Alterations in white matter structure in young children with type 1 diabetes

Naama Barnea-Goraly, Mira Raman, Paul Mazaika, Matthew Marzelli, Tamara Hershey, Stuart A Weinzimer, Tandy Aye, Bruce Buckingham, Nelly Mauras, Neil H White, Larry A Fox, Michael Tansey, Roy W Beck, Katrina J Ruedy, Craig Kollman, Peiyao Cheng, Allan L Reiss, Diabetes Research in Children Network (DirecNet), Naama Barnea-Goraly, Mira Raman, Paul Mazaika, Matthew Marzelli, Tamara Hershey, Stuart A Weinzimer, Tandy Aye, Bruce Buckingham, Nelly Mauras, Neil H White, Larry A Fox, Michael Tansey, Roy W Beck, Katrina J Ruedy, Craig Kollman, Peiyao Cheng, Allan L Reiss, Diabetes Research in Children Network (DirecNet)

Abstract

Objective: To investigate whether type 1 diabetes affects white matter (WM) structure in a large sample of young children.

Research design and methods: Children (ages 4 to <10 years) with type 1 diabetes (n = 127) and age-matched nondiabetic control subjects (n = 67) had diffusion weighted magnetic resonance imaging scans in this multisite neuroimaging study. Participants with type 1 diabetes were assessed for HbA1c history and lifetime adverse events, and glucose levels were monitored using a continuous glucose monitor (CGM) device and standardized measures of cognition.

Results: Between-group analysis showed that children with type 1 diabetes had significantly reduced axial diffusivity (AD) in widespread brain regions compared with control subjects. Within the type 1 diabetes group, earlier onset of diabetes was associated with increased radial diffusivity (RD) and longer duration was associated with reduced AD, reduced RD, and increased fractional anisotropy (FA). In addition, HbA1c values were significantly negatively associated with FA values and were positively associated with RD values in widespread brain regions. Significant associations of AD, RD, and FA were found for CGM measures of hyperglycemia and glucose variability but not for hypoglycemia. Finally, we observed a significant association between WM structure and cognitive ability in children with type 1 diabetes but not in control subjects.

Conclusions: These results suggest vulnerability of the developing brain in young children to effects of type 1 diabetes associated with chronic hyperglycemia and glucose variability.

Figures

Figure 1
Figure 1
WM regions of significantly reduced AD values in the type 1 diabetes group compared with the control group (shown in yellow). Results are overlaid on an average FA image generated from the full sample.
Figure 2
Figure 2
A post hoc graphic representation of the association between FA (A) and RD (B) values with gluSD (FA: R = −0.41, P < 0.001; RD: R = 0.39, P < 0.001). (A high-quality color representation of this figure is available in the online issue.)
Figure 3
Figure 3
A post hoc graphic representation of the association between FA values and FSIQ scores in type 1 diabetes (R = 0.4, P < 0.001). Mean FA values were extracted from regions of significant correlations between FA and FSIQ in the type 1 diabetes group. (A high-quality color representation of this figure is available in the online issue.)

