Edited by: Mark Haacke, Wayne State University, United States
Reviewed by: Niels Bergsland, University at Buffalo, United States; Sean K. Sethi, Wayne State University, United States
†ORCID: Jing Li,
This article was submitted to Brain Imaging Methods, a section of the journal Frontiers in Neuroscience
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Brain iron accumulation has been suggested as a pathomechanism in patients with type 2 diabetes mellitus (T2DM) with cognitive impairment. This research aims to examine the total-brain pattern of iron accumulation in relation to executive function decline in patients with T2DM by voxel-based quantitative susceptibility mapping (QSM) analysis.
A total of 32 patients with T2DM and 34 age- and sex-matched healthy controls (HCs) were enrolled in this study. All participants underwent brain magnetic resonance examination, and 48 individuals underwent cognitive function assessments. Imaging data were collected with three-dimensional fast low-angle shot sequences to achieve magnitude as well as phase images. Using voxel-based QSM analysis, we compared the voxel-wise susceptibility values of the whole brain among groups and explored whether the susceptibility values had correlations with cognitive data.
Among the 66 participants, cognitive function was estimated in 23 patients with T2DM (11 males and 12 females; average age, 64.65 ± 8.44 years) and 25 HCs (13 males and 12 females; average age, 61.20 ± 7.62 years). T2DM patients exhibited significantly (
Patients with T2DM presented declined cognitive assessments and elevated iron deposition in the striatum and frontal lobe, suggesting that executive function decline in T2DM might be associated with the cerebral iron burden and that changes in susceptibility values may represent a latent quantitative imaging marker for early assessment of cognitive decline in patients with T2DM.
In type 2 diabetes mellitus (T2DM), peripheral insulin resistance together with compensatory insulin hypersecretion from pancreatic islets likely results in some complications, such as neuropathy, nephropathy, atherosclerosis, and retinopathy (
T2DM patients suffer from cognitive deficits of memory, executive function (EF), attention, visuospatial capabilities, and other domains (
Heretofore, to image biomarkers, several magnetic resonance imaging (MRI) techniques have been proposed in T2DM patients with cognitive impairment (
This cross-sectional research consisted of 32 T2DM patients (20 males; average age, 61.09 ± 9.99 years; age range 39–75 years) and 34 age- and sex-matched healthy control (HC) volunteers (15 males; average age, 58.50 ± 10.07 years; age range, 35–73 years) who were registered from December 2018 to April 2020. The patients all met the diagnostic criteria of T2DM (the diagnosis was based on the American Diabetes Association criteria). In this research, no special selection of T2DM patients according to metabolic control, the existence of micro- or macrovascular complications, neuropathy, the disease duration or treatment type for hyperglycemia, vascular risk factors, or arterial hypertension was applied. The HC volunteers without T2DM had no history of elevated blood glucose levels, and their blood glucose levels were maintained in the normal range (fasting glucose < 5.5 mmol/L). Patients who had a greater than 1-year history of T2DM and willing to undergo the MRI scan were enrolled. The exclusion criteria included a history of psychiatric or neurological disorders (including cerebrovascular accidents), which may affect cognitive functioning, a history of alcohol or substance abuse, acute complications of T2DM (ketoacidosis and severe hypoglycemia) within the 3 months preceding the examination, and MRI scan contraindications. The research obtained approval from the Institutional Review Board of Shandong Medical Imaging Research Institute Affiliated to Shandong University. All of the participants were given information about the experimental procedures and signed consent forms. In consideration of the likely cognitive impairment of the participants, all of the subjects were invited to perform cognitive function assessments according to their educational levels. Finally, 48 people (23 T2DM patients and 25 HCs) completed the questionnaire.
