Is INHBE Only Half of the Activin Story?

The next frontier in obesity therapeutics is no longer simply about how much weight a patient loses, but the metabolic quality of that loss. Where does the displaced lipid go, and is visceral fat reduced while lean mass is preserved? New data from Regeneron surrounding INHBC and INHBE are directly challenging the single-target view of the Activin E–ALK7 pathway, suggesting that achieving truly high-quality weight loss may require a more nuanced, dual-target approach.

Figure 1. Inhbc/Inhbe double-knockout study presented at the 2026 ADA Scientific Sessions ^[1].

That distinction matters as the field increasingly focuses on “high-quality weight loss”: reducing visceral and excess fat while preserving lean mass and improving, rather than redistributing, cardiometabolic risk.

Few emerging targets illustrate this challenge as clearly as INHBE, the liver-enriched gene encoding Activin E. Human genetics made INHBE an attractive obesity target. RNAi therapeutics targeting INHBE have since moved into clinical development, with early human data showing reductions in visceral fat and encouraging body-composition profiles ^[2-3]. But experimental studies in mice have also exposed a biological paradox: removing Inhbe can reduce adiposity while simultaneously promoting hepatic lipid accumulation and insulin resistance ^[4].

Now, new data presented at the 2026 American Diabetes Association Scientific Sessions suggest that INHBE may represent only part of a broader Activin network. The missing piece could be INHBC, or Activin C.

Human Genetics Put INHBE on the Obesity Map

The therapeutic rationale for INHBE emerged largely from human genetics. Rare predicted loss-of-function variants in INHBE have been associated with more favorable fat distribution and lower metabolic risk, helping establish INHBE as a genetically supported target for obesity and cardiometabolic disease. Mechanistically, the biology is also compelling: liver-derived Activin E signals through ACVR1C, or ALK7, in adipocytes, where it suppresses lipolysis and promotes energy storage. Reducing INHBE activity could therefore increase lipid mobilization from adipose tissue and preferentially reduce visceral fat rather than simply drive nonspecific weight loss.

Figure 2. Rare predicted loss-of-function (pLOF) variants in INHBE are strongly associated with a favorable fat distribution phenotype ^[5].

This concept is already being tested clinically. Arrowhead's ARO-INHBE and Wave Life Sciences' WVE-007 are both GalNAc-siRNA programs designed to suppress hepatic INHBE expression. Early clinical data from both programs have shown substantial Activin E reduction together with decreases in visceral or total fat, while WVE-007 has also reported preservation of lean mass ^[2-3]. These results have helped move INHBE into a broader discussion around body composition and “weight quality,” rather than body weight alone.

The INHBE Paradox: When Less Fat Does Not Mean Better Metabolism

The mouse data, however, suggest that the pathway is more complex. In preclinical models, loss of Inhbe or disruption of ALK7 can reduce adiposity by increasing adipose lipolysis, but this can be accompanied by increased fatty-acid flux, hepatic lipid accumulation, glucose intolerance and insulin resistance. In other words, less adipose tissue does not automatically mean better metabolism if mobilized lipid is redirected to the liver ^[6].

This creates a severe translational roadblock. While human genetics strongly link INHBE loss-of-function to healthier fat distribution, completely disrupting this pathway in standard mouse models can trigger metabolically unfavorable consequences. The discrepancy suggests that additional signals may shape the consequences of reduced Activin E activity. One candidate is INHBC, another liver-enriched member of the Activin family.

INHBC Enters the Activin E–ALK7 Story

INHBC encodes the βC subunit that forms Activin C, which can also signal through ALK7. Human genetic studies have reported higher circulating INHBC protein in carriers of INHBE loss-of-function variants, raising the possibility of a compensatory relationship between the two ligands. INHBC and INHBE also share substantial sequence and structural similarity and may participate in a broader signaling network involving Activin C, Activin E and heterodimeric ligands such as Activin AC and Activin AE.

Figure 3. Potential causal associations between circulating INHBC levels and the risk of cardiometabolic diseases ^[7].

At ADA 2026, Regeneron researchers added an important piece to this puzzle. After seven weeks of high-fat feeding, wild-type mice gained approximately 51% body weight, whereas Inhbc/Inhbe double-knockout mice gained only 19%. The double-knockout mice also showed improved insulin sensitivity and approximately 21% lower liver weight. Notably, the same overall protective phenotype was not observed with Inhbe or Acvr1c single knockout ^[1].

These findings shift the scientific question from “What happens when Activin E is inhibited?” to “How do Activin E and Activin C work together to regulate lipid storage, mobilization and redistribution?” They also raise the possibility that high-quality weight loss may depend on the balance between Activin E, Activin C and ALK7-related signaling rather than on a single ligand alone.

From Mechanism to Dual-Target Therapeutic Development

This emerging model changes how INHBE-targeted obesity therapeutics might be viewed. The INHBC findings add a question: whether simultaneous modulation of both targets can improve fat loss while maintaining favorable liver and metabolic outcomes?

