JANUARY 2014

In This Issue of Diabetes Edited by Helaine E. Resnick, PhD, MPH

Marzelli et al. Neuroanatomical correlates of dysglycemia in young children with type 1 diabetes. Diabetes 2014;63:343–353

Sagittal (left) and axial (right) three-dimensional renderings of clusters of signifi cant differences between T1D and control (Con) subjects.

Ye et al. The association between circulating lipoprotein(a) and type 2 diabetes: Is it causal? Diabetes 2014;63:332–342

Type 1 Diabetes Affects Brain Development in Young ChildrenNew work in this issue of Diabetes emphasizes the unfavorable impact of type 1 diabetes (T1D) on both brain volume and cognition in young children. Because early childhood is an important period for brain development, the effects of glucose dysregulation in T1D may result in signifi cant physiological complications as well as cognitive defi cits, especially when T1D appears early. While previous research indicates that young brains are vulnerable to T1D, most studies related to the effects of T1D on brain structure have been conducted in adults and older children. New work by Marzelli et al. (p. 343) investigated the neuroanatomical correlates of dysglycemia in children with early-onset T1D. Using identical scanners, structural MRI images of the brain were obtained from 142 children with T1D and 68 age-matched control subjects. The average age of these participants was 7.0 years with an average age of T1D onset of 4.1 years of age. Voxel-based morphometry was used to examine correlations between regional brain volumes and measures of glycemic exposure as well as regional differences between groups. The children with T1D showed decreased gray matter volume (GMV) in the bilateral occipital and cerebellar regions as well as hyperglycemic exposure–related GMV decreases in the medial frontal and temporal-occipital regions. The T1D group also had increased GMV in the left inferior prefrontal, insula, and temporal pole regions, and glycemic exposure in this group was associated with increased GMV in the lateral prefrontal regions. Although there was a signifi cant positive correlation between GMV and intelligence quotient (IQ) in the medial prefrontal lobe and cerebellum-occipital regions of the children in the control group, this relationship was absent in children with T1D. The connection between differences in GMV and IQ in these young T1D children is suggestive of an adverse impact of early-onset T1D on cognitive function. While a longitudinal analysis of this cohort will help provide a more complete and temporally oriented picture of the effects of T1D on the developing brain, fi ndings from the new study suggest that early-onset T1D affects regions of the brain that are linked to standard cognitive development. — Laura Gehl, PhD

Lipoprotein(a) Is Not Causally Linked to Type 2 DiabetesIn this issue of Diabetes, Ye et al. (p. 332) present fi ndings from a cohort of 18,490 adults suggesting that lipoprotein(a) [Lp(a)] is not causally linked to type 2 diabetes (T2D). In the new study, incident cases of diabetes were ascertained over an average of 10 years using self-report, general practice diabetes registers, and both hospital and mortality data. After excluding participants with prevalent diabetes, 593 incident diabetes cases were identifi ed among the 17,908 participants who were free of diabetes at baseline. Prospective analyses indicated a strong inverse association between baseline Lp(a) levels and incident T2D. However, Mendelian randomization analysis did not show an association between genetically elevated Lp(a) levels and reduced risk of T2D, indicating that a causal relationship does not exist between Lp(a) levels and T2D. Using the same method, the investigators also analyzed coronary heart disease (CHD) data from the same cohort to compare baseline Lp(a) levels with CHD and T2D end points. Unlike the fi ndings for T2D, the investigators found a direct positive association between Lp(a) levels and CHD, results that are in agreement with a large body of literature. However, although the investigators pointed out that methodological issues such as survivor bias and residual confounding could be potential explanations for the divergent results, there was no evidence that reverse association bias explained their fi ndings. Together, these data suggest that elevated Lp(a) levels are not causally associated with a lower risk of T2D, despite a strong inverse association between Lp(a) levels and new-onset T2D. — Laura Gehl, PhD

Diabetes Volume 63, January 2014 1

JANUARY 2014

Zhao et al. Short leukocyte telomere length predicts risk of diabetes in American Indians: the Strong Heart Family Study. Diabetes 2014;63:354–362

Nathan et al. Relationship of glycated albumin to blood glucose and HbA1c values and to retinopathy, nephropathy, and cardiovascular outcomes in the DCCT/EDIC study. Diabetes 2014;63:282–290

Shorter Telomeres Linked to Higher Risk of Type 2 DiabetesData from Zhao et al. (p. 354) in this issue suggest that shorter telomere length may predict type 2 diabetes (T2D) in American Indians. Although telomere shortening has been linked to a number of age-related disorders, the new report offers the fi rst prospective evidence supporting an independent association between leukocyte telomere length (LTL) and future diabetes risk. With genomic DNA isolated from peripheral blood samples, baseline LTL was measured as the ratio of telomeric product/single copy gene using PCR. This information was examined in relation to 5-year diabetes risk in 2,328 nondiabetic American Indians aged 14–93 years who were enrolled in the Strong Heart Family Study. At 5 years, roughly 12% of the cohort had developed T2D, and the risk of diabetes among individuals in the lowest LTL quartile (i.e., shortest LTL values) was almost double that of subjects in the highest LTL quartile. The data suggested a threshold pattern with respect to diabetes risk because neither the second nor the third quartiles of LTL differed from the fourth. Thus, all the excess LTL-associated diabetes risk was concentrated in the fi rst LTL quartile. The association between low LTL values and diabetes risk persisted through several sensitivity and subgroup analyses as well as adjustment for potential confounders. The new fi ndings suggest that LTL may be a useful biomarker of diabetes risk in American Indians and may pave the way for broader testing of this association in other ethnic groups. — Wendy Chou, PhD

Complex Interplay Among Various Glycemic Indices and Risk of Complications New work by Nathan et al. (p. 282) in this issue of Diabetes assesses how well long-term, intermediate-term, and acute measures of glycemia predict the risk for microvascular complications and cardiovascular disease (CVD) in type 1 diabetic patients. Using a case-cohort design, the new report focuses on various measures of glycemia in relation to retinopathy, nephropathy, and CVD in the Diabetes Control and Complications Trial (DCCT)/Epidemiology of Diabetes Interventions and Complications (EDIC) cohort. The investigators analyzed longitudinal data collected annually for glycated hemoglobin (HbA1c), glycated albumin (GA), and mean blood glucose (MBG) (estimated from a seven-point profi le). These variables were examined individually and in combination in proportional hazards models that were modifi ed for use with case-cohort data. HbA1c and GA each signifi cantly predicted retinopathy outcomes, and the relationship was strengthened when both were considered together. For nephropathy, the combination of HbA1c with GA did not strengthen the model fi t, but these indices predicted risk when individually examined. In contrast, GA was not a signifi cant predictor of CVD outcomes—alone or in combination. For all models, MBG was not a signifi cant predictor of any outcomes when glycation products were also considered. The new fi ndings shed light on the complex interrelationships among various glycemic indices and their differential impact on the prediction of small and large vessel complications. — Wendy Chou, PhD

DOI: 10.2337/db14-ti01

© 2014 by the American Diabetes Association. See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.

Diabetes Volume 63, January 20142