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CELA2A mutations predispose to early-onset atherosclerosis and metabolic syndrome and affect plasma insulin and platelet activation

Abstract

Factors that underlie the clustering of metabolic syndrome traits are not fully known. We performed whole-exome sequence analysis in kindreds with extreme phenotypes of early-onset atherosclerosis and metabolic syndrome, and identified novel loss-of-function mutations in the gene encoding the pancreatic elastase chymotrypsin-like elastase family member 2A (CELA2A). We further show that CELA2A is a circulating enzyme that reduces platelet hyperactivation, triggers both insulin secretion and degradation, and increases insulin sensitivity. CELA2A plasma levels rise postprandially and parallel insulin levels in humans. Loss of these functions by the mutant proteins provides insight into disease mechanisms and suggests that CELA2A could be an attractive therapeutic target.

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Fig. 1: Schematics showing CELA2A pedigrees, amino acid substitutions and conservation.
Fig. 2: Human WT and mutant CELA2A structures and functions.
Fig. 3: Mouse and human Cela2a tissue expression, human CELA2A plasma levels and activities.
Fig. 4: Cela2a induction of insulin secretion in vivo and in vitro.
Fig. 5: Insulin secretion, degradation and sensitivity of WT-CELA2A and p.D121N-CELA2A proteins.
Fig. 6: Effect of WT- versus p.D121N-CELA2A on platelet activity compared with vehicle.
Fig. 7: Schematic of CELA2A actions and its malfunction in p.D121N-CELA2A.

Data availability

Human variants and phenotypes have been reported to ClinVar under accession numbers SCV000916382, SCV000916383, SCV000916384 and SCV000916385. The data have also been reported to NIH with other identified variants in the Yale Center for Mendelian Genomics. Proteomics data are available on request.

References

  1. 1.

    Murray, C. L. & Lopez, A. D. Global mortality, disability, and the contribution of risk factors: global burden of disease study. Lancet 349, 1436–1442 (1997).

    CAS  Article  Google Scholar 

  2. 2.

    Malik, S. et al. Impact of the metabolic syndrome on mortality from coronary heart disease, cardiovascular disease, and all causes in United States adults. Circulation 110, 1245–1250 (2004).

    Article  Google Scholar 

  3. 3.

    Marenberg, M., Risch, N., Berkman, L. F., Floderus, B. & Defaire, U. Genetic susceptibility to death from coronary heart-disease in a study of twins. N. Engl. J. Med. 330, 1041–1046 (1994).

    CAS  Article  Google Scholar 

  4. 4.

    Abifadel, M. et al. Mutations in PCSK9 cause autosomal dominant hypercholesterolemia. Nat. Genet. 34, 154–156 (2003).

    CAS  Article  Google Scholar 

  5. 5.

    Mani, A. et al. LRP6 mutation in a family with early coronary disease and metabolic risk factors. Science 315, 1278–1282 (2007).

    CAS  Article  Google Scholar 

  6. 6.

    Keramati, A. R. et al. A form of the metabolic syndrome associated with mutations in DYRK1B. N. Engl. J. Med. 370, 1909–1919 (2014).

    Article  Google Scholar 

  7. 7.

    Szepessy, E. & Sahin-Toth, M. Inactivity of recombinant ELA2B provides a new example of evolutionary elastase silencing in humans. Pancreatology 6, 117–122 (2006).

    CAS  Article  Google Scholar 

  8. 8.

    Largman, C., Brodrick, J. W. & Geokas, M. C. Purification and characterization of two human pancreatic elastases. Biochemistry 15, 2491–2500 (1976).

    CAS  Article  Google Scholar 

  9. 9.

    Adzhubei, I. A. et al. A method and server for predicting damaging missense mutations. Nat. Methods 7, 248–249 (2010).

    CAS  Article  Google Scholar 

  10. 10.

    Warren, H. R. et al. Genome-wide association analysis identifies novel blood pressure loci and offers biological insights into cardiovascular risk. Nat. Genet. 49, 403–415 (2017).

    CAS  Article  Google Scholar 

  11. 11.

    Wain, L. V. et al. Novel blood pressure locus and gene discovery using genome-wide association study and expression data sets from blood and the kidney. Hypertension https://doi.org/10.1161/HYPERTENSIONAHA.117.09438 (2017).

