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Molecular Genetic Testing for Mitochondrial Disease: From One Generation to the Next

Overview of attention for article published in Neurotherapeutics, April 2013
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1 CiteULike
Title
Molecular Genetic Testing for Mitochondrial Disease: From One Generation to the Next
Published in
Neurotherapeutics, April 2013
DOI 10.1007/s13311-012-0174-1
Pubmed ID
Authors

Elizabeth McCormick, Emily Place, Marni J. Falk

Abstract

Molecular genetic diagnostic testing for mitochondrial disease has evolved continually since the first genetic basis for a clinical mitochondrial disease syndrome was identified in the late 1980s. Owing to global limitations in both knowledge and technology, few individuals, even among those with strong clinical or biochemical evidence of mitochondrial respiratory chain dysfunction, ever received a definitive molecular diagnosis prior to 2005. Clinically available genetic diagnostic testing options improved by 2006 to include sequencing and deletion analysis of an increasing number of individual nuclear genes linked to mitochondrial disease, genome-wide microarray analysis for chromosomal copy number abnormalities, and mitochondrial DNA whole genome sequence analysis. To assess the collective effect of these tests on the genetic diagnosis of suspected mitochondrial disease, we report here results from a retrospective review of the diagnostic yield in patients evaluated from 2008 to 2011 in the Mitochondrial-Genetics Diagnostic Clinic at The Children's Hospital of Philadelphia. Among 152 patients aged 6 weeks to 81 years referred for clinical evaluation of multisystem presentations concerning for suspected mitochondrial disease, a genetic etiology was established that confirmed definite mitochondrial disease in 16.4% and excluded primary mitochondrial disease in 9.2%. Substantial diagnostic challenges remain owing to the clinical difficulty and frank low yield of a priori selecting individual nuclear genes to sequence based on particular symptomatic or biochemical manifestations of suspected mitochondrial disease. These findings highlight the particular utility of massively parallel nuclear exome sequencing technologies, whose benefits and limitations are explored relative to the clinical genetic diagnostic evaluation of mitochondrial disease.

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 113 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Iran, Islamic Republic of 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 110 97%

Demographic breakdown

Readers by professional status Count As %
Researcher 19 17%
Student > Ph. D. Student 15 13%
Student > Bachelor 14 12%
Student > Master 13 12%
Other 11 10%
Other 27 24%
Unknown 14 12%
Readers by discipline Count As %
Medicine and Dentistry 35 31%
Biochemistry, Genetics and Molecular Biology 29 26%
Agricultural and Biological Sciences 20 18%
Neuroscience 3 3%
Pharmacology, Toxicology and Pharmaceutical Science 2 2%
Other 7 6%
Unknown 17 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 May 2017.
All research outputs
#17,285,668
of 25,374,647 outputs
Outputs from Neurotherapeutics
#1,053
of 1,307 outputs
Outputs of similar age
#136,676
of 212,991 outputs
Outputs of similar age from Neurotherapeutics
#6
of 10 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,307 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.2. This one is in the 13th percentile – i.e., 13% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 212,991 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.