Brain Volume Abnormalities and Neurocognitive Deficits ... - CiteSeerX

Adv Ther (2010) 27(2):63-80. DOI 10.1007/s12325-010-0011‑z

REVIEW

Brain Volume Abnormalities and Neurocognitive Deficits in Diabetes Mellitus: Points of Pathophysiological Commonality with Mood Disorders? Roger S. McIntyre · Heather A. Kenna · Ha T. Nguyen · Candy W. Y. Law · Farah Sultan · Hanna O. Woldeyohannes · Mohammad T. Alsuwaidan · Joanna K. Soczynska · Amanda K. Adams · Jenny S. H. Cheng · Maria Lourenco · Sidney H. Kennedy · Natalie L. Rasgon

Received: February 4, 2010 / Published online: April 8, 2010 © Springer Healthcare 2010

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ABSTRACT Background: It is hypothesized that diabetes mellitus (DM) and mood disorders share points of pathophysiological commonality in the central nervous system. Methods: A PubMed search of all English-language articles published between 1966 and March 2009 was performed with the following search terms: depression, mood disorders, hippocampus, amygdala, central nervous system, brain, neuroimaging, volumetric, morphometric, and neurocognitive deficits, cross-referenced with DM. Articles selected for review were based on adequacy of sample size, the use of standardized

Roger S. McIntyre () Associate Professor of Psychiatry and Pharmacology, University of Toronto, Head of Mood Disorders Psychopharmacology Unit, University Health Network, 399 Bathurst Street, Toronto, Ontario, Canada, M5T 2S8. Email: [email protected] Ha T. Nguyen · Candy W. Y. Law · Farah Sultan · Hanna O. Woldeyohannes · Mohammad T. Alsuwaidan · Joanna K. Soczynska · Amanda K. Adams · Jenny S. H. Cheng · Maria Lourenco · Sidney H. Kennedy Mood Disorders Psychopharmacology Unit, University Health Network, Toronto, Ontario, Canada Heather A. Kenna · Natalie L. Rasgon Stanford University, Palo Alto, California, USA

experimental procedures, validated assessment measures, and overall manuscript quality. The primary author was principally responsible for adjudicating the merit of articles that were included. Results: Volumetric studies indicate that individuals with Type 1/2 DM exhibit regional abnormalities in both cortical and subcortical (eg, hippocampus, amygdala) brain structures. The pattern of neurocognitive deficits documented in individuals with Type 1 DM overlap with Type 2 populations, with suggestions of discrete abnormalities unique to each phenotype. The pattern of volumetric and neurocognitive deficits in diabetic populations are highly similar to that reported in populations of individuals with major depressive disorder. Conclusion: The prevailing models of disease pathophysiology in DM and major depressive disorder are distinct. Notwithstanding, the common abnormalities observed in disparate effector systems (eg, insulin resistance, immunoinflammatory activation) as well as brain volume and neurocognitive performance provide the nexus for hypothesizing that both conditions are subserved by overlapping pathophysiology. This conception provides a novel framework for disease modeling and treatment development in mood disorder.

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Keywords: amygdala; brain; diabetes mellitus; hippocampus; mood disorders; morphometric; MRI; neurocognitive deficits

INTRODUCTION Diabetes mellitus (DM) is associated with an increased risk of stroke, vascular dementia, and mild cognitive impairment, as well as Alzheimer’s disease.1 The appellation “diabetic encephalopathy”, although not rigorously defined, is an erstwhile notion referring to the consequences of abnormal glucose-insulin homeostasis on brain structure and function.2 During the past decade, intensified research efforts have begun to parse out insulin’s salience to both physiological and pathophysiological brain function.3,4 For example, brain insulin receptors, as well as insulin-sensitive glucose transporters, are regionally distributed throughout the central nervous system (CNS) with differential expression in brain regions subserving affective and cognitive function (eg, anterior cingulate cortex, prefrontal cortex, hippocampus).4 The consequences of DM on CNS structure and function have both clinical and research implications. For example, individuals with DM are differentially affected by psychiatric syndromes (eg, mood disorders) that pose a hazard for the course and outcome of DM (and vice versa).5 Moreover, DM is an independent risk factor for incident mood disorders and Alzheimer’s disease, conditions characterized by progressive neurocognitive decline.6 Identifying points of pathophysiological commonality between DM and mood disorders may provide an opportunity to refine models of disease pathophysiology for both conditions.3 In keeping with this view, postmortem studies indicate that mood disorders are associated with regional and layer-specific alterations in the

