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

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...
Human Genetics01:28

Human Genetics

Human genetics provides a profound framework for understanding the interplay between genetic predispositions and human psychology. At the heart of this discipline lies the study of how genes influence physical traits, behaviors, and susceptibility to diseases. Each person carries a unique genetic code that subtly or significantly shapes their psychological and behavioral landscape.
The complex relationship between genetics and psychology is observable through common biological components such...
Single Nucleotide Polymorphisms-SNPs01:05

Single Nucleotide Polymorphisms-SNPs

A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
Principles of Pharmacogenetics: Types of Genetic Variants01:27

Principles of Pharmacogenetics: Types of Genetic Variants

The human genome is over 99.9% identical between individuals, yet genetic differences exist at millions of bases. The human genome contains approximately 3 million variant positions per individual, many of which are heterozygous, contributing to genetic diversity and individual traits. Genetic variations include single-nucleotide polymorphisms (SNPs), insertions, deletions, and copy number variations (CNVs).SNPs, the most common variation, involve single-base changes in DNA. These can be...
Polygenic Traits01:18

Polygenic Traits

When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...
Polygenic Traits01:18

Polygenic Traits

When more than one gene is responsible for a given phenotype, the trait is considered polygenic. Human height is a polygenic trait. Studies have uncovered hundreds of loci that influence height, and there are believed to be many more. Due to the high number of genes involved, as well as environmental and nutritional factors, height varies significantly within a given population. The distribution of height forms a bell-shaped curve, with relatively few individuals in the population at the...

You might also read

Related Articles

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

Sort by
Same author

Genetic studies of quantitative MCI and AD phenotypes in ADNI: Progress, opportunities, and plans.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2015
Same author

Development of the human fetal hippocampal formation during early second trimester.

NeuroImage·2015
Same author

2014 Update of the Alzheimer's Disease Neuroimaging Initiative: A review of papers published since its inception.

Alzheimer's & dementia : the journal of the Alzheimer's Association·2015
Same author

Sharing data in the global alzheimer's association interactive network.

NeuroImage·2015
Same author

Imaging in StrokeNet: Realizing the Potential of Big Data.

Stroke·2015
Same author

The Image and Data Archive at the Laboratory of Neuro Imaging.

NeuroImage·2015

Related Experiment Video

Updated: May 23, 2026

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

Predicting white matter integrity from multiple common genetic variants.

Omid Kohannim1, Neda Jahanshad, Meredith N Braskie

  • 1Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095-1769, USA.

Neuropsychopharmacology : Official Publication of the American College of Neuropsychopharmacology
|April 19, 2012
PubMed
Summary
This summary is machine-generated.

Common genetic variants influence brain white matter integrity. A study of five single-nucleotide polymorphisms (SNPs) in healthy adults revealed a combined effect on corpus callosum microstructure, impacting fractional anisotropy (FA).

More Related Videos

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)

Published on: August 21, 2016

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
09:38

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Published on: November 14, 2017

Related Experiment Videos

Last Updated: May 23, 2026

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration
04:41

Mapping Alzheimer's Disease Variants to Their Target Genes Using Computational Analysis of Chromatin Configuration

Published on: January 9, 2020

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)
11:35

Screening for Functional Non-coding Genetic Variants Using Electrophoretic Mobility Shift Assay (EMSA) and DNA-affinity Precipitation Assay (DAPA)

Published on: August 21, 2016

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease
09:38

Generalized Psychophysiological Interaction (PPI) Analysis of Memory Related Connectivity in Individuals at Genetic Risk for Alzheimer's Disease

Published on: November 14, 2017

Area of Science:

  • Neuroscience
  • Genetics
  • Biomedical Imaging

Background:

  • Common genetic variants influence white matter microstructure measured by diffusion tensor imaging (DTI).
  • Individual genetic variants explain small proportions of variance in brain microstructure.

Purpose of the Study:

  • To explore the combined effect of common genetic variants on the white matter integrity of the corpus callosum.
  • To investigate the individual and aggregate effects of candidate single-nucleotide polymorphisms (SNPs) on white matter structure.

Main Methods:

  • Measured six common candidate SNPs (COMT, NTRK1, BDNF, ErbB4, CLU, HFE) in 395 healthy adult twins and siblings (age 20-30).
  • Utilized 4-tesla 94-direction high angular resolution diffusion imaging for brain scanning.
  • Employed mixed-effects linear regression for combined genetic effect analysis.

Main Results:

  • A joint model of five SNPs (COMT, NTRK1, ErbB4, CLU, HFE) explained approximately 6% of the variance in corpus callosum fractional anisotropy (FA).
  • The predictive model showed detectable effects on FA in 82% of corpus callosum voxels, including genu, body, and splenium.

Conclusions:

  • Combined genetic variants significantly predict white matter microstructure in the corpus callosum.
  • Predicting brain fiber microstructure from genotypes may aid in early risk assessment for neuropsychiatric disorders.