Share this content in WeChat
Research progress of MRI on the relationship between blood glucose fluctuations and cognitive dysfunction in type 2 diabetes
XU Kun  WANG Jun  LIU Guangyao  ZHANG Jing 

Cite this article as: XU K, WANG J, LIU G Y, et al. Research progress of MRI on the relationship between blood glucose fluctuations and cognitive dysfunction in type 2 diabetes[J]. Chin J Magn Reson Imaging, 2023, 14(10): 137-140, 146. DOI:10.12015/issn.1674-8034.2023.10.024.

[Abstract] Type 2 diabetes mellitus (T2DM) is one kind of high risk factor of cognitive dysfunction. Fluctuations in blood glucose will increase the risk of cognitive dysfunction in patients with T2DM. MRI, as a non-invasive neuroimaging technique, has been widely used to study the pathogenesis associated with cognitive dysfunction with T2DM. This article mainly reviews the literature on blood glucose fluctuations and cognitive dysfunction in T2DM to clarify the relationship between them, and to provide targets for clinical treatment.
[Keywords] type 2 diabetes mellitus;blood glucose fluctuations;cognitive dysfunction;magnetic resonance imaging

XU Kun1, 2   WANG Jun1, 2   LIU Guangyao1, 3   ZHANG Jing1, 3*  

1 Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou 730030, China

2 Second Clinical School, Lanzhou University, Lanzhou 730030, China

3 Gansu Province Clinical Research Center for Functional and Molecular Imaging, Lanzhou 730030, China

Corresponding author: ZHANG J, E-mail:

Conflicts of interest   None.

ACKNOWLEDGMENTS National Natural Science Foundation of China (No. 81960309); Science and Technology Project of Gansu Province (No. 18JR3RA317, 21JR7RA438); Health Industry Science Research Project of Gansu Province (No. GSWSKY2021-031).
Received  2023-02-07
Accepted  2023-09-14
DOI: 10.12015/issn.1674-8034.2023.10.024
Cite this article as: XU K, WANG J, LIU G Y, et al. Research progress of MRI on the relationship between blood glucose fluctuations and cognitive dysfunction in type 2 diabetes[J]. Chin J Magn Reson Imaging, 2023, 14(10): 137-140, 146. DOI:10.12015/issn.1674-8034.2023.10.024.