Adv Ther (2010) 27(2):63-80.

size, shape, and density of neurons and glia.7,8 Volumetric imaging and neuropsychological studies have provided correlative findings indicating that constituents of the anterior limbic circuit (eg, hippocampus) are abnormal in structure and function, respectively, in individuals with mood disorders.9 Moreover, emerging evidence also indicates that individuals with DM exhibit similar volumetric and neurocognitive deficits to persons with mood disorders. Although the pathophysiology of mood disorders and DM are distinct, there appears to be several points of commonality in the CNS.3,10 The objective of this review is to summarize the evidentiary base reporting on brain volumetric abnormalities and neurocognitive deficits in individuals with DM. The encompassing aim of this endeavor is to reify the conception that mood disorders and DM may share pathophysiological substrates and/or consequences in the CNS. This paper does not review the neuroanatomical and neurocognitive deficits in individuals with mood disorders, as they are reviewed elsewhere.9

METHODS A PubMed search of all English-language articles published between 1966 and March 2009 was performed with the following search terms: depression, mood disorders, hippocampus, amygdala, central nervous system, brain, neuroimaging, volumetric, morphometric, and neurocognitive deficits, cross-referenced with DM. Articles selected for review were based on adequacy of sample size, the use of standardized experimental procedures, validated assessment measures, and overall manuscript quality. The primary author was principally responsible for adjudicating the merit of the articles that were included.

Adv Ther (2010) 27(2):63-80.

RESULTS Several investigations have reported on brain volume and neurocognitive deficits in mixed populations with DM (Table 1 contains detailed information regarding each of these studies).11-27 Soininen et al. evaluated neurocognitive performance and computed tomography-measured abnormalities in three discrete groups: non-diabetic (n=59; mean age=74.0±6.4 years), diet-treated noninsulin-dependent diabetics (n=13; mean age=76.0±8.3 years) and medication-treated non-insulin-dependent diabetics (n=12; mean age=77.6±7.4 years). There were no significant between-group differences in measures of neurocognitive performance. Nevertheless, medication-treated diabetic patients exhibited more pronounced central temporal atrophy as evidenced by a significantly wider right temporal horn compared with that in the nondiabetic group. Fasting blood glucose positively correlated with the width of the right temporal horn in the two diabetic groups.11 Araki et al. evaluated and compared magnetic resonance imaging (MRI)-measured brain volume amongst individuals (n=159; mean age=60.4 years) with DM (disease duration=3-30 years; mean duration=13.5 years) to age-matched individuals without DM (n=2566). Most individuals in the diabetic group were non-insulin-dependent (n=144). A significantly higher frequency of cerebral atrophy was observed in the diabetic group when compared with the control group. Cerebral atrophy increased as a function of age in both groups, with more pronounced abnormalities noted in the diabetic group (eg, 41.2% vs. 19.8%, 60% vs. 38.9%, 92.3% vs. 56.8% in the sixth, seventh, and eighth decade of life, respectively).12 Convit et al. reported that non-diabetic, nondemented subjects (n=27; mean age=69 years)

