Submitted:
29 September 2024
Posted:
30 September 2024
You are already at the latest version
Abstract
Keywords:
Introduction
Materials and Methods
Blood Sampling
Routine Blood Analysis
Microarray Analysis in Serum
Indirect ELISA of CDH3
Statistical Analysis
Results
Discussion
Conclusions
Limitations
Funding
Acknowledgments
Conflicts of Interest
References
- Pettitt J (2005) The cadherin superfamily. WormBook 1-9.
- Kumara HM, Bellini GA, Caballero OL, Herath SA, Su T, Ahmed A, Njoh L, Cekic V, Whelan RL (2017) P-Cadherin (CDH3) is overexpressed in colorectal tumors and has potential as a serum marker for colorectal cancer monitoring. Oncoscience 4: 139–147.
- Zhou Y, Chi Y, Bhandari A, Xia E, Thakur PC, Qu J, Wang O, Zhang X (2020) Downregulated CDH3 decreases proliferation, migration, and invasion in thyroid cancer. Am J Transl Res 12: 3057–3067.
- Seppälä M, Jauhiainen L, Tervo S, Al-Samadi A, Rautiainen M, Salo T, Lehti K, Monni O, Hautaniemi S, Tynninen O, Mäkitie A, Mäkinen L K, Paavonen T, Toppila-Salmi S (2021) The expression and prognostic relevance of CDH3 in tongue squamous cell carcinoma. APMIS 129: 717–728.
- Gumanova NG, Vasilyev DK, Bogdanova NL, Havrichenko YI, Kots AY, Metelskaya VA (2022) Application of an antibody microarray for serum protein profiling of coronary artery stenosis. Biochem Biophys Res Commun 631: 55–63.
- Task Force Members; Montalescot G, Sechtem U, Achenbach S, Andreotti F, Arden C, Budaj A, Bugiardini R, Crea F, Cuisset T, Di Mario C, Ferreira JR, Gersh BJ, Gitt AK, Hulot JS, Marx N, Opie LH, Pfisterer M, Prescott E, Ruschitzka F, Sabaté M, Senior R, Taggart DP, van der Wall EE, Vrints CJ; ESC Committee for Practice Guidelines; Zamorano JL, Achenbach S, Baumgartner H, Bax JJ, Bueno H, Dean V, Deaton C, Erol C, Fagard R, Ferrari R, Hasdai D, Hoes AW, Kirchhof P, Knuuti J, Kolh P, Lancellotti P, Linhart A, Nihoyannopoulos P, Piepoli MF, Ponikowski P, Sirnes PA, Tamargo JL, Tendera M, Torbicki A, Wijns W, Windecker S; Document Reviewers; Knuuti J, Valgimigli M, Bueno H, Claeys MJ, Donner-Banzhoff N, Erol C, Frank H, Funck-Brentano C, Gaemperli O, Gonzalez-Juanatey JR, Hamilos M, Hasdai D, Husted S, James SK, Kervinen K, Kolh P, Kristensen SD, Lancellotti P, Maggioni AP, Piepoli MF, Pries AR, Romeo F, Rydén L, Simoons ML, Sirnes PA, Steg PG, Timmis A, Wijns W, Windecker S,Yildirir A, Zamorano JL (2013) 2013 ESC guidelines on the management of stable coronary artery disease: the Task Force on the management of stable coronary artery disease of the European Society of Cardiology. Eur Heart J 34(38):2949-3003.
- Metelskaya VA, Gavrilova NE, Zhatkina MV, Yarovaya EB, Drapkina OM (2022) A Novel Integrated Biomarker for Evaluation of Risk and Severity of Coronary Atherosclerosis, and Its Validation. J Pers Med 12: 206.
- Metelskaya V, Zhatkina M, Gavrilova N, Yarovaya E, Bogdanova N, Kutsenko V, Rudenko B, Drapkina O (2021) Associations of circulating biomarkers with the presence and severity of coronary, carotid and femoral arterial atherosclerosis. Cardiovascular Therapy and Prevention 20:3098. (In Russian).
- Gensini GG (1983) A more meaningful scoring system for determining the severity of coronary heart disease. Am J Cardiol 51: 606.
- Gumanova NG, Gavrilova NE, Chernushevich OI, Kots AY, Metelskaya VA (2017) Ratios of leptin to insulin and adiponectin to endothelin are sex-dependently associated with extent of coronary atherosclerosis. Biomarkers : biochemical indicators of exposure, response, and susceptibility to chemicals 22: 239–245.
