Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

ACC inhibitor alone or co-administered with a DGAT2 inhibitor in patients with non-alcoholic fatty liver disease: two parallel, placebo-controlled, randomized phase 2a trials

Nature Medicine volume 27, pages 1836–1848 (2021)Cite this article

Subjects

Abstract

Alterations in lipid metabolism might contribute to the pathogenesis of non-alcoholic fatty liver disease (NAFLD). However, no pharmacological agents are currently approved in the United States or the European Union for the treatment of NAFLD. Two parallel phase 2a studies investigated the effects of liver-directed ACC1/2 inhibition in adults with NAFLD. The first study (NCT03248882) examined the effects of monotherapy with a novel ACC1/2 inhibitor, PF-05221304 (2, 10, 25 and 50 mg once daily (QD)), versus placebo at 16 weeks of treatment; the second study (NCT03776175) investigated the effects of PF-05221304 (15 mg twice daily (BID)) co-administered with a DGAT2 inhibitor, PF-06865571 (300 mg BID), versus placebo after 6 weeks of treatment. The primary endpoint in both studies was percent change from baseline in liver fat assessed by magnetic resonance imaging–proton density fat fraction. Dose-dependent reductions in liver fat reached 50–65% with PF-05221304 monotherapy doses ≥10 mg QD; least squares mean (LSM) 80% confidence interval (CI) was −7.2 (−13.9, 0.0), −17.1 (−22.7, −11.1), −49.9 (−53.3, −46.2), −55.9 (−59.0, −52.4) and −64.8 (−67.5, −62.0) with 16 weeks placebo and PF-05221304 2, 10, 25 and 50 mg QD, respectively. The overall incidence of adverse events (AEs) did not increase with increasing PF-05221304 dose, except for a dose-dependent elevation in serum triglycerides (a known consequence of hepatic acetyl-coenzyme A carboxylase (ACC) inhibition) in 23/305 (8%) patients, leading to withdrawal in 13/305 (4%), and a dose-dependent elevation in other serum lipids. Co-administration of PF-05221304 and PF-06865571 lowered liver fat compared to placebo (placebo-adjusted LSM (90% CI) −44.6% (−54.8, −32.2)). Placebo-adjusted LSM (90% CI) reduction in liver fat was −44.5% (−55.0, −31.7) and −35.4% (−47.4, −20.7) after 6 weeks with PF-05221304 or PF-06865571 alone. AEs were reported for 10/28 (36%) patients after co-administered PF-05221304 and PF-06865571, with no discontinuations due to AEs, and the ACC inhibitor-mediated effect on serum triglycerides was mitigated, suggesting that PF-05221304 and PF-06865571 co-administration has the potential to address some of the limitations of ACC inhibition alone.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Patient disposition.
Fig. 2: PF-05221304 monotherapy effects on liver fat, liver enzymes, NASH-related biomarkers and fasting lipids in patients with NAFLD.
Fig. 3: PF-05221304 and PF-06865571 co-administration reverses ACC inhibitor-induced SREBP-1 activation and circulating triglyceride increases in Western diet-fed rats and is more efficacious than monotherapy in the CDAHFD rat fibrosis model.
Fig. 4: PF-05221304 and PF-06865571 co-administration effects on liver fat, liver enzymes and markers of lipid metabolism in patients with NAFLD.

Similar content being viewed by others

Data availability

Upon reasonable request, and subject to certain criteria, conditions and exceptions (see https://www.pfizer.com/science/clinical-trials/trial-data-and-results for more information), Pfizer will provide access to individual de-identified participant data from Pfizer-sponsored global interventional clinical studies conducted for medicines, vaccines and medical devices (1) for indications that have been approved in the United States and/or the European Union or (2) in programs that have been terminated (that is, development for all indications has been discontinued). Pfizer will also consider requests for the protocol, data dictionary and statistical analysis plan. Data may be requested from Pfizer trials 24 months after study completion. The de-identified participant data will be made available to researchers whose proposals meet the research criteria and other conditions, and for which an exception does not apply, via a secure portal. To gain access, data requestors must enter into a data access agreement with Pfizer. Requests are handled on a case-by-case basis depending on the nature of the request and in the order they are received. See https://www.pfizer.com/science/clinical-trials/trial-data-and-results for more information. Source data are provided with this paper.

References

  1. Chalasani, N. et al. The diagnosis and management of nonalcoholic fatty liver disease: practice guidance from the American Association for the Study of Liver Diseases. Hepatology 67, 328–357 (2018).

    Article  PubMed  Google Scholar 

  2. EASL-EASD-EASO. EASL-EASD-EASO clinical practice guidelines for the management of non-alcoholic fatty liver disease. J. Hepatol. 64, 1388–1402 (2016).

    Article  Google Scholar 

  3. Brunt, E. M., Janney, C. G., Di Bisceglie, A. M., Neuschwander-Tetri, B. A. & Bacon, B. R. Nonalcoholic steatohepatitis: a proposal for grading and staging the histological lesions. Am. J. Gastroenterol. 94, 2467–2474 (1999).

    Article  CAS  PubMed  Google Scholar 

  4. Marengo, A., Jouness, R. I. & Bugianesi, E. Progression and natural history of nonalcoholic fatty liver disease in adults. Clin. Liver. Dis. 20, 313–324 (2016).

    Article  PubMed  Google Scholar 

  5. Rafiq, N. et al. Long-term follow-up of patients with nonalcoholic fatty liver. Clin. Gastroenterol. Hepatol. 7, 234–238 (2009).

    Article  PubMed  Google Scholar 

  6. Lambert, J. E., Ramos-Roman, M. A., Browning, J. D. & Parks, E. J. Increased de novo lipogenesis is a distinct characteristic of individuals with nonalcoholic fatty liver disease. Gastroenterology 146, 726–735 (2014).

    Article  CAS  PubMed  Google Scholar 

  7. Dowman, J. K., Tomlinson, J. W. & Newsome, P. N. Pathogenesis of non-alcoholic fatty liver disease. QJM 103, 71–83 (2010).

    Article  CAS  PubMed  Google Scholar 

  8. Esler, W. P. & Bence, K. K. Metabolic targets in nonalcoholic fatty liver disease. Cell. Mol. Gastroenterol. Hepatol. 8, 247–267 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  9. Saggerson, D. Malonyl-CoA, a key signaling molecule in mammalian cells. Annu. Rev. Nutr. 28, 253–272 (2008).

    Article  CAS  PubMed  Google Scholar 

  10. Abu-Elheiga, L. et al. The subcellular localization of acetyl-CoA carboxylase 2. Proc. Natl Acad. Sci. USA 97, 1444–1449 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. McGarry, J. D. & Brown, N. F. The mitochondrial carnitine palmitoyltransferase system. From concept to molecular analysis. Eur. J. Biochem. 244, 1–14 (1997).

    Article  CAS  PubMed  Google Scholar 

  12. Harwood, H. J. Jr. et al. Isozyme-nonselective N-substituted bipiperidylcarboxamide acetyl-CoA carboxylase inhibitors reduce tissue malonyl-CoA concentrations, inhibit fatty acid synthesis, and increase fatty acid oxidation in cultured cells and in experimental animals. J. Biol. Chem. 278, 37099–37111 (2003).

    Article  CAS  PubMed  Google Scholar 

  13. Ross, T. T. et al. Acetyl-CoA carboxylase inhibition improves multiple dimensions of NASH pathogenesis in model systems. Cell. Mol. Gastroenterol. Hepatol. 10, 829–851 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  14. Stiede, K. et al. Acetyl-coenzyme A carboxylase inhibition reduces de novo lipogenesis in overweight male subjects: a randomized, double-blind, crossover study. Hepatology 66, 324–334 (2017).

    Article  CAS  PubMed  Google Scholar 

  15. Griffith, D. A. et al. Decreasing the rate of metabolic ketone reduction in the discovery of a clinical acetyl-CoA carboxylase inhibitor for the treatment of diabetes. J. Med. Chem. 57, 10512–10526 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Loomba, R. et al. GS-0976 reduces hepatic steatosis and fibrosis markers in patients with nonalcoholic fatty liver disease. Gastroenterology 155, 1463–1473 (2018).

