related to severe forms of infection and the characterization of defective pathways involved in pejorative forms of SARS-COv2 disease in order to identify putative therapeutic targets.
Description: Number of genes affected by pathogenic variants in the SEVERE GROUP and for which no mutations have been observed in the CONTROL group For each gene sharing variants in the SEVERE GROUP and not in CONTROLS, the protein encoded by this gene will be identified and his function analyzed in the frame of various protein network software. The frequency of each mutation, so called the minor allele frequency will be evaluated in order to highlight only those which are rare (MAF < 0,01) in the normal population and thus suggesting a putative pathogenic role in the response to SARS-CoV2 infection.
Measure: Primary criteria of data evaluation Time: through study completion, average 6 monthsAlphabetical listing of all HPO terms. Navigate: Correlations Clinical Trials
Data processed on December 13, 2020.
An HTML report was created for each of the unique drugs, MeSH, and HPO terms associated with COVID-19 clinical trials. Each report contains a list of either the drug, the MeSH terms, or the HPO terms. All of the terms in a category are displayed on the left-hand side of the report to enable easy navigation, and the reports contain a list of correlated drugs, MeSH, and HPO terms. Further, all reports contain the details of the clinical trials in which the term is referenced. Every clinical trial report shows the mapped HPO and MeSH terms, which are also hyperlinked. Related HPO terms, with their associated genes, protein mutations, and SNPs are also referenced in the report.
Drug Reports MeSH Reports HPO Reports