Nicolas R. Bolo1,2, Alan M. Jacobson3, Brandon Hager1, Gail Musen2,4, Matcheri Keshavan1,2, and Donald C. Simonson5,6
1Psychiatry, Beth Israel Deaconess Medical Center, Boston, MA, United States, 2Psychiatry, Harvard Medical School, Boston, MA, United States, 3Research Institute, Winthrop University Hospital, Mineola, NY, United States, 4Research Division, Joslin Diabetes Center, Boston, MA, United States, 5Division of Endocrinology, Brigham and Women's Hospital, Boston, MA, United States, 6Harvard Medical School, Boston, MA, United States
Synopsis
Our goal is to elucidate
the independent effects of hyperglycemia and hyperinsulinemia on brain
function. We measured whole-brain amplitude of low frequency fluctuations (ALFF)
in slow-band 5 (SB5: 0.01-0.027Hz) and slow-band 4 (SB4: 0.027-0.073Hz) in 10 healthy non-diabetic
subjects using resting state fMRI during
fasting baseline euglycemia (EU), hyperglycemia (HG) and euglycemic
hyperinsulinemia (EU-HI). SB5 fractional ALFF was decreased in the left medial frontal
gyrus and right posterior cingulate/cuneus/precuneus cortices during
HG, but not during EU-HI, relative
to EU. Our findings may help understand brain functional
adaptations to chronic hyperglycemia in diabetes, and their implications for comorbid
neuropsychiatric complications.Purpose
The independent
effects of plasma glucose and insulin on brain function are not clearly
defined. Chronically elevated plasma
glucose is characteristic of type-1 diabetes (T1D). Altered brain function has been associated
with poor glucose control in T1D
1,2, and hyperglycemia has been implicated in associated
cognitive and mood impairments
3.
Elevated plasma insulin is often present in type-2 diabetes (T2D) and metabolic
syndrome. These metabolic disorders have
been associated with altered brain function
4 and an elevated risk for mild cognitive
impairment and Alzheimer’s disease
5; chronic hyperinsulinemia related to insulin
resistance may also be a contributing factor
6. Yet,
the mechanisms by which these metabolic disorders affect brain metabolism and
function are still poorly understood.
The goal of this study was to elucidate the independent effects of
hyperglycemia and hyperinsulinemia on regional brain function measured by amplitude
of low frequency fluctuations (ALFF) using resting state functional magnetic
resonance imaging (rs-fMRI) in healthy individuals.
Methods
We measured
whole brain ALFF
7 and fractional ALFF (fALFF)
8 in slow-band 5 (SB5: 0.01-0.027 Hz) and
slow-band 4 (SB4: 0.027-0.073 Hz)
9 during 2 separate MRI scanning visits in 10 healthy non-diabetic
subjects [mean (± SD) age = 28 ± 7 yrs, 6 M / 4 F, HbA1c = 5.5
± 0.3%, fasting plasma glucose = 93 ± 6
mg/dl, fasting insulin = 4.0 ± 2.5
μU/ml]. Subjects were
instructed to keep their eyes open and stare at a cross during a 6-minute
rs-fMRI run. During
visit 1, rs-fMRI was
performed in the fasted
euglycemic (EU1) state
followed by
a hyperglycemic (HG) clamp during which a primed-variable glucose infusion was used to
raise plasma glucose concentration by approximately 100 mg/dl for 60 minutes (mean glucose
= 205 ± 17 mg/dl, insulin response = 36 ± 24 μU/ml). During visit 2, at least 15 days
later, subjects were again studied in the basal state
(EU2) followed by a hyperinsulinemic euglycemic clamp
(EU-HI) during which a primed-continuous insulin infusion was
administered to match the insulin levels achieved during the HG clamp, and a
variable glucose infusion was administered to maintain euglycemia (mean glucose = 96 ±
7 mg/dl, insulin = 32 ± 21 μU/ml). All MRI data was acquired on a 3T GE Signa
HDxt scanner. A T1-weighted structural
scan (MPRAGE) was acquired for each session to aid registration of the fMRI
data to standard MNI-152 space. A BOLD-EPI
sequence was used for rs-fMRI (TR/TE=3000/27 ms, flip=8º, voxel size = 3.75 x
3.75 x 4 mm,180 volumes). We analyzed
rs-FMRI data using the FSL (fsl.fmri.ox.ac.uk) and DPARSF (rfmri.org) software
packages to obtain SB4 and SB5 ALFF and fALFF on a voxel-wise basis for each
subject during each condition. We
performed paired comparisons of SB5 fALFF during 1) EU1 vs. HG (Visit 1), 2) EU2 vs.
