Neuroanatomical correlates of dysglycemia in young children with type 1 diabetes

Matthew J Marzelli, Paul K Mazaika, Naama Barnea-Goraly, Tamara Hershey, Eva Tsalikian, William Tamborlane, Nelly Mauras, Neil H White, Bruce Buckingham, Roy W Beck, Katrina J Ruedy, Craig Kollman, Peiyao Cheng, Allan L Reiss, Diabetes Research in Children Network (DirecNet), Eva Tsalikian, Michael J Tansey, Julie Coffey, Joanne Cabbage, Sara Salamati, Nelly Mauras, Larry A Fox, M Allison Cato, Kim Englert, Kaitlin Sikes, Tina Ewen, Bruce A Buckingham, Darrell M Wilson, Tandy Aye, Kimberly Caswell, Stuart A Weinzimer, William V Tamborlane, Amy Steffen, Kate Weyman, Melinda Zgorski, Neil H White, Ana Maria Arbelaez, Lucy Levandoski, Angie Starnes, Tamara Hershey, Roy W Beck, Katrina J Ruedy, Craig Kollman, Peiyao Cheng, Beth Stevens, Allan L Reiss, Naama Barnea-Goraly, Matthew J Marzelli, Paul M Mazaika, Tamara Hershey, Colleen Considine, Aiden Bondurant, Michaela Cuneo, Emily Bihun, Sarah June Grafeman, Matthew J Marzelli, Paul K Mazaika, Naama Barnea-Goraly, Tamara Hershey, Eva Tsalikian, William Tamborlane, Nelly Mauras, Neil H White, Bruce Buckingham, Roy W Beck, Katrina J Ruedy, Craig Kollman, Peiyao Cheng, Allan L Reiss, Diabetes Research in Children Network (DirecNet), Eva Tsalikian, Michael J Tansey, Julie Coffey, Joanne Cabbage, Sara Salamati, Nelly Mauras, Larry A Fox, M Allison Cato, Kim Englert, Kaitlin Sikes, Tina Ewen, Bruce A Buckingham, Darrell M Wilson, Tandy Aye, Kimberly Caswell, Stuart A Weinzimer, William V Tamborlane, Amy Steffen, Kate Weyman, Melinda Zgorski, Neil H White, Ana Maria Arbelaez, Lucy Levandoski, Angie Starnes, Tamara Hershey, Roy W Beck, Katrina J Ruedy, Craig Kollman, Peiyao Cheng, Beth Stevens, Allan L Reiss, Naama Barnea-Goraly, Matthew J Marzelli, Paul M Mazaika, Tamara Hershey, Colleen Considine, Aiden Bondurant, Michaela Cuneo, Emily Bihun, Sarah June Grafeman

Abstract

Studies of brain structure in type 1 diabetes (T1D) describe widespread neuroanatomical differences related to exposure to glycemic dysregulation in adults and adolescents. In this study, we investigate the neuroanatomical correlates of dysglycemia in very young children with early-onset T1D. Structural magnetic resonance images of the brain were acquired in 142 children with T1D and 68 age-matched control subjects (mean age 7.0 ± 1.7 years) on six identical scanners. Whole-brain volumetric analyses were conducted using voxel-based morphometry to detect regional differences between groups and to investigate correlations between regional brain volumes and measures of glycemic exposure (including data from continuous glucose monitoring). Relative to control subjects, the T1D group displayed decreased gray matter volume (GMV) in bilateral occipital and cerebellar regions (P < 0.001) and increased GMV in the left inferior prefrontal, insula, and temporal pole regions (P = 0.002). Within the T1D group, hyperglycemic exposure was associated with decreased GMV in medial frontal and temporal-occipital regions and increased GMV in lateral prefrontal regions. Cognitive correlations of intelligence quotient to GMV were found in cerebellar-occipital regions and medial prefrontal cortex for control subjects, as expected, but not for the T1D group. Thus, early-onset T1D affects regions of the brain that are associated with typical cognitive development.

Figures

Figure 1
Figure 1
Sagittal (left) and axial (right) three-dimensional renderings of clusters of significant differences between T1D and control subjects. Increased GMV in lateral temporo-frontal regions in T1D relative to control subjects (red cluster, P < 0.01) was also found to be associated with higher HbA1cDX. Decreased GMV in occipital regions and cerebellum in T1D relative to control subjects (yellow cluster, P < 0.001) was found to be associated with higher HbA1cAUC6% and higher mean glucose.
Figure 2
Figure 2
Significant GMV clusters from whole-brain regression analysis of glycemic measures in the T1D group (height threshold of T = 1.66, cluster extent threshold of P < 0.05, and corrected for FWE and nonstationary smoothness). Clusters are overlaid on the average GM template. HbA1cAUC6% (−) (P < 0.001), T1D duration (−, GMV) (P = 0.001), T1D duration (−, WMV) (P < 0.001), HbA1cDX (+) (P = 0.01), mean BG (−) (P = 0.007), and mean BG (+) (P = 0.03).
Figure 3
Figure 3
Regions with significant correlations between IQ and GMV. Top: Clusters from whole-brain regression analysis of IQ in the control group (height threshold of T = 1.66, cluster extent threshold of P < 0.05, and corrected for FWE and nonstationary smoothness). Bottom: Conjunction regions with IQ-GMV correlations in control subjects and glycemic-GMV correlations in T1D. Color denotes glycemic variable/contrast: T1D duration (−) (blue), mean glucose (−) (green), control >T1D (red), overlap (yellow). Clusters are overlaid on the average GM template.

References

    1. Boulton AJM, Vinik AI, Arezzo JC, et al. American Diabetes Association Diabetic neuropathies: a statement by the American Diabetes Association. Diabetes Care 2005;28:956–962
    1. Brands AMA, Biessels GJ, de Haan EHF, Kappelle LJ, Kessels RPC. The effects of type 1 diabetes on cognitive performance: a meta-analysis. Diabetes Care 2005;28:726–735
    1. Grey M, Whittemore R, Tamborlane W. Depression in type 1 diabetes in children: natural history and correlates. J Psychosom Res 2002;53:907–911
    1. Giedd JN, Snell JW, Lange N, et al. Quantitative magnetic resonance imaging of human brain development: ages 4-18. Cereb Cortex 1996;6:551–560
    1. King GL, Loeken MR. Hyperglycemia-induced oxidative stress in diabetic complications. Histochem Cell Biol 2004;122:333–338
    1. Fort PE, Losiewicz MK, Reiter CEN, et al. Differential roles of hyperglycemia and hypoinsulinemia in diabetes induced retinal cell death: evidence for retinal insulin resistance. PLoS ONE 2011;6:e26498.
    1. Hayashi T, Faustman DL. Role of defective apoptosis in type 1 diabetes and other autoimmune diseases. Recent Prog Horm Res 2003;58:131–153
    1. Auer RN, Siesjö BK. Hypoglycaemia: brain neurochemistry and neuropathology. Baillieres Clin Endocrinol Metab 1993;7:611–625
    1. Araki Y, Nomura M, Tanaka H, et al. MRI of the brain in diabetes mellitus. Neuroradiology 1994;36:101–103
    1. Ferguson SC, Blane A, Wardlaw J, et al. Influence of an early-onset age of type 1 diabetes on cerebral structure and cognitive function. Diabetes Care 2005;28:1431–1437
    1. van Elderen SGC, Brandts A, van der Grond J, et al. Cerebral perfusion and aortic stiffness are independent predictors of white matter brain atrophy in type 1 diabetic patients assessed with magnetic resonance imaging. Diabetes Care 2011;34:459–463
    1. Musen G, Lyoo IK, Sparks CR, et al. Effects of type 1 diabetes on gray matter density as measured by voxel-based morphometry. Diabetes 2006;55:326–333
    1. Wessels AM, Simsek S, Remijnse PL, et al. Voxel-based morphometry demonstrates reduced grey matter density on brain MRI in patients with diabetic retinopathy. Diabetologia 2006;49:2474–2480
    1. Perantie DC, Koller JM, Weaver PM, et al. Prospectively determined impact of type 1 diabetes on brain volume during development. Diabetes 2011;60:3006–3014
    1. Hershey T, Perantie DC, Wu J, Weaver PM, Black KJ, White NH. Hippocampal volumes in youth with type 1 diabetes. Diabetes 2010;59:236–241
    1. Perantie DC, Wu J, Koller JM, et al. Regional brain volume differences associated with hyperglycemia and severe hypoglycemia in youth with type 1 diabetes. Diabetes Care 2007;30:2331–2337
    1. Aye T, Reiss AL, Kesler S, et al. The feasibility of detecting neuropsychologic and neuroanatomic effects of type 1 diabetes in young children. Diabetes Care 2011;34:1458–1462
    1. Wechsler D. Wechsler Abbreviated Scale of Intelligence (WASI). San Antonio, TX, The Psychological Corporation, 1999
    1. Wechsler D. Wechsler Preschool Primary Scale of Intelligence-Third Edition (WPPSI-III) San Antonio, TX, The Psychological Corporation, 2002
    1. Wechsler D. Wechsler Intelligence Scale for Children-Fourth Edition (WISC-IV) San Antonio, TX, The Psychological Corporation, 2003
    1. Kovatchev BP, Otto E, Cox D, Gonder-Frederick L, Clarke W. Evaluation of a new measure of blood glucose variability in diabetes. Diabetes Care 2006;29:2433–2438
    1. Jack CR, Jr, Bernstein MA, Fox NC, et al. The Alzheimer’s Disease Neuroimaging Initiative (ADNI): MRI methods. J Magn Reson Imaging 2008;27:685–691
    1. Talairach J, Tournoux P. Co-Planar Stereotaxic Atlas of the Human Brain: 3-Dimensional Proportional System: An Approach to Cerebral Imaging. New York, Thieme Medical Publishers, 1988
    1. Ashburner J, Friston KJ. Unified segmentation. Neuroimage 2005;26:839–851
    1. Zhang Y, Brady M, Smith S. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm. IEEE Trans Med Imaging 2001;20:45–57
    1. Ashburner J. A fast diffeomorphic image registration algorithm. Neuroimage 2007;38:95–113
    1. Worsley KJ, Andermann M, Koulis T, MacDonald D, Evans AC. Detecting changes in nonisotropic images. Hum Brain Mapp 1999;8:98–101
    1. Stonnington CM, Tan G, Klöppel S, et al. Interpreting scan data acquired from multiple scanners: a study with Alzheimer’s disease. Neuroimage 2008;39:1180–1185
    1. Franc DT, Kodl CT, Mueller BA, Muetzel RL, Lim KO, Seaquist ER. High connectivity between reduced cortical thickness and disrupted white matter tracts in long-standing type 1 diabetes. Diabetes 2011;60:315–319
    1. Tiemeier H, Lenroot RK, Greenstein DK, Tran L, Pierson R, Giedd JN. Cerebellum development during childhood and adolescence: a longitudinal morphometric MRI study. Neuroimage 2010;49:63–70
    1. Paulin MG. The role of the cerebellum in motor control and perception. Brain Behav Evol 1993;41:39–50
    1. Stoodley CJ, Schmahmann JD. Functional topography in the human cerebellum: a meta-analysis of neuroimaging studies. Neuroimage 2009;44:489–501
    1. Taki Y, Hashizume H, Sassa Y, et al. Correlation among body height, intelligence, and brain gray matter volume in healthy children. Neuroimage 2012;59:1023–1027
    1. Lenroot RK, Giedd JN. Brain development in children and adolescents: insights from anatomical magnetic resonance imaging. Neurosci Biobehav Rev 2006;30:718–729
    1. Shaw P, Greenstein D, Lerch J, et al. Intellectual ability and cortical development in children and adolescents. Nature 2006;440:676–679
    1. Bondy CA, Cheng CM. Signaling by insulin-like growth factor 1 in brain. Eur J Pharmacol 2004;490:25–31
    1. Wang W-T, Lee P, Yeh H-W, Smirnova IV, Choi I-Y. Effects of acute and chronic hyperglycemia on the neurochemical profiles in the rat brain with streptozotocin-induced diabetes detected using in vivo ¹H MR spectroscopy at 9.4 T. J Neurochem 2012;121:407–417
    1. Hansen SH. The role of taurine in diabetes and the development of diabetic complications. Diabetes Metab Res Rev 2001;17:330–346
    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. 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. Antenor-Dorsey JA, Meyer E, Rutlin J, et al. White matter microstructural integrity in youth with type 1 diabetes. Diabetes 2013;62:581–589
    1. Miyake A, Friedman NP, Emerson MJ, Witzki AH, Howerter A, Wager TD. The unity and diversity of executive functions and their contributions to complex “frontal lobe” tasks: a latent variable analysis. Cognit Psychol 2000;41:49–100
    1. Craig AD. How do you feel? Interoception: the sense of the physiological condition of the body. Nat Rev Neurosci 2002;3:655–666
    1. Binder JR, Frost JA, Hammeke TA, et al. Human temporal lobe activation by speech and nonspeech sounds. Cereb Cortex 2000;10:512–528
    1. Fang F, Lue L-F, Yan S, et al. RAGE-dependent signaling in microglia contributes to neuroinflammation, Abeta accumulation, and impaired learning/memory in a mouse model of Alzheimer’s disease. FASEB J 2010;24:1043–1055

Source: PubMed

Sponsor e collaboratori

Condizioni mediche

Interventi farmacologici

3
Sottoscrivi