Exploration of Cardiology

Table 6. Correlation analysis of serum UBE2E3-Ab levels with the clinical data of CKD cohort

Patient data	s-UBE2E-Ab
Patient data	*rho*	P value
Age*	0.0726	0.2100
Height	0.0935	0.1065
Weight	0.0211	0.7165
Body mass index (BMI)	–0.0257	0.6584
Dialysis period	–0.0981	0.0897
Plaque score	0.1478	0.0109**
Maximum intima-media thickness (max-IMT)	0.1187	0.0412
Ankle brachial pressure index (ABI) (right)	0.0253	0.6664
ABI (left)	–0.0003	0.9952
Cardio-ankle vascular index (CAVI) (right)	0.1915	0.0013
CAVI (left)	0.1716	0.0038
Glycated hemoglobin (HbA1c)	–0.0865	0.2959
Whole parathyroid hormone (W-PTH)	0.0954	0.0993
Transferrin saturation ratio	0.0030	0.9584
Standardized urea clearance (Kt/V)	–0.1515	0.0086
Red blood cell	–0.0712	0.2187
Hemoglobin	–0.0354	0.5410
Hematocrit	–0.0205	0.7238
Platelet	–0.0681	0.2394
Total protein	–0.0318	0.5832
Albumin	–0.0537	0.3544
Urea nitrogen (UN)	–0.1427	0.0134
Creatinin	–0.0498	0.3902
Uric acid	–0.0859	0.1376
Na	0.0389	0.5018
K	–0.1030	0.0749
Cl	0.0255	0.6599
Ca	–0.0110	0.8491
Inorganic phosphate (IP)	–0.0280	0.6287
Ca	0.0186	0.7478
Mg	0.0899	0.1202
Fe	–0.0595	0.3046
Ferritin	0.1319	0.0223
Aspartate aminotransferase (AST)	0.1212	0.0359
Alanine amino transferase (ALT)	0.0658	0.2560
Lactate dehydrogenase (LDH)	0.0701	0.2258
γ-glutamyl transpeptidase (γ-GTP)	0.0465	0.4223
Alkaline phosphatase (ALP)	–0.0389	0.5026
Total bilirubin (tBil)	0.0229	0.6934
Amylase	–0.0284	0.6246
Creatin kinase (CK)	–0.0127	0.8273
Total cholesterol	–0.0540	0.3516
High-density lipoprotein cholesterol (HDL-c)	–0.1261	0.0290
Low-density lipoprotein cholesterol (LDL-c)	–0.0399	0.4913
Triglyceride (TG)	0.1030	0.0747
C-reactive protein (CRP)	0.1129	0.0507

Return to article view

Correlation coefficients (rho) and P values obtained by Spearman’s correlation analysis between UBE2E3-Ab levels and the subjects’ data are shown. *Subjects’ data used were age, height, weight, body mass index (BMI), maximum intima-media thickness (max-IMT), plaque score, cardio-ankle vascular index (CAVI), ankle brachial pressure index (ABI), glycated hemoglobin (HbA1c), whole parathyroid hormone (W-PTH), dialysis period, angiotensin II receptor blocker (ARB), angiotensin converting enzyme (ACE), prothrombin (PTA), iron (Fe), ferritin, Transferrin saturation ratio (TSAT ratio), standardized urea clearance (Kt/V), red blood cell number (RBC), hemoglobin (HGB), hematocrit (HCT), platelet number (PLT), total protein (TP), albumin (ALB), urea nitrogen (UN), creatinine (CRE), uric acid (UA), sodium (Na), potassium (K), chlorine (Cl), calcium (Ca), inorganic phosphate (IP), magnesium (Mg), aspartate aminotransferase (AST), alanine amino transferase (ALT), lactate dehydrogenase (LDH), γ-glutamyl transpeptidase (γ-GTP), alkaline phosphatase (ALP), total bilirubin (tBil), amylase (AMY), creatinine kinase (CK), total cholesterol (T-CHO), high-density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), triglyceride (TG), and C-reactive protein (CRP). **Significant correlations (P < 0.05) are marked in bold

Supplementary materials

The supplementary materials for this article are available at: https://www.explorationpub.com/uploads/Article/file/101258_sup_1.pdf.

