Low density lipoprotein receptor‐related protein 5 (<i>LRP5</i>) mutations and osteoporosis, impaired glucose metabolism and hypercholesterolaemia
Bibliographic record
Abstract
OBJECTIVE: Mutations in the low-density lipoprotein receptor-related protein 5 gene (LRP5) underlie osteoporosis-pseudoglioma syndrome. Animal models implicate a role for LRP5 in lipid and glucose homeostasis. The objective was to evaluate metabolic consequences of LRP5 mutations in humans. DESIGN AND PATIENTS: Thirteen Finnish individuals with homozygous or heterozygous LRP5 mutations were assessed for bone health, glucose and lipid metabolism, and for serum serotonin concentration. Results were compared with findings in family members without mutations. MEASUREMENTS: Bone mineral density (BMD), vertebral morphology, oral and intravenous glucose tolerance tests, lipid profile and serum serotonin concentrations. RESULTS: Two individuals were homozygous for R570W, one compound heterozygous for R570W and R1036Q, and 10 were heterozygous (six for R570W, three for R1036Q and one for R925C). Subjects with two LRP5 mutations had multiple spinal fractures and low BMD. Subjects with one mutation had significantly lower median lumbar spine (P = 0.004) and femoral neck (P = 0.005) BMD Z-scores, and more often vertebral fractures than the 18 individuals without mutations. Of the 12 subjects with LRP5 mutation six had diabetes and one had impaired glucose tolerance. Intravenous glucose tolerance tests suggested impaired beta-cell function; no insulin resistance was observed. Prevalence of hypercholesterolaemia was similar in mutation positive and negative subjects. Serum serotonin concentrations showed a trend towards higher concentrations in subjects with LRP5 mutation. CONCLUSIONS: We found high prevalence of osteoporosis and abnormal glucose metabolism in subjects with LRP5 mutation(s). Further studies are needed to establish the role of LRP5 in glucose and lipid metabolism.
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 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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".