Molecular neuroanatomy of anorexia nervosa
Bibliographic record
Abstract
Abstract Anorexia nervosa is a complex eating disorder with genetic, metabolic, and psychosocial underpinnings. Using unbiased genome-wide methods, recent studies have associated a variety of genes with the disorder. We characterized these genes by projecting them into aggregated gene expression data from reference transcriptomic atlases of the prenatal and adult human brain. We found that genes from an induced stem cell study of anorexia nervosa are expressed at higher levels in the lateral parabrachial and the ventral tegmental areas. The adult expression enrichment of the lateral parabrachial is confirmed with genes from two independent genetic studies. In the fetal brain, enrichment of the ventral tegmental area is also observed for the six genes near the only common variant associated with the disorder (rs4622308). We also observed signals in the adult and fetal pontine raphe, but they were not observed when using the genes from the genetic studies. In addition to signals related to calcitonin gene-related peptide neurons and the tachykinin, we found more than the expected number of microglia marker genes within the gene sets. Using mouse transcriptomic data, we identified several anorexia nervosa associated genes that are differentially expressed during food deprivation. While these genes that respond to fasting are not enriched in the gene sets, we highlight RPS26 which is proximal to rs4622308. We did not observe expression enrichment in the cingulate cortex or hypothalamus suggesting other targets for deep brain stimulation should be considered for severe cases. This work improves our understanding of the neurobiological causes of anorexia nervosa by suggesting disturbances in subcortical appetitive circuits.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".