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Record W2565209491 · doi:10.1016/j.molmet.2016.12.009

Dipeptidyl peptidase-4 inhibitor treatment induces a greater increase in plasma levels of bioactive GIP than GLP-1 in non-diabetic subjects

2017· article· en· W2565209491 on OpenAlexaff
Tsuyoshi Yanagimachi, Yukihiro Fujita, Yasutaka Takeda, Jun Honjo, Hidemitsu Sakagami, Hiroya Kitsunai, Yumi Takiyama, Atsuko Abiko, Yuichi Makino, Timothy J. Kieffer, Masakazu Haneda

Bibliographic record

VenueMolecular Metabolism · 2017
Typearticle
Languageen
FieldMedicine
TopicDiabetes Treatment and Management
Canadian institutionsUniversity of British Columbia
FundersJapan Society for the Promotion of ScienceJapan Diabetes FoundationJapan Diabetes SocietyEli Lilly and Company
KeywordsIncretinDipeptidyl peptidaseBioassayGlucagon-like peptide-1Gastric inhibitory polypeptideInternal medicineEndocrinologyReceptorDipeptidyl peptidase-4LuciferaseBiological activityChemistryDipeptidyl peptidase-4 inhibitorTransfectionGlucagonIn vitroMedicineType 2 diabetesDiabetes mellitusBiologyInsulinBiochemistryEnzymeGene

Abstract

fetched live from OpenAlex

OBJECTIVE: Glucose-dependent insulinotropic polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) possess multiple bioactive isoforms that are rendered non-insulinotropic by the enzyme dipeptidyl peptidase-4 (DPP-4). Recently, some ELISA kits have been developed to specifically measure "active" GIP and GLP-1, but it is unclear if these kits can accurately quantify all bioactive forms. Therefore, it remains uncertain to what extent treatment with a DPP-4 inhibitor boosts levels of biologically active GIP and GLP-1. Thus, we evaluated our novel receptor-mediated incretin bioassays in comparison to commercially available ELISA kits using plasma samples from healthy subjects before and after DPP-4 inhibitor administration. METHODS: We utilized cell lines stably co-transfected with human GIP or GLP-1 receptors and a cAMP-inducible luciferase expression construct for the bioassays and commercially available ELISA kits. Assays were tested with synthetic GIP and GLP-1 receptor agonists and plasma samples collected from subjects during a 75 g oral glucose tolerance test (OGTT) performed before or following 3-day administration of a DPP-4 inhibitor. RESULTS: increased luciferase activity similarly to GIP(1-42) in the GIP bioassay but was not detectable by either a total or active GIP ELISA kit. During an OGTT, total GIP levels measured by ELISA rapidly increased from 0 min to 15 min, subsequently reaching a peak of 59.2 ± 8.3 pmol/l at 120 min. In contrast, active GIP levels measured by the bioassay peaked at 15 min (43.4 ± 6.4 pmol/l) and then progressively diminished at all subsequent time points. Strikingly, at 15 min, active GIP levels as determined by the bioassay reached levels approximately 20-fold higher after the DPP-4 inhibitor treatment, while total and active GIP levels determined by ELISA were increased just 1.5 and 2.1-fold, respectively. In the absence of DPP-4 inhibition, total GLP-1 levels measured by ELISA gradually increased up to 90 min, reaching 23.5 ± 2.4 pmol/l, and active GLP-1 levels determined by the bioassay did not show any apparent peak. Following administration of a DPP-4 inhibitor there was an observable peak of active GLP-1 levels as determined by the bioassay at 15 min after oral glucose load, reaching 11.0 ± 0.62 pmol/l, 1.4-fold greater than levels obtained without DPP-4 inhibitor treatment. In contrast, total GLP-1 levels determined by ELISA were decreased after DPP-4 inhibitor treatment. CONCLUSION: Our results using bioassays indicate that there is a greater increase in plasma levels of bioactive GIP than GLP-1 in subjects treated with DPP-4 inhibitors, which may be unappreciated using conventional ELISAs.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.264
Teacher spread0.245 · 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 designBench or experimental
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

Citations37
Published2017
Admission routes1
Has abstractyes

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