Download PDF
Exp Clin Endocrinol Diabetes 2021; 129(08): 553-559
DOI: 10.1055/a-0950-9828
Article

The Relationship Between β-cell Function Indices and Sudomotor Function in Chinese Patients with Type 2 Diabetes

Bai-lu Cao‡
1   Department of Endocrinology, the affiliated Jinling Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
,
Yue Yao‡
2   Department of Endocrinology, Jinling Hospital, Nanjing University, Nanjing, Jiangsu, China
,
Yi-xin Xu‡
1   Department of Endocrinology, the affiliated Jinling Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
,
Jiang Fang
3   Department of Neurosurgery, Jinling Hospital, Southeast University, Nanjing, Jiangsu, China
,
Wen-jing Song
4   Department of Endocrinology, Jinling Hospital, Southern Medical University, Nanjing, Jiangsu, China
,
Bin Hu
2   Department of Endocrinology, Jinling Hospital, Nanjing University, Nanjing, Jiangsu, China
,
Qing-yu Guo
2   Department of Endocrinology, Jinling Hospital, Nanjing University, Nanjing, Jiangsu, China
,
Bin Lu
1   Department of Endocrinology, the affiliated Jinling Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
,
Jie Li
1   Department of Endocrinology, the affiliated Jinling Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
,
Ping Gu
1   Department of Endocrinology, the affiliated Jinling Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
,
Jia-qing Shao
1   Department of Endocrinology, the affiliated Jinling Hospital of Nanjing Medical University, Nanjing, Jiangsu, China
› Author Affiliations
› Further Information
Also available at
    Permissions and Reprints

Abstract

Purpose SUDOSCAN, a new non-invasive, quick, sensitive and quantitative technique, has been developed to detect diabetic peripheral neuropathy, and the latter is believed to be correlated with impaired β-cell function. The purpose of the present study was to investigate the associations between β-cell function indices and sudomotor function in Chinese type 2 diabetes.

Methods A total of 266 Chinese patients with type 2 diabetes were enrolled. Sudomotor function was assessed using electrochemical skin conductance of hands and feet. Pancreatic β-cell function was determined by homeostasis model assessment of β-cell function index, early-phase β-cell function indices and total β-cell function indices. Pearson correlation analysis and multiple linear stepwise regression analysis were carried out to explore the associations between β-cell function indices and sudomotor function.

Results Patients with lower early-phase β-cell function had lower electrochemical skin conductance levels of hands and feet and higher asymmetry ratio of hands and feet. Both Pearson correlation analysis and multiple linear stepwise regression analysis showed significantly positive relationships between early-phase β-cell function and electrochemical skin conductance levels of hands and feet, after controlling for potential confounders (P<0.05).

Conclusions Impaired early-phase β-cell function was positively associated with sudomotor dysfunction in Chinese patients with type 2 diabetes. We speculated that impaired early-phase β-cell function may be associated with the incidence of sudomotor dysfunction in patients with T2DM.

Key words

Early-phase insulin secretion - SUDOSCAN - Diabetic peripheral neuropathy


Publication History

Received: 07 October 2018
Received: 28 May 2019

Accepted: 04 June 2019

Article published online:
03 July 2019

© 2019. Thieme. All rights reserved.

© Georg Thieme Verlag KG
Stuttgart · New York

 