- Zhatkina M, Gavrilova N, Makarova Y, Metelskaya V, Rudenko B, Drapkina O (2020) Diagnosis of multifocal atherosclerosis using the Celermajer test. Cardiovascular Therapy and Prevention 19:2638 (In Russian).
- Aboyans V, Ricco J-B, Marie-Louise EL, Bartelink MB, Brodmann M, Cohnert T, Collet J-P, Czerny M, De Carlo M, Debus S, Espinola-Klein C, Kahan T, Kownator S, Mazzolai LA, Naylor R, Roffi M, Röther J, Sprynger M, Tendera M, Tepe G, Venermo M, Vlachopoulos C, Desormais I, ESC Scientific Document Group. 2017 ESC Guidelines on the Diagnosis and Treatment of Peripheral Arterial Diseases, in collaboration with the European Society for Vascular Surgery (ESVS): Document covering atherosclerotic disease of extracranial carotid and vertebral, mesenteric, renal, upper and lower extremity arteries Endorsed by: the European Stroke Organization (ESO) The Task Force for the Diagnosis and Treatment of Peripheral Arterial Diseases of the European Society of Cardiology (ESC) and of the European Society for Vascular Surgery (ESVS). Eur Heart J (2018) 39:763–816.
- Gao, M., Hua, Y., Zhao, X., Jia, L., Yang, J., & Liu, B. (2018). Optimal Ultrasound Criteria for Grading Stenosis of the Superficial Femoral Artery. Ultrasound Med Biol 44, 350–358.
- Zhatkina M, Metelskaya V, Gavrilova N, Yarovaya E, Makarova Y, Litinskaya O, Bogdanova N, Rudenko B, Drapkina O (2021) Biochemical markers of coronary atherosclerosis: building models and assessing their prognostic value regarding the lesion severity. Russian Journal of Cardiology 26:4559.
- Miranda KM, Espey MG, Wink DA (2001) A rapid, simple spectrophotometric method for simultaneous detection of nitrate and nitrite. Nitric oxide : biology and chemistry 5: 62–71.
- Metelskaia VA, Gumanova NG 2005 Screening as a method for determining the serum level of nitric oxide metabolites. Klin Lab Diagn 6:15-8. (in Russian).
- Gumanova NG, Klimushina MV, Metel'skaya VA (2018) Optimization of Single-Step Assay for Circulating Nitrite and Nitrate Ions (NOx) as Risk Factors of Cardiovascular Mortality. Bulletin of experimental biology and medicine 165: 284–287.
- Ershova A, Meshkov A, Shalnova S, Shcherbakova N, Andreenko E, Romanchuk S, Shutemova E, Belova O, Boytsov S (2014) Ultrasound parameters of carotid and femoral atherosclerosis in patients with coronary heart disease. The Russian Journal of Preventive Medicine 6: 108-116.
- Gumanova NG, Teplova NV, Ryabchenko AU, Denisov EN (2015) Serum nitrate and nitrite levels in patients with hypertension and ischemic stroke depend on diet: a multicenter study. Clin Biochem 48: 29–32.
- McKearnan SB, Wolfson J, Vock DM, Vazquez-Benitez G, O'Connor PJ (2018) Performance of the Net Reclassification Improvement for Nonnested Models and a Novel Percentile-Based Alternative. Am J Epidemiol 187: 1327–1335.
- Pencina MJ, D'Agostino RB, Vasan RS (2010) Statistical methods for assessment of added usefulness of new biomarkers. Clin Chem Lab Med 48, 1703–1711. [CrossRef]
- Cavallaro U, Dejana E (2011) Adhesion molecule signalling: not always a sticky business. Nat Rev Mol Cell Biol 12: 189–197.
- Larue L, Antos C, Butz S, Huber O, Delmas V, Dominis, M, Kemler R (1996) A role for cadherins in tissue formation. Development 122: 3185–3194.
- Raymond K, Deugnier MA, Faraldo MM, Glukhova MA (2009) Adhesion within the stem cell niches. Curr Opin Cell Biol 21: 623–629.
- Jang Y, Lincoff AM, Plow EF, Topol EJ (1994) Cell adhesion molecules in coronary artery disease. J Am Coll Cardiol 24: 1591–1601.
- Soeki T, Tamura Y, Shinohara H, Sakabe K, Onose Y, Fukuda N (2004) Elevated concentration of soluble vascular endothelial cadherin is associated with coronary atherosclerosis. Circ J 68: 1–5.
