Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Autoimmune Disorders01:29

Autoimmune Disorders

Autoimmune diseases are a group of disorders in which the body's immune system mistakenly attacks its own cells, tissues, and organs. This results from an overactive immune response against substances and tissues normally present in the body. Let's delve into the concept and mechanism of autoimmune diseases from an immune system point of view, explore different causes and examples of such diseases, and discuss potential solutions.
Concept and Mechanism of Autoimmune Diseases
The immune system...
Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu01:29

Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu

Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
Coronary Artery Disease I: Introduction01:30

Coronary Artery Disease I: Introduction

Coronary Artery Disease (CAD): An Overview with Scientific InsightsCoronary Artery Disease (CAD), often referred to as C-A-D, is a prevalent blood vessel disorder classified under the broader category of atherosclerosis. Atherosclerosis is a pathological process characterized by the hardening and narrowing of arteries due to the accumulation of atherosclerotic plaques. These plaques are composed of cholesterol, fatty substances, inflammatory cells, calcium, and fibrin, reducing blood flow to...
Psychoneuroimmunology: Cardiovascular Disease01:27

Psychoneuroimmunology: Cardiovascular Disease

Psychoneuroimmunology (PNI) is a multidisciplinary field that examines how psychological factors, particularly stress, interact with the immune system and impact physical health. Research in PNI has shown that chronic or traumatic stress can disrupt both the hypothalamic-pituitary-adrenal axis and the sympathetic nervous system. These disruptions contribute to serious health conditions, including cardiovascular diseases.
A key area of focus in PNI is the relationship between stress and coronary...
Atherosclerosis II: Clinical Manifestations and Diagnostic Tests01:27

Atherosclerosis II: Clinical Manifestations and Diagnostic Tests

Atherosclerosis is a progressive disorder that leads to the thickening and narrowing of arterial walls due to plaque buildup. This condition can cause various symptoms depending on the arteries affected:Coronary Artery Disease (CAD): This condition affects the coronary arteries and may lead to chest pain (angina), shortness of breath (dyspnea), heart attacks, and other heart disease symptoms.Cerebrovascular Disease: This affects blood flow to the brain, causing transient ischemic attacks (TIAs)...
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
GWAS does not require the identification of the target gene involved in...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Monocular Markerless Motion Capture Enables Quantitative Assessment of Upper Extremity Reachable Workspace.

Sensors (Basel, Switzerland)·2026
Same author

Multi-level Asymmetric Contrastive Learning for Medical Image Segmentation Pre-training.

IEEE journal of biomedical and health informatics·2026
Same author

BMRetriever: Tuning Large Language Models as Better Biomedical Text Retrievers.

Proceedings of the Conference on Empirical Methods in Natural Language Processing. Conference on Empirical Methods in Natural Language Processing·2026
Same author

Knowledge-Infused Prompting: Assessing and Advancing Clinical Text Data Generation with Large Language Models.

Findings of ACL. ACL·2026
Same author

Biomarkers.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2026
Same author

Alzheimer's Imaging Consortium.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2025
Same journal

Magnetic Resonance Spectroscopy Deep Learning with Magnetic Resonance Background Generator Enables In Vivo Metabolite Quantification of Hepatic Encephalopathy.

IEEE transactions on bio-medical engineering·2026
Same journal

Use of RPNIs and Implanted Electrodes for Prosthetic Wrist and Multi-Grip Hand Control during Functional Tasks: A Case Study.

IEEE transactions on bio-medical engineering·2026
Same journal

Healthy Limb Driven Prediction for Real Time Control of Unilateral Exoskeletons in Gait Rehabilitation.

IEEE transactions on bio-medical engineering·2026
Same journal

A Miniature Wearable Ultrasound System for Continuous Bladder Monitoring with Sleeping-Position-Robust Modeling Strategies.

IEEE transactions on bio-medical engineering·2026
Same journal

A Bi-objective Array Optimization Framework for Magnetocardiographic Source Imaging.

IEEE transactions on bio-medical engineering·2026
Same journal

A Dynamic Mutual Information Measure of Phase-Amplitude Coupling with Uncertainty Quantification.

IEEE transactions on bio-medical engineering·2026
See all related articles

Related Experiment Videos

Polygenic Stroke Risk and Autoimmune Disease: Associations and Clinical Modifiers.

Andrew Hornback, Yifei Wang, Marco Piazzi

    IEEE Transactions on Bio-Medical Engineering
    |June 9, 2026
    PubMed
    Summary
    This summary is machine-generated.

    Polygenic risk scores (PRSs) offer less predictive value for stroke in individuals with autoimmune diseases due to higher baseline risk. This study quantifies how genetic risk interacts with immune status for better disease prediction.

    Related Experiment Videos

    Area of Science:

    • Genetics
    • Immunology
    • Neurology

    Background:

    • Polygenic risk scores (PRSs) aid complex disease prediction.
    • Autoimmune diseases may alter stroke risk and genetic prediction utility.
    • Distinct inflammatory profiles can influence disease susceptibility.

    Purpose of the Study:

    • To assess if PRSs differentially improve 10-year stroke prediction in individuals with and without autoimmune diseases.
    • To quantify the added value of genetic information in distinct clinical subgroups.
    • To explore interactions between genetic and immune-mediated risk factors for stroke.

    Main Methods:

    • Utilized UK Biobank data to identify individuals with prevalent autoimmune diseases.
    • Modeled 10-year incident stroke using logistic regression, gradient boosting, and XGBoost.
    • Compared prediction error between non-genetic and PRS-inclusive models to quantify PRS contribution.

    Main Results:

    • Elevated baseline stroke risk in autoimmune disease patients reduced the incremental predictive benefit of PRSs.
    • Confirmed established links between immune-mediated disease and cerebrovascular risk.
    • Identified subgroups where PRS inclusion improved or worsened stroke prediction accuracy.

    Conclusions:

    • Genetic risk prediction's utility is context-dependent, influenced by clinical factors like autoimmune status.
    • This approach quantifies interactions between genetic and immune-mediated risk.
    • Highlights the need to consider individual clinical profiles when applying PRSs for disease risk assessment.