Relationship between serum adipokine expression and insulin resistance in people with different degrees of impaired glucose tolerance and its value in predicting risk of disease progression in prediabetes

SHEN Yanmei; LI Huifang; LI Ya; YANG Chaoju

doi:10.7619/jcmp.20242935

Journal of Clinical Medicine in Practice > 2024 > 28(23): 116-120, 131. > DOI: 10.7619/jcmp.20242935

SHEN Yanmei, LI Huifang, LI Ya, YANG Chaoju. Relationship between serum adipokine expression and insulin resistance in people with different degrees of impaired glucose tolerance and its value in predicting risk of disease progression in prediabetes[J]. Journal of Clinical Medicine in Practice, 2024, 28(23): 116-120, 131. DOI: 10.7619/jcmp.20242935

Citation:

PDF (1001 KB)

Relationship between serum adipokine expression and insulin resistance in people with different degrees of impaired glucose tolerance and its value in predicting risk of disease progression in prediabetes

1.
Department of Clinical Laboratory, Shijiazhuang City Second Hospital, Shijiazhuang, Hebei, 050000
2.
Department of Clinical Laboratory, Hebei Provincial People's Hospital, Shijiazhuang, Hebei, 050000

More Information

Received Date: July 10, 2024
Revised Date: September 22, 2024

Graphical Abstract

Abstract

Abstract

Objective
To investigate the relationship between serum adipokine expression and insulin resistance in individuals with different degrees of glucose intolerance, and to assess the value of these adipokines in predicting the risk of progression in prediabetes.
Methods
A total of 114 participants with oral glucose tolerance test were enrolled and divided into three groups based on diagnostic and classification criteria for diabetes: normal glucose tolerance (NGT, n=32), impaired glucose tolerance (IGT, n=46), and type 2 diabetes mellitus (T2DM, n=36). Serum levels of adiponectin (APN), leptin (LEP) and preadipocyte factor-1 (Pref-1) as well as homeostasis model assessment for insulin resistance (HOMA-IR) and homeostasis model assessment for pancreatic β-cell function (HOMA-β) were compared among the three groups. Pearson correlation analysis was conducted to explore the correlations of serum APN, LEP and Pref-1 levels with HOMA-IR and HOMA-β. Receiver operating characteristic (ROC) curve was used to analyze the predictive values of serum APN, LEP and Pref-1 levels for the progression of prediabetes.
Results
Serum APN levels were significantly lower in the T2DM and IGT groups compared to the NGT group, with further significant reduction observed in the T2DM group compared to the IGT group (P < 0.05); conversely, serum LEP, Pref-1, fasting plasma glucose (FPG), 2-hour postprandial glucose (2 hPG), fasting insulin (FINS), glycated hemoglobin (HbA1c), triglycerides (TG) and C-reactive protein (CRP) levels were significantly higher in the T2DM and IGT groups than in the NGT group, with additional significant increases observed in the T2DM group compared to the IGT group (P < 0.05). HOMA-IR was significantly lower in both the T2DM and IGT groups than in the NGT group, with a further significant decrease in the T2DM group compared to the IGT group (P < 0.05). HOMA-β was significantly higher in both the T2DM and IGT groups compared to the NGT group, with a further significant increase in the T2DM group versus the IGT group (P < 0.05). Serum APN level was positively correlated with HOMA-IR (r=0.547, P < 0.05) and negatively correlated with HOMA-β (r=-0.506, P < 0.05); serum LEP and Pref-1 levels were negatively correlated with HOMA-IR (r=-0.325, -0.459, P < 0.05) and positively correlated with HOMA-β (r=0.317, 0.428, P < 0.05). ROC curve analysis revealed optimal cut-off values for serum APN, LEP and Pref-1 levels in predicting the progression of prediabetes were 15.98 mg/L, 4.23 mg/L and 18.85 μg/L, respectively. The combination of these three biomarkers showed a sensitivity of 80.43%, a specificity of 96.87%, and an area under the curve (AUC) of 0.925.
Conclusion
Serum levels of APN, LEP and Pref-1 abnormally change in patients with impaired glucose tolerance and are associated with insulin resistance. These adipokines can serve as sensitive indicators for predicting the progression of prediabetes, with higher predictive value when used in combination.
- impaired glucose tolerance,
- adipokines,
- type 2 diabetes mellitus,
- insulin resistance,
- prediabetes