- Dejana E, & Giampietro C (2012) Vascular endothelial-cadherin and vascular stability. Curr Opin Hematol 19: 218–223.
- Takeichi M (2011) Self-organization of animal tissues: cadherin-mediated processes. Dev Cell 21:24–26.
- Speed JS, Heimlich JB, Hyndman KA, Fox BM, Patel V, Yanagisawa M, Pollock JS, Titze JM, Pollock DM (2015) Endothelin-1 as a master regulator of whole-body Na+ homeostasis. FASEB J 29: 4937–4944.
- Yamashita K, Discher, DJ, Hu J, Bishopric NH, Webster KA (2001) Molecular regulation of the endothelin-1 gene by hypoxia. Contributions of hypoxia-inducible factor-1, activator protein-1, GATA-2, AND p300/CBP. J Biol Chem 276: 12645–12653.
- Jenkins HN, Rivera-Gonzalez O, Gibert Y, Speed JS (2020) Endothelin-1 in the pathophysiology of obesity and insulin resistance. Obes Rev 21: e13086.
- Davenport AP, Hyndman KA, Dhaun N, Southan C, Kohan DE, Pollock JS, Pollock DM, Webb DJ, Maguire JJ (2016) Endothelin. Pharmacol Rev 68: 357–418.
- Juan CC, Chang CL, Lai YH, Ho LT (2005) Endothelin-1 induces lipolysis in 3T3-L1 adipocytes. Am J Physiol Endocrinol Metab 288: E1146–E1152.
- Jenkins HN, Williams LJ, Dungey A, Vick KD, Grayson BE, Speed JS (2019) Elevated plasma endothelin-1 is associated with reduced weight loss post vertical sleeve gastrectomy. Surg Obes Relat Dis 15: 1044–1050. [CrossRef]
- Sartori C, Scherrer U (1999) Insulin, nitric oxide and the sympathetic nervous system: at the crossroads of metabolic and cardiovascular regulation. J Hypertens 17: 1517–1525.
- Scherrer U, Sartori C (2000) Defective nitric oxide synthesis: a link between metabolic insulin resistance, sympathetic overactivity and cardiovascular morbidity. Eur J Endocrinol 142(4), 315–323.
- Owlya R, Vollenweider L, Trueb L, Sartori C, Lepori M, Nicod P, Scherrer U (1997) Cardiovascular and sympathetic effects of nitric oxide inhibition at rest and during static exercise in humans. Circulation 96:3897–3903.
- Lucas CP, Estigarribia JA, Darga LL, Reaven GM (1985) Insulin and blood pressure in obesity. Hypertension 7: 702–706.
- Steinberg HO, Brechtel G, Johnson A, Fineberg N, Baron AD (1994) Insulin-mediated skeletal muscle vasodilation is nitric oxide dependent. A novel action of insulin to increase nitric oxide release. J Clin Invest 94: 1172–1179.
- Wu G, Meininger CJ (2009) Nitric oxide and vascular insulin resistance. BioFactors 35:21–27.
- Gumanova NG, Gorshkov AU, Klimushina MV, Kots AY (2020) Associations of endothelial biomarkers, nitric oxide metabolites and endothelin, with blood pressure and coronary lesions depend on cardiovascular risk and sex to mark endothelial dysfunction on the SCORE scale. Horm Mol Biol Clin Investig 41:10.1515/hmbci-2020-002441.