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with abnormal glucose tolerance exhibited smaller hippocampal volumes, which were associated with impairment in memory (ie, immediate and delayed) performance. Delayed paragraph recall was also significantly correlated with hippocampal volume. No further brain volumetric abnormalities were noted in other brain regions of interest (eg, parahippocampal gyrus, the superior temporal gyrus).13 Perros et al. aimed to determine the effect of insulin-dependent DM (IDDM) on MRImeasured brain volumes. Neurometabolic parameters were also evaluated with magnetic resonance spectroscopy (MRS) an association with neurocognitive function was evaluated. Eleven patients with IDDM and no history of severe hypoglycemia were compared with eleven IDDM patients with a history of five or more episodes of severe hypoglycemia. Of the twentytwo IDDM patients, leukoaraiosis, manifesting as white matter hyperintensities (WMH) with T2-weighted MRI, was present in four patients (18.2%) while cortical atrophy was noted in five patients (22.7%).14 There were no significant differences between groups in the prevalence of leukoaraiosis, although numerically more individuals with recurrent hypoglycemia exhibited cortical atrophy. Individuals with recurrent hypoglycemia had a lower IQ score; no other significant between-group differences were reported on any neurocognitive measure. Moreover, there was no association between the presence of MRI-measured cortical atrophy and cognitive function, although trends for diminished psychomotor speed were noted in patients with cortical atrophy.14 Den Heijer et al. examined the association between Type 2 DM, insulin resistance, and hippocampal and amygdala atrophy as part of the Rotterdam Study. The Rotterdam study was a large population-based cohort study conducted

n Population

MRI parameters (Tesla)

Method (psychometric measures) Aim

Soininen H et al. (1992)11

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(continued on next page)

To evaluate cognitive performance in DM Not WAIS CT measures for overall brain Non-DM (n=59). and non-DM patients using CT. indicated Compilation of analysis ECG, chest X-ray, NIDDM treated with diet. neuropsychological test electroencephalogram. (n=13). presented as one SD score NIDDM treated with drugs (n=12). 68-84 years. Results: No difference between groups in cognitive performance. Drug-treated DM exhibited greater central temporal atrophy and wider frontal horns (all women). CT measures were comparable. Araki Y et al. 1.5 None To assess the central effects of DM 2725 DM (n=159; NIDDM, 144; MRI-assessed frequency of (1994)12 with MRI. cerebral infarcts hemorrhages, IDDM, 15). atrophy, and subcortical Healthy controls (n=2566). arteriosclerotic encephalopathy. Results: Cerebral atrophy was significantly more frequent in DM group than controls from the 6th to 8th decade of life. No significant differences in occurrences of cerebrovascular diseases at any age. Convit A et al. MRI-derived volumes assessing 1.5 None To evaluate the involvement of the 76 Normal elderly (n=27). (1997)13 the temporal lobe. temporal lobe in the preclinical stages Minimal cognitive impairment of DAT. non-DAT (n=22), DAT (n=27). Results: Hippocampal volumes were reduced for the MCI and DAT groups compared with normal elderly. To assess IDDM for brain lesions with Perros P et al. MRI and MRS evaluated Not WAIS 22 IDDM with no history of and without a history of hypoglycemia (1997)14 overall brain structure. indicated NART hypoglycemia (n=11). IDDM and the relationship of any cognitive AVLT with history of hypoglycemia impairments. IT (n=11). CRT PASAT RVIP Results: Abnormalities were observed in the periventricular WM and cortical atrophy was found in IDDM with history of hypoglycemia. MRS scans showed no differences. No significant relations were found in psychometric measures.

Author

Method (including neuroimaging and neurocognitive testing)

Table 1. Brain volume and neurocognitive abnormalities in diabetic populations.3

66 Adv Ther (2010) 27(2):63-80.

506

den Heijer T et al. Type 2 DM controls (n=41).

Non-DM (n=465).

Population

and the degree of hippocampal and amygdala atrophy. To investigate whether DM increases the

function

atrophy using MRI. Marked for WML and infarcts present.

development of DAT through neuropathy.

To investigate the association between DM, IDDM,

1.5

15 word learning test

Assessed degree of Overall z-score for cognitive

Aim

hippocampal and amygdala

Method (psychometric measures)

74

exposure to severe hypoglycemia.

IT

hippocampal areas. PASAT

structure in individuals with Type 1 DM with

NART

To investigate cognitive performance and brain

temporal lobe and amygdala-

HADS

hypoglycemia.

1.0 WAIS-R

MRI assessed for TBV, CSF, and RBV. VBM assessed

Type 1 DM youth (n=74) with sufficient exposure severe

71 structure.

7 years (n=26). Later-onset Type 1 DM between 7-17 years (n=45).

MRI assessed overall brain

Early-onset Type 1 DM before

1.0

structure.

PASAT

BVFT

IT

in youth, on cognitive performance and brain NART

To evaluate the effects of early-onset Type 1 DM WAIS-R

HADS

26 30-50 years of age.

(n=13). Non-DM (n=13).

Type 1 DM with 10 years duration

MRI scans to determine hippocampal volume and CSF.

1.0

15-item CESDS

TMT

DS

SCWT

Paired association

performance in individuals with Type 1 DM.

To examine hippocampal volume and memory

psychomotor speed and selective attention.


Results: Hippocampal volumes and memory performance did not differ between subjects and controls. However, significant increase in CSF volume suggests mild cerebral atrophy. Also found impaired

(2006)18

Lobnig BM et al.

group that those with later-onset.

Results: Intellectual ability and information processing ability was inferior in the early-onset DM group; LV volumes were 37% greater and ventricular atrophy was more prevalent in the early-onset

17

(2005)

Ferguson SC et al.

processing, attention, and concentration abilities.

Results: Severe hypoglycemia did not influence cognitive ability or brain structure. Background retinopathy was associated with a significant cognitive disadvantage in fluid intelligence, information

(2003)16

Ferguson SC et al.

men.

and mid brain has negative relation to BMI in men. GMV in bilateral inferior frontal gyri, posterior lobe of cerebellum, frontal lobes temporal lobes thalami, and caudate shows positive relation to BMI in

Results: Significant negative relation in men but not women between BMI and GMV. VBM showed that GMV in bilateral medial temporal lobes, anterior lobes of cerebellum, occipital lobe, frontal lobe,

(2003)15

n

Author

Method (including MRI neuroimaging and parameters neurocognitive testing) (Tesla)

Table 1. Brain volume and neurocognitive abnormalities in diabetic populations.3 (Continued)

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118

Musen G et al. (2006)19

Type 1 DM (n=82). MRI screened for brain Healthy controls (n=36). structural abnormalities. VBM assessed GMV, 25-40 years, 5-10 years disease duration. WMV, and CSF.

Population 1.5

WAIS D-KEFS WMS DS Grooved peg board

Method (psychometric measures)

To examine DM and metabolic disturbances with changes in GMV and CSF.

Aim


Results: DM showed lower GMD in regions for language processing and memory. Wessels AM et al. 52 VBM comparing GMD 1.5 None To investigate whether long-term Type 1 DM without (2006)20 between groups. hyperglycemia, resulting in advanced microvascular complications retinopathy, contributes to structural changes (n=18). Type 1 DM with a in GMD. microvascular complication (n=13). Healthy controls (n=21). Results: Patients with diabetic retinopathy exhibited smaller GMD in the right inferior frontal gyrus and right occipital lobe compared with those without diabetic retinopathyand healthy controls. Wessels AM et al. 34 Type 1 DM (n=25). Comparing fractional brain 1.5 DS forward and backward To assess cognitive performance in Type 1 DM patients who may be compromised due to (2007)21 Healthy controls (n=9). tissue volumes with VBM. 15 word test chronic hyperglycemia, associated with GMV ROCF test and WMV. Delayed recall condition WAIS-Symbol Substitution Learning test TMT (A&B) SCWT (I, II & III) GIT sorting WCST WISC-Mazes CWF task WAIS-block design Results: Type 1 DM patients exhibited inferior performance on measures of speed of information processing and visuoconstruction. Patients with microvascular complication had a significantly smaller WMV than non-diabetic controls, also associated with lower performance on the domains of speed of information processing, attention, and executive functioning.

n

Author



68 Adv Ther (2010) 27(2):63-80.

n Population

Aim

159

Type 1 DM youth (n=108). Healthy control siblings (n=51). Age 7-17 years.