FullText(HTML)

References (19)

References

[1]	张磊, 乔岗, 韩丽, 等. 2型糖尿病患者炎性因子与糖脂代谢指标的相关性及其预测微血管病变的价值[J]. 实用临床医药杂志, 2023, 27(13): 114-118. doi: 10.7619/jcmp.20230092
[2]	GBD 2021 Diabetes Collaborators. Global, regional, and national burden of diabetes from 1990 to 2021, with projections of prevalence to 2050: a systematic analysis for the Global Burden of Disease Study 2021[J]. Lancet, 2023, 402(10397): 203-234. doi: 10.1016/S0140-6736(23)01301-6
[3]	ZHU X Q, CHEN L, LIN J S, et al. Association between fatty acids and the risk of impaired glucose tolerance and type 2 diabetes mellitus in American adults: NHANES 2005-2016[J]. Nutr Diabetes, 2023, 13(1): 8. doi: 10.1038/s41387-023-00236-4
[4]	LEE D H, LIM J A, KIM J H, et al. Longitudinal changes of high molecular weight adiponectin are associated with postpartum development of type 2 diabetes mellitus in patients with gestational diabetes mellitus[J]. Endocrinol Metab, 2021, 36(1): 114-122. doi: 10.3803/EnM.2020.831
[5]	KIERNAN K, NICHOLS A G, ALWARAWRAH Y, et al. Effects of T cell leptin signaling on systemic glucose tolerance and T cell responses in obesity[J]. PLoS One, 2023, 18(6): e0286470. doi: 10.1371/journal.pone.0286470
[6]	HUANG Y H, CUI D H, CHEN L J, et al. A pref-1-controlled non-inflammatory mechanism of insulin resistance[J]. iScience, 2023, 26(6): 106923. doi: 10.1016/j.isci.2023.106923
[7]	张琳, 董鹏, 李友芳, 等. 口服葡萄糖耐量试验负荷后1小时血糖筛查糖调节受损和糖尿病的最佳切点值及糖调节受损患者转归的随访研究[J]. 现代生物医学进展, 2023, 23(19): 3642-3645, 3677.
[8]	胡秀娟, 惠灿灿, 王淑倩, 等. 血浆致动脉硬化指数联合胰岛素抵抗指数对2型糖尿病患者估算肾小球滤过率降低的预测价值[J]. 实用临床医药杂志, 2023, 27(20): 29-32. doi: 10.7619/jcmp.20232415
[9]	IKOH RPH C L, TANG TINONG R. The incidence and management of type 2 diabetes mellitus after gestational diabetes mellitus[J]. Cureus, 2023, 15(8): e44468.
[10]	KIM J E, KIM J S, JO M J, et al. The roles and associated mechanisms of adipokines in development of metabolic syndrome[J]. Molecules, 2022, 27(2): 334. doi: 10.3390/molecules27020334
[11]	VENOJÄRVI M, LINDSTRÖM J, AUNOLA S, et al. Improved aerobic capacity and adipokine profile together with weight loss improve glycemic control without changes in skeletal muscle GLUT-4 gene expression in middle-aged subjects with impaired glucose tolerance[J]. Int J Environ Res Public Health, 2022, 19(14): 8327. doi: 10.3390/ijerph19148327
[12]	DUMOLT J, POWELL T L, JANSSON T, et al. Normalization of maternal adiponectin in obese pregnant mice prevents programming of impaired glucose metabolism in adult offspring[J]. FASEB J, 2022, 36(7): e22383. doi: 10.1096/fj.202200326R
[13]	韩晓文, 孙桢, 李雪姣, 等. 25-(OH)D₃、脂联素、趋化素与妊娠期糖尿病患者胰岛素抵抗的相关性分析[J]. 国际生物医学工程杂志, 2022, 45(6): 527-531. doi: 10.3760/cma.j.cn121382-20220708-00610
[14]	HAN Y, HE Y, HARRIS L, et al. Identification of a GABAergic neural circuit governing leptin signaling deficiency-induced obesity[J]. Elife, 2023, 12: e82649. doi: 10.7554/eLife.82649
[15]	CHENG W H, CHEN C L, CHEN J Y, et al. Hypoxia-induced preadipocyte factor 1 expression in human lung fibroblasts through ERK/PEA3/c-Jun pathway[J]. Mol Med, 2021, 27(1): 69. doi: 10.1186/s10020-021-00336-w
[16]	BRISMAR K, HILDING A, ANSURUDEEN I, et al. Adiponectin, IGFBP-1 and-2 are independent predictors in forecasting prediabetes and type 2 diabetes[J]. Front Endocrinol, 2022, 13: 1092307.
[17]	AN M, PARK Y H, LIM Y H. Antiobesity and antidiabetic effects of the dairy bacterium Propionibacterium freudenreichii MJ2 in high-fat diet-induced obese mice by modulating lipid metabolism[J]. Sci Rep, 2021, 11(1): 2481. doi: 10.1038/s41598-021-82282-5
[18]	AREOLA E D, ADEWUYI I J, USMAN T O, et al. Sildenafil augments fetal weight and placental adiponectin in gestational testosterone-induced glucose intolerant rats[J]. Toxicol Rep, 2021, 8: 1358-1368. doi: 10.1016/j.toxrep.2021.06.011
[19]	茅晶晶, 项颖, 陈青红. 妊娠期糖尿病患者产后6周糖代谢转归和胰岛素抵抗状况分析[J]. 中国妇幼保健, 2022, 37(7): 1196-1199.

