, 12:95 | Cite as

Human amylin proteotoxicity impairs protein biosynthesis, and alters major cellular signaling pathways in the heart, brain and liver of humanized diabetic rat model in vivo

  • Amro Ilaiwy
  • Miao Liu
  • Traci L. Parry
  • James R. Bain
  • Christopher B. Newgard
  • Jonathan C. Schisler
  • Michael J. Muehlbauer
  • Florin DespaEmail author
  • Monte S. WillisEmail author
Original Article



Chronic hypersecretion of the 37 amino acid amylin is common in type 2 diabetics (T2D). Recent studies implicate human amylin aggregates cause proteotoxicity (cell death induced by misfolded proteins) in both the brain and the heart.


Identify systemic mechanisms/markers by which human amylin associated with cardiac and brain defects might be identified.


We investigated the metabolic consequences of amyloidogenic and cytotoxic amylin oligomers in heart, brain, liver, and plasma using non-targeted metabolomics analysis in a rat model expressing pancreatic human amylin (HIP model).


Four metabolites were significantly different in three or more of the four compartments (heart, brain, liver, and plasma) in HIP rats. When compared to a T2D rat model, HIP hearts uniquely had significant DECREASES in five amino acids (lysine, alanine, tyrosine, phenylalanine, serine), with phenylalanine decreased across all four tissues investigated, including plasma. In contrast, significantly INCREASED circulating phenylalanine is reported in diabetics in multiple recent studies.


DECREASED phenylalanine may serve as a unique marker of cardiac and brain dysfunction due to hyperamylinemia that can be differentiated from alterations in T2D in the plasma. While the deficiency in phenylalanine was seen across tissues including plasma and could be monitored, reduced tyrosine was seen only in the brain. The 50 % reduction in phenylalanine and tyrosine in HIP brains is significant given their role in supporting brain chemistry as a precursor for catecholamines (dopamine, norepinephrine, epinephrine), which may contribute to the increased morbidity and mortality in diabetics at a multi-system level beyond the effects on glucose metabolism.


Amylin Metabolomics Neurodegenerative disease Cardiomyopathy Diabetes Proteotoxicity 



Amyloid beta protein precursor


Gamma-aminobutyric acid


Rat model expressing pancreatic human amylin


Human islet amyloid polypeptide


Principal component analysis


Partial least squares discriminant analysis


Variable importance in projection



This work was supported by the National Institutes of Health (R01HL104129 to M.W.; R01HL118474 to F.D.), a Jefferson-Pilot Corporation Fellowship (to M.W.), National Science Foundation (CBET 1357600 to F.D.), Alzheimer’s Association (VMF-15-363458 to FD) and the Leducq Foundation (to M.W.).

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.

Ethical approval

All applicable international, national, and/or institutional guidelines for the care and use of animals were followed.

Supplementary material

11306_2016_1022_MOESM1_ESM.pdf (3.2 mb)
Supplemental Fig. 1. Non-targeted cardiac metabolomics of HIP heart tissue at one year of age. A. Enrichment by pathway-associated metabolite sets. B. Location-Based Metabolite sets determined from t-test significant metabolites identified. Supplementary material 1 (PDF 3304 kb)
11306_2016_1022_MOESM2_ESM.pdf (4.2 mb)
Supplemental Fig. 2. Non-targeted cardiac metabolomics of HIP brain tissue at one year of age Enrichment by A. Pathway-associated metabolite sets, B. Location-Based Metabolite sets, and C. Disease-associated metabolite sets in the brain determined from from t-test significant metabolites identified. Supplementary material 2 (PDF 4314 kb)
11306_2016_1022_MOESM3_ESM.pdf (3.1 mb)
Supplemental Fig. 3. Non-targeted cardiac metabolomics of HIP liver tissue at one year of age. Enrichment by A. Pathway-associated metabolite sets and B. Location-Based Metabolite sets determined from from t-test significant metabolites identified. Supplementary material 3 (PDF 3213 kb)
11306_2016_1022_MOESM4_ESM.pdf (4.5 mb)
Supplemental Fig. 4. Non-targeted cardiac metabolomics of HIP plasma at one year of age. Enrichment by A. Pathway-associated metabolite sets, B. Location-Based Metabolite sets, and C. Disease-associated metabolite sets in the blood determined from from t-test significant metabolites identified. Supplementary material 4 (PDF 4564 kb)
11306_2016_1022_MOESM5_ESM.pdf (3.8 mb)
Supplemental Fig. 5. Pathway enrichment analysis of significant metabolite sets identified by non-targeted cardiac metabolomics. A. Heart, B. Brain, C. Liver, and D. Plasma. A-D indicates top pathways identified, along with the specific significant metabolites found that placed it in this category. Supplementary material 5 (PDF 3869 kb)
11306_2016_1022_MOESM6_ESM.pdf (724 kb)
Supplemental Fig. 6. Significantly altered HIP-unique metabolites found by non-targeted metabolomics analysis of the heart using a recently published type 2 diabetes model (Kouzu et al. 2015). Data was normalized to the strain-matched wildtype control, followed by an ANOVA analysis of all four groups and included significantly altered metabolites found in both studies (see supplemental materials and methods for details, Supplemental Table 2 for data used in analysis). A. HIP significant cardiac metabolites, not altered in T2D model (indicated by *). B. HIP significant cardiac amino acids, not altered in T2D model (indicated by *). C. Comparison of HIP transgenic model (current study) and T2D model used in this analysis recently published (Kouzu et al. 2015). Boxes indicate similarly altered metabolites in both HIP and T2D models. A One-Way ANOVA was performed, with Holm-Sidak post hoc comparisons made to the wildtypeHIPTg+. Significance was defined as p < 0.05. Data is mean ± SEM. Supplementary material 6 (PDF 723 kb)
11306_2016_1022_MOESM7_ESM.xlsx (456 kb)
Supplementary material 7 (XLSX 456 kb)
11306_2016_1022_MOESM8_ESM.xlsx (33 kb)
Supplementary material 8 (XLSX 33 kb)
11306_2016_1022_MOESM9_ESM.pptx (50 kb)
Supplementary material 9 (PPTX 50 kb)


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.Faculty of MedicineUniversity of DamascusDamascusSyria
  2. 2.Department of Pharmacology and Nutritional SciencesUniversity of KentuckyLexingtonUSA
  3. 3.Department of PharmacologyUniversity of North CarolinaChapel HillUSA
  4. 4.McAllister Heart InstituteUniversity of North CarolinaChapel HillUSA
  5. 5.Sarah W. Stedman Nutrition and Metabolism Center, Duke Molecular Physiology InstituteDuke University Medical CenterDurhamUSA
  6. 6.Division of Endocrinology, Metabolism, and Nutrition, Department of MedicineDuke University Medical CenterDurhamUSA
  7. 7.Department of Pathology & Laboratory MedicineUniversity of North CarolinaChapel HillUSA

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