For oligonucleotide drug developers, this emerging biology could open new directions. Current clinical programs predominantly target INHBE alone, but growing interest in INHBC and increasing RNAi patent activity suggest that INHBC single-target inhibition, combination approaches and INHBC/INHBE dual-target siRNA strategies may become increasingly relevant. Answering that question also places new demands on preclinical models. Dual-target programs need systems that can evaluate both human targets in the same genetic background, distinguish target-specific pharmacodynamic effects and support downstream measurements such as visceral fat, liver fat, insulin sensitivity and pathway signaling.

Translating INHBE/INHBC Biology into Better Preclinical Studies

To support this next stage of obesity and metabolic drug development, Cyagen has developed the huINHBC/huINHBE double-humanized mouse model (C001931). Because INHBC and INHBE are closely linked in the genome, conventional cross-breeding of single-humanized strains is highly inefficient and biologically imprecise. Cyagen solved this by replacing the corresponding mouse genomic region with the human INHBC/INHBE sequence in a single, elegantly integrated design.

The model retains the human INHBE promoter region and expresses both human INHBC and human INHBE while eliminating the corresponding mouse transcripts. RT-qPCR confirmed human INHBC and INHBE expression in liver, and human INHBE transcript levels were higher than those observed in an earlier huINHBE single-humanized strain.

Figure 4. Hepatic transcript levels of human and mouse INHBC and INHBE in huINHBC/huINHBE mice.

Serum human Activin E can also be specifically quantified using a validated ELISA without detectable cross-reactivity to human INHBC, providing a clearer pharmacodynamic readout for INHBE-directed studies.

Figure 5. Serum levels of human INHBE protein in different mouse strains.

Importantly, the model shows a stable baseline metabolic phenotype. Total cholesterol, triglycerides, HDL-C, LDL-C, AST and ALT were not significantly different from wild-type controls under baseline conditions, supporting its use in high-fat-diet obesity, insulin-resistance and metabolic efficacy studies.

Figure 6. Comparison of blood biochemical parameters between huINHBC/huINHBE mice and WT mice.

Beyond the double-humanized model, Cyagen has built a broader INHBE/INHBC model portfolio that includes Inhbe knockout mice, huINHBE/ob mice, and combination humanized models involving ALK7, GDF8, CIDEB and PCSK9. Together, these models can support single-target mechanism studies, receptor-pathway analysis, obesity comorbidity research, combination therapy and the preclinical evaluation of INHBC/INHBE dual-target inhibitory siRNA and other RNA-based therapeutics.

Figure 7. Cyagen’s related model portfolio.

As INHBE-targeting RNA medicines advance clinically and INHBC emerges as a potential second node in the pathway, the central question is becoming more nuanced. The goal is no longer simply to make adipose tissue smaller, but to control where lipid moves, how the liver responds and whether the resulting weight loss is metabolically healthier.

If that balance depends on the coordinated biology of Activin E, Activin C and ALK7-related signaling, then INHBE may indeed be only half of the Activin story.

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Reference

[1] Li D, Mastaitis J, Min SH, Goebel E, Liu Y, Ho A, Altarejos J. Double knockout of INHBC and INHBE protect against diet-induced obesity and insulin resistance in mice. Diabetes. 2026;75(Suppl 1):2555-P. doi:10.2337/db26-2555-P.

[2] Caracta C, Ghosh D, Goel V, Haegele J, Hart A, Narayanan P, Singh K, Strahs A, Wright CI. Interim results from INLIGHT, a Phase 1 study of investigational WVE-007, an INHBE GalNAc siRNA for the treatment of overweight and obesity. Diabetes. 2026;75(Suppl 1):1792-P. doi:10.2337/db26-1792-P.

[3] Arrowhead Pharmaceuticals, Inc. Arrowhead Pharmaceuticals presents new clinical data on RNAi-based obesity and MASH candidate ARO-INHBE at EASL 2026 [Internet]. Pasadena (CA): Arrowhead Pharmaceuticals, Inc.; 2026 May 27 [cited 2026 Aug 27]. Available from: https://ir.arrowheadpharma.com/news-releases/news-release-details/arrowhead-pharmaceuticals-presents-new-clinical-data-rnai-based

[4] Griffin JD, Buxton JM, Culver JA, Barnes R, Jordan EA, White AR, Flaherty SE, Bernardo B, Ross T, Bence KK, Birnbaum MJ. Hepatic Activin E mediates liver-adipose inter-organ communication, suppressing adipose lipolysis in response to elevated serum fatty acids. Mol Metab. 2023 Dec;78:101830. doi: 10.1016/j.molmet.2023.101830. Epub 2023 Oct 28. PMID: 38787338; PMCID: PMC10656223.

[5] Akbari P, Sosina OA, Bovijn J, et al. Multiancestry exome sequencing reveals INHBE mutations associated with favorable fat distribution and protection from diabetes. Nat Commun. 2022;13(1):4844.

[6] Adam RC, Pryce DS, Lee JS, et al. Activin E-ACVR1C cross talk controls energy storage via suppression of adipose lipolysis in mice. Proc Natl Acad Sci U S A. 2023;120(32):e2309967120. doi:10.1073/pnas.2309967120.

[7] Loh NY, et al. Bidirectional Mendelian Randomization Highlights Causal Relationships Between Circulating INHBC and Multiple Cardiometabolic Diseases and Traits. Diabetes. 2024;73(12):2084-2094.