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Record W2104341883 · doi:10.1186/1755-8794-1-50

Multiplex ligation-dependent probe amplification for genetic screening in autism spectrum disorders: Efficient identification of known microduplications and identification of a novel microduplication in ASMT

2008· article· en· W2104341883 on OpenAlexaff
Guiqing Cai, Lisa Edelmann, Juliet Goldsmith, Ninette Cohen, Alisa Nakamine, Jennifer Reichert, Ellen J. Hoffman, Danielle Zurawiecki, Jeremy M. Silverman, Eric Hollander, Latha Soorya, Evdokia Anagnostou, Catalina Betancur, Joseph D. Buxbaum

Bibliographic record

VenueBMC Medical Genomics · 2008
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsHolland Bloorview Kids Rehabilitation HospitalUniversity of Toronto
FundersNational Institutes of HealthAmerican Academy of Child and Adolescent PsychiatryNational Institute of Mental HealthEli Lilly and CompanyAutism Speaks
KeywordsMultiplex ligation-dependent probe amplificationGene duplicationCopy-number variationGeneticsBiologySegmental duplicationGeneDiGeorge syndromeComparative genomic hybridizationGenomeGene familyExon

Abstract

fetched live from OpenAlex

BACKGROUND: It has previously been shown that specific microdeletions and microduplications, many of which also associated with cognitive impairment (CI), can present with autism spectrum disorders (ASDs). Multiplex ligation-dependent probe amplification (MLPA) represents an efficient method to screen for such recurrent microdeletions and microduplications. METHODS: In the current study, a total of 279 unrelated subjects ascertained for ASDs were screened for genomic disorders associated with CI using MLPA. Fluorescence in situ hybridization (FISH), quantitative polymerase chain reaction (Q-PCR) and/or direct DNA sequencing were used to validate potential microdeletions and microduplications. Methylation-sensitive MLPA was used to characterize individuals with duplications in the Prader-Willi/Angelman (PWA) region. RESULTS: MLPA showed two subjects with typical ASD-associated interstitial duplications of the 15q11-q13 PWA region of maternal origin. Two additional subjects showed smaller, de novo duplications of the PWA region that had not been previously characterized. Genes in these two novel duplications include GABRB3 and ATP10A in one case, and MKRN3, MAGEL2 and NDN in the other. In addition, two subjects showed duplications of the 22q11/DiGeorge syndrome region. One individual was found to carry a 12 kb deletion in one copy of the ASPA gene on 17p13, which when mutated in both alleles leads to Canavan disease. Two subjects showed partial duplication of the TM4SF2 gene on Xp11.4, previously implicated in X-linked non-specific mental retardation, but in our subsequent analyses such variants were also found in controls. A partial duplication in the ASMT gene, located in the pseudoautosomal region 1 (PAR1) of the sex chromosomes and previously suggested to be involved in ASD susceptibility, was observed in 6-7% of the cases but in only 2% of controls (P = 0.003). CONCLUSION: MLPA proves to be an efficient method to screen for chromosomal abnormalities. We identified duplications in 15q11-q13 and in 22q11, including new de novo small duplications, as likely contributing to ASD in the current sample by increasing liability and/or exacerbating symptoms. Our data indicate that duplications in TM4SF2 are not associated with the phenotype given their presence in controls. The results in PAR1/PAR2 are the first large-scale studies of gene dosage in these regions, and the findings at the ASMT locus indicate that further studies of the duplication of the ASMT gene are needed in order to gain insight into its potential involvement in ASD. Our studies also identify some limitations of MLPA, where single base changes in probe binding sequences alter results. In summary, our studies indicate that MLPA, with a focus on accepted medical genetic conditions, may be an inexpensive method for detection of microdeletions and microduplications in ASD patients for purposes of genetic counselling if MLPA-identified deletions are validated by additional methods.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.045
GPT teacher head0.303
Teacher spread0.258 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations94
Published2008
Admission routes1
Has abstractyes

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