STRACHAN M W, REYNOLDS R M, MARIONI R E, et al. Cognitive function, dementia and type 2 diabetes mellitus in the elderly[J]. Nat Rev Endocrinol, 2011, 7(2): 108-114. DOI: 10.1038/nrendo.2010.228.
MAKINO K, LEE S, BAE S, et al. Diabetes and prediabetes inhibit reversion from mild cognitive impairment to normal cognition[J/OL]. J Am Med Dir Assoc, 2021, 22(9): 1912-1918.e2 [2023-02-06]. DOI: 10.1016/j.jamda.2021.02.033.
Chinese Society of Endocrinology. Experts Consensus on Management of Glycemic Variability of Diabetes Mellitus[J]. Chinese Journal of Endocrinology and Metabolism, 2017, 33(8): 633-636. DOI: 10.3760/cma.j.issn.1000-6699.2017.08.002.
CZERWONIUK D, FENDLER W, WALENCIAK L, et al. GlyCulator: a glycemic variability calculation tool for continuous glucose monitoring data[J]. J Diabetes Sci Technol, 2011, 5(2): 447-451. DOI: 10.1177/193229681100500236.
RODBARD D. New and improved methods to characterize glycemic variability using continuous glucose monitoring[J]. Diabetes Technol Ther, 2009, 11(9): 551-565. DOI: 10.1089/dia.2009.0015.
CHOLEAU C, AUBERT C, CAHANE M, et al. High day-to-day glucose variability: a frequent phenomenon in children and adolescents with type 1 diabetes attending summer camp[J]. Diabetes Metab, 2008, 34(1): 46-51. DOI: 10.1016/j.diabet.2007.12.002.
OHARA M, FUKUI T, OUCHI M, et al. Relationship between daily and day-to-day glycemic variability and increased oxidative stress in type 2 diabetes[J]. Diabetes Res Clin Pract, 2016, 122: 62-70. DOI: 10.1016/j.diabres.2016.09.025.
SAKAMOTO M. Type 2 diabetes and glycemic variability: Various parameters in clinical practice[J]. J Clin Med Res, 2018, 10(10): 737-742. DOI: 10.14740/jocmr3556w.
MONNIER L, COLETTE C, OWENS D R. The application of simple metrics in the assessment of glycaemic variability[J]. Diabetes Metab, 2018, 44(4): 313-319. DOI: 10.1016/j.diabet.2018.02.008.
CERIELLO A, MONNIER L, OWENS D. Glycaemic variability in diabetes: clinical and therapeutic implications[J]. Lancet Diabetes Endocrinol, 2019, 7(3): 221-230. DOI: 10.1016/s2213-8587(18)30136-0.
KOVATCHEV B P. Metrics for glycaemic control - from HbA(1c) to continuous glucose monitoring[J]. Nat Rev Endocrinol, 2017, 13(7): 425-436. DOI: 10.1038/nrendo.2017.3.
RODBARD D. Glucose variability: A review of clinical applications and research developments[J/OL]. Diabetes Technol Ther, 2018, 20(S2): S25-S215 [2023-02-06]. DOI: 10.1089/dia.2018.0092.
LI T C, YANG C P, TSENG S T, et al. Visit-to-visit variations in fasting plasma glucose and HbA(1c) associated with an increased risk of Alzheimer disease: Taiwan diabetes study[J]. Diabetes Care, 2017, 40(9): 1210-1217. DOI: 10.2337/dc16-2238.
KIM C, SOHN J H, JANG M U, et al. Association between visit-to-visit glucose variability and cognitive function in aged type 2 diabetic patients: A cross-sectional study[J/OL]. PLoS One, 2015, 10(7): e0132118 [2023-02-06]. DOI: 10.1371/journal.pone.0132118.
RAVONA-SPRINGER R, HEYMANN A, SCHMEIDLER J, et al. Trajectories in glycemic control over time are associated with cognitive performance in elderly subjects with type 2 diabetes[J/OL]. PLoS One, 2014, 9(6): e97384 [2023-02-06]. DOI: 10.1371/journal.pone.0097384.
YU Z B, ZHU Y, LI D, et al. Association between visit-to-visit variability of HbA(1c) and cognitive decline: a pooled analysis of two prospective population-based cohorts[J]. Diabetologia, 2020, 63(1): 85-94. DOI: 10.1007/s00125-019-04986-8.
BANCKS M P, CARNETHON M R, JACOBS D R, et al. Fasting Glucose Variability in Young Adulthood and Cognitive Function in Middle Age: The Coronary Artery Risk Development in Young Adults (CARDIA) Study[J]. Diabetes Care, 2018, 41(12): 2579-2585. DOI: 10.2337/dc18-1287.
RIZZO M R, MARFELLA R, BARBIERI M, et al. Relationships between daily acute glucose fluctuations and cognitive performance among aged type 2 diabetic patients[J]. Diabetes Care, 2010, 33(10): 2169-2174. DOI: 10.2337/dc10-0389.
