White matter microstructure alterations in type 2 diabetes mellitus and its correlation with cerebral small vessel disease and cognitive performance.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
02 Jan 2024
02 Jan 2024
Historique:
received:
28
02
2023
accepted:
25
12
2023
medline:
4
1
2024
pubmed:
4
1
2024
entrez:
3
1
2024
Statut:
epublish
Résumé
Microstructural abnormalities of white matter fiber tracts are considered as one of the etiology of diabetes-induced neurological disorders. We explored the cerebral white matter microstructure alteration accurately, and to analyze its correlation between cerebral small vessel disease (CSVD) burden and cognitive performance in type 2 diabetes mellitus (T2DM). The clinical-laboratory data, cognitive scores [including mini-mental state examination (MMSE), Montreal cognitive assessment (MoCA), California verbal learning test (CVLT), and symbol digit modalities test (SDMT)], CSVD burden scores of the T2DM group (n = 34) and healthy control (HC) group (n = 21) were collected prospectively. Automatic fiber quantification (AFQ) was applied to generate bundle profiles along primary white matter fiber tracts. Diffusion tensor images (DTI) metrics and 100 nodes of white matter fiber tracts between groups were compared. Multiple regression analysis was used to analyze the relationship between DTI metrics and cognitive scores and CSVD burden scores. For fiber-wise and node-wise, DTI metrics in some commissural and association fibers were increased in T2DM. Some white matter fiber tracts DTI metrics were independent predictors of cognitive scores and CSVD burden scores. White matter fiber tracts damage in patients with T2DM may be characterized in specific location, especially commissural and association fibers. Aberrational specific white matter fiber tracts are associated with visuospatial function and CSVD burden.
Identifiants
pubmed: 38167604
doi: 10.1038/s41598-023-50768-z
pii: 10.1038/s41598-023-50768-z
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
270Subventions
Organisme : National Natural Science Foundation of China
ID : 81801657
Organisme : National Natural Science Foundation of China
ID : 81671646
Informations de copyright
© 2024. The Author(s).
Références
Biessels, G. J., Strachan, M. W., Visseren, F. L., Kappelle, L. J. & Whitmer, R. A. Dementia and cognitive decline in type 2 diabetes and prediabetic stages: Towards targeted interventions. Lancet Diabetes Endocrinol. 2, 246–255. https://doi.org/10.1016/S2213-8587(13)70088-3 (2014).
doi: 10.1016/S2213-8587(13)70088-3
pubmed: 24622755
Biessels, G. J. & Reijmer, Y. D. Brain changes underlying cognitive dysfunction in diabetes: What can we learn from MRI?. Diabetes 63, 2244–2252. https://doi.org/10.2337/db14-0348 (2014).
doi: 10.2337/db14-0348
pubmed: 24931032
Chornenkyy, Y., Wang, W. X., Wei, A. & Nelson, P. T. Alzheimer’s disease and type 2 diabetes mellitus are distinct diseases with potential overlapping metabolic dysfunctionupstream of observed cognitive decline. Brain Pathol. 29, 3–17. https://doi.org/10.1111/bpa.12655 (2019).
doi: 10.1111/bpa.12655
pubmed: 30106209
Werhane, M. L. et al. Arterial stiffening moderates the relationship between type-2 diabetes mellitus and white matter hyperintensity burden in older adults with mild cognitive impairment. Front. Aging Neurosci. 13, 716638. https://doi.org/10.3389/fnagi.2021.716638 (2021).
doi: 10.3389/fnagi.2021.716638
pubmed: 34759811
pmcid: 8574966
Sanahuja, J. et al. Increased burden of cerebral small vessel disease in patients with type 2 diabetes and retinopathy. Diabetes Care 39, 1614–1620. https://doi.org/10.2337/dc15-2671 (2016).
doi: 10.2337/dc15-2671
pubmed: 27281772
Pantoni, L. Cerebral small vessel disease: From pathogenesis and clinical characteristics to therapeutic challenges. Lancet Neurol. 9, 689–701. https://doi.org/10.1016/S1474-4422(10)70104-6 (2010).
doi: 10.1016/S1474-4422(10)70104-6
pubmed: 20610345
Cannistraro, R. J. et al. CNS small vessel disease: A clinical review. Neurology 92, 1146–1156. https://doi.org/10.1212/WNL.0000000000007654 (2019).
doi: 10.1212/WNL.0000000000007654
pubmed: 31142635
pmcid: 6598791
Iadecola, C. The neurovascular unit coming of age: A journey through neurovascular coupling in health and disease. Neuron 96, 17–42. https://doi.org/10.1016/j.neuron.2017.07.030 (2017).