The participants underwent an elaborate interview as well as a clinical examination. Age, education level (the number of years in elementary school, high school, and college), and the duration and medical treatment of diabetes were registered and recorded. Systolic blood pressure (BP) and diastolic BP were measured. Arterial hypertension was defined as an average systolic BP > 140 mm Hg and a diastolic BP > 90 mm Hg or self-reported use of medication to lower BP, and fasting glucose, HbA1c fasting triglycerides, and fasting cholesterol were determined by laboratory testing of venous blood samples. Weight and height were measured and used to calculate body mass index (BMI). After the above medical history collection, blood sample collection, and clinical examinations were finished, the participants were invited to visit the clinic on separate days for cognitive tests and MRI scans. The following items were evaluated on the same day, and the interval was 1–4 days between these two visits. The severity of cerebral small vessel disease (CSVD) was assessed using the Fazekas scale (0–3) oriented with periventricular hyperintensity (PVH) together with deep white matter hyperintensity (DWMH) lesions (
Standardized general and detailed neurological examinations were conducted on the participators, 48 of whom (23 T2DM patients and 25 HCs) underwent the cognitive assessment, and the assessment tools included the Montreal Cognitive Assessment (MoCA) and the Chinese version of the Trail-making Test (TMT). The MoCA is a one-page 30-point test administered in 10 min (
All of the subjects were imaged on a MAGNETOM Skyra 3.0-T MR scanner (Siemens Healthcare, Erlangen, Germany) using a 32-channel head coil for signal reception. The brain scanning protocol consisted of a 3D T1-weighted (T1W) magnetization-prepared rapid gradient echo (MPRAGE) sequence for anatomic structure [repetition time (TR) = 7.3 ms, echo time (TE) = 2.4 ms, inversion time (TI) = 900 ms, flip angle = 9°, and isotropic voxel size = 1 mm3]and a 3D multi-echo gradient echo (ME-GRE) sequence for QSM (
Brain QSM maps were computed from complex ME-GRE image data using morphology-enabled dipole inversion with an automatic uniform cerebrospinal fluid (CSF) zero reference algorithm (MEDI + 0) (
We first acquired gray matter volume images by segmenting the T1 anatomical image through Statistical Parametric Mapping version 12
The enrolled subjects were separated into two groups (T2DM and HCs). To compare voxel-based QSM values, we used a two-sample
This research included 32 patients with T2DM (20 males and 12 females with an average age of 61.09 ± 9.99 years) and 34 HCs (15 males and 19 females with an average age of 58.50 ± 10.07 years). These participants showed no significant difference in age or sex (
Clinical features of the participants.
Sex (male) | 15 (44.12%) | 20 (62.50%) | 2.236a | 0.133 |
Age (years) | 58.50 ± 10.07 | 61.09 ± 9.99 | 1.049 | 0.298 |
Risk factors for cardiovascular disease | ||||
BMI (kg/m2) | 25.3 ± 4.7 | 27.5 ± 5.6 | 1.315b | 0.104 |
Fasting serum cholesterol (mmol/L) | 5.3 ± 0.9 | 5.4 ± 1.1 | 0.398b | 0.634 |
Fasting serum triglycerides (mmol/L) | 2.2 ± 0.6 | 2.6 ± 0.8 | 1. 324b | 0.117 |
Hypertension | 13 (38.24%) | 15 (46.88%) | 0.504b | 0.478b |
Use of antihypertensive medication | 11 (32.35%) | 12 (37.50%) | 0.192b | 0.661b |
History of myocardial infarction | 0 | 0 | ||
CSVD scores | 1.1 ± 0.34 | 1.3 ± 0.45 | 1.291c | 0.208c |
Type 2 diabetes-related factors | ||||
Fasting plasma glucose (mmol/L) | 5.2 ± 1.26 | 9.2 ± 2.44 | 3.551b | <0.001 |
HbA1c (mmol/ml) | – | 61.1 ± 10.3 | ||
HbA1c (%) | – | 7.9 ± 1.3 | ||
Diabetes duration (years) | – | 11.2 ± 6.5 | ||
Insulin use | – | 16 (50.00%) |
Cognitive functioning assessment of the participants.
Gender (male) | 13 (52.00%) | 12 (52.17%) | 0.000a | 0.990 |
Age, years | 61.20 ± 7.62 | 64.65 ± 8.44 | 1.847b | 0.071 |
Education, years | 12.60 ± 2.41 | 11.34 ± 2.26 | 1.488b | 0.144 |
MoCA | 29 (28, 29) | 27 (27, 28) | 4.288c | <0.001 |
TMT-A | 53.00 (36.50, 63.50) | 71.00 (51.00, 100.00) | 2.612c | 0.009 |
TMT-B | 150.00 (103.00, 172.50) | 185.00 (149.00, 260.00) | 2.797c | 0.005 |
Cognitive score (MoCA and TMT) differences between T2DM patients and HCs. MoCA, Montreal Cognitive Assessment; TMT, Trail-making Test; T2DM, type 2 diabetes mellitus; HC, healthy control.
Results of whole-brain voxel-based analyses of susceptibility values between T2DM patients and HCs.
Right caudate/putamen/pallidum | 30 | 4 | 9 | 1,348 | −4.52 | 4.03 | 0.018 | 87.84 ± 19.57 | 63.23 ± 26.02 |
Right frontal inferior triangular gyrus | 53 | 25 | 20 | 591 | −4.48 | 3.99 | 0.021 | 15.74 ± 14.44 | 4.47 ± 9.25 |
Right precentral gyrus | 49 | −5 | 46 | 221 | −3.77 | 3.37 | 0.041 | 8.46 ± 13.00 | −3.39 ± 14.19 |
Results of whole-brain voxel-based analyses of susceptibility values between T2DM patients and HCs. The subjects with T2DM showed significantly higher susceptibility values than HCs in the caudate/putamen/pallidum, frontal inferior triangular gyrus, and precentral gyrus on the right side. T2DM, type 2 diabetes mellitus; HC, healthy control.
