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:

Non-invasive monitoring of chronic liver disease via near-infrared and shortwave-infrared imaging of endogenous lipofuscin

An Author Correction to this article was published on 24 November 2020

This article has been updated

Abstract

Monitoring the progression of non-alcoholic fatty liver disease is hindered by a lack of suitable non-invasive imaging methods. Here, we show that the endogenous pigment lipofuscin displays strong near-infrared and shortwave-infrared fluorescence when excited at 808 nm, enabling label-free imaging of liver injury in mice and the discrimination of pathological processes from normal liver processes with high specificity and sensitivity. We also show that the near-infrared and shortwave-infrared fluorescence of lipofuscin can be used to monitor the progression and regression of liver necroinflammation and fibrosis in mouse models of non-alcoholic fatty liver disease and advanced fibrosis, as well as to detect non-alcoholic steatohepatitis and cirrhosis in biopsied samples of human liver tissue.

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

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

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

Fig. 1: Real-time and non-invasive imaging of quantifiable autofluorescent pigments in the livers of rodents with progressive fibrosis.
Fig. 2: Quantification of lipofuscin/ceroid pigment by autofluorescence microscopy in progressive liver fibrosis model tissue.
Fig. 3: Regression of liver fibrosis is accompanied by the reversal of the lipofuscin/ceroid autofluorescence signal.
Fig. 4: Tracking lipofuscin autofluorescence with the progression of NAFLD in a high-fat diet mouse model.
Fig. 5: Significant autofluorescence signal and fibrosis in a lipodystrophy mouse model.
Fig. 6: Liver injury in humans with restructuring of lipofuscin distribution and quantity.

Similar content being viewed by others

Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. The raw and analysed datasets generated during the study are too big to be publicly shared but are available for research purposes from the corresponding authors on reasonable request.

Change history

References

  1. Younossi, Z. M. et al. Global epidemiology of nonalcoholic fatty liver disease-Meta-analytic assessment of prevalence, incidence, and outcomes. Hepatology 64, 73–84 (2016).

    Article  PubMed  Google Scholar 

  2. Younossi, Z. et al. Global burden of NAFLD and NASH: trends, predictions, risk factors and prevention. Nat. Rev. Gastroenterol. Hepatol. 15, 11–20 (2018).

    Article  PubMed  Google Scholar 

  3. Ward, Z. J. et al. Projected U.S. state-level prevalence of adult obesity and severe obesity. N. Engl. J. Med. 381, 2440–2450 (2019).

    Article  PubMed  Google Scholar 

  4. Satapathy, S. K. & Sanyal, A. J. Epidemiology and natural history of nonalcoholic fatty liver disease. Semin. Liver Dis. 35, 221–235 (2015).

    Article  PubMed  Google Scholar 

  5. Brunt, E. M. et al. Nonalcoholic fatty liver disease. Nat. Rev. Dis. Primers 1, 15080 (2015).

  6. Kleiner, D. E. On beyond staging and grading: liver biopsy evaluation in a posttreatment world. Hepatology 65, 1432–1434 (2017).

    Article  PubMed  Google Scholar 

  7. Rockey, D. C., Caldwell, S. H., Goodman, Z. D., Nelson, R. C. & Smith, A. D. Liver biopsy. Hepatology 49, 1017–1044 (2009).

    Article  PubMed  Google Scholar 

  8. Dietrich, C. F. et al. EFSUMB guidelines and recommendations on the clinical use of liver ultrasound elastography. Ultraschall Med. 38, e16–e47 (2017).

    PubMed  Google Scholar 

  9. Masarone, M. et al. Role of oxidative stress in pathophysiology of nonalcoholic fatty liver disease. Oxid. Med. Cell. Longev. 2018, 9547613 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  10. Koyama, Y. & Brenner, D. A. Liver inflammation and fibrosis. J. Clin. Invest. 127, 55–64 (2017).

  11. Marcellin, P. & Kutala, B. K. Liver diseases: a major, neglected global public health problem requiring urgent actions and large-scale screening. Liver Int. 38(Suppl. 1), 2–6 (2018).

    Article  PubMed  Google Scholar 

  12. Vishwanath, K. & Ramanujam, N. in Encyclopedia of Analytical Chemistry (ed. Meyers, R.A.) 20–56 (John Wiley & Sons, 2011).

  13. Croce, A. C., Ferrigno, A., Bottiroli, G. & Vairetti, M. Autofluorescence-based optical biopsy: an effective diagnostic tool in hepatology. Liver Int. 38, 1160–1174 (2018).

    Article  CAS  PubMed  Google Scholar 

  14. Monici, M. Cell and tissue autofluorescence research and diagnostic applications. Biotechnol. Annu. Rev. 11, 227–256 (2005).

    Article  CAS  PubMed  Google Scholar 

  15. Frangioni, J. V. In vivo near-infrared fluorescence imaging. Curr. Opin. Chem. Biol. 7, 626–634 (2003).

    Article  CAS  PubMed  Google Scholar 

  16. Ntziachristos, V., Ripoll, J. & Weissleder, R. Would near-infrared fluorescence signals propagate through large human organs for clinical studies? Opt. Lett. 27, 333–335 (2002).

    Article  PubMed  Google Scholar 

  17. Lim, Y. T. et al. Selection of quantum dot wavelengths for biomedical assays and imaging. Mol. Imaging 2, 50–64 (2003).

    Article  CAS  PubMed  Google Scholar 

  18. Carr, J. A. et al. Shortwave infrared fluorescence imaging with the clinically approved near-infrared dye indocyanine green. Proc. Natl Acad. Sci. USA 115, 4465–4470 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Bruns, O. T. et al. Next-generation in vivo optical imaging with short-wave infrared quantum dots. Nat. Biomed. Eng. 1, 0056 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  20. Iwaisako, K. et al. Origin of myofibroblasts in the fibrotic liver in mice. Proc. Natl Acad. Sci. USA 111, E3297–E3305 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Delire, B., Stärkel, P. & Leclercq, I. Animal models for fibrotic liver diseases: what we have, what we need, and what is under development. J. Clin. Transl. Hepatol. 3, 53–66 (2015).

    Article  PubMed  PubMed Central  Google Scholar 

  22. Scholten, D., Trebicka, J., Liedtke, C. & Weiskirchen, R. The carbon tetrachloride model in mice. Lab. Anim. 49, 4–11 (2015).

    Article  CAS  PubMed  Google Scholar 

  23. Geerts, A. M. et al. Comparison of three research models of portal hypertension in mice: macroscopic, histological and portal pressure evaluation. Int. J. Exp. Pathol. 89, 251–263 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Tag, C. et al. Induction of experimental obstructive cholestasis in mice. Lab. Anim. 49, 70–80 (2015).

    Article  CAS  PubMed  Google Scholar 

  25. Majno, G. & Joris, I. in Cells, Tissues, and Disease: Principles of General Pathology (eds Majno, G. & Joris, I.) 74–128 (Oxford University Press, 2004).

  26. Terman, A. & Brunk, U. T. Lipofuscin. Int. J. Biochem. Cell Biol. 36, 1400–1404 (2004).

    Article  CAS  PubMed  Google Scholar 

  27. Rantakari, P. et al. Stabilin-1 expression defines a subset of macrophages that mediate tissue homeostasis and prevent fibrosis in chronic liver injury. Proc. Natl Acad. Sci. USA 113, 9298–9303 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Barden, H. The intragranular location of carboxyl groups in neuromelanin and lipofuscin in human brain and in meningeal melanosomes in mouse brain. J. Histochem. Cytochem. 34, 1271–1279 (1986).

    Article  CAS  PubMed  Google Scholar 

  29. Lillie, R. D. A Nile blue staining technic for the differentiation of melanin and lipofuscins. Stain Technol. 31, 151–153 (1956).

    Article  CAS  PubMed  Google Scholar 

  30. Evangelou, K. & Gorgoulis, V. G. in Oncogene-Induced Senescence: Methods and Protocols, Methods in Molecular Biology Vol. 1534 (ed. Nikiforov, M.) 111–119 (Humana Press, 2017).

  31. Everson Pearse, A. G. in Histochemistry Theoretical and Applied Vol. 2, 898–928 (Churchill Livingstone, 1985).

  32. Terman, A., Kurz, T., Navratil, M., Arriaga, E. A. & Brunk, U. T. Mitochondrial turnover and aging of long-lived postmitotic cells: the mitochondrial–lysosomal axis theory of aging. Antioxid. Redox Signal. 12, 503–535 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Seehafer, S. S. & Pearce, D. A. You say lipofuscin, we say ceroid: defining autofluorescent storage material. Neurobiol. Aging 27, 576–588 (2006).