doi: 10.1016/j.neuron.2017.07.030
pubmed: 28957666
pmcid: 5657612
Fang, F. et al. The silent occurrence of cerebral small vessel disease in nonelderly patients with type 2 diabetes mellitus. J. Diabetes 13, 735–743. https://doi.org/10.1111/1753-0407.13164 (2021).
doi: 10.1111/1753-0407.13164
pubmed: 33559402
Teng, Z. et al. Cerebral small vessel disease is associated with mild cognitive impairment in type 2 diabetes mellitus. Diabetes Metab. Syndr. Obes. 15, 1985–1994. https://doi.org/10.2147/DMSO.S368725 (2022).
doi: 10.2147/DMSO.S368725
pubmed: 35814027
pmcid: 9259063
van Sloten, T. T., Sedaghat, S., Carnethon, M. R., Launer, L. J. & Stehouwer, C. D. A. Cerebral microvascular complications of type 2 diabetes: Stroke, cognitive dysfunction, and depression. Lancet Diabetes Endocrinol. 8, 325–336. https://doi.org/10.1016/S2213-8587(19)30405-X (2020).
doi: 10.1016/S2213-8587(19)30405-X
pubmed: 32135131
Duering, M. et al. Neuroimaging standards for research into small vessel disease-advances since 2013. Lancet Neurol. 22, 602–618. https://doi.org/10.1016/S1474-4422(23)00131-X (2023).
doi: 10.1016/S1474-4422(23)00131-X
pubmed: 37236211
Xiong, Y. et al. Brain microstructural alterations in type 2 diabetes: Diffusion kurtosis imaging provides added value to diffusion tensor imaging. Eur. Radiol. 29, 1997–2008. https://doi.org/10.1007/s00330-018-5746-y (2019).
doi: 10.1007/s00330-018-5746-y
pubmed: 30338363
Cui, Y. et al. Disturbed interhemispheric functional and structural connectivity in type 2 diabetes. J. Magn. Reson. Imaging 55, 424–434. https://doi.org/10.1002/jmri.27813 (2022).
doi: 10.1002/jmri.27813
pubmed: 34184359
Huang, L. et al. Abnormalities of brain white matter in type 2 diabetes mellitus: A meta-analysis of diffusion tensor imaging. Front. Aging Neurosci. 13, 693890. https://doi.org/10.3389/fnagi.2021.693890 (2021).
doi: 10.3389/fnagi.2021.693890
pubmed: 34421572
pmcid: 8378805
Andica, C. et al. White matter fiber-specific degeneration in older adults with metabolic syndrome. Mol. Metab. 62, 101527. https://doi.org/10.1016/j.molmet.2022.101527 (2022).
doi: 10.1016/j.molmet.2022.101527
pubmed: 35691528
pmcid: 9234232
Quan, M. et al. Effects of gene mutation and disease progression on representative neural circuits in familial Alzheimer’s disease. Alzheimer’s Res. Ther. 12, 14. https://doi.org/10.1186/s13195-019-0572-2 (2020).
doi: 10.1186/s13195-019-0572-2
Jing, J. et al. Reduced white matter microstructural integrity in prediabetes and diabetes: A population-based study. EBioMedicine 82, 104144. https://doi.org/10.1016/j.ebiom.2022.104144 (2022).
doi: 10.1016/j.ebiom.2022.104144
pubmed: 35810560
pmcid: 9278067
Yeatman, J. D., Dougherty, R. F., Myall, N. J., Wandell, B. A. & Feldman, H. M. Tract profiles of white matter properties: Automating fiber-tract quantification. PLoS One 7, e49790. https://doi.org/10.1371/journal.pone.0049790 (2012).
doi: 10.1371/journal.pone.0049790
pubmed: 23166771
pmcid: 3498174
Zhang, X. et al. Characterization of white matter changes along fibers by automated fiber quantification in the early stages of Alzheimer’s disease. Neuroimage Clin. 22, 101723. https://doi.org/10.1016/j.nicl.2019.101723 (2019).
doi: 10.1016/j.nicl.2019.101723
pubmed: 30798166
pmcid: 6384328
Kreilkamp, B. A. K. et al. Comparison of manual and automated fiber quantification tractography in patients with temporal lobe epilepsy. Neuroimage Clin. 24, 102024. https://doi.org/10.1016/j.nicl.2019.102024 (2019).
doi: 10.1016/j.nicl.2019.102024
pubmed: 31670154
pmcid: 6831895
Deng, F. et al. Abnormal segments of right uncinate fasciculus and left anterior thalamic radiation in major and bipolar depression. Prog. Neuropsychopharmacol. Biol. Psychiatry 81, 340–349. https://doi.org/10.1016/j.pnpbp.2017.09.006 (2018).
doi: 10.1016/j.pnpbp.2017.09.006
pubmed: 28912043
Cai, W. et al. Right arcuate fasciculus and superior longitudinal fasciculus abnormalities in primary insomnia. Brain Imaging Behav. 13, 1746–1755. https://doi.org/10.1007/s11682-019-00160-1 (2019).
doi: 10.1007/s11682-019-00160-1
pubmed: 31327125
Jiang, Y. et al. Segmental abnormalities of white matter microstructure in end-stage renal disease patients: An automated fiber quantification tractography study. Front. Neurosci. 15, 765677. https://doi.org/10.3389/fnins.2021.765677 (2021).
doi: 10.3389/fnins.2021.765677
pubmed: 34938154
pmcid: 8685541
American Diabetes, A. Diagnosis and classification of diabetes mellitus. DiabetesCare. 37(Suppl 1), S81-90. https://doi.org/10.2337/dc14-S081 (2014).
doi: 10.2337/dc14-S081
Somers, M. et al. On the relationship between degree of hand-preference and degree of language lateralization. Brain Lang. 144, 10–15. https://doi.org/10.1016/j.bandl.2015.03.006 (2015).
doi: 10.1016/j.bandl.2015.03.006
pubmed: 25880901
Jia, J. et al. Association between healthy lifestyle and memory decline in older adults: 10 year, population based, prospective cohort study. BMJ 380, e072691. https://doi.org/10.1136/bmj-2022-072691 (2023).
doi: 10.1136/bmj-2022-072691
pubmed: 36696990
pmcid: 9872850
Harwood, R. H. et al. Promoting activity, independence, and stability in early dementia and mild cognitive impairment (PrAISED): Randomised controlled trial. BMJ 382, e074787. https://doi.org/10.1136/bmj-2023-074787 (2023).
doi: 10.1136/bmj-2023-074787
pubmed: 37643788
pmcid: 10463053
Siru, R. et al. Cognitive impairment in people with diabetes-related foot ulceration. J. Clin. Med. https://doi.org/10.3390/jcm10132808 (2021).
doi: 10.3390/jcm10132808
pubmed: 34202360
pmcid: 8268193
Aslaksen, P. M., Bystad, M. K., Ørbo, M. C. & Vangberg, T. R. The relation of hippocampal subfield volumes to verbal episodic memory measured by the California Verbal Learning test II in healthy adults. Behav. Brain Res. 351, 131–137. https://doi.org/10.1016/j.bbr.2018.06.008 (2018).
doi: 10.1016/j.bbr.2018.06.008
pubmed: 29890200
Collyer, T. A. et al. Association of dual decline in cognition and gait speed with risk of dementia in older adults. JAMA Netw. Open 5, e2214647. https://doi.org/10.1001/jamanetworkopen.2022.14647 (2022).
doi: 10.1001/jamanetworkopen.2022.14647
pubmed: 35639376
pmcid: 9157262
Huang, H. et al. White matter characteristics of damage along fiber tracts in patients with type 2 diabetes mellitus. Clin. Neuroradiol. 33, 327–341. https://doi.org/10.1007/s00062-022-01213-7 (2022).
doi: 10.1007/s00062-022-01213-7
pubmed: 36112176
pmcid: 10220145
Ma, T. et al. Gray and white matter abnormality in patients with T2DM-related cognitive dysfunction: A systemic review and meta-analysis. Nutr. Diabetes 12, 39. https://doi.org/10.1038/s41387-022-00214-2 (2022).
doi: 10.1038/s41387-022-00214-2
pubmed: 35970833
pmcid: 9378704
Zhou, C. et al. Altered white matter microstructures in type 2 diabetes mellitus: A coordinate-based meta-analysis of diffusion tensor imaging studies. Front. Endocrinol. 12, 658198. https://doi.org/10.3389/fendo.2021.658198 (2021).
doi: 10.3389/fendo.2021.658198
Banfi, C. et al. White matter alterations and tract lateralization in children with dyslexia and isolated spelling deficits. Hum. Brain Mapp. 40, 65–776. https://doi.org/10.1002/hbm.24410 (2019).