[1]	LIU Kun, XU Qingyi, ZHU Jun, CHEN Fang. A comparison of macular morphology and microcirculation index in patients with pathological myopic choroidal neovascularization at different ages[J]. Journal of Clinical Medicine in Practice, 2023, 27(18): 65-69. DOI: 10.7619/jcmp.20231883
[2]	REN Yizhou, LIU Xiaorong, LI Zhe, XU Min, CHEN Fang, GAN Chunlan. Quantitative study of vessel density in optic disc and macular region in patients with nonarteritic anterior ischemic optic neuropathy[J]. Journal of Clinical Medicine in Practice, 2023, 27(4): 70-75, 79. DOI: 10.7619/jcmp.20222588
[3]	SHEN Yongzhi, HUANG Jiali, XIAN Kegong, LI Zhihui, ZHAO Fentu. Application of optical coherence tomography angiography in fundus screening in newly diagnosed patients with type 2 diabetes[J]. Journal of Clinical Medicine in Practice, 2023, 27(4): 56-60. DOI: 10.7619/jcmp.20222539
[4]	WU Huihui, ZHANG Xue, WANG Yan, LIU Yan, LUO Na, CHEN Fang. Quantitative study of optic disc blood flow density and thickness of peripapillary retinal nerve fiber layer in patients with diabetes mellitus[J]. Journal of Clinical Medicine in Practice, 2022, 26(7): 57-61. DOI: 10.7619/jcmp.20213748
[5]	ZHOU Chunshan, HUANG Yan, YAN Wenchao. Value of computed tomography scan versus magnetic resonance imaging in the diagnosis of pancreatic cystadenocarcinoma[J]. Journal of Clinical Medicine in Practice, 2020, 24(20): 47-50. DOI: 10.7619/jcmp.202020013
[6]	ZHAO Chenghua. Value of artificial intelligence assisted diagnostic system combined with CT test in diagnosis of pulmonary nodules[J]. Journal of Clinical Medicine in Practice, 2020, 24(19): 9-11. DOI: 10.7619/jcmp.202019003
[7]	LU Cuihong, ZHANG Baoyuan. Brain computed tomography findings and their diagnostic value in elderly patients with cerebral hemorrhage[J]. Journal of Clinical Medicine in Practice, 2019, 23(24): 8-10. DOI: 10.7619/jcmp.201924003
[8]	GONG Yujing, WU Binghui, SUO Yan, LU Huiqin, QU Xiaoyu. Characteristics of choroidal neovascularization in optical coherence tomography angiography versus fluorescein angiography[J]. Journal of Clinical Medicine in Practice, 2019, 23(22): 14-16. DOI: 10.7619/jcmp.201922005
[9]	TIAN Juan, WANG Huifang, DONG Jianghua. Value of abdominal computed tomography in evaluating extramural vascular invasion of gastric cancer[J]. Journal of Clinical Medicine in Practice, 2019, 23(7): 29-31, 36. DOI: 10.7619/jcmp.201907008
[10]	JIANG Hongfen, GU Jie, XU Yanling, MENG Haoyu, ZHANG Dingguo, JIA Enzhi, CHEN Leilei, WANG Liansheng, SHI Dongmei. Perioperative nursing of new generation optical coherence tomography in diagnosis of percutaneous coronary intervention[J]. Journal of Clinical Medicine in Practice, 2018, (12): 4-7. DOI: 10.7619/jcmp.201812002