    Article  CAS  PubMed  Google Scholar 

  17. Kim, C. W. et al. Acetyl CoA carboxylase inhibition reduces hepatic steatosis but elevates plasma triglycerides in mice and humans: a bedside to bench investigation. Cell. Metab. 26, 394–406 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Goedeke, L. et al. Acetyl-CoA carboxylase inhibition reverses NAFLD and hepatic insulin resistance but promotes hypertriglyceridemia in rodents. Hepatology 68, 2197–2211 (2018).

    Article  CAS  PubMed  Google Scholar 

  19. Choi, C. S. et al. Suppression of diacylglycerol acyltransferase-2 (DGAT2), but not DGAT1, with antisense oligonucleotides reverses diet-induced hepatic steatosis and insulin resistance. J. Biol. Chem. 282, 22678–22688 (2007).

    Article  CAS  PubMed  Google Scholar 

  20. Yu, X. X. et al. Antisense oligonucleotide reduction of DGAT2 expression improves hepatic steatosis and hyperlipidemia in obese mice. Hepatology 42, 362–371 (2005).

    Article  CAS  PubMed  Google Scholar 

  21. Yen, C. L., Stone, S. J., Koliwad, S., Harris, C. & Farese, R. V. Jr. Thematic review series: glycerolipids. DGAT enzymes and triacylglycerol biosynthesis. J. Lipid Res. 49, 2283–2301 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Amin, N. B. et al. Targeting diacylglycerol acyltransferase 2 for the treatment of nonalcoholic steatohepatitis. Sci. Transl. Med. 11, eaav9701 (2019).

    Article  CAS  PubMed  Google Scholar 

  23. Saxena, A., Chidsey, K., Somayaji, V., Ogden, A. & Duvvuri, S. Diacylglycerol acyltransferase 2 (DGAT2) inhibitor PF-06865571 reduces liver fat by MRI–PDFF after 2 weeks in adults with NAFLD. Hepatology 70, 1260A (2019).

    Google Scholar 

  24. Loomba, R. et al. An international, randomized, placebo-controlled phase 2 trial demonstrates novel effects of DGAT2 antisense inhibition in reducing steatosis without causing hypertriglyceridemia in T2DM patients. J. Hepatol. 70, e67–e68 (2019).

    Article  Google Scholar 

  25. Friedman, S. L., Neuschwander-Tetri, B. A., Rinella, M. & Sanyal, A. J. Mechanisms of NAFLD development and therapeutic strategies. Nat. Med. 24, 908–922 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Fiorucci, S., Biagioli, M. & Distrutti, E. Future trends in the treatment of non-alcoholic steatohepatitis. Pharmacol. Res. 134, 289–298 (2018).

    Article  CAS  PubMed  Google Scholar 

  27. Adams, L. A. et al. The natural history of nonalcoholic fatty liver disease: a population-based cohort study. Gastroenterology 129, 113–121 (2005).

    Article  PubMed  Google Scholar 

  28. Ekstedt, M. et al. Fibrosis stage is the strongest predictor for disease-specific mortality in NAFLD after up to 33 years of follow-up. Hepatology 61, 1547–1554 (2015).

    Article  CAS  PubMed  Google Scholar 

  29. Bates, J. et al. Acetyl-CoA carboxylase inhibition disrupts metabolic reprogramming during hepatic stellate cell activation. J. Hepatol. 73, 896–905 (2020).

    Article  CAS  PubMed  Google Scholar 

  30. Kelly, K. L. et al. De novo lipogenesis is essential for platelet production in humans. Nat. Metab. 2, 1163–1178 (2020).

    Article  CAS  PubMed  Google Scholar 

  31. Lawitz, E. J. et al. Acetyl-CoA carboxylase inhibitor GS-0976 for 12 weeks reduces hepatic de novo lipogenesis and steatosis in patients with nonalcoholic steatohepatitis. Clin. Gastroenterol. Hepatol. 16, 1983–1991 (2018).

    Article  CAS  PubMed  Google Scholar 

  32. Younossi, Z. M. et al. From NAFLD to MAFLD: implications of a premature change in terminology. Hepatology 73, 1194–1198 (2020).

    Article  Google Scholar 

  33. Stine, J. G. et al. Change in MRI–PDFF and histologic response in patients with nonalcoholic steatohepatitis: a systematic review and meta-analysis. Clin. Gastroenterol. Hepatol. 31, 31220–31229 (2020).

    Google Scholar 

  34. Patel, J. et al. Association of noninvasive quantitative decline in liver fat content on MRI with histologic response in nonalcoholic steatohepatitis. Ther. Adv. Gastroenterol. 9, 692–701 (2016).

    Article  CAS  Google Scholar 

  35. Savage, D. B. et al. Reversal of diet-induced hepatic steatosis and hepatic insulin resistance by antisense oligonucleotide inhibitors of acetyl-CoA carboxylases 1 and 2. J. Clin. Invest. 116, 817–824 (2006).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Bergman, A. et al. Safety, tolerability, pharmacokinetics and pharmacodynamics of a liver-targeting ACC inhibitor (PF-05221304): a three-part randomized phase 1 study. Clin. Pharmacol. Drug. Dev. 9, 514–526 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Lawitz, E. J. et al. Fenofibrate mitigates increases in serum triglycerides due to the ACC inhibitor firsocostat in patients with advanced fibrosis due to NASH: a phase 2 randomized trial. American Association for the Study of Liver Diseases meeting, Boston, MA, USA (2019).

  38. Fabbrini, E. et al. Effect of fenofibrate and niacin on intrahepatic triglyceride content, very low-density lipoprotein kinetics, and insulin action in obese subjects with nonalcoholic fatty liver disease. J. Clin. Endocrinol. Metab. 95, 2727–2735 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Oscarsson, J. et al. Effects of free omega-3 carboxylic acids and fenofibrate on liver fat content in patients with hypertriglyceridemia and non-alcoholic fatty liver disease: a double-blind, randomized, placebo-controlled study. J. Clin. Lipido. 12, 1390–1403 (2018).

    Article  Google Scholar 

  40. Parker, H. M. et al. Effect of fish oil supplementation on hepatic and visceral fat in overweight men: a randomized controlled trial. Nutrients 11, 475 (2019).

    Article  CAS  PubMed Central  Google Scholar 

  41. Lawler, P. R. et al. Atherogenic lipoprotein determinants of cardiovascular disease and residual risk among individuals with low low-density lipoprotein cholesterol. J. Am. Heart Assoc. 6, e005549 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  42. Mora, S. et al. Atherogenic lipoprotein subfractions determined by ion mobility and first cardiovascular events after random allocation to high-intensity statin or placebo: the justification for the use of statins in prevention: an Intervention Trial Evaluating Rosuvastatin (JUPITER) trial. Circulation 132, 2220–2229 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Kanter, J. E. et al. Increased apolipoprotein C3 drives cardiovascular risk in type 1 diabetes. J. Clin. Invest. 129, 4165–4179 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  44. Brown, W. V. & Baginsky, M. L. Inhibition of lipoprotein lipase by an apoprotein of human very low density lipoprotein. Biochem. Biophys. Res. Commun. 46, 375–382 (1972).

    Article  CAS  PubMed  Google Scholar 

  45. Ginsberg, H. N. et al. Apolipoprotein B metabolism in subjects with deficiency of apolipoproteins CIII and AI. Evidence that apolipoprotein CIII inhibits catabolism of triglyceride-rich lipoproteins by lipoprotein lipase in vivo. J. Clin. Invest. 78, 1287–1295 (1986).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. Wang, C. S., McConathy, W. J., Kloer, H. U. & Alaupovic, P. Modulation of lipoprotein lipase activity by apolipoproteins. Effect of apolipoprotein C-III. J. Clin. Invest. 75, 384–390 (1985).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Yamaguchi, K. et al. Inhibiting triglyceride synthesis improves hepatic steatosis but exacerbates liver damage and fibrosis in obese mice with nonalcoholic steatohepatitis. Hepatology 45, 1366–1374 (2007).

    Article  CAS  PubMed  Google Scholar 

  48. Gluchowski, N. L. et al. Hepatocyte deletion of triglyceride-synthesis enzyme acyl CoA: diacylglycerol acyltransferase 2 reduces steatosis without increasing inflammation or fibrosis in mice. Hepatology 70, 1972–1985 (2019).

    Article  CAS  PubMed  Google Scholar 

  49. Le, T. A. et al. Effect of colesevelam on liver fat quantified by magnetic resonance in nonalcoholic steatohepatitis: a randomized controlled trial. Hepatology 56, 922–932 (2012).