References

    1. Mauras N, Beck R, Xing D, et al. Diabetes Research in Children Network (DirecNet) Study Group A randomized clinical trial to assess the efficacy and safety of real-time continuous glucose monitoring in the management of type 1 diabetes in young children aged 4 to <10 years. Diabetes Care 2012;35:204–210
    1. Yang C, DeVisser A, Martinez JA, et al. Differential impact of diabetes and hypertension in the brain: adverse effects in white matter. Neurobiol Dis 2011;42:446–458
    1. Hernández-Fonseca JP, Rincón J, Pedreañez A, et al. Structural and ultrastructural analysis of cerebral cortex, cerebellum, and hypothalamus from diabetic rats. Exp Diabetes Res 20092009:329632
    1. Malone JI, Hanna SK, Saporta S. Hyperglycemic brain injury in the rat. Brain Res 2006;1076:9–15
    1. Malone JI, Hanna S, Saporta S, et al. Hyperglycemia not hypoglycemia alters neuronal dendrites and impairs spatial memory. Pediatr Diabetes 2008;9:531–539
    1. Yakovlev PI, Lecours AR. Regional Development of the Brain in Early Life. Boston, MA, Blackwell Scientific Publications, 1967
    1. Rovet JF, Ehrlich RM, Czuchta D. Intellectual characteristics of diabetic children at diagnosis and one year later. J Pediatr Psychol 1990;15:775–788
    1. Pierpaoli C, Jezzard P, Basser PJ, Barnett A, Di Chiro G. Diffusion tensor MR imaging of the human brain. Radiology 1996;201:637–648
    1. Pierpaoli C, Basser PJ. Toward a quantitative assessment of diffusion anisotropy. Magn Reson Med 1996;36:893–906
    1. Sen PN, Basser PJ. A model for diffusion in white matter in the brain. Biophys J 2005;89:2927–2938
    1. Kinoshita Y, Ohnishi A, Kohshi K, Yokota A. Apparent diffusion coefficient on rat brain and nerves intoxicated with methylmercury. Environ Res 1999;80:348–354
    1. Qiu D, Tan L-H, Zhou K, Khong P-L. Diffusion tensor imaging of normal white matter maturation from late childhood to young adulthood: voxel-wise evaluation of mean diffusivity, fractional anisotropy, radial and axial diffusivities, and correlation with reading development. Neuroimage 2008;41:223–232
    1. Chen C-I, Mar S, Brown S, Song S-K, Benzinger TLS. Neuropathologic correlates for diffusion tensor imaging in postinfectious encephalopathy. Pediatr Neurol 2011;44:389–393
    1. Song S-K, Sun S-W, Ramsbottom MJ, Chang C, Russell J, Cross AH. Dysmyelination revealed through MRI as increased radial (but unchanged axial) diffusion of water. Neuroimage 2002;17:1429–1436
    1. Hoeft F, Barnea-Goraly N, Haas BW, et al. More is not always better: increased fractional anisotropy of superior longitudinal fasciculus associated with poor visuospatial abilities in Williams syndrome. J Neurosci 2007;27:11960–11965
    1. Antenor-Dorsey JAV, Meyer E, Rutlin J, et al. White matter microstructural integrity in youth with type 1 diabetes. Diabetes 2013;62:581–589
    1. van Duinkerken E, Schoonheim MM, Ijzerman RG, et al. Diffusion tensor imaging in type 1 diabetes: decreased white matter integrity relates to cognitive functions. Diabetologia 2012;55:1218–1220
    1. Aye T, Barnea-Goraly N, Ambler C, et al. White matter structural differences in young children with type 1 diabetes: a diffusion tensor imaging study. Diabetes Care 2012;35:2167–2173
    1. Kodl CT, Franc DT, Rao JP, et al. Diffusion tensor imaging identifies deficits in white matter microstructure in subjects with type 1 diabetes that correlate with reduced neurocognitive function. Diabetes 2008;57:3083–3089
    1. Wilson DM, Xing D, Beck RW, et al. Juvenile Diabetes Research Foundation Continuous Glucose Monitoring Study Group Hemoglobin A1c and mean glucose in patients with type 1 diabetes: analysis of data from the Juvenile Diabetes Research Foundation continuous glucose monitoring randomized trial. Diabetes Care 2011;34:540–544
    1. Marzelli MJ, Mazaika PK, Barnea-Goraly N, et al. Neuroanatomical correlates of dysglycemia in young children with type 1 diabetes. Diabetes 2014;63:343–353
    1. Service FJ, Molnar GD, Rosevear JW, Ackerman E, Gatewood LC, Taylor WF. Mean amplitude of glycemic excursions, a measure of diabetic instability. Diabetes 1970;19:644–655
    1. Vollmar C, O’Muircheartaigh J, Barker GJ, et al. Identical, but not the same: intra-site and inter-site reproducibility of fractional anisotropy measures on two 3.0T scanners. Neuroimage 2010;51:1384–1394
    1. Hershey T, Cato A, Bondurant A, et al. Cognitive and behavioral differences in young children with type 1 diabetes mellitus: preliminary results (Abstract). Diabetes 2012;61(Suppl. 1):A53
    1. Smith SM, Jenkinson M, Johansen-Berg H, et al. Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 2006;31:1487–1505
    1. Nichols TE, Holmes AP. Nonparametric permutation tests for functional neuroimaging: a primer with examples. Hum Brain Mapp 2002;15:1–25
    1. Muftuler LT, Davis EP, Buss C, et al. Development of white matter pathways in typically developing preadolescent children. Brain Res 2012;1466:33–43
    1. Barnea-Goraly N, Menon V, Eckert M, et al. White matter development during childhood and adolescence: a cross-sectional diffusion tensor imaging study. Cereb Cortex 2005;15:1848–1854
    1. Kumar R, Nguyen HD, Macey PM, Woo MA, Harper RM. Regional brain axial and radial diffusivity changes during development. J Neurosci Res 2012;90:346–355
    1. Song S-K, Sun S-W, Ju W-K, Lin S-J, Cross AH, Neufeld AH. Diffusion tensor imaging detects and differentiates axon and myelin degeneration in mouse optic nerve after retinal ischemia. Neuroimage 2003;20:1714–1722
    1. Cai XJ, Xu HQ, Lu Y. C-peptide and diabetic encephalopathy. Chin Med Sci J 2011;26:119–125
    1. Friedrich MJ. Insulin effects weigh heavy on the brain. JAMA 2006;296:1717–1718
    1. Holmes CS, Richman LC. Cognitive profiles of children with insulin-dependent diabetes. J Dev Behav Pediatr 1985;6:323–326
    1. Hershey T, Craft S, Bhargava N, White NH. Memory and insulin dependent diabetes mellitus (IDDM): effects of childhood onset and severe hypoglycemia. J Int Neuropsychol Soc 1997;3:509–520
    1. Reichard P, Pihl M, Rosenqvist U, Sule J. Complications in IDDM are caused by elevated blood glucose level: the Stockholm Diabetes Intervention Study (SDIS) at 10-year follow up. Diabetologia 1996;39:1483–1488
    1. Lin A, Northam EA, Rankins D, Werther GA, Cameron FJ. Neuropsychological profiles of young people with type 1 diabetes 12 yr after disease onset. Pediatr Diabetes 2010;11:235–243
    1. Northam EA, Anderson PJ, Jacobs R, Hughes M, Warne GL, Werther GA. Neuropsychological profiles of children with type 1 diabetes 6 years after disease onset. Diabetes Care 2001;24:1541–1546
    1. Desrocher M, Rovet J. Neurocognitive correlates of type 1 diabetes mellitus in childhood. Child Neuropsychol 2004;10:36–52
    1. Toth C, Martinez J, Zochodne DW. RAGE, diabetes, and the nervous system. Curr Mol Med 2007;7:766–776
    1. Toth C, Schmidt AM, Tuor UI, et al. Diabetes, leukoencephalopathy and rage. Neurobiol Dis 2006;23:445–461
    1. Sugimoto K, Yasujima M, Yagihashi S. Role of advanced glycation end products in diabetic neuropathy. Curr Pharm Des 2008;14:953–961
    1. Ryle C, Leow CK, Donaghy M. Nonenzymatic glycation of peripheral and central nervous system proteins in experimental diabetes mellitus. Muscle Nerve 1997;20:577–584
    1. Pekiner C, Cullum NA, Hughes JN, et al. Glycation of brain actin in experimental diabetes. J Neurochem 1993;61:436–442
    1. Vlassara H, Brownlee M, Cerami A. Accumulation of diabetic rat peripheral nerve myelin by macrophages increases with the presence of advanced glycosylation endproducts. J Exp Med 1984;160:197–207
    1. Vlassara H, Brownlee M, Cerami A. Recognition and uptake of human diabetic peripheral nerve myelin by macrophages. Diabetes 1985;34:553–557
    1. Monnier L, Mas E, Ginet C, et al. Activation of oxidative stress by acute glucose fluctuations compared with sustained chronic hyperglycemia in patients with type 2 diabetes. JAMA 2006;295:1681–1687

Source: PubMed

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