Results: No difference in WMV and GMV. DM subjects have greater brain atrophy and CSF volume.

Perantie DC et al. (2007)22


1.5 None To quantify RBV differences. Structural MRI. VBM determined TBV in Type 1 DM youth not previously relationship between studied. prior hypo-hyperglycemia to regions of GMV and WMV. Results: No significant difference reported between DM and healthy controls. Severe hypoglycemia was associated with smaller GMV in the left superior temporal region. Exposure to hyperglycemia was associated with smaller GMV in the right cuneus and precuneus, smaller WMV in the right posterior parietal region, and larger GMV in the right prefrontal region. Type 2 DM is known to be associated Jongen C et al. 1.5 An overall z-score was 145 Type 2 DM (n=99; 56Automated segmentation with brain atrophy and cognitive decline; (2007)23 acquired for cognition 80 years). Healthy controls technique associated with association of WML is unclear. composite that included 11 (n=46; 55-78 years). Type 2 DM, related DM different tests addressing risk factors, and cognition cognitive domains of visuowith WML volumes construction, attention MRI assessed WMV, and executive function, GMV, LV, CSF, and WML information processing speed, memory, and abstract reasoning Results: Significantly smaller GMV and significantly larger lateral ventricle volumes than controls. History of macrovascular disease was associated with larger total CSF. DM patients with lower composite cognitive performance showed smaller TBV. Kumar R et al. To examine the neuroanatomical and 478 DM (n=39), no DM (n=428). MRI 1.5 MMSE (2008)24 60-64 years. Spot-the Word Test Version A neurocognitive differences in diabetic participants (60-64 years) SDMT with depression. Immediate and delayed recall Purdue Pegboard Test (both hands) Reaction time (simple and choice) Goldberg Scale (for depression)

Author

Method (including MRI neuroimaging and parameters Method neurocognitive testing) (Tesla) (psychometric measures)


Adv Ther (2010) 27(2):63-80. 69

50

Kodl CT et al. (2008)25

Type 1 DM for 15 years DTI for assessment of (n=25), age-and sex-matched WM microstructure. non-diabetic (n=25).

Population 3.0

Method (psychometric measures) Aim

AVLT=Auditory Verbal Learning Test; BMI=body mass index; BVFT=behavioral variant frontotemporal dementia; CESDS=Centre for Epidemiologic Studies Depression Scale; CPT=Connor’s Continuous Performance Test; CRT=Choice Reaction Time test; CSF=cerebrospinal fluid; CT=computed tomography; CVLT=California Verbal Learning Test; CWF=Category Word Fluency task; D-KEFS=Delis-Kaplan Executive Function System; DAT=dementia of Alzheimer’s type; DM=diabetes mellitus; DS=digit span; DTI=diffusion tensor imaging; DVT=Digit Vigilance Test; ECG=electrocardiograph; FSIQ=full scale IQ; GIT=general information test; GMD=gray matter density; GMV=gray matter volume; HADS=Hospital Anxiety and Depression Scale; LV=left ventricular; MCI=minimal cognitive impairment; MDD=major depressive disorder; mI=myo-inositol; MMSE=mini-mental state evaluation; MRI=magnetic resonance imaging; MRS=magnetic resonance spectroscopy; NART=National Adult Reading Test; N/IDDM=non/insulin-dependent diabetes mellitus; PASAT=Paced Auditory Serial Addition Test; PIQ=performance IQ; RBV=relative blood volume; ROCF=Rey-Osterrieth Complex Figure; RVIP=Rapid Visual Information Processing; SCWT=Stroop Color-Word Test; SDMT=Symbol Digit Modalities Test; TBV=total brain volume; TMT=Trail Making Test; VBM=voxel-based morphometry; VIQ=verbal IQ; WAIS=Wechsler Adult Intelligence Scale; WASI=Wechsler Abbreviated Scale of General Intelligence; WCST=Wisconsin Card Sorting Test; WISC=Wechsler Intelligence Scale for Children; WML=white matter lesions; WMS=Wechsler Memory Scale; WMV=white matter volume.