Declarations

Acknowledgments

The authors would like to thank Prof. Masaki Takiguchi (Chiba University), Prof. Kenichiro Kitamura (Yamanishi University), Prof. Hao Wang (Jinan University), Dr. Xiao-Meng Zhang (Chiba University), Dr. Mari Oba (National Center of Neurology and Psychiatry, Tokyo), Dr. Risa Kimura (Chiba University), for supporting this research as well as Ms. Seiko Otsuka, Masae Suzuki, Chiho Kusaka, Satoko Ishibashi, and Akiko Kimura for technical assistance.

Author contributions

TH: Conceptualization, Investigation, Writing—original draft. YY: Writing—review & editing, Validation. MK: Investigation, Writing—original draft. BSZ: Investigation, Writing—original draft. SYL: Investigation, Writing—original draft. T Matsutani: Resource, Validation, Writing—review & editing. SH: Resource, Validation. MT: Conceptualization, Resource, Validation. KI: Investigation, Validation. SM: Resource, Validation. T Machida: Conceptualization, Validation, Writing—review & editing. YK: Conceptualization, Resource, Validation. HT: Resource, Validation. MI: Resource, Validation. SY: Resource, Validation. HS: Conceptualization, Writing—review & editing, Supervision. KY: Writing—review & editing, Supervision. YH: Writing—review & editing, Supervision. All authors read and approved the submitted version.

Conflicts of interest

The authors declare that they have no conflicts of interest.

Ethical approval

This study was approved by the Local Ethical Review Board of Chiba University, Graduate School of Medicine [approved numbers: 2012-438, 2014-44, 2016-86, 2017-251, 2018-320, 2020-1129, 2022-623, 2023-836], Toho University, Faculty of Medicine [approved numbers: A18103_A17052_A16035_A16001_26095_25024_ 24038_22047, 25131_23005], Toho University Omori Medical Center [approved number: 26-255], and Port Square Kashiwado Clinic [approved number: 2012‑001] as well as by the review boards of the participating hospitals. All experimental procedures were performed in accordance with the Declaration of Helsinki, version 2013.

Consent to participate

Written informed consent was obtained from all participants by following the protocols approved by their institutional ethical committees.

Consent to publication

Not applicable.

Availability of data and materials

All of the results of ProtoArray are available in the public Figshare database (https://figshare.com/articles/dataset/Results_of_protein_array_for_atherosclerosis/25906330). The other raw data supporting the conclusions of this manuscript will be made available by the authors, without undue reservation, to any qualified researcher.

Funding

This work was supported, in part, by research grants from the Japan Science and Technology Agency [JST: Exploratory Research No. 14657335], Japan Science and Technology Agency SPRING [grant nos. JPMJSP2109], and research grants from Japan Society for the Promotion of Science KAKENHI [Grant Number: 20K17953, 22K07273, 20K07810, 21K19437, 21K08695, 16K10520]. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Copyright

Publisher’s note

Open Exploration maintains a neutral stance on jurisdictional claims in published institutional affiliations and maps. All opinions expressed in this article are the personal views of the author(s) and do not represent the stance of the editorial team or the publisher.

References

Kikuchi Y, Shimada H, Yamasaki F, Yamashita T, Araki K, Horimoto K, et al. Clinical practice guidelines for molecular tumor marker, 2nd edition review part 2. Int J Clin Oncol. 2024;29:512–34. [DOI] [PubMed]

Nakashima K, Shimada H, Ochiai T, Kuboshima M, Kuroiwa N, Okazumi S, et al. Serological identification of TROP2 by recombinant cDNA expression cloning using sera of patients with esophageal squamous cell carcinoma. Int J Cancer. 2004;112:1029–35. [DOI] [PubMed]

Kuboshima M, Shimada H, Liu T, Nakashima K, Nomura F, Takiguchi M, et al. Identification of a novel SEREX antigen, SLC2A1/GLUT1, in esophageal squamous cell carcinoma. Int J Oncol. 2006;28:463–8. [PubMed]

Hou J, Zhao R, Xia W, Chang C, You Y, Hsu J, et al. PD-L1-mediated gasdermin C expression switches apoptosis to pyroptosis in cancer cells and facilitates tumour necrosis. Nat Cell Biol. 2020;22:1264–75. [DOI] [PubMed] [PMC]

