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Record W2083639543 · doi:10.1371/journal.pone.0092957

Investigation of Genetic Variants, Birthweight and Hypothalamic-Pituitary-Adrenal Axis Function Suggests a Genetic Variant in the SERPINA6 Gene Is Associated with Corticosteroid Binding Globulin in the Western Australia Pregnancy Cohort (Raine) Study

2014· article· en· W2083639543 on OpenAlexafffund
Laura N. Anderson, Laurent Briollais, Helen C. Atkinson, Julie Marsh, Jingxiong Xu, Kristin L. Connor, Stephen G. Matthews, Craig E. Pennell, Stephen J. Lye

Bibliographic record

VenuePLoS ONE · 2014
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsUniversity of TorontoLunenfeld-Tanenbaum Research InstituteMount Sinai Hospital
FundersNational Health and Medical Research CouncilWomen and Infants Research FoundationCanadian Institutes of Health ResearchCurtin University of TechnologyMedical Research CouncilRaine Medical Research Foundation
KeywordsSingle-nucleotide polymorphismEndocrinologyCandidate geneInternal medicineBiologyAdrenocorticotropic hormoneTranscortinMedicineGeneticsGeneHormoneGlobulinGenotype

Abstract

fetched live from OpenAlex

BACKGROUND: The hypothalamic-pituitary-adrenal (HPA) axis regulates stress responses and HPA dysfunction has been associated with several chronic diseases. Low birthweight may be associated with HPA dysfunction in later life, yet human studies are inconclusive. The primary study aim was to identify genetic variants associated with HPA axis function. A secondary aim was to evaluate if these variants modify the association between birthweight and HPA axis function in adolescents. METHODS: Morning fasted blood samples were collected from children of the Western Australia Pregnancy Cohort (Raine) at age 17 (n = 1077). Basal HPA axis function was assessed by total cortisol, corticosteroid binding globulin (CBG), and adrenocorticotropic hormone (ACTH). The associations between 124 tag single nucleotide polymorphisms (SNPs) within 16 HPA pathway candidate genes and each hormone were evaluated using multivariate linear regression and penalized linear regression analysis using the HyperLasso method. RESULTS: The penalized regression analysis revealed one candidate gene SNP, rs11621961 in the CBG encoding gene (SERPINA6), significantly associated with total cortisol and CBG. No other candidate gene SNPs were significant after applying the penalty or adjusting for multiple comparisons; however, several SNPs approached significance. For example, rs907621 (p = 0.002) and rs3846326 (p = 0.003) in the mineralocorticoid receptor gene (NR3C2) were associated with ACTH and SERPINA6 SNPs rs941601 (p = 0.004) and rs11622665 (p = 0.008), were associated with CBG. To further investigate our findings for SERPINA6, rare and common SNPs in the gene were imputed from the 1,000 genomes data and 8 SNPs across the gene were significantly associated with CBG levels after adjustment for multiple comparisons. Birthweight was not associated with any HPA outcome, and none of the gene-birthweight interactions were significant after adjustment for multiple comparisons. CONCLUSIONS: Our study suggests that genetic variation in the SERPINA6 gene may be associated with altered CBG levels during adolescence. Replication of these findings is required.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.056
GPT teacher head0.237
Teacher spread0.181 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations14
Published2014
Admission routes2
Has abstractyes

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