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Microarray testing in clinical diagnosis: an analysis of 5,300 New Zealand patients

Overview of attention for article published in Molecular Cytogenetics, March 2016
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Title
Microarray testing in clinical diagnosis: an analysis of 5,300 New Zealand patients
Published in
Molecular Cytogenetics, March 2016
DOI 10.1186/s13039-016-0237-9
Pubmed ID
Authors

Adrian Mc Cormack, Karen Claxton, Fern Ashton, Philip Asquith, Edward Atack, Roberto Mazzaschi, Paula Moverley, Rachel O’Connor, Methat Qorri, Karen Sheath, Donald R. Love, Alice M. George

Abstract

The use of Microarray (array CGH) analysis has become a widely accepted front-line test replacing G banded chromosome studies for patients with an unexplained phenotype. We detail our findings of over 5300 cases. Of 5369 pre and postnatal samples, copy number variants (CNVs) were detected in 28.3 %, of which ~40 % were deletions and ~60 % were duplications. 96.8 % of cases with a CNV <5 Mb would not have been detected by G banding. At least 4.9 % were determined to meet the minimum criteria for a known syndrome. Chromosome 17 provided the greatest proportion of pathogenic CNVs with 65 % classified as (likely) pathogenic. X chromosome CNVs were the most commonly detected accounting for 4.2 % of cases, 0.7 % of these being classified as cryptic (likely) pathogenic CNVs. Microarray analysis as a primary testing strategy has led to a significant increase in the detection of CNVs (~29 % overall), with ~9 % carrying pathogenic CNVs and one syndromic case identified per 20 referred patients. We suggest these frequencies are consistent with other heterogeneous studies. Conversely, (likely) pathogenic X chromosome CNVs appear to be greater compared with previous studies.

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Mendeley readers

The data shown below were compiled from readership statistics for 12 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 3 25%
Other 2 17%
Student > Bachelor 2 17%
Lecturer 1 8%
Professor 1 8%
Other 2 17%
Unknown 1 8%
Readers by discipline Count As %
Unspecified 3 25%
Biochemistry, Genetics and Molecular Biology 2 17%
Agricultural and Biological Sciences 2 17%
Medicine and Dentistry 2 17%
Nursing and Health Professions 1 8%
Other 1 8%
Unknown 1 8%