Routsias JG, Tzioufas AG. Autoimmune response and target autoantigens in Sjogren’s syndrome. Eur J Clin Invest. 2010;40:1026–36. [DOI] [PubMed]

Fularski P, Czarnik W, Dąbek B, Lisińska W, Radzioch E, Witkowska A, et al. Broader Perspective on Atherosclerosis-Selected Risk Factors, Biomarkers, and Therapeutic Approach. Int J Mol Sci. 2024;25:5212. [DOI] [PubMed] [PMC]

Hiwasa T, Machida T, Zhang XM, Kimura R, Wang H, Iwase K, et al. Elevated levels of autoantibodies against ATP2B4 and BMP-1 in sera of patients with atherosclerosis-related diseases. Immunome Res. 2015;11:097. [DOI]

Hiwasa T, Tomiyoshi G, Nakamura R, Shinmen N, Kuroda H, Kunimatsu M, et al. Serum SH3BP5-specific antibody level is a biomarker of atherosclerosis. Immunome Res. 2017;13:132. [DOI]

Li S, Yoshida Y, Kobayashi E, Kubota M, Matsutani T, Mine S, et al. Serum anti-AP3D1 antibodies are risk factors for acute ischemic stroke related with atherosclerosis. Sci Rep. 2021;11:13450. [DOI] [PubMed] [PMC]

10.

Hiwasa T, Yoshida Y, Kubota M, Li S, Zhang B, Matsutani T, et al. Serum antiKIAA0513 antibody as a common biomarker for mortal atherosclerotic and cancerous diseases. Med Int (Lond). 2024;4:45. [DOI] [PubMed] [PMC]

11.

Makrilia N, Lappa T, Xyla V, Nikolaidis I, Syrigos K. The role of angiogenesis in solid tumours: an overview. Eur J Intern Med. 2009;20:663–71. [DOI] [PubMed]

12.

Tapia-Vieyra JV, Delgado-Coello B, Mas-Oliva J. Atherosclerosis and Cancer; A Resemblance with Far-reaching Implications. Arch Med Res. 2017;48:12–26. [DOI] [PubMed]

13.

Hiwasa T, Wang H, Goto K, Mine S, Machida T, Kobayashi E, et al. Serum anti-DIDO1, anti-CPSF2, and anti-FOXJ2 antibodies as predictive risk markers for acute ischemic stroke. BMC Med. 2021;19:131. [DOI] [PubMed] [PMC]

14.

Nishiura R, Fujimoto S, Sato Y, Yamada K, Hisanaga S, Hara S, et al. Elevated osteoprotegerin levels predict cardiovascular events in new hemodialysis patients. Am J Nephrol. 2009;29:257–63. [DOI] [PubMed]

15.

Komatsu H, Fujimoto S, Hara S, Fukuda A, Fukudome K, Yamada K, et al. Recent therapeutic strategies improve renal outcome in patients with IgA nephropathy. Am J Nephrol. 2009;30:19–25. [DOI] [PubMed]

16.

Goto K, Sugiyama T, Matsumura R, Zhang XM, Kimura R, Taira A, et al. Identification of cerebral infarction-specific antibody markers from autoantibodies detected in patients with systemic lupus erythematosus. J Mol Biomark Diagnos. 2015;6:2. [DOI]

17.

Hamanaka S, Nakagawa T, Hiwasa T, Ohta Y, Kasamatsu S, Ishigami H, et al. Investigation of novel biomarkers for predicting the clinical course in patients with ulcerative colitis. J Gastroenterol Hepatol. 2018;33:1975–83. [DOI] [PubMed]

18.

Naito A, Hiwasa T, Tanabe N, Sanada TJ, Sugiura T, Shigeta A, et al. Elevated levels of autoantibodies against EXD2 and PHAX in the sera of patients with chronic thromboembolic pulmonary hypertension. PLoS One. 2019;14:e0211377. [DOI] [PubMed] [PMC]

19.

Vermeulen N, de Béeck KO, Vermeire S, Steen KV, Michiels G, Ballet V, et al. Identification of a novel autoantigen in inflammatory bowel disease by protein microarray. Inflamm Bowel Dis. 2011;17:1291–300. [DOI] [PubMed]

20.

Chumpolkulwong N, Sakamoto K, Hayashi A, Iraha F, Shinya N, Matsuda N, et al. Translation of ‘rare’ codons in a cell-free protein synthesis system from Escherichia coli. J Struct Funct Genomics. 2006;7:31–6. [DOI] [PubMed]

21.