| Stratification after 3-year follow up | Baseline characteristics | ||||||
|---|---|---|---|---|---|---|---|
| Parameter | Patients with no CV-events* | Patients with CV-events | Total cohort | Patients with Gensini score=0 | Patients with Gensini score>0 | ||
| N | 77 | 99 | 218 | 76 | 142 | ||
| Mean (SD) | P | Mean (SD) | P | ||||
| General characteristic | |||||||
| Sex | 1.48 | 1.46 | NS | 1.39 | 1.57 | 1.42(0.49) | 0.036 |
| Age | 59.7 (12.1) | 63.7 (9.3) | NS | 63.2 (10.9) | 60.5 (11.9) | 63.5(10.1) | NS |
| Smoking (0/1/2)**, % | 53/14/33 | 41/13/47 | NS | 45/13/42 | 50/14/36 | 42/9/46 | NS |
| Patients with CV- family history ***, % | 59.7 | 75 | 0.01 | 67.8 | 47.4 | 81 | >0.0001 |
| BMI, kg/m2 | 28.8(4.7) | 30.1 (4.8) | NS | 29.9 (5.8) | 29.4 (5.6) | 30.1(5.1) | NS |
| WS, cm | 90.4 (9.9) | 94.9 (13.2) | NS | 93.7 (12.5) | 92.1 (12.2) | 93.7(12.3) | NS |
| SBP, mm Hg | 128.5 (13.2) | 130.1 (14.1) | NS | 128.5 (12.7) | 126.53(11.5) | 131.1(14.3) | 0.02 |
| DBP, mm Hg | 73.1 (7.4) | 72.3 (8.7) | NS | 71.8 (7.8) | 71.8 (7.6) | 73.5(8.6) | NS |
| Biochemical markers | |||||||
| NOx, µM | 42.62 (23.9) | 39.62 (26.74) | NS | 41.29 (25.30) | 51.73(32.03) | 35.50(18.35) | 0.000 |
| Endothelin-1, pg/ml | 1.72 (0.8) | 1.73 (0.36) | NS | 1.68(0.63) | 1.72 (0.84) | 1.66(0.47) | 0.005 |
| TC, mmol/L | 4.30 (1.1) | 4.23 (1.04) | NS | 4.13 (1.08) | 4.45(1.08) | 4.24(1.08) | NS |
| Triglycerides, mmol/L | 1.55 (0.96) | 1.57 (0.61) | NS | 1.58 (0.90) | 1.54(0.85) | 1.50(0.72) | NS |
| LDL-cholesterol, mmol/L | 2.45 (0.92) | 2.46 (0.88) | NS | 2.33 (0.90) | 2.62(0.97) | 2.43(0.91) | NS |
| HDL-cholesterol, mmol/L | 1.20 (0.31) | 1.06 (0.27) | NS | 1.10 (0.31) | 1.18(0.32) | 1.12(0.30) | NS |
| Glucose, mmol/L | 6.12 (1.53) | 6.53 (1.91) | 0.000 | 6.32 (1.79) | 5.85(1.35) | 6.60(1.78) | 0.000 |
| Insulin, µIU/ml | 12.01 (10.7) | 14.99 (14.22) | 0.000 | 12.90 (9.82) | 10.94(10.18) | 14.55(12.89) | 0.002 |
| HOMA-IR | 3.58 (4.21) | 4.75 (5.83) | 0.002 | 3.82 (3.66) | 2.96(3.26) | 4.64(5.4) | 0.000 |
| CRP, mg/L | 5.70 (16.3) | 7.98 (12.6) | 0.000 | 9.46 (22.23) | 6.80(21.62) | 7.48(15.72) | NS |
| Fibrinogen, g/L | 4.60 (1.35) | 4.88 (1.21) | 0.01 | 5.03 (1.40) | 4.59(1.40) | 4.87(1.25) | 0.01 |
| Adiponectin, µg/mL | 8.80 (3.61) | 8.55 (4.72) | NS | 8.86 (5.01) | 9.30(4.55) | 9.08(5.93) | NS |
| Leptin, ng/mL | 44.18 (46.2) | 29.04 (38.21) | NS | 34.00 (42.50) | 39.14(43.99) | 34.78(41.94) | NS |
| CDH3, pg/mL | 3.50 (2.68) | 4.29 (2.96) | 0.016 | 4.02 (2.88) | 2.88 (2.72) | 4.72 (2.76) | 0.000 |
| Statin treatment before blood withdrawal, % | 49.3 | 65.2 | 0.006 | 58.2 | 32.3 | 72.3 | 0.000 |
| Statistical method | P | ||||
|---|---|---|---|---|---|
| N total=172; CV-outcomes* N=95; CDH3 (continuous) |
AUC (95%CI) |
0.58 (0.52-0.64) |
0.017 |
Optimal cut-off for CDH3 = 4.6 pg/mL |
Sensitivity 0.55 Specify 0.63 |
| CV-outcomes N (50/45); CDH3 (binary) N (53/24); cut-off 4.6 pg/mL |
OR (95%CI) | 1.81 (1.07-3.72) | 0.022 |
| Parameters | B | Wald (chi-squared) |
P | |
|---|---|---|---|---|
| Sex | 1.251 | 0.720 | 0.396 | |
| Age | 0.430 | 30.021 | 0.082 | |
| Smoking | -0.038 | 40.713 | 0.030 | |
| Patients with CV- family history ** | -0.544 | 0.781 | 0.377 | |
| Gensini score | 0.407 | 70.346 | 0.007 | |
| Systolic blood pressure, mm Hg | -0.021 | 40.058 | 0.044 | |
| Diastolic blood pressure, mm Hg | -0.039 | 50.353 | 0.021 | |
| Total cholesterol, mmol/L | 0.078 | 0.846 | 0.358 | |
| Triglycerides, mmol/L | 590.197 | 0.840 | 0.359 | |
| LDL-cholesterol, mmol/L | -270.063 | 0.856 | 0.355 | |
| HDL-cholesterol, mmol/L | -590.539 | 0.764 | 0.382 | |
| Glucose, mmol/L | -560.314 | 30.088 | 0.079 | |
| C-reactive protein, mg/L | -0.211 | 0.889 | 0.346 | |
| CDH3, pg/mL | 0.013 | 30.726 | 0.049 | |
| Classification table for base model including sex, age at a median cut-off of 65 years, Patients with CV- family history (yes/no), smoking, systolic blood pressure at a median cut-off of 130 mm Hg, diastolic blood pressure at a median cut-off of 70 mm Hg, and total cholesterol at a median cut-off of 4.2 mmol/L | |||
| Observed | Predicted | ||
| 0 | 1 | % of corrected observations | |
| 0 | 29 | 48 | 37.7% |
| 1 | 20 | 75 | 78.9% |
| Total % | 28.5% | 71.5% | 60.5% |
| Classification table for base model plus CDH3 | |||
| 0 | 1 | % of corrected observations | |
| 0 | 37 | 36 | 50.7% |
| 1 | 21 | 66 | 75.9% |
| Total % | 36.2% | 63.7% | 64.4% |
| Parameters | N | OR (95%CI) | P |
|---|---|---|---|
| Routine cardiac risk factors** | 29/48 20/75 |
2.26 (1.15-4.45) | 0.017 |
| Routine cardiac risk factors plus CDH3 (cut-off 4.6 pg/mL) | 37/36 21/66 |
3.23 (1.64-6.32) | 0.0006 |
| AUC (95%CI) for binary CDH3 (cut-off 4.6 pg/mL) |
Optimal cut-off for the corresponding parameters according to AUC | P | |
|---|---|---|---|
| General characteristics | |||
| Sex | - | NS | |
| Age | - | NS | |
| Smoking (0/1/2)**, % | NS | ||
| Patients with CV- family history. | 0.61 (0.52-0.69) | 0.016 | |
| BMI, kg/m2 | - | NS | |
| WS, cm | - | NS | |
| SBP, mm Hg | - | NS | |
| DBP, mm Hg | 0.58 (0.53-0.63) | 71.0 | 0.006 |
| Biochemical markers | |||
| NOx, µM and endothelin-1 in model | 0.64 (0.54-0.74) | 33.01 | 0.005 |
| Endothelin-1, pg/mL | 0.66(0.57-0.75) | 1.67 | 0.001 |
| TC, mmol/L | - | ||
| Triglycerides, mmol/L | - | NS | |
| LDL-cholesterol, mmol/L | - | NS | |
| HDL-cholesterol, mmol/L | - | NS | |
| Glucose, mmol/L | - | NS | |
| Insulin, µIU/mL | - | NS | |
| HOMA-IR | - | NS | |
| CRP, mg/L | - | NS | |
| Fibrinogen, g/L | - | NS | |
| Adiponectin, µg/mL | - | NS | |
| Leptin, ng/mL | - | NS | |
| Statins treatment before blood withdrawal, % | NS |
| Parameter | B | S.E. | Wald | df | P | Exp(B) | |
|---|---|---|---|---|---|---|---|
| NOх, µM | 0.006 | 0.007 | 0.855 | 1 | 0.355 | 1.006 | |
| Endothelin-1 (pg/mL) | 0.854 | 0.301 | 8.055 | 1 | 0.005 | 2.349 | |
| Unstandardized coefficients | Standardized coefficients | P | |||
|---|---|---|---|---|---|
| Dependent variable | Models | B | S.E. | Beta | |
| Systolic blood pressure, mm Hg | Endothelin-1, pg/mL | -0.687 | 1.382 | -0.041 | 0.620 |
| NOx, µM | -0.054 | 0.027 | -0.162 | 0.045 | |
| CDH3, pg/mL | 0.158 | 0.315 | 0.041 | 0.616 | |
| Diastolic blood pressure, mm Hg | Endothelin-1, pg/mL | -1.995 | 0.931 | -0.172 | 0.034 |
| NOx, µM | -0.016 | 0.018 | -0.069 | 0.382 | |
| CDH3, pg/mL | 0.561 | 0.212 | 0.212 | 0.009 | |
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