A VALIDATION, WITH NEW CLINICAL APPLICABILITY, OF A CLINICAL-GENETIC RISK MODEL THAT PREDICTS THROMBOSIS WITH HIGH SENSITIVITY IN PATIENTS WITH LYMPHOMA

2019 ◽  
Vol 37 ◽  
pp. 534-534
Author(s):  
M. Bastos-Oreiro ◽  
J. Ortiz ◽  
V. Pradillo ◽  
C. Martinez-Laperche ◽  
E. Salas ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Risk Model ◽  
High Sensitivity ◽  
Clinical Genetic ◽  
Clinical Applicability

scholarly journals Multivariable clinical-genetic risk model for predicting venous thromboembolic events in patients with cancer

2018 ◽  
Vol 118 (8) ◽  
pp. 1056-1061 ◽  
Author(s):  
Andrés J. Muñoz Martín ◽  
Israel Ortega ◽  
Carme Font ◽  
Vanesa Pachón ◽  
Victoria Castellón ◽  
...  
Keyword(s):  
Genetic Risk ◽  
Risk Model ◽  
Thromboembolic Events ◽  
Clinical Genetic ◽  
Patients With Cancer ◽  
Venous Thromboembolic Events ◽  
Venous Thromboembolic

Discoveries in gene-environment interactions that influence CVD, lipid traits, obesity, diabetes, and hypertension appear to be able to influence gene therapy.

2021 ◽  
Author(s):  
Moataz Dowaidar
Keyword(s):  
Gene Therapy ◽  
Genetic Risk ◽  
Environmental Influences ◽  
Biological Processes ◽  
Significant Progress ◽  
Therapy Outcomes ◽  
Genetic Therapy ◽  
Clinical Genetic ◽  
Gene Environment ◽  
Made In

In a relatively short amount of time, significant progress has been made in discovering gene-environment interactions that influence CVD, lipid traits, obesity, diabetes, and hypertension. These correlations appear to change genetic vulnerability, which may help researchers better understand the genetic processes that influence CVD development in the future. In order to advance the field, further research is required to confirm initial comparisons, identify the biological processes by which environmental influences modify genetic risk, and investigate strategies that use this knowledge to influence clinical genetic therapy outcomes.

scholarly journals Interaction of Neighborhood and Genetic Risk on Waist Circumference in African-American Adults: A Longitudinal Study

2020 ◽  
Author(s):  
Tyler McDaniel ◽  
Dawn K Wilson ◽  
M Sandra Coulon ◽  
Allison M Sweeney ◽  
M Lee Van Horn
Keyword(s):  
African American ◽  
Waist Circumference ◽  
Genetic Risk ◽  
Social Life ◽  
Risk Model ◽  
Neighborhood Environment ◽  
Buccal Swab ◽  
Metabolic Risk ◽  
African American Adults ◽  
The Impact

Abstract Background Understanding determinants of metabolic risk has become a national priority given the increasingly high prevalence rate of this condition among U.S. adults. Purpose This study’s aim was to assess the impact of gene-by-neighborhood social environment interactions on waist circumference (WC) as a primary marker of metabolic risk in underserved African-American adults. Based on a dual-risk model, it was hypothesized that those with the highest genetic risk and who experienced negative neighborhood environment conditions would demonstrate higher WC than those with fewer risk factors. Methods This study utilized a subsample of participants from the Positive Action for Today’s Health environmental intervention to improve access and safety for walking in higher-crime neighborhoods, who were willing to provide buccal swab samples for genotyping stress-related genetic pathways. Assessments were conducted with 228 African-American adults at baseline, 12, 18, and 24 months. Results Analyses indicated three significant gene-by-environment interactions on WC outcomes within the sympathetic nervous system (SNS) genetic pathway. Two interactions supported the dual-risk hypotheses, including the SNS genetic risk-by-neighborhood social life interaction (b = −0.11, t(618) = −2.02, p = .04), and SNS genetic risk-by-informal social control interaction (b = −0.51, t(618) = −1.95, p = .05) on WC outcomes. These interactions indicated that higher genetic risk and lower social-environmental supports were associated with higher WC. There was also one significant SNS genetic risk-by-neighborhood satisfaction interaction (b = 1.48, t(618) = 2.23, p = .02) on WC that was inconsistent with the dual-risk pattern. Conclusions Findings indicate that neighborhood and genetic factors dually influence metabolic risk and that these relations may be complex and warrant further study. Trial Registration NCT01025726.

scholarly journals Prediction of type 1 diabetes using a genetic risk model in the Diabetes Autoimmunity Study in the Young

2017 ◽  
Vol 19 (2) ◽  
pp. 277-283 ◽  
Author(s):  
Brigitte I Frohnert ◽  
Michael Laimighofer ◽  
Jan Krumsiek ◽  
Fabian J Theis ◽  
Christiane Winkler ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Genetic Risk ◽  
Risk Model

microRNAs in cardiovascular disease – clinical application

2017 ◽  
Vol 55 (5) ◽  
Author(s):  
Christian Schulte ◽  
Mahir Karakas ◽  
Tanja Zeller
Keyword(s):  
Cardiovascular Disease ◽  
High Sensitivity ◽  
Specific Protein ◽  
Therapeutic Agents ◽  
Circulating Biomarkers ◽  
Circulating Mirnas ◽  
Clinical Applicability ◽  
Artery Disease ◽  
Prognostic Power ◽  
Cardiac Troponins