Cited By

Cited by

Periodical cited type(15)

1.	薛彦霞，刘雨情，续自凤. 升降散加减治疗重症肺炎(痰热壅肺型)的效果及对炎症因子和外周血T淋巴细胞群的影响. 中外医疗. 2024(09): 31-34 .
2.	张敏. 中医定向透药疗法对肺炎患儿临床疗效及炎性因子水平的影响. 反射疗法与康复医学. 2024(17): 8-10+17 .
3.	李文艳，许志强. 呼吸机相关肺炎危重症患者使用合生元制剂联合肠内营养序贯治疗的临床研究. 中国药物与临床. 2024(20): 1341-1345 .
4.	闵翼，殷智，潘旭. 清金降火汤治疗痰热壅肺型肺炎的临床研究. 航空航天医学杂志. 2023(01): 66-68 .
5.	李思灵，颜沃志，廖夏萍. 纤维支气管镜下盐酸氨溴索注射液肺泡灌洗治疗COPD合并呼吸衰竭的效果. 中国医学创新. 2023(02): 50-54 .
6.	郑相，范青红，邱芳晖. 清肺化痰汤联合西医常规治疗呼吸机相关性肺炎老年患者临床研究. 新中医. 2023(04): 21-24 .
7.	董璐阳，张琳，李怡辉. 中医护理干预对呼吸机相关肺炎患者血气指标、生活质量的影响. 实用中医内科杂志. 2023(02): 80-83 .
8.	丁鑫，钱占红. 升降散对脓毒症所致急性肺损伤小鼠的保护作用. 环球中医药. 2023(04): 591-597 .
9.	罗志辉，王昆秀，张艳琳，陈子琴，陈贝，陈佳，周婷，顾骁磊，李崇立，闫鹏，田玲玲，徐驰成，陈柏霖，陈松，祁青. 回顾性分析三消饮加减方治疗轻型/普通型新型冠状病毒肺炎患者的临床疗效. 中国实验方剂学杂志. 2022(01): 150-156 .
10.	周同鑫，石静娟，裴昶，曹振华，殷智，钱丽. “支炎一号”方治疗成人痰热壅肺型支气管扩张临床疗效分析. 中外医疗. 2022(02): 103-106 .
11.	章文莉，汪芬华，陈梅. 天枢穴贴敷联合升降散保留灌肠治疗呼吸机相关性肺炎52例. 中国中医药科技. 2022(05): 931-932+935 .
12.	马文静，张维利，刘素梅，祁佩红. 加味温胆汤对痰湿蕴肺型慢性阻塞性肺疾病急性加重期患者炎症细胞因子表达及BODE指数的影响. 中医药信息. 2022(09): 53-57+62 .
13.	姜立娟，魏岩，张文风. 升降散证治探微. 长春中医药大学学报. 2022(10): 1063-1066 .
14.	张爱宝，白小丽，成媛，薛云霞. 超声脉冲电导辅助治疗小儿支气管肺炎的临床观察. 中国民间疗法. 2021(15): 77-79 .
15.	刘蓉. 心外科ICU呼吸机相关性肺炎患者病原菌的分布分析与研究. 名医. 2020(10): 85-86 .

Other cited types(2)

Get Citation

PDF

XML

Article views (91) PDF downloads (5) Cited by(17)

Turn off MathJax

Article Contents

Abstract

References

Relationship between serum adipokine expression and insulin resistance in people with different degrees of impaired glucose tolerance and its value in predicting risk of disease progression in prediabetes