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Record W4403153281 · doi:10.1210/jendso/bvae163.017

8040 Precision-Engineered Activin and GDF Ligand Trap HS235: A Novel Lean Mass-Preserving Treatment for Obesity

2024· article· en· W4403153281 on OpenAlexaff
Gauthier Schang, Mathilde De Molliens, Emilie Brûlé, Cristina Chauvet, Jean-François Denis, Ariane Sours, Vann Ganesh, Gilles Tremblay, Julia Schoelermann, Maureen O’Connor

Bibliographic record

VenueJournal of the Endocrine Society · 2024
Typearticle
Languageen
FieldMedicine
TopicAdvanced Breast Cancer Therapies
Canadian institutionsMicropharma (Canada)
Fundersnot available
KeywordsTrap (plumbing)Activin receptorChemistryLigand (biochemistry)Cell biologyBiologyPhysicsReceptorTransforming growth factorBiochemistry

Abstract

fetched live from OpenAlex

Abstract Disclosure: G. Schang: Employee; Self; 35Pharma. M. De Molliens: Employee; Self; 35Pharma. E. Brule: Employee; Self; 35Pharma. C. Chauvet: Employee; Self; 35Pharma. J. Denis: Employee; Self; 35Pharma. A. Sours: Employee; Self; 35Pharma. V. Ganesh: Employee; Self; 35Pharma. G. Tremblay: Employee; Self; 35Pharma. J. Schoelermann: Employee; Self; 35Pharma. M. O'Connor: Employee; Self; 35Pharma. Introduction: Novel anti-obesity medications including incretin mimetics have revolutionized the pharmacotherapy of obesity and type 2 diabetes, leading to unprecedented weight loss and clinically meaningful improvement of glucose metabolism and cardiometabolic health. However, incretins reduce body mass in a non-selective manner; both fat mass and lean mass are lost with incretin treatment. In obese patients treated with incretins, undesirable loss of lean body mass (LBM) can account for up to 40% of overall weight loss. Loss of LBM negatively impacts resting metabolic rate, leading to a weight loss plateau and often unsustainable results. Furthermore, individuals with sarcopenia, characterized by low muscle mass and strength, are at greater risk for heart failure. The preservation, or even increase, of LBM is therefore a desirable treatment goal for obesity pharmacotherapy and overall cardiometabolic health. Activins and growth differentiation factors (GDFs), which are members of the TGF-beta superfamily, are validated targets controlling body composition and metabolism. Specifically, blockade of activins and GDFs has anabolic effects in metabolically active tissues such as skeletal muscle and brown adipose tissue, while reducing white adipose tissue mass. Therefore, specific and selective blockade of activins and GDFs represents a novel anti-obesity treatment strategy which can act orthogonally to current anti-obesity medications. HS235 is an activin receptor ectodomain-based (ActR) Fc-fusion protein that has been rationally designed to attain optimal inhibition of ligands controlling body composition in obesity. Methods: A structure-assisted rational molecular engineering approach coupled with cell-based potency screening was employed to design HS235. To validate the anti-obesogenic potential of HS235, diet-induced obese (DIO) mice were injected with HS235, an incretin mimetic, or a combination of both. Fat mass, LBM, muscle weights, and biomarker readouts were assessed at the end of study. Results: In cell-based assays, HS235 potently and selectively neutralized activins and GDFs implicated in body composition. This translated to complete in vivo target engagement and pharmacodynamic response. In a DIO mouse model, both HS235 and the incretin mimetic significantly improved metabolic parameters and decreased fat mass, but only HS235 increased LBM, while incretin-based treatment led to LBM loss. Importantly, the addition of HS235 to the incretin mimetic lead to a synergistic fat mass loss and prevented loss of LBM. Conclusion: Potent and selective inhibition of activins and GDFs by HS235 represents a novel LBM preserving weight loss strategy orthogonal to incretin mimetics. Collectively, these data support the development of HS235 as a novel anti-obesity agent to complement currently approved incretin-based medications to improve quality of weight loss. Presentation: 6/3/2024

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.433
Threshold uncertainty score0.456

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
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)0.0000.000

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 head0.314
Teacher spread0.288 · 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 teacher head, 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

Citations1
Published2024
Admission routes1
Has abstractyes

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