Correlation analysis between voxel-based susceptibility value and cognitive scores with sex and age as covariates was conducted. A significance cluster-level
The correlation using whole-brain voxel-based analyses of susceptibility values in the patients with T2DM.
TMT-A | Left thalamus | −4 | −8 | 19 | 1,035 | 4.84 | 0.53 | 0.001 |
TMT-B | Right thalamus | 9 | −17 | 14 | 239 | 4.28 | 0.35 | 0.019 |
Left thalamus | −9 | −14 | 14 | 104 | 4.49 | 0.38 | 0.017 |
The correlation using whole-brain voxel-based analyses of susceptibility values in the healthy participants.
TMT-B | Right precentral/middle frontal gyrus/inferior frontal gyrus/Inferior triangular gyrus | 61 | 23 | 27 | 1,533 | 4.21 | 0.59 | 0.010 |
In this study, we found that brain iron in T2DM patients compared with HCs was significantly increased in the striatum containing the caudate/putamen/pallidum and in the frontal lobe (frontal inferior triangular gyrus and precentral gyrus) (
Brain susceptibility value disparities among the patients with T2DM and HCs.
Brain susceptibility value disparities among the patients with T2DM and HCs.
Brain susceptibility value disparities among the patients with T2DM and HCs.
QSM is a new MRI technique that can measure susceptibility-changing materials quantitatively and accurately. It has the ability to non-invasively analyze the brain iron deposition (
In this study, using voxel-based QSM analysis, more affected areas were detected, including the striatum containing the caudate/putamen/pallidum and the frontal lobe (frontal inferior triangular gyrus and precentral gyrus). In a previous research, the difference of susceptibility changes caused by iron accumulation was compared among three groups, cognitive normal (CN) elderly, patients with amnestic MCI (aMCI), and patients with early state AD. The differences of the QSM data among the three groups were investigated by voxel-based and ROI-based comparisons. The results of the voxel-based analysis demonstrated more regions with significant difference than the ROI-based analysis (
In our study, the affected areas were the striatum containing the caudate/putamen/pallidum and the frontal lobe (frontal inferior triangular gyrus and precentral gyrus). In T2DM patients, the right thalamus and left thalamus showed a significant relationship with TMT scores. In subcortical structures, the thalamus and striatum play key roles in sustaining normal cognitive function. The thalamus functions as an integration center for subcortical and cortical regions; hence, it is a critical component of functions such as awareness and sensory, motor, and cognitive functions. The striatum is one of the main neural structures of the extrapyramidal motor system, which includes the caudate nucleus and lentiform nucleus, the latter of which is divided into the putamen and pallidum (
According to a prior investigation on iron deposition in T2DM patients’ brains using QSM as well as the relevant cognitive impairments, T2DM patients with MCI exhibited significantly increased susceptibility values in the left putamen than T2DM patients without MCI. The susceptibility values of the left putamen showed a close connection to neuropsychological cognitive scores (
Our study has several limitations. First, there exists background error and white noise in the original susceptibility maps. Therefore, the cluster in the precentral gyrus with susceptibility value close to 0 is subject to the systematic error of QSM reconstruction or white noise. Second, the susceptibility maps normalized to MNI space may suffer from error introduced in VBM pipeline. We found a slightly lower susceptibility values of deep gray matter (DGM) as compared with other studies. Low susceptibility in DGM is also reported in two previous voxel-based QSM analyses (
In sum, those suffering from with T2DM presented enhanced iron deposition within the striatum and frontal lobe, suggesting that the EF decline in T2DM might be associated with the cerebral iron burden. Using voxel-based data, we identified that the mean susceptibility values of the thalamus, striatum, and frontal lobe had significant correlation with TMT scores, which might reflect a key role of iron deposition during the T2DM process. The changes in susceptibility values throughout these areas likely represent quantitative imaging markers of central nervous system injury among patients with T2DM. Furthermore, QSM might be a beneficial tool for the detection and evaluation of such injuries.
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation, to any qualified researcher.
The studies involving human participants were reviewed and approved by the Institutional Review Board of Shandong Medical Imaging Research Institute Affiliated to Shandong University. The patients/participants provided their written informed consent to participate in this study.
JL and LG wrote the main manuscript text. QZ prepared imaging data and
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
The Supplementary Material for this article can be found online at: