Infertility in Female Mice with a Gain-of-Function Mutation in the Luteinizing Hormone Receptor Is Due to Irregular Estrous Cyclicity, Anovulation, Hormonal Alterations, and Polycystic Ovaries1
Bibliographic record
Abstract
The luteinizing hormone receptor, LHCGR, is essential for fertility in males and females, and genetic mutations in the receptor have been identified that result in developmental and reproductive defects. We have previously generated and characterized a mouse model (KiLHR(D582G)) for familial male-limited precocious puberty caused by an activating mutation in the receptor. We demonstrated that the phenotype of the KiLHR(D582G) male mice is an accurate phenocopy of male patients with activating LHCGR mutations. In this study, we observed that unlike women with activating LHCGR mutations who are normal, female KiLHR(D582G) mice are infertile. Mice exhibit irregular estrous cyclicity, anovulation, and precocious puberty. A temporal study from 2-24 wk of age indicated elevated levels of progesterone, androstenedione, testosterone, and estradiol and upregulation of several steroidogenic enzyme genes. Ovaries of KiLHR(D582G) mice exhibited significant pathology with the development of large hemorrhagic cysts as early as 3 wk of age, extensive stromal cell hyperplasia and hypertrophy with luteinization, numerous atretic follicles, and granulosa cell tumors. Ovulation could not be rescued by the addition of exogenous gonadotropins. The body weights of the KiLHR(D582G) mice were higher than wild-type counterparts, but there was no increase in the body fat composition or metabolic abnormalities such as impaired glucose tolerance and insulin resistance. These studies demonstrate that activating LHCGR mutations do not produce the same phenotype in female mice as in humans and clearly illustrate species differences in the expression and regulation of LHCGR in the ovary, but not in the testis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".