Hyperphagia in Bardet–Biedl syndrome: Pathophysiology, burden, and management
Bibliographic record
Abstract
Bardet-Biedl syndrome (BBS) is a rare, genetically heterogeneous, and highly pleiotropic autosomal recessive ciliopathy. Patients typically present with early loss of vision, hyperphagia, severe obesity, learning difficulties, and renal dysfunction. In patients with BBS, dysfunction of the immotile primary cilia in the hypothalamic melanocortin-4 receptor (MC4R) pathway responsible for controlling energy balance, hunger, and satiety results in severe hyperphagia manifesting in food-seeking behaviors that drive the development of obesity early in childhood. These behaviors have negative impacts on many areas of the lives of patients with BBS and their families/caregivers, including sleep, mood, school/work, and social/family relationships. Additionally, many patients feel stigmatized due to their hyperphagia-associated food-seeking behaviors and the resulting obesity, which exacerbates the impacts of hyperphagia on quality of life. Early identification and management of hyperphagia in patients with BBS is key: mitigating food-seeking and weight gain can improve quality of life and reduce the risk of metabolic and cardiovascular diseases that is increased in patients with BBS. Until recently, the only treatment strategies available were lifestyle and diet modifications. However, targeted treatment with the novel MC4R agonist setmelanotide now offers an effective management option to reduce hyperphagia and weight in patients with BBS, improving overall health and quality of life.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
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".