    Article  CAS  PubMed  Google Scholar 

  50. Loomba, R. et al. Ezetimibe for the treatment of nonalcoholic steatohepatitis: assessment by novel magnetic resonance imaging and magnetic resonance elastography in a randomized trial (MOZART trial). Hepatology 61, 1239–1250 (2015).

    Article  CAS  PubMed  Google Scholar 

  51. Caussy, C., Reeder, S. B., Sirlin, C. B. & Loomba, R. Noninvasive, quantitative assessment of liver fat by MRI–PDFF as an endpoint in NASH trials. Hepatology 68, 763–772 (2018).

    Article  PubMed  Google Scholar 

  52. Mashhood, A. et al. Reproducibility of hepatic fat fraction measurement by magnetic resonance imaging. J. Magn. Reson. Imaging 37, 1359–1370 (2013).

    Article  PubMed  Google Scholar 

Download references

Acknowledgements

These studies were sponsored by Pfizer Inc. The authors would like to thank the patients who offered their time, interest and participation as well as the staff across all sites who recruited at least one patient in the clinical studies. The authors would also like to thank colleagues at Nordic Bioscience, M. Karsdal and D. J. Leeming, for their help with analysis of the serum procollagens—Pro-C3, Pro-C4, Pro-C6 and Pro-C18—in NCT03248882; M. Birnbaum for helpful discussions; K. Kelly and D. Beebe for help with in vivo studies; J. Morin and D. Shanthappa for assistance with shear-wave elastography measurements; J. Travers and A. Robertson for histology; S. Vargas for microscopic imaging of histological sections; and P. Garnick for clinical study management. Medical writing support, under the direction of the authors, was provided by C. Cairney, CMC Connect, McCann Health Medical Communications, and was funded by Pfizer in accordance with Good Publication Practice guidelines (Ann. Intern. Med. 163, 461–464 (2015)).

Author information

Author notes

  1. These authors contributed equally: Roberto A. Calle, Neeta B. Amin.

Authors and Affiliations

  1. Internal Medicine Research Unit, Pfizer Inc, Cambridge, MA, USA

    Roberto A. Calle, Neeta B. Amin, Trenton T. Ross, Collin Crowley, Anthony Rinaldi, Kou Kou, Greg Tesz, Robert Dullea, Kendra K. Bence, Albert M. Kim, Jeffrey A. Pfefferkorn & William P. Esler

  2. Early Clinical Development, Pfizer Inc, Cambridge, MA, USA

    Santos Carvajal-Gonzalez, Arthur Bergman, Sudeepta Aggarwal, Jessica Mancuso, Veena Somayaji & Theresa A. Tuthill

  3. Aggarwal and Associates Limited, Brampton, ON, Canada

    Naresh Aggarwal

  4. Department of Infectious Diseases, Liver Diseases and Acquired Immune Deficiencies, Wrocław Medical University, Wrocław, Poland

    Malgorzata Inglot

  5. Dobrostan, Wrocław, Poland

    Malgorzata Inglot

  6. Drug Safety Research and Development Global Pathology, Pfizer Worldwide Research and Development, Cambridge, MA, USA

    Magalie Boucher

Authors
  1. Roberto A. Calle
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Neeta B. Amin
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Santos Carvajal-Gonzalez
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Trenton T. Ross
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Arthur Bergman
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sudeepta Aggarwal
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Collin Crowley
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Anthony Rinaldi
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jessica Mancuso
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Naresh Aggarwal
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Veena Somayaji
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Malgorzata Inglot
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Theresa A. Tuthill
    View author publications

    You can also search for this author in PubMed Google Scholar

  14. Kou Kou
    View author publications

    You can also search for this author in PubMed Google Scholar

  15. Magalie Boucher
    View author publications

    You can also search for this author in PubMed Google Scholar

  16. Greg Tesz
    View author publications

    You can also search for this author in PubMed Google Scholar

  17. Robert Dullea
    View author publications

    You can also search for this author in PubMed Google Scholar

  18. Kendra K. Bence
    View author publications

    You can also search for this author in PubMed Google Scholar

  19. Albert M. Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  20. Jeffrey A. Pfefferkorn
    View author publications

    You can also search for this author in PubMed Google Scholar

  21. William P. Esler
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

R.A.C., N. Amin, S.C.-G., T.T.R., T.A.T., A.B., A.M.K., J.A.P. and W.P.E. were responsible for study conceptualization. R.A.C., T.T.R., C.C., A.R., A.B., V.S., S.C.-G., G.T., R.D., K.K.B., A.M.K. and W.P.E. were responsible for study design. R.A.C., N. Amin, S.C.-G., T.T.R., A.B., C.C., A.R., J.M., T.A.T., K.K. and M.B. were responsible for data analysis. R.A.C., N. Amin, T.T.R., S.A., C.C., A.R., N. Aggarwal, M.I., T.A.T. and K.K. contributed to study conduct. All authors were responsible for data interpretation. N. Amin and T.A.T. provided resources and were responsible for project administration. N. Amin, S.C.-G. and A.B. were responsible for data curation. N. Amin and W.P.E. were responsible for funding acquisition. N. Amin was responsible for data visualization. R.A.C., N. Amin and T.T.R. were responsible for supervision. R.A.C., N. Amin, T.T.R., T.A.T. and W.P.E. wrote the original draft manuscripts. All authors reviewed and edited the manuscript and approved the final draft.

Corresponding author

Correspondence to William P. Esler.

Ethics declarations

Competing interests

R.A.C., N. Amin, S.C.-G., T.T.R., A.B., S.A., C.C., A.R., J.M., V.S.,T.A.T., K.K., M.B., G.T., R.D., K.K.B., A.M.K., J.A.P. and W.P.E. are employees of, and might hold stock options in, Pfizer Inc. N. Aggarwal and M.I. have no conflicts of interest to declare.

Additional information

Peer review information: Nature Medicine thanks Victor Volovici and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Jennifer Sargent was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 PF-05221304 efficacy in patients with NAFLD.

MMRM analysis of percent change from baseline over time in a, CAP in the overall population (Placebo n = 55, PF-05221304 2 mg, n = 56, 10 mg n = 62, 25 mg n = 52, 50 mg n = 53) and, b, VCTE in the NASH subgroup (Placebo n = 42, PF-05221304 2 mg, n = 43, 10 mg n = 42, 25 mg n = 39, 50 mg n = 42), using FibroScan®, and in c, T-bili (Placebo n = 40, PF-05221304 2 mg, n = 42, 10 mg n = 42, 25 mg n = 39, 50 mg n = 40), and d–g, procollagen isoforms in the NASH subgroup (Placebo n = 39, PF-05221304 2 mg, n = 40, 10 mg n = 42, 25 mg n = 35, 50 mg n = 38), and h, HbA1c in patients with T2D (Placebo n = 23, PF-05221304 2 mg, n = 23, 10 mg n = 26, 25 mg n = 25, 50 mg n = 23). i, Percent change from baseline to last observation in liver fat (MRI–PDFF) versus fasting serum triglyceridesa and j, percent change from baseline in fasting serum triglycerides versus baseline fasting serum triglyceridesa. MMRM analysis of percent change from baseline over time to week 16 in the overall population in k, total cholesterol (Placebo n = 58, PF-05221304 2 mg, n = 62, 10 mg n = 62, 25 mg n = 58, 50 mg n = 59), and l, Apo E (Placebo n = 57, PF-05221304 2 mg, n = 60, 10 mg n = 62, 25 mg n = 54, 50 mg n = 56). Data in panels a–h and k–l represent LSM (80% CI) from an MMRM model. aOne patient in the PF-05221304 10 mg treatment group with a percent change from baseline to last observation in fasting serum triglycerides of 1727.9 was excluded from these graphs for visualization but was included in the analysis. This patient had a percent change in liver fat of –38.9 and fasting serum triglycerides at baseline were 104 mg/dL (1.17 mmol/L). Apo, apolipoprotein; CAP, controlled attenuation parameter; CI, confidence interval; HbA1c, glycated hemoglobin; LSM, least squares mean; MMRM, mixed-effects model for repeated measures; MRI–PDFF, magnetic resonance imaging-proton density fat fraction; NAFLD, non-alcoholic fatty liver disease; NASH, non-alcoholic steatohepatitis; PF’1304, PF-05221304; Pro-C, procollagen type; T-bili, total bilirubin; T2D, type 2 diabetes; VCTE, vibration-controlled transient elastography.

Source data

Extended Data Fig. 2 Hepatic expression of SREBP target genes in the Western-diet rat study.

a, ACC1, b, FASN, c, SCD1, d, SREBP-1c, e, GPAT1, f, PCSK9. Data are mean (standard error) with n = 12 in each treatment group. Statistical significance based on ANOVA model adjusting for unequal variances between groups. ACC1, acetyl-coenzyme A carboxylase 1; ANOVA, analysis of variance; FASN, fatty acid synthase; GPAT1, glycerol-3-phosphate acyltransferase 1; PCSK9, proprotein convertase subtilisin/kexin type 9; SCD1, stearoyl coenzyme A desaturase 1; SREBP-1c, sterol regulatory element-binding protein 1c.

Source data

Extended Data Fig. 3 Liver fat and hepatic expression of pro-inflammatory cytokine (TNFA, IL1B, IL12A, IL12B, IFNG), anti-inflammatory cytokine (IL10), inflammatory cell infiltrate marker (CCL2, CCL11, CXCL1, CXCL9), inflammatory cell marker (CD4, CD68), and fibrogenic (ACTA2, COL1A1, COL3A1) genes in the CDAHFD rat fibrosis model relative to chow-fed rats.

a, Relative change in hepatic triglycerides (n = 12 per group). Relative expression of b, ACTA2 (n = 12 per group), c, COL1A1 (n = 12 per group), d, IL10 (control diet n = 10, vehicle n = 11, PF-05221304 n = 11, PF-06865571 n = 11, and PF-05221304 and PF-06865571 co-administration n = 10), e, CCL2 (n = 12 per group), f, CCL11 (n = 12 per group), g, TNF (control diet n = 11, vehicle n = 12, PF-05221304 n = 11, PF-06865571 n = 12, and PF-05221304 and PF-06865571 co-administration n = 11), h, CD4 (control diet n = 11, vehicle n = 12, PF-05221304 n = 11, PF-06865571 n = 12, and PF-05221304 and PF-06865571 co-administration n = 11), i, IL1B (n = 12 per group), j, CD68 (control diet n = 11, vehicle n = 12, PF-05221304 n = 10, PF-06865571 n = 12, and PF-05221304 and PF-06865571 co-administration, n = 12), k, IL12A (n = 12 per group), l, IL12B (control diet n = 11, vehicle n = 10, PF-05221304 n = 11, PF-06865571 n = 11, and PF-05221304 and PF-06865571 co-administration n = 12), m, IFNG (n = 12 per group, except control diet n = 11), n, CXCL1 (n = 12 per group), o, CXCL9 (control diet n = 12, vehicle n = 10, PF-05221304 n = 11, PF-06865571 n = 12, and PF-05221304 and PF-06865571 co-administration n = 12), p, COL3A1 (control diet n = 11, vehicle n = 12, PF-05221304 n = 10, PF-06865571 n = 11, and PF-05221304 and PF-06865571 co-administration n = 10). Data are mean (standard error). Statistical significance based on ANOVA model adjusting for unequal variances between groups. ACTA2, alpha smooth muscle actin; ANOVA, analysis of variance; choline-deficient, amino acid-defined, high-fat diet; IFN, interferon; IL, interleukin; PF’1304, PF-05221304 monotherapy; PF’5571, PF-06865571 monotherapy; PF’1304 + PF’5571, PF-05221304 and PF-06865571 co-administration; TNF, tumor necrosis factor.

Source data

Extended Data Fig. 4 Relative percent change from baseline in a, total cholesterol, b, HDL-C, and c, LDL-C at week 6, and d, liver fat as assessed by CAP over time to week 6, in patients with NAFLD.

Placebo n = 12, PF-05221304 n = 22, PF-06865571 n = 24, PF-05221304 and PF-06865571 n = 26. Data represent LSM (90% CI). Statistical significance versus placebo was pre-defined as a two-sided p value of <0.05 based on an ANCOVA model in panels a–c, and from an MMRM model with no adjustment for multiple comparisons in panel d. ANCOVA, analysis of covariance; CAP, controlled attenuation parameter; CI, confidence interval; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; LSM, least squares mean; MMRM, mixed-effects model for repeated measures; NAFLD, non-alcoholic fatty liver disease; PF’1304, PF-05221304 monotherapy; PF’5571, PF-06865571 monotherapy; PF’1304 + PF’5571, PF-05221304 and PF-06865571 co-administration.

Source data

Extended Data Fig. 5 Chemical structures of a, ACC inhibitor PF-05221304 and b, DGAT2 inhibitor PF-06865571.

ACC, acetyl-coenzyme A carboxylase; DGAT2, diacylglycerol acyltransferase 2.

Source data

Extended Data Fig. 6 Clinical study designs.

a, PF-05221304 monotherapy study design, b, steps to identifying the sponsor-defined population, based on pre-qualification and Screen 1 assessments in the PF-05221304 monotherapy study, c, PF-05221304 and PF-06865571 co-administration study design. All blood samples were collected after an overnight fast of ≥8 h. In the PF-05221304 monotherapy study, samples for clinical safety-related laboratory tests were collected at pre-qualification, Screen 1 (main study screen), baseline, and at all visits throughout the treatment and follow-up periods. Samples for exploratory biomarkers, including NASH-related biomarkers, apolipoproteins, and glycemic parameters were collected at baseline and day 1 and weeks 4, 8, 12, and 16 of treatment. Samples for fasting lipid profile and HbA1c were collected at all timepoints. Non-HDL-C was derived as total cholesterol minus HDL-C, and VLDL was calculated as triglycerides/5 and reported only when triglycerides <400 mg/dL. All other parameters were measured directly. In the 1st tier stratification of the PF-05221304 monotherapy study, patients classified in the diagnosed or presumed NASH subgroup had to have a documented liver biopsy with histological evidence of NASH within 24 months of Screen 1, or meet the following criteria at pre-qualification and again at Screen 1: liver stiffness measure ≥7.0 kPa based on FibroScan® assessment; ALT > ULN and ≤5× ULN. Patients with liver stiffness measure <7.0 kPa and ALT ≤ 1.25× ULN at pre-qualification and again at Screen 1 were classified as NAFLD with likely minimal inflammation and fibrosis. aRisk factors for NAFLD/NASH: BMI of ≥25 or ≥22.5 kg/m2 in Western or Asian sites, respectively; fasting plasma glucose ≥100 mg/dL (5.6 mmol/L); fasting serum HDL-C < 40 mg/dL (1 mmol/L) or <50 mg/dL (1.3 mmol/L) for males and females, respectively; fasting serum triglycerides ≥150 mg/dL (1.7 mmol/L); seated blood pressure ≥130/85 mm Hg; waist circumference ≥40 inches (102 cm) or ≥35 inches (89 cm) for males and females, respectively; or the use of pharmacological agents with the explicit purpose of improving glycemic control, increasing HDL-C, decreasing triglycerides, or controlling blood pressure. ALT, alanine aminotransferase; BMI, body mass index; CAP, controlled attenuation parameter; HDL-C, high-density lipoprotein cholesterol; MRI–PDFF, magnetic resonance imaging-proton density fat fraction; NAFLD, non-alcoholic fatty liver disease; NASH, non-alcoholic steatohepatitis; PBO, placebo; PF’1304, PF-05221304 monotherapy; PF’5571, PF-06865571 monotherapy; PF’1304 + PF’5571, PF-05221304 and PF-06865571 co-administration; ULN, upper limit of normal; VLDL, very-low-density lipoprotein; wks, weeks.

Source data

Supplementary information

Source data

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Calle, R.A., Amin, N.B., Carvajal-Gonzalez, S. et al. ACC inhibitor alone or co-administered with a DGAT2 inhibitor in patients with non-alcoholic fatty liver disease: two parallel, placebo-controlled, randomized phase 2a trials. Nat Med 27, 1836–1848 (2021). https://doi.org/10.1038/s41591-021-01489-1

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41591-021-01489-1

This article is cited by

Search

Advanced search

Quick links

Nature Briefing: Translational Research

Sign up for the Nature Briefing: Translational Research newsletter — top stories in biotechnology, drug discovery and pharma.

Get what matters in translational research, free to your inbox weekly. Sign up for Nature Briefing: Translational Research