Literature DB >> 25904692

White matter hyperintensities in middle-aged adults with childhood-onset type 1 diabetes.

Karen A Nunley1, Christopher M Ryan1, Trevor J Orchard1, Howard J Aizenstein1, J Richard Jennings1, John Ryan1, Janice C Zgibor1, Robert M Boudreau1, Tina Costacou1, John D Maynard1, Rachel G Miller1, Caterina Rosano2.   

Abstract

OBJECTIVE: Although microvascular complications are common in type 1 diabetes mellitus (T1DM), few studies have quantified the severity, risk factors, and implications of cerebral microvascular damage in these patients. As life expectancy in patients with T1DM increases, patients are exposed to age- and disease-related factors that may contribute to cerebral microvascular disease.
METHODS: Severity and volume of white matter hyperintensities (WMH) and infarcts were quantified in 97 middle-aged patients with childhood-onset T1DM (mean age and duration: 50 and 41 years, respectively) and 81 non-T1DM adults (mean age: 48 years), concurrent with cognitive and health-related measures.
RESULTS: Compared with non-T1DM participants, patients had more severe WMH (Fazekas scores 2 and 3 compared with Fazekas score 1, p < 0.0001) and slower information processing (digit symbol substitution, number correct: 65.7 ± 10.9 and 54.9 ± 13.6; pegboard, seconds: 66.0 ± 9.9 and 88.5 ± 34.2; both p < 0.0001) independent of age, education, or other factors. WMH were associated with slower information processing; adjusting for WMH attenuated the group differences in processing speed (13% for digit symbol, 11% for pegboard, both p ≤ 0.05). Among patients, prevalent neuropathies and smoking tripled the odds of high WMH burden, independent of age or disease duration. Associations between measures of blood pressure or hyperglycemia and WMH were not significant.
CONCLUSIONS: Clinically relevant WMH are evident earlier among middle-aged patients with childhood-onset T1DM and are related to the slower information processing frequently observed in T1DM. Brain imaging in patients with T1DM who have cognitive difficulties, especially those with neuropathies, may help uncover cerebral microvascular damage. Longitudinal studies are warranted to fully characterize WMH development, risk factors, and long-term effects on cognition.
© 2015 American Academy of Neurology.

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Year:  2015        PMID: 25904692      PMCID: PMC4442104          DOI: 10.1212/WNL.0000000000001582

Source DB:  PubMed          Journal:  Neurology        ISSN: 0028-3878            Impact factor:   9.910


  38 in total

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Journal:  Diabetes       Date:  2006-06       Impact factor: 9.461

2.  Long-term survival in adults 65 years and older with white matter hyperintensity: association with performance on the digit symbol substitution test.

Authors:  Caterina Rosano; Yue-Fang Chang; Lewis H Kuller; Jack M Guralnik; Stephanie A Studenski; Howard J Aizenstein; Peter J Gianaros; Oscar L Lopez; William T Longstreth; Anne B Newman
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3.  The cognitive correlates of white matter abnormalities in normal aging: a quantitative review.

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4.  Proliferative retinopathy: absence of white matter lesions at MR imaging.

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5.  Prevalence of cerebral white matter lesions in elderly people: a population based magnetic resonance imaging study. The Rotterdam Scan Study.

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6.  Incidence, manifestations, and predictors of worsening white matter on serial cranial magnetic resonance imaging in the elderly: the Cardiovascular Health Study.

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7.  Mortality trends in type 1 diabetes. The Allegheny County (Pennsylvania) Registry 1965-1999.

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8.  Evidence for diabetic encephalopathy.

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9.  Increasing incidence of type 1 diabetes in youth: twenty years of the Philadelphia Pediatric Diabetes Registry.

Authors:  Terri H Lipman; Lorraine E Levitt Katz; Sarah J Ratcliffe; Kathryn M Murphy; Alexandra Aguilar; Iraj Rezvani; Carol J Howe; Shruti Fadia; Elizabeth Suarez
Journal:  Diabetes Care       Date:  2013-01-22       Impact factor: 19.112

10.  White Matter Lesion Assessment in Patients with Cognitive Impairment and Healthy Controls: Reliability Comparisons between Visual Rating, a Manual, and an Automatic Volumetrical MRI Method-The Gothenburg MCI Study.

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  24 in total

1.  Brain changes in T1DM--a microvascular complication?

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Journal:  Nat Rev Endocrinol       Date:  2015-06-09       Impact factor: 43.330

2.  A Diffusion Tensor Imaging Study on White Matter Abnormalities in Patients with Type 2 Diabetes Using Tract-Based Spatial Statistics.

Authors:  Y Xiong; Y Sui; Z Xu; Q Zhang; M M Karaman; K Cai; T M Anderson; W Zhu; J Wang; X J Zhou
Journal:  AJNR Am J Neuroradiol       Date:  2016-03-17       Impact factor: 3.825

3.  Regional Gray Matter Volumes as Related to Psychomotor Slowing in Adults with Type 1 Diabetes.

Authors:  Karen A Nunley; Christopher M Ryan; Howard J Aizenstein; J Richard Jennings; Rebecca L MacCloud; Trevor J Orchard; Caterina Rosano
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4.  Altered Brain Dynamics in Patients With Type 1 Diabetes During Working Memory Processing.

Authors:  Christine M Embury; Alex I Wiesman; Amy L Proskovec; Elizabeth Heinrichs-Graham; Timothy J McDermott; Grace H Lord; Kaitlin L Brau; Andjela T Drincic; Cyrus V Desouza; Tony W Wilson
Journal:  Diabetes       Date:  2018-03-12       Impact factor: 9.461

5.  Glycemic Variability and Brain Glucose Levels in Type 1 Diabetes.

Authors:  Janice J Hwang; Lihong Jiang; Elizabeth Sanchez Rangel; Xiaoning Fan; Yuyan Ding; Wai Lam; Jessica Leventhal; Feng Dai; Douglas L Rothman; Graeme F Mason; Robert S Sherwin
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6.  Neural correlates of slower gait in middle-aged persons with childhood-onset type 1 diabetes mellitus: The impact of accelerated brain aging.

Authors:  Sarah K Royse; Tina Costacou; Karen A Nunley; Trevor J Orchard; Caterina Rosano
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7.  Hypoglycemia unawareness in type 1 diabetes suppresses brain responses to hypoglycemia.

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Journal:  J Neural Transm (Vienna)       Date:  2017-08-01       Impact factor: 3.575

9.  Physical activity and hippocampal volume in middle-aged patients with type 1 diabetes.

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Journal:  Neurology       Date:  2017-03-10       Impact factor: 9.910

10.  Moderation of the effect of glycemia on the risk of cardiovascular disease in type 1 diabetes: The DCCT/EDIC study.

Authors:  Ionut Bebu; Barbara H Braffett; Trevor J Orchard; Gayle M Lorenzi; David M Nathan; William H Herman; John M Lachin
Journal:  Diabetes Res Clin Pract       Date:  2020-12-10       Impact factor: 5.602

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