Disease Gene Identification
Disease Gene Identification - Related Videos
14:27
Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
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Cited by 73 •
2013
Multivariate techniques including principal component analysis (PCA) have been used to identify signature patterns of regional change in functional brain images. We have developed an algorithm to identify reproducible network biomarkers for the diagnosis of neurodegenerative disorders, assessment of disease progression, and objective evaluation of treatment effects in patient populations.
08:17
VIGS-Mediated Forward Genetics Screening for Identification of Genes Involved in Nonhost Resistance
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Cited by 22 •
2013
Virus-induced gene silencing is an useful tool for identifying genes involved in nonhost resistance of plants. We demonstrate the use of bacterial pathogens expressing GFPuv in identifying gene silenced plants susceptible to nonhost pathogens. This approach is easy, fast and facilitates large scale screening and similar protocol can be applied to studying various other plant-microbe interactions.
06:34
Identification of Rare Bacterial Pathogens by 16S rRNA Gene Sequencing and MALDI-TOF MS
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Cited by 29 •
2016
Matrix-assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) and molecular techniques (16S rRNA gene sequencing) permit the identification of rare bacterial pathogens in routine diagnostics. The goal of this protocol lies in the combination of both techniques which leads to more accurate and reliable data.
08:09
Gene-environment Interaction Models to Unmask Susceptibility Mechanisms in Parkinson's Disease
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Cited by 10 •
2014
Lipoxygenase (LOX) isozymes can generate products that may increase or decrease neuroinflammation and neurodegeneration. A gene-environment interaction study could identify LOX isozyme-specific effects. Using the 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) model of nigrostriatal damage in two LOX isozyme-deficient transgenic lines allows for comparison of the contribution of LOX isozymes on dopaminergic integrity and inflammation.
14:12
Rodent Identification II
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2015
Source: Kay Stewart, RVT, RLATG, CMAR; Valerie A. Schroeder, RVT, RLATG. University of Notre Dame, IN Animal records must be accurately maintained to ensure that data collection is correct. Records range from maintaining information on cage cards to having a detailed database with all of the relevant information on each animal. The primary component of recordkeeping is the individual identification of research animals. There are a variety of methods suitable for identifying mice and rats. This...
FAQs
These approaches examine genetic contributions from complementary perspectives. Family-based linkage analysis compares genetic information among affected and unaffected relatives, genome-wide association studies examine patterns across broader groups, and DNA sequencing directly evaluates genetic sequence information. Using more than one approach can help researchers identify candidate genes or variants and then assess whether the findings consistently relate to disease biology.
A genetic association alone does not explain how disease develops or progresses. Researchers therefore examine whether a candidate variant alters gene function or affects a biological pathway connected with disease. This functional interpretation links genetic evidence to mechanism, helping distinguish a potentially important contributor from a variant that merely appears alongside disease-related genetic information.
Researchers compare genetic information from affected and unaffected individuals and interpret the results alongside evidence about gene function and biological pathways. This combination helps clarify which disease-related patterns may reflect inherited susceptibility rather than unrelated influences. The distinction is important for interpreting risk accurately and for connecting genetic findings with disease mechanisms.
The investigation can address genes or genetic variants associated with disease susceptibility, development, or progression. These categories describe different biological relationships: a finding may relate to the likelihood of developing disease, to how disease begins, or to how it changes over time. Separating these possibilities helps researchers interpret candidate findings and their potential clinical relevance.
Researchers begin by comparing genetic information from affected and unaffected individuals, using family-based linkage analysis, genome-wide association studies, DNA sequencing, or a combination of these approaches. They then examine candidate variants for effects on gene function or biological pathways. Findings that connect genetic differences with plausible biological effects can support further interpretation as disease-related evidence.
This work is useful when researchers need to clarify disease mechanisms, evaluate genetic risk, or find molecular features that distinguish patients. Its results can support genetic diagnosis and risk assessment, while also helping organize patients into groups with relevant genetic characteristics. In research, the same findings can guide investigation of biomarkers and potential therapeutic targets.
The process can produce several biologically and clinically relevant outcomes. It may clarify how disease develops or progresses, identify genetic factors associated with susceptibility, and reveal biomarkers or possible therapeutic targets. These findings can also contribute to patient stratification, genetic diagnosis, and risk assessment, connecting molecular evidence with more precise approaches to understanding and treating disease.