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

Randomized Experiments01:13

Randomized Experiments

8.7K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
8.7K
Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

799
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
799
Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

15.1K
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...
15.1K
Mouse Models of Cancer Study02:43

Mouse Models of Cancer Study

6.2K
Mice have long served as models for studying human biology and pathology because of their phylogenetic and physiological similarity with humans. They are also easy to maintain and breed in the laboratory, and hence, many inbred strains are now available for research. Studies on mice have contributed immeasurably to our understanding of cancer biology.
The development of transgenic, knockout, and knock-in mice has led to an exponential increase in their use as model organisms in research,...
6.2K
Confounding in Epidemiological Studies01:27

Confounding in Epidemiological Studies

487
Confounding in statistical epidemiology represents a pivotal challenge, referring to the distortion in the perceived relationship between an exposure and an outcome due to the presence of a third variable, known as a confounder. This variable is associated with both the exposure and the outcome but is not a direct link in their causal chain. Its presence can lead to erroneous interpretations of the exposure's effect, either exaggerating or underestimating the true association. This...
487

You might also read

Related Articles

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

Sort by
Same author

Trajectories of brain structure and function in young adult carriers of genetic frontotemporal dementia variants.

medRxiv : the preprint server for health sciences·2026
Same author

Author Correction: Large-scale network analysis of the cerebrospinal fluid proteome identifies molecular signatures of frontotemporal lobar degeneration.

Nature aging·2025
Same author

Large-scale network analysis of the cerebrospinal fluid proteome identifies molecular signatures of frontotemporal lobar degeneration.

Nature aging·2025
Same author

Association of Initial Side of Brain Atrophy With Clinical Features and Disease Progression in Patients With <i>GRN</i> Frontotemporal Dementia.

Neurology·2024
Same author

Gene-Specific Effects on Brain Volume and Cognition of <i>TMEM106B</i> in Frontotemporal Lobar Degeneration.

Neurology·2024
Same author

Large-scale network analysis of the cerebrospinal fluid proteome identifies molecular signatures of frontotemporal lobar degeneration.

Research square·2024
Same journal

Movement disorders in GLUT1 deficiency syndrome: a systematic review of the literature.

Journal of neurology·2026
Same journal

Detailed clinical characteristics of musical hallucinations in 81 patients.

Journal of neurology·2026
Same journal

The dual role of mTOR in multiple sclerosis pathophysiology: a systematic review.

Journal of neurology·2026
Same journal

Brain-first versus body-first Parkinson's disease: Differential findings on pupillary, brainstem and vagus sonography.

Journal of neurology·2026
Same journal

Spontaneous intracranial hypotension due to pelvic cerebrospinal fluid leak.

Journal of neurology·2026
Same journal

Morbidity and medication use preceding a diagnosis of late-onset Alzheimer's disease: a Danish nationwide study.

Journal of neurology·2026
See all related articles

Related Experiment Video

Updated: Dec 18, 2025

Cigarette Smoke Exposure in Mice using a Whole-Body Inhalation System
06:07

Cigarette Smoke Exposure in Mice using a Whole-Body Inhalation System

Published on: October 22, 2020

7.3K

Smoking and multiple sclerosis risk: a Mendelian randomization study.

Marijne Vandebergh1,2, An Goris3,4

  • 1Department of Neurosciences, Laboratory for Neuroimmunology, KU Leuven, Herestraat 49 bus 1022, 3000, Leuven, Belgium.

Journal of Neurology
|June 13, 2020
PubMed
Summary
This summary is machine-generated.

Mendelian randomization (MR) shows body mass index (BMI) causally increases multiple sclerosis (MS) risk. Smoking, despite observational links, does not appear to causally affect MS risk in this genetic analysis.

Keywords:
EnvironmentGeneticsMendelian randomizationMultiple sclerosisSusceptibility

More Related Videos

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.5K
Author Spotlight: Creating a Versatile Experimental Autoimmune Encephalomyelitis Model Relevant for Both Male and Female Mice
05:44

Author Spotlight: Creating a Versatile Experimental Autoimmune Encephalomyelitis Model Relevant for Both Male and Female Mice

Published on: October 13, 2023

2.0K

Related Experiment Videos

Last Updated: Dec 18, 2025

Cigarette Smoke Exposure in Mice using a Whole-Body Inhalation System
06:07

Cigarette Smoke Exposure in Mice using a Whole-Body Inhalation System

Published on: October 22, 2020

7.3K
Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry
05:53

Candidate Gene Testing in Clinical Cohort Studies with Multiplexed Genotyping and Mass Spectrometry

Published on: June 21, 2018

10.5K
Author Spotlight: Creating a Versatile Experimental Autoimmune Encephalomyelitis Model Relevant for Both Male and Female Mice
05:44

Author Spotlight: Creating a Versatile Experimental Autoimmune Encephalomyelitis Model Relevant for Both Male and Female Mice

Published on: October 13, 2023

2.0K

Area of Science:

  • Neuroepidemiology
  • Genetic Epidemiology
  • Public Health

Background:

  • Multiple sclerosis (MS) demographics suggest modifiable exposures influence risk.
  • Identifying specific environmental and lifestyle factors like smoking and obesity is crucial for MS prevention.
  • Mendelian randomization (MR) offers a robust method to assess causality in observational studies.

Purpose of the Study:

  • To investigate the causal relationship between smoking and body mass index (BMI) with multiple sclerosis (MS) risk using genetic data.
  • To differentiate the causal impact of smoking and BMI on MS development.

Main Methods:

  • Utilized genetic variants from large genome-wide association studies for smoking and BMI.
  • Employed two-sample Mendelian randomization (MR) analysis with MS meta-analysis data.
  • Applied multivariable MR to account for genetic correlations between smoking and BMI.

Main Results:

  • MR analyses found no causal effect of smoking on MS risk.
  • Each standard deviation increase in BMI (approx. 5 kg/m²) was associated with a 30% increased risk of MS.
  • BMI demonstrated a consistent causal contribution to MS risk across both univariable and multivariable MR.

Conclusions:

  • Causal link between smoking and MS risk could not be confirmed via MR, contrasting with observational findings.
  • MR results align with observational data, confirming a causal role for BMI in MS risk.
  • Further research is needed to reconcile the discrepancy between observational and MR findings regarding smoking and MS.