Matsumura T, Terada J, Kinoshita T, Sakurai Y, Yahaba M, Tsushima K, et al. Circulating autoantibodies against neuroblastoma suppressor of tumorigenicity 1 (NBL1): A potential biomarker for coronary artery disease in patients with obstructive sleep apnea. PLoS One. 2018;13:e0195015. [DOI] [PubMed] [PMC]

22.

Camp RL, Dolled-Filhart M, Rimm DL. X-tile: a new bio-informatics tool for biomarker assessment and outcome-based cut-point optimization. Clin Cancer Res. 2004;10:7252–9. [DOI] [PubMed]

23.

Liu Y, Cai G, Chen P, Jiang T, Xia Z. UBE2E3 regulates cellular senescence and osteogenic differentiation of BMSCs during aging. PeerJ. 2021;9:e12253. [DOI] [PubMed] [PMC]

24.

Sánchez-Duffhues G, Hiepen C, Knaus P, Dijke PT. Bone morphogenetic protein signaling in bone homeostasis. Bone. 2015;80:43–59. [DOI] [PubMed]

25.

Tran LTT, Park H, Kim H. Is the carotid intima-media thickness really a good surrogate marker of atherosclerosis? J Atheroscler Thromb. 2012;19:680–90. [DOI] [PubMed]

26.

Zureik M, Ducimetière P, Touboul PJ, Courbon D, Bonithon-Kopp C, Berr C, et al. Common carotid intima-media thickness predicts occurrence of carotid atherosclerotic plaques: longitudinal results from the Aging Vascular Study (EVA) study. Arterioscler Thromb Vasc Biol. 2000;20:1622–9. [DOI] [PubMed]

27.

Shirai K, Utino J, Otsuka K, Takata M. A novel blood pressure-independent arterial wall stiffness parameter; cardio-ankle vascular index (CAVI). J Atheroscler Thromb. 2006;13:101–7. [DOI] [PubMed]

28.

Fan J, Watanabe T. Atherosclerosis: Known and unknown. Pathol Int. 2022;72:151–60. [DOI] [PubMed]

29.

Libby P, Buring JE, Badimon L, Hansson GK, Deanfield J, Bittencourt MS, et al. Atherosclerosis. Nat Rev Dis Primers. 2019;5:56. [DOI] [PubMed]

30.

Nakamura R, Tomiyoshi G, Shinmen N, Kuroda H, Kudo T, Doi H, et al. An anti-deoxyhypusine synthase antibody as a marker of atherosclerosis-related cerebral infarction, myocardial infarction, diabetes mellitus, and chronic kidney disease. SM Atheroscler J. 2017;1:1001.

31.

Sumazaki M, Shimada H, Ito M, Shiratori F, Kobayashi E, Yoshida Y, et al. Serum anti-LRPAP1 is a common biomarker for digestive organ cancers and atherosclerotic diseases. Cancer Sci. 2020;111:4453–64. [DOI] [PubMed] [PMC]

32.

Li S, Yoshida Y, Kobayashi E, Adachi A, Hirono S, Matsutani T, et al. Association between serum antiASXL2 antibody levels and acute ischemic stroke, acute myocardial infarction, diabetes mellitus, chronic kidney disease and digestive organ cancer, and their possible association with atherosclerosis and hypertension. Int J Mol Med. 2020;46:1274–88. [DOI] [PubMed] [PMC]

33.

Jarvandi S, Davidson NO, Schootman M. Increased risk of colorectal cancer in type 2 diabetes is independent of diet quality. PLoS One. 2013;8:e74616. [DOI] [PubMed] [PMC]

34.

Fujihara S, Kato K, Morishita A, Iwama H, Nishioka T, Chiyo T, et al. Antidiabetic drug metformin inhibits esophageal adenocarcinoma cell proliferation in vitro and in vivo. Int J Oncol. 2015;46:2172–80. [DOI] [PubMed]

35.

Gallagher EJ, LeRoith D. Obesity and Diabetes: The Increased Risk of Cancer and Cancer-Related Mortality. Physiol Rev. 2015;95:727–48. [DOI] [PubMed] [PMC]

36.

Goto A, Yamaji T, Sawada N, Momozawa Y, Kamatani Y, Kubo M, et al. Diabetes and cancer risk: A Mendelian randomization study. Int J Cancer. 2020;146:712–9. [DOI] [PubMed] [PMC]

37.

Zhang C, Yang M. Functions of three ubiquitin-conjugating enzyme 2 genes in hepatocellular carcinoma diagnosis and prognosis. World J Hepatol. 2022;14:956–71. [DOI] [PubMed] [PMC]

38.

Yang Y, Chang Y, Tsai K, Hung M, Kang B. UBE2C triggers HIF-1α-glycolytic flux in head and neck squamous cell carcinoma. J Cell Mol Med. 2022;26:3716–25. [DOI] [PubMed] [PMC]

39.

Ma S, Chen Q, Li X, Fu J, Zhao L. UBE2C serves as a prognosis biomarker of uterine corpus endometrial carcinoma via promoting tumor migration and invasion. Sci Rep. 2023;13:16899. [DOI] [PubMed] [PMC]

40.

Li S, Xue S, Li Z. Osteoporosis: Emerging targets on the classical signaling pathways of bone formation. Eur J Pharmacol. 2024;973:176574. [DOI] [PubMed]

41.

Cai J, Pardali E, Sánchez-Duffhues G, Dijke Pt. BMP signaling in vascular diseases. FEBS Lett. 2012;586:1993–2002. [DOI] [PubMed]

42.

Dyer LA, Pi X, Patterson C. The role of BMPs in endothelial cell function and dysfunction. Trends Endocrinol Metab. 2014;25:472–80. [DOI] [PubMed] [PMC]

43.

Zhang M, Sara JD, Wang F, Liu L, Su L, Zhe J, et al. Increased plasma BMP-2 levels are associated with atherosclerosis burden and coronary calcification in type 2 diabetic patients. Cardiovasc Diabetol. 2015;14:64. [DOI] [PubMed] [PMC]

44.

Sorescu GP, Sykes M, Weiss D, Platt MO, Saha A, Hwang J, et al. Bone morphogenic protein 4 produced in endothelial cells by oscillatory shear stress stimulates an inflammatory response. J Biol Chem. 2003;278:31128–35. [DOI] [PubMed]

45.

Kim CW, Song H, Kumar S, Nam D, Kwon HS, Chang KH, et al. Anti-inflammatory and antiatherogenic role of BMP receptor II in endothelial cells. Arterioscler Thromb Vasc Biol. 2013;33:1350–9. [DOI] [PubMed] [PMC]

46.

Yao Y, Bennett BJ, Wang X, Rosenfeld ME, Giachelli C, Lusis AJ, et al. Inhibition of bone morphogenetic proteins protects against atherosclerosis and vascular calcification. Circ Res. 2010;107:485–94. [DOI] [PubMed] [PMC]

47.

Machida T, Kubota M, Kobayashi E, Iwadate Y, Saeki N, Yamaura A, et al. Identification of stroke-associated-antigens via screening of recombinant proteins from the human expression cDNA library (SEREX). J Transl Med. 2015;13:71. [DOI] [PubMed] [PMC]

48.

Braig S, Bosserhoff A. Death inducer-obliterator 1 (Dido1) is a BMP target gene and promotes BMP-induced melanoma progression. Oncogene. 2013;32:837–48. [DOI] [PubMed]

49.

Zhou W, Yan K, Xi Q. BMP signaling in cancer stemness and differentiation. Cell Regen. 2023;12:37. [DOI] [PubMed] [PMC]

50.

Sharma T, Kapoor A, Mandal CC. Duality of bone morphogenetic proteins in cancer: A comprehensive analysis. J Cell Physiol. 2022;237:3127–63. [DOI] [PubMed]

51.

Ehata S, Miyazono K. Bone Morphogenetic Protein Signaling in Cancer; Some Topics in the Recent 10 Years. Front Cell Dev Biol. 2022;10:883523. [DOI] [PubMed] [PMC]

52.

Alkhathami AG, Abdullah MR, Ahmed M, Ahmed HH, Alwash SW, Mahdi ZM, et al. Bone morphogenetic protein (BMP)9 in cancer development: mechanistic, diagnostic, and therapeutic approaches? J Drug Target. 2023;31:714–24. [DOI] [PubMed]