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Impact of IQ on the diagnostic yield of chromosomal microarray in a community sample of adults with schizophrenia

Overview of attention for article published in Genome Medicine, November 2017
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  • Good Attention Score compared to outputs of the same age (68th percentile)

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Title
Impact of IQ on the diagnostic yield of chromosomal microarray in a community sample of adults with schizophrenia
Published in
Genome Medicine, November 2017
DOI 10.1186/s13073-017-0488-z
Pubmed ID
Authors

Chelsea Lowther, Daniele Merico, Gregory Costain, Jack Waserman, Kerry Boyd, Abdul Noor, Marsha Speevak, Dimitri J. Stavropoulos, John Wei, Anath C. Lionel, Christian R. Marshall, Stephen W. Scherer, Anne S. Bassett

Abstract

Schizophrenia is a severe psychiatric disorder associated with IQ deficits. Rare copy number variations (CNVs) have been established to play an important role in the etiology of schizophrenia. Several of the large rare CNVs associated with schizophrenia have been shown to negatively affect IQ in population-based controls where no major neuropsychiatric disorder is reported. The aim of this study was to examine the diagnostic yield of microarray testing and the functional impact of genome-wide rare CNVs in a community ascertained cohort of adults with schizophrenia and low (< 85) or average (≥ 85) IQ. We recruited 546 adults of European ancestry with schizophrenia from six community psychiatric clinics in Canada. Each individual was assigned to the low or average IQ group based on standardized tests and/or educational attainment. We used rigorous methods to detect genome-wide rare CNVs from high-resolution microarray data. We compared the burden of rare CNVs classified as pathogenic or as a variant of unknown significance (VUS) between each of the IQ groups and the genome-wide burden and functional impact of rare CNVs after excluding individuals with a pathogenic CNV. There were 39/546 (7.1%; 95% confidence interval [CI] = 5.2-9.7%) schizophrenia participants with at least one pathogenic CNV detected, significantly more of whom were from the low IQ group (odds ratio [OR] = 5.01 [2.28-11.03], p = 0.0001). Secondary analyses revealed that individuals with schizophrenia and average IQ had the lowest yield of pathogenic CNVs (n = 9/325; 2.8%), followed by those with borderline intellectual functioning (n = 9/130; 6.9%), non-verbal learning disability (n = 6/29; 20.7%), and co-morbid intellectual disability (n = 15/62; 24.2%). There was no significant difference in the burden of rare CNVs classified as a VUS between any of the IQ subgroups. There was a significantly (p=0.002) increased burden of rare genic duplications in individuals with schizophrenia and low IQ that persisted after excluding individuals with a pathogenic CNV. Using high-resolution microarrays we were able to demonstrate for the first time that the burden of pathogenic CNVs in schizophrenia differs significantly between IQ subgroups. The results of this study have implications for clinical practice and may help inform future rare variant studies of schizophrenia using next-generation sequencing technologies.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 59 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 14%
Student > Doctoral Student 6 10%
Student > Master 6 10%
Student > Bachelor 5 8%
Lecturer 2 3%
Other 5 8%
Unknown 27 46%
Readers by discipline Count As %
Medicine and Dentistry 9 15%
Psychology 6 10%
Biochemistry, Genetics and Molecular Biology 3 5%
Nursing and Health Professions 3 5%
Chemical Engineering 1 2%
Other 7 12%
Unknown 30 51%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 24 July 2018.
All research outputs
#7,481,035
of 24,598,501 outputs
Outputs from Genome Medicine
#1,152
of 1,517 outputs
Outputs of similar age
#138,722
of 447,797 outputs
Outputs of similar age from Genome Medicine
#31
of 35 outputs
Altmetric has tracked 24,598,501 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 1,517 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.2. This one is in the 23rd percentile – i.e., 23% 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 447,797 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 35 others from the same source and published within six weeks on either side of this one. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.