  12. 12.

    Hoffmann, T. J. et al. Genome-wide association analyses using electronic health records identify new loci influencing blood pressure variation. Nat. Genet. 49, 54–64 (2017).

    CAS  Article  Google Scholar 

  13. 13.

    Fersht, A. & Sperling, J. The charge relay system in chymotrypsin and chymotrypsinogen. J. Mol. Biol. 74, 137–149 (1973).

    CAS  Article  Google Scholar 

  14. 14.

    Frey, P. A., Whitt, S. A. & Tobin, J. B. A low-barrier hydrogen bond in the catalytic triad of serine proteases. Science 264, 1927–1930 (1994).

    CAS  Article  Google Scholar 

  15. 15.

    Oleksyszyn, J. & Powers, J. C. Irreversible inhibition of serine proteases by peptide derivatives of (alpha-aminoalkyl)phosphonate diphenyl esters. Biochemistry 30, 485–493 (1991).

    CAS  Article  Google Scholar 

  16. 16.

    Yang, X., Pratley, R. E., Tokraks, S., Bogardus, C. & Permana, P. A. Microarray profiling of skeletal muscle tissues from equally obese, non-diabetic insulin-sensitive and insulin-resistant Pima Indians. Diabetologia 45, 1584–1593 (2002).

    CAS  Article  Google Scholar 

  17. 17.

    Marselli, L. et al. Gene expression profiles of beta-cell enriched tissue obtained by laser capture microdissection from subjects with type 2 diabetes. PLoS ONE 5, e11499 (2010).

    Article  Google Scholar 

  18. 18.

    Hulme, J. T. et al. Sites of proteolytic processing and noncovalent association of the distal C-terminal domain of CaV1.1 channels in skeletal muscle. Proc. Natl Acad. Sci. USA 102, 5274–5279 (2005).

    CAS  Article  Google Scholar 

  19. 19.

    Gao, T. et al. C-terminal fragments of the α1C (CaV1.2) subunit associate with and regulate l-type calcium channels containing C-terminal-truncated α1C subunits. J. Biol. Chem. 276, 21089–21097 (2001).

    CAS  Article  Google Scholar 

  20. 20.

    Steneberg, P. et al. The type 2 diabetes-associated gene ide is required for insulin secretion and suppression of α-synuclein levels in β-cells. Diabetes 62, 2004–2014 (2013).

    CAS  Article  Google Scholar 

  21. 21.

    Farris, W. et al. Insulin-degrading enzyme regulates the levels of insulin, amyloid β-protein, and the β-amyloid precursor protein intracellular domain in vivo. Proc. Natl Acad. Sci. USA 100, 4162–4167 (2003).

    CAS  Article  Google Scholar 

  22. 22.

    Schilling, R. J. & Mitra, A. K. Degradation of insulin by trypsin and α-chymotrypsin. Pharm. Res 8, 721–727 (1991).

    CAS  Article  Google Scholar 

  23. 23.

    Poy, M. N. et al. CEACAM1 regulates insulin clearance in liver. Nat. Genet. 30, 270–276 (2002).

    Article  Google Scholar 

  24. 24.

    Shattil, S. J., Hoxie, J. A., Cunningham, M. & Brass, L. F. Changes in the platelet membrane glycoprotein IIb·IIIa complex during platelet activation. J. Biol. Chem. 260, 11107–11114 (1985).

    CAS  PubMed  Google Scholar 

  25. 25.

    Yeh, J. J. et al. P-selectin-dependent platelet aggregation and apoptosis may explain the decrease in platelet count during Helicobacter pylori infection. Blood 115, 4247–4253 (2010).

    CAS  Article  Google Scholar 

  26. 26.

    Kato, S. et al. Increased calcium-channel currents of pancreatic β cells in neonatally streptozocin-induced diabetic rats. Metabolism 43, 1395–1400 (1994).

    CAS  Article  Google Scholar 

  27. 27.

    Calanna, S. et al. Secretion of glucagon-like peptide-1 in patients with type 2 diabetes mellitus: systematic review and meta-analyses of clinical studies. Diabetologia 56, 965–972 (2013).

    CAS  Article  Google Scholar 

  28. 28.

    Herzberg-Schafer, S., Heni, M., Stefan, N., Haring, H. U. & Fritsche, A. Impairment of GLP1-induced insulin secretion: role of genetic background, insulin resistance and hyperglycaemia. Diabetes Obes. Metab. 14, 85–90 (2012).

    Article  Google Scholar 

  29. 29.

    Pidard, D., Frelinger, A. L., Bouillot, C. & Nurden, A. T. Activation of the fibrinogen receptor on human platelets exposed to alpha chymotrypsin. relationship with a major proteolytic cleavage at the carboxyterminus of the membrane glycoprotein IIb heavy chain. Eur. J. Biochem. 200, 437–447 (1991).

    CAS  Article  Google Scholar 

  30. 30.

    Robert, L., Jacob, M. P. & Labat-Robert, J. Cell–matrix interactions in the genesis of arteriosclerosis and atheroma: effect of aging. Ann. NY Acad. Sci. 673, 331–341 (1992).

    CAS  Article  Google Scholar 

  31. 31.

    Katsunuma, H., Shimizu, K., Iwamoto, T. & Kiyokawa, M. Anti-atherosclerotic action of elastase—with special reference to its effect on elastic fibres. Age Ageing 12, 183–194 (1983).

    CAS  Article  Google Scholar 

  32. 32.

    Zureik, M. et al. Serum elastase activity, serum elastase inhibitors, and occurrence of carotid atherosclerotic plaques: the Etude sur le Vieillissement Arteriel (EVA) study. Circulation 205, 2638–2645 (2002).

    Article  Google Scholar 

  33. 33.

    Tzoulaki, I. et al. Relative value of inflammatory, hemostatic, and rheological factors for incident myocardial infarction and stroke: the Edinburgh Artery Study. Circulation 115, 2119–2127 (2007).

    Article  Google Scholar 

  34. 34.

    Talukdar, S. et al. Neutrophils mediate insulin resistance in mice fed a high-fat diet through secreted elastase. Nat. Med. 18, 1407–1412 (2012).

    CAS  Article  Google Scholar 

  35. 35.

    Lee, J., Hong, Y. P., Shin, H. J. & Lee, W. Associations of sarcopenia and sarcopenic obesity with metabolic syndrome considering both muscle mass and muscle strength. J. Prev. Med. Public Health 49, 35–44 (2016).

    Article  Google Scholar 

  36. 36.

    NHLBI GO Exome Sequencing Project (ESP), Exome Variant Server http://evs.gs.washington.edu/EVS/ (accessed June 2013).

  37. 37.

    Szabo, A., Pilsak, C., Bence, M., Witt, H. & Sahin-Toth, M. Complex formation of human proelastases with procarboxypeptidases A1 and A2. J. Biol. Chem. 291, 17706–17716 (2016).

    CAS  Article  Google Scholar 

  38. 38.

    Go, G. W. et al. The combined hyperlipidemia caused by impaired Wnt-LRP6 signaling is reversed by Wnt3a rescue. Cell Metab. 19, 209–220 (2014).

    CAS  Article  Google Scholar 

  39. 39.

    Miller, M. B. et al. Brain region and isoform-specific phosphorylation alters kalirin SH2 domain interaction sites and calpain sensitivity. ACS Chem. Neurosci. 8, 1554–1569 (2017).

    CAS  Article  Google Scholar 

  40. 40.

    Baucum, A. J., Shonesy, B. C., Rose, K. L. & Colbran, R. J. Quantitative proteomics analysis of CaMKII phosphorylation and the CaMKII interactome in the mouse forebrain. ACS Chem. Neurosci. 6, 615–631 (2015).

    CAS  Article  Google Scholar 

  41. 41.

    Lee, S. H. et al. Inducing mitophagy in diabetic platelets protects against severe oxidative stress. EMBO Mol. Med. 8, 779–795 (2016).

    CAS  Article  Google Scholar 

Download references

Acknowledgements

We thank T. Lam, J. Kanyo, W. Wang and N. Rauniar from the Yale Keck Mass Spectrometry and Proteomics Services for help with the proteomics analysis, and J. Murphy from the Department of Pharmacology at Yale University School of Medicine for preparing the ribbon diagrams. This work was supported by grants from the National Institutes of Health (NIH) (RHL135767A and P30 DK34989 to A.M., NIH R01DK095753 to M.S.-T. and NIH T32DK to F.E. (DK007356)), a grant from the NIH Centers for Mendelian Genomics (5U54HG006504) and a VA Merit Award to F.S.G. (NIH S10 (SIG) OD018034 awarded to the Mass Spectrometry and Proteomics Resource of the W.M. Keck Foundation Biotechnology Resource Laboratory at Yale University). The authors would like to thank the NHLBI GO Exome Sequencing Project and its ongoing studies, which produced and provided exome variant calls for comparison: the Lung GO Sequencing Project (HL-102923), the WHI Sequencing Project (HL-102924), the Broad GO Sequencing Project (HL-102925), the Seattle GO Sequencing Project (HL-102926) and the Heart GO Sequencing Project (HL-103010).

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F.E. contributed primarily to designing and performing the experiments, as well as to preparing the figures and manuscript. J.S.B., R.C., T.T., A.S., N.U., M.V.M., M.G., B.A., S.C., M.F. and A.A. were involved with performing the experiments. S.M., R.P.L., M.H.N., J.H., M.S.-T. and R.G.K. were involved in the design and supervision of certain aspects of the project. G.K., E.W., J.B. and E.S. were involved in patient recruitment and clinical characterizations. R.B.-D. carried out all of the OGTT and hyperglycemic clamp studies. N.U. was involved in the analysis of the genetic data. F.S.G. was involved in the design and supervision of aspects of the project, and participated in manuscript writing. A.M. designed the study and oversaw its implementation, supervised all aspects of the project from performing the experiments to the analysis of all data, and wrote the manuscript.

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Correspondence to Arya Mani.

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Integrated supplementary information

Supplementary Figure 1 Selected laboratory and clinical data in p.D121N carriers vs. non-carriers of the kindred CAD-2001.

a, Plasma TG levels (mg/dl; mean ± s.e.m.; n = 14 non-carriers vs. n = 10 carriers; Student’s t-test, two-sided at **P < 0.0001). b, BMI (kg/m2) (mean ± s.e.m. ; n = 14 non-carriers vs. n = 13 carriers; Student’s t-test, two-sided at **P = 0.002). c, Plasma cortisol levels (μg/ml; mean ± s.e.m.; n = 8 non-carriers vs. n = 8 carriers; Student’s t-test, two-sided at *P = 0.011). d, Plasma GLP1 levels (pm/L; mean ± s.e.m; n = 8 non-carriers vs. n = 8 carriers; Student’s t-test, two-sided, P = n.s). e, Plasma globular adiponectin levels (ng/ml; mean ± s.e.m.; n = 8 non-carriers vs. n = 7 carriers, Student’s t-test, two-sided; P = n.s). TG, triglycerides; BMI, body mass index; GLP1, Glucagon-like peptide 1.

Supplementary Figure 2 Validation of CELA2A antibody used in western blot analysis and immunohistochemistry.

a, Western blot image of different quantities of rCela2a using CELA2A-specific antibody and CELA2A antibody (Sigma-Aldrich, SAB1104798) pre-blocked with rCela2a (MyBiosource, MBS1246487). The 25-kDa rCela2a bands are almost invisible in the western blot carried out using pre-blocked antibody (n = 2 independent experiments). b, Western blot analysis using the supernatants of the 293T cells overexpressing either empty vector, WT-CELA2A or p.D121N His-CELA2A. The 25-kDa and 75-kDa His-CELA2A bands are no longer visible in the western blot carried out using pre-blocked antibody; the MW marker (middle) has been greatly overexposed to allow visualization of the CELA2A bands (n = 2 independent experiments). c, Immunohistochemistry staining of mouse skeletal muscle for CELA2A in WT mice injected with rCela2a vs. saline. IgG staining was used as negative control (n = 5 independent experiments). d, Validation of the ELISA kit assay for human CELA2A using known concentrations of purified WT-CELA2A and p.D121N-CELA2A represented as bar charts with mean ± s.e.m. The vehicle served as a negative control (n = 3 independent experiments; triplicates of one experiments have been represented). e, Whole membrane of the western blot for Cela2a, shown in Fig. 3b.

Supplementary Figure 3 Tissue distribution of CELA2A.

a-c, Immunohistochemical staining of mouse adrenal gland cortex and medulla (a) (n = 3 independent experiments), small intestine (b) (n = 3 independent experiments), and exocrine pancreas (c) (n = 5 independent experiments). Scale bar, 100 μm. Arrows indicate lymphoid follicles in the small intestine. Different zones in the adrenal gland are shown. d, Western blot analysis of CELA2A in human cadaveric liver, white adipose tissue (WAT) and pancreas.

Supplementary Figure 4 Expression of CELA2A in disease states from Gene Expression Omnibus (GEO) datasets and insulin, glucose and glucagon levels before and after the meal in human subjects.

a, Relative expression of CELA2A mRNA in vastus lateralis muscle samples from insulin-resistant obese (n = 5) and insulin sensitive (n = 5) Pima Indians. b, Beta-cell enriched pancreatic tissues obtained from subjects with T2D (n = 10) and without T2D (n = 10), shown as dot plots (mean ± s.e.m). Data were derived from GEO database (see the references in the text). Statistical analyses were carried out using two-sided Student’s t-test; P = 0.0115 and P = 0.0150, respectively. c, Glucagon level (pg/dl; mean ± s.e.m) in p.D121N-CELA2A carriers compared to controls (n = 7 control samples vs. 8 p.D121N-carriers). Statistical analyses were carried out using two-sided Student’s t-test, P = 0.033. d,e, Plasma glucagon levels (pg/dl; mean ± s.e.m) in fast/fed healthy individuals and correlation with plasma CELA2A in healthy subjects before and after meal (n = 8 samples). Statistical analyses were carried out using two-sided Student’s t-test; P = 0.049. Correlation coefficient (r2 = -0.72) for e was performed using GraphPad. f, CELA2A to glucose ratios (mean ± s.e.m) at 60 min hyperglycemic clamp and OGTT represented as bar chart (n = 5 samples, Student’s t-test, two-sided, P = n.s.). g,h, Average values of CELA2A and glucagon (pg/dl; mean ± s.e.m) during hyperglycemic clamp and OGTT studies (n = 5 samples). OGTT, oral glucose tolerance test. AU, arbitrary units. All human studies were performed only once.

Supplementary Figure 5 rCela2a administration in vivo and in human islets.

a,b, Plasma insulin and glucose levels (mean ± s.e.m.) after intravenous administration of rCela2a to normoglycemic wild-type C57BL/6 mice (n = 5 in each group). Statistical analyses were carried out using two-sided Student’s t-test. *P < 0.05. c,d, Insulin and C-peptide secretion of human islets in response to WT-CELA2A. Response to KCl is used as a positive control and test of viability. Violin plots represent median, minimum and maximum. Statistical analyses were carried out using two-sided Student’s t-test per condition (n = 4). **P <0.01. e, Insulin secretion of human islets in response to WT-CELA2A (human) compared to rCela2a (mouse) represented in bar charts (mean ± s.e.m; n = 4 samples). Statistical analyses were carried out using two-sided Student’s t-test per conditions (***P <0.001). Response to KCl is used as a positive control and test of viability.

Supplementary Figure 6 Quantification of insulin signaling activation by WT-CELA2A and p.D121N-CELA2A protein.

a-e, Plots show relative intensities compared to controls for the phosphoproteins in the western blots shown in Fig. 5g displayed as bar charts (mean ± s.e.m.; n = 2 independent experiments). Statistical analyses were performed using one-way ANOVA. *P < 0.05, **P < 0.001.

Supplementary Figure 7 Whole blot figures used in the study.

Whole blots from western blot analysis of CELA2A in human serum in Fig. 3d; insulin/mTOR signaling pathways in 3T3L1 cells treated with insulin, WT- or p.D121N-CELA2A, and predigested insulin with WT- or p.D121N-CELA2A in Fig. 3g; Coomassie blue and western blot of GPIIb/IIIa in Fig. 6e, f.

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Esteghamat, F., Broughton, J.S., Smith, E. et al. CELA2A mutations predispose to early-onset atherosclerosis and metabolic syndrome and affect plasma insulin and platelet activation. Nat Genet 51, 1233–1243 (2019). https://doi.org/10.1038/s41588-019-0470-3

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