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Showing posts with label Genetic Variation. Show all posts
Showing posts with label Genetic Variation. Show all posts

Monday, August 7, 2017

Association Between Genetic Variation And Influenza Severity.

It is estimated that in the USA influenza -related deaths in recent years have ranged from 12,000 to 56,000. Factors like age, obesity, pregnancy and such chronic health conditions as asthma, chronic lung disease and heart disease are associated with an elevated risk of complications and death.

However, there are no proven genetic markers of influenza risk with an established mechanism of action. Interferon Induced Transmembrane Protein 3 (IFITM3) is an anti-viral protein that helps to block influenza infection of lung cells and to promote survival of the killer T cells that help clear the infection in the airways.

Image: A scanning electron micrograph of a CD8+ T cell engaging a virus.
(Photo courtesy of Dennis Kunkel).
A group of scientists collaborating with those at St. Jude Children's Research Hospital (Memphis, TN, USA) searched for other possible IFITM3 variants that correlated with gene expression, levels of the IFITM3 proteins and were common in influenza patients in the USA. The search led to an IFITM3 variant known as rs34481144. They checked 86 children and adults in Memphis with confirmed influenza infections and found two-thirds of patients with the most severe symptoms carried at least one copy of the newly identified high-risk IFITM3 variant. The high-risk variant was found in just 32% of patients with milder symptoms.

The team also found an association between the newly identified high-risk variant and severe and fatal influenza infections in 265 critically ill pediatric patients hospitalized in one of 31 intensive care units nationwide. The patients did not have health problems that put them at high risk for severe influenza. Of the 17 patients in this group who died from the infection, 14 carried at least one copy of the newly identified high-risk variant. Further study revealed how binding differed between the high-risk and protective variants. Those differences led to lower levels of the IFITM3 protein in individuals with two copies of the high-risk gene variant compared to other patients. The Memphis influenza patients also had fewer of the killer T cells in their upper airways. The study identifies a new regulator of IFITM3 expression that associates with CD8+ T cell levels in the airways and a spectrum of clinical outcomes.

Paul Thomas, PhD, an immunologist and corresponding author of the study, said, “A genetic marker of influenza risk could make a life-saving difference, particularly during severe influenza outbreaks, by helping prioritize high-risk patients for vaccination, drug therapy and other interventions. These results raise hopes that this newly identified IFITM3 variant might provide such a marker.” The study was published on July 17, 2017, in the journal Nature Medicine.

Source: labmedica

Saturday, August 27, 2016

The Genetic Components of Rare Diseases

Techniques for determining which genes or genetic variants are truly detrimental

Last fall, the conclusion of the 1000 Genomes Project revealed 88 million variants in the human genome. What most of them mean for human health is unclear. Of the known associations between a genetic variant and disease, many are still tenuous at best. How can scientists determine which genes or genetic variants are truly detrimental?

Patients with rare diseases are often caught in the crosshairs of this uncertainty. By the time they have their genome, or portions of it, sequenced, they’ve endured countless physician visits and tests. Sequencing provides some hope for an answer, but the process of uncovering causal variants on which to build a treatment plan is still one of painstaking detective work with many false leads. Even variants that are known to be harmful show no effects in some individuals who harbor them, says Adrian Liston, a translational immunologist at the University of Leuven in Belgium who works on disease gene discovery.


CROSS COMPARE: Each model organism has its own vocabulary that researchers use to describe
an array of characteristics. The Monarch Initiative has mapped phenotype descriptions used in model
systems to human clinical features. The Initiative’s Exomiser software employs this mapping strategy
to help users better understand human genetic disorders by widening the pool of gene-function
associations. ROBINSON ET AL., GENOME RES, 24:340–48, 2014.
Source: the-scientist
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