doi: 10.1002/hbm.24410
Scheffels, J. F. et al. The influence of age, gender and education on neuropsychological test scores: Updated clinical norms for five widely used cognitive assessments. J. Clin. Med. https://doi.org/10.3390/jcm12165170 (2023).
doi: 10.3390/jcm12165170
pubmed: 37629212
pmcid: 10455991
de Groot, M. et al. Tract-specific white matter degeneration in aging: The rotterdam study. Alzheimers Dement. 11, 321–330. https://doi.org/10.1016/j.jalz.2014.06.011 (2015).
doi: 10.1016/j.jalz.2014.06.011
pubmed: 25217294
Luo, W. et al. Alterations of cerebral blood flow and its connectivity in olfactory-related brain regions of type 2 diabetes mellitus patients. Front. Neurosci. 16, 904468. https://doi.org/10.3389/fnins.2022.904468 (2022).
doi: 10.3389/fnins.2022.904468
pubmed: 35898415
pmcid: 9309479
Sun, L. et al. Risk factors for cognitive impairment in patients with type 2 diabetes. J. Diabetes Res. 2020, 4591938. https://doi.org/10.1155/2020/4591938 (2020).
doi: 10.1155/2020/4591938
pubmed: 32377520
pmcid: 7196145
Sun, J. et al. The mechanisms of type 2 diabetes-related white matter intensities: A review. Front. Public Health 8, 498056. https://doi.org/10.3389/fpubh.2020.498056 (2020).
doi: 10.3389/fpubh.2020.498056
pubmed: 33282807
pmcid: 7705244
Alotaibi, A. et al. Investigating brain microstructural alterations in type 1 and type 2 diabetes using diffusion tensor imaging: A systematic review. Brain Sci. https://doi.org/10.3390/brainsci11020140 (2021).
doi: 10.3390/brainsci11020140
pubmed: 34827465
pmcid: 8615713
Wang, J. et al. Tractography in type 2 diabetes mellitus with subjective memory complaints: A diffusion tensor imaging study. Front. Neurosci. 15, 800420. https://doi.org/10.3389/fnins.2021.800420 (2022).
doi: 10.3389/fnins.2021.800420
pubmed: 35462734
pmcid: 9019711
Whittaker, H. T. et al. T1, diffusion tensor, and quantitative magnetization transfer imaging of the hippocampus in an Alzheimer’s disease mouse model. Magn. Reson. Imaging 50, 26–37. https://doi.org/10.1016/j.mri.2018.03.010 (2018).
doi: 10.1016/j.mri.2018.03.010
pubmed: 29545212
pmcid: 6461204
Figley, C. R. et al. Potential pitfalls of using fractional anisotropy, axial diffusivity, and radial diffusivity as biomarkers of cerebral white matter microstructure. Front. Neurosci. 15, 799576. https://doi.org/10.3389/fnins.2021.799576 (2022).
doi: 10.3389/fnins.2021.799576
pubmed: 35095400
pmcid: 8795606
Reijmer, Y. D. et al. Microstructural white matter abnormalities and cognitive functioning in type 2 diabetes: A diffusion tensor imaging study. Diabetes Care 36, 137–144. https://doi.org/10.2337/dc12-0493 (2012).
doi: 10.2337/dc12-0493
pubmed: 22961577
pmcid: 3526236
Xie, Y. et al. White matter microstructural abnormalities in type 2 diabetes mellitus: A diffusional kurtosis imaging analysis. AJNR Am. J. Neuroradiol. 38, 617–625. https://doi.org/10.3174/ajnr.A5042 (2017).
doi: 10.3174/ajnr.A5042
pubmed: 27979796
pmcid: 7959974
van Bloemendaal, L. et al. Alterations in white matter volume and integrity in obesity and type 2 diabetes. Metab. Brain Dis. 31, 621–629. https://doi.org/10.1007/s11011-016-9792-3 (2016).
doi: 10.1007/s11011-016-9792-3
pubmed: 26815786
pmcid: 4863900
Liu, J., Zhu, J., Yuan, F., Zhang, X. & Zhang, Q. Abnormal brain white matter in patients with right trigeminal neuralgia: A diffusion tensor imaging study. J. Headache Pain 19, 46. https://doi.org/10.1186/s10194-018-0871-1 (2018).
doi: 10.1186/s10194-018-0871-1
pubmed: 29931400
pmcid: 6013416
Li, M. et al. Changes in the structure, perfusion, and function of the hippocampus in type 2 diabetes mellitus. Front. Neurosci. 16, 1070911. https://doi.org/10.3389/fnins.2022.1070911 (2023).