WASI To assess the validity of using DTI for PASAT identifying differences in the brain of DVT patients with chronic Type 1 DM and its Trails A and B possible association with deficits identified ROCF by neurocognitive tests. Grooved Pegboard Test CPT-II Results: The posterior corona radiate and optic radiation of subjects with diabetes showed a decreased mean fractional anisotropy than non-diabetic controls. 57 Subjects with DM & MDD MRS to measure levels 1.5 ROCF (ROCF-Recall To determine whether visuospatial Haroon E et al. 26 (n=18). Subjects with DM of mI & ROCF-Recognition) deficits were attributable to elevations in (2009) but no MDD (n=20). dorsolateral mI in patients with DM & Controls, not depressed or MDD. diabetic (n=19). Results: No association reported between dorsolateral mI levels and visuospatial deficits in patients with DM and MDD. WASI: FSIQ, VIQ To examine brain functioning in youths Northam EA et al. 181 Type 1 DM (n=106), control MRS, MRI: volumetry subjects (n=75). and PIQ 12 years after diagnosis Type 1 DM. (2009)27 Results: Type 1 DM showed decreased GMV in bilateral thalami and right parahippocampal gyrus and insular cortex. Type 1 DM showed decreased WMV in bilateral parahippocampi, left temporal lobe, and middle frontal area.

n

Author



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Adv Ther (2010) 27(2):63-80.

in the Netherlands that aimed to investigate the prevalence, incidence, and determinants of chronic disease in the elderly. Baseline examinations were completed between 1990 and 1993. In 1996, 506 living members (60-90 years of age) were investigated with MRI to evaluate age-related brain abnormalities. Type 2 DM was operationalized as the reported use of oral antidiabetic treatment, and a plasma glucose level following a 2-hour glucose tolerance greater than or equal to 11.1 mmol/L. Insulin resistance in non-diabetic subjects was assessed by the ratio of postload insulin levels divided by peripheral glucose concentration.15 None of the participants were known to have a dementing disorder; nevertheless, individuals with Type 2 DM (n=41; 8.1%) exhibited decreased performance in memory testing. Individuals with DM had more atherosclerotic plaques in the carotid arteries and were 1.7 times more likely to exhibit cerebral infarctions compared with those without Type 2 DM. Individuals with Type 2 DM had smaller bilateral hippocampal and amygdala volumes after adjusting for body mass index, pack-years of cigarette smoking, blood pressure, and cholesterol levels. Exclusion of participants with infarcts did not change the results, nor did stratification as a function of APOE (a genetic vulnerability factor for Alzheimer’s disease) status. Individuals with high postload insulin concentrations or insulin resistance also exhibited smaller amygdala volume, but no difference in hippocampal volume. Volumetric changes noted in the insulin-resistant group remained after multivariate analysis. The association between insulin resistance and amygdala volume was statistically significant only in non-carriers of the APOE ε4 allele.15 It has been documented that tight glycemic control reduces the risk of diabetic microangiopathy and increases the risk for hypoglycemia. Protracted periods of

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hypoglycemia predominantly affect neuronal function in the frontal lobes and subcortical grey matter. 28 Repeat exposure to severe hypoglycemia has been associated with cortical atrophy. 14 Susceptibility to hypoglycemiarelated cerebral atrophy may be higher in older populations (ie, over 45 years).14,29 Available evidence suggests that both hyperglycemia and hypoglycemia exert toxic effects on brain structure and function. Ferguson et al. cross-sectionally evaluated individuals (minimum 10 years illness duration) with Type 1 DM (n=74; age at illness onset