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Record W2023767508 · doi:10.1186/s12920-014-0070-0

SNP arrays: comparing diagnostic yields for four platforms in children with developmental delay

2014· article· en· W2023767508 on OpenAlex
Guylaine D’Amours, Mathieu Langlois, Géraldine Mathonnet, Raouf Fetni, Sonia Nizard, Myriam Srour, Frédérique Tihy, Michael Phillips, Jacques L. Michaud, Emmanuelle Lemyre

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBMC Medical Genomics · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGenomic variations and chromosomal abnormalities
Canadian institutionsMontreal Heart InstituteUniversité de MontréalCentre Hospitalier Universitaire Sainte-Justine
Fundersnot available
KeywordsUniparental disomySNP arrayCopy-number variationBiologyGeneticsSNPGenotypingComparative genomic hybridizationLoss of heterozygosityCopy number analysisSNP genotypingSingle-nucleotide polymorphismHuman geneticsCytogeneticsHuman genomeMolecular Inversion ProbeKaryotypeGenotypeGenomeChromosomeGeneAllele

Abstract

fetched live from OpenAlex

BACKGROUND: Molecular karyotyping is now the first-tier genetic test for patients affected with unexplained intellectual disability (ID) and/or multiple congenital anomalies (MCA), since it identifies a pathogenic copy number variation (CNV) in 10-14% of them. High-resolution microarrays combining molecular karyotyping and single nucleotide polymorphism (SNP) genotyping were recently introduced to the market. In addition to identifying CNVs, these platforms detect loss of heterozygosity (LOH), which can indicate the presence of a homozygous mutation or uniparental disomy. Since these abnormalities can be associated with ID and/or MCA, their detection is of particular interest for patients whose phenotype remains unexplained. However, the diagnostic yield obtained with these platforms is not confirmed, and the real clinical value of LOH detection has not been established. METHODS: We selected 21 children affected with ID, with or without congenital malformations, for whom standard genetic analyses failed to provide a diagnosis. We performed high-resolution SNP array analysis with four platforms (Affymetrix Genome-Wide Human SNP Array 6.0, Affymetrix Cytogenetics Whole-Genome 2.7 M array, Illumina HumanOmni1-Quad BeadChip, and Illumina HumanCytoSNP-12 DNA Analysis BeadChip) on whole-blood samples obtained from children and their parents to detect pathogenic CNVs and LOHs, and compared the results with those obtained on a moderate resolution array-based comparative genomic hybridization platform (NimbleGen CGX-12 Cytogenetics Array), already used in the clinical setting. RESULTS: We identified a total of four pathogenic CNVs in three patients, and all arrays successfully detected them. With the SNP arrays, we also identified a LOH containing a gene associated with a recessive disorder consistent with the patient's phenotype (i.e., an informative LOH) in four children (including two siblings). A homozygous mutation within the informative LOH was found in three of these patients. Therefore, we were able to increase the diagnostic yield from 14.3% to 28.6% as a result of the information provided by LOHs. CONCLUSIONS: This study shows the clinical usefulness of SNP arrays in children with ID, since they successfully detect pathogenic CNVs, identify informative LOHs that can lead to the diagnosis of a recessive disorder. It also highlights some challenges associated with the use of SNP arrays in a clinical laboratory.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.125
Threshold uncertainty score0.483

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.019
GPT teacher head0.223
Teacher spread0.203 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it