  • References

  • 1 Vinik AI, Marie-Laure N, Carolina C. The new age of sudomotor function testing. a sensitive and specific biomarker for diagnosis, estimation of severity, monitoring progression, and regression in response to intervention. Frontiers in Endocrinology 2015; 6: 94
    CrossrefPubMedGoogle Scholar
  • 2 Prato SD. Loss of early insulin secretion leads to postprandial hyperglycaemia. Diabetologia 2003; 46 Suppl 1 M2-M8
    CrossrefPubMedGoogle Scholar
  • 3 Kohnert KD, Augstein P, Zander E. et al. Glycemic variability correlates strongly with postprandial beta-cell dysfunction in a segment of type 2 diabetic patients using oral hypoglycemic agents. Diabetes Care 2009; 32: 1058-1062
    CrossrefPubMedGoogle Scholar
  • 4 Su Jian-bin Wang. et al. Glycemic variability in gestational diabetes mellitus and its;association with beta cell function. Endocrine 2013; 43: 370-375
    CrossrefPubMedGoogle Scholar
  • 5 Sartore G, Chilelli NC, Burlina S. et al. Association between glucose variability as assessed by continuous glucose monitoring (CGM) and diabetic retinopathy in type 1 and type 2 diabetes. Acta Diabetologica 2013; 50: 437-442
    CrossrefPubMedGoogle Scholar
  • 6 Hu YM, Zhao LH, Zhang XL. et al. Association of glycaemic variability evaluated by continuous glucose monitoring with diabetic peripheral neuropathy in type 2 diabetic patients. Endocrine 2018; 60: 1-9
    CrossrefPubMedGoogle Scholar
  • 7 Jin HY, Lee KA, Park TS. The impact of glycemic variability on diabetic peripheral neuropathy. Endocrine 2016; 53: 1-6
    CrossrefPubMedGoogle Scholar
  • 8 Wen X, Zhu Y, Yang X. et al. Glycemic variability is an important risk factor for cardiovascular autonomic neuropathy in newly diagnosed type 2 diabetic patients. International Journal of Cardiology 2016; 215: 263-268
    CrossrefPubMedGoogle Scholar
  • 9 Gong S, Shuhua M, Hong T. et al. Association of glycemic variability and the presence and severity of coronary artery disease in patients with type 2 diabetes. Cardiovasc Diabetol 2011; 10: 19
    CrossrefPubMedGoogle Scholar
  • 10 Sayer WJ, Marchant B, Gelding VS. et al. Autonomic dysfunction is related to impaired pancreatic beta cell function in patients with coronary artery disease. Heart 2000; 83: 210-216
    CrossrefPubMedGoogle Scholar
  • 11 Xiaojing M, Yaping H, Xiang H. et al. 1,5-anhydroglucitol is associated with early-phase insulin secretion in chinese patients with newly diagnosed type 2 diabetes mellitus. Diabetes Research & Clinical Practice 2016; 120: S63-S63
    CrossrefPubMedGoogle Scholar
  • 12 LJCJD Biggelaar, SJS Sep, Eussen SJPM. et al. Discriminatory ability of simple OGTT-based beta cell function indices for prediction of prediabetes and type 2 diabetes. The CODAM study. Diabetologia 2017; 60: 1-10
    CrossrefPubMedGoogle Scholar
  • 13 Casellini CM, Parson HK, Richardson MS. et al. Sudoscan, a noninvasive tool for detecting diabetic small fiber neuropathy and autonomic dysfunction. Diabetes Technology & Therapeutics 2013; 15: 948-953
    CrossrefPubMedGoogle Scholar
  • 14 Hubert D, Brunswick P, Calvet JH. et al. Abnormal electrochemical skin conductance in cystic fibrosis. Journal of Cystic Fibrosis 2011; 10: 15-20
    CrossrefPubMedGoogle Scholar
  • 15 Hsu WC, Chiu SY, Yen AM. et al. Somatic neuropathy is an independent predictor of all- and diabetes-related mortality in type 2 diabetic patients. A population-based 5-year follow-up study (KCIS No. 29). European Journal of Neurology 2012; 19: 1192-1198
    CrossrefPubMedGoogle Scholar
  • 16 Aksenov IV. Neuropathic Diabetic Foot Ulcers. New Engl J Med 2004; 351: 1694-1695
    CrossrefPubMedGoogle Scholar
  • 17 Tesfaye S, Chaturvedi N, Eaton SE. Vascular risk factors and diabetic neuropathy. Journal of Vascular Surgery 2005; 41: 1079. doi:10.1016/j.jvs.2005.03.051
    CrossrefPubMedGoogle Scholar
  • 18 El Boghdady NA, Badr GA. Evaluation of oxidative stress markers and vascular risk factors in patients with diabetic peripheral neuropathy. Cell Biochemistry & Function 2012; 30: 328-334
    CrossrefPubMedGoogle Scholar
  • 19 Melles E, Jörrnvall H, Tryggvason S. et al. Degradation of proinsulin C-peptide in kidney and placenta extracts by a specific endoprotease activity. Cell Mol Life Sci 2004; 61: 2979-2982
    CrossrefPubMedGoogle Scholar
  • 20 Marx N, Walcher D. C-Peptide and atherogenesis. C-Peptide as a mediator of lesion development in patients with type 2 diabetes mellitus? Experimental. Diabetes Research 2014; 2008: 385108
    PubMedGoogle Scholar
  • 21 Lachin JM, McGee P, Palmer JP. Impact of C-peptide preservation on metabolic and clinical outcomes in the Diabetes Control and Complications Trial. Diabetes 2014; 63: 739-748 doi:10.2337/db13-0881
    CrossrefPubMedGoogle Scholar
  • 22 Bo S, Gentile L, Castiglione A. et al. C-peptide and the risk for incident complications and mortality in type 2 diabetic patients. A retrospective cohort study after a 14-year follow-up. Eur J Endocrinol 2012; 167: 173-180 doi:10.1530/EJE-12-0085
    CrossrefPubMedGoogle Scholar
  • 23 Fang P, Dong J, Zeng F. et al. Analysis of the association between glucose profiles and β-cell function for diabetic cardiovascular autonomic neuropathy in China. Journal of Diabetes Investigation 2017; 8: 354-362
    CrossrefPubMedGoogle Scholar
  • 24 Vinik AI, Smith AG, Singleton JR. et al. Normative values for electrochemical skin conductances and impact of ethnicity on quantitative assessment of sudomotor function. Diabetes Technol Ther 2016; 18: 391-398
    CrossrefPubMedGoogle Scholar
  • 25 Hotta H, Uchida S. Aging of the autonomic nervous system and possible improvements in autonomic activity using somatic afferent stimulation. Geriatrics & Gerontology International 2010; 10: S127-S136
    CrossrefPubMedGoogle Scholar
  • 26 Tesfaye S, Stevens LK, Stephenson JM. et al. Prevalence of diabetic peripheral neuropathy and its relation to glycaemic control and potential risk factors. The EURODIAB IDDM Complications Study. Diabetologia 1996; 39: 1377-1384
    CrossrefPubMedGoogle Scholar
  • 27 Xu F, Zhao LH, Su JB. et al. The relationship between glycemic variability and diabetic peripheral neuropathy in type 2 diabetes with well-controlled HbA1c. Diabetology & Metabolic Syndrome 2014; 6: 1-7
    CrossrefPubMedGoogle Scholar
  • 28 Yajnik CS, Kantikar VV, Pande AJ. et al. Quick and simple evaluation of sudomotor function for screening of diabetic neuropathy. Isrn. Endocrinology 2015; 2012: 103714
    PubMedGoogle Scholar
  • 29 Rosson GD, Lee Dellon A. Vascular risk factors and diabetic neuropathy. N Engl J Med 2005; 352: 1925-1927
    CrossrefPubMedGoogle Scholar
  • 30 Wang DD, Bakhotmah BA, Hu FB. et al. Prevalence and correlates of diabetic peripheral neuropathy in a Saudi Arabic population. A cross-sectional study. Plos One 2014; 9: e106935
    CrossrefPubMedGoogle Scholar
  • 31 Sheshah E, Madanat A, Al-Greesheh F. et al. Electrochemical skin conductance to detect sudomotor dysfunction, peripheral neuropathy and the risk of foot ulceration among Saudi patients with diabetes mellitus. Journal of Diabetes & Metabolic Disorders 2015; 15: 29
    CrossrefPubMedGoogle Scholar
  • 32 Papanas N, Demetriou M, Katsiki N. et al. Increased serum levels of uric acid are associated with sudomotor dysfunction in subjects with type 2 diabetes mellitus. Experimental Diabetes Research 2011; 2011: 346051
    CrossrefPubMedGoogle Scholar
  • 33 Papanas N, Katsiki N, Papatheodorou K. et al. Peripheral neuropathy is associated with increased serum levels of uric acid in type 2 diabetes mellitus. Angiology 2011; 62: 291-295
    CrossrefPubMedGoogle Scholar
  • 34 Shuai Y, Ying C, Xu H. et al. Serum Uric Acid Levels and Diabetic Peripheral Neuropathy in Type 2 Diabetes. A Systematic Review and Meta-analysis. Molecular Neurobiology 2015; 53: 1045-1051
    PubMedGoogle Scholar