doi: 10.3389/fnins.2022.1070911
pubmed: 36699515
pmcid: 9868830
Palejwala, A. H. et al. Anatomy and white matter connections of the lateral occipital cortex. Surg. Radiol. Anat. 42, 315–328. https://doi.org/10.1007/s00276-019-02371-z (2020).
doi: 10.1007/s00276-019-02371-z
pubmed: 31734739
Takeuchi, H. & Kawashima, R. Effects of diastolic blood pressure on brain structures and cognitive functions in middle and old ages: Longitudinal analyses. Nutrients https://doi.org/10.3390/nu14122464 (2022).
doi: 10.3390/nu14122464
pubmed: 36364932
pmcid: 9656760
Jin, Y. et al. 3D tract-specific local and global analysis of white matter integrity in Alzheimer’s disease. Hum. Brain Mapp. 38, 1191–1207. https://doi.org/10.1002/hbm.23448 (2017).
doi: 10.1002/hbm.23448
pubmed: 27883250
Chen, H. F. et al. Microstructural disruption of the right inferior fronto-occipital and inferior longitudinal fasciculus contributes to WMH-related cognitive impairment. CNS Neurosci. Ther. 26, 576–588. https://doi.org/10.1111/cns.13283 (2020).
doi: 10.1111/cns.13283
pubmed: 31901155
pmcid: 7163793
Gao, S. et al. White matter microstructural change contributes to worse cognitive function in patients with type 2 diabetes. Diabetes 68, 2085–2094. https://doi.org/10.2337/db19-0233 (2019).
doi: 10.2337/db19-0233
pubmed: 31439643
pmcid: 6804632
Guzzardi, M. A., La Rosa, F. & Iozzo, P. Trust the gut: Outcomes of gut microbiota transplant in metabolic and cognitive disorders. Neurosci. Biobehav. R. 149, 105143. https://doi.org/10.1016/j.neubiorev.2023.105143 (2023).
doi: 10.1016/j.neubiorev.2023.105143
Barbiellini Amidei, C. et al. Association between age at diabetes onset and subsequent risk of dementia. JAMA-J. Am. Med. Assoc. 325, 1640–1649. https://doi.org/10.1001/jama.2021.4001 (2021).
doi: 10.1001/jama.2021.4001
Efremova, E., Shutov, A. & Skorodumova, E. Factors of adherence to lifestyle modification in older patients with cardiovascular comorbidity. Eur. Heart J. https://doi.org/10.1093/eurheartj/ehab724.2356 (2021).
doi: 10.1093/eurheartj/ehab724.2356
Hayden, K. et al. Legacy of a 10-year multidomain lifestyle intervention on the cognitive trajectories of overweight and obese individuals with type 2 diabetes mellitus. Alzheimers Dement. https://doi.org/10.1002/alz.039108 (2020).
doi: 10.1002/alz.039108
pubmed: 32966694
pmcid: 7920533
Chen, X. et al. Association of type 2 diabetes mellitus with cognitive function in adults: A prospective cohort study. J. Alzheimers Dis. 93, 1509–1520. https://doi.org/10.3233/JAD-220822 (2023).
doi: 10.3233/JAD-220822
pubmed: 37212092
Sun, F., Huang, Y., Wang, J., Hong, W. & Zhao, Z. Research progress in diffusion spectrum imaging. Brain Sci. https://doi.org/10.3390/brainsci13101497 (2023).
doi: 10.3390/brainsci13101497
pubmed: 38137099
pmcid: 10742209
Juvekar, P., Szczepankiewicz, F., Noh, T. & Golby, A. NIMG-16. Exploratory evaluation of Q-space trajectory imaging parameters as novel imaging biomarkers for gliomas. Neuro-Oncology 22, ii150–ii150. https://doi.org/10.1093/neuonc/noaa215.629 (2020).
doi: 10.1093/neuonc/noaa215.629
pmcid: 7651348
Schilling, K. G. et al. Functional tractography of white matter by high angular resolution functional-correlation imaging (HARFI). Magnet Reson Med. 81, 2011–2024. https://doi.org/10.1002/mrm.27512 (2018).
doi: 10.1002/mrm.27512
Mishra, V., Ritter, A., Cordes, D. & Caldwell, F. Diffusion kurtosis imaging suggests sex‐specific alteration of white matter in mild cognitively impaired participants. Alzheimers Dement. https://doi.org/10.1002/alz.046130 (2020).
doi: 10.1002/alz.046130