Evidence map›Paper›PMID 19047251›Full record

ArticlePediatrics2008

Genomic imbalances in neonates with birth defects: high detection rates by using chromosomal microarray analysis.

Xin-Yan Lu, Mai T Phung, Chad A Shaw, Kim Pham, Sarah E Neil, Ankita Patel, Trilochan Sahoo, Carlos A Bacino, Pawel Stankiewicz, Sung-Hae Lee Kang and 5 more

Open access · greenAbstract readComparative Study
In one paragraph

Article in Pediatrics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 66 papers.

0numbers the graph read from it
0cells of the map it votes in
66citing papers in PubMed
10.1field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

66 citing papers in PubMed, 155 citations in OpenAlex.

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  9. Detection and impact of genetic disease in a level IV neonatal intensive care unit.Journal of perinatology : official journal of the California Perinatal Association · 2022
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  14. Exome sequencing compared with standard genetic tests for critically ill infants with suspected genetic conditions.Genetics in medicine : official journal of the American College of Medical Genetics · 2020
    Article
  15. Insights into genetics, human biology and disease gleaned from family based genomic studies.Genetics in medicine : official journal of the American College of Medical Genetics · 2019
    Review
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6 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

15 authors at 1 institution in 1 country.

Xin-Yan LuBaylor College of Medicine, Department of Molecular and Human Genetics, One Baylor Plaza, NAB 2015, Houston, TX 77030, USA.
Mai T Phung
Chad A Shaw
Kim Pham
Sarah E Neil
Ankita Patel
Trilochan Sahoo
Carlos A Bacino
Pawel Stankiewicz
Sung-Hae Lee Kang
Seema Lalani
A Craig Chinault
James R Lupski
Sau W Cheung
Arthur L Beaudet
Baylor College of Medicine · US

Funding

UNDERSTANDING FXTAS AMONG MALES WITH THE FMR1 PREMUTATIONP30HD024064 · NICHD · BAYLOR COLLEGE OF MEDICINE · PI TOLIAS, KIMBERLY R · 1988 to 2013
$29.4M
NICHD NIH HHS HD024064-20NICHD NIH HHS P30 HD024064
6 · The paper itself

Abstract

objectivesOur aim was to determine the frequency of genomic imbalances in neonates with birth defects by using targeted array-based comparative genomic hybridization, also known as chromosomal microarray analysis.

methodsBetween March 2006 and September 2007, 638 neonates with various birth defects were referred for chromosomal microarray analysis. Three consecutive chromosomal microarray analysis versions were used: bacterial artificial chromosome-based versions V5 and V6 and bacterial artificial chromosome emulated oligonucleotide-based version V6 Oligo. Each version had targeted but increasingly extensive genomic coverage and interrogated>150 disease loci with enhanced coverage in genomic rearrangement-prone pericentromeric and subtelomeric regions.

resultsOverall, 109 (17.1%) patients were identified with clinically significant abnormalities with detection rates of 13.7%, 16.6%, and 19.9% on V5, V6, and V6 Oligo, respectively. The majority of these abnormalities would not be defined by using karyotype analysis. The clinically significant detection rates by use of chromosomal microarray analysis for various clinical indications were 66.7% for "possible chromosomal abnormality"+/-"others" (other clinical indications), 33.3% for ambiguous genitalia+/-others, 27.1% for dysmorphic features+multiple congenital anomalies+/-others, 24.6% for dysmorphic features+/-others, 21.8% for congenital heart disease+/-others, 17.9% for multiple congenital anomalies+/-others, and 9.5% for the patients referred for others that were different from the groups defined. In all, 16 (2.5%) patients had chromosomal aneuploidies, and 81 (12.7%) patients had segmental aneusomies including common microdeletion or microduplication syndromes and other genomic disorders. Chromosomal mosaicism was found in 12 (1.9%) neonates.

conclusionsChromosomal microarray analysis is a valuable clinical diagnostic tool that allows precise and rapid identification of genomic imbalances and mosaic abnormalities as the cause of birth defects in neonates. Chromosomal microarray analysis allows for timely molecular diagnoses and detects many more clinically relevant genomic abnormalities than conventional cytogenetic studies, enabling more informed decision-making and management and appropriate assessment of recurrence risk.

Indexed as

Chromosome AberrationsComparative Genomic HybridizationAbnormalities, MultipleCohort StudiesCongenital AbnormalitiesFemaleGenomic InstabilityHumansInfant, NewbornIn Situ Hybridization, FluorescenceMaleMosaicismOligonucleotide Array Sequence AnalysisSensitivity and Specificity

Identifiers

PMID19047251
PMCPMC2795566
OpenAlexW1969211599

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.