Sudden infant death syndrome (SIDS) in African Americans: polymorphisms in the gene encoding the stress peptide pituitary adenylate cyclase‐activating polypeptide (PACAP)
Bibliographic record
Abstract
AIMS: Mice lacking pituitary adenylate cyclase-activating polypeptide (PACAP) are prone to sudden death in the second post-natal week, having respiratory and metabolic disturbances reminiscent of the human Sudden Infant Death Syndrome (SIDS). Here we test the hypothesis that the human PACAP gene is a site of genetic variance associated with SIDS in a cohort of 92 victims and 92 matched controls. METHODS: Using polymerase chain reaction and sequencing, we examined the PACAP gene in 92 SIDS cases (46 Caucasians and 46 African Americans) and 92 race- and gender-matched controls. RESULTS: We found no significant associations between PACAP and SIDS in Caucasians. However, in the African Americans, a non-synonymous single nucleotide polymorphism (i.e. an aspartic acid/glycine coding variant, rs2856966) within exon 2 of PACAP was significantly associated with SIDS (p = 0.004), as were haplotypes containing this polymorphism (p < 0.0001). Glycine was three times more likely at this location in the African-American SIDS victims (17 cases) than African-American controls (5 cases). CONCLUSION: These data are the first to suggest an association between a variant within the coding region of the PACAP gene and SIDS. Based on these findings, further investigations are warranted into the functional importance of PACAP signaling in neonatal survival and the role of PACAP-signaling abnormalities in SIDS.
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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) | 0.000 | 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 | 0.000 | 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".