Effects of insulin resistance on white matter microstructure in middle-aged and older adults.
OBJECTIVE
To investigate the potential relationship between insulin resistance (IR) and white matter (WM) microstructure using diffusion tensor imaging in cognitively healthy middle-aged and older adults.


METHODS
Diffusion tensor imaging was acquired from 127 individuals (age range 41-86 years). IR was evaluated by the homeostasis model assessment of IR (HOMA-IR). Participants were divided into 2 groups based on HOMA-IR values: "high HOMA-IR" (≥2.5, n = 27) and "low HOMA-IR" (<2.5, n = 100). Cross-sectional voxel-based comparisons were performed using Tract-Based Spatial Statistics and anatomically defined regions of interest analysis.


RESULTS
The high HOMA-IR group demonstrated decreased axial diffusivity broadly throughout the cerebral WM in areas such as the corpus callosum, corona radiata, cerebral peduncle, posterior thalamic radiation, and right superior longitudinal fasciculus, and WM underlying the frontal, parietal, and temporal lobes, as well as decreased fractional anisotropy in the body and genu of corpus callosum and parts of the superior and anterior corona radiata, compared with the low HOMA-IR group, independent of age, WM signal abnormality volume, and antihypertensive medication status. These regions additionally demonstrated linear associations between diffusion measures and HOMA-IR across all subjects, with higher HOMA-IR values being correlated with lower axial diffusivity.


CONCLUSIONS
In generally healthy adults, greater IR is associated with alterations in WM tissue integrity. These cross-sectional findings suggest that IR contributes to WM microstructural alterations in middle-aged and older adults.
From the Department of Neurology (S.Y.R.), Daejeon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea; Departments of Radiology (S.Y.R., J.-P.C., H.D.R., D.H.S.) and Neurology (H.D.R.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston; Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology (J.-P.C), Massachusetts Institute of Technology, Cambridge; and VA Boston Healthcare System (D.H.S.), Boston, MA. streamline@catholic.ac.kr.
Seon Young
SY
Ryu
From the Department of Neurology (S.Y.R.), Daejeon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea; Departments of Radiology (S.Y.R., J.-P.C., H.D.R., D.H.S.) and Neurology (H.D.R.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston; Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology (J.-P.C), Massachusetts Institute of Technology, Cambridge; and VA Boston Healthcare System (D.H.S.), Boston, MA.
Jean-Philippe
JP
Coutu
From the Department of Neurology (S.Y.R.), Daejeon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea; Departments of Radiology (S.Y.R., J.-P.C., H.D.R., D.H.S.) and Neurology (H.D.R.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston; Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology (J.-P.C), Massachusetts Institute of Technology, Cambridge; and VA Boston Healthcare System (D.H.S.), Boston, MA.
H Diana
HD
Rosas
From the Department of Neurology (S.Y.R.), Daejeon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea; Departments of Radiology (S.Y.R., J.-P.C., H.D.R., D.H.S.) and Neurology (H.D.R.), Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Harvard Medical School, Boston; Harvard-Massachusetts Institute of Technology Division of Health Sciences and Technology (J.-P.C), Massachusetts Institute of Technology, Cambridge; and VA Boston Healthcare System (D.H.S.), Boston, MA.
David H
DH
Salat
D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D001921:Brain / Q000033:anatomy & histology*; D001931:Brain Mapping; D056324:Diffusion Tensor Imaging; D005260:Female; D006801:Humans; D007333:Insulin Resistance / Q000502:physiology*; D008297:Male; D008875:Middle Aged; D009413:Nerve Fibers, Myelinated / Q000648:ultrastructure*