EU-HI (Visit 2), and 3)
HG (Visit 1) vs. EU-HI
(Visit 2)
using the general
linear model.
Results
SB5 fALFF was
significantly decreased in the left medial frontal gyrus (MFG) and right
posterior cingulate (PCC) and cuneus/precuneus cortices during HG relative to EU1 (p<0.01, corrected - Fig.
1), but no significant difference was found during EU-HI relative
to EU2. No significant
difference was found in these
regions between the HG (hyperglycemia) and
EU-HI (matched hyperinsulinemic euglycemia)
clamps, but SB5 fALFF was decreased in
the left putamen during HG relative to EU-HI (p<0.01, corrected - Fig. 2). Thus, high
plasma glucose combined with high insulin significantly decreased MFG/PCC
SB5 fALFF, while high
plasma insulin alone with normal glucose
levels had no significant
independent effect on SB5 fALFF.
Discussion and Conclusion
Our results demonstrate that acute high plasma glucose and insulin,
such as may be encountered after a high glycemic load meal, decreases SB5 fALFF
in the MFG and PCC/precuneus, while matching high plasma insulin has no
significant independent effect on these brain regions in healthy individuals. ALFF and fALFF have been proposed to reflect
the regional intensity of spontaneous neuronal
activity (SNA)
10,11. We evaluated ALFF and fALFF
as proposed by Zuo et al.
12 in distinct frequency bands based on work suggesting that independent
frequency bands are generated by distinct oscillators
9. We focused on fALFF because
it was shown to be less sensitive to signal fluctuations due to physiological noise
8, and on SB5 because it was shown to be preferentially localized in cortical grey
matter
12. Our results suggest that SNA decreases in MFG and PCC/precuneus, regions
associated with executive function and the default mode respectively, during
hyperglycemia. These findings on the acute
effects of hyperglycemia may be helpful in understanding brain functional adaptations to
chronic hyperglycemia in diabetes, and their implications for comorbid
neuropsychiatric complications.
Acknowledgements
This work was supported by NIH grant DK-084202
(PI: N. Bolo).References
1. Bolo,
N. R. et al. Brain activation during working memory is altered in
patients with type 1 diabetes during hypoglycemia. Diabetes 60,
3256–3264 (2011).
2. Bolo, N. R. et al. Functional
Connectivity of Insula, Basal Ganglia, and Prefrontal Executive Control
Networks during Hypoglycemia in Type 1 Diabetes. J Neurosci 35,
11012–11023 (2015).
3. Lyoo, I. K. et al. Altered
prefrontal glutamate-glutamine-gamma-aminobutyric acid levels and relation to
low cognitive performance and depressive symptoms in type 1 diabetes mellitus. Arch
Gen Psychiatry 66, 878–887 (2009).
4. Musen, G. et al. Resting-state
brain functional connectivity is altered in type 2 diabetes. Diabetes 61,
2375–2379 (2012).
5. Craft, S. & Watson, G. S. Insulin and
neurodegenerative disease: shared and specific mechanisms. Lancet neurology
3, 169–178 (2004).
6. Luchsinger, J. A., Tang, M.-X., Shea, S.
& Mayeux, R. Hyperinsulinemia and risk of Alzheimer disease. Neurology
63, 1187–1192 (2004).
7. Zang, Y.-F. et al. Altered
baseline brain activity in children with ADHD revealed by resting-state
functional MRI. Brain Dev. 29, 83–91 (2007).
8. Zou, Q.-H. et al. An improved
approach to detection of amplitude of low-frequency fluctuation (ALFF) for
resting-state fMRI: Fractional ALFF. J. Neurosci. Methods 172,
137–141 (2008).
9. Buzsáki, G. & Draguhn, A. Neuronal
oscillations in cortical networks. Science 304, 1926–1929 (2004).
10. Fox, M. D. & Raichle, M. E. Spontaneous
fluctuations in brain activity observed with functional magnetic resonance
imaging. Nat Rev Neurosci 8, 700–711 (2007).
11. Balduzzi, D., Riedner, B. A. & Tononi,
G. A BOLD window into brain waves. Proc Natl Acad Sci USA 105,
15641–15642 (2008).
12. Zuo, X.-N. et al. The oscillating
brain: complex and reliable. NeuroImage 49, 1432–1445 (2010).