AbstractmicroRNAs (miRNAs) are well-known, powerful regulators of gene expression, and their potential to serve as circulating biomarkers is widely accepted. In cardiovascular disease (CVD), numerous studies have suggested miRNAs as strong circulating biomarkers with high diagnostic as well as prognostic power. In coronary artery disease (CAD) and heart failure (HF), miRNAs have been suggested as reliable biomarkers matching up to established protein-based such as cardiac troponins (cT) or natriuretic peptides. Also, in other CVD entities, miRNAs were identified as surprisingly specific biomarkers – with great potential for clinical applicability, especially in those entities that lack specific protein-based biomarkers such as atrial fibrillation (AF) and acute pulmonary embolism (APE). In this regard, miRNA signatures, comprising a set of miRNAs, yield high sensitivity and specificity. Attempts to utilize miRNAs as therapeutic agents have led to promising results. In this article, we review the clinical applicability of circulating miRNAs in CVD. We are giving an overview of miRNAs as biomarkers in numerous CVD entities to depict the variety of their potential clinical deployment. We illustrate the function of miRNAs by means of single miRNA examples in CVD.

scholarly journals Successful incorporation of a genetic risk prediction research platform into routine newborn screening

2021 ◽  
Author(s):  
Owen M Bendor-Samuel ◽  
Tabitha Wishlade ◽  
Louise Willis ◽  
Parvinder Aley ◽  
Edward Choi ◽  
...  
Keyword(s):  
Newborn Screening ◽  
Genetic Risk ◽  
Screening Programme ◽  
Genomic Medicine ◽  
Genetic Research ◽  
Population Based ◽  
Clinical Genetic ◽  
Screening Programs ◽  
Increased Risk ◽  
The Uk

ABSTRACTAn increasing number of diseases can be offered treatments that are transformative if administered in a timely manner. However, many of these diseases are currently not included in the newborn screening programs because they lack sensitive and specific metabolic biomarkers, and detection of children at increased risk relies on genetic methods. Type 1 diabetes (T1D) constitutes a potential example of such disease.Between April 2018 and November 2020, over 15500 babies were enrolled into ‘INGR1D’ (Investigating Genetic Risk for T1D), a research study to identify newborns with an increased genetic risk of T1D. This project, performed as part of a T1D primary prevention study (the Primary Oral Insulin Trial, POInT), has helped to pioneer the integration of genetic screening into the NHS Newborn Blood Spot Screening Programme (NBSSP) for consenting mothers, without affecting the screening pathway. The use of prospective consent to perform personalised genetic testing on samples obtained through the routine NBSSP represents a novel mechanism for clinical genetic research in the UK and provides a model for further population based genetic studies in the newborn.This project builds on the UK’s role as a world leader in genomic medicine, e.g. through its inception and completion of the 100 000 Genomes Project, and its subsequent ambition to map 5 million further genomes over the next 5 years.Our aim is therefore to describe the methodology used by INGR1D as a way to demonstrate how a successful research and clinical trial tool can be integrated into a national screening programme, with the potential for the tool to be developed to incorporate multiple diseases with genetic markers without altering the screening pathway.

Predictive accuracy of the breast cancer genetic risk model based on eight common genetic variants: The BACkSIDE study

2019 ◽  
Vol 299 ◽  
pp. 1-7 ◽  
Author(s):  
Zuzana Danková ◽  
Pavol Žúbor ◽  
Marián Grendár ◽  
Katarína Zelinová ◽  
Marianna Jagelková ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Genetic Variants ◽  
Genetic Risk ◽  
Risk Model ◽  
Predictive Accuracy ◽  
Cancer Genetic ◽  
Model Based ◽  
Common Genetic Variants

Application of the genetic risk model for the analysis of predisposition to nonlacunar ischemic stroke

2019 ◽  
Vol 16 (5) ◽  
pp. 369-378
Author(s):  
Vitaly Korchagin ◽  
Konstantin Mironov ◽  
Alexander Platonov ◽  
Olga Dribnokhodova ◽  
Elina Akselrod ◽  
...  
Keyword(s):  
Ischemic Stroke ◽  
Genetic Risk ◽  
Operating Characteristic ◽  
Risk Model ◽  
Characteristic Curve ◽  
Predictive Ability ◽  
Classification Model ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Satisfactory Performance

Aim: The purpose of our study was to analyze the predictive ability of the multiplicative model of genetic risk of nonlacunar ischemic stroke (IS) for independent samples from Russia. Patients & methods: A total of 181 patients and 360 healthy controls were included in this study. The discriminative accuracy of model was evaluated by the area under the receiver operating characteristic curve (AUC). Results: Classification model based on 15 single-nucleotide polymorphisms (SNPs), which are associated with a cardioembolic subtype of IS, had an AUC of 0.62 in patients with corresponding subtypes and an AUC of 0.58 for all patients. Conclusion: Risk calculation approach based on IS-associated SNPs had satisfactory performance in predicting the predisposition to the disease.

scholarly journals Risk prediction of recurrent venous thromboembolism: a multiple genetic risk model

2018 ◽  
Vol 47 (2) ◽  
pp. 216-226 ◽  
Author(s):  
Abrar Ahmad ◽  
Kristina Sundquist ◽  
Karolina Palmér ◽  
Peter J. Svensson ◽  
Jan Sundquist ◽  
...  
Keyword(s):  
Venous Thromboembolism ◽  
Risk Prediction ◽  
Genetic Risk ◽  
Risk Model ◽  
Recurrent Venous Thromboembolism
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