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Record W2028121819 · doi:10.1002/humu.9417

Distinct patterns of germ-line deletions inMLH1 andMSH2: the implication of Alu repetitive element in the genetic etiology of Lynch syndrome (HNPCC)

2006· article· en· W2028121819 on OpenAlexafffund
Lili Li, S McVety, Rami Younan, Ping Liang, Desirée du Sart, Philip H. Gordon, Pierre Hutter, Frans B.L. Hogervorst, George Chong, William D. Foulkes

Bibliographic record

VenueHuman Mutation · 2006
Typearticle
Languageen
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsJewish General HospitalMcGill University
FundersCancer Research SocietyMcGill University
KeywordsBiologyAlu elementLynch syndromeGeneticsBioinformaticsGeneDNA mismatch repairGenomeHuman genomeDNA repair

Abstract

fetched live from OpenAlex

A relatively high frequency of germ-line genomic rearrangements in MLH1 and MSH2 has been reported among Lynch Syndrome (HNPCC) patients from different ethnic populations. To investigate the underlying molecular mechanisms, we characterized the DNA breakpoints of 11 germ-line deletions, six for MLH1 and five for MSH2. Distinct deletion patterns were found for the two genes. The five cases of MSH2 deletions result exclusively from intragenic unequal recombination mediated by repetitive Alu sequences. In contrast, five out of the six MLH1 deletions are due to recombinations involving sequences of no significant homology (P=0.015). A detailed analysis of the DNA breakpoints in the two genes, previously characterized by other groups, validated the observation that Alu-mediated unequal recombination is the main type of deletion in MSH2 (n=34), but not in MLH1 (n=21) (P<0.0001). Plotting the distribution of known DNA breakpoints among the introns of the two genes showed that, the highest breakpoint density is co-localized with the highest Alu density. Our study suggests that Alu is a promoting factor for the genomic recombinations in both MLH1 and MSH2, and the local Alu density may be involved in shaping the deletion pattern.

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 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 score0.206
Threshold uncertainty score0.250

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 head0.305
Teacher spread0.286 · 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 teacher head, 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

Citations56
Published2006
Admission routes2
Has abstractyes

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