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Record W2085126908 · doi:10.1093/humrep/17.11.3003-a

Reported relationship between increased CTG repeat lengths in myotonic dystrophy and azoospermia

2002· letter· en· W2085126908 on OpenAlexaffabout
Nicola Dean, Steven J. Phillips, Pei‐Ying S. Chan, Seang Lin Tan, Aasen Ao

Bibliographic record

VenueHuman Reproduction · 2002
Typeletter
Languageen
FieldNeuroscience
TopicGenetic Neurodegenerative Diseases
Canadian institutionsMcGill University
Fundersnot available
KeywordsMyotonic dystrophyAzoospermiaMedicineGynecologyAudiologyBiologyGeneticsInternal medicinePregnancyInfertility

Abstract

fetched live from OpenAlex

Dear Sir, We read with interest the analysis by Pan and colleagues. in which they conclude that, in the myotonic dystrophy protein kinase (DMPK) variable CTG repeat region, alleles of 18 or more repeat units are observed only in patients with non-obstructive azoospermia and not in controls (Pan et al., 2002). We have previously performed an analysis on the size of the DMPK CTG repeat in 118 male partners of couples undergoing IVF. Forty-three couples had male factor infertility, 52 had female factors, three had both male and female indications and 20 had unexplained infertility. None of the male partners had idiopathic azoospermia. The range of CTG repeat units elucidated in these 236 DMPK alleles was from 5–32 with a mean of 11 and median of 10. There were 15 males (12.7%) and 16 alleles (6.8%) found to carry a DMPK CTG of >18 repeat units of which 14 men had one allele >18 and one man had both alleles >18 repeat units. The range in these 16 larger alleles was 20–32 with an average CTG length of 23 and a median of 21. Thirteen of these 15 men had semen parameters defined as normozoospermic. Twelve couples underwent an IVF cycle with an average fertilization rate of 67% per couple. Three couples underwent ICSI, one for oligoasthenoteratozoospermia, one for obstructive azoospermia due to a previous vasectomy and one because few oocytes were collected. Within the total group there were six clinical pregnancies (40%) of which five (42%) were in the IVF group and one (33%) was in the ICSI group. In the study published by Pan et al. (2002) the analysis was carried out on men with idiopathic azoospermia and in a control group of men with proven fertility. The men we studied were from infertile couples who presented for IVF and constitute a different population to that reported in the publication. However, seven of the 15 men who were found to have these larger normal DMPK CTG repeats had fathered previous pregnancies without the help of assisted conception. Different ethnic groups are known to have different distributions of DMPK CTG repeat sizes (Davies et al., 1992; Imbert et al ., 1993; Zerylnick et al., 1995). The prevalence of larger normal DMPK CTG repeats (19–37) is higher in the Caucasian population than generally found in the Chinese population. In the Taiwanese population this is stated to be 1.4% (Pan et al., 2001). Based on this low frequency, it is necessary to test more than the 47 control individuals used in the published study, to definitively exclude the presence of these larger CTG repeats. We would expect, and observed, a higher percentage of males carrying this larger allele in our Canadian, predominantly Caucasian, population. However, as none of these males had idiopathic azoospermia and almost half of them had proven fertility, the suggestion that there is a correlation between idiopathic azoospermia and larger normal DMPK CTG repeats does not seem applicable in our study group. It could be that, in general, azoospermic men have larger CTG repeat units at the DMPK locus but, unlike the suggestion made by Pan and colleagues (2002), these larger repeats are not exclusive to this group and are also found in normozoospermic men. Therefore, the statement that the genetic defects associated with azoospermia could be linked to triplet repeat instability is unlikely to be valid, at least at the DMPK locus.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.312
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.113
GPT teacher head0.300
Teacher spread0.187 · 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.

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

Citations4
Published2002
Admission routes2
Has abstractyes

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