ZHONG Y, ZHANG X Y, MIAO Y, et al. The relationship between glucose excursion and cognitive function in aged type 2 diabetes patients[J]. Biomed Environ Sci, 2012, 25(1): 1-7. DOI: 10.3967/0895-3988.2012.01.001.
TOUSOULIS D, KAMPOLI A M, TENTOLOURIS C, et al. The role of nitric oxide on endothelial function[J]. Curr Vasc Pharmacol, 2012, 10(1): 4-18. DOI: 10.2174/157016112798829760.
WEI X, SCHNEIDER J G, SHENOUDA S M, et al. De novo lipogenesis maintains vascular homeostasis through endothelial nitric-oxide synthase (eNOS) palmitoylation[J]. J Biol Chem, 2011, 286(4): 2933-2945. DOI: 10.1074/jbc.M110.193037.
EL-OSTA A, BRASACCHIO D, YAO D, et al. Transient high glucose causes persistent epigenetic changes and altered gene expression during subsequent normoglycemia[J]. J Exp Med, 2008, 205(10): 2409-2417. DOI: 10.1084/jem.20081188.
LI W, MALONEY R, AW T. High glucose, glucose fluctuation and carbonyl stress enhance brain microvascular endothelial barrier dysfunction: Implications for diabetic cerebral microvasculature[J]. Redox biology, 2015, 5: 80-90. DOI: 10.1016/j.redox.2015.03.005.
WANG H, DENG J, CHEN L, et al. Acute glucose fluctuation induces inflammation and neurons apoptosis in hippocampal tissues of diabetic rats[J]. J Cell Biochem, 2021, 122(9): 1239-1247. DOI: 10.1002/jcb.29523.
COSTANTINO S, PANENI F, BATTISTA R, et al. Impact of Glycemic Variability on Chromatin Remodeling, Oxidative Stress, and Endothelial Dysfunction in Patients With Type 2 Diabetes and With Target HbA Levels[J]. Diabetes, 2017, 66(9): 2472-2482. DOI: 10.2337/db17-0294.
OHARA M, NAGAIKE H, GOTO S, et al. Improvements of ambient hyperglycemia and glycemic variability are associated with reduction in oxidative stress for patients with type 2 diabetes[J]. Diabetes Res Clin Pract, 2018, 139: 253-261. DOI: 10.1016/j.diabres.2018.02.017.
HUANG Y, LIAO Z, LIN X, et al. Overexpression of miR-146a Might Regulate Polarization Transitions of BV-2 Cells Induced by High Glucose and Glucose Fluctuations[J/OL]. Front Endocrinol (Lausanne), 2019, 10: 719 [2023-02-06]. DOI: 10.3389/fendo.2019.00719.
YANG J, ZHAO Z, YUAN H, et al. The mechanisms of glycemic variability accelerate diabetic central neuropathy and diabetic peripheral neuropathy in diabetic rats[J]. Biochem Biophys Res Commun, 2019, 510(1): 35-41. DOI: 10.1016/j.bbrc.2018.12.179.
XIA W, LUO Y, CHEN Y C, et al. Glucose fluctuations are linked to disrupted brain functional architecture and cognitive impairment[J]. J Alzheimers Dis, 2020, 74(2): 603-613. DOI: 10.3233/JAD-191217.
WANG J, ZHOU S, DENG D, et al. Compensatory thalamocortical functional hyperconnectivity in type 2 Diabetes Mellitus[J]. Brain Imaging Behav, 2022, 16(6): 2556-2568. DOI: 10.1007/s11682-022-00710-0.
VAISHNAVI S N, VLASSENKO A G, RUNDLE M M, et al. Regional aerobic glycolysis in the human brain[J]. Proc Natl Acad Sci U S A, 2010, 107(41): 17757-17762. DOI: 10.1073/pnas.1010459107.
VELDHUIS J D, IRANMANESH A, LIZARRALDE G, et al. Amplitude modulation of a burstlike mode of cortisol secretion subserves the circadian glucocorticoid rhythm[J/OL]. Am J Physiol, 1989, 257(1Pt 1): E6-E14 [2023-02-06]. DOI: 10.1152/ajpendo.1989.257.1.E6.
SCHEEN A J, STURIS J, POLONSKY K S, et al. Alterations in the ultradian oscillations of insulin secretion and plasma glucose in aging[J]. Diabetologia, 1996, 39(5): 564-572. DOI: 10.1007/bf00403303.
HAJJAR I, ZHAO P, ALSOP D, et al. Association of blood pressure elevation and nocturnal dipping with brain atrophy, perfusion and functional measures in stroke and nonstroke individuals[J]. Am J Hypertens, 2010, 23(1): 17-23. DOI: 10.1038/ajh.2009.187.
KOLOPP M, BICAKOVA-ROCHER A, REINBERG A, et al. Ultradian, circadian and circannual rhythms of blood glucose and injected insulins documented in six self-controlled adult diabetics[J]. Chronobiol Int, 1986, 3(4): 265-280. DOI: 10.3109/07420528609079544.
CUI X, ABDULJALIL A, MANOR B D, et al. Multi-scale glycemic variability: a link to gray matter atrophy and cognitive decline in type 2 diabetes[J/OL]. PLoS One, 2014, 9(1): e86284 [2023-02-06]. DOI: 10.1371/journal.pone.0086284.
HUANG J, PENG X, FAN R, et al. Disruption of Circadian Clocks Promotes Progression of Alzheimer's Disease in Diabetic Mice[J]. Mol Neurobiol, 2021, 58(9): 4404-4412. DOI: 10.1007/s12035-021-02425-7.
XIONG Z, LI J, ZHONG X, et al. Visit-to-Visit Fasting Glucose Variability in Young Adulthood and Hippocampal Integrity and Volume at Midlife[J]. Diabetes Care, 2019, 42(12): 2334-2337. DOI: 10.2337/dc19-0834.
MINAMI T, ITO Y, YAMADA M, et al. The effect of long-term past glycemic control on executive function among patients with type 2 diabetes mellitus[J]. Diabetol Int, 2020, 11(2): 114-120. DOI: 10.1007/s13340-019-00411-y.
LEE J H, CHOI Y, JUN C, et al. Neurocognitive changes and their neural correlates in patients with type 2 diabetes mellitus[J]. Endocrinol Metab (Seoul), 2014, 29(2): 112-121. DOI: 10.3803/EnM.2014.29.2.112.
RAVONA-SPRINGER R, MOSHIER E, SCHMEIDLER J, et al. Changes in glycemic control are associated with changes in cognition in non-diabetic elderly[J]. J Alzheimers Dis, 2012, 30(2): 299-309. DOI: 10.3233/jad-2012-120106.
OGAMA N, SAKURAI T, KAWASHIMA S, et al. Postprandial Hyperglycemia Is Associated With White Matter Hyperintensity and Brain Atrophy in Older Patients With Type 2 Diabetes Mellitus[J]. Front Aging Neurosci, 2018, 10: 273. DOI: 10.3389/fnagi.2018.00273.
LIVNY A, RAVONA-SPRINGER R, HEYMANN A, et al. Long-term variability in glycemic control is associated with white matter hyperintensities in APOE4 genotype carriers with type 2 diabetes[J]. Diabetes Care, 2016, 39(6): 1056-9. DOI: 10.2337/dc15-2331.
KOUTSODENDRIS N, NELSON M R, RAO A, et al. Apolipoprotein E and Alzheimer's disease: findings, hypotheses, and potential mechanisms[J]. Annu Rev Pathol, 2022, 17: 73-99. DOI: 10.1146/annurev-pathmechdis-030421-112756.
KIM K J, LEE B W. The roles of glycated albumin as intermediate glycation index and pathogenic protein[J]. Diabetes Metab J, 2012, 36(2): 98-107. DOI: 10.4093/dmj.2012.36.2.98.
IBERG N, FLÜCKIGER R. Nonenzymatic glycosylation of albumin in vivo. Identification of multiple glycosylated sites[J]. J Biol Chem, 1986, 261(29): 13542-13545.
KOGA M. Glycated albumin; clinical usefulness[J]. Clin Chim Acta, 2014, 433: 96-104. DOI: 10.1016/j.cca.2014.03.001.
OGAWA A, HAYASHI A, KISHIHARA E, et al. New indices for predicting glycaemic variability[J/OL]. PloS One, 2012, 7(9): e46517 [2023-02-06]. DOI: 10.1371/journal.pone.0046517.
TAMURA Y, KIMBARA Y, YAMAOKA T, et al. White matter hyperintensity in elderly patients with diabetes mellitus is associated with cognitive impairment, functional disability, and a high glycoalbumin/glycohemoglobin ratio[J/OL]. Front Aging Neurosci, 2017, 9: 220 [2023-02-06]. DOI: 10.3389/fnagi.2017.00220.
OHARA T, FURUTA Y, HIRABAYASHI N, et al. Elevated serum glycated albumin and glycated albumin : hemoglobin a1c ratio were associated with hippocampal atrophy in a general elderly population of Japanese: The hisayama study[J]. J Diabetes Investig, 2020, 11(4): 971-979. DOI: 10.1111/jdi.13220.
DONG S, WANG L, ZHAO C, et al. Relationship between key continuous glucose monitoring-derived metrics and specific cognitive domains in patients with type 2 diabetes mellitus[J/OL]. BMC Neurol, 2023, 23(1): 200 [2023-02-06]. DOI: 10.1186/s12883-023-03242-2.

PREV Research progress of functional MRI-based neurovascular coupling in central nervous system diseases
NEXT Progresseson MRI characteristics of the effect of cerebral small vessel disease on cognitive function in patients with type 2 diabetes mellitus

Tel & Fax: +8610-67113815    E-mail: