Dataset Information

Longitudinal assessment of hippocampus structure in children with type 1 diabetes.

ABSTRACT: The extant literature finds that children with type 1 diabetes mellitus (T1D) experience mild cognitive alterations compared to healthy age-matched controls. The neural basis of these cognitive differences is unclear but may relate in part to the effects of dysglycemia on the developing brain. We investigated longitudinal changes in hippocampus volume in young children with early-onset T1D. Structural magnetic resonance imaging data were acquired from 142 children with T1D and 65 age-matched control subjects (4-10?years of age at study entry) at 2 time points, 18 months apart. The effects of diabetes and glycemic exposure on hippocampal volume and growth were examined. Results indicated that although longitudinal hippocampus growth did not differ between children with T1D and healthy control children, slower growth of the hippocampus was associated with both increased exposure to hyperglycemia (interval HbA1c) and greater glycemic variability (MAGE) in T1D. These observations indicate that the current practice of tolerating some hyperglycemia to minimize the risk of hypoglycemia in young children with T1D may not be optimal for the developing brain. Efforts that continue to assess the factors influencing neural and cognitive development in children with T1D will be critical in minimizing the deleterious effects of diabetes.

SUBMITTER: Foland-Ross LC

PROVIDER: S-EPMC6195484 | biostudies-literature | 2018 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Longitudinal assessment of hippocampus structure in children with type 1 diabetes.

Foland-Ross Lara C LC Reiss Allan L AL Mazaika Paul K PK Mauras Nelly N Weinzimer Stuart A SA Aye Tandy T Tansey Michael J MJ White Neil H NH

Pediatric diabetes 20180419

The extant literature finds that children with type 1 diabetes mellitus (T1D) experience mild cognitive alterations compared to healthy age-matched controls. The neural basis of these cognitive differences is unclear but may relate in part to the effects of dysglycemia on the developing brain. We investigated longitudinal changes in hippocampus volume in young children with early-onset T1D. Structural magnetic resonance imaging data were acquired from 142 children with T1D and 65 age-matched con ...[more]

PMID: 29675980

Similar Datasets

Project description:Immune analytes have been widely tested in efforts to understand the heterogeneity of disease progression, risk, and therapeutic responses in type 1 diabetes (T1D). The future clinical utility of such analytes as biomarkers depends on their technical and biological variability, as well as their correlation with clinical outcomes. To assess the variability of a panel of 91 immune analytes, we conducted a prospective study of adults with T1D (<3 years from diagnosis), at 9-10 visits over 1 year. Autoantibodies and frequencies of T-cell, natural killer cell, and myeloid subsets were evaluated; autoreactive T-cell frequencies and function were also measured. We calculated an intraclass correlation coefficient (ICC) for each marker, which is a relative measure of between- and within-subject variability. Of the 91 analytes tested, we identified 35 with high between- and low within-subject variability, indicating their potential ability to be used to stratify subjects. We also provide extensive data regarding technical variability for 64 of the 91 analytes. To pilot the concept that ICC can be used to identify analytes that reflect biological outcomes, the association between each immune analyte and C-peptide was also evaluated using partial least squares modeling. CD8 effector memory T-cell (CD8 EM) frequency exhibited a high ICC and a positive correlation with C-peptide, which was also seen in an independent dataset of recent-onset T1D subjects. More work is needed to better understand the mechanisms underlying this relationship. Here we find that there are a limited number of technically reproducible immune analytes that also have a high ICC. We propose the use of ICC to define within- and between-subject variability and measurement of technical variability for future biomarker identification studies. Employing such a method is critical for selection of analytes to be tested in the context of future clinical trials aiming to understand heterogeneity in disease progression and response to therapy.

Dataset Information

Longitudinal assessment of hippocampus structure in children with type 1 diabetes.

Publications

Longitudinal assessment of hippocampus structure in children with type 1 diabetes.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets