Multi-scale glycemic variability: a link to gray matter atrophy and cognitive decline in type 2 diabetes.
OBJECTIVE
Type 2 diabetes mellitus (DM) accelerates brain aging and cognitive decline. Complex interactions between hyperglycemia, glycemic variability and brain aging remain unresolved. This study investigated the relationship between glycemic variability at multiple time scales, brain volumes and cognition in type 2 DM.


METHODS
Forty-three older adults with and 26 without type 2 DM completed 72-hour continuous glucose monitoring, cognitive tests and anatomical MRI. We described a new analysis of continuous glucose monitoring, termed Multi-Scale glycemic variability (Multi-Scale GV), to examine glycemic variability at multiple time scales. Specifically, Ensemble Empirical Mode Decomposition was used to identify five unique ultradian glycemic variability cycles (GVC1-5) that modulate serum glucose with periods ranging from 0.5-12 hrs.


RESULTS
Type 2 DM subjects demonstrated greater variability in GVC3-5 (period 2.0-12 hrs) than controls (P<0.0001), during the day as well as during the night. Multi-Scale GV was related to conventional markers of glycemic variability (e.g. standard deviation and mean glycemic excursions), but demonstrated greater sensitivity and specificity to conventional markers, and was associated with worse long-term glycemic control (e.g. fasting glucose and HbA1c). Across all subjects, those with greater glycemic variability within higher frequency cycles (GVC1-3; 0.5-2.0 hrs) had less gray matter within the limbic system and temporo-parietal lobes (e.g. cingulum, insular, hippocampus), and exhibited worse cognitive performance. Specifically within those with type 2 DM, greater glycemic variability in GVC2-3 was associated with worse learning and memory scores. Greater variability in GVC5 was associated with longer DM duration and more depression. These relationships were independent of HbA1c and hypoglycemic episodes.


CONCLUSIONS
Type 2 DM is associated with dysregulation of glycemic variability over multiple scales of time. These time-scale-dependent glycemic fluctuations might contribute to brain atrophy and cognitive outcomes within this vulnerable population.
Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, United States of America.
Xingran
X
Cui
Wright Center of Innovation, Dept. of Radiology, The Ohio State University, Columbus Ohio, United States of America.
Amir
A
Abduljalil
Institute for Aging Research, Hebrew SeniorLife, Roslindale, Massachusetts, United States of America ; Division of Gerontology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, United States of America.
Brad D
BD
Manor
Division of Interdisciplinary Medicine and Biotechnology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, United States of America ; Center for Dynamical Biomarkers and Translational Medicine, National Central University, Chung-Li, Taiwan.
Chung-Kang
CK
Peng
Division of Stroke, Dept. of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, United States of America.
Vera
V
Novak
D000368:Aged; D000369:Aged, 80 and over; D001284:Atrophy; D001786:Blood Glucose; D001921:Brain / Q000473:pathology; D016022:Case-Control Studies; D002540:Cerebral Cortex / Q000473:pathology*; D003072:Cognition Disorders / Q000209:etiology* / Q000473:pathology / Q000503:physiopathology; D015331:Cohort Studies; D003924:Diabetes Mellitus, Type 2 / Q000097:blood* / Q000150:complications*; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009929:Organ Size; D012307:Risk Factors
D001786:Blood Glucose