Share:
Share this content in WeChat
X
Original Article
Functional connectivity of the cerebellar Crus Ⅰ in type 2 diabetes mellitus:A resting-state functional MRI study
TIAN Jing  ZHAO Lianping  LIU Ruifang  LU Yashan  HUANG Gang  GONG Rui  LIANG Fengli  GAO Yanyan  ZHANG Wenwen 

Cite this article as: Tian J, Zhao LP, Liu RF, et al. Functional connectivity of the cerebellar Crus Ⅰ in type 2 diabetes mellitus: A resting-state functional MRI study[J]. Chin J Magn Reson Imaging, 2022, 13(5): 64-69. DOI:10.12015/issn.1674-8034.2022.05.012.


[Abstract] Objective To investigate the alteration of functional connectivity (FC) between cerebellar Crus Ⅰ and the whole-brain in patients with type 2 diabetes mellitus (T2DM) using resting-state functional MRI (rs-fMRI).Materials and Methods Seventy-eight T2DM patients and fifty-seven healthy subjects (HCs) matched in gender, age and years of education were prospectively collected pertaining to clinical data, neuropsychological test and rs-fMRI data. Seed-based FC analysis was calculated using bilateral cerebellar Crus Ⅰa and Crus Ⅰb as seed points. The differences of cerebellar FC values, clinical variables, differences in test scores and correlations between the two groups were statistically analyzed.Results Compared with the HCs, T2DM had presented higher scores of Beck Depression Self-assessment Questionnaire, Beck Anxiety Scale, and lower scores of Montreal Cognitive Assessment (P<0.05); the FC between the left cerebellar Crus Ⅰa and left lingual gyrus/cerebellum Ⅳ-Ⅴ was decreased, and the FC between the right cerebellar Crus Ⅰb and right inferior frontal gyrus was increased (GRF correction, voxel-P<0.005, cluster-P<0.05), and the latter was positively correlated with low density lipoprotein (r=0.30, P=0.01).Conclusions The abnormal FC values of cerebellar subregions may be involved in the neuropathology of T2DM cognitive and mood dysfunction.
[Keywords] diabetes mellitus, type 2;resting-state functional magnetic resonance imaging;cerebellum;brain damage, chronic;cognitive dysfunction;mood disorders;functional connectivity

TIAN Jing1   ZHAO Lianping1, 2*   LIU Ruifang1   LU Yashan2   HUANG Gang1, 2   GONG Rui3   LIANG Fengli2   GAO Yanyan2   ZHANG Wenwen2  

1 First Clinical Medical College of Gansu University of Chinese Medicine (Gansu Provincial Hospital), Lanzhou 730000, China

2 Department of Radiology, Gansu Provincial Hospital, Lanzhou 730000, China

3 Cadre Endocrinology Department, Gansu Provincial Hospital, Lanzhou 730000, China

Zhao LP, E-mail: lianping_zhao007@163.com

Conflicts of interest   None.

Received  2021-10-23
Accepted  2022-04-13
DOI: 10.12015/issn.1674-8034.2022.05.012
Cite this article as: Tian J, Zhao LP, Liu RF, et al. Functional connectivity of the cerebellar Crus Ⅰ in type 2 diabetes mellitus: A resting-state functional MRI study[J]. Chin J Magn Reson Imaging, 2022, 13(5): 64-69.DOI:10.12015/issn.1674-8034.2022.05.012

[1]
Liu S, Lu Y, Cai X, et al. Glycemic control is related to cognitive dysfunction in elderly people with type 2 diabetes mellitus in a rural chinese population[J]. Curr Alzheimer Res, 2019, 16(10): 950-962. DOI: 10.2174/1567205016666191023110712.
[2]
Guo D, Yuan Y, Huang R, et al. Association between plasma adipsin level and mild cognitive impairment in chinese patients with type 2 diabetes: A cross-sectional study[J]. BMC Endocr Disord, 2019, 19(1): 108. DOI: 10.1186/s12902-019-0431-y.
[3]
Ma S, Li S, Lv R, et al. Prevalence of mild cognitive impairment in type 2 diabetes mellitus is associated with serum galectin-3 level[J]. J Diabetes Investig, 2020, 11(5): 1295-1302. DOI: 10.1111/jdi.13256.
[4]
Saeedi P, Petersohn I, Salpea P, et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the international diabetes federation diabetes atlas, 9(th) edition[J]. Diabetes Res Clin Pract, 2019, 157: 107843. DOI: 10.1016/j.diabres.2019.107843.
[5]
Zhao LP, Liu RF, Lu YS, et al. Resting-State Hippocampal Functional Connectivity in Patients with Type 2 Diabetes Mellitus[J]. Chin J Med Imaging, 2020, 28(7): 482-487. DOI: 10.3969/j.issn.1005-5185.2020.07.001.
[6]
Olivito G, Lupo M, Iacobacci C, et al. Structural cerebellar correlates of cognitive functions in spinocerebellar ataxia type 2[J]. J Neurol, 2018, 265(3): 597-606. DOI: 10.1007/s00415-018-8738-6.
[7]
Batsikadze G, Diekmann N, Ernst TM, et al. The cerebellum contributes to context-effects during fear extinction learning: A 7t fmri study[J]. Neuroimage, 2022, 253: 119080. DOI: 10.1016/j.neuroimage.2022.119080.
[8]
Luo X, Chen G, Jia Y, et al. Disrupted cerebellar connectivity with the central executive network and the default-mode network in unmedicated bipolar ii disorder[J]. Front Psychiatry, 2018, 9: 705. DOI: 10.3389/fpsyt.2018.00705.
[9]
Liu RF, Tian J, Zhao LP, et al. Resting-State Cerebellar Functional Connectivity in Patients with Type 2 Diabetes Mellitus[J]. Chin J Med Imaging, 2021, 29(10): 974-979. DOI: 10.3969/j.issn.1005-5185.2021.10.004.
[10]
Gagnepain P, Hulbert J, Anderson MC. Parallel regulation of memory and emotion supports the suppression of intrusive memories[J]. J Neurosci, 2017, 37(27): 6423-6441. DOI: 10.1523/jneurosci.2732-16.2017.
[11]
Alalade E, Denny K, Potter G, et al. Altered cerebellar-cerebral functional connectivity in geriatric depression[J]. PLoS One, 2011, 6(5): e20035. DOI: 10.1371/journal.pone.0020035.
[12]
Guo W, Liu F, Xue Z, et al. Abnormal resting-state cerebellar-cerebral functional connectivity in treatment-resistant depression and treatment sensitive depression[J]. Prog Neuropsychopharmacol Biol Psychiatry, 2013, 44: 51-57. DOI: 10.1016/j.pnpbp.2013.01.010.
[13]
Huang H, Wang HL, Zhou Y, et al. Aberrant functional connectivity within and across the default mode, central-executive, and salience network in patients with schizophrenia: a resting-state functional magnetic resonance imaging study[J]. Chin J Psychiatry, 2015, 48(3): 175-181. DOI: 10.3760/cma.j.issn.1006-7884.2015.03.016.
[14]
Anderson JS, Ferguson MA, Lopez-Larson M, et al. Reproducibility of single-subject functional connectivity measurements[J]. AJNR Am J Neuroradiol, 2011, 32(3): 548-555. DOI: 10.3174/ajnr.A2330.
[15]
Birn RM, Molloy EK, Patriat R, et al. The effect of scan length on the reliability of resting-state fmri connectivity estimates[J]. Neuroimage, 2013, 83: 550-558. DOI: 10.1016/j.neuroimage.2013.05.099.
[16]
Roy B, Ehlert L, Mullur R, et al. Regional brain gray matter changes in patients with type 2 diabetes mellitus[J]. Sci Rep, 2020, 10(1): 9925. DOI: 10.1038/s41598-020-67022-5.
[17]
Buckner RL, Sepulcre J, Talukdar T, et al. Cortical hubs revealed by intrinsic functional connectivity: Mapping, assessment of stability, and relation to alzheimer's disease[J]. J Neurosci, 2009, 29(6): 1860-1873. DOI: 10.1523/jneurosci.5062-08.2009.
[18]
Qi D, Wang A, Chen Y, et al. Default mode network connectivity and related white matter disruption in type 2 diabetes mellitus patients concurrent with amnestic mild cognitive impairment[J]. Curr Alzheimer Res, 2017, 14(11): 1238-1246. DOI: 10.2174/1567205014666170417113441.
[19]
Zhang D, Qi F, Gao J, et al. Altered cerebellar-cerebral circuits in patients with type 2 diabetes mellitus[J]. Front Neurosci, 2020, 14: 571210. DOI: 10.3389/fnins.2020.571210.
[20]
Stange JP, Bessette KL, Jenkins LM, et al. Attenuated intrinsic connectivity within cognitive control network among individuals with remitted depression: Temporal stability and association with negative cognitive styles[J]. Hum Brain Mapp, 2017, 38(6): 2939-2954. DOI: 10.1002/hbm.23564.
[21]
Zhen D, Xia W, Yi ZQ, et al. Alterations of brain local functional connectivity in amnestic mild cognitive impairment[J]. Transl Neurodegener, 2018, 7: 26. DOI: 10.1186/s40035-018-0134-8.
[22]
Cui Y, Jiao Y, Chen YC, et al. Altered spontaneous brain activity in type 2 diabetes: A resting-state functional mri study[J]. Diabetes, 2014, 63(2): 749-760. DOI: 10.2337/db13-0519.
[23]
Zhang D, Gao J, Yan X, et al. Altered functional connectivity of brain regions based on a meta-analysis in patients with t2dm: A resting-state fmri study[J]. Brain Behav, 2020, 10(8): e01725. DOI: 10.1002/brb3.1725.
[24]
Cui Y, Li S F, Gu H, et al. Disrupted brain connectivity patterns in patients with type 2 diabetes[J]. AJNR Am J Neuroradiol, 2016, 37(11): 2115-2122. DOI: 10.3174/ajnr.A4858.
[25]
Zhao LP, Wang Y, Huang L. Advances in cerebellar imaging studies of mood disorders[J]. Chin J Psychiatry, 2015, 48(5): 303-306. DOI: 10.3760/cma.j.issn.1006-7884.2015.05.009.
[26]
Liu P, Vandemeer MRJ, Joanisse MF, et al. Depressogenic self-schemas are associated with smaller regional grey matter volume in never-depressed preadolescents[J]. Neuroimage Clin, 2020, 28: 102422. DOI: 10.1016/j.nicl.2020.102422.
[27]
Vijayakumar N, Cheng TW, Pfeifer JH. Neural correlates of social exclusion across ages: A coordinate-based meta-analysis of functional mri studies[J]. Neuroimage, 2017, 153: 359-368. DOI: 10.1016/j.neuroimage.2017.02.050.
[28]
Quah SKL, McIver L, Roberts AC, et al. Trait anxiety mediated by amygdala serotonin transporter in the common marmoset[J]. J Neurosci, 2020, 40(24): 4739-4749. DOI: 10.1523/jneurosci.2930-19.2020.
[29]
He Z, Lin Y, Xia L, et al. Critical role of the right vlpfc in emotional regulation of social exclusion: A tdcs study[J]. Soc Cogn Affect Neurosci, 2018, 13(4): 357-366. DOI: 10.1093/scan/nsy026.
[30]
Fang P, An J, Tan X, et al. Changes in the cerebellar and cerebro-cerebellar circuit in type 2 diabetes[J]. Brain Res Bull, 2017, 130: 95-100. DOI: 10.1016/j.brainresbull.2017.01.009.
[31]
Salmi J, Pallesen KJ, Neuvonen T, et al. Cognitive and motor loops of the human cerebro-cerebellar system[J]. J Cogn Neurosci, 2010, 22(11): 2663-2676. DOI: 10.1162/jocn.2009.21382.
[32]
Qin C, Liang Y, Tan X, et al. Altered whole-brain functional topological organization and cognitive function in type 2 diabetes mellitus patients[J]. Front Neurol, 2019, 10: 599. DOI: 10.3389/fneur.2019.00599.
[33]
Lo JC, Ljubicic S, Leibiger B, et al. Adipsin is an adipokine that improves β cell function in diabetes[J]. Cell, 2014, 158(1): 41-53. DOI: 10.1016/j.cell.2014.06.005.

PREV Value of T2WI-FS radiomics combined with imaging features in predicting the efficacy of HIFU ablation of hysteromyoma
NEXT Analysis of local efficiency and node local efficiency changes in patients with type 2 diabetes based on graph theory
  



Tel & Fax: +8610-67113815    E-mail: editor@cjmri.cn