    Article  CAS  PubMed  Google Scholar 

  34. Schnell, S. A., Staines, W. A. & Wessendorf, M. W. Reduction of lipofuscin-like autofluorescence in fluorescently labeled tissue. J. Histochem. Cytochem. 47, 719–730 (1999).

    Article  CAS  PubMed  Google Scholar 

  35. Erben, T., Ossig, R., Naim, H. Y. & Schnekenburger, J. What to do with high autofluorescence background in pancreatic tissues—an efficient Sudan black B quenching method for specific immunofluorescence labelling. Histopathology 69, 406–422 (2016).

    Article  PubMed  Google Scholar 

  36. Nazeer, S. S., Saraswathy, A., Shenoy, S. J. & Jayasree, R. S. Fluorescence spectroscopy as an efficient tool for staging the degree of liver fibrosis: an in vivo comparison with MRI. Sci. Rep. 8, 10967 (2018).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  37. Kisseleva, T. et al. Myofibroblasts revert to an inactive phenotype during regression of liver fibrosis. Proc. Natl Acad. Sci. USA 109, 9448–9453 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Duffield, J. S. et al. Selective depletion of macrophages reveals distinct, opposing roles during liver injury and repair. J. Clin. Invest. 115, 56–65 (2005).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Liu, C. et al. Kupffer cells are associated with apoptosis, inflammation and fibrotic effects in hepatic fibrosis in rats. Lab. Invest. 90, 1805–1816 (2010).

    Article  CAS  PubMed  Google Scholar 

  40. Beljaars, L. et al. Hepatic localization of macrophage phenotypes during fibrogenesis and resolution of fibrosis in mice and humans. Front. Immunol. 5, 430 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  41. Matsumoto, M. et al. An improved mouse model that rapidly develops fibrosis in non-alcoholic steatohepatitis. Int. J. Exp. Pathol. 94, 93–103 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Giannessi, F., Giambelluca, M. A., Scavuzzo, M. C. & Ruffoli, R. Ultrastructure of testicular macrophages in aging mice. J. Morphol. 263, 39–46 (2005).

    Article  PubMed  Google Scholar 

  43. Jara, M., Carballada, R. & Esponda, P. Age-induced apoptosis in the male genital tract of the mouse. Reproduction 127, 359–366 (2004).

    Article  CAS  PubMed  Google Scholar 

  44. Brunk, U. T. & Terman, A. Lipofuscin: mechanisms of age-related accumulation and influence on cell function. Free Radic. Biol. Med. 33, 611–619 (2002).

    Article  CAS  PubMed  Google Scholar 

  45. Softic, S. et al. Lipodystrophy due to adipose tissue-specific insulin receptor knockout results in progressive NAFLD. Diabetes 65, 2187–2200 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  46. 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 

  47. Alonso, C. et al. Metabolomic identification of subtypes of nonalcoholic steatohepatitis. Gastroenterology 152, 1449–1461 (2017).

    Article  PubMed  Google Scholar 

  48. Brunt, E. M., Janney, C. G., Bisceglie, A. M. Di, 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 

  49. Orchard, G.E., in Bancroft’s Theory and Practice of Histological Techniques (eds Suvarna, S. K., Layton, C. et al.) 239–270 (Elsevier, 2013).

  50. Schmittgen, T. D. & Livak, K. J. Analyzing real-time PCR data by the comparative CT method. Nat. Protoc. 3, 1101–1108 (2008).

    Article  CAS  PubMed  Google Scholar 

  51. Casteilla, L., Pénicaud, L., Cousin, B. & Calise, D. Choosing an adipose tissue depot for sampling: factors in selection and depot specificity. Methods Mol. Biol. 456, 23–38 (2008).

    Article  PubMed  Google Scholar 

  52. Schneider, C. A., Rasband, W. S. & Eliceiri, K. W. NIH Image to ImageJ: 25 years of image analysis. Nat. Methods 9, 671–675 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank S. Roberge for excellent technical support, W. Ho for RT-qPCR support and T. Reiberger for early discussions. This work received financial support, in part, from the National Institutes of Health through the Laser Biomedical Research Center (grant no. 9-P41-EB015871-26A1 to M.G.B.) and the US Army Research Office through the Institute for Soldier Nanotechnologies at MIT, under cooperative agreement no. W911NF-18-2-0048 (to M.G.B.). M.S. was supported by the National Science Foundation Graduate Research Fellowship Program (grant no. 1122374). J.A.C. was supported by a National Defense Science and Engineering Graduate Fellowship 32 CFR 168a. K.v.L., Y.Z. and M.G.B. were supported by a Grand Challenges Grant from the MGH/MIT Strategic Initiative. This work was also in part supported by grants from the National Foundation for Cancer Research, the Ludwig Center at Harvard, the US National Cancer Institute (grant nos. P01-CA080124, R35-CA197743, R01-CA208205 and U01-CA224173 to R.K.J.). J.M.P. was supported by a NIH Training Grant (grant no. T32HL007627). This work was further supported in part by the NIH (grant nos. R01 DK031036 and R01 DK033201 to C.R.K., and grant nos. K12 HD000850 and P30 DK40561) and a NASPGHAN Young Investigator/Nestle Nutrition Award to S.S. M.P. was supported by an Erwin Schroedinger Fellowship from the Austrian Science Fund (FWF; project number J 3747-B28). S.C. was supported by an ABTA Basic Research Fellowship, MGH Tosteon and Fund for Medical Discovery Fellowship and PCRF Emerging Investigator Fellowship Grant. O.T.B. was supported by a European Molecular Biology Organization long-term fellowship.

Author information

Authors and Affiliations

Authors

Contributions

Conceptualization/evolution: W.J.K., J.A.C., I.X.C., M.P., K.v.L., O.T.B., R.K.J. and M.G.B. Formal analysis: M.S., W.J.K., J.A.C. and I.X.C. Funding acquisition: S.S., C.R.K., K.v.L., R.K.J. and M.G.B. Investigation/experiments: M.S., W.J.K., J.A.C., I.X.C., J.M.P., J.Z., Y.Z., M.P. and S.C. Methodology: M.S., W.J.K., J.A.C., I.X.C., J.M.P., A.S., R.K.J. and M.G.B. Project management: M.S., W.J.K. and J.A.C. Resources: S.S., C.R.K., K.v.L., R.K.J. and M.G.B. Supervision: R.K.J. and M.G.B. Validation: M.S., W.J.K. and J.A.C. Visualization: M.S. and J.A.C. Writing of the original draft: M.S., W.J.K. and J.A.C. Writing, review and editing: all authors.

Corresponding authors

Correspondence to Rakesh K. Jain or Moungi G. Bawendi.

Ethics declarations

Competing interests

M.P. is an investigator for Bayer, BMS and Lilly; a consultant for Bayer, BMS, Ipsen, Eisai and Lilly; and has received speaker honoraria from Bayer, BMS, Eisai and MSD as well as travel support from Bayer and BMS. R.K.J. received honorarium from Amgen; consultant fees from Chugai, Merck, Ophthotech, Pfizer, SPARC, SynDevRx and XTuit; owns equity in Enlight, Ophthotech, SynDevRx; and serves on the Boards of Trustees of Tekla Healthcare Investors, Tekla Life Sciences Investors, Tekla Healthcare Opportunities Fund and Tekla World Healthcare Fund. M.G.B. is a consultant and owns equity in Lumicell Inc. Neither any reagent nor any funding from these organizations was used in this study. MIT and MGH have filed a patent (United States application no. 62/654,665; international application no. PCT/US2019/026550) based on some of the findings described in this manuscript.

Additional information

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

Supplementary information

Supplementary Information

Supplementary methods, figures and references.

Reporting Summary

Supplementary Dataset 1

Supplementary Tables 1–11.

Supplementary Dataset 2

Statistical details.

Supplementary Video 1

Real-time and non-invasive imaging of quantifiable autofluorescent pigments in rodent liver with progressive fibrosis.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Saif, M., Kwanten, W.J., Carr, J.A. et al. Non-invasive monitoring of chronic liver disease via near-infrared and shortwave-infrared imaging of endogenous lipofuscin. Nat Biomed Eng 4, 801–813 (2020). https://doi.org/10.1038/s41551-020-0569-y

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41551-020-0569-y

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing