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Record W2474399366 · doi:10.1186/s12864-016-2785-0

Genome-wide association study of prolactin levels in blood plasma and cerebrospinal fluid

2016· article· en· W2474399366 on OpenAlexfundno aff
Lyndsay A. Staley, Mark Ebbert, Sheradyn Parker, Matthew H. Bailey, Perry G. Ridge, Alison Goate, John Kauwe

Bibliographic record

VenueBMC Genomics · 2016
Typearticle
Languageen
FieldMedicine
TopicGrowth Hormone and Insulin-like Growth Factors
Canadian institutionsnot available
FundersNational Institute on AgingNational Institute of Biomedical Imaging and BioengineeringCanadian Institutes of Health ResearchUniversity of California, San FranciscoUniversity of California, San DiegoNational Institutes of HealthIXICOServierUniversity of California, DavisEisaiGenentechErasmus Medisch CentrumBundesministerium für Bildung und ForschungHjartaverndNorthern California Institute for Research and EducationPfizerBiogenBioClinicaF. Hoffmann-La RocheUniversity of PennsylvaniaUniversity of Southern CaliforniaBrigham Young UniversityWellcome TrustSynarcNational Heart, Lung, and Blood InstituteNovartis Pharmaceuticals CorporationU.S. Department of DefenseEli Lilly and CompanyBristol-Myers SquibbAlzheimer's AssociationFoundation for the National Institutes of HealthMedpaceBrigham and Women's HospitalAlzheimer's Disease Neuroimaging InitiativeMedical Research CouncilMeso Scale Diagnostics
KeywordsProlactinCerebrospinal fluidBiologyLactationHormoneImmune systemSingle-nucleotide polymorphismEndocrinologyInternal medicineReproductionImmunologyGeneticsPregnancyMedicineNeuroscienceGeneGenotype

Abstract

fetched live from OpenAlex

BACKGROUND: Prolactin is a polypeptide hormone secreted by the anterior pituitary gland that plays an essential role in lactation, tissue growth, and suppressing apoptosis to increase cell survival. Prolactin serves as a key player in many life-critical processes, including immune system and reproduction. Prolactin is also found in multiple fluids throughout the body, including plasma and cerebrospinal fluid (CSF). METHODS: In this study, we measured prolactin levels in both plasma and CSF, and performed a genome-wide association study. We then performed meta-analyses using METAL with a significance threshold of p < 5 × 10(-8) and removed SNPs where the direction of the effect was different between the two datasets. RESULTS: We identified 12 SNPs associated with increased prolactin levels in both biological fluids. CONCLUSIONS: Our efforts will help researchers understand how prolactin is regulated in both CSF and plasma, which could be beneficial in research for the immune system and reproduction.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.010
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0010.003
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.026
GPT teacher head0.244
Teacher spread0.218 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

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